The potential of business intelligence tools for expert finding

Authors

  • Mehdi Dadkhaha
  • Mohammad Lagziana
  • Fariborz Rahim-niaa
  • Khalil Kimiafar

DOI:

https://doi.org/10.37380/jisib.v9i2.471

Keywords:

Business intelligence, business intelligence tools, expert selection, expert selection criteria, participant selection

Abstract

Finding the right experts for data gathering through interview serves as a key for particular research works. However, most expert finding methods in the literature require great deals of technical knowledge, making them somewhat impracticable for business researchers without deep technical knowledge. Accordingly, there is a need for an expert finding solution for researchers without a deep technical background. As business researchers may have knowledge about business intelligence and its tools, the use of business intelligence tools can be used to solve such issue. The present paper discusses the process of using business intelligence tools to find potential experts for example topics. Subsequently, based on a literature review, criteria are presented for distinguishing different experts. Finally, the analytic hierarchy process is discussed for assigning weights to both selection criteria and potential experts. The audience of this paper is researchers who are familiar with business intelligence tools or would like to learn how to work with them

References

Afzal, M. T., Kulathuramaiyer, N., & Maurer, H. (2008). Expertise finding for an electronic

journal. proceedings of I-Know (Graz, Austria, 436-440.

Afzal, M. T., & Maurer, H. A. (2011). Expertise Recommender System for Scientific Community. J. UCS, 17(11), 1529-1549.

Beatty, S. (2015). Analysis tools-Analyze thousands of search results in less than a minute Retrieved from https://blog.scopus.com/topics/analysis-tools

Benner, P., Tanner, C., & Chesla, C. (1992). From beginner to expert: gaining a differentiated clinical world in critical care nursing. ANS Adv Nurs Sci, 14(3), 13-28.

Bernardino, J., & Tereso, M. (2013). Business Intelligence Tools, Dordrecht.

Boeva, V., Angelova, M., & Tsiporkova, E. (2017). Data-driven Techniques for Expert Finding. Paper presented at the International Conference on Agents and Artificial Intelligence.

Bozzon, A., Brambilla, M., Ceri, S., Silvestri, M., & Vesci, G. (2013). Choosing the right crowd: expert finding in social networks. Paper presented at the Proceedings of the 16th International Conference on Extending Database Technology, Genoa, Italy.

Cameron, D. H. L., Aleman-Meza, B., Decker, S., & Arpinar, I. B. (2007). SEMEF: A taxonomybased discovery of experts, expertise and collaboration networks. University of Georgia.

Chaudhuri, S., Dayal, U., & Narasayya, V. (2011). An overview of business intelligence technology. Commun. ACM, 54(8), 88-98. doi:10.1145/1978542.1978562 DBxtra. (2018). DBxtra Online Documentation. Retrieved from www.dbxtra.com/documentation/

Demartini, G. (2007). Finding experts using wikipedia. Paper presented at the Proceedings of the 2nd International Conference on Finding Experts on the Web with SemanticsVolume 290.

Deng, H., King, I., & Lyu, M. R. (2008, 15-19 Dec. 2008). Formal Models for Expert Finding on DBLP Bibliography Data. Paper presented at the 2008 Eighth IEEE International Conference on Data Mining.

Flick, U. (2008). Designing Qualitative Research: SAGE Publications. Girvan, C., & Savage, T. (2013). Guidelines for Conducting Text Based Interviews in Virtual Worlds. In M. Childs & A. Peachey (Eds.),

Understanding Learning in Virtual Worlds (pp. 21-39). London: Springer London.

Gretsch, S., Mandl, H., & Hense, J. (2011). The Difficulty of Finding Experts-Implementation Process of Corporate Yellow Pages. Paper presented at the KMIS.

Hirsch, J. E. (2005). An index to quantify an individual's scientific research output. Proceedings of the National Academy of Sciences of the United States of America, 102(46), 16569-16572. doi:10.1073/pnas.0507655102

Imhoff, C., & White, C. (2011). Self-service business intelligence: Empowering users to generate insights. TDWI best practices report, 40.

Isaak, D. (2016). PubMed2XL (version 2.01). Journal of the Medical Library Association: JMLA, 104(1), 92.

Kao, W.-C., Liu, D.-R., & Wang, S.-W. (2010). Expert finding in question-answering websites: a novel hybrid approach. Paper presented at the Proceedings of the 2010 ACM Symposium on Applied Computing, Sierre, Switzerland.

Kardan, A., Omidvar, A., & Farahmandnia, F. (2011, 17-19 May 2011). Expert finding on social network with link analysis approach. Paper presented at the 2011 19th Iranian Conference on Electrical Engineering.

Lin, S., Hong, W., Wang, D., & Li, T. (2017). A survey on expert finding techniques. Journal of Intelligent Information Systems, 49(2), 255279. doi:10.1007/s10844-016-0440-5

Louise Barriball, K., & While, A. (1994). Collecting data using a semi-structured interview: a discussion paper. Journal of Advanced Nursing, 19(2), 328-335. doi:doi:10.1111/j.1365-2648.1994.tb01088.x

Markham, A. N. (2004). Internet communication as a tool for qualitative research. Qualitative research: Theory, method and practice, 2, 95124.

Marshall, M. N. (1996). Sampling for qualitative research. Family practice, 13(6), 522-526.

Matsuo, Y., & Ishizuka, M. (2004). Keyword Extraction From A Single Document Using Word Co-Occurrence Statistical Information. International Journal on Artificial Intelligence Tools, 13(01), 157-169. doi:10.1142/s0218213004001466

Merrouni, Z. A., Frikh, B., & Ouhbi, B. (2016, 2426 Oct. 2016). Automatic keyphrase extraction:

An overview of the state of the art. Paper presented at the 2016 4th IEEE International Colloquium on Information Science and Technology (CiSt).

Naeem, M., Khan, M. B., & Afzal, M. T. (2013). Expert Discovery: A web mining approach. Journal of AI and Data Mining, 1(1), 35-47. doi:10.22044/jadm.2013.116 Negash, S. (2004). Business intelligence. Communications of the association for information systems, 13(1), 177-195.

OpenRefine. (2018). Retrieved from http://openrefine.org/ Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., &

Hoagwood, K. (2015). Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Administration and Policy in Mental Health and Mental Health Services Research, 42(5), 533-544. doi:10.1007/s10488-013-0528-y

Patton, M. Q. (2002). Qualitative research and evaluation methods. Thousand Oaks, CA: Sage.

Quatrini Carvalho Passos Guimarães, H. C., Pena, S. B., Lopes, J. d. L., Lopes, C. T., & Bottura Leite de Barros, A. L. (2016). Experts for Validation Studies in Nursing: New Proposal and Selection Criteria. International Journal of Nursing Knowledge, 27(3), 130-135. doi:doi:10.1111/2047-3095.12089

Riahi, F., Zolaktaf, Z., Shafiei, M., & Milios, E. (2012). Finding expert users in community question answering. Paper presented at the Proceedings of the 21st International Conference on World Wide Web, Lyon, France.

Rose, S., Engel, D., Cramer, N., & Cowley, W. (2010). Automatic keyword extraction from individual documents. Text Mining: Applications and Theory, 1-20.

Ru, Z., Xu, W., & Guo, J. (2007). An Expert Experience Probabilistic Model for Enterprise Expert Finding. Paper presented at the Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007).

Saaty, T. L. (1977). A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, 15(3), 234-281.

Saaty, T. L. (1990). How to make a decision: The analytic hierarchy process. European Journal of Operational Research, 48(1), 9-26.

Saaty, T. L. (2013). Analytic Hierarchy Process. In S. I. Gass & M. C. Fu (Eds.), Encyclopedia of Operations Research and Management Science (pp. 52-64). Boston, MA: Springer US.

Serdyukov, P., & Hiemstra, D. (2008). Modeling documents as mixtures of persons for expert finding. Paper presented at the European Conference on Information Retrieval.

Sherman, R. (2014). Business Intelligence Guidebook: From Data Integration to Analytics. Newnes. Smuts, M., Scholtz, B., & Calitz, A. (2015). Design guidelines for business intelligence tools for novice users. Paper presented at the Proceedings of the 2015 Annual Research Conference on South African Institute of Computer Scientists and Information Technologists.

SuperDecsion. (2018). Retrieved from http://www.superdecisions.com/ Verborgh, R., & De Wilde, M. (2013). Using OpenRefine: Packt Publishing Ltd.

Wang, G. A., Jiao, J., Abrahams, A. S., Fan, W., & Zhang, Z. (2013). ExpertRank: A topicaware expert finding algorithm for online knowledge communities. Decision support systems, 54(3), 1442-1451.

Yang, K.-H., Chen, C.-Y., Lee, H.-M., & Ho, J.-M. (2008). EFS: Expert finding system based on Wikipedia link pattern analysis. Paper presented at the 2008 IEEE International Conference on Systems, Man and Cybernetics.

Zhang, J., Tang, J., & Li, J. (2007). Expert Finding in a Social Network, Berlin, Heidelberg.

Zhang, J., Tang, J., Liu, L., & Li, J. (2008). A Mixture Model for Expert Finding, Berlin, Heidelberg.

Zhao, Z., Zhang, L., He, X., & Ng, W. (2014). Expert finding for question answering via graph regularized matrix completion. IEEE Transactions on Knowledge and Data Engineering, 27(4), 993-1004.

Søilen, K.S. (2019) How managers stay informed about the surrounding world. Journal of Intelligence Studies in Business. 9 (1) 28-35.

Lashgari, M., Sutton-Brady, C., Solberg Søilen, K., & Ulfvengren, P. (2018). Adoption strategies of social media in B2B firms: a multiple case study approach. Journal of Business & Industrial Marketing, 33(5), 730-743.

Tontini, G., & Söilen, K. S. (2017). Nonlinear antecedents of customer satisfaction and loyalty in third-party logistics services (3PL). Asia Pacific Journal of Marketing and Logistics, (just-accepted), http://www.emeraldinsight.com/doi/pdfplus/10.1108/APJML-09-2016-0173

Søilen, K. S. (2017). Why care about competitive intelligence and market intelligence? The case of Ericsson and the Swedish Cellulose Company. Journal of Intelligence Studies in Business, 7(2).

Söilen, K. S. (2017). Why the social sciences should be based in evolutionary theory: the example of geoeconomics and intelligence studies. Journal of Intelligence Studies in Business, 7(1).

Solberg Søilen, K. (2016). Economic and industrial espionage at the start of the 21st century–Status quaestionis. Journal of Intelligence Studies in Business, 6(3).

Solberg Søilen, K. (2016). Users’ perceptions of Data as a Service (DaaS). Journal of Intelligence Studies in Business, 6(2), 43-51.

Solberg Søilen, K. (2016). A research agenda for intelligence studies in business. Journal of Intelligence Studies in Business, 6(1), 21-36.

Gedda, David, Nilsson, Billy, Såthén, Zebastian and Solberg Søilen, Klaus (2016). Crowdfunding: Finding the optimal platform for funders and entrepreneurs. Technology Innovation Management Review, 6, 3, pp. 31-40

Solberg Søilen, Klaus (2015). A place for intelligence studies as a scientific discipline. Journal of Intelligence Studies in Business, Vol. 5, No 3, pp. 34-46.

Oubrich, Mourad, Aziza, Amine, Solberg Søilen, Klaus (2015). The impact of CRM on QoE: An exploratory study from mobile phone industry in Morocco. Journal of Intelligence Studies in Business, Vol 5, No 2, pp. 22-35.

Drozdz, Sebastian, Dufwa, Marcus, Meconnen, Robiel, Solberg Søilen, Klaus (2015). An assessment of Customer Shared Value in the restaurant industry. Theoretical and Applied Economics, No. 4, 605, pp. 85-98

Granquist, C., Strömberg, F., Solberg Søilen, K. (2015). Games as a marketing channel – the impact of players and spectators. International Journal of Electronic Business Management, Vol. 13, No. 1, pp. 57-65

Vriens, Dirk, Solberg Søilen, Klaus (2014). Disruptive Intelligence - How to gather Information to deal with disruptive innovations. Journal of Intelligence Studies in Business, Vol. 4, No 3, pp. 63-78

Solberg Søilen, Klaus (2014). A survey of users’ perspectives and preferences as to the value of JISIB – A spot-check. Journal of Intelligence Studies in Business, Vol. 4, No 2, pp. 61-65

Svensson, B., Frestad Solér, M. Solberg Søilen, K. (2014). Bara segrar

Tontini, G., Söilen, K. S., & Zanchett, R. (2017). Nonlinear antecedents of customer satisfaction and loyalty in third-party logistics services (3PL). Asia Pacific Journal of Marketing and Logistics, 29(5), 1116-1135.

Agostino, Alessandro, Solberg Søilen, Klaus, Gerritsen, Bart (2013). Cloud solution in Business Intelligence for SMEs –vendor and customer perspectives, Journal of Intelligence Studies in Business Vol 3, No 3, pp. 5-28

Solberg Søilen, K. (2013). An overview of articles on Competitive Intelligence in JCIM and CIR. Journal of Intelligence Studies in Business Vol 3, No 1, pp. 44-58.

Solberg Søilen, K., Jenster, P. (2013). The Relationship between Strategic Planning and Company Performance – A Chinese perspective. Journal of Intelligence Studies in Business, Vol 3, No 1, pp. 15-30.

Tontini, G., Solberg Søilen, K., Silveira, A. (2013). How interactions of service attributes affect customer satisfaction: A study of the Kano model’s attributes. Total Quality Management & Business Excellence, Volume 24, Issue 11-12, pages 1253-1271

Solberg Søilen, K., Nerme, P., Stemström, C., Darefelt, N. (2013). Usage of internet banking among different segments – trust and information needs. Journal of Internet Banking and Commerce, Vol 18, No 2, pp. 2-18

Fri, W., Pehrsson, T., Solberg Søilen, K. (2013). How the phases of cluster development are associated with innovation – the case of China. International Journal of Innovation Science, Vol. 5, Nr. 1, pp. 31-43.

Hansson, L., Wrangmo, A. Solberg Søilen, K. (2013). Optimal ways for companies to use Facebook as a marketing channel. Journal of Information, Communication and Ethics in Society. Vol. 11 Iss: 2, pp. 112 – 126.

Solberg Søilen, K., Tontini, G. (2013). Knowledge Management systems and Human Resource Management policies for Innovation benchmarking: a study at ST Ericsson. Internatinal Journal of Innovation Science, Vol 5, No 3, pp. 159-171

Yasmina, A., Solberg Søilen, K., Vriens, D. (2012). Using the SSAV model to evaluate Business Intelligence Software. Journal of Intelligence Studies in Business, Vol 2, No 1, pp. 29-40.

Solberg Søilen, K. Hasslinger, A. (2012). Factors shaping vendor differentiation in the Business Intelligence software industry. Journal of Intelligence Studies in Business, Vol 2, No 3, pp. 48-54.

Sabanovic, A., Solberg Søilen, K. (2012). Customers’ Expectations and Needs in the Business Intelligence Software Market. Journal of Intelligence Studies in Business, Vol 2, No 1, pp. 5-20.

Solberg Søilen, K. (2012). The Fallacy of the Service Economy. European Business Review, Vol 24, Iss: 4, pp. 308-319.

. Solberg Søilen, K. (Planned for 2020) Digital Marketing. Springer: Heidelberg/Berlin

Solberg Søilen, K. (2013). Exhibit Marketing & Trade Show Intelligence - Successful Boothmanship and Booth Design. Springer Verlag, Berlin

Solberg Søilen, K. (2012). Geoeconomics. Ventus Publishing ApS/Bookboon, London (50 000+ downloads per year)

Jenster, P., Solberg Søilen, K. (2009). Market Intelligence: Building Strategic Insight. Copenhagen Business School Press, Denmark

Solberg Søilen, K. and Huber, S. (2006). 20 svenska studier för små och medelstora företag – pedagogik och vetenskaplig metod. Studentlitteratur, Lund

Solberg Søilen, K. (2005). Introduction to Public and Private Intelligence. Studentlitteratur, Lund

Solberg Søilen, K. (2005). En liten bok i Logikk. Hvordan lære å tenke. GRIN Humanities, Norderstedt, Germany

Solberg Søilen, K. (2005). Wirtschaftsspionage in Verhandlungen aus Informationsökonomischer Perspektive - Eine Interdisziplinäre Analyse. Dissertation. Faculty of Economics/Wirtschaftswissenshaftlichen Fakultät Universität Leipzig, Germany

Downloads

Published

2019-11-13

Issue

Vol. 9 No. 2 (2019): Journal of Intelligence Studies in Business

Section

Article

License

Authors who publish with this journal agree to the following terms:

    1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.

    1. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.

  1. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).