Privacy and security in mobile technology: A bibliometric analysis for marketing strategies
References
- Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., & Ayyash, M. (2015). Internet of Things: A survey on enabling technologies, protocols, and applications. IEEE Communications Surveys & Tutorials, 17(4), 2347–2376. doi:
10.1109/COMST.2015.2444095 . - Alhitmi, H. K., Mardiah, A., Al-Sulaiti, K. I., & Abbas, J. (2024). Data security and privacy concerns of AI-driven marketing in the context of economics and business field: An exploration into possible solutions. Cogent Business & Management, 11(1), 2393743. doi:
10.1080/23311975.2024.2393743 . - Ali, J., & Sofi, S. A. (2022). Blockchain enabled architecture with selective consensus mechanisms for iot based saffron-agri value chain. Scalable computing-practice and experience
10.12694/scpe.v23i4.2038 . - Alkahtani, M., Khalid, Q. S., Jalees, M., Omair, M., Hussain, G., & Pruncu, C. I. (2021). E-agricultural supply chain management coupled with blockchain effect and cooperative strategies. Sustainability, 13(2), 816. doi:
10.3390/su13020816 . - AlRyalat, S. A., Malkawi, L., & Momani, S. (2019). Comparing bibliometric analysis using PubMed, scopus, and web of science databases. Journal of Visualized Experiments, 152, e58494. doi:
10.3791/58494 . - Aria, M., & Cuccurullo, C. (2017, November). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. doi:
10.1016/j.joi.2017.08.007 . - Ayaz, T. B., Özara, M. F., Sezer, E., Çelik, A. E., & Akbulut, A. (2024, July). Enhancing targeting in CRM campaigns through explainable AI. In International Conference on Intelligent and Fuzzy Systems (pp. 203–214). Springer Nature Switzerland. doi:
10.1007/978-3-031-70018-7_23 . - Bakar, M. S. A., & Bidin, R. (2014). Technology acceptance and purchase intention towards movie mobile advertising among youth in Malaysia. Procedia-Social and Behavioral Sciences, 130, 558–567. doi:
10.1016/j.sbspro.2014.04.065 . - Banerjee, S. (2019). Geosurveillance, location privacy, and personalization. Journal of Public Policy & Marketing, 38(4), 484–499 doi:
10.1177/0743915619860137 . - Benslama, T., & Jallouli, R. (2020, June). Clustering of social media data and marketing decisions. In International Conference on Digital Economy (pp. 53–65). Springer International Publishing. doi:
10.1007/978-3-030-64642-4_5 . - Benslama, T., & Jallouli, R. (2022). Social media data analytics for marketing strategies: The path from data to value. Journal of Telecommunications and the Digital Economy, 10(2), 96–110. doi:
10.18080/jtde.v10n2.523 . - Benslama, T., & Jallouli, R. (2024). An empirical study of the impact of social media data analytics on marketing strategy: Which social media data analytics metrics to select?. Journal of Telecommunications and the Digital Economy, 12(1), 575–594. doi:
10.18080/jtde.v12n1.830 . - Beresford, A. R., & Stajano, F. (2004). Location privacy in pervasive computing. IEEE Pervasive Computing, 2(1), 46–55. doi:
10.1109/MPRV.2003.1186725 . - Bodorik, P., Liu, C., & Jutla, D. (2023). TABS: Transforming automatically BPMN models into blockchain smart contracts. Blockchain: Research and Applications, 4(1), 100115. doi:
10.1016/j.bcra.2022.100115 . - Boukis, A. (2020). Exploring the implications of blockchain technology for brand-consumer relationships: A future research agenda. Journal of Product and Brand Management, 29(3), 307320. doi:
10.1108/JPBM-03-2018-1780 . - Buck, C., & Burster, S. (2017). App information privacy concerns. Twenty-third Americas Conference on Information Systems.
- Budiarto, R., Alqarni, A. A., Alzahrani, M. Y., Pasha, M. F., Firdhous, M. F. M., & Stiawan, D. (2022). User behavior traffic analysis using a simplified memory-prediction framework. Computers, Materials and Continua, 70(2), 2679–2698. doi:
10.32604/cmc.2022.019847 . - Callon, M., Courtial, J. P., & Laville, F. (1991). Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemistry. Scientometrics, 22(1), 155–205. doi:
10.1007/BF02019280 . - Capkun, S., & Hubaux, J.-P. (2006). Secure positioning in wireless networks. IEEE Journal on Selected Areas in Communications, 24(2), 221–232. doi:
10.1109/JSAC.2005.861380 . - Chaabouni, N., Mosbah, M., Zemmari, A., Sauvignac, C., & Faruki, P. (2019). Network intrusion detection for IoT security based on learning techniques. IEEE Communications Surveys and Tutorials, 21(3), 2671–2701. doi:
10.1109/COMST.2019.2896380 . - Chen, C.-L., Deng, Y.-Y., Weng, W., Zhou, M., & Sun, H. (2021). A blockchain-based intelligent anti-switch package in tracing logistics systems. The Journal of Supercomputing, 77(7), 7791–7832. doi:
10.1007/s11227-020-03558-7 . - Cheng, X., Liu, T., Shu, F., Ma, C., Li, J., & Wang, J. (2022). Providing location information at edge networks: A federated learning-based approach. IEEE Network, 36(5), 114–120. doi:
10.1109/MNET.001.2200212 . - Cheng, Y., Mei, S., Zhong, W., & Gao, X. (2023). Managing consumer privacy risk: The effects of privacy breach insurance. Electronic Commerce Research, 23(2), 807–841. doi:
10.1007/s10660-021-09492-x . - Cheng, W. M., & Wang, S. M. (2021). Research on the general algorithm and benefit of real-time positioning advertising system-based on the use of 5G base station data. Future Internet, 13(8), 187. doi:
10.3390/fi13080187 . - Clark, J., Paiement, J. F., & Provost, F. (2023). Who’s watching TV? Information Systems Research, 34(4), 1622–1640. doi:
10.1287/isre.2023.1204 . - Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field. Journal of Informetrics, 5(1), 146–166. doi:
10.1016/j.joi.2010.10.002 . - Cooper, D. A., Yalcin, T., Nistor, C., Macrini, M., & Pehlivan, E. (2023). Privacy considerations for online advertising: A stakeholder’s perspective to programmatic advertising. Journal of Consumer Marketing, 40(2), 235–247. doi:
10.1108/JCM-04-2021-4577 . - De Sousa, A., Moro, S., Pereira, R., & Prati, A. (2023). Cluster-based approaches toward developing a customer loyalty program in a private security company. Applied Sciences (Basel), 14(1), 78. doi:
10.3390/app14010078 . - Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009). ImageNet: A large-scale hierarchical image database. 2009 IEEE Conference on Computer Vision and Pattern Recognition (pp. 248–255). doi:
10.1109/CVPR.2009.5206848 . - Dhar, S., & Bose, I. (2020). Securing IoT devices using zero trust and blockchain. Journal of Organizational Computing and Electronic Commerce, 31(1), 18–34. doi:
10.1080/10919392.2020.1831870 . - Dionysis, S., Chesney, T., & McAuley, D. (2022). Examining the influential factors of consumer purchase intentions for blockchain traceable coffee using the theory of planned behaviour. British Food Journal, 124(12), 4304–4322. doi:
10.1108/BFJ-05-2021-0541 . - Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. doi:
10.1016/j.jbusres.2021.04.070 . - Dwork, C., McSherry, F., Nissim, K., & Smith, A. (2006). Calibrating noise to sensitivity in private data analysis. In S. Halevi & T. Rabin (Eds.), Theory of cryptography (Vol. 3876, pp. 265–284). Springer Berlin Heidelberg. doi:
10.1007/11681878_14 . - Ebrahimi, F., Tushev, M., & Mahmoud, A. (2021). Mobile app privacy in software engineering research: A systematic mapping study. Information and Software Technology, 133, 106466. doi:
10.1016/j.infsof.2020.106466 . - Egghe, L. (2006, October). Theory and practice of the g-index. Scientometrics, 69(1), 131–152. doi:
10.1007/s11192-006-0144-7 . - Esposito, C., & Choi, C. (2017). Signaling game based strategy for secure positioning in wireless sensor networks. Pervasive and Mobile Computing, 40, 611–627. doi:
10.1016/j.pmcj.2017.06.025 . - Ford, E., Curlewis, K., Wongkoblap, A., & Curcin, V. (2019). Public opinions on using social media content to identify users with depression and target mental health care advertising: Mixed methods survey. JMIR Mental Health, 6(11), e12942. doi:
10.2196/12942 . - Gambetti, P., Roccazzella, F., & Vrins, F. (2022). Meta-learning approaches for recovery rate prediction. Risks, 10(6), 124. doi:
10.3390/risks10060124 . - Gangrade, P. (2024). Suggesting new techniques and methods for big data analysis: Privacy-preserving data analysis techniques. In Big data analytics techniques for market intelligence (pp. 265–291). IGI Global Scientific Publishing. doi:
10.4018/979-8-3693-0413-6.ch010 . - Gao, S., & Zang, Z. (2016). An empirical examination of users’ adoption of mobile advertising in China. Information Development, 32(2), 203–215. doi:
10.1177/0266666914550113 . - Gawshinde, S., Khurana, A., Kaur, H., & Kaur, S. (2024, December). Harnessing IoT data for real-time marketing insights and consumer engagement. In International Conference on Leveraging Emerging Technologies and Analytics for Development (pp. 355–371). Springer Nature Singapore. doi:
10.1007/978-981-96-2548-2_18 . - Greaves, S. P., & Figliozzi, M. A. (2008). Collecting commercial vehicle tour data with passive global positioning system technology: Issues and potential applications. Transportation Research Record, 2049(1), 158–166. doi:
10.3141/2049-19 . - Gruteser, M., & Grunwald, D. (2003, May). Anonymous usage of location-based services through spatial and temporal cloaking. Proceedings of the 1st International Conference on Mobile Systems, Applications and Services, (pp. 31–42). doi:
10.1145/1066116.1189037 . - Hammedi, W., Brik, B., & Senouci, S. M. (2022). Toward optimal MEC-based collision avoidance system for cooperative inland vessels: A federated deep learning approach. IEEE Transactions on Intelligent Transportation Systems, 24(2), 2525–2537. doi:
10.1109/TITS.2022.3154158 . - He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 770–778). doi:
10.1109/CVPR.2016.90 . - Hentati, A., Jallouli, R. (2024, May). Diagnosing mobile banking applications to optimize user experience and engagement method, features and recommendations. In International Conference on Digital Economy (pp. 244–266). Springer Nature Switzerland. doi:
10.1007/978-3-031-76368-7_16 . - Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 102(46), 16569–16572. doi:
10.1073/pnas.0507655102 . - Hoh, B., Gruteser, M., Xiong, H., & Alrabady, A. (2010). Achieving guaranteed anonymity in GPS traces via uncertainty-aware path cloaking. IEEE Transactions on Mobile Computing, 9(8), 1089–1107. doi:
10.1109/TMC.2010.62 . - Hu, C., Song, M., & Guo, F. (2019). Intellectual structure of market orientation: A citation/co-citation analysis. Marketing Intelligence & Planning, 37(6), 598–616. doi:
10.1108/MIP-08-2018-0325 . - Huo, Z., Wang, T., Fan, Y., & He, P. (2023). Privacy-preserving global user profile construction through federated learning. International Journal of Computational Science and Engineering, 26(2), 199–209. doi:
10.1504/IJCSE.2023.129739 . - Kalnis, P., Ghinita, G., Mouratidis, K., & Papadias, D. (2007). Preventing location-based identity inference in anonymous spatial queries. IEEE Transactions on Knowledge and Data Engineering, 19(12), 1719–1733. doi:
10.1109/TKDE.2007.190662 . - Kong, X. J., Gao, H. R., Shen, G. J., Duan, G. H., & Das, S. K. (2022). FEDVCP: A federated-learning-based cooperative positioning scheme for social Internet of vehicles. IEEE Transactions on Computational Social Systems, 9(1), 1–10. doi:
10.1109/TCSS.2021.3062053 . - Koroniotis, N., Moustafa, N., Sitnikova, E., & Turnbull, B. (2019). Towards the development of realistic botnet dataset in the Internet of Things for network forensic analytics: Bot-IoT dataset. Future Generation Computer Systems, 100, 779–796. doi:
10.1016/j.future.2019.05.041 . - Koubaa, H., Ben Said, F., & Jallouli, R. (2024, May). Bibliometric analysis and network mapping on mobile technologies in the area of marketing: Emerging topics and research recommendations. In International Conference on Digital Economy (pp. 339–365). Springer Nature Switzerland. doi:
10.1007/978-3-031-76365-6_20 . - Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017). ImageNet classification with deep convolutional neural networks. Communications of the ACM, 60(6), 84–90. doi:
10.1145/3065386 . - Kumar, R., Khan, A. A., Kumar, J., Zakria, Golilarz, N. A., Zhang, S., Ting, Y., Zheng, C., & Wang, W. (2021). Blockchain-federated-learning and deep learning models for COVID-19 detection using CT imaging. IEEE Sensors Journal, 21(14), 16301–16314. doi:
10.1109/JSEN.2021.3076767 . - Lakshmi, V. R. V., & Kumar, T. G. (2017). Mobile social networks: Architecture, privacy, security issues and solutions. Journal of Communications, 12(9), 524–531. doi:
10.12720/jcm.12.9.524-531 . - Li, C., Fu, Y., Yu, F. R., Luan, T. H., & Zhang, Y. (2020). Vehicle position correction: A vehicular blockchain networks-based GPS error sharing framework. IEEE Transactions on Intelligent Transportation Systems, 22(2), 898–912. doi:
10.1109/TITS.2019.2961400 . - Li, Z., Hui, P., Zhang, P., Huang, J., Wang, B., Tian, L., Zhang, J., Gao, J., & Tang, X. (2021, April). What happens behind the scene? Towards fraud community detection in e-commerce from online to offline. In Companion Proceedings of the Web Conference 2021 (pp. 105–113). doi:
10.1145/3442442.3451147 . - Liu, H., Tian, Y., Peng, C., & Wu, Z. (2023). Privacy-utility equilibrium data generation based on Wasserstein generative adversarial networks. Information Sciences, 642, 119069. doi:
10.1016/j.ins.2023.119069 . - Lopes, H., Pires, I. M., San Blas, H. S., García-Ovejero, R., & Leithardt, V. (2020). Priada: Management and adaptation of information based on data privacy in public environments. Computers, 9(4), 77. doi:
10.3390/computers9040077 . - Majzoubi, M., & Zhao, E. Y. (2023). Going beyond optimal distinctiveness: Strategic positioning for gaining an audience composition premium. Strategic Management Journal, 44(4), 907–931. doi:
10.1002/smj.3460 . - Manda, V. K., Sagi, S., & Yadav, A. (2024). Blockchain in advertising and marketing: Revolutionizing the industry through transparency and trust. In New trends in marketing and consumer science (pp. 89–112). IGI Global. doi:
10.4018/979-8-3693-2754-8.ch005 . - Mao, B., Liu, J., Wu, Y., & Kato, N. (2023). Security and privacy on 6G network edge: A survey. IEEE Communications Surveys & Tutorials, 25(2), 1095–1127. doi:
10.1109/COMST.2023.3244674 . - Meidan, Y., Bohadana, M., Mathov, Y., Mirsky, Y., Shabtai, A., Breitenbacher, D., & Elovici, Y. (2018). N-BaIoT-network-based detection of IoT botnet attacks using deep autoencoders. IEEE Pervasive Computing, 17(3), 12–22. doi:
10.1109/MPRV.2018.03367731 . - Meyer, N., Ben Said, F., Alkathiri, N. A., & Soliman, M. (2023). A scientometric analysis of entrepreneurial and the digital economy scholarship: State of the art and an agenda for future research. Journal of Innovation and Entrepreneurship, 12(1), 70. doi:
10.1186/s13731-023-00340-w . - Michael, K., & Clarke, R. (2013). Location and tracking of mobile devices: Uberveillance stalks the streets. Computer Law & Security Review, 29(3), 216–228. doi:
10.1016/j.clsr.2013.03.004 . - Milne, G., & Bahl, S. (2010). Are there differences between consumers’ and marketers’ privacy expectations? A segment- and technology-level analysis. Journal of Public Policy & Marketing, 29(1), 138–148. doi:
10.1509/jppm.29.1.138 . - Nagaraj, P., Muneeswaran, V., Dharanidharan, A., Aakash, M., Balananthanan, K., & Rajkumar, C. (2023, January). E-commerce customer churn prediction scheme based on customer behaviour using machine learning. In 2023 International Conference on Computer Communication and Informatics (ICCCI) (pp. 1–6). IEEE. doi:
10.1109/ICCCI56745.2023.10128498 . - Nanni, M., Trasarti, R., Monreale, A., Grossi, V., & Pedreschi, D. (2016). Driving profiles computation and monitoring for car insurance CRM. ACM Transactions on Intelligent Systems and Technology, 8(1), 26. doi:
10.1145/2912148 . - Narang, U., & Shankar, V. (2019). Mobile marketing 2.0: State of the art and research agenda. Marketing in a Digital World (pp. 97–119). Emerald Publishing Limited. doi:
10.1108/S1548-643520190000016008 . - Naser, A., Lotfi, A., & Zhong, J. (2020). Adaptive thermal sensor array placement for human segmentation and occupancy estimation. IEEE Sensors Journal, 21(2), 1993–2002. doi:
10.1109/JSEN.2020.3020401 . - Nguyen, V.-L., Lin, P.-C., & Hwang, R.-H. (2019). Multi-array relative positioning for verifying the truthfulness of V2X messages. IEEE Communications Letters, 23(10), 1704–1707. doi:
10.1109/LCOMM.2019.292797 . - Orouji, N., & Mosavi, M. R. (2020). Novel secure positioning method in ultra-wide band framework based on overshadowing attack probabilistic model. IET Communications, 14(1), 1–10. doi:
10.1049/iet-com.2019.1138 . - Ozturk, O. (2021). Bibliometric review of resource dependence theory literature: An overview. Management Review Quarterly, 71(3), 525–552. doi:
10.1007/s11301-020-00192-8 . - O’Mahony, G. D., McCarthy, K. G., Harris, P. J., & Murphy, C. C. (2021). Developing novel low complexity models using received in-phase and quadrature-phase samples for interference detection and classification in wireless sensor network and GPS edge devices. Ad Hoc Networks, 120, 102562. doi:
10.1016/j.adhoc.2021.102562 . - Parwekar, P., & Gupta, G. (2019). Cloud data for marketing in tourism sector. In Smart Trends in Computing and Communications: Proceedings of SmartCom 2019 (pp. 143–153). Springer Singapore. doi:
10.1007/978-981-15-0077-0_16 . - Penagos-Londoño, G. I., Rodriguez–Sanchez, C., Ruiz-Moreno, F., & Torres, E. (2021). A machine learning approach to segmentation of tourists based on perceived destination sustainability and trustworthiness. Journal of Destination Marketing & Management, 19, 100532. doi:
10.1016/j.jdmm.2020.100532 . - Peng, T., Liu, Q., & Wang, G. (2014). Enhanced location privacy preserving scheme in location-based services. IEEE Systems Journal, 11(1), 219–230. doi:
10.1109/JSYST.2014.2354235 . - Peng, W., & Xin, B. G. (2019). A social trust and preference segmentation-based matrix factorization recommendation algorithm. EURASIP Journal on Wireless Communications and Networking, 2019(1), 272. doi:
10.1186/s13638-019-1600-4 . - Piao, Y. J., & Cui, D. Y. (2021). Privacy analysis and comparison of pandemic contact tracing apps. KSII Transactions on Internet and Information Systems, 15(11), 4145–4162. doi:
10.3837/tiis.2021.11.015 . - Poddar, S. D., Murali, M., Rajasekaran, P., & Prabakaran, N. (2024, March). A comprehensive study on security threats in autonomous vehicles: Safeguarding the future. In 2024 1st International Conference on Cognitive, Green and Ubiquitous Computing (IC-CGU) (pp. 1–6). IEEE. doi:
10.1109/IC-CGU58078.2024.10530760 . - Pour, M. S., Mangino, A., Friday, K., Rathbun, M., Bou-Harb, E., Iqbal, F., Samtani, S., Crichigno, J., & Ghani, N. (2020). On data-driven curation, learning, and analysis for inferring evolving Internet-of-Things (IoT) botnets in the wild. Computers & Security, 91 101707. doi:
10.1016/j.cose.2019.101707 . - Pranckutė, R. (2021). Web of science (WoS) and scopus: The titans of bibliographic information in today’s academic world. Publications, 9(1), 12. doi:
10.3390/publications9010012 . - Purwanto, E., Deviny, J., & Mutahar, A. M. (2020). The mediating role of trust in the relationship between corporate image, security, word of mouth and loyalty in M-banking using among the millennial generation in Indonesia. Management & Marketing, 15(2), 255–274. doi:
10.2478/mmcks-2020-0016 . - Radanliev, P., Santos, O., Brandon-Jones, A., & Joinson, A. (2024). Ethics and responsible AI deployment. Frontiers in Artificial Intelligence, 7, 1377011. doi:
10.3389/frai.2024.1377011 . - Rafieian, O., & Yoganarasimhan, H. (2021). Targeting and privacy in mobile advertising. Marketing Science, 40(2),193–218. doi:
10.1287/mksc.2020.1235 . - Raza, S., Wallgren, L., & Voigt, T. (2013). SVELTE: Real-time intrusion detection in the Internet of Things. Ad Hoc Networks, 11(8), 2661–2674. doi:
10.1016/j.adhoc.2013.04.014 . - Sachdev, R. (2020, April). Towards security and privacy for edge AI in IoT/IoE based digital marketing environments. In 2020 Fifth International Conference on Fog and Mobile Edge Computing (FMEC) (pp. 341–346). IEEE. doi:
10.1109/FMEC49853.2020.9144755 . - Sakas, D. P., & Giannakopoulos, N. T. (2021). Big data contribution in desktop and mobile devices comparison, regarding airlines’ digital brand name effect. Big Data and Cognitive Computing, 5(4), 48. doi:
10.3390/bdcc5040048 . - Senavirathne, N., & Torra, V. (2020, December). On the role of data anonymization in machine learning privacy. In 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) (pp. 664–675). IEEE. doi:
10.1109/TrustCom50675.2020.00093 . - Serrano-Malebran, J., Vidal-Silva, C., & Veas-González, I. (2023). Social media marketing as a segmentation tool. Sustainability, 15(2), 1151. doi:
10.3390/su15021151 . - Shastri, M. D., & Pandit, A. A. (2021). Remodeling: Improved privacy preserving data mining (PPDM). International Journal of Information Technology, 13(1), 131–137. doi:
10.1007/s41870-020-00531-8 . - Shi, Y., Siddik, A., Masuku, M., Zheng, G. W., Hamayun, M., & Ibrahim, A. M. (2022). The antecedents of willingness to adopt and pay for the IoT in the agricultural industry: An application of the UTAUT 2 theory. Sustainability, 14(11), 6640. doi:
10.3390/su14116640 . - Simonyan, K., & Zisserman, A. (2014). Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556. doi:
10.48550/arXiv.1409.1556 . - Simpson, B. (2014). Tracking children, constructing fear: GPS and the manufacture of family safety. Information & Communications Technology Law, 23(2), 273–285 doi:
10.1080/13600834.2014.970377 . - Sinha, M., Majra, H., Hutchins, J., & Saxena, R. (2019). Mobile payments in India: The privacy factor. International Journal of Bank Marketing, 37(1), 192–209. doi:
10.1108/IJBM-05-2017-0099 . - Song, Y., Fu, Y., Yu, F. R., & Zhou, L. (2020). Blockchain-enabled internet of vehicles with cooperative positioning: A deep neural network approach. IEEE Internet of Things Journal, 7(4), 3485–3498. doi:
10.1109/JIOT.2020.2972337 . - Srivastava, P. R., Sharma, D., Kaur, I., & Wamba, S. F. (2021). Intellectual structure and publication pattern in journal of global information management: A bibliometric analysis during 2002–2020. Journal of Global Information Management (JGIM), 29(4), 1–31. doi:
10.4018/JGIM.20210701.oa1 . - Stachl, C., Au, Q., Schoedel, R., Gosling, S., Harari, G., Buschek, D., Völkel, S. T., Schuwerk, T., Oldemeier, M., Ullmann, T., & Hussmann, H. (2020). Predicting personality from patterns of behavior collected with smartphones. Proceedings of the National Academy of Sciences, 117(30), 17680–17687. doi:
10.1073/pnas.1920484117 . - Sukhoparov, M. E., & Lebedev, I. S. (2023) Improving the quality of the identification of the information security state based on sample segmentation. Automatic Control and Computer Sciences, 57(8), 1071–1075. doi:
10.3103/S0146411623080321 . - Sweeney, L. (2002). k-anonymity: A model for protecting privacy. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 10(5), 557–570. doi:
10.1142/S0218488502001648 . - Taylor, M., Reilly, D., & Wren, C. (2020). Internet of things support for marketing activities. Journal of Strategic Marketing, 28(2), 149–160. doi:
10.1080/0965254X.2018.1493523 . - Teodorescu, C. A., Ciurea, C. E., Saftiuc, B. P., & Staicu, D. (2025), The evolution of mobile cybersecurity regulations in the European Union. Management & Marketing, 20(1), 52–63.
10.2478/mmcks-2025-0004 . - Thakur, R., & Srivastava, M. (2013). Customer usage intention of mobile commerce in India: An empirical study. Journal of Indian Business Research, 5(1), 52–72. doi:
10.1108/17554191311303385 . - Thangavel, P., & Chandra, B. (2023). Two decades of M-commerce consumer research: A bibliometric analysis using R biblioshiny. Sustainability, 15(15), 11835 doi:
10.3390/su151511835 . - Thomaz, F., Salge, C., Karahanna, E., & Hulland, J. (2019, November 11). Learning from the Dark Web: Leveraging conversational agents in the era of hyper-privacy to enhance marketing. Journal of the Academy of Marketing Science, 48(1), 43–63. doi:
10.1007/s11747-019-00704-3 . - Ullah, I., Boreli, R., & Kanhere, S. S. (2023). Privacy in targeted advertising on mobile devices: A survey. International Journal of Information Security, 22(3), 647–678 doi:
10.1007/s10207-022-00655-x . - Uysal, D. T., Yoo, P. D., & Taha, K. (2022). Data-driven malware detection for 6G networks: A survey from the perspective of continuous learning and explainability via visualization. IEEE Open Journal of Vehicular Technology, 4, 61–71. doi:
10.1109/OJVT.2022.3219898 . - Van Angeren, J., Vroom, G., McCann, B. T., Podynitsyna, K., & Langerak, F. (2022). Optimal distinctiveness across revenue models: Performance effects of differentiation of paid and free products in a mobile app market. Strategic Management Journal, 43(10), 2066–2100. doi:
10.1002/smj.3394 . - Varnali, K., & Toker, A. (2010). Mobile marketing research: The-state-of-the-art. International Journal of Information Management, 30(2), 144–151. doi:
10.1016/j.ijinfomgt.2009.08.009 . - Vittala, K. P., Kumar, K., Seranmadevi, R., & Tyagi, A. K. (2024). Artificial intelligence-Internet of Things integration for smart marketing: Challenges and opportunities. Advancing software engineering through AI, federated learning, and large language models (pp. 295–307). IGI Global. doi:
10.4018/979-8-3693-3502-4.ch019 . - Wang, Y., Liu, Q., Mihankhah, E., Lv, C., & Wang, D. (2021). Detection and isolation of sensor attacks for autonomous vehicles: Framework, algorithms, and validation. IEEE Transactions on Intelligent Transportation Systems, 23(7), 8247–8259. doi:
10.1109/TITS.2021.3077015 . - Wu, H. T. (2022). The Internet-of-Vehicle traffic condition system developed by artificial intelligence of things. Journal of Supercomputing, 78(2), 2665–2680. doi:
10.1007/s11227-021-03969-0 . - Yadav, A., & Kumar, A. (2025). Mobile data anonymization in cyber security: Techniques, applications, and future directions. In Artificial intelligence for cyber security and industry 4.0 (pp. 343–370). CRC Press. doi:
10.1201/9781032657264-15 . - Yang, Y., & Kels, C. (2016). Does the shoe fit? Ethical, legal, and policy considerations of global positioning system shoes for individuals with Alzheimer’s disease. Journal of the American Geriatrics Society, 64(8), 1708–1715. doi:
10.1111/jgs.14265 . - Zakroum, M., Francois, J., Chrisment, I., & Ghogho, M. (2022). Monitoring network telescopes and inferring anomalous traffic through the prediction of probing rates. IEEE Transactions on Network and Service Management, 19(4), 5170–5182. doi:
10.1109/TNSM.2022.3183497 . - Zhang, G., Chen, X., Zhang, L., Feng, B., Guo, X., Ling, J., & Zhang, Y. (2022). STAIBT: Blockchain and CP-ABE empowered secure and trusted agricultural IoT blockchain terminal. IJIMAI, 7(5), 66–75. doi:
10.9781/ijimai.2022.07.004 . - Zhang, J. Z., Srivastava, P. R., Sharma, D., & Eachempati, P. (2021). Big data analytics and machine learning: A retrospective overview and bibliometric analysis. Expert Systems with Applications, 184, 115561. doi:
10.1016/j.eswa.2021.115561 . - Zhu, J., & Liu, W. (2020). A tale of two databases: The use of Web of Science and Scopus in academic papers. Scientometrics, 123(1), 321–335. doi:
10.1007/s11192-020-03387-8 . - Zhu, Y., Liu, Y., Yu, J., & Yuan, X. (2021). Semi-supervised federated learning for travel mode identification from GPS trajectories. IEEE Transactions on Intelligent Transportation Systems, 23(3), 2380–2391. doi:
10.1109/TITS.2021.3092015 .
Language: English
Page range: 28 - 47
Submitted on: Jul 3, 2025
Accepted on: Sep 9, 2025
Published on: Sep 30, 2025
Published by: Society for Business Excellence
In partnership with: Paradigm Publishing Services
Publication frequency: 4 times per year
Related subjects:
© 2025 Hasna Koubaa El Euch, Foued Ben Said, Rim Jallouli, published by Society for Business Excellence
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.