Article
Engineering, Electrical & Electronic
Dario Petri, Paolo Carbone, Luca Mari
Summary: This article introduces a general-purpose framework aimed at capturing the concept of quality of measurement information (MI) and provides systematic analysis for evaluating, communicating, and improving MI quality, with an application example presented to test the framework. The framework, based on general criteria from ISO standards, classifies criteria according to syntactic, semantic, and pragmatic layers, forming a structured approach that includes both top-down analysis and bottom-up synthesis.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Green & Sustainable Science & Technology
Jeong Sik Kim
Summary: This study empirically explores and verifies the impact of participatory decision making on employees' task performance and personal growth, and reveals the sequential mediating role of perceived job meaningfulness and job involvement.
Article
Computer Science, Information Systems
Xiaofang Li, Huchang Liao
Summary: Large-scale group decision making (LSGDM) has gained attention from scholars recently due to the involvement of a large number of experts. The development of social media has promoted communication among experts, making them interdependent. Existing LSGDM methods primarily use aggregation strategies that cannot reflect the real opinion of the expert group. To address this, a new LSGDM method based on empathetic network and spatial information aggregation is proposed. The model is solved using a genetic algorithm and its validity is demonstrated through a practical example on the selection of urgent risks in COVID-19 vaccine transportation.
INFORMATION SCIENCES
(2023)
Article
Engineering, Chemical
Tiantian Zhu, Stein Haugen, Yiliu Liu
Summary: In order to prevent major accidents in process industries, it is crucial to provide decision-makers with accurate risk information to aid in risk-related decisions. A framework is proposed to organize and provide risk information so that decision-makers can more effectively detect, assess, and address risk issues.
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES
(2021)
Article
Economics
Xiaotong Li, Qianyao Xue
Summary: This paper explores the complexities of information security investment decisions among substitutable enterprises by considering factors such as substitution rate, enterprise quantity, and hacker invasion probability. A game model is constructed and the optimal investment level is analyzed under individual and joint decision-making scenarios. This research provides a new solution to information security investment decisions among substitutable enterprises.
MANAGERIAL AND DECISION ECONOMICS
(2021)
Article
Computer Science, Software Engineering
Fachao Li, Chenxia Jin, Xiao Zhang
Summary: This study introduces a knowledge reliability-based attribute importance computation method DE-AIM and analyzes its value and structure features through theoretical proof and example calculation. The research indicates that DE-AIM is suitable for solving multi-attribute decision-making problems and can reflect different decision preferences.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2021)
Article
Computer Science, Artificial Intelligence
Jinyu Zhang, Yunlong Chen, Chenhui Xia
Summary: This study focuses on the decision-making behavior of agents in information diffusion and its influence from local network structures. By utilizing the cause-effect graph method to model the interaction structures of agents in social networks, the researchers propose decision-making models for agents. These models can comprehensively consider factors such as social positions, interaction strengths, and diffusion strategies of agents, helping to better understand the mechanisms that influence diffusion in real social networks.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Computer Science, Interdisciplinary Applications
Shreyanshu Parhi, Kanchan Joshi, Milind Akarte
Summary: This study fills the research gap by quantifying smart manufacturing performance indicators. Through a literature review methodology, potential indicators are defined, and a conceptual framework for decision-making in smart manufacturing is proposed.
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
(2023)
Review
Nursing
Ebru Bakir, Michelle Briggs, Carolyn Mackintosh-Franklin, Marie Marshall, Francisca Achaliwie
Summary: This study conducted a systematic scoping review to examine the child-parent-nurse relationships during postoperative pain management. The findings showed that the deficient relationships significantly contributed to suboptimal pain care, leading to prolonged and untreated postoperative pain in children. This study highlights the importance of improving nursing pain management practices by acknowledging the role of the relationships between children, parents, and nurses.
JOURNAL OF CLINICAL NURSING
(2023)
Article
Engineering, Industrial
Sai S. Nudurupati, Sofiane Tebboune, Patrizia Garengo, Richard Daley, Julie Hardman
Summary: This study investigates the development of performance measurement systems and the driving of appropriate resources and capabilities in data-intensive organizations. The findings emphasize the importance of organizational structure and cross-functional communication in cultivating senior management commitment and developing data capture and analytical capabilities for effective decision-making.
PRODUCTION PLANNING & CONTROL
(2022)
Article
Psychology, Multidisciplinary
Weijane Lin, Jui-Ying Wang, Hsiu-Ping Yueh
Summary: This study illustrated the formal process of designing a situated serious game to facilitate learning of information ethics. The results showed that the game significantly improved participants' knowledge of information ethics. Analysis of participants' behavioral features supported the effectiveness of the game in improving their understanding and judgment of information ethics issues.
FRONTIERS IN PSYCHOLOGY
(2022)
Article
Economics
Sabine E. Grimm, Xavier Pouwels, Bram L. T. Ramaekers, Nicolien T. van Ravesteyn, Valerie D. V. Sankatsing, Janneke Grutters, Manuela A. Joore
Summary: Analyzing the barriers to the implementation of Value of Information (VOI) analysis and proposing corresponding actions and tools can be beneficial for health technology assessment organizations aiming to use VOI analysis in technology assessment and research prioritization. Further research should focus on the application and evaluation of the proposed actions in real assessment processes.
Article
Economics
Xileidys Parra, Xavier Tort-Martorell, Fernando Alvarez-Gomez, Carmen Ruiz-Vinals
Summary: The decision-making process (DMP) in organizations has undergone changes influenced by information technologies and computational science. This study provides a chronological review of the information-driven DMP evolution and discusses how technology has impacted information generation, storage, management, and its utilization for improved decision-making and knowledge acquisition.
JOURNAL OF THE KNOWLEDGE ECONOMY
(2022)
Article
Computer Science, Artificial Intelligence
Xiangyu Zhong, Xuanhua Xu, Mark Goh, Bin Pan
Summary: This study incorporates trust relationships between decision-makers into the large group decision-making process by transforming them into compromise information. By considering this compromise information throughout various stages of the decision-making process, the rationality and scientificity of the decision results can be improved.
COGNITIVE COMPUTATION
(2023)
Article
Automation & Control Systems
Yucheng Dong, Quanbo Zha, Hengjie Zhang, Francisco Herrera
Summary: This article introduces a trust relationships CRP with a feedback mechanism, consisting of leader-based preference adjustment and trust relationships improvement. It bridges opinion dynamics and group decision making, highlighting the role of leaders and trust relationships in GDM problems. It also discusses a new strategic manipulation issue called trust relationship manipulation and presents clique-based strategies for manipulating trust relationships.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Operations Research & Management Science
Luciano Novais, Juan Manuel Maqueira, Angel Ortiz, Sebastian Bruque
Summary: Hypothesis contrast using structural equations is a popular technique in supply chain management research, providing a static view of reality, while dynamic analyses are necessary to visualize business behaviors in future scenarios. This paper proposes a method to perform simulations at a strategic level by combining structural equation models and system dynamics models, allowing for prospective strategic analysis. Two applications demonstrate the usefulness of this approach in various supply chain management situations.
CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH
(2021)
Article
Operations Research & Management Science
Maria-Jose Verdecho, Faustino Alarcon-Valero, David Perez-Perales, Juan-Jose Alfaro-Saiz, Raul Rodriguez-Rodriguez
Summary: This research proposes a methodology for supporting supplier selection decisions, combining sustainability performance and supplier assessment criteria, to help organizations choose suppliers that align with their sustainability strategy.
CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH
(2021)
Article
Operations Research & Management Science
Maria-Jose Verdecho, Juan-Jose Alfaro-Saiz, Raul Rodriguez-Rodriguez, Pedro Gomez-Gasquet
Summary: This paper addresses the importance of measuring product/service performance in organizations and developing and assessing transversal competences in universities. The research finds that the achievement of transversal competences can be assessed at different levels of study to support students in improving employability.
CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH
(2021)
Article
Computer Science, Information Systems
Ramona-Diana Leon, Raul Rodriguez-Rodriguez, Pedro Gomez-Gasquet, Josefa Mula
INFORMATION PROCESSING & MANAGEMENT
(2020)
Article
Green & Sustainable Science & Technology
Carla Andrade Arteaga, Raul Rodriguez-Rodriguez, Juan-Jose Alfaro-Saiz, Maria-Jose Verdecho
Article
Engineering, Multidisciplinary
Ana Esteso, M. M. E. Alemany, Angel Ortiz
Summary: The agri-food sector is the largest manufacturing sector in Europe, employing over four million people and generating revenue exceeding one trillion euro. However, up to 88 million tons of food are wasted annually in Europe, which highlights the importance of sustainability in agri-food supply chains. Product perishability has a significant impact on supply chain design and economic performance, especially for products with short shelf lives.
APPLIED MATHEMATICAL MODELLING
(2021)
Article
Operations Research & Management Science
Ana Esteso, M. M. E. Alemany, Angel Ortiz, Shaofeng Liu
Summary: This study proposes a novel centralized multi-objective mathematical programming model to support sustainable crop planning definition for a region, aiming to maximize supply chain profits, minimize waste, and reduce unfairness among farmers. The research finds trade-offs among the three objectives and introduces some new techniques like anticipating operational decisions and the possibility of waste clearance.
CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH
(2022)
Article
Engineering, Industrial
Ana Esteso, M. M. E. Alemany, Angel Ortiz, Herve Panetto
Summary: This research develops a model to improve the quality and freshness of sold vegetables through a funding program between farmers and retailers. The model solves the optimization problem of supply chain profits, vegetable waste, economic unfairness among farmers, unfairness in the distribution of funds, and the freshness of sold vegetables.
JOURNAL OF INDUSTRIAL ENGINEERING AND MANAGEMENT-JIEM
(2022)
Article
Engineering, Chemical
Jairo Nunez Rodriguez, Hugo Hernando Andrade Sosa, Sylvia Maria Villarreal-Archila, Angel Ortiz
Summary: Based on a case study of medical implant manufacturing, it was found that additive manufacturing (AM) has a longer production time but performs better under conditions of lower demand due to its customization and small batch production capabilities.
Article
Operations Research & Management Science
Ana Esteso, M. M. E. Alemany, Fernando Ottati, Angel Ortiz
Summary: This paper proposes a tool based on a system dynamics model to determine the robustness of an already designed five-stage fresh agri-food supply chain and its planting planning to disruptions in demand, supply, transport, and the operability of its nodes. The model is validated using the known behavior replication test and the extreme conditions test. A methodology for the improvement of the supply chain's robustness is presented and applied to a case study. The model is then re-run to evaluate the impact of proactive strategies on the supply chain and select the most beneficial for improving its robustness.
OPERATIONAL RESEARCH
(2023)
Article
Operations Research & Management Science
Ana Esteso, M. M. E. Alemany, Angel Ortiz
Summary: This paper proposes a multi-objective optimization model for planning the production and sale of fresh crops, aiming to enhance the sustainability of the agricultural supply chain. The model considers five objectives related to profitability, waste reduction, meeting demand, freshness, and minimizing economic injustice. The tool is validated through a case study in Argentina and demonstrates its potential application by real decision-makers.
JOURNAL OF DECISION SYSTEMS
(2023)
Article
Engineering, Multidisciplinary
Miguel Rodriguez-Garcia, Angel Ortiz Bas, Jose Carlos Prado-Prado, Andrew Lyons
Summary: This study develops a cost framework for online grocery retailing, using timedriven activity-based costing (TDABC), to identify the most suitable e-fulfillment strategy. The framework is based on insights from two large European grocery retailers and focuses on cost drivers such as picking and delivery costs. The study highlights the importance of considering less studied logistics activities in total expenses for both retail store and warehouse e-fulfillment strategies.
INTERNATIONAL JOURNAL OF PRODUCTION MANAGEMENT AND ENGINEERING
(2023)
Proceedings Paper
Automation & Control Systems
Ana Esteso, M. M. E. Alemany, Angel Ortiz, Rina Iannacone
Summary: This study proposes a multi-objective mixed integer linear programming model for vegetable supply chain design that optimizes both supply chain profits and the average freshness of sold vegetables. By solving the model for different weight assignments to the objectives, the results demonstrate the impact of maximizing the freshness of vegetables on the supply chain configuration.
IOT AND DATA SCIENCE IN ENGINEERING MANAGEMENT
(2023)
Article
Management
Miguel Rodriguez Garcia, Iria Gonzalez Romero, Angel Ortiz Bas, J. Carlos Prado-Prado
Summary: This study develops two frameworks for identifying the elements of value proposition and logistics strategy of grocery pure players, with a focus on key elements and design characteristics determined through literature review and exploratory studies. The analysis categorizes the elements into ten for value proposition and twelve for logistics strategy, highlighting important differences among intermediaries and independent pure players in the relationships among these elements.
INTERNATIONAL JOURNAL OF LOGISTICS-RESEARCH AND APPLICATIONS
(2022)
Article
Engineering, Industrial
Eduardo Guzman Ortiz, Beatriz Andres, Francisco Fraile, Raul Poler, Angel Ortiz Bas
Summary: This paper describes the implementation of a Fleet Management System (FMS) for logistics tasks by mobile robots in a hospital environment. The FMS includes a routing engine, a task scheduler, an Endorse Broker, a controller and a backend API. The system supports dynamic path planning and fleet management, using advanced algorithms and tools for efficient execution of tasks.
JOURNAL OF INDUSTRIAL ENGINEERING AND MANAGEMENT-JIEM
(2021)
Article
Computer Science, Interdisciplinary Applications
Francesco Pistolesi, Michele Baldassini, Beatrice Lazzerini
Summary: More than one in four workers worldwide suffer from back pain, resulting in the loss of 264 million work days annually. In the U.S., it costs $50 billion in healthcare expenses each year, rising up to $100 billion when accounting for decreased productivity and lost wages. The impending Industry 5.0 revolution emphasizes worker well-being and their rights, such as privacy, autonomy, and human dignity. This paper proposes a privacy-preserving artificial intelligence system that monitors the posture of assembly line workers. The system accurately assesses upper-body and lower-body postures while respecting privacy, enabling the detection of harmful posture habits and reducing the likelihood of musculoskeletal disorders.
COMPUTERS IN INDUSTRY
(2024)
Article
Computer Science, Interdisciplinary Applications
Xavier Boucher, Camilo Murillo Coba, Damien Lamy
Summary: This paper explores the new business strategies of digital servitization and smart PSS delivery, and develops conceptual prototypes of smart PSS value offers for early stages of the design process. It presents the development and experimentation of a modelling language and toolkit, and applies it to the design of a smart PSS in the field of heating appliances.
COMPUTERS IN INDUSTRY
(2024)
Article
Computer Science, Interdisciplinary Applications
Dieudonne Tchuente, Jerry Lonlac, Bernard Kamsu-Foguem
Summary: Artificial Intelligence (AI) is becoming increasingly important in various sectors of society. However, the black box nature of most AI techniques such as Machine Learning (ML) hinders their practical application. This has led to the emergence of Explainable artificial intelligence (XAI), which aims to provide AI-based decision-making processes and outcomes that are easily understood, interpreted, and justified by humans. While there has been a significant amount of research on XAI, there is currently a lack of studies on its practical applications. To address this research gap, this article proposes a comprehensive review of the business applications of XAI and a six-step framework to improve its implementation and adoption by practitioners.
COMPUTERS IN INDUSTRY
(2024)
Article
Computer Science, Interdisciplinary Applications
Francois-Alexandre Tremblay, Audrey Durand, Michael Morin, Philippe Marier, Jonathan Gaudreault
Summary: Continuous high-frequency wood drying, integrated with a traditional wood finishing line, improves the value of lumber by correcting moisture content piece by piece. Using reinforcement learning for continuous drying operation policies outperforms current industry methods and remains robust to sudden disturbances.
COMPUTERS IN INDUSTRY
(2024)
Article
Computer Science, Interdisciplinary Applications
Luyao Xia, Jianfeng Lu, Yuqian Lu, Wentao Gao, Yuhang Fan, Yuhao Xu, Hao Zhang
Summary: Efficient assembly sequence planning is crucial for enhancing production efficiency, ensuring product quality, and meeting market demands. This study proposes a dynamic graph learning algorithm called assembly-oriented graph attention sequence (A-GASeq), which optimizes the assembly graph structure to guide the search for optimal assembly sequences. The algorithm demonstrates superiority and broad utility in real-world scenarios.
COMPUTERS IN INDUSTRY
(2024)
Article
Computer Science, Interdisciplinary Applications
Mutahar Safdar, Padma Polash Paul, Guy Lamouche, Gentry Wood, Max Zimmermann, Florian Hannesen, Christophe Bescond, Priti Wanjara, Yaoyao Fiona Zhao
Summary: Metal-based additive manufacturing can achieve fully dense metallic components, and the application of machine learning in this field has been growing rapidly. However, there is a lack of framework to manage these machine learning models and guidance on the fundamental requirements for a cross-disciplinary platform to support process-based machine learning models in industrial metal AM.
COMPUTERS IN INDUSTRY
(2024)
