Table 4 Regression results highlighting tourist preferences for rural tourism attributes.

From: Segmenting Chinese rural tourist preferences: insights from a choice experiment

Variable

Conditional Logit Model

Mixed Logit Model

Coefficient

Mean

SD

Price

–0.001***

–0.001***

 
 

(0.000)

(0.000)

 

Driving Distance_3 hours

0.017

0.022

–0.048

(0.071)

(0.086)

(0.180)

Driving Distance_4 hours

–0.273***

–0.390***

0.541***

(0.074)

(0.099)

(0.189)

Natural Scenery_Good

0.549***

0.676***

–0.543***

 

(0.075)

(0.095)

(0.179)

Natural Scenery_Excellent

0.630***

0.766***

0.859***

(0.073)

(0.103)

(0.147)

Local Cuisine

0.509***

0.609***

0.504***

 

(0.053)

(0.074)

(0.135)

Cultural Experience

0.457***

0.569***

0.094

 

(0.053)

(0.068)

(0.238)

Outdoor Activities

0.359***

0.467***

0.438***

 

(0.054)

(0.075)

(0.133)

Hotels & Homestays

0.403***

0.488***

0.529***

 

(0.053)

(0.073)

(0.145)

Hospitality

0.212***

0.266***

0.034

 

(0.053)

(0.067)

(0.159)

Opt-out

0.376**

–0.511*

2.452***

 

(0.150)

(0.276)

(0.225)

Observations

6372

6372

 

LR chi2

633.18

430.14

 

Log likelihood

–2016.8649

–1801.795

 

AIC

4055.73

3645.59

 

BIC

4130.086

3787.543

 
  1. Values in parentheses are standard errors.
  2. The “Opt-out” row reports the alternative-specific constant (ASC) for the “Neither” option and is included for completeness.
  3. SD of random parameters (MLM) follows the software’s unconstrained scale parameterization and may appear with positive or negative signs. Only their magnitudes are meaningful; the implied variances are the squares of these entries.
  4. SD standard deviation.
  5. *p < 0.1, **p < 0.05, ***p < 0.01.