Data Quality Strategy Selection in CRIS: Using a Hybrid Method of SWOT and BWM

Otmane Azeroual, Mohammad Javad Ershadi, Amir Azizi, Melikasadat Banihashemi, Reza Edris Abadi


Data quality has been considerably faced with more attention in recent years. While improving the quality of any type of information system needs to apply data quality dimensions, this process is a strategic decision of any organization. Current Research Information System (CRIS) is a state of the art information system which manages different processes for acquisition, indexing, and dissemination of researches funded by research funders. In this paper, quality improvement programs for a CRIS are strategically defined using Strength, Weakness, Opportunity and Threaten (SWOT) approach. According to examined SWOT method, weaknesses (such as failure to evaluate the quality of information contained in the research), strengths (such as the accuracy of information classification), opportunities (such as the presence of university representatives in the process of thesis/dissertation registration) and threats (such as transfer of incorrect information by other systems) are identified and categorized. Besides, data quality dimensions are considered for determining all strategies for improving CRIS. An advanced multi-criteria decision-making method called Best-Worst Method (BWM) is applied for prioritizing obtained strategies. Results of proposed methodology indicated that the development and classification of the appropriate space for recording, controlling, indexing and disseminating the received information is obtained the first rank among the other strategies. Also, the creation of a comprehensive knowledge database for all researches in different universities is another main strategy that is ranked in second priority.

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Azeroual, O. & Schöpfel, J. (2019). Quality Issues of CRIS data: An exploratory investigation with universities from twelve countries. Publications, 7(1), 14.

Ershadi, M. J., & Aiassi, R. (2017). A Model for Quality Assurance on Acquisition and Registration, Processing, and Dissemination of Theses and Dissertations Systems.Journal of Information Technology Management,9(2), 167-190.

Waddington, S., Sudlow, A., Walshe, K., Scoble, R., Mitchell, L., Jones, R., & Trowell, S. (2013). Feasibility study into the reporting of research information at a national level within the uk higher education sector. New review of information networking, 18(2), 74-105.

Quix, C., & Jarke, M. (2014). Information integration in research information systems. Procedia Computer Science, 33, 18-24.

Azeroual, O., Saake, G. & Abuosba, M. (2018). Data quality measures and data cleansing for research information systems. Journal of Digital Information Management, 16(1), 12–21.

Azeroual, O., Saake, G. & Schallehn, E. (2018). Analyzing data quality issues in research information systems via data profiling. International Journal of Information Management, 41, 50–56.

Chitsaz, N., & Azarnivand, A. (2017). Water scarcity management in arid regions based on an extended multiple criteria technique. Water Resources Management, 31(1), 233-250.

Maghsoodi, A. I., Mosavat, M., Hafezalkotob, A., & Hafezalkotob, A. (2019). Hybrid hierarchical fuzzy group decision-making based on information axioms and BWM: Prototype design selection. Computers & Industrial Engineering, 127, 788-804.

Gupta, H., & Barua, M. K. (2018). A framework to overcome barriers to green innovation in SMEs using BWM and Fuzzy TOPSIS. Science of The Total Environment, 633, 122-139.

Cassidy, A. (2016).A practical guide to information systems strategic planning. CRC press.

Dubey, S., Verma, K., Rizvi, M. A., & Ahmad, K. (2018). SWOT Analysis of Cloud Computing Environment. In Big Data Analytics(pp. 727–737). Springer, Singapore.

Batini, C., Cappiello, C., Francalanci, C., & Maurino, A. (2009). Methodologies for data quality assessment and improvement. ACM computing surveys(CSUR), 41(3), 16.

Blumenberg, S., Wagner, H. T., & Beimborn, D. (2009). Knowledge transfer processes in IT outsourcing relationships and their impact on shared knowledge and outsourcing performance. International Journal of Information Management, 29(5), 342–352.

Al-Emran, M., Mezhuyev, V., Kamaludin, A., & Shaalan, K. (2018). The impact of knowledge management processes on information systems: A systematic review. International Journal of Information Management, 43, 173–187.

Lee, J. N. (2001). The impact of knowledge sharing, organizational capability and partnership quality on IS outsourcing success. Information & Management, 38(5), 323–335.

Lee, C. P., Lee, G. G., & Lin, H. F. (2007). The role of organizational capabilities in successful e-business implementation. Business Process Management Journal, 13(5), 677–693.

Lee, J. C., Shiue, Y. C., & Chen, C. Y. (2016). Examining the impacts of organizational culture and top management support of knowledge sharing on the success of software process improvement. Computers in Human Behavior, 54, 462–474.

Spender, J. C. (1996). Making knowledge the basis of a dynamic theory of the firm. Strategic management journal, 17(S2), 45–62.

De Long, D. (1997). Building the knowledge-based organization: How culture drives knowledge behaviors. Ernst & Young Center for Business Innovation, Working Paper, Boston.

Soto-Acosta, P., Popa,S., & Palacios-Marqués, D. (2017). Social web knowledge sharing and innovation performance in knowledge-intensive manufacturing SMEs. The Journal of Technology Transfer, 42(2), 425–440.

Tiwana, A. (2000). The knowledge management toolkit: practical techniques for building a knowledge management system. Prentice Hall PTR.

Figueiredo, M. S. N., & Pereira, A. M. (2017). Managing knowledge–the importance of databases in the scientific Production. Procedia Manufacturing, 12, 166-173.

Hoegl, M., & Schulze, A. (2005). How to Support Knowledge Creation in New Product Development: An Investigation of Knowledge Management Methods. European management journal, 23(3), 263-273.

Chong, A. Y. L., Chan, F. T., Goh, M., & Tiwari, M. K. (2013). Do inter-organizational relationships and knowledge-management practices enhance collaborative commerce adoption? International Journal of Production Research, 51(7), 2006–2018.

Lin, H. F., & Lee, G. G. (2005). Impact of organizational learning and knowledge management factors on e-business adoption. Management Decision, 43(2), 171–188.

Migdadi, M. M., Abu Zaid, M. K. S., Al-Hujran, O. S., & Aloudat, A. M. (2016). An empirical assessment of the antecedents of electronic-business implementation and the resulting organizational performance. Internet Research, 26(3), 661–688.

Turban, E., Sharda, R., & Delen, D. (2010). Decision Support and Business Intelligence Systems (9thEdition). Prentice Hall, Upper Saddle River.

Mitchell, H. J. (2003). Technology and knowledge management: Is technology just an enabler or does it also add value?In Knowledge management: Current issues and challenges (pp. 66–78). IGI Global.

Aljumaili, M., Karim, R., & Tretten, P. (2016). Metadata-based data quality assessment.VINE Journal of Information and Knowledge Management Systems,46(2), 232–250.

Ershadi, M. J., Aiasi, R., & Kazemi, S. (2018). Root cause analysis in quality problem solving of research information systems: a case study.International Journal of Productivity and Quality Management,24(2), 284-299.

Collins, F. S., & Tabak, L. A. (2014). Policy: NIH plans to enhance reproducibility. Nature, 505(7485), 612-613.

Li, F., Hu, J., Xie, K., & He, T. C. (2015). Authentication of experimental materials: A remedy for the reproducibility crisis?Genes & diseases, 2(4), 283.

Timmerman, Y., & Bronselaer, A. (2019). Measuring data quality in information systems research. Decision Support Systems, 126, 113138.

Ershadi, M. J., & Forouzandeh, M. (2019). Information Security Risk Management of Research Information Systems: A hybrid approach of Fuzzy FMEA, AHP, TOPSIS and Shannon Entropy.Journal of Digital Information Management,17(6), 321.

Ershadi, M. J., Jalalimanesh, A., & Nasiri, J. (2019). Designing a Metadata Quality Model: Case Study of Registration System of Iranian Research Institute for Information Science and Technology.Iranian Journal of Information processing and Management,34(4), 1505-1534.

Mezghani, E., Exposito, E., & Drira, K. (2016). A collaborative methodology for tacit knowledge management: Application to scientific research. Future Generation Computer Systems, 54, 450–455.

Ershadi, M. J., Niaki, S. T. A., & Sadeghee, R. (2019). Evaluation and improvement of service quality in information technology department of a detergent production company using the SERVQUAL approach.International Journal of Services and Operations Management,34(2), 228-240.

Batini, C., & Scannapieco, M. (2016). Data and information quality.Cham, Switzerland: Springer International Publishing.

Marsden, J. R., & Pingry, D. E. (2018). Numerical data quality in IS research and the implications for replication. Decision Support Systems, 115, A1-A7.

Azeroual, O., Saake, G. & Wastl, J. (2018). Data measurement in research information systems: Metrics for the evaluation of the data quality. Scientometrics, 115(3), 1271–1290.

Wang, R. Y., & Strong, D. M. (1996). Beyond accuracy: Whatdata quality means to data consumers? Journal of management information systems, 12(4), 5–33.

Gürel, E., & Tat, M. (2017). SWOT ANALYSIS: A THEORETICAL REVIEW.Journal of International Social Research,10(51).

Phadermrod, B., Crowder, R. M., & Wills, G. B. (2019). Importance-performance analysis based SWOT analysis.International Journal of Information Management,44, 194–203.

Johansson, Å., & Ottosson, M. O. (2012). A national current research information system for Sweden.

Fernandes, S. (2019). Looking deep at current research information systems. Qualitative and Quantitative Methods in Libraries, 7(2), 281-291.

Rezaei, J. (2015). Best-worst multi-criteria decision-making method.Omega,53, 49–57.

Bruce, T. R., & Hillmann, D. I. (2004). The continuum of metadata quality: defining, expressing, exploiting. ALA editions.

Campanella, P., Lovato, E., Marone, C., Fallacara, L., Mancuso, A., Ricciardi, W., & Specchia, M. L. (2015). The impact of electronic health records on healthcare quality: a systematic review and meta-analysis.The European Journal of Public Health,26(1), 60–64.

Zimmerman, E.H. (2002). CRIS-Cross: Research Information Systems at a Crossroads. CRIS2002: 6th International Conference on Current Research Information Systems (Kassel, August 29-31, 2002).

Wenaas, L., Karlstrom, N., Vatnan, T. (2012). From a national CRIS along the road to Green Open Access –and back again: Building infrastructure from CRIStin to Institutional Repositories in Norway. CRIS2012: 11th International Conference on Current Research Information Systems (Prague, June 6-9, 2012).


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