Applying means-end chain theory to eliciting system requirements and understanding users perceptual orientations
Introduction
User participation in systems development has been considered to be an important factor in achieving system success. Thus, in requirement analysis it provides a more accurate and complete definition of the information requirements [26]. User requirement analysis occurs at the early stage of system development process, and determining correct and complete information requirements sets the stage for an effective development process that increases the likelihood of success in the implementation and allows for early correction of errors while the cost is lower [9].
Requirements analysis is where system analysts interact with end users to identify and specify material needed to develop an IS [2]. This paper concentrates on the determination of needs. Various techniques exist, including interviewing, using questionnaires, observing users, analyzing documents, prototyping, joint application design (JAD), and others. But these are not concerned with how users perceive the benefits produced by the system attributes (features), and what personal values the benefits reinforce.
Means-end chain theory is a methodology to identify the linkages between the attributes that exist in products, the consequences to the consumers provided by the attributes, and the personal values that the consequences reinforce [25]. It has been successfully applied to new product development, brand positioning, advertising strategy development, etc. [30]. However, means-end chain theory has not been applied to IS development. This research demonstrated the value in applying this approach to eliciting user requirements and understanding how users perceive the benefits to users. The sample system is Web-based and used for editing, transmitting, and managing organizational documents: i.e., a Web-based document management system.
To meet the challenge of developing systems that satisfy various user requirements, system developers need to achieve a better understanding of factors that lead to system usage [13]. Values are believed to be centrally held cognitive elements that stimulate motivation for behavioral response (e.g., brand choice and product usage) [12], [16], [17], [20], [22], [29]. Based on this, the proposed model fuses the attribute–consequence–value (A–C–V) model and the technology acceptance model (TAM), into an A–C–V–I (intention)–U (use) model. TAM assumed that perceived usefulness and perceived ease of use are fundamental determinants of user acceptance of information technology [3]. However, the A–C–V–I–U model posits that factors at the consequence level lead to factors at the value level, which in turn lead to behavioral intention to use the system. The A–C–V–I–U model allows us to understand the attribute, consequence and value factors that ultimately lead to system usage.
Section snippets
Means-end chain theory
The means-end chain theory involves people’s cognitive structures of purchasing behavior. A means-end chain model [8] results from the linkages between product attributes, consumption consequences or benefits produced by the product, and personal values.
Attributes are features or aspects of products or services. They can be physical, such as color, or abstract, such as quality. Consequences (functional or psychosocial) accrue to people from consuming products or services. Functional
Sample
My research used focus group to elicit all attribute, consequence, and value elements. The group consists of 32 participants of two types: staff and part-time MIS graduate students in the same university. The staff has experience in editing, transmitting, and managing documents, and some in browsing information and using Web-based systems. The part-time MIS graduate students have more knowledge about the Web technology than the staff. Each group consisted of four staff and four graduate
Conclusions, implications, and limitations
When developing a large and sophisticated IS, system analysts and developers would like to gather correct and complete information requirements, understand factors that ultimately lead to system usage, detect errors, and take corrective action early, and thus increase the likelihood of success in the implementation of the IS.
Many techniques exist for eliciting user requirements. The techniques, however, generally deal with determination of functional and interface features. Understanding users’
Acknowledgements
The author wishes to thank the chief editor and anonymous reviewers for their helpful comments. Thanks are also due to Chin-Feng Lin and Meng-Hsiang Hsu for their helpful suggestions. This research was supported in part by the National Science Council (NSC) of Taiwan under grant number NSC 91-2416-H-327-015.
Chao-Min Chiu is an Associate Professor in the Department of Information Management at the National Kaohsiung First University of Science and Technology, Taiwan, ROC. He holds a Ph.D. in Management from the Rutgers University. His current research interests include hypermedia support for decision-making, electronic commerce, and knowledge management. His research has been published in the Computer Networks and ISDN Systems, Decision Support Systems, Information & Management, Information and
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Chao-Min Chiu is an Associate Professor in the Department of Information Management at the National Kaohsiung First University of Science and Technology, Taiwan, ROC. He holds a Ph.D. in Management from the Rutgers University. His current research interests include hypermedia support for decision-making, electronic commerce, and knowledge management. His research has been published in the Computer Networks and ISDN Systems, Decision Support Systems, Information & Management, Information and Software Technology, Information Systems Management, Information Technology & Management, and Journal of Information Science, etc.