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Lee, C.H.; Lee, H.N.; Choi, J.I. Mobile Live Commerce on Purchase Intention. Encyclopedia. Available online: (accessed on 20 April 2024).
Lee CH, Lee HN, Choi JI. Mobile Live Commerce on Purchase Intention. Encyclopedia. Available at: Accessed April 20, 2024.
Lee, Chae Hyun, Han Na Lee, Jeong Il Choi. "Mobile Live Commerce on Purchase Intention" Encyclopedia, (accessed April 20, 2024).
Lee, C.H., Lee, H.N., & Choi, J.I. (2024, March 18). Mobile Live Commerce on Purchase Intention. In Encyclopedia.
Lee, Chae Hyun, et al. "Mobile Live Commerce on Purchase Intention." Encyclopedia. Web. 18 March, 2024.
Mobile Live Commerce on Purchase Intention

Mobile live commerce is emerging as a new distribution channel as connectivity and information sharing become easier due to the increase in the use of SNS and mobile phones.

mobile live commerce hedonic value perceived value purchase intention

1. Introduction

The convenience of mobile shopping has increased with its recent popularization, and mobile e-commerce has transformed into a mobile-shopping environment that can be used without space–time constraints. Particularly, when COVID-19 broke out at the end of 2019, there was a greater increase in online shopping than in offline shopping. As the sales of goods and services on online platforms continued to increase, the frequency of mobile shopping also started increasing. According to an online trend obtained by the National Statistical Office in September 2020, online shopping transactions have increased by 30.7% year-on-year, and mobile shopping transactions account for 64.8% of these transactions [1].
With the changes in the contactless economy, the distribution channels of mobile commerce have also changed, and the mobile commerce market has been expanding accordingly. With the increase in people engaging in personal broadcasting on social networking sites (SNSs) such as YouTube and Instagram, and the resultant combination of mobile and live commerce, distribution channels are changing. The spread of smartphones is expanding, and the percentage of customers using the Internet with smartphones is increasing. Mobile shopping market sales grew from USD 1.3 billion in 2012 to USD 32.6 billion in 2017 [2]; USD 137.5 trillion was achieved in 2020; and live broadcast users exceeded 617 million as of December 2020 [3]. Live commerce using smartphones is also expected to grow, and the success or failure of fierce competition in this live commerce distribution industry is expected to be determined by the enjoyment of use and the intention to continue using it.

2. Mobile Live Commerce

Mobile live commerce is a new method to transmit media in network streaming, wherein clients communicate with information in real time using the Internet, images, text, and videos within mobile devices through multimedia formats [4]. The platform of live commerce has the characteristics of online and offline shopping convergence that allows real-time communication with broadcasters, such as purchasing products directly from offline stores, while providing convenience for online shopping [5]. Mobile commerce is drawing fresh attention from distribution channels. Particularly, it differs from existing e-commerce as a platform wherein sellers, and consumers can communicate through real-time streaming channels using e-commerce media on the Internet and thereby interact with products and services [5][6][7]. In other words, mobile live commerce will grow into a new paradigm where consumption activities accelerate in China’s digital economy and online after COVID-19. Countries other than China are actively introducing it through live commerce platforms, and it is predicted as a distribution industry that can be further expanded in a few years [8].

3. Service Characteristics of Mobile Live Commerce

Mobile commerce can be defined as e-commerce in a mobile environment that connects anytime, anywhere through a network, shares information, and purchases products. Service characteristics of such mobile commerce include ubiquity, accessibility, convenience, security, location verification, personalization, and immediate accessibility.
Convenience is still an important factor in technology-based self-services, mainly in social, cultural, and economic fields; achieving a goal with the shortest amount of effort compared to the cost has been defined as convenient [9]. Regarding the functions of mobile devices, they can be accessed anytime and anywhere while moving, enabling them to provide service functions more frequently; these can be considered the biggest advantages of mobile commerce [10].
Ubiquity is a characteristic that offers flexibility and convenience on the Internet and has a significant impact on the accommodation of mobile information technology [11]. Companies can typically obtain information whenever and wherever they want, including when consumers are obtaining access through mobile devices [12]. In e-commerce, connectivity with consumers is important and involves providing access to information, which can affect sales.
Social presence also refers to social existence, which represents the sense of coexistence and social intimacy that individuals feel with one another [13]. A sense of reality is a practical state that makes one mistake it as if it really happened [14]. This makes it feel as though one is together with another; it can be defined as a sense of social reality [15].

4. Information Source Characteristics of Mobile Live Commerce

Information sources act as a medium for efficient advertising as a means of communication of advertisements. Therefore, the effect on persuasion varies depending on the source’s credibility, such as experience, reliability, expertise, and business motivation, depending on which source delivers it.
Attractiveness can be divided into physical and psychological attractiveness [16]. Research on the attractiveness of informants has revealed that the attractiveness and persuasiveness of informants depends on the degree of familiarity an individual has with the informant [17][18]. The attractiveness of a source increases the interest the consumer shows toward the messages they convey [18][19].
Vividness comes from emotional fun; imagination; and temporal, spatial, and emotional familiarity. It is important to specify and characterize concreteness and actuality when conveying information [20]. The more specific the messaging of lively information is over that of abstract information, the greater the impact of the information [21].
Expertise is the degree to which an informant correctly answers, presents, or perceives the topic or problem they want to convey [22] and is defined as the awareness that consumers have in providing correct responses and making accurate judgments about the topics and issues of the messages conveyed by the informant [23].

5. System Characteristics of Mobile Live Commerce

Traditionally, the success model of an information system measured the success factors of a system by dividing it into information quality and system quality [24], and accessibility means that people can connect anytime, anywhere when they need services. In addition, in order to increase mobility in mobile commerce, compatibility in the payment system is expected to have an important influence on the intention to introduce a new system.
Information quality indicates the speed at which meaningful information is delivered, its accuracy, and its level of usefulness to users [25]. Regarding high information quality, an enterprise can provide consumers with information about a product by utilizing information systems so the consumers can recognize the product [26].
Compatibility between various systems is essential when multiple devices are used to provide services and is particularly important for mobile devices. Compatibility represents the convenience users have when utilizing these devices and their offline and online payment systems [27]. Additionally, it is important for information technology users to harmonize and recognize life values, ways of doing things, and experiences [28].

6. Value of Consumption

The level of enjoyment consumers has in shopping is directly related to their satisfaction with the product and their pursuit of hedonic values [29]. Consumers use mobile commerce for purposes such as social exchanges and information acquisition, while satisfying various purchasing needs. To obtain pleasure from shopping, consumers also select a market that reflects their subjective feelings [30].
Hedonic value is an important factor in shopping behavior. Consumers tend to be satisfied with a product and enjoy the shopping experience more when they pursue hedonic value [29]. Additionally, hedonic value can be considered a measure of the subjective or personal empirical benefits that buyers enjoy from shopping daily and the emotional stimulation provided by goods or services [31][32].
Perceived value refers to the value that consumers gain from purchasing goods or using services [33]; it refers to a consumer’s personal beliefs [34]. It has been recognized as an important concept that determines the consumer behavior even in mobile environments [35].

7. Purchase Intention

Purchase intention represents the subjective behavior of a consumer, such as the beliefs and attitudes they have about a product [36]. It was also defined as the possibility that a belief or attitude leads to an act or action of purchase [37]. Purchase intention also refers to the subjective possibility or personal condition of consumers, including the relationships among their purchasing attitudes, knowledge, and behavior.
Additionally, purchase intention is a consumer’s preference for an entity, which is a subjective personal belief that modifies their future planned behavior, including their emotional, perceptual, or consumption behavior before and after a purchase [38]. Purchase intention also refers to the degree to which a consumer would want to purchase a product online [39]. Information systems in the field of online shopping have been proven to facilitate purchases or repurchases [40].


  1. Kostat. Online Shopping Trends in September 2020 and Online Overseas Direct Sales and Purchase Trends in the Third Quarter. Available online: (accessed on 20 July 2020).
  2. Lee, J.; Kwon, K.H. Mobile Shopping Beauty Live Commerce Changes in COVID-19 Pandemic Focused on Fun Contents of MZ Generation in Republic of Korea. J. Cosmet. Dermatol. 2022, 21, 2298–2306.
  3. Choi, S.J.; Kim, K.A. The Influence of Influencers on Shopping Value and Product Trust in Live Commerce. In Proceedings of the KMIS 2022: 14th International Conference on Knowledge Management and Information Systems, Valletta, Malta, 24–26 October 2022; pp. 646–651.
  4. Hu, Y.L. Analysis of the Influence of Mobile Live Likeliness and Fashion Shopping Benefit on the Behavior of 20 to 30 Aged Chinese Women Consumers. Master’s Thesis, Kyung Hee University, Seoul, Republic of Korea, 2019.
  5. Sun, Y.; Shao, X.; Li, X.; Guo, Y.; Nie, K. A 2020 Perspective on “How Live Streaming Influences Purchase Intentions in Social Commerce: An IT Affordance Perspective”. Electron. Commer. Res. Appl. 2020, 40, 100958.
  6. Cai, J.; Wohn, D.Y.; Mittal, A.; Sureshbabu, D. Utilitarian and Hedonic Motivations for Live Streaming Shopping. In Proceedings of the 2018 ACM International Conference on Interactive Experiences for TV and Online Video, New York, NY, USA, 26–28 June 2018.
  7. Cai, J.; Wohn, D.Y. Live Streaming Commerce: Uses and Gratifications Approach to Understanding Consumers’ Motivations. In Proceedings of the 52nd Hawaii International Conference on System Sciences, Grand Wailea, HI, USA, 8–11 January 2019.
  8. Bhattarai, A. The Future of Online Retail Looks a Lot Like QVC, with Live Streams of Influencers, Including Dogs, Doing the Hawking. Washington Post. Available online: (accessed on 9 July 2021).
  9. Morganosky, M.A. Cost-Versus Convenience-Oriented Consumers: Demographic, Lifestyle, and Value Perspectives. Psychol. Mark. 1986, 3, 35–46.
  10. Park, E.; Kim, K.J. User Acceptance of Long-Term Evolution (LTE) Services: An Application of Extended Technology Acceptance Model. Data Technol. Appl. 2013, 47, 188–205.
  11. Looney, C.A.; Jessup, L.M.; Valacich, J.S. Emerging Business Models for Mobile Brokerage Services. Commun. ACM 2004, 47, 71–77.
  12. Siau, K.; Lim, E.P.; Shen, Z. Mobile Commerce: Promises, Challenges and Research Agenda. J. Database Manag. 2001, 12, 4–13.
  13. Lombard, M.; Snyder-Duch, J. Interactive Advertising and Presence: A Framework. J. Interact. Advert. 2001, 1, 56–65.
  14. Lee, K.M. Presence, Explicated. Commun. Theory 2004, 14, 27–50.
  15. Biocca, F.; Harms, C.; Burgoon, J.K. Toward a More Robust Theory and Measure of Social Presence: Review and Suggested Criteria. Presence Teleoper. Virtual Environ. 2003, 12, 456–480.
  16. Erdogan, B.Z.; Baker, M.J.; Tagg, S. Selecting Celebrity Endorsers: The Practitioner’s Perspective. J. Advert. Res. 2001, 41, 39–48.
  17. Kahle, L.R.; Homer, P.M. Physical Attractiveness of the Celebrity Endorser: A Social Adaptation Perspective. J. Consum. Res. 1985, 11, 954–961.
  18. McGuire, W.J. Attitudes and Attitude Change. In The Handbook of Social Psychology; Lindzey, G., Aronson, E., Eds.; Random House: New York, NY, USA, 1985; Volume 2, pp. 233–346.
  19. Kelman, H.C. Compliance, Identification, and Internalization Three Processes of Attitude Change. J. Confl. Resolut. 1958, 2, 51–60.
  20. Nisbett, R.E.; Ross, L. Human Inference: Strategies and Shortcomings of Social Judgment; Prentice-Hall: Hoboken, NJ, USA, 1980; pp. 1621–1636.
  21. Newman, M.E.J. The Structure and Function of Complex Networks. SIAM Rev. 2003, 45, 167–256.
  22. Ohanian, R. Construction and Validation of a Scale to Measure Celebrity Endorser‘s Perceived Expertise, Trustworthiness, and Attractiveness. J. Advert. 1990, 19, 39–52.
  23. Birnbaum, M.H.; Stegner, S.E. Source Credibility in Social Judgment: Bias, Expertise, and the Judge’s Point of View. J. Pers. Soc. Psychol. 1979, 37, 48–74.
  24. DeLone, W.H.; McLean, E.R. Information Systems Success: The Quest for the Dependent Variable. Inf. Syst. Res. 1992, 3, 60–95.
  25. Ahn, T.; Ryu, S.; Han, I. The Impact of the Online and Offline Features on the User Acceptance of Internet Shopping Malls. Electron. Commer. Res. Appl. 2004, 3, 405–420.
  26. Mentzer, J.T.; Flint, D.J.; Kent, J.L. Developing a Logistics Service Quality Scale. J. Bus. Logist. 1999, 20, 9–32.
  27. Park, I.S.; Ahn, H.C. A Study on the User Acceptance Model of Mobile Credit Card Service Based on UTAUT. e-Bus. Stud. 2012, 13, 551–574.
  28. Schiertz, P.G.; Schilke, O.; Wirtz, B.W. Understanding Consumer Acceptance of Mobile Payment Services: An Empirical Analysis. Electron. Commer. Res. Appl. 2010, 9, 209–216.
  29. Westbrook, R.A.; Black, W.C. A Motivation-Based Shopper Typology. J. Retail. 1985, 61, 78–103.
  30. Bloch, P.H.; Ridgway, N.M.; Dawson, S.A. The Shopping Mall as Consumer Habitat. J. Retail. 1994, 70, 23–42.
  31. Babin, B.J.; Darden, W.R.; Griffin, M. Work and/or Fun: Measuring Hedonic and Utilitarian Shopping Value. J. Consum. Res. 1994, 20, 644–656.
  32. Overby, J.W.; Lee, E.J. The Effects of Utilitarian and Hedonic Online Shopping Value on Consumer Preference and Intentions. J. Bus. Res. 2006, 59, 1160–1166.
  33. Zeithaml, V.A. Service Quality, Profitability, and the Economic Worth of Customers: What We Know and What We Need to Learn. J. Acad. Mark. Sci. 2000, 28, 67–85.
  34. Zeithaml, V.A. Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence. J. Mark. 1988, 52, 2–22.
  35. Kim, H.W.; Chan, H.C.; Gupta, S. Value-Based Adoption of Mobile Internet: An Empirical Investigation. Decis. Support Syst. 2007, 43, 111–126.
  36. Blackwell, R.D.; Miniard, P.W.; Engel, J.F. Consumer Behavior, 9th ed.; Harcourt: New York, NY, USA, 2001.
  37. Engel, J.F.; Blackwell, R.D.; Miniard, P.W. Consumer Behavior, 8th ed.; Dryden Press: Hinsdale, IL, USA, 1995.
  38. Boulding, W.; Kalra, A.; Staelin, R.; Zeithaml, V.A. A Dynamic Process Model of Service Quality: From Expectations to Behavioral Intentions. J. Mark. Res. 1993, 30, 7–27.
  39. Poddar, A.; Donthu, N.; Wei, Y. Web Site Customer Orientations, Web Site Quality, and Purchase Intentions: The Role of Web Site Personality. J. Bus. Res. 2009, 62, 441–450.
  40. Siekpe, J.S. An Examination of the Multidimensionality of Flow Construct in a Computer-Mediated Environment. J. Electron. Commer. Res. 2005, 6, 31–43.
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