Service Modularity Innovation—Emperical Research of Hotel Chain Innovation in China

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Description
As the global economy and digital technology rapidly advance, the service industry faces increasingly intense market competition and challenges in meeting diverse customer demands. This study, set against the backdrop of chain hotels in China, empirically analyzes how service modularity

As the global economy and digital technology rapidly advance, the service industry faces increasingly intense market competition and challenges in meeting diverse customer demands. This study, set against the backdrop of chain hotels in China, empirically analyzes how service modularity could impact customer perceived value and contribute to innovation performance of hotels. Using two innovative prototypes from Jinjiang Hotels at different development stages as examples, both quantitative and qualitative research methods were employed to delve into the effects of service modularity innovation. For the “fit-up” module at the incubation phase, conjoint analysis was applied to understand consumer preferences and willingness to pay for the module combination, defining the product version 1.0. Regarding the “pure room” module at the pilot phase, structural equation modeling (SEM) was used to validate the relationship between modular innovation and perceived value, satisfaction, and consumer willingness, laying the foundation for optimizing and promoting version 1.0. Empirical results indicate that service modularity significantly enhances customer perceived value, enabling efficient personalized service innovation design to respond more rapidly to consumer demand iterations. Service modularity, as a crucial trend in service management, holds significant importance in improving service efficiency, meeting customer needs, and enhancing enterprise competitiveness. This study enriches the theoretical framework of service modularity and innovation performance, providing empirical evidence of its impact on customer perceived value and innovation performance. Furthermore, as an innovation management strategy, service modularity proves effective in enhancing the innovation performance and service upgrades of chain hotels, especially the mid-scale segment, offering meaningful insights and references to strengthen competitive advantages.
Date Created
2024
Agent

The Performance Effects of Cross-Industry Mergers and Acquisitions at Firms Listed in China’s Growth Enterprises Market

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Description
This study investigates the performance effects of cross-industry mergers and acquisitions (M&A) using a sample of firms listed in China’s Growth Entrepreses Market (GEM). Compared to firms listed in the Shanghai and Shenzhen Stock Exchanges, firms listed in the GEM

This study investigates the performance effects of cross-industry mergers and acquisitions (M&A) using a sample of firms listed in China’s Growth Entrepreses Market (GEM). Compared to firms listed in the Shanghai and Shenzhen Stock Exchanges, firms listed in the GEM are much smaller and tend to derive the majority of their revenues from a single industry. I first analyze the motives for firms listed in the GEM to engage in M&As and propose a set of factors that may influence their likelihood of M&A activities. Using data on 55 cross-industry M&As between January 1, 2012 and December 31, 2016, I find that investor generally responded positively in short-term, as indicated by the positive accumulated abonormal returns over the first five trading days following the announcements. Meanwhile, I found no evidence that investors benefited from cross-industry M&As in long-term over three years after the event. Further analysis suggests that the short-term effects of cross-industry M&As by GEM listed firms were influenced by the target firm’s market valuation, whether the M&A was paid by cash, the amount of the payment, and the degree of difference between the acquiring firm’s and the target firm’s industries. These findings have important implications for the investors and senior executives of firms listed in the GEM.
Date Created
2018
Agent