Amsterdam Business School
Bachelor Economics and Business
Specialization: Business Administration
Emotions will never lie:
To what extent do the sentiments of online reviews lead to the exploration of a
new market segment ?
BSc Thesis by
Ágota Szögi
11088605
Supervisor: Dr. Frederik Situmeang
Amsterdam: June 26th 2018
Statement of originality
This document is written by Student Ágota Szögi, 11088605, who declares to take full responsibility for the contents of this document.
I declare that this text and the work presented in this document are original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
Abstract
This study focuses on what drives companies to engage in risk-taking behavior by exploring new market segments in the creative industries, and particularly in the movie industry. Academic literature acknowledges the fact that managers tend to be risk-averse and base their decisions on past performance according to the prospect and behavioral theory. Moreover, performing below a targeted level directly affects someone’s behavior to be more risk-taking. This study contributes to previous literature by investigating how financial performance drives the strategic decisions of managers in case of movie sequels, and how other performance indicators, such as the sentiments of the highly influential online consumer reviews affect organizational strategies. The paper further explains the spillover effect of evaluations in relation to product extension strategies. By analyzing a sample of 182 movie sequels, the results reveal that both the financial indicators of past performance, and the sentiments of consumers have a positive effect on the explorative behavior of firms. Thus, this study has differing results to prior literature on risk-taking behavior, such as managers are more willing to engage in a risky explorative behavior when they have higher revenues, and not when they face financial difficulties. More importantly, the analysis of the consumer reviews provides new insight on their effects, such as the forward spillover of online reviews also has an impact on the explorative behavior or firms, and not only the performance of their future products. To conclude, organizations might identify the positive sentiments of the reviews with a positive image that consumers may use to associate with a high quality of their products. Therefore, this would drive firms to engage in a risky, explorative behavior.
Keywords: content of online consumer reviews, positive sentiments, financial performance, explorative
Table of Contents
Abstract……….……….……….. 2
I. Introduction ……….……….………... 4
II. Theoretical Background ………...………...……….…………... 7
2.1 Explorative versus Exploitative Strategy …..………..…...……….. 7
2.2 Online Reviews…………...…………..………...………….……….. 8
2.2.1 Different Aspects of Online Reviews ……..………...…………...….………. 9
2.2.2 Content of Online Reviews. ………..………... 10
2.2.3 Expert versus Consumer Online Reviews……….…….………...11
III. Methodology ………..……….. 13
3.1 Data Collection ……….……….………. 14
3.2 Data Cleaning………...……… 14
3.3 Description of Data and Variables ………...………... 15
IV. Results ………....……….. 18
4.1 Descriptive Statistics and Correlations ………....18
4.2 Regression ………..………. 19
V. Discussion ………....………. 21
5.1 Discussion of Findings.……… 21
5.2 Theoretical Implications ………. 23
5.3 Practical Implications ………….………. 24
5.4 Limitations and Future Research …....………... 25
VI. Conclusion ……….……….. 26
I Introduction
“Of what use is freedom of speech to those who fear to offend?” “Your intellect may be confused, but your emotions will never lie to you.”
- Roger Ebert
Online reviews are proved to be more and more important, such as according to a survey by Bright Local (2014) cited by Forbes Magazine, 88 % of the consumers trust online reviews as much as personal recommendations. Therefore, online reviews are proven to be an important type of electronic word of mouth (eWOM), thus it has been in the center of attention both for theory and practice. However most of the researches have been focusing on the valence and volume of the reviews (Duan, Gu, & Whinston, 2008; Purnawirawen, Eisend, De Pelsmacker & Dens, 2015). King, Racherla, & Bush (2014) argue that only a few studies have focused on the importance of semantics and narratives (on the actual content) in eWOM messages.
According to Archak, Anindya, and Panagiotis (2011) reviews that give more subjective points of view are more important for experiential goods, such as movie DVDs and music. Product reviews are especially important in the creative (entertainment) industries, as it is difficult to establish quality prior to the experience (Situmeang, Gemser, Wijnberg, & Leenders, 2016). For this reason there has been an extensive research done on online reviews specifically in the movie industry (Liu, 2006).
The importance of entertainment and media industry is unquestionably proven as it is expected to worth 2.14 trillion U.S. dollars by 2020 (“Statista”, 2016), and particularly the film and movie industry is projected to increase from 38 billion U.S dollars’ worth (in 2016) to 50 billion U.S. dollars in 2020. Sequels, like Harry Potter and Lord of the Rings, have become huge successes with an enormous fan base. The box office revenue of the last sequel of Harry Potter and the Deathly Hallows Part 2, as of January 2018, reached 1341.5 million U.S. dollars (“Statista”, n.d.). However, most of the studies in the marketing literature did not take into account the importance of sequels, they have treated the fact that the product is a sequel as a control variable (Situmeang, Leenders & Wijnber, 2014).
Sequels are showed to be performing better in general as the original product creates a positive image, which is carried over to the sequel, which in return increases sales. This phenomenon is called the “carry over mechanism” (Hennig-Thurau et al., 2009). The performance of sequels suggests that companies are more likely to be exploitative than explorative based on the high revenues earned by the first movie, and more likely to follow an exploitative brand extension strategy, such as they are more
likely to release a sequel in the same genre than adding a new one the next sequel. This is aligning with both prospect and behavioral theory as both of them suggest that managers tend to be risk-averse and respond to past performance by being exploitative, rather than follow their expectations of future possibilities and be explorative (Lant and Shapira, 2008). This suggests that when the first sequel performs well, there is no need to release the next sequel in a market new to the organization; instead it is more beneficial to release the next edition in the same market segment.
However, unlike previous studies where the attention has been mainly on the financial performance of products (measured by sales) and on the quantitative aspect of online reviews in relation to brand and product extensions (Duan, Gu, & Whinston, 2008; Purnawirawen, Eisend, De Pelsmacker & Dens, 2015; Situmeang et al., 2016), this study takes a different perspective and looks at other variables, such as at the content of the highly influential online reviews. Affective cues in review texts might influence the attitudes of consumers (Cohen, Pham, Andrade, Haugtvedt, Herr and Kardes, 2008), and these affective reviews could drive their purchasing behavior, which however is still not completely clear in what way. Therefore, more insight is needed on their impact. As the findings on the numerical surrogates of online reviews are contradictory and offer little guidance (Tirunialli and Tellis, 2012), by taking into account the sentimental content online reviews possibly new insights could be found on their impact. More could be explained on the carry and spillover effect in relation to product extension strategies. As so far only a few scholars have examined the content of reviews and the role of emotions and their impact (Ludwig, de Ruyter, Friedman, Brüggen, Wetzels & Pfan, 2013; Archak et al., 2011) more research is needed in this area.
The presented findings show the importance of online reviews for companies in the creative industries and particularly in the movie industry. However, the sentiments of online movie reviews and their impact have not received enough attention, and it has been mainly explored in relationship to movie sales. The findings show that organizational strategies (on product extensions) are dependent on the performance of the first product, but there has been no research done on the sentiments of online reviews in relation to product extension strategies.
Therefore the current research will fill the gap in literature by investigating the following: “To what extent do the sentiments of online reviews lead to the exploration of a new market segment ?
Through this investigation we can potentially explain more on the spillover effect by focusing on the review texts in relation to product extension strategies, and can potentially find evidence on the effects of the textual properties of online reviews. The results derived from this research can also contribute to organizational decisions on product extension strategies in the creative industries and can provide implications on quality assurance for managers.
This thesis is structured as follows: The introduction follows up with a review of the academic knowledge about product extension strategies, such as exploitation and exploration, and about the different aspects of online reviews, such as critic and consumer reviews, and about the quantitative and contextual aspects of reviews. Afterwards, the methodology, the research design and finally the variables used in testing the hypotheses are explained. The results of this study will be presented in the fourth chapter. Then these results will be discussed in detail together with the managerial and theoretical implications and limitations of the paper in the fifth chapter. In the last chapter the conclusions will be presented.
II Theoretical Background
This paper first investigates the conditions that can influence the decisions of organizations to choose between an explorative or an exploitative product extension strategy. In the movie industry this is often measured by the choice of genre of the released sequel. Moreover, the academic literature on online reviews is presented, and both the critic and consumer reviews are discussed together with their numerical and contextual aspects. Finally, the hypotheses and the conceptual model of the thesis is introduced.
2.1 Explorative versus Exploitative Strategy
Choosing an explorative strategy might be risky, because the possible outcome of such a decision is uncertain and may result in loss (Lehman and Hahn, 2013).
Research and development (R&D) intensity is one way of determining companies’ organizational strategic choices regarding the decision between explorative and exploitative behavior (Lee, Wu & Pao, 2014). Firm explorativeness (the notion of the use of knowledge new to the organization), is treated as the degree of using new knowledge in the pursuit of innovation in Lee et al (2014)’s research.
The results of their analysis show that the higher the R&D intensity is, the less likely a firm will choose to be explorative. Due to managerial risk aversion or organizational inertia, firms tend to spend R&D resources in an exploitative way due to two possible reasons, such as failure-intolerant nature or short-term oriented mindset (Lee et al., 2014). These findings of the behavior of industrial (technological) firms can serve as a possible explanation for organizational strategy choices in the movie industries as well, such as they are likely to extend their existing products, less likely to innovate, less likely to release a movie in a new genre due to risk-aversion and affright of failure.
In the entertainment industry it is common to describe movies based on their genres, for example Websites, such as IMDB, Box Office Mojo, or Netflix, group movies based on their genres (Sood et. al, 2006). Therefore, also in this particular research, product extension strategy was represented by the choice of genre of the sequel. For this reason, choosing exploitation means staying loyal to the first sequel’s genre, such as the second sequel is released in the same genre(s) as the previous one. According to Sood et al. (2006) adding a new genre to the sequel is a strategy to make the movie more interesting. For instance adding a romance element in addition to an originally action-orientated sequel. It is therefore an explorative strategy. The sequel becomes less similar to the previous one, which is risky as it would might result in loss of popularity among the consumers (Sood et al., 2006). The reason why the original sequel was popular before, is its action orientation, but with adding a new genre to the next sequel it loses its action orientation. For this reason, the consumers might not favor the new released sequel as much as the previous one with the original genre.
Risk-taking behavior can also be a result from one’s past performance and knowledge of the performance of others according to the prospect and behavioral theory (Cyert and March, 1963). Performing below a targeted level directly affects one’s strategy to be more risk-taking, while performing above that level leads to risk avoidance (Baum, Rowley, Shipilov, & Chuang, 2005). For instance, firms experiencing financial slack are more willing to experiment to reap financial gains, while bearing mind the potential downside of the risk-taking behavior (Lee et al., 2014). This is especially the case in dynamic industries that observing negative trend in performance will influence companies to take risks (Situmeang et al., 2016).
These studies suggest that a negative performance, such as low sales are more likely to end in an explorative behavior, such as a firm is more likely to explore and enter a new market segment. Firms in the movie industry are more likely release the next sequel in a dissimilar genre. Such as Situmeang et al. (2016) found that a negative market performance trend is positively associated with the likelihood of organizational entry to a new market segment, and a positive market performance is positively associated with staying at its existing market. This was true in the entertainment industry and particularly in the video industry.
These results suggest that companies in the movie industry with positive performance would be less likely to release the next sequel in a dissimilar genre to the organization (sequel is a type of product extension, which serves the same market segment) . They would be more likely to follow an exploitative organizational strategy. Therefore, the following is hypothesized:
Hypothesis 1: A positive market performance trend is negatively related to the likelihood of exploring a
new market segment.
2.2 Online Reviews
As acknowledged in prior literature, online reviews are an important type of eWOM, and there has been an extensive research done on the online reviews in the marketing literature related to the creative industries (Duan, Gu, Winston, 2008; Situmeang, Leenders, Wijnberg, 2014). EWOM can be defined as “any positive or negative statement made by potential, actual, or former customers about a product or company, which is made available to a multitude of people and institutions via the Internet” (Hennig-Thurau et al., 2004, p 39).
The final success of the company might be dependent on obtaining online expert recognition (Basuroy et al., 2003) and not only on financial results. Especially in the creative industries it is hard to establish product quality prior to the purchase of the product, thus product reviews can influence the
success of companies. By gaining recognition for one product of the company that recognition might “carry over” to the next sequel to the next product (Situmeang et al. 2014), and even if the organization enters a new segment there could be a “spillover effect”. Thus, with the analysis of online reviews we could possibly explain more about these effects and about the influence of online reviews on product extension strategies.
2.2.1 Different Aspects of Online Reviews
Prior research has been focusing on the valence, and mostly quantitative surrogates of reviews such as rating and volume, and mostly in relation to sales (Duan et al., 2008; Purnawirawen et al., 2015). The research of Purnawirawan et al. (2015) investigated the role of valence in online reviews (whether reviews in a review set are mostly positive or negative) and found that valence affects perceived usefulness of the reviews in a different way than it affects attitudes toward products. Review valence has proved to have a stronger influence on perceived usefulness when the reviews referred to experience products, and it had a stronger influence on attitudes for unfamiliar brands. Finally, the strongest influence of review valence referred to recommendation intentions. Hennig-Thurau et al. (2009) also showed that positive evaluations of earlier editions have a positive impact on the sequel sales, which they argue that can be explained by an image carry over effect. Furthermore, the major findings of Duan et al. (2008) included that the ratings of online user reviews have no significant effect on movies’ box office sales, but the volume of online posting is highly influential. Moreover, the movie’s box office revenue and WOM valence positively influence the WOM volume, and thus WOM volume in return leads to high sales performance (Duan et al., 2008). Also, according to Liu (2006) most of the explanatory power stems from the volume of WOM and not from the valence, as measured by the percentages of negative and positive messages.
However, often these empirical investigations of the numerical cues provide mixed results which raises some doubts about their predictive ability on firm outcomes (Yong, 2006). Chevalier and Mayzlin (2006) found that positive ratings on Amazon.com increase book sales, whilst negative ones decrease them. However, other scholars did not find a significant impact of positive ratings on sales, and even some of them found that negative ratings increase sales for products with lower awareness (Chen, Wu & Jungsun 2004; Berger, Sorensen & Rasumussen, 2010). Particularly in the movie industry, Dellarocas, Xiaoquan, and Awad (2007) found that numerical ratings are positively influence box office revenue, irrespective of the volume of the reviews, whereas as it has been mentioned above, Duan et al. (2008) and Yong (2006) found the opposite, such as not ratings, but review volume drives sales.
These mixed findings could be the result of (1) methodological problems; for example cross-sectional context and the inability to control for unobserved differences, which includes quality (Zhu and
Zhang, 2010), or (2) the inability of numeric cues to do justice to the expressive nature of online reviews (Cao, Duan, & Gan, 2011).
2.2.2 Content of Online Reviews
By analyzing the content of reviews, and taking a dynamic perspective, this could lead to clarifications on the impact of reviews other than numerical factors (Tirunialli and Tellis, 2012). The spillover and carry over effect could be explained further. So far, only a few scholars have examined the content of reviews, and the role of emotions and their impact. Ludwig et al. (2013) found that helpful reviews increase conversion rates. In contrast to previous researches, they analysed not sales, but conversion rates, the content of reviews and not only numerical variables. Thus, Ludwig et al. (2013) are one of the few studies who have focused on the importance of content in eWOM messages. The few other studies include Archak et al. (2011), who found that the style of a review reflects consumer sentiments, and can also influence the sales and pricing power of music and movie DVDs. Li and Zhan (2011) have also showed that reviews are most helpful when they are positive, comprehensive and easy to read.
Therefore, researchers are turning to the reviews’ textual properties and assessing their impact on performance (Chevalier and Mayzlin, 2006). For instance, affective cues provided in review texts (e.g., “I love the book,” “worst book I ever read”) might influence respondents’ attitudes (Cohen et al., 2008), and as a consequence of the heuristic nature of online information processing, it seems likely that the affective content of review texts could drive their behavior (Jones, Ravid, and Rafaeli, 2004; Das, Martinez-Jerez, and Tufano 2005;). Affective content words (emotions) such as anger and happiness reveal the aim of a text, and thus refer to the internal feelings of oneself (Cohen et al., 2008). Hu, Liu and Zhang (2008) found that when consumers are processing the online reviews, they do not only care about the review scores, but they also pay attention to other contextual factors of the evaluations. Moreover, in the individual level, the affective words in reviews influence consumers who have no prior knowledge of the quality (Cohen et al., 2008). Thus, on the aggregate level it is assumed that sentiments will drive behavior.
However, insights about the possible impact of sentimental and affective words of online reviews are still needed to investigate their impact, and on whether they affect the success of companies or not (Andrade, 2005; Roehm and Roehm, 2005; Hu et al., 2008). There was an identified gap for research on the investigation on the impact of sentiments and narratives on different type of firm outcomes (King et al., 2014). This paper is one of the first ones that investigates the content of online reviews in relation to brand extensions. Thus, this paper is trying to fill the gap in research, and find more clarifications about the impact of content characteristics of online reviews, and to see whether these characteristics influence the strategies of companies regarding goods in the creative industries. The sentiments of online reviews
could possibly drive the behavior of companies, and not only consumers’ purchasing behavior, it could possibly explain more about the carry over and spillover effect in relation to movie sequel performance. In practice it could be done by focusing on the sentiments of the online reviews, instead of numerical aspects.
2.2.3 Expert versus Consumer Online Reviews
To investigate the content of online reviews it is important to mention that there are two types of online reviews, such as expert (critic) reviews which are written by professionals, who write assessments on products as their line of work, and are paid by news and publishing companies, while the other type is consumer reviews, which are evaluations written by ‘users’ who satisfy their current needs, and write for different reasons, such as pleasure for instance (Situmeang et al., 2016). Despite that there is an overlap between expert and critic reviews, there can be a clear distinction made between the two. (Holbrook, 1999).
Expert reviews tend to boost organizational confidence and organizations’ ability that they can create something unique, different than before (Situmeang et al., 2016). These third party endorsements provide signals to companies that they are able to create something new and innovative, and also they might create a favorable reputation of the firm among consumers (Graffin and Ward, 2010). As a result, prior literature found that positive expert evaluations influence the success of products (Hennig-Thurau et al., 2009; Situmeang et al., 2014), and not only the ones in the same market segment. For instance, Situmeang et al. (2014) found that a positive expert evaluation has a relatively strong effect on organizational behavior, such as it suggests to the company that they are able to provide more unique, high quality products. Thus, expert reviews are able to boost the confidence of organizations with their evaluations. Thus, companies are more willing to explore new product segments as they believe that higher evaluation (critic rating) will carry over across all the editions in one series (Situmeang et al., 2014). Following that the success of one sequels could carry over to the next product.
A negative trend of expert evaluations, on the other hand signals that the experts are less satisfied with organizational outcomes; as a result this can diminish an organization's confidence to explore new markets (Situmeang et al., 2016). Also, organizations might care less about the critics made by experts as long as their consumers stay loyal, and buy their products, as long as the demand stays constant (Chaudhuri and Holbrook, 2011). This suggests that consumer reviews are as important as expert reviews (if not more important) in decision making. The analysis of the content of online consumer reviews could leads to findings about the uncaptured variance by quantitative market performance on the likelihood of exploring a new market segment. This could be possibly explained by the content of consumers’ post purchase reviews (experiences). Therefore, this research focuses on the content of online consumer
reviews in relation to organizations’ product extension strategies to contribute to research about product extension strategies and online reviews in the creative industries.
Consumer evaluations tend to be based on the entertainment value of the movie, whereas experts tend to analyze the aesthetic value according to formal, artistic standards and norms (Hirschman and Pieros, 1985). Compared to expert reviews, consumer reviews are usually less scientific and more focused on the direct pleasure derived from the product itself rather than evaluating the product in a more quantitative and technical way (Hirschman and Pieros, 1985). Furthermore, consumers seem more appreciative of products or services that satisfy their current needs and wishes; they often have difficulty to see beyond the current state (Menguc, Auh, & Yannopoulous, 2014). Consumers can leave reviews for several reasons. They leave a review for self-enhancement reasons, for example by leaving a ‘good’ review they could be ranked among the top ones in the contribution rankings list (Hennig-Thurau et al., 2004). Furthermore, they also tend to write reviews to receive focus-related utility, which is the utility what the consumer receives when they add value to a community. Motives for this behavior include the concern for other consumers, helping the company, social benefits and exerting power (Hennig-Thurau et al., 2004).
Therefore these reviews left by their consumers could signal the company which product extension strategy they should follow by knowing their opinion about their previous products. By focusing on the sentimental content of reviews, and not only numerical aspects as they found to be contradictory, more could be explained about whether the sentiments of the reviews are predictors of organizational behavior. Whether these mixed sentimental online consumer reviews also affects companies, and not only past financial performance in choosing a strategy, which could result in an ultimate success for the company. Whether the more sentimental consumer reviews would “carry over” to the next sequel and would result in explorative behavior.
Thus, this thesis adds to previous researches by analyzing the influence of sentiments (both positive and negative (mixed) of online reviews on product extension strategies. Therefore, the following is hypothesized:
Hypothesis 2: Positive (negative) sentiments of online consumer reviews positively (negatively) affect
the exploration of a new market segment (the company releases the next sequel in genre new to the organization ).
The purpose of the conceptual model is to contribute to literature by improving the already existing models on product extension strategies by analyzing the sentiments of online consumer reviews (in addition to sales and expert reviews) in relation to explorative product extension strategy.
H1:-
Figure 1: Conceptual model of the current research
Sales of Previous
Product
New Market Segment Exploration Sentiments of Online
III Methodology
In light of the presented academic literature, the conditions that can influence companies choices between being exploitative or explorative, the impact of sales and sentimental reviews will be tested and will be combined to a construct. In this chapter, the method used to test the hypothesis of the paper will be outlined: the data collection and description, data cleaning steps and analysis method.
3.1 Data collection
Most of the data used for this research was collected by data mining movie reviews and ratings, which was provided by the supervisor of this thesis, which he obtained from Metacritic`s and from Box Office Mojo’s database of movies. Metacritic.com is a website, which was founded in 2001 (“Metacritic”, n.d.), providing user ratings and user reviews, critic ratings and critic reviews, scores for users and meta-scores for critics for entertainment products, such as music albums, video games, TV shows and movies. Box Office Mojo is the number one movie website in the world (“About Box Office Mojo”, n.d.). Originally Box Office Mojo was founded in 1999, and later in 2008 the Amazon owned IMDB purchased it. Box office Mojo provides a leading box-office revenue tracking system (“About Box Office Mojo”, n.d.). Therefore, all the worldwide box office sales for this study were obtained from Box Office Mojo, and all the evaluations were obtained from Metacritic.com.
The collected data set consists of box office movies from 1968 until 2017. The original data contains 5,231 movies with 203,512 user reviews and 185,368 critic reviews. The cleaning and analysis of data involved the use of Microsoft Excel, which was used as a storage of the data, for sorting, matching and for the calculations. SentiStrength software was used for the analysis of the consumer review texts. SentiStrength estimates the strength of positive and negative sentiments in texts. It reports two sentiment strengths: -1 (not negative) to -5 (extremely negative), and 1 (not positive) to 5 (extremely positive). The reason for that is that people process two opposite valenced (negative and positive/mixed) emotions at the same time (Berrios, Totterdell, and Kellett, 2015). Finally, IBM SPSS Statistics 24 (Statistical Package for the Social Sciences) was used to run analyses to test the hypotheses.
3.2 Data Cleaning
The previously collected data has required the organization and cleaning of data. Therefore several steps were taken:
1. For this research, we selected manually all the movies, which belong to the same sequel series and created a separate spreadsheet for them. All in all, we found 399 sequels, and therefore these 399 sequels were used for the analysis. We have created a unique franchise ID for each sequels,
for instance CLERK and CLERK-2 for Clerks and Clerks II or BADSA and BADSA-2 for Bad Santa and Bad Santa 2.
2. For the purpose of measuring the explorative behavior of companies in the movie industry I created a new (dummy) variable, and assigned either a 0 or 1 to each sequel based on the genre of that movie. Thus, if there was a change in the genre of the investigated sequel compared to the previous sequel in the series that was indicated with a 1.
3. We adjusted all the worldwide box office movie sales to inflation based on the U.S. inflation factor. First, we created a new sheet in the same Excel file with all the data, then with the use of VLOOKUP function we matched the average inflation rate per year with the sales for each movie.
4. Based on the genres of the movies, we created new columns for each of the genres and assigned 0 or 1 based on each movie’s genre.
3.3 Description of Data and Variables
After all the data was collected and cleaned, the variables were allocated to their roles based on the literature review. The variables used in this study are summarized in Table 1, each of them with a description.
The likelihood of explorative behavior (the dependent variable), such as entering a new market segment was measured based on whether the organization released the next sequel in a new genre or not. I compared the genres listed for each sequel to the genres of their earlier editions. If the sequel had genres, which were not present in the preceding, then it means that they are dissimilar, which means that the company follows an explorative product extension strategy by entering a new genre. Thus, the dependent variable was coded as a binary variable: 1 = there was a change in the genre compared to the previous sequel (exploration of a new market segment) , 0 = the sequel had the same genre as the previous one (no exploration of a new market segment ).
There were two independent variables investigated in this study. The first one was the box office (worldwide) movie sales of the preceding sequel. The other two indicated the sentiments of the consumer reviews. The higher the number was for the worldwide sales, the higher the revenues were for the sequels. The measurement of sentiments was done by taking the sum of both positive and negative sentiments in the reviews. Regarding the positive sentiments: the higher the number, the more positive sentiments were found in the reviews (the numbers are between 1 and 5). For the negative sentiments the opposite applies, such as the higher the number the more negative sentiments were found in the consumer reviews (the numbers are between -1 and -5).
I controlled for several variables based on previous studies, as these variables could affect the relationship of the investigated variables. Namely, for the average user review scores, which were given for the previous sequels, and for the four most important and popular genres, such as for action, comedy, thriller and drama. It is essential to control for the movie genres, as these are one of the most important factors, which consumers consider when they are deciding about watching a specific movie or not (Austin and Gordon, 1987), and therefore they have crucial impact on the future box office success of the movie. Thus, the most popular genres can predict organizational outcomes and performance (Chang and Ki, 2005). For instance, in prior literature it was found that drama is negatively related to box office performance (Litman and Kohl, 1989). Moreover, as negative reviews tend to have a negative impact on box office revenues, studios would rather make their next movies in more familiar genres to the audience. This way they would try to reduce the possible impact of reviews (Desai and Basuroy, 2005). These findings all suggest that the choice of genre has important implications for studios on their organizational strategies. For this reason they could influence companies decisions on exploring a new market segment or not.
The average user score of the previous edition was measured by the meta score, which was given by consumers. When consumers read online reviews, they pay attention to both to the contextual information of the review and to the score, which the reviewer gave (Hu et al., 2008). Furthermore, according to prior literature, low consumer ratings have a negative effect on explorative behavior, which means that companies are more likely to follow an explorative product extension strategy when they receive a negative review rating, rather than a positive one from their consumers (Situmeang et al., 2016). All in all, based on these findings it is essential to control for the user score given by other consumers.
Table 1. Overview of variables Variable name Description
Sales Worldwide box office sales of the previous sequel adjusted to inflation. (In 100 million units)
Positive Sentiments Sum of positive sentiments in the online consumer review text of the previous sequel. (Measured on a scale between 1 and 5)
Negative Sentiments Sum of negative sentiments in the online consumer review text of the previous sequel. (Measured on a scale between -1 and -5)
User Rating The average online score of the previous sequel given by the consumer. (The scale on, which it is measured is between 0 and 10, thus on a 11-point scale with higher numbers indicating more favorable evaluations)
Action Type of movie genre with high energy, big-budget physical stunts and chases, possibly with rescues, battles, fights, escapes, destructive crises. For example: James Bond. (Measured as a dummy variable: 0 or 1 = Yes / No)
Thriller Type of movie genre which typically has an exciting plot and involves a crime. It gives the viewers heightened feelings such as excitement, fear, surprise or anxiety. (Measured as a dummy variable: 0 or 1 = Yes / No)
Comedy Type of movie genre with light-hearted plots designed to consistently amuse and provoke laughter by exaggerating situations, the relationships, actions, languages and characters. (Measured as a dummy variable: 0 or 1 = Yes / No)
Drama Type of movie genre with serious plot-driven presentations, portraying realistic characters, settings, life situations, and stories involving intense character development and interaction. (Measured as a dummy variable: 0 or 1 = Yes / No)
Exploration Organizational strategy which results in entering a genre, which is new to the organization. Exploration of a new market segment. (Measured as a dummy variable: 0 or 1 = Yes / No)
IV. Results
4.1 Descriptive statistics and correlations
Initially we collected 399 sequel series out of the total 5,231 movies. However, for the purpose of this particular study, I disregarded all the original (first) movies of these series to investigate the product extension strategies of the sequels only. This step decreased the sample size to 182. The mean box office sales were 408.7 million dollars (M = 4.087 in 100 million units) and the mean positive sum of sentiments were 4.714 (M = 4.414, SD = 1.318) from which it can be observed that most of the positive sentimental reviews included a high volume of positive sentiments. The mean user rating was 6.480, thus it was higher than the average of the scale on which it was measured (between 0 and 10) (M = 6.480, SD = 1.314).
Table 2 presents the bivariate descriptive statistics and correlations between the variables, and shows initial insights in the hypotheses. The correlations table provides a preliminary evidence on the expected effects. None of the predictive variables had a significant relationship with the dependent variable before the regression analysis was done, as the correlations do not take into account the binary nature of the dependent variable. The table shows that there was a negative relationship between the exploration and the sales of the previous sequel, however it was insignificant (r = -.018, p >.050). There was a positive correlations between positive sentiments and exploration, however it was insignificant as well (r = .099, p >.050). Furthermore, there was a strong (significant) correlation between positive and negative sentiments, and between positive sentiments and sales, which exceeded the r = .500 level, thus multicollinearity seemed a major concern here ( r = .992 p < .050; r = .515 p < .050). Therefore, I checked the multicollinearity for each variables, and the results indeed indicated that there was a strong multicollinearity between the two variables (VIF = 101.038 for positive sentiments; VIF= 98.176 for negative sentiments). Thus, I decided to exclude the negative sentiments from the analysis as a solution for the severe multicollinearity between the negative and positive sentiments. This step proved to be a good solution for the problem, as the multicollinearity decreased for positive sentiments, and for sales it was not a primary problem. Finally, the variation inflation factor showed that multicollinearity was not a major concern anymore (VIF= 1.495 for positive sentiments, VIF= 1.486 for sales). Thus, both of these two variables were used in the regression analysis.
The inspection of the correlations between control variables and the key study variables indicated that none of them were significantly correlated with the dependent variable, however the comedy control variable was significantly correlated with the positive and negative sentiments, and also with the worldwide sales of the previous sequel (r = -.327, p < .010; r = -.336, p < .010; r = -.261 p < .010 respectively).
Table 2: Bivariate correlations and descriptive of statistics Variable Name M SD 1 2 3 4 5 6 7 8 1.Exploration .590 .494 2.Sales 4.087 3.615 -.018 3. Positive Sentiments 4.714 1.318 .099 .515** 4. Negative Sentiments -4.719 -1.317 .095 .470** .992** 5. User Rating 6.480 1.314 -.037 .248 .043 -.019 6. Action .360 .480 .018 .098 .133 .120 .189* 7. Comedy .230 .193 -.136 -.261** -.327** -.336** -.103 -.155* 8. Drama .030 .419 .004 -.123 -.156* -.167* -.001 -.125 .070 9. Thriller .040 .164 -.065 -.053 -.083 -.091 .091 .030 -.108 -.034
Note: Sales in 100 million units
*Correlation is significant at the .050 level (2-tailed) **Correlation is significant at the .010 level (2-tailed)
4.2 Regression
Following the analysis of correlations, a binary logistic regression was used to explain the occurrence of entering a new market segment in relation to market performance and the sentiments of online reviews. The reason for the use of logistic regression is the binary nature of the dependent variable such as the market segment exploration was coded with either ‘1’ (=Yes / Market segment exploration) or ‘0’ (=No / No market segment exploration). The model contains both of the independent variables, all the control variables and the dependent variable. It is used to test both of the hypotheses. All in all, the model explained 6.6 % - 8.7% variance in the dependent variable, in the exploration of a new market segment (Cox & Snell R2 = .066; Nagelkerke R2= .087). This level of explained variance on the exploration of new segment is quite low, but as there was no previous analysis performed with these variables, it is still quite a contribution on the explorative behavior of companies. All of the results of the logistic regression are summarized in Table 3.
The results show that the positive sales of previous editions had a positive relationship with the exploration of a new market segment (B = .000, p < .100). Thus, these findings suggest that an organization with high sales are more likely to take a risky decision and explore a new market segment,
enter a new genre. This contradicts with the first hypothesis of this study, and therefore Hypothesis 1 was rejected. Regarding the second statement that the more positive the sentiments are the more likely that the company will choose an explorative strategy, the more likely they will release the next sequel in a genre new to the organization, it was indeed the case (B = .186, p <.100). Therefore Hypothesis 2 was supported. However, as I had to disregard the negative sentiments of online reviews, because of the severe multicollinearities, the hypothesis regarding the negative relationship between negative sentiments and market segment exploration was not tested. Thus, there was no finding on the effect of negative sentiment of online reviews on organizational strategies.
Furthermore, one of the control variables, namely the comedy genre had a negative relationship with the exploration of new market segment, which indicated that after releasing a movie, which is described by a comedy genre, organizations less likely to follow an explorative strategy, less likely to release the next sequel in a new genre (B = -.658, P < .100). The results regarding the other control variables show no significant relationship with the explorative behavior of the organization (Action: B= .002, p >.100; Drama: B = .206, p >.100; Thriller: B = -.780, p >.100), thus they did not have a direct effect on the dependent variable.
Table 3: Results report.
Variable Coefficient S.E. VIF
Salesi−1 .000* .000 1.486
Positive Sentimentsi−1 .186* .121 1.495
User Ratingi−1 -.013 .089 1.128
Action .002 .361 1.079
Thriller -.780 5.110 1.041
Comedy -.658* .410 1.175
Drama .206 8.805 1.043
R2 Cox & Snell 𝑅𝑅2 = .066 Nagelkerke 𝑅𝑅2 =.087
Note 1: Binary Logit Model, the dependent variable is : (Market Segment) Exploration (Yes=1/No=0).
Note 2: the reported coefficients are not standardized due to the binary nature of the dependent variable (c.f. Chang et al., 2012), i-1 relates to the edition before the focal sequel
N=182
V. Discussion
This section will elaborate on the results presented in the previous section. The supported and unsupported hypotheses together with all the findings will be discussed. These findings could contribute to the academic literature when linked and compared to past research. Afterwards the theoretical and practical implications will be discussed. Finally, the limitations will be presented together with several suggestions for future research.
5.1 Discussion of Findings
The current research has examined the sentiments of online consumer reviews, and the sales of previous sequels in a series, in relation to organizational strategy to explain more about the spillover effect, about organizational strategic decisions, and to investigate in more depth the effects of online consumer reviews.
There has been an extensive research done already on the firms’ risk-taking behavior (Cyert and March, 1963; Sood et al., 2006; Baum et al., 2005, Lee et al., 2014, Situmeang et al., 2016). This paper contributes to this existing literature in several ways. First of all, it investigated the financial performance of sequels in relation to organizational strategies in the movie industry. Second, it analyzed the content of online consumer reviews in relation to market segment exploration, while prior literature mostly focused on numerical factors and on financial performance. Third, it takes into account the sentimental words in the content of consumer reviews, as a signal for companies about how their consumers may perceive the quality of their products, which could give them direction and motivation for making risky decisions in the future.
The first hypothesis of the study was formulated based on the prospect and behavioral theories of companies’ risk-taking behavior. It was the following: a positive market performance (particularly the high sales of the previous product) is negatively related to the exploration of a new market segment (by entering a genre new to the organization). However, the hypothesis was rejected based on the results. The analysis showed a positive relationship between sales of the earlier product and the exploration of a new market segment. Thus, the findings of this research is in contrast with prior academic papers (Baum et al., 2006; Situmeang et al. 2016), which suggested that when companies face negative financial performance they are likely to follow an explorative product extension strategy.
Following from the results of this study, organizations are more likely to explore a new market segment, a new genre when they experience a positive market performance, and not when they experience financial difficulties. One reason could be, for this positive relationship, is that the companies, who are financially unstable, are more restricted to deploy their financial resources for explorative activities
(Situmeang et al., 2016). It would therefore limit them to exploit their current market segment, current genre. In some cases, they might enter a more similar genre, which is not completely new to the organization. This would help in reducing the risk of getting cash trapped (Situmeang et al., 2016). Thus, organizations with positive sales are more willing to take risks, and choose to be more explorative. They do not experience difficulties in exploiting their resources for the purpose of pursuing exploratory activities. However, as it was mentioned above, previous research stated that performing above a ‘targeted level’ leads to risk avoidance (Baum et al., 2005). Therefore, showing that a positive market performance can give incentives to companies to engage in risk-taking behavior in the movie industry is an important contribution to prior literature.
The second, and most important contribution of this study that it takes into account the sentiments of consumer reviews in analyzing the decisions on product extension strategies. In the past, there was no research done on the sentiments of online reviews in relation to organizational strategies. Besides financial indicators and numerical aspects of online reviews, this study considers the sentiments as a signal for the company of the appreciation of the quality of their existing products in the consumers’ eyes. One reason for that is as it was showed in prior research, the affective words in the content of online reviews can drive consumers’ behavior (Jones et al., 2004). In return that could motivate companies to follow an explorative behavior. That is why the second hypothesis of this research was that the sentimental online consumer reviews positively affect the exploration of a new market segment. This hypothesis was supported as there was a significant positive relationship found between positive sentiments and the exploration of a new market segment, new genre. This result suggest that the positive sentiments of online consumer reviews drive the behavior of companies in the creative industry and particularly in the movie industry.
Thereupon, with these results, the “spillover effect” (Hennig-Thurau et al., 2009) can be further explained in relation to consumer reviews and product extension strategies. In a sense that besides past performance, online reviews also affect organization strategies. Considering the forward spillover of online reviews (Situmeang et al., 2014; Situmeang et al., 2016) the positive sentiments in the reviews of the preceding sequel could spillover to the next edition, which the company is releasing. This could not only affect the performance of the new sequel, but the explorative behavior of the firm. Organizations may see these positive sentiments, as a positive image that the customer may use to associate with a good quality. For this reason, these positive evaluations, this positive image, could boost the confidence of firms about their ability of following a risky strategy, and exploring new market segments. Thus, as Das Martinez-Jerez and Tufano (2005) mentioned, the positive affective content in the review texts might not only influence consumers’ attitudes but the behavior of companies. Also, the findings contribute to Li and Zhan (2011) research, as they found that reviews are most helpful when they are positive, thus they are
also helpful for companies. Such as, the more positive sentiments are in the consumer evaluations, the more confidence they give to organizations about their ability to enter into new markets. Thus, it could give them the opportunity to utilize the spillover effects which is the result of the positive sentimental consumer reviews of the previous edition. Also, to maintain the level of positive sentiments of consumer online reviews, organizations would feel even more pressured to innovate, and would give them the possibility to gain more sales.
In sum, by making use of the sentimental consumer reviews, the sentiments could signal to companies the associations, which consumers have with their current products, and thus provide a picture for future on how customers would react to the next product they release. This would give them direction for future strategies.
The results furthermore suggest that the content of online consumer reviews have similar effects as the financial market performance of the product on the exploration of the market segment. In particular, when the sales of the previous product and the sentiments of the online reviews are positive, organizations are more motivated to engage in an explorative behavior.
5.2 Theoretical Implications
This thesis contributes to academic literature on the highly influential online consumer reviews (eWOM) and on risk-taking behavior of companies in terms of product extension strategies.
Regarding the impact of financial performance on market exploration or exploitation, this study found controversial results with previous research. Instead of supporting other scholars about the risk-averse behavior of companies when they experience high performance (high sales) (e.g., Lee et al.,2014; Lehman and Hahn, 2013) and on being tolerant and open for risk-taking behavior when they experience financial difficulties (Situmeang et al., 2016; Lee et al., 2014). This study found that positive sales result in exploration rather than in exploitation. Overall, the results disagrees with the predictions of prospect and behavioral theories, which both say that managers are more risk-averse and more likely to respond to past performance, than level up their expectations of future possibilities (Cyert and March, 1963). Thus, the results here provide no evidence for the risk-averse behavior of managers. Regardless of the extensive research done in risk-taking behavior of managers this paper cannot confirm these previous studies.
This study moreover provides new insights on the impact of online consumer reviews and on the forward spillover effect. In prior literature mixed results were found about the impact of numerical aspects of online reviews. Thus, it provides qualifications on the impact of online reviews on performance outcomes. So far, the numerical factors of evaluations were not be able to control for quality and / or were unable to do justice on the expressive nature of online reviews (Zhu and Zhang, 2010; Cao, Duan & Gan, 2011). Therefore, in this paper I turned to the contextual factors of online reviews as previous research
has done it (Tirunialli and Tellis, 2012). Previous scholars found that the valence (especially when it is positive), the style and the affective content has an impact on the sales of the product on the success of the organizations and on the behavior of the consumers (Jones et al., 2004; Andrade, 2005; Roehm and Roehm, 2005), but they showed no evidence on their impact on product extension strategies. Thus, the results of this paper contributes to the stream of literature on the impact of sentimental consumer reviews on various firm outcomes, such as in this case, on brand extension strategies. Positive sentiments showed to have a positive relationship with the exploration of a new market segment. Thus, this paper adds to literature about the ‘spillover effect’ (Hennig-Thurau et al., 2009) in a sense that the more positive sentiments are in the online consumer reviews, the more likely it would spilllover to the next sequel and would result in not only a positive performance, but an enhanced confidence in the attitude of companies towards an explorative behavior.
5.3 Practical Implications
In terms of managerial implications, the result of this paper could help managers in deciding when to follow an explorative product extension strategy by analyzing their financial performance, and the content of online reviews.
They could also predict when do their competitors explore new market segments or stay in their segment, which they already know. Therefore, the findings of this study can help managers judge the market extension strategies of their competitors. Furthermore, the results suggest that when an organization financially performs well, they are more willing to explore a market segment, which is new to them, than when they face resource constraints. Managers can predict their competitors’ next move, their risk-taking behavior by analyzing their financial performance.
However, managers should not only look at financial indicators of past performance when they are deciding on a product extension strategy for their companies. They should focus on other indicators as well, such as on the online consumer evaluations, as these provide signals to the company on how their consumers perceived, evaluated their already existing products. Based on that imagine, which the customers might have of the previous product, companies could predict the future performance of the next edition. The positive sentiments of online reviews proved to be an important predictor of market exploration and gave clarification on the confusion, which the mixed findings on the numerical aspects of reviews caused in the creative industry. Thus, the more positive sentiments can be found in the consumer reviews, the more managers are advised to follow an explorative strategy as it signals to the company that consumers value their already existing products and thus it could give them an opportunity to exploit the spillover effects resulting from the positive image of the quality of the first product. All in all, companies should not underestimate the importance of customer reviews. It provides information for customers
about the quality of a product and therefore they base their purchase decision on the reviews made by other consumers (LightSpeed Research, 2011). These results show that managers should also take into account the highly influential online consumer reviews when making future decisions for their company.
5.4 Limitations and Future Research
The contributions of this paper should be however considered in light of its general limitations. To begin with, the empirical relationships found in this study was based on information of sequels in the movie industry. More research could be done outside of the creative sector to validate the findings of this paper to other types of products. For example, in educational institutes where positive sentiments of past consumer reviews could also influence the product extension strategies. Such as universities could base their decision about introducing a completely new course for students (dissimilar to previous ones) on the positive sentiments of consumer reviews.
Furthermore, as in this particular study opposite results were found compared to prior literature on risk-aversion and risk-taking behaviors, further research is needed with a robustness test to analyze the degree of companies’ risk-taking behavior to see whether managers indeed tend to be more risk-taking when they are facing positive sales.
Third, more reviews should be analyzed from different sources as the analyzed reviews in this research were retrieved from two sources only. Moreover, the analyzed evaluations may have included some less reliable and fake reviews. For instance, businesses might have left fake glowing reviews on their competitors’ products in a face of a consumer (Fertik, 2012). Thus, more attention should be paid on the quality of the reviews.
Fourthly, in this research the exploration of a new market segment was operationalized by examining whether studios release the next sequel in a genre new to them. However, this operationalization might not be adequate method in non-creative industries.
Furthermore, different and more control variables could be used in future research, as I did not control for the production budget of the previous product, as there was lack of information about it for several sequels. Thus, in future research, data could be collected on each sequels’ production budget and could be used as additional control variables, as the financial resources are important determinants of future organizational decisions.
Finally, as the negative sentiments were disregarded from the analysis, it limits the findings on consumer sentiments to only the positive ones. Therefore, further research is needed on the impact of negative sentiments.
VI Conclusion
The main objective of this study was to extend existing literature on movie sequels, on product extension strategies, and on the impact of online consumer reviews. To contribute to the prospect and behavioral theories on risk-taking decisions, and to further explain the spillover effect in the context of organizational strategies.
The findings partially found support for previous researches on product extension strategies. On the one hand, I did not find support for the behavioral and prospect theory, and about the risk-averse behavior of firms, which says that managers tend to follow a risk-avoiding behavior when they experience a positive financial performance. Instead, the results indicated that a positive financial performance was positively related to the exploration of a new market segment. This could be explained by the financial constraints, which companies face in case of a negative market performance, and therefore they are not willing to exploit their resources fully. On the other hand, I found evidence for the positive relationship between positive sentiments of online consumer reviews and new market segment exploration. Therefore, it can be concluded that the spillover of online reviews not only affects the performance of future editions, but also the explorative behavior of companies. As the organization might see the positive sentiments as a positive image that consumers associate with high quality, and therefore it encourages them to engage in a risky explorative behavior.
Finally, I hope that the results of this study contributes to the existing literature on the behavioral and prospect theory, and on the highly influential online reviews. In general, the content of online reviews are a useful signal of quality for customers to make decisions. However, it is still challenging for companies to decide on how they could take into account these information in making future organizational decisions. Thus, the sentimental content of reviews is an interesting base for future academic research.
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