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This study applied a uses and gratifications approach to investigate social games — the game applications integrated in social networking platforms. Users' expected social gratifications and game gratifications from playing social games were examined. The investigation focused on three dimensions of game play: frequency, duration, and engagement of game activities. A hierarchical regression analysis found that social interaction and diversion are positive predictors of game play. Results suggest that there is a distinctly social aspect to social games that reflects their social networking characteristics. Social games should be described as social media rather than as just one category of online computer games.
What are social games?
Theoretical framework
Discussion and conclusions
Growing crops in your virtual gardens, helping out on friends' farms, or even rustling piggies and stealing fruit from their fields, over 15 million players in China spend more than five hours a day [1] on Happy Farm, one of the most popular games running on social networking sites (SNS).
Social games, which are gaming applications integrated into social networking platforms such as Facebook and MySpace, have enjoyed enormous popularity. Facebook imported Happy Farm in April 2009. The game peaked with over two million monthly active players within that year (Facebook, 2009), and brought in 30 to 40 percent of Facebook's monthly revenue [2]. Top social game companies have gained a massive user pool over the past three years: Zynga [3] has a user base with 242 million monthly active users; Five Minutes [4] has 73 million; and Playfish [5] has 50 million. The social gaming market generated revenues of US$76 million in 2008, US$639 million in 2009, and a predicted US$826 million in 2010 (Caoili, 2010).
This explosive growth in social games could have its own important implications for research. A traditional core concern for media scholars is the possible negative social impacts brought about by the diffusion of media such as television, cable, and the Internet. Based on the observation of the general decline in social engagement in contemporary America during the rise of television, Putnam (2000) has proposed that people are leading more isolated lives in which time is spent on passive media at the expense of social and community activities. This concern has led to a debate as to whether Internet–based activities displace valuable social activities. Some scholars have argued that the Internet makes people lonelier, encroaching on time that could otherwise be spent with family and friends (Kraut, et al., 1998; Nie and Erbring, 2002). Others have argued that the Internet, unlike traditional passive media such as television, is capable of connecting people across time and space and thus facilitates social interaction and communicative activities (Williams, 2006; Wellman, 2001; Boase, et al., 2006). While both sides of the debate have received empirical support, a growing number of scholars are suggesting a more nuanced approach to examine Internet use (Shen and Williams, 2010; Steinkuehler and Williams, 2006; Williams, 2007). People use the Internet in different ways. They are able to engage in a variety of online activities — surfing Web sites for information, watching videos, writing e–mail messages, chatting with friends, participating in virtual communities, and others — along a continuum from asocial to social. It would be more rigorous to consider the impact of differentiated uses on social engagement afforded by the underlying social mechanics of each activity.
Residing on the social networking platforms, social games may have the capacity to serve as a unique venue for socialization in a playful manner. The designed–in structures of social games indeed encourage users to interact with their friends in order to play well in the game. Moreover, a January 2010 survey by PopCap Games [6] found that 24 percent of the 4,917 respondents played social games at least once a week, which indicated that social games have reached an enormous portion of the population. And contrary to prevailing stereotypes, the average age of social gamers was 43, and females (55 percent) were more likely to play social games than males (45 percent). This appeal of social games to a vast, formerly 'nongamer' audience, combined with their particular social mechanism, might suggest an unusual fashion of social game use among players for both game enjoyment and social engagement.
Yet few published research studies have focused on social games. This means that we still have limited knowledge of what social games are and why people play them, and that we have even less understanding of whether their particular social structures provide new "places" for social interaction (Putman, 2000; Steinkuehler and Williams, 2006). The present study attempts to fill this research gap.
Uses and gratifications are useful for studying the motives and usage patterns of computer game players (Lee, et al., 2009; Williams, et al., 2008). This research framework assumes the centrality of people who choose particular communication to satisfy certain needs or interests (Baran and Davis, 2006; Rubin, 2009). Gamers are not passive recipients of the influence of games. Rather they direct the action and make choices throughout the play experience (Williams, et al., 2008). Gamers with different demographic and social backgrounds have always had different expectations and uses of the same media (Sherry, et al., 2006). They purposely engage in a game and expect certain kinds of gratifications from playing (Sherry, 2001; Lee, et al., 2009). The uses and gratifications approach is well fitted for studying the interactive nature of game playing (Sherry, 2001). It provides a foundation to gain insight on the impact of game experiences, the role of players' choices and actions, and their usage patterns (Willams, et al., 2008). This study applies a uses and gratifications approach to examine the motives of social game use.
The following section discusses the four key characteristics of social games that distinguish them from the other types of digital games. Subsequently, uses and gratifications theory is introduced, and possible social motives and game motives of social game players are hypothesized. This paper finds that older players who expect to interact with others and to divert themselves through social games tend to be involved in greater use of those games.
Social games refer to the game applications that are integrated in the social networking platforms. Key components, which differentiate social games from other computer games, are: (1) social platform–based; (2) multiplayer; (3) real identity; and, (4) casual gaming.
The first three components of social games can be considered together as the social feature. Being one category of applications on social networking platforms, social games must operate on social platforms, such as social networking sites (SNS). A player's social connections are an important part of the game. The main game play of a typical social game involves social activates like trading, chatting, flirting, or mischief–making. In other words, social activities taking place within a game's design provide interaction among players in whatever manner the game affords, be it fighting, cooperating, or romancing.
A social game is not social unless it is played with other people whether it's two or two hundred. As many SNS users do not necessarily develop a network in order to meet new people but rather to communicate with people who are already a part of their existing social networks (boyd and Ellison, 2007), social games enable players to interact with real–time friends, like old classmates, work buddies, and family members. Players can browse through friends' game pages and see their activity logs. Yet it is not necessary for all the friends to be online at the same time to play the game. The game world persists whether the user logs on or not, which is the same as in a Massively–Multiplayer Online game (MMO) (Yee, 2006; Schmid, 2008). Events and interactions, which are driven by other users, occur in the game world even when the user is not logged on. Therefore, users themselves are an integral part of the social games. Ideally, in order to play well in a social game, players need to pay attention to their friends' activities.
SNS also provide users with an identity to play their game applications. This means social game players do not need to apply for an extra subscription. Some SNS require a real–name registration. For example, Facebook initially targeted itself as a campus–oriented and real–name registration Web site (Facebook, 2007). Although some SNS have abandoned such policy or less than stringently enforced it less stringently, most SNS users still register with their real name so that their friends can find them. Especially for Chinese SNS users, who appreciate the environment abounding with personalization and self–expression, real–names are very much the "norm" (Kuo, 2008). As such, a social game players usually use real–name identities.
The fourth component of a social game highlights its game feature, which is close to a casual game. Being casual means that a social game is easy to pick up as opposed to an intense and complex hardcore game. Most social games have simple interfaces and they enable players to make visible progress relatively quickly. Interacting with friends can be achieved in the game without any barriers. For example, in Happy Farm, players can perform the farming task by simply clicking on several icons. Lots of small rewards are given out during the game, while no negative consequences are given (e.g., players' levels are always going up, and you never get kicked out unless you choose to). Yet traditional competitive structures, like skill progression and friends–only leaderboards, are still included in the games.
Although some studies have explored the motives and uses of different types of digital games (Williams, et al., 2008; Yee, 2006; Molen and Jongbloed, 2007; Sun, et al., 2006; Lucas and Sherry, 2004; Bartle, 1996), social games can be distinguished from the others. Since social games are social–platform grounded, they can take advantage of a Web sites' social networking capabilities. That is, players have already got an established network of friends and acquaintances to play with. The fact that social gamers mainly play with real–life friends makes social games different from a general MMO, whose players are mostly virtual friends (Yee, 2006) who have never met in real life (Nardi and Harris, 2006). People act differently when there is shared history. Studies have consistently documented that increased friendship and closeness (friends vs. strangers) generally lead to an expansion of cooperative acts (Majolo, et al., 2006), mutual support and toleration (Cords, 1997), and greater accuracy of social judgments, such as mind–reading ability (Funder, 1995; Thomas and Fletcher, 2003). Playing games with friends can have a different dynamic from playing with strangers. A social game is also different from a role–playing game (RPG), in which players assume the role of characters in a fantasy setting, because in a social game people represent themselves since most social networking sites require real name registration. According to many game design experts, social games are poised to set off a revolution in the game industry (Chen, 2009).
But why do people engage in social games? What do users expect from playing? Studies found that motivations behind game play are good predictors of players' usage patterns (Williams, et al., 2008; Sherry, et al., 2006). The predominant research framework for studying media use and other forms of communication activities from the user's perspective is uses and gratifications.
Uses and gratifications in the Internet environment
The uses and gratifications approach assumes that individuals actively use certain media to satisfy certain needs (Baran and Davis, 2006). It has been regarded as better suited for the studies of Internet use (Morris and Ogan, 1996; Newhagen and Rafaeli, 1996; Ruggiero, 2000), since users are more actively engaged communication participants in the Internet environment as compared to degrees of engagement in other traditional media (Ruggiero, 2000). Stafford (2008) and Stafford, et al. (2004) found that internet gratifications could be broken into three categories: process, content, and social gratifications. Ko, et al. (2005) identified four dimensions of Internet uses and gratifications investigating a marketing Web site, namely information, convenience, entertainment, and social–interaction motivations. Starkman (2007) pointed out that the primary motivations for using the Internet are the desires for relaxation, fun, encouragement, and status.
An expectancy–value approach of uses and gratifications
However, as many earlier Internet–related studies have reconfirmed that gratification seeking did not explain media behavior very well (LaRose, et al., 2001; Palmgreen, et al., 1985), a departure from the gratifications sought/gratifications obtained (GS/GO) formulation has been the innovative operational definitions of gratifications, or what might be called prospective gratifications. This approach proposes expectancy–value models of media uses and gratifications (Rayburn and Palmgreen, 1984).
The expectancy–value models predict gratification seeking from communication channels based on an expected outcome. This approach links users' expectations to their individual goal satisfaction (Palmgreen, 1984; Vroom, 1995). According to this approach, gratifications expected "influence the seeking of gratifications, which influence media consumption" [7]. Gratifications expected have been formed over time and are constantly being reevaluated through the degree of satisfaction of past experiences. An individual's feeling of satisfaction derived from past media experience can increase the gratifications expected in the prospective future behavior.
Studies that have employed prospective measures (e.g., Lin, 1999; Charney and Greenberg, 2002; LaRose, et al., 2001) ask what the gratifications are that respondents expect from the media are in the future as opposed to those that they desire or have obtained in the past. Studies (LaRose and Eastin, 2004; LaRose, et al., 2001) found that expected outcomes (e.g., "when using the Internet it is likely that I will have fun") improve the predictive power of Internet use compared to both gratifications sought (e.g., "I use the Internet because I want fun") and gratifications obtained (e.g., "I use the Internet to have fun"). Thus, gratifications expected reflect current beliefs and perceptions about the outcomes of prospective media use. This study uses gratification expected to predict the use of social games.
SNS gratifications
Social games share important attributes with social networking sites in that the former are based on the later. There have been a few attempts to explore uses and gratifications of SNS (Urista, et al., 2009; Joinson, 2008; Subrahmanyam, et al., 2008; Cha, 2010). SNS offers a combination of several computer–mediated communication (CMC) applications, including walls, blogs, music, photo albums, video, and emails (Urista, et al., 2009); previous studies explored the multifunctional uses of SNS that are able to fulfill a variety of needs in one location. As social games are one of the many applications grounded in SNS, it is plausible to examine whether users play social games for the similar social motives identified in prior research of SNS.
Some recent studies have investigated individuals' motivations for using SNS. Urista, et al. (2009) examined two leading online SNS: MySpace and Facebook. Through focus groups, they found that "1) efficient communication, 2) convenient communication, 3) curiosity about others, 4) popularity, and 5) relationship formation and reinforcement" [8] are the factors that motivate young people to use SNS to fulfill their needs. Similarly other studies found that college students used Facebook and MySpace to maintain connections with friends (Lampe, et al., 2007; Ellison, et al., 2007; Cha, 2010) family and relatives (Subrahmanyam, et al., 2008), and because all their friends had SNS accounts (Subrahmanyam, et al., 2008).
Joinson (2008), using an online survey, identified six unique motivations for using Facebook: "social connection (α = .89), shared identities (α = .74), content (α = .74), social investigation (α = .75), social network surfing (α = .79), and status updating (α = .71)" [9]. The third motivation for using Facebook — content gratifications — investigated the gratifications obtained through the use of applications within Facebook, such as "playing games", and "quizzes" [10]. Among the six factors, status updates significantly predict the site visiting frequency, while content gratifications predict the number of hours spent online.
Although these studies have focused on different SNS servers and populations, the motivations found from them are largely overlapping. According to Joinson's (2008) findings, to upkeep "social connections" reflects "relationship formation and reinforcement" [11] motives; ; the motive to obtain "shared identities" may be the result of the consideration that "all friends had SNS accounts" (Subrahmanyam, et al., 2008) and users do not want to feel isolated; to conduct "social investigation" and "networking surfing" are highly correlated (r = .54, ρ < .01) and can be combined together. They cover the motives for "efficient and convenient communication" [12] with friends as well as for fulfilling the needs of being "curious about others" [13].
Comparing and synthesizing the motives for SNS use that are identified in prior research (Joinson, 2008; Urista, et al., 2009; Subrahmanyam, et al., 2008; Cha, 2010), the present study applied all of the U&G factors found in these studies except "content" gratifications (Joinson, 2008). As mentioned earlier in Joinson's study (2008), the content factor measures the gratifications obtained from using different applications within SNS. Social game is one of the SNS applications. Since this study aimed to develop a social game specific measure, the content factor did not apply here.
Accordingly, after eliminating replicated motives, this study located five factors that motivate SNS use and applied them to social games use. These factors are social connection (to keep in touch with friends and maintain relationships); social investigation (to see what friends do and to make new friends); shared identity (to join friends' groups to avoid being left out); popularity (to become a popular figure among friends); and, self–expression (to update one's status or to let friends know your news). It is expected that these motives for using SNS may be salient reasons for playing social games, therefore:
H1a, 1b, 1c, 1d, & 1e. Expected gratifications for social connection (1a), social investigation (1b), shared identity (1c), popularity (1d), and self–expression (1e) from social games will be positively related to the frequency of game play.
H2a, 2b, 2c, 2d, & 2e. Expected gratifications for social connection (2a), social investigation (2b), shared identity (2c), popularity (2d), and self–expression (2e) from social games will be positively related to the duration of game play.
H3a, 3b, 3c, 3d, & 3e. Expected gratifications for social connection (3a), social investigation (3b), shared identity (3c), popularity (3d), and self–expression (3e) from social games will be positively related to the engagement of game activities.
Game gratifications
Social games are one category of general digital games. As such, this study also considers the game motives of social game players. In order to generate gratification items for video game play, Lucas and Sherry (2004) reopened the basic question of what we use the media for by beginning with focus group and interviews. They identified six general categories of video game play motivation: "(a) competition (α = .86) — to compete with other players in the game; (b) challenge (α = .80) — to attempt to beat the game; (c) social interaction (α = .81) — to interact with friends through the game; (d) diversion (α = .89) — to pass time or to stop boredom, (e) fantasy (α = .88) — to do things that are impossible in real life; and, (f) arousal (α = .85) — to play the game because it is exciting" [14].
Sherry, et al. (2006) found that challenge was the most reported motivation for playing video games. Based on the same scale, a recent study of free online games among children (9–13 year–olds) in the Netherlands revealed that among all children challenge was the most popular reason for playing games, followed by fantasy, arousal, social interaction, diversion, and competition (Molen and Jongbloed, 2007). Sun, et al. (2006) found that the gratifications sought by Chinese online gamers, in the order of importance, are: diversion, competition, interaction, meeting strangers, and self–expression. Williams, et al. (2008) found that the motivations for achievement highly determined the total playing time among MMO players. Sherry, et al. (2006) found that video game players' motivations for diversion and social interaction were the most important predictors of the total number of hours they spent playing during a typical week. Yee (2006) found that motivations for escapism were correlated with hours of usage per week for both male and female MMORPGs players.
Social games have some common characteristics with traditional video games in that both are digital games that involve gaming mechanisms and playful features. Therefore, the uses and gratifications scale developed by Sherry, et al. (2006) is employed to explore the game motives of social games players. Accordingly, it is expected that:
H4a, 4b, 4c, 4d, 4e, & 4f. Expected gratifications for competition (4a), challenge (4b), social interaction (4c), diversion (4d), fantasy (4e), and arousal (4f) from social games will be positively related to the frequency of game play.
H5a, 5b, 5c, 5d, 5e, & 5f. Expected gratifications for competition (5a), challenge (5b), social interaction (5c), diversion (5d), fantasy (5e), and arousal (5f) from social games will be positively related to the duration of game play.
H6a, 6b, 6c, 6d, 6e, & 6f. Expected gratifications for competition (6a), challenge (6b), social interaction (6c), diversion (6d), fantasy (6e), and arousal (6f) from social games will be positively related to the engagement of game activities.
Social game selection: Happy Farm
Happy Farm is a virtual agriculture game running on a Chinese SNS Kaixin001. The basic task in the game involves raising crops and livestock. As users spend more time in the game and become sophisticated players, their skill levels go up. And players' "farm cash" accumulate through selling their harvests. Yet perhaps what makes the game extremely popular is perhaps that it also allows players to visit friends' farms, to send them handiwork, and to steal their products. Such social elements within the game's design can be found in many other social games. The present study was targeted at the users of Happy Farm because of its popularity and its representativeness of general social games.
Cross–sectional data were collected through self–administered online questionnaires. Participants were Happy Farm players recruited using a snowball sampling technique. Messages were sent via the SNS with a request for participation as well as a link to the questionnaire. Several players were sent a private message asking them to forward the survey link to their friends who are also Happy Farm players. In the final analysis, a total of 140 Happy Farm players responded to the survey, and 93 of them (66.4 percent) provided usable data: 66.2 percent female, and 33.8 percent male. Other data entries with considerable missing values were removed from the analysis. The mean age was 25.65 (SD = 2.36), ranging from 20 to 37.
Three main categories of variables were measured in the survey: (1) expected social gratifications for playing Happy Farm; (2) expected game gratifications for playing Happy Farm; and, (3) game play variables. A survey instrument describing the measurement of these variables can be found in the Appendix.
Expected social gratifications. To measure expected social gratifications, an 18–item scale was created based on SNS U&G factors developed in previous studies (Joinson, 2008; Urista, et al., 2009). Respondents were asked to what extent they agree (1 = strongly disagree; 7 = strongly agree) that they would expect five different kinds of social gratifications from playing Happy Farm: social connection, social investigation, shared identity, popularity, and self–expression.
Expected game gratifications. To measure expected game gratifications, a 22–item scale developed by Lucas and Sherry (2004) was applied in the questionnaires. Each item was measured using Likert scale questions, which asked the respondents to assess the level of agreement with each scale item (1 = strongly disagree; 7 = strongly agree). The scale consisted of six expected game gratifications: competition, challenge, social interaction, diversion, fantasy, and arousal.
Game play variables. Prior studies have suggested the need to distinguish different types of scales of measuring the amount of media/game use such as frequency and duration (Tidwell and Walther, 2002; Cha, 2010). Joinson (2008) found that, among Facebook users, status updates significantly predict the site visiting frequency, while content gratifications predict the number of hours spent on the site. Therefore, the predictors of media use might depend on what usage measurement is employed.
The present study differentiated three game play variables that measured: (1) the frequency of game play. Respondents were asked to report how often (1 = less than once every couple of months, 12 = more than five times every day) they logged onto Happy Farm; (2) the duration of game play. Respondents were also asked to report the average amount of time (1 = less than 10 minutes every time, 5 = more than two hours every time) they spent on Happy Farm; and, (3) the engagement of game activities. Respondents were asked how often (1 = never, 5 = very often) they played Happy Farm within several special categories of gaming activities. The categories were: collecting harvest; stealing friends' harvests; watering plants for friends, using strategies; growing crops on friends' farms; using 'tools', such as fertilizer and pesticide; looking for tips to play well; and, paying attention to rankings. The measures of activities were summed and averaged to create an index of the engagement of game activities.
Across the total sample, players logged onto Happy Farm five times a week on average (M = 8.82, SD = 2.97), and the average amount of time played each session was around 10 minutes (M = 1.87, SD = 1.05). Among all the gaming activities, players reported that they often grew crops on friends' farms (M = 3.68, SD = 1.63), while they seldom paid attention to the rankings among friends (M = 1.99, SD = .89).
To ensure the reliability of the gratification scales, item analyses were firstly performed. This was followed by an analysis of multicollinearity in order to preclude inappropriate regression analyses.
Construct reliability check
In the present study, the Cronbach's alpha values of the five social gratifications indices were as follow (Table 1): social connection (M = 4.58, SD = .88, α =.90), social investigation (M = 4.16, SD = .95, α = .63), shared identity (M = 3.95, SD = .83, α = .81), popularity (M = 3.53, SD =.91, α = .88), and self–expression (M = 3.86, SD = .99, α = .70). The reliability coefficient of social investigation was low, indicating that the construct had poor internal consistency.
Table 1: Analysis of social expected gratifications. Item number Item n M SD α Social connection 78 4.58 .88 .90 3 I will reconnect with people I've lost contact with. 81 4.52 1.21 5 I will receive some friends' requests. 80 4.40 1.04 6 I will find people I haven't seen for a while. 80 4.74 1.15 7 I will find out what old friends are doing now. 81 4.78 1.04 9 I will be able to contact long distance friends. 81 4.54 1.03 18 I will maintain relationships with people I may not get to see very often. 80 4.29 1.01 Social investigation 79 4.16 .95 .70 4 I will want to see what my friends are doing. 80 4.35 1.24 8 I will use advanced search to look for specific types of people. 81 4.47 1.18 10 I will meet new people. 80 3.39 1.27 (removed) 13 I will stalk some people (pay great attention). 80 3.36 1.17 Shared identity 80 3.95 .83 .81 11 I will join events or activities of my friends. 80 4.26 .92 14 I will belong to the group. 80 3.75 1.03 17 I will decrease the likelihood of being left out. 80 3.82 .97 Popularity 78 3.53 .91 .88 2 I will be more popular among friends. 81 3.35 1.26 12 My friends will think I am very active in the group. 79 3.67 .92 15 I will be more famous among friends. 79 3.51 .89 Self–expression 80 3.86 .99 .70 1 I will attract my friends to view my status and my photos. 81 3.54 1.24 16 I will be able to let my friends know my updates. 80 4.14 1.05
Item analyses were conducted on the social investigation index. Initially, each of the four items was correlated with the total score for social investigation (with the item removed). All the correlations were greater than .45 except for item 10 (M = 3.39, SD = 1.27): "I will meet new people" (r = .23). The correlation between item 10 and the other three social investigation items — to see what others are doing (M = 4.35, SD = 1.24, r = .12, ρ = .30), to look for a special person (M = 4.47, SD = 1.18, r = .12, ρ = .28), and to stalk some people (M = 3.66, SD = 1.17, r = .30, ρ = .01) — were especially low. Item 10 differed in content from the other three items in that it emphasized getting to know new people and networking through games. And according to the above mean scores, players reported they did not expect to meet new people on Happy Farm as much as to get involved in other social investigation activities, which is in line with boyd and Ellison's (2007) findings that SNS users do not necessarily develop a network to meet new people. Based on these results, this item assessing new network development was eliminated from the index. When item 10 was removed, the alpha reliability coefficient of social investigation rose to .70. Through item analyses, the Cronbach's alpha values of the five social gratifications indices were all above .70.
The Cronbach's alpha values of the six game gratification indices in this study were as follow (Table 2): competition (M = 3.26, SD = .94, α = .80), challenge (M = 3.38, SD = .89, α = .84), social interaction (M = 4.38, SD = .97, α = .79), diversion (M = 3.89, SD = .90, α = .81), fantasy (M = 3.45, SD = .92, α = .84), and arousal (M = 3.25, SD = .91, α = .89). Reliability coefficients exceeded .79 for all indices, indicating a reliable measure.
Table 2: Analysis of game expected gratifications. Item number Item n M SD α Competition 82 3.26 .94 .80 7 I will prove my friends that I am good at this game. 82 3.29 1.34 13 I will immediately want to play again if I lose to someone. 82 3.60 1.15 16 It will be important to me to be the most skilled person playing the game. 82 3.39 1.14 20 I will get upset when I lose to my friends. 82 2.74 1.13 Challenge 80 3.38 .89 .84 3 I will feel proud when I master an aspect of a game. 82 3.41 1.14 9 I will feel very rewarding to get to the next level. 81 3.56 1.17 14 I will play until I complete a level or win a game. 81 3.14 1.08 (removed) 22 I will enjoy finding new and creative ways to work through the game. 82 3.34 1.03 Social interaction 82 4.38 .97 .79 10 My friends and I use this video game as a reason to get connected. 82 4.35 1.12 17 Often, a group of friends and I will play the games together. 82 4.41 1.01 Diversion 80 3.89 .90 .81 4 I will forget some of the real-life problems I have. 81 3.67 1.30 5 I will play video games when I have other things to do. 81 3.89 1.13 8 I will vent and relieve stress from the day. 82 3.71 1.17 12 I will feel relaxed. 82 4.27 1.02 Fantasy 81 3.45 .92 .84 1 I will be able to do things I can't do in real life. 82 4.11 1.12 21 I will be able to pretend I am someone/somewhere else. 82 3.17 1.09 15 I will like to do something that I could not normally do in real life. 81 3.28 1.18 18 I will enjoy the excitement of assuming an alter ego in a game. 82 3.29 1.11 Arousal 81 3.25 .91 .89 2 My level of adrenaline will be raised. 82 3.49 .98 6 I will be kept on the edge of my seat. 82 2.98 1.10 11 My emotions will be stimulated. 82 3.49 1.03 19 The game will excite me. 81 3.07 1.09
Multi–collinearity check
Since the zero–order correlations among the 11 expected gratifications ranged from .21 (ρ = .06) to .83 (ρ < .001), the possibility of multicollinearity was checked. The condition number κ [15] (Kappa) was 14, not exceeding the conventional threshold value of 30 above which serious problems of multicollinearity are indicated [16]. Therefore, multicollinearity did not significantly affect the interpretation of results.
Primary results
Three hierarchical regression models were used to examine the contributions of background characteristics, and motivations in explaining the frequency, the duration, and the engagement level of social game play. The demographic control variables were entered in the first block, followed by the eleven gratification variables in the second blocks. The results of the three regression models are reported in Table 4.
Table 3: Amount of game play, engagement in game activity, and demographic variables. Variable n M SD Frequency of game play 95 8.87 2.97 Duration of game play 94 1.87 1.05 Engagement in game activity 91 2.74 .59 Collecting harvest 91 2.67 .90 Stealing friends' harvest 91 3.42 1.09 Watering plants for friends 91 3.10 1.06 Using strategies 91 2.18 1.24 Growing crops in friends' farms 91 3.68 1.63 Using 'tool' functions 90 2.30 1.07 Looking for tips to play well 89 2.17 .97 Paying attention to rankings 91 1.99 .89 Gender Female 50 66.7% Male 25 33.8% Age
(range: 20 to 37 yrs. old)
73 25.6 2.34
Table 4: Multiple hierarchical regressions explaining frequency of game play, duration of game play, and engagement in game activity.
Note: Regression entries are standardized beta coefficients.
* ρ < .10, ** ρ < .05, *** ρ < .01.
Predictors Frequency Duration Engagement ΔR2 Beta ΔR2 Beta ΔR2 Beta Block 1. Control .01 .09* .03 Gender .16 .02 .20 Age -.07 .29** .12 Block 2. .33** .27 .39*** Connection -.27 -.37 -.09 Investigation -.03 .18 .24 Shared identity .08 .20 -.24 Popularity .09 -.42 .08 Self–expression .09 .27 -.08 Competition .21 .34 .30 Challenge .36 -.20 .10 Social interaction .37* .54** .59*** Diversion .46** .04 .35* Fantasy -.64** -.42* -.53** Arousal -.29 .22 -.07 Total R2 .33 .36 .42** F 1.74* 1.87* 2.45** n 59 58 59
Predicting the frequency of playing Happy Farm
The results indicated that diversion (β4d = .46, ρ = .037) and social interaction ((β4c = .37, ρ = .092) were the significant positive contributors in the model. Another significant contributor was found of expected gratification for fantasy (β4e = -.64, ρ = .013), but the relationship was negative and counterintuitive (see Table 4 for the coefficients of other predictors). The final equation accounted for 33.4 percent of the variance in the frequency of game play. Accordingly, the expected gratifications of filling time and relaxing, and interacting with others predicted increased frequency of playing, whereas the expected gratifications of fantasy was a predictor of playing less frequently.
Predicting the duration of playing Happy Farm
Age (β = .29, ρ = .037), and social interaction (β5c = .54, ρ = .015) were significantly associated with the duration of game play. Fantasy motive (β5e = -.42, ρ = .099) was a statistically significant yet negative contributor in the model. The overall equation accounted for 36 percent of the variance in the amount of time spent on the game. Therefore, the results suggested that older users who played Happy Farm for the purpose of interacting with others stayed in the game longer than did their counterparts.
Predicting the engagement of Happy Farm activities
Social interaction motive (β6c = .59, ρ = .005), and diversion motive (β6d = .35, ρ = .092) were significant contributors of the engagement of game activities. Again fantasy motive (β6e= -.53, ρ = .028) was a negatively significant predictor in the model. The final equation accounted for 42 percent of the variance in the engagement of game activities. Accordingly, Happy Farm players who expected to interact with others and find diversion reported that they became more engaged in the game activities.
While social games are experiencing an explosive growth in popularity, they are still very unfamiliar terrain for researchers. This paper presented a quantitative explorative study of social games using the uses and gratifications approach. Based on the special characteristics of social games, the present study proposed that the expected gratifications of social game players include both social motives and game motives. Three dimensions of the game play — frequency, duration, and the engagement of game activities — were examined separately.
The findings indicated that respondents played social games more frequently and became more engaged in different kinds of game activities for the purpose of diversion. That is, social games are used to relax, escape from stress, and avoid responsibilities. Diversion has long been considered a reason for playing video games (Sherry, et al., 2006; Sun, et al., 2006; Yee, 2006; Molen and Jongbloed, 2007). This motivation may not be surprising here. Social games are casual, easy to pick up, "masterable" to a vast, formerly "nongamer" audience, and they require fewer mental resources to process gaming tasks. In addition, "Casual game design commonly features excessive positive feedback for every successful action the player performs" [17]. Such designed–in structures of social games make them cheerful and easygoing 'places': lots of small rewards are given out during the game, and progress is made quickly and is visible. More traditional hardcore game designs, on the other hand, require large amounts of time and resources commitment. In addition, hardcore games generally challenge and punish the player for failing. Players with little knowledge of game conventions and low tolerance for difficulty in hardcore games are likely to become frustrated rather than relax. In prior studies, challenge and competition have been documented as the most popular reasons for playing video games (Lucas and Sherry, 2004; Sherry, et al., 2006; Molen and Jongboled, 2007; Sun, et al., 2006). But neither was a significant motive for playing social games. It is possible that social gamers do not necessarily enjoy the challenge of "beating the game," or beating friends. The "lenient difficulty/punishment structures" [18 of casual design affords that almost all social game players can master the game. Even if they play badly, no punishments are given. Thus, social games do not enforce winning or competing, rather they accommodate more flexible playing styles. Such a carefree and optimistic playing manner may be able to provide desirable places for users to temporarily avoid, forget about, and escape from real–life stress and problems.
There is also a distinctly social aspect to social games. The findings demonstrated that respondents played social games more frequently, spent more time on the game, and got more engaged in game activities for the purpose of social interaction. In fact, the social interaction motive was a stronger predictor of game play variables than the diversion motive. Players want to interact with friends and to keep up social connections through social games. This social reason for playing games is intriguing. It is consistent with what the game developers have envisioned: "social game design isn't about creating a game that is strategically deep as much as it is about making sure that the game, in turn, creates interesting interaction between players" [19. Social networking platforms provide opportunity for the social embedding of games. Applied together, the platforms and the designed–in structures make the social context a critical component of the game play and enjoyment.
The results also revealed that social interaction predicted both frequency and duration of game playing, while diversion only predicted only frequency. As discussed above, social games generally allow the players to make progress or complete a game within short periods. But the game design is also very flexible. In other words, social games require small commitments while allowing the player to spend more time with the game if desired. The findings may suggest that users, who play games for the purpose of interaction with close ties, are willing to play with large time investments. While the underlying structure of social games encourages social interaction in general, users do not passively accept what the technology affords but actively appropriate technology to accomplish their own goals (Bargh and McKenna, 2004). As social games are played in social settings, social considerations may become part of the player's deliberations (Juul, 2010). It is likely that users who relish the social values of game actions and desire to enhance their social standing in the game tend to play long sessions at a time. For instance, they want to help as many friends as they can in the game, or they try to choose specific gifts for particular friends.
The negative relationship between the fantasy factor and game play intensity was unexpected. However, prior studies on MMO (Williams, et al., 2008) have found negative association between the players' motive to be immersed in a fantasy world and the total playing time. They have suggested that some MMO players may not find fantasy elements of the game–play satisfying, such as role–playing. As mentioned, social game players usually use real–name identities in order to interact with real–life friends. They may find that interacting with friends through games does not differ much from real–life social exchanges. For example, close friends who help each other in real life may also help each other out on Happy Farm. Another possible explanation is that as the major game play is to interact with friends, the fantasy factor is not an important element for the players to enjoy the games.
It is worth noting that research on MMO consumption (Shaw, et al., 2006) has indicated that "habit strength" [20 is a powerful predictor of game usage. Habit and consciously planned behavior have been found to be separate and opposing processes (Landis, et al., 1978; Shaw, et al., 2006). This study only investigates only the expected gratifications from social game play. However, the interplay between habit and active decision–making of game play is not considered. Happy Farm players may be initially drawn to the game by the expectation of being popular figures among friends. However, over time game play becomes an automatic, conditioned response and the original motivations are no longer actively reflected during the play (Shaw, et al., 2006). Most users play social games not once or twice but instead repeatedly on an ongoing basis. Logging onto Happy Farm may be triggered by sensory cues and a consistent context (e.g., the sight of the Happy Farm link when surfing the Internet at leisure hours of the day) rather being a planned decision based on expected outcomes. Thus, some expected gratifications may become less salient upon repetition (LaRose and Eastin, 2004). And the game play becomes habitual.
The playing habits may also explain the non–salient predictors of motives for game competition and challenge because most of the players in the present sample may have long since acquired the skills needed to master their game, besides the reason that the design of social games is simple and casual itself.
The author cautions against overly zealous interpretations of the findings from this study; it is not without limitations. In particular, this study relies on a non–probabilistic sampling method (e.g., snowball sampling); the selection of participants was primarily based on a self–chosen strategy. It is worthwhile to select a diverse population to replicate the results. The participant pool presented in the present study makes it problematic to generalize findings to the entire population of social game players. The findings revealed a significant interaction between age and the duration of game play, suggesting that older participants may stay in the game longer. With a relatively small age range of the respondents, the results should be interpreted with caution. Studies have shown that there are significant differences in the preference of game genres across age groups (Sherry, et al., 2003). It is possible that social games are liked best by older people, who have less knowledge of game conventions and can only make small commitments because of a life with parenting, jobs, and general adult responsibilities.
Future research should explore a broader spectrum of social and psychological characteristics that might influence the amount of social game play. Previous studies have consistently shown gender differences in playing computer games (Williams, et al., 2008; Eglesz, et al.,, 2005; Lucas and Sherry, 2004; Shaw, et al.,, 2006). Due to the snowball sampling technique, demographic variances are limited in this study. Further inclusion of individual differences into the study can help us understand the impact of demographic variance on social game playing patterns. In addition, personality also predicts the frequency of game playing (McClure and Mears, 1984). As the current findings suggest that social games are a means of social interaction with friends, it may allow individuals with certain characteristics to become connected in society more comfortably. For instance, one prior study (Sheeks and Birchmeier, 2007) found that people who are shy but wish to be social were able to develop a better relationship with others online. Thus, individual characteristics such as shyness, sociability, and communication skills could be investigated in future research to determine their impact on social game experience.
Although this study suggests that social games have the potential to provide a unique venue for social activities, it is unclear how the use of social games might influence the psychosocial well–being of the players. Recent studies found that online interactions with strangers can come at the cost of meaningful activities with off–line friends and family, while interacting with one's existing social ties through the Internet can enhance social involvement (Shen and Williams, 2011). Social gamers mainly play with close ties. Future research can examine whether social games could serve as a particular site that produces meaningful interaction with high–quality communication. One may also want to take into consideration the size of the in–game network and a player's desire to manage the social situation through games, when investigating the psychosocial outcomes of social game play.
Future research might also focus on various phases of a new medium diffusion process, such as the initiation and termination of social game play and the processes through which habits are formed and broken. According to Hiltz and Turoff (1978, 1981; Rice, 1993), the uses of new media evolve as users become more familiar with them. A combination of uses and gratifications and diffusion of innovations may extend the theoretical approach to understand the uses of a specific game.
Taken as a whole, the findings suggest that players use social games to interact with social ties and to find diversion from real–life stress. These gratifications are also afforded by the particular underlying game structure. Social games are potential avenues to enhance one's social circles, and they should be described as social media rather than as just one of many online computer games.
About the author
Jinghui (Jove) Hou is a doctoral student at the Annenberg School of Communication and Journalism, University of Southern California. Her research primarily focuses on the social psychological factors related to human–computer interaction and technology–mediated communication.
E–mail: jinghuih [at] usc [dot] edu
1. Global Times (2009).
2. Ibid.
3. Zynga is a U.S.–based social game developer. It also claims to be the largest social gaming company in terms of the number of active users. The company develops FarmVille and CityVille that are popular on Facebook.
4. Five Minutes is a Chinese social game company that has developed Happy Farm, the first SNS farming game and likely the most popular social game in China.
5. Playfish is a U.S. social game developer. One of Playfish's hit products is Pet Society, which attracts 21.5 million monthly active users on Facebook.
6. PopCap Games is an American video game developer and publisher. Its games are available for Web, PC, Xbox, cell phones, PDAs, and etc. Its flagship titles include Bejeweled and Plants vs. Zombies.
7. Rayburn and Palmgreen, 1984, p. 540.
8. Urista, et al., 2009, p. 221.
9. Joinson, 2008, pp. 3—10.
10. Joinson, 2008, p. 5.
11. Urista, et al., 2009, p. 221.
12. Ibid.
13. Urista, et al., 2009, p. 221.
14. Lucas and Sherry, 2004, p. 503.
15. See http://en.wikipedia.org/wiki/Condition_number, accessed 1 July 2011.
16. Cohen, et al., 2003, p. 424.
17. Juul, 2010, p. 50.
18. Juul, 2010, p. 54.
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Happy Farm use survey.
Note: The original questionnaire is in Chinese. It was translated by the researcher, who is bilingual in English and Chinese.
Amount of Happy Farm play Frequency: How often do you play Happy Farm on average? (Reverse coded)
- I play every day, and I play more than 5 times per day.
- I play every day, and I play 2–5 times per day.
- I play every day, and I play 1–2 times per day.
- I do NOT play every day. I play 5–6 times per week.
- I play 4 times per week.
- I play 3 times per week.
- I play 2 times per week.
- I play 1 times per week.
- I play less than once a week, but more than once every half a month.
- I play less than once every half a month, but more than once every month.
- I play once every several months.
- Since the installation, I have played only for once or twice.
Duration: On average, when you play, about how long do you play for? (Reverse coded)
- More than 2 hours every time.
- About 1–2 hours every time.
- About 30 minutes to 1 hour every time.
- About 15 minutes to 30 minutes.
- About 10 minutes to 15 minutes.
- Less than 10 minutes every time.
Engagement in Happy Farm game activities How often do you collect harvest on average?
- Never
- Seldom
- Sometimes
- Often
- Very often
How often do you steal friends' harvest on average?
- Never
- Seldom
- Sometimes
- Often
- Very often
How often do you water plants and clean weeds and bugs for friends on average?
- Never
- Seldom
- Sometimes
- Often
- Very often
How often do you use some strategies to play the game on average?
- Never
- Seldom
- Sometimes
- Often
- Very often
How often do you grow crops in friends' farms on average?
- Never
- Seldom
- Sometimes
- Often
- Very often
How often do you use 'tool' functions on average, such as fertilizers, and pesticides?
- Never
- Seldom
- Sometimes
- Often
- Very often
How often do you look for expert tips, and advices in order to play the game well?
- Never
- Seldom
- Sometimes
- Often
- Very often
How often do you pay attention to the rankings among your farm neighbors (i.e., other players) on average?
- Never
- Seldom
- Sometimes
- Often
- Very often
Happy Farm social gratifications Please rate the following statements on how strongly you agree or disagree with them (1= strongly disagree, 7 = strongly agree). When playing Happy Farm:
- I will attract my friends to view my status and my photos.
- I will be more popular among friends.
- I will reconnect with people I've lost contact with.
- I will want to see what my friends are doing.
- I will receive some friends' requests.
- I will find people I haven't seen for a while.
- I will find out what old friends are doing now.
- I will use advanced search to look for specific types of people.
- I will be able to contact long distance friends.
- I will meet new people.
- I will join events or activities of my friends.
- My friends will think I am very active in the group.
- I will stalk some people (pay great attention).
- I will feel the belonging to the group.
- I will be more popular among friends.
- I will be able to let my friends know my updates.
- I will decrease the likelihood of being left out.
- I will maintain relationships with people I may not get to see very often.
Happy Farm social gratifications Please rate the following statements on how strongly you agree or disagree with them (1= strongly disagree, 7 = strongly agree). When playing Happy Farm:
- I will be able to do things I cant do in real life.
- My level of adrenaline will be raised.
- I will feel proud when I master an aspect of a game.
- I will forget some of the real–life problems I have.
- I will play video games when I have other things to do.
- I will be kept on the edge of my seat.
- I will prove my friends that I am good at this game.
- I will vent and relieve stress from the day.
- I will feel very rewarding to get to the next level.
- My friends and I use this video game as a reason to get connected.
- My emotions will be stimulated.
- I will feel relaxed.
- I will immediately want to play again if I lose to someone.
- I will play until I complete a level or win a game.
- I will like to do something that I could not normally do in real life.
- It will be important to me to be the most skilled person playing the game.
- Often, a group of friends and I will play the games together.
- I will enjoy the excitement of assuming an alter ego in a game.
- The game will excite me.
- I will get upset when I lose to my friends.
- I will be able to pretend I am someone/somewhere else.
- I will enjoy finding new and creative ways to work through the game.
Demographic control variables Gender:
- Female
- Male
Editorial history
Received 6 April 2011; accepted 19 June 2011.
"Uses and gratifications of social games: Blending social networking and game play" by Jinghui Hou is licensed under a Creative Commons Attribution–NonCommercial 3.0 Unported License.
Uses and gratifications of social games: Blending social networking and game play
by Jinghui Hou.
First Monday, Volume 16, Number 7 - 4 July 2011
A Great Cities Initiative of the University of Illinois at Chicago University Library.
© First Monday, 1995-2019. ISSN 1396-0466.


text:
Theatre of Change
"Blood at the Root," a newly commissioned play by award-winning playwright Dominique Morisseau, is embarking on an international tour this summer.
When the members of the Penn State School of Theatre's M.F.A. Acting class of 2014 finish their degrees, they will have a lot more than the Penn State mainstage on their résumés. They will have the experience of performing, marketing and touring — throughout Pennsylvania and internationally — a newly commissioned play that examines issues of race, class, sexuality and discrimination in a way that only live theatre can.
The School of Theatre commissioned up-and-coming playwright Dominique Morisseau, who recently won the prestigious Kennedy Prize for Drama Inspired by American History, to write a play for the class of 2014. Commissioning a playwright to create a new work for the graduating class is nothing new — the School of Theatre has been doing it since 2010. But what happened over the past year has taken the students — literally and figuratively — farther than they ever imagined.
"Together we developed a performance piece that celebrates looking beyond our differences in order to move forward."—director Steve Broadnax, associate director of theatre and head of the graduate acting program
Modern-day inspiration
The play, "Blood at the Root" was inspired by the story of the "Jena Six," six black teenagers in Jena, La., who were charged with attempted murder for a schoolyard fight after nooses were hung from a tree at their high school. Because previous assaults on black students had generated far lesser penalties, the conviction of the Jena Six sparked protests and civil rights demonstrations across the country.
The play "represents the culmination of a deeply personal and highly collaborative process," says director Steve Broadnax, associate professor of theatre and head of the graduate acting program. "Together we developed a performance piece that celebrates looking beyond our differences in order to move forward."
During the course of developing and performing the play, it became clear the cast had an overarching goal—to get people talking.
The story of the Jena Six may be one for the history books, but it's a 21st-century tale that played out in 2006-07. "Many people don't realize events like this are still happening," says Tyler Reilly, cast member and managing director for the tour. "This play points to conversations that are begging to be had."
The cast of six — five graduate students and one undergraduate — started those conversations in summer 2013, when they performed the play on a four-city tour of South Africa, culminating at the National Arts Festival in Grahamstown. "We knew the play worked in the rehearsal room, but because it's an American story, we were not sure how it would play out in South Africa," says Reilly. "What we learned was that the play's specificity of time, place and culture is actually what allows people to see themselves, their culture and their issues in the piece."
Each performance ends with a "talkback," during which the cast and audience exchange questions and answers about the play.
The talkback session
The cast members' experience in South Africa made them realize they needed to share the play with an even wider audience. When they returned to the United States, they formed their own tour company, designating specific responsibilities — such as managing director and marketing coordinator — to each cast member. They also began working with Penn State's Office of Student Affairs to schedule performances at the Commonwealth campuses, which began in January 2014.
Each presentation of "Blood at the Root" — starting with the South Africa performances last summer — includes a "talkback" at the play's end, facilitated by Broadnax, a cast member or other associated Penn State faculty. During a talkback session, the facilitator, cast and audience exchange questions and answers about the play's artistic, technical and social aspects.
"It became clear in South Africa that we were starting very important conversations," says Allison Jaye, marketing coordinator for the tour. "We feel we have a responsibility to provide a space where people can have these discussions. And we take responsibility for what we're putting out there."
What they're putting out there is not necessarily easy to discuss, but the talkback sessions have shown that the play resonates with a wide audience. In South Africa, Reilly says, "in every city, we were told why the play was relevant to them and why it was important that we were performing it in their city."
Jaye agrees, noting the play "has really become a conversation with the audiences we're taking it to." The response has been humbling, she adds. "It has been bigger and brighter and more enthusiastic than we ever dreamed. It has really become something bigger than us — it has become a 'service.' "
"The play has been bigger and brighter and more enthusiastic than we ever dreamed."—Allison Jaye, marketing coordinator
Taking it abroad
Providing that "service" has also provided the student actors with an experience they never anticipated. Before they performed in South Africa last summer, they never considered a tour, let alone an international one. But this summer, the company will not only return to South Africa in June, but also perform at the Edinburgh Festival Fringe in August. When Dan Carter, director of the School of Theatre, brought up the possibility of a tour, Reilly says, "we knew it was way too good an opportunity to pass up. But we also realized that if we wanted it to happen, we needed to take the reins and make it happen."
Each cast member has a role beyond performing — in addition to managing director and marketing coordinator, there are coordinators for education programs, development, events and production. The students have organized several fundraising performances, including the U.S. premiere of the play at State College Area High School.
For Jaye, the experience has taught her anything is possible — if you're dedicated. "You have to keep up, and you have to get out of your own way. You have to be willing to go at the speed that things are going to take off," she says. "If one person is dedicated — if I believe in it with all my heart, and dedicate my time, energy and focus to it — then everyone else around me will begin to believe and be dedicated, too. That has been an invaluable lesson."
This summer, the company will not only return to South Africa in June, but also perform at the Edinburgh Festival Fringe in August.
While "Blood at the Root" is based on a story of racial injustice, the cast says the play is about much more than race. "This is not a Louisiana story; this is OUR story," says Jaye. "This is happening here in State College, in Pittsburgh, in southern California, in Syracuse, N.Y. — all places I call home. And I want audiences to go beyond 'race' or deciding 'this piece is about race.' It's not just about that — race is a heavy-weight vehicle for the themes that 'Blood at the Root' brings up, which I believe are challenge and change."
During the course of developing and performing the play, it became clear the cast had an overarching goal — to get people talking. And if audience response is any indication, they have been successful.
" 'Blood at the Root' doesn't just stop here," said an audience member at the Penn State Abington presentation. "It starts here. It plants the seed to have these conversations."
The tour of "Blood at the Root" has been supported by the Penn State School of Theatre, College of Arts and Architecture, Graduate School, Office of the Executive Vice President and Provost, Office of the Vice President for Research, Office of the Vice President for Commonwealth Campuses, Office of the Vice Provost for Educational Equity, Student Affairs, Africana Research Center, Commission for Women, Commission on Racial/Ethnic Diversity and LGBTA Student Resource Center.

subset: commoncrawl


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Kate Upton is the ultimate overnight sensation that managed to become famous for her appearances in the Sports Illustrated Swimsuit Issue, first in 2011, when she was named Rookie of the Year, and then in 2012, when she was announced as the cover model. Now, the 20-year-old blonde bombshell heats up the July 2012 cover of GQ magazine. It seems that everything started last April with "the Dougie", a video filmed at a Clippers game at the Staples Center in L.A., showing Upton dancing to the hit "Teach Me How to Dougie" by the hip hop ... Read More


text:
Kiwi Income Property Trust plans a major expansion of its $187.8 million LynnMall shopping centre in Auckland's New Lynn, possibly spending up to $50 million.
Chris Gudgeon, Kiwi chief executive, said a resource consent application was lodged last year to expand by 1.5ha of floor space, taking the mall from 32,000sq m to 47,000sq m. The amount spent would be probably nearer $50 million than $100 million.
Consent is not yet granted and Gudgeon said there were no immediate plans to build on the site straddling a block between Great North Rd, Totara Ave, Memorial Dr and Veronica St in New Lynn, West Auckland.
"It could be years away. We're just putting in place the building blocks. We want to get planning in place for the future. LynnMall is capable of being a bigger and better offer," Gudgeon said of the property which has 1412 carparks and earns Kiwi $15.3 million annual net rental from total annual sales of $223.8 million.
The property presents Kiwi with big opportunities.
"As far as the Auckland Plan is concerned, New Lynn is a growth centre so it's got metropolitan centre status in the Auckland spatial plan.
"Auckland Council has earmarked it for growth and infrastructure so there's been the railway and roading improvements, and you can see what's happening with the transport centre there and what Infratil has done in that area around the Merchant Quarter," Gudgeon said.
"What we're doing is planning ahead and we have a master plan for LynnMall which includes an entertainment precinct and cinemas ... we've undertaken market research and we think our customers would love to see that."
The food offering at the mall would be included in that multiplex expansion in what Gudgeon referred to as a dining lane.
Building out towards Great North Rd and activating the edge of the centre, with shops on the street front, was on the cards.
He said architecture work had been done by Dave Thornton of the Buchan Group, a business Kiwi had worked with on Hamilton's Centre Place shopping centre.
Kiwi has total real estate valued at $2 billion and Derek Battersby, Whau Local Board chairman, said his organisation was extremely supportive of Kiwi's "magnificent" mall revamp.
Battersby said the property had big potential and additions would be a significant boost to the community.
In a low-key way, Kiwi revealed on an Auckland asset tour last March that it had big ambitions for the site, saying "master planning" was progressing. Property experts believe Kiwi will build out to the edges of the site on the carpark facing Great North Rd, adding a multiplex cinema and many more street-front shops.
"We're looking at the whole mix - the food and entertainment, the mix of the [retailing] majors and mini-majors and specialties to get the right mix," said Gudgeon.
Last year, Kiwi said master planning on the mall was progressing, sales were up, a food court upgrade was complete and new branding and signage was up.
Gudgeon said the Farmers store had been upgraded and a 15-year lease was negotiated "and they're really trading well".
Kiwi investor information said the shopping centre opened in 1963.
"It has been refurbished and extended over the years and is anchored by a Farmers department store, Countdown supermarket and a cluster of popular mini-major retailers," Kiwi said of the mall, next to the new integrated rail and bus interchange by the expanding Merchants Quarter.


text:
Nobody could accuse the press of ignoring the fiasco-on-a-server that is HealthCare.gov. The Obamacare website's woes are dominating coverage on the network news, the cable talk shows, the blogs and, of course, high-octane websites like POLITICO.
But did the press do a good job of covering the Affordable Care Act before the health care exchanges went online—sort of—on Oct. 1? Were we adequately warned of the troubles that were to come? And now that HealthCare.gov's problems are headline news, is the coverage of it any better?
Story Continued Below
Sure, one can find a few examples of one news outlet or another warning of impending catastrophe. In March, CQ's Jane Norman reported that federal health officials were working on "contingency plans" in case the exchanges didn't work. She quoted two: Gary Cohen, director of the Center for Consumer Information and Insurance Oversight, who said he was "pretty nervous" about the rollout, and Centers for Medicare and Medicaid Services official Henry Chao, who said, "Let's just make sure it's not a third-world experience." A few conservative sites picked up the quotes, as did National Journal a few days later, warning flatly: "Prepare for disaster."
But a June report by the Government Accountability Office failed to sound the alarm, noting dryly: "Much progress has been made, but much remains to be accomplished within a relatively short amount of time"—and the coverage of it was accordingly muted. POLITICO did note that "IT could end up being health reform's highest hurdle." The Washington Post , in August, and the New York Times, in late September, highlighted problems with the state exchanges, but not the more serious internal concerns about HealthCare.gov. Overall, the press was not very prescient, not just about the ACA's looming tech problems, but also in informing readers and viewers about this admittedly complicated bill's downstream consequences.
So when the law actually came into effect on Oct. 1, Americans were by and large not prepared—not for the website when it froze up and not for the millions of cancellation notices that went out to Americans in the individual insurance market. The news hit like a bomb—and the political impact hit that much harder for the Obama administration. Why hadn't the media caught wind of HealthCare.gov's troubles? Had President Obama lied when he promised, "If you like your health care plan, you can keep your health care plan." And if so, why didn't the media call him on it at the time?
One obvious reason: Health policy is tough stuff. Since 2007, I have written more than 700 posts for the Columbia Journalism Review examining the coverage of health reform, starting with the debates of the 2008 election and long beyond. From this perch, I've seen most of what the press has sent out to the public during the debate over the Affordable Care Act through its implementation last month. And I have to say: With a few exceptions, much of it has been dismal.
Some of that is inherent to the subject matter. "There's been a tension between trying to talk about the law without boring people and making the explanations too complicated," explains Josh Archambault, a senior fellow with the Foundation for Government Accountability, a conservative think tank active in state capitals.
There's no question most of us failed to dig into the most basic question of all: Would the darn thing work?
But it's more than that. Although the media spoke or wrote zillions of words about the ACA, relatively few explained in meaningful ways what the law was all about, who would be affected by it and how—in short, how would it affect peoples' lives and why they should care. The media, for the most part, fell down on the job when it came to dissecting the promises made by supporters (for example, that people could keep their insurance and their doctors); who would pay for the subsidies; why essential benefits were important; and why there had to be an individual mandate with penalties for not buying insurance. And there's no question most of us failed to dig into the most basic question of all: Would the darn thing work?
What the press delivered instead was mostly a conversation among policy wonks and Beltway political elites without letting in the people who would be most affected by the nostrums they were prescribing. The public was the victim of a messaging war, with much of the conversation shaped by spin and talking points. And as in all wars, truth is the first casualty. Americans needed clear, direct explanations, honesty, dot connection and a probe of the carefully crafted words that came to define the debate. Yes, there were plenty of fact-checkers keeping watch, but as press critic and political scientist Brendan Nyhan has pointed out, these services can fall short. Their one-the-one hand, on-the-other hand format often confuses more than illuminates. Against this backdrop, the backlash of the last few weeks was probably inevitable.


text:
Note: re-published to fix typos in the opening paragraph. Oh the perils of late night posting.
In BIRT 2.3.1 a new extension point was added to support the creation of user defined functions. Jason has all ready blogged about the ScriptFunctionExecutor here . In this post, I would like to show how this extension point can be used to automate handling Multi-Select input parameters in SQL statements.
BIRT 2.3 added support for Multi-Select parameters. The most typical application of this technology is to support using an IN statement within a SQL where clause. Imagine having the following SQL:
select status
from orders
where state in (?)
What you would like to be able to do is have a user select multiple parameters from a drop down list, and then have them work in the query. At this time, BIRT does not support this, mostly because of the way JDBC property binding works. JDBC would require a new parameter binding (?) to be added for each parameter value that was passed, e.g.
where state in (?, ?, ?)
First, we want to modify our SQL so that the parameters are defined within the SQL. To use my function your SQL will look like this:
select status
from orders
where status in ('MS:pStatus') and
state in ('MS:pState')
In this scenario you have two parameters pStatus and pState that are defined in the report parameters. Then you modify the BeforeOpen method of your DataSet to have the following code:
this.queryText = BlackboardFunctions
.MultiSelectSql(this.queryText, reportContext);
That's is all you have to do. All of the SQL modification and checks for injection strings are done for you in the ScriptFunction. Now the caveats: I realize that there are still SQL Injection issues here. I welcome your suggestions on how to reduce the risk. There is a way that this can be done using Java Bind variables, but it is significantly more difficult.
If you would like to download the full source to the plugin, I have it on my Subversion server here. For the curious, the remainder of this article will talk about how it was done.
First, let's look at the ScriptFunctionFactory. I absolutely hate having to keep code coordinated in more than one place. The ScriptFunction requires that you define the Script in the plugin.xml and in the FunctionFactory. In addition, you will have the actual ScriptFunctionExecutor classes.
What I did was came up with a simple rule, the name of the Function (in plugin.xml), is the name of the ScriptFunctionExecutor class. This simplifies my FunctionFactory to just use the name passed in to find the appropriate class:
Next we need to have the ScriptFunction code that walks through the queryText replacing the messages with the appropriate parameter values
public IScriptFunctionExecutor getFunctionExecutor(String functionName )
throws BirtException {
String fullClassName = plugin_id + "." + functionName;
try {
Class<? extends IScriptFunctionExecutor> functionClass = Class
.forName( fullClassName )
.asSubclass( IScriptFunctionExecutor.class );
IScriptFunctionExecutor scriptFunction = functionClass
return scriptFunction;
catch ( Exception e ) {
throw new BirtException( plugin_id, "Unable to find class: "
+ fullClassName,
getResourceBundle(), e );
public Object execute( Object[] args, IScriptFunctionContext context ) throws BirtException {
final String sqlText = args[ 0 ].toString();
IReportContext reportContext = super.getReportContext( args[ 1 ] );
// find the Multi-Select replacement string
List<String> matchList = new ArrayList<String>();
try {
Pattern regex = Pattern.compile( "\\('MS:[A-Za-z0-9]+'\\)" );
Matcher regexMatcher = regex.matcher( sqlText );
while ( regexMatcher.find() ) {
matchList.add( regexMatcher.group() );
catch ( PatternSyntaxException ex ) {
// Syntax error in the regular expression
String rtnStr = sqlText;
// iterate through each multi-select parameter
// in the sql and replace with appropriate parameter values
for ( final String matchStr : matchList ) {
String searchFor = matchStr.substring( 2, matchStr.length() - 2 );
String paramName = searchFor.substring( 3 );
Object obj = reportContext.getParameterValue( paramName );
if ( obj == null )
removeLine( matchStr, rtnStr );
if ( obj instanceof Object[] ) {
StringBuffer sb = new StringBuffer();
Object[] pVals = (Object[]) obj;
for ( int i = 0; i < pVals.length; i++ ) {
super.testSqlInjection( pVals[ i ].toString() );
sb.append( pVals[ i ].toString() );
if ( i < pVals.length - 1 ) {
sb.append( "', '" );
rtnStr = rtnStr.replaceAll( searchFor, sb.toString() );
return rtnStr;
There are two sub-functions that are lurking in that text. First, a common task for ScriptFunctions will be getting the ReportContext from the EventHandler, while not difficult, it makes sense to have appropriate error handling and testing, so I put that in an abstract super class.
protected IReportContext getReportContext( final Object rcArgument )
throws BirtException {
if ( rcArgument == null ) {
throw new BirtException( InnoventFunctionFactory.plugin_id,
"ReportContext object is null in "
+ this.getClass()
.getResourceBundle() );
if ( ( rcArgument instanceof IReportContext ) != true ) {
throw new BirtException( InnoventFunctionFactory.plugin_id,
"ReportCtxt is not instance of IReportContext in "
+ this.getClass()
.getResourceBundle() );
return (IReportContext) rcArgument;
Not completely tricky, but who wants to write that code over and over again?
The other statement is the call to test for likely SQL Injection tokens. I know the list is not complete, but what do you expect when you have free advice.
protected void testSqlInjection( String paramValue )
throws BirtException {
List<String> errList = new ArrayList<String>();
try {
Pattern regex = Pattern.compile( "[%]|[']|[;]|[(]|[)]|[=]" );
Matcher regexMatcher = regex.matcher( paramValue );
while ( regexMatcher.find() ) {
errList.add( regexMatcher.group() );
catch ( PatternSyntaxException ex ) {
// Syntax error in the regular expression
if ( errList == null || errList.size() == 0 ) {
// Uh oh, something is fishy in this parameter
StringBuffer sb = new StringBuffer();
sb.append( "Failure to add parameter value :\n" );
sb.append( paramValue );
.append( "The following values are not allowed in parameters \n{ " );
for ( String err : errList ) {
sb.append( err );
sb.append( " " );
sb.append( " }" );
throw new BirtException( InnoventFunctionFactory.plugin_id, sb
.toString(), InnoventFunctionFactory.getResourceBundle() );
Well that is about it. It is probably a lot easier to just download the code and have a look.
I hope to see you all at EclipseCon in two weeks. We have a number of really great talks on BIRT including a four hour tutorial by John Ward. I am teaming up with Seth Grimes to have a discussion about the value of Business Intelligence. I'll be showing a few BIRT reports, but I am going to try and keep a layer or two above the gory implementation details.
One talk that I am really looking forward to will show how you can integrate BIRT into your Rich Internet Applications (RAP) projects. This talk is by Benny Muskalla from EclipseSource and it promises to be really good.
Innovent Solutions, my company, will be at the exhibitors hall. If you enjoy the blog, drop by and say hi.