Supply Chain Responsiveness Research Articles

Unearthing the relationship between supply chain social capital and firm performance: the role of supply chain responsiveness

PurposeThis paper examines the nexus between supply chain social capital (relational social capital and structural social capital), supply chain responsiveness (operations system responsiveness and supplier network responsiveness) and firm performance. Additionally, the study examines the mediating role of supply chain responsiveness on the relationship between supply chain social capital and firm performance.Design/methodology/approachThe authors test their hypotheses on a sample of 120 firms operating in Ghana. The measurement model and hypothesized paths were assessed using partial least squares structural equation modelling.FindingsThe findings revealed that structural social capital had a significant direct effect on firm performance, but relational social capital did not. It was also revealed that both relational and structural social capital have significant effects on operations system responsiveness and supplier network responsiveness. Additionally, operations system responsiveness fully mediated the effect of relational social capital on firm performance and partially mediated the effect of structural social capital on firm performance. Supplier network responsiveness, on the other hand, partially mediated the effect of both relational and structural social capital on firm performance.Originality/valueThis study contributes to the limited literature on supply chain social capital by unearthing the mechanisms through which supply chain social capital enhances firm performance. Specifically, the study demonstrates the intervening role of operations system responsiveness and supplier network responsiveness in the supply chain social capital–firm performance link.

Blockchain technology adaptation and organizational inertia: moderating role between knowledge management processes and supply chain resilience

PurposeSupply chain resilience and knowledge management (KM) processes have received increasing attention from researchers and practitioners. Nevertheless, previous studies often treat the two streams of literature independently. Drawing on the knowledge-based theory, this study aims to reconcile these two different streams of literature and examine how and when KM processes influence supply chain resilience.Design/methodology/approachThis research develops a conceptual model to test a sample of data from 203 Chinese manufacturing firms using a structural equation modeling method. Specifically, the current study empirically examines how KM processes affect different forms of supply chain resilience (supply chain readiness, responsiveness and recovery) and examines the moderating effect of blockchain technology adaptation and organizational inertia on the relationship between KM processes and supply chain resilience.FindingsThe findings show that KM processes positively affect three dimensions of supply chain resilience, i.e., supply chain readiness, responsiveness and recovery. Besides, the study reveals that blockchain technology adoption positively moderates the relationships between KM processes and supply chain resilience, whereas organizational inertia negatively moderates these above relationships.Originality/valueThis research linked the two research areas of supply chain resilience and KM processes, further bridging the gap in the research exploration of KM in the supply chain field. Next, this study contributes to supply chain resilience research by investigating how KM systems positively impact supply chain readiness, responsiveness and recovery. In addition, this study found a moderating effect of blockchain technology adaption and organizational inertia on the relationship between KM processes and supply chain resilience. These findings provide a reference for Chinese manufacturing firms to strengthen supply chain resilience, achieve secure supply chain operations and gain a competitive advantage in the supply chain. This studys’findings advance the understanding of supply chain resilience and provide practical implications for supply chain managers.

Process modularity, supply chain responsiveness, and moderators: The Médecins Sans Frontières response to the Covid-19 pandemic.

The unprecedented scale of the Covid‐19 pandemic has been a challenge for health supply chains around the world. Many international humanitarian organizations have had to ensure the continuity of their already complex development programs, while addressing their supply chain disruptions linked to the pandemic. Process modularity has frequently been advocated as a strategy to mitigate such disruptions, although empirical evidence regarding its impact on supply chain responsiveness and what moderates this impact is scarce. This exploratory research uses supply chain data analysis, qualitative content analysis, interviews, and a three‐round Delphi study to investigate how Doctors without Borders (Médecins Sans Frontières; MSF) and its 151 missions employed process modularity during the Covid‐19 pandemic. Our results show that despite severe disruptions, process modularity—based on a modular architecture, interfaces, and standards—has helped MSF maintain supply chain responsiveness. Specifically, it (1) enabled time‐consuming, nonessential tasks to be skipped, (2) relieved internal and external bottlenecks, and (3) facilitated better allocation and prioritization. Our analyses also put forward eight moderators, structured in three dimensions (visibility, alignment, and resource orchestration), which can affect the impact of process modularity on supply chain responsiveness. We extend the literature on supply chain responsiveness and process modularity by presenting extensive empirical results suggesting that process modularity improves responsiveness in crisis situations, how it does so, and what moderates this impact. Our study thereby highlights the potential of this strategy and provides operationally relevant insights that could help organizations to implement or to review and redesign their process modularity.

Supply Chain Response during the COVID-19 Pandemic: A Multiple-Case Study

This study explores the responses of manufacturing and service provision companies in Santiago de Cali to stimuli during the COVID-19 pandemic. The responses included changes in demand, absenteeism, and the development of new products, which affected the supply chain (SC). The qualitative methodology of the multiple-case study was used. The evidence for the multiple-case studies was collected through semi-structured interviews, where the interviewees were SC experts from four manufacturing companies and one service company. The data analysis was performed in two phases. In phase one, the case study protocol was completed, and in phase two, thematic analysis was used to identify supply chain response (SCR) patterns. The results revealed two aspects of the SCR. First, to respond to a stimulus, SC adapted activities other than those of suppliers and manufacturers, such as product design and development, human resources, budgeting, and logistics. Second, the SCs used several alternatives to respond to the stimuli. This study contributes to two aspects of the SCR literature: (1) it documents the identification, detection, planning, and evaluation of SCR in response to a stimulus, and (2) it proposes the concept of the response alternatives. The response alternatives concept facilitates decision-making and resource management in SCR.

The impact of the COVID-19 pandemic on global trade-embodied carbon emissions

We evaluate the response of global supply chains to carbon emissions through compiling multi-regional input-output (MRIO) models for import and export shocks in 14 countries/territories dominated by the COVID-19 crisis. Instead of traditional production-based inventories, we achieve CO2 emissions inventories based on intermediate inputs and final consumption to analyze the connected environmental impacts. In addition, we adopt the available data up to date to construct inventories of carbon emissions involved in imports and exports from different sectors. The results show that global carbon emissions could be decreased by 6.01% during the COVID-19, while export carbon emissions remained basically unchanged. As a result, imported carbon emissions fell by 5.2%, with the energy products sector most affected by the pandemic. Transport sector witnessed 18.42% carbon emission reduction. The impact of developing countries with a large proportion of resource-based industries is comparatively higher than that of developed countries with the technological advantage. International trade plays a crucial role in the choice of supply chain partners to control carbon emissions. Building a sustainable supply chain and reducing the “trade carbon deficit” between countries/regions requires the coordination of all departments of each country/region to promote the trade of energy-saving products, environmental protection services and environmental services.

Building responsive and resilient supply chains: Lessons from the COVID‐19 disruption

Building responsive and resilient supply chains: Lessons from the <scp>COVID</scp>‐19 disruption

Study on the optimization of Chinese automotive supply chain under unstable environment

As a pillar industry of the national economy, the automobile industry is one of the fundamental forces in driving domestic demand and promoting economic growth. With the spread of the epidemic worldwide, various parts of the automotive supply chain have been disrupted. The current “supply cut-off” crisis in the auto industry has begun to receive widespread attention, and the impact on the global auto industry chain has already started to emerge. In the face of the increasingly unstable environment, it is worth exploring what impact the epidemic has had on the automotive supply chain, what risks are there for vehicle manufacturers and component manufacturers, and what insights this epidemic has for the upgrading and long-term development of corporate supply chain systems. Based on this, this paper will share some preliminary thoughts on the short-term supply chain response suggestions and long-term supply chain system construction in light of the epidemic from the supply chain perspective.

PENGUKURAN KINERJA MANAJEMEN RANTAI PASOK PADA CV. BERAS PUSPA JOGED BALI

Supply chain management is the integration of the production process, starting from the procurement of raw materials and ending with the delivery of products to consumers. The implementation of this system affects the company's overall performance, so it is necessary to measure performance to determine the productivity that has been achieved. This research was conducted on CV. Beras Puspa Joged Bali, which sometimes suffers from a shortage of production raw materials, so it is necessary to bring them in from outside the Bali area with greater risk during expeditions. This study aims to determine the performance of supply chain management CV. Beras Puspa Joged Bali, which includes supply chain reliability, responsiveness, cost, and asset management performance. Interview and observation methods are used to get the data, as well as data analysis methods that use the Supply Chain Operations Reference (SCOR) model. The calculation results show the Perfect Order Fulfillment (POF) metric value of 99.88%, the Order Fulfillment Cycle Time (OFCT) metric for 3 days, the Cost of Goods Sold (COGS) metric of 86%, and the Cash to Cash Cycle Time (CTCCT) metric for 20 days

Big data analytics in flexible supply chain networks

Supply chain responsiveness and Big Data Analytics (BDA) have incited an ample amount of interest in academia and among practitioners. This work is concerned with improving responsiveness in supply chain networks by extending production capacity to cope with changes and variations in demand. BDA helps researchers make sense of the current challenges of data: high volume, high velocity, and high variety. In this work, we will look at sales data and at large warehouses, which envelop all the said three characteristics of Big Data (BD). This is quite important as demand market data is increasingly shared with supply chain managers. Here, a working architecture is introduced to handle the challenges of BD. The work uses a neural network to detect patterns within the demand. The work combines deep learning with nonlinear programming to enable flexibility at supply chain production facilities to respond to the forecasted demand. The parameters in the neural network are analyzed and studied for each different product type. We see significant prediction improvements when the parameters are better tuned. Further, the work introduces a BD architecture that automates the acquisition of the data, data mining, and the storage of input and output files. Overall, the work utilizes a gradient search method, a genetic algorithm, ARIMA, a deep learning algorithm, and a mixed-integer nonlinear program.

Towards a Responsive Resilient Supply Chain based on Industry 5.0: A Case Study in Healthcare Systems

&#x0D; Executives and academics have presented the idea of Industry 5.0, which is an attempt to build upon the previous iteration, Industry 4.0, by including many important tenets such as human-centricity, resilience, and sustainability. Because of the significance of this idea, the current study provides a decision-making framework to examine a responsive supply chain dubbed responsive supply chain 5.0 for healthcare systems. This framework takes into consideration the aspects of Industry 5.0. In order to do this, at the onset, the most important connected factors and strategies are determined by consulting the relevant experts and body of published research. This problem has been considered a multi-criteria decision-making (MCDM) problem. Initially, the DEMATEL method was used to assess and prioritize the main criteria and their sub-indicators. Secondly, the CRADIS method was used to evaluate and rank the strategies used to make the supply chain more responsive. The results indicate that the collaboration and sharing of information strategy is the most appropriate strategy if applied.&#x0D;

Keep concentrated and carry on: redesigning supply chain concentration in the face of COVID-19

ABSTRACT The global COVID-19 outbreak has led to significant challenges for supply chain management, while insights on how to configure the supply chain network to respond to this crisis are limited. Therefore, the present research extends the understanding of supply chain resilience by investigating whether supply chain concentration has influenced the shock of COVID-19 on firm performance. This study assesses four sub-dimensions of supply chain concentration: supplier, customer, product, and region. Based on a large-scale sample of Chinese listed manufacturing firms, we employed a difference-in-difference approach to investigate whether supply chain concentration ameliorated or exacerbated the shock of COVID-19. The results indicate that treatment groups (firms with lower supplier, customer, product, and region concentration) have experienced a considerably more significant performance deterioration than control firms. Overall, this study paves the way for future research and offers vital insights into the redesign of supply chains in response to COVID-19 and similar crises.

Simulation of Supply Chain Performance in the Period of Implicit Uncertainty using Cellular Automata

Managing a distribution planning problem in an integrated supply chain environment is daunting. These challenges are aggravated when there are multiple stakeholders involved. The proposed simulation model provides an environment to gauge the existing adversities in the distribution plan of a two-stage supply chain (SC) network. In addition to the underlined issues, the model captures the influence of decisions from neighboring firms in a periodical decision-making plan. A cellular automaton (CA) based approach is implemented to present the complete analysis and impact of endogenous and exogenous situations affecting the decision-making. The decision environment involves two states of selecting an efficient supply chain strategy (ESC) and responsive supply chain strategy (RSC) based on the implicit uncertainty and performance of Moore-based neighboring cells. The study contributes to the scant literature on the application of CA-based evolutionary decisions in the SC context. The simulation model characterizes the neighboring firm's influences in strategic decision-making and the implicit uncertainty in supply and demand. The modeling framework is tested with a significantly larger set, and the results are graphically presented to provide further clarity.

How risk, transparency, and knowledge influence the adaptability and flexibility dimensions of the responsiveness view

Supply chain transparency is an underdeveloped area in the literature. Accordingly, this manuscript explores supply chain transparency, its relationship to risk management and knowledge creation, and its value chain application from a Responsiveness View of logistics and supply chain management. Specifically, we examine supply chain transparency as an important antecedent to responsiveness, considering strategic dimensions of adaptability (structural adjustment) and flexibility (policy adjustment). Drawing on the responsiveness and knowledge-based views, a model is proposed and evaluated using data collected from supply chain professionals. The results reveal that supply chain transparency drives knowledge creation and mediates the relationship between a firm’s risk management and responsiveness. Specifically, transparency and knowledge creation partially mediate the relationship between flexibility and risk management.The concept of supply chain transparency is discussed as a mechanism to translate information collected and disseminated as knowledge within a partnership, leading to the development of tangible capabilities. Our research builds an introductory model of strategic considerations important to further exploring theory related to supply chain responsiveness.

Proposed Improvement of Pertalite Fuel Outbound Logistics Performance to Achieve Pertamina Patra Niaga MS2 Compliance (A Case Study of Bandung City)

PT. Pertamina Patra Niaga was founded in 2004, is a sub-holding of PT. Pertamina which handles Pertamina’s downstream oil and gas processes, especially fuel trading and handling, as well as fleet and depot management. This study took Fuel Terminal Bandung Group – Ujung Berung as a research location which encounter issue related to the not achieved of the MS2 Compliance target in delivery time delay related to the external logistics performance. This research focuses on the delivery of Pertalite fuel in the city of Bandung in the third quarter of 2022. This study aims to identify the factor that affect the value of MS2 Compliance in Fuel Terminal Bandung Group-Ujung Berung and initiate the improvement initiatives to improve outbound logistic performance for Fuel Terminal Bandung Group – Ujung Berung. The conceptual framework used in this research describes the supply chain design and focuses on outbound logistics in terms of moving the final product to the retailers to achieve responsive supply chain strategy is improving the outbound logistic performance. The equipment that used to carry the delivery are tank trucks. The method used in this study uses a quantitative approach with heuristic methods using a sweep algorithm. Quantitative data were obtained from company data, observations at the company and interviews with departments that related to the company’s logistics. Secondary data analysis using literature and company data. The analysis was carried out by finding the root of the problem with a fishbone diagram and analysing quantitative data with a sweep algorithm. The analysis is carried out by taking days that have low MS2 Compliance in Quarter III 2022 in one week, where one day has three delivery batch. From the results of the analysis, it was found that there were four main causes, namely method, environment, human, and equipment factors. Then examine by the sweep algorithm analysis which results in more effective route selection and maximizing the use of tank trucks by calculating the travel time for each shipment by considering the allowance time for each shipment.

Uncertainty, responsiveness and operational performance in supply chain: a conceptual study using contingency theory approach

Amid uncertainty from customers and suppliers, academicians and practitioners have focused on building a supply chain that is robust enough to withstand the disruption damages. Given the several supply chain risk mitigation strategies like flexibilities, agility and postponement, this is the first such paper to analyse the relationship between supply chain responsiveness and supply chain uncertainty through contingency theory lenses. To arrive at a conceptual framework that aims to build the relationship among the constructs, this study in detail has studied the literature of selected articles on supply chain uncertainty from peer-reviewed journals. Findings not only draw attention to the role of responsiveness in the supply chain under uncertainty but also indicate towards analysing the effect of the relationship between uncertainty and performance. Therefore, we believe that supply chain responsiveness, being a mediator in the framework presented, might lessen the impact of supply chain uncertainty on operational performance.

Modeling 4Ps of Toyota way principles in MSMEs supply Chain-an empirical approach

Micro, Small & Medium Enterprises (MSMEs) have witnessed many remarkable contributions to the country's economy in the recent years. But, till now it suffers from profit, quality, efficiency and others issues. The previous contributions by researchers have enlightened on the MSMEs in the context of applying lean principles. This paper aim to guide MSMEs in embarking on transformation exercise by means of applying principles and tools of lean to its supply chain. And, also to establish the relationship between application and understanding of relevance of lean principle model for MSMEs. It is observed that to be successful in the market, competition is not between one company to another company but, between one supply chains to the other supply chain. Company’s competitive strategy is best supported by balance between the supply chain responsiveness and efficiency. So, the scale of this paper is not just restricted to MSMEs but to its entire supply chain. In this epidemic situation, companies are facing a high risk of surviving in the market. The interlinked nature of the supply chain makes them vulnerable to wide range of risk, as the buying patterns of the consumers across the supply chain is changing rapidly due to unpredictable situation. So, to sustain in the market, competition is to see how efficiently the entire process is set by implementing lean principles. The exact need and area of implementation of 4Ps of Toyota way principles are done to entire supply chain of MSMEs Finally; gap that exists in applying and relevance of 14 Toyota way principles for the MSMEs in taking care and how, lean principles to become more effective during pandemic situation is reflected. A structured questionnaire was prepared on 4Ps of Toyota way, with its predefined attributes and data was collected from MSMEs through survey forms. The quantitative data collected was outlined to rank the 14 principles applied in the MSMEs supply chain, and also the extent of perceiving their relevance. The results reflected that all the attributes of each 4Ps model were appreciated by the respondents for their relevance, but still many of them lack in application.

Predicting Bike Usage and Optimizing Operations at Repair Shops in Bike Sharing Systems

Supply chain responsiveness and big data analytics (BDA) have garnered considerable interest in academia and among practitioners. BDA helps researchers understand the current challenges in data management, including the high volume, velocity, and variety of data. This study is concerned with improving the responsiveness of supply chain networks to bike-sharing systems (BSS), which exhibit BDA characteristics. To address the challenges of forecasting bike usage and accordingly optimizing repair shop operations, we analyze multi-factor BSS data (Data from Washington D.C. BSS available to public), wherein attributes, such as weather conditions, registration, humidity, date, and time, are present. We use machine learning algorithms, such as neural networks, decision-tree-based regression, K-nearest neighbor, support vectors, and ensemble random forest, to predict bike usage and repair. This work contests the results and demonstrates the effectiveness of combining machine learning with supply chain network design. Supply chain networks model bike repairs by means of capacity extensions, which entails a nonlinear problem. In this study, we utilize a gradient search to solve a nonlinear supply chain network model. By enabling capacity extension, bike repair shops within the BSS exhibit a promising 50 % reduction in lead repair time. Furthermore, a 25 % overall throughput increase in BSS is achieved. Ultimately, this study demonstrates the importance of operational flexibility in responding to big data challenges.

Modelling of RFID-enables jewellery hallmark transparency attributes inter-relationship and ranking performance criterion in Supply chain Responsiveness: Using ISM-AHP Approach

Modelling of RFID-enables jewellery hallmark transparency attributes inter-relationship and ranking performance criterion in Supply chain Responsiveness: Using ISM-AHP Approach

The moderating effect of farming contracts on the relationship between responsive supply chain elements and supply chain resilience

Food supply chain disruptions have of recent increased in terms of severity and frequency leading to viability problems for most businesses in related supply chain networks and hunger among millions of human beings. In the extant supply chain literature elements of responsive supply chain such as velocity, versatility, and visibility have been suggested as some of the possible strategies to build supply chain resilience. It has therefore been suggested in this study that these elements’ influence on supply chain resilience is moderated by contract farming as a special form of supplier development. Farming contracts are either production or marketing contracts. Data was collected from a conveniently selected sample of 200 restaurants that use supplier development in the form of contract farming for acquiring critical resources for their operations. A structural equation modelling was used to analyse data related to the direct effects and multi group structural equation modelling was used to assess the moderating effects. The results revealed that there is a statistically significant relationship between the three selected elements of responsive supply chain management and supply chain resilience, and all the hypothesised relationships were moderated by type of farming contracts, with the relationships being stronger under marketing contracts for supply chain velocity, and under production contracts than under marketing contracts for relationships involving versatility and visibility. Therefore, the study recommended that production contracts be used in the fast-food restaurant industry in order to reduce supply chain vulnerabilities, and marketing contracts to build supply chain capabilities. This is the first study that has sought to assess the differential utility of different farming contracts through assessing their moderating effects as a build-up on previous research that has already established that supplier development in the form of contract farming leads to supplier development.

Modelling a framework of RFID-enabled transparency in Jewellery Supply Chain Responsiveness: Using ISM Methodology.

Modelling a framework of RFID-enabled transparency in Jewellery Supply Chain Responsiveness: Using ISM Methodology.