Impact Analysis of Incentive Scheme for Dump Truck Driver to Reduce Overspeeding at Oil and Gas Company

Authors

  • Rangga Budi Aditya Institut Teknologi Sepuluh Nopember, Indonesia
  • Ratna Sari Dewi Institut Teknologi Sepuluh Nopember, Indonesia

DOI:

https://doi.org/10.59141/jrssem.v5i2.1080

Keywords:

driver incentives, dump truck, overspeeding, work safety, linear regression, chi-square

Abstract

The phenomenon of overspeeding in transportation equipment is commonly encountered in daily life. This also frequently occurs in industries involving long-distance travel using transportation or heavy equipment, such as in the mining industry, where dump trucks are widely used. This study focuses on a case in the oil and gas industry. The research adopts a quantitative approach using linear regression analysis to identify the relationship between average daily incentives and the percentage of overspeeding, chi-square test to examine the association between types of incentive schemes and overspeeding categories, and t-test to compare the average incentives between drivers who commit overspeeding violations and those who do not. The data were obtained from the Integrated Journey Management System (IJMS), covering 1,087 dump trucks over a six-month period. The results indicate a positive relationship between incentive amounts and overspeeding levels. Incentive schemes based on trip productivity tend to increase the risk of speed violations compared to distance-based schemes. These findings have important implications for companies and contractors in designing incentive policies that not only consider productivity but also driver safety. Integrating safety indicators into the incentive structure is key to building a safe and sustainable internal transportation system in the oil and gas industry.

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Published

2025-09-16

How to Cite

Aditya, R. B., & Dewi, R. S. (2025). Impact Analysis of Incentive Scheme for Dump Truck Driver to Reduce Overspeeding at Oil and Gas Company. Journal Research of Social Science, Economics, and Management, 5(2), 3297–3303. https://doi.org/10.59141/jrssem.v5i2.1080