Benchmarking supply chain collaboration dimensions with insights from resource-based theories
a key to manufacturing competitiveness
DOI:
https://doi.org/10.14488/BJOPM.2221.2024Keywords:
Supply chain collaboration, Customer collaboration, Supplier collaboration, Internal collaboration, Manufacturing competitivenessAbstract
Goal: Despite the increased attention to the role of supply chain collaboration on firm performance, insufficient evidence exists about the relative importance of each dimension of supply chain collaboration on manufacturing competitiveness. The purpose of this study is to examine the influence and relative importance of supply chain collaboration dimensions on manufacturing competitiveness based on resource-based theories.
Design/methodology/approach: This study employs a deductive approach to derive empirical evidence from the responses of 300 officials of manufacturing firms. The PLS-SEM is used to test the significance of conceptual predictions and IPMA is used to benchmark the most important collaborative dimensions.
Results: It is revealed that manufacturing firms capitalize on all supply chain collaboration dimensions. However, customer collaboration and supplier collaboration have a significant and positive direct influence while internal collaboration exhibits a complementary partial mediation effect. Customer collaboration is the most important dimension followed by internal collaboration and supplier collaboration.
Limitations of the investigation: This study employed a cross-section design lacking the longitudinal effect. Nevertheless, the identification, testing and validation of the conceptual model, backed up by an extensive literature review, could assist researchers in developing meaningful comparative studies.
Originality/value: The study applied PLS-SEM and IPMA to reveal the role and relative importance of supply chain collaborative dimensions on manufacturing competitiveness. Managers of manufacturing firms can emulate this knowledge within their settings and be able to compete amid increased competition and supply chain complexity.
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Andalib Ardakani, D., Soltanmohammadi, A. and Seuring, S. (2023), "The impact of customer and supplier collaboration on green supply chain performance", Benchmarking: An International Journal, Vol. 30, No. 7, pp. 2248-2274.
Antwi, S.K. and Kasim, H. (2015), “Qualitative and Quantitative Research Paradigms in Business Research: A Philosophical Reflection”, European Journal of Business and Management, Vol. 7, No. 3, pp. 217–225.
Assensoh-Kodua, A. (2019), “The resource-based view: A tool of key competency for competitive advantage”, Problems and Perspectives in Management, Vol. 17, No. 3, pp. 143.
Bagozzi, R.P. and Phillips, L. (1982), “Representing and Testing Organizational Theories: A Holistic Construal”, Administrative Science Quarterly, Vol. 27, No. 3, pp. 459–489.
Banchuen, P., Sadler, I. and Shee, H. (2017), “Supply Chain Collaboration Aligns Order-Winning Strategy with Business Outcomes”, IIMB Management Review, Vol. 29, No. 2, pp. 109–121.
Barney, J. (1991), “Firm Resources and Sustained Competitive Advantage”, Journal of Management, Vol. 17, No. 1, pp. 99–120.
Baron, R.M. and Kenny, D.A. (1986), “The Moderator-Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations”, Vol. 51, No. 6, pp. 1173–1182.
Benitez, J. et al. (2020), “How to Perform and Report an Impactful Analysis Using Partial Least Squares: Guidelines for Confirmatory and Explanatory IS Research”, Information & Management, Vol. 57, No. 2, pp. 1–16.
Bhattacherjee, A. (2012), Social Science Research: Principles, Methods, and Practices. Textbooks, University of South Florida. Textbooks. University of South Florida.
Biermann, R. and Harsch, M. (2017), “Resource Dependence Theory”, in Palgrave Handbook of Inter-Organizational Relations in World Politics, pp. 135–155.
Boyd, B.K., Haynes, K.T. and Hitt, M.A. (2012), “Contingency Hypotheses in Strategic Management Research: Use, Disuse, or Misuse?”, Journal of Management, Vol. 38, No. 1, pp. 278–313.
Cepeda, G., Nitzl, C. and Roldan, J.L. (2017), “Mediation analyses in partial least squares structural equation modeling. Guidelines and empirical examples”, in Partial Least Squares Path Modelling. Springer, Cham, pp. 173–195.
Chin, W.W. (1998), “The Partial Least Squares Approach to Structural Equation Modeling”, Modern methods for business research, Vol. 295, No. 2, pp. 295–336.
Duarte, T.E., Ribeiro, P.C.C. and Costa, H.G. (2024), “Indicators and performance requirements for suppliers’ evaluation in the Brazilian electricity sector”, Brazilian Journal of Operations and Production Management, Vol. 21, No. 3. Available at:
https://doi.org/10.14488/BJOPM.1984.2024
Duhamel, F., Carbone, V. and Moatti, V. (2016), “The Impact of Internal and External Collaboration on the Performance of Supply Chain Risk Management”, International Journal of Logistics Systems and Management, Vol. 23, No. 4, pp. 534–557.
Emon, M. M. H., Khan, T. and Siam, S. A. J. (2024), “Quantifying the influence of supplier relationship management and supply chain performance: an investigation of Bangladesh’s manufacturing and service sectors”, Brazilian Journal of Operations and Production Management, Vol. 21, No. 2. Available at: https://doi.org/10.14488/BJOPM.2015.2024
Errassafi, M., Abbar, H. and Benabbou, Z. (2019), “The mediating effect of internal integration on the relationship between supply chain integration and operational performance: evidence from Moroccan manufacturing companies”, Journal of Industrial Engineering and Management, Vol. 12, No. 2, pp. 254–273.
Gligor, D.M. and Holcomb, M. (2013), “The Road to Supply Chain Agility: An RBV Perspective on the Role of Logistics Capabilities”, International Journal of Logistics Management, Vol. 25, No. 1, pp. 160–179.
Grant, R.M. (2001), “The Resource-Based Theory of Competitive Advantage”, California Management Review, Vol. 33, No. 3, pp. 114–135.
Haider, I. (2014), “Collaboration in Supply Chain Management: What it is and How to Use It?”, International Journal of Research, Vol. 1, No. 6, pp. 499–507.
Hair, J.F. et al. (2017), A primer on partial least squares structural equation modeling (PLS-SEM). 2nd edn. SAGE Publications, Inc., California.
Hair, J.F. et al. (2019), “When to use and how to report the results of PLS-SEM”, European Business Review, Vol. 31, No. 1, pp. 2–24.
Henseler, J., Hubona, G. and Ray, P.A. (2016), “Using PLS Path Modeling in New Technology Research: Updated Guidelines”, Industrial Management and Data Systems, Vol. 116, No. 1, pp. 2–20.
Henseler, J., Ringle, C.M. and Sinkovics, R.R. (2009), “The Use of Partial Least Squares Path Modeling in International Marketing”, Advances in International Marketing, Vol. 20, pp. 277–319.
Hock, C., Ringle, C.M. and Sarstedt, M. (2010), “Management of Multi-Purpose Stadiums: Importance and Performance Measurement of Service Interfaces”, International Journal of Services Technology and Management, Vol. 14, No. 2/3, pp. 188–207.
Hosseinnezhad, D., Nugroho, Y. K., and Heavey, C. (2023), “Horizontal collaboration between suppliers to mitigate supply chain disruption: A secure resource sharing strategy”, Computers & Industrial Engineering, Vol. 177, 109088.
Hulland, J. (1999), “Use of Partial Least Squares (Pls) in Strategic Management Research: A Review of Four Recent Studies”, Strategic Management Journal, Vol. 20, pp. 195–204.
Iranmanesh, M. and Foroughi, B. (2019), “The Impact of Multinational Corporations’ Socially Responsible Supplier Development practices on their Corporate Reputation and Financial Performance”, International Journal of Physical Distribution & Logistics Management [Preprint], (November). Available at: https://doi.org/10.1108/IJPDLM-01-2019-0002.
Jimenez-Jimenez, D., Martínez-Costa, M. and Rodriguez, S. (2018), “The Mediating Role of Supply Chain Collaboration on the Relationship between Information Technology and Innovation”, Journal of Knowledge Management [Preprint]. Available at: https://doi.org/10.1108/JKM-01-2018-0019.
Karam, A., Reinau, K.H. and Østergaard, C.R. (2021), “Horizontal collaboration in the freight transport sector: barrier and decision-making frameworks”, European Transport Research Review, Vol. 13, No. 1, pp. 1–22.
Kock, N. (2015), “Common Method Bias in PLS-SEM: A full collinearity assessment approach”, International Journal of e-Collaboration, Vol. 11, No. 4, pp. 1–10.
Kock, N. (2016), “Hypothesis Testing with Confidence Intervals and P Values in PLS-SEM”, International Journal of e-Collaboration, Vol. 12, No. 3, pp. 1–6.
Kumar, R. (2011), Research methodology: A step-by-step guide for beginners. 3rd ed. SAGE Publications Ltd, London.
Laosirihongthong, T., Adebanjo, D. and Choon Tan, K. (2013), “Mediation Analysis in Partial Least Squares Path Modeling: Helping researchers discuss more sophisticated models”, Industrial Management & Data Systems, Vol. 113, No. 8, pp. 1008–1109.
Lotfi, M. and Larmour, A. (2022), “Supply chain resilience in the face of uncertainty: how horizontal and vertical collaboration can help?”, Continuity & Resilience Review, Vol. 4, No. 1, pp. 37–53.
Lugina, E.J., Mwakalobo, A.B.S. and Lwesya, F. (2022). “Effects of industrialization on Tanzania’s economic growth: a case of manufacturing sector”, Future Business Journal, Vol. 8, No. 62. Available at: https://doi.org/10.1186/s43093-022-00177-x.
Mackinnon, D.P., Coxe, S. and Baraldi, A.N. (2012), “Guidelines for the Investigation of Mediating Variables in Business Research”, Journal of Business Psychology, Vol. 27, pp. 1–14.
Malik, T., Hassan, S.M. and Tufail, M. (2024), “The impact of supply chain risk and supply chain integration on organizational performance: evidence from dairy sector of developing economy”, Brazilian Journal of Operations and Production Management, Vol. 21, No. 1, e20241682. https://doi.org/10.14488/BJOPM.1682.2024
Martilla, J.A. and James, J.C. (1977), “Importance-Performance Analysis’, Journal of Marketing, Vol. 41, No. 1, pp. 77–79.
Matthews, L. (2017), “Applying Multigroup Analysis in PLS-SEM: A Step-by-Step Process”, in Partial Least Squares Path Modelling. Springer International Publishing, pp. 219–243.
Melander, L. (2018), “Customer and Supplier Collaboration in Green Product Innovation: External and Internal Capabilities”, Business Strategy and the Environment, Vol 27, No. 6, pp. 677–693.
Min, H. (2015), The essentials of supply chain management: new business concepts and applications. Pearson Education LTD.
Mishra, D. et al. (2016), ”Bridging and Buffering: Strategies for Mitigating Buyer-Supplier Risk and Improving Supply Chain Performance”, International Journal of Production Economics, Vol. 180, No. 2016, pp. 183–197.
Moran, T.J. and Meso, P. (2011), “A Resource-Based View of Manufacturing Strategy and Implications to Organizational Culture and Human Resources”, Journal of Business & Economics Research (JBER), Vol. 6, No. 11, pp. 99–110.
Myamba, B.M. and Nguni, W.S. (2022), “Aligning the Risk Hedging Strategy with Supplier Collaboration and Manufacturing Competitiveness: A Resource-Based and Contingency Approach”, International Journal of Productivity and Performance Management [Preprint]. Available at: https://doi.org/10.1108/IJPPM-03-2021-0131.
NBS (2017), Statistical Abstract, National Bureau of Statistics.
Nyaga, G.N., Whipple, J.M. and Lynch, D.F. (2010), “Examining Supply Chain Relationships: Do Buyer and Supplier Perspectives on Collaborative Relationships Differ?”, Journal of Operations Management, Vol. 28, No. 2, pp. 101–114.
Ocampo, J.R., Hernández-matías, J.C. and Vizán, A. (2017), “Method for Estimating Manufacturing Competitiveness: The Case of the Apparel Maquiladora Industry in Central America”, Dyna, Vol. 84, No. 200, pp. 97–106.
Peteraf, M.A. and Barney, J.B. (2003), “Unraveling the Resource-Based Tangle”, Managerial and Decision Economics, Vol. 24, No. 4, pp. 309–323.
Pfeffer, J. and Alison, D.-B. (1987), “Understanding Organizational Wage Structures: A Resource Dependence Approach”, The Academy of Management Journal, Vol. 30, No. 3, pp. 437–455.
Preacher, K.J. and Hayes, A.F. (2008), “Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models”, Behavior Research Methods, Vol. 40, No. 3, pp. 879–891.
Qi, Y., Boyer, K.K. and Zhao, X. (2009), “Supply Chain Strategy, Product Characteristics, and Performance Impact: Evidence from Chinese Manufacturers”, Decision Sciences, Vol. 40, No. 4, pp. 667–695.
Rahimnia, F. and Keyvanipoor, S. (2014), “Analysis of BSC Perspectives as Related to the Alignment of Environmental Uncertainty and Supply Chain Strategy”, Benchmarking: An International Journal, Vol. 21, No. 6, pp. 903–916.
Ramayah, T. et al. (2018), Assessment of mediation analysis in Partial least squares structural equation modeling (PLS-SEM) using SmartPLS 3.0 analysis: An updated and practical guide to statistical analysis. 2nd edn, pp. 1–16.
Renko, S. (2011), “Vertical collaboration in the supply chain”, in Supply Chain Management - new Perspectives. In Tech, Europe, pp. 183–198.
Ringle, C.M. and Sarstedt, M. (2016), “Gain More Insight from Your PLS-SEM Results: The Importance-Performance”, Industrial Management and Data Systems, Vol. 116, No. 9, pp. 1865–1886.
Roh, J., Hong, P. and Min, H. (2014), “Implementation of a Responsive Supply Chain Strategy in Global Complexity: The Case of Manufacturing Firms”, International Journal of Production Economics, Vol. 147, pp. 198–210.
Rwehumbiza, D.A. (2021), “Firm-specific orientations and manufacturing capability under institutional voids”, Africa Journal of Management, Vol. 7, No. 2, pp. 263–285.
Saenz, M.J., Ubaghs, E. and Cuevas, A.I. (2015), Vertical Collaboration and Horizontal Collaboration in Supply Chain’, in Enabling Horizontal Collaboration Through Continuous Relational Learning. Springer, pp. 7–10. Available at: https://doi.org/10.1007/978-3-319-08093-2_3.
Salam, M.A. (2017), “Analyzing Supply Chain Uncertainty to Deliver Sustainable Operational Performance: Symmetrical and Asymmetrical Modeling Approaches”, Sustainability, Vol. Vol. 9(2217), pp. 1–17.
Saunders, M., Lewis, P. and Thornhill, A. (2013), Research methods for business students. 6th ed. Pearson, England.
Silva, F.H. and Fernandes, P.O. (2011), “Importance-Performance Analysis as a Tool in Evaluating Higher Education Service Quality: The Empirical Results of ESTiG (IPB)”, in the 17th International Business Information Management Association Conference, pp. 306–315.
Singh, H., Garg, R.K. and Sachdeva, A. (2018), “Supply Chain Collaboration: A State-of-the-art Literature Review’, Uncertain Supply Chain Management, 6(2), pp. 149–180.
Solaimani, S. and van der Veen, J. (2021), “Open supply chain innovation: an extended view on supply chain collaboration”, Supply Chain Management, Vol. 5, No. April 2021, pp. 597–610.
Soosay, C. (2016), “Strategies for Sustaining Manufacturing Competitiveness: Comparative Case studies in Australia and Sweden”, Journal of Manufacturing Technology Management, Vol. 27, No. 1, pp. 1–34.
Srivastava, S., Iyer, P., Davari, A., Williams Jr, W. A., and Parke, P. L. (2024), “How much customer collaboration is too much”? Implications for user entrepreneurship and product performance. Journal of Business and Industrial Marketing, Vol. 39, No. 5, pp.919-932.
Stank, T.P., Keller, S.B. and Daugherty, P.J. (2001), “Supply Chain Collaboration and Logistical Service Performance”, Journal of Business Logistics, Vol. 22, pp. 29–48.
Tailab, M.M.K. (2020), “Using Importance-Performance Matrix Analysis to Evaluate the Financial Performance of American Banks During the Financial Crisis”, SAGE Open, Vol. 10, No. 1, pp. 1–17.
Thatte, A.A. and Rao, S.S. (2013), “Impact of SCM Practices of a Firm on Supply Chain Responsiveness and Competitive Advantage of a Firm”, Journal of Applied Business Research, Vol. 29, No. 2, pp. 499–530.
Tukamuhabwa, B.R., Eyaa, S. and Derek, F. Me (2011), “Mediating Variables in the Relationship between Market Orientation and Supply Chain Performance: A Theoretical Approach”, International Journal of Business and Social Science, Vol. 2, No. 22, pp. 99–107.
Umanath, N.S. (2003), “The Concept of Contingency Beyond “‘It Depends’”: Illustrations from IS Research Stream”, Information & Management, Vol. 40, No. 6, pp. 551–562.
Venkatraman, N. (1989), “The Concept of Fit in Strategy Research: Towards Verbal and Statistical Correspondence”, Academy of Management Review, Vol. 14, No. 3, pp. 423–444.
Wong, C.Y., Boon-itt, S. and Wong, C.W.Y. (2021), “The contingency effects of internal and external collaboration on the performance effects of green practices”, Resources, Conservation and Recycling, Vol. 167, No. December 2020, Available at: https://doi.org/10.1016/j.resconrec.2020.105383.
Wong, K.K. (2016), “Technical Note: Mediation Analysis, Categorical Moderation Analysis, and Higher-order Constructs Modeling in Partial Least Squares Structural Equation Modeling (PLS-SEM): A B2B Example Using SmartPLS”, Marketing Bulletin, Vol. 26, 1, pp. 1–22.
Wu, F. et al. (2006), “The Impact of Information Technology on Supply Chain Capabilities and Firm Performance: A resource-based view”, Industrial Marketing Management, Vol. 35, No. 2006, pp. 493–504.
Wu, T. et al. (2014), “Aligning Supply Chain Strategy with Corporate Environmental Strategy: A Contingency Approach”, International Journal of Production Economics, Volume, 147, pp. 220–229.
Wyrod-Wrobel, J. and Biesok, G. 2017, “Decision Making on Various Approaches to Importance-Performance Analysis”, European Journal of Business and Technology, Vol. 2.
Yamane, T. (1973), Statistics; An introductory analysis. 2nd ed. Harper & Row, New York.
Zhao, X., Lynch, J.G. and Chen, Q. (2010), “Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis”, Journal of Consumer Research, Vol. 37, No. August, pp. 197–206.
Zhong, J. et al. (2022), “Internal and external collaboration and supply chain performance: a fit approach”, International Journal of Logistics Research and Applications, pp. 1–18. Available at: https://doi.org/10.1080/13675567.2022.2042226.
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