Significance of Driver and Vehicle Key Performance Indicators on Organisational Performance and Customer Satisfaction: Case of Bulk Fuel Supply Chain in Zimbabwe
Keywords:
fuel, hydrocarbon, performance measurement, key performance indicators, truckdriversAbstract
Fuel supply is classified under critical and dangerous goods distribution. Truck Drivers (TD) and trucks are the two components involved in every stage of fuel road-distribution hence a focus on driver and vehicle key performance indicator measurements. The study examines the significance of driver key performance indicators and vehicle performance indicators on organisational performance and on customer satisfaction in the bulk fuel supply chain. A quantitative research methodology was conducted with 91 respondents drawn from the fuel sector. SMART PLS 3.3.3 was utilised for data analysis. The study found that there are positive and significant relationships between Vehicle KPIs and Driver KPIs; Driver KPIs and Organisational Performance (OP); Vehicle KPIs and OP; Driver KPIs and Customer service (CS), and OP and CS. The study also noted that Driver KPIs have significant mediating impact on OP. The mediating role of OP on CS was found to be insignificant.
References
Aguinis, H. (2013). Performance management. Boston, MA: Pearson.
Ambituuni, A., Amezaga, J., & Werner, D. (2015). Risk assessment of petroleum product transportaton by road: A framework for regulatory improvement. Safety Science, 79(2015), 324-335. Retrieved from htps://doi.org/10.1016/j.ssci.2015.06.022
Appleton, L. (2017). Libraries and key performance indicators. In L. Appleto, An overview of key performance indicators (pp. 61-72). Cambridge: Chandos Publishing.
Babbie, E., & Mouton, J. (2014). The Practice of Social Research. Oxford: Oxford University Press.
Bimha, H., Hoque, M., & Munapo, E. (2020). The impact of supply chain management practices on industry competitiveness: A mixed-methods study on the Zimbabwean petroleum industry. African Journal of Science, Technology, Innovation and Development, 12(1), 97-109.
Casal, J. ( 2018). Chapter 12 - Transportaton of hazardous materials . In Evaluaton of the effects and consequences of major accidents in industrial plant (pp. 483-519). Elsevier: Amsterdam.
Conca , A., Ridella , C., & Sapori, E. (2016). A risk assessment for road transportaton of dangerous goods: A routng soluton,. Transportaton Research Procedia, 14(2016), 2890-2899. doi:https://doi.org/10.1016/j.trpro.2016.05.407
Davidovic, J., Pešić, D., & Bo, K. L. (2020). The Significance of the Development of Road Safety Performance Indicators Related to Driver Fatigue. Transportation Research Procedia, 45(2020), 333–342. doi:10.1016/j.trpro.2020.03.024
Dijkstra , T. K., & Henseler, J. (2015). Consistent and Asymptotically Normal PLS Estimators for Linear Structural Equations. Computational Statistics & Data Analysis, 81(1), 10-23.
Douglas , M., & Swartz, S. (2017). Knights of the road: Safety, ethics, and the professional truck driver’,. Journal of Business Ethics, 142(3), 567-58. doi:htps://doi.org/10.1007/ s10551-015-2761-7
Dubey, R., & Gunasekaran, A. (2015). The role of truck driver on sustainable transportation and logistics. Industrial and Commercial Training, 47(31), 27-134. Retrieved from htps://doi.org/10.1108/ICT-08-2014-0053
Elhuni , R. M., & Ahmad, M. M. (2017). Key performance indicators for sustainable producton evaluaton in oil and gas sector. Procedia Manufacturing, 11(2017), 718- 724. doi: htps://doi.org/10.1016/j.promfg.2017.07.172
Fawcet, S., Ellram, L., & Orgden, J. (2014). Supply chain management: From vision to implementaton. London: Pearson.
Fiorencio , L., Oliveira , F., Nunes, P., & Hamacher, E. (2015). Investment planning in the petroleum downstream infrastructure. Internatonal Transactons in Operatonal Research, 22(2), 339-362. doi:htps://doi.org/10.1111/itor.12113
Gefen, D., & Straub, D. W. (2005). A practical guide to factorial validity using PLS-Graph: tutorial and annotated example. Communications of the AIS, 16, 91-109.
Hald, K., & Mouritsen, J. (2018). The evolution of performance measurement systems in a supply chain: A longitudinal case study on the role of interorganisational factors. International Journal of Production Economics, 205(2018), 256-271.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. J. of the Acad. Mark. Sci., 43, 115-135. Retrieved from https://doi.org/10.1007/s11747-014-0403-8
Hu, L., & Bentler, P. (1999). Cutoff criteria for fit indices in covariance structure analysis: conventional criteria versus new alternatives. Structural Equation Modelling, 1-55.
Hugos, M. (2018). Essentals of supply chain management. Hoboken, NJ.: John Wiley & Sons, Inc.
Kazemi , Y., & Szmerekovsky, J. (2015). Modelling downstream petroleum supply chain: The importance of mult-mode transportaton to strategic planning. Transportaton Research Part E, 83(2015), 111-125. doi:htps://doi.org/10.1016/j. tre.2015.09.004
Li, Z., & Jiang, C. (2016). Study on the Transportation Problem of Petrol Secondary Distribution with Considering Shortage Costs. Open Journal of Modelling and Simulation, 34-40.
Lohmoller, J. B. (1989). Latent Variable Path Modeling with Partial Least Squares.
Heidelberg: Physica.
Makhanda, G., Pwaka, O., & Mafini. (2019). Liquid Petroleum Gas Supply Chain Challenges in Rural Medical Facilities in Zimbabwe. (pp. 288-301). Cham: Springer.
Moss, S. (2021, August 06). Fit indices for structural equation modeling. Retrieved from Sico Tests: https://www.sicotests.com/psyarticle.asp?id=277
Mules, I. (2019, January 14). Zimbabwe: Fuel price hike sparks protests amid economic crisis. Retrieved from DW.Com: htps://www.dw. com/en/zimbabwe-fuel-price-hike- sparks-protests-amid-economic-crisis/ a-47078162.
Newman, W. (2014). Social research methods: Quanttatve and qualitatve approaches.
London.: Person Educaton.
Parmenter, D. (2015). Key performance indicators: Developing, implementng, and using winning KPIs. Hobok en, N.J: John Wiley & Sons iNC.
Pearson, Boston , M., Chukwuma , A. O., & Atelhe, G. (2015). Fuel tanker explosion disaster, road safety and human security in Nigeria: A threat-impact analysis. Journal of Public Policy & Governance, 2(2), 68-74.
The Global Economy. (2021, August 04). Oil consumption - Country rankings. Retrieved from The Global Economy.com: https://www.theglobaleconomy.com/rankings/oil_consumption/
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
