Effect of Logistic Service Reliability Capability on Performance of Manufacturing Firms: The Moderating Role of Supply Chain Linkages

  • E. Kimitei Department of Marketing & Logistics, Moi University, Kenya
  • J. Chepkwony Department of Marketing & Logistics, Moi University, Kenya
  • C. Lagat Department of Marketing & Logistics, Moi University, Kenya
  • D. Koskei Department of Management Science, Moi University, Kenya
Keywords: Performance; Logistic Capabilities; Logistic Service Reliability Capability; Supply Chain Linkages


Business organizations striving to improve their performance rely on several capabilities including logistic service reliability capability. However, there is also a need to understand how external variables may moderate the effect of logistic capabilities and performance. This study evaluated the moderating effect of supply chain linkages on the relationship between logistic service reliability capability and firm performance of manufacturing firms in Kenya. The study anchored on explanatory research design. A sample size of 442 firms was selected using stratified and simple random sampling approaches. The study established that logistic service reliability capability positively and significantly affects firm performance, subject to moderation by supply chain linkages. For the design of management system in a firm, there is need to integrate and improve the overall effects of logistic service reliability capability by incorporating supply chain linkages in the model. There is need for firm managers to understand and find ways to effectively manage the interactions between logistic service reliability capability and supply chain linkages in order to improve performance and meet the customer requirements satisfactorily. In many manufacturing firms especially in developing countries such interactions are rarely studied.


Al-Matari, E.M., Al-Swidi, A.K., Fadzil, F.H.B. (2014). The measurements of firm performance's dimensions. Asian Journal of Finance & Accounting. 6, 24.

Barney, J.B. (2001). Resource-based theories of competitive advantage: A ten-year retrospective on the resource-based view. Journal of management. 27, 643-650.

Benitez-Amado, J., Walczuch, R.M. (2012). Information technology, the organizational capability of proactive corporate environmental strategy and firm performance: a resource-based analysis. European Journal of Information Systems. 21, 664-679.

Bishara, A.J., Hittner, J.B. (2012). Testing the significance of a correlation with nonnormal data: comparison of Pearson, Spearman, transformation, and resampling approaches. Psychological methods. 17, 399.

Brace, I. (2018). Questionnaire design: How to plan, structure and write survey material for effective market research. Kogan Page Publishers.

Cegarra-Navarro, J.-G., Jiménez-Jiménez, D., Garcia-Perez, A. (2019). An integrative view of knowledge processes and a learning culture for ambidexterity: Towards improved organisational performance in the banking sector. IEEE Transactions on Engineering Management. (In-press).

Chapman, R.L., Soosay, C., Kandampully, J. (2002). Innovation in logistic services and the new business model: a conceptual framework. Managing Service Quality: An International Journal.

de Souza Miguel, P.L., Brito, L.A.L. (2011). Supply chain management measurement and its influence on operational performance. Journal of Operations and Supply Chain Management. 4, 56-70.

Farris, P.W., Bendle, N., Pfeifer, P., Reibstein, D. (2010). Marketing metrics: The definitive guide to measuring marketing performance. Pearson Education.

Franceschini, F., Rafele, C. (2000). Quality evaluation in logistic services. International Journal of Agile Management Systems. 2, 49-54.

Garner, M., Wagner, C., Kawulich, B. (2016). Quantitative or qualitative: Ontological and epistemological choices in research methods curricula, Teaching research methods in the social sciences. Routledge, pp. 81-90.

Gopal, P., Thakkar, J. (2012). A review on supply chain performance measures and metrics: 2000-2011. International Journal of Productivity and Performance Management. 61, 518-547.

Hendra, R., Hill, A. (2018). Rethinking response rates: New evidence of little relationship between survey response rates and nonresponse bias. Evaluation review. 0193841X18807719.

Hill, N., Alexander, J. (2017). The handbook of customer satisfaction and loyalty measurement. Routledge.

Hope, O.-K., Thomas, W.B., Vyas, D. (2013). Financial reporting quality of US private and public firms. The Accounting Review. 88, 1715-1742.

Hsu, C.-C., Kannan, V.R., Tan, K.-C., Keong Leong, G. (2008). Information sharing, buyer-supplier relationships, and firm performance: a multi-region analysis. International Journal of Physical Distribution & Logistics Management. 38, 296-310.

Huang, C.-J., Huang, K.-P. (2012). The logistics capabilities scale for logistics service providers. Journal of Information and Optimization Sciences. 33, 135-148.

Joong-Kun Cho, J., Ozment, J., Sink, H. (2008). Logistics capability, logistics outsourcing and firm performance in an e-commerce market. International journal of physical distribution & logistics management. 38, 336-359.

Kim, H.-Y. (2013). Statistical notes for clinical researchers: assessing normal distribution (2) using skewness and kurtosis. Restorative dentistry & endodontics. 38, 52-54.

Kolade, O., Obembe, D., Salia, S. (2019). Technological constraints to firm performance: the moderating effects of firm linkages and cooperation. Journal of Small Business and Enterprise Development. 26, 85-104.

Kraaijenbrink, J., Spender, J.-C., Groen, A.J. (2010). The resource-based view: a review and assessment of its critiques. Journal of management. 36, 349-372.

Kurian, G. (2013). The AMA dictionary of business and management. Amacom.

Lai, K.-h. (2004). Service capability and performance of logistics service providers. Transportation Research Part E: Logistics and Transportation Review. 40, 385-399.

Lau, C.M., Sholihin, M. (2005). Financial and nonfinancial performance measures: How do they affect job satisfaction? The British Accounting Review. 37, 389-413.

Lavery, M.R., Acharya, P., Sivo, S.A., Xu, L. (2019). Number of predictors and multicollinearity: What are their effects on error and bias in regression? Communications in Statistics-Simulation and Computation. 48, 27-38.

Leavy, P. (2017). Research design: Quantitative, qualitative, mixed methods, arts-based, and community-based participatory research approaches. Guilford Publications.

Lu, C.-S., Yang, C.-C. (2010). Logistics service capabilities and firm performance of international distribution center operators. The Service industries journal. 30, 281-298.

Nallusamy, S., Muhammad Umarmukdhar, A., Suganthini Rekha, R. (2016). A proposed supply chain model for productivity enhancement in medium scale foundry industries, International Journal of Engineering Research in Africa. Trans Tech Publ, pp. 248-258.

Owens, I., Wilson, T., Abell, A. (2019). Information and Business Performance: A Study of Information Systems and Services in High-Performing Companies. Walter de Gruyter GmbH & Co KG.

Oztekin, A., Delen, D., Zaim, H., Turkyilmaz, A., Zaim, S. (2015). The influence of knowledge management on financial and non-financial performance. Journal of Information & Knowledge Management. 14, 1550013.

Patino, C.M., Ferreira, J.C. (2018). Internal and external validity: can you apply research study results to your patients? Jornal Brasileiro de Pneumologia. 44, 183-183.

Prajogo, D., Toy, J., Bhattacharya, A., Oke, A., Cheng, T. (2018). The relationships between information management, process management and operational performance: Internal and external contexts. International Journal of Production Economics. 199, 95-103.

Rahi, S. (2017). Research design and methods: A systematic review of research paradigms, sampling issues and instruments development. International Journal of Economics & Management Sciences. 6, 1-5.

Santos, J.B., Brito, L.A.L. (2012). Toward a subjective measurement model for firm performance. BAR-Brazilian Administration Review. 9, 95-117.

Schroeder, R.G., Bates, K.A., Junttila, M.A. (2002). A resource‐based view of manufacturing strategy and the relationship to manufacturing performance. Strategic management journal. 23, 105-117.

Shepherd, C., Günter, H. (2010). Measuring supply chain performance: current research and future directions, Behavioral Operations in Planning and Scheduling. Springer, pp. 105-121.

Shou, Z., Chen, J., Zhu, W., Yang, L. (2014). Firm capability and performance in China: The moderating role of guanxi and institutional forces in domestic and foreign contexts. Journal of Business Research. 67, 77-82.

Siguaw, J.A., Simpson, P.M., Enz, C.A. (2006). Conceptualizing innovation orientation: A framework for study and integration of innovation research. Journal of product innovation management. 23, 556-574.

Stank, T.P., Pellathy, D.A., In, J., Mollenkopf, D.A., Bell, J.E. (2017). New frontiers in logistics research: theorizing at the middle range. Journal of Business Logistics. 38, 6-17.

Sunder, S. (2016). Better financial reporting: Meanings and means. Journal of Accounting and Public Policy. 35, 211-223.

Sundquist, V., Gadde, L.-E., Hulthén, K. (2018). Reorganizing construction logistics for improved performance. Construction management and economics. 36, 49-65.

Taber, K.S. (2018). The use of Cronbach’s alpha when developing and reporting research instruments in science education. Research in Science Education. 48, 1273-1296.

Teece, D.J. (2018). Business models and dynamic capabilities. Long Range Planning. 51, 40-49.

Tokito, S. (2018). Environmentally-Targeted Sectors and Linkages in the Global Supply-Chain Complexity of Transport Equipment. Ecological economics. 150, 177-183.

Torres, R., Sidorova, A., Jones, M.C. (2018). Enabling firm performance through business intelligence and analytics: A dynamic capabilities perspective. Information & Management. 55, 822-839.

Wamba, S.F., Gunasekaran, A., Akter, S., Ren, S.J.-f., Dubey, R., Childe, S.J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research. 70, 356-365.

Wang, Y., Wallace, S.W., Shen, B., Choi, T.-M. (2015). Service supply chain management: A review of operational models. European Journal of Operational Research. 247, 685-698.

Wei, S., Ke, W., Liu, H., Wei, K.K. (2019). Supply Chain Information Integration and Firm Performance: Are Explorative and Exploitative IT Capabilities Complementary or Substitutive? Decision Sciences.

Westfall, P.H. (2014). Kurtosis as peakedness, 1905–2014. RIP. The American Statistician. 68, 191-195.

Wiengarten, F., Pagell, M., Ahmed, M.U., Gimenez, C. (2014). Do a country's logistical capabilities moderate the external integration performance relationship? Journal of Operations Management. 32, 51-63.

Wilding, R., Wagner, B., Gligor, D.M., Holcomb, M.C. (2012). Understanding the role of logistics capabilities in achieving supply chain agility: a systematic literature review. Supply Chain Management: An International Journal.

Wiley, J.F., Pace, L.A. (2015). Multiple regression, Beginning R. Springer, pp. 139-161.

Williams, M.N., Grajales, C.A.G., Kurkiewicz, D. (2013). Assumptions of multiple regression: Correcting two misconceptions.

Yang, C.-C., Marlow, P.B., Lu, C.-S. (2009). Assessing resources, logistics service capabilities, innovation capabilities and the performance of container shipping services in Taiwan. International Journal of Production Economics. 122, 4-20.

Yang, M.G.M., Hong, P., Modi, S.B. (2011). Impact of lean manufacturing and environmental management on business performance: An empirical study of manufacturing firms. International Journal of Production Economics. 129, 251-261.
How to Cite
Kimitei, E., Chepkwony, J., Lagat, C., & Koskei, D. (2019, December 23). Effect of Logistic Service Reliability Capability on Performance of Manufacturing Firms: The Moderating Role of Supply Chain Linkages. African Journal of Education,Science and Technology, 5(3), Pg 155-169. Retrieved from http://ajest.info/index.php/ajest/article/view/403