An Investigation of the Factors That Impact the Intention to Adopt and Use mICT in the Libyan Construction Industry
Main Article Content
Abstract
Information technology has been identified as a vital means for supporting construction project processes, but the level of adoption in the construction industry has been low relative to other sectors. Mobile Information and communications technology (mICT) allows people to access information from wherever they are, and as work in the construction industry is mainly fieldwork with highly mobile workers, mICT holds promise for the sector, particularly in developing countries. The aim of the study reported in this paper was to investigate factors that could impact stakeholders' adoption of mICT in the Libyan construction industry. A model of mICT adoption was developed and tested using data collected from a survey of 202 construction industry stakeholders from 15 companies in Libya. The analysis was undertaken using structural equation modelling. It was found that perceived usefulness and ease of use are important in determining the intention to adopt mICT and that they are influenced by self-efficacy and facilitating conditions. The cost of technology was not found to be a barrier to adoption. Recommendations are made to the construction industry in Libya and relevant government authorities to help improve awareness of the potential of mICT and to help improve potential users' self-efficacy.
Article Details

This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Australian Bureau of Statistics. (2015). Business Use of Information Technology. Canberra, Australia, 2013–2014, Commonwealth of Australia. Available at: http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/8129.0201112?OpenDocument.
Agarwal, R. and Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies? Decision Sciences, 30(2): 361–391. https://doi.org/10.1111/j.1540-5915.1999.tb01614.x.
Agarwal, R., Sambamurthy, V. and Stair, R.M. (2000). Research report – The evolving relationship between general and specific computer selfefficacy: An empirical assessment. Information Systems Research, 11(4): 418–430. https://doi.org/10.1287/isre.11.4.418.11876.
Ahsan, S., El-Hamalawi, A., Bouchlaghem, D. and Ahmad, S. (2007). Mobile technologies for improved collaboration on construction sites. Architectural Engineering and Design Management, 3(4): 257–272.
Anumba, C.J., Aziz, Z. and Obonyo, E.A. (2003). Mobile communications in construction: Trends and prospects. In C. Anumba (ed.). Innovative Developments in Architecture, Engineering and Construction. Rotterdam: Millpress, 159–168.
Bowden, S., Dorr, A., Thorpe, T. and Anumba, C. (2006). Mobile ICT support for construction process improvement. Automation in Construction, 15(5): 664–676. https://doi.org/10.1016/j.autcon.2005.08.004.
Brewer, G. and Gajendran, T. (2012). Attitudes, behaviours and the transmission of cultural traits: Impacts on ICT/BIM use in a project team. Construction Innovation: Information, Process, Management, 12(2): 198–215. https://doi.org/10.1108/14714171211215949.
Cheng, T.C.E., Lam, D.Y.C. and Yeung, A.C.L. (2006). Adoption of internet banking: An empirical study in Hong Kong. Decision Support Systems, 42(3): 1558– 1572. https://doi.org/10.1016/j.dss.2006.01.002.
Cheong, J.H. and Park, M.C. (2005). Mobile internet acceptance in Korea. Internet Research, 15(2): 125–140. https://doi.org/10.1108/10662240510590324.
Chong, S. and Pervan, G. (2007). Factors influencing the extent of deployment of electronic commerce for small-and medium sized enterprises. Journal of Electronic Commerce in Organizations, 5(1): 1–29. https://doi.org/10.4018/jeco.2007010101.
Compeau, D.R. and Higgins, C.A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2): 189–211. https://doi.org/10.2307/249688.
Compeau, D.R., Higgins, C.A. and Huff, S. (1999). Social cognitive theory and individual reactions to computing technology: A longitudinal study. MIS Quarterly, 23(2): 145–158. https://doi.org/10.2307/249749.
Dasgupta, S., Paul, R. and Fuloria, S. (2011). Factors affecting behavioral intentions towards mobile banking usage: Empirical evidence from India. Romanian Journal of Marketing, 6(1): 6–28.
Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3): 318–339. https://doi.org/10.2307/249008.
Davis, F.D., Bagozzi, R.P. and Warshaw, P.R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14): 1111–1131. https://doi.org/10.1111/j.1559-1816.1992.tb00945.x.
Davis, F.D., Bagozzi, R.P. and Warshaw, P.R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8): 982–1003. https://doi.org/10.1287/mnsc.35.8.982.
Department for Business, Innovation and Skills (2011). Rebuilding Libya: Opportunities for British Business. London: Department for Business, Innovation and Skills. Available at: https://www.gov.uk/government/speeches/rebuilding-libya-opportunities-for-british-business.
Dwivedi, Y.K., Khoumbati, K., Williams, M.D. and Lal, B. (2007). Factors affecting consumers' behavioural intention to adopt broadband in Pakistan. Transforming Government: People, Process and Policy, 1(3): 285–297.
Froese, T., Han, Z. and Alldritt, M. (2007). Study of information technology development for the Canadian construction industry. Canadian Journal of Civil Engineering, 34(7): 817–829. https://doi.org/10.1139/l06-160.
Geisser, S. (1974). A predictive approach to the random effect model. Biometrika, 61(1): 101–107. https://doi.org/10.1093/biomet/61.1.101.
Hair, J.F.Jr., Tomas, M., Hult, G.T., Ringle, C. and Sarstedt, M. (2013). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Thousand Oaks, CA: Sage Publications.
Harindranath, G., Dyerson, R. and Barnes, D. (2008). ICT in small firms: Factors affecting the adoption and use of ICT in southeast England SMEs. In European Conference on Information Systems 2008 Proceedings. Galway: ECIS, 889–900.
Henderson, J.R. and Ruikar, K. (2010). Technology implementation strategies for construction organisations. Engineering, Construction and Architectural Management, 17(3): 309–327. https://doi.org/10.1108/09699981011038097.
Hsu, M.H. and Chiu, C.M. (2004). Predicting electronic service continuance with a decomposed theory of planned behaviour. Behaviour and Information Technology, 23(5): 359–373. https://doi.org/10.1080/01449290410001669969.
Hu, P.J., Chau, P.Y.K., Sheng, O.R.L. and Tam, K.Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2): 91–112. https://doi.org/10.1080/07421222.1999.11518247.
Igbaria, M., Iivari, J. and Maragahh, H. (1995). Why do individuals use computer technology? A Finnish case study. Information and Management, 29(5): 227–238. https://doi.org/10.1016/0378-7206(95)00031-0.
Ikediashi, D.I. and Ogwueleka, A.C. (2016). Assessing the use of ICT systems and their impact on construction project performance in the Nigerian construction industry. Journal of Engineering, Design and Technology, 14(2): 252–276. https://doi.org/10.1108/JEDT-08-2014-0047.
Jones, C., Kennedy, S., Kerr, S., Mitchell, J. and Safayeni, D. (2012). Furthering Democracy in Libya with Information Technology: Opportunities for the International Donor Community. Ontario, Canada: Centre for International Governance Innovation. Available at: http://www.cigionline.org/sites/default/files/no4_0.pdf [Accessed on 20 May 2016].
Kim, B., Choi, M. and Han, I. (2009). User behaviors toward mobile data technologies: The role of perceived fee and prior experience. Expert Systems with Applications, 36(4): 8528–8536. https://doi.org/10.1016/j.eswa.2008.10.063.
Kripanont, N. and Tatnall, A. (2009). The role of a modified technology acceptance model in explaining Internet usage in higher education in Thailand. International Journal of Actor-Network Theory and Technological Innovation, 1(2): 31–49. https://doi.org/10.4018/jantti.2009040103.
Lu, J., Lu, C., Yu, C.S. and Yao, J.E. (2014). Exploring factors associated with wireless internet via mobile technology acceptance in mainland China. Communications of the International Information Management Association, 3(1): 101–120.
Luarn, P. and Lin, H. (2005). Towards an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior, 21(6): 873–891. https://doi.org/10.1016/j.chb.2004.03.003.
Manley, K., Marceau, J. and Hampson, K. (2001). Technology transfer and the Australian construction industry: Exploring the relationship between publicsector research providers and research users. Journal of Scientific and Industrial Research, 60: 919–928.
Ngab, A.S. (2007). Libya: The construction industry; An overview. International Workshop-Cements Based Materials and Civil Infrastructure. Karachi, Pakistan, 10–11 December. Karachi: NED University of Engineering And Technology.
Oladapo, A.A. (2006). The impact of ICT on professional practices in Nigerian Construction Industry. The Electronic Journal on Information System in Developing Countries, 24(2): 1–19.
Ong, C.S., Lai, J.Y. and Wang, Y.S. (2004). Factors affecting engineers' acceptance of asynchronous e-learning systems in high-tech companies. Information and Management, 41(6): 795–804. https://doi.org/10.1016/j.im.2003.08.012.
Ooi, K.-B., Sim, J.-J., Yew, K.-T. and Lin, B. (2011). Exploring factors influencing consumers' behavioural intention to adopt broadband in Malaysia. Computers in Human Behavior, 27(3): 1168–1178. https://doi.org/10.1016/j.chb.2010.12.011.
Pagani, M. (2004). Determinants of adoption of third generation mobile multimedia technologies. Journal of Interactive Marketing, 18(3): 46–59. https://doi.org/10.1002/dir.20011.
Pavlou, P.A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3): 101–134.
Peansupap, V. and Walker, D.H.T. (2006). Information communication technology (ICT) implementation constraints: A construction industry perspective. Engineering, Construction and Architectural Management, 13(4): 361–379. https://doi.org/10.1108/09699980610680171.
Pedersen, P. (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. https://doi.org/10.1207/s15327744joce15032.
Saidi, K., Haas, C.T. and Balli, N.A. (2002). The value of handheld computers in construction. Evaluation, 13: 1–6.
Shih, Y. and Chen, C. (2013). The study of behavioral intention for mobile commerce: Via integrated model of TAM and TTF. Quality and Quantity, 47(2): 1009–1020. https://doi.org/10.1007/s11135-011-9579-x.
Son, H., Park, Y., Kim, C. and Chou, J.S. (2012). Toward an understanding of construction professionals' acceptance of mobile computing devices in South Korea: An extension of the technology acceptance model. Automation in Construction, 28: 82–90. https://doi.org/10.1016/j.autcon.2012.07.002.
Sripalawat, J., Thongmak, A. and Ngramyarn A. (2011). M-banking in metropolitan Bangkok and a comparison with other countries. Journal of Computer Information Systems, 51(3): 67–76.
Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society, Series B (Methodological), 36(2): 111–147.
Sun, Q., Cao, H. and You, J. (2010). Factors influencing the adoption of mobile service in China: An integration of TAM. Journal of Computers, 5(5): 799– 806. https://doi.org/10.4304/jcp.5.5.799-806.
Teo, T. (2010). Examining the influence of subjective norm and facilitating conditions on the intention to use technology among pre-service teachers: A structural equation modeling of an extended technology acceptance. Asia Pacific Education Review, 11(2): 253–262. https://doi.org/10.1007/s12564-009-9066-4.
Teo, T., Lee, C.B. and Chai, C.S. (2008). Understanding pre?service teachers' computer attitudes: Applying and extending the technology acceptance model. Journal of Computer Assisted Learning, 24(2): 128–143. https://doi.org/10.1111/j.1365-2729.2007.00247.x.
Thompson, R.L., Higgins, C.A. and Howell, J.M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1): 125–143. https://doi.org/10.2307/249443.
Twati, J.M. and Gammack, J.G. (2006). The impact of organisational culture innovation on the adoption of IS/IT: The case of Libya. Journal of Enterprise Information Management, 19(2): 175–191. https://doi.org/10.1108/17410390610645076.
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. https://doi.org/10.1287/isre.11.4.342.11872.
Venkatesh, V. and Davis, F.D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2): 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926.
Venkatesh, V. and Davis, F.D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3): 451–481. https://doi.org/10.1111/j.1540-5915.1996.tb01822.x.
Venkatesh, V. and Morris, M.G. (2000). Why don't 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. https://doi.org/10.2307/3250981.
Venkatesh, V., Morris, M., Davis, G. and Davis, F. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3): 425– 479.
Venkatesh, V. and Zhang, X. (2010). Unified theory of acceptance and use of technology: U.S. vs. China. Journal of Global Information Technology Management, 13(1): 5–7. https://doi.org/10.1080/1097198X.2010.10856507.
Venkatraman, S. and Yoong, P. (2009). Role of mobile technology in the construction industry: A case study. International Journal of Business Information Systems, 4(2): 195–209. https://doi.org/10.1504/IJBIS.2009.022823.
Vijayasarathy, L.R. (2004). Predicting consumer intentions to use on-line shopping: The case for an augmented technology acceptance model. Information and Management, 41(6): 747–762. https://doi.org/10.1016/j.im.2003.08.011.
Wang, Y.-S., Wang, Y.-M., Lin, H.-H. and Tang, T.-I. (2003). Determinants of user acceptance of internet banking: An empirical study. International Journal of Service Industry Management, 14(5): 501–519. https://doi.org/10.1108/09564230310500192.
Warrington, T., Abgrab, N. and Caldwell, H. (2000). Building trust to develop competitive advantage in e-business relationship. Competitiveness Review, 10(2): 160–168. https://doi.org/10.1108/eb046409.
Yaghoubi, N. and Bahmani, E. (2010). 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. https://doi.org/10.5539/ijbm.v5n9p159.
Zarmpou, T., Saprikis, V. and Vlachopoulou, M. (2010). Investigating the influential factors towards mobile technologies adoption in Greece. Information Assurance and Security Letters, 1: 72–79.
Zou, W., Ye, X., Peng, W. and Chen, Z. (2006). A brief review on application of mobile computing in construction. In First International Multi-Symposiums on Computer and Computational Sciences 2006 (IMSCCS'06). Vol. 2. Los Alamitos, CA: IEEE Computer Society, 657–661. https://doi.org/10.1109/IMSCCS.2006.141.