Article

Explaining User Experience in Mobile Gaming Applications: An fsQCA Approach

Abstract and Figures

Purpose: In the complex ecosystem of mobile applications multiple factors have been used to explain users' behavior, without though focusing on how different combinations of variables may affect user behavior. We show how price value, game content quality, positive and negative emotions, gender, and gameplay time interact with each other to predict high intention to download mobile games. Design/methodology/approach: Building on complexity theory we present a conceptual model followed by research propositions. Our propositions are empirically validated through configurational analysis, employing fuzzy-set qualitative comparative analysis (fsQCA) on 531 active users of mobile games. Findings: Findings identify ten solutions that explain high intention to download mobile games. Alternative paths are identified depending on the gender and the time users spend playing mobiles games. We highlight the role of price value and game content quality, as well as that of positive emotions which are always core factors when present. Originality/value: To identify complex interactions among the variables of interest, fsQCA is employed, differentiating from traditional studies using variance-based methods, leading to multiple solutions explaining the same outcome. None of the variables explains intention to download on its own, but only when they combine with each other. We (1) extend existing knowledge on how price value, game content quality, emotions, gender, and gameplay time combine to lead to high intention to download mobile games, and (2) present a methodology for how to bridge complexity theory with fsQCA, improving our understanding of intention to adopt mobile applications.
Content may be subject to copyright.
Internet Research, (2019), (online first)
https://www.emeraldinsight.com/doi/full/10.1108/IntR-12-2017-0479
* Corresponding author:
Ilias O. Pappas can be contacted at: ilpappas@ntnu.no; ilias.pappas@uia.no 1
Internet Research
DOI: 10.1108/IntR-12-2017-0479
Explaining User Experience in Mobile Gaming
Applications: An fsQCA Approach
Ilias O. Pappas*
Department of Computer Science,
Norwegian University of Science and Technology, Trondheim, Norway and Department of Information
Systems, University of Agder, Kristiansand, Norway
Patrick Mikalef and Michail N. Giannakos
Department of Computer Science,
Norwegian University of Science and Technology, Trondheim, Norway, and
Panos E. Kourouthanassis
Department of Informatics, Ionian University, Corfu, Greece
Abstract
Purpose
In the complex ecosystem of mobile applications multiple factors have been used to explain users’ behavior, without
though focusing on how different combinations of variables may affect user behavior. We show how price value,
game content quality, positive and negative emotions, gender, and gameplay time interact with each other to predict
high intention to download mobile games.
Design/methodology/approach
Building on complexity theory we present a conceptual model followed by research propositions. Our propositions
are empirically validated through configurational analysis, employing fuzzy-set qualitative comparative analysis
(fsQCA) on 531 active users of mobile games.
Findings
Findings identify ten solutions that explain high intention to download mobile games. Alternative paths are identified
depending on the gender and the time users spend playing mobiles games. We highlight the role of price value and
game content quality, as well as that of positive emotions which are always core factors when present.
Originality/value
To identify complex interactions among the variables of interest, fsQCA is employed, differentiating from traditional
studies using variance-based methods, leading to multiple solutions explaining the same outcome. None of the
variables explains intention to download on its own, but only when they combine with each other. We (1) extend
existing knowledge on how price value, game content quality, emotions, gender, and gameplay time combine to lead
to high intention to download mobile games, and (2) present a methodology for how to bridge complexity theory with
fsQCA, improving our understanding of intention to adopt mobile applications.
Keywords (Required)
Content quality, experience, emotions, fsQCA, gender, price value
Pappas et al., 2019 / User experience in mobile gaming applications
Internet Research
DOI: 10.1108/IntR-12-2017-0479
Introduction
Electronic games are constantly evolving and they provide a big diversity regarding their content, their pricing
strategies, and platform availability, all critical factors in influencing users’ future behavior (Seo et al., 2015).
Furthermore, mobile applications have greatly improved the past ten years, and the majority of consumption is
performed through mobile applications, with application usage making up for 52% of the total digital media
engagement (Lella and Lipsman, 2014). Users’ download patterns become dynamic as they gain experience and
develop different needs (Son, 2017) Video game industry, including mobile games (e.g., smartphone, tablet) has
grown considerably in revenues leading to increased value creation for both the industry and the gamers (Marchand
and Hennig-Thurau, 2013). In 2016, 19.2B downloads were made on Apple’s “App Store” and Google’s “Google
Play” (SensorTower, 2017a). Also, in 2016 iPhone users spent on average $40 per device on premium applications,
more than they did in 2015, with mobile games dominating consumer spending (SensorTower, 2017b). It is thus
critical to understand how to better design mobile games to satisfy the targeted users and increase value creation.
Extant research investigates how companies may offer increased value to consumers to gain a competitive advantage,
as well as what factors can predict adoption of online and mobile games (Chang et al., 2013; Davis and Lang, 2012;
Wei and Lu, 2014). Seminal work on marketing and IS disciplines consider perceived value to be a prominent
determinant in forming processes of behavior toward pay-per-use services (Sweeney and Soutar, 2001; Zeithaml,
1988). With the main goal being to understand why consumers buy what they buy and how they make their choices,
the Theory of Consumption Values (TCV) suggests that consumers attach different values to products and that these
values influence their motivations to choose or purchase a product (Sheth et al., 1991). TCV has been extended to
better capture consumers’ value perceptions with previous studies showing that not all dimensions are equally
important and, although they are interrelated, a change in one does not necessarily lead to a similar change to another
dimension (Sheth et al., 1991; Turel et al., 2010). Indeed, as relations among variables are more complex, this suggests
that they are more likely to be of asymmetrical form (Pappas, 2018; Pappas, Giannakos and Sampson, 2017;
Woodside, 2014, 2017). Since most studies in the area assume symmetric relations between value dimensions and
their variables (Park and Lee, 2011; Turel et al., 2010), it is likely that the current approaches or methods are not able
to fully capture this complexity of perceived value. Methodology defines how we study a phenomenon, how we view
it, and how we think about it (Bagozzi, 2007), thus it is essential especially when we want to get a deeper understanding
of real-life phenomena.
Value comprises of price value, quality value, emotional value, and social value (Sweeney and Soutar, 2001), with all
dimensions of value being important in predicting users’ behavior depending on the context. To improve our
understanding of how value perceptions relate with behavior in a complex and ever evolving environment such as the
one of mobile gaming, further work is needed (Rezaei and Ghodsi, 2014; Zhou, 2013). In the context of mobile
applications and games, perceived value, content quality, emotions, and various demographics are important
antecedents of users’ intention to download or use mobile applications and games (Hsiao and Chen, 2016; Su et al.,
2016; Zhou, 2013). Previous studies show that price value is a main antecedent of users’ intention to pay for extra
content while playing, however it doesn’t influence users’ mobile game loyalty (Hsiao and Chen, 2016), which in
general is expected to influence behavioral intentions. Also, in online gaming price value and quality may affect
positively users’ intention to repurchase online games (Rezaei and Ghodsi, 2014). Mobile games adoption is likely to
increase if they are more fun (Liang and Yeh, 2011), especially for casual gamers than hardcore ones (Neys et al.,
2014), as users will enjoy creative storylines (Ha et al., 2007). Also, although in mobile application adoptions male
and female users may have different motivations (Liu and Guo, 2017), in the context of mobile entertainment no
gender differences were found (Leong et al., 2013). Therefore, since these factors are critical for increasing users’
behavior, they should be studied together to assess their effects on users’ intention to download mobile games.
Multiple ways exist in which the aforementioned factors interact with each other, however more work is needed to
understand how such interplays may offer a deeper understanding on adoption of mobile applications, and how they
may lead to high intention to download mobile games. The majority of the studies in the area focus on main effects
among the various antecedents and employs symmetric tests, [e.g., structural equation modelling (SEM) and multiple
regression analysis (MRA)] to measure their effect on users’ behavior. Regression based models (RBMs) build on
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DOI: 10.1108/IntR-12-2017-0479
variance theories, which suggest that a predictor variable needs to be both necessary and sufficient condition to achieve
the desired outcome. Indeed, focusing on symmetric and net effects may be misleading, since such effects do not apply
to all cases in the dataset, thus the relationship between two variables is rather unlikely to be of symmetrical form
(Ragin, 2008; Woodside, 2014). For instance, the presence of price value may be sufficient in explaining high intention
to download, while if it is absent, intentions may still be high, suggesting that price value is not a necessary condition,
hence, more work is needed towards this direction to complement previous studies. To address the gap in the literature,
we are based on complexity theory and configuration theory to identify the different causal patterns of factors
influencing intention to download mobile games. These theories build on the principle of equifinality, which suggests
that multiple complex configurations of the same conditions can explain the same outcome (Woodside, 2014), and on
causal asymmetry, which suggests that the causes explaining the presence of an outcome, are likely to be different
from those explaining the absence of the same outcome (Ragin, 2008). Thus, the following research question is
framed:
RQ: What conditions of price value, game content quality, positive and negative emotions, gender, and gameplay time
are sufficient or necessary to create causal combinations that explain high intention to download mobile games?
To answer our research question, we employ configurational analysis using fuzzy-set qualitative comparative analysis
(fsQCA) (Ragin, 2008). FsQCA provides multiple solutions that can explain an outcome, thus showing how intention
to download mobiles games is explained by its antecedents. When fsQCA is employed with complexity and
configuration theories can lead to improved theory building (Fiss, 2011; Woodside, 2014), as it can identify the
complex relations among variables. The findings offer multiple, distinct, and equally effective combinations of price
value, game content quality, emotions, gender, and gameplay time, which explain high intention to download mobile
games. The findings show that none of the factors is either necessary or sufficient in explaining intention to download
mobile games on its own, instead it is their combinations that can lead to high intentions.
The contribution of this paper in the literature is twofold. First, we extend the literature by exploring how different
types of gamers choose mobile games, through the lens of price value, game content quality, and emotions, as we
examine their combined effects on intention to download mobile games. Second, we employ fsQCA, an innovative
methodology for data analysis, which offers a deeper insight on the data, and should be considered as an alternative
and complementary method to traditional variance-based approaches. Identifying the interplay among the
aforementioned constructs should help managers and practitioners to specify detailed patterns of factors that stimulate
gamers’ behavioral intentions and help them create and offer better targeted mobile games with increased quality and
value.
The paper is organized as follows. In Section 2, the theoretical background on price value, game content quality, and
emotions is presented, along with discussion on the conceptual model and research propositions. Section 3 describes
the research methodology and provides details on fsQCA and how it is implemented. Section 4 presents the empirical
results from the configurational analysis with fsQCA. Finally, Section 5 discusses the findings highlighting theoretical,
methodological, and practical implications, along with limitations and avenues for future research.
Background and research propositions
Perceived Value
The concept of perceived value in consumer research has been largely examined in economic, strategic and marketing
literature, is defined as “the consumer’s total assessment and evaluation of the total utility of a product which is based
on perceptions of what is received and what is given” (Zeithaml, 1988). Based on this value, consumers are expected
to make a choice. The question of why we buy what we buy is a critical one in consumer behavior and marketing
literature (Sheth et al., 1991). Why users play online games is a critical question and identifying gamers’ motivation
is important to be understood as online and mobile evolve over time (Demetrovics et al., 2011). The Theory of
Consumption Values (TCV) suggests that consumers attach different values to products and that these values can
influence their motivations to choose or purchase the specific products (Sheth et al., 1991). TCV draws from multiple
consumer behavior models and suggests that consumer choice is based on multiple consumption values. Consumption
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DOI: 10.1108/IntR-12-2017-0479
value perceptions include multiple dimensions of consumer utilities, like emotional value, price value, and quality
(Sheth et al., 1991; Turel et al., 2010). TCV suggests that the dimensions are independent from one another and the
existence of one influences the other, but a change in one dimension will not result to a change of a similar level to
another dimension (Sheth et al., 1991). This indicates that the relation among dimensions is asymmetrical and that the
typical variance-based approaches may not be able to fully capture their complexity.
The importance of the different dimensions of consumer value perceptions can change as it depends on the context.
In the context of hedonic digital artefacts emotional values may be more important than functional values, while in an
organizational context functional values may be more important (Turel et al., 2010). Consumers’ perceived value is
a multidimensional construct composing of price value, quality value, emotional value, and social value (Sweeney
and Soutar, 2001). However, previous findings in the context of hedonic technologies show that social value has no
effect on users’ overall perceived value (Turel et al., 2010). Mobile games are considered as hedonic technologies
since users choose to download or pay for them mainly because they enjoy it. Similarly, users’ may not be influenced
from the social aspect of value when examining in-app purchase intentions in mobile games (Hsiao and Chen, 2016)
or purchase intention in online games (Rezaei and Ghodsi, 2014). Furthermore, a modified theory of consumption
values for online gaming does not include social value, however it includes price and emotional values (Park and Lee,
2011). Thus, in the study we focus on price value, quality value, emotional value. However, due to the critical role of
emotions in online environments and hedonic activities (Bagozzi et al., 2016; Pappas et al., 2016) and the fact that
emotional value is mainly measured through positive emotions (Sweeney and Soutar, 2001), we differentiate and
examine both positive and negative emotions to gain a deeper understanding on their role in forming users’ intentions.
Price value and content quality of mobile games
Research on mobile application has received increased attention, mainly due to the evolution and expansion of
contemporary technologies, with studies focusing on explaining user behavior and adoption. Various theories exist
that explain user behavior and technology adoption [e.g., Theory of Reason Action (TRA), Unified Theory of
Acceptance and Use of Technology (UTAUT)]. Various predictors of user behavior and adoption of mobile gaming
applications have been examined, such as perceived value, content quality, flow experience, hedonic motivations,
emotions, and various demographics (Hsiao and Chen, 2016; Su et al., 2016; Zhou, 2013), however this study builds
on TCV and seeks to understand what drives a consumer to make a choice, thus we focus on perceived value as a main
antecedent of user behavioral intentions. Every product or service, including mobile game applications, has a value
and a price, thus the two characteristics are indispensable for one another (Rezaei and Ghodsi, 2014). Here, we define
price value as users’ perceptions that mobile games have a good value for money and are reasonably priced. Price
value has a significant influence on users’ intention to adopt mobile applications (Venkatesh et al., 2012) and online
gaming (Rezaei and Ghodsi, 2014). Also, price value has been found as the main antecedent of in-app purchase
intention in mobile games, however it had no effect on mobile game loyalty (Hsiao and Chen, 2016). Taking into
account the increased penetration of mobile applications and the advancement of smartphones, it is critical to
investigate the role of price value in predicting users’ intention to download mobile games.
Next, we define quality value as users’ perception on attractiveness, timeliness and personalization of mobile game
content, that is game content quality. High quality has been found to increase users’ satisfaction as it will make users
feel good about using a certain service or product (Zhao et al., 2012). Also, quality may have a positive effect on
users’ intention to repurchase online games, (Rezaei and Ghodsi, 2014), since a game that is well made and performs
consistently will increase users’ intention to play it. Game content quality plays a significant role in the users’ overall
flow experience when playing mobile games (Zhou, 2013). The existence of numerous mobile games at different
prices, creates many opportunities and options for the users to find the best game, based on their personal preferences
and characteristics. However, high content quality may not always influence users’ to pay a higher price for a game,
even if it increases their repurchase intentions, (Rezaei and Ghodsi, 2014) indicating the existence of others factors
influencing this relation or different types of relations among the variables, such as asymmetric relations. Thus, it is
crucial to investigate how game content quality combines with price value, and other factors examined here, to better
explain users’ intention to download mobile games. Indeed, recent studies highlight the importance of emotions as
they can significantly influence consumers’ online behavior (Bagozzi et al., 2016; Pappas et al., 2014; Pappas et al.,
2017a). As emotional value is inherent in consumers’ perceived value, we need to examine how emotions may
influence mobile gaming adoption, as they can have equivocal effects on users’ intention to download mobile games.
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DOI: 10.1108/IntR-12-2017-0479
The role of emotions on mobile games
The use of mobile game applications, as with all services, leads to different experiences for their users which may be
either positive or negative, thus influencing their intentions to adopt them. Emotions have an important role in
formulating users behavior, and recent studies identify different types of emotions as predictors of behavioral
intentions in different fields [e.g., (Bagozzi et al., 2016; Pappas et al., 2014)] including mobile applications (Sutanto
et al., 2013) and online gaming (Rezaei and Ghodsi, 2014). Users may decide to play a game because it arouses them
and creates feelings of affect, leading to emotions, which might be either positive or negative depending on the game
as well as on the overall gaming experience (Rezaei and Ghodsi, 2014). Mobile games adoption is likely to increase
if they are more fun (Liang and Yeh, 2011) as users will enjoy more creative and solid storylines (Ha et al., 2007).
Similarly, in the context of social media games, enjoyment increases gamers’ continuous participation (Wu et al.,
2018). Further, emotions are linked with users’ perceptions of value towards the adoption of mobile applications (Liu
et al., 2015) and online games (Rezaei and Ghodsi, 2014), raising the need to examine their interrelations with price
value and game content quality in mobile gaming applications.
Previous studies have examined the role of specific types of emotions as predictors of user behavior in various contexts
(Koo and Ju, 2010; Liu and Li, 2011). Emotions comprise of two major categories, the positive and the negative
emotions, which are independent, universal and may exist at the same time (Bagozzi et al., 2016; Pappas et al., 2016;
Pappas et al., 2017a). Thus, examining positive and negative emotions together can lead to a better explanation of user
behavior, due to their interrelation, as well as to the different effect they can have on users’ behavior (Barclay and
Kiefer, 2014). Indeed, in the context of online services, positive and negative emotions can influence consumers’
intentions in various ways, and might even neutralize each other (Pappas et al., 2016). Here, positive emotions are
defined as the level that users feels happy, valued, and have a warm feeling when playing mobile games, and negative
emotions are defined as the level that users feel irritated, in a bad mood, and upset when playing mobile games (Pappas
et al., 2014). One may feel both types of emotions at the same time, for example when downloading a cheap or free
game with good content users may feel happy by their choice or because they found it at a good price, but also feel
irritated or upset if they have to view advertisements (if it is free) or if it promotes in-game purchases to get better
content. Although emotions are correlated, their interrelation is asymmetric (Pappas et al., 2016), since the presence
of one does not guarantee or exclude the presence of the other. Thus, it is critical to capture such asymmetric relations
and identify what are the different combinations that explain users’ behavior in mobile gaming.
Research propositions
The importance of mobile games and applications constantly increases as technology evolves, new markets are
created, and the number of users grows. There is a call for research to go beyond the technological aspects of online
gaming (Huang and Hsieh, 2011) and take into account users’ value perceptions that may influence their behavior.
Thus, following the previous discussion, there is a need to examine the adoption of mobile applications and especially
of mobile games, by identifying the interrelations and combinations among critical factors that influence behavior in
different settings, that is price value, game content quality value, and emotions (Hsiao and Chen, 2016; Rezaei and
Ghodsi, 2014; Su et al., 2016; Sutanto et al., 2013). Also, we control for gender and time spent playing mobile games,
to explain intention to download a mobile game for different types of users (Ha et al., 2007; Hsiao and Chen, 2016).
Gender differences have been examined broadly in the area, though various results exist in the context of mobile
applications, games, and services (Leong et al., 2013; Liu and Guo, 2017; Wu et al., 2018). In detail, a study in the
context of mobile entertainment found no gender differences regarding adoption of mobile services (Leong et al.,
2013), however this was not verified more recently, when it was found that male and female users of mobile
applications have different motivations (Liu and Guo, 2017), as well as This raises the need to examine the role of
gender in formulating behavioral intentions, in this context, and how it combines with price value, game content
quality value, and emotions. We also examine the gameplay time (i.e., time that users spend each day playing mobile
games), as literature on online gaming has identified different motivations and different behavior for users, depending
on the amount of time they spend playing online games (Neys et al., 2014). For example, enjoyment can be a more
important factors for casual gamers than hardcore ones (Neys et al., 2014). Different results exist on how the
aforementioned factors influence gamers behavioral intentions, thus additional work is needed to obtain a
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DOI: 10.1108/IntR-12-2017-0479
comprehensive overview of their role, and their interrelations, in explaining users’ intention to download mobile
games.
To address this gap, we explain users’ intention to download mobile games by identifying configurations of causally
related sets of factors. Relations between two factors (e.g., A, B) are complex, and the presence of one (A) may lead
to the presence of the other (B), suggesting sufficiency. Further, factor B may be also present when A is absent, thus
the presence of A is a sufficient but unnecessary condition for B to occur. Similarly, with the presence of other factors,
A may be necessary but insufficient for B to occur. We posit that for different types of gamers there is a synergy
between price value, game content quality and emotions in explaining high intention to download mobile games.
Specifically, there is not one unique, optimal, configuration of such values, but multiple and equally effective
configurations of causal conditions exist, which may include different combinations of predictors of gamers’
intentions. This approach allows the identification of asymmetrical relations among the examined factors and the
outcome.
To visualize these relations, we designed a conceptual model (Figure 1) illustrating five independent variables and
their intersections, as shown on the left, and the outcome of interest, on the right. The overlapped areas represent
possible combinations among factors, that is, areas that one factor may exist together with the other factors. Also, to
identify such patterns of factors in a complex system as adoption of mobile games and applications, formulating
hypotheses, common in variance-based methods that are framed as correlational expressions, does not allow for a
holistic approach that will lead to the identification of multiple solutions. Indeed, technology adoption models and
theories need to evolve to capture the complexity of phenomena under investigation (Bagozzi, 2007). Thus, we employ
configuration theory approaches in which research propositions are formulated as causal recipes to capture the
different combinations among factors, and theoretically specify which should be present or absent from the causal
recipe (El Sawy et al., 2010; Fiss, 2007; Ragin, 2008).
Figure 1. Venn diagram illustrating the conceptual model that explains intention to download mobile games
Complexity theory and theory of configuration build on the principle of equifinality, which suggests that a result may
be equally explained by alternative sets of causal conditions (Fiss, 2011; Woodside, 2014). In a complex system,
relations among factors (i.e., causes) are complex and depending on how they combine together, both high and low
conditions of a certain factor may explain high scores of an outcome. These conditions may be combined in sufficient
configurations to explain the focal outcome (Fiss, 2011; Woodside, 2014). Price value, game content quality, positive
and negative emotions, gender and gameplay time are important causal conditions for understanding intention to
download mobile games occurs through the different combinations of price value, game content quality, positive and
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DOI: 10.1108/IntR-12-2017-0479
negative emotions, gender and gameplay time, thus they may interact with each other in various configurations.
Studies show that users’ perceptions on price value, game content quality, and emotions vary, and they may consider
different sets of attributes before using a mobile application or service (Liu and Li, 2011; Rezaei and Ghodsi, 2014).
For example, users may download a mobile game because of its low price even if they are not satisfied with the game
content. Also, users may decide to download a more expensive mobile game with a not so good content because they
feel happy playing it, or because they spend many hours playing during the day, thus they play many games.
Next, configuration theory proposes the concept of causal asymmetry, which means that, for an outcome to occur, the
presence and absence of a causal condition depends on how this condition combines with the other conditions (Fiss,
2011; Woodside, 2014). A predictor variable may have an asymmetric relation with the outcome, which means that
even if one variable is insufficient for the outcome to occur, it is still able to serve as a necessary condition for the
outcome variable (Fiss, 2007; Fiss, 2011; Woodside, 2013). In this case, a necessary condition is a variable that is
present, at least to a degree, in every configuration that explains the outcome, making it indispensable to the outcome.
In other words, different values of the same condition (i.e., high and low levels of a factor) may appear in different
combinations explaining intention to download mobile games, depending on how these conditions combine with each
other. For example, high intention to download may be achieved through both high and low perceptions towards price,
depending on how good the game content is perceived to be, or how the users’ feel when they play. Thus, for the
conditions explaining high intention to download mobiles games, it is important to examine how the presence or
absence of price value, for different types of users, will influence the presence or absence of game content quality or
emotions, and vice versa. Similar interrelations may exist among all adoption values.
Following the above discussion, it is common in studies that employ fsQCA to make propositions that describe the
various configurations and asymmetric relations among variables that explain the outcome of interest [e.g., (Leischnig
and Kasper-Brauer, 2015; Pappas et al., 2016)]. Here, we assume that such propositions hold true, and we formulate
specific testable propositions which include configurations that are expected to hold true for a part (small or large) of
the sample. This, in addition to identifying all the possible solutions that explain high intention to download mobile
games, we will also identify within the sample specific cases, or persons, (who and how many) that will have high
intentions depending on specific antecedent conditions (if they are high or low/medium).
Proposition 1: Users’ having high price value, high game content quality, and high positive emotions, will have high
intention to download mobile games.
Proposition 2: Users’ having high game content quality and high positive emotions will have high intention to
download mobile games.
Proposition 3: Users’ high price value, high game content quality, high positive emotions, and high negative emotions
will have high intention to download mobile games.
Proposition 4: Users’ having low price value, high game content quality, and high positive emotions will have high
intention to download mobile games.
Proposition 5: Users’ having low gameplay time and high positive emotions will have high intention to download
mobile games.
Proposition 6: Users’ having high price value, low game content quality, and high positive emotions will have high
intention to download mobile games.
Methodology
Sampling
This study employs a survey conducted through the delivery and collection of individual questionnaires, following a
snowball sampling methodology to attract respondents. To find appropriate sample, experienced mobile gamers were
contacted (i.e., individuals that play games on their mobile devices), who then forwarded the survey to their business
and personal contacts. The respondents were asked to answer based on their personal evaluations and perceptions
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towards mobile games. Also, they were asked to state their experience with mobile games. Users with no previous
experience were removed from the sample. We aimed at about 1800 users, out of which 593 responded, and 531 play
mobile games, thus comprising the sample of this study. The sample consists of more males (60%) than females
(40%). Most (47%) are younger than 28 years old, followed by users between 29 and 35 years old (26%). Also, 19%
are between 36-45 years old, and the rest (8%) are 46 years old or older. Finally, the sample is rather diverse regarding
employment as it consists of 38% private employees, 32% students, 25% state employees, and 5% retired or
unemployed.
Measures
Respondents were asked about their demographic characteristics, as well as about the constructs as identified in the
background section. The Appendix presents the definitions of the adopted constructs and their source in the literature.
In all cases, except gameplay time, 7-point Likert scales (1 Not at all - 7 Very Much) are used to measure the
constructs. Gameplay time is defined as the hours (approximately) that users spend playing mobile games during the
day. All items along with their descriptive statistics and loadings are also presented in the Appendix.
Next, we evaluate the constructs for reliability with the Composite Reliability and Cronbach alpha indicator, which
needs to be higher than .7 for every factor. Construct validity requires average variance extracted (AVE) to be higher
than .50 (Fornell and Larcker, 1981), the correlation between variables in the confirmatory models shall not exceed
.8, which would indicate low discrimination, and the square root of each factor’s AVE shall be greater than its
correlations with the other factors (Table 1). Also, variance inflation factor (VIF) for every variable is below 3, thus
multicollinearity is not an issue (O’brien, 2007). Based on the common latent factor technique and the CFA marker
variable technique, common method bias is not an issue, as their values are 08 and .21, respectively (Podsakoff et al.,
2003).
Table 1. Descriptive statistics and correlations of latent variables
Construct
Construct
Mean
SD
CR
AVE
3
5
1. Price Value
4.06
1.39
.93
.81
2. Game Content Quality
4.63
1.25
.89
.72
3. Positive Emotions
4.66
1.43
.94
.82
.91
4. Negative Emotions
2.62
1.60
.95
.86
-.01
5. Intention to download
4.96
1.42
.93
.76
.72
.87
Note: Diagonal elements (in bold) are the square root of the average variance extracted (AVE). Off-diagonal elements are the correlations among
constructs (all correlations higher than 0.1 are significant, p< 0.01;). For discriminant validity, diagonal elements should be larger than off-diagonal
elements.
Fuzzy-set Qualitative Comparative Analysis
The study applies fuzzy-set Qualitative Comparative Analysis (fsQCA), which integrates fuzzy set and fuzzy logic
with QCA (Ragin, 2008). FsQCA identifies patterns of elements (i.e., configurations), among independent and
dependent variables, and goes beyond the traditional analyses of variance and MRAs (Woodside, 2014). Also, these
patterns of independent variables, may lead to solutions that are not identified by MRAs, as their effect on the outcome
exists only for a small number of cases (Woodside, 2014), in contrast to the main effects. The benefits of
configurational analysis and fsQCA mainly occur from the limitations of regression-based methods (El Sawy et al.,
2010; Liu et al., 2017; Pappas et al., 2016; Pappas, Giannakos and Sampson, 2017; Woodside, 2013, 2014). Regression
based methods take a net effect approach in examining the effects among factors of interest and the variables are
examined in a competing environment. The covariance among the variables in a model suggests that the presence or
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absence of one variable influences their effect, both on the other variables and the on the rest as well as on the expected
outcome, adding to the importance of applying configurational analysis, which is based on this notion (Fiss, 2007).
FsQCA offers two types of configurations, which are created with both necessary and sufficient conditions, and
provides multiple solutions explaining the same outcome, on which the configurations may be present, absent, or on
a “do not care” condition (i.e., either present or absent). Necessary and sufficient conditions create a distinction among
core (i.e., strong causal condition with the outcome) and peripheral elements (i.e., weak causal condition with the
outcome) (Fiss, 2011). First, an analysis of necessity is performed, which will identify if any of the causal conditions
is a necessary (i.e., indispensable) condition for the presence of intention download mobile games, that is high
intention download mobile games. Necessity, from a set theory approach, means that a condition is a superset of the
outcome (Ragin, 2006), thus for each case in the sample, the fuzzy-set membership score of the outcome is smaller
than the fuzzy-set membership score of the causal conditions. For a condition to be necessary, its consistency should
exceed the threshold of 0.9 (Schneider and Wagemann, 2010). Consistency is the degree to which the cases in the
sample that share a causal condition or configuration agree in displaying the focal outcome (Ragin, 2006). To examine
necessity, the dedicated function in fsQCA software is used, which calculates the consistency and coverage scores for
every causal condition and their negation.
Data Calibration
Next, the variables need to be calibrated into fuzzy sets, by giving them values from 0 to 1, on which 1 stands for the
full-set membership and 0 the full non-set membership. For data calibration, three thresholds need to be defined, that
is full membership, full non-membership and the cross-over point, which represent the level that a case belongs to a
set (Ragin, 2008). This way of calibration is the direct method of calibration. In the direct method, the researcher
chooses three qualitative thresholds, whereas in the indirect method, the measurements require rescaling based on
qualitative assessments. Either method may be chosen based on the data and the underlying theory. Here, the procedure
employed by Pappas et al. (2016) is followed, so the three thresholds are based on the questionnaire scale (7-point
Likert scale). Similar calibration approaches are common in previous studies (Ordanini et al., 2014; Pappas, 2018).
The full membership threshold is set at the value of 6; the full non-membership is set at value 2; and the crossover
point is set at value 4. All values are calibrated on a logistic function to fit into the three thresholds.
Obtaining the Solutions
Next, fsQCA produces a truth table of 2k rows, where k represents the number of outcome predictors and each row
represents each possible combination. For instance, a truth table between two variables (i.e., conditions) provides four
possible logical combinations between them. The truth table needs to be sorted based on frequency and consistency
(Ragin, 2008). Frequency refers to the number of observations for every combination. Consistency refers to the
degree to which cases correspond to the set-theoretic relationships expressed in a solution(Fiss, 2011). A frequency
cut-off point should be set to ensure that a minimum number of empirical observations is obtained. For small and
medium-sized samples, a cut-off point of 1 is appropriate, but for large-scale samples [e.g., over 150 cases], the cut-
off point should be set higher (Ragin, 2008). Here, the frequency cut-off point is set at 3 (Fiss, 2011). Also, a low
consistency threshold leads to the identification of more necessary conditions, reducing type II errors (i.e., false
negatives), but increasing type I errors (i.e., false positives) (Dul, 2016). Thus, a relatively high consistency threshold
is set at >.85; not too high, but higher than the recommended value of 0.75.
Findings
First, we ran an analysis of necessity. For the presence of intention to download mobile games consistency values
range between 0.25-0.73, for both the presence and absence (i.e., negation) of the causal conditions. None of the causal
conditions exceeds 0.9 (Schneider and Wagemann, 2010), that is the threshold for a condition to be considered as a
superset of the outcome of interest, thus, none of them can be considered necessary for high intention to download
mobile games. Since none of the conditions is indispensable (necessary) to the outcome, we proceeded with the fuzzy
set analysis, the main analysis of this study, to identify sufficient combinations of the causal conditions that explain
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high intention to download mobile games. Table 2 presents the outcomes of the fuzzy set analysis for high intention
to download mobile games. Black circles (●) represent the presence of a condition, crossed-out circles () its absence
(Fiss, 2011) and blank spaces indicate a “do not care” situation (i.e., a causal condition may be either present or
absent). Large circles symbolize core elements of a configuration, and small circles peripheral ones. Table 2 includes
set-theoretic consistency values for each configuration as well as for the overall solution, with all values being above
the threshold (>0.75). Consistency measures the degree that a subset relationship has been approximated, and coverage
assesses the empirical relevance of a consistent subset (Ragin, 2008).
Table 2. Configurations leading to high intention to download mobile games
Solutions
Configuration
S1
S2
S3
S4
S5
S6
S7
S8
S9
S10
Gameplay Time (>1 hour/day)
!
!
!
!
Gender (Males)
"
"
"
U
U
U
Price Value
"
U
"
"
!
U
Game Content Quality
!
!
U
!
!
!
"
U
Positive Emotions
!
!
!
!
!
!
!
Negative Emotions
!
!
Consistency
.96
.96
.93
.92
.96
.95
.94
.95
.93
.94
Raw Coverage
.64
.59
.07
.16
.19
.19
.11
.09
.07
.06
Unique Coverage
.08
.07
.01
.01
.01
.01
.02
.01
.01
.01
Overall solution consistency
.937
Overall solution coverage
.791
Note: Black circles (") indicate the presence of a condition, and circles with “x” (U) indicate its absence. Large circles indicate core conditions;
small ones, peripheral conditions. Blank spaces indicate “don’t care”.
The overall solution coverage indicates the extent that high intentions can be determined based on the identified
configurations and is comparable to the R-square value. An overall solution coverage of .791 suggests that the ten
solutions accounted for a substantial proportion of the outcomes.
For high intention to download mobile games, solutions 1-10 present combinations for which the different factors may
be present or absent depending on how they combine with each other. Specifically:
Solutions 1 and 2: All types of users, who perceive content quality to be high and they feel happy or satisfied when
playing mobile games, they will have high intention to download a game, if negative emotions are not high or if the
price value is high. These findings are intuitive considering the importance of quality, price value, and emotions in
the adoption of mobile applications. Indeed, the raw coverage shows that the two solutions explain a very large part
of the sample.
Solution 3: There is a small part in the sample, regardless of gameplay time and gender, who have high intention to
download mobile games when they feel happy and satisfied playing them, even if the price value and content quality.
This solution complements solutions 1-2, as it explains a smaller sample and shows that even with the absence of the
same values the same outcome can be achieved.
Solution 4: Male gamers with low gameplay time, can have high intention to download mobile games when both
positive and negative emotions are high, regardless of quality and price value. This solution points to occasional
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DOI: 10.1108/IntR-12-2017-0479
gamers, who download mobiles games without putting too much focus on value and content, and may end up with
both positive and negative emotions from such experiences.
Solutions 5-6: Male gamers with high gameplay time, have high intention to download a mobile game when negative
emotions are low or medium, and high price value is combined with either high positive emotions or high game content
quality. This shows that users who play often during the day know what they are looking for, want to have fun, and
do not want to overspend, pointing towards heavy gamers.
Solutions 7-8: For female gamers with high gameplay time, high game content quality is very important, as it combines
with the presence of positive emotions or the absence of negative ones, with price value being at low or medium levels
in both cases. This finding shows that female heavy gamers are willing to spend more money if they believe that a
game is of high quality, differentiating from the male gamers in solution 5-6.
Solution 9: Female gamers with low gameplay time, will have high intention to download a mobile game when both
price value and game content quality are high, with negative emotions being at low or medium levels. This highlights
the importance of value and content for female users, compared to male users in solution 4.
Solution 10: Finally, for a small part of female gamers, high intention can be high when both emotions are also high,
with price value and game content quality being at low or medium levels. This finding shows the importance of
emotions, as they may help in overcoming perceptions of low value or content quality, pointing to users with different
motivations when downloading mobile games. For example, users who download a mobile game in order to receive
some type of service, such as free Wi-Fi, or participate at a contest.
The findings offer support for propositions 1 as the combination of high price value, high game content quality, and
high positive emotions is sufficient to achieve high intention to download mobile games (solution 2). Regrading
proposition 2, the findings show that high game content quality and high positive emotions are necessary conditions
in specific combinations but are not sufficient as they need to be combined with either low/medium negative emotions
(solution 1) or for female gamers with high gameplay time who also have low/medium price values (solution 7). The
findings provide support that multiple combinations of sufficient and necessary conditions exist that explain high
intention to download mobile games.
Furthermore, we test specific propositions to identify how the defined configurations explain the outcome of interest
(i.e., high intention to download mobile games), and especially for which cases and for how many in our sample. This
is done by computing the specific configuration in fsQCA software and plotting it against the outcome of interest. The
process on how to compute a specific configuration is described in detail in Pappas (2018). In the plots, “*” means
and, “~” means not. We measure the coverage and consistency for every configuration to see how much and how
strongly it explains the outcome. Furthermore, because configurations with consistency larger than 0.80 are useful and
may be used for advancing theory (Woodside, 2017), we highlight how many cases within the sample have both high
intention to download mobiles games (over 0.7) and consistency 0.8 or larger.
Figure 2 presents the fuzzy XY plots for testing propositions 3 and 4 and identifies cases that represent persons in the
sample for which their intention to download mobile games can be either high or low/medium (i.e., not high). The
findings support this proposition as it explains 21% of the sample (coverage = 0.21) with a high consistency of 0.96.
Also, findings show 21 persons with high price value, high game content quality, high positive emotions, and high
negative emotions (scores over 0.7), out of which only 19 have high intention to download mobile games (scores over
0.80). Thus, proposition 3 includes only 21 cases, but 19 out of 21 will have high intention to download mobile games
(upper right corner). Next, the findings support proposition 4 as it explains 39% of the sample (coverage = 0.39) with
a high consistency of 0.95. Also, proposition 4 includes 16 cases (persons with low price value, high game content
quality, and high positive emotions), but 9 out of 16 will have high intention to download mobile games (upper right
corner).
Pappas et al., 2019 / User experience in mobile gaming applications
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Figure 2. Fuzzy XY plots for testing propositions 3 and 4. The propositions identify cases that have values over 0.7
but intention to download mobile games can be either high or low, describing different persons in the sample.
Similarly, Figure 3 presents the fuzzy XY plots for testing propositions 5 and 6 identifying the cases for which their
intention to download mobile games can be either high or low/medium. The findings support proposition 5 as it
explains 30% of the sample (coverage = 0.30) with a high consistency of 0.88. Also, findings show 47 persons with
low gameplay time and high positive emotions (scores over 0.7), out of which only 33 have high intention to download
mobile games (scores over 0.80). Thus, proposition 5 includes only 47 cases, but 33 out of 47 will have high intention
to download mobile games (upper right corner). Lastly, the findings support proposition 6 as it explains 27% of the
sample (coverage = 0.27) with a high consistency of 0.92. Also, proposition 6 includes 8 cases (persons with high
price value, low game content quality, and high positive emotions), but only 1 out of 8 will have high intention to
download mobile games (upper right corner).
Figure 3. Fuzzy XY plots for testing propositions 5 and 6. The propositions identify cases that have values over 0.7
but intention to download mobile games can be either high or low, describing different persons in the sample.
The configurations identified through propositions may not correspond to a specific solution identified by fsQCA,
instead they allow us to identify what conditions of price value, game content quality, positive and negative emotions,
gender, and gameplay time are sufficient or necessary to create causal combinations that explain high intention to
download mobile game, answering our research question. Furthermore, these configurations allow us to capture
specific cases, or persons (who and how many), within the sample that will have high intention to download mobile
game, depending on specific antecedent conditions (if they are high or low/medium) (Pappas, 2018; Woodside, 2017).
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The asymmetric analysis shows that high scores on a configuration may occur for high scores on the outcome
condition, making the configuration useful for researchers. However, a configuration does not predict all cases with
high scores on the outcome, as was the case for propositions 3-6, since other configurations exist that can predict high
scores for the same outcome (i.e., the upper left side in the plot).
Discussion, Implications and Future Work
The present work suggests that for the adoption of mobile game applications combinations of users’ perceptions of
price value and game content quality, their positive and negative emotions, the time they spend playing mobile games,
and their gender, form configurations that explain high intention to download mobile games. Drawing from
complexity theory and configuration theory, we build a conceptual model serving as the basis for identifying the
aforementioned configurations. The findings identify ten configurations explaining high intention to download mobile
games, and show how the same antecedents can be more or less important for different types of users.
The study highlights the importance of positive emotions, consistent with prior works (Kuo and Wu, 2012; Pappas et
al., 2014; Pappas et al., 2017a), as they are present in 7 out of 10 solutions, always as a core condition. This suggests
that users who feel happy and satisfied when playing mobile games, are like to disregard low perceptions on price
value and game content (e.g., an expensive game with poor content) or even any negative emotions when it comes to
download a mobile game. Furthermore, the findings confirm the importance of game content quality as well as that of
price value, regarding mobile applications, as when they are high, intention to download with also be high for all types
of users. This is an intuitive finding, as mobile games that offer content of a certain quality and in accordance with
their price, are more likely to be downloaded. Similarly, it is interesting to point out that female heavy gamers with
high perceptions of game content quality, will have high intention to download mobile games even when price value
is low. This suggests that, gameplay time is linked with game content, and some users may be willing to pay a higher
price for a mobile game, as they consider its content to be of high quality and they spend a lot of time during the day
playing (e.g., playing while commuting).
Also, the findings show that for gamers who play on average over an hour per day, game content quality is more
important than price value, as the former appears mainly as a core factor, while the latter is always a peripheral factor
(either present or absent). Instead, for users that play less than an hour, price value is very important (i.e., core factor)
when it is present, indicating that occasional gamers are more particular on how much money they spend on gaming,
as opposed to heavy gamers who may pay more on game content, and might be willing to spend more money for a
game of high quality. The findings suggest that male and female gamers have similar behavior regarding their
emotions and gameplay time. Nonetheless, females may focus more on game content, which is present in more
solutions, and less on price value, which is absent in more solutions. The latter points towards an interesting
differentiation, where female gamers may seek high quality games even if they are not reasonably priced.
Theoretical and Methodological Implications
Prior research shows that consumers’ perceived value is a complex construct that comprises multiple dimensions and
plays a pivotal role in formulating users’ behaviours in various contexts (Sweeney and Soutar, 2001; Zeithaml, 1988).
Thus, to understand what drives consumers to make a specific choice and why they buy a product or service the Theory
of Consumption Values (TCV) has been proposed (Sheth et al., 1991). In TCV not all the dimensions of perceived
value are equally important and although they may relate with each other they are independent and a change in one
will not lead to a similar change to another dimension (Sheth et al., 1991; Turel et al., 2010). Although this indicates
to asymmetric relations among dimensions, most studies in the area build and extend TCV by assuming the existence
of symmetric relations and employing variance-based approaches to examine consumers perceived value (Park and
Lee, 2011; Turel et al., 2010). To address this limitation, we employ a different methodological approach that allows
researchers to the asymmetry inherent in real-life phenomena. Methodology is critical, as it defines how we study a
phenomenon and how we think about it (Bagozzi, 2007). The findings present the combinations of price value, game
content quality, emotions, gender, and gameplay time can be sufficient or necessary to explain high intention to
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DOI: 10.1108/IntR-12-2017-0479
download mobile game. Thus, this study contributes to the literature on consumer value by the identifying the
asymmetric relations within its dimensions that explain users’ intentions in the context of mobile gaming.
Next, following previous studies that employ TCV (Park and Lee, 2011; Turel et al., 2010), the findings suggest that
the dimension of emotional value may be extended by including more dimensions of emotions, both positive and
negative, considering their significant role in other contexts (Bagozzi et al., 2016; Pappas et al., 2017a), especially in
the highly experiential and hedonic environment of mobile games. The findings show that positive emotions, a
typically main antecedent of satisfaction (Oliver, 2014) as well as of users’ intentions in online and mobile gaming
(Liang and Yeh, 2011; Wu et al., 2018), is present as a core factor in 7 out of 10 solutions, which means that they are
a necessary condition for these solutions. Also, the presence or absence of negative emotions is necessary in 7 out 10
solutions, and in 4 solutions both types of emotions play a role together. We contribute to the literature by offering
deeper insight on how emotions, a multidimensional factor, combine with users’ perceived value to predict their
intention to download mobile games, thus, aiding researchers to revisit models and theories on user behavior to better
capture the complexity of online and mobile gaming. This can be achieved by extending traditional MRAs and SEM
analyses with fsQCA, which when employed with complexity theory contributes to theory building (Fiss, 2011;
Woodside, 2014), and can lead to the identification of new research questions based on the multiple solutions that
explain the same outcome. To this end, here we test specific models, based on specific propositions, that allow us to
identify how many male or female users, within the sample, with similar levels of perceived value, emotions, time
playing mobile games, have different intention to download mobile games. The results show complex causal patterns
among the predictor variables and highlight asymmetric relationships that lead to the same outcome, towards the
development of new hypotheses and new models of consumer behavior.
The study complements extant research in the area of mobile gaming applications [e.g., (Hsiao and Chen, 2016; Liang
and Yeh, 2011; Su et al., 2016)], by offering an alternative view on how users decide which game to download, and
by showing how important antecedents of users behavior can combine with each other to explain future intentions. In
addition, by employing configurational analysis we include in our results part of the sample that cannot be identified
by the traditional analyses of variance. Thus, we offer multiple solutions that cover a larger part of the sample and at
the same time empirically validate the synergetic nature of price value, game content quality, positive and negative
emotions, gender, and gameplay time as they combine to explain intention to download mobile games. The findings
are consistent with recent studies that highlight the importance of price value and content quality on users mobile
gaming experience and behavioral intentions (Rezaei and Ghodsi, 2014; Zhou, 2013). Furthermore, we complement
these studies by showing that price value and content quality can be necessary conditions for specific solutions, thus
going beyond the discussion of importance and significance that stems from the identification of a single best solution.
On the other hand, our findings contradict online and mobile gaming studies (Liu and Li, 2011; Rezaei and Ghodsi,
2014), that found no effect of emotions on behavioral intentions, although we expect users to choose games because
they like them, feel happy or have a positive experience. Nonetheless, the aforementioned studies take a net effects
approach and do not examine how different combinations and interrelations of the same factors can better explain
intentions. This study contributes by addressing this gap and providing deeper insight on the role of price value and
game content quality, as well as details on how it combines with emotions to explain high intention to download a
mobile game, for different types of gamers.
The most important contribution of this paper are its methodological implications, as it differs from previous studies
in mobile gaming adoption that employ variance methods, such as regression and structural equation modelling, to
examine users’ intentions (Hsiao and Chen, 2016; Liu and Li, 2011). Different from the traditional hypotheses, here
research propositions are formulated which can capture causal recipes taking a holistic approach of complex,
interconnected systems and processes that should be studied together (El Sawy et al., 2010; Ragin, 2008). Thus, this
study formulates research propositions and a configuration analysis is performed with the use of the data analysis tool
fsQCA to examine the asymmetric relationships among the factors. This methodology has recently received increased
attention in marketing and e-business studies (Pappas et al., 2016; Schmitt et al., 2017), and when applied together
with complexity theory and configuration theory, is able to contribute towards the creation of new hypotheses and
theories (Woodside, 2014). To this end, we propose a conceptual model to predict users’ intention to download mobile
games. An analysis of necessity is conducted to detect if any of the antecedent conditions is indispensable for
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explaining intention to download mobile games. It is important to highlight such factors, as they can help in identifying
what conditions should be met or avoided, for the presence or the absence of an outcome. The findings provide
complex causal patterns among the predictor variables and highlight asymmetric relationships that may lead to the
same outcome, and the results lead to the development of new hypotheses to be examined.
Practical and Managerial Implications
This study offers specific paths leading to high intention to download mobile games, which may be used by
practitioners to improve their games and the ways they communicate with their users. As video game industry has
grown considerably generating value for both the industry and the gamer (Marchand and Hennig-Thurau, 2013), game
developers should take into consideration users’ characteristics based on their gameplay time, choose to target specific
types of gamers, and highlight different aspects each time. The findings show that game content quality, price value,
and positive emotions, are essential for all types of users. For existing and well-established companies it is likely that
they have exhausted the possibilities to make such holistic improvements, nonetheless, there is still room for
improvement, since for example in United Stated of America application usage makes up for 52% of the total digital
media engagement (Lella and Lipsman, 2014). Indeed, to increase users’ engagement personalization techniques
should be employed (Zhou, 2013). And since information about user's preferences based on their usage history can be
easily collected, our findings can guide companies on how to communicate with different types of gamers. For
example, promote the quality of the content when addressing heavy users, or the price when addressing users who do
not play a lot during the day. The former may be willing to spend more money if the game offers high content quality,
while the latter prefer to spend less as they do not intend to take full advantage of all the available game content. Such
an approach can be successful by employing freemium pricing strategies, on which the main content is offered free of
charge, but the user has to pay to receive more and better content. By extension, developers may choose different
communication channels, based on the gamers’ gender or how much time they spend within the game. For instance,
in might be an effective strategy if in-game advertisements focus on heavy gamers since they spend more time playing,
or target female heavy users are they are willing to overspend if the content is of high quality, compared to male heavy
users
Developers should constantly interact with their users, through various channels, to capture their preferences, and
emotions, in order to design challenging and interesting games (Liu and Li, 2011). Indeed, the companies that create
and sell mobile games should employ designs and strategies, to better address user needs, evoke positive emotions,
and mitigate the formulation of negative emotions. Also, since the presence or absence of price value is a necessary
condition for 8 solutions, developers may take into account specific characteristics of their games that can influence
either positively or negatively in-game prices (Hsiao and Chen, 2016; Xu et al., 2017). A variety of information
technology tools can be used to capture perceptions regarding content quality, price value, and emotions, such as text
mining of user reviews and feedback (Ganu et al., 2013) and developing collaborative filtering or pattern analysis of
user ratings and comments (Choi et al., 2012). Various channels exist on which developers can employ such
techniques, such as within the stores that sell the mobile games (e.g., Apple’s App Store) or on multiple technology
and gaming forums. Mobile games need to have engaging topics and plots, to avoid making the users feel bored after
playing the game for a while. Combining such knowledge, with users’ gameplay time, which the developers already
know, can help them improve not just their games but also their communication strategies.
Limitations and Suggestions for Future Work
This study has some limitations. First, we used a non-random sampling, thus the generalization of the findings should
be done with caution. Nonetheless, we used a snowballing approach to contact experienced users with mobile gaming.
We also controlled for mobile gaming experience, and all respondents were removed from the analysis. Next, we did
not control for the use context (e.g., playing while commuting), which has been found to be important in mobile game
adoption (Liu and Li, 2011). The findings are based on self-reported data. For an interdepended approach, future
studies may combine self-reported data with archival data from mobile game providers, and extend them with semi-
structured interviews, and observations, as well as data from actual downloads, which may provide deeper insight on
user behavior. The vast number of data generated when we use mobile games and applications could also play an
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DOI: 10.1108/IntR-12-2017-0479
important role in the value of digital transformations that emerges in big data analytics ecosystems (Pappas et al.,
2018).
Next, based on the different solutions for male and female gamers, qualitative approaches including netnography may
be employed as they have been shown to offer useful insight in female online games (Wang et al., 2017). Furthermore,
we do not examine social factors, social interactions, or motivations to download a game, however future studies
should take them into account, as contradicting results exist on how they influence intentions, offering deeper insights
in explaining user behavior (Rezaei and Ghodsi, 2014; Zhou, 2013). To this end, considering the relation of mobile
games with social media future studies may examine how users decide to share electronic word-of-mouth promotional
messages in their networks, based on tie strength or concreteness of the message (Choi et al., 2017).
Future studies may also examine value co-creation in mobile gaming applications, as consumers and companies have
been collaborating at different levels to improve their games or services. Especially, with the evolution of mobile
phones and applications, as well as social networks, value co-creation can lead to better services and products in the
broader “gaming” market, that includes more than just the games (Harwood and Garry, 2010; Roberts et al., 2014).
Employing fsQCA to examine value co-creation (Pappas et al., 2017b), can help in better understanding the
complexity and multidimensionality of value co-creation in service ecosystems (Akaka et al., 2014; Vargo et al., 2008;
Zhang et al., 2017) by capturing the interrelations among the different actors who aim to create value together.
This paper differs from previous studies in the area that focus on net effects among variables, adopts complexity theory
and employs configurational analysis to better explain intention to download mobile games. This study is among the
first to employ fsQCA in mobile application adoption, to advance the field by better understanding the gamer through
a novel approach. Future studies should take a similar approach to verify our findings, and to extend theory in different
contexts. Furthermore, future studies may set research boundaries by putting specific focus in terms of types of mobile
games or specific user segments. It should be noted that fsQCA does not identify the unique contribution of every
variable for every solution, instead it identifies complex combinations of variables and the amount of the outcome that
is explained by these combinations
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Appendix
Construct and scale items
S.D.
Loading
Price value, Cronbach alpha = .88
Users’ perceptions that mobile games are reasonably priced and have a good value for money (Rezaei & Ghodsi, 2014)
Mobile games are reasonably priced
1.63
0.86
Mobile games offer value for money
1.57
0.93
Mobile games are good product for the price
1.45
0.91
Game Content Quality, Cronbach alpha = .81
Users’ perception towards attractiveness, timeliness and personalization of mobile game content (Zhou, 2013)
Mobile games provide up to date contents
1.58
0.83
Mobile games provide attractive content
1.38
0.87
Mobile games provide content pertaining to my needs
1.46
0.85
Positive Emotions, Cronbach alpha = .91
The level that users feel happy, satisfied or valued when playing mobile games. (Pappas et al., 2014)
I feel happy when I play mobile games
1.59
0.94
I feel satisfied when I play mobile games
1.57
0.94
I feel valued when I play mobile games
1.64
0.83
Negative emotions, Cronbach alpha = .94
The level that users feel angry, in a bad mood, or upset when playing mobile games. (Pappas et al., 2014)
I feel angry when I play mobile games
1.74
0.90
I feel in a bad mood when I play mobile games
1.74
0.93
I feel upset when I play mobile games
1.73
0.93
Intention to download, Cronbach alpha = .90
Users’ intention to download mobile games in the future. (Pappas et al., 2014)
In the future, I intend to continue downloading mobile games.
1.63
0.89
My general intention to download mobile games very high.
1.64
0.89
I will download mobile games in the future.
1.60
0.81
I will think to download mobile games.
1.63
0.90
Appendix. Construct definition, scale items with mean, standard deviation, and standardized loading
... It uses a definite configuration of causal antecedents in order to predict the outcome variable [1]. The advantages of such configurational analysis occur due to the limitations of existing regression-based methodologies [5][6][7]. The fsQCA is one of the few first tools for examining causal relationships [4], providing multiple solutions that can explain the same outcome, thus showing how loyalty of digital health intention among people is explained by its antecedents. ...
... The fsQCA is one of the few first tools for examining causal relationships [4], providing multiple solutions that can explain the same outcome, thus showing how loyalty of digital health intention among people is explained by its antecedents. fsQCA offers a deeper insight into the data and should be considered as an alternative and complementary method to traditional variance-based approaches [6,7]. The findings of fsQCA offer multiple, distinct, and equally effective combinations of reliability, convenience, responsiveness, and flexibility, which explain high intention toward loyalty to digital health. ...
... According to Refs. [6,7]; the fsQCA mainly offers two types of configurations. These are created using both the necessary and sufficient conditions in order to provide a number of solutions explaining the same outcome depending on the presence, absence, or on a "do not care" condition (i.e., either present or absent) of the configurations. ...
Article
Purpose Loyalty towards digital health services has received unprecedented attention and acceptance during the Covid-19 pandemic period. However, whether this popularity will be retained into the future and the factors that can influence such loyalty is undetermined. This paper provides insight into this issue through a cross-cultural examination of the influence of digital service quality (e-quality) on consumer satisfaction and loyalty (e-loyalty) in the digital health service sector during a pandemic. Methodology A fuzzy-set qualitative comparative analysis (fsQCA) is applied using a sample of 50 customers drawn from different professions across different countries who actively showed loyalty towards digital health during the pandemic. Research constructs evaluation for reliability and internal consistency was subsequently performed using Cronbach's alpha and Correlation analysis. Results The results reveal a significant positive relationship between service quality and the twin outcomes of consumer satisfaction and loyalty, while the findings established satisfaction as a prominent mediator for digital health. Findings from the fsQCA analysis identified four core factors that underpin loyalty in digital health platforms. Alternative paths have been identified based on gender, current education status, and other professions. In addition, two topologies are introduced taking digital health services from different platforms during the pandemic. Originality Because of the primary nature of the data, this is first-hand experience gathered from the people who are directly or indirectly involved in receiving help from digital health services in a pandemic context. The application of the fsQCA technique for examining loyalty towards digital health services is applied in the e-health or digital health literature for the first time. Implications The study findings will assist digital health service providers seeking insight into the factors that influence loyalty of e-health service consumers, enabling them to focus more accurately on the service quality dimensions that are effective in influencing consumer satisfaction and retention. The findings of this study contain a number of contributions, illustrating different topologies towards digital health that provide educators and policymakers with valuable insights.
... Fuzzy-set qualitative comparative analysis (fsQCA) is one of the first tools for examining causal relationships (Rihoux and Ragin, 2009), offering multiple solutions that can explain the same outcome, demonstrating how perceived service quality of online education among university students is defined by its antecedents in this study. Fuzzy-set qualitative comparative analysis gives a more in-depth interpretation of the data and should be seen as an alternate and supplementary way to traditional variance-based approaches (Pappas et al., 2019). The findings of fsQCA provide diverse, unique, and equally effective combinations of the core teaching process, reliability, convenience, and IT system structure, which explain students' satisfaction toward online education. ...
... Both essential and sufficient variables can exist as core conditions (leading to a strong causal link with the result) or ancillary factors (Rihoux and Ragin, 2009) (Fiss, 2011). According to (Pappas et al., 2019), the fsQCA primarily provides two sorts of setups. These are implemented employing both the needed and sufficient conditions to give alternative solutions describing the same outcome dependent on the presence, absence, or do not care condition (i.e. ...
... (Fiss, 2011) An analysis of necessity is performed for both the presence and absence of the condition to evaluate if any causal conditions are required for the availability of purpose towards perceived service quality (Table 2). According to (Ragin, 2006) necessity shows that a condition is a "superset of the result," which means that the output's fuzzy-set membership score is smaller than the causal conditions' fuzzy-set membership score for each occurrence in the given data (Pappas et al., 2019). Likewise, (Schneider and Wagemann, 2010) contended that for a condition to be necessary, its consistency must always be more than 0.9. ...
Article
Background During COVID-19 lockdown worldwide, classroom education continues remotely through online. The question remains, comparing with the face-to-face education, does online education has a similar satisfaction level among the students? There are only a few studies that examine the perceived service quality of online education. Objective The study aims to analyze the factors of perceived service quality of online education during a pandemic. Research Design A structured questionnaire elicits information from 147 students from different study backgrounds of various universities worldwide. The fuzzy-set qualitative comparative analysis (fsQCA) is used for data analysis and model design. Research constructs evaluation for reliability and internal consistency are subsequently performed. A snowball random sampling method is applied for data collection. Results Findings from the fsQCA analysis identify four core factors that underpin student satisfaction through positive perceived service quality of online education. Alternative paths are determined based on gender, students’ current education status, and their loyalty toward online education. We also introduce two topologies of perceived quality regarding online education and student satisfaction. Originality Because of the primary nature of the data, this is firsthand experience gathered from different universities around the world who have willingly or unwillingly experienced online learning during the pandemic. The fsQCA technique for examining perceived service quality of online education. Conclusions The findings contain a number of contributions, illustrating different topologies of the student from different backgrounds and their intention, satisfaction and loyalty towards e-learning, and identifying causal factors that influence willingness to recommend online education.
... appealing) visual aesthetics are subjective (Zen and Vanderdonckt, 2016), which complicates creating balanced user experiences for critical masses. Especially in mobile environments, the adoption of mobile game applications is a complex entity of varying perceptions, such as gender, content price and quality and time spent playing mobile games (Pappas et al., 2019). Therefore, insight into what aspects of GUI element aesthetics are preferred by segmentation is needed. ...
... Prior research has indicated that not only the main effects of age, gender and time are to be investigated, but also the interactions of these demographics should be taken into account, as significant relationships have been found between, e.g. age and gender on technology adoption (Morris et al., 2005) as well as gender and time on mobile entertainment (Hsiao and Chen, 2016;Pappas et al., 2019). Research regarding demographic differences in relation to aesthetic perceptions of GUI elements is scarce at present. ...
... Moreover, users have been found to be selective with aesthetics based on experience (Hartmann et al., 2008). Prior research on mobile entertainment has identified that time spent interacting with mobile systems affect user intentions and motivations, such as mobile game preference (Hsiao and Chen, 2016) and the level of investment on downloading mobile games (Pappas et al., 2019). Involvement with GUI elements may impact users in several ways in regards to skill level, user experience, decision-making processes and perceptions of aesthetics. ...
Article
Full-text available
Purpose Customization by segmenting within human–computer interaction is an emerging phenomenon. Appealing graphical elements that cater to user needs are considered progressively important, as the way a graphic is visually represented can greatly contribute to the interaction. However, aesthetic perceptions are subjective and may differ by target group. Understanding variations in user perceptions may aid in design processes; therefore, we set out to investigate the effects of demographic differences relating to perceptions of graphical user interface (GUI) element (i.e. game app icon) aesthetics. Design/methodology/approach The authors employed a vignette experiment with random participant ( n = 513) assignment to evaluate 4 icons from a total of 68 pre-selected mobile game icons using semantic differential scales. This resulted in a total of 2052 individual icon evaluations. Regression analyses were performed with the effects of age, gender and time using graphical user interfaces (i.e. app stores) and the interactions of these variables relating to perceptions of GUI element aesthetics. Findings The results indicate that, overall, demographic factors have relatively little effect on how icons are perceived. Significant relations suggest that experienced users, younger audiences and women are more critical in their perception of aesthetic excellence, and that perceptions change for younger women. The implications of the findings are discussed via adaptive decision-making theory. Originality/value In the context of graphical user interface element aesthetics, demographic differences have received minimal attention as moderating variables regardless of their relevance in design and development. Hence, it merits further research.
... Second, in real-life contexts, human perceptions and behavior are rarely linear in terms of antecedent-outcome relationships. Indeed, complexity theory focuses on complex systems that operate in a nonlinear fashion, suggesting that outcomes are the result of interactions from various antecedents (Woodside et al., 2015;Olya & Akhshik, 2019;Pappas, 2019). In other words, rather than a clear direct path, it is often a combination of various antecedents that can lead to a particular outcome (Ragin, 2008). ...
... Mobile gaming systems in education strive to integrate situations, active learning, and social dynamics in an allegorically informed visual-audio environment [1]. Despite its rapidly changing technological components, educational mobile games offer an opportunity to revise the learning process [2]. ...
Article
Full-text available
Simulation-based pedagogy is fully considered when designing collaborative learning processes. However, particularly for training managerial skills in hospitality industries, limited work has been performed on analysing the impact of business simulations in the direction of a mobile gaming system. This paper presents a tablet gaming setup for a hospitality business simulator representing tourist flow characteristics, resource management, and the interaction of actors based on a competition relationship among hotel chain operators involved in the hospitality industry. The mobile gaming system was tested in game-based learning exercises, as in distance and classroom learning case studies, following identically parameterised scenarios. First, survey scores were collected using the self-report Learning Experience and Outcomes Questionnaire to evaluate ubiquitous human mobile-web interaction. Second, lag sequential analysis was employed to examine learning effects. Finally, a regression analysis was carried out to understand whether mobile gaming behaviours were likely to predict hotel performance as the outcome of the collaborative learning process. A total of 90 graduate students participated in game-based learning sessions in the autumn and spring semesters of 2020 and 2021, respectively. For the self-efficacy section, there were no significant differences in the scores. Sixty percent of the scored items in the classroom learning case study outperformed those in distance learning. Face-to-face participation enables more interaction between participants and mobile devices. The regression analysis delivered a △R2 of 0.43 (F4,31 = 7.56, P
... Given the highly interactive, immersive nature of online videogames, we concur that the identified factors exert an important effect on consumer-perceived ad value and behavior (Miller, 2019;Oertzen et al., 2020). Unlike in-game advertising, where cluttered content may reduce ad effectiveness (Seo et al., 2018), we focus on game breakleveraging pop-up ads (e.g. by being shown at users' progression to the next game level/page loading intervals). ...
Article
Purpose Though the videogame literature is thriving, little remains known regarding the effectiveness of pop-up ads that appear in videogames. Addressing this gap, this study, therefore, aims to explore pop-up ads as an important tool to prompt gamer-perceived advertisement value and their subsequent intent to install the advertised videogame. Design/methodology/approach To frame the analyses, the authors adopt and extend Ducoffe’s advertising value model by incorporating the visual/audio aesthetic videogame components that are largely overlooked in prior research. Using a self-administered survey, data were collected from 321 online gamers. The authors tested the model by using partial-least-squares-based structural equation modeling (PLS-SEM). Findings The results indicate that pop-up ad-related incentives, entertainment, credibility, personalization, audio aesthetics and irritation significantly affect user-perceived ad value. In turn, perceived ad value was found to affect players’ intent to install the advertised videogame. Research limitations/implications Though the findings corroborate the importance of pop-up ads being perceived as informative and/or entertaining, they also emphasize the value of personalized ads, ad-related incentives and audio aesthetic, which impact gamers’ intent to install the advertised videogame. Practical implications This study advances managerial understanding of videogame-based services, which is expected to be particularly useful for freemium-based videogame marketers and developers. Originality/value By extending Ducoffe’s model of advertising value, the authors apply the proposed framework in the online videogaming-based pop-up ad context, and explore the effect of user-perceived pop-up ad value on their intent to install the advertised videogame.
... Given the highly interactive, immersive nature of online videogames, we concur that the identified factors exert an important effect on consumer-perceived ad value and behavior (Miller, 2019;Oertzen et al., 2020). Unlike in-game advertising, where cluttered content may reduce ad effectiveness (Seo et al., 2018), we focus on game breakleveraging pop-up ads (e.g. by being shown at users' progression to the next game level/page loading intervals). ...
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In the complex environments of online personalization multiple factors have been considered to explain consumers' online behaviour, but largely without considering the role of specific configurations of variables, and how they may affect consumer behaviour. This study shows how trust towards online vendors, privacy, emotions, and experience combine to predict consumers' purchase intentions. Building on complexity theory we present a conceptual model followed by research propositions. Our propositions are empirically validated through configurational analysis, employing fuzzy-set qualitative comparative analysis (fsQCA) on 182 customers with experience in personalized online shopping. Predictive validity analysis is also performed. Five solutions of trust, privacy, emotions, and experience increase intention to purchase, and six solutions inhibit it. The findings verify the importance of trust and happiness in successful personalized online shopping. Their absence inhibits purchase intentions. Also, high experience may help to overcome low trust or negative emotions, while low experience requires the combination of high trust and happiness. None of the examined factors are indispensable to explain purchase intentions. The study employs fsQCA, differentiating from traditional studies in the area that use variance-based methods, and identifies multiple solutions explaining the same outcome. The proposed approach contributes to theory development in the field. The multiple solutions lead to new ways on how companies may approach their customers, as each one covers a specific part of the sample, adding to the fact that in personalized marketing there is not one single optimal solution explaining customer purchase intentions This study contributes by (1) extending existing knowledge on how trust, privacy, emotions and experience combine to increase or mitigate intention to purchase, towards the development of new emotion-centric theories and the design and provision of personalized services; and (2) presenting a step-by-step methodological approach for how to apply fsQCA in e-commerce studies.
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Mobile technologies and their applications have the potential to benefit various learning contexts. Users' perceptions of mobile learning (m-learning) technologies are of great importance and precede the successful integration of these technologies in education. M-learning adoption has been investigated in the literature with reference to various factors and learning analytics, but largely without considering the role of different configurations (i.e., specific combinations of variables), and how these configurations might affect the adoption of various user groups. For instance, users with different backgrounds, experiences, learning styles, and so on might not be represented by the one-model-fits-all produced from the common regression approaches. In this study, we briefly review factors that have been proven important in the context of mobile learning adoption, and build on complexity theory and configuration theory in order to explore the causal patterns of factors that stimulate the use of mobile learning. To test its propositions, the study employs fuzzy-set qualitative comparative analysis (fsQCA) on a data sample from 180 experienced m-learning users. Findings indicate eight configurations of cognitive and affective characteristics, and social and individual factors, that explain m-learning adoption. This research study contributes to the literature by (1) offering new insights on how predictors of m-learning adoption interrelate; (2) extending existing knowledge on how cognitive and affective characteristics , and social and individual factors, combine to lead to high m-learning adoption; and (3) presenting a step-by-step methodological approach for how to apply fsQCA in the area of learning systems and learning analytics.
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This book takes the reader beyond net effects and main and interaction effects thinking and methods. Complexity theory includes the tenet that recipes are more important than ingredients-any one antecedent (X) condition is insufficient for a consistent outcome (Y) (e.g., success or failure) even though the presence of certain antecedents may be necessary. A second tenet: modeling contrarian cases is useful because a high or low score for any given antecedent condition (X) associates with a high Y, low Y, and is irrelevant for high/low Y in some recipes in the same data set. Third tenet: equifinality happens-several recipes indicate high/low outcomes. © Springer International Publishing AG 2017. All rights reserved.
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Several issues relating to goodness of fit in structural equations are examined. The convergence and differentiation criteria, as applied by Bagozzi, are shown not to stand up under mathematical or statistical analysis. The authors argue that the choice of interpretative statistic must be based on the research objective. They demonstrate that when this is done the Fornell-Larcker testing system is internally consistent and that it conforms to the rules of correspondence for relating data to abstract variables.
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Purpose Drawn from the social playfulness literature and the elaboration likelihood model, this study proposes and tests a research model to examine users’ continuous participation in SNS game applications. Design/methodology/approach A field survey with 133 subjects was conducted to test the research model. Findings Two identified design features, symbolic physicality and inherent sociability, are found to influence users’ perceived curiosity and perceived enjoyment toward playing SNS game applications. Perceived enjoyment is significantly associated with perceived curiosity and predicts users’ continuous participation of SNS game applications. We also observed a gender difference of social playfulness design on perceived curiosity. Research limitations/implications Use intention was used as a proxy for actual use behavior, since objective data on continuance behavior was not available. Additionally, the contributions of this study may be constrained by one single sample. Practical implications The findings of the study suggest practical guidelines for designing game applications in SNS through socialization design and symbolic physicality. Further, based on the findings of gender differences, a personalization game design strategy is provided. Originality/value The study contributes to the post-adoption IS literature and sheds light on the interesting area of social media participation. Additionally, this study enriches the online gaming research by demonstrating gender differences.
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Purpose: Thriving brand communities are inseparable from engaged members and their word-of-mouth behavior. The purpose of this paper is to investigate which customer experience elevates customer engagement and consequent word-of-mouth intention in online brand communities, and how. Design/methodology/approach: From the perspective of service ecosystem theory, a framework with several hypotheses was proposed. The model was verified with structural equation modeling based on questionnaire data collected from smartphone communities in China. Findings: Empirical results indicate that customer experience promotes community engagement, and further enhances word-of-mouth intention. Furthermore, the mediating effect of community engagement in the relation between customer experience (social support and flow) and word-of-mouth intention has been verified. Practical implications: This paper informs practitioners about the importance of experience co-creation with community members in brand and community promotion, and provides several implications to encourage more engaged customers with fostering pleasant customer experiences. Originality/value: This study contributes to the theory of service ecosystem by empirical examination of its several propositions in a brand community context. The paper extends the present theory with the discussion of the mediation effect of community engagement in the continuing value co-creation process.
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Purpose: The purpose of this paper is to explore in depth the special context and unique life experience of the online role-playing game and to provide insights regarding an interpretation of the situational context model. Design/methodology/approach: This study uses netnography, online interviews, and the physical travel of researchers to the field for field participation and observations. The combination of netnography and online interviews combines online and offline studies to achieve more consistency in the data collection, analysis, and other processes. In-person participation in observations makes the research more realistic. The combination of these qualitative methods is helpful in achieving a more comprehensive and accurate research process. Findings: The findings of the study can be classified into a three-stage situational context approach, which is presented in the form of propositions. Finally, the insight of the situational context model was developed. Research limitations/implications: This study only focussed on office workers and students in online role-playing game. Therefore, the samples should be extended to other massively multiplayer online games, including different nationalities and professions for comparative analysis and related studies. Through the expansion of the sample size, a representative and stable cyber model can be established. Originality/value: The theoretical contribution of this study is to establish an interpretation of the situational context model and eight related propositions. The study revealed the mystery of female online role-playing games.
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Purpose Massively multiplayer online role-playing games (MMORPGs) create quasi-real social systems in which players can interact with one another, and quasi-real economic systems where players can consume and trade in-game items with virtual currency. The in-game currency price, an important indicator of a virtual economy, is highly contingent on players’ behavioral interaction in MMORPGs. The purpose of this paper is to adopt a network perspective to examine how topological characteristics of social networks in an MMORPG, namely, network externalities, density, and closure, would exert impacts on the in-game currency price. Design/methodology/approach Players’ behavioral data were collected from a popular MMORPG in China on a weekly basis for 52 weeks. With a time series analytical approach, the empirical model for the price function of in-game currency was estimated with vector autoregression. Findings The results show that the number of core avatars and network density are positively associated with in-game currency price, while network closure has a negative effect on in-game currency price. However, in-game currency price is found to have no significant relationship with the trade volume of the currency. Originality/value This study fills in an important research gap by investigating factors influencing the in-game currency price of MMORPGs from a network perspective, which contributes to the existing literature of network effects and advances our understanding about how players’ interaction will influence the dynamics of a virtual economy. The findings could offer useful insights for online game companies to better understand their players’ social interaction and consumption behavior.