Modelling and analysis of key enablers of digital transformation in food SMEs using ISM and MICMAC approach
(2023) In International Journal of Intelligent Enterprise 10(4). p.419-444- Abstract
- The food business in India is the backbone of the country, meeting the fundamental human need of food for a large portion of the country's population while also exporting it to other countries. Small and medium-sized enterprises (SMEs) account for the major share of total food production, even though they lack the necessary technological infrastructure and operating standards. Due to COVID-19 crisis, the food sector has been obliged to resolve and upgrade to the new laws tralatitious by the government, which has significantly stimulated the long-awaited digital transformation of food SMEs in India. The purpose of this study is to identify and analyse the major enablers of digital transformation in food SMEs. The interpretive structural... (More)
- The food business in India is the backbone of the country, meeting the fundamental human need of food for a large portion of the country's population while also exporting it to other countries. Small and medium-sized enterprises (SMEs) account for the major share of total food production, even though they lack the necessary technological infrastructure and operating standards. Due to COVID-19 crisis, the food sector has been obliged to resolve and upgrade to the new laws tralatitious by the government, which has significantly stimulated the long-awaited digital transformation of food SMEs in India. The purpose of this study is to identify and analyse the major enablers of digital transformation in food SMEs. The interpretive structural modelling (ISM) methodology has been used to categorise the identified enablers of digital transformation, which further helps in identifying the most proactive enabler and assess the integration of other enablers in the technological paradigm. (Less)
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https://lup.lub.lu.se/record/fe0acbc7-8d72-4de0-aeef-47126647406c
- author
- Chandrayan, Bhavesh ; Gupta, Sumit ; Kumar, Ravinder ; Dangayach, Govind Sharan and Jagtap, Sandeep LU
- publishing date
- 2023
- type
- Contribution to journal
- publication status
- published
- subject
- in
- International Journal of Intelligent Enterprise
- volume
- 10
- issue
- 4
- pages
- 419 - 444
- publisher
- Inderscience Publishers
- external identifiers
-
- scopus:85174262490
- ISSN
- 1745-3232
- DOI
- 10.1504/IJIE.2022.10047970
- language
- English
- LU publication?
- no
- id
- fe0acbc7-8d72-4de0-aeef-47126647406c
- date added to LUP
- 2023-09-17 16:10:01
- date last changed
- 2024-03-21 07:03:09
@article{fe0acbc7-8d72-4de0-aeef-47126647406c, abstract = {{The food business in India is the backbone of the country, meeting the fundamental human need of food for a large portion of the country's population while also exporting it to other countries. Small and medium-sized enterprises (SMEs) account for the major share of total food production, even though they lack the necessary technological infrastructure and operating standards. Due to COVID-19 crisis, the food sector has been obliged to resolve and upgrade to the new laws tralatitious by the government, which has significantly stimulated the long-awaited digital transformation of food SMEs in India. The purpose of this study is to identify and analyse the major enablers of digital transformation in food SMEs. The interpretive structural modelling (ISM) methodology has been used to categorise the identified enablers of digital transformation, which further helps in identifying the most proactive enabler and assess the integration of other enablers in the technological paradigm.}}, author = {{Chandrayan, Bhavesh and Gupta, Sumit and Kumar, Ravinder and Dangayach, Govind Sharan and Jagtap, Sandeep}}, issn = {{1745-3232}}, language = {{eng}}, number = {{4}}, pages = {{419--444}}, publisher = {{Inderscience Publishers}}, series = {{International Journal of Intelligent Enterprise}}, title = {{Modelling and analysis of key enablers of digital transformation in food SMEs using ISM and MICMAC approach}}, url = {{http://dx.doi.org/10.1504/IJIE.2022.10047970}}, doi = {{10.1504/IJIE.2022.10047970}}, volume = {{10}}, year = {{2023}}, }