Letnik: ZO I Številka: O I ОПТ A Volume: OZ. Number:	\J IO
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NASE GOSPODARSTVO
Revija za aktualna ekonomska in poslovna vprašanja
OUR ECONOMY
Journal of Contemporary Issues in Economics and Business
OUR ECONOMY
Vol. 62, No. 2, 2016
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Vsebina / Contents
ARTICLES
Renata Gabryelczyk
Does Grade Level Matter for the Assessment
Cif1 Business Process Management Maturity?	3
Igor Perko, Peter Ototsky
Big Data for Business Ecosystem Players	12
Katalin Dobrai, Ferenc Farkas
Nonprofit Organizations from the Perspective of Organizational Developm ent and Their Influence on Professionalization	25
Ewa Wi^cek-Janka, RafaJ Mieizwirk, Joanna Kijewska
The Analysis of Barriers in Succession Processes of Family Business with the Usee of Gney Incidence Analysis (Polish Perspective)	33
Eva Lorenčič
Testing t he Pe rformance of Cubic Spline s
.and Nelson-Siegel Model for Estimating
the Zero-coupon Yield Curve	42
Maja Koražija, Simona Šaro tar Žižek, Damijan Mumel
Thre Relationship between Spiritual
Intelligence and Work Satisfaction among
Leaders and Employees	51
Does Grade Level Matter for the Assessment of Business Process Management Maturity?
Renata Gabryelczyk
University of Warsaw, Faculty of Economic Sciences, Poland r.gabryelczyk@wne.uwedu.pl
Abstract
The purpose of this paper is to create and test the practical application of a business process management maturity assessment conducted at two different grade levels (management and professional level) in an organization. The conceptual framework for this research includes creating a business process maturity indicator (BPMI) for six process areas: strategy, documentation, optimization, implementation, execution, and controlling. The comparative analysis of the business process management maturity is performed using the BPMI on two cases: inside a single organization and the sector internally.
Keywords: business process management, maturity of business process management, maturity models, grade levels in the maturity assessment
1 Introduction
Maturity models are used for measuring the performance and maturity of individual functional areas or processes, as well as that of the whole organization (Rosemann & de Bruin, 2005; Hammer, 2007; Lockamy & McCormack, 2004; McCormack & Johnson, 2001; OMG, 2008; Rosemann, de Bruin, & Power, 2006; Zwicker, Fettke, & Loos, 2010). Business process maturity is the ability of an organization to control its processes efficiently—that is, to define, implement, and measure its processes as well as make continual improvement decisions based on performance measurements. The process of achieving maturity is associated with developing some features characteristic of the given maturity level (Rosemann & de Bruin, 2005; Hammer, 2007; Lockamy & McCormack, 2004; McCormack & Johnson, 2001; OMG, 2008; Rosemann et al., 2006; Zwicker et al., 2010) and improving the process management areas according to the business process li-fecycle (Jost & Scheer, 2002), process management lifecycle (BOC, 2007), or business process management lifecycle (Macedo de Morais, Kazan, Ines Dallav-alle de Padua, & Lucirton Costa, 2014). Studies of business process management maturity in Polish literature encompass testing the degree of business process maturity of the selected companies (Dobrzynski, Dziekonski, & Jurczuk, 2012) or the diagnosis of process maturity in terms of project objectives (Jurczuk & Gabryelczyk, 2015). Literature studies have helped uncover a gap in the study of perception of maturity for different grade levels. Thus, the purpose of this paper is to create and test the practical application of the business process management maturity assessment conducted on two different grade levels in the organization: the management level and professional level. The research will be based on two case studies: (1) a large company representing the fuel sector and (2) a sample
ORIGINAL SCIENTIFIC PAPER
RECEIVED: NOVEMBER 2015 REVISED: FEBRUARY 2016 ACCEPTED: MARCH 2016
DOI: 10.1515/ngoe-2016-0007 UDK: 005.5 JEL: M10, L20
Citation: Gabryelczyk, R. (2016). Does Grade Level Matter for the Assessment of Business Process Management Maturity?. Naše gospodarstvo/Our Economy, 62(2), 3-11. DOI: 10.1515/ ngoe-2016-0007
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NASE GOSPODARSTVO OUR ECONOMY
Vol.
. 62 No. 2 2016
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from the commercial banking sector. The survey covered six process areas distinguished in the process management life cycle (PMLC) model (i.e., strategy, documentation, optimization, implementation, execution, controlling) and was conducted on a group from the organization's employees representing the two different grade levels (i.e., management and professional). The research questions were formulated as follows:
RQ1: Is the employees' perception of the organization's process areas' maturity the same for both grade levels?
RQ2: Which of the process areas are most relevant in shaping the organization's business process management maturity in the opinion of employees representing different grade levels?
To express the perception of the analyzed areas' maturity in quantitative terms, a business process maturity indicator (BPMI) was designed. It enabled a t-test to be performed in order to answer RQ1 and to investigate the correlation between the general maturity of the organization and the maturity components according to the PMLC stages, thereby answering RQ2.
2 Literature Review
2.1 Maturity models in business process management (BPM)
While discussing processes, the notion of "maturity" is most typically defined as the capability of an organization and its processes to systematically deliver improved outcomes of its activity (Rosemann & de Bruin, 2005). The term organizational maturity was first defined by Philip Crosby (1979) as the organization's ability to professionally employ quality management methods and techniques. The Quality Management Maturity Grid (Crosby, 1979) is regarded as a precursor to the Capability Maturity Model Integration (CMMI) developed by Software Engineering Institute (Gibson, Goldenson, & Kost, 2006; SEI, 2006). The CMMI is currently one of the most popular organizational maturity assessment tools (Gibson et al., 2006; Humphrey, 1988). The key maturity models originating from this trend are the Business Process Management Maturity Model (Rosemann & de Bruin, 2005; Rosemann et al., 2006), Business Process Orientation Maturity Model (McCormack & Johnson, 2001), Process and Enterprise Maturity Model (Hammer, 2007), Business Process Maturity Model (OMG, 2008), and Process Maturity Ladder (Harmon, 2007). Röglinger, Poppelbuss, and
Becker (2012) provided an overview of organizational and process maturity models.
The maturity of an organization is usually measured on a four- or five-degree scale and should address the factors determining the process repeatability, as well as the resources and capabilities that ensure such repeatability. According to Kohlbacher and Reijers (2013), the relevant aspects of maturity evaluation include process documentation, management commitment, process ownership, process measurement and monitoring, and continuous process improvement methods and techniques as well as organizational culture and structure. A higher level of maturity leads to a better control of the results, more accurate forecasting of goals, costs, and performance, greater effectiveness in reaching the defined goals, and the increased ability of an organization to plan and implement organizational changes (Lockamy & McCormack, 2004).
2.2 Process management lifecycle
As a rule, the business process management (BPM) life-cycle determines the management practice activities for several consecutive stages. According to Houy, Fettke, and Loos (2010), the number of steps and the terminology used when defining BPM lifecycles differ to a certain extent, but the concepts cover the same activities. Kohlbacher (2010) stressed that the BPM lifecycle not only encompasses business process analysis, design, development, and execution, but also addresses the interactions between these areas and an organization's control, optimization, and strategy. The process management lifecycle phases are most typically defined based on Deming's plan-do-check-act or plan-do-study-act cycle (Kalinowski, 2011) or using the approaches adapted by authors of process management architectures (BOC, 2007; Jost & Scheer, 2002). An overview of the literature on BPM lifecycle models, with common characteristics and peculiarities, is presented by Macedo de Morais et al. (2014), who described the seven BPM lifecycle models proposed by Van der Aalst (2004), Zur Muehlen and Ho (2006), Netjes, Reijers, and Van der Aalst (2006), Weske (2007), Hallerbach, Bauer, and Reichert (2008), Verma (2009), and Houy et al. (2010).
The PMLC (BOC, 2007) covers six basic dimensions of process management: process strategy, process documentation, process optimization, process implementation, process execution, and process controlling. These dimensions reflect the situation in the analyzed area or throughout the organization in terms of process maturity, while indicating opportunities for improvement and development toward the process management approach. PMLC is a model of procedures for process performance and
management. Conceptually, it contains all BPM lifecycle stages referred to in the literature.
3 Methodology 3.1 Research approach
The organization's process maturity evaluation exercise included a questionnaire-based survey conducted for two cases. Case 1 was a major company from the fuel sector and was listed on the Warsaw Stock Exchange. This case was selected based on the information in the management reports about the implementation of BPM in the organization and based on the practical criteria of data availability. Case 2 was a study of the banking sector, which—according to Polish authors—is the most advanced sector in process approach implementation (Nosowski, 2010). Employees in both organizations from case studies are divided into five main levels: paraprofessionals, professionals, middle and top management, executives, and board members. The professional and management groups in both case studies considered in the research were the most numerous and the most involved in the projects of business process management implementation. The study does not include paraprofessionals, executives, or board members due to the very small sample size and the inability to collect data. The professional grade level includes positions that require experience, skills, and theoretical and conceptual knowledge of the specialization in specific areas. The management grade level refers to employees focused on managing people and implementing policies and strategies to meet the organization's objectives. Employees of the organizations representing these grade levels were asked questions concerning the six process areas of the PMLC model. The questionnaire survey covered six basic dimensions distinguished in the PMLC model (BOC, 2007): process strategy, process documentation, process optimization, process implementation, process execution, and process controlling. In each area nine questions were asked.
For the process strategy, the questions of the survey revealed whether the organization's strategy is reflected in the process flows, especially those of strategic importance. The questions covered the following issues: the process objectives' definition in strategy; the interrelations between strategy and activities; the regularity of analyzing how processes contribute to the achievement of objectives; the process strategy communication; and the organization's process competence centers. The purpose of the questions concerning documentation was to find out if the processes of the organization have been identified, structured, and documented in the form of models. Understanding the organization's processes is a starting point for the development of a system for measuring
and improving process performance and effectiveness. The questions explored such issues as the use of IT standards, methods and tools for process modeling, the contents of model description, the process of updating the model, and the assignment of the organization's resources to processes. In regard to process optimization, we asked if any organizational and technical barriers prevented the prompt and efficient execution of processes and if any potential process improvement opportunities were identified by the employees. Furthermore, the questionnaire covered process standardization, optimization of internal and inter-organizational processes, and process risk identification and reduction. The process implementation dimension specifies the extent to which the process approach has been implemented within the organization, resulting in the following issues being covered: employees' understanding of the new, process-based style of work; process-related training activities; the use of the organization's resources in the newly designed processes; and the limits of the organization's business units as potential barriers to the operation of processes. The process execution perspective shows the organization's maturity in aspects of the process control from the organizational and technical point of view. Here, the respondents assessed the quality of processes, the security and accessibility of the IT architecture and services, and the process risk management. Controlling enables managers to evaluate the achievement of process objectives on a regular basis by means of process monitoring and analysis tools. The questionnaire explored the issue of monitoring process performance indicators, internal process benchmarking, process planning, control and monitoring regardless of the business units' limitations, and the adjustment of the process objectives and indicators to the organization's fluctuating overall goals.
The responses were expressed on a 5-point Likert scale, ranging from 1 to 5. When answering the questions, the respondents expressed their subjective perception of the business model maturity, referring to each of the elements. The overall perception—the business process maturity indicator (BPMI)—was computed for the company as an arithmetic mean of the results obtained in the six process areas in the PMLC:
BPMi ^siuc^L^)
where x.. is the value of the answer to the jth question in the zth process area, i = 1, 2, ..., 6, j = 1, 2, ..., к, and к. is the number of questions for the ith process area.
To answer RQ1, a t-test was conducted using BPMI, which allowed the evaluation of two groups, the management and professional grade levels, which are significantly different
from each other. Furthermore, BPMI enabled the examination of the correlations between the overall maturity of the organization and the maturity components as per PMLC.
3.2 Conceptual framework
The study was based on the conceptual framework shown in Figure 1, adapted from Roztocki and Weistroffer (2015). The literature overview focused mainly on the business process management maturity and PMLC studies. However, these studies have not covered the perception of maturity for different grade levels; therefore, the paper proposed research questions about differences of opinions expressed by the management and professional grade levels. The research approach proposes a formula for computing the BPMI for the six areas distinguished in PMLC. A comparative analysis for different grade levels was conducted. Case 1 covered an analysis inside an organization while Case 2 included an analysis inside the banking sector.
4 Results of the Study 4.1 Case 1
The business process maturity survey was conducted on a sample of 47 respondents in a large company representing the fuel sector in Poland. According to the job scale, the sample included 30 respondents classified as the management grade level (middle and top level management) and 17 respondents at the professional grade level. Descriptive statistics of the BPMI for both groups are summarized in Table 1.
In order to answer the RQ1, a t-test was conducted to investigate the significance of differences in the BPMI mean values in general and, with respect to the six process areas of PMLC, in both grade levels (Table 1). The BPMI results show strong, significant differences in means between the management and professional groups. Received significance is less than 0.05 for BPMI in general and for five of six process areas, which means that there are statistically significant differences between the employees' perception of the organization's
Figure 1. Conceptual framework
Research Focus
-	Business Process Management Maturity
-	Process Management Life Cycle: 6 process areas
-	Assessment of the maturity for different grade levels
Research Approach
-	Business Process Maturity Indicator for 6 process areas
-	Comparative analysis for different grade levels
-	Case 1: Analysis inside an organization
-	Case 2: Analysis inside a sector
Research Outcomes
-	The assessment of the employees' perception of the organization's process maturity areas
-	Finding the process areas most relevant to shape the organization's process maturity
Table 1. Comparison of BPMI Elements between Management and Professional Grade Levels: Analysis within an organization
	Management grade level		Professional grade level		t-test
	Mean	Std. Dev.	Mean	Std. Dev.	p value
BPMI	3.788	0.715	3.219	0.632	0.0070""
BPMI Strategy	4.137	0.738	3.733	0.697	0.0681"
BPMI Documentation	3.852	0.746	3.320	0.919	0.0478""
BPMI Optimization	3.784	0.846	3.204	0.866	0.0310""
BPMI Implementation	3.922	0.543	3.200	0.816	0.0022""
BPMI Execution	3.529	0.945	2.986	0.839	0.0473""
BPMI Controlling	3.500	1.163	2.871	0.830	0.0365""
Notes: Mean, standard deviation, and results of two-tailed t-test assuming equal variances. *p < 0.1; ** p < 0.05
Anderson-Darling statistic was used to determine that data meet the assumption of normality or are very similar to a normal distribution.
process areas maturity. The outcomes can be used as inputs to RQ1 regarding the organization's process maturity perception by respondents representing different grade levels, showing higher BPMI scoring in the middle and top level management category. Strategy is the only area where differences in both groups' perception are not as apparent, which may indicate that process strategy is well communicated and perceived consistently by each of the two groups. An in-depth analysis of differences between the management and professional grade level groups' perceptions of both general and area-specific process maturity was conducted using a correlation matrix (Table 2). All process areas showed a positive correlation compatible with the PMLC model logic. According to the management grade level, execution, optimization, and controlling were the aspects most strongly correlated with the general maturity of the organization. These dimensions were strongly correlated throughout the process management cycle. Optimization uses data from controlling as inputs for the verification of process performance and effectiveness through the prism of objectives. Execution forms the organization's maturity in terms of process control from the organizational and technical point of view and collects data for controlling. As the process areas referred to thus far fall within the managers' scope of competence, they were perceived by this group as having the strongest impact on the BPMI level. Process documentation was of the least interest to the company's management.
According to the professionals, the BPMI level was most significantly affected by documentation and implementation. Professionals were interested in such areas as business process identification and modeling with the use of modeling notation as well as the practical implementation of these processes in the environment of those who perform them. Professionals perceived the area of controlling as showing the lowest degree of correlation with the overall maturity of a company.
Table 2. Pearson's Correlation Coefficients of BPMI Elements for Management and Professional Grade Levels: Analysis within an organization
	Management grade level	Professional grade level
	BPMI	BPMI
BPMI	1.0000	1.0000
BPMI Strategy	0.8660""	0.7181""
BPMI Documentation	0.6477""	0.8459""
BPMI Optimization	0.9314""	0.8110""
BPMI Implementation	0.8671""	0.8369""
BPMI Execution	0.9334""	0.8128""
BPMI Controlling	0.8873""	0.5415""
Notes: Significance level ** p < 0.05
4.2. Case 2
For the research of the business process maturity of the six process areas, the survey was conducted on a sample of 53 employees from commercial banks in Poland. This sample included 35 respondents classified as the management grade level (middle and top level management) and 18 respondents classified as the professional grade level. BPMI descriptive statistics for both groups are summarized in Table 3. The results of the general BPMI and for each of process area indicate differences in means between the management and professional groups. BPMI scoring is higher in the middle and top level management category.
As in Case 1, the strategy area shows less significant differences between the groups (p < 0.1). The fact that, in the perception of controlling, no significant differences exist between the management and professional groups seems to be peculiar to the banking sector. The financial sector is
Table 3. Comparison of BPMI Elements between Management and Professional Grade Levels: Analysis within the sector
	Management grade level		Professional grade level		t-test
	Mean	Std. Dev.	Mean	Std. Dev.	p value
BPMI	3.162	0.696	2.729	0.532	0.0148""
BPMI Strategy	3.296	0.862	2.902	0.651	0.0673"
BPMI Documentation	3.302	0.749	2.686	0.639	0.0028""
BPMI Optimization	3.056	0.596	2.641	0.565	0.0163""
BPMI Implementation	3.179	0.687	2.746	0.522	0.0134""
BPMI Execution	3.160	0.770	2.711	0.597	0.0228""
BPMI Controlling	2.975	0.866	2.686	0.640	0.1734
Notes: Mean, standard deviation, and results of two-tailed t-test assuming equal variances. *p < 0.1; **p < 0.05
Anderson-Darling statistic was used to determine that data meets the assumption of normality or are very similar to a normal distribution.
governed by the policies and rules imposed by international regulatory bodies (e.g., Sarbanes Oxley Act, Basel II) and national regulatory bodies (Polish Financial Regulatory Authority) and is therefore required to adopt formal internal regulations in various areas, including control effectiveness reporting. The process approach determines formal risk management and control regulations (Nosowski, 2010). Hence, the special nature of the banking sector may explain the fact that there are no statistically significant differences in the perception of controlling between the management and professional grade levels, as well as the strong, significant correlation between BPMI general and controlling for both groups. (Table 4).
The continual process of controlling provides information about the organization's strategy translated into activities and enables the organization to make the most of the complete business process management loop. Furthermore, the management grade level showed a strong correlation between BPMI for the execution and strategy process areas and lowest for process documentation. Also as in Case 1, the correlation between documentation and maturity was perceived to be stronger by professionals than by managers.
5 Discussion
The maturity model and the process management life-cycle models should be regarded as a formalized set of elements (features) describing fully efficient processes or requirements that, when satisfied, enable the achievement of maturity (Rosemann & de Bruin, 2005; Hammer, 2007; Lockamy & McCormack, 2004). It is a form of a roadmap and a standardized method of communication between participants of a project designed to build a process-oriented
Table 4. Pearson's Correlation Coefficients of BPMI Elements for Management and Professional Grade Levels: Analysis within the sector
	Management grade level	Professional grade level
	BPMI	BPMI
BPMI	1.0000	1.0000
BPMI Strategy	0.9525""	0.8826""
BPMI Documentation	0.8191""	0.8783""
BPMI Optimization	0.9021""	0.9011""
BPMI Implementation	0.9141""	0.8679""
BPMI Execution	0.9810""	0.8378""
BPMI Controlling	0.9479""	0.9238""
Notes: Significance level **p < 0.05
organization. Therefore, it is important for both managers and process operators to fully understand their roles and be aware of the organization's maturity when implementing process management (Hammer, 2007; Lockamy & McCormack, 2004). A thorough self-assessment performed using maturity models and lifecycle models enables the organization to identify sources of deficiencies as well as areas for improvement within the continual improvement cycle. Maturity models can be particularly useful for organizations initiating formalized process management, as they facilitate the identification of the current situation, thereby providing the motivation to act, while suggesting best practices that could be employed. The process management lifecycle method was chosen because the highlighted process areas in this model can be used for a comparative analysis of their perceptions by different grade levels.
The findings show that the respondents from the management group perceived their organization more optimistically than the professionals, which can be explained by the impression management theory (Wayne & Linden, 1995), according to which managers may be trying to regulate and control information in their interaction with the personnel and the business environment in order to give them the best impression of the company, its objectives, and its management methods (RQ1). The highest scores given to process strategy confirmed the deep commitment of management at the strategy building stage and good strategy communication within the organization. The finding was supported by professionals' high perception of maturity and the fact that both grade levels differed least most notably in their perception of maturity. The t-test results confirmed that differences in the assessment of business process management maturity are significant between the professional and management groups (RQ1). The correlation matrix identified the process areas most relevant to shape the organization's business process management maturity in the opinion of employees (RQ2). The correlations show how individual process areas are interdependent with the organization's general BPM maturity in the perception of employees representing the management and professional grade levels. Each of the respondent groups in Case 1 favored its respective areas of involvement: optimization, execution, and controlling for the management grade level and documentation and implementation for the professional grade level. Management often participates in the business process management implementation projects in their preparation phases until the moment of the project launch (documentation, implementation), while showing no commitment later on. Professionals, who are actually involved in process tasks, have better insights into the operation aspects, which translate into the lower final maturity ranks. Out of all process areas, the controlling and execution dimensions were given lowest scores by both respondent categories,
but emphatically higher by the management group, which should come as no surprise as managers are specifically responsible for the regular evaluation of the achievement of process goals by means of process monitoring and analysis tools. In Case 2, the influence of the banking sector's nature on the process maturity perception was observed. The effect of external regulations on internal regulations is reflected in processes and seems particularly significant here. They are highly important to all employees of the banking area at various grade levels. The findings support that process maturity perception depends on the scope of responsibility of the personnel evaluating the organization as well as the communication of the business process management implementation results. Yet in both the internal analysis of a single organization (Case 1) and the analysis within a sector (Case 2), the maturity of all processes as well as the overall business process management maturity is given unequivocally higher marks by managers.
6 Conclusions and Limitations of the Study
The fact that the process approach has been implemented is not a sufficient condition for improving an organization's performance. The process maturity measurement provides a
basis for making processes and process areas more efficient as well as for ensuring continual improvement. Maturity models and process management lifecycle management models may be used to (1) describe the current status of the organization; (2) ensure improvement, as the models include recommendations for the improvements required; and (3) provide comparative analyses, as they may be referred to as benchmarks for comparisons with historical data, illustrating process performance and organizational maturity, as well as for comparing maturity perception declared by employees representing different grade levels. It seems that the less diversified the maturity perception declared by personnel representing various levels in the organization, the more trustworthy the summarized evaluation of the analyzed organization's maturity. The process maturity measurement in a breakdown of six areas consistent with the PMLC reflects the process maturity of an area or of an organization as a whole while simultaneously showing opportunities for improvements and development of the organization toward process management. Limitations of this study are the small sample and cases from different fields. The presented research is only an initial study of the measuring instrument. The revision of this instrument should be done based on larger samples and through a comparative analysis of a company case in a particular branch against the same survey across the branch.
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Author
Renata Gabryelczyk, Ph.D., is an assistant professor at the Department of Information Systems and Economic Analysis, Faculty of Economic Sciences, and partner of Digital Economy Lab at the University of Warsaw. Her academic experience also includes studying at the Institute for Information Systems at Saarland University as well as research fellowships at scientific centers in Heidelberg, Constance, and Vienna. Her professional pursuits include business process management, performance management, business models, and entrepreneurship. She is also a member of the Polish Certificate of BPMN in Systems Research Institute of the Polish Academy of Science.
ALi je delovno mesto pomembno za presojo zrelosti menedžmenta poslovnih procesov?
Izvleček
Namen tega prispevka je narediti in testirati praktično aplikacijo za presojanje zrelosti menedžmenta poslovnih procesov na dveh različnih ravneh (na menedžerski in strokovni ravni) v organizaciji. Konceptualni okvir za to raziskavo vključuje izdelavo indikatorja zrelosti poslovnih procesov za šest procesnih področij, tj. strateško, dokumentacijsko, optimizacijsko, implementacijsko, izvedbeno in nadzorno. Za primerjalno analizo zrelosti menedžmenta poslovnih procesov smo uporabili indikator zrelosti poslovnih procesov, in sicer v okviru posamezne organizacije in sektorja.
Ključne besede: menedžment poslovnih procesov, zrelost menedžmenta poslovnih procesov, modeli zrelosti, delovno mesto v presojanju zrelosti
ORIGINAL SCIENTIFIC PAPER
RECEIVED: JANUARY 2016 REVISED: APRIL 2016 ACCEPTED: MAY 2016
DOI: 10.1515/ngoe-2016-0008 UDK: 659.2:004 JEL: 033
Citation: Perko, I., & Ototsky, P. (2016). Big Data for Business Ecosystem Players. Naše gospodarstvo/Our Economy, 62(2), 12-24. DOI: 10.1515/ ngoe-2016-0008
NG
NASE GOSPODARSTVO OUR ECONOMY
Vol.
. 62 No. 2 2016
. 12-24
Big Data for Business Ecosystem Players
Igor Perko
University of Maribor, Faculty of Economics and Business, Slovenia igor.perko@um.si
Peter Ototsky
Russian Academy of Sciences, Keldysh Institute of Applied Mathematics, Russia
peter@ototsky.com
Abstract
In the provided research, some of the Big Data most prospective usage domains connect with distinguished player groups found in the business ecosystem. Literature analysis is used to identify the state of the art of Big Data related research in the major domains of its use-namely, individual marketing, health treatment, work opportunities, financial services, and security enforcement. System theory was used to identify business ecosystem major player types disrupted by Big Data: individuals, small and mid-sized enterprises, large organizations, information providers, and regulators. Relationships between the domains and players were explained through new Big Data opportunities and threats and by players' responsive strategies. System dynamics was used to visualize relationships in the provided model.
Keywords: Business ecosystems; Big Data; information providers; system dynamics
1 Introduction
Big Data (BD)-related technologies—namely, data extraction and blending, predictive analytics, and user experience—provide a disruptive force by redefining the communication patterns and the insight levels on all players in business ecosystems and surrounding social and natural systems. BD positively influences the reactivity and provides a higher level of transparency (McAfee & Brynjolfsson, 2012).
Players in business ecosystems (BE) face new opportunities and challenges to survive and thrive (Evans, 2014). The BD effect on BE is twofold: On one hand it provides new means to execute internal and external processes faster and cheaper; on the other hand, the higher ecosystem security level enables the option to lower the barriers that protected companies in the previously hostile environment. Consequently, the roles of existing players shift and new players emerge on the field, such as system integrators, providing BD-supported networking services.
System thinking provides the theoretical basis for understanding complex systems on multiple levels (Lane, 2000). It also provides a rich toolset, such as system
dynamics, to help us understand the system members, their relationships, and the triggers that direct their behavior. BD technologies influence BE players through multiple domains, identifying opportunities and threats for the players. Players respond by using diverse strategies. In this paper, we provide an oversight of the influences BD will have on the BE players, using system thinking as a tool. We focus on a combination of the limited number of BD domains—namely, individual marketing, health treatment, work opportunities, financial services, and security enforcement—with a selected group of players: individuals, small and mid-sized enterprises (SMEs), large organizations, information providers, and regulators.
The paper is organized as follows. First, relevant backgrounds and the state of the art of BD, BE, and system thinking are elaborated. Next, BE players' objectives are elaborated and, according to the selected BD domains, opportunities and threats to players' responsive strategies are explained. Then the system dynamics overview is provided, visualizing the relationships between BD domains and BE players. The paper concludes with a discussion and future directions. The paper offers insights for BD architects regarding which services to design, business managers regarding what to expect from BD technologies, and researchers who plan to design BE to help them formulate a requisitely holistic set of requirements.
2 Background 2.1 Big Data
BD technologies of information processing (such as Ma-pReduce) first appeared for searching and parsing Internet (Bryant, Katz, & Lazowska, 2008; Lämmel, 2008). The BD boom correlates with exponential growth of stored and sent information and will eventually lead to a metasystem transition of information technologies and shift in progress direction (Press, 2013). The digitalization of BE is part of that transition (Bryant et al., 2008; Cukier, 2014; Evans, 2014; McAfee & Brynjolfsson, 2012).
Historically, enterprise information systems (EIS), commonly known by its key subsystem enterprise resource planning (ERP) solutions, operate with internal data corresponding to a structure of the business. In fact, IT companies implement not only IT systems (ERP, etc.), but also enforce typical business models and structures. The standardization of business models logically follows the technical aspect: Data models and business logics are programmed in a database structure at a low level (Davenport, 1998; Wood, 2010). Subsequent the organization processes are limited by
the EIS variety and can hardly cope with the internal complexity or the complexity of the BE (Waelchli, 1989).
One of the key BD technologies is MapReduce scalable distributed computing (Lämmel, 2008). The idea is that very simple processing is carried out in two stages: (1) map—one large computational task is divided to many similar small tasks and small tasks are then processed on distributed nodes; and (2) reduce—all results are combined into the one result. If the node is a human, not a computer, then the same MapReduce logic may be used for task distribution to performers (crowd sourcing). In this way, the "act" part can be also digitalized using the same BD methods as in the "sense" part.
Predictive analytics exploits the BD potentials not only to provide the whole picture, but also to predict future events (Waller & Fawcett, 2013). Combining BD and predictive analytics is an extremely powerful combination. It enables organizations to use collective memory in planning their actions, thereby provide management the sharable vision of the future and the capability to anticipate the unexpected.
2.2 Business ecosystems
Moore (1993, p. 2) defined business ecosystems as an economic community supported by a foundation of interacting organizations and individuals—the organisms of the business world. The economic community produces goods and services of value to customers, who are themselves members of the ecosystem. The member organisms also include suppliers, lead producers, competitors, and other stakeholders. In a business ecosystem, companies coevolve capabilities around a new innovation: they work cooperatively and competitively to support new products, satisfy customer needs, and eventually incorporate the next round of innovations. Over time, they tend to align themselves with the directions set by one or more central companies. Those companies holding leadership roles may change over time, but the function of ecosystem leader is valued by the community because it enables members to move toward shared visions to align their investments, and to find mutually supportive roles.
BE are not formalized; therefore, they provide a challenge for researchers to identify their structure, relationships, processes, and—above all—the reason for their existence. Gao, Zhang, Tian, Guan, and Li (2013) combined the evolutionary aspect of complex network theories to explain the e-BE development. Hellstrom, Tsvetkova, Gustafsson, and Wikstrom (2015) identified the cooperation mechanisms and their effect on closer collaboration, sustainability, and increased overall value creation. They pinpointed the
importance of identifying the factors driving the business models of the collaborating companies to facilitate changes. BE sizes range from closed supply chains, through local habitats, such as cities or national economies (Mavric, Tominc, & Bobek, 2014; McAfee & Brynjolfsson, 2012), to global markets (Korez-Vide, 2004; Umpleby & Lim, 2007).
BE consist of multiple players' roles. Basic entities in BE are individuals and organizations in the form of companies, information service providers, and regulators. Each player follows the goal of surviving and maximizing the bounty gained from the system. The strategies they use depend on the ecosystem resources, rules, and knowledge about how to exploit them.
Individuals follow their objectives or act as agents for the accomplishment of the organization's goals. Regardless of the role they play, the system is organized to utilize capacities and fulfill desires of every individual. The individual's personal engagement, and consequently the organizations' success, depends on the organizations' preparedness to represent their beliefs and support their needs and interests (Drucker, 2002; Waelchli, 1989). The behavior analysis and predictions found key individuals related to research issues (Ajzen, 1991; Nelson, 1970; Zhang, Chen, Mao, Hu, & Leung, 2014).
Companies ranging from micro enterprises to SMEs and large multinational organizations (Barney, 1991) use their knowledge and means to efficiently produce products and services from the available resources. They actively communicate with external players and employees (Frohlich & Westbrook, 2001; Tomlin, 2006). Dunkl, Jiménez, Zizek, Milfelner, and Kallus (2015), for instance, compared classical transformational leadership and health-oriented leadership, finding considerable differences in stress recovery processes.
The business software developers are providing significant support in developing and digitalizing BE. For example, SAP (Fauscette, 2014) develops high performance platforms for suppliers and procurement professionals to build collaborative relationships. IBM (Rometty, 2013) creates support for the development of smart organizations, while Salesforce connects companies and customers (Payne & Frow, 2005). Yet no matter how complex these tools are, they cannot reflect the complexity of the systems they should manage.
Software developers possess knowledge of business operations. Access to cloud-stored business data gives them an opportunity to evolve to a new meta-level. They can become business integrators, providing companies with services to instantly identify appropriate business partners and manage business partners' related processes effortlessly, significantly
affecting the communication processes (Bregman, Peng, & Chin, 2015; Fauscette, 2014).
Regulators form and enforce rules under which the players execute their activities. Their role in the systemic sense is to support positive processes and omit the use of negative ones. Although players usually experience them through their repressing instruments (Beyer, Cohen, Lys, & Walther, 2010; King, Lenox, & Terlaak, 2005), they are responsible for the success of the whole ecosystem, its internal structure, and effects on other ecosystems. Cancer, Rebernik, and Knez-Riedl (2013) proposed methods for assessing the environmental reputation and the creation of new sets of values.
Attempts have been made to address the BE management issues requisitely holistically using diverse approaches. Razavi, Moschoyiannis, and Krause (2009) proposed a peer-to-peer network design that aims to support business activities conducted through a network of collaborations that generate value. We agree that some technologies can help optimize BE; nevertheless, to maximize the positive technological effect the BE, properties must undergo a systemic investigation.
2.3 System research
Systems and their viability have been defined by many researchers. The systemic view was provided by cybernetics, where Beer (1972) introduced the Viable System Model (VSM), based on biological and psychological observations and the Ashby's law of requisite variety.
Figure 1. The simplified organizational VSM
" V..............
Management
\	\	^/Attenuators
\ \ А~~1 \ X
\ Variety \ ^X£ /	M
Amplifier/ I ^
N.	...............^ Operations W-\ ^Variety
\	J J	Amplifier
Adapted from (Beer, 1985)
Waelchli (1989) explained the relationships with the environment in VSM using a simplified version of the model (see Figure 1). The organizational components were reduced to management (in the rectangle) and Operations (in circle): Management regulates Operations, and Operations regulates
the environment. The viability of the system is supported by massive flows of information within the organization as well as between the organization and the environment. The main focus of the VSM is designing methods to transmit and manage very large amounts of information in real time. In Figure 1, the information communication channels, represented by arrows, interlock elements of the Organization (Management and Operations) and link the Organization to the Environment.
Researchers have proposed using systemic tools, such as system dynamics to help manage complex environments. Bianchi (2002) emphasized the need for a learning-oriented approach to planning and control as a prerequisite for SMEs' survival and growth. Oyebisi, Momodu, and Olabode (2013) compared models for managing a technological innovation system (TIS), defined drawbacks of conventional models, and proposed the use of system dynamic models as a valid solution. They all pointed out that potent modeling and simulation software and knowledge in multiple domains are required for successful modeling.
Limiting business information to financial or marketing information has been strongly challenged. Systemic thinking and requisite holism are a valid basis for innovation (Mulej & Potocan, 2007; Zenko & Mulej, 2011). It is insufficient to design processes by ignoring the information that cannot be attained by the current state of technology. We followed the advice to expand the observed data and use BD resources to get a step closer to a higher BE meta level.
3 Business Ecosystems Players
Rich BE provide an environment for multiple players with high diversity (Gao et al., 2013; Moore, 1993; Nachira, Dini, & Nicolai, 2013). In this section, we elaborate on the objectives and strategies of five BE players greatly affected by BD technologies: individuals, SMEs, large organizations, information providers, and regulators. The business players selection is based on Moore's (1993) definition of the business ecosystems and upgraded with information providers and regulators, which play an important role in the viable system perspective (Espejo, Bowling, & Hoverstadt, 1999).
For every player, a question arises: How can I exploit the available BE resources for individual growth and, more importantly, what do I need to invest into it to do it in the future? The answer depends on the individual strategies, which range from focusing on the short-term success to breaking down the ecosystem defense barriers and exploiting the system resources as well as taking a leadership role and generating sustainable resources needed for the other
ecosystem members to survive. Independent of the decision about what role to play, the individual depends on information concerning other players.
Although BD affects players on multiple fields of attack (Cukier, 2014; McAfee & Brynjolfsson, 2012; Press, 2013; Zhang et al., 2014), we narrowed the field of identified topics identified to five influential topics that will identify opportunities and threats for BE players: individual marketing, health treatment, work opportunities, financial services, and security enforcement. The reduction criterion is based on a preliminary keyword analysis conducted in Google and Google Scholar. Selected topics related to "Big Data" achieved an average of 55,900 results in research-related contents and 48-900,000 in a general search.
To preserve the required level of standard deviation in model transparency, only the most important strategies are displayed. This results in hiding the direct feedback loops. Nevertheless, when observing from a distance, some of the most important system level loops ranging among multiple players can be identified. For instance, individuals receive protection from organizations and information providers by the regulators.
3.1 Individuals
Individuals are usually anonymized as customers or roles in organizations (Drucker, 2002; Dunkl et al., 2015). Nevertheless, if compared to the biological ecosystems, they play the role of cells with the special ability to stand alone or group with others to form an organization (Ajzen, 1991; Waelchli, 1989). Individuals actually run all the players in the ecosystem. Thus, every role—no matter how important—is designed to be executed by an individual. The question is, why do we not treat them as individuals? One of the obvious reasons is that it is exceedingly hard to follow the behavior of individuals and even harder to predict their actions while simultaneously not violating their personal integrity (Nelson, 1970; Zhang et al., 2014).
Individual objectives are highly volatile; they change over time and adapt to situations. Sometimes they are conflicting. For instance, they like autonomy in driving a car, but are averse to taking responsibility. The duality regarding BD technologies is that they like receiving customized services, but do not want to share uncensored personal data (Zhang et al., 2014).
Table 1 presents opportunities and threats to individuals for the selected BD domain. For opportunities, strategies on how to achieve them are represented; on the threat side, mitigation strategies are explained.
Table 1. BD Individual-related Opportunities and Threats and Strategies Used
BD domain	Opportunity	Threat
Individual marketing	Receive customized offers, potentials of choosing best-suited deals.	Becoming a target of marketing harassment, trading with individual data.
Strategies	Sharing data on their properties, preferences, and activities.	Relying on the system protection. Sharing data with trusted players, limiting data content, protecting from undesired listening, rejecting unwanted messages.
Health treatment	Individual diagnosis and treatment propositions based on group knowledge.	Misuse of individual medical data.
Strategies	Continually sharing medical data, using predictive models results.	Anonymization of shared data, audited data entry and data access.
Work opportunities	Finding perfect engagement.	Disclosure of job-seeking activities, deceiving job offers.
Strategies	Searching for work opportunities that match my Active management of data privacy, checking properties and offer desired rewards. the employee reputation.	
Financial services	Access to investment and funding opportunities	Fraud and default risks.
Strategies	Using tools for accessing inexpensive funding and profile-adjusted investments.	Using investment services with integrated fraud prediction.
Security enforcement	Using system security measures for a desired environment safety level.	Control misuse.
Strategies	Using available system services and resources, sharing data when observed.	Using legislation to protect individual rights, using social communities to control security organizations.
Source: Author's own data
BD technologies focus not only on individuals, but also try to collect data on their activities. Generally, this can have great positive effects on the usability of the services offered to an individual in an instance; on the other hand, this information can be used to harm the individual and exploit his/her potential weaknesses. Individuals can support the positive effects by sharing information, but they need system-generated protection to prevent undesired behavior by other players.
3.2 SMEs
SMEs operate on limited resources; consequently, they use external resources and a narrow set of products and services for a limited market (Barney, 1991). Their viability depends on the capacity to adjust to properties of the BE (Beer, 1972). Because of their abundant numbers and the enthusiasm of the involved individuals, they are considered the most important innovation force (Zenko & Mulej, 2011) and a major BE producer (E._C._European_Commission, 2004). In their domain, SMEs actively research and develop new approaches that will provide them enough resources. In other domains. they use existing state-of-the-art services.
As depicted in Table 2, SMEs in all business domains use BD services to optimize the exploitation of their business environment and expand their influence. These services are used as a plug-and-play appliance to minimize the costs of new
activities. SMEs typically face two kinds of threats: the active role of their competition and the disclosure of their behavior.
3.3 Large organizations
Large organizations have major influence in the local or global ecosystem (Beer, 1985; Davenport, 1998). In their domains (such as car manufacturing, energy providers, and pharmacy), they actively coordinate other players in the system. Large organizations include companies, public organizations such as hospitals, research organizations, educational organizations, and others. They possess the resources to lead big projects expecting long-term results (Moore, 1993); they systematically scan for promising solutions and adapt them to fit their needs. On the other hand, their adoption rate to changes in the ecosystem is rather slow.
Large organizations want to increase their influence and actively change their environment. To this end, they invest heavily in their domain-related research, and they go beyond using state-of-the-art toolsets and actively participate in their development until they fit their needs.
Large organizations use active participation in harnessing BD-related opportunities (see Table 3). They use BD technologies to gather more detailed data (for instance, using sensor data) or acquire data from their environment (such
as global medical data). They also actively participate in (for instance, social media-based profiling in the employ-data analysis research to develop tailored BD-based tools ment-recruiting process).
Table 2. BD SMEs' Related Opportunities and Threats and Strategies Used
BD domain	Opportunity	Threat
Individual marketing	Reach existing and new customers, with high selling potential.	Losing customer trust or being replaced by the competition.
Strategies	Combining classic marketing methods with outsourced services, offered by information providers.	Focusing on the customers, willing to accept marketing actions, providing them a real value added.
Health treatment	Using BD-based diagnosis and treatment selection services for their patients.	Potential of missuses by pharmaceutical companies.
Strategies	Using existing predictive models based on medical BD on individual symptoms to determine diagnosis and treatment.	Using generally acknowledged information sources, involving organizations with high reputation.
Work opportunities	Acquiring employees fitting the position.	Dishonest applicant information.
Strategies	Comparing the position requirements with the candidate properties.	Automatic profile assessment.
Financial services	Global direct investment and funding opportunities.	Fraud and default risks.
Strategies	Using services for finding the most appropriate P2P funding, building low-level risk reputation.	Using investment services with integrated fraud prediction.
Security enforcement	Attaining a desired safety level.	Total control.
Strategies	Using system information services to gain data on business partners' security risks.	Avoiding control or automatic reporting.
Source: Author's own data		
Table 3. BD Large Organizations' Related Opportunities and Threats and Strategies Used		
BD domain	Opportunity	Threat
Individual marketing	Retain existing customers, gain market shares, and access new markets more efficiently.	Not understanding the needs of customers, using wrong communication channels, sending wrong messages
Strategies	In-house data analysis, accessing external data for data mining, actively cooperating with information providers.	Analyzing the content and volume of communication, used by the targeted groups of customers, and adapting to their patterns.
Health treatment	Design systems that use existing knowledge for diagnosis and treatment selection.	Forcing selling of selected products, resulting in suboptimal medical treatment.
Strategies	Active cooperation in data design and knowledge extraction.	Building reputation, combining clinical results of healing substances produced by competing producers.
Work opportunities	Acquiring employees fit for the position.	Dishonest applicant information.
Strategies	Designing support for comparative analysis of a candidate's potential and the tasks laid out for him.	Profiling applicant data.
Financial services	Managing investment portfolio and using inexpensive funding resources, financing customers.	Fraud and default risks
Strategies	Using predictive analytics on investments, attracting low-risk investors.	Supporting the developments of fraud prediction models
Security enforcement	Designing a safe environment to conduct global operations.	Contra intelligence of players in external systems.
Strategies	Algorithms for identifying localized threats based on behavior analysis and social contacts.	Data security measures, protecting the knowledge of behavioral analytics.
3.4 Information providers
BD and cloud computing are responsible for the emergence of highly innovative new companies or the reorganization of companies with a long tradition of delivering information (rating agencies, registers, ERP providers, etc.). Information providers use their knowledge on how to access data, store data, blend data (publicly available, internal or restricted, social media, sensor-generated data, etc.), and analyze data to create services and products for other BE players. As they possess data from multiple sources and the knowledge to process it, they can actively use it to upgrade providing services to a new meta level, thereby becoming business integrators, financial intermediators, or service coordinators.
One of the common questions arising is whether the business partner will deliver. The most common strategy for predicting future behavior in a situation is using the knowledge of the masses. In the BD domains presented in Table 4, data on individual behavior are blended from multiple sources: In individual marketing, it is social media, sales, and localization data whereas in health treatment, data from diagnostic apparatuses are combined with medical records. BD projects are executed in cooperation with organizations or, as in the case of security enforcement, regulators.
Threats are often connected with the change of transparency in the system that information providers deliver. On one hand, all players would like a higher level of transparency of the system around them; on the other hand, they would like to conceal their potentially depraved behavior.
3.5 Regulators
Regulators' mission is to ensure that the desired processes in their regulation domain are executed efficiently and prevent undesired events. They do this by providing support, rules, and control mechanisms for the players' behavior. They consider players' viability, the level of activity in the system, and the system effects to the environment (Prosser, 1997; Warhurst, 2005). For instance, in the financial services domain, national and EU central banks provide rules and execute control in the form of constant reporting, but they regulate finance resources' prices and provide the required funds for the financial institutions to function (Beyer et al., 2010). For the regulators to act proactively, they need to measure activities and recognize the effects of desired and undesired behavior in the system (e.g., financial institutions are reporting to central banks for stress testing).
Table 4. BD Information Providers' Related Opportunities and Threats and Strategies Used
BD domain	Opportunity	Threat
Individual marketing	Offer data and services for identifying and sending customized offers to customers. Adapting a new role of market integrator.	Being accused of marketing harassment and trading with individual data.
Strategies	Predicting future individual customer desires based on BD associative data mining. Designing new cooperative channels.	Following the system rules that enable sharing of personal data to referenced players, applying control mechanisms, respecting the individual integrity, preventing misuse by their customers.
Health treatment	Diagnosis and treatment proposition based on group knowledge	Sharing individual medical data
Strategies	Designing predictive data-mining models for understanding patients based on knowledge stored in clinical BD.	Anonymization of shared data, audited data entry and data access.
Work opportunities	Connecting job seekers with potential employers.	Lack of discretion, dishonesty of job seekers and employees.
Strategies	Design global and local comparative analysis of job offers and profile data algorithms.	Developing data security measures and reputation models.
Financial services	Connecting investors and loan receivers.	Fraud and default risks
Strategies	Developing algorithms for finding the most appropriate peer-to-peer funding.	Developing fraud prediction algorithms and reputation analysis services.
Security enforcement	Providing methods of gathering, storing and analyzing BD.	Data leakage, data analysis methods' leakage.
Strategies	Developing new communication channels, BD storages, multimedia analysis, threat detection models.	Data security measures, protecting the knowledge on BD methods.
Table 5. BD Regulators' Related Opportunities and Threats and Strategies Used
BD domain	Opportunity	Threat
Individual marketing	Market optimization, reduced communication noise between the system players, better coordination between supply and demand.	Examples of marketing harassment, especially on players with low protection barriers
Strategies	Designing protocols for individual marketing, redesigning rules and support mechanisms by involving all players on the market. Design methods for continuous rule redesign process.	Using BD exception identification technologies to redesign system level rules and control mechanisms.
Health treatment	Creating a global knowledge-based medical system.	Sharing individual medical data.
Strategies	Designing protocols for safe medical data sharing, predictive data mining based on comparing the instance data with shared data pool.	Forming rules and creating control mechanisms on a system level for anonymization of shared data, audited data entry and data access. .
Work opportunities	Creating a transparent, secure environment for individuals and employees.	Indiscreet behavior, not fulfillment of obligations.
Strategies	Registration and validation of activities in the job-seeking and evaluation system.	Developing tools to build and express reputation of individuals and organizations.
Financial services	Design and manage fluid financial markets.	Prevent liquidity shortage or overflow, manage and mitigate risks.
Strategies	Co-design and manage new financing and investment models. Financial needs prediction model.	Design investment activities, demand and supply and projects' default rate of predictive analytics.
Security enforcement	Preventing undesired behavior of system and external players.	Misuse of security enforcement toolset.
Strategies	Forming dynamic rules and control mechanisms for identifying and mitigating undesired behavior based on all available data, exception analytics and behavior predictions.	Developing control systems over protocol execution and delivering them to the system players.
Source: Author's own data
Regulators use BD technologies' potentials (Table 5) to optimize players' interactions and use of the resources, provide a higher level of transparency in the system, and predict future interactions. To address threats to the weakest players in the system in the form of marketing harassment or indiscreet behavior, regulators use BD technologies to design a more transparent environment and elaborate on the reputation qualities. In terms of security enforcement, they use similar strategies as do organizations to profile their partners, but they do it on a larger scheme. Regulators can only be successful by recognizing the power of all of the participants in the system.
4 BD System Impact
In this section, the five players' strategies are presented, addressing opportunities and threats. To create a system overview, the effects of players' strategies in relation to the other players' strategies are visualized. This will help us support the potential cooperation among players, eliminate threats, and achieve a win-win-win situation.
Figure 2 presents a highly simplified model of the effects BD have on the BE players, and their responses are provided. For every combination of five players and five BD domains, only one opportunity and one threat are represented. In addition, only one player's strategy is selected for every one of these. To preserve the minimal state of readability, the effects of a player's strategies with other players' strategies are not displayed. Positive (or supporting) flows are marked with "+" and negative (mitigation) ones are marked with "-".
Individuals are the main source of data. At the same time, end users—either of BD results or of products and services— tailor their resources to their desires with the help of BD. They are the most vulnerable group as they are threatened by marketing harassment, data trading, misuse, and disclosure. Interestingly, they are positioned at the opposite side of the information providers, assessing the relationships among these entities as relatively weak. Because the regulators' strategies are primarily focused on mitigating threats toward them, they are positioned in their vicinity.
A high level of overlap exists in opportunities and threats for SMEs and large organizations, ranging from reach existing
and new customers to total control of the system. Nevertheless, their strategies differ considerably. SMEs tend to use newly developed BD-based tools and services whereas large organizations co-develop these in their domains of interest. For instance, to reach better diagnosis and treatment selection, SMEs (e.g., practicing doctor offices) will use existing predictive models whereas large organizations (e.g., clinical centers and pharmaceutic companies) actively cooperate in data and algorithm design. They also share threats (losing trust, fraud, and default risks). Their strategies range from building up their reputation to the development and use of fraud prediction models.
Information providers' strategies are highly correlated with large organizations' strategies. They use organizations to blend data from multiple sources and deliver results to indi-viduals—again through organizations (development of peer-to-peer algorithms to connect investors and loan receivers). Because of their knowledge of multiple domains, they tend to integrate multiple domains, such as marketing, sales, and finance, where they correlate with the regulators' objectives of coordinating the players.
The role of the information providers has significantly increased as they provide services to all players in the system and redesign domain processes. Thus, information providers' initiatives should be closely monitored by the regulators and above all by the public initiatives of individuals.
Regulators play a two-sided role: First, they rearrange the ecosystem processes to achieve a higher level of optimization; second, they provide system protection for the vulnerable players. The regulators' optimization efforts (market optimization, better coordination, fluid financial markets) provide guidelines for information providers. The protective side of the regulators is highly connected with the threats to individuals (marketing harassment, data trading, misuse, and disclosure) and organizations (losing trust, fraud, and default risks). To execute strategies to prevent threats (e.g., sharing rules and control mechanisms, building reputation, using predictive analytics), they include and co-design products and services offered by the information providers.
Monitoring individual actions and generating a smart reputation can create a major shift in cooperation. It may provide worldwide personal reputation transparency and provide a way for individuals to act socially responsibly. This will not only change business behavior, but will also affect all parts of the society.
On the negative side, BD will raise considerable privacy and security issues for individuals and organizations. It will redefine business secrets and fundamentally challenge
individuals' privacy rights. Lowering organizational and personal independence will increase the possibility of rapid misinformation dispersion.
5 Discussion and Conclusion
BD promises to be a disrupting technology, facilitating significant changes. In the BD R&D community, many efforts have been focused on storing and integrating large quantities of rapidly changing data with a high variety in form and content. Some focus has been put into supporting new ways of collaborations, predictions, and advanced user experiences. Although some researchers follow a requisitely holistic vision in the effort to create smart environments, most efforts focus on resolving partial issues.
It is hard to gain an appropriate perspective on the impact. An overly schematic view obscures all the important details and provides no value added or reference. A detailed view is too crowded and prohibits seeing the forest because of the trees. To provide a (somewhat) transparent view and still display important details, we used system analysis to achieve a visualization repository, displaying only the most important entities that occur in a selected viewpoint. We decided to include a limited number of players (5), BD domains (5), opportunities and threats (one of each for every BD domain and a player combination), and strategies to use the opportunities and mitigate threats (one for every opportunity and threat). The selection of the appropriate representatives is based on the literature reviewed.
The system of creating an overview is twofold. In step one, for every player in the system, its objectives, BD domains, related opportunities, threats, and strategies are scripted. This provides a brief profile of a player, his motivation, and resources he is capable or willing to engage when facing changes in his environment. In the second step, a system dynamic diagram is used to provide an overview of all the involved entities. The visualization of relationships among entities provides the desired overview effect and simultaneously gives information on particular strategies involved in reaching particular players' objectives.
This paper delivers important insights for multiple R&D communities. For BE designers and policymakers, it provides a tool to overview intersections of BE players and BD domains. It helps BD architects recognize the potentials their services offer to the players and threats they need to help preventing. It helps business managers direct organizations' development to fully exploit the BD potentials. Finally, it helps individuals actively influence the development of society and build their reputation.
Figure 2. The system dynamics diagram of BD opportunities, threats, objectives, and strategies
This paper has provided a restricted view of the system. To generate a better BE-BD map, multiple limitations should be surmounted. It is hard to condense the system complexity: the players, their relationships, and strategies over time for entire populations at the instance level and the predictions based upon BD in a standard research paper, formatted for a static (even printed) version.
Thus, two paths should be followed. The first relates to the research scope. In terms of all the important relationships
and strategies, we need to focus on the single instance—a single strategy that needs to be described in detail—to discover its complexity and its impact on the system entities and then connect them in a holistic map. The second involves a dynamic, highly visual communication channel for distributing the research results, capable of representing the research models' full complexity that goes well beyond current scientific journals' formats.
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Authors
Igor Perko is an assistant professor at the University of Maribor, Faculty of Economics and Business, Slovenia. His PhD thesis was "Intelligent agents in management information systems." His research interests include business intelligence systems and Big Data, focusing on cooperation support in business ecosystems. He is connecting the use of knowledge management structures, business data sharing, Big Data, cloud technologies, and predictive analytics to provide intelligence support of trans-business processes. He is the author of professional and scientific papers, actively involved in business ICT development, and a member of WOSC.
Peter Ototsky graduated as applied mathematics and physics master in 2005 in Moscow Institute of Physics and Technology (Moscow). From 2003 to 2005 he worked in information technologies domain supporting SAP R/3 in JSC Gasprom Export. In 2008 he received PhD for a complex systems modelling at synergetic science school in the Keldysh Institute of Applied Mathematics, Russian Academy of Science. Since 2009 works as a commercial director in a wholesale company. From 2010 to 2012 was teaching a course of systems modelling and management cybernetics. At 2010 co-found a Moscow Management Cybernetics club. Since 2008 he leads a Cognitive Centers team at the Keldysh Institute of Applied Mathematics performing
research and several projects for regional administration and private companies. His research interests are modelling, cybernetics, complexity management and innovation management.
Veliki podatki za soudeležence poslovnih ekosistemov
Izvleček
V predstavljeni raziskavi povezujemo nekaj najbolj perspektivnih področij uporabe velikih podatkov z reprezentativnimi predstavniki skupin poslovnih ekosistemov. Z analizo literature identificiramo trenutno stanje razvoja velikih podatkov na pomembnejših področjih njihove uporabe: pri osebnem trženju, zdravstvenih storitvah, priložnostih za delo, finančnih storitvah in zagotavljanju varnosti. Teorije sistema smo uporabili za identifikacijo predstavnikov skupin, na katere vplivajo veliki podatki: posamezniki, mala in srednja podjetja, velike organizacije, ponudniki informacij in regulatorji. Razmerja med področji uporabe velikih podatkov in deležniki pojasnjujemo z analizo priložnosti in tveganj ter strategij, s katerimi se ti deležniki odzivajo. Za vizualizacijo relacij smo oblikovali model z orodji sistemske dinamike.
Ključne besede: poslovni ekosistemi, veliki podatki, ponudniki informacij, sistemska dinamika
Nonprofit Organizations from the Perspective of Organizational Development and Their Influence on Professionalization
Katalin Dobrai
University of Pecs, Faculty of Business and Management, Department of Leadership and Organizational Sciences, Hungary dobrai@ktk.pte.hu
Ferenc Farkas
University of Pecs, Faculty of Business and Management, Department of Leadership and Organizational Sciences, Hungary farkas@ktk.pte.hu
Abstract
The aim of this paper is to give an overview of the phenomenon of professionalization that is observable in organizations from the nonprofit sector. Empirical research was conducted among Hungarian nonprofit organizations, and the data were collected within the framework of a country-wide survey. Through the analysis of the research results, the paper provides deeper insights into knowledge about professionalization trends in the nonprofit sector. It proves that organizational development positively impacts nonprofit organizations' improvement of their professionalization level and the members of these organizations.
Keywords: organizational development, nonprofit organizations, professionalization, learning, knowledge
ORIGINAL SCIENTIFIC PAPER
RECEIVED: NOVEMBER 2015
REVISED: FEBRUARY 2016
ACCEPTED: APRIL 2016
DOI: 10.1515/ngoe-2016-0009
UDK: 334.72
JEL: L30, O15
Citation: Dobrai, K., & Farkas, F. (2016). Nonprofit Organizations from the Perspective of Organizational Development and Their Influence on Professionalization. Naše gospodarstvo/ Our Economy, 62(2), 25-32. DOI: 10.1515/ngoe-2016-0009
1 Introduction
The purpose of this paper is to provide an overview of special issues related to the growing professionalization of nonprofit organizations from both theoretical and practical perspectives. In recent years, new dilemmas have arisen for those involved in the nonprofit sector. These dilemmas regard knowledge processes such as learning and development of individuals working for nonprofit organizations (NPOs) as well as organizational development (OD) and the importance of professionalization for individuals and organizations.
Taking these circumstances into consideration, this article focuses on the relationship between the development of skills and the growing professionalization of their activities. With the participation of Hungarian nonprofit organizations, a large sample survey of Hungarian nonprofit organizations provided the basis for the empirical evidence. A general decline in the number of organizations during the last four years (Statisztikai Tükör, 2014) has drawn the authors' attention to the fact that sustainable existence of the organizations of the nonprofit sector to a large extent depends on their development.
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. 62 No. 2 2016
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. 25-32
The paper consists of two parts. The first part includes desk research in which we utilized papers discussing the profes-sionalization of NPOs that were published mainly in the last decade. The second part contains a detailed research methodology along with analysis and discussion of the empirical research. The paper concludes with lessons learned from the research, limitations of the research, and suggestions for further research ideas.
2 Theoretical Framework
In this chapter, we briefly clarify the basic terms and phenomena relevant for the empirical research.
2.1 Nonprofit organizations and challenges
Different terms are used worldwide for organizations in the nonprofit sector (non-governmental, voluntary, etc.), and the terms themselves are used in various meanings. For this reason, it is necessary to explain our understanding of this term. We accept Salamon and Anheier's (1992) definition according to which nonprofit organizations are entities that:
•	are institutionalized and have regularity in their activities;
•	are private and independent from the government, even if they receive support from the government;
•	do not distribute profits to their owners or leaders, but reinvest their surplus earnings into the objectives of the organizations;
•	are not controlled by other entities from outside the organization; and
•	provide voluntary membership or participation in the activities.
However, these principles are often are compromised in practice in many countries.
The changing environment makes daily operations for nonprofit entities increasingly difficult. Some challenges include the emergence of the so-called knowledge-intensive business services (Dobrai & Farkas, 2008), competition from other sectors and from organizations in the nonprofit sector, and more rigorous regulations. Meeting these challenges involves making changes in nonprofit organization, structure, leadership and organizational processes (Epstein & McFarlen, 2011). Performance is more essential than ever; thus, fulfilling commitments is challenging for the NPOs. NPOs must learn constantly so that they acquire knowledge from business sector companies (Chen & Graddy, 2010; Kreutzer, 2009). By precisely defining their goals, they increase the likelihood of success in the accomplishment of
their mission (Bradach, Tierney, & Stone, 2008). Acquiring new and specialized knowledge in other fields also enables them to use models and solutions to implement methods of the business sector for long-term existence, better performance, and sustainable success (Al-Tabbaa, Leach, & March, 2014). These changes found their way into the nonprofit sector from the business sector through the public sector, where methods of new public management were introduced. This led to the adoption of management practices of for-profit organizations (Lewis, 2001; Roberts, Jones, & Fröhling, 2005).
2.2 Professionalization in nonprofit organizations
2.2.1 The term "professionalization"
The terms professionalization and professionalism have been the topic of continuous discussions. In numerous publications, Evetts has provided a very detailed and critical analysis of the sociological aspects of professionalism as well as its changes during the last decade to the present (Evetts, 2011; Maister, 2003).
Professionalization in NPOs can be understood as the implementation of business strategies and the use of methods and tools to help entities become market oriented (Mannsky & Siebart, 2010). This process is characterized by the usage of tools and methods transferred into the nonprofit from the for-profit sector (Alfirević, Pavičić, & Najev Čačija, 2014). This requires implementing strategic thinking into these organizations (Clark, 2012) and enabling them to perform well in special areas not focused on earlier, such as marketing (Chad, Kyriazis, & Motion, 2014) or organizational performance (Alfirević et al., 2014). Publications reveal different concepts of professionalization, including organizational, occupational, and managerial factors (Evetts, 2011; Salamon, 2012).
Professionalization from the perspective of organizational sciences has become a current topic with respect to nonprofit organizations both in countries where NPOs have long existed and in the post-socialist countries where the sector's professionalization level is generally low (Rakar & Kolarič, 2010). However, efforts have already addressed a large variety of country-specific questions (Alfirević et al. 2014; Čada & Ptačkova, 2014; Dill, 2014; Dill, Zrinščak, & Coury, 2012; Korolczuck, 2014; Strečansky & Stolarikova, 2012; Rakar et al., 2011).
Practice-oriented publications, such as those by Callanan, Gardner, Mendonca, and Scott (2014), suggest professional solutions for eliminating deficiencies in most leadership fields and activities. In addition, cultivating and staffing talent is
attracting more attention now as a way to professionalize performance (Green & Hauser, 2012; Neff & Randal, 2011).
Based on the different concepts of professionalization and professionalism discussed and approaching them from the perspective of organizational sciences, we formulated our own definition that we found to be applicable for our empirical research. Hence, we understand professionalization as the process of becoming professional (i.e., developing a high level of professionalism). This involves not being an amateur anymore, showing expertise, skillfully executing organizational tasks, and providing superior services both internally and externally.
2.2.2	Professionalization practices in the sector
It is increasingly characteristic of the sector that, along with the traditional nonprofit organizations (associations and foundations), new legal and hybrid forms are emerging. Hybrid organizations possess characteristics of more than one sector (Billis, 2010; Davie, 2011; Strečansky & Stolarikova, 2012) and systematically integrate the civil society and markets (Jäger & Schröer, 2014). They use governance and operational methods, employ techniques of different organizational types, and are characterized by an improved business mindset. Their emergence is a sign of the dynamism and resilience of the sector's organizations (Salamon, 2012) that offer new solutions and opportunities, such as accessing social networks and other formalized structures, while bringing professionalized knowledge into the organizations. Dynamism and resilience are phenomena that accompany the implementation of different governance methods and techniques (Wellens & Jegers, 2013). In addition, various intra-and inter-sector cooperative efforts contribute to improved organizational learning in the nonprofit sector as well as its becoming more effective (Al-Tabbaa et al., 2014; Chen & Graddy, 2010; Cousins, Goh, Elliott, Aubry, & Gilbert, 2014).
2.2.3	Organizational development (OD)
By narrowing the tools of professionalization, we now concentrate our attention on OD as a relevant component of our empirical research. Although a variety of definitions of OD are accepted and used by organizations, some common elements can be identified, as can be seen in the following brief overview.
Raia (1972, p. 13) sees the contribution of OD in its features in that it "focuses on innovation and planned change in organizations." Its outcome is an increased body of knowledge. According to one popular definition, organizational development is "the system-wide application and transfer of
behavioral science knowledge to the planned development, improvement and reinforcement of the strategies, structures and processes that lead to organizational effectiveness" (Cummings & Worley, 2008, p. 752). Jackson (2006, p. 33) also stressed that OD is a collaborative process to improve organizational effectiveness.
OD is also viewed as a means of professionalization and capacity building. OD is a process that focuses on the organization and not the individual, although it provides the individual with an opportunity to learn, acquire, and develop new knowledge. In the nonprofit sector, the choice of how to develop different capacities depends on stakeholders' interests as they have different preferences and different reasons to support organizational development initiatives (Millesen, Carman, & Bies, 2010). OD practitioners play a central role in the OD process. They are consultants who work as facilitators together with nonprofits in fields where OD is necessary—namely, in various areas of interventions in the nonprofit organizations such as people carrying out the projects, staff and organization leaders, or even donors (Tschirhart & Bielefeld, 2012).
OD practitioners provide knowledge-intensive services (Dobrai & Farkas, 2008) that lead to a joint learning process and the co-production of new knowledge. Wirtenberg and her colleagues (2007) found that OD experts can and should contribute to the development of nonprofit organizations in areas of urgency by working together with the leaders of nonprofits, transferring knowledge to them, and presenting a high level of flexibility.
For our empirical research, we built upon the previously mentioned features of OD. We view this management tool as a top-down effort that involves the whole organization and aims to increase the efficiency and lifecycle of an organization by taking structured actions. Thus, in conclusion to this brief overview, we can say that the implementation and usage of management tools and techniques, the introduction of new and better solutions, networking, cooperation and special processes such as OD are critical to improving the professionalization level of an organization.
3 Empirical Research
The following sections of the paper provide a brief summary and analysis of the empirical research.
3.1 Hypotheses
This article summarizes the findings that answer the following hypotheses:
H1. A significant difference can be observed in the level of professionalism between the organizations that have already participated in OD programs and those organizations that have not taken part in such programs.
H2. Organizational development programs help the professionalization of nonprofit organizations.
H3. There is a connection between the perceived professionalization level of the respondent and that of his/her perception of the organizational level of professionalization.
H4.The differences perceived in the personal and organizational professionalism show a close correlation.
For the country-wide survey, 18,000 questionnaires were sent to organizations via e-mail; 841 questionnaires were returned, representing each of the official activities listed by the Hungarian Statistical Office. The returned questionnaires met the requirements of representativeness regarding the location of the organizations and showed the approximate relationship between the two basic legal forms (associations and foundations).
4 Results and Discussion
4.1 Findings
3.2 Methodology
In order to determine whether organizational development a suitable tool for promoting and enhancing the professionalization of nonprofit organizations, we used various methods during the different phases of the research (Table 1).
The empirical research started in 2011-2012 with a pilot project that included two counties in Hungary (there are 19 regional units called counties in Hungary). An online questionnaire was sent to 58 participants of an organizational development program at the House of Civil Communities in Pécs and was returned by 33 organizations. In the next phase, semi-structured interviews were conducted with representatives of 38 organizations, most of whom participated in the online survey. In the third phase (i.e., 2013), a large sample survey took place that used the experiences of the first two phases and the database of the Central Statistical Bureau of Hungary. We also conducted 41 additional interviews in the last research phase with organizations from different regions of the country.
We can make the following general statements about the participating organizations and the people who filled out the questionnaire for those organizations:
There is a medium-strength positive relationship between the age of the organization and the number of full-time employees, which implies that older organizations have a higher number of full-time employees (Pearson correlation: 0.250**, significant at the 0.01 level, 2-tailed).
•	There is a positive relationship between the age of the organizations and the number of members, suggesting long-term development and the opportunity for performance improvement (Pearson correlation: 0.297**, significant at the 0.01 level, 2-tailed).
•	Both findings have very important implications for the performance of the organizations in the sector. It is well known that many organizations do not have any paid employees for obvious reasons.
•	The analysis of the relationship between personal and organizational professionalization (Table 2) shows that:
Table 1. Phases of the Research and Methods Applied
Research Phases	Methods Used	Number of Organizations Involved	Location of Organizations Involved
Phase 1	questionnaire	33	2 counties
Phase 2	interviews	38	2 counties
Phase 3	questionnaire	841	country-wide
Phase 4	interviews	41	country-wide
Source: Authors' own data			
Table 2. Participation in an OD Progi	ram, and the Perceived Level of Professionalization (7-Point Scale, Mean)		
Participation in OD Program	Evaluation of Professionalization (7-point scale)		
Participated	Individual		Organization
	4.78		4.62
Did not participate	3.60		3.41
•	Respondents who previously participated in OD programs gave their own professionalization level an average score of 4.78 on a 7-point scale and placed the professionalization level of their organization somewhat lower, with an average score of 4.62; and
•	Respondents who had never participated in an OD program perceived the two professionalization levels as being much lower: 3.60 for the individual and 3.41 for the organization. (H1)
This result was also supported by a correlation analysis that pointed out a positive connection between participation in an OD program and the perceived professionalization level (H2)—namely:
•	A medium-strength positive connection between participation in an OD program and the perceived level of personal professionalization (Cramer's V: 0.355; p = 0.000, Pearson correlation: 0.493. Correlation is significant at the 0.01 level, 2-tailed); and
•	A medium-strength positive connection between participation in an OD program and the perceived level of organizational professionalization (Pearson correlation: 0.575. Correlation is significant at the 0.01 level, 2-tailed).
The hypothesis was also accepted (Table 3) regarding the impact on satisfaction with the program by the program provider's origin. According to the research findings, how efficient participants find an OD program depends on the provider of the OD program. Although no significant difference exists
between the averages of the three categories, those who had participated in an EU-supported OD program found that they had reached a high level of professionalism. Those least satisfied were the participants of domestic programs (H3).
If we look at the whole sample, we can say that, regarding the personal and organizational professionalization level (Table 4), for their own personalization level, respondents gave on average a score of 3.93 and scored their organization's professionalization level 3.75 on average. Skewing and kurtosis showed normal distribution in both cases. This difference implies that opportunities exist for further professionalization of the organizations if they utilize members' knowledge.
If we want to analyze the relationship between perceived level of personal professionalization and the field of activity of the represented organization by using the test of homogeneity of variances and ANOVA, we can state that, at the 5% significance level, a connection exists between the two variables (p = 0.017). By using the same methods, we also find a relationship between the perceived level of organizational professionalism and the field of activity of the represented organization (p = 0.000).
The data from our research also show that the higher the perceived level of the personal professionalization, the higher the perceived level of organization professionalization (Pearson correlation: 0.753**, Sig. (2-tailed) 0.000, strong and positive relationship. [H4]).
Table 3. Provider of the OD program and the Perceived Level of Professionalization (7-Point Scale, Mean)
Origin of the Organization Providing the OD program	Level of Personal Professionalism Level of Organizational Professionalism	
Hungary	4.67	4.50
EU	5.03	4.81
Foreign	4.87	4.87
Source: Authors' own data		
Table 4. Comparison of Perceived Level of Personal and Organizational Professionalization		
Characteristics	Personal	Organizational
Professionalism		
N	776	774
Mean	3.93	3.75
Std. deviation	1.584	1.598
Mode	5	3
Skewness	-.158	-.699
Std. Error of Skewness	0.88	0.88
Kurtosis	-.632	-.763
Std. Error of Kurtosis	.175	.176
Source: Authors' own data		
Observing the connection between the professionalization level of the organization and the age of the organization, we can conclude that those organizations that achieved the highest professionalization level (4.10) had been operating for 9 to 15 years whereas the lowest level was characteristic of organizations that had existed for 1 to 3 years (2.88). The difference between these values also supports our assumptions regarding the connection among age, development, and professionalism at both the individual and organizational levels.
4.2 Limitations of present study and opportunities for future research
As the survey results demonstrated, the OD programs helped people and organizations learn and improve their skills and knowledge and become more professional in their service. Hence, it is a good tendency not only to look at the targeted community that these organizations serve, but also take care of the organization. The finding that the OD programs and OD providers influence the subjective professionalization level of the individual can facilitate a better choice of OD program.
The research limitations are twofold. In some cases, although it was clear that there was a difference between the different categories, some tests to prove it with a more sophisticated method could not be carried out because the sample did not satisfy certain criteria of that method. The comparability of the results with research in other countries is limited as most papers address a diversity of topics related to country-specific problems of professionalization as mentioned in the theoretical part of the paper (Dill, 2014; Korolczuck, 2014; Strečansky & Stolarikova, 2012). However, this also
suggests the possibilities for further research to be expanded internationally based on the existing experiences and to be deepened and broadened.
5 Conclusion
Through an analysis of writings and examples from actual practice, this article has provided evidence of the fact that nonprofit organizations feel the importance of organizational development from the perspective of their sustainable existence. As the survey results demonstrated, OD programs help nonprofit organizations learn and improve their skills and knowledge and become more professional in their services.
The findings support our hypotheses that OD programs and OD providers influence the subjective professionalization level of the individual and of the organization and that a strong positive relationship exists between personal and organizational professionalism. The hypotheses were verified, and the answer to the research question is that organizational development is a suitable tool to promote and enhance the professionalization of nonprofit organizations.
However, our research should also be compared with research in other countries. Future research could be expanded internationally and Phase 4 interviews deeply analyzed.
This paper contributes to the knowledge of the professionalization in the nonprofit sector not only in Hungary, but also in other post-socialist countries. As a result, Western counterparts can also see the development of the sector in this region.
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Acknowledgments: The authors are grateful to the Hungarian Scientific Research Fund project No. 101886 for supporting
the research "Knowledge-based services—Professionalization of nonprofit organizations," analyzed in the paper. This paper
is dedicated to the 650th anniversary of the establishment of the University of Pécs, Hungary.
Authors
Katalin Dobrai, Ph.D., is an associate professor at the Department of Leadership and Organizational Sciences of the Faculty of Business and Economics of the University of Pécs. Her teaching areas include leadership and organization, knowledge management, and human resource management. Her research focuses on knowledge management and organizational learning in knowledge-intensive businesses and nonprofit organizations. Postal address: 7622 Pecs, Rakoczi str. 80, Hungary; Phone: (36) 72/ 501599 ext. 23132, e-mail: dobrai@ktk.pte.hu
Ferenc Farkas, Ph.D., is a full professor at the Department of Leadership and Organizational Sciences of the Faculty of Business and Economics of the University of Pécs. His teaching areas include change management, organizational behavior, and leadership. His research interest focuses on nonprofit management and leadership as well as HRM. He has been the team leader of Hungarian and international projects, financed by the EU and the Hungarian government. Postal address: 7622 Pecs, Rakoczi str. 80, Hungary; Phone: (36) 72/ 501599 ext. 23130, e-mail: farkas@ktk.pte.hu
Neprofitne organizacije z vidika organizacijskega
• ••	i •	Г" *	I *	* *
razvoja in njegovega vpliva na profesionalizacijo
Izvleček
Cilj tega članka je predstaviti fenomen, ki se imenuje profesionalizacija in ki ga je mogoče opaziti v organizacijah neprofitnega sektorja. Empirična analiza je bila izvedena v madžarskih neprofitnih organizacijah, podatki pa so bili pridobljeni v okviru deželne raziskave. Z analizo raziskovalnih izsledkov omogoča članek globlji vpogled v znanje o profesionalizacijskih trendih v neprofitnem sektorju. V članku dokazujemo, da organizacijski razvoj pozitivno vpliva na izboljšanje ravni profesionalizacije v neprofitnih organizacijah in pri njihovih članih.
Ključne besede: organizacijski razvoj, neprofitne organizacije, profesionalizacija, učenje, znanje
The Analysis of Barriers in Succession Processes of Family Business with the Use of Grey Incidence Analysis (Polish Perspective)
Ewa Wi^cek-Janka
Poznan University of Technology, Poznan, Poland ewa.wiecek-janka@put.poznan.pl
Rafat Mierzwiak
Poznan University of Technology, Poznan, Poland rafal.mierzwiak@put.poznan.pl
Joanna Kijewska
Poznan University of Technology, Poznan, Poland joanna.kijewska@put.poznan.pl
Abstract
ORIGINAL SCIENTIFIC PAPER
RECEIVED: FEBRUARY 2016
REVISED: APRIL 2016
ACCEPTED: MAY 2016
DOI: 10.1515/ngoe-2016-0010
UDK: 334.722.24
JEL: D64, L26, M12
Citation: Wi^cek-Janka, E., Mierzwiak, R., & Kijewska, J. (2016). The Analysis of Barriers in Succession Processes of Family Business with the Use of Grey Incidence Analysis (Polish Perspective). Naše gospodarstvo/Our Economy, 62(2), 33-41. DOI: 10.1515/ngoe-2016-0010
The article presents results of research on the identification and evaluation of barriers faced by successors in family businesses during the first process of succession. The analysis of empirical material used grey systems theory, which was considered as an equivalent for the analysis of small samples and qualitative research. While conducting the literature review and empirical study, the authors concentrated on (a) the identification of barriers in the development of family firms and (b) eliciting the perspective of the new generation of owners in family firms entering the succession process through an empirical analysis of the assessed level of risk in relationships with family and business.
Keywords: Family business, grey incidence analysis, grey system theory
1 Introduction
Succession in a family firm can be discussed in various contexts—namely, as an act finalizing the period of management of one generation, without which it is difficult to define a company as a family business (Barach & Ganitsky, 1995; Ganitsky, Carson, & Doochin, 1988; Litz, 1995; Sharma, 2002; Ward, 1987); as a process that accompanies the owners and successors during the generation change (Astrachan & Kolenko, 1994; Astrachan & Shanker, 2003; Blake & Saleh, 1995; Budge & Janoff, 1991; Cadieux, Lorrain, & Hugron, 2002; Danco, 1975; Davis, 1982; Klein 2000; Duh, 2003; Duh, Belak, & Milferner, 2010; Dyer, 2006; Dyer, 2003; Letonja & Duh, 2015); and as a systemic challenge that changes the view on the components of a family firms, redefines the norms and values, and influences business and family relations (Wi^cek-Janka, 2013). While discussing succession, one ought to look at a family firm as a system. The main challenge for explicitly defining the notions of family enterprise or family firm is the difficulty in the proper conceptualization of the level of component dependency,
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which is its immanent feature. Kepner (1991) considered that the strands of the family and business system are so tightly intertwined that it is impossible to disentangle them without seriously damaging one of them. Budge and Janoff (1991) conducted research to explain how business families draw from two discourses—the family and the business—to communicate and to understand themselves and the world. Similar research was conducted by Swagger (1991) who, studying the succession process in family firms, was analyzing the pattern of relationships among all the members of the generation of successors—namely, sons and daughters, including their spouses. He was interested in the influence of the relationships among the members of the next generation and their personal needs. In these approaches, the functioning spheres of the individuals, family, and business are combined within the framework of the concept of mul-tigenerationality. The aforementioned fields (strands and discourses) are governed by different rules, needs, and values. Part of them function in co-existence, and some of them generate the effect of positive synergy; yet some have a negative influence. Maintaining a relative balance between fields defined in this manner forces the owners to engage in constant activity in order to merge the interests of these fields and redefine the values and order governing them. For the needs of this article, the authors adopted a definition that takes this division into account. Thus, a family enterprise is defined as:
a market organism trigonal in its structure, encompassing family, business and individuals, which functions according to various, but mutually adapted objectives, and which devotes its energy to accomplishing them in multigenerational perspective by management and the control over its functioning and ownership (Wi^cek-Jan-ka, 2013, p. 35).
Many researchers and practitioners in the circle of family entrepreneurship have expressed the opinion that the responsibility for ensuring succession rests chiefly on the founders and owners of these firms (Danco, 1975). The remaining ones relate to the success of the succession process with the traits, competencies, and experiences of the subsequent generations (Barnes, 1988; Aldrich & Cliff, 2003; Handler & Kram, 1989; Dunk, Jimenez, Sarotar Zizek, Milfelner & Kallus, 2015). The scientific papers also include a view that succession depends on family values and upbringing models employed by the parents (Arnoff, McClure, & Ward, 2012; Davis, 1982; Handler & Kram, 1989; Kedmenec, Sebjan, & Tomic, 2015). Lansberg (1988) treated the succession process as "a change which influences the functioning the whole system of family and business, including the family members, and the environment meant as the suppliers, customers and local economy" (p. 120). The authors of the article acknowledge a similar approach to succession and treat succession as a planned change (Letonja & Duh, 2015;
Wi^cek-Janka, 2013). A planned change can help impede conflicts and secure the relationships within the family, especially considering that succession process usually involves resistance—first at the planning level and later in the realization itself—which concerns the founders themselves (the seniors), the successor, the remaining members of the family, and finally non-family employees. Family enterprises frequently postpone the decision about entering the succession process in order to avoid problems and conflicts that can be related to it.
In the context of multigenerationality, one ought to strive for the recognition of succession as a systematic change, accomplished at the pre-assumed period of time, such as every 25 years (with the assumption of a family firm's proper course of development). Hence, what can the planned and systematic successional change be linked with, apart from the time frames? It can consist in a deliberate and organized search for and shaping of the opportunities to accomplish the objectives concerning upbringing and education, oriented toward preparing first the successor, second the senior to assume a new social role, and third the environment to accept the new (Duh et al., 2010; Wi^cek-Janka, 2011).
The aim of this article is to identify and analyze the barriers that may emerge in the succession process, especially barriers concerning the successors themselves. While conducting the literature review and empirical study, the authors concentrated on (a) the identification of barriers in the development of family firms and (b) the elicitation of the perspective of the new generation of owners in family firms entering the succession process, through an empirical analysis of the assessed level of risk of encountering the identified barriers in their personal succession-related experiences.
Due to the complex characteristics of barriers' identification in the functioning of family firms, especially succession, the accomplished studies ought to be treated not as responses to detailed questions, but as a complementary situational study, drawing from the experiences of the experts, including the founders of the companies, as well as the successors from the next generation.
2 Description of the Collected Empirical Material
The study was conducted in two stages, employing two research methods: an in-depth group interview and a survey. The objective of the first stage was the identification of the barriers in the succession process, based on the opinion of the successors in Polish family firms according to their responses during in-depth group interviews. The results of
the conducted survey allowed for the classification of the barriers in the succession process into two groups: internal and external ones. Internal barriers are related to personal traits comprising knowledge, competencies, and personality, while the external ones encompass market conditions, culture along with family and business values, and finally interpersonal relationships. The model of successors' barriers in the succession process, taking their source into account, is presented in Table 1.
The study of Polish successors was conducted using an elaborate methodology whose chief objective was to elicit the subjectively identified barriers in the succession process. The statements had open characteristics and were obtained during two in-depth group interviews with successors entering the succession process (n = 25). In a survey led by a moderator, the interviewees presented their experiences related to the process of succession and the emotions associated with it. In one of the stages of the interview, the respondents were asked to name several (between 3 and 5) barriers that, in their opinion, impede the succession process. The obtained list of barriers is presented in Table 2.
In the surveyed sample, fear was identified as a significant barrier. During the interview, the analysis of this category was deepened. As it turned out, fear in the succession process can be interpreted differently and can have different backgrounds. Hence, fear was divided into several different categories: fear of responsibility, fear of criticism, fear of competition, and fear of being unsuccessful.
In the second stage of the study, the successors themselves assessed the impact that the identified successors' barriers have. The test group consisted of successors of Polish family firms in the course of the succession process (n = 25). The identified barriers (X^X ) were included in the questionnaire and submitted for assessment in a five-point scale, where the influence of the identified barriers on the successor was rated as 1 (has no influence), 2 (has little influence), 3 (has a moderate influence), 4 (has a rather large influence), or 5 (has considerable influence). The following symbols were used: Xt = lack of professional training; X2 = lack of experience; X3 = bad relations with parents; X4 = other plans; X5 = successor is too young; X6 = large number of successors; X7 = lack of perspectives for development of the
Table 1. Barriers to Successors, Identified by Experts from Foreign Academic Centers
Successors' internal barriers
External barriers
Personality-related:
•	Inability to accept change
•	Limited resistance to stress
•	Inclination to impose one's own will instead of listening to others
•	Inexorability
•	Lack of sensitivity to other people's needs
•	Lack of openness
Market conditions:
•	Competition from larger companies
•	Not realizing the requirements of globalization
Level of knowledge:
•	Experience
•	Professionalism
•	Lack of commitment
Culture and values:
The senior's approach and employees' attitude Maladjustment to work requirements after the freedom successors had when growing up Lack of knowledge about organizational culture Questionable attitude to honesty
Competencies:
•	Problems with communication
•	Lack of ability to work in a group
•	Lack of creativity and innovativeness
Interpersonal relations:
Large number of successors Distorted family relationships
Source: Authors' own data
Table 2. Classification of Identified Barriers in Succession Process from Successors' Perspective (n = 25)
Internal barriers
External barriers
Fears (encompassing several indications)
Lack of professional training
Lack of experience
Lack of practical experience
Other points of interest
Other plans (including reluctance to run a business) Too young age
Bad relations with parents The number of successors Uncertainty
Unfamiliarity with the trade
Lack of perspectives for development of the firm
Lack of capital
Bureaucracy
Young age of the present owner
firm; X8 = fear of responsibility; X9 = fear of being unsuccessful; X = fear of criticism; X = reluctance to run a business; X12 = lack of capital; X13 = large competition in the market; X = uncertainty; X15 = bureaucracy; X = young age of the present owner; X17 = lack of practical experience; X = other points of interest; and X = unfamiliarity with the trade. The questionnaire also included questions about the completed succession process (X0) and whether the company possessed a business model (X21). The responses to these questions were coded in a 0-1 scale, where 0 meant "no" and 1 meant "yes." Moreover, the respondents were asked how they assessed the strategies implemented in their firm (X ). They answered this question using a five-point Likert scale. The collation of results obtained in the conducted study is presented in Table 3.
The largest barrier, often paralyzing the successor in the succession process, is the fear of responsibility. Both the weighted means and the dispersion of results indicated that
this barrier was the most challenging according to successors. The next two barriers, also related to successors' personality traits, were fear of criticism from parents, seniors, and firm employees and fear of competition, understood as the competition within the family and competition on the market. The obtained data allowed us to elaborate on the visualization of the profile of the successors' largest barriers in the succession process of Polish family firms, as illustrated in Figure 1.
3 Research Methodology Using a Grey Incidence Analysis
Due to the small sample, composed of the representatives of 25 family enterprises, the analysis of the results was conducted using a grey incidence analysis (Liu & Yi, 2006; Mierzwiak & Wi^cek-Janka, 2015). The main objective of
Table 3. Results of Empirical Study
No.	X0	X2	X3	X4	X5	X6	X7	X8	X9	X10	Xn	X12	X13	X14	X15	X16	X17	X18	X19	X20	X21
1	0	5	4	3	3	3	3	4	3	3	3	3	4	4	5	4	4	3	4	3	0
2	0	4	4	4	4	4	5	4	4	4	3	5	4	4	5	4	4	3	4	1	0
3	1	5	5	3	3	3	3	3	3	3	2	4	4	2	1	3	2	2	1	3	1
4	0	4	3	3	3	4	4	5	3	3	5	4	4	4	3	3	4	3	2	2	0
5	0	2	5	4	4	5	4	1	2	5	4	4	3	4	3	4	3	4	5	1	0
6	1	3	2	2	2	2	3	2	2	2	3	3	3	3	3	4	3	1	3	3	1
7	0	4	3	3	3	3	3	3	3	4	3	3	4	4	2	3	4	4	2	3	1
8	0	5	5	3	3	4	4	3	3	3	3	3	4	4	4	3	4	3	2	3	0
9	0	3	3	4	3	4	3	4	4	4	3	4	3	3	4	3	3	4	3	2	0
10	1	2	3	3	3	1	1	3	3	2	2	1	3	3	3	3	4	3	1	3	1
11	1	4	3	2	3	2	1	1	1	1	1	3	3	3	3	3	2	2	3	3	1
12	0	5	4	5	3	3	5	5	5	5	5	3	3	3	5	3	5	5	3	1	0
13	1	4	4	4	1	2	3	4	3	1	1	3	3	2	4	2	3	2	4	3	1
14	0	5	4	5	3	3	3	3	4	3	3	3	5	5	5	4	4	3	3	1	0
15	0	3	3	2	2	5	5	3	3	3	3	4	2	2	4	4	4	4	4	2	1
16	0	3	3	3	3	3	3	3	3	3	4	4	4	3	5	4	4	4	3	2	1
17	0	3	4	5	3	3	4	3	4	5	5	5	4	3	2	3	3	3	3	2	0
18	1	2	3	3	4	3	2	3	3	4	3	3	3	3	3	3	3	1	1	3	1
19	0	5	5	5	5	4	5	5	5	5	5	5	4	4	3	4	4	4	4	1	0
20	0	5	4	4	4	4	4	3	3	3	3	4	4	5	3	4	4	4	3	1	0
21	0	5	4	2	3	3	4	4	3	5	5	5	4	4	3	4	4	4	3	1	0
22	0	4	3	3	3	3	4	4	3	3	3	3	4	3	3	3	4	2	3	2	1
23	1	3	2	2	2	3	4	4	4	3	3	3	2	3	3	2	4	2	1	3	1
24	1	3	3	3	3	3	3	3	4	4	4	4	3	3	3	3	3	3	2	3	1
25	0	4	4	4	4	4	3	3	3	3	3	4	4	3	4	4	4	3	3	1	0
Figure 1. Profile of barriers in succession process from the successor's point of view (n = 25).
Fear of responsibility
Other points of interests Unfamiliarity with the trade
Lack of capital Young age of the present owner
Succesor's too young age
Uncertainty Reluctance to run a business
Number of successors
Fear of being unsuccessful Fear of criticism
Relationships with parents Lack of experiences
Lack of conficence on the part of the family
Lack of education Lack of practice
Lack of perspectives for development of the firm
Others plans	Large competition on the market
Bureaucracy
Results are expressed as the weighted means. Source: Author's own data
employing this method was to discover the relationships between the identified barriers and undergoing the succession process by a firm, possessing the company's own business models and undergoing the succession process by a firm, as well as the assessment of strategy realisation and undergoing the succession process by a firm. (Wi^cek-Janka & Mierzwiak, 2015, p 310).
In order to determine the influence of particular barriers on the succession process, the absolute degree of grey incidence process was applied in order to measure the correlation between the sequences (Liu & Yi, 2006).
Assuming that X0 is a description of the surveyed enterprise system and that the relevant factors are X1-X19, the calculation is as follows (Liu & Yi, 2006):
1. Computing zero starting point images of X0 and X.
X,D = 0сг(1Кх,.(2)</.....Xi{n)d),k = 1,2,...,25
xt (k)d = X, (к) - Xi (1)
(1)
X'0 (0,0,1,0,0,1,0,0,0,1,1,0,1,0,0,0,0,1,0,0,0,0,1,1,0)
X'1 (0,0,2,0,1,0,0,0,0,-1,2,2,1,2,-2,0,0,0,1,1,0,1,0,0,2) X'2 (0,-1,0,-1,-3,-2,-1,0,-2,-3,-1,0,-1,0,-2,-2,-2,-3,0,0,0,-1,-2,-2,-1)
X'3 (0,0,1,-1,1,-2,-1,1,-1,-1,-1,0,0,0,-1,-1,0,-1,1,0,0,-1,-2,-1,0)
X'4 (0,1,0,0,1,-1,0,0,1,0,-1,2,1,2,-1,0,2,0,2,1,-1,0,-1,0,1)
X'5 (0,1,0,0,1,-1,0,0,0,0,0,0,-2,0,-1,0,0,1,2,1,0,0,-1,0,1)
X'6 (0,1,0,1,2,-1,0,1,1,-2,-1,0,-1,0,2,0,0,0,1,1,0,0,0,0,1) X'7 (0,2,0,1,1,0,0,1,0,-2,-2,2,0,0,2,0,1,-1,2,1,1,1,1,0,0) X'8 (0,0,-1,1,-3,-2,-1,-1,0,-1,-3,1,0,-1,-1,-1,-1,-1,1,-1,0,0,0,-1,-1) X'9 (0,1,0,0,-1,-1,0,0,1,0,-2,2,0,1,0,0,1,0,2,0,0,0,1,1,0) X'10 (0,1,0,0,2,-1,1,0,1,-1,-2,2,-2,0,0,0,2,1,2,0,2,0,0,1,0) X'11 (0,0,-1,2,1,0,0,0,0,-1,-2,2,-2,0,0,1,2,0,2,0,2,0,0,1,0)
X'12 (0,2,1,1,1,0,0,0,1,-2,0,0,0,0,1,1,2,0,2,1,2,0,0,1,1)
X'u (0,0,0,0,-1,-1,0,0,-1,-1,-1,-1,-1,1,-2,0,0,-1,0,0,0,0,-2,-1,0) X'14 (0,0,-2,0,0,-1,0,0,-1,-1,-1,-1,-2,1,-2,-1,-1,-1,0,1,0,-1,-1,-1,-1) Х'и (0,0,-4,-2,-2,-2,-3,-1,-1,-2,-2,0,-1,0,-1,0,-3,-2,-2,-2,-2,-2,-2,-2,-1) Х'и (0,0,-1,-1,0,0,-1,-1,-1,-1,-1,-1,-2,0,0,0,-1,-1,0,0,0,-1,-2,-1,0) X'17 (0,0,-2,0,-1,-1,0,0,-1,0,-2,1,-1,0,0,0,-1,-1,0,0,0,0,0,-1,0) X'18 (0,0,-1,0,1,-2,1,0,1,0,-1,2,-1,0,1,1,0,-2,1,1,1,-1,-1,0,0) X'19 (0,0,-3,-2,1,-1,-2,-2,-1,-3,-1,-1,0,-1,0,-1,-1,-3,0,-1,-1,-1,-3,-2,-1)
2. Calculating
WWW»-". 1*41*1 — — 1'*"'— *o|*

k=2 л—1
> £
(2)
(k) - x] (*)] + ± [x° (ft) - x°j (и)]
t=7.	^
[s0| = 8,^1 = U|s2| = 29,5,[$3| = 10,|tf4| = 8,5,|sj| = l,5,|s6| = 5,5,[s7| = 11,
— — 6,|s10|~~ 9, |sjj| = 7,|su| = 14,5,|j13| = 12,|j14| = 15,5, У = 38,5, |s16| = 16,|j17| = 10,|j18| = l,|s19| = 29,5.
Г0 — Г20 —	— 12.
P20 So\ —	— 4-
: Jj
= 37,5, j3 -£0| =18,|Ä4
= 0,5,
\ss J0| 6,5,1Sq| —2,5, |s7 -s^oI	^o|-24,5,
l^g — Sq| = 2,|Ä10 — 5o|= 1,1^11 -^o I = — ^ol = 6,5,
1^13 S0\ 20,|S14 JqI 23,5, |s15 — iSq) — 46,5,	— 24,
1^17 — = 1 1^18 — = — = 37,5.
3. Computing the absolute degree of grey incidence
1 + Ы+ j,
1 + I + \Sj + LS J - S i
(3)
Em =0,87;% =0,507;£„З = 0,514;£04 = 0,972; ej,,, =0,618; ^ = 0,853; £07 =0,87;£os =0,51 £09 =0,882;£010 =0,947;£0>11 = 0,941;£OJ2 = 0,783; ew = 0,512;£ol4 = 0,5 ];eWJ =0,505; ew =0,51 ew =0,514; £|у8 = 0,588;^ =0,507
Based on the absolute degree of grey incidence coefficient, we identified the following arrangement of the influence of the barriers on succession process: X4 (other plans) > X (fear of criticism) > X (reluctance to run a business) > X9 (fear of being unsuccessful) > Xt (lack of professional training) > X7 (lack of perspectives for development of the firm) > X6 (large number of successors) > X (lack of capital) > X5 (successor is too young) > X (other points of interest) > X3 (bad relationships with parents) > X (lack of practical experience) > X13 (large competition on the market)
>	X (uncertainty) > X16 (young age of the present owner)
>	X8 (fear of responsibility) > X2 (lack of experience) > X (unfamiliarity with the trade) > X (bureaucracy).
In order to determine the relationship among the company's business models (X ), the assessment of strategy realization (X ), and the company's succession process, the absolute degree of grey incidence method was employed again, resulting in the following calculations:
1.	Computing zero starting point images of X0, X20, and X21 based on formula (1)
X0 (0,0,1,0,0,1,1,0,0,1,1,0,1,0,1,1,0,1,0,0,0,1,1,1,0)
X20 (0,-2,0,-1,-2,0,0,0,-1,0,0,-2,0,-2,-1,-1,-1,0,-2,-2,-2,-1,0,0,-2)
X21 (0,0,1,0,0,1,0,0,0,1,1,0,1,0,0,0,0,1,0,0,0,0,1,1,0)
2.	Calculating KI'Kol'Kil'Ko _Jo|>|Ä2i _Jo| based on formula (2)
3. Computing the absolute degree of grey incidence based on formula (3)
s0 20 = 0,508; f021 = 0,84 =>
X21 (there is a business model) > X20 (strategic planning)
The absolute degree of grey incidence indicated the relationship between the system's factors (X21, X22) and characteristics (X0). The relationship was assessed using the geometric similarities of its sequences. The higher the value of the absolute degree of grey incidence, where the lowest value of the relative relational degree is 0.5 (Xie & Liu, 2009), the higher the similarity between the system's factors and characteristics is. Therefore, having a company's own business model (X21) is related more to the ongoing succession when compared to the strategy realization (X20).
4 Conclusions
The obtained material allowed the researchers to verify the elaborated provisional model, which has been considerably changed as a result of the conducted analysis. The results of the study indicated a distinct arrangement of the barriers influencing the succession process in the opinion of the successors in Polish family firms. Barrier X4 (other plans) ought to be considered the most significant barrier after the verification of the model, as the value of absolute degree of grey incidence equaled 0.972. The obtained result is close to the result obtained for the succession process. Enterprises in which this barrier received the highest rating have not undergone the succession process thus far.
The next significant barrier was X10 (fear of criticism) with a value of 0.947. Successors assessed this barrier similarly to X4, and the explanation of such behavior of variables can be the thesis that this barrier is primordial to the previously discussed one. It might be shaped in the process of upbringing and socialization, even it successors' early years. Fear of criticism might be built into the individual value system, and the idiosyncratic defense mechanism of a particular personality reacted with transference (Valliant, 2005). Due to such a mechanism, a more objective barrier emerged—namely, the socially accepted other plans. Another barrier might be shaped on the basis of the same mechanism and is related to the declared reluctance to run a business (X11), with an equally high absolute degree of grey incidence amounting to 0.941. Other barriers distinguished and highly correlated to undergoing the succession process belong to the group
of primordial barriers shaped over the years of socialization and formation (or rather their absence) of social and entrepreneurial competencies. They encompass X9 (fear of being unsuccessful) with the result of 0.882, Xt (perceived lack of professional training) with the result of 0.870, and X7 (lack of perspectives for development of the firm) with exactly the same result.
The barriers indicated and verified according to the presented methodology also suggested the capability to assess one's
condition leading to self-complacency. The respondents' assessments of the barriers in the succession process might have been drawn from their so-called pre-understanding, which is created from previous experiences and often shaped in early childhood (Anderson & Goolishian, 1992).
The employed methodology of the absolute degree of grey incidence enabled us to develop a final version of the model of successors' barriers in the course of the succession process in Polish family firms (see Figure 2).
Figure 2. Profile of barriers in succession process from successor's point of view (n = 25)
Unfamiliarity with the trade Lack of experience
Fear of responsibility
Young age of the present owner Uncertainty
Large competition on the market
Practical experience
Relations with parents
Source: Author's own data
own competencies as a successor1 and knowledge of market conditions of family business functioning. The number of successors (X6) with the result amounting to 0.870 has an equally large influence on the positive course of succession. The remaining identified barriers in the succession process did not receive such considerable results from the absolute degree of grey incidence analysis, indicating that their relation to the course of succession process is not as close.
The original view obtained on the classification of barriers in the Polish succession process did not considerably diverge from the psychodynamic approach, which explains that people have a natural tendency to maintain an equilibrium of the mind and actions and make their decisions rationally. Moreover, the human psyche strives to drift away from the imbalanced state, leaving negative and often chaotic scenarios and thoughts, and attempts to reach a more stable
Other plans
Bureaucracy	1	Fear of criticism
Reluctance to run a business
Fear of being unsuccessful
Lack of professional training
Lack of perspectives for development of the firm
Number of successors
Lack of capital
Successor's too young age Other points of interest
The conducted study identified, for the first time in Poland, considerable deficiencies in the research carried out thus far. The obtained profile of statistical successors' barriers corroborated that the barriers to the succession of Polish successors can result from the inappropriate preparation of the younger generation to taking over the business. Hence, one can put forward a hypothesis, to be corroborated in further research, that the upbringing process lacks the ideas for shaping entrepreneurial competencies, which might be helpful in overcoming the fears that the successors have to face when taking over family firms.
As presented in other studies by the research team.
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Authors
Ewa Wi^cek-Janka, Doctor of economics, MA in psychology, engineer of management, works at the Faculty of Engineering Management Poznan University of Technology, Marketing and Economic Engineering Department. She is a member of the Family Business Initiative, Association of Polish Engineers and Mechanics. She is the author of 98 publications, including books on applied management tools. She has participated in conferences abroad (Denmark, Sweden, Slovenia, USA, Italy) and has conducted in internship research and teaching in Finland, Mexico, Bulgaria, Romania, Hungary, Serbia, Slovenia, and Slovakia.
Joanna Kijewska, Ph.D. candidate in the Marketing and Economic Engineering Department at Poznan University of Technology, is completing her Ph.D. thesis on quality management of the integrated marketing communication. Her research interests center on the science of the quality, principles of marketing, and marketing management, especially the environmental scanning and quality of the marketing information system.
Rafat Mierzwiak, Ph.D., focuses on research into applications of grey systems theory in management. In this area, his most important efforts are his publications in scientific magazines, such as Journal of Cleaner Production, Lecture Notes of Computer Science, and Grey Systems: Theory and Application. He received prizes for the best paper at the international conferences in Cracow and Leicester.
Analiza ovir v procesih nasledstva družinskih podjetjih z uporabo sive incidenčne analize (poljska perspektiva)
Izvleček
v prispevku predstavljamo izide raziskave o zaznavanju in ocenjevanju ovir, s katerimi se srečujejo nasledniki v družinskih podjetjih v prvem procesu nasledstva. V empirični analizi smo uporabili sivo sistemsko teorijo, ki smo jo ocenili kot enakovredno za analizo majhnih vzorcev in kvalitativno raziskavo. Pri pregledu literature in v empirični raziskavi smo se osredotočili na: a) identifikacijo ovir pri razvoju družinskih podjetij ter b) opredeljevanje perspektive nove generacije lastnikov v družinskih podjetjih, ki vstopajo v proces nasledstva, z empirično analizo ocenjene ravni tveganja v povezavi z družino in poslom.
Ključne besede: družinsko podjetje, siva incidenčna analiza, siva sistemska teorija
ORIGINAL SCIENTIFIC PAPER
RECEIVED: DECEMBER 2015
REVISED: MARCH 2016
ACCEPTED: MARCH 2016
DOI: 10.1515/ngoe-2016-0011
UDK: 303.725.35
JEL: E43, G12, C52
Citation: Lorenčič, E. (2016). Testing the Performance of Cubic Splines and Nelson-Siegel Model for Estimating the Zero-coupon Yield Curve. Naše gospodarstvo/Our Economy, 62(2), 42-50. DOI: 10.1515/ngoe-2016-0011
Testing the Performance of Cubic Splines and Nelson-Siegel Model for Estimating the Zero-coupon Yield Curve
Eva Lorenčič
Ranca 35, 2211 Pesnica pri Mariboru, Slovenia eva.loren@gmail.com
Abstract
Understanding the relationship between interest rates and term to maturity of securities is a prerequisite for developing financial theory and evaluating whether it holds up in the real world; therefore, such an understanding lies at the heart of monetary and financial economics. Accurately fitting the term structure of interest rates is the backbone of a smoothly functioning financial market, which is why the testing of various models for estimating and predicting the term structure of interest rates is an important topic in finance that has received considerable attention for many decades. In this paper, we empirically contrast the performance of cubic splines and the Nelson-Siegel model by estimating the zero-coupon yields of Austrian government bonds. The main conclusion that can be drawn from the results of the calculations is that the Nelson-Siegel model outperforms cubic splines at the short end of the yield curve (up to 2 years), whereas for medium-term maturities (2 to 10 years) the fitting performance of both models is comparable.
Keywords: Cubic splines; Nelson-Siegel; yield curve; zero-coupon bonds; term structure of interest rates
1 Introduction
NG
NASE GOSPODARSTVO OUR ECONOMY
Vol.
. 62 No. 2 2016
pp
. 42-50
Thn purpose rf this prper is tr construct r zero-coupon yinid curve Irsnd rn thn drtr for coupon yinids, price, rnd maturity rf Austrian government bonds. Thn mrdnis used rre thn Nnisrn-fingni rnd cubic spiines. Forecasting thn term structure rf interest rrtes is r prerequisite for mrnrging investment portfolios, pricing finrnciri rssets rnd their derivrtives, cricuirting risk mersures, vriuing crpitri goods, mrnrging pension funds, frrmuirting economic priicy, mrking hrusehrid finrnce decisions, rnd mrnrging fixed-income werith. Prices rf fixed-income securities such rs swrps, bonds, rnd mrrtgrge-lrcked securities depend rn the yieid curve. The yieids rn defruit-free government bonds thrt hrve different mr-turities, when exrmined together, reveri infrrmrtirn rbrut frrwrrd rrtes, which crn predict reri economic rctivity rnd rre, hence, rf interest for priicymrkers, mrrket prrticiprnts, rnd economists. For instrnce, frrwrrd rrtes rre often inputs tr pricing mrdeis rnd mry indicrte mrrket expectations rf the movement rf inflrtirn rrtes rnd currency rllrecirtien/delrecirtien rrtes in the future. Understrnding the reirtirnship between interest rrtes rnd the term tr mrturity rf securities is r prerequisite for deveirping rnd testing finrnciri theory rnd, therefore, iies rt the herrt
of monetary and financial economics. Accurately fitting the term structure of interest rates is the backbone of a smoothly functioning financial market, which is why refining yield curve modeling and forecasting methods is an important topic in finance that has received considerable attention for many decades (De Rezende & Ferreira, 2013; Diebold, Li, & Yue, 2008; Exterkate, van Dijk, Heij, & Groenen, 2013; Ioannides, 2003; Jordan & Mansi, 2003; Linton, Mammen, Nielsen, & Tanggaard, 2001; Rugengamanzi, 2013).
The yield curve is a graphical representation of the term structure of interest rates (i.e., a one-to-one relationship between yields and corresponding maturities of default-free zero-coupon securities issued by sovereign lenders). The term structure of interest rates contains information about the yields of zero-coupon bonds1 of various maturities at a certain date. Constructing the term structure of interest rates is not a straightforward task due to the scarcity of zero-coupon bonds on the market, which represent the essential part of the term structure of interest rates. The majority of bonds traded in the market bear coupons. The yields to maturity on coupon-bearing bonds, whose maturities or coupons differ, are not immediately comparable. As a result, a uniform way of measuring the term structure of interest rates is needed: The spot interest rates2 (i.e., the yields earned on bonds that pay no coupon) must be estimated from coupon bond prices of bonds with different maturities by using interpolation methods, such as polynomial splines (e.g., cubic splines) and parsimonious functions (e.g., Nelson-Siegel). This is how the yield curve of zero-coupon bonds is constructed (Christensen, Diebold, & Rudebusch, 2011; Christofi, 1998; Gauthier & Simonato, 2012; Luo, Han, & Zhang, 2012; Teichmann & Wüthrich, 2013; Yu & Zivot, 2011).
The most widely used models for estimating the zero-coupon yield curve are Nelson-Siegel and cubic splines. For instance, the central banks of Belgium, Finland, France, Germany, Italy, Norway, Spain, and Switzerland use the Nel-son-Sigel model or some type of its enhanced extension to fit and forecast yield curves (BIS, 2005). The European Central Bank uses the Sonderlind-Svensson model, an extension of the Nelson-Siegel model, to estimate yield curves in the Eurozone (Coroneo, Nyholm & Vidova-Koleva, 2011).
The remainder of the paper is organized as follows. Section 2 gives an overview of the existing literature and relevant research studies. Section 3 presents the data; Section 4 lays out the methodology and the results. Section 5 concludes the paper.
1	Another name for "zero-coupon bond" is discount bond.
2	The terms "yield to maturity on a zero-coupon bond," "zero-cou-
pon interest rate," "spot interest rate" and "zero-coupon yield" are synonyms; they all describe the same aspect of reality.
2 Literature Review
The yield curve estimation methods originated in McCull-och's (1975) cubic splines and in Nelson and Siegel's (1987) parsimonious function. Most of the research studies on the term structure of interest rates build on these two methods and propose improvements and extensions. McCulloch (1975) modeled the discount curve with a spline. The fitted discount curve gives a poor fit of the yield curves, most notably at longer maturities. Nelson-Siegel's parsimonious function allows for various shapes of the yield curve. The forward rates are a solution to a second-order differential equation. The forward rate curve under McCulloch's method is not smooth, whereas the forward rate curve under Nelson-Siegel's method is smooth, but still unable to accurately price instruments at the longest end of the yield curve (Rugengamanzi, 2013).
The Nelson-Siegel type of models are relatively efficient in capturing the general shapes of the yield curve, which is why they are extensively used by central banks and market practitioners. Nevertheless, the Nelson-Siegel type of models are still inferior to the dynamic term structure models, like the quadratic or affine term structure models or the forward rate-based arbitrage-free model introduced by Heath, Jarrow, and Morton (1992). Jordan and Mansi (2003) used five distinct yield curve-smoothing methods to derive spot rates from on-the-run treasuries. All methods used the bootstrapping3 technique either in discrete time or in continuous time. Yield curve-smoothing methods based on continuous-time bootstrapping deliver a superior approximation of the term structure of interest rates to those methods that employ the discrete-time bootstrapping technique. Of the five yield curve-smoothing methods, the linear spline interpolation produces the worst results; the second-worst method is cubic splines; and the two best methods are Mansi-Phillips and Nelson-Siegel.
Diebold and Li (2006) developed a dynamic version of the Nelson-Siegel model. They showed that the three factors present in the Nelson-Siegel model can be interpreted as the level, slope, and curvature of the yield curve. They also corroborated that the dynamic model improves the forecasting accuracy. Diebold, Rudebusch, and Aruoba (2006) combined the Diebold-Li model with macroeconomic variables to analyze the relationship between the yield curve and the economy. Diebold et al. (2008) extended the dynamic Diebold-Li model to a global context. A large set of country yield curves was modeled in a setting that allows for both country-specific and global factors. The researchers found that the global yield level and slope factors exist and can
3 "Bootstrapping" refers to calculating spot rates from bond yields in an iterative manner (Jordan et al., 2003).
explain a substantial proportion of variation in country bond yields. Christensen, Diebold, and Rudebusch (2009) proposed a generalized arbitrage-free Nelson-Siegel model using five factors. Christensen et al. (2011) added the arbitrage-free restriction to the Diebold-Li model, thereby creating an affine arbitrage-free Nelson-Siegel model (AFNS). The results show an improvement in the model's predictive performance. Yu and Zivot (2011) empirically tested Diebold and Li's dynamic Nelson-Siegel three factor model and found that the dynamic Diebold-Li factor AR(1) model is superior to other models on the out-of-sample forecast accuracy. Luo et al. (2012) compared the forecasting ability of the Diebold-Li, dynamic Svennson, and dynamic Björk and Christensen models for the term structure of Chinese treasury yields. The results showed that all three models fit the data very well and that more flexible models produced superior in-sample fitting performance.
Gauthier and Simonato (2012) developed linearized algorithms for estimating spot interest rate term structures. These algorithms converge much faster while retaining the important characteristics of the original approaches. These algorithms are superior in that they enable the inclusion of prior information about some of the parameters, thereby enhancing the precision of the estimated spot rate curves. Using the Brazilian yield curve data, De Rezende and Ferreira (2013) compared the in-sample adjustment and the out-of-sample forecasting performance of four different Nelson-Siegel type models: Nelson-Siegel, Bliss, Svensson, and a new five-factor model that is an extension of the Svensson model and could improve the fitting flexibility. The introduction of the fifth factor into the model produced the best in-sample fitting, but poor out-of-sample forecasting. Exterkate et al. (2013) investigated whether the inclusion of additional macroeconomic information into the Nelson-Siegel model results in improved yield curve forecasts. In general, the forecasts could not be improved in stable times (e.g., 1994-1998): When the yields are not volatile, the dynamic Nelson-Siegel model produces good yield curve forecasts. The inclusion of additional macroeconomic variables can substantially improve the yield curve forecast accuracy when the yields are volatile (e.g., 2008-2009).
3 Data
We empirically tested the fitting performance of the Nelson-Siegel model and cubic splines on the data for Austrian government bonds. The data were retrieved from Bloomberg4 on October 8, 2013(see Table 1). All prices are in euros.
Table 1. Data on Austrian Government Bonds (retrieved from Bloomberg on October 8, 2013).
AT -Benchmark	Maturity	Coupon (%)	Bid (EUR)	Ask (EUR)
1YBUND	20.10.2014	3,40	103,32	103,35
2YBUND	15.07.2015	3,50	105,72	105,77
3YBUND	15.09.2016	4,00	110,14	110,18
4YBUND	15.09.2017	4,30	113,39	113,46
5YBUND	15.01.2018	4,65	115,53	115,58
6YBUND	15.03.2019	4,35	116,25	116,29
7YBUND	15.07.2020	3,90	114,85	114,91
8YBUND	15.09.2021	3,50	112,44	112,50
9YBUND	20.04.2022	3,65	113,35	113,42
10YBUND	20.10.2023	1,75	95,98	96,02
13YBUND	15.03.2026	4,85	125,63	125,81
4 We do not have access to more recent data, as Bloomberg terminal subscription costs around $20,000 per user per annum, which is why the license is mostly bought by and available in major institutions only.
Source: Bloomberg.
The raw data given in Table 1 was used to calculate the accrued interest and the dirty price (i.e., the market value, the present value). The dirty price is a sum of the clean price (i.e., the average of the "bid quote" and the "ask quote") and the accrued interest. The accrued interest is the interest that a bond holder would have obtained in theory between the last coupon date of each bond and the current date (which we assumed to be October 8, 2013—the day the data were extracted).
The Nelson-Siegel model and cubic splines were applied to the data in Table 1 to estimate the zero-coupon bond yield curve.
4 Methodology and Results
The two main categories of methods for estimating a yield curve are the spline methods and the parsimonious methods. The spline methods use a piecewise polynomial function (usually a cubic one) to approximate the yield curve. Cubic splines were first introduced by McCulloch (1975) and subsequently improved by Fisher, Nychka, and Zervos (1995), Waggoner (1997), and Anderson and Sleath (1999). The parsimonious methods (such as Nelson-Siegel model [1987]; Nelson-Siegel-Svensson model [Sevensson, 1995], and models described by Wiseman [1994] and Bjork and Christensen [1997]) approximate the yield curve by estimating the parameters in a single parametric function. With spline methods, it is possible to capture almost any shape of the yield curve, whereas parsimonious methods can capture only yield curves obeying certain financial constraints. Both groups of methods have specific advantages and disadvantages, but none of them seems to be able to consistently
outperform the other (Manousopoulos & Michalopoulos, 2009). In this paper, we employed the most representative type of each method (cubic splines and Nelson-Siegel) with the goal of estimating the zero-coupon yield curve.
4.1 Cubic splines model
The cubic splines method, developed by McCulloch (1971) and McCulloch (1975), divides the zero-coupon yield curve into distinct intervals. In each of these intervals, a cubic spline acts as vertebra in the vertebrate spinal column. If the yield curve is divided into k-1 knots, then we need k parameters to describe the entire zero-coupon yield curve. The optimal parameters are obtained by constructing the matrix A, defined in the continuation of the paper. The optimal parameters and the optimal zero-coupon yield curve minimize the discrepancy (the error) between the model price and the market price of government bonds (McCulloch, 1975; Jankowitsch & Pichler, 2003; Rugengamanzi, 2013).
To fit the observed market data for government bond yield curve, McCulloch (1971) used the discount function presented in (1):
Ö(0 = l+Z;=i W-Oj,
(1)
a. When j = 1:
d. = d,1 = 0
i i-i
b. When j = k: f (t) = t
(6)
(7)
In f. (t), t stands for time and j is a knot number (j = 1, ..., k-1). Because the number of knots is equal to k-1, we need к parameters. The knots are denoted as d.. We used four parameters (k = 4) and three knots (k-1 = 3). We set the first knot equal to zero (dx = 0), the second knot equal to five (d2 = 5), and the third knot equal to 13 (d3 = 13), which corresponds to the maturity of the last bond (McCulloch, 1975; Jankowitsch & Pichler, 2003; Rugengamanzi, 2013).
The zero-coupon yields are calculated from the discount function defined by (1) as follows:

(8)
In order to calculate the parameters a. (which are needed in (1) and (8)), we first need to construct matrix A:
A = (X-XTy1-XT-Y,
(9)
where a are the parameters that need to be estimated. For j < k, f. (t) is a cubic polynomial defined as follows:
I. When t < d
i-1'
f(t) = 0
(2)
II. When d., < t < d :
.-1 .
m =
(t-đj. о3 6 ■ (dj - dj^y
(3)
III. When d < t < d :
i i+1
/#CO = — + — + -
JJK ' fi 2 2
2 2 6-(dj+x~ đ/)'
(4)
where c = d- d , and e = t - d..
. .-1 .
IV. When d < t:
i+1
fj(t) = (dj+1 - dj.J
Two additional conditions have to be met:
2 ■ d]+1 - dj - dj_! ^ t - dj+1
where X is a matrix and Y is a matrix. X1 and Y are the transposed matrices of matrices X and Y. The matrix A has j rows and one column. The element a of matrix A (where j = 1, ..., k) is an optimal parameter a., needed to calculate the discount function, as defined by (1).
The matrix X is given as follows:
xij = YjZi{h)-fj{wi(h))
(10)
h=1
for every i=1,...,n and for every j=1,..,k,
where R. = the number of future cash flows of bond i,
i '
Z. (h) = a future cash flow h of bond i, w. (h) = the time to maturity of a next cash flow h of bond i in years, and
f (t) = a function of time t, defined by equations (.2) to (5).
. (5) The matrix Y is given as follows:
Rt
Vi=Pi - ^ ZiQì) for every i = h.-.n
(11)
ft=i
where P. = the dirty price (the present value, the market value) of bond i.
The estimated zero-coupon yield curve is displayed in Figure 1.
The dirty price (the present value, the market value) P. of bond is defined as follows:
P=clean price from Bloomberg+accrued interest. (12) The accrued interest is defined as follows:
accrued = the next cash flow interest (coupon amount)
time that has passed between the last coupon payment and today
time between two consecutive coupon payments
(13)
Table 2. Estimated Discount Factors (D(t)) and Zero-coupon Yields for t = 1, 2.....10.
t	D(t)	r(t)	r(t) in %
1	1,00056	-0,00056	-0,05606
2	0,99443	0,00279	0,27943
3	0,98238	0,00594	0,59424
4	0,96517	0,00890	0,89031
5	0,94355	0,01169	1,16896
6	0,91830	0,01431	1,43070
7	0,89024	0,01675	1,67481
8	0,86020	0,01900	1,90021
9	0,82901	0,02105	2,10539
10	0,79751	0,02288	2,28837
The final results obtained by empirically testing the cubic splines model (equations (1) to (13)) on data given in Table 1 (Austrian government bonds) are summarized in Table 2.
Figure 1. The zero-coupon yield curve, estimated with the cubic splines model.
4.2 Nelson-Siegel model
Nelson and Siegel (1987) developed a parsimonious function to model forward rates. The zero-coupon yield (the spot rate) can be derived as follows:
r(t) =ß1+ß2
1-е
t_
Ti
■+ß3■
1-е
t_ ч
= ß1 + (ß2+ß3)
1-е Ti T ti
~ß3
t_ Ti
■ e Ti,
ti
(14)
where t = time to maturity of a bond (in years), ß1 = parameter beta 1 (the level factor), ß2 = parameter beta 2 (the slope factor), ß3 = parameter beta 3 (the curvature factor), t1 = parameter tau 1 (the rate of exponential decay), and
e = exponential function.
The parameters ß1, ß2, ß3, and т1 can be calculated with the Excel add-in "Solver" by minimizing the sum of squared residuals between the dirty price (market value, present value) of the bonds and the model price of the bonds. (The dirty price is a sum of the clean price, retrieved from Bloomberg, and accrued interest.) The price of zero-coupon securities for time t is calculated as follows:
-r(t)t
p(t) = e «о .
(15)
The market value (MV) of a bond i according to the Nelson-Siegel model is calculated as follows:
MV Nelson Siegel (bondt) = J^h ziQ0 " Р(.щ00), (16)
2,5 2 1,5 g 1 0,5 0
-0,5
12 345 6 789 10 t
where R. = the number of future cash flows of bond i,
i '
Z. (h) = a future cash flow h of bond i,
w. (h) = the time to maturity of a future cash flow h
of bond i in years, and
P(t) = the present value of a zero-coupon security with nominal value 1 and maturity in time t.
The error of the Nelson-Siegel model for bond i is defined as follows:
The error of the model for bond i = = (dirty price of bond. - MV Nelson Siegel of bond. )2
(17)
X
The final results obtained by empirically testing the cubic splines model (equations (14) to (17)) on data given in Table 1 (Austrian government bonds) are summarized in Table 3.
The estimated zero-coupon yield curve is displayed in Figure 2.
4.3 Comparison of the two models
Our coupon bond price estimation results (Tables 4 and 5) are comparable with the in-sample coupon bond price estimation results of Jordan and Mansi (2003; see Table 2). Jordan and Mansi's (2003) results show that, at the short end of the yield curve (0 to 5 years), the Nelson-Siegel model outperforms cubic splines; the same is true for the intermediate range (5 to 10 years). Our findings are similar to Jordan and Mansi's (2003) findings in that the Nelson-Siegel model performed better than cubic splines at the short end of the yield curve (up to 5 years) and in the intermediate range (5-10 years); however, the supremacy of the Nelson-Siegel model over cubic splines was more pronounced for short-term maturities than for medium-term maturities.
The cubic splines and Nelson-Siegel estimates of zero-coupon yields are summarized and compared in Table 6. The Nelson-Siegel model outperformed cubic splines at the short end of the yield curve (up to 2 years), whereas for medium-term maturities (2 to 10 years), the fitting performance of both models was comparable.
t
Table 4. Comparison of Cubic Splines and Nelson-Siegel Estimates of Bond Prices.
Maturity of the bond	Actual bond price	Cubic splines bond price estimation	Nelson-Siegel bond price estimation	Cubic splines squared price error*	Nelson-Siegel squared price error**
1 year	106.62	106.85	106.68	0.05061	0.00308
2 years	106.56	106.63	106.55	0.00532	0.00006
3 years	110.41	110.24	110.31	0.02882	0.01081
4 years	113.70	113.60	113.69	0.00949	0.00001
5 years	118.94	118.89	118.97	0.00301	0.00082
6 years	118.74	118.76	118.77	0.00058	0.00134
7 years	115.79	115.90	115.84	0.01271	0.00242
8 years	112.69	112.67	112.60	0.00038	0.00797
9 years	115.10	115.26	115.21	0.02767	0.01350
10 years	97.69	97.47	97.52	0.04878	0.02825
13 years	128.47	128.52	128.54	0.00213	0.00422
				Sum: 0.18951	Sum: 0.07246
Notes. *Cubic splines squared price error is equal to the squared difference between the actual bond price and the cubic splines bond price estimation.
**Nelson-Siegel squared price error is equal to the squared difference between the actual bond price and the Nelson-Siegel bond price estimation.
Table 3. Estimated Zero-coupon Yields for t = 1, 2.....10.
t	r(t) in %
1	0.11
2	0.30
3	0.57
4	0.86
5	1.15
6	1.42
7	1.67
8	1.89
9	2.09
10	2.26
Figure 2. The zero-coupon yield curve, estimated with the Nelson-Siegel model.
Table 5. Comparison of Cubic Splines and Nelson-Siegel Squared Price Errors for Short-term and Medium-term Maturities.
	Sum of squared	Sum of squared
Maturity	price errors, cubic	price errors,
	splines	Nelson-Siegel
Up to 5 years	0.0972"	0.01477"
> 5-10 years	0.09012""	0.05348""
Notes. *Sum of squared price errors for maturities from 1 to 5 years. **Sum of squared price errors for maturities from 6 to 10 years.
Table 6. Comparison of Cubic Splines and Nelson-Siegel Estimates of Zero-coupon Yields.
			Absolute
	Cubic splines	Nelson-Siegel	difference
	estimates of	estimates of	between the
	zero-coupon	zero-coupon	two model
	yields in %	yield in %	estimates in
			basis points
1	-0.06	0.11	17
2	0.28	0.30	2
3	0.59	0.57	2
4	0.89	0.86	3
5	1.17	1.15	2
6	1.43	1.42	1
7	1.67	1.67	0
8	1.90	1.89	1
9	2.11	2.09	2
10	2.29	2.26	3
Sum of absolute differences in basis points:			33
The term structure of interest rates, as estimated by the two models, is displayed in Figure 3.
Figure 3. The term structure of interest rates, as estimated with cubic splines (grey line) and Nelson-Siegel (black line).
2,5
2
1,5
g 1 r
0,5 0
-0,5
12 3 4
5 6 t
7 8 9 10
conclusion drawn from the results of the calculations was that the Nelson-Siegel model outperformed cubic splines at the short end of the yield curve (up to 2 years), whereas for medium-term maturities (2 to 10 years) the fitting performance of both models was comparable. In estimating the term structure of interest rates, we employed the simplest versions of the two models without any further extensions. In reality, Nelson-Siegel is one of the most widely used models for deriving the zero-coupon yield curve; however, the central banks and more sophisticated commercial banks use its enhanced versions.
Our study is limited in that we test the fitting performance of the models on the data of government bonds from only one country (Austria). In order to further substantiate our findings, the fitting performance of the models could be tested on a wider set of data, such as government bond data from various countries.
5 Conclusion
In this paper, we empirically contrasted the performance of cubic splines and the Nelson-Siegel model by estimating the zero-coupon yields of Austrian government bonds. The main
As shown in the theoretical part of this paper, the researchers recently derived the dynamic and no-arbitrage improved versions of the Nelson-Siegel model, which are characterized by a greater estimate precision and forecast accuracy. Further research studies are warranted to evaluate and analyze the performance of the more recent versions of the model.
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Author
Eva Lorenčič holds a Master's Degree in Economics, awarded by the University of Maribor, Faculty of Economics and Business, and is currently a trainee at the European Central Bank in Frankfurt. She has authored and co-authored several original scientific papers, review papers, and professional papers. She interned with Erste Group Bank AG (in Vienna), Sberbank Europe AG (in Vienna), and Nova KBM (in Maribor). Her professional interests include corporate finance, banking regulation and supervision, monetary and fiscal policy, macroeconomics and international economics.
Testiranje učinkovitosti modela kubičnih zlepkov in Nelson-Sieglovega modela pri ocenjevanju krivulje donosa brezkuponskih vrednostnih papirjev
Izvleček
Razumevanje razmerja med obrestnimi merami in časom do dospelosti vrednostnih papirjev je osnovni pogoj za razvoj in ovrednotenje pravilnosti finančne teorije. Ta tematika je zato v osrčju monetarne in finančne ekonomije. Natančno prilagajanje terminske strukture obrestnih mer je hrbtenica tekoče delujočega finančnega trga. To je razlog, da je testiranje različnih modelov, ki ocenjujejo in napovedujejo terminsko strukturo obrestnih mer, na področju financ pomembna vsebina, ki je že nekaj desetletij deležna precejšnje pozornosti. V tem članku empirično primerjamo učinkovitost modela kubičnih zlepkov in Nelson-Sieglovega modela, tako da ocenimo donosnost brezkuponskih avstrijskih državnih vrednostnih papirjev. Ključni sklep, ki ga lahko izpostavimo na podlagi dobljenih rezultatov, je, da Nelson-Sieglov model bolje aproksimira brezkuponsko krivuljo donosa na kratkem koncu (do dveh let), na srednjem delu krivulje donosa (od dveh do desetih let) pa med rezultati obeh modelov ni bistvenih razlik.
Ključne besede: kubični zlepki, Nelson-Sieglov model, krivulja donosa, brezkuponske obveznice, terminska struktura obrestnih mer
The Relationship between Spiritual Intelligence and Work Satisfaction among Leaders and Employees
Maja Koražija
PhD Student at the University of Maribor, Faculty of Economics and
Business, Slovenia
maja.korazija@gmail.com
Simona Šarotar Žižek
University of Maribor, Faculty of Economics and Business, Slovenia simona.sarotar-zizek@um.si
Damijan Mumel
University of Maribor, Faculty of Economics and Business, Slovenia damijan.mumel@um.si
Abstract
This study aims to investigate the relationship between spiritual intelligence and work satisfaction among both leaders and employees. Most studies in this area have focused on researching the relationship between employees' spiritual intelligence and work satisfaction, so we also researched the relationship between leaders' spiritual intelligence and work satisfaction. Our leading thesis was that leaders and employees with a higher level of spiritual intelligence have a higher level of work satisfaction. In our study, we found no significant relationship between spiritual intelligence and work satisfaction for leaders, but we found a significant positive relationship between spiritual intelligence and workplace satisfaction for employees.
Keywords: spiritual intelligence, work satisfaction, leaders, employees
1 Introduction
The majority of the developed world is in a post-materialistic period, in which not only people's basic needs but also their needs in the workplace are changing. Because jobs have largely transformed from routine to more creative positions in which the main components are the abilities and competence of the human mind, higher-order needs have emerged. To satisfy these needs, leadership must be based not on profits, but on values (Fry, 2003). Such a leader has not only a high level of cognitive intelligence, but also a high degree of emotional and spiritual intelligence. Cognitive and emotional intelligence constructs are fairly well known; meanwhile, the theory of spiritual intelligence is in the early stages of development. In one of the earliest definitions, Zohar and Marshal (2000) defined spiritual intelligence as what we use to develop our longing and capacity for meaning, vision, and value. It allows us to dream and to strive. It underlies the things we believe in and the role our beliefs and values play in the actions that we take and the way we shape our lives. (p. 3)
ORIGINAL SCIENTIFIC PAPER
RECEIVED: JUNE 2015 REVISED: JANUARY 2016 ACCEPTED: JANUARY 2016
DOI: 10.1515/ngoe-2016-0012 UDK: 005.32:331.101.32 JEL: M54
Citation: Koražija, M., Šarotar Žižek, S., & Mumel, D. (2016). The Relationship between Spiritual Intelligence and Work Satisfaction among Leaders and Employees. Naše gospodarstvo/Our Economy, 62(2), 51-60. DOI: 10.1515/ ngoe-2016-0012
NG
NASE GOSPODARSTVO OUR ECONOMY
Vol.
. 62 No. 2 2016
pp
. 51-60
To create a complete picture of human intelligence, we need to understand all of the various types of intelligence. In his theory of multiple intelligences, Gardner (1999) included nine different types of intelligence (natural, musical, logical, existential, interpersonal, physical, linguistic, emotional, and spatial). Spiritual intelligence is integrated into the model of multiple intelligences as a concept of existential intelligence, which is concerned with the "ultimate issues" of life (Gardner, 1999). Halama and Strizenec (2004) subsequently concluded that the existential and spiritual intelligences are "related and overlapping constructs with some common as well as unrelated aspects" (p. 15).
Working without purpose and meaning leaves people unsatisfied and causes organizations to struggle to create an identity in the market and contribute to the communities they serve (Covey, 1990; Deming, 1981). The results of a study among teachers in master's (MA) and bachelor's (BA) programs conducted by Yahyazadeh-Jeloudar and Lotli-Goodarzi (2012) showed a significant relationship between work satisfaction and spiritual intelligence.
Both leaders and employees are equally important group entities for a successful organization. Several research papers have examined the relationship between employees' spiritual intelligence and work satisfaction (Nodehi & Nehardani, 2013; Sadeghi, Zamani, & Mamasani, 2015; Yahyazadeh-Jeloudar & Lotli-Goodarzi, 2012), but due to a lack of studies among leaders, the main objective of the present study is to investigate the relationship between spiritual intelligence and the work satisfaction of both leaders and employees. The conceptual framework presented in this paper will help provide a modest contribution to the literature on this phenomenon, especially on the empirical fronts.
2 Definitions of Key Concepts 2.1 Spiritual intelligence
It is important to realize how we perceive the environment, how we understand the background and meaning of events, and that we have the ability to imagine new steps and open up new possibilities. "Intelligence is the strongest predictor of our cognitive achievements, as well as our school and academic performance" (Musek & Maravič, 2004, p. 5).
Gardner (1999) first introduced the theory of multiple intelligences, which posits that intelligence is more than a single property of the human mind. He did not include the concept of spiritual intelligence in his theory; instead,
he used the concept of existential intelligence as viable. Emmons (2000) took it a step further in presenting the evidence that spirituality meets the criteria for intelligence. He identified five components of spiritual intelligence: the capacity for transcendence; the ability to enter into heightened spiritual states of consciousness; the ability to invest everyday activities, events, and relationships with a sense of the sacred; the ability to utilize spiritual resources to solve problems in living; and the capacity to engage in virtuous behavior (to show forgiveness, to express gratitude, to be humble, and to display compassion).
With a high level of spiritual intelligence, we can use our spirituality to bring meaning, importance, and general enrichment to our lives. This helps us achieve personal integrity, determine the purpose of our lives, and stay on the right path (Zohar & Marshall, 2000). Because of spiritual intelligence, we are integrated—rationally, emotionally, and spiritually—creatures/individuals (Zohar & Marshall, 2000). Ideally, these three (cognitive, emotional, and spiritual) basic human intelligences work together and support each other, but each can operate independently in a certain area.
Emotional intelligence enables us to assess the situation we are in and how we can properly find ourselves in it. On the other hand, spiritual intelligence allows us to ask ourselves whether we want to be in this particular situation or whether we would prefer to change the situation and create another, more appropriate one. This means changing and moving our limitations, which allows us to self-direct our position. Spiritual intelligence links all of our intelligences by allowing us to recognize what is truly important (Schwartz, 1995; Vaughan, 2002).
Wolman (2001) defined spiritual intelligence as "the human capacity to ask ultimate questions about the meaning of life and to experience simultaneously the seamless connection between each of us and the world in which we live" (p. 83). Wolman (2001) identified seven factors that make up human spiritual experience and behavior: divinity, mindfulness, intellectuality, community, extrasensory perception, childhood spirituality, and trauma. A clear and widely accepted definition suggested by Vaughan (2002) describes spiritual intelligence as "a capacity for a deep understanding of existential questions and insight into multiple levels of consciousness" (p. 19). King (2008) proposed four core components to comprise spiritual intelligence: critical existential thinking, personal meaning production, transcendental awareness, and conscious state expansion. Ronel (2008) continued the idea, asserting that spiritual intelligence is a key capability that connects us to something bigger than ourselves and is reflected not only in the values, but also in the motivation, intentions, emotions,
and personality structure of an individual. He described spiritual intelligence as the ability to understand, emote, evaluate, create, and administrate. He understood spiritual intelligence to be an ability that goes beyond the desires and motives of individuals; it is not present to serve their selfish interests, but to lead them toward spiritual meaning.
Wigglesworth (2012) defined spiritual intelligence as "the ability to behave with wisdom and compassion, while maintaining inner and outer peace, regardless of the situation" (p. 7). She asserted that we can develop the ability to hear the voice of our higher self and our ego and then be guided by deep wisdom and compassion.
2.1.1	Spiritually intelligent leaders
Spiritually intelligent leaders represent more than just a new kind of ideal leadership; they represent a shift in the paradigm of leadership. This shift affects employees and managers as they transform their standards of success. No matter what kind of work we perform, it can always be done with heart and soul (Fairholm, 2000). The new paradigm of spiritual leadership focuses on vision, empowerment, risk, creativity, harmony, trust, honesty, and compassion. The terms that accompany this new paradigm are spiritual leadership (Wolf, 2004), moral conduct (Thompson, 2004), authentic leadership (Beagrie, 2005), and ethical conduct (Marques, 2006).
Leaders need to feel responsible in all situations and be respected by others (i.e., employees). Decision-making must take place through the prism of empathy (Šarotar Žižek,
2008).	Leaders who exhibit grace and values such as joy, beauty, optimism, and confidence are more likely to inspire their employees. Kouzes and Posner (as cited in Amram,
2009)	stressed the importance of self-orientation—which refers to being circumspect, possessing clarifying values, being honest, and living in conjunction with these princi-ples—and setting criteria for employees. These are some of the essential qualities of spiritually intelligent leadership, which every good leader should possess and learn to emphasize.
2.1.2	Spiritually intelligent employees
Spiritually intelligent leaders are not the only ones who are important to the overall organizational structure; equally important are employees. Spiritual intelligence and profitability are not mutually exclusive; in fact, integrating ethics and spiritual values into the workplace can lead to higher productivity and profitability, happier employees, and more honest relationships with customers and can
help build the organization's reputation (Marques, 2006). Spiritually intelligent employees are more consistent with themselves, happier, and more deeply integrated and harmonious (George, 2006).
Despite the fact that spiritually intelligent employees are of great value for organization, George (2006) stressed that no universal prescription exists for how to seek and find spiritual intelligence. Each individual has to find it for him-/herself, and only he/she knows how to obtain it. There is also a universal question of how to find an external power and vitality and give it meaning and significance for all external events. Such challenges are much more present for employees during difficult times, when values are not the priority for their leaders and employees are seen only as tools for gaining profits.
2.1.3 Spiritually intelligent organization
Fry (2003) argued that "organizational environments in the 21st century are chaotic and require rapid response from highly committed, productive, intrinsically motivated learning organizations" (p. 717). In order for organizations to meet the great challenges they face successfully, they have to make a radical shift and transformation to a new business model—a spirituality-based organization.
Spiritual intelligence provides employees a sense of in-terconnectedness and community. Workplaces are places where people spend most of their lives, develop friendships, create value, and make their most meaningful contributions to society (Fairholm, 2000). Furthermore, companies that engage not just the minds, but also the hearts and emotions of their employees will be more profitable. In other words, an organization that earnestly treats its employees and leaders as part of its community and emotionally engages them in the organization's purposes, which makes all the difference in the world and will attract a higher level of leaders and employees' motivation and loyalty, ultimately leading to higher organizational performance (Brown, 1999).
2.2 Work satisfaction
The term "work satisfaction" is used in several different sciences, including (organizational) psychology, sociology, and management. A number of experts believe that the trends of work satisfaction influence the functioning of the labor market and labor productivity, work effort, work absenteeism, and staff resignations (European Foundation for the Improvement of Living and Working Conditions, 2007).
Organizations have a major impact on the people who work in them. One of these effects is reflected in individuals' relationship with (Brayfield & Rothe, 1951) and about their workplace (Spector, 1997, as cited in European Foundation for the Improvement of Living and Working Conditions, 2007). Evans's (1997) definition connects work satisfaction to the needs associated with the workplace and an individual's perception of the degree of satisfaction.
An alternative to the traditional view of work satisfaction was offered by Sousa-Paz and Sousa-Poza (2000) based on the assumption that there are basic and universal human needs. If an individual's needs are met in their current situation, that person can be considered happy. Due to the fact that people spend a major part of their life in the workplace, it is important that they are "happy in the workplace" (Nguyen, Taylor, & Bradley, 2003, p. 133). "More satisfied employees are more efficient and effective at their work. For this reason an organization can be truly effective and successful only if inside of that organization work a majority of satisfied individuals" (Regent, 2013).
spiritual intelligence and work satisfaction, but found no significance.
Given the contradictory results we found in the investigation of the relationship between employees' spiritual intelligence and work satisfaction, and because it makes sense to investigate the same relationship in leaders, we decided to conduct a study to answer the following research question: Is the spiritual intelligence of leaders and employees positively correlated with their level of work satisfaction? Based on the reviewed literature and our research question, we designed the thesis of this research: Leaders and employees with a higher level of spiritual intelligence also have a higher level of work satisfaction. Thus, we formulated the following two hypotheses:
H1: Leaders with a higher level of spiritual intelligence have a higher level of work satisfaction.
H2: Employees with a higher level of spiritual intelligence have a higher level of work satisfaction.
3 Research Question and Hypothesis Development
Personal characteristics that can be developed through a higher level of spiritual intelligence and those needed for higher work satisfaction are very similar and, at some point, even overlap (Tischler, Biberman, & McKeage, 2002; Zembylas & Papanastasious, 2004). It is important to realize that a person who is happy in the workplace will consequently experience the world outside the work environment as less stressful. Generally speaking, such a person has a greater sense of well-being (Marques, 2006). Spiritual intelligence can be considered a method for improving the well-being of management executives as well as organizational well-being (Subramaniam & Panchanatham, 2014).
People with a higher level of spirituality are happier and more satisfied with life than people with a lower level of spirituality (Cohen, 2002; Perrone, Webb, Wright, Jackson, & Ksiazak, 2006). Spirituality can have a tremendous impact on an individual's life, such as by creating a better balance of work, family, and life satisfaction (Perrone et al., 2006).
Some studies have demonstrated a significant positive relationship between employees' spiritual intelligence and work satisfaction (Nodehi & Nehardani, 2013; Sadeghi et al., 2015; Yahyazadeh-Jeloudar & Lotli-Goodarzi, 2012). In contrast, Rastgar, Davoudi, Oraji, and Abbasian (2012) investigated the relationship between employees'
4 Method 4.1. Instruments
To measure spiritual intelligence we used the Integrated Spiritual Intelligence Scale (ISIS) (Amram & Dryer, 2007). The reliability of the ISIS was high (i.e., Cronbach's alpha = 0.97). This self-reporting instrument provides an overall measure of spiritual intelligence as well as scores for five dimensions of spiritual intelligence: consciousness, grace, meaning, transcendence, and truth (Amram & Dryer, 2007). The instrument comprises 45 items and uses a 5-point sum-mative response scale. Positively worded items are scored from 1 to 5 while negatively worded items are scored conversely. Overall scores for an individual can range from a minimum of 45 to a maximum of 225. A low score indicates a lower level of spiritual intelligence whereas a high score indicates a higher level of spiritual intelligence. Overall, spiritual intelligence measured based on the sum of the ISIS dimensions scores was previously used by Shabani, Hassan, Ahmad, and Baba (2010) and Yahyazadeh-Jeloudar and Lot-fi-Goodarzi (2012).
To measure the work satisfaction, we used the Job Descriptive Index (JDI) (Smith, Kendall, & Hulin, 1969), which is one of the most widely used measures of work satisfaction (Landy, Shankster, & Kohler, 1994). We used a version that was already translated into the Slovenian language and validated in Slovenia (Sabadin, 1978). There are five dimensions of JDI: work, coworkers, supervision, pay, and promotion
(Smith et al., 1969). The version we used is composed of 106 items and uses a 3-point summative response scale. Positively worded items are scored with 3, 1, and 0 points whereas negatively worded items are scored conversely. Overall, scores for an individual can range from a minimum of 0 to a maximum of 318; a low score indicates a lower level of work satisfaction whereas a high score indicates a higher level of work satisfaction. Overall, work satisfaction measured using the sum of the JDI dimensions scores was previously used by Crossman and Abou-Zaki (2003) and Shaikh, Bhutto and Maitlo (2012).
When analyzing the reliability of the instruments used in our study, we calculated Cronbach's alpha coefficients. The Cronbach's alpha for ISIS was 0.810 and for JDI was 0.946, which indicates a high level of reliability according to George and Mallery (2003).
4.2 Data collection procedure and sample profile
5 Results
5.1 Spiritual intelligence and work satisfaction of leaders and employees
The means (M) and standard deviations (SD) of leaders' and employees' work satisfaction and spiritual intelligence are presented in Table 2.
We tested normality using the Shapiro-Wilk test. Given that W = 0.957 and p = 0.167 for the leaders' spiritual intelligence, W = 0.976 and p = 0.160 for employees' spiritual intelligence, W = 0.971 and p = 0.424 for leaders' work satisfaction, and W = 0.974 and p = 0.130 for employees' work satisfaction (p > 0.05), we concluded that both variables for both independent samples were normally distributed. Therefore, the assumption of normality was met. In addition, our data satisfied the assumption of homoscedasticity of variances via Levene's F test: F (110) = 2, p = 0, 160.
Data were collected in one of the largest metal manufacturing companies in Slovenia, which employs 1,150 people. Surveys were sent to a random sample of 100 leaders and 100 employees (a total of 200 questionnaires). We used a drop-off/pick-up method with printed copies of the questionnaire. The response rates were 37% (37 respondents) for leaders and 75% (75 respondents) for employees, resulting in a total of 112 respondents. The overall response rate was 56%. Table 1 summarizes the sample profile.
An independent-samples t-test was conducted to compare the differences between the means of leaders' and employees' spiritual intelligence and between the means of leaders' and employees' work satisfaction. Leaders (M = 154.5, SD = 12.04) showed significantly higher scores than employees (M = 147.0, SD = 14.56) on the spiritual intelligence scale (p < 0.05), but no significant difference existed between leaders (M = 184.5, SD = 49.65) and employees (M = 168.5, SD = 47.40) in terms of work satisfaction (Table 2).
Table 1. Sample Profile
Frequency		Leaders		Employees		Total	
		Proportion	Frequency	Proportion	Frequency	Proportion	
Gender	Female	16	0.43	33	0.44	49	0.44
	Male	21	0.57	42	0.56	63	0.56
	Below 30	3	0.8	18	0.24	21	0.19
Age	31-40	18	0.49	23	0.31	41	0.37
	41-50	12	0.32	23	0.31	35	0.30
	Above 50	4	0.11	11	0.14	15	0.14
	Short-cycle tertiary education	5	0.14	42	0.56	47	0.42
Education	Bachelor or equivalent	9	0.24	11	0.15	20	0.18
	Master or equivalent	17	0.46	21	0.28	38	0.34
	Doctorate or equivalent	6	0.16	1	0.10	7	0.60
	Below 10	6	0.16	24	0.32	30	0.27
Years of work	11-20	18	0.49	26	0.35	44	0.39
experience	21-30	10	0.27	16	0.21	26	0.23
	Above 30	3	0.8	9	0.12	12	0.11
Table 2. Means, Standard Deviations, and t-tests of Variables Used in the Study for Leaders and Employees
		Leaders			Employees			Total			t-test	
ScaLe	N	M	SD	N	M	SD	N	M	SD	t	df	P
Overall spirituaL intelligence	37	154.5	12.04	75	147.0	14.56	112	149.5	14.17	2.69	110	.008
Overall work satisfaction	37	184.5	49.65	75	168.5	47.40	112	173.8	48.53	2.87	110	.101
5.2 Hypothesis testing
Hypothesis H1 predicts that leaders with a higher level of spiritual intelligence will have a higher level of work satisfaction. A Pearson's correlation was applied to determine the relationship between two variables. No statistically significant correlation existed between spiritual intelligence and work satisfaction for leaders (p > 0.05; see Table 3). Therefore, leaders' spiritual intelligence and work satisfaction were not found to be significantly correlated, and hypothesis H1 was not accepted.
Table 3. Correlation between Spiritual Intelligence and Work Satisfaction of Leaders and Employees
Sig. (2-tailed)	0.596	0.012
N	37	75
Hypothesis H2 predicts that employees with a higher level of spiritual intelligence will have a higher level of work satisfaction, so we examined the relationship between spiritual intelligence and work satisfaction among employees. The correlation between employees' work satisfaction and spiritual intelligence showed that they are significantly positively correlated (p < 0.05), so hypothesis H2 was accepted.
between leaders' spiritual intelligence and work satisfaction. For this reason, we expanded the scope of our research to explore the relationship between leaders' spiritual intelligence and work satisfaction.
6.1 Conclusions
The results of our research showed a significant positive relationship between employees' spiritual intelligence and work satisfaction, which is inconsistent with some of the previous literature that found employees' spiritual intelligence and work satisfaction are not significantly correlated (Rastgar et al., 2012). The differences between Rastgar et al.'s (2012) findings and our findings can be explained by the different methodological approaches applied. Rastgar et al. used other measurement instruments and statistical methods. To measure spiritual intelligence, they used the Psycho Matrix Spirituality Inventory, whereas we used ISIS. To measure work satisfaction, they used the Index of Work Satisfaction whereas we used JDI. They tested their hypothesis using structural equation modeling (SEM); we used with Pearson's correlation coefficient. However, our results are consistent with the findings of Yahyazadeh-Jeloudar and Lotli-Goodarzi (2012), Nodehi and Nehardani (2013), and Sadeghi et al. (2015), who also found a significant relationship between employees' spiritual intelligence and work satisfaction.
Leaders	Employees
Pearson Correlation	0.090	0.289
6 Discussion and Implications
Few studies have been conducted on spirituality as spiritual intelligence has only been recently recognized. Spiritual intelligence is currently expanding as a researched phenomenon, although research is still in its early stages. In Slovenia, only a few studies by Musek (2008) and Šarotar Žižek (2008, 2012) have explored the field of spiritual intelligence.
Most researchers initially focused only on the exploration of the separate constructs: leaders' spiritual intelligence and employees' work satisfaction. They subsequently investigated the relationship, but only of employees' spiritual intelligence and work satisfaction. They missed the relationship
For leaders, we found no significant relationship between spiritual intelligence and work satisfaction. We could not compare this result with other studies as we found no previous relevant research. Comparing the spiritual intelligence of leaders and employees, we found that the level of leaders' self-reported spiritual intelligence is significantly higher than that of employees. Although leaders' self-reported level of work satisfaction was higher than that of employees, no significant difference emerged.
6.2 Managerial implications
Zohar and Marshall (2004) argued that spiritual intelligence should be grown and developed with training. This
is consistent with Wigglesworth's (2012) study, which found that mature leadership requires spiritual intelligence development. The development of employees' spiritual intelligence level will enhance their abilities and increase their level of work satisfaction.
The findings of our study suggest that human resource managers should formulate strategies for developing and increasing employees' spiritual intelligence, because we found a significant positive relationship between employees' spiritual intelligence and work satisfaction. These strategies could help increase employees' work satisfaction, which can result in higher productivity, organizational commitment, and organizational efficiency as well as loyalty, presentism, and less absenteeism and fluctuation. Therefore, the concepts of spiritual intelligence and work satisfaction need to be understood in greater detail by human resource managers and leaders.
Human resource managers should assess the spiritual intelligence of their job applicants in order to recruit the best candidates. They should do the same throughout employees' careers so they can adjust training and education to their spiritual needs. The development of spiritual intelligence could be a valuable part of an organization's development strategy as a way to create similar objectives and goals among employees in relation to the objectives and goals of the entire organization.
7 Limitations and Further Research
Our research has some limitations. We gathered information in only one organization, so we cannot generalize the results
of our research to other organizations. Our study only represents the situation in that particular organization. In addition, self-reporting can vary in terms of reliability and validity, although it is generally considered a useful technique to measure work satisfaction and spiritual intelligence. Future research should use multiple assessments of leaders' and employees' spiritual intelligence. In addition to self-assessments, leaders can assess employees' spiritual intelligence and vice versa.
The spiritual intelligence construct is far from achieving consensus across the scientific community. New definitions and findings on spiritual intelligence (Mahajan, 2015) have appeared in different segments and in general, which opens new dimensions for understanding spiritual intelligence.
We only used an overall measure of work satisfaction for the purposes of this article. In terms of practice, by measuring all five dimensions of work satisfaction, organizations and their managers can obtain a complete view of employees' specific work satisfaction with work itself, pay, opportunity for promotion, supervision, and coworkers.
We found a significant relationship between employees' spiritual intelligence and workplace, but not with leaders. Future studies are needed to extend these findings using more diverse predictors and criteria.
Spiritual intelligence is a good predictor of general well-being (Musek, 2008), subjective well-being (Šarotar Žižek, Treven, & Mulej, 2011), and health (Perrone et al. 2006; Sousa-Poza & Sousa-Poza, 2000). Because all these studies were conducted separately for each pair of constructs, it could be beneficial if more concepts were analyzed in one comprehensive study.
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Authors
Maja Koražija is currently a Ph.D. student at the Faculty of Economics and Business at the University of Maribor. She earned her master's degree in human resource management, in which her main focus of study and research also lies. She actively participated in an international conference in India and presented her doctoral theme at Cambridge University. During most of her academic years, she has worked in the economic sector for Elektro Maribor and Steklarna Rogaška, where she worked on European funding projects.
Dr. Simona Šarotar Žižek is an assistant professor at the University of Maribor's Faculty of Economic and Business. She is the author and/or co-author of several articles published in various international and Slovenian journals and/or presented at scientific and expert conferences. She has prepared several scientific monographs and chapters in scientific and expert monographs. On several occasions she has been invited to present her papers at scientific and expert conferences. She is also active in preparing and implementing projects.
Dr. Damijan Mumel works as a professor of marketing at the University of Maribor, Faculty of Economics and Business. He is the head of the Marketing Institute and vice dean for research. His main areas of interest and lecturing are consumer behavior, research methodology, qualitative research, and communication. He has presented his work at international scientific conferences and published original scientific papers in domestic and foreign scientific journals. He is a member of the Slovenian Marketing Association and the Slovenian Psychologists' Association as well as the European Marketing Academy (EMAC).
Povezanost med duhovno inteligentnostjo in delovnim zadovoljstvom pri vodjih in zaposlenih
Izvleček
Namen študije je raziskati odnos med duhovno inteligentnostjo in delovnim zadovoljstvom tako pri vodjih kot tudi pri zaposlenih. Raziskave v preteklosti so se osredotočale le na raziskovanje povezanosti med duhovno inteligentnostjo in delovnim zadovoljstvom pri zaposlenih, zato smo v našo raziskavo vključili tudi ugotavljanje povezanosti med duhovno inteligentnostjo in delovnim zadovoljstvom pri vodjih. Naša vodilna teza je bila, da vodje in zaposleni z višjo stopnjo duhovne inteligentnosti občutijo tudi več delovnega zadovoljstva. V študiji smo ugotovili, da pri vodjih ni bilo statistično pomembne povezave med duhovno inteligentnostjo in delovnim zadovoljstvom, hkrati pa je bila ugotovljena statistično pomembna pozitivna povezava med duhovno inteligentnostjo in delovnim zadovoljstvom pri zaposlenih.
Ključne besede: duhovna inteligentnost, delovno zadovoljstvo, vodje, zaposleni
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Primer 1a: Another graphic way of determining the stationari-ty of time series is correlogram of autocorrelation function (Gujarati, 1995).
Primer 1b: Another graphic way of determining the stationari-ty of time series is correlogram of autocorrelation function (Gujarati, 1995, p. 36). Primer 2a: Engle and Granger (1987) present critical values also for other cointegration tests.
Primer 2b: Engle and Granger (1987, p. 89) present critical
values also for other cointegration tests. Navedbe virov v seznamu virov
Primer 1 - Knjiga: Gujarati, D. N. (1995). Basic Econometrics. New York: McGraw-Hill.
Primer 2 - Članek v reviji: Engle, R. F., & Granger, C. W. J. (1987). Co-integration and Error Correction: Representation, Estimation and Testing. Econometrica, 55(2), 251-276.
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Primer 4 - Elektronski vir: Esteves, J., Pastor, J. A., & Casanovas, J. (2002). Using the Partial Least Square (PLS): Method to Establish Critical Success Factors Interdependence in ERP Implementation Projects. Retrieved from http://erp. ittoolbox.com/doc.asp?i=2321
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References in the text
Example 1a: Another graphic way of determining the station-arity of time series is correlogram of autocorrelation function (Gujarati, 1995). Example 1b: Another graphic way of determining the station-arity of time series is correlogram of autocorrelation function (Gujarati, 1995, p. 36). Example 2a: Engle and Granger (1987) present critical values
also for other cointegration tests. Example 2b: Engle and Granger (1987, p. 89) present critical
values also for other cointegration tests. References in the list of references
Example 1 - Book: Gujarati, D. N. (1995). Basic Econometrics. New York: McGraw-Hill.
Example 2 - Journal article: Engle, R. F., & Granger, C. W. J. (1987). Co-integration and Error Correction: Representation, Estimation and Testing. Econometrica, 55(2), 251-276. Example 3 - Book chapter or article from conference proceedings: MacKinnon, J. (1991). Critical Values for Cointegration Tests. In R. F. Engle & C.W. J. Granger, (Eds.), Long-Run Economic Relationships: Readings in Cointegration (pp. 191-215). Oxford: University Press. Example 4 - Web source: Esteves, J., Pastor, J. A., & Casanovas, J. (2002). Using the Partial Least Square (PLS): Method to Establish Critical Success Factors Interdependence in ERP Implementation Projects. Retrieved from http://erp.ittoolbox.com/ doc.asp?i=2321
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