Purpose—In the business sector, reliable and timely data are crucial for business management to formulate a company’s strategy and enhance supply chain efficiency. The main goal of this study is to examine how strong brand strength affects shareholder value with a new Supplier Relationship Management System (SRMS) and to find the specific system qualities that are linked to SRMS adoption. This leads to higher brand strength and stronger shareholder value. Design/Methodology/Approach—This study employed a cross-sectional design with an explanatory survey as a deductive technique to form hypotheses. The primary method of data collection used a drop-off questionnaire that was self-administered to the UAE-based healthcare suppliers. Of the 787 questionnaires sent to the healthcare suppliers, 602 were usable, yielding a response rate of 76.5%. To analyze the data gathered, the study used Partial Least Squares Structural Equation modelling (PLS-SEM) and artificial neural network (ANN) techniques. Findings—The study’s data proved that SRMS adoption and brand strength positively affected and improved healthcare suppliers’ shareholder value. Additionally, it demonstrates that user satisfaction is the most significant predictor of SRMS adoption, while the results show that the mediating role of brand strength is the most significant predictor of shareholder value. The results demonstrated that internally derived constructs were better explained by the ANN technique than by the PLS-SEM approach. Originality/Value—This study demonstrates its practical value by offering decision-makers in the healthcare supplier industry a reference on what to avoid and what elements to take into account when creating plans and implementing strategies and policies.

The COVID-19 pandemic had an adverse impact on the mental health of frontline workers including firefighters. To better understand this occurrence, this cross-sectional study evaluated the prevalence of depression, anxiety, and stress among 105 operational team and elite team firefighters in Kota Bharu, Kelantan State, Malaysia before and after the pandemic. The Depression, Anxiety and Stress Scale-21 (DASS-21), a validated self-reporting survey tool, was used to assess symptoms of depression, anxiety, and stress among the survey respondents. Findings revealed that firefighters had an increased level of anxiety and depression during the post-pandemic period compared to the pre-pandemic period. However, there was a decrease in the stress levels (20%) reported by study participants. Respondents belonging to the operational team had a higher reported level of depression, anxiety, and stress than those from the elite team. This may be attributed the operational team being more exposed to the risk of COVID-19 infection on account of their routine and more voluminous workload. The findings of this study suggest that firefighters, in general, are at an increased risk of mental health problems as a result of the COVID-19 pandemic. Knowing this, it is important to consider these findings when addressing the prevention and management of mental health among firefighters. This includes providing additional support and devoting more resources to those who are most at risk for experiencing symptoms of mental health such as firefighters performing functions aligned with that of an operational team.

This study explores the attributes of service quality for overseas residents provided by island county governments, using the example of the Kinmen County Government’s service center in central Taiwan. This research aims to identify key service elements that can enhance the satisfaction of Kinmen overseas residents. Drawing upon the SERVQUAL scale and a comprehensive literature review, service quality is divided into five dimensions: “administrative service,” “life counseling,” “information provision,” among others, comprising 24 service quality elements. A total of 311 valid questionnaires were collected through a survey, and Kano’s two-dimensional quality and IPA analysis were used to classify service factors. The Kano two-dimensional quality analysis revealed that “employment counseling,” “entrepreneurship counseling,” and “setting up service counters at airports and terminals during festivals” belong to attractive quality. Nine elements were classified as “one-dimensional quality” and “must-be quality,” including “one-stop service,” “exclusive consultation hotline,” and “exclusive website reveals information.” Through Quality Function Deployment (QFD), service elements that align with Kano’s two-dimensional quality and IPA priority improvement were selected for detailed study, including “financial assistance in emergencies,” “subsidy for transportation expenses back home,” “subsidies for education allowances,” and “various subsidy application information.” Following expert discussions and questionnaire surveys, eight strategies for improving key service quality elements were identified. This research not only provides actionable insights for the Kinmen County Government but also offers valuable strategies that can be applied to similar contexts globally, where remote and rural populations require specialized governmental support.

An unprecedented demand for accurate information and action moved the industry toward RegTech where computing, big data, and social and mobile technologies could help achieve the demand. With the introduction and adoption of RegTech, regulatory changes were introduced in some countries. Enhanced regulatory changes to ease the barriers to market entry, data protection, and payment systems were also introduced to ensure a smooth transition into RegTech. However, regulatory changes fell short of comprehensiveness to address all the issues related to RegTech’s operation. This article is an attempt to devise a Privacy Model for RegTech so industries and regulators can protect the interests of various stakeholders. This model comprises four variables, and each variable consists of many items. The four variables are data protection, accountability, transparency, and organizational design. It is expected that the adoption of this Privacy Model will help industries and regulators embrace standards while being innovative in the development and use of RegTech.

Catastrophes, like earthquakes, bring sudden and severe damage, causing fatalities, injuries, and property loss. This often triggers a rapid increase in insurance claims. These claims can encompass various types, such as life insurance claims for deaths, health insurance claims for injuries, and general insurance claims for property damage. For insurers offering multiple types of coverage, this surge in claims can pose a risk of financial losses or bankruptcy. One option for insurers is to transfer some of these risks to reinsurance companies. Reinsurance companies will assess the potential losses due to a catastrophe event, then issue catastrophe reinsurance contracts to insurance companies. This study aims to construct a valuation model for catastrophe reinsurance contracts that can cover claim losses arising from two types of insurance products. Valuation in this study is done using the Fundamental Theorem of Asset Pricing, which is the expected present value of the number of claims that occur during the reinsurance coverage period. The number of catastrophe events during the reinsurance coverage period is assumed to follow a Poisson process. Each impact of a catastrophe event, such as the number of fatalities and injuries that cause claims, is represented as random variables, and modeled using Peaks Over Threshold (POT). This study uses Clayton, Gumbel, and Frank copulas to describe various dependence characteristics between random variables. The parameters of the POT model and copula are estimated using Inference Functions for Margins method. After estimating the model parameters, Monte Carlo simulations are performed to obtain numerical solutions for the expected value of catastrophe reinsurance based on the Fundamental Theorem of Asset Pricing. The expected reinsurance value based on Monte Carlo simulations using Indonesian earthquake data from 1979–2021 is Rp 10,296,819,838.

Despite many investigations concerning antecedents of organizational commitment in the workplace, very few studies so far have analyzed the direct or indirect impact of HR change leadership role on organizational commitment via HR attribution. Therefore, given the reciprocal principle of social exchange theory, attribution theory and signal theory, this study formulated hypotheses and a model to test the relationships between included variables by employing the mixed-method approach. In-depth interviews were initially conducted to develop questionnaires to collect quantitative data. Employing PLS-SEM to analyze the data collected from 1058 employees working in 24 sustainable enterprises in Vietnam, the findings show that the degree of adopting HR change leadership role was positive, directly affecting organizational commitment. Also, both well-being and performance HR attribution play partially mediated roles in the relationship. The findings suggest that the organizational commitment depends on not only how the degree of adopting HR change leadership role is executed, but also how employees perceive and interpret the underlying management intent of these practices. In a sustainable context, adopting HR change leadership role plays a critical role in shaping employees’ interpretations of sustainable HR practices and their subsequent attributions. Besides, employees’ belief on why are sustainable HRM practices implemented has an influence on the organizational commitment that in turn contributes to the overall sustainable performance.