Effective hospital response to covid-19evidence from social healthcare organizations in Brazil and Portugal

  1. Lopes Fonseca, Gleison 1
  2. Briones Peñalver, Antonio Juan
  3. Fernandes da Anunciação, Pedro
  1. 1 Universidad Politécnica de Cartagena
    info

    Universidad Politécnica de Cartagena

    Cartagena, España

    ROR https://ror.org/02k5kx966

Journal:
CIRIEC - España. Revista de economía pública, social y cooperativa

ISSN: 0213-8093

Year of publication: 2022

Issue: 104

Pages: 267-301

Type: Article

DOI: 10.7203/CIRIEC-E.104.21758 DIALNET GOOGLE SCHOLAR

More publications in: CIRIEC - España. Revista de economía pública, social y cooperativa

Sustainable development goals

Abstract

This study analyzes the impact of effective knowledge management, organizational intelligence, and organizational performance on the effective hospital response and social health to covid-19. Data were collected through a research questionnaire sent to physicians and nurses who worked in hospitals in Brazil and Portugal. We sent the survey link using a professional social network and 101 valid responses were obtained. The PLS-SEM analysis technique was used to test hypotheses. The results showed that there is a positive relationship between the constructs of effective knowledge management and organizational performance, and effective response to covid-19. This study also indicates that effective knowledge management has a positive association with organizational intelligence and organizational performance, in addition to a positive relationship between organizational intelligence and organizational performance. As practical implications, our research reinforces the importance of effective knowledge management for pandemic management and validates the relationships between effective knowledge management, organizational intelligence, organizational performance, and hospital response effectiveness. From these results, hospitals and social health organizations will be able to improve their effectiveness in responding to new disease outbreaks. As originality, this work presents a model to manage the response of these health care and hospital institutions to pandemics.

Bibliographic References

  • ABBO, A.R., MILLER, A., GAZIT, T., SAVIR, Y. & CASPI, O. (2020): “Technological developments and strategic management for overcoming the COVID-19 challenge within the hospital setting in Israel”, Rambam Maimonides Medical Journal, 11(3), 1-9. https://doi.org/10.5041/RMMJ.10417
  • ALBRECHT, K. (2003): “The power of minds at work: “Organizational intelligence in action”, In American Management Association, AMACOM. https://doi.org/10.1111/j.1744-6570.2004.014_11.x
  • ALMEIDA, F.C., LESCA, H. & CANTON, A.W.P. (2016): “Intrinsic motivation for knowledge sharing – competitive intelligence process in a telecom company”, Journal of Knowledge Management, 20(6), 1282-1301. https://doi.org/10.1108/JKM-02-2016-0083
  • AMMIRATO, S., LINZALONE, R. & FELICETTI, A.M. (2020): “Knowledge management in pandemics. A critical literature review”, Knowledge Management Research & Practice, 105(2), 1-12. https://doi.org/10.1080/14778238.2020.1801364
  • ANUNCIAÇÃO, P.F. & GEADA, N.S. (2021): “Change Management Perceptions in Portuguese Hospital Institutions Through ITIL”, International Journal of Healthcare Information Systems and Informatics, 16(4), 1-20. https://doi.org/10.4018/ijhisi.20211001.oa18
  • ARMSTRONG, R.A., KANE, A.D. & COOK, T.M. (2020): “Outcomes from intensive care in patients with COVID-19: a systematic review and meta-analysis of observational studies”, Anaesthesia, 75(10), 1340-1349. https://doi.org/10.1111/anae.15201
  • BANDALOS, D.L. (2018): “Measurement theory and applications for the social sciences”. In: Methodology in the social sciences, The Guilford Press.
  • BDEIR, F., HOSSAIN, L. & CRAWFORD, J. (2013): “Emerging coordination and knowledge transfer process during disease outbreak”, Knowledge Management Research & Practice, 11(3), 241- 254. https://doi.org/10.1057/kmrp.2012.1
  • BIDO, D.D.S. & SILVA, D. (2019): “Smartpls 3: specification, estimation, evaluation and reporting”, Administração: Ensino e Pesquisa, 20(2), 465-513. https://doi.org/10.13058/raep.2019.v20n2.1545
  • BRIONES-PEÑALVER, A.J., BERNAL-CONESA, J.A. & DE NIEVES NIETO, C. (2020): “Knowledge and innovation management model. Its influence on technology transfer and performance in Spanish Defence industry”, International Entrepreneurship and Management Journal, 16(2), 595-615. https://doi.org/10.1007/s11365-019-00577-6
  • BRIONES-PEÑALVER, A.J., SANTOS, J.A.C., BERNAL CONESA, J.A. & CUSTÓDIO SANTOS, M. (2018): “Influence of cooperation and collaborative ICT in knowledge management”, Journal of Scientific and Industrial Research, 77(6), 313-317.
  • BRIONES-PEÑALVER, J.A., LOPES CASTELAO, M.P. & CARDOSO DE SOUSA, F. (2012): “La economía social ibérica: el caso de las santas casas de la misericordia de Portugal como instituciones particulares de solidaridad social”, REVESCO, Revista de Estudios Cooperativos, 107, 7-32. https://doi.org/10.5209/rev_REVE.2012.v107.38745
  • BRYCE, C., RING, P., ASHBY, S. & WARDMAN, J.K. (2020): “Resilience in the face of uncertainty: early lessons from the COVID-19 pandemic”, Journal of Risk Research, 1-8. https://doi.org/10.1080/13669877.2020.1756379
  • CHANG, T.C. & CHUANG, S.H. (2011): “Performance implications of knowledge management processes: Examining the roles of infrastructure capability and business strategy”, Expert Systems with Applications, 38(5), 6170-6178. https://doi.org/10.1016/j.eswa.2010.11.053
  • COHEN, J. (1988): “Statistical power analysis for the social sciences”. In: Statistic power analysis for the behavioral science, Lawrence Erlbaum Associates.
  • COMFORT, L.K., KAPUCU, N., KO, K., MENONI, S. & SICILIANO, M. (2020): “Crisis decision-making on a global scale: Transition from cognition to collective action under threat of COVID-19”, Public Administration Review, 80(4), 616-622. https://doi.org/10.1111/puar.13252
  • DAŇA, J., CAPUTO, F. & RÁČEK, J. (2020): “Complex network analysis for knowledge management and organizational intelligence”, Journal of the Knowledge Economy, 11(2), 405-424. https://doi.org/10.1007/s13132-018-0553-x
  • DALKEY, N. & HELMER, O. (1963): “An experimental application of Delphi method to use of experts”, Management Science, 9(3), pp. 458-467. https://doi.org/10.1287/mnsc.9.3.458
  • DALKIR, K. (2013): “Knowledge management in theory and practice”, In: Knowledge Management in Theory and Practice, Routledge. https://doi.org/10.4324/9780080547367
  • DARROCH, J. (2005): “Knowledge management, innovation and firm performance”, Journal of Knowledge Management, 9(3), 101-115. https://doi.org/10.1108/13673270510602809
  • DE ANGELIS, C.T. (2013): “A Knowledge Management and Organizational Intelligence Model for Public Administration”, International Journal of Public Administration, 36(11), 807–819. https://doi.org/10.1080/01900692.2013.791315
  • DEVELLIS, R.F. (2016): “Scale Development: Theory and Applications”, Sage Publications.
  • DOBRE, T. & HĂHĂIANU, F. (2016): “The 12th International Scientific Conference eLearning and Software for Education”, The 12th International Scientific Conference eLearning and Software for Education, 77-82. https://doi.org/10.12753/2066-026X-16-011
  • DU PLESSIS, M. (2007): “The role of knowledge management in innovation”, Journal of Knowledge Management, 11(4), 20-29. https://doi.org/10.1108/13673270710762684
  • FAUL, F., ERDFELDER, E., BUCHNER, A. & LANG, A.G. (2009): “Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses”, Behavior Research Methods, 41(4), 1149-1160. https://doi.org/10.3758/BRM.41.4.1149
  • FERLIE, E., CRILLY, T., JASHAPARA, A. & PECKHAM, A. (2012): “Knowledge mobilisation in healthcare: A critical review of health sector and generic management literature”, Social Science & Medicine, 74(8), 1297-1304. https://doi.org/10.1016/j.socscimed.2011.11.042
  • FORNELL, C. & LARCKER, D.F. (1981): “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error”, Journal of Marketing Research, 18(1), 39. https://doi.org/10.2307/3151312
  • FRANKE, G. & SARSTEDT, M. (2019): “Heuristics versus statistics in discriminant validity testing: a comparison of four procedures”, Internet Research, 29(3), 430-447. https://doi.org/10.1108/IntR-12-2017-0515
  • GARSON, G.D. (2016): “Partial least squares: Regression and structural equation models”. In: Politeness and Audience Response in Chinese-English Subtitling, Statistical Associates Publishers. https://doi.org/10.3726/978-3-0353-0280-6/8
  • GAVIRIA-MARIN, M., MERIGÓ, J.M. & BAIER-FUENTES, H. (2018): “Knowledge management: A global examination based on bibliometric analysis”, Technological Forecasting and Social Change, 140, 194-220. https://doi.org/10.1016/j.techfore.2018.07.006
  • GHOSH, B. & SCOTT, J.E. (2006): “Effective knowledge management systems for a clinical nursing setting”, Information Systems Management, 24(1), 73-84. https://doi.org/10.1080/10580530601038188
  • GOLD, A.H., MALHOTRA, A. & SEGARS, A.H. (2001): “Knowledge management: An organizational capabilities perspective”, Journal of Management Information Systems, 18(1), 185-214. https://doi.org/10.1080/07421222.2001.11045669
  • HAIR, J.F., BLACK, W.C., BABIN, B.J. & ANDERSON, R.E. (2018): “Multivariate data analysis”, Cengage Learning EMEA. http://doi.wiley.com/10.1002/9781119409137.ch4
  • HAIR, J.F., HULT, G.T., RINGLE, C. & SARSTEDT, M. (2017): A primer on partial least squares structural equation modeling (PLS-SEM), Sage Publications.
  • HAIR, J.F., RINGLE, C.M. & SARSTEDT, M. (2014): “PLS-SEM: Indeed a silver bullet”, Journal of Marketing Theory and Practice, 19(2), 139-152. https://doi.org/10.2753/MTP1069-6679190202
  • HASSON, F., KEENEY, S. & MCKENNA, H. (2000): “Research guidelines for the Delphi survey technique”, Journal of Advanced Nursing, 32(4), 1008-1015. https://doi.org/10.1046/j.1365-2648.2000.t01-1-01567.x
  • HENSELER, J. (2018): “Partial least squares path modeling: Quo Vadis?”, Quality & Quantity, 52(1), 1-8. https://doi.org/10.1007/s11135-018-0689-6
  • HODGINS, M., VAN LEEUWEN, D., BRAITHWAITE, J., HANEFELD, J., WOLFE, I., LAU, C., DICKINS, E., MCSWEENEY, J., MCCASKILL, M. & LINGAM, R. (2021): “The COVID-19 System Shock Framework: Capturing Health System Innovation During the COVID-19 Pandemic”, International Journal of Health Policy and Management, 2019(x), 1-11. https://doi.org/10.34172/ijhpm.2021.130
  • HOSSEINI, S.S., TEKMEDASH, Y.N., KARAMI, A. & JABARZADEH, Y. (2019): “The impact of knowledge management strategy on service innovation performance in private and public hospitals”, Iranian Journal of Management Studies, 12(1), 2345-3745. https://doi.org/10.22059/IJMS.2018.249784.672966
  • HU, L. & BENTLER, P.M. (1999): “Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives”, Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55. https://doi.org/10.1080/10705519909540118
  • HUANG, C.-Y. & SHIH-WEI, F. (2020): “Public-private collaborations in a Dunkirk moment”, Knowledge Management Research & Practice, 00(00), 1-6. https://doi.org/10.1080/14778238.2020.1802359
  • ISTUDOR, N., URSACESCU, M., SENDROIU, C. & RADU, I. (2016): “Theoretical framework of organizational intelligence: a managerial approach to promote renewable energy in rural economies”, Energies, 9(8), 639. https://doi.org/10.3390/en9080639
  • JAD, S.M.M., GERAVANDI, S., MOHAMMADI, M.J., ALIZADEH, R., SARVARIAN, M., RASTEGARIMEHR, B., AFKAR, A., YARI, A. R., MOMTAZAN, M., VALIPOUR, A., MAHBOUBI, M., KARIMYAN, A., MAZRAEHKAR, A., NEJAD, A.S. & MOHAMMADI, H. (2017): “The relationship between knowledge of leadership and knowledge management practices in the food industry in Kurdistan province, Iran”, Data in Brief, 15, 155-159. https://doi.org/10.1016/j.dib.2017.09.031
  • KÄNSÄKOSKI, H. (2017): “Information and knowledge processes as a knowledge management framework in health care”, Journal of Documentation, 73(4), 748-766. https://doi.org/10.1108/JD-11-2016-0138
  • KESHAVARZ, H., GIVI, M.R.E. & SHEKARI, M.R. (2018): “Knowledge management infrastructures and organizational intelligence in Iranian research centers”, Data Technologies and Applications, 52(1), 2-15. https://doi.org/10.1108/DTA-12-2016-0080
  • KOCK, N. & LYNN, G.S. (2012): “Lateral collinearity and misleading results in variance based SEM: An illustration and recommendations”, Journal of the Association for Information Systems, 13(7), 546-580.
  • KOTHARI, A., HOVANEC, N., HASTIE, R. & SIBBALD, S. (2011): “Lessons from the business sector for successful knowledge management in health care: A systematic review”, BMC Health Services Research, 11(1), 173. https://doi.org/10.1186/1472-6963-11-173
  • LATAN, H. (2018): “PLS path modeling in hospitality and tourism research: The golden age and days of future past”. In: Applying Partial Least Squares in Tourism and Hospitality Research, Emerald Publishing Limited. https://doi.org/10.1108/978-1-78756-699-620181004
  • LEAL-RODRÍGUEZ, A.L., ROLDÁN, J.L., LEAL, A.G. & ORTEGA-GUTIÉRREZ, J. (2013): “Knowledge management, relational learning, and the effectiveness of innovation outcomes”, The Service Industries Journal, 33(13-14), 1294-1311. https://doi.org/10.1080/02642069.2013.815 735
  • LEE, E.J., KIM, H.S. & KIM, H.Y. (2014): “Relationships between core factors of knowledge management in hospital nursing organisations and outcomes of nursing performance”, Journal of Clinical Nursing, 23(23-24), 3513–3524. https://doi.org/10.1111/jocn.12603
  • LEE, H. & CHOI, B. (2003): “Knowledge management enablers, processes, and organizational performance: An integrative view and empirical examination”, Journal of Management Information Systems, 20(1), 179-228. https://doi.org/10.1080/07421222.2003.11045756
  • LI, Q., WANG, L., WANG, B. & LU, H. (2021): “The COVID-19-designated hospitals in China: preparing for public health emergencies”, Emerging Microbes and Infections, 10(1), 998-1001. https://doi.org/10.1080/22221751.2021.1931467
  • LI, W.-T. & HUNG, S.-Y. (2009): “The influence of knowledge management capability and knowledge management infrastructure on market-interrelationship performance: An empirical study on hospitals”, Managing Knowledge for Global and Collaborative Innovations, 163-175. https://doi.org/10.1142/9789814299862_0014
  • LIM, H.W., LI, Z. & FANG, D. (2020): “Impact of management, leadership, and group integration on the hospital response readiness for earthquakes”, International Journal of Disaster Risk Reduction, 48(November 2019), 101586. https://doi.org/10.1016/j.ijdrr.2020.101586
  • LIMA, J.E., WEST, G.R.B., WINSTON, B.E. & WOOD, J.A. (2016): “Measuring organizational cultural intelligence: The development and validation of a scale”, International Journal of Cross Cultural Management, 16(1), 9-31. https://doi.org/10.1177/1470595815615625
  • MALEKZADEH, G., KAZEMI, M., LAGZIAN, M. & MORTAZAVI, S. (2016): “Modeling organizational intelligence using DEMATEL method in Iranian public universities”, Journal of Modelling in Management, 11(1), 134-153. https://doi.org/10.1108/JM2-12-2013-0062
  • MARTINEZ-CONESA, I., SOTO-ACOSTA, P. & CARAYANNIS, E.G. (2017): “On the path towards open innovation: assessing the role of knowledge management capability and environmental dynamism in SMEs”, Journal of Knowledge Management, 21(3), 553-570. https://doi.org/10.1108/JKM-09-2016-0403
  • MASSARO, M., DUMAY, J. & GARLATTI, A. (2015): “Public sector knowledge management: a structured literature review”, Journal of Knowledge Management, 19(3), 530-558. https://doi.org/10.1108/JKM-11-2014-0466
  • NETEMEYER, R.G., BEARDEN, W.O. & SUBHASH, S. (2003): “Scaling Procedures: Issues and Applications”, Sage Publications.
  • NISAR, T.M., PRABHAKAR, G. & STRAKOVA, L. (2019): “Social media information benefits, knowledge management and smart organizations”, Journal of Business Research, 94(May 2018), 264-272. https://doi.org/10.1016/j.jbusres.2018.05.005
  • PETERS, M.D., WIEDER, B., SUTTON, S.G. & WAKEFIELD, J. (2016): “Business intelligence systems use in performance measurement capabilities: implications for enhanced competitive advantage”, International Journal of Accounting Information Systems, 21, 1-17. https://doi.org/10.1016/j.accinf.2016.03.001
  • PREECE, M. (2015): “Managing information and knowledge in service industries”. In: M. Quaddus & A. G. Woodside, Sustaining competitive advantage via business intelligence, knowledge management, and system dynamics, Emerald Group Publishing Limited. https://doi.org/10.1108/S1069-09642015000022B002
  • RINGLE, C.M., WENDE, S. & BECKER, J.M. (2015): “SmartPLS 3 (SmartPLS 3)”, SmartPLS 3. https://www.smartpls.com/
  • ROEMER, E. (2016): “A tutorial on the use of PLS path modeling in longitudinal studies”, Industrial Management and Data Systems, 116(9), 1901-1921. https://doi.org/10.1108/IMDS-07-2015-0317
  • SANTORO, G., VRONTIS, D., THRASSOU, A. & DEZI, L. (2018): “The Internet of Things: Building a knowledge management system for open innovation and knowledge management capacity”, Technological Forecasting and Social Change, 136, 347-354. https://doi.org/10.1016/j.techfore.2017.02.034
  • SIBBALD, S.L., WATHEN, C.N. & KOTHARI, A. (2016): “An empirically based model for knowledge management in health care organizations”, Health Care Management Review, 41(1), 64- 74. https://doi.org/10.1097/HMR.0000000000000046
  • SOTO-ACOSTA, P. & CEGARRA-NAVARRO, J.G. (2016): “New ICTs for knowledge management in organizations”, Journal of Knowledge Management, 20(3), 417-422. https://doi.org/10.1108/JKM-02-2016-0057
  • SZALMA, S., KOKA, V., KHASANOVA, T. & PERAKSLIS, E.D. (2010): “Effective knowledge management in translational medicine”, Journal of Translational Medicine, 8(1), 68. https://doi.org/10.1186/1479-5876-8-68
  • TEECE, D.J. (2007): “Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance”, Strategic Management Journal, 28(13), 1319-1350. https://doi.org/10.1002/smj.640
  • THRASSOU, A., VRONTIS, D., CHEBBI, H. & YAHIAOUI, D. (2012): “A preliminary strategic marketing framework for new product development”, Journal of Transnational Management, 17(1), 21-44. https://doi.org/10.1080/15475778.2012.650108
  • VIEIRA, C.L.C., BRIONES-PEÑALVER, A.J. & CEGARRA-NAVARRO, J.G. (2015): “Absorptive Capacity and Technology Knowledge: Enhancing Relational Capital”, Knowledge and Process Management, 22(4), 305-317. https://doi.org/10.1002/kpm.1494
  • WAMBA, S.F., GUNASEKARAN, A., AKTER, S., REN, S.J. FAN, DUBEY, R. & CHILDE, S.J. (2017): “Big data analytics and firm performance: effects of dynamic capabilities”, Journal of Business Research, 70, 356-365. https://doi.org/10.1016/j.jbusres.2016.08.009
  • WHO (2020): “Statement on the second meeting of the International Health Regulations (2005) Emergency Committee regarding the outbreak of novel coronavirus (2019-nCoV)”, World Health Organization. https://www.who.int/news-room/detail/30-01-2020-statementon-the-second-meeting-of-the-international-health-regulations-(2005)-emergency-committee-regarding-the-outbreak-of-novel-coronavirus-(2019-ncov)
  • WU, I.-L. & HU, Y.-P. (2012): “Examining knowledge management enabled performance for hospital professionals: A Dynamic Capability view and the mediating role of process capability”, Journal of the Association for Information Systems, 13(12), 976-999. https://doi.org/10.17705/ 1jais.00319
  • YEH, Y.J., LAI, S.Q. & HO, C.T. (2006): “Knowledge management enablers: A case study”, Industrial Management and Data Systems, 106(6), 793-810. https://doi.org/10.1108/02635570610671489
  • ZANGOUEINEZHAD, A. & MOSHABAKI, A. (2009): “The role of structural capital on competitive intelligence”, Industrial Management & Data Systems, 109(2), 262-280. https://doi.org/10.1108/02635570910930136
  • ZHANG, B., TANG, F., SUN, B., NIU, Y., TANG, Z. & SUN, X. (2021): “High-performance work systems, multiple commitments, and knowledge exchange and combination among Chinese public hospital nurses”, Nursing Open, 9(2):1445-1455. https://doi.org/10.1002/nop2.921
  • ZHANG, F., KARAMAGI, H., NSENGA, N., NANYUNJA, M., KARINJA, M., AMANFO, S., CHASE-TOPPING, M., CALDER-GERVER, G., MCGIBBON, M., HUBER, A., WAGNER-GAMBLE, T., GUO, C.G., HAYNES, S., MORRISON, A., FERGUSON, M., AWANDARE, G.A., MUTAPI, F., YOTI, Z., CABORE, J. & WOOLHOUSE, M.E.J. (2021): “Predictors of COVID-19 epidemics in countries of the World Health Organization African Region”, Nature Medicine, 27(November). https://doi.org/10.1038/s41591-021-01491-7
  • ZHANG, X., MAJID, S. & FOO, S. (2012): “Perceived environmental uncertainty, information literacy and environmental scanning: towards a refined framework”, Information Research, 17(2).
Data source: Dialnet