Contents |
Authors:
Sedat Aydin, ORCID: https://orcid.org/0000-0001-7564-9638 MBA, Graduate School of Business, Sakarya University, Turkey Mustafa Cahit Ungan, ORCID: https://orcid.org/0000-0003-2041-1344 Professor, Ph.D., School of Business, Sakarya University, Turkey
Pages: 235-253
Language: English
DOI: https://doi.org/10.21272/mmi.2023.1-20
Received: 12.01.2023
Accepted: 18.03.2023
Published: 31.03.2023
Download: |
Views: |
Downloads: |
|
|
|
Abstract
Today’s businesses experience many uncertainties in their internal operations and environments. Manufacturing flexibility is an excellent response to these uncertainties. Volume, modification, mix, and expansion flexibilities are the manufacturing flexibilities that businesses look for when they select their suppliers. In parallel, these flexibilities are often used as a supplier selection criterion in the literature. The supplier selection decision is a strategic issue for today’s businesses as a typical company is highly dependent on its suppliers to procure raw materials and parts. Sound supplier selection decision leads to competitive advantage because it is related to a positive relationship between buyer and supplier and reciprocal improvement of performance and trust between both parties. However, a literature review for this study showed a need for more empirical work on the relationship among types of flexibilities, supplier selection, performance improvement, long-term relationships, and trust. In order to fill the gap in this area, data was collected from 148 automotive companies operating in Turkey. For the data collection, the automotive industry was chosen as it is subjected to more uncertainties due to its connections to many other industries. The data were then analyzed using the structural equation model. The results showed a significant positive relationship between types of manufacturing flexibility and supplier selection. Also, positive relationships were found among supplier selection, performance, long-term relationships, and trust. Mediation and indirect effect analysis were also conducted. Long-term relationships and performance fully mediated the relationship between supplier selection and trust. An indirect relationship between supplier selection and trust was also found. The study results are expected to contribute to Sheth’s buyer-behavior model by introducing manufacturing flexibility, long-term relationship, performance, and trust to the model. Also, the study’s findings assist executives in making more informed decisions concerning supplier selection, depending on the level and types of flexibility they demand from their suppliers, performance, long-term relationships, and trust.
Keywords: long term relationship, manufacturing flexibility, trust, performance, purchasing, supplier selection.
JEL Classification: M10, M11.
Cite as: Aydin, S. & Ungan, M (2023). Contribution to Industrial Buyer Behavior Model: An Empirical Research Marketing and Management of Innovations, 1, 235-253. https://doi.org/10.21272/mmi.2023.1-20
This work is licensed under a Creative Commons Attribution 4.0 International License
References
- Al-Doori, J. A. (2019). The impact of supply chain collaboration on performance in automotive industry: Empirical evidence. Journal of Industrial Engineering and Management, 12(2), 241-253. [Google Scholar] [CrossRef]
- Al-Ma’aitah, N. (2018). The role of justice in achieving long-term buyer-supplier relationship: The case of Jordanian manufacturing sector. International Review of Management and Marketing, 8(2), 109-117. [Google Scholar]
- Avunduk, H. (2018). The Relationshıp Between Manufacturing Flexibility and Performance: A Meta Analytical Study. International Journal of Contemporary Economics and Administrative Sciences, 8(1), 20-33. [Google Scholar]
- Bartlett, M. S. (1954). A note on the multiplying factors for various chi square approximations. Journal of The Royal Statistical Society, 16(2), 296-298. [Google Scholar]
- Becker, J.M., Klein, K., & Wetzels, M. (2012). Hierarchical latent variable models in PLS-SEM: Guidelines for using reflective-formative type models. Long Range Planning, 45(5-6), 359-394. [Google Scholar] [CrossRef]
- Bengtsson, J. (2001). Manufacturing flexibility and real options: A review. International Journal of Production Economics, 74(1-3), 213-224. [Google Scholar] [CrossRef]
- Bodaghi, G., Jolai, F., & Rabbani, M. (2018) An integrated weighted fuzzy multi-objective model for supplier selection and order scheduling in a supply chain. International Journal of Production Research, 56(10), 3590-3614. [Google Scholar] [CrossRef]
- Bruno, G., Esposito, E., Genovese, A., & Simpson, M. (2016). Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment. Expert Systems with Applications, 43, 271-285. [Google Scholar] [CrossRef]
- Cao, M., Vonderembse, M. A., Zhang, Q., & Ragu-Nathan, T. S. (2010). Supply chain collaboration: Conceptualisation and instrument development. International Journal of Production Research, 48(22), 6613-6635. [Google Scholar] [CrossRef]
- Chauhan, A. S., Badhotiya, G. K., Soni, G., & Kumari, P. (2020). Investigating interdependencies of sustainable supplier selection criteria: an appraisal using ISM. Journal of Global Operations and Strategic Sourcing, 13(2), 195-210. [Google Scholar] [CrossRef]
- Che, Z. H., & Wang, H. S. (2008). Supplier selection and supply quantity allocation of common and non-common parts with multiple criteria under multiple products. Computers & Industrial Engineering, 55(1), 110-133. [Google Scholar] [CrossRef]
- Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295–336. [Google Scholar]
- Choffray, J. M., & Lilien, G. L. (1980). Market Planning For New İndustrial Products. John Wiley&Sons, 1th ed.
- Cristea, C., & Cristea, M. (2017). A multi-criteria decision making approach for supplier selection in the flexible packaging industry. In MATEC Web of Conferences (Vol. 94, p. 06002). EDP Sciences. [Google Scholar] [CrossRef]
- Das, A. (2001). Towards theory building in manufacturing flexibility. International Journal of Production Research, 39(18), 4153-4177. [Google Scholar] [CrossRef]
- De Toni, A., & Tonchia, S. (1998). Manufacturing flexibility: A literature review. International Journal of Production Research, 36(6), 1587-617. [Google Scholar] [CrossRef]
- Diamantopoulos, A., & Siguaw, J. A. (2006). Formative versus reflective indicators in organizational measure development: A comparison and empirical illustration. British Journal of Management, 17(4), 263-282. [Google Scholar] [CrossRef]
- Dixon, J. R. (1992). Measuring manufacturing flexibility: An empirical investigation. European Journal of Operational Research, 60(2), 131-143. [Google Scholar] [CrossRef]
- Doney, P.M., & Cannon, J.P. (1997). An examination of the nature of trust in buyer–seller relationships. Journal of Marketing, 61(2), 35-51. [Google Scholar] [CrossRef]
- Essien, E. E., & Udo-Imeh, P. T. (2013). A review of organizational buyer behaviour modelsand theories. Journal of Research in National Development, 11(1), 54-58. [Google Scholar]
- Fischer, C. (2013). Trust and communication in European agri‐food chains. Supply Chain Management, 18(2), 208-218. [Google Scholar] [CrossRef]
- Fornell, C., Cha, J., & Bagozzi, R. (Ed.). (1994). Advanced Marketing Research. John Wiley & Sons. [Google Scholar]
- Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. [Google Scholar] [CrossRef]
- Ganesan, S. (1994). Determinants of long-term orientation in buyer-seller relationships. Journal of Marketing, 58(2), 1-19. [Google Scholar] [CrossRef
- Gao, T., Sirgy, M. J., & Bird, M. M. (2005). Reducing buyer decision-making uncertainty in organizational purchasing: Can supplier trust, commitment, and dependence help? Journal of Business Research, 58(4), 397-405. [Google Scholar] [CrossRef]
- Geisser, S. (1974). Apredictive approach to the random effectsmodel. Biometrika, 61(1), 101-107. [Google Scholar] [CrossRef]
- Gerwin, D. (1993). Manufacturing flexibility: A strategic perspective. Management Science, 39(4), 395-410. [Google Scholar] [CrossRef
- Ghosh, A., & Fedorowicz, J. (2008). The role of trust in supply chain governance. Business Process Management Journal, 14(4), 453-470. [Google Scholar] [CrossRef]
- Goswami, M., & Ghadge, A. (2020). A supplier performance evaluation framework using single and bi-objective DEA efficiency modelling approach: individual and crossefficiency perspective. International Journal of Production Research, 58(10), 3066-3089. [Google Scholar] [CrossRef]
- Gulati, R. (1995). Does familiarity breed trust? The implications of repeated ties for contractual choice in alliances. Academy of Management Journal, 38(1), 85-112. [Google Scholar] [CrossRef]
- Gupta, Y. P., & Somers, T. M. (1992). Measurement of manufacturing Flexibility. European Journal of Operational Research, 60(2), 166-182. [Google Scholar] [CrossRef]
- Ha, B., Park, Y., & Cho, S. (2011). Suppliers’ affective trust and trust in competency in buyers: Its effect on collaboration and logistics efficiency. International Journal of Operations & Production Management, 31(1), 56-77. [Google Scholar] [CrossRef]
- Hair Jr, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014b). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26(2), 106-121. [CrossRef]
- Hair, J., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2014a). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (Los Angeles: SAGE Publications, Incorporated). [Google Scholar]
- Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). An Introduction to Structural Equation Modeling. In: Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R. Classroom Companion: Business. Springer, Cham. [Google Scholar] [CrossRef]
- Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-152. [Google Scholar] [CrossRef]
- Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24. [Google Scholar] [Crossref]
- Hallgren, M., & Olhager, J. (2009). Flexibility configurations: Empirical analysis of volume and product mix flexibility. Omega, 37(4), 746-756. [Google Scholar] [Google Scholar]
- Hays, R. D., & Revicki, D. A. (2005). Reliability and validity (including responsiveness). Assessing quality of life in clinical trials, 2, 25-39. [Google Scholar]
- Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of The Academy of Marketing Science, 43(1), 115-135. [Google Scholar] [CrossRef]
- Henseler, J., & Sarstedt, M. (2013). Goodness-of-fit indices for partial least squares path modeling. Computational Statistics, 28(2), 565-580. [Google Scholar] [CrossRef]
- Hoyle, R. H. (1995). Structural equation modeling: Concepts, issues, and applications. Sage. [Google Scholar]
- Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55. [Google Scholar] [CrossRef]
- Hu, S., & Dong, Z. S. (2019). Supplier selection and pre-positioning strategy in humanitarian relief. Omega, 83, 287-298. [Google Scholar] [CrossRef]
- Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal, 20(2), 195–204. [Google Scholar] [CrossRef]
- Imeri, S., Shahzad, K., Takala, J., Liu, Y., Sillanpaa, I., & Ali, T. (2015). Evaluation and selection process of suppliers through analytical framework: An emprical evidence of evaluation tool. Management and Production Engineering Review, 6(3), 10-20. [Google Scholar] [CrossRef]
- Jain, A., Jain, P. K., Chan, F. T., & Singh, S. (2013). A review on manufacturing flexibility. International Journal of Production Research, 51(19), 5946-5970. [Google Scholar] [CrossRef]
- Jambulingam, T., Kathuria, R., & Nevin, J. R. (2009). How fairness garners loyalty in the pharmaceutical supply chain: Role of trust in the wholesaler‐pharmacy relationship. International Journal of Pharmaceutical and Healthcare Marketing, 3(4), 305-322. [Google Scholar] [CrossRef]
- Junaid, M., Xue, Y., Syed, M. W., Li, J. Z., & Ziaullah, M. (2019). A Neutrosophic AHP and TOPSIS Framework for Supply Chain Risk Assessment in Automotive Industry of Pakistan. Sustainability, 12(1), 154. [Google Scholar] [CrossRef]
- Kaiser, H. F. (1970). A second generation little jiffy. Psychometrika, 35(4), 401–415. [Google Scholar] [CrossRef]
- Kanani, R. (2020). The impact of Logistics Information Sharing and the Mediating Effect of Logistics Performance on Buyer Trust. Orsea Journal, 9(1), 1-15. [Google Scholar]
- Kleinbaum, D. G., Kupper, L. L., & Muller, K. E. (1988). Applied Regression Analysis and Other Multivariate Methods, PWS-KENT: Wedsworth. Inc., Boston, Massachusetts. [Google Scholar]
- Koste, L. L., & Malhotra, M. K. (1999). A theoretical framework for analyzing the dimensions of manufacturing flexibility. Journal of Operations Management, 18(1), 75–93. [Google Scholar] [CrossRef]
- Koufteros, X., Vickery, K. S., & Dröge, C. (2012). The Effects of Strategic Supplier Selection on Buyer Competitive Performance In Matched Domains: Does Supplier Integration Mediate The Relatıonshıps?. Journal of Supply Chain Management, 48(2), 93-115. [Google Scholar] [CrossRef]
- Lee, D. M., & Drake, P. R. (2010). A portfolio model for component purchasing strategy and the case study of two South Korean elevator manufacturers. International Journal of Production Research, 48(22), 6651-6682. [Google Scholar] [CrossRef
- Lilien, G. L., Kotler, P., & Moorthy, K. S. (1992). Marketing models (Vol. 803). Englewood Cliffs, NJ: Prentice-Hall. [Google Scholar]
- Little, T. D., Card, N. A., Bovaird, J. A., Preacher, K. J., & Crandall, C. S. (2007). Structural equation modeling of mediation and moderation with contextual factors. Modeling contextual effects in longitudinal studies, 1, 207-230. [Google Scholar]
- Lu, Z., Sun, X., Wang, Y., & Xu, C. (2019). Green supplier selection in straw biomass industry based on cloud model and possibility degree. Journal of Cleaner Production, 209, 995-1005. [Google Scholar] [CrossRef].
- Matawale, C. R., Datta, S., & Mahapatra, S. S. (2016). Supplier selection in agile supply chain: Application potential of FMLMCDM approach in comparison with Fuzzy-TOPSIS and Fuzzy-MOORA. Benchmarking: An International Journal, 23(7), 2027-2060. [Google Scholar] [CrossRef[
- Mesic, Ž., Molnár, A., & Cerjak, M. (2018). Assessment of traditional food supply chain performance using triadic approach: The role of relationships quality. Supply Chain Management, 23(5), 396-411. [Google Scholar] [CrossRef]
- Mishra, R. (2020). Empirical analysis of enablers and performance outcome of manufacturing flexibility in an emerging economy. Journal of Manufacturing Technology Management, 31(6), 1301-1322. [Google Scholar] [CrossRef]
- Mofokeng, T. M., & Chinomona, R. (2019). Supply chain partnership, supply chain collaboration and supply chain integration as the antecedents of supply chain performance. South African Journal of Business Management, 50(1), 1-10. [Google Scholar]
- Moin, C. J., Iqbal, M., Malek, A. B. M., Khan, M. M. A., & Haque, R. (2022). Prioritization of environmental uncertainty and manufacturing flexibility for labor-intensive industry: A case study on ready-made garment industries in Bangladesh. Systems, 10(3), 67. [Google Scholar] [CrossRef]
- Mukherjee, K. (2016). An integrated approach of sustainable procurement and procurement postponement for the multi-product, assemble-to-order (ATO) production System. Production, 26(2), 249-260. [Google Scholar] [CrossRef]
- Narasimhan, R., & Das, A. (1999). An empirical investigation of the contribution of strategic sourcing to manufacturing flexibilities and performance. Decision Sciences, 30(3), 683-718. [Google Scholar] [CrossRef]
- Narasimhan, R., Talluri, S., & Das, A. (2004). Exploring flexibility and execution competencies of manufacturing firms. Journal of Operations Management, 22(1), 91-106. [Google Scholar] [CrossRef]
- Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). New York, NY: McGraw-Hill.
- Parkinson, S. T., & Baker, M. J. (1986). Organizational Buying Behaviour: Purchasing and Marketing Management Implications, MacMillan Press Ltd., London 1th edition. [Google Scholar]
- Parkouhi, S. V., & Ghadikolaei, A. S. (2017). A resilience approach for supplier selection: Using Fuzzy Analytic Network Process and grey VIKOR techniques. Journal of Cleaner Production, 161, 431-451. [Google Scholar] [CrossRef]
- Parkouhi, S. V., Ghadikolaei, A. S., & Lajimi, H. F. (2019). Resilient supplier selection and segmentation in grey environment. Journal of Cleaner Production, 207, 1123-1137. [Google Scholar] [CrossRef]
- Peterson, R. A., & Kim, Y. (2013). On the relationship between coefficient alpha and composite reliability. Journal of Applied Psychology, 98(1), 194–198. [Google Scholar] [CrossRef]
- Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of applied psychology, 88(5), 879. [Google Scholar]
- Powers, T. L., & Reagan, W. R. (2007). Factors influencing successful buyer–seller relationships. Journal of Business Research, 60(12), 1234–1242. [Google Scholar] [CrossRef]
- Prahinski, C., & Benton, W. C. (2004). Supplier evaluations: communication strategies to improve supplier performance. Journal of Operations Management, 22(1), 39-62. [Google Scholar] [CrossRef]
- Premsankar, R., Jeyapoovan, T., & Pramod, V. R. (2020). A correlation study between the dimensions of supply chain flexibility and performance of manufacturing firms. International Journal of Advanced Research in Engineering and Technology (IJARET), 11(3), 424-436. [Google Scholar]
- Ranta, J., & Alabyan, A. K. (1988). Interactive analysis of FMS productivity and flexibility. W.P.-88-098, IIASA, A-2361 Laxenburg, Austria. [Google Scholar]
- Ringle, C. M., Wende, S., & Becker, J. M. (2015). SmartPLS 3. Bönningstedt: SmartPLS.
- Robinson, P. J., Faris, C. W., & Wind, Y. (1967). Industrial buying and creative marketing. Allyn & Bacon. Boston, MA. [Google Scholar]
- Saenz, M. J., Knoppen, D., & Tachizawa, E. M. (2018). Building manufacturing flexibility with strategic suppliers and contingent effect of product dynamism on customer satisfaction. Journal of Purchasing and Supply Management, 24(3), 238-246. [Google Scholar] [CrossRef]
- Sako, M., & Helper, S. (1998). Determinants of trust in supplier relations: Evidence from the automotive industry in Japan and the United States. Journal of Economic Behavior & Organization, 34(3), 387-417. [Google Scholar] [CrossRef]
- Sarkis, J., & Dhavale, D. G. (2015) Supplier selection for sustainable operations: A triple-bottom-line approach using a Bayesian framework. International Journal of Production Economics, 166, 177-191. [Google Scholar] [CrossRef]
- Schotanus, F., Engh, G. V., Nijenhuis, Y., & Telgen, J. (2022). Supplier selection with rank reversal in public tenders. Journal of Purchasing and Supply Management, 28(2), 100744. [Google Scholar] [CrossRef]
- Sheth, J.N. (1973). A model of industrial buyer behavior. Journal of Marketing, 37(4), 50-56. [CrossRef]
- Shin, H., Collier, D. A., & Wilson, D. D. (2000). Supply management orientation and supplier/buyer performance. Journal of Operations Management, 18(3), 317-333. [Google Scholar] [CrossRef]
- Singh, R.K., Acharya, P., & Modgil, S. (2020). A template-based approach to measure supply chain flexibility: A case study of Indian soap manufacturing firm. Measuring Business Excellence, 24(2), 161-181. [Google Scholar] [CrossRef]
- Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society, 36(2), 111-147. [Google Scholar] [CrossRef]
- Taherdoost, H., & Brard, A. (2019). Analyzing the process of supplier selection criteria and methods. Procedia Manufacturing, 32, 1024-1034. [Google Scholar] [CrossRef]
- Taştan, S., & Uralcan, G. S. (2019). Economic and Technological Determinants of New Startups in the Global Financial Technology Sector, Haliç Üniversity. Journal of Social Sciences, 2(1), 41-69. Retrieved from [Link]
- Tenenhaus, M., Vinzi, V. E., Chatelin, Y., & Lauro, C. (2005). PLS path modelling. Computational Statistics & Data Analysis, 48(1), 159–205. [Google Scholar] [CrossRef]
- Thiruchelvam, S., & Tookey, J. E. (2011). Evolving trends of supplier selection criteria and methods. International Journal of Automotive and Mechanical Engineering, 4(1), 437-454. [Google Scholar] [CrossRef]
- Um, K. H., & Kim, S. M. (2019). The effects of supply chain collaboration on performance and transaction cost advantage: The moderation and nonlinear effects of governance mechanisms. International Journal of Production Economics, 217, 97-111. [Google Scholar] [CrossRef]
- Upton, D. M. (1994). The Management of Manufacturing Flexibility. California Management Review, 36 (2): 72–89. [Google Scholar] [CrossRef]
- Wagner, S. M., Grosse-Ruyken, P. T., & Erhun, F. (2018). Determinants of sourcing flexibility and its impact on performance. International Journal of Production Economics, 205, 329-341. [Google Scholar] [CrossRef]
- Webster, F. E., & Wind, Y. (1972). Organizational Buying Behavior, 1th ed. Prentice Hall. [Google Scholar]
- Wetzstein, A., Hartmann, E., Benton Jr, W. C., & Hohenstein, N. O. (2016). A systematic assessment of supplier selection literature–state-of-the-art and future scope. International Journal of Production Economics, 182, 304-323. [Google Scholar] [CrossRef]
- Wiengarten, F., Humphreys, P., Cao, G., Fynes, B., & McKittrick, A. (2010). Collaborative supply chain practices and performance: exploring the key role of information quality. Supply Chain Management, 15(6), 463-473. [Google Scholar] [CrossRef]
- Wilson, S., & Platts, K. (2010). How do companies achieve mix flexibility?. International Journal of Operations & Production Management, 30(9), 978-1003. [Google Scholar] [CrossRef]
- Wong, K. K. K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24(1), 1-32. Retrieved from [Link]
- Xu, Q., Fernando, G. D., & Tam, K. (2019). Trust and firm performance: A bi-directional study. Advances in Accounting, 47, 100433. [Google Scholar] [CrossRef]
- Yadav, V., & Sharma, M. K. (2015). Multi-criteria decision making for supplier selection using fuzzy AHP Approach. Benchmarking: An International Journal, 22(6), 1158-1174. [Google Scholar]] [CrossRef]
|