Consistency and commonality in advertising content: Helping or Hurting?

Scholars and practitioners widely argue that strong, successful brands are built on consistent and unique positioning, which should be reflected in the brands’ advertising. Surprisingly, however, little empirical evidence supports this claim, especially with regard to advertising content. The authors investigate whether and to what extent brands’ advertising content consistency—the similarity in the firm’s own advertising content over time—and commonality—the similarity between the firm’s and competitors’ advertising content—affect brands’ sales. Insights emerge from the analysis of the impact on sales of the content of 247 television ads aired by 33 brands in six consumer packaged goods categories over a four-year period. Results indicate that more than advertising spending, both consistency and commonality in advertising content affect sales, especially with respect to long-term cumulative sales. However, brands differ considerably regarding the direction of the effects. While small brands tend to benefit from increased consistency and commonality in advertising content, large brands tend to suffer from increased consistency. Thus, whether consistency and commonality in advertising content will help or hurt depends on the size of the brand.     

Social commerce advertising avoidance and shopping cart abandonment: A fs/QCA analysis of German consumers

In recent years, due to the extensive use of social media advertisement and the development of social commerce tools, scholars and practitioners pay more attention to interaction with the digital channel, shopping intention, satisfaction, and retention. The objective of this study is to understand the shopping cart abandonment behavior as an outcome condition of ad avoidance on social media platforms. This research takes into consideration of cognitive, affective, and behavioral ad avoidance; alongside its antecedent conditions of perceived goal impediment, perceived add clutter, and prior negative experiences on social media. The research is conducted in Germany and Fuzzy sets/Qualitative Comparative Analysis (fs/QCA) is applied to understand the outcome condition of shopping cart abandonment. The findings imply that ad avoidance can create a learning mechanism for consumers about shopping cart abandonment of a brand or product if interrupted by a futile message or content. Theoretical and practical implications are discussed.     

How firm communication affects the impact of layoff announcements on brand strength over time

Firms usually undertake layoffs to improve financial performance. However, layoffs often have negative effects on various stakeholders, including consumers. In this paper, we examine the magnitude and duration of the potential negative effect of layoff announcements on brand strength. We also examine how a firm's communication accompanying a layoff can potentially counteract the observed negative effect of layoff announcements on brand strength. We compare how advertising communication intensity, social media communication (i.e., brand-initiated tweets), public relation (PR) communication, and communication of CSR initiatives moderate the main effect of layoff announcements on brand strength. Using an error correction model and drawing on 366 announcements of layoff events in Germany, this study identifies the magnitude and duration of the main effect. An examination of five years of weekly consumer brand perception data across multiple industries and domestic and foreign firms shows that advertising communication intensity and social media communication amplify the negative impact of layoff announcements on brand strength. Conversely, PR communication and communication of CSR initiatives help mitigate the negative effect. These findings provide guidance on the best way for firms to design firm communication in the context of layoff announcements.     

基于城市轨道交通网络的广告营销站点选择研究

城市轨道交通网络背景下的广告营销已成为一种流行的产品推广方式，快速、准确筛选出传播范围广、影响力高的站点，运营方和投资商对其投入大量广告可以产生较高的宣传力度和回报收益。影响力最大化的提出，为解决站点筛选提供了一种新的思路，首先提出一种融合节点结构信息和网络拓扑结构信息的网络表示学习模型，并将其用于学习网络节点的特征向量；进一步将网络节点的特征向量输入聚类算法中有效筛选候选种子集，同时结合贪婪策略从候选种子集中筛选出种子节点集合，进而有效提升网络节点影响力最大化问题求解效果。以武汉地铁网络为例进行验证，结果表明所提方法在传播范围上优于现有的影响力最大化方法，筛选高影响力站点具备合理性。