Beyond conjoint analysis: Advances in preference measurement

Netzer, Oded; Toubia, Olivier; Bradlow, Eric T.; Dahan, Ely; Evgeniou, Theodoros; Feinberg, Fred M.; Feit, Elea McDonnell; Hui, Sam K.; Johnson, Joseph; Liechty, John; Orlin, James B.; Rao, Vithala R.

doi:10.1007/s11002-008-9046-1

Cited by 110 publications

(58 citation statements)

References 113 publications

(104 reference statements)

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“…A more fine-grained assessment of consumers' preferences relies on a graded paired comparison (GPC, also referred to as constant sum paired comparison; see Day 1965;Netzer and Srinivasan 2011;Netzer, Toubia, Bradlow, Dahan, Evgeniou, Feinberg, Feit, Hui, Johnson, Liechty, Orlin and Rao 2008;Oishi, Hahn, Schimmack, Radhakrishan, Dzokoto and Ahadi 2005;Scholz, Meissner and Decker, 2010). In a GPC, individual consumers are instructed to rate the direction and intensity of their preference by dividing a particular sum of points among the two alternatives in every pair.…”

Section: Introductionmentioning

confidence: 99%

On the optimal number of scale points in graded paired comparisons

2012

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In market research, it is common practice to measure individuals' brand or product preference through graded paired comparisons (GPCs). One important decision concerns the (odd) number of scale points (e.g., five, seven, nine, or eleven) that has to be assigned to either brands or products in each pair. Using data from an experiment with 122 students, we assessed the extent to which GPCs with a higher number of scale points (requiring more cognitive effort) really outperform GPCs with a smaller number of scale points (requiring less cognitive effort). Our data analyses have shown that one may reduce the (odd) number of scale points from eleven to nine or seven, depending on what minor compromises one is willing to make. The detailed psychometric results presented in this paper are useful to applied researchers as they help them in making well-informed decisions on the number of scale points in a GPC task. On the optimal number of scale points in graded paired comparisons RESEARCH NOTEOn the optimal number of scale points in graded paired comparisons Abstract In market research, it is common practice to measure individuals' brand or product preference through graded paired comparisons (GPCs). One important decision concerns the (odd) number of scale points (e.g., five, seven, nine, or eleven) that has to be assigned to either brands or products in each pair. Using data from an experiment with 122 students, we assessed the extent to which GPCs with a higher number of scale points (requiring more cognitive effort) really outperform GPCs with a smaller number of scale points (requiring less cognitive effort). Our data analyses have shown that one may reduce the (odd) number of scale points from eleven to nine or seven, depending on what minor compromises one is willing to make. The detailed psychometric results presented in this paper are useful to applied researchers as they help them in making well-informed decisions on the number of scale points in a GPC task.

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Section: Introductionmentioning

confidence: 99%

On the optimal number of scale points in graded paired comparisons

2012

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“…There is clearly a need for more rigorous work to incorporate behavioral effects in preference measurement. While this may create a conflict between isomorphic goal of fit and paramorphic goal of predictive validity [130], a greater dialogue and collaboration between the two research camps is essential for improved quality of conjoint research. 2.…”

Section: Suggested Directions For Future Researchmentioning

confidence: 99%

“…Several marketing scholars (see [130], [70], and [83]) identified the importance of advanced research into the direct modeling of behavioral effects on decision-making and choice (e.g., in choice-based conjoint analysis). The research issues include understanding of such behavioral phenomena as self-control, context effects, inattention, or reference dependence.…”

Section: Suggested Directions For Future Researchmentioning

confidence: 99%

“…Conjoint researchers need to recognize that consumers often think of products in terms of "meta-attributes" including needs, motivations, and goals which may correspond to bundles of attributes [130]. Research in judgment and decisionmaking has incorporated the role of multiple goals and how situational and task factors including goal-framing effects [123] activate and chronically elevate their accessibility which in turn determine decision rules-e.g., deontological goal of "what is right", consequentialist goal of "what has the best outcomes", versus affective goal of "what feels right" [13].…”

Section: C3 Meta-attributes and Complexity Of Stimulimentioning

confidence: 99%

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An Interdisciplinary Review of Research in Conjoint Analysis: Recent Developments and Directions for Future Research

Agarwal

DeSarbo

Malhotra

et al. 2014

Cust. Need. and Solut.

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This review article provides reflections on the state of the art of research in conjoint analysis-where we came from, where we are, and some directions as to where we might go. We review key articles, mostly contemporary published since 2000, but some classic, drawn from the major marketing as well as various interdisciplinary academic journals to highlight important areas related to conjoint analysis research and identify more recent developments in this area. We develop an organizing framework that attempts to integrate various threads of research in conjoint methods and models. Our goal is to (a) emphasize the major developments in recent years, (b) evaluate these developments, and (c) to identify several potential directions for future research.

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“…Draganska and Jain (2006) showed that yogurt's consumers value line attributes more than flavor attributes through a discrete-choice model formed by both a demand-side and a supply-side model. Other studies contain sophisticated operations research models that take into consideration consumer preferences as well as several tests to check the reliability of results obtained from different models (for example, see Netzer et al 2008;Camm et al 2006;Green et al 1991Green et al , 1993.…”

Section: Fragnière Lombardi and Moresino: Designing And Pricing Sermentioning

confidence: 99%

Designing and Pricing Services Based on Customer-Perceived Value: An Airline Company Feasibility Study

Fragnière¹,

Lombardi²,

Moresino³

2012

Service Science

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W e propose a new integrated model for pricing airline tickets that takes into account the perceived value of multiple services associated with a given flight. For instance, clients perceive benefits on different attributes such as refund options, baggage allowances, time slots, days of operations, Web check-in services, as well as airline brand. These elements of perceived values are not, to our knowledge, modeled in existing yield management systems. Our integrated model includes a classical aggregate planner for services as well as a share of choice. In this paper, we have worked closely with an airline company and provided it with relevant managerial recommendations.

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Beyond conjoint analysis: Advances in preference measurement

Abstract: Preference measurement, Conjoint analysis, Marketing research,

Cited by 110 publications

References 113 publications

On the optimal number of scale points in graded paired comparisons

On the optimal number of scale points in graded paired comparisons

An Interdisciplinary Review of Research in Conjoint Analysis: Recent Developments and Directions for Future Research

Designing and Pricing Services Based on Customer-Perceived Value: An Airline Company Feasibility Study

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