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This study aims to investigate the impact of climate change risk disclosure (CCRD) on Corporate Value while exploring how corporate characteristics such as size, financial performance and leverage may moderate this relationship.

This research used a sample of 50 companies from the EGX100 index on the Egypt Stock Exchange, covering the years 2018–2022 (250 observations). For the first hypothesis, the authors use ordinary least squares regression, while for the other hypotheses, the authors use the PROCESS program developed by Andrew F. Hayes to analyze moderation.

The findings indicate a negative association between CCRD and corporate value. However, the extent of this influence can vary depending on the company’s characteristics. Specifically, CCRD negatively affects the value of small-sized, less profitable and highly leveraged corporates. Conversely, it positively impacts the value of large-sized, more profitable and less leveraged corporates.

The findings have significant implications for stakeholders in Egypt and similar developing countries. This significance stems from the substantial impact of CCRD on corporate value. CCRD can heighten investors’ perception of risk as a new risk factor, potentially leading to increased corporate risk. Therefore, CCRD is vital in identifying corporate value reflected in stock prices.

As far as we know, this is the pioneering study in Egypt to offer new evidence on how CCRD affects corporate value. It investigates the moderating role of corporate characteristics, such as corporate size, financial performance and leverage, in this relationship.

This study aims to analyze the existing body of knowledge concentrating on institutional investors’ behavior. It seeks to track how this domain has evolved through collaborative networks, as well as significant contributors, themes and research opportunities for future work.

The present study applies bibliometric analysis to examine the trends in the selected research field, using 446 articles from highly recognized journals indexed in the Scopus database.

The authors discovered that research on institutional investors’ behavior has significantly increased over the past four decades due to academic interest in the topic. This study observed five themes that unite the research in this field: institutional investors and corporate behavior; determinants of institutional investors’ trading patterns and performance; trading activity and its outcomes; herding, causes and consequences; and institutional investment and corporate performance. Moreover, future directions are penned down, such as how institutional investors’ control influences governance disclosures.

This study serves as a guide by mapping and analyzing the intellectual development of the research literature on institutional investors’ behavior. The authors contribute to the knowledge base by providing a solid foundation for further studies.

This integrative review was conducted to provide an overview of existing research on digital (in)equity and the digital divide in developed countries.

We searched academic and grey literature to identify relevant papers. From 8464 academic articles and 183 grey literature, after two levels of screening, 31 articles and 54 documents were selected, respectively. A thematic analysis was conducted following the steps suggested by Braun and Clarke and results were reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

The results showed that most articles and papers were either from Europe or North America. Studies used a range of research methods, including quantitative, qualitative and mixed methods. The results demonstrated four major dimensions of the digital divide among various vulnerable groups, including digital literacy, affordability, equity-deserving group-sensitive content and availability or access to infrastructure. Among vulnerable groups, low-income people were reported in the majority of the studies followed by older adults, racial and ethnic minorities, newcomers/new immigrants and refugees, Indigenous groups, people with disabilities and women. Most reported barriers included lack of access to the internet, digital skills, language barriers and internet costs.

To the best of our knowledge, there have been limited attempts to thoroughly review the literature to better understand the emerging dimensions of digital equity and the digital divide, identifying major vulnerable populations and their unique barriers and challenges. This review demonstrated that understanding intersectional characteristics (age, gender, disability, race, ethnicity, Indigenous identity and immigration status) and their interconnections is crucial for analyzing the dynamics of digital (in)equity and divide.

This paper aims to identify the impacts of sociodemographic covariates on behavioural biases (BB) scores; the psychometric evidence of the BB measurement instruments; and the main BB that influences the decision-making of individual investors.

Papers were retrieved through search using keywords in ten databases. This systematic review is based on 69 peer-reviewed papers, most of which were published between 2017 and 2021. The relevance of the included papers was assessed through the analysis of statistical/psychometric methods used, and content analysis of the BB literature and its sociodemographic correlations.

Overconfidence is higher in men and not related to age. There was no consensus regarding the relationship between BB and other sociodemographic variables. Most measuring instruments are ad hoc, showing ≤ 4 types of psychometric evidence and assessing ≤ 9 BB. Therefore, the findings demonstrate that there is no gold standard instrument for measuring investors’ BB. Furthermore, 37 BB were cited as influencers of individual investors’ decision-making and overconfidence, herding, anchoring, representativeness and loss aversion were the most prevalent.

Considering that very few systematic reviews have been published in the behavioural finance area, this paper highlights the current state-of-the-art and identifies significant gaps in the literature that can be explored by further research.

To the best of the authors’ knowledge, this is the first systematic review that analyses the psychometric properties of instruments used for individual investors BB assessment.

This study aims to gain a deep understanding of the process of international commercial terms (Incoterms) selection by small and medium enterprises (SMEs) in Bangladesh and identify the key factors that influence their choices. The study also intends to explore the discrepancy between the literature and the actual industry practice so that policymakers and traders can make more informed decisions in this respect.

The study adopts a mixed methodology. Initially, 20 factors under five principle components were identified by reviewing the literature. The semi-structured one-to-one interview method has been used to gather expert opinions on the factors and to identify the discrepancy between literature and actual industry practices. Finally, eight factors have been identified and surveyed using the best-worst method (BWM) to determine their relative significance or weights in Incoterm selection.

The study has found that government policies, the influence of banks and currency fluctuations are the top three influential factors in selecting Incoterms by SMEs in Bangladesh. As a result, the most commonly used Incoterms are free on board (FOB) for the exporters and cost and freight (CFR) for the importers. However, discrepancies have been identified between the selected and the actual application of the Incoterms.

To the best of the authors’ knowledge, this is the first study to identify and analyse the factors that influence the selection of Incoterms by the SMEs in the context of a developing nation. The study has identified the factors from both importers’ and exporters’ perspectives that have not been done by any previous studies. Moreover, this study explores the discrepancies between the agreed Incoterm and the actual industry practices which is a unique contribution to the literature.

The purpose of this study is to investigate the impact of e-service quality and e-trust on customer e-satisfaction and, subsequently, on customer e-loyalty towards a website in the online shopping environment of Pakistan.

The research employed a quantitative approach and utilised structural equation modelling to investigate the relationship between e-service quality and e-trust on consumers’ e-satisfaction and e-loyalty. The data were collected from 250 individuals who actively use online shopping websites to purchase products in Pakistan.

The findings revealed that e-service quality and e-trust offered on e-commerce websites significantly impacted customer e-loyalty. However, it was found that both e-service quality and e-trust do not have a significant impact on customer e-satisfaction. In addition, the findings showed that customer e-satisfaction positively impacts e-loyalty.

Overall, these findings emphasise the importance of e-service quality, e-trust and customer e-satisfaction and their role in cultivating customer loyalty within the context of the online shopping environment in Pakistan.

This study contributes to the existing literature on online shopping in Pakistan by exploring the factors influencing consumer behaviour in this context. The findings add to the academic understanding of consumer behaviour and provide valuable insights for e-commerce businesses in Pakistan.

The agriculture sector is crucial for all economies, especially the developing ones. However, agricultural production is influenced by government intervention, which outshines the significant role of good governance indicators in agricultural productivity. In addition to this, the major climate changes also posed various challenges and led to water shortages and yield losses. Thus affecting agricultural production. In this paper, we address the issue by determining the association between state governance and agricultural productivity in N-11 countries.

Panel data have been collected from 2000 to 2021 through the Governance Indicator, World Development Indicator and World Bank databases. For data analysis, the researcher has utilized the autoregressive distributed lag (ARDL) estimations.

Through ARDL estimations, it is suggested that corruption (CC), employment in agriculture (EAG), political stability and violence absence (PS), rule of law (RL), regulatory equality (RQ) and water quality (WQ) significantly impact agricultural productivity (AGP) in the long run. In the short run, the impact of RL on AGP has been significant.

This study follows the method of data collection from secondary sources, which hinders the effectiveness of this study as, on the basis of the respective data, the potential of the researcher to get specific answers to research questions has been affected. Also, this study examines the context of N-11 countries from 2000 to 2021, which exerts a geographical limitation. While exploring the association between state governance and agricultural productivity, this study neglects the internal aspects of implementing state policies in firms.

On practical grounds, the significant association demonstrated by this study encourages agricultural firms to keenly consider state policies to gain sustainable agricultural development. Moreover, this study encourages agricultural firms to efficiently follow governance policies for efficient productivity. The outcomes of the study have shown that agricultural employment and governance infrastructure can efficiently enhance agricultural productivity. Besides, as per the results, water quality also positively impacts agricultural productivity; thus, relevant steps can be taken by the agricultural sector to improve the quality of water.

The recent pandemic caused by coronavirus disease 2019 (COVID-19) has significantly impacted the operational performances of pharmaceutical supply chains (SCs), especially in emerging economies that are critically vulnerable due to their inadequate resources. Finding the possible barriers that continue to impede the sustainable performance of SCs in the post-COVID-19 era has become essential. This study aims to investigate and analyze the barriers to achieving sustainability in the pharmaceutical SC of an emerging economy in a bid to help decision-makers recognize the most influential barriers.

To achieve the goals, two decision-making tools are integrated to analyze the most critical barriers: interpretive structural modeling (ISM) and the matrix of cross-impact multiplications applied to classification (MICMAC). In contrast to other multi-criteria decision-making (MCDM) approaches, ISM develops a hierarchical decision tool for decision-makers and cluster analysis of the barriers using the MICMAC method based on their driving and dependency powers.

The findings reveal that the major barriers are in a four-level hierarchical relationship where “Insufficient SC strategic plans to ensure agility during crisis” acts as the most critical barrier, followed by “Poor information structure among SC contributors,” and “Inadequate risk management policy under pandemic.” Finally, the MICMAC analysis validates the findings from the ISM approach.

This study provides meaningful insights into barriers to achieving sustainability in pharmaceutical SCs in the post-COVID-19 era. The study can help pharmaceutical SC practitioners to better understand what can go wrong in post-COVID-19, and develop actionable strategies to ensure sustainability and resilience in practitioners' SCs.

This research mainly intends to ascertain the stimulus of investor investment tendencies on the amount of capital investment in the share market.

Utilizing a sample of 477 individual investors who actively trade on the Bangladesh capital market, this empirical study was conducted. The objective of this examination is to ascertain the investment trading behavior of retail investors in the Bangladesh capital market using multiple regression, hypothesis testing and correlation analysis.

The coefficients of market categories, preferred share price ranges and investment source reveal negative predictor correlations; all predictors are statistically significant, with the exception of investment source. Positive predictive correlations exist between investor category, financial literacy degree, investment duration, emotional tolerance level, risk consideration, investment monitoring activities, internal sentiment and correct investment selection. Except for risk consideration and investment monitoring activities, all components have statistically significant predictions. The quantity of capital invested in the stock market is heavily influenced by the investment duration, preferred share price ranges, investor type, emotional toleration level and decision-making accuracy level.

This investigation was conducted exclusively with Bangladeshi individual stockholders. Therefore, the existing study can be extended to institutional investors and conceivably to other divisions. It is possible to conduct this similar study internationally. And the query can enlarge with more sample size and use a more sophisticated econometric model. Despite that the outcomes of this study help the regulatory authorities to arrange more informative seminars and consciousness programs.

The conclusions have practical implications since they empower investors to modify their portfolios based on elements including share price ranges, investment horizons and emotional stability. To improve chances of success and reach financial objectives, they stress the significance of bettering financial understanding, active monitoring and risk analysis. Results can also be enhanced by distributing ownership over a number of market sectors and price points. The results highlight the value of patience and giving potential returns enough time.

This study on the trading behavior of investors in Bangladesh is unique and based on field study, and the findings of this study will deliver information to the stakeholders of the capital market regarding the investors’ trading behavior belonging to different categories, financial literacy level, investment duration, emotional tolerance level and internal feeling.