How Technology is Changing Retail

Shankar, Venkatesh; Kalyanam, Kirthi; Setia, Pankaj; Golmohammadi, Alireza; Tirunillai, Seshadri; Douglass, Tom; Hennessey, John; Bull, Jonathan; Waddoups, Rand

doi:10.1016/j.jretai.2020.10.006

Cited by 268 publications

(145 citation statements)

References 43 publications

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“…In particular, AR allows "customers to see how a particular product looks in a simulated real-life environment" (Gauri et al, 2021, p. 12). This type of customer-facing technology is changing retailing (Shankar et al, 2021). The growth of mobile device-based AR is fostering new ways of retailing (Caboni and Hagberg, 2019).…”

Section: Theoretical Framework and Hypotheses Developmentmentioning

confidence: 99%

“…The TAM and its extensions have been used to study the acceptance of AR apps (Pantano et al, 2017;Perannagari and Chakrabarti, 2020;Shankar et al, 2021) through the analysis of its core constructs, ease of use, usefulness and attitude (Davis, 1989), and by adding ARrelated features as antecedents. We adopt this extended view, that is, we place the TAM at the core of the model and add selected antecedents from the AR literature.…”

Section: Theoretical Framework and Hypotheses Developmentmentioning

confidence: 99%

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A model of adoption of AR-based self-service technologies: a two country comparison

Bigné

2021

IJRDM

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PurposeThis paper proposes a model that extends the technology acceptance model (TAM) by identifying factors that influence consumers' acceptance of augmented reality (AR) self-service technologies (AR-based SSTs) in the retail sector, resulting in the Augmented Reality in Retail Model (ARiR Model).Design/methodology/approachThis study is based on an online questionnaire responded to by 284 makeup-using women from Nicaragua and the USA. It is based on an AR mobile app used to shop in retail stores. Partial least squares-structural equation modelling was used to validate the ARiR model and test the hypotheses.FindingsAesthetics and navigation are significant predictors of perceived usefulness and perceived ease of use (PEOU), and self-efficacy also explains perceived ease of use. Technology readiness and the need for personal interaction were not found to be influencing factors. A cross-cultural comparison indicated that both countries have similar overall attitudes towards AR-based SSTs.Research limitations/implicationsThis paper provides insights into the perceived value of, and motives for customer acceptance of, AR-based SSTs, which can serve as guidelines for their future implementation. Furthermore, it validates and confirms the application of the proposed ARiR model for technology acceptance in both developed and developing countries.Practical implicationsThe paper provides new insights for retailers on the implementation of AR at the point of sale.Originality/valueThe model extends the original TAM to AR and introduces five new constructs: need for personal interaction, aesthetics, navigation, self-efficacy and technology readiness. It was tested in both a developing and a developed country.

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Section: Theoretical Framework and Hypotheses Developmentmentioning

confidence: 99%

Section: Theoretical Framework and Hypotheses Developmentmentioning

confidence: 99%

A model of adoption of AR-based self-service technologies: a two country comparison

Bigné

2021

IJRDM

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“…This study contributes to the literature on in-store technologies and retail innovation. First, it offers new insights on the extent of retail change related to in-store technologies (Brown, 1987; Etgar, 1984; Shankar et al , 2020). Second, it extends our understanding of innovation management by focussing on the fashion retailers' perspective (Hristov and Reynolds, 2015; Pinto et al , 2017).…”

Section: Introductionmentioning

confidence: 99%

Tracking technology diffusion in-store: a fashion retail perspective

Alexander

Kent

2021

IJRDM

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PurposeContinuous change has long been recognized as a core characteristic of retailing, its recent acceleration unprecedented, yet innovation in retailing remains under-researched, especially within fashion retailing. Therefore, the aim of this paper is to generate a deeper understanding of if, and to what extent, fashion retailers across different market segments are innovating in terms of in-store technology diffusion over time by taking a long-term perspective over five years.Design/methodology/approachDrawing on retail change and innovation diffusion theory, the study takes a qualitative approach, using direct observation of 71 fashion stores in London (UK) in 2014 and 2019. In total, 142 stores were tabulated in Excel and qualitatively analysed manually and with NVivo.FindingsThe findings identify the innovation adoption strategies implemented, the types of in-store technologies adopted over time and the fashion retail innovation adopters.Originality/valueThe research offers new knowledge in terms of retail innovation and retail change, specifically on retail diffusion of innovation and the importance of in-store technology integration. Several practical implications for improving technology innovation management are also identified.

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“…Yet, the parallel element of 'self-service' has been left largely unnoticed. Although the expedited uptake of shopping technologies has almost been an observed fact during the pandemic [19][20][21], the question 'Does COVID-19 promote a self-service spirit (via technologies) among modern shoppers?' remains answered.…”

Section: Introductionmentioning

confidence: 99%

Does COVID-19 Promote Self-Service Usage among Modern Shoppers? An Exploration of Pandemic-Driven Behavioural Changes in Self-Collection Users

Wang

Wong

Yuen

2021

IJERPH

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Due to health concerns related to COVID-19, shoppers have learned to minimise social contact by adopting various contactless self-service technologies to fulfil their consumption needs. This study explores shoppers’ behavioural changes in relation to self-service, using the special research context of e-commerce self-collection services. By synthesising insights from the health psychology literature, this study proposes an affective-cognitive-social perspective to explain the pandemic-driven behavioural changes of self-collection users. The survey instrument is used for online data collection (n = 500), and a combined (descriptive and quantitative) method is adopted for data analysis. Our results suggest that, although with a relatively weak predictive power, the affective and cognitive appraisals of health risks lead to the reinforced usage of self-collection service. This also applies to the factors of action/coping planning and subjective norm. This study theoretically contributes to the self-service literature and creates managerial implications for retailers and logistics operators.

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How Technology is Changing Retail

Cited by 268 publications

References 43 publications

A model of adoption of AR-based self-service technologies: a two country comparison

A model of adoption of AR-based self-service technologies: a two country comparison

Tracking technology diffusion in-store: a fashion retail perspective

Does COVID-19 Promote Self-Service Usage among Modern Shoppers? An Exploration of Pandemic-Driven Behavioural Changes in Self-Collection Users

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