Abhishek Bhushan Singhal

59011985900

Publications - 4

Perceived Barriers of Gen AI Integration in Entrepreneurship Education: Implications for Information Systems Scholars and Practitioners

Armando Papa Rekha Attri Intesar Almugren Gábor Szábo-Szentgróti Abhishek Bhushan Singhal

Publication Name: Journal of Global Information Management

Publication Date: 2026-01-01

Volume: 34

Issue: 1

Page Range: Unknown

Description:

Generative AI can enhance venture creation education, yet faculty adoption remains limited. This study explores why through a three-stage mixed-methods approach. Stage 1 reviewed 2020–25 literature to identify 23 barriers across pedagogical, technical, institutional, and ethical domains. Stage 2 involved interviews with experienced entrepreneurship educators, refining and reducing the list to 15 context-specific challenges. Stage 3 used a fuzzy-DEMATEL survey to capture expert causal judgments, while thematic coding of interviews added narrative depth. The resulting influence map highlights a clear hierarchy: lack of staff training, unclear governance, and weak technical support are key upstream barriers, while concerns like plagiarism and over-reliance are downstream effects. Cluster analysis groups drivers into pedagogical, organisational, and infrastructural clusters, suggesting a phased response: begin with training and transparent policy, then invest in tools and assessments.

Open Access: Yes

DOI: 10.4018/JGIM.400249

Unpacking Technological Frames in AI-Enabled Hearing Care: A Mixed-Methods Causal Analysis of Adoption Barriers

Reeti Agarwal Manlio Del Giudice Hadeel Alsaleh Attila Kurucz Abhishek Bhushan Singhal

Publication Name: Journal of Global Information Management

Publication Date: 2026-01-01

Volume: 34

Issue: 1

Page Range: Unknown

Description:

Artificial intelligence-enabled diagnostics promise to transform hearing healthcare, yet real-world adoption remains limited. This study identifies and prioritizes barriers to AI integration in clinical audiology through a three-phase mixed-methods approach. Phase I reviewed literature, surfacing 20 obstacles across workflow, infrastructure, culture, and ethics. Phase II involved expert interviews, refining these into nine context-specific barriers. In Phase III, a fuzzy-DEMATEL survey and thematic coding revealed a causal hierarchy: algorithmic inaccuracy, privacy concerns, and lack of training erode clinician trust and widen the knowledge gap. Cost, integration issues, and resource limitations add systemic stress, while ethical concerns emerge downstream. Cluster analysis groups the barriers into three blocs: Clinical Workflow, Governance and Trust, and Tech Infrastructure. This is the first study to apply fuzzy-DEMATEL to AI barriers in audiology, producing a causal map and cluster framework that offer both theoretical insights and practical guidance for adoption strategies.

Open Access: Yes

DOI: 10.4018/JGIM.400760

Generative AI Integration in Entrepreneurship Education: A Mixed-Methods Investigation of Drivers and Acceptance

Armando Papa Rekha Attri Intesar Almugren Gábor Szábo-Szentgróti Abhishek Bhushan Singhal

Publication Name: Journal of Global Information Management

Publication Date: 2026-01-01

Volume: 34

Issue: 1

Page Range: Unknown

Description:

Generative AI holds promise for venture-creation curricula, yet faculty adoption remains hindered by poorly understood incentives and barriers. This study employs a three-stage mixed-methods design to clarify those drivers. A systematic review identified 28 factors, refined by expert panel to 16 key variables. A fuzzy-DEMATEL survey revealed that faculty training, institutional support, and curricular integration exert the strongest causal influence. Clustering these factors yields three intervention domains—pedagogical, organizational, and technological—suggesting a phased adoption strategy. This framework shifts focus from tool access to educator-led implementation, offering academic leaders an evidence-based roadmap for cost-effective AI integration.

Open Access: Yes

DOI: 10.4018/JGIM.402747

Exploring the Adoption of AI Hearing Care: A Mixed Methods Investigation Using DEMATEL and Thematic Analysis

Ankit Mehrotra Manlio Del Giudice Hadeel Alsaleh Attila Kurucz Abhishek Bhushan Singhal

Publication Name: Journal of Global Information Management

Publication Date: 2026-01-01

Volume: 34

Issue: 1

Page Range: 1-33

Description:

This paper explores the key enablers driving clinical adoption of AI-enabled audiology tools. Despite rapid technological maturity, real-world uptake remains uneven. Using a three-phase mixed-methods design, the authors identified and prioritised adoption drivers. Phase I involved a targeted literature scan (1991–2025), yielding 21 candidate factors. Phase II refined these through interviews with audiologists, physicians, engineers, and health-IT managers, distilling 10 core drivers. Phase III applied a decision-making trial and evaluation laboratory survey with 27 clinicians, revealing a causal chain where data accuracy, real-time analytics, and seamless integration enhance workflow efficiency, clinician confidence, and patient personalisation. Robust technical support and structured training further amplify adoption. Cluster analysis grouped drivers into technological, human-capital, and process domains, suggesting distinct tactical interventions. This study provides the first domain-specific causal influence map for AI adoption in hearing healthcare.

Open Access: Yes

DOI: 10.4018/JGIM.405162