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1 – 2 of 2Lina Dagilienė, Viktorija Varaniūtė and Judith Maja Pütter
Taking into account retailers' critical position in the value chain, their sector's economic significance and environmental externalities, in addition to the institutional agenda…
Abstract
Purpose
Taking into account retailers' critical position in the value chain, their sector's economic significance and environmental externalities, in addition to the institutional agenda, this paper aims to explore the drivers influencing retailers to shift to more sustainable business models.
Design/methodology/approach
The paper utilises the institutional competing logic, including in-depth interviews with major supermarket retail chains and one expert group discussion. The data gathered in Germany and Lithuania were complemented by desk research analysis, including corporate social responsibility (CSR) reports and management reports.
Findings
The paper provides empirical insights into how multiple drivers through institutional competing logic are brought about influencing the shift to more sustainable business models. The results show that retail chains in both countries implement their sustainability based on triple environmental-legal-financial drivers. However, different types of retail chains–namely premium retailers, typical retailers and discounters–implement their sustainability discourse differently.
Research limitations/implications
Because of the chosen research approach, the results may lack generalisability. Therefore, researchers are encouraged to test the proposed propositions further.
Social implications
Interestingly, retailers “shift” their responsibility to the consumers rather than encourage themselves to make more sustainable choices. The authors observe a more passive and responsive role of retailing chains because of the inherent trade-off between revenue growth and sustainable consumption.
Originality/value
The original contribution lies in exploring how retail chains adapt institutional competing logic and are influenced by multiple drivers when implementing their sustainability activities. In addition, the authors propose a conceptual model for retailers' sustainability management, as well as formulate three research propositions.
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Keywords
Darius-Aurel Frank, Lina Fogt Jacobsen, Helle Alsted Søndergaard and Tobias Otterbring
Companies utilize increasingly capable Artificial Intelligence (AI) technologies to deliver modern services across a range of consumer service industries. AI autonomy, however…
Abstract
Purpose
Companies utilize increasingly capable Artificial Intelligence (AI) technologies to deliver modern services across a range of consumer service industries. AI autonomy, however, sparks skepticism among consumers leading to a decrease in their willingness to adopt AI services. This raises the question as to whether consumer trust in companies can overcome consumer reluctance in their decisions to adopt high (vs low) autonomy AI services.
Design/methodology/approach
Using a representative survey (N = 503 consumers corresponding to N = 3,690 observations), this article investigated the link between consumer trust in a company and consumers' intentions to adopt high (vs low) autonomy AI services from the company across 23 consumer service companies accounting for six distinct service industries.
Findings
The results confirm a significant and positive relationship between consumer trust in a company and consumers' intentions to adopt AI services from the same company. AI autonomy, however, moderates this relationship, such that high (vs low) AI autonomy weakens the positive link between trust in a company and AI service adoption. This finding replicates across all 23 companies and the associated six industries and is robust to the inclusion of several theoretically important control variables.
Originality/value
The current research contributes to the recent stream of AI research by drawing attention to the interplay between trust in companies and adoption of high autonomy AI services, with implications for the successful deployment and marketing of AI services.
Details