Journal of Interactive Marketing最新文献

Tools for analyzing social media text data to gain marketing insight have recently emerged. While a wealth of research has focused on automated human personality assessment, little research has focused on advancing methods for obtaining brand personality from social media content. Brand personality is a nuanced aspect of brands that has a consistent set of traits aside from its functional benefits. In this study, we introduce a novel, automated, and generalizable data analytics approach to extract near real-time estimates of brand personalities in social media networks. This method can be used to track attempts to change brand personality over time, measure brand personality of competitors, and assess congruence in brand personality. Applied to consumer data, firms can assess how consumers perceive brand personality and study the effects of brand–consumer congruence in personality. Our approach develops a novel hybrid machine learning algorithmic design (LDA2Vec), which bypasses often extensive manual coding tasks, thus providing an adaptable and scalable tool that can be used for a range of management studies. Our approach enhances the theoretical understanding of channeled and perceived brand personality as it is represented in social media networks and provides practitioners with the ability to foster branding strategies by using big data resources.

Today, online social networks (OSNs) constitute a major part of our lives and have, to a large extent, replaced traditional media for direct communication, as well as information dissemination and gathering. In the vast amount of posts that get published in OSNs each day, some posts do not draw any attention while others catch on, become viral, and develop as so-called buzzes. Buzzes are defined through their characteristics of immediacy, unexpectedness, and intensity. The early detection of buzzes is of vital importance for companies, public figures, institutions, or political parties—e.g., for the pricing of profitable advertising placement or the development of an appropriate social media strategy. While previous researchers developed systems for detecting trending topics, mainly characterized by their intensity, this is the first study to implement a buzz detection system (BDS). Based on almost 120,000 manually classified Facebook posts, we estimated and trained models for the BDS by applying various classification techniques. Our results highlight that, among other predictors, the number of previously passive users who then engage in the buzz post, as well as the number of likes given to the comments, are important. Evaluating the BDS over a five-month evaluation period, we found that these two classifiers perform best and detected over 97% of the buzzes.

“Over-the-air” software upgrades are a recent trend in the automotive industry to distribute firmware directly to customers via the Internet. These upgrades can endow the vehicle with completely new functions that enhance safety, convenience, and performance. The US manufacturer Tesla was the first to integrate such upgrades on a regular basis to let customers participate in continuous innovation, giving Tesla a competitive edge over rival brands. Since then, several premium manufacturers have followed suit. This research examines how consumers perceive and respond to software upgradeability in durable high-tech products vis-à-vis integral product alternatives and hardware upgradeability. Results of four studies with more than 3,000 participants suggest that consumers evaluate software upgrades less positive than hardware upgrades because they perceive software as less capable to enhance product quality. However, bundling software upgrades to larger packages and stressing the low effort required to integrate new functions are viable ways to remedy this perception. Importantly, the findings suggest that offering products fully equipped with all premium functions to be unlocked via software upgrades—as done by several premium brands—is a risky strategy. Consumers react negatively to the artificial restriction of functionalities, irrespective of whether these are offered as temporary leases or permanent purchases. The findings provide initial evidence for the game-changing potential of software upgradeability and offer managers concrete guidance for designing and marketing upgradeable hardware-software platforms.

Digital marketing campaigns increasingly utilize social media influencers. Research in influencer marketing has investigated popularity metrics but found conflicting results on how the number of followers and likes on posts might influence consumers' behaviors. The present research investigates green living orientation of influencers as a moderating characteristic that leads to differential interpretation of popularity metrics in the context of green advertising messages. Specifically, lower popularity metrics seem to benefit green influencers or “greenfluencers.” An increased perception of trust in greenfluencers with lower popularity results in enhanced attitudes toward a sponsored product and increased purchase intentions. Additionally, consumers are willing to donate higher amounts to a related charity after exposure to a promotional post by a green influencer with low following. We present the results of three lab studies and discuss theoretical and practical implications.

Understanding customer experience with branded content on social media has become critical as brands allocate a considerable budget to the creation and dissemination of branded content. Customers interact with social media branded content such as brand-related images, videos, and text posts, and respond by engaging with content on social media. However, despite growing scholarly interest in social media experiences, there is a lack of research on the conceptualization and operationalization of the “branded content experience” (BCE) on social media. This research aims to enhance the understanding of customer experience with branded content by exploring several experience dimensions and construct a BCE scale. We derived seven BCE dimensions, including self-identity, social bonding, utilitarian, aesthetic, humor, awe-inspiring, and discerning with the help of two qualitative studies. We employed exploratory and confirmatory factor analysis to propose a reliable and valid 35-item BCE scale. The findings suggested that BCE predicts consumer engagement with branded content (CEBC) on social media.

The marketing literature has continued to examine trust and consumer privacy concern. A 1999 study that examined 17 industries found that improving trust and reducing privacy concern are two distinct approaches to managing consumer information, with the former being a more effective strategy than the latter (Milne & Boza, 1999). However, considering the shifting levels of consumer vulnerability due to technologies, managerial actions, and legal environment in the past two decades, a re-evaluation and extension of their findings is warranted. The current study uses a new and expanded dataset as well as new analytical techniques to re-examine the role of trust and privacy concern in managing consumer information. The new analysis shows that building trust still has a greater effect than reducing privacy concern on consumers' willingness to participate in information markets. Although trust and privacy concern have a negative relationship with each other, we find that privacy concern, paradoxically, is not negatively but positively related to direct marketing usage. This study also assesses the impact of trust and privacy concern across a typology for four quadrants of industries, the relationship of trust and concern with the managerial levels of transparency and control, and the moderating influence of age and sex.

Ephemeral social media is growing in popularity and brands are increasingly using this method to engage with and advertise to consumers. Yet, little research attention has been paid to how consumers perceive and retain social media content, particularly marketing communications, when they are aware it will disappear. Across five studies we find that when viewers know content is ephemeral, their recall of the content is heightened compared to when they believe the content will be accessible later. We find that this increase in recall due to ephemerality is mediated by processing effort, such that when consumers believe content will disappear, they expend more effort processing the content than if the content is believed to be accessible again. Relevant to advertisers, we find this effect spills over to advertising embedded within ephemeral social media content. Our findings represent a novel means of increasing advertising recall, qualify past findings and theory, and suggest an important new stream of research.