Research Article
Artificial Intelligence and Social Trust in Earthquake Early Warning Systems: A Comparative Perspective
Dilek Peri*
Issue:
Volume 11, Issue 4, August 2026
Pages:
89-94
Received:
29 May 2026
Accepted:
1 September 2026
Published:
14 September 2026
Abstract: This study argues that earthquake early warning systems should be evaluated not only in terms of their technical efficiency but also in terms of their capacity to generate social trust. The effectiveness of these systems is shaped not only by their technical performance but also by their ability to influence disaster outcomes, including social vulnerability and post-earthquake housing crises. Although AI-supported early warning systems have significantly improved the early detection of seismic risks, their societal effectiveness remains uneven. This study aims to examine the performance of early warning systems within a broader framework that includes technological infrastructure, social trust, risk perception, and public policy. Adopting a comparative perspective, the cases of Japan and Turkey are analysed to highlight the role of social factors in determining system effectiveness. The findings suggest that technological advancements alone are insufficient for reducing disaster impacts. Instead, the integration of technology with social trust and institutional capacity is essential.
Abstract: This study argues that earthquake early warning systems should be evaluated not only in terms of their technical efficiency but also in terms of their capacity to generate social trust. The effectiveness of these systems is shaped not only by their technical performance but also by their ability to influence disaster outcomes, including social vuln...
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Research Article
Newspaper Vendor Problem: Some Insights Concerning the Expected Value of Perfect Information
Thomas Wedel*
Issue:
Volume 11, Issue 4, August 2026
Pages:
95-100
Received:
4 September 2026
Accepted:
17 September 2026
Published:
14 October 2026
DOI:
10.11648/j.ajmse.20261104.12
Downloads:
Views:
Abstract: The single-period inventory problem with uncertain demand, also known as the Newspaper Vendor Problem, is a commonly encountered occurrence in industry and significant research literature exists on the subject. The critical ratio or fractile method provides the decision maker with a method for quickly calculating the optimal stock quantity that either maximizes expected profit or minimizes the expected cost. The critical ratio or fractile method is based upon the concept of finding the optimal balance between the opportunity costs of having excess inventory versus having a insufficient supply on hand. Little research publication, however, exists concerning EVPI for the Newspaper Vendor problem. This paper addresses that gap in literature. Market research is often available to more accurately estimate next periods demand but usually it has an attached cost. The Expected Value of Perfect Information (EVPI) represents the most that the decision maker would ever pay for market research. It provides the scale for which all sources of information about future demand can be rated. This paper demonstrates the procedure for finding EVPI for cases where demand is estimated by either a discrete or a continuous probability distribution. Practical examples of both profit maximization and cost minimization are provided in the paper.
Abstract: The single-period inventory problem with uncertain demand, also known as the Newspaper Vendor Problem, is a commonly encountered occurrence in industry and significant research literature exists on the subject. The critical ratio or fractile method provides the decision maker with a method for quickly calculating the optimal stock quantity that eit...
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