RSS 1.0Ingeniería Industrial
Recent Submissions
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Validation of an Instrument to Measure the Level of Safety Culture in Peru(Academy of Medical and Health Sciences of Catalonia and the Balearic Islands, 2025-01-01)Objective: Workplace safety culture plays a critical role in preventing occupational risks and improving worker well-being. However, despite existing regulations, its implementation remains inconsistent in various industries. This study aims to validate an instrument for measuring the level of safety culture in Peru to identify critical improvement areas and support evidence-based strategies. Method: A three-part validation was conducted: selection of the instrument through a review of the scientific literature, qualitative validation through expert judgment, and quantitative validation via a pilot test with 42 workers. Reliability was assessed using Cronbach’s alpha and McDonald’s omega, while construct validity was examined using Exploratory Factor Analysis with Unweighted Least Squares and Promax rotation. Results: The validated instrument consists of 16 questions grouped into five dimensions: a) active participation in safety, b) awareness and compliance with safety regulations, c) risk knowledge and safety training, d) concern for safety and adherence to procedures, and e) prevention and communication about safety. The final model demonstrated good internal consistency (Cronbach’s α = 0.822, Omega = 0.83) and a stable factorial structure, explaining 75.79% of the variance. Conclusions: This validated questionnaire is a reliable tool for assessing safety culture in companies in Peru, allowing organizations to identify weaknesses and implement targeted safety interventions.Acceso abierto
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Ergonomics in Linemen Activities: A Proposal for the Redesign of a Telescopic Pole(Springer Nature, 2025-01-01)Maintaining electrical towers is critical for a stable power supply but presents substantial risks to linemen’s health and safety. In 2020, the Peruvian Ministry of Labor documented 1,508 occupational accidents in the electrical sector, representing 4.6% of all workplace incidents nationwide. This study aimed to analyze the ergonomic conditions of linemen engaged in tower maintenance, specifically addressing issues associated with the telescopic pole. Using a mixedmethods approach, we applied User-Centered Design tools, such as journey mapping and interviews with linemen from Peruvian power transmission companies, to uncover ergonomic challenges and operational experiences. Ergonomic risks were assessed through Rapid Entire Body Assessment (REBA) and Hierarchical Task Analysis (HTA), revealing that tasks involving safety, electrical voltage handling, and temporary line positioning are time-intensive and high-risk. The telescopic pole emerged as a primary ergonomic issue, hindering task efficiency and safety in power line maintenance. These findings highlight the urgency for improved ergonomic solutions; consequently, a motorized pole design was proposed to enhance working conditions, minimize injury risks, and streamline maintenance processes.
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Reduction of Defects in Flexographic Material Production: An Innovative Approach Based on Artificial Intelligence and Optimal Work Methods(Association for Computing Machinery, Inc, 2025-04-28)The graphic industry faces an ongoing problem: printing defects, which, despite their impact, have not been widely studied. Globally, the demand for commercial printing is expected to grow by 24%. In Peru, this sector plays a significant role in the economy. According to INEI, it is part of the manufacturing industry, contributing 12.5% to the national GDP and employing 8.5% of the Economically Active Population (EAP). Additionally, in 2021, it saw a 7.3% increase in sales. This study proposes an innovative model to tackle this issue by combining AI-driven digital technologies with industrial engineering tools. Defects affect more than just finances; they also lead to customer loss and damage to a company’s reputation. Key causes include poor design procedures, printer malfunctions, failure to follow proper storage practices, and prolonged storage, all of which contribute to defective prints and the use of degraded raw materials. In response, various improvements have been implemented, including method studies, work standardization, planned maintenance, adherence to good storage practices, and the use of Economic Order Quantity (EOQ) and Demand Driven Material Requirements Planning (DDMRP). The main contribution of this study is the identification and validation of a model that helps graphic companies overcome challenges in quality and order fulfillment. The model was tested using Arena simulation software and implemented in a Peruvian company specializing in commercial printing. The results showed a 12.03% decrease in defect rates (from 17.59% to 5.56%), an increase in the meantime between failures by 400.7 hours (from 46.35 to 447.05 hours), and a reduction in defective raw materials from 23.81% to 11.11%. Additionally, the capacity of the printing and storage processes has been optimized. According to the Process Capability Analysis, the capability of the printing process increased from 0.73 to 3.22 and that of the storage process from 0.54 to 2.09, making them capable processes that ensure a high level of quality. In conclusion, the improvement model narrowed the technical gap, boosting quality in the graphic sector, and leading to greater customer satisfaction and higher profits.
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Waste reduction model trough DDMRP & Machine learning to achieve zero hunger: A Peruvian fishing company case(Association for Computing Machinery, Inc, 2025-04-28)The food industry faces the persistent and multifaceted problem of food waste at all levels of its supply chain, significantly impacting sectors that deal with perishable products. This issue primarily arises due to inadequate and inefficient purchasing and replenishment management practices. In the context of Peru, fish stands out as a crucial product, with the fishing and food industry experiencing a remarkable growth rate of 27% over the last decade. This sector now contributes approximately 4% to the national manufacturing GDP and employs a significant portion of the labor force, underpinning its economic importance. However, despite its growth and significance, this industry suffers from substantial levels of waste, accounting for 23% of the total food waste generated in its processes. This is particularly concerning given the global context where hunger levels are growing in Peru and 828 million people around the world suffer from hunger. Motivated by the pressing need to reduce global food waste, particularly in the fish industry, we have developed an integrated and innovative methodology. This methodology combines Demand Driven Material Requirements Planning (DDMRP) for effective inventory management with advanced Machine Learning techniques for accurate demand forecasting. Our approach meticulously identifies the optimal replenishment policy, leading to significant reductions in waste. The study conclusively demonstrates that the application of these advanced techniques can effectively and efficiently address food waste issues within the fish industry. Based on comprehensive bibliographic evidence, it has been shown that it is possible to reduce waste levels by up to 75% using the described tools and methodologies. This research offers a promising pathway for other industries facing similar challenges.
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Maintenance Model Integrating 4DX, RCM and I4.0 to Improve the Availability of Critical Assets(Association for Computing Machinery, Inc, 2025-04-28)Availability is a widely used and important indicator of machine status. To improve availability, it is crucial to reduce breakdowns and have adequate maintenance plans. In addition, current maintenance needs demand the ability to predict failures to keep the machines in good condition. This study evaluates the subway loaders of a company in the mining sector. This sector is a fundamental part of the growth of the world economy, especially in Latin American countries such as Peru. A crucial part of the growth of the sector is the optimal operation of heavy machines since productivity depends mainly on their good performance. In that sense, this study proposes a predictive maintenance plan for subway loaders based on Industry 4.0 (IoT and Machine Learning) with the RCM methodology, additionally, it is planned to apply the EOQ method to ensure that the loader spare parts are available and does not extend maintenance times. To validate the effectiveness of the model, the simulation by Weibull statistical distribution and Arena software are suggested, since they are adequate to treat data and variables corresponding to maintenance plans and inventory management, respectively. With this, it is expected to increase availability by 8% to reach the industry-recommended 85%.
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Model to improve the availability of subway loaders in a mining company by applying rcm methodology with industry 4.0(Association for Computing Machinery, Inc, 2025-04-28)Availability is a widely used and important indicator of machine status. To improve availability, it is crucial to reduce breakdowns and have adequate maintenance plans. In addition, current maintenance needs demand the ability to predict failures to keep the machines in good condition. This study evaluates the subway loaders of a company in the mining sector. This sector is a fundamental part of the growth of the world economy, especially in Latin American countries such as Peru. A crucial part of the growth of the sector is the optimal operation of heavy machines since productivity depends mainly on their good performance. In that sense, this study proposes a predictive maintenance plan for subway loaders based on Industry 4.0 (IoT and Machine Learning) with the RCM methodology, additionally, it is planned to apply the EOQ method to ensure that the loader spare parts are available and does not extend maintenance times. To validate the effectiveness of the model, the simulation by Weibull statistical distribution and Arena software are suggested, since they are adequate to treat data and variables corresponding to maintenance plans and inventory management, respectively. With this, it is expected to increase availability by 8% to reach the industry-recommended 85%.
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Increasing efficiency in flexographic MSEs through standard work, SMED, Artificial Intelligence and RCM in?Latin?America(Association for Computing Machinery, IncAssociation for Computing Machinery, Inc, 2025-04-28)In the graphics sector, companies face a significant challenge: a high rate of order noncompliance due to limited capacity in their production processes. The importance of this problem is not only defined in the dissatisfaction among customers, but also in the direct impact on profits due to the economic loss due to unfulfilled orders. Significant efforts have been made to address this issue, including the proposal of an improvement model that seeks to increase efficiency through standard working practices, SMED, AI and RCM. The motivation to solve these problems lies in the need to improve the efficiency and profitability of companies in the graphic sector, as well as in customer satisfaction. The main contribution of this study lies in the identification and validation of an improvement model that can help companies in the graphics sector to overcome their efficiency and order fulfillment challenges. The validation of the proposed model was carried out through simulations in the Arena software and its implementation was in a Peruvian company dedicated to the printing of self-adhesive labels. The main result achieved was a 13.3% increase in the efficiency indicator of the ILMA 340 printer (from 63 to 76.3%), a 27% reduction in machine assembly times (from 90.5 to 65.3 minutes) and an increase in the average time between failures by 53.4% (from 30.0 to 46.5 hours). In conclusion, the improvement model managed to overcome the technical gap, increasing efficiency and productivity for companies in the graphic sector, which contributes to customer satisfaction and increased profits.
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Implementing Lean Office and Cloud Computing to Innovate the Management of Industrial Projects and Services in Peruvian SMEs(Association for Computing Machinery, IncAssociation for Computing Machinery, Inc, 2025-04-28)Many companies require engineering models to optimize their processes, reducing process times and eliminating non-value-added activities to balance the gaps in the sector. The business services sector represents 4.58% of national GDP, relying primarily on professional, technical, and scientific activities. Therefore, this article aims to contribute to the service sector with methodologies and tools designed to reduce waste in administrative processes. A case study was developed in a water treatment services company implementing the standard work, Kaizen, Kanban supported by a Cloud Computing system to obtain better results reducing report lead times; as well as the identification and reduction of unnecessary processes, maintaining those with value. These results will be evaluated through a Value Stream Desing (VSD) comparing the current and future situation. The goal is to reduce the high frequency (75%) and percentage (124%) of delays in the delivery of services and projects, particularly in the development of reports by optimizing the process flow. This is expected to demonstrate the feasibility of combining Lean and Industry 4.0 tools to enhance administrative processes and, consequently, the operational performance of the company. The model will be validated through a literature review of lean implementation success stories in industrial service companies as a reference for the expected results in our case study, such as the decrease of 87% in the report lead time.
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Improvement Model of OEE in the Production Process of Cardboard Boxes Through SMED, TPM, Automation, and IoT(Seventh Sense Research Group, 2025-06-01)As processes become more complex, measuring them using key KPI indicators, such as Overall Equipment Effectiveness (OEE), is essential. This study analyses the OEE of the cardboard box production process-the product with the highest annual revenue in a Peruvian printing company. The current OEE is 64.27%, which falls short of the graphic industry standard (72.5%). Increasing the OEE would provide several benefits, such as higher availability, improved product quality, reduced setup times, and lower machine wear. Therefore, an innovative solution model is proposed that will use SMED and TPM tools, as well as Automation and IoT technologies. These Lean tools will be enhanced through the mentioned technologies. The solution model will follow the PMBOK approach due to its significant contributions to project management and will consist of three phases: initial, implementation, and closure. Improvements will be projected for key SMART indicators that are identified. Subsequently, these improvements will be validated through simulation in Arena software across three scenarios: moderate, optimistic, and pessimistic. All three scenarios will show improvements over the current OEE, approaching the industry standard. Setup time in die-cutting was reduced to 836.69 minutes, die-cutter wear decreased to 24.58%, and lubricant usage in guillotines and offset machines increased to 255.04 ml and 569.21 ml, respectively.Acceso abierto
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Design and Layout of Warehouses to Increase Productivity Using ABC and SLP Techniques in a Mining Company(Seventh Sense Research Group, 2025-06-01)This research addresses the design and optimized distribution of a mining spare parts warehouse to increase productivity using the ABC and Systematic Layout Planning (SLP) techniques. The current problem of the company under study is centered on poor manual inventory management, characterized by disorganization, lack of a strategic classification of materials and inefficient routes, which negatively impacts response times and the accuracy of records, directly affecting productivity and profitability. To address these challenges, a design is proposed that integrates the ABC technique for prioritizing products according to their value and rotation, together with SLP, to optimize the layout of the areas and internal flows of the warehouse. The initial diagnosis revealed critical deficiencies, including an inventory accuracy of 88.19%, an OTIF delivery efficiency of 87.41% and an overall productivity of 76.83%. The study is based on existing literature, highlighting the positive impact of tools such as 5S, Lean Warehousing and ABC-SLP analysis in optimizing operational productivity. The design proposal includes a "U"-shaped layout to minimize travel times and optimize the location of high-turnover products, validated through simulations to assess its impact on key performance indicators. After implementation and reduced time and distance travelled factors, 94.97% for FILL RATE and 93.12% for OTIF were obtained, an improvement of 7.05% and 5.71%, respectively.Acceso abierto
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Motivations, Quality, and Loyalty: Keys to Sustainable Adventure Tourism in Natural Destinations(Multidisciplinary Digital Publishing Institute (MDPI), 2025-07-01)This study examines the key factors that influence tourists’ perceptions of destination quality and loyalty in the context of adventure tourism in Santa Elena, Ecuador, an emerging destination in Latin America. A quantitative approach was used, with data collected through an online questionnaire completed by 318 participants. Structural equation modeling was conducted using SmartPLS 4 to examine the relationships between motivational constructs (intellectual curiosity, health assurance, stress relief, physical condition, and social connection), perceived destination quality, and loyalty. The findings reveal that health assurance (β = 0.395, p < 0.001), stress relief (β = 0.417, p < 0.001), and intellectual curiosity (β = 0.143, p = 0.010) significantly influence perceived destination quality, while social connection and physical condition did not show significant effects. Moreover, perceived destination quality strongly predicts tourist loyalty (β = 0.634, p < 0.001). The model explains 63.5% of the variance in destination quality and 48.1% of that in loyalty. These results highlight the importance of post-pandemic health concerns, emotional well-being, and intellectual engagement as drivers of satisfaction and loyalty in adventure tourism. While existing research has largely focused on motivations and quality perceptions in adventure tourism within developed regions, studies in post-pandemic settings across Latin America—especially using validated structural models—remain scarce. This study also contributes to filling a gap in the literature by analyzing post-pandemic tourist behavior in Latin America, an underexplored context in existing research on sustainable and adventure tourism. The findings offer theoretical contributions to the field of adventure tourism and practical recommendations for destination managers seeking to enhance their competitiveness and visitor retention in the post-pandemic context.Acceso abierto
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Re-Designing Business Process Models for Enhancing Sustainability in Spinach Production Through Lean Tools with Digital Transformation(Multidisciplinary Digital Publishing Institute (MDPI), 2025-07-01)This study addresses rising sustainability demands in the agro-industry by examining how data-driven approaches can reduce inefficiencies, waste, and poor resource use in spinach production. It investigates the impact of Total Productive Maintenance (TPM), First-In–First-Out (FIFO), process standardization, and circular economy practices—enhanced through digital transformation—on operational efficiency in a Peruvian agro-industrial firm. An exploratory case study was conducted using pilot implementations, direct observation, and quantitative analysis. Statistical tools, including Holt–Winters forecasting, were applied to assess the effectiveness of the interventions. Digital technologies supported data collection, traceability, and decision-making. An exploratory case study was conducted using pilot implementations, direct observation, and quantitative analysis. The integration of digital tools with lean and circular practices supports sustainable agro-industrial supply chains, contributing to food security and socio-economic resilience. This research offers a holistic, data-driven framework that aligns operational excellence with sustainability and digital innovation. Findings are based on a single case, limiting their generalizability. Broader applications and long-term effects warrant further study. Practitioners should adopt system-thinking approaches integrating digital, lean, and circular strategies. Future research should explore scalability, cost-efficiency, and policy support mechanisms.Acceso abierto
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Enhancement of Operational Efficiency in a Plastic Manufacturing Industry Through TPM, SMED, and Machine Learning—Case Study(Multidisciplinary Digital Publishing Institute (MDPI), 2025-08-01)The plastics manufacturing sector has experienced remarkable growth, requiring more optimized operations through reduced repair times and product defects. In this context, the theoretical aim of this research is to prove that the integration of classic continuous improvement tools (TPM and SMED) with advanced data science techniques (machine learning) forms a synergistic approach capable of significantly increasing operational efficiency in manufacturing environments. The study was conducted at a Peruvian plastic container manufacturing company with a first overall equipment efficiency (OEE) of 61.87%, affected by low availability of injection and blow molding machines and a high rework rate. Total Productive Maintenance (TPM) strategies were implemented to improve equipment maintenance, the SMED method to reduce setup times, and a machine learning model to predict defects and burs in products. The effectiveness of the approach was confirmed through simulations in Arena and analysis of historical data. As a result, OEE increased to 80.86%, reducing downtime and rework. In conclusion, this study shows that the combination of TPM, SMED, and machine learning not only improves operational performance but also offers a replicable and robust methodological framework for process optimization in the manufacturing industry.
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A Production Management Method to Reduce Non-Fulfillment of Orders Based on Lean Tools and Change Management: Case of a Peruvian Apparel Company(Seventh Sense Research Group, 2025-04-01)In Peru, the textile and apparel industry ranks third in the manufacturing sector. In 2023, there are 44,600 formal microenterprises in this sector. Currently, apparel companies operate with long and inefficient delivery times and other obstacles that erode their competitiveness. One of the most relevant problems is the non-fulfilment of orders. In addition, resistance to change, lack of training, and a lack of business culture are some of the most frequent obstacles in this industry. For this reason, it is proposed to implement a method to manage production that combines 5s, SMED, standardization and change management techniques are proposed to improve the existing gap in the level of order fulfillment. The sustainability of the proposal is evaluated by considering the economic, social, and environmental aspects. After validation, the results obtained were an order fulfillment level of 77.9%, a reduction of non-value-added activities by up to 6.45%, shorter set-up times with a reduction of up to 52% and a reduction of defective seams by up to 4.38%. In addition, a pollution reduction of up to 22% of non-usable waste.
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Use of Supply Chain Analytics Technologies in Peru's Agri-Food Supply Chain: Supporting Agility and Supply Chain Cost Reduction(John Wiley and Sons Inc, 2025-03-01)This research examines how the use of supply chain analytics technologies (USCAT) can increase financial performance by enabling agility and quality management capabilities in the Peruvian coffee supply chain. Using an empirical research approach, we theorize and test a model based on the dynamic capabilities view. We collected survey data from supply chain management experts working in the Peruvian coffee supply chain and used covariance-based structural equation modeling to test a series of hypotheses. This research supports the relationship between USCAT and improvements in supply chain agility, quality focus, and supply chain cost performance for agri-food supply chains (AFSC). These findings offer valuable insights for agri-food businesses, especially in developing economies, suggesting that strategic technological investment can enhance competitiveness and financial sustainability. Stakeholders (scholars and managers alike) operating in developing areas can use the results to motivate and leverage the value of readying themselves and their supply chain partners to participate in current and future supply chain technology-enabled business opportunities. This research contributes to the literature by providing a unique perspective on the impact of new supply chain technologies in emerging markets, specifically within the Peruvian agri-food sector, and extends the discourse on technology adoption in global agri-food supply chains.
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Designing a sustainable performance measurement system for an agri-food supply chain through supply chain agility based on digital technologies(Emerald Publishing, 2025-01-01)Purpose: This research aims to identify and model metrics and sub-metrics that enhance sustainable performance measurement in agri-food supply chains. Design/methodology/approach: The study evaluates five key metrics and 18 sub-metrics critical to this industry, establishing interrelationships among them to ensure a successful sustainable performance measurement system. The decision-making trial and evaluation laboratory technique was employed, integrated with fuzzy theory and expert opinions. Findings: The findings suggest that metrics like information technology and organizational productivity, alongside the sub-metric of information integration, significantly contribute to sustainable supply chain performance. Originality/value: This study proposes a performance measurement system that enables organizations to achieve optimal performance levels through a sustainable supply chain (SCC) and supply chain agility (SCA) framework, supported by digital technologies.
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Avances sobre ergonomia en tareas de paletizacion(Universidad Peruana de Ciencias Aplicadas (UPC), 2014-12-31)Objetivo: El siguiente estudio de revisión bibliográfica se propone como objetivo general evidenciar con bibliografía actualizada, estudios que nos permitan comprender la magnitud del riesgo que afronta el trabajador frente a las demandas que exige las tareas de paletizado, a nivel biomecánico, fisiológico y riesgos relacionados al trabajo así como el beneficio de la implementación de apoyos mecánicos. Material y Métodos: Se realizo una búsqueda bibliográfica en los diferentes motores de búsqueda: Google académico, HINARI, revista APPLIED ERGONOMICS de editorial Elsevier y revista ERGONOMICS de Taylor & Francis, así mismo también se usaron textos de consultas actuales sobre ergonomía y biomecánica. Resultados: Se evidencian que la carga física biomecánica al paletizar es alta sobretodo en trabajos donde los trabajadores no tienen experiencia, así mismo la forma de la caja, el tamaño, la distancia de paletizado, la frecuencia y el modo operatorio afecta notablemente el riesgo de lesión en columna lumbosacra así como incrementa el nivel de gasto energético. Se adoptan los criterios establecidos por NIOSH (1994) que establecen no sobrepasar el 50% de la capacidad aeróbica en tareas que duren menos o una hora, el 40 % en tareas que duren entre 1 y 2 horas y el 33% en tareas que duren entre 2 a 8 horas. Conclusiones: Las técnicas posturales empleadas por trabajadores experimentados no garantizan una protección elevada contra el riesgo de lesión de columna, sin embargo las técnicas son mejores y mas estables para disminuir el riesgo que en los trabajadores no experimentados. El costo beneficio es un factor importante al momento de buscar soluciones para justificar el gasto, en el estudio presentado sobre grúas en pacientes se observa que se ahorra hasta en 70% en costos directos e indirectos al trabajador.Acceso abierto
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Integrated Maintenance Management to Increase the Availability of Drilling Equipment: Case Study in a Peruvian Mine(Trans Tech Publications Ltd, 2024-01-01)Drilling equipment is the main asset of mining companies; therefore, a decrease in the operability and availability of such equipment can generate negative impacts on organizations, such as the generation of extra expenses due to the hiring of third parties for the performance of activities and contractual projects. According to statistics from previous studies, the availability of equipment in the sector should be 95% to be considered optimal for use in mining operations. Equipment downtime can be avoided by establishing and following a preventive maintenance schedule and having spare parts and hydraulic components readily available for maintenance. The purpose of this work is the implementation and follow-up of a maintenance management plan based on a failure mode analysis and autonomous maintenance and preventive maintenance with the purpose of keeping the equipment in optimal conditions, maintaining an adequate level of availability and extending the useful life of the assets. With the simulation of the Arena program, a possible availability of 95% was evidenced, which corresponds to being adequate for the optimal operation of the equipment and the continuity of the projects.Acceso restringido temporalmente
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Lean Maintenance Design to Optimize the Manufacturing Process: A Peruvian Textile Company Case(Trans Tech Publications Ltd, 2024-01-01)In recent years, the textile industry has increased its exports compared to previous years and produces thousands of jobs per year. However, some manufacturing companies in the textile industry experience low efficiency, such as the current textile company under study associated with unplanned machine downtime and idle time. In this sense, this study aims to promote the capacity, productivity, and efficiency of textile companies that manufacture garments. Therefore, a Lean Maintenance model supported by the integration of Lean Manufacturing instruments and techniques such as TPM, 5S, Kaizen is proposed in order to improve machine availability and quality through management metrics. After the implementation of the proposed tool integration, the activities of the operations were standardized, an increase in efficiency was generated, and a favorable change in maintenance metrics was achieved.Acceso restringido temporalmente
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A diverse, unbiased group decision-making framework for assessing drivers of the circular economy and resilience in an agri-food supply chain(Taylor and Francis Ltd., 2024-01-01)The circular economy (CE) and supply chain resilience have received significant scientific attention in the recent supply chain literature. Incorporating CE practices and resilience practices into a supply chain enables companies to address their sustainability goals. This research explores the joint impact of implementing CE practices and resilience practices in an agri-food supply chain in Peru. The synergetic assessment of CE practices and resilience practices in a supply chain constitutes a multi-criteria decision-making challenge, requiring the involvement of subject-matter experts. Most studies have selected subject-matter experts based on the researchers’ convenience, which may lead to biased evaluations by some experts, resulting in unreliable study results. To mitigate potential bias, this research introduces a new framework named Diverse and Unbiased Group Decision-Making (DUGDM). Subsequently, the study examines the interaction between the drivers of CE and resilience using the Grey-DEMATEL method. The results indicate that drivers, such as the economic growth level, agricultural contamination, and collaborative operation of multiple firms are most influential in the successful integration of circular economy and resilience into a Peruvian agri-food supply chain system.Acceso restringido temporalmente
