بررسی تاثیر فرهنگ سازمانی، استراتژی سازمانی و نوآوری در فناوری بر اثربخشی سیستمهای الکترونیکی مدیریت ارتباط با مشتری

الموضوعات : دو فصلنامه مدیریت زنجیره ارزش

زینب سلطانی ¹ (باشگاه پژوهشگران جوان و نخبگان، واحد تبریز، دانشگاه آزاد اسلامی، تبریز، ایران.)
نیما جعفری نویمی پور ² (2. گروه مهندسی کامپیوتر،واحد تبریز، دانشگاه آزاد اسلامی، تبریز،ایران.)

تاريخ الإرسال : 19 الثلاثاء , رجب, 1437 تاريخ التأكيد : 10 الأربعاء , رمضان, 1437 تاريخ الإصدار : 14 السبت , شعبان, 1437

الکلمات المفتاحية: نوآوری, اثربخشی, استراتژی سازمانی, مدیریت الکترونیکی ارتباط با مشتری, فرهنگ ‌سازمانی,

ملخص المقالة :

امروزه شرط بقای مؤسسات در توانایی جذب و نگهداری مشتریان آگاه است. در این میان مدیریت الکترونیکی ارتباط با مشتری (E-CRM)یک استراتژی برای بازاریابی، فروش و یکپارچه‌سازی خدمات آنلاین است که نقش مهمی در شناسایی، به دست آوردن و حفظ مشتریان دارد که به‌عنوان بزرگ‌ترین سرمایه شرکت‌ها در نظر گرفته می‌شود. E-CRM ارتباط میان شرکت و مشتریان را با استفاده از ایجاد و افزایش روابط با آن‌ها از طریق فناوری مدرن بهبود و افزایش می‌دهد. اماموفقیتدر E-CRM تنهاازطریق شناخت عوامل مؤثر بر اثربخشی و موفقیت E-CRM قابل‌دستیابیاست. این مطالعه به ارائه مدل و چارچوبی برای تعیین برخی عوامل مؤثر در اثربخشی E-CRM پرداخته است. مدل ارائه‌شده با استفاده از معادلات ساختاری با حداقل مربعات جزئی مورد آزمایش قرار گرفت. نتایج حاصل از داده‌های جمع‌آوری‌شده از 98 نفر از کارکنان اداره کل گمرک استان آذربایجان شرقی نشان می‌دهد که تأثیر رضایت کارکنان بر عملکرد سازمان‌ها با فرهنگ‌سازمانی، استراتژی سازمانی و نوآوری آغاز می‌شود و حضور کامل این عوامل تأثیر مثبت بر اثربخشی سیستم‌های E-CRM دارد.

المصادر:

منابع

• Adebanjo, D. (2008). E-crm Implementation—a comparison of three approaches. Paper presented at the Management of Innovation and Technology, 2008. ICMIT 2008. 4th IEEE International Conference on.


• Ahmad, M. A., & Tarmudi, S. M. (2012). Generational Differences in Satisfaction with E-Learning among Higher Learning Institution Staff. Procedia-Social and Behavioral Sciences, 67, 304-311.


• Benitez-Amado, J., Perez-Arostegui, M. N., & Tamayo-Torres, J. (2010). Information technology-enabled innovativeness and green capabilities. The Journal of Computer Information Systems, 51(2), 87.


• Bergek, A., Hekkert, M., & Jacobsson, S. (2008). Functions in innovation systems: A framework for analysing energy system dynamics and identifying goals for system-building activities by entrepreneurs and policy makers. Innovation for a low carbon economy: economic, institutional and management approaches, 79.


• Bruque, S., & Moyano, J. (2007). Organisational determinants of information technology adoption and implementation in SMEs: The case of family and cooperative firms. Technovation, 27(5), 241-253.


• Chen, H.-R., & Tseng, H.-F. (2012). Factors that influence acceptance of web-based e-learning systems for the in-service education of junior high school teachers in Taiwan. Evaluation and program planning, 35(3), 398-406.


• Chen, Q., & Chen, H.-M. (2004). Exploring the success factors of eCRM strategies in practice. The Journal of Database Marketing & Customer Strategy Management, 11(4), 333-343.


• Chen, Q., Chen, H.-M., & Kazman, R. (2007). Investigating antecedents of technology acceptance of initial eCRM users beyond generation X and the role of self-construal. Electronic Commerce Research, 7(3-4), 315-339.


• Cheng, H.-H., & Yang, H.-L. (2014). The antecedents of collective creative efficacy for information system development teams. Journal of Engineering and Technology Management, 33, 1-17.


• Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-336.


• Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research, 14(2), 189-217.


• Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334.


• Davidson, G. (2004). Organisational culture and financial performance in a South African investment bank. unpublished Master’s dissertation. University of South Africa, Pretoria.


• Denison, D. R., & Mishra, A. K. (1995). Toward a theory of organizational culture and effectiveness. Organization science, 6(2), 204-223.


• Dickinger, A., Haghirian, P., Murphy, J., & Scharl, A. (2004). An investigation and conceptual model of SMS marketing. Paper presented at the System Sciences, 2004. Proceedings of the 37th Annual Hawaii International Conference on.


• Dotan, A. (2008). E-crm implementation: a comparison of three approaches. management of innovation and technology. Paper presented at the 4th IEEE International Conference.


• Falk, R., Miller, N., & Miller, N. A primer for soft modeling. 1992. Ohio University of Akron Press, Akron.


• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 39-50.


• Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate Data Analysis Pearson Prentice Hall. Upper Saddle River, NJ.


• Howell, K. E., & Annansingh, F. (2013). Knowledge generation and sharing in UK universities: A tale of two cultures? International Journal of Information Management, 33(1), 32-39.


• Huang, Y.-M., Huang, Y.-M., Huang, S.-H., & Lin, Y.-T. (2012). A ubiquitous English vocabulary learning system: Evidence of active/passive attitudes vs. usefulness/ease-of-use. Computers & Education, 58(1), 273-282.


• Hwang, Y. (2009). The impact of uncertainty avoidance, social norms and innovativeness on trust and ease of use in electronic customer relationship management. Electronic Markets, 19(2-3), 89-98.


• Islam, A. N. (2014). Sources of satisfaction and dissatisfaction with a learning management system in post-adoption stage: A critical incident technique approach. Computers in Human Behavior, 30, 249-261.


• Javadi, M. H. M., & Azmoon, Z. (2011). Ranking branches of system group company in terms of acceptance preparation of electronic customer relationship management using AHP method. Procedia Computer Science, 3, 1243-1248.


• Josiassen, A., Assaf, A. G., & Cvelbar, L. K. (2014). CRM and the bottom line: Do all CRM dimensions affect firm performance? International Journal of Hospitality Management, 36, 130-136.


• Jutla, D., Craig, J., & Bodorik, P. (2001). Enabling and measuring electronic customer relationship management readiness. Paper presented at the System Sciences, 2001. Proceedings of the 34th Annual Hawaii International Conference on.


• Khan, A., Ehsan, N., Mirza, E., & Sarwar, S. Z. (2012). Integration between customer relationship management (CRM) and data warehousing. Procedia Technology, 1, 239-249.


• Kimiloglu, H., & Zarali, H. (2009). What signifies success in e-CRM? Marketing Intelligence & Planning, 27(2), 246-267.


• Liao, S.-H., & Wu, C.-c. (2010). System perspective of knowledge management, organizational learning, and organizational innovation. Expert Systems with Applications, 37(2), 1096-1103.


• Lopez-Nicolas, C., & Soto-Acosta, P. (2010). Analyzing ICT adoption and use effects on knowledge creation: An empirical investigation in SMEs. International Journal of Information Management, 30(6), 521-528.


• Lumpkin, G. T., & Dess, G. G. (1996). Clarifying the entrepreneurial orientation construct and linking it to performance. Academy of management Review, 21(1), 135-172.


• Mahdavi, I., Cho, N., Shirazi, B., & Sahebjamnia, N. (2008). Designing evolving user profile in e-CRM with dynamic clustering of Web documents. Data & Knowledge Engineering, 65(2), 355-372.


• Mahdavi, I., Movahednejad, M., & Adbesh, F. (2011). Designing customer-oriented catalogs in e-CRM using an effective self-adaptive genetic algorithm. Expert Systems with Applications, 38(1), 631-639.


• Mao-qin, G., Ling, G., & Qi, X. (2011). The critical success factors for the banks implementing e-CRM. Paper presented at the E-Business and E-Government (ICEE), 2011 international conference on.


• Mostaghel, R., Oghazi, P., Beheshti, H. M., & Hultman, M. (2015). Strategic use of enterprise systems among service firms: Antecedents and consequences. Journal of Business Research, 68(7), 1544-1549.


• Navimipour, N. J., & Soltani, Z. (2016). The impact of cost, technology acceptance and employees' satisfaction on the effectiveness of the electronic customer relationship management systems. Computers in Human Behavior, 55, 1052-1066.


• Navin, A. H., Navimipour, N. J., Rahmani, A. M., & Hosseinzadeh, M. (2014). Expert grid: new type of grid to manage the human resources and study the effectiveness of its task scheduler. Arabian Journal for Science and Engineering, 39(8), 6175-6188.


• Nunnally, J. (1978). Psychometric methods. New York: McGraw.


• Ocker, R. J., & Mudambi, S. (2003). Assessing the readiness of firms for CRM: a literature review and research model. Paper presented at the System Sciences, 2003. Proceedings of the 36th Annual Hawaii International Conference on.


• Paksoy, T., Pehlivan, N. Y., & Kahraman, C. (2012). Organizational strategy development in distribution channel management using fuzzy AHP and hierarchical fuzzy TOPSIS. Expert Systems with Applications, 39(3), 2822-2841.


• Pollitt, D., & Klein, D. (2005). Diversity is about more than observing the letter of the law. Human Resource Management International Digest, 13(4), 37-40.


• Ringle, C. M. (2006). Segmentation for path models and unobserved heterogeneity: The finite mixture partial least squares approach. University of Hamburg Research Paper on Marketing and Retailing(35).


• Schein, E. (2004). Organizational culture and leadership . San Francisco: John Willey & Sons: Inc.


• Schein, E. H. (2010). Organizational culture and leadership (Vol. 2): John Wiley & Sons.


• Sivaraks, P., Krairit, D., & Tang, J. (2011). Effects of e-CRM on customer–bank relationship quality and outcomes: The case of Thailand. The Journal of High Technology Management Research, 22(2), 141-157.


• Slone, R. E., Mentzer, J. T., & Dittmann, J. P. (2007). Are you the weakest link in your company's supply chain? Harvard Business Review, 85(9), 116.


• Sweetman, D., Luthans, F., Avey, J. B., & Luthans, B. C. (2011). Relationship between positive psychological capital and creative performance. Canadian Journal of Administrative Sciences/Revue Canadienne des Sciences de l'Administration, 28(1), 4-13.


• Tenenhaus, M., Vinzi, V. E., Chatelin, Y.-M., & Lauro, C. (2005). PLS path modeling. Computational statistics & data analysis, 48(1), 159-205.


• Tsai, P. C.-F., Yen, Y.-F., Huang, L.-C., & Huang, C. (2007). A study on motivating employees’ learning commitment in the post-downsizing era: Job satisfaction perspective. Journal of World Business, 42(2), 157-169.


• Wang, P., & Ramiller, N. C. (2009). Community learning in information technology innovation. MIS Quarterly, 709-734.


• Wetzels, M., Odekerken-Schröder, G., & Van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS quarterly, 177-195.


• Yeh, Y.-P. (2014). Exploring the impacts of employee advocacy on job satisfaction and organizational commitment: Case of Taiwanese airlines. Journal of Air Transport Management, 36, 94-100.


• Yu, X., Nguyen, B., Han, S. H., Chen, C.-H. S., & Li, F. (2015). Electronic CRM and perceptions of unfairness. Information Technology and Management, 1-12.


• Ziyae, B., Mobaraki, M. H., & Saeediyoun, M. (2015). The Effect of Psychological Capital on Innovation in Information Technology. Journal of Global Entrepreneurship Research, 5(1), 1-12.