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Abstract: Research Question (RQ):This study addresses how content marketing can be clearly defined and applied, particularly for organizations that are in the early stages of adoption or have not yet implemented it, with emphasis on its key elements, interaction with consumers, and its influence on consumer purchase decision-making.Purpose:The purpose of this research was to examine the influence of content marketing on consumer purchase decisions. The aim of the research was to highlight the importance of content marketing in terms of strategic marketing planning and its impact on achievingeffective and competitive marketing organizations.Method:The research is based on a primary empirical quantitative approach. It was conducted on a sample of 128 students and younger employed persons from the city of Zagreb. Various scientific research methods were used, including analysis and synthesis, abstraction and concretization, generalization and specialization, inductive and deductive methods, classification, description, and statistical methods. For hypothesis testing, univariate and bivariate analyses were applied, particularly correlation and regression analysis.Results:The research results showed a statistically significant and positive influence of content marketing on consumer purchase decisions (p < 0.001). Regression analysis confirmed the predictive ability of content marketing in shaping purchase decisions, which also confirmed the research hypothesis.Organization:The findings of the research have important practical implications for managers and marketing experts, as they show that content marketing is an effective strategy for increasing company performance, creating greater value for consumers, and achieving competitive advantage in the market.Society:The research highlights the role of digital communities and viral communication in shaping new social dynamics that extend beyond individual consumer behavior to broader societal interactions.Originality:The originality of the research lies in the development of a simple research model for examining the influence of content marketing on purchase decisions. The study contributes to the understanding of this relatively new field and opens possibilities for the further development of this research domain.Limitations / Further Research:The study is limited by a relatively small sample size and cross-sectional design, which restricts generalization and longitudinal analysis. Future research should include larger samples and longitudinal approaches.
Keywords: content marketing, consumer behaviour, purchase decisions, digital marketing, viral communication, marketing strategy, online communities, decision-making
Published in RUP: 12.06.2026; Views: 94; Downloads: 4
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Abstract: In the context of fierce competition among tourist destinations and increasing difficulty of differentiation, developing a strong destination image is particularly important. A comprehensive understanding of how tourists perceive destinations through user-generated images can help destination management organizations (DMOs) design more effective marketing strategies. This is especially relevant for destinations with spatially and temporally dispersed tourism resources and strong seasonal dynamics. This paper analyses inbound tourist photographs by combining deep learning techniques with spatial analysis to examine the spatial and temporal distribution of photo scenes and shifts in scene preferences among tourists. The study focuses on three distinct types of destinations in Slovenia—urban (Ljubljana), nature-based/alpine (Bled), and coastal (Piran, Izola, Koper)—providing insights into how image-based spatial scene analysis can inform destination marketing strategies. The results reveal significant spatial and temporal heterogeneity of scenes across micro destinations. Nature-based destinations exhibit lower topic entropy and fewer topic changes per user, whereas urban destinations show higher variability, with users changing topics on average five times per day. Seasonal effects are moderate: nature-based destinations display lower topic entropy in winter and higher in autumn and spring, coastal destinations show less pronounced seasonal variation, and urban destinations show almost none. These findings provide valuable insights into the spatial and temporal distribution of tourist interests and offer practical guidance for DMOs in strategic marketing planning.
Keywords: tourist destination image, user-generated content, deep learning, spatial-temporal analysis, destination marketing strategy
Published in RUP: 18.02.2026; Views: 549; Downloads: 10
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Keywords: blockchain, centralized/decentralized marketplace, games, marketing, liquidity, NFT, player retention, game engagement
Published in RUP: 04.10.2025; Views: 715; Downloads: 11
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Keywords: influencer marketing, celebrity endorsement, authenticity, consumer trust, digital marketing, social media engagement
Published in RUP: 14.07.2025; Views: 1149; Downloads: 20
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Keywords: socialni marketing, vpliv na otroke, tehnološka podjetja
Published in RUP: 07.04.2025; Views: 1393; Downloads: 45
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