Abstract
Social businesses, despite having a huge potential to generate substantial and sustainable value, are often structurally and financially fragile. Technological interventions, such as social media analytics, big data, Internet of Things, and blockchain can help social businesses by leveraging the practices towards financial and operational sustainability. This study is the first of its kind in that it analyses existing scholarly works on social businesses using bibliometric analysis. In so doing, this paper presents an in-depth statistical analysis of the literature on technological interventions in sustainable social business, showcasing the development of the scholarship, major themes, and possible future research trajectories. The SCOPUS database is used to identify a large section of articles. The study shows that most of the work in social business has been done by scholars based in developed countries, with limited contributions emanating from developing countries. The study proposes a framework for the use of technology in sustainable social businesses with focus areas of research such as social innovation, digital technology, information systems, and decision making for sustainability. The results show that digital technologies are increasingly being accepted as tools for the sustainability and scalability of social businesses. The paper offers useful recommendations for future research in relevant fields.
| Original language | English |
|---|---|
| Article number | 120818 |
| Pages (from-to) | 1-15 |
| Number of pages | 15 |
| Journal | Technological Forecasting and Social Change |
| Volume | 169 |
| Early online date | 30 Apr 2021 |
| DOIs | |
| Publication status | Published - 1 Aug 2021 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
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SDG 17 Partnerships for the Goals
Keywords
- technological intervention
- sustainable social business
- industry 4.0
- big data
- sustainability
- bibliometric analysis
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