Meta-análisis aplicado a Business Intelligence para la toma de decisiones objetivas en entidades financieras

Trabajo de InvestigaciónBusiness intelligence se ha convertido en un sistema significativo para las entidades financieras en cuanto a la toma de decisiones, el cual está basado en una serie de técnicas, herramientas y procesos, los cuales permiten obtener información rápida y útil para el desempeño y ventaja competitiva de la misma. Se realizó un meta-análisis bajo la metodología de revisiones sistemáticas, construyendo una serie de preguntas para la identificación de artículos referentes a modelos de BI aplicables en diferentes organizaciones, con el propósito de encontrar un modelo único.PregradoIngeniero de Sistema

The necessities for building a model to evaluate Business Intelligence projects- Literature Review

In recent years Business Intelligence (BI) systems have consistently been rated as one of the highest priorities of Information Systems (IS) and business leaders. BI allows firms to apply information for supporting their processes and decisions by combining its capabilities in both of organizational and technical issues. Many of companies are being spent a significant portion of its IT budgets on business intelligence and related technology. Evaluation of BI readiness is vital because it serves two important goals. First, it shows gaps areas where company is not ready to proceed with its BI efforts. By identifying BI readiness gaps, we can avoid wasting time and resources. Second, the evaluation guides us what we need to close the gaps and implement BI with a high probability of success. This paper proposes to present an overview of BI and necessities for evaluation of readiness. Key words: Business intelligence, Evaluation, Success, ReadinessComment: International Journal of Computer Science & Engineering Survey (IJCSES) Vol.3, No.2, April 201

Aplicación del proceso analítico de red (ANP) para seleccionar nuevos mercados extranjeros para exportar servicios de software: Estudio de firmas colombianos

La selección de los mercados de exportación es una decisión compleja e importante para las pequeñas y medianas empresas (PYME) en el desarrollo para los países interesados en exportar por primera vez. Por ello, la importancia de los programas de exportación de consultoría para su proceso de internacionalización. Los programas están dirigidos por la oficina de comercio de Colombia, y por Promoción del Comercio Organización. Este OPC ha desarrollado un modelo de selección de mercado pero carece de un proceso para validar los pesos seleccionados y los resultados del modelo OPC son deficientes en la generación de confianza suficiente como para motivar al propietario de la empresa para exportar. Por otra parte, solo algunos de los criterios utilizados en el modelo OPC se relacionan entre sí, ya que la mayoría asume este modelo criterios independientes. La selección de los mercados de exportación es una decisión multicriterio y se ha propuesto un modelo de la ANP para la selección de países para exportar servicios de software para las PYME colombiana. Al comparar el modelo de selección de mercado de las OPC con el modelo de la ANP, se identificó que los resultados de ambos modelos son similares en el ranking de los países. El modelo propuesto es mejor porque tiene una metodología estructurada de asignación de pesos, que permite la evaluación de la consistencia de los miemos con asignación a los criterios seleccionados, son ponderados los cambios como la sensibilidad prioritaria.Abstract: The selection of export markets is a complex and important decision for small and medium enterprises (SMEs) of developing countries interested in exporting for the first time. Given this issue, SMEs enroll export programs to receive consultancy for their internationalization process. One of this export programs is directed by the Colombian trade bureau, a Trade Promotion Organization (TPO). This TPO developed a market selection model that lacks a process to validate the weights selected. Therefore, the results of the TPO model are deficient in generating enough confidence to motivate the company owner to export. On the other hand, we identified that some of the criteria used in the TPO model were related to each other, but this model assumes criteria as independent. Due to the fact that the selection of export markets is a multi-criteria decision that involves feedback, we proposed an ANP model for the selection of countries to export software services for Colombian SMEs. Upon comparing the market selection model of the TPO with the ANP model, we identified that the results of both models are similar in the ranking of the countries. However, we concluded that the proposed model is better because it has a structured methodology to assign weights that allows evaluation of the consistency of the weights allocated to the selected criteria. Besides, we also preferred it because allows analyzing sensitivity to changes in the priority weights. The categories of variables that we used in both models are: market, economy and logistics, among other

Business Intelligence and analytics success factors: A case study in the financial sector

Business Intelligence and Analytics (BI&A) can support organizations to improve their decision-making and performance. However, despite the increasing investment in BI&A, a lot of organizations have failed to implement it successfully. Therefore, it is vital for organizations to clearly understand Critical Success Factors (CSFs) for the implementation of BI&A. Although various CSFs of BI&A are suggested by prior studies, there is little consensus on determining these factors. Furthermore, most former studies only deliver a list of theoretical CSFs of BI&A, while little evidence is given on the practical relevance of these factors and the reasoning and rationale behind them. The objective of this research is to theoretically identify and empirically evaluate these CSFs. We identify a set of CSFs of BI&A through a systematic literature review. Then, through a case study in the financial sector in the Netherlands, we provide an in-depth understanding of the practical relevance of these CSFs and the rationale behind them

Of BI research : a tale of two communities

The Business intelligence (BI) literature is in flux, yet the knowledge about its varying theoretical roots remains elusive. This state of affairs draws from two different scientific communities (informatics and business) that have generated multiple research streams, which duplicate research, neglect each other’s contributions, and overlook important research gaps. In response, we structure the BI scientific landscape and map its evolution to offer scholars a clear view of where research on BI stands and the way forward. For this endeavor, we systematically review articles published in top-tier ABS journals and identify 120 articles covering 35 years of scientific research on BI. We then run a co-citation analysis of selected articles and their reference lists. This yields the structuring of BI scholarly community around six research clusters: Environmental Scanning (ES), Competitive Intelligence (CI), Market Intelligence (MI), Decision Support (DS), Analytics Technologies (AT), and Analytics Capabilities (AC). The Co-citation network exposed overlapping and divergent theoretical roots across the six clusters and permitted mapping the evolution of BI research following two pendulum swings. Our article contributes by 1) structuring the theoretical landscape of BI research, 2) deciphering the theoretical roots of BI literature, 3) mapping the evolution of BI scholarly community, and 4) suggesting an agenda for future research.© 2020 Emerald Publishing Limited. This manuscript version is made available under the Creative Commons Attribution–NonCommercial 4.0 International (CC BY–NC 4.0) license, https://creativecommons.org/licenses/by-nc/4.0/fi=vertaisarvioitu|en=peerReviewed

Gestión de la información para tener éxito en la toma de decisiones en marketing

In a globalized world in continuous change, companies that want to achieve sustainable competitive advantages should be aware that the information is the most valuable strategic resource of the company, as it is the core of decision-making. This review article presents a comparative analysis between the concepts that have a significant impact in the decision-making process for the management of marketing, in current organizations: information system, business intelligence, research market and technological surveillance.For this a search, organization and analysis of documents was carried out that allowed compiling conceptual information through a comparative chart, which summarizes the basic terms and how complement each other to achieve decision-making successful in marketing management by individuals and companies interested therein, with minimal knowledge and little experience in these areas of learning. Throughout the article each of the concepts, following a same thread are described in depth: what is in itself, why it is important in marketing and how to apply it. The most outstanding item product of the article is building a conceptual comparison chart, which aims to differentiate each term and clearly establish the "synergistic" relationship between them for a successful decision making process.En un mundo globalizado en permanente cambio, las empresas que quieren lograr ventajas competitivas sostenibles, deben ser conscientes de que la información es el recurso estratégico más valioso de la compañía, por cuanto es el eje central de la toma de decisiones. Este artículo de revisión presenta un análisis comparativo entre los conceptos que inciden de manera significativa en la toma de decisiones para la gestión del marketing, en las organizaciones actuales: sistema de información, inteligencia de negocios, investigación de mercados y vigilancia tecnológica.Para ello se hizo una búsqueda, organización y análisis de documentos que permitieron, la compilación de información conceptual a través de un cuadro comparativo, que sintetiza los términos básicos y cómo se complementan entre sí para lograr una toma de decisiones exitosa en la gestión del marketing por parte de las personas y empresas interesadas, con conocimientos mínimos y poca experiencia en estas áreas del conocimiento. A lo largo del artículo se describen a profundidad cada uno de los conceptos, siguiendo un mismo hilo conductor: qué es en sí mismo, por qué es importante en el marketing y cómo se aplica.El producto más destacado del artículo es la construcción de un cuadro comparativo conceptual, que tiene como objetivo diferenciar cada termino y establecer claramente la relación “sinérgica” entre los mismos para un exitoso proceso de toma de decisiones.

Stakeholder perceptions on better management of Cross-timbers forest resources

The Cross-timbers ecoregion represents the broad ecotone between the Eastern Deciduous Forest and the Tallgrass Prairie. The region is threatened by both natural and anthropogenic factors including urban development, increasing climate variability, and the encroachment of eastern redcedar (Juniperus virginiana). In particular, the exclusion of fire has dramatically changed the composition and structure of the Cross-timbers forests, which historically experienced multiple fires per decade. Active management practices such as prescribed fire, timber thinning, and fuels reduction are largely absent in the region. These management practices are further limited by a lack of a forest resource market. This study utilized a mixed-mode data collection method, which involved focus group meetings as well as an online version of the survey to determine how stakeholders perceived both active management and market opportunities within the Cross-timbers. The requisite data were analyzed using the strengths, weaknesses, opportunities, and threats (SWOT)-Analytic Network Process (ANP) framework. The results suggested that the presence of healthy and resilient forests and the opportunities associated with increased revenue could be the driving forces in active Cross-timbers management. In addition, the availability of a variety of natural resources and the restoration of ecosystem services could be the key to developing a sustainable market within the Cross-timbers. However, stakeholders across-the-board revealed that the financial burden of management and the risk of uncontrolled fire were the major obstacles in these efforts. Further, uncertain markets, lack of enthusiasm from manufacturers, and low quality resources may be what currently hinder the market potential of the Cross-timbers

A decision support model for identification and prioritization of key performance indicators in the logistics industry

YesPerformance measurement of logistics companies is based upon various performance indicators. Yet, in the logistics industry, there are several vaguenesses, such as deciding on key indicators and determining interrelationships between performance indicators. In order to resolve these vaguenesses, this paper first presents the stakeholder-informed Balanced Scorecard (BSC) model, by incorporating financial (e.g. cost) and non-financial (e.g. social media) performance indicators, with a comprehensive approach as a response to the major shortcomings of the generic BSC regarding the negligence of different stakeholders. Subsequently, since the indicators are not independent of each other, a robust multi-criteria decision making technique, the Analytic Network Process (ANP) method is implemented to analyze the interrelationships. The integration of these two techniques provides a novel way to evaluate logistics performance indicators from logisticians' perspective. This is a matter that has not been addressed in the logistics industry to date, and as such remains a gap that needs to be investigated. Therefore, the proposed model identifies key performance indicators as well as various stakeholders in the logistics industry, and analyzes the interrelationships among the indicators by using the ANP. Consequently, the results show that educated employee (15.61%) is the most important indicator for the competitiveness of logistics companies

Strategic insights : navigating business intelligence implementation : phases, tasks, and risks : a case study on an international manufacturing company

PURPOSE: This article aims to present a comprehensive case study of implementing a business intelligence system in the manufacturing company. Therefore, a comprehensive understanding of key implementation aspects and associated risks is vital for meticulous planning before investing in information systems.DESIGN/METHODOLOGY/APPROACH: Through qualitative research, the study will identify the main implementation phases, assign key tasks, and highlight the potential risks encountered during the process. By examining the case study, readers can gain insights into the effective implementation of a business intelligence system in manufacturing company, enabling them to better navigate similar ventures a significant input for researchers to create an implementation model.FINDINGS: Having accurate and timely information is a crucial asset for businesses, influencing their competitive advantage. Information is essential for decision-making, enabling organizations to identify opportunities, threats, strengths, weaknesses, and changes. Business Intelligence (BI) solutions cater to these needs by automatically transforming data into actionable information. However, due to the wide array of tools available in the market, the implementation process of BI can be complex.PRACTICAL IMPLICATIONS: The findings from this article's case study can serve as a foundation for proposing an implementation model for business intelligence systems.ORIGINALITY/VALUE: By analyzing the challenges, key phases, and risks identified in the case study, future research can develop a structured framework or model that outlines the necessary steps, considerations, and best practices for implementing BI systems specifically tailored to manufacturing industries.peer-reviewe