PurposeThis paper aims to analyze the risks faced by the Cambodian rice supply chain (RSC), including risk identification, risk investigation and risk management.Design/methodology/approachThe first qualitative area of exploration from this exploratory sequential design is to identify the potential risks, in which the authors conduct in-depth interviews with ten different experts in Cambodia. Using the structural equation model (SEM) in AMOS and descriptive statistics analysis, this study investigates the risks that affect the RSC performance on an environmental, social and economic basis and subsequently proposes risk management strategies. The authors collect quantitative data from 200 Cambodian farmers through interviews and surveys.FindingsThe results illustrate that the farm households face 18 risk factors. The researchers consolidate 18 risk factors into four classifications: supply risks, production risks, demand risks and environmental risks. Nine experts out of the ten who were interviewed (90%) consider themselves “highly vulnerable” (with a rating of 4 or 5 on the Likert scale), while only one expert has a “neutral” stance (with a rating of 3 on the Likert scale); these results concerning risk identification are visualized in the likelihood effect matrix of the RSC. After investigating the risks, the authors found that RSC performance is significantly affected by the RSC risks. In particular, four groups are created, representing two different approaches to mitigate, avoid, transfer and cope with agricultural risks, i.e. ex ante and ex post risk management strategies.Originality/valueThis study fully answers research questions regarding risk identification, risk investigation and risk management.
Driver fatigue is a recognized risk factor for commercial road transport industry drivers. The aim of this cross-sectional research was to assess the fatigue and its determining factors among 99 chemical transportation drivers in Chonburi. Driving fatigue was assessed by both subjective questionnaire (n = 99) and flicker fusion instrument (n = 88). The association between driving fatigue and related factors were analyzed by Pearson’s correlation and Chi-square (χ2). The results revealed that the prevalence of fatigue as assessed by critical flicker fusion analyzer, subjective fatigue question and either one of the instruments were 32.32 %, 16.16 % and 43.43 %, respectively. Multiple regression analysis indicated that the predictive factors of objective fatigue were alcohol drinking, musculoskeletal disorder and road accident history. The results suggest thatscreening for alcohol use and musculoskeletal disorders was further needed for policy settings and routine checks.
Problem statement: Pricing is one of the fundamental management decisions required by a truckload carrier. Traditional pricing based on an average all relevant costs including fixed and variable costs is not capable of providing adequate margins that prevent losses during operation uncertainties inherent in truckload operation including demand variability and variation in service times. Approach: This study utilizes Conditional Value at Risk (CVaR) as a measure of risk with significant advantage over Value at Risk (VaR), to full truckload pricing when conditions are unpredictable. It criterion focuses on the tail of the loss distribution and provides a measure of the expected loss exceeding Value-at-Risk. Therefore, it was applied to control the maximum loss or the minimum gain within a specified tolerance level to enable more flexible full truckload pricing. A simulation model is developed to capture the stochastic patterns inherent in the operation of full truckload network. Results: Price per trip from 95% CVaR is less than traditional pricing for delivery over short distances while extremely higher for delivery over long distances. We apply traditional prices back to the truckload operation and network imitated in the simulation model and find that even the traditional prices are set to include a certain percentage of profit over the average cost there is still a large chance that the carrier will be subjected to a loss. Conclusion: The numerical analysis for this study demonstrates a pricing method for transportation carriers who are risk averse. Transportation carriers in this group dislike risk and will stay away from high risk.
This study examined the impact of rest breaks on driver fatigue. The study developed and tested a work-rest model to reduce fatigue for chemical truck drivers, following International Labor Organization (ILO) guidelines. The model was tested on a small sample of workers driving from a gas filling plant in Sattahip District, Chonburi Province to Muang District, Samut Sakorn Province. To test the model, data on driver fatigue was assessed using an interview questionnaire and a flicker fusion instrument, and the Z-test was used to compare fatigue among three work-rest patterns. The results showed 24% of working time (173 min) for the drivers sampled was allocated for relaxation, based on a mean driving time of 12 h. Two work-rest models were developed, considering driving distance, time and levels of fatigue. The findings indicated that the regular schedule pattern resulted in the highest levels of fatigue, both as measured by subjective questionnaire and objectively by the critical flicker frequency value (CFF). Model II, with two 26-min rest breaks, offers a more effective model to reduce fatigue, using less driving time than model I, with four 13-min rest breaks. However, this resulted in other new challenges, for example, the need for extended shifts, an increase in production costs and personal costs. Transportation business owners should prepare meals and drinks for chemical transport drivers on the Sattahip to SamutSakorn route (and other cross-province routes) in order to make it more convenient for themto follow safety practices.
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