Surabhi Verma, Vibhav Singh, Ana Alina Tudoran and Som Sekhar Bhattacharyya
In this study, we investigated the positive and negative effects of stress that is driven by responsible artificial intelligence (RAI) principles on employee job outcomes by…
Abstract
Purpose
In this study, we investigated the positive and negative effects of stress that is driven by responsible artificial intelligence (RAI) principles on employee job outcomes by adapting the challenge–hindrance stressors model.
Design/methodology/approach
The study design involved empirically validating the proposed model on 299 respondents who use AI for work-related tasks.
Findings
The results revealed several RAI-driven challenge and hindrance stressors related to employees’ positive and negative psychological responses and task performance in a digital workplace. Practitioners could use the RAI characteristics to improve employees’ RAI-driven task performance.
Research limitations/implications
This study contributes to the ongoing discussion on technostress and awareness in the context of RAI in the AI literature. By extending the C-HS model to the RAI context, it complements the context-specific technostress literature by conceptualizing different characteristics of RAI as RAI-driven stressors.
Originality/value
Adoption and use of technologies like RAI are not automatically translated into expected job outcomes. Instead, practitioners and academicians also need to know whether the RAI characteristics actually help employees show positive or negative behavior. Furthermore, relying on the challenge–hindrance stressor (C-HS) model, we try to reveal the beneficial and detrimental effects of different RAI characteristics on employees’ job outcomes.
Details
Keywords
Self-Service Technology (SST) is a disruptive technology that has reshaped customer interactions, increased efficiency, and enabled data-driven decision-making. Its impact…
Abstract
Self-Service Technology (SST) is a disruptive technology that has reshaped customer interactions, increased efficiency, and enabled data-driven decision-making. Its impact continues to evolve as technology advances and customer expectations change, making it a key consideration for businesses in a dynamic landscape. This chapter delves into critical findings regarding the adoption and implications of SST in tourism and hospitality. The relevant studies are sourced from the Scopus database. A mixed literature review methodology was employed to review papers. The literature review findings show facets of SST adoption, shedding light on the intricate relationships between consumer readiness variables, context-specific influences, preferred SST features, and psychological attributes. The study reveals consumer preferences, including convenience, ease of use, and speed of service, as primary drivers of the adoption of SST. The bibliometric analysis reveals the scope for developing SST literature in tourism and hospitality. Collaborations among scholars, research and funding institutions could help provide the impetus. Research in SST security, sustainability, and resilience could help enhance the SST literature. Comparative studies evaluating SST's social and economic implications are also suggested.