Journal of Supply Chain Management Systems

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Reverse Logistics, Stakeholder Influence and Supply Chain Performance in Ghanaian Manufacturing Sector


Affiliations
1 Transportation Engineering College, Dalian Maritime University, China
2 Department of Marketing and Supply Chain Management, University of Cape Coast, Ghana
     

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The study primarily aimed at assessing the perceived stakeholder influence on reverse logistics (RL) adoption and further examined how the adoption of RL influences supply chain performance, with a focus in the Ghanaian manufacturing sector. A total of 193 operation managers, logistics managers and production managers were carefully selected via stratified sampling technique for the study. A structured questionnaire was used for the primary data collection instrument. Formulated hypotheses were tested using Partial Least Squares structural equation modelling. The findings revealed that all the stakeholder variables (top management support, corporate citizenship pressure and customer pressure), except for environmental regulations, have a strong influence on RL adoption. Furthermore, supply chain performance is enhanced through RL. The results provide strategic insight for managers to willingly support RL and design effective product return policies that meet both customers and society’s ‘greening’ expectation to enhance their supply chains. Governments and other environmental regulatory bodies should also design national waste management policies aimed at mounting pressure on manufacturing firms to comply and adopt RL into their operations.

Keywords

Stakeholder Influence, Reverse Logistics, Supply Chain Performance.
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  • Abdullah, N. A. H. N. & Yaakub, S. (2017). The pressure for reverse logistics adoption among manufacturers in Malaysia. Asian Journal of Business and Accounting, 8(1), 151-178.

  • Álvarez-Gil, M. J., Berrone, P., Husillos, F. J., & Lado, N. (2007). Reverse logistics, stakeholders’ influence, organizational slack, and managers’ posture. Journal of Business Research, 60(5), 463-473.

  • Ambe, I. M. (2014). Key indicators for optimising supply chain performance: The case of light vehicle manufacturers in South Africa. Journal of Applied Business Research (JABR), 30(1), 277-290.

  • Azungah, M. H. (2014). Dealing with plastic waste in Metropolitan Accra: Challenges and policy instruments. The problem of plastic waste in Metropolitan Accra. Waste Management, 34(12), 3-5.

  • Bodoff, D., & Ho, S. Y. (2016). Partial least squares structural equation modeling approach for analyzing a model with a binary indicator as an endogenous variable. Communications of the Association for Information Systems, 38(1), 400-419.

  • Clarkson, M. E. (1995). A stakeholder framework for analyzing and evaluating corporate social performance. Academy of Management Review, 20(1), 92-117.

  • Darnall, N., Jolley, G. J., & Handfield, R. (2008). Environmental management systems and green supply chain management: Complements for sustainability?. Business Strategy and the Environment, 17(1), 30-45.

  • David, K. G., & Shalle, N. (2014). An assessment of the effects of reverse logistics adoption on supply chain performance in the manufacturing sector in Kenya: A case of Hewlett-Packard Kenya. Eur. J. Bus. Manage., 2(1), 161-173.

  • Dowlatshahi, S. (2011). An empirical study of the ISO 9000 certification in global supply chain of maquiladoras. International Journal of Production Research, 49(1), 215-234.

  • Gattiker, T. F., & Carter, C. R. (2010). Understanding project champions’ ability to gain intra-organizational commitment for environmental projects. Journal of Operations Management, 28(1), 72-85.

  • Govindan, K., Soleimani, H., & Kannan, D. (2015). Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future. European Journal of Operational Research, 240(3), 603-626.

  • Hair, J., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. L. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management & Data Systems, 117(3), 442-458.

  • Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications.

  • Hazen, B. T., Cegielski, C., & Hanna, J. B. (2011). Diffusion of green supply chain management: Examining perceived quality of green reverse logistics. The International Journal of Logistics Management, 22(3), 373-389.

  • 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.

  • Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In New Challenges to International Marketing (pp. 277-319). Emerald Group Publishing Limited.

  • Huscroft, J. R. (2008). Practical challenges in managing the reverse logistics process in a supply chain. Auburn University, Auburn, AL.

  • Karel, K., & Ales, K. (2012). Role of customers in stakeholders’ approach in company corporate governance. World Academy of Science, Engineering and Technology, International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering, 6(10), 2514-2518.

  • Khalili-Damghani, K., Tavana, M., & Najmodin, M. (2015). Reverse logistics and supply chains: A structural equation modeling investigation. The International Journal of Industrial Engineering: Theory, Applications and Practice, 22(3), 354-368.

  • Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration (IJeC), 11(4), 1-10.

  • Laosirihongthong, T., Adebanjo, D., & Choon Tan, K. (2013). Green supply chain management practices and performance. Industrial Management & Data Systems, 113(8), 1088-1109.

  • Mandota, E. (2015). The impact of reverse logistics on supply chain performance in Malawi manufacturing sector: A case study of Carlsberg Malawi (Kanengo Plant) (Doctoral Dissertation, Exploits University).

  • Mathiyazhagan, K., & Noorul Haq, A. (2013). Analysis of pressures for adoption of Green supply chain management using interpretive structural modeling. 3rd International Conference on Production and Industrial Engineering CPIE-2013. March 29-31. NITJalandhar, India.

  • Peng, D. X., & Lai, F. (2012). Using partial least squares in operations management research: A practical guideline and summary of past research. Journal of Operations Management, 30(6), 467-480.

  • Rebs, T., Brandenburg, M., Seuring, S., & Stohler, M. (2018). Stakeholder influences and risks in sustainable supply chain management: A comparison of qualitative and quantitative studies. Business Research, 11(2), 197-237.

  • Rogers, D. S., & Tibben-Lembke, R. (2001). An examination of reverse logistics practices. Journal of Business Logistics, 22(2), 129-148.

  • Sarkis, J., Gonzalez-Torre, P., & Adenso-Diaz, B. (2010). Stakeholder pressure and the adoption of environmental practices: The mediating effect of training. Journal of Operations Management, 28(2), 163-176.

  • Sarstedt, M., Hair, J. F., Ringle, C. M., Thiele, K. O., & Gudergan, S. P. (2016). Estimation issues with PLS and CBSEM: Where the bias lies! Journal of Business Research, 69(10), 3998-4010.

  • Shafiq, M. S., & Naqvi, I. H. (2012). Top management support partially optimized reverse logistics in the manufacturing sector of Pakistan. International Journal of Business and Social Research, 2(3), 119-125.

  • Sharma, S. K., Panda, B. N., Mahapatra, S. S., & Sahu, S. (2011). Analysis of barriers for reverse logistics: An Indian perspective. International Journal of Modeling and Optimization, 1(2), 101.

  • Sillanpää, I. (2015). Empirical study of measuring supply chain performance. Benchmarking: An International Journal, 22(2), 290-308.

  • Somuyiwa, A. O., & Adebayo, I. T. (2014). Empirical study of the effect of reverse logistics objectives on economic performance of food and beverages companies in Nigeria. International Review of Management and Business Research, 3(3), 1484.

  • Stock, J. R. (1992). Reverse logistics: White paper. Council of Logistics Management.

  • Sung, R. J. (2010). The impact of green supply chain practices on supply chain performance. Unpublished MA, University of Nebraska at Lincoln. Retrieved from http://digitalcommons.unl.edn/businessdiss/l,

  • Trivedi, K., Trivedi, P., & Goswami, V. (2018). Sustainable marketing strategies: Creating business value by meeting consumer expectation. International Journal of Management, Economics and Social Sciences (IJMESS), 7(2), 186-205.

  • Turrisi, M., Bruccoleri, M., & Cannella, S. (2013). Impact of reverse logistics on supply chain performance. International Journal of Physical Distribution & Logistics Management, 43(7), 564-585.

  • Vanalle, R. M., Ganga, G. M. D., Godinho Filho, M., & Lucato, W. C. (2017). Green supply chain management: An investigation of pressures, practices, and performance within the Brazilian automotive supply chain. Journal of Cleaner Production, 151, 250-259.

  • Wainaina, G. (2014). Reverse logistics practices and profitability of large scale manufacturing firms in Nairobi, Kenya (Doctoral Dissertation, School of Business in Partial Fulfillment of the Requirements for the Degree of Master of Business Administration, University of Nairobi).

  • Wells, P., & Seitz, M. (2005). Business models and closed-loop supply chains: A typology. Supply Chain Management: An International Journal, 10(4), 249-251.

  • Yu, W., & Ramanathan, R. (2015). An empirical examination of stakeholder pressures, green operations practices and environmental performance. International Journal of Production Research, 53(21), 6390-6407.

  • Zhu, Q., & Geng, Y. (2013). Drivers and barriers of extended supply chain practices for energy saving and emission reduction among Chinese manufacturers. Journal of Cleaner Production, 40, 6-12.


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  • Reverse Logistics, Stakeholder Influence and Supply Chain Performance in Ghanaian Manufacturing Sector

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Authors

Ebenezer Afum
Transportation Engineering College, Dalian Maritime University, China
B. Zhuo Sun
Transportation Engineering College, Dalian Maritime University, China
C. Lawrence Yaw Kusi
Department of Marketing and Supply Chain Management, University of Cape Coast, Ghana

Abstract


The study primarily aimed at assessing the perceived stakeholder influence on reverse logistics (RL) adoption and further examined how the adoption of RL influences supply chain performance, with a focus in the Ghanaian manufacturing sector. A total of 193 operation managers, logistics managers and production managers were carefully selected via stratified sampling technique for the study. A structured questionnaire was used for the primary data collection instrument. Formulated hypotheses were tested using Partial Least Squares structural equation modelling. The findings revealed that all the stakeholder variables (top management support, corporate citizenship pressure and customer pressure), except for environmental regulations, have a strong influence on RL adoption. Furthermore, supply chain performance is enhanced through RL. The results provide strategic insight for managers to willingly support RL and design effective product return policies that meet both customers and society’s ‘greening’ expectation to enhance their supply chains. Governments and other environmental regulatory bodies should also design national waste management policies aimed at mounting pressure on manufacturing firms to comply and adopt RL into their operations.

Keywords


Stakeholder Influence, Reverse Logistics, Supply Chain Performance.

References