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The empirical study aims to examine the impact of board diversity with respect to gender and nationality on firm performance in an emerging economy. This research further splits the sample into family and non-family domains and investigates the diversity–performance nexus in isolation.

The sample consists of 183 listed companies in Bangladesh over the period 2007 to 2017. This study employed the generalised method of moments (GMM) technique to address the possible endogeneity issue in the governance–performance connection. To underscore the strength of diversity, three distinctive assessment measures were used: percentage representation of females and foreign directors, the Blau index and the Shannon index.

The results for the full sample models reveal that board heterogeneity regarding both female and foreign directors positively and significantly influences firm performance as measured by return on assets (ROA). Further to this, female directors in family-owned businesses have a positive association with profitability, whereas foreign nationals demonstrate a significant positive association with performance in non-family firms. Additionally, at least three women directors are needed to make a positive difference in profitability; however, a sole director with foreign nationality is capable of demonstrating a similar impact on performance.

The findings are significant for policymakers and organisations that advocate diversity on corporate boards of directors, and the minimum number of diverse board members needs to be considered depending on the identity to bring about a significant change in organisational outcome. Therefore, the findings of this study may be applied to other emerging economies with similar institutional characteristics.

This study reinforces the existing stock of knowledge on the impact of board diversity on the profitability of firms, especially in the context of an emerging economy – Bangladesh. Irrespective of the given backdrop, this study finds that both gender and nationality diversity in the case of Bangladesh is found to have a positive and significant effect on financial performance with respect to all the diversity metrics, i.e. the proportionate number of female and foreign directors on the boards, the Blau index and the Shannon index.

This study aims to highlight the impact of introducing women directors to board committees, thereby empowering them to contribute to decision-making, and as a result, influence firms’ financial performance in an emerging economy.

This study uses a fixed-effects panel data regression model to test the impact of gender diversity on corporate boards as well as board committees on firms’ financial performance. Two widely used diversity measures, the Blau index and the Shannon index, have been used to enhance the robustness of the results.

The findings suggest that gender diversity on prominent board committees (remuneration committee and nomination committee) positively affects firms’ financial performance when measured by the market-based performance measure, but it is insignificant when measured through accounting-based performance indicator. Furthermore, the benefits of gender diversity accrue to the firms only when women are part of prominent committees and are engaged in governance mechanisms, rather than just being appointed on corporate boards as a means of tokenism.

This study is among the first to investigate the relationship between gender diversity and financial performance through the lens of committee assignments. Moreover, the unique cultural and institutional setting offered by India, which is an emerging economy, provides a fertile ground for understanding the role of women leaders in the workforce.

Diversity in boards has gained attention as a reflection of societal imbalances. The purpose of this paper is to investigate the impact of diversity in terms of both gender and nationality in management boards of small and medium-sized enterprises (SMEs) on firm performance from an upper echelons perspective. The authors also examine how board-specific characteristics influence the structural makeup of boards in gender and nationality diversity terms.

The authors focus on the UK because of its individualistic society and flexible labour market and assess 309 SMEs in the manufacturing industry over 2009–2019. A 3-stage least squares (3SLS) estimator is used to analyse the data, the Shannon index to measure board diversity, return on assets as proxy for firm performance, and owner-manager presence, board member age and tenure are the board-specific characteristics of primary interest.

Both gender and nationality diversity contribute to firm performance and represent distinct upper echelon characteristics that change the cognitive and psychological dynamics of boards. Firms with larger boards do not perform better, but diverse boards reduce the narrowing view of CEOs. Yet the presence of owner-managers, despite their performance-enhancing contribution, holds firms back from benefitting from diversity as a strategic choice.

This study extends the upper echelons theory to include board diversity as an important aspect that should become more central in upper echelon thinking when understanding firm performance. The authors’ findings suggest that theoretical developments in search of understanding firm behaviour must proceed by accounting for diversity and not simply focusing on decision-making styles.

We propose a risk factor for idiosyncratic entropy and explore the relationship between this factor and expected stock returns.

We estimate a cross-sectional model of expected entropy that uses several common risk factors to predict idiosyncratic entropy.

We find a negative relationship between expected idiosyncratic entropy and returns. Specifically, the Carhart alpha of a low expected entropy portfolio exceeds the alpha of a high expected entropy portfolio by −2.37% per month. We also find a negative and significant price of expected idiosyncratic entropy risk using the Fama-MacBeth cross-sectional regressions. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

We propose a risk factor of idiosyncratic entropy and explore the relationship between this factor and expected stock returns. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

Given the lack of focus on a standardized measurement framework (e.g. benchmarking tool) to assess and quantify complexity within the supply chain, this study has developed a unified supply chain complexity (SCC) index and validated its utility by examining the relationship with firm performance. More importantly, it examines the role of firm owners' business knowledge, sales strategy and board management on the relationship between SCC and firm performance.

In this study, the unit of analysis is Indian manufacturing companies listed on the Bombay Stock Exchange (BSE). This research has merged panel data from two secondary data sources: Bloomberg and Prowess and empirically operationalized five key SCC drivers, namely, number of suppliers, the number of supplier countries, the number of products, the number of plants and the number of customers. The study employs panel data regression analyses to examine the proposed conceptual model and associated hypotheses. Moreover, the present study employs models that incorporate robust standard errors to account for heteroscedasticity.

The results show that complexity has a negative and significant effect on firm performance. Further, the study reveals that an owner's business knowledge and the firm's effective sales strategy and board management can significantly lessen the negative effect of SCC.

This study develops an SCC index and validates its utility. Also, it presents a novel idea to operationalize the measure for SCC characteristics using secondary databases like Prowess and Bloomberg.

This study investigates information flow of market constituents and global indices at multi-frequencies.

The study’s findings were obtained using the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (I-CEEMDAN)-based cluster analysis executed for Rényi effective transfer entropy (RETE).

The authors find that significant negative information flows among sustainability equities (SEs) and conventional equities (CEs) at most multi-frequencies, which exacerbates diversification benefits. The information flows are mostly bi-directional, highlighting the importance of stock markets' constituents and their global indices in portfolio construction.

The authors advocate that both SE and CE markets are mostly heterogeneous, revealing some levels of markets inefficiencies.

The empirical literature on CEs is replete with several dynamics, revealing their returns behaviour for diversification purposes, leaving very little to know about the returns behaviour of SE. Wherein, an avalanche of several initiatives on Corporate Social Responsibility (CSR) enjoin firms to operate socially responsible, but investors need to have a clear reason to remain sustainable into the foreseeable future period. Accordingly, the humble desire of investors is the formation of a well-diversified portfolio and would highly demand stocks to the extent that they form a reliable portfolio, especially, amid SEs and/or CEs.

本研究擬審查多頻率的及為市場成份的信息流和全球指數。

研究人員使用基於改良完全集合經驗模態分解自適應噪聲(Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise)的聚類分析法,取得Rényi有效轉移熵,藉此得到研究結果。

我們發現、於大部份多頻率,在持續性股票和傳統股票間有顯著的負信息流動,這會增加多樣化的益處。這些信息流大部份是雙向的,這強調了股票市場成份及其全球指數在構建投資組合上的重要性。

我們認為持續性股票市場和傳統股票市場大多為異質市場,這顯示了市場的低效率,而且這低效率的程度頗大。

關於傳統股票的實證性文獻裡是充滿了變革動力的,這顯示了它們以多樣化為目的的回報行為。這使我們對關於持續性股票的回報行為、認識變得實在太少了。於此,大量的企業社會責任的新措施不斷提醒各公司、要本著企業社會責任的理念去營運;但投資者需清晰明白他們為何需在可見的將來保持可持續性。因此,他們卑微的願望是一個較好的多樣化投資組合得以形成,故此他們高度要求股票要有組成可靠投資組合的性質和能力,特別是在持續性股票和/或傳統股票當中。

The relationship between the various existing smell taxonomies and the smell impacting factors has been established. The ideology is to identify the most critical smell influencing factors in the vicinity of various software development environments.

To fulfill the said task, the utilization of the amalgamation of two multicriteria decision-making techniques, namely, Entropy method and CODAS method, is presented.

Through this article, the most critical smell impacting criteria with respect to the smell taxonomies is identified. Furthermore, the behaviour of 4 software development principles was then analysed, and their working state has been successfully assessed.

The ideology to study design-related smells in the software system has been studied by a lot of researchers. Some of them have worked upon their detection and the corresponding refactoration process with the help of several algorithms like machine learning and artificial intelligence. But how and to what extent these design-related smells impact the software development environment has remained out of the limelight till now. Through this article, this research gap has been identified, and an attempt to fill it has been made.

A number of recent artificial intelligence (AI)-enabled technologies, including summarisers, paraphrasers and the cutting-edge chatbots not only have outstanding potentials in modern educational systems but also could lead to a dramatic paradigm shift in the whole education process. This study aims to explore the factors that shape the academic community’s desire and intention to use AI conversational chatbot technology, with a particular focus on the leading ChatGPT.

This study uses a mixed method approach to explore the educators’ adoption of chatbots through an empirically validated model. The model, known as the “Educators’ Adoption of ChatGPT”, was developed by integrating the theoretical foundations of both the Unified Theory of Acceptance and Use of Technology and Status Quo Bias (SQB) frameworks, as well as insights gathered from interviews. The relationships within this model were then tested using a quantitative approach. The partial least squares-structural equation modelling method was used to analyse 243 valid survey responses.

The outcomes of the analysis indicated that perceived educators’ effort expectancy, educators’ autonomous motivation, perceived learners’ AI competency, perceived educators’ competency, innovative behaviour towards technological agility and perceived students’ engagement are significant determinants of educators’ intention to use chatbots. In contrast, perceived unfair evaluation of students, perceived students’ overreliance and perceived bias/inaccuracies were shown to have significant impacts on the resistance to use the technology, which typically implies a negatively significant influence on the educators’ use intention. Interestingly, perceived fraudulent use of ChatGPT was proven insignificant on the resistance to use chatbots.

This study makes a significant contribution to the field of educational technology by filling the gap in research on the use and acceptance of AI-enabled assistants in education. It proposes an original, empirically validated model of educator adoption, which identifies the factors that influence educators’ willingness to use chatbots in higher education and offers valuable insights for practical implementation.

This research fills a gap in process science by defining and explaining entropy and the increase of entropy in processes.

This is a theoretical treatment that begins with a conceptual understanding of entropy in thermodynamics and information theory and extends it to the study of degradation and improvement in a transformation process.

A transformation process with three inputs: demand volume, throughput and product design, utilizes a system composed of processors, stores, configuration, human actors, stored data and controllers to provide a product. Elements of the system are aligned with the inputs and each other with a purpose to raise standard of living. Lack of alignment is entropy. Primary causes of increased entropy are changes in inputs and disordering of the system components. Secondary causes result from changes made to cope with the primary causes. Improvement and innovation reduce entropy by providing better alignments and new ways of aligning resources.

This is the first detailed theoretical treatment of entropy in a process science context.

Globally, prefabrication in housebuilding has evolved as an innovative approach to attain sustainability and affordability. However, the SC, including non-producers and producers, of prefabricated housebuilding projects is still not perceptually aligned, hindering innovation diffusion. This paper investigates the contemporary industry perspective on PHB for conceptualisation, market share and growth, innovation diffusion and the producer's role in the context of New Zealand.

An exploratory qualitative research design was chosen to learn the perceptual stance of the industry. A semi-structured survey was conducted, followed by interviews with selected supply chain participants, who were producers and non-producers and had relevant experience in the PHB industry.

This study reports the common terminologies used by supply chain members, with justification and explanation. Further, the perceived market share and growth of the PHB industry are obtained and compared with subsequent studies to determine the capability and capacity. The perception of the diffusion of PHB by type is reported to portray the overall trend of the industry. In the last, the role of producers as the suppliers of PHB projects is investigated to establish the stakeholder positional criticality.

This study can help researchers and practitioners gain insight into the PHB industry from a multi-dimensional perspective. This study is a potential first step to formalise the policy, programme, strategies and action plan for the uptake of the PHB in the New Zealand.

PHB diffusion in the supply chain perspective, considering multi-dimensional aspects, has not been considered in previous studies as government agencies produce most of the literature. This academic research establishes the theoretical linkage towards PHB diffusion and reports the current status.