Tarifa Almulhim

Studies of the Venture Capital (VC) screening process traditionally assume that VC criteria are independent of other criteria. However, these criteria may interact and influence each other in cause‐and‐effect relationships. Therefore, there is a need to understand the interdependence of VC screening criteria. In this study, a decision support framework is proposed for VC screening criteria, based on the Decision‐Making Trial and Evaluation Laboratory (DEMATEL) method and Intuitionistic Fuzzy Set (IFS) theory (IFS‐DEMATEL). Building on prior work on VC investors, we identify a holistic list of 20 evaluation criteria in seven categories (founding team, product or service, financial, market, environmental, social, and governance characteristics). The IFS‐DEMATEL method is used to identify the relative importance attached by VC investors to different criteria, pinpoint the most significant criteria, and explicate the cause‐and‐effect relationships between criteria. Finally, the proposed framework is used to empirically examine VC screening criteria based on a case study involving VC experts/investors from the UK and the US. We find that environmental protection, the team and working environment, and profitability are the most influential criteria; that is, they have the greatest impact on the other criteria. This study both enhances the VC screening literature and makes an important practical contribution by proposing and illustrating a decision support framework capable of addressing VC screening decisions in complex and imprecise real‐world scenarios.

The development of renewable energy has been extensively studied at the national level. However, few studies have comprehensively examined solar and wind energy together within a nation‐specific context while addressing the impact of conflicting evaluation indices through dimensionless processing. This study bridges this gap by evaluating the evolutionary performance of solar and wind energy across 21 countries from 2018 to 2023 using a four‐stage multi‐criteria decision‐making (MCDM) framework. The proposed methodology involves constructing a multidimensional model to identify key dimensions and evaluation indices, applying the criteria importance through inter‐criteria correlation (CRITIC) method to determine objective index weights through dimensionless processing, ranking countries using the combined compromise solution (CoCoSo) method and classifying the results, followed by sensitivity analyses to verify robustness and stability. The findings identify critical dimensions influencing solar and wind energy development, including energy supply, market demand, financial implementation costs, environmental benefits and social impacts. The most influential indicators include the share of solar and wind power generation, renewable energy consumption efficiency per unit of gross domestic product (GDP), CO ₂ emissions per capita and total renewable electricity generation per capita. The results indicate that Germany, Spain, the United States, China, the Netherlands, Italy, Australia, France and Greece are the leading countries in renewable energy performance. Sensitivity analyses and comparative evaluations confirm the robustness and reliability of the proposed framework. The study concludes with policy recommendations aimed at improving renewable energy efficiency, reducing emissions and promoting equitable access to clean energy, thereby supporting sustainable and resilient global energy transitions. The proposed framework also provides a replicable model for renewable energy performance evaluation in other regions worldwide.

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

Decision-making trial and evaluation laboratory (DEMATEL) is a practical method used to analyze the interrelationships between criteria while evaluating their importance in multi-criteria decision-making (MCDM) problems. This paper proposes an extension to DEMATEL using a fuzzy set—specifically, an interval-valued spherical fuzzy set (IVSFS)—which is one of the latest fuzzy developments. In contrast to the fuzzy extensions of DEMATEL reported in the literature, this study proposes a new IVSFS version of the DEMATEL methodology that incorporates experts’ weights. The proposed IVSFS–DEMATEL methodology uniquely manages the weights of experts using the form of IVSFSs, differing from existing DEMATEL methodologies. Furthermore, it aims to maintain the fuzziness of operations until the later stages, unlike existing methodologies that implement defuzzification operations at the early stages. A real case study of an early-stage investment process is conducted to justify the feasibility and applicability of the proposed methodology. Sensitivity and comparison analysis are performed to confirm the validity of the results.

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 capital requirement should be established for insurance companies at a level that allows them to fulfil their engagements towards policyholders. As such, evaluating an accurate amount of reserve and capital within different lines of business is a fundamental procedure for any company. However, studying the dependence between lines of business and the uncertainty regarding this dependence has been neglected in prior actuarial research. In practice, the evaluation of a Solvency Capital Requirement may be inaccurate when the risks of different business lines are independent. Thus, the present article aims to provide an appropriate modelling approach for claim amounts by taking into account the multivariate dependence between risks. To alleviate this issue, it uses vine copula functions to capture dependence between multivariate distributions of risks for five lines of business. Moreover, the dependence structure may be uncertain which leads to determining different levels of capital. Therefore, we propose a fuzzy inference system to handle the uncertainty of dependence structure. The obtained results reveal that considering the multivariate dependence structure produces a higher amount of Solvency Capital Requirement than the independence case. Moreover, the Solvency Capital Requirement level is decided according to the degree of dependence between risks.