The challenges of developing the information systems (IS) that support modern enterprises are becoming less about engineering and more about people. Many of the technical issues of the past, such as hardware size and power, connectivity, and robust software, are engineering problems that have largely been solved. In the next stage of computing, the human factor will be far more important than it has been in the past: the colors of an interface or the shape of an icon are the engineering problems of the past, and the availability and usefulness of such basic solutions is rapidly coming to a close. A new paradigm is needed that provides a roadmap of higher level conceptions and values, one about humane computing. A part of this older, mechanistic approach are quantitative, economic values whose impact on IS are readily visible and acknowledged within software engineering. However, qualitative values, and in particular consumer preferences, have been researched to a lesser degree, and there has been very little direct application. To create the next-generation information systems, requirements engineers and systems developers need new methods to capture the real preferences of consumers, conceptualize these abstract concepts, and then relate such preferences to concrete requirements for information systems. To address this problem, this thesis establishes a conceptual link between the preferences of consumers and system requirements by accommodating the variations between them and expressing them via a conceptual model. Modeling such preferences and values so that they can be used as requirements for IS development is the primary contribution of this work. This is accomplished via a design science research paradigm to support the creation of the works’ primary artifact—the Consumer Preference-aware Meta-Model (CPMM). CPMM is intended to improve the alignment between business and information systems by capturing and concretizing the real preferences of consumers and then expressing such preferences via the requirements engineering process, with the eventual output being information systems. CPMM’s development relies on theoretical research contributions within three areas in information systems—Business Strategy, Enterprise Architecture, and Requirements Engineering—whose relationships to consumer values have been under-researched and under-applied. The case studies included in this thesis each demonstrate the significance of consumer preferences to each of these three areas. In the first, a set of logical mappings between CPMM and a common approach to business strategy (strategy maps/balanced scorecards) is produced. In the second, CPMM provides the conceptual undergirding to process a massive amount of unstructured consumer-generated text to generate system requirements for the airline industry. In the concluding case, an investigation of foreign and domestic students at Swedish universities is structured through CPMM, one that first discovers the requirements for a consumer preference-based online education and then produces feature models for such a software product line-based system. The significance of CPMM as a lens for discovering new concepts and highlighting important information within consumer preference data is clearly seen, and the usefulness of the meta-model is demonstrated by its broad and beneficial applicability within information systems practice and research.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:su-135505 |
Date | January 2016 |
Creators | Svee, Eric Oluf |
Publisher | Stockholms universitet, Institutionen för data- och systemvetenskap, Stockholm : Department of Computer and Systems Sciences, Stockholm University |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Doctoral thesis, comprehensive summary, info:eu-repo/semantics/doctoralThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
Relation | Report Series / Department of Computer & Systems Sciences, 1101-8526 ; 16-016 |
Page generated in 0.0024 seconds