A Capability Maturity Model to Assess Supply Chain Performance

In an overcapacity world, where the customers can choose from many similar products to satisfy their needs, enterprises are looking for new approaches and tools that can help them not only to maintain, but also to increase their competitive edge. Innovation, flexibility, quality, and service excellence are required to, at the very least, survive the on-going transition that industry is experiencing from mass production to mass customization. In order to help these enterprises, this research develops a Supply Chain Capability Maturity Model named S(CM)2. The Supply Chain Capability Maturity Model is intended to model, analyze, and improve the supply chain management operations of an enterprise. The Supply Chain Capability Maturity Model provides a clear roadmap for enterprise improvement, covering multiple views and abstraction levels of the supply chain, and provides tools to aid the firm in making improvements. The principal research tool applied is the Delphi method, which systematically gathered the knowledge and experience of eighty eight experts in Mexico. The model is validated using a case study and interviews with experts in supply chain management. The resulting contribution is a holistic model of the supply chain integrating multiple perspectives, and providing a systematic procedure for the improvement of a company’s supply chain operations.

Ellátási lánc kapcsolatok modellezése = Modeling of supply chain relationships

A dolgozatban az ellátási láncokban meglévő diadikus kapcsolatok minőségét állítjuk a vizsgálatok középpontjába. Az irodalomban számtalan megközelítés ismert az ellátási lánc kapcsolatok fejlődésének leírására. Ezen fejlődési elméletek inkább elméleti szinten írják le a diadikus kapcsolatok változását, annak empirikus tesztelhetőségét nem vizsgálják. Dolgozatunkban kísérletet teszünk az ellátási lánc kapcsolatok fejlődésének empirikus vizsgálatára. Arra próbálunk választ találni, hogy az életciklus hipotézis az üzleti kapcsolatok időbeli fejlődésére alkalmazható-e. = Our paper combines two approaches using data of an internet based questionnaire and applying quantitative analysis it tests the hypothesis business relationship development in time can be described with the concept of life cycle. The concept of life cycle is widely used in business research. Among others the diffusion of innovation is described using this concept, or the concept of product life cycle just to name a few. All of these researches analyze the life cycle along a specific variable (for example the volume of sales or revenue in case of the product life cycle) which (except the last stage of the cycle, the decline) has a cumulative character resulting in the widely known specific shape of a life cycle. Consequently testing a life cycle hypothesis inevitably means the acceptance of some type cumulativity in the development.

Influence of Lean and Green on supply chain performance: an interpretive structural modelling model

This work aims to identify and rank a set of Lean and Green practices and supply chain performance measures on which managers should focus to achieve competitiveness and improve the performance of automotive supply chains. The identification of the contextual relationships among the suggested practices and measures, was performed through literature review. Their ranking was done by interviews with professionals from the automotive industry and academics with wide knowledge on the subject. The methodology of interpretive structural modelling (ISM) is a useful methodology to identify inter relationships among Lean and Green practices and supply chain performance measures and to support the evaluation of automotive supply chain performance. Using the ISM methodology, the variables under study were clustered according to their driving power and dependence power. The ISM methodology was proposed to be used in this work. The model intends to provide a better understanding of the variables that have more influence (driving variables), the others and those which are most influenced (dependent variables) by others. The information provided by this model is strategic for managers who can use it to identify which variables they should focus on in order to have competitive supply chains.

BIOMASS SUPPLY CHAIN ANALYSIS WITH DENSIFIED WASTE

ABSTRACT The possibility to vary the energy matrix, thus reducing the dependency on fossil fuels, has amplified the acceptance of biomass as an alternative fuel. Despite being a cheap and renewable option and the fact that Brazil is a major producer of waste from agriculture and forestry activities, the use of these materials has barriers due to its low density and low energetic efficiency, which can raise the costs of its utilization. Biomass densification has drawn attention due to its advantage in comparison to in natura biomass due to its better physical and combustion characteristics. The objective of this paper is to evaluate the impact of biomass densification in distribution and transport costs. To reach this objective, a mathematical model was used to represent decisions at a supply chain that coordinates the purchase and sale of forestry and wood waste. The model can evaluate the options to deliver biomass through the supply chain combining demand meeting and low cost. Results point to the possibility of an economy of 60% in transport cost and a reduction of 63% in the required quantity of trucks when densified waste is used. However, costs related to the densifying process lead to an increase of total supply costs of at least 37,8% in comparison to in natura waste. Summing up, the viability of biomass briquettes industry requires a cheaper densification process.

Measuring supply chain management practices

Purpose: This paper aims to perform an empirical investigation about the constructs and indicators of the supply chain management practices framework. Design/methodology/approach: The measuring framework proposed is based on a survey that was carried out on 107 Brazilian companies. Statistical techniques were employed to verify, validate, and test the reliability of the constructs and their indicators. To validate this framework principal component analysis and structural equation modeling techniques were used. Findings: In general, previous studies suggest six constructs for measuring the supply chain management practices framework. However, in this study a framework was achieved with four constructs of supply chain management practices, namely, supply chain (SC) integration for production planning and control (PPC) support, information sharing about products and targeting strategies, strategic relationship with customer and supplier, and support customer order. This framework has adequate levels of validity and reliability. Research limitations/implications: The main limitation of this study was that only a small sample of companies in a single sector and country were surveyed, and therefore there needs to be further research considering the special conditions in other countries. Originality/value: This study investigated statistically set indicators to discuss the topic supply chain management practices. The framework obtained has good quality of validity and reliability indicators. Thus, an alternative framework has been added to measure supply chain management practices, which is currently a popular topic in the supply chain mainstream literature. Both defined constructs and the validated indicators can be used in other studies on supply chain management. © Emerald Group Publishing Limited.

Mixed methodology to analyze the relationship between maturity of environmental management and the adoption of green supply chain management in Brazil

The aim of this research is to verify the relationship between the maturity levels of environmental management and the adoption of green supply chain management (GSCM) practices by electro-electronic companies in Brazil. In this work a two-phase research was conducted, with one quantitative and the other qualitative. The quantitative phase aimed to test whether a relationship between the maturity levels of environmental management and GSCM exists, while the qualitative phase tried to detail the characteristics of this relationship. The quantitative phase was conducted through a survey with 100 Brazilian electro-electronic companies and the collected data were processed using Structural Equation Modeling. For the qualitative phase, a multiple case study was conducted with three companies located in Brazil. The results indicate that: (1) The main hypothesis was confirmed and considered statistically valid, indicating that, indeed, the maturity level of environmental management influences the adoption of GSCM practices; (2) a coevolution tends to occur between the environmental maturity and the GSCM practices; that is, the more developed is the company's environmental management, more complex GSCM practices are adopted; and (3) the GSCM internal practices tend to present a greater relative adoption than the external practices; these external practices of GSCM tend to be adopted when the company is inserted in a higher environmental stage and/or operates under a scenario of stronger normative environmental pressure. By the way, this is the first research mixing survey and case studies on GSCM in Brazil. (C) 2014 Elsevier B.V. All rights reserved.

Evidências da relação entre evolução da gestão ambiental e a adoção de práticas de Green Supply Chain Management no setor eletroeletrônico brasileiro

The objective of this research is to examine if the environmental management evolution is positively related towards the adoption of green supply chain management practices (GSCM) by companies in the electronics sector in Brazil. To reach this objective, a quantitative research was conducted by survey with 100 companies in the electronics sector in Brazil. The collected data were processed using descriptive statistics, Exploratory Factor Analysis and Structural Equation Modeling. The most important results are: in the sample, GSCM practices to the recovery of investment, as the resale of scrap and other waste materials, and the adequacy with legislation and auditing, obtained high scores; and research hypothesis (H1) was confirmed and considered statistically valid, indicating that, in fact, the evolution of environmental management influences the adoption of GSCM practices.

Development of an optimization model for biofuel facility size and location and a simulation model for design of a biofuel supply chain

To mitigate greenhouse gas (GHG) emissions and reduce U.S. dependence on imported oil, the United States (U.S.) is pursuing several options to create biofuels from renewable woody biomass (hereafter referred to as “biomass”). Because of the distributed nature of biomass feedstock, the cost and complexity of biomass recovery operations has significant challenges that hinder increased biomass utilization for energy production. To facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization and tapping unused forest residues, it is proposed to develop biofuel supply chain models based on optimization and simulation approaches. The biofuel supply chain is structured around four components: biofuel facility locations and sizes, biomass harvesting/forwarding, transportation, and storage. A Geographic Information System (GIS) based approach is proposed as a first step for selecting potential facility locations for biofuel production from forest biomass based on a set of evaluation criteria, such as accessibility to biomass, railway/road transportation network, water body and workforce. The development of optimization and simulation models is also proposed. The results of the models will be used to determine (1) the number, location, and size of the biofuel facilities, and (2) the amounts of biomass to be transported between the harvesting areas and the biofuel facilities over a 20-year timeframe. The multi-criteria objective is to minimize the weighted sum of the delivered feedstock cost, energy consumption, and GHG emissions simultaneously. Finally, a series of sensitivity analyses will be conducted to identify the sensitivity of the decisions, such as the optimal site selected for the biofuel facility, to changes in influential parameters, such as biomass availability and transportation fuel price. Intellectual Merit The proposed research will facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization in the renewable biofuel industry. The GIS-based facility location analysis considers a series of factors which have not been considered simultaneously in previous research. Location analysis is critical to the financial success of producing biofuel. The modeling of woody biomass supply chains using both optimization and simulation, combing with the GIS-based approach as a precursor, have not been done to date. The optimization and simulation models can help to ensure the economic and environmental viability and sustainability of the entire biofuel supply chain at both the strategic design level and the operational planning level. Broader Impacts The proposed models for biorefineries can be applied to other types of manufacturing or processing operations using biomass. This is because the biomass feedstock supply chain is similar, if not the same, for biorefineries, biomass fired or co-fired power plants, or torrefaction/pelletization operations. Additionally, the research results of this research will continue to be disseminated internationally through publications in journals, such as Biomass and Bioenergy, and Renewable Energy, and presentations at conferences, such as the 2011 Industrial Engineering Research Conference. For example, part of the research work related to biofuel facility identification has been published: Zhang, Johnson and Sutherland [2011] (see Appendix A). There will also be opportunities for the Michigan Tech campus community to learn about the research through the Sustainable Future Institute.

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR BIOFUEL FACILITY SIZE AND LOCATION AND A SIMULATION MODEL FOR DESIGN OF A BIOFUEL SUPPLY CHAIN

A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.

Reconfiguration of supply chain network:an ISM-based roadmap to performance

Purpose: Short product life cycle and/or mass customization necessitate reconfiguration of operational enablers of supply chain (SC) from time to time in order to harness high levels of performance. The purpose of this paper is to identify the key operational enablers under stochastic environment on which practitioner should focus while reconfiguring a SC network. Design/methodology/approach: The paper used interpretive structural modeling (ISM) approach that presents a hierarchy-based model and the mutual relationships among the enablers. The contextual relationship needed for developing structural self-interaction matrix (SSIM) among various enablers is realized by conducting experiments through simulation of a hypothetical SC network. Findings: The research identifies various operational enablers having a high driving power towards assumed performance measures. In this regard, these enablers require maximum attention and of strategic importance while reconfiguring SC. Practical implications: ISM provides a useful tool to the SC managers to strategically adopt and focus on the key enablers which have comparatively greater potential in enhancing the SC performance under given operational settings. Originality/value: The present research realizes the importance of SC flexibility under the premise of reconfiguration of the operational units in order to harness high value of SC performance. Given the resulting digraph through ISM, the decision maker can focus the key enablers for effective reconfiguration. The study is one of the first efforts that develop contextual relations among operational enablers for SSIM matrix through integration of discrete event simulation to ISM. © Emerald Group Publishing Limited.

Advances in decision support systems on the endeavour for supply chain optimality

Industry practitioners are seeking to create optimal logistics networks through more efficient decision-making leading to a shift of power from a centralized position to a more decentralized approach. This has led to researchers, exploring with vigor, the application of agent based modeling (ABM) in supply chains and more recently, its impact on decision-making. This paper investigates reasons for the shift to decentralized decision-making and the impact on supply chains. Effective decentralization of decision-making with ABM and hybrid modeling is investigated, observing the methods and potential of achieving optimality.