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Artificial intelligence (AI) is increasingly considered a source of competitive advantage in operations and supply chain management (OSCM). However, many organisations still struggle to adopt it successfully and empirical studies providing clear indications are scarce in the literature. This research aims to shed light on how AI applications can support OSCM processes and to identify benefits and barriers to their implementation. To this end, it conducts a multiple case study with semi-structured interviews in six companies, totalling 17 implementation cases. The Supply Chain Operations Reference (SCOR) model guided the entire study and the analysis of the results by targeting specific processes. The results highlighted how AI methods in OSCM can increase the companies' competitiveness by reducing costs and lead times and improving service levels, quality, safety, and sustainability. However, they also identify barriers in the implementation of AI, such as ensuring data quality, lack of specific skills, need for high investments, lack of clarity on economic benefits and lack of experience in cost analysis for AI projects. Although the nature of the study is not suitable for wide generalisation, it offers clear guidance for practitioners facing AI dilemmas in specific SCOR processes and provides the basis for further future research. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic's impacts have been devastating for the global economy, and particularly for manufacturing companies. Many firms were unprepared for a crisis of this magnitude and adapted their operations in an ad-hoc manner. Some of these adaptations were facilitated by digital technologies (DTs). This article examines extant literature using a systematic review methodology in order to extend our understanding of what DTs have been used in manufacturing companies during the pandemic, how DTs have helped manufacturing companies cope with the pandemic, and how these innovations can be used in the post-pandemic world. The major outcome of our study is a novel classification of DT applications in the pandemic setting in the manufacturing industry. In addition, we propose an agenda for future research. [ABSTRACT FROM AUTHOR]

PT. Sinergi Gula Nusantara Sei Semayang Sugar Factory unit is a sugar-producing company which collaborates with suppliers and distributors along its supply chain. The challenges which are faced by PT. Sinergi Gula Nusantara Sei Semayang Sugar Factory unit, are delays in raw material deliveries and production schedules, limitations and mismatches of raw materials with criteria, and production outcomes not meeting targets. Therefore, it is necessary to measure supply chain management performance in order to know the conditions and assess the performance of supply chain management at PT. Sinergi Gula Nusantara Sei Semayang Sugar Factory unit, from 2020 to 2023. Furthermore, the methods used were SCOR as the model for mapping the measurement matrix and FAHP was used in order to determine the priority weights for each criterion in the matrix. The supply chain management performance measurement results at PT. Sinergi Gula Nusantara Sei Semayang Sugar Factory unit, from 2020 to 2023, obtain a score of 81.24, which is categorized into good category. However, there are still 5 KPIs which need improvement, in which it can be achieved by improving record-keeping and documentation with software assistance, sorting raw materials, and implementing the SCOR-FAHP method in supply chain management performance measurement. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Animal Production & Processing Technology / JurnalIlmu Produksi dan Teknologi Hasil Peternakan is the property of IPB University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The paper analyses the importance of Supply Chain in comparison to other critical business areas within companies. Consulting Supply Chain literature always ultimately creates the impression that it "boosts" the company success by lower operational costs and sales growth by better performance. A quantitative literature review of the top 100 biggest German company reports gives the result that Supply Chain Management is a very important business area but customer focus, being defined as "Sales & Marketing" and the product itself (e.g. R&D) are more important for companies on a strategic level. The outcome therefore is, that there must be a good Sales & Marketing and product in the first place to ensure business success, leading to the fact the SCM can be understood as a major supportive function for manufacturing companies.

This study aims to identify the supply chain condition of the red snapper fish processing industry, assess the supply chain performance, and recommend performance improvements based on the performance measurement results. The study was conducted in Brondong District, Lamongan Regency, East Java, Indonesia. The methods used are the Supply Chain Operations Reference (SCOR) model and the Analytical Hierarchy Process (AHP), which measure effectiveness and efficiency parameters. Data were collected through interviews and field observations with expert respondents representing fishermen, collectors, and the fish processing industry. The results showed that the supply chain performance of the fishermen, collectors, and fish processing industry was 67.52% (poor), 88.11% (average), and 95.09% (excellent). The low performance was mainly in the fish catch composition accuracy and raw material handling practices. Root cause analysis was conducted to identify the leading causes, such as poor raw material quality, high raw material costs, and low cash-to-cash cycle time. Recommendations for improvement include handling raw materials training, using better cooling technology, and accelerating debt payments. Implementing lean supply chain management with the 5S system will improve operational efficiency and final product quality. Support from all stakeholders and government is essential for successfully implementing this strategy. Further study on the impact of lean implementation on environmental and social sustainability and exploration of new technologies for efficient fish handling and processing is needed.

In the post-pandemic era, the uncertain global market and rising social-environmental issues drive organizations to adapt their supply chain strategies to more dynamic, flexible models, leveraging advanced technologies like AI, big data analytics, and decision support systems. This review paper aims to examine the current research on AI-integrated technologies in sustainable supply chain management (SSCM) to inform future research directions. We adopted bibliometric and text analysis, targeting 170 articles published between 2004 and 2023 from the Scopus database following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol. We confirm that AI-integrated technologies have demonstrated the capability to enable SSCM across various sectors. We generated ten future research topics using the Latent Dirichlet Allocation (LDA) method and proposed 20 propositions. The results show that AI-integrated technologies in supply chain processes primarily address sustainability, focusing on environmental and economic issues. However, there is still a technological gap in tackling social issues like working conditions and fair dealing. Thus, we proposed a dynamic framework of AI in SSCM to help researchers and practitioners synthesize AI-integrated technologies in SSCM and optimize their supply chain models in future directions. [ABSTRACT FROM AUTHOR]

PT. PG Candi Baru is a manufacturing company in Indonesia that produces sugar in the form of White Crystal Sugar (GKP) from sugar cane as raw material. Application of the supply chain concept at PT PG. Candi Baru is needed to fulfill the needs of end customers. The aim of the research is to integrate the lean six sigma supply chain management concept to design and measure performance measurement models and determine the causes of company performance failures and then provide recommendations for improvement according to the lean concept. This research was carried out only up to the improvement stage. The result of this research is an overall performance measurement of 66.6666 where this value can be categorized as "Average". This value shows that supply chain management activities at PT. PG Candi Baru is running moderately and obtained 9 KPIs that have not reached the target. Waste is the cause of the 9 KPIs not achieving the target, namely waste defects, waiting, not utilizing employee knowledge, skills and abilities and extra processing. Recommendations for improvement given to the company to reduce the occurrence of waste are: For defects in sugar quality, the proposed improvement is to carry out milling in accordance with established standards and use raw materials that comply with specifications. When waiting for raw materials to be late, the proposed improvement is that the plant department must carry out earlier purchasing planning to avoid waste waiting and prioritize TS suppliers because they have a higher weight than other suppliers. Not utilizing employees' knowledge, skills and abilities, the proposed improvement for the production department is training on how to forecast production scheduling. In extra processing, the proposed improvement is that the company can provide a quality control list when inspecting the finished product so that the inspection is more controlled. [ABSTRACT FROM AUTHOR]

Current research on the supply chain risks of prefabricated construction mainly treats risk factors as isolated points, lacking a comprehensive analysis of the interplay between these factors. Taking a stakeholder perspective and a full lifecycle approach, employing the SCOR (supply chain operations reference) model to identify risk factors, a risk assessment model based on social network analysis was constructed to investigate the risk factors and their interactions in the supply chain of prefabricated construction. By calculating various SNA( social network analysis) indicators, key risks and critical relationships were determined. Finally, risk control measures were proposed and the effectiveness of risk response was evaluated. This result provides an effective method for evaluating and mitigating supply chain risks in prefabricated construction, enhancing the effectiveness and accuracy of risk control for all stakeholders involved. [ABSTRACT FROM AUTHOR]

Performance evaluation is essential in defining supply chain strategies because by taking measurements, companies can find out how the business processes in the supply chain are running and formulate strategic policies to improve supply chain performance. Specialty coffee is a premium coffee with a unique aroma and flavor originating from a specific region, and it is easy to trace its origin from the farm to the consumer. This study aims to evaluate the performance of the Kayumas specialty coffee supply chain using the SCOR-ANP method and determine performance improvement strategies using ANP analysis. The research results can be concluded that (1) Kayumas specialty coffee supply chain consists of farmers, farmer groups, distributors/resellers, and consumers, (2) the performance position of Kayumas specialty coffee is inferior, (3) the performance improvement strategy needed to improve product quality is a partnership between supply chain members to reach a price agreement.

A company that operates in the culinary business certainly requires a supply chain function for raw materials. However, supply chain activities may involve risks that can hamper the business. This research aimed to identify risks that might occur in the supply chain at PT AU, carry out a risk assessment, and recommend mitigation actions. In this research, the researcher have used the initial method, namely SCOR, to map existing activities, then identify risk events and their severity values, identify the causes of risks and their occurrence values, calculate the ARP value with the help of Microsoft Excel, and see the highest ranking. Next, HOR phase 2 is to provide recommendations for mitigation actions that are suitable for implementation by the company, which will then be calculated to determine the priority ranking for implementing the mitigation actions that have been given. [ABSTRACT FROM AUTHOR]

In an era of economic development, business competition demands the acquisition of as many consumers as possible. This naturally requires a sound strategy in order to gain a competitive edge over rivals. The aim of this research is to evaluate the supply chain performance of Multi-level Marketing (MLM) companies by measuring SCM performance. SCM performance measurement is carried out using the SCOR model with the weights for each level divided equally and processing the actual data for each performance metric. After processing the data there are 7 SCOR performance metrics. Based on the results of data processing, the actual values are then normalized using the De Boer Snorm to obtain SCOR performance metric measurement values. The results obtained were a total score of 72.2 which is included in the good category, these results indicate that there is still a need to evaluate and improve performance. [ABSTRACT FROM AUTHOR]

The selection of agro-industry location is essential in establishing, growing, and relocating agro-industrial systems for all forms of product development. In this regard, white copra has displayed a great economic potential due to export demand. To response this challenge, Indragiri Hilir Regency in Riau Province might become the most promising area since the location is lack of agroindustrial activity. Such condition leads to a excessive supply of coconut, which is in turn, causing the low price. This work aimed determine the best location for developing agroindustry for edible white copra based on multiple criteria. According to the findings, this research successfully created a new integration SCOR with Fuzzy AHP based on a multiple-criteria approach. At the first and second level, each option has equal rate of importance for each attribute and metric, while at the third level, corresponding to the highest importance, is the adaptability for increased shipping, procurement cost, days for coconut inventory, days for edible white copra stock. The fourth level, also corresponding to the highest importance, includes standard conformity, transportation facility, and the percentage of orders with the correct content. Based on the analysis, the locations showing the highest to the lowest importance were Tembilahan Hulu (0.194), Tempuling (0.152), Batang Tuaka (0.160), Kempas (0.118), Kuala Indragiri (0.100), Tembilahan (0.100), Teluk Belengkong (0.087), Pelangiran (0.080), and Enok (0.072). This research is expected to increase the development of edible white copra agroindustry in the Regency of Indragiri Hilir.

This study evaluates the effectiveness of the blood supply chain and determines potential causes of substandard supply chain performance. Unfulfilled demand for blood at UDD PMI Indragiri Hilir in 2021 reached 970 bags, or 14.1% of all orders. The method used is SCOR (supply chain operation references) and CLD (cause loop diagram). The novelty of this research is applying the SCOR model to holistically measure the blood supply chain's performance and determine the leading causes of low performance. The total value of supply chain performance is 77.78, which is a good category. The results show that Five matrices fall into the low-performance process on the Production attribute (28.24), Capacity Utilization Screening (37.50), Capacity Utilization of Blood Quarantine Storage Cabinets (39.01), Capacity Utilization of Healthy Blood (44.44), and Capacity Utilization Crossmatch (33.3). Based on CLD analysis, potential root causes of the low performance of the supply chain with the CLD model are five low-performance matrices on production attributes influenced by voluntary donors and replacement donors, the number of donors, and blood tapping.

Transformations in socio-economic space affect functioning of entrepreneurial activity, leading to a change in the configuration of business processes. In the context of increasing complexity of external environment and digitalization, subjects must ensure the activities effectiveness based on supply chains optimization. Entities are required to use progressive methods of supply chain management. The purpose of the study is to analyze main optimization models in supply chain management (SCM) to determine progressive ways to improve them. The issues of SCM have been worked out, models of their optimization considered and suggestions for their improvement made. Theoretical analysis and generalization of information that allow to substantiate the SCM optimization models’ apparatus (SCOR, DCOR, CCOR) act as a methodological basis. As a result, it is proposed to focus on possibilities of progressive supply chain management, which make it possible to use information technologies to work through a large array of data and continuously obtain values for indicators, contributing to the development of models for optimizing logistics operations and processes in the SCM. The developments obtained are planned to be used for the development of practical models for optimizing enterprises’ supply chains.

Motivated by the increasing interest in machine learning algorithms for data-driven applications in agri-food addressing sustainability issues and by the ongoing discussion on the interpretability and sustainability of such algorithms, we compare congruently the performance of some state-of-the-art techniques and a new version (here proposed for the first time) of Co-Active Neuro-Fuzzy Inference System, equipped with fractional regularization (CANFIS-T for short). To this end, we consider two case studies retrieved from the literature and dealing with two approaches for sustainability development, i.e. ex-ante Life Cycle Assessment and Supply Chain Operations Reference in the agri-food context. Such approaches are set in a data-driven framework and completed by the above-mentioned machine learning techniques. The state-of-the-art techniques from the relevant literature are the ensemble ANFIS, Radial Basis Function Network and Decision Tree. The techniques are compared from the computational, interpretability and energy standpoints. From a formal perspective, we prove what negatively affects the accuracy of ensemble ANFIS. On the basis of the performed experiments, we notice that except for the ensemble ANFIS, all the approaches can be regarded as sustainable, with energy savings over 99%, while only CANFIS-T keeps both good accuracy and interpretability (with up to 4 rules) when the number of input and output variables gets large. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Agroindustrial Technology / Jurnal Teknologi Industri Pertanian is the property of IPB University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Jurnal Agroindustri Halal is the property of Universitas Djuanda and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The upstream segment of the minerals supply chain (MiSC) is the backbone for achieving the transition to clean energy by securing the supply of minerals. Recently, the MiSC has been disrupted, affecting mineral supply and generating uncertainty among clean energy producers. Supply chain (SC) mapping addresses this uncertainty, providing a holistic end-to-end view. However, MiSC mapping studies mainly focus on the downstream segment, leaving aside the upstream segment. In this context, the fundamental gap is the lack of standardized modelling frameworks that can accurately represent the upstream segment dynamics and, at the same time, seamlessly integrate with the downstream segment. This paper bridges this gap, designing a model for the MiSC upstream segment (MiSCOR). Framed within design science research methodology, MiSCOR is built by adapting two reference models, the Exploration and Mining Business Reference Model (EM) and the Supply Chain Operations Reference Model (SCOR), focusing on the commodity-making process. The MiSCOR demonstrates its applicability and robustness in real operational scenarios of one of the largest copper producers. MiSCOR provides a management tool for practitioners and decision-makers in the MISC's upstream segment, offering blueprints to throw functional silos, foster collaboration, and a standardized framework that integrates seamlessly with the downstream segment. [ABSTRACT FROM AUTHOR]

In every large, medium and small industrial enterprise, risks must occur in the business process. The study conducted at one of the small medium enterprise (SME) in the Bantul, Yogyakarta. It begins with the fact that obstacles that often occur are delays in delivery, product damage, and also other obstacles. Hence, those are the reasons of this study conducted. Further, the risk management framework has an important role in reducing these problems. The approach used ISO 31000 method and the SCOR Model in making a proposed framework to improve risk management performance. Based on the proposed framework that has been made, the risk identification process in Rajut Bamboo has 32 risks in its business processes. The risk mitigation proposal is carried out on seven risks in the high-risk category. The risk mitigation results are obtained in the risk codes (D3) unfinished product and absence of SOP, (M2) quality control takes a long time, (P5) unplanned overhead costs, and (A1) products in storage are damaged or lost, thus it showed down to medium risk category, then the risk codes (D9) expensive packaging material costs, (D2) order time exceeds the specified time, and (M6) no mitigation planning, thus it showed down to low-risk category.

This study examines the effects of process improvement on sustainable supply chain management performance via the SCOR model using Lean Six Sigma tools. The transportation company is used as a case study. The critical success factors and reasons for the use of tools are reviewed. In research, it is found that process improvement increases the effectiveness of supply chain management. In addition, sustainability plays a major role in supply chain management. To measure and improve the effectiveness of this model, Lean Six Sigma tools have been used. The paper concludes that firms can have savings in terms of money and time. Furthermore, it is proved that CO2 emissions could be reduced. This paper prompts the efficacy of well-publicized methodologies and evaluates their implementation for process improvement for the firms. The practical application, constraints, and resultant effects of developing Lean Six Sigma were reviewed to give impetus to the methodology. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Management & Agribusiness / Jurnal Manajemen & Agribisnis is the property of IPB University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Ciamis Regency is a potentially developed coffee-producing area in West Java with Arabica and Robusta coffee types. However, in the current marketing process, it is still faced with various obstacles that make the supply chain flow non-optimal. Therefore, in optimizing the Ciamis coffee supply chain management, it is necessary to conduct further research related to supply chain flow, performance, and farmer’s share. This study aims to determine the flow, performance, and farmer’s share of the coffee supply chain in Ciamis Regency. This research uses the descriptive, SCOR, and farmer’s share methods. The results showed that the supply chain flow consisted of material flow in the form of green beans that flowed from upstream to downstream, the flow of information in the form of information (quantity, price, and quality of green beans) that flowed from upstream to downstream and from downstream to upstream, and financial flows in the form of cash payment transactions that flow from downstream to upstream. The performance of coffee supply chain management in Ciamis Regency has an average category with a value of 56.91. The most significant farmer's share value is found in the distribution channel from farmers to inter-regency traders, ending with outside-regency traders.

Supply chain is a valuable and strategic decision even for small enterprises. This research aimed to identify the supply chain characteristic of small enterprises in Malang. Data and information were collected through observation and in-depth interviews based on business processes in the SCOR model. The result shows that small organic farming already has a strong relationship between stakeholders. However, the research found a lack of traceability for organic input, unstable production due to some situations, and a limited served market.

This article uses the approach of a literature review study sourced from previous research and relevant to this research, namely the Supply Chain Operations Reference model. The phenomenon is that previous studies have not reviewed the Supply Chain Operations Reference (SCOR) model as an interesting thing to study in collaboration with other methods in a structured way. This study aims to give a proposed framework of the SCOR model as a reference for detailed information related to the SCOR model in Indonesia's retail, manufacturing, and service industries. The results of the paper are the year of publication for the 50 articles reviewed consists of 2018-2021 for the country of Indonesia. The research object consists of 3 objects, namely the retail, manufacturing, and service industries. Most supply chain performance levels in Indonesia are in a good category. Most of the research variables majority of the five variables often used in the SCOR model: plan, source, make, deliver, and return. The performance attribute priority that needs to be improved is the reliability attribute. The method used by previous research is 17 methods. This method can be used as an illustration to see how the SCOR model can collaborate with other methods. The paper's conclusion is the research proposed framework regarding the application of the SCOR model that can be collaborated with other methods.

This paper presents a generic representation of supply network resilience implemented using Agent-Based Modelling and Simulation (ABMS) and simulation experiments. The representation captures the relationships between tactical and strategic decisions and their impact on the performance of multi-echelon networks under supply uncertainty. This representation expands practitioners' understanding of the behaviour of their supply chains by using the Supply Chain Operations Reference model processes and performance metrics and developing a simulation model that can be adapted to a firm's unique supply structure (sourcing strategy) and its product's technological assembly order (Bill of Materials). To demonstrate the applicability and usability of the proposed representation, a case with single and dual sourcing network structures was analysed under disruptions of operational and strategic nature. The example demonstrates the flexibility and functionality of the proposed representation to understand the performance and resilience of multi-echelon networks under a wide range of disruptive scenarios. [ABSTRACT FROM AUTHOR]

In every large, medium and small industrial enterprise, risks must occur in the business process. The study conducted at one of the small medium enterprise (SME) in the Bantul, Yogyakarta. It begins with the fact that obstacles that often occur are delays in delivery, product damage, and also other obstacles. Hence, those are the reasons of this study conducted. Further, the risk management framework has an important role in reducing these problems. The approach used ISO 31000 method and the SCOR Model in making a proposed framework to improve risk management performance. Based on the proposed framework that has been made, the risk identification process in Rajut Bamboo has 32 risks in its business processes. The risk mitigation proposal is carried out on seven risks in the high-risk category. The risk mitigation results are obtained in the risk codes (D3) unfinished product and absence of SOP, (M2) quality control takes a long time, (P5) unplanned overhead costs, and (A1) products in storage are damaged or lost, thus it showed down to medium risk category, then the risk codes (D9) expensive packaging material costs, (D2) order time exceeds the specified time, and (M6) no mitigation planning, thus it showed down to low-risk category. [ABSTRACT FROM AUTHOR]

This study aims to analyze the efficiency of raw materials supply and measure supply chain performance at PT XYZ. The method used to measure supply chain performance is SCOR. This research is limited to PKO raw material from suppliers and lauric acid products by PT XYZ. Results showed that the method of raw material procurement in PT XYZ was already efficient. The supply chain performance in PT XYZ was good yet only the POF matrix gives an unfavorable result compared to the brancmark from a similar company. Commonly in running operation of production, PT XYZ has several steps of supply chain that only involve suppliers, PT XYZ and direct to customer. The result showed from the measurement of matrix: level 1 is POF=88.36%, OFCT=44 days, and CTCCT=51 days. In level 2, PT XYZ conducted all activities in planning process (P1-P5), executing (S2, M1, M2, M3, D2, D3 and DR1) and enabling. On the mapping of level 2 obtained that the result of deliver process have the lowest performance and analysis in level 3 should be conducted to explain the deliver process in more detail.

Supply chain organizations should calmly and cautiously take the most accurate and sustainable decisions quickly and put them into practice. It is obvious that traditional time series–based demand and supply planning approaches are insufficient to meet current business needs due to factors such as sharp changes in market and commercial dynamics, pandemics, and natural disasters on the management of green supply chains, especially these days. In the near future, there will be a need for more resilient supply chains with a flexible business models that are not affected by sudden changes and that can make sustainable decisions dynamically. Additionally, all stakeholders must act with a green supply chain approach to conduct production and service activities in a way that causes the least damage to nature. Companies must build more resilient supply chains by considering environmental sensitivities to compete in the market and ensure their continuity. In this context, the green supply chains should be evaluated according to their resilience. For this purpose, Supply Chain Operations Reference (SCOR) model is extended with novel performance attributes to evaluate resilience of green supply chains in this study. The SCOR-embedded novel green supply chain resilience evaluation model is structured as a three-level performance attribute hierarchical structure. Then, the model is handled as a multi-criteria decision-making problem to determine importance of the performance attributes. Best Worst Method integrated Interval Valued Intuitionistic Fuzzy Analytic Hierarchy Process is used to determine the importance of performance attributes. Most important performance attributes are determined in each level of hierarchy. According to results, organizational factors play a key role to build more resilient supply chains. Especially, integrated systems are required for supply chain resilience. [ABSTRACT FROM AUTHOR]

Considering the importance of small and medium-sized industrial units for economic growth, social cohesion, regional and local development, this study presents a model for the merger so that they can make use of each other's capacities and facilities to achieve higher efficiency levels. The involved criteria have been chosen using the SCOR model with the consideration of sustainability, resilience and agility criteria in each part of the supply chain network. PCA has been used to reduce the dimensionality and the efficiency of units has been determined by network DEA. Next, a mathematical model has been used to determine the best combination for merger. The model chosen for the finalization of the merger process is inverse network DEA, which tries to determine the final inputs of the merged units for a specific target. In addition to theoretical benefits, the results have practical applications. The results can give supply chain partners a common language for better communication and help them settle on standardized definitions. The model has been implemented using real-world data gathered from other articles, which pertain to 26 stone industries of Iran. The DEA model and the mathematical model have been solved through GAMS and the PCA approach through MATLAB. [ABSTRACT FROM AUTHOR]

In lithium mining in the Argentine Northwest, mining companies are located strategically, depending on the availability of brines, but far from urban centers. Therefore, when selecting the right provider, it is necessary to consider multiple criteria. This paper presents the first multi-criteria decision model for the selecting suppliers in the lithium industry in the Argentine Northwest, in which a criterion of great importance for the region is considered and which is novel for the sector. From it, companies can select the best supplier through a ranking of qualifications without the variation that the preference of the person making the decision supposes. Fuzzy Analytical Hierarchy Process (FAHP) methods were integrated with Fuzzy Logic and the SCOR model. Therefore, it can be used in environments of uncertainty and ambiguity, combining quantitative and qualitative information. 6 criteria were defined with 3 levels of assessment: Quality, Price, Financial Solidity, Performance, After-sales Service, and Belonging. 729 combinations with possible selection results were obtained. This model was applied to four local suppliers by evaluating the input criteria. The result of the output variable Supplier Preferability was obtained, and from this, it was established which of them should be selected. This model it is expected to contribute to the decision-making of mining companies in the area. [ABSTRACT FROM AUTHOR]

This study aims to investigate the relative operational efficiency of major Turkish container ports based on the Data Envelopment Analysis - Supply Chain Operations Reference (DEA-SCOR) model. While Turkish export and import figures are growing, the scientifical studies on operational efficiency of Turkish ports are gaining more attention day by day. Of course, one of the important import countries is China for Türkiye and BRI (One Belt and One Road Initiative) tends to support Turkish trade between western and eastern countries. Therefore, Turkish ports' efficiencies should be identified and suggestions have been presented for further development. The sampling frame was chosen from the members of TURKLIM and therefore, the SCOR and Data Envelopment Methodology examined 23 seaports. Both methodologies are generally used for analyzing the operational efficiency of ship inward-outward and stackings. The findings of the study show that four major ports are the most efficient gateways to handle inward and outward container traffic with their input variables. However, there are some challenges in port investment for BRI. This study should be used for the further analysis in the sector reports and scientific papers. [ABSTRACT FROM AUTHOR]