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Quality Functioni Deployment (QFD) is a useful planning process in new product development. It achieves the maximum custom satisfaction through translating Voice of the Customer (VOC) into voice of the engineer in the House of Quality (HOQ), and ensures the customer focus from house to house translation. In QFD, the relationship matrix and correlation matrix are important pars, which will influence the final priorities of the technical response. According to the traditional methods, these matrices are determined by the people’s experience and filled with ordinal numbers. It would inevitably result in inaccuracy and curtness. Design of Experiments (DOE) is employed to determine the effect of variables on the process. In this paper, the author puts forward the idea of integrating DOE into the process of QFD. This integration helps to produce scientific decision and robust product design. A famework on QFD/DOE is presented and explanations are also made.

The purpose of this paper is to improve the key quality performance of the terminal of earphone in an electronic company.

Sequential experimental designs are employed. Significant input variables are found through a full factorial design. Then a response surface model is constructed considering curvature in the linear model.

Optimized key input variables’ parameters are found using the response surface model. The key quality performance, coplanarity of the terminal of earphone has been improved.

Instead of running a full factorial design in the first stage, a fractional factorial may be used to reduce experimental runs.

The paper presents a good solution for reducing defects caused by large coplanarity of a kind of earphone terminal.

The methodology used in this case can be easily extended to similar cases.

This paper discusses multi‐response robust parameter design problems based on response surface method. Most research effort on multi‐response parameter design problem focuses much on finding out optimal parameters based on certain criteria or objectives. Research shows that optimal solution in terms of some criteria may not be robust. To achieve robust solution we should consider how sensitive the solution is when the factors change around it. A comparative study of methods for multi‐response robust parameter design is conducted. Solution with consideration of robustness and optimality is proposed with applications of the example.

The purpose of this paper is to analyze the causal relationships among categories in the China Quality Award (CQA) model based on the Malcolm Baldrige National Quality Award model.

The paper identifies seven factors from CQA categories: leadership, strategic planning, human resource focus, process management, customer and market focus, information and analysis, and results. Extending the basic Baldrige theory “Leadership drives the system that creates results,” this paper identifies driver (leadership), direction (strategic planning), foundation (information and analysis), system (human resource focus, process management, and customer and market focus), and results(business results). Structural equation model (SEM) is used to analyze the empirical data and estimate the path coefficients among CQA categories.

First, driver has not only a direct influence on results, but also has an indirect influence on results through system. Leadership has a great influence on foundation and direction. Second, direction affects human resource focus and customer and market focus of system while it has no influence on process management. Third, human resource focus and customer and market focus both affect process management, and process management has a significant impact on results. Fourth, foundation affects direction and all of the categories of system.

There are few studies which try to analyze the causal relationships among categories in the CQA model.

Due to the rapid development of automotive industry, China has become the world first in car production and consumption. However, under the pressure of environment pollution, traffic congestion and parking restriction in big cities, the car rental service, as an alternative solution for private car, becomes a new trend. The market is disorganized now. This research aims to use SERVQUAL model to further examine which dimension has great contribution to service quality.

A service quality evaluation scale for the car rental industry in China is designed based on PZB's SERVQUAL model. The reliability and exploratory factor analysis methods are adopted to measure the validity and reliability of the scale from the sampled data. At the same time, the relationship between service quality, customer satisfaction and customer loyalty is discussed with the path analysis method.

The results show that the contribution of empathy to the total service quality ranks the top. At the same time, empathy has a strong impact on customer satisfaction and customer loyalty.

It is very important to attract customers depending on personalized services or service providing mode, that is, the empathy.

As a new mode in China, the car rental market is disorganized and has low service quality. The evaluation scale is designed including five dimensions. The analysis results provide guidance on how to improve their service quality to managers in car rental industry in China.

The development of mega container ships and operational pressures puts forward higher requirements on the operational ability of the container terminal. Accordingly, the purpose of this paper is to propose an effective method for quay crane (QC) scheduling of multiple hatches vessel considering double-cycling strategy to improve the operation efficiency and reduce the risk of delay.

A mixed integer programming model, which covers the main operational constraints in a container terminal, is formulated to solve the quay crane scheduling problem (QCSP) with a novel objective.

A case study is presented and a number of numerical experiments are conducted to validate the effectiveness of the proposed model. Meanwhile, management insights are proposed. The results demonstrate that the proposed method can efficiently solve QCSP in a container terminal, and an interesting finding is that reducing the stack layers on the vessel can improve the operation efficiency of QC.

A new mathematical model is proposed for QC scheduling at the operational level, which considers the constraints of double-cycling strategy, multiple hatches and hatch covers. The proposed model also provides methods to research the QC double-cycling problem considering the balance between energy cost and operation efficiency.

E-retailing grows rapidly in recent years. The majority of previous research on e-retailing service recovery has been mainly focussed on the customers’ perspective. The purpose of this paper is to examine service recovery from the operations management perspective of the e-retailing industry in order to investigate the impact of an integrated service recovery system on e-retailers’ capability improvement and market performance.

Empirical data consists of a sample of 256 employees from a leading e-retailer in China. Structural Equation Model was used to verify the relationship between the integrated recovery system and employees’ job satisfaction and organizational citizenship behavior (OCB) as well as e-retailers’ capability improvement and market performance.

The empirical results reveal that e-retailers need to pay attention to establishing an integrated recovery system. The system can facilitate employee job satisfaction and OCB, ultimately the e-retailer’s market performance. However, the relationships between job satisfaction and OCB as well as market performance are found to be low in the context of e-retailing in China.

This research contributes to the effectiveness of an integrated service recovery system in the context of e-retailing and the important role played by employees during recovery process.

The challenges that propane companies face in maintaining a balance in inventories during the summer and winter months, and the factors that influence the residential propane demand were addressed. This chapter presents a forecasting model for propane consumption within the residential sector. Forecasting the propane demand helps to determine whether there will be a shortage of propane in the storage or distribution center, and is there a need for new distribution station or a storage facility, or vice-versa that there is an overabundance of propane, that is, far more than the demand and if there is a need to shut down few facilities. The dynamic behavior of different variables that affected the propane consumption was studied and using Base SAS we developed a forecasting model. The results indicated that the forecasting model provides a potentially useful forecast for residential propane consumption. This research has been limited to forecasting for normal periods, that is periods without irregularities in demand caused by holidays or festivals. The forecasts developed were useful in improving the inventory balance for a local propane company during different months.