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The purpose of this paper is to examine the evolution of interconnectedness of European insurers among themselves, as well as with other non-financial firms, for the period 2000–2021 and to analyze the stock return movements around the costliest catastrophic events (hurricanes) in the past two decades.

This paper follows the “simple” approach of Patro et al.(2013) and examines the daily stock return correlations of the largest 30 insurers and the largest 30 non-financial firms headquartered in Europe. In addition, the study uses event study methodology to examine stock return movements around the costliest hurricanes.

We find that the European insurance sector has become highly interconnected during the past two decades; however, its increasing connectedness with non-financial firms is limited to a few firms. In addition, we find weak evidence of the destabilizing effects of catastrophic events on European insurers and non-financial firms; however, the potential for cat risk contagion effects exists as the insurance industry becomes heavily interconnected.

The extant literature is largely concerned with the contribution of the insurance sector to the systemic risk of the financial sector. We focus on a specific region (Europe) and analyze the evolution of interconnectedness of the largest insurers within the insurance sector as well as with the largest non-financial firms encapsulating important crisis periods. In addition, we relate to the literature that examines the market reactions around catastrophic events to test the relevance of traditional insurance activities in instigating potential contagion shocks.

This article aims to analyse the trait emotional intelligence (TEI) of business students of various programmes. This study aims to answer the question, to what extent these future leaders are uniformly equipped with essential emotional intelligence competences, necessary in the VUCA world.

The Trait Emotional Intelligence Questionnaire (TEIQue) was used to measure TEI of 120 business students. Spearman's and Tau–Kendall's rank correlation coefficients show the strength of the correlation between age and TEI level. The non-parametric Mann–Whitney U test was employed to evaluate the consistency of TEI-level distributions in selected subgroups of respondents.

Future business leaders and management specialists are unequally prepared to manage teams and organizational change effectively. Their TEI distribution is significantly different regarding the type of programme of study. Students of “social fields” (Management, Communication and Psychology in Business) show higher TEI than students of “analytical fields” (Economics, Finance and Accounting, Logistics). Master's students are characterized by higher TEI compared to undergraduates. However, there were no statistically significant differences in TEI between: full-time and part-time, female and male, as well as working and non-working students.

The results provide valuable guidance for organizations recruiting junior managers and for business universities.

This research was based on a well-established concept of emotional intelligence using a reliable research tool. The obtained results complement the existing research on TEI of various professional groups and provide a precious reference point for future, more in-depth analyses of TEI.

The purpose of this study is to assess the impact of cyberfraud in the South African banks with the aim to provide recommendations to effectively mitigate it.

The study uses a qualitative approach involving the use of structured questionnaires. The questionnaires were made available to the staff of 17 licensed banks in South Africa who deal with management, operation, administration and banking services. Two hypotheses were formulated and non-parametric statistical analyses involving the use of Chi-square test, Fischer’s Exact test and Spearman’s correlation were carried out. The two hypotheses formulated were tested to draw a conclusion.

The results obtained indicate that the impact of cyberfraud in the South African banking industry is highly significant and has affected the reputation of some of the banks. This calls for the need to review the diverse ways of curbing cyberfraud to lessen their impact and that of associated fraud risks on the banking operation.

This study provides an analysis on the relationship cyberfraud occurrences and the reputation of South African banks. The implementation of the recommendations may reinforce the existing security measures in the fight against cyberfraud.

The novelty of this study lies in the fact that the assessment of the impact of cyberfraud on the banking industry in South Africa has not been sufficiently highlighted by the existing literature.

This paper aims to investigate the impact of acquisition and organic growth on the operating efficiency and total factor productivity change of retailing networks.

The assessment uses low-frequency data of newly opened stores and acquired stores of a large supermarket (S/M) network in Athens, for a period (financial year 2014) where the network began to refocus on its organic growth after a two-year period of deep recession (financial years 2012–2013). To evaluate the performance effects of both strategies, the authors employ the innovative benchmarking tool of bootstrap data envelopment analysis (DEA) for measuring operational efficiency and the Malmquist productivity index DEA approach for measuring productivity change over time.

The short-run evidence indicates that compared to organic growth, acquisitions lead to lower operating efficiency. However, this difference gradually converges over time as acquired stores show a higher rate of productivity compared to newly opened stores. The authors interpret this as a result of the smooth integration of the acquired chain store into the organizational structure of the existing store network given their significant similarities in terms of products and customers.

The authors inform managers of store chains that during the process of organic growth, a general improvement in efficiency takes place while in the case of acquisitions, the required post-acquisition streamlining actions cause a short delay on the realization of efficiency gains. Therefore, managers should not take it for granted that acquisitions cause a long-term decrease in efficiency.

The study contributes to the literature on growth strategies and retailing performance in general, by offering new evidence regarding the comparative effect of the horizontal growth modes on the efficiency of store chains.

This study aims to assess the efficiency of managing working capital in 1,388 Indian manufacturing firms from 2008 to 2019 and investigate the effects of firm-specific and macro-level determinants on working capital management (WCM) efficiency.

The current study accommodates a slack-based measure (SBM) in data envelopment analysis (DEA) for computing WCM efficiency. Further, we implement a panel data fixed-effects model that controls for heterogeneity across firms in determining the relationships of selected variables with WCM efficiency.

The results highlight that manufacturing firms operate at around 50 percent efficiency, which is constant throughout the study period. Furthermore, among the selected variables, yield, earnings, age, size, ability to create internal resources, interest rate and gross domestic product (GDP) significantly affect WCM efficiency.

Instead of the traditional models used for assessing efficiency, the SBM-DEA model is unit-invariant and monotone for slacks, implying that it can handle zero and negative data, which overcomes the incapability of prior DEA models. Hence, this provides accurate efficiency scores for robust analysis. Additionally, this paper provides a holistic working capital model recognizing firm-specific and macro-level determinants for a more explicit estimation of the relationship between WCM efficiency and the selected determinants.

The author develops a bilateral Nash bargaining model under value uncertainty and private/asymmetric information, combining ideas from axiomatic and strategic bargaining theory. The solution to the model leads organically to a two-tier stochastic frontier (2TSF) setup with intra-error dependence. The author presents two different statistical specifications to estimate the model, one that accounts for regressor endogeneity using copulas, the other able to identify separately the bargaining power from the private information effects at the individual level. An empirical application using a matched employer–employee data set (MEEDS) from Zambia and a second using another one from Ghana showcase the applied potential of the approach.

Women are exposed to vulnerabilities that can lead to drug use or hinder recovery. However, there is a dearth of studies on recovery programs for women. This study aims to add to the literature by examining the feasibility of a women-only aftercare program for recovering users in the Philippines.

The study used a mixed-method design with pre and post-program surveys used to measure changes in participants’ recovery capital. Focused group discussions elicited participants’ context, their reactions, perceived outcomes and suggestions on the program.

Women in the program shared narratives of pain, trauma and abuse before treatment. Participants reported significant improvements in personal, community and family recovery capital dimensions. The program enabled personal growth in the form of new knowledge, skills and self-confidence. The women-only program also provided a safe space for women, to receive support from other women, community members and family. However, the women continue to face continuing challenges related to stigma and discrimination and a lack of livelihood opportunities.

A limitation of the study was its small sample size and the lack of a control group. Another limitation was the variability in treatment received by the women, which could have affected overall outcomes. Future studies using a randomized control trial and longitudinal designs may provide more robust conclusions on the effectiveness of the program.

Given punitive contexts, gender-sensitive and trauma-informed programs and services for women involved in drug use could potentially mitigate the abuse, stigma and vulnerabilities they experience.

This study contributes to the sparse literature on women-only aftercare, particularly in countries that criminalize drug use.

Visual aesthetics are a vital aspect of environmental quality. The objective of this study is to demonstrate the implementation of visibility analysis and visual quality standards on a campus to enhance productivity and effectiveness.

This study has identified the most crucial and valuable metrics for evaluating the visual quality of open spaces through an analysis of theoretical foundations and relevant background information. To achieve research goal, a multi-method approach was employed, incorporating a survey, user satisfaction ratings and ISOVIST simulation techniques. Specifically, this study focused on assessing the quality of open spaces in three open areas located on the campus of the Iran University of Science and Technology.

Based on the study’s findings, the most significant factors that students considered when evaluating the visual quality of open spaces on the Iran University of Science and Technology campus were green areas, gathering spaces and architectural elements such as furniture, color and texture. Among the three open areas examined, “Open Space One” was identified as the most satisfactory location for students. According to the study, “sensory richness,” “complexity” and “mystery” were significant indicators of students' satisfaction in this area. This area also had the widest radius and field of view feasible, which gave it a feeling of openness and spaciousness.

This study explores the influence of students' experiences, behavioral patterns and visual analyses on their use of open spaces on university campuses, with a focus on the Iran University of Science and Technology. By assessing students' satisfaction levels with these spaces, this research provides valuable insights that can guide the initial analysis stage before the design process and facilitate design optimization during the development stages. The results highlight the importance of considering user experiences and visual analysis when planning and creating open spaces on university campuses.

Highlights

1. Conducting an initial analysis before developing a design plan can be very helpful in understanding how users think and behave.

2. The three criteria of visual quality that have the strongest correlation with students' satisfaction with “open space” are “mystery,” “sensory richness” and “complexity.”

3. Two factors, namely the “radius of vision” and the “area” index, significantly influence students' satisfaction with open spaces.

4. Outdoor designers should incorporate “green space” and “gathering spaces” into their designs since the presence of these is effective in attracting and satisfying students.

5. The number of people using an open space has little to do with how satisfied students are with it.

6. Half of the students use open areas between 11:00 and 14:00, so the provision of “canopy” and “shelter” in these spaces is essential.

Conducting an initial analysis before developing a design plan can be very helpful in understanding how users think and behave.

The three criteria of visual quality that have the strongest correlation with students' satisfaction with “open space” are “mystery,” “sensory richness” and “complexity.”

Two factors, namely the “radius of vision” and the “area” index, significantly influence students' satisfaction with open spaces.

Outdoor designers should incorporate “green space” and “gathering spaces” into their designs since the presence of these is effective in attracting and satisfying students.

The number of people using an open space has little to do with how satisfied students are with it.

Half of the students use open areas between 11:00 and 14:00, so the provision of “canopy” and “shelter” in these spaces is essential.

The purpose of the research is to analyze the factors that determine the intention of small- and medium-sized enterprises (SMEs) to adopt the Metaverse. For this purpose, the analysis of the effort expectancy and performance expectancy of the constructs in relation to business satisfaction is proposed.

The analysis was performed on a sample of 182 Spanish SMEs in the technology sector, using a PLS-SEM approach for development. For the confirmation of the model and its results, an analysis with PLSpredict was performed, obtaining a high predictive capacity of the model.

After the analysis of the model proposed in this research, it is recorded that the valuation of the effort to be made and the possible performance expected by the companies does not directly determine the intention to use immersive technology in their strategic behavior. Instead, the results obtained indicate that business satisfaction will involve obtaining information, reducing uncertainty and analyzing the competition necessary for approaching this new virtual environment.

The study represents one of the first approaches to the intention of business behavior in the development of performance strategies within Metaverse systems. So far, the literature has approached immersive systems from perspectives close to consumer behavior, but the study of strategic business behavior has been left aside due to the high degree of experimentalism of this field of study and its scientific approach. The present study aims to contribute to the knowledge of the factors involved in the intention to use the Metaverse by SMEs interested in this field.

A semiparametric stochastic frontier model is proposed for panel data, incorporating several flexible features. First, a constant elasticity of substitution (CES) production frontier is considered without log-transformation to prevent induced non-negligible estimation bias. Second, the model flexibility is improved via semiparameterization, where the technology is an unknown function of a set of environment variables. The technology function accounts for latent heterogeneity across individual units, which can be freely correlated with inputs, environment variables, and/or inefficiency determinants. Furthermore, the technology function incorporates a single-index structure to circumvent the curse of dimensionality. Third, distributional assumptions are eschewed on both stochastic noise and inefficiency for model identification. Instead, only the conditional mean of the inefficiency is assumed, which depends on related determinants with a wide range of choice, via a positive parametric function. As a result, technical efficiency is constructed without relying on an assumed distribution on composite error. The model provides flexible structures on both the production frontier and inefficiency, thereby alleviating the risk of model misspecification in production and efficiency analysis. The estimator involves a series based nonlinear least squares estimation for the unknown parameters and a kernel based local estimation for the technology function. Promising finite-sample performance is demonstrated through simulations, and the model is applied to investigate productive efficiency among OECD countries from 1970–2019.