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This study aims to find out whether firms in the local textiles industry are benefiting from the combined implementation of lean practices (LPs) and quick-response manufacturing (QRM) during the era of COVID-19. The study further explores the mediating role played by quick response manufacturing in the relationship between LPs, internal process performance (IPP) and customer performance.

A questionnaire is used to garner data from 123 local firms in Ghana’s textile industry. The analysis for all the hypothesized relationships is done using partial least square structural equation.

The results of the study indicate that LPs significantly strengthen the implementation of QRM. The result also suggests that LPs and QRM can be combined to influence IPP and customer performance. The results further suggest that QRM mediates the relationship between LPs, IPP and customer performance.

This study proposes and develops an integrated research model that explores the synergistic application of LPs and QRM in achieving improvements in IPP and customer performance from an emergent country perspective during the era of COVID-19. QRM serves as an important mechanism through which the relationship between LPs, IPP and customer performance can be explained.

This study aims to solve the problems of large training sample size, low data sample quality, low efficiency of the currently used classical model, high computational complexity of the existing concern mechanism, and high graphics processing unit (GPU) occupancy in the current visualization software defect prediction, proposing a method for software defect prediction termed recurrent criss-cross attention for weighted activation functions of recurrent SE-ResNet (RCCA-WRSR). First, following code visualization, the activation functions of the SE-ResNet model are replaced with a weighted combination of Relu and Elu to enhance model convergence. Additionally, an SE module is added before it to filter feature information, eliminating low-weight features to generate an improved residual network model, WRSR. To focus more on contextual information and establish connections between a pixel and those not in the same cross-path, the visualized red as integer, green as integer, blue as integer images are inputted into a model incorporating a fused RCCA module for defect prediction.

Software defect prediction based on code visualization is a new software defect prediction technology, which mainly realizes the defect prediction of code by visualizing code as image, and then applying attention mechanism to extract the features of image. However, the challenges of current visualization software defect prediction mainly include the large training sample size and low sample quality of the data, and the classical models used today are not efficient, and the existing attention mechanisms have high computational complexity and high GPU occupancy.

Experimental evaluation using ten open-source Java data sets from PROMISE and five existing methods demonstrates that the proposed approach achieves an F-measure value of 0.637 in predicting 16 cross-version projects, representing a 6.1% improvement.

RCCA-WRSR is a new visual software defect prediction based on recurrent criss-cross attention and improved residual network. This method effectively enhances the performance of software defect prediction.

This systematic review aims to identify the key determinants of knowledge transfer (KT) activities among researchers.

This study systematically reviewed KT literature in academic settings from 1995–2023. The authors searched Web of Science and Scopus using predefined keywords, following PRISMA guidelines for screening and eligibility assessment. From 158 selected articles, the authors extracted data and conducted a descriptive analysis to map KT activities’ evolution. A narrative synthesis approach categorized determinants of researchers’ KT activities.

The systematic review findings revealed a general conceptual framework that categorizes the identified determinants of KT into four categories. At the individual level, the factors are related to the sociodemographic characteristics of the researcher (e.g. gender, age, experience), their psychological aspects (e.g. attitude, intrinsic motivation, intention) and personal characteristics (e.g. self-efficacy, communication skills). At the research team level, leadership style and team dynamics. At the organizational level, the findings emphasize university characteristics (e.g. size, structure and ranking), KT culture installed and university resources. At the inter-organizational level, the key determinants were funding sources, network strength and trust.

The studies included in our database were different in terms of contexts, country of the study, the disciplines of KT and the types of KT activities examined. This variety restricts the direct comparison of research findings thus the generalizability of our conclusions. Future research should focus on specific contexts, disciplines, countries or types of KT activities to provide generalizable findings.

A better understanding of all the factors influencing KT among university researchers is essential for several reasons. First, it will enable the government to develop effective policies to promote KT ecosystems. Second, universities can create strategies, policies and programs to support researchers’ engagement in KT activities. Finally, researchers can be more strategic in their KT efforts.

This systematic review contributes to the literature by providing a comprehensive conceptual framework that identifies KT determinants at different levels and fills a gap in the existing literature that only addresses specific aspects of KT determinants. This framework can be a theoretical reference for future empirical studies. Furthermore, it practically provides recommendations for different actors including, government, universities and researchers.

This paper aims to systematically visualize the structure and trends from 2005 to 2021, which will help scholars gain a deeper appreciation for existing studies and grasp future research possibilities and directions.

The approach is bibliometric, using VOSviewer and CiteSpace to analyze 765 journal articles and reviews from the Web of Science (WoS) and Scopus databases over the past 16 years.

There is considerable interest in urban tourism destination image (U-TDI), partly because of the role of image in promoting the economic development of urban tourism and the associated benefits to stakeholders. Most research output concerns China, the USA, Spain and the United Kingdom (UK); research in the USA context has had a particularly wide range of influence. Highly cited journals play a crucial role, while subject structure, key articles and high-frequency keywords indicate popular topics, sub-themes and development trends. Drawing on these findings, the authors identify four topics that deserve further study.

This systematic review will enhance understanding of U-TDI research and inform future research directions as well as highlighting the need to explore destination image in greater depth, it guides policymakers in the tourism industry seeking to develop city image.

The heterogeneous character of Industry 4.0 opens opportunities for studies to understand the difficulties and challenges found in the transformation process of manufacturers. This article aims to present a critical analysis of the modernization process of an Industry 3.0 automated cell into a fully autonomous cell of Industry 4.0. The objective is to elucidate the difficulties found in this transition process and the possible ways to overcome the challenges, focusing on the management perspective.

For this, the needed steps for the technology transition were defined and the main I4.0 enabling technologies were applied, such as the application of machine learning algorithms to control quality parameters in milling.

The main challenges found were related to the obsolescence of the equipment present in the cell, challenges in data integration and communication protocols, in addition to the training of people who work actively in the project team. The difficulties faced were discussed based on similar studies in the literature and possible solutions for each challenge.

This understanding of possible barriers in the modernization process, and the step-by-step defined for this transition, can be important references for professionals working in manufacturing industries and researchers who aim to deepen their studies in this important and disruptive stage of world industrialization.

This study aims to explore how artificial intelligence (AI) can enhance mental health care in Tanzania, focusing on its potential to enhance mental health services and address challenges in a low-resource setting.

A qualitative case study approach was used, with data collected through semi-structured interviews and focus group discussions involving key stakeholders in mental health and AI, including policymakers, technical experts, health-care providers and patient advocacy groups. Thematic analysis was used to identify key themes related to the opportunities and barriers to AI integration in mental health care.

This study identified several benefits of AI in mental health care, including improved diagnostic accuracy, personalised treatment and the potential for real-time monitoring of patients. However, significant barriers to AI adoption remain, such as infrastructure limitations, data privacy concerns and the need for training and resources to effectively integrate AI into mental health services.

This study contributes to the growing literature on AI in health care by focusing on its application in mental health care in Tanzania, a low-resource setting. The research provides valuable insights into how AI can bridge gaps in mental health service delivery, particularly in underserved regions, while highlighting the challenges that must be addressed for successful implementation.

The primary objective of this study is to understand how gamification elements, perceived teacher support and boredom relate to academic performance and how these relationships are mediated by perceived enjoyment while pointing out such influence on educational outcomes.

A quantitative survey methodology was conducted with 350 Lebanese university students specializing in digital marketing. This study used structural equation modeling (SEM) to analyze the data and provide exciting insights into the complex ties between variables.

The results indicate that well-implemented gamification elements significantly increased perceived enjoyment and positively influenced academic performance. Furthermore, perceived teacher support enhanced the effectiveness of gamification by increasing student engagement and enjoyment. Conversely, boredom negatively affects perceived enjoyment and academic performance, underscoring the need for well-designed gamification strategies that sustain interest and motivation.

Structural equation modeling and other quantitative tools excel at discovering connections but may not reveal the origins of the patterns they uncover. Given the complexity of causation, quantitative studies examining the mediating role of subjective satisfaction may gain more insight using a mixed or qualitative approach. Although the data supplied by the 350 responders were interesting, the sample size was insufficient to make any definitive conclusions. These findings may not be generalizable because Lebanon’s student bodies are diverse. The ability to detect tiny changes in the target variables requires researchers to consider how much time and energy they can dedicate to gathering data while structuring their investigations.

This study contributes to understanding gamification as a powerful tool for innovation in education and reshaping learning into motivating, engaging and sustaining productive experiences to improve educational quality. Therefore, our recommendations shed light on such improvements' impact on society. In this vein, we enrich this path by highlighting the crucial role of teachers and decision-makers in developing new professional programs.

This study demonstrates the importance of perceived enjoyment in the transformative gamification process in education. This study emphasizes the value of effective gamification implementation supported by teachers as a powerful tool for enhancing learning experiences and improving the quality of education.

Earned value management systems (EVMS), also called integrated project and program management systems, have been greatly examined in the literature, which has typically focused on their technical aspects rather than social. This study aims to hypothesize that improving both the technical maturity of EVMS and the social environment elements of EVMS applications together will significantly impact project performance outcomes. For the first time, empirical evidence supports a strong relationship between EVMS maturity and environment.

Data was collected from 35 projects through four workshops, attended by 31 industry practitioners with an average of 19 years of EVMS experience. These experts, representing 23 organizations, provided over 2,800 data points on sociotechnical integration and performance outcomes, covering projects totaling $21.8 billion. Statistical analyses were performed to derive findings on the impact of technical maturity and social environment on project success.

The results show statistically significant differences in cost growth, compliance, meeting project objectives and business drivers and customer satisfaction, between projects with high EVMS maturity and environment and projects with poor EVMS maturity and environment. Moreover, the technical and social dimensions were found to be significantly correlated.

Key contributions include a novel and tested performance-driven framework to support integrated project management using EVMS. The adoption of this detailed assessment framework by government and industry is driving a paradigm shift in project management of some of the largest and most complex projects in the U.S.; specifically transitioning from a project assessment based upon a binary approach for EVMS technical maturity (i.e. compliant/noncompliant to standards) to a wide-ranging scale (i.e. 0–1,000) across two dimensions.

This study examines the influence of product market competition on investment inefficiency of Indian firms in context of agency problems. Additionally, this study also investigates whether intense competition is a substitute for or complementary to corporate governance in reducing investment inefficiency of firms.

Utilizing the residuals extracted from Biddle et al. (2009) investment model, investment inefficiency, overinvestment and underinvestment are measured for 506 non-financial Indian listed firms with 6,998 firm-year observations from 2009 to 2022. Product market competition is measured using various proxies such as the Herfindahl–Hirschman index, top-four firm concentration ratio, total number of firms in industry, industry market size, weighted average of entry costs and research and development (R&D) to sales ratio. Firms' internal governance is measured using a newly corporate governance index developed with 65 new governance stipulations. Several pooled ordinary least squares (OLS) panel regressions were estimated involving investment inefficiency of firms, product market competition, governance index and firm-specific variables. Endogeneity issues were addressed through two-stage least squares. Robustness checks were also conducted using a two-step system generalized method of moments (GMM).

The main finding of the study indicates that heightened product market competition reduces investment inefficiency, overinvestment and underinvestment among the selected Indian firms suggesting that firms facing intense competition are less prone to invest below or above optimal levels. This is primarily because in highly competitive industries, managers face greater liquidation risks, prompting more efficient capital investment decisions. The results also indicate that robust corporate governance significantly mitigates investment inefficiencies in non-competitive industries compared to competitive ones suggesting heightened competition reduces managerial slack, resulting in diminished benefits from good governance in competitive settings. Overall results indicate a substitution effect between corporate governance and competition in reducing investment inefficiency, with robustness across various empirical specifications, industry classifications and alternative competition and inefficiency measures.

The evidence from this work emphasizes the pivotal roles of market competitiveness and corporate governance in shaping investment efficiency. Regulators must closely monitor monopolistic behaviors to safeguard stakeholder interests, enhance investment efficiency and foster value creation. Recognizing the positive impact of market competition, firms should prioritize initiatives to promote industrial openness and intensify competition while strengthening market mechanisms. Policymakers should consider implementing competition-centric governance policies, such as deregulation and antitrust laws, to stimulate market competition. These measures can mitigate governance-related costs and promote a competitive marketplace.

This study provides fresh evidence concerning the effects of product market competition on investment efficiency of Indian firms under new governance norms, an unexplored area in India as most of the existing work has primarily examined the association between competition and investment levels. To best of our knowledge, this is one of the earliest studies demonstrating the substitution effects of competitiveness and governance systems on lowering investment inefficiency suggesting a significant influence of corporate governance in non-competitive industries. Finally, this study contributes to the field of methodology by developing a new firm-specific governance index based on 65 governance indicators.

The purpose of this study is to examine the evolving landscape of e-learning, which has become a transformative educational approach accelerated by technological advancements and the global impact of the COVID-19 pandemic. It aims to explore the adoption and impact of e-learning across diverse educational settings, focusing on its effectiveness, quality and potential challenges. Furthermore, this research delves into the often-overlooked role of psychological resources and capabilities, particularly Psychological Capital (PsyCap), in enhancing academic performance among university students engaged in e-learning. By investigating the influence of psychological resources and their intersection with e-learning, this study seeks to contribute to a deeper understanding of the factors that shape successful e-learning experiences and academic achievement.

In this research methodology, data was collected from an e-learning institution, with a focus on students in various computer science semesters to ensure comprehensive representation. To minimize standard method bias, a random sampling technique was employed, and data collection was conducted with the support of locally hired research associates. Participant confidentiality and anonymity were carefully preserved, and ethical approval was obtained. The study began with demographic data collection and an assessment of PsyCap dimensions. Most measurements were self-reported, except for GPA, retrieved from the institute directly. The study initially involved 468 students, but only 213 provided complete responses, resulting in a 46% response rate. Demographic data included age, marital status and gender. The sample featured diverse generational representation, with 58% from Generation Z, 13% Millennials, 22% Generation X and 6% Baby Boomers. This comprehensive data will help analyse generational influences on e-learning outcomes.

The study’s findings underscore the significance of self-efficacy, hope, resilience and optimism in e-learning success. Higher self-efficacy positively impacts student engagement, aligning with previous research. PsyCap, which includes these traits, proves relevant in educational settings. Resilience is notably beneficial, aiding students in overcoming challenges and bolstering their self-belief. Hope enhances problem-solving and adaptability, while optimism fosters a proactive attitude and perseverance, both vital for academic excellence. These insights have broad implications for e-learning practices, emphasizing the need to nurture psychological resources. Incorporating PsyCap-based interventions can enhance the educational experience, promoting student success.

This study has certain limitations that should be considered. It focused exclusively on computer science students, which may limit the generalizability of the findings. Future research should encompass a wider range of academic disciplines for broader applicability. The study was conducted within a specific cultural and regional context, emphasizing a collectivist culture in an Asian setting. To enhance the applicability of the results, it is crucial to explore different regions and cultural contexts. While the study controlled for generational cohort effects on academic performance, further investigation is warranted to understand how different generational cohorts perceive e-learning. Additionally, the study suggests examining how psychological resources influence students' perceptions of e-learning as a stressor or motivator. Furthermore, a comprehensive study comparing the impact of PsyCap on academic performance in both e-learning and traditional education, involving diverse samples and various cultural settings, is needed to provide a more comprehensive understanding.

This research contributes by thoroughly examining the impact of e-learning in diverse educational settings, focusing on its effectiveness, quality and potential challenges. A novel aspect is the exploration of the often-overlooked role of PsyCap in enhancing academic performance among university students engaged in e-learning. This sheds light on the intersection of psychological resources and e-learning. Additionally, the study’s rigorous research methodology underscores its commitment to ethical and responsible research conduct. The research also presents valuable demographic data on generational cohorts and gender, offering insights into how these factors influence e-learning outcomes. These original contributions collectively enhance our understanding of the multifaceted dynamics of e-learning and the pivotal role of psychological resources in academic success.