Research On The Effect Of Recommender Systems On Business Ethics Education

The development of Artificial Intelligence has brought new opportunities and challenges to business ethics education.The Principles for Responsible Management Education(PRME)clearly proposes to create innovated educational approaches for responsible management.The Association to Advance Collegiate Schools of Business(AACSB)requires curriculum content to cultivate agility with current and emerging technologies.Top universities such as Harvard University,University of California,and Massachusetts Institute of Technology try to apply recommender systems to business ethics education.Many platforms also provide online business ethics courses for university certification.As recommender systems are increasingly applied in business ethics education,research on the impact of recommender systems on business ethics education has become very important.However,there is still a lack of empirical research on whether the application of recommender systems to business ethics education can produce a positive effect.This article empirically studies whether using recommender algorithms to construct education content is really conducive to the cultivation of business ethics.The elaboration likelihood model is utilized to understand how information provided by recommender systems impacts corporate social responsibility(CSR)attitude and intention,and the effects of recommender systems with different principles.We designed a CSR case recommender system and implemented a randomized field experiment based on a real case-based teaching course.We found that recommender systems facilitate students’ positive CSR attitude change and CSR intention depending on the different information-processing routes(peripheral or central)and system expectation confirmation moderates these influences.Meanwhile,experts-supervised algorithm has a more significant impact on CSR attitude change than interest-supervised algorithm and unsupervised algorithm.Our study contributes to CSR education field on how to design the advanced teaching tools and optimize the teaching process.