Chia-Chun Wu 2* Assistant Professor Dept. of Information Management I-Shou University Kaohsiung, Taiwan

Transcription

1 IRACST- International Journal of Research in Management & Technology (IJRMT), ISSN: Utilizing the Technology Acceptance Model to Explore the Effects on Purchase Lisa Y. Chen 1 Associate Professor Dept. of Information Management I-Shou University Kaohsiung, Taiwan lisachen@isu.edu.tw Chia-Chun Wu 2* Assistant Professor Dept. of Information Management I-Shou University Kaohsiung, Taiwan chiachun@isu.edu.tw Mr. Ti-Lung Li 3 Dept. of Information Management I-Shou University Kaohsiung, Taiwan angle012025@gmail.com Abstract The recent and rapidly expanding capabilities of mobile devices present retailers with both challenges and opportunities. Mobile devices offer an unparalleled depth of potential interaction with consumers, enabling opportunities to increase sales and expand markets, by motivating retailers to integrate mobile solutions into their consumer-engagement strategies. This study identifies some key determinants of consumer attitudes related to mobile and consumer purchase intentions, offering insights into the successful adoption. This study investigated some of the influencing factors of consumer behaviors related to mobile, such as usefulness, ease of use and the influence on purchasing intentions generated by mobile. The technology acceptance model (TAM) was used for this research. A self-administered questionnaire was also used as a quantitative evaluation method for data collection. Correlation and multiple regression analyses were conducted to test the proposed model and hypotheses, utilizing a sample of 187 Taiwanese consumers. The results revealed that the interactions have a positive influence on usefulness and the ease of use. Additionally, the usefulness and the ease of use had positive influence on the attitudes toward mobile. The attitudes also had a positive influence on the consumers product purchasing intention. Some of the limitations of this study and directions for future research are also discussed. Keywords-Mobile ; technology acceptance model; mobile attitude; purchase intention I. INTRODUCTION As consumers increasingly use their mobile devices to navigate, inform, and engage in real-time messaging, mobile is becoming a proven channel for driving both brand engagement/interaction and response to effectively reach target markets. A successful mobile campaign requires an integrated mobile marketing strategy, spanning promotion, sales, and customer service. A series of standalone advertisements on small screens is not adequate. The advancement communication technologies has enabled a meteoric rise in the new medium (Bakar & Bidin, 2014). Mobile communications provides information and services between individuals and corporations, enabling wireless network surfing to view realtime messages and share such messages with others in an easy to use and highly interactive environment (Yang et al., 2013). This study adopts TAM as the research model and, from the four perspectives of Information, Interaction, fulness and Ease of, analyzes the impact on mobile user purchase intention. This study also discusses the relevance and the causal relationship between the mobile content and the interaction provided by mobile service providers, and discusses, also, user attitudes toward mobile and purchase intention. The aim of this study is to provide mobile service providers with some guidance and suggestions for overall marketing direction and for service development strategies for launching mobile campaigns. II. LITERATURE REVIEW A. Definition Mobile Mobile refers to messages that appear on wireless devices. The Wireless Association (WAA) states that when messages are sent by means of a non-fixed network to wireless communication devices such as a cell phone or PDA to achieve an advertisement push effect, that this can be called mobile. However, with the progress in wireless devices, the Short Message Service (SMS) is extending its multimedia support capabilities, by integrating images, sound, animation and text, into the Multimedia Messaging Service (MMS). MMS is, therefore, able to send and receive messages that are made up of text, sound, images and video to mobile phones that support the service. In addition, the Carat Interactive Company has, also, divided mobile according to the 208

2 transmission mode of either Push or Pull (Leppäniemi et al., 2005). Push actively sends messages to wireless users, and Pull displays ads based on web browsing activity. The biggest advantage relates to the personalized, localized, and real-time environment that is created. Business Insider (2014) pointed out that mobile is growing rapidly and global mobile spend is expected to grow with an average of 26% each year over the next five years. Several major reasons why mobile will grow and thrive via personalized mediums, direct responses, and interactive communications. These mechanisms attract younger groups, one-to-many communications, (opt-in), and positioning services, all of which find expression in mobile s Environmental Interaction function. Interactivity was defined as a message receiver s feedback to message content and message source. Interactivity, therefore, compared to research on traditional and online, focuses on mobile and the Interaction with the Media Environment (McMillan, 1999). B. Technology Acceptance Model The Technology Acceptance Model (TAM) is the result of modifications by Davis et al. (1989) to the Theory of Reasoned Action (TRA) (Fishbein & Ajzen, 1975; Ajzen, 1988) and the Theory of Planned Behavior (TPB) (Ajzen, 1985). Other researchers Lee, et al. (2006), Hongwei et al. (2012) and Peslak et al. (2010) have addressed customer perceptions, utilizing different models, but not from the approach of this study. This study, with Davis et al. (1989) s Technology Acceptance Model (see Fig. 1), first discusses the basic framework then extends that discussion to the Technology Acceptance Model II, which was re-proposed by Venkatesh and Davis in 2000 in order to cover the constructs fulness and to. In 2008, Venkatesh and Bala further proposed the Technology Acceptance Model III, which introduced two new perceptions into Davis Technology Acceptance Model I: fulness (PU) and Ease of (PEOU). *** Insert Fig. 1 Here *** After modification, Venktesh s Technology Acceptance Model II (see fig. 2) integrates two major key items: Social Influence Process (Subjective Norm, Spontaneity, and Impression) and Perception Promoting Process (Task Relevance, Output Quality, Outcome Accountability, and Ease of ). *** Insert Fig. 2 Here *** After modification, the important conclusions of the Technology Acceptance Model II are as follows: 1. The relation between the Subjective Norm and is adjusted by Experience and Spontaneity, and that only in mandatory usage and early experience can Subjective Norm significantly and directly affect. 2. The relation between Subjective Norm and fulness is significantly adjusted by Experience, IRACST- International Journal of Research in Management & Technology (IJRMT), ISSN: but Impression directly affects fulness, instead of being adjusted by Experience. 3. fulness is subject to significant influence by Task Relevance, Output Quality and Outcome Accountability. Venkatesh & Bala s (2008) Technology Acceptance Model III (see fig. 3) includes two constructs: Personal Anchor and System Adjustment, and suggests that Experience and Voluntariness are significant disturbance variables. In addition, the variable Subjective Norm, which is not discussed in the original Technology Acceptance Model, is taken into consideration in the Technology Acceptance Model II and the Technology Acceptance Model III to discuss its impact on the use of new information technology. The conclusion is that the Subjective Norm has an influence on to, fulness and Image. *** Insert Fig. 3 Here *** Wallace & Sheetz (2013) studied the model that is based on the technology acceptance model and operationalized the usefulness construct according to the desirable properties of software measures. Their results suggested that both the ease of use and usefulness of a software measure can increase the likelihood of software measure use. The usefulness of a software measure can be measured by an assessment of the measure s applicability throughout the life cycle, dependence on a particular programming language, ability to prescribe solutions or actions, and the validity of the software measure. In addition, the ease of use of the software measure can also influence the perceptions of the measure's usefulness. Lee & Lehto (2013) examined their study that was framed using the technology acceptance model to identify determinants affecting behavioral intention to use YouTube. Their conceptual framework included two proximal antecedents of behavioral intention as proposed by the TAM- usefulness and ease of use. Overall their findings suggested that YouTube may augment its function as a common channel for procedural learning and instruction. III. RESEARCH METHOD This section describes the research method of this study and develops the research hypotheses, utilizing the variables from the section 2 literature review. The research framework is established based on those variables and operational definitions, and then, using the questionnaire as the research tool, empirical data was collected to test the research hypotheses. The four parts consisting of the Research Framework, Research Hypotheses, Research Design, as well as, the Data Statistics and Analysis Method are described as follows. A. Research Framework and Hypotheses As discussed in the section 2 literature review, this study adopted the technology acceptance model (TAM) proposed by Davis et al. (1989) as the basic theoretical framework (see fig. 4) to discuss whether Information and Interaction of 209

3 mobile will, through fulness and Ease of, affect Attitude. *** Insert Fig. 4 Here *** The TAM was adopted as the basic theory to explore the relationships between information, interaction, users usefulness, ease of use, and attitude. Further, this study examined the relationships between the attitudes and purchase intentions. The research hypotheses proposed are as follows: H1a: Information has a positive influence on usefulness. H1b: Information has a positive influence on ease of use. H2a: Interaction has a positive influence on usefulness. H2b: Interaction has a positive influence on ease of use. H3: usefulness has a positive influence on attitude. H4: ease of use has a positive influence on attitude. H5: attitude has a positive influence on purchase intention. B. Operationalization of Variables and Measurement The questionnaire used in this study was adopted from previous studies and is assumed to be more reliable and persuasive than the researcher s self-developed scales (Rudestam & Newton, 1995). The below shows the research variables and their operational definitions: Information is defined as accuracy of information provided by mobile, and evaluating the correctness and real-timeliness s content (Bailey & Pearson, 1983; Doll & Torkzadeh, 1988; Zeithaml et al., 2002; Varnali et al., 2012). Interaction is defined as the users autonomous right to use mobile in mobile environment and the frequency of interaction with other users (McMillan & Hwang, 2002; Liang & Mackey, 2011). usefulness is defined as the users feeling of the usefulness and efficiency of the purchase - products through using the mobile s information and interaction. ease of use is defined as the degree of effort and proficiency required of the users to use mobile (Davis, 1989; Suki & Suki, 2011). attitude is defined as the users reaction of identity (identification or disidentification) through mobile (Bauer et al., 2005; Argyriou & Melewar, 2011). Purchase intention is defined as evaluating the intensity of the users willingness to buy the commodities marketed by mobile and whether they prefer to buy such commodities (Dodds, 1991; Bian & Forsythe, 2012). IRACST- International Journal of Research in Management & Technology (IJRMT), ISSN: C. Data Statistics and Analysis Method This study adopts average Taiwanese consumers as questionnaire respondents, who will, according to their own actual state and feelings choose the closest answer to each option. In this study, the consumer questionnaire, consists of seven parts: comprising Information, Interaction, fulness, Ease of, Attitude, Purchase and Basic Personal Data. After the questionnaires were returned, the data obtained from the samples were visually checked, numbered and recorded, and then analyzed with the appropriate statistical methods. This research adopted SPSS for Windows as the statistical package for the analysis of the questionnaire data. The analysis included descriptive statistics, reliability analysis, validity analysis, factor analysis, Pearson Correlation Coefficient analysis, as well as, Multiple Regression analysis. IV. RESEARCH RESULTS AND DISCUSSIONS The physical questionnaire was used to collect data from Taiwan s mobile consumers. Random samples of 193 were returned and six questionnaires were invalidated, leaving 187 valid questionnaires. In this study, the questionnaires were based on the previous literatures, and 50 samples of pre-test questionnaires were issued to consumers for evaluation, resulting in the modification of the content of the questionnaire. The hypothetical constructs were subjected to a reliability analysis; finding that the Cronbach s α value of every variable in this questionnaire was greater than 0.7, suggesting that the questionnaire had a high reliability. The questionnaire was not completed until a consensus was reached on the questionnaire s considerable degree of reliable validity. The demographic characteristics of study participants shown that 53% respondents are male with 46% have college degree. There are 38% with age range between years old and majority of participant (34%) have at least 5 years work experience. This study adopted the Pearson Correlation Analysis to discuss the correlation between the variables, and it was found that the coefficient of correlation between average consumer variables in this questionnaire ranged from between and 0.715, suggesting a correlation between the variables and constructs in this questionnaire. The results of the correlation analysis of constructs are shown in Table 1. ***Insert Table 1 Here*** In this study, a multiple regression analysis was used to test the hypotheses, and it was found that all the hypotheses were supported. Table 2 shows the results of a regression analysis. For H1a and H1b, this study adopted information, which was measured as an independent variable, and usefulness and ease of use as dependent variables. As the results showed that, D-W=1.996 and were close to 2, suggesting no autocorrelation; VIF is 1.000, indicated that colinearity was not serious. However, the multiple determination coefficient of H1a R2 =0.252, Adj- R2 =0.248, F=62.264, and β=0.502 (P=0.00<0.001) reached a significance level. The multiple determination coefficient of 210

4 H1b R2 =0.213, Adj- R2 =0.208, F=49.971, and β=0.461 (P=0.00<0.001) also reached a significance level. The results indicated that information had a positive influence on usefulness and ease of use. For H2a and H2b, this study adopted interaction, which was measured as an independent variable, and usefulness and ease of use as dependent variables. The results showed that D-W=1.968 and were close to 2, suggesting no autocorrelation; VIF is 1.000, indicated that colinearity was not serious. However, the multiple determination coefficient of H2a R2 =0.424, Adj- R2 =0.421, F= , and β=0.651 (P=0.00<0.001) reached a significance level. The multiple determination coefficient of H2b R2 =0.278, Adj- R2 =0.275, F=71.401, and β=0.528 (P=0.00<0.001) also reached a significance level. The results indicated that the interaction had a positive influence on usefulness and ease of use. For H3 and H4, usefulness and ease of use were measured as independent variables and attitude as a dependent variable. The results showed D- W=1.948 and were close to 2, suggesting no autocorrelation. VIF is 1.000, indicated that colinearity was not serious. However, the multiple determination coefficient of H3 R2 =0.376, Adj- R2 =0.372, F= and β=0.613 (P=0.00<0.001) reached a significance level, and the multiple determination coefficient of H4 R2=0.269, Adj- R2 =0.265, F=68.177, and β=0.519 (P=0.00<0.001) reached a significance level. The results indicated that both usefulness and ease of use had a positive influence on attitude. For H5, this study adopted attitude which was measured as an independent variable and purchase intention as a dependent variable for H5. The results showed that D- W=1.961 was close to 2, suggesting no autocorrelation; VIF is 1.000, indicated that colinearity was not serious. However, the multiple determination coefficient of H5 R2 =0.512, Adj- R2 =0.509, F= , and β=0.715 (P=0.001) reached a significance level. The results indicated that attitude had a positive influence on purchase intention. ***Insert Table 2 Here*** V. RESEARCH RESULTS AND DISCUSSIONS With increasingly fierce market competition, informative is becoming more and more important, with the goal to establish selective demand, i.e. the demand for a specific brand. This paper demonstrated that the construct Mobile can become a measurement indicator to establish selective demand. With knowledge of consumer attitudes, intentions and specific behavior profiles, it will be possible to design a mobile strategy that is consistent with the significant consumer attributes. This will be conducive to providing direction and reference for mobile communication system service providers or for those who wish to use mobile for marketing. The research results demonstrated that Taiwan s mobile consumers have a high sense of identity with the statement: I IRACST- International Journal of Research in Management & Technology (IJRMT), ISSN: can exchange the experience using the mobile, with I will dedicate more time to paying attention to information about the goods and services marketed by mobile with a preference to purchase if mobile product prices are within an acceptable range. Customers highly satisfied with mobile will, through interaction with mobile, recommend those products to relatives and friends, thereby promoting manufacturer s sales and profits. This study finds that mobile can significantly affect purchase intention, especially in the competitive global economy. The quality and creativity impacts the performance of product marketing. Improving the mobile effect can positively affect sales performance and competitive strategies. Consumer attitudes toward mobile can, also, significantly affect consumers purchase intentions. Apart from the corporate image, attitudes toward mobile are an important consideration of consumers. Positive consumer attitudes toward mobile can increase the chances of successful product access to markets, increase market shares, boost a company s marketing effort, positively enhance consumer product impressions, and thereby producing purchase intention and potentially increase a company s profitability. This study has, of course, limitations. Future research could expand and test relevant issues specific to every product class separately, for a more extensive and in-depth knowledge of the subject area. The research objective could be expanded to survey consumers worldwide, for a more representative research conclusion. However, this paper adopted TAM, and suggests that future research add in other influencing factors for analysis and comparison. Finally, it is suggested that future research develop a more thorough knowledge communications to obtain more complete research results on the impact on consumer behavior. Figures and Tables Variables Information Interaction Ease of Ease of Advertisin g Attitude Purchase TABLE I. Information ** CORRELATION BETWEEN THE VARIABLES Interaction Ease of 0.502** 0.651** Ease of 0.461** 0.528** 0.755** Attitude 0.552** 0.661** 0.613** 0.519** Purchase 0.431** 0.615** 0.597** 0.530** 0.715** a. ** Significance Level: p<

5 IRACST- International Journal of Research in Management & Technology (IJRMT), ISSN: TABLE II. THE RESULTS OF A REGRESSION ANALYSIS Experience Voluntariness H1a H1b H2a H2b H3 H4 H5 information information interaction interaction Variable F β t VIF usefulness *** R 2 =0.252, Adj-R 2 =0.248,, P=0.000, D-W=1.996 ease of use *** R 2 =0.213, Adj-R 2 =0.208, P=0.000, D-W=1.942 usefulness R 2 =0424, Adj-R 2 =0.421, P=0.000, D-W=1.968 ease of use *** *** R 2 =0.278, Adj-R 2 =0.275, P=0.000, D-W= ** usefulness attitude 6 * R 2 =0.376, Adj-R 2 =0.372, P=0.000, D-W= *** ease of use attitude R 2 =0.269, Adj-R 2 =0.265, P=0.000, D-W=1.998 purchase ** attitude intention 8 * R 2 =0.512, Adj-R 2 =0.589, P=0.000, D-W=1.961 Subjective Norm Image Job Relevance Output Quality Result Demonstrabilit Anchor Computer Self efficacy Perceptions of External Computer Anxiety Computer Playfulness Adjustment Enjoyment Objective Usability fulness Ease of Behavioral Behavior Technology Acceptance Model (TAM) Figure 3. Technology Acceptance Model III External Variables fulness (U) Ease of (E) Attitude Toward Using (A) Behavioral to (BI) Actual System Mobile Information Interaction fulness Ease of Attitude Purchase Figure 1. Framework of Technology Acceptance Model (TAM) Figure 4. Framework of Research Model Subjective Norm Image Job Relevance Output Quality Result Demonstrability Experience fulness Ease of Voluntariness to Figure 2. Technology Acceptance Model II Usage Behavior Technology Acceptance Model ACKNOWLEDGMENT The author would like to thank the Editor and anonymous reviewers for their valuable comments and suggestions to improve the quality of the manuscript. REFERENCES [1] I. Ajzen, From intentions to action: A theory of planned behavior, In J. Kuhl & J. Beckman (Eds.), Action control: From cognitions to behaviors, New York: Springer, [2] I. Ajzen, Attitudes, personality and behavior. Milton Keynes: Open University Press, 1988 [3] E. Argyriou, and T. C. Melewar, Consumer Attitudes Revisited: A Review of Attitude Theory in Marketing Research, International Journal of Management Reviews, vol. 13, Iss. 4, pp , [4] J. E. Bailey, and S. W. Pearson, Development of a Tool for Measuring and Analyzing Computer r Satisfaction, Management Science, vol. 29, Iss. 5, pp , [5] M. S. Bakar, and R. Bidin, Engaging rs Using Movie Mobile : technology Acceptance and Purchase, Asian Social Science, vol. 10, Iss. 7, pp ,

6 IRACST- International Journal of Research in Management & Technology (IJRMT), ISSN: [6] J. J. Bauer, D. P. Mcadams, and A. R. Sakaeda, Interpreting the good Electronic Commerce Research and Applications, vol. 11, Iss. 6, pp. life: growth memories in the lives of mature, happy people, Journal of , Personality and Social Psychology, vol. 88, pp , 2005 [27] V. Venkatesh, and H. Bala, Technology Acceptance Model 3 and a [7] Q. Bian, and S. Forsythe, S, Purchase intention for luxury brands: A Research Agenda on Interventions, Decision Sciences, vol. 39, Iss. 2, cross cultural comparison, Journal of Business Research, vol. 65, Iss. pp , , pp , 2012 [28] V. Venkatesh, and F. D. Davis, Theoretical extension of the technology [8] Business Insider, It s Now Clear That Mobile Is The Growth Engine acceptance model: four longitudinal field studies, Management Sciece, For All Digital, Retrieved May 25, 2014 from vol.46, Iss. 2, pp , [29] L. G. Wallace, and S. D. Sheetz, The adoption of software measures: A technology acceptance model (TAM) perspective, Information & [9] P. Chatterjee, Online reviews: Do consumers use them? In M. C. Gilly, Management, vol. 51, Iss. 2, pp , 2013 & J. Myers-Levy (Eds.), Advances in consumer research, Provo, UT: [30] P. R. Warshaw, Predicting Purchase and Other Behaviours from Association for Consumer Research, pp , General and Contextually Specific s, Journal of Marketing [10] F. D. Davis, R. P. Bagozzi, and P. R. Warshaw, r Acceptance of Research, vol. 17, pp , 1980 Computer Technology: A Comparison of Two Theoretical Models, [31] B. Yang, Y. Kim, and C. Yoo, The integrated mobile Management Science, vol. 35, Iss. 8, pp , model: the effects of technology- and emotion-based [11] M. T. Dishaw, and D. M. Strong, Extending the technology acceptance evaluations, Journal of Business Research, vol. 66, Iss. 9, pp model with task-technology fit constructs, Information & Management, 1352, 2013 vo. 36, Iss. 1, pp. 9-21, [32] V. A. Zeithaml, A. Parasuraman, and A. Malhotra, Service quality [12] W. B. Dodds, K. B. Monroe, and D. Grewal, Effect of price, brand and delivery through Web sites: a critical review of extant knowledge, store information on buyers product evaluations., Journal of Marketing Journal of the Academic of Marketing Science, vol. 30, Iss. 4, pp Research, vol. 28,Iss. 3, pp , , 2002 [13] W. J. Doll, W. Xia, and G. Torkzadeh, A Confirmatory Factor Analysis of the End-r Computing Satisfaction Instrument, MIS Quarterly, pp , [14] M. Fishbein, & I. Ajzen, Belief, attitude, intention and behavior: An introduction to theory and research, Reading, MA: Addison-Wesley, [15] Y. Hongwei, H. Liu, and L. Zhou, Predicting young Chinese consumers mobile viral attitudes, intents and behavior, Asia Pacific Journal of Marketing and Logistics, vol. 24, Iss. 1, pp , [16] D. Y. Lee, and M. R. Lehto, r acceptance of YouTube for Procedural learning: An extension of the Technology Acceptance Model, Computers & Education, pp , [17] F. S. Lee, Y. C. Tsai, and W. J. Jih, An empirical examination of customer perceptions, Information Resources Management Journal, vol. 19, Iss. 4, pp , [18] M. Leppäniemi, and H. Karjaluoto, Factors Influencing Consumers Willingness to Accept Mobile : A Conceptual Model, International Journal Communications, vol. 3, Iss. 3, pp , [19] B. A. Liang, and T. Mackey, Direct to Consumer with Interactive Internet Media: Global Regulation and Public Health Issues, JAMA, vol. 305, Iss. 8, pp , [20] S. J. McMillan, Age and Interactivity: tracing Media Evolution through the Trade Press, In M. Roberts (Ed.), Proceedings of the 1999 Conference of the American Academy of, Gainesville, FL: University of Florida, [21] S. J. McMillan, and Hwang, Measures of Interactivity: An Exploration of the Role of Direction of Communication, r Control, and Time in Shaping Perceptions of Interactivity, Journal of, vol. 31, Iss. 3, pp , [22] Peslak, W. Ceccucci, and P. Sendall, An empirical study of instant messaging (IM) behavior using theory of reasoned action, Journal of Behavioral and Applied Management, vol. 11, Iss. 3, pp , [23] K. E. Rudestam, and R. R. Newton, Surviving You Dissertation, 2nd ed: Sage Publications, Inc., [24] D. Sledgianowski, and S. Kulviwat, Using social network sites: the effects of playfulness, critical mass and trust in a hedonic context, Journal of Computer Information Systems, vol. 49, Iss. 4, pp , 2009 [25] N. M. Suki, and N. M. Suki, Exploring the relationship between usefulness, ease of use, enjoyment, attitude and subscribers intention towards using 3G mobile services, Journal of Information Technology Management, vol. 22, Iss. 1, pp. 1-7, 2011 [26] K. Varnali, C. Yilmaz, and T. Aysegul, Predictors of attitudinal and behavioral outcomes in mobile : A field experiment, 213