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The growing number of firms leveraging social media ads highlight the urgent need for firms to understand social media ads and their effects on consumer perceptions and attitudes. This research examines whether and how different types of social media ads exert influences on ad engagement and how consumers’ psychological characteristics including regulatory orientation and lay rationalism moderate the influence of social media ads on ad engagement.

This research conducts three quasi experiments featuring two types of social media ads – interactive and transactional – to collect empirical evidence. Results are analyzed using ANOVA and Process in SPSS.

This research reveals that interactive ads lead to higher perceived enjoyment and perceived responsiveness, which further lead to higher ad engagement. Promotion focus moderates the effect of social media ads (interactive vs transactional ads) on perceived enjoyment and perceived responsiveness, and lay rationalism moderates the effect on perceived responsiveness, while prevention focus has no such effect.

First, this research establishes the connection between ad types and ad engagement in social media, which offers a new perspective to understand ad engagement. Second, it explores the underlying mechanisms of processing different types of social media ads. Third, it justifies the moderating effects of consumers’ regulatory orientation and lay rationalism on the effects of ad types on ad engagement, providing the first evidence on the moderating role of consumers’ lay rationalism in ad processing. This research helps firm marketers to fine-tune their social media ads according to consumer characteristics.

This paper aims to investigate the extent to which nostalgic advertising can foster brand love. It examines the effects of two common forms of nostalgia in advertising – that is, personal and historical nostalgia – on consumers’ love towards a brand in both a developed (the UK) and a developing country (India).

A pre-test and post-test quasi-experimental study was conducted with two representative samples of consumers (i.e. 277 British and 255 Indian). Respondents were randomly exposed to one ad evoking either personal or historical nostalgia, or a non-nostalgic ad.

The results indicate that the use of nostalgia in advertising increases brand love in both countries. However, the effectiveness of each type of nostalgia varies depending on the country considered. In the UK, personal nostalgia increases brand love more than historical nostalgia, whereas, in India, historical nostalgia was found to be more significantly related to brand love than personal nostalgia.

The primary implication for marketers is to consider nostalgic advertising as a critical lever to building longer-term value for a brand (i.e. brand love) whilst being mindful of the country-specific differences regarding how such a lever should be executed to achieve effectiveness be effective.

The paper contributes to the advancement of the brand love literature by clarifying whether, and under what circumstances, the use of specific types of nostalgia in advertising increases consumers’ love towards a brand.

Running advertising campaigns and attracting the traffic, as well as collecting information from users who have entered the website once, provides the conditions to perform retargeting campaigns and consequently increases website visit rates and sales. The purpose of this research is to design a roadmap of retargeting campaign for small and medium enterprises (SMEs), as well as to compare normal and retargeting advertising campaigns in order to confirm the effectiveness of retargeting campaigns.

A single-case-study strategy was adopted by choosing advertising Company-X to design the roadmap of retargeting campaigns and evaluate its effectiveness. Using a purposive sampling, semi-structured interviews were conducted with 14 experts of advertising Company-X. Furthermore, the documents and reports available in the company were also analyzed. Thematic analysis was employed to analyze the interviews and documents. Next, a one-way ANOVA test and a two-sample t-test were used to measure the effectiveness of retargeting campaigns of the Company-X compared to normal campaigns with secondary data of 22 SMEs for a six-month period.

The qualitative phase led to the presentation of a roadmap for the retargeting campaigns in three stages: preparation, process and implementation. The results of the quantitative phase revealed that the ratio of clicks to impressions (click-through rate) and the ratio of successful purchase tags to clicks (conversion rate) are much higher in the retargeting product campaign. Therefore, the performance of selected SMEs as an example in the product retargeting campaign was better than that of the non-retargeting campaigns. Also, the ratio of cost to the successful purchase tag was higher for the product retargeting campaigns.

This study contributes to the literature of retargeting. First, this study provides SMEs with a successful roadmap for retargeting campaigns. Second, this research reveals the effectiveness and mechanism of retargeting for SMEs.

Advertisements facilitate certain emotions, subsequently influencing purchase intentions. Humor, as an influential way of information expression, is frequently used in ads to elicit emotions. Drawing upon literature on advertisement humor and new product purchase intention and the theory of planned behavior, the study proposes that humor stimulation in advertisements can affect consumers' new product purchase intentions, in which two process mechanisms, namely, emotional arousal and cognitive flexibility, play a mediating effect.

To test the assertions, the authors conduct three experimental studies. The authors' first study assesses the main effect between advertisement humor and purchase intentions. In the second study, the authors show the mediating effects of emotional pleasure, emotional arousal, and cognitive flexibility on the relationship between advertisement humor and purchase intentions. In the first two experiments, the authors study incremental new products. In the third study, the authors study the same mediating relationships for radically new products.

This study's results show consumers that watch humorous ads are more likely to choose new products than those who watch non-humorous ads (Study 1); compared with non-humorous ads, humorous ads can enhance emotional arousal, thus promoting cognitive flexibility and making consumers more inclined to choose new products (Study 2 and Study 3). That said, the authors find that these mediation effects are only partial.

This study's results have important implications for firms vying to enhance consumers' new product purchase intentions by deploying humorous ads.

Sports advertisements such as the Super Bowl showcase products and brands that have invested increasingly large sums financially to gain viewers’ attention. However, how audio features in advertisements impact viewers' behavior remains unexplored.

Using the lens of signaling theory, this research uses advanced data analytics of voice and music audio in Super Bowl advertisements to examine its impacts on viewers.

Results show that advertisement viewers prefer more voiced frames and have a greater liking behavior of voiced frames with a low intensity (less loud) and a higher F1 frequency, which is typically associated with male vocal tracts. A fast music tempo works better for longer advertisements. The model controls for various types of ad appeals. The research underlines the importance of voice and music in signaling successful brand features that are likely to increase the ad-liking behavior of consumers (positive effect).

The current research implies that brands advertising through sports ads must carefully select voice actors and music in order to provide the most positive signals for a brand to have the most significant effect and, thus, a greater return on the high sums invested in the ads.

First, this research contributes in terms of a new research process for using audio analytics in advertising. The detailed research process outlined can be used for future research examining audio and music from advertisements. Second, our findings provide additional support to the important role of voice features (e.g. intensity and frequency) as signals in inducing responses from consumers (Biswas et al., 2019; Hagtvedt and Brasel, 2016). Third, the study surfaces a new theoretical association: the effect of tempo in moderating the relationship between duration and propensity to like an ad.

This study aims to explore the attraction, influence and persuasive effect of advertising (with or without metaphor) across different types of hotels (luxury vs. budget hotels).

Two independent variables – namely, the hotel category (luxury versus budget) and the use of rhetorical figures (text with metaphors versus text without metaphors) – serve as the basis for the investigation. The research design is a 2 × 2 within-subjects construct based on eye-tracking methodology complemented by questionnaire-based data collection. Participants were engaged with hotel advertisements under four specific conditions, each reflecting a distinct combination of the two independent variables.

The findings reveal the augmented attention-grabbing prowess of advertisements that use metaphors compared to those that do not. Furthermore, the study findings reveal that the hotel category significantly influences the efficacy of advertising; advertisements promoting luxury hotels were found to stimulate superior impression recall, garner higher customer affinity and prompt a more potent intention to patronize the hotel. Finally, the study shows that neither congruent nor incongruent pairings of visual (budget or luxury hotel) and verbal elements (with or without metaphor) yield additional advertising benefits.

This research addresses the limited empirical guidance available for hotel operators at various levels regarding the design of advertisements incorporating rhetorical devices. It highlights the potential benefits of using figurative rhetoric, especially metaphors, in advertising for both budget and luxury hotels. The study reveals a notable correlation between hotel category, particularly luxury offerings, and customer attention, retention, preference and intention to visit. Furthermore, it encourages hotel operators, regardless of their hotel’s ranking, to incorporate metaphorical language into their advertising designs, underscoring the need for strategic integration in overall advertisement planning.

Using high-resolution online eye-tracking technology, this study innovatively examines the influence of hotel category and rhetorical devices on the effectiveness and attention-grabbing potential of advertisements. Through this approach, the study seeks to offer valuable managerial and advertising insights for those involved in hotel marketing.

This study investigates advertising avoidance behavior among consumers, specifically in the realm of meta-platforms. It explores the impacts of digital burnout, advertising clutter, perceived advertising risk, and goal impediment on cognitive and behavioral ad avoidance.

With a sample of 410 respondents, the research employs a comprehensive analysis approach with SEM and CFA, integrating Avoidance Motivation Theory. It examines direct and indirect influences on ad avoidance, mediated by consumer emotions and attitudes. The study highlights the moderating role of content quality in shaping these relationships.

Significant links were found between digital burnout, clutter, perceived advertising risk, and goal impediment with cognitive and behavioral ad avoidance. The study emphasizes the importance of content quality and suggests strategies that focus on emotional resonance, user alignment, and reduced intrusion.

For advertisers and marketers in digital spaces, the findings recommend strategies promoting healthy technology usage, streamlined advertising content, transparent communication aligned with user goals, and emotionally resonant campaigns to mitigate ad avoidance behaviors.

Understanding consumer sentiments aids policymakers in creating conducive advertising models, benefiting both consumers and businesses. This enhances user experiences in digital environments.

The paper distinctively applies the Avoidance Motivation Theory to the context of avoiding social media advertisements, thereby uncovering the causes of negative consumer emotions and attitudes, and highlighting the crucial role of content quality as a means to counteract these adverse reactions.

This paper aims to manage the dilemma of cyberspace operations, as the incidence of cybercrimes has increased tremendously in the past few decades, turning cyberspace into a field of war in which all nations must fight. For many countries, cyberattacks and conflicts, and even the basic operation of cyberspace in general, are new territories. Furthermore, international law today does not address many aspects of cyber warfare, as it typically has dealt with only traditional warfare.

This study examined this crime whether it is a domestic or an international crime and whether cyber wars are under international law or domestic law to address these issues.

Although many attempts to criminalize these actions occurred, the findings suggest that the world has failed to frame the legal instruments against cyberattacks. The findings also suggest recommendations to solve this issue.

To the best of the author’s knowledge, this study analyzed the comparison between the same crime in the perspective of domestic and international law, highlighting an unsolved dilemma in the world, suggesting some unprecedented solutions to solve.

This study aims to test Singer’s suggestion that ‘over the next 20 years meat could follow smoking into disrepute” using the findings of the recent literature on meat consumption, education and smoking and data from consumers in Switzerland in 1990–2017.

We hypothesise that meat consumption in developed countries has increasingly shifted to people with less education, as has been observed for smoking in previous studies. Using trend analysis by regressions, we describe the consumption dynamics of nine sorts of meat in Switzerland and estimate meat consumption trends for populations with and without university education separately.

Our results partly confirm the hypothesis. Less educated households consume more non-fish meat per person than households with at least one member educating or having finished education at university. For most categories of meat, the relative decline in consumption has been significantly higher for households in which at least one person holds a university education.

Our study contributes to the studies on sociology of meat eating and suggests paying more attention to risks related to meat consumption and to awareness of the population about these risks.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0335

Earned value management (EVM)–based models for estimating project actual duration (AD) and cost at completion using various methods are continuously developed to improve the accuracy and actualization of predicted values. This study primarily aimed to examine natural gradient boosting (NGBoost-2020) with the classification and regression trees (CART) base model (base learner). To the best of the authors' knowledge, this concept has never been applied to EVM AD forecasting problem. Consequently, the authors compared this method to the single K-nearest neighbor (KNN) method, the ensemble method of extreme gradient boosting (XGBoost-2016) with the CART base model and the optimal equation of EVM, the earned schedule (ES) equation with the performance factor equal to 1 (ES1). The paper also sought to determine the extent to which the World Bank's two legal factors affect countries and how the two legal causes of delay (related to institutional flaws) influence AD prediction models.

In this paper, data from 30 construction projects of various building types in Iran, Pakistan, India, Turkey, Malaysia and Nigeria (due to the high number of delayed projects and the detrimental effects of these delays in these countries) were used to develop three models. The target variable of the models was a dimensionless output, the ratio of estimated duration to completion (ETC(t)) to planned duration (PD). Furthermore, 426 tracking periods were used to build the three models, with 353 samples and 23 projects in the training set, 73 patterns (17% of the total) and six projects (21% of the total) in the testing set. Furthermore, 17 dimensionless input variables were used, including ten variables based on the main variables and performance indices of EVM and several other variables detailed in the study. The three models were subsequently created using Python and several GitHub-hosted codes.

For the testing set of the optimal model (NGBoost), the better percentage mean (better%) of the prediction error (based on projects with a lower error percentage) of the NGBoost compared to two KNN and ES1 single models, as well as the total mean absolute percentage error (MAPE) and mean lags (MeLa) (indicating model stability) were 100, 83.33, 5.62 and 3.17%, respectively. Notably, the total MAPE and MeLa for the NGBoost model testing set, which had ten EVM-based input variables, were 6.74 and 5.20%, respectively. The ensemble artificial intelligence (AI) models exhibited a much lower MAPE than ES1. Additionally, ES1 was less stable in prediction than NGBoost. The possibility of excessive and unusual MAPE and MeLa values occurred only in the two single models. However, on some data sets, ES1 outperformed AI models. NGBoost also outperformed other models, especially single models for most developing countries, and was more accurate than previously presented optimized models. In addition, sensitivity analysis was conducted on the NGBoost predicted outputs of 30 projects using the SHapley Additive exPlanations (SHAP) method. All variables demonstrated an effect on ETC(t)/PD. The results revealed that the most influential input variables in order of importance were actual time (AT) to PD, regulatory quality (RQ), earned duration (ED) to PD, schedule cost index (SCI), planned complete percentage, rule of law (RL), actual complete percentage (ACP) and ETC(t) of the ES optimal equation to PD. The probabilistic hybrid model was selected based on the outputs predicted by the NGBoost and XGBoost models and the MAPE values from three AI models. The 95% prediction interval of the NGBoost–XGBoost model revealed that 96.10 and 98.60% of the actual output values of the testing and training sets are within this interval, respectively.

Due to the use of projects performed in different countries, it was not possible to distribute the questionnaire to the managers and stakeholders of 30 projects in six developing countries. Due to the low number of EVM-based projects in various references, it was unfeasible to utilize other types of projects. Future prospects include evaluating the accuracy and stability of NGBoost for timely and non-fluctuating projects (mostly in developed countries), considering a greater number of legal/institutional variables as input, using legal/institutional/internal/inflation inputs for complex projects with extremely high uncertainty (such as bridge and road construction) and integrating these inputs and NGBoost with new technologies (such as blockchain, radio frequency identification (RFID) systems, building information modeling (BIM) and Internet of things (IoT)).

The legal/intuitive recommendations made to governments are strict control of prices, adequate supervision, removal of additional rules, removal of unfair regulations, clarification of the future trend of a law change, strict monitoring of property rights, simplification of the processes for obtaining permits and elimination of unnecessary changes particularly in developing countries and at the onset of irregular projects with limited information and numerous uncertainties. Furthermore, the managers and stakeholders of this group of projects were informed of the significance of seven construction variables (institutional/legal external risks, internal factors and inflation) at an early stage, using time series (dynamic) models to predict AD, accurate calculation of progress percentage variables, the effectiveness of building type in non-residential projects, regular updating inflation during implementation, effectiveness of employer type in the early stage of public projects in addition to the late stage of private projects, and allocating reserve duration (buffer) in order to respond to institutional/legal risks.

Ensemble methods were optimized in 70% of references. To the authors' knowledge, NGBoost from the set of ensemble methods was not used to estimate construction project duration and delays. NGBoost is an effective method for considering uncertainties in irregular projects and is often implemented in developing countries. Furthermore, AD estimation models do fail to incorporate RQ and RL from the World Bank's worldwide governance indicators (WGI) as risk-based inputs. In addition, the various WGI, EVM and inflation variables are not combined with substantial degrees of delay institutional risks as inputs. Consequently, due to the existence of critical and complex risks in different countries, it is vital to consider legal and institutional factors. This is especially recommended if an in-depth, accurate and reality-based method like SHAP is used for analysis.