66
may heighten consumer awareness of potential improper access to their
data stored in the cloud, and consequently, increase their concerns around
such access. The Errors measure of concern focuses on individuals’ concerns that the organisation storing their personal information does not
have the measures in place to prevent and correct errors in the data (Smith
et al. 1996). This dimension may not be relevant in all consumer cloud
contexts, but issues around controlling data flows which are inherent in
the cloud may cause concern around organisations’ ability to track information, and as a result their capabilities to identify and remedy errors.
The Control dimension focuses on individuals’ concerns regarding the
lack of control they have over their personal information (Malhotra et al.
2004). Issues around control over data has been highlighted as an important cloud privacy issue that warrants exploration (Sun et al. 2011; Pearson
and Benameur 2010). The Awareness dimension centres around individuals’ concerns regarding their lack of awareness of how an organisation uses
and protects their personal information (Malhotra et al. 2004). Awareness
represents another core concern in the cloud context, with lack of transparency around where data is stored and the protection mechanisms in
place (e.g. Singh et al. 2015). It is important to therefore examine (1) if
consumers lack awareness of privacy practices in the cloud and (2) if a lack
of awareness heightens concerns for the privacy of one’s personal
information.
The broader privacy literature offers a rich theoretical base from which
the role of privacy in cloud computing can be advanced. Privacy theories
are typically discussed from five perspectives—(1) drivers of privacy concern, (2) behavioural consequences, (3) trade-offs, (4) institutional drivers
and (5) individual factors (Li 2012). In contrast to the broader literature,
the privacy research in the cloud context is relatively nascent. A review of
the literature did not identify any studies leveraging theories in four of
these five categories. However, two related studies drew on privacy calculus theory (PCT), a theory commonly utilised to understand the tradeoffs between the benefits and the risks associated with the behaviour in
question such as information disclosure or using a new technology (Culnan
and Armstrong 1999). PCT posits that individuals engage in a cognitive
comparison of the benefits and potential negative outcomes which may
result from using a certain technology (Culnan and Armstrong 1999).
According to this theory, individuals will utilise the technology as long as
their perceptions of the benefits outweigh their risk perceptions (Culnan
1993). The first study focused on consumers’ willingness to disclose
G. FOX
may heighten consumer awareness of potential improper access to their
data stored in the cloud, and consequently, increase their concerns around
such access. The Errors measure of concern focuses on individuals’ concerns that the organisation storing their personal information does not
have the measures in place to prevent and correct errors in the data (Smith
et al. 1996). This dimension may not be relevant in all consumer cloud
contexts, but issues around controlling data flows which are inherent in
the cloud may cause concern around organisations’ ability to track information, and as a result their capabilities to identify and remedy errors.
The Control dimension focuses on individuals’ concerns regarding the
lack of control they have over their personal information (Malhotra et al.
2004). Issues around control over data has been highlighted as an important cloud privacy issue that warrants exploration (Sun et al. 2011; Pearson
and Benameur 2010). The Awareness dimension centres around individuals’ concerns regarding their lack of awareness of how an organisation uses
and protects their personal information (Malhotra et al. 2004). Awareness
represents another core concern in the cloud context, with lack of transparency around where data is stored and the protection mechanisms in
place (e.g. Singh et al. 2015). It is important to therefore examine (1) if
consumers lack awareness of privacy practices in the cloud and (2) if a lack
of awareness heightens concerns for the privacy of one’s personal
information.
The broader privacy literature offers a rich theoretical base from which
the role of privacy in cloud computing can be advanced. Privacy theories
are typically discussed from five perspectives—(1) drivers of privacy concern, (2) behavioural consequences, (3) trade-offs, (4) institutional drivers
and (5) individual factors (Li 2012). In contrast to the broader literature,
the privacy research in the cloud context is relatively nascent. A review of
the literature did not identify any studies leveraging theories in four of
these five categories. However, two related studies drew on privacy calculus theory (PCT), a theory commonly utilised to understand the tradeoffs between the benefits and the risks associated with the behaviour in
question such as information disclosure or using a new technology (Culnan
and Armstrong 1999). PCT posits that individuals engage in a cognitive
comparison of the benefits and potential negative outcomes which may
result from using a certain technology (Culnan and Armstrong 1999).
According to this theory, individuals will utilise the technology as long as
their perceptions of the benefits outweigh their risk perceptions (Culnan
1993). The first study focused on consumers’ willingness to disclose
G. FOX