1. Consumer-Led Behavioral Intention and Psychological Risk Aversion
toward Location-based Social Media Mobile Apps
Structural Abstract
Purpose – The purpose of the current study is to investigate what consumers are more like to
use location-based social media mobile apps and what the underlying mechanism is for
revealing their GPS locations.
Design/methodology/approach – The study employs an online survey using m-turk to adapt
anticipated gains of using location-aware mobile apps and anticipated losses of not using
location-aware mobile apps. A structural equation model is used to test the hypothesized
relations among constructs (e.g. subjective norms/social value, privacy concern,
entertainment, perceived behavior control, intention, risk aversions, location-based check-in
behavior)
Findings – Our aim is to find that social pressure (subjective norm), privacy concern about
revealing users’ GPS location, entertainment, and behavior control contribute to social media
“check-in” behavior intention and risk aversion (anticipated gains of using location-aware
mobile apps and anticipated losses of not using location-aware mobile apps), which in turn
eventually leads to “check-in” behavior on mobile apps.
Research limitations/implications – This study mainly shows consumer-led behavioral
intention to use location-aware mobile apps. The future research will be able to conduct
research on current location-aware apps users and their actual responses on motivation as
well as marketing/advertising responses.
Practical implications – Marketers are able to understand consumers’ psychological
motivation/intention/need to use location-based mobile apps. Thus, they are able to obtain
more app users by providing better mobile app environment for consumer experiences and
develop advertising/marketing strategies on those users.
Originality/value – Although there are many studies on social consumer behavior, little is
known about location-based social mobile app users’ intentions who must reveal their GPS
location to share with social friends and marketers.
Keywords: Location-based social media mobile apps, planned behavior theory, prospect
theory
The track the paper is intended for Online Marketing & Social Media

2. Introduction
As mobile marketing/advertising is rapidly growing, the future trend in mobile marketing is
moving forward to location-aware mobile marketing/advertising (Hendrix, 2015). The new
mobile strategies focus on consumers with mobile phones, especially for location-based
marketing (Hendrix, 2015).
Since location-based mobile marketing (geotargeting) are between the digital and physical
world (Heggestuen, 2014), mobile apps with GPS function have given an added value to
consumers, not only traditional location services, but also valuable information (e.g.
discount/marketing offers) through voluntarily sharing users’ location information. Thus,
marketers are able to engage with their consumers any time, selected time (e.g. morning,
night), or real-time through consumers’ mobile apps. Marketers are able to target consumers
on their mobile device to make them drive foot traffic and increase sales at brick-and-mortar
stores (Heggestuen, 2014).
The mobile apps eventually could be integrated with advanced technology to track
consumers’ location down at shopping malls, grocery stores, subways, attractions, etc.
(Hendrix, 2015). Thus marketers can send real-time attractive coupons or advertising
messages to consumers who are around the radius that mobile devices can catch.
Traditional mobile advertising can expand from non-personalized mass messaging (Richard
& Meuli, 2013). Location-based mobile apps add more values on geotrageting marketing to
identify specific consumers through geo-consumer profiling. Thus, the current study is to
examine consumers’ intentions to use those location-based mobile apps in their social circles.
In the future, based on understanding underlying mechanism for revealing users’ GPS
locations, marketers and advertisers are able to target consumers who use or are willing to use
location-based mobile apps for their marketing purpose.
In sum, a conceptual framework (Figure 1) is developed to explore the relationship of
anticipated factors and consequences of mobile app usage intention. This study is to
investigate consumers’ behavioral intention to use location-aware mobile apps. Specifically,
it is 1) to determine the attitude towards consumer-led check-in intention; 2) to determine the
social media “Check-in” intention/ risk aversion towards location-based mobile apps; 3) to
find out the relation between the mobile users’ intention/ risk aversion and check-in behavior;
and 4) to offers suggestions to the practitioner who are able to develop consumer friendly
apps in order to obtain mobile app users.
Figure 1. Consumer-led behavioral intention & risk aversion on mobile “Check-in” behavior

3. Conceptual background and hypotheses
In this study, we use Theory of Planned Behavior (Ajzen, 1991), Prospect Theory (Kahneman
and Tversky 1979) and Conformity Theory (Crutchfield, 1955) to understand consumers’
voluntarily “Check-in” behavioral intention. Whenever consumers go to restaurants, stores,
etc. consumers do social “check-in” using location-based mobile apps (e.g. Swarm) for social
engagement. So their friends know where they are in order to share information and users
also can benefits to have information about restaurants and coupons, and build social
relationship/engagement with their social circle.
First, Ajzen’s theory of planned behavior (1992) is the guiding research model framework.
This theory is to predict behavior intentions and there are several constructs (e.g. attitudes,
subjective norms, perceived behavior control) to measure consumers’ behavioral intentions.
We modify some constructs for the current study in order to reflect the purpose of the current
study.
In the previous study (Richard & Meuli, 2013), subjective norm and entertainment
significantly influenced behavior intention of permission-based location-aware advertising.
Moreover, previous studies show that privacy issues (Okazaki, Molina, & Hirose, 2012),,
attitude (Haghirian & Madlberger, 2005; Oh &Xu, 2003), and subjective norms (H. H. Bauer,
Reichardt, Barnes, & Neumann, 2005), and technological self-efficacy (Compeau & Higgins,
1995; Neill & Richard, 2012) (in our study-perceived behavior control) influence consumers’
acceptance toward technology related to mobile advertising/marketing.
Second, conformity is also the theoretical concept for this current study. It is defined as
yielding to consumers’ group pressures in their social circle (Crutchfield, 1955). According
to Crutchfield (1955), it is also known as majority influence as group pressures. Due to social
pressure in social circle based on conformity concept, we hypothesize that there will be a
positive relationship between social pressure (subjective norm) and behavioral intention (or

4. check-in behavior if consumers already adapted to these kind of apps). Therefore, the
following hypotheses are proposed:
H1: Subjective norm/social pressure is positively related to intention (or check-in behavior).
H2: Privacy concern is negatively related to intention (or check-in behavior).
H3: Entertainment is positively related to intention (or check-in behavior).
H4: Perceived behavior control is positively related to intention (or check-in behavior).
Third, we use Prospect Theory (Kahneman and Tversky, 1979) that is consumers’ decision
making under uncertainty and consumers have value in terms of anticipated gains or losses
for subsequent evaluation and choice (e.g. action or inaction). In the previous study, Byun
and Sternquist (2012) used this theory on consumer behavior and developed the
measurements of anticipated buying and gains and anticipated losses of not buying. We
modify their scales to measure anticipated gains of using location-aware mobile apps and
anticipated losses of not using location-aware mobile apps. In the Byun and Sternquist’ study
(2012), the authors explain that prospect theory predicts consumers relate greater
psychological discomfort with losses than pleasure with gains due to the loss aversion
propensity. Based on prospect theory, we propose that consumers react to location-based
mobile apps and its marketing by assigning values to the anticipated gains of social
engagement in social circle, information, and ad coupons and anticipated losses of not using
those apps. Therefore, we propose the following hypotheses.
H5: Anticipated gains of using location-aware mobile apps strengthen the relationship
between subjective norm and intention (or check-in behavior).
H6: Anticipated gains of using location-aware mobile apps moderate the relationship
between privacy concern and intention (or check-in behavior).
H7: Anticipated gains of using location-aware mobile apps strengthen the relationship
between entertainment and intention (or check-in behavior).
H8: Anticipated gains of using location-aware mobile apps strengthen the relationship
between perceived behavior control and intention (or check-in behavior).
H9: Anticipated losses of Not using location-aware mobile apps strengthen the relationship
between subjective norm and intention (or check-in behavior).
H10: Anticipated losses of Not using location-aware mobile apps moderate the relationship
between privacy concern and intention (or check-in behavior).

5. H11: Anticipated losses of Not using location-aware mobile apps strengthen the relationship
between entertainment and intention (or check-in behavior).
H12: Anticipated losses of Not using location-aware mobile apps strengthen the relationship
between perceived behavior control and intention (or check-in behavior).
Methodology
In this study, we use an online survey using M-turk (Amazon Mechanical Turk) consumers
about 150 participants. Survey participants receive a monetary reward. We mainly use CFA
to purify measurements and SEM (Structural Equation Modeling) to find structural paths. We
adapt the existing scales and modify them into our research context (mobile app usage). We
examine the validity and reliability of the constructs. Finally, we conduct a SEM analysis on
the hypothesized relationships.
Scales
Entertainment: Ducoffe (1996)
(Revised/modified questionnaires)
I think a mobile location-based check-in app would be enjoyable.
I think a mobile location-based check-in app would be pleasing.
I think a mobile location-based check-in app would be fun to use.
I think a mobile location-based check-in app would be exciting.
I think a mobile location-based check-in app would be entertaining.
Privacy concern: Smith et al (1996) concern for unauthorized secondary use.
I am paranoid that people through mobile apps would know where I am.
Online companies should not use personal information (GPS-location) for any purpose unless
it has been authorized by the individual who provided information.
When people give personal location (GPS) information to an online company for some
reason, the online company should never use the information for any other reason.
Online companies should never share personal location information with other companies
unless it has been authorized by the individuals who provided the information.
Subjective Norm: Adapted from Shimp and Kavas (1984), Richard and Meuli (2013)
If I use a mobile location-based check-in app (location-based apps), most of the people who
are important to me (in my social circle) will regard it as valuable.
If I use a mobile location-based check-in app (location-based apps), most of the people who
are important to me (in my social circle) will regard it as valuable.
People who are important to me (in my social circle) would think that I should use a mobile
location-based check-in app (location-based apps).
If I use a mobile location-based check-in app (location-based apps), most of people who are
important to me (in my social circle) would regard it as wise.
Scales (questionnaire) Adapted from Byun and Sternquist (2012)

6. Anticipated Gains of Buying (modified)
Social engagement in social circle, information, and ad coupons and anticipated losses of not
using those apps.
Using location-based mobile apps (e.g. Swarm) would enhance my social engagement with
social network friends.
Using location-based mobile apps (e.g. Swarm) would make me feel social belonging when
my social media friends use in my social circle.
Using location-based mobile apps (e.g. Swarm) would make me information savvy (e.g.
coupon, restaurant information, etc.) when my social media friends use in my social circle.
Anticipated Losses of Not Buying
If I do not use location-based mobile apps (e.g. Swarm), I would regret it later because my
friends would start to use it.
I thought that it would be a loss about discount/coupon benefits if I do not use location-based
mobile apps (e.g. Swarm).
If I do not get it immediately, I would lose an opportunity to purchase products with discount
benefits
Results (Research in Progress): Results will be provided upon request.
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