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The objective of this study is to modify the SERVPERF scale by incorporating the additional dimension of recoverability, and to empirically test and refine the modified SERVPERF instrument using survey data from China. The study aims to assess the potential antecedents of customer satisfaction in the fast food industry in China. The antecedents include service quality, food quality, and perceived value. Finally, it seeks to examine the relationship between behavioral intentions and customer satisfaction in the fast food industry in mainland China.

A survey was used to evaluate customer perceptions of the service quality in fast‐food restaurants (FFRs). Exploratory factor analysis and confirmatory factor analysis were used to assess the reliability and validity of the modified Chinese FFR SERVPERF instrument. Structural equation modeling was employed to assess the hypothesized relationships.

Reliability, recoverability, tangibles, and responsiveness were all significant dimensions of perceived service quality. Food quality, perceived value and service quality all had a direct and positive relationship with satisfaction, which in turn influenced behavioral intentions.

Western‐style fast food franchises are increasingly crossing national boundaries and looking for growth among customers in China. China is becoming a major player in the global market because of its size and growth potential, particularly after its accession to the World Trade Organization. The transference of a western business model is not appropriate in the context of China without testing because of dietary and cultural differences. The study modified the SERVPERF instrument and empirically validated the instrument using data from China. The results contribute to the understanding of service quality in China's fast food industry and provide insight about service management and improvement opportunities in Chinese service operations.

Since the opening of China (aka, reform and opening-up), a great number of rural residents have migrated to large cities in the past 40 years. Such a one-way population inflow to urban areas introduces nontrivial social conflicts between urban natives and migrant workers. This study aims to investigate the most discussed topics about migrant workers on Sina Weibo along with the corresponding sentiment divergence.

An exploratory-descriptive-explanatory research methodology is employed. The study explores the main topics on migrant workers discussed in social media via manual annotation. Subsequently, guided LDA, a semi-supervised topic modeling approach, is applied to describe the overall topical landscape. Finally, the authors verify their theoretical predictions with respect to the sentiment divergence pattern for each topic, using regression analysis.

The study identifies three most discussed topics on migrant workers, namely wage default, employment support and urban/rural development. The regression analysis reveals different diffusion patterns contingent on the nature of each topic. In particular, this study finds a positive association between urban/rural development and the sentiment divergence, while wage default exhibits an opposite relationship with sentiment divergence.

The authors combine unique characteristics of social media with well-established theories of social identity and framing, which are applied more to off-line contexts, to study a unique phenomenon of migrant workers in China. From a practical perspective, the results provide implications for the governance of urbanization-related social conflicts.