International Journal of Management Education最新文献

This study presents new evidence on how attending class –particularly synchronous virtual lessons– affects academic performance in higher education. We analyse data from over 500 undergraduate students enrolled in four finance courses at the University of Murcia, a Spanish public university where attendance is non-mandatory. After controlling for the student's previous admission grade, academic experience, and demographic factors, the results show that online class attendance significantly increases the likelihood of taking the exam and improves the success rate as well as the final grades. Moreover, when the analysis distinguishes between attending lectures and practical lessons, there is a similar (positive) effect on student performance.

Key performance indicators (KPIs) are a fundamental tool for understanding the outcomes of business policies. Teaching these indicators is conventionally accomplished through verbal lecturing using mathematical equations, accompanied by presentation graphics and tabular information representing the company's operational, financial, and strategic achievements. The conventional teaching method enables the student to understand what a KPI means and how it is calculated, however, it does not enable the student to understand easily how to interpret it. Here, a hybrid fuzzy-crisp rule-based AI system is presented and its effectiveness when applied with a group of management and organization students at the University of Belgrade, Faculty of Organizational Sciences, during the 2022/2023 academic year is evaluated. The potential of this tool is reflected in its ability to simulate adaptive and realistic business economic situations, its high interactivity and user-friendly interface, and intuitive graphical and tabular results that are easy to interpret enhanced with natural-language-inference-explanations. Univariate analysis along with some complementary statistical tests was used to examine students' satisfaction with the system and to distinguish between students who used the system, and students who attended conventional classes, both in terms of acquiring knowledge and retaining knowledge. In general, the results showed high students' satisfaction with the system. The scores obtained by the former group on the objective knowledge assessment test were on average significantly higher compared to those of the latter, proving the positive effect of the hybrid fuzzy-crisp rule-based AI teaching approach.

This paper aims to provide guidance for the redesign of sport management education post-pandemic, by gathering insights from various stakeholders within the sport ecosystem, using Thailand as a case study. Twenty-four key informants from different sectors of the sport ecosystem were invited for in-depth interviews. The findings, derived from a concurrent analysis of reflexive thematic and narrative elements, identified four subthemes related to the redesign of sport management education post-pandemic. Data from multiple stakeholders revealed that key considerations for reshaping future sport management education include connecting stakeholders, equipping students with essential skills, developing lecturers, and adjusting curriculum components.

This study investigates the role of TikTok, a prominent short-form video platform, in facilitating active learning intention within management education. Employing an extended Technology Acceptance Model (TAM), the research examines how perceived ease of use, usefulness, playfulness, interactivity, immersion, and virtual reward enhance students' active learning intention. Data collected from 414 students majoring in international business across two universities in China reveal that perceived ease of use and usefulness significantly influence interactivity, while virtual rewards impact immersion and playfulness, further influencing students' active learning intention. The study developed a new scale to measure active learning intention in TikTok usage, rigorously validating its reliability and validity through pre-testing and statistical analyses. Furthermore, the research uncovers the moderating role of novelty experience in the relationship between these factors and active learning intention. The findings offer significant implications for integrating emerging technologies like TikTok into management education, highlighting the need for pedagogical strategies that leverage the unique features of social media platforms for creating and sharing short videos to enhance student engagement and learning outcomes. By providing empirical evidence and a discussion of the practical implications, this research contributes to advancing the understanding of digital pedagogies in management education and encourages exploring innovative teaching methods to promote management learning in the digital era.

The advent of the COVID-19 pandemic has brought about unprecedented disruptions in the field of education, necessitating a reevaluation of pedagogical approaches in the post-COVID era. This research paper introduces a novel interval-valued fuzzy simple additive weighting (SAW), weighted product model (WPM), and weighted aggregates sum product assessment (WASPAS) multi-criteria decision-making (MCDM) framework to address the challenge of promoting inclusivity in education amidst the post-COVID era. Leveraging the uncertainty inherent in the post-pandemic educational landscape, the proposed method offers a comprehensive pedagogy selection approach incorporating interval-valued fuzzy sets to account for imprecise and ambiguous data. By integrating the principles of inclusivity and diversity, the method evaluates various pedagogical approaches and their effectiveness in fostering an inclusive learning environment for diverse student populations. The study showcases the application of pedagogy selection in real-world educational scenarios, demonstrating its potential to inform policy decisions and enable educational institutions to adapt and cater to the evolving needs of learners in the aftermath of the COVID-19 pandemic.

Generative AI tools are revolutionizing various sectors, including management education, and assessing their effectiveness is crucial to unlock their full potential. The study explores the perspectives of management educators in utilizing Generative AI tools, as they face a dilemma in balancing technology usage while maintaining relevance and fostering authentic learning. This article utilizes the Social Construction of Technology (SCOT) theory, which emphasizes the influence of human interventions and discourses on Generative AI technology. The study utilized a mixed-methods approach to evaluate the impact of Generative AI on teaching-learning compared to the traditional method. Initially, it analyzed news stories and found the frequently used words like management education, ChatGPT, AI, ethics, B-schools etc. in form of word cloud. Further, sentiment analysis of tweets from the ‘X’ platform was conducted to understand the ongoing discussions. The analysis revealed positive and negative emotions which were associated with specific terms related to management education. Thereafter, the qualitative insights gathered from management education experts helped in identifying various focal themes like assessment, curriculum, pedagogy, and regulation considering early adopters' perspectives. The study shed light on how Generative AI tools can be judiciously embraced through research and application and how they can reshape the management education landscape. It provides evidence-based guidance for educators and researchers to effectively utilize this technology while addressing administrative and ethical issues.

The field of entrepreneurship education (EE) is intricate and necessitates a thorough evaluation incorporating a broad spectrum of research. This study addresses this gap by utilizing big data analytics and machine learning techniques to analyze existing EE research. By dissecting the most prominent publications, journals, and authors in the EE domain, this study presents an up-to-date overview of the current state of research. The investigation focuses on seven key themes in EE research, namely gender and pedagogy, innovation and technology transfer, entrepreneurial intention, entrepreneurial mindset, entrepreneurial learning, entrepreneurial ecosystem and self-efficacy, and the theory of planned behavior. Through a systematic analysis, this paper provides valuable insights and recommendations for future research in EE. These recommendations include investigating the impact of Entrepreneurship Education on students, exploring the role of entrepreneurial intentions in start-up success, assessing the influence of Entrepreneurship Education on entrepreneurial intentions and capabilities, formulating strategies for effective Entrepreneurship Education and entrepreneurial intentions, and examining the factors that influence entrepreneurial intentions in university students. By addressing these research areas, this study aims to propel the field of EE forward and contribute to a more comprehensive understanding of entrepreneurship education.

This study investigates the effects of narcissism on entrepreneurial intentions through entrepreneurial alertness, entrepreneurial passion, and internal locus of control. The data for our research model is collected from a sample of 422 business students from nine universities in Vietnam. The findings from structural equation modelling reveal that the relationship between narcissism and entrepreneurial intentions was fully mediated by both entrepreneurial alertness and entrepreneurial passion. Moreover, internal locus of control is found to moderate the relationships between entrepreneurial alertness and entrepreneurial passion and entrepreneurial intentions. Our study provides important theoretical and practical implications.

This study delves into the factors that kindle entrepreneurial intentions among Indian polytechnic students, shedding light on the pivotal roles of course curriculum, institutional support, family, and peers. Prior research in various fields has often employed the theory of planned behaviour to explore entrepreneurial intentions. However, a noticeable gap exists as no study has investigated this phenomenon among polytechnic students until now. This research uses the theory of planned behaviour to scrutinize entrepreneurial intentions among students in government polytechnic colleges in Malappuram and Calicut districts in India. Analyzing data from 254 valid questionnaires, the study employs the Partial Least Square Structural Equation Modeling method for analysis. The results reveal that peers significantly influence perceived behavioural control, attitude, and subjective norms. These findings resonate with earlier studies and emphasize the critical roles of peers, course curriculum, and institutional support in shaping entrepreneurial intentions. Ultimately, the findings underscore the potential of tailoring polytechnic education towards entrepreneurship, offering technical students opportunities for growth and facilitating positive economic and societal transformations.

With the advent of Artificial Intelligence (AI) and its transformative effects across different sectors, including entrepreneurship, there is a pressing need to understand how AI is integrated into entrepreneurial practices. This study applies the Stimulus-Organism-Response theory to explain the impacts of ChatGPT adoption in entrepreneurship, opportunity recognition, and digital entrepreneurial knowledge on digital entrepreneurial self-efficacy, which in turn, increases digital entrepreneurial intentions and behaviors. Moreover, our study examines the moderating role of technostress in the relationship between digital entrepreneurial self-efficacy, digital entrepreneurial intention, and digital entrepreneurial behaviors. Drawing on the sample of 1326 MBA Vietnamese students who used ChatGPT for their entrepreneurial activities, with the stratified random sampling approach, structural equation modeling is employed to test formulated hypotheses. This study reveals that ChatGPT adoption in entrepreneurship positively influences opportunity recognition, digital entrepreneurial knowledge, and digital entrepreneurial self-efficacy. Digital entrepreneurial self-efficacy was also found to significantly mediate the impacts of AI-related stimuli on digital entrepreneurial intention and behavior. Furthermore, technostress negatively moderates the relationship between digital entrepreneurial self-efficacy and intention. The findings of this research thus extend the theoretical understanding of AI-driven entrepreneurship and offer practical implications for practitioners.