Driving innovation through big open linked data (BOLD): Exploring antecedents using interpretive structural modelling

Information Systems Frontiers

Volumn 19, Issue 2, 2017, Pages 197-212

  Dwivedi, Yogesh K ^a   Janssen, Marijn ^b   Slade, Emma L ^a   Rana, Nripendra P ^a   Weerakkody, Vishanth ^c   Millard, Jeremy ^c,d   Hidders, Jan ^e   Snijders, Dhoya ^f  

^a SWANSEA UNIVERSITY   (United Kingdom)

^b DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

^c BRUNEL UNIVERSITY   (United Kingdom)

^d DANISH TECHNOLOGICAL INSTITUTE   (Denmark)

^e VRIJE UNIVERSITEIT BRUSSEL   (Belgium)

^f Researcher Data Society   (Netherlands)

Author keywords

Big data; Innovation; Interpretive structural modelling; Linked data; Open data

Indexed keywords

DATA HANDLING; INNOVATION;

DATA QUALITY; EXTERNAL PRESSURES; KNOWLEDGE BUILDING; LINKED DATUM; NEW SOLUTIONS; OPEN DATUM; STRUCTURAL MODELLING; TECHNICAL INFRASTRUCTURE;

BIG DATA;

EID: 84978160759     PISSN: 13873326     EISSN: 15729419     Source Type: Journal    
DOI: 10.1007/s10796-016-9675-5     Document Type: Article

References (37)

1. Agarwal, A., Shankar, R., & Tiwari, M. K. (2007). Modeling agility of supply chain. Industrial Marketing Management, 36(4), 443–457.
2. Attri, R., Dev, N., & Sharma, V. (2013). Interpretive structural modelling (ISM) approach: An overview. Research Journal of Management Science., 2(2), 3–8.
3. Behkamal, B., Kahani, M., Bagheri, E., & Jeremic, Z. (2014). A metrics-driven approach for quality assessment of linked open data. Journal of Theoretical and Applied Electronic Commerce Research., 9(2), 64–79.
4. Chen, H., Chiang, R. & Storey, V. (2012). Business intelligence and analytics: from big data to big impact. MIS Quarterly 36(4), 1165–1188.
5. Dwivedi, Y. K., Wastell, D., Laumer, S., Henriksen, H. Z., Myers, M. D., Bunker, D., Elbanna, A., Ravishankar, M. N., & Srivastava, S. C. (2015a). ‘research on information systems failures and successes: status update and future directions’. Information Systems Frontiers, 17(1), 143–157.
6. Dwivedi, Y., Weerakkody, V., Janssen, M., Millard, J., Hidders, J., Snijders, D., Rana, N. & Slade, E. (2015b). Driving innovation using big open linked data (BOLD) panel. Proceedings of the 14th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society. 13–15 October, Delft, The Netherlands.
7. Ferro, E., Loukis, E., Charalabidis, Y., & Osella, M. (2013). Policy making 2.0: From theory to practice. Government Information Quarterly, 30(4), 359–368.
8. Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137–144.
9. Hauser, J., Tellis, G., & Griffin, A. (2006). Research on innovation: A review and agenda for Marketing Science. Marketing Science, 25(6), 687–717.
10. Holland, J. H. (1996). Hidden order. How adaptation creates complexity. Reading, MA: Addison Wesley.
11. Hossain, M. A., Dwivedi, Y. K., & Rana, N. P. (2016). State of the art in open data research: insights from existing literature and a research agenda. Journal of Organizational Computing and Electronic Commerce, 26(1–2), 14–40.
12. Hota, C., Upadhyaya, S., & Al-Karaki, J. N. (2015). Advances in secure knowledge management in the big data era. Information Systems Frontiers, 17(5), 983–986.
13. Hughes, D. L., Dwivedi, Y. K., Simintiras, A. C., & Rana, N. P. (2015). Success and failure of IS/IT projects: A state of the art analysis and future directions. Springer Briefs in Information Systems, Springer International Publishing, available at: http://link.springer.com/book/10.1007%2F978-3-319-23000-9.
14. Janssen, M. & Kuk, G. (2016). Big and open linked data (BOLD) in research, policy and practice. Journal of Organizational Computing and Electronic Commerce. 26(1–2), 3–13.
15. Janssen, M., Matheus, R. & Zuiderwijk, A. (2015). Big and open linked data (BOLD) to create smart cities and citizens: Insights from smart energy and mobility cases. Proceedings of the 14th IFIP WG 8.5 International Conference on EGOV. 30 August-2 September, Thessaloniki, Greece.
16. Janssen, M., Charalabidis, Y., & Zuiderwijk, A. (2012). Benefits, adoption barriers and myths of open data and open government. Information Systems Management, 29(4), 258–268.
17. Jetzek, T., Avital, M., & Bjorn-Andersen, N. (2014). Data-driven innovation through open government data. Journal of Theoretical and Applied Electronic Commerce Research., 9(2), 100–120.
18. Jharkharia, S., & Shankar, R. (2005). IT-enablement of supply chains: understanding the barriers. Journal of Enterprise Information Management, 18(1), 11–27.
19. Juell-Skielse, G., Hjalmarsson, A., Juell-Skielse, E., Johannesson, P., & Rudmark, D. (2014). Contests as innovation intermediaries in open data markets. Information Polity, 19(3, 4), 247–262
20. Kankanhalli, A., Hahn, J., Tan, S., & Gao, G. (2016). Big data and analytics in healthcare: introduction to the special section. Information Systems Frontiers 18(2), 233–235.
21. Lassinantti, J., Bergvall-Kåreborn, B., & Ståhlbröst, A. (2014). Shaping local open data initiatives: Politics and implications. Journal of Theoretical and Applied Electronic Commerce Research., 9(2), 17–33.
22. Mandal, A., & Deshmukh, S. G. (1994). Vendor selection using interpretive structural modelling (ISM). International Journal of Operations & Production Management, 14(6), 52–59.
23. McKinsey & Company (2011). Big Data: The Next Frontier for Innovation, Competition and Productivity. Accessed from file:///C:/users/Emma%20Slade/Downloads/MGI_big_ data_full_report.pdf. Accessed on 8 November 2015.
24. Nugroho, R. P., Zuiderwijk, A., Janssen, M., & de Jong, M. (2015). A comparison of national open data policies: lessons learned. Transforming Government: People, Process and Policy, 9(3), 286–308.
25. Open Government Partnership (2014). Annual Report Accessed from http://www.opengovpartnership.org/sites/default/files/attachments/2014%20OGP%20Annual%20Report.pdf. Accessed on 8 November 2015.
26. Park, S.-H., Huh, S.-Y., Oh, W., & Han, S. (2012). A social network-based inference model for validating customer profile data. MIS Quarterly, 36(4), 1217–1237.
27. Sage, A. P. (1977). Interpretive structural modelling: Methodology for Large Scale Systems. New York. New York: McGraw-Hill.
28. Sayogo, D., Zhang, J., Pardo, T., Tayi, G., & Hrdinova, J. (2014). Going beyond open data: Challenges and motivations for smart disclosure in ethical consumption. Journal of Theoretical and Applied Electronic Commerce Research., 9(2), 1–16.
29. Shadbolt, N., O’Hara, K., Berners-Lee, T., Gibbins, N., Glaser, H., Hall, W. & Schraefel, M. (2012). Linked open government data: lessons from Data.gov.uk. IEEE Intelligent Systems 27(3), 16–24.
30. Singh, R. K., Garg, S. K., & Deshmukh, S. G. (2007). Interpretive structural modelling of factors for improving competitiveness of SMEs. International Journal of Productivity and Quality Management., 2(4), 423–440.
31. Susha, I., Grönlund, Å., & Janssen, M. (2015). Organizational measures to stimulate user engagement with open data. Transforming Government: People, Process and Policy, 9(2), 181–206.
32. Talib, F., Rahman, Z., & Qureshi, M. N. (2011). An interpretive structural modelling approach for modelling the practices of total quality management in service sector. International Journal of Modelling in Operations Management, 1(3), 223–250.
33. Van der Panne, G., Van Beers, C. & Kleinknecht, A. (2003). Success and failure of innovation: a literature review. International Journal of Innovation Management 7(3), 1–30.
34. Warfield, J. N. (1974). Toward interpretation of complex structural models. IEEE Transactions on Systems, Man, and Cybernetics, 4(5), 405–417.
35. Zuiderwijk, A., Janssen, M. & Dwivedi, Y. (2015). Acceptance and use predictors of open data technologies: drawing upon the unified theory of acceptance and use of technology. Government Information Quarterly Doi:10.1016/j.giq.2015.09.005.
36. Zuiderwijk, A. & Janssen, M. (2014). The negative effects of open government data – Investiating the dark side of open data. Proceedings of the 15th Annual International Conference on Digital Government Research. 18–21 June, Aguascalientes City, Mexico.
37. Zuiderwijk, A., Helbig, N., Gil-García, R. & Janssen, M. (2014). Special issue on innovation through open data – A review of the state-of-the-art and an emerging research agenda: Guest editors’ introduction. Journal of Theoretical and Applied Electronic Commerce Research. 9(2), I-XIII