Association for Information Systems AIS Electronic Library (AISeL) PACIS 2014 Proceedings Pacific Asia Conference on Information Systems (PACIS) 2014 PLAYFULNESS, BIG FIVE TRAITS, AND CYBERLOAFING Ronnie Jia Illinois State University, rjia@ilstu.edu Heather H. Jia Illinois State University, hhjia@ilstu.edu Follow this and additional works at: http://aisel.aisnet.org/pacis2014 Recommended Citation Jia, Ronnie and H. Jia, Heather, "PLAYFULNESS, BIG FIVE TRAITS, AND CYBERLOAFING" (2014). PACIS 2014 Proceedings. 286. http://aisel.aisnet.org/pacis2014/286 This material is brought to you by the Pacific Asia Conference on Information Systems (PACIS) at AIS Electronic Library (AISeL). It has been accepted for inclusion in PACIS 2014 Proceedings by an authorized administrator of AIS Electronic Library (AISeL). For more information, please contact elibrary@aisnet.org.
PLAYFULNESS, BIG FIVE TRAITS, AND CYBERLOAFING Ronnie Jia, Illinois State University, Normal, IL, USA, rjia@ilstu.edu Heather H. Jia, Illinois State University, Normal, IL, USA, hhjia@ilstu.edu Abstract Few IS studies have examined the phenomenon of cyberloafing, i.e., nonwork-related Internet use by employees during work time. This in-progress research proposes to take an individual trait approach and investigates the impact of general traits, like the Big Five, as well as domain-specific ones, such as computer playfulness. It is hypothesized that while the Big Five will be significant predictors of cyberloafing, computer playfulness, as a domain-specific trait, will explain significant incremental variance above and beyond the Big Five. Expected contributions are discussed. Keywords: cyberloafing, trait, Big Five, computer playfulness
1 INTRODUCTION Cyberloafing refers to employee nonwork-related Internet use during work time, such as playing online games and browsing the Internet for personal reasons (Lim 2002). Though much has been written in the popular press about its pervasiveness and consequences (Adschiew 2000; Conlin 2000; Fox 2010), this phenomenon has received limited attention in the IS literature. Research in business management has examined a set of situational factors related to cyberloafing, such as employee perception of injustice (Teo, Lim & Lai 1997; Lim 2002) and avoidance of less rewarding tasks (Hills & Argyle 2003; Lavoie & Pychyl 2001). With few exceptions (e.g., Jia, Jia & Karau 2013), limited attention has been paid to the role that individual traits play in cyberloafing. Even less work has looked to IT-related specific traits for potential explanations. Personality traits play a powerful role in explaining various individual attitudes and behaviors in the workplace (John & Srivastava 1999). In the IS literature, individual traits, such as the Big Five, have been found to predict technology adoption and use (e.g., Devaraj et al. 2008; McElroy et al. 2007). Despite their explanatory power, many have pointed out the lack of and need to study individual traits (Devaraj et al. 2008; McElroy et al. 2007; Venkatesh & Windeler 2012). Individuals attitudes, beliefs and cognitions with respect to technology are, at least in part, determined by their traits after all (Venkatesh & Windeler 2012). This study strives for a deeper understanding of the cyberloafing phenomenon as it also contributes to the trait literature in IS. We take an individual trait approach and examine the influence of general traits like the Big Five as well as specific ones, such as computer playfulness, since domain-specific traits likely have superior explanatory power (Agarwal & Prasad 1998; Webster & Martocchio 1992). This study examines the relative explanatory power of the Big Five and computer playfulness. In sum, this research has two objectives: 1) testing the Big Five and computer playfulness as predictors of cyberloafing, and 2) examining their relative explanatory power. We begin by first reviewing research on the Big Five and playfulness, and then develop their relationships with cyberloafing. 2 PRIOR LITERATURE AND HYPOTHESIS DEVELOPMENT 2.1 Big five traits and cyberloafing Individual traits refer to attributes that consistently distinguish people from one another in terms of their basic tendencies to think, feel, and act in certain ways (Ones et al. 2005) and are reasonably consistent over time across situational stimuli (Buss 1991). Amongst the existing frameworks to study individual trait, the Five-Factor Model, or the Big Five, including extraversion, agreeableness, conscientiousness, emotional stability, and openness to experience, has been regarded as the most agreed upon framework because of its consistency with various psychological theories, validity across age, gender and culture, and links to a biological component (Costa & McCrae 1992a/b; Goldberg 1993; Viswesvaran & Ones 2004; Zweig & Webster 2004). The Big Five have been found to predict the amount of technology use, particularly Internet use (Deveraj et al. 2008; Landers & Lounsbury 2006; McElroy et al. 2007). Thus, we expect that the Big Five can predict employee nonproductive Internet use as well. H1: The Big Five traits are significant predictors of cyberloafing.
2.2 Computer playfulness and cyberloafing Computer playfulness, as a trait, has been defined as the degree of cognitive spontaneity in microcomputer interactions (Webster & Martocchio 1992) and has been one of the most frequently studied trait in the IS literature. See Wu and Lu (2013) for a review. As an intrinsic motivator to use technology, playfulness has been posited to lead to non-productive plays, such as playing computer games at work (Webster & Martocchio 1992). Thus, we expect it to contribute to Internet loafing at work. Prior work has also shown that playful individuals are more likely to experience cognitive absorption and flow during IT use (Agarwal & Karahanna 2000), which can prolong their nonproductive play. H2: Playfulness is a significant predictor of cyberloafing. 2.3 Relative explanatory power The use of domain-specific traits has received support in other fields (e.g., Flynn & Goldsmith 1993; Goldsmith & Hofacker 1991; Paunonen & Ashton 2001). Though IS researchers have made similar arguments conceptually -- that in order to achieve high predictive power, the predictor must be domain specific rather than global (Agarwal & Prasad 1998), and that Situation-specific individual characteristics relate more strongly than more general individual characteristics to organizational outcomes (Webster & Martocchio 1992) there has been little empirical work supporting the use of domain-specific traits in IS. Such empirical tests are needed since much trait research in IS has focused on IT-specific traits. This study examines their relative explanatory power. H3: Playfulness explains significant incremental variance in cyberloafing beyond the Big Five traits. 3 METHOD The hypothesized relationships will be examined using a survey of working adults. All survey items used in this study will be extracted from existing scales in the literature. Cyberloafing will be measured with items from a scale from Lim and Teo (2005). The Big Five traits will be assessed with the International Personality Item Pool (IPIP, Goldberg et al. 2006). Playfulness will be measured by a scale from Webster and Martocchio (1992). Hierarchical regression will be used for data analysis because it can assess the incremental explanatory power of the predictors as they are entered sequentially into the regression model (Hair et al. 2006). 4 EXPECTED CONTRIBUTIONS This study aims to take an important step toward a deeper understanding of cyberloafing, a phenomenon that so far has received little attention in IS research. This research takes the individual trait approach to examine the impact of general traits, such as the Big Five, and a domain-specific trait, like computer playfulness. We expect that the Big Five will predict cyberloafing, and that playfulness will explain significant incremental variance beyond the Big Five. While much IS literature has focused on the positive outcomes of playfulness, this study can contribute to the literature by showing that playfulness can also lead to negative outcomes, such as cyberloafing.
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