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Generation Z and Information Visualization: Work from Home Managerial Task Context
Corresponding Author(s) : Dyah Sekar J
Proceedings Universitas Muhammadiyah Yogyakarta Undergraduate Conference,
Vol. 2 No. 1 (2022): Strengthening Youth Potentials for Sustainable Innovation
Abstract
The remote working method, especially the work from home (WFH) method, will create its own challenges for employees, especially at the managerial level. Information visualization is used to present information in supporting the work from home process which in theory is expected to improve the quality of tasks and managerial decisions. Different generations may respond to remote work situations differently, so it is necessary to re-examine the effect of visualization in the context of work from home (WFH). in different generations. This study will examine whether there are differences in efficiency, effectiveness, and satisfaction of managerial decisions that work with the work from home (WFH) method when faced with information visualization and carried out by different generations. This test uses efficiency, effectiveness, and satisfaction as dependent variables, as well as information visualization and generation as independent variables. The participants used are practitioners and students who have or are currently carrying out assignments using the work from home (WFH) method. The type of data used in this study is primary data. The data in this study were collected using an experimental instrument with a given case. Based on the process of the instrument being distributed, 33 participants were obtained which could be further processed. Hypothesis testing in this study used Two-way Anova with software. The results showed that there were differences in the level of efficiency, effectiveness, and satisfaction of managerial decisions between participants who completed assignments with high information visualization and low information visualization. This study also shows that there is no difference in the level of efficiency, effectiveness, and managerial satisfaction between participants who complete assignments with generation Z and non-Z generations.
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- Bencsik, A., & Machova, R. (2016, April). Knowledge Sharing Problems from the Viewpoint of Intergeneration Management. In ICMLG2016 - 4th International Conferenceon Management, Leadership and Governance: ICMLG2016 (p.42). Academic Conferences andpublishing limited.
- Borthick, A. F., & Pennington, R. R. (2017). When data become ubiquitous, what becomes of accounting and assurance? Journal of Information Systems, 31(3). https://doi.org/10.2308/isys-10554
- Brink, W. D., & Lee, L. S. (2016). LOOKS CAN B DECEIVING Pictorial or graphical presentations can help explain difficult concepts or highlight new patterns. The trick is avoiding the following 5 pitfalls.
- Handiwidjojo, W., & Ernawati, L. (2016). Pengukuran Tingkat Ketergunaan (Usability) Sistem Informasi Keuangan Studi Kasus: Duta Wacana Internal Transaction (Duwit). JUISI, 02(01).
- Hutchinson, J. W., Heyman, S. J., Alba, J. W., & Eisenstein, E. M. (2010). Heuristics and Biases in Data-Based Decision Making: Effects of Experience, Training, and Graphical Data Displays. Journal of Marketing Research, XLVII, 627–642. http://www.marketingpower.com/jmraug10
- ISOErgonomic reqirements for office work with visual display terminals (VDTs) – Part 11: Guidance on usability, (1998).
- Marni Waruwu, L., & Wulandari, T. (2020). PERANCANGAN VISUALISASI INFORMASI DATA WAREHOUSE DAN DASHBOARD SYSTEM DATA PERGURUAN TINGGI DI UNIVERSITAS MERCUBUANA JAKARTA JAKARTA. Jurnal Ilmu Teknik Dan Komputer, 4(2), 11650.
- Nahartyo, E., & Utami, I. (2016). Panduan Praktis Riset Eksperimen (S. Bambang (ed.); Cetakan 1). PT Indeks.
- Perkhofer, L. M., Hofer, P., Walchshofer, C., Plank, T., & Jetter, H. C. (2019). Interactive visualization of big data in the field of accounting: A survey of current practice and potential barriers for adoption. Journal of Applied Accounting Research, 20(4), 497–525. https://doi.org/10.1108/JAAR-10-2017-0114
- Perkhofer, L., Walchshofer, C., & Hofer, P. (2020). Does design matter when visualizing Big Data? An empirical study to investigate the effect of visualization type and interaction use. Journal of Management Control, 31(1–2), 55–95. https://doi.org/10.1007/s00187-020-00294-0
- Rubin, J., & Chisnell., D. (2008). Handbook of Usibility Testing, How to Plan, Design, and Conduct Effective Test. Wiley Publishing.
- Rudolph, C. W., & Zacher, H. (2020). “The COVID-19 generation”: A cautionary note. Work, Aging and Retirement, 6(3), 139–145. https://doi.org/10.1093/workar/waaa009
- Schneiderman, B. (1998). Designing for Effective Human/Computer Interaction (3rd ed.). Addison Wesley Longman Inc.
- Silabus. (2018). Generasi Z Berdasarkan Teori Generasi. Silabus Web. https://www.silabus.web.id/generasi-z-berdasarkan-teori-generasi/
- Umanath, Narayan s, Vessey, & Iris. (1994). Multi-attribute Data Presentation and Human Judgment: A Cognitive Fit Perspective. Decision Sciences.
- Vessey. (1991). Cognitive Fit: A Theory-Based Analysis of the Graphs Versus Tables Literature.
References
Bencsik, A., & Machova, R. (2016, April). Knowledge Sharing Problems from the Viewpoint of Intergeneration Management. In ICMLG2016 - 4th International Conferenceon Management, Leadership and Governance: ICMLG2016 (p.42). Academic Conferences andpublishing limited.
Borthick, A. F., & Pennington, R. R. (2017). When data become ubiquitous, what becomes of accounting and assurance? Journal of Information Systems, 31(3). https://doi.org/10.2308/isys-10554
Brink, W. D., & Lee, L. S. (2016). LOOKS CAN B DECEIVING Pictorial or graphical presentations can help explain difficult concepts or highlight new patterns. The trick is avoiding the following 5 pitfalls.
Handiwidjojo, W., & Ernawati, L. (2016). Pengukuran Tingkat Ketergunaan (Usability) Sistem Informasi Keuangan Studi Kasus: Duta Wacana Internal Transaction (Duwit). JUISI, 02(01).
Hutchinson, J. W., Heyman, S. J., Alba, J. W., & Eisenstein, E. M. (2010). Heuristics and Biases in Data-Based Decision Making: Effects of Experience, Training, and Graphical Data Displays. Journal of Marketing Research, XLVII, 627–642. http://www.marketingpower.com/jmraug10
ISOErgonomic reqirements for office work with visual display terminals (VDTs) – Part 11: Guidance on usability, (1998).
Marni Waruwu, L., & Wulandari, T. (2020). PERANCANGAN VISUALISASI INFORMASI DATA WAREHOUSE DAN DASHBOARD SYSTEM DATA PERGURUAN TINGGI DI UNIVERSITAS MERCUBUANA JAKARTA JAKARTA. Jurnal Ilmu Teknik Dan Komputer, 4(2), 11650.
Nahartyo, E., & Utami, I. (2016). Panduan Praktis Riset Eksperimen (S. Bambang (ed.); Cetakan 1). PT Indeks.
Perkhofer, L. M., Hofer, P., Walchshofer, C., Plank, T., & Jetter, H. C. (2019). Interactive visualization of big data in the field of accounting: A survey of current practice and potential barriers for adoption. Journal of Applied Accounting Research, 20(4), 497–525. https://doi.org/10.1108/JAAR-10-2017-0114
Perkhofer, L., Walchshofer, C., & Hofer, P. (2020). Does design matter when visualizing Big Data? An empirical study to investigate the effect of visualization type and interaction use. Journal of Management Control, 31(1–2), 55–95. https://doi.org/10.1007/s00187-020-00294-0
Rubin, J., & Chisnell., D. (2008). Handbook of Usibility Testing, How to Plan, Design, and Conduct Effective Test. Wiley Publishing.
Rudolph, C. W., & Zacher, H. (2020). “The COVID-19 generation”: A cautionary note. Work, Aging and Retirement, 6(3), 139–145. https://doi.org/10.1093/workar/waaa009
Schneiderman, B. (1998). Designing for Effective Human/Computer Interaction (3rd ed.). Addison Wesley Longman Inc.
Silabus. (2018). Generasi Z Berdasarkan Teori Generasi. Silabus Web. https://www.silabus.web.id/generasi-z-berdasarkan-teori-generasi/
Umanath, Narayan s, Vessey, & Iris. (1994). Multi-attribute Data Presentation and Human Judgment: A Cognitive Fit Perspective. Decision Sciences.
Vessey. (1991). Cognitive Fit: A Theory-Based Analysis of the Graphs Versus Tables Literature.