Towards adoption of Green IS: A literature review using classification methodology

Expectation management in AI: A framework for understanding stakeholder trust and acceptance of artificial intelligence systems

As artificial intelligence systems gain traction, their trustworthiness becomes paramount to harness their benefits and mitigate risks. This study underscores the pressing need for an expectation management framework to align stakeholder anticipations before any system-related activities, such as data collection, modeling, or implementation. To this end, we introduce a comprehensive framework tailored to capture end-user expectations specifically for trustworthy artificial intelligence systems. To ensure its relevance and robustness, we validated the framework via semi-structured interviews, encompassing questions rooted in the framework's constructs and principles. These interviews engaged fourteen diverse end users across the healthcare and education sectors, including physicians, teachers, and students. Through a meticulous qualitative analysis of the interview transcripts, we unearthed pivotal themes and discerned varying perspectives among the interviewee groups. Ultimately, our framework stands as a pivotal tool, paving the way for in-depth discussions about user expectations, illuminating the significance of various system attributes, and spotlighting potential challenges that might jeopardize the system's efficacy.

Adoption of green IT in Pakistan: a comparison of three competing models through model selection criteria using PLS-SEM

The growing adverse impact of IT products in developing countries like Pakistan is increasing, seeking academicians' and practitioners' attention to adopt green IT products in Pakistan. In this regard, several researchers provided different independent theoretical models for adopting green IT, but which model fits best in the scenario is still vague. Therefore, this study used three well-developed competing models: the technology acceptance model, the unified theory of acceptance and use of technology, and the decomposed theory of planned behavior to investigate green IT adoption in Pakistan. For this purpose, data were collected through a survey method using a purposive sampling technique, and partial least squares structural equation modeling (PLS-SEM) was used to analyze three competing models. Using the PLS model selection criteria along with standard model selection criteria, the results suggested that the decomposed theory of planned behavior (DTPB) is the most parsimonious and has the best explanatory and predictive power than other available alternative theoretical models. Moreover, the study identified different significant factors affecting consumers' intention to adopt green IT products in Pakistan. The theoretical and practical implication of this study is discussed. In the final section, limitations and future directions are elaborated.