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User Acceptance of Location-Based Mobile Advertising: An Empirical Study in Iran

User Acceptance of Location-Based Mobile Advertising: An Empirical Study in Iran

Kiyana Zolfaghar, Farid Khoshalhan, Mohammad Rabiei
ISBN13: 9781466600416|ISBN10: 1466600411|EISBN13: 9781466600423
DOI: 10.4018/978-1-4666-0041-6.ch005
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MLA

Zolfaghar, Kiyana, et al. "User Acceptance of Location-Based Mobile Advertising: An Empirical Study in Iran." E-Adoption and Technologies for Empowering Developing Countries: Global Advances, edited by Sushil K. Sharma, IGI Global, 2012, pp. 59-71. https://doi.org/10.4018/978-1-4666-0041-6.ch005

APA

Zolfaghar, K., Khoshalhan, F., & Rabiei, M. (2012). User Acceptance of Location-Based Mobile Advertising: An Empirical Study in Iran. In S. Sharma (Ed.), E-Adoption and Technologies for Empowering Developing Countries: Global Advances (pp. 59-71). IGI Global. https://doi.org/10.4018/978-1-4666-0041-6.ch005

Chicago

Zolfaghar, Kiyana, Farid Khoshalhan, and Mohammad Rabiei. "User Acceptance of Location-Based Mobile Advertising: An Empirical Study in Iran." In E-Adoption and Technologies for Empowering Developing Countries: Global Advances, edited by Sushil K. Sharma, 59-71. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-4666-0041-6.ch005

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Abstract

Location-based advertising (LBA) opens up new frontiers for marketers to place their advertisements in front of consumers. LBA is a new form of marketing communication that uses location-tracking technology in mobile networks to target consumers with location-specific advertising on their cell phones. It provides more targeted communication and interaction between the marketer and its potential customers. This paper reviews different aspects of LBA advertising and investigates the drivers of consumer acceptance toward it. Achieving this, a research framework is developed to explore the factors influencing consumer intention for using LBA in Iran. Individuals’ responses to questions about intention to accept/use of LBA advertising were collected and analyzed with various factors modified from UTAUT with main constructs of utility expectancy, trust, effort expectancy, and control. While the model confirms the classical role of utility expectancy and effort expectancy as the key factors in technology acceptance, the results also show that users’ behavioral intentions are influenced by trust and their control on ads flow.

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