An integrated Multi-Criteria Decision Making Model for Sustainability Performance Assessment for Insurance Companies

To stay competitive in a business environment, continuous performance evaluation based on the triple bottom line standard of sustainability is necessary. There is a gap in addressing the computational expense caused by increased decision units due to increasing the performance evaluation indices to more accuracy in the evaluation. We successfully addressed these two gaps through (1) using principal component analysis (PCA) to cut the number of evaluation indices, and (2) since PCA itself has the problem of merely using the data distribution without considering the domain-related knowledge, we utilized Analytic Hierarchy Process (AHP) to rank the indices through the expert’s domain-related knowledge. We propose an integrated approach for sustainability performance assessment in qualitative and quantitative perspectives. Fourteen insurance companies were evaluated using eight economic, three environmental, and four social indices. The indices were ranked by expert judgment though an analytical hierarchy process as subjective weighting, and then principal component analysis as objective weighting was used to reduce the number of indices. The obtained principal components were then used as variables in the data envelopment analysis model. So, subjective and objective evaluations were integrated. Finally, for validating the results, Spearman and Kendall’s Tau correlation tests were used. The results show that Dana, Razi, and Dey had the best sustainability performance.This article belongs to the Special Issue Sustainability Assessmen

Sustainable Assessment in Supply Chain and Infrastructure Management

In the competitive business environment or public domain, the sustainability assessment in supply chain and infrastructure management are important for any organization. Organizations are currently striving to improve their sustainable strategies through preparedness, response, and recovery because of increasing competitiveness, community, and regulatory pressure. Thus, it is necessary to develop a meaningful and more focused understanding of sustainability in supply chain management and infrastructure management practices. In the context of a supply chain, sustainability implies that companies identify, assess, and manage impacts and risks in all the echelons of the supply chain, considering downstream and upstream activities. Similarly, the sustainable infrastructure management indicates the ability of infrastructure to meet the requirements of the present without sacrificing the ability of future generations to address their needs. The complexities regarding sustainable supply chain and infrastructure management have driven managers and professionals to seek different solutions. This Special Issue aims to provide readers with the most recent research results on the aforementioned subjects. In addition, it offers some solutions and also raises some questions for further research and development toward sustainable supply chain and infrastructure management

Competing Methods for Efficiency Measurement : A Systematic Review of Direct DEA vs SFA/DFA Comparisons

Various authors have advised a wait and see approach in evaluating the relative precision of alternative techniques, such as data envelopment analysis (DEA) and stochastic frontier analysis (SFA), in estimating industry-average and firm-specific inefficiency. Chirikos and Sear (2000), for example, contend that "policy-makers may be well advised to wait until additional research clarifies reasons why DEA and stochastic frontier models yield divergent results" (p. 1389). The main objective of this paper is to highlight the likely trade-offs between competing methods based on direct empirical comparisons using simulated data and to demonstrate the wealth of evidence bearing on a range of real-world applications. Whilst this systematic review indicates that a good deal of evidence is already available, evidence of a different sort may be required to identify a `correct' approach in addressing specific policy problems. In particular, the now routine practice of cross checking should be taken one step further to include realistic simulation studies along-side real-world DEA vs SFA comparisons

Sağlık Hizmetlerinde Performans Değerlendirmede Kullanılan Araç ve Yöntemler

Son yıllarda, sağlık sistemlerinde, hastaların artan beklenti ve ihtiyaçları doğrultusunda hızla gelişmekte olan bağımsız ve tarafsız performans değerlendirme kavramı, denetlenebilir, hasta odaklı, hesap verebilirliği fazla olan, verimli, iyileştirilebilir, sürdürülebilir ve erişilebilir sistemler meydana getirebilmek açısından büyük bir önem taşımaktadır. Performans değerlendirme sürecinin ana aktörlerinden biri, belirli performans göstergelerinin tanımlanabileceği ve sağlık sisteminde gereken alanlarda düzenli olarak kullanılabilecek bir yapının sunulması olmakla beraber, bu sürece netlik kazandırmak amacıyla performansın bütünsel bir görünümünü oluşturabilmek için konuyu odak noktası alan araştırmacılar tarafından, sağlık sisteminin çeşitli yapıtaşlarında farklı araç ve yöntemler kullanılarak çalışmalara devam edilmektedir. Sağlık hizmetlerinde performans değerlendirme, her ne kadar zor ve karmaşık bir süreç olsa da sistemin iyileştirilebilmesi-geliştirilebilmesi adına kritik bir önem taşımaktadır. Bu derleme çalışmasında, sağlık alanında 2011-2021 yılları arasında gerçekleştirilen çeşitli performans değerlendirme çalışmalarında kullanılan araç ve yöntemler incelenerek özetlenmiş, çalışmalarda öne çıkan kavramlar sınıflandırılmıştır. Çalışmanın sonucunda literatürdeki eksikliklerin gözlemlenmesiyle, gerçekleştirilen çalışmanın, mevcut literatüre katkı sağlaması amaçlanmıştır

A decision support system for assessing management interventions in a mental health ecosystem: The case of Bizkaia (Basque Country, Spain)

Evidence-informed strategic planning is a top priority in Mental Health (MH) due to the burden associated with this group of disorders and its societal costs. However, MH systems are highly complex, and decision support tools should follow a systems thinking approach that incorporates expert knowledge. The aim of this paper is to introduce a new Decision Support System (DSS) to improve knowledge on the health ecosystem, resource allocation and management in regional MH planning. The Efficient Decision Support-Mental Health (EDeS-MH) is a DSS that integrates an operational model to assess the Relative Technical Efficiency (RTE) of small health areas, a Monte-Carlo simulation engine (that carries out the Monte-Carlo simulation technique), a fuzzy inference engine prototype and basic statistics as well as system stability and entropy indicators. The stability indicator assesses the sensitivity of the model results due to data variations (derived from structural changes). The entropy indicator assesses the inner uncertainty of the results. RTE is multidimensional, that is, it was evaluated by using 15 variable combinations called scenarios. Each scenario, designed by experts in MH planning, has its own meaning based on different types of care. Three management interventions on the MH system in Bizkaia were analysed using key performance indicators of the service availability, placement capacity in day care, health care workforce capacity, and resource utilisation data of hospital and community care. The potential impact of these interventions has been assessed at both local and system levels. The system reacts positively to the proposals by a slight increase in its efficiency and stability (and its corresponding decrease in the entropy). However, depending on the analysed scenario, RTE, stability and entropy statistics can have a positive, neutral or negative behaviour. Using this information, decision makers can design new specific interventions/policies. EDeS-MH has been tested and face-validated in a real management situation in the Bizkaia MH system.The present research study is frameworked in the REFINEMENT Spain project (Project PI15/01986), funded by the Carlos III Health Institute (http://www.isciii.es/)

Disentangling the resiliency of international transportation systems under uncertainty by a novel multi-layer spherical fuzzy decision-making framework:Evidence from an emerging economy

Although transportation systems play a critical role in the global socio-economic facets, they are acknowledged as vulnerable systems directly impacted by unexpected events, e.g., natural calamities, war, traffic accidents, terrorist attacks, and public health. In this respect, improving the resiliency of transportation systems under uncertainty is a controversial global challenge that this study could underpin. To do so, a systematic literature review (SLR) extracted a list of resiliency factors for resilient transportation systems. Next, a novel version of spherical fuzzy Delphi (SFD) screened factors, considering the case of Iran’s international maritime transportation system. Moreover, the causal network relationship of the finalised factors was analysed by a novel hybrid spherical fuzzy approach, including a decision-making trial and evaluation laboratory (DEMATEL) and the analytic network process (ANP). Later, the unexpected events that occurred after 2000 were investigated. The SLR deeply investigated 51 of the top relevant articles. As a result, 12 factors and 22 subfactors that affect transportation systems resiliency were extracted. Notably, the rest of the findings primarily apply to the Iranian context. By implementing the SFD, ten factors were screened for Iran’s international maritime transportation system and then analysed by SF-DEMATEL. After, the analysed factors were weighted by SFANP, where “recoverability” was selected as the most critical factor, and the “technological and communicational” factor was chosen as the least critical factor. Furthermore, the results provide a critical analysis of the policies adopted by Iran’s international maritime transportation system to enhance resiliency under disruptive events

Disentangling the resiliency of international transportation systems under uncertainty by a novel multi-layer spherical fuzzy decision-making framework:Evidence from an emerging economy

Although transportation systems play a critical role in the global socio-economic facets, they are acknowledged as vulnerable systems directly impacted by unexpected events, e.g., natural calamities, war, traffic accidents, terrorist attacks, and public health. In this respect, improving the resiliency of transportation systems under uncertainty is a controversial global challenge that this study could underpin. To do so, a systematic literature review (SLR) extracted a list of resiliency factors for resilient transportation systems. Next, a novel version of spherical fuzzy Delphi (SFD) screened factors, considering the case of Iran’s international maritime transportation system. Moreover, the causal network relationship of the finalised factors was analysed by a novel hybrid spherical fuzzy approach, including a decision-making trial and evaluation laboratory (DEMATEL) and the analytic network process (ANP). Later, the unexpected events that occurred after 2000 were investigated. The SLR deeply investigated 51 of the top relevant articles. As a result, 12 factors and 22 subfactors that affect transportation systems resiliency were extracted. Notably, the rest of the findings primarily apply to the Iranian context. By implementing the SFD, ten factors were screened for Iran’s international maritime transportation system and then analysed by SF-DEMATEL. After, the analysed factors were weighted by SFANP, where “recoverability” was selected as the most critical factor, and the “technological and communicational” factor was chosen as the least critical factor. Furthermore, the results provide a critical analysis of the policies adopted by Iran’s international maritime transportation system to enhance resiliency under disruptive events

The Influence of Public Service Motivation on Ethical Behaviour and Organizational Performance in Public Administration Sector: Evidence from the Hashemite Kingdom of Jordan

The Hashemite Kingdom of Jordan (HKJ) faces internal and external challenges and hazards that pose significant encounters for HKJ. Such challenges cast a heavy shadow on several public sectors, the most important of which is the public health sector. However, this dissertation aimed to investigate the influence of Public Service Motivation on Ethical behavior and Organizational Performance in Jordanian public hospitals. This dissertation had been divided into two folds that filled numerous flagrant gaps in the arena of PSM. In the first fold, we investigated the influence of PSM on Ethical Behavior using three-level models via SEM. In the second fold, we contribute to the methodological linking between PSM and Organizational Performance using econometrics techniques