Article
Management
Stephanie Kelley, Anton Ovchinnikov, David R. Hardoon, Adrienne Heinrich
Summary: This study simulates the impact of different antidiscrimination laws and their corresponding data management and model-building regimes on gender-based discrimination in nonmortgage fintech lending. The study finds that regimes prohibiting the use of gender increase discrimination, while machine learning models are less discriminatory, more accurate, and more profitable than traditional statistical models. Measures such as feature engineering, feature selection, and gender-aware hyperparameter selection can help reduce discrimination.
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
(2022)
Article
Computer Science, Software Engineering
Zhenpeng Chen, Jie M. Zhang, Federica Sarro, Mark Harman
Summary: This study presents a large-scale empirical investigation of 17 representative bias mitigation methods for Machine Learning classifiers. The results show that these methods significantly decrease ML performance in 53% of scenarios, improve fairness in 46% of scenarios, and even lead to a decrease in both fairness and ML performance in 25% of scenarios.
ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY
(2023)
Review
Radiology, Nuclear Medicine & Medical Imaging
Imon Banerjee, Kamanasish Bhattacharjee, John L. Burns, Hari Trivedi, Saptarshi Purkayastha, Laleh Seyyed-Kalantari, Bhavik N. Patel, Rakesh Shiradkar, Judy Gichoya
Summary: Despite the high performance of AI models in medical imaging tasks, real-world performance failures and biases limit its usefulness for improving patients' lives. The authors discuss various types of biases from shortcut learning in AI models, propose tool kits for evaluating and mitigating bias, and summarize current techniques for mitigating bias during different phases of AI model development.
JOURNAL OF THE AMERICAN COLLEGE OF RADIOLOGY
(2023)
Article
Education & Educational Research
Aidan Pucchio, Raahulan Rathagirishnan, Natasha Caton, Peter J. Gariscsak, Joshua Del Papa, Jacqueline Justino Nabhen, Vicky Vo, Wonjae Lee, Fabio Y. Moraes
Summary: This study examines the perceptions of undergraduate medical students in Canada regarding AI in medicine, their need for AI learning opportunities, and their preferred medium for AI curriculum delivery. The findings suggest that students believe AI applications will become common and beneficial in medicine, and they acknowledge the need to learn and understand AI in their medical careers. Additionally, the majority of students agree that AI should be formally taught in medical education. However, many students reported a lack of formal educational opportunities about AI and expressed dissatisfaction with the current level of AI-related learning opportunities.
BMC MEDICAL EDUCATION
(2022)
Article
Economics
William Padula, Noemi Kreif, David J. Vanness, Blythe Adamson, Juan-David Rueda, Federico Felizzi, Pall Jonsson, Maarten J. IJzerman, Atul Butte, William Crown
Summary: Advances in machine learning and artificial intelligence have great potential benefits in healthcare, including health economics and outcomes research. Machine learning can enhance these areas by analyzing big data effectively. However, a lack of transparency in how machine learning methods deliver solutions, especially in unsupervised circumstances, increases risk when using machine learning results.
Article
Psychology, Multidisciplinary
Sara Lumbreras
Summary: There are interesting synergies between artificial intelligence (AI) and belief formation. AI can provide explanations for the logical derivation and quantitative explanations of beliefs. Integration of AI with human belief processes, such as reflecting, rationalizing, and communicating through semantic coding, enables potential advancements in Interpretable Machine Learning.
FRONTIERS IN PSYCHOLOGY
(2022)
Review
Biochemistry & Molecular Biology
Somayah Albaradei, Maha Thafar, Asim Alsaedi, Christophe Van Neste, Takashi Gojobori, Magbubah Essack, Xin Gao
Summary: Metastasis, the primary cause of cancer-related deaths, has been the focus of research utilizing technologies like high-throughput sequencing to unravel cellular processes. Machine learning and deep learning methods have been used to predict metastasis onset, enhancing diagnostic and disease treatment outcomes.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2021)
Article
Mathematics
Catalina Lozano-Murcia, Francisco P. Romero, Jesus Serrano-Guerrero, Jose A. Olivas
Summary: Machine learning is a subfield of artificial intelligence that focuses on creating algorithms capable of learning from data and making predictions. However, in actuarial science, the interpretability of these models often poses challenges, leading to concerns about their accuracy and reliability. Explainable artificial intelligence (XAI) has emerged as a solution to address these issues by facilitating the development of accurate and comprehensible models.
Article
Multidisciplinary Sciences
Shamil Islamov, Alexey Grigoriev, Ilia Beloglazov, Sergey Savchenkov, Ove Tobias Gudmestad
Summary: This study explores the creation of a machine learning model for the oil and gas industry to predict risks in drilling processes. Analyzing historical data shows that a gradient boosting model outperforms other models in classifying drilling problems.
Review
Biochemical Research Methods
Lena Davidson, Mary Regina Boland
Summary: Through a systematic review, it was found that supervised learning methods are more popular in the field of artificial intelligence and machine learning, and AI and ML methods are mainly used in prenatal care, perinatal care, and preterm birth in the pregnancy domain. Future research should focus on less-studied areas such as postnatal and postpartum care, and more emphasis should be placed on the clinical adoption of AI methods and the ethical implications of such adoption.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Agronomy
Gniewko Niedbala, Jaroslaw Kurek, Bartosz Swiderski, Tomasz Wojciechowski, Izabella Antoniuk, Krzysztof Bobran
Summary: In this paper, a high-accuracy model for predicting blueberry yield is presented. The model is trained using innovative datasets that include agronomic, climatic, soil, and satellite-imaging vegetation data. After extensive data preprocessing and training of 11 models, the Extreme Gradient Boosting algorithm is identified as the best performing solution, with a MAPE value of 12.48%. The research has practical significance in improving the overall yield management process for blueberries.
Review
Pharmacology & Pharmacy
Magnus Gray, Ravi Samala, Qi Liu, Denny Skiles, Joshua Xu, Weida Tong, Leihong Wu
Summary: This literature review examines the current state of research on AI bias, including its sources, as well as methods for measuring, benchmarking, and mitigating it. The paper specifically focuses on biases and methods of mitigation relevant to the healthcare field, and offers a perspective on bias measurement and mitigation in regulatory science decision making.
CLINICAL PHARMACOLOGY & THERAPEUTICS
(2023)
Review
Computer Science, Information Systems
Tomasz Wlodarczyk, Szymon Plotka, Tomasz Szczepanski, Przemyslaw Rokita, Nicole Sochacki-Wojcicka, Jakub Wojcicki, Michal Lipa, Tomasz Trzcinski
Summary: Preterm births affect 15 million children globally each year, with current efforts focusing on mitigating rather than preventing prematurity. Machine learning shows promise as a tool for supporting preterm birth diagnosis; this study presents various machine learning algorithms applied to preterm birth prediction. The analysis of a wide range of data sets, from electrohysterogram signals to transvaginal ultrasounds, is a key strength of the research.
Review
Computer Science, Artificial Intelligence
Tiago P. Pagano, Rafael B. Loureiro, Fernanda V. N. Lisboa, Rodrigo M. Peixoto, Guilherme A. S. Guimaraes, Gustavo O. R. Cruz, Maira M. Araujo, Lucas L. Santos, Marco A. S. Cruz, Ewerton L. S. Oliveira, Ingrid Winkler, Erick G. S. Nascimento
Summary: One of the challenges in artificial intelligence is to ensure fairness and absence of bias in model decisions. This study examined current knowledge on bias and unfairness in machine learning models and found that most research focuses on identification and mitigation techniques, offering tools, statistical approaches, important metrics, and datasets used for bias experiments.
BIG DATA AND COGNITIVE COMPUTING
(2023)
Review
Health Care Sciences & Services
Farida Mohsen, Balqees Al-Saadi, Nima Abdi, Sulaiman Khan, Zubair Shah
Summary: Precision medicine has the potential to revolutionize cardiovascular diseases by tailoring treatment strategies to individual characteristics. Artificial intelligence (AI) is increasingly being applied in various areas of cardiovascular medicine, including diagnosis, prognosis, risk prediction, and treatment planning.
JOURNAL OF PERSONALIZED MEDICINE
(2023)
Article
Business
Stephan Ludwig, Dennis Herhausen, Dhruv Grewal, Liliana Bove, Sabine Benoit, Ko de Ruyter, Peter Urwin
Summary: This study reveals that in online freelance marketplaces, buyers attract more bids when they provide moderate task information and concreteness, avoid sharing personal information, and limit emotional intensity. Freelancers' bid success and price premiums increase when they mimic the level of task information and emotional intensity shown by buyers. However, mimicking lack of personal information and concreteness reduces freelancers' success, so freelancers should always be more specific and offer more personal information than buyers. These findings suggest that balancing uncertainty in communication can lead to success for both buyers and freelancers in the gig economy.
JOURNAL OF MARKETING
(2022)
Article
Business
Dennis Herhausen, Bjorn Ivens, Robert Spencer, Michael Weibel
Summary: This paper contributes to the key account management (KAM) literature by studying different KAM configurations and KAM performance drivers. By analyzing survey data from 411 managers, it identifies five unique KAM configurations and highlights the importance of KAM capabilities and social media communication in improving KAM effectiveness and market performance.
INDUSTRIAL MARKETING MANAGEMENT
(2022)
Article
Business
Nadine Kammerlander, Jochen Menges, Dennis Herhausen, Petra Kipfelsberger, Heike Bruch
Summary: Research suggests that firms with family CEOs have unique characteristics that influence the emotions of employees. Family CEOs are more likely to infuse positive emotions in employees compared to hired professional CEOs, and these emotions spread through the organization via emotional contagion. The presence of family CEOs is also associated with lower voluntary turnover rates, especially in smaller and centralized firms. This research highlights the importance of family CEOs in creating pleasant work environments.
LONG RANGE PLANNING
(2023)
Article
Business
Dennis Herhausen, Lauren Grewal, Anne Roggeveen, Krista Hill L. Cummings, Francisco Villarroel Ordenes, Dhruv Grewal
Summary: This study identifies ways to mitigate negative arousal in text-based social media complaining, specifically through active listening and empathy. The findings provide important implications for dealing with public social media complaints.
JOURNAL OF MARKETING
(2023)
Article
Business
Petra Kipfelsberger, Anneloes Raes, Dennis Herhausen, Ronit Kark, Heike Bruch
Summary: This study proposes a leader-follower transfer model of work meaningfulness based on self-concept theory, examining the role of leaders' own experience of meaningfulness in enhancing followers' work meaningfulness. The study confirms the moderated-mediation model and rules out alternative transfer mechanisms, contributing to the understanding of work meaningfulness and offering practical insights for enhancing it in organizations.
JOURNAL OF ORGANIZATIONAL BEHAVIOR
(2022)
Article
Business
Dhruv Grewal, Dennis Herhausen, Stephan Ludwig, Francisco Villarroel Ordenes
Summary: This article discusses the impact of digital communication on consumers and markets, and explores new trends and future opportunities in digital communication research. The article emphasizes the importance of understanding the properties of communication dynamics and communication multimodality in predicting consumer behavior and market developments. It also identifies the challenges and research agenda in studying these areas.
JOURNAL OF RETAILING
(2022)
Article
Business
Luigi M. De Luca, Dennis Herhausen, Gabriele Troilo, Andrea Rossi
Summary: Big data technologies and analytics have the potential to offer new digital services and lead to superior performance, but many firms fail to effectively leverage their investments in big data. Researchers have developed a framework based on affordance theory to analyze the impact of big data investments on service innovation and performance, focusing on customer behavior pattern spotting, real-time market responsiveness, and data-driven market ambidexterity. The empirical analysis validates the constructs and examines the direct, indirect, and conditional effects of big data marketing affordances on perceived big data performance.
JOURNAL OF THE ACADEMY OF MARKETING SCIENCE
(2021)
Article
Business
Dennis Herhausen, Robert E. Morgan, Danilo Brozovi, Henk W. Volberda
Summary: The study conducted a meta-analysis on the enablers, inhibitors, and triggers of strategic flexibility, revealing a significant performance effect. It was found that the measurement of SF and certain dimensions of the environment moderate the performance effect, and that innovation outcomes and market outcomes mediate the relationship between SF and financial performance.
BRITISH JOURNAL OF MANAGEMENT
(2021)
Article
Business
Dennis Herhausen, Sven Henkel, Petra Kipfelsberger
BRQ-BUSINESS RESEARCH QUARTERLY
(2020)
Article
Business
Dennis Herhausen, Dario Miocevic, Robert E. Morgan, Mirella H. P. Kleijnen
INDUSTRIAL MARKETING MANAGEMENT
(2020)
Article
Business
Dennis Herhausen, Oliver Emrich, Dhruv Grewal, Petra Kipfelsberger, Marcus Schoegel
JOURNAL OF MARKETING RESEARCH
(2020)
Article
Business
Robert E. Morgan, Dario Miocevic, Dennis Herhausen
INDUSTRIAL MARKETING MANAGEMENT
(2019)
Article
Psychology, Applied
Petra Kipfelsberger, Heike Bruch, Dennis Herhausen
GROUP & ORGANIZATION MANAGEMENT
(2019)
Article
Business
Dennis Herhausen, Stephan Ludwig, Dhruv Grewal, Jochen Wulf, Marcus Schoegel
JOURNAL OF MARKETING
(2019)
Article
Business
Sylvie Chetty, Oscar Martin Martin, Wensong Bai
Summary: Foreign market selection and entry are important decisions for internationalizing SMEs as they involve uncertainty and influence performance. This study contributes to the field by proposing a model that explains SMEs' international performance through causal and effectual logic, as well as business network theory.
JOURNAL OF BUSINESS RESEARCH
(2024)
Article
Business
Yaming Wang, Xingyuan Wang, Haipeng (Allan) Chen, Qiang Ouyang
Summary: Negative psychological experiences, such as exposure to a status threat, can significantly influence consumers' behavior. Previous studies have shown that consumers often choose to cope with a status threat by purchasing status-related or hedonic products, but this research suggests that consumers who perceive the threat as controllable are more likely to prefer self-improvement products within their own domain. Furthermore, trade-off beliefs play a moderating role in the relationship between status threat and perceived loss of control, which subsequently predicts consumers' preference for self-improvement products across different domains.
JOURNAL OF BUSINESS RESEARCH
(2024)
Article
Business
Maud Pindard-Lejarraga, Jose Lejarraga
Summary: The information source used by nascent entrepreneurs affects their performance expectations. Experience-based information leads to lower expectations of success, while descriptive information leads to higher expectations. These effects are influenced by industry conditions.
JOURNAL OF BUSINESS RESEARCH
(2024)
Article
Business
George Kuk, Mario Schaarschmidt, Dirk Homscheid
Summary: Much research on open source software development has tended to overlook the behavioral differences between various developer groups. This study expands upon the private-collective innovation model using a networking approach and reveals the influence of network closure and positional embeddedness on technical contribution. The empirical findings show that network closure has a negative impact on technical contribution, while the relationship between positional embeddedness and technical contribution follows an inverted U-shape. Moreover, high positional embeddedness can counteract the negative influence of extensive network closure on technical contribution. These effects are moderated by different developer groups.
JOURNAL OF BUSINESS RESEARCH
(2024)
Review
Business
Jie Wu, Narisa Zhao, Tong Yang
Summary: This article introduces an innovative method for conducting SWOT analysis using online reviews. Overcoming the subjectivity and limitations of traditional SWOT analysis, this method effectively addresses the dynamic business environment and helps managers develop preventive strategies.
JOURNAL OF BUSINESS RESEARCH
(2024)
Article
Business
Karin Sanders, Phong T. Nguyen, Dave Bouckenooghe, Alannah E. Rafferty, Gavin Schwarz
Summary: During times of crisis, employees look to their managers for information and guidance. Sharing distinctive, consistent, and consensual information, also known as human resource management (HRM) system strength, makes it easier for employees to understand their roles. This study explores the factors that influence managers when sharing information with employees, and suggests that the interaction between managers' motivation and their cultural values can explain HRM system strength in times of crisis. The findings indicate that crisis severity and organization reputation have stronger effects on HRM system strength in countries with high uncertainty avoidance, but weaker effects in countries with high power distance. Implications for theory and practice are discussed.
JOURNAL OF BUSINESS RESEARCH
(2024)
Article
Business
Sumaya Albalooshi, Mehrad Moeini-Jazani
Summary: This study shows that economic inequality increases the preference for personal control appeals in advertising. The effect is observed when economic inequality is objectively measured or experimentally manipulated. The study also identifies financial threat as the mechanism underlying this effect, which reduces consumers' sense of control. Moreover, it is found that a boost in the sense of control or stronger belief in economic mobility can mitigate the psychological threats of higher economic inequality and reduce the preference for personal control appeals.
JOURNAL OF BUSINESS RESEARCH
(2024)
Article
Business
Oihab Allal-Cherif, Jose Manuel Guaita-Martinez, Eduard Montesinos Sansaloni
Summary: This article explores how sustainable esports entrepreneurs in emerging countries manage to build successful businesses and have a positive impact on society. They overcome various challenges such as failing infrastructure, high equipment costs, limited purchasing power, low public and private investment, lack of institutional recognition, and the strong domination of leading countries, by utilizing their knowledge, talents, and innovative processes and technologies, and demonstrating resilience and audacity in adversity.
JOURNAL OF BUSINESS RESEARCH
(2024)
Article
Business
Dasha Antsipava, Joanna Strycharz, Eva A. van Reijmersdal, Guda van Noort
Summary: This study examines the factors that influence the adoption of blockchain technology in the online advertising ecosystem from a multi-stakeholder perspective. The findings reveal that all factors of the Interactive Communication Technology Adoption Model (ICTAM) simultaneously affect blockchain adoption, often in contradictory ways. The study extends the application of the ICTAM to a whole ecosystem perspective and identifies the essential factors for successful blockchain adoption in online advertising. The study concludes that more education about blockchain's potential, favorable regulation, and ready-to-use applications are needed for wide-scale adoption.
JOURNAL OF BUSINESS RESEARCH
(2024)
Article
Business
Nadine Pieper, David M. Woisetschla
Summary: This study examines the use of external regulation and introjected actions to reduce customer misbehavior in access-based mobility services. The results show that these two prevention strategies usually do not provide advantages, and thus, the actions should be carefully selected depending on the service setting.
JOURNAL OF BUSINESS RESEARCH
(2024)
Article
Business
Yi Wu, Yuanyuan Cai, Xiaohan Zhou, Xinyi Huang
Summary: This study proposed a novel sensory marketing strategy using shape cues to influence consumers' reactions to distant brand extensions. The findings suggest that circular shapes lead to more favorable evaluations of distant brand extensions compared to angular shapes, and these effects are mediated by consumers' cognitive flexibility and fit perceptions. The influence of shapes on brand extension evaluation diminishes when a sub-branding strategy is used to introduce the extension product, but is not affected when a direct-branding strategy is used. These results were replicated across different product categories and cultures and have implications for both theory and practice.
JOURNAL OF BUSINESS RESEARCH
(2024)
Article
Business
Elizabeth Napier, Steven Y. H. Liu, Jingting Liu
Summary: Organizational resilience has become a critical concept in today's international business environment. It encompasses multiple levels including individuals, organizations, ecosystems, institutions, and the global level, and is examined through a dynamic process model to help multinational enterprises navigate change, adapt to adversity, and achieve success.
JOURNAL OF BUSINESS RESEARCH
(2024)
Article
Business
Jose Antonio Porfirio, Jose Augusto Felicio, Tiago Carrilho
Summary: This study analyzes the impact of digital transformation on banking performance in Portugal. It identifies the factors and configurations between employees, internal factors, and external factors that influence the impact of digital transformation. The study highlights the importance of flexibility and management capacity in enhancing the impact of digital transformation.
JOURNAL OF BUSINESS RESEARCH
(2024)
Article
Business
Omar Al-Tabbaa, Nadia Zahoor
Summary: By integrating alliance capability and resource-based view, this study examines how SMEs can expand their internationalization through collaboration. The results show that alliance management capability enhances radical and incremental co-innovation in SMEs, leading to their international expansion. Furthermore, the study reveals the moderating effects of alliance partner diversity on the relationship between alliance management capability and co-innovation.
JOURNAL OF BUSINESS RESEARCH
(2024)
Article
Business
P. D. Harms, Joshua V. White, Tyler N. A. Fezzey
Summary: This paper introduces the concept of the emerging entrepreneurial economy and its impact on the understanding of work. It discusses the influence of dark personality traits on interest in new occupations and explores the uncertainty surrounding the functioning of individuals with dark traits in these vocational contexts enhanced by artificial intelligence technology. It proposes improvements for future research in order to achieve a more comprehensive understanding of dark personality in the entrepreneurial economy.
JOURNAL OF BUSINESS RESEARCH
(2024)