Search results

Contemporary literature reveals that, to date, the poultry livestock sector has not received sufficient research attention. This particular industry suffers from unstructured supply chain practices, lack of awareness of the implications of the sustainability concept and failure to recycle poultry wastes. The current research thus attempts to develop an integrated supply chain model in the context of poultry industry in Bangladesh. The study considers both sustainability and supply chain issues in order to incorporate them in the poultry supply chain. By placing the forward and reverse supply chains in a single framework, existing problems can be resolved to gain economic, social and environmental benefits, which will be more sustainable than the present practices.

The theoretical underpinning of this research is ‘sustainability’ and the ‘supply chain processes’ in order to examine possible improvements in the poultry production process along with waste management. The research adopts the positivist paradigm and ‘design science’ methods with the support of system dynamics (SD) and the case study methods. Initially, a mental model is developed followed by the causal loop diagram based on in-depth interviews, focus group discussions and observation techniques. The causal model helps to understand the linkages between the associated variables for each issue. Finally, the causal loop diagram is transformed into a stock and flow (quantitative) model, which is a prerequisite for SD-based simulation modelling. A decision support system (DSS) is then developed to analyse the complex decision-making process along the supply chains.

The findings reveal that integration of the supply chain can bring economic, social and environmental sustainability along with a structured production process. It is also observed that the poultry industry can apply the model outcomes in the real-life practices with minor adjustments. This present research has both theoretical and practical implications. The proposed model’s unique characteristics in mitigating the existing problems are supported by the sustainability and supply chain theories. As for practical implications, the poultry industry in Bangladesh can follow the proposed supply chain structure (as par the research model) and test various policies via simulation prior to its application. Positive outcomes of the simulation study may provide enough confidence to implement the desired changes within the industry and their supply chain networks.

The purpose of this paper is to develop a conceptual framework of integrated supply chain model that can be used to measure, evaluate and monitor operational performance under dynamic and uncertain conditions.

The research methodology consists of two stages: configuration of a conceptual framework of integrated supply chain model linked with performance measures and illustration of the integrated supply chain model and delivery performance using a case of dairy industry. The integrated supply chain model is based on a unitary structuring technique and forms the basis for measuring and evaluating supply chain performance. Delivery performance with variation of demand (forecast and actual) is monitored using a fuzzy-based decision support system, based on three inputs: capacity utilization (influenced by production disruption), raw materials shortage and quality of dairy products.

Integration of supply chain components (materials, resources, operations, activities, suppliers, etc.) of key processes using unitary structuring approach enables information integration in real time for performance evaluation and monitoring in complex supply chain situations. In addition, real-time performance monitoring is recognized as being of great importance for supply chain management in responding to uncertainties inherent in the operational environment.

Implementation of an integrated model requires maintenance of supply chain components with all necessary data and information in a system environment such as enterprise resource planning.

The integrated model provides decision-makers with an overall view of supply chain components and direct links that need to be maintained for supply chain performance evaluation and monitoring. Wider adaptation and diffusion of the proposed model require further validation of the model and feasibility of implementation, using real-time data and information on selected performance measures.

Integration of supply chain components across supply chain processes directly linked with performance measures is a novel approach for effective supply chain performance evaluation and monitoring in complex supply chains under dynamic and uncertain conditions.

The purpose of this paper is to compare various inventory policies and their effect on various performance metrics at different levels of a multi stage supply chain. Later the model is integrated to include optimization of entire supply chain through implementation of collaborative supply chain model.

Alternative inventory policies have been developed at different echelons and a comparison reflecting the usability on various factors such as inventory level, inventory cost and service level is presented so as to support the decision-making process. Various inventory policies such as economic order quantity, periodic ordering (T, M) and stock to demand have been considered. Along with the basic assumptions; lead time, demand variability, variability in demand during lead time, stock out costs have also been included to make the model more applicable to practical situations.

After the selection of most appropriate inventory policy at each level through a decision matrix, the total cost of operating such a supply chain is calculated along with other parameters such as service level and inventory turns. The approach is of aggregating the optimized value at each echelon referred to as aggregated supply chain in the paper. Then the concept of integrated supply chain is introduced which optimizes the supply chain as a whole, rather than aggregating local optima. The comparison is made between the two approaches that prove the integrated supply chain's superiority. Furthermore, dependent optimization is run as it is not practically possible for each echelon to optimize at the same time.

Each echelon is allowed to optimize at a time and other echelons assume corresponding values. This final comparative multi criterion analysis is based on the three factors, i.e. inventory cost, customer service level and inventory turnover with different weights assigned to each factor at different levels of a supply chain. Finally a consolidation of results is made to reflect the overall preference which proves that an integrated supply chain best serves all the parameters combined together.

The main purpose is to minimize the total inventory cost of chain, whereas the stochastic constraints are satisfied. In other words, the goal is to find optimum agreed stockpiles and period length for products to minimize the total inventory cost of the chain while the stochastic constraints are fulfilled.

This paper designs and optimizes an integrated inventory model in a four-echelon supply chain that contains a supplier, a producer, a wholesaler and multiple retailers. All four levels agree with each other to make an integrated inventory system. Products in this model have a multi-stage production process, and the model is bounded by multiple stochastic constraints. The problem model is nonlinear and large. So, the interior point method as an effective algorithm is used for solving the recent convex nonlinear model. Two numerical examples are solved to demonstrate the application of this methodology and to evaluate the performance of the proposed approach.

The findings showed the model is applicable for real-world supply chain problems in the cases that echelons are going to do executive external integration. Also, the Interior Point algorithm has a satisfactory performance and a high efficiency in terms of optimum solution for solving nonlinear and large models.

The authors designed and optimized the inventory cost in a four-level integrated supply chain in stochastic conditions. The new decision variables, number of chain levels, multi-products, stochastic constraints and multi-stage products in four-level integrated supply chain are other novelties of this paper. The authors provided an efficient algorithm for solving a large-scale and nonlinear model in this research, too.

Due to the importance of quality to customers, this study considers criteria of quality and profit and optimizes both in a multi-echelon cold chain of perishable agricultural products whose quality immediately begins to deteriorate after harvest. The two objectives of the proposed cold chain are to maximize profit and quality. Since postharvest quality loss in the supply chain depends on various decisions and factors, in addition to strategic decisions, the authors consider the temperature setting in refrigerated facilities and transportation vehicles due to the unfixed shelf life of the products which is related to the temperature found by Arrhenius formula.

The authors use bi-objective mixed-integer nonlinear programming to design a four-echelon supply chain. The authors integrate the supply chain echelons to detect the sources and factors of quality loss. The four echelons include supply, processing, storage and customer. The decisions, including facility location, assigning nodes of each echelon to corresponding nodes from the adjacent echelon, allocation of vehicles to transport the products from farms to wholesalers, processing selection, and temperature setting in refrigerated facilities, are made in an integrated way. Model verification and validation in the case study are done based on three perishable herbal plants.

The model obtains a 29% profit against a total cost of 71 and 93% of original quality of the crops is maintained, indicating a 7% quality loss. The final quality of 93% is the result of making a US$6m investment in the supply chain, including the procurement of high-quality raw materials; facility establishment; high-speed, high-capacity vehicles; location assignment; processing selection and refrigeration equipment in the storage and transportation systems, helping to maximize both the final quality of the products and the total profit.

The proposed supply chain model should help managers with modeling decisions, especially when it comes to cold chains for agricultural products. The model yields these results – optimal location-allocation decisions for the facilities to minimize distances between the network nodes, which save time and maintain the majority of the products’ original quality; choosing the most appropriate processing method, which reduces the perishability rate; providing high-capacity, high-speed vehicles in the logistics system, which minimizes transportation costs and maximizes the quality; and setting the right temperature in the refrigerated facilities, which mitigates the postharvest decay reaction rate of the products.

Comparison of the results of the present research with those of the traditional chain (obtained through experts) shows that since the designed chain increases the profit as well as the final quality, it has benefits for the main chain stakeholders, which are customers of agricultural products. This study model is expected to have a positive impact on the environment by placing strong emphasis on quality and preventing excessive waste generation and air pollution by imposing a financial penalty on extra demand production.

Since profit and quality of the final product are two important factors in all cultures and communities, the proposed supply chain model can be used in any food industry around the world. Applying the proposed model induces growth in local industries and promotes the culture of prioritizing quality in societies.

To the best of the authors’ knowledge, this is the first research on a bi-objective four-echelon (supply, processing, storage and customer) postharvest supply chain for agricultural products including that integrates transportation logistics and considers the deterioration rate of products as a time-dependent variable at different levels of decision-making.

Purpose – To describe the evolution of an integrated ‘lean’ and ‘agile’ supply chain process that employed Just‐in‐time (JIT) lean manufacturing approaches at an electronics company. Design/methodology/approach – A case study was designed to examine the links between specific efficiencies and cost savings that derived from transitions in the evolution of the integrated lean and agile supply chain. The case study focused on the company's supply chain management innovations that led to specific improvements in production processes that in turn resulted in enhanced financial outcomes. Findings – The data revealed how specific quality enhancing and lean manufacturing components evolved over a period of seven years in a two stage transition from a ‘lean’ supply chain to one that represented an integrated lean and agile paradigm based on the decoupling point approach (Christopher & Towill, 2001). Research limitations/implications – A single site case study limits the generalizability of the findings. Additional research is necessary to replicate the findings in other firms/industries. Practical implications – By incorporating improvements in production processes in the supply chain, managers can determine how inefficiencies in the supply chain process can be tracked and eliminated to improve a firm's financial performance. Originality/value – Research that documents links between different managerial functions, e.g. supply chain management, improved manufacturing processes, and accounting issues (e.g. cost reduction and improved profitability), is particularly useful.

Poultry production supply chains produce substantial wastes that are transformable into favorable environmental outcomes and profitable products. While overwhelming evidence supports this conclusion, scant literature is available on how such transformations are doable. Using systems dynamics, this study addresses this research gap in a national (Bangladesh) context. This study aims to contribute an integrated model for poultry supply chains that incorporate reverse flows of wastes using system dynamics (SD) engineering with empirical simulations.

This study applies SD and simulations of alternative supply chains with versus without reverse loops that transform wastes into viable products in poultry production and downstream marketing operations. This research reports on an in-depth case study of systems thinking and use of the Massachusetts Institute of Technology systems dynamics software. Data for the study are longitudinal and come from written operation records and extensive, repeated, one-on-one Interview from a large poultry plant operation in Bangladesh.

This study finds that several current poultry waste production problems are solvable through an integrated approach that generates viable new marketable products with substantial profitable opportunities that also contributes to reductions in industrial pollution. This study confirms that forward, backward and reverse supply chains need to be under one umbrella system to achieve economic, social and environmental benefits.

This study’s SD model and outputs need additional applications in poultry supply chains in multiple countries. Applying the firm-level model that this study provides is a necessary but insufficient step toward empirical confirmation through replicating.

Recent research has highlighted the beneficial role of supply chain resilience for ensuring efficient production and business processes. The purpose of this study is to explore enablers of supply chain resilience. In particular, the authors examine whether and how dynamic capabilities and knowledge management can help firms develop a resilient supply chain in times of high disruption and uncertainty.

A single longitudinal case study design was adopted. Data was collected over 8 years from a Pakistani textile producer and supplier through semi-structured interviews and was analyzed through NVivo to generate codes and themes that contributed to the development of the supply chain resilience model.

The analysis of case study shows that our focal firm strategically acquired, transferred and integrated market knowledge by investing in digital technologies and idiosyncratic resources and consequently developed a supply chain model that was resilient in addressing logistics and delivery challenges in uncertain & critical times.

The study brings together three main research streams of organizational theory, namely supply chain, knowledge management and dynamic capabilities, and proposes a nuanced resilient supply chain model.

By applying the research findings, managers can adjust, develop and adopt supply chain resilience to address market volatilities, thereby creating value and longevity in their supply chain operations. However, the findings are context specific and should be applied cautiously.

The outcomes provide early hints on how companies in emerging economies can adopt and integrate novel digital technologies, and overhaul their organizational routines to facilitate knowledge management and develop dynamic capabilities, and consequently enhance the resilience of their supply chain operations.

This study aims to comprehend the role of leagility and resilience in developing sustainable global supply chains, mitigating short-term disruptions and long-term economic impacts from various disasters, in the context of Australian civil infrastructure projects.

The study employs systematic review approach to establish that addressing project success dimensions (i.e. leagility, resilience and sustainability) requires an integrated and extended supply chain approach, encompassing traditional supply chain strategic model elements (i.e. cost/capital, quality and service goals) and supply chain eco-system (i.e. organisations, societies, economies and nature).

The study underscores the need to enhance supply chain leagility and resilience to achieve sustainability. This can be achieved by developing skills needed to plan across project phases and time frames, aligning with short and long-term organisational goals, assuming smart risks in the face of uncertainty.

This study extends the traditional supply chain strategic model by introducing new priorities to minimise the consequences of disruptions and to effectively respond to them. The integration of leanness, agility and resilience ensures a sustainable supply chain even in the times of uncertainty, disruption and volatility.

This research provides an opportunity for practitioners and policymakers to rethink and redesign the conventional supply chain model of cost, capital, quality and service objectives. It introduces pioneering concepts by acknowledging and incorporating emerging priorities, especially in Australian civil infrastructure projects. The study integrates leagility and resilience into the existing strategic framework, adding crucial dimensions for sustainable supply chains in infrastructure companies.

Supply chain is an important aspect for all the companies and can affect many aspects of companies. Especially the disruption in supply chain is causing huge impacts and consequences that are difficult to deal with. This chapter presents a review of selected multiple criteria problems used in supply chain optimization. Research analyzed the multiple criteria decision-making methods to tackle the problem of supplier evaluation and selection. It also focuses on the problem of supply chain when a disruption happens and presents strategies to deal with the issue of disruptions in supply chain and how to mitigate the impact of disruptions. Prevention, response, protection, and recovery strategies are explained. Practical part is focused in the risk-averse models to minimize expected worst-case scenario by single sourcing. Computational experiments for practical examples have been solved using CPLEX solver.