A Framework to Predict the Adoption of Social Customer Relationship Management in Small and Medium Enterprises

Saeed Farahani, HamidReza Ahmadifar, Azam Ahmadyan

Abstract


This research develops a new model for the use of Social Customer Relationship Management in the Iranian Small and Medium Enterprises. Our model is based on Information Process components (Information Capture, Information Use, and Information Sharing), Technology Acceptance Model and several factors from the literature. By developing ten hypotheses, this model investigates how Social Customer Relationship Management can be adopted by the Small and Medium Enterprises for their business purposes. To evaluate the hypotheses and verify the research model, a survey questionnaire was conducted and the data was collected from 100 Iranian Small and Medium Enterprises. We use Partial Least Squares Structural Equation Modeling approach to analysis the data. The results revealed that all of the proposed hypotheses are accepted. The results on the data analysis are discussed and the limitation and the future work are presented. 


Keywords


Social Customer Relationship Management, Small and Medium Enterprises, Information Process, Partial Least Squares Structural Equation Modeling

Full Text:

Abstract PDF

References


Ahani, A., Rahim, N. Z. A., & Nilashi, M. (2017a). Firm performance through social customer relationship management: Evidence from small and medium enterprises. Paper presented at the Research and Innovation in Information Systems (ICRIIS), 2017 International Conference on.

Ahani, A., Rahim, N. Z. A., & Nilashi, M. (2017b). Forecasting social CRM adoption in SMEs: A combined SEM-neural network method. Computers in Human Behavior, 75, 560-578.

Ali, F., Rasoolimanesh, S. M., Sarstedt, M., Ringle, C. M., & Ryu, K. (2018). An assessment of the use of partial least squares structural equation modeling (PLS-SEM) in hospitality research. International Journal of Contemporary Hospitality Management, 30(1), 514-538.

Askool, S., & Nakata, K. (2011). A conceptual model for acceptance of social CRM systems based on a scoping study. Ai & Society, 26(3), 205-220.

Balaji, M., Roy, S. K., & Lassar, W. M. (2017). Language divergence in service encounters: Revisiting its influence on word-of-mouth. Journal of Business Research, 72, 210-213.

Dalvi-Esfahani, M., Ramayah, T., & Nilashi, M. (2017). Modelling upper echelons’ behavioural drivers of Green IT/IS adoption using an integrated Interpretive Structural Modelling–Analytic Network Process approach. Telematics and Informatics, 34(2), 583-603.

Dangelico, R. M., Pujari, D., & Pontrandolfo, P. (2017). Green product innovation in manufacturing firms: A sustainabilityâ€oriented dynamic capability perspective. Business Strategy and the Environment, 26(4), 490-506.

Greenberg, P. (2010). The impact of CRM 2.0 on customer insight. Journal of Business & Industrial Marketing, 25(6), 410-419.

Harrigan, P., & Miles, M. (2014). From e-CRM to s-CRM. Critical factors underpinning the social CRM activities of SMEs. Small Enterprise Research, 21(1), 99-116.

Hasani, T., Bojei, J., & Dehghantanha, A. (2017). Investigating the antecedents to the adoption of SCRM technologies by start-up companies. Telematics and Informatics, 34(5), 655-675.

Heller Baird, C., & Parasnis, G. (2011). From social media to social customer relationship management. Strategy & leadership, 39(5), 30-37.

Hur, K., Kim, T. T., Karatepe, O. M., & Lee, G. (2017). An exploration of the factors influencing social media continuance usage and information sharing intentions among Korean travellers. Tourism Management, 63, 170-178.

Malthouse, E. C., Haenlein, M., Skiera, B., Wege, E., & Zhang, M. (2013). Managing customer relationships in the social media era: Introducing the social CRM house. Journal of Interactive Marketing, 27(4), 270-280.

Mardani, N., Mardani, A., & Nilashi, M. (2017). Evaluating the Knowledge Management Practices in State Welfare Organization (Behzisti): Application of Fuzzy MCDM Approach. Journal of Soft Computing and Decision Support Systems, 4(3), 1-20.

Mohammed, F., Ibrahim, O., Nilashi, M., & Alzurqa, E. (2017). Cloud computing adoption model for e-government implementation. Information Development, 33(3), 303-323.

Munir, F. F. A. (2018). Reliability and Validity Analysis on the Relationship between Learning Space, Student’s Satisfaction and Perceived Performance Using SMART-PLS. International Journal of Academic Research in Business and Social Sciences, 8(1), 775-783.

Nilashi, M., Jannach, D., bin Ibrahim, O., Esfahani, M. D., & Ahmadi, H. (2016). Recommendation quality, transparency, and website quality for trust-building in recommendation agents. Electronic Commerce Research and Applications, 19, 70-84.

Payne, A., & Frow, P. (2005). A strategic framework for customer relationship management. Journal of Marketing, 69(4), 167-176.

Trainor, K. J., Andzulis, J. M., Rapp, A., & Agnihotri, R. (2014). Social media technology usage and customer relationship performance: A capabilities-based examination of social CRM. Journal of Business Research, 67(6), 1201-1208.

Yadegaridehkordi, E., Hourmand, M., Nilashi, M., Shuib, L., Ahani, A., & Ibrahim, O. (2018). Influence of big data adoption on manufacturing companies' performance: An integrated DEMATEL-ANFIS approach. Technological Forecasting and Social Change.

Yadegaridehkordi, E., Nilashi, M., Nasir, M. H. N. B. M., & Ibrahim, O. (2018). Predicting determinants of hotel success and development using Structural Equation Modelling (SEM)-ANFIS method. Tourism Management, 66, 364-386.

Yadegaridehkordi, E., Shuib, L., Nilashi, M., & Asadi, S. (2018). Decision to adopt online collaborative learning tools in higher education: A case of top Malaysian universities. Education and Information Technologies, 1-24.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.