Abstract
Marketing stimuli such as free trial has been widely used to increase user acceptance and intention to purchase information services. Information technology (IT) acceptance theories, such as the technology acceptance model and the unified theory of acceptance and use of technology, have been widely used to explain information system (IS) usage. These theories, however, do not explicitly consider the effect of marketing stimuli that would influence and shape user beliefs, attitude and behavior towards the use and purchase of new IS/IT. Echoing calls for advancing knowledge in technology acceptance, we propose a theoretical model based on expectation conformation theory to investigate the effect of marketing stimuli in the form of free trial and price of using IS on consumers’ acceptance decision process. In this study, free trial of mobile newspaper is used as the research context. A survey sample of 192 responses is used to test the model. Results suggest that the trial experience has an impact on post-trial beliefs and attitude. Perceived fee also has an effect on the acceptance of the information service when the users need to pay for the service.
Similar content being viewed by others
References
Agarwal R, Prasad J (1998) The antecedents and consequents of user perceptions in nformation technology adoption. Decis Support Syst 22(1):15–29
Barclay D, Higgins C, Thompson R (1995) The partial least squares (PLS) approach to causal modeling: personal computer adoption and use as an illustration. Technol Stud 2(2):285–309
Bawa K, Shoemaker R (2004) The effects of free sample promotions on incremental brand sales. Market Sci 23(3):345–363
Benbasat I, Zmud RW (2003) The identity crisis within the is discipline: defining and communicating the discipline’s core properties. MIS Q 27(2):183–194
Berger IE, Mitchell AA (1989) The effect of advertising on attitude accessibility, attitude confidence, and the attitude-behavior relationship. J Consum Res 16(3):269–279
Bettinger CO, Dawson LE Jr, Wales HG (1979) The impact of free-sample advertising. J Advert Res 19(3):35–39
Bhattacherjee A (2001) Understanding information systems continuance: an expectation-confirmation model. MIS Q 25(3):351–370
Bhattacherjee A, Premkumar G (2004) Understanding changes in belief and attitude toward information technology usage: a theoretical model and longitudinal test. MIS Q 28(2):229–254
Bhattacherjee A, Sanford C (2006) Infulence processes for information technology acceptance: an elaboration likelihood model. MIS Q 30(4):805–825
Burton-Jones A, Hubona GS (2005) Individual differences and usage behavior: revisiting a technology acceptance model assumption. SIGMIS Datab 36(2):58–77
Cheng HK, Tang QC (2010) Free trial or no free trial: optimal software product design with network effects. Eur J Oper Res 205(2):437–447
Chin WW (1998) The partial least squares approach to structural equation modeling. In: Marcoulides GA (ed) Modern methods for business research. Lawrewnce Erlbaum, Mahwah
Chin WW, Todd PA (1995) On the use, usefulness, and ease of use of structural wquation modeling in MIS research: a note of caution. MIS Q 19(2):237–246
Cronin JJ, Brady M, Hult T (2000) Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intention in service environments. J Retail 76(2):193–218
Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 13(3):319–340
Davis FD, Bagozzi RP, Warshaw PR (1989) User acceptance of computer technology: a comparison of two theoretical models. Manage Sci 35(8):982–1003
Davis FD, Bagozzi RP, Warshaw PR (1992) Extrinsic and intrinsic motivation to use computers in the workplace. J Appl Soc Psychoi 22(14):1111–1132
Falk R, Miller NB (1992) A primer for soft modeling. University of Akron Press, Akron
Festinger LA (1957) A theory of cognitive dissonance. Row, Peterson, Evanston
Fornell C, Larcker DF (1981) Evaluating structural equation models with unobserved variables and measurement error. J Mark Res 18(1):39–50
Fornell CR, Tellis GL, Zinkhan GM (1982) Validity assessment: a structural equations approach using partial least squares. American Marketing Association Educators’ conference. Chicago: American Marketing Association. pp 405–409
Goering PA (1985) Effects of product trial on consumer expectations, demand, and prices. J Consum Res 12(1):74–82
Hong S-J, Tam KY (2006) Understanding the adoption of multipurpose information applicances: the case of mobile data services. Inf Syst Res 17(2):162–179
Hong SJ, Thong JYL, Tam KYJ (2006) Understanding continued information technology usage behavior: a comparison of three models in the context of mobile Internet. Decis Support Syst 42(3):1819–1834
Hong S-J, Thong JYL, Moon J-Y, Tam K-Y (2008) Understanding the behavior of mobile data services consumers. Inf Syst Front 10(4):431–445
Howard JA, Sheth JN (1969) The theory of buyer behavior. John Wiley, New York
Hu PJ, Chau PYK, Sheng ORL, Tam KY (1999) Examining the technology acceptance model using physician acceptance of telemedicine technology. J Manage Inf Syst 16(2):91–112
Karahanna E, Straub DW, Chervany NL (1999) Information technology adoption across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Q 23(2):183–213
Kempf DS (1999) Attitude formation from product trial: distinct roles of cognition and affect for hedonic and functional products. Psychol Market 16(1):35–50
Kempf DS, Smith RE (1998) Consumer processing of product trial and the influence of prior advertising: a structural modeling approach. J Mark Res 35(3):325–338
Kim S, Garrison G (2009) Investigating mobile wireless technology adoption: an extension of the technology acceptance model. Inf Syst Front 11(3):323–333
Kim H-W, Chan HC, Gupta S (2007) Value-based adoption of mobile internet: an empirical investigation. Decis Support Syst 43(1):111–126
LaTour SA, Peat NC (1980) The role of situationally-produced expectations, others’ experiences, and prior experience in determining consumer satisfaction. In: Olson JC (ed) Advances in consumer research. Association for Consumer Research, Ann Arbor, pp 588–592
Legris P, Ingham J, Collerette P (2003) Why do people use information technology? A critical review of the technology acceptance model. Inf Manage 40(3):191–204
Limayem M, Hirt SG, Cheung CMK (2007) How habit limits the predictive power of intention: the case of information systems continuance. MIS Q 31(4):705–737
Liu Z, Min Q, Ji S (2008) A comprehensive review of research in IT adoption. Wireless communications, networking and mobile computing, 2008. WiCOM ‘08. 4th international conference on. 1–5
Mackintosh R, Heikkonen M (2001) The freedom economy: gaining the mCommerce edge in the era of the wireless Internet. McGraw-Hill Companies, Berkeley
Monroe KB, Krishnan R (1985) Perceived quality. In: Jacoby J, Olson J (eds) The effect of price on subjective product evaluations. Lexington Books, Lexington, pp 209–232
Moon J-W, Kim Y-G (2001) Extending the TAM for a world-wide-web context. Inf Manage 38(4):217–230
Nilakanta S, Scamell RW (1990) The effect of information sources and communication channels on the diffusion of innovation in a data base development environment. Manage Sci 36(1):24–40
Nunnally JC (1978) Psychometric theory, 2nd edn. McGraw Hill, New York
Oliver RL (1980) A cognitive model of the antecedents and consequences of satisfaction decisions. J Mark Res 17(4):460–496
Ringle CM, Wende S, Will S (2005) SmartPLS Hamburg: http://www.smartpls.de
Rivard S, Huff S (1988) Factors of success for end user computing. Commun ACM 31(5):552–561
Rogers EM (1995) Diffusion of innovations, 4th edn. Free Press, New York
Smith RE, Swinyard WR (1982) Information response models: an integrated approach. J Market 46(1):81–93
Smith RE, Swinyard WR (1983) Attitude-behavior consistency: the impact of product trial versus advertising. J Mark Res 20(3):257–267
Smith RE, Swinyard WR (1988) Cognitive response to advertising and trial: belief strength, belief confidence and product curiosity. J Advert 17(3):3–14
Starbuck W, Webster J (1991) When is play productive? Account Manage Inf Technol 1(1):71–90
Swanson EB (1988) Information system implementation: bridging the gap between design and utilization. Irwin, Homewood
Sweeney JC, Soutar GN (2001) Consumer perceived value: the development of a multiple item scale. J Retail 77(2):203–220
Thaler R (1985) Mental accounting and consumer choice. Market Sci 4(3):199–214
Thong JYL, Hong SJ, Tam KY (2006) The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. Int J Hum Comput Stud 64(9):799–810
Tse DK, Wilton PC (1988) Models of consumer catisfaction formation: an extension. J Mark Res 25(2):204–212
Van der Heijden H (2004) User acceptance of hedonic information systems. MIS Q 28(4):695–704
Venkatesh V (2006) Where to go from here? Thoughts on future directions for research on individual-level technology adoption with a focus on decision making. Dec Sci 37(4):497–518
Venkatesh V, Morris MG, Gordon BD, Davis FD (2003) User acceptance of information technology: toward a unified view. MIS Q 27(3):425–478
Wright AA, Lynch JG Jr (1995) Communication effects of advertising versus direct experience when both search and experience attributes are present. J Consum Res 21(4):708–718
Wu J-H, Wang S-C (2005) What drives mobile commerce?: an empirical evaluation of the revised technology acceptance model. Inf Manage 42(5):719–729
Xin M, Levina N (2008) Software-as-a-service model: elaborating client-side adoption factors. In: 29th international conference on information systems. Paris, France
Zmud RW (1983) The effectiveness of external information channels in facilitating innovation within software development groups. MIS Q 7(2):43–58
Author information
Authors and Affiliations
Corresponding author
Appendices
Appendix 1: a sample of mobile newspaper—Shanghai daily
.
Appendix 2: scale items
2.1 Confirmation: (Bhattacherjee 2001)
-
CON1: My experience with using Mobile Newspaper was better than what I expected.
-
CON2: The service level provided by Mobile Newspaper was better than what I expected.
-
CON3: Overall, most of my expectations from using Mobile Newspaper were confirmed.
2.2 Perceived usefulness: (Moon and Kim 2001)
-
PU1: Using Mobile Newspaper enables me to get the news more quickly.
-
PU2: Using Mobile Newspaper enhances the effectiveness of getting news.
-
PU3: Using Mobile Newspaper makes it easier to get the news.
-
PU4: Using Mobile Newspaper saves me time and effort in getting news.
-
PU5: Using Mobile Newspaper gives me more news.
2.3 Perceived ease of use: (Moon and Kim 2001)
-
PEOU1: Learning to operate Mobile Newspaper is easy for me.
-
PEOU2: Using Mobile Newspaper does not require a lot of mental effort.
-
PEOU3: It does not take too long a time to learn to use Mobile Newspaper.
-
PEOU4: My interaction with Mobile Newspaper is clear and understandable.
-
PEOU5: It is easy to remember how to use Mobile Newspaper.
-
PEOU6: It is easy for me to become skillful at using Mobile Newspaper.
2.4 Perceived enjoyment: (Moon and Kim 2001)
-
PE1: When reading Mobile Newspaper, I do not realize the time elapsed.
-
PE2: When reading Mobile Newspaper, I am not aware of any noise.
-
PE3: Using Mobile Newspaper gives enjoyment to me for my life.
-
PE4: Using Mobile Newspaper is pleasurable.
-
PE5: I have fun with using Mobile Newspaper.
-
PE6: I find using Mobile Newspaper to be interesting.
2.5 Satisfaction: (Bhattacherjee 2001)
How do you feel about your overall experience of using Mobile Newspaper?
-
SAT1: Very dissatisfied—very satisfied
-
SAT2: Very displeased—very pleased
-
SAT3: Very frustrated—very contented
-
SAT4: Absolutely terrible—absolutely delighted
-
SAT5: Absolutely unwise choice—Absolutely wise choice
-
SAT6: Absolutely wrong choice—Absolutely right choice
2.6 Perceived fee: (Sweeney and Soutar 2001)
-
PF1: Mobile newspaper is reasonably priced
-
PF2: Mobile newspaper offers value for money
-
PF3: I am pleased with the fee that I have to pay for the use of mobile newspaper
-
PF4: Mobile newspaper is economical
-
PF5: Mobile newspaper appears to be a good bargain
2.7 Continuance intention: (Bhattacherjee 2001)
-
CUI1: My intentions are to continue using mobile newspaper than use any alternative means (printed and online newspaper or magazine).
-
CUI2: I intend to continue using mobile newspaper in the future.
-
CUI3: If I could, I would like to continue my use of mobile newspaper.
Rights and permissions
About this article
Cite this article
Wang, T., Oh, LB., Wang, K. et al. User adoption and purchasing intention after free trial: an empirical study of mobile newspapers. Inf Syst E-Bus Manage 11, 189–210 (2013). https://doi.org/10.1007/s10257-012-0197-5
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10257-012-0197-5