First Step in Social Media: Measuring the Influence of Online Management Responses on Customer Satisfaction

By Bin Gu, Qiang Ye. 2014

424 citations recorded by the source corpus.

Subfields: Marketing, Organizational Behavior and Human Resource Management, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/fb039e9edd4b19823f6a00884ef75c4ee0166d94

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Marketing

1. Markus Schuckert
2. Karen L. Xie
3. Alexander Chaudhry
4. R. Law
5. Geng Cui
6. Kevin Kam Fung So
7. Ling Peng
8. Xianwei Liu

In Organizational Behavior and Human Resource Management

1. Xun Xu
2. Alexander Chaudhry
3. R. Law
4. Geng Cui
5. Kevin Kam Fung So
6. Xianwei Liu
7. Mingshu Wang
8. Yabing Zhao

In Sociology and Political Science

1. Markus Schuckert
2. Xianwei Liu
3. Xun Xu
4. Karen L. Xie
5. Alexander Chaudhry
6. R. Law
7. Geng Cui
8. Kevin Kam Fung So

Citations in the corpus

• Predicting overall customer satisfaction: Big data evidence from hotel online textual reviews (2019, background): “Providing prompt and efficient responses to online customers’ negative reviews is an effective approach to implement service recovery actions and retain customers (Gu and Ye, 2014).”
• The signaling effect of management response in engaging customers: A study of the hotel industry (2017, background): “As a form of proactive intervention on many review platforms, management response has been on the rise due to its public nature (e.g., Gu & Ye, 2014; Xie, Zhang, & Zhang, 2014).”
• When and how Managers' Responses to Online Reviews Affect Subsequent Reviews (2018, background): “First, we show that MR-N and MR-P lead to different effects on subsequent reviews, offering a potential explanation for the divergent findings in the literature on MR (Chevalier, Dover, and Mayzlin 2017; Gu and Ye 2014; Ma, Sun, and Kekre 2015; Proserpio and Zervas 2017).”
• A segmentation of online reviews by language groups: How English and non-English speakers rate hotels differently (2015, background): “English ratio (NER) on MD (Liu et al., 2014; Gu and Ye, 2014):”
• Joint effects of management responses and online reviews on hotel financial performance: A data-analytics approach (2017, result): “Our study also differs from previous management response research (e.g., Gu and Ye, 2014; Sparks et al., 2016) by shifting the focus from customer perception or intention to the key financial performance indicators of revenue, average daily rate (ADR), and occupancy.”
• Hospitality and Tourism Online Reviews: Recent Trends and Future Directions (2015, background): “Empirical research shows that although online responses increase the future satisfaction of complaining customers, the future satisfaction of complaining customers who do not receive responses decreases (Gu & Ye, 2014).”