University-industry scientific production and the Great Recession

Azagra‐Caro, Joaquín M.; Tijssen, Robert; Tur, Elena M.; Yegros-Yegros, Alfredo

doi:10.1016/j.techfore.2018.10.025

Cited by 30 publications

(12 citation statements)

References 69 publications

(81 reference statements)

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“…According to another study, the median time to acceptance for COVID-19-related articles in Scopus journals in the first half of 2020 was 19.3 days. Comparatively, non-COVID-19-related articles had an average time to acceptance of 91.4 days over the same period (Aviv-Reuven and Rosenfeld, 2020 [75]).…”

Section: (6) Quick Diffusion Of Research Results and Its Use By Policymentioning

confidence: 99%

Science, technology and innovation in the time of COVID-19

2021

OECD Science, Technology and Industry Policy Papers

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Science, technology and innovation (STI) have played a key role in responding to the COVID-19 pandemic and the unprecedented socio-economic crisis it has triggered. This paper explores how the pandemic affected STI in 2020, including how STI was mobilised to provide vaccines, treatments and innovative (often digital) solutions to address "social distancing". The paper also reviews the quick and agile STI policy responses implemented across countries to stimulate research and innovation activities to find solutions to the pandemic. Moreover, the paper covers STI policies that targeted universities, research centres, innovative businesses and entrepreneurs most affected by the crisis. It also raises key debates on the effectiveness of such policies. Follow-up work will leverage more and better data to improve this early assessment of the impacts of the crisis and STI policy responses.

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Section: (6) Quick Diffusion Of Research Results and Its Use By Policymentioning

confidence: 99%

Science, technology and innovation in the time of COVID-19

2021

OECD Science, Technology and Industry Policy Papers

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“…From university perspective, the literature review revealed performance indicators of UIC. Indeed, the most frequent UIC performance indicators were (1) number of publications [16,29,31,34,[37][38][39][40][41][42][43][44][45][46][47][48][49][50][51], (2) number of registered patents [3,7,16,20,29,37,40,48,[50][51][52][53][54][55][56][57][58], (3) number of occurrences for each UIC activity (consulting and services, research, and training and education) [6,21,33,37,47,50,[59][60][61][62][63], (4) number of generated start-ups and spinoffs [16,37,…”

Section: Summary Of Key Uic Performance Indicatorsmentioning

confidence: 99%

A Review and Comprehensive Analysis of the Performance of University – Construction Industry Collaboration

2021

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University–construction industry collaboration (UIC) has become an essential part of driving innovation and fostering construction industry growth. Measuring the performance of such collaboration is an emergent field of study that is scattered through the current literature. This study aims to identify the UIC performance indicators advocated by the top-cited references, and map UIC performance indicators in the context of the state of Qatar. The present research evaluated the literature related to measuring the performance of UIC, considering publications in selected scientific databases over the period of 2004 – 2020. The publications were obtained through a search of the Science Direct, Emerald Insight, Scopus, Web of Science, Springer Link, SAGE, Research Gate, and Taylor & Francis Online databases. Keywords used in searching for publications included university, construction industry, business, cooperation, collaboration, relation, performance, and measurement. The findings were discussed and confirmed in the context of Qatar’s education and innovation ecosystem through semi-structured interviews with two renowned scholars who are involved in UIC. The study revealed that both universities and the construction industry are increasingly focused on measuring the performance of collaboration through specific performance indicators. The results show that both universities and the construction industry share some interests when it comes to four key performance indicators. These performance indicators are (1) the number of registered patents, (2) the number of patent applications, (3) the number of innovations (process/marketing/product/organisational), and (4) the number of publications. This study contributes to a general understanding of measuring UIC performance and defining trends in this research field. It also highlights research limitations and provides an arena for future research in the field. Doi: 10.28991/cej-2021-03091688 Full Text: PDF

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“…Our selected economic variables/indexes for recession prediction come from the St. Louis Fed (FRED) 2 and the Institute for Supply Management (ISM) 3 , which updates economic indexes daily from more than 85 public and proprietary sources with over 200,000 indexes in terms of money, banking& finance, population, employment, national accounts, production & business activity, prices, and U.S. regional/international, academic data. According to [37], we choose three recession-related categories which are shown as follows:…”

Section: Data Sourcementioning

confidence: 99%

Economic Recession Prediction Using Deep Neural Network

Wang¹,

Li²,

Xia³

et al. 2021

Preprint

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We investigate the effectiveness of different machine learning methodologies in predicting economic cycles. We identify the deep learning methodology of Bi-LSTM with Autoencoder as the most accurate model to forecast the beginning and end of economic recessions in the U.S. We adopt commonly-available macro and market-condition features to compare the ability of different machine learning models to generate good predictions both in-sample and out-of-sample. The proposed model is flexible and dynamic when both predictive variables and model coefficients vary over time. It provided good out-of-sample predictions for the past two recessions and early warning about the COVID-19 recession.

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University-industry scientific production and the Great Recession

Cited by 30 publications

References 69 publications

Science, technology and innovation in the time of COVID-19

Science, technology and innovation in the time of COVID-19

A Review and Comprehensive Analysis of the Performance of University – Construction Industry Collaboration

Economic Recession Prediction Using Deep Neural Network

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