Supply Chain Network Management Research Articles

Blockchain and Its Impacts on Agri-Food Supply Chain Network Management

Blockchain is an emerging meta-technology and considered a new institutional technology with the potential to change the governance of vertically integrated food supply chains. This paper investigates the effects on coordination mechanisms in vertically cooperating agri-food networks that result from the implementation of different blockchain technology platform types (BCTPT). The research is based on an extensive literature overview and exploratory use cases of BCTPT implementations in the agri-food industry which are presented to illustrate the applicability of the findings. Our analysis shows that BCTPT predominantly differentiate through the coordination mechanisms exerting of power, information sharing, decision-making, and collective learning benefits. We also reveal that blockchain use cases with high success rates typically operate in a vertical ecosystem where a focal firm assumes the responsibility for coordinating the activities in the supply chain network. These use cases are typically operationalized in tracking and tracing applications as well as in provenance-based information provision, which either operate in vertically coordinated private blockchain or consortium-type blockchain platforms. We conclude that the choice of a specific BCTPT with its respective coordination mechanisms is a key determinant of the economic success of the intended use case, the efficient management of the supply chain network, and eventually for the chosen digital business model. This paper will close a research gap, as the potential impacts of different blockchain technology platform types on digital agri-food business models and its supply chain management have scarcely been researched.

Design of Experiment with Variance Analysis (ANOVA) and Covariance Analysis (ANCOVA): Determination of Effective Factors Affecting the Lead Time in a Food Company

Küreselleşme ile rekabet koşullarının giderek ağırlaştığı günümüz şartlarında işletmelerin varlıklarına devam edebilmesi etkin tedarik zinciri faaliyetleri ile mümkündür. İyi yönetilen bir ağ mekanizmasında, sipariş edilen ürünün doğru yer ve doğru zamanda teslim edilmesinin yanı sıra kaliteli, sürdürülebilir ve paydaşlarla doğrudan ilişkili etkin bir tedarik zincir ağına ihtiyaç vardır. Bu çalışmada bir gıda işletmesinin tedarik zinciri ağ yönetiminde tedarik süresine etki eden faktörler belirlenerek, etkin faktörlerin tedarik süresi ile ilişkisi araştırılmıştır. Buna göre varyans analizi (ANOVA) ve kovaryans analizi (ANCOVA) ile entegre bir deney tasarımı gerçekleştirilmiş ve elde edilen sonuçlar karşılaştırılmıştır. Etkin faktör seviyeleri arasında farklılıkları görmek için Duncan ve Tukey testleri uygulanmıştır. Elde edilen sonuçlara göre işletmenin tedarik zinciri performansı iyileştirilerek taktiksel ve stratejik seviyede kararlar alınmasına yardımcı olunması amaçlanmıştır.

The thematic landscape of literature on supply chain management in India: a systematic literature review

PurposeTo assess the state of supply chain management (SCM) research in India and to understand the research trends and methodologies used. The present study also aims to create a taxonomy of the subject areas researched in India.Design/methodology/approachThe present study employed the systematic literature review methodology. Literature from 395 peer journal papers in 67 leading journals over a 20-year period (2000–2020 Quarter-1) was comprehensively reviewed and assessed.FindingsSCM research in India started around the year 2000. The quantum of research was low (single digit) until 2010. There has been steady growth over the last decade, and over 50% of the total papers up until now has been published in the last four years. The present study created a three-tiered taxonomy of the subject areas and classified the papers as per it. The first tier (level-1) has seven categories (SCM strategy, network design, SCM processes and integration, IT systems, skills, performance measurement and others). A perusal of the newly created taxonomy revealed that, except for a few areas under level-1 categories (such as SCM processes and SCM strategy), the other level-1 categories have not seen much research. Similarly, there is little or no research in a large number of level-2 categories (such as outsourcing strategy, channel strategy, demand management, demand fulfillment, customer relationship management, integrated supply chain planning, new product development, returns, supply chain orientation, performance monitoring, performance improvement, SCM adoption process, SCM implementation issues and quantified benefits of SCM). Methodologically, the rigor of SCM research in India needs improvement.Originality/valueA comprehensive taxonomy of SCM subject areas researched in India at three cascading levels was created for the first time in the present study. The taxonomy will help provide researchers with a clear understanding of the structure of the subject areas and help in identifying areas where research has been carried out and the subject areas where gaps exist for future research to proceed. The present study also provides an overview of the methodological rigor of SCM research in India and points out some of the limitations that researchers should avoid in future studies.

WEEE closed-loop supply chain network management considering the damage levels of returned products.

Due to economic, social, and environmental concerns, managing waste electrical and electronic equipment (WEEE) has become an important research area. The WEEE directive gives responsibility to producers for developing a system for recycling and disposal activities and handle all associated costs. This study proposes a mixed integer programming model for decision-makers to manage their activities on the WEEE closed-loop supply chain network. A decision-maker may be a single producer of any size or a managing body formed by a group of producers and/or third-party companies in the network. The model contributes to the research field by integrating product returns with different quality and damage levels. A set of scenarios was designed to evaluate the effects of the directive and the network design related issues (e.g., the minimum collection rates, the number of producers and stores in the network) on the objective function. The results indicate that the capacity balance among stores, producers, and recovery centers is vital to make the network profitable and sustainable.

RFID Implementation in Supply Chain Management

A network that is based on a traditional telecommunications network and the Internet is known as the internet of things (IoT). The devices in such networks connect peers and form advanced collaborations. radio frequency identification (RFID) has become a hot topic in recent years with the development of the IOT. However, the traditional RFID reader systems have some drawbacks, such as: single node failure, limited effective reading distance of the reader, and slow reading speeds. The proposed system describes how to estimate the location of an object using RFID technology. This article also incorporates a peer-to-peer (P2P) system to locate individual objects in a supply chain management network, which enables scalable indexing of objects in large distributed traceable networks.

Management and optimisation of chaotic supply chain system using adaptive sliding mode control algorithm

This paper deals with adaptive super-twisting (STW) sliding mode control (SMC) algorithm to manage chaotic supply chain system. A multi-echelon supply chain system having parametric perturbations and disturbances is presented to demonstrate chaotic nonlinear dynamical behaviours. When changing input variables slightly in the supply chain system, the predicted outputs will be completely different due to chaotic behaviours with bifurcation. In addition, various uncertainties along with exogenous disturbances make the system dynamics more complex to manage as they propagate both upstream and downstream of the supply chain networks. Particularly, the adaptive STW SMC algorithm has been designed for chaos suppression and synchronisation of the supply chain system. Next, the robust control algorithm with adaptive law for the closed-loop system has been proved by using Lyapunov stability theorem. Then, extensive numerical simulations are conducted to demonstrate the validity of the active control synthesis for optimal operations management of chaotic supply chain networks. The control algorithm based on system theory provides satisfactory performance on achieving chaos suppression and synchronisation of the chaotic supply system. The control system theory can be expanded into new integration software applications for operations management of supply chain networks. Finally, the presented control synthesis with dynamical analysis is essential for strategic decision-makers in the modern supply chain management.

Coordination and Profit Optimization by Producer-Distributor System of Agricultural Products in Bangladesh

This study, presents three different mathematical models: Producer, Distributor and Coordination modelwhich negotiate with a Producer-Distributor system for producing and distributing ofagricultural products in Bangladesh. In this paper, we investigated supply chain network (SCN) are two distinct freelance supply organizations. SCN management has the difficulties for the disconnected and freelance economic people. Further, fast technological changes and high fight build SCN a lot of complicated. The problem of locating distribution centers (DCs) is one among the foremost necessary problems in design of SCN. Current study, SCN was modeled using a formulation in mixed integer linear programming (MILP) problem, in which the facilities are coordinated by mutually sharing information with each other between producer and wholesaler. We think, this research presents a real life coordination optimization problem. The formulated MILP model is solved by using a mathematical programming language (AMPL) and results obtained by appropriate solver MINOS.

Incorporation of life cycle emissions and carbon price uncertainty into the supply chain network management of PVC production

Emissions trading schemes have been widely implemented by many countries to enforce the “cap and trade” concept for mitigating CO2 emissions. Thus, the carbon price influences the manufacturing costs in all stages of production, recycling, and disposal. Consideration of the carbon price is especially important for the economic efficiency of the downstream manufacturing sectors, such as in plastic product manufacturing, to substantially reduce their costs through the design and management of networked supply chains, which results in purchasing feedstocks from different technological routes, as well as choosing plants, warehouses and various transportation modes with diverse CO2 emission intensities. Supporting the decision-making in such situations requires the integration of life cycle analysis and networked supply chain management methodologies with an analysis of the carbon-market uncertainties. Such approaches have not been sufficiently quantified in the existing literature. This study presents a stochastic mixed-integer linear programming model developed for polyvinyl chloride pipe manufacturing in China, which is used to evaluate the effects of the life cycle emissions of procurement on the whole supply chain under carbon market uncertainty. Our results illustrate that the carbon market uncertainty would not only significantly influence the carbon-intensive production sectors but also the downstream manufacturing sectors. The five scenarios with carbon price variation exhibit distinctively different choices in procurement and supply chain configurations, as well as in their performances regarding total emissions and associated costs.

Fast artificial bee colony algorithm with complex network and naive bayes classifier for supply chain network management

In supply chain network (SCN) management, multi-objective Pareto optimization means the network can meet the demand for both minimal cost and minimal lead-time in SCN. Due to the compromise between cost and lead-time, it is a non-trivial issue to search for multi-objective Pareto optimal solutions (POS) in SCN. Furthermore, with the wide application of the internet, an increasing number of SCN applications have been based on the internet. As a result, the complexity of SCN increases exponentially with the number of suppliers increasing. It is really a big challenge to find the global multi-objective POS within a limited time in SCN management. In order to solve this problem, first, this paper proposes an artificial bee colony (ABC) optimization algorithm with two improvements: (1) a novel solution framework designed to extend the application field of the SCN based on complex network; (2) the acceleration of search speed by adopting naive Bayes classifier. Second, the paper provides a case example of optimizing a three-echelon SCN with the objective of minimizing both cost and lead-time. After the simulation with this example, it turns out that the enhanced ABC algorithm can satisfy the requirements of: (1) finding the global multi-objective POS; (2) improving the speed of finding optimal solutions in SCN management.

Robust Control of Supply Chain Networks with Multiple Lead Times and Demand Uncertainties

Abstract Multiple lead times, coupled with demand uncertainties, make the dynamic control and management of supply chain networks rather challenging. To this end, a difference equation-based state space model is developed and transformed for a supply chain network with multiple retailers and multiple manufacturers. A state-space augmentation technique is employed to transform the model, which facilitates the solution by existing robust control methods. The effectiveness of our method is verified numerically with a automobile case. The numerical results show that order and inventory fluctuations can be substantially mitigated.

Product Channeling in an O2O Supply Chain Management as Power Transmission in Electric Power Distribution Systems

With the aim of delivering goods and services to customers, optimal delivery channel selection is a significant part of supply chain management. Several heuristics have been developed to solve the variants of distribution center allocation and vehicle routing problems. In reality, small-scale suppliers cannot afford research and development departments to optimize their distribution networks. In this context, this research work develops a model for an online to offline (O2O) supply chain management network of a small-scale household electric components manufacturer for delivering goods to its distribution centers and retailers. Retailers are acquired by the company through investment in the O2O channel of e-commerce. Electric power transmission and distribution is considered as representative of the product distribution network. A model is developed using a combination of the supply chain management technique and power transmission terminologies. The constrained linear programming model is solved through the linear programming tool of the LINGO optimization software and the global optimum results for the proposed quantity allocation problem are achieved. A numerical experiment is provided to illustrate the practical applicability of the model and the optimal results are analyzed for model robustness.

Recent advances in hybrid priority-based genetic algorithms for logistics and SCM network design

Abstract Design and optimization of logistics and supply chain management (SCM) network is very important issue, which plans, implements and controls the efficient, effective forward and reverse flow and storage of goods, services and related information between the point of origin and the point of consumption to meet customers’ requirements. A multistage based logistics or SCM network can be modeled by means of a sequence of stages, each consisting of a set of functions, i.e. the existing or potential facilities located in several countries or regions of the world where goods are transformed or manufactured or stocked and delivered: suppliers, plants, distribution centers (DCs) and customers. The structure of each stage of the supply chain is completed by a set of arcs connected to the nodes and representing the flow of goods: each arc has a weight proportional to the cost incurred in between the two nodes it connects together. In this paper, we survey a recent advance on hybrid priority-based genetic algorithms for solving a multistage logistics or SCM network problems. In particular, the following multistage based logistics or SCM network models will be introduced: (1) the sugarcane SCM network model, (2) multiobjective supply chain network model, (3) flexible multistage logistics network model, and (4) multiobjective reverse logistics network model. In each model, we summarize the background, mathematical model, hybrid priority-based genetic algorithm and numerical experiment. We also enhance a hybrid genetic algorithm (HGA) by combining a local search (LS) technique and tuning GA parameters by a fuzzy logic control (FLC) to fast the search ability of GA. Finally, numerical experiment of each case study is carried out to show the effectiveness of the proposed approach by the hybrid priority-based genetic algorithms.

Performance analysis of supply chain on saroo model shoes products using SCOR model

The purpose of this study was to measure the performance of Supply Chain Management in a company engaged in the shoe industry. Shoe model which is used as object in this research is model of Sarro which is model of shoes which most in demand by consumer. The method of measuring the performance of Supply Chain Management used in this research is SCOR (Supply Chain Operation Reference) method which can integrate three main elements in management that is business process reengineering, benchmarking and measurement process. The result of this is to evaluate the performance of Supply Chain Management network on the company to three important components which become the main basis of assessment on SCOR method so that this will have implication to strategy that can be done by company in order to increase sales of shoes product so that can compete in market.

A Two-Phase Approach for Supply Chain Network Design: A Real-World Case Study from Automotive Industry

Effective design and management of Supply Chain Networks (SCN) support the production and delivery of products at low cost, high quality, high variety, and short lead times. In this study, a SCN is designed for an automotive company by integrating various approaches. The study has been carried out in two phases: The first phase involves selecting suppliers and distributors by using Data Envelopment Analysis (DEA) and integer-programming model. In the second phase, first the priority ranking of selected suppliers and distributors is determined using the Analytical Hierarchy Process (AHP) and then these priority rankings are integrated into the transportation models developed to identify the optimal routing decisions for all members of the supply chain.

Hybrid improved cuckoo search algorithm and genetic algorithm for solving Markov-modulated demand

One of the fundamental problems in supply chain management is to design the effective inventory control policies for models with stochastic demands because efficient inventory management can both maintain a high customers’ service level and reduce unnecessary over and under-stock expenses which are significant key factors of profit or loss of an organization. In this study, a new formulation of an inventory system is analyzed under discrete Markov-modulated demand. We employ simulation-based optimization that combines simulated annealing pattern search and ranking selection (SAPS&RS) methods to approximate near-optimal solutions of this problem. After determining the values of demand, we employ novel approach to achieve minimum cost of total SCM (Supply Chain Management) network. In our proposed approach, hybrid improved cuckoo search algorithm (ICS) and genetic algorithm (GA) are presented as main platform to solve this problem. The computational results demonstrate the effectiveness and applicability of the proposed approach.

Bi-objective design of fresh food supply chain networks with reusable and disposable packaging containers

Abstract Packaging is crucial in protecting and handling products through the stages of their logistic networks. Actually, both disposable and reusable packaging containers are used. The former ends its life at the last stage of the distribution chain, the latter requires reverse flows to collect, recondition and, then, reuse it. Costs and emissions associated to the two types of packaging containers are different in nature, i.e. raw materials and landfill cost and emissions vs. reverse logistic costs and emissions, so that their choice is not univocal. Furthermore, such choice heavily affects the supply chain network structure and management. This paper addresses this topic aiming at designing a supply chain network including the packaging container best selection, storage/handling node location and flow allocation. An original bi-objective mixed integer linear programming model supports the decisional process. Despite the approach is general, a deep focus is on fresh fruit and vegetable distribution chain because of disposable and reusable packaging containers coexist in practice. The model looks at the cost and environmental impact minimisation over the whole network getting the Pareto frontier and supporting the logistic managers, industrial practitioners and policy makers in the network design and management. A real instance from Emilia-Romagna region, Italy, showcases the model application getting the economic and environmental optima together with best-balance configurations. Results stress the convenience of mixing reusable and disposable packaging containers to reach a global optimum. 47.1% reusable and 52.9% disposable is a possible good balance configuration reducing emissions while containing the cost increase.

Managing military involvement in emergency preparedness in developed countries

Purpose The purpose of this paper is to analyse supply chain network management (SCNM) in the context of emergency preparedness management (EPM). The results of this study revealed that civil-military relations are essential for EPM to function as a coordinated approach to safety and security, and are necessary to respond effectively to complex emergencies and mitigating threats to developed countries. Civil-military relations are still a concern in the context of communication, the exercise of authority, and the coordination of emergency supplies (ES) to emergency operations. Design/methodology/approach This qualitative study is based on field observations, with attention focused on the EPM of Sweden, Finland, and Poland. The analysis of a broader SCNM through EPM was supported by semi-structured interviews among civil-military actors in Sweden, information collected from informal conversations known as “hanging out”, and secondary materials. Empirically, the analysis included a variety of civil-military relationships and identified implications for management, policy, and planning that are applicable to developed countries. Findings The management of civil-military relations is a meaningful resource when used as an overall approach for safety and security. The integration of civil-military relations in EPM in the planning of ES is a long-standing and complex matter. The management of Swedish civil-military relations in EPM is recognising that implications for management are imbedded in continuous policy changes in, for example, the Swedish policy history. Civil-military relational complications that arise in the field of operations are impossible to anticipate during emergency planning, as those complications are grounded in policy changes. Originality/value Escalating threats to developed countries are highlighted. The study underlines the primary measures used in studying military involvement in EPM. An understanding of SCNM as a choice for management can be obtained in future research that focuses on a broader role of the military in EPM. Sweden has emphasised a clearer role for the military by reactivating total defence planning and by evolving common practices and processes with civil actors in civil defence. Meanwhile, Poland and Finland are increasing their focus on supporting the management of civil-military policies on safety and security regarding communication, authority, and developing coordination. Consistent with findings from previous reports on SCNM, civil-military relations are essential for EPM. This study confirmed the importance of civil-military coordination, the management and practice of authority, and shared forms of communication.

Social Network Theory and Management of the Sub-supply Network in Complex Sectors

Studies on complex product development have seen different improvement approaches to achieve shorter product development lead times and higher return on investment. Complex product development still lack on the ‘better, faster and cheaper’ paradigm for efficient communication and information exchange flow process. This paper aims at understanding how the critical interdependent techniques are managed in the sub-supply network of a complex sector such as Business Aviation Industry. Thus, the aim is to envisage the best practice approach for technical communication networks among these systems-design teams and also how the bottlenecks existing could be effectively and efficiently addressed to enhance collaborative industrial supply-chain management network competitive advantage.This paper employing social network theory propose information flow process toward enhancing an industrial sustainable competitive advantage. From a methodological point of view, the research is based on a single case study, a questionnaire was used to collect data for the level of communication network from Business Aviation supply chain network.The outcome of the research highlights how communication in the sub-supply network significantly influences the attention the teams pay to the organization of the critical interdependent techniques. Moreover this research identifies an effective and efficient communication is sees as the driver for effective organization management, which need enhancement for industrial competitive advantage. Finally, the research carried-out undoubtedly gives a considerable contribution in understanding critical and complex issues in the relationships in sub-supplying in Business Aviation Industry.The outcome could be further developed by extending the interviews to the businesses involved in the sub-supply chain.

Automaker-supplier relationships and new product development in the truck industry: the case of Volvo do Brasil

Previous studies have focused on differences between western and Japanese approaches to supply chain network management techniques as regards NPD and relationship-specific ties. Based on in-depth interviews with senior managers at Volvo Trucks Brazil and two Spanish first tier suppliers, the aim of this research is to learn about the types of NPD collaboration ties used between Volvo and suppliers and to examine the supply chain network management techniques and routines used to intensify inter-firm collaboration and promote value-chain optimisation. One main finding of this research is that there is not one best buyer-supplier relationship style for NPD, but that relationships differ significantly depending on the degree to which the buyer relies on the capacity and technology possessed by each provider. Lower NPD frequency than in the car industry and the introduction of the Volvo production system in 2007 also make buyer-supplier relationships focused on NPD stronger in Volvo Trucks than in previously researched big car firms.

A robust bi-objective uncertain green supply chain network management

Conflicting objectives becomes a common issue in many supply chain network optimization problems. In this paper, a new model is formulated to design a green supply chain network through a new mixed integer linear programming problem. Uncertain demand and stochastic environmental respect levels are the main parameters of the formulation. The first objective function minimizes the cost of the supply chain while the second objective function minimizes CO2 emission. Conditional Value at Risk (CVaR) approach is adapted to deal with demand uncertainty and the stochastic CO2 emission level. Finally, the model outputs and its results discussion are illustrated through a numerical example.