Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Advertisement

Springer Nature Link
Log in

Web personalization for user acceptance of technology: An empirical investigation of E-government services

  • Published:
Information Systems Frontiers Aims and scope Submit manuscript

Abstract

E-Commerce firms have adopted Web Personalization techniques extensively in the form of recommender systems for influencing user behavior for customer retention. Although there are numerous studies in this area, academic research addressing the role of Web Personalization in user acceptance of technology is very scant. Further, owing to the potential of recommender systems to attract and retain customers, most studies in web personalization have been done in E-Commerce setting. In this research, the ‘Consumer Acceptance and Use of Information Technology’ theory proposed in previous research has been extended to include web personalization as a moderator and has been tested in an E-Government context. Data collection involved conducting a laboratory experiment with the treatment group receiving personalized web forms for requesting an E-Government service. Our analyses show that personalizing the Web by self-reference and content relevance has a significant moderator role in influencing the relationship between determinants of intention to use and behavioral intention in certain cases.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Notes

  1. Impact Assessment of E-Government Services, Ministry of Communications and Information technology, Government of India, 2008.

References

  • Adomavicius, G. & Tuzhilin, A. (2011). Context-aware recommender systems, Recommender Systems Handbook, pp. 217–253.

  • Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179–211.

    Article  Google Scholar 

  • Arora, N., Dreze, X., Ghose, A., Hess, J. D., Iyengar, R., Jing, B., et al. (2008). Putting one-to-one marketing to work: personalization, customization, and choice. Marketing Letters, 19(3–4), 305–321.

  • Bhatnagar, S. (2009). Unlocking E-Government potential- concepts, cases and practical insights. New Delhi: Sage Publications.

    Google Scholar 

  • Carter, L., & Weerakkody, V. (2008). E-government adoption: a cultural comparison. Information Systems Frontiers, 10, 473–482. doi:10.1007/s10796-008-9103-6.

    Article  Google Scholar 

  • Chau, P. Y., & Lung Hui, K. (1998). Identifying early adopters of new IT products: a case of windows 95. Information & Management, 33(5), 225–230.

    Article  Google Scholar 

  • Davis, F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.

    Article  Google Scholar 

  • Dombeu, J.V.F., & Huisman, M. (2011). Semantic-driven e-government: A case study of formal representation of government domain ontology. In IST-Africa Conference Proceedings, 2011 (pp. 1–9). IEEE.

  • Dombeu, J.V.F., & Huisman, M. (2013). Practicing Semantic web Technologies in e‐Government. In Proceedings of the 13th European Conference on eGovernment: ECEG 2013 (p. 166). Academic Conferences Limited.

  • Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading: Addison-Wesley.

    Google Scholar 

  • Gao, M., Liu, K., & Wu, Z. (2010). Personalisation in web computing and informatics: theories, techniques, applications, and future research. Information Systems Frontiers, 12(5), 607–629.

    Article  Google Scholar 

  • Gefen, D., & Straub, D. (2005). A practical guide to factorial validity using pls-graph: tutorial and annotated example. Communications of the Association for Information Systems, 16, 109.

  • Hair, J. F., Jr., Money, A. H., Samouel, P., & Page, M. (2007). Research methods for business, John Wiley and Sons, Ltd.

  • Hamner, M., Negrón, M. A., Taha, D., & Brahimi, S. (2012). e-Government Implementation in a Developing Country: A Case Study. Managing E-government Projects: Concepts, Issues and Best Practices, 262.

  • Han, L., & Li, M. (2010). Application and research on ontology in e-Government workflow model. International Conference on Computer, Mechatronics, Control and Electronic Engineering (CMCE 2010), (pp. 474–477).

  • Heeks, R., & Bailur, S. (2007). Analyzing e-government research: perspectives, philosophies, theories, methods, and practice. Government information quarterly, 24(2), 243–265.

    Article  Google Scholar 

  • Henseler, J. & Fassott G. (2010) Testing moderating effects in PLS path models: An illustration of available procedures, Handbook of Partial Least Squares, Springer, 713–735.

  • Hesterberg, T., Moore, D. S., Monaghan, S., Clipson, A., & Epstein, R. (2006). Chapter 14: Bootstrap methods and permutation tests. In D. S. Moore & G. P. Mccabe (Eds.), Introduction to the practice of statistics. New York: Freeman.

    Google Scholar 

  • Hind, L., Chiadmi, D., & Benhlima, L. (2014). How semantic technologies transform e-government domain: a comparative study and framework. Transforming Government: People, Process and Policy, 8(1), 49–75.

    Article  Google Scholar 

  • Hong, W., Thong, J., & Tam, K. (2004). Does animation attract online users’ attention? The effects of flash on information search performance and perceptions. Information Systems Research, 15(1), 60–86.

    Article  Google Scholar 

  • Hsu, I. C. (2013). Personalized web feeds based on ontology technologies. Information Systems Frontiers, 15(3), 465–479.

    Article  Google Scholar 

  • Jiang, Z. (2007). The effects of presentation formats and task complexity on online consumers’ product understanding. MIS Quarterly, 31(3), 475–500.

    Google Scholar 

  • Joreskog, K. G., & Wang, F. (1996). Nonlinear structural equation models: The Kenney-Judd model with interaction effects. In R. E. Shumacker & G. A. Marcoulides (Eds.), Advanced structural equation modeling: Issues and techniques (pp. 57–58). Mahwah: Lawrence Erlbaum.

    Google Scholar 

  • Kobsa, A. (2001). Generic user modeling systems. User modeling and user-adapted interaction, 11(1), 49–63.

    Article  Google Scholar 

  • Komiak, S. Y. X., & Benbasat, I. (2006). The effects of personalization and familiarity on trust and adoption of recommendation agents, MIS Quarterly, 30(4), 941–960.

  • Krishnaraju, V., & Mathew, S. K. (2013). Web personalization research: an information systems perspective. Journal of Systems and Information Technology, 15(3), 254–268.

    Article  Google Scholar 

  • Li, D., & Liu, X. L. (2012). A model for E-government information resource integration based on ontology. Applied Mechanics and Materials, 220, 2364–2370.

    Article  Google Scholar 

  • Liang, C., Yang, D., & Si, G. (2012). Ontology based personalized catalog system of e-government information resource. Journal of Tsinghua University Science and Technology, 52(11), 1650–1656.

    Google Scholar 

  • Liang, H., Saraf, N., Hu, Q., & Xue, Y. (2007). Assimilation of enterprise systems: the effect of institutional pressures and the mediating role of top management. MIS Quarterly 31, 59–87.

  • Maigre, R., Grigorenko, P., Haav, H. M., & Kalja, A. (2013, January). A semantic method of automatic composition of e-government services. In Databases and Information Systems VII: Selected Papers from 10th Int. Baltic Conf. on Databases and Information Systems, Baltic DB&IS 2012 (pp. 204–217).

  • Mirchandani, D. A., Johnson, J. H., & Joshi, K. (2008). Perspectives of citizens towards e-government in Thailand and Indonesia: a multigroup analysis. Information Systems Frontiers, 10(4), 483–497.

    Article  Google Scholar 

  • Mobasher, B., Cooley, R., & Srivastava, J. (2000). Automatic personalization based on web usage mining. Communications of the ACM, 43(8), 142–151.

    Article  Google Scholar 

  • Nunes, P. F., & Kambil, A. (2001). Personalization? No Thanks!, Harvard Business Review, 79(4), 32–34.

  • Peterson, R., Balasubramanian, S., & Bronnenberg, B. (1997). Exploring the implications of the internet for consumer marketing. Journal of the Academy of Marketing Science, 25(4), 329–346.

  • Prahlad, C. K., & Krishnan, M. S. (2008). The new age of innovation: driving co-created value through global networks, Tata McGraw-Hill, New Delhi.

  • Rana, N. P., Dwivedi, Y. K., & Williams, M. D. (2013). A meta-analysis of existing research on citizen adoption of e-government. Information Systems Frontiers. doi:10.1007/s10796-013-9431-z. Published online: 16 April 2013.

    Google Scholar 

  • Rana, N. P., Dwivedi, Y. K., Williams, M. D., & Weerakkody, V. (2014). Investigating success of an e-government initiative: validation of an integrated IS success model. Information Systems Frontiers. doi:10.1007/s10796-014-9504-7. Published online: 23 May 2014.

    Google Scholar 

  • Schafer, J., Konstan, J. & Riedi, J. (1999). Recommender systems in e-commerce, Proceedings of the 1st ACM conference on Electronic commerce, ACM, 158–166.

  • Sheng; L., & Lingling, L. (2011). Application of Ontology in E-Government. Fifth International Conference on Management of e-Commerce and e-Government (ICMeCG 2011), (pp. 93 – 96).

  • Silcock, R. (2001). What is e-government? Parliamentary affairs, 54(1), 88–101.

    Article  Google Scholar 

  • Sinha, B., Chandra, S., & Garg, M. (2015). Development of ontology from Indian agricultural e-governance data using IndoWordNet: a semantic web approach. Journal of Knowledge Management, 19(1).

  • Stevens, R., Robinson, A., & Goble, C. (2003). Mygrid: personalised bioinformatics on the information grid. Bioinformatics, 19(1), 302.

  • Tam, K. Y., & Ho, S. Y. (2006). Understanding the impact of web personalization on user information processing and decision outcomes. MIS Quarterly, 30(4), 865–890.

    Google Scholar 

  • Taylor, S., & Todd, P. (1995). Understanding information technology usage: a test of competing models. Information Systems Research, 6(2), 144–176.

    Article  Google Scholar 

  • Tenenhaus, M., Vinzi, V. E., Chatelin, Y-M., & Lauro, C. (2005). PLS path modeling. Computational Statistics and Data Analysis, 48(1), 159–205.

  • Venkatesh, V., Morris, M., Davis, G., & Davis, F. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425–478.

    Google Scholar 

  • Venkatesh, V., Thong, J., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178.

    Google Scholar 

  • Vo, G. N., & Lai, R. (2014, May). A method for simplifying the submission of an online request for an E-Government service. In Technology Management and Emerging Technologies (ISTMET), 2014 International Symposium on (pp. 377–382). IEEE.

  • Weerakkody, V., Irani, Z., Lee, H., Osman, I., & Hindi, N. (2013). E-government implementation: a bird’s eye view of issues relating to costs opportunities, benefits and risks. Information Systems Frontiers. doi:10.1007/s10796-013-9472-3. Published online: 17 December 2013.

    Google Scholar 

  • Willcocks, L., Feeny, D., & Olson, N. (2006). Implementing core IS capabilities: Feeny-Willcocks IT governance and management framework revisited. European Management Journal, 24(1), 28–37.

    Article  Google Scholar 

  • Yildiz, M. (2007). E-government research: reviewing the literature, limitations, and ways forward. Government Information Quarterly, 24(3), 646–665.

    Article  Google Scholar 

  • Zakaria, M.R. (2013). Personalized E-government System: Towards an Adaptive Maturity Model. International Journal of Business Information and Technology (IJBIT), 2(1).

  • Zhao, J., Su, H., Dong, Y., & Zhang, Z. (2013). An ontology model for user-centered e-government in China. In LISS 2012 (pp. 1339–1344). Berlin Heidelberg: Springer.

    Google Scholar 

Download references

Acknowledgement

The work of the third author has been partially supported by Oakland University, 2014 School of Business Administration Spring/Summer Research Fellowship.

Author information

Authors and Affiliations

  1. Department of Management Studies, Indian Institute of Technology Madras, Chennai, TN, 600 036, India

    Vinodh Krishnaraju & Saji K Mathew

  2. Department of Decision and Information Sciences, School of Business Administration, Oakland University, Rochester, MI, 48309, USA

    Vijayan Sugumaran

Authors
  1. Vinodh Krishnaraju
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Saji K Mathew
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Vijayan Sugumaran
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vijayan Sugumaran.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Krishnaraju, V., Mathew, S.K. & Sugumaran, V. Web personalization for user acceptance of technology: An empirical investigation of E-government services. Inf Syst Front 18, 579–595 (2016). https://doi.org/10.1007/s10796-015-9550-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10796-015-9550-9

Keywords

Search

Navigation