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This study extends research on buyer firm roles in improving supplier sustainability practices by considering institutions – norms and rules – in the organisational field in which suppliers and sub-suppliers operate, exerting pressures on these actors to align their respective practices. We introduce the resource-based view to arrive at a framework outlining key capabilities for institutional entrepreneurs that seek institutionalisation of corporate sustainability standards (CSS) as a new institution across a multi-tier supply chain. The paper draws on the results of an exploratory research study using six comparative case studies within four industries. While institutional entrepreneurship explains how organisations drive institutional change, the resource-based view outlines criteria for organisational capabilities enabling the focal firm to achieve the targeted institutional change. Our analysis suggests five key capabilities enabling a buying firm to effectively institutionalise their requirements in multi-tier supply chains: (1) inter-firm dialogue, (2) risk management, (3) external stakeholder collaboration, (4) cross-functional integration, and (5) continuous improvement. The key organisational capabilities identified help to extend the theory of institutional entrepreneurship with concepts that facilitate institutional change in multi-tier supply chains with respect to corporate sustainability. This exploratory work opens up avenues of additional research in general and supply chain theory development.

Companies manage their product portfolios to create value. Products and associated materials are important flows that link supply chains entities from upstream to downstream. Product deletion is a ...

The circular economy (CE) has gained importance in the post-COVID-19 pandemic recovery. Businesses, while realising the CE benefits, have challenges in justifying and evaluating the CE benefits usi...

The modern supply chain is characterised by an ill-defined and porous perimeter, allowing entry points for potential adversaries to intercept sensitive information and disrupt operations. Such supp...

This work introduces a methodology to evaluate, rank, and select suppliers for an organisation managing a large and complex construction project. The company’s procedure to complete a supplier eval...

Product management activities by marketing, operations, and finance functions have typically focused on the innovation, acquisition, growth, and management of product lines and products. The same i...

Reverse supply chains are receiving increased attention for business and sustainability opportunities. As few organizations are adept at both forward and reverse supply chains, subcontracting various activities is imperative. Vendor selection that best achieves combined expertise for reverse supply chains, while quickly forming virtual enterprises to seize market opportunities, is an emerging issue. We formulate a novel 0-1 integer nonlinear optimization model, subsequently linearized to enable efficient computational performance, to select vendors that minimize the maximum formation time for creating agile virtual reverse supply chains. We then generate a portfolio of diverse, high-quality vendor assignments by adapting a recent algorithmic technique, thereby allowing industrial managers to address intangible factors into their final decisions. Computational experiments on simulated data demonstrate the model’s efficiency for generating sets of high-quality and diverse solutions in reasonable timeframes.

Blockchain – also known as distributed ledger – technology is set to revolutionise data and business process management and transactions. Blockchain adoption, pioneered initially as a financial tec...

Transparency has become a supply chain concern from competitive and reputational perspectives. It is also one of the riskiest and hardest aspects to introduce within logistics and supply chain mana...

Blockchain technology and the circular economy (CE) are two emergent concepts that can change the way we live for decades. Arrival of Industry 4.0 is set to transform organisational activities thro...

Contemporary multi-tier supply chains are increasingly international, complex, and challenging for suppliers and focal companies. In addition to this, internal and external stakeholders, regulators, consumers and non-governmental organizations all now require firms to take responsibility for and action towards mitigating unsustainable practices and misconduct in their supply chains. In dealing with this complex supply chain context, quantitative modeling approaches are relevant in their ability to capture the complexity of problems in order to propose effective and sustainable solutions. The main objective of this study is to review selected literature on the effective management of sustainability in supply chains, and its attendant implications for multi-tier supply chain modeling problems. Previously published modeling research that may directly or indirectly provide lessons for multi-tier sustainable supply chains is investigated utilizing the Scopus database. After analyzing the relevant literature, we deliver the following contributions: (a) a systematization and classification of the selected papers; (b) a description of 16 research gaps that remain in the literature and that may be useful in expanding research efforts in this domain; (c) four lessons for both practitioners and managers dealing with sustainability in multi-tier supply chains; (d) an integrative framework which encapsulates key areas of focus to develop multi-tier sustainable supply chains. Implications for theory and practice are suggested, as well as limitations concerning the scope of this systematic review.

Sustainability issues pervade the supply chain deep into the recesses of various global regions and resources. Supply chains can become quite complex as they form multiple tiers of organizations and across networks. Solving anthropocentric pressures on the environment and human society means compelling supply chains to alleviate their environmental and social burdens. The strategic and operational complexities of multi-tier supply chain sustainability are transcendent. Addressing these concerns is still in its relative infancy amongst business, engineering, and production economics solutions. It is within this environment that this special issue in the International Journal of Production Economics advances this important research stream. Twenty-three articles using multiple methodologies, theories, and developments provide insights, clarifications and potential solutions to some of the most pernicious problems of multi-tier sustainable supply chains. This editorial overviews the various contentions, study interrelationships, whilst providing some future research directions.

Third-party reverse logistics provider (3PRLP) selection plays an important role in the operation and implemention of reverse logistics or reverse supply chains. Economic and cost based partner relationships are no longer acceptable for 3PRLPs or for organizations that seek to introduce sustainable supply chain management. Recent emphasis on sustainability has made 3PRLP evaluation and selection more complex. In order to advance this area of research and to help further incorporate sustainability into 3PRLPs selection modeling, a novel multi-stage, multi-method, multi-criteria approach is developed. Methodologically, this is the first time that neighborhood rough set (NRS) theory is integrated with TOPSIS and VIKOR techniques. Neighborhood rough set, as a data management and soft computation tool, can help reduce the number of 3PRLP to be evaluated and ranked using TOPSIS combined with VIKOR's compromise conception decision tools. A conceptual application is developed using business, environmental, and social factors within the context of reverse logistics management decisions. A sensitivity analysis evaluating various neighborhood rough set parameters is also introduced to investigate robustness of solutions using the multi-stage methodology. Methodological implications and future research and application directions conclude the paper.

The circular economy (CE) is an evolving economic and sustainable development model. In this new environment, companies face a more dynamic, uncertain, and complex market environment. These challen...

In developing economies agriculture and farming play crucial roles for economic sustainable development. Farmer credit risk evaluation is an important issue when determining financial support to farmers, improving agricultural supply chain performance, and ensuring profitability of financial institutions. Credit risk evaluation, or creditworthiness, is not a trivial exercise due to various complexities. Honoring complexity is necessary to effectively evaluate and predict farmer creditworthiness. A methodology using fuzzy rough-set theory and fuzzy C-means clustering is used to evaluate and investigate the complex relationships between farmer characteristics, competitive environmental factors, and farmer credit level. The methodology is detailed using actual bank data from 2044 farmers within China. This empirical methodology generates decision rules that provide insight to more complex relationships than can be found through standard econometric multivariate approaches. A rule-based methodological outcome can be used to predict the creditworthiness of farmers and to aid in agricultural loan decision making. Prediction accuracy of the rule-base was 81.16%. A central finding is that education and skills related characteristics are important for determining farmer credit-worthiness. Other implications are presented along with study limitations and future research directions.

Organisational and managerial decisions are influenced by corporate sustainability pressures. Organisations need to consider economic, environmental and social sustainability dimensions in their decisions to become sustainable. Supply chain decisions play a distinct and critical role in organisational good and service outputs sustainability. Sustainable supplier selection influences the supply chain sustainability allowing many organisations to build competitive advantage. Within this context, the social sustainability dimension has received relatively minor investigation; with emphasis typically on economic and environmental sustainability. Neglecting social sustainability can have serious repercussions for organisational supply chains. This study proposes a social sustainability attribute decision framework to evaluate and select socially sustainable suppliers. A grey-based multi-criteria decision-support tool composed of the ‘best-worst method’ (BWM) and TODIM (TOmada de Decisão Interativa e Multicritério – in Portuguese ‘Interactive and Multicriteria Decision Making’) is introduced. A grey-BWM approach is used to determine social sustainability attribute weights, and a grey-TODIM method is utilised to rank suppliers. This process is completed in a group decision setting. A case study of an Iranian manufacturing company is used to exemplify the applicability and suitability of the proposed social sustainability decision framework. Managerial implications, limitations, and future research directions are introduced after the application of the model.

The growth of vendor procurement and supply chain management simultaneously emerged as organizational outsourcing practices increased. Outsourcing, as an important strategic organizational practice, needs to be carefully examined from an organizational performance perspective to ensure satisfactory quality of services and goods from supply chains. This article provides a model for performance assessment of an outsourcer's processes in a supply chain comprised of several internal and external entities. Internal entities are entities in a supply chain that the outsourcer can manage and control. External entities are entities whose processes are not within the management sphere and control of the outsourcer, yet affect an outsourcer's performance. A slacks-based measure is incorporated into a hybrid network data envelopment analysis model to evaluate the outsourcer performance incorporating both entity types. A case study of a service supply chain in the banking industry comprised of a commercial bank, its sub-processes, and an external investment bank is used as an illustrative application of the model. Insights are presented and future research directions are identified.

The Belt and Road Initiative (BRI) has resulted in international, cross-border supply chains returning to a new prominence. The BRI presents opportunities for cross-border supply chain collaboration research. Assessing the influencing factors of cross-border supply chain collaboration is beneficial for understanding and improving this evolving, globally influential international trade policy. The BRI is quite complex so that subjective assessment methods are useful but should be improved. To address this issue, this paper initially develops a cross-border supply chain collaboration factor framework based on synergetic theory. A vague set and DEMATEL methods are integrated to form a unified model to support the assessment. A combination weighting that uses analytical hierarchy process (AHP) and an entropy weighting method, i.e., a data crawler for BRI-related documents, to ensure that objective importance weights of the factors in the Belt and Road context are achieved. The results show that information sharing, profit allotment, the degree of trust and goal congruence as common drivers of supply chain collaboration are not driving factors in the Belt and Road cross-border context. They are core issues that do not affect cross-border supply chain collaboration directly. Senior manager support and customs regulation are two important drivers of cross-border supply chain collaboration. The practitioners of cross-border supply chain collaboration should not only focus on the support from senior managers and customs regulation but also attempt to improve performance, such as information sharing and trust, to obtain more support from senior managers and policy makers to promote cross-border supply chain collaboration indirectly.

This work proposes and empirically tests a new framework for evaluating the relationship between stakeholder pressures, the adoption of low-carbon operations practices and firms’ carbon performance. It seeks to expand upon stakeholder theory and the natural-resource-based view (NRBV) to understand further the role of operations management in a low-carbon environment. Our theoretical hypotheses were tested through the Partial Least Squares method with bias-corrected and accelerated (BCA) bootstrap confidence intervals. The key findings encapsulate a mixture of expected and unexpected research results: (i) stakeholder pressures influence both barriers and motivators for decarbonising operations management practices; (ii) a variety of barriers and motivators significantly affect the adoption of low-carbon operations management practices; (iii) developing positive relationships with stakeholders is important to overcome barriers from the external environment and enhance organisational competitiveness; (iv) low-carbon operations management has an overall effect on firms’ carbon performance; However, unexpectedly: (v) firms seem to face difficulties in understanding stakeholder pressures when developing low-carbon products and logistics, due to a lack of awareness of the sources of barriers to the adoption of low-carbon management practices; (vi) in terms of stakeholders, competitors tend to exert significant pressure towards the adoption of low-carbon operations, while government does not; (vii) more research is necessary to better understand the apparent weak link between low-carbon logistics and firms’ low-carbon performance.

Sustainable supply chain management (SSCM) faces greater complexity because it considers additional stakeholder requirements, broader sustainable performance objectives, increased sustainable busin...

Product management activities have typically focused on the innovation, acquisition, expansion and management of product lines and products. However, product deletion or discontinuation is also critical. Despite its strategic importance, product deletion has received relatively less attention in both academia and practice. Researchers have conceptually investigated product deletion, its influence on firm's resources, the factors influencing product deletion decisions, and the product deletion process. However, very few papers have related product deletion decisions to supply chain management, especially when leanness and sustainability are major objectives. This paper aims to integrate lean and sustainable supply chain dimensions with product deletion by proposing a multilevel decision model that can facilitate a product deletion decision with an objective of developing a leaner and more sustainable supply chain. The model has three major decision dimensions with 8 factors with 29 influencing determinants. The model uses an integrated analytical hierarchy/network process (AHP/ANP) and a benefits, opportunities, cost and risks (BOCR) analysis. An illustrative company scenario is provided for the model application. The paper contributes by filling an important gap by integrating lean and sustainable supply chain management and product deletion literature to formulate a product deletion decision making model which aids in enhancing the leanness and sustainability of supply chains. The model also allows for cross-functional participation involving marketing, operations, finance, and environmental sustainability fields.

Globalisation of supply chains makes their management and control more difficult. Blockchain technology, as a distributed digital ledger technology which ensures transparency, traceability, and sec...

Lean manufacturing practices (LMPs) and corporate environmental sustainability are becoming inextricably linked. Throughout the lean and green debate, many organisations have recognised that LMPs h...

This paper presents a multiperiod supply chain with freight carriers network model. In this model manufacturers, retailers, and carriers maximize the net present value (NPV) of their investments in ecologically friendly technology. Future production, inventory, transaction, and transportation costs savings are used to help fund investments. The environmental impact of production, inventory, transportation, and consumption of products in the supply chain network are all integrated. The tradeoff between the initial technology investment and its ecological footprint effect is considered for the supply chain planning period. We provide variational inequality formulations of the equilibrium conditions and then propose the modified projection method, along with conditions for convergence. Numerical examples are examined with an analysis of the effects of ecologically friendly technology investments on supply chain network production, transportation, and sales.

Organizations have demonstrated increasing interest in both leaning and greening activities. Lean manufacturing practices, with an emphasis on waste elimination, have an affinity with environmental...

Internal rate of return (IRR) is a widely used tool in ranking capital budgeting projects and eventual accept or reject decisions. In this paper, we consider an investment decision involving a sustainable, energy efficient, greenhouse gases (GHG) reducing asset and incorporate the value of carbon emission allowances for the investing company. These allowances create cash flows that may be characterized by significant volatility and uncertainty. The methodology developed in this paper allows decision makers to integrate their knowledge of carbon trading markets and the cash flows that result from sale of emissions credits. The novel methodology utilizes a Bayesian model for IRR that uses Gibbs sampler. Analysis of the results shows that IRR is influenced by volatility and uncertainty of carbon credit cash flows. Ignoring those uncertainty characteristics and simply using the expected values of cash flows can result in significantly inaccurate investment rate of returns. When compared to deterministic IRR calculations, the results show that the occurrence of very high and very low cash flows affects IRR positively, whereas higher variability of cash flow distribution affects IRR of GHG-reducing asset negatively. In other words, frequent large or small cash flows are preferred over fluctuating cash flows. The results may also provide a rationale for the existence of an anomalous consumer behavior known as the energy efficiency gap.

Blockchain technology has been widely touted for building and supporting supply chain management capabilities. The technology has substantial potential to enhance operational effectiveness and profitability. Blockchain platform evaluation and selection still requires investigation. Blockchain platform selection and adoption decision making in a multi-organizational supply chain context is complex. Effective blockchain adoption and operations requires consideration of multiple vendors—service providers—and platforms while satisfying multiple users and stakeholders. This study introduces a managerial decision support method to assist organizations evaluate and select joint blockchain service vendor and platforms for multiple organizational functions and organizations. Using literature and practice, we introduce blockchain service vendor and platform attributes from user, vendor, and platform perspectives. A social network theory lens sets the foundation for an innovative group decision-making method—a DEMATEL-based hierarchical best-worst method—integrating characteristics from this decision environment. The technological and distributed network nature of blockchain technology requires evaluation by decision makers from various levels of a supply chain network. These decision makers will likely have varying blockchain technology knowledge and subjective preferences that need integration. The proposed method helps to operationalize social network relationships to comprehend partial and idiosyncratic expert opinions about blockchain technology. An illustrative example and various scenarios are presented to identify managerial and research implications. Methodological limitations and future research are presented for this emergent managerial and technological concern across supply chains.

The research on production and operations management and its linkage to environmental sustainability has seen growth in recent years. The International Journal of Production Research (IJPR) communi...

Globalization and greening are two major trends manufacturing. Each trend has increased organizational and supply chain risk and uncertainty. Advanced manufacturing technology (AMT) are resources that can competitively aid modern industry in this volatile and complex environment. Thus, the evaluation, selection and implementation of more environmentally conscious AMT is important for meeting global requirements, especially with respect to environmental sustainability. Although a wide variety of methods to support AMT selection and evaluation processes exist, important aspects including green flexibility performance and psychological characteristics of decision makers under risk and uncertainty are missing. This paper presents a novel method for general investment appraisal of AMT, but especially introducing the context of green flexibility within manufacturing organizations. This paper aims to (1) develop effective green flexibility measures for manufacturing firms, incorporating various economic and environmental flexibility types, (2) introduce a hybrid possibility multiple criteria decision model for AMT evaluation and ranking integrating neighborhood rough set theory and cumulative prospect theory based on the three-parameter interval grey number, and (3) investigate the application of the proposed method in an illustrative case example to help manufacturing practitioner and researchers understand how to investigate various AMTs in this decision environment. Various advantages and disadvantages of the methodology are introduced. The results are evaluated with theoretical, methodological and managerial implications identified. This paper sets the foundation for significant future research in green manufacturing flexibility in an AMT environment.

Production and consumption in our industrial systems typically begin in the extractive, mining, industries. Typically these activities begin in emerging economies, such as Ghana. It is also clear that supply chain activities in mining operations may have severe environmental and social problems with serious economic consequences. Greening the supply chain of mining operations are an important avenue that can provide beneficial consequences. Developing, evaluating, assessing, and selecting essential green supply chain management (GSCM) practices are a goal for successful GSCM implementation. These practices may have interrelated and complex relationships. Understanding them and their relative importance is an initial step for achieving the assessment goals for successful GSCM implementation in the mining industry. This study adopts a proposed comprehensive and integrative GSCM major practices and sub-practices (framework); determines the relative relationships and influences within this GSCM framework, and identifies the perceived impact of the GSCM framework on organizational sustainable performance (economic, environmental, and social – triple bottom-line) pertinent to the mining industry, in the emerging economy nation of Ghana. An integrated methodology identifying and limiting interdependencies within GSCM factors will be utilized. The methodology uses fuzzy-DEMATEL and analytical network process (ANP) for the evaluation. Multiple field studies within Ghana's mining industry are used to illustrate the applicability of the proposed methodology. The results can provide valuable clues and guidelines to decision-makers and analysts inside and outside the mining industry, for improving corporate sustainable production and consumption. Future research and practical implications are also introduced in the paper.

China has faced environmental concerns due to its increased economic growth. Corporations are under various pressures to address environmental issues and may be critical to social change in China. Competitive advantage from building green markets and green consumers can occur as social mores and norms evolve. Sustainable consumption can also be managed through green marketing and green consumerism efforts. This paper reviews the emergent research on green marketing and consumerism in China. A total 52 peer reviewed journal publications are identified and reviewed from a variety of journals ranging from technological to marketing based journals. A conceptual framework has been used to identify gaps and future research directions based on marketing strategy, industrial sector, international comparisons, and green consumerism, all of which play a role in society and its sustainability. This work is the first to analyze green marketing and consumerism in China.

Decisions regarding offshoring and reshoring of manufacturing facilities and processes are of strategic importance for companies. These decisions often require the consideration of multiple financial, quantitative and qualitative factors. Integrating these often disparate factors can be extremely difficult for managers. This article presents a methodology, based on expert and practitioner input and literature, which aids in this process. The methodology incorporates concepts from activity-based costing, multi-attribute decision making and utility theory. An illustrative example using factors derived from literature and practice is presented to demonstrate the methodology and to discuss the issues which must be considered when making offshoring/reshoring decisions. The results of a series of interviews with supply chain professionals to establish the validity of the approach are discussed.

Green supplier development focuses on helping organizations integrate activities to improve the natural environmental performance of their supply chains. These green-supplier-development programs require substantial resources and investments by a buyer company. Investigation into investment management in this context has only begun. This paper introduces a methodology to help manage investment in green-supplier-development and business-supplier-development practices. Managing these practices and their outcomes requires managing of a large sets of data. We propose a combination of rough set theoretic and fuzzy clustering means (FCM) approaches; first to simplify, and then sharpen the focus on the complex environment of evaluation of the investment decisions. The combined methodology, based on performance measures of supplier practices and agreed-upon investment objectives, identifies a set of guidelines that can help make decisions about sound investments in the supplier practices more effectively and judiciously. Various steps involved in the methodology are illustrated through using an example developed to highlight the salient steps and issues of the methodology. We show how the results may be interpreted to obtain many insights useful from both practical and research perspectives. Although the impetus to developing this methodology came from sustainability considerations, the methodology is general enough to be applicable in other areas where management and evaluation of investments is based on large data sets.

The fourth industrial revolution, also labelled Industry 4.0, was beget with emergent and disruptive intelligence and information technologies. These new technologies are enabling ever-higher levels of production efficiencies. They also have the potential to dramatically influence social and environmental sustainable development. Organizations need to consider Industry 4.0 technologies contribution to sustainability. Sufficient guidance, in this respect, is lacking in the scholarly or practitioner literature. In this study, we further examine Industry 4.0 technologies in terms of application and sustainability implications. We introduce a measures framework for sustainability based on the United Nations Sustainable Development Goals; incorporating various economic, environmental and social attributes. We also develop a hybrid multi-situation decision method integrating hesitant fuzzy set, cumulative prospect theory and VIKOR. This method can effectively evaluate Industry 4.0 technologies based on their sustainable performance and application. We apply the method using secondary case information from a report of the World Economic Forum. The results show that mobile technology has the greatest impact on sustainability in all industries, and nanotechnology, mobile technology, simulation and drones have the highest impact on sustainability in the automotive, electronics, food and beverage, and textile, apparel and footwear industries, respectively. Our recommendation is to take advantage of Industry 4.0 technology adoption to improve sustainability impact but each technology needs to be carefully evaluated as specific technology will variably influence industry and sustainability dimensions. Investment in such technologies should consider appropriate priority investment and championing.

Emergy accounting has existed for decades. Emergy evaluates the donor side contribution of nature at region or country, macro-level analyses. It has been rarely applied and considered for organizational or supply chain management. In this study we provide an introduction and background on how emergy accounting analysis can be adjusted and applied at the supply chain level. Supplier selection is the example supply chain application for which actual emergy measures are used. The purpose of this study is to introduce the concept as a valuable tool for investigation by operations and supply chain management scholars and practitioners. The application provides some initial insight. This work at the nexus of sustainable supply chains and performance measurement is an initial study with significant future opportunities. These opportunities include effectively internalizing environmental and resource externalities for more thoughtful business models and evaluations. Implications and future research directions are summarized for this important, yet understudied field. It contributes by expanding the supplier performance measurement field.

Organizational sustainability requires production systems improvement and adaptation simultaneously balancing environmental, social and business dimensions. This exploratory study investigates how quality management exploitation and exploration may ambidextrously contribute to support environmentally sustainable production development. The study uses data collected through an online survey from ISO 9001 certified manufacturing firms. Drawing upon organizational ambidexterity in management literature, and using fuzzy-set qualitative comparative analysis (fsQCA) to examine the data, we develop a set of propositions that link quality ambidexterity to environmentally sustainable production. Results reveal alternative equifinal configurations of quality management practices that lead to environmentally sustainable production. All configurations combine quality exploration and exploitation practices. The consideration of multiple goals, and especially the requirement for cost efficiency, reveals tensions between the two quality learning modes. The study provides evidence that quality management ambidexterity, the simultaneous presence of quality exploitation and exploration practices, is an important determinant of environmentally sustainable production. The findings provide insights for managers on how to leverage organizational improvement capabilities to achieve sustainability goals.

Sustainability is hinged on innovation. The importance of sustainable innovation management in sustainable supply chain management (SSCM) cannot be underestimated. Studies on SSCM have emphasised the need for sustainable innovation in achieving sustainability but none provide deep insights into sustainable innovation management in SSCM implementation. This lack of research depth stimulates this study to identify and investigate criteria for sustainable supply chain management innovation advancement. This paper proposes a sustainable innovation criteria framework for investigating sustainable supply chains in manufacturing companies. To exemplify the applicability and efficiency of the proposed framework, a sample of five Indian manufacturing companies are used to evaluate and prioritise the sustainable innovation management criteria, using the ‘best–worst’ multi-criteria decision-making (BW-MCDM) model. The criteria weights for all companies from BWM are aggregated, averaged and used for ranking. The respondent managers viewed ‘financial availability for innovation’ as the most important sustainable innovation sub-criteria. The results of the study will inform industrial managers, practitioners and decision-makers on which criteria to focus on during the implementation stage, to increase sustainability in manufacturing supply chains, and further advance corporate and supply chain sustainable development. The framework may also serve as a theoretical construct for a future empirical study on sustainable supply chain innovation in the manufacturing sector. This paper sets the stage for further research in sustainable innovation practices in the manufacturing sector and its supply chains.

As supply chain risk management has transitioned from an emerging topic to a growing research area, there is a need to classify different types of research and examine the general trends of this research area. This helps identify fertile research streams with great potential for further examination. This paper presents a systematic review of the quantitative and analytical models (i.e. mathematical, optimization and simulation modeling efforts) for managing supply chain risks. We use bibliometric and network analysis tools to generate insights that have not been captured in the previous reviews on the topic. In particular, we complete a systemic mapping of the literature that identifies the key research clusters/topics, interrelationships, and generative research areas that have provided the field with the foundational knowledge, concepts, theories, tools, and techniques. Some of our findings include (1) quantitative analysis of supply chain risk is expanding rapidly; (2) European journals are the more popular research outlets for the dissemination of the knowledge developed by researchers in United States and Asia; and (3) sustainability risk analysis is an emerging and fast evolving research topic.

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.

In evaluating and selecting sustainable suppliers, we take a triple-bottom-line (profit, people and planet) approach and consider business operations as well as environmental impacts and social responsibilities of the suppliers. Different metrics are introduced to measure performance in these three areas. To examine the influences of different organizational and supply chain operating philosophies, the objectives in selection of suppliers are designed so that some of them favor profit or the business operations, others the planet or the environment and the remaining focusing on people or social responsibility. A novel methodological approach based on a Bayesian framework and Monte Carlo Markov Chain (MCMC) simulation is developed to rank and select suppliers using specific selection objectives. This technique is also effective when smaller or missing data sets exist, which is an especially prevalent characteristic for newer and complex measures such as in a sustainability decision environment. Results obtained from the MCMC simulation provide a wealth of information about supplier performance, which form the basis for additional statistical analyses. The model allows the decision maker to execute various scenarios by changing importance weights attached to the triple-bottom-line areas. We present results for some of those scenarios with managerial and research implications and future research directions identified.

This article presents a tactical supply chain planning model that can be used to investigate tradeoffs between cost and environmental degradation including carbon emissions, energy consumption and waste generation. The proposed model also incorporates other aspects of real world supply chains such as multiple transport lot sizing and flexible holding capacity of warehouses. A solution methodology, the Nested Integrated Cross-Entropy (NICE) method, is developed to solve the proposed mixed-integer nonlinear mathematical model. The application of the model and solution method is investigated in an actual case problem. Analysis of the numerical results focuses on investigating the relationship between lean practices and green outcomes. We find that (1) not all lean interventions at the tactical supply chain planning level result in green benefits, and (2) a flexible supply chain is the greenest and most efficient alternative when compared to strictly lean and centralized situations.

Carbon pricing (taxes) and carbon emissions trading are two globally practiced carbon regulatory policy schemes. This paper presents an analytical supply chain planning model that can be used to examine the supply chain performance at the tactical/operational planning level under these two policy schemes. Model implementation and analyses are completed using actual data from a company operating in Australia, where these environmental regulatory policies are practiced. Numerical results provide important managerial and practical implications and policy insights. In particular, the results show that there are inflection points where both carbon pricing and trading schemes could influence costs or emissions reductions. An erratic nonlinear emissions reduction trend is observed in a carbon pricing scheme as the carbon price increases steadily; whereas emissions reduction in a carbon trading scheme follows a relatively linear trend with a nonlinear cost increase. Overall, a carbon trading mechanism, although imperfect, appears to result in better supply chain performance in terms of emissions generation, cost, and service level; even though a carbon tax may be more worthwhile from an uncertainty perspective as emissions trading costs depend on numerous uncertain market conditions.