178 Managing Multichannel Integration, Designing Perceived Affordances, and Developing Customer Relationship in the Online and Offline Retailing influence of offline satisfaction on offline loyalty is significantly positive (β = 0.579, p < 0.05), and therefore, H10 is supported. Hypothesis 11 shows that offline satisfaction would have a positive influence on online satisfaction. The influence of offline satisfaction on online satisfaction is significantly positive (β = 0.334, p < 0.05), and therefore, H11 is supported. Hypothesis 12 shows that offline loyalty would have a positive influence on online loyalty. The influence of offline loyalty on online loyalty is significantly positive (β = 0.183, p < 0.05), and therefore, H12 is supported. Table 2 SEM Results Path H Coefficient t value Multichannel integration → Economic value H1 0.361* 6.861 Multichannel integration → Relational value H2 0.358* 6.330 Perceived affordances → Economic value H3 0.476* 6.027 Perceived affordances → Relational value H4 0.332* 4.222 Economic value → Online satisfaction H5 0.455* 7.738 Economic value → Offline satisfaction H6 0.400* 7.217 Relational value → Online satisfaction H7 0.289* 4.291 Relational value → Offline satisfaction H8 0.597* 9.943 Online satisfaction → Online loyalty H9 0.337* 7.510 Offline satisfaction → Offline loyalty H10 0.579* 10.451 Offline satisfaction → Online satisfaction H11 0.334* 4.945 Offline loyalty → Online loyalty H12 0.183* 4.366 Note: * p < 0.05 4.3 Supplementary Analysis Using the SPSS PROCESS developed by Hayes (2013), we perform mediating analyses to test indirect effects. As suggested by Hayes (2009), the indirect effects and 95% confidence intervals are estimated using 5000 bootstrap samples. The criterion is to identify significant indirect effects, as indicated by the 95% confidence interval without the zero value. The results show that the 12 indirect effects occur and are significant (see Table 3).
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