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1 – 2 of 2Li Chen, Dirk Ifenthaler, Jane Yin-Kim Yau and Wenting Sun
The study aims to identify the status quo of artificial intelligence in entrepreneurship education with a view to identifying potential research gaps, especially in the adoption…
Abstract
Purpose
The study aims to identify the status quo of artificial intelligence in entrepreneurship education with a view to identifying potential research gaps, especially in the adoption of certain intelligent technologies and pedagogical designs applied in this domain.
Design/methodology/approach
A scoping review was conducted using six inclusive and exclusive criteria agreed upon by the author team. The collected studies, which focused on the adoption of AI in entrepreneurship education, were analysed by the team with regards to various aspects including the definition of intelligent technology, research question, educational purpose, research method, sample size, research quality and publication. The results of this analysis were presented in tables and figures.
Findings
Educators introduced big data and algorithms of machine learning in entrepreneurship education. Big data analytics use multimodal data to improve the effectiveness of entrepreneurship education and spot entrepreneurial opportunities. Entrepreneurial analytics analysis entrepreneurial projects with low costs and high effectiveness. Machine learning releases educators’ burdens and improves the accuracy of the assessment. However, AI in entrepreneurship education needs more sophisticated pedagogical designs in diagnosis, prediction, intervention, prevention and recommendation, combined with specific entrepreneurial learning content and entrepreneurial procedure, obeying entrepreneurial pedagogy.
Originality/value
This study holds significant implications as it can shift the focus of entrepreneurs and educators towards the educational potential of artificial intelligence, prompting them to consider the ways in which it can be used effectively. By providing valuable insights, the study can stimulate further research and exploration, potentially opening up new avenues for the application of artificial intelligence in entrepreneurship education.
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Quratulain Burhan and Muhammad Faisal Malik
The purpose of this study is to introduce the concept of workplace camaraderie and to investigate the mechanism through which workplace camaraderie influences incivility at the…
Abstract
Purpose
The purpose of this study is to introduce the concept of workplace camaraderie and to investigate the mechanism through which workplace camaraderie influences incivility at the workplace. The study is explained by taking the sequential mediation of personal biases leading to cronyism and favoritism. Social identity theory is used as the underpinning theory to explain the framework adopted.
Design/methodology/approach
Positivism research philosophy followed by the deductive approach is followed to meet the objectives of the current study. In total, 171 employees working in public sector organizations were taken as the respondents to the study. A purposive sampling technique was used to collect the data through self-administrated questionnaires. Path model is used through Mplus to generate the results and test hypotheses.
Findings
The results suggested that workplace camaraderie significantly affects incivility at a workplace with the sequential mediation of personal biases leading to cronyism and favoritism.
Originality/value
Although several researchers have studied the link between camaraderie and other employees’ related attitudinal and behavioral outcomes, few have explored the roles of personal biases, cronyism and favoritism in the relationship to incivility. This study thus posits a novel sequential mediation mechanism, based on the social identity theory, through which camaraderie is translated into civil behavior. Moreover, this study adds value by investigating this model in the public sector, where camaraderie can come up with important consequences.
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