Pressure analysis for green supply chain management implementation in Indian industries using analytic hierarchy process

Due to growing awareness about environment protection, firms are forced to implement environmental practices to enhance their green image. In recent times, academicians and practitioners have shown interest in green marketing and green supply chain management (GSCM). Fields of green branding and sustainability have seen special interest from different business disciplines including information management, marketing, supply chain management, etc. Due to economical and ecological impact, there is a growing concern for the environment and related critical issues. Pressure on the environment is dynamic and diverse, and demands new levels of accountability, financial commitment and supply chain capabilities. Indian manufacturing industries have started adopting green concepts in their supply chain management giving special attention to environmental issues based on pressures from different directions, e.g. customer pressure, government regulations etc. Yet, industries struggle hard to identify essential pressures for implementation of GSCM. This work focuses mainly on identifying such pressures for implementation of GSCM. Initially 65 pressures were identified through detailed literature and categorised into six groups. Then common acceptable pressures were identified through a questionnaire survey from different industrial sectors in Phase 1. Finally, essential pressures are prioritised with the help of analytic hierarchy process in Phase 2.     

Leagile supply chain: design drivers and business performance implications

In the context of a dynamic and hypercompetitive business environment, effective supply chain design helps organisations to align resources for improved flow of products and services and satisfy customers’ diverse needs. Scholars have proposed several mutually exclusive supply chain designs such as efficient versus responsive, and lean versus agile. Quantitative testing has revealed that supply chain designs of many firms do not match with what was conceptually expected. To address this mismatch, in this study, a new approach to supply chain leagility is introduced and the impact of uncertainty as the key design driver of supply chains on leagility is investigated. The partial least squares (PLS) was employed to analyse data collected from 299 Australian firms by administering a structured questionnaire. Results indicate that higher performance is achievable on minimising the deviation from a balanced supply chain in which aspects of both leanness and agility are equally embedded. Further, the level of uncertainty directly and positively affects the Deviation from Leagility (DFL) index.     

A hybrid multi-stage predictive model for supply chain network collapse recovery analysis: a practical framework for effective supply chain network continuity management

In this paper, we present a multi-stage hybrid model for analysing a supply chain network (SCN) collapse recovery possibility. In the first stage of the model, we analyse the ability of an SCN to fulfil its customers required due date (RDD). As soon as the SCN defaults to timely fulfil their customers RDD, the second stage of the model is triggered to measure the collapse recovery possibility (CRP) of the SCN. Then, we calculate the final collapse recovery possibility (FCRP) of the SCN. Since the operation times, customer demand and external supply of raw material are uncertain, we use fuzzy triangular numbers to estimate the value of foregoing parameters. Consequently, we employ fuzzy program evaluation and review technique (FPERT) to calculate the completion time of SCN operations. In the third stage, for the critical elements of the SCN obtained from FPERT, the SC simulator is developed to provide a dynamic view of the SC and assesses the impact of decisions recommended by the SC fuzzy models on SC performance. Moreover, an empirical example is presented to validate the effectiveness of the proposed model. Finally, we conduct sensitivity analysis on the parameters employed in the model to analyse the behaviour of each parameter.     

Review of supply chain configuration and design decision-making for new product

The nature of competitive markets continuously pushes manufacturers to develop new products to meet the increasingly diversified customer demands. Manufacturers thus have to handle the complexities generated during the total life cycles of various product types, from product design to procurement, production, marketing and recycling. Though some management practices in mass customisation help to improve the performance of manufacturing systems, there are still some fundamental problems not covered. Joint decision-making of product and supply chain design, for example, is one of them. The existing industrial practice tends to treat these two problems separately. Decoupling these two problems decrease the design complexity but may lead to suboptimal decision outcome. To enhance understanding of the interconnected decisions for supply chain management and product design, this review collects related literature on this topic and focuses on the analysis of existing papers from an operation research perspective.     

A green supply chain is a requirement for profitability

Many companies are not dramatically changing to more sustainable environmental practices despite pressure from the investment community, the government and consumers. This study explores a simple model that companies can use to understand and improve supply chain sustainability practices. It applies this model in two case studies, Coca-Cola, a leader in global sustainability, and Apple, a company that has only recently started to develop a sustainability strategy. The model was developed through a review of existing research and an application of supply chain principles. The results of this study demonstrate that following this model to eliminate waste throughout the supply chain will make the supply chain more profitable. The outcomes from this study highlight the importance for every company to do so in order to stay competitive. This study is unique in the relative simplicity of its model, combined with the supporting evidence that a sustainable supply chain is the same as a supply chain that is using best practices to reduce waste.     

A multi-agent system for chemical supply chain simulation and management support

Modern chemical production is customer-driven and the desired delivery time for the products is often shorter than their campaign length. In addition, the raw materials supplying time is often long. These features make it desirable to provide tools to support collaborative supply chain decision making, preferably over the Internet, and where there are conflicts, compromise decisions can be quickly reached and the effects of the decisions can be quantitatively simulated. This paper des cribes such a multi-agent system (MAS) that can be used to simulate the dynamic behaviour and support the management of chemical supply chains over the Internet. Geographically distributed retailers, logistics, warehouses, plants and raw material suppliers are modelled as an open and re-configurable network of co-operative agents, each performing one or more supply chain functions. Communication between agents is made through the common agent communication language KQML (knowledge query message language). A t the simulation layer, the MAS allows distributed simulation of the chain behaviour dynamically, so that compromise decisions can be rapidly and quantitatively evaluated. Because in a chemical supply chain the scheduling of the plant often dominates the chain performance, an optimum scheduling system for batch plants is integrated into the MAS. The functions of the system are illustrated by reference to a case study for the supply and manufacture using a multi-purpose batch plant of paints and coatings.     

A GIS-based green supply chain model for assessing the effects of carbon price uncertainty on plastic recycling

Recycling plastic can abate the environmental pollution as well as CO₂ emissions by saving the carbon-intensive feedstock input. The uncertain carbon price places significant effects on the establishment and operation of the whole supply chain. This study develops a green supply chain model combined with geographic information system (GIS) to account for carbon price uncertainty and evaluate its effects on the closed-loop supply chain (CLSC) of plastic recycling. A two-stage stochastic programming model is constructed, in which the stochastic variable, CO₂ price is modelled as a geometric Brownian motion process. Six scenarios are designed with respect to price expectation and volatility. A case study is performed with the GIS information of the plastic supply chain in Zhejiang province, China. The results illustrate that triggering the establishment of reverse logistics requires a carbon price threshold significantly beyond the current level. Lower price volatility would facilitate the decision-making of investment into the reverse logistics. Mechanisms to alleviate the market variation shall be introduced. A sound market condition is desired to obtain the optimal balance that encourages the CLSC without creating extra pressure on the firms. The proposed modelling framework can be easily applied to other sectors with similar characteristics.     

A three-stage model for closed-loop supply chain configuration under uncertainty

In this paper, a general closed-loop supply chain (CLSC) network is configured which consists of multiple customers, parts, products, suppliers, remanufacturing subcontractors, and refurbishing sites. We propose a three-stage model including evaluation, network configuration, and selection and order allocation. In the first stage, suppliers, remanufacturing subcontractors, and refurbishing sites are evaluated based on a new quality function deployment (QFD) model. The proposed QFD model determines the relationship between customer requirements, part requirements, and process requirements. In addition, the fuzzy sets theory is utilised to overcome the uncertainty in the decision-making process. In the second stage, the closed-loop supply chain network is configured by a stochastic mixed-integer nonlinear programming model. It is supposed that demand is an uncertain parameter. Finally in the third stage, suppliers, remanufacturing subcontractors, and refurbishing sites are selected and order allocation is determined. To this end, a multi-objective mixed-integer linear programming model is presented. An illustrative example is conducted to show the process. The main novel innovation of the proposed model is to consider the CLSC network configuration and selection process simultaneously, under uncertain demand and in an uncertain decision-making environment.     

A dynamic model for serial supply chain with periodic delivery policy

A three-echelon, dynamic lot-sizing model is presented for computing the parameters of a serial supply chain, which consists of integrated material replenishment, production at a capacity constraint, and outbound dispatching with a periodic delivery policy. The model is applicable in the general context of a three-echelon model with capacity constraint at the middle echelon of the serial supply chain which was not considered in most of the literature. This paper addresses a number of structural properties of the model and proposes a polynomial-time algorithm for deriving the optimal solution of minimising the total system costs over the planning horizon. Examples are provided to describe the algorithm.     

Green supply chain contracts with eco-labels issued by the sales platform: profitability and environmental implications

Considering environmentally conscious consumers, a manufacturer, and a sales platform which provides eco-labels for qualified manufacturers, this paper develops a supply chain model to study how eco-labels affect green supply chain operations, from the profitability and environmental perspectives. The results show that the sales platform prefers the agency contract, but the manufacturer prefers the wholesale price contract. Considering the performance of the supply chain, the agency contract brings a higher profit while the wholesale price contract results in a bigger environmental improvement. An unexpected but interesting result is that when the agency contract is used and consumer green awareness increases, the sale price declines rather than increasing as it does under the wholesale price contract. This decline happens because the required marketing effort of the sales platform will be lower, which incentivises the platform to reduce the commission rate. Consequently, the manufacturer faces a lower commission rate and a higher margin when consumers display greater green awareness. Moreover, as the core and more powerful player of the supply chain, the sales platform can propose a platform-led revenue sharing contract to fully coordinate the supply chain, which improves the performance of the supply chain both in profitability and environmental perspectives.     

A framework for designing supply chain disruptions management considering productive systems and carrier viewpoints

With the advent of the global and digital world, the number of geographically dispersed firms throughout the world has increased and the problem of Supply Chain (SC) disruption appeared as a main concern to many industries. In such context, designing disruptions management strategies for a robust SC has become a critical worldwide issue that is still under-explored. Since its design phase, this class of robust and global SC must integrate technologies and agents of production. However, the existing works only consider the Productive Systems (PSs) and the carrier viewpoint must also be considered since goods should be produced and distributed at the right quantity, at the right place and at the right time. In this complex task of designing disruptions management, a formal method must be used to integrate technologies ensuring the compliance of certain requirements, such as: developing collaborative and autonomous models, allowing reuse templates, considering analysis/simulation abilities and facilitating the interaction among engineering practitioners. Therefore, this paper presents a framework to model, analyse, control and monitor the robust and global SC, designing and integrating models with Petri Net, agent-based model techniques for disruptions management and considering both PSs and carrier viewpoints. A case study is investigated and the findings demonstrated the proposed solution supports decisions making for solving problems of design, analysis and control.     

A matrix-based Bayesian approach for manufacturing resource allocation planning in supply chain management

Nowadays, the supply chain of manufacturing resources is typically a large complex network, whose management requires network-based resource allocation planning. This paper presents a novel matrix-based Bayesian approach for recommending the optimal resource allocation plan that has the largest probability as the optimal selection within the context specified by the user. A proposed matrix-based representation of the resource allocation plan provides supply chain modelling with a good basis to understand problem complexity, support computer reasoning, facilitate resource re-allocation, and add quantitative information. The proposed Bayesian approach produces the optimal, robust manufacturing resource allocation plan by solving a multi-criteria decision-making problem that addresses not only the ontology-based static manufacturing resource capabilities, but also the statistical nature of the manufacturing supply chain, i.e. probabilities of resource execution and resource interaction execution. A genetic algorithm is employed to solve the multi-criteria decision-making problem efficiently. We use a case study from manufacturing domain to demonstrate the applicability of the proposed approach to optimal manufacturing resource allocation planning.     

供应链管理中对供方的评价与选择

供应链管理是企业价值链上的重要环节,对供方的选择评价是供应链管理中的一项重要内容。讨论了建立供方评价指标体系应遵循的原则,对供方的评价选择进行了分析,提出了选择评价供方时应注意的几个问题。     

An integrated approach for production and distribution planning in supply chain management

Many firms have been trying to optimize their production and distribution systems separately, but using this approach limits any possible increase in profit. Thus, it is becoming more important to analyse these two systems simultaneously. This paper presents the solutions for integrated production and distribution planning and investigates the effectiveness of their integration through a computational study, in a multi-plant, multi-retailer, multi-item, and multi-period logistic environment where the objective is to maximize the total net profit. Computational results on test problems using the proposed heuristic confirm the substantial advantage of the integrated planning approach over the decoupled one. Sensitivity analysis on the input parameters indicates that, under the right conditions, the effectiveness of integrating production and distribution functions can be extremely high.     

A simulation-optimisation approach for supply chain network design under supply and demand uncertainties

We investigate a three-echelon stochastic supply chain network design problem. The problem requires selecting suppliers, determining warehouses locations and sizing, as well as the material flows. The objective is to minimise the total expected cost. An important feature of the investigated problem is that both the supply and the demand are uncertain. We solve this problem using a simulation-optimisation approach that is based on a novel hedging strategy that aims at capturing the randomness of the uncertain parameters. To determine the optimal hedging parameters, the search process is guided by particle swarm optimisation procedure. We present the results of extensive computational experiments that were conducted on a large set of instances and that provide evidence that the proposed hedging strategy constitutes an effective viable solution approach.     

A strategic model for exact supply chain network design and its application to a global manufacturer

This paper presents a comprehensive model that captures significant strategic decisions involved in designing or redesigning high-performance supply chains from the perspective of the manufacturer. The problem considers deterministic demand by multiple clients, for multiple products, over the periods of a long-term horizon. The design decisions involve selection of suppliers, establishment or resizing of production facilities and distribution centres, possible subcontracting of related activities, and selection of transportation modes and routes. The problem is formulated by a Mixed Integer Linear Programming model. Its objective is to minimise the overall costs associated with procurement, production, inventory, warehousing, and transportation over the design horizon. Appropriate constraints model the complex relationships among the links of the supply chain. The proposed model has been applied to a large case study of a global manufacturing firm, providing valuable insights into the transformation of the firm’s current supply chain network, as well as into the potential of the proposed approach.     

A survey of semiconductor supply chain models Part II: demand planning,inventory management,and capacity planning

Part I of this three-part series described semiconductor supply chains from the decision-making and functional perspectives, using this as a framework to review the industrial engineering and operations research literature on the problems arising in these supply chains. Part I then reviewed the literature on Strategic Network Design, supply chain coordination, sustainability and simulation-based decision support. This paper, Part II, reviews the areas of Demand Planning, Inventory Management and Capacity Planning in semiconductor supply chains. Part III concludes the series by discussing models to support Master Planning, Production Planning and Demand Fulfilment in this industry.     

A pricing/ordering model for a dyadic supply chain with buyback guarantee financing and fairness concerns

The paper investigates pricing/ordering issues in a dyadic supply chain, in which a core supplier sells products through a budget-constrained retailer. The retailer faces stochastic demand and is fairness-concerned as well. If needed, the retailer can get financing support from bank by means of buyback guarantee financing (BGF) mode, which is often used in China. By introducing Nash bargaining solution as the fairness reference point, we formulate the retailer’s fairness-concerned utility function and develop a two-echelon pricing/ordering game model. We then study the combined impacts of fairness concerns and BGF on two members’ equilibrium strategies and supply chain performance. We also discuss the corresponding issues under no budget constraint, no financing service and bank financing. Our results show that: (1) two members’ equilibrium strategies are significantly influenced by the retailer’s fairness-concerned behaviour and initial budget; (2) as compared to no budget constraint, BGF can bring the whole supply chain more performance, which means that BGF can yield value-added; (3) When the retailer takes the risk of uncertain market solely, the retailer’s fairness concerns are beneficial for supply chain to improve the performance.     

A highly optimised tolerance-based approach for multi-stage,multi-product supply chain network design

In this paper we propose an algorithm called Highly Optimised Tolerance (HOT) for solving a multi-stage, multi-product supply chain network design problem. HOT is based on power law and control theory. The proposed approach takes its traits from the local incremental algorithm (LIA), which was initially employed to maximise the design parameter (i.e. yield), particularly in the percolation model. The LIA is somewhat analogous to the evolution by natural selection schema. The proposed methodology explores a wide search space and is computationally viable. The HOT algorithm tries to make the system more robust at each step of the optimisation. The objective of this paper is to reduce the total cost of supply chain distribution by selecting the optimum number of facilities in the network. To examine the effectiveness of the HOT algorithm we compare the results with those obtained by applying simulated annealing on a supply chain network design problem with different problem sizes and the same data sets.     

A mathematical model and solution methods for rail freight transportation planning in an Indian food grain supply chain

This paper addresses the rail transportation of food grains undertaken by Food Corporation of India (FCI) to meet the requirements of the food security programme called Public Distribution System (PDS). The research focuses on improving the allocation of railway rakes transporting food grains to a set of storage warehouses. A penalty factor based approach is adopted to represent the considerations in transportation planning and three penalty factors such as rake penalty factor, weekly penalty factor and capacity utilization penalty factor are introduced for the purpose. The single source - multiple destination problem is formulated and solved using exact method to minimize the sum of these three penalty factor values, termed total penalty. Further, a heuristic named optimum rake allocation algorithm is developed and tested using a set of 35 problem instances. The proposed heuristic is found to be highly efficient in terms of solution quality and computation time. A case study of FCI Kerala Region is also carried out to validate the formulated model and the proposed heuristic. The work provides valuable insights into the practical issues encountered in rail freight transportation planning and proposes an effective solution methodology to address them.