Supply Chain Operations Management Research Articles

Reforming Global Supply Chain Operations Management under Pandemics: The GREAT-3Rs Framework and Research Agenda

The recent outbreak of COVID-19 has posed serious threats and challenges to global supply chain operations. To survive the crisis, it is critical to rethink the proper setting of global supply chains and reform many related operational strategies. In this paper, we combine a careful literature review with real-world case explorations to examine the impacts and specific challenges brought by the pandemic to global supply chains. We first classify the related literature from the demand and supply sides. Based on the insights obtained, we search and report real practices of global supply chain operations under COVID-19 in nine top global enterprises. To achieve 3Rs (responsiveness, resilience, and restoration), we then propose the “GREAT-3Rs” framework, which shows the critical issues and factors for proper global supply chain operations management (GSCOM) under different pandemic stages (i.e., pre, during, post-pandemic stages). In particular, the “GREAT” part of the framework includes five critical domains, namely government proactive policies and measures, redesigning global supply chains, economic and financing strategies under risk, adjustment of operations, and technology adoption, to help global enterprises to survive the pandemic and achieve 3Rs. Finally, we establish a future research agenda.

Developing guidance templates and terminology to support multiple traceability objectives in the grain supply chain

AbstractBackground and objectivesGrain traceability is a multifaceted activity that aims to streamline supply chain operations, from farm to fork. Traceability involves several supply chain participants and takes into account the nature of their business(s). Implementing traceability in a supply chain system requires efforts from several parties in documenting the necessary data from supply chain processes or events. Food regulations and standards such as ISO 22000:2018 and ISO 220005:2007 provide an architecture for implementing traceability in food and feed establishments, but it fails to develop a concrete stepwise methodological traceability framework. The primary objective of this study was to create guidance documents for the application of traceability in the grain supply chain.FindingsThe minimum traceability requirement is to document the record of “one step up, one step down” but to effectively trace and track grain, more information is necessary. Therefore, this study developed a methodological guidance on what and how information needs to be captured to consider traceability for an entire grain supply chain system.ConclusionsIn practice, the approach of defining and documenting information as a measure to trace and track processes in a supply chain has proven to be successful in achieving various traceability objectives such as chain of custody, grain safety, quality, documentation, comply with regulations, and brand protection. This paper presents an information‐based traceability system as a collaborative effort of various supply chain participants which keeps a record of both material and information flow, across and within the supply chain system.Significance and noveltyManagement of grain traceability in a bulk commodity handling system is challenging because of comingling, which can easily compromise grain safety and quality. Several regulatory agencies in the United States and worldwide have set rules and guidelines to improve supply chain management operations. Grain traceability is one of the important components of the rulemaking involved in managing the grain supply chain.

ANALYTICAL RESULTS ON THE SERVICE PERFORMANCE OF STOCHASTIC CLEARING SYSTEMS

Stochastic clearing theory has wide-spread applications in the context of supply chain and service operations management. Historical application domains include bulk service queues, inventory control, and transportation planning (e.g., vehicle dispatching and shipment consolidation). In this paper, motivated by a fundamental application in shipment consolidation, we revisit the notion of service performance for stochastic clearing system operation. More specifically, our goal is to evaluate and compare service performance of alternative operational policies for clearing decisions, as quantified by a measure of timely service referred to as Average Order Delay ($AOD$). All stochastic clearing systems are subject to service delay due to the inherent clearing practice, and $\textrm {AOD}$ can be thought of as a benchmark for evaluating timely service. Although stochastic clearing theory has a long history, the existing literature on the analysis of $\textrm {AOD}$ as a service measure has several limitations. Hence, we extend the previous analysis by proposing a more general method for a generic analytical derivation of $\textrm {AOD}$ for any renewal-type clearing policy, including but not limited to alternative shipment consolidation policies in the previous literature. Our proposed method utilizes a new martingale point of view and lends itself for a generic analytical characterization of $\textrm {AOD}$, leading to a complete comparative analysis of alternative renewal-type clearing policies. Hence, we also close the gaps in the literature on shipment consolidation via a complete set of analytically provable results regarding $\textrm {AOD}$ which were only illustrated through numerical tests previously.

Barriers in omnichannel retailing returns: a conceptual framework

PurposePerforming retailing in a complete omnichannel manner is not a simple task, and it considerably increases the complexity of supply chain management operations. This paper aimed at identifying the barriers hindering efficient management of a return channel in this type of retail.Design/methodology/approachA systematic literature review procedure was used, including descriptive and content analysis of results. The review was performed using four academic databases. Applicable barriers were categorized thematically, a conceptual framework was proposed and future research avenues were drawn.FindingsThe contribution of this paper comprises a theoretical description of reverse logistics applied to omnichannel retail, the identification of the return barriers in omnichannel and a conceptual framework for a holistic view of the problem. In all, 43 barriers were identified including high investments, product restocking, additional transportation costs and poor communication.Research limitations/implicationsThe link between reverse logistics and omnichannel area is recent and publications are still scarce, so the newness of this study limits the opportunity for further deepening or more robust validation of the results.Practical implicationsThe results offered may be used by managers in the areas of retail and supply chain management in general in order to reduce the natural complexity in omnichannel environment.Originality/valueRegarding previous literature on omnichannel retail, only a few works consider the after-sales stage. This work intended to pave the way in this poorly explored intersection (reverse logistics and omnichannel) by presenting a conceptual framework to classify various barriers in omnichannel retail return.

Blockchain-driven supply chain decentralized operations – information sharing perspective

PurposeInformation sharing helps improve the efficiency of the supply chain. However, there are some problems in the multi-stage structure supply chain, such as untimely information feedback and distortion. Despite recent progress in ensuring improved collaboration in the past decade or so, the inefficiency status continues to persist. It is also difficult to add value to the supply chain. The information sharing framework and decentralized model designed in this paper are to deal with existing problems.Design/methodology/approachThis paper is based on the theoretical research of supply chain information asymmetry and synergetics. We attempt to introduce blockchain technology into supply chain operation management, reconstruct information sharing architecture and provide a new decentralized mode to promote the collaborative operation of all nodes. The information sharing and decentralization operational model are built, which has changed the hierarchical relationship between upstream and downstream enterprises, regarding customers as the center of the whole system and effectively reducing the bullwhip effect. Finally, we selected the home supply chain as an example design and performed system dynamics simulation on the blockchain-based operation process.FindingsThe model of setting up the scene application mode based on blockchain is helpful to realize the goal of supply chain management to reduce cost, improve quality and enhance the overall efficiency of the system.Originality/valueBased on the blockchain technology, this paper constructed a new supply chain operation mode and used the synergetic theory and the concept of the product–service system to explain the process of value increment in detail.

Quality Output, Workplace Environment, and Employee Retention: The Positive Influence of Emotionally Intelligent Supply Chain Managers

Industry advancements are accelerating at phenomenal rates and changing the management of logistics and supply chain operations. Employers must develop supervision with advanced skills to manage and retain the most effective employees making up the new workforce of highly skilled and technologically advanced personnel. Emotional intelligence is a managerial competence leveraged by leaders to connect with subordinates on a psychologically emotional level. Our research evaluates and applies emotional intelligence within the context of managing logistics and supply chain employees. Recognizing that employees are critical to production and service delivery, logistics and supply chain managers must be able to cognitively analyze situations and connect with employees in a positive manner even during challenging times. We find that managers possessing higher levels of emotional intelligence are better equipped to help their employees manage emotions, build more positive working conditions for subordinates, increase retention of employees, and achieve more positive service outcomes for external customers.

Coordination Mechanism of Supply Chain considering the Bullwhip Effect under Digital Technologies

The bullwhip effect (BWE) and stochastic demand coexist in supply chain operation management, which leads to a lower performance. In recent years, with the development of blockchain, cloud computing, big data, and other digital technologies (DTs), many enterprises hope to use them to weaken the BWE and improve profits. This paper focuses on improving the application level of DTs in the supply chain through coordination for enhancing the performance. We consider a supply chain with one-supplier-one-retailer and coordinate it with the cost-sharing contract and revenue-cost-sharing contract (the improved contract). We find out that the retailer and supplier did not always have the willingness to use DTs to alleviate the BWE. Even if they have the intention to use DTs, their ideal application level is not the same. After coordination, both the application level of DTs and the performance of the supply chain are improved, and we find that the improved contract has a better coordination effect. Finally, we validate our model by numerical simulation.

Vehicle routing problem and related algorithms for logistics distribution: a literature review and classification

The scheduling of deliveries and the routing of vehicles are of great importance for supply chain operations, as both determine to a great extent the distribution costs, as well as customer satisfaction. The fact that the distribution of goods is being affected by multiple factors, stemming from the demands of transportation companies, customers, and the external environment, has made the vehicle routing problem (VRP) among the most studied topics in operational research. These factors are transformed either to constraints or variables of the problem and finally lead to the creation of different variants of the VRP, formulated and studied by researchers. Moreover, the management of logistics and supply chain operations is being enhanced by the use of algorithms, integrated into information systems, enabling the optimization of real-life distribution cases. This paper presents a methodology for classifying the multiple VRP variants related to freight transportation, that most logistics and distribution companies face in their daily operations, as well as the algorithms solving the various problems. The application of the research methodology concluded to 334 papers, which were further sorted to 263 papers on the subject of freight transportation, aiming to identify the trends of the VRP variants and the applied algorithms, during the last decade. The correlation between the VRP variants and the applied algorithms is also identified. Finally, the paper presents the quantitative and qualitative results of the literature review and discusses the scientific publications with a significant impact on the research community.

Supply Chain Quality and Organizational Performance: Moderating Role of Competitive Advantages

Efficient Supply Chain Management (SCM) has become an extremely flexible means of obtainingmarket advantages and improving company productivity as there is no longer rivalry within firms but supplychains. Such investigations conceptualize and address five facets of SCM practices (supplier strategic alliance,customer relationships, information exchange, efficiency exchange, and postponement) and examine thecorrelation with SCM operations, competitive gains, and organizational outcomes. Data was collected from 232Jordanian individuals, and structural equation analysis was used to assess the connections involved in theresearch. The results indicate that competitive advantages have a small effect on supply chain efficiency andorganizational performance. The comparative edge would therefore specifically and valuably impact corporateperformance. This work provides theoretical evidence to support methodological and prescriptive conclusions onthe consequences of SCM practices in the literature.

What Makes Managers Insource their Production? A Behavioral Experiment

Insourcing as a means to countermand former outsourcing decisions is becoming a widespread practice nowadays, particularly in high-tech manufacturing industries. Researchers have focused on the underlying Operations & Supply Chain Management (OSCM) performance drivers (e.g., lead times, control costs, or responsiveness), while the behavioral aspects underlying insourcing decisions remain less empirically explored. We derive a model grounded in the theory of planned behavior (TPB) to study the effects of managers’ internal and external drivers as well as their interaction on insourcing intentions and behavior. We test our hypotheses in a vignette-based experiment among 145 managers. We find support for the positive effects of attitude and mimetic pressure on insourcing intentions and several interaction effects, both on insourcing intentions and behavior. Our contextualization of motivational drivers provides new empirical insights into the behavioral aspects of insourcing decision making and suggests a theoretical integration between TPB and Institutional Theory in explaining individual decision making. As part of our results, we provide evidence of a unique boundary condition to TPB in the insourcing context, which allows deriving interesting avenues for future inquiry and recommendations for managers considering insourcing.

APPLICATION OF FRACTAL DIMENSION OF FRACTIONAL BROWNIAN MOTION TO SUPPLY CHAIN FINANCING AND OPERATIONAL COMPREHENSIVE DECISION-MAKING

For a long time, the mismatch between material flow and capital flow in the supply chain operation management practice is very prominent, which has led to the inefficiency of supply chain operation and hindered the exertion of supply chain’s advantages. In the field of supply chain management theory research, the information completeness in capital market has long been a hypothetical premise, which has led to the separation of corporate financing and operational decision-making research. In addition to production, inventory, procurement, pricing and other strategies in supply chain operations, payment options and credit incentives are also important decisions for both parties, especially for products with long production and sales cycles; different payment methods directly affect corporate capital flows and the enterprise’s long-term development. On the basis of summarizing and analyzing previous works, this paper analyzed the research status and significance of supply chain financing and operational comprehensive decision-making, expounded the development background, current situation, and future challenges of the fractal dimension of fractional Brownian motion; elaborated the principles and methods of the scaling properties of fractional Brownian motion and the phase space reconstruction of time series, established a financial management analysis model based on the fractal dimension of fractional Brownian motion, performed the analysis of the agglomeration degree, time series and multi-fractal characteristics of supply chain financing, explored the coupling relationship between the comprehensive operational decision-making and Brownian motion’s scaling properties. The final empirical analysis showed that when own funds are sufficient, the production should be carried out with the goal of maximizing profits, and full consideration should be given customer channel stickiness, relative costs of offline and online channel products, and product profitability; the proposed analysis model can achieve the optimal order quantity in supply chain, and reach risk and benefit sharing among financial institutions, retailers, and suppliers by setting the financing interest rate, wholesale price, repurchase price and other parameters, thereby improving supply chain performance. This study results of this paper provided a reference for further researches on the application of fractal dimension of the fractional Brownian motion to the supply chain financing and operational comprehensive decision-making.

When blockchain meets social-media: Will the result benefit social media analytics for supply chain operations management?

Social media analytics is very critical in modern supply chain operations management (SCOM). However, in terms of methods, conducting social media analytics (SMA) for SCOM faces many challenges. Problems such as data accuracy (e.g., fake data), user privacy, data security, etc. are all present. Recently, with the emergence of blockchain technology (BCT), many new social media apps and platforms are developed. Motivated by the fact that (i) SMA is important for SCOM, (ii) the traditional social media (TSM) has insufficiency, and (iii) the “blockchain technology supported social media” (BSM) platforms have emerged, we explore whether and how the BSM would enhance social media analytics for SCOM. To be specific, by reviewing papers published in leading SCOM journals, we identify the applications and limitations of SMA for SCOM. Then, we conduct real case studies to examine the shortcomings of the TSM platforms and reveal features of their BSM counterparts. We investigate how the blockchain technology would potentially improve the use of SMA for SCOM. Finally, a future research agenda is proposed.

Demand-driven supply chain operations management strategies – a literature review and conceptual model

ABSTRACT The literature on demand-driven supply chain operations management strategies (DDSCOMSs) is excellent in describing when, where and how the strategies can be used. However, managers of manufacturing companies usually employ more than one DDSCOMS when designing and operating their supply chains, thus needing to understand when, how and why two or more DDSCOMSs can be used in combination. The answers to these questions are not stated well in the literature. The purpose of this study is therefore to explore the relations among the DDSCOMSs, using a combination of a structured literature review and analytical conceptual research. The study identifies and establishes both direct and indirect relations among the five studied DDSCOMSs. These results assist in nuancing the complex and dynamic relations between the DDSCOMSs, by showing the effects different decisions have on operational performance. The study also points out further research directions, such as the DDSCOMS relations that are under-studied.

Real-time data processing in supply chain management: revealing the uncertainty dilemma

PurposeParticularly in volatile, uncertain, complex and ambiguous (VUCA) business conditions, staff in supply chain management (SCM) look to real-time (RT) data processing to reduce uncertainties. However, based on the premise that data processing can be perfectly mastered, such expectations do not reflect reality. The purpose of this paper is to investigate whether RT data processing reduces SCM uncertainties under real-world conditions.Design/methodology/approachAiming to facilitate communication on the research question, a Delphi expert survey was conducted to identify challenges of RT data processing in SCM operations and to assess whether it does influence the reduction of SCM uncertainty. In total, 14 prospective statements concerning RT data processing in SCM operations were developed and evaluated by 68 SCM and data-science experts.FindingsRT data processing was found to have an ambivalent influence on the reduction of SCM complexity and associated uncertainty. Analysis of the data collected from the study participants revealed a new type of uncertainty related to SCM data itself.Originality/valueThis paper discusses the challenges of gathering relevant, timely and accurate data sets in VUCA environments and creates awareness of the relationship between data-related uncertainty and SCM uncertainty. Thus, it provides valuable insights for practitioners and the basis for further research on this subject.

Exploring Big Data Applications in Supply Chain Operations: A Review Article

The vast growth of Big Data has led to applying analytics in supply chain operations management. With this growth, professionals from various organizations started to understand the value of applying Big Data concepts. This paper reviews some of the advantages of Big Data applications, but mainly in supply chain operations. The researcher relied on review papers related to challenges, issues and benefits of big data analytics in supply chain configurations. More than 20 papers (including literature reviews, research papers, and review articles) were revised by the researcher to summarize the outcomes of what published and discussed by scholars in this field. Lastly, the paper concludes with some recommendations, and highlights the gaps in the current research of applying Big Data in supply chain management.

The Stability and Complexity Analysis of a Low-Carbon Supply Chain Considering Fairness Concern Behavior and Sales Service.

This paper studies a low-carbon dual-channel supply chain in which a manufacturer sells products through the direct channel and traditional channel, and a retailer sells products through the traditional channel. The manufacturer considers carbon emission reduction and has fairness concern behavior. The retailer provides sales service in the traditional channel and considers fairness concern behavior. The objective of this paper is to analyze the effects of different parameter values on the price stability and utility of the supply chain system emphatically using 2D bifurcation diagram, parameter plot basin, the basins of attraction, chaos attractor and sensitivity to the initial value, etc. The results find that the retailer’s fairness concern behavior shrinks the stability of the supply chain system more than that of the manufacturer’s fairness concern behavior. The system stability region decreases with the increase of carbon emission reduction level and the retailer’s fairness concern. The customers’ preference for the direct channel decreases the stable range of the direct channel, while it enlarges the stable range of the traditional channel. The supply chain system enters into chaos through flip bifurcation with the increase of price adjustment speed. In a stable state, the manufacture improving customer’s preference for the direct channel and the retailer choosing the appropriate fairness concern level can achieve the maximum utility separately. In a chaotic state, the average utilities of the manufacturer and retailer all decline, while that of the retailer declines even more. By selecting appropriate control parameter, the low-carbon dual-channel supply chain system can return to a stable state from chaos again. The research of this paper is of great significance to price decisions of participants and supply chain operation management.

A Dynamic Price Game Model in a Low-Carbon, Closed-Loop Supply Chain Considering Return Rates and Fairness Concern Behaviors.

In this paper, we developed a dynamic price game model for a low-carbon, closed-loop supply chain system in which (1) the manufacturer had fairness concern and carbon emission reduction (CER) behaviors, and market share and profit maximization were their objectives, and (2) the retailer showed fairness concern behaviors in market competition and provided service input to reduce return rates. The retailer recycled old products from customers, and the manufacturer remanufactured the recycled old products. The effects of different parameter values on the stability and utility of the dynamic price game model were determined through analysis and numerical simulation. Results found that an increasing customer loyalty to the direct marketing channel decreased the stable region of the manufacturer’s price adjustment and increase that of the retailer. The stable region of the system shrank with an increase of CER and the retailer’s service level, which expanded with return rates. The dynamic system entered into chaos through flip bifurcation with the increase of price adjustment speed. In the chaotic state, the average utilities of the manufacturer and retailer all declined, while that of the retailer declined even more. Changes to parameter values had a great impact on the utilities of the manufacturer and retailer. By selecting appropriate control parameters, the dynamic system can return to a stable state from chaos again. The research of this paper is of great significance to participants’ price decision-making and supply chain operation management.

Modelling wholesale distribution operations: an artificial intelligence framework

PurposeThe purpose of this paper is to propose an artificial intelligence-based framework to support decision making in wholesale distribution, with the aim to limit wholesaler out-of-stocks (OOSs) by jointly formulating price policies and forecasting retailer’s demand.Design/methodology/approachThe framework is based on the cascade implementation of two artificial neural networks (ANNs) connected in series. The first ANN is used to derive the selling price of the products offered by the wholesaler. This represents one of the inputs of the second ANN that is used to anticipate the retailer’s demand. Both the ANNs make use of several other input parameters and are trained and tested on a real wholesale supply chain.FindingsThe application of the ANN framework to a real wholesale supply chain shows that the proposed methodology has the potential to decrease economic loss due to OOS occurrence by more than 56 percent.Originality/valueThe combined use of ANNs is a novelty in supply chain operation management. Moreover, this approach provides wholesalers with an effective tool to issue purchase orders according to more dependable demand forecasts.

The Complexity Analysis for Price Game Model of Risk-Averse Supply Chain Considering Fairness Concern

This paper, considering risk aversion and fair concern, establishes a dynamic price game model of a dual-channel supply chain in which dual-channel retailer sells products through traditional channel and online channel and the online retailer only sells products through online channel. The stability of the system and the influences of different parameter values on utilities are analyzed emphatically using game theory and nonlinear dynamic theory, such as 2D and 3D bifurcation diagram, parameter plot basin, chaos attractor, and sensitivity to initial value. The results find that the system is more likely to lose stability and fall into chaos with the customer demand fluctuating greatly. The system enters into chaos through flip bifurcation with the increase of the price adjustment speed; adjusting the risk-aversion levels or the fairness concern levels of the two retailers can make the system be in a stable state or delay the occurrence of system instability. When the system is in chaos, the average utility of the online retailer will decrease and one of the dual-channel retailers will increase. Using the state feedback control method, the system can return to a stable state from chaos by selecting appropriate control parameters. The research of this paper is of great significance to the decision-makers’ price decision and supply chain operation management.

INTEGRATING SUSTAINABILITY INTO SUPPLIER SELECTION: A GREY-BASED TOPSIS ANALYSIS

Sustainable supplier selection plays an important role in sustainable supply chain management operations and implementation. In this paper a novel formal modeling approach is conceptually developed and presented to address sustainable supplier selection. Grey theory and TOPSIS, a distance based multiple criteria method, are used for the integration and evaluation of sustainable supplier performance for sustainable supplier selection. From a research perspective, TOPSIS is improved to more effectively deal with grey numbers by integrating a degree of likelihood rather than converting grey numbers into crisp numbers functions, and it provides more flexible supplier rankings. This methodology strengthens the sustainable supplier selection process, and can be applied to other multiple criteria decision making problems. Illustrative calculations are made using data on sustainable supplier selection and evaluation published by Bai and Sarkis (2010). The technique is relatively accurate, matching well with results from a published grey rough set approach. The methodology easily implementable with minimal complex calculations required. It can also provide support for sustainable supplier selection, benchmarking, and improvement decisions. This is one of the first papers to integrate a broad set of sustainability factors for grey-based TOPSIS and supplier selection.