Artificial intelligence (AI) has rapidly emerged as a transformative force in multiple sectors, with digital marketing being a prominent beneficiary. As AI technologies continue to advance, their potential to reshape the digital marketing landscape becomes ever more apparent, leading to profound implications for businesses and their digital outreach strategies. This research seeks to answer the pivotal question: “How could AI applications be leveraged to optimize digital marketing strategies”? Drawing from a systematic literature review guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework, this study has identified 211 pertinent articles. Through a comprehensive bibliometric analysis, the findings were categorized into distinct clusters, namely: AI/ML (Machine Learning) Algorithms, Social Media, Consumer Behavior, E-Commerce, Digital Advertising, Budget Optimization, and Competitive Strategies. Each cluster offers insights into how AI applications can be harnessed to augment digital marketing efforts. The conclusion synthesizes key findings and suggests avenues for future exploration in this dynamic intersection of AI and digital marketing. This research contributes to the field by providing a comprehensive bibliometric analysis of AI in digital marketing, identifying key trends, challenges, and future directions. Our systematic approach offers valuable insights for businesses and researchers alike, enhancing the understanding of AI’s evolving role in digital marketing strategies.

The World Wide Web has become an essential modern tool for people’s daily routine. The fact that it is a convenient means for communication and information search has made it extremely popular. This fact led companies to start using online advertising by creating corporate websites. With the rapid increase in the number of websites, search engines had to come up with a solution of algorithms and programs to qualify the results of a search and provide the users with relevant content to their search. On the other side, developers, in pursuit of the highest rankings in the search engine result pages (SERPs), began to study and observe how search engines work and which factors contribute to higher rankings. The knowledge that has been extracted constituted the base for the creation of the profession of Search Engine Optimization (SEO). This paper consists of two parts. The first part aims to perform a literature review of the factors that affect the ranking of websites in the SERPs and to highlight the top factors that contribute to better ranking. To achieve this goal, a collection and analysis of academic papers was conducted. According to our research, 24 website characteristics came up as factors affecting any website’s ranking, with the most references mentioning quality and quantity of backlinks, social media support, keyword in title tag, website structure, website size, loading time, domain age, and keyword density. The second part consists of our research which was conducted manually using the phrases “hotel Athens”, “email marketing”, and “casual shoes”. For each one of these keywords, the first 15 Google results were examined considering the factors found in the literature review. For the measurement of the significance of each factor, the Spearman correlation was calculated and every factor was compared with the ranking of the results individually. The findings of the research showed us that the top factors that contribute to higher rankings are the existence of website SSL certificate as well as keyword in URL, the quantity of backlinks pointing to a website, the text length, and the domain age, which is not perfectly aligned with what the literature review showed us.

Start-up development, success, and sustainability are affected by contextual factors that constitute a regional entrepreneurship ecosystem. Based on previous literature, we propose the conceptual framework Start-Up Ecosystem (StUpEco) that highlights the contextual drivers of a start-up business affected by the entrepreneurial ecosystem entities involved within the quadruple helix model. Furthermore, the proposed framework is tested according to the perceptions of Greek start-uppers through an empirical survey. According to our findings, the start-uppers’ motivation is explained mainly through opportunity rather than necessity. The study identifies government issues, such as tax incentives and acceleration of starting procedures, availability of funding opportunities, connectivity of stakeholders, entrepreneurship education, previous start-up experience, incubator support, as well as mentoring, as the most significant issues affecting the successful development of start-ups.

The agribusiness sector shows tremendous growth and sustainability prospects by exploiting the challenges of “AgriFood-Tech” business models in the digital environment, by encouraging innovation, accelerating institutional and structural change, enhancing productivity, and introducing new products and services to the market. The purpose of this study is to investigate different types of “AgriFood-Tech” digital models and analyze their role in the agribusiness and AgriFood sector. Based on relevant literature research, the authors present and discuss five indicative examples of “AgriFood-Tech” models, using the Business Model Canvas (BMC) framework. The methodology included the analysis of the components of innovative AgriFood innovative business models paradigms, such as distribution channels, key partnerships, customer selection and relationships, financial viability, and value proposition. The goal was to explore their building blocks and the required decisions that create, deliver, and capture value. Our findings highlight the importance of specific features of the models, including online sharing of information between the stakeholders, online searches of agri-products, and logistics services in the agribusiness sector.

Purpose: The purpose of this paper is to present the evolution in notions from bibliometrics to altmetrics and confront them taking into consideration specific criteria. The objective of this paper is to present the evolution of research, regarding the above fields, the study of metrics and indicators used, and the strength and weaknesses resulting from the current literature. Furthermore, the authors present the manipulation techniques for both fields as their main weakness, as well as further key points, analyzing the alternative options of bibliometrics and altmetrics. Design/methodology/approach: First, the authors present the evolution of the literature, concerning the specific field and metrics used, following with a brief description of basic indicators related to the field of bibliometrics (journal impact factor (JIF), eigenfactor, article influence score and h-index) discussing their advantages and disadvantages. In the second part, the authors describe altmetrics and present the differences with bibliometrics. Findings: Both bibliometrics and altmetrics remain weak indicators as fraught with disadvantages with manipulation being the greatest of all. Nevertheless, the combination of the two is proposed in order to export safer conclusions on assessing the impact. Regarding the manipulation there is yet not a clean technique to eliminate manipulation. In specific, regarding bibliometrics, the manipulation of indicators refers only to the human factor intervention. The theoretical implication of this study constitutes of collecting the relevant literature regarding scientific indicators. Research limitations/implications: We must consider the study of new indicators, which combine metrics and methodologies used in both bibliometrics and altmetrics. The theoretical implication of this study constitutes of collecting the relevant literature regarding scientific indicators. Therefore, researchers are encouraged to test the proposed propositions further. Practical implications: The practical contribution, on the other side, provides scholars with the knowledge of how making their work more accessible, increasing their impact. Originality/value: The authors add to the originality by providing a framework of the relevant literature for bibliometrics and altmetrics for future researchers. The authors describe altmetrics and present the differences with bibliometrics. The authors conclude the research with the implications of the conducted analysis and the potential directions for future research. Regarding manipulation, the authors provide with the techniques so researchers are aware of the methods in order to protect their academic profile.