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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Designing Mobile Technology to Promote Sustainable Food Choices</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>General Terms Design</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Human Factors</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Theory.</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Conor Linehan, Jonathan Ryan, Mark Doughty, Ben Kirman, Shaun Lawson Lincoln Social Computing Research Centre University of Lincoln</institution>
          ,
          <addr-line>Brayford Pool Lincoln, LN6 7TS</addr-line>
          ,
          <country country="UK">UK</country>
        </aff>
      </contrib-group>
      <pub-date>
        <year>2010</year>
      </pub-date>
      <fpage>7</fpage>
      <lpage>10</lpage>
      <abstract>
        <p>This paper is an experience report based on challenges encountered when designing scalable mobile persuasive HCI applications to help users make informed choices over their food consumption. We recently developed Tagliatelle, a social tagging system to help users to accurately monitor and assess their dietary behaviour and to promote healthier food choices. In this paper we propose a similar system in order to help users understand the sustainability of their food choices. We discuss the challenges inherent in doing so, and extrapolate some important issues that need to be addressed by technological developments that aim to persuade users to adopt more sustainable behaviours. H.5.3 [Group and computing.</p>
      </abstract>
      <kwd-group>
        <kwd>eol&gt;Eco-feedback</kwd>
        <kwd>sustainability</kwd>
        <kwd>sustainable consumption</kwd>
        <kwd>tagging</kwd>
        <kwd>feedback</kwd>
        <kwd>persuasive</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>1. INTRODUCTION</title>
    </sec>
    <sec id="sec-2">
      <title>1.1 Background</title>
      <p>
        Recent studies have identified that topsoil erosion [17], depletion
of fish stocks [
        <xref ref-type="bibr" rid="ref6">13</xref>
        ], tainting of meat products, depletion of oil
reserves and climate change can all be linked to the method in
which food is currently produced, distributed and consumed [17].
It is clear that reaching and understanding of, and improving the
sustainability of, food that we purchase and consume is of
growing interest [9]. As social computing researchers we are
interested in how online mobile and social technology may
facilitate these goals. In particular, we believe there is a need to
directly engage the individual consumer in the process.
It is also clear, however, that, there is currently no
allencompassing measure of sustainability that we can use to deliver
feedback to users. For instance, there are a number of different
issues that the term ‘sustainability’ can refer to; these include
environmental sustainability and social sustainability. Indeed,
within environmental sustainability, there exist subtleties that
make it hard to define how sustainable any given item is. For
example, the question of whether it is preferable to grow fruit at a
low carbon cost in the third world and air freight it to the UK, or
to grow the fruit at a higher carbon cost in the UK, is a dilemma
that currently appears to be a value judgment. Since the problem
domain is so unclear, it is difficult at present to create meaningful
applications that give judgement on an objective level.
Complicating the issue further, there is currently no requirement
for manufacturers to disclose where ingredients and components
have been sourced (known as supply chain transparency [1]).
Nevertheless, in order to design mobile tools to encourage more
sustainable consumption, we must have some useable definition
of sustainability. As such, in our recent work, we have adopted
the goals of the “Slow Food” movement, which emphasises the
consumption of local and seasonal produce over that which is
imported and/or out-of-season (see http://www.slowfood.com for
more details). Hence, in the technology proposed here, users’
food consumption will be evaluated in terms of how closely it
adheres to the goals of the “Slow Food” movement.
      </p>
      <p>
        There are also a number of challenges facing any programme,
technological or otherwise, that aims to change consumer habits.
For example, although reports show that consumers are prepared
to pay more for eco-friendly items [
        <xref ref-type="bibr" rid="ref3">5</xref>
        ], and rate sustainable items
as of high importance, in fact they rarely purchase such items
[
        <xref ref-type="bibr" rid="ref7">14</xref>
        ]. It appears that in order to bridge this attitude-behaviour gap,
consumers need both access to sustainable produce and
confidence in their ability to identify sustainable produce [11].
We believe that significant potential exists with existing mobile
technology to develop tools that allow people to identify the
overall sustainability of their personal food purchases and take
action to improve it. Indeed, the inclusion of motivational tools
such as visual feedback, goal-setting and mini-games may help
persuade consumers to make more sustainable choices.
      </p>
    </sec>
    <sec id="sec-3">
      <title>1.2 Tagliatelle</title>
      <p>
        In previous work, we attempted to utilise the persuasive power of
social media as a means of facilitating dietary behaviour change
[7]. Specifically, we identified that the development of new and
innovative methodologies aimed at helping people determine the
nutritional content of their own food intake and motivating them
to choose healthier options is an urgent goal. We proposed that
exposing participants’ eating habits to each other may act as
triggers [
        <xref ref-type="bibr" rid="ref4">6</xref>
        ] for motivating both healthier food choices and the
maintenance of those choices over an extended period of time. In
order to examine this, we developed an application in which users
uploaded digital photos of meals that they had eaten to a server,
which anonymously distributed these photos to other users for
tagging. Each user was required to tag one photo that had been
previously uploaded by another user before they could upload a
photo of their own. In addition, users were free to visit the
website at any time in order to tag randomly selected images.
Thus, each photo uploaded was tagged several times by different
users, generating a rich history of tags for each photograph
uploaded.
      </p>
      <p>
        An evaluation of a basic prototype of Tagliatelle [7] suggested
that although we encountered problems extrapolating valid
nutritional information from the tags generated by participants,
the activity of tagging fellow users’ uploaded food photographs
was very popular among participants. This finding is consistent
with work in the field of human computation ([
        <xref ref-type="bibr" rid="ref8">15</xref>
        ][
        <xref ref-type="bibr" rid="ref9">16</xref>
        ]), where
games are used to motivate users to tag digital images with
relevant content labels that can later be used in text-based image
retrieval. In effect, the players of these games function as a data
analysis tool. It seems that this type of crowd-sourced image
analysis may prove useful for a number of different tasks,
including food sustainability.
      </p>
    </sec>
    <sec id="sec-4">
      <title>2. A MOBILE APPLICATION TO</title>
    </sec>
    <sec id="sec-5">
      <title>ENCOURAGE SUSTAINABILITY IN FOOD</title>
    </sec>
    <sec id="sec-6">
      <title>CONSUMPTION</title>
      <p>We are interested in exploring the possibility of harnessing the
apparently intrinsically motivating activity of tagging images as a
means of creating mobile applications that allow users to
accurately monitor, assess and change the sustainability of food
they consume. We believe that this type of approach may prove
very effective in helping users to gain an overall picture of the
sustainability of their own food choices. The main advantages of
designing a system with a social tagging architecture are both the
lack of need for expert involvement and huge potential for
scalability.</p>
      <p>Thus, we propose a system based on our experiences in the
design, development and evaluation of the Tagliatelle project.
However, instead of taking photographs of prepared meals,
participants will photograph their food at the point of purchase.
In addition, as mentioned above food consumption will be
evaluated in terms of how closely it adheres to the goals of the
“Slow Food” movement.</p>
      <p>The system will be composed of a mobile phone application and a
server-side database. Users will interact with the database
primarily through the mobile application, although it is envisioned
that a standalone website will also be created. The application
will allow three interactive experiences: uploading of photos,
tagging of photos and presenting of feedback. These are now
discussed in turn.</p>
    </sec>
    <sec id="sec-7">
      <title>2.1 Photo Uploading</title>
      <p>The mobile phone application will allow users to take
photographs of their purchases and to easily upload these photos
to their personal profile on the server with one button click. The
server will anonymously assign all uploaded photos to other users
for later tagging.</p>
      <p>One particular challenge lies in motivating users to photograph
each individual item that they purchase and upload these items to
the server. Failure to report a significant proportion of food
items, or the selective uploading of only ‘good’ items would lead
to inappropriate feedback. Exactly which tools are most effective
at motivating honest participation is an empirical question that we
intend to pursue over the course of this and related work.</p>
    </sec>
    <sec id="sec-8">
      <title>2.2 Photo Tagging</title>
      <p>
        Users will have the option of tagging photographs either through
the mobile phone application itself, or through a standalone
website. Specifically, a mini-game, inspired by [
        <xref ref-type="bibr" rid="ref8">15</xref>
        ] and [
        <xref ref-type="bibr" rid="ref9">16</xref>
        ] will
be created in which users rate the food content of the photos
presented in terms of sustainability. As in [
        <xref ref-type="bibr" rid="ref9">16</xref>
        ], ratings will only
be accepted if agreement is reached between independent raters.
Exactly what form these ratings will take is, at this time, an
empirical question. There is no obviously superior option between
numerical, visual or other methodologies. However, we do
recognize that a vital part of this research will involve educating
users on how closely items do or do not adhere to the goals of
“Slow Food.”
      </p>
    </sec>
    <sec id="sec-9">
      <title>2.3 Providing Feedback</title>
      <p>Each user will receive feedback on the overall sustainability of
their food choices through a number of possible methods such as
graphs and mini-games. This feedback will be reported both in
terms of personal goals and in comparison to the mean results for
other users.</p>
    </sec>
    <sec id="sec-10">
      <title>3. DESIGNING USEFUL FEEDBACK FOR</title>
    </sec>
    <sec id="sec-11">
      <title>PERSUASIVE APPLICATIONS</title>
      <p>Apart from the very specific problems of ensuring that food is
tagged validly and reliably, and that participants photograph and
upload appropriate quantities of their food, there are some basic
issues that need to be dealt with when setting out to design any
technology that promotes sustainable consumption.</p>
      <p>One criticism that can be leveled at the vast majority of persuasive
tools, mobile or otherwise, is that although these technologies are
designed with the specific aim of effecting change in user
behaviour, very few have implemented empirically established
methods for doing so (see [8]). Indeed, very little of the
published work on persuasive technology gives any specific
insights into the processes involved in behaviour change, nor
specific examples on how to apply these processes. Fortunately,
however, there is an entire academic discipline that sets out to
examine precisely these questions.</p>
      <p>
        Behaviour analysis is the scientific study of learning [
        <xref ref-type="bibr" rid="ref1">3</xref>
        ]. It is, by
definition, practical and pragmatic, as it presumes that all
behaviour is determined by interactions with and feedback from
the surrounding environment [
        <xref ref-type="bibr" rid="ref5">12</xref>
        ]. Successful behaviour is
maintained, while unsuccessful behaviour is not. Crucially,
behavioural psychologists suggest that because behaviour is
determined by the environment, it can be changed readily by
analysis and manipulation of that environment (see [10] for an
excellent introduction to behavioural interventions; [
        <xref ref-type="bibr" rid="ref2">4</xref>
        ] for an
indepth analysis). Hence, the field of behaviour analysis has spent
decades investigating exactly how to deliver feedback in order to
generate real and lasting behaviour change. We believe that,
regardless of the target behaviour, in order to create effective
persuasive technologies, the science and methodologies of
behaviour analysis must be employed as an integral design phase.
Indeed, assuming that the principles of behaviour don’t apply
when a person is interacting with a computing device is a stance
that is uninformed, and will lead to a large amount of duplication
of effort in addressing questions that have already been
comprehensively answered.
      </p>
      <p>In the application introduced in section 2, the way in which
feedback is delivered to participants will be informed by the
methods of behaviour analysis. Specifically, we will endeavour
to provide consistent, regular and specific feedback, regardless of
whether participants reach their goals or not. This will, at times,
necessitate the considered use of aversive feedback [8]. We will
also design the system so that there is a range of available reward
structures, such as mini-games, social networking and competitive
leader boards, and will ensure that the system is adaptive enough
to recognize and utilize the types of rewards that are most
effective for each participant.</p>
    </sec>
    <sec id="sec-12">
      <title>4. CONCLUSION</title>
      <p>A discussion addressing the problems facing any mobile
application that attempts to promote sustainable food choices has
been presented. We have proposed the design of a system based
around the popular activity of photograph tagging that may help
users to gain an overall picture of the sustainability of their own
food choices. We have also discussed how behaviour analysis can
help HCI researchers design the way in which feedback is
delivered to users, in order to create applications that are both
engaging and useful.</p>
    </sec>
    <sec id="sec-13">
      <title>5. REFERENCES</title>
      <p>[1] Bonanni, L. Hockenberry, M. Zwarg, D.</p>
      <p>Csikszentmihalyi, C. and Ishii, H. 2010. Small business
applications of sourcemap: a web tool for sustainable design and
supply chain transparency, In Proceedings of the 28th
international conference on Human factors in computing systems,
937-946.
[2] Brown, B., Chetty, M., Grimes, A., and Harmon, E.
2006. Reflecting on health: a system for students to monitor diet
and exercise. In Proceedings of the 24th international conference
extended abstracts on Human factors in computing systems,, 1807
– 1812.
[10]
Bantam.
[7] Linehan, C. Doughty, M. Lawson, S., Kirman, B. Olivier,
P. and Moynihan, P. 2010. Tagliatelle: Social Tagging to
Encourage Healthier Eating. . In Proceedings of the 28th
international conference extended abstracts on Human factors in
computing systems, 3331-3336.
[8] Kirman, B. Linehan, C. Lawson, S. Foster, D. and
Doughty, M. 2010. There's a Monster in my Kitchen: Using
Aversive Feedback to Motivate Behaviour Change. In
Proceedings of the 28th of the international conference extended
abstracts on Human factors in computing systems, 2685-2694.
[9] Pachauri, R.K. and Reisinger, A. 2007. Contribution of
Working Groups I, II and III to the Fourth Assessment Report of
the Intergovernmental Panel on Climate Change. Geneva,
Switzerland: IPCC.</p>
      <p>Pryor, K. 1999. Don’t Shoot the Dog. New York:</p>
    </sec>
  </body>
  <back>
    <ref-list>
      <ref id="ref1">
        <mixed-citation>
          [3]
          <string-name>
            <surname>Catania</surname>
            ,
            <given-names>C. A.</given-names>
          </string-name>
          <year>1998</year>
          . Learning (4th ed). Cornwall-onHudson, NY: Sloan Publishing.
        </mixed-citation>
      </ref>
      <ref id="ref2">
        <mixed-citation>
          [4]
          <string-name>
            <surname>Cooper</surname>
            ,
            <given-names>J.O.</given-names>
          </string-name>
          <string-name>
            <surname>Heron</surname>
            ,
            <given-names>T.E.</given-names>
          </string-name>
          and
          <string-name>
            <surname>Heward</surname>
            ,
            <given-names>W.L.</given-names>
          </string-name>
          <year>2007</year>
          .
          <article-title>Applied Behavior Analysis (2nd Ed)</article-title>
          . New Jersey: Pearson/Prentice Hall.
        </mixed-citation>
      </ref>
      <ref id="ref3">
        <mixed-citation>
          [5]
          <string-name>
            <given-names>De</given-names>
            <surname>Pelsmacker</surname>
          </string-name>
          ,
          <string-name>
            <given-names>P.</given-names>
            <surname>Janssens</surname>
          </string-name>
          ,
          <string-name>
            <given-names>W.</given-names>
            and
            <surname>Mielants</surname>
          </string-name>
          ,
          <string-name>
            <surname>C.</surname>
          </string-name>
          <year>2005</year>
          .
          <article-title>Consumer values and fair-trade beliefs, attitudes and buying behaviour</article-title>
          .
          <source>International Review on Public and Nonprofit Marketing</source>
          ,
          <volume>2</volume>
          ,
          <fpage>50</fpage>
          -
          <lpage>69</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref4">
        <mixed-citation>
          [6]
          <string-name>
            <surname>Fogg</surname>
            ,
            <given-names>B.J.</given-names>
          </string-name>
          <year>2009</year>
          .
          <article-title>A Behavior Model for Persuasive Design</article-title>
          .
          <source>In Proceedings of the 4th International Conference on Persuasive Technology, Article</source>
          <volume>40</volume>
          .
        </mixed-citation>
      </ref>
      <ref id="ref5">
        <mixed-citation>
          [12]
          <string-name>
            <surname>Skinner</surname>
            ,
            <given-names>B.F.</given-names>
          </string-name>
          <year>1974</year>
          .
          <string-name>
            <given-names>About</given-names>
            <surname>Behaviorism</surname>
          </string-name>
          . New York: Random House.
        </mixed-citation>
      </ref>
      <ref id="ref6">
        <mixed-citation>
          [13]
          <string-name>
            <surname>Thurstan</surname>
            ,
            <given-names>R.H.</given-names>
          </string-name>
          <string-name>
            <surname>Brockington</surname>
            ,
            <given-names>S.</given-names>
          </string-name>
          and
          <string-name>
            <surname>Callum</surname>
            ,
            <given-names>M.R.</given-names>
          </string-name>
          <year>2010</year>
          .
          <article-title>The effects of 118 years of industrial fishing on UK bottom trawl fisheries</article-title>
          .
          <source>Nature Communications</source>
          ,
          <volume>1</volume>
          , Article 15.
        </mixed-citation>
      </ref>
      <ref id="ref7">
        <mixed-citation>
          [14]
          <string-name>
            <surname>Vermeir</surname>
            ,
            <given-names>I.</given-names>
          </string-name>
          and
          <string-name>
            <surname>Verbeke</surname>
            ,
            <given-names>W.</given-names>
          </string-name>
          <year>2004</year>
          .
          <article-title>Sustainable Food Consumption: Exploring the Consumer Attitude Behaviour Gap</article-title>
          .
          <source>Journal of Agricultural and Environmental Ethics</source>
          ,
          <volume>19</volume>
          ,
          <fpage>169</fpage>
          -
          <lpage>194</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref8">
        <mixed-citation>
          [15]
          <string-name>
            <given-names>Von</given-names>
            <surname>Ahn</surname>
          </string-name>
          , L. Liu,
          <string-name>
            <given-names>R.</given-names>
            and
            <surname>Blum</surname>
          </string-name>
          ,
          <string-name>
            <surname>M.</surname>
          </string-name>
          <year>2006</year>
          .
          <article-title>Peekaboom: a game for locating objects in images</article-title>
          .
          <source>In Proceedings of the SIGCHI conference on Human Factors in computing systems</source>
          ,
          <volume>55</volume>
          -
          <fpage>64</fpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref9">
        <mixed-citation>
          [16]
          <string-name>
            <given-names>Von</given-names>
            <surname>Ahn</surname>
          </string-name>
          ,
          <string-name>
            <surname>L.</surname>
          </string-name>
          <year>2007</year>
          .
          <article-title>Human computation</article-title>
          .
          <source>In Proceedings of the 4th international conference on knowledge capture</source>
          ,
          <fpage>5</fpage>
          -
          <lpage>6</lpage>
          . [17]
          <string-name>
            <surname>Weber</surname>
            ,
            <given-names>K.</given-names>
          </string-name>
          <year>2009</year>
          . Food, INC. Participant Media.
        </mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>