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The prediction of stock market (SM) indices is a fascinating task. An in-depth analysis in this field can provide valuable information to investors, traders and policy makers in attractive SMs. This article aims to apply a correlation feature selection model to identify important technical indicators (TIs), which are combined with multiple deep learning (DL) algorithms for forecasting SM indices.

The methodology involves using a correlation feature selection model to select the most relevant features. These features are then used to predict the fluctuations of six markets using various DL algorithms, and the results are compared with predictions made using all features by using a range of performance measures.

The experimental results show that the combination of TIs selected through correlation and Artificial Neural Network (ANN) provides good results in the MADEX market. The combination of selected indicators and Convolutional Neural Network (CNN) in the NASDAQ 100 market outperforms all other combinations of variables and models. In other markets, the combination of all variables with ANN provides the best results.

This article makes several significant contributions, including the use of a correlation feature selection model to select pertinent variables, comparison between multiple DL algorithms (ANN, CNN and Long-Short-Term Memory (LSTM)), combining selected variables with algorithms to improve predictions, evaluation of the suggested model on six datasets (MASI, MADEX, FTSE 100, SP500, NASDAQ 100 and EGX 30) and application of various performance measures (Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error(RMSE), Mean Squared Logarithmic Error (MSLE) and Root Mean Squared Logarithmic Error (RMSLE)).

The enormous amount of waste generated and the scarcity of natural resources worldwide have encouraged societies and industries to adopt the Circular Supply Chain (CSC) concept. With a focus on zero-waste generation, Circular Economy (CE) mimics the ecosystem cycle as an alternative to the traditional linear economic model. This paper aims to investigate the evolution of research themes in this research area, hence, trace the trajectory of development in the field of CSC.

The authors conduct scientometric analysis using Pajek and VOSviewer software to identify key themes in the Circular Supply Chain Management (CSCM) field. The Citation Path Analysis (CPA), including Main Path and Local Path analysis, has been followed by a critical review of the papers. This paper includes highlighting the interrelationships between the information flows in the topic of study as well as an analysis of keywords co-occurrence.

The analysis of keywords co-occurrence revealed that the earlier years of research in CSC were more inclined toward value chain, stakeholders and green supply chains, whereas, in recent years, topics like logistics, Industry 4.0 and food supply chain have been more focused upon. Further, the Main Path Analysis (MPA) revealed an evolving trajectory that examines challenges and opportunities in CSC, the economic aspects of implementing CSC, the impact on the firm's revenue growth and collaboration between multiple echelons of a supply chain and Industry 4.0.

The adoption of scientometrics analysis unveils the hidden flow of information, various themes of research and their interconnections. The development of research trajectories and progressive attention paid to certain topics is also discovered. The research findings could be used by researchers for further theoretical and research development.

This paper traces the path of development in the field of CSC and its emerging trends and provides a thorough understanding of the same. It enables research scholars to conduct an in-depth study in the CSC domain, adding to the body of literature.

This study investigates the views of Italian aquaculture production science students, in their role of future operators, on the application of circular economy strategies.

A key step in the development of professional knowledge is to solicit the opinions of the future operators in the aquaculture sector. The authors used the Q methodology to assess the perceptions of the students on four different knowledge dimensions of the CE: operations, culture and organization, products and services, and ecosystem.

Four discourses emerge from the results, representing the respondents' views on the CE. The first discourse considers CE as business strategy applicable to products and services, the second a corporate mission and the fourth an operational efficiency strategy. Finally, the third discourse views CE as a multidimensional concept.

This study contributes to the scientific and institutional debate on how to accelerate the aquaculture's circular transition. First and foremost, it offers insights to guide policy makers in the development of appropriate knowledge and information systems. Second, it offers the opportunity to improve training programmes to enable current students to be prepared for the future challenges.

The results reflect a different perceived knowledge of CE among future operators, whose opinions are little explored in the literature.

In recent years, both academics and institutions have acknowledged the crucial role multinational enterprises (MNEs) can play in addressing the sustainability challenges, as formalized by the sustainable development goals (SDGs). Nevertheless, because of their extensiveness and their design as country-level targets, SDGs have proven challenging to operationalize at a firm level. This problem opens new and relevant avenues for research in international business (IB). This chapter attempts to frame the topic of extended value chain sustainability in the IB literature. In particular, it addresses a specific topic, that is, how sustainability and resilience-building practices interact in global value chains (GVCs). To do so, the present study develops the case of STMicroelectronics (ST), one of the biggest semiconductor companies worldwide.

Given the relevance of female directors in the governance of any firm, this paper aims to examine their effect on firms’ financial performance by investigating their general impact and segregating the same into different subgroups based on Kanter’s theory.

To achieve the purpose, this study selects a sample of the top 100 listed Indian firms for the period of 2014–2018 and gathers the data pertaining to the variables under consideration from the respective firms’ annual report and corporate database Capitaline Plus. For undertaking the investigation, the authors have segregated the sample into three groups, i.e. firms with boards having less than 10% of female directors are called skewed boards; firms with boards having female directors that range from 10% to 20% are called as tilted board; and firms with boards having sizable representation of female directors of above 20%. To examine the performance impact of overall female directors and their different subgroups, the authors have used a generalized estimating equation model. For the robustness test, the authors have used the fixed-effect model.

The authors find a significant positive impact of the overall percentage of female directors on the financial performance of firms. Additionally, the results indicate that boards with a titled group of female directors and boards with a sizable representation of female directors significantly positively impact firms’ performance. However, the authors fail to extricate any significant performance impact of boards with a skewed group of female directors.

First, the study reveals that despite prevailing nepotism in India, female directors, owing to their core characteristics, can create a favorable perception of firms in the market. Second, it also works as an eye-opener for regulators by revealing the minimum threshold for female directors that a board should have to exploit the benefits of a gender quota rather than mere compliance with the requirements of the Companies Act, 2013. Third, it implies that more gender-diverse boards can improve a firm’s financial performance only if female directors range between the thresholds of 10% to 20%. Finally, the finding is significant for changing the business culture in India, where institutions are traditionally less supportive of women than in other emerging countries.

Departing from existing studies, which provide evidence on the performance impact of the overall percentage of female directors, the study unveils the differential impact of female directors on firms’ financial performance depending on their level of representation on the board. To the best of the authors’ knowledge, this is the first study in the context of an emerging market to test Kanter’s theory.

Loneliness is widely prevalent in modern society. Despite the growth in studies, very limited studies so far have attempted to systematically review the literature. This study aims to consolidate the antecedents of loneliness by reviewing the literature.

The systematic literature review method is adopted to identify the antecedents. Full texts of each article were taken for analysis which was published from 2002 to 2022. Multiple databases were examined and total of 60 articles were included for systematic literature review.

The study presents the descriptive analysis of the articles. Also, the paper thematically presents the key antecedents of loneliness in three themes (a) Loss of love, (b) Individual cognitive and personal factors and (c) Childhood experiences and parenting practices. The study also highlights the moderating effect of demographic factors and lifestyle changes.

The current study is the first systematic literature review to present the antecedents of loneliness. The study contributes by offering an enhanced understanding of loneliness. Also, the study presents contemporary understanding of loneliness and proposes a conceptual framework. The findings are useful to academicians as well as policymakers.

Poland generally has a homogeneous society, conservative towards changes and diversity. The corporate culture in Polish companies reflects this mindset, leading to a lack of inclusion on the corporate board. Additionally, many companies may not fully understand the benefits of an inclusive workplace and legal requirements for gender diversity.

The main objective of the study is to provide a better understanding of the attitude of Polish companies towards diversity policies and reveal differences in actual and expected levels of gender diversity in corporate boards. Thus, we examine compliance with the gender diversity guidelines in the corporate governance code.

Using a sample of 367 Polish companies listed on the Warsaw Stock Exchange, we study the composition of the management and supervisory boards to check if they meet the expected gender diversity criteria. We also look at companies' explanations for non-compliance with the main principles regarding diversity policy.

We find that the current composition of corporate boards of stock companies in Poland is male-dominated. Women represent only 12.72% and 17.12% of the management board and supervisory board members, respectively, and 68.94% (42.23%) of companies have no women on their management (supervisory) board. Moreover, only a small percentage of companies comply with the principles related to gender diversity. Qualifications, experience and education are pointed out as the most important criteria for decision-making on board appointments, with only 2% of companies applying gender as an additional criterion. The study suggests that larger companies are more likely to implement diversity policies.

Rapid innovation and developments in personal electronic technology have encouraged users to change users' devices more frequently than ever, which has resulted in creating a massive increase in the amount of electronic waste. The study focuses on identifying the barriers to closed-loop supply chain (CLSC) in the electronic industry.

A framework for analyzing the relationships among CLSC adoption barriers is designed. The authors adopted the decision-making trial and evaluation laboratory (DEMATEL) technique to determine the critical barriers of electronic CLSC from the opinion of experts in the field.

The outcome from the analysis suggests that cost barriers, financial barrier, process barriers and supplier-side barriers are the main causal factors that prevent the adoption and implementation of e-waste CLSC. The causal relationship indicates that financial barrier is the most influential factor, while phycological barrier is the most flexible barrier to the adoption of e-waste CLSC.

This study is restricted to CLSC adoption barriers in the electronic industry by evaluating 36 sub-barriers grouped into 8 main dimensions related to different members of the supply chain.

Closed-loop adoption barriers have been proposed to understand the crucial barriers to implementation of CLSC in the electronic industry. The cause-and-effect relationship indicates the critical factors to be improved to increase adoption of e-waste CLSC, helping managers and regulatory bodies to mitigate the problem areas.

This study contributes to the literature on CLSC by adopting a multi-criteria decision-making (MCDM) technique which captures the critical barriers of e-waste CLSC adoption in Indian scenario.

Many European businesses are small and medium enterprises (SMEs), contributing significantly to the well-being of local economies and regions. Even so, SMEs face many challenges in fostering innovation and improving performance. Furthermore, the raw material consumption is increasing globally, necessitating the development of strategies that will reduce the number of raw materials extracted and imported while improving the sustainability of small and medium-sized businesses. Consequently, promoting circular economy (CE) strategies, such as industrial symbiosis (IS) partnerships, whereby waste products from other industries serve as a source of raw materials for companies, is critical. Identifying and analysing enablers or drivers that support IS collaborations among SMEs is necessary to achieve this goal. In this regard, the purpose of this study will explore the enablers of IS among SMEs considering sustainability dimensions (environmental, social and economic). As facing a decision-making (DM) problem, the multiple attribute decision-making (MADM) approach was applied in a hesitant fuzzy (HF) environment in this research to answer the research questions. In this regard, in phase 1, IS enablers were identified and extracted using a literature review and experts’ opinions. In phase 2, the hesitant fuzzy Delphi (HFD) method was implemented to screen and finalise the enablers identified. In phase 3, casual relations among final enablers were determined using the hesitant fuzzy ANP (HF-ANP) method. Finally, in phase 4, the relative importance of enablers was calculated using the hesitant fuzzy best–worst method (HF-BWM). Consequently, this study provided potential strategies for IS that can be implemented quickly and used by local authorities to support SMEs in achieving circular waste management.