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Consumer ethnocentrism (CE) is a matter of interest for marketers over the decades. However, buying intentions toward domestically produced household electronic products in developing and underdeveloped countries have not been examined sufficiently. Hence, this study investigated the consumers' ethnocentrism and attitude toward domestically-produced household electronic goods. The purpose of this study is to examine the influence of consumer demographic attributes on ethnocentrism and its moderating effect on choosing domestically produced household electronic goods in the context of Bangladesh.

Primary data have been collected from a sample of 172 respondents using a mall-intercept survey. Consumers' ethnocentrism level has been measured using CETSCALE on a five-point Likert scale. ANOVA and t-test were performed to compare different demographic groups regarding ethnocentrism levels. This study also applied the qualitative method by applying a manual approach.

The result shows that consumers' ethnocentrism levels do not vary with gender and income level. However, other demographic attributes, like occupation, age and education level, play a considerable role in CE tendency.

The study is one of the few that examines the consumers' ethnocentrism and attitudes toward electronic products produced in a developing country. The researchers expect that the outcome of the study would contribute to the domestic manufacturer focusing more rigorously on producing electronic products that would be accepted locally as well as globally.

The purpose of this study is to empirically examine the impact of ownership structure variables on the level of sustainability reporting (SR) of listed BRICS energy firms as well as the moderating role of the board sustainability committee on this relationship.

This study used a sample of 1,260 firm-year observations from BRICS for the period 2010–2019. This study uses the Bloomberg database, companies’ annual reports and companies’ websites for data collection and the ordinary least squares (OLS) and instrutemental variables (IV) two-stage least squares (2SLS) regressions for data analysis.

This study provides empirical evidence that foreign ownership, managerial ownership and blockholder ownership have a positive and statistically significant impact on the level of SR. However, the results indicate institutional ownership impacts SR negatively. The findings remain qualitatively the same after addressing endogeneity concerns using the IV 2SLS regression method.

This paper has some limitations. This study focuses on listed companies in BRICS. Therefore, future studies should look at non-listed small and medium enterprises. Similarly, because this study focuses on emerging economies, future studies should consider comparative studies between developed and developing economies.

This study makes significant empirical, theoretical and regulatory contributions to policymakers, investors and management on the ownership type that positively influence the level of SR.

This study contributes to the corporate governance and sustainability literature and extends existing empirical literature on the role of ownership structure on the level of SR in the context of emerging economies. This study provides important theoretical and empirical evidence for regulators and policymakers.

This study aims to investigate the impact of FinTech on money laundering within the context of Nigeria. The motivation stems from observations suggesting that FinTech platforms might be used for illicit money transfers, particularly from developed to developing economies. While existing literature predominantly highlights the positive aspects of FinTech, there's a dearth of studies addressing its potential association with money laundering. Current understanding of this relationship relies heavily on anecdotal evidence derived from reported or convicted cases. Thus, the primary goal of this study is to analyze the influence of FinTech on money laundering while also considering the moderating effects of financial regulation and financial literacy as perceived by users. The research delves into regulatory perspectives concerning money laundering and FinTech.

To fulfill the study's objectives, a quantitative research design is used. A survey of 248 FinTech users in Nigeria is conducted using structured questionnaires. Data collected from the questionnaires is analyzed using partial least square structural equation modeling (PLS-SEM).

The quantitative analysis revealed a significant relationship between FinTech and money laundering and that financial regulation moderates the relationship between FinTech and money laundering in Nigeria, but such was not established with respect to financial literacy. The results of the quantitative approach that uses secondary data are consistent with the qualitative approach. FinTech the results indicate the presence of technology induced money laundering in Nigeria. Regulating technology-based anti-money laundering poses serious challenges for developing countries due to the absence of specific laws that mitigate the threats.

The paper focuses on Nigeria as a case study, which may limit the generalizability of the findings to other countries with different FinTech ecosystems, regulatory frameworks and financial literacy levels.

The finding is useful in developing guidelines and regulations by policymakers and strategies by practitioners in relation to FinTech, money laundering, financial regulation and financial literacy. On the basis of the above, the authors recommend regulation at the national and industry level to mitigate the adverse effect of technology on money laundering. Thus, multilateral partnerships can help in tackling tech-induced money laundering through strengthened cooperation.

Money laundering risks: The study highlights that FinTech, while beneficial, also poses significant risks for money laundering activities, especially in developing countries like Nigeria. Regulatory Importance: It emphasizes the critical role of financial regulations in mitigating the risks associated with FinTech and money laundering. Financial Literacy: The paper suggests that financial literacy does not significantly moderate the relationship between FinTech and money laundering, indicating the need for stronger regulatory measures rather than relying solely on financial literacy. Policy Formulation: The findings are crucial for policymakers to formulate strategies that balance the benefits of FinTech with the need to prevent money laundering and ensure financial system integrity.

This research presents a novel approach to methodology, specifically focusing on the qualitative research design, addressing population, sampling techniques and data collection methods. It emphasizes techniques aimed at ensuring measurement quality and achieving research objectives. Data collection used survey questionnaires, while analysis involved both statistical package for social science (SPSS) and PLS-SEM. SPSS facilitated descriptive and preliminary analyses, while PLS-SEM confirmed measurement quality and tested hypotheses. Ethical considerations were paramount throughout the research process, underscoring the commitment to maintaining originality in research endeavors.

This paper aims to investigate the impact of board characteristics on environmental, social and governance (ESG) disclosure in the energy industry of emerging economies.

The authors adopt the Bloomberg ESG rating to measure the extent of ESG disclosure using a sample of 1,260 observations from BRICS emerging economies. Multiple regression techniques were used to estimate the effect of board characteristics on ESG disclosures of a sample Brazil, Russia, India, China, and South Africa (BRICS) listed companies between 2010 and 2019.

The authors find a relatively low (at 37%) level of ESG disclosure among the sampled firms and a relatively high degree of variability. The authors also find that board gender diversity, board composition and board diligence are positively related to the level of ESG disclosure while the study documents no relationship between board size and ESG disclosure.

The study’s findings highlight the importance of corporate board attributes in influencing strategic decisions such as the level of ESG disclosure and the findings may be useful to regulators, policymakers and investors in making informed investment decisions.

To the best of the authors’ knowledge, this study is one of the first attempts at examining the impact of board characteristics on ESG disclosure in the energy industry in emerging economies. The paper provides new evidence on the relationship between board characteristics (BC) and ESG disclosure in the energy industry of emerging BRICS countries within a panel multi-country research setting.

This paper aims to examine the relationship between terrorism and innovation and the moderating role of venture capital.

The paper has used panel data from 140 countries covering the period of 2007–2016 and has analysed the data by using generalised method of moments instrumental variables (GMM-IV) estimation method to control for unobserved endogeneity among the variables.

The authors find that terrorism has negative impact on innovation. Interesting results emerge when we separated the developed countries from others. The results show that the impact of terrorism on innovation is lower in developed countries. This is due to the fact that strong institutional settings in developed countries make the investors confident by providing support and incentives. Better institutional settings in developed countries also help to reduce uncertainty, which maximise innovation and minimise terrorism risk. The authors also find that venture capital positively moderates the terrorism and innovation relationship. This implies that by providing sufficient fund for technological development, venture capital may help to reduce terrorism risk.

These results may guide the policy makers to find a business solution instead of lengthy political solution to mitigate terrorism risk in emerging countries. Overall, this paper will provide the basis for improving the counter-terrorism approaches from an innovation perspective.

The paper has used terrorism and venture capital data from 140 countries and finds interesting results that may help the policy makers to reduce the effect and intensity of terrorism in emerging countries.

This study aims to examine the association between non-audit fees and audit quality by using the context of gender-diverse audit committees. Further, the authors assess whether this link is moderated by industry-specialist auditors.

This study used non-financial FTSE-350 firms over the period of seven years. In addition, the authors use ordinary least squares regression to test the research hypotheses.

The authors find that female directors on audit committees are negatively related to non-audit fees, suggesting that non-audit fees reduce audit quality. Moreover, the results indicate that industry-specialist auditors positively moderate the link between gender-diverse audit committees and non-audit fees. This suggests that non-audit fees improve audit quality when the auditor is an industry-specialist.

The study does not support blanket restrictions on non-audit fees. It recommends regulators to consider industry expertise of auditors when devising non-audit fee restrictions. Moreover, the findings of this study have implications for firms aiming to understand whether non-audit fees could be used for enhancing audit quality.

By using the context of female directors on audit committees, the authors conclusively assess the link between non-audit fees and audit quality. Further, this study provides a more robust evidence on whether industry-specialist auditors affect the relationship between non-audit fees and audit quality.

With suitable optimization criteria, hybrid models have proven to be efficient for preparing portfolios in capital markets of developed countries. This study adapts and investigates these methods for a developing country, thus providing a novel approach to the application of banking and finance. Our specific objectives are to employ a stochastic dominance criterion to evaluate the performances of over-the-counter (OTC) companies in a developing country and to analyze them with a hybrid model involving particle swarm optimization and artificial neural networks.

In order to achieve these aims, the authors conduct a case study of OTC companies in Iran. Weekly and daily returns of 36 companies listed in this market are calculated for one year during 2014–2015. The hybrid model is particularly interesting, and the results of the study identify first-, second- and third-order stochastic dominances among these companies. The study’s chosen model uses the best performing combination of activation functions in our analysis, corresponding to TPT, where T represents hyperbolic tangent transfers and P represents linear transfers.

Our portfolios are based on the shares of companies ranked with respect to the stochastic dominance criterion. Considering the minimum and maximum numbers of shares to be 2 and 10 for each portfolio, an eight-share portfolio is determined to be optimal. Compared with the index of Iran OTC during the research period of this study, our selected portfolio achieves a significantly better performance. Moreover, the methods used in this analysis are shown to be as efficient as they were in the capital markets of developed countries.

The problem of optimizing investment portfolios has to allow for correlations among returns from the financial maintenance period under consideration if an asymmetric distribution of returns exists (Babaei et al., 2015). Therefore, it is desirable to select an appropriate criterion in order to prepare an optimal portfolio and prioritize investment options. Although a back propagation technique is very popular in artificial neural (ANN) training, it is time-consuming to train a network in this way, and other methods such as particle swarm optimization (PSO) should be considered instead. In the hybrid combination of PSO and ANN, it is not the structure of a neural network that changes. Rather, the weighting method and the training technique chosen for the network are the important aspects, and these relate to PSO, so the only role ANN plays in this process is to reduce the errors.

The hybrid model combining ANN and PSO is seen to be considerably successful for generating optimal results and appropriate activation functions. These results are consistent with the theoretical findings of Das et al. (2013) and an application of the simple PSO in a study conducted by Pederson and Chipperfield (2010). Our research results also confirm the efficiency of stochastic dominance criteria as noted in the studies conducted by Roman et al. (2013), ANN as in a study carried out by Kristijanpoller et al. (2014) and PSO as in studies conducted by Liu et al. (2015) and Deng et al. (2012). These studies were carried out in the capital markets of developed countries, whereas the authors’ analysis relates to a developing country.

The authors deduce that the tools and methods whose efficiency was proven in the capital markets of developed countries also apply to, and demonstrate efficiency in, two novel applications of portfolio optimization within developing countries. The first of these is gaining familiarity with the theory and practice of these research tools and the methods that enrich financial knowledge of investors in developing countries. The second of these is the application of tools and methods identified by investors in the capital markets of developing countries, which enables optimal allocation of financial resources and growth of the markets. The authors expect that these findings will contribute to improving the economies of developing countries and thus help with economic development and facilitation of improving trends.

Discussions of supply chain management (SCM) techniques have focused on large manufacturers and retailers. Smaller firms are part of a larger supply chain(s), and also experience market uncertainties and difficulties in maintaining efficient material and information flow. This paper reports on a study of the use of SCM techniques in medium‐to‐small manufacturing (MTSM) firms. The study consisted of interviews with executives, and a mail questionnaire asking participants to indicate the extent of their firm's use of specific techniques identified in the literature as contributing to the success of SCM. The study found that the use of SCM techniques vary in extent and between industries, and that the organizational structure of MTSM firms has both helped and hindered the implementation of SCM. Greater education about the benefits, costs, and techniques of SCM is required at all levels of organization.

This study aims to examine the asymmetric effects of average temperature (TP) and rainfall (RF) on the Moroccan food security, measured by the food production index (FPI), using annual data from 1961 to 2020.

The study uses the Climate Change and Food Security Framework (CCFS) developed by the Food and Agriculture Organization (FAO) and employs the nonlinear auto-regressive distributed lag (NARDL) model and various econometric techniques to show the effects of climate variability in the short and long-term. It also examines if the impacts on Moroccan food security are asymmetric by analyzing the positive and negative partial sums of mean temperature and rainfall.

The study shows that RF has a long-term relationship with FPI, with increased RF leading to increased FPI and decreased RF leading to decreased FPI. FPI responds more strongly and persistently to a positive shock in RF than to an adverse shock. The study also identifies an asymmetric relationship between FPI and RF, with increased TP enhancing food output in the long run and a decrease reducing food production in the long run.

The current study could have some limitations. For instance, there are several other non-climate factors that might potentially impact food security. In particular, CO2 emissions which from the literature is a key variable that represent climate change impact on food security, was not included. The present research has not included those factors mainly because adding more variables to the model reduces the degree of freedom available to estimate the parameters, resulting in inaccurate results.

This paper contributes to the food security literature by utilizing the latest asymmetry methodology to decompose climate changes into their positive and negative trends and examining the contrasting impacts food production.