Research article Special Issues

Maintaining energy efficiencies and reducing carbon emissions under a sustainable supply chain management

  • Received: 12 March 2022 Revised: 21 July 2022 Accepted: 15 August 2022 Published: 22 September 2022
  • Currently, most countries are moving towards digitalization, and their energy consumption is increasing daily. Thus, power networks face major challenges in controlling energy consumption and supplying huge amounts of electricity. Again, using excessive power reduces the stored fossil fuels and affects the environment in terms of $ {\rm CO_{2}} $ emissions. Keep these issues in mind; this study focuses on energy-efficient products in an energy supply chain management model under credit sales, variable production, and stochastic demand. Here, the manufacturer grants a credit period for the retailer to get more orders; thus, the order quantity is related to the credit period envisaged in this model. Considering such components, supply chain members can reduce negative environmental impacts and significant energy consumption, achieve optimal results and avoid drastic financial losses. Additionally, including a credit period increases the possibility of default risk, for which a certain interest is charged. The marginal reduction cost for limiting carbon emissions, flexible production to meet fluctuating demand, and continuous investment to improve product quality are considered here. The global optimality of system profit function and decision variables (credit period, quality improvement, and production rate) is ensured through the classical optimization method. Interpretive sensitivity analyses and numerical investigations are performed to validate the proposed model. The results demonstrate that the idea of credit sales, flexible production, and quality improvement increases total system profit by $ 28.64\% $ and marginal reduction technology reduces $ {\rm CO_{2}} $ emissions up to $ 4.01\% $.

    Citation: Mowmita Mishra, Santanu Kumar Ghosh, Biswajit Sarkar. Maintaining energy efficiencies and reducing carbon emissions under a sustainable supply chain management[J]. AIMS Environmental Science, 2022, 9(5): 603-635. doi: 10.3934/environsci.2022036

    Related Papers:

  • Currently, most countries are moving towards digitalization, and their energy consumption is increasing daily. Thus, power networks face major challenges in controlling energy consumption and supplying huge amounts of electricity. Again, using excessive power reduces the stored fossil fuels and affects the environment in terms of $ {\rm CO_{2}} $ emissions. Keep these issues in mind; this study focuses on energy-efficient products in an energy supply chain management model under credit sales, variable production, and stochastic demand. Here, the manufacturer grants a credit period for the retailer to get more orders; thus, the order quantity is related to the credit period envisaged in this model. Considering such components, supply chain members can reduce negative environmental impacts and significant energy consumption, achieve optimal results and avoid drastic financial losses. Additionally, including a credit period increases the possibility of default risk, for which a certain interest is charged. The marginal reduction cost for limiting carbon emissions, flexible production to meet fluctuating demand, and continuous investment to improve product quality are considered here. The global optimality of system profit function and decision variables (credit period, quality improvement, and production rate) is ensured through the classical optimization method. Interpretive sensitivity analyses and numerical investigations are performed to validate the proposed model. The results demonstrate that the idea of credit sales, flexible production, and quality improvement increases total system profit by $ 28.64\% $ and marginal reduction technology reduces $ {\rm CO_{2}} $ emissions up to $ 4.01\% $.



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    [1] Luo X, Wang J, Dooner M, et al. (2015) Overview of current development in electrical energy storage technologies and the application potential in power system operation. Applied Energy 137: 511–536. https://doi.org/10.1016/j.apenergy.2014.09.081 doi: 10.1016/j.apenergy.2014.09.081
    [2] Nosratabadi SM, Hooshmand RA, Gholipour E (2017) A comprehensive review on microgrid and virtual power plant concepts employed for distributed energy resources scheduling in power systems. Renewable and Sustainable Energy Reviews 67: 341–363. https://doi.org/10.1016/j.rser.2016.09.025 doi: 10.1016/j.rser.2016.09.025
    [3] Yang L, Elisa N, Eliot N (2019) Privacy and security aspects of E-government in smart cities. Smart cities cybersecurity and privacy 2019: 89–102. https://doi.org/10.1016/B978-0-12-815032-0.00007-X doi: 10.1016/B978-0-12-815032-0.00007-X
    [4] Kim H, Choi H, Kang H, et al. (2021) A systematic review of the smart energy conservation system: From smart homes to sustainable smart cities. Renewable and Sustainable Energy Reviews 140: 110755. https://doi.org/10.1016/j.rser.2021.110755 doi: 10.1016/j.rser.2021.110755
    [5] Williams J, Alizadeh R, Allen JK, et al. (2020) Using network partitioning to design a green supply chain. International Design Engineering Technical Conferences and Computers and Information in Engineering Conference 84010: V11BT11A050. https://doi.org/10.1115/DETC2020-22644 doi: 10.1115/DETC2020-22644
    [6] Lebrouhi B, Khattari Y, Lamrani B, et al. (2021) Key challenges for a large-scale development of battery electric vehicles: A comprehensive review. Journal of Energy Storage 44: 103273. https://doi.org/10.1016/j.est.2021.103273 doi: 10.1016/j.est.2021.103273
    [7] Torkayesh AE, Alizadeh R, Soltanisehat L, et al. (2022) A comparative assessment of air quality across European countries using an integrated decision support model. Socio-Economic Planning Sciences 81: 101198. https://doi.org/10.1016/j.seps.2021.101198 doi: 10.1016/j.seps.2021.101198
    [8] Lariviere MA, Porteus EL (2001) Selling to the newsvendor: An analysis of price-only contracts. Manufacturing & Service Operations Management 3(4): 293–305. https://doi.org/10.1287/msom.3.4.293.9971 doi: 10.1287/msom.3.4.293.9971
    [9] Teng JT, Lou KR, Wang L (2014) Optimal trade credit and lot size policies in economic production quantity models with learning curve production costs. International Journal of Production Economics 155: 318–323. https://doi.org/10.1016/j.ijpe.2013.10.012 doi: 10.1016/j.ijpe.2013.10.012
    [10] Shaikh AA, Das SC, Bhunia AK, et al. (2021) Decision support system for customers during availability of trade credit financing with different pricing situations. RAIRO-Operations Research 55(2): 1043–1061. https://doi.org/10.1051/ro/2021015 doi: 10.1051/ro/2021015
    [11] Wang WC, Teng JT, Lou KR (2014) Seller's optimal credit period and cycle time in a supply chain for deteriorating items with maximum lifetime. European Journal of Operational Research 232: 315–321. https://doi.org/10.1016/j.ejor.2013.06.027 doi: 10.1016/j.ejor.2013.06.027
    [12] Vandana, Singh SR, Yadav D, et al. (2021) Impact of energy and carbon emission of a supply chain management with two-level trade-credit policy. Energies 14(6): 1569. https://doi.org/10.3390/en14061569 doi: 10.3390/en14061569
    [13] Sarkar B, Mridha B, Pareek S (2022) A sustainable smart multi-type biofuel manufacturing with the optimum energy utilization under flexible production. Journal of Cleaner Production 332: 129869. https://doi.org/10.1016/j.jclepro.2021.129869 doi: 10.1016/j.jclepro.2021.129869
    [14] Taguchi T (2008) Present status of energy saving technologies and future prospect in white LED lighting. IEEJ Transactions on Electrical and Electronic Engineering 3: 21–26. https://doi.org/10.1002/tee.20228 doi: 10.1002/tee.20228
    [15] Khorasanizadeh H, Parkkinen J, Parthiban R, et al. (2015) Energy and economic benefits of LED adoption in Malaysia. Renewable and Sustainable Energy Reviews 49: 629–637. https://doi.org/10.1016/j.rser.2015.04.112 doi: 10.1016/j.rser.2015.04.112
    [16] Sardar SK, Sarkar B (2020) How Does Advanced Technology Solve Unreliability Under Supply Chain Management Using Game Policy? Mathematics 8(7): 1191. https://doi.org/10.3390/math8071191 doi: 10.3390/math8071191
    [17] Mondal AK, Pareek S, Chaudhuri K, Bera A, Bachar RK, Sarkar B (2022) Technology license sharing strategy for remanufacturing industries under a closed-loop supply chain management bonding. RAIRO-Operations Research 56 : 3017 – 45. https://doi.org/10.1051/ro/2022058 doi: 10.1051/ro/2022058
    [18] Li R, Skouri K, Teng JT, et al. (2018) Seller's optimal replenishment policy and payment term among advance, cash, and credit payments. International Journal of Production Economics 197: 35–42. https://doi.org/10.1016/j.ijpe.2017.12.015 doi: 10.1016/j.ijpe.2017.12.015
    [19] Wang K, Ding P, Zhao R (2021) Strategic credit sales to express retail under asymmetric default risk and stochastic market demand. Omega 101: 102253. https://doi.org/10.1016/j.omega.2020.102253 doi: 10.1016/j.omega.2020.102253
    [20] Lazarov BS, Sigmund O, Meyer KE, et al. (2018) Experimental validation of additively manufactured optimized shapes for passive cooling. Applied Energy 226: 330–339. https://doi.org/10.1016/j.apenergy.2018.05.106 doi: 10.1016/j.apenergy.2018.05.106
    [21] Gorgulu S, Kocabey S (2020) An energy saving potential analysis of lighting retrofit scenarios in outdoor lighting systems: A case study for a university campus. Journal of Cleaner Production 260: 121060. https://doi.org/10.1016/j.jclepro.2020.121060 doi: 10.1016/j.jclepro.2020.121060
    [22] Zarindast A, Sharma A, Wood J (2021) Application of text mining in smart lighting literature-an analysis of existing literature and a research agenda. International Journal of Information Management Data Insights 1: 100032. https://doi.org/10.1016/j.jjimei.2021.100032 doi: 10.1016/j.jjimei.2021.100032
    [23] Chen LH, Chen YC (2010) A multiple-item budget-constraint newsboy problem with a reservation policy. Omega 38: 431–439. https://doi.org/10.1016/j.omega.2009.10.007 doi: 10.1016/j.omega.2009.10.007
    [24] Zhan J, Chen X, Hu Q (2019) The value of trade credit with rebate contract in a capital-constrained supply chain. International Journal of Production Research 57: 379–396. https://doi.org/10.1080/00207543.2018.1442946 doi: 10.1080/00207543.2018.1442946
    [25] Jani MY, Betheja MR, Chaudhari U, et al. (2021) Optimal Investment in Preservation Technology for Variable Demand under Trade-Credit and Shortages. Mathematics 9: 1301. https://doi.org/10.3390/math9111301 doi: 10.3390/math9111301
    [26] Kishore A, Cárdenas-Barrón LE, Jaggi CK (2022) Strategic decisions in an imperfect quality and inspection scenario under two-stage credit financing with order overlapping approach. Expert Systems with Applications 2022: 116426. https://doi.org/10.1016/j.eswa.2021.116426 doi: 10.1016/j.eswa.2021.116426
    [27] Wu J, Ouyang LY, Cárdenas-Barrón LE, et al. (2014) Optimal credit period and lot size for deteriorating items with expiration dates under two-level trade credit financing. European Journal of Operational Research. 237: 898–908. https://doi.org/10.1016/j.ejor.2014.03.009 doi: 10.1016/j.ejor.2014.03.009
    [28] Wang K, Zhao R, Peng J (2018) Trade credit contracting under asymmetric credit default risk: Screening, checking or insurance. European Journal of Operational Research 266: 554–568. https://doi.org/10.1016/j.ejor.2017.10.004 doi: 10.1016/j.ejor.2017.10.004
    [29] Kaur A, Vandana (2019) Two-level trade credit with default risk in the supply chain under stochastic demand. Omega 88: 4–23. https://doi.org/10.1016/j.omega.2018.12.003 doi: 10.1016/j.omega.2018.12.003
    [30] Tsao YC, Vu TL, Lu JC (2021) Pricing, capacity and financing policies for investment of renewable energy generations. Applied Energy 303: 117664. https://doi.org/10.1016/j.apenergy.2021.117664 doi: 10.1016/j.apenergy.2021.117664
    [31] Chen SC, Teng JT (2015) Inventory and credit decisions for time-varying deteriorating items with upstream and down-stream trade credit financing by discounted cash flow analysis. European Journal of Operational Research 243: 566–575. https://doi.org/10.1016/j.ejor.2014.12.007 doi: 10.1016/j.ejor.2014.12.007
    [32] Shaikh AA, Cárdenas-Barrón LE (2020) An EOQ inventory model for non-instantaneous deteriorating products with advertisement and price sensitive demand under order quantity dependent trade credit. Investigación Operacional 41: 168–187.
    [33] Sarkar B, Joo J, Kim Y, Park H, Sarkar M (2022) Controlling defective items in a complex multi-phase manufacturing system. RAIRO–Operations Research 56(2).
    [34] Sepehri A, Mishra U, Sarkar B (2021) A sustainable production-inventory model with imperfect quality under preservation technology and quality improvement investment. Journal of Cleaner Production 310: 127332. https://doi.org/10.1016/j.jclepro.2021.127332 doi: 10.1016/j.jclepro.2021.127332
    [35] Choi SB, Dey BK, Sarkar B (2022) Retailing and servicing strategies for an imperfect production with variable lead time and backorder under online-to-offline environment. Journal of Industrial and Management Optimization. https://doi.org/10.3934/jimo.2022150 doi: 10.3934/jimo.2022150
    [36] Habib MS, Omair M, Ramzan MB, Chaudhary TN, Farooq M, Sarkar B (2022) A robust possibilistic flexible programming approach toward a resilient and cost-efficient biodiesel supply chain network. Journal of Cleaner Production 366 : 132752. https://doi.org/10.1016/j.jclepro.2022.132752 doi: 10.1016/j.jclepro.2022.132752
    [37] Sarkar B, Dey BK, Sarkar M, Kim SJ (2022) A smart production system with an autonomation technology and dual channel retailing. Computers & Industrial Engineering 28:108607. https://doi.org/10.1016/j.cie.2022.108607 doi: 10.1016/j.cie.2022.108607
    [38] Sarkar B, Ullah M, Sarkar M (2022) Environmental and economic sustainability through innovative green products by remanufacturing. Journal of Cleaner Production 332: 129813. https://doi.org/10.1016/j.jclepro.2021.129813 doi: 10.1016/j.jclepro.2021.129813
    [39] Yadav D, Singh R, Kumar A, Sarkar B (2022) Reduction of pollution through sustainable and flexible production by controlling by-products. Journal of Environmental Informatics https://doi.org/10.3808/jei.202200476 doi: 10.3808/jei.202200476
    [40] Sarkar B, Debnath A, Chiu AS, wt al. (2022) Circular economy-driven two-stage supply chain management for nullifying waste. Journal of Cleaner Production 339: 130513. https://doi.org/10.1016/j.jclepro.2022.130513 doi: 10.1016/j.jclepro.2022.130513
    [41] Habib MS, Asghar O, Hussain A, et al. (2021) A robust possibilistic programming approach toward animal fat-based biodiesel supply chain network design under uncertain environment. Journal of Cleaner Production 278: 122403. https://doi.org/10.1016/j.jclepro.2020.122403 doi: 10.1016/j.jclepro.2020.122403
    [42] Kumar S, Sigroha M, Kumar K, et al. (2022) Manufacturing/remanufacturing based supply chain management under advertisements and carbon emission process. RAIRO Operations Research 56: 831–851. https://doi.org/10.1051/ro/2021189 doi: 10.1051/ro/2021189
    [43] Moon I, Yun W, Sarkar B (2022) Effects of variable setup cost, reliability, and production costs under controlled carbon emissions in a reliable production system. European Journal of Industrial Engineering 16: 371–397. doi: 10.1504/EJIE.2022.123748
    [44] Kugele AS, Ahmed W, Sarkar B (2022) Geometric programming solution of second degree difficulty for carbon ejection controlled reliable smart production system. RAIRO-Operations Research 56 : 1013 – 29. doi: 10.1051/ro/2022028
    [45] Hota SK, Ghosh SK, Sarkar B (2022) A solution to the transportation hazard problem in a supply chain with an unreliable manufacturer. AIMS Environmental Science 9: 354–380. https://doi.org/10.3934/environsci.2022023 doi: 10.3934/environsci.2022023
    [46] Pal B, Sarkar A, Sarkar B (2023) Optimal decisions in a dual-channel competitive green supply chain management under promotional effort. Expert Systems with Applications 211:118315. https://doi.org/10.1016/j.eswa.2022.118315 doi: 10.1016/j.eswa.2022.118315
    [47] Elsarrag E (2008) Experimental study of using fuel cells in dwellings for energy saving lighting and other low power applications. International journal of hydrogen energy 33: 4427–4432. https://doi.org/10.1016/j.ijhydene.2008.05.049 doi: 10.1016/j.ijhydene.2008.05.049
    [48] Arce P, Medrano M, Gil A, et al. (2011) Overview of thermal energy storage (TES) potential energy savings and climate change mitigation in Spain and Europe. Applied energy 88: 2764–2774. https://doi.org/10.1016/j.apenergy.2011.01.067 doi: 10.1016/j.apenergy.2011.01.067
    [49] Navarro L, De Gracia A, Colclough S, et al. (2016) Thermal energy storage in building integrated thermal systems: A review. Part 1. active storage systems. Renewable Energy. 88: 526–547. https://doi.org/10.1016/j.renene.2015.11.040 doi: 10.1016/j.renene.2015.11.040
    [50] Kiwan S, Abo Mosali A, Al-Ghasem A (2018) Smart Solar-Powered LED outdoor lighting system based on the energy storage level in batteries Buildings 8: 119. https://doi.org/10.3390/buildings8090119 doi: 10.3390/buildings8090119
    [51] Nie B, Palacios A, Zou B, et al. (2020) Review on phase change materials for cold thermal energy storage applications. Renewable and Sustainable Energy Reviews 134: 110340. https://doi.org/10.1016/j.rser.2020.110340 doi: 10.1016/j.rser.2020.110340
    [52] Zhang K, Pan M, Li X (2022) A novel efficient and economic integrated energy system based on solid oxide fuel cell with energy storage and carbon dioxide capture. Energy Conversion and Management 252: 115084. https://doi.org/10.1016/j.enconman.2021.115084 doi: 10.1016/j.enconman.2021.115084
    [53] Mandal B, Dey BK, Khanra S, et al. (2021) Advance sustainable inventory management through advertisement and trade-credit policy. RAIRO-Operations Research 55: 261–284. https://doi.org/10.1051/ro/2020067 doi: 10.1051/ro/2020067
    [54] Sarkar B, Zhang C, Majumder A, et al. (2018) A distribution free newsvendor model with consignment policy and retailer's royalty reduction. International Journal of Production Research 56:5025–5044. https://doi.org/10.1080/00207543.2017.1399220 doi: 10.1080/00207543.2017.1399220
    [55] Sarkar B, Bhuniya S (2022) A sustainable flexible manufacturing–remanufacturing model with improved service and green investment under variable demand. Expert Systems With Applications 202: 117154. https://doi.org/10.1016/j.eswa.2022.117154 doi: 10.1016/j.eswa.2022.117154
    [56] Ghosh SK, Seikh MR, Chakrabortty M (2020) Analyzing a stochastic dual-channel supply chain under consumers' low carbon preferences and cap-and-trade regulation. Computers & Industrial Engineering 149: 106765. https://doi.org/10.1016/j.cie.2020.106765 doi: 10.1016/j.cie.2020.106765
    [57] Padiyar SV, Vandana V, Bhagat N, Singh SR, Sarkar B (2022) Joint replenishment strategy for deteriorating multi-item through multi-echelon supply chain model with imperfect production under imprecise and inflationary environment. RAIRO-Operations Research 56 : 3071–96. https://doi.org/10.1051/ro/2022071 doi: 10.1051/ro/2022071
    [58] Hua G, Zhang Y, Cheng T, et al. (2020) The newsvendor problem with barter exchange. Omega 92: 102149. https://doi.org/10.1016/j.omega.2019.102149 doi: 10.1016/j.omega.2019.102149
    [59] Ullah M, Asghar I, Zahid M, et al. (2021) Ramification of remanufacturing in a sustainable three-echelon closed-loop supply chain management for returnable products. Journal of Cleaner Production 290: 125609. https://doi.org/10.1016/j.jclepro.2020.125609 doi: 10.1016/j.jclepro.2020.125609
    [60] Rahman SM, Pompidou S, Alix T, et al. (2021) A review of LED lamp recycling process from the 10 R strategy perspective. Sustainable Production and Consumption 28: 1178–1191. https://doi.org/10.1016/j.spc.2021.07.025 doi: 10.1016/j.spc.2021.07.025
    [61] Hota SK, Ghosh SK, Sarkar B (2022) Involvement of smart technologies in an advanced supply chain management to solve unreliability under distribution robust approach. AIMS Environmental Science 9: 505–525. https://doi.org/10.3934/environsci.2022030 doi: 10.3934/environsci.2022030
    [62] Bachar RK, Bhuniya S, Ghosh SK, et al. (2022) Sustainable green production model considering variable demand, partial outsourcing, and rework. AIMS Environmental Science 9: 325–353. https://doi:10.3934/environsci.2022022 doi: 10.3934/environsci.2022022
    [63] Zhang B, Chen M, Wei L (2022) Impacts of barter exchange and decision biases in a two‐level supply chain under pull contract. International Transactions in Operational Research 29: 1868–1896. https://doi.org/10.1111/itor.13057 doi: 10.1111/itor.13057
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