International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

Frequency: 12
line decor
  
line decor

 Volume 10, Issue 2 (February 2023), Pages: 128-138

----------------------------------------------

 Original Research Paper

 Application of the updated DeLone and McLean IS success method to investigate e-CRM effectiveness

 Author(s): 

 Elham Abdulwahab Anaam 1, *, Ali Ahmed H. Alyam 2, Yahya Ali Abdelrahman Ali 3, Mohammed Dauwed 4, Abdullah Alshahrani 5, Wael Jabbar Abed Al-Nidawi 6

 Affiliation(s):

 1Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Malaysia
 2Department of Information System, College of Computer Science and Information Systems, Najran University, Najran, Saudi Arabia
 3Department of Information System, Faculty of Computer Science and Information System, Najran University, Najran, Saudi Arabia
 4Department of Medical Instrumentations Techniques Engineering, Dijlah University College, Baghdad, Iraq
 5Department of Computer Science and Artificial Intelligence, College of Computer Science and Engineering, University of Jeddah, Jeddah, Saudi Arabia
 6Computer Techniques Engineering Department, Al-Mustaqbal University College, Hillah, Iraq

  Full Text - PDF          XML

 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0002-1497-5509

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2023.02.016

 Abstract:

Information and communication technology has a significant influence on employee procedures. Businesses are investing in e-CRM technologies, yet it is difficult to assess the performance of their e-CRM platforms. The DeLone and McLean Information Systems Success framework can be modified to the current e-CRM assessment difficulties. The new framework's different aspects provide a concise framework for organizing the e-CRM key metrics identified in this study. The purpose of this study is to apply and verify that the Updated DeLone and McLean IS Model can be employed to explain e-CRM adoption among employees, along with the extended Updated DeLone and McLean Model with its five output factors, namely system quality, service quality, information quality, ease of use employee satisfaction. For this study, data was collected from 300 employees working on e-CRM and the data were analyzed using PLS-SEM. The experimental framework has a significant effect and shows that most of the hypotheses of the study are supported. Moreover, the framework contributes to the area of the success of e-CRM and individual performance.

 © 2022 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Updated DeLone and McLean model, E-CRM, Employee satisfaction, Individual performance

 Article History: Received 22 May 2022, Received in revised form 7 October 2022, Accepted 4 November 2022

 Acknowledgment 

No Acknowledgment.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Anaam EA, Alyam AAH, Ali YAA, Dauwed M, Alshahrani A, and Al-Nidawi WJA (2023). Application of the updated DeLone and McLean IS success method to investigate e-CRM effectiveness. International Journal of Advanced and Applied Sciences, 10(2): 128-138

 Permanent Link to this page

 Figures

 Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6 

 Tables

 Table 1 Table 2 

----------------------------------------------    

 References (59)

  1. Abdulfattah F (2012). The effect of electronic customer relationship on customer satisfaction a study in web banking in Saudi Arabia. Ph.D. Dissertation, University of Huddersfield, Huddersfield, UK.   [Google Scholar]
  2. Akinnuwesi BA, Uzoka FM, Olabiyisi SO, Omidiora EO, and Fiddi P (2013). An empirical analysis of end‐user participation in software development projects in a developing country context. The Electronic Journal of Information Systems in Developing Countries, 58(1): 1-25. https://doi.org/10.1002/j.1681-4835.2013.tb00413.x   [Google Scholar]
  3. Alatawi FMH, Dwivedi YK, and Williams MD (2013). Developing a conceptual model for investigating adoption of knowledge management system in Saudi Arabian public sector. International Journal of Business Information Systems, 14(2): 135-163. https://doi.org/10.1504/IJBIS.2013.056121   [Google Scholar]
  4. Allozi A, Alryalat H, and Hadi WE (2016). Applying electronic customer processes to electronic customer retention (Field study in Jordanian telecommunication sector). International Journal of Business and Management, 11(1): 152-163. https://doi.org/10.5539/ijbm.v11n1p152   [Google Scholar]
  5. Alnassar BAY (2014). The factors that impact of e-customer relationship management performance (e-CRM) of mobile services in Jordan. Journal of Management Research, 6(3): 199-213. https://doi.org/10.5296/jmr.v6i3.4751   [Google Scholar]
  6. Alshibly HH (2015). Customer perceived value in social commerce: An exploration of its antecedents and consequences. Journal of Management Research, 7(1): 17-37. https://doi.org/10.5296/jmr.v7i1.6800   [Google Scholar]
  7. Al-Weshah GA, Al-Manasrah E, and Al-Qatawneh M (2019). Customer relationship management systems and organizational performance: Quantitative evidence from the Jordanian telecommunication industry. Journal of Marketing Communications, 25(8): 799-819. https://doi.org/10.1080/13527266.2018.1449007   [Google Scholar]
  8. Anaam EA, Abu Bakar KA, Mohd Satar NS, and Ma’arif MY (2020a). Investigating the electronic customer relationship management success key factors in the telecommunication companies: A pilot study. Journal of Computational and Theoretical Nanoscience, 17(2-3): 1460-1463. https://doi.org/10.1166/jctn.2020.8825   [Google Scholar]
  9. Anaam EA, Bakar KAA, and Satar NSM (2020b). A model of electronic customer relationship management system adoption in telecommunication companies. Amazonia Investiga, 9(35): 61-73. https://doi.org/10.34069/AI/2020.35.11.5   [Google Scholar]
  10. Anaam EA, Bakar KAA, Satar NSM, and Kamrul M (2021a). Critical success factors for electronic customer relationship management success adoption: Telecommunication companies case study. International Journal of Advanced and Applied Sciences, 8(10): 116-130. https://doi.org/10.21833/ijaas.2021.10.013   [Google Scholar]
  11. Anaam EA, Khairul A, Abu Bakar NS, and Mohd S (2018). A theoretical review of conceptual model for E-CRM success in telecommunication companies. International Journal of Engineering and Technology, 7(4): 6381-6390.   [Google Scholar]
  12. Anaam EA, Magableh MNY, and Ridha A (2022). Key factors influence on decision making to IoT adoption in telecommunication companies: A review. International Journal of Engineering and Technology, 11(1): 14-19.   [Google Scholar]
  13. Anaam EA, Magableh MNY, Hamdi M, Hmoud AYR, and Alshalabi H (2021b). Data mining techniques with electronic customer relationship management for telecommunication company. Amazonia Investiga, 10(48): 288-304. https://doi.org/10.34069/AI/2021.48.12.30   [Google Scholar]
  14. Awa HO, Awara NF, and Lebari ED (2015). Critical factors inhibiting electronic commerce (EC) adoption in Nigeria: A study of operators of SMEs. Journal of Science and Technology Policy Management, 6(2): 143-164. https://doi.org/10.1108/JSTPM-07-2014-0033   [Google Scholar]
  15. Bin-Nashwan SA and Hassan H (2017). Impact of customer relationship management (CRM) on customer satisfaction and loyalty: A systematic review. Journal of Advanced Research in Business and Management Studies, 6(1): 86-107.   [Google Scholar]
  16. Chang IC, Li YC, Hung WF, and Hwang HG (2005). An empirical study on the impact of quality antecedents on tax payers' acceptance of Internet tax-filing systems. Government Information Quarterly, 22(3): 389-410. https://doi.org/10.1016/j.giq.2005.05.002   [Google Scholar] PMid:32288164 PMCid:PMC7125980
  17. Chang WY (2014). A literature review of wind forecasting methods. Journal of Power and Energy Engineering, 2(4): 161-168. https://doi.org/10.4236/jpee.2014.24023   [Google Scholar]
  18. Chinje NB (2013). Customer relationship management (CRM) implementation within the banking and mobile telephony sectors of Nigeria and South Africa. Ph.D. Dissertation, University of the Witwatersrand, Johannesburg, South Africa.   [Google Scholar]
  19. Dauwed MA, Yahaya J, Mansor Z, and Hamdan AR (2018). Determinants of internet of things services utilization in health information exchange. Journal of Engineering and Applied Sciences, 13(24): 10490-10501.   [Google Scholar]
  20. DeLone WH and McLean ER (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1): 60-95. https://doi.org/10.1287/isre.3.1.60   [Google Scholar]
  21. DeLone WH and McLean ER (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4): 9-30. https://doi.org/10.1080/07421222.2003.11045748   [Google Scholar]
  22. Dubey A and Srivastava AK (2016). Impact of service quality on customer loyalty-A study on telecom sector in India. IOSR Journal of Business and Management (IOSR-JBM), 18(2): 45-55.   [Google Scholar]
  23. Dubihlela J and Sandada M (2014). Impact of strategic planning on small and medium-sized enterprises’ (SMEs) performance: The role of employee participation, implementation incentives and evaluation and control. Journal of Economics, 5(1): 45-55. https://doi.org/10.1080/09765239.2014.11884983   [Google Scholar]
  24. Evanschitzky H, Ramaseshan B, Woisetschläger DM, Richelsen V, Blut M, and Backhaus C (2012). Consequences of customer loyalty to the loyalty program and to the company. Journal of the Academy of Marketing Science, 40(5): 625-638. https://doi.org/10.1007/s11747-011-0272-3   [Google Scholar]
  25. Ghobakhloo M and Hong TS (2014). IT investments and business performance improvement: The mediating role of lean manufacturing implementation. International Journal of Production Research, 52(18): 5367-5384. https://doi.org/10.1080/00207543.2014.906761   [Google Scholar]
  26. Ghobakhloo M, Hong TS, Sabouri MS, and Zulkifli N (2012). Strategies for successful information technology adoption in small and medium-sized enterprises. Information, 3(1): 36-67. https://doi.org/10.3390/info3010036   [Google Scholar]
  27. Govindan K, Khodaverdi R, and Jafarian A (2013). A fuzzy multi criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach. Journal of Cleaner Production, 47: 345-354. https://doi.org/10.1016/j.jclepro.2012.04.014   [Google Scholar]
  28. Hair J, Hollingsworth CL, Randolph AB, and Chong AY (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management and Data Systems, 117(3): 442-458. https://doi.org/10.1108/IMDS-04-2016-0130   [Google Scholar]
  29. Heeks R (2006). Understanding and measuring eGovernment: International benchmarking studies. In the UNDESA workshop, “E-Participation and E-Government: Understanding the Present and Creating the Future”, Budapest, Hungary: 27-28.   [Google Scholar]
  30. Hosseini SY, Bahreini Zadeh M, Ziaei Bideh A (2013). Providing a multidimensional measurement model for assessing mobile telecommunication service quality (MS-Qual). Iranian Journal of Management Studies (IJMS), 6(2): 7-29.   [Google Scholar]
  31. Huang PL, Lee BC, and Chen CC (2019). The influence of service quality on customer satisfaction and loyalty in B2B technology service industry. Total Quality Management and Business Excellence, 30(13-14): 1449-1465. https://doi.org/10.1080/14783363.2017.1372184   [Google Scholar]
  32. Joshi DV and Sharma R (2015). CRM in telecommunication industry: Issues and challenges in Indian context. International Journal of Research in Management, 5(2): 90-113.   [Google Scholar]
  33. Jun M, Yang Z, and Kim D (2004). Customers' perceptions of online retailing service quality and their satisfaction. International Journal of Quality and Reliability Management, 21(8): 817-840. https://doi.org/10.1108/02656710410551728   [Google Scholar]
  34. Kabak Y and Dogac A (2010). A survey and analysis of electronic business document standards. ACM Computing Surveys, 42(3): 1-31. https://doi.org/10.1145/1670679.1670681   [Google Scholar]
  35. Kianto A, Vanhala M, and Heilmann P (2016). The impact of knowledge management on job satisfaction. Journal of Knowledge Management, 20(4): 621-636. https://doi.org/10.1108/JKM-10-2015-0398   [Google Scholar]
  36. Kim KH, Kabir E, and Kabir S (2015). A review on the human health impact of airborne particulate matter. Environment International, 74: 136-143. https://doi.org/10.1016/j.envint.2014.10.005   [Google Scholar] PMid:25454230
  37. Kline MA (2015). How to learn about teaching: An evolutionary framework for the study of teaching behavior in humans and other animals. Behavioral and Brain Sciences, 38: e31. https://doi.org/10.1017/S0140525X14000090   [Google Scholar] PMid:24856634
  38. Kuegler M, Smolnik S, and Kane G (2015). What’s in IT for employees? Understanding the relationship between use and performance in enterprise social software. The Journal of Strategic Information Systems, 24(2): 90-112. https://doi.org/10.1016/j.jsis.2015.04.001   [Google Scholar]
  39. Landrum HT, Prybutok VR, Strutton D, and Zhang X (2008). Examining the merits of usefulness versus use in an information service quality and information system success web-based model. Information Resources Management Journal (IRMJ), 21(2): 1-17. https://doi.org/10.4018/irmj.2008040101   [Google Scholar]
  40. Mala J and Černá Ľ (2012). Information quality, its dimension and the basic criteria for assessing information quality. Trnava Slovak University of Technology in Bratislava, 20: 86-93. https://doi.org/10.2478/v10186-012-0015-4   [Google Scholar]
  41. Mohammadi R and Wit EC (2019). BDgraph: An R package for Bayesian structure learning in graphical models. Journal of Statistical Software, 89(3): 1-30. https://doi.org/10.18637/jss.v089.i03   [Google Scholar]
  42. Mueller H and Nyfeler T (2011). Quality in patent information retrieval–Communication as the key factor. World Patent Information, 33(4): 383-388. https://doi.org/10.1016/j.wpi.2011.06.012   [Google Scholar]
  43. Navimipour NJ and 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. https://doi.org/10.1016/j.chb.2015.10.036   [Google Scholar]
  44. Nikou SA and Economides AA (2016). The impact of paper-based, computer-based and mobile-based self-assessment on students' science motivation and achievement. Computers in Human Behavior, 55: 1241-1248. https://doi.org/10.1016/j.chb.2015.09.025   [Google Scholar]
  45. Pandit A and Vilches-Montero S (2016). Are reward cards just a business deal? The role of calculative versus emotional card commitment in driving store loyalty. Journal of Retailing and Consumer Services, 31: 355-360. https://doi.org/10.1016/j.jretconser.2016.05.001   [Google Scholar]
  46. Park BI (2011a). Knowledge transfer capacity of multinational enterprises and technology acquisition in international joint ventures. International Business Review, 20(1): 75-87. https://doi.org/10.1016/j.ibusrev.2010.06.002   [Google Scholar]
  47. Park HM (2011b). Practical guides to panel data modeling: A step-by-step analysis using stata. Public Management and Policy Analysis Program, Graduate School of International Relations, International University of Japan, 12: 1-52.   [Google Scholar]
  48. Petter S, DeLone W, and McLean E (2008). Measuring information systems success: Models, dimensions, measures, and interrelationships. European Journal of Information Systems, 17(3): 236-263. https://doi.org/10.1057/ejis.2008.15   [Google Scholar]
  49. Poelmans S and Reijers HA (2009). Assessing workflow management systems: A quantitative analysis of a worfklow evaluation model. In the 11th International Conference on Enterprise Information Systems, Milan, Italy: 183-189. https://doi.org/10.5220/0002005401830189   [Google Scholar]
  50. Raza A, Ilyas MI, Rauf R, and Qamar R (2012). Relationship between corporate social responsibility (CSR) and corporate financial performance (CFP): Literature review approach. Elixir Financial Management, 46(9): 8404-8409.   [Google Scholar]
  51. Rigo GE, Pedron CD, Caldeira M, and Araújo CC (2016). CRM adoption in a higher education institution. JISTEM-Journal of Information Systems and Technology Management, 13: 45-60. https://doi.org/10.4301/S1807-17752016000100003   [Google Scholar]
  52. Salaün Y and Flores K (2001). Information quality: Meeting the needs of the consumer. International Journal of Information Management, 21(1): 21-37. https://doi.org/10.1016/S0268-4012(00)00048-7   [Google Scholar]
  53. Sönmez F (2018). Technology acceptance of business intelligence and customer relationship management systems within institutions operating in capital markets. International Journal of Academic Research in Business and Social Sciences, 8(2): 400-422. https://doi.org/10.6007/IJARBSS/v8-i2/3882   [Google Scholar]
  54. Wang Y, Chen C, Wang J, and Baldick R (2015). Research on resilience of power systems under natural disasters-A review. IEEE Transactions on Power Systems, 31(2): 1604-1613. https://doi.org/10.1109/TPWRS.2015.2429656   [Google Scholar]
  55. Wang YS and Liao YW (2007). The conceptualization and measurement of m-commerce user satisfaction. Computers in Human Behavior, 23(1): 381-398. https://doi.org/10.1016/j.chb.2004.10.017   [Google Scholar]
  56. Wu IL and Wu KW (2005). A hybrid technology acceptance approach for exploring e-CRM adoption in organizations. Behaviour and Information Technology, 24(4): 303-316. https://doi.org/10.1080/0144929042000320027   [Google Scholar]
  57. Yang X, Peterson L, Thieringer R, Deignan JL, Wang X, Zhu J, and Lum PY (2010). Identification and validation of genes affecting aortic lesions in mice. The Journal of Clinical Investigation, 120(7): 2414-2422. https://doi.org/10.1172/JCI42742   [Google Scholar] PMid:20577049 PMCid:PMC2898611
  58. Yusof MM (2015). A case study evaluation of a critical care information system adoption using the socio-technical and fit approach. International Journal of Medical Informatics, 84(7): 486-499. https://doi.org/10.1016/j.ijmedinf.2015.03.001   [Google Scholar] PMid:25881560
  59. Yusof MM, Kuljis J, Papazafeiropoulou A, and Stergioulas LK (2008). An evaluation framework for health information systems: Human, organization and technology-fit factors (HOT-fit). International Journal of Medical Informatics, 77(6): 386-398. https://doi.org/10.1016/j.ijmedinf.2007.08.011   [Google Scholar] PMid:17964851