American Academic & Scholarly Research Journal Vol. 1, No. 1, November 2011

Transcription

1 Extending TAM: Success factors of Mobile Marketing Xing Who Management Infomraiton Systems Department, Univerity of Shanghai, China, Abstract The Technology Acceptance Model (TAM) is an information systems theory that models how users come to accept and use a technology. In mobile marketing, trust is perceived to be an important factor affecting the use of this new marketing channel. This study intends to test the impact of trust on mobile marketing adoption based on and extended technology acceptance model. A survey is conducted among a sample of respondents from five shopping centers. Statistial correlations and regressions analysis was used to test the research main hypotheses. The results shows that the new factor added to TAM significantly conftibute to the success factors of mobile marketing. Кеу words Technology Acceptance Model, Trust, Mobile Marketing Introduction The Technology Acceptance Model presented by Davis in 1989 suggests that when users are presented with a new technology, a number of factors influence their decision about how and when they will use it. [1]. TAM as a model is based on the Theory of Reasoned Action by Ajzen and Fishbein [2]. TAM clearly shows that perceived ease of use and perceived usefulness affect the degree of adoption of new technology [1]. According to the model perceived ease of use shows the degree to which a person believes that using a particular system would be free from effort; and perceived usefulness shows the degree to which a person believes that using a particular system would enhance his or her job performance. Perceived ease of use also affects the perceived usefulness as depicted in (Figure 1). The TAM have been continuously studied and expanded, the two major upgrade being the TAM 2 [9] and the Unified Theory of Acceptance and Use of Technology [9]. A TAM 3 have also been proposed [13]. The model provides a tool to study the impact of external variables on internal beliefs, attitudes and intentions. The intention to use affects the real usage behavior. TAM is designed to study information systems at work to anticipate if the users will actually take a certain system into use in their jobs. Davis and other researchers tested and extended TAM to suite the research domain. TAM has been applied mostly in studying adoptin of new technology including Interent, Web and Mobile Applications [25]. Figure 1 Technology Acceptance Model [1]. In addition to TAM s factors we introduce Trust as a new extended factor to TAM which indicates that people s adoption of technology is vulnerable to the actions of other people [4]. Trust is known to have a direct influence on a consumer's behavioral intention to use the product of service [7]. Trust is one of the determinants of perceived usefulness especially in a mobile environment. Trust has a positive effect on perceived usefulness in an m-commerce setting according to Mayer [8]. In this research the researcher explores this new marketing channel by extending TAM model and and adding Trust as one of the success factors of mobile marketing. Research Model This study empirically test the influence of trust along with the attributes of the technology acceptance model (TAM) on mobile marketing adoption. The researchers used mobile marketing as the targeted technology under investigation. The researchers hypothesized that trust, utility and ease of use positively affect an individual s adoptin of mobile marketing technology and are perceived as success factors for this new marketing channel. The research model for this study is shown in Figure 2. Trust EOU Mobile Marketing Adoption PU PU stands for Perceived Usefulness EOU stands for Ease of Use Figure 2 Research model Research hypotheses formulated in this study. H1: Perceived Usefulness of mobile marketing is positively related to the adoption of mobile marketing. H2: Ease of use of mobile marketing is positively related to the adoption of mobile marketing. H3: Trust of mobile marketing is positively related to the adoption of mobile marketing. 1

2 Previous Studies Table 1 briefly explains some of the related studies made by various researchers. Davis et al [9] compared Theory of Reasoned (TRA) and TAM in terms of user adoption of computer technology. Davis [1] Technology Acceptance Model (TAM) measure perceived usefulness, perceived ease of use and user adoption of information technology. Yan et al. [10] used TAM to measure user acceptance of short message service (SMS) in Hong Kong and China and recommended that in order to formulate a successful business strategy for a specific service in a specific market, a mobile operator has to conduct a comprehensive study and identify the key external factors that will affect the perceived usefulness, perceived ease of use, and subjective norms towards adoption of that particular service in a specific market. TABLE 1 Theories and models that inform the primary research Authors Relevent Finidings [1] Usefulness was significantly more stronger linked than was ease of use [12] Both TRA and TAM postulated that Behavioral Intention (BI) is the major determinants of usage behavior [13] LOOP, which is a marketing campaign approach marketers use to build an effective process of interactivity with consumers [10] Perceived expressiveness and perceived enjoyment emphasize the importance of taking into consideration relatively untraditional antecedent of technology usage. [11] Research delineating the various stimuli to consider for successful technology adoption in a global setting, which can account for differential impacts across regions Relevant studies on trust and their findings are shown in Table 2 below. These studies support the importance of trust as a direct or indirect influencing factor in an individual s intention to engage in electronic business activities. TABLE 2 Previous Research on Trust Authors Relevent Finidings [6] Trust was a significant predictor of intention to transact in both samples. Trust had a significant effect on perceived risk, perceived usefulness, and perceived ease of use. [5] Trust was a significant predictor of purchase intention for both potential and repeat customers. Familiarity and disposition to trust were significant on trust for both customers. [15] Consumers willingness to transact online was influenced by trust, which in turn was affected by familiarity. Familiarity was significant on consumers willingness to transact. [16] Privacy and Internet trustworthiness were significant determinants of attitude toward Internet purchasing. In turn, attitude had a significant effect on intent to purchase. [17] Willingness to buy in an Internet store was affected by attitude and perception of risk. Attitude and perception of risk were affected by trust, which in turn was affected by consumer s perception of size and reputation of the store. [18] Trust in one s bank had a significant influence on him or her to use Internet banking. Other factors were Internet accessibility, attitude towards change, computer and Internet access costs, security concerns, ease of use, and convenience. 2

3 Methodology Subjects for this study were consumers age 18 and above surveyed at five shopping centers in Amman - Jordan. Variables used in the questionaire were adopted from previously validated instruments [25]. Regression analysis was used to analyze the data. A confirmatory factor analysis was performed to assess the reliability and validity of the measurement model before the regression analysis was performed. Analysis The sample of shopping centers selected for this study followed the sampling procedures suggested by Sudman [19]. Various locations such as door entrances and different stores were rotated to avoid potential biases [19] since sampling from only one entrance of a shopping center can create a socioeconomic or geographical bias [19]. Visitors were informed of the purpose of the study and were asked to spare about 10 minutes to answer the questionnaire. A total of 731 visitors were asked to take part, and 273 people agreed. The response rate was a little higher for the group under age 25 and lower for the group over age 45. Among the questionnaires answered, nine responses were unusable, because more than 23% of the total items were missing [20]. The total number of usable questionnaires was 264. Graph 1 and 2 provides the respondents demographic characteristics. The size of the 18 to 44 age group was 73% which is lower than the Jordanian population statistics of 82%. Similarly, a sample size of participants who are age 35 and older was 27% and that is smaller than that of the Jordanian population statistic of 31%. The result is reasonable, since younger groups reflects an important market segments for mobile marketing in Jordan. Female and male respondents accounted for 47.8% and 52.2%, respectively. Therefore, the difference between female and male sample is not significant. Percent Female Male Gender Graph 1 : Male Female Distribution (n = 264) Percent and older Graph 2 : Demographic Characteristics (n = 264) The goodness of fit ( ANOVA ) was generated using SPSS statistical software. It represented a significance - sig value of.000 (sig <.01) therefore the model is significant at 99% and therefore a relationship was found and we accept the research model. The R value for the three independent variables (utility, ease of use and trust) was 0.863, and the R2 of indicated that 67.3% of the variance in adoption of mobile marketing could be explained by the independent variables (utility, ease of use and trust). The results indicated that the three constructs were significantly related to adoption of mobile marketing. We conducted multiple regression analysis and extracted the table of coefficients as shown in Table 3 below. TABLE 3 COEFFICIENTS(A) Model Beta t Sig. (Constant) Utility Ease of Use Trust

4 A graphic representation of the final structural model which includes the standardized path coefficients is displayed in Figure 3. PT β =.831 (Sig. =.000) β =.248 (Sig. =.001) PEU PU Mobile Marketing Adoption β =.639 (Sig. =.004) PU = Perceived Utility PEU = Perceived Ease of Use PT = Perceived Trust Figure 3 Final model Findings and Practical Implications The coefficients for the final model are reported above and the model is represented by: (H1): The regression coefficient for perceived utility is (p = 0.004, p < = 0.05). The regression results in Table 3 indicated that the H1 hypothesis stands. Perceived utility of mobile marketing is positively related to the adoption of mobile marketing. This result is similar to that of Davis et al. [9], Straub et al. [21], Szajna [22], Igbaria (1997) [23], and Thompson et al [24] that perceived utility is positively related to adoption of technology. (H2): For the second hypothesis, the regression coefficient is 0.248, and the significance level is (p < 0.05). Therefore, Ease of Use is positively related to adoption of mobile marketing. (H3): The regression coefficient is.831, and the significance level is (p < 0.05). Therefore, Perceived Trust is positively related to adoption of mobile marketing. Trust and Utility have a much stronger positive influence on Adoption than Ease of Use. In particular, based on the Beta value and the significance levels, one may suggest that Trust component, followed by Utility are the strongest predictors of Adoption. Ease of Use play relatively a marginal role in the prediction and the explanation of Adoption. Conclusion The study s main theme was developed based on the technology acceptance model. The researcher added trust as a third construct to the model in addition to the utility and ease of use constructs originally found in the technology acceptance model. These three constructs were found to be significant in determining adoption of mobile marketing. There are many factors that influence technology adoption according to Davis and others. Technology adoption is one of the crucial keys to successful applications choice and use. The results of the statistical regression indicated that Trust and Utility has a strong positive influence on adoption. Therefore, the research findings strongly supported the hypothesis designed in the research model that utility, ease of use and trust are the key attributes that affect adoption of mobile adverting leads to the conclusion that backs up the research title that Trust is a success factor of Mobile Marketing. References [1] Fred Davis, Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quartely, 13/1989, pp , [2] Icek Ajzen, Martin Fishbein, Understanding attitudes and predicting social behavior, EngleCliffs-Wood: NJ: Prentice Hall, [3] Paul Legris, John Ingham, Pierre Collerette, Why do people use information technology?, A critical review of the Technology Acceptance Model. Information & Management, 40, pp , [4] Mayer, R.C., Davis, J.H., & Schoorman, F.D. An integrative model of organizational trust. Academy of Management Review, 20(3), , [5] Pavlou, P.A. Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3), , [6] Gefen, D., Karahanna, E., & Straub, D.W. Inexperience and experience with online stores: The importance of TAM and trust. IEEE Transactions on Engineering Management, 50(3), , [7] Cunningham, S. The major dimensions of perceived risk. IN:Cox, D(Ed.), Risk taking and information handling in consumer behavior. Harvard university press, Cambridge, MA, [8] Mayer, R. C., David, F. D. and Schoorman, F. D. An integrative model of organizational trust. Academy of Management Review, 20(3): , [9] Fred Davis, Viswanath Venkatesh, Toward preprototype user acceptance testing of new information systems: implications for software project management, IEEE Transactions on Engineering Management, Vol. 51, No 1, [10] Yan, X., Gong, M., & Thong, J.Y.L. : Two tales of one service: user acceptance of short message service (SMS) in Hong Kong and China. Vol.8 NO. 1, pp , Emerald Group Publishing Limited, [11] Baron, S., Patterson, A., & Harris, K. : Beyond technology acceptance: understanding consumer practice. International Journal of Service Industry Management. Vol. 17 No.2, pp Emerald Group Publishing Limited, [12] Davis, F.D., Bagozzi, R.P., and Warshaw, P.R. : User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management of Science; 35, 8; ABI/INFORM Global pg.984 Aug 1989; 4

5 [13] Davis, R. & Yung, D. : Understanding the Interactivity between Television and Mobile Commerce. Communications of ACM,Vol.48, No. 7 July [14] Nysveen, H., Pedersen, P.E., & Thorbjornsen, H. : Intentions to Use Mobile Services: Antecendents and Cross-Service Comparisons. Academy of Marketing Science. Journal;Summer [15] Bhattacherjee, A.. Individual trust in online firms: Scale development and initial test. Journal of Management Information Systems, 19(1), , [16] George, F.F.. Influences on the intent to make Internet purchases. Internet Research: Electronic Networking Applications and Policy, 12(2), , [17] Jarvenpaa, S.L., Tractinsky, N., & Vitale, M.. Consumer trust in an Internet store. Information Technology and Management, 1, 45-71, [18] Sohail, S., & Shanmugham, B.. E-banking and customer preferences in Malaysia: An empirical investigation. Information Sciences, 150, , [19] Seymour Sudman, "Improving the quality of shopping center sampling," Journal of Marketing Research, , November [20] George Darren, Paul Mallery, SPSS for windows step by step: a simple guide and reference 12.0 update, Boston: Allyna and Bacon, [21] Detmar Straub, Mark Keil, Walter Brenner. Testing the technology acceptance model across cultures: A three country study, Information & Management, 33, 1 11, [22] Bernadette Szajna, Empirical evaluation of the revised technology acceptance model, Management Science, 42, 85 92, [23] Magid Igbaria, Nancy Zinatelli, Paul Cragg, Personal computing acceptance factors in SMEs: A structural equation Model, MIS Quarterly, 21, , [24] Ronald Thompson, Higgins, Jane Howell, Personal computing: Toward a conceptual model of utilization, MIS Quarterly, 15, , [25] Samer Barakat, Asim El Shikh, "Trust and User Acceptance of Mobile Advertising", European, Mediterranes & Middle Eastern Conference on Informaitn Systems, Abu Dhabi,