A Theory of Decision Support System Design for User Calibration

Kasper, George M.

doi:10.1287/isre.7.2.215

Cited by 87 publications

(55 citation statements)

References 84 publications

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“…The latter are computer-based technologies designed to assist an individual (or a group) in making a decision or choosing a course of action in a nonroutine situation that requires judgment (Kasper 1996). Decision support systems contain one or more tools, or decision aids, that perform distinct information processing tasks or functions (e.g., search a database or sort objects by some criterion).…”

Section: Human Decision Making and Decision Aidsmentioning

confidence: 99%

Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids

2000

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Despite the explosive growth of electronic commerce and the rapidly increasing number of consumers who use interactive media (such as the World Wide Web) for both pre-purchase information search and online shopping, very little is known about how consumers make purchase decisions in such settings. A unique characteristic of online shopping environments is that they allow vendors to create retail interfaces that include highly interactive features. One form of interactivity that is desirable from a consumer perspective is the implementation of sophisticated tools designed to assist shoppers in making their purchase decisions by customizing the electronic shopping environment to their individual preferences. The availability of such tools, which we refer to as interactive decision aids for consumers, may lead to a transformation of the way in which shoppers search for product information and make purchase decisions. The primary objective of this paper is to investigate the nature of the effects that interactive decision aids may have on consumer decision making in online shopping environments.A well-known phenomenon regarding purchase decision making is that consumers are often unable to evaluate all available alternatives in great depth and, thus, tend to use two-stage processes to reach their decisions. A typical purchase decision process may unfold as follows: First, the consumer screens a large set of relevant products and identifies a subset that includes the most promising alternatives. Subsequently, s/he evaluates the latter in more depth, performs relative comparisons across products on important attributes, and makes a purchase decision. Given the different tasks to be performed in the course of such a two-stage process, interactive tools that provide support to consumers in the following two respects are particularly valuable: (1) the initial screening of available products to determine which ones are worth considering further and (2) the indepth comparison of selected products before making the actual purchase decision. This paper examines the effects of two decision aids, each designed to assist consumers in performing one of the above tasks, on purchase decision making in an online store.The first of the two interactive tools, a recommendation agent (RA), allows consumers to more efficiently screen the (potentially very large) set of alternatives available in an online shopping environment. Based on self-explicated information about a consumer's own utility function (attribute importance weights and minimum-acceptable attribute levels), the RA generates a personalized list of recommended alternatives. The second decision aid, a comparison matrix (CM), is designed to assist consumers in making in-depth comparisons among those alternatives that appear most promising based on the initial screening. The CM allows consumers to organize attribute information about multiple products in an alternatives × attributes matrix and to have alternatives sorted by any attribute.Based on theoretical and empiri...

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Section: Human Decision Making and Decision Aidsmentioning

confidence: 99%

Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids

2000

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“…Much work remains to be carried out in this area but Kasper (1996) has proposed a theory on how support systems should be designed to enable the user to achieve, what he calls, "perfect calibration". Underpinning this theory is the notion that a person's calibration depends upon two factors: i) what they know and ii) what they think they know and that these factors, in turn, are based on their mental representation of a problem (Gigerenzer et al,1991).…”

Section: ) Manipulating Users' Confidencementioning

confidence: 99%

The design features of forecasting support systems and their effectiveness

Fildes

Goodwin

Lawrence

2006

Decision Support Systems

109

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Forecasts play a key role in the management of the supply chain. In most organisations such forecasts form part of an information system on which other functions such as scheduling, resource planning and marketing depend. Forecast accuracy is, therefore, an important component in the delivery of an effective supply chain. Typically, the forecasts are produced by integrating managerial judgment with quantitative forecasts within a forecasting support system (FSS). However, there is much evidence that this integration is often carried out poorly with deleterious effects on accuracy. This study considers the role that a well-designed FSS might have in improving this situation. It integrates the literatures on forecasting and decision support to explain the causes of the problem and to identify design features of FSSs that might help to ameliorate it. An assessment is made of the extent to which currently available business forecasting packages, which are widely employed in supply chain management, possess these features.

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“…This is precisely our position; certainly our efforts are complementary to Gregor and Jones. However, while they propose extending knowledge capture by extending the definition of an ISDT, we propose keeping the Walls et al definition of ISDT as almost purely prescriptive and extending knowledge capture with the addition of DREPT. We justify this on several grounds: First, we observe that the ISDT of Walls et al (1992Walls et al ( , 2004) is currently more familiar to the majority of DSRIS practitioners (March & Storey, 2008) and since that ISDT definition guided many past exemplars of DSRIS (Adomavicius, Bockstedt, Gupta, & Kauffman, 2008;Kasper, 1996;Markus et al, 2002;PriesHeje & Baskerville, 2008), it allows us to make highly informative cross-study comparisons. Second, we propose that two distinct modes of knowledge capture intended for quite different purposes -a prescriptive ISDT to capture low-level (construction) design knowledge and DREPT to capture artifact-relevant explanatory-predictive knowledge -are more comprehensible and do not overburden the already "busy", multifaceted Walls et al information representation.…”

Section: Extending Knowledge Capture In Dsris: Alternative Approachesmentioning

confidence: 87%

“…In Section 8, we present an epistemological perspective of the framework and relate it to specific activities in the design research activity cycle. Throughout these discussions, abstract points are related to aspects of concrete projects (Kasper, 1996;Kuechler & Vaishnavi, 2008b;). In Section 9, to demonstrate the utility of the framework, we extend several published examples of DSRIS with proposals for mid-range theories that derive logically from the constructs in the kernel theories and the design theories of the examples.…”

Section: Extending Knowledge Capture In Dsris: Alternative Approachesmentioning

confidence: 99%

A Framework for Theory Development in Design Science Research: Multiple Perspectives

Kuechler¹,

Vaishnavi²

2012

JAIS

197

180

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A Theory of Decision Support System Design for User Calibration

Cited by 87 publications

References 84 publications

Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids

Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids

The design features of forecasting support systems and their effectiveness

A Framework for Theory Development in Design Science Research: Multiple Perspectives

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