Do consumers need decision support capabilities?

by Dan Power

Purchase decisions have become increasingly complex with the advent of Internet shopping. Making decisions where many retail sources and comparable solutions exist to meet needs necessitates improved and systematic decision support for consumers. Consumers in developed economies need more and better computerized decision support. Consumers can benefit from both web-based and mobile decision support tools.

Producers, distributors and retailers would like to provide consumer decision support, but such a biased origin may lead consumers to make poor decisions. Finding unbiased decision support capabilities is however difficult because consumers seem reluctant to pay for decision support. Advertiser financed consumer decision support has many of the same inherent problems as decision support provided by a company in the supply chain for goods or services.

Consumers face a dilemma. If I purchase a decision support capability, will it save enough to justify the cost? If I don't purchase a decision support capability, will I really incur much disadvantage and excess cost? If I don't have a decision support capability, will I realize that my decision is suboptimal? Which provider benefits from providing free decision support? Will my benefits be greatly reduced by relying on the decision support capability provided free by a provider of a class of goods and services? The solution may be to use multiple tools and use a paid subscription service for important decisions. Let's examine decision support tools in a single important consumer decision making domain -- healthcare.

Healthcare decision making is a decision domain where patient/customer decision support may be especially helpful and useful. Healthcare decisions and recommendations can be complex, sequential decisions with limited choices and some choices may be "poor" choices. According to von Glahn (2007), "As more consumers become involved in making decisions about their health care, they are contending with issues ranging from increasingly complex medical science to ever-evolving care options." There are many web-based tools. In 2007 von Glahn evaluated tools in three specific decision areas: 1) treatment option support; 2) hospital choice; and 3) personal cost decision support. In the area of web-based treatment decision support tools, he focused on four vendors: BestTreatments, HealthDialog, Healthwise and NexCura. Three hospital choice products were evaluated: HealthGrades, Subimo/WebMD and WebMD Select Quality Care. Many health insurance plans have cost evaluators, including, UnitedHealthcare, Aetna, Blue Cross of California, and CIGNA. WebMD has a less specific evaluator. A major evaluation criterion was "effectiveness of the decision support techniques".

Consumer decision support will continue to expand and evolve. But many consumers seem to lack awareness of tools and the need in some domains is not clearly defined. The complexity of consumer decisions in many domains will only increase and this area of decision support is increasingly important.


von Glahn, T., "Evaluation of Consumer Decision Support Tools: Helping People Make Health Care Decisions," California Healthcare Foundation, September 2007, URL .

Westerman, S.J., G.C. Tuck, S.A. Booth and K. Khakzar, "Consumer decision support systems: Internet versus in-store application," Computers in Human Behavior, Volume 23 Issue 6, November, 2007, Pages 2928-2944.

Westerman et al. (2007) abstract "This paper reports a study of consumer decision support in the context of Internet and in-store applications. A sample (n=30) of experienced runners made running shoe selections in either 'product only', 'decision support system only', or 'decision support system and product' conditions. Participants' decisions tended to be more uniform and of better quality when the DSS was available. Decision making was clearly influenced by DSS recommendations, but these were not always accepted. In this latter circumstance participants reported themselves to be relatively less happy with and less confident in their decision. Consistent with previous literature, abstract attributes were considered more frequently and given higher weightings when using the decision support system. However, predicted differences between conditions with respect to the types of attributes considered and the importance ascribed to different types of attributes were not found."

Last update: 2013-02-27 09:27
Author: Daniel Power

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