Purpose： In order to explain and predict the adoption of personal cloud storage, this study explores the critical factors involved in the adoption of personal cloud storage and empirically validates their relationshi...Purpose： In order to explain and predict the adoption of personal cloud storage, this study explores the critical factors involved in the adoption of personal cloud storage and empirically validates their relationships to a user＇s intentions.Design/methodology/approach： Based on technology acceptance model（TAM）, network externality, trust, and an interview survey, this study proposes a personal cloud storage adoption model. We conducted an empirical analysis by structural equation modeling based on survey data obtained with a questionnaire.Findings： Among the adoption factors we identified, network externality has the salient influence on a user＇s adoption intention, followed by perceived usefulness, individual innovation, perceived trust, perceived ease of use, and subjective norms. Cloud storage characteristics are the most important indirect factors, followed by awareness to personal cloud storage and perceived risk. However, although perceived risk is regarded as an important factor by other cloud computing researchers, we found that it has no significant influence. Also, subjective norms have no significant influence on perceived usefulness. This indicates that users are rational when they choose whether to adopt personal cloud storage.Research limitations： This study ignores time and cost factors that might affect a user＇s intention to adopt personal cloud storage.Practical implications： Our findings might be helpful in designing and developing personal cloud storage products, and helpful to regulators crafting policies.Originality/value： This study is one of the first research efforts that discuss Chinese users＇ personal cloud storage adoption, which should help to further the understanding of personal cloud adoption behavior among Chinese users.展开更多
The recent increase in the use of artificial intelligence has led to fundamental changes in the development of training and teaching methods for executive education. However, the success of artificial intelligence in ...The recent increase in the use of artificial intelligence has led to fundamental changes in the development of training and teaching methods for executive education. However, the success of artificial intelligence in regional centers for teaching and training professions will depend on the acceptance of this technology by young executive trainees. This article discusses the potential benefits of adopting AI in executive training institutions in Morocco, specifically focusing on CRMEF Casablanca Settat. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003), this study proposes a model to identify the factors influencing the acceptance of artificial intelligence in regional centers for teaching professions and training in Morocco. To achieve this, a structural equation modeling approach was used to quantitatively describe the impact of each factor on AI adoption, utilizing data collected from 173 young executive trainees. The results indicate that perceived ease of use, perceived usefulness, trainer influence, and personal innovativeness influence the intention to use artificial intelligence. Our research provides managers of CRMEFs with a set of practical recommendations to enhance the implementation conditions of an artificial intelligence system. It aims to understand which factors should be considered in designing an artificial intelligence system within regional centers for teaching professions and training (CRMEFs).展开更多
基金supported by Social Science Fund of Hebei Province (Grant No.:HB15TQ019)
文摘Purpose： In order to explain and predict the adoption of personal cloud storage, this study explores the critical factors involved in the adoption of personal cloud storage and empirically validates their relationships to a user＇s intentions.Design/methodology/approach： Based on technology acceptance model（TAM）, network externality, trust, and an interview survey, this study proposes a personal cloud storage adoption model. We conducted an empirical analysis by structural equation modeling based on survey data obtained with a questionnaire.Findings： Among the adoption factors we identified, network externality has the salient influence on a user＇s adoption intention, followed by perceived usefulness, individual innovation, perceived trust, perceived ease of use, and subjective norms. Cloud storage characteristics are the most important indirect factors, followed by awareness to personal cloud storage and perceived risk. However, although perceived risk is regarded as an important factor by other cloud computing researchers, we found that it has no significant influence. Also, subjective norms have no significant influence on perceived usefulness. This indicates that users are rational when they choose whether to adopt personal cloud storage.Research limitations： This study ignores time and cost factors that might affect a user＇s intention to adopt personal cloud storage.Practical implications： Our findings might be helpful in designing and developing personal cloud storage products, and helpful to regulators crafting policies.Originality/value： This study is one of the first research efforts that discuss Chinese users＇ personal cloud storage adoption, which should help to further the understanding of personal cloud adoption behavior among Chinese users.
文摘The recent increase in the use of artificial intelligence has led to fundamental changes in the development of training and teaching methods for executive education. However, the success of artificial intelligence in regional centers for teaching and training professions will depend on the acceptance of this technology by young executive trainees. This article discusses the potential benefits of adopting AI in executive training institutions in Morocco, specifically focusing on CRMEF Casablanca Settat. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003), this study proposes a model to identify the factors influencing the acceptance of artificial intelligence in regional centers for teaching professions and training in Morocco. To achieve this, a structural equation modeling approach was used to quantitatively describe the impact of each factor on AI adoption, utilizing data collected from 173 young executive trainees. The results indicate that perceived ease of use, perceived usefulness, trainer influence, and personal innovativeness influence the intention to use artificial intelligence. Our research provides managers of CRMEFs with a set of practical recommendations to enhance the implementation conditions of an artificial intelligence system. It aims to understand which factors should be considered in designing an artificial intelligence system within regional centers for teaching professions and training (CRMEFs).
