Academic literature on the topic 'Financial Decision Support'

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Journal articles on the topic "Financial Decision Support"

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Kundisch, Dennis, and Jochen Dzoienziol. "Decision Support for Financial Planning." Journal of Decision Systems 17, no. 2 (January 2008): 175–209. http://dx.doi.org/10.3166/jds.17.175-209.

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Zopounidis, Constantin, Dimitrios Niklis, and Michalis Doumpos. "“Financial decision support”: feature issue editorial." EURO Journal on Decision Processes 6, no. 1-2 (March 9, 2018): 61–62. http://dx.doi.org/10.1007/s40070-018-0080-9.

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McDonald, H. Stephen, Chris Stori, and Greg Dennis. "FINANCIAL DECISION SUPPORT FOR PROJECT FINANCING AND REVENUE PROGRAM DEVELOPMENT." Proceedings of the Water Environment Federation 2003, no. 11 (January 1, 2003): 28–29. http://dx.doi.org/10.2175/193864703784756075.

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Palma-dos-Reis, António, and Fatemeh “Mariam” Zahedi. "Designing personalized intelligent financial decision support systems." Decision Support Systems 26, no. 1 (July 1999): 31–47. http://dx.doi.org/10.1016/s0167-9236(99)00027-5.

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Holland, Michael M., and J. Louis Heck. "PROPHET: A FINANCIAL MANAGEMENT DECISION SUPPORT SYSTEM." Financial Review 20, no. 3 (August 1985): 60. http://dx.doi.org/10.1111/j.1540-6288.1985.tb00238.x.

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Dimitras, A., and C. Siriopoulos. "Modelling and decision support in financial markets." Operational Research 6, no. 2 (May 2006): 83–84. http://dx.doi.org/10.1007/bf02941225.

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Shumilin, P. E., and V. A. Eremenko. "ACCOUNTING MODEL OF DECISION SUPPORT SYSTEM." Scientific Review: Theory and Practice 10, no. 4 (May 4, 2020): 612–19. http://dx.doi.org/10.35679/2226-0226-2020-10-4-612-619.

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The digital development of the economy opens up new horizons for accounting. On the one hand, dissolution of accounting in corporate management systems takes place, on the other hand, the accounting functions for managing economic information remain relevant. This article uses the accounting modeling method. We offer a five-blocks accounting model of the decision support system. The model is formed by such blocks as the interface for collecting primary data on company transactions in the context of the formation of financial, managerial, strategic accounting accounts, ETL (extract, transform, loading) of processes for combining credentials from various sources within the framework of a structured work plan of accounts; predicted accounting iterations, having a synergistic, reorganization, reorganization, immunization, hedging and other areas; express audit of the management decision, which consists in assessing the impact of the management decision on the effectiveness of the company, which includes such elements as tax and legal expertise; SWOT analysis; reporting visualization tools that allow you to generate different types of reporting: financial, managerial, statistical, not just in tabular form, but using digital visualization methods; accounting and analytical indicators of managerial decisions, which can be described as a system of indicators reflecting the financial and economic situation of the enterprise under the influence of managerial decisions; the state of its financial stability, profitability, solvency, liquidity; the size of the property of the founders. The introduction and use of this model will allow generating relevant accounting information based on the needs of management, supporting the adoption of management decisions at a scientifically sound level that meets the criteria of business efficiency and protect the interests of owners.
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Tsai, Chih-Fong. "Financial decision support using neural networks and support vector machines." Expert Systems 25, no. 4 (September 2008): 380–93. http://dx.doi.org/10.1111/j.1468-0394.2008.00449.x.

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Tynjala, Teemu. "Validation in Supply Chain Decision Support Systems." International Journal of Information Systems and Supply Chain Management 5, no. 2 (April 2012): 39–58. http://dx.doi.org/10.4018/jisscm.2012040103.

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Decision Support Systems are used currently to support various high impact decisions in industry. This study explores the subcategory of DSSs related to Supply Chain Management. More precisely we explore the problem of integrating companies’ strategic supply chain decision support systems to financial reporting systems for the purpose of validation. The study is done through literature survey, and inductive case studies. The author finds that integration is challenging because systems are typically disjoint and capture data at different levels of granularity. The author conceptualizes the present problem and proposes a generic solution framework.
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Ruzakova, O. "DECISION SUPPORT SYSTEM IN THE TASKS OF FINANCIAL ANALYSIS." Agrosvit, no. 5 (March 19, 2019): 67. http://dx.doi.org/10.32702/2306-6792.2019.5.67.

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Dissertations / Theses on the topic "Financial Decision Support"

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Goonatilake, Suran. "An intelligent hybrid system for financial decision support." Thesis, University College London (University of London), 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.307300.

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Gao, Shijia. "Intelligent agent assisted decision support for family financial planning /." access full-text access abstract and table of contents, 2005. http://libweb.cityu.edu.hk/cgi-bin/ezdb/thesis.pl?mphil-is-b19887735a.pdf.

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Thesis (M.Phil.)--City University of Hong Kong, 2005.
"Submitted to Department of Information Systems in partial fulfillment of the requirements for the degree of Master of Philosophy" Includes bibliographical references (leaves 114-132)
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Hamilton, S. Keith. "A financial decision support system for U.S. Navy public works departments." Thesis, Monterey, California. Naval Postgraduate School, 1989. http://hdl.handle.net/10945/27055.

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Manongga, D. H. F. "Using genetic algorithm-based methods for financial analysis." Thesis, University of East Anglia, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.320950.

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McIntyre-Bahatty, Yasen Timothy. "Neural network modelling, evaluation and end-user orientation in the financial markets." Thesis, University of Bristol, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.389130.

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Muntermann, Jan. "Event-driven mobile financial Information-Services : design of an intraday decision support System /." Wiesbaden : Dt. Univ.-Verl, 2007. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=016494719&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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Hedén, Per Julian. "Real-time decision support system using visualization of a global decentralized financial system." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-260330.

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Decentralized digital currencies are emerging in today’s society. Bitcoin was the first to surface in late 2009, and today there are thousands of digital currencies with various properties. The vast amount of transaction data being generated from decentralized systems can be difficult to comprehend. Information visualization can be used to simplify this apprehension difficulty. It is a tool that allows us to effectively understand complex data by projecting it to a visual medium. This is a research study on multiple stakeholders for a web-based real-time decision support system for visualizing transaction data in a global decentralized financial system and set out to explore the stakeholders requirements in order to provide them support. To achieve this, an exploratory interview was conducted in order to gain knowledge of the requirements for each type of stakeholders. After which, a prototype of the decision support system was made, built upon the requirements and fundamental principles in information visualization. The prototype is web compliant with room for configurations to personalize. It is best suited for an overview. Complementary research could be additional studies on the stakeholders to improve the usability or develop additional supportive features to make it a smart system.
Decentraliserade digitala valutor växer fram i dagens samhälle. Bitcoin var den första som skapades i slutet av 2009 och idag finns det tusentals digitala valutor med olika egenskaper. Den stora mängd transaktionsdata som genereras från decentraliserade system kan vara svår att förstå. Informationsvisualisering kan användas för att förenkla denna förståelsen. Det är ett verktyg som gör det möjligt för oss att effektivt förstå komplex data genom att projicera det till ett visuellt medium. Detta är en undersökning på multipla användare för ett webbaserat realtid beslutstödssystem för att visualisera transaktionsdata i ett globalt decentraliserat finansiellt system med mål att utarbeta användarnas krav för att kunna ge dom stöd. För att uppnå detta genomfördes en förberedande intervju för att få kunskap om kraven för varje typ av användare. Därefter gjordes en prototyp av beslutsstödsystemet, byggt på kraven och grundläggande principer för informationsvisualisering. Prototypen är webkompatibel med utrymme för konfigurationer för att personifiera. Den passar bäst för att ge en översikt. Kompletterande forskning kan vara ytterligare studier på intressenterna för att förbättra användbarheten eller utveckla ytterligare stödfunktioner för att göra det till ett smart system.
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Rajabi, Mohammad. "New decision support systems for Public Private Partnership projects." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/25747.

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It is well established that one of the key contributing factors to the growth of countries’ economies is the existence of appropriate economic and social infrastructures. The setup of these infrastructures and their operation or delivery of public services associated with them have proved to be a costly and often unaffordable business for most governments. Therefore, private sector participation in the delivery of public services has been opted for by governments under Public-Private Partnerships (PPPs). Additional reasons for the public sector to choose a PPP framework to deliver public services include the public sector representatives’ lack of sufficient technical knowledge and specifications required by most projects; the required amount of investment to implement such projects is too high to be affordable by the public sector alone; the increasing difficulties of predicting and controlling the uncertainties that typically govern the phases of such projects including the level of actual demand for the related services by the time the project is operational; the level of bureaucracy in the public sector and its implications on the time frame of decision-making processes; the relatively low efficiency in project execution by the public sector; and most importantly the fact that, in practice, these difficulties are often better managed by the private sector who seem to possess both the financial and the executive capabilities to undertake such projects Currently, there is a gap in the game theory literature on modelling PPP related decisions and issues. This thesis contributes to reducing such gap by proposing three novel and practice-oriented game theoretical models along with algorithms for solving them, namely an ordinal game for the shortlisting of potential private sector partners; two non-cooperative dynamic games for negotiation with shortlisted private sector partners and selection of private sector partner to award the PPP contract to; and a non-cooperative dynamic game for financial renegotiation post-PPP contract award. In sum, each novel game addresses an important problem faced by the private sector during the typical stages of the life cycle of PPPs, namely private sector partner selection at the tendering stage; negotiation between the public sector and shortlisted bidders to select the candidate to whom to award a PPP contract to at the post-tendering stage; and financial re-negotiation between the public sector and the selected private sector partner at the post-contract award stage.
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Hamilton, Angela. "Simulations for Financial Literacy." Master's thesis, University of Central Florida, 2012. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5235.

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Financially literate consumers are empowered with the knowledge and skills necessary to make sound financial decisions that ensure their long-term economic well-being. Within the context of the range of cognitive, psychological, and social factors that influence consumer behavior, simulations enhance financial literacy by developing consumers' mental models for decision-making. Technical communicators leverage plain language and visual language techniques to communicate complex financial concepts in ways that consumers can relate to and understand. Simulations for financial education and decision support illustrate abstract financial concepts, provide a means of safe experimentation, and allow consumers to make informed choices based on a longitudinal comparison of decision outcomes. Technical communicators develop content based on best practices and conduct evaluations to ensure that simulations present information that is accessible, usable, and focused on the end-user. Potential simulation formats range from low- to high-fidelity. Low-fidelity simulations present static data in print or digital formats. Mid-fidelity simulations provide digital interactive decision support tools with dynamic user inputs. More complex high-fidelity simulations use narrative and dramatic elements to situate learning in applied contexts.
ID: 031001493; System requirements: World Wide Web browser and PDF reader.; Mode of access: World Wide Web.; Adviser: Dan Jones.; Title from PDF title page (viewed July 25, 2013).; Thesis (M.A.)--University of Central Florida, 2012.; Includes bibliographical references (p. 76-80).
M.A.
Masters
English
Arts and Humanities
English; Technical Communications
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Meharia, Priyanka. "USE OF VISUALIZATION IN DIGITAL FINANCIAL REPORTING: THE EFFECT OF SPARKLINE." UKnowledge, 2012. http://uknowledge.uky.edu/busadmin_etds/1.

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Information visualization (InfoViz) is an essential component of decision support systems (DSS). Sparklines is a visualization tool. This study examines if Sparklines in digital financial reports aids novice investors and if so under what circumstances? Does it enhances decision-making performance and facilitates effective decision-making experience? Additionally, does it lowers decision making effort; reduces dilution effect from non-relevant data in financial reports and mitigates recency bias in using digital financial reports? The hypothesis is guided by the theory of Proximity Compatibility Principle and the Theory of Cognitive Fit. The research methodology for this study is a repeated measure, controlled laboratory based experiment. A pilot test was conducted in with a sample of forty undergraduate students from Gatton College of Business and Economics. The sample size for this study was 275 subjects. The result revealed that there was significant effect of sparklines on decision making performance and it provides an incremental value over a tabular format. Sparklines makes an important contribution towards mitigating recency bias. The results also suggested that the irrelevant information cue in the shareholder’s report were not able to weaken the impact of relevant information in the audited financial data reported using sparklines. Sparklines increased the attention of the readers to the tables. Subjects performed the integrative tasks and spatial better when using Sparklines. For tasks such as symbolic tasks, Sparkline does not necessarily improve decision performance. It was also found out that decision makers experience greater satisfaction when using sparklines. The overall cognitive load experienced by subjects was lower using sparklines when task demands are high (such as in a bankruptcy prediction task). Interestingly, the results indicate that there is no significant effect of sparkline on decision confidence and time. In conclusion, recall of facts and pattern among subjects was found superior with use of sparkline. This study provides an empirical and justifiable basis for policy makers to make explicit recommendations about use of novel graphics such as sparkline in digital financial reports. Limitations of this study are noted.
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Books on the topic "Financial Decision Support"

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Wong, J. A. M. Financial decision support system in the hospitality industry. Oxford: Oxford Brookes University, 1998.

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Ip, Yiu Lam. Design a decision support system for personal financial advisory function. [s.l: The Author], 1992.

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Hamilton, S. Keith. A financial decision support system for U.S. Navy public works departments. Monterey, Calif: Naval Postgraduate School, 1989.

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Fink, Carl. Knowledge-based systems for financial executives. Morristown, N.J: Financial Executives Research Foundation, 1991.

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Nzeako, Jude Okwudiri. A prototype decision support system to support the accountants role in the provision of financial advice and preparation of financial information. London: University of East London, 1996.

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Morrow, Alice Mills. Making financial decisions when divorce occurs: An Oregon guide. [Corvallis, Or: Oregon State University Extension Service, 1986.

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Morrow, Alice Mills. Making financial decisions when divorce occurs: An Oregon guide. Corvallis, Or: Oregon State University Extension Service, 1990.

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Charaeva, Marina. Corporate finance management strategy: investments and risks. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1064905.

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The article examines and develops the methodological and methodological basis of corporate finance management in the context of their strategic development, when investment and financing decisions are particularly relevant from the point of view of determining acceptable risks and the financial well-being of the corporation. The conceptual and methodological foundations of analytical support for corporate finance management are developed, based on the definition of investment policy, its implementation through investment business planning and identification and assessment of financial risks in the framework of achieving strategic goals related to the modernization of Russian corporations. The ways of improving the quality of the corporate finance management strategy based on the introduction of budgeting technology and the use of controlling the implementation of the corporation's financial strategy are proposed. It is intended for postgraduates, undergraduates, university teachers, researchers and practitioners, full-time and part-time students studying in the areas of "Economics", "Management", "Finance and Credit" (master's level), as well as anyone interested in the problems of strategic management of corporate finance.
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Budget issues: Financial reporting to better support decision-making. Washington, D.C: The Office, 1993.

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Erickson, Mark Allen. Financial and real options theory and lattice techniques. 2000.

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Book chapters on the topic "Financial Decision Support"

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Forcellati, Corrado Lillelund, Claire Georgeson, Mikael Lind, Sukhjit Singh, Carl Sjöberger, and Johan Woxenius. "Support for Financial Decision-Making." In Progress in IS, 255–73. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-50892-0_16.

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Junginger, W., and A. Kor. "Decision Support in Financial Planning." In Operations Research ’92, 326–29. Heidelberg: Physica-Verlag HD, 1993. http://dx.doi.org/10.1007/978-3-662-12629-5_94.

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Zopounidis, Constantin, and Michael Doumpos. "Decision Support Systems." In Intelligent Decision Aiding Systems Based on Multiple Criteria for Financial Engineering, 37–82. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4663-4_2.

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Ireland, A. M., and M. A. H. Dempster. "A Financial Expert Decision Support System." In Mathematical Models for Decision Support, 415–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-83555-1_25.

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Locarek, Hermann, and Carl-M. Preuß. "Dsfinance — Decision Support for Financial Planning." In Knowledge, Data and Computer-Assisted Decisions, 337–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-84218-4_26.

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Sánchez-Cervantes, José Luis, Giner Alor-Hernández, María del Pilar Salas-Zárate, Jorge Luis García-Alcaraz, and Lisbeth Rodríguez-Mazahua. "FINALGRANT: A Financial Linked Data Graph Analysis and Recommendation Tool." In Exploring Intelligent Decision Support Systems, 3–26. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74002-7_1.

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Weber, Bruce W. "Financial DSS: Systems for Supporting Investment Decisions." In Handbook on Decision Support Systems 2, 419–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-48716-6_20.

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Methlie, Leif B. "On Knowledge-Based Decision Support Systems for Financial Diagnostics." In Decision Support Systems: Theory and Application, 335–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-83088-4_12.

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Zopounidis, Constantin, and Michael Doumpos. "Knowledge-Based Decision Support Systems." In Intelligent Decision Aiding Systems Based on Multiple Criteria for Financial Engineering, 121–66. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4663-4_4.

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Drenik, E. Delidzakova. "The context-sensitivity of a financial management controlling system in a company undergoing restructuring." In Context Sensitive Decision Support Systems, 146–57. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-0-387-35356-2_9.

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Conference papers on the topic "Financial Decision Support"

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Tseng, Chiu-Che. "Probabilistic Financial Decision Support Framework." In 9th Joint Conference on Information Sciences. Paris, France: Atlantis Press, 2006. http://dx.doi.org/10.2991/jcis.2006.244.

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Shijia Gao, Huaiqing Wang, Dongming Xu, Yingfeng Wang, Wenqi Shen, and Siubun Yeung. "Intelligent Decision Support for Family Financial Planning." In Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06). IEEE, 2006. http://dx.doi.org/10.1109/hicss.2006.224.

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Lawrencia, Clarisca, and Win Ce. "Fraud Detection Decision Support System for Indonesian Financial Institution." In 2019 International Conference on Information Management and Technology (ICIMTech). IEEE, 2019. http://dx.doi.org/10.1109/icimtech.2019.8843719.

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Zhang, Minli, Yueran Gu, and Junwu Zhu. "Analysis of the Framework for Financial Decision Support System." In 2009 International Conference on Wireless Networks and Information Systems (WNIS). IEEE, 2009. http://dx.doi.org/10.1109/wnis.2009.66.

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Du, LingLing. "Financial Decision Support System Research Based on Data Warehouse." In 2009 International Conference on Information Management, Innovation Management and Industrial Engineering. IEEE, 2009. http://dx.doi.org/10.1109/iciii.2009.163.

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Pawełoszek, Ilona. "Integrating Semantic Web Services into Financial Decision Support Process." In 2016 Federated Conference on Computer Science and Information Systems. IEEE, 2016. http://dx.doi.org/10.15439/2016f99.

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Rigopoulos, George, Nikolaos Karadimas, Alessandra Orsoni, and Javier Otamendi. "An Interactive Web Based Decision Support System for Financial Decisions within a Team." In 2007 Innovations in Information Technologies (IIT). IEEE, 2007. http://dx.doi.org/10.1109/iit.2007.4430455.

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Yada, Katsutoshi, and Kohei Ichikawa. "Decision support system for policy making during a financial crisis." In 2011 IEEE International Conference on Granular Computing (GrC-2011). IEEE, 2011. http://dx.doi.org/10.1109/grc.2011.6122693.

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Korczak, Jerzy, Marcin Hernes, and Maciej Bac. "Fuzzy logic in the multi-agent financial decision support system." In 2015 Federated Conference on Computer Science and Information Systems. IEEE, 2015. http://dx.doi.org/10.15439/2015f155.

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Perevozchikov, Nikita, and Oleg Golovnin. "Decision-Making Support for Supervisory Control of Non-Banking Financial Institutions." In 8th Scientific Conference on Information Technologies for Intelligent Decision Making Support (ITIDS 2020). Paris, France: Atlantis Press, 2020. http://dx.doi.org/10.2991/aisr.k.201029.011.

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Reports on the topic "Financial Decision Support"

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Rusk, Todd, Ryan Siegel, Linda Larsen, Tim Lindsey, and Brian Deal. Technical and Financial Feasibility Study for Installation of Solar Panels at IDOT-owned Facilities. Illinois Center for Transportation, August 2021. http://dx.doi.org/10.36501/0197-9191/21-024.

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The Smart Energy Design Assistance Center assessed the administrative, technical, and economic aspects of feasibility related to the procurement and installation of photovoltaic solar systems on IDOT-owned buildings and lands. To address administrative feasibility, we explored three main ways in which IDOT could procure solar projects: power purchase agreement (PPA), direct purchase, and land lease development. Of the three methods, PPA and direct purchase are most applicable for IDOT. While solar development is not free of obstacles for IDOT, it is administratively feasible, and regulatory hurdles can be adequately met given suitable planning and implementation. To evaluate IDOT assets for solar feasibility, more than 1,000 IDOT sites were screened and narrowed using spatial analytic tools. A stakeholder feedback process was used to select five case study sites that allowed for a range of solar development types, from large utility-scale projects to small rooftop systems. To evaluate financial feasibility, discussions with developers and datapoints from the literature were used to create financial models. A large solar project request by IDOT can be expected to generate considerable attention from developers and potentially attractive PPA pricing that would generate immediate cash flow savings for IDOT. Procurement partnerships with other state agencies will create opportunities for even larger projects with better pricing. However, in the near term, it may be difficult for IDOT to identify small rooftop or other small on-site solar projects that are financially feasible. This project identified two especially promising solar sites so that IDOT can evaluate other solar site development opportunities in the future. This project also developed a web-based decision-support tool so IDOT can identify potential sites and develop preliminary indications of feasibility. We recommend that IDOT begin the process of developing at least one of their large sites to support solar electric power generation.
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Homan, Rick, and Catherine Searle. Programmatic implications of a cost study of home-based care programs in South Africa. Population Council, 2005. http://dx.doi.org/10.31899/hiv14.1001.

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The HIV/AIDS epidemic has meant that an increasing number of chronically ill people need ongoing assistance with care and support. Programs providing home-based care (HBC) services are a key component of the response to HIV/AIDS. However, few programs are using operations research, including cost studies, to decide what services to provide and how to structure their services. In 2004, the Horizons Program undertook a study of six HBC programs from different South African provinces to provide key information to NGOs, government ministries, donors, and the programs themselves to inform decisions about service delivery. The study analyzed the cost of HBC services, the best use of resources, and how well programs are able to meet the needs of beneficiaries and their families. The sample represents programs that operate in rural areas and informal settlements. This brief focuses on the coverage, organization, volume, and costs of the services and on findings from two of the methods of data collection: financial records and service statistics, and interviews with financial officers, program managers, and caregivers.
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Nitz, Peter, and Jürgen Fluch. Collection of available solar process heat related national and trans-national research and funding programs. IEA SHC Task 64, April 2021. http://dx.doi.org/10.18777/ieashc-task64-2021-0001.

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Within Task 64/IV Solar Process Heat, Subtask E Guideline to Market is aiming to support a wider penetration of solar thermal technologies in the supply of heating (and cooling) in industry, demonstrating Solar Heat for Industrial Processes (SHIP) to be an important contribution to the decarbonisation of the industrial sector. This requires not only to overcome technical and/or technological barriers, but it is crucial to also address on technical barriers. Whereas well suited system integration strategies, design tools, standardized procedures or modular components are all in all paramount for the development of reliable and prompt off the shelve solutions, experience shows that often non-technological barriers might have a critical role in the decision making process. Above all, competitiveness and investment/financing related barriers prove in many cases to be the bottleneck for the adoption of solar thermal technologies in the industrial framework.
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Vargas-Herrera, Hernando, Juan Jose Ospina-Tejeiro, Carlos Alfonso Huertas-Campos, Adolfo León Cobo-Serna, Edgar Caicedo-García, Juan Pablo Cote-Barón, Nicolás Martínez-Cortés, et al. Monetary Policy Report - April de 2021. Banco de la República de Colombia, July 2021. http://dx.doi.org/10.32468/inf-pol-mont-eng.tr2-2021.

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1.1 Macroeconomic summary Economic recovery has consistently outperformed the technical staff’s expectations following a steep decline in activity in the second quarter of 2020. At the same time, total and core inflation rates have fallen and remain at low levels, suggesting that a significant element of the reactivation of Colombia’s economy has been related to recovery in potential GDP. This would support the technical staff’s diagnosis of weak aggregate demand and ample excess capacity. The most recently available data on 2020 growth suggests a contraction in economic activity of 6.8%, lower than estimates from January’s Monetary Policy Report (-7.2%). High-frequency indicators suggest that economic performance was significantly more dynamic than expected in January, despite mobility restrictions and quarantine measures. This has also come amid declines in total and core inflation, the latter of which was below January projections if controlling for certain relative price changes. This suggests that the unexpected strength of recent growth contains elements of demand, and that excess capacity, while significant, could be lower than previously estimated. Nevertheless, uncertainty over the measurement of excess capacity continues to be unusually high and marked both by variations in the way different economic sectors and spending components have been affected by the pandemic, and by uneven price behavior. The size of excess capacity, and in particular the evolution of the pandemic in forthcoming quarters, constitute substantial risks to the macroeconomic forecast presented in this report. Despite the unexpected strength of the recovery, the technical staff continues to project ample excess capacity that is expected to remain on the forecast horizon, alongside core inflation that will likely remain below the target. Domestic demand remains below 2019 levels amid unusually significant uncertainty over the size of excess capacity in the economy. High national unemployment (14.6% for February 2021) reflects a loose labor market, while observed total and core inflation continue to be below 2%. Inflationary pressures from the exchange rate are expected to continue to be low, with relatively little pass-through on inflation. This would be compatible with a negative output gap. Excess productive capacity and the expectation of core inflation below the 3% target on the forecast horizon provide a basis for an expansive monetary policy posture. The technical staff’s assessment of certain shocks and their expected effects on the economy, as well as the presence of several sources of uncertainty and related assumptions about their potential macroeconomic impacts, remain a feature of this report. The coronavirus pandemic, in particular, continues to affect the public health environment, and the reopening of Colombia’s economy remains incomplete. The technical staff’s assessment is that the COVID-19 shock has affected both aggregate demand and supply, but that the impact on demand has been deeper and more persistent. Given this persistence, the central forecast accounts for a gradual tightening of the output gap in the absence of new waves of contagion, and as vaccination campaigns progress. The central forecast continues to include an expected increase of total and core inflation rates in the second quarter of 2021, alongside the lapse of the temporary price relief measures put in place in 2020. Additional COVID-19 outbreaks (of uncertain duration and intensity) represent a significant risk factor that could affect these projections. Additionally, the forecast continues to include an upward trend in sovereign risk premiums, reflected by higher levels of public debt that in the wake of the pandemic are likely to persist on the forecast horizon, even in the context of a fiscal adjustment. At the same time, the projection accounts for the shortterm effects on private domestic demand from a fiscal adjustment along the lines of the one currently being proposed by the national government. This would be compatible with a gradual recovery of private domestic demand in 2022. The size and characteristics of the fiscal adjustment that is ultimately implemented, as well as the corresponding market response, represent another source of forecast uncertainty. Newly available information offers evidence of the potential for significant changes to the macroeconomic scenario, though without altering the general diagnosis described above. The most recent data on inflation, growth, fiscal policy, and international financial conditions suggests a more dynamic economy than previously expected. However, a third wave of the pandemic has delayed the re-opening of Colombia’s economy and brought with it a deceleration in economic activity. Detailed descriptions of these considerations and subsequent changes to the macroeconomic forecast are presented below. The expected annual decline in GDP (-0.3%) in the first quarter of 2021 appears to have been less pronounced than projected in January (-4.8%). Partial closures in January to address a second wave of COVID-19 appear to have had a less significant negative impact on the economy than previously estimated. This is reflected in figures related to mobility, energy demand, industry and retail sales, foreign trade, commercial transactions from selected banks, and the national statistics agency’s (DANE) economic tracking indicator (ISE). Output is now expected to have declined annually in the first quarter by 0.3%. Private consumption likely continued to recover, registering levels somewhat above those from the previous year, while public consumption likely increased significantly. While a recovery in investment in both housing and in other buildings and structures is expected, overall investment levels in this case likely continued to be low, and gross fixed capital formation is expected to continue to show significant annual declines. Imports likely recovered to again outpace exports, though both are expected to register significant annual declines. Economic activity that outpaced projections, an increase in oil prices and other export products, and an expected increase in public spending this year account for the upward revision to the 2021 growth forecast (from 4.6% with a range between 2% and 6% in January, to 6.0% with a range between 3% and 7% in April). As a result, the output gap is expected to be smaller and to tighten more rapidly than projected in the previous report, though it is still expected to remain in negative territory on the forecast horizon. Wide forecast intervals reflect the fact that the future evolution of the COVID-19 pandemic remains a significant source of uncertainty on these projections. The delay in the recovery of economic activity as a result of the resurgence of COVID-19 in the first quarter appears to have been less significant than projected in the January report. The central forecast scenario expects this improved performance to continue in 2021 alongside increased consumer and business confidence. Low real interest rates and an active credit supply would also support this dynamic, and the overall conditions would be expected to spur a recovery in consumption and investment. Increased growth in public spending and public works based on the national government’s spending plan (Plan Financiero del Gobierno) are other factors to consider. Additionally, an expected recovery in global demand and higher projected prices for oil and coffee would further contribute to improved external revenues and would favor investment, in particular in the oil sector. Given the above, the technical staff’s 2021 growth forecast has been revised upward from 4.6% in January (range from 2% to 6%) to 6.0% in April (range from 3% to 7%). These projections account for the potential for the third wave of COVID-19 to have a larger and more persistent effect on the economy than the previous wave, while also supposing that there will not be any additional significant waves of the pandemic and that mobility restrictions will be relaxed as a result. Economic growth in 2022 is expected to be 3%, with a range between 1% and 5%. This figure would be lower than projected in the January report (3.6% with a range between 2% and 6%), due to a higher base of comparison given the upward revision to expected GDP in 2021. This forecast also takes into account the likely effects on private demand of a fiscal adjustment of the size currently being proposed by the national government, and which would come into effect in 2022. Excess in productive capacity is now expected to be lower than estimated in January but continues to be significant and affected by high levels of uncertainty, as reflected in the wide forecast intervals. The possibility of new waves of the virus (of uncertain intensity and duration) represents a significant downward risk to projected GDP growth, and is signaled by the lower limits of the ranges provided in this report. Inflation (1.51%) and inflation excluding food and regulated items (0.94%) declined in March compared to December, continuing below the 3% target. The decline in inflation in this period was below projections, explained in large part by unanticipated increases in the costs of certain foods (3.92%) and regulated items (1.52%). An increase in international food and shipping prices, increased foreign demand for beef, and specific upward pressures on perishable food supplies appear to explain a lower-than-expected deceleration in the consumer price index (CPI) for foods. An unexpected increase in regulated items prices came amid unanticipated increases in international fuel prices, on some utilities rates, and for regulated education prices. The decline in annual inflation excluding food and regulated items between December and March was in line with projections from January, though this included downward pressure from a significant reduction in telecommunications rates due to the imminent entry of a new operator. When controlling for the effects of this relative price change, inflation excluding food and regulated items exceeds levels forecast in the previous report. Within this indicator of core inflation, the CPI for goods (1.05%) accelerated due to a reversion of the effects of the VAT-free day in November, which was largely accounted for in February, and possibly by the transmission of a recent depreciation of the peso on domestic prices for certain items (electric and household appliances). For their part, services prices decelerated and showed the lowest rate of annual growth (0.89%) among the large consumer baskets in the CPI. Within the services basket, the annual change in rental prices continued to decline, while those services that continue to experience the most significant restrictions on returning to normal operations (tourism, cinemas, nightlife, etc.) continued to register significant price declines. As previously mentioned, telephone rates also fell significantly due to increased competition in the market. Total inflation is expected to continue to be affected by ample excesses in productive capacity for the remainder of 2021 and 2022, though less so than projected in January. As a result, convergence to the inflation target is now expected to be somewhat faster than estimated in the previous report, assuming the absence of significant additional outbreaks of COVID-19. The technical staff’s year-end inflation projections for 2021 and 2022 have increased, suggesting figures around 3% due largely to variation in food and regulated items prices. The projection for inflation excluding food and regulated items also increased, but remains below 3%. Price relief measures on indirect taxes implemented in 2020 are expected to lapse in the second quarter of 2021, generating a one-off effect on prices and temporarily affecting inflation excluding food and regulated items. However, indexation to low levels of past inflation, weak demand, and ample excess productive capacity are expected to keep core inflation below the target, near 2.3% at the end of 2021 (previously 2.1%). The reversion in 2021 of the effects of some price relief measures on utility rates from 2020 should lead to an increase in the CPI for regulated items in the second half of this year. Annual price changes are now expected to be higher than estimated in the January report due to an increased expected path for fuel prices and unanticipated increases in regulated education prices. The projection for the CPI for foods has increased compared to the previous report, taking into account certain factors that were not anticipated in January (a less favorable agricultural cycle, increased pressure from international prices, and transport costs). Given the above, year-end annual inflation for 2021 and 2022 is now expected to be 3% and 2.8%, respectively, which would be above projections from January (2.3% and 2,7%). For its part, expected inflation based on analyst surveys suggests year-end inflation in 2021 and 2022 of 2.8% and 3.1%, respectively. There remains significant uncertainty surrounding the inflation forecasts included in this report due to several factors: 1) the evolution of the pandemic; 2) the difficulty in evaluating the size and persistence of excess productive capacity; 3) the timing and manner in which price relief measures will lapse; and 4) the future behavior of food prices. Projected 2021 growth in foreign demand (4.4% to 5.2%) and the supposed average oil price (USD 53 to USD 61 per Brent benchmark barrel) were both revised upward. An increase in long-term international interest rates has been reflected in a depreciation of the peso and could result in relatively tighter external financial conditions for emerging market economies, including Colombia. Average growth among Colombia’s trade partners was greater than expected in the fourth quarter of 2020. This, together with a sizable fiscal stimulus approved in the United States and the onset of a massive global vaccination campaign, largely explains the projected increase in foreign demand growth in 2021. The resilience of the goods market in the face of global crisis and an expected normalization in international trade are additional factors. These considerations and the expected continuation of a gradual reduction of mobility restrictions abroad suggest that Colombia’s trade partners could grow on average by 5.2% in 2021 and around 3.4% in 2022. The improved prospects for global economic growth have led to an increase in current and expected oil prices. Production interruptions due to a heavy winter, reduced inventories, and increased supply restrictions instituted by producing countries have also contributed to the increase. Meanwhile, market forecasts and recent Federal Reserve pronouncements suggest that the benchmark interest rate in the U.S. will remain stable for the next two years. Nevertheless, a significant increase in public spending in the country has fostered expectations for greater growth and inflation, as well as increased uncertainty over the moment in which a normalization of monetary policy might begin. This has been reflected in an increase in long-term interest rates. In this context, emerging market economies in the region, including Colombia, have registered increases in sovereign risk premiums and long-term domestic interest rates, and a depreciation of local currencies against the dollar. Recent outbreaks of COVID-19 in several of these economies; limits on vaccine supply and the slow pace of immunization campaigns in some countries; a significant increase in public debt; and tensions between the United States and China, among other factors, all add to a high level of uncertainty surrounding interest rate spreads, external financing conditions, and the future performance of risk premiums. The impact that this environment could have on the exchange rate and on domestic financing conditions represent risks to the macroeconomic and monetary policy forecasts. Domestic financial conditions continue to favor recovery in economic activity. The transmission of reductions to the policy interest rate on credit rates has been significant. The banking portfolio continues to recover amid circumstances that have affected both the supply and demand for loans, and in which some credit risks have materialized. Preferential and ordinary commercial interest rates have fallen to a similar degree as the benchmark interest rate. As is generally the case, this transmission has come at a slower pace for consumer credit rates, and has been further delayed in the case of mortgage rates. Commercial credit levels stabilized above pre-pandemic levels in March, following an increase resulting from significant liquidity requirements for businesses in the second quarter of 2020. The consumer credit portfolio continued to recover and has now surpassed February 2020 levels, though overall growth in the portfolio remains low. At the same time, portfolio projections and default indicators have increased, and credit establishment earnings have come down. Despite this, credit disbursements continue to recover and solvency indicators remain well above regulatory minimums. 1.2 Monetary policy decision In its meetings in March and April the BDBR left the benchmark interest rate unchanged at 1.75%.
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