Mobile Information Systems: An Empirical Analysis of the Determinants of Mobile Commerce Acceptance in Jordan

Although mobile commerce have been used and widely researched in developed nations, there is a low usage in the Arab world. Also, there is a limited empirical research on mobile commerce in Jordan despite the high penetration of mobile phone subscribers in 2009. Among the aims of this quantitative r...

Full description

Saved in:
Bibliographic Details
Main Author: Al-Najjar, Ghassan M.
Format: Thesis
Language:eng
eng
Published: 2012
Subjects:
Online Access:https://etd.uum.edu.my/3269/1/GHASSAN_M.AL-NAJJAR.pdf
https://etd.uum.edu.my/3269/2/GHASSAN_M.AL-NAJJAR.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-uum-etd.3269
record_format uketd_dc
institution Universiti Utara Malaysia
collection UUM ETD
language eng
eng
advisor Mahmuddin, Massudi
topic HF5548.34 Mobile Commerce
spellingShingle HF5548.34 Mobile Commerce
Al-Najjar, Ghassan M.
Mobile Information Systems: An Empirical Analysis of the Determinants of Mobile Commerce Acceptance in Jordan
description Although mobile commerce have been used and widely researched in developed nations, there is a low usage in the Arab world. Also, there is a limited empirical research on mobile commerce in Jordan despite the high penetration of mobile phone subscribers in 2009. Among the aims of this quantitative research is to empirically investigate the determinants of mobile commerce adoption in a collectivist culture such as Jordan where social norms are valued and individual actions are influenced greatly by important reference groups. The Technology Acceptance Model (TAM) is extended to include four factors (facilitating conditions, cost, personal innovativeness in IT (PIIT) and subjective norms). Furthermore, in order to understand subjective norms in collectivist culture; subjective norms were decomposed into different levels (personal and societal injunctive and descriptive norms). The research framework consists of twelve latent variables (seven exogenous and five endogenous). Using self-administered survey, 40 items with 7-point Likert scale is used to collect data. Out of the 500 samples, 448 responses (89.6 % response rate) were collected; eventually 401 responses were usable. Structural Equation Modeling is applied to analyze the data. The findings of this study revealed that facilitating conditions, cost, PIIT, attitude and perceived usefulness are significant determinants of behavioral intention in Jordan. In addition, subjective norms, facilitating conditions, cost and perceived ease of use are significant antecedents of attitude which in turn influencing behavioral intention. Moreover, the empirical evidence indicated that personal injunctive norm, personal descriptive norm and societal injunctive norm are indeed antecedents of subjective norms. It can be concluded that extended TAM successfully enriched the model and increased the exploratory power to 53% in explaining behavioral intention variance.
format Thesis
qualification_name Ph.D.
qualification_level Doctorate
author Al-Najjar, Ghassan M.
author_facet Al-Najjar, Ghassan M.
author_sort Al-Najjar, Ghassan M.
title Mobile Information Systems: An Empirical Analysis of the Determinants of Mobile Commerce Acceptance in Jordan
title_short Mobile Information Systems: An Empirical Analysis of the Determinants of Mobile Commerce Acceptance in Jordan
title_full Mobile Information Systems: An Empirical Analysis of the Determinants of Mobile Commerce Acceptance in Jordan
title_fullStr Mobile Information Systems: An Empirical Analysis of the Determinants of Mobile Commerce Acceptance in Jordan
title_full_unstemmed Mobile Information Systems: An Empirical Analysis of the Determinants of Mobile Commerce Acceptance in Jordan
title_sort mobile information systems: an empirical analysis of the determinants of mobile commerce acceptance in jordan
granting_institution Universiti Utara Malaysia
granting_department Awang Had Salleh Graduate School of Arts & Sciences
publishDate 2012
url https://etd.uum.edu.my/3269/1/GHASSAN_M.AL-NAJJAR.pdf
https://etd.uum.edu.my/3269/2/GHASSAN_M.AL-NAJJAR.pdf
_version_ 1747827534623408128
spelling my-uum-etd.32692022-04-10T06:08:26Z Mobile Information Systems: An Empirical Analysis of the Determinants of Mobile Commerce Acceptance in Jordan 2012 Al-Najjar, Ghassan M. Mahmuddin, Massudi Awang Had Salleh Graduate School of Arts & Sciences Awang Had Salleh Graduate School of Arts & Sciences HF5548.34 Mobile Commerce Although mobile commerce have been used and widely researched in developed nations, there is a low usage in the Arab world. Also, there is a limited empirical research on mobile commerce in Jordan despite the high penetration of mobile phone subscribers in 2009. Among the aims of this quantitative research is to empirically investigate the determinants of mobile commerce adoption in a collectivist culture such as Jordan where social norms are valued and individual actions are influenced greatly by important reference groups. The Technology Acceptance Model (TAM) is extended to include four factors (facilitating conditions, cost, personal innovativeness in IT (PIIT) and subjective norms). Furthermore, in order to understand subjective norms in collectivist culture; subjective norms were decomposed into different levels (personal and societal injunctive and descriptive norms). The research framework consists of twelve latent variables (seven exogenous and five endogenous). Using self-administered survey, 40 items with 7-point Likert scale is used to collect data. Out of the 500 samples, 448 responses (89.6 % response rate) were collected; eventually 401 responses were usable. Structural Equation Modeling is applied to analyze the data. The findings of this study revealed that facilitating conditions, cost, PIIT, attitude and perceived usefulness are significant determinants of behavioral intention in Jordan. In addition, subjective norms, facilitating conditions, cost and perceived ease of use are significant antecedents of attitude which in turn influencing behavioral intention. Moreover, the empirical evidence indicated that personal injunctive norm, personal descriptive norm and societal injunctive norm are indeed antecedents of subjective norms. It can be concluded that extended TAM successfully enriched the model and increased the exploratory power to 53% in explaining behavioral intention variance. 2012 Thesis https://etd.uum.edu.my/3269/ https://etd.uum.edu.my/3269/1/GHASSAN_M.AL-NAJJAR.pdf text eng public https://etd.uum.edu.my/3269/2/GHASSAN_M.AL-NAJJAR.pdf text eng public http://sierra.uum.edu.my/record=b1239811~S1 Ph.D. doctoral Universiti Utara Malaysia Abu-Samaha, A., & Mansi,I. (2007). Information Technology Diffusion in the Jordanian Telecom Industry Organizational Dynamics of Technology-Based Innovation: Diversifying the Research Agenda. In T. McMaster, D. Wastell, E. Ferneley & J. DeGross (Eds.), (Vol. 235, pp. 431-442): Springer Boston. AbuShanab, E., Pearson, J.M., & Setterstrom, A.J. (2010). Internet banking and customers’ acceptance in Jordan: The unified model’s perspective. Communications of the Association for Information Systems, 26(1), 23. Agarwal, R., & Prasad ,J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204-215. Ajzen,I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211. Al-Gahtani, S.S., Hubona, G.S., & Wang, J. (2007). Information technology (IT) in Saudi Arabia: Culture and the acceptance and use of IT. Information & Management, 44(8), 681-691. Al-Jaghoub, S., & Westrup, C. (2003). Jordan and ICT-led development: towards a competition state? Information Technology & People, 16(1), 93-110. Al-Khasawneh, A.M. (2010). Mobile computing in Jordan: a roadmap to wireless. International Journal of Information Technology and Management, 9(3), 260-272. Aldás-Manzano, J., Ruiz-Mafé, C., & Sanz-Blas, S. (2009). Exploring individual personality factors as drivers of M-shopping acceptance. Industrial Management & Data Systems, 109(6), 739-757. AlHinai, Y., Kurnia, S., & Johnston, R. (2007). Adoption of Mobile Commerce Services by Individuals: A Meta-Analysis of the Literature. Paper presented at the International Conference on the Management of Mobile Business, ICMB 2007, Washington, DC,USA. Almutairi, H. (2007). Is the “Technology Acceptance Model” Universally Applicable?: The Case of the Kuwaiti Ministries. Journal of Global Information Technology Management, 10(2), 57-80. 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.E., & Schwager, P.H. (2004). SME adoption of wireless LAN technology: Applying the UTAUT Model. Paper presented at the 7th Annual Conference of the Southern Association for Information Systems. Savannah, GA, USA. Atlastours.net. (2008). Jordan Map & Sites. Available from http://www.atlastours.net/jordan/sites.html/ Accessed 10.05.2011. Bagozzi, R.P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94. Bandyopadhyay, K., & Fraccastoro, K.A. (2007). The Effect of Culture on User Acceptance of Information Technology. Communications of AIS, 2007(19), 522-543. Bannister, J., Mather, P., & Coope, S. (2004). Convergence technologies for 3G networks: IP, UMTS, EGPRS and ATM: John Wiley & Sons Inc. Barnes, S.J., & Huff, S.L. (2003). Rising sun: iMode and the wireless Internet. Communications of the ACM, 46(11), 78-84. Basole, R.C. (2006). Modeling and analysis of complex technology adoption decisions: An investigation in the domain of mobile ICT (PhD Dissertation, Georgia Institute of Technology ). Retrieved from http://etd.gatech.edu/theses/ available/etd-06162006-142751/. Benbasat,I., & Barki,H. (2007). Quo vadis TAM? Journal of the Association for Information Systems, 8(4), 16. 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. Biljon,J.v., & Kotzé,P. (2008). Cultural factors in a mobile phone adoption and usage model. Journal of Universal Computer Science, 14(16), 2650-2679. Bradley,J. (2009). The Technology Acceptance Model and Other User Acceptance Theories. Handbook of research on contemporary theoretical models in information systems research, 277-294. Brislin,R.W. (1970). Back-translation for cross-cultural research. Journal of cross-cultural psychology, 1(3), 185. Brown,T.A. (2006). Confirmatory factor analysis for applied research. New York, NY: The Guilford Press. Byrne,B.M. (2010). Structural equation modeling with AMOS: Basic concepts, applications, and programming. New York, NY: Taylor & Francis Group. 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. Charbaji,R., Rebeiz,K., & Sidani,Y. (2009). Antecedents and Consequences of the Risk Taking Behavior of Mobile Commerce Adoption in Lebanon. Handbook of Research on E-Government Readiness for Information and Service Exchange: Utilizing Progressive Information Communication Technologies, 354-380. Chau,P.Y.K., & Hu,P.J.-H. (2001). Information Technology Acceptance by Individual Professionals: A Model Comparison Approach. Decision Sciences, 32(4), 699-719. Chen,J.V., Yen,D.C., & Chen,K. (2009). The acceptance and diffusion of the innovative smart phone use: A case study of a delivery service company in logistics. Information & Management, 46(4), 241-248. Cheong,J.H., & Park,M.C. (2005). Mobile internet acceptance in Korea. Internet Research, 15(2), 125-140. Cheung,W., Chang,M.K., & Lai,V.S. (2000). Prediction of Internet and World Wide Web usage at work: a test of an extended Triandis model. Decision Support Systems, 30(1), 83-100. Chong,A.Y.L., Darmawan,N., Ooi,K.B., & Lee,V.H. (2010). Determinants of 3G adoption in Malaysia: A structural analysis. Journal of Computer Information Systems, 51(2), 71. CIA. (2011). The World Factbook. Retrieved July 5, 2011, from https://www.cia.gov/library/publications/the-world-factbook/geos/jo.html Ciborra, C., & Navarra, D.D. (2005). Good governance, development theory, and aid policy: Risks and challenges of e-government in Jordan. Information Technology for Development, 11(2), 141-159. Crabbe, M., Standing, C., Standing, S., & Karjaluoto, H. (2009). An adoption model for mobile banking in Ghana. International Journal of Mobile Communications, 7(5), 515-543. Dai,H., & Palvia,P.C. (2009). Mobile commerce adoption in China and the United States: a cross-cultural study. The DATA BASE for Advances in Information Systems, 40(4), 43-61. 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., Bagozzi,R.P., & Warshaw,P.R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management science, 35(8), 982-1003. De Vaus, D.A. (2002). Surveys in social research (5 ed.). Crows Nest, Australia: Routledge London. Diab, S. (2011). Jordan Telecom. Retrieved February 7, 2011, from http://www.rasmala.com/equity_report/Jordan_ Telecom_04Jan11.pdf 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. Dutta,S., & Mia,I. (2009). The Global Information Technology Report 2008–2009, Mobility in a Networked World. Retrieved July 1, 2010, from https://members.weforum.org/pdf/ gitr/2009/gitr09fullreport.pdf Eckhardt,A., Laumer,S., & Weitzel,T. (2009). Who influences whom Analyzing workplace referents social influence on IT adoption and non-adoption. Journal of Information Technology, 24(1), 11-24. Er,M., & Kay,R. (2005). Mobile technology adoption for mobile information systems: An activity theory perspective. Paper presented at the International Conference on Mobile Business (ICMB’05), Sydney, Australia Feng, H., Hoegler, T., & Stucky, W. (2006). Exploring the critical success factors for mobile commerce. Paper presented at the International Conference on Mobile Business (ICMB’06), Copenhagen, Denmark. Field, A.P. (2009). Discovering statistics using SPSS (3 ed.). Thousand Oaks, CA: SAGE Publications Inc. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley. Gefen, D., Karahanna, E., & Straub, D.W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51-90. Goi,C.L. (2008). Review on the Implementation of Mobile Commerce in Malaysia. Journal of Internet Banking and Commerce, 13(2), 2008-2008. Grandón, E.E., Nasco, S.A., & Mykytyn Jr, P.P. (2011). Comparing theories to explain e-commerce adoption. Journal of Business Research, 64(3), 292-298. Gu, J.-C., Lee, S.-C., & Suh, Y.-H. (2009). Determinants of behavioral intention to mobile banking. Expert Systems with Applications, 36(9), 11605-11616. Gunasekaran, A., & McGaughey, R.E. (2009). Mobile commerce: issues and obstacles. International Journal of Business Information Systems, 4(2), 245-261. 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. Hagger, M.S., & Chatzisarantis, N.L.D. (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.). Saddle River, NJ: Prentice-Hall International. Hill, C.E., Loch, K.D., Straub, D.W., & El-Sheshai, K. (1998). A qualitative assessment of Arab culture and information technology transfer. Journal of Global Information Management, 6(3), 29-38. Hofstede, G. (2009). Geert Hofstede’s Cultural Dimensions. Retrieved January 19, 2011, from http://www.clearlycultural.com/geert-hofstede-cultural-dimensions/ Hong,S.-J., Thong,J., Moon,J.-Y., & Tam,K.-Y. (2008). Understanding the behavior of mobile data services consumers. Information Systems Frontiers, 10(4), 431-445. 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), 162-179. Hosni,N.A., Ali,S., & Ashrafi,R. (2010). The key success factors to mobile commerce for Arab countries in Middle East. Paper presented at the Proceedings of the 12th International Conference on Information Integration and Web-based Applications & Services. Hu,W.C., Lee,C.W., & Kou,W. (2005). Advances in security and payment methods for mobile commerce. Hershey, PA: Idea Group Publication. ICT-Jordan. (2007). National ICT Strategy of Jordan 2007-2011. Retrieved June, 2010, from http://www.intaj.net/sites/default/files/ National-ICT-Strategy-of-Jordan-2007-2011.pdf ITP.net. (2008).UAE leads the Middle East in ICT readiness. Retrieved March 1, 2010, from http://www.itp.net/518509-uae-leads-the-middle-east-in-ict-readiness ITU. (2009). The Information Society Statistical Profles 2009: Arab States. Available from http://www.itu.int/dms_pub/itu-d/opb/ind/D-IND-RPM.AR-2009-R1-PDF-E.pdf. ITU. (2010a). Measuring the Information Society. Retrieved May 10, 2010, from http://www.itu.int/ITU-D/ict/publications/idi/ 2010/Material/MIS_2010_without_annex_4-e.pdf ITU. (2010b). The World in 2010: ICT Facts Figures. Retrieved March 25, 2011, from http://www.itu.int/ITU-D/ict/material/Facts Figures2010.pdf ITU. (2011). Measuring the Information Society Retrieved October 6, 2011, from http://www.itu.int/net/pressoffice/backgrounders/general/pdf/5.pdf Jayasingh,S., & Eze,U.C. (2010). The role of Moderating Factors in Mobile Coupon Adoption: An extended TAM Perspective. Communications of the IBIMA, 2010, 1-13. Kanaan,R.K. (2009). Making Sense of E-government Implementation in Jordan: A Qualitative Investigation, PhD Thesis, Faculty of Information Technology,De Montfort University, UK 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. Kargin,B., & Basoglu,N. (2006). Adoption factors of mobile services. Paper presented at the International Conference on Mobile Business ICMB '06, Copenhagen, 41-41. Khalifa, M., & Shen, K.N. (2008a). Drivers for transactional B2C m-commerce adoption: extended theory of planned behavior. Journal of Computer Information Systems, 48(3), 111-117. Khalifa, M., & Shen, K.N. (2008b). Explaining the adoption of transactional B2C mobile commerce. Journal of Enterprise Information Management, 21(2), 110-124. Khasawneh, A.M. (2009). The key success to mobile internet in the Middle East: wireless set to take the lead. International Journal of Business Information Systems, 4(4), 477-488. Khawam, N., & Saadi, T.A. (2009). Orange Jordan signs agreement with Ericsson to launch 3G mobile services in Q1 2010. Retrieved February 5, 2010, from http://jordantelecomgroup.jo/jtg/group/press.php Kim,B., Choi,M., & Han,I. (2009a). User behaviors toward mobile data services: The role of perceived fee and prior experience. Expert Systems with Applications, 36(4), 8528-8536. Kim, C., Mirusmonov, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310-322. Kim,J., Ma,Y.J., & Park,J. (2009b). Are US consumers ready to adopt mobile technology for fashion goods? An integrated theoretical approach. Journal of Fashion Marketing and Management, 13(2), 215-230. Kim,S., & Garrison,G. (2009). Investigating mobile wireless technology adoption: An extension of the technology acceptance model. Information Systems Frontiers, 11(3), 323-333. Koenig-Lewis, N., Palmer, A., & Moll, A. (2010). Predicting young consumers' take up of mobile banking services. International Journal of Bank Marketing, 28(5), 410-432. Krogstie, J. (2009). Usable M-Commerce Systems. Encyclopedia of Information Science and Technology, Second Edition (pp. 3904-3908): IGI Global. 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(1), 103-110. Laudon, K.C., & Laudon, J.P. (2004). Management information systems (8 ed.). New Jersey: Pearson Prentice Hall. Lee, Y., Lee, J., & Lee, Z. (2006). Social influence on technology acceptance behavior: self-identity theory perspective. SIGMIS Database, 37(2-3), 60-75. Li, Y., Fu, Z.T., & Li, H. (2007). Evaluating factors affecting the adoption of mobile commerce in agriculture: An empirical study. New Zealand Journal of Agricultural Research, 50(5), 1213-1218. Liang, H., Xue, Y., & Byrd, T.A. (2003). PDA usage in healthcare professionals: testing an extended technology acceptance model. International Journal of Mobile Communications, 1(4), 372-389. Liang, T.P., & Yeh, Y.H. (2011). Effect of use contexts on the continuous use of mobile services: the case of mobile games. Personal and Ubiquitous Computing, 15(2), 187-196. 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. Liu, D.S., & Chen, W. (2009). An Empirical Research on the Determinants of User M-Commerce Acceptance Software Engineering, Artificial Intelligence, Networking and Parallel/ Distributed Computing. In R.Lee & N.Ishii (Eds.), (Vol. 209, pp. 93-104): Springer Berlin/ Heidelberg. Liu,Y., & Li,H. (2011). Exploring the impact of use context on mobile hedonic services adoption: An empirical study on mobile gaming in China. Computers in Human Behavior, 27(2), 890-898. Loch,K.D., Straub,D.W., & Kamel,S. (2003). Diffusing the Internet in the Arab world: The role of social norms and technological culturation. IEEE Transactions on Engineering Management, 50(1), 45-63. López-Nicolás, C., Molina-Castillo, F.J., & Bouwman, H. (2008). An assessment of advanced mobile services acceptance: Contributions from TAM and diffusion theory models. Information & Management, 45(6), 359-364. Lu, H.P., & Su, P.Y.J. (2009). Factors affecting purchase intention on mobile shopping web sites. Internet Research, 19(4), 442-458. Lu, J., Liu, C., Yu, C.S., & Wang, K. (2008). Determinants of accepting wireless mobile data services in China. Information & Management, 45(1), 52-64. Lu, J., Yao, J.E., & Yu, C.-S. (2005). Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. The Journal of Strategic Information Systems, 14(3), 245-268. Lu, J., Yu, C.S., Liu, C., & Yao, J.E. (2003). Technology acceptance model for wireless Internet. Internet Research, 13(3), 206-222. Lu,Y., Deng,Z., & Wang,B. (2010). Exploring factors affecting Chinese consumers' usage of short message service for personal communication. Information Systems Journal, 20(2), 183-208. Luarn, P., & Lin, H.-H. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior, 21(6), 873-891. Malhotra, Y., & Galletta, D.F. (1999). Extending the technology acceptance model to account for social influence: theoretical bases and empirical validation. Paper presented at the Thirty-Second Annual Hawaii International Conference on System Sciences , Hawaii,USA. Mallat, N., Rossi, M., Tuunainen, V.K., & O¨orni, A. (2008). An empirical investigation of mobile ticketing service adoption in public transportation. Personal Ubiquitous Comput., 12(1), 57-65. Mallat, N., Rossi, M., Tuunainen, V.K., & Öörni, A. (2009). The impact of use context on mobile services acceptance: The case of mobile ticketing. Information & Management, 46(3), 190-195. Manochehri, N.N., & AlHinai, Y.S. (2008). Mobile-phone users’ attitudes towards’ mobile commerce & services in the Gulf Cooperation Council countries: Case study. Paper presented at the 2008 International Conference on Digital Object Identifier, Doha, Qatar. Mao, E., Srite, M., Thatcher, J., & Yaprak, O. (2005). A research model for mobile phone service behaviors: empirical validation in the US and Turkey. Journal of Global Information Technology Management, 8(4), 7-27. 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. SIGMIS Database, 32(3), 86-112. Min, Q., Ji, S., & Qu, G. (2008). Mobile Commerce User Acceptance Study in China: A Revised UTAUT Model. Tsinghua Science & Technology, 13(3), 257-264. Mofleh,S.I. (2008). Developing countries and ICT initiatives: lessons learnt from Jordan’s experience. The Electronic Journal of Information Systems in Developing Countries, 34(5), 1-17. Mohd, F., & Osman, S. (2005). Towards the Future of Mobile Commerce (M-Commerce) in Malaysia. Paper presented at the Proceedings of IADIS: IADIS International Conference, Web based Communities 2005, Algarve, Portugal. MOHE. (2010). Statistics. Retrieved March 1, 2011, from http://www.mohe.gov.jo/Statistics2010/tabid/579/language/en-US/Default.aspx Myers,J.L., & Well,A. (2003). Research design and statistical analysis (2 ed.). Mahwah, NJ: Lawrence Erlbaum. Mylonopoulos,N.A., Doukidis,G.I., & Editors,G. (2003). Introduction to the Special Issue: Mobile Business: Technological Pluralism, Social Assimilation, and Growth. International Journal of Electronic Commerce, 8(1), 5-22. Ngai, E., Poon, J., & Chan, Y. (2007). Empirical examination of the adoption of WebCT using TAM. Computers & Education, 48(2), 250-267. Ngai, E.W.T., & Gunasekaran, A. (2007). A review for mobile commerce research and applications. Decision Support Systems, 43(1), 3-15. Nguyen,T.D., & Barrett,N.J. (2006). The adoption of the internet by export firms in transitional markets. Asia Pacific Journal of Marketing and Logistics, 18(1), 29-42. Nysveen, H., Pedersen, P., & Thorbjørnsen, H. (2005a). Explaining intention to use mobile chat services: moderating effects of gender. Journal of Consumer Marketing, 22(5), 247-256. Nysveen, H., Pedersen,P., & Thorbjørnsen,H. (2005b). Intentions to use mobile services: Antecedents and cross-service comparisons. Journal of the Academy of Marketing Science, 33(3), 330-346. Ondrus, J., Lyytinen, K., & Pigneur, Y. (2009). Why Mobile Payments Fail? Towards a Dynamic and Multi-Perspective Explanation. Paper presented at the 42nd Hawaii International Conference on System Sciences, Big Island, HI Pallant,J. (2011). SPSS survival manual A step by step guide to data analysis using SPSS (4 ed.). Crows Nest, Australia: Allen & Unwin. Park,H.S., & Smith,S.W. (2007). Distinctiveness and Influence of Subjective Norms, Personal Descriptive and Injunctive Norms, and Societal Descriptive and Injunctive Norms on Behavioral Intent: A Case of Two Behaviors Critical to Organ Donation. Human Communication Research, 33(2), 194-218. Park,Y., & Chen,J.V. (2007). Acceptance and adoption of the innovative use of smartphone. Industrial Management & Data Systems, 107(9), 1349-1365. Pavlou, P.A., & Chai, L. (2002). What Drives Electronic Commerce across Cultures? Across-Cultural Empirical Investigation of the Theory of Planned Behavior. Journal of Electronic Commerce Research, 3(4), 240-253. 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(3), 203-222. Petrova, K. (2008). Mobile Commerce Applications and Adoption. Electronic Commerce: Concepts, Methodologies, Tools, and Applications Hershey, Ed. IGI Global, 889-897. Portioresearch. (2010). Mobile Payments 2010-2014. Retrieved May 11, 2011, from http://www.portioresearch.com/Mob_payment_s10- 14.html Raleting,T., & Nel,J. (2011). Determinants of low-income non-users’ attitude towards WIG mobile phone banking: Evidence from South Africa. African Journal of Business Management, 5(1), 212-223. Ramayah, T., Rouibah, K., Gopi, M., & Rangel, G.J. (2009). A decomposed theory of reasoned action to explain intention to use Internet stock trading among Malaysian investors. Computers in Human Behavior, 25(6), 1222-1230. Raykov, T., & Marcoulides, G.A. (2006). A first course in structural equation modeling (2 ed.). Mahwah, NJ: Lawrence Erlbaum. Robles,P. (2010). Mobile commerce to grow to $119bn by 2015: report. Retrieved June 22, 2011, from http://econsultancy.com/us/blog/5435- mobile-commerce-to-grow-to-119bn-by-2015-report Rogers,E.M. (1983). Diffusion of Innovations (3 ed.). New York,NY: The Free Press. Rouibah, K., & Abbas,H. (2006). A Modified Technology Acceptance Model for Camera Mobile Phone Adoption: Development and validation. ACIS 2006 Proceedings, 13. Rouibah, K., Abbas,H., & Rouibah, S. (2011). Factors affecting camera mobile phone adoption before e-shopping in the Arab world. Technology in Society, 33(3-4), 271–283. Rouibah, K., & Ould-Ali, S. (2009). Mobile-Commerce Intention to Use via SMS: The Case of Kuwait Emerging markets and e-commerce in developing economies (pp.230-253): IGI Global. Rouibah, K., Thurasamy, R., & May, O.S. (2009). User Acceptance of Internet Banking In Malaysia: Test of Three Competing Models. International Journal of E-Adoption (IJEA), 1(1), 1-19. Saeed,K. (2011). Understanding the Adoption of Mobile Banking Services: An Empirical Assessment. Paper presented at the AMCIS 2011 Proceedings-All Submissions, Detroit, Michigan. Saunders, M., Lewis, P., & Thornhill, A. (2007). Research methods for business students (4 ed.). Essex, England: Prentice Hall. Saunders, M., Lewis, P., & Thornhill, A. (2009). Research methods for business students (5 ed.). Essex, England: Prentice Hall. Schepers, J., & Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information & Management, 44(1), 90-103. 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(3), 209-216. Schumacker, R.E., & Lomax, R.G. (2004). A beginner's guide to structural equation modeling (2 ed.). Mahwah, NJ: Lawrence Erlbaum. Sekaran, U., & Bougie,R. (2009). Research Methods for Business A skill Building Approach. West Sussex, England: John Wiley & Sons. Serenko, A. (2008). A model of user adoption of interface agents for email notification. Interacting with Computers, 20(4-5), 461-472. Shih, 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. Shin, D.-H. (2009). Towards an understanding of the consumer acceptance of mobile wallet. Computers in Human Behavior, 25(6), 1343-1354. Shin, D.H. (2011). The influence of perceived characteristics of innovating on 4G mobile adoption. International Journal of Mobile Communications, 9(3), 261-279. Smadi, Z.M.d.A., & Al-jawazneh, B.E. (2011). The Consumer Decision Making Styles of Mobile Phones among the University Level Students in Jordan International Bulletin of Business Administration (10), 104-121. Sohn, S.Y., & Kim, Y. (2008). Searching customer patterns of mobile service using clustering and quantitative association rule. Expert Systems with Applications, 34(2), 1070-1077. Somekh, B., & Lewin, C. (2005). Research methods in the social sciences. Thousand Oaks,CA: : Sage Publications Ltd. Sripalawat, J., Thongmak, M., & Ngarmyarn, A. (2011). M-banking in metropolitan bangkok and a comparison with other countries. Journal of Computer Information Systems, 51(3), 67-76. Srite, M., & Karahanna, E. (2006). The role of espoused national cultural values in technology acceptance. MIS Quarterly, 30(3), 679-704. Stafford, T.F., & Khasawneh, A.M. (2009). Individual Adopter Differences Among Jordanian Technology Users. AMCIS 2009 Proceedings. Paper 409. Stevens, J.P. (2009). Applied multivariate statistics for the social sciences (5 ed.). New York, NY: Routledge. Straub, D.W., Loch, K.D., & Hill, C.E. (2003). Transfer of information technology to the Arab world: a test of cultural influence modeling. Advanced topics in global information management (pp.141-172): IGI Publishing. Suki,N.M. (2011). Subscribers’ intention towards using 3G mobile services. Journal of Economics and Behavioral Studies, 2(2), 67-75. Sun,H., & Zhang,P. (2006). The role of moderating factors in user technology acceptance. International Journal of Human-Computer Studies, 64(2), 53-78. Tabachnick, B.G., & Fidell, L.S. (2007). Using multivariate statistics (5 ed.). Boston, MA: Pearson Education. Taylor, S., & Todd, P. (1995a). Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions. International Journal of Research in Marketing, 12(2), 137-155. Taylor, S., & Todd, P. (1995b). Understanding Information Technology Usage: A Test of Competing Models. Information Systems Research, 6(2), 144-176. Teo, T. (2009). The Impact of Subjective Norm and Facilitating Conditions on Pre-Service Teachers' Attitude toward Computer Use: A Structural Equation Modeling of an Extended Technology Acceptance Model. Journal of Educational Computing Research, 40(1), 89-109. Teo, T.S.H., & Pok, S.H. (2003). Adoption of WAP-enabled mobile phones among Internet users. Omega, 31(6), 483-498. The-Jordan-Times. (2009). Internet users reach 28 per cent in first three quarters. Retrieved February 7, 2010, from http://www.jordantimes.com/?news=21795&search For=mobile%20phones Tiwari, R., & Buse, S. (2007). The Mobile Commerce Prospects: A Strategic Analysis of Opportunities in the Banking Sector: Hamburg University Press Turban, E., King, D., Lee, J., & Viehland, D. (2004). Electronic Commerce: a managerial perspective (3rd ed.): NJ:Prentice Hall. Turel, O., Serenko, A., & Bontis, N. (2007). User acceptance of wireless short messaging services: Deconstructing perceived value. Information & Management, 44(1), 63-73. U.S.,D.o.S. (2010). Retrieved March 3, 2010, from U.S Department of State http://www.state.gov/r/pa/ei/bgn/3464.htm Urbaczewski, A., Wells, J., Sarker, S., & Koivisto, M. (2002). Exploring cultural differences as a means for understanding the global mobile internet: a theoretical basis and program of research. Paper presented at the 35th International Conference on System Sciences, Big Island, HI, USA. Valente, T.W. (2010). Social networks and health: Models, methods, and applications. New York, NY: Oxford Univ Press. Van Biljon, J., & Kotzé, P. (2008). Cultural factors in a mobile phone adoption and usage model. Journal of Universal Computer Science, 14(16), 2650-2679. VanderStoep, S.W., & Johnson, D.D. (2009). Research Methods for Everyday Life. San Francisco, CA: Jossey-Bass. Varshney, U. (2003). Wireless I: mobile and wireless information systems: applications, networks, and research problems. Communications of the Association for Information Systems, 12(12), 155-166. Venkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39(2), 273-315. Venkatesh, V., Brown, S.A., Maruping, L.M., & Bala, H. (2008). Predicting different conceptualizations of system use: The competing roles of behavioral intention, facilitating conditions, and behavioral expectation. MIS Quarterly, 32(3), 483-502. 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., Davis, G.B., & Davis, F.D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 27(3), 425-478. Venkatesh, V., & Zhang, X. (2010). Unified Theory of Acceptance and Use of Technology: US Vs. China. Journal of Global Information Technology Management, 13(1), 5-27. Verkasalo, H., López-Nicolás, C., Molina-Castillo, F.J., & Bouwman, H. (2010). Analysis of users and non-users of smartphone applications. Telematics and Informatics, 27(3), 242-255. Wang, J., & Lei, P. (2007). Mobile Commerce. Taniar, David, Encyclopedia of Mobile Computing and Commerce, Hershey, Ed. IGI Global, 455-460. Wang, Y.S., Lin, H.H., & Luarn, P. (2006). Predicting consumer intention to use mobile service. Information Systems Journal, 16(2), 157-179. 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 Systems, 109(3), 370-388. Wessels, L., & Drennan, J. (2010). An investigation of consumer acceptance of M-banking. International Journal of Bank Marketing, 28(7), 547-568. Wu, J.-H., & Wang, S.-C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information & Management, 42(5), 719-729. Wu, J.H., Wang, S.C., & Lin, L.M. (2007). Mobile computing acceptance factors in the healthcare industry: A structural equation model. International journal of medical informatics, 76(1), 66-77. Wu, Y.-L., Tao, Y.-H., & Yang, P.-C. (2008). The use of unified theory of acceptance and use of technology to confer the behavioral model of 3G mobile telecommunication users. Journal of Statistics & Management Systems, 11(5), 919-949. Yang,K. (2010). The Effects of Technology Self-Efficacy and Innovativeness on Consumer Mobile Data Service Adoption between American and Korean Consumers. Journal of International Consumer Marketing, 22(2), 117-127. Yang,K.C.C. (2005). Exploring factors affecting the adoption of mobile commerce in Singapore. Telematics and Informatics, 22(3), 257-277. Yaseen, S.G., & Zayed, S. (2010). Exploring Critical Determinants in Deploying Mobile Commerce Technology. American Journal of Applied Sciences, 7(1), 120-126. Zhang,J., & Mao,E. (2008). Understanding the acceptance of mobile SMS advertising among young Chinese consumers. Psychology and Marketing, 25(8), 787-805. Zhang,J., Yuan,Y., & Archer,N. (2002). Driving Forces for M-Commerce Success. Journal of Internet Commerce, 1(3), 81-105.