Articles publicats en revistes (Empresa)

URI permanent per a aquesta col·leccióhttps://hdl.handle.net/2445/21571

Estadístiques

Examinar

Mostrant 1 - 20 de 564

Quantum kernel methodsfor marketing analytics withconvergence theory and separationbounds
(Nature Publishing Group, 2026-02-17) Sáez Ortuño, Laura; Forgas Coll, Santiago; Ferrara, Massimiliano
This work studies the feasibility of applying quantum kernel methods to a real consumer classification task in the NISQ regime. We present a hybrid pipeline that combines a quantum-kernel Support Vector Machine (Q-SVM) with a quantum feature extraction module (QFE), and benchmark it against classical and quantum baselines in simulation (hardware validation remains future work). Hyperparameters were selected via nested cross-validation on the training partition and then fixed for test evaluation; under these settings, the proposed Q-SVM attains 0.7790 accuracy, 0.7647 precision, 0.8609 recall, 0.8100 F1, and 0.83 ROC AUC, exhibiting higher sensitivity while maintaining competitive precision relative to classical SVM. All headline metrics are obtained via high-fidelity simulation. We interpret these results as an initial indicator and a concrete starting point for NISQ-era workflows and hardware integration, rather than a definitive benchmark. Methodologically, our design aligns with recent work that formalizes quantum–classical separations and verifies resources via XEB-style (Cross-Entropy Benchmarking) approaches, motivating shallow yet expressive quantum embeddings to achieve robust separability despite hardware noise constraints.
From urban transport model diversity to user preferences: A multilayer perceptron prediction
(Springer Verlag, 2025-12-17) Guillén Pujadas, Miguel; Lima Rua, Orlando; Alaminos Aguilera, David; Vizuete Luciano, Emilio
The research addresses the complexity of urban mobility, highlighting the need to select the appropriate transport model under the user’s perception and under the sustainable development of modern cities. Achieving equitable, efficient, and environmentally responsible mobility systems necessitates collaboration among public and private sectors, complemented by active societal participation. Utilizing a dataset of 593 survey responses, a Multilayer Perceptron neural network was implemented to predict individual mobility preferences by integrating behavioral, demographic, and infrastructural determinants, including age, gender, occupation, car ownership, and Taxi/VTC usage frequency. Three primary mobility types were identified: public, shared, and private transport. The results indicate that car ownership and Taxi/VTC use are the most significant positive predictors of private mobility, whereas younger respondents exhibit a higher probability of adopting shared transport options. Methodologically, the application of neural network modeling enables the detection of nonlinear interactions and latent behavioral patterns often overlooked by conventional statistical approaches, thereby enhancing predictive precision and interpretability. These findings underscore the complex, multidimensional nature of mobility decision-making and highlight the utility of artificial intelligence techniques in advancing the analysis of travel behavior. The study’s implications extend to the formulation of inclusive, data-driven transport policies aimed at improving equity, accessibility, and sustainability in urban mobility systems, reinforcing the relevance of machine learning as a tool for evidence-based urban planning and policy development.
Tech startups and general data protection regulation: an empirical exploration of compliance challenges
(Emerald Publishing, 2025-12-01) Smirnova, Yelena; Travieso-Morales, Victoriano
Purpose – This study investigates specific challenges that tech startups in Catalonia face in complying with the General Data Protection Regulation (GDPR) from the perspective of Technology-Organization-Environment (TOE) framework. It also examines how factors such as startup’s size, age, and sector influence compliance experiences. Design/methodology/approach – A mixed-methods approach was employed, combining survey data from 107 Catalonian tech startups with in-depth interviews with senior executives from three startups to provide qualitative insightsfor triangulation. GDPR compliance challenges were analysed using regression analysis and One-Way ANOVA. Findings – The results of the study underscore the interconnected nature of GDPR compliance challenges, revealing that staff training mediates the relationship between regulatory and technical complexities and compliance costs. While compliance costs, regulatory complexity, and technical complexity are viewed as significant challenges of equal importance, staff training is not considered a primary concern for Catalonian startups. Additionally,factorssuch asthe startup’ssize, age, and sectorsignificantly influence how these challenges are perceived and addressed, with smaller, younger, and non-tech startups experiencing greater difficulties. Research limitations/implications – Relatively smallsample size and geographic focus on Catalonia potentially limit generalizability of the findings. Practical implications – The findings have implications for startups, policymakers, and industry regulators, emphasizing the need for simplified regulatory guidance, accessible technical support, and tailored compliance training programs for startups. Originality/value – This study fills a literature gap by applying the TOE framework to explore regulatory adoption challenges by tech startups. It reveals how staff training mediatesthe effect of regulatory and technical complexities on compliance costs highlighting the role of organizational capabilities in regulatory adoption.
Generative AI as a tool for bank valuation analysis
(Elsevier, 2026-03) Alaminos Aguilera, David; Guillén Pujadas, Miguel
This study examines the potential of generative AI, specifically ChatGPT, in bank valuation using established financial models such as the Dividend Discount Model, Free Cash Flow to Equity, Excess Return, and Relative Valuation techniques. Through a four-stage evaluation, ChatGPT's performance is compared to human-driven analysis, highlighting its ability to process complex data, apply structured frameworks, and integrate nuanced assumptions. Results show high accuracy for large banks, with minimal deviations when explicit formulas and assumptions are included, though challenges persist for smaller banks and complex models. The findings demonstrate ChatGPT's potential as a complementary tool for financial analysts, capable of automating routine valuation tasks and improving efficiency. Its adaptability to established frameworks underscores its value in financial modeling and decision-making. This study provides practical findings into integrating AI in finance while identifying opportunities for further research, including hybrid human-AI approaches, diverse datasets, and ethical considerations in AI-driven financial analysis.
Ordered Weighted Average Operators Into Deep Learning and Quantum Computing for Algorithmic Trading
(John Wiley & Sons, 2026-01) Alaminos Aguilera, David; Salas Compas, M. Belén; Cisneros Ruiz, Ana J.
Crypto-assets have experienced significant growth in recent years, attracting substantial investments from institutional entities and individual investors alike. This surge in popularity necessitates sophisticated strategies to optimize returns. Concurrently, advancements in machine learning have revolutionized the forecasting of crypto-asset returns, facilitating algorithmic trading. Leveraging robust algorithms, this approach enables comprehensive market exploration and capitalizes on escalating computational capabilities. This manuscript presents a comparative analysis of neural networks, genetic algorithms, and fuzzy logic, framed within the Ordered Weighted Average (OWA) operator paradigm. These methods are integrated with deep learning and quantum computing principles to predict price movements in crypto-assets and other financial indices. Our findings indicate that the Quantum Genetic Algorithm excels in accurately forecasting asset price trends, while the Quantum Fuzzy Approach exhibits comparatively lower precision in predicting cryptocurrency price fluctuations. The empirical analysis employs high-frequency data sampled at 10-, 30-, and 60-minute intervals from October 2021 to February 2023. The dataset encompasses eleven cryptocurrencies (e.g., Bitcoin, Ethereum), ten Fan Tokens, ten NFTs, and nine reference financial indices (including Gold, WTI Oil, S&P 500, and Euro Stoxx 60). The implications of this research extend to the development of advanced algorithmic trading strategies, offering valuable tools for market participants and stakeholders in the financial sector. The methodologies discussed herein provide versatile and quantitative frameworks for analyzing diverse financial markets, highlighting their potential to enhance decision-making and improve investment outcomes.
La personalidad encuentra la satisfacción: Un Viaje hacia el impacto de los rasgos del personal hotelero en las experiencias de los huéspedes
(Universitat d'Alacant, 2026-01-07) Louzao, Nuria; Heras Gil, Claudia; Crespi Vallbona, Montserrat; Mendoza, Neus
Even though Hospitality and Psychology are closely related fields, the in-depth exploration of their shared relationship remains limited. This research explores the correlation between employee personality traits and their impact on service quality during the arrival process at a four-star hotel in Barcelona. The combination of a psychological model and a perceived quality model makes the research original in its approach. Based on a dual-perspective methodology rooted in both Hospitality and Psychology, the study leverages the Five Factor Inventory, known as The Big Five, to assess the personality traits of receptionists. Guest satisfaction is evaluated using the SERVQUAL model. Primary data was collected through a survey administered to the entire reception staff and customers (247 valid responses), complemented by a semi-structured interview with a psychology expert in order to gain deeper insights into personality dynamics. The findings offer significant managerial implications, providing a scalable model applicable to various departments and processes. Furthermore, the methodology is presented step-by-step so as to facilitate the replication of the model in any type of accommodation establishment.
Rising Bubbles by Margin Calls
(Elsevier, 2025-03-01) Alaminos Aguilera, David
This paper examines price bubble formation in commodity markets driven by margin calls, highlighting mechanisms causing extreme price volatility. Analyzing Nickel, WTI Oil, Silver, Copper, Wheat, Corn, and Soybean, I test five hypotheses on leverage, liquidity reduction, and positive feedback loops using advanced detection methods like LPPLS and GSADF. Results show high leverage and margin calls amplify volatility through forced trades and speculation. Asymmetrical reactions and herding behavior further exacerbate bubbles, particularly under supply constraints. My findings stress the need for improved risk management and regulatory measures to curb leverage-driven volatility, enhancing market stability and resilience.
Hybrid genetic algorithms in agent-based artificial market model for simulating fan tokens trading
(Elsevier Ltd., 2024-01-04) Alaminos Aguilera, David; Salas Compas, M. Belén; Fernández Gámez, Manuel Á.
In recent years cryptographic tokens have gained popularity as they can be used as a form of emerging alternative financing and as a means of building platforms. The token markets innovate quickly through technology and decentralization, and they are constantly changing, and they have a high risk. Negotiation strategies must therefore be suited to these new circumstances. The genetic algorithm offers a very appropriate approach to resolving these complex issues. However, very little is known about genetic algorithm methods in cryptographic tokens. Accordingly, this paper presents a case study of the simulation of Fan Tokens trading by implementing selected best trading rule sets by a genetic algorithm that simulates a negotiation system through the Monte Carlo method. We have applied Adaptive Boosting and Genetic Algorithms, Deep Learning Neural Network-Genetic Algorithms, Adaptive Genetic Algorithms with Fuzzy Logic, and Quantum Genetic Algorithm techniques. The period selected is from December 1, 2021 to August 25, 2022, and we have used data from the Fan Tokens of Paris Saint-Germain, Manchester City, and Barcelona, leaders in the market. Our results conclude that the Hybrid and Quantum Genetic algorithm display a good execution during the training and testing period. Our study has a major impact on the current decentralized markets and future business opportunities.
Financial services support for entrepreneurial projects: Key issues in the business angels investment decision process
(Taylor & Francis, 2013) Argerich, Jaume; Hormiga Pérez, Esther; Valls Pasola, Jaume
The objective of this paper is to provide knowledge about the determinants of success in the screening phase of the investment process and to demonstrate its relationship with success in obtaining capital from business angels (BA). This research sets out to achieve this objective by analyzing the impact that the evaluation of the business opportunity, the managing team and the presentation have on success in the screening phase. To do this, the research proposes four main hypotheses that are tested on 215 projects presented at a BA’s network. The data for the analysis are extracted both from the BA and from the entrepreneurs. The results show that the evaluation of the presentation is the most important factor that influences success in the screening phase, followed by the evaluation of the business opportunity.
The impact of relational capital on the success of new business start-ups
(Wiley, 2011-09-28) Hormiga Pérez, Esther; Batista Canino, Rosa M.; Sánchez Medina, Agustín
This study seeks to highlight the key role played by relational capital in new business start-ups. Following a review of previous research examining the success factors of new ventures and the role played by intellectual capital, our study sets out to achieve this objective by analyzing the impact of a set of intangible relational assets on the initial success of new business start-ups. Based on a study of 130 firms, we analyzed six hypotheses regarding the possible positive relationship between the relational capital of a start-up company and its success in its first few years of business.
The role of intellectual capital in the success of new ventures
(Springer Verlag, 2011) Hormiga Pérez, Esther; Batista Canino, Rosa M.; Sánchez Medina, Agustín
Identifying the factors that contribute to the success of new ventures is a difficult and challenging task. In that respect, this paper proposes an analysis of the intellectual capital within new business ventures. Based on the study of a sample of 130 new companies, for the purpose of this work we have analysed the influence of the proposed intangible assets on the success of newly-created organizations, acknowledging the key role of the human and relational capital in the first few years of the life of the business.
Understanding challenges of GDPR implementation in business enterprises: a systematic literature review.
(Emerald Publishing, 2024-01-18) Smirnova, Yelena; Travieso-Morales, Victoriano
Purpose The general data protection regulation (GDPR) was designed to address privacy challenges posed by globalisation and rapid technological advancements; however, its implementation has also introduced new hurdles for companies. This study aims to analyse and synthesise the existing literature that focuses on challenges of GDPR implementation in business enterprises, while also outlining the directions for future research. Design/methodology/approach The methodology of this review follows the preferred reporting items for systematic reviews and meta-analysis guidelines. It uses an extensive search strategy across Scopus and Web of Science databases, rigorously applying inclusion and exclusion criteria, yielding a detailed analysis of 16 selected studies that concentrate on GDPR implementation challenges in business organisations. Findings The findings indicate a predominant use of conceptual study methodologies in prior research, often limited to specific countries and technology-driven sectors. There is also an inclination towards exploring GDPR challenges within small and medium enterprises, while larger enterprises remain comparatively unexplored. Additionally, further investigation is needed to understand the implications of emerging technologies on GDPR compliance. Research limitations/implications This study’s limitations include reliance of the search strategy on two databases, potential exclusion of relevant research, limited existing literature on GDPR implementation challenges in business context and possible influence of diverse methodologies and contexts of previous studies on generalisability of the findings. Originality/value The originality of this review lies in its exclusive focus on analysing GDPR implementation challenges within the business context, coupled with a fresh categorisation of these challenges into technical, legal, organisational, and regulatory dimensions.
The Scandinavian Journal of Economics at 125: a bibliometric overview
(Wiley, 2024-12-17) Figuerola Wischke, Anton; Gil Lafuente, Anna Maria; Merigó Lindahl, José M.; Kydland, Finn E.; Amiguet, Lluís
Established in 1899 by David Davidson, The Scandinavian Journal of Economics is one of the most respected journals in the field of economics. In 2024, the journal celebrates its 125th anniversary. To commemorate this exceptional event, this study presents a comprehensive bibliometric analysis of the publications of the journal. The objective is to identify the leading trends that have occurred in the journal, especially during the last decades. The bibliographic data are retrieved from the Web of Science Core Collection and Scopus databases. The work also uses the VOSviewer and Biblioshiny software tools to construct and visualize bibliometric maps. The results reveal that authors affiliated with Scandinavian institutions are the most productive in the journal, along with those from the United States, the United Kingdom, and Germany. The keyword and topical analysis shows that The Scandinavian Journal of Economics covers a wide range of topics within economics, publishing frequently on labour, monetary, public, and international economics.
100 volumes of Mathematical Methods of Operations Research: a bibliometric overview
(Springer Verlag, 2024-12-01) Barcellos de Paula, Luciano; Merigó Lindahl, José M.; Gil Lafuente, Anna Maria
The Mathematical Methods of Operations Research is a scholarly journal that publishes high-quality contributions related to mathematics, statistics, and computer science, focusing specifically on operations research. It was established in 1956 and will reach Volume 100 in 2024. To mark this significant milestone, this study aims to identify and elucidate the main patterns in the journal's publication and citation structure, highly cited documents, prolific authors, universities and countries, and popular keywords and topics. To achieve this, all publications from 1956 to 2023 were collected from the Scopus database and Web of Science (WoS) Core Collection from 1997 to 2023, and their bibliographic information was analysed using various bibliometric indicators. Additionally, the study creates a visual representation of the bibliographic data using the Visualization of Similarities (VOS) viewer software. This approach encompasses different bibliometric techniques, such as bibliographic coupling, co-citation, and co-occurrence of keywords. The findings reveal a significant growth in the journal over the past few years and its international presence with contributions from various parts of the world. The most productive researchers are based in Germany and Netherlands, experiencing a substantial increase in output over the last two decades.
30 years of the European Research on Management and Business Economics: A bibliometric retrospective
(Elsevier España, 2025-12-01) Rey-Ortiz, Pedro P.; Crespo-Velando, Miguel A.; Merigó, José M.; Gil Lafuente, Anna Maria
The European Research on Management and Business Economics is a well-established journal in the fields of management, business, and economics. Founded 30 years ago in Spain under the name Investigaciones Europeas de Dirección y Economía de la Empresa, the journal initially published in Spanish. Since 2015, it shifted to English-language publications and has experienced a significant increase in visibility, citation impact, and international reach. This study presents a comprehensive bibliometric analysis of the publications of the journal from 1995 to 2024, using data from the Scopus and Web of Science databases. The analysis is complemented by the use of VOSviewer and Bibliometrix software to map research trends, co-citation networks, and keyword patterns. Findings indicate that the journal is currently undergoing a phase of international growth and consolidation. The most productive and influential research topics include entrepreneurship, corporate social responsibility, strategic management, tourism, and customer behaviour. Moreover, the results also highlight the increasing importance of contributions from Asian and Latin American countries.
From Collaboration to Capability: The Role of NGO Partnerships in Enhancing Operational Environmental Management
(Elsevier, 2025-10-11) Gandra de Carvalho, Ana Catarina; Cassânego, Vitor Melão; Moralles, Herick Fernando; Nascimento, Daniel Luiz de Mattos
This study examines how partnerships between corporations and non-governmental organizations (NGOs) are related to the development of internal environmental capabilities, with a specific focus on the effectiveness of Environmental Management Teams (EMTs). Drawing on the Dynamic Capabilities (DC) framework, we conceptualize NGO collaborations as strategic resources that enable firms to sense, seize, and transform environmental opportunities at the operational level. Using a unique dataset of over 25,000 firm-year observations across multiple countries and industries, we employ a series of econometric models, including Ordinary Least Squares (OLS), Feasible Generalized Least Squares (FGLS), hierarchical linear modeling (HLM), Propensity Score Matching (PSM), and Inverse Probability Weighting (IPW), to assess the robustness of the relationship. The results consistently show that NGO partnerships are positively and significantly associated with higher EMT scores. Furthermore, internal leadership variables such as executive ESG participation and board size are identified as essential enablers of this relationship. These findings contribute to the literature on stakeholder engagement and environmental strategy by demonstrating how external collaborations can activate internal learning mechanisms and foster the development of dynamic capabilities. The study also offers managerial insights by identifying structural conditions under which NGO partnerships are most likely to support operational environmental improvements.
Exploring the Impact of Industry 4.0 Information Technologies on Supply Chain Responsiveness: A Dynamic Capabilities Theory Perspective
(Institute of Electrical and Electronics Engineers (IEEE), 2025-11-20) Iglesias-Pardo, Andrea Patricia; Moyano-Fuentes, José; Maqueira Marín, Juan Manuel; Nascimento, Daniel Luiz de Mattos
This study presents a comprehensive review of the current literature on supply chain (SC) responsiveness capabilities enabled by Industry 4.0 (I4.0) technologies, focusing on flexibility and agility as core dimensions. A systematic literature review was conducted using the Web of Science and Scopus databases, identifying 237 studies that addressed SC flexibility and 206 that addressed agility. The findings reveal distinct interrelationships between specific I4.0 technologies and SC responsiveness capabilities, highlighting the need for an integrated perspective beyond isolated technological applications. Drawing on dynamic capabilities theory, this work proposes a novel conceptual framework that systematically maps enabling I4.0 technologies to the sensing, seizing, and transforming processes underpinning SC agility and flexibility. In doing so, the study identifies critical research gaps and offers a structured foundation for future empirical and theoretical developments. The proposed framework enhances understanding of the synergistic potential of I4.0 technologies and supports strategic decision-making in SC digital transformation.
Supply Chain Sustainability Performance in the Manufacturing Sector of a Developing Economy
(Wiley, 2026-01) Alsmairat, Mohammad A. K.; Al-Chami, Riad; Garza-Reyes, Jose Arturo; Nascimento, Daniel Luiz de Mattos
To assess supply chain (SC) sustainability performance, it is essential to understand the influence of key enablers. This study examines the impact of legal pressure, competitive pressure, internal resources and customer preferences on SC sustainability performance, with a particular focus on the mediating role of strategic direction. A quantitative survey was conducted with 390 operations managers from manufacturing sectors across Qatar, Saudi Arabia, the United Arab Emirates, Oman and Jordan. The data were analysed using partial least squares structural equation modelling (PLS-SEM). The results indicate that competitive pressure, internal resources and customer preferences significantly influence strategic direction, which in turn positively mediates their effect on sustainable supply chain (SSCM) performance. Legal pressure, however, was not found to significantly impact strategic direction, suggesting that regulatory mandates exert limited influence on manufacturing firms in the region. This study provides actionable insights for managers in developing strategic initiatives that enhance sustainability performance, particularly in contexts with constrained resources.
Analysing Credibility of Femvertising Campaigns: A Focus on Colombian Female Athletes
(SAGE Publications) Sánchez Torres, Javier Alirio; López Correa, Carolina; Arroyo Cañada, Francisco Javier; Argila Irurita, Ana María; Vila Márquez, Fátima
Advertising campaigns featuring female athletes have gained significant importance given the positive implications of gender equality, female empowerment and modern social dynamics, in which women play a crucial role, especially in Western societies. However, advertising campaigns in which female athletes are visible can be perceived by the public as false, sometimes known as woman-washing. This study explores the perception of woman-washing in femvertising-type campaigns—that is, those focused on female athletes. An empirical model is proposed and tested with partial least squares structural equation modelling. The results validate all the hypotheses, demonstrating that factors such as the public’s identification with the athlete, the fit between the athlete and the brand, and brand positioning are of great importance for the credibility of the campaign. The contributions of this paper are novel for sports marketing, femvertising and the planning of advertising campaigns.
Sustainability and Competitive Advantage in Small Restaurants: A Dynamic Resource–Relationship Framework
(Emerald Publishing, 2025-12-02) Hernandez Maskivker, Gilda; Nicoara-Popescu, Doriana; Fornells Herrera, Albert
This study examines how sustainability strategies contribute to sustained competitive advantage in small restaurants, using an integrated framework that combines the Resource-Based View (RBV), Stakeholder Theory and Dynamic Capabilities (DC). Design/methodology/approach A mixed-methods study of 128 restaurants in Barcelona assesses environmental and social sustainability commitments and analyzes how restaurant size, responsible practices and certifications relate to competitive advantage. Findings Despite limited resources, small restaurants achieve sustainable competitive advantage by strategically leveraging stakeholder trust and eco-certifications as DC, reconfiguring resources and relationships to adapt to evolving sustainability demands and market conditions. Research limitations/implications The study is context-specific to Barcelona, limiting generalizability to other regions. Practical implications Restaurant owners can strengthen sustainability performance by developing adaptive capabilities that convert certifications and stakeholder relationships into strategic assets. Policymakers should simplify eco-certification schemes and tailor them to SME needs. Social implications Strengthening stakeholder relationships can foster community engagement, promote fair labor practices and enhance social cohesion in the hospitality sector. Originality/value This study advances a hybrid framework integrating the RBV, Stakeholder Theory and DC, showing that small restaurants achieve sustainable competitive advantage from the strategic orchestration of key resources in response to evolving stakeholder and environmental pressures.

Examinar

Enviaments recents