The Influence Factors Towards Mobile Advertising Message Content on Consumer Purchase Intention

Abstract

The purpose of this research is to study consumer attitude towards mobile advertising in Malaysia, and whether this attitude results in the intention to purchase the products or services advertised. This article reports on the results, based on factors such as entertainment, informativeness, irritation and credibility, which the research framework derives from Ducoffe (1996, Advertising value and advertising on the Web, Journal of Advertising Research, 36(5), 21–35) and Mackenzie (1989, An empirical examination of the structural antecedents of attitude toward the ad in an advertising pretesting context, Journal of Marketing, 53(4), 48–65). Attitudes towards behaviours, and subjective norms, based on the research by Ajzen (1991, The theory of planned behaviour, Organizational Behaviour & Human Decision Processes, 50(2), 179–211), are included in understanding consumer intention. A survey is conducted on 150 respondents, and the partial least squares analysis is used to determine the antecedents of mobile advertising that lead to consumer acceptance of mobile advertising, and the resulting intention to purchase. Results show that the advertising message content has the largest impact on attitude in advertising that is done via mobile phone. Attitudes towards mobile advertising are linked to the intention to purchase the product or services advertised. The main implication of the study shows that marketing managers should focus their marketing communication on mobile advertising, and increasing the attractiveness of this form of advertising, so as to reflect consumers’ intention to purchase. This study opens a new channel of communication for multiple unexamined matters concerning the mobile advertising industry. Based on the results, a number of recommendations are proposed and suggestions for future studies are made.

Keywords

Mobile advertising entertainment informativeness irritation credibility purchase intention

Get full access to this article

View all access options for this article.

References

Ajzen

(1991). The theory of planned behaviour. Organizational Behaviour and Human Decision Processes, 50(2), 179–211.

Ajzen

& Fishbein

(1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice Hall.

Ayyad

(2011). Internet usage vs. traditional media usage among university students in the United Arab Emirates. Journal of Arab & Muslim Media Research, 4(1), 209–226.

Bartsch

& Viehoff

(2010). The use of media entertainment and emotional gratification. Procedia Social and Behavioral Sciences, 5, 2247–2255.

Barwise

& Strong

(2002). Permission based mobile advertising. Journal of Interactive Marketing, 16(1), 14–24.

Bauer

Barnes

Reichardt

& Neumann

M. M.

(2005). Driving consumer acceptance of mobile marketing: A theoretical framework and empirical study. Journal of Electronic Commerce Research, 6(3), 181–192.

Becker

(2005). Effectiveness of mobiel channel additions and a conceptual model detailing the interaction of influential variables. Mobile Marketing Association. Retrieved 12 July 2018, from http://www.mmaglobal.com/articles/effectiveness-mobile-channel-additions-and-conceptual-model-detailing-interaction-influenti

Boyd

T. C.

& Mason

C. H.

(1999). The link between attractiveness of ‘extrabrand’ attributes and the adoption of innovations. Journal of the Academy of Marketing Science, 27(3), 306–319.

Brackett

L. K.

& Carrs

B. N.

(2001). Cyberspace advertising vs. other media: Consumer vs. mature student attitudes. Journal of Advertising Research, 41(5), 32–32.

10.

Budde

(2016). Malaysia—Key statistics, telecoms market overview, infrastructure and forecasts. Retrieved 12 July 2018, from http://www.budde.com.au/Research/Malaysia-Key-Statistics-Telecoms-Market-Overview-Infrastructure-and-Forecasts.html

11.

Chaffey

(2016). Mobile marketing statistics compilation. Smart Insights (Marketing Intelligence) Ltd. Retrieved 12 July 2018, from http://www.smartinsights.com/mobile-marketing/mobile-marketing-analytics/mobile-marketing-statistics/

12.

Charney

& Greenberg

B. S.

(2002). Uses and gratifications of the internet. In Lin

C. A.

& Atkin

D. J.

(Eds), Communication technology and society: Audience adoption and uses (pp. 379–408). Cresskill, NJ: Hampton Press.

13.

Chen

& Hsieh

(2012). Personalized mobile advertising: Its key attributes, trends, and social impact. Technological Forecasting & Social Change, 79(3), 543–557.

14.

Cheung

C. M. K.

& Lee

M. K. O.

(2010). A theoretical model of intentional social action in online social networks. Decision Support Systems, 49(1), 24–30.

15.

Chin

W. W.

(1998). The partial least squares approach for structural equation modeling. In Marcoulides

G. A.

(Ed.), Modern business research methods. Mahwah, NJ: Lawrence Erlbaum Associates.

16.

Chin

W. W.

(2010). How to write up and report PLS analyses. In Vinzi

V. E.

Chin

W. W.

Henseler

& Wang

(Eds), Handbook of partial least squares: Concepts, methods and application (pp. 691–711). New York, NY: Springer.

17.

Chowdhury

H. K.

Parvin

Weitenberner

& Becker

(2006). Consumer attitude toward mobile advertising in an emerging market: An empirical study. International Journal of Mobile Marketing, 1(2), 33–42.

18.

Couper

M. P.

(2000). Web surveys: A review of issues and approaches. Public Opinion Quarterly, 64(4), 464–494.

19.

Davis

F. D.

Bagozzi

R. P.

& Warshaw

P. R.

(1989). User acceptance of computer technology: Comparison of two theoretical models. Management Science, 35(8), 982–1003. Retrieved 12 July 2018, from http://dx.doi.Org/10.1287/mnsc.35.8.982

20.

Dhar

& Varshney

(2011). Challenges and business models for mobile location based services and advertising. Communications of the ACM, 54(5), 121–129.

21.

Dickinger

A. S.

(2005). Diffusion and success factors of mobile marketing. Electronic Commerce Research and Applications, 4(2), 159–173. Retrieved 12 July 2018, from http://dx.doi.Org/10.1016/j.elerap.2004.10.006

22.

Ducoffe

(1996). Advertising value and advertising on the web. Journal of Advertising Research, 36(5), 21–35.

23.

Fishbein

& Ajzen

(1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.

24.

Fornell

& Cha

(1994). Partial least squares. In Bagozzi

R. P.

(Ed.), Advanced methods of marketing research (pp. 52–78). Cambridge, MA: Blackwell Business.

25.

Fornell

& Larcker

D. F.

(1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.

26.

Goldsmith

R. E.

& Bridges

(2000). E-tailing versus retailing: Using attitudes to predict online buying behaviour. Quarterly Journal of Electronic Commerce, 1(3), 245–253.

27.

Hair

J. F.

Black

W. C.

Babin

B. J.

& Anderson

R. E.

(2010). Multivariate data analysis (7th ed.). Upper Saddle River, NJ: Pearson.

28.

Hashim

N. H.

& Zolkepli

I. A.

(2014). The effect of mobile advertising message content on consumer purchase intention. Proceedings of 7th Asia-Pacific Business Research Conference, 25–26 August, Singapore.

29.

Ibrahim

(2002). Environmental literacy: Toward a greener society. Realizing Agenda 21th: International Conference on Environmental Management, Universiti Kebangsaan Malaysia, Bangi, pp. 529–537.

30.

Isaid

E. N.

& Faisal

M. N.

(2015). Consumers’ repurchase intention towards a mobile phone brand in Qatar: An exploratory study utilizing theory of reasoned action framework. Global Business Review, 16(4), 594–608.

31.

Kaasinen

(2003). User needs for location-aware mobile services. Personal and Ubiquitous Computing, 7(1), 70–79. Retrieved 12 July 2018, from http://dx.doi.org/10.1007/s00779-002-0214-7

32.

Katterback

(2002, 1 February. Die SMS—Verkaufer. Impulse, p. 76.

33.

Kotler

(1999). Kotler on marketing: How to create, win, and dominate markets. New York, NY: The Free Press.

34.

Laszlo

(2009). The new unwired world: A lab status report on mobile advertising. Journal of Advertising Research, 49(1), 27–43.

35.

T. D.

& Nguyen

B. T. H.

(2014). Attitudes toward mobile advertising: A study of mobile web display and mobile app display advertising. Asian Academy of Management Journal, 19(2), 87–103.

36.

Lee

M.-C.

(2009). Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit. Electronic Commerce Research and Applications, 8(3), 130–141.

37.

Mackenzie

S. R.

(1989). An empirical examination of the structural antecedents of attitude toward the ad in an advertising pretesting context. Journal of Marketing, 53(4), 48–65.

38.

Madahi

& Sukati

(2016). An empirical study of Malaysian consumers’ channel-switching intention: Using theory of planned behaviour. Global Business Review, 17(3), 489–523.

39.

MCMC (Malaysian Communications and Multimedia Commission) (2013). MCMC annual report 2013. Retrieved from http://www.skmm.gov.my/Resources/Publications/Annual-Reports.aspx

40.

McQuail

(1987). Mass communication theory: An introduction. London: SAGE.

41.

Moore

& Benbasat

(1993). An empirical examination of a model of the factors affecting utilization of information technology by end-users (Working Paper). Vancouver: Faculty of Commerce, University of British Columbia.

42.

Novak

T. P.

Hoffman

D. L.

& Yung

(2000). Measuring the customer experience in online environments: A structural modeling approach. Marketing Science, 19(1), 22–42. Retrieved 12 July 2018, from http://www.jstor.org/pss/193257

43.

Pagani

(2004). Determinants of adoption of third generation mobile multimedia services. Journal of Interactive Marketing, 18(3), 46–59.

44.

Pavlou

P. A.

& Stewart

D. W.

(2000). Measuring the effects and effectiveness of interactive advertising: A research agenda. Journal of Interactive Advertising, 1(1), 62–78.

45.

Pedersen

P. E.

& Ling

(2002). Mobile end-user service adoption studies: A selective review. Scandinavian Journal of Information Systems, 14(1), 3–17.

46.

Ramayah

Lee

J. W. C.

& Boey

J. C. I.

(2011). Network collaboration and performance in the tourism sector. Service Business, 5(4), 411–428.

47.

Ringle

C. M.

Wende

& Will

(2005). SmartPLS 2.0 (beta). Retrieved 12 July 2018, from http://www.smartpls.de

48.

Roach

(2009). Consumer perceptions of mobile phone marketing: A direct marketing innovation. Direct Marketing: An International Journal, 3(2), 124–138.

49.

Robins

(2003). The marketing of 3G. Marketing Intelligence & Planning, 21(6), 370–378.

50.

Rodgers

& Thorson

(2000). The interactive advertising model: How users perceived and process online ads. Journal of Interactive Advertising, 1(1), 40–60.

51.

Rogers

E. M.

(2003). Diffusion of innovations. New York, NY: The Free Press.

52.

Sang

Lee

J. D.

& Lee

(2010). E-government adoption in Cambodia: A partial least squares approach. Transforming Government: People, Process and Policy, 4(2), 138–157.

53.

Sekaran

& Bougie

(2010). Research methods for business: A skill building approach (5th ed.). UK: Wiley.

54.

Shang

& Zhe

(2016). An empirical examination of users’ adoption of mobile advertising in China. Information Development, 32(2), 203–215.

55.

Shavitt

Lowrey

& Haefner

(1998). Public attitudes towards advertising: More favourable than you might think. Journal of Advertising Research, 38(4), 7–22.

56.

Siau

K. S.

(2003). Building customer trust in mobile commerce. Communications of the ACM, 46(4), 91–94.

57.

Smith

N. C.

& Quelch

J. A.

(1996). Ethics in marketing. New York, NY: McGraw Hill.

58.

Solomon

M. R.

(2004). Consumer behavior: Buying, having and being. Upper Saddle River, NJ: Pearson Education.

59.

Stewart

D. W.

& Pavlou

P. A.

(2002). From consumer response to active consumer: Measuring the effectiveness of interactive media. Journal of the Academy of Marketing Science, 30(4), 376–396.

60.

Taylor

& Todd

(1995). Understanding the information technology usage: A test of competing models. Information Systems Research, 6(2), 144–176.

61.

Varnali

& Toker

(2010). Mobile marketing research: The state-of-the-art. International Journal of Information Management, 30(2), 144–151.

62.

Varshney

(2003). Location management for mobile commerce applications in wireless Internet environment. ACM Transactions on Internet Technology, 3(3), 236–255. Retrieved 12 July 2018, from http://dx.doi.org/10.1145/857166.857169

63.

Venkatesh

& Davis

F. D.

(2000). A theoretical extension of the technology acceptance model. Management Science, 46(2), 186–204.

64.

Venkatesh

Morris

M. G.

Davis

F. D.

& Davis

G. B.

(2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.

65.

Vezina

& Paul

(1997). Provocation in advertising: A conceptualization and an empirical assessment. International Journal of Research in Marketing, 14(2), 177–192.

66.

Yang

K. C. C.

(2007). Exploring factors affecting consumer intention to use mobile advertising in Taiwan. Journal of International Marketing, 20(1), 33–49.

67.

Zernigah

K. I.

& Sohail

(2012). Consumers’ attitude towards viral marketing in Pakistan. Management & Marketing: Challenges for the Knowledge Society, 7(4), 645–662.

68.

Zhang

(2003). Delivery of personalized & adaptive content to mobile devices: A framework and enabling technology. Communication AIS, 12(13), 183–202.

69.

Zoller

Housen

V. L.

& Matthews

(2001). Wireless Internet business models: Global perspective, regional focus. UK: Ovum Ltd.