Work management solution in the context of modern supporting technologies
DOI:
https://doi.org/10.20397/2177-6652/2021.v21i3.2170Palabras clave:
work management solutoons, embedded systems, work assistance, work supporting technologies, disability assistive technologiesResumen
This paper presents the results of research on embedded systems and their potential to become supporting solutions for work management of disabled people. First, the general idea of work organization is presented. Then, the modern technologies have been presented and peoples’ approach to modern technologies have been also described. What is more, the general rules of hiring disabled persons have been presented, with regard to older persons and other outsiders. Next, the general rules of hiring disabled persons have been presented. The scientific approach, logical reasoning and various analytical methods were used to verify if disabled people perceive the embedded systems as a modern supporting technology for work management solutions. According to the presented final results of the research that been presented, both the professionals having deep knowledge about electronics and the disabled persons recognize the potential in using the embedded systems for helping peoples with disabilities at work and as work management solutions.
Citas
A Survey on Optimized Implementation of Deep Learning Models on the NVIDIA Jetson Platform, (accessed: 10.12.2020),
Alavi, M., & Leidner, D. (1999). Knowledge Management Systems: Issues, Challenges, and Benefits. Communications of the Association for Information Systems, 1. https://doi.org/10.17705/1CAIS.00107
ARM Webpage, (accessed: 02.12.2020),
Baryshnikova, N., Kiriliuk, O., & Klimecka-Tatar, D. (2021). Enterprises’ strategies transformation in the real sector of the economy in the context of the COVID-19 pandemic. Production Engineering Archives, 27(1), 8–15. https://doi.org/10.30657/pea.2021.27.2
Bilan, Y., Hussain, H. I., Haseeb, M., & Kot, S. (2020). Sustainability and Economic Performance: Role of Organizational Learning and Innovation. Engineering Economics, 31(1), 93–103. https://doi.org/10.5755/j01.ee.31.1.24045
Buhalis, D., & Law, R. (2008). Progress in information technology and tourism management: 20 years on and 10 years after the Internet—The state of eTourism research. Tourism Management, 29(4), 609–623. https://doi.org/10.1016/j.tourman.2008.01.005
Chajduga, T. (2021). Embedded systems ensuring safety for people with disabilities. System Safety: Human - Technical Facility - Environment, 3(1), (in press).
Chmielarz, G. (2019). Present state and future application of smart technologies in manufacturing processes. Production Engineering Archives, 24(24), 14–19. https://doi.org/10.30657/pea.2019.24.04
Edge computing with low power consumption, (accessed: 11.12.2020),
Embedded systems, Omni Sci, (accessed: 11.12.2020),
Frăticiu, L., Mihăescu, D., & Andănuţ, M. (2015). Culture-Civilization-Organizational Culture and Managerial Performance. Procedia Economics and Finance, 27, 69–72. https://doi.org/10.1016/S2212-5671(15)00973-9
Frustaci, F., Perri, S., Cocorullo, G., & Corsonello, P. (2020). An embedded machine vision system for an in-line quality check of assembly processes. Procedia Manufacturing, 42(1–3), 211–218. https://doi.org/10.1016/j.promfg.2020.02.072
Gede Riana, I., Suparna, G., Gusti Made Suwandana, I., Kot, S., & Rajiani, I. (2020). Human resource management in promoting innovation and organizational performance. Problems and Perspectives in Management, 18(1), 107–118. https://doi.org/10.21511/ppm.18(1).2020.10
Gomes, J. G. C., Okano, M. T., & Otola, I. (2020). Creation of indicators for classification of business models and business strategies in production systems. Polish Journal of Management Studies, 22(2), 142–157. https://doi.org/10.17512/pjms.2020.22.2.10
Grabara, J., Cehlar, M., & Dabylova, M. (2019). Human factor as an important element of success in the implementation of new management solutions. Polish Journal of Management Studies, 20(2), 225–235. https://doi.org/10.17512/pjms.2019.20.2.19
Haque, A. u., Aston, J., Kozlovski, E., & Caha, Z. (2020). Role of external CSR and social support programme for sustaining human capital in contrasting economies. Polish Journal of Management Studies, 22(1), 147–168. https://doi.org/10.17512/pjms.2020.22.1.10
http://users.ece.utexas.edu/~valvano/arm/outline1.htm
https://developer.sony.com/develop/spresense/
https://forum.arduino.cc/index.php?topic=539419.0
https://www.omnisci.com/technical-glossary/embedded-systems
https://www.precisioncomputers.com.au/nvidia-jetson-tx2-tegra-developer-kit/
Ingaldi, M. (2018). Overview of the main methods of service quality analysis. Production Engineering Archives, 18(18), 54–59. https://doi.org/10.30657/pea.2018.18.10
Ingaldi, M., & Klimecka-Tatar, D. (2020). People’s Attitude to Energy from Hydrogen—From the Point of View of Modern Energy Technologies and Social Responsibility. Energies, 13(24), 6495. https://doi.org/10.3390/en13246495
Isensee, C., Teuteberg, F., Griese, K.-M., & Topi, C. (2020). The relationship between organizational culture, sustainability, and digitalization in SMEs: A systematic review. Journal of Cleaner Production, 275, 122944. https://doi.org/10.1016/j.jclepro.2020.122944
KAMAMI oficjalnym partnerem STMICROELECTRONICS, (accessed: 10.12.2020), https://stm32.eu/
Kapusta, M., Sukiennik, M., & Bąk, P. (2018). Effectiveness of occupational health and safety rules in shaping organizational culture. Inżynieria Mineralna, 19(1), 245–254. https://doi.org/10.29227/IM-2018-01-37
Kim, J., Lee, S., Chun, H., & Lee, C. (2021). Compact curved-edge displacement sensor-embedded spindle system for machining process monitoring. Journal of Manufacturing Processes, 64(12), 1255–1260. https://doi.org/10.1016/j.jmapro.2021.02.056
Klimecka-Tatar, D., & Ingaldi, M. (2020). How to indicate the areas for improvement in service process - the Knowledge Management and Value Stream Mapping as the crucial elements of the business approach. G&T, Revista Gestão & Tecnologia, 20(2), 52–74. https://doi.org/10.20397/2177-6652/2020.v20i2.1878
Klimecka-Tatar, D., & Niciejewska, M. (2021). Small-sized enterprises management in the aspect of organizational culture. G&T, Revista Gestão & Tecnologia, 21(1), 4–24. https://doi.org/10.20397/2177-6652/2021.v21i1.2023
Knijn, T., & van Wel, F. (2014). Better at work: Activation of partially disabled workers in the Netherlands. Alter, 8(4), 282–294. https://doi.org/10.1016/j.alter.2014.09.005
Korpysa, J. (2021). Process Ambidexterity in Startups Innovation. Management Systems in Production Engineering, 29(1), 27–32. https://doi.org/10.2478/mspe-2021-0004
Lazar, S., Klimecka-Tatar, D., & Obrecht, M. (2021). Sustainability Orientation and Focus in Logistics and Supply Chains. Sustainability, 13(6), 3280. https://doi.org/10.3390/su13063280
Liu, J., & Feng, J. (2021). Design of embedded digital image processing system based on ZYNQ. Microprocessors and Microsystems, 83(1), 104005. https://doi.org/10.1016/j.micpro.2021.104005
Lozhkin, A., Maiorov, K., & Bozek, P. (2021). Convolutional Neural Networks Training for Autonomous Robotics. Management Systems in Production Engineering, 29(1), 75–79. https://doi.org/10.2478/mspe-2021-0010
Matuszny, M. (2020). Building decision trees based on production knowledge as support in decision-making process. Production Engineering Archives, 26(2), 36–40. https://doi.org/10.30657/pea.2020.26.08
Mistarihi, M. Z. (2020). A data set on anthropometric measurements and degree of discomfort of physically disabled workers for ergonomic requirements in work space design. Data in Brief, 30, 105420. https://doi.org/10.1016/j.dib.2020.105420
NVIDIA Jetson TX2 Tegra Developer Kit, (accessed: 11.12.2020),
Pietraszek, J., Radek, N., & Goroshko, A. V. (2020). Challenges for the DOE methodology related to the introduction of Industry 4.0. Production Engineering Archives, 26(4), 190–194. https://doi.org/10.30657/pea.2020.26.33
Raspberry Pi 400 – Your complete personal computer built into a compact keyboard, (accessed: 10.12.2020), https://www.raspberrypi.org/
Raspberry Pi GPIO pins. (accessed: 11.12.2020)
Safta, C. G., Stan, E., Suditu, M., & Iurea, C. (2011). Facilitating the disabled persons’ insertion in the Labour market through a professional counselling process directed towards the certification of competences. Procedia - Social and Behavioral Sciences, 15, 1120–1124. https://doi.org/10.1016/j.sbspro.2011.03.249
Schwenk, C. H. (1986). Information, Cognitive Biases, and Commitment to a Course of Action. Academy of Management Review, 11(2), 298–310. https://doi.org/10.5465/amr.1986.4283106
Sharma, A., Zsarnoczky, M., & Dunay, A. (2018). An empirical study on the influences of management’s attitudes toward employees with disabilities in the hospitality sector. Polish Journal of Management Studies, 18(2), 311–323. https://doi.org/10.17512/pjms.2018.18.2.25
Teo, T. S.H., & Too, B. L. (2000). Information Systems Orientation and Business Use of the Internet: An Empirical Study. International Journal of Electronic Commerce, 4(4), 105–130. https://doi.org/10.1080/10864415.2000.11518381
Tkachenko, V., Klymchuk, M., & Tkachenko, I. (2021). Recursive and Convergence Methodology of the Investment Management of the Enterprise Digitalization Processes. Management Systems in Production Engineering, 29(1), 14–19. https://doi.org/10.2478/mspe-2021-0002
Valvano, J.W. PhD, Embedded systems: introduction to arm cortex-m microcontrollers (accessed: 11.12.2020)
Wright, P. M., & Snell, S. A. (1998). Toward a Unifying Framework for Exploring Fit and Flexibility in Strategic Human Resource Management. Academy of Management Review, 23(4), 756. https://doi.org/10.2307/259061
Wuellrich, J.-P. (2010). The effects of increasing financial incentives for firms to promote employment of disabled workers. Economics Letters, 107(2), 173–176. https://doi.org/10.1016/j.econlet.2010.01.016
Zhang, K. (2021). Animation virtual reality scene modeling based on complex embedded system and FPGA. Microprocessors and Microsystems, 80(1), 103632. https://doi.org/10.1016/j.micpro.2020.103632
Zhou, J. (2020). Real-time task scheduling and network device security for complex embedded systems based on deep learning networks. Microprocessors and Microsystems, 79(1), 103282. https://doi.org/10.1016/j.micpro.2020.103282
Descargas
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2021 Journal of Management & Technology
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial 4.0.
Os direitos, inclusive os de tradução, são reservados. É permitido citar parte de artigos sem autorização prévia desde que seja identificada a fonte. A reprodução total de artigos é proibida. Em caso de dúvidas, consulte o Editor.
