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This research attempts to assess the role of green intellectual capital components with respect to the sustainability business performance of manufacturing SMEs in Malaysia.

Empirical data for this study were gathered through structured questionnaire forms, from entrepreneurs, managers, and decision-makers of manufacturing, small and medium enterprises. A sample of 500 individuals from 170 manufacturing SMEs from Malaysia was participated. Partial Least Squares (PLS) Structural Equation Modelling technique was used to examine the impact of green intellectual capital on the sustainability business performance of SMEs.

Results expressed that green intellectual capital has a positive significant impact on the sustainability business performance of manufacturing SMEs in Malaysia. Results also posited that the three components such as green customer capital, green technological capital, and green spiritual capital were supported while green human capital, green structural capital, and green social capital were not supported.

The present study inspects how entrepreneurs, managers, and policymakers should practice the concept of green and sustainability to attain maximum benefits from green intellectual capital to increase the sustainability business performance of their organizations.

This pioneering research produces a comprehensive theoretical model of green intellectual capital, supporting the current literature where similar works have been yet. This theoretical model will guide entrepreneurs and managers of SMEs to measure green intellectual capital in SMEs. Despite the significant contribution, this study offers insights to researchers, academicians and practitioners to mitigate environmental destruction and to achieve the sustainable business performance of SMEs in Malaysia and developing countries.

The research examines how behavioral intentions, as a higher-order construct, indirectly affect financial inclusion through service trust, usage behavior and financial literacy in mobile money adoption.

Following the positivist research philosophy, a cross-sectional study design was used to collect data through questionnaires comprised of scales adapted from prior studies. With a usable sample size of 340 respondents, this study employs partial least squares structural equation modeling to assess the model.

The study revealed the significant indirect role of behavioral intention on financial inclusion through use behavior, behavioral intentions on use behavior through service trust, and use behavior on financial inclusion through financial literacy. The role of behavioral intentions on financial inclusion through serial mediation of service trust, use behavior and financial literacy was also found to be significant.

This study's novelty resides in examining the indirect relationship between behavioral intentions and financial inclusion, specifically via the serial mediation of service trust, use behavior and financial literacy.

The rapid rise of large language models (LLMs) has propelled them to the forefront of applications in natural language processing (NLP). This paper aims to present a comprehensive examination of the research landscape in LLMs, providing an overview of the prevailing themes and topics within this dynamic domain.

Drawing from an extensive corpus of 198 records published between 1996 to 2023 from the relevant academic database encompassing journal articles, books, book chapters, conference papers and selected working papers, this study delves deep into the multifaceted world of LLM research. In this study, the authors employed the BERTopic algorithm, a recent advancement in topic modeling, to conduct a comprehensive analysis of the data after it had been meticulously cleaned and preprocessed. BERTopic leverages the power of transformer-based language models like bidirectional encoder representations from transformers (BERT) to generate more meaningful and coherent topics. This approach facilitates the identification of hidden patterns within the data, enabling authors to uncover valuable insights that might otherwise have remained obscure. The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

This classification offers practical guidance for researchers, developers, educators, and policymakers to focus efforts and resources. The study underscores the importance of addressing challenges in LLMs, including potential biases, transparency, data privacy, and responsible deployment. Policymakers can utilize this information to shape regulations, while developers can tailor technology development based on the diverse applications identified. The findings also emphasize the need for interdisciplinary collaboration and highlight ethical considerations, providing a roadmap for navigating the complex landscape of LLM research and applications.

This study stands out as the first to examine the evolution of LLMs across such a long time frame and across such diversified disciplines. It provides a unique perspective on the key areas of LLM research, highlighting the breadth and depth of LLM’s evolution.

This paper aims to conceptually extend the religious aspect of consumption beyond the intrinsic motivation, i.e. religiosity, to a broader consideration of its social and cultural surroundings by highlighting the concept of “religiocentrism”.

The paper is conceptual and qualitative. It explores the concept of religiocentrism in several disciplines, including theology, politics, sociology, marketing and consumption.

The paper introduces the concept of religiocentrism in understanding religious consumption and marketing among consumers within a religious context. This paper further discusses the origin of the term religiocentrism; religiocentrism as looking beyond the intrinsic motivation, i.e. religiosity, religiocentrism from the social identity theory; past research on religiocentrism in theology, politics, sociology, education, marketing and consumption, as well as suggesting potential future research in religiocentrism within marketing and consumption studies.

The lack of research relating to religiocentrism in marketing makes the depth of the discussion rather limited. This paper, however, does not discuss the term religiocentrism from the theology roots but focuses more on the marketing and consumption aspects of religiocentrism.

Several research papers exist within the different disciplines about religiocentrism. However, to the best of the authors’ knowledge, it can be argued that this paper is one of its kind to highlight the concept of “religiocentrism” in consumption and marketing that considers the social and cultural surroundings.

This study aims to demystify the mediating mechanism behind the relationship between green human resource management (HRM) and an organization’s environmental performance with the support of resource-based view theory and social exchange theory. Specifically, this study investigates the sequential mediation of green work engagement and green innovation on the direct effect of green HRM on environmental performance.

This quantitative study collected data from 311 employees working in various Indian manufacturing firms using an online survey. Structural equation modeling was used to determine the model fit of the serial mediation model, and PROCESS macro was used to test the hypotheses.

The findings of the study revealed the following important results. First, green HRM positively affects an organization’s environmental performance. Second, green work engagement mediates the effect of green HRM on environmental performance. Third, green innovation mediates the effect of green HRM on environmental performance. Fourth, green work engagement and green innovation sequentially mediate the green HRM–environmental relationship.

This study offers the following practical implications. First, it improves the managerial comprehension of the processes in enhancing environmental performance. Second, it implies that managers need to implement green HRM in their organizations as they play a pivotal role in improving employees’ green work engagement, organizations’ green innovation and environmental performance.

The present study is one of the primary research works that examined the serial mediating effect of green work engagement and green innovation in the relationship between green HRM and environmental performance. This study enriches the existing literature on green HRM and environmental performance by uncovering the mediating mechanism of green work engagement and green innovation.

Previous evidence has shown a generally positive relationship between continuously developed innovation, known as innovation persistence and employment growth in firms. This study investigates whether firm size moderates this relationship and how, considering persistent product and process innovation.

The authors studied the influence of firm size on the relationship between innovation persistence and employment using a 10-year panel database of firms based on national innovation surveys. The authors consider firm size as sales and measure innovation persistence through the hazard rate of innovation spells. To assess the main model, they use a system generalized method of moments (GMM) estimator.

The authors' main findings indicate that firm size negatively moderates the relationship between persistent innovation and employment growth. These results suggest that the positive effects of product and process persistent innovation on employment growth decrease as firm size increases. The authors also find evidence indicating that the moderator role of firm size is greater when firms innovate more persistently. Robustness tests with different specifications confirm the results.

The authors show that firm size negatively affects the strength of the relationship between innovation persistence and employment growth in product and process innovations. The authors also show that the moderator role of firm size is greater when firms are more persistent in generating product and process innovation. Additionally, using a panel dataset, they provide evidence from a sample of firms in a developing country where no studies on this matter have previously been conducted.

Drawing on the natural resource-based view (NRBV) theory, the study aimed to examine the mediating role of green innovation (GI) in the nexus between green human resource management practices (Green HRMPs) and sustainable business performance (SBP).

This study adopted the descriptive time-lagged research design. Data were collected from 278 managerial staff of five mining companies in Ghana at different waves within a 3-month interval. Descriptive and inferential statistics were used to analyse the data received using the statistical package for the social sciences (SPSS) statistics (V. 26.0) and Smart PLS (V.4.0).

The study found that Green HRMPs significantly related more to economic performance (EP) than social performance (SP) but did not significantly relate to environmental performance (EnP). Moreover, the results revealed that GI partially mediated the nexus between Green HRMPs and both SP and EP but fully mediated the link between Green HRMPs and EnP.

The relevance of Green HRMPs in ensuring corporate sustainability has been largely established in the extant literature. However, there is an evidential dearth of studies in the literature concerning the mediating role of GI in the nexus between Green HRMPs and SBP, especially in developing economies context. Hence, this study serves as a significant contributing card from Ghana by advancing the NRBV theory.

Nowadays, textiles play a striking role in various medical applications. Compression bandages are the most essential medical fabrics that help treat venous flow and edema. This study aims to investigate the characteristics of different woven compressive bandage structures produced using compact cotton and cotton/lycra.

Four samples were weaved by matt-plain2/2, twill2/2, stripe-stain4 and mock-leno structures. Several properties were tested that related to structural performance. Tensile strength, elastic and sub-bandage pressure are considered the main functional properties. Three different analysis tools were performed: chart-diagram, one-factor ANOVA and radar chart area.

The woven structures critically affected the performance of woven compression bandage samples as well as their classifications.

The woven structures critically affected the performance of woven compression bandage samples as well as their classifications.

The primary goal of this study is to look at the behavioral factors that influence an individual's decision to invest in the Pakistan Stock Exchange (PSX).

Existing behavioral finance theories serve as a foundation for hypotheses. Further hypotheses were investigated by disseminating questionnaire results from a number of individual Pakistani investors. Brokerage and asset management fund managers were also questioned in semi-structured interviews. The obtained data were analyzed using statistical package for the social sciences, and latent variables were identified using the structural equation model (SEM) and an asset management operating system (AMOS).

Individual investor investment decisions in the PSX are influenced by five behavioral factors: herding, market, prospect, overconfidence and gambler fallacy and anchoring-ability bias. The majority of the variables have a modest impact; however, the market component has a significant impact. Only three behavioral elements, herding, prospect and heuristic, are found to influence investment performance among the behavioral factors stated above. Heuristic habits have been discovered to have the greatest positive impact on investment performance.

This study is one of the few in Pakistan that looked at the factors that influence stock investment decisions using behavioral finance. Prior research has only considered the effects of a restricted number of behavioral characteristics on Pakistani individual investors; however, this study seeks to use a whole collection of behavioral factors to examine their impacts on Pakistani individual investors.

The focus of the study remains on the individual investor, whereas the impact of institutional investors on investment behavior could bring different outcomes.

This is among the few studies that investigated the impact of cognitive factors on investment decisions in the context of Pakistan and will help policy makers, opinion makers and individuals.

For the provision of smart library services to end users, tools of the Internet of Things (IoT) play a significant role. The study aims to discover the factors influencing the adoption of IoT in university libraries, investigate the impact of IoT on university library services and identify challenges to adopt IoT applications in university libraries.

A systematic literature review was carried out to address the objectives of the study. The 40 most relevant research papers published in the world’s leading digital databases were selected to conduct the study.

The findings illustrated that rapid growth in technology, perceived benefits, the networked world and the changing landscape of librarianship positively influenced the adoption of IoT in university libraries. The study also displayed that IoT supported library professionals to initiate smart library services, assisted in service efficiency, offered context-based library services, provided tracking facilities and delivered effective management of library systems. Results also revealed that a lack of technical infrastructure, security and privacy concerns, a lack of technological skills and unavailability of policy and strategic planning caused barriers to the successful adoption of IoT applications in university libraries.

The study has provided theoretical implications through a valuable addition to the current literature. It has also offered managerial implications for policymakers to construct productive policies for the implementation of IoT applications in university libraries for the attainment of fruitful outcomes. Finally, the study provides a baseline for understanding the adoption of IoT in academic libraries.