Social issues in sustainable supply chain networks: state of the art and further research directions

The study of supply networks sustainability is a field with a long path behind. Nonetheless, most studies to date are focused on the environmental sub dimension of sustainability, while the social perspective in supply chain networks research still shows a potential for pioneering contri butions. Moreover, from the development standpoint we have observed a paradigm shift advancing from a narrow concept of development, centered on purely economic dimensions, towards more refined issues such as inclusive business, shared value or poverty footprint, all of which are highly related to supply chain activities. In this paper we present a review of the current state of the art on social sustainability of supply chains and we identify the main existing trends in this field. After conducting this study, we can state that a new sphere of knowledge is emerging at the interface between sustainable supply chain networks and development research. The academic community is called to play an important dovetailing role in this scenario by advancing both conceptual and methodological contributions.

Supply Chain da informação legislativa no Senado Federal

Inclui organograma de gestão da cadeia (gerenciamento) do suprimento da informação legislativa no Senado Federal

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.

The journal of gas lighting, water supply & sanitary improvement.

Mode of access: Internet.

Outsourcing and inter-intra supply chain dynamics: Strategic management issues

This article analyzes the outsourcing of information technology services, using an action inquiry methodology. Research spanned the disengagement and beginning of IT service functions transferred from work groups in the parent company to outsource teams. Results identified the importance of addressing strategic issues and inter/intra relationships between parent company team members and their outsource-counterparts. Conclusions indicate that behavioral issues such as psychological contracts within inter/intra work groups, power and trust are highly significant managerial issues in the success or failure of an outsourcing strategy.

The Function and Consequences of Alternative Fresh Produce Supply Chain Models

Around the world, consumers and retailers of fresh produce are becoming more and more discerning about factors such as food safety and traceability, health, convenience and the sustainability of production systems, and in doing so they are changing the way in which fresh produce supply chains are configured and managed. When consumers demand fresh, safe, convenient, value-for-money produce, retailers in an increasingly competitive environment are attracted to those business models most capable of meeting these demands profitably. Traditional models are proving less and less able to deliver competitive advantage in such an environment. As a result, opportunistic, adversarial, price-based approaches to doing business between chain members are being replaced by approaches that are more strategic, collaborative and value-based. The shaping force behind this change is the need for producers, wholesalers, category managers, retailers and consumers to have more certainty about the performance of the supply chains upon which they rely. Certainty is generated through the supply chain's ability to create, deliver and share value. How to build supply chains that create, deliver and share value is arguably the single biggest challenge to the competitiveness of fresh produce firms, and therefore to the industries to which they belong.

The impact of supply chain performance measurement systems on dynamic behaviour in supply chains

The amplification of demand variation up a supply chain widely termed ‘the Bullwhip Effect’ is disruptive, costly and something that supply chain management generally seeks to minimise. Originally attributed to poor system design; deficiencies in policies, organisation structure and delays in material and information flow all lead to sub-optimal reorder point calculation. It has since been attributed to exogenous random factors such as: uncertainties in demand, supply and distribution lead time but these causes are not exclusive as academic and operational studies since have shown that orders and/or inventories can exhibit significant variability even if customer demand and lead time are deterministic. This increase in the range of possible causes of dynamic behaviour indicates that our understanding of the phenomenon is far from complete. One possible, yet previously unexplored, factor that may influence dynamic behaviour in supply chains is the application and operation of supply chain performance measures. Organisations monitoring and responding to their adopted key performance metrics will make operational changes and this action may influence the level of dynamics within the supply chain, possibly degrading the performance of the very system they were intended to measure. In order to explore this a plausible abstraction of the operational responses to the Supply Chain Council’s SCOR® (Supply Chain Operations Reference) model was incorporated into a classic Beer Game distribution representation, using the dynamic discrete event simulation software Simul8. During the simulation the five SCOR Supply Chain Performance Attributes: Reliability, Responsiveness, Flexibility, Cost and Utilisation were continuously monitored and compared to established targets. Operational adjustments to the; reorder point, transportation modes and production capacity (where appropriate) for three independent supply chain roles were made and the degree of dynamic behaviour in the Supply Chain measured, using the ratio of the standard deviation of upstream demand relative to the standard deviation of the downstream demand. Factors employed to build the detailed model include: variable retail demand, order transmission, transportation delays, production delays, capacity constraints demand multipliers and demand averaging periods. Five dimensions of supply chain performance were monitored independently in three autonomous supply chain roles and operational settings adjusted accordingly. Uniqueness of this research stems from the application of the five SCOR performance attributes with modelled operational responses in a dynamic discrete event simulation model. This project makes its primary contribution to knowledge by measuring the impact, on supply chain dynamics, of applying a representative performance measurement system.