How has data-driven marketing evolved: Challenges and opportunities with emerging technologies

Rosário, Albérico Travassos; Dias, Joana Carmo

doi:10.1016/j.jjimei.2023.100203

Cited by 58 publications

(7 citation statements)

References 66 publications

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“…In contrast to traditional literature reviews, SBLR follows a replicable, scientific, and transparent process that aims to minimize bias by exhaustively searching both published and unpublished literature related to the study topic [28][29][30]. The researcher also provides an audit trail, enabling readers to evaluate the quality of the studies included in the review, as well as the research procedures and conclusions.…”

Section: Methodsmentioning

confidence: 99%

Bibliometric Systematic Literature Review of Problem-Based Learning Entrepreneurship

Raimundo,

Rosário

2024

Preprint

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The augmenting commitment in the entrepreneurial learning process, both at academic and industry level, has led to new mechanisms and methodologies. Entrepreneurship literature has shown evidence of raising interest in the problem-based learning (PBL) methodology with regard to upcoming events from the surrounding learning context. This paper presents a Systematic Bibliographic Literature Review (SBLR) with respect to the application of PBL throughout distinct entrepreneurial processes either in higher education, or in industry. It aimed to identify relevant entrepreneurial opportunities for PBL. Bibliographic databases were searched for documents published between 2002 and May 2024 to categorize key topics discussed in the literature on PBL and entrepreneurship. The review process identified 142 empirical and non-empirical papers on entrepreneurship related PBL. Data analysis revealed diverse subthemes for PBL uses in entrepreneurship in both higher education institutions and industry. The research questions “What is the interplay of problem-based learning methodology with entrepreneurship?” guided the study. The central output of the research is the discovery of the varying uses of PBL to cope with diverse events arising within entrepreneurship context. Future research directions are suggested.

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Section: Methodsmentioning

confidence: 99%

Bibliometric Systematic Literature Review of Problem-Based Learning Entrepreneurship

Raimundo,

Rosário

2024

Preprint

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“…On the other hand, it optimizes customer information to develop a marketing strategy. It involves using online and offline channels to collect complex data that is then analyzed to understand customers better Rosario & Dias (2023).…”

Section: Sources Of Information From the Physical Environment Using Aimentioning

confidence: 99%

Model of Consumer Behavior When Applying Ai at Every Point of Consumer Contact

Zlatanova-Pazheva

2024

Int. J. Eng. Tech. Mgmt. Res.

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The article outlines the basic aspects needed to study the consumer behavior. The first of them is related to existing sources of information on consumer behavior that use modern technologies. For this purpose, both online and physical sources of information using AI are presented. The second aspect is about the factors that influence consumer behavior. The third question is related to the role of AI technology for consumer experience in the purchase process. These three aspects are set as the framework needed to build the presented model of consumer behavior when applying AI at every point of consumer contact.

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“…Real-world applications showcase the breadth of impact. In marketing, campaigns become more targeted and effective through data-driven insights (Rosário, et al, 2023, Ikwuagwu et al, 2020. In manufacturing, processes optimize efficiency based on analytics-derived recommendations.…”

Section: Impact On Decision-making Processes In Big Data Analytics In...mentioning

confidence: 99%

Big Data Analytics: A Review of Its Transformative Role in Modern Business Intelligence

Chioma Ann Udeh,

Omamode Henry Orieno,

Obinna Donald Daraojimba

et al. 2024

Comput. sci. IT res. j.

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In the dynamic landscape of modern business intelligence, Big Data Analytics has emerged as a transformative force, reshaping the way organizations derive insights from vast and diverse datasets. This paper provides a concise overview of the key themes explored in the comprehensive review of Big Data Analytics and its impact on modern business intelligence. Big Data Analytics represents a paradigm shift in decision-making processes, offering organizations the capability to harness the full potential of their data assets. The review delves into the multifaceted role of Big Data Analytics, emphasizing its significance in strategic planning, risk management, operational optimization, and customer-centric initiatives. Strategic planning takes a quantum leap forward as organizations leverage predictive analytics to anticipate market trends. The integration of analytics-derived insights aligns decision-making with overarching organizational objectives, driving a more informed and forward-thinking approach to strategic initiatives. Risk management becomes more proactive with the integration of Big Data Analytics, particularly in fraud detection and prevention. The ability to process large volumes of data in real-time enhances vigilance, mitigating financial risks associated with fraudulent activities cenario modeling further empowers organizations to assess and address potential risks before they materialize. Operational optimization becomes a focal point as analytics uncovers inefficiencies in manufacturing processes, supply chains, and retail operations. Real-time decision-making in retail, enabled by data analytics, ensures agility and responsiveness to changing market dynamics and customer preferences. Customer-centric initiatives are elevated through personalized marketing campaigns and predictive analytics in customer support. The review explores how Big Data Analytics enables organizations to craft personalized experiences, enhancing customer satisfaction and loyalty. The study encapsulates the transformative journey of Big Data Analytics in modern business intelligence, emphasizing its role in navigating strategic complexities, mitigating risks, optimizing operations, and placing the customer at the center of decision-making processes. The comprehensive review provides insights for organizations seeking to harness the transformative potential of Big Data Analytics in the data-driven era. Keywords: Big Data, Business Intelligence, Data Analytics, Modern Business, Review.

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How has data-driven marketing evolved: Challenges and opportunities with emerging technologies

Cited by 58 publications

References 66 publications

Bibliometric Systematic Literature Review of Problem-Based Learning Entrepreneurship

Bibliometric Systematic Literature Review of Problem-Based Learning Entrepreneurship

Model of Consumer Behavior When Applying Ai at Every Point of Consumer Contact

Big Data Analytics: A Review of Its Transformative Role in Modern Business Intelligence

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