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With the fast growing economy, China has become the biggest automobile market in the world. Many Chinese families buy automobiles to promote individual wellbeing and facilitate the convenience of lives. Automobile purchase has become a general and important decision for a Chinese family. However, it is always difficult to make a decision on the automobile purchase that balance the automobiles performance and its cost. Moreover, the automobile maintenance market in China is monopolistic. Thus, the maintenance cost is a significant consideration in automobile purchase decision. This paper employs the concept of data envelopment analysis (DEA) to measure cost performance of the automobile with considering the monopoly maintenance cost. The RCA (ratio of the total price of accessories of an automobile to the price of the automobile) 100 index system is used to represent the maintenance cost of each automobile. The structure of the automobile maintenance market can be reflected with including the RCA 100 index system in the performance evaluation. Results of the case study of 28 automobiles in China verify the necessity of considering the maintenance cost in automobile purchase decision.

Highlights • A new multi-objective optimization method for risk response planning is proposed. • Project development process is considered in risk identification. • Process risk correlation network is considered in our method. • Risk response effects would be better if process risks are controlled earlier. • Initial risks in each sub-process is an important reference in resource allocation. Abstract Project risk response planning is an important component of project risk management to help ensure project success. However, thus far, the relevant research has ignored the correlations between risk factors during different project development subprocesses. This study proposes a novel risk response method by opening the black box of the project process and considering the risk correlations among different subprocesses to help practitioners create a practical risk response plan. In our method, we first identify process risk factors from two-dimensional criteria called risk categories and project development subprocesses. Then, we consider the risk correlations between different subprocesses to assess the true effect of each process risk factor. Finally, we build a multiobjective risk response model under resource constraints to minimize the total expected losses, the total expected schedule delay, and the total expected quality reduction. Based on the model, we obtain a set of Pareto-optimal risk response plans. Project managers can select a satisfactory risk response plan based on their experience and objective project requirements. Finally, we apply the proposed method to a real software development project. We find that the risk response effects are better if managers control the process risks earlier. Moreover, the number of initial risk factors in each subprocess is an important reference in risk response resource allocation. [ABSTRACT FROM AUTHOR]