Relevant bibliographies by topics / Economia data-driven

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Economia data-driven'

Author: Grafiati
Published: 4 June 2021
Last updated: 2 February 2022

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Journal articles on the topic "Economia data-driven"

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Kheradmandi, Masoud, and Prashant Mhaskar. "Data Driven Economic Model Predictive Control." Mathematics 6, no. 4 (2018): 51. http://dx.doi.org/10.3390/math6040051.

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Gros, Sebastien, and Mario Zanon. "Data-Driven Economic NMPC Using Reinforcement Learning." IEEE Transactions on Automatic Control 65, no. 2 (2020): 636–48. http://dx.doi.org/10.1109/tac.2019.2913768.

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Neuhold, Johannes, Matthias Landgraf, Stefan Marschnig, and Peter Veit. "Measurement Data-Driven Life-Cycle Management of Railway Track." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 11 (2020): 685–96. http://dx.doi.org/10.1177/0361198120946007.

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Track engineers face increasing cost pressure and budget restrictions in their work today. This leads to growing difficulty in legitimizing crucial maintenance and renewal measures. As a result, infrastructure managers must ensure they invest all available financial resources as sustainably and efficiently as possible. These boundary conditions require an objective tool enabling both a component-specific condition evaluation and preventive maintenance with renewal planning. The present research introduces such a tool for railway tracks based on innovative track data analyses. This tool include
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Alschner, Wolfgang, Joost Pauwelyn, and Sergio Puig. "The Data-Driven Future of International Economic Law." Journal of International Economic Law 20, no. 2 (2017): 217–31. http://dx.doi.org/10.1093/jiel/jgx020.

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Agbozo, Ebenezer, and Benjamin Kwesi Asamoah. "Data-driven E-Government: Exploring the Socio-Economic Ramifications." JeDEM - eJournal of eDemocracy and Open Government 11, no. 1 (2019): 81–90. http://dx.doi.org/10.29379/jedem.v11i1.510.

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The evident benefits of big data, artificial intelligence and machine learning in society have begun to influence the transition towards a data-driven public sector. Decision-making in the public sector is in an infancy phase of a revolution owing to the inclusion of these new technological innovations. Research has revealed that data-driven e-government policies improve socio-economic development in some nations. Despite the immense opportunities data-driven e-government models have for governments, similar to every system, there are ramifications. This study explores the concept of data-driv
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Mulvenna, Maurice, Marian Norwood, and Alex Büchner. "Data-Driven Marketing." Electronic Markets 8, no. 3 (1998): 32–35. http://dx.doi.org/10.1080/10196789800000038.

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Shen, Tuofu. "Research on economic development strategy based on big data." E3S Web of Conferences 235 (2021): 03080. http://dx.doi.org/10.1051/e3sconf/202123503080.

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Since the 21st century, data has grown exponentially, and the world has entered the era of big data. In the era of big data, the core assumptions and research methods of economics have changed, and data-driven development paradigm has gradually become the main development paradigm of economics. From the perspective of economics and economics, this paper expounds the impact of economics, economics and Economics on the development of data driven models. The research in this paper is conducive to in-depth understanding of the development and changes of economics in the era of big data, and can pr
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Lourenço, Rui Pedro, Suzanne Piotrowski, and Alex Ingrams. "Open data driven public accountability." Transforming Government: People, Process and Policy 11, no. 1 (2017): 42–57. http://dx.doi.org/10.1108/tg-12-2015-0050.

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Purpose This paper aims to analyse extant literature on open data, distinguish and categorize the strands of public accountability research and use the results to provide better clarity in the concept of open data-driven public accountability. Design/methodology/approach Systematic review of 135 open data articles and 155 accountability articles from the e-government reference library. A multi-stage analysis results in 12 articles which are categorized using Bovens’ (2007) accountability theory of information, discussion and consequences. Conceptual development, using the literature analysis,
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Mitchener, Kris James. "The 4D Future of Economic History: Digitally-Driven Data Design." Journal of Economic History 75, no. 4 (2015): 1234–39. http://dx.doi.org/10.1017/s0022050715001655.

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Boutsouki, Christina. "Impulse behavior in economic crisis: a data driven market segmentation." International Journal of Retail & Distribution Management 47, no. 9 (2019): 974–96. http://dx.doi.org/10.1108/ijrdm-08-2018-0165.

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Purpose Clustering is a highly popular and widely used tool for identifying data-based market segments. The purpose of this paper is to apply cluster analysis to identify homogeneous subgroups among impulse buyers based on their demographic characteristics and their preference of atmospheric elements. Design/methodology/approach Based on a survey approach with 480 fashion consumers, the study discusses impulse purchases during financial crisis. SPSS process is used to determine the effect of atmospherics on impulse purchases as well as the moderating role of demographics. Cluster analysis (k-m
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Dissertations / Theses on the topic "Economia data-driven"

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Ciandrini, Giovanni. "Elaborazione del linguaggio naturale nell'IA e tecnologie moderne: Sentiment Analysis come caso di studio." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/8966/.

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L'informatica e le sue tecnologie nella società moderna si riassumono spesso in un assioma fuorviante: essa, infatti, è comunemente legata al concetto che ciò che le tecnologie ci offrono può essere accessibile da tutti e sfruttato, all'interno della propria quotidianità, in modi più o meno semplici. Anche se quello appena descritto è un obiettivo fondamentale del mondo high-tech, occorre chiarire subito una questione: l'informatica non è semplicemente tutto ciò che le tecnologie ci offrono, perchè questo pensiero sommario fa presagire ad un'informatica "generalizzante"; l'informatica invece
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On, Robert. "Data-driven Development| Essays on the Use of Mobile Phone Data and Information to Measure and Reduce Poverty." Thesis, University of California, Berkeley, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=13421115.

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<p>Mobile phone ubiquity in much of the developing world has turned from a question of when rather than if. Some of the poorest and most remote parts of the world are being connected to the global telecommunications network to enable an unprecedented ability to both observe and interact with previously hard-to-reach populations at scale. While many mobile phone owners adopt this technology for basic phone use, the connectedness this expansive ownership enables presents an opportunity to the study and practice of economic development that extend beyond simple peer-to-peer communication. The mo
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Broms, Arvid, and Olsson Simon Liljenberg. "Data-driven Decision-making for Efficient & Sustainable Production." Thesis, KTH, Industriell ekonomi och organisation (Inst.), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-297504.

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As a result of digitalization, previously analog systems in the manufacturing industry have become digitalized, including the decision-making processes. Companies are, therefore,becoming more dependent on data for strategic decisions. However, because of the rapid development of digitalization, companies are left blindfolded in the path towards smarter manufacturing which often leads to unsuccessful technological implementations. Therefore, the thesis will explore this problem by asking: What are the required initiatives for successfully implementing digital data-driven decision-making to impr
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Leo, Yannick. "Deep dive into social network and economic data : a data driven approach for uncovering temporal ties, human mobility, and socioeconomic correlations." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEN066/document.

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Dans cette thèse, j'étudie des jeux de données concernant des liens sociaux entre personnes (appels et SMS), leur mobilité ainsi que des informations économiques sur ces personnes, comme leur revenu et leurs dépenses. Les sept travaux couvrent un spectre assez large et apportent des contributions en informatique des réseaux mais aussi en sociologie, économie et géographie. Les questions posées sont très diverses. Comment quantifier la perte d'information causée par une agrégation de flot de liens en série de graphe ? Comment inférer les mouvements des utilisateurs quand on ne connaît que les l
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O'Malley, John Richard Jr. "Electronic Data Interchange: An Inventory Perspective of Its Economic Viability and Recommendations for Information Technology Driven Implementation." Diss., Virginia Tech, 2000. http://hdl.handle.net/10919/37365.

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Electronic commerce (EC) in its various forms is perceived by many organizations as the way that business will be conducted in the future. Much of the current wave of interest in EC is driven by new, readily available technologies like the Internet and the World Wide Web. The excitement regarding Web Commerce has lead many to believe that EC is relatively new. In reality, EC in the form of Electronic Data Interchange (EDI) has existed for 30 years and accounts for far more business than WC. It is the preferred, and often required, way of doing business with many large organizations such as t
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Andersson, Johan, and Amirhossein Gharaie. "It is Time to Become Data-driven, but How : Depicting a Development Process Model." Thesis, Högskolan i Halmstad, Akademin för företagande, innovation och hållbarhet, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-45353.

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Background: The business model (BM) is an essential part of firms and it needs to be innovated continuously to allow firms to stay or become competitive. The process of business model innovation (BMI) unfolds incrementally by re-designing or developing new activities in order to provide value propositions (VP). With increasing availability of data, pressure on BMI to orchestrate their activities towards putting data as a key resource and develop data-driven business models (DDBM) is growing. Problematization: The DDBM provides valuable possibilities by utilizing data to optimize current busine
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Galozy, Alexander. "Data-driven personalized healthcare : Towards personalized interventions via reinforcement learning for Mobile Health." Licentiate thesis, Högskolan i Halmstad, CAISR Centrum för tillämpade intelligenta system (IS-lab), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-44091.

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Medical and technological advancement in the last century has led to the unprecedented increase of the populace's quality of life and lifespan. As a result, an ever-increasing number of people live with chronic health conditions that require long-term treatment, resulting in increased healthcare costs and managerial burden to the healthcare provider. This increase in complexity can lead to ineffective decision-making and reduce care quality for the individual while increasing costs. One promising direction to tackle these issues is the active involvement of the patient in managing their care.
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Marby, Josephine, and Ying Chen. "Ranking risks and opportunities of African cities : - A data-driven model to support MNE’s FDI strategies." Thesis, KTH, Industriell Management, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-210315.

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The purpose of this paper is to build a model that incorporates current data of Africa, both regarding risks and opportunities into a strategic framework that should enable a more informed foreign direct investment decision for multinational enterprises (MNEs). The parameters used in the model were carefully chosen as determinants to foreign direct investment (FDI) based on extensive literature reviews. The model currently covers 101 major cities in 40 African countries. The model calculates and ranks indexes of African cities in terms of prospective investment opportunities. It is a general m
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Morselli, Luca. "Analisi e implementazione di un sistema di Data Visualization in relazione al modello organizzativo aziendale." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020.

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Le aziende oggi sono sopraffatte dall'enorme quantitativo di dati con cui hanno a che fare: una corretta archiviazione di questi è presupposto fondamentale per consentire un'accurata rappresentazione dei dati per poter poi essere analizzati da parte dei diversi attori aziendali. Per fare ciò si ricorre all'utilizzo di sistemi di Business Intelligence in grado di fornire un supporto fondamentale lungo tutto il processo decisionale a diversi livelli. L'elaborato ha dunque come scopo principale la presentazione delle tecniche di Data Visualization a supporto di tale processo in funzione del ruol
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Krumpe, Kati Petersen. "Linking Resource Allocation to Student Achievement: A Study of Title 1 and Title 1 Stimulus Utilization." Digital Commons at Loyola Marymount University and Loyola Law School, 2012. https://digitalcommons.lmu.edu/etd/244.

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With the emphasis on high standards and fiscal accountability, there is a heightened need to inform the research linking student achievement to the allocation of resources. This mixed methods inquiry sought to study how schools utilized Title 1 and Title 1 stimulus funding from 2009-2011 to determine if correlations existed between areas of resource utilization and student achievement by studying both the use of funding and the processes that fifteen elementary and middle Title 1 schools in southern California utilized. The focus was to document resource use of Title 1 and Title 1 stimulus all
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Books on the topic "Economia data-driven"

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Gendron, Michael. Business driven data communications. Pearson Prentice Hall, 2013.

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Communications, Racom, ed. Accountable marketing: The economics of data-driven marketing. AMA, 2004.

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Gendron, Michael. Business Driven Data Communications. Pearson Education, Limited, 2011.

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Bazerman, Max H., and Michael Luca. Power of Experiments - Decision Making in a Data-Driven World. MIT Press, 2020.

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Callahan, Sean, and Russell Glass. Big Data-Driven Business: How to Use Big Data to Win Customers, Beat Competitors, and Boost Profits. Wiley & Sons, Incorporated, John, 2014.

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Callahan, Sean, and Russell Glass. Big Data-Driven Business: How to Use Big Data to Win Customers, Beat Competitors, and Boost Profits. Wiley & Sons, Incorporated, John, 2014.

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Data-driven organization design: Sustaining the competitive edge through organizational analytics. Kogan Page, 2015.

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Peter, Jackson, and Caroline Carruthers. Data Driven Business Transformation: How to Disrupt, Innovate and Stay Ahead of the Competition. Wiley & Sons, Incorporated, John, 2019.

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Jackson, Peter, and Caroline Carruthers. Data Driven Business Transformation: How to Disrupt, Innovate and Stay Ahead of the Competition. Wiley & Sons, Incorporated, John, 2019.

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Callahan, Sean, and Russell Glass. The Big Data-Driven Business: How to Use Big Data to Win Customers, Beat Competitors, and Boost Profits. Wiley, 2014.

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Book chapters on the topic "Economia data-driven"

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Andersen, Michael Moesgaard, and Torben Pedersen. "Heading toward a digital innovation economy." In Data-Driven Innovation. Routledge, 2021. http://dx.doi.org/10.4324/9781003041702-7.

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Pick, Doreén. "Data-driven Marketing in the Carsharing Economy – Focus on Privacy Concerns." In Data-driven Marketing. Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-29995-8_10.

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Seebacher, Uwe. "Predictive Intelligence and the Basic Economic Principles." In Predictive Intelligence for Data-Driven Managers. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69403-6_1.

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Katos, Vasilios, and Pavlos Efraimidis. "Privacy in Data-Driven Circular Economy." In Encyclopedia of Cryptography, Security and Privacy. Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-642-27739-9_1615-1.

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Tiwari, Ashu, and Archana Patro. "Data Protection in Market-Driven Network Economies." In Role of IT- ITES in Economic Development of Asia. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4206-0_24.

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Cavanillas, José María, Edward Curry, and Wolfgang Wahlster. "The Big Data Value Opportunity." In New Horizons for a Data-Driven Economy. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-21569-3_1.

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Zillner, Sonja, and Sabrina Neururer. "Big Data in the Health Sector." In New Horizons for a Data-Driven Economy. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-21569-3_10.

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Munné, Ricard. "Big Data in the Public Sector." In New Horizons for a Data-Driven Economy. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-21569-3_11.

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Hussain, Kazim, and Elsa Prieto. "Big Data in the Finance and Insurance Sectors." In New Horizons for a Data-Driven Economy. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-21569-3_12.

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Rusitschka, Sebnem, and Edward Curry. "Big Data in the Energy and Transport Sectors." In New Horizons for a Data-Driven Economy. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-21569-3_13.

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Conference papers on the topic "Economia data-driven"

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Heo, Joon, and Okyu Kwon. "User-Driven Economic Data Analysis Framework." In 2014 IEEE World Congress on Services (SERVICES). IEEE, 2014. http://dx.doi.org/10.1109/services.2014.54.

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Nazarov, A. D. "Big Data Driven Marketing." In Proceedings of the International Scientific and Practical Conference on Digital Economy (ISCDE 2019). Atlantis Press, 2019. http://dx.doi.org/10.2991/iscde-19.2019.3.

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Zeynalli, Aytan. "Data-Driven Decision Making in Strategy Management of Enterprises." In International Academic Conference on Management and Economics. Acavent, 2019. http://dx.doi.org/10.33422/conferenceme.2019.11.647.

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Luo, Wuheng. "Enterprise data economy: A hadoop-driven model and strategy." In 2013 IEEE International Conference on Big Data. IEEE, 2013. http://dx.doi.org/10.1109/bigdata.2013.6691690.

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Ueda, Toshiki, and Yoshikazu Ikeda. "Socio-economics and educational case study with cost-effective IOT campus by the use of wearable, tablet, cloud and open E-learning services." In 2017 ITU Kaleidoscope: Challenges for a Data-Driven Society (ITU K). IEEE, 2017. http://dx.doi.org/10.23919/itu-wt.2017.8246994.

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Zhao, Mingxiao. "Data-driven Scene Marketing Based on Consumer Insight." In 2020 International Conference on Big Data Economy and Information Management (BDEIM). IEEE, 2020. http://dx.doi.org/10.1109/bdeim52318.2020.00023.

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Karagiannidis, Pavlos, and Nikolaos Themelis. "Data-Driven Ship Propulsion Modeling with Artificial Neural Networks." In SNAME 7th International Symposium on Ship Operations, Management and Economics. SNAME, 2021. http://dx.doi.org/10.5957/some-2021-011.

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The paper examines data-driven techniques for the modeling of ship propulsion that could support a strategy for the reduction of emissions and be utilized for the optimization of a fleet’s operations. A large, high-frequency and automated collected data set is exploited for producing models that estimate the required shaft power or main engine’s fuel consumption of a container ship sailing under arbitrary conditions. A variety of statistical calculations and algorithms for data processing are implemented and state-of-the-art techniques for training and optimizing Feed-Forward Neural Networks (
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Yan, Ziming, Yan Xu, Yu Wang, and Xue Feng. "Data-driven Economic Control of Battery Energy Storage System Considering Battery Degradation." In 2019 9th International Conference on Power and Energy Systems (ICPES). IEEE, 2019. http://dx.doi.org/10.1109/icpes47639.2019.9105413.

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Mehra, Chetan Saran, Adam Prugel-Bennett, Enrico Gerding, and Valentin Robu. "Constructing smart portfolios from data driven quantitative investment models." In 2014 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr). IEEE, 2014. http://dx.doi.org/10.1109/cifer.2014.6924069.

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Najdawi, Anas, and Sree karan Patkuri. "Modeling Business Intelligence Process: Toward Smart Data-Driven Strategies." In 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE). IEEE, 2021. http://dx.doi.org/10.1109/iccike51210.2021.9410804.

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Reports on the topic "Economia data-driven"

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Dime, Roselle, Juzhong Zhuang, and Edimon Ginting. Estimating Fiscal Multipliers in Selected Asian Economies. Asian Development Bank, 2021. http://dx.doi.org/10.22617/wps210309-2.

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The surge of the coronavirus disease (COVID-19) pandemic has driven countries worldwide to launch substantial stimulus packages to support economic recovery. This paper estimates effects of fiscal measures on output using data from 2000 to 2019 for a panel of nine developing Asian economies and a vector autoregression model. Results show that (i) the 4-quarter and 8-quarter cumulative fiscal multipliers for general government spending range between 0.73 and 0.88 in baselines, in line with recent estimates for developed countries but larger than those for developing countries; (ii) government s
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Kim, Changmo, Ghazan Khan, Brent Nguyen, and Emily L. Hoang. Development of a Statistical Model to Predict Materials’ Unit Prices for Future Maintenance and Rehabilitation in Highway Life Cycle Cost Analysis. Mineta Transportation Institute, 2020. http://dx.doi.org/10.31979/mti.2020.1806.

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The main objectives of this study are to investigate the trends in primary pavement materials’ unit price over time and to develop statistical models and guidelines for using predictive unit prices of pavement materials instead of uniform unit prices in life cycle cost analysis (LCCA) for future maintenance and rehabilitation (M&amp;R) projects. Various socio-economic data were collected for the past 20 years (1997–2018) in California, including oil price, population, government expenditure in transportation, vehicle registration, and other key variables, in order to identify factors affecting
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Beuermann, Diether, Nicolas L. Bottan, Bridget Hoffmann, C. Kirabo; Jackson, and Diego A. Vera-Cossio. Does Education Prevent Job Loss during Downturns?: Evidence from Exogenous Schools Assignments and COVID-19 in Barbados. Inter-American Development Bank, 2021. http://dx.doi.org/10.18235/0003624.

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Canonical human capital theories posit that education, by enhancing worker skills, reduces the likelihood that a worker will be laid off during times of economic change. Yet, this has not been demonstrated causally. We link administrative education records from 1987 through 2002 to nationally representative surveys conducted before and after the onset of COVID-19 in Barbados to explore the causal impact of improved education on job loss during this period. Using a regression discontinuity (RD) design, Beuermann and Jackson (2020) show that females (but not males) who score just above the admis
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Cao, Shoufeng, Uwe Dulleck, Warwick Powell, Charles Turner-Morris, Valeri Natanelov, and Marcus Foth. BeefLedger blockchain-credentialed beef exports to China: Early consumer insights. Queensland University of Technology, 2020. http://dx.doi.org/10.5204/rep.eprints.200267.

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The BeefLedger Export Smart Contracts project is a collaborative research study between BeefLedger Ltd and QUT co-funded by the Food Agility CRC. This project exists to deliver economic value to those involved in the production, export and consumption of Australian beef to China through: (1) reduced information asymmetry; (2) streamlined compliance processes, and; (3) developing and accessing new data-driven value drivers, through the deployment of decentralised ledger technologies and associated governance systems. This report presents early insights from a survey deployed to Chinese consumer
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