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Original Articles

The nature and components of perceived behavioural control as an element of theory of planned behaviour

Pages 65-85 | Received 11 Jan 2010, Accepted 16 Sep 2011, Published online: 04 Nov 2011

References

  • Ajzen, I., 1991. The theory of planned behaviour. Organizational Behaviour and Human Decision Processes, 50(2), 179–211. doi: 10.1016/0749-5978(91)90020-T
  • Ajzen, I., 2002. Constructing a theory of planned behaviour questionnaire: conceptual and methodological considerations, Available from Ajzen Homepage at http://www.people.umass.edu/aizen/pdf/tpb.measurement.pdf [Accessed 26 April 2005]
  • Ajzen, I., Madden, T. J., 1986. Predication of goal-directed behavior: attitude, intentions, and perceived behavioural control. Journal of Experimental Social Psychology, 22(1), 453–474. doi: 10.1016/0022-1031(86)90045-4
  • Al-Sabbagh, I., Molla, A., 2004. Adoption and use of Internet banking in the sultanate of Oman: an exploratory study. Journal of Internet Banking and Commerce; Web Archive, 9(2),
  • Amireault, S., et al., 2008. Moderators of the intention–behaviour and perceived behavioural control-behaviour relationships for leisure-time physical activity [online]. International Journal of Behavioral Nutrition and Physical Activity, 5(7), Available from: http://www.ijbnpa.org/content/pdf/1479-5868-5-7.pdf [Accessed 2 November 2011]
  • Armitage, C. J., Conner, M., 1999a. Distinguishing perceptions of control from self-efficacy: predicting consumption of a low-fat diet using the theory of planned behaviour. Journal of Applied Social Psychology, 29(1), 72–90. doi: 10.1111/j.1559-1816.1999.tb01375.x
  • Armitage, C. J., Conner, M., 1999b. The theory of planned behaviour: assessment of predictive validity and perceived control. British Journal of Social Psychology, 38(1), 35–54. doi: 10.1348/014466699164022
  • Armitage, C. J., Conner, M., 2001. Efficacy of the theory of planned behaviour: a meta-analytic review. British Journal of Social Psychology, 40(4), 471–499. doi: 10.1348/014466601164939
  • Bentley, L. D., Whitten, J. L., 2007. Systems analysis and design for the global enterprise, 7th ed. New York: McGraw-Hill.
  • 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. doi: 10.1109/3468.852435
  • Bhattacherjee, A., Sanford, C., 2009. The intention–behaviour gap in technology usage: the moderating role of attitude strength. Behaviour & Information Technology, 28(4), 389–401. doi: 10.1080/01449290802121230
  • Brown, I., et al., 2004. The impact of national environment on the adoption of Internet banking: comparing Singapore and South Africa. Journal of Global Information Management, 12(2), 1–26. doi: 10.4018/jgim.2004040101
  • Catell, R. B., 1966. The Scree test for number of factors. Multivariate Behavioural Research, 1(1), 245–276. doi: 10.1207/s15327906mbr0102_10
  • Celik, H., 2008. What determines Turkish customers' acceptance of internet banking. International Journal of Bank Marketing, 26(5), 353–370. doi: 10.1108/02652320810894406
  • 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. doi: 10.1016/S0378-7206(01)00075-1
  • Chen, C. D., Cheng, C. J., 2009. Understanding consumer intention in online shopping: a respecification and validation of the DeLone and McLean model. Behaviour & Information Technology, 28(4), 335–345. doi: 10.1080/01449290701850111
  • 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. doi: 10.1016/S0167-9236(00)00125-1
  • Compeau, D. R., Higgins, C. A., 1995. Computer self-efficacy: development of a measure and initial test. MIS Quarterly, 19(2), 189–211. doi: 10.2307/249688
  • Dabholkar, P. A., 1996. Consumer evaluations of new technology-based self-service options: an investigation of alternative models of service quality. International Journal of Research in Marketing, 13(1), 29–51. doi: 10.1016/0167-8116(95)00027-5
  • Davis, F. D., 1986. A technology acceptance model for empirically testing new end-user information systems: theory and results. Thesis (PhD), Sloan School of Management, MIT.
  • 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. doi: 10.1287/mnsc.35.8.982
  • Doll, J., Ajzen, I., 1992. Accessibility and stability of predictors in the theory of planned behaviour. Journal of Personality and Social Psychology, 63(5), 754–765. doi: 10.1037/0022-3514.63.5.754
  • Fishbein, M., Ajzen, I., 1975. Belief, attitude, intention and behaviour: an introduction to theory and research, USA: Addison-Wesley. Electronic version available from http://www.people.umass.edu/aizen/f&a1975.html [Accessed 23 January 2005]
  • Gist, M. E., Mitchell, T. R., 1992. A theoretical analysis of its determinants and malleability. The Academy of Management Review, 17(2), 183–211.
  • Grant, D. M., Malloy, A. D., Murphy, M. C., 2009. A comparison of student perceptions of their computer skills to their actual abilities. Journal of Information Technology Education, 8(1), 141–160.
  • Hair, J. F., et al., 2006. Multivariate data analysis, 6th ed. Upper Saddle River, NJ: Prentice Hall International.
  • Hartshorne, R., Ajjan, H., 2009. Examining student decisions to adopt Web 2.0 technologies: theory and empirical tests. Journal of Computing in Higher Education, 21(1), 183–198. doi: 10.1007/s12528-009-9023-6
  • Hartzel, K., 2003. How self-efficacy and gender issues affect software adoption and use. Communications of the ACM, 46(9), 167–171. doi: 10.1145/903893.903933
  • Hernandez, J. M.C., Mazzon, J. A., 2007. Adoption of Internet banking: proposition and implementation of an integrated methodology approach. International Journal of Bank Marketing, 25(2), 72–88. doi: 10.1108/02652320710728410
  • Hill, T., Smith, N. D., Mann, M. F., 1987. Role of efficacy expectations in predicting the decision to use advanced technologies: the case of computers. Journal of Applied Psychology, 72(2), 307–313. doi: 10.1037/0021-9010.72.2.307
  • 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. doi: 10.1016/S1567-4223(03)00008-5
  • Igbaria, M., Iivari, J., 1995. The effects of self-efficacy on computer usage, Omega. International Journal Management Science, 23(6), 587–605.
  • Jiang, J., et al., 2000. E-commerce user behaviour model: an empirical study. Human Systems Management, 19(4), 265–276.
  • Kraft, P., et al., 2005. Perceived difficulty in the theory of planned behaviour: perceived behavioural control or affective attitude. British Journal of Social Psychology, 44(1), 479–496. doi: 10.1348/014466604X17533
  • Lai, V. S.L., Li, H. L., 2004/2005. Technology acceptance model for Internet banking: an invariance analysis. Information & Management, 42(2), 373–386. doi: 10.1016/j.im.2004.01.007
  • Lassar, W., Manolis, C., Lassar, S. S., 2005. The relationship between consumer innovativeness, personal characteristics, and online banking adoption. International Journal of Bank Marketing, 23(2), 176–199. doi: 10.1108/02652320510584403
  • Laudon, K., Laudon, J., 2010. Management information systems: managing the digital firm, 11th ed. Upper Saddle River, NJ: Pearson Prentice Hall.
  • Lee-Partridge, J., Ho, P. S., 2003. A retail investor's perspective on the acceptance of Internet stock trading, Proceedings of the 36th Hawaii international conference on system sciences – 2003, http://www.hicss.hawaii.edu/HICSS36/HICSSpapers/INEMG02.pdf [Accessed 16 July 2005]
  • Liao, S., et al., 1999. The adoption of virtual banking: an empirical study. International Journal of Information Management, 19(1), 63–74. doi: 10.1016/S0268-4012(98)00047-4
  • Liu, Y., Doucette, W. R., Farris, K. B., 2007. Perceived difficulty and self-efficacy in the factor structure of perceived behavioural control to seek drug information from physicians and pharmacists. Research in Social and Administrative Pharmacy, 3(2), 145–159. doi: 10.1016/j.sapharm.2006.07.002
  • Lopez, D. A., Manson, D. P., 1997. A study of individual computer self-efficacy and perceived usefulness of the empowered desktop information system, Available from http://www.csupomona.edu/~jis/1997/Lopez.pdf [Accessed 11 April 2009]
  • Lu, J., et al., 2003. Technology acceptance model for wireless Internet. Internet Research, 13(3), 206–222. doi: 10.1108/10662240310478222
  • Luarn, P., Lin, H., 2005. Toward an understanding of the behavioural intention to use mobile banking. Computers in Human Behaviour, 21(6), 873–891. doi: 10.1016/j.chb.2004.03.003
  • Malhotra, N. K., 2009. Marketing research: an applied orientation, 6th ed. Upper Saddle River, NJ: Pearson Prentice Hall.
  • Malhotra, P., Singh, B., 2004. Adoption of Internet banking: an empirical investigation of Indian banking sector. Journal of Internet Banking and Commerce,, 9(2), Web Archive
  • Mathieson, K., 1991. Predicting user intention: comparing the technology acceptance model with the theory of planned behaviour. Information Systems Research, 2(3), 173–191. doi: 10.1287/isre.2.3.173
  • Mathieson, K., Peacock, E., Chin, W., 2001. Extending the technology acceptance model: the influence of perceived user resources. The DATA BASE for Advances in Information Systems, 32(3), 86–112. doi: 10.1145/506724.506730
  • Mattila, M., Karjaluoto, H., Pento, T., 2003. Internet banking adoption among mature customers: early majority or laggards. Journal of Services Marketing, 17(5), 514–528. doi: 10.1108/08876040310486294
  • Murphy, G. D., 2009. Improving the quality of manually acquired data: applying the theory of planned behaviour to data quality. Reliability Engineering and System Safety, 94(1), 1881–1886. doi: 10.1016/j.ress.2009.05.008
  • Ndubisi, N. O., 2007. Customers’ perceptions and intention to adopt Internet banking: the moderation effect of computer self-efficacy. AI & Society, 21(3), 315–327. doi: 10.1007/s00146-006-0062-5
  • Nielsen, J. F., Viggo, H., Niels, P. M., 2003. Drivers of adoption of Internet-based marketing channels, University of AARHUS Denmark, Department of Management, Working Paper 2003-3
  • Pallant, J., 2005. SPSS survival manual: a step by step guide to data analysis using SPSS version 12, 2nd ed. New York: Open University Press, McGraw-Hill Education.
  • Pavlou, P. A., 2002. What drives electronic commerce? A theory of planned behaviour perspective, Academy of management proceedings, 2002, A1–A6 [Accessed 28 May 2005, from ebscohost]
  • Pavlou, P. A., Fygenson, M., 2006. Understanding and predicting electronic commerce adoption an extension of the theory of planned behaviour. MIS Quarterly, 30(1), 115–143.
  • 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. doi: 10.1108/02652320110392527
  • Ratnasingam, P., Gefen, D., Pavlou, P. A., 2005. The role of facilitating conditions and institutional trust in electronic marketplaces. Journal of Electronic Commerce in Organizations, 3(3), 69–82. doi: 10.4018/jeco.2005070105
  • Rhodes, R., Courneya, K., 2003a. Self efficacy, controllability and intentions in the theory of planned behaviour: measurement redundancy or causal independence. Psychology and Health, 18(1), 79–91. doi: 10.1080/0887044031000080665
  • Rhodes, R., Courneya, K., 2003b. 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. doi: 10.1348/014466603763276162
  • Rotchanakitumnuai, S., Speece, M., 2003. Barriers to Internet banking adoption: a qualitative study among corporate customers in Thailand. International Journal of Bank Marketing, 21(6/7), 312–323. doi: 10.1108/02652320310498465
  • Sciglimpaglia, D., Ely, D., 2003. Internet banking: a customer-centric perspective [online], Proceedings of the 35th Hawaii international conference on system sciences, January7–10. 2420–2429, Available from: http://ieeexplore.ieee.org/iel5/7798/21442/00994179.df?tp=&isnumber=&arnumber=994179 [Accessed 29 October 2011]
  • Sekaran, U., 2003. Research methods for business: a skill building approach, 4th ed. New York: John Wiley & Sons.
  • Shih, Y., 2006. The effect of computer self-efficacy on enterprise resource planning usage. Behaviour & Information Technology, 25(5), 407–411. doi: 10.1080/01449290500168103
  • Shih, Y., Fang, K., 2004. The use of a decomposed theory of planned behaviour to study Internet banking in Taiwan. Internet Research, 14(3), 213–223. doi: 10.1108/10662240410542643
  • Stafford, B., 2001. Risk management and Internet banking: what every banker needs to know. Community Banker, 10(2), 48–49.
  • Suoranta, M., Mattila, M., 2004. Mobile banking and consumer behaviour: new insights into the diffusion pattern. Journal of Financial Services Marketing, 8(4), 354–366. doi: 10.1057/palgrave.fsm.4770132
  • Sutton, S., et al., 2003. Eliciting salient beliefs in research on the theory of planned behaviour: the effect of question wording. Current Psychology: Developmental, Learning, Personality, Social, 22(3), 234–251. doi: 10.1007/s12144-003-1019-1
  • Tabachnick, B. G., Fidell, L. S., 2007. Using multivariate statistics, 5th ed. Boston: Pearson Education.
  • Tan, M., Teo, T. S.H., 2000. Factors influencing the adoption of Internet banking. Journal for association of information system, 1(5), [online]. Available from www.isworld.org [Accessed 18 March 2007]
  • Tavousi, M., et al., 2009. Are perceived behavioural control and self-efficacy distinct constructs?. European Journal of Scientific Research, 30(1), 146–152.
  • Taylor, S., Todd, P. A., 1995a. Understanding information technology usage: a test of competing model. Information Systems Research, 6(2), 144–176. doi: 10.1287/isre.6.2.144
  • Taylor, S., Todd, P., 1995b. Decomposition and crossover effects in the theory of planned behaviour: a study of consumer adoption intentions. International Journal of Research in Marketing, 12(2), 137–155. doi: 10.1016/0167-8116(94)00019-K
  • 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. doi: 10.2190/EC.40.1.d
  • Thompson, R. L., Higgins, C. A., Howell, J. M., 1991. Personal computing: toward a conceptual model of utilization. MIS Quarterly, 15(1), 124–143. doi: 10.2307/249443
  • Thompson, R. L., Higgins, C. A., Howell, J. M., 1994. Influence of experience on personal computer utilization: testing a conceptual model. Journal of Management Information Systems, 11(1), 167–187.
  • Trafimow, D., et al., 2002. Evidence that perceived behavioural control is a multi-dimensional construct: Perceived control and perceived difficulty. The British Journal of Social Psychology, 41(1), 101–121. doi: 10.1348/014466602165081
  • Trafimow, D., et al., 2004. Affective and cognitive control of persons and behaviours. British Journal of Social Psychology, 43(1), 207–224. doi: 10.1348/0144666041501642
  • Triandis, H. C., 1980. Values, attitudes, and interpersonal behaviour. In Page, M. M. (Ed.), Nebraska symposium on motivation, 1979: beliefs, attitudes, values, (pp. 195–259). Lincoln: University of Nebraska Press.
  • Venkatesh, V., 2000. Determinants of perceived ease of use: integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342–365. doi: 10.1287/isre.11.4.342.11872
  • Venkatesh, V., et al., 2003. User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425–478.
  • Wang, J., Kim, S., 2007. Time to get in: The contrasting stories about government interventions in information technology standards (the case of CDMA and IMT-2000 in Korea). Government Information Quarterly, 24(1), 115–134. doi: 10.1016/j.giq.2006.04.001
  • Wang, Y., et al., 2003. Determinants of user acceptance of Internet banking an empirical study. International Journal of Service Industry Management, 14(5), 501–519. doi: 10.1108/09564230310500192
  • Zolait, A. H., 2010. An examination of the factors influencing Yemeni bank users' behavioural intention to use Internet banking services. Journal of Financial Services Marketing, 15(1), 76–94. doi: 10.1057/fsm.2010.1
  • Zolait, A. H. S., Ainin, S., 2008. Incorporating the innovation attributes introduced by Rogers' theory into theory of reasoned action: an examination of Internet banking adoption in Yemen. Journal of Computer and Information Science, 1(1), 36–51.
  • Zolait, A. H. S., Sulaiman, A., Alwi, S. F. S., 2008. Prospective and challenges of Internet banking in Yemen: an analysis of bank websites. International Journal of Business Excellence, 1(3), 353–374. doi: 10.1504/IJBEX.2008.017887

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