Everything Is Relative: How Citizens Form and Use Expectations in Evaluating Services

Author(s):  
Nathan Favero ◽  
Minjung Kim

Abstract In recent years, studies of citizen satisfaction have increasingly relied on the expectancy–disconfirmation model, which highlights the role that expectations play in driving citizen evaluations of government services. But most empirical studies within public administration of the relationship between expectations and satisfaction indicate that expectations have little-to-no net effect on satisfaction. We argue that these results may be largely driven by the weaknesses of existing measurement approaches and inattention in many studies to the distinction between two types of expectations: those about what should happen (normative expectations) versus those about what will happen (predictive expectations). Distinguishing between these two types of expectations is important because they are likely to have different—and perhaps even opposite—effects on satisfaction. We recruited 972 US residents via Amazon’s Mechanical Turk to complete a survey vignette experiment and found that normative expectations are strongly (and negatively) related to satisfaction levels, whereas predictive expectations are barely related to satisfaction at all. We also find that comparative performance information generally has a much stronger effect on predictive expectations than on normative expectations. These findings suggest that theories of satisfaction should more consistently distinguish between different types of expectations. Our results also leave us somewhat optimistic about the ability of ordinary residents to follow a reasonable process when assigning normative meaning to performance information.

2014 ◽  
Vol 15 (1) ◽  
Author(s):  
Nicole ABM Ketelaar ◽  
Marjan J Faber ◽  
Glyn Elwyn ◽  
Gert P Westert ◽  
Jozé C Braspenning

2019 ◽  
Author(s):  
Xunbing Shen

Microexpressions do exist, and they are regarded as valid cues to deception by many researchers, furthermore, there is a lot of empirical evidence which substantiates this claim. However, some researchers don’t think the microexpression can be a way to catch a liar. The author elucidates the theories predicting that looking for microexpressions can be a way to catch a liar, and notes that some data can support for the utilization of microexpressions as a good way to detect deception. In addition, the author thinks that the mixed results in the area of investigating microexpressions and deception detection may be moderated by the stake. More empirical studies which employ high-stake lies to explore the relationship between microexpressions and deception detection are needed.


The environment has always been a central concept for archaeologists and, although it has been conceived in many ways, its role in archaeological explanation has fluctuated from a mere backdrop to human action, to a primary factor in the understanding of society and social change. Archaeology also has a unique position as its base of interest places it temporally between geological and ethnographic timescales, spatially between global and local dimensions, and epistemologically between empirical studies of environmental change and more heuristic studies of cultural practice. Drawing on data from across the globe at a variety of temporal and spatial scales, this volume resituates the way in which archaeologists use and apply the concept of the environment. Each chapter critically explores the potential for archaeological data and practice to contribute to modern environmental issues, including problems of climate change and environmental degradation. Overall the volume covers four basic themes: archaeological approaches to the way in which both scientists and locals conceive of the relationship between humans and their environment, applied environmental archaeology, the archaeology of disaster, and new interdisciplinary directions.The volume will be of interest to students and established archaeologists, as well as practitioners from a range of applied disciplines.


2016 ◽  
Vol 2016 ◽  
pp. 1-11
Author(s):  
Berlin Wu ◽  
Chin Feng Hung

Correlation coefficients are commonly found with crisp data. In this paper, we use Pearson’s correlation coefficient and propose a method for evaluating correlation coefficients for fuzzy interval data. Our empirical studies involve the relationship between mathematics achievement and other projects.


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