Getting Started with Conjoint Analysis: Strategies for Product Design and Pricing Research

By B. Orme. 2005

1,224 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/47a4674000462fea97b37d1dab2651ec6e59e8a1

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Citations in the corpus

• Hotel Guests’ Preferences for Green Guest Room Attributes* (2011, methodology): “(1989) study, we used the typical conjoint analysis approach of presenting respondents with twelve scenarios that they rated on a scale of 0 (not at all preferred) to 10 (extremely preferred) (following, e.g., Hair et al. 2006; Orme 2006).”
• Selection criteria for flagship species by conservation organizations (2009, methodology): “We randomly sampled households from two major Swiss cities, Lugano and Zurich, by direct mail survey; 1980 surveys were delivered to ensure a minimum sample size of 60 (Orme 2006).”
• The Application of Factorial Surveys in General Population Samples: The Effects of Respondent Age and Education on Response Times and Response Consistency (2011, methodology): “Both methods resemble FSs in that respondents are asked to evaluate several short descriptions of objects or situations, consisting of dimensions that vary in their levels (for more details: Louviere, Hensher and Swait 2000; Orme 2006).”
• First Equals Most Important? Order Effects in Vignette-Based Measurement (2017, methodology): “Conjoint analyses are primarily used in marketing research to assess the utility of product features and willingness to pay for these (Carrol and Green 1995; Orme 2006).”
• Preference and Relative Importance for Environmental Attributes of Neighbourhood Open Space in Older People (2010, methodology): “The number of choice tasks that are needed for each participant in order to obtain robust findings is also calculated by conjoint software taking sample size, the number of attributes, and levels into account (Orme, 2006).”
• Identifying Customer Needs from User-Generated Content (2019, methodology): “Established techniques, such as those used in Quality Function Deployment (Sullivan, 1986) and conjoint analysis (Green and Srinivasan, 1978; Orme, 2006), use customer needs to identify benefits associated with product attributes and to decide which attributes to include in product design.”