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Systems
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Business Intelligence as a Tool for Business Competitiveness
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Business Intelligence as a Tool for Business Competitiveness

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Practice in Social Science".

Deadline for manuscript submissions: closed (31 March 2024) | Viewed by 59978

Special Issue Editors

Dr. Rafael Robina-Ramírez

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Guest Editor
Business Management and Sociology Department, University of Extremadura, 10071 Cáceres, Spain
Interests: planning and development; strategic tourism development; tourism impact; underdeveloped region
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Marta Ortiz-de-Urbina-Criado

E-Mail Website
Guest Editor
Directory of Experts in Information Handling, Universidad Rey Juan Carlos, Paseo de los Artilleros, 28032 Madrid, Spain
Interests: open data; innovation; knowledge management; strategic management; human resources
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. José Amelio Medina-Merodio

E-Mail Website
Guest Editor
Departamento de Ciencias de la Computación, Universidad de Alcalá, 28871 Madrid, Spain
Interests: virtualization technology; assessment; e-Learning; cloud computing; computer networks; tools learning and gamification
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The current situation of companies, immersed in a technological and globalized world, makes it necessary to improve and adapt their management and production processes to meet the needs of customers.

In addition, industrial processes are undergoing a process of transformation and change derived mainly from the incorporation and development of new paradigms focused on new technologies.

On the other hand, it is necessary for companies to analyze and find demand patterns, segment customers and suppliers, and analyze consumption trends to find and improve their competitive advantage, which is why an adequate management information system is important.

In this context, decision-making that provides strategic value will depend on the management of the information systems available from a process of transformation and change.

In this process, the incorporation and development of new paradigms focused on new technologies is currently crucial to be competitive. These paradigms are not only affecting industrial process environments but also those related to the management and control of the company and, above all, the behavior of users and teams, their relationships, etc.

The main objective of this Special Issue is to delve into those processes that are taking place in industrial production, management and control processes due to the incorporation of new simulation and management tools.

Understanding the behaviors produced in industrial processes, and ensuring their proper functioning in different environments, will allow their evolution, as well as the definition of new methodologies and tools within them.

This Special Issue invites researchers to submit quality original studies in the domain of industrial process improvement through the incorporation of new methodologies and management models, the use of artificial intelligence, big data, and simulation tools in management and production processes and urges them to address their main subdisciplines, which include, but are not limited to:

  • Business process management
  • Business decision making
  • Technological innovation management
  • Innovative business models and management
  • Data management for decision making
  • Intelligent maintenance management
  • Building Information Modeling (BIM)
  • BI-oriented strategies
  • Design and operation of production systems
  • Decision support systems based on big data
  • Big data technology in business
  • Product, process, and system design and reengineering methodologies
  • Lean and agile production
  • Smart manufacturing
  • Security systems in ICT manufacturing processes
  • ICT used in improving smart manufacturing
  • Virtual and augmented reality used in manufacturing processes
  • Green manufacturing
  • Quality management
  • IoT and Industry 4.0
  • Digital Twins
  • Artificial intelligence applied in production processes, management, an business control
  • Implication of Artificial intelligence in the Human-System
  • Ambient intelligence
  • Privacy and security in AI algorithms
  • Implication of human factors in the incorporation and acceptance of new technologies in the industry

Prof. Dr. Rafael Robina-Ramírez
Prof. Dr. Marta Ortiz-de-Urbina-Criado
Dr. José Amelio Medina-Merodio
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Published Papers (8 papers)

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Research

15 pages, 5740 KiB  
Article
Stacked Noise Reduction Auto Encoder–OCEAN: A Novel Personalized Recommendation Model Enhanced
by Bixi Wang, Wenfeng Zheng, Ruiyang Wang, Siyu Lu, Lirong Yin, Lei Wang, Zhengtong Yin and Xinbing Chen
Systems 2024, 12(6), 188; https://doi.org/10.3390/systems12060188 - 26 May 2024
Cited by 26 | Viewed by 1870
Abstract
With the continuous development of information technology and the rapid increase in new users of social networking sites, recommendation technology is becoming more and more important. After research, it was found that the behavior of users on social networking sites has a great [...] Read more.
With the continuous development of information technology and the rapid increase in new users of social networking sites, recommendation technology is becoming more and more important. After research, it was found that the behavior of users on social networking sites has a great correlation with their personalities. The five characteristics of the OCEAN personality model can cover all aspects of a user’s personality. In this research, a micro-directional propagation model based on the OCEAN personality model and a Stacked Denoising Auto Encoder (SDAE) was built through the application of deep learning to a collaborative filtering technique. Firstly, the dimension of the user and item feature matrices was lowered using SDAE in order to extract deeper information. The user OCEAN personality model matrix and the reduced user feature matrix were integrated to create a new user feature matrix. Finally, the multiple linear regression approach was used to predict user-unrated goods and generate recommendations. This approach allowed us to leverage the relationships between various factors to deliver personalized recommendations. This experiment evaluated the RMSE and MAE of the model. The evaluation results show that the stacked denoising auto encoder collaborative filtering algorithm can improve the accuracy of recommendations, and the user’s OCEAN personality model improves the accuracy of the model to a certain extent. Full article
(This article belongs to the Special Issue Business Intelligence as a Tool for Business Competitiveness)
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24 pages, 2617 KiB  
Article
Leveraging Business Intelligence Systems for Enhanced Corporate Competitiveness: Strategy and Evolution
by Montserrat Jiménez-Partearroyo and Ana Medina-López
Systems 2024, 12(3), 94; https://doi.org/10.3390/systems12030094 - 13 Mar 2024
Cited by 5 | Viewed by 13149
Abstract
This study contextualizes the transformative role of Business Intelligence (BI) over the past two decades, emphasizing its impact on business strategy and competitive advantage. Employing a dual-method approach, it integrates a bibliometric analysis using SciMAT with a qualitative examination of six key articles [...] Read more.
This study contextualizes the transformative role of Business Intelligence (BI) over the past two decades, emphasizing its impact on business strategy and competitive advantage. Employing a dual-method approach, it integrates a bibliometric analysis using SciMAT with a qualitative examination of six key articles from the Web of Science (WoS), analyzed through the Gioia methodology, focusing on BI and competitiveness. The aim is to examine the metamorphosis of Business Intelligence (BI) and how it has evolved from a traditionally supporting role to a central strategic player in shaping corporate strategy and business competitive advantage over the past two decades. It discusses the overall transformation of BI and provides an in-depth examination of the specific ways in which Business Intelligence tools have redefined the landscape in contemporary business practices. Key findings reveal BI’s pivotal role in enhancing knowledge management, innovation, and marketing capabilities. Challenges in BI implementation, such as the necessity for skilled personnel and adaptability to swift technological shifts, are also highlighted. Results advocate for a dynamic BI approach, adaptable to market trends and technological evolutions. The research demonstrates that BI tools, especially when integrated with technologies like AI, IoT, and machine learning, significantly enhances decision making and efficiency in socio–technical and management systems, leading to a paradigm shift in handling complex systems and adapting to changing environments. Full article
(This article belongs to the Special Issue Business Intelligence as a Tool for Business Competitiveness)
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20 pages, 1960 KiB  
Article
Intergenerational Leadership: A Leadership Style Proposal for Managing Diversity and New Technologies
by Virginia Ramírez-Herrero, Marta Ortiz-de-Urbina-Criado and José-Amelio Medina-Merodio
Systems 2024, 12(2), 50; https://doi.org/10.3390/systems12020050 - 3 Feb 2024
Cited by 3 | Viewed by 9806
Abstract
Artificial intelligence, augmented, virtual, and mixed reality applications are improving business tools to increase their efficiency and ability to innovate. Technological innovation offers creative opportunities, but each generation values these advances differently. This study analysed the intergenerational differences and their leadership styles. The [...] Read more.
Artificial intelligence, augmented, virtual, and mixed reality applications are improving business tools to increase their efficiency and ability to innovate. Technological innovation offers creative opportunities, but each generation values these advances differently. This study analysed the intergenerational differences and their leadership styles. The research questions are as follows: what are the main characteristics of each generation? And what leadership style is most appropriate for managing generational diversity in companies? Firstly, the main characteristics of each generation—Boomers, Generation X, Millennials, Generation Z, and Generation Alpha—were identified. Secondly, the most representative leadership styles of each generation were analysed. And thirdly, a proposal for a leadership style that can be used to better manage the intergenerational needs and technological demands of companies was presented. The development of leadership styles that take account of all generations can support economic growth and the creation of innovative and sustainable industries, as well as improve social welfare. Full article
(This article belongs to the Special Issue Business Intelligence as a Tool for Business Competitiveness)
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14 pages, 3236 KiB  
Article
Identification of Customer Churn Considering Difficult Case Mining
by Jianfeng Li, Xue Bai, Qian Xu and Dexiang Yang
Systems 2023, 11(7), 325; https://doi.org/10.3390/systems11070325 - 25 Jun 2023
Cited by 4 | Viewed by 2322
Abstract
In the process of user churn modeling, due to the imbalance between lost users and retained users, the use of traditional classification models often cannot accurately and comprehensively identify users with churn tendency. To address this issue, it is not sufficient to simply [...] Read more.
In the process of user churn modeling, due to the imbalance between lost users and retained users, the use of traditional classification models often cannot accurately and comprehensively identify users with churn tendency. To address this issue, it is not sufficient to simply increase the misclassification cost of minority class samples in cost-sensitive methods. This paper proposes using the Focal Loss hard example mining technique to add the class weight α and the focus parameter γ to the cross-entropy loss function of LightGBM. In addition, it emphasizes the identification of customers at risk of churning and raises the cost of misclassification for minority and difficult-to-classify samples. On the basis of the preceding ideas, the FocalLoss_LightGBM model is proposed, along with random forests, SVM, XGBoost, and LightGBM. Empirical analysis based on a dataset of credit card users publicly available on the Kaggle website. The AUC, TPR, and G-mean index values were superior to the existing model, which can effectively improve the accuracy and stability of potential lost users. Full article
(This article belongs to the Special Issue Business Intelligence as a Tool for Business Competitiveness)
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23 pages, 5582 KiB  
Article
A Change-Sensitive Complexity Measurement for Business Process Models Based on Control Structure
by Changhong Zhou, Dengliang Zhang, Deyan Chen and Cong Liu
Systems 2023, 11(5), 250; https://doi.org/10.3390/systems11050250 - 15 May 2023
Cited by 2 | Viewed by 2090
Abstract
The analysis of the process model complexity has significant implications for the operation, maintenance, and optimization of processes. As process models consist of control structures with specific repetitive patterns, the complexity of the control structures often determines the process model complexity. While the [...] Read more.
The analysis of the process model complexity has significant implications for the operation, maintenance, and optimization of processes. As process models consist of control structures with specific repetitive patterns, the complexity of the control structures often determines the process model complexity. While the existing methods for measuring the process model complexity consider most control structure complexity, some changes in branch structures cannot be reflected in the process model complexity. To address this issue, this paper considers the impact of the number and position of activities in branching structures on the process model complexity, distinguishes the connection forms between branch structures, and defines the complexity of the branching structures. We propose a new complexity measurement (CP) based on the control structures. The theoretical validity of CPs was confirmed using Weyuker’s properties, and the process structure variant model was used to experiment with its sensitivity. The findings indicate that the CP satisfies eight out of the nine properties proposed by Weyuker. Compared with the other complexity measurement methods of the process model, the CP is more sensitive to some structural changes in the process model. Therefore, when the structure of the process model changes, the CP reflects the changes in the process model complexity more accurately. Full article
(This article belongs to the Special Issue Business Intelligence as a Tool for Business Competitiveness)
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29 pages, 5804 KiB  
Article
Customer Attitude toward Digital Wallet Services
by Galina Ilieva, Tania Yankova, Yulia Dzhabarova, Margarita Ruseva, Delian Angelov and Stanislava Klisarova-Belcheva
Systems 2023, 11(4), 185; https://doi.org/10.3390/systems11040185 - 6 Apr 2023
Cited by 17 | Viewed by 23619
Abstract
The goal of this study is to examine and identify the factors influencing customer attitude toward and intention to use digital wallets (electronic wallets, e-wallets) during and after the COVID-19 pandemic. A total of 257 correctly fulfilled questionnaires from an online survey were [...] Read more.
The goal of this study is to examine and identify the factors influencing customer attitude toward and intention to use digital wallets (electronic wallets, e-wallets) during and after the COVID-19 pandemic. A total of 257 correctly fulfilled questionnaires from an online survey were summarized. The main features of e-wallet payment systems were classified with a focus on consumer satisfaction via the integration of classic and modern data analysis methods. Structural Equation Modeling (SEM) was preferred to reveal the dependencies between the variables from e-wallets users’ perspective. The designed model can discover and explain the underlying relationships that determine the e-wallets’ adoption mechanism. The obtained results lead to specific recommendations to stakeholders in the value chain of payment processing. Financial regulatory authorities could employ the presented results in planning the development of payment systems. E-commerce marketers could utilize the proposed methodology to assess, compare and select an alternative way for order payment. E-wallet service providers could establish a reliable multi-criteria system for the evaluation of digital wallet adoption. Being aware of the most important components of e-wallets value, managers can more effectively run and control payment platforms, enhance customer experience, and thus improve the company’s competitiveness. As the perceived value of customer satisfaction is subjective and dynamic, measurements and data analysis should be conducted periodically. Full article
(This article belongs to the Special Issue Business Intelligence as a Tool for Business Competitiveness)
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23 pages, 4086 KiB  
Article
System of Project Management at a Medical Hub as an Instrument for Implementation of Open Innovation
by Igor Ilin, Olga Voronova, Dmitriy Pavlov, Azret Kochkarov, Andrea Tick and Bulat Khusainov
Systems 2023, 11(4), 182; https://doi.org/10.3390/systems11040182 - 1 Apr 2023
Cited by 4 | Viewed by 3120
Abstract
Globalization activates qualitative changes in multiple economic entities and requires the development of alternative forms of business organization. At present, one of the most promising development tracks is represented by the implementation of network structures, aimed at achieving common goals and obtaining a [...] Read more.
Globalization activates qualitative changes in multiple economic entities and requires the development of alternative forms of business organization. At present, one of the most promising development tracks is represented by the implementation of network structures, aimed at achieving common goals and obtaining a win-win outcome via joint effort. Business structures that invite dynamic and consistent transformations on a wide scale prove to be able to successfully compete in the market. In this regard, a project management system at a medical hub serves as a vital tool for implementation of open innovation. Participation in the medical hub allows coordinating intentions and establishing aligned communication between all stakeholders, suppliers and private institutions. In modern sectors of the economy, a developing hub becomes a unique structure, because it unites the contributions of the most important healthcare specialists in a single framework. This research examines the structure of healthcare business process models, and scrutinizes the communication between suppliers, partners and consumers of medical services. It also defines the main directions and outlines strategic goals. Assessment of performance of a project management system at a medical hub proves to be the issue of particular relevance, due to the fact that its tasks should be primarily aimed at increasing the share of successful projects and implementing only those ones that comply with the strategy. Based on the latter, a model for the project management system at a medical hub was designed. As a result, the authors developed an assessment mechanism for innovative projects using SNA methods that align with intra-communication interactions (transactions) between the participants in a medical hub. The conducted research allows concluding that in the current era of cutting-edge technologies, the project management system should be considered the most effective management tool for coordinating the actions of a corporate structure at a medical hub. Full article
(This article belongs to the Special Issue Business Intelligence as a Tool for Business Competitiveness)
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16 pages, 1128 KiB  
Article
Research on the Game Relationship and Behavior Optimization between Banks and Customers in the Omni-Channel Environment
by Jianzhong Xu and Xiaolei Cui
Systems 2023, 11(4), 171; https://doi.org/10.3390/systems11040171 - 26 Mar 2023
Viewed by 1855
Abstract
In an omni-channel environment of banks, the information transmission between banks and customers is the basis for decision-making on both sides. This dissertation analyzes the characteristics of signals sent between banks and customers at different stages and proposes a game model of bank–customer [...] Read more.
In an omni-channel environment of banks, the information transmission between banks and customers is the basis for decision-making on both sides. This dissertation analyzes the characteristics of signals sent between banks and customers at different stages and proposes a game model of bank–customer signals in an omni-channel environment. The model explores the types of banks and customers and the influence of six signals on both parties’ action decisions. Building on this model, a genetic algorithm of the signaling game between banks and customers is developed. This algorithm improves the adaptability of customers to the bank’s omni-channel environment through the “selection–crossover–mutation” process. The algorithm determines the signal that brings the greatest utility among multiple bank–customer combinations. This is carried out by calculating the choices made, resulting in the greatest total utility. Finally, a case study is carried out on the omni-channel transformation of Agricultural Bank of China, illustrating the validity of the research results of the game relationship and action optimization. Overall, this study provides a quantitative tool for the action decision-making of banks and customers and the optimization of the relationship between the two. It also provides a reference for how banks should manage customer relationships in an omni-channel environment. Full article
(This article belongs to the Special Issue Business Intelligence as a Tool for Business Competitiveness)
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