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Kultygin, Oleg P., and Irina Lokhtina. "Business intelligence as a decision support system tool." Journal of Applied Informatics 16, no. 91 (February 26, 2021): 52–58. http://dx.doi.org/10.37791/2687-0649-2021-16-1-52-58.
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The relevance of the topic considered in the article is to solve the problems of designing management decision support systems for enterprises based on business analytics technology. The research purpose is to analyze the applied methodologies during the design stage of the enterprise information system, to develop principles for using management decision support systems based on business intelligence. The problem statement is to analyze the technologies available on the market, which deal with business analyst systems, their potential use for decision support systems, and to identify the main stages of business analyst for enterprises. Business intelligence (BI) is information that can be obtained from data contained in the operational systems of a firm, enterprise, corporation, or from external sources. The BI can help the management of a company make the best decision in the chosen sphere of human activity faster, and, consequently, win the competition in the market for goods and services. A decision support system (DSS) which uses business intelligence, is an automated structure designed to assist professionals in making decisions in a complex environment and to objectively analyze a subject area. The decision support system is the result of the integration of management information systems and database management systems (DBMS). The internal development of BI is more cost-effective. The methods used are Structured Analysis and Design Technique and Object-oriented methods. The results of the research: the analysis of the possibilities was conducted and recommendations relating to the use of BI within DSS were given. Competition between BI software in business analysts reduces the cost of products created making them accessible to end-users – producers, traders and corporations.
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Pfeifer, Marcel Rolf. "Computer-Aided Standardisation for Manufacturing and Maintenance Activities." Technological Engineering 16, no. 1 (October 1, 2019): 22–24. http://dx.doi.org/10.1515/teen-2019-0004.
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Abstract The paper deals with the development and application of computer-aided standardisation (CAS) for the distribution of standardisation data of production and maintenance processes within the company network. Rising integration pressure of company software tools also include CAx technologies. These CAx technologies provide software solutions for different applications, being able to work closely together with ERP-systems, Business Intelligence (BI) tools and further systems. The possibility of integration makes it also feasible to look on the CAS tool and its potential. While CAS is a topic not yet fully discussed, future development may lead to the requirement of integrating the CAS with the ERP and planning system. Approaches, such as CIM, digital factories (DF) and Industry 4.0 benefit from a broader database available with the CAS system employed
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PRIYATNA, ADE. "IMPLEMENTASI SISTEM PENUNJANG KEPUTUSAN MENGGUNAKAN BUSINESS INTELLIGENCE UNTUK UMKM DI GUNUNG PUTRI KAB.BOGOR." Jurnal Khatulistiwa Informatika 7, no. 1 (June 21, 2019): 7–12. http://dx.doi.org/10.31294/jki.v7i1.97.
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Ketersedian data dan informasi menjadi hal yang penting dalam proses pengambilan keputusan sebagai bahan analisa perkembangan UMKM atau organisasi, kebutuhan data dan informasi yang lengkap benar dan tepat juga menjadi kebutuhan bagi kelangsungan perkembangan UMKM ke depan. Sistem penunjang keputusan menggunakan business intelligence ini menggunakan tool pengolahan dari microsoft yaitu sql server integration services (SSIS) dan sql server reporting services (SSRS). Business Intelligenci juga dapat membantu sebuah UMKM atau organisasi untuk mendapatkan pengetahuan yang jelas mengenai faktor-faktor yang mempengaruhi kinerja organisasi sehingga dapat membantu organisasi dalam pengambilan keputusan serta sekaligus meningkatkan keunggulannya (competitive advantage). Business Intelligenci juga dapat membantu suatu organisasi dalam menganalisis perubahan tren yang terjadi sehingga akan membantu organisasi menentukan strategi yang diperlukan dalam mengantisipasi perubahan tren tersebut. penelitian ini bertujuan untuk memberikan hasil dashboard atau report yang nantinya akan digunakan sebagai bahan pengambilan keputusan. penelitian ini dilakukan pada UMKM di Gunung Putri Kab. Bogor. sumber data diperoleh dari sistem lama atau dari user kemudian diolah dengan sistem baru. hasil antara report sistem baru dan sistem lama kemudian dibandingkan menggunakan software spss untuk melihat presentase perbedaan nilainya.
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Kourtz, Peter. "Artificial intelligence: a new tool for forest management." Canadian Journal of Forest Research 20, no. 4 (April 1, 1990): 428–37. http://dx.doi.org/10.1139/x90-060.
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Articicial intelligence is a new science that deals with the representation, automatic acquisition, and use of knowledge. Artificial intelligence programs attempt to emulate human thought processes such as deduction, inference, language, and visual recognition. The goal of artificial intelligence is to make computers more useful for reasoning, planning, acting, and communicating with humans. Development of artificial intelligence applications involves the integration of advanced computer science, psychology, and sometimes robotics. Of the subfields that artificial intelligence can be broken into, the one of most immediate interest to forest management is expert systems. Expert systems involve encoding knowledge usually derived from an expert in a narrow subject area and using this knowledge to mimic his decision making. The knowledge is represented usually in the form of facts and rules, involving symbols such as English words. At the core of these systems is a mechanism that automatically searches for and pieces together the facts and rules necessary to solve a specific problem. Small expert systems can be developed on common microcomputers using existing low-cost commercial expert shells. Shells are general expert systems empty of knowledge. The user merely defines the solution structure and adds the desired knowledge. Larger systems usually require integration with existing forestry data bases and models. Their development requires either the relatively expensive expert system development tool kits or the use of one of the artificial intelligence development languages such as lisp or PROLOG. Large systems are expensive to develop, require a high degree of skill in knowledge engineering and computer science, and can require years of testing and modification before they become operational. Expert systems have a major role in all aspects of Canadian forestry. They can be used in conjunction with conventional process models to add currently lacking expert knowledge or as pure knowledge-based systems to solve problems never before tackled. They can preserve and accumulate forestry knowledge by encoding it. Expert systems allow us to package our forestry knowlege into a transportable and saleable product. They are a means to ensure consistent application of policies and operational procedures. There is a sense of urgency associated with the integration of artificial intelligence tools into Canadian forestry. Canada must awaken to the potential of this technology. Such systems are essential to improve industrial efficiency. A possible spin-off will be a resource knowledge business that can market our forestry knowledge worldwide. If we act decisively, we can easily compete with other countries such as Japan to fill this niche. A consortium of resource companies, provincial resource agencies, universities, and federal government laboratories is required to advance this goal.
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Wynn, Martin George, and Daniel Brinkmann. "Exploiting Business Intelligence for Strategic Knowledge Management." International Journal of Business Intelligence Research 7, no. 1 (January 2016): 11–24. http://dx.doi.org/10.4018/ijbir.2016010102.
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In the German healthcare industry, Business Intelligence systems play a crucial role. For one major health insurance company (discussed here as an alias - AK Healthcare), the deployment of Business Intelligence applications has supported sustained growth in turnover and market share in the past five years. In this article, these tools are classified within an appropriate conceptual framework which encompasses the organisation's information infrastructure and associated processes. Different components of the framework are identified and examples are given - systems infrastructure, data provision/access control, the BI tools and technologies themselves, report generation, and information users. The use and integration of Business Intelligence tools in the strategy development process is then analyzed. Finally, the key functions and features of these tools for strategic knowledge management are discussed. Research findings encompass system access, report characteristics, and end-users profiles and capabilities.
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O'Leary, Daniel E., and John Kingston. "Artificial intelligence in business II: Development, integration and organizational issues." Knowledge Engineering Review 9, no. 1 (March 1994): 1–19. http://dx.doi.org/10.1017/s026988890000655x.
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AbstractThe purpose of this paper is to review the use of knowledge-based systems and artificial intelligence (AI) in business. Part I of this paper provided a broad survey of the use of AI in business, summarizing the application of AI in a number of business domains. In addition, it also provided a summary of the use of different forms of knowledge representation in business applications. Part I has a large set of references, including a number of survey papers, focusing on AI in business. Part II of this paper consists of more detailed analysis of particular systems or issues affecting AI in business. It examines technical issues which are central to the construction of business AI systems, and it also examines the commercial contribution made by methods for the development of AI systems. In addition, part II looks at integration between AI and more traditional information systems. AI can be used to add value to many existing information systems, such as database management systems. Particular attention is given to the integration of AI with operations research, which is the one of the primary “competitors” of AI, providing an alternative set of support tools for decision making.Business organizations are not concerned only with technology issues; there is also concern about the impact of AI on organizations. Further, the evaluation of AI often is based on an economic view of the world. Part II therefore investigates the organizational impact of AI, and the economics of AI, including issues such as value creation. The format of Part II is as follows: Section 8 analyses techniques for improving the performance of AI systems, thus maximizing economic return. Section 9 looks at different forms of uncertainty and ambiguity which must be dealt with by AI systems. It examines the contributions of fuzzy logic and numerical measures of certainty to handling these problems. Section 10 examines the usefulness of different approaches to knowledge acquisition in business situations, and investigates the benefits of methodological approaches to AI applications. It also looks at more recent AI programming techniques which eliminate the need for knowledge elicitation from an expert: neural networks, case-based reasoning and genetic algorithms are discussed. Sections 11 and 12 examine issues of integrating AI systems. Generally, the use of AI in business settings must ultimately be integrated with the broader base of corporate information systems. Section 11 looks at integration with information systems in general, and section 12 looks particularly at integration with operations research. Sections 13 and 14 review the organizational and economic impact of AI. Finally, section 15 provides a brief summary of part II.
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Ristyawan, Mochammad Ridwan. "Artificial Neural Network and Analytical Hierarchy Process Integration: A Tool to Estimate Business Strategy of Bank." 11th GLOBAL CONFERENCE ON BUSINESS AND SOCIAL SCIENCES 11, no. 1 (December 9, 2020): 66. http://dx.doi.org/10.35609/gcbssproceeding.2020.11(66).
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The disruption has been occurring in financial services. Rethinking new strategy of banking is needed to make a sustainable competitive advantage innovation in organizations. The four types of business strategy for banks are prospector, analyzer, defender, and reactor. Studies mentioned that formulating strategy is very costly, time consuming, and comprehensive analysis. The banks have to get rid of execution time inefficiency, lack of flexibility, and lack of ability to present several scenarios in the dynamic business environment. The purpose of this study is to present an integrated intelligence algorithm for estimating strategic resources of the bank strategy in Indonesia. The algorithm has two basic modules which are artificial neural network (ANN) and analytical hierarchy process (AHP). ANN is utilized as an inductive algorithm in discovering predictive strategy of the bank and used to explain the strategic resources which improved in forward. AHP has the capability to handle multi-level decision-making structure with use of expert judgments in pairwise comparison process. AHP is used to measure the weight of the resources and the score is used to determine the strategy. The empirical results indicate that ANN and AHP integration is proved to predict the business strategy of the bank. The strategy choice appropriate with the condition of bank's resources. This framework can be implemented to help banker for the decision making in bank operation. Keywords: business strategy, ANN, AHP, resources
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Yu, Shi Dong, Peng Wu, Yuan Ding, and Feng Gao. "Study on Intelligent Maintenance Service Mechanism and Realization." Applied Mechanics and Materials 644-650 (September 2014): 6355–57. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.6355.
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Taking on the features of agility, intelligence, Internet and socialization in the wake of rapid expansion of global manufacture and cutthroat competition, to establish an e-intelligence maintenance system is crucial for manufacturing enterprise to reduce costs and increase profits in the global market. Based on the analysis of requirement for e-intelligence maintenance in manufacturing industry of our country, this paper puts forward the remote coordination mechanism, the risk control mechanism and the security mechanism. Then explores the eMS strategy formation and optimization which based on Case-based reasoning, intelligent evaluation model of eMS and an effective integration schemes of realizing an enterprise web e-manufacturing and an e-business tool.
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Eger, Robert J., and Christy Smith. "Integrated Business Intelligence and Analytics: The Case of the Department of the Navy." Journal of Governmental & Nonprofit Accounting 10, no. 1 (January 1, 2021): 26–49. http://dx.doi.org/10.2308/jogna-17-001.
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ABSTRACT From a stakeholder perspective, this study explores the viability of data analytics as a tool in government fraud prevention. Using an interview methodology, we analyze the implications of business intelligence and analytics fraud tools on procurement stakeholders. We find that implementing and integrating business intelligence and a fraud program streamlines processes by consolidating information and presenting data within a unique program. The functioning data analytics program increases our stakeholders' confidence level without alleviating their responsibility to perform due diligence in their management functions. Our stakeholders recognized a potential increase in workload; however, they acknowledged no perceived increase in undue administrative burden. JEL Classifications: M48. Data Availability: Data are available from the authors.
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Ristyawan, Mochammad Ridwan. "Artificial Neural Network and Analytical Hierarchy Process Integration: A Tool to Estimate Business Strategy of Bank." GATR Journal of Finance and Banking Review VOL. 5 (4) JAN-MAR. 2021 5, no. 4 (March 29, 2021): 01–09. http://dx.doi.org/10.35609/jfbr.2021.5.4(1).
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Objective – The disruption has been occurring in financial services. Thus, rethinking a new strategy for banking is needed to make a sustainable innovation in organizations. Studies mentioned that formulating strategy is a very costly, time-consuming, and comprehensive analysis. The purpose of this study is to present an integrated intelligence algorithm for estimating the bank’s strategy in Indonesia. Methodology – This study used the integration model between two modules. The algorithm has two basic modules, called Artificial Neural Network (ANN) and Analytical Hierarchy Process (AHP). AHP is capable of handling a multi-level decision-making structure with the use of five expert judgments in the pairwise comparison process. Meanwhile, ANN is utilized as an inductive algorithm in discovering the predictive strategy of the bank and used to explain the strategic factors which improved in forward. Findings and Novelty – The empirical results indicate that ANN and AHP integration was proved to predict the business strategy of the bank in five scenarios. Strategy 5 was the best choice for the bank and Innovate Like Fintechs (ILF) is the most factor consideration. The strategy choice was appropriate for the condition of the bank’s factors. This framework can be implemented to help bankers to decide on bank operations. Type of Paper: Empirical JEL Classification: M15, O32. Keywords: Bank’s strategy, ANN, AHP, BSC, Indonesia. Reference to this paper should be made as follows: Ristyawan, M.R. (2021). Artificial Neural Network and Analytical Hierarchy Process Integration: A Tool to Estimate Business Strategy of Bank, Journal of Finance and Banking Review, 5(4): 01 – 09. https://doi.org/10.35609/jfbr.2021.5.4(1)
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Ajibade, Patrick, Ezra M. Ondari-Okemwa, and Mamadi M. Matlhako. "Information technology integration for accelerated knowledge sharing practices: challenges and prospects for small and medium enterprises." Problems and Perspectives in Management 17, no. 4 (November 26, 2019): 131–40. http://dx.doi.org/10.21511/ppm.17(4).2019.11.
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This paper argues that business enterprises in this competitive global market cannot compete and remain sustainable without effective knowledge sharing to improve business intelligence processes. The central argument hinges on the deployment and use of information technology (IT) as strategic tools to promote business decision making through quick business data analysis and dissemination of business ideas across business units and locations. The study reiterated the critical role IT plays in facilitating a culture of organizational learning and knowledge sharing practices. The study utilized surveys and questionnaires that were distributed to 230 small and medium enterprises (SMEs), and both descriptive and inferential statistics were used to present the results. Findings showed that firms are still using one-on-one meeting to share knowledge, while knowledge sharing activities are controlled through a rigid and inflexible process at the top management level, thereby hindering knowledge flow that is crucial for real-time decision making. The advances in IT have not been used advantageously to improve knowledge sharing and to advance business management. The paper concludes that without strong positive correlation between IT infrastructure integration, and communication strategies and knowledge sharing, the SMEs may not be able to compete in a highly competitive knowledge economy. Consequently, they may lose leverage to another competitor with more robust and mature IT infrastructure alignment for sharing business analytics and intelligence efficiently. A technologically driven, open, and informal approach to knowledge sharing for productive and innovative engagement is recommended. Furthermore, the use of IT that can promote agile and real-time knowledge sharing is recommended.
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Janakova, Milena. "Visualization and Simulation for the Analysis of Business Intelligence Products." International Journal of E-Entrepreneurship and Innovation 2, no. 4 (October 2011): 20–31. http://dx.doi.org/10.4018/jeei.2011100102.
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This paper analyzes information technology products for improvement existing solutions and implementations. Selected products are Business Intelligence (BI) applications in comparison with Customer Relationship Management (CRM), database and operating systems. The subject of interest is the architecture. BI architecture is less sophisticated in regard to adopted arrangements for other products. The best resolution offers an Oracle database system. This arrangement helps provide extraordinary stability to the given system. Operating systems have minimalist architecture with necessary processes and configuration files; similarly as for CRM products. BI architecture is without order, with items as tools for end users, component analysis, database components, components for data transformation and integration, and system sources. The solution is to merge the system source with methods for their transformation, and tools for end users with component analysis. Presented analysis is based on Petri Nets.
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Lokaadinugroho, Indrabudhi, Abba Suganda Girsang, and Burhanudin Burhanudin. "Tableau Business Intelligence Using the 9 Steps of Kimball’s Data Warehouse & Extract Transform Loading of the Pentaho Data Integration Process Approach in Higher Education." Engineering, MAthematics and Computer Science (EMACS) Journal 3, no. 1 (January 31, 2021): 1–11. http://dx.doi.org/10.21512/emacsjournal.v3i1.6816.
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This paper discusses about how to build a data warehouse (DW) in business intelligence (BI) for a typical marketing division in a university. This study uses a descriptive method that attempts to describe the object or subject under study as it is, with the aim of systematically describing the facts and characteristics of the object under study precisely. In the elaboration of the methodology, there are four phases that include the identification and source data collection phase, the analysis phase, the design phase, and then the results phase of each detail in accordance with the nine steps of Kimball’s data warehouse and the Pentaho Data Integration (PDI). The result is a tableau as a tool of BI that does not have complete ETL tools. So, the process approach in combining PDI and DW as a data source certainly makes a tableau as a BI tool more useful in presenting data thus minimizing the time needed to obtain strategic data from 2-3 weeks to 77 minutes.
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Shershakov, Sergey A. "“VTMine for Visio”: Graphical Tool for Modeling in Process Mining." Modeling and Analysis of Information Systems 27, no. 2 (June 24, 2020): 194–217. http://dx.doi.org/10.18255/1818-1015-2020-2-194-217.
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Process-Aware Information Systems (PAIS) is a special class of the IS intended for the support the tasks of initialization, end-to-end management and completion of business processes. During the operation such systems accumulate a large number of data that are recorded in the form of the event logs. Event logs are a valuable source of knowledge about the actual behavior of a system. For example, there can be found information about the discrepancy between the real and the prescribed behavior of the system; to identify bottlenecks and performance issues; to detect anti-patterns of building a business system. These problems are studied by the discipline called “Process Mining”.The practical application of the process mining methods and practices is carried out using the specialized software for data analysts. The subject area of the process analysis involves the work of an analyst with a large number of graphical models. Such work will be more efficient with a convenient graphical modeling tool. The paper discusses the principles of building a graphical tool “VTMine for Visio” for the process modeling, based on the widespread application for business intelligence Microsoft Visio. There are presented features of the architecture design of the software extension for application in the process mining domain and integration with the existing libraries and tools for working with data. The application of the developed tool for solving various types of tasks for modeling and analysis of processes is demonstrated on a set of experimental schemes.
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Panteleeva, Tatiana A. "Opportunities and threats of using artificial intelligence in the business foresight of Russian companies." Market economy problems, no. 1 (2021): 131–48. http://dx.doi.org/10.33051/2500-2325-2021-1-131-148.
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Subject/Topic. The article is devoted to the study of the possibilities and threats of using scientific intelligence in the business foresight and its impact on the business potential of the business in the short and long term. Methodology. In the process of writing the article, general scientific and philosophical methods of knowledge were used, as well as special economic methods based on them. Especially, the articles of the object of research – artificial intelligence – as the current process necessitated the use of problem-chronological and historical-genetic methods, which made it possible to distinguish the main stages of the formation of ideas, concepts, theories and methods for the use of artificial intelligence in business foresight, and the historical-genetic method showed the inseparability and intersectability from one stage to another of the development of the conceptual and methodological apparatus of the object of scientific research. Results. Currently, in business practice, artificial intelligence is used as a foresight tool very individually, since the complexity of its development and significant investments in the landscape infrastructure of its functioning form objective barriers to its rapid spread in the business environment. Currently, the following models of artificial intelligence are used in the business force: anthropocentric, hybrid, instrumental, machine-centric. According to the above calculations, starting from 2020, active growth is expected in the segment of business and IT services using artificial intelligence, it is also expected to increase spending on R&D projects in the field of development of products with artificial intelligence, and the most forward-specific from the point of view of investing capital and development as part of their own business model of AI directions on the horizon 2018-2025 are technologies for remote access (VDI, BKC, online communications, control), AI/ML (artificial intelligence, machine learning), VR/AR (virtual and augmented reality). Conclusions/Significance. In general, in 2020 compared to 2019, the optimism and motivation of the business to introduce artificial intelligence clearly showed a decline, and it should also be noted that the goals set by managers have become more «grounded»: in 2020, 45% spoke in favor of using artificial intelligence as a means of forming their own Big Data libraries, another 45% – for the integration of the artificial intelligence mechanism and existing systems for analysis and collection of information, however, a modern business strategy is not possible without processing huge amounts of customer information, and given their weak structuring and localization in multiple sources, the speed and quality of their processing and interpretation without the use of machine learning mechanisms became economically impractical. Application. The results of the scientific research will be useful both for educational purposes for students and readers interested in the use of artificial in-tech in business management, and for practitioners who plan to use artificial intelligence in foresight business processes.
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Labonte-LeMoyne, Elise, Pierre-Majorique Leger, Jacques Robert, Gilbert Babin, Patrick Charland, and Jean-François Michon. "Business intelligence serious game participatory development: lessons from ERPsim for big data." Business Process Management Journal 23, no. 3 (June 5, 2017): 493–505. http://dx.doi.org/10.1108/bpmj-12-2015-0177.
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Purpose A major trend in enterprise resource planning software (ERP) is to embed business analytics tools within user-centered roles in enterprise software. This integration allows business users to get better and faster insight to action. As a consequence, it is imperative for business students to learn how to use these new tools to adequately prepare them for new expectations in the industry. The paper aims to discuss these issues. Design/methodology/approach In this paper, the authors propose a new serious game, called ERPsim for big data, to enable the learner to acquire abilities at each level of the business analytics learning taxonomy. To maximize the pedagogical impact of the game, participatory design (PD) with professors as co-designers was used during game development. Findings This case study presents the PD approach and analyses the efficacy of the proposed new simulation. Originality/value The authors conclude by providing recommendations and lessons learned from this approach.
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George, Joseph, and Dr Jeyakumar M.K. "A Comparative Analysis of Data Integration and Business Intelligence Tools with an Emphasis on Healthcare Data." International Journal of Engineering Trends and Technology 68, no. 9 (September 25, 2020): 5–9. http://dx.doi.org/10.14445/22315381/ijett-v68i9p202.
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Handika, I. Putu Susila. "Perancangan datawarehouse dan teknologi business intelligence untuk analisa penjualan pada perusahaan retail PT. ABC." Rabit : Jurnal Teknologi dan Sistem Informasi Univrab 5, no. 2 (July 20, 2020): 76–85. http://dx.doi.org/10.36341/rabit.v5i2.1309.
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PT. ABC merupakan salah satu perusahaan yang bergerak dibidang retail. PT. ABC sudah memiliki 378 toko yang tersebar di Bali, Lombok, dan makassar. Saat ini PT. ABC memiliki sistem POS kasir dan warehouse management system untuk membantu menjalankan proses bisnisnya. Permasalahan yang sering terjadi adalah ketika data sudah semakin banyak, proses analisis data menjadi kurang optimal karena data yang diproses sangat banyak dan user yang menggunakan sistem semakin banyak. Dengan demikian diperlukan datawarehouse dan teknologi business intelligence untuk mengolah data dan memvisualisasikan data menjadi informasi yang dapat dengan mudah dianalisa oleh pemangku kepentingan. Metode pemodelan datawarehouse yang digunakan pada penelitian ini adalah metode nine steps kimball, untuk proses ETL digunakan tools dari pentaho data integration, dan proses visualisasi data digunakan tools power business intelligence agar dapat menampilkan data dalam bentuk grafik sehingga pemangku kepentingan dapat menganalisa data dengan cepat dan mudah. Penerapan datawarehouse dan teknologi business intelligence dapat digunakan dan menghasilkan informasi yang sesuai dengan kebutuhan yang didapat pada analisa kebutuhan fungsional. Hal tersebut dibuktikan dengan hasil pengujian black box yang sudah diterima oleh pemangku kepentingan PT. ABC.
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Gallego-Gomez, Cristina, and Carmen De-Pablos-Heredero. "Artificial Intelligence as an Enabling Tool for the Development of Dynamic Capabilities in the Banking Industry." International Journal of Enterprise Information Systems 16, no. 3 (July 2020): 20–33. http://dx.doi.org/10.4018/ijeis.2020070102.
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Banks are investing in artificial intelligence (AI) to develop more innovative business models in order to face competition. The main objective of this paper consists in analyzing bank experiences when they introduce AI from the theory of dynamic capabilities and the resource-based view approach. Documentary research enables the description of experiences in three companies from the financial industry. It has been considered of interest to include different international experiences. For that reason, a firm providing debit and credit card services has been included, MasterCard, along with international banks such as Royal Bank of Scotland and Caixa Bank. Results show that AI enables firms to promote new relationships with customers, detect their needs or experiences, and adapt the service given by firms to be more competitive. AI also allows them to speed up responses to customers answers and doubts through its value chain. This research also shows that the proper implementation of AI permits a reconfiguration of traditional banking scenario. Detection, absorption, integration, and innovation are capabilities that allow these firms to build the managerial skills oriented to save costs, increase efficiency, and be more competitive.
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Guerrero-Contreras, Gabriel, José L. Navarro-Galindo, José Samos, and José Luis Garrido. "A Collaborative Semantic Annotation System in Health: Towards a SOA Design for Knowledge Sharing in Ambient Intelligence." Mobile Information Systems 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/4759572.
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People nowadays spend more and more time performing collaborative tasks at anywhere and anytime. Specifically, professionals want to collaborate with each other by using advanced technologies for sharing knowledge in order to improve/automatize business processes. Semantic web technologies offer multiple benefits such as data integration across sources and automation enablers. The conversion of the widespread Content Management Systems into its semantic equivalent is a relevant step, as this enables the benefits of the semantic web to be extended. The FLERSA annotation tool makes it possible. In particular, it converts the Joomla! CMS into its semantic equivalent. However, this tool is highly coupled with that specific Joomla! platform. Furthermore, ambient intelligent (AmI) environments can be seen as a natural way to address complex interactions between users and their environment, which could be transparently supported through distributed information systems. However, to build distributed information systems for AmI environments it is necessary to make important design decisions and apply techniques at system/software architecture level. In this paper, a SOA-based design solution consisting of two services and an underlying middleware is combined with the FLERSA tool. It allows end-users to collaborate independently of technical details and specific context conditions and in a distributed, decentralized way.
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Schuh, Günther, Stefan Rudolf, Martin Pitsch, Martin Sommer, and Wilhelm Karmann. "Modular Service-Oriented Cyber-Physical Systems for the European Tool Making Industry." Applied Mechanics and Materials 752-753 (April 2015): 1349–55. http://dx.doi.org/10.4028/www.scientific.net/amm.752-753.1349.
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Manufacturing companies in high-wage countries are facing rising challenges in a global market. Increasing customer demands for a higher degree of individualization result in smaller lot sizes and higher variety of products. In addition, competitors from low-wage countries in Asia and Eastern Europe have significantly improved their technical capabilities, resulting in a more competitive environment. The tool making industry provides its customers with the means to achieve excellence in production due to its unique position in the value chain between product development and the serial production of parts. A tool making company’s ability to improve the efficiency of serial production and develop innovative product design is strongly dependent on its capability of integrating itself into the preceding and following customer processes. Over the last years, customer demands for global sourcing of tools have changed from low prices to the demands of extended tool operating life and high operational availability. European tool making companies have learned to take this development as a chance to differentiate themselves from global competitors and subsequently increase their range of services up- and downstream the value chain. As a result, new industrial product-service-systems (IPS²) for the European tool making industry need to be developed that address the demand of a higher degree of integration into the preceding and following customer processes. Within the German Government founded research project “Smart Tools”, an industrial product-service-system (IPS²) for the tool making industry has been developed based on a modular service-oriented cyber-physical system. Core element of the cyber-physical system is the smart tool – an injection molding tool equipped with state-of-the-art sensor technology to capture data on the condition of the tool during its operational use. Its intelligence derives from the condition based interpretation and data management of the collected process data which is also the basis for the design of customer specific services. Besides the successful integration of force and position sensors into the tool, experimental research has delivered important results on the application of solid borne sound sensors for online early detection of tool wear. An innovative concept for the distribution and interpretation of the process data incorporates the specific requirements of the customers. To cope with the demands of individual and small series production in the tool making industry, a modular sensor kit has been developed together with a diagnostic unit for data interpretation and storage of data in an electronic tool book. The developed modular service-oriented cyber-physical system delivers the means to extended tool operating life and improves the overall efficiency of serial production. Based on the results new business models can be developed for tool making companies to differentiate themselves from global competitors and overcome the challenges of production in high-wage countries.
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Akbar, Ricky, Vedo Alfarizi, Tata Bayu Amarta, Nazhifa Najla Ardian, and Mahfuz Jailani Ibrahim. "Implementasi Business Intelligence untuk Mendapatkan Pola Penerbangan Penumpang Pesawat dari atau ke Bandara Internasional Minangkabau." Jurnal Edukasi dan Penelitian Informatika (JEPIN) 4, no. 1 (June 25, 2018): 65. http://dx.doi.org/10.26418/jp.v4i1.25580.
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Pesawat udara saat ini sangat diminati untuk perjalanan jauh bagi pengguna jasa penerbangan baik untuk perjalanan pariwisata maupun perjalanan bisnis. Akibatnya, aktifitas penerbangan selalu ramai. Oleh karenanya, perusahaan pengelola bandar udara memiliki manajemen terkait penjadwalan penerbangan. Kumpulan dari jadwal penerbangan yang bervariasi ini menghasilkan data yang disebut flight daily report. Perkembangan teknologi memiliki penemuan baru untuk memanfaatkan data sebagai hal penting dalam kemajuan bisnis. Salah satunya adalah dengan penerapan business intelligence. Peneliti akan menerapkan business intelligence untuk mendapatkan pola penerbangan penumpang menggunakan data Flight Daily Report (FDR) Bandara Internasional Minangkabau tahun 2017. dengan mendapatkan pola penerbangan kita sebagai pengguna jasa penerbangan dapat mengetahui kapan jadwal padat bandar udara, serta dapat mengetahui kapan orang-orang cendrung melakukan perjalanan udara dari atau ke Bandara Internasioanal Minangkabau (BIM). Tools yang digunakan untuk penelitian ini adalah Pentaho Data Integration dan Microsoft Power BI. Hasil penelitian berupa grafik dari data Flight Daily Report (FDR) Bandara Internasional Minangkabau tahun 2017 yang telah diproses sehingga dapat kita analisa dan simpulkan bahwa jadwal penerbangan tersibuk terjadi pada pukul 14.10 WIB yaitu untuk waktu kedatangan. Kata kunci ― business intelligence, pentaho, Microsoft Power BI, Pola Penerbangan, BIM
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Flaherty, Stephen, Robert Savage, Ingrid Stendhal, Susan Roston, Abhijeet Makhe, and Veronica Mead. "Integration of a cancer registry dataset into a hospital-wide central data warehouse." Journal of Clinical Oncology 32, no. 30_suppl (October 20, 2014): 212. http://dx.doi.org/10.1200/jco.2014.32.30_suppl.212.
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212 Background: The ability to link cancer registry data to clinical and administrative data sets for quality improvement has long been desired. We sought to integrate registry data into a central data warehouse in an effort to make available for the first time consistent and reliable diagnosis and staging data to a broad hospital user group. Methods: After a short period of data analysis, the tables for Cancer Registry data (Oracle) were modeled. The source data (SQL Server) was conformed and integrated using an ETL tool (Informatica). All ETL QA work was performed with SQL queries. Cancer registry data was integrated into reporting architecture (Microstrategy) to facilitate design of standardized and ad hoc reports. Results: 140 distinct fields on demographics, staging (clinical, pathological, collaborative), site specific categories, diagnosis, and treatment were integrated into the Dana-Farber Analytics Reporting Tool (DART) for historic Cancer Registry data beginning with January 2010 newly diagnosed cancers. All Cancer Registry data and patient files (new and old) are updated in DART on a monthly basis. Conclusions: Individuals across the hospital now have the ability to link clinical and administrative data from our EMR, institutional QI data from varied systems, and pharmacy data to Cancer Registry data in the DART tool. One example of the integration of these multiple data sets is the linkage of staging data from the Cancer Registry data set and time to referral data from the administrative data set by patient MRN. As DFCI aims to cohort its patients based on their primary diagnosis for quality improvement and other internal reporting needs, the ability to analyze patients in this way becomes critical. This project sets an example for other centers as they integrate Cancer Registry data into user friendly business intelligence systems to help meet federal reporting mandates and aid internal improvement work. [Table: see text]
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Azeroual, Otmane, and Horst Theel. "The Effects of Using Business Intelligence Systems on an Excellence Management and Decision-Making Process by Start-Up Companies: A Case Study." INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE AND BUSINESS ADMINISTRATION 4, no. 3 (2018): 30–40. http://dx.doi.org/10.18775/ijmsba.1849-5664-5419.2014.43.1004.
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The rapid increase in data volumes in companies has meant that momentous and comprehensive information gathering is barely possible by manual means. Business intelligence solutions can help here. They provide tools with appropriate technologies to assist with the collection, integration, storage, editing, and analysis of existing data. While almost only large companies were interested in this topic a few years ago, it has meanwhile also become necessary for start-up companies, and so the market for business intelligence has been growing for years. This article focuses on the general potentials of using BI in start-ups. First, will be examined which providers of BI solutions that are suitable for start-ups and what opportunities exist for implementing BI systems in start-ups. Then it will be shown to what extent BI has prevailed in start-ups, in which areas the techniques of BI are used in start-ups and what purpose BI has in start-ups. Finally, the success factors for BI projects in start-ups are considered.
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Rouhani, Saeed, and Sogol Rabiee Savoji. "A Success Assessment Model for BI Tools Implementation." International Journal of Business Intelligence Research 7, no. 1 (January 2016): 25–44. http://dx.doi.org/10.4018/ijbir.2016010103.
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In today's rapidly-changing business environment, the need for useful business analytics is vital for organizations, not only to succeed, but also to survive. Traditional enterprise systems have disabilities to meet the expectations of organizational decision makers in the competitive area. In this regard, it is necessary to evaluate the success of BI tools in organizations, and there is a need to provide a model for this assessment. Hence, in this study, a model for assessing the success of business intelligence is presented by identifying and introducing the most important and effective factors in evaluating the success of BI tools. This study is an applied study in terms of purpose and a survey-descriptive, empirical study in terms of methodology. According to statistical methods, importance of the success factors was evaluated and the results show that 24 factors were identified consequential in research model based on four areas such as organizational memory, information integration, knowledge creation, and presentation.
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Veingerl Čič, Živa, Matjaž Mulej, and Simona Šarotar Žižek. "Different intelligences’ role in overcoming the differences in employee value system." Kybernetes 47, no. 2 (February 5, 2018): 343–58. http://dx.doi.org/10.1108/k-06-2017-0200.
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Purpose This paper aims to present the findings of the research about the role of different intelligences in overcoming the differences in employee value system as a source of success. Design/methodology/approach Based on their previous research, the authors used desk and informal field research, the Dialectical Systems Theory and its Law of Requisite Holism. Findings The integration of one’s personal development with one’s individual intelligence influences human value systems. Knowledge and developing of various types of intelligence matter: it lets individuals develop faster, in the long run. The higher one’s level of intelligence is, the easier one finds it to face problems or experience. Thus, one is becoming a mature personality, who can overcome extreme alternatives to the briefed human values. This process can also receive meaningful support from the exercise of social responsibility, which is one’s responsibility for one’s impacts on society, i.e. people and nature. Success of the process depends on “personal requisite holism”. The top managers need significantly more emotional and social competences than the others. Research limitations/implications The topic is researched with qualitative analysis in desk and informal field research. Quantitative methodological approach took place in the authors’ cited previous publications. Practical implications Work distribution makes the leaders and subordinates differ in prevailing values, too. Mastering of these differences will support business success, survival of jobs included and well-being of coworkers from both groups. Application of the cognitive, emotional and spiritual intelligences might help the organization meet this need. The fourth – physical intelligence – supports ensuring the psychological well-being at work; from this, other mentioned intelligences have been developed. Mastering of these differences can also receive support from methods of creative cooperation, social responsibility and personal requisite holism; the authors have reported about these elsewhere, and only point to these in this study. Social implications The more holistic intelligences system generates a more socially responsible society. Originality/value No similar concept is offered in the available literature.
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Iyer, Lakshmi S., and Rajeshwari M. Raman. "Intelligent Analytics." International Journal of Business Intelligence Research 2, no. 1 (January 2011): 31–45. http://dx.doi.org/10.4018/jbir.2011010103.
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Organizations use web analytic tools and technologies to measure, collect, analyze, and report web usage data to help optimize websites. Traditionally, most of this data tends to be non-transactional and non-identifiable. In this regard, there has not been much integration with transactional data that is collected, stored, analyzed, and reported through Business Intelligence (BI). Emerging trends in web analytics provide organizations the ability to aggregate and analyze web analytics data with transactional data to provide valuable insights for building better customer relationship strategies. In this paper, the authors give an overview of web analytics tools, key players, new technology trends and capabilities to integrate web analytics with BI so organizations can leverage intelligent analytics for new marketing initiatives. While the benefits are significant, there are some challenges associated with the integration and a few possible solutions to address.
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SUNKPHO, Jirapon, and Warit WIPULANUSAT. "The Role of Data Visualization and Analytics of Highway Accidents." Walailak Journal of Science and Technology (WJST) 17, no. 12 (December 1, 2020): 1379–89. http://dx.doi.org/10.48048/wjst.2020.10739.
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Thailand has been ranked as one of the most dangerous countries in terms of death from road accidents, representing ineffective road safety policies. The crucial mission of the Thai government is to provide safety and reduce accidents for road users on the highway system. This paper aims to explore the potential of using Business Intelligence (BI) in accident analysis. The availability of open accident data provides an opportunity for the BI, which can provide an advanced platform for conducting data visualization and analytics in both spatial and temporal dimensions in order to illustrate when and where the accidents occur. The accident data and provincial data were combined by using the Talend Data Integration tool. The combined data was then loaded into a MySQL database for data visualization using Tableau. The dashboard was designed and created by using Tableau as an analytical visualization tool to provide insights into highway accidents. This system is advised to be adopted by the Thai government, which can be used for data visualization and analytics to provide a mechanism to formulate strategy options and formulate appropriate contingency plans to improve the accident situation.
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Marengo, Agostino, Alessandro Pagano, and Alessio Barbone. "An Assessment of Customer’s Preferences and Improve Brand Awareness Implementation of Social CRM in an Automotive Company." International Journal of Technology Diffusion 4, no. 1 (January 2013): 1–15. http://dx.doi.org/10.4018/jtd.2013010101.
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The huge amount of online conversations that arises from the new means of communication between users, if analyzed and capitalized, is an important resource for companies and brands alike. Thus, a fundamental tool for the management of the relationship with customers such as CRM seems to be exceeded. The concept of a Social CRM platform was born with the objective of filling the gap between brand and customers connected to various social networks, allowing both parties to achieve tangible benefits from active participation. The key objective of this research involves the implementation of a Social CRM system, which is not yet present on the automotive market. The work starts through the identification and implementation of an experimental prototype that can define and highlight a methodological and technological best practice in the integration of heterogeneous components of an information system composed of independent software and continues with the definition of an integrated system that allows innovative Business Intelligence activities.
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Bimonte, Sandro, Omar Boucelma, Olivier Machabert, and Sana Sellami. "A Generic Spatial OLAP Model for Evaluating Natural Hazards in a Volunteered Geographic Information Context." International Journal of Agricultural and Environmental Information Systems 5, no. 4 (October 2014): 40–55. http://dx.doi.org/10.4018/ijaeis.2014100102.
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Spatial data warehouses (SDW) and spatial OLAP (SOLAP) systems are well-known business intelligence technologies that aim to support a multidimensional and online analysis for a large volume of geo-referenced datasets. SOLAP systems are already used in the context of natural hazards for analyzing sensor data and experts' measurements. Recently, new data gathering tools coined as volunteered geographic information systems (VGI) have been adopted especially by non-expert users. Hence, (spatial) application development is facing a new challenge, which is the integration of expert-oriented data with citizen-provided data. In this paper, we propose a new generic spatio-multidimensional model based on the question/answer risk evaluation model that allows the integration of VGI data with classical SDW and SOLAP systems for the online analysis of natural hazards monitored by volunteers.
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Yablonsky, Sergey. "A multidimensional platform ecosystem framework." Kybernetes 49, no. 7 (April 3, 2020): 2003–35. http://dx.doi.org/10.1108/k-07-2019-0447.
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Purpose Ecosystems that support digital businesses maximize the economic value of network connections. This forces a shift toward platforms and ecosystems that are collaborative by nature by applying business models with multiple actors playing multiple roles. The purpose of this study is to show how the main concepts emerging from research on digital platform ecosystems (DPEs) could be organized in a taxonomy-based framework with different levels or dimensions of analysis. This study discusses some of the contingencies at these different levels and argues that future research needs to study DPEs across multiple levels of analysis. While this integrative framework allows the comparison, contrast and integration of various perspectives at different levels of analysis, further theorizing will be needed to advance the DPE research. The multidimensional framework proposed here involves the use of a multimethodological approach that incorporates a synergy of businesses, technological innovations and management methods to provide support for research in interrelationships across platform ecosystems (PEs) on a regular basis. Design/methodology/approach This paper proposes a new PE framework by constructing a formal taxonomy model that explains a vast group of phenomena produced by the PEs. Findings In addition to illustrating the PE taxonomy framework, this study also proposes a clear and precise description and structuring of the information in the ecosystem domain. The PE framework assists in identification, creation, assessment and disclosure research of platform business ecosystems. Research limitations/implications Because of the large number of taxonomy concepts (over 200), only main taxonomy fragments are shown in the paper. Practical implications The outcomes of this research could be used for planning, oversight and control over ecosystem management and the use of ecosystem’s knowledge-related resources for research purposes. Originality/value The PE framework is original and represents an effective tool for observing PEs.
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Garcia-Muiña, Fernando, Rocío González-Sánchez, Anna Ferrari, and Davide Settembre-Blundo. "The Paradigms of Industry 4.0 and Circular Economy as Enabling Drivers for the Competitiveness of Businesses and Territories: The Case of an Italian Ceramic Tiles Manufacturing Company." Social Sciences 7, no. 12 (December 4, 2018): 255. http://dx.doi.org/10.3390/socsci7120255.
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Sustainable development and the circular economy are two important issues for the future and the competitiveness of businesses. The programs for the integration of sustainability into industrial activities include the reconfiguration of production processes with a view to reducing their impact on the natural system, the development of new eco-sustainable products and the redesign of the business model. This paradigm shift requires the participation and commitment of different stakeholder groups and industry can completely redesign supply chains, aiming at resource efficiency and circularity. Developments in key ICT technologies, such as the Internet of Things (IoT), help this systemic transition. This paper explores the phases of the transition from a linear to a circular economy and proposes a procedure for introducing the principles of sustainability (environmental, economic and social) in a manufacturing environment, through the design of a new Circular Business Model (CBM). The new procedure has been tested and validated in an Italian company producing ceramic tiles, using the digitalization of the production processes of the Industry 4.0 environment, to implement the impact assessment tools (LCA—Life Cycle Assessment, LCC—Life Cycle Costing and S-LCA—Social Life Cycle Assessment) and the business intelligence systems to provide appropriate sustainability performance indicators essential for the definition of the new CBM.
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Gupta, M. P., and Sanjay. "Information Technology Usage: The Indian Experience." Vikalpa: The Journal for Decision Makers 29, no. 1 (January 2004): 83–92. http://dx.doi.org/10.1177/0256090920040107.
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This paper attempts to understand the current state of Information Technology (IT) usage in select Indian organizations based on a questionnaire survey of business executives and IS staff of select IT-savvy organizations. In recent years, rapid changes and developments in the IT domain have created new leaders in the market place. Corporates, the world over, are leveraging on these developments through efficient supply chain, inventory control, and business intelligence applications for gaining an edge over their competitors. The Information System (IS) developed by these organizations is non-replicable thus providing the differentiation. Though Indian companies are aware of concepts such as supply chain, inventory control, etc., the actual implementation of such concepts is not that widespread. Also, the IS function in India is yet to establish itself as a mainstream business function. It is in this context that this paper makes an effort to understand the importance of IT as a key driver for business strategy and recommend to the industry to adopt some of the best practices prevailing in organizations worldwide. The analysis of the responses indicates that there is a discrepancy between the opinions of business executives and IS staff regarding the adequacy of the current IT systems. This situation can be remedied by implementing some of the suggestions which are as follows: The business executives and the IS staff should be located in the same place to integrate IT into the mainstream of business. Business intelligence application needs to be included in the portfolio of applications for business use. The Indian industry needs to be stepped up to the ‘informate’ stage as it is still in the ‘automate’ stage. CIOs have to play an important role by linking IT to business strategy. Information needs of the executives are increasing and necessary steps for imple- menting data warehousing and OLAP solutions need to be taken. Supporting IS should be put in place to facilitate decision-making. Key performance indicators (KPIs) should be clearly identified and incorporated into the IS to monitor the health of the organization. These initiatives are expected to have the following implications: tighter integration of IT with business strategy transformation from the ‘informate mode’ to the ‘transformate’ mode implementation of newer business intelligence tools development of information-based decision-making culture better understanding of organization's KPIs by the IS staff.
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Ahmed, Baumey. "Building a Conceptual Framework for E-Learning Based on Cloud Computing In Egyptian Universities." INTERNATIONAL JOURNAL OF RESEARCH IN EDUCATION METHODOLOGY 7, no. 5 (December 30, 2016): 1384–89. http://dx.doi.org/10.24297/ijrem.v7i5.5159.
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In order to have an intelligent education, we have to make use of all modern education techniques. One of these techniques is the integration of information and communication technologies in education according to the global trend. In other words, to prepare a creative environment using means of existing web tools, techniques, and services to provide Browser-Based-Application. Nowadays Arab countries have a big interest in E-learning techniques and put it into the form of services within Services Oriented Architecture Technique (SOA), and mixing its input and outputs within the components of the Education Business Intelligence and enhance it to simulate reality by educational virtual worlds. This paper presents an idea about tools, instruments, techniques to enhance the educational process in the way that it could reach maximum uses of intelligent education modern technique.
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Debrenti, Attila Sándor, and Miklós Herdon. "Food Industry 4.0 readiness in Hungary." International Journal of Engineering and Management Sciences 5, no. 1 (April 14, 2020): 1–12. http://dx.doi.org/10.21791/ijems.2020.1.1.
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In terms of production value, the food industry is the third-largest in Hungary, the first in Hungary in terms of the number of employees, and the first in Europe in the processing industry, as well as a significant user of resources. The research examined the state of art of digitalization readiness, focusing on I4.0 technologies, which supports the management to operate more efficiently the enterprise and to make better decisions. So the focus was on integrated enterprise information systems, management support systems, business intelligence systems, industry 4.0 technologies, and issues related to their application. The analysis based on an online questionnaire survey the request sent to 4.600 enterprises, the response rate was 5% which was representative of the branches of production, covered the Hungarian food and beverage manufacturing sectors in 2019. The companies were asked the most critical technologies in development, going towards Industry 4.0. The research tools were LimeSurvey, Mailing List Server, Excel, Power BI (Desktop, Publishing Server to distribute the results). The used analysing methods were making calculations, pivot tables, models, dasboards. We found that a significant portion of businesses, 78 %, use mobile devices in the manufacturing process. The three most relevant digital technologies are geolocating (GPS, GNSS), cloud computing, and sensor technology. The current level of digitalization and integration cannot be said to be high, but respondents are very optimistic about expectations. Improvements are expected in all areas in the next 2-3 years in terms of digitalisation and integration. Vertical integration involves, first and foremost, cooperation with partners in the supply chain. Horizontal integration means close, real-time connectivity and collaboration within the company. Unfortunately, between 6% and 15% of SMEs (approximately 9% on average) and large enterprises, 36% have a digital strategy. According to the survey, the sector needs significant improvement and creating a digitalization strategy.
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Singh, Ritika, and Chandan Bhar. "System dynamics to turnaround an Indian microfinance institution." Kybernetes 45, no. 3 (March 7, 2016): 411–33. http://dx.doi.org/10.1108/k-05-2014-0111.
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Purpose – The purpose of this paper is to present a policy comparison tool for Indian Microfinance Institutions (MFIs) so that they can choose the best policy for implementation. It provides for turnaround of a troubled MFI by analyzing the performance of different policies. Design/methodology/approach – The paper has done a web survey to identify the need of a strategic tool for MFI. It has built a Decision Support System (DSS) using system dynamics. A corporate model of MFI has been constructed using iThink 10.0.2 software. A quantitative validity test has been done to find the robustness of the model. Finally four policies are tested and the performance indicators have been used to suggest the best policy. Apart from this DSS is used to test the implementation range of a policy. Findings – “Integration of Microfinance with country’s mainstream financial system along with provisioning 1 percent of outstanding loans” is recommended for the MFI as this will increase the financial performance. Research limitations/implications – In its present form the corporate model developed for MFI is not applicable for judging social performance. Therefore MFIs might be sceptic toward it. However, incorporation of certain performance indicators such as financial-self-sufficiency ratio might help in overcoming this reluctance. Practical implications – “Integration of Microfinance with country’s mainstream financial system along with restricting provision” will generate better performance for the MFI. Therefore this policy should be implemented by the MFI. There are other considerations which need to be taken into account while implementing this policy. The integration may require outsourcing of certain operations to banks, utilization of bank branches to disseminate knowledge related to the conduct of transactions, usage of customized bank software to handle the day-to-day business, development of new softwares for mobile messaging to help poor customers avail of schemes run by the banks, fill loan application forms online, send reminders for loan recovery; provide incentives such as upgradation of poor customers to become regular customers of banks. Social implications – By improving the health of the MFI a bigger goal to reach the poor will be achieved in the long run. The MFI has around five million clients at present and if the company becomes insolvent then the future of these clients is going to be impacted. The organization has interacted closely with these clients and therefore knows how to upgrade their financial state. Originality/value – The tool is first of its kind in the microfinance industry. So far the microfinance technology providers have dealt with Management Information System and Information and Communication Technology. The tool has been built to present a quantitative model for overall operations of the MFI. The simulation of this model helps in predicting future scenarios.
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West, Emily. "Amazon: Surveillance as a Service." Surveillance & Society 17, no. 1/2 (March 31, 2019): 27–33. http://dx.doi.org/10.24908/ss.v17i1/2.13008.
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This essay argues that Amazon, the leading e-commerce platform in many parts of the world, uses surveillance not just as a key tool in the platform logic of its growing constellation of businesses but also increasingly as a service to its consumers. In contrast to prevailing assumptions that platforms will obscure the surveillant aspects of their businesses and that users will resist the intrusive nature of corporate surveillance, Amazon’s business practices point to the rapid normalization, and even embrace, of surveillant logics by consumers. Given the importance of consumer data to its operations, Amazon increasingly designs services whose purpose is, at least in part, to collect more data about consumers. The zenith of Amazon’s surveillance capabilities of its customers is no doubt its family of Echo devices enabled by the artificial intelligence interactive-voice service Alexa, which connects to the cloud run by Amazon, itself, through Amazon Web Services. Alexa is similar to competing digital voice assistants like Apple’s Siri and Google’s Assistant, but with more cultural visibility, worldwide market penetration, and greater integration with a host of Internet-of-Things devices produced by a variety of manufacturers. Amazon seeks to make Alexa an indispensable service to consumers, one that sweetens the granular forms of surveillance in more private spaces and situations that it now has the capability to gather, relative to the company’s more established forms of surveillance. While a typical association with surveillance might be the alienation and disempowerment of social control, I suggest that Amazon’s practices of consumer surveillance cultivate a sense of intimacy, borne of being seen between consumer and brand. In other words, I advocate for recognizing the subjectification of contemporary practices of platform surveillance, in addition to its structural elements.
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Spasiteleva, Svitlana O., and Volodymyr L. Buriachok. "PERSPECTIVES FOR DEVELOPMENT OF BLOCKCHAIN APPLICATIONS IN UKRAINE." Cybersecurity: Education, Science, Technique, no. 1 (2018): 35–48. http://dx.doi.org/10.28925/2663-4023.2018.1.3548.
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The article is devoted to the definition of problems using of blockchain technologies, and ways to overcome them to create distributed, secure applications. The paper considers the theoretical fundamentals of blockchain technologies and blockchain applications, new models of blockchain business, blockchain applications development platform, blockchain applications security, blockchain applications development problems, prospects for further research. The analysis of recent research and publications in the field of blockchain technologies are made in the article. Based on this analysis, it was determined that the blockchain industry has not yet completed the process of generating a generally accepted multilevel technology description. The overview of existing models of business blockchain, their characteristics and areas of application are done in the article. Software tools for creating and maintaining blockchain applications are considered. The article deals with the features, advantages and problems of using blockchain technology for creating distributed, secure applications. The problem of integration of new and existing private systems with an open blockchains is considered. A possible solution to this problem is the creation of a blockchain authentication service to implement a global security level. Such a service can become a standard security infrastructure for new models of mixed private and public systems that will be useful to all participants in different areas of the economy. The directions of development of protected blockchain applications in the sphere of public administration and private business in Ukraine are determined. In addition, the priority tasks that need to be solved for successful implementation of technology in Ukraine are determined based on the analysis of the current state of development of blockchains. There are three main areas of development of blockade technology: standardization, application security and integration of block systems with existing private systems and modern technologies of artificial intelligence, large data and the Internet of things, and described prospects for further research for them.
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Zhou, Liming, Ming Li, Bingkun Chen, Feng Li, and Xiaolin Li. "An inhomogeneous cell-based smoothed finite element method for the nonlinear transient response of functionally graded magneto-electro-elastic structures with damping factors." Journal of Intelligent Material Systems and Structures 30, no. 3 (November 29, 2018): 416–37. http://dx.doi.org/10.1177/1045389x18812712.
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In this article, an inhomogeneous cell-based smoothed finite element method (ICS-FEM) was proposed to overcome the over-stiffness of finite element method in calculating transient responses of functionally graded magneto-electro-elastic structures. The ICS-FEM equations were derived by introducing gradient smoothing technique into the standard finite element model; a close-to-exact system stiffness was also obtained. In addition, ICS-FEM could be carried out with user-defined sub-routines in the business software now available conveniently. In ICS-FEM, the parameters at Gaussian integration point were adopted directly in the creation of shape functions; the computation process is simplified, for the mapping procedure in standard finite element method is not required; this also gives permission to utilize poor quality elements and few mesh distortions during large deformation. Combining with the improved Newmark scheme, several numerical examples were used to prove the accuracy, convergence, and efficiency of ICS-FEM. Results showed that ICS-FEM could provide solutions with higher accuracy and reliability than finite element method in analyzing models with Rayleigh damping. Such method is also applied to complex structures such as typical micro-electro-mechanical system–based functionally graded magneto-electro-elastic energy harvester. Hence, ICS-FEM can be a powerful tool for transient problems of functionally graded magneto-electro-elastic models with damping which is of great value in designing intelligence structures.
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Panagiotakopoulos, Panagiotis, Angela Espinosa, and Jon Walker. "Integrated sustainability management for organizations." Kybernetes 44, no. 6/7 (June 1, 2015): 984–1004. http://dx.doi.org/10.1108/k-12-2014-0291.
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Purpose – The purpose of this paper is to propose the Viable System Model (VSM) as an effective model to base the analysis of organizational sustainability (long-term viability). It is specifically proposed as a model to integrate the various sustainability tools, and as the basis for designing a unified Sustainability Management System. Design/methodology/approach – The VSM is used as an organizational model to examine three prominent sustainability standards: ISO 26000, ISO 14001 and ISO 14044. A generic manufacturing company is used as a template; and its typical business processes are related to each of the VSM’s components. Each clause of the three sustainability standards is then mapped on to the VSM model. These three models are integrated into one, by analysing the differences, similarities and complementarities in the context of each VSM component, and by identifying common invariant functions. Findings – In all, 12 generic sustainability functions are identified. ISO 26000 has the widest scope; ISO 14001 is focused primarily on internal measurement and control (System 3), while ISO 14044 is a complex performance indicator at the System 3 level. There is a general absence of System 2. Each standard can be regarded as a distinct management layer, which needs to be integrated with the Business Management layer. Research limitations/implications – Further research is needed to explore the specifics of integration. Practical implications – This integration should not be based on creating distinct roles for each management layer. Originality/value – The paper uses the insights of organizational cybernetics to examine prominent sustainability standards and advance sustainability management at the business level.
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Horbovyy, Artur, and Alina Khaletska. "The road ahead for age-friendly community in Ukraine." Geopolitical, Social Security and Freedom Journal 2, no. 1 (November 1, 2019): 46–59. http://dx.doi.org/10.2478/gssfj-2019-0005.
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Abstract As in other countries, Ukraine has persistent ageing stereotypes, with old age associated with wealth reduction, financial instability and social exclusion. Shifting these negative attitudes to active-ageing and seniors’ inclusion requires a systematic challenge. Not so long times ago the majority of people in their third age were unaware of active-ageing or expressed scepticism about the feasibility of creating an age-friendly community in Ukraine. Since the large-scale integration of Ukrainian UTAs into the EU agenda for intellectual, economic and social progress of society and individuals regardless of age, the changes in lifelong activities and participation in personally and socially meaningful ways for seniors caused a new outlook for them involving active vitality and optimism, confidence in intelligence, personal and social inclusion. This publication is devoted to the analysis of possible road ahead for the age-friendly community in Ukraine, negative stereotyping towards senior people from the side of business and individuals. The main goal is introducing methodology, practices and tools for the successful performance of initiative for age-friendly compass in Ukraine aimed to measure ageism in society.
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Varis, Iryna, Oksana Kravchuk, and Sofiia Zavhorodnia. "Business’s digital transformation: choice, implementation and improvement of CRM-systems." Marketing and Digital Technologies 5, no. 2 (June 29, 2021): 48–66. http://dx.doi.org/10.15276/mdt.5.2.2021.5.
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The aim of the article. The aim of the article is to determine the essence, advantages and disadvantages of business’s digital transformation, describe the importance of business-process management through its digital transformation, define the nature, types and capabilities of CRM-systems, identify and describe trends in their development, analyze the results of prior researches and select the most popular CRM-systems, as well as research for existing problems of using defined CRM-systems, suggest recommendations for eliminating shortcomings of existing CRM-systems. Analyses results. The coronavirus pandemic has forced companies to rapidly change business processes and shift to remote work, which in turn has led to widespread using of CRM systems in customer relationship management. The modern market offers different goods and services, but they are mostly similar in many ways. The question is how to keep the customer for a long time? The introduction of CRM systems will help answer this question. The definition of CRM stands for Customer Relationship Management, which refers to all the strategies, methods, tools and technologies that a business uses to develop, retain and attract customers. Customer Relationship Management is a special approach of doing business, where the first priority of the company is to focus on the client. The main purpose of the CRM strategy is to create a single ecosystem, which helps to attract new and develop existing customers. Managing relationships means attracting new customers, turning neutral customers into loyal ones, and forming business partners from regular customers. The concept of CRM means that separate business tools are combined into a well-established system. CRM includes programs for collecting customer’s data, managing transactions, control and monitoring manager’s decisions, analytics and forecasting. The article considers the essence of modern transformation of business processes, their advantages and disadvantages, defines the concepts, types, existing opportunities and trends in CRM-systems. The article analyses the experts’ opinions of the most popular modern CRM-systems and generalizes its shortcomings, measures the main elimination of revealed problems. The article conducted a study based on a survey of experts, the main purpose of which was to identify the share of popular CRM-systems among consumers, as well as to identify the main problems and limitations of these systems. Conclusions and directions for further research. The main goal of the CRM strategy is to create a single ecosystem for attracting new customers and developing existing ones. The main tasks of CRM-systems include: attracting new customers through various channels, communication, choice of interaction strategy, Purchase funnel, document management, closing sales, re-communication and analytics of the company. There are three types of CRM systems: desktop, client-server and cloud systems. The main trends in CRM systems development include: increasing usage of artificial intelligence, service automation, data integration, usage of blockchains and social CRM-system, a large number of different applied subsystems and voice interface. The most popular systems are proved to be: Agile CRM, Salesforce Sales Cloud, Zoho CRM, Dynamics 365 and Bitrix24. The main problems of existing CRM-systems can be identified as: slow work on query processing and data output; wasting time on system administration; a large number of built-in tools increases the time to get used with the system; high cost of service, etc. Prospects for further development of CRM-systems include: integration with Big Data and AI; usage of voice technologies as a method for increasing operational efficiency; usage of data from social networks; as well as the creation of a single and common approach of customer identification. In the future, vendors should simplify their product versions and reduce the number of tools to basic, which will reduce the monthly fee for service, as well as speed up data processing by the system, due to the lack of unnecessary add-ons. On the other hand, companies that use CRM systems in their daily work should pay more attention to the integration CRM systems with social networks, which contain essential share of information about their target audience and existing customers.
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Le, Quang-Hung, Son-Lam Vu, Thi-Kim-Phuong Nguyen, and Thi-Xinh Le. "A State-of-the-Art Survey on Context-Aware Recommender Systems and Applications." International Journal of Knowledge and Systems Science 12, no. 3 (July 2021): 1–20. http://dx.doi.org/10.4018/ijkss.2021070101.
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In the digital transformation era, increasingly more individuals and organizations use or create services in digital spaces. Many business transactions have been moving from the offline to online mode. For example, sellers intend to introduce their products on e-commerce platforms rather than display them on store shelves as in traditional business. Although this new format business has advantages, such as more space for product displays, more efficient searches for a specific item, and providing a good tool for both buyers and sellers to manage their products, it is also accompanied by the obviously important problem that users are confused when choosing an appropriate item due to a large amount of information. For this reason, the need for a recommendation system appears. Informally, a recommender system is similar to an information filtering system that helps identify a set of items that best satisfy users' demands based on their preference profiles. The integration of contextual information (e.g., location, weather conditions, and user's mood) into recommender systems to improve their performance has recently received considerable attention in the research literature. However, incorporating such contextual information into recommendation models is a challenging task because of the increase in both the dimensionality and sparsity of the model. Different approaches with their own advantages and disadvantages have been proposed. This paper provides a comprehensive survey on context-aware recommender systems in recent years. In particular, the authors pay more attention to journal and conference proceedings papers published from 2016 to 2020. In addition, this paper also presents open issues for context-aware recommender systems and discuss promising directions for future research.
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Shook, Jim, Robyn Smith, and Alex Antonio. "Transparency and Fairness in Machine Learning Applications." Symposium Edition - Artificial Intelligence and the Legal Profession 4, no. 5 (April 2018): 443–63. http://dx.doi.org/10.37419/jpl.v4.i5.2.
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Businesses and consumers increasingly use artificial intelligence (“AI”)— and specifically machine learning (“ML”) applications—in their daily work. ML is often used as a tool to help people perform their jobs more efficiently, but increasingly it is becoming a technology that may eventually replace humans in performing certain functions. An AI recently beat humans in a reading comprehension test, and there is an ongoing race to replace human drivers with self-driving cars and trucks. Tomorrow there is the potential for much more—as AI is even learning to build its own AI. As the use of AI technologies continues to expand, and especially as machines begin to act more autonomously with less human intervention, important questions arise about how we can best integrate this new technology into our society, particularly within our legal and compliance frameworks. The questions raised are different from those that we have already addressed with other technologies because AI is different. Most previous technologies functioned as a tool, operated by a person, and for legal purposes we could usually hold that person responsible for actions that resulted from using that tool. For example, an employee who used a computer to send a discriminatory or defamatory email could not have done so without the computer, but the employee would still be held responsible for creating the email. While AI can function as merely a tool, it can also be designed to act after making its own decisions, and in the future, will act even more autonomously. As AI becomes more autonomous, it will be more difficult to determine who—or what—is making decisions and taking actions, and determining the basis and responsibility for those actions. These are the challenges that must be overcome to ensure AI’s integration for legal and compliance purposes.
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Khrupovych, Svitlana, and Tetiana Borysova. "Using of an artificial intelligence in the marketing analysis of unstructured data." Marketing and Digital Technologies 5, no. 1 (March 14, 2021): 17–26. http://dx.doi.org/10.15276/mdt.5.1.2021.2.
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The aim of the article. The aim of the article is to find effective ways to use an artificial intelligence in the marketing analysis of unstructured data. This will allow us to highlight the benefits of using big data in marketing. To develop end-to-end analytics, it is necessary to develop a scheme of aggregation of personalized information about the client. Analyses results. It is established that the accumulated information in marketing contains a huge potential for new knowledge and can provide many new opportunities for decision-making. Unstructured data is described as information that does not have a predefined data model, or is poorly organized and structured. This data can be obtained from video content, e-mails, images, social media posts, PDF files. The article proposes systematization of unstructured data in accordance with content sources. Unstructured data analysis will allow us to model a portrait of the target consumer; study and analyze loyal consumer demands through automated content analysis of social networks; to influence consumer behavior through personalized communication content; set up personalized advertising appeals; effectively forecast production costs for the creation of new products and the withdrawal from the market of those, that are not in demand; generate and retain the target audience. Artificial intelligence technology makes unstructured data an extremely valuable resource for marketing analytics to their automated processing. It is noted that the biggest advantage of using unstructured data in marketing is that artificial intelligence can analyze texts by scanning emails and processing documents by word processors. Data mining through smart machine algorithms also allows marketers to see hidden patterns and identify associations of events, sequences of events and the correlation between them. The tools of practice of the individualized approach in marketing which work on the basis of big data are highlighted. Contextual advertising, which with the help of artificial intelligence algorithms itself "guesses" that the potential customer is looking for, having only keywords from the given parameters. Chatbots are ready to answer standardized questions round-the-clock. Using this artificial intelligence program helps reduce marketing costs, optimize customer service time, and increase conversions. It is investigated that the world practice of marketing analytics in big data processing is based on a powerful and free Microsoft Power BI platform. It is noted that the introduction of such end-to-end analytics through the integration of all data sources, can significantly increase profitability. A business process model of unstructured data analytics based on the Microsoft Power BI platform is proposed. Among the basic benefits that we can get from the use of artificial intelligence in the analysis of unstructured data in order to personalize content, is the formation of a portrait of each client. This data, combined with specialized analytical information processing software, enables marketers to move from understanding the customer-consumer to the customer-person. Conclusions and directions for further research. The research conducted in the field of using artificial intelligence algorithms for the practical direction of marketing analysis of unstructured data, indicates to us that we can better target proposals for individual consumers. In summary, we note that cognitive technologies and analytical platforms based on artificial intelligence allow us to understand the visual image and text through machine learning. This process can only be ensured by creating a partnership between the human consumer and the computer systems of various business areas. Replacing routine work with a machine algorithm of artificial intelligence will allow the cognitive system to use unstructured data to improve marketing analytics in the context of personalizing content for each consumer. Keywords: marketing analysis, unstructured data, artificial intelligence, information, cognitive system.
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Pfouga, Alain, and Josip Stjepandić. "Leveraging 3D geometric knowledge in the product lifecycle based on industrial standards." Journal of Computational Design and Engineering 5, no. 1 (November 20, 2017): 54–67. http://dx.doi.org/10.1016/j.jcde.2017.11.002.
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Abstract With their practical introduction by the 1970s, virtual product data have emerged to a primary technical source of intelligence in manufacturing. Modern organization have since then deployed and continuously improved strategies, methods and tools to feed the individual needs of their business domains, multidisciplinary teams, and supply chain, mastering the growing complexity of virtual product development. As far as product data are concerned, data exchange, 3D visualization, and communication are crucial processes for reusing manufacturing intelligence across lifecycle stages. Research and industry have developed several CAD interoperability, and visualization formats to uphold these product development strategies. Most of them, however, have not yet provided sufficient integration capabilities required for current digital transformation needs, mainly due to their lack of versatility in the multi-domains of the product lifecycle and primary focus on individual product descriptions. This paper analyses the methods and tools used in virtual product development to leverage 3D CAD data in the entire life cycle based on industrial standards. It presents a set of versatile concepts for mastering exchange, aware and unaware visualization and collaboration from single technical packages fit purposely for various domains and disciplines. It introduces a 3D master document utilizing PDF techniques, which fulfills requirements for electronic discovery and enables multi-domain collaboration and long-term data retention for the digital enterprise. Highlights With their practical introduction by the 1970s, virtual product data have emerged to a primary technical source of intelligence in manufacturing. Modern organization have since then deployed and continuously improved strategies, methods and tools to feed the individual needs of their business domains, multidisciplinary teams, and supply chain, mastering the growing complexity of virtual product development. As far as product data are concerned, data exchange, 3D visualization, and communication are crucial processes for reusing manufacturing intelligence across lifecycle stages. Research and industry have developed several CAD interoperability, and visualization formats to uphold these product development strategies. Most of them, however, have not yet provided sufficient integration capabilities required for current digital transformation needs, mainly due to their lack of versatility in the multi-domains of the product lifecycle and primary focus on individual product descriptions. This paper analyses the methods and tools used in virtual product development to leverage 3D CAD data in the entire life cycle. It presents a set of versatile concepts for mastering exchange, aware and unaware visualization and collaboration from single technical packages fit purposely for various domains and disciplines. It introduces a 3D master document utilizing PDF techniques, which fulfills requirements for electronic discovery and enables multi-domain collaboration and long-term data retention for the digital enterprise. 3D interoperability makes an important contribution to engineering collaboration. Several formats made to that end successively deal with challenges of their time. Some of these such as STEP are highly verbose formats, which gradually encapsulate all information necessary to define a product, its manufacture, and lifecycle support. Others are focusing best on lightweight visualization use cases and endure better with increasing size and complexity of data. Traditional formats like STEP and JT, though, are not capable of supporting the publishing activity in even broader fashion. New tendencies therefore are aiming at strengthening these individual formats through combination with complementary standards or by using document-based approaches. Unlike STEP or JT, 3D PDF can serve multiple purposes and leverages 3D data downstream throughout the product lifecycle to create, distribute and manage ubiquitous, highly consumable, role-specific rich renditions. Based on its container structure, 3D PDF is a fundamentally different approach from traditional experience established in product development – it is an exceptionally proficient contextual aggregation of multi-domain and multi-disciplinary product data. The manufacturing community should embrace it as an addition and great improvement to current engineering collaboration standards. All engineering components required for its descriptions are meanwhile published international standards. The productive use of 3D PDF for sure requires a change in the current mode of operation, be it simply because the traditional CAD model promptly demands new technical descriptions. More perspectives, which have not been primary focus of this approach need to be addressed in order to implement the 3D digital master concept of this paper in the industry. For the complete process to work properly, the actual workflows of today's business organizations must succeed a readiness check involving enhanced technical documentation capabilities of the authoring (CAx) applications based on 3D, PLM, and manufacturing workflows as well as new ways for engineering data communication with supply chain partners in the digital enterprise.
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Becker, Christoph, Luis Faria, and Kresimir Duretec. "Scalable decision support for digital preservation: an assessment." OCLC Systems & Services: International digital library perspectives 31, no. 1 (February 9, 2015): 11–34. http://dx.doi.org/10.1108/oclc-06-2014-0026.
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Purpose – This article aims to evaluate a new architecture for scalable decision-making and control in preservation environments for its ability to address five key goals: scalable content profiling; monitoring of compliance, risks and opportunities; efficient creation of trustworthy plans; context awareness; and loosely coupled preservation ecosystems. Scalable decision support and business intelligence capabilities are required to effectively secure content over time. Design/methodology/approach – We conduct a systematic evaluation of the contributions of the SCAPE Planning and Watch suite to provide effective and scalable decision support capabilities. We discuss the quantitative and qualitative evaluation of advancing the state of art and report on a case study with a national library. Findings – The system provides substantial capabilities for semi-automated, scalable decision-making and control of preservation functions in repositories. Well-defined interfaces allow a flexible integration with diverse institutional environments. The free and open nature of the tool suite further encourages global take-up in the repository communities. Research limitations/implications – The article discusses a number of bottlenecks and factors limiting the real-world scalability of preservation environments. This includes data-intensive processing of large volumes of information, automated quality assurance for preservation actions, and the element of human decision-making. We outline open issues and future work. Practical implications – The open nature of the software suite enables stewardship organizations to integrate the components with their own preservation environments and to contribute to the ongoing improvement of the systems. Originality/value – The paper reports on innovative research and development to provide preservation capabilities. The results of the assessment demonstrate how the system advances the control of digital preservation operations from ad hoc decision-making to proactive, continuous preservation management, through a context-aware planning and monitoring cycle integrated with operational systems.
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CRISTEA, Lavinia Mihaela. "Emerging IT Technologies for Accounting and Auditing Practice." Audit Financiar 18, no. 160 (October 29, 2020): 731–51. http://dx.doi.org/10.20869/auditf/2020/160/023.
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The IT impact can be noticed in all activity fields of this world, and the audit is no exception from the evolution of this technological trend. Motivation: Given that professionals are progressively pursuing experimentation in working with new technologies, the development of Artificial Intelligence (AI), Blockchain, RPA, Machine Learning through the Deep Learning subset is a particularly interesting case, on which the researcher argues for debate. The objective of the article is to present the latest episode of the new technologies impact that outline the auditor profession, the methods and tools used. The quantitative, applied and technical research method allows the analysis of the emerging technologies impact, completing a previous specialized paper of the same author. The results of this paper propose the integration of AI, Blockchain, RPA, Deep Learning and predictive analytics in financial audit missions. The projections resulted from discussions with auditing and IT specialists from Big Four companies show how the technologies presented in this paper could be applied on concrete cases, facilitating current tasks. Machine Learning and Deep Learning would allow a development for prescriptive analytics, revolutionizing the data analytics process. Both the analysis of the literature and the conducted interviews admit AI as a business solution that contributes to the data analytics in an intelligent way, providing a foundation for the development of RPA.
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Escobar, Pilar, María del Mar Roldán-García, Jesús Peral, Gustavo Candela, and José García-Nieto. "An Ontology-Based Framework for Publishing and Exploiting Linked Open Data: A Use Case on Water Resources Management." Applied Sciences 10, no. 3 (January 22, 2020): 779. http://dx.doi.org/10.3390/app10030779.
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Nowadays, the increasing demand of water for electricity production, agricultural and industrial uses are directly affecting the reduction of available quality water for human consumption in the world. Efficient and sustainable maintenance of water reservoirs and supply networks implies a holistic strategy that takes into account, as much as possible, information from the stages of water usage. Next,-generation decision-making software tools, for supporting water management, require the integration of multiple and heterogeneous data sources of different knowledge domains. In this regard, Linked Data and Semantic Web technologies enable harmonization of different data sources, as well as the efficient querying for feeding upper-level Business Intelligence processes. This work investigates the design, implementation and usage of a semantic approach driven by ontology to capture, store, integrate and exploit real-world data concerning water supply networks management. As a main contribution, the proposal helps with obtaining semantically enriched linked data, enhancing the analysis of water network performance. For validation purposes, in the use case, a series of data sources from different measures have been considered, in the scope of an actual water management system of the Mediterranean region of Valencia (Spain), throughout several years of activity. The obtained experience shows the benefits of using the proposed approach to identify possible correlations between the measures such as the supplied water, the water leaks or the population.
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Sousa, Maria José, and Ivo Dias. "Business Intelligence for Human Capital Management." International Journal of Business Intelligence Research 11, no. 1 (January 2020): 38–49. http://dx.doi.org/10.4018/ijbir.2020010103.
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This article presents the results of an exploratory study of the use of business intelligence (BI) tools to help to make decisions about human resources management in Portuguese organizations. The purpose of this article is to analyze the effective use of BI tools in integrating reports, analytics, dashboards, and metrics, which impacts on the decision making the process of human resource managers. The methodology approach was quantitative based on the results of a survey to 43 human resource managers and technicians. The data analysis technique was correlation coefficient and regression analysis performed by IBM SPSS software. It was also applied qualitative analysis based on a focus group to identify the impacts of business intelligence on the human resources strategies of Portuguese companies. The findings of this study are that: business intelligence is positively associated with HRM decision-making, and business intelligence will significantly predict HRM decision making. The research also examines the process of the information gathered with BI tools from the human resources information system on the decisions of the human resources managers and that impacts the performance of the organizations. The study also gives indications about the practices and gaps, both in terms of human resources management and in processes related to business intelligence (BI) tools. It points out the different factors that must work together to facilitate effective decision-making. The article is structured as follows: a literature review concerning the use of the business intelligence concept and tools and the link between BI and human resources management, methodology, and the main findings and conclusions.