Supply Chain Management Decisions Research Articles

Addressing uncertainty in closed-loop supply chain networks: a multi-objective approach to integrated production and transportation problems

Purpose This study aims to address the inherent uncertainties within closed-loop supply chain (CLSC) networks through the application of a multi-objective approach, specifically focusing on the optimization of integrated production and transportation processes. The primary purpose is to enhance decision-making in supply chain management by formulating a robust multi-objective model. Design/methodology/approach In dealing with uncertainty, this study uses Pythagorean fuzzy numbers (PFNs) to effectively represent and quantify uncertainties associated with various parameters within the CLSC network. The proposed model is solved using Pythagorean hesitant fuzzy programming, presenting a comprehensive and innovative methodology designed explicitly for handling uncertainties inherent in CLSC contexts. Findings The research findings highlight the effectiveness and reliability of the proposed framework for addressing uncertainties within CLSC networks. Through a comparative analysis with other established approaches, the model demonstrates its robustness, showcasing its potential to make informed and resilient decisions in supply chain management. Research limitations/implications This study successfully addressed uncertainty in CLSC networks, providing logistics managers with a robust decision-making framework. Emphasizing the importance of PFNs and Pythagorean hesitant fuzzy programming, the research offered practical insights for optimizing transportation routes and resource allocation. Future research could explore dynamic factors in CLSCs, integrate real-time data and leverage emerging technologies for more agile and sustainable supply chain management. Originality/value This research contributes significantly to the field by introducing a novel and comprehensive methodology for managing uncertainty in CLSC networks. The adoption of PFNs and Pythagorean hesitant fuzzy programming offers an original and valuable approach to addressing uncertainties, providing practitioners and decision-makers with insights to make informed and resilient decisions in supply chain management.

Post-dictatorship Protest and Ecocriticism in Selected Works of Ogaga Ifowodo

The principal link between technology and competitive advantage is innovation. The quest for sustainable competitive advantage has caused firms to invest in innovation, consequently, innovation is responsible for new industries coming into being, and it is innovation, which allows some firms to dominate in that space. Thus, this study aimed to examine the critical supply chain (SC) innovation indicators that enhance business performance. This research study centred on the operational activities of the Weir Minerals Africa (WMA) Isando facility in Johannesburg, South Africa, including all elements associated with the supply chain activities of the plant. The study sample of 230 respondents was considered representative of the population. The philosophical worldview in this research is positivism. Positivism hinges on computable observations that lead to statistical interpretations. The study was quantitative, adopted the deductive research approach, and a set of hypotheses were formulated for the research to confirm or reject a theory. For this population, the researcher applied a census-based sampling approach. The results showed that there is a significant number of indicators that enhance business performance and these include a clear culture of continuous improvement, focusing on new markets both locally and globally, product portfolio changes, constant connection and engagement with customers and cost structures. In light of these findings, the study provided a set of recommendations. Weir Minerals has a significant number of supply chain innovation hubs and metrics that include improvement and innovation culture across the entire organisation, an aggressive drive to create new markets and a clear posture to enforce standards and consistent value to its customers. However, it has not made a significant and noticeable effort to connect regularly with its customers. It has to improve on its customer relationship management frontier. The study findings underscored the relevance of a holistic overview of the supply chain problems at Weir Minerals Isando (WMI) that may inform the supply chain management decisions and expand academic knowledge. Keywords: Supply Chain Innovation, Supply Chain Management, Sustainable Business Performance

Critical Supply Chain Innovation Indicators that Enhance Business Performance: A Case Study of Weir Minerals Africa

The principal link between technology and competitive advantage is innovation. The quest for sustainable competitive advantage has caused firms to invest in innovation, consequently, innovation is responsible for new industries coming into being, and it is innovation, which allows some firms to dominate in that space. Thus, this study aimed to examine the critical supply chain (SC) innovation indicators that enhance business performance. This research study centred on the operational activities of the Weir Minerals Africa (WMA) Isando facility in Johannesburg, South Africa, including all elements associated with the supply chain activities of the plant. The study sample of 230 respondents was considered representative of the population. The philosophical worldview in this research is positivism. Positivism hinges on computable observations that lead to statistical interpretations. The study was quantitative, adopted the deductive research approach, and a set of hypotheses were formulated for the research to confirm or reject a theory. For this population, the researcher applied a census-based sampling approach. The results showed that there is a significant number of indicators that enhance business performance and these include a clear culture of continuous improvement, focusing on new markets both locally and globally, product portfolio changes, constant connection and engagement with customers and cost structures. In light of these findings, the study provided a set of recommendations. Weir Minerals has a significant number of supply chain innovation hubs and metrics that include improvement and innovation culture across the entire organisation, an aggressive drive to create new markets and a clear posture to enforce standards and consistent value to its customers. However, it has not made a significant and noticeable effort to connect regularly with its customers. It has to improve on its customer relationship management frontier. The study findings underscored the relevance of a holistic overview of the supply chain problems at Weir Minerals Isando (WMI) that may inform the supply chain management decisions and expand academic knowledge. Keywords: Supply Chain Innovation, Supply Chain Management, Sustainable Business Performance

Application of fuzzy analytic hierarchy process – multi-layer fuzzy inference system in product design evaluation

To enhance profitability of production cycle, any manufacturer needs effective product design and evaluation procedures. This study proposed a novel approach combining fuzzy analytic hierarchy process (FAHP) and multi-layer fuzzy inference system (MFIS). It is based on consumer online comments to improve product design. This method possesses several advantages over traditional design evaluation methods. It can quickly acquire consumer preferences, effectively handle multi-criteria decision problems and integrate uncertain and fuzzy information. The Fuzzy Analytic Hierarchy Process–Multi-layer Fuzzy Inference System (FAHP-MFIS) involves the following steps: screening of factors, hierarchical modeling, quantification of qualitative factors, and conversion of these factors into quantitative values. It is a knowledge-based system that uses logical rules. The quantity and levels of input variables directly correlates with the quantity of logical rules. However, with multi-factor and multi-level inference, the establishment of a rule base becomes impractical due to the overwhelming number of rules. To address this issue, the Taguchi orthogonal table is applied to reduce the number of logical rules. Taking a household oxygen generator for medical devices as an example, the proposed model is applied in real-time. In the first stage, web crawlers are used to collect user reviews of the household oxygen generators on large e-commerce platforms. Latent Dirichlet Allocation (LDA) models are used to screen for principal and sub-factors in the second stage. Then, sub-factors of the FAHP screening are used as inputs, and the principal factors are used as outputs. In the third stage, priority indicators are established based on principal factors such as Appearance, Basic Function, and Advanced Function. Established evaluation models are then used to rank the selected designs. The results show that the higher the priority index value of the product design scheme, the better the scheme, and vice versa. This study holds significant reference value in aiding enterprises to enhance the efficiency of their manufacturing cycle and determining the direction of product design and innovation with improved pace and accuracy. Moreover, it can be applied to other fields such as supply chain management, risk assessment, and investment decisions.

Management accounting and control, supply chain resilience and healthcare performance under disruptive impact

PurposeBuilding supply chain (SC) resilience has become a priority for many organizations, following a global increase in disruptive events. While management accounting and control (MAC) systems play a supportive role in supply chain management (SCM) decisions, little is known about the contributions offered to resilience decisions in service organizations. The purpose of this study is to examine the performance implications of MCS's impact on proactive and reactive resilience of healthcare supply chains.Design/methodology/approachThis study conducted a survey of 127 public health managers via structural equation modeling. The partial least squares version 3.3.3 was used.FindingsThe results show a statistically positive impact of MAC dimensions on proactive and reactive resilience, which in turn impacts the quality, delivery speed and cost effectiveness of the health SC. However, the integration dimension had an insignificant effect on reactive resilience but a positive effect on proactive resilience.Research limitations/implicationsThis study examined the performance implications of MAC system dimensions and proactive and reactive resilience on operational performance in health SCs, using empirical data from only one country. Thus, generalizing the findings to include other jurisdictions may be impossible.Practical implicationsHealthcare managers in public health facilities should embrace the four MAC dimensions (except the integrated dimension in reactive resilience) to support information generation in SC resilience decisions.Originality/valuePerhaps, the first to provide preliminary empirical evidence on the interactive effect of proactive and reactive resilience and MAC dimensions in terms of broad scope, timeliness, integration and aggregation on health SC operational performance under disruption, in the context of an emerging economy.

A multi-criteria decision-making model for analyzing a project-driven supply chain under interval type-2 fuzzy sets

Reviewing and integrating decisions in the supply chain and project management is crucial. This problem is known as a project-driven supply chain problem. By the growing dependency of project-driven companies on suppliers since they prefer to concentrate on their core and subcontracting processes, the project-based organization's dependence on suppliers has increased. A project-driven supply chain (PDSC) focuses on integrating project management activities into the supply chain. In this paper, a new model is presented for the integration of supply chain and project management decisions. Firstly, a new method is proposed to determine the resilience score of suppliers. This new model consists of three parts: the weighting of criteria, the weighting of experts, and the ranking of suppliers. To give weight to the experts, a new version of the combinative distance-based assessment (CODAS) method is presented based on the average and positive ideal concepts. Also, the importance of the criteria is specified by an expanded best-worst method (BWM). Computing the resilience score of suppliers is done through a developed CODAS method that is extended by the average and positive concepts. Furthermore, in order to consider the uncertainty of project-driven supply chain problems, interval type-2 fuzzy sets (IT2FSs) are used. Secondly, a new subtraction operation is defined to avoid producing negative in recursive critical path method (CPM) calculations in the IT2F environment. Also, the criticality score of the project's activities is defined. According to the criticality and resilience indexes of activities, suggestions are made to project management to prevent delays. Finally, a case study of hospital construction is solved to illustrate the strengths of the proposed model.

The role of absorptive capacity and big data analytics in strategic purchasing and supply chain management decisions

Big data analytics (BDA) is widely used in sales, marketing, distribution, and finance; however, its implementation in supply chain management, specifically in purchasing and supply management (PSM), has been slow and uneven. This study investigates the impact of BDA on strategic PSM decisions and how it interacts with a company's absorptive capacity. We conducted a survey of 222 purchasing and supply chain managers in international companies across various industries. Using structural equation modeling, we found that the exploration, assimilation, and transformation capabilities of purchasing departments are crucial in facilitating the use of BDA for strategic decision-making in PSM. Companies that excel in BDA in the PSM space are better equipped to capitalize on new and existing knowledge sources, which improves their performance. However, only businesses with the right resources can fully leverage BDA for high-level strategic decision-making; when BDA is applied to operational PSM activities, the desired effects may not be achieved.

SUPPLY CHAIN MANAGEMENT CONTRIBUTION TO ORGANISATIONAL SUSTAINABILITY

Sustainability is an element that is increasingly considered within the organisation. Therefore, the aim of this scientific article is to explore the contributions of supply chain management (SCM) to organisational sustainability. The study was based on a closed-ended question distributed to strategic managers from eleven business sectors, and the answers to this question were selected according to our objectives and grouped to generate six questions that were applied through a questionnaire to a total of 220 companies from the three economic sectors, companies that have implemented sustainable SCM practices. The main findings from the descriptive analysis used for the data show that sustainability practices integrated into SCM, such as sustainable sourcing, green design, and supply chain loop. Improving relationships with suppliers and customers by promoting closed-loop corporate social responsibility (CSR) values has a positive impact on organisational sustainability. These practices reduce environmental impact, improve financial performance, enhance reputation, and increase stakeholder satisfaction. The main conclusion of this study is that the adoption of sustainable SCM practices is critical to organisational sustainability. Organisations must prioritise sustainability in their SCM decisions to ensure their long-term success.

The role of operations and supply chain management during epidemics and pandemics: Potential and future research opportunities

Epidemics have been posing significant challenges to health, existence, and continuity. From the emergence of an outbreak to its elimination, managing an epidemic/pandemic entails many operations and supply chain management decisions that can contribute to a lessening of its impact. With these decisions, epidemic-/pandemic-imposed challenges related to forecasting, planning, supply, manufacturing, storage, and transportation can be addressed in an effort to curtail and end the epidemic/pandemic. We have witnessed these disruptions first-hand during the COVID-19 pandemic, which has had a destructive effect on many well-established supply chains, threatening the existence of firms. The role of operations and supply chain management is thus pivotal for navigating epidemics/pandemics. Against this background, we present a systematic literature review on the role of operations and supply chain management during epidemics and pandemics, illustrating its potential and calling for future research. Leveraging bibliographic coupling analysis, we identify major research areas and contributions that serve as a foundation to propel these domains forward. We further critically review these research areas, identifying multiple themes of which many have been perennially relevant, while others have come to the fore only recently due to the COVID-19 pandemic. Our review provides an integrative view of the field, concurrently advancing theory, and offering ten distinct future research directions. Overall, this paper is meant to serve as a starting point for researchers in operations and supply chain management aiming to investigate this increasingly important domain.

Integration of RFID strategic value attributes mechanism decision in apparel supply chain: fuzzy AHP-TOPSIS approach

PurposeThe purpose of this paper is to identify the radio frequency identification (RFID) strategic value attributes (RFIDSVAs) mechanism selections preferences and also integration of RFID tags with technology coordination tools (IRTWTCTs) alternatives ranking performance decisions in supply chain management (SCM). RFID-enabled techno-economic feasibility decisions are enhancing the SC visibility in apparel supply chains (ASCs). The RFIDSVAs mechanism selections have performed significant agility to strategic competitive advantages, namely, inventory visibility, multi-tags ownership transfer within trusted third party, etc.Design/methodology/approachFuzzy analytical hierarchy process (FAHP) and FAHP-fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) approaches have been used to evaluate the quantitative assessment of RFIDSVA mechanisms selection decision based on weight priority orders and IRTWTCTs alternatives selection in ASC networks. The comparison of FAHP and FAHP-FTOPSIS approaches to evaluate the integrated framework develop in RFIDSVAs mechanisms and IRTWTCTs alternatives selection decisions in Indian multi-tier ASC networks.FindingsThe result found that the FAHP-FTOPSIS approaches have used to prioritizing the RFIDSVA mechanism selection weights and also identify the IRTWTCTs alternatives ranking preferences order in apparel SCM. The comparison between the FAHP and FAHP-FTOPSIS approach to quantitative assessments from RFIDSVA mechanisms and IRTWTCTs alternatives selection decisions, which enable them SC agility potential across multi-tier visibility in ASC networks. ASC stakeholders can be benefited by techno-economic feasibility decisions, RFID-enabled shop floor activities, multi-tags ownerships transfer in SCs and knowledge-based cryptography tags/items separation in SCs.Research limitations/implicationsThe research work has considered only five RFIDSVA mechanisms and also three integration of RFIDTWTCTs alternatives in multi-tier ASC. The strategic competitive advantages are achieved by RFID-enabled break-even tags price decisions and also techno-economic feasibility decision by contractual design multi-tier SC stakeholder’s involvements.Practical implicationsThe pilot project study explores that the quantitative assessment decision has based on RFID-enable techno-economic feasibility in ASCs. Stakeholders can be benefited by inventory control of the financial losses, reducing the inventory inaccuracies and multi-tags ownership transfer within trusted third-party traceability in ASC networks.Originality/valueThis study explores the RFID-enabled apparel SC process and activities visibility (natural fibre’s fibre producer, fibre dyeing producer, yarn spinning producer, knitting and finishing producer).

Research on Supply Chain Decision-making Considering Fairness Concerns and Green Technology Innovation

A supply chain consisting of a manufacturer and a retailer is constructed. On this basis, the Stackelberg game between the upper and lower levels of the supply chain is adopted, Consider the balance between manufacturers and retailers in the development of green technology innovation under the concern of fairness. The research shows that green technology innovation has a significant positive impact on the whole supply chain system. Retailers' fair concern behavior will have a certain negative impact on the whole supply chain system and increase the potential conflict among the members of the supply chain. Enterprises need to actively incorporate environmental protection into supply chain management and partner selection decisions, and should not ignore the negative impact of fairness concerns on team cooperation.

INTEGRATION OF CASH FLOW MANAGEMENT AND FURTHER ASPECTS OF THE SUPPLY CHAIN MANAGEMENT IN PRODUCTION SYSTEM DESIGN

One major goal of production system design is to decide on space requirements in the plant. In this phase, detailed information about the supply chain network (e.g. which suppliers deliver which parts) is often unavailable. Nevertheless, typical decisions in supply chain management, like the definition of replenishment processes and quantities or make-or-buy decisions, impact space requirements and the capital investment in raw materials. Therefore, it should be considered in factory and production planning. This research article proposes a simulation approach for a production simulation in which raw material replenishment is integrated to evaluate the capital investment and space requirements for raw materials.

Real-time large-scale supplier order assignments across two-tiers of a supply chain with penalty and dual-sourcing

Supplier selection and order allocation (SSOA) are key strategic decisions in supply chain management which greatly impact the performance of the supply chain. Although, the SSOA problem has been studied extensively but less attention paid to scalability presents a significant gap preventing adoption of SSOA algorithms by industrial practitioners. This paper presents a novel multi-item, multi-supplier double order allocations with dual-sourcing and penalty constraints across two-tiers of a supply chain, resulting in cooperation and in facilitating supplier preferences to work with other suppliers through bidding. We propose Mixed-Integer Programming models for allocations at individual-tiers as well as an integrated allocations. An application to a real-time large-scale case study of a manufacturing company is presented, which is the largest scale studied in terms of supply chain size and number of variables so far in literature. The use case allows us to highlight how problem formulation and implementation can help reduce computational complexity using Mathematical Programming (MP) and Genetic Algorithm (GA) approaches. The results show an interesting observation that MP outperforms GA to solve SSOA. Sensitivity analysis is presented for sourcing strategy, penalty threshold and penalty factor. The developed model was successfully deployed in a large international sourcing conference with multiple bidding rounds, which helped in more than 10% procurement cost reductions to the manufacturing company.

Research on the Influence of COVID-19 on Overall Sales of Cars and Cars in Different Categories in China

COVID—19 outbreak has caused a global economic recession; automotive industry plays a key role in economy nowadays. Previous studies were focused on the short-term impact of the COVID outbreak. This study is aimed to evaluate two years after the COVID outbreak, what impact did COVID post on the Chinese automotive industry overall and across different categories, how sales of car models with different price, nationality, and car type reacts to the COVID outbreak. The result of this study shows that COVID posted a significant negative impact on Chinese car sales overall. The higher priced car models impacted less by the COVID outbreak, chinse models impacted more by the COVID outbreak, and no significant evidence to show how SUV models impacted by the COVID outbreak. These findings can help car companies to make the most ideal production, operation and supply chain management decisions when a natural shock happens in the future.

An Ontology-Based Approach for Knowledge Acquisition: An Example of Sustainable Supplier Selection Domain Corpus

Selecting the right supplier is a critical decision in sustainable supply chain management. Sustainable supplier selection plays an important role in achieving a balance between the three pillars of a sustainable supply chain: economic, environmental, and social. One of the most crucial aspects of running a business in this regard is sustainable supplier selection, and, to this end, an accurate and reliable approach is required. Therefore, the main contribution of this paper is to propose and implement an ontology-based approach for knowledge acquisition from the text for a sustainable supplier selection domain. This approach is dedicated to acquiring complex relationships from texts and coding these in the form of rules. The expected outcome is to enrich the existing domain ontology by these rules to obtain higher relational expressiveness, make reasoning, and produce new knowledge.

Supplier selection and order allocation planning using predictive analytics and multi-objective programming

Supplier Selection and Order Allocation (SSOA) are two critical strategic decisions in supply chain management. It is challenging to make these decisions when the demand is unknown. Prediction of demand is a complex problem as it highly depends on some parameters such as product cost. In this research, a three-stage framework is proposed to tackle the hurdles of SSOA planning problem. In the first stage, a hybrid deep learning technique based on multistep Long-Short Term Memory (LSTM) network is developed to determine the future product demands. The efficiency of the developed model is evaluated using two standard error measuring techniques. Then, the results are compared with two other forecasting models to have accurate forecast. One of them is Seasonal Auto-Regressive Integrated Moving Average (SARIMA), and the other one is a deep learning model named Multilayer Perceptron (MLP). In the second stage, a fuzzy supplier evaluation model based on Strengths, Weaknesses, Opportunities, and Threats (SWOT) model is developed to consider qualitative criteria. The third stage fetches the results from the forecasting model in Stage 1, and the results of the fuzzy model in the second stage. A unique multi-objective programming model is developed to select the best suppliers and to determine the allocated orders to them. To derive the efficient solutions, the weighted-sum method is used. The application of the proposed framework is discussed using a real dataset from the Canadian Juice industries. The results of the performance comparison among the considered forecasting models show that the developed LSTM model can lead to less forecasting errors compared to the SARIMA and MLP models.

An overview on the use of operations research in additive manufacturing

Additive Manufacturing (AM) is a disruptive production technology that challenges many well-established, conventional practices in Operations and Supply Chain Management decisions. Consequently, new context-specific decision problems have appeared in this area, while existing decision problems must be adapted or extended to this context. In this overview, these decision problems in AM are highlighted and classified, describing the different decision in an unified manner and citing the underlying OR techniques that have been applied to solve them. The aim of the paper is that, by presenting an overview of the AM-related problems in a systematic, OR- or Decision-Making-centred (rather than technology-centred) manner, the OR community can become more aware of this stream of research and thus be more active and contribute with some high-quality work. Open research challenges, as well as avenues for future research are also discussed.

The Role of Managerial Ability in Supply Chain Management

This study investigates whether supplier firms’ managerial ability affects their strategic decisions in supply chain management. Previous research documents that suppliers could collaborate with or be exploited by powerful major customers. I expect that suppliers with high-ability managers are perceived to be with more favorable future prospects to fulfill contractual obligations and thus possess stronger bargaining power. As a result, these suppliers could resist rent extraction from major customers and achieve supply chain collaboration, making it beneficial for them to operate with a concentrated customer base. Using a comprehensive sample of supply chain links, I hypothesize and find a positive association between managerial ability and customer concentration. I also find that suppliers with more able managers are more likely to continue their existing supply chain relationships. This paper extends the implications of managerial ability to the supply chain setting and adds to the understanding of collaboration/competition between suppliers and customers.

Supply Chain Efficiency and Effectiveness Management

The optimal productivity model plays a significant role in various supply chain management (SCM) decision support systems. Therefore, the precision of the optimal productivity model is necessary to improve SCM's effectiveness. A factor often ignored is that transactions of certain goods are assembled within an enterprise as dynamic structures of various distribution ratios. Regardless of such structure, optimal model productivity is often produced; however, the productivity model's optimal precision can be enhanced by taking it into account. This focusses on strategic thinking and planning, where various process improvement mechanisms are developed. Therefore, in this study, data envelopment analysis (DEA) has been utilized to enhance supply chain efficiency and effectiveness management. This paper explores an optimal productivity model that evaluates the supply chain efficiency and effectiveness management. This paper discusses the policy preparation demands of the decision support systems and develops a framework that organisations can use to control the implementation process.

Effect of Supply Chain Management on Organizational Performance of selected Fast Moving Consumer Goods in Karu, Nigeria

The study examined the effect of supply chain management on organizational performance of selected fast moving consumer goods in Karu local government area. The study has a general objected of ascertain the effect of supply chain management on organizational performance with specific objective to; investigate the effect of strategic supplier partnership on organizational performance of selected FMCGs in Karu L.G.A, assess the effect of information sharing on organizational performance of selected FMCGs in Karu L.G.A and evaluate the effect of customer relationship on organizational performance of selected FMCGs in Karu L.G.A. The study employed a survey research design and data used was primary data. The questionnaire was the data collection instrument used in collecting primary data and it was worded in a positive tone. The population of the study was the employees in charge of supply chain management decisions in the selected fast moving consumer goods manufacturers in Karu L.G.A which was six hundred and thirty two (632) that is four hundred and forty one (441) water factories and one hundred and ninety one (191) bread factories. The sample size was gotten by way of Taro Yamane formula and was 245, but 30% was added in the event of wrongful filling, unreturned questionnaire and response bias, which brought the total number of questionnaires distributed to 319 with 300 returned. Data was presented via tables and analyzed by way descriptive statistics, correlation analysis and regression analysis. The result from the study showed that the independent variable could predict 88% of variation in the dependent variable while 12% of variation could be explained by other factors not captured by the study. The study also found that strategic supplier partnership, customer relationship management and information sharing all have a statistically significant effect and relationship on organizational performance, with information sharing being the highest contributor. The study concluded that supply chain management had a positive and significant effect on organizational performance of selected fast moving consumer goods in Karu L.G.A. the study recommended that the organizations should emphasize and be consistent with these supply chain management practices as they are critical in increasing organizational performance in an effective and efficient manner.