Effect of Internal Competencies on the Operational Performance of Manufacturing Firms in Chemical and Allied Industry, Kenya
Authors
Chuka University (Kenya)
Chuka University (Kenya)
Chuka University (Kenya)
Article Information
DOI: 10.47772/IJRISS.2026.100900194
Subject Category: Supply Chain Management
Volume/Issue: 10/9 | Page No: 2700-2717
Publication Timeline
Submitted: 2026-09-16
Accepted: 2026-09-22
Published: 2026-10-06
Abstract
ABSTRACT
Internal competencies has emerged as a strategic imperative for manufacturing firms operating in both local and global markets. However, despite increased investments in supply chain systems and organizational capabilities, chemical and allied manufacturing firms continue to experience inefficiencies reflected in delayed deliveries, high operational costs and inconsistent production performance. Therefore, this study examined the relationship between Internal competencies and operational performance of chemical and allied manufacturing firms in Kenya. The study was anchored on the, Resource-Based View theory. The study employed a cross-sectional descriptive research design. The unit of analysis was 94 chemical and allied manufacturing firms while the unit of observation was 282 personnel, comprising of 94 operations managers, 94 supply chain managers and 94 procurement officers. A census technique was adopted and primary data was collected using a structured questionnaire. Piloting of the study was conducted on 28 respondents from 10 chemical and allied non registered firms under KAM in Nairobi County. The validity of the research was ascertained by expert review. Reliability of the instruments was tested using Cronbach’s Alpha. Descriptive statistics were used to summarize the key characteristics of data using mean, standard deviation, minimum and maximum. Ordinary least squares regression analysis was used to examine the relationship between variables at a 5% significance level with the aid of Statistical Package for Social Sciences (SPSS) version 31.0. Linearity, multi-collinearity, normality and homoscedasticity tests was performed to check whether ordinary least squares regression assumptions hold. Data was presented using tables and graphs. The findings revealed that supply chain responsiveness had a positive and statistically significant effect on operational performance (β=0.627, p=0.00<0.05). The study concluded that internal significantly enhances the operational performance of manufacturing firms in the chemical and allied industry in Kenya. The study therefore recommends that firms should support sector-specific training programs and technology upgrading schemes that raise internal competencies across chemical firms.
Key words: Internal Competencies, Operational Performance and Chemical and Allied Manufacturing Firms
Keywords
Internal Competencies, Operational Performance and Chemical and Allied Manufacturing Firms
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References
1. Adoe, V. S. (2025). The Role of Core Competencies in Enhancing Operational Efficiency in Micro, Small and Medium Enterprises (MSMEs) in Indonesia. The Eastasouth Management and Business, 4(01), 185-194. [Google Scholar] [Crossref]
2. Ahmed, R., Karim, S., & Hossain, M. (2024). Logistics responsiveness and operational performance among retail supermarket chains in Bangladesh. Journal of Retail Supply Chain Management, 11(1), 54-70. [Google Scholar] [Crossref]
3. Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Sage. [Google Scholar] [Crossref]
4. Al Humdan, E., Shi, Y., Behnia, M., & Najmaei, A. (2020). Supply chain agility: a systematic review of definitions, enablers and performance implications. International Journal of Physical Distribution & Logistics Management, 50(2), 287-312. [Google Scholar] [Crossref]
5. Ali, A. (2020). Information Sharing and Supply Chain Responsiveness of Manufacturing Firms listed at Nairobi Securities Exchange, Kenya (Doctoral dissertation, University of Nairobi). [Google Scholar] [Crossref]
6. Association, K. (2026). Kenya Association of Manufacturers. Kenya Association of Manufacturers. https://www.kam.co.ke/ [Google Scholar] [Crossref]
7. Atkinson, A. C., Riani, M., & Corbellini, A. (2021). The box–cox transformation: Review and extensions. DOI: 10.1214/20-STS778 [Google Scholar] [Crossref]
8. Bag, S., Gupta, S., Kumar, A., & Sivarajah, U. (2021). Role of technological capability and supply chain responsiveness in improving organizational performance. Technological Forecasting and Social Change, 166, 120607. [Google Scholar] [Crossref]
9. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. [Google Scholar] [Crossref]
10. Barney, J. B. (1986). Strategic factor markets: Expectations, luck and business strategy. Management Science, 32(10), 1231–1241. https://doi.org/10.1287/mnsc.32 .10.1231 [Google Scholar] [Crossref]
11. Benzidia, S., & Makaoui, N. (2020, July). Improving SMEs performance through supply chain flexibility and market agility: IT orchestration perspective. In Supply chain forum: An international journal (Vol. 21, No. 3, pp. 173-184). Taylor & Francis. [Google Scholar] [Crossref]
12. Chen, M., Tan, X., Zhu, J., & Dong, R. K. (2025). Can supply chain digital innovation policy improve the sustainable development performance of manufacturing companies? Humanities and Social Sciences Communications, 12(1), 1-15. [Google Scholar] [Crossref]
13. Chen, X., Li, Y., & Huang, Z. (2022). Demand responsiveness and operational performance in electronic manufacturing firms in China. International Journal of Production and Operations Management, 14(3), 145-163. [Google Scholar] [Crossref]
14. Company search | Lusha. (2024, January 4). Lusha. https://www.lusha.com/company-search/chemical-manufacturing/3b7d526ebc/kenya/124/ [Google Scholar] [Crossref]
15. Davis, G. F., & DeWitt, T. (2021). Organization theory and the resource-based view of the firm: The great divide. Journal of Management, 47(7), 1684-1697. [Google Scholar] [Crossref]
16. Emon, M. M. H. (2025). The mediating role of supply chain responsiveness in the relationship between key supply chain drivers and performance: Evidence from the FMCG industry. Brazilian Journal of Operations & Production Management, 22(1), 10-14488. [Google Scholar] [Crossref]
17. Fernando, Y., & Wulansari, P. (2021). Perceived understanding of supply chain integration, communication and teamwork competency in the global manufacturing companies. European Journal of Management and Business Economics, 30(2), 191-210. [Google Scholar] [Crossref]
18. Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). Sage. [Google Scholar] [Crossref]
19. Freeman, R. E., Dmytriyev, S. D., & Phillips, R. A. (2021). Stakeholder theory and the resource-based view of the firm. Journal of management, 47(7), 1757-1770. [Google Scholar] [Crossref]
20. Government of Kenya. (2008). Kenya Vision 2030 | Kenya Vision 2030. Vision2030.Go.ke. https://vision2030.go.ke/ [Google Scholar] [Crossref]
21. Gunasekaran, A. (1999). Agile manufacturing: a framework for research and development. International journal of production economics, 62(1-2), 87-105. [Google Scholar] [Crossref]
22. Gunasekaran, A., Yusuf, Y. Y., Adeleye, E. O., Papadopoulos, T., Kovvuri, D., & Geyi, D. A. G. (2019). Agile manufacturing: an evolutionary review of practices. International Journal of Production Research, 57(15-16), 5154-5174. [Google Scholar] [Crossref]
23. Hweshure, N. C. (2022). Operational Capabilities, Firm Competitive Performance and Supply Chain Responsiveness in the Fast-moving Consumer Good Manufacturing Industry in Gauteng Province (Master's thesis, Vaal University of Technology (South Africa). [Google Scholar] [Crossref]
24. Jafari, H., Ghaderi, H., Malik, M., & Bernardes, E. (2023). The effects of supply chain flexibility on customer responsiveness: the independent role of innovation orientation. Production Planning & Control, 34(16), 1543-1561. [Google Scholar] [Crossref]
25. Kapoor, M., & Aggarwal, V. (2020). Tracing the economics behind dynamic capabilities theory. International Journal of Innovation Science, 12(2), 187-201 [Google Scholar] [Crossref]
26. Kazungu, M. K. (2024). Effect of Value Chain Financing on the Financial Performance of Agricultural and Manufacturing Firms Listed at the Nairobi Securities Exchange (Doctoral dissertation, University of Nairobi). [Google Scholar] [Crossref]
27. Kenya Association of Manufacturers. (2026). Sector reports 2026. https://www.kam.co.ke/ [Google Scholar] [Crossref]
28. Kenya National Bureau of Statistics. (2025). Economic survey 2025. https://www.knbs.or.ke/ [Google Scholar] [Crossref]
29. Kenya. (2007). Kenya vision 2030. Government of the Republic of Kenya. [Google Scholar] [Crossref]
30. KNBS. (2024). Kenya National Bureau of Statistics. Kenya National Bureau of Statistics. https://www.knbs.or.ke/ [Google Scholar] [Crossref]
31. Land, A., Gruchmann, T., Siems, E., & Beske-Janssen, P. (2022). Dynamic capabilities theory. In Handbook of Theories for Purchasing, Supply Chain and Management Research (pp. 378-398). Edward Elgar Publishing. [Google Scholar] [Crossref]
32. Li, Y., Wang, X., Gong, T., & Wang, H. (2023). Breaking out of the pandemic: how can firms match internal competence with external resources to shape operational resilience? Journal of Operations Management, 69(3), 384-403. [Google Scholar] [Crossref]
33. Lizzy, A. O. (2024). Strategic Capabilities and Performance of Selected Manufacturing Small and Medium Enterprises in Nairobi City County, Kenya. [Google Scholar] [Crossref]
34. Lubis, N. W. (2022). Resource based view (RBV) in improving company strategic capacity. Research Horizon, 2(6), 587-596. [Google Scholar] [Crossref]
35. Macharia, K. K., Gathiaka, J. K., & Ngui, D. (2022). Energy efficiency in the Kenyan manufacturing sector. Energy Policy, 161, 112715. [Google Scholar] [Crossref]
36. Machiri, N. S., Oloko, M., Ngugi, J. K., & Odhiambo, R. (2023). Corporate technological capability as a driver to firm performance: A study on firms listed at the Nairobi securities exchange. Economit Journal: Scientific Journal of Accountancy, Management and Finance, 3(3), 148-162. [Google Scholar] [Crossref]
37. MacKenzie, S. B., & Podsakoff, P. M. (2012). Common method bias in marketing: Causes, mechanisms and procedural remedies. Journal of Retailing, 88(4), 556–562. [Google Scholar] [Crossref]
38. Mbima, D., & Tetteh, F. K. (2023). Effect of business intelligence on operational performance: the mediating role of supply chain ambidexterity. Modern Supply Chain Research and Applications, 5(1), 28-49. [Google Scholar] [Crossref]
39. Mikalef, P., Islam, N., Parida, V., Singh, H., & Altwaijry, N. (2023). Artificial intelligence (AI) competencies for organizational performance: A B2B marketing capabilities perspective. Journal of Business Research, 164, 113998. [Google Scholar] [Crossref]
40. Miller, D. (2019). The resource-based view of the firm. In Oxford research encyclopedia of business and management. [Google Scholar] [Crossref]
41. Mwinuka, D. (2022). The Impact of Efficient Supply Chain Management on Firm Performance (Doctoral dissertation, Institute of accountancy Arusha). [Google Scholar] [Crossref]
42. Nenavani, J., & Jain, R. K. (2022). Examining the impact of strategic supplier partnership, customer relationship and supply chain responsiveness on operational performance: the moderating effect of demand uncertainty. Journal of Business & Industrial Marketing, 37(5), 995-1011. [Google Scholar] [Crossref]
43. Ngirachu, J. K. (2020). Coverage of the Big Four Agenda in the Daily Nation and The Standard newspapers in Kenya. [Google Scholar] [Crossref]
44. Ngunzi, V., Njoka, F., & Kinyua, R. (2023). Modeling, simulation and performance evaluation of a PVT system for the Kenyan manufacturing sector. Heliyon, 9(8). [Google Scholar] [Crossref]
45. Otieno, C. O., & Thogori, M. (2024). Lean Supply Chain Management and Performance of Chemical & Allied Manufacturing Sector in Nairobi City County. International Journal of Social Sciences Management and Entrepreneurship (IJSSME), 8(4). [Google Scholar] [Crossref]
46. Richey, R. G., Roath, A. S., Adams, F. G., & Wieland, A. (2022). A responsiveness view of logistics and supply chain management. Journal of Business Logistics, 43(1), 62-91. [Google Scholar] [Crossref]
47. Salman, M., Ganie, S. A., & Saleem, I. (2020). Employee competencies as predictors of organizational performance: a study of public and private sector banks. Management and Labour Studies, 45(4), 416-432. [Google Scholar] [Crossref]
48. Salvato, C., & Vassolo, R. (2018). The sources of dynamism in dynamic capabilities. Strategic management journal, 39(6), 1728-1752. [Google Scholar] [Crossref]
49. Saragih, J., Tarigan, A., Silalahi, E. F., Wardati, J., & Pratama, I. (2020). Supply chain operational capability and supply chain operational performance: Does the supply chain management and supply chain integration matters? International Journal of Supply Chain Management. [Google Scholar] [Crossref]
50. Secretariat, M. S. (2021). Ministry of Economy, Trade and Industry. Basic Document in March, 2021. [Google Scholar] [Crossref]
51. Siagian, H., & Johono, D. F. (2022). Impact of supply chain integration, supply chain responsiveness and innovation capability on operational performance in era covid-19. Petra International Journal of Business Studies, 5(1), 30-43. [Google Scholar] [Crossref]
52. Siagian, H., Tarigan, Z. J. H., & Jie, F. (2021). Supply chain integration enables resilience, flexibility and innovation to improve business performance in COVID-19 era. Sustainability, 13(9), 4669. [Google Scholar] [Crossref]
53. Tarigan, Z. J. H., Siagian, H., & Jie, F. (2021). Impact of internal integration, supply chain partnership, supply chain agility and supply chain resilience on sustainable advantage. Sustainability, 13(10), 5460. [Google Scholar] [Crossref]
54. Teece, D. J. (2018). Dynamic capabilities as (workable) management systems theory. Journal of Management & Organization, 24(3), 359-368. [Google Scholar] [Crossref]
55. Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533. [Google Scholar] [Crossref]
56. Wang, Y., & Webster, S. (2022). Product flexibility strategy under supply and demand risk. Manufacturing & Service Operations Management, 24(3), 1779-1795. [Google Scholar] [Crossref]
57. Wardhana, A. H., Setywan, A., & Mon, M. D. (2026). The Role of Digital Competency in the influence of operational competence, Managerial competence and technical competence on organizational performance. Asian Journal of Management, Entrepreneurship and Social Science, 6(01), 349-364. [Google Scholar] [Crossref]
58. Weill, P., & Olson, M. H. (1989). An assessment of the contingency theory of management information systems. Journal of management information systems, 6(1), 59-86. [Google Scholar] [Crossref]
59. Were, A. (2016). Manufacturing in Kenya: Features, challenges and opportunities. International Journal of Science, Management and Engineering, 4(6), 15-26. [Google Scholar] [Crossref]
60. Wooldridge, J. M. (2013). Introductory econometrics: A modern approach (5th ed.). South-Western Cengage Learning. [Google Scholar] [Crossref]
61. Wooldridge, J. M. (2016). Introductory econometrics a modern approach. South-Western cengage learning. ISBN: 978-1-305-27010-7 [Google Scholar] [Crossref]
62. Yusuf, Y. Y., Sarhadi, M., & Gunasekaran, A. (1999). Agile manufacturing:: The drivers, concepts and attributes. International Journal of production economics, 62(1-2), 33-43. [Google Scholar] [Crossref]
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