Human emotions' role in phenomena related to information systems (IS) is increasingly of interest to research and practice, and is now informed by a burgeoning literature in neuroscience. This study develops a nomological network with an overarching view of relationships among emotions and other constructs of interest in IS research. The resulting 3-emotion systems' nomological network includes three interacting emotion systems: language, physiology, and behavior. Two laboratory experiments were conducted to test the nomological network, with six online travel service Web pages used as stimuli. The first study used paper-based self-report measures and qualitative comments, whereas the second included both self-reports and electroencephalography (EEG) measures. An outcome measure of e-loyalty was included in each study. The results of both studies showed positive and negative emotion-inducing stimuli were related to positive and negative emotions when viewing the Web sites as indicated by both self-reports and EEG data. In turn, positive and negative emotions as measured by both self-reports and EEG measures were linked to e-loyalty to some degree. This research is novel and significant because it is possibly the first in-depth study to link the study of emotions in IS with a sound theory base and multiple measurement approaches, including neuroscience measures. It shows that an EEG measure has some predictive power for an outcome such as e-loyalty. Implications of the research are that IS studies should distinguish between the different emotion systems of language and physiology, choose emotion measures carefully, and also recognize the intertwining of the emotion systems and cognitive processing.
Design science research (DSR) has staked its rightful ground as an important and legitimate Information Systems (IS) research paradigm. We contend that DSR has yet to attain its full potential impact on the development and use of information systems due to gaps in the understanding and application of DSR concepts and methods. This essay aims to help researchers (1) appreciate the levels of artifact abstractions that may be DSR contributions, (2) identify appropriate ways of consuming and producing knowledge when they are preparing journal articles or other scholarly works, (3) understand and position the knowledge contributions of their research projects, and (4) structure a DSR article so that it emphasizes significant contributions to the knowledge base. Our focal contribution is the DSR knowledge contribution framework with two dimensions based on the existing state of knowledge in both the problem and solution domains for the research opportunity under study. In addition, we propose a DSR communication schema with similarities to more conventional publication patterns, but which substitutes the description of the DSR artifact in place of a traditional results section. We evaluate the DSR contribution framework and the DSR communication schema via examinations of DSR exemplar publications. INSET: Exhibit 1. Illustration of DSR Theory Development and Knowledge...
The aim of this research essay is to examine the structural nature of theory in Information Systems. Despite the importance of theory, questions relating to its form and structure are neglected in comparison with questions relating to epistemology. The essay addresses issues of causality, explanation, prediction, and generalization that underlie an understanding of theory. A taxonomy is proposed that classifies information systems theories with respect to the manner in which four central goals are addressed: analysis, explanation, prediction, and prescription. Five interrelated types of theory are distinguished: (I) theory for analyzing, (2) theory for explaining, (3) theory for predicting, (4) theory for explaining and predicting, and (5) theory for design and action. Examples illustrate the nature of each theory type. The applicability of the taxonomy is demonstrated by classifying a sample of journal articles. The paper contributes by showing that multiple views of theory exist and by exposing the assumptions underlying different viewpoints. In addition, it is suggested that the type of theory under development can influence the choice of an epistemological approach. Support is given for the legitimacy and value of each theory type. The building of integrated bodies of theory that encompass all theory types is advocated.
Information systems with an "intelligent" or "knowledge" component are now prevalent and include knowledge-based systems, decision support systems, intelligent agents, and knowledge management systems. These systems are in principle capable of explaining their reasoning or justifying their behavior. There appears to be a lack of under, standing, however, of the benefits that can flow from explanation use, and how an explanation function should be constructed. Work with newer types of intelligent systems and help functions for everyday systems, such as word-processors, appears in many cases to neglect lessons learned in the past. This paper attempts to rectify this situation by drawing together the considerable body of work on the nature and use of explanations. Empirical studies, mainly with knowledge-based systems, are reviewed and linked to a sound theoretical base. The theoretical base combines a cognitive effort perspective, cognitive learning theory, and Toulmin's model of argumentation. Conclusions drawn from the review have both practical and theoretical significance. Explanations are important to users in a number of circumstances--when the user perceives an anomaly, when they want to learn, or when they need a specific piece of knowledge to participate properly in problem solving. Explanations, when suitably designed, have been shown to improve performance and learning and result in more positive user perceptions of a system. The design is important, however, because it appears that explanations will not be used if the user has to exert "too much" effort to get them. Explanations should be provided automatically if this can be done relatively unobtrusively, or by hypertext links, and should be context-specific rather than generic. Explanations that conform to Toulmin's model of argumentation, in that they provide adequate justification for the knowledge offered, should be more persuasive and lead to greater trust, agreement, satisfaction, and acceptance--of the explanation and possibly also of the system as a whole.