Review
Agronomy
Theo Martin, Pierre Gasselin, Nathalie Hostiou, Gilles Feron, Lucette Laurens, Francois Purseigle, Guillaume Ollivier
Summary: Robots in agriculture are considered part of a new revolution that can reduce working hours or improve working conditions. However, the transformations of work in agriculture are more complex than anticipated. Studies mainly focus on the automated milking system (AMS) and examine the impact on farm structures, the labor market, work organization, and the meaning of work. While AMS reduces physical workload, it introduces new mental workload due to monitoring alarms. There is no evidence supporting a reduction in working hours after installing AMS.
AGRONOMY FOR SUSTAINABLE DEVELOPMENT
(2022)
Article
Chemistry, Multidisciplinary
Younggeun Hyun, Dongseop Lee, Uri Chae, Jindeuk Ko, Jooyeoun Lee
Summary: Digitalization has brought about changes and innovations in daily life and business environments, with Robotics Process Automation playing a key role in improving productivity. CoPA, a form of RPA, has shown to enhance business productivity by saving time and improving document quality in office environments.
APPLIED SCIENCES-BASEL
(2021)
Review
Computer Science, Information Systems
Zineb Ellaky, Faouzia Benabbou, Sara Ouahabi
Summary: This article conducts a systematic literature review on the best practices for malicious SMB recognition in online social networks (OSNs). The study classifies OSN profiles and identifies various types of malicious SMBs. It also proposes a classification of SMBs detection techniques and highlights the limitations of current public datasets. The study concludes by discussing future research directions in this field.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2023)
Article
Business
Tiago Goncalves, Carla Curado, Mirian Oliveira
Summary: Knowledge withholding (KW) is a multidimensional construct in the knowledge management literature. This paper reviews the theoretical backgrounds, antecedents, consequents, and methodological choices related to KW research. Differences between KW-related constructs are identified, and future research directions and practical implications are discussed. The contributions of this work include an overview and clarification of the KW research agenda, as well as a comprehensive analytic framework to guide future research.
JOURNAL OF BUSINESS RESEARCH
(2023)
Review
Information Science & Library Science
Christopher Collins, Denis Dennehy, Kieran Conboy, Patrick Mikalef
Summary: This study addresses the issue of lack of cumulative knowledge building in AI research by conducting a systematic literature review in the IS field between 2005 and 2020. It identified 98 primary studies and synthesized key themes, making important contributions to understanding the current business value, research and practical implications, and future research opportunities of AI.
INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT
(2021)
Review
Business
Marcello M. Mariani, Novin Hashemi, Jochen Wirtz
Summary: Consumer research on conversational agents (CAs) is growing. A systematic literature review (SLR) was conducted to explore research in this field. Four main areas were identified: consumers' trust in CAs, Natural Language Processing (NLP) in developing and designing CAs, communication with CAs, and the impact of CAs on value creation and business. The findings provide an updated synopsis of existing scientific work and a framework for future research.
JOURNAL OF BUSINESS RESEARCH
(2023)
Review
Business
Anupriya Khan, Satish Krishnan, Amandeep Dhir
Summary: The relationship between e-government and corruption has attracted considerable attention, but there is a lack of coherent viewpoints. Through a systematic literature review, we classified and synthesized prior studies, identified key gaps in the literature, discovered potential research areas, and expanded avenues for future studies.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2021)
Review
Green & Sustainable Science & Technology
M. L. Lode, G. te Boveldt, T. Coosemans, L. Ramirez Camargo
Summary: Energy Communities (ECs) have various advantages, but their emergence varies across countries and regions. Currently, the research on the factors for the emergence of ECs is fragmented, and some aspects remain under-explored.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Review
Business
Ivana Sucic Funko, Bozidar Vlacic, Marina Dabic
Summary: After the financial crises of 2008, the public sector sought alternatives to privatization to decrease government participation. This study aims to synthesize literature on public entrepreneurship (PE) and establish a research agenda in this field. By applying various bibliometric techniques, the paper presents the intellectual domain and future research avenues of PE in the public sector.
JOURNAL OF INNOVATION & KNOWLEDGE
(2023)
Review
Business
Emilia Filippi, Mariasole Banno, Sandro Trento
Summary: This paper reviews prior studies on the impact of automation technologies on employment. A structured systematic review of 102 publications from Web of Science, Scopus, and hand searching was conducted. The literature in this area is complex and detailed, as it evaluates the impact of automation at various levels of analysis using different methods. The results are often inconsistent and inconclusive, with few clear findings emerging. Research gaps and future research directions are identified based on previous evidence.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2023)
Review
Business
Rodoula H. Tsiotsou, Achilleas Boukis
Summary: This study provides a systematic review and organization of the literature on in-home service consumption, using a hybrid systematic review approach. The study identifies four major thematic clusters and synthesizes the findings into an integrative framework called InHoServ. It also highlights four fruitful areas for future research in the field of in-home service consumption.
JOURNAL OF BUSINESS RESEARCH
(2022)
Review
Business
Sadasivan Pillai Sandesh, S. Sreejesh, Justin Paul
Summary: The emergence of various approaches in relationship marketing has transformed business marketing practices in managing strategic clients. Key Account Management (KAM) has evolved and gained importance as a distinct sub-division of business-to-business (B2B) marketing. However, the current academic understanding is diverse and disintegrated, posing challenges for better managerial practice. This study reviews the extant KAM literature and provides future research directions based on theory, context, characteristics, and methodology.
JOURNAL OF BUSINESS RESEARCH
(2023)
Review
Business
Chiara Ancillai, Andrea Sabatini, Marco Gatti, Andrea Perna
Summary: Digital technologies have a profound impact on companies' activities and processes, leading to changes in value creation, delivery, and capture mechanisms. However, despite significant investments in digital technologies and transformation, firms struggle to fully utilize them, resulting in a digital paradox. This study conducts a systematic literature review to identify thematic areas and provide future research directions to address this issue.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2023)
Review
Business
Peter Guckenbiehl, Graciela Corral de Zubielqui, Noel Lindsay
Summary: This paper examines the use of knowledge for innovation in start-ups, and presents an integrated framework through a systematic literature review to highlight the focus and gaps in existing research. The findings indicate a predominant focus on for-profit start-ups, with limited attention to the interplay between knowledge sources, mechanisms, and types.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2021)
Review
Hospitality, Leisure, Sport & Tourism
Varsha Jain, Jochen Wirtz, Parth Salunke, Robin Nunkoo, Ayushi Sharma
Summary: This article provides a systematic review of the literature on luxury hospitality, using a quantitative bibliometric method. It identifies the intellectual structure of the field and presents six research clusters. The article also highlights the most frequently used theories and outlines a future research agenda.
INTERNATIONAL JOURNAL OF HOSPITALITY MANAGEMENT
(2023)
Article
Computer Science, Interdisciplinary Applications
Jorge Munoz-Gama, Niels Martin, Carlos Fernandez-Llatas, Owen A. Johnson, Marcos Sepulveda, Emmanuel Helm, Victor Galvez-Yanjari, Eric Rojas, Antonio Martinez-Millana, Davide Aloini, Ilaria Angela Amantea, Robert Andrews, Michael Arias, Iris Beerepoot, Elisabetta Benevento, Andrea Burattin, Daniel Capurro, Josep Carmona, Marco Comuzzi, Benjamin Dalmas, Rene de la Fuente, Chiara Di Francescomarino, Claudio Di Ciccio, Roberto Gatta, Chiara Ghidini, Fernanda Gonzalez-Lopez, Gema Ibanez-Sanchez, Hilda B. Klasky, Angelina Prima Kurniati, Xixi Lu, Felix Mannhardt, Ronny Mans, Mar Marcos, Renata Medeiros de Carvalho, Marco Pegoraro, Simon K. Poon, Luise Pufahl, Hajo A. Reijers, Simon Remy, Stefanie Rinderle-Ma, Lucia Sacchi, Fernando Seoane, Minseok Song, Alessandro Stefanini, Emilio Sulis, Arthur H. M. ter Hofstede, Pieter J. Toussaint, Vicente Traver, Zoe Valero-Ramon, Inge van de Weerd, Wil M. P. van der Aalst, Rob Vanwersch, Mathias Weske, Moe Thandar Wynn, Francesca Zerbato
Summary: Process mining techniques are not widely used in healthcare beyond targeted case studies, and there is a need for further research and improvement to consider the characteristics of healthcare processes.
JOURNAL OF BIOMEDICAL INFORMATICS
(2022)
Article
Computer Science, Artificial Intelligence
Jing Yang, Chun Ouyang, Wil M. P. van der Aalst, Arthur H. M. ter Hofstede, Yang Yu
Summary: In order to simplify business processes and enhance organizational competitiveness, it is crucial to gain deep insights into the collaboration of various resources in achieving organizational goals. Process mining can derive organizational models from event logs containing resource-related data, but existing techniques are insufficient in handling the multifaceted nature of business processes and determining the involvement of resource groupings in process execution. Moreover, there is a lack of evaluation methods for discovered organizational models. To address these challenges, a novel framework called OrdinoR is proposed, which supports the discovery, evaluation, and analysis of organizational models using event logs. The framework incorporates a comprehensive organizational model concept where resource groupings are linked to different dimensions of process execution, and provides a set of measures for systematic evaluation and behavior analysis of resource groups.
DECISION SUPPORT SYSTEMS
(2022)
Article
Computer Science, Information Systems
Kanika Goel, Wasana Bandara, Guy Gable
Summary: This paper presents a conceptual framework for the success of the Business Correspondent model and validates its relevance through empirical research on four implementations. The framework provides a strong theoretical foundation and practical guidance for understanding and evaluating the success of the Business Correspondent model.
INFORMATION SYSTEMS FRONTIERS
(2023)
Article
Computer Science, Information Systems
Anastasiia Pika, Chun Ouyang, Arthur H. M. ter Hofstede
Summary: This article presents a novel approach for identifying batching behavior from process execution data recorded in event logs. The approach can discover different types of batch-processing behaviors and allows users to configure batch-processing characteristics they are interested in. The approach is implemented and evaluated through experiments with synthetic event logs and case studies with real-life event logs, demonstrating its effectiveness in identifying various batch-processing behaviors in business processes.
ACM TRANSACTIONS ON MANAGEMENT INFORMATION SYSTEMS
(2022)
Article
Multidisciplinary Sciences
Robert Andrews, Bayan Bevrani, Brigitte Colin, Moe T. Wynn, Arthur H. M. ter Hofstede, Jackson Ring
Summary: The risk posed by wildlife to air transportation is a global concern. Airport operations have significant impacts on bird populations. Current wildlife risk assessment techniques in Australia are limited to ranking identified hazard species. This study aims to develop a dynamic, evidence-based risk assessment model. Three assessment techniques (Algebraic, Bayesian, and Clustering) are introduced to measure the likelihood of bird strike under changing environmental conditions.
Article
Computer Science, Interdisciplinary Applications
Iris Beerepoot, Claudio Di Ciccio, Hajo A. Reijers, Stefanie Rinderle-Ma, Wasana Bandara, Andrea Burattin, Diego Calvanese, Tianwa Chen, Izack Cohen, Benoit Depaire, Gemma Di Federico, Marlon Dumas, Christopher van Dun, Tobias Fehrer, Dominik A. Fischer, Avigdor Gal, Marta Indulska, Vatche Isahagian, Christopher Klinkmueller, Wolfgang Kratsch, Henrik Leopold, Amy Van Looy, Hugo Lopez, Sanja Lukumbuzya, Jan Mendling, Lara Meyers, Linda Moder, Marco Montali, Vinod Muthusamy, Manfred Reichert, Yara Rizk, Michael Rosemann, Maximilian Roeglinger, Shazia Sadiq, Ronny Seiger, Tijs Slaats, Mantas Simkus, Ida Asadi Someh, Barbara Weber, Ingo Weber, Mathias Weske, Francesca Zerbato
Summary: This paper provides an overview of the major research problems in the field of Business Process Management. These challenges have been identified through an open call to the community, discussed and refined in a workshop, and described in detail in this paper with motivations for further investigation. This overview aims to inspire both novice and advanced scholars interested in innovative ideas for analyzing, designing, and managing work processes using information technology.
COMPUTERS IN INDUSTRY
(2023)
Article
Computer Science, Information Systems
Jan Martijn E. M. van der Werf, Artem Polyvyanyy, Bart R. van Wensveen, Matthieu Brinkhuis, Hajo A. Reijers
Summary: A process discovery algorithm aims to construct a precise, general, and simple process model that accurately represents the real-world process stored in event data. However, existing algorithms often neglect the relationship between input and output quality, leading to a lack of guarantee for better quality models with better quality input data. This paper calls for a more rigorous design of process discovery algorithms that include properties connecting input and output qualities. Four incremental maturity stages for process discovery algorithms and concrete guidelines for formulating relevant properties and experimental validation are presented.
INFORMATION SYSTEMS
(2023)
Article
Health Care Sciences & Services
Rehan Syed, Rebekah Eden, Tendai Makasi, Ignatius Chukwudi, Azumah Mamudu, Mostafa Kamalpour, Dakshi Kapugama Geeganage, Sareh Sadeghianasl, Sander J. J. Leemans, Kanika Goel, Robert Andrews, Moe Thandar Wynn, Arthur ter Hofstede, Trina Myers
Summary: The aim of this study was to develop a consolidated digital health DQ dimension and outcome (DQ-DO) framework. Through a systematic literature review and analysis, 6 dimensions of digital health DQ, their interrelationships, and 5 DQ outcomes were identified.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2023)
Article
Business
Azumah Mamudu, Wasana Bandara, Sander J. J. Leemans, Moe Thandar Wynn
Summary: This study proposes a framework to assess the impacts of process mining on an organization's business processes and identifies key categories of impacts and their interrelationships. The study finds that the impacts of process mining can be categorized into four main categories: impact on the process, customer impact, financial impact, and impact on innovation and learning. The study also identifies the interrelationships between these categories.
BUSINESS PROCESS MANAGEMENT JOURNAL
(2023)
Review
Operations Research & Management Science
Wasana Bandara, Rehan Syed
Summary: This tutorial-paper provides a detailed description of a literature review protocol, including its definition, major components, and design guidelines. It also offers a comprehensive toolkit with step-by-step instructions, templates, and examples for researchers to adapt to their own projects. This information is useful for novice and expert researchers conducting literature reviews for publication, as well as reviewers, editors, and educators.
JOURNAL OF DECISION SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Sander J. J. Leemans, James M. McGree, Artem Polyvyanyy, Arthur H. M. ter Hofstede
Summary: Through process mining, organisations can improve business processes by utilizing recorded data. Despite advances in the field, a solid statistical foundation is still lacking. This article contributes statistical tests and measures for treating process behavior as a variable, providing a more objective assessment method.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Jelmer J. Koorn, Xixi Lu, Henrik Leopold, Niels Martin, Sam Verboven, Hajo A. Reijers
Summary: This paper proposes a novel relation mining approach for healthcare processes that explicitly considers confounding variables and transparently communicates their effects to the user. Through evaluation experiments, the applicability and importance of this approach are demonstrated in healthcare decision making and causal model estimation.
2022 4TH INTERNATIONAL CONFERENCE ON PROCESS MINING (ICPM 2022)
(2022)
Proceedings Paper
Computer Science, Information Systems
Francesca Zerbato, Jelmer J. Koorn, Iris Beerepoot, Barbara Weber, Hajo A. Reijers
Summary: This paper presents the results of an interview study on question development in process mining, providing insights from expert interviewees and six recommendations to enhance existing methodologies. Concrete examples of how process mining analyses can support question formulation and refinement are also presented.
ENTERPRISE DESIGN, OPERATIONS, AND COMPUTING, EDOC 2022
(2022)
Proceedings Paper
Business
Azumah Mamudu, Wasana Bandara, Moe T. Wynn, Sander J. J. Leemans
Summary: Process mining is a technique used to extract insights from event logs of Information Systems (IS) in order to improve operational efficiency. However, there is limited research on the critical success factors of process mining, and the relationships between these factors are not well understood.
BUSINESS PROCESS MANAGEMENT (BPM 2022)
(2022)
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)
