An Innovative Approach Examining the Asymmetrical and Nonlinear Relationship Between Attribute-Level Performance and Service Outcomes
This study introduces and tests an innovative approach for investigating the asymmetrical and nonlinear relationship between attribute-level performance and service outcomes. Such approach entails scale division, regression analysis and coefficient comparisons, and curve approximation. The analysis of a set of patient satisfaction survey data indicates: (1) the S-shaped value function suggested by the prospect theory cannot describe the relationships between patients’ likelihood to recommend the hospital (LTR) and perceived performances on all satisfaction-maintaining attributes; and (2) “Spiritual Care” is considered as “patient delight”, with continuous improvements on this attribute providing increasing marginal returns of LTR.
Citation:
Xiaomeng Fan, Sandra Liu, and Michael Zhu (2009) ,"An Innovative Approach Examining the Asymmetrical and Nonlinear Relationship Between Attribute-Level Performance and Service Outcomes", in NA - Advances in Consumer Research Volume 36, eds. Ann L. McGill and Sharon Shavitt, Duluth, MN : Association for Consumer Research, Pages: 569-570.
Authors
Xiaomeng Fan, Purdue University, USA
Sandra Liu, Purdue University, USA
Michael Zhu, Purdue University, USA
Volume
NA - Advances in Consumer Research Volume 36 | 2009
Share Proceeding
Featured papers
See MoreFeatured
Moral Arguments Are Most Persuasive in Changing Attitudes of Opponents of Genetically Modified Foods
Sydney Scott, Washington University, USA
Yoel Inbar, University of Toronto, Canada
Paul Rozin, University of Pennsylvania, USA
Featured
F4. Social Support First, Money Later: Perceived Economic Mobility Increases Happiness When Perceived Social Support Opens the Door
Yong Ju Kwon, Seoul National University, USA
Sara Kim, University of Hong Kong
Youjae Yi, Seoul National University
Featured
K9. Measuring Internet Slang Style in Advertisement: Scale Development and Validation
Shixiong Liu, Shenzhen University
Yi Wu, Tsinghua University
Wu Gong, Shenzhen University