Pub Date : 2023-05-21DOI: 10.37380/jisib.v13i1.992
A. Kanade, Sachin Bhoite, Shantanu Kanade, Niraj Jain
Both the globe and technology are growing more quickly than ever. Artificial intelligence's design and algorithm are being called into question as its deployment becomes more widespread, raising moral and ethical issues. We use artificial intelligence in a variety of industries to improve skill, service, and performance. Hence, it has both proponents and opponents. AI uses a given collection of data to derive action or knowledge. There is therefore always a chance that it will contain some inaccurate information. Since artificial intelligence is created by scientists and engineers, it will always present issues with accountability, responsibility, and system reliability. There is great potential for economic development, societal advancement, and improved human security and safety thanks to artificial intelligence.
{"title":"Artificial Intelligence and Morality: A Social Responsibility","authors":"A. Kanade, Sachin Bhoite, Shantanu Kanade, Niraj Jain","doi":"10.37380/jisib.v13i1.992","DOIUrl":"https://doi.org/10.37380/jisib.v13i1.992","url":null,"abstract":"Both the globe and technology are growing more quickly than ever. Artificial intelligence's design and algorithm are being called into question as its deployment becomes more widespread, raising moral and ethical issues. We use artificial intelligence in a variety of industries to improve skill, service, and performance. Hence, it has both proponents and opponents. AI uses a given collection of data to derive action or knowledge. There is therefore always a chance that it will contain some inaccurate information. Since artificial intelligence is created by scientists and engineers, it will always present issues with accountability, responsibility, and system reliability. There is great potential for economic development, societal advancement, and improved human security and safety thanks to artificial intelligence.","PeriodicalId":43580,"journal":{"name":"Journal of Intelligence Studies in Business","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46977700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-21DOI: 10.37380/jisib.v13i1.988
Luis Madureira, Aleš Popovič, M. Castelli
Competitive Intelligence (CI) is vital for sustaining the performance of organisations in an increasingly volatile, uncertain, complex, and ambiguous (VUCA) world. However, the impact of CI on performance is proportional to its maturity level. The article aims to review and integrate the existing literature on Competitive Intelligence Maturity Models (CIMMs) to provide a go-to framework for setting up, assessing, and developing CI. The CIMMs were sourced from scholarly databases, registers, the social web, and using backwards and forward searches. All the CIMMs respecting the characterisation criteria were included in the study. A scientific and empirically validated definition of CI guided the integration and synthesis of the fourteen selected CIMMs. The primary outcome is a proposed unified CIMM (UCIMM) covering all the CI dimensions and aspects in tandem with the respective implementation guidance frameworks. The proposed UCIMM and implementation frameworks effectuate the guidance needed to set up, assess, and develop the CI practice and theory and, ultimately, the performance of organisations.
{"title":"Competitive Intelligence Maturity Models: Systematic Review, Unified Model and Implementation Frameworks","authors":"Luis Madureira, Aleš Popovič, M. Castelli","doi":"10.37380/jisib.v13i1.988","DOIUrl":"https://doi.org/10.37380/jisib.v13i1.988","url":null,"abstract":"Competitive Intelligence (CI) is vital for sustaining the performance of organisations in an increasingly volatile, uncertain, complex, and ambiguous (VUCA) world. However, the impact of CI on performance is proportional to its maturity level. The article aims to review and integrate the existing literature on Competitive Intelligence Maturity Models (CIMMs) to provide a go-to framework for setting up, assessing, and developing CI. The CIMMs were sourced from scholarly databases, registers, the social web, and using backwards and forward searches. All the CIMMs respecting the characterisation criteria were included in the study. A scientific and empirically validated definition of CI guided the integration and synthesis of the fourteen selected CIMMs. The primary outcome is a proposed unified CIMM (UCIMM) covering all the CI dimensions and aspects in tandem with the respective implementation guidance frameworks. The proposed UCIMM and implementation frameworks effectuate the guidance needed to set up, assess, and develop the CI practice and theory and, ultimately, the performance of organisations.","PeriodicalId":43580,"journal":{"name":"Journal of Intelligence Studies in Business","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42887126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-21DOI: 10.37380/jisib.v13i1.987
A. Cekuls
Recently, a lot of attention has been paid to several aspects of CI, which influence the decision-making of organizations and the acquisition of competitive advantages. Organizations must leverage data, artificial intelligence (AI), and social capital to enhance their competitive intelligence processes. Social media data, AI and machine learning, big data analytics, dynamic capabilities, and intraorganizational social capital all play significant roles in driving strategic decision-making and improving customer experiences. By integrating these elements effectively, organizations can gain valuable insights, mitigate risks, and stay ahead of the competition.
{"title":"Unveiling the Value of Competitive Intelligence: Coordinated Communication and Added Value","authors":"A. Cekuls","doi":"10.37380/jisib.v13i1.987","DOIUrl":"https://doi.org/10.37380/jisib.v13i1.987","url":null,"abstract":"Recently, a lot of attention has been paid to several aspects of CI, which influence the decision-making of organizations and the acquisition of competitive advantages. Organizations must leverage data, artificial intelligence (AI), and social capital to enhance their competitive intelligence processes. Social media data, AI and machine learning, big data analytics, dynamic capabilities, and intraorganizational social capital all play significant roles in driving strategic decision-making and improving customer experiences. By integrating these elements effectively, organizations can gain valuable insights, mitigate risks, and stay ahead of the competition.","PeriodicalId":43580,"journal":{"name":"Journal of Intelligence Studies in Business","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46951794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-09DOI: 10.37380/jisib.v12i3.896
T. Chankoson, Fenglei Chen, Zhiting Wang, Mengqi Wang, Khunanan Sukpasjaroen
This study aims to provide a systematic and complete knowledge map for researchers working in the field of research on the application of artificial intelligence in education. In addition, it is designed to help researchers quickly understand author collaboration characteristics, institutional collaboration characteristics, trending research topics, evolutionary trends, and research frontiers of scholars from a library informatics perspective. In this study, a bibliometric approach was used to quantitatively analyze the retrieved literature with the help of the bibliometric analysis software CiteSpace. The analysis results are presented in tables and visual images in this paper. The results of this study indicate that collaborative relationships among scholars need to be improved and collaborative research relationships among research institutions are more fragmented. This study also points out the shortcomings of this study: Chinese educational researchers and practitioners still have a relatively vague understanding of some fundamental issues in the process of integration and development of AI and education. Therefore, this paper uses quantitative research methods such as bibliometrics and visualization pictures to systematically and intuitively reveal the research progress and trends on the application of artificial intelligence in education based on the published literature and to provide a reference for further research on this topic in the future.
{"title":"Knowledge Mapping for the Study of Artificial Intelligence in Education Research: Literature Reviews","authors":"T. Chankoson, Fenglei Chen, Zhiting Wang, Mengqi Wang, Khunanan Sukpasjaroen","doi":"10.37380/jisib.v12i3.896","DOIUrl":"https://doi.org/10.37380/jisib.v12i3.896","url":null,"abstract":"This study aims to provide a systematic and complete knowledge map for researchers working in the field of research on the application of artificial intelligence in education. In addition, it is designed to help researchers quickly understand author collaboration characteristics, institutional collaboration characteristics, trending research topics, evolutionary trends, and research frontiers of scholars from a library informatics perspective. In this study, a bibliometric approach was used to quantitatively analyze the retrieved literature with the help of the bibliometric analysis software CiteSpace. The analysis results are presented in tables and visual images in this paper. The results of this study indicate that collaborative relationships among scholars need to be improved and collaborative research relationships among research institutions are more fragmented. This study also points out the shortcomings of this study: Chinese educational researchers and practitioners still have a relatively vague understanding of some fundamental issues in the process of integration and development of AI and education. Therefore, this paper uses quantitative research methods such as bibliometrics and visualization pictures to systematically and intuitively reveal the research progress and trends on the application of artificial intelligence in education based on the published literature and to provide a reference for further research on this topic in the future.","PeriodicalId":43580,"journal":{"name":"Journal of Intelligence Studies in Business","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43149223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-09DOI: 10.37380/jisib.v12i3.893
Shelly Freyn, Fred Hoffman
Information Age trends have caused the competitive intelligence (CI) industry to flourish while changing the way CI is conducted. Universities educating CI analysts are interested in knowing what knowledge and skills are necessary for future practitioners. In 2022, Harvard Business Review addressed this topic’s relevancy, noting increases in CI departments and growing demand for analysts to sift through unconfirmed information. This study addresses the question of what skill sets are needed for future CI analysts and how do instructors prepare them for an evolving and dynamic future in CI? Over 130 CI practitioners were surveyed about recommended skills and curriculum for the next generation. Results confirmed CI’s technology evolution (e.g., faster turnarounds, greater client expectations). While tech-savvy skills are essential, soft skills consistently ranked as top requirements. Findings are applicable to other disciplines that analyze data for business strategy.
信息时代的趋势使竞争情报(CI)行业蓬勃发展，同时也改变了CI的实施方式。培养CI分析师的大学有兴趣了解未来从业者所需的知识和技能。2022年，《哈佛商业评论》(Harvard Business Review)讨论了这一主题的相关性，指出CI部门的增加以及对分析师筛选未经证实信息的需求不断增长。本研究解决了未来CI分析师需要哪些技能组合以及教师如何为CI不断发展和动态的未来做好准备的问题。超过130名CI从业者接受了关于下一代推荐技能和课程的调查。结果证实了CI的技术发展(例如，更快的周转，更高的客户期望)。虽然精通技术的技能是必不可少的，但软技能一直是最重要的要求。研究结果适用于为商业战略分析数据的其他学科。
{"title":"Competitive intelligence in an AI world: Practitioners’ thoughts on technological advances and the educational needs of their successors","authors":"Shelly Freyn, Fred Hoffman","doi":"10.37380/jisib.v12i3.893","DOIUrl":"https://doi.org/10.37380/jisib.v12i3.893","url":null,"abstract":"Information Age trends have caused the competitive intelligence (CI) industry to flourish while changing the way CI is conducted. Universities educating CI analysts are interested in knowing what knowledge and skills are necessary for future practitioners. In 2022, Harvard Business Review addressed this topic’s relevancy, noting increases in CI departments and growing demand for analysts to sift through unconfirmed information. This study addresses the question of what skill sets are needed for future CI analysts and how do instructors prepare them for an evolving and dynamic future in CI? Over 130 CI practitioners were surveyed about recommended skills and curriculum for the next generation. Results confirmed CI’s technology evolution (e.g., faster turnarounds, greater client expectations). While tech-savvy skills are essential, soft skills consistently ranked as top requirements. Findings are applicable to other disciplines that analyze data for business strategy.","PeriodicalId":43580,"journal":{"name":"Journal of Intelligence Studies in Business","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49045549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-09DOI: 10.37380/jisib.v12i3.961
A. Cekuls
In the world of business, the importance of competitive intelligence cannot be overdone. As companies compete for market share and seek to gain an edge over their competitors, understanding the market and their competition becomes increasingly critical. As artificial intelligence continues to evolve, its potential to impact competitive intelligence grows.
{"title":"AI-Driven Competitive Intelligence: Enhancing Business Strategy and Decision Making","authors":"A. Cekuls","doi":"10.37380/jisib.v12i3.961","DOIUrl":"https://doi.org/10.37380/jisib.v12i3.961","url":null,"abstract":"In the world of business, the importance of competitive intelligence cannot be overdone. As companies compete for market share and seek to gain an edge over their competitors, understanding the market and their competition becomes increasingly critical. As artificial intelligence continues to evolve, its potential to impact competitive intelligence grows.","PeriodicalId":43580,"journal":{"name":"Journal of Intelligence Studies in Business","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43226436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-09DOI: 10.37380/jisib.v12i3.929
Hidayet Beyhan, Burç Ulengin
An artificial financial market is built on top of the Genoa Artificial Stock Market. The market is populated with agents having different trading strategies and they are let to interact with each other. Agents differ in the trading method they use to trade, and they are grouped as noise, technical, statistical analysis, and machine learning traders. The model is validated by the replication of stylized facts in financial asset returns. We were able to replicate the leptokurtic shape of the probability density function, volatility clustering, and the absence of autocorrelation in asset returns. The wealth dynamics for each agent group are analyzed throughout the trading period. Agents with a higher time complexity trading strategy outperform those with a strategy comparing their final wealth.
{"title":"Does more intelligent trading strategy win? Interacting trading strategies: an agent-based approach","authors":"Hidayet Beyhan, Burç Ulengin","doi":"10.37380/jisib.v12i3.929","DOIUrl":"https://doi.org/10.37380/jisib.v12i3.929","url":null,"abstract":"An artificial financial market is built on top of the Genoa Artificial Stock Market. The market is populated with agents having different trading strategies and they are let to interact with each other. Agents differ in the trading method they use to trade, and they are grouped as noise, technical, statistical analysis, and machine learning traders. The model is validated by the replication of stylized facts in financial asset returns. We were able to replicate the leptokurtic shape of the probability density function, volatility clustering, and the absence of autocorrelation in asset returns. The wealth dynamics for each agent group are analyzed throughout the trading period. Agents with a higher time complexity trading strategy outperform those with a strategy comparing their final wealth.","PeriodicalId":43580,"journal":{"name":"Journal of Intelligence Studies in Business","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44667384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-09DOI: 10.37380/jisib.v12i3.906
Shereen Aly
The purpose of this study is to examine the effect of marketing intelligence (MI) adoption on enhancing the profitability indicators of banks adopting MI and listed in the Egyptian stock exchange. A statistical analysis was carried based on data collected, using a questionnaire instrument to measure the efficiency of adopting MI among 12 banks adopting MI and listed in the Egyptian stock exchange. The study focuses on using 2 measures of profitability indicators; return on equity (ROE) and return on assets (ROA).The profitability indicators (ROE, ROA) of 12 central banks adopting MI and listed in the Egyptian stock exchange were measured during the period (2012–2021). Then, statistical analysis was conducted based on data collected using the simple linear regression model. The results of the study indicated a significant effect of MI adoption on enhancing the profitability indicators of 12 banks adopting MI and listed in the Egyptian stock exchange.
{"title":"The effect of marketing intelligence adoption on enhancing profitability indicators of banks listed in the Egyptian stock exchange","authors":"Shereen Aly","doi":"10.37380/jisib.v12i3.906","DOIUrl":"https://doi.org/10.37380/jisib.v12i3.906","url":null,"abstract":"The purpose of this study is to examine the effect of marketing intelligence (MI) adoption on enhancing the profitability indicators of banks adopting MI and listed in the Egyptian stock exchange. A statistical analysis was carried based on data collected, using a questionnaire instrument to measure the efficiency of adopting MI among 12 banks adopting MI and listed in the Egyptian stock exchange. The study focuses on using 2 measures of profitability indicators; return on equity (ROE) and return on assets (ROA).The profitability indicators (ROE, ROA) of 12 central banks adopting MI and listed in the Egyptian stock exchange were measured during the period (2012–2021). Then, statistical analysis was conducted based on data collected using the simple linear regression model. The results of the study indicated a significant effect of MI adoption on enhancing the profitability indicators of 12 banks adopting MI and listed in the Egyptian stock exchange.","PeriodicalId":43580,"journal":{"name":"Journal of Intelligence Studies in Business","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48083196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we proposed a decision support tool for recruiters to improve their hiring decisions of suitable candidates for such a vacancy post. For this purpose, we proposed the use of the Artificial Neural Network (ANN) method from Artificial Intelligence (AI), thus we used real data from a semi-public recruitment agency in Morocco. However, for the adopted methodology, we used the process opted by the methods and techniques related to Data Mining. As a result, after completing the modelling process, we were able to obtain a model capable of predicting the decision to accept or reject such a candidate for such a vacancy. However, we obtained a model with an accuracy of 99% as well as with a very low error rate. However, our results show that Artificial Intelligence techniques can provide a better decision support tool for recruiters while minimising the cost and time of processing applications and maximising the accuracy of the decisions made.
{"title":"Towards a digital enterprise: the impact of Artificial Intelligence on the hiring process","authors":"Karim Amzile, Mohamed Beraich, Imane Amouri, Cheklekbire Malainine","doi":"10.37380/jisib.v12i3.894","DOIUrl":"https://doi.org/10.37380/jisib.v12i3.894","url":null,"abstract":"In this paper, we proposed a decision support tool for recruiters to improve their hiring decisions of suitable candidates for such a vacancy post. For this purpose, we proposed the use of the Artificial Neural Network (ANN) method from Artificial Intelligence (AI), thus we used real data from a semi-public recruitment agency in Morocco. However, for the adopted methodology, we used the process opted by the methods and techniques related to Data Mining. \u0000As a result, after completing the modelling process, we were able to obtain a model capable of predicting the decision to accept or reject such a candidate for such a vacancy. However, we obtained a model with an accuracy of 99% as well as with a very low error rate. \u0000However, our results show that Artificial Intelligence techniques can provide a better decision support tool for recruiters while minimising the cost and time of processing applications and maximising the accuracy of the decisions made.","PeriodicalId":43580,"journal":{"name":"Journal of Intelligence Studies in Business","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45940816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-23DOI: 10.37380/jisib.v12i2.952
Mati Ur Rehman, R. Ullah, Hawraa Allowatia, Shabana Perween, Qurat Ul Ain, Muhammad Ammad, Tarique Noorul Hasan
The sector of healthcare is one of the most growing and developing sector of the current economy. The leaders of healthcare system need keys that would help them to advance business processes, decision-making, communication between physicians, administration andpatients, as-well-as effective data access. In this case, Business Intelligence (BI) systems may be useful.BI is a new multidisciplinary research field that is being used in a variety of industries. It entails extracting information from large amounts of data and delivering it to stakeholders in a decision-making context that is correct. Many BI applications in the healthcare industryattempt to analysing data, predictions, supporting decision-making, and attaining total sector improvements. In today’s rapidly evolving health-care industry, decision-makers must cope with increasing demands for administrative and clinical data in order to meet regulatory and public-specific standards. The application of BI is realized as a viable resolution to this problem.As the current data on BI is mainly focusing on the area of industry, So the aim of the current input is to adapt and translate the present research findings for the health-care industry.For this reason, various BI definitions are explored and consolidated into a framework. The objective of this review is to give an overview of how to use BI to aid decision-making in healthcare companies. Along these the sector specific requisites for effective BI-application and role in future are discussed.
{"title":"Elaborating the Role of Business Intelligence (BI) in Healthcare Management","authors":"Mati Ur Rehman, R. Ullah, Hawraa Allowatia, Shabana Perween, Qurat Ul Ain, Muhammad Ammad, Tarique Noorul Hasan","doi":"10.37380/jisib.v12i2.952","DOIUrl":"https://doi.org/10.37380/jisib.v12i2.952","url":null,"abstract":"The sector of healthcare is one of the most growing and developing sector of the current economy. The leaders of healthcare system need keys that would help them to advance business processes, decision-making, communication between physicians, administration andpatients, as-well-as effective data access. In this case, Business Intelligence (BI) systems may be useful.BI is a new multidisciplinary research field that is being used in a variety of industries. It entails extracting information from large amounts of data and delivering it to stakeholders in a decision-making context that is correct. Many BI applications in the healthcare industryattempt to analysing data, predictions, supporting decision-making, and attaining total sector improvements. In today’s rapidly evolving health-care industry, decision-makers must cope with increasing demands for administrative and clinical data in order to meet regulatory and public-specific standards. The application of BI is realized as a viable resolution to this problem.As the current data on BI is mainly focusing on the area of industry, So the aim of the current input is to adapt and translate the present research findings for the health-care industry.For this reason, various BI definitions are explored and consolidated into a framework. The objective of this review is to give an overview of how to use BI to aid decision-making in healthcare companies. Along these the sector specific requisites for effective BI-application and role in future are discussed.","PeriodicalId":43580,"journal":{"name":"Journal of Intelligence Studies in Business","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42279491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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