Research on supply chain management can be broadly classified into three categories, namely, operational, design, and strategic. While many analytical and numerical models have been proposed to handle operational and design issues, formal models for strategic planning are scarce. The supply chain operations reference (SCOR) model, developed by the Supply Chain Council, is a strategic planning tool that allows senior managers to simplify the complexity of supply chain management. It is firmly rooted in industrial practices and is poised to become an industrial standard that enables next-generation supply chain management. This paper gives a brief introduction to the SCOR model, analyzes its strength and weakness, and discusses how it can be used to assist managers for strategic decision making.

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Successful supply chain management calls for robust supply chain design and evaluation tools. Many published papers focused on high level strategic aspects of supply chain design and the results are usually generic guidelines for business executives rather than specific tools for plant managers. In this paper, we present a decision-based methodology for supply chain design that a plant manager can use to select suppliers. The methodology utilizes the techniques of analytic hierarchy process and preemptive goal programming. Supply chain operations reference model level I performance metrics are incorporated into the methodology as the decision criteria. In addition, a set of performance metrics is developed to evaluate the overall supply chain effectiveness, which allows direct comparison of different supply chain designs.

33Promoting the penetration of distributed photovolataic systems (PV) at the end-34 user side is an important contribution to carbon reduction. This study aims to evaluate 35 the promotion impact of the level of smart consumers on the installation of distributed 36 PV using a non-cooperative game theoretical model, which can find the Nash 37 equilibrium of residential smart consumers with different levels of demand control 38 capability in a electricity power market with real-time pricing mechanism under 39 different installed PV capacities and battery capacities. As a case study, 5 levels of smart 40 control, 32 combinations of PV installed capacities and battery capacities were 41 analyzed and inter-compared using the developed model. The results show that: (i) the 42 consumers with higher smart control level are able to accept larger PV capacity because 43 the marginal revenue of new installed PV for smart consumers decreases much more 44 slowly compared to that of a common consumer; (ii) the smarter consumers need less 45 batteries to promote PV economic acceptability; (iii) the smarter consumers can meet 46 the electricity demand in real-time with least expenditure thanks to their advanced 47 demand-response capability, so they get more ultimate benefit from the games. 48 49 Game, Complementarity Model 51 7 price is usually set as exogenous. The consumers are price-takers rather than players in 131 the market, which means that the consumers' behavior has no impact on the electricity 132 price. The other type of model is the game theoretical model, for example the non-133 cooperative game models handling games among residential consumers equipped with 134 distributed electricity generators [18][19][20], Stackelberg game models dealing with games 135 between utility companies and smart end-users (such as residential smart homes) in 136 demand response programs [21], and market equilibrium models focusing on the whole 137

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