A Study of Factors Affecting Intention to Adopt a Cloud-Based Digital Signature Service
Abstract
:1. Introduction
2. Literature Review
2.1. Cloud Computing Service
2.2. Cloud Digital Signature Service
2.3. Technology–Organization–Environment Framework
2.4. UTAUT Model
2.5. Task−Technology Fit Model
2.6. Service Readiness
3. Research Model and Hypothesis Testing
3.1. Research Model
3.2. Hypothesis Development
3.2.1. Technical Characteristics and Suitability
3.2.2. Organizational Characteristics and Suitability
3.2.3. Organizational Characteristics and Service Readiness
3.2.4. Environmental Characteristics and Suitability
3.2.5. Environmental Characteristics and Service Readiness
3.2.6. Economic Characteristics and Service Readiness
3.2.7. Suitability and Intention to Adopt
3.2.8. Service Readiness and Intention to Adopt
3.3. Variable Operational Definition and Questionnaire
4. Research Method and Results
4.1. Sample Design and Data Collection
4.2. Factor Analysis
4.3. Reliability and Validity Analysis
4.3.1. Reliability Analysis
4.3.2. Validity Analysis
4.4. Statistical Hypothesis Testing
5. Discussion and Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts 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]
Variable | Operational Definition and Questionnaire | Related Studies |
---|---|---|
Simplicity (SM) | Degree of ease and simplicity of cloud-based digital signature service | [30] |
| ||
Relative advantage (RA) | Degree of perception that cloud-based digital signatures are better than traditional digital signatures | [4,7,30] |
| ||
Compatibility (COM) | Degree of compatibility between cloud-based digital signature service and company infrastructure | [4,31] |
| ||
Perceived security (PS) | Degree of belief that the process of using the cloud-based digital signature service is safely protected | [4,7,31] |
| ||
Collaboration (COL) | Degree of collaboration between departments, such as exchange activities and mutual support to achieve common goals within the organization | [22,32,33] |
| ||
Management support (MS) | Degree of management support for information system introduction and cloud-based digital signature introduction and use | [22,34] |
| ||
Innovation (INO) | Degree of organization’s willingness to actively pursue and leverage innovation | [22,35] |
| ||
Pressure (PRES) | Degree of competitor influence in introducing cloud-based digital signature services | [7,24,30] |
| ||
Government support (GS) | Degree of governmental financial and legal assistance to support the adoption of cloud-based digital signature services | [7,24] |
| ||
Facilitation conditions (FC) | Degree of support associated with the organization’s infrastructure to introduce cloud-based digital signature services. | [13,36] |
| ||
Expected profitability (EP) | Degree of investment, maintenance, and other costs involved in the introduction of cloud-based electronic signature services | [4,25] |
| ||
Uncertainty (UNC) | Degree of unpredictability due to the introduction of cloud-based digital signature service | [7,26] |
| ||
Suitability (SUIT) | Degree of suitability of cloud-based digital signature services and tasks that organization members feel to do their jobs | [7,37] |
| ||
Service readiness (SR) | Degree of company preparation for the introduction of cloud-based electronic signatures perceptual to the members of the organization, such as budget, policy, and technical resources | [8] |
| ||
Intention to adopt a cloud-based digital signature service (IA) | Degree of thought or plan to introduce cloud-based digital signature service | [31] |
|
Construct | Frequency | Percentage (%) | |
---|---|---|---|
Gender | Male | 134 | 47.3 |
Female | 149 | 52.7 | |
Age | 20−29 | 49 | 17.3 |
30−39 | 137 | 48.4 | |
40−49 | 73 | 25.8 | |
50−59 | 15 | 5.3 | |
60+ | 9 | 3.2 | |
Industry field | Financial | 7 | 2.5 |
Public | 50 | 17.7 | |
IT | 41 | 14.5 | |
Manufacturing | 74 | 26.1 | |
Distribution | 24 | 8.5 | |
Service | 55 | 19.4 | |
Machinery | 5 | 1.8 | |
Electronics | 6 | 2.1 | |
Etc. | 21 | 7.4 | |
Position | Staff | 188 | 66.4 |
Team leader | 68 | 24.0 | |
Department head | 22 | 7.8 | |
Executives | 5 | 1.8 | |
Corporation size (staff) | 2 or more and less than 100 | 112 | 39.6 |
100 or more and less than 500 | 89 | 31.4 | |
500 or more and less than 1000 | 41 | 14.5 | |
More than 1000 | 41 | 14.5 | |
Cloud use or not | Use | 187 | 66.1 |
Not | 96 | 33.9 | |
Total | 283 | 100 |
SIM | RA | COM | PS | COL | MS | INO | PRES | GS | FC | EP | UNC | SUIT | SR | IA | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
SIM1 | 0.911 | 0.691 | 0.583 | 0.447 | 0.461 | 0.432 | 0.445 | 0.333 | 0.320 | 0.390 | 0.517 | 0.115 | 0.544 | 0.345 | 0.320 |
SIM2 | 0.833 | 0.531 | 0.409 | 0.334 | 0.371 | 0.217 | 0.170 | 0.165 | 0.254 | 0.212 | 0.298 | 0.050 | 0.364 | 0.178 | 0.173 |
SIM3 | 0.879 | 0.588 | 0.511 | 0.425 | 0.382 | 0.303 | 0.341 | 0.194 | 0.255 | 0.289 | 0.392 | 0.053 | 0.388 | 0.248 | 0.200 |
RA1 | 0.684 | 0.829 | 0.605 | 0.459 | 0.411 | 0.439 | 0.400 | 0.350 | 0.271 | 0.367 | 0.491 | 0.089 | 0.495 | 0.337 | 0.340 |
RA3 | 0.577 | 0.863 | 0.629 | 0.393 | 0.388 | 0.477 | 0.384 | 0.385 | 0.293 | 0.398 | 0.445 | 0.046 | 0.527 | 0.373 | 0.392 |
RA4 | 0.615 | 0.905 | 0.652 | 0.447 | 0.450 | 0.472 | 0.402 | 0.407 | 0.299 | 0.441 | 0.475 | 0.110 | 0.573 | 0.413 | 0.392 |
RA5 | 0.564 | 0.867 | 0.653 | 0.397 | 0.468 | 0.461 | 0.329 | 0.394 | 0.322 | 0.418 | 0.426 | 0.040 | 0.562 | 0.385 | 0.400 |
COM1 | 0.452 | 0.575 | 0.755 | 0.335 | 0.354 | 0.328 | 0.290 | 0.221 | 0.157 | 0.271 | 0.402 | 0.177 | 0.403 | 0.309 | 0.225 |
COM2 | 0.454 | 0.569 | 0.804 | 0.368 | 0.417 | 0.427 | 0.330 | 0.317 | 0.262 | 0.348 | 0.398 | 0.138 | 0.431 | 0.349 | 0.316 |
COM4 | 0.492 | 0.635 | 0.864 | 0.410 | 0.464 | 0.592 | 0.491 | 0.451 | 0.419 | 0.534 | 0.512 | 0.136 | 0.553 | 0.548 | 0.518 |
COM5 | 0.520 | 0.623 | 0.850 | 0.472 | 0.377 | 0.453 | 0.375 | 0.378 | 0.327 | 0.429 | 0.455 | 0.064 | 0.523 | 0.391 | 0.392 |
PS1 | 0.429 | 0.457 | 0.433 | 0.915 | 0.369 | 0.417 | 0.393 | 0.298 | 0.463 | 0.323 | 0.402 | 0.013 | 0.399 | 0.368 | 0.319 |
PS2 | 0.450 | 0.443 | 0.440 | 0.928 | 0.385 | 0.429 | 0.403 | 0.287 | 0.456 | 0.377 | 0.380 | −0.031 | 0.411 | 0.391 | 0.307 |
PS3 | 0.401 | 0.439 | 0.434 | 0.879 | 0.408 | 0.452 | 0.392 | 0.310 | 0.443 | 0.407 | 0.409 | 0.005 | 0.399 | 0.407 | 0.321 |
PS4 | 0.407 | 0.427 | 0.455 | 0.895 | 0.381 | 0.402 | 0.343 | 0.271 | 0.483 | 0.361 | 0.421 | 0.090 | 0.421 | 0.349 | 0.309 |
COL1 | 0.476 | 0.506 | 0.477 | 0.390 | 0.835 | 0.472 | 0.537 | 0.287 | 0.252 | 0.376 | 0.358 | 0.050 | 0.463 | 0.424 | 0.269 |
COL2 | 0.434 | 0.498 | 0.459 | 0.374 | 0.874 | 0.499 | 0.566 | 0.321 | 0.324 | 0.404 | 0.382 | 0.041 | 0.520 | 0.492 | 0.311 |
COL3 | 0.399 | 0.454 | 0.473 | 0.354 | 0.896 | 0.548 | 0.539 | 0.381 | 0.372 | 0.469 | 0.401 | 0.126 | 0.512 | 0.533 | 0.356 |
COL4 | 0.385 | 0.367 | 0.410 | 0.352 | 0.868 | 0.525 | 0.595 | 0.356 | 0.400 | 0.472 | 0.413 | 0.088 | 0.479 | 0.539 | 0.396 |
COL5 | 0.351 | 0.341 | 0.336 | 0.387 | 0.866 | 0.527 | 0.572 | 0.355 | 0.367 | 0.453 | 0.369 | 0.035 | 0.501 | 0.513 | 0.389 |
MS1 | 0.415 | 0.515 | 0.516 | 0.420 | 0.600 | 0.810 | 0.698 | 0.549 | 0.390 | 0.581 | 0.544 | 0.142 | 0.546 | 0.615 | 0.484 |
MS2 | 0.321 | 0.482 | 0.516 | 0.400 | 0.537 | 0.931 | 0.659 | 0.642 | 0.536 | 0.709 | 0.533 | 0.108 | 0.560 | 0.760 | 0.714 |
MS3 | 0.315 | 0.447 | 0.499 | 0.448 | 0.496 | 0.933 | 0.618 | 0.678 | 0.562 | 0.727 | 0.500 | 0.132 | 0.559 | 0.743 | 0.734 |
MS4 | 0.337 | 0.491 | 0.510 | 0.434 | 0.523 | 0.935 | 0.646 | 0.705 | 0.580 | 0.749 | 0.571 | 0.114 | 0.578 | 0.746 | 0.741 |
INO1 | 0.387 | 0.415 | 0.412 | 0.398 | 0.606 | 0.670 | 0.938 | 0.472 | 0.448 | 0.592 | 0.477 | 0.053 | 0.523 | 0.612 | 0.481 |
INO2 | 0.345 | 0.407 | 0.464 | 0.401 | 0.614 | 0.692 | 0.947 | 0.534 | 0.474 | 0.623 | 0.557 | 0.041 | 0.547 | 0.679 | 0.530 |
PRES1 | 0.279 | 0.454 | 0.402 | 0.247 | 0.405 | 0.613 | 0.487 | 0.768 | 0.540 | 0.659 | 0.542 | 0.066 | 0.631 | 0.524 | 0.536 |
PRES2 | 0.189 | 0.245 | 0.251 | 0.204 | 0.243 | 0.514 | 0.368 | 0.794 | 0.558 | 0.607 | 0.409 | 0.082 | 0.403 | 0.514 | 0.539 |
PRES3 | 0.188 | 0.386 | 0.387 | 0.275 | 0.318 | 0.639 | 0.446 | 0.818 | 0.541 | 0.598 | 0.478 | 0.065 | 0.434 | 0.606 | 0.667 |
PRES4 | 0.146 | 0.216 | 0.224 | 0.200 | 0.150 | 0.417 | 0.270 | 0.774 | 0.545 | 0.496 | 0.413 | 0.082 | 0.377 | 0.361 | 0.414 |
PRES5 | 0.264 | 0.379 | 0.374 | 0.321 | 0.362 | 0.561 | 0.468 | 0.761 | 0.582 | 0.538 | 0.497 | 0.080 | 0.479 | 0.499 | 0.477 |
GS1 | 0.250 | 0.286 | 0.327 | 0.366 | 0.332 | 0.542 | 0.471 | 0.700 | 0.870 | 0.670 | 0.477 | 0.021 | 0.542 | 0.527 | 0.610 |
GS2 | 0.339 | 0.337 | 0.347 | 0.497 | 0.370 | 0.486 | 0.450 | 0.606 | 0.896 | 0.606 | 0.533 | 0.003 | 0.579 | 0.506 | 0.482 |
GS3 | 0.262 | 0.286 | 0.313 | 0.488 | 0.354 | 0.500 | 0.379 | 0.569 | 0.887 | 0.587 | 0.471 | 0.000 | 0.545 | 0.541 | 0.497 |
FC1 | 0.287 | 0.428 | 0.447 | 0.327 | 0.443 | 0.755 | 0.604 | 0.728 | 0.618 | 0.893 | 0.541 | 0.046 | 0.622 | 0.751 | 0.724 |
FC2 | 0.274 | 0.412 | 0.453 | 0.344 | 0.445 | 0.731 | 0.583 | 0.702 | 0.650 | 0.917 | 0.536 | 0.063 | 0.671 | 0.756 | 0.685 |
FC3 | 0.323 | 0.403 | 0.434 | 0.328 | 0.475 | 0.633 | 0.570 | 0.600 | 0.565 | 0.886 | 0.442 | 0.000 | 0.655 | 0.700 | 0.587 |
FC4 | 0.364 | 0.397 | 0.404 | 0.432 | 0.382 | 0.538 | 0.481 | 0.569 | 0.615 | 0.780 | 0.528 | 0.013 | 0.614 | 0.540 | 0.486 |
EP1 | 0.359 | 0.347 | 0.420 | 0.320 | 0.268 | 0.443 | 0.417 | 0.490 | 0.435 | 0.454 | 0.814 | 0.133 | 0.423 | 0.486 | 0.390 |
EP2 | 0.428 | 0.499 | 0.516 | 0.433 | 0.424 | 0.544 | 0.500 | 0.551 | 0.527 | 0.553 | 0.884 | 0.120 | 0.593 | 0.547 | 0.473 |
EP3 | 0.416 | 0.480 | 0.432 | 0.364 | 0.421 | 0.504 | 0.467 | 0.482 | 0.439 | 0.464 | 0.820 | 0.128 | 0.565 | 0.486 | 0.414 |
UNC1 | 0.100 | 0.109 | 0.164 | 0.047 | 0.075 | 0.151 | 0.050 | 0.112 | 0.043 | 0.051 | 0.164 | 0.965 | 0.101 | 0.130 | 0.026 |
UNC2 | 0.060 | 0.027 | 0.113 | −0.023 | 0.075 | 0.094 | 0.042 | 0.052 | −0.046 | 0.009 | 0.107 | 0.910 | 0.027 | 0.083 | −0.003 |
SUIT1 | 0.369 | 0.467 | 0.465 | 0.400 | 0.488 | 0.549 | 0.525 | 0.527 | 0.600 | 0.640 | 0.534 | 0.033 | 0.830 | 0.556 | 0.472 |
SUIT2 | 0.485 | 0.601 | 0.574 | 0.410 | 0.541 | 0.574 | 0.533 | 0.588 | 0.532 | 0.684 | 0.576 | 0.087 | 0.892 | 0.536 | 0.476 |
SUIT3 | 0.460 | 0.569 | 0.536 | 0.365 | 0.527 | 0.524 | 0.502 | 0.518 | 0.554 | 0.637 | 0.562 | 0.048 | 0.905 | 0.516 | 0.435 |
SUIT4 | 0.439 | 0.547 | 0.519 | 0.375 | 0.516 | 0.553 | 0.501 | 0.562 | 0.579 | 0.650 | 0.534 | 0.070 | 0.912 | 0.546 | 0.485 |
SUIT5 | 0.447 | 0.562 | 0.527 | 0.414 | 0.500 | 0.572 | 0.492 | 0.546 | 0.521 | 0.669 | 0.569 | 0.067 | 0.893 | 0.556 | 0.480 |
SUIT6 | 0.486 | 0.535 | 0.488 | 0.413 | 0.429 | 0.492 | 0.436 | 0.454 | 0.526 | 0.588 | 0.542 | 0.097 | 0.835 | 0.486 | 0.426 |
SR1 | 0.233 | 0.406 | 0.450 | 0.348 | 0.518 | 0.738 | 0.632 | 0.627 | 0.530 | 0.727 | 0.559 | 0.083 | 0.554 | 0.918 | 0.696 |
SR2 | 0.215 | 0.362 | 0.429 | 0.335 | 0.504 | 0.710 | 0.607 | 0.616 | 0.508 | 0.713 | 0.555 | 0.094 | 0.533 | 0.904 | 0.639 |
SR3 | 0.332 | 0.420 | 0.475 | 0.425 | 0.572 | 0.679 | 0.636 | 0.497 | 0.495 | 0.665 | 0.551 | 0.125 | 0.568 | 0.872 | 0.574 |
SR4 | 0.313 | 0.366 | 0.436 | 0.406 | 0.529 | 0.700 | 0.637 | 0.557 | 0.525 | 0.727 | 0.512 | 0.115 | 0.515 | 0.902 | 0.676 |
SR5 | 0.292 | 0.406 | 0.466 | 0.370 | 0.478 | 0.744 | 0.573 | 0.628 | 0.603 | 0.736 | 0.539 | 0.114 | 0.558 | 0.899 | 0.772 |
IA1 | 0.226 | 0.382 | 0.375 | 0.288 | 0.303 | 0.662 | 0.438 | 0.631 | 0.521 | 0.604 | 0.435 | 0.058 | 0.391 | 0.678 | 0.812 |
IA4 | 0.230 | 0.389 | 0.413 | 0.303 | 0.375 | 0.687 | 0.514 | 0.625 | 0.534 | 0.669 | 0.450 | 0.010 | 0.486 | 0.682 | 0.924 |
IA5 | 0.266 | 0.386 | 0.386 | 0.329 | 0.368 | 0.671 | 0.481 | 0.600 | 0.552 | 0.649 | 0.452 | −0.012 | 0.492 | 0.658 | 0.936 |
IA6 | 0.279 | 0.431 | 0.455 | 0.332 | 0.389 | 0.670 | 0.503 | 0.609 | 0.551 | 0.668 | 0.496 | 0.004 | 0.527 | 0.683 | 0.933 |
MVs | Cronbach’s α | DG’s Rho | Eigenvalue | |
---|---|---|---|---|
SIM | 3 | 0.850 | 0.909 | 2.309 |
RA | 4 | 0.889 | 0.923 | 3.002 |
COM | 4 | 0.838 | 0.892 | 2.696 |
PS | 4 | 0.926 | 0.947 | 3.274 |
COL | 5 | 0.918 | 0.939 | 3.767 |
MS | 4 | 0.924 | 0.947 | 3.267 |
INO | 2 | 0.874 | 0.941 | 1.777 |
PRES | 5 | 0.844 | 0.889 | 3.081 |
GS | 3 | 0.861 | 0.915 | 2.347 |
FC | 4 | 0.892 | 0.926 | 3.031 |
EP | 3 | 0.790 | 0.878 | 2.116 |
UNC | 2 | 0.870 | 0.939 | 1.770 |
SUIT | 6 | 0.940 | 0.953 | 4.629 |
SR | 5 | 0.941 | 0.955 | 4.042 |
IA | 4 | 0.923 | 0.946 | 3.258 |
SIM | RA | COM | PS | COL | MS | INO | PRES | GS | FC | EP | UNC | SUIT | SR | IA | AVE | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
SIM | 0.875 | 0.765 | ||||||||||||||
RA | 0.702 | 0.866 | 0.750 | |||||||||||||
COM | 0.585 | 0.733 | 0.819 | 0.671 | ||||||||||||
PS | 0.467 | 0.488 | 0.487 | 0.905 | 0.818 | |||||||||||
COL | 0.469 | 0.496 | 0.495 | 0.427 | 0.868 | 0.753 | ||||||||||
MS | 0.381 | 0.533 | 0.565 | 0.47 | 0.593 | 0.904 | 0.817 | |||||||||
INO | 0.388 | 0.436 | 0.467 | 0.424 | 0.647 | 0.722 | 0.942 | 0.888 | ||||||||
PRES | 0.278 | 0.442 | 0.431 | 0.323 | 0.392 | 0.714 | 0.533 | 0.783 | 0.613 | |||||||
GS | 0.321 | 0.343 | 0.374 | 0.509 | 0.398 | 0.576 | 0.49 | 0.706 | 0.884 | 0.782 | ||||||
FC | 0.354 | 0.47 | 0.501 | 0.405 | 0.502 | 0.769 | 0.645 | 0.749 | 0.702 | 0.87 | 0.758 | |||||
EP | 0.478 | 0.528 | 0.545 | 0.445 | 0.443 | 0.592 | 0.55 | 0.604 | 0.558 | 0.586 | 0.84 | 0.705 | ||||
UNC | 0.373 | 0.461 | 0.484 | 0.377 | 0.48 | 0.555 | 0.503 | 0.518 | 0.559 | 0.606 | 0.546 | 0.938 | 0.880 | |||
SUIT | 0.502 | 0.635 | 0.611 | 0.458 | 0.599 | 0.682 | 0.613 | 0.649 | 0.639 | 0.781 | 0.658 | 0.745 | 0.878 | 0.771 | ||
SR | 0.319 | 0.446 | 0.505 | 0.422 | 0.554 | 0.805 | 0.669 | 0.673 | 0.611 | 0.796 | 0.599 | 0.535 | 0.684 | 0.899 | 0.808 | |
IA | 0.282 | 0.432 | 0.461 | 0.347 | 0.397 | 0.716 | 0.526 | 0.652 | 0.578 | 0.802 | 0.502 | 0.449 | 0.593 | 0.739 | 0.902 | 0.814 |
Hypothesis | Path | Estimate | Std. Error | t-Value | p-Value | Result |
---|---|---|---|---|---|---|
H1 | SIM -> SUIT | 0.208 | 0.046 | 2.352 | 0.019 | Accept |
H2 | RA -> SUIT | 0.247 | 0.060 | 4.090 | 0.000 | Accept |
H3 | COM -> SUIT | 0.188 | 0.054 | 1.962 | 0.050 | Accept |
H4 | PS -> SUIT | −0.033 | 0.045 | −0.736 | 0.791 | Reject |
H5 | COL -> SUIT | 0.156 | 0.048 | 3.210 | 0.001 | Accept |
H6 | MS -> SUIT | 0.123 | 0.067 | 1.980 | 0.048 | Accept |
H7 | INO -> SUIT | 0.027 | 0.054 | 0.508 | 0.612 | Reject |
H8 | COL -> SR | 0.190 | 0.042 | 2.100 | 0.036 | Accept |
H9 | MS -> SR | 0.316 | 0.060 | 5.210 | 0.000 | Accept |
H10 | INO -> SR | 0.094 | 0.051 | 1.84 | 0.066 | Reject |
H11 | PRES -> SUIT | 0.009 | 0.061 | 0.154 | 0.878 | Reject |
H12 | GS -> SUIT | 0.209 | 0.057 | 3.640 | 0.000 | Accept |
H13 | FC -> SUIT | 0.417 | 0.064 | 6.440 | 0.000 | Accept |
H14 | PRES -> SR | −0.061 | 0.055 | −1.090 | 0.277 | Reject |
H15 | GS -> SR | 0.035 | 0.048 | 0.734 | 0.464 | Reject |
H16 | FC -> SR | 0.407 | 0.059 | 6.810 | 0.000 | Accept |
H17 | EP -> SR | 0.192 | 0.043 | 2.100 | 0.036 | Accept |
H18 | UNC -> SR | −0.046 | 0.032 | −1.440 | 0.150 | Reject |
H19 | SUIT -> IA | 0.125 | 0.049 | 2.510 | 0.012 | Accept |
H20 | SR -> IA | 0.666 | 0.049 | 13.400 | 0.000 | Accept |
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/).
Share and Cite
Chong, K.W.; Kim, Y.S.; Choi, J. A Study of Factors Affecting Intention to Adopt a Cloud-Based Digital Signature Service. Information 2021, 12, 60. https://doi.org/10.3390/info12020060
Chong KW, Kim YS, Choi J. A Study of Factors Affecting Intention to Adopt a Cloud-Based Digital Signature Service. Information. 2021; 12(2):60. https://doi.org/10.3390/info12020060
Chicago/Turabian StyleChong, Kyung Won, Yong Seok Kim, and Jeongil Choi. 2021. "A Study of Factors Affecting Intention to Adopt a Cloud-Based Digital Signature Service" Information 12, no. 2: 60. https://doi.org/10.3390/info12020060
APA StyleChong, K. W., Kim, Y. S., & Choi, J. (2021). A Study of Factors Affecting Intention to Adopt a Cloud-Based Digital Signature Service. Information, 12(2), 60. https://doi.org/10.3390/info12020060