Content design of advertisement for consumer exposure: Mobile marketing through short messaging service

International Journal of Information Management

Volumn 37, Issue 4, 2017, Pages 257-268

  Shareef, Mahmud Akhter ^a   Dwivedi, Yogesh K ^b   Kumar, Vinod ^a   Kumar, Uma ^a  

^a CARLETON UNIVERSITY   (Canada)

^b SWANSEA UNIVERSITY   (United Kingdom)

Author keywords

Advertisement; Consumer; Exposure; Mobile marketing; Promotional marketing; SMS

Indexed keywords

CELLULAR TELEPHONES; COMMERCE; MOBILE TELECOMMUNICATION SYSTEMS; SAMARIUM;

ADVERTISEMENT; CONSUMER; CONSUMER EXPOSURE; CRITICAL VARIABLES; EXPOSURE; MOBILE MARKETING; SHORT MESSAGING SERVICE; UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY;

MARKETING;

EID: 85015424876     PISSN: 02684012     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijinfomgt.2017.02.003     Document Type: Article

References (60)

1. Ajzen, I., The theory of planned behavior. Organizational Behavior and Human Decision Processes 50 (1991), 179–211.
2. AlAlwan, A., Dwivedi, Y.K., Rana, N.P., Factors influencing adoption of mobile banking by jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management 37:3 (2017), 99–110.
3. Bagozzi, R.P., The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the AIS 8:4 (2007), 244–254.
4. Bandura, A., Self-efficacy: the exercise of control. 1997, W.H. Freeman, New York.
5. Barwise, P., Strong, C., Permissionbased mobile advertising. Journal of Interactive Marketing 16:1 (2002), 14–24.
6. Bearden, W.O., Etzel, M., Reference group influence on product and brand decisions. Journal of Consumer Research 9:April (1982), 183–194.
7. Burnham, T.C., Chapman, J.F., Gray, P., McIntyre, M., Lipson, S., Ellison, P., Men in committed, romantic relationships have lower testosterone. Hormones and Behavior 44:2 (2003), 119–122.
8. Chang, Y.M., Age matters: Short message service advertising reading behaviors. International Journal of Mobile Communications 11:2 (2013), 159–175.
9. Chellappa, R.K., Sin, R.G., Personalization versus privacy: An empirical examination of the online consumer's dilemma. Information Technology and Management 6 (2005), 181–202.
10. Chen, C., O'Brien, M., Guo, L., Consumer trust and loyalty in e-Tail. Close, A.G., (eds.) Online consumer behavior: Theory and research in social media, advertising, and E-Tail, 2012, Taylor & Francis Group, NY, USA, 297–322.
11. Daft, R.L., Lengel, R.H., Organizational information requirements: Media richness and structural design. Management Science 32:5 (1986), 554–572.
12. Davis, F.D., Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly 13:3 (1989), 319–340.
13. Durkin, M., Tweet me cruel: Perspectives on battling digital marketing myopia. The Marketing Review 13:1 (2013), 51–63.
14. Dwivedi, Y.K., Kapoor, K.K., Williams, M.D., Williams, J., RFID systems in libraries: An empirical examination of factors affecting system use and user satisfaction. International Journal of Information Management 33:2 (2013), 367–377.
15. Dwivedi, Y.K., Shareef, M.A., Simintiras, A.C., Weerakkody, V., A generalized adoption model for services: A cross-Country comparison of mobile health (m-Health). Government Information Quarterly 33:1 (2016), 174–187.
16. Espinoza, M.M., Assessing the cross-cultural applicability of a service quality measure A comparative study between Quebec and Peru. International Journal of Service Industry Management 10:5 (1999), 449–468.
17. Fornell, C., Larcker, D.F., Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research 18:1 (1981), 39–50.
18. Gefen, D., Karahanna, E., Straub, D.W., Trust and TAM in online shopping: An integrated model. MIS Quarterly 7:1 (2003), 51–90.
19. Gray, J.A., Brain systems that mediate both emotion and cognition. Cognition & Emotion 4:3 (1990), 269–288.
20. Hu, Li-tze, Bentler, P.M., Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling 6:1 (1999), 1–55.
21. Jarad, G.A., Marketing over social media networks. European Journal of Business and Management 6:13 (2014), 114–118.
22. Kim, G.S., Park, S.B., Oh, J., An examination of factors influencing consumer adoption of short message service (SMS). Psychology & Marketing 25 (2008), 769–786.
23. Kim, C., Oh, E., Shin, N., Chae, M., An empirical investigation of factors affecting ubiquitous computing use and U-business value. International Journal of Information Management 29:6 (2009), 436–448.
24. Kline, R.B., Principles and practice of structural equation modeling. 2005, The Guilford Press, NY.
25. Koenigstorfer, J., Groeppel-Klein, A., Consumer acceptance of the mobile Internet. Marketing Letters 23:4 (2012), 917–928.
26. LaRose, R., Mastro, D.A., Eastin, M.S., Understanding Internet usage: A social cognitive approach to uses and gratifications. Social Science Computer Review 19 (2001), 395–413.
27. Lai, J.-Y., Chang, C.Y., User attitudes toward dedicated e-book readers for reading. The effects of convenience, compatibility and media richness. Online Information Review 35:4 (2011), 558–580.
28. Lee, S., Park, S., Improving accessibility and security for mobile phone shopping. Journal of Computer Information Systems 46 (2006), 124–133.
29. Liao, S., Li, Q., Xu, D., A Bayesian network-based framework for personalization in mobile commerce applications. Communications of the Association for Information Systems 15 (2005), 494–511.
30. MMA, Wireless definitions: MMA privacy and spam definitions. mobile marketing association. 2005 [Retrieved on April 26, 2006, from http://mmaglobal.com/modules/content/index.php?id=6.].
31. Mallat, N., Exploring consumer adoption of mobile payments − A qualitative study. Journal of Strategic Information Systems 16 (2007), 413–432.
32. Martins, C., Oliveira, T., Popovič, A., Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management 34:1 (2014), 1–13.
33. McKnight, D.H., Choudhury, V., Kacmar, C., Developing and validating trust measures for e-commerce: An integrative typology. Information Systems Research 13 (2002), 334–359.
34. Mortimer, G., Neale, L., Hasan, S.F.E., Dunphy, B., Investigating the factors influencing the adoption of m-banking: A cross cultural study. International Journal of Bank Marketing 33:4 (2015), 545–570.
35. Nasco, S., Bruner, G.C. II, Comparing consumer responses to advertising and non-advertising mobile communications. Psychology & Marketing, 2008, 822–838.
36. Nunnally, J.C., Bernstein, I.H., Psychometric theory. 1994, McGraw-Hill, New York.
37. Nysveen, H., Pedersen, P., Thorbjørnsen, H., Explaining intention to use mobile chat services: Moderating effects of gender. Journal of Consumer Marketing 22 (2005), 247–256.
38. Nysveen, H., Pedersen, P.E., Thorbjørnsen, H., Intention to use mobile services: Antecedences and cross-service comparisons. Journal of the Academy of Marketing Science 33 (2005), 330–347.
39. Oliver, R.L., A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research 17:4 (1980), 460–469.
40. Park, J., Yang, S., The moderating role of consumer trust and experiences: Value driven usage of mobile technology. International Journal of Mobile Marketing 1 (2006), 24–32.
41. Park, N., Roman, R., Lee, S., Chung, J.E., User acceptance of a digital library system in developing countries: An application of the Technology Acceptance Model. International Journal of Information Management 29:3 (2009), 196–209.
42. Pavlou, P.A., Fygenson, M., Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS Quarterly 30:1 (2006), 115–143.
43. Pihlström, M., Brush, G.J., Comparing the perceived value of information and entertainment mobile services. Psychology & Marketing 25:8 (2008), 732–755.
44. Rau, P.-L.P., Zhang, T., Shang, X., Zhou, J., Content relevance and delivery time of SMS advertising?. International Journal of Mobile Communication 9:1 (2011), 19–38.
45. Rosenberg, M., Conceiving the Self. 1979, Basic Books, New York.
46. Rettie, R., Grandcolas, U., Deakins, B., Text message advertising: Response rates and branding effects. Journal of Targeting, Measurement and Analysis for Marketing 13:4 (2005), 304–312.
47. Shareef, M.A., Kumar, U., Kumar, V., Dwivedi, Y.K., E-government adoption model (GAM): Differing service maturity levels. Government Information Quarterly 28:1 (2011), 17–35.
48. Shareef, M.A., Kumar, V., Kumar, U., Hasin, A.A., Application of behavioral theory in predicting consumers adoption behavior. Journal of Information Technology Research 6:4 (2013), 36–54.
49. Shareef, M.A., Archer, N., Fong, W., Rahman, M., Mann, I.J., Online buying behavior and perceived trustworthiness. British Journal of Applied Science & Technology 3:4 (2013), 662–683.
50. Shareef, M.A., Dwivedi, Y.K., Rana, N.P., Consumer behaviour in the context of SMS-based marketing. The Marketing Review 15:2 (2015), 135–160.
51. Sirgy, M.J., Self-Concept in consumer behavior: A critical review. Journal of Consumer Research 9:December (1982), 287–300.
52. Sweller, J., Cognitive load during problem solving: Effects on learning. Cognitive Science 12:June (2) (1988), 257–285.
53. Taylor, D.G., Pentina, I., Source characteristics in online shopping: DO avatar expertise, similarity, and attractiveness affect purchase outcomes?. Close, A.G., (eds.) Online consumer behavior: Theory and research in social media, advertising, and E-Tail, 2012, Taylor & Francis Group, NY, USA, 35–54.
54. Taylor, S., Todd, P., Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions. International Journal of Research in Marketing 12 (1995), 137–155.
55. Venkatesh, V., Davis, F.D., Morris, M.G., Dead or alive? The development, trajectory and future of technology adoption research. Journal of the AIS 8:4 (2007), 268–286.
56. Venkatesh, V., Thong, J.Y.L., Xu, X., Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly 36:1 (2012), 157–178.
57. Weerakkody, V., El-Haddadeh, R., Al-Sobhi, F., Shareef, M.A., Dwivedi, Y.K., Examining the influence of intermediaries in facilitating e-government adoption: An empirical investigation. International Journal of Information Management 33:5 (2013), 716–725.
58. Wu, K., Zhao, Y., Zhu, Q., Tan, X., Zheng, H., A meta-analysis of the impact of trust on technology acceptance model: Investigation of moderating influence of subject and context type. International Journal of Information Management 31:6 (2011), 572–581.
59. Xu, D., Liao, S., Li, Q., Combining empirical experimentation and modeling techniques: A design research approach for personalized mobile advertising applications. Decision Support Systems 44:3 (2008), 710–724.
60. Yang, H., Zhou, L., Extending TPB and TAM to mobile viral marketing: An exploratory study on American young consumers’ mobile viral marketing attitude, intent and behavior. Journal of Targeting, Measurement and Analysis for Marketing 19:2 (2011), 85–98.