A temporal approach to expectations and desires from knowledge management systems☆
Introduction
Knowledge management systems (KMS) are technologies employed by organizations to better retain and utilize organizational knowledge, as well as support knowledge sharing within and between organizations [2], [29]. KMS are strongly tied to the organizational practice of knowledge management (KM), which is expected to lead organizations to positive outcomes such as better decision making, improved productivity, and enhanced competitiveness. While much has been studied on the overall practice of KM and the application of KMS (see the special issues of MIS Quarterly, March/June 2005), some aspects of these systems require further study. In particular, there is still mixed evidence with respect to the success of such systems in organizations [15], [44]. Managing information systems projects is a complex task. For example, the Chaos report, published by the Standish group, indicates that in 2004 29% of IS projects failed, and a further 53% were ‘challenged’.1 A major cause of these challenges is said to be rooted in the poor understanding of users and their needs, expectations, and desires from the information systems.
This paper thus focuses on one aspect of KMS that can contribute to studies on KMS success: the formation and realization of expectations and desires related to these systems. The particular path from expectations and desires to KMS success goes through satisfaction. The expectation-confirmation theory (ECT; [28], [32]), a prominent theory from the field of marketing, places expectations and their confirmation as an important antecedent of satisfaction. IS researchers have demonstrated the applicability of this theory to IS products and the role of expectations in forming IS satisfaction in various settings (e.g., [3], [22], [23], [26], [36]). Satisfaction, in turn, has been widely investigated in the IS field in various contexts (see reviews by Khalifa and Liu [22], Sedera and Tan [31], Zviran and Erlich [46], and a meta-analysis by Mahmood et al. [25]). For example, IS researchers have examined links between satisfaction and IS evaluation [9], [11], [18], IS success [1], [31], behavioral intention to use the IS [16], organizational effectiveness and performance [18], [46], decision making and efficiency [3], and continued adoption [4], [5], [6]. Thus, a better understanding of expectations and desires from KMS, and their impact on satisfaction, is important in realizing a wide set of potential benefits.
The theoretical lens of the ECT suggests that people form expectations and desires concerning a specific product which they then compare to the perceived performance of that product. If expectations and desires are met or exceeded, satisfaction results. Otherwise the consumer is likely to become dissatisfied. Unfortunately, understanding expectations and desires of various stakeholders2 is a challenging task in the context of IS products [22], [27]. The novelty of many IS products, limited product knowledge and experience, and the dynamic nature of technology are but a few of the challenges involved in forming accurate and realistic expectations and desires [23]. These challenges may intensify with the complexity of the IS product, for example if the IS supports different business areas, promises a diverse set of benefits, or is functionally difficult to understand [27]. Such is the case of KMS.
KMS are most commonly defined as a group of technologies intended to support organizational knowledge management activities, with these activities being knowledge generation, codification, transfer, and application [2]. Indeed, an examination of a practitioners’ KM website3 reveals a long list of technologies that are viewed as KMS, including business intelligence tools, decision support tools, collaboration tools, content management and document management tools, enterprise search engines and portals, intellectual property management tools, and records management tools. Moreover, although these technologies have been around for several years, KMS are still new to many stakeholders who have limited experience with KM in general, and even more limited experience with particular technologies.
As a result, we foresee three main challenges in forming and evaluating expectations, desires, and ultimately satisfaction from KMS. First, the limited product knowledge and poor understanding of KMS may reduce the accuracy of the expectations and desires generated, leading to unrealistic perceptions of what the system should deliver to its stakeholders. Second, the obscurity of the technology may make it difficult for users to link expectations and/or desires at the product attributes level (e.g., I expect/would like to have strong business intelligence capabilities) with expectations and/or desires at the organizational outcomes level (e.g., I would like to gain market share). It makes it difficult for users to understand and/or justify how the technology is actually providing the expected and desired benefits. And third, there may be a time discrepancy between the purchase and implementation of the KMS and the confirmation of the expectations and desires from it. For example, it is likely that there will be a delay before the realization of the desire for increased market share can be evaluated reasonably. This time difference is crucial to understanding satisfaction; it may enable KMS users who are aware of the benefit lag to be more tolerant and forward looking in forming their assessments of the KMS.
In this paper, we explore the three challenges highlighted above in greater detail in order to see whether ECT can extend to contexts similar to those of KMS. Specific research questions studied in this paper are: how are expectations and desires formed? How – and if – are they translated from an abstract level to the product attributes level? And how are they realized over time? The motivation for studying these questions is both theoretical and applied. In terms of theory, ECT applications in IS have thus far focused on simple IS products and services; the theory’s extension to more complex contexts is not straightforward. Thus an examination of the nature of KMS expectations and desires constitutes an important contribution to ECT applications within the IS field. In terms of practice, if systems analysts are able to pinpoint the difficulties that stakeholders have in forming accurate expectations and desires, they can devise better strategies for communicating the capabilities and potential benefits of the systems to stakeholders. Either way, as demonstrated above, better understanding of expectations and desires is expected to lead to improved satisfaction from the system.
Because of the limited knowledge on KMS expectations and desires, this paper takes an exploratory approach, gaining insights through interviews with top managers involved with the purchase decision of their organization’s KMS. Insights from these interviews can be used in the design of KMS, in the software sale process, in the implementation phase to improve satisfaction and KM project success, and even to support post-purchase adoption (e.g., [4], [26]). The paper begins with a review of the literature, setting the background for our research objectives. We then describe the interviews conducted and the insights obtained. We conclude by highlighting the contributions of our study.
Section snippets
Expectations and desires
An expectation is a belief about the probabilities associated with a future state of affairs [17]. The literature on expectations often defines them as a hierarchy of outcomes ranging from the ideal to the worst imaginable [30]. This hierarchy is mainly concerned with how the outcome is perceived. For example, ideal expectations represent beliefs about what “can be”, while predictive expectations represent beliefs about what “will be”, and minimum tolerable expectations represent beliefs about
Method
The above sections provide the motivation for this study and identify the gaps in the literature that we seek to address. Empirically, our goal is thus to explore the applicability of a well-established theory in a new context and to modify it as needed. We are especially concerned with the suitability of the independent variables of the theory – namely expectations and desires – in the new context. Thus, quantitative approaches to theory testing may not provide sufficient insights and
Research findings
Recalling the research questions presented earlier, our goal was to answer the following: how are expectations and desires formed? How – and if – are they translated from an abstract level to the product level? And how are they realized over time? This section provides insights from the interviews with respect to these three questions.
Discussion
In the introduction to this paper, we highlighted three challenges to understanding KMS users’ expectations, desires, and ultimately satisfaction. We noted that the formation of accurate and realistic expectations and desires might be difficult; that individuals may have difficulties linking specific product attributes with desired organizational outcomes; and that the effect of expectations and desires on satisfaction may be more sequential than simultaneous. Our interviews confirmed two of
Summary
The insights obtained in this paper have important theoretical contributions both to the KMS literature and to the general literature on information systems satisfaction. These results supplement the literature focusing on expectations as opposed to desires and clarify these two terms and the relationship between them, in the context of KMS.
In addition to this theoretical contribution, this paper also provides important contributions for practitioners. Specifically, we highlight that the
Dorit Nevo is an assistant professor of Management Information Systems at the Schulich School of Business, York University, Toronto. She received her Ph.D. in Management Information Systems from the University of British Columbia and her M.Sc. in Economics from the Technion-Israel Institute of Technology. Her current research interests include expectations management, requirements analysis, and design and evaluation of knowledge management systems.
References (46)
- et al.
A critical review of end-user information system satisfaction research and a new research framework
Omega
(2002) An empirical analysis of the antecedents of electronic commerce service continuance
Decision Support Systems
(2001)- et al.
An experimental investigation of web-based information systems success in the context of electronic commerce
Decision Support Systems
(2005) The relation between user satisfaction, usage of information systems and performance
Information and Management
(1998)- et al.
Organizational knowledge resources
Decision Support Systems
(2001) - et al.
Theoretical principles for knowledge management system design: application to pediatric bipolar disorder
Decision Support Systems
(2006) - et al.
Measuring KMS success: a respecification of the DeLone and McLean’s model
Information and Management
(2006) - et al.
Using the end-user computing satisfaction (EUCS) instrument to measure satisfaction with a web site
Decision Sciences
(2005) - et al.
Review: knowledge management and knowledge management systems: conceptual foundations and research issues
MIS Quarterly
(2001) Understanding information systems continuance: an expectation-confirmation model
MIS Quarterly
(2001)
Understanding changes in belief and attitude toward information technology usage: a theoretical model and longitudinal test
MIS Quarterly
Perceived usefulness, perceived ease of use, and user acceptance of information technology
MIS Quarterly
The DeLone and McLean model of information systems success: a ten-year update
Journal of Management Information Systems
Information systems success: the quest for the dependent variable
Information Systems Research
The meaning and measurement of user satisfaction: a multigroup invariance analysis of the end-user computing satisfaction instrument
Journal of Management Information Systems
Knowledge management strategies: toward a taxonomy
Journal of Management Information Systems
Consumer satisfaction for internet service providers: an analysis of underlying processes
Information Technology and Management
The effects of knowledge management on team members’ ratings of project success and impact
Decision Sciences
The challenge of knowledge management systems: analyzing the dynamic process
Information Technology and People
Goal activation, expectations, and the placebo effect
Journal of Personality and Social Psychology
The use of comparison standards in customer satisfaction research and management: a review and proposed typology
Journal of Marketing Theory and Practice
Determinants of continued use of the WWW: an integration of two theoretical models
Industrial Management and Data Systems
Cited by (33)
Reporting health data in waiting rooms with mobile technology: Patient expectation and confirmation
2021, International Journal of Medical InformaticsIT-enabled operational agility: An interdependencies perspective
2017, Information and ManagementCitation Excerpt :Accordingly, many scholars have contributed to the knowledge of IT-enabled operational agility in this context [3–5]. In practice, however, although often carefully rationalized in advance, firms fail to realize all the expected benefits immediately post IT implementation, such that expectations of packaged solutions like enterprise systems are often disassociated from their continuance [6,7]. An understanding of the developmental and management aspects of IT-enabled operational agility continues to elude research and practice [3].
Continuance of protective security behavior: A longitudinal study
2016, Decision Support SystemsCitation Excerpt :This stream has been widely used in behavioral research to study consumer satisfaction, repurchase intentions, and associated post-purchase behaviors, including service quality expectations and perceptions [23] and mobile commerce [24]. Recently, ECT has been applied to the field of information systems for understanding user satisfactions and intentions to re-use various information technologies, including knowledge management systems [25] and application service provision [26]. Within the realm of information systems, a more sophisticated, two-step model of belief and attitude change was developed [27].
Clinical information systems end user satisfaction: The expectations and needs congruencies effects
2015, Journal of Biomedical InformaticsCitation Excerpt :In the context of end user satisfaction of information systems, it will be more useful to explore the influence of higher-level desires on end user satisfaction because there has already been extensive research on the various attributes of information systems that can affect end user satisfaction. Furthermore, prior IS studies [19] have shown that the conversion of higher-level desires into concrete product attributes (especially in the case of complex IS such as CIS) is not easy or straightforward for different IS stakeholders. To identify these higher-level needs (desires), we reviewed needs theories in the psychology literature.
Examining the adoption of KMS in organizations from an integrated perspective of technology, individual, and organization
2014, Computers in Human BehaviorCitation Excerpt :These three constructs thus represent users’ overall evaluations of a system, and have positive effects on user satisfaction. Nevo and Chan (2007a), Nevo and Chan (2007b) find that system-related attributes and quality, such as useful system functions (i.e., system quality), high quality content and appropriate formats of system outputs (i.e., information quality), and quick responses to the queries regarding system use (i.e., service quality), are positively associated with employee intentions to use a KMS. Based on the above discussion, the following hypotheses are proposed:
Dorit Nevo is an assistant professor of Management Information Systems at the Schulich School of Business, York University, Toronto. She received her Ph.D. in Management Information Systems from the University of British Columbia and her M.Sc. in Economics from the Technion-Israel Institute of Technology. Her current research interests include expectations management, requirements analysis, and design and evaluation of knowledge management systems.
Yolande E. Chan is a Professor and E. Marie Shantz Research Fellow in MIS at Queen’s University in Canada. She holds a Ph.D. from the University of Western Ontario, an M.Phil. in Management Studies from Oxford University, and S.M. and S.B. degrees in Electrical Engineering and Computer Science from MIT. Prior to joining Queen’s, she worked with Andersen Consulting (now Accenture). Currently she serves as Director, The Monieson Centre. Dr. Chan conducts research on knowledge management, information privacy, strategic alignment, and information systems performance. She has published her findings in journals such as Information Systems Research, MIS Quarterly Executive, Journal of Management Information Systems, Journal of the Association for Information Systems, Journal of Strategic Information Systems, Information and Management, IEEE Transactions on Engineering Management and The Academy of Management Executive. Dr. Chan is a member of several journal editorial boards and is an officer of the Association for Information Systems.
- ☆
This work was supported by grants from the Natural Sciences and Engineering Research Council of Canada and the Social Sciences and Humanities Research Council of Canada. We would like to thank the editor and three anonymous reviewers for their suggestions and insights.