논문 영어: 서론편 2, 문제제기 (1~20)

1. This study examines the ways in which users with varying levels of expertise use alternative types of KBS explanations and the impact of such use on users’ judgments.
2. Prior research has studied the use of various subsets of explanation types by KBS users of varying knowledge levels.
3. This study examines how professionals with high levels of task experience use a KBS that has a full range of explanation types.
4. Prior research has demonstrated that the type of explanations selected by users differs based on available options.
5. Additionally, prior KBS studies have not used professional decision makers to make high-level, complex judgments, limiting the understanding of how KBS are used and the related impact on decision making processes for systems deployed in corporate environments.
6. The objective of this paper is to examine the relationship between information transparency and consumer willingness to partake in personalization.
7. We examine two research questions.
8. This paper uses a utility maximization theory framework to examine these questions.
9. The key question is: What constitutes appropriate research standards for tenure and promotion?
10. The goal of this paper is to provide a set of empirical benchmarks that can be used as a foundation for establishing local standards for research performance in the promotion and tenure decision.
11. We then use these percentiles to develop our recommendations for different local standards.
12. We draw from and extend Nonaka’s (1994) theory of knowledge creation to develop a model of media selection and use in the KC process.
13. In our model development, we explore KC as a dynamic, time- and experience-dependent process.
14. We incorporate time as a central concept to explain the KC process and the behavior of individuals engaged in it.
15. Our objective is to characterize the KC process and its relationship to media selection and use.
16. Recently, IS researchers have begun investigating an emerging, technology-enabled innovation that involves the use of intelligent software agents along the enterprise supply chain. For instance, many scholars.
17. Early results from the laboratory suggest this enables supply chain management and decision making in modes not supported previously by IT. For instance, emerging, agent-enabled, supply chain functionalities can enable whole new business models and modes of operation.
18. Indeed, federations and swarms of software agents today are moving the boundaries of computer-aided decision making.
19. Some of the shifts (e.g., people using agents such as shopping “bots” to gather product information) are technologically incremental, explained well by IS theory, and found broadly in practice today. But other shifts (e.g., software agents using people to clarify procurement ambiguity) are technologically abrupt, explained less well in terms of current theory, and found rarely in practice today.
20. As the advancing capabilities of software agents enable progressive transition from computer-based decision aids to computer-based decision makers, important questions arise about where to use such agents best, how much decision-making authority to grant them, when people need to intervene in autonomous-agent processes, and how new designs may overcome persistent technological inadequacies of agent software today.