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BİLİŞİM SİSTEMLERİ BAŞARISI VE ÖRGÜTSEL ATİKLİK: SİGORTA ŞİRKETLERİ ÜZERİNE İLİŞKİSEL ÇALIŞMA

Year 2017, Volume: 4 Issue: 11, 421 - 444, 12.09.2017

Abstract

Örgütsel atiklik ve Bilişim Sistemleri (IS), operasyonel mükemmeliyet ve rekabet avantajı açısından kuruluşlar için çağdaş temel faktörlerdir. Kurumların hayatta kalabilmeleri için tüm çevresel değişikliklere karşı esnek ve proaktif olmaları gerektiğinden dolayı, organizasyonlar ve çevrelerindeki bilgi akışı düzgün bir şekilde yönetilmelidir. Bilişim sistemleri (IS), kuruluşların bu bilgi akışını yönetmesini ve hayatta kalabilmek için gerekli özelliklere sahip olmalarını sağlar. Bu çalışmada; bilişim sistemleri başarısı ve örgütsel atiklik arasındaki ilişki, literatür taraması ve korelasyonel çalışmalara dayanarak, tartışılmıştır. Bunu yapmak için, TRAMER bilgi sistemini kullanan 75 sigorta şirketine bilişim sistemleri başarısı ve örgütsel atiklik anketleri uygulanmıştır. Toplanan veriler analiz edilmiş ve sonuca göre; bütün bilişim sistemleri başarı faktörlerinin örgütsel atiklikle ilişkili olduğu görülmüştür Regresyon analizi ise, örgütsel çevikliğin neredeyse yarısının (% 54) IS başarısı tarafından açıklanabileceğini göstermektedir. Ayrıca, hizmet kalitesi, bilgi kalitesi ve net fayda faktörlerinin örgütsel çeviklik üzerinde nispeten daha yüksek etkileri olduğu gözlemlenmektedir.  

References

  • Agourram, H. (2009). Defining Information System Success in Germany. International Journal of Information Management, 29, ss. 129–137.
  • Babbie, E. (1990). Survey research methods (2nd Ed). Belmont, CA: Wadsworth.
  • Balaban, I., Mu., E., & Divjak B. (2013). Development of An Electronic Portfolio System Success Model: An Information Systems Approach. Computers & Education, 60, ss. 396–411.
  • Baraka, H. A., Baraka, H. A.,& El-Gamily, I. H. (2013). Assessing Call Centers’ Success: A Validation of The Delone and Mclean Model For Information System. Egyptian Informatics Journal, 14, ss. 99–108.
  • Bharati, P., & Berg, D. (2005). Service Quality from The Other Side: Information Systems Management at Duquesne Light. International Journal of Information Management, 25, ss. 367–380.
  • Bhattacherjee, A. (2001). Understanding Informatıon Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly, 25 (3), ss. 351-370.
  • Chatterjee, S. & Hadi, A. S. (2006). Regression Analysis by Example (4th. ed). Hoboken, New Fersey: John Wiley & Sons.
  • Cho, J., Park, I., & Michel J. W. (2011). How Does Leadership Affect Information Systems Success? The Role of Transformational Leadership. Information & Management, 48, ss. 270–277.
  • Coronado M., A. E., Sarhadi, M., & Millar C. (2002). Defining a Framework for Information Systems Requirements for Agile Manufacturing. International Journal of Production Economics, 75, ss. 57–68.
  • Crocitto M., & Youssef M. (2003). The Human Side of Organizational Agility. Industrial Management & Data Systems, 103 (6), ss. 388-397.
  • Davis, F. D. (1985). A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory and Results. Massachusetts Institute of Technology.
  • DeGroote, S. E., & Marx, T. G. (2013). The Impact of It on Supply Chain Agility and Firm Performance: an Empirical Investigation. International Journal of Information Management 33, ss. 909–916.
  • DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean Model of Information Systems Success: A Ten-Year Update. Journal of Management Information Systems, ss. 19 (4), ss. 9-30.
  • Ganguly, A., Nilchiani, R., & Farr, J. V. (2009). Evaluating Agility in Corporate Enterprises. International Journal of Production Economics, 118, ss. 410–423.
  • Ghasemi, A., & Zahediasl, S. (2012). Normality Tests for Statistical Analysis: A Guide for Non-Statisticians. Int J Endocrinol Metab, 10 (2), ss. 486-489. doi: 10.5812/ijem.3505.
  • Goodhue, D. L., & Thompson, R. L. (1995). Task-Technology Fit and Individual Performance. MIS Quarterly, 19 (2), ss. 213-236.
  • Gorla, N., & Somer, T. M. (2014). The Impact of IT Outsourcing on Information Systems Success. Information & Management, 51, ss. 320–335.
  • Halonen, R., Acton, T., Golden, W., & Conboy, K. (2009). Delone & Mclean Success Model As A Descriptive Tool İn Evaluating The Use of A Virtual Learning Environment. Paper Presented at International Conference on Organizational Learning, Knowledge and Capabilities (Olkc 2009), Amsterdam, The Netherlands.
  • Jiang, J. J., Klein, G., & Discenza, R. (2002). Perception Differences of Software Success: Provider and User Views Of System Metrics. The Journal of Systems and Software, 63, ss. 17–27.
  • Kremelberg, D. (2011). Practical Statistics. USA: Sage Publications.
  • Landrum, H., Prybutok, V. R., & Zhang, X. (2010). The Moderating Effect of Occupation on the Perception of Information Services Quality and Success. Computers & Industrial Engineering, 58, ss. 133–142.
  • Laudon, K., & Laudon, J. (2015). Management Information Systems: International Edition, 14/E. Pearson Higher Education.
  • Lee, Y., & Kozar, K. A. (2006). Investigating the Effect of Website Quality on E-Business Success: An Analytic Hierarchy Process (AHP) Approach. Decision Support Systems, 42, ss. 1383–1401.
  • Liao, D., & Valliant, R. (2012). Variance Inflation Factors in the Analysis of Complex Survey Data. Survey Methodology, 38 (1), ss. 53-62
  • Lu, Y., & Ramamurthy, K. (2011). Understanding the Link between Information Technology Capability and Organizational Agility: An Empirical Examination”, MIS Quarterly, 35 (4), ss. 931-954.
  • Marett, K., Otondo, R. F., & Taylor, G. S. (2013). Assessıng The Effects of Benefıts and Instıtutıonal Influences on The Contınued Use of Envıronmentally Munificent Bypass Systems in Long-Haul Truckıng. MIS Quarterly, 37 (4), ss. 1301-1312.
  • Narasimhan, R., Swink, M., & Kim S. W. (2006). Disentangling Leanness and Agility: An Empirical Investigation. Journal of Operations Management, 24, ss. 440–457.
  • Nijssen, M., & Paauwe, J. (2012). HRM in Turbulent Times: How to Achieve Organizational Agility?. The International Journal of Human Resource Management, 23 (16), ss. 3315–3335.
  • Parasurman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A Multiple-Item Scale for Measuring Consumer Perceptions of Service Quality. Journal of Retailing, 64 (1), ss. 12-40.
  • Petter S., & Fruhling, A. (2011). Evaluating the Success of an Emergency Response Medical Information System. International Journal of Medical Informatics, 80, ss. 480–489.
  • Petter, S., Delone, W., & Mclean, E. R. (2008). Measuring İnformation Systems Success: Models, Dimensions, Measures, and Interrelationships. European Journal of Information Systems, 17, ss. 236–263.
  • Powers, D. A., & Xie, Y. (2000). Statistical Methods for Categorical Data Analysis. California, USA: Academic Press.
  • Prybutok, V. R., Zhang, X., & Ryan, S. D. (2008). Evaluating Leadership, IT Quality, and Net Benefits in an E-Government Environment. Information & Management, 45, ss. 143–152.
  • Raghavan, V., Zhang, X., & Jeyaraj, A. (2010). Implementation Success of Clinician Information Systems in Healthcare Contexts. Americas Conference on Information Systems (AMCIS), paper333. Retrieved from:http://aisel.aisnet.org/cgi/viewcontent.cgi?article=1330&context=amcis2010
  • Ramayah, T., Ahmad, N. H., & Lo, M. (2010). The Role of Quality Factors in Intention to Continue Using an E-Learning System in Malaysia. Procedia Social and Behavioral Sciences, 2, ss. 5422–5426.
  • Raschke, R. L. (2010). Process-Based View of Agility: The Value Contribution of IT and the Effects on Process Outcomes. International Journal of Accounting Information Systems, 11, ss. 297–313.
  • Ratten, V. (2015). Continuance Use İntention of Cloud Computing: Innovativeness and Creativity Perspectives. Journal of Business Research. Doi.Org/10.1016/J.Jbusres.2015.10.047
  • Reddy, C., Balasubramanyam, P., & Subbarayudu, M. (2013). An Effective Approach to Resolve Multicollinearity in Agriculture Data. International Journal of Research in Electronics and Computer Engineering, 1(1), ss. 27-30.
  • Seddon, P. B., & Kiew, M. (1996). A Partıal Test and Development of Delone and Mclean's Model Of Is Success. Australasian Journal of Information Systems, 4 (1), ss. 90-109.
  • Sherehiy, B., Karwowski, W., & Layer, J. K. (2007). A Review of Enterprise Agility: Concepts, Frameworks, and Attributes. International Journal of Industrial Ergonomics, 37, ss. 445–460.
  • Sivo, S., Saunders, C., Chang, Q., & Jiang, J. J. (2006). How Low Should You Go? Low Response Rates and the Validity of Inference in IS Questionnaire Research. Journal of the Association for Information Systems, 7 (6), ss. 351-414.
  • Steinskog, D. J., Tjøstheım, D. B., & Kvamstø, N. G. (2007). A Cautionary Note on the Use of the Kolmogorov–Smirnov Test for Normality. American Meteorological Society, 135, ss. 1151-1157. doi: 10.1175/MWR3326.1
  • Tallon, P. P., & Pinsonneault, A. (2011). Competıng Perspectıves On The Lınk Between Strategıc Informatıon Technology Alıgnment and Organızatıonal Agılıty: Insıghts From A Mediation Model. MIS Quarterly, 35 (2), ss. 463-486.
  • Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach’s alpha. International Journal of Medical Education, 2, ss. 53-55. doi: 10.5116/ijme.4dfb.8dfd
  • Tseng, Y., & Lin, C. (2011). Enhancing Enterprise Agility By Deploying Agile Drivers, Capabilities and Providers. Information Sciences,181, ss. 3693–3708.
  • Vessey, I., & Galletta, D. (1991). Cognitive Fit: an Empirical Study of Information Acquisition. Information Systems Research, 2 (1), ss.63-84.
  • Wang, Y., & Liao, Y. (2008). Assessing eGovernment Systems Success: A Validation of the Delone and McLean Model of Information Systems Success. Government Information Quarterly, 25, ss. 717–733.
  • Wang, Y., & Shih, Y. (2009). Why Do People Use Information Kiosks? A Validation of The Unified Theory of Acceptance and Use of Technology. Government Information Quarterly, 26, 158–165.
  • Wu, J., & Wang, Y. (2006). Measuring KMS Success: A Respecification of the Delone and Mclean’s Model. Information & Management, 43, ss. 728–739.
  • Yen, H. R., Li, E. Y., & Niehoff, B. P. (2008). Do Organizational Citizenship Behaviors Lead To Information System Success? Testing the Mediation Effects of Integration Climate and Project Management. Information & Management, 45, ss. 394–402.
  • Yoon, C., & Rolland, E. (2015). Understandıng Contınuance Use in Socıal Networkıng Servıces. Journal of Computer Information Systems, 55 (2), ss. 1-8.
  • Zain, M., Kassim, N. M., & Mokhtar, E. (2003). Use of Information Technology and Information Systems for Organisational Agility in Malaysian Firms. Singapore Management Review, 25 (1), ss. 69-83.
  • Zain, M., Rose, R. C., Abdullah, I., & Masrom, M. (2005). The Relationship between Information Technology Acceptance and Organizational Agility in Malaysia. Information & Management, 42, ss. 829–839.
  • Zheng, Y., Zhao, K., & Stylianou, A. (2013). The Impacts of Information Quality and System Quality on Users' Continuance Intention in Information-Exchange Virtual Communities: An Empirical Investigation. Decision Support Systems, 56, ss. 513–524.

NFORMATION SYSTEMS SUCCESS AND ORGANIZATIONAL AGILITY: A CORRELATIONAL STUDY ON INSURANCE COMPANIES

Year 2017, Volume: 4 Issue: 11, 421 - 444, 12.09.2017

Abstract

Organizational Agility and Information Systems (IS) are the contemporary key factors for organizations in terms of operational excellence and competitive advantage. Since organizations have to be flexible and proactive against all environmental changes fosurvival, information flow through the organizations and their environment should be managed properly. Information systems (IS) enable organizations to manage this information flow and to have necessary features for survival. In this study, the relationship between information systems success (IS Success) and organizational agility is discussed based on literature review and a correlational study. To do so, IS success and organizational agility questionnaires applied to 75 insurance companies that use insurance information and monitoring information system (TRAMER). Collected data was analyzed and results show that all IS success factors significantly related with organizational agility. Regression analysis show that almost half of (54%) organizational agility can be explained by IS success. Moreover, it is observed that service quality, information quality and net benefits factors have relatively higher effects on organizational agility.  

References

  • Agourram, H. (2009). Defining Information System Success in Germany. International Journal of Information Management, 29, ss. 129–137.
  • Babbie, E. (1990). Survey research methods (2nd Ed). Belmont, CA: Wadsworth.
  • Balaban, I., Mu., E., & Divjak B. (2013). Development of An Electronic Portfolio System Success Model: An Information Systems Approach. Computers & Education, 60, ss. 396–411.
  • Baraka, H. A., Baraka, H. A.,& El-Gamily, I. H. (2013). Assessing Call Centers’ Success: A Validation of The Delone and Mclean Model For Information System. Egyptian Informatics Journal, 14, ss. 99–108.
  • Bharati, P., & Berg, D. (2005). Service Quality from The Other Side: Information Systems Management at Duquesne Light. International Journal of Information Management, 25, ss. 367–380.
  • Bhattacherjee, A. (2001). Understanding Informatıon Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly, 25 (3), ss. 351-370.
  • Chatterjee, S. & Hadi, A. S. (2006). Regression Analysis by Example (4th. ed). Hoboken, New Fersey: John Wiley & Sons.
  • Cho, J., Park, I., & Michel J. W. (2011). How Does Leadership Affect Information Systems Success? The Role of Transformational Leadership. Information & Management, 48, ss. 270–277.
  • Coronado M., A. E., Sarhadi, M., & Millar C. (2002). Defining a Framework for Information Systems Requirements for Agile Manufacturing. International Journal of Production Economics, 75, ss. 57–68.
  • Crocitto M., & Youssef M. (2003). The Human Side of Organizational Agility. Industrial Management & Data Systems, 103 (6), ss. 388-397.
  • Davis, F. D. (1985). A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory and Results. Massachusetts Institute of Technology.
  • DeGroote, S. E., & Marx, T. G. (2013). The Impact of It on Supply Chain Agility and Firm Performance: an Empirical Investigation. International Journal of Information Management 33, ss. 909–916.
  • DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean Model of Information Systems Success: A Ten-Year Update. Journal of Management Information Systems, ss. 19 (4), ss. 9-30.
  • Ganguly, A., Nilchiani, R., & Farr, J. V. (2009). Evaluating Agility in Corporate Enterprises. International Journal of Production Economics, 118, ss. 410–423.
  • Ghasemi, A., & Zahediasl, S. (2012). Normality Tests for Statistical Analysis: A Guide for Non-Statisticians. Int J Endocrinol Metab, 10 (2), ss. 486-489. doi: 10.5812/ijem.3505.
  • Goodhue, D. L., & Thompson, R. L. (1995). Task-Technology Fit and Individual Performance. MIS Quarterly, 19 (2), ss. 213-236.
  • Gorla, N., & Somer, T. M. (2014). The Impact of IT Outsourcing on Information Systems Success. Information & Management, 51, ss. 320–335.
  • Halonen, R., Acton, T., Golden, W., & Conboy, K. (2009). Delone & Mclean Success Model As A Descriptive Tool İn Evaluating The Use of A Virtual Learning Environment. Paper Presented at International Conference on Organizational Learning, Knowledge and Capabilities (Olkc 2009), Amsterdam, The Netherlands.
  • Jiang, J. J., Klein, G., & Discenza, R. (2002). Perception Differences of Software Success: Provider and User Views Of System Metrics. The Journal of Systems and Software, 63, ss. 17–27.
  • Kremelberg, D. (2011). Practical Statistics. USA: Sage Publications.
  • Landrum, H., Prybutok, V. R., & Zhang, X. (2010). The Moderating Effect of Occupation on the Perception of Information Services Quality and Success. Computers & Industrial Engineering, 58, ss. 133–142.
  • Laudon, K., & Laudon, J. (2015). Management Information Systems: International Edition, 14/E. Pearson Higher Education.
  • Lee, Y., & Kozar, K. A. (2006). Investigating the Effect of Website Quality on E-Business Success: An Analytic Hierarchy Process (AHP) Approach. Decision Support Systems, 42, ss. 1383–1401.
  • Liao, D., & Valliant, R. (2012). Variance Inflation Factors in the Analysis of Complex Survey Data. Survey Methodology, 38 (1), ss. 53-62
  • Lu, Y., & Ramamurthy, K. (2011). Understanding the Link between Information Technology Capability and Organizational Agility: An Empirical Examination”, MIS Quarterly, 35 (4), ss. 931-954.
  • Marett, K., Otondo, R. F., & Taylor, G. S. (2013). Assessıng The Effects of Benefıts and Instıtutıonal Influences on The Contınued Use of Envıronmentally Munificent Bypass Systems in Long-Haul Truckıng. MIS Quarterly, 37 (4), ss. 1301-1312.
  • Narasimhan, R., Swink, M., & Kim S. W. (2006). Disentangling Leanness and Agility: An Empirical Investigation. Journal of Operations Management, 24, ss. 440–457.
  • Nijssen, M., & Paauwe, J. (2012). HRM in Turbulent Times: How to Achieve Organizational Agility?. The International Journal of Human Resource Management, 23 (16), ss. 3315–3335.
  • Parasurman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A Multiple-Item Scale for Measuring Consumer Perceptions of Service Quality. Journal of Retailing, 64 (1), ss. 12-40.
  • Petter S., & Fruhling, A. (2011). Evaluating the Success of an Emergency Response Medical Information System. International Journal of Medical Informatics, 80, ss. 480–489.
  • Petter, S., Delone, W., & Mclean, E. R. (2008). Measuring İnformation Systems Success: Models, Dimensions, Measures, and Interrelationships. European Journal of Information Systems, 17, ss. 236–263.
  • Powers, D. A., & Xie, Y. (2000). Statistical Methods for Categorical Data Analysis. California, USA: Academic Press.
  • Prybutok, V. R., Zhang, X., & Ryan, S. D. (2008). Evaluating Leadership, IT Quality, and Net Benefits in an E-Government Environment. Information & Management, 45, ss. 143–152.
  • Raghavan, V., Zhang, X., & Jeyaraj, A. (2010). Implementation Success of Clinician Information Systems in Healthcare Contexts. Americas Conference on Information Systems (AMCIS), paper333. Retrieved from:http://aisel.aisnet.org/cgi/viewcontent.cgi?article=1330&context=amcis2010
  • Ramayah, T., Ahmad, N. H., & Lo, M. (2010). The Role of Quality Factors in Intention to Continue Using an E-Learning System in Malaysia. Procedia Social and Behavioral Sciences, 2, ss. 5422–5426.
  • Raschke, R. L. (2010). Process-Based View of Agility: The Value Contribution of IT and the Effects on Process Outcomes. International Journal of Accounting Information Systems, 11, ss. 297–313.
  • Ratten, V. (2015). Continuance Use İntention of Cloud Computing: Innovativeness and Creativity Perspectives. Journal of Business Research. Doi.Org/10.1016/J.Jbusres.2015.10.047
  • Reddy, C., Balasubramanyam, P., & Subbarayudu, M. (2013). An Effective Approach to Resolve Multicollinearity in Agriculture Data. International Journal of Research in Electronics and Computer Engineering, 1(1), ss. 27-30.
  • Seddon, P. B., & Kiew, M. (1996). A Partıal Test and Development of Delone and Mclean's Model Of Is Success. Australasian Journal of Information Systems, 4 (1), ss. 90-109.
  • Sherehiy, B., Karwowski, W., & Layer, J. K. (2007). A Review of Enterprise Agility: Concepts, Frameworks, and Attributes. International Journal of Industrial Ergonomics, 37, ss. 445–460.
  • Sivo, S., Saunders, C., Chang, Q., & Jiang, J. J. (2006). How Low Should You Go? Low Response Rates and the Validity of Inference in IS Questionnaire Research. Journal of the Association for Information Systems, 7 (6), ss. 351-414.
  • Steinskog, D. J., Tjøstheım, D. B., & Kvamstø, N. G. (2007). A Cautionary Note on the Use of the Kolmogorov–Smirnov Test for Normality. American Meteorological Society, 135, ss. 1151-1157. doi: 10.1175/MWR3326.1
  • Tallon, P. P., & Pinsonneault, A. (2011). Competıng Perspectıves On The Lınk Between Strategıc Informatıon Technology Alıgnment and Organızatıonal Agılıty: Insıghts From A Mediation Model. MIS Quarterly, 35 (2), ss. 463-486.
  • Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach’s alpha. International Journal of Medical Education, 2, ss. 53-55. doi: 10.5116/ijme.4dfb.8dfd
  • Tseng, Y., & Lin, C. (2011). Enhancing Enterprise Agility By Deploying Agile Drivers, Capabilities and Providers. Information Sciences,181, ss. 3693–3708.
  • Vessey, I., & Galletta, D. (1991). Cognitive Fit: an Empirical Study of Information Acquisition. Information Systems Research, 2 (1), ss.63-84.
  • Wang, Y., & Liao, Y. (2008). Assessing eGovernment Systems Success: A Validation of the Delone and McLean Model of Information Systems Success. Government Information Quarterly, 25, ss. 717–733.
  • Wang, Y., & Shih, Y. (2009). Why Do People Use Information Kiosks? A Validation of The Unified Theory of Acceptance and Use of Technology. Government Information Quarterly, 26, 158–165.
  • Wu, J., & Wang, Y. (2006). Measuring KMS Success: A Respecification of the Delone and Mclean’s Model. Information & Management, 43, ss. 728–739.
  • Yen, H. R., Li, E. Y., & Niehoff, B. P. (2008). Do Organizational Citizenship Behaviors Lead To Information System Success? Testing the Mediation Effects of Integration Climate and Project Management. Information & Management, 45, ss. 394–402.
  • Yoon, C., & Rolland, E. (2015). Understandıng Contınuance Use in Socıal Networkıng Servıces. Journal of Computer Information Systems, 55 (2), ss. 1-8.
  • Zain, M., Kassim, N. M., & Mokhtar, E. (2003). Use of Information Technology and Information Systems for Organisational Agility in Malaysian Firms. Singapore Management Review, 25 (1), ss. 69-83.
  • Zain, M., Rose, R. C., Abdullah, I., & Masrom, M. (2005). The Relationship between Information Technology Acceptance and Organizational Agility in Malaysia. Information & Management, 42, ss. 829–839.
  • Zheng, Y., Zhao, K., & Stylianou, A. (2013). The Impacts of Information Quality and System Quality on Users' Continuance Intention in Information-Exchange Virtual Communities: An Empirical Investigation. Decision Support Systems, 56, ss. 513–524.
There are 54 citations in total.

Details

Journal Section Articles
Authors

İbrahim Yıldız

Güler Erkal Karaman This is me

Ersin Karaman

Publication Date September 12, 2017
Published in Issue Year 2017 Volume: 4 Issue: 11

Cite

APA Yıldız, İ., Erkal Karaman, G., & Karaman, E. (2017). BİLİŞİM SİSTEMLERİ BAŞARISI VE ÖRGÜTSEL ATİKLİK: SİGORTA ŞİRKETLERİ ÜZERİNE İLİŞKİSEL ÇALIŞMA. Gazi Üniversitesi Sosyal Bilimler Dergisi, 4(11), 421-444.
AMA Yıldız İ, Erkal Karaman G, Karaman E. BİLİŞİM SİSTEMLERİ BAŞARISI VE ÖRGÜTSEL ATİKLİK: SİGORTA ŞİRKETLERİ ÜZERİNE İLİŞKİSEL ÇALIŞMA. ASBİDER. September 2017;4(11):421-444.
Chicago Yıldız, İbrahim, Güler Erkal Karaman, and Ersin Karaman. “BİLİŞİM SİSTEMLERİ BAŞARISI VE ÖRGÜTSEL ATİKLİK: SİGORTA ŞİRKETLERİ ÜZERİNE İLİŞKİSEL ÇALIŞMA”. Gazi Üniversitesi Sosyal Bilimler Dergisi 4, no. 11 (September 2017): 421-44.
EndNote Yıldız İ, Erkal Karaman G, Karaman E (September 1, 2017) BİLİŞİM SİSTEMLERİ BAŞARISI VE ÖRGÜTSEL ATİKLİK: SİGORTA ŞİRKETLERİ ÜZERİNE İLİŞKİSEL ÇALIŞMA. Gazi Üniversitesi Sosyal Bilimler Dergisi 4 11 421–444.
IEEE İ. Yıldız, G. Erkal Karaman, and E. Karaman, “BİLİŞİM SİSTEMLERİ BAŞARISI VE ÖRGÜTSEL ATİKLİK: SİGORTA ŞİRKETLERİ ÜZERİNE İLİŞKİSEL ÇALIŞMA”, ASBİDER, vol. 4, no. 11, pp. 421–444, 2017.
ISNAD Yıldız, İbrahim et al. “BİLİŞİM SİSTEMLERİ BAŞARISI VE ÖRGÜTSEL ATİKLİK: SİGORTA ŞİRKETLERİ ÜZERİNE İLİŞKİSEL ÇALIŞMA”. Gazi Üniversitesi Sosyal Bilimler Dergisi 4/11 (September 2017), 421-444.
JAMA Yıldız İ, Erkal Karaman G, Karaman E. BİLİŞİM SİSTEMLERİ BAŞARISI VE ÖRGÜTSEL ATİKLİK: SİGORTA ŞİRKETLERİ ÜZERİNE İLİŞKİSEL ÇALIŞMA. ASBİDER. 2017;4:421–444.
MLA Yıldız, İbrahim et al. “BİLİŞİM SİSTEMLERİ BAŞARISI VE ÖRGÜTSEL ATİKLİK: SİGORTA ŞİRKETLERİ ÜZERİNE İLİŞKİSEL ÇALIŞMA”. Gazi Üniversitesi Sosyal Bilimler Dergisi, vol. 4, no. 11, 2017, pp. 421-44.
Vancouver Yıldız İ, Erkal Karaman G, Karaman E. BİLİŞİM SİSTEMLERİ BAŞARISI VE ÖRGÜTSEL ATİKLİK: SİGORTA ŞİRKETLERİ ÜZERİNE İLİŞKİSEL ÇALIŞMA. ASBİDER. 2017;4(11):421-44.