Modern Research in Decision Making

The Role of Data-Driven Analytics and Artificial Intelligence in Enhancing Decision-Making and Corporate Marketing Capabilities

Document Type : Original Article

Authors

Seyed Alireza Safavian 1
Fereshteh Mansouri Moayyed 2
Seyed Hamid Khodadad Hosseini 3

1 Master's Degree, Department of Business Administration, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran

2 Associate Professor, Business Administration, Department of Business Administration, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran

3 Professor, Business Administration, Department of Business Administration, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran

Abstract
In modern business, organizations require data-driven marketing analytics, big data capabilities, and artificial intelligence (AI) to make effective decisions. This study simultaneously examines these three elements and evaluates the role of AI as both a mediator and moderator in enhancing marketing analytics and strengthening corporate marketing capabilities. The volume of data generated across multiple channels, along with the complexity of consumer behavior, poses significant challenges for extracting actionable insights for effective marketing strategies. This research is applied in nature. The study population included industry and academic experts from Iran and Canada. Using Cohen’s formula for an undefined population, the sample size was determined as 138 participants and selected through a non-probabilistic convenience sampling method. Data were collected via a questionnaire, with reliability confirmed for all items (Cronbach’s alpha = 0.778). Findings indicate that big data capabilities significantly impact data-driven marketing analytics, while AI functions as both a mediator and moderator in the relationships among variables. Furthermore, results suggest that the development of corporate marketing capabilities through marketing analytics can be achieved with higher accuracy and speed. The main contribution of this study lies in examining the simultaneous mediating and moderating roles of AI in strengthening the relationship between big data capabilities and the effectiveness of data-driven marketing analytics.

Keywords

Marketing analytics
Big data capabilities
Artificial intelligence
Corporate marketing capabilities
Decision-making
[1]    G. Agag et al., “Understanding the relationship between marketing analytics, customer agility, and customer satisfaction: A longitudinal perspective.,” Journal of Retailing and Consumer Services, vol. 77, p. 103663, Mar. 2024, doi: 10.1016/J.JRETCONSER.2023.103663.
[2]    M. Wedel and P. K. Kannan, “Marketing Analytics for Data-Rich Environments,” J Mark, vol. 80, no. 6, pp. 97–121, Nov. 2016, doi: 10.1509/jm.15.0413.
[3]    A. Gunasekaran et al., “Big data and predictive analytics for supply chain and organizational performance,” J Bus Res, vol. 70, pp. 308–317, Jan. 2017, doi: 10.1016/J.JBUSRES.2016.08.004.
[4]    G. Cao and N. Tian, “Enhancing customer-linking marketing capabilities using marketing analytics,” Journal of Business & Industrial Marketing, vol. 35, no. 7, pp. 1289–1299, Jun. 2020, doi: 10.1108/JBIM-09-2019-0407.
[5]    R. Abdollahzadeh, H. Vazifehdoost and A. Vafaeinejad, “Location-Based marketing of banks by using a new Geomarketing model based on Spatial Data Infrastructure (Case study: Semnan city)” Modern researches in decision making, vol. 7, no. 1, p. 1-25, 2022, dor: 20.1001.1.24766291.1401.7.1.1.6. [in Persian].
[6]    X. Liang, G. Li, H. Zhang, E. Nolan, and F. Chen, “Firm performance and marketing analytics in the Chinese context: A contingency model,” J Bus Res, vol. 141, pp. 589–599, Mar. 2022, doi: 10.1016/J.JBUSRES.2021.11.061.
[7]    S. Akter, S. Sultana, M. Mariani, S. F. Wamba, K. Spanaki, and Y. K. Dwivedi, “Advancing algorithmic bias management capabilities in AI-driven marketing analytics research,” Industrial Marketing Management, vol. 114, pp. 243–261, Oct. 2023, doi: 10.1016/j.indmarman.2023.08.013.
[8]    D. D. C. Tarn and J. Wang, “Can data analytics raise marketing agility?-A sense-and-respond perspective,” Information & Management, vol. 60, no. 2, p. 103743, Mar. 2023, doi: 10.1016/J.IM.2022.103743.
[9]    R. Dwivedi, S. Nerur, and V. Balijepally, “Exploring artificial intelligence and big data scholarship in information systems: A citation, bibliographic coupling, and co-word analysis,” International Journal of Information Management Data Insights, vol. 3, no. 2, p. 100185, Nov. 2023, doi: 10.1016/J.JJIMEI.2023.100185.
[10]    G. Cao, Y. Duan, and A. El Banna, “A dynamic capability view of marketing analytics: Evidence from UK firms,” Industrial Marketing Management, vol. 76, pp. 72–83, Jan. 2019, doi: 10.1016/J.INDMARMAN.2018.08.002.
[11]    T. Davenport, A. Guha, D. Grewal, and T. Bressgott, “How artificial intelligence will change the future of marketing,” J Acad Mark Sci, vol. 48, no. 1, pp. 24–42, Jan. 2020, doi: 10.1007/s11747-019-00696-0.
[12]    R. Bouncken, M. Ratzmann, R. Barwinski, and S. Kraus, “Coworking spaces: Empowerment for entrepreneurship and innovation in the digital and sharing economy,” J Bus Res, vol. 114, pp. 102–110, Jun. 2020, doi: 10.1016/J.JBUSRES.2020.03.033.
[13]    M. Gupta and J. F. George, “Toward the development of a big data analytics capability,” Information & Management, vol. 53, no. 8, pp. 1049–1064, Dec. 2016, doi: 10.1016/j.im.2016.07.004.
[14]    U. Awan, S. Shamim, Z. Khan, N. U. Zia, S. M. Shariq, and M. N. Khan, “Big data analytics capability and decision-making: The role of data-driven insight on circular economy performance,” Technol Forecast Soc Change, vol. 168, p. 120766, Jul. 2021, doi: 10.1016/j.techfore.2021.120766.
[15]    C. Adrian, R. Abdullah, R. Atan, and Y. Y. Jusoh, “Conceptual Model Development of Big Data Analytics Implementation Assessment Effect on Decision-Making,” International Journal of Interactive Multimedia and Artificial Intelligence, vol. 5, no. 1, p. 101, 2018, doi: 10.9781/ijimai.2018.03.001.
[16]    R. Vidgen, S. Shaw, and D. B. Grant, “Management challenges in creating value from business analytics,” Eur J Oper Res, vol. 261, no. 2, pp. 626–639, Sep. 2017, doi: 10.1016/j.ejor.2017.02.023.
[17]    M. Gupta and J. F. George, “Toward the development of a big data analytics capability,” Information & Management, vol. 53, no. 8, pp. 1049–1064, Dec. 2016, doi: 10.1016/j.im.2016.07.004.
[18]    M. L. Santos-Vijande, A. B. del Río-Lanza, L. Suárez-Álvarez, and A. M. Díaz-Martín, “The brand management system and service firm competitiveness,” J Bus Res, vol. 66, no. 2, pp. 148–157, Feb. 2013, doi: 10.1016/j.jbusres.2012.07.007.
[19]    J. B. Barney, “How marketing scholars might help address issues in resource-based theory,” J Acad Mark Sci, vol. 42, no. 1, pp. 24–26, Jan. 2014, doi: 10.1007/s11747-013-0351-8.
[20]    E. Fang and S. Zou, “Antecedents and consequences of marketing dynamic capabilities in international joint ventures,” J Int Bus Stud, vol. 40, no. 5, pp. 742–761, Jun. 2009, doi: 10.1057/jibs.2008.96.
[21]    R. K. Srivastava, T. A. Shervani, and L. Fahey, “Market-Based Assets and Shareholder Value: A Framework for Analysis,” J Mark, vol. 62, no. 1, pp. 2–18, Jan. 1998, doi: 10.1177/002224299806200102.
[22]    G. Day, “Closing the Marketing Capabilities Gap,” J Mark, vol. 75, pp. 183–195, Jul. 2011, doi: 10.2307/41228619.
[23]    S. Arunachalam, S. N. Ramaswami, P. Herrmann, and D. Walker, “Innovation pathway to profitability: the role of entrepreneurial orientation and marketing capabilities,” J Acad Mark Sci, vol. 46, no. 4, pp. 744–766, Jul. 2018, doi: 10.1007/s11747-017-0574-1.
[24]    H. Wilson and M. Mcdonald, Marketing Plans: How to prepare them, how to use them - 7th edition. 2011.
[25]    N. Morgan, D. Vorhies, and C. Mason, “Market Orientation, Marketing Capabilities, and Firm Performance,” Strategic Management Journal, vol. 30, pp. 909–920, Jan. 2009.
[26]    N. A. Morgan, C. S. Katsikeas, and D. W. Vorhies, “Export marketing strategy implementation, export marketing capabilities, and export venture performance,” J Acad Mark Sci, vol. 40, no. 2, pp. 271–289, Mar. 2012, doi: 10.1007/s11747-011-0275-0.
[27]    N. R. Sanders, “How to Use Big Data to Drive Your Supply Chain,” Calif Manage Rev, vol. 58, no. 3, pp. 26–48, May 2016, doi: 10.1525/cmr.2016.58.3.26.
[28]    A. Gandomi and M. Haider, “Beyond the hype: Big data concepts, methods, and analytics,” Int J Inf Manage, vol. 35, no. 2, pp. 137–144, 2015.
[29]    K. Eisenhardt and J. Martin, “Dynamic Capabilities: What Are They?,” Strategic Management Journal, vol. 21, pp. 1105–1121, Oct. 2000, doi: 10.1002/1097-0266(200010/11)21:10/113.0.CO;2-E.
[30]    V. Sena, S. Bhaumik, A. Sengupta, and M. Demirbag, “Big Data and Performance: What Can Management Research Tell us?,” British Journal of Management, vol. 30, no. 2, pp. 219–228, Apr. 2019, doi: 10.1111/1467-8551.12362.
[31]    Kumar Ayush, “Artificial Intelligence (AI) For Marketing Analytics,” Analytics Steps. Accessed: Aug. 12, 2023. [Online]. Available: https://www.analyticssteps.com/blogs/artificial-intelligence-ai-marketing-analytics
[32]    M. A. Hossain, R. Agnihotri, M. R. I. Rushan, M. S. Rahman, and S. F. Sumi, “Marketing analytics capability, artificial intelligence adoption, and firms’ competitive advantage: Evidence from the manufacturing industry,” Industrial Marketing Management, vol. 106, pp. 240–255, Oct. 2022, doi: 10.1016/j.indmarman.2022.08.017.
[33]    G. Cao, Y. Duan, and A. El Banna, “A dynamic capability view of marketing analytics: Evidence from UK firms,” Industrial Marketing Management, vol. 76, pp. 72–83, Jan. 2019, doi: 10.1016/j.indmarman.2018.08.002.
[34]    N. A. Morgan, R. J. Slotegraaf, and D. W. Vorhies, “Linking marketing capabilities with profit growth,” International Journal of Research in Marketing, vol. 26, no. 4, pp. 284–293, Dec. 2009, doi: 10.1016/j.ijresmar.2009.06.005.
[35]    Gefen, Rigdon, and Straub, “Editor’s Comments: An Update and Extension to SEM Guidelines for Administrative and Social Science Research,” MIS Quarterly, vol. 35, no. 2, p. iii, 2011, doi: 10.2307/23044042.
[36]    D. F. Benoit, S. Lessmann, and W. Verbeke, “On realising the utopian potential of big data analytics for maximising return on marketing investments,” Journal of Marketing Management, vol. 36, no. 3–4, pp. 233–247, Feb. 2020, doi: 10.1080/0267257X.2020.1739446.
[37]    K. Conboy, P. Mikalef, D. Dennehy, and J. Krogstie, “Using business analytics to enhance dynamic capabilities in operations research: A case analysis and research agenda,” Eur J Oper Res, vol. 281, no. 3, pp. 656–672, Mar. 2020, doi: 10.1016/j.ejor.2019.06.051.
[38]    C. Stadler, C. E. Helfat, and G. Verona, “The Impact of Dynamic Capabilities on Resource Access and Development,” Organization Science, vol. 24, no. 6, pp. 1782–1804, Dec. 2013, doi: 10.1287/orsc.1120.0810.
[39]    B. Merrilees, S. Rundle-Thiele, and A. Lye, “Marketing capabilities: Antecedents and implications for B2B SME performance,” Industrial Marketing Management, vol. 40, no. 3, pp. 368–375, Apr. 2011, doi: 10.1016/j.indmarman.2010.08.005.
[40]    G. Cao, N. Tian, and C. Blankson, “Big Data, Marketing Analytics, and Firm Marketing Capabilities,” Journal of Computer Information Systems, vol. 62, no. 3, pp. 442–451, 2022, doi: 10.1080/08874417.2020.1842270.
[41]    J. Cohen, Statistical Power Analysis for the Behavioral Sciences. Routledge, 2013. doi: 10.4324/9780203771587.
[42]    D. S. Soper, “A-priori Sample Size Calculator for Structural Equation Models [Software].” Accessed: Mar. 22, 2025. [Online]. Available: https://www.danielsoper.com/statcalc
[43]    A. Field, Discovering Statistics Using IBM SPSS Statistics: And Sex and Drugs and Rock “N” Roll, 4th ed. Los Angeles, London, New Delhi: SAGE Publications, 2013.
[44]    M. A. Ashaari, K. S. D. Singh, G. A. Abbasi, A. Amran, and F. J. Liebana-Cabanillas, “Big data analytics capability for improved performance of higher education institutions in the Era of IR 4.0: A multi-analytical SEM & ANN perspective.,” Technol Forecast Soc Change, vol. 173, Dec. 2021, doi: 10.1016/j.techfore.2021.121119.
[45]    P. Mikalef, N. Islam, V. Parida, H. Singh, and N. Altwaijry, “Artificial intelligence (AI) competencies for organizational performance: A B2B marketing capabilities perspective,” J Bus Res, vol. 164, Sep. 2023, doi: 10.1016/j.jbusres.2023.113998.
[46]    L. J. Cronbach, “Coefficient Alpha and the Internal Structure of Tests,” Psychometrika, vol. 16, no. 3, pp. 297–334, 1951, doi: DOI: 10.1007/BF02310555.
[47]    C. Fornell and D. F. Larcker, “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error,” Journal of Marketing Research, vol. 18, no. 1, p. 39, Feb. 1981, doi: 10.2307/3151312.
[48]    B. Thompson, Exploratory and confirmatory factor analysis:  Understanding concepts and applications. Washington,  DC,  US: American Psychological Association, 2004. doi: 10.1037/10694-000.
[49]    R. B. Kline, Principles and practice of structural equation modeling, 4th ed. in Methodology in the social sciences. New York,  NY,  US: Guilford Press, 2016.
[50]    M. Stone, “Cross-Validatory Choice and Assessment of Statistical Predictions,” Journal of the Royal Statistical Society. Series B (Methodological), vol. 36, no. 2, pp. 111–147, 1974, [Online]. Available: http://www.jstor.org/stable/2984809
[51]    J. Bettray, A. Suessmair, and T. Dorn, “Perceived Price Fairness in Pay-What-You-Want: A Multi-Country Study,” American Journal of Industrial and Business Management, vol. 07, no. 05, pp. 711–734, 2017, doi: 10.4236/ajibm.2017.75051.
[52]    J. F. Hair, R. Christian M., and M. and Sarstedt, “PLS-SEM: Indeed a Silver Bullet,” Journal of Marketing Theory and Practice, vol. 19, no. 2, pp. 139–152, Apr. 2011, doi: 10.2753/MTP1069-6679190202.
[53]    L. Hu and P. M. Bentler, “Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives,” Struct Equ Modeling, vol. 6, no. 1, pp. 1–55, Jan. 1999, doi: 10.1080/10705519909540118.
[54]    M. E. Sobel, “Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models,” Sociol Methodol, vol. 13, p. 290, 1982, doi: 10.2307/270723.
[55]    R. Rialti, L. Zollo, A. Ferraris, and I. Alon, “Big data analytics capabilities and performance: Evidence from a moderated multi-mediation model,” Technol Forecast Soc Change, vol. 149, p. 119781, Dec. 2019, doi: 10.1016/J.TECHFORE.2019.119781.
[56]    Ö. Işık, M. C. Jones, and A. Sidorova, “Business intelligence success: The roles of BI capabilities and decision environments,” Information & Management, vol. 50, no. 1, pp. 13–23, Jan. 2013, doi: 10.1016/j.im.2012.12.001.
[57]    W. Yu, G. Zhao, Q. Liu, and Y. Song, “Role of big data analytics capability in developing integrated hospital supply chains and operational flexibility: An organizational information processing theory perspective,” Technol Forecast Soc Change, vol. 163, p. 120417, Feb. 2021, doi: 10.1016/j.techfore.2020.120417.
[58]    P. Mikalef, V. A. Framnes, F. Danielsen, J. Krogstie, and D. Olsen, “Big data analytics capability: antecedents and business value,” 2017.
[59]    J. S. Johnson, S. B. Friend, and H. S. Lee, “Big Data Facilitation, Utilization, and Monetization: Exploring the 3Vs in a New Product Development Process,” Journal of Product Innovation Management, vol. 34, no. 5, pp. 640–658, Sep. 2017, doi: 10.1111/jpim.12397.
[60]    H. Zhang, M. Song, and H. He, “Achieving the Success of Sustainability Development Projects through Big Data Analytics and Artificial Intelligence Capability,” Sustainability, vol. 12, no. 3, p. 949, Jan. 2020, doi: 10.3390/su12030949.
[61]    R. Srinivasan and M. Swink, “An Investigation of Visibility and Flexibility as Complements to Supply Chain Analytics: An Organizational Information Processing Theory Perspective,” Prod Oper Manag, vol. 27, no. 10, pp. 1849–1867, Oct. 2018, doi: 10.1111/poms.12746.
[62]    M. Ghobakhloo, A. Rajabzadeh Ghatari, A. Toloie Eshlaghy, and mahmood Alborza, “Provide an Opinion Analysis-Based Recommender System for Personalized Personal Banking Services,” Modern researches in decision making, vol. 5, no. 1, pp. 25–49, 2020, [Online]. Available: https://journal.saim.ir/article_39238.html [in Persian].
[63]    S. F. Wamba, A. Gunasekaran, S. Akter, S. J. fan Ren, R. Dubey, and S. J. Childe, “Big data analytics and firm performance: Effects of dynamic capabilities,” J Bus Res, vol. 70, pp. 356–365, Jan. 2017, doi: 10.1016/J.JBUSRES.2016.08.009.
[64]    C. Stadler, C. E. Helfat, and G. Verona, “The Impact of Dynamic Capabilities on Resource Access and Development,” Organization Science, vol. 24, no. 6, pp. 1782–1804, Dec. 2013, doi: 10.1287/orsc.1120.0810.
[65]    B. Merrilees, S. Rundle-Thiele, and A. Lye, “Marketing capabilities: Antecedents and implications for B2B SME performance,” Industrial Marketing Management, vol. 40, no. 3, pp. 368–375, Apr. 2011, doi: 10.1016/j.indmarman.2010.08.005.
[66]    R. Kachouie, F. Mavondo, and S. Sands, “Dynamic marketing capabilities view on creating market change,” Eur J Mark, vol. 52, no. 5/6, pp. 1007–1036, Apr. 2018, doi: 10.1108/EJM-10-2016-0588.
[67]    S. H. Khodadad Hosseini, A. Meshbaki, and S. Khoddami, “Designing a market performance model based on dynamic marketing capabilities with an operational agility approach,” Management Research in Iran, vol. 19, no. 3, pp. 83–112, 2021, [Online]. Available: https://mri.modares.ac.ir/article_368.html [in Persian].
[68]    K. J. Preacher, D. D. Rucker, and A. F. Hayes, “Addressing moderated mediation hypotheses: Theory, methods, and prescriptions,” Multivariate Behav Res, vol. 42, no. 1, pp. 185–227, 2007, doi: 10.1080/00273170701341316.

Home

Guide for Authors

Submit Manuscript

Reviewers

Contact Us