18071838 1 Impression M anagement in M usic al Taste : I nvestigating the I nfluence s of I mpression M anagement S trategies and I ndividual D ifferences in M usic S haring B ehaviour. 18071838 Supervised by Dr. Adam Lonsdale March 2021 Statement of originality By including this statement, I am agreeing that: Except for those parts in which it is explicitly stated to the contrary, this thesis is my own work. It has not been submitted for any degree at this or any other academic or professional institution. 18071838 2 I agree that the thesis may be made available for reading and photocopying at the discretion of the Dean of the Faculty of Health and Life Sciences. Permission for anyone other than the author to reproduce or photocopy any part o f the thesis must be obtained from the Dean of Faculty who will give his/her permission for such reproduction only to an extent which he/she considers to be fair and reasonable. 18071838 3 Acknowledgements I would like to thank my supervisor Dr. Adam Lonsdale for all his support and advice throughout my project, Wakefield Morys - Carter for his advice during analysis, and everyone that completed my questionnaire for this study. Finally, I dedicate this piece of work to myself – my determination sees me through everything , and I am incredibly proud of how much I continue to invest in myself despite every challenge I have had to face. 18071838 4 Word count: 5,997 Abstract Individuals engage in impression management behaviour in order to influence and manipulate how others perceive them. Music sharing has been suggested to be one way in which individuals might achieve this. The present study aimed to investigate the extent t o which impression management use could predict music sharing behaviour, as well as self - esteem, self - monitoring and personality traits. Participants were asked to complete an online questionnaire concerned with use of impression management strategies, sel f - esteem, self - monitoring, personality traits and their frequency and attitudes towards music sharing online and face - to - face. It was found that only the supplication strategy, as well as self - monitoring behaviour, extraversion, openness to experience and conscientiousness were highly significant in predicting individuals’ music sharing behaviour. It was concluded that an individual’s use of impression management strategies may not be predictive of their music sharing behaviour in online and offline setting s, and neither are other Big Five personality traits, or their self - esteem Keywords: impression management, music sharing, self - esteem, self - monitoring, personality traits 18071838 5 Introduction In the course of our everyday social interactions, individuals will often seek to influence and manipulate how other people perceive them. This is a process widely referred to as ‘impression management’ (Goffman, 1959). According to Goffman (1959), individ uals will present themselves a certain way (either consciously or subconsciously) during social interactions in order to influence the perceptions that others’ have of them. This theory was later expanded upon by Jones and Pittman (1982), in which five spe cific strategies were outlined that individuals utilise in order to manage their impression on others. Individuals use strategies such as self - promotion, ingratiation and exemplification to appear likeable to others, and strategies such as intimidation and supplication in order to appear aggressive and powerful, or less able, to coerce others into providing them help (Jones & Pittman, 1982). The use of impression management strategies has been studied across a number of different social contexts. In the w orkplace, it has been found that some members of staff will often report staying later or arriving earlier to work in order to give the impression of a dedicated employee, using an ‘exemplification’ strategy (Bolino & Turnley, 1999). In online settings, pe ople have been found to employ a number of strategies to portray a particular image of themselves on social media (Krämer & Winter, 2008). Self - promotion has also been found to be the most used and most successful strategy in job interviews, to help to sec ure the position an individual is interviewing for (Stevens & Kristof, 1995). These strategies have been found in turn to produce successful outcomes in one’s career (Judge & Bretz, 1994; Wayne & Liden, 1995). For example, an employee’s use of self - enhance ment and exemplification strategies early on in their employment has been seen to promote more likeability with supervisors, leading to better workplace performance ratings (Wayne & Liden, 1995) Outside of the workplace , impression management has also been seen in sharing one’s cultural and art preferences (Johnson & Ranzini, 2018). Previous studies have found that individuals will often publicly share or communicate their interests regarding books, films and music in th eir social media profiles to portray a certain image of themselves, rather than giving information that accurately reflects their tastes (e.g., Johnson & Ranzini, 2018; Liu, 2007). 18071838 6 This has also been found specifically in the context of sharing one’s musical taste with others , as m any researchers have found the presence of impression management when studying music sharing behaviours ( e.g., Voida, Grinter, Ducheneaut, Edwards & Newman, 2005) Individuals will often monitor and control the extent t o which they share their musical taste and listening behaviours, and with whom, to ensure they are portraying the desired image with their music library (Voida et al., 2005) This result has been established in many studies investigating individuals’ music sharing behaviour on different online platforms. Studies by Håkansson, Rost and Holmquist (2007), and Voida et al., (2005) both found that individuals monitored and adjusted which songs they were listening to and sending to others in order to communicate a certain version of themselves, as well as browsing others’ music libraries. In multiple q ualitative studies using interviews and diary entries , individuals also reported curating their listening profiles o n streaming services when they knew others could see what they were listening to, labelling some tracks ‘unshareable’ because they did not align with the impression that they wanted to give others (Hagen & Luders, 2007; Kirk, Durrant, Leong & Wright, 2016) Individuals have even reported not listening to songs that they enjoy, because they do not match the perception that they wish others to have of them, which would lead to personal embarrassment (Silfverberg, Liikkanen & Lampinen, 2011). The present study aims to further investigate this behaviou r , as t here is scope to continue to explore this effect in music sharing Most, if not all, research on this topic ha s u sed qualitative methods to gain these findings, and studies have not yet investigated impression management behaviour in this context using standardized measures , or by measuring individuals’ use of specific impression management strategies outlined in previous literature (Jones & Pittman, 1982). This research will therefore provid e more generalizability to previous findings , by measuring these specific strategies ’ associations with individuals ’ music sharing behaviour This will further knowledge in this area as to whether the impression management strategies that have been displayed in other settings are predictive of music sharing. 18071838 7 Previous studies have also only investigat ed this music sharing behaviour in online settings, such as streaming services and social media. For example, Voida et al., (2005) investigated impression management behaviour in music sharing between employees at one corporation, solely through their use of the music service iTunes . Similarly, S ilfverberg et al., (2011) only investigat ed th is behaviour through interview s about individuals’ profiles on the music platform Last.fm. There is therefore a lack of knowledge as to whether this impression management is also present when individuals share their music offline, in face - to - face settings T he significant effects of i mpression management in other settings , such as the workplace , have , in contrast, primarily been found through investigat ion of face - to - face contexts ( Bolino & Turnley, 1999; Stevens & Kristof, 1995; Wayne & Liden, 1995 ) , but t h ese contexts ha ve not yet been investigated in music sharing. Th e present study therefore aims to investigate this impression management behaviour in both online and face - to - face settings , extending current knowledge of this behaviour by examining whether both contexts produce the same effects. It is expected that if sharing one’s music is a form of impression management, the use of impression management strategies will predict a higher frequency and more positive attitudes towards sharing music with others in both online and offline settings T here has also been little exploration of individual difference effects in this context In other settings, there have been indicated links between certain individual differences and the impression management strategies that individuals employ. For example, personality traits have been associated with different strategies of impression managem ent in multiple previous studies. Sadler, Hunger and Miller (2010) found that traits of negative emotionality and aggression were both related to more use of impression management tactics , with aggression being significantly positively correlated with the use of intimidation. In addition, studies by both Bourdage, Schmidt, Wiltshire, Nguyen and Lee (2020), and Kristof - Brown, Barrick and Franke (2002) , found significant positive relationships between extraversion and the use of ingratiation and self - promotio n strategies , and a negative relationship between conscientiousness and the use of deceptive self - promotion in interviews. It was also indicated in Kristof - Brown et al., (2002) that agreeable individuals engaged in significantly more positive non - verbal behaviour in order to manage their impression Personality effects ha ve also been found in online sharing behaviour , with extraversion, neuroticism and 18071838 8 conscientiousness leading to increased sharing of information pertaining to one’s life, activ ities and entertainment knowledge with others ( Deng, Lin, Liu, Chen & Li, 2017; Krämer & Winter, 2008; Marshall, Lefringhausen & Ferenczi, 2015; Teh, Yong, Chong & Yew, 201 1). This indicates a relationship between personality traits, specifically belonging to the Big Five (Costa & McCrae, 1992) , and the use of different strategies of impression management , and information sharing behaviour If this is the case, it is expected that personality traits could have a significant role in the way individuals manage their impression through sharing their music. S imilarly, s elf - esteem level and self - monitoring behaviour have also been associated with impression management use. Research by Schlenker, Weigold and Hallam (1990) found that , when comparing individuals with different levels of self - esteem, their styles of presentin g themselves with others were also different. As social pressure was increased, those with high self - esteem became more boastful with others, and those with low self - esteem became more apprehensive , not sharing as much information This indicate s that self - esteem may have an influence on the impression management that individuals employ T hose with higher self - esteem may engage in more self - promotion behaviour, as they are cited to have been more ‘boastful’ when presenting themselves socially. I t has also been found that self - esteem may play a role in individuals’ motivati on f or sharing information on online platforms. Self - esteem level has been associated with motivation for posting photos of oneself online, as well as updates regarding romantic relationship s (Marshall et al., 2015; Pounders, Kowalczyk, & Stowers, 2016). These findings indicate that there is a potential influence of self - esteem in sharing behaviours, which may also extend to music sharing behaviour. However , other previou s studies that have investigated impression management use , both online and offline, have not found a significant influence of self - esteem level Both Krämer & Winter (2008), and Norris and Porter (2011) , when investigating the use of impression management in individuals’ online sharing behaviour , and behaviour in the workplace (respectively), found no significant associations between this behaviour and self - esteem. The overall mixed nature of previous findings means there requires further investigation, to provide some clarity as to whether there is a role of self - esteem in impression management, specifically in the context of music sharing , which has not yet been explored 18071838 9 Self - monitoring, in contras t, has received much more consistent empirical support , as this trait is one of the most frequently associated with impression management behaviour (Riordan, Gross & Maloney, 1994) Norris and Porter (2011) found high self - monitors to be the most likely to use impression management with others , and this trait was the most significant in predicting the use of impression management strategies. High self - monitors have also displayed better skill at us i ng these strategies, specifically in the case of self - promotion, ingratiation and exemplification , when trying to portray a flattering image of themselves amongst their colleagues (Bolino & Turnley, 2001). Bolino and Turnley (2003) also found that high self - monitors favour these positive strategies of impression management over negative ones when interacting with others. High self - monitors have also been shown to be more likely to manipulate information in workplace settings , in order to show themselves in a positive way (Fandt & Ferris, 1990). T hese findings indicate a robust association between self - monitoring and the use of impression management strategies. This trait may therefore be significant in predicting impression management in t he context of music sharing, though this has not yet been investigated Th e present study aims to investigate the potential influences of these individual differences of self - esteem, self - monitoring and Big Five personality traits in predicting individuals’ frequency and attitudes towards sharing their music with others , in both online and offline settings , adding knowledge to these gaps in previous literature T he overall aim of this study is to investigate whether individuals’ use of impression management strategies outlined by Jones and Pittman (1982) , and Big F ive personality traits, self - esteem level, and level of self - monitoring predict their frequency of sharing their music and attitudes towards music sharing with others , in onlin e and face - to - face settings. As p revious literature has indicat ed that impression management is present in sharing music ( e.g., Voida et al., 2005) , it is hypothesised that an individuals’ use of impression management strategies will significantly predict a higher frequency and positive attitudes towards sharing music in both online and offline settings. It is also hypothesised that Big Five personality traits, individuals’ self - esteem level , and self - monitoring behaviour will significantly predict a higher frequency and positive attitudes towards sharing music in online and offline settings with others. 18071838 10 Method Participants Four hundred participants ( 329 female, 68 male , 1 non - binary and 2 did not describe their gender ) took part in the study voluntarily and were recruited through an online link on social media platforms and private messages . Participant s’ ages ranged from 18 to 70 years old (M = 37 2 4 SD = 12.39 ). Two hundred and twenty - five participants were emp loyed full - time ( 56 %), 67 were employed part - time ( 17 %), 50 were unemployed (13%), and 58 responded ‘Other’ for employment status (14%). 13 participants were taught postgraduate students ( 3 %), 43 were undergraduate students ( 11 %), 7 were research postgraduate students (2%) and 337 were non - students (84%). Measures The present investigation asked participants to complete an online questionnaire through Qualtrics (Qualtrics, Provo, UT) , concerned with ‘ individual differences in music sharing behaviour ’ . The first page of the online questionnaire was an information sheet and consent form. Demographic information (i.e., age, gender & employment status) w as then collected (See Appendix A) . The remainder of the questionnaire was divided into the following six sections. Impression management A 22 - item scale (Bolino & Turnley, 1999) was used to assess use of impression management strategies (See Appendix B) . Participants were asked to respond to statements according to how they feel they behave around other people (e.g., “Talk proudly about your experience or education”) using a 5 - point Likert scale (1 = Never behave this way, 5 = Often behave this way). The 22 - item measure is divided into five distinct sub - scales, namely (1) Self - promotion (i.e., trying to present oneself as capable to others , 4 - items); (2) Ingratiation (i.e., trying to present oneself as likeable to others, 4 - items ); (3) Exemplification (i.e., presenting oneself as dedicated to others , 4 - items); (4) Intimidation (i.e., presenting oneself as to be feared by others , 5 - items) and (5) 18071838 11 Supplication (i.e., presenting oneself as less able to others , 5 - items). Scores on each subscale were calculated as the mean of the relevant 4 or 5 items (sub - scale scores range d from 1 to 5 ). A high score on each of these sub - scales indicated a high frequency of use of th is impression management strateg y with others. Cronbach’s alpha for each of the sub - scales showed that they were all internally consistent : Self - promotion (α = .8 3 ) , Ingratiat ion (α = .84), Exemplification (α = .79), Intimidation (α = .80) , Supplication (α = .86). Self - esteem The Rosenberg self - esteem scale (RSE; Rosenberg, 1965) was used to assess participants’ self - esteem (See Appendix C) . Participants were asked to rate the extent to which they agree with each of the 10 statements ( e.g., “On the whole I am satisfied with myself”) using a 5 - point Likert scale (1= Strongly dis agree, 5 = Strongly agree). Overall RSE scores were calculated as the mean of all 10 - items , an d as such ranged from 1 to 5 . High RSE scores would indicate a high level of self - esteem for the participant . In the present study, the RSE was found to be internally consistent (α=. 92). Self - monitoring A 25 - item scale (Snyder, 1974) was used to assess self - monitoring behaviour (See Appendix D) . Participants were asked to rate the extent to which they agree with each of the 25 statements , according to how they feel they behave socially (e.g., “ At parties and social gatherings, I do not attempt to do or say things that others will like ”) using a 5 - point Likert scale (1 = Strongly disagree , 5 = Strongly agree ). Overall self - monitoring scores were calculated as the mean of the 25 - items , and as such ranged from 1 to 5 High scores would indicate a high amount of self - monitoring behaviour in social settings . In the present study, the self - monitoring scale was found to be internally consistent (α =. 83) , after the removal of 12 items with very low item - rest correlations Personality The Ten Item Personality Inventory (TIPI; Gosling, Rentfrow, & Swann, 2003) was used to assess Big Five personality traits (See Appendix E) Participants were asked to rate the extent to which they agreed with each statement according to how they see themselves (e .g., “I see myself as extraverted, enthusiastic”), using a 7 - point Likert 18071838 12 scale (1 = Disagree strongly , 7 = Agree strongly ). Overall scores for each personality trait were calculated as the mean of the relevant 2 items , and as such ranged from 1 to 7 High scores would indicate prominence of this personality trait for the participant Frequency of sharing music A 10 - item scale was used to assess participants’ frequency of sharing music online and in face - to - face settings (See Appendix F) . Participants were asked to select how far they agree with each statement about their music sharing behaviour The 10 - item scale measure is divided into two distinct sub - scales, namely (1) Frequency of sharing music online (i.e., how frequently participants share their music on online platforms/social media ( e.g., “ I often share my music by uploa ding songs that I have listened to on online platforms / social media ”), 5 - items); and (2) Frequency of sharing music face - to - face (i.e., how frequently participants share their music in face - to - face settings with others ( e.g., “ I often share my music by suggesting or playing songs that I like in social settings ”) 5 - items) using a 5 - point Likert scale (1 = Strongly disagree, 5 = Strongly agree) . Scores on each subscale were calculated as the mean of the relevant 5 items (sub - scale scores range d from 1 to 5 ). High scores would indicate a high frequency of sharing one’s music with others . In the present study, both sub - scales were found to be internally consistent (α=. 84 , & α= 84 ). Attitudes towards sharing music A 10 - item scale was used to assess attitudes towards music sharing. Participants were asked to select how far they agree with each statement about sharing their music (See Appendix G) The 10 - item scale measure is divided into two distinct sub - scales, namely (1) Attitudes towards sharing music online (i.e., how participants feel about sharing their music online ( e.g., “ I feel that my musical taste is too personal to share via posts on on line platforms / social media ”), 5 - items); and (2) Attitudes towards sharing music face - to - face (i.e., how participants feel about sharing their music in face - to - face settings with others ( e.g., “ I feel that my musical taste is too personal to share with o thers in social settings ”) 5 - items) , on a 5 - point Likert scale (1 = Strongly disagree, 5 = Strongly agree) . Scores on each subscale were calculated as the mean of the relevant 5 - items (sub - scale scores range d from 1 to 5 ). High scores would indicate a positive attitude 18071838 13 towards sharing one’s musical taste with others . In the present study, both sub - scales were found to be internally consistent (α= 86 & α= 87 ). Results Descriptive statistics Prior to inferential analys i s, means and standard deviations were calculated in order to indicate participants’ average scores for each of the variable s measured (see Table 1). Table 1 – Means and Standard Deviations for all variables Variable Mean Standard Deviation Self - promotion Ingratiation Exemplification Intimidation Supplication Self - esteem Self - monitoring Extraversion Agreeableness Openness to experience 2.81 3.77 2.77 1.50 1.78 3.12 2.78 3.23 5.17 4.88 0.80 0.87 1.05 0.59 0.74 0.82 0.65 1.63 1.12 1.14 18071838 14 Neuroticism Conscientiousness Frequency of sharing music online Frequency of sharing music face - to - face Attitudes towards music sharing online Attitudes towards music sharing face - to - face 4.32 4.95 2.13 2.98 2.68 2.89 1.58 1.37 1.00 0.96 0.96 0.92 A s can be seen in Table 1, participants seem to have reported using the strategy of ingratiation on average more than other strategies of impression management , according to mean scores (M = 3.77, SD = 0.87). Mean scores also suggest that participants may show a higher frequency and more positive attitudes towards sharing music in face - to - face settings than online (M = 2.98, SD = 0.96) ( M = 2.89, SD = 0.92). Inferential statistics Four multiple linear regression analyses were run in order to test how significant impression management use, self - esteem, self - monitoring and Big Five personality traits are in predict ing an individuals’ frequency of sharing their music online and in face - to - face settings, and their attitudes towards music sharing in online and in face - to - face settings. (See Table 2 , 3, 4 and 5 ). 18071838 15 Findings from the first multiple regression analysis were that a model consisting of impression management strategies , self - esteem, self - monitoring, and Big Five personality traits was a significant predictor of individuals’ frequency of sharing music online , F( 12 , 3 87 ) = 2.02 , p = 0.02 , Adj. R2 = .0 6 . The Durbin - Watson test suggested that the residuals were slightly positively autocorrelated, and examination of the Q - Q plot indicated that they were negatively skewed. The residual plots indicated homoscedasticity of variance of the residuals with no ou tliers. All variance inflation factors were below 3 , indicating no issues of multicollinearity between predictors. Table 2 - Regression model coefficients for frequency of sharing music online 95% Confidence interval Predictor Estimate SE T P Stand. estimate Lower Upper Intercept Self - promotion Ingratiation Exemplification Intimidation Supplication Self - esteem Self - monitoring Extraversion 1.89 0.07 0.03 0.04 - 0.06 - 0.01 - 0.05 0.13 0.03 0.57 0.08 0.07 0.05 0.09 0.07 0.09 0.11 0.04 3.29 0.96 0.45 0.80 - 0.64 - 0.12 - 0.59 1.16 0.71 < 0.0 1 0.3 4 0.65 0.43 0.52 0.91 0.56 0.25 0.48 0.06 0.03 0.04 - 0.04 - 0.01 - 0.04 0.08 0.05 - 0.06 - 0.09 - 0.07 - 0.14 - 0.12 - 0.18 - 0.06 - 0.09 0.18 0.14 0.15 0.07 0.10 0.10 0.22 0.19 18071838 16 Agreeableness Openness to experience Neuroticism Conscientiousness - 0.07 0.08 - 0.01 - 0.08 0.05 0.05 0.04 0.04 - 1.32 1.76 - 0.35 - 1.91 0.19 0.08 0.72 0.06 - 0.07 0.10 - 0.02 - 0.11 - 0.18 - 0.01 - 0.15 - 0.22 0.04 0.20 0.10 0.00 As can be seen in Table 2, no impression management strategies or individual differences were significant in predicting individuals’ frequency of sharing music online. Findings from the second multiple regression analysis were that a model consisting of impression management strategies , self - esteem, self - monitoring, and Big Five personality traits was a significant predictor of individuals’ frequency of sharing music in face - to - face settings , F(12, 387) = 3.29 , p <.001 , Adj. R2 = .06. The Dur bin - Watson test suggested that the residuals were slightly positively autocorrelated, and examination of the Q - Q plot indicated that they were n ormally distributed . The residual plots indicated homoscedasticity of variance of the residuals with no outliers . All variance inflation factors were below 3, indicating no issues of multicollinearity between predictors. 18071838 17 Table 3 - Regression model coefficients for frequency of sharing music in face - to - face settings 95% Confidence interval Predictor Estimate SE T P Stand. estimate Lower Upper Intercept Self - promotion Ingratiation Exemplification Intimidation Supplication Self - esteem Self - monitoring Extraversion Agreeableness Openness to experience Neuroticism Conscientiousness 1. 63 0.0 5 0.0 2 0.0 7 0.02 0.04 - 0.0 1 0. 22 0.0 4 0.01 0.08 - 0.0 0 - 0.0 6 0. 54 0.0 7 0.0 6 0.05 0.0 9 0.07 0.0 8 0.1 0 0.04 0.05 0.05 0.04 0.04 3. 00 0. 72 0. 26 1.34 0.21 0.59 - 0. 18 2.15 1.04 0.25 1.7 3 - 0. 07 - 1. 49 < 0.01 0. 47 0. 80 0. 18 0. 83 0. 55 0. 86 0. 03 0. 30 0. 81 0.08 0. 94 0. 14 0.0 4 0.0 1 0.0 7 0.01 0.03 - 0.0 1 0. 15 0.0 7 0.01 0. 09 - 0.0 0 - 0. 08 - 0.0 7 - 0. 10 - 0.0 3 - 0.1 0 - 0. 07 - 0.1 5 0.01 - 0.0 6 - 0. 09 - 0.01 - 0.1 3 - 0. 19 0.1 6 0.1 2 0.1 8 0. 12 0.1 4 0.1 3 0.2 9 0. 21 0. 12 0.20 0.1 2 0.0 3 18071838 18 As can be seen in Table 3, self - monitoring behaviour was highly significant in positively predicting individuals’ frequency of sharing music in face - to - face settings (t = 2.15, p = .03 ) No i mpression management strategies or other individual differences were significant. Findings from the third multiple regression analysis were that a model consisting of impression management strategies , self - esteem, self - monitoring, and Big Five personality traits was a significant predictor of individuals’ attitudes t owards sharing music online, F(12, 387) = 2. 68 , p < 0.01 , Adj. R2 = .0 8 . The Durbin - Watson test suggested that the residuals were slightly positively autocorrelated, and examination of the Q - Q plot indicated that they were negatively skewed. The residual pl ots indicated homoscedasticity of variance of the residuals with no outliers. All variance inflation factors were below 3, indicating no issues of multicollinearity between predictors. Table 4 - Regression model coefficients for attitudes towards sharing music online 95% Confidence interval Predictor Estimate SE T P Stand. estimate Lower Upper Intercept Self - promotion Ingratiation 2.69 0.0 9 0.0 1 0.5 5 0.0 7 0.0 6 4.91 1.20 0. 18 < .001 0. 23 0. 86 0.0 7 0.0 1 - 0.0 5 - 0. 10 0.1 9 0.1 2 18071838 19 Exemplification Intimidation Supplication Self - esteem Self - monitoring Extraversion Agreeableness Openness to experience Neuroticism Conscientiousness - 0.02 - 0.0 0 - 0. 16 - 0.0 4 0.1 4 0.0 4 - 0.0 2 0.0 7 - 0.0 5 - 0.08 0.05 0.09 0.07 0.0 8 0.1 0 0.04 0.05 0.05 0.04 0.04 - 0.48 - 0. 02 - 2.26 - 0. 45 1. 32 1.08 - 0.33 1. 49 - 1.27 - 2.01 0. 63 0. 98 0. 02 0. 65 0. 19 0. 28 0. 74 0. 14 0. 20 0.0 5 - 0.03 - 0.0 0 - 0. 12 - 0.0 3 0.0 9 0.0 7 - 0.0 2 0. 08 - 0.0 8 - 0.11 - 0. 13 - 0.1 1 - 0. 23 - 0.1 7 - 0.0 5 - 0.0 6 - 0.1 3 - 0.0 3 - 0. 20 - 0.22 0. 08 0. 11 - 0.02 0.1 1 0.2 3 0. 21 0.0 9 0. 19 0. 04 0.00 As can be seen in Table 4, the use of the supplication impression management strategy (t = - 2.26, p = .02 ) , and the Big Five personality trait conscientiousness (t = - 2.01, p = .05) w ere both highly significant in predicting individuals’ positive attitudes towards sharing music online No other impression management strategies or individual differences were significant. 18071838 20 Findings from the fourth multiple regression analysis were that a model consisting of impression management strategies , self - esteem, self - monitoring, and Big Five personality traits was a significant predictor of individuals’ attitudes towards sharing music in face - to - face settings , F(12, 387) = 3.80 , p< .0 01, Adj. R2 = 11 . The Durbin - Watson test suggested that the residuals were slightly positively autocorrelated, and examination of the Q - Q plot indicated that they were normally distributed . The residual plots indicated homoscedasticity of variance of the residuals with no outliers. All variance inflation factors were below 3, indicating no issues of multicollinearity between predictors. Table 5 - Regression model coefficients for attitudes towards sharing music in face - to - face settings 95% Confidence interval Predictor Estimate SE T P Stand. estimate Lower Upper Intercept Self - promotion Ingratiation Exemplification Intimidation Supplication Self - esteem Self - monitoring 2.11 - 0.01 - 0.02 - 0.00 0.02 - 0.0 4 0.02 0. 07 0.5 2 0.0 7 0.0 6 0.05 0.0 8 0.07 0.0 8 0.1 0 4.07 - 0.17 - 0.30 - 0.09 0.29 - 0. 52 0.30 0.70 < .00 1 0. 87 0. 77 0. 93 0. 78 0. 60 0. 76 0. 49 - 0.01 - 0.02 - 0.00 0.02 - 0.0 3 0.02 0.0 5 - 0. 13 - 0. 13 - 0. 11 - 0. 09 - 0.1 3 - 0.1 2 - 0.0 9 0. 11 0. 09 0.1 0 0. 12 0. 08 0.1 6 0. 18