Article
Business
Sergey Anokhin, Todd Morgan, William Schulze, Robert Wuebker
Summary: Reputation has a positive impact on a corporate venture capital firm's ability to attract potential investments, with a reputation for experience, active involvement in startups, and misconduct all being factors. However, the influence of reputation also depends on other factors, such as the policy of active engagement with portfolio companies.
JOURNAL OF BUSINESS RESEARCH
(2022)
Article
Business, Finance
Tomonori Manabe, Kei Nakagawa
Summary: This study explores the value of reputation capital in the early stages of the COVID-19 pandemic stock market crash. It found that firms with a positive reputation for the usefulness of their products/services in their business network had higher stock returns compared to firms with a low reputation score, indicating that a positive reputation among stakeholders can act as insurance against shocks in times of crisis. Notably, results suggest that firms that can build public trust due to the usefulness of their products/services are more resilient in the face of crashes caused by real economic damage, such as the COVID-19-related crash.
FINANCE RESEARCH LETTERS
(2022)
Article
Psychology, Multidisciplinary
Silvio Carlo Ripamonti, Laura Galuppo, Sara Petrilli, Angelo Benozzo
Summary: This study investigates how managers perceive the role of intangible assets in organizational change within a trade union context, highlighting the significant role of metaphors in narrating change. The results illustrate the impact of different metaphors on the perception and value attributed to the trade union's intangible assets.
FRONTIERS IN PSYCHOLOGY
(2021)
Article
Business
Xian Gu, Iftekhar Hasan, Haitian Lu
Summary: Using data from China's public debt markets, this study examines the value of corporate reputation and its interaction with legal and cultural forces to ensure accountability. The findings suggest that lawsuits resulting in reputational damage lead to a decrease in bond values and tighter borrowing conditions for the involved firms. Moreover, the effects are more prominent for private firms, firms based in provinces with weaker legal protections, and firms based in provinces with higher social capital. These results imply that reputational penalties serve as substitutes for legal protections and complements cultural forces in promoting accountability and trust-building.
JOURNAL OF BUSINESS ETHICS
(2023)
Article
Management
Mehmet I. Canayaz, Alper Darendeli
Summary: We investigate the relationship between country reputation as an intangible firm asset and corporate sales. By examining variations in nationalities of foreign victims in local terror attacks, we discover unexpected distortions in the reputations of local countries in foreign nations, resulting in reduced sales for local firms in foreign markets. These reductions in sales are economically and statistically significant, persist over time, and are more pronounced after attacks that receive extensive media coverage in foreign countries. Local firms with names resembling their countries of origin experience greater declines in sales. These distortions in country reputations are also associated with depreciations in overall firm value, sales growth, and profitability.
MANAGEMENT SCIENCE
(2023)
Article
Business, Finance
Fangjian Fu, Sheng Huang, Rong Wang
Summary: From 1980 to 2020, capital expenditures of U.S. public firms, relative to total assets, decreased by more than half. This decline is observed across industries and firms of different characteristics, and cannot be explained by traditional determinants of investment or other plausible reasons. The decline is consistent with the shift in production technology towards greater reliance on intangible capital and less on fixed assets. Similar declining trend in capital expenditure is also observed in other developed countries.
JOURNAL OF EMPIRICAL FINANCE
(2022)
Article
Economics
Nene Lartey Addico, Godfred Amewu, Anthony Owusu-Ansah
Summary: This study investigates the investment decision techniques and tools used in practice by listed firms in Ghana. The findings reveal that chief financial officers (CFOs) primarily rely on the payback period as their most used capital budgeting tool, which contrasts with current literature trends. Additionally, the study indicates that CFOs put low or no effort into estimating the cost of equity when calculating the cost of capital, suggesting they may be using the cost of debt instead. This article provides valuable insights for improving firm value maximization in a frontier market.
MANAGERIAL AND DECISION ECONOMICS
(2022)
Article
Information Science & Library Science
Binh Thi Thanh Truong, Phuong Van Nguyen, Demetris Vrontis, Zafar U. Ahmed
Summary: This study explores the relationship between the three components of intellectual capital (human, structural, and relational) and corporate innovation, as well as how effective knowledge management can improve business performance, innovation, and environmental compliance. The study also investigates the impact of environmental compliance on overall business performance. The findings indicate that all three components of intellectual capital have a significant positive effect on business performance. Additionally, corporate innovation, knowledge management success, and environmental compliance all contribute to increased business performance. Moreover, knowledge management success indirectly enhances business performance through innovation and environmental compliance.
JOURNAL OF KNOWLEDGE MANAGEMENT
(2023)
Article
Computer Science, Information Systems
Fairtown Zhou Ayoungman, Liyuan Pang, Yingjing Chu
Summary: This paper investigates the influence of entrepreneurs' geographic and academic relationships on corporate innovation. The study finds that these relationships have a significant positive effect on corporate innovation, especially when entrepreneurs have strong ability endowment. Furthermore, the more prestigious the entrepreneurs' university education is, the stronger their academic relationships promote corporate innovation.
JOURNAL OF ORGANIZATIONAL AND END USER COMPUTING
(2022)
Article
Business, Finance
Lan Wang, Zimo Lang, Jiayin Duan, Hanyu Zhang
Summary: This paper discusses the evolutionary mechanism of corporate technological innovation networks from the perspective of corporate reputation in the field of venture capital investment. It constructs an integrated model for the relationships between heterogeneous venture capital investment, corporate reputation, and technological innovation network evolution. The study finds that independent venture capital is more conducive to enhancing internal corporate reputation and promoting the evolution of technological innovation networks towards being self-centered, while corporate venture capital is more conducive to consolidating external reputation and promoting the evolution of technological innovation networks towards being holistic. Corporate reputation has some mediating effects on the relationship between heterogeneous venture capital and technological innovation network evolution.
FINANCE RESEARCH LETTERS
(2023)
Article
Green & Sustainable Science & Technology
Xin Huang, Xianling Jiang, Wei Liu, Qian Chen
Summary: Business groups play a crucial role in the development of emerging markets, affecting affiliated firms' CSR performance through resource allocation, rent-seeking initiatives, and corporate reputation. Group affiliation benefits a firm's CSR performance in terms of employee's responsibilities, consumer's responsibilities, and environmental responsibilities, but has a lower impact on shareholder's responsibilities.
Article
Business
Ranya Saeed Alhmoudi, Sanjay Kumar Singh, Francesco Caputo, Teresa Riso, Francesca Iandolo
Summary: This paper investigates the influence of corporate social responsibility (CSR) on Innovative Work Behavior (IWB). It explores the mediating role of passion and organizational commitment in understanding the effect of CSR on companies' performances from a behavioral perspective. By conducting an exploratory literature review and using content analysis, the possible relationships among CSR, human capital, relational capital, and innovative work behaviors are explored. The paper provides propositions for enhancing the potential contribution of perceived CSR to improve companies' performance by adopting IWBs, enriching the ongoing debate about CSR's influence on companies' performances.
CORPORATE SOCIAL RESPONSIBILITY AND ENVIRONMENTAL MANAGEMENT
(2022)
Article
Green & Sustainable Science & Technology
Patrocinio Carmen Zaragoza-Saez, Enrique Claver-Cortes, Bartolome Marco-Lajara, Mercedes ubeda-Garcia
Summary: This study aims to analyze the relationship between sustainable intangible capital and performance, and explore the mediating role of corporate social responsibility and strategic knowledge management. The findings suggest that sustainable intangible capital does not directly influence hotel performance, but rather has a significant impact through the mediation of corporate social responsibility and strategic knowledge management.
JOURNAL OF SUSTAINABLE TOURISM
(2023)
Article
Business
Renato Civitillo, Giuseppe Festa, Constantinos-Vasilios Priporas, Matteo Rossi
Summary: The study aims to explore the impact of proactive governance, management, and marketing on the intellectual capital of nonprofit organizations and its relation to corporate reputation. The research findings show that there has been fluctuating interest in this area, with a focus on qualitative analysis of institutional scope, human resources, and operational functioning.
INTERNATIONAL MARKETING REVIEW
(2022)
Article
Business
Marcella Giacomarra, S. M. Riad Shams, Maria Crescimanno, Georgia Sakka, Gian Luca Gregori, Antonino Galati
Summary: This study examines the decision-making factors of an Italian family-owned winery attempting to balance its internal and external R&D teams, using an integrated theoretical framework based on transaction costs and resource-based view theory.
JOURNAL OF BUSINESS RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Jose Ignacio Pelaez, Jose Antonio Gomez-Ruiz, Javier Fornari, Gustavo F. Vaccaro
Article
Green & Sustainable Science & Technology
Francisco E. Cabrera, Manuel Amaya, Gustavo Fabian Vaccaro Witt, Jose Ignacio Pelaez
Article
Multidisciplinary Sciences
David Alaminos, Jose Ignacio Peliez, M. Belen Salas, Manuel A. Fernandez-Gamez
Summary: This article introduces new models for predicting sovereign debt and currency crises using various computational techniques, aiming to increase precision and provide insights from a global sample. The superiority of computational techniques over statistics methods in terms of precision for sovereign debt crises and the best methods for forecasting currency crises are discussed, with potential significant impacts on countries' macroeconomic policies.
Article
Neurosciences
Pablo Sanchez-Nunez, Manuel J. Cobo, Gustavo Vaccaro, Jose Ignacio Pelaez, Enrique Herrera-Viedma
Summary: This study aims to identify highly cited papers in the field of neuromarketing, consumer neuroscience, and neuroaesthetics, summarize academic work produced in the last decade, and show patterns, features, and trends that define the past, present, and future of this knowledge area. Through analyzing 50 HCPs, we can gain insights into the key contributors to the development of this field, including authors, institutions, sources, countries, documents, and references. The use of H-Classics methodology and Bibliometrix R Package and SciMAT software provides an objective method to identify core knowledge in neuroscience disciplines.
Article
Chemistry, Analytical
Francisco E. Cabrera, Pablo Sanchez-Nunez, Gustavo Vaccaro, Jose Ignacio Pelaez, Javier Escudero
Summary: This study explored the impact of visual design elements and principles (VDEPs) on brain activity by analyzing EEG signals of 32 participants watching music videos. Results demonstrated that changes in light/value, rhythm/movement, and balance significantly affected EEG band power, while a Convolutional Neural Network accurately predicted VDEPs of video fragments based on viewer EEG signals.
Article
Hospitality, Leisure, Sport & Tourism
Pilar Alarcon-Urbistondo, Maria-Mercedes Rojas-de-Gracia, Ana Casado-Molina
Summary: This study proposes a method to measure tourism destination image using user-generated content (UGC) on the internet and confirms the validity of UGC as a data source. The results also indicate that not all attributes influence the overall impression of a destination.
JOURNAL OF HOSPITALITY & TOURISM RESEARCH
(2023)
Article
Business
Ana Maria Casado-Molina, Maria Mercedes Rojas-de Gracia, Pilar Alarcon-Urbistondo, Maria Romero-Charneco
Summary: This study demonstrates the significance of emojis in brand communications and their relationship with user engagement. It provides practical implications for businesses in terms of how to effectively use emojis in their communication strategies.
INTERNATIONAL JOURNAL OF BUSINESS COMMUNICATION
(2022)
Article
Social Issues
Maria-Mercedes Rojas-de-Gracia, Ana-Maria Casado-Molina, Pilar Alarcon-Urbistondo
Summary: This study demonstrates the significant impact of a company's integrity of governance on the formation of its corporate reputation, which in turn affects share price variations.
TECHNOLOGY IN SOCIETY
(2021)
Article
Business
Celia M. Q. Ramos, Ana-Maria Casado-Molina
Summary: Managing online corporate reputation is strategically important for improving a company's economic performance. By collecting, processing, and analyzing online comments, intangible assets can be evaluated for their impact on tangible assets, with findings showing that ethical experience has the greatest impact on economic performance in the banking sector.
JOURNAL OF BUSINESS RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Gustavo Vaccaro, Francisco E. Cabrera, Jose Ignacio Pelaez, L. G. Vargas
APPLIED SOFT COMPUTING
(2020)
Article
Computer Science, Information Systems
Pablo Sanchez-Nunez, Manuel J. Cobo, Carlos De las Heras-Pedrosa, Jose Ignacio Pelaez, Enrique Herrera-Viedma
Article
Multidisciplinary Sciences
Maria-Mercedes Rojas-de-Gracia, Pilar Alarcon-Urbistondo, Ana-Maria Casado-Molina
Article
Hospitality, Leisure, Sport & Tourism
Maria-Mercedes Rojas-de-Gracia, Pilar Alarcon-Urbistondo, Ana-Maria Casado-Molina
JOURNAL OF DESTINATION MARKETING & MANAGEMENT
(2019)
Article
Social Sciences, Interdisciplinary
Noudehouenou Lionel Jaderne Houssou, Juan Durango Cordero, Audren Bouadjio-Boulic, Lucie Morin, Nicolas Maestripieri, Sylvain Ferrant, Mahamadou Belem, Jose Ignacio Pelaez, Melio Saenz, Emilie Lerigoleur, Arnaud Elger, Benoit Gaudou, Laurence Maurice, Mehdi Sagalli
JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION
(2019)
Article
Social Sciences, Interdisciplinary
Pablo Sanchez-Nunez, Carlos de las Heras-Pedrosa, Jose Ignacio Pelaez
SOCIAL SCIENCES-BASEL
(2020)
Review
Computer Science, Artificial Intelligence
Wei Gao, Shuangshuang Ge
Summary: This study provides a comprehensive review of slope stability research based on artificial intelligence methods, focusing on slope stability computation and evaluation. The review covers studies using quasi-physical intelligence methods, simulated evolutionary methods, swarm intelligence methods, hybrid intelligence methods, artificial neural network methods, vector machine methods, and other intelligence methods. The merits, demerits, and state-of-the-art research advancement of these studies are analyzed, and possible research directions for slope stability investigation based on artificial intelligence methods are suggested.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Khuong Le Nguyen, Hoa Thi Trinh, Saeed Banihashemi, Thong M. Pham
Summary: This study investigated the influence of input parameters on the shear strength of RC squat walls and found that ensemble learning models, particularly XGBoost, can effectively predict the shear strength. The axial load had a greater influence than reinforcement ratio, and longitudinal reinforcement had a more significant impact compared to horizontal and vertical reinforcement. The performance of XGBoost model outperforms traditional design models and reducing input features still yields reliable predictions.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Bo Hu, Huiyan Zhang, Xiaoyi Wang, Li Wang, Jiping Xu, Qian Sun, Zhiyao Zhao, Lei Zhang
Summary: A deep hierarchical echo state network (DHESN) is proposed to address the limitations of shallow coupled structures. By using transfer entropy, candidate variables with strong causal relationships are selected and a hierarchical reservoir structure is established to improve prediction accuracy. Simulation results demonstrate that DHESN performs well in predicting algal bloom.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Limin Wang, Lingling Li, Qilong Li, Kuo Li
Summary: This paper discusses the urgency of learning complex multivariate probability distributions due to the increase in data variability and quantity. It introduces a highly scalable classifier called TAN, which utilizes maximum weighted spanning tree (MWST) for graphical modeling. The paper theoretically proves the feasibility of extending one-dependence MWST to model high-dependence relationships and proposes a heuristic search strategy to improve the fitness of the extended topology to data. Experimental results demonstrate that this algorithm achieves a good bias-variance tradeoff and competitive classification performance compared to other high-dependence or ensemble learning algorithms.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Zhejing Hu, Gong Chen, Yan Liu, Xiao Ma, Nianhong Guan, Xiaoying Wang
Summary: Anxiety is a prevalent issue and music therapy has been found effective in reducing anxiety. To meet the diverse needs of individuals, a novel model called the spatio-temporal therapeutic music transfer model (StTMTM) is proposed.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Nur Ezlin Zamri, Mohd. Asyraf Mansor, Mohd Shareduwan Mohd Kasihmuddin, Siti Syatirah Sidik, Alyaa Alway, Nurul Atiqah Romli, Yueling Guo, Siti Zulaikha Mohd Jamaludin
Summary: In this study, a hybrid logic mining model was proposed by combining the logic mining approach with the Modified Niche Genetic Algorithm. This model improves the generalizability and storage capacity of the retrieved induced logic. Various modifications were made to address other issues. Experimental results demonstrate that the proposed model outperforms baseline methods in terms of accuracy, precision, specificity, and correlation coefficient.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
David Jacob Kedziora, Tien-Dung Nguyen, Katarzyna Musial, Bogdan Gabrys
Summary: The paper addresses the problem of efficiently optimizing machine learning solutions by reducing the configuration space of ML pipelines and leveraging historical performance. The experiments conducted show that opportunistic/systematic meta-knowledge can improve ML outcomes, and configuration-space culling is optimal when balanced. The utility and impact of meta-knowledge depend on various factors and are crucial for generating informative meta-knowledge bases.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
G. Sophia Jasmine, Rajasekaran Stanislaus, N. Manoj Kumar, Thangamuthu Logeswaran
Summary: In the context of a rapidly expanding electric vehicle market, this research investigates the ideal locations for EV charging stations and capacitors in power grids to enhance voltage stability and reduce power losses. A hybrid approach combining the Fire Hawk Optimizer and Spiking Neural Network is proposed, which shows promising results in improving system performance. The optimization approach has the potential to enhance the stability and efficiency of electric grids.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Zhijiang Wu, Guofeng Ma
Summary: This study proposes a natural language processing-based framework for requirement retrieval and document association, which can help to mine and retrieve documents related to project managers' requirements. The framework analyzes the ontology relevance and emotional preference of requirements. The results show that the framework performs well in terms of iterations and threshold, and there is a significant matching between the retrieved documents and the requirements, which has significant managerial implications for construction safety management.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Yung-Kuan Chan, Chuen-Horng Lin, Yuan-Rong Ben, Ching-Lin Wang, Shu-Chun Yang, Meng-Hsiun Tsai, Shyr-Shen Yu
Summary: This study proposes a novel method for dog identification using nose-print recognition, which can be applied to controlling stray dogs, locating lost pets, and pet insurance verification. The method achieves high recognition accuracy through two-stage segmentation and feature extraction using a genetic algorithm.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Shaohua Song, Elena Tappia, Guang Song, Xianliang Shi, T. C. E. Cheng
Summary: This study aims to optimize supplier selection and demand allocation decisions for omni-channel retailers in order to achieve supply chain resilience. It proposes a two-phase approach that takes into account various factors such as supplier evaluation and demand allocation.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Jinyan Hu, Yanping Jiang
Summary: This paper examines the allocation problem of shared parking spaces considering parking unpunctuality and no-shows. It proposes an effective approach using sample average approximation (SAA) combined with an accelerating Benders decomposition (ABD) algorithm to solve the problem. The numerical experiments demonstrate the significance of supply-demand balance for the operation and user satisfaction of the shared parking system.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Review
Computer Science, Artificial Intelligence
Soroor Motie, Bijan Raahemi
Summary: Financial fraud is a persistent problem in the finance industry, but Graph Neural Networks (GNNs) have emerged as a powerful tool for detecting fraudulent activities. This systematic review provides a comprehensive overview of the current state-of-the-art technologies in using GNNs for financial fraud detection, identifies gaps and limitations in existing research, and suggests potential directions for future research.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Review
Computer Science, Artificial Intelligence
Enhao Ning, Changshuo Wang, Huang Zhang, Xin Ning, Prayag Tiwari
Summary: This review provides a detailed overview of occluded person re-identification methods and conducts a systematic analysis and comparison of existing deep learning-based approaches. It offers important theoretical and practical references for future research in the field.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Jiajun Ma, Songyu Hu, Jianzhong Fu, Gui Chen
Summary: The article presents a novel visual hierarchical attention detector for multi-scale defect location and classification, utilizing texture, semantic, and instance features of defects through a hierarchical attention mechanism, achieving multi-scale defect detection in bearing images with complex backgrounds.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
