Identifying research streams in online gambling and gaming literature: A bibliometric analysis

Journal Pre-proof Identifying research streams in online gambling and gaming literature: A bibliometric analysis Julia M. Stehmann PII:

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https://doi.org/10.1016/j.chb.2019.106219

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Computers in Human Behavior

Received Date: 26 June 2019 Revised Date:

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Accepted Date: 3 December 2019

Please cite this article as: Stehmann J.M., Identifying research streams in online gambling and gaming literature: A bibliometric analysis, Computers in Human Behavior (2020), doi: https://doi.org/10.1016/ j.chb.2019.106219. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.

Identifying research streams in online gambling and gaming literature: A bibliometric analysis

Julia M. Stehmann *

Faculty of Business Administration Chair of Marketing & Customer Insight University of Hamburg Moorweidenstraße 18 20148 Hamburg, Germany

November 2019

Declarations of interest None.

Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

*

Tel.: +49 40 42838 8676. E-mail address: [email protected]

1

Identifying research streams in online gambling and gaming literature: A bibliometric analysis

Abstract With the widespread use of the Internet, online gambling and gaming activities have entered everyday life and have increasingly converged in the online marketplace. Since both of these activities seem to meet similar consumer needs and have many characteristics in common, research can no longer consider the two topics separately. As several disciplines have influenced online gambling and gaming studies, researchers and managers have to deal with fragmented knowledge, which makes it difficult to gain a coherent overview and proper understanding of the origins and recent developments of the field. By applying a bibliometric analysis, this study addresses this issue and provides a holistic synthesis of online gambling and gaming research that has been covered by 84 169 cited references in 1876 citing articles. Citation analysis identifies the journals and publications that have received the most attention in this field. Factor and social network analyses reveal that online gambling and gaming literature consists of six main research streams. The results advance our understanding of these streams, including their most representative articles, their key themes, their network connectedness, and their temporal development. Based on the findings, this study proposes directions for future research.

Keywords: Internet gambling; online gaming; convergence; consumer behavior; bibliometric analysis; co-citation

2 1.

Introduction

In recent years, online games have become an integral part of consumers’ daily lives, making them one of the fastest growing leisure activities today (Grimes & Feenberg, 2009; Newzoo, 2018). According to market intelligence firm Newzoo’s latest study (2018), worldwide, more than 2.3 billion consumers play games. In addition, global game revenues have more than tripled from $35 billion in 2007 to $137.9 billion in 2018, and they are expected to reach $180.1 billion by 2021 (Newzoo, 2018). One of the main reasons for the extraordinary growth of the industry has been the advent of the Internet and its widespread use on smartphones, tablets, and computers. Internet technology allows consumers to access online activities everywhere and at any time, thus blurring the boundaries between gambling and gaming (Albarrán Torres & Goggin, 2014; Griffiths, 2011). From a legal point of view, gambling principally requires a monetary wager with a potential financial payout that is mainly determined by chance (Gainsbury, Hing, Delfabbro, & King, 2014; King, Gainsbury, Delfabbro, Hing, & Abarbanel, 2015; Parke, Wardle, Rigbye, & Parke, 2013). Gaming, in contrast, is characterized by active player involvement with a primarily skill-based outcome, and includes contextual elements of progression and success, such as player levels, points, badges, or leaderboards for comparison with other players (Gainsbury et al., 2014; King et al., 2015; Parke et al., 2013). In the online marketplace, however, new hybrid forms of gambling and gaming activities have emerged and continue to do so (King, Delfabbro, & Griffiths, 2010; Owens, 2010). In these hybrid forms, social elements (e.g., chat rooms and social media applications) now appear in gambling activities, while monetary mechanisms (e.g., virtual currencies and items) can be found in conventional games (King et al., 2010; King et al., 2015). Initial research indicates that these two kinds of activities have many characteristics in common (e.g.,

3 Bramley & Gainsbury, 2015; Karlsen, 2011). They also seem to meet similar consumer needs, so that users of one feel familiar when they encounter the other, which in turn could encourage migration between gambling and gaming (e.g., Gainsbury, Russell, King, Delfabbro, & Hing, 2016). Despite these activities continuously converging in the online marketplace, and being motivated by the same factors, research has mainly discussed gambling and gaming topics separately and as distinct from each other. The obvious connection between the two is not explicitly established or recognized (Gainsbury et al., 2014). To date, only a handful of review articles that provide a deep understanding of different aspects, have dealt with both areas together. These reviews provide a taxonomy of online gambling and gaming activities (e.g., Gainsbury et al., 2014), summarize potential consequences of social casino games for future gambling behavior (e.g., Wohl, Salmon, Hollingshead, & Kim, 2017), or address the neurobiology of Internet gaming and gambling disorders (e.g., Fauth-Bühler & Mann, 2017). Another hurdle in the advancement of the research field is presented by online gambling and gaming scholars having borrowed and assimilated methodologies and theories from multiple disciplines, such as computer science, psychology, and communication studies (Mäyrä, Van Looy, & Quandt, 2013). Given these dynamic interchanges, the body of literature on online gambling and gaming appears to be heterogeneous and scattered (Mäyrä et al., 2013; McGowan, Droessler, Nixon, & Grimshaw, 2000). This makes it challenging for researchers and managers to derive insights applicable to their particular area of investigation, and to effectively translate research findings into practice. These circumstances emphasize the need for a systematic review, which includes the research activities of both online gambling and gaming across disciplines (Griffiths, 2011). In this way, researchers and managers can benefit from bringing together fragmented knowledge to better understand the roots and recent developments of online gambling and gaming

4 research, to more easily apply the research findings to their field of interest, and to support the identification of new directions for future research. Against this background, the study adopts a large-scale quantitative bibliometric analysis of online gambling as well as online gaming research covered by 84 169 cited references used in 1876 citing articles across multiple disciplines. The study addresses the following research questions: 1. Which are the most cited publications and journals within online gambling and gaming research and thus provide a starting point in identifying high impact research in the field? 2. What are the major research streams in the large body of online gambling and gaming literature that promote a common understanding of the prevailing schools of thought? 3. Which interactions already exist in the research network? 4. How has the prevalence of research streams changed over time? 5. Which directions offer potential for future research?

2.

Status quo of systematic literature reviews of online gambling and gaming

Research on gambling and gaming have historically been treated as separate issues (Gainsbury et al., 2014; Parke et al., 2013). The influences of various disciplines, including computer science, psychology, and communication studies, have reinforced the division of the field, which continues into the present (Mäyrä et al., 2013; McGowan et al., 2000). Previous literature reviews reflect these circumstances, as most authors provide valuable insights either on gambling or on gaming topics. Thus, it remains unclear how research projects in the areas of gambling and gaming relate to, or build on, each other and, in particular, what opportunities and risks arise for gambling and gaming companies from the increasing convergence of the two activities in the online marketplace.

5 Surprisingly, to date only a few systematic reviews that provide a deep understanding of different aspects of the field, have simultaneously investigated online gambling and online gaming topics. For instance, the review articles by Gainsbury et al. (2014), King et al. (2015), as well as Parke et al. (2013) proposed definitions and classifications of online gambling and gaming activities. Other reviews examined the prevalence (Ferguson, Coulson, & Barnett, 2011) or the neurobiological correlates (Fauth-Bühler & Mann, 2017) of Internet gaming disorder, drawing analogies between Internet gaming disorder and pathological gambling. In turn, Wohl et al. (2017), as well as King and Delfabbro (2016) summarized literature on potential consequences that non-financial, simulated gambling activities, such as social casino games, have for future gambling behavior. Besides those mentioned above, there is only one citation study in the socio-cultural domain of gambling and gaming (McGowan et al., 2000), which was published almost 20 years ago, and that misses a multidisciplinary view on recent developments in the online marketplace. In addition, that study’s sample size of 264 publications is considerably smaller than the 1876 articles in the case of this study. Still, the citation study by McGowan et al. (2000) stressed the relevance of consolidating gambling and gaming research, which was clearly growing due to the rapid spread of the Internet and the increasing convergence of these online activities.

3.

Bibliometric methods

The technique used in this study is rooted in bibliometrics, which is a statistical method to identify the intellectual structure and development of a scientific field (Culnan, 1986; White & Griffith, 1981). A major advantage of bibliometrics is its objective approach in using quantitative parameters of citation data from a variety of studies for citation and co-citation

6 analyses, thus counteracting possible subjective evaluation of literature reviews (Acedo & Casillas, 2005; Garfield, 1979; Vogel & Güttel, 2013). Citation analysis is based on the assumption that the number of citations can be used as a measure of the utility or impact of scientific work (Garfield, 1979). It has been applied in this study to provide information on the most cited journals and publications in online gambling and gaming research. Specifically, citation analysis suggests that a publication with a high citation count has been considered useful by a large number of scientists, which indicates a greater influence on the research field than a less frequently cited publication (Culnan, 1986; Garfield, 1979). It should be noted, however, that citations do not reveal authors’ reasons for citing certain articles and excluding others, and therefore considering numbers requires careful judgment (Garfield, 1979). In addition, a co-citation analysis was done to examine the frequency with which any two publications are cited together in the later literature (McCain, 1990; Small, 1973). The underlying assumption of the method is that the more often two articles are jointly cited, the higher their perceived similarity (McCain, 1990; White & Griffith, 1981). The output of the co-citation analysis is a symmetric matrix, showing all cited articles as column and row headings, and the co-citation frequencies for all cited article pairs in the cells. The diagonal cells of the matrix were replaced by the sum of the three highest co-citation values for each cited document divided by two, following the procedure put forward by White and Griffith (1981). The co-citation matrix then served as a basis for further analyses. 3.1

Factor analysis and social network analysis

Exploratory factor analysis is a common technique in bibliometrics for identifying subgroups in a field (e.g., Culnan, 1986; McCain, 1990). To standardize the data and avoid possible scale effects, the raw co-citation matrix was converted into a matrix of Pearson correlation coefficients (McCain, 1990; White & Griffith, 1981). The subsequent exploratory

7 factor analysis, using principal component analysis and Varimax rotation with Kaiser normalization, grouped publications with similar co-citation patterns into factors (Culnan, 1986; McCain, 1990; Pilkington & Liston-Heyes, 1999; White & Griffith, 1981). Thus, each factor captures a common intellectual theme, defined by the publications that are grouped together in that factor (Nerur, Rasheed, & Natarajan, 2008; Small, 1973). Factors can therefore be considered as research streams or discourses, which together constitute the intellectual structure of the field. The amount of variance explained by a factor is an indicator of a stream’s importance for the conceptual foundation of the field. The factor loading reflects the extent to which an article represents the prevailing theme of the respective discourse (Nerur et al., 2008). To complement the results of factor analysis, social network analysis was performed on the co-citation matrix to visualize structural patterns and linkages within the research network (Pilkington & Meredith, 2009; Vogel, 2012; Vogel & Güttel, 2013). The network diagram was produced with the spring embedder algorithm, using the software UCINET by Borgatti, Everett, and Freeman (2002). This graph layout algorithm positions articles according to their geodesic distance, indicating their centrality in the network (Vogel & Güttel, 2013). In addition, network density measures for the connectedness of research streams within the network were computed (Otte & Rousseau, 2002). After dichotomizing the co-citation matrix, density is calculated as the ratio of existing linkages between articles to all possible linkages within a research stream. A density value of zero represents that articles in a stream have no connection to all other articles in that stream, while a density value of one indicates that all articles in that stream are connected to one other and exchange information intensively (Hanneman & Riddle, 2005; Otte & Rousseau, 2002; Vogel & Güttel, 2013).

8 3.2

Database

To assess the extant research on both online gambling and gaming topics, data was collected from the Social Sciences Citation Index that provides bibliographic references of every article (Ramos-Rodríguez & Ruíz-Navarro, 2004). The search terms used were “online gam*” and “Internet gam*”. To ensure a high-quality data set, only double-blind, peerreviewed articles that are also regarded as certified knowledge were included (RamosRodríguez & Ruíz-Navarro, 2004). The search with these criteria resulted in a finding of 2318 publications. Of these, 442 were excluded from the analysis, because a manual inspection of the title and abstract showed that they either fell outside of the scope of the present study (e.g., they were from other research fields, such as online gamma-ray spectroscopy from physics) or addressed topics of offline gambling and gaming without reference to the Internet. This manual inspection resulted in 1876 articles with 84 169 cited references, covering a wide range of different disciplines, such as psychology, computer science, psychiatry, business and economics, education, and communication studies. Following common practice in bibliometrics (e.g., Pilkington & Liston-Heyes, 1999; Vogel, 2012), different spelling forms of the same cited reference were manually adjusted to assure accurate analytical results.

4.

Results of citation analysis

Fig. 1 shows the time distribution of the 84 169 cited references, revealing that the growth in numbers of cited articles primarily began in the mid-1960s. Before that, online gambling and gaming research was still in its infancy and accounted for less than one percent of all citations. Thus, for reasons of clarity, only data as of 1965, from the beginning of the actual growth period, are displayed. In particular, since the end of the 1990s, research in this field

9 has flourished in number of citations, indicating an ongoing interest of the engaged community in online gambling and gaming topics. After the peaks in 2007 and 2009, there was a slight decrease in citations, which is due to the fact that it takes time for a publication to be recognized and widely cited (Pilkington & Meredith, 2009). Fig. 1 here 4.1

Most cited journals

Table 1 lists the journals most cited in the 1876 citing articles, giving their number of citations (TC), number of publications (TP), and average citations received per article (TC/TP). At the top of the list, with the most citations and the highest average of citations per article, is the journal Cyberpsychology, Behavior, and Social Networking (formerly CyberPsychology & Behavior) that received 4255 citations within 531 articles, and 8.01 citations per article. Only the journal Computers in Human Behavior shows higher productivity with 2459 citations in a total of 609 articles, i.e., the second highest number of citations on the ranking. Both these journals address social, behavioral, and psychological impacts of social networking practices or computer use, including online gambling and gaming issues. The list in Table 1 also includes journals that deal with only one of the two topics. For instance, the journal International Gambling Studies covers theory, methods, practice, and history of gambling, while the journal Games and Culture investigates socio-cultural and economic dimensions of gaming. Interestingly, the Journal of Psychiatric Research, which focuses on psychiatry and cognate disciplines, such as epidemiology and neurosciences, reaches the second highest productivity rating across both topics, with 7.98 citations per article. Despite this journal producing fewer articles, the ones it publishes receive relatively many citations, with 47 articles covering 375 citations.

10 Overall, the most cited journals in Table 1 indicate the multidisciplinary scope of online gambling and gaming research, especially in the areas of psychology (e.g., Journal of Personality and Social Psychology, Psychological Bulletin), computer science (e.g., Computers & Education, MIS Quarterly), as well as psychiatry and mental health (e.g., Addiction, International Journal of Mental Health and Addiction). Table 1 here 4.2

Most cited publications

Table 2 provides a first insight into the topical structure of online gambling and gaming research, showing the publications that are most cited in the 1876 citing articles. Six of the ten most cited articles (rank one, three, six to nine) focus on addiction to online gambling and gaming as well as to the Internet. The other four of the most cited publications (rank two, four, five, and ten) deal with what motivates online game playing, stereotypical player profiles, and social interaction, especially in massively multiplayer online games. To investigate the results further, the average number of citations received within the 1876 citing articles per year up until 2017 (TC/t) is measured. The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM) of the American Psychiatric Association (APA, 2013) dominates the list with 273 citations, as well as the highest ratio of citations at 54.6 per year. This manual is the one most widely used in psychiatric practice, research, and academia as it establishes the main diagnostic criteria for mental disorders. The DSM-5 not only addresses gambling disorder, but also lists Internet gaming disorder in Section III as a condition requiring further study for the first time (APA, 2013). This listing represents a major advance in providing essential foundations, definitions, and diagnoses for the field of online gambling and gaming, thus explaining the manual the large number of citations it has received within a relatively short time.

11 Table 2 here

5.

Results of factor analysis

Researchers have found that bibliometric data are highly skewed in their upper tails, indicating that a large number of publications receive very few citations and therefore have no great or meaningful influence on the development of a scientific field (e.g., Chen & Leimkuhler, 1986; Pilkington & Liston-Heyes, 1999; Pilkington & Teichert, 2006). Thus, in line with standard procedures of bibliometric analyses to identify major research streams in a given field, the correlation matrix for factor analysis was limited to the 163 most cited articles that received at least 30 citations (e.g., Culnan, 1986; McCain, 1990). The examination of different citation thresholds confirmed that the chosen threshold was neither too restrictive, nor too broad for the area of investigation, since the assignment of the publications to the extracted research streams remained stable. Therefore, the author continued this study with the first chosen threshold. In addition, articles with a measure of sampling adequacy of less than .5 (Kaiser & Rice, 1974) were excluded, which resulted in a final factor solution of 150 articles. The overall measure of sampling adequacy of .77 was meritorious (Kaiser & Rice, 1974), and Bartlett’s test of sphericity was statistically significant (p < .001), which confirms the suitability of the factor analysis. In all, six factors were extracted from the data, explaining 79 percent of the variance. Table 3 presents each research stream with its ten most representative publications based on the highest factor loadings. Subsequently, the assigned publications were thoroughly analyzed to reveal the respective streams’ prevailing themes and schools of thought, which are discussed in sections 5.1 to 5.6 below. Primarily, publications with high factor loadings, indicating high representativeness for the respective discourse, served as references. Table 3 here

12 5.1

Assessment of Internet gaming disorder

The first research stream includes publications which deals with the question of the assessment of Internet gaming disorder also known as problematic online gaming, Internet gaming addiction, or pathological video gaming. Griffiths (2005) provides a theoretical contribution with a model of addiction that includes six components: (1) salience, when gaming constantly determines thoughts, feelings, and behavior, (2) mood modification, when mood changes as a consequence of gaming, (3) tolerance, once an increasing amount of time spent gaming is required to generate priorly experienced mood-changing effects, (4) withdrawal, as negative moods or physical consequences occur due to interruption or reduction of play, (5) conflict, due to excessive gaming, with oneself, with other people, and/or in activities (e.g., at school, at work, in social life), and (6) relapse, which manifests as the tendency to return to previous patterns of gaming after a period of abstinence or control. Other articles of this stream contribute empirically by developing scales for the assessment of Internet gaming disorder based on survey data. Most of these scales have been adapted from the criteria for pathological gambling in the DSM-IV (e.g., Gentile, 2009) or are based on the proposed criteria for Internet gaming disorder in the DSM-5 (e.g., Pontes, Király, Demetrovics, & Griffiths, 2014), both with parallels to Griffiths’ (2005) model of addiction (Lemmens, Valkenburg, & Gentile, 2015). The systematic review of psychometric assessment tools for pathological video gaming by King, Haagsma, Delfabbro, Gradisar, and Griffiths (2013) points out that the available measures (a total of 18 instruments used in 63 studies) differed widely in how they described core addiction criteria and thresholds for determining clinical significance. In addition, in their meta-analysis Ferguson et al. (2011) show that the different measurement methods led to various prevalence rates of pathological gaming. In sum, articles in this stream stress the need for a unified approach toward assessing Internet gaming disorder for it to be recognized as an independent clinical entity.

13 5.2

Neurobiological processes

The second research stream contains articles that deepen our understanding of the neurobiological processes that underpin people’s longing for online games or, more generally, their addiction to the Internet. The majority of studies in this stream apply neuroimaging techniques, such as functional magnetic resonance imaging (fMRI) or electroencephalography (EEG), to record brain structure and activity in experimental designs. The investigated brain areas include those associated with inhibitory control, attention, reward, and punishment (e.g., Dong, Lu, Zhou, & Zhao, 2010; Dong, Huang, & Du, 2011). Regarding inhibitory control and attention, Dong et al. (2010) indicate that compared to healthy control subjects, Internet addicts require more cognitive effort to inhibit their response impulses (higher P3 amplitude, calculated at the positive maximum between 250 and 450 ms), are less efficient in information processing (longer P3 peak latency), and have a lower activation in detecting response conflict (lower N2 amplitude, calculated at the negative maximum between 180 and 220 ms). A later study by Dong, DeVito, Du, and Cui (2012) confirms diminished cognitive efficiency in Internet addicts (through greater activity in the anterior and posterior cingulate cortices). In addition, Yuan et al. (2011) provide evidence that, in the long-term, Internet addiction results in structural brain abnormalities related to impaired cognitive control. Regarding reward and punishment processing, the study by Dong et al. (2011) reveals that Internet addicts demonstrate enhanced reward sensitivity in win trials (strong activation in orbitofrontal cortex), while their response to monetary loss is decreased (lower anterior cingulate activation). In turn, the study by Ko, Liu, Yen, Chen, Yen, and Chen (2013) shows that the desire to play online games not only involves the reward system in Internet gaming addicts, but also provokes higher motivation activation (anterior cingulate) in them, as well as stimulating memory (parahippocampus), executive function (dorsolateral prefrontal cortex),

14 and the visual system (precuneus). To sum up, this stream provides evidence that neurobiological processes play a crucial role in delivering a more complete picture of Internet gaming disorder or, more generally, Internet addiction. 5.3

Internet gambling associated with problem gambling

The third research stream includes articles which provide insight into Internet gambling and its association with problem gambling. Most studies in this stream use descriptive analyses of survey data, all of which produce similar results, finding that Internet gamblers compared to non-Internet gamblers are more likely to be relatively young male adults, who are well-educated, and professionally employed (e.g., Griffiths, Wardle, Orford, Sproston, & Erens, 2009; Wood & Williams, 2007). In addition, several articles in this stream investigate the potential link between Internet gambling and problem gambling (e.g., Griffiths & Barnes, 2008; Griffiths et al., 2009). Problem gambling is characterized by continued gambling despite negative consequences for the gamblers themselves and their environment (Petry & Weinstock, 2007; Wood & Williams, 2007). One of the largest online surveys at that time by Wood and Williams (2007) explored the nature of problem gambling and showed that of 1920 American, Canadian, and international Internet gamblers, recruited from typical online gambling sites, 42.7 percent could be classified as problem gamblers, and another 23.9 percent were at risk of becoming problem gamblers. Moreover, the survey revealed that the amount of time people spend gambling online is a strong predictor of problem gambling. Another empirical study by Griffiths and Barnes (2008) reported that changes in the structural and situational characteristics of Internet gambling, such as ease of access, convenience, 24-h availability, and a sense of anonymity, have a major influence on respondents’ Internet gambling behavior, and could therefore contribute to potential problem gambling. Also, McBride and Derevensky (2009) have claimed that the characteristics of the Internet pose risk factors for

15 gambling problems. Moreover, their survey of online gamblers demonstrates that problem gamblers are significantly more likely than non-problem gamblers to spend excessive amounts of time and money gambling, that they gamble alone, and they consume alcohol or drugs while gambling (McBride & Derevensky, 2009). In all, this research stream calls attention to the potential risk factors of problem gambling given the structural and situational characteristics of the Internet that facilitate gambling behavior. 5.4

Psychological characteristics

Publications assigned to the fourth research stream explore psychological characteristics of online game players or, more generally, of Internet users, to draw conclusions on their engagement or even addiction potential. Davis (2001) makes a theoretical contribution to this stream by introducing a cognitive-behavioral model of pathological Internet use, which emphasizes that cognition about the self and about the world is the main source of developing pathological Internet use. Caplan (2002) operationalized Davis’s (2001) theoretical construct and showed that loneliness is a significant predictor of negative effects associated with pathological Internet use. Morahan-Martin and Schumacher (2000) support this finding, specifying that men who feel lonely and are technologically sophisticated are at greater risk of developing Internet-related problems, such as academic, work, or interpersonal problems. Chak and Leung (2004), in turn, have identified shyness and locus of control as significant predictors. Specifically, they reveal that the higher the person’s level of shyness, the less confidence he or she has in own control, the firmer the belief in the power of others, and the greater the expectation of chance determining one’s life, the more likely it is that the user will be addicted to the Internet. Regarding psychological characteristics of online game players, Kim, Namkoong, Ku, and Kim (2008) have indicated that higher aggression and narcissistic personality traits, lower self-control (i.e., the ability to resist an impulse), and lower quality of interpersonal

16 relationships, predict the extent and severity of online game addiction. Using qualitative interviews, Wan and Chiou (2006) add that the individual’s desire to compensate for unfulfilled psychological needs, such as diversion from loneliness, finding satisfying interpersonal relationships, and need to achieve highly, play a crucial role in online game addiction. Overall, this research stream deepens the understanding that several psychological factors predispose certain users to become highly engaged in, or even addicted to, the Internet and online gaming. 5.5

Social interaction

The fifth research stream comprises articles which examine the influence of social interaction in large collaborative online games known as massively multiplayer online games (MMOGs). Steinkuehler and Williams (2006) introduce a theoretical framework of the social form and function of MMOGs. They suggest that MMOGs serve as a new digital third space for informal sociability similar to the traditional ones like pubs, cafes, or parks (Oldenburg, 1999). Hence, Steinkuehler and Williams (2006) conclude that MMOGs are particularly suited to form large relationship networks that are rich in information and resources, but weak in emotional support. Such kinds of relationships are known as bridging social capital (Putnam, 2000). Many ethnographic studies in this stream have built on Putnam’s (2000) work on social capital to analyze how MMOGs affect social interaction. Nardi and Harris (2006), for instance, discovered that relationships in World of Warcraft, the most popular MMOG in the USA, could take on various forms, from brief informal encounters to highly organized structured groups. Their results further suggest that the variety of collaborations enhanced players’ enjoyment and provided an important resource for learning. Williams, Ducheneaut, Xiong, Zhang, Yee, and Nickell (2006) found that the depth of relationships varied widely. More specifically, they revealed that many players got in touch with a wide range of people

17 (i.e., bridging social capital), while about one third maintained and even reinforced preexisting offline interactions (i.e., bonding social capital) through gameplay. The longitudinal study by Ducheneaut, Yee, Nickell, and Moore (2006), in turn, suggests that the extent of social activities is overestimated, as their finding was that many players, instead of actively playing and interacting with other people, relied on them as an audience in providing an entertaining spectacle, and as a source of information. Nevertheless, on the whole, articles in this stream agree that social interaction, even of varying strengths, constitute a major attraction in bringing consumers to online games. 5.6

Motivational factors

The sixth research stream covers publications which analyze motivational factors to better understand why consumers continue to play online games. Most of the articles in this stream assess causal relationships using structural equation modeling, and inter alia, they apply the theory of reasoned action (Fishbein & Ajzen, 1975) to explain human behavior, or the technology acceptance model (Davis, 1989) to predict user acceptance of information technology. Hsu and Lu (2007), who applied the theory of reasoned action and a modified technology acceptance model, show that perceived enjoyment (i.e., the extent to which online gaming is perceived as entertaining), social norms (i.e., the degree to which the user perceives that others approve of his or her game participation), and a positive attitude toward online gaming, had a significant impact on customer loyalty in online games. In addition, they report that perceived ease of use (i.e., the degree to which the user believes that playing online games is effortless) enhanced both perceived enjoyment and attitude. Wu and Liu (2007) adapted the theory of reasoned action and achieved similar results, revealing that of the abovementioned factors, enjoyment was the strongest predictor of intention to play. Further, they examined the role of trust in online game websites, which

18 affected attitude toward online gaming and thus, through attitude, had an indirect effect on intention to play. In another study, Wu, Wang, and Tsai (2010) showed that service mechanisms, such as quality of network connections, data privacy, and loyalty incentives, significantly affected the continuance motivation, which in turn, was crucial to players’ online game loyalty. Other important design features found to promote game enjoyment included suitable goals to be achieved during the game, adequate instruments to achieve these goals, feedback on the current score, places to communicate in the virtual world, and communication tools to exchange opinions (Choi & Kim, 2004). Overall, this stream reveals that enjoyment and sociability are key motivators for customer loyalty in online games, and should, therefore, be reflected in the game design.

6.

Results of social network analysis

Based on social network analysis, Fig. 2 reveals patterns and linkages of the various streams within the online gambling and gaming research network. The lines indicate cocitations, while the nodes represent the cited publications. The size of the nodes depends on the number of citations an article received, where a larger node indicates that a publication is more frequently cited and thus more influential. Fig. 2 here Fig. 2 shows that the network structure largely corresponds to the extracted research streams outlined in section 5. In addition, the network consists of two sub-networks that are highly internally connected and only loosely connected across the two sub-networks. The network to the right includes only publications of the stream on Internet gambling associated with problem gambling. The network to the left, in contrast, covers articles from all other streams. This visual subdivision is in line with previous findings, reporting that research on

19 gambling has historically been addressed separately to research on gaming (Gainsbury et al., 2014; Parke et al., 2013). A central hub of the entire network is the DSM-5 of the American Psychiatric Association (APA, 2013), which is assigned to the stream on the assessment of Internet gaming disorder and connects the two sub-networks, as well as the individual discourses, with each other. By providing the main classification system for diagnosing mental disorders, this manual has become centrally important in the entire field. While the previous DSM-IV covered only pathological gambling (APA, 1994), the DSM-5 now lists Internet gaming disorder as a condition that requires additional research (APA, 2013). This first listing contributes considerably to unifying definitions and diagnostic criteria, to which the other streams can refer and on which they can build, when addressing research questions in their area of interest. Yee (2006) is a study of far-reaching impact on the field, which goes beyond its own stream of social interaction. By introducing an empirical model of player motivations in online games, Yee (2006) shows that social factors are essential motivations for playing. Further, his study reveals that players’ psychological characteristics in relation to their motivations can be used to predict the individual’s susceptibility to problematic use of online games. Thereby he brings knowledge together from the streams on social interaction, motivational factors, psychological characteristics, and Internet gaming disorder. 6.1

Network density and knowledge exchange

To assess the connectedness of the network, Table 4 presents the density values within and between the research streams. The density values confirm the division into two sub-networks, as depicted in Fig. 2. More specifically, the density values show that the articles in the network to the right (i.e., the stream on Internet gambling associated with problem gambling) are completely connected to each other (density value = 1), but only loosely connected to

20 articles in the other streams of the network, given to the left (density values ≤ .29). Despite the subdivision, the high density value of the entire network (density value = .61) reveals that the research field of online gambling and gaming as a whole is largely connected, and maintains an intensive exchange of information. The stream on the assessment of Internet gaming disorder plays an essential role in the connectedness of the network, as it provides theoretical frameworks and measurement methods, which form a basis for further research. This stream’s central position in the network and its high density values, especially regarding the discourses on psychological characteristics (density value = .92) and neurobiological processes (density value = .79), confirm its huge influence. A great flow of information takes place here, as insights from neurobiological processes, for instance, help researchers to better classify and understand the disorder with regard to a player’s nervous system. Findings on psychological characteristics of players, in turn, can be used to draw conclusions about the individual vulnerability to this disorder. In view of the addressed topics, these three streams on the assessment of Internet gaming disorder, psychological characteristics, and neurobiological processes are subsumed under the challenges of online gambling and gaming. Other intensive knowledge exchanges and high density values are evidenced between the streams on psychological characteristics, social interaction, and motivational factors (density values ≥ .76). Due to their thematic proximity to the determinants of play, although studied from different angles, these discourses appear close to each other in the network and show many linkages, which indicate intensive sharing of ideas. Following the key themes addressed, these three streams are subsumed under the opportunities to promote play, that will open up to the online gambling and gaming field in the future. Note that the stream on psychological characteristics has an important dual role, because its findings can be used to better understand individuals’ pathological dependence, as well as non-pathological high

21 engagement in playing online games. Apart from that, the streams identified as covering challenges and opportunities exchange knowledge to a lesser extent. Especially, the stream on neurobiological processes shares little information with the discourses on motivational factors (density value = .24) and social interaction (density value = .35), which becomes visible in the positioning on opposite sides of the network. Overall, there is great potential for future research in areas where little knowledge exchange has taken place so far. This is indicated by spatial distance in the network and low density values. Particularly, this is the case for the stream on Internet gambling associated with problem gambling, as well as partly being the case for the discourse on neurobiological processes. Both streams are likely to reveal new insights by sharing more ideas, theories, and methods with the other streams, which will contribute to the future development of the entire field. Table 4 here 6.2

Temporal evolution

Fig. 3 provides a dynamic perspective on the different research streams’ prevalence over time. A particular stream’s prevalence is measured by the number of citations it received in the 1876 citing articles divided by the total number of citations all streams received in a given time. This reveals the extent to which the 1876 articles refer to ideas or methods used in the six research streams within the timeframe 2000 to 2017. Fig. 3 here In the first period, from 2000 to 2002, the research field was largely driven by the stream on Internet gambling associated with problem gambling, because the then current DSM-IV (APA, 1994) and the DSM-IV-TR (APA, 2000) only contained diagnostic criteria for pathological gambling, but not for Internet gaming disorder. Since this stream primarily used descriptive analyses of survey data to investigate the potential link between Internet gambling

22 and problem gambling, this approach’s prevalence declined after the online gambling and gaming community applied additional research methods. In the second period, from 2003 to 2005, research on neurobiological processes dominated the field and thus replaced the most prevalent discourse on Internet gambling associated with problem gambling. Neuro-imaging techniques for recording brain structure and activity, such as fMRI and EEG, enabled scholars and practitioners to gain a more nuanced understanding of why people become addicted to the Internet or online games. At the same time, the streams on psychological characteristics and social interaction gained relevance. Often building on Putnam’s (2000) work on social capital, ethnographic studies provided valuable insights into the role of social interaction in attracting consumers to online games. Thus, the latter led the field from 2006 to 2014. Since 2015, online gambling and gaming research has fundamentally changed from focusing on the opportunities to promote play (e.g., through social interaction) to increased awareness of the challenges of addiction. As the latest DSM-5 (APA, 2013) lists Internet gaming disorder as a condition requiring further research for the first time, the assessment of Internet gaming disorder has become the most popular stream. This change reflects the community’s prevailing interest in uniform diagnostic criteria for recognition of Internet gaming disorder as an independent clinical entity. Overall, the temporal evolution reveals that research on the challenges of addiction currently prevails over research on the opportunities to promote online gambling and gaming. Further, neuro-imaging techniques, such as fMRI and EEG, have become more important than descriptive analyses of traditional survey data. Thus, there is considerable potential for future research to produce new findings, specifically by taking further methods which to date have only been applied in the stream on neurobiological processes. Likewise, the hitherto exclusive use of structural equation modeling in the stream on motivational factors, could be

23 extended to the other streams in order to better understand, for example, the antecedents and outcomes of increasingly converging online gambling and gaming activities.

7.

Discussion

The widespread use of the Internet on multiple devices and the associated convergence of online gambling and gaming activities have increased the need for a systematic literature review that no longer analyzes these two topics as independent phenomena. In addition, the common characteristics and similar motivations to play make a joint consideration of the two activities inevitable. Therefore, the purpose of this study was to provide a holistic synthesis of online gambling and gaming research, using a bibliometric analysis of 84 169 cited references taken from 1876 citing articles. The study’s findings point to substantial benefits for researchers and managers. Regarding research question (1), the results of citation analysis provide straightforward information on the most cited journals and publications. Specifically, the journals Cyberpsychology, Behavior, and Social Networking and Computers in Human Behavior make a significant contribution, revealing that online gambling and gaming studies have their roots at the interface between human and computer-based activities, i.e., in psychology and computer science. In addition, related disciplines, such as psychiatry and mental health, marketing, and neurology, conduct research on online gambling and gaming, confirming the multidisciplinary background of the field. The Diagnostic and Statistical Manual of Mental Disorders (DSM-5) of the American Psychiatric Association (APA, 2013) represents a milestone in the literature. By providing essential definitions and diagnoses for mental disorders, including gambling disorder and, for the first time, Internet gaming disorder as a

24 condition for further research, in a very short time the DSM-5 has become the most cited work in online gambling and gaming research. Addressing research question (2), the results of factor analysis provide comprehensible access to the six main research streams of online gambling and gaming literature. Each stream investigates specific topics within this research area, and each is supported by a large number of researchers. The prevailing themes of the streams this study has identified, are the assessment of Internet gaming disorder, neurobiological processes of Internet addicts, Internet gambling and its association with problem gambling, psychological characteristics of highly engaged or even addicted online game players and Internet users, social interaction in massively multiplayer online games, and motivational factors in online games. In addition, each stream uses specific theories (e.g., Griffiths’ (2005) model of addiction, Putnam’s (2000) concept of social capital) and specific methodologies (e.g., neuro-imaging techniques, structural equation modeling), thereby confirming the multidisciplinary origin of online gambling and gaming research. Concerning research question (3), social network analysis visualizes linkages of the various research streams within the online gambling and gaming network. In line with previous findings (Gainsbury et al., 2014; Parke et al., 2013), the visualization confirms that scholars have discussed online gambling and gaming topics in largely unconnected networks (see Fig. 2), which indicates considerable potential for future research, especially on gambling. Regarding research question (4), the dynamic perspective on the various streams’ prevalence over time shows that online gambling and gaming research has undergone substantial changes. Specifically, the focus has shifted from the opportunities to promote play to an increasing recognition of the challenges of Internet addiction and Internet gaming disorder. Finally, addressing research questions (5), future research could generate new

25 insights by borrowing proven methodologies, such as neuro-imaging techniques or structural equation modeling, which to date have only been applied in specific streams. In conclusion, this study makes an important contribution to online gambling and gaming literature, as it identifies the most cited journals and publications, characterizes the main research streams with their prevailing topics, visualizes their connectedness, and analyzes their temporal evolution. This synthesis of existing literature is, therefore, of high interest for both researchers and managers, enabling them to access the currently fragmented knowledge more easily. 7.1

Limitations

The main drawback of co-citation analyses is the impossibility of fully collecting and displaying the entire existing literature. In the case of this study, the scope of the included publications was limited in accordance with standard bibliometric criteria (e.g., Culnan, 1986; McCain, 1990). Even so, by following best practices and examining different citation thresholds without observing significant changes in the extracted research streams and network structure, the author is confident to have captured a representative sample of online gambling and gaming research. An additional limitation arises from the cited references themselves. Based solely on the bibliography, it is not possible to differentiate between negative or affirmative citations, nor to identify self-citations. However, several researchers (e.g., Cano, 1989; Chubin & Moitra, 1975; Spiegel-Rösing, 1977) who checked for this, found a very low incidence of negative citations. Self-citations are indeed frequently used, but an author would have to publish a very large number of articles to have a real impact, i.e., one that would change citation frequencies (Garfield, 1979). Thus, there is no need for cleaning by type of citation (Glänzel & Thijs, 2004). However, citations can increase over time, which could possibly favor articles from earlier stages (Ramos-Rodríguez & Ruíz-Navarro, 2004), and therefore

26 represent only a dynamic snapshot, depending on when the analysis was performed (Vogel & Güttel, 2013). To take this into account, this study suggests directions for future research in section 7.2, which includes attention to more recent articles. Another weakness inherent to the Social Sciences Citation Index, although it is one of the most frequently used data sources for bibliometric analyses, is that the cited references list only the first authors instead of all authors. Thus, the citation rate does not reflect contributions of the second or further authors, which could affect citations accuracy regarding some authors (Garfield, 1979). To account for this, this study used publications as the unit of analysis and the omitted authors were added to yield more accurate results. 7.2

Directions for future research

The findings suggest that there are several white spots in the online gambling and gaming research landscape, which could be explored in future research. For example, assessing Internet gaming disorder is an increasingly important topic. Currently, the latest DSM-5 lists Internet gaming disorder as a condition requiring further research (APA, 2013), while the 11th revision of the International Classification of Diseases, which will be applicable as from 1 January 2022, now includes gaming disorder (World Health Organization, 2019). However, further research is required to clarify the extent to which players’ psychological characteristics, structural game characteristics, and motives for playing are the causes or the consequences of (Internet) gaming disorder (Király, Griffiths, & Demetrovics, 2015; Wartberg, Kriston, Zieglmeier, Lincoln, & Kammerl, 2019). In addition, clinical studies and clinical validation of the various measurement instruments are needed to better distinguish between subgroups from non-pathological highly engaged to truly addicted players, and to develop specific treatments (Billieux, Thorens, Khazaal, Zullino, Achab, & Van der Linden, 2015; Király et al., 2015; Pontes et al., 2014).

27 Limitations of previous neurobiological studies include the fact that the majority focused on Internet addiction more generally (Fauth-Bühler & Mann, 2017). Thus, additional research should specifically address the neurobiological basis of Internet gaming disorder to bring a conclusion to the ongoing debates and reach consensus on its diagnostic criteria and its conceptualization (Griffiths et al., 2016; Király et al., 2015; Kuss, Pontes, & Griffiths, 2018). Further, neuro-imaging techniques, such as fMRI and EEG, could be applied to the different streams on motivational factors and social interaction, to better understand the heterogeneous target groups and their motivations for playing online games. Building on this, game designers could more effectively translate these different needs into specific design features, improving the player experience without reinforcing dependence even further in the future. The discourse on Internet gambling associated with problem gambling shows that through intensive information exchange within the discourse itself, the target group of Internet gambling activities is well understood. However, there is still a great deal of research potential due to limited sharing of knowledge and methods with other streams. For instance, future research could apply structural equation modeling and longitudinal cohort studies to identify causal relationships and determine relative strength of the connection between different risk factors and the development of problem gambling (Abbott & Clarke, 2007; Volberg, McNamara, & Carris, 2018). Another fruitful avenue to explore might be the increased use of neuro-imaging techniques to further investigate the similarities and differences between pathological gambling, Internet gaming, and other mental disorders. The aim would be to improve patient classification and develop specific treatment strategies (Fauth-Bühler & Mann, 2017; Van Timmeren, Daams, Van Holst, & Goudriaan, 2018). Deeper insight into the psychological characteristics and motivations of gamblers could contribute to a better prediction of gambling propensity (Mowen, Fang, & Scott, 2009). Such findings could, in turn, be used to prevent or counteract any developments of problem

28 gambling at an early stage. In addition, questions regarding whether and how users distinguish between online gambling and gaming products become particularly interesting given their increasing convergence. Future research could extend first results that suggest consumers have difficulties in distinguishing between these activities (Albarrán Torres & Goggin, 2014; Teichert, Gainsbury, & Mühlbach, 2017), to identify product risk potential that would require regulation and other kinds of provision (Gainsbury et al., 2014; Parke et al., 2013). Furthermore, issues of socialization have been widely neglected in online gambling research (Parke et al., 2013). New projects could verify whether insights concerning patterns of grouping and formation of social capital (Putnam, 2000), that have been intensively investigated in online gaming literature, could be transferred to gambling research. These aspects will gain relevance in view of the increasing spread of social gambling activities, which opens new possibilities for leisure and socialization in gambling (Albarrán Torres & Goggin, 2014). Future research needs to assess whether these new kinds of interaction in social gambling attract a new type of gambler, influence the migration from gaming to gambling, and contribute to the development of disordered gambling and Internet gaming disorder (Kim, Wohl, Salmon, Gupta, & Derevensky, 2015; Parke et al., 2013; Wohl et al., 2017). In this context, research should also evaluate how advertisement of online gambling sites on social media impacts future gambling behavior. New studies should assess whether and which public policy measures are needed to increase consumer protection (Kim, Wohl, Gupta, & Derevensky, 2016; Terlutter & Capella, 2013).

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41

Fig. 1. Time distribution of citation numbers. 6000 5500 5000

4000 3500 3000 2500 2000 1500 1000 500

Year cited

(1.5-column fitting image)

2017

2015

2013

2011

2009

2007

2005

2003

2001

1999

1997

1995

1993

1991

1989

1987

1985

1983

1981

1979

1977

1975

1973

1971

1969

1967

0 1965

Number of citations

4500

42 Fig. 2. Research network of online gambling and gaming.

Note: For better graphical representation, only the first author is listed (tie strength > 9).

(1.5-column fitting image)

43 Fig. 3. Temporal evolution of research streams. 100%

Streams' prevalence (in percent of citation counts)

90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 2000-2002

2003-2005

2006-2008

Assessment of Internet gaming disorder Neurobiological processes Internet gambling associated with problem gambling

2009-2011

2012-2014

Psychological characteristics Social interaction Motivational factors

(1.5-column fitting image)

2015-2017

44 Table 1 Most cited journals in online gambling and gaming research (sorted by TC). R

Journal

Journal Abbreviation

TC

TP

TC/TP

1

Cyberpsychology, Behavior, and Social Networking

CYBERPSYCH BEH SOC N

4255

531

8.01

2

Computers in Human Behavior

COMPUT HUM BEHAV

2459

609

4.04

3

Journal of Gambling Studies

J GAMBL STUD

1265

442

2.86

4

Addiction

ADDICTION

958

221

4.33

5

International Journal of Mental Health and Addiction

INT J MENT HEALTH AD

865

146

5.92

6

Journal of Personality and Social Psychology

J PERS SOC PSYCHOL

634

345

1.84

7

PloS ONE

PLOS ONE

565

193

2.93

8

Games and Culture

GAMES CULT

484

115

4.21

9

International Gambling Studies

INT GAMBL STUD

442

118

3.75

10 Addictive Behaviors

ADDICT BEHAV

400

154

2.60

11 Computers & Education

COMPUT EDUC

398

188

2.12

12 MIS Quarterly

MIS QUART

391

125

3.13

13 Journal of Consumer Research

J CONSUM RES

386

204

1.89

14 Psychological Bulletin

PSYCHOL BULL

379

156

2.43

15 Journal of Psychiatric Research

J PSYCHIAT RES

375

47

7.98

16 Journal of Computer-Mediated Communication

J COMP-MEDIAT COMM

374

77

4.86

17 American Journal of Psychiatry

AM J PSYCHIAT

356

113

3.15

18 Psychology of Addictive Behaviors

PSYCHOL ADDICT BEHAV

355

87

4.08

19 NeuroImage

NEUROIMAGE

350

211

1.66

20 Journal of Behavioral Addictions

J BEHAV ADDICT

338

107

3.16

Note: R = Rank; TC = Total number of citations; TP = Total number of publications; TC/TP = Average citations per article.

45 Table 2 Most cited publications in online gambling and gaming research (sorted by TC). R

Title

1

Journal / Book

TC

TC/t

Diagnostic and statistical manual of mental American Psychiatric 2013 disorders (DSM-5) Association (APA)

FIFTH EDITION

273

54.60

2

Motivations for play in online games

2006

CYBERPSYCH BEH 226 SOC N

18.83

3

Internet addiction: The emergence of a new Young clinical disorder

1998

CYBERPSYCH BEH 172 SOC N

8.60

4

The demographics, motivations, and derived Yee experiences of users of massively multi-user online graphical environments Social interactions in massively multiplayer Cole and Griffiths online role-playing gamers

2006

PRESENCE

138

11.50

2007

CYBERPSYCH BEH 120 SOC N

10.91

HUM 112

10.18

5

Author/s

Yee

Year

6

Distinguishing addiction and high engagement in Charlton and the context of online game playing Danforth

2007

COMPUT BEHAV

7

An international consensus for assessing Internet Petry et al. gaming disorder using the new DSM 5 approach

2014

ADDICTION

103

25.75

8

Pathological video game use among youths: A Gentile et al. two-year longitudinal study

2011

PEDIATRICS

102

14.57

9

Addiction to the Internet and online gaming

2005

CYBERPSYCH BEH SOC N

99

7.62

2008

J COMP-MEDIAT COMM

96

9.60

Ng and Wiemer-Hastings

10 Who plays, how much, and why? Debunking the Williams et al. stereotypical gamer profile

Note: R = Rank; TC = Total number of citations; TC/t = Average citations per year up until 2017.

46 Table 3 Most representative publications of each research stream (sorted by FL). Assessment of Internet gaming disorder Variance explained: 19 percent TP: 37

Neurobiological processes

Internet gambling associated with problem gambling Variance explained: 14 percent TP: 26

Variance explained: 16 percent TP: 32

Publication

FL

Publication

FL Publication

FL

King et al., 2013, CLIN PSYCHOL REV

.92

Dong et al., 2012, PSYCHIAT RES-NEUROIM

.89 Wood and Williams, 2007, NEW MEDIA SOC

.94

Griffiths et al., 2014, .90 NEUROPSYCHIATRY-LOND

Ko et al., 2012, EUR PSYCHIAT

.89 Petry and Weinstock, 2007, AM J ADDICTION

.93

Pontes et al., 2014, PLOS ONE

.89

Ko et al., 2013, ADDICT BIOL

.88 Wood and Williams, 2009, INTERNET GAMBLING

.93

Mentzoni et al., 2011, CYBERPSYCH BEH SOC N

.88

Zhou et al., 2011, EUR J RADIOL

.86 McBride and Derevensky, 2009, INT J MENT HEALTH AD

.93

Lemmens et al., 2015, PSYCHOL ASSESSMENT

.88

Dong et al., 2010, NEUROSCI LETT

.86 Wardle et al., 2007, NATCEN

.92

Festl et al., 2013, ADDICTION

.87

Patton et al., 1995, J CLIN PSYCHOL

.86 Griffiths and Barnes, 2008, INT J MENT HEALTH AD

.91

Ferguson et al., 2011, J PSYCHIAT RES

.87

Beard and Wolf, 2001, CYBERPSYCHOL BEHAV

.85 Wood et al., 2007, CYBERPSYCHOL BEHAV

.91

Gentile, 2009, PSYCHOL SCI

.86

Dong et al., 2011, J PSYCHIAT RES

.84 Wardle et al., 2011, INT GAMBL STUD

.91

Griffiths, 2005, J SUBST USE

.86

Yuan et al., 2011, PLOS ONE

.84 Griffiths et al., 2009, CYBERPSYCHOL BEHAV

.91

Demetrovics et al., 2012, PLOS ONE

.85

Grant et al., 2010, AM J DRUG ALCOHOL AB

.83 Ladd and Petry, 2002, PSYCHOL ADDICT BEHAV

.90

Psychological characteristics

Social interaction

Motivational factors

Variance explained: 14 percent TP: 25

Variance explained: 12 percent TP: 22

Variance explained: 4 percent TP: 8

Publication

FL Publication

FL Publication

FL

Caplan, 2002, COMPUT HUM BEHAV

.80 Steinkuehler and Williams, 2006, J COMP-MEDIAT COMM

.91 Hsu and Lu, 2007, COMPUT HUM BEHAV

.89

Wan and Chiou, 2006a, CYBERPSYCHOL BEHAV

.78 Nardi and Harris, 2006, CSCW’06

.88 Wu and Liu, 2007, J ELECTRON COMMER RE

.89

Chak and Leung, 2004, CYBERPSYCHOL BEHAV

.76 Williams et al., 2006, GAMES CULT

.88 Davis, 1989, MIS QUART

.85

Morahan-Martin and Schumacher, 2000, COMPUT HUM BEHAV

.75 Ducheneaut et al., 2006, CHI’06

.88 Wu et al., 2010, COMPUT HUM BEHAV

.82

Ng and Wiemer-Hastings, 2005, CYBERPSYCHOL BEHAV

.74 Putnam, 2000, BOWLING ALONE

.85 Choi and Kim, 2004, CYBERPSYCHOL BEHAV

.78

Kim et al., 2008, EUR PSYCHIAT

.73 Taylor, 2006, PLAY BETWEEN WORLDS

.84 Chou and Ting, 2003, CYBERPSYCHOL BEHAV

.59

Wan and Chiou, 2006b, CYBERPSYCHOL BEHAV

.70 Castronova, 2005, SYNETHTIC WORLDS

.84 Ryan et al., 2006, MOTIV EMOTION

.52

Young, 1998, CAUGHT IN THE NET

.69 Williams, 2006, J COMP-MEDIAT COMM

.82 Przybylski et al., 2010, REV GEN PSYCHOL

.46

Davis, 2001, COMPUT HUM BEHAV

.69 Williams et al., 2008, J COMP-MEDIAT COMM

.80 (only eight publications allocated to this research stream)

Griffiths et al., 2004, J ADOLESCENCE

.68 Turkle, 1995, LIFE ON THE SCREEN

.80

Note: FL= Factor loading; TP = Total number of publications.

47 Table 4 Density values within and between research streams. Research stream

1

2

3

4

5

Assessment of Internet gaming disorder

1

.98

Neurobiological processes

2

.79

.97

Internet gambling associated with problem gambling

3

.29

.22

1

Psychological characteristics

4

.92

.72

.26

.99

Social interaction

5

.62

.35

.19

.85

.95

Motivational factors

6

.50

.24

.17

.76

.81

Entire research network

6

1 .61

Highlights •

The paper provides a holistic synthesis of online gambling and gaming research.

•

Online gambling and gaming literature consists of six main research streams.

•

Social network analysis visually represents a division into two sub-networks.

•

The community has increasingly focused on the challenges of addictive behavior.

•

A discussion of the findings reveals important potential future research avenues.

Author Contribution Statement

Julia M. Stehmann: Conceptualization; Methodology; Software; Validation; Formal analysis; Investigation; Resources; Data curation; Writing - original draft; Writing - review & editing; Visualization; Supervision; Project administration.