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Computer-mediated communication and risk-taking behaviour
Computers in Human Behavior 27 (2011) 1794–1799
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Computers in Human Behavior journal homepage: www.elsevier.com/locate/comphumbeh
Computer-mediated communication and risk-taking behaviour Lynette Y.Q. Goh a, James G. Phillips a,⇑, Alex Blaszczynski b a b
School of Psychology & Psychiatry, Monash University, Australia Psychology Department, University of Sydney, Australia
a r t i c l e
i n f o
Article history: Available online 20 April 2011 Keywords: Videoconference Risk Gambling Internet Collaboration
a b s t r a c t In an unregulated environment Internet use is not without risk, and video has been proposed to influence riskiness and trust behaviour. This experiment explored the differences in willingness to take risks on events portrayed over the Internet via a videolink, relative to events occurring in close proximity (collocated). Thirty-four participants played a roulette game on a computer, wagering points upon the outcomes of spins of a real roulette wheel. The amounts, types of bets and the time to place them were analysed. It was found that confidence (points wagered) did not change, but people went for lower risk (when more was at stake), or thought more about the risks they took (when more was at stake) over a videolink. People accepted greater risk on outcomes occurring in close proximity, than those events portrayed over a videolink. Variations in perceived risk in response to online versus offline events probably reflect differences in the potential to influence outcomes. Crown Copyright Ó 2011 Published by Elsevier Ltd. All rights reserved.
1. Introduction The use of video for communication within organisations is increasing. Videolinks have been proposed to increase cooperation between organisational members (TenCate, 2007), to improve communication outcomes and offer better services online. Gambling syndicates have also used videolink (otherwise known as videoconferencing) technology to further authenticate the online gambling experience (The Star, 2009). As videolinks are becoming more pervasive it is important to understand how such technology might affect human behaviour, and as the Internet can be a poorly regulated environment this study specifically addresses whether videolink technologies affect human risk-taking behaviour.
Access to videoconferencing technology is becoming increasingly pervasive. Our surveys of university student populations (Phillips, Jory, Wijenayake, & Hii, 2010) have indicated that the proportions of students videoconferencing has risen from 17% in 2006 (N = 318) to 51.2% in 2010 (N = 203), with their possession of the necessary hardware increasing from 30% to 83% over the same period. Peter, Valkenburg, and Schouten (2007) found that 57% of the 1060 adolescents surveyed occasionally used webcams whilst instant messaging people, and 32% of them used microphones to enhance the visuo-auditory experience. Peter et al. (2007) suggested that people’s subjective perceptions affect their usage of videolink technology more than actual media features, finding that adolescents’ usage of webcams and microphones depended upon how important they found the lack of visual or auditory cues to be for them individually.
1.1. Videolink technology 1.2. Communication and collaboration Psychologists have studied computer-mediated communication (CMC), but previous work has primarily addressed text and audiobased interactions. However technological advancements are enhancing CMC, providing additional realism in the form of videolinks (e.g. Skype, GoogleMail). A person gains access to videolink technology if they have a webcam, a computer or laptop, the appropriate software application to use it and Internet access. High-speed broadband access improves the quality and frames per second of the video image seen. ⇑ Corresponding author. Address: School of Psychology & Psychiatry, Monash University (Bld. 17), Clayton, VIC 3800, Australia. Tel.: +61 3 9905 3914. E-mail address: [email protected] (J.G. Phillips).
Advocates of videolink technology suggest that it can improve communication. Videolink has the potential to improve communication because of its additional ‘‘richness’’. Media richness theory stresses that each communication channel carries a different amount and variety of information to its users (Daft & Lengel, 1986). According to Bekkering and Shim (2006, p. 104), a channel’s richness may consist of the ‘‘availability of instant feedback, the use of multiple cues (such as facial expressions, voice inflections, and gestures), the use of natural language for conveying a broad set of concepts and ideas, and the personal focus of the medium. Face-to-face communication is high in richness, while a typed note with numerical content is low’’.
0747-5632/$ - see front matter Crown Copyright Ó 2011 Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.chb.2011.03.006
L.Y.Q. Goh et al. / Computers in Human Behavior 27 (2011) 1794–1799
Organisations have adopted videolink technology to enhance collaboration. For instance the University of Washington opened the Odegaard Videoconference Studio to allow communication between groups on campus that were in different physical locations (TenCate, 2007). Research indicates that people are least likely to help in response to textual requests for assistance, while helping behaviour improves to requests for assistance over the phone, and helping is greatest when requests for assistance are made ‘‘in person’’ in the same physical location (Weinberger, 1981). Brosig, Ockenfels, and Weimann (2002) found that people who used video and audio cooperated on a level similar to that of faceto-face interaction (although it did take a longer time). If a communication channel contains less richness (meaning there is a loss of information from source to receiver), then people are less likely to trust the technology and information received (Riegelsberger, Sasse, & McCarthy, 2007).
1.3. Videolinks and perceived risk Videolink technology is being used for a variety of applications, not just for commercial functions but also for socialising (e.g. http://www.vdateonline.com/) and also for gambling (The Star, 2009). The decision to use such technology can be considered to involve a choice between ‘‘real’’ and ‘‘virtual’’ interaction, and such a choice is likely to be influenced by perceived risk. When using the internet technology socially online for friendship or relationships (Whitty, 2008) there is an element of risk. People tend to lie and present false identities online, more so than in face-to-face interaction, and deception can be hard to detect when it is computer mediated (Green, 2007). A degree of disinhibition online that is associated with diminished feedback appears to contribute to deceptive or harmful behaviours (Suler, 2004; Whitty & Carville, 2008). Online disinhibition has been discussed primarily within the context of text-based CMCs, while the potential contribution of video has rarely been addressed. Another area of increased risk where existing controls are challenged is in the area of internet gambling (Phillips, Ostojic, & Blaszczynski, in press). In a gambling context, deception occurs in a variety of ways. There can be dishonest payouts, game cheating, fake license claims and unethical business practices (e.g. http://www.casinomeister.com/rogue/). For instance, Sevigny, Cloutier, Pelletier, and Ladouceur (2005) considered whether online casinos provided misleading (inflated) payout rates during the ‘demo’ period and then reduce the odds when playing for real money. This study documented statistically that 39% of the 117 online casinos studied demonstrated misleading payout rates. To examine issues associated with the selection of ‘‘real’’ versus ‘‘virtual’’ interaction, the present study used a simulated gambling task to address perceptions of risk engendered by videolink technology. Psychology has had a long tradition of using simulated gambling tasks to address decision making and risk (Lim, 2003). Risk is present when there is the possibility of negative outcomes in a situation (Green, 2007). People are generally risk averse (Schneider & Lopes, 1986). Simply put, if a situation is deemed to be risky people will take less risks with their behaviour but in a less risky situation people will display more risk-taking behaviour. Perceived risk apparently affects people’s risk-taking behaviour more than the actual risk present (Horswill & McKenna, 1999; Paine Schofield & Joinson, 2008), and this influences how much risk a person is willing to take in a situation. In consumer behaviour research, the higher the perceived risk of an Internet service, the less favourably regarded is the use of that Internet service (Polasik & Wisniewski, 2009). For instance, Fogel and Nehmad (2009) looked at risk-taking, trust and privacy concerns on Internet social networks. They found that individuals who utilise social network-
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ing websites (Facebook and MySpace) have greater risk taking attitudes than those who do not. Risk can be offset by considerations of trust. Trust serves to reduce fear and perceived risk and uncertainty in risky situations (Koenig-Lewis, Palmer, & Moll, 2010). Perceived risk can be lessened when trust is built by a variety of means. In electronic commerce, if the object of trust behaves in an honest, reputable and predictable manner, it gains credibility (Corritore, Kracher, & Wiedenbeck, 2003). Videolink technology has the potential to reduce perceived risk by building trust via the availability of visual images. 1.4. Aims and hypotheses The present study was conducted to examine whether risk-taking behaviour would change in response to outcomes conveyed through the computer over a videolink as compared to outcomes occurring in the same physical location. This experiment sought to examine differences in willingness to take risks on events portrayed over the Internet, relative to events occurring in close proximity (collocated). Human risk-taking has previously been examined using gambling analogues (e.g. Bechara, Damásio, Damásio, & Anderson, 1994). The present study used a game of roulette, where the outcomes were determined by the spin of a real roulette wheel. The roulette wheel could be in the same physical location (collocated), or in a remote location where the outcome was conveyed by a videolink. As videolinks afford a less rich interaction (Bekkering & Shim, 2006) than face to face communication, outcomes portrayed over a videolink are likely to be perceived to be less reliable and thus more risky. It was thus predicted that people would be less willing to wager on the roulette game when a videolink was used to display the roulette wheel. As the videolink is not as rich an experience, it was predicted that people would prefer physical collocation, which is comparable to face-to-face interaction, over videolink communication of outcomes. 2. Method 2.1. Participants There were 34 participants, 25 of the participants were male (age: M = 23.04, SD = 4.13) and nine were female (age: M = 23.00, SD = 5.83). Participants were screened for prior gambling problems and were reimbursed for their time ($6 per hour). This project had ethical approval from the Monash University Human Research Ethics Committee. 2.2. Apparatus A personal computer was used with custom written software that recorded wagering patterns and timed responses. A 22 cm diameter French style roulette wheel manufactured by Dal Rossi of Italy was employed. A printed copy of the roulette wheel layout was also available. The computer software roulette game emitted a beep that was to initiate the beginning of each bet. A message ‘‘Place your bets’’ would then appear on the screen. Participants would have 3 s to place a bet down otherwise that bet would be registered as a null bet, with the computer moving onto the next betting opportunity. This was to simulate a degree of time pressure as found in casinos. Participants entered their wagers (points 1–9) and then specified the location of their bets by inserting a first number and a last number, similar to the call betting system used in casinos. Only recognised call bets were accepted. The location of the bets was highlighted onscreen on the roulette layout. The roulette layout
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in the software was similar to the layout in casinos with the exception that players could not bet on odds/evens, and red/black. Nor did the software allow the corner bet of 0–3 that had the odds of 8–1. Payouts and odds for each bet were then displayed before moving onto the next bet within the same spin. Up to 15 bets could be placed for each spin, but participants need not place all 15. The total amount of bets placed for each spin was indicated at the bottom of the screen. After the bets were placed, an experimenter spun the roulette wheel. After the spin, the experimenter entered the number spun and that number would appear in the row of 10 previous numbers that have been spun before. This row of numbers was constantly shown in the game as a decision aid. Participants were informed of the result of the spin from an onscreen message that included how much they bet on the number spun and the payout. The total amount won or lost was displayed at the bottom-right of the computer screen per condition. To examine the effect of computer mediation communication upon wagering behaviour, the locations of the wheel were either: collocated (wheel and experimenter present in the same room as participant) or, videolink (wheel and experimenter in a separate room with the wheel actions displayed on a computer monitor inclusive of real-time video and audio feeds using Marratech software). To manipulate risk, the points participants wagered were multiplied. In the low risk condition, points were multiplied by 1. In the high risk condition, points were multiplied by 5. 2.3. Procedure The experimenter explained how the roulette game worked and described the four conditions. Participants were instructed to try to win as many points as possible as iPod Classics were to be given to the two highest scorers. In the absence of real money, the prizes of iPod Classics served as motivators to encourage participants to take a more considered approach when betting points. The participants did a practice trial of two spins before starting on the experiment itself. Responses during the roulette game were logged automatically by the computer. Outcomes, payouts and totals were determined. For the 2 2 risk by location design, each participant had to complete four conditions. The conditions were low risk and collocated; low risk and videolink; high risk and collocated; high risk and videolink. Conditions were presented in a randomised order to ensure that any order or practice effects would not have a systematic effect on the factors of interest. In between the four conditions there was a short rest interval of about 3 min for the participants while the equipment was being set up. It took between 1 and 2 h per participant for the entire roulette game. After they have played the game, the experimenter asked the participants which wheel location (collocation or videolink) they preferred and why. At the end of the experimental task, participants were debriefed on the purpose of the study and the irrational beliefs that gamblers have.
3. Results There are a variety of ways of quantifying wagering within roulette (Wagenaar, 1988). One way to measure the degree of preferred risk was to look at the mean amount of points bet. As there is also considerable opportunity to vary betting strategies, the mean amount of numbers covered on the roulette layout was also examined across every condition. As roulette offers a wide range of betting opportunities, we analysed the payouts sought. This was the average amount that would be won if a participant’s numbers came up. Two-way repeated measures Analysis of
Table 1 Descriptive statistics for the four conditions between risk and location factors levels. Low
Mean bet Numbers covered Payout sought Reaction time bet Reaction time first no. Reaction time last no.
High
Collocation
Videolink
Collocation
26.10 (3.44) 20.51 (1.27)
30.72 (4.64) 20.63 (1.38)
128.51 (25.58) 111.87 (20.89) 20.10 (1.27) 21.83 (1.22)
Videolink
53.33 (10.17) 55.12 (10.13) 257.23 (59.54) 181.59 (41.75) .35 (.03)
.35 (.03)
.31 (.03)
.35 (.03)
1.26 (.15)
1.15 (.11)
1.04 (.11)
1.22 (.13)
.61 (.05)
.63 (.05)
.56 (.05)
.67 (.06)
Note: standard errors are in parentheses. Times are in seconds.
Variance (ANOVA) was conducted on all of the meaningful variables. The mean number of points bet was examined because it taps into the issue of confidence and trust. The descriptives for the mean number of bets the participants placed across each condition is shown in Table 1. A significant main effect for risk was found, F (1, 33) = 28.51, p < .01, g2 = .46. Participants placed significantly fewer points for their bets in the low risk conditions and more points in the high risk conditions, indicating that a manipulation of risk was effective. There was no interaction between Risk and Location, and neither was there a significant main effect for Location. A common strategy when playing roulette is to place bets covering more of the layout (Wagenaar, 1988). This strategy is intended to reduce risk for the player. The mean number of numbers covered was analysed. There was no effect of Risk (F (1, 33) = 0.42, p > .05, g2 = .01). Nor was there an effect of Location (F (1, 33) = 3.27, p = .08, g2 = .09), although people tended to cover more of the roulette layout within the videolinked condition (see Table 1). There was no interaction between Risk and Location, suggesting that participants tended to cover the same amount of the layout during wagering across conditions. Another index of risk-taking behaviour is the mean possible payout participants sought. For instance, a participant that placed 2 points on a single 8/1 bet would obtain a value of 16 for this measure. The mean possible payout measured the odds selected by participants. There was a significant main effect found for Risk on the possible payouts, F (1, 33) = 16.39, p < .01, g2 = .33. There was also a significant main effect for the Location of the roulette wheel, F (1, 33) = 6.92, p < .05, g2 = .17 and a significant interaction between Location and Risk upon possible payouts, F (1, 33) = 5.69, p < .05, g2 = .15. This indicates that the effect of roulette wheel location varied as a function of risk. To interpret this interaction, the simple main effects were calculated. It was found that there was no significant effect of Location upon possible payouts sought for the low risk conditions, F (1, 33) = .01, p > .05 (see Fig. 1), but there was a significant effect of Location for the high risk condition F (1, 33) = 10.87, p < .05. This meant that people sought higher payouts when collocated and higher risk, but sought significantly lower payouts when videolinked and higher risk. Changes in risk-taking behaviour may also be inferred from the times that participants took to place down their bets and register the first and last numbers of their ‘‘call bets’’. Slower reaction times would imply more consideration or concern when making decisions. There were neither significant effects nor interactions for the mean reaction times to place down their bets or when keying in their last number of their ‘‘call bet’’. But a significant interaction was found between the two factors for the mean reaction time to key in their first number, F (1, 33) = 4.79, p < .05, g2 = .13.
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300
Mean Payout Sought
Collocated 250 200
a significant preference for a particular location. The expected range was between 1.00 (collocation) and 2.00 (videolink). The Kolmogorov–Smirnov z-score was statistically significant at 4.70, p < .001. There was a marked preference for collocation among the sample.
Videolink 150
4. Discussion
100 50 0 Low Risk
High Risk
Risk Fig. 1. Preferred risk by the mean average payouts as a function of the location of the roulette wheel and the amount of risk.
Mean RT First No. (sec)
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1.4
Videolink 1.2
1.0
To understand psychological mechanisms underpinning the use of videolink technologies, this study considered whether videolinking of events alters perceptions of risk and risk-taking behaviour. Participants were asked to wager points at various levels of risk upon outcomes that could be collocated with the participant or conveyed over a videolink. Participants played a roulette game on the computer and their level of risk-taking behaviour was measured with a variety of indices. Although participants did not alter the number of points wagered, or the amount of the roulette layout covered, they selected bets with lower odds in the riskier videolinked condition and appeared to spend more time thinking about bet locations in higher risk videolinked condition. This demonstrated that the videolink altered the appreciation of risk. Indeed people preferred the collocated to the videolinked versions of roulette.
4.1. Location
Collocated 0.8 Low Risk
High Risk
Risk Fig. 2. Mean reaction times (in seconds) for first call bet when wheel location was varied and at low risk or high risk.
As there was a significant interaction between location and risk, simple main effects were examined to identify where the differences in reaction times to position bets were occurring. It was found that risk only had an effect on response latencies in the collocated condition, F (1, 33) = 5.25, p < .05. People were significantly slower in deciding their first number in the low risk condition than in the high risk condition, but this occurred when the roulette wheel was collocated (see Fig. 2). People thought less about placing high risk bets when collocated. As it is conceivable that continued exposure to the videolink might strengthen trust in the technology, the effects of trial block (viz 1st, 2nd, 3rd condition experienced) was analysed. Such an analysis considers whether there is a systematic effect of exposure or practice (but otherwise confounds experimental manipulations). We separately analysed the effects of trial block number, comparing the first, second, third and fourth conditions that participants experienced. There was no effect of trial block number upon the average amount bet (F (3, 99) = 0.220, p > .05) or the average payout sought (F (3, 99) = 1.224, p > .05). Hence exposure or practice did not influence perception of risk. However, familiarity did influence the amount of thought put into wagering. As participants became more familiar with the task, they required less time to indicate the first (F (3, 99) = 11.824, p < .001, g2 = .26) and second (F (3, 99) = 8.576, p < .001, g2 = .21) number of their call bets. When the experiment had concluded, the participants were asked which roulette wheel location they preferred (collocation or videolink). A one-sample Kolmogorov–Smirnov test was conducted against a uniform distribution to see whether there was
It was anticipated that people would wager less, preferring to take less risk when the videolink was used to transfer the roulette wheel image from an external location onto the computer screen. This hypothesis was supported by analysing a variety of measures of preferred risk. The mean average payouts sought varied as a function of risk and roulette wheel location. This measure was sensitive to the types of odds (i.e. 35-1, 17-1, 11-1, 8-1, 5-1, 2-1, 1-1) selected. People sought lower payouts, seeming to perceive higher risk when outcomes were conveyed over a videolink. In addition, the reaction time taken to select the first number in call bets varied significantly with location and risk. Collocation was treated as lower risk, and people thought less about bet placements at higher risk when collocated. The greater illusion of control when wagering ‘‘in person’’ (Langer, 1975) indicates that people are more trusting when collocated, and this is as would be expected from media richness theory where face-to-face interaction has the richer amounts of interpersonal cues (Bekkering & Shim, 2006; Campbell, 2006). There was no difference in the number of points placed or the amount of numbers covered on the roulette layout. Although people commonly vary the amount of the layout covered, this is by no means a uniform strategy (Wagenaar, 1988). Participants could have employed other betting strategies. They sought a lower payout rate that tended to cover more numbers on the roulette layout, thus taking less risk. However, there was no effect of location for the mean amount of bets placed, which suggested that players’ confidence did not vary, just their evaluation of risk. Although there were some slight indications that people wagered fewer points when the roulette wheel was shown through videolink, it was quite marginal and not significant. Therefore the present data suggest that the videolink was not affecting confidence as measured by the points participants wagered. Instead, people varied the riskiness of their wagers. People displayed lower risk-taking behaviour in the videolink condition than when collocated but again, it was mainly for the high risk situation. As these effects were found for high risk situations, it seems that risk and the videolink potentiated their effects making people more aware and cautious of what they were wagering on.
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4.2. Preferred mode People chose collocation when asked which location of the roulette wheel they preferred. This finding supported previous research about communication channel richness where people would favour face-to-face interaction more than any other communication medium because a face-to-face interaction provides far more informational cues (Bekkering & Shim, 2006). Nevertheless, the number of videolink users is increasing. The increase in users could reflect convenience. Indeed Wood, Williams and Lawton’s (2007) reported one reason for people choosing to gamble online over land-based venues was because of convenience. When given the choice between using videolink or having nothing, people would probably choose to implement videolink even though to them collocation was the preferred choice. 4.3. Limitations The present study employed a within subjects design that makes obvious any comparisons between different formats. We do not think that a within subjects design is of concern as it allows comparisons of perceived risk while controlling individual differences in predispositions towards risk taking (participants serve as their own controls). All the forms of roulette in this experiment are available within Australian casinos. Indeed gamblers are free to move from one version to the other (e.g. real versus videolinked versus videogame and $2 versus $5 tables), but when the casino is crowded players may be constrained by issues such as access to the tables. Hence the within subjects design is quite appropriate and ecologically valid. Indeed the evaluation of preference and perceived risk actually requires people to be exposed to all conditions. The within subjects design does however allow the potential for carry-over effects. To address the potential for systematic effects of exposure to the apparatus, we presented the experimental conditions in a randomised order. Carry-over effects were considered by analysing the effects of the order in which the conditions were presented (i.e. 1st, 2nd, 3rd, 4th). There were no effects of order of presentation upon perceived risk as indicated by the payouts sought, indicating that it was indeed the videolink that influenced perceptions of risk. Nevertheless there were some indications that wagering became faster as the experiment progressed, but as conditions were randomly presented, the effect of exposure would not have had a systematic effect upon the appreciation of risk. A theoretical limitation of this study is the observation that videolinks appear to decrease perceived risk at times (e.g. online disinhibition and inappropriate behaviour over ChatRoulette), while they increase perceived risk at other times (e.g. aversion to rich communication channels in the anxious). An explanation could be that of reduced reliability or fidelity, such that the increased psychological distance imposed by the use of videolink would reduce the potential to influence people on the other end (Suler, 2004). This reduction of influential potential could lead to less risky bets because there is less potential to influence outcomes at their remote source. However, this reduced potential to influence could also result in an increase of inappropriate behaviour for there is lesser likelihood of censure. Chatroulette has many individuals prone to masturbation on their webcams and Chatroulette had to fit in some features such as a ‘‘report inappropriate behaviour’’ label and geolocation mapping functions in an attempt to reduce these sorts of behaviour. 4.4. Implications This study has implications for the social environment online. There is an element of risk associated with Internet use. Indeed so-
cial networking site users are more likely to be risk takers (Fogel & Nehmad, 2009). Thus, this study suggested that there would be a difference between risk-taking behaviour online (via video) and offline. As video has the potential to authenticate users, people seeking to engage in anti-social and risky behaviour that is aggressive and deceitful might want to avoid video technologies (Whitty & Carville, 2008). The Internet might promote disinhibited behaviour (Suler, 2004), but there may be a reluctance to rely on it for important outcomes. Organisations seeking to deliver services electronically may use videolink to increase trust, but there may still be a perception that it is not as good as collocation. 5. Conclusion The present study found that people were reluctant to take risks on remote events, particularly when events were of higher risk, and preferred to take risks on events occurring in close proximity. This research has implications for the implementation of videolink technology in organisations using collaborative technologies. A videolink might engender more trust than text, but it will elicit less trust than that afforded face to face. Acknowledgement The authors would like to acknowledge funding support from Gambling Research Australia (Tender No. 119/06). References Bechara, A., Damásio, A. R., Damásio, H., & Anderson, S. W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50, 7–15. Bekkering, E., & Shim, J. P. (2006). I2i trust in videoconferencing. Communications of the ACM, 49(7), 103–107. Brosig, J., Ockenfels, A., & Weimann, J. (2002). The effects of communication media on cooperation. German Economic Review, 4(2), 217–241. Campbell, J. (2006). Media richness, communication apprehension and participation in group videoconferencing. Journal of Information, Information Technology, and Organizations, 1, 87–96. Corritore, C. L., Kracher, B., & Wiedenbeck, S. (2003). On-line trust: Concepts, evolving themes, a model. International Journal of Human–Computer Studies, 58, 737–758. Daft, R. L., & Lengel, R. H. (1986). Organizational information requirements, media richness and structural design. Management Science, 32(5), 554–571. Fogel, J., & Nehmad, E. (2009). Internet social network communities: Risk-taking, trust, and privacy concerns. Computers in Human Behavior, 25(1), 153–160. Green, M. C. (2007). Trust and social interaction on the Internet. In A. N. Joinson (Ed.), The Oxford handbook of Internet psychology (pp. 43–51). New York: Oxford University Press. Horswill, M. S., & McKenna, F. P. (1999). The effect of perceived control on risk taking. Journal of Applied Social Psychology, 29(2), 377–391. Koenig-Lewis, N., Palmer, A., & Moll, A. (2010). Predicting young consumers’ take up of mobile banking services. International Journal of Bank Marketing, 28(5), 410–432. Langer, E. J. (1975). The illusion of control. Journal of Personality and Social Psychology, 32, 311–328. Lim, N. (2003). Consumers’ perceived risk: Sources versus consequences. Electronic Commerce Research and Applications, 2, 216–228. Paine Schofield, C. B., & Joinson, A. N. (2008). Privacy, trust and disclosure online. In A. Barak (Ed.), Psychological aspects of cyberspace: Theory, research and applications (pp. 13–31). New York: Cambridge University Press. Peter, J., Valkenburg, P. M., & Schouten, A. P. (2007). Precursors of adolescents’ use of visual and audio devices during online communication. Computers in Human Behavior, 23, 2473–2487. Phillips, J. G., Ostojic, P., & Blaszczynski, A. (in press). Mobile phones and inappropriate content. In M. C. Barnes & N. P. Meyers (Eds.), Mobile phones: Technology, networks and user issues. New York: Nova Science Publishers. Phillips, J. G., Jory, M. K., Wijenayake, L., & Hii, P. (2010). Videoconferencing capability and educational institutions. In A. T. Ragusa (Ed.), Interaction in communication technologies & virtual learning environments: Human factors (pp. 246–268). IGI Global. Polasik, M., & Wisniewski, T. P. (2009). Empirical analysis of internet banking adoption in Poland. International Journal of Bank Marketing, 27(1), 32–52. Riegelsberger, J., Sasse, M. A., & McCarthy, J. D. (2007). Trust in mediated interactions. In A. N. Joinson (Ed.), The Oxford handbook of Internet psychology (pp. 53–69). New York: Oxford University Press.
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Computers in Human Behavior journal homepage: www.elsevier.com/locate/comphumbeh
Computer-mediated communication and risk-taking behaviour Lynette Y.Q. Goh a, James G. Phillips a,⇑, Alex Blaszczynski b a b
School of Psychology & Psychiatry, Monash University, Australia Psychology Department, University of Sydney, Australia
a r t i c l e
i n f o
Article history: Available online 20 April 2011 Keywords: Videoconference Risk Gambling Internet Collaboration
a b s t r a c t In an unregulated environment Internet use is not without risk, and video has been proposed to influence riskiness and trust behaviour. This experiment explored the differences in willingness to take risks on events portrayed over the Internet via a videolink, relative to events occurring in close proximity (collocated). Thirty-four participants played a roulette game on a computer, wagering points upon the outcomes of spins of a real roulette wheel. The amounts, types of bets and the time to place them were analysed. It was found that confidence (points wagered) did not change, but people went for lower risk (when more was at stake), or thought more about the risks they took (when more was at stake) over a videolink. People accepted greater risk on outcomes occurring in close proximity, than those events portrayed over a videolink. Variations in perceived risk in response to online versus offline events probably reflect differences in the potential to influence outcomes. Crown Copyright Ó 2011 Published by Elsevier Ltd. All rights reserved.
1. Introduction The use of video for communication within organisations is increasing. Videolinks have been proposed to increase cooperation between organisational members (TenCate, 2007), to improve communication outcomes and offer better services online. Gambling syndicates have also used videolink (otherwise known as videoconferencing) technology to further authenticate the online gambling experience (The Star, 2009). As videolinks are becoming more pervasive it is important to understand how such technology might affect human behaviour, and as the Internet can be a poorly regulated environment this study specifically addresses whether videolink technologies affect human risk-taking behaviour.
Access to videoconferencing technology is becoming increasingly pervasive. Our surveys of university student populations (Phillips, Jory, Wijenayake, & Hii, 2010) have indicated that the proportions of students videoconferencing has risen from 17% in 2006 (N = 318) to 51.2% in 2010 (N = 203), with their possession of the necessary hardware increasing from 30% to 83% over the same period. Peter, Valkenburg, and Schouten (2007) found that 57% of the 1060 adolescents surveyed occasionally used webcams whilst instant messaging people, and 32% of them used microphones to enhance the visuo-auditory experience. Peter et al. (2007) suggested that people’s subjective perceptions affect their usage of videolink technology more than actual media features, finding that adolescents’ usage of webcams and microphones depended upon how important they found the lack of visual or auditory cues to be for them individually.
1.1. Videolink technology 1.2. Communication and collaboration Psychologists have studied computer-mediated communication (CMC), but previous work has primarily addressed text and audiobased interactions. However technological advancements are enhancing CMC, providing additional realism in the form of videolinks (e.g. Skype, GoogleMail). A person gains access to videolink technology if they have a webcam, a computer or laptop, the appropriate software application to use it and Internet access. High-speed broadband access improves the quality and frames per second of the video image seen. ⇑ Corresponding author. Address: School of Psychology & Psychiatry, Monash University (Bld. 17), Clayton, VIC 3800, Australia. Tel.: +61 3 9905 3914. E-mail address: [email protected] (J.G. Phillips).
Advocates of videolink technology suggest that it can improve communication. Videolink has the potential to improve communication because of its additional ‘‘richness’’. Media richness theory stresses that each communication channel carries a different amount and variety of information to its users (Daft & Lengel, 1986). According to Bekkering and Shim (2006, p. 104), a channel’s richness may consist of the ‘‘availability of instant feedback, the use of multiple cues (such as facial expressions, voice inflections, and gestures), the use of natural language for conveying a broad set of concepts and ideas, and the personal focus of the medium. Face-to-face communication is high in richness, while a typed note with numerical content is low’’.
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Organisations have adopted videolink technology to enhance collaboration. For instance the University of Washington opened the Odegaard Videoconference Studio to allow communication between groups on campus that were in different physical locations (TenCate, 2007). Research indicates that people are least likely to help in response to textual requests for assistance, while helping behaviour improves to requests for assistance over the phone, and helping is greatest when requests for assistance are made ‘‘in person’’ in the same physical location (Weinberger, 1981). Brosig, Ockenfels, and Weimann (2002) found that people who used video and audio cooperated on a level similar to that of faceto-face interaction (although it did take a longer time). If a communication channel contains less richness (meaning there is a loss of information from source to receiver), then people are less likely to trust the technology and information received (Riegelsberger, Sasse, & McCarthy, 2007).
1.3. Videolinks and perceived risk Videolink technology is being used for a variety of applications, not just for commercial functions but also for socialising (e.g. http://www.vdateonline.com/) and also for gambling (The Star, 2009). The decision to use such technology can be considered to involve a choice between ‘‘real’’ and ‘‘virtual’’ interaction, and such a choice is likely to be influenced by perceived risk. When using the internet technology socially online for friendship or relationships (Whitty, 2008) there is an element of risk. People tend to lie and present false identities online, more so than in face-to-face interaction, and deception can be hard to detect when it is computer mediated (Green, 2007). A degree of disinhibition online that is associated with diminished feedback appears to contribute to deceptive or harmful behaviours (Suler, 2004; Whitty & Carville, 2008). Online disinhibition has been discussed primarily within the context of text-based CMCs, while the potential contribution of video has rarely been addressed. Another area of increased risk where existing controls are challenged is in the area of internet gambling (Phillips, Ostojic, & Blaszczynski, in press). In a gambling context, deception occurs in a variety of ways. There can be dishonest payouts, game cheating, fake license claims and unethical business practices (e.g. http://www.casinomeister.com/rogue/). For instance, Sevigny, Cloutier, Pelletier, and Ladouceur (2005) considered whether online casinos provided misleading (inflated) payout rates during the ‘demo’ period and then reduce the odds when playing for real money. This study documented statistically that 39% of the 117 online casinos studied demonstrated misleading payout rates. To examine issues associated with the selection of ‘‘real’’ versus ‘‘virtual’’ interaction, the present study used a simulated gambling task to address perceptions of risk engendered by videolink technology. Psychology has had a long tradition of using simulated gambling tasks to address decision making and risk (Lim, 2003). Risk is present when there is the possibility of negative outcomes in a situation (Green, 2007). People are generally risk averse (Schneider & Lopes, 1986). Simply put, if a situation is deemed to be risky people will take less risks with their behaviour but in a less risky situation people will display more risk-taking behaviour. Perceived risk apparently affects people’s risk-taking behaviour more than the actual risk present (Horswill & McKenna, 1999; Paine Schofield & Joinson, 2008), and this influences how much risk a person is willing to take in a situation. In consumer behaviour research, the higher the perceived risk of an Internet service, the less favourably regarded is the use of that Internet service (Polasik & Wisniewski, 2009). For instance, Fogel and Nehmad (2009) looked at risk-taking, trust and privacy concerns on Internet social networks. They found that individuals who utilise social network-
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ing websites (Facebook and MySpace) have greater risk taking attitudes than those who do not. Risk can be offset by considerations of trust. Trust serves to reduce fear and perceived risk and uncertainty in risky situations (Koenig-Lewis, Palmer, & Moll, 2010). Perceived risk can be lessened when trust is built by a variety of means. In electronic commerce, if the object of trust behaves in an honest, reputable and predictable manner, it gains credibility (Corritore, Kracher, & Wiedenbeck, 2003). Videolink technology has the potential to reduce perceived risk by building trust via the availability of visual images. 1.4. Aims and hypotheses The present study was conducted to examine whether risk-taking behaviour would change in response to outcomes conveyed through the computer over a videolink as compared to outcomes occurring in the same physical location. This experiment sought to examine differences in willingness to take risks on events portrayed over the Internet, relative to events occurring in close proximity (collocated). Human risk-taking has previously been examined using gambling analogues (e.g. Bechara, Damásio, Damásio, & Anderson, 1994). The present study used a game of roulette, where the outcomes were determined by the spin of a real roulette wheel. The roulette wheel could be in the same physical location (collocated), or in a remote location where the outcome was conveyed by a videolink. As videolinks afford a less rich interaction (Bekkering & Shim, 2006) than face to face communication, outcomes portrayed over a videolink are likely to be perceived to be less reliable and thus more risky. It was thus predicted that people would be less willing to wager on the roulette game when a videolink was used to display the roulette wheel. As the videolink is not as rich an experience, it was predicted that people would prefer physical collocation, which is comparable to face-to-face interaction, over videolink communication of outcomes. 2. Method 2.1. Participants There were 34 participants, 25 of the participants were male (age: M = 23.04, SD = 4.13) and nine were female (age: M = 23.00, SD = 5.83). Participants were screened for prior gambling problems and were reimbursed for their time ($6 per hour). This project had ethical approval from the Monash University Human Research Ethics Committee. 2.2. Apparatus A personal computer was used with custom written software that recorded wagering patterns and timed responses. A 22 cm diameter French style roulette wheel manufactured by Dal Rossi of Italy was employed. A printed copy of the roulette wheel layout was also available. The computer software roulette game emitted a beep that was to initiate the beginning of each bet. A message ‘‘Place your bets’’ would then appear on the screen. Participants would have 3 s to place a bet down otherwise that bet would be registered as a null bet, with the computer moving onto the next betting opportunity. This was to simulate a degree of time pressure as found in casinos. Participants entered their wagers (points 1–9) and then specified the location of their bets by inserting a first number and a last number, similar to the call betting system used in casinos. Only recognised call bets were accepted. The location of the bets was highlighted onscreen on the roulette layout. The roulette layout
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in the software was similar to the layout in casinos with the exception that players could not bet on odds/evens, and red/black. Nor did the software allow the corner bet of 0–3 that had the odds of 8–1. Payouts and odds for each bet were then displayed before moving onto the next bet within the same spin. Up to 15 bets could be placed for each spin, but participants need not place all 15. The total amount of bets placed for each spin was indicated at the bottom of the screen. After the bets were placed, an experimenter spun the roulette wheel. After the spin, the experimenter entered the number spun and that number would appear in the row of 10 previous numbers that have been spun before. This row of numbers was constantly shown in the game as a decision aid. Participants were informed of the result of the spin from an onscreen message that included how much they bet on the number spun and the payout. The total amount won or lost was displayed at the bottom-right of the computer screen per condition. To examine the effect of computer mediation communication upon wagering behaviour, the locations of the wheel were either: collocated (wheel and experimenter present in the same room as participant) or, videolink (wheel and experimenter in a separate room with the wheel actions displayed on a computer monitor inclusive of real-time video and audio feeds using Marratech software). To manipulate risk, the points participants wagered were multiplied. In the low risk condition, points were multiplied by 1. In the high risk condition, points were multiplied by 5. 2.3. Procedure The experimenter explained how the roulette game worked and described the four conditions. Participants were instructed to try to win as many points as possible as iPod Classics were to be given to the two highest scorers. In the absence of real money, the prizes of iPod Classics served as motivators to encourage participants to take a more considered approach when betting points. The participants did a practice trial of two spins before starting on the experiment itself. Responses during the roulette game were logged automatically by the computer. Outcomes, payouts and totals were determined. For the 2 2 risk by location design, each participant had to complete four conditions. The conditions were low risk and collocated; low risk and videolink; high risk and collocated; high risk and videolink. Conditions were presented in a randomised order to ensure that any order or practice effects would not have a systematic effect on the factors of interest. In between the four conditions there was a short rest interval of about 3 min for the participants while the equipment was being set up. It took between 1 and 2 h per participant for the entire roulette game. After they have played the game, the experimenter asked the participants which wheel location (collocation or videolink) they preferred and why. At the end of the experimental task, participants were debriefed on the purpose of the study and the irrational beliefs that gamblers have.
3. Results There are a variety of ways of quantifying wagering within roulette (Wagenaar, 1988). One way to measure the degree of preferred risk was to look at the mean amount of points bet. As there is also considerable opportunity to vary betting strategies, the mean amount of numbers covered on the roulette layout was also examined across every condition. As roulette offers a wide range of betting opportunities, we analysed the payouts sought. This was the average amount that would be won if a participant’s numbers came up. Two-way repeated measures Analysis of
Table 1 Descriptive statistics for the four conditions between risk and location factors levels. Low
Mean bet Numbers covered Payout sought Reaction time bet Reaction time first no. Reaction time last no.
High
Collocation
Videolink
Collocation
26.10 (3.44) 20.51 (1.27)
30.72 (4.64) 20.63 (1.38)
128.51 (25.58) 111.87 (20.89) 20.10 (1.27) 21.83 (1.22)
Videolink
53.33 (10.17) 55.12 (10.13) 257.23 (59.54) 181.59 (41.75) .35 (.03)
.35 (.03)
.31 (.03)
.35 (.03)
1.26 (.15)
1.15 (.11)
1.04 (.11)
1.22 (.13)
.61 (.05)
.63 (.05)
.56 (.05)
.67 (.06)
Note: standard errors are in parentheses. Times are in seconds.
Variance (ANOVA) was conducted on all of the meaningful variables. The mean number of points bet was examined because it taps into the issue of confidence and trust. The descriptives for the mean number of bets the participants placed across each condition is shown in Table 1. A significant main effect for risk was found, F (1, 33) = 28.51, p < .01, g2 = .46. Participants placed significantly fewer points for their bets in the low risk conditions and more points in the high risk conditions, indicating that a manipulation of risk was effective. There was no interaction between Risk and Location, and neither was there a significant main effect for Location. A common strategy when playing roulette is to place bets covering more of the layout (Wagenaar, 1988). This strategy is intended to reduce risk for the player. The mean number of numbers covered was analysed. There was no effect of Risk (F (1, 33) = 0.42, p > .05, g2 = .01). Nor was there an effect of Location (F (1, 33) = 3.27, p = .08, g2 = .09), although people tended to cover more of the roulette layout within the videolinked condition (see Table 1). There was no interaction between Risk and Location, suggesting that participants tended to cover the same amount of the layout during wagering across conditions. Another index of risk-taking behaviour is the mean possible payout participants sought. For instance, a participant that placed 2 points on a single 8/1 bet would obtain a value of 16 for this measure. The mean possible payout measured the odds selected by participants. There was a significant main effect found for Risk on the possible payouts, F (1, 33) = 16.39, p < .01, g2 = .33. There was also a significant main effect for the Location of the roulette wheel, F (1, 33) = 6.92, p < .05, g2 = .17 and a significant interaction between Location and Risk upon possible payouts, F (1, 33) = 5.69, p < .05, g2 = .15. This indicates that the effect of roulette wheel location varied as a function of risk. To interpret this interaction, the simple main effects were calculated. It was found that there was no significant effect of Location upon possible payouts sought for the low risk conditions, F (1, 33) = .01, p > .05 (see Fig. 1), but there was a significant effect of Location for the high risk condition F (1, 33) = 10.87, p < .05. This meant that people sought higher payouts when collocated and higher risk, but sought significantly lower payouts when videolinked and higher risk. Changes in risk-taking behaviour may also be inferred from the times that participants took to place down their bets and register the first and last numbers of their ‘‘call bets’’. Slower reaction times would imply more consideration or concern when making decisions. There were neither significant effects nor interactions for the mean reaction times to place down their bets or when keying in their last number of their ‘‘call bet’’. But a significant interaction was found between the two factors for the mean reaction time to key in their first number, F (1, 33) = 4.79, p < .05, g2 = .13.
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300
Mean Payout Sought
Collocated 250 200
a significant preference for a particular location. The expected range was between 1.00 (collocation) and 2.00 (videolink). The Kolmogorov–Smirnov z-score was statistically significant at 4.70, p < .001. There was a marked preference for collocation among the sample.
Videolink 150
4. Discussion
100 50 0 Low Risk
High Risk
Risk Fig. 1. Preferred risk by the mean average payouts as a function of the location of the roulette wheel and the amount of risk.
Mean RT First No. (sec)
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1.4
Videolink 1.2
1.0
To understand psychological mechanisms underpinning the use of videolink technologies, this study considered whether videolinking of events alters perceptions of risk and risk-taking behaviour. Participants were asked to wager points at various levels of risk upon outcomes that could be collocated with the participant or conveyed over a videolink. Participants played a roulette game on the computer and their level of risk-taking behaviour was measured with a variety of indices. Although participants did not alter the number of points wagered, or the amount of the roulette layout covered, they selected bets with lower odds in the riskier videolinked condition and appeared to spend more time thinking about bet locations in higher risk videolinked condition. This demonstrated that the videolink altered the appreciation of risk. Indeed people preferred the collocated to the videolinked versions of roulette.
4.1. Location
Collocated 0.8 Low Risk
High Risk
Risk Fig. 2. Mean reaction times (in seconds) for first call bet when wheel location was varied and at low risk or high risk.
As there was a significant interaction between location and risk, simple main effects were examined to identify where the differences in reaction times to position bets were occurring. It was found that risk only had an effect on response latencies in the collocated condition, F (1, 33) = 5.25, p < .05. People were significantly slower in deciding their first number in the low risk condition than in the high risk condition, but this occurred when the roulette wheel was collocated (see Fig. 2). People thought less about placing high risk bets when collocated. As it is conceivable that continued exposure to the videolink might strengthen trust in the technology, the effects of trial block (viz 1st, 2nd, 3rd condition experienced) was analysed. Such an analysis considers whether there is a systematic effect of exposure or practice (but otherwise confounds experimental manipulations). We separately analysed the effects of trial block number, comparing the first, second, third and fourth conditions that participants experienced. There was no effect of trial block number upon the average amount bet (F (3, 99) = 0.220, p > .05) or the average payout sought (F (3, 99) = 1.224, p > .05). Hence exposure or practice did not influence perception of risk. However, familiarity did influence the amount of thought put into wagering. As participants became more familiar with the task, they required less time to indicate the first (F (3, 99) = 11.824, p < .001, g2 = .26) and second (F (3, 99) = 8.576, p < .001, g2 = .21) number of their call bets. When the experiment had concluded, the participants were asked which roulette wheel location they preferred (collocation or videolink). A one-sample Kolmogorov–Smirnov test was conducted against a uniform distribution to see whether there was
It was anticipated that people would wager less, preferring to take less risk when the videolink was used to transfer the roulette wheel image from an external location onto the computer screen. This hypothesis was supported by analysing a variety of measures of preferred risk. The mean average payouts sought varied as a function of risk and roulette wheel location. This measure was sensitive to the types of odds (i.e. 35-1, 17-1, 11-1, 8-1, 5-1, 2-1, 1-1) selected. People sought lower payouts, seeming to perceive higher risk when outcomes were conveyed over a videolink. In addition, the reaction time taken to select the first number in call bets varied significantly with location and risk. Collocation was treated as lower risk, and people thought less about bet placements at higher risk when collocated. The greater illusion of control when wagering ‘‘in person’’ (Langer, 1975) indicates that people are more trusting when collocated, and this is as would be expected from media richness theory where face-to-face interaction has the richer amounts of interpersonal cues (Bekkering & Shim, 2006; Campbell, 2006). There was no difference in the number of points placed or the amount of numbers covered on the roulette layout. Although people commonly vary the amount of the layout covered, this is by no means a uniform strategy (Wagenaar, 1988). Participants could have employed other betting strategies. They sought a lower payout rate that tended to cover more numbers on the roulette layout, thus taking less risk. However, there was no effect of location for the mean amount of bets placed, which suggested that players’ confidence did not vary, just their evaluation of risk. Although there were some slight indications that people wagered fewer points when the roulette wheel was shown through videolink, it was quite marginal and not significant. Therefore the present data suggest that the videolink was not affecting confidence as measured by the points participants wagered. Instead, people varied the riskiness of their wagers. People displayed lower risk-taking behaviour in the videolink condition than when collocated but again, it was mainly for the high risk situation. As these effects were found for high risk situations, it seems that risk and the videolink potentiated their effects making people more aware and cautious of what they were wagering on.
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4.2. Preferred mode People chose collocation when asked which location of the roulette wheel they preferred. This finding supported previous research about communication channel richness where people would favour face-to-face interaction more than any other communication medium because a face-to-face interaction provides far more informational cues (Bekkering & Shim, 2006). Nevertheless, the number of videolink users is increasing. The increase in users could reflect convenience. Indeed Wood, Williams and Lawton’s (2007) reported one reason for people choosing to gamble online over land-based venues was because of convenience. When given the choice between using videolink or having nothing, people would probably choose to implement videolink even though to them collocation was the preferred choice. 4.3. Limitations The present study employed a within subjects design that makes obvious any comparisons between different formats. We do not think that a within subjects design is of concern as it allows comparisons of perceived risk while controlling individual differences in predispositions towards risk taking (participants serve as their own controls). All the forms of roulette in this experiment are available within Australian casinos. Indeed gamblers are free to move from one version to the other (e.g. real versus videolinked versus videogame and $2 versus $5 tables), but when the casino is crowded players may be constrained by issues such as access to the tables. Hence the within subjects design is quite appropriate and ecologically valid. Indeed the evaluation of preference and perceived risk actually requires people to be exposed to all conditions. The within subjects design does however allow the potential for carry-over effects. To address the potential for systematic effects of exposure to the apparatus, we presented the experimental conditions in a randomised order. Carry-over effects were considered by analysing the effects of the order in which the conditions were presented (i.e. 1st, 2nd, 3rd, 4th). There were no effects of order of presentation upon perceived risk as indicated by the payouts sought, indicating that it was indeed the videolink that influenced perceptions of risk. Nevertheless there were some indications that wagering became faster as the experiment progressed, but as conditions were randomly presented, the effect of exposure would not have had a systematic effect upon the appreciation of risk. A theoretical limitation of this study is the observation that videolinks appear to decrease perceived risk at times (e.g. online disinhibition and inappropriate behaviour over ChatRoulette), while they increase perceived risk at other times (e.g. aversion to rich communication channels in the anxious). An explanation could be that of reduced reliability or fidelity, such that the increased psychological distance imposed by the use of videolink would reduce the potential to influence people on the other end (Suler, 2004). This reduction of influential potential could lead to less risky bets because there is less potential to influence outcomes at their remote source. However, this reduced potential to influence could also result in an increase of inappropriate behaviour for there is lesser likelihood of censure. Chatroulette has many individuals prone to masturbation on their webcams and Chatroulette had to fit in some features such as a ‘‘report inappropriate behaviour’’ label and geolocation mapping functions in an attempt to reduce these sorts of behaviour. 4.4. Implications This study has implications for the social environment online. There is an element of risk associated with Internet use. Indeed so-
cial networking site users are more likely to be risk takers (Fogel & Nehmad, 2009). Thus, this study suggested that there would be a difference between risk-taking behaviour online (via video) and offline. As video has the potential to authenticate users, people seeking to engage in anti-social and risky behaviour that is aggressive and deceitful might want to avoid video technologies (Whitty & Carville, 2008). The Internet might promote disinhibited behaviour (Suler, 2004), but there may be a reluctance to rely on it for important outcomes. Organisations seeking to deliver services electronically may use videolink to increase trust, but there may still be a perception that it is not as good as collocation. 5. Conclusion The present study found that people were reluctant to take risks on remote events, particularly when events were of higher risk, and preferred to take risks on events occurring in close proximity. This research has implications for the implementation of videolink technology in organisations using collaborative technologies. A videolink might engender more trust than text, but it will elicit less trust than that afforded face to face. Acknowledgement The authors would like to acknowledge funding support from Gambling Research Australia (Tender No. 119/06). References Bechara, A., Damásio, A. R., Damásio, H., & Anderson, S. W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50, 7–15. Bekkering, E., & Shim, J. P. (2006). I2i trust in videoconferencing. Communications of the ACM, 49(7), 103–107. Brosig, J., Ockenfels, A., & Weimann, J. (2002). The effects of communication media on cooperation. German Economic Review, 4(2), 217–241. Campbell, J. (2006). Media richness, communication apprehension and participation in group videoconferencing. Journal of Information, Information Technology, and Organizations, 1, 87–96. Corritore, C. L., Kracher, B., & Wiedenbeck, S. (2003). On-line trust: Concepts, evolving themes, a model. International Journal of Human–Computer Studies, 58, 737–758. Daft, R. L., & Lengel, R. H. (1986). Organizational information requirements, media richness and structural design. Management Science, 32(5), 554–571. Fogel, J., & Nehmad, E. (2009). Internet social network communities: Risk-taking, trust, and privacy concerns. Computers in Human Behavior, 25(1), 153–160. Green, M. C. (2007). Trust and social interaction on the Internet. In A. N. Joinson (Ed.), The Oxford handbook of Internet psychology (pp. 43–51). New York: Oxford University Press. Horswill, M. S., & McKenna, F. P. (1999). The effect of perceived control on risk taking. Journal of Applied Social Psychology, 29(2), 377–391. Koenig-Lewis, N., Palmer, A., & Moll, A. (2010). Predicting young consumers’ take up of mobile banking services. International Journal of Bank Marketing, 28(5), 410–432. Langer, E. J. (1975). The illusion of control. Journal of Personality and Social Psychology, 32, 311–328. Lim, N. (2003). Consumers’ perceived risk: Sources versus consequences. Electronic Commerce Research and Applications, 2, 216–228. Paine Schofield, C. B., & Joinson, A. N. (2008). Privacy, trust and disclosure online. In A. Barak (Ed.), Psychological aspects of cyberspace: Theory, research and applications (pp. 13–31). New York: Cambridge University Press. Peter, J., Valkenburg, P. M., & Schouten, A. P. (2007). Precursors of adolescents’ use of visual and audio devices during online communication. Computers in Human Behavior, 23, 2473–2487. Phillips, J. G., Ostojic, P., & Blaszczynski, A. (in press). Mobile phones and inappropriate content. In M. C. Barnes & N. P. Meyers (Eds.), Mobile phones: Technology, networks and user issues. New York: Nova Science Publishers. Phillips, J. G., Jory, M. K., Wijenayake, L., & Hii, P. (2010). Videoconferencing capability and educational institutions. In A. T. Ragusa (Ed.), Interaction in communication technologies & virtual learning environments: Human factors (pp. 246–268). IGI Global. Polasik, M., & Wisniewski, T. P. (2009). Empirical analysis of internet banking adoption in Poland. International Journal of Bank Marketing, 27(1), 32–52. Riegelsberger, J., Sasse, M. A., & McCarthy, J. D. (2007). Trust in mediated interactions. In A. N. Joinson (Ed.), The Oxford handbook of Internet psychology (pp. 53–69). New York: Oxford University Press.
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