Ambivalence and Coping Responses in Post-Adoptive Information Systems Use

Satisfaction to Stay, Regret to Switch: Understanding Post-adoption Regret in Choosing Competing Technologies When Herding

Facing hundreds of similar alternatives in any technology adoption decision, users commonly take a shortcut in the decision making: following others in the herd! Although herding is found to be an influential force for technology adoption, this research sheds light on its distal on user staying power in post-adoption evaluations. Supplementing the dominant perspective that users will stay with the chosen technology when satisfactory with the technology performance, this research proposes a new regret perspective to account for users’ concerns about the competing technologies and the decision process in the technology adoption decision. A research model is accordingly constructed and tested in two longitudinal field studies on user adoption and post-adoption evaluations across competing technologies in both forms of free software and paid hardware, with samples collected in Asia and Europe. Based on the findings and insights, this research suggests to IT vendors on how to retain users in the new era with competing technologies by understanding how post-adoption regret, the predominant factor of user switching, is formed and how it can be lessened.

Hope, tolerance and empathy: employees' emotions when using an AI-enabled chatbot in a digitalised workplace

Purpose

Information Systems research on emotions in relation to using technology largely holds essentialist assumptions about emotions, focuses on negative emotions and treats technology as a token or as a black box, which hinders an in-depth understanding of distinctions in the emotional experience of using artificial intelligence (AI) technology in context. This research focuses on understanding employees' emotional experiences of using an AI chatbot as a specific type of AI system that learns from how it is used and is conversational, displaying a social presence to users. The research questions how and why employees experience emotions when using an AI chatbot, and how these emotions impact its use.

Design/methodology/approach

An interpretive case study approach and an inductive analysis were adopted for this study. Data were collected through interviews, documents review and observation of use.

Findings

The study found that employee appraisals of chatbots were influenced by the form and functional design of the AI chatbot technology and its organisational and social context, resulting in a wider repertoire of appraisals and multiple emotions. In addition to positive and negative emotions, users experienced connection emotions. The findings show that the existence of multiple emotions can encourage continued use of an AI chatbot.

Originality/value

This research extends information systems literature on emotions by focusing on the lived experiences of employees in their actual use of an AI chatbot, while considering its characteristics and its organisational and social context. The findings inform the emerging literature on AI.

Conflicting social influences regarding controversial information systems: the case of online dating

Purpose

Controversial information systems (IS) represent a unique context in which certain members of a user's social circle may endorse the use of a system while others object to it. The purpose of this paper is to explore the simultaneous and often conflicting roles of such positive and negative social influences through social learning and ambivalence theories in shaping user adoption intention of a representative case of controversial IS, namely online dating services (ODS).

Design/methodology/approach

The model was tested with two empirical studies using structural equation modeling techniques. The data of these studies were collected from 451 (Study 1) and 510 (Study 2) single individuals (i.e. not in a relationship).

Findings

(1) Positive social influence has a stronger impact on perceived benefits and adoption intention, while negative social influence exerts a greater impact on perceived risks; (2) positive and negative social influences affect adoption intention toward ODS differently, through benefit and risk assessments; and (3) ambivalence significantly negatively moderates the effects of social influences on adoption.

Originality/value

This study enriches and extends the IS use, ambivalence theory, prospect theory, and social learning theory research streams. Furthermore, this study suggests that it is necessary to focus on not only the oft-considered positive but also negative social influences in IS research.