In Industry 4.0, the business model innovation plays a crucial role in enabling organizations to stay competitive and capitalize on the opportunities presented by digital transformation. Industry 4.0 is driven by digitalization and characterized by integrating various emerging technologies. These technologies can potentially change traditional business models and create new value propositions for customers. This paper aims to analyze and review the research papers through a bibliometric approach scientifically. The data were extracted from reputable Clarivate Web of Science (WoS) Core Collection sources from 2010 to 2023 (June). However, the publication started in 2018 for the research fields. The results show that scientific publications on research domains have increased significantly from 2020. VOSviewer, R Language, and Microsoft Excel were utilized for analysis. Bibliometric and Scientometric approaches conducted to determine and explore the publication patterns with significant keywords, topical trends, and content clustering better discussions of the publication period. The visualization of the data set related to research trends of Industry 4.0 in relation to Business Model Innovation resulted in several co-occurrence clusters namely: 1) Business Model Innovation; 2) Industry 4.0; 3) Digital transformation; and 4) Technology implementation and analysis. The study results would identify worldwide research trends related to the research domains and recommendations for future research areas.

The aim of this study is to determine how bank diversification affects bank stability. To this end, it examines data of 136 commercial banks operating in 14 MENA (Middle East and North Africa) countries observed from 2005 to 2021, using the System Generalized Method of Moments (GMM) panel data regression analysis. The selected countries are Bahrain, Egypt, Jordan, Kuwait, Oman, Qatar, Saudi Arabia, Morocco, Lebanon, Algeria, Tunisia, Iran, Iraq, and the United Arab Emirates. The main results point to the enhancing effect of income diversification on bank stability. Our results underline the “Bright Side” of banking income diversification in the MENA region. However, this stabilizing income diversification effect is not always maintainable. The results also point to a non-linear relationship between interest/non-interest income and financial stability, suggesting that higher diversification reduces risk. We use a dynamic panel threshold model to determine income diversification thresholds that stabilize banks in the MENA region.

This research examines intangible assets or intellectual capital (IC) performance of tourism-related industries in an underexplored area which is a tourism intensively-dependent country. In this study, VAIC which is a monetary valuation method and also the most widely applied measurement method, is utilized as the performance measurement method for quantifying IC performance to monetary values. Moreover, to better understand performance, the standard efficiency levels are further applied for classifying the performance levels of tourism industries. The sample sizes of study are 20 companies operating in the tourism-related industries in the world top travel destination or Thailand, and the companies’ data are collected from 2012 to 2021. Therefore, finally, there are 187 firm-year observations. The utilization of VAIC could assess IC performance of tourism firms and industries, and the standard efficiency levels further support the uniform interpretation of IC efficiency levels. The obtained results show the strong performance of both human and structural capital of the focused tourism dependent country especially in the logistics industry that directly supports and connects to the tourism attractions. Moreover, the finding also highlights the significance of human capital which plays as a major contributor for overall IC performance in this tourism dependent economy. This study contributes the new exploration of IC in the high impact industries and also specifically in the top significant tourism country. Moreover, the application of VAIC also confirms a practical application for management. The limited number of studied countries is a limitation of study. However, these new obtained data and information could be further applied for making comparisons or in-depth or statistical analysis in the future works.

The UN agenda of Sustainable Development Goals (SDGs) 2015–2030 is a holistic approach. Universities play an important role in dissemination of quality knowledge, developing the skills and attitudes of a large number of youth across the world. Though the emphasis on Education for Sustainable Development (ESD) started as early as 1992, yet Universities adopted the concept of Green Campus integrating the environmental, social and economic aspects of sustainability quite recently. In developing countries including Pakistan, the Green Campus Initiatives (GCI) have not been implemented in the majority of the Universities. Northern Pakistan comprising Azad Jammu & Kashmir (AJ&K) and Gilgit Baltistan (GB) faces multiple challenges including Climate Impacts at the top. The fragile ecosystem of the region requires more sustainable initiatives at the University and community levels. In this research, the readiness of the seven universities located in Northern Pakistan have been assessed for GCI on the basis scanning of the websites and questionnaire survey of the relevant stakeholders. The results have shown that there is little commitment of resources for sustainability from senior management, lack of awareness in faculty & staff and less research focus on the related themes of green campus. The co-curricular activities in universities are not linked with sustainability and there are no incentives for faculty, staff and students to this end. It has been recommended that Green Campus Framework may be developed for Pakistani Mountain Universities, with commitment from leaders of the universities and allocation of sufficient resources for development of sustainable campuses. The Higher Education Commission of Pakistan (HEC) needs to allocate special funds for promoting GCI across universities in Pakistan.

In older adults with disabilities, muscle weakness reduces mobility and causes postural issues. Electrical muscle stimulation (EMS) training is effective for increasing strength by inducing involuntary skeletal muscle contractions. Thus, this study aimed to examine changes in lumbar movement, muscle activity during walking, and maximum muscle strength of lower-limb joints based on an 8-week EMS exercise program for older adults with physical disabilities. Sixteen older adults (aged 56–78 years) with physical disabilities were selected and randomly assigned to either the exercise group (EG, n = 8) or the control group (CG, n = 8). EG participants were instructed to wear EMS suits and participate in an elastic band and bare-body exercise program, whereas CG participants performed the exercise program without the EMS suits. Lumbar range of motion (ROM), body circumference, partial volume, maximum muscle strength, and muscle activity were measured. Statistical analysis was performed using SPSS 28.0 for Windows, with the critical value of α = 0.05. Compared to CG participants, EG participants had a superior ROM, body volume, partial volume, maximum muscle strength (knee joints), and muscle activity while walking. These positive outcomes highlight the efficacy of combining EMS with an exercise program for strength and rehabilitation training in older adults with physical disabilities.

The objective of this work was to analyze the effect of the use of ChatGPT in the teaching-learning process of scientific research in engineering. Artificial intelligence (AI) is a topic of great interest in higher education, as it combines hardware, software and programming languages to implement deep learning procedures. We focused on a specific course on scientific research in engineering, in which we measured the competencies, expressed in terms of the indicators, mastery, comprehension and synthesis capacity, in students who decided to use or not ChatGPT for the development and fulfillment of their activities. The data were processed through the statistical T-Student test and box-and-whisker plots were constructed. The results show that students’ reliance on ChatGPT limits their engagement in acquiring knowledge related to scientific research. This research presents evidence indicating that engineering science research students rely on ChatGPT to replace their academic work and consequently, they do not act dynamically in the teaching-learning process, assuming a static role.

This study aims to examine and analyze financial statement fraud from the perspective of the hexagon theory using secondary data. The research sample was selected through purposive sampling, consisting of Ministries and Agencies in Indonesia. The research method employing the OLS (ordinary least squares) approach involves testing the model’s suitability through the F-statistical test, evaluating the coefficient of determination by examining, and conducting hypothesis testing using EViews. The findings of this study suggest that pressure and sscapability do not significantly influence financial reporting fraud. In contrast, opportunity, rationalization, arrogance, and collusion positively and significantly impact financial fraud reports. Implementing a whistleblowing system is crucial for ensuring that e-procurement encompasses all elements of government organizations, serving as a means of transparency and accountability to mitigate the occurrence of fraudulent financial reports within government entities, particularly in Ministries and Agencies in Indonesia. The financial audit opinion is not intended to detect fraud but to assess conformity with government accounting standards, the extent of disclosure, compliance with legislation, and the effectiveness of the government's internal control system. This can encourage institutions in other countries to strengthen the financial security of their organizations.

In recent years, China’s economy has undergone rapid development. Increased disposable income and the rapid expansion of Internet-based financial services have positioned China as the largest market for luxury goods. Gen Z, the youngest demographic within emerging markets, is expected to play a pivotal role as the primary driver of the luxury market. However, while China’s luxury market continues to exhibit a high growth rate, this growth has gradually decelerated in comparison to the previous two years according to researchers. This presents a significant challenge for the luxury industry, as maintaining and enhancing the global growth trend has become a pressing concern where consumer behavior is concerned. The second key issue addressed in this study revolves around the concepts of compulsive buying and brand addiction, which can lead individuals, particularly Gen Z, to develop an addiction to luxury consumption. This study is based on an integrated model of conspicuous consumption, social comparison, and impression management theory. The key variables are materialism, brand consciousness, status-seeking, peer pressure, and collectivism to predict the luxury consumption model with debt attitude introduced as a moderating variable to study consumer behaviour in this age group. A non-probability sampling method and 480 people were selected as research samples. Quantitative analysis was used in this study, and SPSS and Smart PLS were used as data analysis tools. Structural equation model (SEM) using partial least squares method was used to determine the relationship of the variables and the moderating effect of debt attitude. The results showed that brand consciousness, status seeking, debt attitude and materialism had the strongest relationship with luxury consumption. Debt attitude as a moderating factor has a significant impact on the hypothesized relationship of the model. This paper provides empirical evidence for research on Gen Z’s luxury consumption, which has practical implications to marketers, luxury companies, local luxury brands and credit institutions.