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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.
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Tofan, Dragoş Ovidiu. "Business Intelligence Security." Review of Economic and Business Studies 9, no. 1 (June 1, 2016): 157–69. http://dx.doi.org/10.1515/rebs-2016-0030.
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AbstractExcess information characteristic to the current environment leads to the need for a change of the organizations’ perspective and strategy not only through the raw data processing, but also in terms of existing applications generating new information. The overwhelming evolution of digital technologies and web changes led to the adoption of new and adapted internal policies and the emergence of regulations at level of governments or different social organisms. Information security risks arising from the current dynamics demand fast solutions linked to hardware, software and also to education of human resources. Business Intelligence (BI) solutions have their specific evolution in order to bring their contribution to ensure the protection of data through specific components (Big Data, cloud, analytics). The current trend of development of BI applications on mobile devices brings with it a number of shortcomings related to information security and require additional protective measure regarding flows, specific processing and data storage.
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Foshay, Neil, Todd Boyle, and Jacob Mather. "A Hierarchy of Metadata Elements for Business Intelligence Information Resource Retrieval." International Journal of Business Intelligence Research 4, no. 4 (October 2013): 33–44. http://dx.doi.org/10.4018/ijbir.2013100103.
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Effectively managing information resources is an important activity contributing to the competitive advantage of modern organizations. Organizational knowledge workers must be able to search for pertinent information quickly and effectively. This research identifies the relative usefulness of the metadata elements associated with the Dublin Core metadata standard for the effective retrieval of three different information resources – structured business intelligence reports, structured spreadsheet reports, and unstructured reports in formats such as Word and PowerPoint. A survey of knowledge workers was conducted to determine the relative usefulness of the metadata elements for each of the three information resources and to develop a framework outlining where metadata tag requirements differ between such resources. Overall, the study and resulting framework emphasize the need for system developers and database management personnel to be cognizant of the type of information resources being used, and ensure that search metadata elements that are appropriate for these specific resources are in place.
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Muñoz-Cañavate, Antonio, and Pedro Hípola. "International Intelligence in Spain: An Approach to Information Resources for Business." Journal of Business & Finance Librarianship 20, no. 4 (October 2, 2015): 302–17. http://dx.doi.org/10.1080/08963568.2015.1072894.
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Senik, Zizah Che, and Ridzuan Md. Sham. "SME Internationalization Intelligence Information and Knowledge on International Opportunities." Gadjah Mada International Journal of Business 13, no. 2 (December 1, 2014): 161. http://dx.doi.org/10.22146/gamaijb.5489.
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Small and medium enterprises (SMEs) internationalization intelligence, referring to the process of gathering information and knowledge on international opportunities, is crucial to initiate SMEs’ internationalization. The literature has stressed organizational resources, networks and information sharing as means to acquire internationalization intelligence, suggesting that the resource-based, network and social capital perspectives can be adopted to explore this issue. However, previous literature still lacks evidence on how SMEs acquire relevant intelligence, and who or what are involved with the process. To address this lack of evidence, we interviewed 54 SME owners/key personnel in the manufacturing sector to: identify sources of internationalization intelligence; examine how those sources assist SMEs to internationalize; and develop propositions on internationalization intelligence. Analyzing the data using NVivo, four themes emerged including institutions, business associates, personal efforts, and other means. The analysis suggests internationalization intelligence occurs mainly through the networks of the SME owners/key personnel, built on their firm’s resources through their internal and external information sharing activities, indicating the need of the SMEs to position themselves in their environments. These findings are developed into propositions. The study indicates multiple perspectives in conceptualizing the process of internationalization intelligence. This study advances a conceptualization of internationalization intelligence, and offers avenues for future research.
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Ahmadzai, Abdul Shabir, Qurban Yazdani, and Adamu Abubakar. "Analysis of Business Intelligence Systems Transmission Session." Journal of Science and Technology 27, no. 1 (December 6, 2022): 16–28. http://dx.doi.org/10.20428/jst.v27i1.1984.
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Information and Communication Technology (ICT) is the central part of Intelligent systems. Business Intelligence (BI) utilizes ICT resources and capabilities to enhance decision-making from the available information. One of the core components of ICT resources is the network. Hypertext Transfer Protocol (HTTP) is an application layer protocol in a network model responsible for handling "requests" in a transmission session. Transmission Control Protocol (TCP) establishes connections session and keeps track of the state of the communication session. Unfortunately, a request from a critical online transaction over TCP in a BI environment is bound to face some uncertainty. There is a lack of studies on the impact of communication over transmission sessions on BI operations. This paper presented an experimental evaluation of the BI transaction transmission session. Various transactions were performed to monitor and analyze the request made with HTTP over a TCP transmission session. Both the HTTP and TCP features for all transactions were captured. The finding indicates that time is highly associated with less traffic congestion and transaction overhead.
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Carson, Grace, Christina O'Connor, and Geoff Simmons. "The crucial role of market intelligence in the development of small business marketing capabilities." Journal of Small Business and Enterprise Development 27, no. 5 (June 19, 2020): 797–816. http://dx.doi.org/10.1108/jsbed-12-2019-0394.
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PurposeDrawing on the resource-based view of the firm, this article explores the influences of market intelligence on the development of small business marketing capabilities, with reference to specialized marketing capabilities, architectural marketing capabilities and dynamic capabilities.Design/methodology/approachThe conceptual framework and propositions present and interpret the resource–capability complementarity between market intelligence and small business marketing capabilities and outline the relationship between individual capability sets.FindingsMarket intelligence is shown to be crucial in the development of small business marketing capabilities and in the implementation of more formalized marketing strategies that allow small businesses to create value for customers and improve their performance. However, the level to which market intelligence is utilized and marketing capabilities are developed is found to be considerably influenced by the small business owner-manager and firm learning.Practical implicationsIt is imperative that small businesses acknowledge the practical benefits of market intelligence and harness these advantages accordingly. However, owner-managers must be motivated to encourage the development of more formalized marketing capabilities and act incisively upon the information derived from market intelligence.Originality/valueRecent research indicates that market intelligence and marketing capabilities can interact to enable a firm to align its resources with the market, by providing customer insights that guide them as to which value-adding activities they should implement. However, extant research in this area remains in its infancy, and very little is known about the adoption processes of market intelligence in small businesses and its role in developing marketing capabilities.
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KULVATUNYOU, BOONSERM, NENAD IVEZIC, RICHARD A. WYSK, and ALBERT JONES. "Integrated product and process data for business to business collaboration." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 17, no. 3 (August 2003): 253–70. http://dx.doi.org/10.1017/s0890060403173076.
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Collaborative development of engineered products in a business to business (B2B) environment requires more than the selection of components from an on-line catalogue. It involves the electronic exchange of product, process, and production engineering information during both design and manufacturing. Although the state of the practice does include a variety of ways to exchange product data electronically, it does not extend to the exchange of manufacturing process data. The reason is simple: process data are usually tied to specific manufacturing resources. These resources are not known typically at product development time. This paper proposes an approach called integrated product and process data, in which manufacturing process data are considered during product development. This approach replaces traditional process plans, which are resource specific, with a resource-independent process representation. Such a representation will allow a much wider collaboration among business partners and provide the necessary base for collaborative product development.
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Kapoor, Bhushan, and Joseph Sherif. "Human resources in an enriched environment of business intelligence." Kybernetes 41, no. 10 (October 12, 2012): 1625–37. http://dx.doi.org/10.1108/03684921211276792.
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Stipanović, Christian. "BUSINESS INTELLIGENCE IN MAKING TOURISM ENTERPRISES COMPETITIVE." Tourism and hospitality management 11, no. 2 (December 2005): 111–19. http://dx.doi.org/10.20867/thm.11.2.10.
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In the dynamic process of creating competitive ability, tourism enterprises need to valorise new inputs (knowledge, intellectual capital) in generating advantages (quick response, quality, price). It is crucial to implement a new business philosophy based on re-engineering and earned out by encouraging innovations, asserting knowledge as a key resource, and introducing benchmarking and business intelligence. Business Intelligence represents the totality of an enterprise’s information, perceptual and operational competencies as a basis for managing change and building competitiveness. It centres on protecting the data of one enterprise, while gathering the data of others in creating the information needed for a development strategy. Tourist enterprises in Croatia have not yet realised the importance of business intelligence.
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Festervand, Troy A., and David B. Meinert. "Purchasing Intelligence Systems In Small Manufacturing Firms: Present Status and Future Direction." International Journal of Logistics Management 3, no. 1 (January 1, 1992): 37–45. http://dx.doi.org/10.1108/09574099210804796.
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Information obtained from a Purchasing Management Intelligence System (PMIS) can provide the valuable input into a firm's strategic planning process. Because of scarce resources and the criticality of market mistakes, it is even more essential that small firms take advantage of this information resource. This articles reports the results of a study undertaken to determine the status of purchasing intelligence systems in small manufacturing firms. The results indicate that while purchasing intelligence systems exist in most small manufacturing organizations, their focus is on conventional rather than strategic activities. The results also indicate that numerous obstacles limit the effectiveness of purchasing intelligence systems. In addition to a lack of preparedness respondents identified procedural problems, a lack of resources and a weak effort/outcome relationship.
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Kapoor, Bhushan, and Yaggeta Kabra. "Current and Future Trends in Human Resources Analytics Adoption." Journal of Cases on Information Technology 16, no. 1 (January 2014): 50–59. http://dx.doi.org/10.4018/jcit.2014010105.
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While many organizations use business intelligence and analytics in business functions including Supply Chain, Finance, Accounting and Marketing, they have taken little advantage of this in the Human Resources (HR) management area. Seeing tremendous opportunities in the use of analytics, businesses are taking big measures, such as creating a culture of making critical decisions validated by data driven approaches and hiring analytics professionals in areas that promises high rates of return. Experts continue to emphasize the importance of analytics for HR to transform itself into a more effective resource for the organization. In this paper the authors study the current and the near future states of analytics in Human Resources area. With information collected from leading job search engines, SimplyHired.com and Indeed.com, the authors have modeled trends in hiring analytics professionals in different functional areas of business. The authors compared the HR analytics trend with trends in hiring analytics professionals in Supply Chain, Finance, Accounting and Marketing functions. The extent to which companies are hiring analytics professionals now should be a good indication of analytics adoptions in the future.
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Kocakoç, Ipek Deveci, and Sabri Erdem. "Business Intelligence Applications in Retail Business: OLAP, Data Mining & Reporting Services." Journal of Information & Knowledge Management 09, no. 02 (June 2010): 171–81. http://dx.doi.org/10.1142/s0219649210002541.
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As a result of today's competitive business environment, companies have been trying to improve the utilization of funds effectively in their budgets for information technology investments. These companies retrieve more information with the same set of resources by means of business intelligence methods. According to Rubin (Chabrow, 2004) IT budgets are not simply declining or levelling off, rather, companies are shifting from a pure cost-cut mode to a model that emphasises agility and efficiency. Tremendous daily growth of the company data requires more funds and investment for establishing the technologies and infrastructure necessary for gathering fast and crucial information that supports the decision making process. This necessity gave birth to various business intelligence methods, which mainly aim to process mass amount of collected data from their existing application, and represent it in a way with which companies can apply to their daily competitive decisions. This application primarily concerns the implementation of business intelligence for a retail business company. The aim is to implement built-in business intelligence solutions of the Microsoft SQL Server that holds the commercial information of the company for the past three years. The customer company has already been using Microsoft products. The key items used for analyzing data are sales, momentary inventory and logistics information. The application can be grouped in five main areas: Building the data warehouse, constructing OLAP cubes, applying data mining algorithms on OLAP cubes, representing the results in reports with reporting services, and implementation.
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Buhasho, Edward, Agnes Wausi, and James Njihia. "Business Intelligence Capability, Complementary Resources and Performance among Public Listed Firms in Kenya." International Journal of Business and Management 15, no. 9 (August 16, 2020): 66. http://dx.doi.org/10.5539/ijbm.v15n9p66.
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Whereas Business Intelligence initiative has been a primary focus many organisations globally for several years and accounting for billions of dollars in capital expenditure, empirical research remains sparse on the actual impact derived from this investment. Even when the benefits are established, its indirect and delayed impact on business results make it difficult to assess its value. Available literature on how insights triggered by Business Intelligence are transformed into profitable business learning is vague and fragmented. Hence, the main objective of this study was to establish the influence of complementary resources on the relationship between Business Intelligence capability and firm performance. The study used interdisciplinary theories to achieve the research objective, namely, Information systems capability theory and organisational learning. The study was performed using a mixed methods research methodology and cross-sectional approach. Data was collected from 64 public listed companies in Kenya. Findings indicated that complementary resources have a positive and significant impact on the relationship between Business Intelligence capability and performance. The study contributed to theory by building a framework for business intelligence assessment, including factors that significantly lead to improved performance. The results also provide new insights into the existing literature and suggest directions for future research with implications for academia, policymakers and management.
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Cristescu, Marian Pompiliu. "Business Intelligence Integrated Solutions." Land Forces Academy Review 22, no. 4 (December 1, 2017): 270–75. http://dx.doi.org/10.1515/raft-2017-0036.
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Abstract A Business Intelligence solution concerns the simple, real-time access to complete information about the business shown in a relevant format of the report, graphic or dashboard type in order help the taking of strategic decisions regarding the direction in which the company goes. Business Intelligence does not produce data, but uses the data produced by the company’s applications. BI solutions extract their data from ERP (Enterprise Resource Planning), CRM (Customer Relationship Management), HCM (Human Capital Management), and Retail, eCommerce or other databases used in the company.
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Cao, Xiao Jun, and Xiu Feng Yang. "Application of Business Intelligence in Hospital Information Management." Applied Mechanics and Materials 373-375 (August 2013): 1098–101. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.1098.
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With the fast development of the hospital information system, the hospital database has accumulated vast amounts of management and clinical medical data. Therefore, we establish the hospital information platform to integrate the various resource of information in hospital and make the effective development and utilization, so that we can construct a data analysis platform which focuses on the patients clinical diagnosis information and the management information for hospital. In this respect, this paper introduces the business intelligence technology into the hospital information statistical field, and sets up the business intelligence system which focusing on the integration of business data and assistant decision support analysis.
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Valentin, Grecu, and Nate Silviu. "Managing Sustainability with Eco-Business Intelligence Instruments." Management of Sustainable Development 6, no. 1 (August 22, 2014): 25–30. http://dx.doi.org/10.2478/msd-2014-0003.
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Abstract In response to increasing concerns of society about environmental degradation and increasing demands for a transition to a more sustainable society, the business companies are increasingly active in aligning their processes and services with a sustainability agenda. Production, distribution and supply of goods and services require material and energy consumption, having an impact on natural resources both quantitatively and qualitatively, generating waste, pollution and disrupting ecosystems. Ecobusiness intelligence is the capacity of people, processes and applications/tools to organize business information, to facilitate consistent access to them and analyse them in order to improve management decisions, for better performance management of the organizations that are increasingly pressed to synchronize their processes and services with a sustainable development agenda, through the development, testing and implementation of decision support software. This paper advances the idea that BI methods and tools have an important but as yet not well studied role to play in helping organizations implement and monitor sustainable and socially responsible business practices.
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Booto Ekionea, Jean-Pierre. "Digitization and Business Intelligence at the Heart of a Business Strategy Within African Industries Funds." European Conference on Knowledge Management 23, no. 1 (August 25, 2022): 97–106. http://dx.doi.org/10.34190/eckm.23.1.797.
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This paper focuses on the possibility of collecting information and with a view to the digitization of business processes with the strategic thought of identifying private investment opportunities in the provinces entities which would allow it: - To better collect information on the collection of resources in order to enable it to replenish its fund and meet management and financing needs in the provinces entities ; - Improve the decision-making process at all organizational levels with the help of digitization. This study is based on the application of the knowledge management organizational capacity maturity model (Booto Ekionea, 2012) in the context of African industries Founds to identify the current state of knowledge management organizational capacities towards an ideal model which facilitates the appropriate recommendations.
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Zeng, Zhen, and Longqi Qi. "“Internet + Artificial Intelligence” Human Resource Information Management System Construction Innovation and Research." Mathematical Problems in Engineering 2021 (March 19, 2021): 1–11. http://dx.doi.org/10.1155/2021/5585753.
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Human resources are the cornerstone of operational operation. Good management of human resource information can enable businesses to operate effectively. However, for the time being, most enterprises still use traditional methods of allocating human resources, which are difficult to meet the development needs of enterprises. In order to find the optimal allocation of human resources in an enterprise, this article is based on “Internet + artificial intelligence,” using methods such as case analysis and literature analysis to collect data from databases such as CNKI, Wanfang Database, and SSCI, and uses fog computing to build a model for the optimal allocation of human resources which is proposed, and a large number of relevant literature studies are read and analyzed through the literature survey method. According to the research needs, through the research and summary of the content of the literature, the research structure found that there are many problems in the current human resource information management system. After the optimization of models and algorithms, the allocation of human resources has been greatly improved. The matching rate of personnel and job positions has increased by more than 50%. The operation efficiency index of the enterprise is above 0.8, an increase of about 30%. This shows that “Internet + artificial intelligence” can effectively optimize the enterprise human resource information management system, promote the greater use of its human resource value, bring higher economic returns to the enterprise, and provide assistance for the long-term stable and healthy development of the enterprise.
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Elbashir, Mohamed Z., Philip A. Collier, Steve G. Sutton, Michael J. Davern, and Stewart A. Leech. "Enhancing the Business Value of Business Intelligence: The Role of Shared Knowledge and Assimilation." Journal of Information Systems 27, no. 2 (July 1, 2013): 87–105. http://dx.doi.org/10.2308/isys-50563.
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ABSTRACT Business intelligence (BI) systems have attracted significant interest from senior executives and consultants for their ability to exploit organizational data and provide operational and strategic benefits through improved management control systems. A large body of literature indicates that organizations have largely failed to use their business intelligence investments effectively to exploit the wealth of data they capture in their ERP systems. As a result, BI has too often failed to support organizations' managerial decision making at both the strategic and operational levels and, thus, failed to enhance business value. Whether and how organizations achieve business benefits from their BI investments remains unclear. This study draws on the strategic alignment and IT assimilation literature to develop a research model that theorizes the importance of BI systems assimilation, and the need for shared knowledge among the strategic and operational levels as the drivers of BI business value. Results from the study confirm the crucial role of BI assimilation in translating organizational resources into capabilities that enhance the business value of BI. The findings also contribute evidence on the importance of shared domain knowledge and the interrelations between senior business, IT executives, and operational-level managers for enhancing BI assimilation.
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Kasemsap, Kijpokin. "Multifaceted Applications of Data Mining, Business Intelligence, and Knowledge Management." International Journal of Social and Organizational Dynamics in IT 5, no. 1 (January 2016): 57–69. http://dx.doi.org/10.4018/ijsodit.2016010104.
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This article reviews the literature in the search for the multifaceted applications of data mining (DM), business intelligence (BI), and knowledge management (KM). The literature review highlights the overviews of DM, BI, and KM; the practical applications of DM, BI, and KM; and the prospects of DM, BI, and KM in terms of marketing, business, human resources, and manufacturing. DM plays a key role in organizing huge amount of data and condensing it into valuable information. BI involves the delivery and integration of relevant and useful business information in an organization. KM allows companies to manage a system of core competencies in order to maximize business opportunities and minimize the risk of losing business opportunities. The findings present valuable insights and further understanding of the way in which DM, BI, and KM efforts should be focused.
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Zucca, Joe. "Business Intelligence Infrastructure for Academic Libraries." Evidence Based Library and Information Practice 8, no. 2 (June 11, 2013): 172. http://dx.doi.org/10.18438/b83g75.
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Objective – To describe the rationale for and development of MetriDoc, an information technology infrastructure that facilitates the collection, transport, and use of library activity data.
Methods – With the help of the Institute for Museum and Library Services, the University of Pennsylvania Libraries have been working on creating a decision support system for library activity data. MetriDoc is a means of “lighting up” an array of data sources to build a comprehensive repository of quantitative information about services and user behavior. A data source can be a database, text file, Extensible Markup Language (XML), or any binary object that contains data and has business value. MetriDoc provides simple tools to extract useful information from various data sources; transform, resolve, and consolidate that data; and finally store them in a repository.
Results – The Penn Libraries completed five reference projects to prove basic concepts of the MetriDoc framework and make available a set of applications that other institutions could test in a deployment of the MetriDoc core. These reference projects are written as configurable plugins to the core framework and can be used to parse and store EZ-Proxy log data, COUNTER data, interlibrary loan transactional data from ILLIAD, fund expenditure data from the Voyager integrated library system, and transactional data from the Relais platform, which supports the BorrowDirect and EZBorrow resource sharing consortiums. The MetriDoc framework is currently undergoing test implementations at the University of Chicago and North Carolina State University, and the Kuali-OLE project is actively considering it as the basis of an analytics module.
Conclusion – If libraries decide that a business intelligence infrastructure is strategically important, deep collaboration will be essential to progress, given the costs and complexity of the challenge.
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Hawking, Paul, and Carmine Sellitto. "A Fast-Moving Consumer Goods Company and Business Intelligence Strategy Development." International Journal of Enterprise Information Systems 13, no. 2 (April 2017): 22–33. http://dx.doi.org/10.4018/ijeis.2017040102.
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The paper used the case study approach to report on how a Fast Moving Consumer Goods (FMCG) company developed their Business Intelligence strategy. Many companies are aware of the benefits that Business Intelligence brings to the corporation— however struggle to have an appropriate or well defined strategy. The authors document in the paper how the company experienced limited benefits with their initial Business Intelligence implementation— however, the subsequent development of a Business Intelligence strategy allowed the firm to redress initial project short-comings across several business areas. The company's Business Intelligence strategy included elements that directly addressed governance and resource management, business technology alignment, innovation and skills capability. The research investigated the experiences of a global FMCG company regarding their Business Intelligence use and the findings may not be generalizable.
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Hassanein, Mohamed Sameh, Mohamed Hamed Elfar, and Abdel Nasser H. Zaied. "WATER RESOURCES MANAGEMENT FRAMEWORK TO IMPROVE DECISION-MAKING BASED ON BUSINESS INTELLIGENCE." Journal of Southwest Jiaotong University 57, no. 4 (August 29, 2022): 443–54. http://dx.doi.org/10.35741/issn.0258-2724.57.4.39.
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This article introduces a business intelligence framework to manage water resources, relying on a design science research methodology, data warehousing platform, and Power BI visualization. This framework consists of three phases. The data preprocessing phase comprises the core functions to validate, clean, transform, aggregate, and load data for the next phase. The processing phase includes the warehousing platform that organizes the data, builds a relationship among these data, and exports them in an appropriate format. Finally, the visualization phase generates descriptive reports for data after integrating the exported warehousing platform with the Power BI interface throughout multi-filters. For validating the performance of this framework, a heuristic evaluation was conducted, showing users' feedback regarding the framework, and a usability evaluation was conducted to determine any major issues such as visibility, flexibility, learnability, and operability. The results indicated that the tool allows for improved decision-making and transforming raw data into useful information. In addition, the dashboards provide a good way to visualize data and identify trends. These aspects align directly with the requirements for a BI tool to support strategic water resources management in Egypt. For example, agriculture consumes 46.49 billion cubic meters of water annually, accounting for nearly 60% of Egypt's total water consumption. Therefore, it is the first area of rationalization and consideration. AlShirkia governorate consumes the most water in agriculture, with an annual consumption value of approximately 4 billion 631 million cubic meters, 8 million people, 1.5 million acres, and 11.3 million tons of production.
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Chikohora, Teressa Tjwakinna, and Bukohwo Michael Esiefarienrhe. "A Hybrid Framework for The Implementation of Business Intelligence Systems in Small Scale Enterprises." Journal of Information Systems and Informatics 4, no. 1 (March 15, 2022): 40–54. http://dx.doi.org/10.51519/journalisi.v4i1.221.
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Small scale enterprises can improve their operations by implementing business intelligence systems. The business intelligence systems are complex and require expertise to ensure successful implementation, hence the need for small scale enterprises to determine their readiness before undertaking the project. To improve chances for successful implementation, this study proposed a framework to guide small scale enterprises on the requirements for business intelligence systems. The design steps defined by Edwards and Goodrich & Tamassia were followed to design the framework. The framework components were informed by the Diffusion of Innovation and Technology Organization and Environment theories, the Information Evaluation Model, and the critical success factors for BIS implementation. A small business may evaluate its resources against the framework components to determine whether to implement a business intelligence system. In future, the framework may be extended to include weights and other criteria to calculate a business’s status.
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Bauer, Jan Christian, and Michael Wolff. "The Deinstitutionalization of Business Support Functions through Artificial Intelligence." Information 13, no. 8 (July 22, 2022): 352. http://dx.doi.org/10.3390/info13080352.
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Technological advances in the field of artificial intelligence offer enormous potential for organizations. In recent years, organizations have leveraged this potential by establishing new business models or adjusting their primary activities. In the meantime, however, the potential for greater efficiency and effectiveness in support functions such as human resource management (HRM), supply chain management (SCM), or financial management (FM) through these technological advances is also increasingly being recognized. We synthesize the current state of research on AI regarding the potentials and diffusion within these support functions. Building upon this, we assess the deinstitutionalization power of AI for altering organizational processes within business support functions and derive implications to harness the full potential of AI across organizations.
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L, Ramyalakshmi, and Girish P. "ARTIFICIAL INTELLIGENCE AND ITS UTILIZATION IN HR AND BUSINESS ANALYTICS." International Journal of Engineering Applied Sciences and Technology 7, no. 3 (July 1, 2022): 100–104. http://dx.doi.org/10.33564/ijeast.2022.v07i03.015.
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Analytics have been employed by companies for several decades, but now many firms are interested in building their capabilities for artificial intelligence (AI) as well. Many AI systems, however, are based on statistics and other forms of analytics. Companies can get a “running start” on AI by building upon their analytical competencies. In the last few years, all companies have been interested in the analysis of data related to Human Resources and have focused on human capital, which is considered the major factor influencing the company’s development and all its activities at all levels of human resource policies. Data analysis (HR analytics) will significantly improve business profitability over the next years. We started with an extensive survey of different human resources problems and risks reported by HR specialists, then a comprehensive review of recent research efforts on computer science techniques proposed to solve these problems, and finally focused on suggested artificial intelligence methods. This review article will be an archive and a reference for computer scientists working on HR by summarizing the IT solutions already made in human resources for the period between 2008 and 2018. It aims to present the issues that HR researchers face and for which computer scientists seek solutions. It summarizes at the same time the recent and different methods, IT approaches, and tools already used by highlighting those using artificial intelligence. AI also provides the HR department with an opportunity to improve the candidate and employee experience by automating repetitive, lowvalue tasks and freeing up the time to focus on more strategic, creative work.
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Fu, Hsin-Pin, Tien-Hsiang Chang, Ying-Hua Teng, Chien-Hung Liu, and Hsiao-Chi Chuang. "Critical Factors Considered by Companies to Introduce Business Intelligence Systems." Axioms 11, no. 7 (July 13, 2022): 338. http://dx.doi.org/10.3390/axioms11070338.
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The advent of intelligent technology has spurred most large companies to introduce business intelligence systems (BIS), but those with low information maturity still have a wait-and-see attitude towards BIS. In order to accelerate the introduction of BIS, this study found and analyzed the critical factors (CFs) considered by companies when introducing BIS. First, the literature on factors considered by companies to introduce BIS was reviewed. The three stages before, during, and after introduction in marketing that organizations undergo during the procurement process were developed into a three-layer hierarchy factor table. An expert questionnaire with pairwise factors was then designed and sent to senior executives in companies that had introduced BIS, and the weights of all factors were calculated by the fuzzy analytic hierarchy process (FAHP) based on the collected questionnaire data. After this, four critical factors—system function integrity, approaching corporate strategy, licensing fee, and information technology maturity—were determined objectively by using the conditions for the acceptable advantage of Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) and further explored in order to help companies input fewer resources, introduce BIS efficiently, and thus increase their decision-making power.
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Buchana, Yasser, and Visvanathan Naicker. "The Effect Of Mobile BI On Organisational Managerial Decision-Making." Journal of Applied Business Research (JABR) 30, no. 4 (June 30, 2014): 1003. http://dx.doi.org/10.19030/jabr.v30i4.8649.
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<p>Managerial decision-making has always involved the use of numerous distinct information resources. Modern managerial decision-making processes require a wealth of information that is enhanced and transformed into knowledge in order to take effective action. Mobility in business is increasingly exercising influence on core business processes of organisations. Recent advances in wireless technologies coupled with the rapid growth of mobile devices in business have led to a new era in business computing. Mobile Business Intelligence (Mobile BI) is a system that has been conceived to assist, accelerate and to enhance the managerial decision-making processes. Drawing from an array of previous studies that attempted to measure the value of Business Intelligence (BI) and other IT systems in organisations, this study develops a new kind of measure which is based on an understanding of the distinct properties of Mobile BI systems in an organisational-oriented context.</p>
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Kudyba, Stephan, Jerry Fjermestad, and Thomas Davenport. "A research model for identifying factors that drive effective decision-making and the future of work." Journal of Intellectual Capital 21, no. 6 (April 16, 2020): 835–51. http://dx.doi.org/10.1108/jic-05-2019-0130.
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PurposeThe evolving digital transformations of organizational processes involve vast complexities. Factors such as labor resources at the individual and team levels that integrate and utilize information resources and evolving technologies to achieve collective intelligence are essential to this process. In order to better understand evolving demands of labor resources, existing research regarding worker/technology interactions for firm performance must be implemented and adapted to the changing market. This paper provides a conceptual research model enabling organizations to better understand the integration of worker/team attributes with collaboration modes, information resources and augmented technologies that yield effective collective intelligence for decision-making.Design/methodology/approachThis manuscript includes a literature review on worker/team attributes interfacing with various technology platforms and the creation of collective intelligence. It then reviews complementary research including leadership elements for organizational outcomes and introduces more current work involving a digital transformation. The literature review provides the underpinnings for a conceptual model that incorporates essential elements for the creation of collective intelligence for decision-making and adds factors that are relevant for digital transformations. These elements include augmented technologies including cognitive technologies, collaborative platforms and worker attributes (skills, social sensitivity, leadership) all of which illustrate components of intellectual capital.FindingsThe paper summarizes key findings of existing research in worker/team interactions with technology platforms on organizational performance and provides an applied, conceptual research model incorporating these findings, along with new elements in the digital era for better identifying new worker requirements.Originality/valueThe value of this work is the introduction of an applied conceptual model based on established literature findings that includes new technologies (e.g. cognitive technologies), collaboration modes and worker/team attributes to address the requirements of the evolving knowledge worker in the digital era. It provides a framework to better understand more optimal resource allocations for the creation of collective intelligence and integrates the model components within an intellectual capital framework.
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Adeel Munawar. "Cloud Computing: Needs Enabling Data Mining and Business Intelligent Applications." Lahore Garrison University Research Journal of Computer Science and Information Technology 5, no. 1 (February 9, 2021): 1–8. http://dx.doi.org/10.54692/lgurjcsit.2021.0501170.
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As a new computational paradigm, cloud computing is attracting a lot of interest from researchers in the field of the business community and information technology sector and it can integrate with several heterogeneous resources makes it distinguished and unique to fulfill the demands of different types of users. The rapid increase in data volume and fixed access to online resources, which is related to all departments need to mine data for the discovery of knowledge. Its principal peculiarities incorporate a versatile asset design and along this line a suitable system for tending to be comprehended in an ideal mode. From the specific situations where cloud computing can be integrated, its use in business information and intelligence also conveys the highest aspirations from data mining to updates. This study gives an outline of the recent condition of the arrangement of Cloud Computing and elaborates, its implications in Business Intelligence and Data Mining. This study defines multiple layers that are expected to create such a framework in distinctive levels of deliberation, from the fundamental equipment stages to the product assets accessible to actualize the applications. At the end of this study, a few cases related to Data mining methodologies have been relocated to the Cloud Computing paradigm.
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Turluev, Rizvan, and Laura Hadjieva. "Artificial Intelligence in Corporate Governance Systems." SHS Web of Conferences 93 (2021): 03015. http://dx.doi.org/10.1051/shsconf/20219303015.
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The presence of a direct causal relationship between management decisions and the analytical and research role of information allows us to prove the strategic importance of information resources. Typically, the need for data is considered at the management level of a company or organization. This position indicates the unambiguity of the confirmation regarding the results of the analyzed data and the possibility of their monetization. Information data is a kind of fundamental basis, demanded by the key structural links of any company. Information serves as an effective identifier of the company's potential opportunities and probable losses in an unstable business environment, as well as quality support from strategically significant initiatives. Of no small importance today is attached to the possibilities of joint application of relevant information on the part of all divisions of the company in order to react as quickly as possible to the transformation of the economic space. It should be noted that information is a kind of asset, the level of efficiency of which is especially important for successful activity. The article discusses artificial intelligence in corporate governance systems.
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Ali Qhal, Eissa Mohammed. "Role of Business Intelligence and Knowledge Management in Solving Business Problems." Tehnički glasnik 16, no. 3 (June 23, 2022): 371–78. http://dx.doi.org/10.31803/tg-20220531145604.
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The term “Business intelligence” is described as a plan or a strategy where the operations like reporting, data analysis, data mining, event processing are performed to improve the production and growth of a business enterprise or a business entity. And on the other hand, the “Knowledge management” is explained as well-organized management of resources and information within a commercial organization it can be a business too. Almost all business will have limitations and challenges which can be also known as the business problems. One of the main business problem is demand, the business plans must work according to the demand of the consumers. Analyzing the demand would provide the solutions for queries like what is the business trend? What is the need of the users? What should be the improvement make in the production? Where is the current position of the enterprise? And who all will be the competitors? For the predictive analysis a dataset of bitcoin is taken. The major aim of the study is to implement the strategies to overcome the business problems mainly the demand prediction. And the objective is to find out the relevant issues and the remedies by using knowledge management and business intelligence to the common business problems. The dataset has columns called lowest price, highest price, open price, close price, trading volume and market capital. The research methodology used is predictive analysis using PCA and K-means clustering algorithm. By this dataset predictive plots are developed as achieved results for easy analysis by using research methodology. PCA and K-means are the algorithm used for accurate prediction. The importance of study is to predict the future sale, as it is very essential for a business enterprise to find future demand so that the organization can improve production.
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Bousquet, Françoise, Vladislav V. Fomin, and Dominique Drillon. "Anticipatory Standards Development and Competitive Intelligence." International Journal of Business Intelligence Research 2, no. 1 (January 2011): 16–30. http://dx.doi.org/10.4018/jbir.2011010102.
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More and more companies operate today in a worldwide market under conditions of globalization, increased complexity, and competition. In such an environment, business decisions need to be made quickly yet intelligent, substantiated by the most salient and relevant information available. Under the global competition, with a diligent and measured manner, many companies are increasingly treating business like an economic war. Enterprises are methodically monitoring and investigating their competitors, while deploying all the resources they have at their disposal in order to beat their current or future rivals. Competitive Intelligence (CI) has become the ‘latest weapon in the world war of economics’. This paper contributes to the growing body of literature on competitive intelligence by synthesizing knowledge stemming from many years of experience in the standardization arena. The authors aim to show how, in the economic war, engaging in committee-based standards development may be used for winning the competition battle.
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Vovk, M. V., O. V. Kindrat, and O. Y. Hrymak. "Information systems and technologies in the business process management." Scientific Messenger of LNU of Veterinary Medicine and Biotechnologies 22, no. 95 (October 28, 2020): 3–9. http://dx.doi.org/10.32718/nvlvet-e9501.
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With the rapid development of information technologies and information economy ingeneral, effective information management determines the success of almost every business operation, and the choice of information and management decisions in general relieson IT managers. However, it is rather difficult for functional or line managers decidewhether it is important to participate in the formation of information strategy of their own business and whether they need to know what tools are available to turn a large array of information into business intelligence. This article is intended to reveal the important role of information and information resources in the activities of modern enterprises. The concepts of “data” and “information” are described. The data model and data types used by business information systems are described. The role of the database in the business process management system is revealed. It is indicated how important it is to form the information space of the enterprise correctly and choose the necessary software product for a particular enterprise. It is determined that the information system of the enterprise is based on the integrated use of potential and available information resources, taking into account their main features. The connections between the component of management systems are investigated and it is noted that the business process management system of the enterprise covers all levels of the enterprise. It is said that the enterprise may face different problems without data administration procedures. The types of information support using different levels of management are given. The internal and external information which his taken into account during making management decisions is characterized. It is proposed to invest in the management practice of developing an information strategy that significantly improves the management process and increases its efficiency. The typical structure of the proposed document and the role of information strategy regarding the levels of enterprise management are given.
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Shehada, Muna, and F. V. Akulinin. "Innovation and information technology in management." Normirovanie i oplata truda v promyshlennosti (Rationing and remuneration of labor in industry), no. 9 (September 1, 2021): 68–72. http://dx.doi.org/10.33920/pro-3-2109-09.
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Information technology, artificial intelligence and other innovative areas of economic development allow manufacturers to reduce their operating costs by improving resource planning. Optimizing supply chain management (SCM) can improve the efficiency of all business processes in an organization, while reducing costs and increasing financial sustainability.
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NIKOLENKO, Larysa. "Governing economic processes using artificial intelligence: conceptual foundation." Economics. Finances. Law, no. 2/2 (February 28, 2020): 15–18. http://dx.doi.org/10.37634/efp.2020.2(2).3.
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Introduction. The article describes the main digital economy development directions on the way of improving business processes management by using modern information technologies. The digital economy is evolving at an incredible rate due to its ability to collect, use and analyze vast amounts of information. A common approach to digital management of the economy is based on the informational resources and their organization. Opportunity to combine external and internal economic information sources, the direction of information flows and modern methods of economic management arises because of local and general management goals and objectives. The purpose of the paper is to develop the management decision-making concept in the context of a dynamically changing environment. This concept should significantly reduce the role of personalized management components and enhance the role of the intellectual component - artificial intelligence. Results. As a result, the digital economy management concept is established, which works at all management levels, and is based on the development of intellectual information processing solutions – artificial intelligence for management and accounting personnel. Opportunities are analyzed for digitalization of the process of establishing the new model of managing the enterprise economical processes, and their practical use along with modern informational trends – artificial intelligence. As long as economical processes of Ukrainian business transform, a mature enterprise management approach should develop, which involves fulfilling six important points in order to fully rebuild the organizational structure. Conclusion. It’s proven that the mature business management approach should be built up while transforming economic enterprise processes. Using artificial intelligence is the key factor in making prudent management decisions and leads to decision transparency and customer trust.
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Chornous, Galyna O., and Viktoriya L. Gura. "Integration of Information Systems for Predictive Workforce Analytics: Models, Synergy, Security of Entrepreneurship." European Journal of Sustainable Development 9, no. 1 (February 1, 2020): 83. http://dx.doi.org/10.14207/ejsd.2020.v9n1p83.
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The era of information economy leads to redesigning not only business models of organizations but also to rethinking the human resources paradigm to harness the power of state-of-the-art technology for Human Capital Management (HCM) optimization. Predictive analytics and computational intelligence will bring transformative change to HCM. This paper deals with issues of HCM optimization based on the models of predictive workforce analytics (WFA) and Business Intelligence (BI). The main trends in the implementation of predictive WFA in the world and in Ukraine, as well as the need to protect business data for security of entrepreneurship and the tasks of predictive analysis in the context of proactive HCM were examined. Some models of effective integration of information systems for predictive WFA were proposed, their advantages and disadvantages were analyzed. These models combine ERP, HCM, BI, Predictive Analytics, and security systems. As an example, integration of HCM system, the analytics platform (IBM SPSS Modeler), BI system (IBM Planning Analytics), and security platform (IBM QRadar Security Intelligence Platform) for predicting the employee attrition was shown. This integration provides a cycle ‘prediction – planning – performance review – causal analysis’ to support protected data-driven decision making in proactive HCM The results of the research support ensuring the effective management of all spectrum of risks associated with the collection, storage and use of data.
Keywords: Workforce Analytics (WFA), Human Capital Management (HCM), Predictive Analytics, Proactive Management, BI, Information Systems (IS), Integration, Security of Entrepreneurship
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Nofal, Muhmmad Islam Mahmoud, and Zawiyah Mohammad Yusof. "Conceptual model of enterprise resource planning and business intelligence systems usage." International Journal of Business Information Systems 21, no. 2 (2016): 178. http://dx.doi.org/10.1504/ijbis.2016.074260.
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Monte Santo Andrade, Sergio Henrique. "Data Analytics to Increase Performance in the Human Resources Area." Journal of Autonomous Intelligence 2, no. 4 (March 31, 2020): 15. http://dx.doi.org/10.32629/jai.v2i4.80.
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In a digital era, traditional areas like Human Resources have to adapt themselves to stay alive and competitive. The processes have been drasticallychanging from paper and talks into systems and workflows. Data is now morethan ever in the spotlight and have become an essential asset to ensure delivery, performance, quality and predictability. But first, data has to be organized, combined, verified, treated and transformed to become meaningful information, not forgetting automatized to be delivered in time and supporting decision making in a daily basis. Business Intelligence (BI) is the tool capable to do it and we are the minds to pull it off.
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Gorbachova, Veronika V., and Natal'ya Yu Sopilko. "HUMAN RESOURCE AS THE MAIN FACTOR IN THE IMPLEMENTATION AND DEVELOPMENT OF BUSINESS INTELLIGENCE SYSTEMS IN AN INDUSTRIAL ENTERPRISE." Science and art of management / Bulletin of the Institute of Economics, Management and Law of the Russian State University for the Humanities, no. 4 (2021): 22–30. http://dx.doi.org/10.28995/2782-2222-2021-4-22-30.
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This paper highlights the existing need to move from traditional principles and methods of managing the activities of industrial enterprises to completely new, automated and technological management tools, the article also underlines the importance of human resources the in those processes. It considers information infrastructure of an organization at the present stage of development as well as the main trends in the development of business analytics, in particular the development of BI projects. Based on the analysis, conclusions are drawn that the efficiency of economic activity directly depends on the capabilities of digital management and the use of the information resources, with a special role assigned to information and analytical systems that allow integrating data in different directions and influencing the speed and quality of decisions made in the company.
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Cheng, Cheng, Kevin Hayes, Kristy Lee, Jill Locascio, and Colleen Lougen. "Big picture in statistical frame – a statistical analysis and data visualization project of price change for electronic resources in academic libraries." Library Hi Tech News 35, no. 6 (August 6, 2018): 12–16. http://dx.doi.org/10.1108/lhtn-09-2017-0071.
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Purpose The purposes of this paper are as follows: first analyze and visualize the price-changing pattern of common electronic resources; second, provide predictions for future price changes at the vendor level; third, discover any potential cause of such price changes; and fourth assess the practice of skills and techniques used for statistical analysis and data visualization. Design/methodology/approach Statistical analysis and data visualization of library’s expenditure data were conducted using business intelligence tools, in this case, Microsoft Excel and IBM SPSS. Findings This study reports the price changes of electronic resources over the past few years, as well as future prediction until 2018. Originality/value Overall, this research combines statistics analysis and data visualization to unveil current price-changing trends of E-resources, provides price prediction of near future and offers unique, while valuable, reference for future evidence-based acquisition decisions.
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Kang, Xi, and Yijun Zeng. "Entrepreneurial Bricolage Based on Big Data and Artificial Intelligence Decision-Making." Wireless Communications and Mobile Computing 2022 (March 14, 2022): 1–7. http://dx.doi.org/10.1155/2022/7821069.
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After entering the new century, the rapid development of information technology has brought a huge impact to traditional social life, which has also triggered drastic changes in the production environment of enterprises. As long as we seize the opportunity of the development of the times, we will quickly accumulate huge wealth. Some new types of companies have surpassed traditional large companies with decades of history in a short period of time, which makes entrepreneurship very attractive. At the same time, the state has also given strong support to people’s entrepreneurship, encouraging capable people to start their own businesses in terms of policies and funds, which has stimulated a wave of entrepreneurship among the people. However, due to the short period of time for the construction of China’s market economy system, the vast majority of new ventures cannot obtain sufficient resource stock to grow and develop and can only turn to the external market to seek opportunities for development. Entrepreneurial bricolage has become a “keyword of the times” in recent years under this background. Previous studies have shown that entrepreneurial bricolage has a relatively positive effect in alleviating the plight of enterprise development resources, and many new ventures regard it as an important way to obtain development resources. The development of big data and artificial intelligence decision-making provides more possibilities for information sharing and personalized analysis and also gives new ventures more opportunities to choose development resources that suit their own characteristics. However, from the actual situation, it is obvious that Chinese enterprises have not achieved very obvious results in how to make full use of big data and artificial intelligence decision-making technology to improve their entrepreneurial and bricolage capabilities. Based on the technical support provided by big data and artificial intelligence decision-making, this research studies the entrepreneurial bricolage activities of China’s new ventures in this context, through the questionnaire survey and tracking analysis of 135 enterprises established in the two provinces from 2015 to 2020. After comparative analysis of a large amount of data, it is found that enterprises that combine big data and artificial intelligence technologies can obtain more high-quality resources and make more informed decisions in the process of starting a business. It can be concluded that the companies that have excellent application of big data and artificial intelligence decision-making technology have more opportunities to obtain ideal resources in entrepreneurial bricolage. The study conducted an in-depth analysis of the problems of China’s new ventures in entrepreneurial bricolage and put forward suggestions for improvement based on the specific conditions of this type of enterprise. It is hoped that it can help start-ups to realize the alleviation of resource constraints.
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Levina, Elena V. "The application of platform solutions in the assessment of corporate resources of industrial enterprises." Market economy problems, no. 3 (2021): 108–16. http://dx.doi.org/10.33051/2500-2325-2021-3-108-116.
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In this article the author examines the features of the use of digital platforms in the assessment and planning of corporate resources of industrial enterprises. The subject of the research is platform solutions and the use of artificial intelligence elements in the process of analyzing corporate resources of business structures. The purpose of the article is to analyze the possibilities of using digital platforms and elements of artificial intelligence in the analysis of the level of availability of necessary resources of industrial enterprises. Materials and methods. The methodological basis of the article consists of theoretical and applied research of Russian and foreign scientists, regulatory legal acts regulating the processes of digital transformation of industries and complexes. The author of the article uses such general scientific methods as analysis and synthesis to study the features of the use of digital platforms in the assessment of corporate resources of enterprises, system, structural, functional and situational approaches to study platform solutions as a system of interrelated and interdependent elements, the method of economic and statistical analysis to study the dynamic aspects and identify patterns of transformation of industries and complexes. Results. The article presents an analysis of the current state of corporate resources of industrial enterprises, and offers a universal method for assessing the level of human resources availability of business structures. Conclusions. In the current conditions of economic transformation, the use of platform solutions with elements of artificial intelligence in the analysis of technical, technological and information and communication support for industrial enterprises is becoming relevant and requires further research, especially in the context of providing industries with highly qualified specialists necessary for the effective operation of business structures. Application. The results obtained can be used for further analysis of the results and implementation of the methodology for evaluating corporate resources of industrial enterprises.
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Li, Jun, Kai Zou, Shang Xiang, Zhen Wan, and Lining Xing. "Complementary External Resource Allocation to Information Security in Smart Cities." Tobacco Regulatory Science 7, no. 5 (September 30, 2021): 1036–48. http://dx.doi.org/10.18001/trs.7.5.21.
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With the rapid development of technologies, such as big data, artificial intelligence, and cloud computing, the work cooperation among cities and the resources involved in business exchanges are deeply complementary. At the same time, information security has become one of the challenges for smart cities, which is ubiquitous and easy to cause public security issues. For this reason, this research modeled the actual problems and then made decisions on resource allocation by considering full cooperation and non-cooperation situations. Their influence with respect to city size, probability of intrusion by illegal users, and propagation probability of one-time intrusion were analyzed. Based on these foundation works, this research proposed incentive mechanisms to ensure the optimized information security for smart cities. These mechanisms ensure that cities not only voluntarily increase the intensity of resource allocation to information security, but also make the co-operation in line with the reality. Therefore, this balances the advantages and disadvantages of non-cooperation and full cooperation, so as to ensure that the information security level of urban agglomerations reaches the optimal state.
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Rajala, Risto, Esko Hakanen, Juri Mattila, Timo Seppälä, and Mika Westerlund. "How Do Intelligent Goods Shape Closed-Loop Systems?" California Management Review 60, no. 3 (March 5, 2018): 20–44. http://dx.doi.org/10.1177/0008125618759685.
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Disruptive technologies can increase the intelligence of goods and revitalize business models in the circular economy. Applying an industrial ecology perspective, this article discusses how intelligent goods can boost the sustainability of industrial ecosystems. North American and European cases highlight how business model innovators can utilize goods-related information to develop more competitive closed-loop systems. The authors identify three archetypes of closed-loop systems—inner circles, decentralized systems, and open systems—and delineate how they leverage information resources for collaboration. This study advances the understanding of closed-loop systems in the circular economy, which is more dependent than ever on digital platforms.
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Monte Santo Andrade, Sergio Henrique. "Data Analytics to Increase Performance in the Human Resources Area." Journal of Autonomous Intelligence 4, no. 1 (March 31, 2021): 59. http://dx.doi.org/10.32629/jai.v4i1.80.
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<p>In a digital era, traditional areas like Human Resources have to adapt themselves to stay alive and competitive. The processes have been drastically changing from paper and talks into systems and workflows. Data is now more than ever in the spotlight and have become an essential asset to ensure delivery, performance, quality and predictability. But first, data has to be organized, combined, verified, treated and transformed to become meaningful information, not forgetting automatized to be delivered in time and supporting decision making in a daily basis. Business Intelligence (BI) is the tool capable to do it and we are the minds to pull it off.</p>
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Khatua, Apalak, Aparup Khatua, Xu Chi, and Erik Cambria. "Artificial Intelligence, Social Media and Supply Chain Management: The Way Forward." Electronics 10, no. 19 (September 25, 2021): 2348. http://dx.doi.org/10.3390/electronics10192348.
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Supply chain management (SCM) is a complex network of multiple entities ranging from business partners to end consumers. These stakeholders frequently use social media platforms, such as Twitter and Facebook, to voice their opinions and concerns. AI-based applications, such as sentiment analysis, allow us to extract relevant information from these deliberations. We argue that the context-specific application of AI, compared to generic approaches, is more efficient in retrieving meaningful insights from social media data for SCM. We present a conceptual overview of prevalent techniques and available resources for information extraction. Subsequently, we have identified specific areas of SCM where context-aware sentiment analysis can enhance the overall efficiency.
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Tiara, Khanna, Siti Nurhayati, and Novita Heriyani. "Optimalisasi Business Intelligence Pada Widuri Berbasis Mediawiki Dalam Monitoring Rekapitulasi Data." Creative Information Technology Journal 4, no. 1 (December 1, 2016): 72. http://dx.doi.org/10.24076/citec.2016v4i1.96.
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Seiring perkembangan zaman dan teknologi pada Perguruan Tinggi yang mengalami peningkatan sangat pesat. Peranan modal intelektual menjadi sangat penting dan strategis dalam pengelolaan program akademik untuk mencapai keunggulan kompetitif. Business Intelligence sebagai elemen penting dalam Perguruan Tinggi difungsikan untuk membantu manajerial mengelola modal intelektual dalam proses pengambilan keputusan guna meningkatkan kinerja Perguruan Tinggi. Penelitian ini bertujuan untuk mengimplementasikan Business Intelligence demi mendukung pengelolaan program akademik kearah yang lebih kompetitif melalui sistem perencanaan, pengukuran dan meningkatkan kinerja berbasis modal intelektual. Salah satu implementasi yang menggunakan sistem Business Intelligence dalam Perguruan Tinggi Raharja ialah website Widuri. Penggunaan Business Intelligence pada Widuri berbasis pada teknologi informasi yang bertujuan untuk mendesain, mengukur, mengelola dan mengembangkan modal intelektual, antara lain berupa pengetahuan, skill dan keahlian sumberdaya manusia Perguruan Tinggi Raharja. Penggunaan indikator kinerja Perguruan Tinggi Raharja dianalisis untuk memenuhi standar mutu Perguruan Tinggi yang kompetitif. Sehingga dengan penggunaan Business Intelligence pada Widuri mempermudah pengguna dan Admin mengetahui data secara akurat.As the development of the times and the technology at the College is currently undergoing a very rapid increase. The role of intellectual capital is becoming very important and strategic in the management of academic programs to achieve competitive advantage. Business Intelligence as an important element in the College functioned to help manage intellectual capital in the managerial decision-making process in order to improve the performance of colleges. This research aims to implement Business Intelligence to support the management of academic program towards a more competitive through a system of planning, measuring and improving performance-based intellectual capital. One implementation uses a system of Business Intelligence in the College website is Widuri Raharja. The use of Business Intelligence in information technology-based Thistle aims to design, measure, manage and develop intellectual capital, inter alia in the form of knowledge, skill and expertise of human resources College Raharja. The use of indicator performance College Raharja analyzed to meet quality standards at competitive Colleges. So with the use of Business Intelligence at Thistle make it easier users and Admins know data accurately.
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Ouedraogo, Dr Honore, Dr Issa Compaoré, and Dr Théophile Bindeouè Nassè. "PRACTICE OF BUSINESS INTELLIGENCE BY SMEs IN BURKINA FASO." International Journal of Management & Entrepreneurship Research 4, no. 1 (January 19, 2022): 48–58. http://dx.doi.org/10.51594/ijmer.v4i1.262.
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The integration of information technologies in business management is essential in the context of the globalization of trade and competition. Small and medium-sized enterprises (SMEs) in Burkina Faso do not escape this constraint with a view to improving productivity. Through an exploratory approach, the objective is to provide a better understanding of the appropriation of Business Intelligence by SMEs in Burkina Faso. Thanks to a mixed, quantitative and qualitative method, sixty SMEs were surveyed and three resource people were interviewed from February to April 2021. The descriptive statistics and the analysis grid led to the results according to which the practice of BI by SMEs in Burkina Faso is at an elementary level, despite its relevance for the organizational performance of SMEs. It should be noted that several myths are to be defied and to be able to adapt BI to the needs and realities of SMEs in Burkina Faso for its popularization. Keywords: Information System, Business Intelligence, Small and Medium Enterprises.