Determining the Key Indicators affecting Electronic Customer Relationship Management (e-CRM) Using an integration of balanced scorecard and fuzzy screening techniques (Case Study: Companies Covered by Parsian Data-Processors Group)
محورهای موضوعی : Operation ResearchAbbas Shahnavazi 1 , Mehran Nemati Gonbaghi 2 , Seyedeh Faezeh Teymouri 3 , Bahman Ghasemi dakdare 4
1 - Department of Business Management, Roudbar Branch, Islamic Azad University, Roudbar, Iran
2 - Department of Mathematics, Roudbar Branch, Islamic Azad University, Roudbar, Iran
3 - Department of Computer Science, Roudbar Branch, Islamic Azad University, Roudbar, Iran
4 - Phd student in Marketing Management, Rasht Branch, Islamic Azad University, Rasht, Iran
کلید واژه: Performance Evaluation, Balanced Scorecard, Electronic customer relationship management, Yager’s Fuzzy Screening Technique,
چکیده مقاله :
Nowadays, increasing competition among companies and the huge cost of attracting new customers has led to companies seeking to retain existing customers rather than looking to attract new customers. These factors together have led to the emergence of customer relationship management. Thanks to the development of information and communication technology, especially the Internet, the use of customer relationship management has expanded and facilitated, and electronic customer relationship management has been formed. Customer Relationship Management (EMS) seeks to deepen and empower customer relationships by utilizing a variety of information and communication technologies such as websites. With the aim of identifying key indicators of performance and improving the performance of the Balanced Scorecard, this research paper has attempted to integrate it with Yager’s Fuzzy screening technique. This integrated model was implemented to develop a balanced scorecard for customer relationship management evaluation of companies covered by Parsian Data-Processors Group. The scale of “very important” was set as an acceptable scale for going through the screening process and for agreeing between managers and experts on the most important indicators. The results showed that the five indicators of customer viewpoint including increasing customer support during Purchasing Process and Afterward, Increasing Brand Confidence and Credibility , Participating in the Online Environment, Enhancing Customer Service After Sales, Increasing Customer Satisfaction, Increasing Site Usage and Various Site Capabilities, the four indicators of learning and innovating viewpoint including continuous improvement and modernization of the company's current services, the ability to use the new technologies, knowledge management capabilities in the organization and the ability of the company to learn from the market and to react it, the four indicators of financial viewpoint including Increased profitability; Increased share of online sales, flexibility in financing and increased annual sales , and the four indicators of exchange (processes) viewpoint including increased software update, increased use of advanced technologies compared to competitors; increased and improved use of Technology and Increasing Diversity of Services Offered on the Site (E-mail) have extracted as Key Indicators of Balanced Card Relationship Management Evaluation.
Nowadays, increasing competition among companies and the huge cost of attracting new customers has led to companies seeking to retain existing customers rather than looking to attract new customers. These factors together have led to the emergence of customer relationship management. Thanks to the development of information and communication technology, especially the Internet, the use of customer relationship management has expanded and facilitated, and electronic customer relationship management has been formed. Customer Relationship Management (EMS) seeks to deepen and empower customer relationships by utilizing a variety of information and communication technologies such as websites. With the aim of identifying key indicators of performance and improving the performance of the Balanced Scorecard, this research paper has attempted to integrate it with Yager’s Fuzzy screening technique. This integrated model was implemented to develop a balanced scorecard for customer relationship management evaluation of companies covered by Parsian Data-Processors Group. The scale of “very important” was set as an acceptable scale for going through the screening process and for agreeing between managers and experts on the most important indicators. The results showed that the five indicators of customer viewpoint including increasing customer support during Purchasing Process and Afterward, Increasing Brand Confidence and Credibility , Participating in the Online Environment, Enhancing Customer Service After Sales, Increasing Customer Satisfaction, Increasing Site Usage and Various Site Capabilities, the four indicators of learning and innovating viewpoint including continuous improvement and modernization of the company's current services, the ability to use the new technologies, knowledge management capabilities in the organization and the ability of the company to learn from the market and to react it, the four indicators of financial viewpoint including Increased profitability; Increased share of online sales, flexibility in financing and increased annual sales , and the four indicators of exchange (processes) viewpoint including increased software update, increased use of advanced technologies compared to competitors; increased and improved use of Technology and Increasing Diversity of Services Offered on the Site (E-mail) have extracted as Key Indicators of Balanced Card Relationship Management Evaluation.
Aggarwal, A. G., & Aakash. (2018). Multi-criteria-based prioritisation of B2C e-commerce website. International Journal of Society Systems Science, 10(3), 201-222.
Alzahrani, J. (2019). The impact of e-commerce adoption on business strategy in Saudi Arabian small and medium enterprises (SMEs). Review of Economics and Political Science, 4(1), 73-88.
Andonova, V. (2003). Online Disintermediation: Differences in the Behavior of Traditional Retailers in Adopting E‐Commerce. Management Research: Journal of the Iberoamerican Academy of Management, 27(2), 246 – 267.
Bhati, A., Thu, Y. T., Woon, S. K. H., Phuong, L. L., & Lynn, M. M. (2017). E-commerce usage and user perspectives in Myanmar: an exploratory study. Advanced Science Letters, 23(1), 519-523.
Brown, I., & Jayakody, R. (2008). B2C e-commerce success: A test and validation of a revised conceptual model. The Electronic Journal Information Systems Evaluation, 11(3), 167-184.
Bull, C. (2003). Strategic issues in customer relationship management (CRM) implementation. Business process management Journal, 9(5), 592-602.
Chavan, M. (2009). The balanced scorecard: a new challenge. Journal of management development, 28(5), 393-406.
Chiu, W., & Cho, H. (2019). E-commerce brand. Asia Pacific Journal of Marketing and Logistics, 10(5), 439-450.
Choshin, M., & Ghaffari, A. (2017). An investigation of the impact of effective factors on the success of e-commerce in small-and medium-sized companies. Computers in Human Behavior, 66, 67-74.
Delone, W. H., & Mclean, E. R. (2004). Measuring e-commerce success: Applying the DeLone & McLean information systems success model. International Journal of electronic commerce, 9(1), 31-47.
Eduardsen, J. (2018). Internationalisation Through Digitalisation: the Impact of E-Commerce Usage on Internationalisation in Small-and Medium-Sized Firms. International Business in the Information and Digital Age, 159-186.
Eduardsen, J. (2018). Internationalisation Through Digitalisation: the Impact of E-Commerce Usage on Internationalisation in Small-and Medium-Sized Firms. International Business in the Information and Digital Age, 159-186.
electronic customer relationship management (E-CRM) ”First International conference of
Faraoni, M., Rialti, R., Zollo, L., & Pellicelli, A. C. (2019). Exploring e-Loyalty Antecedents in B2C e-Commerce. British Food Journal, 121(2), 574-589.
Hassan, H., & Tibbits, H.R.(2000). Strategic Managementof Electronic Commerce; an adaption of balanced Scorecard, Internet Research: Electronic Networking Applications and Policy,
Hassan, S. H., Haniba, N. M. M., & Ahmad, N. H. (2019). Social customer relationship management (s-CRM) among small-and medium-sized enterprises (SMEs) in Malaysia. International Journal of Ethics and Systems, 35(2),284-302.
Hidayanto, A. N., Ovirza, M., Anggia, P., Budi, N. F. A., & Phusavat, K. (2017). The roles of electronic word of mouth and information searching in the promotion of a new e-commerce strategy: A case of online group buying in Indonesia. Journal of theoretical and applied electronic commerce research, 12(3), 69-85.
Hladchenko, M. (2015). Balanced Scorecard–a strategic management system of the higher education institution. International Journal of Educational Management, 29(2), 167-176.
Hua, N. (2016). E-commerce performance in hospitality and tourism. International Journal of Contemporary Hospitality Management, 28(9), 2052-2079.
Hua, N., Hight, S., Wei, W., Ozturk, A. B., Zhao, X. R., Nusair, K., & DeFranco, A. (2019). The power of e-commerce. International Journal of Contemporary Hospitality Management, 31(4), 1906-1923.
Jarrahi,M.,Hossain (2005). Explanation the Strategy and Establishment and Development of
Kabir, G., & Hasin, M. A. A. A. (2011). Evaluation of customer oriented success factors in mobile commerce using fuzzy AHP. Journal of Industrial Engineering and Management (JIEM), 4(2), 361-386.
Kaplan, R. S., Robert, N. P. D. K. S., Kaplan, R. S., & Norton, D. P. (2001). The strategy-focused organization: How balanced scorecard companies thrive in the new business environment. Harvard Business Press.
Karakostas, B., Kardaras, D., & Papathanassiou, E. (2005). The state of CRM adoption by the financial services in the UK: an empirical investigation. Information & Management, 42(6), 853-863.
Kımıloğlu, H., & Zaralı, H. (2009). What signifies success in e‐CRM?. Marketing Intelligence & Planning,
Ko, E., Kim, S. H., Kim, M., & Woo, J. Y. (2008). Organizational characteristics and the CRM adoption process. Journal of Business Research, 61(1), 65-74.
Kremez, Z., Frazer, L., Weaven, S., & Quach, S. (2019). Ecommerce structures for retail and service franchises. Asia Pacific Journal of Marketing and Logistics.
Li, P., & Xie, W. (2012). A strategic framework for determining e‐commerce adoption. Journal of Technology Management in China, 7(1), 22-35.
Lim, S. F. W., Jin, X., & Srai, J. S. (2018). Consumer-driven e-commerce. International Journal of Physical Distribution & Logistics Management, 48(3), 308-332.
Liu, Y., Zhou, C. F., & Chen, Y. W. (2006, August). Determinants of E-CRM in influencing customer satisfaction. In Pacific Rim International Conference on Artificial Intelligence (pp. 767-776). Springer, Berlin, Heidelberg.
Mainela, T., & Ulkuniemi, P. (2013). Personal interaction and customer relationship management in project business. Journal of Business & Industrial Marketing, 28(2), 103-110.
Martinson, S, Davidson.M.R and Tse, D.(1999). The balanced Scorecard: a foundation for the
Molla, A., & Licker, P. S. (2001). E-commerce systems success: An attempt to extend and respecify the Delone and MacLean model of IS success. J. Electron. Commerce Res., 2(4), 131-141.
Payne,A, And Cantor.P, (2000). E-Channel management: Electronic Customer Relationship
Rasouli, H., & Valmohammadi, C. (2019). Proposing a conceptual framework for customer identity and access management. Global Knowledge, Memory and Communication.
Sharma, G., & Lijuan, W. (2015). The effects of online service quality of e-commerce Websites on user satisfaction. The Electronic Library, 33(3), 468-485.
Sharma, H., & Aggarwal, A. G. (2019). Finding determinants of e-commerce success: a PLS-SEM approach. Journal of Advances in Management Research.
Sharma, H., & Aggarwal, A. G. (2019). Finding determinants of e-commerce success: a PLS-SEM approach. Journal of Advances in Management Research, 16(4), 453-471.
Sigala, M. (2018). Implementing social customer relationship management. International Journal of Contemporary Hospitality Management, 30(7), 2698-2726.
Statish Chander & Tedj Strick Land (2004). Technological Difference between CRM and E-CER
Stevenson, A., & Hamill, J. (2002). Internet forum. International Marketing Review, 19(2/3), 323.
Tam, C., Loureiro, A., Oliveira, T., Tam, C., Loureiro, A., & Oliveira, T. (2019). The individual performance outcome behind e-commerce: Integrating information systems success and overall trust. Individual performance outcome, 1.
Tan, X., Yen, D. C., & Fang, X. (2002). Internet integrated customer relationship management a key success factor for companies in the e-commerce arena. Journal of Computer Information Systems, 42(3), 77-86.
Thampi, S. M., Gelbukh, A., & Mukhopadhyay, J. (Eds.). (2014). Advances in signal processing and intelligent recognition systems. Berlin: Springer International Publishing.
Wang, Y. S. (2008). Assessing e‐commerce systems success: a respecification and validation of the DeLone and McLean model of IS success. Information Systems Journal, 18(5), 529-557.
Yager, R. R. (1993). Fuzzy screening systems. In Fuzzy Logic (pp. 251-261). Springer, Dordrecht.
Yan, H. B., & Ma, T. (2015). A fuzzy group decision making approach to new product concept screening at the fuzzy front end. International Journal of Production Research, 53(13), 4021-4049.
Zahoor, A., & Sahaf, M. A. (2018). Investigating causal linkages in the balanced scorecard: an Indian perspective. International Journal of Bank Marketing, 36(1), 184-207.