Earticle

최근 유통산업에서 리테일테크를 활용한 비즈니스 모델의 혁신이 급속히 확산되고 있다. 따라서 유통기업들은 성장 동력을 창출하기 위해 리 테일테크 개발 및 도입에 적극적으로 나서고 있다. 본 연구는 최근 유통산업에서 등장하고 있는 리테일테크의 활용이 소비자의 구매 의도에 미 치는 영향을 기술수용모델을 바탕으로 분석했다. 이는 파괴적인 혁신을 창출하고 있는 새로운 기술에 대해 소비자들의 인식 및 행동을 고찰하였 다는 점에서 의미가 있다. 실증분석에 사용된 표본은 중국(500부), 한국(300부) 총 800부이며 리테일테크에 대한 지식 및 경험이 있는 소비자들을 대상으로 수집하였다. 분석 결과, 한국과 중국 소비자를 포함한 분석에서는 모든 경로가 유의하게 나타났다. 단, 국가별 분석에서는 중국은 모든 경로가 유의하게 났으나, 한국은 인공지능 기술이 인지된 유용성으로 가는 경로가 유의하지 않은 것을 발견했다. 이는 중국의 경우, 인공지능 기 술을 적용해 소비자들에게 맞춤형 서비스를 제공하는 스마트 유통모델이 중국 전역으로 확대되고 있는 반면, 한국은 대기업을 중심으로 리테일 테크를 도입 및 활용하고 있지만 아직 전반적으로 확산되지 못한 상황이다. 따라서 이러한 영향이 분석에 반영된 것으로 사료된다. 끝으로, 분석 결과를 바탕으로 향후 한국 유통산업이 나아가야 할 방향 및 전략적 시사점을 제시했다.

This study aimed to analyze the effect of using retail tech, which has recently emerged in the distribution industry, on consumer purchase intention. This is because firms must consider consumer perceptions and behaviors about new technologies (retail tech) that create disruptive innovations. We analyzed Korean and Chinese consumers who have experience and knowledge about retail tech. For the empirical analysis, questionnaires fromChina (500) and Korea (300) were used. Results showed that, all paths were significant in the combined analysis of Korean and Chinese consumers. However, in the country-specific analysis, China found that all paths were significant, but Korea found that artificial intelligence (AI) was not significant to perceived usefulness. The reason is in China, smart distribution models that provide customized services to consumers by applying AI are expanding throughout China. However, although Korea utilizes retail tech centered by large firms, it has not spread in general yet. Therefore, it is considered that these effects are reflected in the analysis results. Based on these results, we suggested directions and strategies for the Korean distribution industry and firms tomove forward.

This study aims to understand the role of digital technology empowerment in shaping the dynamic relationship between value co-creation and“shadow work” in unmanned retail environments. As an emerging business model, unmanned retail leverages advanced digital technologies to automate and streamline the shopping process, providing consumers with a convenient and efficient shopping experiences [16, 18]. However, while digital empowerment introduces innovation and operational efficiency, it also raises significant theoretical and practical challenges related to consumer participation and labor dynamics [6, 7]. This research emphasizes the core concept of value co-creation, highlighting the collaborative interaction between consumers and businesses to create mutual value [12, 13]. In the context of unmanned retail, digital technology facilitates deeper consumer involvement in value co-creation through mechanisms such as self-checkout systems and intelligent recommendations [3, 6, 14]. Yet, this increased consumer engagement often leads to a form of unrecognized labor termed “ shadow work,” where consumers perform tasks that benefit the business without compensation or formal recognition [4, 8, 9]. Despite the potential for value co-creation, the emergence of shadow work raises important questions about consumer rights and the recognition of labor in digital environments [1, 10, 11, 17]. To address these challenges, the study adopts the Service-Dominant Logic (SDL) framework, which views service as the core component of economic exchange and emphasizes the interdependent relationship between businesses and consumers [2, 5, 16, 17]. From this perspective, digital technology empowerment not only enhances service quality and efficiency but plays a crucial role in driving the interaction between value co-creation and shadow work [15]. This paper employs a mixed-methods approach, combining qualitative and quantitative methods, focusing on the four key areas: 1. Analyzing the Impact of Digital Technology Empowerment: Understanding how various digital tools influence the interaction between value co-creation and shadow work, particularly how the introduction of advanced analytics, artificial intelligence, and user-friendly interfaces enhances consumer participation while potentially leading to shadow work scenarios. 2. Investigating Shadow Work: Delving into the manifestations and contributions of shadow work in unmanned retail settings, analyzing specific tasks that consumers undertake without formal recognition, such as managing inventory via self-service kiosks or participating in feedback loops through review systems, and exploring the implications of this unrecognized labor on consumer satisfaction and loyalty. 3. Identifying Challenges: Addressing the complex challenges associated with labor value recognition and rights protection within the unmanned retail context, evaluating existing frameworks for consumer protection in digital environments, and proposing enhancements that accommodate the unique nature of shadow work. 4. Proposing Optimization Strategies: Recommending strategies to optimize the relationship between value co-creation and shadow work, assisting businesses in enhancing user experience while ensuring that consumers feel valued and recognized for their contributions. This article adopts a comprehensive mixed-methods design, integrating qualitative and quantitative research methods to explore the dynamic relationship between digital technology empowerment, consumer participation, and shadow work in unmanned retail environments. Initially, the research plans to employ qualitative methods, including in-depth interviews and observation, to recruit participants and gain a nuanced understanding of their behaviors and experiences during the shopping process. It is anticipated that this approach will reveal how consumers engage in value co-creation in a technology-driven environment, finding out a variety of forms of unrecognized labor. In the quantitative phase, the study plans to conduct a survey involving approximately 150 to 200 consumers who have previously shopped in unmanned retail environments, ensuring scientific rigor and reliability of the results. This sample size adequately considers the diversity of consumer behavior, statistical power, and the potential for reducing sampling bias, while employing structured questionnaires to ensure data validity and consistency. The collected data is expected to be analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), a widely utilized statistical method for exploring complex causal relationships. This research will validate whether the embedding of digital technologies (such as self-checkout and intelligent recommendations) has a significant positive impact on consumer engagement. Furthermore, it will examine whether this enhanced engagement may concurrently accompany the phenomenon of “shadow work,” wherein consumers perform certain tasks for businesses without formal recognition or compensation. Additionally, the study intends to investigate whether significant differences exist in participation patterns and labor recognition responses between light and heavy users, providing new insights into the diversity of consumer behavior in unmanned retail environments. In summary, this study aims to provide a solid theoretical foundation for understanding the complexities of consumer behavior in unmanned retail environments while offering significant practical implications for unmanned retail strategy, consumer participation, and experience design. Based on the role of digital technology empowerment, this research is expected to contribute to the formulation of effective strategies that promote consumer participation, thereby enhancing consumer satisfaction and loyalty. Via an analysis of consumer behavior, this study not only offers substantive recommendations for advancing the sustainable development of the unmanned retail industry but also provides robust theoretical support for related enterprises in optimizing customer experience strategies. Furthermore, the outcomes of this research enable to ensure that consumers ’ labor and contributions in the digital environment receive appropriate recognition and acknowledgment, fostering fairer business practices and a healthy development of the digital economy. This research not only enriches existing academic discourse but offers practical guidance for policymakers and industry practitioners, aiding in the construction of a more inclusive and equitable digital economic system.

최근 리테일이나 유통업체들이 AR, VR, AI, 무인점포 등의 기술을 활용한 리테일 테크 (Retail Tech)를 적극 도입하고 있다. 본 연구에서는 뉴미디어 및 디지털 시대 고객들의 의사결정 및 경험에 영향을 미치는 요인을 설명하는 Control 이론, Telepresence 이론, Interactivity 이론, Social Presence 이론의 4가지 이론으로부터 리테일 테크의 성공에 영향을 미치는 6가지 요인을 도출하였다: 1) 인지통제, 2) 능력통제, 3) 양방향 커뮤니케이션, 4) 생동감, 5) 휴먼 사회적 실재감, 6) 자동화된 사회적 실재감. 이 6가지 요인에 의해 국내외 13가지 리테일 테크의 사례를 사례분석 방법 (Case Study Method) 을 활용하여 분석해 보았다. 분석결과, 대부분의 사례들이 인지통제 및 능력통제를 강조하고 있는 것으로 나타났으며, 양방향 커뮤니케이션이나 생동감은 중간 수준인 것으로 나타났다. 또한, AI를 활용한 리테일 테크를 제외하고는 휴먼 사회적 실재감이나 자동화된 사회적 실재감은 아직 낮은 수준으로 나타났다. 본 연구는 4가지 이론을 활용하여 6가지 요인을 도출함으로써, 향후 리테일 테크에 대해 연구하는 연구자들에게 이론적 근거를 제공하고 있으며, 리테일 테크를 도입하는 유통업체들에게 성공적인 리테일 테크의 전략을 제시하고 있다.

Increasing number of retailers are adding new technologies such as AR (Augmented Reality), VR (Virtual Reality), AI (Artificial Intelligence), and automated store. Based on four theories (i.e., control theory, telepresence theory, interactivity theory, social presence theory) derived from new media and digital consumer behavior literatures, six key elements affecting the success of high-tech retail store are identified : 1) cognitive control, 2) behavioral control, 3) two-way communications, 4) vividness, 5) human social presence, and 6) automated social presence. Using case study method, 13 high-tech retail cases have been analyzed based on the six key elements. The results indicate that successful high-tech retailers are adopting new technologies to enhance consumers’ cognitive control and behavioral control. The levels of two-way communication and vividness of high-tech retailers were found as medium, and except AI retail stores, relatively low level of social presence was identified. Our study sheds some light on the development of high-tech retailing literatures as well as high-tech retail management.

많은 리테일 기업들은 새로운 기술을 도입하여 매장 내 고객경험을 강화하고 있다. 새롭게 도입된 리테일 기술들은 고객의 접점 경험, 고객-기업의 관계를 빠르게 변화시키고 있으며, 쇼핑환경을 보다 편리하게 하여 고객여정 전반을 변화시키고 있다. 이에 본 연구에서는 Becker & Jaakkola(2020)의 고객경험 프레임워크를 바탕으로 고객경험의 선행요인과 고객경험 그리고 고객경험 결과 요인을 도출하고 실증모델을 검증하였다. 먼저 고객경험의 선행요인을 리테일 테크 변수로 환경 임베딩과 개인 맞춤 추천으로 도출하였고, 고객경험과 고객인게이지먼트에 어떠한 영향을 주는지 검증해 보고자 하였다. 이러한 관계에서 소비자 디지털 디톡스 성향에 따라 리테일 테크에 대한 고객경험이 어떻게 달라지는지 검증해 보고자 하였다. 연구결과는 리테일 테크 변수인 환경 임베딩과 개인 맞춤 추천은 인지적, 정서적 고객경험에 긍정적인 영향을 주는 것으로 나타났으며, 고객경험은 고객인게이지먼트에도 긍정적인 영향을 주는 것으로 나타났다. 또한 리테일 테크에 대한 고객경험은 소비자 디지털 디톡스 성향에 따라 달라지는 것으로 나타났다. 이를 바탕으로 마케팅 시사점과 한계점을 제시하고 향후 연구방안을 논의하였다.

Many retailers are introducing new technologies to enhance the in-store customer experience. Newly introduced retail technologies are rapidly changing the customer contact experience and customer-company relationship, and are changing the overall customer journey by making the shopping environment more convenient(van Doorn et al., 2017). Therefore, in this study, based on the customer experience framework of Becker and Jaakkola(2020), the prior factors of customer experience, customer experience, and customer experience result factors were derived and the empirical model was verified. It was attempted to derive the leading factors of customer experience through environment embedding and personalized recommendations as retail tech variables, and to verify how they affect customer experience and customer engagement. As a result of the study, it was found that environment embedding and personalized recommendation, which are retail tech variables, have a positive effect on cognitive and emotional customer experience. And customer experience was found to have a positive effect on customer engagement. In addition, it was found that the customer experience for retail tech varies according to the consumer's digital detox tendency. Based on this, marketing implications and limitations were presented, and future research plans were discussed.