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Tytuł artykułu

Assessing competency and sub-competency for pharmaceutical 4.0 - a Delphi study

Treść / Zawartość
Identyfikatory
Warianty tytułu
PL
Ocena kompetencji i podkompetencji dla farmaceutyki 4.0 - badanie Delphi
Języki publikacji
EN
Abstrakty
EN
This research aims to conduct competency mapping and sub-competencies quantitatively through Delphi method in two rounds to provide comprehensive results. The application of Delphi's approach then refers to several rounds of expert surveys based on existing questionnaires. The first round involved 15 practitioners from the Pharmaceutical Industry. In the first phase, the research explores what competencies are most needed through questionnaires. Furthermore, in phase two, a greater number of participants are obtained through research relations. The second round involves the participation of 71 experts, including practitioners from 19 Pharmaceutical Industries and academics. The results of the study were processed using Exploratory Factor Analysis and produced six factors representing six competencies: learning and innovation skills, research skills, digital skills, bioinformatics, data ethics, and regulatory compliance. In addition, this study produced 44 sub-competencies that representing 6 core competencies. Competencies and sub-competencies achieved can be used as a referral for pharmaceutical practices in the Era of Pharmaceutical 4.0. More research on competencies in the Pharmaceutical Industry is needed to achieve reliable and valid instruments.
PL
Niniejsze badanie ma na celu ilościowe mapowanie kompetencji i podkompetencji metodą Delphi w dwóch rundach w celu uzyskania kompleksowych wyników. Zastosowanie podejścia Delphi odnosi się następnie do kilku rund ankiet eksperckich opartych na istniejących kwestionariuszach. W pierwszej rundzie wzięło udział 15 praktyków z branży farmaceutycznej. W pierwszej fazie badanie za pomocą kwestionariuszy sprawdza, jakie kompetencje są najbardziej potrzebne. Ponadto w fazie drugiej większą liczbę uczestników uzyskuje się poprzez relacje badawcze. W drugiej turze udział bierze 71 ekspertów, w tym praktycy z 19 Branży Farmaceutycznej oraz pracownicy naukowi. Wyniki badania zostały przetworzone za pomocą eksploracyjnej analizy czynnikowej i wygenerowały sześć czynników reprezentujących sześć kompetencji: umiejętności uczenia się i innowacji, umiejętności badawcze, umiejętności cyfrowe, bioinformatykę, etykę danych i zgodność z przepisami. Ponadto w badaniu uzyskano 44 podkompetencje, które reprezentują 6 kluczowych kompetencji. Uzyskane kompetencje i podkompetencje mogą być wykorzystane jako skierowanie do praktyk farmaceutycznych w Erze Farmaceutyki 4.0. Potrzebne są dalsze badania nad kompetencjami w przemyśle farmaceutycznym, aby uzyskać niezawodne i ważne instrumenty.
Rocznik
Strony
421--436
Opis fizyczny
Bibliogr. 41 poz., rys., tab.
Twórcy
  • Institut Teknologi Bandung, School of Business Management
  • Institut Teknologi Bandung, School of Business Management
  • Institut Teknologi Bandung, School of Business Management
  • Biofarma, Indonesia
Bibliografia
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  • 4.Atkinson, J., De Paepe, K., Pozo, A., Rekkas, D., Volmer, D., Hirvonen, J., Bozic, B., Skowron, A., Mircioiu, C., Marcincal, A., Koster, A., Wilson, K. and van Schravendijk, C., (2016). A Study on How Industrial Pharmacists Rank Competences for Pharmacy Practice: A Case for Industrial Pharmacy Specialization. Pharmacy, 4(1), 13.
  • 5.Attwood, T. K., Blackford, S., Brazas, M. D., Davies, A. and Schneider, M. V., (2019). A global perspective on evolving bioinformatics and data science training needs. Briefings in Bioinformatics, 20(2), 398-404.
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  • 7.Bates, I., John, C., Bruno, A., Fu, P. and Aliabadi, S., (2016). An analysis of the global pharmacy workforce capacity. Human Resources for Health, 14(1), 1-7.
  • 8.Buda, A., Framling, K., Borgman, J., Madhikermi, M., Mirzaeifar, S. and Kubler, S., (2015). Data supply chain in Industrial Internet. IEEE International Workshop on Factory Communication Systems - Proceedings, WFCS, 2015-July.
  • 9.Da Glória Prado, A., Chiareto, J., Oliva, F. L. and De Hildebrand E Grisi, C. C., (2017). Ethical implications in the way some marketing activities is using big data. WMSCI 2017 - 21st World Multi-Conference on Systemics, Cybernetics and Informatics, Proceedings.
  • 10.de Winter, J. C. F., Dodou, D. and Wieringa, P. A., (2009). Exploratory factor analysis with small sample sizes. Multivariate Behavioral Research, 44(2), 147-181.
  • 11.Delpasand, K., Kiani, M., Afshar, L., Tavakkoli, S. N., Farshad, S. and Shirazi, H., (2018). Extracting the Ethical Challenges of Pharmacy Profession in Iran, a Qualitative Study. Journal of Research in Medical and Dental Science |, 6(1), 52-58.
  • 12.Dirican, C., (2015). The Impacts of Robotics, Artificial Intelligence On Business and Economics. Procedia - Social and Behavioral Sciences, 195:564-73.
  • 13.Fitsilis, P., Tsoutsa, P. and Gerogiannis, V., (2018). Industry 4.0: Required Personnel Competences. Industry 4.0, 3(3), 130-133.
  • 14.Flores, E., Xu, X. and Lu, Y., (2020). Human Capital 4.0: a workforce competence typology for Industry 4.0. Journal of Manufacturing Technology Management, 31(4), 687-703.
  • 15.Flynn, A., (2019). Using artificial intelligence in health-system pharmacy practice: Finding new patterns that matter. American Journal of Health-System Pharmacy, 76(9), 622-627.
  • 16.Gangani, N., McLean, G. N. and Braden, R. A., (2008). A Competency-Based Human Resource Development Strategy. Performance Improvement Quarterly, 19(1), 127-139.
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  • 18.Grzybowska, K., Łupicka, A., (2017). Key competencies for Industry 4.0. Economics and Management Innovations (ICEMI), 1(March 2018), 250-253.
  • 19.Hanif, H., Rakhman, A., Nurkholis, M. and Pirzada, K., (2019). Intellectual capital: extended VAIC model and building of a new HCE concept: the case of Padang Restaurant Indonesia. African Journal of Hospitality, Tourism and Leisure, 8 (S), 1-15.
  • 20.Hauben, M., Hung, E. and Hsieh, W.-Y., (2017). An exploratory factor analysis of the spontaneous reporting of severe cutaneous adverse reactions. Therapeutic Advances in Drug Safety, 8(1), 4-16.
  • 21.Hemanth Kumar, S., Talasila, D., Gowrav, M. P., and Gangadharappa, H. V., (2020). Adaptations of Pharma 4.0 from Industry 4.0. Drug Invention Today |, 14(3), 2020.
  • 22.Jerman, A., Bertoncelj, A., Dominici, G., Pejić Bach, M. and Trnavčević, A., (2020). Conceptual Key Competency Model for Smart Factories in Production Processes. Organizacija, 53(1).
  • 23.Juwita, I., Kamil, I., Jonrinaldi, J., Yuliandra, B. and Halim, I., (2020). Mastery of Skills 4.0 Effects on the Readiness College Students to Face Revolution of Industry 4.0. Jurnal Optimasi Sistem Industri, 19(1), 1.
  • 24.Kannan, K. S. P. N., Garad, A., (2020). Competencies of quality professionals in the era of industry 4.0: a case study of electronics manufacturer from Malaysia. International Journal of Quality and Reliability Management, 38(3):839-71.
  • 25.Le Deist, F. D., Winterton, J., (2005). What is competence? In Human Resource Development International.
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  • 28.Mor, R. S., Bhardwaj, A., Singh, S. and Arora, V. K., (2020). Exploring the factors affecting supply chain performance in dairy industry using exploratory factor analysis technique. International Journal of Industrial and Systems Engineering, 36(2), 15-31.
  • 29.Mulder, N., Schwartz, R., Brazas, M. D., Brooksbank, C., Gaeta, B., Morgan, S. L., Pauley, M. A., Rosenwald, A., Rustici, G., Sierk, M., Warnow, T. and Welch, L., (2018). The development and application of bioinformatics core competencies to improve bioinformatics training and education. PLoS Computational Biology, 14(2), 1-14.
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  • 33.Pirzada, K., (2016). Providers and users’ perception of voluntary need of human resource disclosure: A content analysis. Polish Journal of Management Studies, 14(2), 232-242.
  • 34.Rampasso, I. S., Mello, S. L. M., Walker, R., Simão, V. G., Araújo, R., Chagas, J., Quelhas, O. L. G. and Anholon, R., (2020). An investigation of research gaps in reported skills required for Industry 4.0 readiness of Brazilian undergraduate students. Higher Education, Skills and Work-Based Learning, 11(1), 34-47.
  • 35.Rowe, G., Wright, G., (2001). Expert Opinions in Forecasting: The Role of the Delphi Technique (pp. 125-144). Springer, Boston, MA.
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  • 39.Spencer, L. M., McClelland, D. C. and Spencer, S., (1994). Competency assessment methods History and state of the art. Boston: Hay/McBer Research Press. In In Handbook of Industrial, Work and Organizational Psichology- Volume 1 Personnel Psichology, 88-121.
  • 40.Spoorthy, M. S., Singh, L. K., Tikka, S. K. and Hara, S. H., (2021). Exploratory Factor Analysis of Young’s Internet Addiction Test Among Professionals from India: An Online Survey. Indian Journal of Psychological Medicine, 43(1).
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Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b1d2d991-9273-48cc-a234-fce0fc3a41fd
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