Special Session Summary Personalization and Decision Support Tools: Effects on Search and Consumer Decision Making



Citation:

Kristin Diehl (2003) ,"Special Session Summary Personalization and Decision Support Tools: Effects on Search and Consumer Decision Making", in E - European Advances in Consumer Research Volume 6, eds. Darach Turley and Stephen Brown, Provo, UT : Association for Consumer Research, Pages: 233-234.

European Advances in Consumer Research Volume 6, 2003      Pages 233-234

SPECIAL SESSION SUMMARY

PERSONALIZATION AND DECISION SUPPORT TOOLS: EFFECTS ON SEARCH AND CONSUMER DECISION MAKING

Kristin Diehl, University of South Carolina, USA

With the emergence of the Internet, the amount of information available to users at low search costs has increased dramatically. Without sophisticated search and decision support tools, however, "the contents of the Internet might be likened to the contents of the Library of Congress, without call numbers, and dumped out on the floor." (Burk 1999). In fact, Alba et al. (1997) argued that personalized screening is the most important development in online shopping, comparing such screening agents to a super-salesperson with excellent knowledge of both the qualities of the inventory and the taste of the consumer. The thriving academic and commercial interest in "personalization" technology attests to the potential benefits such personalized agents and similar decision facilitating tools can have online (e.g., Ansari, Essegaier and Kohli 2000; Gershoff and West 1998; West et al. 1999). Initial research in this area has focused on demonstrating the benefits that screening and comparison tools can provide (Haubl and Trifts 2000; Lynch and Ariely, 2000). Their research shows that personalized search and decision support tools allow consumers to find options that are of higher quality, while at the same time reducing the decision maker’s effort.

The research presented in this session builds on these initial findings, but provides a more advanced and nuanced perspective on the effects that personalization and decision support tools have on consumer search and decision making. Specifically, the three papers investigate important moderators that alter the effect of such tools on decision quality as well as search behavior. While the first two papers demonstrate the positive effects that online decision tools can have, the third papers reveals boundary conditions when decision tools lead consumers to make worse choices.

The paper presented by Nina Mazar contrasts the different decision environments consumers face online vs. in the brick and mortar world. It investigates the effects that a decision support tool such as a comparison matrix will have on attribute importance weights, product choice and customer satisfaction online compared to how information is presented in a more traditional environment. Empirical results show that contrary to fears of ruinous price competition in interactive environments, supporting consumers’ use of comparative decision tools can increase consumer loyalty and retailers’ profit.

Barbara Fasolo’s work demonstrates how negative inter-attribute correlations affect information acquisition, and consumer satisfaction for choices made from web-based comparison tables, opinion portals, and decision-facilitating sites. She shows that when attributes are negatively related consumers search comparison tables more by product than for positively correlated attributes. However, they find choice to be more difficult and dissatisfactory. Also on opinion portals, where options are accompanied by summary star ratings, negative correlations make choice more difficult. The same is true for decision web sites that facilitate an attribute-wise elimination-by-aspect strategy. When decision sites facilitate a simple compensatory process like MAU, however, negative attribute correlations make choosing easier and more satisfying . This research shows how important it is for online decision tools to support the frequent and unpleasant cases where attributes are negatively related.

The paper by Kristin Diehl shows that under certain conditions, decision tools can lead consumers to make worse decisions. This research demonstrates that when options have previously been screened by an ordering tool, reducing search costs can lead to lower quality choices. This effect is caused by consumers considering inferior options and consequently making worse choices. Similar to what Hauser (1978) has shown, considering inferior options in the first place has much stronger effects on the final decision than selectivity among these considered options. Findings also show that trying to be more accurate can exacerbate this effect. When search costs are low, a strong accuracy goal can motivate consumers to consider a wider array of alternatives and further decrease choice quality.

Taken together, these three papers present a detailed and multi-faceted view on how personalization and decision support tools affect consumer search and decision making. The research presented here initiates discussion on the topic of personalization and decision support tools as well as the real conceptual differences between online and brick and mortar environments by identifying factors that affect search behavior and decision quality.

 

CONSUMER DECISION MAKING AT ONLINE RETAILERS AS OPPOSED TO TRADITIONAL OFFLINE RETAILERS: THE ROLE OF AN INTERACTIVE COMPARISON MATRIX

Nina Mazar, Johannes-Gutenberg Universitat, Germany and MIT, USA

The paper examines the effects of a very simple interactive tool that can tailor information extremely fast: the interactive comparison matrix (CM). This research shows that the CM has the potential to represent a useful and practicable solution matching the needs of both, consumers and retailers. On the one hand, it increases consumer welfare and gives consumers more control over the environment. On the other hand, it gives retailers the possibility to influence consumer choice and escape the threat of increased consumer price focus.

 

THE ROLE OF ATTRIBUTE CORRELATIONS IN ONLINE DECISIONS

Barbara Fasolo, Max Planck Institute for Human Development, Germany

Negative inter-attribute correlations affect decision processes and satisfaction for choices made from consumer websites. Consumers are shown to search comparison tables more by product when attributes are negatively related, and more by attribute when attributes are positively related. Search by product in negative-correlated environments is accompanied by increased dissatisfaction and difficulty of choice. Negative correlations make choice more difficult also on opinion portals, where products are accompanied by summary ratings, and on sites facilitating an attribute-wise elimination-by-aspect strategy. With negative correlations, choice is easier and more satisfying when decision sites facilitate a simple process that integrates conflicting attribute information.

 

TEMPTED BY THE CHEAP AND EASY: THE NEGATIVE EFFECTS OF LOW SEARCH COSTS IN ORDERED ENVIRONMENTS

Kristin Diehl, University of South Carolina, USA

One of the most cited benefits from technology changes has been the reduction in consumer search cost. This research shows that with access to personalized orderings, factors that stimulate search, such as lower search cost or more recommendations, actually lead to worse decisions. When options are ordered, investigating more options yields little benefit in terms of finding better options. At the same time, more search decreases the quality of the consideration set while increasing the complexity of the decision, leading to more superficial processing. Findings show, these factors can decrease the quality of a consumer’s decision.

BIBLIOGRAPHY

Alba, Joe, John G. Lynch Jr., Barton Weitz, Chris Janiszewski, Richard Lutz, Alan Sawyer and Stacy Wood (1997), "Interactive Home Shopping: Consumer, Retailer, and Manufacturer Incentives to Participate in Electronic Marketplaces,"Journal of Marketing, 61 (July), 38-53.

Ansari, Asim, Skander Essegaier and Rajeev Kohli (2000), "Internet Recommendation Systems", Journal of Marketing Research, 37 (August), 363-375.

Burk, Dan (1999), "Muddy Rules for Cyberspace", Cardozo Law Review, 121 (October), 152-153.

Gershoff, Andrew and Patricia M. West (1998), "Using a Community of Knowledge to Build Intelligent Agents," Marketing Letters, 9 (January), 835-847.

HSubl, Gerald and Valerie Trifts (2000), "Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids,"Marketing Science, 19 (Winter), 4-21.

Hauser, John R. (1978), "Testing the Accuracy, Usefulness and, Significance of Probabilistic Choice Models: An Information Theoretic Approach,"Operations Research, 26 (3), 406-421.

Lynch, Jr., John G. and Dan Ariely (2000), "Wine Online: Search Costs Affect Competition on Price, Quality, and Distribution", Marketing Science, 19 (1), 83-103.

West, Patricia, Dan Ariely, Steve Bellman, Eric Bradlow, Joel Huber, Eric Johnson, Barbara Kahn, John Little, and David Schkade (1999), "Agents to the Rescue?" Marketing Letters, 10 (August), 285-300.

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Authors

Kristin Diehl, University of South Carolina, USA



Volume

E - European Advances in Consumer Research Volume 6 | 2003



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