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A. Adyatama

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An expert survey-based investigation of preferences and trade-offs

Journal article (2026) - Aryasatya Adyatama, Srijith Balakrishnan, Beatrice Cassottana, Jan Anne Annema, Nazli Y. Aydin
Amid escalating climate risks and a widening adaptation finance gap, especially in low- and middle-income countries (LMICs), prioritizing adaptation measures for road infrastructure is essential for building sufficient resilience through both public and private adaptation financing. Despite the urgency of the issue, adaptation finance for infrastructure is often hampered by a lengthy and complex decision-making process that involves conflicting stakeholder interests. Existing taxonomies and benchmarks for adaptation finance typically focus on identifying optimal engineering solutions, often overlooking the numerous factors that influence these implementation decisions. To address this gap, this study develops an approach to understand stakeholders’ and decision makers’ preferences for road infrastructure adaptation measures using empirical evidence based on a global survey of 72 out of 129 respondents from industry, academia, and government. Multi-criteria decision analysis is applied using the Best-Worst Method (BWM) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Four relative importance criteria are assessed, namely, disaster risk reduction, maladaptation risk, adverse societal impact, and project cost, and rank 11 widely-adopted adaptation measures targeting intense precipitation and extreme heat. Results show preventive, cost-effective, and sustainable options, such as improved drainage systems, vegetation plans, and monitoring systems, are consistently favored over capital-intensive structural solutions like alternative road construction and road reallocation. Overall, the findings demonstrate a systematic approach that incorporates diverse stakeholder perspectives into road adaptation planning to enhance the transparency, legitimacy, and implementability of selected adaptation measures. ...
Conference paper (2020) - A. Adyatama
According to the Central Borneo coal mining company annual report, the biggest financial loss due to workplace accidents is when the dump truck drivers were transporting coal from ROM (run of mine) to port which is called as hauling activity. Hauling’s drivers unsafe act which is caused by their tendency to disobey the company’s regulation in a certain situation is the root cause of safety management problems in the coal mining industry. This study proves that dump truck drivers’ mental process before taking a risk on unsafe act is significantly influenced by several cognitive factors, such as, work experience, job dissatisfaction, negative affectivity, and supervisory rating. This study uses Partial Least Square - Structural Equation Model (PLS-SEM) to analyze the correlation between cognitive variables and the tendency to take an unsafe risk. ...
Conference paper (2019) - A. Adyatama, Danu Hadi Syaifullah, Boy Nurtjahyo Moch
One of the biggest financial loss due to workplace accidents at coal mining companies is caused by dump truck drivers' sleepiness during hauling activities, resulting in loss of steering control. Drowsiness is an indicator of occupational fatigue as a body reaction to prevent another serious illness. An efficient fatigue management policy is needed to reduce the number of coal mining workplace accidents. Health and safety department should assess the driver's physical condition is fit to work before hauling activity is started as a preventive program. This study was analyzing the physical factors that significantly influence the dump truck drivers occupational fatigue. A mathematical model to assess the probability of whether dump truck drivers are suspected of having occupational fatigue or not is the result of this study. This study used logistic regression statistical method to give an accurate occupational fatigue calculation which can be implemented in Indonesia coal mining companies. ...