An Empirical Review of Library Discovery Tools


The Internet search concept has fostered an expectation that all users need to do is to feed relevant terms to a search engine to describe a topic or to ask a question, and click “search”. The search engine is then expected to return a list of possible relevant and useful results for users to choose from. Based on this search concept, library system developers have been developing and constructing software programs for library databases that manage scholarly information. These software programs are known as library discovery tools, or web-scale discovery (WSD) tools. In this article, the term “library discovery tools” is used when discussing search engines designed for the libraries, WSD is included. Library discovery tools are intended for intelligent searches for educational or research purposes. This article provides a practical analysis of available library discovery tools in context of the present-day explosion of available open search engines on the Internet. The focuses of our analysis include how discovery tools are expected to manage library collections, provide access to scholarly information content, as well as other factors, such as budgetary considerations, when choosing or adding a discovery tool for a library.

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Shi, X. and Levy, S. (2015) An Empirical Review of Library Discovery Tools. Journal of Service Science and Management, 8, 716-725. doi: 10.4236/jssm.2015.85073.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Luther, J. (2003) Trumping Google: Metasearching’s Promise. Library Journal, 128, 36-39.
[2] Al-Maskari, A. and Sanderson, M. (2011) The Effect of User Characteristics on Search Effectiveness in Information Retrieval. Information Processing and Management, 47, 719-729.
[3] Gross, J. and Sheridan, L. (2011) Web Scale Discovery: The User Experience. New Library World, 112, 236-247.
[4] Thompson, J., Obrig, K. and Abate, L. (2013) Web-Scale Discovery in an Academic Health Sciences Library. Medical Reference Services Quarterly, 32, 26-41.
[5] Au, N.N., Ngai, E.T. and Cheng, T.E. (2008) Extending the Understanding of End User Information Systems Satisfaction Formation: An Equitable Needs Fulfillment Model Approach. MIS Quarterly, 32, 43-66.
[6] Bolton, R.N. and Drew, J.H. (1991) A Multistage Model of Customers’ Assessments of Service Quality and Value. Journal of Consumer Research, 17, 375-384.
[7] Heinbokel, T., Sonnentag, S., Frese, M. and Stolte, W. (1996) Don’t Underestimate the Problems of User Centeredness in Software Development Projects—There Are Many! Behaviour& Information Technology, 15, 226-236.
[8] Hsieh, J., Rai, A., Petter, S. and Ting, Z. (2012) Impact of User Satisfaction with Mandated CRM Use on Employee Service Quality. MIS Quarterly, 36, 1065-A3.
[9] Condit Fagan, J., Mandernach, M., Nelson, C.S., Paulo, J.R. and Saunders, G. (2012) Usability Test Results for a Discovery Tool in an Academic Library. Information Technology & Libraries, 31, 83-112.
[10] Bhattacherjee, A. (2001) Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly, 25, 351-370.
[11] Churchill Jr., G.A. and Surprenant, C. (1982) An Investigation into the Determinants of Customer Satisfaction. Journal of Marketing Research (JMR), 19, 491-504.
[12] Shi, X., Holahan, P.J. and Jurkat, M. (2004) Satisfaction Formation Processes in Library Users: Understanding Multisource Effects. Journal of Academic Librarianship, 30, 122-131.
[13] Spreng, R.A. and Olshavsky, R.W. (1993) A Desires Congruency Model of Consumer Satisfaction. Journal of the Academy Of Marketing Science, 21, 169-177.
[14] Spreng, R.A., MacKenzie, S.B. and Olshavsky, R.W. (1996) A Reexamination of the Determinants of Consumer Satisfaction. Journal of Marketing, 60, 15-32.
[15] Petter, S., De Lone, W. and McLean, E.R. (2013) Information Systems Success: The Quest for the Independent Variables. Journal of Management Information Systems, 29, 7-62.
[16] Hoeppner, A. (2012) The Ins and Outs of Evaluating Web-Scale Discovery Services. Computers in Libraries, 32, 6-40.
[17] Buttcher, S. and Soboroff, I. (2007) Reliable Information Retrieval Evaluation with Incomplete and Biased Judgments. Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Amsterdam, 23-27 July 2007, 63-70.
[18] Vaughan, L. and Thelwall, M. (2004) Search Engine Coverage Bias: Evidence and Possible Causes. Information Processing & Management, 40, 693-707.
[19] Hoy, M.B. (2012) An Introduction to Web-Scale Discovery Systems. Medical Reference Services Quarterly, 31, 323-329.
[20] Oliver, R.L. (1995) Attribute Need Fulfillment in Product Usage Satisfaction. Psychology & Marketing, 12, 1-17.
[21] Maslow, A.H. (1943) A Theory of Human Motivation. Psychological Review, 50, 370-396.
[22] Sirgy, M. (1984) A Social Cognition Model of Consumer Satisfaction/Dissatisfaction: An Experiment. Psychology & Marketing, 1, 27-44.
[23] Cole, C. (2011) A Theory of Information Need for Information Retrieval That Connects Information to Knowledge. Journal of the American Society for Information Science and Technology, 62, 1216-1231.
[24] Saracevic, T. (2007) Relevance: A Review of the Literature and a Framework for Thinking on the Notion in Information Science. Part II: Nature and Manifestations of Relevance. Journal of the American Society for Information Science & Technology, 58, 1915-1933.
[25] Hjørland, B. (2013) User-Based and Cognitive Approaches to Knowledge Organization: A Theoretical Analysis of the Research Literature. Knowledge Organization, 40, 11-27.
[26] Venkatesh, V. and Goyal, S. (2010) Expectation Disconfirmation and Technology Adoption: Polynomial Modeling and Response Surface Analysis. MIS Quarterly, 34, 281-303.
[27] DeLone, W.H. and McLean, E.R. (1992) Information Systems Success: The Quest for the Dependent Variable. Information Systems Research, 3, 60-95.
[28] DeLone, W.H. and McLean, E.R. (2003) The DeLone and McLean Model of Information Systems Success: A Ten-Year Update. Journal of Management Information Systems, 19, 9-30.
[29] Boddy, D. and Paton, R. (2005) Maintaining Alignment over the Long-Term: Lessons from the Evolution of an Electronic Point of Sale System. Journal of Information Technology (Palgrave Macmillan), 20, 141-151.
[30] Staples, D., Wong, I. and Seddon, P.B. (2002) Having Expectation of Information Systems Benefits That Match Received Benefits: Does It Really Matter? Information & Management, 40, 115-131.
[31] Woodroof, J.B. and Kasper, G.M. (1998) A Conceptual Development of Process and Outcome User Satisfaction. Information Resources Management Journal, 11, 37-43.

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