Evaluating the influence of advanced analytics on client management systems in UAE telecom firms
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Author(s)Amer MorshedLink to ORCID Index: https://orcid.org/0000-0002-9756-5854
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DOIhttp://dx.doi.org/10.21511/im.20(4).2024.04
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Article InfoVolume 20 2024, Issue #4, pp. 41-51
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Creative Commons Attribution 4.0 International License
Amid rapid technological advancements, the telecommunications sector in the United Arab Emirates increasingly adopts big data analytics to optimize customer relationship management. This study investigates the effects of big data on customer satisfaction, decision-making, operational efficiency, and ethical practices. Data from 296 stakeholders, including employees, management, and customers, were analyzed using structural equation modeling with the Analysis of Moment Structures.
The results demonstrate a strong positive correlation between big data integration and improved decision-making in customer relationship management (r = 0.75, p < 0.001), which significantly enhances customer satisfaction (r = 0.80, p < 0.001). Additionally, big data integration directly influences customer satisfaction (r = 0.42, p < 0.001), further validating its critical role. However, ethical data usage presents challenges, showing a negative correlation with customer satisfaction (r = –0.15, p < 0.05) and decision-making (r = –0.50, p < 0.001). Descriptive statistics indicate strong approval for big data integration (mean = 3.6) and decision-making (mean = 3.93), while ethical practices score lower (mean = 3.38), and the complexity of big data analytics remains high (mean = 4.43), revealing significant implementation barriers.
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JEL Classification (Paper profile tab)M30, M31, O33, C38
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References42
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Tables7
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Figures0
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- Table 1. Sample distribution
- Table 2. Demographic information
- Table 3. Descriptive statistics
- Table 4. Reliability analysis
- Table 5. Correlation matrix
- Table 6. Model fit indices
- Table 7. Path coefficients
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- Ali, H., & Morshed, A. (2024). Augmented reality integration in Jordanian fast-food apps: Enhancing brand identity and customer interaction amidst digital transformation. Journal of Infrastructure, Policy and Development, 8(5), 3856.
- Aljumah, A. I., Nuseir, M. T., & Alam, M. M. (2021). Organizational performance and capabilities to analyze big data: Do the ambidexterity and business value of big data analytics matter? Business Process Management Journal, 27(4), 1088-1107.
- Aloulou, M., Grati, R., Al-Qudah, A. A., & Al-Okaily, M. (2023). Does FinTech adoption increase the diffusion rate of digital financial inclusion? A study of the banking industry sector. Journal of Financial Reporting and Accounting, 22(2), 289-307.
- Barua, E., & Dutta, M. (2024). Privacy-preserving association rule mining: A survey of techniques for sensitive rule identification and enhanced data protection. International Journal of Computers and Applications, 46(4), 252-265.
- Bauer, C., Galvan, J. M., Hancock, T., Hunter, G. K., Nelson, C. A., Riley, J., & Tanner, E. C. (2023). Integrating technology within the sales-service ecosystem: The emergent sales techno-ecosystem. European Journal of Marketing, 58(3), 782-811.
- Bauer, J., Brüggmann, D., Klingelhöfer, D., Maier, W., Schwettmann, L., Weiss, D. J., & Groneberg, D. A. (2020). Access to intensive care in 14 European countries: A spatial analysis of intensive care need and capacity in the light of COVID-19. Intensive Care Medicine, 46, 2026-2034.
- Chatterjee, S., Chaudhuri, R., & Vrontis, D. (2022). Big data analytics in strategic sales performance: Mediating role of CRM capability and moderating role of leadership support. EuroMed Journal of Business, 17(3), 295-311.
- Chordiya, R., & Hubbell, L. (2023). Fostering internal pay equity through gender neutral job evaluations: A case study of the federal job evaluation system. Public Personnel Management, 52(1), 25-47.
- Comunian, S., Dongo, D., Milani, C., & Palestini, P. (2020). Air pollution and COVID-19: The role of particulate matter in the spread and increase of COVID-19’s morbidity and mortality. International Journal of Environmental Research and Public Health, 17(12), 4487.
- Cristescu, M. P., Mara, D. A., Culda, L. C., Nerișanu, R. A., Bâra, A., & Oprea, S.-V. (2023). The Impact of Data Science Solutions on the Company Turnover. Information, 14(10), 573.
- Elgendy, N., Elragal, A., & Päivärinta, T. (2022). DECAS: A modern data-driven decision theory for big data and analytics. Journal of Decision Systems, 31(4), 337-373.
- Elia, G., Polimeno, G., Solazzo, G., & Passiante, G. (2020). A multi-dimension framework for value creation through big data. Industrial Marketing Management, 90, 617-632.
- Guida, M., Caniato, F., Moretto, A., & Ronchi, S. (2023). The role of artificial intelligence in the procurement process: State of the art and research agenda. Journal of Purchasing and Supply Management, 29(2), 100823.
- Gupta, S., Justy, T., Kamboj, S., Kumar, A., & Kristoffersen, E. (2021). Big data and firm marketing performance: Findings from knowledge-based view. Technological Forecasting and Social Change, 171, 120986.
- Haddad, A., Ameen, A., Isaac, O., Alrajawy, I., Al-Shbami, A., & Midhun Chakkaravarthy, D. (2020). The Impact of Technology Readiness on the Big Data Adoption Among UAE Organisations. In Sharma, N., Chakrabarti, A., & Balas, V. E. (Eds.), Data Management, Analytics and Innovation (pp. 249-264). Singapore: Springer.
- Hashim, M. A., Che Ibrahim, C. K. I., Jaafar, N. A. L., Kordi, N. E., Haron, A. T., & Umeokafor, N. (2024). Building data driven culture for digital competitiveness in construction industry: A theoretical exploration. International Journal of Construction Management, 1-13.
- Hassine, M. B., & Youssef, A. B. (2023). Investigating the importance of big data use in the customer relationship management context. International Journal of Technology Marketing, 17(3), 276-295.
- Hayes, A. F., & Coutts, J. J. (2020). Use omega rather than Cronbach’s alpha for estimating reliability. But…. Communication Methods and Measures, 14(1), 1-24.
- Heuninckx, S., Meitern, M., Te Boveldt, G., & Coosemans, T. (2023). Practical problems before privacy concerns: How European energy community initiatives struggle with data collection. Energy Research & Social Science, 98, 103040.
- Jankovic, S. D., & Curovic, D. M. (2023). Strategic integration of artificial intelligence for sustainable businesses: Implications for data management and human user engagement in the digital era. Sustainability, 15(21), 15208.
- Jiang, Y., Feng, T., & Huang, Y. (2024). Antecedent configurations toward supply chain resilience: The joint impact of supply chain integration and big data analytics capability. Journal of Operations Management, 70(2), 257-284.
- Johora, F., Almalawi, D., Abdullah, M. N. A., Hossain, S., Shehadeh, Z. F., & Basak, A. K. (2023). Non-monotonic potential description of α+ 209Bi elastic scattering. Nuclear Physics A, 1031, 122610.
- Jum’a, L., Zimon, D., & Madzik, P. (2024). Impact of big data technological and personal capabilities on sustainable performance on Jordanian manufacturing companies: The mediating role of innovation. Journal of Enterprise Information Management, 37(2), 329-354.
- Kakeesh, D. F., Al-Weshah, G. A., & Alalwan, A. A. (2024). Entrepreneurial marketing and business performance in SMEs: The mediating role of competitive aggressiveness. Journal of Marketing Analytics.
- Kastouni, M. Z., & Lahcen, A. A. (2022). Big data analytics in telecommunications: Governance, architecture and use cases. Journal of King Saud University-Computer and Information Sciences, 34(6), 2758-2770.
- Khan, A. R., & Aziz, M. T. (2023). Harnessing Big Data for Precision Marketing: A Deep Dive into Customer Segmentation and Predictive Analytics in the Digital Era. AI, IoT and the Fourth Industrial Revolution Review, 13(7), 91-102.
- Kirova, V. (2023). The wind of change: A dynamic managerial capabilities perspective on the role of marketing managers as strategic change agents. Journal of Business Research, 160, 113817.
- Kokshagina, O., Le Masson, P., & Luo, J. (2024). Beyond the data fads: Impact of big data on contemporary innovation and technology management. In Technovation (Vol. 134, p. 103026). Elsevier.
- Ledro, C., Nosella, A., & Dalla Pozza, I. (2023). Integration of AI in CRM: Challenges and guidelines. Journal of Open Innovation: Technology, Market, and Complexity, 100151.
- Lehrer, C., Wieneke, A., Vom Brocke, J., Jung, R., & Seidel, S. (2018). How Big Data Analytics Enables Service Innovation: Materiality, Affordance, and the Individualization of Service. Journal of Management Information Systems, 35(2), 424-460.
- Magatef, S., Al-Okaily, M., Ashour, L., & Abuhussein, T. (2023). The impact of electronic customer relationship management strategies on customer loyalty: A mediated model. Journal of Open Innovation: Technology, Market, and Complexity, 9(4), 100149.
- Myers, S., Syrdal, H. A., Mahto, R. V., & Sen, S. S. (2023). Social religion: A cross-platform examination of the impact of religious influencer message cues on engagement – The Christian context. Technological Forecasting and Social Change, 191, 122442.
- Nuryanto, U., Basrowi, B., & Quraysin, I. (2024). Big data and IoT adoption in shaping organizational citizenship behavior: The role of innovation organizational predictor in the chemical manufacturing industry. International Journal of Data and Network Science, 8(1), 225-268.
- Poma, L., Shawwa, H. A., & Maini, E. (2020). Industry 4.0 and big data: Role of government in the advancement of enterprises in Italy and UAE. International Journal of Business Performance Management, 21(3), 261.
- Qi, Y., Sajadi, S. M., Baghaei, S., Rezaei, R., & Li, W. (2024). Digital technologies in sports: Opportunities, challenges, and strategies for safeguarding athlete wellbeing and competitive integrity in the digital era. Technology in Society, 102496.
- Ram, J., & Zhang, Z. (2022). Examining the needs to adopt big data analytics in B2B organizations: Development of propositions and model of needs. Journal of Business & Industrial Marketing, 37(4), 790-809.
- Rane, N. (2023). Enhancing Customer Loyalty through Artificial Intelligence (AI), Internet of Things (IoT), and Big Data Technologies: Improving Customer Satisfaction, Engagement, Relationship, and Experience.
- Rosário, A. T., & Dias, J. C. (2023). How has data-driven marketing evolved: Challenges and opportunities with emerging technologies. International Journal of Information Management Data Insights, 3(2), 100203.
- Umrani, W. A., Tariq, B., Bodolica, V., Nawaz, A., & Pahi, M. H. (2023). Corporate entrepreneurship in banks: The role of technology self-efficacy and technology-based customer relationship management. Journal of General Management, 030630702311714.
- Wassouf, W. N., Alkhatib, R., Salloum, K., & Balloul, S. (2020). Predictive analytics using big data for increased customer loyalty: Syriatel Telecom Company case study. Journal of Big Data, 7(1), 29.
- Williamson, S. M., & Prybutok, V. (2024). Balancing Privacy and Progress: A Review of Privacy Challenges, Systemic Oversight, and Patient Perceptions in AI-Driven Healthcare. Applied Sciences, 14(2), 675.
- Zakaria, A. F., Lim, S. C. J., & Aamir, M. (2024). A pricing optimization modelling for assisted decision making in telecommunication product-service bundling. International Journal of Information Management Data Insights, 4(1), 100212.
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Factors affecting service quality at Vietnamese retail banks
Tran Phi Hoang
doi: http://dx.doi.org/10.21511/bbs.13(2).2018.04
Banks and Bank Systems Volume 13, 2018 Issue #2 pp. 39-48 Views: 6409 Downloads: 1352 TO CITE АНОТАЦІЯSustainable growth and development can be the most important lesson that banks have learned in recent decades. Banks would gain many benefits, win the competition and develop sustainably if there have been more and more loyal customers. Customer satisfaction will help build customer loyalty. In order to have loyal customers, service quality must be good. Quality customer service of the bank is to ensure customer satisfaction and take their needs into consideration to improve service quality. High customer service quality will generate value not only to meet customer needs but also the expectations of customers and make banks more prominent than their competitors. This study identifies factors that affect customer satisfaction with the service quality at Vietnamese retail banks. The results are obtained by qualitative and quantitative method. The research model with a questionnaire consisting of 22 variables, 5 scales for a survey of 554 customers, is identified and developed through interviews with experts and group discussions. The findings show that customer satisfaction with the service quality at retail banks is influenced by “reliability”, “responsiveness”, “empathy”, “security”, and “tangibles”. Based on the findings, solutions for improving service quality are proposed for Vietnamese retail banks.
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Antecedents of behavioral intention to use online food delivery services: An empirical investigation
Vinish P. ,
Prakash Pinto ,
Iqbal Thonse Hawaldar 
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Slima Pinto
doi: http://dx.doi.org/10.21511/im.17(1).2021.01
The online food delivery market in India perseveres to grow at a sustained pace. The business has unique dynamics and challenges with the spike in orders during weekends, meeting delivery schedules during peak demand, offering deep discounts to address wavering customer loyalty, reducing cash burns, and managing food quality inconsistency. In contrast, the fast-paced life and the rise of millennials in the workforce is likely to assure a promising future for the food aggregators. The above backdrop has led the researchers to pursue this study. An empirical study was carried out to explore the consumption occasion and the antecedents of online food ordering in the select cities in Karnataka, India. The data was collected from 385 respondents through telephonic and mail survey using a structured questionnaire. The responses were analyzed using exploratory factor analysis and multiple regression. The result of the study indicated a positive association between the constructs ‘buying motives’, ‘aggregator attractiveness’, and customer satisfaction. The variation in customers` satisfaction is largely attributable to the convenience of order placing, food quality, availability of food and restaurant reviews, offers and discounts, faster home delivery, and the wide choice of restaurants listed on the aggregator’s website. Additionally, the aggregator attractiveness showed a higher impact on customer satisfaction as compared to buying motives.
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Retraction: Leaders and decision making: a study of the drivers of courage
Rasoava Rijamampianina
doi: http://dx.doi.org/10.21511/ppm.16(1).2018.31
Problems and Perspectives in Management Volume 16, 2018 Issue #1 pp. 320-329 Views: 2080 Downloads: 192 TO CITE АНОТАЦІЯRetracted on the 15th of October, 2020 by the Journal’s Editor-in-Chief request dated October 12, 2020. The type of retraction – plagiarism.
The journal was asked to retract this article because of plagiarism. The request came from the author of the article. The author informed the journal that original idea published in this paper wasn’t his and asked to remove the article.
