A circular economy perspective on sustainable supply chain management: an updated survey

Closed-loop coordination and operations. While the above work on closed-loop supply-chain coordination and design typically adopts a marketing channel perspective [Savaskan et al., 2004], a further stream of work has introduced operational considerations into the analysis by explicitly modelling manufacturing and remanufacturing operations and including inventory-related costs in the decision model. The work by Pishchulov with co-authors [Pishchulov et al., 2014] combines in this regard essential elements of the conventional joint economic lot size problem [Banerjee, 1986], the economic order quantity model for a production-inventory system with product recovery and disposal [Richter, 1996], and the closed-loop supply-chain coordination model as per Savaskan with coauthors [Savaskan et al., 2004]. Specifically, Pishchulov with co-authors consider a closed- loop supply chain comprising a manufacturer and a retailer (see Figure 6) [Pishchulov et al., 2014]. The manufacturer can produce new products and remanufacture used ones

Figure 6 Product flows and stock levels in the closed-loop supply chain model due to Pishchulov et al.

Note: adapted from: Pishchulov G., Dobos I., Gobsch B., Pakhomova N., Richter K. A vendor-purchaser economic lot size problem with remanufacturing // Journal of Business Economics, 2014. Vol. 84, no. 5. P. 749-791

at production rates P_M and P_R respectively. Remanufactured products serve the retailer's demand on a par with the new ones. After receiving an order of the size q from the retailer, the manufacturer produces the lot while accumulating the items in stock and then ships it to the retailer. The retailer's stock is being depleted by the customer demand at the rate D, which makes the retailer repetitively re-order the product from the manufacturer. The retailer also exerts a collection effort for getting used items back, which determines their return rate 5. Returning products are being accumulated at the retailer as non-serviceable inventory and shipped to the manufacturer in batches. The manufacturer keeps them in the non-serviceable stock that becomes subsequently depleted during remanufacturing. The authors derive optimal decisions of the parties with regard to lot sizing, collection effort, and refunding the retailer for the used items in a Stackelberg and a cooperative setting. They demonstrate that coordination can be difficult to achieve with conventional, simple contracts between supply-chain members, and propose to this end a contract form with a three-part tariff and a refund amount.

A number of studies have addressed similar settings, for which we provide an overview in Table 2. Dobos with co-authors [Dobos et al., 2013] study a setting closely related to Pishchulov with co-authors [Pishchulov et al., 2014] while assuming cooperative as well as competitive action of supply-chain members. Both these works assume at most one manufacturing and one re-manufacturing batch per production cycle. Jaber with coauthors [Jaber et al., 2014] expand the modelling approach in this regard by permitting multiple manufacturing and remanufacturing batches and adopting a consignment stock policy [Braglia, Zavanella, 2003], which assumes that the stock at the retailer's side is managed by the manufacturer and remains in his ownership until being actually used by the retailer. These authors assume, however, a fixed collection rate of used products and a centralised decision making by the supply-chain partners. Bazan with co-authors expand this

Leadership Leadership designates the most powerful supply-chain member or a coalition of members: manufacturer (M), retailer (R), retailer and manufacturer (RM), retailer, manufacturer and collector (MC), manufacturer and supplier (RMS), retailer, manufacturer and collector (RMC), or retailers, distributors, manufacturer and collector (RDMC). A dash represents the case of no leadership, when all parties move simultaneously, and the solution is defined in terms of a Nash equilibrium (Osborne M. ]., Rubinstein A. A Course in Game Theory. Cambridge, Massachusetts: The MIT Press, 1994, 368 p.).

analysis further to investments in product durability and costs of greenhouse gas emissions in production and transportation [Bazan et al., 2017]. Yuan and Gao assume the retailer to be the most powerful supply chain member and include additionally a supplier and a collecting firm in the model [Yuan, Gao, 2010], while Yuan with co-authors explore supply-chain performance under different leadership structures [Yuan et al., 2015]. Their numerical analysis reveals that integrating the retailer in the decision-making coalition is essential for the supply-chain's as well as manufacturer's and retailer's profits. Jonrinaldi and Zhang study lot sizing in a multi-tier supply chain model with tier-1 and tier-2 suppliers, a manufacturer, distributors, retailers and a 3^rd party who collects used products [Jonrinaldi, Zhang, 2013].

While the above studies assume fully deterministic settings, a number of works further address different kinds of uncertainty in closed-loop supply chains (see Table 2). For example, Kim and Glock assume a stochastic return rate of reusable containers from the retailer to the supplier under a deterministic constant demand [Kim, Glock 2014], while Bhattacharya with co-authors study a multi-period, finite-horizon model with uncertain demand [Bhattacharya et al., 2006]. The latter assumption implies that by the end of each period, there can be either unsatisfied demand (lost sales) or leftover stock at the retailer, which both are costly to the retailer. A certain fraction of returning used products and leftover stock can be remanufactured to as-good-as-new products in the next period by a 3^rd party remanufacturer who then sells these to the manufacturer -- from whom, in turn, the retailer orders the product. The authors use dynamic programming to derive optimal decisions of supply-chain members under different leadership structures and establish a supply-chain coordination mechanism using two-part tariffs. Chuang with co-authors [Chuang et al., 2014] consider a setting similar to Savaskan with co-authors [Savaskan et al., 2004] and Atasu with co-authors [Atasu et al., 2013], yet assuming an uncertain demand and a fixed return rate of used products, and compare the retailer's order quantity and the manufacturer's profit under different reverse channel designs and different scale effects in the logistics costs of used product collection.

Table 2 reveals that all of the studies listed adopt the assumption of either a constant or a stationary demand, and only a few include decision dynamics in the model. Also, only a few studies take into account collection effort and investments in the product design. We can also see in the table that questions of coordination mechanisms for independent supply-chain members and reverse channel design are rarely addressed. We refer the reader to Guo with co-authors [Guo et al., 2017] and Krapp and Kraus [Krapp, Kraus, 2017] for a more comprehensive overview of the literature on decentralised control and coordination in closed-loop supply chains, including asymmetric information and stochastic settings, as well as discussion of existing study gaps.

Acquisition and remanufacturing policies for used products

While most of the above reviewed work makes simplified assumptions about the nature of product returns, used products may in fact return in a highly variable condition, which typically implies different costs of remanufacturing them to serviceable products. What is more, in many real-world settings, the actual quality condition of a returned product remains uncertain until the product undergoes inspection, first after which a decision about remanufacturing can be made. Such a situation requires using an acquisition policy for used products that takes into account both their uncertain quality condition and the subsequent remanufacturing decisions. In this regard, Teunter and Flapper study a setting in which used products are being acquired in bulk at an equal price and sorted into several quality grades after inspection [Teunter, Flapper, 2011]. Each quality grade implies a specific unit remanufacturing cost, which is lowest for the highest quality grade. Further, each quality grade has a known probability of occurrence; however, the actual fraction of products of any quality grade in the acquired batch is uncertain. Given a deterministic demand for the remanufactured product, a decision needs to be made about the acquisition volume of used products, taking into account the opportunity to remanufacture then only the higher-quality ones and dispose of the rest. The authors derive the expected cost expression associated with any given acquisition volume and give a numerical example demonstrating the expected cost difference between the optimal acquisition decision and the one that is based on the assumption of a fixed fraction of products of each grade in the batch. This analysis is further extended to the case of a stochastic product demand, which in addition requires to determine the remanufacture-up-to levels for different quality grades ahead of the realisation of uncertain demand. The authors' solution approach permits a straightforward implementation on a spreadsheet.

Figure 7 Price variables a\, po, pr and cost parameters ci in the problem setting by Bulmuз et al

The work by Bulmu§ with co-authors [Bulmu§ et al., 2014b] extends the analysis to a setting that excludes demand and quality uncertainty from consideration but involves pricing decisions with regard to used, remanufactured, and new products. Specifically, it allows for differentiated acquisition of products of different quality grades, whose acquisition volumes are determined by the acquisition prices a_i (see Figure 7). They can be remanufactured at different unit costs ci to an equal quality standard and sold on the market at the price pr. In addition, new products can be manufactured at the unit cost c0 and sold on the same market at the price p₀. Using a standard demand modelling approach for new and remanufactured products [Ferguson, Toktay, 2006], the authors express the inverse demand functions, derive properties of optimal pricing policies, and devise a computational procedure for finding these. Their sensitivity analysis reveals, among others, that increase in the unit remanufacturing cost of a particular quality grade decreases its acquisition price, thus decreasing its and also the total acquisition and output volumes, while increasing other acquisition prices and the sales price pr.

Mutha with co-authors study a setting in which acquisition of used products extends over two periods: first, when the product demand is yet uncertain, and, second, when the demand has become known [Mutha et al., 2016]. The second period is usually shorter and implies higher acquisition and remanufacturing costs. In each period, the remanufacturing firm may acquire used products in bulk -- with uncertain quality condition, as well as sorted by quality grade. Sorted acquisition removes uncertainty about product quality, but implies, on average, a higher acquisition price per unit compared to the bulk purchase. In each period, the firm has to make two consecutive decisions: how much to purchase, in bulk and sorted, and which products to remanufacture then. In view of uncertain demand (period 1), acquisition of sorted products should strike a balance between profit from remanufacturing and risk of over-investment, which may lead the firm to purchasing a mix of higher- and lower-quality products. Some of them may not be remanufactured until period 2, when product demand becomes realised, and some of them may not be remanufactured at all -- either due to a low demand or due to the opportunity of purchasing more profitable products in period 2. The authors accordingly develop a four-stage stochastic programme that captures optimal decision making of the firm over the entire horizon, determine structural properties of optimal decision policies, and illustrate application of the model using empirical data of a smartphone remanufacturing company.

Limited product durability and restricted life-cycle

In addition to the studies reviewed by Atasu with co-authors [Atasu et al., 2008] with regard to the issues of a limited product durability and its restricted life-cycle, we refer to reader to the work by El Saadany with co-authors [El Saadany et al., 2013] who link two distinguished lot-sizing approaches due to Richter [Richter, 1997] and Teunter [Teunter, 2001] (Stream 1, Section 3.1) to the problem of a limited product durability and investment in durability improvement. They then compare cost performance of the respective production-inventory systems under the assumptions of a limited and unlimited durability using a series of numerical examples. However, all comparisons are made only for the special case of an equal manufacturing and remanufacturing cost per unit. Bazan with coauthors [Bazan et al., 2017] employ this framework in a setting with closed-loop supply- chain coordination and operations (Stream 2, Section 3.2.1), while Dobos with co-authors [Dobos et al., 2018] study a lot-sizing setting with a limited product durability, in which quality condition of used products depends on the number of remanufacturing cycles they underwent and determines their inventory holding and remanufacturing setup costs. We refer the reader further to the study by Atasu and Qetinkaya [Atasu, Qetinkaya, 2006] who address the problem of a restricted product life-cycle in a closed-loop supply chain setting with optimal timing and lot-sizing of used product returns.

Strategy stream

While the above Stream 2 considers closed-loop supply chain management from a more holistic perspective than Stream 1, Stream 3 refers to strategic competition in remanufacturing [Atasu et al., 2008]. We refer the reader to Atasu with co-authors for an exposition of foundational studies in this stream, and discuss in this section selected follow-up research [Atasu et al., 2008].

We first refer to the study by Ferrer and Swaminathan who consider a single-firm, two-period setting with manufacturing and remanufacturing [Ferrer, Swaminathan, 2006]. Specifically, in the first period, new products are being manufactured. Returns collected by the end of that period can be remanufactured in the second period to as-good- as-new products. In addition, new products can be manufactured as well, but at a higher unit cost compared to remanufacturing. The firm has to optimally decide pricing of the product on the market in each period. The analysis by the authors reveals that maximising the profit in the first period straight on can be sub-optimal; instead, the firm may consider selling the product in the first period at a low price in order to generate a high demand volume, which will provide a higher volume of returns, and thus generate bigger savings from remanufacturing in the second period -- that can surpass the profit sacrificed in the first period. This shows that new and remanufactured products are not only substitutes but also complements of one another [Atasu et al., 2008]. Ferrer and Swaminathan further extend their analysis to a setting in which the manufacturer competes with a 3^rd party who collects remaining used products by the end of the first period and remanufactures them in the second period to a low-quality product, which the customers value less than the product remanufactured “genuinely” by the original manufacturer [Ferrer, Swaminathan, 2006]. Under these assumptions, the authors derive Nash equilibrium strategies of the players in dependence of the model parameters and prove that under certain conditions, competition is forcing the manufacturer to charge lower prices either in the second or in both periods, compared to the case without competition. This analysis is further extended to a multi-period and infinite-horizon settings.

Ferguson and Toktay similarly address a two-period setting but assume that customers distinguish between new and remanufactured products [Ferguson, Toktay, 2006]. Furthermore, customers are heterogeneous with regard to their valuation of the new product, and each has a respectively lower valuation of the remanufactured version. The firm thus needs to decide about joint pricing of both kinds of product, taking into account that each sale of the remanufactured product cannibalizes a new product sale [Atasu et al., , which thus reflects competition between the two product versions [Ferguson, Toktay, 2006]. The authors accordingly derive the inverse demand functions for new and remanufactured products (the same approach has also been adopted by a number of studies in Stream 2, see Sections 3.2.1 and 3.2.2). Assuming the presence of a fixed collection and remanufacturing cost, they further obtain conditions under which a monopolist firm will not collect and remanufacture used products. They then expand the analysis to the case where a 3^rd party remanufacturer may enter the market and collect used products, which would create an external competition to the manufacturer, and which makes him collect and remanufacture used products for deterring the competitor's entry.

Ferrer and Swaminathan further extend their earlier analysis of a monopolist firm to a multi-period setting, in which customers distinguish between new and remanufactured products [Ferrer, Swaminathan, 2010], while Subramanian with co-authors study competition between a manufacturer and a 3^rd party, in which the manufacturer can use product design as a strategic instrument [Subramanian et al., 2013]. In their study setting, two product variants (high-end and low-end) may share common components. This would, on the one hand, simplify operations and supply chain management to the manufacturer, but on the other, increase unit cost of the low-end product. Further, it would reduce the customers' valuation of the high-end product while increasing their valuation of the low- end product. Finally, component commonality would reduce the cost of remanufacturing a high-end product for the manufacturer, but also for a 3^rd party competitor. The manufacturer therefore needs to strike a balance between these effects when deciding about component commonality in the product design. The authors derive equilibrium strategies of the firms and conduct a large-scale numerical study to generate insights into situations, in which remanufacturing and competition reverse the manufacturer's component commonality decision. They further provide a real-world illustration of their analysis on the example of the Apple iPad™ product family. We refer the reader to a similar study approach by Orsdemir with co-authors who consider product quality level as strategic instrument and further investigate the impact of competition with a 3^rd party remanufacturer on the environment and on consumer and social surplus [Orsdemir et al., 2014]. Interestingly, their results show that competitive remanufacturing can lead to a lower consumer and social surplus compared to the case of no remanufacturing, which happens due to the manufacturer's quality level choice under the pressure of competition.

Differently from the above studies, Bulmus with co-authors study competition between a manufacturer and a 3^rd party remanufacturer, which takes place both in sales of the serviceable products and in the acquisition of used products [Bulmus et al., 2014a]. They consider a two-period setting where the manufacturer produces new product in the first period, and both parties can collect used products at the beginning of the second period by choosing their acquisition prices. Collected products are being remanufactured in the same period; in addition, the manufacturer can also produce new products. They determine equilibrium strategies of the parties in the second period and, based on that, obtain the manufacturer's optimal production quantity in the first period. The authors explore three cases: (i) when customers do not distinguish between new and remanufactured products, (ii) when they do, and (iii) when they do not distinguish between the new and remanufactured products of the manufacturer but distinguish them from the products remanufactured by the 3^rd party. A numerical study reveals, among other insights, that a larger market size in the second period may in fact decrease the manufacturer's production in the first period -- when used products are difficult to collect for the manufacturer but are easy to for the 3^rd party, so that the manufacturer protects its market share by cutting the number of products available for remanufacturing.

Unlike the above work, Wu and Zhou study competition between two closed-loop supply chains [Wu, Zhou, 2017]. Each supply chain is modelled according to Savaskan with co-authors [Savaskan et al., 2004] while assuming that competition between them takes place in sales only. Each supply chain has to adopt a particular design -- that is, choose whether the manufacturer or the retailer will collect used products (Section 3.2.1), as decided by the manufacturer in each supply chain. While the study by Savaskan with co-authors [Savaskan et al., 2004] shows that collection by the retailer represents the most beneficial design in the absence of competition, the analysis by Wu and Zhou [Wu, Zhou, 2017] reveals that in certain situations, competition may entail one of the two manufacturers to undertake collection of used products -- which happens when the unit cost saving from remanufacturing is high enough, or when used products can be collected with a low effort, or both. When both retailers are collecting in such circumstances, sales competition between them is intensified, which drives down the retail price. As both manufacturers in this supply-chain design pass on direct savings from remanufacturing to their retailers (Section 3.2.1), they inevitably have to decrease their wholesale prices -- to the extent that one of the manufacturers switches to collecting himself in equilibrium. Interestingly, the authors further show that collection by both retailers may actually represent an equilibrium situation in the prisoner's dilemma [Osborne, Rubinstein, 1994, p. 16] -- in which both manufacturers could have gained by collecting themselves, but these strategies do not form an equilibrium.

Behavioural stream

Atasu with co-authors classify research in Stream 4 as the studies addressing behavioural aspects pertaining to product returns and perception of remanufactured products [Atasu et al., 2008]. In addition to the work reviewed by Atasu with co-authors [Atasu et al., 2008], we discuss the following studies in this stream.

The study by Zeng, discussed above in the context of reverse supply chain coordination (Section 3.2.1), involves an empirical investigation of consumer attitudes towards used product return [Zeng, 2013]. To this end, Zeng conducted a customer survey referring to one specific kind of product -- ink cartridges [Zeng, 2013]. The results of the survey suggest that it is reasonable to divide the customer base into three segments according to the factors that make customers return used products: either a pecuniary reward, or environmental awareness, or none. Further, the first and the second segments may to some degree overlap. The results of the survey can be used for estimating, at least partly, the relative segment sizes and customer response to the efforts directed towards attracting returns from different segments.

Agrawal with co-authors conducted a behavioural experiment study revealing that the presence of remanufactured products may in fact influence customer perception of the new products [Agrawal et al., 2015]. Their study referred to two kinds of electronic products -- portable audio players and consumer-grade printers, for which remanufactured versions are broadly available. The results of the study show that if a strong brand owner remanufactures its own products, this is likely to reduce the valuation of the new product by the customers. In contrast, if the product is remanufactured by a 3^rd party, this tends to increase the perceived value of the new product. This provides new insights into the issues of cannibalization and competition in remanufacturing studied in the strategy stream (Section 3.3).

The study by Abbey with co-authors empirically tests the assumption made in much of the literature that customers equally discount their valuation of the remanufactured product in comparison to the new product [Abbey et al., 2017]. Referring to a strong brand of consumer electronic products, the study suggests that discounting of the remanufactured product by the customers can be attributed to a perceived risk of functional and cosmetic defects in the product; different risk preferences of the customers accordingly result in different discounting behaviours. The study obtains an empirical distribution of discounting factors for a remanufactured iPhone^TM product and employs it in an infinite-horizon monopolist pricing problem (see Section 3.3), assuming that products can be remanufactured at most once. The results demonstrate that classical linear demand modelling via a constant discount factor may lead to sub-optimal pricing and significantly underestimate the potential profit from remanufacturing, thus being potentially misleading in the strategic decision about adopting product remanufacturing.

4. Summary and outlook

We have discussed supply chain management in the context of sustainable development goals and identified main paradigms, around which related academic research has been centred: the circular economy paradigm -- represented by closed-loop supply chain research, the emissions reduction paradigm -- represented by green forward supply chain management research, and a combined paradigm. We then focused on the circular economy paradigm and provided an overview of research in closed-loop supply chain management. As it would not be possible to review this body of research in its entirety here, we overviewed selected studies by adopting the research taxonomy proposed by Atasu with co-authors [Atasu et al., 2008] and aiming to address representative and recent work in four research streams. In so doing, we intended to outline essential features of analytical approaches and present key insights offered by the literature.

Apart from that, our review refines the original taxonomy and highlights various connections that have emerged between the four research streams over the past decade, which is the use of inventory management approaches (Stream 1) in supply chain coordination and limited product durability settings (Stream 2), studying supply chain coordination and design (Stream 2) under competition (Stream 3), differentiation between new and remanufactured products (Stream 3) in studying supply chain coordination and acquisition and pricing policies (Stream 2), and using behavioural models (Stream 4) for studying supply chain coordination (Stream 2) and pricing policies (Stream 3). This suggests that research is evolving towards an integrated perspective matching the definition of closed- loop supply chain management (Section 2).

While the closed-loop supply chain research agenda puts emphasis on economic benefits of product re-use [Eskandarpour et al., 2015; Geissdoerfer et al., 2017], the work centring around the emissions reduction paradigm and the combined paradigm is more explicit in emphasizing both economic and environmental dimensions of sustainability. As it would not be possible to review this work in the present article for reasons of space, we refer the reader to the following reviews addressing these paradigms. Ansari and Kant [Ansari, Kant, 2017] and Rajeev with co-authors provide a recent account of research evolution in sustainable supply chain management over the last 15 years, paying attention to all three sustainability dimensions [Rajeev et al., 2017]. Eskandarpour with co-authors focus on research work in the area of supply-chain network design [Eskandarpour et al., , while Chen with co-authors overview studies addressing supply chain coordination and collaboration [Chen et al., 2017]. Jaehn offers a systematic discussion of studies addressing operational-level planning [Jaehn, 2016]. We further refer the reader to Zimmer with co-authors for an overview of methods for supplier selection, monitoring and development involving all three sustainability dimensions [Zimmer et al., 2016], and to Feng with co-authors -- for an overview of literature addressing corporate social responsibility issues in the context of supply chain management [Feng et al., 2017].

Future work should be directed towards embracing both the circular economy and the emissions reduction paradigms -- studies that only begin to emerge [Yenipazarli, . Furthermore, the broad adoption of the sustainability mindset by the society and the trend towards digitalisation of economy requires a better understanding of the interplay between the societal and the technological developments, which invites supply chain management research and practice integrating both these perspectives [Lopes de Sousa Jabbour et al., 2018; Koppius et al., 2014].

Acknowledgments

The first author gratefully acknowledges financial support by the University of Dortmund, Germany, where this research has been partly conducted.

Literature

1. Abbey J. D., Kleber R., Souza G. C., Voigt G. The Role of Perceived Quality Risk in Pricing Remanufactured Products. Production and Operations Management, 2017, vol. 26, no. 1, pp. 100-115.

2. Agrawal V V., Atasu A., van Ittersum K. Remanufacturing, Third-Party Competition, and Consumers' Perceived Value of New Products. Management Science, 2015, vol. 61, no. 1, pp. 60-72.

3. Ahi P, Searcy C. A comparative literature analysis of definitions for green and sustainable supply chain management. Journal of Cleaner Production, 2013, vol. 52, pp. 329-341.

4. Akзali E., Зetinkaya S. Quantitative models for inventory and production planning in closed-loop supply chains. International Journal of Production Research, 2011, vol. 49, no. 8, pp. 2373-2407.

5. Akзali E., Зetinkaya S., Ьster H. Network design for reverse and closed-loop supply chains: An annotated bibliography of models and solution approaches. Networks, 2009, vol. 53, no. 3, pp. 231-248.

6. Alshamsi A., Diabat A. A Genetic Algorithm for Reverse Logistics network design: A case study from the GCC. Journal of Cleaner Production, 2017, vol. 151, pp. 652-669.

7. Alshamsi A., Diabat A. A reverse logistics network design. Journal of Manufacturing Systems, 2015, vol. 37, no. 3, pp. 589-598.

8. Alumur S. A., Nickel S., Saldanha-Da-Gama F., Verter V Multi-period reverse logistics network design. European Journal of Operational Research, 2012, vol. 220, no. 1, pp. 67-78.

9. Ansari Z. N., Kant R. A state-of-art literature review reflecting 15 years of focus on sustainable supply chain management. Journal of Cleaner Production, 2017, vol. 142, pp. 2524-2543.

10. Atasu A., Зetinkaya S. Lot Sizing for Optimal Collection and Use of Remanufacturable Returns over a Finite Life-Cycle. Production and Operations Management, 2006, vol. 15, no. 4, pp. 473-487.

11. Atasu A., Guide V D. R., Van Wassenhove L. N. Product Reuse Economics in Closed-Loop Supply Chain Research. Production and Operations Management, 2008, vol. 17, no. 5, pp. 483-496.

12. Atasu A., Guide V. D. R., Van Wassenhove L. N. So What If Remanufacturing Cannibalizes My New Product Sales? California Management Review, 2010, vol. 52, no. 2, pp. 56-76.

13. Atasu A., Toktay L. B., Van Wassenhove L. N. How Collection Cost Structure Drives a Manufacturer's Reverse Channel Choice. Production and Operations Management, 2013, vol. 22, no. 5, pp. 1089-1102.

14. Atasu A., Van Wassenhove L. N., Sarvary M. Efficient Take-Back Legislation. Production and Operations Management, 2009, vol. 18, no. 3, pp. 243-258.

15. Aydin R., Kwong C. K., Ji P Coordination of the closed-loop supply chain for product line design with consideration of remanufactured products. Journal of Cleaner Production, 2016, vol. 114, pp. 286-298.

16. Ayvaz B., Bolat B., Aydin N. Stochastic reverse logistics network design for waste of electrical and electronic equipment. Resources, Conservation and Recycling, 2015, vol. 104, pp. 391-404.

17. Banerjee A. A joint economic-lot-size model for purchaser and vendor. Decision Sciences, 1986, vol. 17, no. 3, pp. 292-311.

18. Bazan E., Jaber M. Y., Zanoni S. Carbon emissions and energy effects on a two-level manufacturer-retailer closed-loop supply chain model with remanufacturing subject to different coordination mechanisms. International Journal of Production Economics, 2017, vol. 183, pp. 394-408.

19. Benjaafar S., Li Y., Daskin M. Carbon footprint and the management of supply chains: Insights from simple models. IEEE Transactions on Automation Science and Engineering, 2013, vol. 10, no. 1, pp. 99-116.

20. Beske-Janssen P., Johnson M. P., Schaltegger S. 20 Years of Performance Measurement in Sustainable Supply Chain Management -- What Has Been Achieved? Supply Chain Management: An International Journal, 2015, vol. 20, no. 6, pp. 664-680.

21. Bhattacharya S., Guide V D. R., Wassenhove L. N. Optimal Order Quantities with Remanufacturing Across New Product Generations. Production and Operations Management, 2006, vol. 15, no. 3, pp. 421-431.

22. Braglia M., Zavanella L. Modelling an industrial strategy for inventory management in supply chains: The “Consignment Stock” case. International Journal of Production Research, 2003, vol. 41, no. 16, pp. 37933808.

23. Brandenburg M., Govindan K., Sarkis J., Seuring S. Quantitative models for sustainable supply chain management: Developments and directions. European Journal of Operational Research, 2014, vol. 233, no. 2, pp. 299-312.

24. Bulmus S. C., Zhu S. X., Teunter R. Competition for cores in remanufacturing. European Journal of Operational Research, 2014a, vol. 233, no. 1, pp. 105-113.

25. Bulmuз S. C., Zhu S. X., Teunter R. H. Optimal core acquisition and pricing strategies for hybrid manufacturing and remanufacturing systems. International Journal of Production Research, 2014b, vol. 52, no. 22, pp. 6627-6641.

26. Cachon G. P. Supply Chain Coordination with Contracts. Eds Kok de A. G., Graves S. C. Supply Chain Management: Design, Coordination and Operation. Handbooks in Operations Research and Management Science, vol. 11. Amsterdam, Elsevier, 2003, pp. 227-339.

27. Carter C. R., Easton P. L. Sustainable supply chain management: evolution and future directions. International Journal of Physical Distribution & Logistics Management, 2011, vol. 41, no. 1, pp. 46-62.

28. Cetinkaya B., Cuthbertson R., Ewer G., Klaas-Wissing T., Piotrowicz W, Tyssen C. Sustainable Supply Chain Management: Practical Ideas for Moving Towards Best Practice. Berlin, Springer, 2011, XVIII+283 pp.

29. Chen L., Zhao X., Tang O., Price L., Zhang S., Zhu W Supply chain collaboration for sustainability: A literature review and future research agenda. International Journal of Production Economics, 2017, vol. 194, pp. 7387.

30. Choi T.-M., Li Y., Xu L. Channel leadership, performance and coordination in closed loop supply chains. International Journal of Production Economics, 2013, vol. 146, no. 1, pp. 371-380.

31. Christopher M. Logistics and Supply Chain Management. 4^th ed. Harlow, Pearson, 2011, 288 pp.

32. Chuang C.-H., Wang C. X., Zhao Y. Closed-loop supply chain models for a high-tech product under alternative reverse channel and collection cost structures. International Journal of Production Economics, 2014, vol. 156, pp. 108-123.

33. Dekker R., Fleischmann M., Inderfurth K., Van Wassenhove L. N. (Eds). Reverse Logistics: Quantitative Models for Closed-Loop Supply Chains. Springer, Berlin, 2004, VIII+436 p.

34. Diabat A., Abdallah T., Henschel A. A closed-loop location-inventory problem with spare parts consideration. Computers and Operations Research, 2015, vol. 54, pp. 245-256.

35. Dobos I., Gobsch B., Pakhomova N., Pishchulov G., Richter K. Design of contract parameters in a closed-loop supply chain. Central European Journal of Operations Research, 2013, vol. 21, no. 4, pp. 713-727.

36. Dobos I., Pishchulov G., Gossinger R. How to control a reverse logistics system when used items return with diminishing quality. Eds Kliewer N., Ehmke J. F., Borndorfer R. Operations Research Proceedings 2017. Berlin, Springer, 2018, forthcoming.

37. Elkington J. Enter the Triple Bottom Line. The triple bottom line: does it all add up?: assessing the sustainability of business and CSR. Eds Henriques A., Richardson J. London, Earthscan, 2004, pp. 1-16.

38. Elkington J. Towards the Sustainable Corporation: Win-Win-Win Business Strategies for Sustainable Development. California Management Review, 1994, vol. 36, no. 2, pp. 90-100.

39. Eskandarpour M., Dejax P, Miemczyk J., Pйton O. Sustainable supply chain network design: An optimization- oriented review. Omega, 2015, vol. 54, pp. 11-32.

40. Directive 2003/87/EC of the European Parliament and of the Council of 13 October 2003 establishing a scheme for greenhouse gas emission allowance trading within the Community. European Commission.Official Journal of the European Union, 2003, vol. 46, no. L 275, pp. 32-46.

41. Directive 2012/27/EU of the European Parliament and of the Council of 25 October 2012 on energy efficiency. European Commission. Official Journal of the European Union, 2012, vol. 55, no. L 315, pp. 1-56.

42. Directorate-General for Climate Action. EU ETS Handbook. European Commission. Brussels, 2015. Available at: https://ec.europa.eu/clima/sites/clima/files/docs/ets_handbook_en.pdf (accessed: 29.03.2018).

43. El Saadany A. M. A., Jaber M. Y., Bonney M. How many times to remanufacture? International Journal of Production Economics, 2013, vol. 143, no. 2, pp. 598-604.

44. Feng Y., Zhu Q., Lai K.-H. Corporate social responsibility for supply chain management: A literature review and bibliometric analysis. Journal of Cleaner Production, 2017, vol. 158, pp. 296-307.

45. Ferguson M. E., Toktay L. B. The Effect of Competition on Recovery Strategies. Production and Operations Management, 2006, vol. 15, no. 3, pp. 351-368.

46. Ferrer G., Swaminathan J. M. Managing new and differentiated remanufactured products. European Journal of Operational Research, 2010, vol. 203, no. 2, pp. 370-379.

47. Ferrer G., Swaminathan J. M. Managing New and Remanufactured Products. Management Science, 2006, vol. 52, no. 1, pp. 15-26.

48. Fleischmann M., Bloemhof-Ruwaard J. M., Dekker R., van der Laan E., van Nunen J. a. E. E., Van Wassenhove L. N. Quantitative models for reverse logistics: A review. European Journal of Operational Research, 1997, vol. 103, no. 1, pp. 1-17.

49. Fьgenschuh A., Martin A. Computational Integer Programming and Cutting Planes. Eds Aardal K., Nemhauser G., Weismantel R. Discrete Optimization. Handbooks in Operations Research and Management Science, vol. 12. Amsterdam, North Holland, 2005, pp. 69-121.

50. Gao J., Han H., Hou L., Wang H. Pricing and effort decisions in a closed-loop supply chain under different channel power structures. Journal of Cleaner Production, 2016, vol. 112, pp. 2043-2057.

51. Geissdoerfer M., Savaget P, Bocken N. M. P, Hultink E. J. The Circular Economy -- A new sustainability paradigm? Journal of Cleaner Production, 2017, vol. 143, pp. 757-768.

52. De Giovanni P., Reddy P. V, Zaccour G. Incentive strategies for an optimal recovery program in a closed-loop supply chain. European Journal of Operational Research, 2016, vol. 249, no. 2, pp. 605-617.

53. De Giovanni P, Zaccour G. A two-period game of a closed-loop supply chain. European Journal of Operational Research, 2014, vol. 232, no. 1, pp. 22-40.

54. Gomes M. I., Barbosa-Povoa A. P, Novais A. Q. Modelling a recovery network for WEEE: A case study in Portugal. Waste Management, 2011, vol. 31, no. 7, pp. 1645-1660.

55. Govindan K., Fattahi M., Keyvanshokooh E. Supply chain network design under uncertainty: A comprehensive review and future research directions. European Journal of Operational Research, 2017, vol. 263, no. 1, pp. 108-141.

56. Govindan K., Popiuc M. N. Reverse supply chain coordination by revenue sharing contract: A case for the personal computers industry. European Journal of Operational Research, 2014, vol. 233, no. 2, pp. 326-336.

57. Govindan K., Soleimani H., Kannan D. Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future. European Journal of Operational Research, 2015, vol. 240, no. 3, pp. 603-626.

58. Guide V. D. R., Van Wassenhove L. N. The Evolution of Closed-Loop Supply Chain Research. Operations Research, 2009, vol. 57, no. 1, pp. 10-18.

59. Guo S., Shen B., Choi T.-M., Jung S. A review on supply chain contracts in reverse logistics: Supply chain structures and channel leaderships. Journal of Cleaner Production, 2017, vol. 144, pp. 387-402.

60. Harrington L. Closing the loop: Building the environmental supply chain. Bonn, DHL Supply Chain, 2014, 24 p. Available at: http://supplychain.dhl.com/Enviro-Resilience (accessed: 29.03.2018).

61. Hong X., Wang Z., Wang D., Zhang H. Decision models of closed-loop supply chain with remanufacturing under hybrid dual-channel collection. The International Journal of Advanced Manufacturing Technology, 2013, vol. 68, no. 5-8, pp. 1851-1865.

62. Ilgin M. A., Gupta S. M. Environmentally conscious manufacturing and product recovery (ECMPRO): A review of the state of the art. Journal of Environmental Management, 2010, vol. 91, no. 3, pp. 563-591.

63. Jaber M. Y., Zanoni S., Zavanella L. E. A consignment stock coordination scheme for the production, remanufacturing and waste disposal problem. International Journal of Production Research, 2014, vol. 52, no. 1, pp. 50-65.

64. Jaehn F. Sustainable Operations. European Journal of Operational Research, 2016, vol. 253, no. 2, pp. 243-264.

65. Jonrinaldi, Zhang D. Z. An integrated production and inventory model for a whole manufacturing supply chain involving reverse logistics with finite horizon period. Omega, 2013, vol. 41, no. 3, pp. 598-620.

66. Khatami M., Mahootchi M., Farahani R. Z. Benders' decomposition for concurrent redesign of forward and closed-loop supply chain network with demand and return uncertainties. Transportation Research Part E: Logistics and Transportation Review, 2015, vol. 79, pp. 1-21.

67. Kim K., Jeong B., Jung H. Supply chain surplus: Comparing conventional and sustainable supply chains. Flexible Services and Manufacturing Journal, 2014, vol. 26, no. 1-2, pp. 5-23.

68. Kim T., Glock C. H. On the use of RFID in the management of reusable containers in closed-loop supply chains under stochastic container return quantities. Transportation Research Part E: Logistics and Transportation Review, 2014, vol. 64, pp. 12-27.

69. Koppius O., Цzdemir Akyildirim Ц., Laan E. van der. Business Value from Closed-loop Supply Chains. International Journal of Supply Chain Management, 2014, vol. 3, no. 4, pp. 107-120.

70. Krapp M., Kraus J. B. Coordination contracts for reverse supply chains: a state-of-the-art review. Journal of Business Economics, 2017 (in press). doi: 10.1007/s11573-017-0887-z.

71. Krass D., Nedorezov T., Ovchinnikov A. Environmental taxes and the choice of green technology. Production and Operations Management, 2013, vol. 22, no. 5, pp. 1035-1055.

72. Kumar V. N. S. A., Kumar V, Brady M., Garza-Reyes J. A., Simpson M. Resolving forward-reverse logistics multi-period model using evolutionary algorithms. International Journal of Production Economics, 2017, vol. 183, no. B, pp. 458-469.

73. Kyoto Protocol to the United Nations Framework Convention on Climate Change, 2005. United Nations Treaty Collection. Registration Number 30822. URL: https://treaties.un.org/Pages/showDetails. aspx?objid=0800000280021a16 (accessed: 29.03. 2018).

74. Laporte G., Louveaux F. V. The integer L-shaped method for stochastic integer programs with complete recourse. Operations Research Letters, 1993, vol. 13, no. 3, pp. 133-142.

75. Lee H. L., Tang C. S. Socially and Environmentally Responsible Value Chain Innovations: New Operations Management Research Opportunities. Management Science, 2018, vol. 64, no. 3, pp. 983-996.

76. Linton J. D., Klassen R., Jayaraman V. Sustainable supply chains: An introduction. Journal of Operations Management, 2007, vol. 25, no. 6, pp. 1075-1082.

77. Lopes de Sousa Jabbour A. B., Jabbour C. J. C., Godinho Filho M., Roubaud D. Industry 4.0 and the circular economy: a proposed research agenda and original roadmap for sustainable operations. Annals of Operations Research, 2018, in press. doi: 10.1007/sl0479-018-2772-8.

78. Louveaux F. V., Schultz R. Stochastic Integer Programming. Eds Ruszczynski A., Shapiro A. Handbooks in Operations Research and Management Science: Stochastic Programming, vol. 10. Amsterdam, Elsevier, 2003, pp. 213-266.

79. Maiti T., Giri B. C. A closed loop supply chain under retail price and product quality dependent demand. Journal of Manufacturing Systems, 2015, vol. 37, pp. 624-637.

80. Maiti T., Giri B. C. Two-way product recovery in a closed-loop supply chain with variable markup under price and quality dependent demand. International Journal of Production Economics, 2017, vol. 183, no. A, pp. 259-272.

81. Montreal Protocol on Substances that Deplete the Ozone Layer. United Nations. United Nations Treaty Series, 1989, vol. 1522, no. 26369, pp. 29-40.

82. Mutha A., Bansal S., Guide V D. R. Managing Demand Uncertainty through Core Acquisition in Remanufacturing. Production and Operations Management, 2016, vol. 25, no. 8, pp. 1449-1464.

83. Oeser G. Risk-Pooling Essentials. Cham, Springer, 2015, IX+91 pp.

84. Цrsdemir A., Kemahlioglu-Ziya E., Parlaktьrk A. K. Competitive Quality Choice and Remanufacturing. Production and Operations Management, 2014, vol. 23, no. 1, pp. 48-64.

85. Osborne M. J., Rubinstein A. A Course in Game Theory. Cambridge, Massachusetts, The MIT Press, 1994, 368 pp.

86. Цzkir V., Ba^ligil H. Modelling product-recovery processes in closed-loop supply-chain network design. International Journal of Production Research, 2012, vol. 50, no. 8, pp. 2218-2233.

87. Pakhomova N. V, Richter K. K., Vetrova M. A. Transition To Circular Economy and Closed-Loop Supply Chains As Driver of Sustainable Development. St Petersburg University Journal of Economic Studies, 2017, vol. 33, no. 2, pp. 244-268.

88. Pishchulov G., Dobos I., Gobsch B., Pakhomova N., Richter K. A vendor-purchaser economic lot size problem with remanufacturing. Journal of Business Economics, 2014, vol. 84, no. 5, pp. 749-791.

89. Rajeev A., Pati R. K., Padhi S. S., Govindan K. Evolution of sustainability in supply chain management: A literature review. Journal of Cleaner Production, 2017, vol. 162, pp. 299-314.

90. Report of the Conference of the Parties on its twenty-first session, held in Paris from 30 November to 13 December 2015. Addendum. Part two: Action taken by the Conference of the Parties at its twenty-first session. United Nations Framework Convention on Climate Change (UNFCCC), Document No. FCCC/ CP/2015/10/Add.1. Geneva, 29.01. 2016. 36 p. Available at: http://unfccc.int/resource/docs/2015/cop21/ eng/10a01.pdf (accessed: 29.03.2018).

91. Report of the World Commission on Environment and Development. United Nations.Official Document System of the United Nations, Document No. A/42/427. Geneva, August 4, 1987. Available at: https://documents- dds-ny.un.org/doc/UNDOC/GEN/N87/184/67/img/N8718467.pdf (accessed: 29.03.2018).

92. Richter K. Pure and mixed strategies for the EOQ repair and waste disposal problem. OR Spektrum, 1997, vol. 19, no. 2, pp. 123-129.

93. Richter K. The EOQ repair and waste disposal model with variable setup numbers. European Journal of Operational Research, 1996, vol. 95, no. 2, pp. 313-324.

94. Robson A. Australia's Carbon Tax: An Economic Evaluation. Economic Affairs, 2014, vol. 34, no. 1, pp. 35-45.

95. Saha S., Sarmah S. P, Moon I. Dual channel closed-loop supply chain coordination with a reward-driven remanufacturing policy. International Journal of Production Research, 2016, vol. 54, no. 5, pp. 1503-1517.

96. Sahyouni K., Savaskan R. C., Daskin M. S. A Facility Location Model for Bidirectional Flows. Transportation Science, 2007, vol. 41, no. 4, pp. 484-499.

97. Savaskan R. C., Bhattacharya S., Van Wassenhove L. N. Closed-Loop Supply Chain Models with Product Remanufacturing. Management Science, 2004, vol. 50, no. 2, pp. 239-252.

98. Savaskan R. C., Van Wassenhove L. N. Reverse Channel Design: The Case of Competing Retailers. Management Science, 2006, vol. 52, no. 1, pp. 1-14.