## 5 Conclusions and Future Work  
This study proposed a design concept decision approach based on rough sets and the Shapley value for PSS, which can determine the optimal solution to satisfy users and the needs of enterprises by weighing the conflicting interests between the CV and economic objectives. First, EWM and BWM were used to obtain the comprehensive weights of the evaluation criteria for both sets of objectives. The rough set technique was then applied to these weights to objectively acquire the initial value of each solution. Second, a multi-objective utility function was constructed based on the solution values, and the Shapley value was used to obtain the optimal allocation of utilities to the CV and economic objectives of the product. The solution closest to this ratio is thus the optimal PSS solution. Finally, a case study of electric forklift PSS concept design is adopted to demonstrate the effectiveness of the proposed method. Compared with other decision models for PSS design, the objectives of this research are shown in three parts: (1) constructing customer value and economic objectives as important factors for enterprises and users, assisting designers to develop the comprehensive optimal PSS with a higher applicability in industrial enterprises; (2) performing the combination of the Shapley value method and the comprehensive weighting model to quantify explains the interaction between CV and economic objectives on each other from raw evaluation data during the early design phase; and (3) using coalition game theory to weigh the marginal utility of each game player in the overall design expectation, so as to form a stable and fair design expectation distribution in the game process of multi-objective conflict of interest, which can reduce the risk of subsequent design. The comprehensive weighting method developed in this study is an effective way to holistically aggregate personal preferences and subjective weights. Unlike other subjective weighting methods (such as AHP), the rough BWM only needs to make _2j_-3 pairwise comparisons, and then the structured comparison method simplifies the data and calculation process, and makes the results more reliable. Considering the subjective judgment of decision makers on the value proposition of PSS design, the rough set technique is used to quantify subjective judgments without requiring auxiliary parameters and to obtain PSS design value information in the form of interval values. Specifically, compared with other decision models such as TOPSIS, the main purpose of our proposed game decision model is to measure the \"equilibrium solution\" between customer value and the economic  
Figure 6: Comparison of game utility results of two decision methods. cost to the enterprises of satisfying customer service needs, in a way that supports the evaluation and ranking of PSS concepts through numerical models at early design stage. In addition, the game process does not require complex mathematical formulas, which can avoid the introduction of unnecessary subjective parameters and the change in decision results (Figure 6). Despite its advantages, the decision approach for product PSS design still has the following limitations. (1) Because the accuracy of the utility calculations depends on the reliability of the solution value data, it is difficult to adapt this approach to novel products without well-defined design attributes or performance data. (2) Because the calculation of Shapley values will become increasingly complex as the number of players in the game increases, the proposed decision analysis model is only suitable for decision problems that have a small number of players. Future research will develop a more comprehensive evaluation model that incorporates more uncertainties and validation techniques into the decision framework.