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This paper aims to examine the comovement among green bonds, energy commodities and stock market to determine the advantages of adding green bonds to a diversified portfolio.

Generic 1 Natural Gas and Energy Select SPDR Fund are used as proxies to measure energy commodities, bonds index of S&P Dow Jones and Bloomberg Barclays MSCI are used to represent green bonds and the New York Stock Exchange is considered to measure the stock market. Granger causality test, wavelet analysis and network analysis are applied to daily price for the select markets from August 26, 2014, to March 30, 2021.

Results from the Granger causality test indicate no causality between any pair of variables, while cross wavelet transform and wavelet coherence analysis confirm strong coherence at a high scale during the pandemic, validating comovement among the three asset classes. In addition, network analysis further corroborates this connectedness, implying a strong association of the stock market with the energy commodity market.

This study offers new evidence of the temporal association among the US stock market, energy commodities and green bonds during the COVID-19 crisis. It presents a novel approach that measures and evaluates comovement among the constituent series, simultaneously using both wavelet and network analysis.

The purpose of this paper is to examine the correlation between firm size, growth and profitability along with other firm-specific variables (like leverage, competition and asset tangibility), macroeconomic variable (like GDP growth-business cycle) and stock market development variable (like MCR).

Using the COMPUSTAT Global database this work uses panel dynamic fixed effects model for nearly 12,001 unique non-financial listed and active firms from 1995 to 2016 for 12 industrial and emerging Asia–Pacific economies. This interrelationship was also examined for small, medium and large size companies classified based on three alternate measures such as total assets, net sales and MCR of firms.

The persistence of profits coefficient was found to be positive and modest. There is evidence of a negative size-profitability and positive growth-profitability relationship suggesting that initially profitability increases with the growth of the firm but eventually, overtime, gains in profit rates reduce, as size increases indicting that large size breeds inefficiency. The relationship between firm's leverage ratio and its asset tangibility is found to be negative with profitability. The business cycle and stock market development variables suggest a positive relationship with the profitability of firms. However, the significance of estimated coefficients was mixed and varied among different selected Asia–Pacific economies.

The study has economic implications on issues such as industrial concentration, risk and optimum size of firms for practicing managers of modern enterprise in emerging markets.

The analysis of the relationship between the firm size, growth and profitability is uniquely determined under a dynamic panel fixed effects framework using firm-specific variables along with macroeconomic and financial development determinants of profitability. This relationship is estimated for a large and new data set of 12 industrial and emerging Asia–Pacific economies.

本研究擬探討公司的規模、成長和盈利能力之間的關係， 同時亦涵蓋公司特有的其它變量 （如愩杆作用， 競爭和資產的有形性）， 宏觀經濟變量 （如國內生產總值增長與景氣之循環）， 以及股市發展變量 (如MCR) 。

本研究以COMPUSTAT 全球資料庫、使用動態面板固定效應模型，涵蓋幾近12001間獨特的、非金融上市及活躍的公司、覆蓋期由1995年至2016年，涉及12個工業及新興的亞太經濟體。這相互關係分析研究亦於大、中及小型企業內進行，而這些企業就規模方面的分類是基於三個交替的測量而釐定的，如總資產、銷售淨額、以及企業的MCR。

研究發現、利潤係數的持續性是正且適中不強的。有證據顯示、規模的大小與盈利能力是負相關的，而增長與盈利能力則為正相關；這暗示盈利能力初時會因企業的成長而增強，但隨著時間的推移最终當規模增大、利潤率的增長會下降，這提示我們：大的規模會導致效率低下。企業的杠桿比率與其資產有形性的關聯被發現與盈利能力成負相關。經濟週期及股市發展變量暗示與企業的盈利能力之關聯為正相關。唯估計係數的意義會因被挑選之各個不同亞太經濟體而有異和不統一的。

本研究對在新興市場的現代企業內工作的業務經理有其實際作用，因研究為他們在業務問題如產業集中度、危機、公司的最佳規模等問題上提供了經濟方面的啟示。

本研究分析公司規模、成長與其盈利能力的關係時，獨特之處是採用了動態面板固定效應模型，並於應用盈利能力的宏觀經濟和金融發展的決定因素的同時，也使用了企業特有的變量。而這關係的分析研究涵蓋12個工業及新興的亞太經濟體的龐大且新的數據集。

This paper provides remarkable insight into the structural components of a firm's core competence and its development via research and development (R&D) activities for innovation and exporting activities.

The authors have used a positivist design and a deductive methodology. The authors have examined the extant literature developing a theoretical framework to empirically investigate the relationships between a firm's core competence, organisational learning (OL), tacitness, dynamic capability and R&D activities. To carry out this investigation, the authors have collected stratified sample data from 330 firms operating in North East England, a peripheral region of England.

The authors have found that there are indeed significant statistical relationships between these structural components, R&D activities and a firm's core competence, and this nexus is pertinent to innovation and exporting. Furthermore, it is found that North East England is significantly constrained by the lack of finance, technological capability, experts and brain drain. Based on these findings, the authors propose a cooperative R&D framework to narrow down these constraints to assist firms in developing core competencies for innovation and exporting in peripheral regions.

There is an urgent need to investigate the incidence of knowledge-driven activities, R&D, the extent of innovation and exporting activities of firms operating in North East England, a peripheral region of the United Kingdom (UK).

This study provides an original and systematic investigation of the firm's core competence and its formation via key structural components for innovation and exporting within an empirical framework.

Since Industry 4.0 (I4.0) is a new idea in Bangladesh, this study supports I4.0 adoption. Companies struggle to implement I4.0 and fully profit from the fourth industrial revolution’s digital transformation due to its novelty. Although barriers to I4.0 adoption are thoroughly studied, the literature has hardly examined the many aspects that are crucial for I4.0 adoption in Bangladesh’s Ready-Made Garment (RMG) industry. So, the purpose of this study is to investigate the barriers of adopting I4.0 in relation to Bangladesh’s RMG industries to enhance the adoption of I4.0 by developing a framework. Ultimately, the goal of this research is to improve the adoption of I4.0 in Bangladesh.

Through a comprehensive analysis of the existing research, this paper aims to reveal the barriers that must be overcome for I4.0 to be adopted. For evaluating those barriers, a decision analysis framework based on the combination of Delphi technique and Decision-Making Trial and Evaluation Laboratory (DEMATEL) method has been developed. The use of DEMATEL has led to a ranking model of those barriers and a map of how the barriers are connected to each other.

The findings reveal that “I4.0 training”, “Lack of Motivation” and “Resistance to Change” are the most significant barriers for adopting Industry 4.0 in RMG sector of Bangladesh based on their prominence scores.

These findings will help the people who make decisions in the RMG industry of Bangladesh, such as company owners, managers and the executive body, come up with a plan for putting I4.0 practices into place successfully. The decision-making framework developed in this research can be utilized by the RMG industry of Bangladesh and other similar industries in developing countries to figure out how important each barrier is for them and how to get rid of them in order of importance.

As far as the authors are aware, there has not been a comprehensive study of the barriers inhibiting the adoption of I4.0 within the scope of Bangladeshi RMG industry. This work is the first to uncover these barriers and analyze them using the combination of Delphi technique and DEMATEL.

The proposal is to answer the following question: based on previous studies, which are the new paths and challenges related to the circular economy (CE) and Industry 4.0 (I4.0)? To answer this question, the research objective is to analyze studies approaching the interface between CE and I4.0.

A systematic literature review (SLR) was conducted on previously published studies pertaining to Scopus and Web of Science bases, and 63 articles were found.

The authors present five new paths and challenges amid the relationship between CE and I4.0: applying those technologies to clean production, using blockchain and big data in the circular supply chain, raising additive manufacturing impact on the CE, seek for a better understanding on how I4.0 technologies can properly support the CE in the stakeholders' view and discerning the factors for implementing those theoretical fields onto supply chains.

Previous studies' sample basis is still recent, lacking research depth. Search strings might have minimized the number of selected studies: there could be a bigger sample.

Practical contributions of this study lay on the applicability of the raised propositions into several sectors' industries.

The authors suggest a transition agenda towards CE, using I4.0 technologies for operational, tactical and strategic personnel within organizations, as well as potential utilization strategies in specific study fields, like supply chain management and product manufacturing per se.

The study presents new paths and challenges amid technologies pertaining to I4.0 and its interfaces with the CE. In the result presentation and analysis, the existing interfaces are described.

The study directs attention to the psychological conditions experienced and knowledge management practices leveraged by faculty in higher education institutes (HEIs) to cope with the shift to emergency remote teaching caused by the COVID-19 pandemic. By focusing attention on faculty experiences during this transition, this study aims to examine an under-investigated effect of the pandemic in the Indian context.

Interpretative phenomenological analysis is used to analyze the data gathered in two waves through 40 in-depth interviews with 20 faculty members based in India over a year. The data were analyzed deductively using Kahn’s framework of engagement and robust coding protocols.

Eight subthemes across three psychological conditions (meaningfulness, availability and safety) were developed to discourse faculty experiences and challenges with emergency remote teaching related to their learning, identity, leveraged resources and support received from their employing educational institutes. The findings also present the coping strategies and knowledge management-related practices that the faculty used to adjust to each discussed challenge.

The study uses a longitudinal design and phenomenology as the analytical method, which offers a significant methodological contribution to the extant literature. Further, the study’s use of Kahn’s model to examine the faculty members’ transitions to emergency remote teaching in India offers novel insights into the COVID-19 pandemic’s effect on educational institutes in an under-investigated context.

Existing research evidence shows a fragmented understanding of the roles of first-line employees (FLEs) as essential factors for successful lean implementation in small- and medium-sized enterprises (SMEs), provoking recent calls for additional research on the identification of enablers and barriers for lean acceptance among workers. Therefore, this paper aims to identify related enablers and barriers to lean implementation among FLEs and determine future research avenues for improving the understanding of lean methodology implementation in SMEs.

Relying on a systematic literature review methodology, the authors aimed to synthesize and evaluate available peer-reviewed papers on the role of FLEs in lean implementation in SMEs. General descriptive and thematic analysis comprehensively depicted the selected research topic and identified the main themes within collected papers and potential future research questions.

The authors identified four main themes related to FLEs’ role in lean implementation: cultural change factors, employee characteristics, management involvement and lean job design. Within each theme, the authors present a comprehensive overview of FLE-related factors and associated enablers and barriers that should be considered for a successful lean implementation in SMEs.

The research outcomes are important to practicing managers in SMEs, helping them facilitate lean acceptance and enhance the likelihood of successful lean implementation.

The insights from this study present building blocks in developing a lean implementation model for SMEs that considers the FLEs’ role more comprehensively.

This study aims to find how can fashion micro-influencers and their electronic word-of-mouth (eWOM) messages increase consumer engagement on social media, focusing on micro-influencers’ influence, typology, eWOM content and consumer engagement.

A total of 20,000 microblogs were collected from Irish fashion micro-influencers and analyzed through keyword classification and content analysis in NVivo. The determinants of eWOM persuasiveness for consumer engagement on social media were investigated based on Sussman and Siegal’s information adoption model.

The study finds that among the four types of micro-influencers, market mavens and their eWOM messages have the highest impact on consumer engagement on social media, and it presents a repetitive and persuasive eWOM model of market mavens to increase consumer participation. Also, the study discovers that micro-influencers’ occasion-related microblogs have an increasing impact on consumer interactions whereas microblogs with brands have a decreasing engagement with consumers on social media.

This study advances prior studies on the relationship between influencers’ eWOM messages and consumer participation on social media by the development of a persuasive eWOM model of micro-influencers to increase consumer engagement and fill in the lack of relevant literature. Also, findings provide actionable insights for marketing communication practitioners to persuade consumers to participate in eWOM communications and establish strong consumer-brand relationships on social media.

Considering the relevance of understanding what influences environmentally sustainable consumer choices, the present study aims to examine and synthesize the key determinants factors from literature and outline a new conceptual framework for explaining green purchasing behaviors (GPBs).

A bibliometric analysis was conducted on 161 articles extracted from Web of Science and Scopus databases, which were systematically evaluated and reviewed, and represent the current GPB knowledge base. Content analysis, science mapping and bibliometric analysis techniques were applied to uncover the major theories and constructs from the state-of-the-art.

The evolving debate between altruistic and self-interest consumer motivations reveals challenges for rational-based theories, as most empirical applications are not focused on buying behaviors, but instead either on pro-environmental (non-buying) activities or on buying intentions. From the subset of leading contributions and emerging topics, nine thematic clusters are unveiled in this investigation, which were combined to create the new PSICHE framework with the purpose of predicting GPB: (P)roduct-related factors, (S)ocial influences, (I)ndividual factors, (C)oncerns about the environment, (H)abits and (E)motions.

By uncovering the multiple intervening factors in GPB decision processes, this study will assist practitioners and academics to move forward on how to foster more sustainable consumer behaviors.

The present study provides readers a summary of an unprecedentedly broad collection of papers, from which the key themes are categorized, the domain's intellectual structure is captured and an actionable framework for enhancing the understanding GPB is proposed. Four new thrust areas and a set of future research questions are included.