Strategising Industry 4.0 for Viksit Bharat 2047: an inclusive approach to public policy design with applications in tourism
Mayank Pathak & Pinosh Kumar Hajoary
What the paper says
Purpose This study aims to examine the state and structure of India’s I4.0 (Industry 4.0) policy, as well as its actors, actions and processes through an inclusive value-first approach at the national and regional levels. Design/methodology/approach The study adopted a systematic literature search and utilised a generalised situation-actor-process-learning-action-performance (SAP-LAP) inquiry method with the Influencer-Facilitator-Initiative (IFI) framework to identify facilitators for a value-first I4.0 policy for India. The state of Himachal Pradesh (HP) in India was taken as a regional context to demonstrate the potential of I4.0 technologies in tourism. Findings The study identified 22 facilitators for value-first I4.0 policy and provides national (India) and regional (HP) level policy recommendations, highlighting implications and pathways for Viksit Bharat 4.0. Research limitations/implications More empirical research is needed to understand the I4.0 policy landscape in developing countries across various industrial sectors to meaningfully inform policy recommendations. Practical implications Findings guide policymakers, managers and officials to understand the I4.0 landscape and develop policies for Viksit Bharat 4.0 at the national and regional levels. Social implications The value-first approach adopted by the study promotes inclusive development and improves policy intention without compromising on delivery. Originality/value This study uses SAP-LAP inquiry with the IFI framework for a strategic overview of India’s I4.0 policy landscape. It adds to I4.0 literature in geographical (HP) and application (tourism) contexts.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.