The Integration of Artificial Intelligence in Retail: Benefits, Challenges and a Dedicated Conceptual Framework

Anica-Popa, Ionuț; Anica-Popa, Liana; Radulescu, Cristina; Vrîncianu, Marinela

doi:10.24818/ea/2021/56/120

Cited by 37 publications

(20 citation statements)

References 17 publications

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“…Starting from the robots used in factories for assembly lines to the ones used already in the hospitals for performing complex operations, AI is starting to be described as a necessary component in the production process. The increase of AI's abilities to replace human actions (Anthes, 2017;Anica-Popa, et al, 2021) like translating human language, conduction online search, can be only a part in the AI future evolution.…”

Section: Literature Reviewmentioning

confidence: 99%

Data Protection as Predictor for the Acquisition of AI Devices

Stanescu¹,

Pelău²,

Barbul³

2021

New Trends in Sustainable Business and Consumption

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The significant development of AI has started to have an important impact on how people interact with robots and intelligent devices in the near future. Starting from the simplest AI forms, such as mobile applications for consumers' daily activities (example: e-commerce or health apps) to more complex forms of AI (example: robotic surgery), people represent its main beneficiary. Still, the consumers' acceptance and embracement of AI can depend on different factors. An important issue is represented by the collection of the individuals' private information, as mobile applications require different permissions in order to be installed and to be used. AI devices will also have the capacity to register private data, under specific forms. The main objective of this research is to analyze if the data protection associated with the AI usage directly influence the buying decision. The study was constructed using three pillars: willingness to buy an AI device, vulnerability of consumer related to data privacy concerns and the ability to control the private data used by AI devices. Using structural equation models in Smart-PLS3, it was shown that the vulnerability generated by the data accumulated by the AI does not influence the buying decision, while the ability to control the private data does play an important role for the willingness of consumers to buy AI devices. The practical implication of the research is given for the design of future AI devices as well as their future marketing and sales strategy. It should be taken into consideration the fact that for consumers it is important to control the availability of private data usage. Therefore AI devices should incorporate the possibility of consumers to switch-off the intelligent devices and enjoy their private life.

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Section: Literature Reviewmentioning

confidence: 99%

Data Protection as Predictor for the Acquisition of AI Devices

Stanescu¹,

Pelău²,

Barbul³

2021

New Trends in Sustainable Business and Consumption

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“…Retailers require insights into how they can strategically use these technologies to maximize consumer experience and performance, and papers in this category consider alternative ways of using AI to improve consumer experience (Moore et al , 2021). Current AI technologies that assist retailers in engaging with consumers across the retail value chain include speech recognition, robotic process automation, machine learning, deep learning, speech recognition, augmented intelligence, computer vision, intelligent applications, chatbots and virtual assistants (Oosthuizen et al , 2021; Anica-Popa, et al , 2021; Kushwaha et al , 2021). Oosthuizen et al (2021) described an example wherein the retailer Sephora equipped in-store employees with handheld devices to scan a consumer’s face and create a personalized cosmetic shade to match the consumer’s complexion.…”

Section: Resultsmentioning

confidence: 99%

Artificial intelligence in retail – a systematic literature review

Heins

2022

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Purpose The purpose of this study is to present a systematic literature review of academic peer-reviewed articles in English published between 2005 and 2021. The articles were reviewed based on the following features: research topic, conceptual and theoretical characterization, artificial intelligence (AI) methods and techniques. Design/methodology/approach This study examines the extent to which AI features within academic research in retail industry and aims to consolidate existing knowledge, analyse the development on this topic, clarify key trends and highlight gaps in the scientific literature concerning the role of AI in retail. Findings The findings of this study indicate an increase in AI literature within the field of retailing in the past five years. However, this research field is fairly fragmented in scope and limited in methodologies, and it has several gaps. On the basis of a structured topic allocation, a total of eight priority topics were identified and highlighted that (1) optimizing the retail value chain and (2) improving customer expectations with the help of AI are key topics in published research in this field. Research limitations/implications This study is based on academic peer-reviewed articles published before July 2021; hence, scientific outputs published after the moment of writing have not been included. Originality/value This study contributes to the in-depth and systematic exploration of the extent to which retail scholars are aware of and working on AI. To the best of the author’s knowledge, this study is the first systematic literature review within retailing research dealing with AI technology.

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“…The powerful self-learning and prediction abilities of artificial intelligence help business organizations in achieving satisfactory online purchasing behaviour for customers (Gupta and Pathak, 2014). Artificial intelligence, besides satisfying consumers and enhancing their online purchasing behaviour, also provides useful information to e-retailing firms regarding the needs and demands of consumers (Anica-Popa et al , 2021). More importantly, the artificial intelligence–enabled technology builds a relationship with the customers, and it ultimately helps online operating retail organisations build a brand value and satisfies the majority of customers.…”

Section: Review Of Literaturementioning

confidence: 99%

Investigating the impact of artificial intelligence on consumer’s purchase intention in e-retailing

Bhagat

Chauhan

Bhagat

2022

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Purpose Technology has been witnessing a rapid growth. The advent of artificial intelligence has further enhanced the satisfaction level of consumers, which makes it even more vital in the current scenario. This paper aims to explore the factors affecting practical implacability of artificial intelligence and its impact on consumers’ online purchase intention. Design/methodology/approach This paper has used a technology-based model as the base to explore the different factors affecting consumers’ purchase intention towards e-retailing. This study has formulated a model that demonstrates the integration of artificial intelligence in retailing by the business organizations so as to understand the needs of customers and help them accept technology. This study has further explored faith, subjective norms and consciousness as constructs which enhance the implacability of artificial intelligence. Findings This study shows that artificial intelligence positively influences consumers’ buying behaviour. This study through a model also shows that integration of artificial intelligence enhances consumers’ purchase intention. Research limitations/implications The study has been focusing on a portion of target population. So there is scope to include the whole set of the population to get closer-to-accurate results. Practical implications The study offers useful inputs for academicians as well as marketers for predicting buying behaviour of consumers. Marketing managers can use artificial intelligence–embedded technology to enhance online purchase intention. Social implications The study shows that an increase in consciousness towards e-retailing has made consumers keenly analyse and purchase products on the basis of merit and usefulness of the products. Originality/value The contribution has been made with the best of knowledge in formulating an integrated artificial intelligence model for consumers’ purchase intention in e-retailing.

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The Integration of Artificial Intelligence in Retail: Benefits, Challenges and a Dedicated Conceptual Framework

Cited by 37 publications

References 17 publications

Data Protection as Predictor for the Acquisition of AI Devices

Data Protection as Predictor for the Acquisition of AI Devices

Artificial intelligence in retail – a systematic literature review

Investigating the impact of artificial intelligence on consumer’s purchase intention in e-retailing

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