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The purpose of this study is to investigate the impact of terrorist attacks on the volatility and returns of the stock market in Tunisia.

The employed sample comprises 1250 trading day from the Tunisian stock index (Tunindex) and stock closing prices of 64 firms listed on the Tunisian stock market (TSM) from January 2011 to October 2015. The research opts for the general autoregressive conditional heteroscedasticity (GARCH) and exponential generalized conditional heteroscedasticity (EGARCH) models framework in addition to the event study method to further assess the effect of terrorism on the Tunisian equity market.

The baseline results document a substantive impact of terrorism on the returns and volatility of the TSM index. In more details, the findings of the event study method show negative significant effects on mean abnormal returns with different magnitudes over the events dates. The outcomes propose that terrorism profoundly altered the behavior of the stock market and must receive sufficient attention in order to protect the financial market in Tunisia.

Very few evidence is found on the financial effects of terrorism over transition to democracy cases. This paper determines the salient reaction of the stock market to terrorism during democratic transition. The findings of this study shall have relevant implications for stock market participants and policymakers.

COVID-19 is an infectious disease caused by the SARS-CoV-2 virus. Considering the restricted and enclosed nature of prisons and closed environments and the prolonged and close contact between individuals, COVID-19 is more likely to have a higher incidence in these settings. This study aims to assess the prevalence of COVID-19 among prisoners.

Papers published in English from 2019 to July 7, 2023, were identified using relevant keywords such as prevalence, COVID-19 and prisoner in the following databases: PubMed/MEDLINE, Scopus and Google Scholar. For the meta-analysis of the prevalence, Cochrane’s Q statistics were calculated. A random effect model was used due to the heterogeneity in COVID-19 prevalence across included studies in the meta-analysis. All analyses were performed in STATA-13.

The pooled data presented a COVID-19 prevalence of 20% [95%CI: 0.13, 0.26] and 24% [95%CI: 0.07, 0.41], respectively, in studies that used PCR and antibody tests. Furthermore, two study designs, cross-sectional and cohort, were used. The results of the meta-analysis showed studies with cross-sectional and cohort designs reported 20% [95%CI: 0.11, 0.29] and 25% [95%CI: 0.13, 0.38], respectively.

Through more meticulous planning, it is feasible to reduce the number of individuals in prison cells, thereby preventing the further spread of COVID-19.

Pre-positioning and distributing relief items are important parts of disaster management as it simultaneously considers activities from both pre- and post-disaster stages. This study aims to address this problem with a novel mathematical model.

In this research, a bi-objective mixed-integer linear programming model is developed to tackle pre-positioning and distributing relief items, and it is formulated as an integrated location-allocation-routing problem with uncertain parameters. The humanitarian supply chain consists of relief facilities (RFs) and demand points (DPs). Perishable and imperishable relief commodities (RCs), different types of vehicles, different transportation modes, a time window for delivering perishable commodities and the occurrence of unmet demand are considered. A scenario-based game theory is applied for purchasing RCs from different suppliers and an integrated best-worst method-technique for order of preference by similarity to ideal solution technique is implemented to determine the importance of DPs. The proposed model is used to solve several random test problems for verification, and to validate the model, Iran’s flood in 2019 is investigated as a case study for which useful managerial insights are provided.

Managers can effectively adjust their preferences towards response time and total cost of the network and use sensitivity analysis results in their decisions.

The model locates RFs, allocates DPs to RFs in the pre-disaster stage, and determines the routing of RCs from RFs to DPs in the post-disaster stage with respect to minimizing total costs and response time of the humanitarian logistics network.

To investigate the impact of board characteristics (board gender diversity, board chair age, board subcommittees, board meetings, board skill, board size and board independence) on corporate social responsibility disclosures (CSRD) of state-owned enterprises (SOEs) in Kenya during the period 2015–2018.

The study employed fixed-effects balanced panel data to examine the impact of board characteristics on CSRD. The analysis is repeated using two regression estimators (robust least square and random effects) and the four CSRD subcomponents to evaluate the robustness of the main analysis.

The results established that board gender diversity, board chair age and board subcommittees had significant negative effects on CSRD. The impact of the remaining board characteristics was found to be insignificant.

The study was limited to the disclosures included in the annual reports, which means that information disclosed in other media, like websites, was not considered. The second limitation concerns mediating and moderator variables that were not considered.

There is a need for a stricter corporate governance implementation mechanism, as opposed to the “comply or explain” principle, since results suggest that most of the board characteristics do not appear to be impactful. Additionally, the low level of reported CSRD calls for the establishment of Corporate Social Responsibility or related committees.

The evidence suggests that SOEs are reluctant to report on issues such as ethics, health and safety initiatives, environment and social investments.

The paper extends the literature on the impact of board characteristics on CSRD in unlisted non-commercial SOEs in a developing country context.

This study aims to address the following research questions: (1) What are the theoretical frameworks and areas of study that influence the development of service ecosystems? and (2) To what extent does a service ecosystem align with the theoretical concepts presented in other research contexts within the study areas, thereby transforming the fundamental structure of the core concept?

We conducted a bibliometric systematic literature review, analyzing 280 papers from a sample of 52 journals listed in the Association of Business Schools (ABS). The review covered the period between 2004 and 2022, and we utilized co-citation analysis, multi-dimensional scaling analysis and hierarchical cluster analysis (HCA) on a total of 2,614 citations.

This study employs co-citation analysis to identify the conceptual structure of the service ecosystem based on highly cited papers. Additionally, we utilize multidimensional scaling (MDS) to uncover key approaches driving service ecosystem research. Through HCA and network analysis, we examine the research scope and its development, emphasizing theory-driven approaches. By combining quantitative and qualitative analysis, we explore the interrelationships between scope, domain and evolution. This comprehensive analysis allows us to delve deeply into the study of service ecosystems. To broaden the research scope, we propose a conceptual framework for comparing the main components of a service ecosystem. The current paper clarifies the service ecosystem's intellectual structure, including service performance, humanistic approach, sustainable innovations and service reflexivity and reformation and proposes a prospective research framework for specialists and researchers by introducing a metaverse service ecosystem.

For the first time, the findings of this study shed light on processes that facilitate the flow of technologies, business models and markets through social structures, ultimately contributing to social change. In service-based systems, the development and application of a more humanistic approach within and surrounding social service ecosystems are crucial as they evolve. Therefore, adopting a dynamic and multifaceted approach offers valuable insights into the drivers of value creation.