DEA Efficiency of Energy Consumption in China s Manufacturing Sectors with Environmental Regulation Policy Constraints

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1 sustaability Article DEA Efficiency Energy Consumption Cha s Manufacturg Sectors with Environmental Regulation Policy Constrats Xiaoqg Chen 1,2 Zaiwu Gong 1,2, * 1 School Economics Management, Nanjg University Information Science Technology, Nanjg , Cha; @163.com 2 Collaborative Innovation Center on Forecast Evaluation Meteorological Disasters, Nanjg University Information Science Technology, Nanjg , Cha * Correspondence: zwgong@nuist.edu.cn; Tel.: Academic Editors: Xiang Li, Jian Zhou, Hua Ke, Xiangfeng Yang Marc A. Rosen Received: 19 December 2016; Accepted: 26 January 2017; Published: 4 February 2017 Abstract: Because overall consumption tensity Cha s manufacturg dustry is extremely high, study that dustry, with an analysis policy impacts tensity reduction or key factors, will no doubt improve utilization dustry stimulate sustaable development with it. This paper uses panel data 28 manufacturg dustries a piecewise lear utility function to construct a data envelopment analysis (DEA) model consumption with environmental regulations constrats. We also exame DEA evaluation manufacturg dustries. We tegrate environmental regulations as qualitative variables to consumption evaluation model to research couplg effects on consumption tensity consumption structure, openg up, environmental regulations, technological progress, competition with dustries. The research shows that policy tensity is not major effect on development low or moderate -consumption dustries, whereas low-- policy is very favorable for development high -consumption dustries. Keywords: manufacturg dustry; consumption tensity; environmental regulations; utility function; DEA model 1. Introduction Manufacturg is pillar dustry Cha. The added value Cha s manufacturg dustry 2010 surpassed that United States to rank first world. The total consumption that dustry has had sustaed growth, from 1.15 billion tons stard coal 2004 to 2.45 billion tons Energy consumption Chese manufacturg dustry usually accounts for a large percentage total Chese consumption; this percentage rose from 56.7% 2004 to 57.4% Cha s manufacturg dustry is currently facg many serious challenges, such as strong dems, shortages, low, substantial consumption. The overall level Cha s consumption tensity is high, almost 1.9 times world average, 4.1 times that Japan, 2.5 times that United States [1]. Studyg analyzg key factors for consumption tensity reduction will lower consumption level Cha s manufacturg dustry, reby promotg its economic development. Research shows that ma effects on consumption are consumption structure, openg up, competition with dustries, technological progress, environmental regulation, policy tensity. Sustaability 2017, 9, 210; doi: /su

2 Sustaability 2017, 9, Because consumption tensity strongly affects dustrial development, analyzg its fluence factors helps to propose relevant policies, improve dustrial competitiveness, ultimately promote dustrial growth. Many academic studies have shown that technological progress, openg up, enterprise scale are major factors for reducg consumption tensity [2 5]. Some researchers have stated that multiple factors may co-drive Cha s. Specifically, reducg consumption tensity requires a combation consumption structure, environmental regulations (-savg policies), competition with dustries [6 8]. Environmental decontamation is characterized by external diseconomies, so government needs to formulate policies measures to regulate manufacturers economic activities, reby matag coordated development environment economy. Environmental regulations government actions have various impacts on distct sectors. An creasg number scholars have argued that environmental regulations government actions are important for [9]. However, previous research has only regarded -savg policy as a reference variable, this was not volved calculation models. In fact, -savg policies have a substantive impact on output as consumption tensity. This paper takes policy tensity as a qualitative variable evaluation models exames coupled impact five quantitative variables on that tensity, such as -savg policy, consumption structure, openg up, environmental regulations, technological progress, competition with dustries. Environmental regulations government actions affectg can be categorized to three areas: Environmental regulations government actions can improve dustry. Impacts on economic growth environmental regulations restriction mechanisms economy are both explored. Research shows that environmental regulations are beneficial to improvg, so development path has been put forward [10,11]. Environmental regulations government actions show various impacts on due to different dustries. Empirical research on implementation -savg emission reduction shows that complementary synergy different policies should be made full use between various dustries [12,13]. Environmental regulations government actions can reduce dustries. Accordg to requirements Cha s fiscal decentralization performance evaluation, studies have shown that government tervention substantially weakens promotion environmental regulations, which is a concern [14,15]. There is strong divergence among scholars conclusions regardg reasons for Cha s consumption tensity decle. However, nearly all agree that this decle overall has been caused by a dimishment manufacturg. Some scholars have elaborated on relationship between which put output variables are selected. For example, creasg put will lead to changes output or correlation between variables, so on [16,17]. However, this paper focused on comparative analysis with policy or not on. As fluence or variables on was also dispensable, all puts were as a whole not separate to study its effects. Accordg to current economic development country, six fundamental factors were selected present work as put dicators. Energy consumption tensity manufacturg is an output dicator. In addition, data envelopment analysis (DEA) was used to assess manufacturg dustry Cha. Energy policy tensity is regarded as a qualitative dicator because it cannot be accurately measured. Thus, sub-paragraph utility functions are troduced paper to quantitatively measure willgness to implement distct policy tensities various dustries. Specifically, policies are divided to three scenarios: strong, moderate, weak. In this paper, DEA method was used to study impact policy variables on.

3 Sustaability 2017, 9, Followg is structure paper: Section 2 gives methods, maly troducg an origal CCR model, data sources, variables description, national policies. Section 3 is results constructg a left-leang, right-deviation, termediate segmented utility function, simulatg policy tentions under various dustrial policy situations. Empirical analysis Chese manufacturg is elaborated. Section 4 gives discussions conclusions. 2. Methods 2.1. Origal CCR Model DEA, troduced by Charnes, Cooper, Rhodes [18] is usually applied to assess relative for DMUs with multiple puts sgle or multiple output(s). DEA is a non-parametric method operations research economics for estimation (empirical heuristics stg for impractical or unattaable analytical optimization). It is used to empirically measure productive decision-makg units. Non-parametric approaches have benefit not assumg a particular functional form or shape for frontier, but do not provide a general relationship (equation) relatg output put. In DEA methodology, is defed as a ratio weighted sum outputs to a weighted sum puts, where weights structure is calculated by means mamatical programmg [19 23]. The score Z 0 can be obtaed by followg CCR model: Model(1) : Z 0 = max s µ k Yi t 0 k s.t. s k=1 µ k Y t ik m v j Xij t j=1 k=1 m v j Xi t 0 j = 1 (1-1) j=1 1, i = 1, 2,..., n (1-2) µ 0, v 0 (1-3) Model (1) is constructed to evaluate DMU i 0, i N = 1, 2,, n for tth year. Where k is output, k = 1, 2,, s, j is put, j = 1, 2,, m; Xij t is quantity jth put for ith DMU, Yik t is quantity kth output for ith DMU; Obviously, v j represents put weights µ k output weights, respectively. The more output gaed by a fixed put DMU i 0, greater value objective function Z 0 will be. DMU i 0 is considered to be efficient if only if Z 0 equals 1; orwise, it is referred to as non-efficient. The relative validity DMU i 0 compared with residual DMUs is analyzed through optimal solution to a lear programmg Model (1). The behavior DMUs, such as enactg policies or regulations, usually has certa consequences, characterized by utility functions [24]. Based on Model (1), DMU preferences are considered put dicators (qualitative variables) DEA models. Assumg that range values for DMU behavioral variables is represented by terval [0, 1], larger values, greater willgness behavior-driven DMUs. One or more DMU terval values correspond to a particular utility value. In or words, DMU preference is reflected followg two aspects. (1) With terval [0, 1], values for behavioral variables DMUs denote some preference characteristic (represented by a certa utility function); (2) DMUs expect greater preference utility, characterizg stronger impact behavior results. The DEA Model (2) with DMU behavioral variables constrats is constructed as follows: (1)

4 Sustaability 2017, 9, Model(2) : Z = max s s.t. ( λ U s k=1 k=1 µ k Y t i 0 k + λ m v j Xi t 0 j = 1 (2-1) j=1 µ k Y t ik m v j Xij t j=1 X t ij Xij [X t ij lt, Xut ij 1, i N (2-2) ), i N, j = 1, 2,..., l ] (2-3), i N, j = 1, 2,..., l (2-4) µ 0, v 0 (2-5) (2) In Model (2), t represents multipliers related to a particular year, n is number DMUs, output dicators expressed as Yik t (which are all quantitative values), put dicators expressed as Xij t (which are hybrid variables, cludg both quantitative dicators DMU behavioral (qualitative) dicators). Assumg that l put dicators above are qualitative variables residual M l dicators are quantitative ones, qualitative dicators are typically bounded by terval [0, 1]. The ] preference terval qualitative dicators for each DMU i (i N) can be expressed as Xij [X t = ij lt, Xut ij, where Xij lt Xij ut are lower upper bounds DMU preferences, ( ) respectively. U Xij t is a measure preference utility function with qualitative variables, utility terval varies from 0 to 1 ( detailed utility function is shown Section 3). The above model maly solves followg two problems: Decision variables constrats, cludg qualitative variables. Utility function constrats represents DMU preferences with a certa terval objective function λ represents DMU utility. The larger utility value, greater willgness behavior-driven DMU Data Sources Energy consumption tensity represents ratio total consumption a certa dustry to its correspondg economic value over a given period, which is consumption per unit gross domestic product (GDP) for dustries. This can reflect utilization production also be an important dicator economy a basis for measurg quality economic growth. Cha s largest -consumption dustry is manufacturg, so studyg consumption manufacturg is important to overall improvement country. Indicators that fluence consumption tensity manufacturg clude consumption structure, openg up, environmental regulations, technological progress ors. These data come from Cha Statistical Yearbook ( ), Cha Energy Statistical Yearbook ( ), Cha Statistical Yearbook Science Technology ( ), Cha Environmental Yearbook ( ), Cha Industrial Statistical Yearbook ( ). Data discarded resources waste material recovery is largely lackg, so se two dustries are ignored. It is well known that data coverage Cha Environmental Yearbooks is different with or statistical yearbooks. Thus, we need to adjust data coverage difference. Orwise, data values is underestimated. In order to improve reliability Chese Statistics, it will be important to ensure dependence statistical bureaus from or agencies political fluence [25] Description Indicator Variables Table 1 shows a simple description quantitative data.

5 Sustaability 2017, 9, Table 1. Simple description quantitative data. First Indicator Secondary Indicators Variable Measurement Description Output dicator Input dicators Energy consumption tensity Energy consumption structure Openg up Environmental regulations Technological progress Competition with dustries Energy consumption per unit GDP for dustries Ratio dustry coal consumption to total consumption Ratio dustry export value to prime operatg revenue each dustry Comprehensive utilization rate dustrial solid waste R D ternal expenditure Number enterprises with dustries Energy consumption tensity. Under constrats environmental regulations, consumption tensity is amount consumed by a certa dustry terms GDP. Statistical data manufacturg GDP could not be accessed, so we used consumption per unit GDP for dustries stead. Based on ratio consumption each sector to all manufacturg (except exhaust gas metal resources equipment repair dustry), all sectors were divided to three types, high, moderate, low -consumption dustries (see Table A1 for dustry classification). Energy consumption structure. Cha s oil natural gas resources are relatively adequate, whereas coal resources are rich. This has been behd coal-based structure country. Hence, we took ratio dustry coal consumption to total consumption as consumption structure. This structure is positively correlated with consumption tensity, i.e., greater proportion coal consumption, higher consumption tensity. Openg up. We used ratio dustrial export value to prime operatg revenue each dustry to measure dustrial openness. A larger ratio dicates greater export delivery value per unit GDP with sectors, greater degree openg up is higher, lower consumption tensity. Technological progress. This progress is result novation. Research development (R D) is able to produce a new vention, foster contuous improvement, enhance product process. Because it is difficult to fd elements actually measurg technological progress, we used R D ternal expenditure stead. Greater R D ternal expenditure means more technological progress lower consumption tensity. Competition with dustries. The more tense is competition with dustries, more urgent need to promote technological novation; competition ten produces more research development centives than monopolies [26]. Generally, if number firms with dustries creases, competition with m is enhanced. Therefore, we regard number enterprises with dustries to represent this competition. Environmental regulations. (1) The first cludes quantifiable dicators. Increasg environmental regulation tensity may improve utilization. The Potter hyposis [27] proposed that environmental regulation will lead companies to reduce pollutant emissions, improve utilization rate waste, reby reducg consumption. So, dicator comprehensive utilization dustrial solid waste is used to measure environmental regulations; higher value this dicator, stronger environmental regulations lower consumption tensity, here we use comprehensive utilization rate dustrial solid waste as a quantitative method. To avoid effects differences data coverage for consumption data, economic data, pollution data, method can be learned from practice [28]; (2) The second category embraces qualitative dicators such as Energy policy tensity. The fluences various policy tensities for dustrial are not identical. We express this effect by constructg a utility function as follows: We assume

6 Sustaability 2017, 9, that (1) high--consumption dustries conform to left-leang policy utility function, i.e., low-tensity policy promotes development dustries; (2) moderate--consumption dustries tend toward termediate policy utility, i.e., moderate-tensity policy can promote development level dustries; (3) low--consumption dustries are le with right-deviation policy utility function, i.e., high-tensity policy enhances development dustries (see Section 3 for a detailed explanation) Cha s Policies on Energy Conservation Emission Reduction Sce 1998, state has enacted implemented new environmental policies, laws, regulations closely related to -savg emission reduction (Table 2). Analysis shows that country has contued to crease policy tensity. Policy characteristics vary by dustry. For very -tensive heavy-pollutg dustries (maly heavy dustries), country has maly implemented very strict regulations suppression policies. For low--consumption light-pollutg dustries (maly high-tech clean or environmental protection ones), government has maly pursued policies encouragement. For moderate--consumption dustries (maly livelihood manufacturg sectors certa heavy dustries), policies with both encouragement suppression have been advanced. Based on relationship between tensity various policies terests dustries, next section constructs left-leang, right-deviation, termediate utility functions. Table 2. National partial policy. Year Specific Policy Object Regulations on Management Environmental Protection Construction Projects dustrial construction projects as clean production processes with low consumption less pollutants put forward by State Council National research, demonstration trag cleaner production implementation national key projects cleaner production technology conducted Comprehensive utilization enterprises, -savg, improved resource utilization, pollution prevention or clean projects crease vestment compensation Intensity pollutg dustries, level auditg power, chemical, paper, or high--consumg dustries controlled Ten key -savg projects are implemented, such as creased dustrial pollution control efforts, vigorous promotion cleaner production, development circular economy, reduced pollution Strength admistrative management elimation backward production capacity high--consumption pollutg dustries are creased Goals creasg conservation environmental protection efforts, tensity -savg emission reduction, should have been reached Industrial structure vigorous development circular economy adjusted optimized; -savg emission reduction technology development application accelerated; -savg emission reduction economic policy improved Goal -savg environmental protection dustries becomg pillar dustries national economy put forward Polluters should be responsible for ir solid waste accordg to law; solid waste recyclg system established Industry Enterprise Enterprise Enterprise Enterprise Enterprise Enterprise Enterprise Enterprise Enterprise 3. Results 3.1. Utility Functions with Qualitative Indicators [ The ] policy tensity is represented by an defite dummy variable [ as ] Xij lt, Xut ij [0, 1]. The larger value, stronger that tensity. Any value Xij t Xij lt, Xut ij ( ) ( ) corresponds to a utility value U Xij t. Suppose U Xij t is a contuous lear piecewise function a

7 Sustaability 2017, 9, corresponds to a utility value UX. Suppose U X is a contuous lear piecewise function t t Sustaability 2017, 9, 210 ij ij 7 19 t t t a sgle variable X ij satisfyg UXij 0,1, where X ij is characterized as utility value ) sgle variable Xij (X t satisfyg U ij t [0, 1], where Xij t t policy a particular dustry. Uis characterized as utility value ( ) X ij can be understood as dustrial policy a particular dustry. t development policy tensity as X U Xij t can be understood as dustrial development policy tensity as Xij t ij, embodied degree willgness to implement policy, embodied degree willgness to implement policy dustries. dustries Utility Function Based on Piecewise Lear Left-Leang High Energy-Consumption Enterprises Utility Function Based on Piecewise Lear Left-Leang High Energy-Consumption Enterprises The basic assumption left-leang utility function is that willgness The basic assumption left-leang utility function is that willgness manufacturg dustry to implement - policy is greater weak policy stage manufacturg dustry to implement - policy is greater weak policy stage less strong policy stage, that margal utility fulfillg policy tention is less strong policy stage, that margal utility fulfillg policy tention is declg. For high -consumption dustries (such as chemical dustries, petroleum declg. For high -consumption dustries (such as chemical dustries, petroleum processg, processg, cokg, nuclear fuel processg), even if government creases cokg, nuclear fuel processg), even if government creases policy policy tensity gives a certa amount compensation, capital dem tensity gives a certa amount compensation, capital dem dustries conductg dustries conductg technological novation to achieve goal -savg is greater. technological novation to achieve goal -savg is greater. Therefore, dustry Therefore, dustry implementation high-tensity policy decreases. As implementation high-tensity policy decreases. As - policy - policy tensity creases, margal revenue dustry development may tensity creases, margal revenue dustry development may decle, as does margal decle, as does margal utility dustries to fulfill high-tensity utility dustries to fulfill high-tensity policy. Accordgly, left-leang policy. Accordgly, left-leang utility function is constructed as follows ( 1). utility function is constructed as follows ( 1). 1. Description Graph left-leang piecewise lear utility function first panel. The left-leang piecewise lear utility function is constructed as: Model(3) : Model(3) : if Oi i f bo i1 (3-1) i < bi1 1 (3-1) 1 bi8 O bi8 1 i 1 1, O i if, b i 1 1 i1 f b b Oi bi3 (3-2) bi8 i8 b 1 b1 i1 1 O i < bi3 1 (3-2) i1 i1bi7 U(o i ) = 1 O i, i f b 1 b bi7 O i7 1 b1 i3 1 O i < b 1 (3) i5 (3-3) i2 i 1 1 (3) Uo ( i ) b, i6 1 O ifi b 1 1, i3if bo i bi5 (3-3) bi7 bi2 bi6 1 b1 i5 1 O i < bi6 1 (3-4) i4 1 0 i f O bi6 O i bi6 1 (3-5) i 1 1, if b 1 1 i5 Oi bi6 (3-4) Here, U(O i ) is willgness bi6 tobi4execute policy dustries, O i is ir 1 willgness to implement - 0 policies, if Oi b b i6 ij 1 (3-5), i N, j = 1, 2,, 8 represent policy tensities government. The larger value bij Here, UOi 1, stronger policy tensity is willgness proposed by to execute government. In itial policy stage dustries, [ b O i is ir i1 1, i3] b1, that tensity is willgness low, to implement willgness- to implement policies, b 1 ij, ipolicy N, j 1,2, dustries,8 represent is greater. In moderate range [ bi3 1 1 policy tensities, i5] b1, policy tensity government contues to crease, dustry willgness toward government. implementation The larger decles, value b ij, margal stronger utility value terval [ bi1 1, [ i3] b1 is less than that terval b 1 i3, bi5] 1 [. In later stage b 1 i5, bi6] 1,

8 1 1 In moderate range bi3, b i5, policy tensity government contues to crease, dustry willgness toward implementation decles, margal 1 1 utility value terval bi1, b i3 is less than that terval 1 1 bi3, b i5. In later stage Sustaability , 9, bi5, b i6, policy tensity government maximizes, dustry willgness to implement wanes rapidly. At that time, margal effect maximizes, is greater policy tensity government maximizes, 1 1 dustry willgness to implement wanes rapidly. than margal utility value At that time, margal effect maximizes, bi3, b i5. is greater than margal utility value [ bi3 1, i5] b Utility Function Based Based on on Piecewise Lear Right-Deviation Low Energy-Consumption Enterprises The The basic basic assumption right-deviation utility utility function is is that that willgness manufacturg dustry to to implement policy policy is less is less weak weak policy policy stage, stage, greater greater strong strong policy policy stage, stage, that that margal margal utility utility fulfillg fulfillg policy policy tention tention decreases. decreases. For lowfor -consumption low -consumption dustries dustries (such as environmental (such as environmental protection protection -savg enterprises), -savg government enterprises), creases government creases policy tensity, policy -savg tensity, enterprises -savg receive enterprises policy support receive topolicy guidesupport marketization to guide marketization dustries. This promotes dustries. This rapidpromotes development rapid those development enterprises, those ir enterprises, willgness toir implement willgness high-tensity to implement high-tensity policy grows. However, policy grows. impact However, national impact high-tensity national high-tensity policy on -savg policy on dustries -savg is relatively dustries small, is relatively is not small, ma factor is not restrictg ma factor development restrictg those development dustries; refore, those dustries; margal refore, utility dustries margal utility to fulfill thatdustries policy decles. to fulfill Based that policy on this, decles. we constructed Based on this, right-deviation we constructed utility right-deviation function as follows utility ( function 2). as follows ( 2). 2. Description 2. Graph Graph right-deviation right-deviation piecewise piecewise lear utility lear function utility function second panel. second panel. The right-deviation piecewise lear utility function is constructed as: The right-deviation piecewise lear utility function is constructed as: Model(4) : 0 i f O i < bi3 2 (4-1) U(o i ) = O i bi3 2 bi5 2 b2 i3 O i bi2 2 bi7 2 b2 i2 O i bi8 2 bi8 2 b2 i1, i f b 2 i3 O i < b 2 i4 (4-2), i f b 2 i4 O i < b 2 i6 (4-3), i f b 2 i6 O i < b 2 i8 (4-4) 1 i f O i b 2 i8 (4-5) Here, U(O i ) is willgness to perform policy dustries, O i is willgness to perform policy dustries, bij 2, i N, j = 1, 2,, 8 represent policy tensity government. The larger value bij 2, stronger policy tensity government. In itial stage [ bi3 2, i4] b2, government policy tensity is low, willgness to implement policy dustries is less. In moderate range [ bi4 2, i6] b2, aforementioned tensity contues to crease, dustry willgness to implement is improved. Then, margal utility value terval [ bi3 2, [ i4] b2 is greater than that terval b 2 i4, bi6] 2 [. In later stage b 2 i6, bi8] 2, government policy tensity maximizes, willgness dustries to implement policy improves rapidly. At this time, margal effect weakens is less than margal utility value [ bi4 2, i6] b2. (4)

9 2 2 stage bi6, b i8, government policy tensity maximizes, willgness dustries to implement policy improves rapidly. At this time, margal b, b 2 2 effect weakens is less than margal utility value i4 i6. Sustaability 2017, 9, Utility Function Based on Piecewise Lear Intermediate Moderate Energy-Consumption Enterprises The Utility followg Function is Based accordg on Piecewise to basic Lear hyposis Intermediate Moderate termediate Energy-Consumption utility function. In Enterprises weak - The followgpolicy is accordg stage, to willgness basic hyposis manufacturg termediate dustry utilityto function. fulfill In - policy tensity policy stage, is an creasg willgness function, manufacturg similar to dustry left-leang to fulfill utility - function. In weak middle policy tensity stage is an policy, creasg that function, willgness similar reaches to a left-leang maximum utility stabilizes. function. In In middle strong - stage policy, policy that willgness stage, willgness reaches a maximum manufacturg stabilizes. sectors In strong decles, - similar to right-deviation policy stage, utility willgness function. For manufacturg moderate -consumption sectors decles, similar dustries to (such right-deviation as wood processg, utility function. paper, For moderate paper products), -consumption willgness dustries may be (such seen as as a wood combation processg, utility paper, function paper left-leang products), right-deviation. willgness Accordgly, may be seen as termediate a combation utility utility function function is constructed left-leang as follows ( right-deviation. 3). Accordgly, termediate utility function is constructed as follows ( 3) Description Description Graph Graph termediate termediate piecewise piecewise lear lear utility utility function function third third panel. panel. The termediate piecewise lear utility function is constructed as: Model(5) : U(o i ) = 0 i f O i < b 3 i3 (5-1) O i bi3 3 bi5 3 b3 i3 O i bi2 3 bi7 3 b3 i2 O i bi1 2 bi8 3 b3 i1, i f b 3 i3 O i < b 3 i4 (5-2), i f b 3 i4 O i < b 3 i6 (5-3), i f b 3 i6 O i < b 3 i8 (5-4) 1 i f b 3 i8 O i < b 3 i9 (5-5) bi8 3 O i bi8 3 b3 i1 bi8 3 O i bi8 3 b3 i1 bi8 3 O i bi8 3 b3 i1, i f b 3 i9 O i < b 3 i11 (5-6), i f b 3 i11 O i < b 3 i13 (5-7), i f b 3 i13 O i < b 3 i14 (5-8) 0 i f O i b 3 i14 (5-9) (5) Here, U(O i ) is willgness to perform policy tensity for dustries, O i is willgness to perform policy tensity dustries. bij 3, i N, j = 1, 2,, 16 represent policy tensity government. The greater value bij 3, stronger government policy tensity. In itial stage [ bi3 3, i8] b3, that tensity is low, dustry willgness to fulfill policy will be left-leang utility. In medium range [ bi8 3, i9] b3, tensity contues to crease, dustry willgness to implement policy remas unchanged. In later stage [ bi9 3, i16] b3, government policy tensity contues to crease, dustry willgness to implement is right-deviation utility Energy Efficiency Assessment Cha s Manufacturg Sectors In this section, 28 Chese manufacturg sectors are regarded as different DMUs. We took consumption tensity as output dicator, competition with dustries, technological progress, consumption structure, openg up, environmental regulations,

10 Sustaability 2017, 9, policy tensity 28 DMUs each year ( ) as put dicators. Considerg that environmental regulation dicators clude qualitative quantitative variables, we separately constructed evaluation models manufacturg sectors, usg only quantitative dicators environmental regulations couplg qualitative quantitative dicators environmental regulations. The results numerical comparison show that policy tensity had little impact on development low or moderate -consumption dustries, low-tensity - policy encourages development high -consumption dustries. The DEA evaluation model manufacturg sectors with only quantitative dicators is constructed as: Model(6) : Z 0 = max µ 1 Y t s.t. µ 1 Y t i1 5 v j Xij t j=1 i v j Xi t 0 j = 1, (6-1) j=1 1, i = 1, 2,..., 28 (6-2) (6) Model (6) is - evaluation manufacturg sectors d i0 for year t(t = 2004, 2005,, 2014). In constrat, X ij (i {1, 2,, 28}, j {1, 2,, 5}) is amount put for dustries i for dicators j Y i1 consumption tensity for sector i. v j is weight put dicator µ 1 is weight consumption tensity. Equation (6-1) is constrat on dustrial put dicator, Equation (6-2) is that on put-output ratio manufacturg sectors. The DEA assessment model manufacturg sectors with - policy tensity (qualitative variables) is constructed as: Model(7) : Z 0 = max (µ 1 Yi t λ) s.t. µ 1 Y t i1 5 v j Xij t j=1 5 v j Xi t 0 j = 1 (7-1) j=1 1, i = 1, 2,..., 28 (7-2) λ U( Xt i6 2/3 ); i = 1, 2,..., 9 (7-3) λ U( Xt i ); i = 1, 2,..., 9 (7-4) λ U( Xt i6 +1/2 1+1/2 ); i = 1, 2,..., 9 (7-5) λ U( Xt i /3 0.1 ); i = 10, 11,..., 19 (7-6) λ U( Xt i6 2/25 12/25 2/25 ); i = 10, 11,..., 19 (7-7) λ U( Xt i6 0.5 ); i = 10, 11,..., 19 (7-8) λ U( 1.1 Xt i6 0.5 ); i = 10, 11,..., 19 (7-9) λ U( 5.1/5 Xt i6 5.1/5 3.1/5 ); i = 10, 11,..., 19 (7-10) λ U( 1 Xt i6 1 2/3 ); i = 10, 11,..., 19 (7-11) λ U( 1 Xt i6 1 2/3 ); i = 20, 21,..., 28 (7-12) λ U( 2.7 Xt i ); i = 20, 21,..., 28 (7-13) λ U( 1.02 Xt i Xi6 [X t i6 lt, Xut i6 ); ] i = 20, 21,..., 28 (7-14) ; i = 1, 2,..., 28 (7-15) (7)

11 Sustaability 2017, 9, Sustaability 2017, 9, Model (7) is evaluation manufacturg sectors willgness Model (7) is evaluation manufacturg sectors d willgness Sustaability 2017, 9, policy tensity year 2004,2005,,2014 policy tensity year 2004,2005,,2014. In constrat, t t. In constrat, Model (7) is evaluation manufacturg sectors d i0 willgness 1, 2, 28 1, 2,,5 is amount DMU for put dicators X 1 ij i1, 2,, 28, jpolicy 1, 2, tensity,5 is year amount t(t = DMU 2004, 2005, i for, 2014). put dicators In constrat, j Y i1, X output ij (i {1, 2, value, 28}, j consumption {1, 2,, 5}) is tensity amount for sector DMU. ij for is weight put dicators put dicator, output value consumption tensity for sector i. v j Y i1, j is weight put dicator j output value for sector i. v j is weight dicator j 1 is that consumption tensity. Equation (7-1) is a certa put constrat on µ 1 is that 1 is that consumption consumption tensity. Equation tensity. (7-1) Equation is a certa (7-1) put is a dustries, Equation (7-2) is put-output ratio constrat constrat certa put on on dustries, constrat on manufacturg. Equation dustries, (7-2) is Equation Equation put-output (7-2) (7-3) through ratio is constrat put-output (7-11) represent on ratio utility constrat constrat manufacturg. on Equation policy (7-3) tensity, through manufacturg. (7-11) Equation represent Equation (7-3) (7-3) utility through through constrat (7-11) represent (7-5) effective utility constrat constrats policy on that tensity, tensity. Equation Equation policy (7-12) (7-3) through through tensity, (7-14) (7-5) Equation represent effective (7-3) constrats through (7-5) utility constrat on that tensity. effective Equation constrats policy (7-12) on that tensity, through tensity. (7-14) Equation Equation represent (7-12) (7-15) utility through qualitative constrat (7-14) represent variables that utility constrat tensity, policy which tensity, is represented Equation policy by terval (7-15) tensity, [0, 1] qualitative Equation ( 4). variables (7-15) that qualitative tensity, which variables is represented that tensity, by terval which [0, is represented 1] ( 4). by terval [0, 1] ( 4). i 0 i 0 Y i 4. Description Graphical representation empirical analysis Description Description Graphical Graphical representation representation empirical empirical analysis. analysis. In Models (6) (7), comparison value each dustry can be obtaed In Models (6) (7), comparison value value each each dustry can can be be obtaed obtaed by by takg different values. In contexts with without policy tensity takg by takg different different t values. t values. In contexts In contexts with without without policy tensity policy constrats, tensity constrats, 5 shows a comparative estimation DEA for all sectors 2014 constrats, 5 shows a comparative 5 shows a comparative estimation estimation DEA DEA for all sectors for all 2014 sectors (Table 2014 A2); (Table A2); or years are similar. or (Table years A2); are or similar. years are similar. 5. Description DEA comparisons dustries from two evaluation models Description Description DEA DEA comparisons comparisons dustries dustries from two from evaluation two evaluation models. models. The next section is based on stpot time dustries, per two aforementioned The next section is based on stpot time dustries, per two aforementioned contexts, The next compares section is based values on stpot DEA time evaluation. dustries, per two aforementioned contexts, compares values DEA evaluation. contexts, compares values DEA evaluation DEA Energy Efficiency Evaluation Comparisons Different Industries Same Year DEA DEA Energy Energy Efficiency Efficiency Evaluation Evaluation Comparisons Comparisons Different Different Industries Industries Same Same Year Year Compared with results dustry all years, results this paper are Compared with results dustry all years, results this paper are similar Compared to that with results policy dustry For DEA all years, results comparison this paper or are similar to that policy For DEA comparison or years, similarsee to that Appendix B. policy For DEA comparison or years, years, see see Appendix Appendix B. B.

12 Sustaability 2017, 9, For low--consumption dustries, even if policy tensity maximizes (at which time willgness to implement policy dustries is greatest), it does not affect DEA evaluation value those dustries. Thus, policy tensity is not ma effect on development low -consumption dustries. For moderate--consumption dustries, even if that tensity has a middle value (at which time willgness to implement policy dustries is maximum), re is no impact on DEA evaluation value dustries, so policy tensity is not a major effect on development such dustries. For high--consumption dustries, when policy tensity is mimum (at which time willgness to implement policy dustries is greatest), ir DEA evaluation value should improve. In low- policy, that value dustries is maximum. In or words, policy tensity is not conducive to high--consumption dustries Comparisons DEA Energy Efficiency Evaluation for Same Industry Different Years By only addg - policy tensity, DEA evaluation values for low--consumption dustries did not change with year. That is, policy did not have a major effect on development those dustries. The DEA evaluation value moderate--consumption dustries across years did not change with addition policy tensity; that policy was thus not ma factor development such dustries. The DEA value for high--consumption dustries improved over years by addg policy tensity, i.e., that policy was beneficial to development low--consumption dustries. In summary, policy tensity was not a major effect on DEA low or moderate--consumption dustries, whereas low-- policies were conducive to improvg high -tensive dustries. The results show that DEA majority low--consumption dustries is relatively low. These dustries clude strumentation culture, fice machery manufacturg, furniture manufacturg, lear fur ir product dustries, textiles garments, shoes, hat manufacturg, special equipment manufacturg, electrical machery equipment, communications equipment, computers, or electronic equipment, general equipment manufacturg, transportation equipment. This means that selected put dicators were not ma factors DEA, so later we can reselect put dicators that dustries. DEA moderate or high--consumption dustries was high some years. These dustries clude tobacco, culture education, sports, prtg recordg media, wood processg, bamboo, rattan, palm grass products, beverage manufacturg, hicrafts or manufacturg, food, chemical fiber pharmaceutical manufacturg, paper products, agricultural sidele food processg, rubber, plastic metal products, textiles, non-ferrous metal smeltg, petroleum processg, cokg nuclear fuel processg, non-metallic meral products, chemical raw materials chemical products manufacturg, ferrous metal smeltg processg. This means that selected put dicators had strong impacts on DEA dustrial output dicators. 4. Discussion Conclusions The present research used method piecewise lear utility function panel data 28 manufacturg sectors from 2004 to We considered consumption structure, openg up, environmental regulations, technological progress, competition with dustries, policy tensity as put dicators, consumption tensity as an output dicator. The DEA evaluation model with policy constrats was constructed, which assessed DEA manufacturg sectors. In DEA evaluation model, various utility

13 Sustaability 2017, 9, functions were used to characterize policy variables. The study showed that policy was not ma driver development low or moderate -consumption dustries. The low - policy promoted development high -consumption dustries. Only by optimizg consumption structure, raisg level technological progress, creasg degree openg up, enhancg competition with dustries can we reduce consumption tensity. Through comparison analysis DEA evaluation 28 dustries, we found that when formulatg -savg emission-reduction targets for various dustries, measurement DEA its fluence factors should be considered. It is necessary to consider differences between dustries, which is only way to develop both targeted practical -savg goals. The followg recommendations are, refore, made. For low--consumption dustries, policy does not much affect DEA, can, thus, be a relaxed policy. For high -consumption dustries, low - policy improves DEA. This dicates that implementation willgness policy monitored by government is adequate, or that this willgness with dustries is adequate. Therefore, government should vigorously strengn policy supervision. At same time, it should accelerate technological novation, adjust consumption structure, encourage development high-end manufacturg projects, mata coordated development environmental protection, promote progress high -consumption dustries, improve high -consumption dustries. Acknowledgments: The authors would like to thank editor all anonymous referees for ir valuable comments suggestions. This research was supported by National Natural Science Foundation Cha ( , , ). Qg Lan Project, Six Talent Peaks Project Jiangsu Provce (2014-JY-014), Project Funded by Priority Academic Program Development Jiangsu Higher Education Institutions Natural Science Foundation Jiangsu, Cha (grant No. BK ). Author Contributions: Xiaoqg Chen was responsible for model development first draft, falized manuscript. Zaiwu Gong conceived ma idea experiments supervised whole process model development manuscript draftg. All coauthors made significant contributions to research contaed this article. Conflicts Interest: The authors declare no conflict terest. Appendix A The top five dustries consumption from 2004 to 2014 were basically same, followed by ferrous metal smeltg rollg processg, chemical raw materials chemical product manufacturg, non-metallic meral manufacturg, petroleum processg, cokg, nuclear fuel, non-ferrous metal smeltg rollg processg. The five sectors accounted for 84.19% total consumption manufacturg. The six dustries that consumed least (accountg for only 0.784%) were furniture manufacturg, tobacco manufacturg, culture, education, sports recreational articles, strument meter manufacturg, prtg recordg media reproduction, lear, fur, fears ir products. The 28 manufacturg dustries were divided to three types: high-, moderate-, low--consumption.

14 Sustaability 2017, 9, Table A1. Rankg consumption manufacturg. Industry Name Total Energy Consumption (Million Tons Stard Coal) Contribution to Total Energy Consumption Manufacturg (%) Smeltg pressg ferrous metals 69, Chemical raw materials chemical products processg 47, Non-metallic meral products 36, Petroleum, cokg nuclear fuel processg 20, Smeltg pressg nonferrous metals 17, Textile dustries Metal products dustries Rubber plastic products Agricultural sidele products processg Transportation manufacturg Paper paper products General equipment manufacturg Computer, communications, or electronic equipment manufacturg Electrical machery equipment Pharmaceutical manufacturg Special equipment manufacturg Chemical fiber manufacturg Food dustries Hicraft manufacturg Beverage manufacturg Wood processg bamboo, rattan, brown, grass manufacturg Textile apparel, apparel dustries Lear, fur, fears ir products manufacturg Prtg recordg media reproduction Cultural, educational, sports products manufacturg Furniture manufacturg Instrumentation manufacturg Tobacco manufacturg Table A2. Calculated results dustrial Industries Name Efficiency an Indefite Variable Efficiency a Defite Variable Tobacco manufacturg Instrumentation manufacturg Furniture manufacturg Cultural, educational sportg goods manufacturg dustries Prtg recordg media reproduction Lear, fur, fears ir manufacturg Textile garment manufacturg Wood, wood, bamboo, rattan, brown, grass manufacturg Beverage manufacturg Hicrafts ir manufacturg 1 1 Food dustries Chemical fiber manufacturg Special equipment manufacturg Pharmaceutical manufacturg Electrical machery equipment Communications equipment, computers General equipment manufacturg Paper paper products Transportation equipment manufacturg Agricultural sidele food processg Rubber plastics manufacturg Metal products dustries Textile dustries Non-ferrous metal smeltg Petroleum processg, cokg nuclear fuel processg 1 1 Manufacture non-metallic merals 1 1 Chemical raw materials chemical products Smeltg pressg ferrous metals 1 1

15 Sustaability 2017, 9, Sustaability 2017, 9, 210 Sustaability 2017, 9, 210 Sustaability B 2017, 9, 210 Appendix Appendix B Appendix B Appendix B Description DEA comparisonsdustries dustries A1.A1. Description DEA DEA comparisons A1. Description comparisons dustries A1. Description DEA comparisons dustries A2. Description DEA comparisons dustries A2. Description comparisons comparisons dustries dustries Description DEA DEA A2. A2. Description DEA comparisons dustries A3. Description DEA comparisons dustries A3. Description DEA comparisons dustries A3. A3. Description comparisons comparisons dustries dustries Description DEA DEA

16 Sustaability 2017, 9, Sustaability 2017, 9, 210 Sustaability 2017, 9, 210 Sustaability 2017, 9, A4. A4. Description DEA comparisons dustries Description DEA DEA A4. Description comparisons comparisons dustries dustries A4. Description DEA comparisons dustries A5. Description DEA comparisons dustries A5. Description DEA comparisons dustries A5. Description Description DEA DEA comparisons comparisons A5. dustries dustries A6. Description DEA comparisons dustries A6. Description DEA comparisons dustries dustries dustries A6. A6. Description Description DEA DEA comparisons comparisons

17 Sustaability 2017, 9, Sustaability 2017, 9, 210 Sustaability 2017, 2017, 9, 9, Sustaability A7. Description Description DEA DEA comparisons comparisons dustries dustries A7. A7. Description Description DEA DEA comparisons comparisons dustries dustries A7. A8. Description DEA comparisons dustries A8. A8. Description Description DEA DEA comparisons comparisons dustries dustries dustries A9. Description DEA comparisons dustries A9. A9. Description Description DEA DEA comparisons comparisons dustries dustries dustries 2012.

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