Competitive Intelligence System Research Articles

A Civil Aviation Customer Service Ontology and Its Applications

ABSTRACT In the process of developing the C919 large aircraft customer service intelligence system, we find that heterogeneous and incomplete data cause the inefficient and inaccurate decision making. Thus, to solve this problem, we propose to introduce the idea of ontology modeling and reasoning into competitive intelligence system building in this paper. We first present the building principles and methods of the civil aviation customer service ontology. We then define the classes and properties to contribute a real-world civil aviation customer service ontology, which is published on the Web (http://www.openkg.cn/dataset/cacso). We finally design SWRL rules corresponding to different intelligence analysis targets to support reasoning in our designed competitive intelligence system.

A multi-attribute decision-making framework for enterprise competitive intelligence system evaluation with 2-tuple linguistic neutrosophic information

Big data is changing our lives and the way we understand the world, as well as the operational patterns of business and social organizations. Fully understanding the value of data and knowing how to use big data to provide a basis for business decision-making has gradually become the most basic thinking that business organizations should possess in the era of big data. Under the thinking mode of data-driven decision-making, many information science researchers have discussed the model, architecture, operation mechanism and other aspects of big data competitive intelligence system. At the same time, more and more enterprises, such as IBM, Amazon, Google, Microsoft, Wal Mart, etc., have begun to attach importance to the development and construction of big data competitive intelligence software systems, and have achieved certain results. The enterprise competitive intelligence system evaluation in the context of big data is regarded as multi-attribute decision-making (MADM). In this paper, the Hamy mean (HM) and the power average (PA) are connected with 2-tuple linguistic neutrosophic sets (2TLNSs) to propose the 2-tuple linguistic neutrosophic numbers power HM (2TLNPHM) operator. Then, use the 2TLNPHM operator to handle MADM with 2TLNS. Finally, taking the enterprise competitive intelligence system evaluation in the context of big data as an example, the proposed method is explained. The main contributions of this study are summarized: the establishment of the 2TLNPHM operator; (2) The 2TLNPHM operator was developed to handle MADM with 2TLNS; (3) Through the empirical application of the enterprise competitive intelligence system evaluation, the proposed method is validated; (4) Some comparative studies have shown the rationality of the 2TLNPHM operator.

The Impact of ChatGPT on Enterprise Competitive Intelligence Systems

The Impact of ChatGPT on Enterprise Competitive Intelligence Systems

Research and Implementation of Association Analysis of Agricultural Insurance Based on Data Mining Algorithm

In order to establish the comprehensive competitive intelligence system of agricultural insurance companies, the process model of agricultural insurance competitive intelligence is constructed by combining data mining and process mining. The model is based on the relationship between data mining, process mining, and competitive intelligence based on analytic hierarchy process, and combines the current agricultural insurance subsidy policy, and the demand characteristics of competitive intelligence of agricultural insurance companies. Experimental results show that, among 11 secondary indicators, 6 indicators are rated above 4.0, that is, good grade or above, and 5 indicators score below 4.0, and still need to be improved. Prove data mining and the AHP algorithm can effectively improve the sustainability of agricultural insurance.

How digital startups use competitive intelligence to pivot

Decision-making about startups' business models is highly dependent on available information, and the role of data analytics capabilities in business model innovation has been emphasized. Today's competitive intelligence tools such as Alexa, Google Analytics, Similarweb, NexLab TrackEngine, etc. easily provide the decision-makers with competitive intelligence. However, the quality of these decisions at the exposure of competitive intelligence is still unknown. We aim to investigate the role of competitive intelligence in entrepreneurs' decisions on business model pivoting at the early stages of their startups. We used a qualitative multi-case study of six startups to investigate the changes in the founders' attitudes toward their business models at the exposure of data analytics. Competitive intelligence led the early-stage entrepreneurs to pivot their business models. However, the quality of the resulted business models was questionable. To ensure the quality of decision-making, founders need to be supported by cognition service systems beyond the current competitive intelligence systems. Based on the findings we propose an extension to the Lean Startup build-measure-learn loop.

Research on the Development Path of Competitive Intelligence System of Commercial Banks Based on SCP

Competition is the essence of market economy, and how commercial Banks reform and develop and occupy a dominant position in competition is a common concern in the fields of finance and information science. By sorting out relevant results, it can provide reference for the development and research of commercial Banks. Starting from financial intelligence, this paper discusses the development evolution of commercial Banks from the perspective of competitive intelligence. Based on SCP analysis of the development dilemma of commercial Banks, this paper proposes the development path of competitive intelligence system of commercial Banks. Putting forward new ideas for the development of commercial Banks, combined with the needs of the industry, in-depth competition intelligence collection and processing work for the innovation and development of commercial Banks is of great significance.

Competitive Intelligence Systems in Practice: Investigating Main Issues and Challenges Regarding Acceptance and Usage Behavior

Gathering information about competitors and understanding their position is a key issue for any organization. The objective of this paper is to identify the main internal issues when it comes to dealing with Competitive Intelligence Systems (CIS) acceptance and usage behavior. We apply the exploratory research method of grounded theory to analyze a CI System of a large industrial company. At a practical level, our study aims at helping managers understanding the important features related to CIS in the postimplementation stage. At a theoretical level, the aim is to address a gap by explain the several relationships between the different categories of contributing actors and identifying the major problems they face after implementing a CIS. Our study identifies 3 main emergent issues in terms of:1. Internal visibility of the system, 2. Legitimacy and recognition by the management 3. System’s technology adoption and use. Results are discussed and managerial implications are addressed.

Modelo de vigilancia tecnológica para la gestión de un grupo de investigación en salud

Introducción. La dinámica constante de la ciencia, la tecnología y la innovación, con el volumen de información disponible, constituyen un reto para el quehacer de los grupos de investigación en su compromiso como unidades generadoras de resultados de conocimiento y de aportes relevantes a su entorno. Una alternativa a la planeación que dé soporte a la toma de decisiones con mayor conocimiento, menor riesgo y oportuna anticipación a los cambios debería estar soportada en un proceso organizado, selectivo y sistemático como lo es la vigilancia tecnológica. Objetivo. Revisión de literatura de tipo descriptivo sobre la vigilancia tecnológica y generación de una propuesta de un modelo de vigilancia tecnológica para la gestión de la actividad científica del grupo de investigación Estudio Genético de Enfermedades Complejas (EGEC). Metodología. Revisión de la literatura de tipo descriptivo. Se consultaron las bases de datos de Medline, SciELO, Ebsco e IEEE y el buscador Google Scholar, mediante la combinación de las palabras clave “vigilancia tecnológica/technological surveillance”, “salud/health”, “enfermedad/disease”, “ejemplos en salud”, “universidad” e “investigación”. Se incluyeron artículos científicos de los últimos cinco años y se excluyeron artículos que solo consideraran la difusión de resultados de ejercicios de vigilancia tecnológica. Con base en el análisis de los resultados, se propone un modelo de vigilancia tecnológica para la gestión de la actividad científica del grupo de investigación EGEC, para lo que se estructuró el diagrama de las etapas, insumos y recursos que integran el modelo propuesto, incluyendo como estrategia de validación el desarrollo de una prueba piloto sobre cáncer, a partir de la cual se hicieron ajustes adicionales al mismo. Resultados. Como referente internacional se encuentra la Norma UNE 166006:2011 de la Asociación Española de Normalización y Certificación (AENOR) y, como referente nacional, España y sus Regiones Intercambian Conocimiento con Antioquia (ERICA) e Innovaciones a partir de la Vigilancia Tecnológica (InnoViTech). Se establecen las etapas conceptuales, buenas prácticas para el ejercicio y recursos para el desarrollo de la vigilancia tecnológica. Los principales componentes del modelo propuesto incluyen la identificación de necesidades, planeación, recolección, auditoría, análisis, documentación y comunicación de información. Conclusiones. El modelo planteado es una base para el desarrollo de una estrategia de gestión del conocimiento de un grupo de investigación y plantea la importancia de escalar hacia el uso de la inteligencia competitiva al interior del mismo. [CarrilloZambrano E, Páez-Leal MC, Suárez JM, Luna-González ML. Modelo de vigilancia tecnológica para la gestión de un grupo de investigación en salud. MedUNAB. 2018;21(1): 84-99. doi: 10.29375/01237047.2746].

DEVELOPMENT OF MARKETING USING SYSTEMIC PROCESS OF COMPETITIVE INTELLIGENCE AND FORESIGHT – FUTURE STUDIES

Development of competitive intelligence and foresight (future studies) leads to the creation of a perfect image of the current status and future of competition scene facing managers for better decision making. Utilizing competitive intelligence and foresight (future studies) leads to the recognition of short-term and long-term strategies in marketing. Here, the research methodology is correlation-descriptive and has been carried out as field study. Statistical population of this research includes all managers at General Department of Youth Affairs and Sport in West Azerbaijan consisting 43 persons. In this research statistical sample equals the statistical population. Questionnaires of this research have been designed in three parts as competitive intelligence, foresight (future studies) and marketing system. In this research correlation and regression methodology have been used. Based on obtained information and analyzing the data about the relationship between competitive intelligence and development of marketing it was found that: creating intelligence has a positive connection with customer relationship. Intelligence distribution is positively associated with the customer relationship. Responsiveness is positively associated with customer relationship. Also about the relationship between foresight (future studies) and development of marketing it was found that: foresight (future studies) is positively associated with customer relationship. Decision-making is positively associated with the creation of differentiated products. Article visualizations:

Factores influyentes, facilitadores y barreras en la implantación de una unidad de inteligencia competitiva: estudios de caso y análisis cuantitativo

Every organizational change project will surely find obstacles and drivers, and the start-up of a competitive intelligence (CI) system confirms the rule. This paper describes the main features of six CI projects leaded by IK4-Ideko , pointing out the challenges and support they experienced while conducting it. This analysis is complemented by quantitatively analyzing the effects of 21 factors considered to have influence on CI system implementation. Results show that CI tools act as drivers and that no factor clearly acts as a barrier for CI, even though human factors are perceived to be nearly inconsequential. The overall handiness of information and the good execution of the first steps of the project can be important factors for future studies.

Design and Implementation of Office Management System in Small and Medium Sized Enterprises Based on Data Mining Technology

This paper introduces data mining technology in enterprise competitive intelligence system; and then introduced theoretical foundation and main clustering method of cluster analysis. The article emphasis on the FCM algorithm and principle and described implementation steps, and proposed the improvement FCM algorithm based on K mean particle size; finally, realize the design and implementation of enterprise competitive intelligence analysis and mining service system, and the improved FCM algorithm is applied in the system.

Enterprise Competitive Intelligence System Research Based on Data Mining Technology

Under the background of current continuous changing market economy and rapid development of information, enterprise will increase the demand of information or data, and correspondingly put forward higher requirements for its quality. For the purpose of better usage and information data control, enterprises put forward pioneering construct competitive intelligence system. Competitive intelligence system can provide accurate, effective and high value, timeliness strong intelligence data to enterprises and the enterprises may adjust their competitive strategy, and effectively enhance their own competitive advantages. The application of data mining technology in enterprise competitive intelligence system can upgrade information reserve capacity and optimize information channels to improve system efficiency effectively. In the process of enterprises development, the establishment of competitive intelligence system based on data mining technology has particularly important practical significance, so we should put more effort into establishing and running the intelligence system.

SWOT analysis on competitive intelligence service in the hospital library

This paper first described the concept of competitive intelligence and hospital competitive intelligence.Then,the resources of hospital library intelligence was analyzed with the method of SWOT,and the feasibility of competitive intelligence service was discussed.Finally,three aspects of the service were elaborated,which included collection of competitive intelligence,instruction of the knowledge of competitive intelligence,and the establishment of competitive intelligence system in hospitals. Key words: Competitive intelligence; Hospital libraries; SWOT analysis; Hospital competitive intelligence

Web data extraction, applications and techniques: A survey

Web Data Extraction is an important problem that has been studied by means of different scientific tools and in a broad range of applications. Many approaches to extracting data from the Web have been designed to solve specific problems and operate in ad-hoc domains. Other approaches, instead, heavily reuse techniques and algorithms developed in the field of Information Extraction.This survey aims at providing a structured and comprehensive overview of the literature in the field of Web Data Extraction. We provided a simple classification framework in which existing Web Data Extraction applications are grouped into two main classes, namely applications at the Enterprise level and at the Social Web level. At the Enterprise level, Web Data Extraction techniques emerge as a key tool to perform data analysis in Business and Competitive Intelligence systems as well as for business process re-engineering. At the Social Web level, Web Data Extraction techniques allow to gather a large amount of structured data continuously generated and disseminated by Web 2.0, Social Media and Online Social Network users and this offers unprecedented opportunities to analyze human behavior at a very large scale. We discuss also the potential of cross-fertilization, i.e., on the possibility of re-using Web Data Extraction techniques originally designed to work in a given domain, in other domains.

The Enterprise Competitive Intelligence System Based on Data Mining

In knowledge economy era, data and information become important economy resources. Drawing valuable information quickly from great amount of datum and reacting immediately, will become the key of corporation success. The paper introduces Competitive Intelligence and Corporation Competitive Intelligence System (CIS) firstly. Then, the paper gives the concept of Data Mining and general process. Furthermore, the paper gives a model of Corporation Competitive Intelligence System based on data mining and its relevant process.

Research and Construction of the Enterprise Competitive Intelligence System

In the era of rapid growth and high competition, a company must possess an information/knowledge advantage in order to hold the upper hand in the industry. Therefore, the company has to continuously monitor its competitors in order to get enough information and convert the information into competitive knowledge. Although information technology has been used in many areas and has many successful examples, it is rarely the case that information technology was used for the task of competitor intelligence. Accordingly, this study describes the Enterprise Competitive Intelligence System. Competitive Intelligence (CI) is one of the key factors for enterprise risk management and decision support. However, the functions of Competitive Intelligence are often greatly restricted by the lack of sufficient information sources about the competitors. Competitive Intelligenceaims to monitor a firms external environment for information relevant to its decision-making process. The article describes the concept and the functions of the Enterprise Competitive Intelligence System, discusses the principle of its construction, and also discusses the construction process and the awareness of CI.

Research and Construction of the Enterprise Competitive Intelligence System

Research and Construction of the Enterprise Competitive Intelligence System

Management des activités de veille stratégique :

Cet article s’interesse aux aspects organisationnels et humains lies a la mise en œuvre d’un systeme d’information de veille strategique en entreprise. L’idee principale etant d’apporter des cles d’interpretation aux managers qui souhaitent implementer/renouveler les activites de veille dans leurs organisations. Il s’inscrit clairement dans une perspective de contribution a l’ingenierie des systemes de veille considerant ces derniers comme un soutien a la prise de decision. A la lumiere d’une revue de la litterature, nous proposons une analyse des systemes de veille considerant les aspects formels et informels de ces derniers. Une illustration a travers un cas d’entreprise est developpee et des recommandations manageriales sont formulees.

Competitive intelligence and information quality

To better understand a competitor's tactical and strategic plans, companies need to take a closer look at competitive intelligence or they risk missing lucrative opportunities. Because of this there is a growing interest in competitive intelligence and intelligence information gathering systems (IIS). This article uses game-theoretic concepts to develop an analytic framework to assess the value of deploying a competitive intelligence gathering information system. Modeling the competitive environment as a game provides a useful approach to study and evaluate competitive strategies given diverse assumptions about the quality of the information known by the players. When determining the value of deploying an IIS, decision makers need to examine three components of the competitive environment: the competitive rules of the game, the state of player knowledge, and the reliability of the information gathered. This framework focuses on competitive environments where the players' state of knowledge (i.e., common versus covert knowledge) and the reliability of the information generated are essential to the decision making process. The article concludes with implications for research and practice.

The Training Strategy of Professional Core Competencies of Talents in Competitive Intelligence

Competitive intelligence is the natural product of modern economic development. As the rapid development of competitive intelligence sources, new techniques and methods are required in competitive intelligence system. Enhancing the techniques of data mining, business administration and applied economics is adopted, in order to promote the professional core competencies. In the light of this, knowledge structure and ability structure of talents are improved for the benefit of development of competitive intelligence.