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Analyzing potential benefits of thermostable vaccines delivered through Micro Array Patch (MAP) has received great attention in low and middle-income countries. The experience may or may not be the same in developed countries where the infrastructure is more developed. It is anticipated that transforming the vaccine supply chain from syringe-and-needle to thermostable MAP-delivered vaccines will result in reduced supply chain costs – including manufacturing/supply, logistics/distribution, and administration costs – as well as reduced wastes and improved safety. This paper provides an end-to-end supply chain analysis comparing the key aspects (cost, safety and environmental aspects) of the conventional syringe-and-needle vaccine supply chain with those of the MAP vaccine supply chain for influenza vaccine delivery in Australia. Directions for future research in this area will be provided. To determine the potential supply chain impacts of replacing syringe-and-needle flu vaccine with MAP-enabled thermostable flu vaccine in Australia. We analyze the current flu vaccine supply chain in Australia to identify practical limitations and opportunities for improvement. Data/information is collected through interviewing the key stakeholders across vaccine supply chain including vaccine manufacturers, logistics providers, clinics, hospitals, and pharmacies. A detailed practice-informed analysis is completed on the key operations of the flu vaccine supply chain. Barriers and limitations of the conventional flu vaccine are discussed, along with potential improvements that can be achieved through the implementation of MAP-enabled flu vaccine delivery. We discuss how technology-driven innovations can help advance vaccine supply chains, improve vaccine visibility, reduce wastes, and enable informed decision-making. We find that the benefits of moving from syringe-and-needle vaccines to thermostable MAP-delivered vaccines are beyond transportation and storage cost saving. Potential benefits through cost saving, waste reduction, and service level improvement are discussed along with various safety and wellbeing consequences followed by directions for future research in this area.

It is anticipated that transforming the vaccine supply chain from syringe-and-needle to thermostable vaccines enabled by Micro Array Patch (MAP) will result in reduced supply chain costs as well as reduced wastes (environmental impact) and improved safety. This paper provides a thorough cost comparison of the conventional syringe-and-needle vaccine supply chain versus the MAP vaccine supply chain for influenza vaccine delivery in Australia. To determine the potential cost implications and general benefits of replacing syringe-and-needle flu vaccine with MAP-enabled thermostable flu vaccine in Australia. We first provide a snapshot of the existing flu vaccine supply chain in Australia including its limitations and opportunities for improvement. Data/information is collected through interviewing the key stakeholders across vaccine supply chain including vaccine manufacturers, logistics providers, clinics, hospitals, and pharmacies. A cost/benefit analysis of the anticipated supply chain of the MAP-enabled vaccine will reveal the opportunities and challenges of supply chain transformation for flu vaccine delivery in Australia. Our high-level practice-informed cost/benefit analysis identifies cold chain removal as an important source of cost saving, but administrative cost savings appear to be even more significant (e.g., time saving for nurses and those involved in cold chain management). Our analysis also identifies the key benefits and limitations of vaccine supply chain transformation in Australia. We conclude that the benefits of moving from syringe-and-needle vaccines to thermostable MAP-delivered vaccines are beyond transportation and storage cost saving. Potential benefits through cost saving, waste reduction, and service level improvement are discussed along with various safety and wellbeing consequences as well as directions for future research in this area.

This paper presents a two-stage stochastic programming model to design a green supply chain in a carbon trading environment. The model solves a discrete location problem and determines the optimal material flows and the number of carbon credits/allowances traded. The study contributes to the existing literature by incorporating uncertainty in carbon price and product demand. The proposed model is applied to a real world case study and the numerical results are carefully analyzed and interpreted. We find that the supply chain configuration can be highly sensitive to the probability distribution of the carbon credit price. More importantly, we observe that carbon price and budget availability for supply chain reconfiguration can both have a positive but nonlinear relationship with greening of the supply chain.

PurposeThe success of a supply chain is highly reliant on effective inventory and ordering decisions. This paper systematically reviews and analyzes the literature on inventory ordering decisions conducted using behavioral experiments to inform the state-of-the-art.Design/methodology/approachThis paper presents the first systematic review of this literature. We systematically identify a body of 101 papers from an initial pool of over 12,000.FindingsExtant literature and industry observations posit that decision makers often deviate from optimal ordering behavior prescribed by the quantitative models. Such deviations are often accompanied by excessive inventory costs and/or lost sales. Understanding how humans make inventory decisions is paramount to minimize the associated consequences. To address this, the field of behavioral operations management has produced a rich body of research on inventory decision-making using behavioral experiments. Our analysis identifies primary research clusters, summarizes key learnings and highlights opportunities for future research in this critical decision-making area.Practical implicationsThe findings will have a significant impact on future research on behavioral inventory ordering decisions while informing practitioners to reach better ordering decisions.Originality/valuePrevious systematic reviews have explored behavioral operations broadly or its subdisciplines such as judgmental forecasting. This paper presents a systematic review that specifically investigates the state-of-the-art of inventory ordering decisions using behavioral experiments.

Purpose – This paper aims to provide a framework which can assist focal companies in the development of sustainable supply chains. Sustainable development from an industrial perspective has extended beyond organisational boundaries to incorporate a supply chain approach. Design/methodology/approach – The literature related to sustainable supply chain management is reviewed by incorporating concepts from four organisational theories, including the resource-based, institutional, stakeholder and social network perspectives, to illustrate key drivers and enablers of sustainability initiatives in the supply chain. A conceptual multidimensional framework is then developed that can be used for the initial assessment of supply chain sustainability. Findings – Development and assessment of sustainability in supply chains are being increasingly incorporated as part of supply chain management today. This paper presents a multidimensional framework which can serve as a tool for research scholars and supply chain practitioners in identifying and assessing various economic, environmental and social performance indicators. Research limitations/implications – The framework and approach presented are conceptual, and require additional and broader validation. Additional theories, at differing levels, such as individual behaviour theory, should be utilised to further enhance and evaluate the framework. Developing and integrating analytical models for prescriptive and practical supply chain solutions can enhance the applicability of the framework. Practical implications – The framework adopts a multidimensional approach to assessing and designing sustainable supply chains, as it not only incorporates economic and environmental dimensions but also provides a practical approach to quantifying and embedding the social dimension into decision-making. The framework helps industry practitioners in initial exploration of trade-offs among economic, environmental and social performance of supply chains, which, in turn, could assist them in creating a business case for sustainability. Originality/value – The paper is one of few studies that incorporates some of the key aspects of all three dimensions of sustainability in a single overarching framework for supply chains and offers significant theoretical contribution and implications for sustainable supply chain management.

This paper presents a robust optimization model for the design of a supply chain facing uncertainty in demand, supply capacity and major cost data including transportation and shortage cost parameters. We first present a base model that aims to determine the strategic ‘location’ and tactical ‘allocation’ decisions for a deterministic four-tier supply chain. The model is then extended to incorporate uncertainty in key input parameters using a robust optimization approach that can overcome the limitations of scenario-based solution methods in a tractable way, i.e. without excessive changes in complexity of the underlying base deterministic model. The application of the approach is investigated in an actual case study where real data is utilized to design a bread supply chain network. Numerical results obtained from model implementation and sensitivity analysis experiments arrive at important managerial insights and practical implications.

One of the most critical operational practices influencing the environmental sustainability of organizations and their supply chains is the transport of materials, products and people. The carbon footprints, materials depletion, and general pollution emissions from transport vehicles makes their environmental burdens significant. Thus, identifying, selecting and implementing more environmentally conscious transportation vehicles can be of paramount importance for the development and management of greener supply chains. Given the relative importance of this issue, it is surprising that research on transport fleet evaluation, especially from an environmental sustainability perspective, has been rather limited. A primary challenge in this context is the broad range of influencing factors that need to be considered, many of which are not fully and easily measurable. This paper aims to (1) develop a holistic framework for sustainable transport fleet appraisal incorporating various vehicle performance, economic and environmental criteria, (2) introduce a novel hybrid approach for sustainable transportation vehicle evaluation and selection by combining a three-parameter interval grey number with a rough set theory and VIKOR method, (3) investigate the application of the proposed approach in a case example where empirical data is collected from industry experts, (4) evaluate the robustness of the methodology through sensitivity analysis experiments, and (5) provide practical insights and directions for future research in this area.

Supply chains (SCs) can be managed at many levels. The use of tactical SC planning models with multiple flexibility options can help manage the usual operations efficiently and effectively, whilst improve the SC resiliency in response to inherent environmental uncertainties. This paper defines tactical SC flexibility and identifies tactical flexibility measures and options for development of flexible SC planning models. A classification of the existing literature of SC planning is introduced that highlights the characteristics of published flexibility inclusive models. Additional classifications from the reviewed literature are presented based on the integration of flexibility options used, solution methods utilized, and real world applications presented. These classifications are helpful for identifying research gaps in the current literature and provide insights for future modeling and research efforts in the field.

Supply chain flexibility is widely recognized as an approach to manage uncertainty. Uncertainty in the supply chain may arise from a number of sources such as demand and supply interruptions and lead time variability. A tactical supply chain planning model with multiple flexibility options incorporated in sourcing, manufacturing and logistics functions can be used for the analysis of flexibility adjustment in an existing supply chain. This paper develops such a tactical supply chain planning model incorporating a realistic range of flexibility options. A novel solution method is designed to solve the developed mixed integer nonlinear programming model. The utility of the proposed model and solution method is evaluated using data from an empirical case study. Analysis of the numerical results in different flexibility adjustment scenarios provides various managerial insights and practical implications.