A Framework for Assessing Green Capacity Utilization Considering CO2 Emissions in China’s High-Tech Manufacturing Industry

China’s high-tech manufacturing industry has become the mainstay of the country’s domestic industrial transformation and upgrading. However, in recent years, the industry has experienced huge blind expansion under policy stimulus, which is not good for long-term industrial development. Therefore, this article attempts to explore the extent to which such an important and critical industry in China utilizes its production capacity and provides a basis for future policymaking. Coupled with the country’s increasing emphasis on the green and low-carbon development of the industry, this article extends the green and low-carbon thinking based on capacity utilization, namely green capacity utilization (CU). On this basis, the study empirically investigates the green CU of the high-tech manufacturing industry in 28 provinces in mainland China from 2010 to 2015. In performing the investigation, the inputs were divided into (quasi-)fixed and variable inputs, and an assessment framework was established based on the data envelopment analysis (DEA) method. Moreover, optimal variable inputs are also available as by-products within the assessment framework. The results were as follows: First, China’s high-tech manufacturing industry showed an excellent overall performance in green CU. Moreover, half of the provinces were at fully utilized capacity, and half were under-utilized. On average, there was a slight deterioration in green CU. Second, the results showed regional differences. The western region had the highest green CU followed by the middle and northeastern regions, and the eastern region had the lowest green CU. Third, regarding the optimal variables inputs, the total amount of labor in China’s high-tech manufacturing industry met the demand, but the distribution was uneven. Fourth, the scale of traditional energy consumption needs to be reduced both in individual provinces and in general. These conclusions have implications for the formulation of policies to promote the green development of China’s high-tech manufacturing industry.

RISKY MULTI-CRITERIA GROUP DECISION MAKING ON GREEN CAPACITY INVESTMENT PROJECTS BASED ON SUPPLY CHAIN

Green capacity investment projects have rapidly emerged involving suppliers, customers, and manufacturing organizations in supply chain systems with environmental challenges. This paper focuses on and identifies both primary strategic and operational elements that will aid managers in evaluating and making risky multi-criteria decisions on green capacity investment projects. We propose a cloud prospect value consensus process consisting of feedback and adjustment mechanisms that provide modification instructions to the corresponding decision makers for a decision matrix based on the cloud model and prospect theory, which considers psychological behavior, disagreements between decision makers, and the ambiguity of linguistic variable assessment across multi-criteria risks. The new model increases the efficiency and accuracy of decision making. To verify the feasibility and validity of the Cloud Prospect Value Consensus Degree based on the Feedback adjustment mechanism, its performance is compared with three state-of-the-art multi-criteria group decision-making methods.

On Minimally Thin Sets in a Stolz Domain

Let D denote the open right half plane anda Stolz domain in D with vertex at the origin. If h is a minimal harmonic function on D with pole at the origin then E⊂D is minimally thin at the origin iff where is the reduced function of h on E in the sense of Brelot. We now definewhere s shall be fixed to be 1/e. For the set E∩In we shall let cn denote the outer ordinary capacity (see [1, pp. 320-321]), An the outer logarithmic capacity, and on the outer Green capacity with respect to D. If E⊂K, Mme. Lelong [3, p. 131] was able to prove that E is minimally thin at the origin Since one cannot easily relate the classical measure theoretic properties of a plane set with its Green capacity, it would appear desirable to find some other criteria for minimal thinness.