Factors Influencing Consumers' Acceptance of Mobile Marketing Services

The research of mobile marketing services is still at the early stage and the reason to explain the acceptance as well as the understanding of the actual usage level of mobile marketing services still remains unclear. To investigate this issue, this study has examined the acceptance of mobile market...

Full description

Saved in:

Bibliographic Details
Main Author:	Mohammad, Ismail
Format:	Thesis
Language:	eng eng
Published:	2012
Subjects:	HF5415.33 Consumer Behavior.
Online Access:	https://etd.uum.edu.my/3502/1/s91480.pdf https://etd.uum.edu.my/3502/8/s91480.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-uum-etd.3502
record_format	uketd_dc
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng
advisor	Che Razak, Razli
topic	HF5415.33 Consumer Behavior.
spellingShingle	HF5415.33 Consumer Behavior. Mohammad, Ismail Factors Influencing Consumers' Acceptance of Mobile Marketing Services
description	The research of mobile marketing services is still at the early stage and the reason to explain the acceptance as well as the understanding of the actual usage level of mobile marketing services still remains unclear. To investigate this issue, this study has examined the acceptance of mobile marketing services by measuring the consumer's intention and actual usage of mobile marketing services. Grounded by the Decomposed Theory of Planned Behaviour (DTPB), this study proposes a framework by decomposing attitude, subjective norm, perceived behavioural control and perceived risk. A total of 334 full-time university students from four public universities in the Northern Region, Malaysia have participated in this study. Data for all the study variables have been collected through self-administered survey questionnaires. Structural Equation Modeling (SEM) is the main statistical technique used in this study. The study has shown that the level of the actual usage is at the lower level. The study also reveals that all the main beliefs (attitude, subjective norm, perceived behavioural control and perceived risk) are found to have significant effect on consumer‟s intention to use mobile marketing services. With regard to antecedents‟ effect on the main beliefs, there are only four factors which are found insignificant namely perceived ease of use, personal innovativeness, media and technology facilitating condition. Whereas, another ten antecedent factors significantly influence the main beliefs. Overall, the results indicate that the model provides a good understanding of the factors that influence intention to use and the actual usage of mobile marketing services. As predicted, decomposition of the main beliefs provides more specific factors that influence the behaviour. Based on the findings, the theoretical and practical implications of the study as well as limitations and suggestions for future studies are also discussed.
format	Thesis
qualification_name	Ph.D.
qualification_level	Doctorate
author	Mohammad, Ismail
author_facet	Mohammad, Ismail
author_sort	Mohammad, Ismail
title	Factors Influencing Consumers' Acceptance of Mobile Marketing Services
title_short	Factors Influencing Consumers' Acceptance of Mobile Marketing Services
title_full	Factors Influencing Consumers' Acceptance of Mobile Marketing Services
title_fullStr	Factors Influencing Consumers' Acceptance of Mobile Marketing Services
title_full_unstemmed	Factors Influencing Consumers' Acceptance of Mobile Marketing Services
title_sort	factors influencing consumers' acceptance of mobile marketing services
granting_institution	Universiti Utara Malaysia
granting_department	Othman Yeop Abdullah Graduate School of Business
publishDate	2012
url	https://etd.uum.edu.my/3502/1/s91480.pdf https://etd.uum.edu.my/3502/8/s91480.pdf
_version_	1747827588004315136
spelling	my-uum-etd.35022016-04-20T02:27:05Z Factors Influencing Consumers' Acceptance of Mobile Marketing Services 2012-06 Mohammad, Ismail Che Razak, Razli Othman Yeop Abdullah Graduate School of Business Othman Yeop Abdullah Graduate School of Business HF5415.33 Consumer Behavior. The research of mobile marketing services is still at the early stage and the reason to explain the acceptance as well as the understanding of the actual usage level of mobile marketing services still remains unclear. To investigate this issue, this study has examined the acceptance of mobile marketing services by measuring the consumer's intention and actual usage of mobile marketing services. Grounded by the Decomposed Theory of Planned Behaviour (DTPB), this study proposes a framework by decomposing attitude, subjective norm, perceived behavioural control and perceived risk. A total of 334 full-time university students from four public universities in the Northern Region, Malaysia have participated in this study. Data for all the study variables have been collected through self-administered survey questionnaires. Structural Equation Modeling (SEM) is the main statistical technique used in this study. The study has shown that the level of the actual usage is at the lower level. The study also reveals that all the main beliefs (attitude, subjective norm, perceived behavioural control and perceived risk) are found to have significant effect on consumer‟s intention to use mobile marketing services. With regard to antecedents‟ effect on the main beliefs, there are only four factors which are found insignificant namely perceived ease of use, personal innovativeness, media and technology facilitating condition. Whereas, another ten antecedent factors significantly influence the main beliefs. Overall, the results indicate that the model provides a good understanding of the factors that influence intention to use and the actual usage of mobile marketing services. As predicted, decomposition of the main beliefs provides more specific factors that influence the behaviour. Based on the findings, the theoretical and practical implications of the study as well as limitations and suggestions for future studies are also discussed. 2012-06 Thesis https://etd.uum.edu.my/3502/ https://etd.uum.edu.my/3502/1/s91480.pdf text eng validuser https://etd.uum.edu.my/3502/8/s91480.pdf text eng public Ph.D. doctoral Universiti Utara Malaysia Adam, D.A., Nelson, R.R., & Todd, P.A. (1992). Perceived usefulness, ease of use and usage of information technology : A Replication. MIS Quarterly, 16(2), 227-247. Agarwal, R. (2000). Individual acceptance of information technologies. In R.W. Zmud, Framing The domains Of IT Management: Projecting The Future Through The Past (pp. 85- 104). Cincinnati: Pinnaflex Educational resources. Agarwal, R., & Karahanna, E. (2000). Time flies when you're having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665-694. Agarwal, R., & Prasad, J. (1998). A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology. Information System Research, 9(2), 204-216. Agarwal, R., & Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies? Decision Sciences, 30(2), 361-391. Agarwal, R., & Prasad, J. (1997). The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decision Sciences, 28(3), 557-582. Ahuja, M., Gupta, B., & Raman, P. (2003). An Empirical Investigation of Online Consumer Purchasing Behavior. Communications of The ACM, 46(12), 145-151. Ainin, S., Noor Ismawati, J., & Suhana, M. (2007). An overview of mobile banking adoption among the urban community. International Journal Mobile Communications, 5(2) , 157-168. Ajzen, I. (2005). Attitudes, Personality and Behavior (Second edition). New York, USA: Open University Press. Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J.K. (Eds.), & J. Beckman, Action-control: From Cognition to Behavior (pp. 11-39). Heidelberg : Springer. Ajzen, I. (2002). Perceived behavorial control, self- efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology, 32(4), 665- 683. Ajzen, I. (1991). The Theory of Planned Behaviour. Organizational behavior and human decision Processes, 50, 179-211. Ajzen, I., & Driver, B. E. (1992). Prediction of leisure participation from behavioral, motive and control beliefs: An application of the theory of planned behavior. Leisure Sciences, 13(3), 185-204. Ajzen, I., & Fishbein, M. (1970). The prediction of behavior from attitudinal and normative variables. Journal of Experimental Social Psychology, 6(4), 466-487. Ajzen, I., & Fishbein, M. (1980). Understanding attitude and predicting social behavior. Englewoods Cliffs, NJ: Prentice-Hall Inc. Ajzen, I., & Madden, T.J. (1986). Prediction of Goal- Directed Behavior: Attitudes, Intentions,and Perceived Behavioral Control. Journal Of Experimental Social Psychology, 453-474. Aldas-Manzano, J., Lassala-Navarre, C., Ruiz-Mafe, C., & Sanz-Blas, S. (2009). The role of consumer innovativeness and perceived risk in online banking usage. International Journal of Bank Marketing, 27(1), 53-75. Al-Gahtani, S.S., & King, M. (1999).Attitudes, satisfaction and usage: factors contributing to each in the acceptance of information technology. Behavior and Information Technology, 18(4), 277-297. Al-Majali, M., & Nik Kamariah, N. M. (2010). Application of Decomposed Theory of Planned Behavior on Internet Banking Adoption in Jordan. Journal of Internet Banking and Commerce, 15(2), 1-7. Amberg, M., Hirschmeie, M., & Wehrmann, J. (2004). The Compass Acceptance Model for the analysis and evaluation of mobile services. International Journal of Mobile Communications, 2(3), 248-259. Amily, F., & Norina, A. J. (2010). The effect of Malaysian teenagers' ethnicities, influence strategies and family purchase decisions of mobile phones. Young Consumers, 11(4) , 330-336. Anckar, B., & D'Incau, D. (2002). Value creation in mobile commerce: findings from a consumer survey. Journal of Information Technology Theory and Application, 4(1), 43-64. Anderson, J.C., & Gerbing, D.W. (1988). Structural equation modelling in practice: A review and recommended two-step approach. Psychology Bulletin, 103(3), 411-423. Anna, C.A., & Bee, N.L. (2010). The Acceptance of the e-Filing System by Malaysian Taxpayers: A Simplified Model. Electronic Journal of e-Government, 8(1), 13-22. Armstrong, J., & Overton, T.S. (1977). Estimating non- response bias in mail surveys. Journal of Marketing Research, 4, 396-402. Arts, J.W., Frambach, R.T., & Bijmolt, T.H. (2011). Generalizations on consumer innovation adoption: A meta-analysis on drivers of intention and behavior. International Journal of Research in Marketing, 28, 134-144. Bagozzi, R.P. (1982). A filed investigation of causal relations among cognitions, affect, intention and behavior. Journal of Marketing Research, 19(4), 562-584. Bagozzi, R.P., & Warshaw, P.R. (1990). Trying to consume. Journal of Consumer Research, 17, 127-140. Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural models. Journal of the Academy of Marketing Science, 16(1), 74-94. Balasubramanian, S., Peterson, R.A., & Jarvenpaa, S.L. (2002). Exploring the Implications of M-Commerce for Markets and Marketing. Journal of academy of Marketing Science, 30(4), 348-361. Balir, E., & Burton, S. (1987). Cognitive processes used by survey respondents to answer behavioral frequency questions. Journal Consumer Research, 14, 280-288. Bandura, A. (1995). Self-Efficacy in changing society. New York: Cambridge University Press. Bandura, A. (1991). Social cognitive theory of self- regulation. Organizational Behavior and Human Decision Processes, 50, 248-287. Bandura, A. (1986). Social foundations of thought and action. Englewood cliffs, NJ: Prentice Hall. Barnes, S.J. (2002). Wireless digital advertising:nature and implications. International Journal of Advertising, 20 (3), 399-420. Barnes, S. J., & Scornavacca, E. (2004). Mobile marketing: the role of permission and acceptance. International Journal Mobile Communication, 2(2), 128-139. Barutcu, S. (2007). Attitudes towards mobile marketing tools: A study of Turkish consumers. Journal of Targeting, Measurement and Analysis for Marketing, 16(1), 26-38. Barwise, P. & Strong, C. (2002). Permission-based Mobile Advertising. Journal of Interactive Marketing, 16(1), 14-24. Bauer, H.H., Barnes, S.J., Reichardt, T., & Neumann, M.M. (2005). Driving Consmer Acceptance Of Mobile Marketing: A Theoretical Framework and Empirical Study. Journal of Electronic Commerce Research, 6(3), 181-192. Bauer, R.A. (1967).Consumer behavior as risk taking. In D.F. Cox, Risk taking and information handling in consumer behavior (pp. 23-33). Boston,MA: Graduate School of Business Administration, Harvard University. Bauer, R.A. (1960). Consumer behavior as risk taking, in R.S. Hancock (ed), Dynamic Marketing for a Changing World. Proceedings of the 43rd National Conference of the American Marketing Association, (pp. 389-398). Becker, M. (2006). Mobile Ecosystem & Strategic Alliances-practice, Elements, and Framework. Retrieved from http://iloopmobile.com Belkhamza, Z., & Syed Azizi, W. (2009). The Effect of Perceived Risk on the Intention to Use E- commerce: The Case of Algeria. Journal of Internet Banking and Commerce, 14(1), 1- 10. Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychology Bulletin, 107(2), 238-246. Bhattacherjee, A. (2000). Acceptance of E-Commerce Services: The Case of Electronic Brokerages. IEEE Transactions on systems, Man And Cybernetics—PART A: Systems And Humans, 30(4), 411-420. Bhatti, T. (2007). Exploring Factors Influencing the Adoption of Mobile Commerce. Journal of Internet Banking and Commerce, 12(3), 1-13. Bigne, E., Ruiz, C., & Sanz, S. (2005). The impact of Internet user shopping patterns and demographics on consumer mobile buying behaviour. Journal of Electronic Commerce Research, 6(3), 193-209. Black, N., Lockett, A., Winklofer, H., & Ennew, C. (2001). The adoption of Internet financial services: a qualitative study. International Journal of Retail & Distribution, 29 (8/9), 390-398. Bobbitt, M. L., & Dabholkar, P. A. (2001). Integtrating attitudinal theories to understand and predict use of technology-based self-services: The Internet as an illustration. International Journal of Service Industry, 12(5), 423-450. Bollen, K. A. (1989). Structural equations with latent variables. New York: John Wiley & Sons. Boomsma, A. (1983). On the robustness of Lisrel against small size and nonnormality. Amsterdam: Sociometric Research Foundation. Braiterman, J., & Becker, M. (2007). Academic Review: Customer Experience and Mobile Marketing. Retrieved from http://mmaglobal.com Brancheau, J., & Wetherbe, J. (1990). The adoption of spreadsheet software: Testing innovation diffusion theory in the context of end user computing. Information Systems Research, 1, 115-143. Briley, D.A., & Williams, J.D. (1998).Emotive and cognitive effects of culture. Asia Pacific Advances in Consumer Research, 3, 26-29. Brislin, R.W. (1970). Back translation for cross-cultural research. Journal of Cross-Cultural Psychology, 1(3), 185- 216. Bruner, G.C., & Kumar, A. (2005). Explaining consumer acceptance of handheld internet devices. Journal of Business Research, 58(5), 553-558. Byrne, B.M. (2010). Structural equation modelling with AMOS: Basic concepts, applications and programming (2nd edition). New York: Routlege Academy. Calisir, F., Gumussoy, C.A., & Bayram, A. (2009). Predciting the behavioral intention to use Enterprise resource Planning Systems; an exploratory extension of the technology acceptance model. Management Research News, 32(7) , 597-613. Carrol, A., Barnes, S., Scornavacca, E., & Fletcher, K. (2007). Consumer Perceptions and attitudes towards SMS advertising: recent evidence from New Zealand. International Journal of Advertising, 26(1), 79-98. Carroll, A., Barnes, S. J., & Scornavacca, E. (2005). Consumers Perceptions and Attitudes towards SMS Mobile Marketing in New Zealand. Proceedings of the Fourth International Conference on Mobile Business (ICMB 2005), (pp. 434-440). Chang, M. K., & Cheung, W. (2001). Determinant of the intention to use Internet/WWW at work: A confirmatory study. Information & Management, 39, 1-14. Chang, M. K., & Cheung, W. (2001). Determinants of the intention to use Internet/WWW at work: a confirmatory study. Information & Management, 39(1), 1-14. Chang, M., Cheung, W., & Lai, V. (2005). Literature derived reference models for the adoption of online shopping. Information & Management, 42(4), 543-559. Chang, T.C., Liao, Y.F., & Lin, J.G. (2008). The study of aircraft flight simulator adoption in technology acceptance model-take an Airman used simulator as an example. Journal Crisis Management, 5(1), 79-88. Chau, P.Y. (1997). Reexamining a model for evaluating information center success using a structural equation modeling approach. Decision Sciences, 28(2), 309-334. Chau, Y.K., & Hu, J.-H. (2001). Information Technology Acceptance by Individual Professionals: A Model Comparison Approach. Decision Sciences, 32(4), 699-719. Chen, L.-d. (2008). A model of consumer acceptance of mobile payment. International Journal Mobile Communications, 6(1), 32-52. Chen, L.-D., Gillenson, M.L., & Sherrell, D.L. (2004). Consumer Acceptance of Virtual Stores: A Theoretical Model and Critical Success Factors for Virtual Stores. Database for Advances in Information Systems, 35(2), 8-31. Chen, L.-D., Gillenson, M.L., & Sherrell, D.L. (2002). Enticing inline consumers: an extended technology acceptance perspective. Information & Management, 39, 705- 719. Cheng, T.C., Lam, D.Y., & Yeung, A.C. (2006). Adoption of internet banking: An empirical study in Hong Kong. Decision Support Systems, 42, 1558-1572. Cheong, J.H., & Park, M.C. (2005). Mobile Internet Acceptance in Korea. Internet Research, 15(2), 125-140. Chin, W.W., & Todd, P.A. (1995). On the use, usefulness and ease of use of structural equation modelling in MIS research: A note of caution. MIS Quarterly, 19(2), 237-245. Chong, Y.-L., Darmawan, N., Ooi, K.-B., & Lee, V.-H. (2010). Determinants of 3G Adoption in Malaysia: A Structural Analysis. The Journal of computer Information Systems, 51(2), 71-80. Chou, C.H., Chang, S.B., Fan, C.J., & Guh, W.Y. (2004). An empirical study on the acceptance of the electronic tax filling. Electronic Commerce Studies, 2(4), 359-380. Churchill, G.A. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64-73. Citrin, A.V., Sprott, D.E., Silverman, S.N., & Stem, D.E. (2000). Adoption of Internet shopping: The role of consumer innovativeness. Industrial Management & Data System, 100(7) , 294-300. Coakes, S.J., & Steed, L.G. (2003). SPSS analysis without anguish. Brisbane Australia: John Wiley & Sons Australia, Ltd. Compeau, D.R., & Higgins, C.A. (1995).Computer Self-Efficacy : Development of a measure and initial test. MIS Quarterly, 19(2), 189-211. Compeau, D., & Higgins, C. (1991). The Development of a Measure of Computer Self-Efficacy. ASAC I99I Conference, (pp. 34-48). New York. Conchar, M.P., Zinkhan, G.M., Peters, C., & Olavarrieta, S. (2004). An Integrated Framework for the Conceptualization of Consumers‟ Perceived-Risk Processing. Journal of the Academy of Marketing Science, 32(4), 418-436. Cox, D.F., & Rich, S.V. (1964).Perceived risk and consumer decision making-the case of telephone shopping. Journal of Market Research, 1, 32-39. Crespo, A.H., & Rodriguez, I.A. (2008). Explaining B2C e-commerce acceptance: An integtrative model based on the framework by Gatignon and Robertson. Interacting with Computer, 20, 212-224. Crespo, A.H., del Bosque, I.R., & Sanchez, M.M. (2009). The influence of perceived risk on Internet shopping behavior: a multidimensional perspective. Journal of Risk Research, 12(2), 259–277. Crook, J. (2009). Mobile marketing industry to reach $50B by 2014: Study. Retrieved from Mobile Marketer: http://www.mobilemarketer.com Cui, G., Bao, W., & Chan, T.S. (2009). Consumers adoption of new technology products: The role of coping strategies. Journal Of Consumer Marketing, 26(2), 110-120. Davis, F.D. (1986). A technology acceptance model for empirically testing new end-user information systems. Theory and results. Doctoral dissertation, Sloan School of Management, Massachusetss Institute of Technology. Davis, F.D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340. Davis, F.D. (1993). User Acceptance of Information Technology: Sytem Characteristics, User Perceptions and Behavioral Impacts. International Journal Man- Machines Studies, 38, 475-487. Davis, F.D., Bagozzi, R.P., & Warshaw, P.R. (1992). Extrinsic and Intrinsic Motivation to use computers in the workplace. Journal of Applied Pscychology, 22(14), 1111-1132 Davis, F.D., Bagozzi, R.P., & Warshaw, P.R. (1989). User Acceptance of Computer Technology: A Comparison of Thwo Theoretical Models. Management Science, 982-1003. De Canniere, M.H., De Pelsmacker, P., & Geuens, M. (2009). Relationship Quality and the Theory of Planned Behavior models of behavioral intentions and purchase behavior. Journal of Business Research, 62, 82-92. DeBaillon, L., & Rockwell, P. (2005). Gender and student-status differences in cellular telephone use. International Journal of Mobile Communications, 3(1), 82-98. Dholakia, & Kshetri. (2002). The global digital divide and mobile business models: Identifying viable patterns of e-development. In S. Krishna, & S. Madon, Proceedings of the Seventh IFIP WG9.4 Conference (pp. 528-540). Bangalore, India. Dholakia, U.M. (2001). A motivational process model of product involvement and consumer risk perception. European Journal of Marketing, 35(11/12), 1340-1362. Dickinger, A., Arami, M., & Meyer, D. (2008). The role of perceived enjoyment and social norm in the adoption of technology with network externalities. European Journal of Information Systems, 17, 4-11. Dickinger, A., Haghirian, P., Murphy, J., & Scharl, A. (2004). An investigation and conceptual model of SMS marketing. Proceedings of 37th Annual Hawaii International Conference on System Sciences, (pp. 31-40). Hawai, USA. Dillon, A., & Morris, M.G. (1996). User acceptance of new information technology: theories and models. Annual Review of Information Science and Technology, 31, 3-32. Ding, L., Velicer, W.F., & Harlow, L.L. (1995). Effects of estimation methods, number of indicators per factor, and improper solutions on structural equation modeling fit indices. Structural Equation Modeling, 2(2), 119-143. Doll, W.J., Hendrickson, A., & Deng, X. (1998). Using Davis's perceived usefulness and ease of use instruments for decision making: A Confirmatory and multigroup invariance analysis. Decision Sciences, 29(4), 839-869. Dowling, G. R. (1986). Perceived risk: the concept and its measurement. Psychology & Marketing, 3, 193-210. Dowling, G.R., & Staelin, R. (1994). A model of perceived risk and intended riks-handling activity. Journal of Consumer Research, 21, 119-134. Earp, J.B., & Baumer, D.L. (2003). Innovative web use to learn about consumer behaviour and online privacy. Communication of the ACM, 46(4), 81-83. Etezadi-Amolo, J., & Farhoomand, A.F. (1996). A structural model of end user computing satifaction and user performance. Information & Management, 30(2), 65-73. Eu, G.T. (2009, November 30). Hello, young phone users. New Straits Times. Facchetti, A., Rangone, A., Renga, F. M., & Savoldelli, A. (2005). Mobile marketing: an analysis of key success factors and the European value chain. International Journal Management and Decision Making, 6(1), 65-80. Fan, Y., Saliba, A., Kendall, E.A., & Newmarch, J. (2005). Speech Interface: An Enhancer to the Acceptance of M- commerce Applications. 4th International Conference on. Sydney. Faziharudean, T.M., & Li-Ly, T. (2011). Consumers' behavioral intentions to use mobile data services in Malaysia. African Journal of Business Management, 5(5), 1811-1821. Featherman, M.S., & Pavlou, P.A. (2003). Predicting e-services adoption: a perceived risk facets perspective. International Journal Human-Computer Studies, 58, 451-474. Fishbein, M., & Ajzen, I. (1975).Belief, Attitude, Intention , Behavior: An Introduction to Theory and Research. Addison-Wesley. Flynn, L.R., & Goldsmith, R.E. (1993). Identifying innovators in consumer service markets. Service Industries Journal, 13(3), 97-109. Fornell, C., & Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. Forsythe, S.M., & Shi, B. (2003). Consumer patronage and risk perceptions in Internet shopping. Journal of Business Research, 56, 867-875. Gatignon, H., & Robertson, T.S. (1985). A Propositional inventory for new diffusion research. Journal of Consumer Research, 11, 849-867. Gefen, D., & Straub, D. (1997). Gender differences in the perception and use of E-mail: An extension to the Technology Acceptance Model. MIS Quarterly, 21(4), 389-400. Gefen, D., & Straub, D. (2000). The relative importance of perceived ease of use in IS adoption: A study of e-commerce. Journal of AIS, 1(8), 1-30. Geoffrey, H.T., Deans, K.R., & Gray, B.J. (2010). Third Screen Communication and the Adoption of Mobile Marketing: A Malaysia Perspective. International Journal of Marketing Studies, 2(1), 36-47. George, J.F. (2002). Influences on the internet to make internet purchases. Internet Research, 12(2), 165-180. George, J.F. (2004). The theory of planned behavior and Internet purchasing. Internet Research, 14(3), 198-212. Gerard, P., & Cunningham, J.B. (2003). The diffusion of Internet banking among Singapore consumers. International Journal of Bank Marketing, 21(1), 16-28. Ginzberg, M.J. (1981).Early diagnosis of MIS implemetation failure: promising results and unanswered questions. Management Science, 27, 459-478. Goldsmith, R.E. (2000). Identifying wine innovators: a test of the domain specific innovativeness scale using known groups. International Journal of Wine Marketing, 12(2), 37- 46. Goldsmith, R.E., & Hofacker, C.F. (1991).Measuring consumer innovativeness. Journal of the Academy of Marketing Science, 19(3), 209-221. Goldsmith, Ronald E; Goldsmith, Elizabeth B. (2002). Buying apparel over the Internet. Journal of Product & Brand Management, 11(2), 89-102. Gu, J.-C., Lee, S.-C., & Suh, Y.-H. (2009). Determinants of behavioral intention to mobile banking. Expert Systems with Applications, 36, 11605–11616. Ha, I., Yoon, Y., & Choi, M. (2007). Determinants of adoption of mobile games under mobile broadband wireless access environment. Information & Management, 44(3), 276-286 Ha, S., Chung, T.-L., Hamilton, J., & Park, J. (2010). Moving Beyond Acceptance:Exploring Determinants Of Consumer Use of Mobile Services. International Journal of Mobile Marketing, 5(2), 30-42. Hager, M.S., & Chatzisarantis, N.L. (2005). First and higher order models of attitudes, normative influence, and perceived behavioural control in the theory of planned behaviour. British journal of Social Psychology, 44(4), 513- 535. Hair, J.F., Black, W.C., Babin, B.J., & Anderson, R.E. (2010). Multivariate data analysis (7th ed). New Jersey: Pearson Prentice Hall. Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E., & Tatham, R.L. (2006). Multivariate Data Analysis (6th ed). New Jersey: Pearson International Edition. Hair, J., Anderson, R., Tatham, R., & Black, W. (1998). Multivariate Data Analysis. Upper Saddle River, New Jersey: Prentice Hall, Inc. Hanley, M., & Becker, M. (2008). Cell phone usage and advertising aceptance among college students. International journal of mobile marketing, 3(1), 67-80. Hanley, M., Becker, M., & Martinsen, J. (2006). Factors Influencing Mobile Advertising Accceptance:Will Incentives Motivate College Students to Accept Mobile Advertising? International Journal of Mobile Marketing, 1(1), 50-58. Hanudin, A. (2007). An analysis of mobile credit card usage intentions. Information Management & Computer Security, 15 (4), 260-269. Hanudin, A. (2009). An Analysis of online banking usage Intentions: An extension of the technology acceptance model . International Journal Business and Society, 10(1), 27-40. Hanudin, A. (2008). Factors affecting the intentions of customers in Malaysia to use mobile phone credit cards. Management Research News, 31(7), 495-503. Harrison, D.A., Mykytyn, P.P., & Riemenschneider, C.K. (1997). Executive decision about adoption of information technology in small businesses: Theory and empirical test. Information System Research, 8(2), 171-195. Hartley, C., Brecht, M., Pagery, P., Weeks, G., Chapanis, A., & Hoecker, D. (1977). Subjective time estimates of work tasks by office workers. Journal Occupational Psychology, 50, 23-36. Heijden, H.V. (2004).User acceptance of Hedonic information systems. MIS Quarterly, 28(4), 695-704. Heijden, H.V., Verhagen, T., & Creemers, M. (2003). Understanding online purchase intentions: Contributions from technology and trust perspectives. European Journal of Information Systems, 12(1), 41-48. Heinonen, K., & Strandvik, T. (2003). Consumer Responsiveness to Mobile Marketing. Proceedings of the Stockholm Mobility Roundtable, (pp. 1-17). Stockholm, Sweden. Herr, P.M., Kardes, F.R., & Kim, J. (1991). effects of word-of-mouth and product attribute information on persuasion: An accessibility diagnosticity perspective. Journal Consumer Research, 17(4), 454-462. Hong, S.-J., & Tam, K.Y. (2006). Understanding the adoption of multipurpose information appliances: The case of mobile data services. Information Systems Research, 17(2), 162-172. Hong, S.-J., Thong, Y.L., Moon, J.-Y., & Tam, K.-Y. (2008). Understanding the behavior of mobile data services consumers. Information System Frontier, 10, 431-445. Horton, R.P., Buck, T., Waterson, P.E., & Clegg, c.W. (2001) . Explaining intranet use with the technology acceptance model. Journal of Information Technology, 16, 237-249. Howcroft, B., Hamilton, R., & Hewer, P. (2002). Consumer attitude and the usage and adoption of home-based banking in the United Kingdom. The International Journal of Bank Marketing, 20(3), 111-121. Hsu, C.-L., & Lu, H.-P. (2004). Why do people play on-line games? An extended TAM with social influences and flow experience. Information & Management, 41, 853-868. Hsu, H.-H., Lu, H.-P., & Hsu, C.-L. (2008). Multimedia Messaging Service acceptance of pre- and post-adopters: a sociotechnical perspective. International Journal of Mobile Communications, 6(5), 598-614. Hsu, M.H., & Chiu, C.M. (2004). Internet self-efficacy and electronic service acceptance. Decision Support Systems, 38(3), 369-381. Hsu, T.-H., Wang, Y.-S., & Wen, S.C. (2006). Using the decomposed theory of planned behaviour to analyse consumer behavioural intention to use mobile coupons. Journal of Targeting, Measurement and Analysis for Marketing, 14(4), 309-324. Hu, J., Chau, Y.K., Sheng, R.L., & Tam, K.Y. (1999). Examining the Technology Acceptance Model Using Physician Acceptance of Telemedicine Technology. Journal of Management information Systems, 16(2), 91-112. Hu, L.T., & Bentler, P.M. (1999). Cutoff criteria for fit indexes in covariance structure. Structural Equation Modelling, 6(1), 1-55. Hung, S.-Y., Ku, C.-Y., & Chang, C.-M. (2003). Critical factors of WAP services adoption: an empirical study. Electronic Commerce Research and Applications, 2 (1), 42-60. Igbaria, M., Crag, N.Z., & Cavaye, A.L. (1997). Personal computing acceptance factors in small firms: A structural equation modelling. MIS Quarterly, 21(3), 279-305. Igbaria, M., Livari, J., & Maragahh, H. (1995). Why do individuals use computer technology? A finnish case study. Information & Management, 5, 227-238. Im, I., Kim, Y., & Han, H.J. (2008). The effects of perceived risk and technology type on users' acceptance of technologies. Information & Management, 45, 1-9. Isaac, S., & Micheal, W.B. (1990). Handbook in Research and Evaluation. San Diego, CA: Edits Publisher. ITU. (2009). 4.6 billion mobile subscriptions by the end of 2009. Retrieved from International Telecommunication Union: http://www.itu.int Jacob, J., & Kaplan, L. (1972). The components of perceived risk. Advances in Consumer Research, 3, 382-383. Jasman, J.M., Osman, M., & Ramayah, T. (2005). Intention to purchase via the internet. Asian Academy of Management Journal, 10(1), 79-95. Javernpaa, S.L., Tractinsky, N., & Vitae, M. (2000). Consumer trust in an Internet Store. Information Technology and Management, 1(1-2), 45-71. Jayasingh, S., & Eze, U.C. (2009). An Empirical Analysis of Consumer Behavioral Intention Toward Mobile Coupons in Malaysia. International Journal of Business and Information, 4(2), 221-242. Jayawardhena, C., Kuckertz, A., Karjaluoto, H., & Kautonen, T. (2009). Antecedents to permission based mobile marketing: an initial examination. European Journal of Marketing, 43(3/4), 473-499. Jin, C.H., & Villegas, J. (2008). Mobile Phone users' Behaviors: The Motivation factors of the mobile phone user. International Journal of Mobile Marketing, 3(2), 1-13. Junco, R., Merson, D., & Salter, D. W. (2010). The Effect of Gender, Ethnicity, and Income on College Students‟ Use of Communication Technologies. Cyberpsychology, Behavior, and Social Networking, 13(6), 619-627. Jung, K., & Kau, A.K. (2004). Culture's Influence on Consumer Behaviors: Differences Among Ethnic Groups in a Multiracial Asian Country. Advances in Consumer Research, 31, 366-372. Kalakota, R., & Robinson, M. (2002). M-business: The Race to Mobility. New York: McGraw- Hill. Kannan, P.K.-M. (2001). Wireless Commerce: Marketing Issues and Possibilities. Proceedings of the 34th Hawaii International Conference on System Sciences. Karahanna, E., Straub, D.W., & Chervany, N.L. (1999). Information technology adoption across time: A cross-sectional comparison of pre-adoption and post adoption beliefs. MIS Quarterly, 23(2), 183-213. Karjaluoto, H., & Alatalo, T. (2007). consumers' attitudes towards and intention to participate in mobile marketing. International Journal Service Technology and Management, 8 (2/3), 155-173. Karjaluoto, H., Leppaniemi, M., & Sinisalo, J. (2005). The role of mobile marketing in companies' promotion mix: empirical evidence from Finland. Journal of International Business and Economics, 2(1), 111-116. Karjaluoto, H., Leppaniemi, M., & Sinisalo, J. (2004). The role of mobile marketing in companies‟ promotion mix: empirical evidence from Finland. Journal of International Business and Economics, 2(1), 111-116. Kavassalis, P., Spyropoulou, N., Drossos, D., Mitrokostas, E., Gikas, G., & Hatzistamatiou, A. (2003). Mobile Permission Marketing: Framing the Market Inquiry. International Journal of Electronic Commerce, 8(1), 55-79. Kelloway, E.K. (1998). Using Lisrel for structural equation modelling. CA: International Educational and Professional Publisher: SAGE Publications. Khalifa, M., & Shen, K.N. (2008).Drivers for Transactional B2C M-Commerce Adoption: Extended Theory of Planned Behavior. Journal of Computer Information Systems, 111-117. Khalil, M.N., & Pearson, J.M. (2008). An Exploratory Study Into The Adoption of Internet Banking in a Developing Country: Malaysia. Journal of Internet Commerce, 7(1), 29- 73. Khan, M.N., & Allil, K. (2010). Determinants of mobile advertising adoption: A cross-country comparison of India and Syria. International Journal of Mobile Marketing, 5(1) , 41-59. Kim, C., Mirusmonov, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26, 310-322. Kim, D.J., Ferrin, D.L., & Rao, H.R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 44, 544-564. Kim, K., & Prabhakar, B. (2000). Initial trust, perceived risk, and the adoption of Internet banking. Proceedings of the 21st International Conference on Information Systems, (pp. 537-543). Kim, K., Kim, G.-M., & Kil, E.S. (2009). Measuring the conpatibility factors in mobile entertainment service adoption. The Journal of Computer Information Systems, 50(1) , 141-148. Kim, L.H., Kim, D.J., & Leong, J.K. (2005). The Effect of Perceived Risk on Purchase Intention in Purchasing Airline Tickets Online. Journal of Hospitality Marketing & Management, 13(2), 33-53. Kleijnen, M., Ruyter, K. d., & Wetzels, M. (2004). Consumer adoption of wireless services: Discovering the rules, while playing the game. Journal of Interactive Marketing, 18(2), 51-61. Knutsen, L., Constantiou, I.D., & Damsgaard, J. (2005). Acceptance and perceptions of advanced mobile services: Alterations during a field study. Proceedings International Conference on Mobile Business, (pp. 326-331). Sydney, Australia. Koivumaki, T., Ristolo, a., & Kesti, M. (2006). Predicting consumer acceptance in mobile services: empirical evidence from an experimental end user environment. International Journal Mobile Communications, 4(4), 418-435. Komulainen, H., Mainela, T., Sinisalo, J., Tahtinen, J., & Ulkuniemi, P. (2005). Models of Mobile Advertising Network. E-business Review, 5, 95-98. Korgaonkar, P. K., & Wolin, L. D. (1999). A multivariate analysis of Web usage. Journal Advertising Research, 39(2), 53-68. Kotler, P. (2003). Marketing Management. New Jersey: Prentice Hall. Koufaris, M. (2002). applying technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205-223. Ktoridou, D., Epaminonda, E., & Kaufmann, H.R. (2008). Technological challenges and consumer perceptions of the use of mobile marketing: Evidence from Cyprus. International Journal of Mobile Marketing, 3(2), 34-43. Kuo, Y.-F., & Yen, S.-N. (2009). Towards an understanding of the behavioral intention to use 3G mobile value-added services. Computers in Human Behavior, 25, 103-110. Kwon, H.S., & Chidambaram, L. (2000). A Test of the Technology Acceptance Model. The Case of Cellular Telephone Adoption. Proceedings of the 33rd Hawaii International Conference on System Sciences, (pp. 1-10). Lai, F.S., Chong, S.C., Sia, B.K., & Ooi, B.C. (2010). Culture and Consumer Behaviour: Comparisons between Malays and Chinese in Malaysia. International Journal of Innovation, Management and Technology, 1(2), 180-185. Lau, A.S. (2002). Strategies to Motivate Brokers Adopting On-line Trading in Hong Kong Financial Market. Review of Pacific Basin Financial Markets and Policies, 5(4), 471-489. Lederer, A.L., Maupin, D.J., Sena, M.P., & Zhuang, Y. (2000) . The technology acceptance model and the World Wide Web. Decision Support Systems, 29, 269–282. Lee, E.-J., Kwon, K.-N., & Schumann, D.W. (2005). Segmenting the non-adopter category in the diffusion of Internet banking. International Journal of Bank Marketing, 23(5), 414-437. Lee, H.Y., Lee, Y.K., & Kwon, D.W. (2005). The intention to use computerized reservation systems: The moderating effects of organizational support and supplier incentive. Journal of Business Research, 58(11), 1552-1561. Lee, H.Y., Qu, H., & Kim, Y.S. (2007). A study of the impact of eprsonal innovativeness on online travel behaviour- a case study of Korean travelers. Tourism Management, 28(3), 886-97. Lee, H.-H., & Lee, S.-E. (2010). Internet vs mobile services: comparisons of gender and ethnicity. Journal of Research in Interactive Marketing, 4(4), 346-375. Lee, K.S., & Lee, H.S. (2007). Factors Influencing the Adoption Behavior of Mobile Banking: A South Korean perspective. Journal of Internet Banking and Commerce, 12 (2), 1-10. Lee, M.S., McGoldrick, P.F., Keeling, K.A., & Doherty, J. (2003). Using ZMET to explore barriers to the adoption of 3G mobile banking services. International Journal of Retail & Distribution Management, 31(6), 340-348. Lee, M.-C. (2010). Explaining and predicting users' continuance intention toward e-learning: An extension of the expectation–confirmation model. Computers & Education, 54, 506-516. Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 40, 191-204. Leppaniemi, M., & Karjaluoto, H. (2005).Factors Influencing Consumers‟ to Accept Mobile Advertising: A Conceptual Model. International Journal of Mobile Communications, 3(3) , 197-213. Leppaniemi, M., Sinisalo, J., & Karjaluoto, H. (2006). A Review of Mobile Marketing Research. International Journal of Mobile Marketing, 1(1), 30-40. Lewis, W., Agarwal, R., & Sambamurthy, V. (2003). Sources of influence on beliefs about information technology use: An empirical study of knowledge. MIS Quarterly, 27(4), 657- 678. Li, S. S. (2004). Examining the factors that influence the intentions to adopt internet shopping and cable television shopping in Taiwan. New Media & Society, 6(2), 173-193. Li, S.S., & Yang, S.C. (2000). Internet shopping and its adopters: examining the factors affecting the adoption of Internet shopping. Paper presented at the 35th Anniversary Conference by the School of Journalism and Communication at the Chinese University of Hong Kong. Hong Kong. Li, Z., & Bai, X. (2010). Influences of Perceived Risk and System Usability on the Adoption of Mobile Banking Service. Proceedings of the Third International Symposium on Computer Science and Computational Technology(ISCSCT’ 10), (pp. 51-54). Jiaozuo, China. Liang, T.P., & Huang, J.S. (1998). An empirical study on consumer acceptance of products in electronic markets: a transaction cost model. Decision Support System, 24(1), 29- 43. Liao, C.H., Tsou, C.W., & Huang, M.F. (2007). Factors influencing the usage of 3G mobile services in Taiwan. Online Information Review, 31(6), 759-774. Liao, S., Shao, Y.P., Wang, H., & Chen, A. (1999). The adoption of virtual banking: An empirical study. International Journal of Information Management, 19(1), 63-74. Liao, Z., & Cheung, M.T. (2001). Internet-based e-shopping and consumer attitudes: an empirical study. Information & Management, 38, 299-306. Lim, N. (2003). Consumers‟ perceived risk: sources versus consequences. Electronic Commerce Research and Applications, 2, 216-228. Limayem, M., Khalifa, M., & Frini, A. (2000). What Makes Consumers Buy from Internet? A Longitudinal Study of Online Shopping. IEEE Transactions On Systems, Man, And Cybernetics—PART A: Systems And Humans, 30 (4), 421-432. Lin, C. C., & Lu, H. (2000). Towards understanding of the behavioural intention to use a web site. International Journal of Information Management, 20(3), 197-208. Lin, H.-F. (2008). Determinants of successful virtual communities: Contributions from system characteristics and social factors. Information & Management, 45, 522-527. Lin, H.-F. (2007). Predicting consumer intentions to shop online: An empirical test of competing theories. Electronic Commerce Research and Applications, 6, 433-442. Ling, R., & Yttri, B. (2002). Nobody sits at home and waits for the telephone to ring: Micro and hyper-coordination through the use of the mobile telephone. In J. Katz, & M.A. (eds), Perpetual Contact : Mobile communication, private talk, public performance. Cambridge: Cambridge University Press. Liu, Y., & Li, H. (2010). Mobile internet diffusion in China:an empirical study. Industrial Management & Data Systems, 110(3), 309-324. Loh, L., & Ong, Y. S. (1998). The adoption of Internet-based stock trading: a conceptual framework and empirical results. Journal Information Technology, 13(2), 81-94. Lu, J., Yao, J.E., & Yu, C.-S. (2005). Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. Journal of Strategic Information Systems, 14, 245-268. Lu, J., Yu, C.-s., Liu, C., & Yao, J.E. (2003). Technology acceptance model for wireless Internet. Internet Research: Electronic Networking Applications and Policy, 13(3), 206- 222. Lu, L., & Ling, S. (2009). Adoption intentions of Taiwanese passengers to use self check-in services on international flight routes. Journal Chinese Institute Transportation, 21 (3), 299-328. Lu, Y., Zhou, T., & Wang, B. (2009). Exploring Chinese users‟ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in Human Behavior, 25, 29-39. Luarn, P., & Lin, H.-H. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior, 21, 873-891. Luo, X., Li, H., Zhang, J., & Shim, J.P. (2010). Examining multi-dimensional trust and multi- faceted risk in initial acceptance of emerging technologies: An empirical study of mobile banking services. Decision Support Systems, 49, 222- 234. Malhotra, N.K., & McCort, J.D. (2001). A cross-cultural comparison of behavioral intention models: Theoretical consideration and an empirical investigation. International Marketing Review, 18(3), 235-269. Mallat, N., Rossi, M., Tuunainen, V.K., & mi, A.O. (2009). The impact of use context on mobile services acceptance: The case of mobile ticketing. Information & Management, 46, 190-195. Mao, E., Strite, M., Thatcher, J.B., & Yaprak, O. (2005). A research model for mobile phone service behaviors: empirical validation in the U.S. and Turkey. Journal of Global Information Technology Management, 8(4), 7-28. Mathieson, K. (1991). Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior. Information Systems Research, 2(3), 173-191. Mathieson, K., Peacock, E., & Chin, W.W. (2001). Extending the technology acceptance model: the influence of perceived user resources. DATA BASE for Advances in Information Systems, 32, 86-112. Matteson, M.T., Ivancevich, J.M., & Smith, S.V. (1984). Relation of type A behaviour to performance and satisfaction among sales personnel. Journal of Vocational Behaviour, 25, 203-214. McAllister, D.J. (1995). Affect and cognition baased trust as foundations for interpersonal cooperation in organizations. academy of Management Journal, 38(1), 24-59. MCMC. (2009). Communication and Multimedia selected facts and figures. Retrieved from http://www.skmm.gov.my MCMC. (2011). Number of cellular telephone subscriptions and penetration rate. Retrieved from http://www.skmm.gov.my Mitchell, V.-W. (1999). Consumer perceived risk: conceptualisations and models. European Journal of Marketing, 33(1/2), 163-195. Mitchell, V.-W. (1992). Understanding consumers' behavior. Can perceived risk theory help. Management Decision, 30(2), 26-31. Mitchell, V.-W., & Greatorex, M. (1990). Perceived risk and risk reducing strategies across product classification. Proceedings of 23rd MEG Conference, (pp. 940-955). Oxford. Mitchell, V.-W., & Greatorex, M. (1993). Risk perception and reduction in the purchase of consumer services. The Service Industries Journal, 13(4), 179-200. Miyazaki, A.D., & Fernandez, A. (2001). Consumer perceptions of privacy and security risks for online shopping. The Journal of Consumer Affairs, 35(1), 27-44. MMA. (2005). Code of Conduct for Global Marketing. Retrieved from http://www.mmaglobal.com MMA. (2009). MMA Updates Definition of Mobile Marketing. Retrieved from http://mmaglobal.com MMA, UK (2005). What is mobile marketing? Retrieved from http://www.mmaglobal.co.uk MoHE. (2009). Entrant and Enrolment of Students and Output of Graduates of Public Higher Education Institution (Public HEI) 2009-2010. Retrieved from www.mohe.gov.my. Moon, J.-W., & Kim, Y.-G. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38, 217- 230. Moore, G.C., & Benbasat, I. (1991). Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation. Information Systems Research, 3, 192-222. Morris, M.G., & Dillon, A. (1997). How User Perceptions Influence Software Use. IEEE Software, 14(4), 58-65. Muthaiyah, S. (2004). Key Success Factors of 3rd Generation Mobile Network Services for M-Commerce in Malaysia. American Journal of Applied Sciences, 1(4), 261-265. Mykytyn, P.P., & Harrison, D.A. (1993). The application of the theory of reasoned action to senior management and strategic information systems. Information Resources Management Journal, 6(2), 15-26. Ngai, E.W., & Gunasekaran, A. (2007). A review for mobile commerce research and applications. Decision Support Systems , 43, 3-15. Norazah, M.S. (2011). Factors Affecting Third Generation (3G) Mobile Service Acceptance: Evidence from Malaysia. Journal of Internet Banking and Commerce, 16(1), 1-12. Norazah, M.S., Ramayah, T., & Norbayah, M.S. (2008). Internet shopping acceptance. Examining the influence of intrinsic versus extrinsic motivations. Direct Marketing: An International, 2(2), 97-110. Nunnally, J.C. (1978). Psychometric Theory (2nd ed). New York: McGraw Hill Book Company. Nysveen, H., Pedersen, P.E., & Thorbjornsen, H. (2005). Intention to use mobile services: Antecedents and Cross-Service Comparisons. Journal of the Academy of Marketing Sciences, 33(3), 330-346. Olson, J.R., & Boyer, K.K. (2002). Technical note: factors influencing the utilization of internet purchasing in small organizations. Journal of Operations Management, 21(2), 225- 245. Ozdemir, S., & Trott, P. (2009). Exploring the adoption of a service innovation: A study of Internet banking adopters and non-adopters. Journal of Financial Services Marketing, 13(4), 284-299. Pagani, M. (2004). Determinants of Adoption of Third Generation Mobile Multimedia Services. Journal Of Interactive Marketing, 18(3), 46-59. Pallant, J. (2007). SPSS survival manual: a step by step guide to data analysis using SPSS for windows third edition. Open University press, Mc Graw Hill. Park, C., & Jun, J.-K. (2003). A cross-cultural comparison of Internet buying behavior. Effects of Internet usage, perceived risks, and innovativeness. International Marketing Review, 20(5), 534-553. Park, J., Lee, D., & Ahn, J. (2004).Risk-Focused E-Commerce Adoption Model: A Cross-Country Study. Journal of Global Information Technology Management, 7(2), 6-30. Park, Y., & Chen, J.V. (2007). Acceptance and adoption of the innovative use of smartphone. Industrial Management & Data Systems, 107(9), 1349-1365. Parthasarathy, M., & Bhattacherjee, A. (1998). Understanding post-adoption behavior in the context of online services. Information Systems Research, 9(4), 362-379 Pavlou, P.A. (2003). Consumer acceptance of Electronic Commerce: Integrating trust and risk with the technology acceeptance model. International Journal of Electronic Commerce, 7(3), 101-134. Pavlou, P.A., & Fygenson, M. (2006). Uunderstanding and predicting electronic commerce adoption:An extension of the theory of planned behavior. MIS Quarterly, 30(1), 115-143. Pavlou, P.A., & Gefen, D. (2004). Building effective online marketplaces with institution-based trust. Information Systems Research, 15(1), 35-62. Pavlou, P. (2001). Integrating trust in electronic commerce with the technology acceptance model; model development and validation. AMCIS Proceedings. Boston, MA. Pedersen, P.E. (2005). Adoption of Mobile Internet Services: An Exploratory Study of Mobile Commerce Early Adopters. Journal of Organizational Computing and Electronic Commerce, 15(2), 203-222. Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004). Consumer acceptance of online banking: an extension of the technology acceptance model. Internet Research, 14(3), 224-235. Plouffe, C.R., Hulland, J.S., & Vandenbosch, M. (2001). Research report: richness versus parsimony in modelling technology adoption decision-Understanding merchant adoption of a smart cardbased payment system. Information System Research, 12(2), 208-222. Polatoglu, V.N., & Ekin, S. (2001). An empirical investigation of the Turkish Consumers' acceptance of internet banking services. International Journal of Bank Marketing, 19(4), 156-165. Poon, W.C. (2008). Users' adoption of e-banking services: the Malaysian perspective. Journal of Business & Industrial Marketing, 23(1), 59-69. Quan, S. (2010). Factors Influencing the Adoption of Mobile Service in China: An Integration of TAM. Journal of Computers, 5(5), 799-806. Quan, S., Hao, C., & Jianxin, Y. (2010).Factors Influencing the Adoption of Mobile Service in China: An Integration of TAM. Journal of Computers, 5(5), 799-806. Ramayah, T., Rouibah, K., Gopi, M., & Rangel, G.J. (2009a). A decomposed theory of reasoned action to explain intention to use Internet stock trading among Malaysian investors. Computers in Human Behavior, 25, 1222-1230. Ramayah, T., Yusliza, M.Y., Norzalila, J., & Amlus, I. (2009b). Applying the Theory of Planned Behavior (TPB) to Predict Internet Tax Filing Intentions. International Journal of Management, 26(2), 272-284. Rao, S., & Troshani, I. (2007). A Conceptual Framework and Propositions for the Acceptance of Mobile Services. Journal of Theoretical and Applied Electronic Commerce Research, 2 (2), 61-73. Rettie, R., Grandcolas, U., & Deakins, B. (2005). Text message advertising: Response rates and branding effects. Journal of Targeting, Measurement and Analysis for Marketing, 13(4), 304-312. Rhodes, R.E., & Courneya, K.S. (2003). Investigating multiple components of attitude, subjective norm and perceived control: An examination of the theory of planned behaviour in the exercise domain. British Journal of Social Psychology, 42(1), 129-146. Roach, G. (2009). Consumer perceptions of mobile phone marketing: a direct marketing innovation. Direct Marketing: An International Journal, 3(2), 124-138. Roger, E.M. (1983).Diffusion of Innovations. New York: Free press. Roger, E.M. (1995).Diffusion of Innovations. New York: Free press. Rohm, A.J., & Sultan, F. (2006). An Exploratory Cross-Market Study of Mobile Marketing Acceptance. International Journal of Mobile Marketing, 1(1), 4-12. Roscoe, J.T. (1975). Fundamental research statistics for the behavioural science (2nd edition). New York: Holt, Rinehart & Winston. Rozario, M., Lewis, I., & White, K.M. (2010).An examination of the factors that influence drivers' willingness to use hand-held mobile phones. Transportation Research Part F: Traffic Psychology and Behaviour, 13(6), 365-376. Samsudin, W., Kaled, A.-M., & Nor Azila, M.N. (2010). The Relationship between E- Service Quality and Ease of Use On Customer Relationship Management (CRM) Performance: An Empirical Investigation In Jordan Mobile Phone Services. Journal of Internet Banking and Commerce, 15(1), 1-15. Sathye, M. (1999). Adoption of Internet banking by Australian consumers: an empirical investigation. International Journal of Bank Marketing, 17(7), 324-334. Scharl, A., Dickinger, A., & Murphy, J. (2005). Diffusion and success factors of mobile marketing. Electronic Commerce Research and Applications, 4, 159-173. Schierz, P.G., Schilke, O., & Wirtz, B.W. (2010). Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Research and Applications, 9, 209-216. Schumacker, R.E., & Lomax, R.G. (1996). A beginner's guide to structural equation modelling. NJ: Lawrence Erlbaum associates Publishers. Schwarzer, R., & Born, A. (1997). Optimistic self-beliefs: Assessment of general perceived self- efficacy in thirteen cultures . World Psychology, 3(1-2), 177-190. Sek, Y.-W., Lau, S.-H., Teoh, K.-K., Law, C.-Y., & Shahril, P. (2010). Prediction of User Acceptance and Adoption of Smart Phone for Learning with Technology Acceptance Model. Journal of applied Sciences, 10(20), 2395-2402. Sekaran, U. (2000). Research Methods for Business: A Skill-Building Approach. New York: John Wiley & Sons. Sekaran, U., & Bougie, R. (2010). Research methods for business: a skill building approach (5th edition). United Kingdom: John Wiley & Sons Ltd. Sheereen, N.Z., & Rozumah, B. (2009). Mobile Phone use Amongst Students in a University in Malaysia: Its Correlates and Relationship to Psychological Health. European Journal of Scientific Research, 37(2), 206-218. Shih, Y.-Y., & Fang, K. (2004). The use of a decomposed theory of planned behavior to study internet banking in Taiwan. Internet Research, 14(3), 213-223. Shim, S., Eastlick, M.A., Lotz, S.L., & Warrington, P. (2001). An online prepurchase intention model: the role of intention to search. Journal of Retailing, 77(3), 397-416. Shimp, T.A., & Kavas, A. (1984). The theory of reasoned action applied to coupon usage. Journal of Consumer Research, 11(3), 795-809. Shin, D.-H. (2009). Towards an understanding of the consumer acceptance of mobile wallet. Computers in Human Behavior, 25, 1343-1354. Shin, H.K., Kim, K.K., & Lee, K.W. (2009). Understanding the user acceptance of multimedia messaging services. Proceedings of the 11th International Conference on Advanced communication Technology, (pp. 1382-1385). Sim, J.J., Tan, G.W., Ooi, K.B., & Lee, a.V. (2011). Exploring the Individual Characteristics on the Adoption of Broadband: An Empirical Analysis. International Journal of Network and Mobile Technologies, 2(1), 1-14. Simpson, L., & Lakner, H.B. (1993). Perceived risk and mail order shopping for apparel. Journal of Consumer Studies and Home Economics, 17, 377-389. Smith, H.J., Milberg, J.S., & Burke, J.S. (1996). Information privacy: Measuring individuals' concerns about organizational practices. MIS Quarterly, 20(2), 167-196. Smith, J.H. (2004).Information privacy and its management. MIS Quarterly Executive, 3, 201-213. Smura, T., Kivi, A., & Toyli, J. (2009). A framework for analysing the usage of mobile services. The journal of policy, regulation and strategy for telecommunications, 11 (4), 53-67. Snell, S.A., & Dean, J.W. (1992). Integrated manufacturing and human resource management: A human capital perspective. Academy of Management Journal, 3, 467-504. Snowden, S., Spafford, J., Michaelides, R., & Hopkins, J. (2006). Technology acceptance and M-Commerce in an operational environment. Journal of Enterprise Information Management, 19(5), 525-539. Stewart, D.W., & Pavlou, 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. Stone, R.N., & Gronhaug, K. (1993). Perceived risk: further considerations for the marketing discipline. European Journal of Marketing, 27(3), 372-394. Suganthi, B., Balachandher, K., & Balanchandran, K. (2001). Internet banking patronage: an empirical investigation of Malaysia. Journal of Internet Banking and Commerce, 6(1), available at:www.arraydev.com/commerce/jibc. Suh, B., & Han, I. (2002). Effect of trust on customer acceptance of Internet banking. Electronic Commerce Research and Applications, 1, 247-263. Sullivan-Mort, G., & Drennan, J. (2002). Mobile digital technology: Emerging issues for marketing. Journal of Database Marketing, 10(1), 9-23. Sultan, F., Rohm, A.J., & Gao, T. (2009). Factors Influencing consumer Acceptance of Mobile Marketing. Journal of Interactive Marketing, 23(4), 308-320. Tahtinen, J. (2005). Mobile Advertising or Mobile Marketing. A Need for a New Concept. Proceedings of e-Business Research, (pp. 152-164). Tahtinen, J., & Salo, J. (2004). Special features of mobile advertising and their utilization. Proceedings of the 33rd EMAC Conference. Murcia, Spain. Tan, M., & Teo, S.H. (2000). Factors Influencing the Adoption of Internet Banking. Journal of the Association for Information Systems, 1(5), 1-42. Taylor, J.W. (1974).The role of risk in consumer behavior. Journal of Marketing, 38, 54-60. Taylor, S., & Todd, P.A. (1995a).Understanding Information Technology Usage: A Test of Competing Models. Information Systems Research, 6(2), 144-176. Taylor, S., & Todd, P. (1995b). Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions. International Journal of Research in Marketing, 12, 137-155. Teo, T.S., & Pok, S.H. (2003). Adoption of WAP-enabled mobile phones among Internet users. Omega : The International Journal of Management Science, 31, 483-498. Teo, T.S., Lim, V.K., & Lai, R.Y. (1999). Intrinsic and extrinsic motivation in Internet usage. Omega: The International Journal of Management Science, 27, 25-37. Torkzadeh, G., & Dhillon, N. (2002). Measuringfactors that influence the success of Internet Commerce. Information System Research, 2, 187-204. Triandis, H.C. (1980). Values, attitudes and interpersonal behavior. In H.E. Howe, & M.M. Page, Nebraska Symposium on Motivation 1979: 2, 195-295. Lincoln, NE: University of Nebraska Press. Truong, Y. (2009). An Evaluation of the Theory of Planned Behaviour in Consumer Acceptance of Online Video and Television Services. Electronic Journal Information Systems Evaluation Volume, 12(2), 177-186. Tsai, C.-Y. (2010). An analysis of usage intentions for mobile travel guide systems. African Journal of Business Management, 13, 2962-2970. Varnali, & Toker. (2010). Mobile marketing research: The-state-of-the-art. International Journal of Information Management, 30, 144-151. Varshney, U., & Vetter, R. (2000). Emerging Mobile and Wireless Networks. Communications of the ACM, 43(6), 73-83. Venkataraman, M.P. (1991). The impact of innovativeness and innovation type on adoption. Journal of Retailing, 67(1), 51-67. Venkatesh, V. (2000). Determinants of perceived ease of use: Integarating control, intrinsic motivation, and emotion into the technology acceptance model. Information System Research, 11(4), 342-365. Venkatesh, V., & Brown, S. A. (2001). A Longitudinal investigation of personal computers in homes: adoption determinants and emerging challenges. MIS Quarterly, 25(1) , 71-102. Venkatesh, V., & Davis, F.D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451-481. Venkatesh, V., & Davis, F.D. (2000).A Theoretical Extension of The Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186-204. Venkatesh, V., & Morris, M.G. (2000). Why dont men ever stop to ask for directions? Gender, social influence and their role in Technology Acceptance and Usage behavior. MIS Quarterly, 24(1), 115-139. Venkatesh, V., Morris, M.G., & Ackerman, P.L. (2000). A Longitudinal Field Investigation of Gender Differences in Individual Technology Adoption Decision-Making Processes. Organizational Behavior and Human Decision Processes, 83(1) , 33–60. Venkatesh, V., Morris, M.G., Davis, G.B., & Davis, F.D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 427-478. Venkatesh, V., Speier, C., & Morris, M.G. (2002). Decision Sciences, 33(2), 297-316. Vijayasarathy, L.R. (2004). Predicting consumer intentions to use on-line shopping: the case for an augmented technology acceptance model. Information & Management, 41, 747-762. Vijayasarathy, L.R., & Jones, J.M. (2000). Print and Internet catalog shopping: Assessing attitudes and intentions. Internet Research: Networking Applications and Policy, 10(3), 191-202. Wang, Y.-S., & Liao, Y.-W. (2008). Understanding Individual Adoption of Mobile Booking Service: An Empirical Investigation. Cyberpsychology & Behavior, 11(5), 603-605. Wang, Y.-S., Lin, H.-H., & Luarn, P. (2006). Predicting consumer intention to use mobile service. Information Systems Journal, 16, 157-179. Wang, Y.-S., Wang, Y.-M., Lin, H.-H., & Tang, T.-I. (2003). Determinants of user acceptance of Internet banking: an empirical study. International Journal of Service Industry Management, 14(5), 501-519. Warrington, T.B., Abgrab, N.J., & Caldwell, H.M. (2000). Building trust to develop competitive advantage in e-business relationships. Competitiveness Review, 10(2), 160-168. Wei, T.T., Marthandan, G., Chong, A.Y.-L., Ooi, K.-B., & Arumugam, S. (2009). What drives Malaysian m-commerce adoption? An empirical analysis. Industrial Management & Data System, 109 (3), 370-388. Wheaton, B., Muthen, B., Alwin, D.F., & Summers, G. (1977). Assessing reliability and stability in panel models. Sociological Methodology, 8(1), 84-136. Wong, C.C., & Hiew, P.L. (2005). Diffusion of Mobile Entertainment in Malaysia: Drivers and Barriers. World Academy of Science, Engineering and Technology, 5, 135-138. Wu, J.-H., & Wang, S.-C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information & Management, 42, 719-729. Xia, W., & King, W.R. (1996). Interdependencies between the determinants of user interaction and usage: An empirical test. proceeding ICIS, (pp. 1-21). Cleveland. Yaghoubi, N.-M., & Bahmani, E. (2011). Factors Affecting the Adoption of Online Banking: An Integration of Technology Acceptance Model and Theory of Planned Behavior. International Journal of Business and Management, 5(9), 159- 165. Yang, D.J., Kao, M.R., & Guo, S.M. (2007). Behavior intention of citizens to participate in forest ecosystem management at the Liukuei experimental forest in Kaohsiung. Taiwan Journal Forest Science, 22(4), 381-398. Yang, K.C. (2005). Exploring factors affecting the adoption of mobile commerce in Singapore. Telematics and Informatics, 22(3), 257-277. Yang, Y., & Zhang, J. (2009). Discussion on the Dimensions of Consumers‟ Perceived Risk in Mobile Service. Eighth International Conference on Mobile Business, (pp. 261-266). Yi, M.Y., Fiedle, K.D., & Park, J.S. (2006). Understanding the role of individual innovativeness in the acceptance of IT-based innovations: comparative analyses of models and measures . Decision Sciences, 37(3), 393-426. Yoh, E., Damhorst, M.L., Sapp, S., & Laczniak, R. (2003). Consumer Adoption of the Internet: The Case of Apparel Shopping. Psychology & Marketing, 20(12), 1095-1118. Yun, H., Lee, C.C., Kim, B.G., & Kettinger, W.J. (2011). What Determines Actual Use of Mobile Web Browsing Services? A Contextual Study in Korea. Communications of the Association for Information Systems, 28(1), 313-328. Yun, H., Lee, C.C., Kim, B.G., & Kim, B.G. (2011). What Determines Actual Use of Mobile Web Browsing Services? A Contextual Study in Korea. Communications of the Association for Information Systems, 28(1), 313-328. Yunos, H.M., Gao, J.Z., & Shim, S. (2003). Wireless Advertising's Challenges and Opportunities. IEEE Computer, 36(5), 30-37. Zikmund, W.G. (2000). Business research methods. Orlando: Dryden Press.

Factors Influencing Consumers' Acceptance of Mobile Marketing Services

Similar Items