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Table 2 POST-CONSUMPTION EMOTIONAL RESPONSES FOR NEGATIVE EXPERIENCE WITH HEDONIC VERSUS UTILITARIAN PRODUCT BENEFITS

in The Role of Hedonic Versus Utilitarian Benefits
by Ravindra Chitturi, Rajagopal Raghunathan, Vijay Mahajan 2007
"... In PAGE 23: ... 3.70, p lt; .01). This demonstrates that the consumption of hedonic vs. utilitarian benefits offered by a product does indeed generate significantly different intensities of post- consumption emotions and is accompanied by greater levels of positive (or negative) word- of-mouth and repurchase intentions when the experience is positive (or negative). ----Insert Table 1 here---- ----Insert Table2 here---- STUDY 2 ... In PAGE 26: ...12, p lt; .05; see Table2 for the means and standard deviation statistics). Next, we tested H4a, H4b, H5a, and H5b.... ..."

Table 1 POST-CONSUMPTION EMOTIONAL RESPONSES FOR POSITIVE EXPERIENCE WITH HEDONIC VERSUS UTILITARIAN PRODUCT BENEFITS

in The Role of Hedonic Versus Utilitarian Benefits
by Ravindra Chitturi, Rajagopal Raghunathan, Vijay Mahajan 2007
"... In PAGE 21: ...05). The cell means and standard deviations for all the positive emotions as a result of consumption experience with a cell phone with superior hedonic benefits versus superior utilitarian benefits are shown in Table1 . A two sample t-test found that in the case of a positive ... In PAGE 23: ... 3.70, p lt; .01). This demonstrates that the consumption of hedonic vs. utilitarian benefits offered by a product does indeed generate significantly different intensities of post- consumption emotions and is accompanied by greater levels of positive (or negative) word- of-mouth and repurchase intentions when the experience is positive (or negative). ----Insert Table1 here---- ----Insert Table 2 here---- STUDY 2 ... In PAGE 25: ...57, p lt; .01; see Table1 for cell means and standard deviation statistics). On the other hand, positive experience with a utilitarian laptop computer leads to greater security and confidence (tsecurity = 3.... ..."

Table 1. Comparison of Hedonic and Contingent Valuation Methods (CVM) Hedonic CVM

in Projects: Uncertain Benefits of Willingness to Pay from Referendum
by Contingent Valuation By, Thomas Lutton, Nancy A. Wentzler, Diego J. Rodriguez, Diego J. Rodriguez 2000
"... In PAGE 11: ... Then, the effects of the proposed investments on ambient conditions should be established which means determining the changes in ambient quality indicators across time and space that the project will bring about. In one ex-post evaluation exercise, the IDB compared hedonic and contingent valuation estimates of benefits of supplying alternative housing solutions to people living in precarious conditions (see Table1 ). The results were consistent with the belief that hedonic method provided an upper bound estimate of benefits.... In PAGE 60: ...0024, a standard deviation ( ) of 4.2697 ( Table1 4, reciprocal of the Btrans parameter), and an index value (-X ) of 6.1622 (Table14).... In PAGE 81: ...3, p. 80), where the factor of proportionality is the sum of f(x) over the sampled points to normalize to one (Pollard 1977): (6) f(xi) (1/G51f(x))G46 [F(xi) - F(xi-1)] The above relationships can be used to compute the mean by numerical integration for any of the formulas in Table1 , even without access to specialized software. While admittedly crude, with a sufficient number of points it is possible to come very close to the analytical results in a simple spreadsheet setup by computing the sum of the products of the interval mid-points (or lower bounds) times the difference in adjacent CDF values, G41F(x).... ..."

TABLE 5 HEDONIC PRICING RESULTS

in WORKING PAPER SERIES MEASURING THE VALUE OF DIFFERENTIATION IN THE UK MONTHLY SAVINGS MARKET
by Damian Ward, Emm Lane 2004

Table 5: Hedonic Price Model (Linear form)

in The Nature of Competition in Electronic Markets: An Empirical Investigation of Online Travel Agent Offerings
by Eric K. Clemons, Il-horn Hann, Lorin M. Hitt 1998
Cited by 24

Table 9 Variables hypothesized to distinguish emotion pairs of the same hedonic tone

in Acknowledgments
by W. Burt, Gayle Gates Adtr, Paul Nolan Rmt-bc 1994
"... In PAGE 7: ...Table 1 Summary of Darwin apos;s observations of vocal expression of emotion 19 Table 2 Summary of results on vocal indicators of emotional states 20 Table 3 Tension-flow rhythms as unique combinations of attributes 28 Table 4 Affinities and emotional states as described by Kestenberg 29 Table 5 Mean rankings and modal descriptors of auditory assessments of acoustic parameters of infant vocalizations during four facial expressions 31 Table 6 Hypothesized vocal co-occurences with facial expressions 34 Table 7 Hypothesized vocal predictors of hedonic tone 35 Table 8 Hypothesized vocal predictors of discrete emotions 3 Table9 Variables hypothesized to distinguish emotion pairs of the same hedonic tone 36 Table 10 Hypothesized Affinities of emotional states 37 Table 11 Hypothesized Tension-Flow Attributes of emotional states 37 Table 12 Hypothesized Shape-Flow Elements of emotional states 38 Table 13 Variables under study 40 Table 14 Max Codes 43 Table ISAffex Codes 5 Table 16 Tension-flow attributes results for tracing of segment 26 by Rater 1 58 Table 17 Inter-observer correlations ofbody movement observations 61 Table 18 Inter-observer agreement percentages and correlations of vocalization variables 63 Table 19 Facial expression by vowel content of vocal expression 65 Table 20 Facial expression by vocal expression descriptor 66 Table 21 Means and standard deviations ofbody movement variablesfor four facial expressions 68 Table 23 Selected Significant Body Movement Inter-Correlations 72 Table 24 Body Movement Shape Flow Inter-correlations 73 Table 25 Selected Significant Correlations of Body Movement and Vocalization Variables 74 Table 26 Selected Significant Vocalization Inter-Correlations 75 Table 27 Tests of Significance, Multivariate. Univariate 79 Table 28 Variables significantly correlating with segment length 80 Table 29 Analyses of Covariance.... In PAGE 102: ... Support for Burt Many of the specified hypotheses set forth at the onset of the project based on Burt apos;s pilot research (1990) were supported with duplicate findings. Referring back to the hypotheses in Table9 , anger does appear to be signaled with the vowel sound quot;a quot; as in quot;pat quot; while sadness is most likely signaled either with quot;e quot; as in quot;pet quot; or quot;i quot; as in quot;pit quot;. Referring to Table 6, anger does seem to be signaled with a wide range of pitch while interest and sadness are more likely expressed with narrow pitch range.... In PAGE 103: ... A contradiction with my previous research was found in that anger was judged to be the slowest of the four expressions in the current study when it was found to be the fastest in the previous study. Regarding the hypotheses presented in Table9 , none of the vocal descriptors were found to discriminate joy from interest, and none of the expected vocal variables distinguished anger from sadness, although vocal phrase duration did. With this support of the previous findings, more evidence is mounting in support of the hypothesis that there are distinguishable vocal signals of the discrete emotions.... ..."

Table 5.3: Hedonic analysis with accessibility to jobs and resident workers

in 4. Title and Subtitle 5. Report Date Access to Destinations: Development of Accessibility Measures
by Ahmed M. El-geneidy, David M. Levinson 2006

Table 2. Summary statistics of variables in the hedonic equations Mean Std. Deviation

in Indonesia
by Arief Anshory Yusuf, Budy P. Resosudarmo, Arief Anshory Yusuf, Budy P. Resosudarmo 2006

TABLE 3 Results for Citywide Hedonic Estimations with Sales Group Dummy Variables

in Do Housing Submarkets Really Matter? *
by Steven C. Bourassa, Martin Hoesli, Vincent S. Peng 2002

Table 1. Hedonic estimations and shadow prices ( X P )

in An Empirical Measure of the Effect of Externalities on Location Choice
by Javier Rodero, Ro V, Alejandro V. Lorca, Pablo Brañas, Pablo Brañas, Garza Javier, Rodero Cosano
"... In PAGE 11: ... We estimate [8] in each zone, as well as in the whole sample. Table1 summarises the... ..."
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