Pub Date : 2023-02-23DOI: 10.37380/jisib.v12i2.956
Admel Husejinovic, Nermina Durmic, Samed Jukic
This paper aims to show how business intelligence can be applied in the credit card approval process. More specifically, the paper investigates how information like an applicant’s age, credit score, debt, income, and prior default can be used in credit card approval prediction.The dataset used for analysis is a publicly available dataset from the UCI machine learning repository. Logistic regression is used to make a prediction model with a reasonable number of attributes for a comprehensible business model. The Chi-square test of independence is used to test the dependence of credit card approval results with attributes. Research uncovers that prior default is supposed to be the most important attribute in the approval process. Finally, the authors propose several visualizations that could help make smarter decisions with effective credit risk assessment.
{"title":"Application of Business Intelligence in Decision Making for Credit Card Approval","authors":"Admel Husejinovic, Nermina Durmic, Samed Jukic","doi":"10.37380/jisib.v12i2.956","DOIUrl":"https://doi.org/10.37380/jisib.v12i2.956","url":null,"abstract":"This paper aims to show how business intelligence can be applied in the credit card approval process. More specifically, the paper investigates how information like an applicant’s age, credit score, debt, income, and prior default can be used in credit card approval prediction.The dataset used for analysis is a publicly available dataset from the UCI machine learning repository. Logistic regression is used to make a prediction model with a reasonable number of attributes for a comprehensible business model. The Chi-square test of independence is used to test the dependence of credit card approval results with attributes. Research uncovers that prior default is supposed to be the most important attribute in the approval process. Finally, the authors propose several visualizations that could help make smarter decisions with effective credit risk assessment.","PeriodicalId":43580,"journal":{"name":"Journal of Intelligence Studies in Business","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48556518","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.v12i2.950
A. Cekuls
In today’s business world, data has become a highly valuable asset. Companies that can effectively harness their data to gain insightsand make informed decisions have a significant competitive advantage. This is where business intelligence and real-time analysis come in. The authors will discuss various business intelligence applications. Such studies, e.g. improving competitive advantage through business intelligence, speed of innovation and quality of innovation in human capital and structural capital are becoming increasingly relevant.
{"title":"Business intelligence factors for decision making","authors":"A. Cekuls","doi":"10.37380/jisib.v12i2.950","DOIUrl":"https://doi.org/10.37380/jisib.v12i2.950","url":null,"abstract":"In today’s business world, data has become a highly valuable asset. Companies that can effectively harness their data to gain insightsand make informed decisions have a significant competitive advantage. This is where business intelligence and real-time analysis come in. The authors will discuss various business intelligence applications. Such studies, e.g. improving competitive advantage through business intelligence, speed of innovation and quality of innovation in human capital and structural capital are becoming increasingly relevant.","PeriodicalId":43580,"journal":{"name":"Journal of Intelligence Studies in Business","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69842493","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.v12i2.951
K. Nuortimo, Janne Härkönen
The opposition to a deployed technology in large construction projects can grow step by step when transferred from a global level to local project delivery. Large construction projects with specific technology implementations put pressure on local public acceptance andcommunity involvement. This pressure is transferred to project management, how to deal with the issue of stakeholder acceptance before, during, and after project execution. Hence, understanding public acceptance and project-specific reputation can prove beneficial. Utilizedmostly in the company Market Intelligence function(MI), modern large dataset media analytics enables mining technology-related sentiments on global, regional, or local project levels. This paper measures the media sentiment towards three large Finnish construction projects.The specific interest is to investigate which stakeholder groups are visible through the editorial and social media and how these can be classified according to the level of required information or participation level. The aim is to gain a numerical value for project reputation, a concept belonging to the marketing field of studies. Relevant technology deployment indications are provided, and a stairs of acceptance concept is conceptualized to reflect the project-specific public acceptance. Specific needs to increase efforts at a local project level are indicated. The means to counteract local resistance can involve the mode of project execution or social marketing.The new algorithm-based method for measuring public acceptance and the introduced stairs of acceptance concept may bring project-level benefits by providing the added focus for increasing public acceptance.
{"title":"Introducing concepts: stairs of acceptance and project specific reputation score. Exploring public acceptance in three Finnish construction projects via large dataset media-analytics","authors":"K. Nuortimo, Janne Härkönen","doi":"10.37380/jisib.v12i2.951","DOIUrl":"https://doi.org/10.37380/jisib.v12i2.951","url":null,"abstract":"The opposition to a deployed technology in large construction projects can grow step by step when transferred from a global level to local project delivery. Large construction projects with specific technology implementations put pressure on local public acceptance andcommunity involvement. This pressure is transferred to project management, how to deal with the issue of stakeholder acceptance before, during, and after project execution. Hence, understanding public acceptance and project-specific reputation can prove beneficial. Utilizedmostly in the company Market Intelligence function(MI), modern large dataset media analytics enables mining technology-related sentiments on global, regional, or local project levels. This paper measures the media sentiment towards three large Finnish construction projects.The specific interest is to investigate which stakeholder groups are visible through the editorial and social media and how these can be classified according to the level of required information or participation level. The aim is to gain a numerical value for project reputation, a concept belonging to the marketing field of studies. Relevant technology deployment indications are provided, and a stairs of acceptance concept is conceptualized to reflect the project-specific public acceptance. Specific needs to increase efforts at a local project level are indicated. The means to counteract local resistance can involve the mode of project execution or social marketing.The new algorithm-based method for measuring public acceptance and the introduced stairs of acceptance concept may bring project-level benefits by providing the added focus for increasing public acceptance.","PeriodicalId":43580,"journal":{"name":"Journal of Intelligence Studies in Business","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69842370","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 : 2022-12-22DOI: 10.37380/jisib.v12i1.924
A. Cekuls
In today’s fast-paced business environment, having a strong understanding of the competitive landscapeis more important than ever. As the old saying goes, “knowledge is power,” and this is especiallytrue when it comes to staying ahead of the competition.Competitive intelligence is the process of gathering, analyzing, and disseminating informationabout the products, services, and strategies of a company’s competitors in order to gain a strategicadvantage. It involves studying the strengths and weaknesses of competitors, as well as trends anddevelopments in the industry, in order to inform business decisions and strategies.The scope of competitive intelligence is broad, and can include a wide range of activities andsources of information. Some common sources of competitive intelligence include public information,such as company websites, press releases, and industry reports, as well as private information, suchas sales data, market research, and customer feedback. Recent research shows that competitive intelligence is beginning to cover an ever wider range. The topics of scientific articles go beyond aspects of business and management.
{"title":"Expand the scope of competitive intelligence","authors":"A. Cekuls","doi":"10.37380/jisib.v12i1.924","DOIUrl":"https://doi.org/10.37380/jisib.v12i1.924","url":null,"abstract":"In today’s fast-paced business environment, having a strong understanding of the competitive landscapeis more important than ever. As the old saying goes, “knowledge is power,” and this is especiallytrue when it comes to staying ahead of the competition.Competitive intelligence is the process of gathering, analyzing, and disseminating informationabout the products, services, and strategies of a company’s competitors in order to gain a strategicadvantage. It involves studying the strengths and weaknesses of competitors, as well as trends anddevelopments in the industry, in order to inform business decisions and strategies.The scope of competitive intelligence is broad, and can include a wide range of activities andsources of information. Some common sources of competitive intelligence include public information,such as company websites, press releases, and industry reports, as well as private information, suchas sales data, market research, and customer feedback. Recent research shows that competitive intelligence is beginning to cover an ever wider range. The topics of scientific articles go beyond aspects of business and management.","PeriodicalId":43580,"journal":{"name":"Journal of Intelligence Studies in Business","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43401132","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 : 2022-12-22DOI: 10.37380/jisib.v12i1.925
D. Triyanto
This study aims to examine the effect of Islamic Corporate Governance and Sharia Compliance on indications of fraud occurring in Indonesia’s Islamic Banks from 2016 to 2020. The independent variables are Islamic Corporate Governance and Sharia Compliance with the Proxy of Islamic Income Ratio and Profit Sharing Ratio. The dependent variable is fraud in Islamic Commercial Banks. The population in this study were all Islamic Banks registered in the Financial Services Authority in the period 2016 to 2020. The samples were selected using the purposive sampling method. In this study, there were 11 Islamic Banks with a 5 years research period so that the total sample used in this study amounted to 55. The analytical method used in this study was logistic regression which was processed using SPSS version 25. The results of this study indicate that the Islamic Corporate Governance variable has a positive influence on indications of fraud occurring in Islamic Commercial Banks, Sharia Compliance with the Proxy Profit Sharing Ratio has a negative influence on indications of fraud occurrence in Islamic Commercial Banks while Sharia Compliance with the proxy of Islamic Income Ratio does not affect the indications of the occurrence of frauds in Islamic Commercial Banks.
{"title":"Sharia Compliance, Islamic Corporate Governance, and Fraud: A study of Sharia Banks in Indonesia","authors":"D. Triyanto","doi":"10.37380/jisib.v12i1.925","DOIUrl":"https://doi.org/10.37380/jisib.v12i1.925","url":null,"abstract":"This study aims to examine the effect of Islamic Corporate Governance and Sharia Compliance on indications of fraud occurring in Indonesia’s Islamic Banks from 2016 to 2020. The independent variables are Islamic Corporate Governance and Sharia Compliance with the Proxy of Islamic Income Ratio and Profit Sharing Ratio. The dependent variable is fraud in Islamic Commercial Banks. The population in this study were all Islamic Banks registered in the Financial Services Authority in the period 2016 to 2020. The samples were selected using the purposive sampling method. In this study, there were 11 Islamic Banks with a 5 years research period so that the total sample used in this study amounted to 55. The analytical method used in this study was logistic regression which was processed using SPSS version 25. The results of this study indicate that the Islamic Corporate Governance variable has a positive influence on indications of fraud occurring in Islamic Commercial Banks, Sharia Compliance with the Proxy Profit Sharing Ratio has a negative influence on indications of fraud occurrence in Islamic Commercial Banks while Sharia Compliance with the proxy of Islamic Income Ratio does not affect the indications of the occurrence of frauds in Islamic Commercial Banks.","PeriodicalId":43580,"journal":{"name":"Journal of Intelligence Studies in Business","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45317980","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 dynamic and complex environments, it can be difficult for small and mediumsizedenterprises (SMEs) to achieve business performance, innovate and survive, even thoughthese actions are crucial for economic growth and competitiveness. Competitive intelligence (CI)appears as a strategic practice to help them. Although there are many theoretical studies thatpropose the relationship between CI and innovation, few studies have conducted empiricalstudies in the context of SMEs. The objective of this paper is to investigate how competitiveintelligence enhances innovation performance in the context of a SME. Based on a literaturereview and empirical data from several interviews with managers of one SME, our findingsallowed us to propose a framework showing the contribution of CI to innovation performancerelying on absorptive capacity. Our findings also highlight that a prospector owner-managercan improve the results of CI in the SME and contribute to better innovation performance.
{"title":"Competitive intelligence and absorptive capacity for enhancing innovation performance of SMEs","authors":"Abdeslam Hassani,Elaine Mosconi","doi":"10.37380/jisib.v1i1.692","DOIUrl":"https://doi.org/10.37380/jisib.v1i1.692","url":null,"abstract":"In dynamic and complex environments, it can be difficult for small and mediumsizedenterprises (SMEs) to achieve business performance, innovate and survive, even thoughthese actions are crucial for economic growth and competitiveness. Competitive intelligence (CI)appears as a strategic practice to help them. Although there are many theoretical studies thatpropose the relationship between CI and innovation, few studies have conducted empiricalstudies in the context of SMEs. The objective of this paper is to investigate how competitiveintelligence enhances innovation performance in the context of a SME. Based on a literaturereview and empirical data from several interviews with managers of one SME, our findingsallowed us to propose a framework showing the contribution of CI to innovation performancerelying on absorptive capacity. Our findings also highlight that a prospector owner-managercan improve the results of CI in the SME and contribute to better innovation performance.","PeriodicalId":43580,"journal":{"name":"Journal of Intelligence Studies in Business","volume":"42 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138515736","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 : 2020-06-30DOI: 10.37380/JISIB.V10I2.582
Vincent Grèzesa, Riccardo Bonazzia, Francesco Maria Cimminoa
Companies’ environments change constantly and very quickly, so each companymust be aligned with its environment and understand what is happening to maintain andimprove its performance. To constantly adapt to its environment, the company must integratea learning process in relation to what is happening and become a "learning company." Thisposture will ensure organizational effectiveness in relation to changes in the environment andallow companies to achieve goals under the best conditions. Our project aims at delivering acompetitive and collective intelligence service allowing to support decision making processesthrough the diagnostic of alignment between internal knowledge of the organization andavailable external information.
{"title":"Atman: Intelligent information gap detection for learning organizations: First steps toward computational collective intelligence for decision making","authors":"Vincent Grèzesa, Riccardo Bonazzia, Francesco Maria Cimminoa","doi":"10.37380/JISIB.V10I2.582","DOIUrl":"https://doi.org/10.37380/JISIB.V10I2.582","url":null,"abstract":"Companies’ environments change constantly and very quickly, so each companymust be aligned with its environment and understand what is happening to maintain andimprove its performance. To constantly adapt to its environment, the company must integratea learning process in relation to what is happening and become a \"learning company.\" Thisposture will ensure organizational effectiveness in relation to changes in the environment andallow companies to achieve goals under the best conditions. Our project aims at delivering acompetitive and collective intelligence service allowing to support decision making processesthrough the diagnostic of alignment between internal knowledge of the organization andavailable external information.","PeriodicalId":43580,"journal":{"name":"Journal of Intelligence Studies in Business","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42383562","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}
For the upcoming conference on Intelligence Studies at ICI 2020 in Bad Nauheim, Germany the focus of this issue of JISIB is on collective intelligence and foresight. The first two papers by Søilen and Almedia and Lesca deal with collective intelligence from an intelligence studies perspective. It may be said that the Internet itself is a gigantic collective intelligence effort, the largest in human history. Open source is a prerequisite for this system to work for everyone. The article by Černý et al. is on open source. All other contributions are on the connection between the Internet, software and intelligence. This issue consists of seven articles to compensate for two articles that were taken out by editors in the last issue. The first article by Søilen entitled “Making sense of the collective intelligence field: a review” is a historical review of the field of collective intelligence. The paper shows how collective intelligence is an interdisciplinary field and argues there is a flaw in the notion of “wisdom of crowds”. Collective intelligence can be understood in terms of social systems theory and as such this approach has been fruitful for the social sciences, although so far not very popular. It also bares relevance for the study of business and economics. The second article by Almeida and Lesca is entitled “Collective intelligence process to interpret weak signals and early warnings”. Early warning and the detection of weak signals is a vital topic for any intelligence organization. Two aspects are discussed in the paper, the importance of new technology and collective sense making or interpretation The third article by Shaikh and Singhal entitled “Study on the various intellectual property management strategies used and implemented by ICT firms for business intelligence” deals with intellectual property rights and patenting strategies. The authors identify a number of defensive and offensive IP strategies applied to ICT companies. The results have a bearing on patent acquisitions. The fourth article by Lamrhari et al. is entitled “Web intelligence for understanding customer satisfaction: application of Latent Dirichlet Allocation (LDA) and the Kano model”. Customer satisfaction today is mostly measured with data from the internet, using different business intelligence techniques. The Kano model is still valuablei,ii, but the way we gather information to assess the different levels in the model has changed. The authors use Latent Dirichlet Allocation to analyze the voice of customer (VOC) in online reviews. They suggest that BI techniques and a fuzzy-Kano model can enable companies to better understand their customers’ online reviews. The fifth article by Nahili et al. is entitled “A new corpus-based convolutional neutral network for big data text analysis”. Companies need efficient ways to analyze everything that is said about them on the internet (reviews, comments). The paper suggests a convolutional neural network (CNN) as it has bee
{"title":"A deeper look at the collective intelligence phenomenon","authors":"Klaus Solberg Søilen","doi":"10.37380/jisib.v9i2.472","DOIUrl":"https://doi.org/10.37380/jisib.v9i2.472","url":null,"abstract":"For the upcoming conference on Intelligence Studies at ICI 2020 in Bad Nauheim, Germany the focus of this issue of JISIB is on collective intelligence and foresight. The first two papers by Søilen and Almedia and Lesca deal with collective intelligence from an intelligence studies perspective. It may be said that the Internet itself is a gigantic collective intelligence effort, the largest in human history. Open source is a prerequisite for this system to work for everyone. The article by Černý et al. is on open source. All other contributions are on the connection between the Internet, software and intelligence. This issue consists of seven articles to compensate for two articles that were taken out by editors in the last issue. The first article by Søilen entitled “Making sense of the collective intelligence field: a review” is a historical review of the field of collective intelligence. The paper shows how collective intelligence is an interdisciplinary field and argues there is a flaw in the notion of “wisdom of crowds”. Collective intelligence can be understood in terms of social systems theory and as such this approach has been fruitful for the social sciences, although so far not very popular. It also bares relevance for the study of business and economics. The second article by Almeida and Lesca is entitled “Collective intelligence process to interpret weak signals and early warnings”. Early warning and the detection of weak signals is a vital topic for any intelligence organization. Two aspects are discussed in the paper, the importance of new technology and collective sense making or interpretation The third article by Shaikh and Singhal entitled “Study on the various intellectual property management strategies used and implemented by ICT firms for business intelligence” deals with intellectual property rights and patenting strategies. The authors identify a number of defensive and offensive IP strategies applied to ICT companies. The results have a bearing on patent acquisitions. The fourth article by Lamrhari et al. is entitled “Web intelligence for understanding customer satisfaction: application of Latent Dirichlet Allocation (LDA) and the Kano model”. Customer satisfaction today is mostly measured with data from the internet, using different business intelligence techniques. The Kano model is still valuablei,ii, but the way we gather information to assess the different levels in the model has changed. The authors use Latent Dirichlet Allocation to analyze the voice of customer (VOC) in online reviews. They suggest that BI techniques and a fuzzy-Kano model can enable companies to better understand their customers’ online reviews. The fifth article by Nahili et al. is entitled “A new corpus-based convolutional neutral network for big data text analysis”. Companies need efficient ways to analyze everything that is said about them on the internet (reviews, comments). The paper suggests a convolutional neural network (CNN) as it has bee","PeriodicalId":43580,"journal":{"name":"Journal of Intelligence Studies in Business","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2019-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46825161","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}
The treatment of weak signals is identified as a method to identify strategic surprises in a firm’s environment. Many researchers address the problem of anticipation of movements that have an impact on a firm’s environment. Weak signals are considered in some approaches and presented in the literature, but also other methods are explored. This article tries to deepen the discussion of how to treat and interpret weak signals collected in a firm’s environment. The concept of a weak signal is explained and the discussion about how to collect and interpret them is presented. Two important aspects are distinguished in the article: the usefulness of information technology in collection and treatment of weak signals and the concept of collective sensemaking in interpreting weak signals. Two cases of weak signal interpretation are presented as illustrations
{"title":"Collective intelligence process to interpret weak signals and early warnings","authors":"Fernando C Almeidaa de, Humbert Lescab","doi":"10.37380/jisib.v9i2.466","DOIUrl":"https://doi.org/10.37380/jisib.v9i2.466","url":null,"abstract":"The treatment of weak signals is identified as a method to identify strategic surprises in a firm’s environment. Many researchers address the problem of anticipation of movements that have an impact on a firm’s environment. Weak signals are considered in some approaches and presented in the literature, but also other methods are explored. This article tries to deepen the discussion of how to treat and interpret weak signals collected in a firm’s environment. The concept of a weak signal is explained and the discussion about how to collect and interpret them is presented. Two important aspects are distinguished in the article: the usefulness of information technology in collection and treatment of weak signals and the concept of collective sensemaking in interpreting weak signals. Two cases of weak signal interpretation are presented as illustrations","PeriodicalId":43580,"journal":{"name":"Journal of Intelligence Studies in Business","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2019-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44547995","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}
Software technology is seeing enormous growth as it is used in all fields of technology. It is continuously evolving at a rapid pace and has a short span of the technological life cycle. The use of the software is not restricted only to information and communication technology but is used in all fields of technology. In many cases, the inventive step of a product or service lies solely in the software. Hence, the software plays a crucial role in all fields of technology. However, ease of copying poses a financial risk for the software industry, thereby creating major disincentives to the development of innovation. Still, the technology is changing very fast and firms investing in this technology expect quick returns on their innovation investments. Strategies for generating and managing intellectual property have subsequently taken center stage for information and communication technology companies, and patents have become an important feature providing maximum protection for any technology. Hence, intellectual property rights strategies in general and patenting strategies especially play a crucial role in the information and communication technology industry to be globally competitive. Firms never publish or disclose their intellectual property strategies; hence, this study makes use of the literature review to highlight various intellectual property management strategies used by information and communication technology firms for managing their intellectual property. These strategies can be offensive or defensive and may be used as proactive or reactive depending on various aspects such as market, territory, technology, or time. The insights provided in this work may help the research community from the IT domain in industry and academia to learn and modify their strategies for patent acquisition.
{"title":"Study on the various intellectual property management strategies used and implemented by ICT firms for business intelligence","authors":"Shabib-Ahmed Shaikha, Tarun Kumar Singhalb","doi":"10.37380/jisib.v9i2.467","DOIUrl":"https://doi.org/10.37380/jisib.v9i2.467","url":null,"abstract":"Software technology is seeing enormous growth as it is used in all fields of technology. It is continuously evolving at a rapid pace and has a short span of the technological life cycle. The use of the software is not restricted only to information and communication technology but is used in all fields of technology. In many cases, the inventive step of a product or service lies solely in the software. Hence, the software plays a crucial role in all fields of technology. However, ease of copying poses a financial risk for the software industry, thereby creating major disincentives to the development of innovation. Still, the technology is changing very fast and firms investing in this technology expect quick returns on their innovation investments. Strategies for generating and managing intellectual property have subsequently taken center stage for information and communication technology companies, and patents have become an important feature providing maximum protection for any technology. Hence, intellectual property rights strategies in general and patenting strategies especially play a crucial role in the information and communication technology industry to be globally competitive. Firms never publish or disclose their intellectual property strategies; hence, this study makes use of the literature review to highlight various intellectual property management strategies used by information and communication technology firms for managing their intellectual property. These strategies can be offensive or defensive and may be used as proactive or reactive depending on various aspects such as market, territory, technology, or time. The insights provided in this work may help the research community from the IT domain in industry and academia to learn and modify their strategies for patent acquisition.","PeriodicalId":43580,"journal":{"name":"Journal of Intelligence Studies in Business","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2019-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46182455","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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