Search Results (139)

The relationship between firm size and the financial performance of advertising and marketing companies remains understudied in the academic literature, including in the regional context. Using a panel data methodology, this study analyzes the impact of three proxies for firm size (total assets, number of employees, and sales) on the financial performance (return on assets and profit margin) of the 500 most profitable advertising and marketing companies from 16 Western European countries over the period 2019–2023. Weighted least squares regression analysis revealed statistically significant negative effects of all three proxies for firm size on financial performance, with the strongest negative effects on total assets on return on assets and sales on profit margin, which is similar to return on sales. Empirical data confirm the inverse relationship between total assets and their profitability; this indicates the advantages of resource-optimized business models with high management flexibility and effective use of intellectual capital compared to material-intensive structures. The inverse relationship between the number of employees and financial performance is due to higher operating personnel costs and the difficulty of effectively managing human resources as the number of employees increases. Increased sales negatively affect profit margins, demonstrating a decrease in the efficiency of converting revenue into profits as operations expand. These findings are important for developing effective financial management strategies and making investment decisions in the industry under study. The research contributes to SDGs 8, 9, and 12 by demonstrating how resource-optimized structures with higher management flexibility and effective use of intellectual capital can outperform material-intensive structures in the advertising and marketing industry. Full article

This research investigates the strategic decision related to original content provision and business model selection within the rapidly evolving online video industry. We develop a two-sided market model involving a video platform, users, and advertisers to analyze how the platform balances subscription and advertising revenue while offering original content. This study finds that the amount of original content provided directly influences market equilibrium, affecting the platform’s choice between a purely subscription-based model or a mixed model. The cost of original content production plays a critical role in this decision-making process. High production costs may lead the platform to favor a mixed model, offering less original content to generate both subscription and ad revenue. Lower costs, however, encourage a subscription model with more original content to boost subscribing revenue. Additionally, factors such as network externalities between users and advertisers also impact the business model choice. Importantly, the model shows that allowing free users limited access to original content can expand both subscriber and advertiser engagement, enabling platforms to enhance dual revenue streams without having to sacrifice one for the other. Full article

Programmatic buying has attracted growing interest from manufacturers and has become a driving force behind the growth of digital advertising. Among various formats, mobile advertisements (ads) have emerged as a preferred choice over traditional ones due to their advanced automation, adaptability, and cost-effectiveness. Despite their increasing adoption, academic research on mobile ads remains relatively limited. Unlike conventional statistical analysis techniques, the proposed feature selection methods eliminate the need for assumptions related to data properties such as independence, normal distribution, and constant variance in regression. Additionally, feature selection techniques have recently gained traction in big data analysis, addressing the limitations inherent in traditional statistical approaches. Consequently, this study aims to determine the key success factors of mobile ads in fostering customer loyalty, offering advertisers valuable insights for optimizing mobile ad design. This study begins by identifying potential factors influencing mobile advertising effectiveness. Then, it applies Support Vector Machine Recursive Feature Elimination (SVM-RFE), correlation-based selection, and consistency-based selection methods to determine the key drivers of customer retention. The findings reveal that “Price” and “Preference” are the most significant contributors to enhancing repurchase intention. Moreover, factors such as “Language”, “Perceived Usefulness”, “Interest”, “Mobile Device”, and “Informativeness” are also essential in maximizing the effectiveness of mobile advertising. Full article

In Taiwan, large advertising billboards on commercial buildings consume significant energy, exacerbating environmental challenges and straining sustainability efforts. This study explores the potential of rooftop solar photovoltaic systems (SPVS) to power these billboards, offering a dual solution for energy reduction and financial viability. Using a fuzzy nonlinear multi-objective programming approach, the research demonstrates that SPVS investments become profitable by the ninth year (0.7232% return), rising to 5.4463% by the twentieth year, while a 26-day reduction in construction time cuts carbon emissions by 223.11 kg. The innovative Revenue–Time–Cost–Quality–Carbon Emissions (RTCQCE) framework balances economic gains with environmental benefits, leveraging advertising revenue to fund SPVS. This model bridges a research gap by integrating financial and ecological factors, providing a practical tool for sustainable urban development in Taiwan. Full article

This paper addresses the issue of distinguishing commercially played songs from non-music audio in radio broadcasts, where automatic song identification systems are commonly employed for reporting purposes. Service call costs increase because these systems need to remain continuously active, even when music is not being broadcast. Our solution serves as a preliminary filter to determine whether an audio segment constitutes “music” and thus warrants a subsequent service call to an identifier. We collected 139 h of non-consecutive 5 s audio samples from various radio broadcasts, labeling segments from talk shows or advertisements as “non-music”. We implemented multiple data augmentation strategies, including FM-like pre-processing, trained a custom Convolutional Neural Network, and then built a live inference platform capable of continuously monitoring web radio streams. This platform was validated using 1360 newly collected audio samples, evaluating performance on both 5 s chunks and 15 s buffers. The system demonstrated consistently high performance on previously unseen stations, achieving an average accuracy of 96% and a maximum of 98.23%. The intensive pre-processing contributed to these performances with the benefit of making the system inherently suitable for FM radio. This solution has been incorporated into a commercial product currently utilized by Italian clients for royalty calculation and reporting purposes. Full article

This study examines the efficacy of a novel form of consumer-generated content (CGC) digital advertising, termed “directed” consumer-generated content (DCGC), in comparison to traditional brand-created social media advertisements. The analysis focuses on performance metrics and return on ad spend (ROAS). Data were gathered from social media campaigns incorporating both DCGC and non-CGC through a field experiment, followed by a rigorous statistical analysis to identify the most effective advertising strategies. Findings indicate that DCGC typically results in significantly higher conversion rates, increased conversions, and superior ROAS. Overall, DCGC advertisements demonstrate enhanced performance relative to non-CGC campaigns, suggesting that they represent a more strategic allocation of a brand’s marketing resources, particularly when the primary objective is to drive sales and achieve elevated conversion rates. This research contributes to the academic discourse and practical implementation of social media advertising by highlighting the advantages of DCGC as a cost-effective and efficient advertising approach for brands. Full article

Written accounts of cultural festivals often deal with the various activities that comprise those types of events. There is a paucity of analyses that discuss how festivals encourage the status quo of consumption practices, while conjuring their hidden costs on society. This paper analyses how the Hamburg Cruise Days Festival attempted to perpetuate the status quo of the cruising industry. The research answers the following question: What would it take to help change the current “cobalt” color promoted by the organizers of the Hamburg’s Waterfront Cruise Days Festival to a “True Blue”, a symbol of the cleanest sky and harbor waters in Germany, and the best example of sustainable Green and Blue Infrastructure in Europe? The research methods comprised in loco fieldwork participant observation in the tradition of participatory action research. It is argued that, from a governance perspective, festival organizers ought to be required to disclaim, in the fashion of “truth in advertising”, the ecological impacts and sponsors’ progress toward reaching existing environmental standards to eradicate costly social and environmental injustices. Said practice will increase our individual and collective awareness of the invaluable richness of the world’s land- and water-based environment before it is irreplaceably exhausted. The article suggests extending events’ emphasis on sustainable tourism to also encompass three additional measures: (i) the socio-ecological performance of the cruise (and shipping) industry; (ii) in the fashion of a Solomonic approach to justice; and (iii) within a formalized Porto of Call Sister Cities Network. Full article

Generative adversarial networks (GANs) are widely used in image conversion tasks and have shown unique advantages in the context of face image beautification, as they can generate high-resolution face images. When used alongside potential spatial adjustments, it becomes possible to control the diversity of the generated images and learn from small amounts of labeled data or unsupervised data, thus reducing the costs associated with data acquisition and labeling. At present, there are some problems in terms of face image beautification processes, such as poor learning of the details of a beautification style, the use of only one beautification effect, and distortions being present in the generated face image. Therefore, this study proposes the facial image beautification generative adversarial network (FIBGAN) method, in which images with different beautification style intensities are generated with respect to an input face image. First, a feature pyramid network is used to construct a pre-encoder to generate multi-layer feature vectors containing the details of the face image, such that it can learn the beautification details of the face images during the beautification style transmission. Second, the pre-encoder combines the separate style vectors generated with respect to the original image and the style image to transfer the beautification style, such that the generated images have different beautification style intensities. Finally, the weight demodulation method is used as the beautification style transmission module in the generator, and the normalization operation on the feature map is replaced with the convolution weight to eliminate any artifacts from the feature map and reduce distortions in the generated images. The experimental results show that the FIBGAN model not only transmits the beautification style to face images in a detailed manner but also generates face images with different beautification intensities while reducing the distortion of the generated face images. Therefore, it can be widely used in the beauty and fashion industry, advertising, and media production. Full article

With the rising trend toward sustainable consumption and the pivotal role of social media in the buying behavior, brands are keen to promote sustainable products through these platforms. Virtual influencers (VIs) have emerged as lower-cost and scandal-resistant alternatives to human influencers (HIs). However, their artificial nature may evoke credibility concerns, potentially undermining marketing effectiveness. Currently, it is unclear whether humans or virtual influencers achieve better endorsement outcomes for sustainable products. This study explores the effectiveness of VIs and HIs in endorsing sustainable products and the conditions under which VIs may outperform HIs. Through two studies (N = 1097), we investigate the impact of influencer type, advertising appeals, and product involvement on consumer purchase intentions and brand attitudes. Our findings reveal that, in low-involvement product scenarios with emotional appeals, HIs are more effective, while in high-involvement product scenarios featuring rational appeals, VIs exhibit superior effectiveness. These results suggest that the choice of influencer type should be tailored to the product involvement level and the nature of the advertising appeal, providing guidance for brands to enhance the impact of their green marketing strategies. Full article

Display field communication (DFC) is an emerging technology that enables seamless communication between electronic displays and cameras. It utilizes the frequency-domain characteristics of image frames to embed and transmit data, which are then decoded and interpreted by a camera. DFC offers a novel solution for screen-to-camera data communication, leveraging existing displays and camera infrastructures. This makes it a cost-effective and easily deployable solution. DFC can be applied in various fields, including secure data transfer, mobile payments, and interactive advertising, where data can be exchanged by simply pointing a camera at a screen. This article provides a comprehensive survey of DFC, highlighting significant milestones achieved in recent years and discussing future challenges in establishing a fully functional DFC system. We begin by introducing the broader topic of screen–camera communication (SCC), classifying it into visible and hidden SCC. DFC, a type of spectral-domain hidden SCC, is then explored in detail. Various DFC variants are introduced, with a focus on the physical layer. Finally, we present promising experimental results from our lab and outline further research directions and challenges. Full article

Background and Objectives: In 2022, the Centers for Disease Control and Prevention (CDC) discovered that 2.55 million middle and high school students were using electronic cigarettes (e-cigarettes) in the US alone. E-cigarettes allow people to inhale a nicotine solution (e-liquid) into their bodies. While e-cigarettes are often advertised as a way to help people quit traditional tobacco products, the World Health Organization (WHO) has stated that there is no proof of e-cigarettes being effective at reducing an individual’s tobacco use. The objective of this study is to determine why adolescents start smoking e-cigarettes. Materials and Methods: For the following study, the National Youth Tobacco Survey (NYTS) 2021 was used. This is a nationally representative cross-sectional survey that includes middle and high school students. The data were analyzed using SAS v.9.4. The odds ratio for smoking e-cigarettes was evaluated for both sex and race via a logistic regression. Results: It was discovered that the percentage of only e-cigarette smokers (12.10%) was 5.5 times the percentage of only traditional smokers (2.19%). Additionally, the median age at which adolescents started smoking e-cigarettes was fifteen years with an IQR (Inter Quartile Range) of two. We used a logistic regression to show that biological sex and race were significant predictors of e-cigarette usage. Conclusions: In general, we saw that adolescents were mostly starting to smoke e-cigarettes because their friends were doing it, out of curiosity, they were depressed or anxious, and/or to get a “high”, implying that adolescents mostly started smoking in order to fit in and/or to numb themselves. Interestingly, reasons like cost, using them to quit smoking, seeing them in the media, and ease of attainment were ranked the lowest when it came to smoking e-cigarettes. However, their lower costs naturally lead to increased accessibility compared to traditional cigarettes, making them easier to reach the hands of teenagers. Overall, in this paper, we aim to identify if adolescents are choosing e-cigarettes as their first foray into tobacco products and why. Full article

It is estimated that 10% to 20% of road accidents are related to fatigue, with accidents caused by drowsiness up to twice as deadly as those caused by other factors. In order to reduce these numbers, strategies such as advertising campaigns, the implementation of driving recorders in vehicles used for road transport of goods and passengers, or the use of drowsiness detection systems in cars have been implemented. Within the scope of the latter area, the technologies used are diverse. They can be based on the measurement of signals such as steering wheel movement, vehicle position on the road, or driver monitoring. Driver monitoring is a technology that has been exploited little so far and can be implemented in many different approaches. This work addresses the evaluation of a multidimensional drowsiness index based on the recording of facial expressions, gaze direction, and head position and studies the feasibility of its implementation in a low-cost electronic package. Specifically, the aim is to determine the driver’s state by monitoring their facial expressions, such as the frequency of blinking, yawning, eye-opening, gaze direction, and head position. For this purpose, an algorithm capable of detecting drowsiness has been developed. Two approaches are compared: Facial recognition based on Haar features and facial recognition based on Histograms of Oriented Gradients (HOG). The implementation has been carried out on a Raspberry Pi, a low-cost device that allows the creation of a prototype that can detect drowsiness and interact with peripherals such as cameras or speakers. The results show that the proposed multi-index methodology performs better in detecting drowsiness than algorithms based on one-index detection. Full article

This paper explores the current status of bio-based insulation materials (BbIMs) integration in Europe, through structured online questionnaires. with industry experts. The findings show that the main common difficulties are obtaining European Conformity (CE) marking, high costs, a skills gap, a lack of trained builders, and slow acceptance from industry decision-makers. On the other hand, the main common opportunities are the gradual improvement with certain supportive policies and incentives, the growing environmental awareness, thermal, acoustic, and environmental performance, long-term cost savings and value, and increasing educational initiatives, advertising, and awareness campaigns. The finding also emphasizes the critical role that users and buyers play in the adoption of these materials as a potential driver and barrier. The professionals suggest strengthening environmentally friendly standards, integrating natural materials into construction databases, leading by example, withdrawing subsidies for hazardous waste disposal, providing continuing education, workshops, collaboration among stakeholders, and referencing exemplary projects in France. Further insights on bio-based building materials integration in building information modeling (BIM) practices indicate that the rate of their integration is very low. This research contributes to the scientific literature on BbIMs, by highlighting the barriers to the widespread use of these materials in practice and promoting the drivers of their widespread use. Future research should address more insights from other uncovered countries and the countries with limited insight (The Netherlands, Switzerland, and Portugal) in the current study as well as End-users’ perceptions. Full article

Agriculture is essential to any country’s economy. Agriculture is crucial not only for feeding a country’s population but also for its impact on other businesses. The paradox of agri-food companies generating substantial profits despite seemingly high product prices is explored in this article, focusing on the role of digital marketing within the agri-food industry. Enhanced digital marketing performance leads to efficient advertising campaigns, through reduced advertising costs and increased resource efficiency. To do so, the authors collected web analytical data from five established agri-food firms with the highest market capitalization. Then, linear regression and correlation analyses were used, followed by the utilization of fuzzy cognitive mapping (FCM) modeling. The analysis revealed that increased traffic through search sources is associated with reduced advertising costs. Additionally, enhanced website engagement contributes to lower advertising expenses, emphasizing the optimization of the user experience. However, it has been discovered that allocating funds for social media advertising eventually results in higher expenses with higher website-abandoning rate. Ultimately, successful management of the balance between product costs and profitability in the agri-food sector lies on the increased use of search sources and greatly reducing the use of social media sources. Full article

Due to social and psychological factors, the COVID-19 pandemic has impacted international trade, dampened consumption globally, and resulted in conservative investment and spending. To stimulate economic recovery while promoting the establishment of a positive consumption awareness among people, enterprises endeavor to enhance competitiveness and expand market share through various means, such as advertising and discounting. With more attention paid to environmentally friendly products, there are greater challenges encountered by green supply chain management. In this study, a green supply chain network problem is analyzed, involving a manufacturer and a retailer. In addition to the construction of centralized and decentralized decision models, two cost-sharing contracts are adopted to reduce promotion costs for the retailer and improve the level of greenery in products. With the help of game theory, equilibrium decisions can be made by solving the models. According to the results of numerical experiment, cost-sharing contracts can effectively improve the level of greenery in products and the profitability of the supply chain, despite the inability to achieve a win–win situation. Full article