DOES THE AUGMENTATION OF SERVICE LEVEL AGREEMENTS AFFECT USER DECISIONS IN CLOUD ADOPTION SCENARIOS? – AN EXPERIMENTAL APPROACH

Despite the benefits of cloud computing, customers are reluctant to use cloud services as they have concerns about data security and privacy. Many of these concerns arise due to the lack of transparen-cy. Consequently, bridging the existing information asymmetry and, thus, fostering trust in the cloud provider is of high relevance. As service level agreements are an important trust building factor and due to their technical and complex nature, the augmentation of these is promising. Therefore, we in-vestigate the effects of augmenting service level agreements (by means of augmented browsing) on the ease of the information gathering process and simultaneously on perceived information overload, comprehension and transparency in a web-based experiment. The results of our online experiment do not confirm our assumed positive effects of augmentation. Nonetheless, we show that the ease of gath-ering information about a cloud service positively influences the perceived trustworthiness. Further-more, we demonstrate that the perceived trustworthiness of a cloud computing provider largely deter-mines the intention to use its services. Thus, besides improving security, cloud providers not only have to communicate trust-critical information but also have to identify suitable measures of information provisioning that considerably improve transparency while lowering information overload

AI-based Conversational Agents for Customer Service – A Study of Customer Service Representative’ Perceptions Using TAM 2

This study aimed to identify the various factors that may influence customer service representatives’ perceptions of artificial intelligence (AI)-based conversational agents (CAs) for customer service. By analyzing 180 publications, a conceptual research model is developed for identifying the factors that may influence customer service representatives’ perceptions of AI-based CAs for customer service. The underlying conceptual research model comprises ten factors. The study is grounded in the application of the Technology Acceptance Model 2 (TAM 2) approach. The research model is empirically evaluated with survey data from 128 participants. Our results show that the direct positive effect of subjective norm on customer service representatives’ perception of using AIbased CAs in customer service decreases with increasing experience. Moreover, our results reveal new insights regarding trust. The results of this study provide an overview of the predominant characteristics of the influencing factors of customer service representatives’ perceptions of AI-based CAs for customer service