Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
ATZ-Fachkongress

Chassis.tech plus 2024


4 Kongresse in einer Veranstaltung

Treffen Sie in München die Fachleute von Chassis, Lenkung, Bremsen sowie Reifen/Räder.
Erweiterte Suche
Anmelden
nach oben
Wireless Personal Communications
Erschienen in: Wireless Personal Communications 4/2013

01.12.2013

Technology Acceptance Model for the Use of Tablet PCs

verfasst von: Eunil Park, Angel P. del Pobil

Erschienen in: Wireless Personal Communications | Ausgabe 4/2013

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Tablet personal computers (tablet PCs) are popular electronic devices worldwide. They influence many aspects of our social lives. Compared with laptop computers, tablet PCs feature characteristics including enhanced portability and display quality. The purposes of this study were to examine users’ attitudes toward tablet personal computers and identify the effects of external factors. This study extended the technology acceptance model and used perceived mobility and viewing experience as the external variables in the proposed model. This study used a web-based survey of 511 participants and found that perceived usefulness and perceived ease of use were key determinants of attitude toward tablet personal computers. Also, the perceived ease of use and usefulness of tablet PCs were significantly enhanced by perceived mobility and viewing experience. In addition, all traditional relationships from the origin technology acceptance model were supported. Lastly, both implications of the study and areas of future research are discussed.
Vorheriger Artikel A Novel Security Scheme for the Smart Grid and SCADA Networks
Nächster Artikel An Adaptable Job Submission System Based on Moderate Price-Adjusting Policy in Market-Based Grids

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Literatur
1.
Sears, A., & Arora, R. (2002). Data entry for mobile devices: An empirical comparison of novice performance with Jot and Graffiti. Interacting with Computers, 14(5), 413–433.CrossRef
2.
Cooper, G., Green, N., Murtagh, G. M., & Harper, R. (2003). Mobile society? technology, distance, and presence. In S. Woolgar (Ed.), Virtual society? technology, cyberbole, reality (pp. 286–301). London: Oxford University Press.
3.
4.
Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Doctoral dissertation, MIT Sloan School of Management, Cambridge.
5.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intentions and behavior: An introduction to theory and research. Boston, MA: Addison-Wesley.
6.
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. New Jersey: Prentice-Hall.
7.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.CrossRef
8.
Davis, F. D. (1993). User acceptance of information technology: System characteristics, user perceptions and behavioral impacts. International Journal of Man-machine Studies, 38(3), 475–487.CrossRef
9.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology a comparison of two theoretical models. Management Science, 35(8), 928–1003.CrossRef
10.
Mathieson, K. (1991). Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3), 173–191.CrossRef
11.
Teo, T. (2010). Establishing gender structural invariance of technology acceptance model (TAM). The Asia-Pacific Education researcher, 19(2), 311–320.CrossRef
12.
Vale, C. M., & Leder, G. C. (2004). Students’ views of computer-based mathematics in the middle years: Does gender make a difference? Education Studies in Mathematics, 56(3), 287–312.CrossRef
13.
Venkatesh, V., Speier, C., & Morris, M. G. (2002). User acceptance enablers in individual decision making about technology: Toward an integrated model. Decision Sciences, 33(2), 297–316.CrossRef
14.
Go, K., & Tsurumi, L. (2010). Arranging touch screen software keyboard split-keys based on contact surface. In E. Mynatt, D. Schoner, G. Fitzpatrick, S. Hudson, K. Edwards, & T. Rodden (Eds.), Proceedings of the 28th international conference on human factors in computing systems (pp. 3805–3810). New York: ACM.
15.
Warkentin, M., Bekkering, E., Schmidt, M., & Johnston, A. (2004). Proposed study of end-user perceptions regarding tablet PCs. In M. Khosrow-Pour, J. Travers, A. Appicello, & M. Rossi (Eds.), Proceedings of the information resources management conference 2004 (pp. 430–431). London: Idea Group Publishing.
16.
Levack, K. (2003). Take one tablet and email me in the morning: Tablet PCs and Enewspapers, Econtent Magazine, pp. 8–9.
17.
18.
Pittman, J. A. (2007). Handwriting recognition: Tablet PC text input. Computer, 40(9), 49–54.CrossRef
19.
Schroeder, D. (2004). Tablet PCs and collaboration software improve classroom engagement at Cabrillo High school. Technological Horizons in Education Journal, 32(4), 49–50.
20.
Sharples, M., & Beale, R. (2003). A technical review of mobile computational devices. Journal of Computer Assisted Learning, 19(3), 392–395.
21.
Weitz, R. R., Wachsmuth, B., & Mirliss, D. (2006). The tablet PC for faculty: A pilot project. Educational Technology & Society, 9(2), 68–83.
22.
Rogers, E. M. (1995). Diffusion of innovations (4th ed.). New York: The Free Press.
23.
Ng, J. K. Y. (2012). Ubiquitous healthcare: Healthcare systems and applications enabled by mobile and wireless technologies. Journal of Convergence, 3(2), 31–36.
24.
Pyshkin, E., & Kuznetsov, A. (2012). Approaches for web search user interface—how to improve the search quality for various types of information. Journal of Convergence, 1(1), 1–8.
25.
Brown, I., & Licker, P. (2003). Exploring differences in internet adoption and usage between historically advantaged and disadvantaged groups in South Africa. Journal of Global Information Technology Management, 6(4), 6–26.
26.
Bruner, G. C., & Kumar, A. (2005). Explaining consumer acceptance of handheld internet devices. Journal of Business Research, 58(5), 553–558.CrossRef
27.
Hu, J., Chau, Y. K., Sheng, R. L., & Tam, K. Y. (1999). Examining technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91–112.
28.
Igbaria, M., & Iivari, J. (1995). The effects of self-efficacy on computer usage. International Journal of Management Science, 23(6), 587–605.
29.
Park, E., & del Pobil, A. P. (2013). Extending the technology acceptance model in remote pointing technology: Identifying the role of perceived mobility and control. Sensor Review, 33(1), 40–47.CrossRef
30.
Hill, T. R., & Roldan, M. (2005). Toward third generation threaded discussions for mobile learning: Opportunities and challenges for ubiquitous collaborative environments. Information Systems Frontiers, 7(1), 55–70.CrossRef
31.
Ting, R. Y. (2005). Mobile learning: Current trend and future challenges. In Proceedings of the 5th IEEE international conference on advanced learning technologies (pp. 603–607), New York: IEEE.
32.
Huang, J., Lin, Y., & Chuang, S. (2007). Elucidating user behavior of mobile learning: A perspective of the extended technology acceptance model. The Electronic Library, 25(5), 585–598.CrossRef
33.
Kim, K. J., Sundar, S. S., & Park, E. (2011). The effects of screen-size and communication modality on psychology of mobile device users. In D. Tan, B. Begole, & W. A. Kellogg (Eds.), Proceedings of the 2011 annual conference on human factors in computing systems (pp. 1207–1212). New York: ACM.
34.
Kim, K. J., & Sundar, S. S. (2011). Does panel type matter for LCD monitors? A study examining the effects of S-IPS, S-PVA, and TN panels in video gaming and movie viewing. Lecture Notes in Computer Science, 6947, 281–288.CrossRef
35.
Park. E., & Kim, K. J. (2013). User acceptance of long-term evolution (LTE) services: An application of extended technology acceptance model. Program: electronic library and information systems, 47(2), 188–205.
36.
Saba, T. (2012). Implications of E-learning systems and self-efficiency on students outcomes: a model approach. Human-centric Computing and Information Sciences, 2(6), 1–11.
37.
Bhattacharya, A., Wu, W., & Yang, Z. (2012). Quality of experience evaluation of voice communication: An affect-based approach. Human-centric Computing and Information Science, 2(7), 1–18.
38.
Cronbach, L. (1971). Test validation. In R. L. Thorndike (Ed.), Educational measurement. Washington, D. C: American Council on Education.
39.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 8(1), 39–50.CrossRef
40.
Qi, J., Li, L., Li, Y., & Shu, H. (2009). An extension of technology acceptance model: Analysis of the adoption of mobile data services in China. Systems Research and Behavioral Science, 26(3), 391–407.CrossRef
41.
Kim, S., & Garrison, G. (2009). Investigating mobile wireless technology adoption: An extension of the technology acceptance model. Information Systems Frontiers, 11(3), 323–333.CrossRef
Metadaten
Titel
Technology Acceptance Model for the Use of Tablet PCs
verfasst von
Eunil Park
Angel P. del Pobil
Publikationsdatum
01.12.2013
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 4/2013
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-013-1266-x

Weitere Artikel der Ausgabe 4/2013

Wireless Personal Communications 4/2013 Zur Ausgabe

OriginalPaper

Contents Recommendation Method Using Social Network Analysis

OriginalPaper

An Adaptable Job Submission System Based on Moderate Price-Adjusting Policy in Market-Based Grids

OriginalPaper

ODSA: Chord-Based Object Discovery Service Architecture for the Internet of Things

EditorialNotes

Advanced Information Technologies in Future Computing Environments

OriginalPaper

A Study on Project Selection Framework for Future ICT Technologies

OriginalPaper

An Efficient Multi-Path Self-Organizing Strategy in Internet of Things

Neuer Inhalt

    Bildnachweise