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ASAYİŞ HİZMETLERİNDE TEKNOLOJİ KABUL MODELİ: GEÇERLİK VE GÜVENİRLİK ÇALIŞMASI

Year 2021, Volume: 10 Issue: 2, 339 - 364, 24.11.2021
https://doi.org/10.28956/gbd.1028635

Abstract

Bu çalışmada, asayiş hizmetlerinde görev yapan personelin BİT kabul düzeylerini betimleyen bir teknoloji kabul modeli önerilmiştir. Bu amaç doğrultusunda 371 katılımcının yer aldığı çalışmanın verileri, t-testi, ANOVA ve yapısal eşitlik modellemesinden yararlanılarak analiz edilmiştir. Analiz sonucunda, sekiz faktörlü bir teknoloji kabul yapısı ortaya konmuştur. Geçerlik ve güvenirlik ölçütleri sağlanan modelin faktörleri arasında anlamlı ilişkiler bulunmuştur. Faktörler arası ilişkileri tespit etmek için yapısal eşitlik modellemesi analizi yapılmıştır. Modelin endojen değişkenleri (algılanan kullanım kolaylığı, algılanan fayda ve davranışsal niyet) hem kendi aralarında hem de modelin eksojen bağımsız değişkenleri ile (teknoloji öz-yeterliği, algılanan zevk, öznel norm ve kaygı) anlamlı ilişkilere sahiptir. Ayrıca, bazı demografik özellik ve kişi bilgileri ile model faktörleri arasında anlamlı ilişkiler tespit edilmiştir. Çalışmanın, asayiş hizmetlerinde teknolojinin kabulü ve benimsenmesi konularındaki yapılacak çalışmalara fayda sağlayacağı değerlendirilmektedir.

References

  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
  • Ajzen, I. ve Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood-Cliffs, N.J.: Prentice-Hall.
  • Aydin, M. D. (2007). Kamu hizmetlerinde bilgi teknolojileri uygulamalari: firsat ve tehditler. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 25(2), 295-322.
  • Bagozzi, R. P. ve Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94.
  • Büyüköztürk, Ş. (2007). Sosyal bilimler için veri analizi el kitabı. Ankara: Pegem Akademi.
  • Colvin, C. A. ve Goh, A. (2005). Validation of the technology acceptance model for police. Journal of Criminal Justice, 33(1), 89-95.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340,
  • Davis, F. D., Bagozzi, R. P. ve Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111-1132.
  • Fornell, C. ve Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18, 382-388.
  • Gültekin, K. (2011). Technology acceptance and the effect of gender in the Turkish National Police: The case of the POLNET system. Turkish Journal of Police Studies, 13(3), 61-80,
  • Hair, J., Black, B., Babin, B., Anderson, R. ve Tatham, R. (2006). Multivariate data analysis (6th Edition). Upper Saddle River, NJ: Prentice-Hall.
  • Holden, R. J. ve Karsh, B. T. (2009). A theoretical model of health information technology usage behaviour with implications for patient safety. Behaviour & Information Technology, 28(1), 21-38.
  • Hu, L. T. ve Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55.
  • İçişleri Bakanlığı (2020). Bilgi işlem dairesi 2019 yılı faaliyet raporu. Erişim adresi https://www.icisleri.gov.tr/bilgiislem/icisleri-bakanligi-2019-yili-faaliyet-raporu-yayinlanmistir
  • J.Gn.K.lığı (2020). 2020 yılı faaliyet raporu. Erişim adresi https://www.jandarma.gov.tr/jandarma-genel-komutanligi-2020-yili-faaliyet-raporu
  • Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183-202.
  • Lawshe, C. H. (1975). A quantitative approach to content validity. Personnel Psychology, 28(4), 563-575.
  • Park, Y., Son, H. ve Kim, C. (2012). Investigating the determinants of construction professionals' acceptance of web-based training: An extension of the technology acceptance model. Automation in Construction, 22, 377-386.
  • Rogers, E. M. (1983). Diffusion of innovations. New York: Free Press.
  • Rose, J. A. ve Lacher, D. C. (2016). Managing public safety technology: Deploying systems in police, courts, corrections, and fire organizations. NY: Routledge.
  • Rui-Hsin, K. ve Lin, C. T. (2018). The usage intention of e-learning for police education and training. Policing: An International Journal of Police Strategies & Management, 41(1), 98-112.
  • Schepers, J. ve Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information & Management, 44(1), 90-103.
  • Schepers, J., Wetzels, M. ve Ruyter, K. (2005). Leadership styles in technology acceptance: do followers practice what leaders preach. Managing Service Quality: An International Journal, 15(6), 496-508.
  • Singh, M. (2017). Mobile technologies for police tasks: An Australian study. Journal of Organizational Computing and Electronic Commerce, 27(1), 66-80,
  • Taylor, S. ve Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176.
  • Terzis, V. ve Economides, A. A. (2011). The acceptance and use of computer based assessment. Computers & Education, 56(4), 1032-1044.
  • Teo, T., Ursavaş, Ö. F. ve Bahçekapili, E. (2011). Efficiency of the technology acceptance model to explain pre-service teachers' intention to use technology: A Turkish study. Campus-Wide Information Systems, 28(2), 93-101.
  • Tucker, L. R. ve Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38(1), 1-10,
  • Ursavaş, Ö. F. (2014). Öğretmenlerin bilişim teknolojilerini kullanmaya yönelik davranışlarının modellenmesi. Yayımlanmamış doktora tezi. Gazi Üniversitesi, Eğitim Bilimleri Enstitüsü, Ankara.
  • Veneziano, L. ve Hooper, J. (1997). A method for quantifying content validity of health-related questionnaires. American Journal of Health Behavior, 21(1), 67-70,
  • Venkatesh, V. ve Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451-481.
  • Venkatesh, V. ve Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
  • Venkatesh, V. ve Morris, M. G. (2000). Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115-139.
  • Venkatesh, V., Morris, M. G., Davis, G. B. ve Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
  • Venkatesh, V. ve Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315.
  • White, M. D., Gaub, J. E. ve Todak, N. (2017). Exploring the potential for body-worn cameras to reduce violence in police–citizen encounters. Policing: A Journal of Policy and Practice, 12(1), 66-76.
  • Yushau, B. (2006). The effects of blended e-learning on mathematics and computer attitudes in pre-calculus algebra. The Mathematics Enthusiast, 3(2), 176-183.

TECHNOLOGY ACCEPTANCE MODEL IN PUBLIC ORDER: A STUDY OF VALIDITY AND RELIABILITY

Year 2021, Volume: 10 Issue: 2, 339 - 364, 24.11.2021
https://doi.org/10.28956/gbd.1028635

Abstract

In this study, a technology acceptance model that describes the ICT acceptance levels of personnel working in public order was proposed. For this purpose, the data of the study, which included 371 participants, were analyzed using t-test, ANOVA and structural equality modeling. According to the results, an eight-factor technology acceptance structure was revealed. There were found significant relationships between the factors of the model, whose validity and reliability criteria are proved. Structural equation modeling analysis was conducted to determine the relationships between factors. Endogenous variables of the model (perceived ease of use, perceived usefulness and behavioral intention) have significant relationships both among themselves and with the exogenous independent variables (technology self-efficacy, perceived pleasure, subjective norm and anxiety). Also, significant relationships were found between some demographic characteristics, personal information and model factors. It is considered that this study will contribute to future studies on the acceptance and adoption of technology in public order.

References

  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
  • Ajzen, I. ve Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood-Cliffs, N.J.: Prentice-Hall.
  • Aydin, M. D. (2007). Kamu hizmetlerinde bilgi teknolojileri uygulamalari: firsat ve tehditler. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 25(2), 295-322.
  • Bagozzi, R. P. ve Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94.
  • Büyüköztürk, Ş. (2007). Sosyal bilimler için veri analizi el kitabı. Ankara: Pegem Akademi.
  • Colvin, C. A. ve Goh, A. (2005). Validation of the technology acceptance model for police. Journal of Criminal Justice, 33(1), 89-95.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340,
  • Davis, F. D., Bagozzi, R. P. ve Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111-1132.
  • Fornell, C. ve Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18, 382-388.
  • Gültekin, K. (2011). Technology acceptance and the effect of gender in the Turkish National Police: The case of the POLNET system. Turkish Journal of Police Studies, 13(3), 61-80,
  • Hair, J., Black, B., Babin, B., Anderson, R. ve Tatham, R. (2006). Multivariate data analysis (6th Edition). Upper Saddle River, NJ: Prentice-Hall.
  • Holden, R. J. ve Karsh, B. T. (2009). A theoretical model of health information technology usage behaviour with implications for patient safety. Behaviour & Information Technology, 28(1), 21-38.
  • Hu, L. T. ve Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55.
  • İçişleri Bakanlığı (2020). Bilgi işlem dairesi 2019 yılı faaliyet raporu. Erişim adresi https://www.icisleri.gov.tr/bilgiislem/icisleri-bakanligi-2019-yili-faaliyet-raporu-yayinlanmistir
  • J.Gn.K.lığı (2020). 2020 yılı faaliyet raporu. Erişim adresi https://www.jandarma.gov.tr/jandarma-genel-komutanligi-2020-yili-faaliyet-raporu
  • Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183-202.
  • Lawshe, C. H. (1975). A quantitative approach to content validity. Personnel Psychology, 28(4), 563-575.
  • Park, Y., Son, H. ve Kim, C. (2012). Investigating the determinants of construction professionals' acceptance of web-based training: An extension of the technology acceptance model. Automation in Construction, 22, 377-386.
  • Rogers, E. M. (1983). Diffusion of innovations. New York: Free Press.
  • Rose, J. A. ve Lacher, D. C. (2016). Managing public safety technology: Deploying systems in police, courts, corrections, and fire organizations. NY: Routledge.
  • Rui-Hsin, K. ve Lin, C. T. (2018). The usage intention of e-learning for police education and training. Policing: An International Journal of Police Strategies & Management, 41(1), 98-112.
  • Schepers, J. ve Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information & Management, 44(1), 90-103.
  • Schepers, J., Wetzels, M. ve Ruyter, K. (2005). Leadership styles in technology acceptance: do followers practice what leaders preach. Managing Service Quality: An International Journal, 15(6), 496-508.
  • Singh, M. (2017). Mobile technologies for police tasks: An Australian study. Journal of Organizational Computing and Electronic Commerce, 27(1), 66-80,
  • Taylor, S. ve Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176.
  • Terzis, V. ve Economides, A. A. (2011). The acceptance and use of computer based assessment. Computers & Education, 56(4), 1032-1044.
  • Teo, T., Ursavaş, Ö. F. ve Bahçekapili, E. (2011). Efficiency of the technology acceptance model to explain pre-service teachers' intention to use technology: A Turkish study. Campus-Wide Information Systems, 28(2), 93-101.
  • Tucker, L. R. ve Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38(1), 1-10,
  • Ursavaş, Ö. F. (2014). Öğretmenlerin bilişim teknolojilerini kullanmaya yönelik davranışlarının modellenmesi. Yayımlanmamış doktora tezi. Gazi Üniversitesi, Eğitim Bilimleri Enstitüsü, Ankara.
  • Veneziano, L. ve Hooper, J. (1997). A method for quantifying content validity of health-related questionnaires. American Journal of Health Behavior, 21(1), 67-70,
  • Venkatesh, V. ve Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451-481.
  • Venkatesh, V. ve Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
  • Venkatesh, V. ve Morris, M. G. (2000). Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115-139.
  • Venkatesh, V., Morris, M. G., Davis, G. B. ve Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
  • Venkatesh, V. ve Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315.
  • White, M. D., Gaub, J. E. ve Todak, N. (2017). Exploring the potential for body-worn cameras to reduce violence in police–citizen encounters. Policing: A Journal of Policy and Practice, 12(1), 66-76.
  • Yushau, B. (2006). The effects of blended e-learning on mathematics and computer attitudes in pre-calculus algebra. The Mathematics Enthusiast, 3(2), 176-183.
There are 37 citations in total.

Details

Primary Language Turkish
Journal Section Articles
Authors

Güray Arık This is me 0000-0003-4435-0881

Süleyman Sadi Seferoğlu 0000-0002-5010-484X

Publication Date November 24, 2021
Submission Date February 25, 2021
Published in Issue Year 2021 Volume: 10 Issue: 2

Cite

APA Arık, G., & Seferoğlu, S. S. (2021). ASAYİŞ HİZMETLERİNDE TEKNOLOJİ KABUL MODELİ: GEÇERLİK VE GÜVENİRLİK ÇALIŞMASI. Güvenlik Bilimleri Dergisi, 10(2), 339-364. https://doi.org/10.28956/gbd.1028635

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