A Conceptual Framework for Integrating Customer Intelligence into Regional Market Expansion Strategies

References

[1] Abimbade, O., Akinyemi, A., Bello, L. and Mohammed, H., 2017. Comparative Effects of an Individualized Computer-Based Instruction and a Modified Conventional Strategy on Students’ Academic Achievement in Organic Chemistry. Journal of Positive Psychology and Counseling, 1(2), pp.1-19.

[2] Adedoja, G., Abimbade, O., Akinyemi, A. and Bello, L., 2017. Discovering the power of mentoring using online collaborative technologies. Advancing education through technology, pp.261-281.

[3] Adekunle, B. I., Chukwuma-Eke, E. C., Balogun, E. D., & Ogunsola, K. O. (2021). A predictive modeling approach to optimizing business operations: A case study on reducing operational inefficiencies through machine learning. International Journal of Multidisciplinary Research and Growth Evaluation, 2(1), 791–799. https://doi.org/10.54660/.IJMRGE.2021.2.1.791-799

[4] Adelana, O.P. and Akinyemi, A.L., 2021. ARTIFICIAL INTELLIGENCE-BASED TUTORING SYSTEMS UTILIZATION FOR LEARNING: A SURVEY OF SENIOR SECONDARY STUDENTS’AWARENESS AND READINESS IN IJEBU-ODE, OGUN STATE. UNIZIK Journal of Educational Research and Policy Studies, 9, pp.16-28.

[5] Adeniran, B.I., Akinyemi, A.L. and Aremu, A., 2016. The effect of Webquest on civic education of junior secondary school students in Nigeria. In Proceedings of INCEDI 2016 Conference 29th-31st August (pp. 109-120).

[6] Adewoyin, M.A., 2021. Developing frameworks for managing low-carbon energy transitions: overcoming barriers to implementation in the oil and gas industry.

[7] Agho, G., Ezeh, M.O., Isong, M., Iwe, D. and Oluseyi, K.A., 2021. Sustainable pore pressure prediction and its impact on geo-mechanical modelling for enhanced drilling operations. World Journal of Advanced Research and Reviews, 12(1), pp.540-557.

[8] Ajayi, O. and Osunsanmi, T., 2018. Constraints and challenges in the implementation of total quality management (TQM) in contracting organisation. Journal of Construction Project Management and Innovation, 8(1), pp.1753-1766.

[9] Akinyemi, A. and Ojetunde, S.M., 2019. Comparative analysis of networking and e-readiness of some African and developed countries. Journal of Emerging Trends in Educational Research and Policy Studies, 10(2), pp.82-90.

[10] Akinyemi, A.L. and Ebimomi, O.E., 2020. Influence of Gender on Students’ Learning Outcomes in Computer Studies. Education technology.

[11] Akinyemi, A.L. and Ojetunde, S.M., 2020. Techno-pedagogical models and influence of adoption of remote learning platforms on classical variables of education inequality during COVID-19 Pandemic in Africa. Journal of Positive Psychology and Counselling, 7(1), pp.12-27.

[12] Akinyemi, A.L., 2013. Development and Utilisation of an Instructional Programme for Impacting Competence in Language of Graphics Orientation (LOGO) at Primary School Level in Ibadan, Nigeria (Doctoral dissertation).

[13] Ali, O., Shrestha, A., Chatfield, A. and Murray, P., 2020. Assessing information security risks in the cloud: A case study of Australian local government authorities. Government Information Quarterly, 37(1), p.101419.

[14] Alon, I., Jaffe, E., Prange, C. and Vianelli, D., 2020. Global marketing: strategy, practice, and cases. Routledge.

[15] Anant, V., Donchak, L., Kaplan, J. and Soller, H., 2020. The consumer-data opportunity and the privacy imperative. McKinsey & Company.

[16] Anasi, S.N., Ukangwa, C.C. and Fagbe, A., 2018. University libraries-bridging digital gaps and accelerating the achievement of sustainable development goals through information and communication technologies. World Journal of Science, Technology and Sustainable Development, 15(1), pp.13-25.

[17] Anny, D., 2019. Enterprise Data Integration for Smarter Customer Insights.

[18] Anshari, M., Almunawar, M.N., Lim, S.A. and Al-Mudimigh, A., 2019. Customer relationship management and big data enabled: Personalization & customization of services. Applied computing and informatics, 15(2), pp.94-101.

[19] Aremu, A. and Laolu, A.A., 2014. Language of graphics orientation (LOGO) competencies of Nigerian primary school children: Experiences from the field. Journal of Educational Research and Reviews, 2(4), pp.53-60.

[20] Auchter, A.M., Mejia, M.H., Heyser, C.J., Shilling, P.D., Jernigan, T.L., Brown, S.A., Tapert, S.F. and Dowling, G.J., 2018. A description of the ABCD organizational structure and communication framework. Developmental cognitive neuroscience, 32, pp.8-15.

[21] Bharadwaj, N., 2018. Strategic decision making in an information-rich environment: a synthesis and an organizing framework for innovation research. In Innovation and strategy (pp. 3-30). Emerald Publishing Limited.

[22] Boone, T., Ganeshan, R., Jain, A. and Sanders, N.R., 2019. Forecasting sales in the supply chain: Consumer analytics in the big data era. International journal of forecasting, 35(1), pp.170-180.

[23] Boppana, V.R., 2019. Data Privacy and Security in Dynamics CRM Implementations. Educational Research (IJMCER), 1(2), pp.35-44.

[24] Božič, K. and Dimovski, V., 2019. Business intelligence and analytics for value creation: The role of absorptive capacity. International journal of information management, 46, pp.93-103.

[25] Brenner, B., 2018. Transformative sustainable business models in the light of the digital imperative—A global business economics perspective. Sustainability, 10(12), p.4428.

[26] Buhalis, D. and Sinarta, Y., 2019. Real-time co-creation and nowness service: lessons from tourism and hospitality. Journal of Travel & Tourism Marketing, 36(5), pp.563-582.

[27] Buttle, F. and Maklan, S., 2019. Customer relationship management: concepts and technologies. Routledge.

[28] Camilleri, M.A. and Camilleri, M.A., 2018. Market segmentation, targeting and positioning (pp. 69-83). Springer International Publishing.

[29] Carson, G., O'Connor, C. and Simmons, G., 2020. The crucial role of market intelligence in the development of small business marketing capabilities. Journal of Small Business and Enterprise Development, 27(5), pp.797-816.

[30] Caserio, C. and Trucco, S., 2018. Enterprise resource planning and business intelligence systems for information quality (p. 21). Springer.

[31] Chiang, L.L.L. and Yang, C.S., 2018. Does country-of-origin brand personality generate retail customer lifetime value? A Big Data analytics approach. Technological Forecasting and Social Change, 130, pp.177-187.

[32] Chima, P. and Ahmadu, J., 2019. Implementation of resettlement policy strategies and community members' felt-need in the federal capital territory, Abuja, Nigeria. Academic journal of economic studies, 5(1), pp.63-73.

[33] Chima, P., Ahmadu, J. and Folorunsho, O.G., 2021. Implementation of digital integrated personnel and payroll information system: Lesson from Kenya, Ghana and Nigeria. Governance and Management Review, 4(2).

[34] Choi, D., Chung, C.Y., Seyha, T. and Young, J., 2020. Factors affecting organizations’ resistance to the adoption of blockchain technology in supply networks. Sustainability, 12(21), p.8882.

[35] Choi, H., Ahn, J. and Woo, J., 2020. Will there be disruptive innovation? Identifying profitable niche segments and product designs for small-and medium-sized companies and startups. IEEE Transactions on Engineering Management, 69(5), pp.2057-2072.

[36] Chukwuma-Eke, E. C., Ogunsola, O. Y., & Isibor, N. J. (2021). Designing a robust cost allocation framework for energy corporations using SAP for improved financial performance. International Journal of Multidisciplinary Research and Growth Evaluation, 2(1), 809–822. https://doi.org/10.54660/.IJMRGE.2021.2.1.809-822

[37] Claro, D.P. and Ramos, C., 2018. Sales intrafirm networks and the performance impact of sales cross-functional collaboration with marketing and customer service. Journal of Personal Selling & Sales Management, 38(2), pp.172-190.

[38] Cluley, R., Green, W. and Owen, R., 2020. The changing role of the marketing researcher in the age of digital technology: Practitioner perspectives on the digitization of marketing research. International Journal of Market Research, 62(1), pp.27-42.

[39] Conboy, K., Mikalef, P., Dennehy, D. and Krogstie, J., 2020. Using business analytics to enhance dynamic capabilities in operations research: A case analysis and research agenda. European Journal of Operational Research, 281(3), pp.656-672.

[40] Desouza, K.C., Dawson, G.S. and Chenok, D., 2020. Designing, developing, and deploying artificial intelligence systems: Lessons from and for the public sector. Business Horizons, 63(2), pp.205-213.

[41] Dienagha, I.N., Onyeke, F.O., Digitemie, W.N. and Adekunle, M., 2021. Strategic reviews of greenfield gas projects in Africa: Lessons learned for expanding regional energy infrastructure and security.

[42] Dimitri, C. and Gardner, K., 2019. Farmer use of intermediated market channels: A review. Renewable Agriculture and Food Systems, 34(3), pp.181-197.

[43] Djerdjouri, M., 2020. Data and Business Intelligence Systems for Competitive Advantage: prospects, challenges, and real-world applications. Mercados y Negocios, (41), pp.5-18.

[44] Ebneyamini, S. and Sadeghi Moghadam, M.R., 2018. Toward developing a framework for conducting case study research. International journal of qualitative methods, 17(1), p.1609406918817954.

[45] Egbuhuzor, N.S., Ajayi, A.J., Akhigbe, E.E., Agbede, O.O., Ewim, C.P.M. and Ajiga, D.I., 2021. Cloud-based CRM systems: Revolutionizing customer engagement in the financial sector with artificial intelligence. International Journal of Science and Research Archive, 3(1), pp.215-234.

[46] Elujide, I., Fashoto, S.G., Fashoto, B., Mbunge, E., Folorunso, S.O. and Olamijuwon, J.O., 2021. Application of deep and machine learning techniques for multi-label classification performance on psychotic disorder diseases. Informatics in Medicine Unlocked, 23, p.100545.

[47] Elujide, I., Fashoto, S.G., Fashoto, B., Mbunge, E., Folorunso, S.O. and Olamijuwon, J.O., 2021. Informatics in Medicine Unlocked.

[48] Evans, J.R. and Mathur, A., 2018. The value of online surveys: A look back and a look ahead. Internet research, 28(4), pp.854-887.

[49] Famaye, T., Akinyemi, A.I. and Aremu, A., 2020. Effects of Computer Animation on Students’ Learning Outcomes in Four Core Subjects in Basic Education in Abuja, Nigeria. African Journal of Educational Research, 22(1), pp.70-84.

[50] Felzmann, H., Villaronga, E.F., Lutz, C. and Tamò-Larrieux, A., 2019. Transparency you can trust: Transparency requirements for artificial intelligence between legal norms and contextual concerns. Big Data & Society, 6(1), p.2053951719860542.

[51] Fenwick, M., Vermeulen, E.P. and Corrales, M., 2018. Business and regulatory responses to artificial intelligence: Dynamic regulation, innovation ecosystems and the strategic management of disruptive technology. Robotics, AI and the Future of Law, pp.81-103.

[52] Fredson, G., Adebisi, B., Ayorinde, O.B., Onukwulu, E.C., Adediwin, O. and Ihechere, A.O., 2021. Revolutionizing procurement management in the oil and gas industry: Innovative strategies and insights from high-value projects. Int J Multidiscip Res Growth Eval [Internet].

[53] Fredson, G., Adebisi, B., Ayorinde, O.B., Onukwulu, E.C., Adediwin, O. and Ihechere, A.O., 2021. Driving organizational transformation: Leadership in ERP implementation and lessons from the oil and gas sector. Int J Multidiscip Res Growth Eval [Internet].

[54] Galvez, J.F., Mejuto, J.C. and Simal-Gandara, J., 2018. Future challenges on the use of blockchain for food traceability analysis. TrAC Trends in Analytical Chemistry, 107, pp.222-232.

[55] Gardé, V., 2018. Digital audience management: Building and managing a robust data management platform for multi-channel targeting and personalisation throughout the customer journey. Applied Marketing Analytics, 4(2), pp.126-135.

[56] Ghaffar, A., 2020. Integration of Business Intelligence Dashboard for Enhanced Data Analytics Capabilities.

[57] Ghasemaghaei, M., Ebrahimi, S. and Hassanein, K., 2018. Data analytics competency for improving firm decision making performance. The Journal of Strategic Information Systems, 27(1), pp.101-113.

[58] Gnizy, I., 2019. Big data and its strategic path to value in international firms. International Marketing Review, 36(3), pp.318-341.

[59] Grover, V., Chiang, R.H., Liang, T.P. and Zhang, D., 2018. Creating strategic business value from big data analytics: A research framework. Journal of management information systems, 35(2), pp.388-423.

[60] Haasnoot, M., Van’t Klooster, S. and Van Alphen, J., 2018. Designing a monitoring system to detect signals to adapt to uncertain climate change. Global environmental change, 52, pp.273-285.

[61] Harris, J.L., Booth, A., Cargo, M., Hannes, K., Harden, A., Flemming, K., Garside, R., Pantoja, T., Thomas, J. and Noyes, J., 2018. Cochrane Qualitative and Implementation Methods Group guidance series—paper 2: methods for question formulation, searching, and protocol development for qualitative evidence synthesis. Journal of clinical epidemiology, 97, pp.39-48.

[62] Holsapple, C.W., Hsiao, S.H. and Pakath, R., 2018. Business social media analytics: Characterization and conceptual framework. Decision Support Systems, 110, pp.32-45.

[63] Ibrahim, A., Thiruvady, D., Schneider, J.G. and Abdelrazek, M., 2020. The challenges of leveraging threat intelligence to stop data breaches. Frontiers in Computer Science, 2, p.36.

[64] Isibor, N.J., Ewim, C.P.M., Ibeh, A.I., Adaga, E.M., Sam-Bulya, N.J. and Achumie, G.O., 2021. A Generalizable Social Media Utilization Framework for Entrepreneurs: Enhancing Digital Branding, Customer Engagement, and Growth. International Journal of Multidisciplinary Research and Growth Evaluation, 2(1), pp.751-758.

[65] James, A.T., Phd, O.K.A., Ayobami, A.O. and Adeagbo, A., 2019. Raising employability bar and building entrepreneurial capacity in youth: a case study of national social investment programme in Nigeria. Covenant Journal of Entrepreneurship.

[66] Kano, L., Tsang, E.W. and Yeung, H.W.C., 2020. Global value chains: A review of the multi-disciplinary literature. Journal of international business studies, 51(4), pp.577-622.

[67] Kilubi, I. and Rogers, H., 2018. Bridging the gap between supply chain risk management and strategic technology partnering capabilities: insights from social capital theory. Supply Chain Management: An International Journal, 23(4), pp.278-292.

[68] Kolade, O., Osabuohien, E., Aremu, A., Olanipekun, K.A., Osabohien, R. and Tunji-Olayeni, P., 2021. Co-creation of entrepreneurship education: challenges and opportunities for university, industry and public sector collaboration in Nigeria. The Palgrave Handbook of African Entrepreneurship, pp.239-265.

[69] Lee, Z.W., Chan, T.K., Chong, A.Y.L. and Thadani, D.R., 2019. Customer engagement through omnichannel retailing: The effects of channel integration quality. Industrial Marketing Management, 77, pp.90-101.

[70] Leimstoll, U. and Wölfle, R., 2020. Direct to Consumer (D2C) E-commerce: Goals and strategies of brand manufacturers. In New trends in business information systems and technology: Digital innovation and digital business transformation (pp. 237-250). Cham: Springer International Publishing.

[71] Li, L., Chi, T., Hao, T. and Yu, T., 2018. Customer demand analysis of the electronic commerce supply chain using Big Data. Annals of Operations Research, 268, pp.113-128.

[72] Losavio, M.M., Chow, K.P., Koltay, A. and James, J., 2018. The Internet of Things and the Smart City: Legal challenges with digital forensics, privacy, and security. Security and Privacy, 1(3), p.e23.

[73] Madhani, P.M., 2019. Building a customer-centric supply chain strategy: Enhancing competitive advantages. The IUP Journal of Business Strategy, 16(2), pp.28-42.

[74] Mandapuram, M., Gutlapalli, S.S., Reddy, M. and Bodepudi, A., 2020. Application of artificial intelligence (AI) technologies to accelerate market segmentation. Global Disclosure of Economics and Business, 9(2), pp.141-150.

[75] Manral, L. and Harrigan, K.R., 2018. Corporate advantage in customer-centric diversification. Journal of Strategic Marketing, 26(6), pp.498-519.

[76] Marr, B., 2019. Artificial intelligence in practice: how 50 successful companies used AI and machine learning to solve problems. John Wiley & Sons.

[77] Martin, K., 2018. The penalty for privacy violations: How privacy violations impact trust online. Journal of Business Research, 82, pp.103-116.

[78] Masa’deh, R.E., Al-Henzab, J., Tarhini, A. and Obeidat, B.Y., 2018. The associations among market orientation, technology orientation, entrepreneurial orientation and organizational performance. Benchmarking: An International Journal, 25(8), pp.3117-3142.

[79] Maynard, M.T., Kennedy, D.M. and Resick, C.J., 2018. Teamwork in extreme environments: Lessons, challenges, and opportunities. Journal of organizational behavior, 39(6), pp.695-700.

[80] Mazurek, G. and Małagocka, K., 2019. Perception of privacy and data protection in the context of the development of artificial intelligence. Journal of Management Analytics, 6(4), pp.344-364.

[81] McMeekin, N., Wu, O., Germeni, E. and Briggs, A., 2020. How methodological frameworks are being developed: evidence from a scoping review. BMC medical research methodology, 20, pp.1-9.

[82] Melander, L., 2020. Customer involvement in product development: Using Voice of the Customer for innovation and marketing. Benchmarking: An International Journal, 27(1), pp.215-231.

[83] Mello, M.M., ADLER‐MILSTEIN, J.U.L.I.A., Ding, K.L. and Savage, L., 2018. Legal barriers to the growth of health information exchange—boulders or pebbles?. The Milbank Quarterly, 96(1), pp.110-143.

[84] Menon, J. and Fink, A., 2019. The fourth industrial revolution and its implications for regional economic integration in ASEAN. Journal of Asian Economic Integration, 1(1), pp.32-47.

[85] Mirzabeiki, V. and Saghiri, S.S., 2020. From ambition to action: How to achieve integration in omni-channel?. Journal of Business Research, 110, pp.1-11.

[86] Moustaka, V., Vakali, A. and Anthopoulos, L.G., 2018. A systematic review for smart city data analytics. ACM Computing Surveys (cSuR), 51(5), pp.1-41.

[87] Namara, M., Wilkinson, D., Lowens, B.M., Knijnenburg, B.P., Orji, R. and Sekou, R.L., 2018, December. Cross-cultural perspectives on eHealth privacy in Africa. In Proceedings of the Second African Conference for Human Computer Interaction: Thriving Communities (pp. 1-11).

[88] Naranjo Rico, J.L., 2018. Holistic business approach for the protection of sensitive data: study of legal requirements and regulatory compliance at international level to define and implement data protection measures using encryption techniques.

[89] Neumann, J., Robson, A. and Sloan, D., 2018. Monitoring and evaluation of strategic change programme implementation—Lessons from a case analysis. Evaluation and program planning, 66, pp.120-132.

[90] Ogunnowo, E., Ogu, E., Egbumokei, P., Dienagha, I. and Digitemie, W., 2021. Theoretical framework for dynamic mechanical analysis in material selection for highperformance engineering applications. Open Access Research Journal of Multidisciplinary Studies, 1(2), pp.117-131.

[91] OJIKA, F.U., OWOBU, W.O., ABIEBA, O.A., ESAN, O.J., UBAMADU, B.C. and IFESINACHI, A., 2021. A Conceptual Framework for AI-Driven Digital Transformation: Leveraging NLP and Machine Learning for Enhanced Data Flow in Retail Operations.

[92] Okolie, C.I., Hamza, O., Eweje, A., Collins, A. and Babatunde, G.O., 2021. Leveraging Digital Transformation and Business Analysis to Improve Healthcare Provider Portal. IRE Journals, 4 (10), 253-254 [online]

[93] Okolie, C.I., Hamza, O., Eweje, A., Collins, A., Babatunde, G.O. and Ubamadu, B.C., 2021. Leveraging digital transformation and business analysis to improve healthcare provider portal. Iconic Research and Engineering Journals, 4(10), pp.253-257.

[94] Olanipekun, K.A., 2020. Assessment of Factors Influencing the Development and Sustainability of Small Scale Foundry Enterprises in Nigeria: A Case Study of Lagos State. Asian Journal of Social Sciences and Management Studies, 7(4), pp.288-294.

[95] Olszak, C.M. and Mach-Król, M., 2018. A conceptual framework for assessing an organization’s readiness to adopt big data. Sustainability, 10(10), p.3734.

[96] Oluokun, O.A., 2021. Design of a Power System with Significant Mass and Volume Reductions, Increased Efficiency, and Capability for Space Station Operations Using Optimization Approaches (Doctoral dissertation, McNeese State University).

[97] Omar, Y.M., Minoufekr, M. and Plapper, P., 2019. Business analytics in manufacturing: Current trends, challenges and pathway to market leadership. Operations Research Perspectives, 6, p.100127.

[98] Oyedokun, O.O., 2019. Green human resource management practices and its effect on the sustainable competitive edge in the Nigerian manufacturing industry (Dangote) (Doctoral dissertation, Dublin Business School).

[99] Oyeniyi, L.D., Igwe, A.N., Ofodile, O.C. and Paul-Mikki, C., 2021. Optimizing risk management frameworks in banking: Strategies to enhance compliance and profitability amid regulatory challenges. Journal Name Missing.

[100] Palmatier, R.W. and Martin, K.D., 2019. The intelligent marketer's guide to data privacy: The impact of big data on customer trust. Cham, Switzerland: Springer International Publishing.

[101] Pappas, I.O., Mikalef, P., Giannakos, M.N., Krogstie, J. and Lekakos, G., 2018. Big data and business analytics ecosystems: paving the way towards digital transformation and sustainable societies. Information systems and e-business management, 16(3), pp.479-491.

[102] Parida, V. and Wincent, J., 2019. Why and how to compete through sustainability: a review and outline of trends influencing firm and network-level transformation. International Entrepreneurship and Management Journal, 15, pp.1-19.

[103] Park, H.Y., Misra, K., Reddy, S. and Jaber, K., 2019. Family firms’ innovation drivers and performance: a dynamic capabilities approach. Journal of Family Business Management, 9(1), pp.4-23.

[104] Radenković, M., Lukić, J., Despotović-Zrakić, M., Labus, A. and Bogdanović, Z., 2018. Harnessing business intelligence in smart grids: A case of the electricity market. Computers in industry, 96, pp.40-53.

[105] Rafif, M.F., 2019. Comparison study of the development of Self-Service Business Intelligence between Power BI and Tableau desktop (Case study: Microsoft Adventure Works).

[106] Saharan, S., Bawa, S. and Kumar, N., 2020. Dynamic pricing techniques for Intelligent Transportation System in smart cities: A systematic review. Computer Communications, 150, pp.603-625.

[107] Schia, N.N., 2018. The cyber frontier and digital pitfalls in the Global South. Third World Quarterly, 39(5), pp.821-837.

[108] Senvar, O., Akburak, D. and Yel, N., 2020. Customer oriented intelligent DSS based on two-phased clustering and integrated interval type-2 fuzzy AHP and hesitant fuzzy TOPSIS. Journal of Intelligent & Fuzzy Systems, 39(5), pp.6121-6143.

[109] Shankar, V. and Narang, U., 2020. Emerging market innovations: Unique and differential drivers, practitioner implications, and research agenda. Journal of the Academy of Marketing Science, 48, pp.1030-1052.

[110] Stier, S., Breuer, J., Siegers, P. and Thorson, K., 2020. Integrating survey data and digital trace data: Key issues in developing an emerging field. Social Science Computer Review, 38(5), pp.503-516.

[111] Strusani, D. and Houngbonon, G.V., 2020. What COVID-19 means for digital infrastructure in emerging markets. International Finance Corporation, World Bank: Geneva, Switzerland.

[112] Syam, N. and Sharma, A., 2018. Waiting for a sales renaissance in the fourth industrial revolution: Machine learning and artificial intelligence in sales research and practice. Industrial marketing management, 69, pp.135-146.

[113] Tabesh, P., Mousavidin, E. and Hasani, S., 2019. Implementing big data strategies: A managerial perspective. Business Horizons, 62(3), pp.347-358.

[114] Tallman, S., Luo, Y. and Buckley, P.J., 2018. Business models in global competition. Global Strategy Journal, 8(4), pp.517-535.

[115] Trautman, L.J., 2018. How Google Perceives Customer Privacy, Cyber, E-Commerce, Political and Regulatory Compliance Risks. Wm. & Mary Bus. L. Rev., 10, p.1.

[116] Tura, N., Hanski, J., Ahola, T., Ståhle, M., Piiparinen, S. and Valkokari, P., 2019. Unlocking circular business: A framework of barriers and drivers. Journal of cleaner production, 212, pp.90-98.

[117] Utterback, J.M. and Abernathy, W.J., 2018. A dynamic model of process and product innovation. In Organizational Innovation (pp. 193-210). Routledge.

[118] Varadarajan, R., 2020. Customer information resources advantage, marketing strategy and business performance: A market resources based view. Industrial Marketing Management, 89, pp.89-97.

[119] Vives, A., Jacob, M. and Payeras, M., 2018. Revenue management and price optimization techniques in the hotel sector: A critical literature review. Tourism economics, 24(6), pp.720-752.

[120] Watson IV, G.F., Weaven, S., Perkins, H., Sardana, D. and Palmatier, R.W., 2018. International market entry strategies: Relational, digital, and hybrid approaches. Journal of International Marketing, 26(1), pp.30-60.

@article{1708471,
      author = {Abiodun Yusuf Onifade, Jeffrey Chidera Ogeawuchi, Abraham Ayodeji Abayomi, Oluwademilade Aderemi Agboola, Remilekun Enitan Dosumu; Oyeronke Oluwatosin George},
      title = {A Conceptual Framework for Integrating Customer Intelligence into Regional Market Expansion Strategies},
      journal = {Iconic Research And Engineering Journals},
      year = {2021},
      volume = {5},
      number = {2},
      pages = {189-205},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1708471.pdf},
      abstract = {In the modern global business environment, regional market expansion has become a critical strategy for companies seeking sustainable growth and competitive advantage. However, expanding into new regions involves complex challenges, including understanding local market dynamics, consumer preferences, and competitive landscapes. Customer intelligence encompassing data collection, analysis, and application of consumer insights plays a pivotal role in addressing these challenges. This review presents a conceptual framework for integrating customer intelligence into regional market expansion strategies, aiming to improve decision-making, reduce market entry risks, and enhance customer engagement. The proposed framework is structured around four key steps: data collection and integration, market segmentation and targeting, strategic decision-making and adaptation, and performance monitoring with continuous feedback. It emphasizes the importance of gathering diverse consumer data from various touchpoints, such as social media, surveys, and transactional data, and using these insights to segment markets, define target customer profiles, and adapt marketing and product strategies. Furthermore, the framework highlights the need for agile decision-making, where businesses can continuously refine their strategies based on real-time customer feedback. Despite its potential, integrating customer intelligence presents challenges, including data availability, cultural differences, and privacy concerns. The framework addresses these obstacles by suggesting solutions such as leveraging local partnerships, investing in technology platforms, and ensuring compliance with regional data privacy regulations. By incorporating customer intelligence into regional market expansion, businesses can more effectively tailor their approaches to local consumer behaviors and preferences, ultimately increasing their chances of success in diverse markets. This conceptual framework provides a valuable roadmap for companies seeking to expand globally while remaining responsive to the evolving needs of regional markets.},
      keywords = {Conceptual framework, Integrating customer, Intelligence, Regional market, Expansion strategies},
      month = {August},
  }