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The efficiency of mobile media richness across different stages of online consumer behavior

Author

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  • Tseng, Chi-Hsing
  • Wei, Li-Fun

Abstract

The popularity of mobile devices has ushered in the prosperity of mobile commerce, yet research on mobile advertising and mobile marketing remains scant. Marketing ads possessing higher media richness generally have a positive effect on consumer decision-making, because rich media conveys more information, but mobile ads with richer media imply higher costs for both the marketer and the audience. The limitations of mobile devices have further highlighted the difficulty of mobile advertising and the issue of advertising costs. Selecting which media to deliver the appropriate information is the latest research trend, but few studies have applied the media richness theory to explain mobile ads’ effect on consumer behavior. This research thus explores the impact of media richness on consumer behavior at different AISAS (attention, interest, search, action, and share) stages, adopting experimental research, convenient sampling, and online questionnaire to collect data. From a total of 424 valid questionnaires, we find that media richness has a greater influence on the three early stages of AIS while having a lower impact on the later stages of AS. This research thus suggests that firms employing mobile ads should choose high richness media for those potential customers who are at the early stage of consumer behavior (AIS). For those who at the later stage (AS), it is good enough for marketers to utilize medium richness mobile ads. Following this suggestion, marketers can place mobile ads more precisely, thus improving the likelihood of a reduction in advertising costs for both the marketer and audience. As mobile ads with high media richness are more effective for high perceived risk products, firms need to use high richness media when they are promoting high perceived risk products even when potential consumers are at the later stage of AS. This research contributes to marketers dedicated to using a mobile advertisement strategy and helps refine both online consumer behavior and the media richness theory when including the context of mobile commerce.

Suggested Citation

  • Tseng, Chi-Hsing & Wei, Li-Fun, 2020. "The efficiency of mobile media richness across different stages of online consumer behavior," International Journal of Information Management, Elsevier, vol. 50(C), pages 353-364.
    • Handle: RePEc:eee:ininma:v:50:y:2020:i:c:p:353-364
    DOI: 10.1016/j.ijinfomgt.2019.08.010
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    Citations

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    Cited by:

    1. Taekyung Kim & Hwirim Jo & Yerin Yhee & Chulmo Koo, 2022. "Robots, artificial intelligence, and service automation (RAISA) in hospitality: sentiment analysis of YouTube streaming data," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(1), pages 259-275, March.
    2. Mei-Ju Chen, 2023. "Antecedents and outcomes of virtual presence in online shopping: A perspective of SOR (Stimulus-Organism-Response) paradigm," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-25, December.
    3. Yao, JingJing & Ota, Takahiro, 2024. "A new interpretation of the AISAS model: An empirical analysis of Chinese consumers’ perceptions of the food traceability system for aquatic and edible bird’s nest products," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 15(02), June.
    4. Trang P. Tran & Christopher P. Furner & Ilia Gugenishvili, 2022. "The Effects of Task Service Fit on Brand Loyalty: A Study of Branded Apps," International Journal of E-Services and Mobile Applications (IJESMA), IGI Global, vol. 14(1), pages 1-19, January.
    5. Sharma, Manisha & Banerjee, Subhojit & Paul, Justin, 2022. "Role of social media on mobile banking adoption among consumers," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    6. Yadav, Rambalak & Giri, Arunangshu & Chakrabarty, Dipanwita & Alzeiby, Ebtesam Abdullah, 2024. "Understanding the consumers webrooming in retailing industry: An application of uses and gratification and uncertainty reduction theory," Technological Forecasting and Social Change, Elsevier, vol. 206(C).
    7. Yanqing Xia & Zijian Liu & Siqin Wang & Chenxi Huang & Wenqiang Zhao, 2025. "Unlocking the Impact of User Experience on AI-Powered Mobile Advertising Engagement," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(1), pages 4818-4854, March.

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