25 ECONOMIC AND BUSINESS REVIEW | VOL. 17 | No. 1 | 2015 | 25-67 INTANGIBLE CAPITAL, INNOVATION AND EXPORT-LED GROWTH: EMPIRICAL COMPARATIVE STUDY OF SLOVENIA AND THE WESTERN BALKANS MARIJA DRENKOVSKA 1 Received: 30 April 2014 TJAŠA REDEK 2 Accepted: 19 May 2015 ABSTRACT: In the face of progressing globalisation and liberalisation of the markets, in- novation is the minimum necessary requirement for companies and countries to be glob- ally competitive, and knowledge is the key input. In a comparative study we investi- gate the intellectual capital of a sample of firms from the Western Balkans and Slovenia, and analyse the link between intellectual capital, innovation, and export volume. Us- ing unique survey data sets for these countries, we propose a structural model to examine our hypotheses. The results suggest that possessing intellectual capital does not suffice for firms’ global competitiveness and that higher presence on global markets may offer ex- posure to more advanced knowledge that firms cannot obtain in their domestic markets. Keywords: intangible capital, innovation, export-led growth, Slovenia, Western Balkans JEL Classification: O32, M21 1. INTRODUCTION There is a consensus among both, scholars and policymakers on the growing role played by intangible assets on firms’ productivity and, consequently, on the performance of local economies. And while this is true in the industrialised countries where competition is predominately based on ideas and innovations, technologically less developed countries need to strategically nurture their intangibles and learning capabilities in order to be able to benefit from the existing knowledge and spur innovation. From a firm’s perspective, the intangibles are crucial for transitioning to and competing in the today’s knowledge-based economy. The reason that they are so valuable in building and sustaining the firm’s competitive advantage resides in their characteristics – they are valuable, rare, and extremely difficult to imitate and substitute for (such are, for example organizational history, culture, learning, and other human dimensions of organizations). There are multiple sources of knowledge creation within companies and their examina- tion has shown that the knowledge base on which innovating firms found their activities has become broader and more complex (Canibano, Garcia-Ayuso & Sanchez, 2001). The 1 University of Ljubljana, Faculty of Economics, Ljubljana, Slovenia, e-mail: marija.drenkovska@ef.uni-lj.si. 2 University of Ljubljana, Faculty of Economics, Ljubljana, Slovenia, e-mail: tjasa.redek@ef.uni-lj.si. ECONOMIC AND BUSINESS REVIEW | VOL. 17 | No. 1 | 2015 26 conversion and utilisation of this knowledge is closely related to the different aspects of firms’ intangible capital (human capital, structural capital, relational capital) and the in- vestment in them. In this study we model the impact of the firm’s intangible capital (IC) on its innovative culture, which in turn is related to the export activity. Based on the dominant stream in the literature, we adopt the following three basic components of intangible capital: (1) hu- man capital, which includes learning, know-how, and skills; (2) structural capital, which contains organizational (and at times, also technological) elements that pursue integration and coordination within the firm, and (3) relational capital, which gathers the value of the relationships that the firm maintains with external agents (business activity close by or with other more distant social agents) (de Castro & López Sáez, 2008, p. 26). Drawing from the overarching literature on innovation, intangible capital, and trade liter- ature, we examine the existing knowledge in firms (captured by the state of the intangible capital), the potential it has in driving their innovativeness (how human capital, structural capital, and relational capital relate to innovation) and, consequently, how innovation re- lates to firms’ competitiveness on foreign markets (reflected in their export volume). We propose that the more the firm’s intellectual assets are interconnected, the more its man- agement values radical innovation, which then builds the firm’s success in the export mar- kets. On a basis of a larger survey on intangible capital conducted in Albania, Republika Srpska of Bosnia and Herzegovina, and Slovenia, we test these hypothesised relationships by using structural equation modeling. The study analyses the role of intangible capital in the manufacturing companies from a region that ranks relatively low in technological de- velopment, low in intangible investments and, with limited openness to foreign markets, and compares it to the state of the manufacturing sector from an economy that has already built a significant presence on the international market. The paper is structured as follows. Section 2 offers a general overview of the economic and innovation development of the Western Balkan economies and of Slovenia. In section 3 we discuss the conceptual framework for our hypotheses, review the definitions and examples of the different aspects of the corporate intangible capital, and innovation as their function, and finally discuss the evidence in the trade literature about the relation- ship between innovation and exports. Section 4 discusses the methodological framework, and section 5 presents the results from the empirical analysis. The study concludes with a discussion in section 6. The contribution of this paper is severalfold. First, this study represents the first empiri- cal study of the linkage between intellectual capital, innovation, and exports at a corpo- rate level in the Western Balkan economies. Expanding it to a comparative study with a more developed economy that has already completed its transition from a shared history it offers additional insights in the discussion on bridging the development gap through export-led growth strategy. The present study uses original firm-level survey data and proposes firm-level measures for human, structural, and relational capital, and reveals which indicators of firm’s knowledge-based assets are significant in the studied countries. Finally, the stylised findings of this study suggest that possessing intellectual capital does M. DRENKOVSKA, T. REDEK | INTANGIBLE CAPITAL, INNOVATION AND EXPORT-LED GROWTH.... 27 not suffice for firms’ foreign market competitiveness, which is an insight that may inform future policy decisions. 2. OVERVIEW OF THE ECONOMIC AND INNOVATION DEVELOPMENT IN THE WESTERN BALKANS AND SLOVENIA The present study examines the cases of two emerging economies from the Western Bal- kans (Albania and Republika Srpska of Bosnia and Herzegovina) on one hand, and Slove- nia, on the other, which is a more developed country from the Balkan region and an EU member from 2004 3 (see table 1) . Table 1: Selected macroeconomic indicators Albania Bosnia and Herzegovina Slovenia Economy & Growth Indicators GDP per capita (current US$) 4,256.0 4,409.6 22,488.4 GDP growth (annual %) 1.6 -1.2 -2.6 Exports of goods and services (% of GDP) 33.3 30.9 73.2 Innovation and S&T Indicators High-technology exports (% of manufactured exports) 0 2 6 Research and development expenditure (% of GDP) n/a n/a 2.80 Financial Sector Indicators Domestic credit to private sector (% of GDP) 39.0 63.0 85.7 Foreign direct investment, net inflows (BoP , current US$) 920,080,650 334,821,080 -227,373,077 Source: World Bank, 2012 All three countries are small, open economies that pursue the export led model of growth (IMF, 2012a; 2012b; 2012c). Slovenia has been successfully following the export-led strat- egy for growth throughout the entire transition period. It is a very open economy (ex- porting two thirds of its GDP) with a highly export-oriented manufacturing sector that places roughly 85% of its products abroad (Damijan & Kostevc, 2006). On the other hand, Bosnia and Herzegovina and Albania have embarked on a growth model that emphasizes exports only recently, predominately as a response of the global financial crisis of 2008 (World Bank, 2013a, 2013b). The export intensity of Albania is at a similar level as that of 3 Slovenia and Albania are independent countries, while Republika Srpska of Bosnia and Herzegovina is part of the federation with Bosnia and Herzegovina. Given the lack of representative data for the entire country, we focus on the market of Republika Srpska of Bosnia and Herzegovina (Republika Srpska in continuing) for which a representative sample was obtained in a company level survey conducted in 2011. ECONOMIC AND BUSINESS REVIEW | VOL. 17 | No. 1 | 2015 28 Bosnia and Herzegovina (31% of GDP). Since 2003 the Albanian economy has witnessed an increase in the share of export in its GDP by 10 percentage points, while the export ori- entation of Bosnia and Herzegovina has remained almost unchanged (a rise of only 1 per- centage point since 2003) (W orld Bank Database, 2014). According to IMF (2012a, 2012b) boosting the exports remains one of the main development challenges for Bosnia and Herzegovina as well as for Albania. IMF (2012a) warns that especially the export sector in Albania is relatively undiversified (comprised primarily of traditional industries, like textiles, with some reorientation to oil and minerals in the past period). Both countries have experienced a decline in the already limited exports due to the financial crisis, while the sharp increases in imports, particularly capital goods, have led to large and growing trade deficits (World Bank, 2013a; 2013b). According to Schwab (2012), both Albania’s and Bosnia and Herzegovina’s economies are currently at the stage of efficiency-driven development. On the other hand, Slovenia at present is an economy that has already transitioned to the third stage, the stage of innova- tion-driven development. The innovation performance of the W estern Balkans economies is overall low, by international standards. According to the Global Innovation Index 4 Rank of 2012, Bosnia and Herzegovina is 72 out of 125 countries, and Albania’s is 90, which is well below the average of other countries of the Western Balkan region (60). Slovenia, for comparison, has an innovation rank of 49.9, which is still above the Europe’ s average rank- ing of 47.9 (INSEAD, WIPO, 2012). The major problems facing the current innovation systems in the Western Balkan econo- mies are the weak R&D capabilities in both, public and private sector, and the marginal government funding, (Silajdzic (2012) and Bartlett et al. (2012)). This context is empha- sized by the lack of effective policy measures for innovation or cohesion between indus- trial and innovation policy. Nonetheless, improving innovation is to large extent in the hands of the companies and the way to achieve it is closely related to strengthening their intangible capital and the utilisation of knowledge. The present study offers an insight in the current state of these aspects and examine and the potential of an export-led model of growth by relating the estimates with the exporting activity of the manufacturing sectors. 3. CONCEPTUAL FRAMEWORK AND HYPOTHESES The present work proposes a model that relates the existing intangible capital in the com- panies (the human capital, structural capital, and relational capital and the dynamism among them), and their relation to innovation, and, consequently, the export volume. In- tegrating the literature on intellectual capital, we propose that the intangible capital com- 4 The Global Innovation Index (GII) score is calculated as the simple average of the Input Sub-index (an aver- age of elements of the included national economies that enable innovative activities, such as institutions, hu- man capital and research, infrastructure, market sophistication, and business sophistication) and the Output Sub-Index (an average of innovation output measures including knowledge and technology outputs, and creative outputs). For more detailed clarification of the calculation of the GII and its objectives, refer to IN- SEAD, WIPO (2012). M. DRENKOVSKA, T. REDEK | INTANGIBLE CAPITAL, INNOVATION AND EXPORT-LED GROWTH.... 29 ponents and their interrelatedness affect innovation positively (Lev, 2003; Chen, Zhu & Xie, 2004; González-Loureiro & Pita-Castelo, 2012). Following evidence in trade theory, and the international marketing literature that more innovative companies are more likely to be more export oriented (Wagner, 1996; Wakelin, 1997; Weifens et al., 2000; Griffith et al., 2006), we further propose that the link between innovation and the export volume is positive. In other words, the present study examines, in a comparative approach, how in- tangible elements in the studied economies are related to their innovation orientation and how that is reflected in the share of output that they export. In continuation we discuss the model and set the hypotheses. The hypothesised model is illustrated in figure 1. Figure 1: Proposed conceptual model 3.1. Definition of intangibles and their interconnectedness As there are different definitions for intangible capital, the literature provides different nomenclatures for its constituent elements as well. The variety of disciplines that are in- terested in studying intangibles (such as economics, organisation, strategy, management, finance, and accounting) as well as different participants (including academics, standard setters, professional bodies, government agencies, and consultants) has used a plethora of measurements and classification of intangible capital. But the most widely used classifica- tion (Roos, Pike & Fernström, 2005; Wall, Kirk & Martin, 2004; Sullivan, 1999; Tayles, Pike & Sofian, 2007; Marr, 2008), which we also employ in this study, is into these follow- ing three components: human capital (HC), structural capital (SC), and relational capital (RC). At a basic level, the conceptual separation of these three aspects of intellectual capi- tal is evident from how each aspect accumulates and distributes knowledge differently: either through (1) individuals, (2) organizational structures, processes, and systems, or (3) relationships and market knowledge. In continuation we discuss these aspects separately. Human capital represents the individual tacit knowledge embedded in the mind of the employees. It has been identified as a foundational source of innovation, strategic renew- ECONOMIC AND BUSINESS REVIEW | VOL. 17 | No. 1 | 2015 30 al of a company, which can be used to realize and create value in the knowledge-based economy. According to the resource-based school of thought, human capital is recognised as an important source of competitive advantage and a firm’s ability to adapt in volatile environments (Barney, 1991; Judge, Naoumova & Douglas, 2009). We follow the definition used by Chen et al. (2004) who define human capital as a com- bination of employee’s competence, attitude, and creativity. Examples of human capital elements are knowledge, expertise, skills, experience, competence, creativity, teamwork capacity, training and education, problem-solving capability, attitude, loyalty, and the motivation of people (Cohen & Kaimenakis, 2007; Hormiga, Batista-Canino & Sanchez- Medina, 2011; Hsu & Fang, 2009; Jacobsen, Hofman-Bang & Nordby, 2005; Johanson, 2005). The knowledge and know-how, which are created by and stored in its people, are central to creating the organizational capability to achieve the firm’s strategic goals. Hu- man resources and human resource management activities are strategically important be- cause they are potentially valuable, rare, and difficult to imitate and substitute for. This, as Buller & McEvoy (2012) put forward, is particularly important when firms face com- petition based on possessing, communicating, and creating superior knowledge, human capital, and social capital versus having superior land, capital, or technology. Intangible capital scholars have used different definitions and measures for the structural capital. Many of them refer to it also as organisational capital, and others - as process capital or processes. In general, among the identified indices for structural capital there are “soft” aspects such are the corporate culture, management processes, routines, support and cooperation between employees; share of knowledge; power and responsibility struc- ture; and those that represent the non-human aspects of the structural capital, such as the institutionalized knowledge utilized through databases, manuals, structures, systems, and processes. And from an evolutionary perspective (Nelson & Winter, 1982), the structural capital is created, preserved, and enhanced through structured, repetitive activities. These include the company’s structures and processes, or clearly mandated procedures and rules for retrieving, sharing, and utilizing knowledge. In our study we define structural capital as the aspect of the intangible capital that deals with the mechanisms and structures of the organization that can help to support employ- ees in their quest for optimum intellectual performance and therefore overall business performance (Chen et al., 2004). In order for the intellectual capital to reach its fullest potential, a company needs to have favourable systems and procedures in place. Accord- ing to Chen, Chen & Hwang (2005), a company with strong structural capital will create favourable conditions to utilize human capital and allow to realize its fullest potential, and subsequently also boost customer capital (Chen et al., 2005). Relational capital has been mostly used in literature to define the knowledge about cus- tomers and the relationships with them, and has been long known under the term of customer capital or market capital. However, the developments in the field of intangible capital has widened its definitional scope and has been referring to it as relational capital since (for example see Lynn, 1998; Choo & Bontis, 2002; etc.). Besides the organisation’s M. DRENKOVSKA, T. REDEK | INTANGIBLE CAPITAL, INNOVATION AND EXPORT-LED GROWTH.... 31 relationships with its customers, relational capital incorporates also relationships with other parties, such as suppliers, other companies in the market/industry, competitors, and different stakeholders where applicable (see Jacobsen et al., 2005; Marr, Schiuma & Neely, 2004; Payne et al., 1995; Roos & Roos, 1997). There is already a pool of evidence that confirms that firms’ market knowledge competences facilitate the design and development of innovative and successful products and have a posi- tive impact on the overall firm performance (Hurley & Hult, 1998; Li & Calantone, 1998). That being said, in our study, we adopt the examples of relational capital stated above and follow Chen et al. (2004) definition of relational capital that Chen et al. (2004) put forward. According to them, relational capital is essential part of intangible capital and presents “the value embedded in the marketing channels and relationships that a company develops by conducting business” . Market intensity, the ultimate expression of customer capital, refers to the current state of market building and its potential (Chen et al, 2004). Interconnectedness of intangibles. Managerial activities related to intellectual capital should complement each other. Edvinsson & Malone (1997) point out that human, structural, and customer capital reciprocally circulate and affect each other. According to Chen et al. (2004), structural capital is subject to human capital, since human capital is a determinative factor of the organizational form. Moreover, structural capital and human capital enable enterprises to form, develop, and use innovation capital and customer capital in a coordinated way. Hsu & Fang (2009) concede this reasoning positing that the collaboration of the elements of intellectual capital in generating knowledge value creates synergy. It is when human capital, structural capital, and relational capital complement and support each other, that intellectual capital will be most effective (Stewart, 1997). The higher the interactions among the IC components, the greater the effect on the performance of the intangible stock of a company (Chen, Zhu & Xie, 2004). This interconnectedness of the knowledge stock is also mentioned by Teece (1987), which Arrighetti et al. (2014) consider is the rea- son for the inverse relationship between the level of intangible assets a company possesses and the marginal costs of further investments in them (higher level of intangible assets is associated with a lower marginal cost of investing in the further extension of the asset stock, as argued by Knott, Bryce & Posen (2003)) In our study we examine whether there is a dynamism between the different aspects of the intangible capital and weather they have the potential to create value for the company. In that respect our model tests the following hypotheses: Hypothesis 1: HC proxy variables are directly and positively related to SC proxy variables. Hypothesis 2: HC proxy variables are directly and positively related to RC proxy variables. Hypothesis 3: SC proxy variables are directly and positively related to RC proxy variables. ECONOMIC AND BUSINESS REVIEW | VOL. 17 | No. 1 | 2015 32 3.2. Intangibles and innovation 5 To build upon the previous hypotheses, we emphasise that intellectual capital is more than simply the sum of the human, structural, and relational resources of the firm. But it is rather an indicator of how the knowledge of a firm is put to work in creating value for the organisation (Roberts, 1998). The different aspects of intellectual capital, both indi- vidually and jointly utilise the corporate knowledge which is essential for innovation. This conversion of the knowledge and its utilisation for new products and processes is the link between intangible capital and innovation. Each of the aspects of intangible capital (in our model) is associated with the different types of knowledge within the company. The tacit knowledge is embedded in the exper- tise, know-how, and the experience of individuals (human capital); the explicit or rule- based knowledge is embedded in the corporate’s internal processes, rules, and routines (structural capital); and the relational (sometimes called cultural) knowledge is expressed through the assumptions and beliefs used by members to assign value and significance to new information or knowledge (relational capital). To create knowledge, companies con- vert tacit to explicit knowledge, integrate and combine knowledge, and acquire or transfer knowledge across boundaries (Choo & Bontis, 2002). Or, as Nonaka & Takeuchi (1995) put it, in the process of new knowledge creation, the organization continuously converts the personal, tacit knowledge of individuals who develop a creative insight to the shared, explicit knowledge by which the organization develops new products and innovations. Innovation is a collective achievement (Van de Ven, 1986) as companies assimilate and integrate knowledge by facilitating its communication, sharing, and transferring among individuals and by encouraging interactions in groups and networks (Allen, 1977). The intangibles in a company collectively determine its ability to rapidly respond to environ- mental change and achieve new and innovative forms of competitive advantage and supe- rior performance outcomes (Teece, Pisano & Shuen, 1997). From a strategic point of view, it is important that the intangibles that a company nurtures are strongly related to the company’s strategic objectives. When a company identifies its critical intangibles, they become the key drivers to the value creation process of the firm. They em- brace the core competencies of the company as well as the present abilities that the company possesses, or needs to leverage in order to attain those objectives (Canibano et al, 2001). There is substantial evidence that intangibles that facilitate innovation are key determi- nants of firm competitiveness, value added, and growth (Sveiby, 1997; Ramezan, 2011; Kramer et al., 2011; González-Loureiro & Pita-Castelo, 2012). And since innovations es- sentially draw upon the knowledge deployed by such intangibles, finding an association between their various aspects and the organisation’s innovation orientation would hardly be surprising. In our study we use the perception that CEOs hold about the importance 5 Some include innovation capital as part of the intangible aspects of a firm. However, as Chen et al. (2004) has pointed out, the origination and development of “innovation capital” are based on the conjoint effects of human, structural, and relational capital. M. DRENKOVSKA, T. REDEK | INTANGIBLE CAPITAL, INNOVATION AND EXPORT-LED GROWTH.... 33 of innovation for the company as a proxy for innovation. Given that the proxy indicators consist of perceptional measures, the concept intrinsically reflects the strategic orienta- tion of the management towards innovation. To examine the ability of the intangibles to contribute towards innovation, we examine the relation between each aspect of intangible capital and the innovation construct. Hypothesis 4: HC proxy variables are directly and positively related to the innovation proxy variables. Hypothesis 5: SC proxy variables are directly and positively related to the innovation proxy variables Hypothesis 6: RC proxy variables are directly and positively related to the innovation proxy variables. 3.3. Intangible capital, innovation and export Many poor countries has chosen to follow the export-led model of economic growth where external demand determines the dynamics of growth. Some countries - most of them in East and South-East Asia - have even achieved unprecedented rates of growth through exports. Others, on the other hand, have tried, but failed to follow the same route (The World Bank, 1993). The successful examples of export-led economic growth are the countries whose exporting sectors were national developmental priorities. These coun- tries’ competitive strengths were systematically developed (e.g. Japanese industrial poli- cy) primarily by strengthening the manufacturing sectors (Grossman & Helpman, 1991; Boltho, 1996; Palley, 2011). An export–oriented manufacturing sector is crucial for build- ing favourable internal environment and fuelling the external demand, which in turn have the potential to push the economic standards upwards. The divergent success in building and maintaining an international competitiveness of countries, regions, and firms is directly related to their knowledge and intellectual capi- tal (Edvinsson & Bounfour, 2004). In the context of the organisational learning idea, the intangible capital of a firm enables the knowledge acquisition, knowledge sharing, and knowledge utilisation within a firm. The knowledge acquisition and creation can be inter - nal or external. Internal learning happens within the firm when through in-house research and development new knowledge is being generated and distributed. External knowledge generation (on which the industries of Albania and Republika Srpska predominately rely (World Bank, 2013a, 2013b)) involves the acquisition of new knowledge through observa- tion and assimilation of external information (Bierly & Chakrabarti, 1996). In practice there may not be a clear distinction between internal and external learning, and some studies have suggested that for successful product innovation and attaining competitive advantage internal and external innovation need to be integrated (Iansiti & Clark, 1994). In that sense, for both technologically advanced and those less technologically advanced organisations, the key components that create and sustain competitiveness are (1) their intangible capital, and (2) the structure of the environment/market where they operate, which includes the pool of available knowledge, and the development level of the market (institutions, competitors, customers, etc.) ECONOMIC AND BUSINESS REVIEW | VOL. 17 | No. 1 | 2015 34 The innovation that is a product of the knowledge created and transformed by the intangible capital facilitates the development of competitive advantage of the company (Barney, 1991; Peppard & Rylander, 2001). International trade literature has found evidence that the more innovative companies are also more present in foreign markets (Wagner, 1996; Wakelin, 1997; Weifens et al., 2000; Griffith et al., 2006; Cassiman & Golovko, 2007) and they export more as they are better established on those markets. In the increasingly global world, inno- vation is the minimum necessary requirement for countries to be competitive. The examina- tion of the link between innovation and export in our two models reveals insight weather in- novation (created through knowledge transformation by the intangible capital) is sufficient for reaching competitiveness on the global market (hypothesis 7). Hypothesis 7: Innovation proxy variables are directly and positively related to the export volume. The above postulated hypotheses are represented with arrows in the conceptualised re- search model in figure 1. 4. METHODOLOGICAL FRAMEWORK 6 The data used in our study was collected in a wider research project on intangibles in firms from the W estern Balkans region. The psychometric questions that the survey consisted of are founded in theory. Additionally, the questionnaire was tested in each separate country in order to confirm its suitability. The survey targeted the companies from the manufacturing and service sectors. The selec- tion of the company was not random, but a stratified sample was composed based on size, industry and location. The surveys were conducted in the second half of 2010 in Slovenia and in the beginning of 2011 in Albania and Republika Srpska of Bosnia and Herzegovina. In total 198 (100 from Slovenia, 40 from Albania, and 58 from Republika Srpska) effective responses were collected, which amounts to an overall response rate of 22.4%. 4.1. Sample The empirical analysis in this study focuses on the surveyed companies from the manufactur- ing sector in all three countries. The rationale behind this criterion is based on the idea that in our model examines radical innovation for which investments in R&D are key (Tether et al., 2002) and it is more likely that the manufacturing companies are engaged in more signifi- cant R&D. In that respect, the manufacturing subsample is deemed a more homogenous and relevant group of companies to include in our analysis. Table 2 provides the basic descriptive statistics of the samples, while the firms’ characteristics according to the answered questions pertaining to intangible capital and innovation are shown in tables A2-A4 in appendix A. 6 For a more detailed discussion about the survey and the measures used in the model, please refer to appendix A - Methodology, data collection and description M. DRENKOVSKA, T. REDEK | INTANGIBLE CAPITAL, INNOVATION AND EXPORT-LED GROWTH.... 35 Table 2: Structure of respondent companies Region Slovenia Pooled * Number of respondents (N = 73) (N =52 ) Size (Number of employees) Small <50 7.4 % 50.9 % Medium 50-100 16.7 % 32.1 % Large >250 75.9 % 17.0 % Export orientation More than 25% 77.8 % 37.7 % More than 50% 72.2 % 17.0 % Other characteristics Form: Ltd. vs. plc** 41 % 30.2 % B2B (vs B2C) 56 % 37.7 % * Pooled data set from the surveys in Albania and Republika Srpska of Bosnia and Herzegovina ** Limited liability company vs. Public limited company 4.2. Measures for the model variables The primary data was acquired through a psychometric type of questionnaire distributed to senior managers and addressed the intangible investments and characteristics of firms. The proxy indicators for all of the intellectual capital elements in the model have been adapted from or developed on the foundations of innovation literature, strategic manage- ment, and literature on intangible capital and growth. The complete list of indicators is given in table A1 in appendix A. The various aspects of intangible capital are not always found in companies in neat, sepa- rate “packages” . Out of the survey data we identified the indicators that were comparable in each of the geographic models and that proved adequate to capture the explanatory potential of the complex variables of the firms’ intangible capital. The proxies used in the models are shown in Table 3. All of the latent variables in the model are first-order constructs. The latent variable human capital (HC) is constructed of four items i.e. proxies, which are evaluated on a dichoto- mous scale (yes = 1; no = 0). The managers were asked to state whether “the company pro- vides regular on-the-job training” , and whether “the knowledge transfer is systematically induced among employees” . These two indicators refer to the investment in the relevant technical and professional knowledge of the employees. The other two proxies of human capital reflect the incentive practice that a company has in place for its employees. In that respect, the managers were asked to state whether “performance measure system can dis- tinguish between different performing employees”, and whether the higher performing employees are differently rewarded than the average performers. ECONOMIC AND BUSINESS REVIEW | VOL. 17 | No. 1 | 2015 36 Structural capital (SC) is a construct whose proxies are also assessed on a dichotomous scale and include aspects related to the: management’s influence in decision making, workers’ participation in the workplace, the worker’s participation in the risk-sharing, and their involvement in the decision-making process. The first two aspects correspond to what Chen et al. (2004) refer to as the organizational structure pertaining to the for- mal power relationships and control system. In that respect the respondents were asked to answer “do top managers and owners make strategic decisions unanimously”, and whether there is “an established open dialog with the workers about key decisions for the firm” . The remaining two aspects refer more to the less formal relationships pertaining to the work culture in the company and existing identification of employees’ goals with those of the company. In that sense, respondents gave answers to the questions that asked whether “cooperation in different teams in individual department is a common form of workers’ operation” , and whether “workers engage in additional training for the good of the firm (not considering training organized by the firm)” . The company’s culture under the guidance of a favourable managing philosophy is a valuable asset. Only under the strong culture can a company give full play to its employees’ competences and motivate them to serve the company and customer heart and soul. (Chen et al, 2004). The proxies with which we measure the latent variable relational capital (RC) examine the firm’s market knowledge competences and are assessed on a 5-point Likert scale. The respondents evaluate the company’s competences in comparison with competitors (with 1 being “considerably worse than the main competitors” and 5 – “considerably better than the main competitors”). The set of measures include questions about company’s knowledge about “customers’ preferences and needs” , “obtaining real time information about competitors” , and establishing and managing long-term relations with both cus- tomers and suppliers. Innovation (INN) is an endogenous latent variable and a function of the three latent vari- ables of intangible capital. The model examines the relations between the different as- pects of intangible capital and the ‘perceived importance of radical innovation’ as a proxy for the innovation variable. The indicators for the construct of innovation incorporated in our model are conceptualised as the significance that the managers place in different types of radical innovation for the company. There are two aspects that these measures reflect – the focus on radical innovation, and the importance with which senior manag- ers perceive the different types of radical innovation. In the context of the first aspect, we decide to focus on radical innovation given that our study analyses manufacturing companies (i.e. companies where R&D investments are most likely to occur, which is of key importance for radical innovations). And although both incremental and radical innovation are important for building and maintaining competitiveness, there is a closer linkage between long-term growth and radical innova- tion (Morone, 1993). Prašnikar & Kotnik (2006) in their study of technological lead- ers and followers further posit that as soon as a company develops new technologies, it ceases to be a follower and moves closer to the technological frontier. M. DRENKOVSKA, T. REDEK | INTANGIBLE CAPITAL, INNOVATION AND EXPORT-LED GROWTH.... 37 The perceived importance of the different types of radical innovation, on the other hand, reflects the official strategic goals of the company related to innovation; it is an indicator of the management’s innovation culture and aspirations. And while companies may or may not succeed in achieving their innovation objectives (which may be related to prod- ucts, markets, efficiency, quality, or the ability to learn and to implement changes), the innovative activities may nonetheless have other or additional effects than those that ini- tially motivated their implementation (OECD/Eurostat, 2005). Methodologically, it could be argued that capturing the objectives may have its flaws since actual effects may differ substantially from expectations. On the other hand, the effects of the (recent) innovation (output) may not be felt within the time period of the survey because of the lagging effect of innovation. Provided that our study relies on cross-sectional data, we opt for examining the objectives for innovation by measuring the perceived importance of radical innova- tions by the company’s management. The rankings placed in the different types of radical innovation are used as indicators of the strategic orientation of the firm in terms of innovation. In general, such examination may reveal whether the firm is engaging its intangible capital towards its innovative activi- ties. 7 The construct Innovation (INN) is built from three indicators of radical innovation, all measured on a three-point Likert scale. Respondents mark the relevance of the suggest- ed types of new products (radical innovations) in the company from 1 = low to 3 = high. The dependent variable Export Volume (Export) is measured by a dummy variable on the reported percentage of output that companies sell on foreign market. For the respondents in Albania and Republika Srpska of Bosnia and Herzegovina it has value 1 if company exported more than 25% of their products and 0 otherwise. For Slovenia, it has a value 1 if the company exported above 50% of its output and 0 otherwise 8 . The amount, or volume, that a company sells in foreign markets is an indicator of the success of the company’s internationalisation through innovation and its external competitiveness, which are very important in any export-led economy. 7 Ajzen (1985) has demonstrated that the intention for action depends on one’s belief and motivation. Organiza- tions valuing innovation put structures and incentives in place to cultivate an innovative climate. By focusing on innovation (and perceived high importance of producing novel products), firms boost their competitive advantage and reinforce their market leadership during an economic crisis (Guellec & Wunsch-Vincent, 2009). 8 The different breakpoint level in the delineation between exporters and non-exporters used in the studied countries comes from the fact that Albania and Republika Srpska of Bosnia and Herzegovina are at the mo- ment still much less export oriented than Slovenia. This reflects their considerably slower transition process due to political reasons, and hence, the slower firm restructuring and strategic reorientation. Consequently, the majority of firms in these countries are still operating primarily in domestic markets. ECONOMIC AND BUSINESS REVIEW | VOL. 17 | No. 1 | 2015 38 Table 3: Validated measurement items Constructs Item Abbreviation Structural capital Workers’ participation in the workplace: Is cooperation in different teams in individual department (not exclusively performing tasks in the same workplace) a common form of workers’ operation? CooperTeams Workers’ participation in decision making: Is there an established open dialog with the workers about key decisions for the firm (workers have the right to information, giving suggestions, debate, protest)? OpenDialogue Workers participation in risk sharing: Do workers engage in additional training for the good of the firm (not considering training organized by the firm)? AddTraining Management influence in decision making: Did top managers and owners make strategic decisions unanimously in the last five years? UnanDecMaking Human capital Does your company provide regular on the job training (e.g. apprenticeship, mentorship, job rotation)? OTJTrain Do you systematically induce knowledge transfer among employees? KnowTrans Do you measure performance in such a way that you can clearly distinguish between high and low performers? MeasPerf Are better performers better rewarded for their work than average performers? Rewards Relational capital Obtaining information about changes of customer preferences and needs. InfoCust Acquiring real time information about competitors. InfoComp Establishing and managing long-term customer relations. LongtermCust Establishing and managing long-term relations with suppliers. LongtermSupp M. DRENKOVSKA, T. REDEK | INTANGIBLE CAPITAL, INNOVATION AND EXPORT-LED GROWTH.... 39 Intangible capital, innovation and export-led growth 14 𝑣𝑣𝑣𝑣 𝑗𝑗𝑗𝑗𝑗𝑗𝑗𝑗 = � 𝑠𝑠𝑠𝑠 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 𝑣𝑣𝑣𝑣 ( 𝑌𝑌𝑌𝑌 𝑗𝑗𝑗𝑗 ; 𝑌𝑌𝑌𝑌 𝑗𝑗𝑗𝑗 ) 0 if 𝑌𝑌𝑌𝑌 𝑗𝑗𝑗𝑗 and 𝑌𝑌𝑌𝑌 𝑗𝑗𝑗𝑗 are adjacent otherwise 𝑌𝑌𝑌𝑌 � 𝑗𝑗𝑗𝑗 ≔ � 𝑣𝑣𝑣𝑣 𝑗𝑗𝑗𝑗𝑗𝑗𝑗𝑗 𝑌𝑌𝑌𝑌 𝑗𝑗𝑗𝑗 𝑗𝑗𝑗𝑗 𝑦𝑦𝑦𝑦 𝑘𝑘𝑘𝑘 𝑗𝑗𝑗𝑗 𝑘𝑘𝑘𝑘 = 𝑤𝑤𝑤𝑤 � 𝑘𝑘𝑘𝑘 𝑗𝑗𝑗𝑗 𝑌𝑌𝑌𝑌 � 𝑗𝑗𝑗𝑗 𝑘𝑘𝑘𝑘 + 𝑒𝑒𝑒𝑒 𝑘𝑘𝑘𝑘 𝑗𝑗𝑗𝑗𝑗𝑗𝑗𝑗 𝑌𝑌𝑌𝑌 𝑗𝑗𝑗𝑗 𝑘𝑘𝑘𝑘 ≔ � 𝑤𝑤𝑤𝑤 � 𝑘𝑘𝑘𝑘 𝑗𝑗𝑗𝑗 𝑦𝑦𝑦𝑦 𝑘𝑘𝑘𝑘 𝑗𝑗𝑗𝑗𝑗𝑗𝑗𝑗 𝑘𝑘𝑘𝑘 𝑗𝑗𝑗𝑗 The symbols used in the equations are explained below: Variables: Indices: y = manifest variable (index) i = 1,…,I for blocks of manifest variables Y = latent variable (construct) j = 1,…,J for latent variables e = outer residuals 𝑘𝑘𝑘𝑘 𝑗𝑗𝑗𝑗 = 1,…,K for manifest variables counted within block j n = 1,…,N for observational units The analysis and interpretation of a PLS model is a two-stage process - first, the reliability and validity of the measurement model are evaluated, and then next the structural model is assessed and hypotheses are tested. This sequence ensures that the constructs’ measures are valid and reliable before attempting to draw conclusions regarding relationships among constructs (Barclay, Higgins & Thompson, 1995). Thus, the measurement model in PLS is assessed in terms of individual item reliability, construct reliability, convergent validity, and discriminant validity. The complete model validation procedures are moved in appendix B. Constructs Item Abbreviation Innovation Extensions to existing product lines / services. Extensions New product lines / services. NewLines New products / services that are novelties also in global markets. GlobalNovelties Export volume A dummy variable: 1 if the company exports above 50% (25% for the less developed economies) of its output, 0 if otherwise Above50 5. RESULTS 5.1. Statistical technique We analysed our theoretical model using structural equation modelling SEM, which identifies the simultaneous relationship between the variables in our model. Partial Least Square is a non-parametric SEM technique described as second generation multivariate analysis (Fornell, 1987). It is most suitable in studies with non-normal data, small sample size, and focus on prediction (Hair et al., 2012). It is also recognised as the most appropri- ate technique for relatively complex models, with low theoretical information, and when the measures are not well established. This method can also effectively manage the high number of variables in the model and the low possible causal relationships between the constructs (Longo & Mura, 2011). The basic PLS algorithm 9 for reflective models is given below. The estimation of inner relationships in the measurement model (weights of indices in a block for a latent variable) is given by: while the structural equation for estimation of outer relationships of the structural model (path coefficients between latent variables) are the following: 9 For further details and debate about the PLS SEM technique please see Lohmöller (1989) Intangible capital, innovation and export-led growth 14 𝑣𝑣𝑣𝑣 𝑗𝑗𝑗𝑗𝑗𝑗𝑗𝑗 = � 𝑠𝑠𝑠𝑠 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 𝑣𝑣𝑣𝑣 ( 𝑌𝑌𝑌𝑌 𝑗𝑗𝑗𝑗 ; 𝑌𝑌𝑌𝑌 𝑗𝑗𝑗𝑗 ) 0 if 𝑌𝑌𝑌𝑌 𝑗𝑗𝑗𝑗 and 𝑌𝑌𝑌𝑌 𝑗𝑗𝑗𝑗 are adjacent otherwise 𝑌𝑌𝑌𝑌 � 𝑗𝑗𝑗𝑗 ≔ � 𝑣𝑣𝑣𝑣 𝑗𝑗𝑗𝑗𝑗𝑗𝑗𝑗 𝑌𝑌𝑌𝑌 𝑗𝑗𝑗𝑗 𝑗𝑗𝑗𝑗 𝑦𝑦𝑦𝑦 𝑘𝑘𝑘𝑘 𝑗𝑗𝑗𝑗 𝑘𝑘𝑘𝑘 = 𝑤𝑤𝑤𝑤 � 𝑘𝑘𝑘𝑘 𝑗𝑗𝑗𝑗 𝑌𝑌𝑌𝑌 � 𝑗𝑗𝑗𝑗 𝑘𝑘𝑘𝑘 + 𝑒𝑒𝑒𝑒 𝑘𝑘𝑘𝑘 𝑗𝑗𝑗𝑗𝑗𝑗𝑗𝑗 𝑌𝑌𝑌𝑌 𝑗𝑗𝑗𝑗 𝑘𝑘𝑘𝑘 ≔ � 𝑤𝑤𝑤𝑤 � 𝑘𝑘𝑘𝑘 𝑗𝑗𝑗𝑗 𝑦𝑦𝑦𝑦 𝑘𝑘𝑘𝑘 𝑗𝑗𝑗𝑗𝑗𝑗𝑗𝑗 𝑘𝑘𝑘𝑘 𝑗𝑗𝑗𝑗 The symbols used in the equations are explained below: Variables: Indices: y = manifest variable (index) i = 1,…,I for blocks of manifest variables Y = latent variable (construct) j = 1,…,J for latent variables e = outer residuals 𝑘𝑘𝑘𝑘 𝑗𝑗𝑗𝑗 = 1,…,K for manifest variables counted within block j n = 1,…,N for observational units The analysis and interpretation of a PLS model is a two-stage process - first, the reliability and validity of the measurement model are evaluated, and then next the structural model is assessed and hypotheses are tested. This sequence ensures that the constructs’ measures are valid and reliable before attempting to draw conclusions regarding relationships among constructs (Barclay, Higgins & Thompson, 1995). Thus, the measurement model in PLS is assessed in terms of individual item reliability, construct reliability, convergent validity, and discriminant validity. The complete model validation procedures are moved in appendix B. ECONOMIC AND BUSINESS REVIEW | VOL. 17 | No. 1 | 2015 40 The symbols used in the equations are explained below: Variables: Indices: y = manifest variable (index) i = 1,…,I for blocks of manifest variables Y = latent variable (construct) j = 1,…,J for latent variables e = outer residuals k j = 1,…,K for manifest variables counted within block j n = 1,…,N for observational units The analysis and interpretation of a PLS model is a two-stage process - first, the reliability and validity of the measurement model are evaluated, and then next the structural model is assessed and hypotheses are tested. This sequence ensures that the constructs’ measures are valid and reliable before attempting to draw conclusions regarding relationships among constructs (Barclay, Higgins & Thompson, 1995). Thus, the measurement model in PLS is assessed in terms of individual item reliability, construct reliability, convergent validity, and discriminant validity. The complete model validation procedures are moved in appendix B. 5.2. Reliability and validity of the measurement model We examine two similar models (for Slovenia and for the pooled data set of Albania and Republika Srpska of Bosnia and Herzegovina). We make a distinction between these two data sets because of two reasons. First, Slovenia is a more developed and more export ori- ented economy. The higher development level also impacts the behaviour and the struc- ture of the companies and the importance of the intangibles for the organisation. On the other hand, Albania and Republika Srpska are similarly developed economies and share common issues at corporate level also with respect to the state and investments in intan- gible capital (see Prašnikar, Memaj & Redek (eds.), 2012; Prašnikar & Knežević Cvelbar (eds.), 2012). And second, by pooling the data for the two less developed economies, we increase the sample size which can lead to more reliable estimates. Taking into consid- eration their similarities, we feel that the increased sample and the estimation reliability outweighs the potential problems of country specific effects. To establish factorial validity and reliability for the measurement model, we followed the PLS validation procedures outlined by Gefen & Straub (2005) (see tables B1 and B3 in ap- pendix B). The complete procedure of model validation is moved to appendix B. Further- more, given that the measures for the dependent and independent variables were taken from the same instrument, we perform four tests to overcome the concern of common method bias in the survey design. First, Harman’s one-factor test was done to see whether one factor accounted for the majority of variance in the data (Podsakoff et al. 2003). Then the Pavlou, Liang & Xue (2007) test was used. Additionally, the latent variable correlations were examined (tables B7 and B8). Finally, a more rigorous test of common methods bias test suggested by Podsakoff et al. (2003) and adapted to PLS analysis by Liang et al. (2007) was performed. Common method bias is observed when a single factor emerges from M. DRENKOVSKA, T. REDEK | INTANGIBLE CAPITAL, INNOVATION AND EXPORT-LED GROWTH.... 41 Intangible capital, innovation and export-led growth 15 (2007) test was used. Additionally, the latent variable correlations were examined (tables B7 and B8). Finally, a more rigorous test of common methods bias test suggested by Podsakoff et al. (2003) and adapted to PLS analysis by Liang et al. (2007) was performed. Common method bias is observed when a single factor emerges from the analysis or when one general factor accounts for the majority of the covariance in the interdependent and dependent variables. As each of the principal constructs explained approximately equal variance, the data did not indicate common method bias. The results from the common method bias test are found in appendix C. 5.3. Hypotheses testing - results and discussion Once unidimensionality, reliability, and construct validity for the measurement models were demonstrated, the structural model fits and proposed hypotheses concerning the main and mediating effects were tested. In particular this study tests the relationships between the elements of intellectual capital in the samples of manufacturing firms and the relationship between each of them with the innovation attitudes of the managers, and consequently, the link between innovation and the volume of export of these firms. The results of our theoretical model testing are depicted in Figure 2. Figure 2 Results* *‘Slovenia’ values provide the result obtained from the sample of manufacturing firms in Slovenia, while the ‘Pooled’ values provide result for the combined sample of manufacturing firms from Albania and Republika Srpska of Bosnia and Herzegovina. The hypotheses pertaining to the interrelatedness of the IC dimensions were found to have significant positive effect in both of the models. Namely, we find that human capital positively affects both structural and relational capital, thus supporting the hypotheses H1 and H2. Structural capital, innovation capital, and relational capital are affiliated to human capital. On one hand, human capital can convert knowledge into market value by converting the other three capitals. On the other hand, human capital can determine the operational forms of the other three capitals and by that convert immaterial knowledge and information into material output and benefit (Chen et al., 2004). STRUCTURAL CAPITAL Slovenia: 0.503*** Pooled: 0.202*** Slovenia: 0.212*** Pooled: 0.583*** Slovenia: 0.108*** Pooled: 0.096* Slovenia: 0.244*** Pooled: 0.308*** Slovenia: 0.295*** Pooled: 0.006 Slovenia: 0.079 Pooled: 0.009 Slovenia: 0.101*** Pooled: 0.364*** RELATIONAL CAPITAL HUMAN CAPITAL EXPORT INNOVATION the analysis or when one general factor accounts for the majority of the covariance in the interdependent and dependent variables. As each of the principal constructs explained approximately equal variance, the data did not indicate common method bias. The results from the common method bias test are found in appendix C. 5.3. Hypotheses testing - results and discussion Once unidimensionality, reliability, and construct validity for the measurement models were demonstrated, the structural model fits and proposed hypotheses concerning the main and mediating effects were tested. In particular, this study tests the relationships between the elements of intellectual capital in the samples of manufacturing firms and the relationship between each of them with the innovation attitudes of the managers, and consequently, the link between innovation and the volume of export of these firms. The results of our theoretical model testing are depicted in Figure 2. Figure 2: Results* *‘Slovenia’ values provide the result obtained from the sample of manufacturing firms in Slovenia, while the ‘Pooled’ values provide result for the combined sample of manufacturing firms from Albania and Republika Srpska of Bosnia and Herzegovina. The hypotheses pertaining to the interrelatedness of the IC dimensions were found to have significant positive effect in both of the models. Namely, we find that human capital positively affects both structural and relational capital, thus supporting the hypotheses H1 and H2. Structural capital, innovation capital, and relational capital are affiliated to human capital. On one hand, human capital can convert knowledge into market value by converting the other three capitals. On the other hand, human capital can determine the operational forms of the other three capitals and by that convert immaterial knowledge and information into material output and benefit (Chen et al., 2004). In the case of Slovenian manufacturing firms, the human capital was shown to have larg- est significant impact on the relational capital (β 0.503; p < 0.001). This may be suggesting that the processes in the Slovenian companies are more focused to translating human capital into market-related capital, as it is more important for maintaining the competi- ECONOMIC AND BUSINESS REVIEW | VOL. 17 | No. 1 | 2015 42 tiveness in their more developed and diversified markets. While in the case of the pooled dataset from Albania and Republika Srpska, the human capital is more heavily related to the structural capital (β 0.583; p < 0.001), which reveals the cultural and institutional significance of the nature of their structural capital that is important for companies from these two countries 10 . The results show that, as expected, the indicators for the construct human capital are closely related to the ‘softer’ aspects of the structural capital in the firm i.e. the culture and the processes. The human capital has a transient nature and organisa- tions are encouraged to, wherever possible, convert it to structural and relational capital. By doing so, i.e. moving from human capital to structural and relational capital, the em- bedded knowledge will become more independent of people. It will consequently remain based in organizational systems, structures and technologies and, thus, become poten- tially easier to control. Our path analysis confirms that this process is more pronounced in the Slovenian companies, which in its own suggests that these are more innovative, better-learning, more competitive companies. With this type of knowledge creation (by converting it from one kind to another) they bridge the gaps in the organization’s existing knowledge which can stand in the way of solving a problem, developing a new product, or taking advantage of an opportunity (see Choo & Bontis, 2002). Additionally, the literature suggests that that human capital significantly affects customer i.e. relational capital in all industries (e.g. Bontis, Keow & Richardson, 2000). Higher qual- ity employees were shown to be more skilled in acquiring, distributing, and utilising more information regarding customers and business partners towards building long-term re- lationships with them. In other words, human capital positively affects relational capital (Hsu & Fang, 2009). The relation between structural capital and relational capital (H3) is somewhat weaker, but nonetheless significant in both models (β 0.108; p < 0.001 and β 0.096; p < 0.005 respectively). The hypotheses H4, H5, and H6 are considering the effects of the three intellectual capital dimensions (SC, HC, RC) on the perceived importance of radical innovation in the com- pany. In Slovenia, the structural capital has the most significant impact on innovation (β 0.244; p < 0.001), while in the pooled case (Albania and Republika Srpska of Bosnia and Herzegovina), the relational capital had strongest impact on the perceived importance of innovation (β 0.364; p < 0.001). The different aspects of intellectual capital accumulate and process knowledge differently. Therefore it is possible that each of them and their interrelationships may influence the company’s innovation in different ways. We tested the mediating effects of the constructs structural capital and relational capital on the influence of human capital on innovation. The estimated paths in the case of Slovenia indicate a mediation effect of human capital on innovation. The performed bootstrapping reveals a full mediation when the interven- ing construct is structural capital and a partial mediation when the intervening variable is relational capital in both models. The assumptions behind the tested mediation are in 10 Companies where there is collaboration between owners and managers are more oriented towards value– enhancing activities (Aoki, 2010; Prašnikar et al., 2014). M. DRENKOVSKA, T. REDEK | INTANGIBLE CAPITAL, INNOVATION AND EXPORT-LED GROWTH.... 43 the expectations that companies that are actively engaged in training their employees (and encouraging learning and knowledge sharing) also encourage learning and innova- tive cultures. Furthermore, employee abilities affect firm’s relations to outside parties, and contribute to ideas and knowledge assimilation. The latter can be later enmeshed in the innovation processes. Table 4: Path estimates – path coefficients and t-values Hypothesis Slovenia Pooled H1: HC  SC 0.212 (4.265) *** 0.583 (20.773) *** H2: HC  RC 0.503 (12.762) *** 0.202 (3.979) *** H3: SC  RC 0.108 (2.465) *** 0.096 (1.725) ** H4: HC  INN 0.079 (1.374) ** 0.009 (0.182) H5: SC  INN 0.244 (1.697) ** 0.308 (6.684) *** H6: RC  INN 0.101 (3.972) *** 0.364 (7.626) *** H7: INN Exp 0.295 (6.875) *** 0.006 (0.119) ***p<0.001 **p<0.05 Finally, we examine the relation of the innovation construct to firm’s export orientation (H7). In the case of Slovenia, the link is positive and significant (β 0.295; p < 0.001) 11 , while in the pooled case (Albania and Republika Srpska of Bosnia and Herzegovina), it is insignificant. These results are in line with the findings of Prašnikar et al. (eds.) (2012) and Prašnikar and Cvelbar Knežević (eds.) (2012) in the studies of intangible capital in Alba- nia and Republika Srpska of Bosnia and Herzegovina, respectively. The study on the intan- gible capital in Albania revealed a predominant inward orientation of the companies and focus on the domestic market. Those Albanian companies that do compete in the global markets exploit their cost competitiveness. Similarly, the study in the Republika Srpska found that most of the (manufacturing) companies are very marginally present elsewhere but at home. This inward orientation, may be limiting the learning opportunities that the more developed and more competitive markets offer. On the other hand, Slovenian companies are very export oriented. A large proportion of Slovenian exports is destined for the highly competitive EU-15 markets (Damijan, Kostevc & Polanec, 2011), and this increases the scope for benefits from either positive spill-overs in the exporting markets or by raising the innovation of exporting firms (learning-by-exporting). Although the re- verse relationship between exporting and innovation is beyond the scope of our empirical analysis, the results in the present study show a significant path-coefficient between the constructs innovation and export volume within the Slovenian sample. The results of the study show that although there is an indication that there is some in- vestment in intangible assets present in the manufacturing companies of Albania and Re- 11 As confirmed by Domadenik, Prašnikar, & Svejnar (2008) for a study made on a Slovenian sample, compa- nies whose management was more R&D oriented, were more likely to be more innovative in the longer term, more productive and, thus more competitive. ECONOMIC AND BUSINESS REVIEW | VOL. 17 | No. 1 | 2015 44 publika Srpska, it is only a part of the story behind the restructuring and the growth of these two developing economies. First, the W estern Balkan countries lack the capacities to undertake scientific and applied industrial research, and to transfer, adapt and assimilate new technologies into economic structures and diffuse them into society (World Bank 2013a, 2013b). And second, the lack of exports is a serious threat to future development, alongside the low competitiveness, relatively high public debt, and the consequent current account deficit (EBRD, 2011). Therefore, the national efforts in these economies should be directed towards strengthening of their research and innovation capacity, which in turn will increase their competitiveness on the global market. In conclusion, the estimated paths from our hypothesised models confirm not only the interconnectedness of IC elements, but also support the hypotheses about their contri- bution the innovation culture in the firm. This is important since the corporate strategy guides the entire organisation and identifies the path that all departments and functions need to pursue (Alcaniz, Gomez-Bezares & Roslender, 2011). The literature agrees that the intellectual capital resources are often performance drivers 12 and, hence, there must be a causal relationship between those resources and value creation. They must be interrelated to create more value (Marr, 2005). Our analysis confirms not only that there is a posi- tive relationship between the elements of intellectual capital and innovation, but also that there is a positive relationship between innovation and the export volume of the firms. The latter linkage, however, holds only for the Slovenian manufacturing companies, which corroborates previous findings that the most innovative Slovenian firms are exhibiting global competitiveness, exporting to a number of global markets (not only the proximity markets of ex-Yugoslavia, but EU and outside of EU markets (Prašnikar et al., 2012)). The insights from the intangible capital literature show that key factors in acquiring and utilising knowledge in a company are its investments in different types of intangibles. The sequential theory of internalisation, on the other hand, holds that the internationalisation process is a path dependent learning process in which the acquisition of knowledge and the commitment of resources are fed back mutually (Andersen, 1993). In that respect, firms go through a gradual process in acquiring knowledge through their own experi- ence, and as they begin competing on foreign markets, they do so in a gradual way, first in countries culturally and geographically close to the country of origin (Johanson & V ahlne, 1977; Davidson, 1980; Benito & Gripsrud, 1992) and subsequently in other countries. This learning process will be, of course, additionally influenced by the development of the markets where the companies export. For a sample of Slovenian companies, De Loecker (2007) and Damijan & Kostevc (2006) find that, by exporting to advanced markets, firms can learn more due to the higher quality, technical, safety and other standard require- ments of those markets, as well as due to the tougher competition. In that sense, the West- 12 It is interesting to note that this is not the first time a direct link has not been observed between a construct of human capital and performance, and that the main relation that explains the dependent variable (innova- tion) is the relation human capital – structural capital. This was also found in a similar study by González- Loureiro & Pita-Castelo (2012) on 140 innovative SMEs from Galicia, Spain. In their case the dependant variable was the firm’s marketing performance (a composite variable of turnover and value added). This occurrence speaks in favour of the higher impact of transformed knowledge (for which a well-established knowledge creation mechanism needs to be in place) on the company’s success. M. DRENKOVSKA, T. REDEK | INTANGIBLE CAPITAL, INNOVATION AND EXPORT-LED GROWTH.... 45 ern Balkan economies, have the potential to eventually, by following the Slovenian path of economic development, become more competitive in the global market. 6. CONCLUSION 6.1. Contributions and limitations Our study contributes to the existing literature in several ways. First, it represents a con- tribution towards the IC valuation models (cf. Sveiby, 2001) in a way that we are able to calculate measures of the different aspects of intangible capital (human capital, structural capital, and relational capital) in the developing economies from the Western Balkans and Slovenia using an original data set, which represents a novelty. Furthermore, we relate the intangibles present in the manufacturing firms to their innovation and consequently to their export intensity, which is a first empirical study of its kind to explore these links on data from these countries. Additionally, exploring the linkage in a comparative study between the Western Balkans (Albania and Republika Srpska of Bosnia and Herzegovina) and the European Union (Slovenia), this study offers additional insights to policy-makers and practitioners as well. Using a unique dataset of firm-level data, the paper is extending the knowledge on inno- vation, corporate behaviour, and competitiveness in foreign markets through the volume of export. The results support the idea that the relationship between the IC components affects innovativeness in technological-follower companies, but reveal a divergent effect of the innovation proxy measures to the volume of export in the different data sets. Clearly the capacity to innovate is closely related to the firm’s intangible capital (the ability to transform and utilise knowledge for the purposes of innovation). But the international literature recognises that the export behaviour of firms is influenced by a mix of differ- ent factors. These factors range from structural ones (size, R&D intensity etc.), through management factors (attitudes towards risk, education of decision makers, etc.) to, finally, incentives and obstacles in the process of internationalisation (competitive pressure, nega- tive domestic trends, availability of information, etc.). As the companies we analyse come from economies that differ with respect to endowments in terms of labour, capital, and the stock of knowledge, these aspects influence the level of their innovation, and consequently its contribution to the level of competitiveness on foreign markets. The differences between countries in innovation levels also reflect the efficiency of their respective national innovation systems, i.e. the producers, users, suppliers, public authori- ties and scientific institutions that constitute them. It is the interaction between the actors on the market, and in general, of the innovation system, that results in new and com- mercially useful knowledge. Therefore, it is very important to make the distinction of the different institutional, economical, and technological settings where innovation can thrive and recognise that there are different innovation processes in technological followers and technological leaders. Only in that way we could hope to gain deeper understanding of the phenomenon and its potential to push the economy up. ECONOMIC AND BUSINESS REVIEW | VOL. 17 | No. 1 | 2015 46 Policy-makers around the globe have recognised investments in intangible capital as a major driving force behind the ‘new economy’ growth model. The successful stories of Asian and European economies have demonstrated that own product development, and global market penetration with innovative products and own brands are key to ensuring stable growth. The current low value-added exports that represent the majority of ex- ports of the W estern Balkan manufacturing companies is a strategy that lacks the potential to bring sustainable competitiveness in foreign markets. A previous study (Prašnikar & Knežević Cvelbar, (eds.) 2012) shows that companies that invest more in intangible assets are on one hand more export-oriented and on the other hand (seemingly paradoxically) less productive than companies oriented towards the domestic market. But the lower pro- ductivity of export-oriented firms is in fact an indicator of the superior competition in the global market. On the other hand, high productivity in domestic markets reveals the lack of competition at home and consequent higher economic rents. Therefore, the increasing openness of domestic markets will further increase competition and lower these, momen- tarily high, rents. Continuous investment in intellectual capital and innovation are the only long term solution to growth. Furthermore, the present study generates a number of practical implications for the study of global competitiveness of the companies in the technology-follower countries. From practitioners’ point of view, the study proposes measures for human, structural, and rela- tional capital in the manufacturing companies. By measuring, reporting, and managing their intellectual capital effectively, companies can improve their competitive advantage. It is by identification of all the assets at their disposal (tangible and intangible), that com- panies will be able to operate at their full potential by making maximum use of their as- set pool. Appropriate management activities in that direction can create new knowledge sources or, improve the value of existing ones. The study faces some limitations, mainly pertaining to the sample size and thus generali- sation of the results. First, given the non-random sample from the population of larger firms in Albania and Republika Srpska of Bosnia and Herzegovina, the results should be interpreted bearing this caveat in mind. Additionally, a larger sample size could improve the predictive accuracy of the models, and contribute to more robust estimates. Future studies can also benefit from an extension of the sample that would incorporate other industries and economies from the Western Balkans, which would provide broader gen- eralization of the obtained results. Finally, the present study relies on cross-sectional data, which limits the examination of the causality between the variables. Therefore, a repeated (longitudinal) study is one of the more important future challenges. Overall, given the good fitting of the models, we feel that this study offers some insights from environments with very poor and even deteriorating national support and policies for human development, as well as national innovation systems, and puts them vis-à-vis the perspective from a more developed “neighbour” . With that, the present study paves the way for future studies that would examine the role played by the intangible factors in these economies and how their effectiveness is affected by the other productive inputs and by environmental factors. M. DRENKOVSKA, T. REDEK | INTANGIBLE CAPITAL, INNOVATION AND EXPORT-LED GROWTH.... 47 6.2. Conclusion The paper examines the relation between the intangible capital (human, structural, and relational capital), innovation, and export orientation in the manufacturing sector. Using a unique survey data set on Slovenia, Albania, and Republika Srpska of Bosnia and Her- zegovina, we propose two theoretical models that reveal the relevance of the IC elements in two different settings: a pooled model of a sample of manufacturing companies from Albania, and Republika Srpska vis-à-vis a comparable Slovenian model. The results seem to highlight that the human capital is the basic starting point in knowl- edge creation in the firms as the estimated paths show that it positively affects both, struc- tural capital and relational capital, and that, consequently, structural capital positively af- fects relational capital. The main link for explaining the high importance of innovation, however, is the HC – SC relationship. This is in-line with the resource–based view of firms, where human capital is recognised as the primary important source of, both firm’s competitive advantage as well as its ability to adapt to volatile environments (Barney, 1991; Judge et al., 2009). Subsequently, many researchers identified the firm-specific human and structural resources as the largest subcategory of businesses’ intangible investments (Van Ark et al., 2009, for US and UK; Fukao et al. 2009, for Japan; Bloom & Van Reenen, 2010). The results from the estimated models reveal that the manufacturing firms in Albania and Republika Srpska of Bosnia and Herzegovina possess intangible capital and that the ele- ments that it is consisted of can be, in fact, measured. However, this is only the first step towards building competitiveness on foreign markets, as these companies have still very limited export orientation (which was confirmed by the insignificant link between the in- novation (as a function of the intangible capital) and the export volume variable. Unlike the pooled model, Slovenian companies are exporting more heavily, which implies their higher competitiveness and success on the global markets. REFERENCES Ajzen, I. (1985). 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The conceptualisation of the questions, which indica- tors we deemed appropriate to for constructing the latent variables in our model(s) are founded in theory. Human capital measures The human capital and motivation indicators concern the internal corporate training practices and policies, as well as the on-the-job training. The questions aim to identify the company’s intention to make collaborative efforts by asking about the provision of organised training based on identified needs of the company. Next, the questions establish the firm’s dedication to measuring the effects of training. Firms that also measure train- ing effectiveness with other methods, rather than solely by conducting a survey at the end of a training programme, are considered more dedicated. The questions examining the on-the-job training aim to identify whether the company actually provides regular on-the-job training (e.g. apprenticeship, mentorship, job rotation etc.) and if it actively promotes spreading knowledge among its employees. If a firm considers on-the-job train- ing an important factor in the promotion of key employees, it will foster successors for most of its key employees, allowing for quick and efficient replacements. As put forward by Chen et al. (2004), human capital is the foundation of the companies’ intangible capital, and refers to such factors as “employees’ knowledge, skill, capability, and attitudes in rela- tion to fostering performances which customers are willing to pay for and the company’s profit comes from” . Structural capital measures The proxies for measuring the latent variable structural capital include management’s in- fluence on decision-making, the workers’ participation in risk sharing, workers’ participa- tion in decision-making, and their role in the workplace. These were measured through adapted psychometric questions, developed and tested by Bloom & Van Reenen (2007). They are organised in cascading set of closed questions, an approach first used by Miya- gawa et al. (2010) 14 . 13 For more details on the comprehensive survey on intangible capital in the developing countries of the West- ern Balkan, please see Prašnikar et al. (eds.) (2012) and Prašnikar & Knežević Cvelbar (eds.) (2012). 14 The cascading approach directs respondents to a systematic way of thinking about the actual situation in the organisation without being biased or thinking too broadly about it. It also increases the reliability of the data by using a set of three simple and clear consecutive ‘Yes/No’ statements. Each consecutive statement in a question set represents a greater degree of complexity of the selected phenomenon, building into a cascading structure, and also allowing empirical testing (more in Prašnikar et al., 2014). ECONOMIC AND BUSINESS REVIEW | VOL. 17 | No. 1 | 2015 54 The proxies for the management’s role in decision-making examine the “power and re- sponsibility in the managing process” (Cheng et al., 2004), or the use of existing resources belongs to managers. The separation of strategic functions (given usually to top man- agement) and day-to-day decisions (which are usually in the hands of middle and lower management) reveals the level of cooperative behaviour of the corporate governance. The literature explains that employee involvement in decision–making may foster the elimina- tion of post–contractual information asymmetry (Freeman and Lazear, 1995), increase investments in human capital (Furubotn, 1988; Furubotn and Wiggins, 1984) and enable the controlling owners to pursue value–enhancing quality management and innovative strategies (Kraft, Stank& Dewenter, 2011). This power and responsibility structure is ac- cording to Chen et al. (2004) one of the expressions of structural capital. The questions on workers’ participation in risk sharing, examine the willingness of em- ployees to do “something more” for the firm, or whether they would voluntarily, outside their working hours, invest themselves in the benefit of the company. Further, questions from this section of the questionnaire examine the workers’ long-term personal vision within the company; their “loyalty” towards the firm reflected through their willingness to stay with the firm even if they had been offered better (paid) employment elsewhere, and lastly their propensity to financially participate in the firm and take financial risks. The workers’ participation in the work place, or the internal cooperation, is examined by questions on the nature of the corporate processes and weather they encourage work in groups; whether it is common for teams to cooperate within same departments, as well as interdepartmentally. These aspects reveal the on one side the softer properties of the structural capital, the organisational culture, reflected through the employees’ attitude about themselves and the firm (Chen et al., 2004). “Company culture under the guidance of a favourable managing philosophy is a valuable asset. Only under the strong culture can a company give full play to its employees’ competence and motivate them to serve the company and customer heart and soul. ” In order to study the effect of workers’ participation in the decision–making process on firm performance, the survey categorises this participation into levels or degrees. Clarke, Roberts, & Fatchet (1972) distinguishes between participation concentrated on work tasks (work–centred participation) and participation concentrated on the distribution of power (power–centred participation). This set of questions are modelled according to Bernstein (1982), who distinguishes between different degrees of workers’ control, and namely: em- ployee consultation, which represents the lowest degree of participation, where workers merely provide written or oral suggestions to management, which can choose to ignore or act on them; employee co–influence, which involves discussions between workers and management, where workers have the right to be informed, discuss their interests, protest, and offer suggestions, but management still makes the final decision; and joint manage- ment, or co–determination, where both parties have the right to veto decisions and form joint decision committees. The most advanced degree, self–management, which enables full participation of all members of the firm, with workers having total control over the decision–making process, was left out from the questionnaires, given that the Republika Srpska of Bosnia and Herzegovina and Albanian normative frameworks do not support M. DRENKOVSKA, T. REDEK | INTANGIBLE CAPITAL, INNOVATION AND EXPORT-LED GROWTH.... 55 workers’ participation. The first question, ’ Are workers informed about key decisions for the firm?’ reflects employee consultation. The second question, ’Is there an established open dialogue with the workers about key decisions for the firm?’ expresses employee co– influence. The last question about workers being members of governing bodies includes joint management or codetermination. The above described indicators are inline with Chen et al. (2004) definition of structural capital according to which this concept deals with the system and structure of a company. They postulate that a company “with strong structural capital will create favourable condi- tions to utilize human capital and allow human capital to realize its fullest potential, and then to boost its innovation capital and customer capital” . Relational capital measures The innovation questionnaire of the survey on intangible capital in developing countries is heavily based on the Community Innovation Survey (CIS), but adapted to capture the specifics of the innovation activities in technology follower countries. The adaptations in the innovation questionnaire follow the recommendations from the literature on innova- tion surveys (OECD/Eurostat, 2005; Mytelka et al., 2004; Mairesse & Mohnen, 2010). The indicators we derive to build the latent construct of relation capital in their core examine the firm’s market knowledge competences. The four proxies are measured on a 5-point Likert scale where CEOs evaluate their company’s competences in comparison with com- petitors (from 1 - considerably worse than the main competitors to 5 - considerably bet- ter than the main competitors). The set of questions include information on company’s knowledge about customers’ preferences and needs, about competitors, and establishing and managing long-term relations with both customers and suppliers. Innovation measures Technical innovation (product and process innovation) is the most used measure for in- novation in companies from the manufacturing sector, which is the type of companies our sample consists of. The proxies we looked into for measuring the construct of innovation in our structural models are conceptualised as opinion on the relevance on the different types of innovation for the company. This question was added in the CIS based question- naire and was the measures were adapted from the survey used by Rajkovič (2011). Given that this survey was prepared to address the needs of measuring innovation in technologi- cal followers (see Prašnikar, Redek & Drenkovska, 2014), it acknowledges the importance to determine not only whether there have been new products introduced by the com- pany, but also the significance that a particular type of innovation holds for the company in terms of competitiveness and it technological (and organizational complexity). CEOs were asked to rate the following types of innovations on a 3-point Likert scale where 1 means low relevance and 3 means high relevance: repositioning; improving existing prod- ucts; extensions to existing product lines; new product lines. The first three types represent incremental innovations, while the last three – radical innovations. Table A1 lists the items we selected and tested as measures for the intangible constructs in the hypothetical model. ECONOMIC AND BUSINESS REVIEW | VOL. 17 | No. 1 | 2015 56 The survey conducted in the three economic entities also collected data about individual characteristics of the surveyed firms, such as export orientation (share of revenues made abroad), ownership type (state or private, domestic or foreign, and dispersed or concen- trated), industry (service or manufacturing), and legal form (limited liability company or joint stock company). In each country, we pilot-tested the questionnaire in order to con- firm its suitability. During the process we asked managers to complete the questionnaire and indicate any ambiguity in the phrasing of questions. Sampling and data collection The questionnaires were mainly sent by post to the CEO’s and/or senior managers in charge of corporate R&D, HR, and other relevant departments as they possess comprehen- sive operational and strategic knowledge on firms, which was required by the question- naire. The initial correspondence included a covering letter that explained the purpose of the research and provided assurance of anonymity and confidentiality. Subsequently, the managers were contacted by phone and, referring to the covering letter were, were notified that a questionnaire will be sent on their email account. Once the postal questionnaires were sent, detailed follow-up where necessary was conducted, by phone, or email one week latest. The questionnaires in Slovenia were administered to the 400 largest Slovenian firms, which constituted the country’s entire population of firms with 100 or more employees from the manufacturing and the service sector. The surveys in Albania and Republika Srpska of Bosnia and Herzegovina were conducted with the assistance of the research teams from the University of Tirana, and the University of Banja Luka, respectively. The surveys were conducted in two waves for both the com- panies from the manufacturing industries and the companies from the service industries. The start of the survey in Slovenia was the autumn of 2010, and for Albania and Republika Srpska of Bosnia and Herzegovina - the beginning of 2011. Each wave of the survey was separated by three to four weeks. After the completion of the survey, 198 (100 from Slove- nia, 40 from Albania, and 58 from RSBiH) effective responses were collected, amounting to an overall response rate of 22.4%. Sample descriptions The Slovenian sample finally consisted of mainly companies from the manufacturing sec- tor (77%), while the rest were service companies. Two thirds of them (66%) exported at least 20%, while 59% exported at least half of products in the observed period. In terms of employment, the sample consists of 40 medium-sized companies (50-249 employees) and 54 large companies (250 employees or more). Over the entire period, the average company had 603 employees. About half of companies (52%) reported the domestic and/or W estern Balkan markets as their main market, while the rest sold the majority of their products to the EU and other foreign markets. M. DRENKOVSKA, T. REDEK | INTANGIBLE CAPITAL, INNOVATION AND EXPORT-LED GROWTH.... 57 The Albanian sample consists of 12 joint stock companies and 28 companies with limited liability. Some 25% (10 companies) are from the construction industry, 37.5% (15 compa- nies) are from the manufacturing sector, while 37.5% are from the tertiary sector: 15% (six companies) are from trade and 22.5% (nine companies) are from service activities other than trade. The sample also justly represents the size structure. The average company in the sample employed 148 people in 2010. Among the respondents from the Republika Srpska of Bosnia and Herzegovina sample 61.4% were manufacturing firms the sample, 22.4% are state-owned firms, 15.5% are owned by foreigners, and 94.8% had concentrated ownership. In 2011, they generated 8.7% of total income and employed 5.4% of employees among all firms registered in Re- publika Srpska of Bosnia and Herzegovina. Table A1: Complete list of indicators for measuring each intellectual capital (IC) element in the theoretical model (as obtained from the questionnaire) Constructs Item Abbreviation Structural capital Management’s influence on decision-making Is the decision making process about strategic questions of the firm separated from the operational decision making process at different levels of the firm? DecMakingSep Did top managers and owners make strategic decisions unanimously in the last five years? UnanDecMaking Are the basic strategic decisions in the firm coordinated among owners, managers and workers? CoordDecMaking Structural capital Workers participation in risk sharing Are most of workers prepared to do “something more” for the firm? SmtMore Do you believe most workers would stay with the firm even if they were offered better employment somewhere else (for example if they were offered a better paid employment)? StayInFirm Are most workers willing to accept a part of business risk (for example financial investment in the firm or deferred payment in the case of profit sharing)? AcceptRisk Do workers engage in additional training for the good of the firm (not considering training organized by the firm)? AddTraining Structural capital Workers’ participation in the workplace Is there a great need for workers to work in work groups because of the nature of the work processes? WorkInGroups Is cooperation in different teams in individual department (not exclusively performing tasks in the same workplace) a common form of workers’ operation? CooperTeams Is there a strong presence of workers’ cooperation between different departments and forming of interdepartmental teams? CooperDepart ECONOMIC AND BUSINESS REVIEW | VOL. 17 | No. 1 | 2015 58 Constructs Item Abbreviation Structural capital Workers’ participation in decision making Are workers informed about key decisions for the firm (workers have the option of giving comments that are then regarded or not. InfoKeyDecis Is there an established open dialog with the workers about key decisions for the firm (workers have the right to information, giving suggestions, debate, protest)? OpenDialogue Are the workers’ representatives in your firm members of the governing bodies (for example the supervisory board and its comities) and are involved in the decision making process? RepresGovern Human capital and motivation Training and knowledge transfer Does your company provide organized training of your employees based on identified needs of the company? OrgTrain Do you involve more than half of your employees in your training programs annually? MoraHalf Do you measure training effectiveness with other methods than conducting a survey at the end of a training program? MeasTrain Does your company provide regular on the job training (e.g. apprenticeship, mentorship, job rotation)? OTJTrain Do you systematically induce knowledge transfer among employees? KnowTrans Do you have successors for most of your key employees, so that they could effectively take on their positions in a short period of time? Successors Human capital Motivation Do you measure performance in such a way that you can clearly distinguish between high and low performers? MeasPerf Are better performers better rewarded for their work than average performers? Rewards Do you apply any other warning sign than oral reprimand for low performers to let them know of their substandard performance? Warning Is goal-setting a part of you set of leadership practices? GoalSetting Are individual goals set for more than half of your employees? IndGoalSetting Do you systematically measure if goal-setting is contributing to improved performance for the majority of your employees? MeasGoalSetting Do you provide regular performance feedback to your employees? PerfFeedback Do you conduct annual performance-review meetings for at least key employees? PerfMeetings Are annual performance-review meetings conduced effectively and thus significantly contribute to improved performance? ImproPerf M. DRENKOVSKA, T. REDEK | INTANGIBLE CAPITAL, INNOVATION AND EXPORT-LED GROWTH.... 59 Constructs Item Abbreviation Relational capital Obtaining information about changes of customer preferences and needs. InfoCust Acquiring real time information about competitors. InfoComp Establishing and managing long-term customer relations. LongtermCust Establishing and managing long-term relations with suppliers. LongtermSupp Radical innovation Mark the relevance of the following types of new products in your company: Extensions to existing product lines / services. Extensions Mark the relevance of the following types of new products in your company: New product lines / services. NewLines Mark the relevance of the following types of new products in your company: New products / services that are novelties also in global markets. GlobalNovelties Exporting volume A dummy variable: 1 if the company exports above 50% (25% for the less developed economies) of its output, 0 if otherwise Export Table A2: Intellectual Capital in firms (% that answered positively) Slovenia Pooled Question (N = 73) (N =52 ) Management’s influence on decision-making The decision making process about strategic questions of the firm as a whole is separated from the operational decision making process at different levels. 81 % 70 % Top managers and owners unanimously reach strategic decisions. 73 % 60 % The basic strategic decisions are coordinated among owners, managers and workers. 63 % 45 % Workers’ participation in risk sharing Most workers are prepared to do “something more” for the firm 89 % 81 % Workers engage in additional training (apart from training organized by the firm) 70 % 64 % Most workers would stay with the firm even upon being offered better conditions elsewhere 59 % 45 % Most workers are willing to accept a part of the business risk (e.g. financial investment in the firm or deferred payment) 26 % 25 % Workers’ participation in the workplace There an increased need for workers to work in work groups given the nature of the work processes 90 % n/a Cooperating in different teams within individual departments is common 77 % n/a ECONOMIC AND BUSINESS REVIEW | VOL. 17 | No. 1 | 2015 60 Slovenia Pooled Question (N = 73) (N =52 ) There is a strong presence of workers’ cooperation between different departments which results in interdepartmental teams 68 % n/a Workers’ participation in decision making Workers are informed on key decisions 92% 60% There is open dialog with the workers regarding key decisions for the firm 84% 51% There are workers’ representatives in governing bodies and are involvedin the decision making process 55% 25% Human capital and motivation – learning The company provides regular on the job training 99% 68% The company systematically induces knowledge transfer among employees 81% 75% There are successors for most of the key employees 38% 66% Human capital and motivation – performance Performance is measured in such a way that you it clearly distinguishes between high and low performers 90% 87% Better performers are better rewarded than average performers 93% 94% Low performers are given different warnings (other than oral reprimand) 64% 83% Table A3: Relational capital in firms (means and standard deviations) Slovenia Pooled Question (N = 73) (N =52 ) Relational capital * mean s.d. mean s.d. Obtaining information about changes of customer preferences and needs 3.00 0.85 2.98 1.57 Acquiring real time information about competitors 3.14 0.82 2.98 1.42 Establishing and managing long-term customer relations 3.60 0.92 3.09 1.62 Establishing and managing long-term relations with suppliers 3.52 0.93 3.23 1.69 *Measured on a Likert scale between 1 and 5 (1 - considerably worse than the main competitors to 5 - consider- ably better than the main competitors) M. DRENKOVSKA, T. REDEK | INTANGIBLE CAPITAL, INNOVATION AND EXPORT-LED GROWTH.... 61 Table A4: Importance of radical innovation in firms (means and standard deviations) Slovenia Pooled Question (N = 73) (N =52 ) Relevance of types of new products * mean s.d. mean s.d. Repositioning of existing products on the market 1.88 0.98 1.57 1.20 Improving existing products 2.53 0.70 1.94 1.21 Extensions to existing product lines 2.10 0.77 1.72 1.66 New product lines 2.08 0.99 1.57 1.20 New products that are novelties also in global markets 1.26 1.14 1.15 1.21 *Measured on a Likert scale between 1 and 3 (1-low relevance, 2-medium relevance, 3-high relevance) ECONOMIC AND BUSINESS REVIEW | VOL. 17 | No. 1 | 2015 62 APPENDIX B – MODEL VALIDATION Table B1: T-statistics for Convergent Validity: Slovenia Construct Indicator T-statistic Human Capital OTJTrain HC 8.185** KnowTrans HC 14.989*** MeasPerf HC 7.150** Rewards HC 21.528*** Relational Capital InfoCust RC 45.361*** InfoComp RC 12.790*** LongtermCust RC 67.705*** LongtermSupp RC 76.731*** Structural Capital CooperTeams SC 6.746** OpenDialogue SC 9.740** Innovation Extensions RI 18.469*** NewLines RI 10.784*** GlobalNovelties RI 12.481*** ***p<0.001 **p<0.05 Table B2: A VE Scores: Slovenia Construct AVE HC (Human Capital) 0.5094 RC (Relational Capital) 0.7317 SC (Structural Capital) 0.5713 INN (Innovation) 0.5700 M. DRENKOVSKA, T. REDEK | INTANGIBLE CAPITAL, INNOVATION AND EXPORT-LED GROWTH.... 63 Table B3: T-statistics for Convergent Validity: Pooled Albania and Republika Srpska Construct Indicator T-statistic Human Capital OTJTrain HC 21.705*** KnowTrans HC 24.681*** MeasPerf HC 15.144*** Rewards HC 15.449*** Relational Capital InfoCust RC 109.076*** InfoComp RC 35.420*** LongtermCust RC 173.208*** LongtermSupp RC 221.149*** Structural Capital AddTraining SC 50.095*** OpenDialogue SC 60.681*** Innovation Extensions RI 89.772*** NewLines RI 48.674** GlobalNovelties RI 37.851*** ***p<0.001 **p<0.05 Table B4: A VE Scores: Pooled Construct AVE HC (Human Capital) 0.5239 RC (Relational Capital) 0.8587 SC (Structural Capital) 0.7235 INN (Radical Innovation) 0.7534 Table B5: Cross Loadings of Measurement Items to Latent Constructs for Slovenia Construct Item HC SC RC RI HC OTJTrain 0.6972 0.1378 0.3189 0.0728 HC KnowTrans 0.7161 0.4021 0.4171 0.1427 HC MeasPerf 0.5969 -0.1492 0.3001 0.1105 HC Rewards 0.8262 0.0235 0.4294 0.1833 SC CooperTeams 0.0889 0.6903 0.1811 0.1994 SC OpenDialogue 0.2193 0.8162 0.149 0.2277 RC InfoCust 0.4441 0.135 0.8458 0.2338 RC InfoComp 0.1795 0.115 0.7279 0.232 RC LongtermCust 0.56 0.2277 0.9181 0.1223 RC LongtermSupp 0.4977 0.2272 0.9158 0.1335 INN Extensions 0.1396 0.3263 0.2391 0.8253 INN NewLines -0.0725 0.09 0.0266 0.7236 INN GlobalNovelties 0.2132 0.1215 0.0784 0.7107 ECONOMIC AND BUSINESS REVIEW | VOL. 17 | No. 1 | 2015 64 Table B6: Cross Loadings of Measurement Items to Latent Constructs for polled Albania and Republika Srpska of Bosnia and Herzegovina Construct Item HC SC RC RI HC OTJTrain 0.7336 0.5122 0.2843 0.107 HC KnowTrans 0.7598 0.4181 0.2067 0.1583 HC MeasPerf 0.7073 0.4041 0.017 0.2586 HC Rewards 0.6928 0.3391 0.2059 0.3616 SC AddTraining 0.4671 0.8492 0.1373 0.4248 SC OpenDialogue 0.5239 0.852 0.2248 0.3155 RC InfoCust 0.3027 0.2629 0.9176 0.364 RC InfoComp 0.0749 0.0988 0.8818 0.3173 RC LongtermCust 0.2816 0.2282 0.9458 0.3909 RC LongtermSupp 0.2395 0.1633 0.9596 0.3555 INN Extensions 0.2607 0.4375 0.4442 0.8998 INN NewLines 0.3247 0.3914 0.2283 0.8884 INN GlobalNovelties 0.1949 0.2781 0.3005 0.8133 Table B7: Correlations of the Latent Scores with the Square Root of A VE Slovenia HC RI RC SC HC 0.5094 0 0 0 INN 0.03404 0.57 0 0 RC 0.276571 0.038259 0.7317 0 SC 0.045071 0.080089 0.046096 0.5713 Table B8: Correlations of the Latent Scores with the Square Root of A VE Pooled HC RI RC SC HC 0.5239 0 0 0 INN 0.09018 0.7534 0 0 RC 0.066203 0.150777 0.8587 0 SC 0.339539 0.189138 0.045412 0.7235 M. DRENKOVSKA, T. REDEK | INTANGIBLE CAPITAL, INNOVATION AND EXPORT-LED GROWTH.... 65 Table B9: Reliability Scores Slovenia Construct Composite Reliability Cronbach’s α HC 0.8039 0.6923 INN 0.7983 0.6621 RC 0.9154 0.8798 SC 0.7258 0.2539 Table B10: Reliability Scores Pooled Construct Composite Reliability Cronbach’s α HC 0.8147 0.6978 INN 0.9014 0.8391 RC 0.9605 0.9454 SC 0.8396 0.6178 ECONOMIC AND BUSINESS REVIEW | VOL. 17 | No. 1 | 2015 66 APPENDIX C - Tests for Common Methods Bias Table C1: Common Method Bias analysis – Slovenia Construct Item Substantive Factor Loading (λ n ) Variance Explained (λ n 2 ) Method Factor Loading (λ m ) Variance Explained (λ m 2 ) HC OTJTrain 0.834*** 0.696 -0.119 0.014 KnowTrans 0.223*** 0.050 0.410*** 0.168 MeasPerf 0.874*** 0.764 -0.183*** 0.033 Rewards 0.880*** 0.774 0.019 0.000 SC CooperTeams 0.759*** 0.576 0.023 0.001 OpenDialogue 0.754*** 0.569 -0.024 0.001 RC InfoCust 0.854*** 0.729 0.003 0.000 InfoComp 1.368*** 1.871 -0.643*** 0.413 LongtermCust 0.577*** 0.333 0.345*** 0.119 LongtermSupp 0.729*** 0.531 0.185*** 0.034 INN Extensions 0.737*** 0.543 0.096 0.009 NewLines 0.908*** 0.824 -0.155*** 0.024 GlobalNovelties 0.663*** 0.440 0.084 0.007 Average 0.782 0.669 0.003 0.063 Table C2: Common Method Bias analysis – Pooled Construct Item Substantive Factor Loading (λ n ) Variance Explained (λ n 2 ) Method Factor Loading (λ m ) Variance Explained (λ m 2 ) HC OTJTrain 0.652*** 0.425 0.089 0.008 KnowTrans 0.772*** 0.596 -0.020 0.000 MeasPerf 0.827*** 0.684 -0.156*** 0.024 Rewards 0.644*** 0.415 0.089 0.008 SC AddTraining 0.864*** 0.746 -0.024 0.001 OpenDialogue 0.837*** 0.701 0.024 0.001 RC InfoCust 0.818*** 0.669 0.118*** 0.014 InfoComp 1.060*** 1.124 -0.199*** 0.040 LongtermCust 0.864*** 0.746 0.095 0.009 LongtermSupp 0.974*** 0.949 -0.022 0.000 INN Extensions 0.741*** 0.549 0.178*** 0.032 NewLines 0.973*** 0.947 -0.100 0.010 GlobalNovelties 0.899*** 0.808 -0.083 0.007 Average 0.840 0.720 -0.001 0.012 M. DRENKOVSKA, T. REDEK | INTANGIBLE CAPITAL, INNOVATION AND EXPORT-LED GROWTH.... 67 APPENDIX D - Testing For Mediation Effects Figure D1: Full mediating effect of Structural Capital in the relationship between Human Capital and Innovation - Slovenia Figure D2: Partial mediating effect of Relational Capital in the relationship between Hu- man Capital and Innovation - Slovenia Total effects: Slovenia: 0.297*** Pooled: 0.353*** APPENDIX D - Testing For Mediation Effects Figure D1 Full mediating effect of Structural Capital in the relationship between Human Capital and Innovation - Slovenia Figure D2 Partial mediating effect of Relational Capital in the relationship between Human Capital and Innovation - Slovenia Effects after controlling for mediation: Slovenia: 0.229*** Pooled: 0.243 Total effects: Slovenia: 0.297*** Pooled: 0.353*** HUMAN CAPITAL RELATIONAL CAPITAL INNOVATION Effects after controlling for mediation: Slovenia: 0.046 Pooled: 0.086 Total effects: Slovenia: 0.297*** Pooled: 0.353*** HUMAN CAPITAL STRUCTURAL CAPITAL INNOVATION APPENDIX D - Testing For Mediation Effects Figure D1 Full mediating effect of Structural Capital in the relationship between Human Capital and Innovation - Slovenia Figure D2 Partial mediating effect of Relational Capital in the relationship between Human Capital and Innovation - Slovenia Effects after controlling for mediation: Slovenia: 0.229*** Pooled: 0.243 Total effects: Slovenia: 0.297*** Pooled: 0.353*** HUMAN CAPITAL RELATIONAL CAPITAL INNOVATION Effects after controlling for mediation: Slovenia: 0.046 Pooled: 0.086 Total effects: Slovenia: 0.297*** Pooled: 0.353*** HUMAN CAPITAL STRUCTURAL CAPITAL INNOVATION