Repositorio Institucional de la Universidad ESAN
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On Cournot and Bertrand competition in collusive mixed oligopolies
No full textWe consider a mixed oligopoly of one public and N private firms where goods are horizontally differentiated. In our setting, an interdependent payoff structure characterizes the degree of collusion among private firms. We show that, whereas in the Bertrand model, private firms are willing to collude as much as possible, in the Cournot model, the existence of a public firm reduces the scope of collusion. We also prove that the classic discussion comparing price and quantity competition crucially depends on market collusion. More precisely, price competition unambiguously yields larger profits for private firms only if collusion is high enough. In an infinitely repeated game, we prove that collusion is easier to sustain in a larger oligopoly because, in this case, a larger N helps mitigate the effect of the public firm on private firms’ collusion sustainability. Finally, we also find that collusion is always more easily sustained in the Bertrand case than in the Cournot case. © The Author(s) 2024
Digital competencies: key drivers of digital transformation in Ibero-America
No full textPurpose: This study aims to determine the importance of digital competencies in companies’ digital transformation processes, particularly in developing contexts. The theoretical framework defines digital competencies in a developing context and highlights companies’ need to develop these competencies to enhance competitiveness and exploit market opportunities. Design/methodology/approach: The methodology involved conducting focus groups with 120 executives from six Latin American countries (Bolivia, Colombia, Peru, Puerto Rico, Uruguay and Venezuela) and Spain. Findings: The findings underscore the significance of competencies in driving digital transformation, outlining the top and bottom three competencies perceived by executives. Moreover, executives recommended additional competencies to supplement a list of 28 predetermined digital competencies. Originality/value: This research provides insights into which competencies are important in companies’ digital transformation processes tailored to the specific needs of organizations in Ibero-America. © 2025, Emerald Publishing Limited
Factors that influence value creation and value capture in companies – evidence in an emerging market
No full textPurpose: The objective of this study is to analyze the influence of the following variables – technological innovation, creativity and innovation management and business model innovation – on two variables: value creation in companies and value capture in companies. Design/methodology/approach: The sample consisted of 222 informants employed by companies listed in the Top 1,000 in the city of Lima. A questionnaire was designed to examine the five variables under study (three independent variables and two dependent variables). Confirmatory and structural factor analyses were performed using structural equations with the SPSS AMOS software. Findings: The study shows that value capture is influenced by technological innovation, creativity and innovation management, as well as business model innovation, while value creation is influenced only by technological innovation and business model innovation. Research limitations/implications: One limitation of this study is that its results are generalized for companies from different business sectors, so its conclusions cannot be associated with specific business sectors. Another limitation of the study is that the data from this research are cross-sectional, so the relationships found between the study variables are not sufficient to establish a definitive causal relationship. Practical implications: For executives, this study offers valuable insights into the significance of their management roles in driving innovation, particularly concerning the dual objectives of value creation and capture within their organizations. Originality/value: A research model is proposed to identify the factors that influence value creation and value capture in companies in a developing country, where consumers have different purchasing power and purchasing preferences compared to consumers in developed countries. Executives focus their efforts on creating and implementing innovative ideas only if they perceive that doing so will achieve monetary results, and it is necessary to emphasize the innovation of internal processes to create value in a way customers will perceive. © 2025, Jhony Ostos and Manuel-Fernando Montoya-Ramírez
Future research opportunities on sustainable smart cities: bibliometric analysis and network visualization
No full textSustainable smart cities are a topic of growing relevance in a world that is increasingly urbanized and concerned about sustainability. This field of study analyzes how emerging technologies and innovative practices transform cities into more efficient, habitable, and ecologically responsible environments. The main objective of this article is to review the state of the art on sustainable smart cities to measure the impact factor, the scientific production of the topic, and identify possible research gaps. The methodology followed four stages: preliminary bibliometric analysis in the Scopus database, bibliometric analysis on sustainable smart cities, network visualization using VOSviewer, and systematic content analysis of the 20 most cited articles. After filtering and cleaning the database, we worked with 2758 articles. The results show an increase in publications from 2020 onwards, with 552 articles published in 2022. Following this growing trend, more publications are expected in 2023, highlighting the knowledge gaps yet to be closed. The journal Sustainability has published the most articles (317). Yigitcanlar is the most cited author (24 citations), followed closely by Bibri (22 citations). China (368) and India (313) have the most publications on the research topic. The qualitative study concludes that the programs, actions, and developments form an innovation ecosystem for the conformation of sustainable smart cities. Regarding research opportunities, there is a pending agenda for researchers in the economic and social approach to smart cities, which are crucial for understanding the broader impacts of these technologies. As a limitation, we worked with the Scopus database, which may exclude some key articles available in other databases like the Web of Science. Future studies could incorporate these databases for a more comprehensive analysis. © The Author(s) 2025
Private equity activity and corporate governance’s spillover
No full textPurpose: We examine the impact of private equity on corporate governance across industries and countries. Design/methodology/approach: We gathered data from 15 countries and 16 industries spanning the period from 2005 to 2015 to construct an average corporate governance index and track private equity deals across both industries and countries. We analyze a country-industry-year panel dataset and address endogeneity issues. Findings: The results indicate a strong and significant relationship between private equity activity and corporate governance quality. When the private equity investment begins earlier, it is more relevant to the corporate governance quality. Foreign private equity investment seems to complement domestic private equity to improve corporate governance in settings with low domestic private equity activity. The experience of the fund that originates the private equity activity is also a determinant of the quality of the corporate governance spillover. Practical implications: Governments and institutions should promote private equity by creating a regulatory environment that attracts investment funds to countries or sectors that lack robust governance frameworks. Investors can design more effective governance practices according to the specific needs of their industries and countries. Shareholders would better understand how private equity corporate governance practices complement the company’s long-term strategies. Finally, the market would benefit from the confidence in private equity investors that promote international corporate governance practices that are valuable to the stakeholders. Originality/value: This research expands our understanding of the benefits of private equity activity on corporate governance quality across industries. We posit the importance of foreign private equity investors complementing domestic private equity activity and fund characteristics such as their experience in boosting corporate governance. © 2024, Hernán Herrera-Echeverri, Diego Cueto, Sandra Gaitan and Daniel Fragua
Model Proposal for Malware Detection Using Deep Learning on Cell Phones with Android Operating System
No full textIn recent years, with the advancement of technology, the number of malware attacks has also increased, Peru being one of the countries with more cyberattacks of this type to electronic devices. Therefore, the main objective of the proposed study is to design a Malware detection model using Deep Learning techniques in cell phones with Android operating system. For this purpose, 5 phases have been carried out in the methodology to be able to recognize Malware anomalies and present error-free data comprising the following: Imported dataset, preprocessing, feature extraction, model implementation and evaluation. In addition, different machine learning models such as DT, RF, SVM and K-NN were developed and the results were evaluated using the metrics Accuracy, Precision, Recall and F1-score. For malware detection, RF presents the highest percentage in all the indicated parameters 89.23%, 87.59% and 88.90% and in Recall it is below K-NN with 85.84%. The RF model outperforms all the algorithms applied in the model, showing that better predictive results can be obtained. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
Implementation of a Web Application to Improve the Collection Management of Means of Payment of a Train Station in the City of Lima
No full textIn Peru, the use of public transport in a train station in the city of Lima has increased exponentially due to the great demand that exists on the part of users who day by day opt for this modality of service, since currently there is no It has not been possible to unify the public transport system or optimize its processes to improve the service as such. The objective of the research is to implement a web application to improve the collection management of the means of payment of a train station in the city of Lima, covering customer service time, payment policies and customer satisfaction regarding to collection management. To carry out the investigation and the solution proposal, the SCRUM development methodology will be used, covering each of its phases. The aforementioned methodology will cover the identification of the basic needs of the sprints, the planning and estimation of the sprints, project implementation, validation of the sprints and finally the deployment. After deploying the application, the survey was applied to the sample to obtain the statistical data, which showed that 97.3 % of the respondents strongly agree that the web application significantly influences the collection management of the means of payment of a train station in the city of Lima. With this, we conclude that the implementation of a web application has a notable influence on collection management, since it has allowed the establishment of a modern technological model that was not available, to improve the collection process, facilitating a better payment alternative where passengers minimize the time invested that usually took longer than it should. © 2024 IEEE
Model Proposal for Phishing Detection in Text Messages Using Machine Learning
No full textIn the dynamic landscape of digital communication, text messages are seamlessly integrated into everyday interactions, but they have become a prime target for cybercriminals using phishing attacks. With around 55% of users falling victim to such fraudulent tactics, addressing the growing threat of SMS phishing is imperative. This article presents an in-depth analysis of the central role of machine learning in cyber security, focusing on the detection and prevention of SMS phishing. Based on several works such as Moncada’s methodology, Dueñas’ study of AI applications, ALMahadin’s optimization based SVM model, Sheik’s email classification and Pandiyan’s algorithms to distinguish between legitimate and malicious websites, the study presents a robust methodology. This approach includes data collection, preprocessing, feature extraction using CountVectorizer and Tf-Idf, and data classification using various machine learning algorithms. The results show that the Random Forest Classifier is the optimal model, achieving an excellent accuracy of 97.94% in distinguishing between legitimate and potentially malicious text messages. The study concludes by highlighting the invaluable contribution of machine learning techniques in strengthening cyber security measures against the threat of SMS phishing. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
Cryptocurrency Investments Forecasting Model Using Deep Learning Algorithms
No full textThe explosive growth of cryptocurrencies has attracted a considerable number of individuals willing to invest, leading to an exponential increase in their market value and trading volume. However, the cryptocurrency market is highly volatile and presents complex datasets where prediction is extremely challenging. Due to this, this article evaluates the implementation of a Prediction System for Cryptocurrency Investments for users using Deep Learning algorithms, aiming to predict the prices of six cryptocurrencies (BTC, ETH, BNB, LTC, XLM, and DOGE). For this, the use of a genetically tuned algorithm with Deep Learning and techniques based on enhanced trees are proposed to compare them. The best result obtained is that the Gated recurrent unit (GRU) model, has an average MAPE of 4%, followed by Convolutional neural networks (CNN) with an average MAPE of 7% and Direct feedforward neural networks (DFNN) of 12%. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024