| Title | Using bibliometric analysis to map innovative business models for vertical farm entrepreneurs |
|---|---|
| ID_Doc | 43878 |
| Authors | Biancone, PP; Brescia, V; Lanzalonga, F; Alam, GM |
| Title | Using bibliometric analysis to map innovative business models for vertical farm entrepreneurs |
| Year | 2022 |
| Published | British Food Journal, 124, 7 |
| Abstract | Purpose This paper aims to explore the literature on vertical farming to define key elements to outline a business model for entrepreneurs. The research aims to stimulate entrepreneurship for vertical farming in a smart cities' context, recognising urban agriculture as technology to satisfy increasing food needs. Design/methodology/approach The research conducts a structured literature review on 186 articles on vertical farming extracted from the Scopus. Moreover, the bibliometric analysis revealed the descriptive statistics on this field and the main themes through the authors' keywords. Findings Different perspectives showed the multidisciplinary nature of the topic and how the intersection of different skills is necessary to understand the subject entirely. The keywords analysis allowed for identifying the topics covered by the authors and the business model's elements. Research limitations/implications The research explores a topic in the embryonic stage to define key strands of literature. It provides business model insights extending George and Bock's (2011) research to stimulate entrepreneurship in vertical farming. Limitations arise from the sources used to develop our analysis and how the topic appears as a frontier innovation. Originality/value Originality is the integration of literature strands related to vertical farming, highlighting its multidisciplinary nature to provide a holistic understanding of the themes. In smart cities' context, innovations allow traditional business models to be interpreted in a novel perspective and revealed the elements for transforming vertical farming from innovative technology to an effective source of food sustenance. Finally, the paper suggests a new methodology application for the analysis of word clusters by integrating correspondence analysis and multidimensional scaling analysis. |
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