Share:


Effective factors of implementing efficient supply chain strategy on supply chain performance

Abstract

Nowadays, the importance of supply chain management and its effect on business performance is undeniable. Boosting competitive environment makes every single firm adopt an assignable supply chain strategy. This study is one of the rare practical researches that recognize key factors related to the application of a successful and efficient supply chain strategy. So far, many researchers have conducted studies on responsive supply chain strategy; but in this study, it is sought to focus on efficient supply chain strategies due to increasing need for organizations to enhance efficiency and reduce costs. Structural equation modelling using SmartPLS software is used to examine the research assumptions. Analysis of the structural model showed that there is a positive relationship between implementation of efficient supply chain strategy with supply chain performance; therefore the main research hypothesis is confirmed. Research revealed internal integration, top management support and information technology as efficient supply chain characteristics that have positive effects on supply chain performance. To reduce costs of implementation of efficient supply chain strategy, it is necessary to invest in factors that influence supply chain performance positively.

Keyword : supply chain, efficiency, performance, strategy, information technology, structural equation modelling

How to Cite
Daneshvar, M., Razavi Hajiagha, S. H., Tupėnaitė, L., & Khoshkheslat, F. (2020). Effective factors of implementing efficient supply chain strategy on supply chain performance. Technological and Economic Development of Economy, 26(4), 947-969. https://doi.org/10.3846/tede.2020.12827
Published in Issue
Jul 2, 2020
Abstract Views
3190
PDF Downloads
3549
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Adenso-Diaz, B., Moreno, P., Gutierrez, E., & Lozano, S. (2012). An analysis of the main factors affecting bullwhip in reverse supply chains. International Journal of Production Economics, 135(2), 917–928. https://doi.org/10.1016/j.ijpe.2011.11.007

Akcay, E. C., Ergan, S., & Arditi, D. (2017). Modeling information flow in the supply chain of structural steel components. Journal of Civil Engineering and Management, 23(6), 753–764. https://doi.org/10.3846/13923730.2017.1281841

Akter, S., D’Ambra, J., & Ray, P. (2011). An evaluation of PLS based complex models: the roles of power analysis, predictive relevance and GoF index. In Proceedings of the 17th Americas Conference on Information Systems (AMCIS2011) (pp. 1–7). Association for Information Systems.

Al-Abdallah, G., Abdallah, A., & Hamdan, K. B. (2014). The impact of supplier relationship management on competitive performance of manufacturing firms. International Journal of Business and Management, 9(2), 192–202. https://doi.org/10.5539/ijbm.v9n2p192

Ali, F., Rasoolimanesh, S., Sarstedt, M., Ringle, C., & Ryu, K. (2018). An assessment of the use of partial least squares structural equation modeling (PLS-SEM) in hospitality research. International Journal of Contemporary Hospitality Management, 30(1), 514–538. https://doi.org/10.1108/IJCHM-10-2016-0568

Amoozad Mahdiraji, H., Beheshti, M., Razavi Hajiagha, S. H., & Zavadskas, E. K. (2018). A fuzzy binary bi objective transportation model: Iranian steel supply network. Transport, 33(3), 810–820. https://doi.org/10.3846/transport.2018.5800

Amoozad Mahdiraji, H., Govindan, K., Zavadskas, E. K., & Razavi Hajiagha, S. H. (2014). Coalition or decentralization: a game-theoretic analysis of a three-echelon supply chain network. Journal of Business Economics and Management, 15(3), 460–485. https://doi.org/10.3846/16111699.2014.926289

APICS. (2016). APICS dictionary (15th ed.).

Bai, C., & Sarkis, J. (2018).Evaluating complex decision and predictive environments: The case of green supply chain flexibility. Technological and Economic Development of Economy, 24(4), 1630–1658. https://doi.org/10.3846/20294913.2018.1483977

Baumgartner, H., & Homburg, C. (1996). Applications of structural equation modeling in marketing and consumer research: A review. International Journal of Research in Marketing, 13(2), 139–161. https://doi.org/10.1016/0167-8116(95)00038-0

Bayraktar, E., Lenny Koh, S. C., Gunasekaran, A., Sari, K., & Tatoglu, E. (2008). The role of forecasting on bullwhip effect for E-SCM applications. International Journal of Production Economics, 113(1), 193–204. https://doi.org/10.1016/j.ijpe.2007.03.024

Birhanu, D., Lanka, K., & Rao, A. N. (2014).A survey of classifications in supply chain strategies. Procedia Engineering, 97, 2289–2297. https://doi.org/10.1016/j.proeng.2014.12.473

Brynjolfsson, E., & Hitt, L. M. (2000). Information technology, organizational transformation and business performance. Journal of Economic Perspectives, 14(4), 23–48. https://doi.org/10.1257/jep.14.4.23

Calhoun, C. (2009). What good is commitment? Ethics, 119(4), 613–641. https://doi.org/10.1086/605564

Chatterjee, K., Pamucar, D., & Zavadskas, E. K. (2018). Evaluating the performance of suppliers based on using the R’AMATEL-MAIRCA method for green supply chain implementation in electronics industry. Journal of Cleaner Production, 184, 101–129. https://doi.org/10.1016/j.jclepro.2018.02.186

Chelariu, C., Asare, A. K., & Brashear-Alejandro, T. (2014). “A ROSE, by any other name”…: relationship typology and performance measurement in supply chains. Journal of Business & Industrial Marketing, 29, 332–343. https://doi.org/10.1108/JBIM-08-2013-0178

Chen, F., Drezner, Z., Ryan, J. K., & Simchi-Levi, D. (2000). Quantifying the bullwhip effect in a simple supply chain: The impact of forecasting, lead times, and information. Management Science, 46(3), 436–443. https://doi.org/10.1287/mnsc.46.3.436.12069

Cheung, W., Chiang, A.-H., Sambamurthy, V., & Setia, P. (2018). Lean vs. agile supply chain: The effect of IT architectures on supply chain capabilities and performance. Pacific Asia Journal of the Association for Information Systems, 10(1), Article 4. https://doi.org/10.17705/1pais.10103

Chin, W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Methodology for business and management. Modern methods for business research (pp. 295–336). Lawrence Erlbaum Associates.

Chin, K.-S., Rao Tummala, V. M., Leung, J. P. F., & Tang, X. (2004). A study on supply chain management practices. International Journal of Physical Distribution & Logistics Management, 34(6), 505–524. https://doi.org/10.1108/09600030410558586

Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Lawrence Earlbaum Associates.

Colin, M., Galindo, R., & Hernandez, O. (2015). Information and communication technology as a key strategy for efficient supply chain management in manufacturing SMEs. Procedia Computer Science, 55, 833–842. https://doi.org/10.1016/j.procs.2015.07.152

Cox, J. F., Blackstone, J. H., & Spencer, M. S. (Eds.). 1995. APICS dictionary. American Production and Inventory Control Society.

Do Valle, P. O., & Assaker, G. (2015). Using partial least squares structural equation modeling in tourism research: A review of past research and recommendations for future applications. Journal of Travel Research, 55(6), 695–708. https://doi.org/10.1177/0047287515569779

Dubey, R., Gunasekaran, A., Childe, S. J., Papadopoulos, T., & Helo, P. (2019). Supplier relationship management for circular economy: Influence of external pressures and top management commitment. Management Decision, 57(4), 767–790. https://doi.org/10.1108/MD-04-2018-0396

Falk, R. F., & Miller, N. B. (1992). A primer for soft modeling. University of Akron Press.

Fan, Y., Chen, J., Shirkey, G., John, R., Wu, S.R., Park, H., & Shao, Ch. (2016). Applications of structural equation modelling (SEM) in ecological studies: an updated review. Ecological Processes, 5, 1–12. https://doi.org/10.1186/s13717-016-0063-3

Fisher, M. L. (1997). What is the right supply chain for your product?. Harvard Business School.

Fornell, C., & Larker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104

Geisser, S. (1975). The predictive sample reuse method with applications. Journal of American Statistical Association, 70, 320–328. https://doi.org/10.1080/01621459.1975.10479865

Goffin, K., Lemke, F., & Szwejczewski, M. (2006). An exploratory study of ‘close’ supplier-manufacturer relationships. Journal of Operations Management, 24(2), 189–209. https://doi.org/10.1016/j.jom.2005.05.003

Hair, J. F., Sarstedt, M., Pieper, T. M., & Ringle, C. M. (2012). The use of partial least squares structural equation modeling in strategic management research: A review of past practices and recommendations for future applications. Long Range Planning, 45(5–6), 320–340. https://doi.org/10.1016/j.lrp.2012.09.008

Han, J. H., Wang, Y., & Naim, M. (2017). Reconceptualization of information technology flexibility for supply chain management: An empirical study. International Journal of Production Economics, 187, 196–215. https://doi.org/10.1016/j.ijpe.2017.02.018

Huo, B. (2012). The impact of supply chain integration on company performance: an organizational capability perspective. Supply Chain Management: An International Journal, 17(6), 596–610. https://doi.org/10.1108/13598541211269210

Huo, B., Zhang, C., & Zhao, X. (2015). The effect of IT and relationship commitment on supply chain coordination: A contingency and configuration approach. Information & Management, 52(6), 728– 740. https://doi.org/10.1016/j.im.2015.06.007

Johnsen, T. E., Johnsen, R. E., & Lamming, R. C. (2008). Supply relationship evaluation: The relationship assessment process (RAP) and beyond. European Management Journal, 26, 274–287. https://doi.org/10.1016/j.emj.2007.10.001

Ju, Q., Ding, L., & Skibniewski, M. J. (2017). Optimization strategies to eliminate interface conflicts in complex supply chains of construction projects. Journal of Civil Engineering and Management, 23(6), 712–726. https://doi.org/10.3846/13923730.2016.1232305

Kadivar, M., & Akbarpour Shirazi, M. (2018). Analyzing the behavior of the bullwhip effect considering different distribution systems. Applied Mathematical Modelling, 59, 319–340. https://doi.org/10.1016/j.apm.2018.01.028

Kannan, V. R., & Tan, K. C. 2010. Supply chain integration: cluster analysis of the impact of span of integration. Supply Chain Management: An International Journal, 15(3), 207–215. https://doi.org/10.1108/13598541011039965

Keshavarz-Ghorabaee, M., Amiri, M., Olfat, L., & Khatami Firouzabadi, S. M. A. (2017). Designing a multi-product multi-period supply chain network with reverse logistics and multiple objectives under uncertainty. Technological and Economic Development of Economy, 23(3), 520–548. https://doi.org/10.3846/20294913.2017.1312630

Khaksar, E., Abbasnejad, T., Esmaeili, A., & Tamošaitienė, J. (2016). The effect of green supply chain management practices on environmental performance and competitive advantage: a case study of the cement industry. Technological and Economic Development of Economy, 22(2), 293–308. https://doi.org/10.3846/20294913.2015.1065521

Kianpuor, K., Jusoh, A., Mardani, A., Štreimikienė, D., Cavallaro, F., Nor Khalil, M. D., & Zavadskas, E. K. (2017). Factors influencing consumers’ intention to return the end of life electronic products through reverse supply chain management for reuse, repair and recycling. Sustainability, 9(9), 1657. https://doi.org/10.3390/su9091657

Lam, J., & Rahma, Y. (2014). Top management commitment to lean – The effects of side-bets on the implementation’s success (Master Thesis). Halmstad.

Lambert, D. M., & Cooper, M. C. (2000). Issues in supply chain management. Industrial Marketing Management, 29, 65–83. https://doi.org/10.1016/S0019-8501(99)00113-3

Lawshe, C. H. (1975). A quantitative approach to content validity. Personnel Psychology, 28, 563–575. https://doi.org/10.1111/j.1744-6570.1975.tb01393.x

Lee, C. W., Kwon, I.-W. G., & Severance, D. (2007). Relationship between supply chain performance and degree of linkage among supplier, internal integration, and customer. Supply Chain Management, 12, 444–452. https://doi.org/10.1108/13598540710826371

Liou, J. H. J., Tamošaitienė, J., Zavadskas, E. K., & Tzeng, G.-H. (2016). New hybrid COPRAS-G MADM Model for improving and selecting suppliers in green supply chain management. International Journal of Production Research, 54(1), 114–134. https://doi.org/10.1080/00207543.2015.1010747

Liu, R., Zeng, Y. R., Qu, H. & Wang, L. (2018). Optimizing the new coordinated replenishment and delivery model considering quantity discount and resource constraints. Computers & Industrial Engineering, 116, 82–96. https://doi.org/10.1016/j.cie.2017.12.014

Lillrank, P. (2003). The quality of standard, routine and nonroutine processes. Organization Studies, 24(2), 215–233. https://doi.org/10.1177/0170840603024002344

Li, S., & Lin, B. (2006). Accessing information sharing and information quality in supply chain management. Decision Support Systems, 42(3), 1641–1656. https://doi.org/10.1016/j.dss.2006.02.011

MacCallum, R. C., & Austin, J. T. (2000). Applications of structural equation modeling in psychological research. Annual Review of Psychology, 51, 201–226. https://doi.org/10.1146/annurev.psych.51.1.201

Marinagi, C., Trivellas, P., & Sakas, D. P. (2014).The impact of information technology on the development of supply chain competitive advantage. Procedia – Social and Behavioral Sciences, 147, 586–591. https://doi.org/10.1016/j.sbspro.2014.07.161

Moss, S. C., Prosser, H., Costello, H., Simpson, N., Patel, P., Rowe, S., Turner, S., & Hatton, C. (1988). Reliability and validity of the PAS-ADD Checklist for detecting psychiatric disorders in adults with intellectual disability. Journal of Intellectual Disability Research, 42, 173–183. https://doi.org/10.1046/j.1365-2788.1998.00116.x

Nektarios, T. (2015). Top management commitment and involvement and their link to key account management effectiveness. Journal of Business & Industrial Marketing, 30(1), 32–44. https://doi.org/10.1108/JBIM-12-2012-0238

Paik, S. & Bagchi, P. (2007), Understanding the causes of the bullwhip effect in a supply chain. International Journal of Retail & Distribution Management, 35(4), 308–324. https://doi.org/10.1108/09590550710736229

Pishdar, M., Ghasemzadeh, F., Antuchevičienė, J., & Šaparauskas, J. (2018). Internet of things and its challenges in supply chain management: a rough strength relation analysis method. E&M Economics and Management, 21(2), 208–222. https://doi.org/10.15240/tul/001/2018-2-014

Porter, M. E. (1998). Competitive strategy: Techniques for analyzing industries and competitors. Free Press.

Power, D. (2005). Supply chain management integration and implementation: a literature review. Supply Chain Management, 10, 252–263. https://doi.org/10.1108/13598540510612721

Prajogo, D., & Olhager, J. (2012). Supply chain integration and performance: The effects of long-term relationships, information technology and sharing, and logistics integration. International Journal of Production Economics, 135, 514–522. https://doi.org/10.1016/j.ijpe.2011.09.001

Qrunfleh, S., & Tarafdar, M. (2014). Supply chain information systems strategy: impacts on supply chain performance and firm performance. International Journal of Production Economics, 147, 340–350. https://doi.org/10.1016/j.ijpe.2012.09.018

Rajaguru, R., & Matanda, M. J. (2019). Role of compatibility and supply chain process integration in facilitating supply chain capabilities and organizational performance. Supply Chain Management: An International Journal, 24(2), 301–316. https://doi.org/10.1108/SCM-05-2017-0187

Ringle, C. M., Sarstedt, M., Mitchell, R., & Gudergan, S. P. (2020). Partial least squares structural equation modeling in HRM research. The International Journal of Human Resource Management, 31(12), 1617–1643. https://doi.org/10.1080/09585192.2017.1416655

Simchi-Levi, D., Kaminsky, P., & Simchi-Levi, E. (2004). Designing and managing the supply chain. Irwin McGraw-Hill Education.

Singh, P. K., Sharma, S. K., Samuel, C., & Verma, S. (2017). Supplier relationship management and selection strategies – A literature review [Conference presentation]. 4th International Conference on Industrial Engineering, Surat, India.

Stadtler, H., & Kilger, C. H. (2005). Supply chain management and advanced planning. Springer. https://doi.org/10.1007/b106298

Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society, 36(2), 111–147. https://doi.org/10.1111/j.2517-6161.1974.tb00994.x

Sukati, I., Hamid, A. B., Baharun, R., & Yusoff, R. M. (2012). The study of supply chain management strategy and practices on supply chain performance. Procedia – Social and Behavioral Sciences, 40, 225–233. https://doi.org/10.1016/j.sbspro.2012.03.185

Tenenhaus, M., Vinzi, V. E., Chatelin, Y.-M., & Lauro, C. (2005). PLS path modeling. Computational Statistics & Data Analysis, 48(1), 159–205. https://doi.org/10.1016/j.csda.2004.03.005

Waltz, C. F., Bausell, R. B. (1983). Nursing research: Design, statistics and computer analysis (2nd ed.). FA Davis Company.

Wold, H. (1985). Partial least squares. In S. Kotz, & N. L. Johnson (Eds.), Encyclopedia of statistical sciences (Vol. 6, pp. 581–591). Wiley.

Wu, F., Yeniyurt, S., Kim, D., & Cavusgil, S. T. (2006). The impact of information technology on supply chain capabilities and firm performance: A resource-based view. Industrial Marketing Management, 35(4), 493–504. https://doi.org/10.1016/j.indmarman.2005.05.003

Wu, W. Y., Chiag, C. Y., Wu, Y. J., & Tu, H. J. (2004). The influencing factors of commitment and business integration on supply chain management. Industrial Management & Data Systems, 104(4), 322–333. https://doi.org/10.1108/02635570410530739

Wu, I-L., & Chiu, M-L. (2018). Examining supply chain collaboration with determinants and performance impact: Social capital, justice, and technology use perspectives. International Journal of Information Management, 39, 5–19. https://doi.org/10.1016/j.ijinfomgt.2017.11.004

Xiong, B., Skitmore, M., & Xia, B. (2015). A critical review of structural equation modelling applications in construction research. Automation in Construction, 49(A), 57–70. https://doi.org/10.1016/j.autcon.2014.09.006

Yazdani, M., Zarate, P., Coulibaly, A., & Zavadskas, E. K. (2017). A group decision making support system in logistics and supply chain management. Expert Systems with Applications, 88, 376–392. https://doi.org/10.1016/j.eswa.2017.07.014

Youn, S., Yang, M. G. M., Hong, P., & Park, K. (2013). Strategic supply chain partnership, environmental supply chain management practices, and performance outcomes: an empirical study of Korean firms. Journal of Cleaner Production, 56, 121–130. https://doi.org/10.1016/j.jclepro.2011.09.026

Zhao, X., Huo, B., Selen, W., & Yeung, J. H. Y. (2011). The impact of internal integration and relationship commitment on external integration. Journal of Operations Management, 29, 17–32. https://doi.org/10.1016/j.jom.2010.04.004

Ziggers, G. W., & Henseler, J. (2016). The reinforcing effect of a firm’s customer orientation and supplybase orientation on performance. Industrial Marketing Management, 52, 18–26. https://doi.org/10.1016/j.indmarman.2015.07.011