Employing digital twin technology in the pursuit to avert sustainable marketing myopia
Anna-Maria Nyquist et al.
What the paper says
Purpose This study investigates the relationship between entrepreneurial marketing and digital twin technology in sustainable marketing, focusing on overcoming sustainable marketing myopia. It aims to determine how combining these approaches can help businesses avoid the pitfalls associated with short-sighted sustainability practices. Design/methodology/approach This research uses an interview methodology focused on the Swedish market to analyse the dynamics of entrepreneurial marketing, characterised by innovation and a strong focus on customer needs. It specifically examines how such marketing strategies serve as a defence against short-sighted or myopic sustainable marketing practices. Findings The study demonstrates that integrating entrepreneurial marketing with digital twin technology can effectively prevent sustainable marketing myopia. This approach helps businesses maintain authentic sustainability claims, comply with data privacy laws and navigate customer-centric models. The findings highlight the advantages of merging entrepreneurial marketing with advanced technologies, promoting sustainable marketing, ensuring long-term industrial success and enhancing transparency and accuracy. Originality/value This research offers unique insights for firms, arguing that merging entrepreneurial marketing with digital twin technology is crucial for enhancing sustainable marketing while sustainable marketing myopia and ensuring long-term success. It underscores the need to balance customer-centric, credible sustainable claims with privacy standards, providing a nuanced approach in the digital era. Additionally, it contributes a range of conceptual and practical propositions to the field.
5 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.41 × 0.4 = 0.16 |
| M · momentum | 0.63 × 0.15 = 0.09 |
| 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.