Role of Supply Chain Practices on Performance of Cement Manufacturing Firms in Kenya

Author(s)

Nathan Mwiti Kamwara , Dr. Noor Ismail ,

Download Full PDF Pages: 11-21 | Views: 914 | Downloads: 231 | DOI: 10.5281/zenodo.3456004

Volume 7 - October 2018 (10)

Abstract

The main aim of the study was to determine the role of cost management  on the performance of Cement Manufacturing firms, examine the role IT integration on performance of Cement Manufacturing firms in Kenya, to find out the extent to which top management supply support affect performance of Cement Manufacturing firms in Kenya and to find out the effect of lead-time on performance of Cement Manufacturing firms in Kenya. A descriptive research design was used. The target population of the study was Managers or equivalent from Six (6) departments that are Procurement, finance, legal, stores, human resource, and quality control because they are directly concerned with the supply chain. The sample size was 83 respondents from a target population of 500. The study adopted the use of a questionnaire as the main research instrument. The study adopted both quantitative and qualitative approaches, implying that both descriptive statistics and inferential statistics were employed. Quantitative data collected from the questionnaire were analyzed statistically using the Statistical Package for Social Scientist (SPSS version 24). The study tested the significance level of each independent variable against the dependent variable at a 95% confidence level using ANOVA, Correlation and regression techniques. The results revealed that cost management has no significant effect on the performance of cement manufacturing firms. However, through IT firms can manage suppliers information in a more effective and efficient manner. Therefore, IT needs to be used to select suppliers and facilitate interaction with suppliers electronically. Finally, firms have to work collaboratively to serve the customers. 

Keywords

cost management, performance, Manufacturing, IT, manufacturing firms

References

        i.        Arani, W., Mukulu, E., Waiganjo, E. & Wambua, J. (2016). Strategic Sourcing an Antecedent of Resilience in Manufacturing firms in Kenya. International Journal of Academic Research in Business and Social Science, 6(10), 1-18.

ii.      Axsater, (2013). Exact and approximate evaluation of Batch-ordering system for two-level distribution systems. Operations Research, 41, 777-785.

iii.    Baiman, S., & Rajan, M. (2012). Incentive issues in inter-firm relationships. Accounting, Organizations and Society, 27, 213-238.

iv.     Bergman, B., & Klefsjo, B. (2010). Quality from customer needs to customer satisfaction. Lund: Studentlitteratur.

v.       Chen, F., Drezner, Z., Ryan, J., & Simchi-Levi, D. (2014). Quantifying the bullwhip effect in a simple Supply Chain: The impact of forecasting, lead times and information. Management Science, 46 (3), 436-443.

vi.     Cheng TCE and Wu YN (2015). The impact of IT integration in a two-level supply chain with multiple retailers. Journal of Operations Research, 56, 1159–1165.

vii.   Chia, R. (2012). The Production of Management Knowledge: Philosophical Underpinnings of Research Design, in Partington, D. (ed.) Essential Skills for Management Research, SAGE Publications Ltd.: London, 1-19.

viii. Clemons, E. K., Reddi, S. P., and Row, M. C. (2013) “The Impact of Information Technology on the Organization of Economic Activity: The „Move to the Middle‟ Hypoproject,” Journal of Management Information Systems (10:2), 20133, pp. 9-35.

ix.     Cox A., Lonsdale C., Watson G., Wu Y. (2004) Supplier relationship management as an investment: evidence from UK study, Journal of General Management, Vol 30, No 4, pp. 27-42.

x.       De Treville, S., Shapiro, R., & Hameri, A.-P. (2004). From supply chain to demand chain: the role of lead time reduction in improving demand chain performance. Journal of Operation Management, 21, 613-627.

xi.     Deuermeyer, B., L. Schwarz, (2011.) A model for the analysis of system service level in warehouse retailer distribution system

xii.   Dubois, A. (2007). Strategic cost management across boundaries of firms. Industrial Marketing Management, 32, 365-374.

xiii. Eroglu & Hofer (2011). Handling multi-lean measures with simulation and simulated annealing. Journal of the Franklin Institute, 348, 1506–1522.

xiv. Fawcett SF, Magnan GM (2012). The rhetoric and reality of supply chain integration. International Journal of Distribution Logistics Management 32(5), 339–361

xv.   Ferreira, W. (2009). Design of a Multi-Echelon Global Supply Chain Network with Microsoft Excel Premium Solver Plataform. All Theses. Paper 534.

xvi. Forsgren, M. and Johanson, J. (2002). Managing Internationalization in Business Network. Gordon & Breach, Philadelphia.

xvii.                       Gallego G and O’zer, O. (2001). Optimal use of demand information in supply chain management. In: Song J and Yao DD (eds).  Structures: Coordination, Information and supply chain. Kluwer Academic Publishers: Boston, 127–168.

xviii.                     Gichuru, M., Iravo, M., & Arani, W.(2015). Collaborative  Practices on Performance of Food and Beverages Companies: A Case Study of Del Monte Kenya Ltd. International Journal of Academic Research in Business and Social Sciences, 5(11), 17-31.

xix. Gunasekaran, A., Patel, C., & Tirtiroglu, E. (2001). Performance measures and metrics in a supply chain environment. International Journal of Operations & Production Management, 21 (1), 71-87.

xx.   Handfield, R.B. and Bechtel, C., 2000. The role of trust and relationship structure in improving supply chain responsiveness. Industrial Marketing Management 31(4), 367-382.

xxi. Hayes, R., Pisano, G., Upton, D. & Wheelwright, S. (2005). Operations, Strategy and Technology: Pursuing the Competitive Edge, New York: John Wiley.

xxii.                       Huan, S.H., Sheoran, S.K., Wang, G. (2004). A review and analysis of supply chain operations reference (SCOR) model. Supply Chain Manage International Journal, 9(1), 23–29.

xxiii.                     Kimani, C. W. (2013).  Management Challenges in Kenya Petroleum Industry: Case of National Oil Corporation of Kenya, International Journal of Social Sciences and Entrepreneurship, 1(3), 231-246.

xxiv.                      Kros, J. F., Falasca, M., & Nadler, S. S. (2006). Impact of just-in-time distribution systems on OEM suppliers. Industrial Management & Data Systems, 106(2), 224–241.

xxv.                        Lambert, D., & Cooper, M. (2016). Issues in supply chain Management. Industrial Marketing Management, 29, 65-83.

xxvi.                      Lwiki, T. (2013). The Impact of Inventory Management Practices on Financial Performance of Sugar Manufacturing Firms in Kenya. International Journal of Business, Humanities and Technology, 3(5), 75-85.

xxvii.                    Moinzadeh, K. (2011). An improved ordering policy for continuous review distribution systems with arbitrary inter-demand time distributions. IIE Transactions, 33, 111–118.

xxviii.                  Musa SN (2011) Identifying risk issues and research advancements in supply chain risk management, International Journal of Production Economics, 133(1), 25–34.

xxix.                      Okanda, O., Namusonge, G.S., & Waiganjo, E.(2016).Influence of Supply Planning Practice on the Performance of the Unit of Vaccines and Immunizations in the Ministry Health, Kenya. International Journal of Healthcare Sciences, 4(1), 276-286.

xxx.                        Okello, J. O., & Were, S. (2014). Influence of supply chain management practices on performance of the Nairobi Securities Exchange’s listed, food manufacturing companies in Nairobi. International Journal of Social Sciences and Entrepreneurship, 1(11), 107-128.

xxxi.                      Pietersen, A. (2012). Working capital management practices of small and medium enterprises in the Western region: A survey of selected SMEs in the Sekondi-Takoradi Metropolis. (Masters in Business Administration), Kwame Nkrumah University of Science and Technology, Kwame.

xxxii.                    Pitamber, H. U. H., & Dharup, M. (2014). Distribution control and valuation systems among retail SMEs in a developing country. Mediterranean Journal of Social Science, 5(8), 81-88.

xxxiii.                  Sahin, F. & Robinson, P. (2012). Flow coordination and information sharing in supply chains: review, implications and directions for future research. Decision Science, 33(4), 505–536.

xxxiv.                  Salawati, S., Tinggi, M., & Kadri, N. (2014). Distribution management in Malaysian construction firms: impact on performance. SIU Journal management, 2, 59-60.

xxxv.                    Sila, I., Ebrahimpour, M., & Birkholz, C. (2016). Quality in supply chain: an empirical analysis SCM. An International Journal, 11, 491-502.

xxxvi.                  Sinha, S, Sarmah SP (2007). Supply chain coordination model with insufficient production capacity and option for outsourcing. Math Comput Modell 46, 1442–1452.

xxxvii.                Topan, E. and Bayindir, Z. P., (2012). Multi-Item Two-Echelon Spare Parts Distribution ... Warehouse Under Compound Poisson Demand (August 2012)

xxxviii.              Tsiakis, P., Shah, N. and Pantelides, C. (2011). Design of Multi-echelon Supply Chain Networks under Demand Uncertainty, Industrial Engineering Chemical Resource. American Chemical Society, 40, 3585-3604.

xxxix.                  Van der Vaart, T., & van Donk, D. P. (2008). A critical review of survey-based research in supply chain integration. International Journal of Production Economics, 111, 42-55.

xl.     World Bank (2016). Kenya Country Economic Memorandum. From Economic Growth to Jobs and Shared Prosperity. The International Bank for Reconstruction and Development, The World Bank: Washington D.C.

xli.   Zhao, W., Wang, Y. (2002). Coordination of joint pricing-production decisions in a supply chain. IIE Trans, 34(8), 701–715.

Cite this Article: