Green sustainable supply chain under cap and trade regulation involving Government introspection

This paper investigates Government intervention in a three-echelon supply chain comprising one manufacturer and one retailer. Government is the top level member trying to reduce environmental impacts based on the amount of carbon emission during the production process. Government controls the chain by collecting tax from the retailer which is indirectly paid by the customer and paying subsidy/imposing ne on the manufacturer. Government encourages manufacturer to reduce carbon emission by contributing some subsidy and also makes an e ort to generate Government net revenue (GNR) by imposing tax. The GNR is generated by collecting tax from the retailer on the sold product and penalty from the manufacturer at the trading price for the extra amount of emissions. The retail price is decided based on the selling price, tax and greening level. We aim to determine optimal levels of pricing, greening and amount of tax to be levied. The models for both linear and iso-elastic demand patterns are developed. The aim of this piece research is two-fold: (i) review the existent literature on the relationship between environ- mental collaboration and sustainability performance and (ii) render a tenable prototype of supply chain to illuminate the relationship between sustainability and profitability. According to the aforesaid goals this paper has carried out a detailed empirical research by using advanced structural equation modelling approaches. The research findings will be particularly important for manufacturing companies struggling to find techniques to achieve sustainability performance. Also it will aid the supply chains in developing environmental collaboration with the Govt. in order to attain the targets of GSCM.

The Effect of Sustainable Supply Chain Management on Company Performance Mediated by Competitive Advantage

This study aims to examine the effect of sustainable supply chain management on company performance mediated by competitive advantage, the subjects of this study were the actors of the pottery Joint Business Group (JBG) in Banten Province, Indonesia. This type of research is quantitative research with descriptive research and causal research using questionnaires distributed directly to the JBG Pottery actors as many as 100 respondents. Moreover, Structural Equation Model (SEM) in the SmartPLS Software version 3.0.m3 (SmartPLS GmbH: Bönningstedt, Germany) was used for data analysis. The results of the study found that sustainable supply chain management affects competitive advantage, company performance was also observed to be influenced by sustainable supply chain management and competitive advantage while company performance was also found to be affected by sustainable supply chain management through the mediating effect of competitive advantage. The significant implication of this study is for managers to ensure competitiveness in the process of implementing sustainability supply chain to improve company performance, while providing recommendations to the government through Disperindagkop and SMEs in conducting the assistance process to MSMEs.

Smart Sustainable Production and Distribution Network Model for City Multi-Floor Manufacturing Clusters

This study focuses on management ways within a city multi-floor manufacturing cluster (MFMC). The application of MFMC in megapolises is closely related to the problem of urban spatial development and the problem of matching transport and logistics services. The operation of the MFMC depends on the efficiency of production and transport management considering technical, economic, end environmental factors. Therefore, conditions affecting decision-making in the field of production planning by MFMCs and accompanying transports within the agglomeration area with the use of the production-service platform were presented. Assumptions were created for the decision model, allowing for the selection of partners within the MFMC to execute the production order. A simplified decision model using the Hungarian algorithm was proposed, which was verified with the use of test data. The model is universal for material flow analysis and is an assessments basis for smart sustainable supply chain decision-making and planning. Despite the narrowing of the scope of the analysis and the simplifications applied, the presented model using the Hungarian algorithm demonstrated its potential to solve the problem of partner selection for the execution of the contract by MFMC.

DEVELOPING OF SUSTAINABLE SUPPLY CHAIN MANAGEMENT INDICATORS IN CONSTRUCTION

Most of the existing supply chain management methods and systems are being transferred to construction sphere regardless of the specifics of companies in the construction sector. Numerous complex factors such as ecological, social and economic are required for the continuous evaluation in the modern management of construction sector. The provided studies and the research to examine sustainable supply chain management in construction sector from a holistic perspective, concentrating on mostly longterm sustainable decision­making by the construction company rather than being centered only on the supply chain management for construction projects. This paper identifies a list of sustainability indicators for examining the supply chains of construction companies. Those indicators were categorized and assigned to one or a couple groups by reviewing their use in the previous literature agreeing to the reasoning to way better reflect the SSCM principle of their use in construction companies. The use of indicators can help develop strategies for the construction sector for sustainable policy makers and construction company managers.

Coordination mechanisms for digital and sustainable textile supply chain

PurposeSupply chain network is complicated to manage due to the involvement of a number of agents. Formation of virtual organization using Industry 4.0 (I4.0) is an approach to improve the efficiency and effectiveness and to overcome the complexities of the channel. However, the task of managing the channel further becomes complicated after incorporating sustainability into the supply chain. To fill this gap, this paper focuses on designing of mechanism and demonstration of I4.0-based virtual organization to coordinate sustainable supply chain.Design/methodology/approachIn this paper, we model and compare I4.0-based virtual organization models using four other traditional contracts with centralized supply chain. The non-cooperative game theoretic approach has been used for the analysis of models.FindingsOur game-theoretic analysis shows that investment in I4.0 and sustainable innovation are beneficial for the overall supply chain. Our results show that linear two-part tariff contract and I4.0-based virtual organization model can perfectly coordinated with the supply chain.Research limitations/implicationsThis study consider deterministic model settings with full information game. Therefore researchers are encouraged to study I4.0-based coordination models under information asymmetry and uncertain situations.Practical implicationsThe paper includes implications for the development of I4.0-based coordination model to tackle the problems of channel coordination.Originality/valueThis study proposes I4.0-based game-theoretic model for the sustainable supply chain coordination.

A Pythagorean fuzzy ANP-QFD-Grey relational analysis approach to prioritize design requirements of sustainable supply chain

A sustainable supply chain (SSC) is vital for company’s sustainability success, so it is imperative to identify and prioritize SSC’s design requirements (DRs) for better SSC planning. For customer-centric markets, the customer requirements (CRs) need to be integrated into SSC’s DRs. This paper thus proposes a customer-centric approach based on Analytic Network Process (ANP), Quality Function Deployment (QFD), Grey Relational Analysis (GRA), and Pythagorean Fuzzy Set (PFS) to rank SSC’s DRs, considering CRs and information ambiguity. The PFS is combined with ANP, QFD, and GRA to better handle uncertainty in the SSC. The Pythagorean fuzzy ANP is applied to analyze the correlations among the sustainable CRs and determine the corresponding weights. The sustainable CRs are transformed into the DRs using the Pythagorean fuzzy QFD. The relationships among the resulting DRs are analyzed through Pythagorean fuzzy GRA to prioritize DRs. The approach is validated through a case study. The results obtained in this paper shows that the proposed method is efficient to prioritize DRs of SSC with the consideration of sustainable CRs under uncertain environment. The novelties of proposed method are that it not only offers a customer-oriented SSC planning method through the integration of ANP, QFD and GRA, but also can reflect the uncertain information with a broader membership representation space via PFSs. Based on the proposed method, the decision-maker can conduct comprehensive analysis to prioritize DRs and design appropriate SSC to fulfill CRs under uncertain environment.

COVID-19 and Its Implications to the Assessment of Sustainable Palm Oil Supply Chain Management: An Indonesian Perspective

Motivated by the low sustainability index and pressure to meet the global demand for eco-friendly crude palm oil (CPO) in the pandemic-ridden environment, this research aims to investigate the implications of the COVID-19 pandemic to assess the drivers of sustainable supply chain management (SSCM) of the Indonesian CPO sector to tackle supply chain disruptions. To achieve this aim, the study seeks to determine the sustainability drivers to accommodate the pandemic-ridden environment and if sustainability indicators can help improve the supply chain management of the CPO sector. A methodology is divided into two interrelated parts: first, based on a careful review of extant literature of the CPO sector and sustainable supply chain in the light of pandemic. The proposed methodology is then tested using the response data of 108 oil mills' representatives collected through survey questionnaires and analyzed using statistical tools of reliability, distribution, Kaiser–Meyer–Olkin (KMO), Confirmatory Factor Analysis (CFA), and diagnostic tests of CFA. The findings designate the environmental costs, rapidity, and adaptability as core economic indicators; the social and workforce development, health, and safety workforce development and consumer issues as crucial social indicators; while energy and material efficiency, management of waste and emissions, and sustainable suppliers as the best environmental indicators. This study provides a holistic platform on the implications of the pandemic to assess the SSCM of the CPO sector. These findings are expected to aid the industrial managers in employee skills and health protocols, customer service, and environmental management. The study is also anticipated to guide the supply-chain partners and government policymakers to take initiatives on SSCM in the context of the pandemic.