The determinants of movie rental revenue earnings.

Terry, Neil ; De'Armond, De'Arno

INTRODUCTION

The average budget of making a motion picture for release in the United States has risen to almost fifty million dollars per movie. This rising cost has resulted in motion picture studios seeking multiple sources of revenue including domestic box office, foreign box office, product placement, merchandising, video sales, and video rental revenue. A single movie can be the difference between millions of dollars of profits or losses for a studio in a given year (Simonoff & Sparrow, 2000). The purpose of this research is to analyze the motion picture industry with a focus on the determinants of video rental revenue. This manuscript is divided into four sections. First, a survey of the related literature is discussed. The second section provides the model specification. The third section puts forth an empirical evaluation of the determinants of video revenue for 214 films released during the year 2006. The final section offers concluding remarks.

SURVEY OF THE LITERATURE

The literature on the determinants of video rental revenue is in its infancy but expected to be highly correlated with the determinants of box office revenue. Many researchers have developed models that explore the potential determinants of motion picture box office performance. Litman (1983) was the first to develop a multiple regression model in an attempt to predict the financial success of films. The original independent variables in the landmark work include movie genre (science fiction, drama, action-adventure, comedy, and musical), Motion Picture Association of America rating (G, PG, R and X), superstar in the cast, production costs, release company (major or independent), Academy Awards (nominations and winning in a major category), and release date (Christmas, Memorial Day, summer). Litman's model provides evidence that the independent variables for production costs, critics' ratings, science fiction genre, major distributor, Christmas release, Academy Award nomination, and winning an Academy Award are all significant determinants of the success of a theatrical movie. Litman and Kohl (1989), Litman and Ahn (1998), and Terry, Butler, and De'Armond (2004) have replicated and expanded the initial work of Litman. None of the extensions of Litman's work has focused on video revenue financial performance.

One area of interest has been the role of the critic (Weiman, 1991). The majority of studies find that critics play a significant role on the success or failure of a film. Eliashberg and Shugan (1997) divide the critic into two roles, the influencer and the predictor. The influencer is a role where the critic will influence the box office results of a movie based on his or her review of the movie. Eliashberg and Shugan's results suggest that critics do have the ability to manipulate box office revenues based on their review of a movie. The predictor is a role where the critic, based on the review, predicts the success of a movie but the review will not necessarily have an impact on how well the movie performs at the box office. Eliashberg and Shugan show that the predictor role is possible but does not have the same level of statistical evidence as the influencer role.

King (2007) explores the theoretical power and weakness of critics on the box office performance of movies. The substantial market power of critics is derived from the following: (1) Film reviews are widely available in newspapers, magazines, and websites. The ubiquitous availability of critical reviews in advance of a movie release creates positive or negative energy in the critical opening weeks; (2) Film critics regard themselves as advisors to their readers. They are often as explicit in their recommendations as Consumer Reports is about other consumer purchases; (3) Film critics are likely to be considered objective. There are too many critics and too many films for serious critical bias to develop. Those who are skeptical about the influence of film critics point to the following counter arguments: (1) It is possible that the effects of aggressive marketing at the time of a film's release might dominate critical evaluations in determining opening attendance; (2) Critics may raise issues that do not concern most audiences. They are more likely to notice and comment on technical issues, like cinematographic technique, than the average member of the audience; (3) Critics may write for a readership that has different tastes from the average cinemagoer. The most obvious potential reason for this is demographic. Cinema audiences are younger than the general population and less likely to pay attention to print reviews. Critics might therefore, be expected to aim their reviews at the older demographic audience and give relatively negative reviews to certain film genres. The empirical results put forth by King (2007) are mixed with respect to the impact of critics on box office earnings for the U.S. box office in 2003. He finds zero correlation between critical ratings for films and gross box office earnings when all releases are considered because of the affinity critics have for foreign movies and documentaries relative to the general public. For movies released on more than 1,000 screens, critical ratings have a positive impact on gross earnings.

Reinstein and Snyder (2000) focus on the critics Siskel and Ebert and how their reviews impact box office success. The authors report that the correlation between good movie reviews and high demand might be false due to unknown quality measurements. In order to circumvent the proposed false correlation Reinstein and Snyder apply a "differences in differences" approach that yields a conclusion that positive reviews have a surprisingly large and positive impact on box office revenue. Reinstein and Snyder also report that their results show that the power to influence consumer demand does not necessarily lie in the entire critic population, but may lie in the hands of a few critics.

Wallace, Seigerman, and Holbrook (1993) employ a sample of 1,687 movies released from 1956 through 1988 to investigate the relationships between movies box office success and critic ratings. They find a poorly rated movie will actually lose money for every positive review it receives while a highly rated movie will continue to gain money for every positive review it receives. Wallace, Seigerman, and Holbrook (1993, p. 11) interpret these findings by saying that "it appears that a bad movie has something to gain by being as trashy as possible. ... [For] a good movie, it apparently pays to strive for even greater excellence." Ravid (1999) has also looked at movie reviews as a source of projecting higher revenues. He concludes that the more reviews a film receive, positive or negative, the higher revenues it will obtain.

Although much research has supported the critic as a positive indicator of box office success, others have shown that the critic plays a much less important role. Levene (1992) surveyed students at the University of Pennsylvania and concludes from her 208 useable surveys that positive critic reviews ranked tenth, behind plot, subject, and word-of-mouth on a list of factors that influence the decision to watch a film. Levene's study reveals that theatre trailers and television advertising were the two most important determinants. Faber and O'Guinn (1984) conclude that film advertising, word-of-mouth and critics' reviews are not important compared to the effect that movie previews and movie excerpts have on the movie going public. Wyatt and Badger (1984) find that negative or positive reviews have little effect on the interest of an individual to see a movie over a mixed review or seeing no review. Further research by Wyatt and Badger (1987) conclude that positive reviews and reviews that contain no evaluative adjectives, which they called non-reviews, are deemed more interesting than a review that was negative or mixed. More recently, Wyatt and Badger (1990) report that reviews containing high information content about a movie raise more interest in a film than a positive review.

Research has shown a seasonal pattern in movie releases and box office performance. Litman (1983) reports that the most important time for a movie release is during the Christmas season. Sochay (1994) counters this with evidence that the summer months are the optimal time of year to release a motion picture. Sochay, referencing Litman (1983), explains his conflicting results are due to competition during the peak times. Sochay adds that the successful season will shift from the summer to Christmas in different years due to film distributors avoiding strong competition. Radas and Shugan (1998) developed a model that captures the seasonality of the motion picture industry and apply it to the release of thirty-one movies. The authors find that the length of a movie release on average is not longer during the peak season but peak season movies typically perform better at the box office. Einav (2001) investigates seasonality in underlying demand for movies and seasonal variation in the quality of movies. He finds that peak periods are in the summer months and the Christmas season because distributors think that is when the public wants to see movies and when the best movies are released. He comments that distributors could make more money by releasing "higher quality" movies during non-peak times because the movie quality will build the audience and there will be less competition than at peak times.

Film ratings passed down from the Motion Picture Association of America (MPAA) may also influence box office performance. Many film companies fight for a better rating, often re-shooting or re-editing scenes multiple times in order to get their preferred ratings, most often being PG or PG-13 because these ratings exclude virtually no one from seeing the movie. Sawhney and Eliashberg (1996) develop a model where the customer's decision-making process on whether to see a movie can be broken into a two-step approach, time-to-decide and time-to-act. The results of their study show that movies with an MPAA rating of restricted (rated R) perform worse at the box office than movies without a restricted rating. The analysis shows that restricted rated movies have a higher time-to-act but have longer time-to-decide periods than family movies. Terry, Butler, and De'Armond (2004) verify the negative impact of the restricted rating on box office performance, providing evidence of a penalty in excess of $10 million. Ravid (1999) provides evidence from a linear regression model that G and PG rated films have a positive impact on the financial success of a film. Litman (1983) on the other hand, finds that film ratings are not a significant predictor of financial success. Austin (1984) and Austin and Gordon (1987) look at film ratings in an attempt to find a correlation between ratings and movie attendance but find no significant relationship.

Anast (1967) was the first to look at how film genre relates to movie attendance. His results show that action-adventure films produce a negative correlation with film attendance while films containing violence and eroticism had a positive correlation. Litman (1983) shows that the only significant movie genre is science fiction. Sawnhey and Eliashberg (1996) use their two-step approach and find that the drama genre has a slower time-to-act parameter while action movies result in a faster time-to-decide than other movie genres. Neelamegham and Chinatagunta (1999) employ a Bayesian model to predict movie attendance domestically and internationally. They find that across countries the thriller genre is the most popular, while romance genre was the least popular.

Awards are important to every industry but few industries experience financial compensation from an award more than the motion picture industry. Litman (1983) shows that an Academy Award nomination in the categories of best actor, best actress, and best picture is worth $7.34 million, while winning a major category Academy Award is worth over $16 million to a motion picture. Smith and Smith (1986) point out that the power of the Academy Award explanatory variable in models explaining patterns in movie rentals will change over time as the effects of different Academy Awards could cause both positive and negative financial results to a movie in different time periods. Nelson, Donihue, Waldman, and Wheaton (2001) estimate that an Academy Award nomination in a major category could add as much as $4.8 million to box office revenue, while a victory can add up to $12 million. The authors find strong evidence toward the industry practice of delaying film releases until late in the year as it improves the chances of receiving nominations and monetary rewards. Dodds and Holbrook (1988) look at the impact of an Academy Award after the nominations have been announced and after the award ceremony. The authors find that a nomination for best actor is worth about $6.5 million, best actress is worth $7 million and best picture is worth $7.9 million. After the award ceremony the best actor award is worth $8.3 million, best picture is worth $27 million, and best actress award is not statistically significant. Simonoff and Sparrow (2000) find that for a movie opening on less than ten screens an Academy Award nomination will increase the movies expected gross close to 250% more than it would have grossed if it had not received the nomination. For movies opening on more than ten screens, an Academy Award nomination will increase the movies gross by nearly 30%.

DATA AND MODEL

Predicting the financial performance of feature films is widely regarded as a difficult endeavor. Each film has a dual nature, in that it is both an artistic statement and a commercial product (Sochay, 1994). Many studies have attempted to estimate the determinants of box office performance by employing empirical models to a limited number of high profile features. The approach of this study provides a unique focus on the determinants of video movie rental revenue. The sample includes 214 motion pictures with for the year 2006.

The primary source of data for this study is the Rotten Tomatoes website (rottentomatoes.com). The website is a unique rating system that summarizes positive or negative reviews of accredited film critics into an easy to use total percentage that is aggregated for each motion picture. In addition to providing a system of aggregate reviews, the website also contains information pertaining to revenue, release date, movie rating, genre, and number of screens featuring a film each week of release. WorldwideBoxoffice.com, Movies.com, Oscars.org, boxofficemojo.com, imdb.com, and the-numbers.com are additional sources of data and information.

The empirical model employed to investigate the determinants of box office performance for this study is specified below as:

(1) [VREVENUE.sub.i] = [B.sub.0] + [B.sub.1][DBOXOFFICE.sub.i] + [B.sub.2][FBOXOFFICE.sub.i] + [B.sub.3][CRITIC.sub.i] + [B.sub.4][AANOM.sub.i] + [B.sub.5][RESTRICTED.sub.i] + [B.sub.6][CHILDREN.sub.i] + [B.sub.7][SEQUEL.sub.i] + [B.sub.8][TIME.sub.i] + [B.sub.9][RELEASE.sub.i] + [B.sub.10][BUDGET.sub.i] + [u.sub.i],

where VREVENUE is domestic video rental and pay-per-view revenue, DBOXOFFICE is domestic box office earnings, FBOXOFFICE is foreign box office earnings, CRITIC is the percent approval rating for a film by an agglomeration of film critics, AANOM is the number of Academy Award nominations a film receives, RESTRICTED is a categorical variable for movies with a restricted rating (Rated R), CHILDREN is a categorical variable for movies in the genre of children's movie, SEQUEL is a categorical variable for movies that are derived from a previously released film, TIME is the number of weeks from domestic box office release to video release, RELEASE is the number of theaters showing the film during the week of wide release, and BUDGET controls for the estimated production and promotion costs for each movie. Several alternative model specifications were considered including control variables for independent films, presence of an established star actor or director, holiday release, and new release competition. Inclusion of these variables into the model affected the standard errors of the coefficients but not the value of the remaining coefficients or they suffer from excessive multicollinearity with variables included in the model. For these reasons, they are not included in the final model.

Descriptive statistics for the model variables are presented in Table 1. The average rental revenue in the sample is $23.69 million, with a maximum of $67.27 million (Pirates of the Caribbean: Dead Man's Chest). The average domestic box office earnings are $42.36 million, with six movies earning more than $200 million (Pirates of the Caribbean: Dead Man's Chest, Night at the Museum, Cars, X-Men: The Last Stand, The DaVinci Code, and Superman Returns). Average foreign box of earnings in the sample are $45.98 lead by Pirates of the Caribbean: Dead Man's Chest, The Da Vinci Code, and Casino Royale. Average critical rating of the movies in the research cohort is approximately 45 percent positive with a standard deviation of 28 percent. The maximum number of Academy Award nominations is eight by Dreamgirls. Thirty percent of the movies in the sample have a restricted rating, 18 percent target children, and nine percent are sequels. The average time from domestic box office to video release is approximately 4.5 weeks. The average release for movies in the sample reached 2,040 theaters during the week of wide release, with Pirates of the Caribbean: Dead Man's Chest, Superman Returns, Mission Impossible III, and Over the Hedge opening on over 4,000 theatres. The budget for movies in the research sample varies from a low of $100,000 (Facing the Giants) to a high of $270 million (Superman Returns).

DETERMINANTS OF VIDEO REVENUE

The estimated empirical relationship between the explanatory variables and movie video revenue is presented in Table 2. Two model specifications are put forth based on incomplete data for the BUDGET variable. The first is the full model, which includes all 214 movies in the sample. The second specification only includes the 120 movies that have BUDGET information available. The full and reduced model specifications are extremely consistent. Both models explain approximately 60 percent of the variance in movie video revenue. None of the independent variables have a correlation higher than 0.68 (DBOXOFFICE and FBOXOFFICE have the highest correlation), suggesting that excessive multicollinearity is not a problem with the analysis. Five out of the ten independent variables are statistically significant in both specifications.

The first two variables in the model are domestic box office (DBOXOFFICE) and foreign box office (FBOXOFFICE). The results indicate that domestic box office has a positive and statistically significant impact on domestic movie rental revenue but the foreign box office is not statistically significant. The results imply that the domestic box office serves as a complement to movie video revenue instead of a substitute, with every $10 million in domestic box office yielding approximately $1 million in video revenue. Movies that perform well at the domestic box office may serve as a signal that a movie is good as an implicit form of word of mouth. In fact, only the movie Failure to Launch ($55.65 million video rental revenue, $88.7 million domestic box office, $39.7 million foreign box office) was a top five video revenue earner without being a ten domestic box office performer. Pirates of the Caribbean: Dead Man's Chest, Night at the Museum, and The Da Vinci Code are all top five performers in both the domestic box office and movie video revenue. A second possible explanation for the complementary relationship between the domestic box office and the home video market is that popular movies become a shared experience. A person that enjoys a movie at the box office may have a propensity to share the experience on video with relatives or friends when visiting during the holidays or via explicit word of mouth. The small coefficient on the foreign box office variable (0.006., t-statistic of 0.46) is somewhat surprising. Foreign box office smashes like Pirates of the Caribbean: Dead Man's Chest ($62.3 million in video rental revenue, $642.9 million foreign box office) and Casino Royale ($43.4 million in video rental revenue, $456.2 million foreign box office) have a large domestic video following but they appear to be more of an exception than a rule. In general, performance in the foreign market does not appear to be significantly correlated with the domestic video rental market.

Critic is the percent approval rating for a film by a leading group of movie critics (CRITIC). Conventional wisdom suggests that critical reviews are extremely important to the popularity of movies, especially in the early stages of a release. Good reviews are expected to stir curiosity and identify quality, while poor reviews are expected to limit the interest of the influential early adopters. More practically speaking, the advertising agency will select favorable excerpts from reviews and incorporate them in its media campaign to give the impression of critical acclaim (Litman, 1983). Empirical evidence supports the positive and significant impact critics have on the box office as a box office predictor or influencer (Litman & Kohl, 1989; Eliashberg & Shugan, 1997; Reinstein & Snyder, 2000; Terry, Butler & De'Armond, 2004; and King, 2007). This study is the first to investigate the impact of critical reviews on movie video rental revenue. Surprisingly, the Table 2 results indicate that the CRITIC variable is positive but not statistically significant in both model specifications. A theoretical explanation for the results is that critics provide a signal in the early stages of a box office release but are insignificant by the time a film enters the video market. It is also possible that the year 2006 is simply an anomaly year for the movie industry. The movies, Half Nelson, Brick, Dave Chappelle's Block Party, Catch a Fire, and The Proposition all received critical ratings above 85 percent approval but each produced less than $5 million each in video revenue. Alternatively, the movies, The Da Vinci Code, Click, The Break-Up, The Pink Panther, The Benchwarmers, Date Movie, The Hills Have Eyes, Underworld: Evolution, and Firewall are movies with critical approval ratings below 35 percent but earning more than $45 million in video rental revenue. Most of the movies with poor critical reviews but high video revenue are catered to a youthful audience, providing evidence for the King (2007) argument that movie audiences are younger than the general population and less likely to pay attention to movie reviews, especially print reviews.

The independent variable AANOM measures the impact of a major industry award nomination (Academy Awards) on movie video revenue. The positive and statistically significant coefficient associated with the variable implies that an Academy Award nomination accentuates interest in the rental market for movies and has a positive impact on video revenue. Thirty-nine of the films in the research sample received one or more academy award nominations in 2006 sample year. Noteworthy nominees include Dreamgirls (8 nominations, $30.4 million in video rental revenue), Babel (7 nominations, $39.6 million in video rental revenue), The Queen (6 nominations, $35.0 million in video rental revenue), Blood Diamond (5 nominations, $45.0 million in video rental revenue), and Little Miss Sunshine (4 nominations, $46.3 million in video rental revenue). It is widely believed that films that receive an Oscar nomination possess what Rosen (1981) describes as the elusive quality of box office appeal, the ability to attract an audience and generate a large volume of transactions. An Oscar nomination serves as a signaling device, indicating which films are viewed by industry experts as being worthy of recognition. The Academy Award nomination also serves as an indirect source of marketing. The empirical results imply that an Academy Awards are worth approximately $1.3 million dollars per nomination in the video rental market. The result is consistent with the propensity for movie releases with award nominations to mention this fact on the jacket of the video rental box.

Another element considered to factor into the financial performance of a film is the rating assigned by the Motion Picture Association of America. The motion picture industry established the code as a means of giving advance information to parents and others about the theme and treatment of films. This voluntary code was adopted to prevent stringent forms of governmental controls. There are four possible ratings given to films in the research sample--G (general audiences), PG (parental guidance suggested), PG-13 (possibly unsuitable for children less than 13 years of age), and R (restricted; children not admitted unless accompanied by an adult). The conventional wisdom is that family product sells, while an adult theme or treatment has a limited customer base because of age restrictions preventing access to the lucrative teenage market. The restricted rating is often negative in previous research related to box office revenue but the coefficient is positive in this study of the video market. The result implies that people are more willing to watch restricted content at home versus the movie theatre, although this result is limited by the fact that the RESTRICTED variable is not a statistically significant determinant of video rental revenue.

The most surprising empirical results are the negative and statistically significant coefficients on the CHILDREN and SEQUEL variables. One possible explanation for the surprising result is the idea that movies for children and sequels are purchased in lieu of renting. People with small children can testify to buying some movies for multiple viewings instead of renting. The empirical model in this paper does not control for video sales because of a lack of data availability for 2006 releases, which might lead to a problem with the model specification. In fact, all five movies in the data set with more than $100 million in sales revenue fit the sequel or children's movie genre (Pirates of the Caribbean: Dead Man's Chest, X-Men: The Last Stand , Ice Age: The Meltdown, Over the Hedge, and Cars). A second explanation is that revenue for some movies, especially sequels, is absorbed at the box office. The motion picture industry produces the sequel because of the built-in audience for a sequel to a popular film. Movies like Rocky Balboa, Big Momma's House II, The Grudge II, Clerks II, Basic Instinct II, and Santa Clause 3 might have a built in audience of loyal fans interested in the evolving story line but a shrinking interest by the time the movie enters the video market. A third explanation is that there are too many sequels and movies for children in the market resulting in the number of video losers being greater than the number of video winners. For example, Barnyard, Flushed Away, Curious George, Nanny McPhee, Flicka, The Ant Bully, Hoot, Miss Potter, Santa Clause III, Phat Girlz, and Zoom are movies in the children's genre with video revenue under $20 million.

The variable TIME measures the number of weeks separating domestic box office from video release. The recent trend in the movie industry is a narrowing box office to video window. The average time from box office to video release for the 2006 data sample is 4.47 weeks, with a minimum of 2 weeks for the movie Doogal ($7.4 million in box office revenue, $23.5 million in video revenue). The empirical results indicate that time from box office to video release has a negative impact on video revenue but is not statistically significant. The negative coefficient is influenced by the economies of scale associated with the marketing of a new film. Much of the box office revenue of a new release is earned within the first few weeks. Movie distributors often find it advantageous to move to the video market quickly in order to capture original marketing effects from the box office efforts in the video market.

The last two variables in the empirical model are RELEASE and BUDGET. Previous research shows a close correlation between financial success of a film and the number of screens on which the movie is shown during its initial launch (Einav, 2001). The opening weekend of a movie release typically accounts for over twenty-five percent of the total domestic box office gross revenue for a film (Simonoff & Sparrow, 2000). The positive and statistically significant coefficient on the RELEASE variable indicates that movies with a wide release perform better in the video market. The result can be explained by the observation that a wide release will lead to domestic box office success, which is an impetus to success in the video market. In addition, movies with a release on many screens garner branding recognition that is a precursor to success in the video market. The BUDGET variable is positive but not statistically significant in the model. Big budget movies with high profile movie stars, brand name directors, expensive special effects, and large advertising budgets might have an advantage drawing crowds at the box office but appear to have a limited impact on the small screen of the video market. Some big budget movies like the remake of All the King's Men ($55 million budget, $7.2 million box office, $12.8 million in video revenue) struggle in video market while lower budget films like The Last King of Scotland ($6 million budget, $17.6 million box office, $31.8 million in video revenue) find great success.

CONCLUSION

The video rental market is an important source of supplementary income to the movie industry as a means of extending profits or minimizing losses. This study examines the determinants of video rental revenue for the year 2006. Regression results indicate the primary determinants of video movie rental revenue are domestic box office performance, academy award nominations, sequels, movies in the children genre, and the number of theaters showing the film during the opening week of wide release. One of the more interesting applications of the results is the observation that an Academy Award nomination is worth an additional $1.3 million in the video market. The coefficient associated with critical review is positive but not statistically significant implying that critical acclaim that is not directly associated with an academy award has a limited impact on video rental revenue. The most surprising results are the negative and statistically significant coefficients on movie sequels and children's movies. Holding other factors constant, sequels and children's movies earn $6 to $10 million less than other movies. One avenue for future research is to include a variable in the model that controls for video sales. Sales information is increasingly available for movies released in 2008 but not widely available in the year 2006.

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Neil Terry, West Texas A&M University De'Arno De'Armond, West Texas A&M University

Table 1: Summary Statistics: Domestic DVD Revenue (2006)

Variable Mean Maximum Minimum Standard Dev.

VREVENUE 23.697 67.270 0.500 15.252
DBOXOFFICE 42.365 423.271 0.845 54.486
FBOXOFFICE 45.985 642.630 0 84.361
CRITIC 0.454 0.97 0.01 0.279
AANOM 0.449 8 0 1.265
RESTRICTED 0.301 1 0 0.361
CHILDREN 0.168 1 0 0.375
SEQUEL 0.089 1 0 0.285
TIME 4.477 13.0 2.0 1.439
RELEASE 2,040 4,133 42 1,180
BUDGET 47.298 270.000 0.100 47.298

n = 214

Table 2: Determinants of Domestic DVD Revenue (2006)

Variable Full Model Reduced Model
 Coefficient Coefficient
 (t-statistic) (t-statistic)

Intercept 6.916 (2.18) * 9.046 (2.05) *
DBOXOFFICE 0.103 (3.06) * 0.124 (3.79) *
FBOXOFFICE 0.006 (0.46) 0.004 (0.24)
CRITIC 1.862 (0.88) 3.806 (1.16)
AANOM 1.303 (2.29) * 1.369 (1.99) *
RESTRICTED 0.671 (0.43) 0.670 (0.31)
CHILDREN -10.031 (-5.25) * -10.450 (-4.36) *
SEQUEL -6.062 (-2.43) * -6.315 (-2.28) *
TIME -0.491 (-1.08) -0.369 (-0.43)
RELEASE 0.007 (8.09) * 0.005 (3.47) *
BUDGET .002 (0.18)
Adjusted R-Square 0.644 0.588
F-Value 43.81 18.34 *
N 214 120

Note: * p<.05