Harbingers of failure do exist: Their positive (negative) pre-release movie reviews provide a strong predictive signal that the movie will turn out to be a flop (success)

What reviews foretell about opening weekend box office revenue: the harbinger of failure effect in the movie industry. Pantelis Loupos, Yvette Peng, Sute Li & Hao Hao. Marketing Letters, April 13 2023. https://link.springer.com/article/10.1007/s11002-023-09665-8

Abstract: We empirically investigate the harbinger of failure phenomenon in the motion picture industry by analyzing the pre-release reviews written on movies by film critics. We find that harbingers of failure do exist. Their positive (negative) pre-release movie reviews provide a strong predictive signal that the movie will turn out to be a flop (success). This signal persists even for the top critic category, which usually consists of professional critics, indicating that having expertise in a professional domain does not necessarily lead to correct predictions. Our findings challenge the current belief that positive reviews always help enhance box office revenue and shed new light on the influencer-predictor hypothesis. We further analyze the writing style of harbingers and provide new insights into their personality traits and cognitive biases.

5 Conclusions and discussion

Predicting a movie’s box office revenue is one of the most fundamental needs in the motion picture industry. This becomes even more challenging when someone tries to predict the opening weekend box office revenue since there is little to no information available about the wider audience’s reaction. As Cabral and Natividad (2016) show in their work, doing well at the box office during the opening weekend has an economically and statistically significant effect on the movie’s eventual performance. Prior research has explored how different attributes of a movie, such as star inclusion (Elberse, 2007; Karniouchina, 2011; Liu et al., 2014), the activity level of editors and viewers of the movie’s corresponding entry in Wikipedia (Mestyán et al., 2013), and competition among movies that are released at the same time (Ainslie et al., 2005; Hennig-Thurau et al., 2007; Delre et al., 2016), could predict the box office performance. With regard to online movie reviews, Moon et al. (2010) show that movie ratings from professional critics and viewers’ communities are predictive of total box office revenue. Moreover, Basuroy et al. (2003) find that both positive and negative reviews are significantly correlated with box office revenue with the impact of negative reviews (but not positive reviews) diminishing over time. We diverge from this research and propose that a distinction should be made among movie critics because as we demonstrate not all positive (negative) reviews are a signal for success (failure).

More specifically, we combine three different data sources to empirically investigate the harbinger of failure phenomenon in the motion picture industry. We analyze the pre-release reviews written on movies by film critics and find that harbingers of failure do exist. Their positive pre-release reviews provide a strong predictive signal that the movie will turn out to be a flop. Moreover, we find the harbinger effect to be symmetric. That is, there are harbinger critics who give negative reviews and the movie turns out to be successful. These findings shed new light on the influencer-predictor hypothesis. We document that in a pre-release setting, there is a portion of movie critics that neither influence nor predict the right outcome of a movie. On the contrary, the outcome of the movie turns out to be the exact opposite of their prediction.

We further analyze the writing style of film critics and connect them to potential cognitive biases that might give rise to the harbinger phenomenon. We find that harbinger critics engage in an analytical and formal style of writing and have a lower rate of self-reference pronouns compared to non-harbingers. These differences indicate that harbinger critics are less self-reflective about the audience’s opinion compared to non-harbingers and tend to show overconfidence in their abilities. When we stratify the analysis across the critic status category, we find the aforementioned differences between harbingers and non-harbingers to be even more significant. In the cohort of top critics, which usually consists of professional and experienced reviewers, we find that top critic harbingers are also using more adverbs than their counterparts in their positive reviews indicating that they are over-optimistic in their assessments of movies. In the case of negative reviews, we find that the top critic harbingers are significantly more analytical than their counterparts.

Our findings have important managerial implications for the motion picture industry and its key channel entities: movie studios, distribution companies, and movie theaters. First, our research provides a methodology based on pre-release film reviews that allows movie producers and distributors to identify early on which movies are going to perform badly. This will in turn allow them to make better pre-launch marketing decisions and save significant marketing costs on flop movies. It will also allow theaters to better allocate their theater space, a finite resource that is crucial to the success of theaters. Second, film studios can greatly benefit from identifying the harbinger critics and using them during the early stages of production. More specifically, movie studios can use harbinger critics to select the scripts that will maximize their box office revenue instead of using mere guesswork. Our approach complements that of Eliashberg et al. (2007), which uses natural-language processing to select the winning scripts. Third, our approach can potentially serve as a diagnostic for reviewers across fields. It is crucial for companies that employ reviewers to know whether their reviewers’ opinions can be used as a diagnostic tool to determine success or failure. Based on that, companies might want to reclassify who they designate as a “top reviewer” or create a new class of reviewers.

We should acknowledge here the limitations of this work and present potential future research avenues. The main limitation of our research, similar to Anderson et al. (2015) and Simester et al. (2019), is that we do not provide a causal explanation about where the harbingers’ preferences are coming from. However, we do provide insights into their personality traits and cognitive biases based on their writing style. This paves new avenues for further experimental behavioral research about the underlying mechanisms of the harbinger phenomenon. A second potential limitation of our research is that movie producers and distributors could potentially strategically pick which critics to invite to their pre-release screenings. However, there is no substantial evidence that this is happening in the movie industry, as it would jeopardize the reputation of, and confidence in, movie studios and movie critics alike. Last, another possibility, unobserved to the researcher, is that critics are getting influenced by other critics before they submit their review by either reading their reviews or talking to them. Future research might include further contextual variables, such as the choice of movies to review by harbingers, the timing of the reviews, and the lack of learning, to further the theoretical understanding of the harbinger phenomenon in the motion picture industry.

To conclude, does the positive (negative) feedback given by film critics before the release of a movie signal its financial failure (success) instead of its success (failure) as currently believed? Our findings document that this is not always the case. At least in a pre-release movie setting, a distinction should be made among film critics because of the existence of harbinger critics; their endorsement of a movie is a signal of the opposite outcome.