Journal of the Academy of Marketing Science最新文献

The use of social media influencers as persuasive marketing agents has become ubiquitous. However, a comprehensive understanding of their effectiveness, mechanisms, and moderation is still lacking. To address this gap, we conducted a meta-analysis of 71 papers, yielding 135 experimental studies and 571 effect sizes related to the impact of social media influencers compared to other forms of brand endorsements. Our results reveal that social media influencers significantly impact both consumer engagement and purchase intention, and they are relatively more effective than brand posts, virtual influencers, and celebrities. A meta-analytic structural equation model analyzing the influencing mechanisms suggests that social media influencers enhance consumer responses indirectly through their credibility and attractiveness. A meta-regression analysis further shows that various factors—including characteristics of the influencers, message, products, social media platforms, and followers, as well as their interaction with influencer size—moderate the effectiveness of social media influencers. Notably, our results indicate that influencer size can address some inconsistencies in previous research. For instance, small and medium-sized influencers are more effective in driving engagement, while larger influencers have greater impact on purchase intention. Our research provides novel, rich, and nuanced insights that can help managers with decisions such as: (a) when to choose influencers over alternatives, and (b) how to optimize their use.

Reports suggest some concerns with chief marketing officer (CMO) performance. We introduce CMO Role Design and theorize it is a critical factor impacting CMO performance outcomes. Employing a role theory lens, we develop a conceptual framework of CMO Role Design and provide an initial empirical examination of three characteristics from the broader model. We theorize that effective CMO Role Design requires alignment between specific characteristics to enable better performance outcomes. Surprisingly, we find that more than half (54%) of CMO roles are misaligned, indicating how challenging it is for firm leaders to design effective CMO roles. As the first conceptual model of CMO Role Design, this paper establishes a platform for future research, identifying over 25 new research questions. For CEOs, executive recruiters, and CMOs, this research offers insight into the importance of CMO Role Design and provides a template to consider when designing and staffing CMO roles.

Despite the importance of determining when it is appropriate to recontact digital customers, considering both retargeting effectiveness and privacy concerns, this issue has been underexplored in previous research. Unlike previous retargeting studies that infer decision stages from fragmented actions, we uncover consumers’ purchase concerns from a series of actions in their purchase journey. A randomized field experiment reveals that personalized retargeting, compared to non-personalized retargeting, improves purchase conversion for consumers with product-related concerns (e.g., product fit or price). However, for consumers with privacy concern dominance, it can backfire, decreasing purchase conversion. These findings highlight the importance of integrating retargeting audience and content research by identifying and addressing dominant purchase concerns. Insights from the studies help firms make better choices about whom to retarget and what messages to convey when developing retargeting strategies, resolving the trade-off between retargeting effectiveness and privacy concerns.

Brands are under increasing pressure to champion customer diversity, equity, and inclusion, but do customers always appreciate such efforts? Drawing on identity literature, we investigate when customer diversity initiatives (CDIs) backfire and propose strategies to mitigate this. Our research reveals that CDIs targeting a dissociative group more permanently evokes higher levels of brand distancing behaviors among existing customers compared to temporary efforts. This effect is driven by identity signaling threat and perceived betrayal. Aligning the duration of CDI with customers’ relationship types can help mitigate these negative reactions for sincere brands. Moreover, a sub-brand or product customization strategy reduces customers’ identity signaling threat toward a dissociative CDI, whilst highlighting the brand’s pro-social goals partially mitigates threat perceptions for sincere brands. Our findings offer critical insights for managers on promoting diversity without alienating existing customers.

Today an increasing number of TV shows and movies are released on online video streaming platforms. This study proposes a forecasting modeling framework that uses measures of a show’s consumption emotional features, or viewer sentiments triggered by the show’s production emotional features such as plot, as predictors to forecast a web show’s viewership. Our forecasting modeling framework has three components: feature construction, feature selection through in-sample prediction, and out-of-sample forecasting. In feature construction, we take advantage of the increasingly popular live commenting function in video streaming, which allows viewers to post spontaneous, visceral comments while watching. We utilize machine learning techniques to process the voluminous, unstructured live comment data to form “emotion waves,” which depict the evolution in viewers’ moment-to-moment sentiments throughout the show. We characterize emotion waves to form measures of consumption emotional features. We separately characterize positive and negative emotion waves, as well as their relative positions, and also separately characterize emotion waves in different narrative segments of a show. In feature selection, we use an in-sample prediction model to verify our proposed measures and use only key measures with significant impacts to build the forecasting model. Lastly, in out-of-sample forecasting, we show that a small number of key measures formed over a small sample of live comments available shortly after a show’s release can effectively forecast the show’s viewership accumulated in an extended period after its release.

Although the adoption of real-time syncing services—that is, services that synchronize online and television ads—is rising, there is still limited evidence about their effectiveness. We address this gap by examining the impact of coordinating branded search engine and television ads for a small direct-to-consumer company. We conducted a field experiment during a national television advertising campaign, randomly enabling and pausing the company’s branded text (text-based links triggered by the brand name) and shopping ads (visual product listing ads) across different geographic regions. The results show that television ads generate more website visits when text ads and both text and shopping ads are enabled compared to when search ads are paused. We also find that television ads alone decrease the conversion rate, but enabling shopping ads attenuates this decrease. The results demonstrate that search and television ads interact, which is a necessary condition for a real-time syncing strategy to increase revenues. Because the interactions occur at different stages of the path to purchase, we run a revenue analysis to assess the implications for real-time syncing. The analysis indicates that a real-time syncing strategy would have likely increased the focal company’s revenue compared with strategies that do not coordinate search and television ads.

This research identifies the differentiating characteristics, scope, trajectory, and navigation of the turbulent consumer journey (TCJ) for mental illness treatment. The TCJ is defined as a prolonged, crisis-ridden, high consequence journey marked by deep uncertainty. An unexpected crisis hijacks the consumer who lacks the knowledge to navigate an ongoing, dynamic, complex, and ambiguous environment. Confusion blindfolds and impedes rational decision-making. The high stakes handcuff the consumer, precluding journey abandonment or heuristic decision making. Examining the mental illness treatment context through sensemaking as an integrative framework, we show how consumers navigate deep uncertainty by noticing and connecting ambiguous cues, drawing inferences, and then taking actions that shape the next phase of the journey. Mapping the TCJ gives managers and policymakers fresh insights to improve the consumer experience in prolonged purchase environments marked by crises, high stakes, and deep uncertainty.

The open and user innovation (OUI) literature indicates that a variety of actors can play pivotal roles in the innovation process, but to date, many of these roles are under researched and poorly understood. Through a multiple stakeholder view combined with a systematic review of the OUI literature, we identify three key stakeholder roles (creator, contributor, customer) and three separate types of actors (individuals, firms, groups) to create a 3 × 3 OUI Stakeholder Matrix typology. This matrix encompasses the major stakeholders found in the OUI literature and is designed to foster closer collaboration between open innovation and user innovation scholars. Specifically, this article prioritizes identifying and understanding overlooked innovation stakeholders to clarify how their activities might create value for both customers and firms. The authors conclude by developing a series of actionable research questions centered on four primary themes that relate to stakeholder power, stakeholder role transitions and multi-role stakeholders, firms’ beliefs around what drives value in an OUI initiative, and the possible emergence of new stakeholders in OUI programs.