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A MA)ER OF TRUST AND EMOTIONS: A
COMPLEXITY THEORY APPROACH TO
EXPLAIN THE ADOPTION OF
EGOVERNMENT SERVICES
Panos Kourouthanassis
Ionian University726;816516/8
Ilias O. Pappas
Norwegian University of Science and Technology137)77)91,15:5;56
Cleopatra Bardaki
Athens University of Economics and Business+3-6*)8);-*/8
Michail Giannakos
Norwegian University of Science and Technology41+0)13/1,15:5;56
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Twenty-Fourth European Conference on Information Systems (ECIS), İstanbul, Turkey, 2016
A MATTER OF TRUST AND EMOTIONS: A COMPLEXITY
THEORY APPROACH TO EXPLAIN THE ADOPTION OF E-
GOVERNMENT SERVICES
Research
Kourouthanassis, Panos E., Ionian University, Corfu, Greece, pkour@ionio.gr
Pappas, Ilias O., Norwegian University of Science and Technology (NTNU), Trondheim,
Norway, ilpappas@idi.ntnu.no
Bardaki, Cleopatra, Athens University of Economics and Business, Athens,
Greece, cleobar@aueb.gr
Giannakos, Michail N., Norwegian University of Science and Technology (NTNU), Norway,
Trondheim, michailg@idi.ntnu.no
Abstract
This research uses complexity theory to offer a deeper insight on the causal patterns of factors explain-
ing the adoption of e-government services. To this end, we propose a conceptual model comprising of
affective factors (positive and negative emotions) and cognitive factors (trust of the government, trust
of the service, and perceived net benefits of e-government services) along with research propositions.
Our propositions are validated by employing a fuzzy-set qualitative comparative analysis (fsQCA) on
a sample of 502 users of e-government services. Findings indicate five configurations of cognitive and
affective perceptions that lead to high intention to use an e-government service. Of paramount im-
portance are affective values and trust values since their mandatory presence or absence is incorpo-
rated in all configurations. The study has both theoretical and practical implications for academic
scholars pertaining the development of new e-government adoption theories and the provision of e-
government services.
Keywords: trust, emotions, e-government, fsQCA
1 Introduction
Research on information systems (IS) adoption has followed a dyadic pathway. On the one hand, re-
searchers have highlighted the importance of cognitive values, such as perceived usefulness, usability,
and overall benefits for the adoption of information technology (IT) innovations. On the other hand,
scholars have begun to transcend these cognitive perspectives of information systems adoption to also
consider specific affective qualities, such as enjoyment and satisfaction. Interestingly, this interplay of
adoption values has been examined under competitive scrutiny; predominant models and theories
(such as the Unified Theory of Acceptance – UTAUT - and Use of Technology and variations of the
Expectation-Confirmation Model) almost uniformly employ variance-based statistical approaches (e.g.
regression-based Structural Equation Modelling) that rank the hypothesized predictive adoption fac-
tors based on their regression ‘weights’, suggesting that information systems adoption may be ex-
plained through a single hierarchy (or configuration) of these factors.
This research posits that there is a synergy between affective and cognitive values on the adoption of
information systems. In particular, we theorize that there is not one single, optimal, configuration of
such values. Instead, multiple and equally effective configurations of causal individual adoption fac-
tors may exist, which may include different combinations of adoption perceptions (i.e. combinations
of high and low perceptions). To investigate our theoretical propositions we used electronic govern-
ment (e-government) services as our application context. The adoption and use of government-to-
Kourouthanassis et al. /A complexity theory approach to explain e-government services adoption
Twenty-Fourth European Conference on Information Systems (ECIS), İstanbul,Turkey, 2016 2
citizen services has already received significant attention by information systems scholars, primarily
through cognitive-based inquiry lenses and adaptation of extant IS adoption models in the e-
government context [e.g. Wang and Liao (2008); Ozkan and Kanat (2011); Lean et al. (2009)]. This
research emphasizes on two critical cognitive adoption values for e-government, namely trust and net
benefits. Trust is an umbrella term that encompasses such dimensions as trust in electronic govern-
ment services and trust in the government. Both dimensions have been reported to have a direct influ-
ence to e-government services adoption (Bélanger and Carter 2008; Srivastava and Teo 2009). Like-
wise, adoption of e-government services is influenced by utilitarian perceptions regarding the net ben-
efits that citizens receive when using the service (Scott et al. 2011).
However, as in IT adoption (Beaudry and Pinsonneault 2010), the use of e-government services also
breeds affective qualities, which also influence citizens’ adoption behaviour. Affect is a multidimen-
sional term that includes a wide range of psychological concepts, such as emotions, moods, and feel-
ings (Russell 2009; Zhang 2013). Affect is conceptualized and measured through a circumplex mode
that uses distinct emotions. In this research, emotional values are measured through the formulation of
positive and negative emotions from using the e-government services. Emotions are considered ‘situa-
tional’ predictors of e-government usage behaviour (Ebbers et al. 2008) and their influence on e-
government services adoption remains largely understudied.
Based on the above, citizens consider both cognitive and affective values before interacting with an e-
government service, suggesting that these values coexist and are likely to be interrelated. Extant stud-
ies on e-government adoption focus only on the main effects of specific predictors (e.g., trust, perfor-
mance expectancy, and effort expectancy) on usage intention [e.g. Srivastava and Teo ; Venkatesh et
al. (2011)] and ignore to examine the combined effects of cognitive and affective perceptions on the
intention to use e-government services. We build on complexity theory and implement a fuzzy-set
qualitative comparative analysis (fsQCA) (Ragin 2008), to identify pertinent configurations leading to
increased adoption of e-government services. fsQCA has received increased attention during the last
years in various fields, because it allows researchers to gain a deeper understanding of the phenome-
non under scrutiny (Ordanini et al. 2014; Wu et al. 2014). The contribution of the paper is two-fold.
On the one hand, we provide empirical evidence pertaining the role of emotions on the adoption of e-
government services. On the other hand, we explore the combined influence of extant cognitive and
affective e-government adoption values (i.e., trust in the system, trust in the government, net benefits,
positive and negative emotions) to the propensity of e-government adoption. To our knowledge, this is
the first research that adopts this investigation stance in the context of e-government.
The structure of the paper is as follows. Section 2 presents the theoretical grounding of this research
and articulates the research propositions. Section 3 outlines the research methodology and sampling
process. Section 4 presents the research findings. Finally, section 5 concludes the paper with a sum-
mary of the theoretical and practical implications of our research.
2 Theoretical Grounding
2.1 Perspectives on e-government adoption
E-government encompasses a wide array of technology-enabled applications and services that support
public administration operations, enhance government transparency, and create better public value to
citizens and businesses (Al-Hujran et al. 2015). It should be noted that the success of e-government
services is highly dependent to their adoption and use (Rose and Grant 2010). Indeed, for most coun-
tries e-government represents an alternative way of citizens to interact with public authorities in which
usage of the electronic service is voluntary. Moreover, e-government users vary in terms of their in-
formation technology and information processing skills, which introduces technology challenges in the
design and interaction modality of the service (Bélanger and Carter 2009). Driven by these observa-
tions, the vast majority of studies investigating the adoption of government-to-citizen services [e.g.
Kourouthanassis et al. /A complexity theory approach to explain e-government services adoption
Twenty-Fourth European Conference on Information Systems (ECIS), İstanbul,Turkey, 2016 3
Carter et al. (2005), Fu et al. (2006), Hung et al. (2006), Van Dijk et al. (2008), and Venkatesh et al.
(2011) to name but a few indicative studies] attempt to examine whether extant IS adoption theories,
such as the Unified Theory of Acceptance and Use of Technology (Venkatesh et al. 2003) and the Dif-
fusion of Innovations theory (Rogers 1995), still hold in the e-government context. Rana et al. (2015)
provide an extensive meta-analysis on the factors that influence e-government services adoption by
citizens. The common denominator of these studies refers to the assumption that the adoption (and
use) of an e-government service is solely the end-product of individuals’ cognitive processing; they
rely on the accumulated knowledge of technical or functional features of the service to inform their
usage behaviour towards the service.
However, this assumption is not always true. Citizens may use e-government services under turbulent
socio-political environments, such as the effects of the economic recession, which led to budget cuts,
or frequent changes to public administrations. This state of uncertainty reinforces the importance of
affective values when studying the adoption of e-government services. For example, many countries
employ e-government as a cornerstone implementation strategy for achieving the government’s auster-
ity goals and consequent economic reform (Ubaldi 2011). In these countries, the adoption of e-
government services will logically be influenced by emotional responses towards the service itself (as
a means of implementing austerity measures) or the government (as the actual implementer of the aus-
terity measures).
Nevertheless, these emotional responses are likely to be affected by trust beliefs. Indeed, citizens’ per-
ceptions on government performance may be influenced by their trusting beliefs towards the govern-
ment (Van de Walle and Bouckaert 2003). Hence, trust may act as a regulator to the development of
positive or negative emotions by increasing individuals’ confidence to the service provider (Johnson
and Grayson 2005). Notably, the emotional aspects of trust have been well grounded to social psy-
chology literature, which conceptualizes trust as a multidimensional factor that has cognitive, affec-
tive, and behavioural properties (Lewis and Weigert 1985). The influence of trust on emotions has also
been documented in the context of electronic services [e.g. Pappas et al. (2013), Hwang and Kim
(2007)] however, literature does not exhibit any studies yet that relate both trust and emotions with
electronic government adoption. To better articulate the theoretical constructs of this research, the fol-
lowing section outlines the core determinants of emotions and trust and further discusses their relation
with the adoption of e-government services.
2.2 The role of emotions on e-government adoption
Emotions are induced affective states which are activated through responses to specific stimuli
(Russell 2009). These responses are subjective in nature and encompass a wide spectrum of feelings
that vary in terms of their arousal and valence (Scherer et al. 2013). Arousal reflects the power of the
response, while valence refers to the direct emotional response ranging from positive to negative
(Russell 2009). In the context of information systems, scholars have shown a positive association be-
tween specific types of emotions (e.g. enjoyment, pleasure, and anger) and behaviour formulation [e.g.
Beaudry et al. (2010), Hong et al. (2006), Kourouthanassis et al. (2015), and many others]. Recently,
scholars showcased that emotions should be studied holistically since individuals may formulate both
positive and negative emotions at the same time while using an information system (Pappas et al.
2014; Pappas et al. 2016).
Interestingly, the role of emotions on e-government adoption remains largely understudied. Extant
studies relate emotions with e-government services adoption only indirectly through individuals’ per-
ceptions of overall satisfaction with the service (Verdegem and Verleye 2009; Welch et al. 2005). In
effect, Ebbers et al. (2008) consider emotions as a situational factor to the decision making process of
individuals for selecting and using an e-government service. However, emotions play a deeper role on
formulating usage intentions.
First, e-government services represent the front-end communication tools of public administrations
therefore, political sentiments would also be associated, to a certain degree, with them. Second, e-
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Twenty-Fourth European Conference on Information Systems (ECIS), İstanbul,Turkey, 2016 4
government services usually instrument reform choices of public administrations (Bertot et al. 2010;
Torres et al. 2005). Whilst such choices may represent new and more efficient ways to deliver public
services, sometimes e-government services are the means of enforcing austerity measures (Ubaldi
2011). Finally, e-government services usually presuppose a certain degree of change management for
end-users who will have to familiarize themselves with the new way of interacting with the govern-
ment (Andersen and Henriksen 2006). Especially in the early stages of adoption, this change is likely
to evoke negative emotions especially if the service suffers from shortcomings related to technical fi-
delity and overall usability. For example, the deployment of the national electronic prescribing system
in Greece generated an extensive debate to the medical community and the public (Krania et al. 2013).
On the one hand, medical doctors and pharmacies were generally satisfied from the overall functional-
ity and resulting benefits of the system (minimization of bureaucracy over prescriptions, streamlining
of financial transactions between pharmacies and the government). On the other hand, the system was
treated with high scepticism because the medical community perceived it as a driver of implementing
budget cuts to public health. Moreover, issues related with system unavailability for extensive time
periods, insufficient IT skills by the user base, and change management issues contributed to the de-
velopment of negative emotions which, in turn, affected the adoption and use of the service.
2.3 The role of trust on e-government adoption
Trust has been a predominant factor of models and theories exploring e-government services adoption
(Carter and Bélanger 2005; Welch et al. 2005). Extant studies decompose trust into two interweaving
perspectives: trust in the entity providing the service (i.e., trust of the government or institution-based
trust) and trust in the reliability of the enabling technology (i.e., trust of the electronic service). Trust
of the government reflects as citizens’ perceptions pertaining the integrity and capability of political
authorities and institutions to providing services that are of their best interests (Bélanger and Carter
2008). Likewise, trust of the electronic service echoes citizens’ beliefs that the e-government website
will fulfil its obligations as the user understands them (Kim et al. 2008).
The aforementioned definitions of both trust dimensions are consistent with the basic notions of cogni-
tion. Trust is knowledge-driven; it arises from the accumulated knowledge stemming from repeated
interactions between focal parties (i.e., the citizen and the government). Johnson and Grayson (2005)
define this dimension of trust as cognitive trust. However, trust may also have strong affective proper-
ties. For example, in service relationships the development of strong connections between the focal
parties may evoke emotional responses, which will in turn strengthen trust in a partner beyond a de-
gree that is justified by available knowledge (Johnson and Grayson 2005). The latter denotes the inter-
play between emotions and trust; using an electronic service may evoke emotional responses, which
depending on their valence and intensity, will form the basis for trusting bonds and elicit commitment
to the service. In the context of electronic government this interplay becomes even more challenging,
since high trust beliefs may alleviate the intensity of negative emotions stemming from poor imple-
mentation of the electronic service, or from misjudging the electronic service as a metaphor of the
government’s austerity measures.
2.4 Research propositions
Based on the above, scholars need to study the adoption of electronic government services through
both cognitive and affective lenses. Following the discussion in the previous sections, the cognitive
angle of this study examines the relation of trust values with e-government services adoption. Trust is
decomposed into two distinct dimensions that measure the reliability of the e-government service (i.e.,
trust of the service) and the belief that the government behaves ethically (i.e., trust of the government).
Both dimensions have been confirmed to positively influence the intention of using electronic services
in past studies [e.g. Bélanger and Carter (2008); Srivastava and Teo (2009)]. Moreover, in order to
address the utilitarian drivers of using e-government services, our research model also incorporates
Kourouthanassis et al. /A complexity theory approach to explain e-government services adoption
Twenty-Fourth European Conference on Information Systems (ECIS), İstanbul,Turkey, 2016 5
citizens’ perceived net benefits of e-government services as an inherent cognitive value. Net benefits
reflect the efficiency and performance welfares for citizens deriving from the usage of an e-
government service (Prybutok et al. 2008) and have been shown to influence usage behaviour (Scott et
al. 2011). The affective angle of this research examines the emotional cues of citizens when using e-
government services. Emotions are distinguished to positive and negative based on their valence
(Scherer et al. 2013). Positive emotions are defined as the extent to which a citizen feels such emo-
tions as pleasure, joy or pride when using the service, while negative emotions refer to the extent to
which a citizen feels emotions related to anger, disappointment, or sadness. Both emotion categories
have been reported to influence adoption behaviour in the context of electronic services (Pappas et al.
2013; Pappas et al. 2016).
However, our analysis suggests that there is an interaction between affective and cognitive factors,
which makes it unclear whether we can assume that a particular factor may dominate adoption behav-
iour and, more importantly, whether there are combinations of these factors that better explain e-
government services adoption and use. To this end, we posit that although the aforementioned drivers
of e-government adoption also matter individually, the synergetic nature between them creates a com-
plex, multidimensional phenomenon, in which the configuration of the adoption drivers is more im-
portant than the individual drivers. This line of reasoning leads to a conceptual framework in order to
explain and better understand citizens’ adoption behaviour in e-government settings based on com-
plexity theory.
Complexity theory incorporates the principle of equifinality, based on which the outcome of interest
can be explained equally by alternative sets of causal conditions that combine in sufficient configura-
tions for the outcome (Fiss 2011; Woodside 2013). In our case, the adoption of e-government services
involves the combination and co-alignment of cognitive adoption values and affective adoption values
(i.e., emotions) with no specific form of co-alignment available as an a priori benchmark. Instead, high
adoption of e-government services may be achieved through different combinations of the causal fac-
tors. For example, emotional factors may affect users when they choose a channel to interact with the
government (Ebbers et al., 2008). In addition, mixed evidence exists regarding the effects of emotional
processing on trust in government organizations (Grimmelikhuijsen 2012), which in turn may affect
the adoption of e-government services. However, the existence of positive or negative emotions may
not always have an equivalent effect on citizens’ intention to interact with government services
(Zavattaro et al. 2015), indicating that various factors may combine together with emotions in order to
explain citizens’ behaviour. In addition, emotions have been found to have a positive effect on citi-
zens’ trust beliefs and perceived benefits towards the service provider, in the context of electronic me-
diated environment (Dai et al. 2015). However, the multidimensional nature of emotions indicates that
they may have both positive and negative effects on factors such as trust, net benefits or behaviour
(Beaudry & Pinsonneault, 2010; Pappas et al., 2013). Such complex interactions between affective and
cognitive perceptions and their combined influence to adoption behaviour may not be fully captured
and examined through the employment of traditional variance-based analysis methods, such as regres-
sion analysis and SEM (Pappas et al., 2016).
Indeed, complexity theory proposes the occurrence of causal asymmetry. Causal asymmetry means
that for an outcome to occur, the presence and absence of a causal condition depend on how this con-
dition combines with one or more others (Fiss, 2011; Woodside 2013). In this case, causal asymmetry
implies that different values of the same causal condition (i.e., positive beliefs and negative beliefs)
may appear in the combinations that explain e-government services adoption depending on how causal
conditions combine with themselves. For example, high perceptions of e-government adoption may be
achieved through both high and low perceptions of trust in the government depending on citizens’ per-
ceptions on the remaining causal factors. A variance-based analysis approach would reveal only one
optimal configuration of outcomes that would explain adoption behaviour. Such configuration might
discard one or more hypothesized causal factors, even if theory suggests an association of the causal
factors with the outcome of interest, due to insufficient statistical loadings. Complexity theory sur-
Kourouthanassis et al. /A complexity theory approach to explain e-government services adoption
Twenty-Fourth European Conference on Information Systems (ECIS), İstanbul,Turkey, 2016 6
passes this limitation and provides additional depth to the analysis by revealing multiple recipes (i.e.,
combination of causal factors) that equally explain the outcome of interest. The following Venn dia-
gram (Figure 1) reflects the conceptual framework of the study, which depicts the relations between
the examined factors.
Cognitive Values
(Net Benefits,
Trust of the
government, Trust
of the service)
Affective Values
(Positive and
Negative
Emotions)
Behaviour
(Intention to use
eGov services)
Figure 1. Conceptual model
Based, on the above, we formulate the following research propositions:
Proposition 1. No single best configuration of citizens’ cognitive and affective perceptions leads to
high intention to use e-government services; instead, multiple, equally effective configurations of
causal factors exist, which commonly lead to high usage intentions.
Proposition 2. Single causal adoption values may be present or absent within configurations for citi-
zens’ high intention to use e-government services, depending on how they combine with other causal
conditions.
3 Research Methodology
3.1 Data Collection
The survey was conducted in May-June 2015. A snowball sampling methodology was used to recruit
participants, as it gives access to a representative sample with an interconnected network of people.
The research instrument controls the prospective participants for their experience with e-government
services. The researchers contacted people with established experience with e-government services.
Similarly, the latter turned to their personal or business contacts (e.g., friends, relatives, colleagues
etc.) with established e-government experience. The participants were asked to answer based on eval-
uations created after using of e-government services. It was made clear that there was no reward for
the respondents, the participation was voluntary and that the study was confidential. Data were col-
lected by means of an online questionnaire. Respondents with no previous experience with e-
government services were excluded from the study. Finally, 613 responses were collected out of which
502 had previous experience with e-government services and comprise our analysis sample.
Kourouthanassis et al. /A complexity theory approach to explain e-government services adoption
Twenty-Fourth European Conference on Information Systems (ECIS), İstanbul,Turkey, 2016 7
3.2 Sample
The sample of respondents consists of more women (58.4%) than men (41.6%). The majority of the
respondents (41%) belonged to the age group 18-28. Further, 12.5% belonged to the age group 29-35,
and 16.5% belonged to the age group 36-45. Almost 29.9% were 46 years old or older. Regarding
their occupation, the sample consists of almost equally (27%) freelance professionals and students,
with the rest working for the private (18.7%) or public (17.9%) sector, and 8.4% are retired. Finally,
regarding experience with e-government services almost half (51%) of the sample uses e-government
services at least once per month.
3.3 Measures
The questionnaire consisted of two parts. The first part included questions on the demographics of the
sample (age, gender, occupation). The second part included measures of the various constructs identi-
fied in the literature review section. For testing our propositions, the survey included reflective scales
for the constructs of our conceptual model. Table 1 lists the operational definitions of the constructs in
this theoretical model as well as the studies from which the measures were adopted. Regarding emo-
tions, we adopt the work of Scherer et al. (2013), who attempt to understand emotions semantics. In
this study emotions were divided based on valence, following the work of Scherer et al. (2013) and
verified with an exploratory factor analysis, into positive and negative emotions. The appendix lists
the questionnaire items used to measure each construct, along with descriptive statistics and loadings.
Construct
Operational Definition
Source
Trust of the service
Users’ affective beliefs regarding the reliability
of the e-government services.
Kim et al. (2008)
Trust of the government
Users’ affective beliefs that the government will
behave ethically.
Bélanger and Carter (2008)
Net Benefits
Users’ beliefs regarding the benefits receiving by
using e-government services.
Prybutok et al. (2008)
Emotions
Measuring users’ emotions, based on valence,
when using e-government services.
Scherer et al. (2013)
Intention to use
Users’ intention to use e-government services.
Wang (2008)
Table 1. Constructs definition
3.4 Analysis methodology
Previous studies on e-government and IS adoption employ symmetric test to investigate their hypothe-
ses and calculate on the net effects on the desired outcomes. The main focus of tests such as multiple
regression analysis is to estimate the significance of the effects between variables or to compare the
effects among the variables between two or more models. However, focusing on net effects may be
misleading, usually because the observed net effects do not apply to all of the cases in a dataset
(Woodside 2014). Thus, we suggest quite a different approach from the commonly used structural
equation modeling in order to show the various combinations that may occur among the variables,
thereby increasing the contribution of the research.
This research employs the prescriptions of the fuzzy-set qualitative comparative analysis methodology
(fsQCA) to explore how affective and cognitive factors combine to explain the adoption of e-
government services. Opposed to variance-based statistical methods (e.g. structural equation model-
ling or partial-least squares based regression models) in which the independent variables ‘compete’
with each other to explain one or more dependent variables, fsQCA treats the hypothesized causal fac-
Kourouthanassis et al. /A complexity theory approach to explain e-government services adoption
Twenty-Fourth European Conference on Information Systems (ECIS), İstanbul,Turkey, 2016 8
tors as conditions that may be related to the phenomenon under investigation either by themselves or
in combination with one another (El Sawy et al. 2010). Hence, fsQCA does not compute a single, op-
timal, solution that attributes weights to the independent variables; instead, the methodology proposes
multiple alternative solutions, which require the presence or absence of each hypothesized causal fac-
tor (Rihoux and Ragin 2009). This is a fundamental difference from variance-based statistical methods
and calls for operationalization of the variables in the dataset.
In effect, fsQCA employs fuzzy set theory and Boolean algebra to evaluate whether the cases in the
dataset belong or not in a certain conceptual state. For example, in this research cases may be evaluat-
ed in order to assess whether an individual feels positive and negative emotions, believes that the gov-
ernment behaves ethically, perceives that e-government services are reliable, and perceives that he/she
receives concrete benefits from using the e-government services. Such operationalizations are captured
through fuzzy set membership scores ranging from 0 (non-membership to the set) to 1 (full member-
ship to the set). In-between scores indicate the distance of each case from the outbound scores. The
researcher may transform the cases’ original values to fuzzy-set membership scores by using special-
ized fs/qca software. This process is coined with the term ‘calibration’. In this research we used
fsQCA 2.0 developed by the University of Arizona and followed the calibration procedure employed
by Ordanini et al. (2014). With this method, the three qualitative anchors for the calibration were
based on the survey scale (seven-point Likert scale). The full membership threshold was fixed at the
rating of 6; the full non-membership threshold was fixed at 2; and the crossover point was fixed at 4.
The values of every variable were calibrated based on a linear function to fit into the three aforemen-
tioned thresholds. The software was also employed throughout the remaining methodology stages.
Fuzzy-set QCA identifies conditions or combinations of conditions that are necessary or sufficient to
explain an outcome (Ragin, 2008). Necessity of a condition implies that an outcome may not derive
without the presence of the condition; nevertheless, the condition alone is not able to produce the out-
come. Sufficiency of a condition implies that the condition alone is capable of producing the outcome.
In practice, if a solution includes the presence of only one condition, then this condition is sufficient to
produce the outcome. The necessary and the sufficient conditions lead to a distinction between core
and peripheral elements (Fiss, 2011). Core elements are the ones with a strong causal condition with
the outcome; peripheral elements are those with a weaker one. To estimate the sufficiency and/ or ne-
cessity of hypothesized conditions, fsQCA follows a Boolean minimization process based on truth
table analysis. The outcome of this process includes the generic combinations of conditions that are
sufficient for the outcome whilst remaining logically true. These are encapsulated in three solutions
that differ based on their complexity, named as complex, intermediate, and parsimonious. Of interest
is the parsimonious solution, which reduces the causal recipes to the smallest number of conditions
possible (Ragin, 2008). However, for purposes of results’ clarity and completeness, scholars report a
combination of the parsimonious and intermediate solutions and distinguish between core and periph-
eral conditions that lead to the outcome of interest (Fiss, 2011; Pappas et al., 2016).
4 Findings
4.1 Measurements
A confirmatory factor analysis is performed to verify the factor structure of the reflective constructs.
The constructs used in this research are evaluated in terms of reliability and validity. Reliability test-
ing, based on the Cronbach alpha indicator, shows acceptable indices of internal consistency since all
constructs exceed the cut-off threshold of 0.70. Establishing validity requires that average variance
extracted (AVE) is greater than 0.50, the correlation between the different variables in the confirmato-
ry models does not exceed 0.8 points, as this suggests low discrimination and that the square root of
each factor’s average variance extracted (AVE) is larger than its correlations with other factors (For-
nell & Larcker, 1981). The AVE for all constructs ranges between 0.59 and 0.77, all correlations are
Kourouthanassis et al. /A complexity theory approach to explain e-government services adoption
Twenty-Fourth European Conference on Information Systems (ECIS), İstanbul,Turkey, 2016 9
lower than 0.80, and square root AVEs for all constructs are larger than their correlations. The find-
ings are illustrated in Table 2.
Construct
Construct
Mean (SD)
CR
AVE
1
2
3
4
5
6
1.Trust of the service
4.09 (1.68)
0.91
0.77
0.88
2.Trust of the government
3.81 (1.47)
0.88
0.65
0.69
0.81
3.Net Benefits
4.26 (1.57)
0.87
0.69
0.66
0.59
0.83
4.Positive Emotions
2.43 (1.19)
0.90
0.75
0.19
0.21
0.24
0.87
5.Negative Emotions
2.05 (1.17)
0.94
0.63
-0.29
-0.26
-0.27
0.06
0.79
6.Intention to use
4.62 (1.67)
0.92
0.59
0.63
0.59
0.67
0.22
-0.29
0.77
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 are significant, p< 0.01). For discriminant
validity, diagonal elements should be larger than off-diagonal elements.
Table 2. Descriptive statistics and correlations of latent variables
4.2 fsQCA Results
Outcomes of the fuzzy set analysis for high intention to use e-government services are presented in the
following table (Table 3). The black circles (●) denote the presence of a condition, while the crossed-
out circles (⊗) indicate the absence of it (Fiss 2011). Core elements of a configuration are marked
with large circles, peripheral elements with small ones, and blank spaces are an indication of a do not
care situation in which the causal condition may be either present or absent. The solution table in-
cludes values of set-theoretic consistency for each configuration as well as for the overall solution,
with all values being above threshold (>0.75). Consistency measures the degree to which a subset rela-
tion has been approximated, whereas coverage assesses the empirical relevance of a consistent subset
(Ragin 2006). The overall solution coverage provides an indication as to what extent high intention to
use e-government services can be determined based on the set of configurations, and is comparable to
the R-square value reported in correlational methods (Woodside 2013). The results indicate an overall
solution coverage of 0.785, which suggests that a substantial proportion of the outcome is covered by
these five solutions.
For high intentions to use e-government services the solutions 1-5 presented in table 3 reflect combi-
nations of the presence and absence cognitive and affective values. All five factors examined appear
both as core and peripheral conditions in the solutions, suggesting their importance, which varies de-
pending on how one factor is combined with the others. In detail, the absence of both types of emo-
tions, along with the absence of trust of the government lead to high intention to use e-government
services regardless of the net benefits of the users (solution 1). Further, when emotions are absent,
then the presence of trust of the government leads to high intentions regardless of both trusting beliefs
and net benefits (solution 2). Next, the combination of trust of the service, trust of the government, and
net benefits coupled with low negative emotions will lead to high intention to use e-government ser-
vices, no matter the presence of absence of positive emotions (solution 3). On the other hand, when
both trust dimensions and net benefits are low, and negative emotions are low as well, then high posi-
tive emotions are able to predict high intention to use e-government services (solution 4). Finally,
when trusting beliefs, trust of the government, and positive emotions are low (i.e., absent), and users
experience high negative emotions then, only their combination with net benefits will be able to lead
to high intention to use e-government services (solution 5).
Kourouthanassis et al. /A complexity theory approach to explain e-government services adoption
Twenty-Fourth European Conference on Information Systems (ECIS), İstanbul,Turkey, 2016 10
Solution
Configuration
1
2
3
4
5
Adoption Values of e-Government Services
Affective Values
Positive Emotions
U
U
"
U
Negative Emotions
U
U
U
U
"
Cognitive Values
Trust of the service
"
"
U
U
Trust of the government
U
"
"
U
U
Net Benefits
#
U
"
Consistency
0.943
0.951
0.987
0.903
0.912
Raw Coverage
0.643
0.607
0.611
0.114
0.111
Unique Coverage
0.069
0.035
0.074
0.012
0.008
Overall solution consistency
0.921
Overall solution coverage
0.785
Note: Black circles (" ) indicate the presence of a condition, and circles with an “x” (
U
) indicate its absence.
Large circles indicate core conditions; small ones indicate peripheral conditions. Blank space indicate a “do not
care” condition.
Table 3. fsQCA Results for high intention to use e-government services
5 Discussion and Conclusions
This work suggests that in e-government, cognitive and affective values combine to form configura-
tions for predicting intention to use e-government services. Towards this end, a conceptual model is
constructed that serves as the basis to identify the aforementioned configurations. The model includes
five predominant values of e-government adoption, namely trust of the government, trust of the ser-
vice, positive and negative emotions, and net benefits of using the e-government service. The findings
indicate that there are multiple recipes leading to adoption of e-government services, which incorpo-
rate alternative combinations of the causal conditions thus, confirming both our research propositions.
Interestingly, the results highlight the importance of both affective and trust values for the adoption
and use of e-government services.
Indeed, adoption behaviour seems to be highly dependent to the (mandatory) absence of negative emo-
tions although in such cases where negative emotions are present, positive perceptions regarding the
derived net benefits from using the service are sufficient to warrant usage intention. Moreover, in case
e-government services do not also evoke positive emotions to citizens, trust values (either each factor
independently or both factors together) are the sole contributors of formulating positive adoption be-
haviour. On the contrary, in cases where trust perceptions are low, positive emotions or net benefits
comprise the determinant factors that certify high usage intention. These findings provide deeper un-
derstanding on the role of trust on e-government adoption since extant studies attribute equivalent
weight to institution-based trust and trust of the service (Bélanger and Carter 2008; Teo et al. 2008).
Instead, our study suggests that even one of these trust values may be required to be present in the ab-
sence of the other, provided that citizens do not feel any type of emotions towards the electronic ser-
vice.
The present study reveals a marginal influence of utilitarian drivers to e-government adoption behav-
iour, since they appear to be highly influential to user adoption in only one solution. We attribute this
observation to the increased familiarity of citizens with e-government services over the years. Indeed,
several e-government services are deeply integrated in everyday interactions of citizens with the gov-
ernment. For example, online tax filing is considered the de facto method of submitting tax declara-
tions. Therefore, the utilitarian value of the service blurs and more affective cues emerge that influ-
Kourouthanassis et al. /A complexity theory approach to explain e-government services adoption
Twenty-Fourth European Conference on Information Systems (ECIS), İstanbul,Turkey, 2016 11
ence the overall adoption behaviour. Nevertheless, utilitarian drivers seem to still hold strong in the
presence of negative emotions and when both trust values are low. In these cases, the net benefits of
the service take over the leading role to explain usage intention. This observation indicates the im-
portance of designing and delivering high quality e-government services, in terms of meeting citizens’
needs and goals. Specifically, the derived value of the service for citizens (e.g. improved convenience,
better customer service, increased access to information, to name but a few reported benefits) seems to
outweigh any feelings of mistrust towards the service and/ or the government as well as the induce-
ment of negative emotions when using the service.
This research has both theoretical and practical implications pertaining the adoption of information
systems and the design of e-government services in particular. First, we empirically demonstrate the
importance and synergetic nature of affective values, when combined with cognitive ones. This find-
ing paves the ground for the development of emotion-centric theories that explain the adoption of in-
formation systems in general and e-government services in particular. Furthermore, we highlight alter-
native paths that lead to high adoption behaviour when specific conditions are absent. These paths may
be used by public administrations for the design of e-government services. Indeed, public administra-
tions should minimize the development of negative emotions while users are visiting e-government
services. For example, e-government websites may sometimes suffer from poor information quality
which, in turn, may lead to frustrated citizens (Welch et al. 2005). Likewise, the design of e-
government services has received criticism for being guided by technological capabilities rather than
the actual needs of the users resulting to poor satisfaction and adoption (Bertot and Jaeger 2006). Pub-
lic administrations may employ user-centered strategies for the design of public websites in order to
better address user needs, evoke positive emotions and mitigate the formulation of negative emotions.
Verdegem and Verleye (2009) further support this argument by providing a starting discussion point
for such user-centered e-government strategies.
Finally, our study pinpoints the need for holistically examining the role of emotions on adoption be-
haviour since extant studies primarily conceptualize emotions uni-dimensionally through a single feel-
ing of particular valence and arousal. As with all empirical studies, there are some limitations. First,
the generalization of the findings should be performed with caution, since the sample comprises of
only Greek users of e-government services. Further, findings are based on self-reported data; for an
interdepended approach semi-structured interviews, observations and actual usage data may be used.
This paper differs from previous studies in IS and e-government adoption which focus on the net ef-
fects among variables, and adopts on complexity theory and employs fsQCA to better explain adop-
tion of e-government services. However, future studies should follow a similar approach to verify and
extend our findings, and also to extend theory in different contexts. Finally, although emotions in this
study are measured as a multidimensional concept, they are grouped only based on valence (i.e., posi-
tive and negative emotions) because, (i) no previous study takes this approach in the context of e-
government and, (ii) this research aims to serve as a precursor for future studies focusing on emotions
in e-government.
Refer ences
Al-Hujran, O., Al-Debei, M. M., Chatfield, A., and Migdadi, M. (2015). "The imperative of
influencing citizen attitude toward e-government adoption and use," Computers in Human
Behavior 53, 189-203.
Andersen, K. V., and Henriksen, H. Z. (2006). "E-government maturity models: Extension of the
Layne and Lee model," Government information quarterly 23 (2), 236-248.
Beaudry, A., and Pinsonneault, A. (2010). "The Other Side of Acceptance: Studying the Direct and
Indirect Effects of Emotions on Information Technology Use," MIS quarterly 34 (4), 689-710.
Kourouthanassis et al. /A complexity theory approach to explain e-government services adoption
Twenty-Fourth European Conference on Information Systems (ECIS), İstanbul,Turkey, 2016 12
Bélanger, F., and Carter, L. (2008). "Trust and risk in e-government adoption," The Journal of
Strategic Information Systems 17 (2), 165-176.
Bélanger, F., and Carter, L. (2009). "The impact of the digital divide on e-government use,"
Communications of the ACM 52 (4), 132-135.
Bertot, J. C., and Jaeger, P. T. (2006). "User-centered e-government: Challenges and benefits for
government Web sites," Government Information Quarterly 23 (2), 163-168.
Bertot, J. C., Jaeger, P. T., and Grimes, J. M. (2010). "Using ICTs to create a culture of transparency:
E-government and social media as openness and anti-corruption tools for societies," Government
information quarterly 27 (3), 264-271.
Carter, L., and Bélanger, F. (2005). "The utilization of e-government services: Citizen trust, innovation
and acceptance factors," Information Systems Journal 15 (1), 5-25.
Dai, H., Luo, X. R., Liao, Q., and Cao, M. (2015). "Explaining consumer satisfaction of services: The
role of innovativeness and emotion in an electronic mediated environment," Decision Support
Systems 70, 97-106.
Ebbers, W. E., Pieterson, W. J., and Noordman, H. (2008). "Electronic government: Rethinking
channel management strategies," Government Information Quarterly 25 (2), 181-201.
El Sawy, O. A., Malhotra, A., Park, Y., and Pavlou, P. A. (2010). "Research Commentary-Seeking the
Configurations of Digital Ecodynamics: It Takes Three to Tango," Information Systems Research
21 (4), 835-848.
Fiss, P. C. (2011). "Building better causal theories: A fuzzy set approach to typologies in organization
research," Academy of Management Journal 54 (2), 393-420.
Fu, J. R., Farn, C. K., and Chao, W. P. (2006). "Acceptance of electronic tax filing: A study of
taxpayer intentions," Information & Management 43, 109-126.
Grimmelikhuijsen, S. (2012). "Linking transparency, knowledge and citizen trust in government: An
experiment," International Review of Administrative Sciences 78 (1), 50-73.
Hong, S.-J., and Tam, K. Y. (2006). "Understanding the adoption of multipurpose information
appliances: The case of mobile data services," Information systems research 17 (2), 162-179.
Hung, S. Y., Chang, C. M., and Yu, T. J. (2006). "Determinants of user acceptance of the e-
Government services: The case of online tax filing and payment system," Government Information
Quarterly 23, 97-122.
Hwang, Y., and Kim, D. J. (2007). "Customer self-service systems: The effects of perceived Web
quality with service contents on enjoyment, anxiety, and e-trust," Decision support systems 43 (3),
746-760.
Johnson, D., and Grayson, K. (2005). "Cognitive and affective trust in service relationships," Journal
of Business Research 58 (4), 500-507.
Kim, D. J., Ferrin, D. L., and Rao, H. R. (2008). "A trust-based consumer decision-making model in
electronic commerce: The role of trust, perceived risk, and their antecedents," Decision Support
Systems 44 (2), 544-564.
Kourouthanassis, P., Boletsis, C., Bardaki, C., and Chasanidou, D. (2015). "Tourists responses to
mobile augmented reality travel guides: The role of emotions on adoption behavior," Pervasive and
Mobile Computing 18, 71-87.
Krania, E., Avgerinou, E., Limaki, E., Bartzis, G., and Mantzana, V. (2013). "E-prescribing in Greece:
Myth or reality," in Informatics, Management and Technology in Healthcare, J. Mantas and A.
Hasman (eds.), IOS Press, pp. 194-196.
Lean, O. K., Zailani, S., Ramayah, T., and Fernando, Y. (2009). "Factors influencing intention to use
e-government services among citizens in Malaysia," International Journal of Information
Management 29 (6), 458-475.
Lewis, J. D., and Weigert, A. (1985). "Trust as a social reality," Social forces 63 (4), 967-985.
Ordanini, A., Parasuraman, A., and Rubera, G. (2014). "When the Recipe Is More Important Than the
Ingredients A Qualitative Comparative Analysis (QCA) of Service Innovation Configurations,"
Journal of Service Research 17 (2), 134-149.
Kourouthanassis et al. /A complexity theory approach to explain e-government services adoption
Twenty-Fourth European Conference on Information Systems (ECIS), İstanbul,Turkey, 2016 13
Ozkan, S., and Kanat, I. E. (2011). "e-Government adoption model based on theory of planned
behavior: Empirical validation," Government Information Quarterly 28 (4), 503-513.
Pappas, I., Giannakos, M., Kourouthanassis, P., and Chrissikopoulos, V. (2013). "Assessing Emotions
Related to Privacy and Trust in Personalized Services," in Collaborative, Trusted and Privacy-
Aware e/m-Services, C. Douligeris, N. Polemi, A. Karantjias and W. Lamersdorf (eds.), Springer
Berlin Heidelberg, pp. 38-49.
Pappas, I., Kourouthanassis, P., Giannakos, M., and Chrissikopoulos, V. (2014). "Shiny happy people
buying: the role of emotions on personalized e-shopping," Electronic Markets 24 (3), 193-206.
Pappas, I. O., Kourouthanassis, P. E., Giannakos, M. N., and Chrissikopoulos, V. (2016). "Explaining
online shopping behavior with fsQCA: The role of cognitive and affective perceptions," Journal of
Business Research 69 (2), 794-803.
Prybutok, V. R., Zhang, X., and Ryan, S. D. (2008). "Evaluating leadership, IT quality, and net
benefits in an e-government environment," Information & Management 45 (3), 143-152.
Ragin, C. C. (2006). "Set relations in social research: Evaluating their consistency and coverage,"
Political Analysis 14 (3), 291-310.
Ragin, C. C. (2008). Redesigning social inquiry: Fuzzy sets and beyond, Wiley Online Library.
Rana, N., Dwivedi, Y., and Williams, M. (2015). "A meta-analysis of existing research on citizen
adoption of e-government," Information Systems Frontiers 17 (3) 2015/06/01, 547-563.
Rihoux, B., and Ragin, C. C. (2009). Configurational comparative methods: Qualitative comparative
analysis (QCA) and related techniques, Sage: Los Angeles, CA.
Rogers, E. M. (1995). Diffusion of Innovations, (4th ed.) Free Press: New York.
Rose, W. R., and Grant, G. G. (2010). "Critical issues pertaining to the planning and implementation
of E-Government initiatives," Government Information Quarterly 27 (1) 1//, 26-33.
Russell, J. A. (2009). "Emotion, core affect, and psychological construction," Cognition and Emotion
23 (7), 1259-1283.
Scherer, K., Shuman, V., Fontaine, J., and Soriano, C. (2013). "The GRID meets the wheel: assessing
emotional feeling via self-report," in Components of emotional meaning : A sourcebook, J.
Fontaine, K. Scherer and S. Soriano (eds.), Oxford University Press: Oxford, UK, pp. 281-298.
Scott, M., DeLone, W. H., and Golden, W. (2011) "IT quality and egovernment net benefits: a citizen
perspective," 19th European Conference on Information Systems, Helsinki, Finland, 2011.
Srivastava, S. C., and Teo, T. S. (2009). "Citizen trust development for e-government adoption and
usage: Insights from young adults in Singapore," Communications of the Association for
Information Systems 25 (1), 31.
Teo, T. S. H., Srivastava, S. C., and Jiang, L. (2008). "Trust and Electronic Government Success: An
Empirical Study," Journal of Management Information Systems 25 (3), 99-132.
Torres, L., Pina, V., and Royo, S. (2005). "E-government and the transformation of public
administrations in EU countries: Beyond NPM or just a second wave of reforms?," Online
Information Review 29 (5), 531-553.
Ubaldi, B. C. (2011). "The impact of the Economic and Financial crisis on e-Government in OECD
Member Countries," European Journal of ePractice 11, 5-18.
Van de Walle, S., and Bouckaert, G. (2003). "Public Service Performance and Trust in Government:
The Problem of Causality," International Journal of Public Administration 26 (8-9) 2003/08/01,
891-913.
Van Dijk, J. A., Peters, O., and Ebbers, W. (2008). "Explaining the acceptance and use of government
internet services: A multivariate analysis of 2006 survey data in the Netherlands," Government
Information Quarterly 25 (3), 379-399.
Venkatesh, V., Morris, M. G., Davis, G. B., and Davis, F. D. (2003). "User acceptance of information
technology: Toward a unified view," MIS Quarterly 27 (3), 425-478.
Venkatesh, V., Thong, J. Y. L., Chan, F. K. Y., Hu, P. J.-H., and Brown, S. A. (2011). "Extending the
two-stage information systems continuance model: incorporating UTAUT predictors and the role
of context," Information Systems Journal 21 (6), 527-555.
Kourouthanassis et al. /A complexity theory approach to explain e-government services adoption
Twenty-Fourth European Conference on Information Systems (ECIS), İstanbul,Turkey, 2016 14
Verdegem, P., and Verleye, G. (2009). "User-centered E-Government in practice: A comprehensive
model for measuring user satisfaction," Government Information Quarterly 26 (3), 487-497.
Wang, Y.-S., and Liao, Y.-W. (2008). "Assessing eGovernment systems success: A validation of the
DeLone and McLean model of information systems success," Government Information Quarterly
25 (4), 717-733.
Wang, Y. S. (2008). "Assessing e-commerce systems success: a respecification and validation of the
DeLone and McLean model of IS success," Information Systems Journal 18 (5), 529-557.
Welch, E. W., Hinnant, C. C., and Moon, M. J. (2005). "Linking citizen satisfaction with e-
government and trust in government," Journal of public administration research and theory 15 (3),
371-391.
Woodside, A. G. (2013). "Moving beyond multiple regression analysis to algorithms: Calling for
adoption of a paradigm shift from symmetric to asymmetric thinking in data analysis and crafting
theory," Journal of Business Research 66 (4), 463-472.
Woodside, A. G. (2014). "Embrace• perform• model: Complexity theory, contrarian case analysis, and
multiple realities," Journal of Business Research 67 (12), 2495-2503.
Wu, P.-L., Yeh, S.-S., and Woodside, A. G. (2014). "Applying complexity theory to deepen service
dominant logic: Configural analysis of customer experience-and-outcome assessments of
professional services for personal transformations," Journal of Business Research 67 (8), 1647-
1670.
Zavattaro, S. M., French, P. E., and Mohanty, S. D. (2015). "A sentiment analysis of US local
government tweets: The connection between tone and citizen involvement," Government
Information Quarterly 32 (3), 333-341.
Zhang, P. (2013). "The Affective Response Model: A Theoretical Framework of Affective Concepts
and Their Relationships in the ICT Context," MIS Quarterly 37 (1), 247-274.
Appendix
Scale items with mean, standard deviation and standardized loading
Construct and scale items
Mean
S.D.
Loading
Trust of the service, CA = 0.95
1. Government websites are trustworthy in general
4.25
1.62
0.87
2. Government websites give the impression that they keep their promises
and commitments.
4.09
1.78
0.89
3. I believe that Government websites have my best interests in mind.
3.93
1.86
0.87
Trust of the government, CA = 0.94
1. I think I can trust state government agencies
3.74
1.57
0.79
2. State government agencies can be trusted to carry out online transac-
tions faithfully
4.07
1.69
0.85
3. I trust state government agencies keep my best interests in mind
3.70
1.57
0.81
4. In my opinion, state government agencies are trustworthy
3.75
1.53
0.78
Net Benefits, CA = 0.92
1. Overall, I am satisfied with the information technologies of e-
government services.
4.11
1.65
0.85
2. Overall, there has been a positive impact as to how much my perfor-
mance was improved by the aid of the information technologies of e-
government services.
4.11
1.79
0.83
3. Overall, there has been a positive impact as to how much the perfor-
mance of e-government services was improved by the aid of infor-
mation technologies.
4.57
1.64
0.81
Kourouthanassis et al. /A complexity theory approach to explain e-government services adoption
Twenty-Fourth European Conference on Information Systems (ECIS), İstanbul,Turkey, 2016 15
Intention to use, CA = 0.97
1. Assuming that you have access to the e-government service, you intend
to reuse it.
4.57
1.71
0.87
2. You will reuse the e-government service in the future.
4.70
1.69
0.86
3. You will frequently use the e-government service in the future.
4.59
1.76
0.87
Emotions
Mean
SD
Loading
Mean
SD
Loading
Positive Emotions, CA = 0.92
1. Pleasure
2.53
1.54
0.88
6. Contentment
2.75
1.57
0.82
2. Joy
2.28
1.45
0.88
7. Admiration
2.32
1.52
0.86
3. Pride
2.20
1.44
0.83
8. Love
1.79
1.26
0.74
4. Amusement
2.30
1.61
0.76
9. Relief
2.57
1.56
0.69
5. Interest
3.09
1.74
0.63
Negative Emotions, CA = 0.93
1. Anger
2.29
1.67
0.83
6. Disappointment
2.83
1.88
0.75
2. Hate
1.84
1.47
0.83
7. Shame
2.16
1.62
0.81
3. Contempt
2.28
1.66
0.82
8. Regret
1.75
1.26
0.75
4. Disgust
2.00
1.62
0.85
9. Guilt
1.58
1.14
0.72
5. Fear
2.06
1.59
0.65
10. Sadness
2.09
1.56
0.75
11. Compassion
1.75
1.24
0.65
CA; Cronbach alpha
