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Despite the remarkable growth in the insurance industry over the past two decades, few studies evaluate the performance of Takaful vs. conventional insurance firms with focus on the standard structure of production as a two-stage process, that is, operations and profitability. Thus, this research examines the performance of Saudi Arabia's insurance market using a two-stage data envelopment analysis to assess the efficiency of the two production stages and accordingly, define the leader stage. The empirical results obtained using data for 26 conventional and seven Takaful insurance firms for 2014-2017 indicate declining average efficiency scores for both firm types. In other words, Saudi Arabia's insurance market warrants new consolidation and foreign participation regulations to assist firms in becoming dynamic and strong. This study makes a significant contribution given the dearth of an exclusive analysis on the two-stage efficiency of Saudi Arabia's Takaful and conventional insurance firms. Further, it offers key implications for decision makers, regulators, and managers associated with the insurance industry in Saudi Arabia and other emerging insurance markets.

The pandemic caused by the spread of the SARS-CoV-2 virus forced governments around the world to impose lockdowns, which mostly involved restricting non-essential activities. Once the rate of infection is manageable, governments must implement strategies that reverse the negative effects of the lockdowns. A decision support system based on fuzzy theory and multi-criteria decision analysis principles is proposed to investigate the importance of a set of key indicators for post-COVID-19 reopening strategies. This system yields more reliable results because it considers the hesitation and experience of decision makers. By including 16 indicators that are utilized by international organizations for comparing, ranking, or investigating countries, our results suggest that governments and policy makers should focus their efforts on reducing violence, crime and unemployment. The provided methodology illustrates the suitability of decision science tools for tackling complex and unstructured problems, such as the COVID-19 pandemic. Governments, policy makers and stakeholders might find in this work scientific-based guidelines that facilitate complex decision-making processes.

A correction to this paper has been published: https://doi.org/10.1007/s11135-021-01154-2

This research aimed to provide a better understanding and analysis of consumer patterns relative to behavioral preferences in the Saudi cooperative motor insurance market. This aim was motivated by the fact that customers’ preferences have been underexplored in this market. Thus, this paper applied a multi-attributes decision analysis methodology to analyze the decision process of purchasing or retaining cooperative motor insurance based on a discrete choice experiment and a choice-based conjoint analysis. The methodology was conducted via a designed questionnaire that asked 385 customers in the Eastern Region to choose between a finite set of decision purchase options that varied along three key attributes: type of coverage, availability of discount, and insurance premium. Sample results showed that the most important attributes were the insurance premium, followed by the type of coverage. The availability of a discount was the least important attribute; however, compared with men, women placed a higher importance on coverage and discounts. The findings can be valuable to policymakers and managers of insurance companies in designing new characteristics for cooperative motor insurance products in Saudi Arabia in line with Saudi Arabia’s Vision 2030. JEL Classification: C9, D7, C13, G22 Plain language summary Analyzing customer preferences in Saudi Arabia’s cooperative insurance sector This study aimed to enhance comprehension of consumer decision-making processes concerning cooperative motor insurance within the Saudi Arabian context, an area that has received limited investigation heretofore. Employing a multi-attribute decision analysis methodology, the research scrutinized the preferences influencing the purchase or retention of cooperative motor insurance, leveraging discrete choice experimentation and choice-based conjoint analysis. Through a structured questionnaire administered to 385 respondents in the Eastern Region, participants were tasked with selecting among predefined insurance options delineated by three pivotal attributes: coverage type, availability of discounts, and insurance premium. Results indicated that the foremost determinant of choice was the insurance premium, trailed by coverage type, while discount availability held lesser significance. Notably, gender discrepancies emerged, with female respondents attributing greater importance to both coverage and discount availability compared to their male counterparts. These findings hold considerable implications for policymakers and insurance industry stakeholders, furnishing insights conducive to the development of tailored cooperative motor insurance products aligning with the objectives outlined in Saudi Arabia’s Vision 2030 agenda.

Insurance industries have grown remarkably since the late 1990s. Governments require a benchmarking tool to measure their insurance industry's performance according to specific various indicators. The best practice benchmarking of insurance can be achieved by evaluating numerous insurance industries through prioritizing and identifying the top industries. This paper presents a multi-criteria evaluation framework for insurance performance of Organization for Economic Cooperation and Development (OECD) countries by investigating conflicting and incommensurate insurance indicators for the period of 2010-2017. For the basis of the evaluation, eight main insurance performance inductors were identified and then their weights were determined using the entropy method. The resultant entropy weights were then applied in the evaluation based on distance from average solution (EDAS) method for determining preferential rankings of insurance industries. The ranked insurance industries were classified into groups of similar levels of performance. Sensitivity analysis was applied to the main criteria to examine the robustness of the prioritizing results. The results indicate insurance markets in United States, the United Kingdom, Germany, France, and Japan are ranked higher than the remaining 25 OECD countries.

Purpose The purpose of this paper is to propose a decision support model to prioritize equity crowdfunding (ECF) evaluation criteria under an uncertain environment. Design/methodology/approach The proposed decision support model first identifies a holistic list of evaluation criteria and subcriteria. These criteria are then analyzed using the analytic hierarchy process (AHP) method in an interval-valued intuitionistic fuzzy (IVIF) environment to identify the relative importance attached by crowdfunding investors to five sets of evaluation criteria (fundraiser, platform, project, campaign and investment characteristics) and their associated subcriteria. The proposed decision support model and ECF evaluation criteria were empirically examined using a real-life case study from January to February 2023. Findings The case study illustrated that the decision support model enhanced fairness and transparency in the prioritization of ECF evaluation criteria. Project characteristics were the most important criterion, followed by fundraiser characteristics and investment characteristics. These results can serve as a benchmark to help crowd investors choose ventures more wisely and make better investment decisions. Originality/value The tasks of modeling and prioritizing ECF evaluation criteria are relatively rarely addressed in the literature, especially under uncertainty. This study is one of the first attempts to use the AHP to explore ECF evaluation criteria in an IVIF environment; in particular, it sheds light on the importance that crowd investors attach to criteria related to fundraiser, platform, project, campaign and investment characteristics.

This study examines the attributes of date palm fruits that influence consumer purchasing decisions and measures the attributes’ relative importance weights for understanding consumption patterns relative to the cultivation areas. A case study was conducted for a selected date fruit, Khalas , which is cultivated in Saudi Arabia and ranked first in the world in exported dates. Our empirical investigation is based on utilizing a proposed quantitative analysis that integrated the entropy weighting method and binary logit models. With this survey design, 486 questionnaires were collected. Analysis results revealed a ranking list of preferred attributes, with size, mellowness, price, and color being the most valued. However, this ranking list fluctuates when different cultivated types of Khalas dates are available. The results also showed that consumption patterns may change in terms of preference index and shopping location. The paper concludes with a discussion of managerial implications, limitations, and future research directions.

A group health insurance plan is an insurance plan that provides healthcare coverage to a selected group of people. In various countries, group health insurance plans are one of the major benefits offered through employers in the private sector. In recent years, the numbers of group health insurance plans offered in the market of health insurance have been increasing rapidly. This is due to compulsory government policies, which are imposed on employers in the private sector leading to an increasing demand for this insurance plan. Accordingly, employers may face a wide variety of available group health insurance plan alternatives. Despite the fact that employers in the private sector have a crucial and significant role in the health insurance market all over the world, little is known about how employers evaluate and choose group health insurance plans to cover their employees against the payments of benefits as a result of sickness or injury. Therefore, the primary concern in this research is to propose a model to assist employers within the private sector to evaluate alternative group health insurance plans and to select the most appropriate, in order to provide the perfect health care environment for their employees.In this research, a new hybrid Fuzzy Multiple Criteria Decision Making (MCDM) model is proposed for the selection problem. The proposed model tackles some issues that may be associated with the selection of the group health insurance plan, such as modelling uncertainty, studying the dependence among decision attributes, deriving decision attributes importance weights and ranking various alternatives. In the proposed hybrid model, four extension approaches based on the Fuzzy Delphi, Fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL), Fuzzy Group Prioritisation and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods are developed. Unlike the existing methods, the four proposed approaches, a new extended Fuzzy Delphi (FDE) method, a new extended Fuzzy DEMATEL method, a new Fuzzy Group Prioritisation (FGP) method and a new extended Fuzzy TOPSIS method, consider the importance weight of each member in group decision making since the selection problem needs evaluations from decision makers (DMs) with different levels of expertise and different perceptions. In the literature, there is some work on these methods, but to our knowledge, no research exists that combines these four methods. Moreover, the proposed model might be applied, due to its novelty, to any MCDM problem uncertainty in different.Furthermore, four new prototype decision support tools, termed Fuzzy Delphi Solver, Fuzzy DEMATEL Solver, Fuzzy Group Prioritisation Solver and Fuzzy TOPSIS Solver were developed in this study, based on the concepts of the four proposed approaches, in order to provide user-friendly interfaces for facilitating the application of these approaches. MATLAB software Version R2013a was adopted as a development environment for prototyping these new decision support tools in this study. The tools developed were validated internally by using hypothetical examples and checking the correctness of the results obtained by comparing them to other results generated from other software, such as Microsoft Excel or LINGO V13.0 software. In addition, a practical validation of the proposed hybrid Fuzzy MCDM model was investigated through conducting a case study of the Saudi health insurance industry. The main objectives of the case study were: 1) investigation of the evaluation process of selecting a group health insurance plan, including identifying the selection criteria and alternatives, studying the dependency issue, deriving the criteria weights, and ranking available alternatives; 2) application of the new decision support tools developed. In this case study, a group of nine DMs, Human Resources (HR) managers at nine different private companies in Saudi Arabia, were selected to take part of this case study. Their involvement achieved the first objective of the case study. At the end of the case study, a sensitivity analysis was conducted to indicate the robustness and the reliability of the results obtained. It is concluded that the proposed model is indeed beneficial. Finally, areas for further research were identified.