Big data-driven fuzzy cognitive map for prioritising IT service procurement in the public sector

Choi, Youngseok; Lee, Habin; Irani, Zahir

doi:10.1007/s10479-016-2281-6

Cited by 60 publications

(26 citation statements)

References 80 publications

(79 reference statements)

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“…In the UK, big data is being used by the public and private sectors, but its widespread adoption is hampered by the lack of proper big data analytics and, as a result, the skills to harness the full potential of big data. The development of methods for analyzing big data has improved the decision-making process in the procurement of IT services in the public sector [9], and using a conceptual model of the value chain, the role of big data in creating value in public services is investigated, as well as the participation of various government institutions in this process [10].…”

Section: Problem Statementmentioning

confidence: 99%

Big Data in Public Administration

Kokh¹,

Kovaleva²,

Ivanova³

2021

Proceedings of International Scientific and Practical Conference “Russia 2020 - A New Reality: Economy and Society” (ISPCR 2020

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Digital transformation affects all spheres of the modern economy. It also influenced the public administration system, where big data gained special importance. Modern technologies make it possible to collect huge amounts of information from various sources, both official and private. By processing and using big data at all levels of public administration, one can maximize the efficiency of public service delivery to society. In this article, the authors analyze the world experience and results of using big data in the system of state administration. The authors examine the successes in the use of big data in the public administration system in countries such as the PRC, USA, Great Britain, Korea, and in the EU. Particular attention is paid to Russia. The past three years have seen a significant leap forward in the use of big data at the federal and regional levels of government. In Russia, several Government decrees have been adopted aimed at maximizing the use of big data in the activities of state bodies, which will improve the quality of territorial management. The article provides examples of the use of big data in the activities of regional government bodies. The option of using big data in controlling the COVID-19 situation is being considered. The authors note the need for cooperation of big data obtained from government agencies, for example Federal State Statistic Service, with big data received from private structures, for example, from Sberbank.

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Section: Problem Statementmentioning

confidence: 99%

Big Data in Public Administration

Kokh¹,

Kovaleva²,

Ivanova³

2021

Proceedings of International Scientific and Practical Conference “Russia 2020 - A New Reality: Economy and Society” (ISPCR 2020

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“…Sustainable innovation routines are chiefly focused on enhancing the technological operations, resource distribution, and decrease of production expenditures among supply chain partners [30]. Decision making and logistics with respect to procurement, as a component of supply chain management, represents a core business operation associated with the economic efficiency of the entire supply chain related to service and product distribution [31].…”

Section: Environmental and Supply Chain Management Measures In Gppmentioning

confidence: 99%

Environmentally Responsible Behavior and Sustainability Policy Adoption in Green Public Procurement

et al. 2020

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Research has identified that there is a paucity of reviews covering green public procurement (GPP) in terms of environmentally responsible behavior and sustainability policy adoption. Using, comprehensively, the most recent (2017–2020) and relevant (Web of Science- and Scopus-indexed) empirical sources, our paper fills the gap in the literature by focusing on the main developing streams of research, that is: How GPP drives the circular economy; GPP of construction and building materials; environmental and supply chain management measures in GPP; the procurement of sustainable innovation; environmental policy objectives of GPP as regards energy, pollution, carbon footprint, and climate change; GPP as an environmental policy mechanism for production and use of sustainable goods and services; and GPP as an integral component of sustainable development and performance. Further investigations can explore hot topics related to the role of GPP in the automated algorithmic decision-making processes taking place in data-driven smart sustainable cities because the harnessing, among other things, of sensing and computing technologies, network connectivity systems, and the Cognitive Internet of Things will fulfill the incessant exigencies of public administration.

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“…The FCM approach has proven its ability to deal with uncertainty in several domain systems [15,16]. Authors in [17] proposed a decision model based on big data analytics and FCM qualitative approach for improving the decision making for IT service procurement process. Authors in [18] introduced Web-mining inference mechanism using FCM inference to analyze the Web data in order to extract useful knowledge.…”

Section: Perspectives On Fcmmentioning

confidence: 99%

Representing and Simulating Uncertainty of the Quality of Service of Web Services using Fuzzy Cognitive Map Approach

Obiedat¹,

Khasawneh²,

Banikhalaf³

et al. 2020

IJACSA

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Web services are growing rapidly to provide clients, either organizations or individuals, with multiple Internet services and to offer solutions for the integration of many applications. Quality of Service (QoS) of a Web service is the key consideration of both service providers and users. Thus, measuring the QoS requires, in addition to its normative requirements, engaging the views of clients and service providers and environmental factors. Human intervention and the environment may lead to uncertainty and result in uncertain factors in assessing QoS. In such a case, traditional computing and statistical techniques cannot provide an accurate representation of inherited uncertainties, especially when uncertain variables are connected with ambiguous (fuzzy) relationships. An alternative is to use a soft computing approach. This paper proposes a Fuzzy Cognitive Map (FCM) model as a soft computing approach that can represent and simulate the uncertainty of QoS. FCM represents the uncertain variables in the domain knowledge and their connections in the form of a signed directed graph consisting of nodes representing the variables and directed arrows representing the cause-effect relationships. In addition, it allows representing imprecise data either using numeric data, i.e. in the ranges [0, 1] and [-1, 1], or linguistic data, i.e., "low, medium, high". For calculations, FCM is converted to an adjacency matrix to find the effects of variables on each other. Scenario simulations can also be implemented to help decision makers to investigate appropriate outcomes. Finally, the proposed approach is tested by an experiment to demonstrate its reasonability and admissibility of the representation and simulation of the uncertainty of the QoS domain knowledge.

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Big data-driven fuzzy cognitive map for prioritising IT service procurement in the public sector

Cited by 60 publications

References 80 publications

Big Data in Public Administration

Big Data in Public Administration

Environmentally Responsible Behavior and Sustainability Policy Adoption in Green Public Procurement

Representing and Simulating Uncertainty of the Quality of Service of Web Services using Fuzzy Cognitive Map Approach

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