5. Discussion and Conclusions
This study attempted to identify factors that could affect the acceptance of cloud-based electronic signature services. To this end, based on the TOE theory used in prior research a research model was proposed by combining work technology suitability and service readiness, and the main results of the empirical analysis are as follows.
First, simplicity, relative advantage, and compatibility in the technical characteristics significantly impacted the suitability, but the perceived security did not significantly affect the suitability. Since this can be seen as a result of a lack of trust by consumers in the complementarity of cloud services, it is necessary to improve consumers’ perception that the cloud service is safe, and this will take some time. In addition, simplicity, relative advantages, and compatibility lower resistance to the adoption of new technologies. Therefore, the cloud-based digital signature service should provide clarity and easy to use than the existing digital signature service and should eliminate difficulties in use and feel convenient by increasing compatibility with the company’s infrastructure. This applies not only to cloud services but also to existing ICT-related services.
Second, it was found that collaboration and support from management in organizational characteristics had a significant effect on both suitability and service readiness, but innovation did not significantly affect either of them. This is consistent with the findings of Gil [
22], in that collaboration and support from management have a significant effect on suitability. In addition, the innovation does not significantly affect suitability and service readiness. This result supports the results of Parasuraman [
23] and Maduku et al. [
34], in that organizations show resistance to innovation in the early stage, and such resistance acts as an impediment to innovation acceptance. Therefore, in order to introduce a cloud-based digital signature service, the interest and willingness of the decision-makers in an organization are indispensable, and the support of the management layer can be achieved only if the interest and willingness are the basis. Through this, it was found that departmental collaboration can be achieved. In order for this to work smoothly, the cloud-based digital signature being provided must be tailored to the organization compared to the existing service.
Third, in the relationship between environmental characteristics and suitability, both facilitation conditions and government support were found to have a significant effect. Through this, it is judged that the government’s support is recognized as appropriate and causes the intention to adopt the investment to rise. In order to expand the government’s willingness to support the policy, companies must first actively seek support for this service and propose improvements to related laws and systems. However, only the facilitation condition was found to have a significant effect in relation to service readiness. It implied that the degree of influence of government support varies depending on the size of the company.
Lastly, it was found that the expected profitability in economic characteristics had a significant effect on service readiness. This supports the findings of Iacovou et al. [
25]. In other words, it was concluded that the use of the cloud digital signature service raises the expectation that better profits can be generated than when using the existing service, and this could affect service preparation and intention to use. On the other hand, it was found that uncertainty did not significantly affect service readiness. This is in line with the existing research results of Das and Teng [
26]. It was concluded that if the organization does not support the cloud-based digital signature service’s reliability, this will lower expectations for service preparation.
However, this study has the following limitations. First, users’ perceptions of cloud-based digital signature services have not been established. Since the current cloud-based digital signature service has just been introduced, there may be a difference in people’s perception of it in the future.
Second, research from an individual perspective is also necessary. The survey used in the study sought to review the organizational perspective on accepting related services. As related services expand to the individual domain, future research needs to develop and analyze individual-level variables.
Lastly, there are limitations on variables for explaining all cloud-based digital signature services. In future research, it is expected that more interesting research results can be obtained by developing additional factors that can better describe cloud services, apart from variables originating from existing ICT research.
Author Contributions
All of the authors contributed equally to the writing of the paper. Conceptualization, K.W.C. and J.C.; methodology, K.W.C., Y.S.K. and J.C.; formal analysis, Y.S.K. and J.C.; resources, K.W.C.; writing—original draft preparation, K.W.C. and Y.S.K.; writing—review and editing, J.C.; visualization, K.W.C. and Y.S.K.; supervision, J.C.; project administration, K.W.C. and J.C. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Ethical review and approval could be waived for this study because the unit of analysis in this research is at the firm level.
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
The data presented in this study are available on request from the corresponding author.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Shin, W.; Ahn, H. Effects of innovation characteristics of cloud computing services, technostress on innovation resistance and acceptance intention: Focused on public sector. Knowl. Manag. Rev. 2019, 20, 59–86. [Google Scholar]
- Min, Y.G. An Empirical Study on Factors Affecting Acceptance and Avoidance of Cloud Service for Each Industry. Ph.D. Thesis, Sangmyung University, Chungnam, Korea, 2016. [Google Scholar]
- Low, C.; Chen, Y.; Wu, M. Understanding the determinants of cloud computing adoption. Ind. Manag. Data Syst. 2011, 111, 1006–1023. [Google Scholar] [CrossRef] [Green Version]
- Mohammed, F.; Ibrahim, O.; Ithnin, N. Factors influencing cloud computing adoption for e-government implementation in developing countries: Instrument development. J. Syst. Inf. Technol. 2016, 18, 297–327. [Google Scholar] [CrossRef]
- Park, E.; Kim, K.J. An integrated adoption model of mobile cloud services: Exploration of key determinants and extension of technology acceptance model. Telemat. Inform. 2014, 31, 376–385. [Google Scholar] [CrossRef]
- Pańkowska, M.; Pyszny, K.; Strzelecki, A. Users’ adoption of sustainable cloud computing solutions. Sustainability 2020, 12, 9930. [Google Scholar] [CrossRef]
- Oliveira, T.; Thomas, M.; Espadanal, M. Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors. Inf. Manag. 2014, 51, 497–510. [Google Scholar] [CrossRef]
- Gangwar, H.; Date, H.; Ramaswamy, R. Understanding determinants of cloud computing adoption using an integrated TAM-TOE model. J. Enterp. Inf. Manag. 2015, 28, 107–130. [Google Scholar] [CrossRef]
- Kim, A.Y.; Kim, T.S.; Oh, H.-K. Factors influencing the intention to adopt new electronic authentication services: Focusing on mobile financial service. J. Korean Inst. Commun. Inf. Sci. 2018, 43, 461–474. [Google Scholar]
- Quinting, A.; Lins, S.; Szefer, J.; Sunyaev, A. Advancing the adoption of a new generation of certifications–A theoretical model to explain the adoption of continuous cloud service certification by certification authorities. In Proceedings of the 13th Internationale Tagung Wirtschaftsinformatik, St. Gallen, Switzerland, 12–15 February 2017. [Google Scholar]
- Behrend, T.S.; Wiebe, E.N.; London, J.E.; Johnson, E.C. Cloud computing adoption and usage in community colleges. Behav. Inf. Technol. 2011, 30, 231–240. [Google Scholar] [CrossRef]
- Lee, S.W. Research on Determinants for Big Data System Adoption in Organizations. Ph.D. Thesis, Sungkyunkwan University, Seoul, Korea, 2016. [Google Scholar]
- Venkatesh, V.; Morris, M.G.; Davis, G.B.; Davis, F.D. User acceptance of information technology: Toward a unified view. MIS Q. 2003, 27, 425–478. [Google Scholar] [CrossRef] [Green Version]
- Jeon, S.H.; Park, N.R.; Lee, C.C. Study on the factors affecting the intention to adopt public cloud computing service. Entrue J. Inf. Technol. 2011, 10, 97–112. [Google Scholar]
- Goodhue, D.L. Development and measurement validity of a task-technology fit instrument for user evaluations of information system. Decis. Sci. 1998, 29, 105–138. [Google Scholar] [CrossRef]
- Goodhue, D.L.; Thompson, R.L. Task-Technology Fit and individual performance. MIS Q. 1995, 19, 213–236. [Google Scholar] [CrossRef]
- Goodhue, D.L. Understanding user evaluations of information systems. Manag. Sci. 1995, 41, 1827–1844. [Google Scholar] [CrossRef]
- Raven, A.; Leeds, E.; Park, C. Digital video presentation and student performance: A task technology fit perspective. Int. J. Inf. Commun. Technol. Educ. (IJICTE) 2010, 6, 17–29. [Google Scholar] [CrossRef] [Green Version]
- Kim, S.; Park, J.; Kim, E.; Park, J. A study on big-data application methods and their expected effect analysis—Impact of data analysis to improve employee decision making in domestic firms. J. Inf. Technol. Archit. 2015, 12, 159–170. [Google Scholar]
- Kim, J.K. A Study on the Usage Intention of Category Types in the Mobile Application Based on the Technology Readiness and Acceptance Model. Ph.D. Thesis, Kongju National University, Kongju, Korea, 2013. [Google Scholar]
- Kim, C.S. A Study on the Consumer Satisfaction Model Incorporating the Technology Readiness Model and the Technology Paradox Theory. Ph.D. Thesis, Korea Aerospace University, Goyang, Korea, 2018. [Google Scholar]
- Gil, H.C. An Empirical Study on Adoption Factor and Performance Analysis of Smart Factory through Technical Acceptance Model: Focusing on TOE and IS Success Model. Ph.D. Thesis, Hansung University, Seoul, Korea, 2019. [Google Scholar]
- Parasuraman, A. Technology Readiness Index (Tri): A multiple-item scale to measure readiness to embrace new technologies. J. Serv. Res. 2000, 2, 307–320. [Google Scholar] [CrossRef]
- Tornatzky, L.G.; Fleischer, M.; Chakrabarti, A.K. The Processes of Technological Innovation; Lexington Books: Lexington, KY, USA, 1990. [Google Scholar]
- Iacovou, C.L.; Benbasat, I.; Dexter, A.S. Electronic data interchange and small organizations: Adoption and impact of technology. MIS Q. 1995, 19, 465–485. [Google Scholar] [CrossRef] [Green Version]
- Das, T.K.; Teng, B.S. The risk-based view of trust: A conceptual framework. J. Bus. Psychol. 2004, 19, 85–116. [Google Scholar] [CrossRef]
- Koo, S.H.; Shin, M.S. The study on the impact of the task-technology fit model and organizational characteristics of the mobile office system on the job performance. J. Korea Acad. Ind. Coop. Soc. 2013, 14, 644–654. [Google Scholar]
- Son, H.T. A Study on the Performance of Public Official’s Decision Making Using GeoPros: Focused on Perceived Task-Technology Fit. Ph.D. Thesis, Soongsil University, Seoul, Korea, 2019. [Google Scholar]
- Lin, J.S.C.; Hsieh, P.L. The role of technology readiness in customers’ perception and adoption of self-service technologies. Int. J. Serv. Ind. Manag. 2006, 17, 497–517. [Google Scholar] [CrossRef]
- Yang, Z.; Sun, J.; Zhang, Y.; Wang, Y. Understanding SaaS adoption from the perspective of organizational users: A Tripod Readiness Model. Comput. Hum. Behav. 2015, 45, 254–264. [Google Scholar] [CrossRef]
- Ahmadi, H.; Nilashi, M.; Shahmoradi, L.; Ibrahim, O. Hospital information system adoption: Expert perspectives on an adoption framework for Malaysian public hospitals. Comput. Hum. Behav. 2017, 67, 161–189. [Google Scholar] [CrossRef]
- Lee, S.M.; Lee, Y.G.; Lee, K.Y. The impacts of SCM partnership on the corporate performance. J. Korean Prod. Oper. Manag. Soc. 2007, 18, 105–133. [Google Scholar]
- Lee, S.J.; Han, P.K.; Kang, B.G. The effect of collaboration and organization’s performance depending on the partnership by information technology using level: Key subject is moderating variable of information technology using level. Inf. Syst. Rev. 2009, 11, 67–90. [Google Scholar]
- Maduku, D.K.; Mpinganjira, M.; Duh, H. Understanding mobile marketing adoption intention by South African SMEs: A multi-perspective framework. Int. J. Inf. Manag. 2016, 36, 711–723. [Google Scholar] [CrossRef]
- Venkatesh, V.; Bala, H. Adoption and impacts of interorganizational business process standards: Role of partnering synergy. Inf. Syst. Res. 2012, 23, 1131–1157. [Google Scholar] [CrossRef] [Green Version]
- Venkatesh, V.; Thong, J.Y.L.; Xu, X. Consumer acceptance and use of information technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Q. 2012, 36, 157–178. [Google Scholar] [CrossRef] [Green Version]
- Zhou, T.; Lu, Y.; Wang, B. Integrating TTF and UTAUT to explain mobile banking user adoption. Comput. Hum. Behav. 2010, 26, 760–767. [Google Scholar] [CrossRef]
- Hoogland, J.J.; Boomsma, A. Robustness studies in covariance structure modeling: An overview and a meta-analysis. Sociol. Methods Res. 1998, 26, 329–367. [Google Scholar] [CrossRef]
- Nunnally, J.C. Psychometric Theory; McGraw-Hill: New York, NY, USA, 1967. [Google Scholar]
- Yoon, C.; Kim, S. A tutorial on PLS structural equating modeling using R: (Centering on) Exemplified research model and data. Inf. Syst. Rev. 2014, 16, 89–112. [Google Scholar]
- Hair, J.F.; Ringle, C.M.; Sarstedt, M. PLS-SEM: Indeed a silver bullet. J. Mark. Theory Pract. 2011, 19, 139–152. [Google Scholar] [CrossRef]
- Cortina, J.M. What is coefficient alpha? An examination of theory and applications. J. Appl. Psychol. 1993, 78, 98–104. [Google Scholar] [CrossRef]
- Fornell, C.; Larcker, D.F. Structural equation models with unobservable variables and measurement error: Algebra and statistics. J. Mark. Res. 1981, 18, 382–388. [Google Scholar] [CrossRef]
- Chin, W.W. The partial least squares approach to structural equation modeling. In Modern Methods for Business Research; Marcoulides, G.A., Ed.; Lawrence Erlbaum Associates: Mahwah, NJ, USA, 1998; pp. 295–336. [Google Scholar]
| Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).