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.

Manufacturing enterprises are generally aware of the importance of digital transformation. However, how to achieve digital transformation troubles traditional manufacturing enterprises. The textile printing and dyeing industry started from early 1980s onwards China's reform and opening up. The industry has reached a stage of high production capacity and is facing significant pressure for transformation and upgrading. Many business operators are struggling to explore and seek to achieve cost reduction and efficiency increase through digital transformation, thereby accelerating industrial innovation and transformation. In order to alleviate the pressure of sharply rising labor, environmental and energy costs, and build a medium to long-term competitive advantage. Printing and dyeing enterprises need to use digital methods to empower and upgrade their previous operational processes from top to bottom, from inside to outside, and reshape new driving forces and advantages through digital transformation throughout the entire process, scenario, touch point, and lifecycle. This article focuses on the digital transformation investment, studies its determining factors and economic consequences from the perspectives of production process performance and overall enterprise performance .It has found that: (1) transformation factors, transformation direction, and transformation cognition all positively affect digital investment, but only the transformation direction has significant impact; (2) Digital investment has promoted the improvement of production process efficiency, and this promotion is significant at the 1% significance level; (3) Digital investment significantly promotes the overall efficiency; (4) The improvement of production process efficiency positively promotes the relationship between digital investment and enterprise efficiency, but this impact is not statistically significant. In other words, the positive correlation between digital investment and enterprise efficiency does not change statistically due to differences in enterprise production process efficiency. This inspires dyeing enterprises to allocate resources reasonably when undergoing digital transformation. Blindly invest in the production process digitization and neglecting the coordinated development of other aspects in digitalization can lead to unreasonable resource allocation, resulting in waste of resources.

The clothing industry is labor-intensive, with many small and medium-sized enterprises and lack of scale effect; Clothing has a short fashion cycle, long operational process, and lack of independent brands; the proportion of clothing exports is relatively large, and the dependence on foreign trade is high. At present, a considerable number of domestic clothing processing enterprises (clothing suppliers) still maintain price driven relationships with customers (clothing purchasers or clothing brands). They pay more attention to short-term goals, although they can establish certain business relationships, they do not pay attention to maintaining relationships. Once affected by external adverse factors, this relationship will be easily abandoned. Upstream clothing supplier enterprises do not attach importance to the concept of supply chain management, neglect the establishment of long-term cooperation mechanisms, and excessively pursue short-term benefits, leading to frequent tension in the cooperation relationship between the supply chain。This study found that：1) The higher the customer business requirements, the stronger the supplier's business willingness; 2) The importance of profit contribution (ImProfit), order attractiveness (OrderAttract), and digitalization of cash flow (Digitizec) cannot promote the relationship between customer business requirement importance (ImRequirement) and business willingness, while cooperation attractiveness (Coordination), development expectation (Expectation), communication effectiveness(Communicate), business risk perception (PerceRisk), digitalization of information flow (Digitizea) and Digitization of logistics（Digitizeb）can significantly enhance the relationship between the importance of customer business requirements and business willingness; 3) The effectiveness of communication directly interacts with business intention, not through customer business requirements, but rather through profit contribution, order attraction, cooperation attraction, development expectation, and risk perception. 4) Digitization has both direct and indirect impacts on the business willingness. The role of digitization is comprehensive, with direct impacts being new revolutionary changes and intermediary impacts being benign and innovative changes. The proportion of intermediary impacts is 24.79%, 26.33%, and 25.92%, respectively.

In the first chapter, I consider a capacity and price bounded profit maximization problem in which a firm determines prices of multiple substitutable products when the supply or capacity of the products is limited and the prices are bounded. This problem applies broadly to many pricing decision settings such as for hotel rooms, airline seats, fashion, or other seasonal retail products, as well as any product line with shared production capacity. In this paper, I characterize structural properties of the constrained profit maximization problems under the Multinomial Logit (MNL) model and the optimal pricing solutions, and present efficient solution approaches. In the second chapter, I consider a data-driven profit maximization problem in which a firm determines the prices of multiple substitutable products. This problem applies broadly to many pricing decision settings such as for hotel rooms, airline seats, fashion, or other seasonal retail products. A typical data-driven optimization problem takes a two-step approach of parameter estimation and optimization for decisions. However, this often returns a suboptimal solution as the estimation error due to the variability in data impacts the quality of the optimal solution. I present the relationship between estimation error and quality of the optimal solution and provide a possible way to reduce the impact of the error on the optimal pricing decision under the MNL model. In the last chapter, I consider a facility layout design problem of a semiconductor fabrication facility (FAB). In designing a facility layout, the traditional approach has been to minimize the flow-weighted distance of materials through the automated material handling system (AMHS). However, distance focused approach sometimes yields one major issue, traffic congestion, that there is a question if it is truly a good criterion to design a layout. In this study, I try to understand what makes such congestion by analyzing the system dynamics and propose another approach with a concept of ``balancing the flow" that focuses more on resolving the congestion. Finally, I compare the performance of the two methods through the simulation of semiconductor FAB layouts.