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Table 4 Generalized multinomial logit model in willingness-to-pay space

From: Analyzing German consumers’ willingness to pay for green electricity tariff attributes: a discrete choice experiment

Variables GMNL-WTP-space I Basic model GMNL-WTP-space II Interaction model
Coefficient (mean) Coefficient (mean)
Random parameters
Alternative-specific constant (ASC)a 21.649*** 27.983***
Share of green energy 0.022*** 0.027***
Switching bonus 0.004** -0.002
Price guarantee 0.148*** 0.063**
Tariff price − 1 [fixed] − 1 [fixed]
Non-random parametersb
Green energy source: solar 0.211** 0.188**
Green energy source: wind 0.196** 0.178**
Green energy source: RE mix 0.059 0.067
Interaction variables
ASC region: eastc   0.502**
ASC × region: southc   − 1.139***
ASC × region: westc   0.671***
ASC × town size d   − 0.496***
ASC × EEG levy acceptancee   0.555***
ASC × Green Party identificatione   − 1.038***
Share of green energy × green Party identificatione   0.010***
ASC × food or fuele   − 0.646***
ASC × environment is important when buying groceriese   1.130**
ASC × never switched beforef   − 0.381***
ASC × wish to outsource switching processe   1.279***
Standard deviations (SD) of parameter distributions
SD ASC 5.654*** 4.999***
SD Share of green energy 0.023*** 0.020***
SD Switching bonus 0.010*** 0.007***
SD Price guarantee 0.088*** 0.116***
Scale heterogeneity
Tau 1.014*** 1.137***
Goodness of fit measures
Participants/observations 371/4,452 371/4,452
McFadden pseudo-R2 0.309 0.322
Log-likelihood at convergence − 2716.756 − 2,670.03
Akaike information criterion 5471.512 5408.06
  1. Source: author’s calculations by means of the STATA-command “gmnl” in STATA 14 using 1000 Halton draws
  2. *p < 0.1; **p < 0.05; ***p < 0.001; randomized WTP coefficients with significant SD are assumed to be normally distributed and correlated; the price coefficient was normalized to be log-normal and constrained to − 1
  3. aBinary coded variable; reference: status quo alternative “No switch.”
  4. bEffect coded; reference: “Energy source: biogas”
  5. cEffect coded; reference: “Region: north”
  6. dThe variable “town size” was divided into five groups, and ranged from “less than 5000 residents” to “more than 500,000 residents”. For a detailed structuring of the groups see Additional file 1: Appendix S3
  7. eEffect coded; reference: “Participant does not support the queried statement”
  8. fEffect coded; reference: “Participant switched the electricity tariff at least once before”