Adoption of AI-Enabled Tools in Social Development Organizations in India
An Extension of UTAUT Model
Bibliographic Data
| ID | 5849075 |
|---|---|
| Authors | Ruchika Jain (0000-0002-5619-9122, Delhi Technological University), Nitika Garg (0000-0001-6694-9663, Delhi Technological University, corresponding author), Naval Garg, Shikha N Khera (Delhi Technological University) |
| Year | 2022 |
| Volume | 13 |
| Publication date | 2022-06-20 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Psychology (JOURNAL) |
| Journal identifiers | ISSN: 1664-1078 • E-ISSN: 1664-1078 |
| Publisher | Frontiers Media (PUBLISHER • CH) |
| DOI | 10.3389/fpsyg.2022.893691 |
| PMID | 35795409 |
| OpenAlex | W4283208487 |
| Language | EN |
| Citations received | 12 |
| References cited | 155 |
Social development organizations increasingly employ artificial intelligence (AI)-enabled tools to help team members collaborate effectively and efficiently. These tools are used in various team management tasks and activities. Based on the unified theory of acceptance and use of technology (UTAUT), this study explores various factors influencing employees' use of AI-enabled tools. The study extends the model in two ways: a) by evaluating the impact of these tools on the employees' collaboration and b) by exploring the moderating role of AI aversion. Data were collected through an online survey of employees working with AI-enabled tools. The analysis of the research model was conducted using partial least squares (PLS), with a two-step model - measurement and structural models of assessment. The results revealed that the antecedent variables, such as effort expectancy, performance expectancy, social influence, and facilitating conditions, are positively associated with using AI-enabled tools, which have a positive relationship with collaboration. It also concluded a significant effect of AI aversion in the relationship between performance expectancy and use of technology. These findings imply that organizations should focus on building an environment to adopt AI-enabled tools while also addressing employees' concerns about AI
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| Unique citing works | 12 |
|---|---|
| Citations per year | 6 |
| Citation span | 2024 - 2026 (3) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 12 |