Category: Computing for business

We have published this paper in the journal Simulation: Transactions of the Society for Modeling and Simulation International. DOI: https://doi.org/10.1177/00375497241296542

ABSTRACT:

Business-to-Consumer (B2C) e-commerce has become a dominant, continuously evolving force in global retail. Most consumers today make cross-border purchases in marketplaces, while enterprises have found great opportunities, and competition has become increasingly fierce. To understand B2C properties is an important endeavor. This paper achieves two goals: it develops a method to prove tendencies in a simulation and shows the oligopolistic nature of cross-border B2C e-commerce marketplaces. These achievements enhance the understanding of cross-border B2C e-commerce, by employing novel approaches: Social simulation, agent-based modeling (ABM) tools, theorem-proving techniques, and scenario analysis. The proving method began with an experimental design to explore the model’s dynamics for parameters defined for specific scenarios of interest, and the agents’ options were randomly selected for a significant number of runs (Monte Carlo experiment). This procedure allowed us to identify and prove the necessity of a tendency (the oligopolistic character of cross-border B2C e-commerce) and determine the factors that drive it. In the second part of the proof procedure, the persistence, independence of the agents’ choices, and scaling validity of the tendency were shown by significantly increasing the number of random experiments and the number of simulated agents. The model was also validated. The developed method satisfactorily addresses some challenges of theorem-proving. In all these experiments, the variable of interest was market share. The resulting order of influence of the factors driving market share was recognition, product and service attributes of the marketplaces, and word of mouth. Surprisingly, word of mouth was the least important factor.

We have published in the journal Environmental Science & Policy. DOI: https://doi.org/10.1016/j.envsci.2024.103856

ABSTRACT:

The science, technology, engineering, and mathematics (STEM) education research delves into the core of sustainable development goals (SDGs), including the pillars of quality education (SDG4), robust economic growth
(SDG8), and diminished inequalities (SDG10). These pursuits stand as keystones in sculpting inclusive societies and bridging societal gaps. While previous studies utilising data envelopment analysis (DEA) have explored educational performance mainly from a macro-perspective, there is a lack of micro-perspective investigation. Our study aims to fill this gap by proposing a DEA approach to assess the relative efficiency of engineering classes. We analysed 70 classes covering 38 subjects in the first semester of 2022 at a South American school. Methodologically, we employed the slack-based measure (SBM) model under the benefit of doubt (BoD) condition. Unlike prior research, we analysed classes’ relative performance considering different pedagogical approaches active-learning classes (15.7 %) and 59 passive-learning classes (84.3 %). Our results showed that 18 classes were efficient (25.7 %). Active classes were more efficient, but few subjects maintained similar efficiencies for all classes. Moreover, efficient classes were concentrated in the last two years prior to graduation (57.9 %). This may represent an additional barrier for low-income students, who tend to drop out in the first years. The findings support several improvement recommendations, such as integrating digital technologies, boosting active learning opportunities, and bolstering classes in foundational subjects. Also, implications for researchers, decision- and policy-makers are discussed. Our approach can be replicated in diverse educational contexts, enabling the identification of strengths and weaknesses for more efficient educational management.

At the Pragmatics laboratory, we have published an article in the journal IEEE Transactions on Professional Communication. DOI: https://doi.org/10.1109/TPC.2023.3260449

ABSTRACT:
Twitter offers tools that facilitate the diffusion of information by which companies can engage consumers to share their messages. Literature review: Communication professionals are using platforms such as Twitter to disseminate information; however, the strategies that they should use to achieve high information diffusion are not clear. This article proposes message repetition as a strategy. Research questions: 1. What is the wear-out point of Twitter? 2. How many times should a company repeat a tweet written on its brand page to maximize the diffusion for seeds? 3. How many times should a company repeat a tweet written on its brand page to maximize the diffusion while minimizing the number of consumers reaching their wear-out point for seeds? 4. How many times should
a company repeat a tweet written on its brand page to maximize the diffusion for non-seeds? 5. How many times should a company repeat a tweet written on its brand page to maximize the diffusion while minimizing the number of consumers reaching their wear-out point for both seeds and non-seeds? Research methodology: An agent-based simulation model for information diffusion is proposed as an approach to measure the diffusion of a tweet that has been repeated. The model considers that consumers can reach their wear-out point when they read a tweet several times. Results: The results of the model indicate the number of times a company should send the same tweet to achieve high information diffusion before this action has negative effects on consumers. Brand followers are key to achieving high information diffusion; however, consumers begin to feel bothered by the tweet by the sixth repetition. Conclusions: To the best of our knowledge, this is the first study to examine tweet repetition as a strategy to achieve higher information diffusion on Twitter. In addition, it extends the information diffusion literature by controlling the wear-out
effect. It contributes to both communication and computational science literature by analyzing a communication problem using an agent-based approach. Finally, this article contributes to the field of technical and professional communication by testing a strategy to reach great information diffusion, and by creating a tool that any company can use to anticipate the results of a communication campaign created in Twitter before launching it.

Our paper that discusses how to use an agent-based model to simulate the touristic preferences to travel to different provinces in Spain has been accepted in the Journal of Simulation, which has been accepted in a WoS journal Q3.

Abstract:
Spain ranks second in the world for the number of international tourists, most of whom need to plan routes during their stay in the country. These tourists have different preferences, which influence their choice of tourist routes depending on the activities offered by provinces. There are currently no customized routes according to the preferences of a travel party, which makes the supply of tourist packages complex. Due to the difficulty of obtaining data that is not always public and is subject to the particular circumstances of the data collection, we propose an agent-based simulation model implemented in Java, named ABM RoutePlanner, which simulates the behaviour of travel parties travelling through 23 provinces of peninsular Spain. The model is developed as an application of the protocol Overview, Design concepts and Details (ODD), which is primarily used as a base of various types of ABMs to represent some complex phenomena. This paper makes an applied contribution, which presents the actual routes that will allow tour operators to define strategic plans that motivate tourists to visit the provinces included in the routes; in addition, we deploy a Web application that shows these routes to any Internet user. The simulation of the model was calibrated and validated with extracted data from the TripAdvisor website and Spanish tourist surveys.