Volumen 13, Número 3, Julio - Setiembre, 2025, Páginas 81 al 90DOI: https://doi.org/10.37787/2c53fe39ARTÍCULO DE REVISIÓN Tecnologías de la información de la cadena de suministro empresarial: Una revisión sistemática.Business Supply Chain Information Technologies: A Systematic Review.Luis M. Llanos 1*, Dennis Noriega 2, Lucio Yep 2 y Frans Fuentes1RESUMENLa transformación de las estrategias tecnológicas en un contexto de la globalización viene transformando de forma incremental la gestión empresarial, teniendo como prioridad migrar al uso de tecnologías de la información (TI) en la gestión de la cadena de suministro (GCS), la investigación contribuyo a identificar y describir las TI más importantes a través de la metodología PRISMA, lo que permite realizar un análisis transparente y sistemático de los antecedentes, entre las tecnologías más relevantes esta la inteligencia artificial (IA) y el aprendizaje automático(ML), que ayudan a la gestión de la empresa mediante la predicción de los comportamientos de los mercados; ofrecen trazabilidad y seguridad en las transacciones (blockchain (BC); internet de las cosas (IoT), que permite el monitorio y control en tiempo real de los procesos logísticos y la automatización robótica de procesos (RPA) permitiendo incrementar la eficiencia en los procesos funcionales, los resultados obtenidos evidencian el impacto positivo reduciendo los tiempos en el procesamiento de grandes volúmenes de datos e información, aumento de la competitividad, mejora en la resiliencia de la cadena de suministro, permitiendo la satisfacción de cliente, las TI desarrollan capacidades en el ser humano como el análisis de datos e información permitiendo tomar decisiones estratégicas.Palabras clave: cadena suministros; inteligencia artificial; IoT; Blockchain; automatización robótica de procesos.ABSTRACTThe transformation of technological strategies in a context of globalisation is gradually transforming business management, with the priority being to migrate to the use of information technology (IT) in supply chain management (SCM). The research contributed to identifying and describing the most important IT through the PRISMA methodology, which allows for a transparent and systematic analysis of the background. Among the most relevant technologies are artificial intelligence (AI) and machine learning (ML), which help in business management by predicting market behaviour; they offer traceability and security in transactions (blockchain (BC)); the Internet of Things (IoT), which enables real-time monitoring and control of logistics processes; and robotic process automation (RPA), which increases the efficiency of functional processes. The results obtained show a positive impact, reducing the time taken to process large volumes of data and information, increasing competitiveness, improving the resilience of the supply chain, enabling customer satisfaction, and allowing IT to develop human capabilities such as data and information analysis, enabling strategic decisions to be made.Keywords: supply chain; artificial intelligence; IoT; Blockchain; robotic process automation.* Autor para correspondencia Universidad Nacional de Jaén, Perú. Email: luis.llanos@unj.edu.pe, ingfrans@unj.edu.pe 2 Universidad Nacional de Trujillo, Perú. Email: noriegadennis5@gmail.com, autor3@gmail.comINTRODUCCIÓNLa GCS está atravesando por una transformación profunda, impulsada por las TI en un entorno complejo empresarial caracterizado por la globalización y la complejidad de los mercados, el uso de los robots de software (RS) para automatizar tareas procesando grandes volúmenes de información (MVI), minimizando errores humanos, costos y tiempo, enfocándose al análisis y toma de decisiones ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"CkUtxxbT","properties":{"formattedCitation":"(Escandon-Barbosa & Salas-Paramo, 2025)","plainCitation":"(Escandon-Barbosa & Salas-Paramo, 2025)","noteIndex":0},"citationItems":[{"id":7831,"uris":["http://zotero.org/users/8164076/items/5SURY253"],"itemData":{"id":7831,"type":"article-journal","abstract":"Purpose: Technological advancements allow us to access diverse resources such as artificial intelligence, machine learning, and virtual reality. As access to resources becomes easier, their effective use becomes crucial for improving companies’ strategic management capacity and resource efficiency. Thus, this research seeks to explore the central role of digital technologies in the relationship between strategic decisions and actions that impact companies’ sustainable performance. To achieve this objective, a survey was conducted among 400 international companies with active commercial presence in various countries and that, in turn, rely heavily on digital technologies to drive their global operations. These data were processed using a structural equation model to analyze the relationships between the study variables. Thus, the findings reveal that strategic choices significantly improve the performance of both Born Globals and Gradual Internationalizers Firms by adopting new technologies and creative business models.","container-title":"Journal of Open Innovation: Technology, Market, and Complexity","DOI":"10.1016/j.joitmc.2025.100536","ISSN":"21998531","issue":"2","journalAbbreviation":"Journal of Open Innovation: Technology, Market, and Complexity","language":"en","page":"100536","source":"DOI.org (Crossref)","title":"Driving success: Leveraging strategic decision-making and digital technology for sustainable performance","title-short":"Driving success","volume":"11","author":[{"family":"Escandon-Barbosa","given":"Diana"},{"family":"Salas-Paramo","given":"Jairo"}],"issued":{"date-parts":[["2025",6]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Escandon-Barbosa & Salas-Paramo, 2025); así como IoT diseñado para interconectar todos los equipos industriales ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"EBxjmY1c","properties":{"formattedCitation":"(Ahmed et\\uc0\\u160{}al., 2023)","plainCitation":"(Ahmed et al., 2023)","noteIndex":0},"citationItems":[{"id":7824,"uris":["http://zotero.org/users/8164076/items/PSM4PFF2"],"itemData":{"id":7824,"type":"article-journal","abstract":"The Industrial Internet of Things (IIoT) is recognized as the fourth industrial revolution as it enhances productivity, dependability, and competitive performance by concentrating on profitability. IIoT-enabled technologies have been reviewed and implemented in several research, but more research into the opportunities and challenges they present is necessary. This paper explores IIoT-enabled technologies and infrastructure, their role in global industrial growth, applications, challenges, and future directions. IIoT applications use the intelligence of things to solve industrial problems like supply chain mismanagement, data privacy risks, a weak cloud strategy, cost containment, and others. For instance, fog computing reduces parking, platform, fuel, and CO2 emissions. A blockchain-based security framework for the cement sector can resolve 51% of security issues and Sybil attacks caused by consensus algorithms like Proof of Work (PoW). Major companies’ performance depends on well-designed IIoT infrastructure, despite significant challenges. Industrial technologies will improve as research and experimentation advance IIoT infrastructure.","container-title":"Computers and Electrical Engineering","DOI":"10.1016/j.compeleceng.2023.108847","ISSN":"00457906","journalAbbreviation":"Computers and Electrical Engineering","language":"en","page":"108847","source":"DOI.org (Crossref)","title":"Industrial Internet of Things enabled technologies, challenges, and future directions","volume":"110","author":[{"family":"Ahmed","given":"Shams Forruque"},{"family":"Alam","given":"Md. Sakib Bin"},{"family":"Hoque","given":"Mahfara"},{"family":"Lameesa","given":"Aiman"},{"family":"Afrin","given":"Shaila"},{"family":"Farah","given":"Tasfia"},{"family":"Kabir","given":"Maliha"},{"family":"Shafiullah","given":"Gm"},{"family":"Muyeen","given":"S.M."}],"issued":{"date-parts":[["2023",9]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Ahmed et al., 2023), en supervisión de biomateriales, productos químicos en cadena productiva de medicamentos ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"9ph2vE9F","properties":{"formattedCitation":"(Sharma et\\uc0\\u160{}al., 2020)","plainCitation":"(Sharma et al., 2020)","noteIndex":0},"citationItems":[{"id":7751,"uris":["http://zotero.org/users/8164076/items/ZE9GDSMQ"],"itemData":{"id":7751,"type":"chapter","abstract":"The Internet of Things (IoT) relates to the Internet working of different types of physical devices that are entrenched with transducers including sensors, detectors, actuators, electronic components, and equipment and website links, in order to maintain the association and stress-free interchange of data in a real-time environment. In respect to its practical world applications, the IoT has the prospect of entirely transforming the pharma industry by facilitating and mechanizing the isolated nursing of patients, the innovation of different types of drugs, their admittance, and much more. The combination of the IoT with the growing digitization of figures in the pharma segment has led to a new direction and opened the floodgates for enormous changes and industrial scale innovations. While striving for ingenious inventions, the software needs to keep pace. As previously observed, artificial intelligence (AI) and machine learning are providing tremendous opportunities in the pharmaceutical industry. Similarly, the IoT offers pharma production with an assortment of innovative prospects, such as an improved mechanism for drug trade and better analytical tools. Now the question is how can the IoT be used to benefit the pharmaceutical industry? The answer is that IoT sensors and detectors can help in enabling the optimal circumstances for supervising different styles of biomaterials and chemicals, detecting tool flaws, and it can be also used to assist in the prevention of fraudulent drug activities. People who are involved in industries like pharmaceuticals work in a risk-prone industry where they must avoid asset failures at any cost, as making mistakes is unacceptable because quality control has a direct impact on the health of the consumer and there should be no opportunities for errors to be made. There are a variety of problems that may arise in plants during the manufacture of drugs, such as wear and tear of equipment with time, corrosion, excessive voltage, and destruction caused by the chemicals used. Keeping a proper track of all these risks is crucial to meet the desired quality of the drug, hence a number of sensors are used for the assimilation of enormous amounts of data from different departments that help in managing, controlling, and supervising everything that takes place, initiating a sequence response for better efficacy and control, which will eventually reduce the production cost, minimize waste, and allow for better control.","container-title":"An Industrial IoT Approach for Pharmaceutical Industry Growth","ISBN":"978-0-12-821326-1","note":"DOI: 10.1016/B978-0-12-821326-1.00006-1","page":"153-190","publisher":"Academic Press","source":"ScienceDirect","title":"Chapter 6 - Internet of Things applications in the pharmaceutical industry","URL":"https://www.sciencedirect.com/science/article/pii/B9780128213261000061","author":[{"family":"Sharma","given":"Deepak Kumar"},{"family":"Bhargava","given":"Saakshi"},{"family":"Singhal","given":"Kartik"}],"editor":[{"family":"Balas","given":"Valentina Emilia"},{"family":"Solanki","given":"Vijender Kumar"},{"family":"Kumar","given":"Raghvendra"}],"accessed":{"date-parts":[["2025",9,17]]},"issued":{"date-parts":[["2020",1,1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Sharma et al., 2020). Actualmente la tecnología IoT ha transformado los modelos de negocio de comercio electrónico va más allá de optimizar procesos en CS, con un eco cada vez mayor en la toma de decisiones basados en datos ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"V08QvPQL","properties":{"formattedCitation":"(Shamsuzzoha & Pelkonen, 2025; Su et\\uc0\\u160{}al., 2025)","plainCitation":"(Shamsuzzoha & Pelkonen, 2025; Su et al., 2025)","noteIndex":0},"citationItems":[{"id":7757,"uris":["http://zotero.org/users/8164076/items/HPZM4AET"],"itemData":{"id":7757,"type":"article-journal","abstract":"This study proposes a robotic process automation (RPA) model to streamline and optimize order-handling procedures in supply chain management. The current manual approach to order handling poses challenges, including limited accessibility and significant cognitive demands on employees. An information systems design methodology is applied to analyze and improve the process, with data gathered through semi-structured interviews to address these issues. The findings highlight that reducing manual labor alleviates workload imbalances and saves time in supply chain automation. Moreover, automating repetitive tasks through well-designed software bots minimizes the risk of human error. While this research focuses on applying RPA in order handling, future studies should explore the potential of artificial intelligence-driven RPA to enhance process automation further.","container-title":"Supply Chain Analytics","DOI":"10.1016/j.sca.2025.100102","ISSN":"2949-8635","journalAbbreviation":"Supply Chain Analytics","page":"100102","source":"ScienceDirect","title":"A robotic process automation model for order-handling optimization in supply chain management","volume":"9","author":[{"family":"Shamsuzzoha","given":"Ahm"},{"family":"Pelkonen","given":"Sini"}],"issued":{"date-parts":[["2025",3,1]]}}},{"id":7749,"uris":["http://zotero.org/users/8164076/items/HV3PEN79"],"itemData":{"id":7749,"type":"article-journal","abstract":"The rapid development of the Internet of Things (IoT) is reshaping e-commerce, driving business model innovation and enhancing operational efficiency. However, existing research primarily focuses on specific application scenarios of IoT, while lacking a systematic exploration of its overall development trends, core research topics, and challenges. To address this gap, this study employed BERTopic topic modeling to systematically analyze key research themes and evolutionary trends of IoT in the e-commerce domain, based on 169 highly relevant papers from the Web of Science database (2010–2024). The findings revealed four core themes: (1) the transformation of e-commerce business models driven by IoT technologies, (2) the role of blockchain in data security and trust mechanisms, (3) the synergy between smart logistics and e-commerce, and (4) privacy protection and personal data management in the IoT ecosystem. Additionally, this study identified a shift in IoT applications from an initial focus on supply chain optimization to an increasing emphasis on data-driven decision-making, intelligent business models, and data privacy protection. By conducting an in-depth analysis of the dynamic evolution of these themes, this research not only fills the knowledge gap regarding the current state and trends of IoT research in e-commerce, but also provides the academic community with an innovative method applicable to large-scale text data analysis. Furthermore, for businesses and policymakers, strengthening cross-sectoral technological integration, improving privacy protection mechanisms, and enhancing policy support are suggested to promote the sustainable development of IoT and e-commerce. This research enriches the academic discourse on the synergy between IoT and e-commerce in the context of digital transformation, and provides strategic guidance for practitioners.","container-title":"Internet of Things","DOI":"10.1016/j.iot.2025.101604","ISSN":"2542-6605","journalAbbreviation":"Internet of Things","page":"101604","source":"ScienceDirect","title":"Detecting latent topics and trends in IoT and e-commerce using BERTopic modeling","volume":"32","author":[{"family":"Su","given":"Yu-Sheng"},{"family":"Wang","given":"Jun-qing"},{"family":"Tu","given":"Shou-Hsi"},{"family":"Liao","given":"Kuo-Ti"},{"family":"Lin","given":"Chien-Liang"}],"issued":{"date-parts":[["2025",7,1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Shamsuzzoha & Pelkonen, 2025; Su et al., 2025). La IA es una tecnología que permite optimizar y analizar datos como gastos y gestión de contratos, predicción de ventas y comportamientos proveedor-cliente ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"trU4Fcyj","properties":{"formattedCitation":"(Bhat & Aljuneidi, 2025; Guida et\\uc0\\u160{}al., 2025; Rahman Mahin et\\uc0\\u160{}al., 2025)","plainCitation":"(Bhat & Aljuneidi, 2025; Guida et al., 2025; Rahman Mahin et al., 2025)","noteIndex":0},"citationItems":[{"id":7804,"uris":["http://zotero.org/users/8164076/items/4YXP2ARM"],"itemData":{"id":7804,"type":"article-journal","abstract":"The viability of intertwined supply networks (ISNs) has recently been studied as a critical topic in operations management. Modelling the viability of ISNs is considered a promising tool to meet the demands of extraordinary events, such as the Russo-Ukrainian War and the COVID-19 pandemic. To enhance the viability of ISNs, the structures of ISN must be modelled, and the behavioral dynamics of interactions between firms in a changing environment should be analyzed. In this study, a trophic chain-based dynamic formulation of ISN viability is presented, and a solution methodology for dynamic analysis of the ISN viability model is designed. The concept of artificial neural networks (ANNs) in ISN analysis is introduced to predict and analyze future behavioral strategies in buyer-supplier relations. The dynamic model of ISN is represented by a system of nonlinear differential equations and described in terms of three dynamic values: suppliers Xτ, focal firms Yτ, and market demand Zτ. The stochastic numerical simulations are performed for the dynamics of ISN model by employing ANNs with a scaled conjugate gradient neural network (SCGNN) in a more advanced and efficient manner. Two numerical cases are investigated to evaluate the performance of the proposed approach. The validation, correctness, and reliability of the proposed stochastic SCGNN technique are analyzed by selecting 78 % of the data for training, 12 % for validation, and 10 % for testing. The correctness of the scheme is authenticated through the overlapping of the proposed and state-of-the-art results. Moreover, the statistical analysis is presented graphically in terms of mean square error, state transitions, function fitness, error histograms. The regression coefficient values are calculated as 1 for each scenario presents the perfect model. Finally, a comparison of numerical results, which shows the overlapping is examined and the absolute error is performed between 10−05 to 10−07. The small mean square error performances enhance the correctness of the scheme. These results indicate that the dynamical model can effectively analyze the ISN structures and help researchers and practitioners ensure the survival of supply chains during extraordinary events.","container-title":"Applied Soft Computing","DOI":"10.1016/j.asoc.2024.112503","ISSN":"1568-4946","journalAbbreviation":"Applied Soft Computing","page":"112503","source":"ScienceDirect","title":"Viable intertwined supply network: Modelling and dynamic analysis using artificial neural networks","title-short":"Viable intertwined supply network","volume":"168","author":[{"family":"Bhat","given":"Shahid Ahmad"},{"family":"Aljuneidi","given":"Tariq"}],"issued":{"date-parts":[["2025",1,1]]}}},{"id":7789,"uris":["http://zotero.org/users/8164076/items/CKTGGEFA"],"itemData":{"id":7789,"type":"article-journal","abstract":"This paper investigates the impact of artificial intelligence (AI) on spend classification in buyer firms, using the organizational information processing theory (OIPT) as a reference framework. Existing research on the use of AI in procurement lacks a holistic approach that effectively integrates human oversight. This gap is particularly evident in procurement activities beyond automating repetitive tasks, especially in advanced analyses supporting strategic purchasing decisions, such as spend classification. Through a case study approach focusing on providers of AI-based spend classification solutions, this research highlights how AI addresses the substantial information processing needs that exceed the internal capabilities of buyer firms. By aligning these needs with the capabilities enabled by the adoption of AI, the study demonstrates a significant advancement in spend classification practices. This research applies the theoretical constructs of the OIPT at the intersection of two relatively unexplored domains—spend classification and AI and aims to translate these constructs into actionable insights for professionals, thereby making a significant contribution to the field.","container-title":"Journal of Purchasing and Supply Management","DOI":"10.1016/j.pursup.2025.100993","ISSN":"14784092","issue":"3","journalAbbreviation":"Journal of Purchasing and Supply Management","language":"en","page":"100993","source":"DOI.org (Crossref)","title":"AI meets spend classification: A new frontier in information processing","title-short":"AI meets spend classification","volume":"31","author":[{"family":"Guida","given":"Michela"},{"family":"Caniato","given":"Federico"},{"family":"Moretto","given":"Antonella"}],"issued":{"date-parts":[["2025",6]]}}},{"id":7766,"uris":["http://zotero.org/users/8164076/items/BH7SW2VH"],"itemData":{"id":7766,"type":"article-journal","abstract":"Managing the supply chain is crucial to success in the competitive business sector. Demand forecasting using sales data is one of the major things in supply chain management because it is directly connected to profit margins, inventory levels, sales, and customer satisfaction. This research tried to provide an innovative approach to sales prediction using advanced machine learning methods to enhance supply chain operations and boost the predictive accuracy of supply chain models after analyzing historical sales data and considering different factors like seasonality, trends, and stock. Various machine learning algorithms were applied, including Linear Regression, Elastic Net Regression, KNN, Random Forest, and the ensemble Voting Regressor. The performance of Random Forest and KNN is very well but the Voting Regressor is better than other models for its strength of multiple algorithms. The Voting Regressor provides the lowest RMSE of 1.54 and the highest R2 of 0.9999. This ensemble method improves sales forecasting accuracy by reducing errors and ensuring computational efficiency. It also provides more reliable tools to manage inventory, prevent overstocks, and minimize holding costs. This research presents the importance of machine learning integration in supply chain management. It shows the Voting Regressor as the most effective approach for demand forecast. Future research could explore the model’s application in broader markets, integrating other key factors and deep learning algorithms to refine predictive capabilities later.","collection-title":"4th International Conference on Evolutionary Computing and Mobile Sustainable Networks","container-title":"Procedia Computer Science","DOI":"10.1016/j.procs.2025.01.006","ISSN":"1877-0509","journalAbbreviation":"Procedia Computer Science","page":"470-479","source":"ScienceDirect","title":"Enhancing Sustainable Supply Chain Forecasting Using Machine Learning for Sales Prediction","volume":"252","author":[{"family":"Rahman Mahin","given":"Md. Parvezur"},{"family":"Shahriar","given":"Munem"},{"family":"Das","given":"Ritu Rani"},{"family":"Roy","given":"Anuradha"},{"family":"Reza","given":"Ahmed Wasif"}],"issued":{"date-parts":[["2025",1,1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Bhat & Aljuneidi, 2025; Guida et al., 2025; Rahman Mahin et al., 2025), la inteligencia artificial (IA) y el machine learning (ML) destacan por su capacidad de automatizar la clasificación de gastos, optimizar contratos, predecir ventas y anticipar el comportamiento proveedor–cliente, además de potenciar el marketing relacional mediante la identificación y aprovechamiento de patrones en el mercado ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"bWDluIwL","properties":{"formattedCitation":"(Cuesta-Vali\\uc0\\u241{}o et\\uc0\\u160{}al., 2025; S. K. Roy et\\uc0\\u160{}al., 2025)","plainCitation":"(Cuesta-Valiño et al., 2025; S. K. Roy et al., 2025)","noteIndex":0},"citationItems":[{"id":7800,"uris":["http://zotero.org/users/8164076/items/4CSIWS7K"],"itemData":{"id":7800,"type":"article-journal","abstract":"Grounded in consumer motivation theory, this study examined how trust in AI, along with its credibility and versatility, drives consumers to adopt AI in online retail, ultimately improving consumer satisfaction and happiness. Survey data from 1,471 consumers in Spain were analysed to scrutinise these linkages. The findings confirmed the proposed estimated model: trust, credibility, and versatility significantly motivated AI adoption, which in turn positively influenced satisfaction and consumer happiness. Сonversely, our results cannot evince the influence of two drivers, namely privacy/security and UI/UX, on consumer motivation to use AI for shopping. The outcomes of this study underscore the strategic value of trustworthy and adaptive AI in shaping consumer behaviour and improving retail experiences, suggesting practical guidance for businesses aiming to foster engagement and emotional connection with their target consumers through AI-driven platforms.","container-title":"European Research on Management and Business Economics","DOI":"10.1016/j.iedeen.2025.100278","ISSN":"2444-8834","issue":"2","journalAbbreviation":"European Research on Management and Business Economics","page":"100278","source":"ScienceDirect","title":"The role of AI as an unconventional salesperson in consumer buying decisions, satisfaction and happiness","volume":"31","author":[{"family":"Cuesta-Valiño","given":"Pedro"},{"family":"Kazakov","given":"Sergey"},{"family":"Durán-Álamo","given":"Patricia"},{"family":"Gutiérrez-Rodríguez","given":"Pablo"}],"issued":{"date-parts":[["2025",5,1]]}}},{"id":7765,"uris":["http://zotero.org/users/8164076/items/Z3YCBHCD"],"itemData":{"id":7765,"type":"article-journal","abstract":"This study explores the interlinkages between artificial intelligence (AI), dynamic capabilities, and relationship marketing (RM) outcomes. Drawing upon insights from dynamic capabilities and RM theory, this study delineates the strategies and initiatives organizations can adopt using machine learning (ML) and AI to enhance their adaptability to changing market dynamics and customer preferences, in order to develop and maintain stronger relationships with their customers. Based on qualitative data from 67 interviews with managers in different organizations in India, this study contributes to existing theoretical knowledge and managerial practices, as it proposes a comprehensive research framework that demonstrates how AI technologies can enhance customer relationships throughout the entire customer journey. More specifically, it adopts a dynamic capabilities lens to extend our understanding of the marketing applications of AI by conceptualizing the dual role of AI as (a) a distinct organizational capability and (b) an enabler of dynamic capabilities, improving firms’ position to sense, seize, and transform organizational resources and fortify customer relationships. Our findings also highlight several facilitators and barriers to the adoption of AI, both as a dynamic capability and as an enabler for RM.","container-title":"Journal of Business Research","DOI":"10.1016/j.jbusres.2025.115309","ISSN":"01482963","journalAbbreviation":"Journal of Business Research","language":"en","page":"115309","source":"DOI.org (Crossref)","title":"AI-capable relationship marketing: Shaping the future of customer relationships","title-short":"AI-capable relationship marketing","volume":"192","author":[{"family":"Roy","given":"Sanjit K."},{"family":"Tehrani","given":"Ali N."},{"family":"Pandit","given":"Ameet"},{"family":"Apostolidis","given":"Chrysostomos"},{"family":"Ray","given":"Subhasis"}],"issued":{"date-parts":[["2025",4]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Cuesta-Valiño et al., 2025; S. K. Roy et al., 2025), asimismo, la combinación IA–Blockchain (BC) mejora la velocidad y seguridad en el comercio electrónico, mientras que el BC de forma independiente asegura la trazabilidad en cadenas agrícolas y logísticas gracias a su carácter descentralizado, transparente e inmutable ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"JH0l6ZVj","properties":{"formattedCitation":"(Pang et\\uc0\\u160{}al., 2024; Valami & Ahmadifar, 2025; Zhu, 2025)","plainCitation":"(Pang et al., 2024; Valami & Ahmadifar, 2025; Zhu, 2025)","noteIndex":0},"citationItems":[{"id":7771,"uris":["http://zotero.org/users/8164076/items/LIWNGEJ6"],"itemData":{"id":7771,"type":"article-journal","abstract":"The integration of blockchain technology in agricultural traceability has shown immense potential, yet its widespread adoption faces significant roadblocks. Using bulk product traceability as a foundational reference, this paper presents a comprehensive evaluation framework for Blockchain-based Agricultural Traceability. The framework accentuates product identification and data traceability across the supply chain, addressing traceability disconnections caused by bulk product blending. It dives into depth levels from adoption decisionmaking to system design, development, and deployment, emphasizing the critical aspects of traceability compliance and standardization. As a result, we identified the obstacles to adopting agricultural digital traceability and pave the pathway to traceability system deployment. We examined the barriers to implementing digital traceability of agricultural products, taking the Australian grain supply chain as an example. Our findings reveal that lack of standardization and participation barriers are the primary challenges in implementing digital traceability for agricultural products. Our paper offers insights and recommendations for researchers, industry practitioners, and business owners to overcome these challenges and enable digital traceability of agricultural products in global supply chains.","container-title":"Computers and Electronics in Agriculture","DOI":"10.1016/j.compag.2024.109548","ISSN":"01681699","journalAbbreviation":"Computers and Electronics in Agriculture","language":"en","page":"109548","source":"DOI.org (Crossref)","title":"A survey on evaluation of blockchain-based agricultural traceability","volume":"227","author":[{"family":"Pang","given":"Shaoning"},{"family":"Teng","given":"Shyh Wei"},{"family":"Murshed","given":"Manzur"},{"family":"Bui","given":"Cuong Van"},{"family":"Karmakar","given":"Priyabrata"},{"family":"Li","given":"Yanyu"},{"family":"Lin","given":"Hao"}],"issued":{"date-parts":[["2024",12]]}}},{"id":7747,"uris":["http://zotero.org/users/8164076/items/UJHPXXM3"],"itemData":{"id":7747,"type":"article-journal","abstract":"Modern transportation systems increasingly rely on information technologies to address key challenges such as ensuring product quality and detecting counterfeit goods. Existing systems track goods online using Internet of Things (IoT) sensors; however, in certain areas—due to factors like adverse weather or geographical barriers—consistent Internet access is unavailable. This gap presents a vulnerability where containers may be replaced with counterfeit cargo. In this paper, we propose a model that uses Global Positioning System (GPS) data to detect counterfeiting containers. Each container is equipped with a digital identifier that transmits an encrypted unique ID (Ki) to authorized receivers. This ID, along with the GPS ID (Gi) and truck engine ID (IDi), forms a triple identifier (Ki, Gi, IDi), which is hashed using the Secure Hash Algorithm (SHA-3) and stored in a blockchain for product tracking. Since the Gi and IDi are inherently available on each truck, no additional IoT sensors are needed, reducing implementation costs. Furthermore, the model records information on all components of a shipment in the blockchain, allowing for comprehensive tracking and authentication along the supply chain, both at authorized intermediate control stations and at the final destination. The proposed model has been evaluated across various qualitative criteria including security, cost-efficiency, scalability, flexibility, traceability, and transparency. It is particularly well-suited for routes where IoT-based tracking is impractical or where GPS and Internet access are limited.","container-title":"Research in Transportation Business & Management","DOI":"10.1016/j.rtbm.2025.101329","ISSN":"2210-5395","journalAbbreviation":"Research in Transportation Business & Management","page":"101329","source":"ScienceDirect","title":"A low cost blockchain-based model for detecting of counterfeiting container in the road transport system","volume":"60","author":[{"family":"Valami","given":"Zahra Hadizadeh"},{"family":"Ahmadifar","given":"HamidReza"}],"issued":{"date-parts":[["2025",6,1]]}}},{"id":7746,"uris":["http://zotero.org/users/8164076/items/CLS6839D"],"itemData":{"id":7746,"type":"article-journal","abstract":"Nowadays, logistics supply chain management is facing increasingly complex challenges, and the efficient and secure processing and transmission of large amounts of data has become a key demand in the industry. The study employed machine learning, deep learning, and other methods to analyze and predict consumer behavior, inventory levels, and transportation methods, thereby achieving optimal control over inventory and logistics. Blockchain technology establishes decentralized databases to ensure high transparency and immutability of transaction records in the supply chain, thus enhancing mutual trust and collaboration efficiency among all parties. The duration of the DDoS (Distributed Denial of Service) attack in the study reached 10 minutes, with a defense success rate of 100%, and did not cause any leakage of e-commerce big data information. This project proposes advanced data analysis and anti-counterfeiting technology aimed at improving the response speed and security performance of e-commerce, thereby promoting the development of the e-commerce industry towards a more intelligent and automated direction.","collection-title":"Sixth International Conference on Futuristic Trends in Networks and Computing Technologies (FTNCT06), held in Uttarakhand, India","container-title":"Procedia Computer Science","DOI":"10.1016/j.procs.2025.04.045","ISSN":"1877-0509","journalAbbreviation":"Procedia Computer Science","page":"923-930","source":"ScienceDirect","title":"E-Commerce Big Data Logistics Supply Chain Control System Based on Artificial Intelligence and Blockchain","volume":"259","author":[{"family":"Zhu","given":"Hao"}],"issued":{"date-parts":[["2025",1,1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Pang et al., 2024; Valami & Ahmadifar, 2025; Zhu, 2025), la TI gemelos digitales (GD) es una tecnología potente que permite la creación virtual de sistemas mediante sensores IoT interactuando con el mundo físico real, esta TI se mejora en gran medida en cuanto a la seguridad de sus datos al registrarse en plataforma BC que brinda una característica inmutable y clara en los datos ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"GHUMOF4B","properties":{"formattedCitation":"(Joshi et\\uc0\\u160{}al., 2025; Lehner et\\uc0\\u160{}al., 2024)","plainCitation":"(Joshi et al., 2025; Lehner et al., 2024)","noteIndex":0},"citationItems":[{"id":7783,"uris":["http://zotero.org/users/8164076/items/GU9ZUYY9"],"itemData":{"id":7783,"type":"chapter","abstract":"Technology advances over the last few decades have entirely altered traditional, natural processes used by industry, education, and healthcare. These changes have disrupted workflow processes and led to new solutions and procedures. Blockchain based DT technology facilitates several opportunities across multiple industries, demonstrating its potential for significant benefits. Numerous studies have been done in this field, but only a small number have been able to comprehend how this technology is used and to summarize the research trends. The term “digital twin” refers to the replica of a real thing or product as a digital representation. The digital twin has intelligent components equipped with sensors that enable real-time data collection about operational status and working circumstances, among other factors. The data collected by these sensors is received and processed by a cloud-based system. Cross-validation is crucial for ensuring the reliability of physical data. It can be achieved by utilizing multiple sensor sources with overlapping fields of view. The blockchain can be utilized for storing cross-validated data to maintain the data's integrity and reliability. Reliable data logged on the blockchain can be utilized in data-driven systems to monitor, diagnose, and optimize control of product lifecycle events. Digital Twins can be utilized for intelligent data analysis, enabling the identification of errors and the recommendation of preventive measures prior to critical incidents. DT empowerment with blockchain in industrial use cases addresses the main challenges of dispersed data repositories, unreliable data distribution, and the need for predictive maintenance. This chapter highlights the benefits of using blockchain-based digital twin and comprehensively analyzes recent research findings on blockchain-based DTs. The DT offers significant advantages that are noteworthy and advantageous. This chapter presents an overview of the latest research trends in Blockchain and Digital twin while examining the existing challenges.","container-title":"Digital Twins for Smart Cities and Villages","ISBN":"978-0-443-28884-5","note":"DOI: 10.1016/B978-0-443-28884-5.00026-9","page":"601-630","publisher":"Elsevier","source":"ScienceDirect","title":"Chapter 26 - Rise of blockchain based digital twin: A transformative tool for new research trends","title-short":"Chapter 26 - Rise of blockchain based digital twin","URL":"https://www.sciencedirect.com/science/article/pii/B9780443288845000269","author":[{"family":"Joshi","given":"Rahul"},{"family":"Kumari","given":"Suman"},{"family":"Pandey","given":"Krishna"}],"editor":[{"family":"Iyer","given":"Sailesh"},{"family":"Nayyar","given":"Anand"},{"family":"Paul","given":"Anand"},{"family":"Naved","given":"Mohd"}],"accessed":{"date-parts":[["2025",9,17]]},"issued":{"date-parts":[["2025",1,1]]}}},{"id":7782,"uris":["http://zotero.org/users/8164076/items/GW42A5YI"],"itemData":{"id":7782,"type":"article-journal","abstract":"In today's VUCA-defined age, accelerated by the rapid digital transformation brought on by the COVID-19 pandemic, the business sector needs to be able to adapt to expected and unexpected changes. Consistently improving the product quality and managing the whole product life cycle, starting from the new product development (NPD) process, and the related data, are important aspects of keeping a company competitive in a global landscape. This paper highlights the growing potential of Industry 4.0, particularly the digital thread (DTH) and digital twin (DT), in addressing these challenges. The research revealed existing gaps in clarity and practical guidelines for digital twin prototypes (DTP) and DTH in the existing literature. Moreover, additional issues within product life cycle management (PLM) were stated, regarding frequent data loss and the complexity of product audits in the perspective of a continuous improvement. Therefore, a definition and novel framework for DTP and DTH implementation was proposed, after analyzing and comparing state of the art literature. This framework is additionally based on product audits carried out during the design stage of the product development process using requirements engineering and quality control information added within the suggested framework. Preliminary tests with DTP and DTH commercial off-the-shelves and prototype solutions were carried out with a consumer product. The tests enabled delivering a better understanding of DTPs, their potential, and their implications for decision-making and implementation.","container-title":"Procedia Computer Science","DOI":"10.1016/j.procs.2024.02.104","ISSN":"18770509","journalAbbreviation":"Procedia Computer Science","language":"en","page":"2875-2886","source":"DOI.org (Crossref)","title":"Digital twin and digital thread within the product lifecycle management","volume":"232","author":[{"family":"Lehner","given":"Christine"},{"family":"Padovano","given":"Antonio"},{"family":"Zehetner","given":"Christian"},{"family":"Hackenberg","given":"Georg"}],"issued":{"date-parts":[["2024"]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Joshi et al., 2025; Lehner et al., 2024) los GD se busca implementar en los diferentes cadenas de suministro como el sector de la construcción que busca mejorar la productividad y la eficiencia operativa en los procesos constructivos ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"19pAdNVn","properties":{"formattedCitation":"(Moshood et\\uc0\\u160{}al., 2024)","plainCitation":"(Moshood et al., 2024)","noteIndex":0},"citationItems":[{"id":7775,"uris":["http://zotero.org/users/8164076/items/KHB9GHIJ"],"itemData":{"id":7775,"type":"article-journal","abstract":"The construction industry has traditionally been slow to adopt digital technology, resulting in inefficient workflows, frequent cost overruns, and delays. Moreover, its fragmented structure, inherent to market dynamics, exacerbates these challenges. Embracing digitalization and transitioning to Industry 4.0 can substantially enhance efficiency and productivity in construction through increased innovation and improved collaboration, ultimately reducing information gaps and data discrepancies. This study aims to assess the potential integration of digital twin technology across various construction stages, spanning from initial design to project delivery. Existing literature emphasizes the transformative power of digital twin technology in advancing building innovation and environmental sustainability. These virtual replicas are crucial in optimizing industrial manufacturing by harmonizing production processes and societal interactions. A focused examination of digital twin technology applications in construction highlights its ability to streamline coordination and facilitate data sharing among stakeholders. Property owners increasingly recognise the value of digital twin technology in local contexts, driving the digitization of design and collaboration methods in construction. Integrating digital twin technology right from a project's inception and extending it across design phases optimizes project delivery, enhances asset quality, and contributes to societal sustainability. As the nexus between digitalization and sustainability goals strengthens, the construction industry stands at the cusp of a significant transformative journey.","container-title":"Technology in Society","DOI":"10.1016/j.techsoc.2024.102519","ISSN":"0160-791X","journalAbbreviation":"Technology in Society","page":"102519","source":"ScienceDirect","title":"Infrastructure digital twin technology: A new paradigm for future construction industry","title-short":"Infrastructure digital twin technology","volume":"77","author":[{"family":"Moshood","given":"Taofeeq D."},{"family":"Rotimi","given":"James OB."},{"family":"Shahzad","given":"Wajiha"},{"family":"Bamgbade","given":"J. A."}],"issued":{"date-parts":[["2024",6,1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Moshood et al., 2024). Si bien es cierto las TI impulsan RI4.0, hoy en día es aplicable a grandes empresas que poseen infraestructura tecnológica de vanguardia, a diferencia de los países en desarrollo que enfrentan barreras tipo organizativas, tecnológicas para su implementación ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"dyBBllA0","properties":{"formattedCitation":"(Awasthy et\\uc0\\u160{}al., 2025; Elhusseiny & Crispim, 2022)","plainCitation":"(Awasthy et al., 2025; Elhusseiny & Crispim, 2022)","noteIndex":0},"citationItems":[{"id":7812,"uris":["http://zotero.org/users/8164076/items/62ADW6TL"],"itemData":{"id":7812,"type":"article-journal","abstract":"Despite numerous use cases, enterprise-wide implementations of blockchains have seen limited success. This raises the question of when do firms adopt blockchains and do blockchains benefit supply chains. To answer this, we examine a dyadic supply chain consisting of a buyer and a supplier and analyze their traceability effort and pricing decisions. Our results show that the demand-side, supply-side and reputational factors influencing blockchain adoption are primarily complementary and in the absence of one of them, firms can still adopt blockchain. Furthermore, even in the absence of individual benefits for a supply chain partner, there exist conditions under which blockchain adoption benefits the supply chain that can incentivize players to join blockchain. Overall, we contribute by offering a framework that supply chain players can use to assess the likelihood of blockchain implementation success or failure and address the challenges pertaining to incentives and cost imbalances in blockchain implementation.","container-title":"European Journal of Operational Research","DOI":"10.1016/j.ejor.2024.10.019","ISSN":"0377-2217","issue":"3","journalAbbreviation":"European Journal of Operational Research","page":"760-774","source":"ScienceDirect","title":"Blockchain enabled traceability — An analysis of pricing and traceability effort decisions in supply chains","volume":"321","author":[{"family":"Awasthy","given":"Prakash"},{"family":"Haldar","given":"Tanushree"},{"family":"Ghosh","given":"Debabrata"}],"issued":{"date-parts":[["2025",3,16]]}}},{"id":7795,"uris":["http://zotero.org/users/8164076/items/5E974MSW"],"itemData":{"id":7795,"type":"article-journal","abstract":"Industry 4.0 (I4.0) enables SMEs to enhance their manufacturing capabilities and compete globally through the deployment of cutting-edge technologies. This review identifies the barriers and opportunities of adopting industry 4.0 in the manufacturing sector in developed vs. developing countries. In total, 54 studies met the screening criteria. The synthesized factors were classified into dimensions to helps the understanding of what type of difficulties SMEs face in the transition to the 4.0 generation. This study found that developing countries face more barriers but also perceive more opportunities in relation to industry 4.0. Organizational barriers and technical Barriers have been the main types of barriers studied in both sets of countries. In terms of benefits, studies have emphasized 1) gains in terms of operations management, and 2) questions related to market, sustainability and supply chain management.","collection-title":"International Conference on ENTERprise Information Systems / ProjMAN - International Conference on Project MANagement / HCist - International Conference on Health and Social Care Information Systems and Technologies 2021","container-title":"Procedia Computer Science","DOI":"10.1016/j.procs.2021.12.086","ISSN":"1877-0509","journalAbbreviation":"Procedia Computer Science","page":"864-871","source":"ScienceDirect","title":"SMEs, Barriers and Opportunities on adopting Industry 4.0: A Review.","title-short":"SMEs, Barriers and Opportunities on adopting Industry 4.0","volume":"196","author":[{"family":"Elhusseiny","given":"Hussein Magdy"},{"family":"Crispim","given":"José"}],"issued":{"date-parts":[["2022",1,1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Awasthy et al., 2025; Elhusseiny & Crispim, 2022); será cuestión de tiempo para que las PYMES rompan las barreras y encuentren soluciones aplicables y accedan a TI ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"UTPBDmmX","properties":{"formattedCitation":"(Nevi et\\uc0\\u160{}al., 2025)","plainCitation":"(Nevi et al., 2025)","noteIndex":0},"citationItems":[{"id":7772,"uris":["http://zotero.org/users/8164076/items/C49VV2Q8"],"itemData":{"id":7772,"type":"article-journal","abstract":"This study aims to investigate the adoption of artificial intelligence (AI) in micro and small enterprises, particularly pharmacies, exploring the role of technological adoption models and entrepreneurial orientation.A mixed-methods approach was employed, beginning with a qualitative analysis through semi-structured interviews with 11 pharmacists to identify suitable adoption models. This was followed by a quantitative regression analysis study of a final sample of 217 Italian pharmacist orders validating the proposed model processed with SPSS V27.Technology and environmental dimensions, such as individual entrepreneurial orientation, significantly influence AI adoption in micro and small enterprises. However, organizational factors and perceived risk have less impact.The study’s limitations include its focus solely on pharmacies and its geographical scope. Future research could expand into different sectors and regions.The findings suggest that enhancing technological capabilities and aligning them with strategic goals are crucial for successful AI adoption in micro and small enterprises.Understanding the factors influencing AI adoption can foster innovation and competitiveness among small and micro businesses, potentially contributing to economic growth and job creation and more attempts from the rise of AI solutions.This study enriches the understanding of AI adoption dynamics in smaller enterprises, emphasizing the roles of entrepreneurial orientation and specific technological dimensions.","container-title":"European Journal of Innovation Management","DOI":"10.1108/EJIM-07-2024-0770","ISSN":"1460-1060","issue":"11","journalAbbreviation":"European Journal of Innovation Management","page":"209-241","source":"Silverchair","title":"Adoption of AI by micro and small health enterprises: effects of entrepreneurial orientation on the TOE model","title-short":"Adoption of AI by micro and small health enterprises","volume":"28","author":[{"family":"Nevi","given":"Giulia"},{"family":"Pizzichini","given":"Lucia"},{"family":"Bastone","given":"Anna"},{"family":"Dezi","given":"Luca"}],"issued":{"date-parts":[["2025",6,16]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Nevi et al., 2025). 6057900844550820082Las TI, se vienen implementando en diferentes campos como la ingeniería, ciencias sociales, ciencias matemáticas, la gestión administrativa entre otros, mediante el uso de sensores inteligentes, Big Data , minería de datos, permitiendo de bases de datos robustas de datos e información, lo que permite tener un cambio en la gestión de la cadena de suministro, posicionando a las TI como herramientas claves en la mejora de procesos operativos, visibilidad en tiempo real y la capacidad de adaptación de la empresas, es así que en el análisis de los antecedentes de las investigaciones ofrece información clara permitiendo fundamentar decisiones sobre inversiones en TI y construir cadenas de suministro más ágiles y competitivas, tal como lo menciona ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"I9VqIH0s","properties":{"formattedCitation":"(Rumson & Hallett, 2019; Sharifmousavi et\\uc0\\u160{}al., 2024)","plainCitation":"(Rumson & Hallett, 2019; Sharifmousavi et al., 2024)","noteIndex":0},"citationItems":[{"id":7760,"uris":["http://zotero.org/users/8164076/items/FY8MUH9H"],"itemData":{"id":7760,"type":"article-journal","abstract":"Insurance plays a crucial role in human efforts to adapt to environmental hazards. Effective insurance can serve as both a measure to distribute, and a method to communicate risk. In order for insurance to fulfil these roles successfully, policy pricing and cover choices must be risk-based and founded on accurate information. This is reliant on a robust evidence base forming the foundation of policy choices. This paper focuses on the evidence available to insurers and emergent innovation in the use of data. The main risk considered is coastal flooding, for which the insurance sector offers an option for potential adaptation, capable of increasing resilience. However, inadequate supply and analysis of data have been highlighted as factors preventing insurance from fulfilling this role. Research was undertaken to evaluate how data are currently, and could potentially, be used within risk evaluations for the insurance industry. This comprised of 50 interviews with those working and associated with the London insurance market. The research reveals new opportunities, which could facilitate improvements in risk-reflective pricing of policies. These relate to a new generation of data collection techniques and analytics, such as those associated with satellite-derived data, IoT (Internet of Things) sensors, cloud computing, and Big Data solutions. Such technologies present opportunities to reduce moral hazard through basing predictions and pricing of risk on large empirical datasets. The value of insurers' claims data is also revealed, and is shown to have the potential to refine, calibrate, and validate models and methods. The adoption of such data-driven techniques could enable insurers to re-evaluate risk ratings, and in some instances, extend coverage to locations and developments, previously rated as too high a risk to insure. Conversely, other areas may be revealed more vulnerable, which could generate negative impacts for residents in these regions, such as increased premiums. However, the enhanced risk awareness generated, by new technology, data and data analytics, could positively alter future planning, development and investment decisions.","container-title":"Science of The Total Environment","DOI":"10.1016/j.scitotenv.2019.01.114","ISSN":"0048-9697","journalAbbreviation":"Science of The Total Environment","page":"598-612","source":"ScienceDirect","title":"Innovations in the use of data facilitating insurance as a resilience mechanism for coastal flood risk","volume":"661","author":[{"family":"Rumson","given":"Alexander G."},{"family":"Hallett","given":"Stephen H."}],"issued":{"date-parts":[["2019",4,15]]}}},{"id":7756,"uris":["http://zotero.org/users/8164076/items/ENRRSUM5"],"itemData":{"id":7756,"type":"article-journal","abstract":"Supply Chain 4.0 is characterized by various factors, including seamless integration and connectivity, the Internet of Things (IoT), Big Data, AI participation, Cyber-Physical Systems (CPSs), flexibility, adaptability, and customer-centricity across different parts of the supply chain. The application of Distributed AI (DAI) systems like Multi-Agent Systems (MAS) opens new horizons to enhance the efficiency, responsiveness, and intelligence of these supply chains. DAI facilitates advanced autonomous decisionmaking and real-time optimization at different stages of the agri-food supply chain, such as demand forecasting, inventory management, production planning, logistics optimization, and quality assurance and control. This article, by focusing on the case of scheduling through the entire supply chain, examines how DAI initiatives, including Multi-Agent Systems (MASs) enhanced with Case-Based Reasoning (CBR), enable the distribution of intelligence across smart, interconnected elements of the supply chain network. It is shown that through the use of DAI in SCM, the performance of the entire supply chain optimizes consistently and adaptively through the use of MAS, in which different parts of SCM collaborate as agents. Supply Chain 4.0 can gain autonomy, self-organization, self-optimization, self-adaptation, robustness, and flexibility, and its knowledge base can be enriched over time by using CBR to learn from past situations. It also discusses the opportunities and challenges associated with the adoption of DAI in Supply Chain 4.0, including operational efficiency, cost reduction, agility enhancement, and improved customer satisfaction. However, several concerns, such as data security, privacy issues, and interoperability, must be addressed.","container-title":"Procedia Computer Science","DOI":"10.1016/j.procs.2024.01.021","ISSN":"18770509","journalAbbreviation":"Procedia Computer Science","language":"en","page":"211-220","source":"DOI.org (Crossref)","title":"Distributed Artificial Intelligence Application in Agri-food Supply Chains 4.0","volume":"232","author":[{"family":"Sharifmousavi","given":"Mahdi"},{"family":"Kayvanfar","given":"Vahid"},{"family":"Baldacci","given":"Roberto"}],"issued":{"date-parts":[["2024"]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Rumson & Hallett, 2019; Sharifmousavi et al., 2024).Sin embargo, la sinergia entre tecnologías como blockchain (BC) y el internet de las cosas (IoT), establecen desafíos como la interoperabilidad y la falta de estándares. Además, las tecnologías de la información tienen algunas limitaciones estructurales como la dependencia de la conexión a internet, fallas en la red, la complejidad de su implementación y mantenimiento. Sumado a la posibilidad de sesgo en los datos, lo cual afecta a la calidad de la información y, en consecuencia, la toma de decisiones estratégicas acertadas.En este contexto el propósito de esta investigación es identificar y describir las TI más relevantes aplicadas en la GCS, así como determinar cuáles son las tecnologías clave actualmente utilizadas en el sector empresarial. Para ello, se recurre al análisis de publicaciones científicas que funcionan como guía y respaldo en torno a la incorporación de TI en la cadena de suministro, además de evaluar el impacto de las TI como la IA, el aprendizaje autónomo (ML), blockchain (BC), IoT y la automatización robótica de procesos (RPA) en la gestión de la cadena de suministro, con el fin de aportar una visión integral sobre sus beneficios, limitaciones y retos en el entorno empresarial actual.MATERIALES Y MÉTODOS El marco metodológico se estructuró bajo el enfoque de revisión sistemática de literatura (RSL), siguiendo las recomendaciones de PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"8yPOiJRh","properties":{"formattedCitation":"(Ahn & Kang, 2018)","plainCitation":"(Ahn & Kang, 2018)","noteIndex":0},"citationItems":[{"id":7821,"uris":["http://zotero.org/users/8164076/items/6MTVU8M3"],"itemData":{"id":7821,"type":"article-journal","container-title":"Korean Journal of Anesthesiology","DOI":"10.4097/kjae.2018.71.2.103","ISSN":"2005-6419, 2005-7563","issue":"2","journalAbbreviation":"Korean J Anesthesiol","language":"English","note":"publisher: Korean Society of Anesthesiologists","page":"103-112","source":"ekja.org","title":"Introduction to systematic review and meta-analysis","volume":"71","author":[{"family":"Ahn","given":"EunJin"},{"family":"Kang","given":"Hyun"}],"issued":{"date-parts":[["2018",4,2]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Ahn & Kang, 2018), identificando las tecnologías de la información (TI) más relevantes aplicadas en la gestión de la cadena de suministro (GCS). La revisión se realizó en la base de datos ScienceDirect, seleccionada por su alta cobertura de artículos científicos indexados y revisados por pares en ingeniería, administración y ciencias aplicadas. Se utilizaron las siguientes combinaciones de palabras clave, “automation” AND “supply chain”, “blockchain” AND “supply chain” AND “business sector”, “IoT” AND “supply chain”, “artificial intelligence” AND “supply chain” AND “business sector”, Se aplicó como filtro el rango temporal hasta el año 2025, considerando únicamente artículos en inglés y español, en los criterios de inclusión se trabajó con artículos científicos publicados en revistas indexadas, estudios empíricos o revisiones que abordaran aplicaciones prácticas de TI (IA, ML, IoT, BC, RPA) en la GCS empresarial y Publicaciones con acceso a texto completo, respecto a la exclusión en la búsqueda fueron artículos duplicados, trabajos que se limitaran a marcos teóricos sin aplicación en GCS, publicaciones en congresos sin revisión por pares o de carácter meramente descriptivo, tras eliminar duplicados y estudios irrelevantes, el número final de artículos analizados fue de 53, continuación se presenta el diagrama de flujo PRISMA.Figura SEQ Figura_ \* ARABIC 1Diagrama de flujo PRISMALa figura1 muestra el proceso sistemático seguido para la identificación, filtro, elegibilidad e inclusión de los artículos considerados en el proceso de revisión. En la fase de identificación se encontraron 179 registros en la base de datos ScienceDirect. Seguidamente, se eliminaron 32 duplicados, quedando 147 estudios para el filtro. De ellos, 94 fueron excluidos por no cumplir los criterios de inclusión. Entre los excluidos se especifican dos causas frecuentes: falta de acceso a texto completo (n=15) y publicaciones no académicas (n=12), en la fase de elegibilidad, se evaluaron 53 artículos con texto completo y que cumplían los criterios definidos, constituyendo el número final de estudios incluidos (n=53) en el análisis.RESULTADOSLa creciente competencia empresarial, sumada a la recesión económica global producto de la pandemia, ha establecido nuevas reglas en el mercado donde la adaptabilidad a entornos dinámicos se convierte en un factor esencial para sostener la competitividad. En ese sentido, las Tecnologías de la Información (TI) a través de la Industria 4.0 (IR4.0), permite la automatización de la gestión de la cadena de suministro (GCS) en el ámbito empresarial, en ese sentido se presenta una tabla describiendo la tecnología, el ámbito de aplicación y beneficios.Tabla SEQ Tabla \* ARABIC 1Tecnologías de la Información aplicadas en la Gestión de la Cadena de Suministro (GCS).TecnologíaÁmbito de aplicaciónBeneficios principalesReferenciasIA / MLLogística, inventarios, transporte, finanzas, marketingAutomatización en tiempo real; predicción de demanda; rutas óptimas; análisis de grandes volúmenes de datos; fidelización de clientes ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"JeCZFDZ7","properties":{"formattedCitation":"(Balan et\\uc0\\u160{}al., 2025; Guida et\\uc0\\u160{}al., 2025; S. K. Roy et\\uc0\\u160{}al., 2025)","plainCitation":"(Balan et al., 2025; Guida et al., 2025; S. K. Roy et al., 2025)","noteIndex":0},"citationItems":[{"id":7809,"uris":["http://zotero.org/users/8164076/items/9HI64GDP"],"itemData":{"id":7809,"type":"article-journal","abstract":"Resilient and adaptive strategies for recovery have been underscored by supply chain disruptions induced by natural disasters, pandemics, and wars. Supply chain resilience protects enterprises, communities, and humanitarian activities during pandemics and wars. This study investigates the utilization of artificial intelligence and machine learning methodologies to enhance supply chain resilience and recovery in the aftermath of these crises. Leveraging data-driven methodologies, these technologies provide opportunities to improve the overall resilience of the supply chain, optimize resource allocation, and enhance decision-making. Proposed newer measures to protect economies, national security, lives, and a more resilient future are discussed in this study. Machine learning and artificial intelligence can process vast amounts of data quickly to provide real-time insights into the state of the supply chain, including damage assessments, demand fluctuations, and disruptions to transportation routes. Machine learning and artificial intelligence in supply chain management have reduced demand forecasting errors by 10–20 % and enhanced disruption reaction times by 20–30 %. The delivery reliability was also enhanced by 10–20 % as the artificial intelligence can forecast the delays and recommend alternate routes. Machine learning and artificial intelligence provide insights, automation, and agility to rebuild and enhance supply chains after challenging circumstances. This work is unique in showing how to improve supply chain resilience at critical moments by combining technologies and adopting hybrid methodologies.","container-title":"Supply Chain Analytics","DOI":"10.1016/j.sca.2025.100121","ISSN":"2949-8635","journalAbbreviation":"Supply Chain Analytics","page":"100121","source":"ScienceDirect","title":"Machine learning and artificial intelligence methods and applications for post-crisis supply chain resiliency and recovery","volume":"10","author":[{"family":"Balan","given":"G. Sakthi"},{"family":"Kumar","given":"V. Santhosh"},{"family":"Raj","given":"S. Aravind"}],"issued":{"date-parts":[["2025",6,1]]}}},{"id":7789,"uris":["http://zotero.org/users/8164076/items/CKTGGEFA"],"itemData":{"id":7789,"type":"article-journal","abstract":"This paper investigates the impact of artificial intelligence (AI) on spend classification in buyer firms, using the organizational information processing theory (OIPT) as a reference framework. Existing research on the use of AI in procurement lacks a holistic approach that effectively integrates human oversight. This gap is particularly evident in procurement activities beyond automating repetitive tasks, especially in advanced analyses supporting strategic purchasing decisions, such as spend classification. Through a case study approach focusing on providers of AI-based spend classification solutions, this research highlights how AI addresses the substantial information processing needs that exceed the internal capabilities of buyer firms. By aligning these needs with the capabilities enabled by the adoption of AI, the study demonstrates a significant advancement in spend classification practices. This research applies the theoretical constructs of the OIPT at the intersection of two relatively unexplored domains—spend classification and AI and aims to translate these constructs into actionable insights for professionals, thereby making a significant contribution to the field.","container-title":"Journal of Purchasing and Supply Management","DOI":"10.1016/j.pursup.2025.100993","ISSN":"14784092","issue":"3","journalAbbreviation":"Journal of Purchasing and Supply Management","language":"en","page":"100993","source":"DOI.org (Crossref)","title":"AI meets spend classification: A new frontier in information processing","title-short":"AI meets spend classification","volume":"31","author":[{"family":"Guida","given":"Michela"},{"family":"Caniato","given":"Federico"},{"family":"Moretto","given":"Antonella"}],"issued":{"date-parts":[["2025",6]]}}},{"id":7765,"uris":["http://zotero.org/users/8164076/items/Z3YCBHCD"],"itemData":{"id":7765,"type":"article-journal","abstract":"This study explores the interlinkages between artificial intelligence (AI), dynamic capabilities, and relationship marketing (RM) outcomes. Drawing upon insights from dynamic capabilities and RM theory, this study delineates the strategies and initiatives organizations can adopt using machine learning (ML) and AI to enhance their adaptability to changing market dynamics and customer preferences, in order to develop and maintain stronger relationships with their customers. Based on qualitative data from 67 interviews with managers in different organizations in India, this study contributes to existing theoretical knowledge and managerial practices, as it proposes a comprehensive research framework that demonstrates how AI technologies can enhance customer relationships throughout the entire customer journey. More specifically, it adopts a dynamic capabilities lens to extend our understanding of the marketing applications of AI by conceptualizing the dual role of AI as (a) a distinct organizational capability and (b) an enabler of dynamic capabilities, improving firms’ position to sense, seize, and transform organizational resources and fortify customer relationships. Our findings also highlight several facilitators and barriers to the adoption of AI, both as a dynamic capability and as an enabler for RM.","container-title":"Journal of Business Research","DOI":"10.1016/j.jbusres.2025.115309","ISSN":"01482963","journalAbbreviation":"Journal of Business Research","language":"en","page":"115309","source":"DOI.org (Crossref)","title":"AI-capable relationship marketing: Shaping the future of customer relationships","title-short":"AI-capable relationship marketing","volume":"192","author":[{"family":"Roy","given":"Sanjit K."},{"family":"Tehrani","given":"Ali N."},{"family":"Pandit","given":"Ameet"},{"family":"Apostolidis","given":"Chrysostomos"},{"family":"Ray","given":"Subhasis"}],"issued":{"date-parts":[["2025",4]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Balan et al., 2025; Guida et al., 2025; S. K. Roy et al., 2025)IoTInventarios, monitoreo de la demandaGestión inteligente de inventarios; reducción de retrasos; monitoreo en tiempo real ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"WXien8ew","properties":{"formattedCitation":"(Jin & Karki, 2025)","plainCitation":"(Jin & Karki, 2025)","noteIndex":0},"citationItems":[{"id":7784,"uris":["http://zotero.org/users/8164076/items/HPDUPE7K"],"itemData":{"id":7784,"type":"article-journal","abstract":"This research aims to develop and optimize an intelligent supply chain framework tailored for the insurance industry by integrating an innovative inventory management policy supported by the Internet of Things (IoT) and blockchain technologies. Through an extensive literature review, key assumptions are established, needs are identified, and objectives are formulated. A multi-objective mathematical planning model is proposed to minimize cost and time within the supply chain, with optimization conducted under deterministic and fuzzy conditions. The model utilizes augmented epsilon constraint and weighted sum methods to address its multi-objectiveness. Noteworthy is the integration of advanced technologies such as Wireless Sensor Networks (WSN), Radio-Frequency Identification (RFID), blockchain, and online sales, distinguishing it from traditional approaches. Initial validation and testing in smaller dimensions demonstrate the model’s adaptability to precise methods, while larger dimensions necessitate the use of meta-heuristic algorithms for efficient problem resolution. Additionally, a comprehensive sensitivity analysis in the insurance industry on objective function coefficients reveals intricate relationships, offering valuable insights into optimization dynamics across diverse conditions.","container-title":"Journal of Engineering Research","DOI":"10.1016/j.jer.2024.04.021","ISSN":"2307-1877","issue":"2","journalAbbreviation":"Journal of Engineering Research","page":"527-537","source":"ScienceDirect","title":"Integrating IoT and blockchain for intelligent inventory management in supply chains: A multi-objective optimization approach for the insurance industry","title-short":"Integrating IoT and blockchain for intelligent inventory management in supply chains","volume":"13","author":[{"family":"Jin","given":"Shan"},{"family":"Karki","given":"Bhishma"}],"issued":{"date-parts":[["2025",6,1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Jin & Karki, 2025) Blockchain (BC)Comercio electrónico, trazabilidadRegistro descentralizado, inmutable y transparente; confianza en transacciones; trazabilidad de productos ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"rKuVozQn","properties":{"formattedCitation":"(Zhu, 2025)","plainCitation":"(Zhu, 2025)","noteIndex":0},"citationItems":[{"id":7746,"uris":["http://zotero.org/users/8164076/items/CLS6839D"],"itemData":{"id":7746,"type":"article-journal","abstract":"Nowadays, logistics supply chain management is facing increasingly complex challenges, and the efficient and secure processing and transmission of large amounts of data has become a key demand in the industry. The study employed machine learning, deep learning, and other methods to analyze and predict consumer behavior, inventory levels, and transportation methods, thereby achieving optimal control over inventory and logistics. Blockchain technology establishes decentralized databases to ensure high transparency and immutability of transaction records in the supply chain, thus enhancing mutual trust and collaboration efficiency among all parties. The duration of the DDoS (Distributed Denial of Service) attack in the study reached 10 minutes, with a defense success rate of 100%, and did not cause any leakage of e-commerce big data information. This project proposes advanced data analysis and anti-counterfeiting technology aimed at improving the response speed and security performance of e-commerce, thereby promoting the development of the e-commerce industry towards a more intelligent and automated direction.","collection-title":"Sixth International Conference on Futuristic Trends in Networks and Computing Technologies (FTNCT06), held in Uttarakhand, India","container-title":"Procedia Computer Science","DOI":"10.1016/j.procs.2025.04.045","ISSN":"1877-0509","journalAbbreviation":"Procedia Computer Science","page":"923-930","source":"ScienceDirect","title":"E-Commerce Big Data Logistics Supply Chain Control System Based on Artificial Intelligence and Blockchain","volume":"259","author":[{"family":"Zhu","given":"Hao"}],"issued":{"date-parts":[["2025",1,1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Zhu, 2025)IoT + BC (sinergia)Logística e inventariosMinimización de retrasos; monitoreo de demanda; visibilidad completa ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"beyHtcDw","properties":{"formattedCitation":"(Jin & Karki, 2025)","plainCitation":"(Jin & Karki, 2025)","noteIndex":0},"citationItems":[{"id":7784,"uris":["http://zotero.org/users/8164076/items/HPDUPE7K"],"itemData":{"id":7784,"type":"article-journal","abstract":"This research aims to develop and optimize an intelligent supply chain framework tailored for the insurance industry by integrating an innovative inventory management policy supported by the Internet of Things (IoT) and blockchain technologies. Through an extensive literature review, key assumptions are established, needs are identified, and objectives are formulated. A multi-objective mathematical planning model is proposed to minimize cost and time within the supply chain, with optimization conducted under deterministic and fuzzy conditions. The model utilizes augmented epsilon constraint and weighted sum methods to address its multi-objectiveness. Noteworthy is the integration of advanced technologies such as Wireless Sensor Networks (WSN), Radio-Frequency Identification (RFID), blockchain, and online sales, distinguishing it from traditional approaches. Initial validation and testing in smaller dimensions demonstrate the model’s adaptability to precise methods, while larger dimensions necessitate the use of meta-heuristic algorithms for efficient problem resolution. Additionally, a comprehensive sensitivity analysis in the insurance industry on objective function coefficients reveals intricate relationships, offering valuable insights into optimization dynamics across diverse conditions.","container-title":"Journal of Engineering Research","DOI":"10.1016/j.jer.2024.04.021","ISSN":"2307-1877","issue":"2","journalAbbreviation":"Journal of Engineering Research","page":"527-537","source":"ScienceDirect","title":"Integrating IoT and blockchain for intelligent inventory management in supply chains: A multi-objective optimization approach for the insurance industry","title-short":"Integrating IoT and blockchain for intelligent inventory management in supply chains","volume":"13","author":[{"family":"Jin","given":"Shan"},{"family":"Karki","given":"Bhishma"}],"issued":{"date-parts":[["2025",6,1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Jin & Karki, 2025) ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"uQqlWPUG","properties":{"formattedCitation":"(Zhu, 2025)","plainCitation":"(Zhu, 2025)","noteIndex":0},"citationItems":[{"id":7746,"uris":["http://zotero.org/users/8164076/items/CLS6839D"],"itemData":{"id":7746,"type":"article-journal","abstract":"Nowadays, logistics supply chain management is facing increasingly complex challenges, and the efficient and secure processing and transmission of large amounts of data has become a key demand in the industry. The study employed machine learning, deep learning, and other methods to analyze and predict consumer behavior, inventory levels, and transportation methods, thereby achieving optimal control over inventory and logistics. Blockchain technology establishes decentralized databases to ensure high transparency and immutability of transaction records in the supply chain, thus enhancing mutual trust and collaboration efficiency among all parties. The duration of the DDoS (Distributed Denial of Service) attack in the study reached 10 minutes, with a defense success rate of 100%, and did not cause any leakage of e-commerce big data information. This project proposes advanced data analysis and anti-counterfeiting technology aimed at improving the response speed and security performance of e-commerce, thereby promoting the development of the e-commerce industry towards a more intelligent and automated direction.","collection-title":"Sixth International Conference on Futuristic Trends in Networks and Computing Technologies (FTNCT06), held in Uttarakhand, India","container-title":"Procedia Computer Science","DOI":"10.1016/j.procs.2025.04.045","ISSN":"1877-0509","journalAbbreviation":"Procedia Computer Science","page":"923-930","source":"ScienceDirect","title":"E-Commerce Big Data Logistics Supply Chain Control System Based on Artificial Intelligence and Blockchain","volume":"259","author":[{"family":"Zhu","given":"Hao"}],"issued":{"date-parts":[["2025",1,1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Zhu, 2025)RPAProcesos administrativos y logísticosDigitalización de procesos; reducción de errores; mayor eficiencia en pedidos ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"3doIJVuX","properties":{"formattedCitation":"(Shamsuzzoha & Pelkonen, 2025)","plainCitation":"(Shamsuzzoha & Pelkonen, 2025)","noteIndex":0},"citationItems":[{"id":7757,"uris":["http://zotero.org/users/8164076/items/HPZM4AET"],"itemData":{"id":7757,"type":"article-journal","abstract":"This study proposes a robotic process automation (RPA) model to streamline and optimize order-handling procedures in supply chain management. The current manual approach to order handling poses challenges, including limited accessibility and significant cognitive demands on employees. An information systems design methodology is applied to analyze and improve the process, with data gathered through semi-structured interviews to address these issues. The findings highlight that reducing manual labor alleviates workload imbalances and saves time in supply chain automation. Moreover, automating repetitive tasks through well-designed software bots minimizes the risk of human error. While this research focuses on applying RPA in order handling, future studies should explore the potential of artificial intelligence-driven RPA to enhance process automation further.","container-title":"Supply Chain Analytics","DOI":"10.1016/j.sca.2025.100102","ISSN":"2949-8635","journalAbbreviation":"Supply Chain Analytics","page":"100102","source":"ScienceDirect","title":"A robotic process automation model for order-handling optimization in supply chain management","volume":"9","author":[{"family":"Shamsuzzoha","given":"Ahm"},{"family":"Pelkonen","given":"Sini"}],"issued":{"date-parts":[["2025",3,1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Shamsuzzoha & Pelkonen, 2025)La Tabla 1 muestra el resumen de las principales TI aplicadas en la gestión de la cadena de suministro, la IA/ML destaca por su capacidad de predicción de la demanda, optimización logística y fidelización de clientes. El IoT facilita el monitoreo en tiempo real y la gestión inteligente de inventarios, mientras que el blockchain (BC) asegura transparencia, trazabilidad y confianza en transacciones, la combinación IoT + BC potencia la visibilidad de los procesos logísticos y el control de inventarios, en conjunto, estas tecnologías fortalecen la eficiencia, la resiliencia y la competitividad empresarial.6096000544830850085Figura SEQ Figura_ \* ARABIC 2Sinergia de Tecnologías de la Información en la GCS.La Figura 2 muestra la gestión de la cadena de suministro (GCS) donde se apoya en tecnologías disruptivas de la Industria 4.0. La IA/ML facilita la predicción de la demanda y la optimización logística, mientras el IoT aporta el control y monitoreo en tiempo real y trazabilidad. El Blockchain refuerza la transparencia y la confianza mediante registros inmutables, y la RPA automatiza procesos permitiendo la reducción de tiempo, en conjunto, estas tecnologías fortalecen la eficiencia, resiliencia y competitividad empresarial.DISCUSIÓNLos antecedentes recientes muestran un cambio constante en el sector empresarial hacia la digitalización y la automatización de procesos en la cadena de suministro (CS), en donde las capacidades tecnológicas se encuentran en constante mejoramiento. Desde este contexto, la implementación de tecnologías aisladas ya no es suficiente; diversos autores destacan que la integración y centralización de la información con ayuda de herramientas tecnológicas como la inteligencia artificial (IA), blockchain (BC), internet de las cosas (IoT) y big data (BD) permite maximizar los resultados y fortalecer la resiliencia empresarial ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"ySfQ2qHF","properties":{"formattedCitation":"(Jin & Karki, 2025; Zhu, 2025)","plainCitation":"(Jin & Karki, 2025; Zhu, 2025)","noteIndex":0},"citationItems":[{"id":7784,"uris":["http://zotero.org/users/8164076/items/HPDUPE7K"],"itemData":{"id":7784,"type":"article-journal","abstract":"This research aims to develop and optimize an intelligent supply chain framework tailored for the insurance industry by integrating an innovative inventory management policy supported by the Internet of Things (IoT) and blockchain technologies. Through an extensive literature review, key assumptions are established, needs are identified, and objectives are formulated. A multi-objective mathematical planning model is proposed to minimize cost and time within the supply chain, with optimization conducted under deterministic and fuzzy conditions. The model utilizes augmented epsilon constraint and weighted sum methods to address its multi-objectiveness. Noteworthy is the integration of advanced technologies such as Wireless Sensor Networks (WSN), Radio-Frequency Identification (RFID), blockchain, and online sales, distinguishing it from traditional approaches. Initial validation and testing in smaller dimensions demonstrate the model’s adaptability to precise methods, while larger dimensions necessitate the use of meta-heuristic algorithms for efficient problem resolution. Additionally, a comprehensive sensitivity analysis in the insurance industry on objective function coefficients reveals intricate relationships, offering valuable insights into optimization dynamics across diverse conditions.","container-title":"Journal of Engineering Research","DOI":"10.1016/j.jer.2024.04.021","ISSN":"2307-1877","issue":"2","journalAbbreviation":"Journal of Engineering Research","page":"527-537","source":"ScienceDirect","title":"Integrating IoT and blockchain for intelligent inventory management in supply chains: A multi-objective optimization approach for the insurance industry","title-short":"Integrating IoT and blockchain for intelligent inventory management in supply chains","volume":"13","author":[{"family":"Jin","given":"Shan"},{"family":"Karki","given":"Bhishma"}],"issued":{"date-parts":[["2025",6,1]]}}},{"id":7746,"uris":["http://zotero.org/users/8164076/items/CLS6839D"],"itemData":{"id":7746,"type":"article-journal","abstract":"Nowadays, logistics supply chain management is facing increasingly complex challenges, and the efficient and secure processing and transmission of large amounts of data has become a key demand in the industry. The study employed machine learning, deep learning, and other methods to analyze and predict consumer behavior, inventory levels, and transportation methods, thereby achieving optimal control over inventory and logistics. Blockchain technology establishes decentralized databases to ensure high transparency and immutability of transaction records in the supply chain, thus enhancing mutual trust and collaboration efficiency among all parties. The duration of the DDoS (Distributed Denial of Service) attack in the study reached 10 minutes, with a defense success rate of 100%, and did not cause any leakage of e-commerce big data information. This project proposes advanced data analysis and anti-counterfeiting technology aimed at improving the response speed and security performance of e-commerce, thereby promoting the development of the e-commerce industry towards a more intelligent and automated direction.","collection-title":"Sixth International Conference on Futuristic Trends in Networks and Computing Technologies (FTNCT06), held in Uttarakhand, India","container-title":"Procedia Computer Science","DOI":"10.1016/j.procs.2025.04.045","ISSN":"1877-0509","journalAbbreviation":"Procedia Computer Science","page":"923-930","source":"ScienceDirect","title":"E-Commerce Big Data Logistics Supply Chain Control System Based on Artificial Intelligence and Blockchain","volume":"259","author":[{"family":"Zhu","given":"Hao"}],"issued":{"date-parts":[["2025",1,1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Jin & Karki, 2025; Zhu, 2025). 6111240941070860086Un aspecto relevante de discusión gira en torno al paradigma cultural sobre remplazar el trabajo de las personas por la IA, en ese sentido la evidencia científica demuestra que la IA no está diseñada para reemplazar al trabajador, sino para mejorar sus capacidades, es así que la IA se centra en el procesamiento de datos, la gestión de información y la automatización de procesos operativos, mientras que el ser humano conserva un rol crítico y el análisis estratégico, la supervisión y la interpretación de los datos e información ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"6AALroAx","properties":{"formattedCitation":"(Balan et\\uc0\\u160{}al., 2025; Guida et\\uc0\\u160{}al., 2025; Shamsuzzoha & Pelkonen, 2025)","plainCitation":"(Balan et al., 2025; Guida et al., 2025; Shamsuzzoha & Pelkonen, 2025)","noteIndex":0},"citationItems":[{"id":7809,"uris":["http://zotero.org/users/8164076/items/9HI64GDP"],"itemData":{"id":7809,"type":"article-journal","abstract":"Resilient and adaptive strategies for recovery have been underscored by supply chain disruptions induced by natural disasters, pandemics, and wars. Supply chain resilience protects enterprises, communities, and humanitarian activities during pandemics and wars. This study investigates the utilization of artificial intelligence and machine learning methodologies to enhance supply chain resilience and recovery in the aftermath of these crises. Leveraging data-driven methodologies, these technologies provide opportunities to improve the overall resilience of the supply chain, optimize resource allocation, and enhance decision-making. Proposed newer measures to protect economies, national security, lives, and a more resilient future are discussed in this study. Machine learning and artificial intelligence can process vast amounts of data quickly to provide real-time insights into the state of the supply chain, including damage assessments, demand fluctuations, and disruptions to transportation routes. Machine learning and artificial intelligence in supply chain management have reduced demand forecasting errors by 10–20 % and enhanced disruption reaction times by 20–30 %. The delivery reliability was also enhanced by 10–20 % as the artificial intelligence can forecast the delays and recommend alternate routes. Machine learning and artificial intelligence provide insights, automation, and agility to rebuild and enhance supply chains after challenging circumstances. This work is unique in showing how to improve supply chain resilience at critical moments by combining technologies and adopting hybrid methodologies.","container-title":"Supply Chain Analytics","DOI":"10.1016/j.sca.2025.100121","ISSN":"2949-8635","journalAbbreviation":"Supply Chain Analytics","page":"100121","source":"ScienceDirect","title":"Machine learning and artificial intelligence methods and applications for post-crisis supply chain resiliency and recovery","volume":"10","author":[{"family":"Balan","given":"G. Sakthi"},{"family":"Kumar","given":"V. Santhosh"},{"family":"Raj","given":"S. Aravind"}],"issued":{"date-parts":[["2025",6,1]]}}},{"id":7789,"uris":["http://zotero.org/users/8164076/items/CKTGGEFA"],"itemData":{"id":7789,"type":"article-journal","abstract":"This paper investigates the impact of artificial intelligence (AI) on spend classification in buyer firms, using the organizational information processing theory (OIPT) as a reference framework. Existing research on the use of AI in procurement lacks a holistic approach that effectively integrates human oversight. This gap is particularly evident in procurement activities beyond automating repetitive tasks, especially in advanced analyses supporting strategic purchasing decisions, such as spend classification. Through a case study approach focusing on providers of AI-based spend classification solutions, this research highlights how AI addresses the substantial information processing needs that exceed the internal capabilities of buyer firms. By aligning these needs with the capabilities enabled by the adoption of AI, the study demonstrates a significant advancement in spend classification practices. This research applies the theoretical constructs of the OIPT at the intersection of two relatively unexplored domains—spend classification and AI and aims to translate these constructs into actionable insights for professionals, thereby making a significant contribution to the field.","container-title":"Journal of Purchasing and Supply Management","DOI":"10.1016/j.pursup.2025.100993","ISSN":"14784092","issue":"3","journalAbbreviation":"Journal of Purchasing and Supply Management","language":"en","page":"100993","source":"DOI.org (Crossref)","title":"AI meets spend classification: A new frontier in information processing","title-short":"AI meets spend classification","volume":"31","author":[{"family":"Guida","given":"Michela"},{"family":"Caniato","given":"Federico"},{"family":"Moretto","given":"Antonella"}],"issued":{"date-parts":[["2025",6]]}}},{"id":7757,"uris":["http://zotero.org/users/8164076/items/HPZM4AET"],"itemData":{"id":7757,"type":"article-journal","abstract":"This study proposes a robotic process automation (RPA) model to streamline and optimize order-handling procedures in supply chain management. The current manual approach to order handling poses challenges, including limited accessibility and significant cognitive demands on employees. An information systems design methodology is applied to analyze and improve the process, with data gathered through semi-structured interviews to address these issues. The findings highlight that reducing manual labor alleviates workload imbalances and saves time in supply chain automation. Moreover, automating repetitive tasks through well-designed software bots minimizes the risk of human error. While this research focuses on applying RPA in order handling, future studies should explore the potential of artificial intelligence-driven RPA to enhance process automation further.","container-title":"Supply Chain Analytics","DOI":"10.1016/j.sca.2025.100102","ISSN":"2949-8635","journalAbbreviation":"Supply Chain Analytics","page":"100102","source":"ScienceDirect","title":"A robotic process automation model for order-handling optimization in supply chain management","volume":"9","author":[{"family":"Shamsuzzoha","given":"Ahm"},{"family":"Pelkonen","given":"Sini"}],"issued":{"date-parts":[["2025",3,1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Balan et al., 2025; Guida et al., 2025; Shamsuzzoha & Pelkonen, 2025).Pero de acuerdo a los avances significativos en la implementación de estas tecnologías aún se identifican vacíos de investigación y diferencias contextuales en su implementación. En países con economías y tecnologías sobresalientes, el proceso de automatización de la CS se ha consolidado gracias a una infraestructura tecnológica robusta, inversiones planificadas y sostenibles en la innovación y capital humano altamente capacitado. En contraste con economías en desarrollo, especialmente en las pequeñas y medianas empresas (PYMES), las TI enfrentan barreras contextuales y estructurales, destacando la poca infraestructura tecnológica, escasez de competencias digitales y la resistencia cultural al cambio organizacional, factores que dificultan la adopción plena de estas tecnologías ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"7NzehQUH","properties":{"formattedCitation":"(Alnoor et\\uc0\\u160{}al., 2025; Awasthy et\\uc0\\u160{}al., 2025; Elhusseiny & Crispim, 2022; Mao, 2025; W. Roy et\\uc0\\u160{}al., 2023; Rumson & Hallett, 2019)","plainCitation":"(Alnoor et al., 2025; Awasthy et al., 2025; Elhusseiny & Crispim, 2022; Mao, 2025; W. Roy et al., 2023; Rumson & Hallett, 2019)","noteIndex":0},"citationItems":[{"id":7828,"uris":["http://zotero.org/users/8164076/items/HG5BYYJ3"],"itemData":{"id":7828,"type":"article-journal","abstract":"Blockchain technology is rapidly replacing traditional technologies. This technology offers numerous benefits, including transparency, safety and security, authenticity, and traceability, which drive business organizations to adopt it. Thus, the factors that generate resistance to the adoption of blockchain technology must be recognized, and an organization's strategy toward adopting blockchain technology must be influenced. In this study, the vital factors that produce resistance to blockchain technology from the perspective of oil companies operating in Iraq were determined. The three-pronged framework of technology, organization, and environment (TOE) was employed to identify the elements that affect resistance to blockchain technology, with subsequent effects on the blockchain strategy. Data were collected using a questionnaire distributed among the managers of the target companies. Among the 381 distributed questionnaires, 313 usable responses were gathered and analyzed via partial least square–structural equation modeling and artificial neural networks to test the proposed hypotheses. The findings show that all the elements of the TOE framework are crucially associated with resistance to blockchain technology and consequently shape the blockchain strategy. Furthermore, resistance to blockchain technology mediates the link between predictors of TOE factors and the blockchain strategy. Therefore, in this work, the present knowledge on resistance to blockchain technology and the blockchain strategy is enhanced by explicating the factors inhibiting blockchain technology adoption in a previously overlooked context. The findings provide practical insight for managers of oil companies to devise effective blockchain strategies for the optimal adoption of blockchain technology.","container-title":"Technological Forecasting and Social Change","DOI":"10.1016/j.techfore.2025.124044","ISSN":"00401625","journalAbbreviation":"Technological Forecasting and Social Change","language":"en","page":"124044","source":"DOI.org (Crossref)","title":"Navigating the power of blockchain strategy: Analysis of technology-organization-environment (TOE) framework and innovation resistance theory using PLS-SEM and ANN insights","title-short":"Navigating the power of blockchain strategy","volume":"214","author":[{"family":"Alnoor","given":"Alhamzah"},{"family":"Abbas","given":"Sammar"},{"family":"Sadaa","given":"Abdullah Mohammed"},{"family":"Chew","given":"XinYing"},{"family":"Bayram","given":"Gül Erkol"}],"issued":{"date-parts":[["2025",5]]}}},{"id":7812,"uris":["http://zotero.org/users/8164076/items/62ADW6TL"],"itemData":{"id":7812,"type":"article-journal","abstract":"Despite numerous use cases, enterprise-wide implementations of blockchains have seen limited success. This raises the question of when do firms adopt blockchains and do blockchains benefit supply chains. To answer this, we examine a dyadic supply chain consisting of a buyer and a supplier and analyze their traceability effort and pricing decisions. Our results show that the demand-side, supply-side and reputational factors influencing blockchain adoption are primarily complementary and in the absence of one of them, firms can still adopt blockchain. Furthermore, even in the absence of individual benefits for a supply chain partner, there exist conditions under which blockchain adoption benefits the supply chain that can incentivize players to join blockchain. Overall, we contribute by offering a framework that supply chain players can use to assess the likelihood of blockchain implementation success or failure and address the challenges pertaining to incentives and cost imbalances in blockchain implementation.","container-title":"European Journal of Operational Research","DOI":"10.1016/j.ejor.2024.10.019","ISSN":"0377-2217","issue":"3","journalAbbreviation":"European Journal of Operational Research","page":"760-774","source":"ScienceDirect","title":"Blockchain enabled traceability — An analysis of pricing and traceability effort decisions in supply chains","volume":"321","author":[{"family":"Awasthy","given":"Prakash"},{"family":"Haldar","given":"Tanushree"},{"family":"Ghosh","given":"Debabrata"}],"issued":{"date-parts":[["2025",3,16]]}}},{"id":7795,"uris":["http://zotero.org/users/8164076/items/5E974MSW"],"itemData":{"id":7795,"type":"article-journal","abstract":"Industry 4.0 (I4.0) enables SMEs to enhance their manufacturing capabilities and compete globally through the deployment of cutting-edge technologies. This review identifies the barriers and opportunities of adopting industry 4.0 in the manufacturing sector in developed vs. developing countries. In total, 54 studies met the screening criteria. The synthesized factors were classified into dimensions to helps the understanding of what type of difficulties SMEs face in the transition to the 4.0 generation. This study found that developing countries face more barriers but also perceive more opportunities in relation to industry 4.0. Organizational barriers and technical Barriers have been the main types of barriers studied in both sets of countries. In terms of benefits, studies have emphasized 1) gains in terms of operations management, and 2) questions related to market, sustainability and supply chain management.","collection-title":"International Conference on ENTERprise Information Systems / ProjMAN - International Conference on Project MANagement / HCist - International Conference on Health and Social Care Information Systems and Technologies 2021","container-title":"Procedia Computer Science","DOI":"10.1016/j.procs.2021.12.086","ISSN":"1877-0509","journalAbbreviation":"Procedia Computer Science","page":"864-871","source":"ScienceDirect","title":"SMEs, Barriers and Opportunities on adopting Industry 4.0: A Review.","title-short":"SMEs, Barriers and Opportunities on adopting Industry 4.0","volume":"196","author":[{"family":"Elhusseiny","given":"Hussein Magdy"},{"family":"Crispim","given":"José"}],"issued":{"date-parts":[["2022",1,1]]}}},{"id":7777,"uris":["http://zotero.org/users/8164076/items/Y25LBR4N"],"itemData":{"id":7777,"type":"article-journal","abstract":"Suppliers, producers, distributors, and retailers are among the many stakeholders in the supply side chain. The data silos between the parties are serious, resulting in poor information flow, which affects the accuracy and practicality of the optimization model. To this end, this paper studies the application strategies and practices of artificial intelligence technology and genetic algorithms in business management supply chain optimization. First, the advantages of artificial intelligence-driven solutions in supply chain management are explored, especially in demand forecasting, inventory management, and warehouse process automation. These technologies provide real-time decision support by processing massive data, reducing inventory waste and improving logistics efficiency. Secondly, a supply chain optimization model based on genetic algorithm is constructed, and the objective function and constraints are clarified, covering key optimization goals such as cost minimization, profit maximization and service level improvement. The model continuously iterates and optimizes the supply chain configuration through the core operation steps of genetic algorithm, including population initialization, fitness evaluation, selection, crossover and mutation. The experimental results show that artificial intelligence technology and genetic algorithm can significantly reduce supply chain costs, improve logistics efficiency and enhance service levels, verifying the effectiveness of the model in practical applications.","collection-title":"The 5th International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT2024)","container-title":"Procedia Computer Science","DOI":"10.1016/j.procs.2025.04.324","ISSN":"1877-0509","journalAbbreviation":"Procedia Computer Science","page":"707-715","source":"ScienceDirect","title":"The Optimization Strategy and Application Practice of Business Management Supply Chain Based on Artificial Intelligence Technology","volume":"261","author":[{"family":"Mao","given":"Hui"}],"issued":{"date-parts":[["2025",1,1]]}}},{"id":1177,"uris":["http://zotero.org/users/8164076/items/4TSRI3W8"],"itemData":{"id":1177,"type":"article-journal","abstract":"Background and Aim: Sars-CoV-19 pandemic necessitated a transition to telemedicine for many healthcare encounters. The environmental impact of this transition in gastroenterology (GI) combined with user experience has not been studied. Methods: We conducted a retrospective cohort study of patients who underwent telemedicine visits (telephone and video) at a GI clinic at West Virginia University. Distance of patients' residence from clinic × 2 was calculated, and Environmental Protection Agency calculators utilized to calculate greenhouse gas (GHG) emissions that were avoided from tele-visits. Patients were reached by telephone and were asked questions to fill in a validated Telehealth Usability Questionnaire with Likert scales (1–7). Variables were also collected via chart review. Results: A total of 81 video and 89 telephone visits were conducted for gastroesophageal reflux disease (GERD) between March 2020 and March 2021. A total of 111 patients were enrolled, with a response rate of 65.29%. Mean age was lower in the video visit cohort compared with the telephone visit cohort (43.45 ± 14.32 years vs 52.34 ± 17.46 years). Most patients had medications prescribed during the visit (79.3%), and a majority had laboratory testing orders placed (57.7%). We calculated a total distance of 8732 miles that the patients would have traveled if they were to present for in-person visits (including return trips). A total of 393.3 gallons of gasoline would have been required to transport these patients to and from the healthcare facility to their residence. A total of 3.5 metric tons of GHG's were saved by avoiding 393.3 gallons of gasoline for travel. In relatable terms, this is equivalent to burning more than 3500 pounds of coal. This averages to 31.5-kg GHG emissions and 3.54 gallons of gasoline saved per patient. Conclusion: Telemedicine for GERD resulted in significant environmental savings and was rated highly for access, satisfaction, and usability by patients. Telemedicine for GERD can be an excellent alternative to in-person visits. © 2023 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.","archive":"Scopus","container-title":"Journal of Gastroenterology and Hepatology (Australia)","DOI":"10.1111/jgh.16148","ISSN":"08159319 (ISSN)","issue":"6","journalAbbreviation":"J. Gastroenterol. Hepatol.","language":"English","note":"publisher: John Wiley and Sons Inc","page":"905-909","title":"Tele-visits for GERD: “Ecofriendly, efficient and effective”","volume":"38","author":[{"family":"Roy","given":"W."},{"family":"Hans","given":"B."},{"family":"Jannat","given":"R.U."},{"family":"Reddy","given":"Y.K."},{"family":"Hadi","given":"Y."},{"family":"Gayam","given":"S."}],"issued":{"date-parts":[["2023"]]}}},{"id":7760,"uris":["http://zotero.org/users/8164076/items/FY8MUH9H"],"itemData":{"id":7760,"type":"article-journal","abstract":"Insurance plays a crucial role in human efforts to adapt to environmental hazards. Effective insurance can serve as both a measure to distribute, and a method to communicate risk. In order for insurance to fulfil these roles successfully, policy pricing and cover choices must be risk-based and founded on accurate information. This is reliant on a robust evidence base forming the foundation of policy choices. This paper focuses on the evidence available to insurers and emergent innovation in the use of data. The main risk considered is coastal flooding, for which the insurance sector offers an option for potential adaptation, capable of increasing resilience. However, inadequate supply and analysis of data have been highlighted as factors preventing insurance from fulfilling this role. Research was undertaken to evaluate how data are currently, and could potentially, be used within risk evaluations for the insurance industry. This comprised of 50 interviews with those working and associated with the London insurance market. The research reveals new opportunities, which could facilitate improvements in risk-reflective pricing of policies. These relate to a new generation of data collection techniques and analytics, such as those associated with satellite-derived data, IoT (Internet of Things) sensors, cloud computing, and Big Data solutions. Such technologies present opportunities to reduce moral hazard through basing predictions and pricing of risk on large empirical datasets. The value of insurers' claims data is also revealed, and is shown to have the potential to refine, calibrate, and validate models and methods. The adoption of such data-driven techniques could enable insurers to re-evaluate risk ratings, and in some instances, extend coverage to locations and developments, previously rated as too high a risk to insure. Conversely, other areas may be revealed more vulnerable, which could generate negative impacts for residents in these regions, such as increased premiums. However, the enhanced risk awareness generated, by new technology, data and data analytics, could positively alter future planning, development and investment decisions.","container-title":"Science of The Total Environment","DOI":"10.1016/j.scitotenv.2019.01.114","ISSN":"0048-9697","journalAbbreviation":"Science of The Total Environment","page":"598-612","source":"ScienceDirect","title":"Innovations in the use of data facilitating insurance as a resilience mechanism for coastal flood risk","volume":"661","author":[{"family":"Rumson","given":"Alexander G."},{"family":"Hallett","given":"Stephen H."}],"issued":{"date-parts":[["2019",4,15]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Alnoor et al., 2025; Awasthy et al., 2025; Elhusseiny & Crispim, 2022; Mao, 2025; W. Roy et al., 2023; Rumson & Hallett, 2019).A pesar de estas limitaciones, el impacto de las TI en la CS resulta cuantificable, significativo y eficiente. Los estudios muestran beneficios como la reducción en los tiempos de procesamiento de grandes volúmenes de información (MVI), la predicción más precisa de la demanda y de segmentos de mercado específicos, el aumento de la capacidad de adaptación organizacional, así como una mayor satisfacción, desarrollo y fidelización de los clientes (Roy et al., 2025). En este sentido, el éxito de estas tecnologías depende de una gestión estratégica de los datos, una integración tecnológica efectiva y la superación de barreras culturales y estructurales.CONCLUSIONES60807603284220870087El uso de las tecnologías de información (TI) vienen posicionándose como herramientas claves en la gestión de la cadena de suministro, sobresaliendo las IA,IoT,ML,BC y RPA, que si trabajan de forma integrada potencian la eficiencia operacional y la resiliencia empresarial, las investigaciones demuestran que la IA, fortalece las capacidades críticas en el procesamiento de grandes volumen de datos e información obteniendo insumos para las decisiones estratégicas ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"kdX81RKA","properties":{"formattedCitation":"(Benchis et\\uc0\\u160{}al., 2025)","plainCitation":"(Benchis et al., 2025)","noteIndex":0},"citationItems":[{"id":7806,"uris":["http://zotero.org/users/8164076/items/CE85EN5L"],"itemData":{"id":7806,"type":"article-journal","abstract":"Blockchain technology (BT) can potentially enhance transparency, efficiency, and trust across all domains. However, it remains unclear how the relative adoption of BT between the private and public sectors compares in light of existing studies. This article contributes to the literature by evaluating the adoption process through the technology, organizational, and environmental dimensions of the TOE framework. A comparative research design was employed through 21 semi-structured interviews with participants from the public and private sectors in Finland. The results indicate that challenges to adoption uniformly exist between both sectors in the form of regulatory concerns and misconceptions regarding energy matters, as well as incentives that are directly linked to the sector. The private sector is incentivized to adopt BT for scalability, efficiency, and responsiveness to market demand in light of competitive advantage. The public sector is motivated to adopt BT through transparency and regulatory concerns, although a willingness to accommodate legacy systems in the short term exists so that public services and activities are not interrupted. In addition, our findings highlight the important role of public institutions in BT adoption. Ultimately, both sectors require strong visionary leadership and training to overcome knowledge deficiencies and proof-of-concept studies to reduce uncertainty and reliance on external applications and partnerships. This article contributes to the literature by comparatively highlighting the similarities and differences in this phenomenon. It offers practical and policy-related implications and encourages an industry-specific approach to adoption, cross-industry innovations, and regulatory policies.","container-title":"Journal of Innovation & Knowledge","DOI":"10.1016/j.jik.2025.100746","ISSN":"2444-569X","issue":"4","journalAbbreviation":"Journal of Innovation & Knowledge","page":"100746","source":"ScienceDirect","title":"Comparative analysis of blockchain adoption in the public and private sectors. A technology-organization-environment (TOE) framework approach","volume":"10","author":[{"family":"Benchis","given":"Melisa Petra"},{"family":"Shahzad","given":"Khuram"},{"family":"Dan","given":"Sorin"}],"issued":{"date-parts":[["2025",7,1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Benchis et al., 2025). Sin embargo, la implementación de estas tecnologías enfrenta barreras significativas en países en proceso de desarrollo, entre ellas altos costos, la falta de infraestructura y la resistencia cultural ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"InSfEhvh","properties":{"formattedCitation":"(Ghobakhloo et\\uc0\\u160{}al., 2023; Govindarajan et\\uc0\\u160{}al., 2025)","plainCitation":"(Ghobakhloo et al., 2023; Govindarajan et al., 2025)","noteIndex":0},"citationItems":[{"id":7792,"uris":["http://zotero.org/users/8164076/items/5UZPRMHG"],"itemData":{"id":7792,"type":"article-journal","abstract":"Although Intelligent Automation (IA) represents the future of business automation, the organizational implementation and sustainability performance of this emerging technological innovation is vastly understudied. Understanding the implications of IA for sustainability is critical since leveraging these technologies shapes operations and policies that can promote sustainable digitalization and automation practices. We study how firms' technological, organizational, environmental, and human resource contexts impact IA implementation. The study further explains how IA may associate with the firm's triple bottom line while accounting for the moderating role of corporate social responsibility strategy. The study surveyed 207 multinational firms in 2022 and used partial least square-structural equation modeling to test the hypothesized relationships. Results showed that IA implementation is mainly determined by the characteristics of the firm's internal environment, such as absorptive capacity, employee socio-behavioral concerns, and social capital competency. IA may offer valuable opportunities for boosting the firm's economic and environmental sustainability performance. Nonetheless, IA is a double-edged sword for social sustainability, harming social values in implementing firms with informal corporate social sustainability strategies. Conversely, firms with formal corporate social sustainability strategy have a significantly higher opportunity to transform the value of IA into social sustainability performance. Findings are expected to assist managers and decision-makers with streamlining an impartial and sustainable transition of organizations toward automation.","container-title":"Technology in Society","DOI":"10.1016/j.techsoc.2023.102301","ISSN":"0160-791X","journalAbbreviation":"Technology in Society","page":"102301","source":"ScienceDirect","title":"Intelligent automation implementation and corporate sustainability performance: The enabling role of corporate social responsibility strategy","title-short":"Intelligent automation implementation and corporate sustainability performance","volume":"74","author":[{"family":"Ghobakhloo","given":"Morteza"},{"family":"Asadi","given":"Shahla"},{"family":"Iranmanesh","given":"Mohammad"},{"family":"Foroughi","given":"Behzad"},{"family":"Mubarak","given":"Muhammad Faraz"},{"family":"Yadegaridehkordi","given":"Elaheh"}],"issued":{"date-parts":[["2023",8,1]]}}},{"id":7790,"uris":["http://zotero.org/users/8164076/items/XTKGZ4RJ"],"itemData":{"id":7790,"type":"article-journal","abstract":"Blockchain technologies are increasingly recognized as a transformative force across industries, offering potential solutions for information management, data security, and operational efficiency improvement. However, integration into the healthcare sector faces significant barriers, ranging from technical challenges to organizational resistance. In this study, a methodology is proposed that examines these critical barriers through a comprehensive analysis of 3265 academic papers and derives actionable solutions from 1566 patents published between 2016 and 2023. This approach bridges the gap between identifying challenges and implementing solutions. Using the “Stepwise Weight Assessment Ratio Analysis (SWARA)”, twelve critical adoption challenges are analyzed, while Top2Vec-based topic modeling identifies innovations that best address the ranked barriers. In addition to this, the proposed ‘healthcare ecosphere’ knowledge map serves as a comprehensive tool to analyze key stakeholders, their interactions, and the alignment of adoption barriers in solution spaces. The findings show that innovations in blockchain technologies are heavily concentrated in areas such as data security and application functionalities, whereas other critical domains—such as consensus mechanisms, governance, and regulatory frameworks—remain underexplored, pointing to opportunities for growth and development. The mapping of barriers to solutions provides practical guidance for healthcare providers, policymakers, and technologists seeking to implement the blockchain technologies effectively.","container-title":"Technological Forecasting and Social Change","DOI":"10.1016/j.techfore.2025.124031","ISSN":"0040-1625","journalAbbreviation":"Technological Forecasting and Social Change","page":"124031","source":"ScienceDirect","title":"Blockchain technologies adoption in healthcare: Overcoming barriers amid the hype cycle to enhance patient care","title-short":"Blockchain technologies adoption in healthcare","volume":"213","author":[{"family":"Govindarajan","given":"Usharani Hareesh"},{"family":"Narang","given":"Gagan"},{"family":"Singh","given":"Dhiraj Kumar"},{"family":"Yadav","given":"Vinay Surendra"}],"issued":{"date-parts":[["2025",4,1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Ghobakhloo et al., 2023; Govindarajan et al., 2025). A esto se suman dependencia tecnológica y riesgos de ciberseguridad, aunque las investigaciones destacan que los beneficios superan los desafíos y que las medidas de mitigación evolucionan al mismo ritmo que las innovaciones ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"FG8HADG0","properties":{"formattedCitation":"(Delgado-von-Eitzen et\\uc0\\u160{}al., 2026)","plainCitation":"(Delgado-von-Eitzen et al., 2026)","noteIndex":0},"citationItems":[{"id":7797,"uris":["http://zotero.org/users/8164076/items/FA9AFGTZ"],"itemData":{"id":7797,"type":"article-journal","abstract":"Blockchain is a technology that gained relevance in various fields due to its transparency and security in recording information in a reliable and immutable manner. In particular, the adoption of private blockchain platforms based on the Ethereum technology grew significantly in enterprise environments. However, there are certain issues concerning privacy and access control that may pose significant challenges in scenarios where private transactions occur between user agents instead of nodes, that is, between blockchain accounts that are not necessarily attached to specific nodes. The Blockchain Application Firewall (BAF) is introduced as a conceptual framework that can be applied in cases where control over data access is needed, including private transactions between accounts. More specifically, the BAF is intended to complement a blockchain endpoint acting as an intermediary between users and blockchain services and data, monitoring and controlling incoming and outgoing traffic, according to an applied access policy. This work investigates BAF’s feasibility and effectiveness in enhancing the capabilities of Ethereum-based blockchains in the described scenarios. A proof-of-concept was implemented with Besu to assess its feasibility, providing evidence that BAF can act as an additional layer of control over data stored, helping to solve key limitations in practical implementations and allowing exploration of new use cases that could not be addressed so far.","container-title":"Computer Standards & Interfaces","DOI":"10.1016/j.csi.2025.104038","ISSN":"0920-5489","journalAbbreviation":"Computer Standards & Interfaces","page":"104038","source":"ScienceDirect","title":"Blockchain beyond immutability: Application firewalls on ethereum-based platforms","title-short":"Blockchain beyond immutability","volume":"95","author":[{"family":"Delgado-von-Eitzen","given":"Christian"},{"family":"Fernández-Iglesias","given":"Manuel José"},{"family":"Anido-Rifón","given":"Luis"},{"family":"Mikic-Fonte","given":"Fernando A."}],"issued":{"date-parts":[["2026",1,1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Delgado-von-Eitzen et al., 2026).REFERENCIAS BIBLIOGRÁFICAS ADDIN ZOTERO_BIBL {"uncited":[],"omitted":[],"custom":[]} CSL_BIBLIOGRAPHY Ahmed, S. 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