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Since its development by Tinbergen (1962), the gravity model of international trade has widely been applied to analyse the effect of various factors on trade relationships between countries. Past studies on trade gravity vary not only in the mix of model variables but also in how they have come into the analysis. This study reviews existing literature on bilateral trade with an aim to identify influential predictors such as changes of trade policy and national development strategy and highlight important yet understudied factors such as transport and logistics infrastructure, and sustainable development. To demonstrate the needs to examine these critical factors across industry sectors, the study presents the case of textiles and clothing (T&C) production and trade between China and its trading partners as an illustration. Through the literature review, it shows how the gravity model can be applied to address current issues in international trade arena such as the potential trade war between the US and China, China’s Belt and Road Initiative (BRI), and other important factors shaping global T&C trade. This study offers future research directions for analysis of global trade in the T&C industry and contributes to the wider literature of international business and trade.

Many experts suggest that the human being explore marine resources and marine new energy sources to alleviate the shortage of land resources and the ecological degradation. However, island coastal zones are considered to be fragile ecosystems; their geographical location and natural characteristics, their biodiversity and associated ecosystems, and their exposure to diverse land and sea conditions all make them highly vulnerable to environmental changes and human activities. Therefore, it is necessary to achieve the goals of environmental protection and sustainable development on the basis of a comprehensive evaluation and understanding of islands.

Due to the importance of island groups, this paper conducts evaluation studies on them. Using the Delphi, AHP and TOPSIS methods, this study evaluated quantitatively the comprehensive development level and comprehensive development potential of island groups in terms of resources, natural environment, economy and society. Innovatively using them as two subsystems, the present study combined the coupling coordination model and the obstacle factor calculation method.

The prospective index of comprehensive development was applied to the Changdao Island Group in Yantai, Shandong Province as an example, and the final evaluation revealed that the comprehensive development prospect of this island group had an upward trend from 2010 to 2017. Future efforts should be made to improve its economic and social conditions and economic development status, apart from promoting its comprehensive development by improving human resources management, increasing the GDP growth rate, and improving fresh water and electricity supply.

This study takes the integrated development level of the island and the integrated development potential of the island as two subsystems, and the innovative application of the coupling coordination degree model is used to calculate the integrated development index of the island to understand the development status of the island area. On the basis of this model, the obstacle factor identification method is designed to identify the main obstacle factors, and on the basis of evaluation and identification, specific measures to ensure the sustainable development of the island area are effectively proposed.

The typical approach of modeling the aerodynamics of an aircraft is to develop a complete database through testing or computational fluid dynamics (CFD). The database will be huge if it has a reasonable resolution and requires an unacceptable CFD effort during the conceptional design. Therefore, this paper aims to reduce the computing effort required via establishing a general aerodynamic model that needs minor parameters.

The model structure was a preconfigured polynomial model, and the parameters were estimated with a recursive method to further reduce the calculation effort. To uniformly disperse the sample points through each step, a unique recursive sampling method based on a Voronoi diagram was presented. In addition, a multivariate orthogonal function approach was used.

A case study of a flying wing aircraft demonstrated that generating a model with acceptable precision (0.01 absolute error or 5% relative error) costs only 1/54 of the cost of creating a database. A series of six degrees of freedom flight simulations shows that the model’s prediction was accurate.

This method proposed a new way to simplify the model and recursive sampling. It is a low-cost way of obtaining high-fidelity models during primary design, allowing for more precise flight dynamics analysis.

The primary purpose of this study is to explore the effects of demographic transition toward aging populations on the performance of stock market indices across various economic developments. The research aims to provide valuable insights into the life-cycle hypothesis on savings patterns, investment behavior and the potential reverberations on global financial markets.

The study adopts a comprehensive global perspective, scrutinizing the effects of aging populations on stock market indices across developed, developing and transitional economies through the panel data analysis. Using annual data spanning the period from 1991 to 2020, encompassing a sample of 10 countries from each economic development level, the study employs the panel autoregressive distributed lag (ARDL) model with fixed effect estimation.

The findings unveil a statistically significant positive impact of the elderly population proportion on global stock market indices. However, the magnitude and contours of this impact exhibit considerable heterogeneity across different country groups. Specifically, the study finds that while the aging population significantly influences stock market performance in developed nations, its effect is overshadowed by other economic factors, such as consumer price indices and interest rates, in developing countries and economies in transition.

The originality and value of this study lie in its comprehensive global perspective, which encompasses a diverse array of economies at varying developmental stages. The research contributes to an understanding of the effects of demographic transitions on stock market performance on a global scale. The insights derived from this study hold significant implications for policymakers, financial institutions and investors seeking to navigate the challenges and opportunities posed by aging societies in an increasingly interconnected global economy. Additionally, the findings highlight the need for specific strategies and policies that account for the unique economic characteristics and developmental stages of different nations.

This study examines voluntary cybersecurity risk disclosures (VCRD) by listed Indian companies. It also investigates how it relates to firm-specific characteristics such as size, leverage, profitability, liquidity, beta, market growth and industry.

The extent of VCRD was measured by assessing the cumulative occurrence of cybersecurity risk keywords in the annual report of 100 listed Indian non-financial companies. Keyword extraction and occurrence counts were performed using Python software. A multiple regression analysis was applied to predict the characteristics of VCRD.

The results showed that the theoretical frameworks underpinned by agency and signalling theories continued to provide a valid explanation of VCRD by Indian companies. Specifically, the findings emphasized the importance of firm size, leverage, and beta as significant VCRD determinants. Additionally, the study found that knowledge-intensive industries had a favourable impact on the extent of VCRD.

This study is relevant because it informs company management, regulators and investors about the nature and characteristics of companies that satisfy stakeholder demands to prevent cyber breaches.

Understanding disclosure characteristics is crucial from policy and regulatory perspectives. Studies on cybersecurity disclosures are related to developed economies such as the United States of America and Canada. This is the first study to explore this issue in a developing nation, in general, and in India, in particular, where cybersecurity risk disclosure has yet to be recognized.

In recent years, the role of environmental, social and governance (ESG) disclosure has become crucial. The aim of this paper is to study how corporate governance affects one part of ESG disclosure: anti-corruption disclosure.

This study examined 140 corporate social responsibility (CSR) reports from companies listed on the Italian stock markets and 50 CSR reports from other companies, then this study analysed the adoption of the Global Reporting Initiative (GRI) standard no. 205.

The results show a low level of disclosure, and that corporate governance issues matter. In particular, the analysis found a positive relationship between the presence of female and outside members, the number of board members and the level of anti-corruption disclosure.

This study acknowledges some limitations. Firstly, the research is based on a one-year sample. Secondly, the research hypotheses are confirmed only when considered in relation to a single section of the GRI standards. Thirdly, this study has a bias towards relatively large enterprises.

It could be worthwhile introducing a soft regulation regarding the composition of the board of directors that requires a certain quantitative and qualitative composition.

To the best of the authors’ knowledge, this is one of the few studies, the first in Italy, that sheds light on anti-corruption disclosure and its determinants.

This study explored how board diversity affects environmental, social, and governance (ESG) performance in the Italian banking sector. Specifically, this study examined whether the presence of specific corporate governance (CG) characteristics (board diversity) in Italian Cooperative Credit banks is related to ESG dimensions.

The authors examined a sample of 247 Italian Cooperative Credit banks for the period 2017–2021 and developed an econometric model by applying unbalanced panel data with firm fixed effects and controls per year. To verify the research hypotheses, the authors analyzed board diversity in terms of board attributes variables (size, gender diversity, age, activity, independence and corporate social responsibility/sustainability committee (CSR) and measured ESG dimensions using the ESG score provided by Refinitiv.

The findings suggest that board size, independence and the existence of a CSR/sustainability committee positively affect banks' ESG performance, while no significant relationship between board average age and ESG performance was found. The study also explored how the critical mass of women on a board affects ESG performance by testing the positive impact of gender diversity on ESG dimensions only up to a certain threshold of female directors.

This study is highly relevant to managers and investors who consider ESG issues in their decision-making processes. The findings support regulators by offering insights into ways to improve ESG performance through the specific design and application of governance mechanisms.

From a practical perspective, this investigation has implications for both practitioners and regulators, suggesting that chief executive officers (CEOs) and managers should pay more attention to CG aspects to improve ESG performance and that policy-makers should give greater consideration to these aspects of CG in their efforts to enhance ESG performance.

This study offers an in-depth analysis of banks' ESG practices and attempts to bridge the gap in the literature on ESG in the Italian banking industry. This study is the first to investigate the relationship between CG variables and ESG dimensions in this context.

Research dealing with earnings management in the public-sector context is expanding. This paper aims to review the existing literature to understand how research is developing and points out gaps deserving further investigation.

This study uses the structured literature methodology to investigate the state-of-the-art and future directions of the literature on earnings management in the public sector. In total, 78 articles were explored.

The critical analysis of the literature shows that different but related streams of literature are emerging, focused on both a macro- and a micro-level perspective (mainly local governments and state-owned enterprises).

This study is the first that offers a comprehensive review of the literature on the emerging topic of earnings management in the public-sector context. The structured literature review enables the identification of future directions for the literature in this field.

The current paper aims to analyse the antecedents of leader–member exchange relationships (LMX) by specifically focusing on the influence of the supervisor’s feedback delivery tactic.

This study uses qualitative research methods with primary interviews as the main data source. Primary interviews with 40 managers from top supermarkets in Nigeria, South Africa and the UK were undertaken.

The authors found that both high-quality positive feedback and constructive criticisms produced the same feelings – more positive interpersonal relationships with their supervisors, higher levels of commitment to their organisations, higher job satisfaction and thus, high-quality LMX relationships. Where criticisms were delivered without greater interpersonal treatment, feedback was perceived as negative, and participants revealed lack of job satisfaction, lack of commitment to their organisations, poor interpersonal relationship with their supervisors, high turnover intent and thus low-quality LMX relationship.

To the best of the authors’ knowledge, the current paper is one of the first studies to highlight the consequences of different feedback delivery tactics on subsequent LMX quality particularly in African context. The authors specifically develop a process-based model of enhancing high-quality LMX, which shows the role of the supervisor’s feedback delivery tactic in the process. The authors also develop a process-based model that illustrates how negative/unconstructive feedback could result in a low-quality LMX. Finally, to the best of the authors’ knowledge, this paper is also one of the first to offer a comparative assessment between African and British (the UK) empirical settings and highlight some interesting dynamics concerning LMX quality and role of supervisor’s feedback delivery tactic.

This empirical study is developed with an aim of exploring how and to what extent the current year’s as well as lagged years’ disclosure level of intellectual capital (IC) influences the firm's value which is measured through the Cost of Equity Capital.

The content analysis technique is applied on the annual reports of 50 sample companies to construct an IC disclosure index for measuring the volume of IC disclosure and to collect other relevant information for the study periods from 2015–16 to 2019–20. However, due to unavailability of information for all the study periods, 7 companies were eliminated and finally 43 companies are used for analytical purpose. Keeping in mind about the aim of this research, regression equations are run to analyze the cause–effect relationship between the IC disclosure level and the Cost of Equity Capital after excluding the influence of other factors like firm size, unlevered beta and market-to-book ratio.

The present study finds that the amount of IC disclosure has an inverse association with the cost of equity capital. Our study also confirms that lagged years’ IC disclosure has a greater inverse effect than the current year’s IC disclosure on the Cost of Equity Capital.

For the first time in the literature of IC disclosure in the perspective of Indian context, this empirical study takes an initiative to investigate the impact of current year’s as well as backlog years’ IC disclosure level on the Cost of Equity Capital.