THE EFFECTS OF NEUROTICISM AND AGREEABLENESS
Master thesis, MscBA, specialization Human Resource Management University of Groningen, Faculty of Economics and Business
February 14, 2016 Harmjan Rusticus Student number: 2578921 Bloemstraat 47-26 9712 LC Groningen Tel: +31 (0)6-25321564 E-mail: h.rusticus@student.rug.nl Supervisors/ University S. Täuber K. M. Bijlsma-Frankema
ABSTRACT
INTRODUCTION
Trust has important interpersonal and organizational consequences and a clear set of core definitions, antecedents and consequences have been found and supported by scholars in the field of organization studies (Bijlsma-Frankema, Wisse, Täuber, Sanders & Sitkin, 2016). Distrust however, as a distinct concept has received less attentions, since it has been seen as the lower end of the construct of trust for a long while (Hardin 2004; Luhmann, 1979; Mayer et al., 1995; Robinson, 1996; Rotter, 1980). More recently, however scholars start to become convinced of and support (see Bijlsma-Frankema, Sitkin & Weibel, 2015), aided by empirical evidence, a different view of trust and distrust. In this new view, initiated by Sitkin and colleagues (Sitkin & Roth, 1993; Sitkin & Stickel, 1996), trust and distrust are distinct constructs, with different antecedents, consequences, and process dynamics. Henceforth, scholars have started to define the core constructs and causal dynamics of distrust. In my study I will build upon this new view by focusing on consequences of distrust, building on the insights gathered so far.
Recently, Bijlsma-Frankema et al. (2015), based on a case study of a court of law, proposed core constructs and the causal dynamics of the cycle of distrust development. The current study extends on the study by Bijlsma-Frankema et al. (2015) by testing a part of their cyclical dynamic model by conducting an experiment (the selection can be found in figure 1). The study by Bijlsma-Frankema et al. (2016) focused on intergroup distrust, while my study focuses on the development of distrust in same status relations between individuals.
Bijlsma-Frankema et al. (2015) propose that once distrust has emerged it will start to develop in an amplifying cycle. Three broad types of factors are included in the amplifying cycle of distrust: negative perceptions and expectations, negative behaviours, and within-group convergence (which is specific to interwithin-group distrust). Negative perceptions entail both negative attributions (of events, intentions, and motives with regards to the other group) and perceived value incongruences and its associated vulnerabilities. In time they both will be increased and become pervasive, in which within-group convergence plays a role. The negative behaviours are diminished cooperation and avoidance of interaction, which are increased by negative reciprocity (Bijlsma-Frankema et al., 2015). The relations between negative behaviours and negative perceptions are two-fold: negative behaviours flow from and are justified by negative perceptions and expectations. In the model of Bijlsma-Frankema et al. (2015), one of the hardest variables to model in a testable way is negative reciprocity, a series of interactions in which parties react to each other’s actions. The present study contributes by proposing a preliminary way to model negative reciprocity, in order to test this crucial element in the distrust cycle.
the distrusted other in reaction to diminished cooperation of the other in reaction to one self’s actions. Diminished cooperation, a negative behaviour that is expected to grow more negative over time, will in turn be justified by negative attributions of the other’s behaviours, which will also cumulate over time to result in an intensification of distrust.
In the current research I will also explore two additional factors that may have an effect on this behavioural and cognitive spiral. It is theorized that personality has an impact on the relationship between distrust and diminished cooperation. Since personality is related to differences in behaviour patterns, cognition and emotion (Mischel, Shoda, & Smith, 2004). A model that has been proven to be useful for assessing individuals is that of the five-factor model of personality, also called the Big Five (McCrae & John, 1992). Two of the Big Five factors seem to be related to trust and distrust. Research by Bergman, Small, Bergman, and Rentsch (2010), and by Omodei and McLennan (2000) has shown that people with a low emotional stability (high neuroticism) tend to have low trust in others. Emotional stability, with a few exceptions, was significantly related to some workplace trust dimensions (Wöhrle, Oudenhoven, Otten, & Van der Zee, 2014). Next to neuroticism, agreeableness was also related to trust. Research by Mooradian, Renzl, and Matzler (2006) and by Evans and Revelle (2008) has shown that agreeableness positively influences trust. However since trust and distrust are seen as distinct concepts, it is interesting to research if they have an effect on the development of distrust as well. Henceforth, both neuroticism and agreeableness will be taken along in the research of the self-amplifying cycle of distrust.
are further described in the theoretical framework section. The explanation of the experiment, its measures and manipulations will be presented in the method section.
The research can be interesting for organizations since it tries to discover in what ways distrust develops and whether certain personality constructs are involved in the development. Distrust is an important phenomenon that needs to be understood by organizations, since it can be very harmful for the organization and its members. Since for example the cooperation between colleagues can be affected by the development of distrust. Organizations could try to develop interventions to stop the emergence and development of distrust. Furthermore they could detect which type of person is more prone to developing distrust.
FIGURE 1
The Self-Amplifying Cycle of Intergroup Distrust
THEORETICAL FRAMEWORK Relationship between trust and distrust
There are two approaches in distinguishing trust and distrust. One of the approaches is seeing trust and distrust on a continuum, in which distrust is on the lower end (Hardin 2004; Luhmann, 1979; Mayer et al., 1995; Robinson, 1996; Rotter, 1980). In this view, low trust and distrust are the same. The other approach is viewing the concepts as separate, since they both have different antecedents, consequences, and process dynamics (Benamati, Serva & Fuller, 2006; Chang & Fang, 2013; Cho, 2006; Dimoka, 2010; Komiak & Benbaset, 2008; Lewicki, McAllister & Bies, 1998; Ou & Sia, 2010; Sitkin & Roth, 1993; Sitkin & Stickel, 1996; Tomlinson & Lewicki, 2006). Lewicki et al. (1998) stated that both trust and distrust involve a movement towards certainty, in which trust has to do with the expectations of things one hopes for and distrust concerns the expectations of things one fears. They see the concepts as related but independent dimensions. Trust and distrust according to them are not on the opposing side of each other. According to Bijlsma-Frankema et al. (2015) empirical tests show support for conceptualizing distrust as a separate concept from trust. This has been shown by early measurement and construction and validation studies by Clark and Payne (1997), Constantinople (1969), and Wrightsman (1974). More recent advanced construct discrimination studies support this even more (Benamati et al., 2006; Chang & Fang, 2013; Cho, 2006; Komiak & Benbasat, 2008; Ou & Sia, 2010). In the current research the concepts are seen as separate from each other and only distrust will be researched.
Trust
positive expectations of the intentions or the behaviour of another” (Rousseau, Sitkin, Burt, & Camerer et al., 1998: 395). For a long time, trust has been seen as an important factor in the organizational and interpersonal context and it has some important consequences (Fox, 1974; Mayer, Davis, & Schoorman, 1995; Zucker, 1986). Trust can be analysed at the interpersonal, organizational, and interorganizational level (e.g. Dirks & Ferrin, 2002; Rousseau et al., 1998; Schoorman, Mayer, & Davis, 2007). Furthermore, it has a clear set of core definitions, constructs and important variables. Distrust, on the other hand, is a different concept which has not been getting a lot of attention in the literature (Bijlsma-Frankema et al., 2015).
Distrust
up with a very specific definition of intergroup distrust: “the shared unwillingness of a group to accept vulnerability, based on pervasive negative perceptions and expectations of the other group’s motives, intentions, or behaviours”. Since this definition is focused on intergroup distrust and not interpersonal trust the following definition will be used: the unwillingness of an individual to accept vulnerability, based on pervasive negative perceptions and expectations of the other individual’s motives, intentions, or behaviours (Bijlsma-Frankema et al., 2015). In the next paragraphs the development of distrust will be addressed.
Distrust emergence and development
distrust, presenting a downward spiral for the trusting relationship (Sherif, Harvey, White, Hood, & Sherif, 1961; Fox, 1974; Sitkin & Roth, 1993; Sitkin & Stickel, 1996; Zand, 1972).
Negative behavioural reciprocity: Diminished cooperation
Once distrust has emerged, individuals feel the need to reciprocate the negative behaviours displayed by others, which is called negative reciprocity (Bijlsma-Frankema et al., 2015). Gouldner (1960) stated that recipients of harm can feel a normative justification to retaliate, thus creating an eye for an eye situation. The negative behaviour that will be researched is that of diminished cooperation, specifically “diminished cooperation in the realm of formal, organizational prescribed relations” (Bijlsma-Frankema et al., 2015: 1031). Previous research by Deutsch (1971), Fox (1974), Cho (2006), and Bijlsma-Frankema et al. (2015) has shown that cooperation is one of the main consequences of distrust. Bijlsma-Frankema et al. (2015: 1031) defined diminished cooperation as: “The decline of the willingness to meet the preferences and desires of the other group. Signifying a reciprocal diminishing willingness to act cooperatively to support the other group’s values and valued goals.” More specifically, in personal communication, Bijlsma-Frankema defined cooperation as: “to put in resources (i.e. energy, attention, time) to further the quality of the work relation and subsequent performance”. Diminished cooperation is eventually expected to grow more negative over time.
Hypothesis 1: Distrust decreases the willingness to cooperate.
Negative perceptions and expectations: Negative attributions
attributions of the other’s behaviours. Next to the intensification of negative attributions through negative reciprocity, negative attributions will accumulate on its own as well, as the sequence of actions and reactions of the other (Bijlsma-Frankema, et al., 2015).
Hypothesis 2: A decreased willingness to cooperate is positively related to negative attributions.
Prospective distrust
The intensified negative attributions will have their effect on distrust; therefore a cyclical model is created. Bijlsma-Frankema et al. (2015) state that negative attributions affect distrust in a direct or indirect way. With the indirect way, it goes through the value incongruence perceptions. In the current research, only the direct way will be researched. Therefore negative attributions is not only a consequence of distrust through negative reciprocity, but also an intensifier of distrust, because the negative perceptions may increase the perceived vulnerability and negative expectations on which distrust is based. Therefore the effect of negative attributions on distrust completes the cycle and makes it into a self-amplifying process since distrust and negative attributions justify negative behaviour, in this case diminished cooperation. The basic conceptual model can be found in figure 2.
Hypothesis 3: Negative attributions are positively related to distrust. FIGURE 2
As discussed before the effects of neuroticism and agreeableness on this
self-amplifying cycle will be researched. The following paragraphs will discuss how these factors relate to the factors of distrust, diminished cooperation, and negative attributions.
Neuroticism/emotional stability
The first factor that will be discussed is that of neuroticism. Neuroticism is one of the personality dimensions of the five-factor model, also called the big-five factor model of personality (McCrae & John, 1992). According to them, neuroticism is the individual difference in the propensity to undergo distress, and the resultant differences in behavioural and cognitive styles. People who score high on neuroticism experience chronic negative affect (Watson & Clark, 1984). Furthermore they are more likely to develop a variety of psychiatric disorders (Zonderman, Stone, & Costa, 1989). People high on neuroticism can experience feelings as depression, frustration, guilt, self-consciousness, and a recurring nervous tension. This is associated with a low self-esteem, a poorer control of cravings and impulses, irrational thinking, somatic complaints, and ineffective coping (McCrae & Costa, 1987). People who are low on neuroticism do not necessarily have a better mental health, but are calmer, more even-tempered, relaxed and composed (McCrae & John, 1992). The trait of emotional stability is highly negatively related to neuroticism (Leone, Van der Zee, Van Oudenhoven, Perugini, & Ercolani, 2005; Van der Zee & Van Oudenhoven, 2000).
Relationship between neuroticism, distrust, and cooperation
Wöhrle et al. (2015) emotional stability was with a few exceptions linked to workplace trust dimensions. This is supported by research from Evans and Revelle (2008) who found that neuroticism was negatively correlated with trust, more specifically individuals with low emotional stability tend to be less willing to make themselves vulnerable to others and because of this are less likely to think that others are worthy of their trust. People low in emotional stability are prone to focus on undesirable aspects of a situation and can see a neutral situation as a danger (Calvo & Eysenck, 2000; Derryberry & Reed, 1998). People low in emotional stability see others as less trustworthy than people high in emotional stability. Furthermore previous research discovered a significant relationship between emotional stability and the propensity to trust (Evans & Revelle, 2008).
Hypothesis 4: Neuroticism moderates the positive relationship between distrust and diminished cooperation. When neuroticism is high, the relationship between distrust and diminished cooperation is stronger than when neuroticism is low.
Agreeableness
Next to neuroticism, agreeableness is also relevant for this research, and it is a factor in the Big Five model as well (McCrae & John, 1992). According to Digman (1990) agreeableness has characteristics like altruism, caring, emotional support, and nurturance at the positive side of the dimension, and hostility, indifference to others, jealousy at others, self-centeredness, and spitefulness at the negative side. The opposite side of agreeableness can be seen as antagonism (Graziano & Eisenberg, 1997). Costa, McCrae, and Dye (1991) noted a cluster of attributes that form a blend of warmth and submission, which includes modesty, trust, and compliance. This definition already includes a link to trust. This link will be discussed further in the next paragraph.
Relationship between agreeableness, distrust, and cooperation
Similarly to neuroticism, there is also a clear connection between agreeableness and trust, therefore it is also interesting to study the effects of this factor on distrust and on its amplifying cycle developed by Bijlsma-Frankema et al. (2015) as well. People scoring high on agreeableness are expected to be more willing to accept vulnerability, since they are more motivated to maintain positive interpersonal relationships (Graziano & Eisenberg, 1997). The stronger willingness is expected to lessen the consequences of distrust, more specifically diminished cooperation. Furthermore research by McCullough et al. (2001) and by Olson and Weber (2004) found that agreeableness is negatively related to the motive of vengeance. Henceforth people scoring high on agreeableness are less inclined to diminish their cooperation as a reaction to the other parties’ behaviours.
Hypothesis 5: Agreeableness moderates the positive relationship between distrust and diminished cooperation. When agreeableness is high, the relationship between distrust and diminished cooperation is weaker than when agreeableness is low.
FIGURE 3 Full conceptual model
METHOD Participants and design
sampling, therefore no participants were sampled incorrectly. Without removing outliers the data is expected to be more representative of the population (Orr, Sackett, & DuBois, 1991). Furthermore bootstrapping was used in the analyses to lessen the effects of outliers. The participants were either compensated with course credits or received a small amount of money wired to their accounts. The participants performed the experiment individually. The experiment was part of a study which consisted of three parts, in which this experiment was the middle part. The data regarding the participant’s gender and age were gathered from the third part of the study, and were coupled by matching the end time of the second part and start time of the third part and IP addresses. The task of the experiment consisted of three rounds and had 5 cycles per round. Participants were randomly assigned to a condition of a 2 (no doubt vs. some doubt) by 2 (Sim decline vs. Sim recovery) design. The experiment was conducted at the FEB research lab located on the first floor of the Duisenberg building. The materials that were needed were a confined space with a personal computer and Qualtrics to program the experiment in, allow the participants to give inputs, and to allow the experimenter to gather the data from the participants inputs.
Procedure
with the amount Sim invested, which depends on the month they are in and which condition. The conditions are: Sim decline and Sim recovery. These amounts will be further discussed in the manipulation section. The participants are then asked a question regarding positive attributions to Sim and one regarding negative attributions. These four parts will repeat for a total of five cycles or months after which a questionnaire will follow, consisting of questions regarding distrust, trust, cooperation, and avoidance. Of which only distrust is used in the current study. After this questionnaire the next stage will start, consisting of the same steps as discussed before. After the second stage, participants will fill in the same questionnaire they filled in after the first stage. They will then continue with the last five cycles or months after which they are asked to fill in a questionnaire similar to the end of stage one and two, thus consisting of questions relating to distrust, trust, cooperation, and avoidance. But in addition also have questions about negative reciprocity norms, and pervasiveness regarding living, studying, and social life. In the end they are asked what they think the subject and hypotheses of the study are. After this they are thanked and offered an opportunity to pose questions or give comments. When they are finished they report back to the experimenter and are registered for their participation in order to get payment or credits.
Manipulations
Distrust. As discussed before, the participants were put into either the no doubt or
does not really slack but does not work very hard as well. But this information is based on a rumour and is not based on direct communication with Sim’s group members. These two manipulations were used to create variance in distrust at the first time distrust was measured, which is after the first stage. The some doubt manipulation was preferred over a doubt condition, since this study wanted to discover how distrust develops, and this requires a low to moderate start of distrust. The manipulations were developed by K.M. Bijlsma-Frankema.
Investment Sim. As discussed before there are two conditions with regards to the
FIGURE 4
Monthly investment by Sim
Measures
Distrust. The amount of distrust was measured at three time intervals, after the first,
second and third stage. The end of the first stage is therefore seen as the starting point of the current study. The amount of distrust was measured by a tool developed by Bijlsma-Frankema et al. (2016). This is a scale with eight items. Items 1,2,3,7, and 8 were developed by these authors, and 4,5, and 6 were taken from the caution scale of Yamagishi and Yamagishi (1994) and from the distrust scale of Greenglass & Julkunen (1989). Items measured are for instance: “I fear that this person will treat me unfairly”, “This person will lie if that suits his/her purpose”, and “If I am not alert, this person will take advantage of me” (1= totally disagree, 7= totally agree). The item list can be found in appendix C. The amount of distrust in the Sim decline condition at the three intervals was measured by taking the average rating of all the eight items. After stage 1 (distrust 1) this resulted in a score that ranged from 1.38 to 6.75 (M = 4.23) and a Cronbach’s alpha of .92. After stage 2 (distrust 2) this resulted in a range from
0 5 10 15 20 25 30 35 40 45 50 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1.00 to 7.00 (M = 5.35) and a Cronbach’s alpha of .95. After stage 3 (distrust 3) the scores ranged from 1.63 to 7.00 (M = 5.86) and a Cronbach’s alpha of .94.
Cooperation development. The development of cooperation was measured by
calculating the difference between the investment scores in cycle one and cycle fifteen (Cooperation development = Investment cycle 1 – Investment cycle 15). This was done in order to see a development of cooperation between the beginning and end of the experiment. The variable cooperation development will be used to determine whether there is diminished cooperation and how this relates to the other variables, with a positive score representing diminished cooperation. With only the Sim decline manipulation selected, the scores on this variable ranged from -50.00 to 100.00 (M = 48.49).
Negative attributions development. Negative attributions development was measured
by calculating the difference between the scores of negative attributions in cycle one and cycle fifteen (Negative attributions development = Negative attributions 15 – Negative attributions 1). Negative attributions were measured after each cycle with the following question: “This person lets me down on purpose” (1= totally disagree, 7= totally agree). With only the Sim decline manipulation selected, the scores on the variable negative attributions development ranged from -3.00 to 6.00 (M = 4.24).
Big five (Emotional stability/Neuroticism and Agreeableness). The participants’
appendix D. The negative keyed items were recoded and the 10 items per factor were formed into two constructs. With only the Sim decline manipulation selected, this resulted in a score on neuroticism that ranged from 1.60 to 6.00 (M = 3.75) with a Cronbach’s alpha of .87. The score on agreeableness ranged from 3.70 to 6.70 (M = 5.35) with a Cronbach’s alpha of .70.
Analyses
Main model. The main part and therefore the first three hypotheses were tested with a
linear multiple regression, more specifically a serial mediation model. The Process procedure of Hayes (2013) was used (model 6), which is a tool that uses a traditional least squares analysis for estimating direct and indirect effects in simple or multiple mediator models. First Process was used to analyse the direct effect of distrust (after stage) 1 on distrust (after stage) 3. Second, it was used to analyse the indirect effect of distrust 1 on distrust 3 through cooperation development. Third, it was used to analyse the indirect effect of distrust 1 on distrust 3 through negative attributions development. Fourth, it was used in order to analyse the indirect effect of distrust 1 on distrust 3 through cooperation development and negative attributions development in series. The main part of the research model can be found in figure 5. In all of the analyses in the current study, the significance level is set at 0.05 (5%).
FIGURE 5
Main part research model
Distrust 1 Distrust 3
Negative attributions development Cooperation
Moderators. The second part of the analyses will test hypothesis 4 and 5 by using a
linear multiple regression. The interaction effects of the moderators will be analysed separately and by using a smaller part of the model. These separate models can be seen in figure 6. The models were analysed separately since it reduces the complexity of the analyses and there is no possibility within Process to test a moderated serial mediation model. The Process macro (model 1) by Hayes (2013) was used to analyse the interaction effect of the moderators by using a multiple traditional least squares regression.
FIGURE 6
Research models moderators
Additional analyses. Next to the main analyses a couple of additional analyses were
performed, since the analysis of the main model yielded results that contradicted hypothesis 2, proposing a positive relation between cooperation development and negative attributions development. In this case negative attributions development will be analysed as a moderator in the main model. More specifically the moderating effect of negative attributions development on the relationship between distrust 1 and cooperation development and on the relationship between cooperation development and distrust 3 will be analysed. The resulting models can be found in figure 7. The Process macro (model 1) (Hayes, 2013) was used to analyse these models with a multiple traditional least squares regression.
FIGURE 7
Research models additional analyses
RESULTS Descriptive Statistics
The overall descriptive statistics and Pearson zero-order correlations between variables are presented in Table 1. Both cooperation development (r = .50, p < 0.01) and age (r = -.28, p < 0.01) correlate with distrust 1. Cooperation development correlates with negative attributions development (r = -.38, p < 0.01). Additionally distrust 1 (r = .52, p < 0.01), cooperation development (r = .27, p < 0.01), and negative attributions development (r = .24, p < 0.05) correlate with distrust 3. The variable gender correlates with neuroticism (r = .36, p < 0.01), agreeableness (r = .27, p < 0.01), and cooperation development (r = -.24, p < 0.05). Age correlates with distrust 1 (r = -.28, p < 0.01), neuroticism (r = .21, p < 0.05), distrust 3 (r = -.23, p < 0.05), and gender (r = .22, p < 0.05). Since both gender and age correlate with some of the independent and dependent factors, they will both be included as control variables. The effect of gender on the moderators was further explored in the Sim decline condition, and it was discovered that males (M = 3.37) score significantly lower than females (M = 4.13) on neuroticism (p < 0.01). Additionally, males (M = 5.19) scored significantly lower on agreeableness compared to females (M = 5.54) as well (p < 0.01). When looking at the conditions (doubt or no doubt), there were no effects discovered on the distribution of age
and gender and there were also no significant differences in the factors researched in the hypothesis testing.
TABLE 1
Descriptive Statistics and Pearson Zero-order Correlations among the Study Variables
Variable Mean SD 1 2 3 4 5 6 7 8 1. Distrust 1 4.23 1.21 2. Neuroticism 3.75 1.05 .11 3. Agreeableness 5.35 0.63 .12 .10 4. Cooperation development -48.49 29.45 .50** -.12 .13 5. Negative attributions development 4.24 1.96 -.17 .04 -.01 -.38** 6. Distrust 3 5.86 1.24 .52** .05 .08 .27** .24* 7. Gender - - -.10 .36** .27** -.24* .07 -.10 8. Age 21.55 2.60 -.28** .21* -.01 -.10 -.02 -.23* .22* Notes: N = 99. Gender is coded in male = 0, female = 1. Correlations with gender have a sample size of 96 and correlations with age have a sample size of 95.
*
p < 0.05 **
p < 0.01
Normality testing
negative attributions development and distrust 3 there is a very high level of negative skewness. Furthermore cooperation development and distrust 3 show high levels of kurtosis.
TABLE 2
Shapiro-Wilk test for normality Descriptives Shapiro-Wilk test Variable N Skewness Kurtosis Statistic Degrees of
freedom Significance Distrust 1 99 -.21 -.68 .98 99 .165 Neuroticism 99 .41 -.38 .97 99 .022 Agreeableness 99 -.31 .02 .99 99 .338 Cooperation development 99 -.43 1.27 .88 99 .000 Negative attributions development 99 -1.09 .76 .84 99 .000 Distrust 3 99 -1.41 2.01 .84 99 .000 Note. N = 99.
Hypothesis Test: Main model
FIGURE 8
Regression Analyses direct effects of main part research model
Note. N = 95. Unstandardized regression coefficients are presented. The direct effect of distrust 1 on distrust 3 is presented in parenthesis.
TABLE 3
Regression Analyses Results Main Model Direct Effects Cooperation development Negative attributions development Distrust 3 B SE B SE B SE Constant -22.11 27.25 6.42** 1.98 3.11** 1.12 Distrust 1 12.80** 2.28 .01 .19 .51** .10 Age 1.04 1.08 -.04 .08 -.03 .04 Gender -12.53 5.37 -.05 .40 -.07 .21 Cooperation development - - -.03** .01 -.01 .00 Negative attributions development - - - - .23** .06 Model statistics R2 = .30 F (3, 91) = 13.04** R2 =.15 F (4, 90) = 4.10** R2 = .40 F (5, 89) = 12.07** Indirect Effects of Distrust 1 on Distrust 3 via Effect SE Boot CILL-UL
Total indirect effect .01 .07 -.11 to .15
Cooperation development only .08 .06 -.02 to .22 Cooperation development Negative
attributions development
-.08 .03 -.18 to -.03
Negative attributions development only .00 .05 -.08 to .11 Note. N = 95. Unstandardized regression coefficients are presented.
*
p < 0.05 **
TABLE 4
Contingency Table of Mean Split
Negative attributions development
Low High Total
Cooperation development
Low Count 14 23 37
% within Cooperation development 37.8% 62.2% 100.0% % within Negative attributions
development
32.6% 41.1% 37.4%
% of total 14.1% 23.2% 37.4%
High Count 29 33 62
% within Cooperation development 46.8% 53.2% 100.0% % within Negative attributions
development
67.4% 58.9% 62.6%
% of Total 29.3% 33.3% 62.6%
Total Count 43 56 99
% within Cooperation development 43.4% 56.6% 100.0% % within Negative attributions
development
100.0% 100.0% 100.0%
% of Total 43.4% 56.6% 100.0%
Hypothesis Test: Neuroticism and Agreeableness as Moderators
The regression results of the two moderation models can be found in table 5. TABLE 5
Regression Analyses Results Moderators Analyses for Cooperation Development Neuroticism Agreeableness
Model Variable β SE β SE
1. Control variables Gender -.33 .20 -.48* .19
Age .12 .10 .08 .09
2. Main effects Distrust 1 .68** .12 .57** .12
Neuroticism -.13 .12 - -
Agreeableness - - -.01 .14
3. Interactions Distrust 1 * Neuroticism -.01 .10 - - Distrust 1 * Agreeableness - - .27† .15
R2 .32** .34**
∆R2
.00 .02†
Note. N = 95. Standardized regression coefficients are presented. † p < 0.10 * p < 0.05 ** p < 0.01
In conclusion, the data are inconsistent with hypothesis 4 and 5. The negative relationship of gender with cooperation development was researched further by comparing the means at cycle 1 and cycle 15. Results show that males (M = 65.04) invested significantly more than females (M = 54.59) at cycle 1 (p < 0.05), there were however no significant differences found at cycle 15.
Hypothesis Test: Additional analyses of the relation between cooperation development and negative attributions development
The regression results of the two moderation models of the additional analyses can be found in table 6. The results show that distrust 1 has a direct positive relationship (β = .58, SE = .11, p < 0.01) with cooperation development, a relation already shown to conform hypothesis 1. Furthermore in this model there is a negative interaction effect (β = -.23, SE = .09, p < 0.05) by negative attributions development. The control variable gender also has a marginally significant negative relationship (β = -.30, SE = .17, p < 0.10) with cooperation development. The addition of negative attributions development significantly increased the explanatory power of the model (∆R2 = 0.04, p < 0.05). The Johnson-Neyman technique was used to verify at which specific interval the model is significant. This analysis shows that there are no statistical significance transition points within the observed range of negative attributions development. The simple slope graph of the first model of the additional analyses can be found in figure 9.
-.20, SE = .06, p < 0.01). The addition of negative attributions development significantly increased the explanatory power of this model as well (∆R2 = 0.08, p < 0.01). The Johnson-Neyman analysis shows that the model is significant at the following interval: Z < .40 (p < 0.05). The simple slope graph of the second model can be found in figure 10.
TABLE 6
Regression Analyses Results Additional Analyses Cooperation development Distrust 3 Model Variable β SE β SE 1. Control variables Gender -.30† .17 .07 .13 Age .06 .09 -.10 .07
2. Main effects Distrust 1 .58** .11 - -
Cooperation development - - .24** .07
Negative attributions development -.10 .12 .34** .07 3. Interactions Distrust * Negative attributions
development
-.23* .09 - -
Cooperation development * Negative attributions development
- - -.20** .06
R2 .42** .32**
∆R2
.04* .08**
FIGURE 9
Distrust 1 and Cooperation Development at different levels of Negative Attributions Development
FIGURE 10
Cooperation Development and Distrust 3 at different levels of Negative Attributions Development -1,2 -1 -0,8 -0,6 -0,4 -0,2 0 0,2 0,4 0,6 0,8
Low Distrust 1 High Distrust 1
Cooper at ion De ve lop m en t
Low Neg Att Dev High Neg Att Dev
-0,4 -0,2 0 0,2 0,4 0,6 0,8 1 Low Diminished Cooperation Development High Diminished Cooperation Development Distr u
st 3 Low Neg Att Dev
DISCUSSION Findings
The goal of the research was to verify if there is a self-amplifying cycle of distrust, with the factors diminished cooperation and negative attributions in series as amplifying factors. It was expected that distrust, as a results of some doubt (priming) and the diminished investments of Sim, the business partner, would cause the respondent to cooperate less and that s(he) would justify his/her diminished cooperation with negative attributions, which in turn would lead to more distrust. Additionally it was expected that agreeableness would weaken and neuroticism would strengthen the relationship between doubt and diminished cooperation.
(which have triggered distrust) in two ways: they develop perceptions and attributions towards that other and they tend to answer the norm of (negative) reciprocity by revenge, showing negative behaviours in return. These own negative behaviours will, in turn be justified by negative attributions. In other words, they picture two routes to an increase of negative attributions to a distrusted other. I found that negative attributions accumulated during the experiment, so the route via accumulation is present. The negative relation found may show that the route via justification of revenge behaviours is less strong here than expected, as the contingency table showed. Many respondents who showed low diminished cooperation did have a high score on negative attributions. In short they resented Sim for his non-cooperativeness, but did not show strong incentive for revenge. Therefore negative attributions would not grow much via the justification route, since there was not much to justify. The lower tendency for revenge may be explained by the attractiveness of being into business with Sim and the revenues that own investments may bring despite Sim’s diminished investment. The results were also in line with hypothesis 3, indicating that there is a positive relation between negative attributions and distrust. Therefore the direct relationship between these variables discussed by Bijlsma-Frankema et al. (2015) was found.
The positive effect of distrust on diminished cooperation was expected to have been strengthened by neuroticism and weakened by agreeableness, this was however not the case. Furthermore in this model, gender had a direct effect on cooperation development as well. However this is likely caused by a significant higher score of males on the initial investment, so this allows a higher level of decline. This higher initial investment can be explained by Eagly (2009), who researched gender differences in pro-social behaviour and discovered that men’s pro-social behaviour is more collectively oriented, more specifically supporting a collective as for instance a group or organization, and in the case of the experiment a new organization was supported by investments. Neuroticism and agreeableness appear to have little to do with the self-amplifying cycle, or the self-amplifying cycle is so strong on its own that it completely diminishes the effect of these personality factors on the process.
In conclusion, the results showed that the amount of distrust did increase during the experiment, both by diminished cooperation and negative attributions in series and by a direct effect of distrust itself. Furthermore there was a clear sign of diminished cooperation, since in most cases there was a decline in the investment from the beginning till the end
Theoretical implications and future research
point is reached that triggers distrust (Bijlsma-Frankema et al., 2015). Additionally it can be interesting to see whether the other three of the big five factors have an effect on the cycle.
Recommendations for future research are to study the tipping point, for example when and how it is reached. It could be studied by case studies and since it needs to be studied before the tipping point is reached, one could study it prematurely in for instance mergers (e.g. Rosalind & Kristie, 2004), takeovers, and reorganizations (e.g. Bijlsma-Frankema et al., 2015). Additionally one could research the effects of a personal attachment style (e.g. Ainsworth, 1989) on the development of distrust. Individuals with certain attachment styles could be more prone to distrust behaviours and attitudes compared to others. The dataset that was created with the experiment allows for more analyses and or studies as well, since a number of other variables were measured as well.
Strengths and limitations
The strong points of the study are that it is an experiment which allows for controlled testing. Furthermore it was a first attempt for a dynamic analysis to measure the relationships between the concepts, for example by engendering and testing negative reciprocity. These measurements were based on validated scales that in this study resulted in a good internal consistency, except for the agreeableness scale, but it was still satisfactory. All of the hypothesis testing analyses were done by using the Process macro by Hayes (2013), and used bootstrapping in order to reduce the impact of outliers. In the start of the experiment the doubt or no doubt conditions were helpful to create a wider range of distrust in the beginning of the experiment.
solved by allowing the participants to gain a real sum of money by investing or not by using a real public goods game. However the effects of economic gain and distrust would have been difficult to break down. A further limitation is in the amount of variables that were tested, since certain variables or relationships are missing from the cycle by Bijlsma-Frankema et al. (2015). For instance in the behaviour category, avoidance of interaction was not analysed and in the cognition category, perceived value incongruences and its associated vulnerabilities were taken into account, but only at the end of the experiment and not at the end of each stage, so value incongruence could not be included in the dynamic analysis. A group would have complicated the experimental design too much in this stage of our understanding of distrust and distrust development, therefore this removed the possibility to research the in group convergence effect. The statistical limitations are that multiple variables are not expected to be normally distributed. Furthermore difference scores were used and according to Edwards (2001) difference scores suffer from numerous methodological problems. The de-selection of the Sim decline condition halved the sample size to a moderate amount.
Conclusion and practical implications
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APPENDIX A. INTRODUCTION EXPERIMENT
APPENDIX B. DISTRUST MANIPULATIONS
No doubt manipulation:
You know Sim as a person you can depend on, a man of his word. Other people describe him in exactly the same way. So you decide to team up with him to develop the app in a jointly owned company, and invest money in the app business on a monthly basis.
Some doubt manipulation:
APPENDIX C. DISTRUST SCALE ITEMS
1. I suspect that this person does not always have my best interest in mind 2. I fear that this person will treat me unfairly
3. I am afraid that this person will behave in a way that will be to my disadvantage 4. This person appears mainly interested in her/his own well-being
5. This person will lie if that suits his/her purpose 6. If I am not alert, this person will take advantage of me
APPENDIX D. IPIP 50 (Agreeableness and Neuroticism)
Agreeableness:
1. I feel little concern for others (- keyed) 2. I am interested in people (+ keyed) 3. I insult people (- keyed)
4. I sympathize with others' feelings (+ keyed)
5. I am not interested in other people's problems (- keyed) 6. I have a soft heart (+ keyed)
7. I am not really interested in others (- keyed) 8. I take time out for others (+ keyed)
9. I feel others' emotions (+ keyed) 10. I make people feel at ease (+ keyed)
Neuroticism:
1. I get stressed out easily (+ keyed) 2. I am relaxed most of the time (- keyed) 3. I worry about things (+ keyed)
4. I seldom feel blue (- keyed) 5. I am easily disturbed (+ keyed) 6. I get upset easily (+ keyed) 7. I change my mood a lot (+ keyed) 8. I have frequent mood swings (+ keyed) 9. I get irritated easily (+ keyed)
