Understanding the genesis of green supply chain management: lessons from leading Brazilian companies

This work discusses the internal structuring processes of leading companies when adopting green supply chain management (GSCM) practices. A multiple case study approach was adopted as the research methodology, with four large Brazilian companies that are leaders in their market segments. The introduction of green products is a key step towards initiating concern for the environment among suppliers and customers. This study's results show the importance of having green teams, a dedicated functional area, and/or green jobs that support the discussion of environmental management among a business and beyond. The practical results of this study offer new insights into the behavior of companies that are adopting GSCM practices, thereby generating new evidence for the extension of GSCM theory. (C) 2014 Elsevier Ltd. All rights reserved.

Export Supply Chain Organization and Food Safety and Quality Standards: a case study of the Moroccan Fruit and Vegetable Sector

Agri-food supply chains extend beyond national boundaries, partially facilitated by a policy environment that encourages more liberal international trade. Rising concentration within the downstream sector has driven a shift towards “buyer-driven” global value chains (GVCs) extending internationally with global sourcing and the emergence of multinational key economic players that compete with increase emphasis on product quality attributes. Agri-food systems are thus increasingly governed by a range of inter-related public and private standards, both of which are becoming a priori mandatory, especially in supply chains for high-value and quality-differentiated agri-food products and tend to strongly affect upstream agricultural practices, firms’ internal organization and strategic behaviour and to shape the food chain organization. Notably, increasing attention has been given to the impact of SPS measures on agri-food trade and notably on developing countries’ export performance. Food and agricultural trade is the vital link in the mutual dependency of the global trade system and developing countries. Hence, developing countries derive a substantial portion of their income from food and agricultural trade. In Morocco, fruit and vegetable (especially fresh) are the primary agricultural export. Because of the labor intensity, this sector (especially citrus and tomato) is particularly important in terms of income and employment generation, especially for the female laborers hired in the farms and packing houses. Hence, the emergence of agricultural and agrifood product safety issues and the subsequent tightening of market requirements have challenged mutual gains due to the lack of technical and financial capacities of most developing countries.

Analysis of spring break-up and its effects on a biomass feedstock supply chain in northern Michigan

Demand for bio-fuels is expected to increase, due to rising prices of fossil fuels and concerns over greenhouse gas emissions and energy security. The overall cost of biomass energy generation is primarily related to biomass harvesting activity, transportation, and storage. With a commercial-scale cellulosic ethanol processing facility in Kinross Township of Chippewa County, Michigan about to be built, models including a simulation model and an optimization model have been developed to provide decision support for the facility. Both models track cost, emissions and energy consumption. While the optimization model provides guidance for a long-term strategic plan, the simulation model aims to present detailed output for specified operational scenarios over an annual period. Most importantly, the simulation model considers the uncertainty of spring break-up timing, i.e., seasonal road restrictions. Spring break-up timing is important because it will impact the feasibility of harvesting activity and the time duration of transportation restrictions, which significantly changes the availability of feedstock for the processing facility. This thesis focuses on the statistical model of spring break-up used in the simulation model. Spring break-up timing depends on various factors, including temperature, road conditions and soil type, as well as individual decision making processes at the county level. The spring break-up model, based on the historical spring break-up data from 27 counties over the period of 2002-2010, starts by specifying the probability distribution of a particular county’s spring break-up start day and end day, and then relates the spring break-up timing of the other counties in the harvesting zone to the first county. In order to estimate the dependence relationship between counties, regression analyses, including standard linear regression and reduced major axis regression, are conducted. Using realizations (scenarios) of spring break-up generated by the statistical spring breakup model, the simulation model is able to probabilistically evaluate different harvesting and transportation plans to help the bio-fuel facility select the most effective strategy. For early spring break-up, which usually indicates a longer than average break-up period, more log storage is required, total cost increases, and the probability of plant closure increases. The risk of plant closure may be partially offset through increased use of rail transportation, which is not subject to spring break-up restrictions. However, rail availability and rail yard storage may then become limiting factors in the supply chain. Rail use will impact total cost, energy consumption, system-wide CO2 emissions, and the reliability of providing feedstock to the bio-fuel processing facility.

SIZE OPTIMIZATION OF A BIOMASS TO LIQUID FUEL CONVERSION FACILITY WITHIN A BIOMASS SUPPLY CHAIN

Bioenergy and biobased products offer new opportunities for strengthening rural economies, enhancing environmental health, and providing a secure energy future. Realizing these benefits will require the development of many different biobased products and biobased production systems. The biomass feedstocks that will enable such development must be sustainable, widely available across many different regions, and compatible with industry requirements. The purpose of this research is to develop an economic model that will help decision makers identify the optimal size of a forest resource based biofuel production facility. The model must be applicable to decision makers anywhere, though the modeled case analysis will focus on a specific region; the Upper Peninsula (U.P.) of Michigan. This work will illustrate that several factors influence the optimal facility size. Further, this effort will reveal that the location of the facility does affect size. The results of the research show that an optimal facility size can be determined for a given location and are based on variables including forest biomass availability, transportation cost rate, and economy of scale factors. These variables acting alone and interacting together can influence the optimal size and the decision of where to locate the biofuel production facility. Further, adjustments to model variables like biomass resource and storage costs have no effect on facility size, but do affect the unit cost of the biofuel produced.

Integration of Truncated Distributions in Exponential Family with Simulation Models of Logistics and Supply Chain Management

Truncated distributions of the exponential family have great influence in the simulation models. This paper discusses the truncated Weibull distribution specifically. The truncation of the distribution is achieved by the Maximum Likelihood Estimation method or combined with the expectation and variance expressions. After the fitting of distribution, the goodness-of-fit tests (the Chi-Square test and the Kolmogorov-Smirnov test) are executed to rule out the rejected hypotheses. Finally the distributions are integrated in various simulation models, e. g. shipment consolidation model, to compare the influence of truncated and original versions of Weibull distribution on the model.

The supply chain in East Asia

East Asia is a major tea-consuming and -producing area; however, few studies have examined the East Asian tea industry from the perspective of the supply chain. Based on field and desktop studies of the tea markets in Taiwan and China, this paper provides an overview of each market together with detailed case studies. In this analysis, the characteristics of the tea industry and the main problems in the current supply chain in terms of governance, upgrading, and food safety and quality control are identified. This paper will help fill the gap in studies of the East Asian tea industry from the perspective of the supply chain.

Auto component supply chain: a path to global India

Supply chain management works to bring the supplier, the distributor, and the customer into one cohesive process. The Supply Chain Council defined supply chain as ‘Supply Chain: The flow and transformation of raw materials into products from suppliers through production and distribution facilities to the ultimate consumer., and then Sunil Chopra and Meindl, (2001) have define Supply chain management as ‘Supply Chain Management involves the flows between and among stages in a supply chain to maximize total profitability.’ After 1950, supply chain management got a boost with the production and manufacturing sector getting highest attention. The inventory became the responsibility of the marketing, accounting and production areas. Order processing was part of accounting and sales. Supply chain management became one of the most powerful engines of business transformation. It is the one area where operational efficiency can be gained. It reduces organizations costs and enhances customer service. With the liberalization of world trade, globalization, and emergence of the new markets, many organizations have customers and competitions throughout the world, either directly or indirectly. Business communities are aware that global competitiveness is the key to the success of a business. Competitiveness is ability to produce, distribute and provide products and services for the open market in competition with others. The supply chain, a critical link between supplier, producer and customer is emerged now as an essential business process and a strategic lever, potential value contributor a differentiator for the success of any business. Supply chain management is the management of all internal and external processes or functions to satisfy a customer’s order (from raw materials through conversion and manufacture through logistics delivery.). Goods-either in raw form or processed, whole sale or retailed distribution, business or technology services, in everyday life- in the business or household- directly or indirectly supply chain is ubiquitously associated in expanding socio-economic development. Supply chain growth competitive performance and supporting strong growth impulse at micro as well as micro economic levels. Keeping the India vision at the core of the objective, the role of supply chain is to take up social economic challenges, improve competitive advantages, develop strategies, built capabilities, enhance value propositions, adapt right technology, collaborate with stakeholders and deliver environmentally sustainable outcomes with minimum resources.

Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

Poster presented in the 24th European Symposium on Computer Aided Process Engineering (ESCAPE 24), Budapest, Hungary, June 15-18, 2014.

Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

In this work, we analyze the effect of incorporating life cycle inventory (LCI) uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear programming (MILP) coupled with a two-step transformation scenario generation algorithm with the unique feature of providing scenarios where the LCI random variables are correlated and each one of them has the desired lognormal marginal distribution. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study of a petrochemical supply chain. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact, and moreover the correlation among environmental burdens provides more realistic scenarios for the decision making process.

Modelling a biomass supply chain through discrete-event simulation

The organizational structure of the companies in the biomass energy sector, regarding the supply chain management services, can be greatly improved through the use of software decision support tools. These tools should be able to provide real-time alternative scenarios when deviations from the initial production plans are observed. To make this possible it is necessary to have representative production chain process models where several scenarios and solutions can be evaluated accurately. Due to its nature, this type of process is more adequately represented by means of event-based models. In particular, this work presents the modelling of a typical biomass production chain using the computing platform SIMEVENTS. Throughout the article details about the conceptual model, as well as simulation results, are provided

Forest-based supply chain modelling using the SimPy simulation framework

Proper management of supply chains is fundamental in the overall system performance of forestbased activities. Usually, efficient management techniques rely on a decision support software, which needs to be able to generate fast and effective outputs from the set of possibilities. In order to do this, it is necessary to provide accurate models representative of the dynamic interactions of systems. Due to forest-based supply chains’ nature, event-based models are more suited to describe their behaviours. This work proposes the modelling and simulation of a forestbased supply chain, in particular the biomass supply chain, through the SimPy framework. This Python based tool allows the modelling of discrete-event systems using operations such as events, processes and resources. The developed model was used to access the impact of changes in the daily working plan in three situations. First, as a control case, the deterministic behaviour was simulated. As a second approach, a machine delay was introduced and its implications in the plan accomplishment were analysed. Finally, to better address real operating conditions, stochastic behaviours of processing and driving times were simulated. The obtained results validate the SimPy simulation environment as a framework for modelling supply chains in general and for the biomass problem in particular.

IT support for managing aircraft spares in a closed-loop supply chain

This paper reports on the development of elements of an e-supply chain management system for managing maintenance, repair and overhaul (MRO) relationships in the aerospace industry. A standard systems development methodology has been followed to produce a process model (i.e. the AMSCR model); an information model (i.e. business rules) and a computerised information management capability (i.e. automated optimisation). The proof of concept for this web-based MRO supply chain system has been established through the collaboration with a sample of the different types of supply chain members. The proven benefit is a reduction in the stock-holding costs for the whole supply chain whilst also minimising non-flying time of the aircraft that the supply chain supports. This type of system is now vital in an industry that has continuously decreasing profit margins, which in turn means pressure to reduce servicing times and increase the interval between maintenance actions.

Optimization of facility location-allocation problem in customer-driven supply chain

This paper develops and applies an integrated multiple criteria decision making approach to optimize the facility location-allocation problem in the contemporary customer-driven supply chain. Unlike the traditional optimization techniques, the proposed approach, combining the analytic hierarchy process (AHP) and the goal programming (GP) model, considers both quantitative and qualitative factors, and also aims at maximizing the benefits of deliverer and customers. In the integrated approach, the AHP is used first to determine the relative importance weightings or priorities of alternative locations with respect to both deliverer oriented and customer oriented criteria. Then, the GP model, incorporating the constraints of system, resource, and AHP priority is formulated to select the best locations for setting up the warehouses without exceeding the limited available resources. In this paper, a real case study is used to demonstrate how the integrated approach can be applied to deal with the facility location-allocation problem, and it is proved that the integrated approach outperforms the traditional costbased approach.

Using min-sum loopy belief propagation for decentralised supply chain formation

Modern business trends such as agile manufacturing and virtual corporations require high levels of flexibility and responsiveness to consumer demand, and require the ability to quickly and efficiently select trading partners. Automated computational techniques for supply chain formation have the potential to provide significant advantages in terms of speed and efficiency over the traditional manual approach to partner selection. Automated supply chain formation is the process of determining the participants within a supply chain and the terms of the exchanges made between these participants. In this thesis we present an automated technique for supply chain formation based upon the min-sum loopy belief propagation algorithm (LBP). LBP is a decentralised and distributed message-passing algorithm which allows participants to share their beliefs about the optimal structure of the supply chain based upon their costs, capabilities and requirements. We propose a novel framework for the application of LBP to the existing state-of-the-art case of the decentralised supply chain formation problem, and extend this framework to allow for application to further novel and established problem cases. Specifically, the contributions made by this thesis are: • A novel framework to allow for the application of LBP to the decentralised supply chain formation scenario investigated using the current state-of-the-art approach. Our experimental analysis indicates that LBP is able to match or outperform this approach for the vast majority of problem instances tested. • A new solution goal for supply chain formation in which economically motivated producers aim to maximise their profits by intelligently altering their profit margins. We propose a rational pricing strategy that allows producers to earn significantly greater profits than a comparable LBP-based profitmaking approach. • An LBP-based framework which allows the algorithm to be used to solve supply chain formation problems in which goods are exchanged in multiple units, a first for a fully decentralised technique. As well as multiple-unit exchanges, we also model in this scenario realistic constraints such as factory capacities and input-to-output ratios. LBP continues to be able to match or outperform an extended version of the existing state-of-the-art approach in this scenario. • Introduction of a dynamic supply chain formation scenario in which participants are able to alter their properties or to enter or leave the process at any time. Our results suggest that LBP is able to deal easily with individual occurences of these alterations and that performance degrades gracefully when they occur in larger numbers.