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Keeping happy and committed workers is an imperative goal for organisations in any field, including higher education. Institutions must, however, have a thorough understanding of the elements that influence various organisational commitment levels before they can develop human resource management guidelines and procedures that work. Hence, by using social exchange theory, this study aimed to investigate the connection between work–life balance (WLB), job satisfaction and organisational commitment among a sample of Zimbabwean higher education institutions. These factors have received relatively minimal attention in academic institutions, particularly in developing nations.

A cross-sectional survey was conducted, using convenience sampling, to examine 224 members of the teaching staff from two universities in western Zimbabwe. The collected data were analysed using partial least squares structural equation modelling.

The results revealed that WLB significantly predicted job satisfaction. Furthermore, the relationship between WLB and affective and normative commitment was found to be indirect and mediated by job satisfaction.

The results of this study suggest that WLB and job satisfaction are crucial factors for higher education institutions that aim to secure their talented faculty's affective and normative commitment. Therefore, universities should implement firm policies and practices that encourage academic staff to maintain a healthy WLB and enhance job satisfaction.

The study's main contribution is the development of a conceptual model that contributes to the ongoing scholarly discourse on how to enhance organisational commitment among academic staff in under-resourced higher education institutions, as well as the concomitant implications for human resource policies within these institutions.

This study aims to examine the potentially important effects of academic embeddedness on college of business student retention and performance as well as the mediating effects of self-efficacy on the academic embeddedness student outcomes relationships. Improvements in student retention and performance reduce costs for students and universities and lead to higher incomes for graduates.

Data were gathered from students in an entry-level business course at a public university in a rural western state. Approximately 45% of the students were female, and the average age of participants was 20 years old. A survey was administered midsemester to gather data on academic embeddedness and self-efficacy. Retention was indicated by a student enrolling in a business course in a subsequent semester. Performance was measured using end-of-semester course grades. Logistic and linear regression as well as mediation analysis were used to test the hypotheses.

Academic embeddedness was found to positively predict both retention and performance, while self-efficacy was found to positively mediate the academic embeddedness retention relationship. The direct effect of embeddedness on performance was not found when controlling for self-efficacy.

Student retention and performance are important to both students and academic administrators. The findings of this study suggest that retention and performance can both be improved by focusing on factors that more strongly embed students to their colleges.

Embeddedness has been found to have high predictive validity in the employment context. This is one of the first studies to consider the effects of embeddedness in the academic context.

This paper aims to investigate the intersection between crowdfunding (CF), open innovation (OI) and responsible innovation (RI) and identify the emerging trends and gaps in research and new paths for CF research in the future. In addition, this paper proposes a conceptual framework and propositions.

This paper is structured in line with the systematic literature review protocol. After reading all the titles, keywords and abstracts, 172 papers focused on OI and RI were selected for this research. Finally, 27 papers that are based on dimensions related to responsible OI were selected for the study.

Due to CF's multidisciplinary nature, the scientific literature on the role of CF in endorsing responsible OI for shared value co-creation appears fragmented and redundant. Several emerging trends and gaps of research and new paths for CF research in the future arise regarding research methodology and theoretical perspective.

To the best of the authors' knowledge, this is the first study investigating the intersection between CF OI and RI.

Digital supply chains require nascent technologies like blockchain and Internet of Things (IoT). There is a need to develop a roadmap for the implementation of these technologies, as they require a huge amount of resources and infrastructure. The purpose of this paper is to analyze the challenges of implementing blockchain-IoT integrated architecture in the green supply chain and develop strategies for the same.

After a thorough literature survey of Scopus-indexed journals and books, 37 barriers were identified, which were then brought down to 15 barriers after confirming with industry and academic experts using the Delphi method. Using the total interpretive structural modeling (TISM) method and cross-impact matrix multiplication applied to classification (MICMAC) analysis, the barriers were modeled, and finally, strategies were formulated using a concept map to handle the barriers in the blockchain-IoT integrated architecture for a green supply chain.

This paper presents the research on barriers that can be considered for incorporating blockchain and IoT in the green supply chain. It was found from the TISM model that environmental concerns are Level-1 barriers and need to be addressed by developing appropriate technology and allocating funds for the same. An integrated ecosystem with blockchain and IoT is developed.

The focus of this study was on the challenges of blockchain and IoT; hence, it is required to extend the research and find challenges for different industries and also analyze the criteria using other multi-criteria decision-making (MCDM) methods. Further research is required for the integration of blockchain-IoT with supply chain functions.

The transformation of a traditional supply chain into a green supply chain is possible with the integration of technologies. This research work and the strategies developed are useful to managers and practitioners working on technology implementation. Planning resources and addressing key barriers is possible with the concept maps and architecture developed.

Green supply chain management (SCM) is gaining importance in industry as well as the academic sector due to government Policies and norms worldwide for reducing emissions and encouraging environment-friendly production systems. Incorporating blockchain and IoT in a green supply chain will further digitize and increase transparency in supply chains.

We have done a categorization of all barriers based on the expert survey by academicians and industry experts from industries in India. The concept map helps in identifying possible solutions for the challenges and initiatives to be taken for the smooth integration of technologies in the green supply chain.

Digital resources such as smart applications reviews and online feedback information are important sources to seek customers’ feedback and input. This paper aims to help government entities gain insights on the needs and expectations of their customers. Towards this end, we propose an aspect-based sentiment analysis hybrid approach that integrates domain lexicons and rules to analyse the entities smart apps reviews. The proposed model aims to extract the important aspects from the reviews and classify the corresponding sentiments. This approach adopts language processing techniques, rules, and lexicons to address several sentiment analysis challenges, and produce summarized results. According to the reported results, the aspect extraction accuracy improves significantly when the implicit aspects are considered. Also, the integrated classification model outperforms the lexicon-based baseline and the other rules combinations by 5% in terms of Accuracy on average. Also, when using the same dataset, the proposed approach outperforms machine learning approaches that uses support vector machine (SVM). However, using these lexicons and rules as input features to the SVM model has achieved higher accuracy than other SVM models.

Despite widespread recognition of the importance of mindfulness in organizational science literature, little is known about how mindfulness motivates individuals to configure information processing and team member exchange relationships to increase creative process engagement. Drawing on motivated information processing theory, this study conceptualizes and empirically examines whether and how mindfulness motivates individuals toward creative process engagement.

The authors collected data through an online survey from 311 respondents working in the Research and Development (R&D) departments of organizations in multiple industries in Pakistan. For analytical purposes, the authors have applied the structural equation modeling technique.

This study advances a different view of individual mindfulness on the creative process engagement in the following ways. First, mindfulness enables individuals to self-regulate in specific situations and become effective in fostering creative process engagement. Second, this study extends research on relational information processing by linking it to mindfulness and creative process engagement. Relational information processing partially mediates the relationship between mindfulness and creative process engagement. Third, this study highlights that mindfulness motivates individuals to focus more on developing quality working relationships, but they seem less willing to participate in idea generation and problem-solving solutions.

The study findings provide implications for research on mindfulness, creativity and motivated information processing to enhance individuals’ creative process engagements. The authors also discuss the implications for executives on the relational and creative benefits of mindfulness.

Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a profound influence on the dissemination of information among participants in stock markets. Consequently, this present study delves into the ramifications of post-pandemic dynamics on stock market behavior. It also examines the relationship between investors' sentiments, underlying behavioral drivers and their collective impact on global stock markets.

Drawing upon data spanning from 2012 to 2023 and encompassing major world indices classified by Morgan Stanley Capital International’s (MSCI) market and regional taxonomy, this study employs a threshold regression model. This model effectively distinguishes the thresholds within these influential factors. To evaluate the statistical significance of variances across these thresholds, a Wald coefficient analysis was applied.

The empirical results highlighted the substantive role that investors' sentiments and behavioral determinants play in shaping the predictability of returns on a global scale. However, their influence on developed economies and the continents of America appears comparatively lower compared with the Asia–Pacific markets. Similarly, the regions characterized by a more pronounced influence of behavioral factors seem to reduce their reliance on these factors in the post-pandemic landscape and vice versa. Interestingly, the post COVID-19 technological advancements also appear to exert a lesser impact on developed nations.

This study pioneers the investigation of these contextual dissimilarities, thereby charting new avenues for subsequent research studies. These insights shed valuable light on the contextualized nexus between technology, societal dynamics, behavioral biases and their collective impact on stock markets. Furthermore, the study's revelations offer a unique vantage point for addressing market inefficiencies by pinpointing the pivotal factors driving such behavioral patterns.

Discussions about digital tourism continue to increase among scholars as Information Communication and Technology (ICT) infrastructure develops. Dynamic changes due to technological aspects have given rise to various developments in the tourism industry. Therefore, this study aims to evaluate the scientific structure of the development of digital tourism topics through a bibliometric analysis approach. In total, 102 publications from research on digital tourism were taken from Scopus database between 2001 and 2021, for further bibliometric analysis using the VOSviewer application. Interesting findings describe the most cited digital tourism publications, the contribution of digital tourism by various authors, institutions, countries, co-citation analysis, bibliographic coupling, and co-occurrence for the main trends of digital tourism. This study compiles a detailed review of digital tourism research. This article adds substantial value to the digital tourism topic by analyzing bibliometric data. It provided scientific information regarding digital tourism for other researchers and future research.

The primary objective of this study is to investigate the association between the dimensions of intellectual capital (IC) and sustainability practices (SP) within the context of manufacturing medium and large (ML) firms in Uganda. The study aims to shed light on whether and how different dimensions of IC contribute to the adoption and implementation of SP by these firms.

This study utilized a cross-sectional and quantitative approach, collecting data through a questionnaire survey from a sample of manufacturing ML firms. The collected data underwent analysis to identify patterns and relationships using the SmartPLS structural equation modeling (SEM) technique.

The findings demonstrated that the three categories of IC (human, structural and relational capital) influence the SP of ML manufacturing enterprises in Uganda. This suggests that IC is a critical component of SP.

Manufacturing enterprises should use their IC to create strategies for sustainable solutions, such as creating new, ecologically and socially responsible products and services and improving current ones to lessen their environmental effect.

This research advances knowledge of SP by revealing if all aspects of IC are significant for the SP of manufacturing enterprises in Uganda.

The objective of this paper is to examine the profound repercussions of workplace bullying (WB), emotional exhaustion (EE), and psychological distress (PD) on poor job performance (PJP) within the intricacies of Thailand’s healthcare sector. It also seeks to elucidate the moderating influence of COVID-19 burnout (CBO) on these variables.

This paper utilized a quantitative research approach. A total of 230 responses were collected from healthcare workers using convenience sampling during a significant surge of the coronavirus in March 2022. To assess the reliability and correlations between constructs, a dual-stage structural equation modeling (SEM) technique was applied.

During the global health crisis caused by COVID-19, WB and PD were found to positively predict PJP, except for EE. The presence of WB elevated EE and PD among Thai hospital staff. PD and EE partially mediated the relationship between WB and PJP. The positive moderating role of CBO among hospital employees significantly buffered the relationship between WB and EE.

The originality of this study lies in the examination of the poor mental health of Thai healthcare workers during the COVID-19 pandemic. Healthcare reforms are required to protect the mental health of Thai healthcare staff to prevent poor job performance following unprecedented circumstances.