Continuance Usage of Collaboration Tools after Social Distancing and The Influential Factors

Authors

  • Aulia Rido Salsabila BPS-Statistics Indonesia
  • Nori Wilantika Politeknik Statistika STIS
  • Ibnu Santoso Politeknik Statistika STIS
  • Achmad Syahrul Choir

Keywords:

Information Systems

Abstract

Working from home (WFH) during the COVID-19 pandemic has challenges in terms of communication and coordination among employees due to the distance. Therefore, collaboration tools were needed during the COVID-19 pandemic. As we recover from the pandemic, the government revoked the social distancing policy restricting people's activities. The revoke is assumed to influence the continued use of collaboration tools. This study aims to understand the continuance usage of collaboration tools after no more social distancing. This study also seeks to identify the factors influencing the ongoing use of collaboration tools by integrating the Technology Acceptance Model (TAM) and Expectation Confirmatory Model (ECM). The method of data analysis employed was the partial least squares structural equation model (PLS-SEM). The findings indicated that most of 437 respondents kept using collaboration tools after no more social distancing. However, there was a decrease in the frequency of use. Our study findings have also proved that Actual Continued Usage is influenced by Continuance Intention by 43%. Furthermore, a factor that influences continuance intention the most is the attitude toward using collaboration tools. The results of this study also support the integration of TAM and ECM to examine user intentions and behavior regarding the continuance use of a technology.

References

A. Rifai, M. S. Maarif, and A. Sukmawati, “Key to Succesful Implementation of Flexible Working Space as A New Normality in Public Organizations,” Bus. Rev. Case Stud., vol. 2, no. 1, pp. 23–35, Apr. 2021, doi: 10.17358/brcs.2.1.24.

S. Q. Yang and L. Li, Emerging Technologies for Librarians. A Practical Approach in Innovation. Massachusetts: Elsevier Ltd., 2016. doi: 10.1016/b978-1-84334-788-0.00013-6.

V. Jackson, A. Van der Hoek, R. Prikladnicki, and C. Ebert, “Collaboration Tools for Developers,” IEEE Softw., vol. 39, no. 2, pp. 7–15, Mar. 2022, doi: 10.1109/MS.2021.3132137.

M. Schmidtner, C. Doering, and H. Timinger, “Agile Working During COVID-19 Pandemic,” IEEE Eng. Manag. Rev., vol. 49, no. 2, pp. 18–32, Jun. 2021, doi: 10.1109/EMR.2021.3069940.

M. L. Rethlefsen, D. L. Rothman, and D. S. Mojon, “Collaboration Tools,” in Internet Cool Tools for Physicians, no. August, Berlin, Heidelberg: Springer Berlin Heidelberg, 2009, pp. 119–128. doi: 10.1007/978-3-540-76382-6_17.

M. Miljanic and N. Zaric, “Review of collaborative software applications and integration with standard collaboration tools,” in 2020 24th International Conference on Information Technology (IT), Feb. 2020, no. November 2019, pp. 1–4. doi: 10.1109/IT48810.2020.9070420.

A. Thayer, M. J. Bietz, K. Derthick, and C. P. Lee, “I love you, let’s share calendars,” in Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work, Feb. 2012, pp. 749–758. doi: 10.1145/2145204.2145317.

K. Tanner, “Visual Design Tools in Support of Novice Creativity,” Standford University, 2019.

P. Farmoudehyamcheh, “A Systems Approach to Graphic Design Practice Recommended Citation,” Georgia Southern University, 2019. [Online]. Available: https://digitalcommons.georgiasouthern.edu/etd/2021

V. Jackson, A. van der Hoek, and R. Prikladnicki, “Collaboration tool choices and use in remote software teams,” in Proceedings of the 15th International Conference on Cooperative and Human Aspects of Software Engineering, May 2022, pp. 76–80. doi: 10.1145/3528579.3529171.

Asosiasi Penyelenggara Jasa Internet Indonesia, “Indonesian Internet Profile 2022,” Jakarta, 2022. [Online]. Available: apji.or.id

Y.-M. Huang, “The factors that predispose students to continuously use cloud services: Social and technological perspectives,” Comput. Educ., vol. 97, pp. 86–96, Jun. 2016, doi: 10.1016/j.compedu.2016.02.016.

A. I. Safira, P. W. Handayani, and A. A. Pinem, “The Meaning of User Satisfaction and Continuance Intentions with Video Conference Applications,” in 2021 International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS, Oct. 2021, pp. 250–256. doi: 10.1109/ICIMCIS53775.2021.9699164.

S. A. Nikou, “Web-based videoconferencing for teaching online: Continuance intention to use in the post-COVID-19 period,” Interact. Des. Archit., vol. 47, no. 47, pp. 123–143, Feb. 2021, doi: 10.55612/s-5002-047-006.

H.-L. Yang and S.-L. Lin, “User continuance intention to use cloud storage service,” Comput. Human Behav., vol. 52, pp. 219–232, Nov. 2015, doi: 10.1016/j.chb.2015.05.057.

X. Tan and Y. Kim, “User acceptance of SaaS-based collaboration tools: a case of Google Docs,” J. Enterp. Inf. Manag., vol. 28, no. 3, pp. 423–442, Apr. 2015, doi: 10.1108/JEIM-04-2014-0039.

F. Gunadi, “Analisa Pengaruh Trust Dan Risk Berbasis Technology Acceptance Models (TAM) (Studi Kasus : Pengguna Google Drive),” MULTINETICS, vol. 6, no. 1, pp. 67–77, Aug. 2020, doi: 10.32722/multinetics.v6i1.2819.

N. Marangunić and A. Granić, “Technology acceptance model: a literature review from 1986 to 2013,” Univers. Access Inf. Soc., vol. 14, no. 1, pp. 81–95, Mar. 2015, doi: 10.1007/s10209-014-0348-1.

C. Liao, P. Palvia, and J.-L. Chen, “Information technology adoption behavior life cycle: Toward a Technology Continuance Theory (TCT),” Int. J. Inf. Manage., vol. 29, no. 4, pp. 309–320, Aug. 2009, doi: 10.1016/j.ijinfomgt.2009.03.004.

S. A. Nikou, “Web-based videoconferencing in online teaching during the COVID-19 pandemic: University students’ perspectives,” in 2021 International Conference on Advanced Learning Technologies (ICALT), Jul. 2021, pp. 431–435. doi: 10.1109/ICALT52272.2021.00137.

M.-C. Lee, “Explaining and predicting users’ continuance intention toward e-learning: An extension of the expectation–confirmation model,” Comput. Educ., vol. 54, no. 2, pp. 506–516, Feb. 2010, doi: 10.1016/j.compedu.2009.09.002.

G. Malik and A. S. Rao, “Extended expectation-confirmation model to predict continued usage of ODR/ride hailing apps: role of perceived value and self-efficacy,” Inf. Technol. Tour., vol. 21, no. 4, pp. 461–482, Dec. 2019, doi: 10.1007/s40558-019-00152-3.

Y.-M. Cheng, “Drivers of physicians’ satisfaction and continuance intention toward the cloud-based hospital information system,” Kybernetes, vol. 50, no. 2, pp. 413–442, Mar. 2021, doi: 10.1108/K-09-2019-0628.

F. D. . Davis, R. P. . Bagozzi, and P. R. . Warshaw, “User Acceptance of Computer Technology: A Comparison of Two Theoretical Models,” Manage. Sci., vol. 35, no. 8, pp. 982–1003, 1989.

F. D. Davis, “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Q., vol. 13, no. 3, pp. 319–340, 1989, [Online]. Available: http://www.biodiversitylibrary.org/bibliography/33621

A. Bhattacherjee, “Understanding Information Systems Continuance: An Expectation-Confirmation Model,” MIS Q., vol. 25, no. 3, pp. 351–370, 2001.

A. P. Oghuma, C. F. Libaque-Saenz, S. F. Wong, and Y. Chang, “An expectation-confirmation model of continuance intention to use mobile instant messaging,” Telemat. Informatics, vol. 33, no. 1, pp. 34–47, Feb. 2016, doi: 10.1016/j.tele.2015.05.006.

N. Fathema, D. Shannon, and M. Ross, “Expanding The Technology Acceptance Model (TAM) to Examine Faculty Use of Learning Management Systems (LMSs) In Higher Education Institutions,” J. Online Learn. Teach. , vol. 11, no. 2, pp. 210–233, 2015.

M. Darwin et al., Metode Penelitian. Pendekatan Kuantitatif. Bandung: CV Media Sains Indonesia, 2020.

J. F. Hair, G. T. M. Hult, C. M. Ringle, and M. Sarstedt, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) Third Edition. Los Angeles: SAGE Publications, Inc., 2022.

R. R. Marliana, “Partial Least Square-Structural Equation Modeling pada Hubungan Antara Tingkat Kepuasan Mahasiswa dan Kualitas Google Classroom Berdasarkan Metode Webqual 4.0,” J. Mat. Stat. dan Komputasi, vol. 16, no. 2, p. 174, Dec. 2019, doi: 10.20956/jmsk.v16i2.7851.

J. F. Hair, J. J. Risher, M. Sarstedt, and C. M. Ringle, “When to use and how to report the results of PLS-SEM,” Eur. Bus. Rev., vol. 31, no. 1, pp. 2–24, Jan. 2019, doi: 10.1108/EBR-11-2018-0203.

C. Fornell and D. F. Larcker, “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error,” J. Mark. Res., vol. 18, no. 1, pp. 39–50, 1981.

Published

2024-12-18

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