319 Organizacija, Volume 53 Issue 4, November 2020Research Papers 1 Received: 2nd May 2020; revised: 5th October 2020; accepted: 12th October 2020 The Impact of Supply Chain Dynamic Capabilities on Operational Performance Mohanad Ali KAREEM1, Harsha Vardhan Reddy KUMMITHA2 1 Szent István University, Faculty of Economic Science, Kaposvár, Hungary, mohannadali25@gmail.com (Corre- sponding author) 2 Budapest Business School, Department of Hospitality and Tourism Budapest, Hungary, harshavardhankummitha@gmail.com Background and purpose: Literature is lacking on how supply chain dynamic capabilities influence operational performance. This study aims to empirically investigate the impact of supply chain dynamic capabilities on opera- tional performance in Hungarian manufacturing companies. Design/Methodology/Approach: The study used an online survey for data collection. The model is tested with data from 208 supply chain management professionals from Hungarian manufacturing industry. Structural equation modelling (SEM) was used to test the proposed hypotheses. Results: The empirical results indicate that supply chain dynamic capabilities namely; collaboration capability, agility capability, and responsiveness capability are significantly and positively associated with operational perfor- mance. However, the results show that integration capability has no significant impact on operational performance Conclusion: The study concludes that in a dynamic environment, developing supply chain dynamic capabilities can help manufacturing company managers to build effective supply chains and achieve superior performance. Further, managers need to recognize that supply chain dynamic capabilities are multidimensional and each dimension has different effects on operational performance. Also, the study provides theoretical and managerial implications that are further ‎discussed in detail. Keywords: Dynamic capabilities, Supply chain, Operational performance DOI: 10.2478/orga-2020-0021 1 Introduction The supply chain has become an increasingly sig- nificant area in business and academia. Due to the rapid economic growth, trends in globalization, and continuous changes in business environments. These challenges pre- vent firms from maintaining their competitive advantages through diagnosing the shifts in the business environment and sensing the opportunities and risks at the right time. Therefore, the key to survival in such situations requires the firms to develop capabilities that enable them to dis- tinguish their processes over competitors. Thus, the sus- tainable competitive advantages and superior operational performance of a firm rely on its dynamic supply chain capability (Ju et al., 2016). In a rapidly changing environ- ment where uncertainty is high, ordinary efficiency-orient- ed supply ‎chains are not appropriate enough to cope with the shifts in the business environment.‎ From the dynamic capabilities perspective, organizations need to adopt the supply chain dynamic capabilities, which enables the or- ganization to meet changes and successfully sustain the organization’s competitive positions and long-term prof- itability (Narasimhan, et al., 2004; Stevenson and Spring, 2007). Supply chain capabilities are the processes of inte- grating the internal and external competences, resources, and information to enhance supply chain practices. Many researchers and scholars have investigated the relationship between supply chain and operational perfor- mance. Morash (2001), Kristal et al. (2010), Miguel and Brito (2011) argue that supply chain practices positively 320 Organizacija, Volume 53 Issue 4, November 2020Research Papers enhance firm performance. Likewise, Gao & Tian, (2014) state that the supply chain positively impacts enterprise performance. Hong et al. (2019) claim that supply chain quality management significantly affect both operational performance and innovation performance. Yu et al. (2018) explore the impact of data-driven supply chain capabili- ties on financial performance. These reviews show that the existing literature is primarily focused on the traditional supply chain practices and their impact on operational per- formance in a static business environment. There has been rather limited research on supply chain dynamic capabilities, and how they can impact on firm performance in a dynamic business environment. Ju et al. (2016) argue that dynamic supply chain capabilities (in- formation sharing, collaboration, integration, and agility) have a significant and positive relationship with techno- logical innovation and operational performance of the or- ganization. Namusonge (2017) argues that supply chain capabilities influence firm performance. Mandal et al. (2016) state that supply chain capabilities of collaboration, flexibility, velocity, and visibility positively influence sup- ply chain resilience and supply chain performance. Some researchers have attempted to explore the indirect rela- tionship between supply chain capabilities and operational performance. (Fung & Chen, 2010) state that human capi- tal moderates the relationship between supply chain capa- bilities and firm performance. Oh et al. (2019) argue that supply chain capabilities influence a firm’s performance through the mediating role of information technology. Despite these efforts, the direct impact of supply chain dynamic capabilities has been largely ignored. To fill this gap in our understanding, this paper aims to investigate the impact of supply chain dynamic capabilities on opera- tional performance and attempts to empirically address the research question: How do dynamic supply chain capabilities influence operational performance? The objective of this paper is to answer this research question by proposing an empirical model that demon- strates that dynamic supply chain capabilities (collabora- tion capability, integration capability, agility capability, and responsiveness capability) have a positive impact on operational performance in the manufacturing industry in Hungary. The study contributes to the literature by giving a better understanding of the nature of the relationship ‎be- tween supply chain dynamic capabilities and operational performance. Also, this study ‎provides an empirical model that demonstrates the hypothesized relationship between supply chain dynamic capabilities and operational perfor- mance. The next parts of this paper are organized in the fol- lowing manner. Section two presents the literature review while section three discusses the methodology. The empir- ical results and findings are discussed in section four while section five provides the dissection and conclusion along with the theoretical and practical implications of the study. 2 Literature review and hypotheses development 2.1 Dynamic supply chain capabilities This study is based on the dynamic capabilities theory. The concept of dynamic ‎capabilities has emerged due to uncertainty and continual changes in the business ‎envi- ronment and market. The dynamic capabilities theory ‎was developed by Teece et al. (1997). They define dynamic ca- pabilities as a firm’s ability to build, ‎integrate and reconfig- ure its internal ‎and external resources and competences to cope with the rapid changes in the business ‎‎environment.‎ Zahra & George, (2002) argue that dynamic capabilities enable‎ firms to renew and reconfigure their resource base to meet evolving ‎customer demands and competitor strat- egies. The use of dynamic capabilities in the supply chain is becoming increasingly important (Witcher et al., 2008 & Allred et al., 2011). The emergence of dynamic capabili- ties in the supply chain are due to the changes in the long and short-term supply and demand, market structure and customer requirements (Ju et al., 2016). Therefore, firms must have dynamic supply chain capabilities to address these changes. Through dynamic supply chain capabilities, firms can create a collaborative relationship with ‎other or- ganizations, customers and suppliers and precisely predict market demands, in turn, ‎enhancing the supply chain re- sponsiveness to meet customer and supplier needs (Sand- ers, 2014). Several researchers have investigated the dynamic ca- pabilities from a supply chain perspective. Mathivathanan et al. (2017) argue that the development of dynamic capa- bilities through the supply chain has an important role to deal with future needs. Oh et al. (2019) describe dynamic supply chain capabilities as a firm’s ability to sense and exploit internal and external ‎resources in order to enhance supply chain practices efficiently and effectively. They also state that dynamic supply chain capabilities include sharing information, coordination, integration, and supply chain responsiveness. Ju et al. (2016) argue that dynam- ic supply chain capabilities are processes of information exchange, supply chain alignment, ‎and information tech- nology in order to meet customer needs and maintain competitiveness ‎in a dynamic environment.‎ Aslam et al. (2018) suggest that supply chain agility and adaptability are coherent components of dynamic supply ‎chain capa- bilities which should be integrated to support supply chain ambidexterity. Many studies (Teece, 2007; Ju et al, 2016 and Yu et al, 2018) argue that dynamic capabilities are the 321 Organizacija, Volume 53 Issue 4, November 2020Research Papers high-order capabilities and this can be disaggregated into different capacities. Thus, in our study, the supply chain dynamic capabilities were disaggregated into the collabo- ration capability, integration capability, agility capability, and responsiveness capability. Each of the four dimensions reflects a firm’s ability to meet customer needs and market requirements in order to achieve sustainable competitive advantage in a dynamic environment. Collaboration capability refers to a firm’s ability to build a long-term partnership in terms of supply chain ac- tivities and exchange of information, resources, and risk to achieve common objectives (Bowersox et al., 2002). Cao and Zhang (2011) argue that supply chain collaboration capability is an organization’s capability to share infor- mation, knowledge and resource, goal consistency. Yunus (2018) discusses that customer collaboration, supplier collaboration, and internal collaboration are important ele- ments to constitute the collaboration supply chain. Integration capability indicates the firm’s capacity to build strategic relationships and collaborate with its sup- ply chain partners (Flynn et al., 2010). Supply chain inte- gration emphasizes the availability of the right products, to the right consumers, at the right time at a competitive price (Angeles, 2009). Rajaguru and Matanda (2019) ar- gue that supply chain integration consists of information flow integration, physical flow integration, and financial flow integration. Agility capability refers to the firm’s ability to respond speedily to the changes and turbulence in the market in order to enhance its suppliers and customers (Aslam et al., 2018). Moreover, supply chain agility is a dynamically process to adjust or reconfigure the current business pro- cess to address the shits in the market and other uncer- tainty. Li et al., (2009) suggest that supply chain agility consists of important elements are strategic readiness and response capability, operational readiness and response capability, and episodic readiness and response capability. Responsiveness capability is defined as the ability of supply chain partners to respond to changes and shifts in the environment (Williams et al., 2013). Singh and Sharma (2015) allude that supply chain responsiveness emphasizes a reduction in lead time, improves service quality, quick response to a customer’s requirements, and transportation optimization. Shekarian et al., (2020) argue that respon- siveness in supply chain has three key elements: first, agil- ity to respond to customer ‎needs; second‎, flexibility to en- sues a new product development and entering new markets and third, reduce the risk of supply chain bottlenecks and disruptions.‎ 2.2 Operational performance In a dynamic environment, firms strive to obtain com- petitive advantages and achieve excellent organizational performance (Rajaguru and Matanda, 2019). Operational performance is related to the firm’s internal operations effi- ciency, which may enable the firm to enhance its competi- tiveness and profitability in the market (Hong et al., 2019). Operational performance is a multidimensional construct that includes the effective transformation of operational capabilities into competitive advantages of organizations. It can be assessed by productivity, quality, cost, delivery, flexibility, and customer satisfaction (Gambi et al., 2015; Ju et al., 2016; Saleh, et al., 2018). We now try to investi- gate and understand how dynamic supply chain capabili- ties interrelate and impact on operational performance as shown follows. 2.3 Supply chain collaboration capability’s contribution to operational performance Previous studies suggested that supply chain collabora- tion benefits include acquisition, sharing and development of new knowledge, learning capability, risk-sharing, and collaborative communication (Cao et al., 2010). Simatu- pang and Sridharan (2005) propose a supply chain collabo- ration index to measure the level of collaborative practices and find that the collaboration index positively impacts on operational performance. Cao and Zhang, (2011) argue that supply chain collaboration enhances collaborative advantage that enables supply chain partners to improve synergies and achieve superior performance. Jimenez et al. (2018) state that the supply chain collaboration with external partners boosts both incremental and radical inno- vations. Stank et al. (2001) suggest that both internal and external partnerships are important to ensure performance. Collaboration can increase profitability, reduce purchasing costs, and enhance technical cooperation. Thus, this study hypothesizes: H1: Collaboration capability has a significant positive impact on operational performance. 2.4 Supply chain integration capability’s contribution to operational performance Supply chain integration capability is a set of continu- ous restructuring activities to facilitate a firm to reorganiz- ing processes and resources more effectively, thus enhanc- ing operational performance (Chen et al., 2009; Wu et al., 2006) argue that supply chain integration capabilities that are established with the organizational processes are likely to have a good potential to achieve a set of organizational performance. Oh et al. (2016) state that supply chain inte- gration contributes to improving firm performance through reducing the bullwhip effect in the supply chain and sup- 322 Organizacija, Volume 53 Issue 4, November 2020Research Papers port a firm to respond to demands of the market more quickly. Flynn et al. (2010) insatiate the impact of supply chain integration on operational performance. They found that supply chain integration was significantly related to both operational and business performance. Furthermore, the results indicated that internal and customer integration were more strongly related to improving performance than supplier integration. Accordingly, we hypothesize that: H2: Integration capability has a significant positive im- pact on operational performance. 2.5 Supply chain agility capability contributes to operational performance In today’s dynamic and uncertain business environ- ment, firms need to pay efforts to their supply chain risk to boost the agility and resilience of their supply chain sys- tems (Tang and Tomlin, 2008). Supply chain agility capability enables a firm to effec- tively match the internal and external resources to market changes. This capability helps a firm’s efforts to take ad- vantage of opportunities or counteract threats from turbu- lent environments (Van Hoek et al., 2001), which may lead to the achievement or maintenance of a competitive posi- tion (Eisenhardt and Martin 2000). Many studies state that the continuous improvement in supply chain agility capa- bility, that is, improving ‎the responsiveness to changes at small costs, has a positive impact on firm ‎performance and competitiveness (Blome et al., 2013; Chakravarty et al., 2013; Oh et al., 2018). Moreover, (Vinodh et al., 2011) argue that supply chain agility may be able to enhance the operational performance by a more effective response to external supply disruptions, provides significant benefits for the internal processes of the firm, lower cost, improves quality, and delivery performance. Accordingly, we hy- pothesize that: H3: Agility capability has a significant positive impact on operational performance. 2.6 Supply chain responsiveness contributes to operational performance In today’s rapidly changing business environment, supply chain responsiveness has become a highly signif- icant capability of a firm’s supply chain system (Williams et al., 2013). Supply chain responsiveness is a firm’s abili- ty to responds quickly to changes in ‎consumer needs, pro- duction and delivery quantities and, product mix, volume, and delivery in response to shifts in demand and supply. These changes are most likely to lead to enhancing perfor- mance outcomes such as a lower production cost, greater customer satisfaction, and faster delivery (Yu et al., 2016). Moreover, (Prajogo and Olhager, 2016; Mandal et al., 2016) show that supply chain responsiveness positively impacts on operational performance. Accordingly, we hy- pothesize that: H4: Supply chain responsiveness capability has a sig- nificant positive impact on operational performance. This study develops an empirical research model con- sidering the above-mentioned hypothesizes ‎and theoretical background as it is shown in Fig.1. Figure 1: Conceptual model 323 Organizacija, Volume 53 Issue 4, November 2020Research Papers 3 Research Methodology 3.1 Questionnaire design and measures In order to assess the proposed hypotheses, we con- ducted a survey to managers, supervisors, and manage- ment personnel of manufacturing enterprises in Hungary. The survey instrument was developed based on the liter- ature. The survey questionnaire was created by the goog- le-forms tool. It was divided into three sections, namely: respondent and organization profile, dynamic supply chain capabilities, and operational performance. The measurements were developed based on an ex- tensive review of the literature. All measurements used a seven-point Likert scale. Dynamic supply chain capabil- ities were operationalized in four-dimensional constructs including collaboration capability, integration capability, agility capability, and ‎responsiveness capability. Twenty items used for measuring dynamic supply chain capabil- ities were adopted from Ju et al. (2016), Wu et al. (2006), Aslam‎ et al. (2018), Oh et al. (2019), Hong‎ et al. (2019), and Rajaguru & Matanda, (2019). Seven items measuring operational performance were adopted from Flynn‎ et al. (2010), Yu et al. (2018‎), and Rajaguru & Matanda, (2019). The list of measurement items is presented in Appendix 1. 3.2 Control variables The firm size and firm age were used as control varia- bles in our model. However, the firm type cannot be a con- trol variable for our study because we validate the research model using data collected from manufacturing firms (Hong et al., 2017). The firm age is a potential character- istic that has a considerable impact on firm performance. The number of employees was used as a proxy for the firm size because larger firms may have more resources for managing supply chain activities, and thus may achieve higher business performance than small firms (Yu et al., 2013). 3.3 Data collection and sample description This study collected data from manufacturing compa- nies in Hungary in the period 05/Jan.2020- 04/Mar.2020 by using an online questionnaire. To avoid the biases as- sociated with convenience sampling (Hong et al., 2017). Thus, the manufacturing companies were selected random- ly from the complete list of manufacturers in Hungary. The types of selected enterprises include private enterprises, state-owned enterprises, foreign-funded enterprises, and joint ventures. The investigated enterprises are involved in a wide range of activities such as furniture production, electricity production, clothing, pharmacy, food, electron- ic products, rubber, and plastic. The respondents mainly included several CEOs, presidents, directors, managers, supervisors, and senior staff who work in jobs related to supply chain management or operation management. We mailed the questionnaire, including a cover letter high- lighting the study’s objectives and the importance of the respondent’s cooperation. Out of 235 companies contact- ed, a total of 421 questionnaires were distributed, out of which 208 completed questionnaires were obtained, with a response rate of 49.40% of the respondents. We distributed more than one questionnaire from the same firm. Because of several managers representing different organizational levels at the same time for one firm. Thus, supply chain dynamic capabilities should be involved the opinions not only from the CEO or president but also from operations and supply chain managers. This approach has the benefit of providing an overall perspective from the top executives and an expert perspective from the relevant functional area of the firm (Li et al., 2008; Yu, 2017). The respondent profile information is presented in Ta- ble 1. It shows that the majority of the companies (23.6%) are food industry. Most of the companies at (33.2%) are private companies. A little lower than half of the inves- tigated companies were in the relatively large company classification of over 500 employees. Most of the compa- nies (36.5%) were more than 20 years old. Characteristics Categories Frequency Percentage（%（ Furniture production 18 8.7 Electricity production 21 10.1 Industry Clothing 15 7.2 Pharmacy 19 9.1 Food 49 23.6 Electronic products 45 21.6 Rubber and plastic 41 19.7 Table 1: Respondent profile information 324 Organizacija, Volume 53 Issue 4, November 2020Research Papers Type of firm State-owned company 35 16.8 Private company 69 33.2 Foreign-owned 62 29.8 Joint venture 42 20.2 Size (Employees) Less than 100 54 26.0 ‎‎100-300 37 17.8 301-500 28 13.5 501-1000 25 12.0 More than 1000 64 30.8 Age of firm Less than 4 years 13 6.3 4-5 years 33 15.9 6-10 years 29 13.9 11-20 years 57 27.4 More than 20 years 76 36.5 Table 1: Respondent profile information (continues) 4 Data analysis and results 4.1 Descriptive statistics Table 2 presents descriptive statistics such (mean, standard deviation, and correlation). The results show that the means score for all the constructs is located between (3.28-4.91) and standard deviation (0.83-1.04) which in- dicates that the firms have a good implementation of sup- ply chain dynamic capabilities. Also, the results show that each of the constructs is positively and significantly corre- lated with each other. 4.2 Reliability and Validity The reliability and validity of measurement scales were assessed by using confirmatory factor analysis (CFA), and AMOS 24 was used to estimate convergent validity and discriminant validity. The reliability of the scales was eval- uated using Cronbach’s alpha coefficient as seen in (Table 3). Cronbach’s alpha coefficient for all constructs ranges between 0.774 and 0.789 which are above the threshold value .50. This indicates that all the items are internally consistent (Hair et al., 2010). The convergent validity was determined in three important indicators, which are factor loadings (standardized estimates), Average Variance Ex- tracted (AVE), and Composite Reliability (CR). This study establishes that out of a total of 27 initial items, 24 items have been maintained (see in Table 3). This indicates that the 3 items were deleted because of poor loadings. The remaining 24 items retained should be loaded highly on one factor with a factor loading of 0.50 or greater and statistically significant (p<0.05) as recom- mended by Hair et al. (2010). Composite reliability (CR) for all constructs ranges between 0.830 and 0.898 which are above 0.50, indicating that all the constructs demon- strate a good level of composite reliability (CR) as rec- ommended by Hair et al. (2012). The average variance extracted (AVE) value for all the constructs is located be- tween 0.707 to 0.764 which is above the threshold value (.50) which is suggested by Hair et al., (2010). Discriminant validity was examined by using (For- nell & Larcker, 1981) method. They suggested that if the Table 2: Descriptive statistics Mean S.D. CC IC AC RC OP CC 3.53 0.92 1 IC 3.37 0.87 0.624** 1 AC 3.49 0.83 0.603** 0.9510** 1 RC 3.28 0.91 0.547** 0.638** 0.680** 1 OP 4.91 1.04 0.480** 0.551** 0.689** 0.627** 1 **. Correlation is significant at the 0.01 level (2-tailed). CC= Collaboration capability, IC= Integration capability, AC=Agility capability, RC= Responsiveness capability, OF= Operational ‎perfor- mance. Measurement Items used for the constitution of the listed variables are presented in Appendix 1. 325 Organizacija, Volume 53 Issue 4, November 2020Research Papers Table 3: CFA results: reliability and validity. a= Cronbach’s alpha, CR = Composite Reliability and Average, AVE=Variance Extracted Constructs Measurement Items Factor Loading a CR AVE P.Value Collaboration capa- bility CC1 0.717 0.778 0.878 0.716 0.000 CC2 0.774 0.000 CC3 0.787 0.000 CC4 0.723 0.000 CC5 deleted Integration capability IC1 0.624 0.783 0.830 0.751 0.000 IC2 deleted IC3 0.614 0.000 IC4 0.591 0.000 IC5 0.635 0.000 Agility capability AC1 0.688 0.785 0.887 0.727 0.000 AC2 0.621 0.000 AC3 0.572 0.000 AC4 0.683 0.000 AC5 0.695 0.000 Responsiveness capability RC1 0.559 0.774 0.874 0.707 0.000 RC2 0.685 0.000 RC3 0.583 0.000 RC4 0.581 0.000 RC5 0.663 0.000 Operational performance OP1 0.599 0.789 0.898 0.764 0.000 OP2 0.669 0.000 OP3 deleted 0.000 OP4 0.614 0.000 OP5 0.611 0.000 OP6 0.601 0.000 OP7 0.687 0.000 square root of the AVE for a latent construct is greater than the correlation values among all the latent variables that means discriminant validity is supported. Table 4 shows that the square root of the AVE values of all the constructs is greater than the inter-construct correlations which confirm discriminant validity. Also, Hair et al. (2010) suggest that if AVE for a latent construct is larger than the maximum shared variance (MSV) with other latent constructs that provides evidence of discriminant validity. The goodness- of-fit measures were used to assess the fitness of a meas- urement model. The results confirm an adequate model fit (CMIN/df= 1.431, GFI=0.873, TLI= 0.898, CFI=0.899, RMSEA=0.047). Thus, the measurement model indicates good construct validity and reliability. 326 Organizacija, Volume 53 Issue 4, November 2020Research Papers 4.3 Common method bias checks The Harman one-factor test (Podsakoff & Organ, 1986) was used to test for common method bias. A princi- pal component analysis (PCA) was performed for all the items included in the study. The results show that the total variance for a single factor is less than 50%. We conclude that common method bias does not confound the interpre- tations of the results. Table 4: Discriminant validity Notes: Bold values in diagonal represent the squared root estimate of AVE. AVE= Average Variance Extracted, MSV= Maximum shared variance. AVE MSV CC IC AC RC OP CC 0.716 0.568 0.846 IC 0.751 0.466 0.332 0.867 AC 0.727 0.604 0.432 0.478 0.853 RC 0.707 0.504 0.664 0.603 0.332 0.841 OP 0.764 0.361 0.621 0.731 0.635 0.719 0.874 4.4 Test of hypotheses The structural equation modeling (SEM) was used ‎to test empirically the proposed hypotheses. The results of the hypothesis test are shown in Table 5 and Fig. 3. The results show that collaboration capability (B=0.446, p<0.001), agility capability (B=0.552, p<0.001), and re- sponsiveness capability (B=0.266, p<.0.021) significant- ly and positively impact on an operational performance, which strongly supports H1, H3, and H4. However, there was no significant relationship between integration capa- bility (B=0.096, p<0.373) and operational performance. Hence, H2 is rejected. Table 5: Result of hypothesis Test NO. Hypotheses Beta Coeffi- cient P.Value Result H1 Collaboration capability→ Operational Performance 0.446 0.00 Supported H2 Integration Capability → Operational Performance 0.096 .373 Not Supported H3 Agility Capability → Operational Performance 0.552 0.00 Supported H3 Responsiveness Capability → Operational Performance 0.266 .021 Supported 327 Organizacija, Volume 53 Issue 4, November 2020Research Papers Figure 2: The SEM model analysis 5 Discussion and conclusion This study investigates the interaction impact between supply chain dynamic capabilities and operational per- formance. In particular, we evaluate the impact of four supply chain dynamic capabilities, namely collaboration capability, integration capability, agility capability, and responsiveness capability on the operational performance of manufacturers in Hungary. The study revealed four key findings. First, we find that collaboration capability has a significant positive impact on operational performance. This is in line with the results of Yu et al. (2018). They argue that when a firm builds a good relationship with part- ners, collaboration supply chain capability has a potential impact on firm operational performance. Our finding is also consistent with the results of Cao and Zhang, (2011) which indicate that supply chain collaboration capability improves collaborative advantage, in turn, positively im- pacts firm performance. Second, this study finds that inte- gration supply chain capability has no significant impact on operational performance. This finding is significantly different from some previous studies. For example, Flynn et al. (2010) argue that integration supply chain capabili- ty positively influences operational performance through customer and supplier integration. However, a potential reason for the inconsistent findings may be due to the fact that it is not an easy task for firms and their partners to implement effective integration supply chain to ensure their objectives (Shashi et al., 2019). Third, we find that agility supply chain capability has the highest significant positive relationship with operational performance. This is in line with the results of (Aslam et al., 2018). They state that supply chain agility capability enables a firm to grab opportunities in the marketplace that may enhance the firm’s performance. Our findings are also consistent with the results of Oh et al. (2018). They argue that the agility supply chain contributes to a firm’s operational perfor- mance through the quick speed to market and customer satisfaction. Fourth, this study finds that supply chain re- sponsiveness capability positively influences operational performance. This is in line with the results of Aslam et al. (2018) and Hong et al. (2019). They argue that a firm’s ability to respond quickly to changing consumer needs, to competitors’ strategies, and to develop new products quickly can improve its performance. Finally, this study concludes that in a changing environment, supply chain dynamic capabilities such as collaboration capability, agil- ity capability, and responsiveness capability have a posi- tive impact on operational performance. 328 Organizacija, Volume 53 Issue 4, November 2020Research Papers 5.1 Theoretical contributions This study provides two important theoretical con- tributions. First, although researches on the supply chain have attracted considerable attention in literature, very limited researches have been done on supply chain dynam- ic capabilities. Therefore, this study introduces an empir- ical approach to investigating the impact of supply chain dynamic capabilities on operational performance. Thus, it has important potential to fills the gap in the literature. Second, the study contributes to supply chain literature by demonstrating a clear understanding of the specific supply chain dynamic capabilities that firms need to develop in order to enhance operational performance. Moreover, we find that these supply chain dynamic capabilities are mul- tidimensional, measurable, and applicable which will help scholars to use these measurements in future research. 5.2 Managerial implications This study provides important practical implications for manufacturers. To survive in changing environments, managers should recognize the role of supply chain dy- namic capabilities in improving operational performance. Our results confirm that collaboration capability, agility capability, and responsiveness capability are significantly and positively associated with operational performance. Also, the results show that integration capability has no positive association with operational performance. The study suggests that building these capabilities can help manufacturing managers to build effective supply chains and achieve superior performance. Further, managers need to recognize that supply chain dynamic capabilities are multidimensional and each dimension has differential effects on operational performance. Thus, manufacturing firm managers have to focus on the supply chain dynamic capabilities that need to be targeted to improve operational performance. 5.3 Limitations and future research This study has some limitations that need to be ad- dressed in future research. First, the study applied cross-sectional research design, thus findings of this study cannot be considered as definitive evidence of the under- lying causal relationships. Future research may use a lon- gitudinal research design that could give conclusive evi- dence for the highlighted relationships. Second, this study used self-reported data for measuring the variables of the study. Future research may employ dataset with knowl- edgeable informants from each firm that may enhance the validity of the findings. Third, this study focuses on four dimensions of supply chain dynamic capabilities. Future research should consider other potential dimensions. Literature Allred, C., Fawcett, S., Wallin, C., & Magnan, G. (2011). 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International Jour- nal of Innovation Science, 10(3), 350-370. https://doi. org/10.1108/IJIS-05-2017-0039 Zahra, S., & George, G. (2002). The net-enabled business innovation cycle and the evolution of dynamic capabil- ities. Information Systems Research, 13(2), 147–155. https://doi.org/10.1287/isre.13.2.147.90 Mohanad Ali Kareem is a Ph.D. candidate at Kaposvár University, Faculty of Economic Science, Doctoral School of Management and Organizational Science, Hungary. His research focuses on human resources management, strategic management, and organizational behavior. Harsha Vardhan Reddy Kummitha is a researcher associate at Budapest Business School, Department of Hospitality and Tourism. Budapest, Hungary. His research focuses on sustainable tourism, ecotourism, eco-entrepreneurship. 331 Organizacija, Volume 53 Issue 4, November 2020Research Papers Vpliv dinamičnih zmožnosti dobavne verige na operativno uspešnost Ozadje in namen: V literaturi najdemo malo raziskav o tem, kako dinamične zmogljivosti dobavne verige vplivajo na njeno operativno uspešnost. Namen te študije je empirično raziskati vpliv dinamičnih zmožnosti dobavne verige na operativne rezultate v madžarskih proizvodnih podjetjih. Zasnova / metodologija / pristop: Študija je uporabila spletno anketo za zbiranje podatkov, v kateri je sodelovalo 208 strokovnjakov za upravljanje dobavne verige iz madžarske predelovalne industrije. Za testiranje predlaganih hipotez so uporabili modeliranje strukturnih enačb (SEM). Rezultati: Empirični rezultati kažejo, da so dinamične zmogljivosti oskrbovalne verige, namreč; sposobnost sodelo- vanja, sposobnost prilagajanja in odzivnost pomembno in pozitivno povezane z operativno učinkovitostjo. Rezultati pa kažejo, da zmožnost integracije nima pomembnega vpliva na operativno uspešnost. Zaključek: Študija ugotavlja, da lahko v dinamičnem okolju razvoj dinamičnih zmogljivosti oskrbovalne verige po- maga vodjem proizvodnih podjetij, da zgradijo učinkovite dobavne verige in dosežejo boljše rezultate. Nadalje mo- rajo upravitelji prepoznati, da so dinamične zmogljivosti dobavne verige večdimenzionalne in ima vsaka dimenzija različne učinke na operativno uspešnost. Študija podaja tudi teoretične in vodstvene posledice, ki so podrobneje predstavljene v članku. Ključne besede: Dinamične zmogljivosti, Dobavna veriga, Operativna uspešnost Appendix A. List of Measurement Items: Supply Chain Dynamic Capabilities Collaboration Capability CC1: Our company operates an agreement with partners CC2: Our company collaborates actively in group decision making with partners CC3: Our company collaborates actively in group problem solving with partners CC4: Our company has a good relationship with partners CC5: Our company develops strategic plans in ‎collaboration with our partners. Integration capability IC1: Our company ensures the standardization of data with partners IC2: Our company ensures integration of information system with partners IC3: Our company removes repetition with partners IC4: Our company ensures data consistency with partners IC5: Our company always forecasts and plans activities collaboratively with our partner Agility capability AC1: Our company adapts services and/or products to new customer requirements quickly AC2: Our company reacts to new market developments quickly AC3: Our company reacts to significant increases and decreases in demand quickly AC4: Our company adjusts product portfolio as per market requirement AC5: Our company responds to competitors strategy change more quickly than our competitors Responsiveness capability RC1: Our company responds quickly to changing consumer needs RC2: Our company ensures feedback to suppliers more quickly and effectively RC3: Our company responses to the quality strategy of competitors more quickly and effectively RC4: Our company responds quickly to changing scope of supply RC5: Our company responses to the risk of the supply chain more quickly and effectively Operational performance OP1: Our company’s effectiveness in fulfilling requirements. OP2: Our company’s effectiveness in responding to changes in market demand. OP3: Our company’s effectiveness in on-time delivery. OP4: Our company’s effectiveness in delivering reliable quality products. OP5: Reduction in lead time to fulfill customers’ orders. OP6: Reduction in overhead costs OP7: Reduction in inventory costs