Carbon pricing versus emissions trading: A supply chain planning perspective Atefe Zakeri a , Farzad Dehghanian a , Behnam Fahimnia b,n , Joseph Sarkis c a Department of Industrial Engineering, Ferdowsi University of Mashhad, Mashhad, Iran b Institute of Transport and Logistics Studies, The University of Sydney Business School, NSW 2000, Australia c Foisie School of Business, Worcester Polytechnic Institute, MA 01609-2280, USA article info Article history: Received 15 November 2013 Accepted 17 November 2014 Available online 4 December 2014 Keywords: Supply chain planning Carbon pricing Carbon tax Carbon trading Cap-and-trade Case study. abstract Carbon pricing (taxes) and carbon emissions trading are two globally practiced carbon regulatory policy schemes. This paper presents an analytical supply chain planning model that can be used to examine the supply chain performance at the tactical/operational planning level under these two policy schemes. Model implementation and analyses are completed using actual data from a company operating in Australia, where these environmental regulatory policies are practiced. Numerical results provide important managerial and practical implications and policy insights. In particular, the results show that there are inflection points where both carbon pricing and trading schemes could influence costs or emissions reductions. An erratic nonlinear emissions reduction trend is observed in a carbon pricing scheme as the carbon price increases steadily; whereas emissions reduction in a carbon trading scheme follows a relatively linear trend with a nonlinear cost increase. Overall, a carbon trading mechanism, although imperfect, appears to result in better supply chain performance in terms of emissions generation, cost, and service level; even though a carbon tax may be more worthwhile from an uncertainty perspective as emissions trading costs depend on numerous uncertain market conditions. & 2014 Elsevier B.V. All rights reserved. 1. Introduction Environmentally sustainable supply chain (SC) planning, also termed green SC planning, aims to develop unified design, planning and optimization models in which economic goals such as profit maximization and cost minimization are integrated with environ- mental goals such as carbon and greenhouse gas emissions mini- mization (Sundarakani et al., 2010; Varsei et al., 2014). The adoption of green SC planning efforts is greatly influenced by two widely- practiced regulatory efforts including carbon pricing (taxing) and carbon trading schemes (Schaltegger and Csutora, 2012). SC planning and optimization on its own is a relatively intricate process with numerous variables and constraints to be taken into consideration and the incorporation of environmental dimensions adds to its complexity (Fahimnia et al., 2014a). Organizations facing these complex decision environments can find utility in tools for planning and managing their SCs. The development of SC modeling tools that have effectively integrated and evaluated environmental issues, alongside economic and business concerns, have only started to receive significant interest (Benjaafar et al., 2013; Brandenburg et al., 2014; Seuring, 2013; Tang and Zhou, 2012). Many of these modeling efforts focus on strategic planning levels of analysis such as the design of SC networks, while challenges at the tactical and operational planning levels are less explored (Seuring, 2013). In fact, the develop- ments in some areas such as reverse logistics have dominated the early and recent green SC modeling literature (Srivastava, 2007). Motivated by actual regulatory climate change pressures that are evolving in Australia, we develop and apply an analytical planning model to explore how organizations can manage their SCs under two carbon regulatory schemes. Not only are practical implications associated with the modeling effort presented, but research implications including further model development and investigations of additional outcomes are thoroughly discussed in this paper. The primary objective of this work focuses on the development and analysis of SC planning under emergent regula- tory regimes. The proposed SC planning model contributes to the green SC modeling literature through helping organizations, pol- icymakers, and even NGO's evaluate the tactical and operational implications from broad-based regulatory policy decisions. The remainder of the paper is organized as follows. We begin in Section 2 with some background on environmental regulatory policies and organizational responses to these policies. Green SC management modeling efforts specifically those with a clear focus Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/ijpe Int. J. Production Economics http://dx.doi.org/10.1016/j.ijpe.2014.11.012 0925-5273/& 2014 Elsevier B.V. All rights reserved. n Corresponding author: Tel.: þ61 2 9114 1801. E-mail addresses: atefe.zakeri@yahoo.com (A. Zakeri), f.dehghanian@um.ac.ir (F. Dehghanian), behnam.fahimnia@sydney.edu.au (B. Fahimnia), jsarkis@wpi.edu (J. Sarkis). Int. J. Production Economics 164 (2015) 197–205