Background: The United Nations' sustainability development goals for 2030 and 2050 areincreasingly challenging for companies. Many firms struggle to integrate sustainability into theirbusiness models while balancing economic profit and effective management with environmental andsocial efforts. Modern digital technologies, especially AI, are proving valuable in this area, withnumerous researchers studying their impact on Sustainable Business Models. Despite this,researchers so far focused often on effect of the digital technologies in general or on quantitativeanalyses only on one specific sector or geographical area. For these reasons, a gap in the literaturewas identified in the lack of qualitative research on the impact of AI on companies’ SBMs, morespecifically in terms of value creation and without a focus on one specific market. Purpose: This research aims to explore how Artificial Intelligence technologies can impactcompanies’ Sustainable Business Model on the three different levels of the triple bottom line. Theresearch, more specifically, will only focus on the value creation aspect of the Sustainable BusinessModel. This choice was made to fill a gap identified in the existing literature and to contribute to theexisting knowledge on this important and fast-changing topic. The paper aims to provide valuableinsights to scholars, researchers, companies, and practitioners in general, allowing them for a deeperunderstanding of the link between AI and SBM’s value creation. Method: This research is structured as a qualitative study using grounded theory approach. To obtainthe findings presented in this paper, the authors used a multi-case study approach. The data collectionprocess started with a purposeful sampling that allowed to identify relevant companies for the study.The study data sample consists of six companies from different countries (Belgium, Italy, Sweden)and different sectors (energy, consulting, manufacturing, banking), and of three independentresearchers. In total, 12 semi-structured open-ended interviews were conducted and constituted theempirical data analysed in the research. Conclusion: Seven different categories of AI technologies influencing company’s SBMs weredetected, namely conversational and personal assistance AI, optimization and system managementAI, visual processing AI, data analytics AI, predictive analytics AI, automation and decision AI, andmarket and revenue optimization AI. These different technologies can positively influence the threeaspects of the triple bottom line in different ways. Valuable insights were obtained on how companiesare currently using this technology to reduce their environmental impact, to boost their economicperformance in nowadays’ rapidly evolving market, and to positively impact the employees and thecommunity they operate in.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:hj-64937 |
| Date | January 2024 |
| Creators | Cognigni, Andrea, Gutermann, Mattijs |
| Publisher | Jönköping University, Internationella Handelshögskolan |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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