ࣔࣂ࢖ࣝࣜࢧ࣮ࢳ࡟࠾ࡅࡿㄢ㢟㸫ୡ⏺࠾ࡼࡧ᪥ᮏ࡟࠾࠸࡚ࠊࣔࣂ࢖ࣝࣜࢧ࣮ࢳࡀ♧ࡍヨࡳ࡜ᶵ఍㸫
Issues for Mobile Research: The Challenges and Opportunities Presented by Mobile Research, Globallyand in Japanࣞ࢖ ࣏࢖ࣥࢱ࣮
Ray Poynter㸯㸬Six key issues
㸰㸬What is mobile?
㸱㸬Is mobile necessary?
㸲㸬What does mobile add and what does it take away?
㸳㸬Are surveys still relevant?
㸴㸬What are mobile ethics?
㸵㸬Where next for mobile?
㸶㸬Challenges to researchers’ models
㸷㸬Final observations
ࠑせ᪨ࠒᮏ✏࡛ࡣ㸪ࣔࣂ࢖ࣝᶵჾࢆ฼⏝ࡍࡿ◊✲⪅ࡀ┤㠃ࡍࡿ  ࡘࡢ㔜せ࡞ㄢ㢟࡟ࡘ࠸᳨࡚ウࡍࡿ㸬㸦㸧ࣔࣂ࢖ࣝࡢᐃ⩏㸪㸦㸧ࣔࣂ࢖ࣝࣜࢧ࣮ࢳࡢᚲせᛶࡢ᳨ド㸪㸦㸧ࣔࣂ࢖ࣝࣜࢧ࣮ࢳࡢ฼⏝࡟ࡼࡗ࡚⏕ࡌࡿኚ໬ࡢ୺
せ㒊ศ㸪㸦㸧ㄪᰝࡢጇᙜᛶࡢ᳨ウ㸪㸦㸧ᕷሙㄪᰝ࠾ࡼࡧ♫఍ㄪᰝ࡟࠾ࡅࡿ೔⌮ⓗᙳ㡪ࡢ୺せ㒊ศ㸪㸦㸧ࣔࣂ࢖ࣝࣜࢧ࣮ࢳࡢḟࡢẁ㝵ࢆ᥎ ࡍࡿ㸬ࡉࡽ࡟ᮏ✏࡛ࡣ㸪࡞ࡐࣔࣂ࢖ࣝࣜࢧ࣮ࢳࡀ୺࡟ࢫ࣐࣮ࢺࣇ࢛ࣥ࡟
㛵ಀࡀ࠶ࡿࡢ࠿㸪ࡲࡓࣔࣂ࢖ࣝࣜࢧ࣮ࢳࡀ᭱ࡶ㢖⦾࡟౑⏝ࡉࢀࡿࡢࡣ㸪ㄪᰝᑐ㇟⪅ࡀ⮬ศࡢࣔࣂ࢖ࣝᶵჾ
࡛࢜ࣥࣛ࢖ࣥㄪᰝࢆ⾜࠺࡜ࡁ࡛࠶ࡿࡇ࡜ࢆ᫂ࡽ࠿࡟ࡍࡿ㸬ࢫ࣐࣮ࢺࣇ࢛ࣥࡢ୺࡞࣓ࣜࢵࢺࡣ㸪ࡲࡎ㸪ேࠎࡀ  ᪥  ᫬㛫㸪㐌  ᪥㸪 ᪥ᡤ᭷ࡋ࡚࠸ࡿࡇ࡜㸪⏬ീࡸࣅࢹ࢜࡟ᐜ᫆࡟グ㘓࡛ࡁࡿࡇ࡜㸪఩⨨᝟ሗ࡞࡝ࢆཷືⓗ࡟グ㘓࡛ࡁࡿࡇ࡜㸪ࡲࡓࠊᆅ⌮఩⨨᝟ሗࡢ฼⏝࡞࡝ࣜࢧ࣮ࢳ࡟᪂ࡋ࠸ᶵ⬟ࡀᘬࡁ㉳ࡇࡉࢀࡿྍ⬟ᛶࡀ࠶ࡿࡇ࡜࡛࠶ࡿ㸬ᮏ✏࡛ࡣ㸪࣓ࢵࢭ࣮ࢪࣥࢢࡢά⏝࡞࡝㸪ࣔࣂ࢖ࣝࣜࢧ࣮ࢳࡀ㏆࠸ᑗ᮶࡟࡝ࡢࡼ࠺࡟
Ⓨᒎࡍࡿ࠿㸪࠸ࡃࡘ࠿ࡢண ࢆᥦ㉳ࡍࡿ㸬This paper examines six key issues facing researchers using mobile devices; specifically, it (1) defines
mobile research, (2) explores whether mobile research is necessary, (3) highlights the changes resulting
from the use of mobile research, (4) discusses the relevance of surveys, (5) highlights the ethicalimplications of market research and social research, and (6) speculates what is next for mobile research.
Furthermore, the paper explains why mobile research is primarily related to smartphones, and thatthe most frequently used feature of mobile research is participants who choose to take online surveys
on their mobile devices. The key benefits of smartphones are as follows: people have them 24-hours aday, 7-days a week, 365-days a year; smartphones facilitate the capture of images and videos; they cancapture passive data such as location; and research activities can be triggered in new ways such as
geolocation. Finally, the paper presents a number of predictions concerning how mobile research willdevelop in the near future, for example, using messaging.
             

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ᨻ⟇࡜ㄪᰝࠉ➨ྕ㸦ᖺ᭶㸧aafngH\fjjkHj
dRUiREfhHUHjHDUbeThis paper looks at the issues facing researchersinterested in utilizing mobile research, andidentifies six key issues that need addressing.
Before looking at what the six issues are andwhy they are the key ones, it is important todefine what we mean by issues. If we consult theOED (Oxford English Dictionary) we find that it
GHILQHV¶LVVXH·DV ´An important topic for debate
or resolutionµ An issue is not the same as aproblem. However, an issue that remains
unresolved can easily become a problem ² hence
the need for debate and resolution.
Mobile is an important topic, for academic,
social, and market and social researchers. For
example, a search on Google Scholar, using the%RROHDQ VHDUFK WHUP ¶0RELOH $1' SuUYH\· IRUacademic papers since the beginning 2017provides about 128,000 hits. The publishedpapers cover a wide range of topics such as:x
Participation in mobile app studies(Annette, 2017).
x
Mixed devices in online studies (Bosnjak,
2018).
x
Effects of mobile versus PC web on survey
response quality (Antoun, 2017).
This deluge of published papers reflects both thegrowing importance of mobile devices and thechallenges created by the use mobile phones foronline surveys, app-based surveys, CATI withmobile, and mobiles used with face-to-faceinterviewing.
This paper identifies and addresses six key issues.

::eDWfjiREfhH_At the heart of mobile research in 2018 is thesmartphone, especially those phones using theApple or Android operating system.
In the context of market and social research theterm mRELOHVRPHWLPHVUHIHUVWR¶IHDWXUHSKRQHV·(phones with fewer features than a smartphone).
The term mobile sometimes refers to tablets andoccasionally to other devices such as smart
watches. However, the central device at the heartof mobile research is the smartphone, and this is
likely to remain true for at least the next few
years.
At the most general level, mobile can refer toanything that is not fixed, including laptop
personal computers. However, when researchers
talk about mobile research, they tend to bereferring to devices that;xpeople have with them all the time,x
can connect to the internet,x
can support surveys, video, photography
and apps.
Smartphones are unique in matching all three ofthese criteria.
One of the best sources of information about thegrowth of mobile devices internationally is the
ITU. The ITU, the International Telecommunication
Union, is a specialized agency of the United
Nations). The ITU (2017) shows that by 2017
there were almost 4 billion active mobile
broadband subscriptions (globally), whichsuggests WKDWRYHURIWKHZRUOG·VSRSXODWLRQ
have access to a mobile device connected to theinternet ² and most of these will be some form ofsmartphone.
Mobile devices are used in a number of different
ways by researchers, including:
1. Online surveys completed by participants
using mobile phones.
2. App-based surveys.
3. Non-survey ¶active· options, such ascollecting images, videos etc.
4.
Non-survey ¶passive· options, collecting
information via the mobile device, forexample app usage, location, and movement.

1. What is mobile?
2. Is mobile necessary?
3. What does mobile add and what does ittake away?
4. Are surveys still relevant?
5. What are mobile ethics?
6. Where next for mobile?
This paper will address each of these six issues,and set the stage for an ongoing debate and forthe resolution of issues.

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

5HVHDUFK 1R 2FWREHU In terms of the market research industry, thelargest of these four (at the moment) is the firstone, online surveys completed by participants
using mobile phones (ESOMAR 2016). Different
sources produce different estimates of the
proportion of online surveys completed byparticipants using mobile devices, but the
numbers are large. For example, ESOMAR
produces two estimates 37% and 30% (ESOMAR
2018a & 2018b).
In terms of surveys completed on smartphones
we can think of a continuum that runs from
Mobile Incompatible, to Mobile Possible, toMobile First, to Mobile Only.
Mobile Impossible tends to refer to studies that
require large screens, dexterity on a large screen,
and/or the use of features hard to support on amobile, such as Virtual Reality. Unfortunately,
Mobile Impossible also refers to surveys where
the design and/or scripting means that they are
not compatible with smaller devices, i.e.
unintentionally -Mobile Impossible.
Mobile Possible refers to studies where aparticipant using a smartphone might be able tocomplete the survey, but where the experience is
sub-optimal. For example, if the design of thesurvey means that participants have to scroll leftright and up-down on a smartphone (but not on acomputer screen) then the survey experience will
be very different across devices ² and the survey
could be described as Mobile Possible.
Many modern survey platforms have an optionWR PDNH VXUYH\V ¶PRELOH FRPSDWLEOH· +RZHYHU
unless researchers ensure that the survey isproperly designed for mobile the result risks only
being ¶0RELOH3RVVLEOH·6XUYH\SODWIRUPVFDnnot,
by themselves, create surveys that work well on
mobile devices. To create a good mobile survey
experience, the researcher needs to ensure that
instructions are short and intuitive, that scales
are short, that answer lists are short (in terms ofnumber of items and the length of text of theanswers), and that options such as rank anddrag-and-drop are avoided.
Mobile First is tending to replace the terms like
Mobile Friendly and Mobile Agnostic. Mobile

Friendly referred to surveys that worked well on
mobile devices, and Mobile Agnostic weresurveys that in theory worked equally well on
computers and mobile devices. The term Mobile
First has risen to prominence because experiencehas taught the research community that the best
way to achieve a survey that works equally wellon both mobiles and computers is to start by
thinking mobile (York, 2017).
Data from the international online access panel
company Research Now (York, 2017), shows thatmany surveys that are being used commerciallyare not, in terms of mobile research, fit for
purpose. Research Now had a scoring system
where they assess the mobile suitability thesurveys from their clients. The figures theyreported were:x
Mobile Incompatible 29%x
Mobile Possible 23%x
Mobile Friendly 33%
x
Mobile Optimized 15%
One of the key concerns from these findings wasthat the figures for 2014 and 2015 were very
similar, i.e. about 50% of commercial market
research studies using online surveys were notsuitable for mobile devices.
Mobile Only refers to research where one ormore features of the mobile are required, forexample always being available, or using GPS
tracking, or taking video during the working day.
Two key areas of growth in Mobile Only research
DUHYLGHRDQG¶LQWKHPRPHQW·
There has been an explosion in the number ofapps and services allowing brands andresearchers to collect video as part of their project(for example Voxpopme and Watch me Think)and services that help curate and process video(such as Living Lens). The initial impact of video
was in qualitative research, but the next trend islikely to be the quantitative analysis of everlarger collections of video. Because smartphones
are with people 24/7 and because they are
sophisticated multimedia devices they are wellplaced to facilitate video-based approaches.
In the moment research refers to techniquesthat seek to avoid the problems created by relying

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ᨻ⟇࡜ㄪᰝࠉ➨ྕ㸦ᖺ᭶㸧If researchers wish to contact representative
samples, then, for most populations, it will benecessary to include data collection via mobile
devices. If research focuses on other devices, suchas personal computers, it may be possible toreach the desired totals, but it is probable thatthe sample will be skewed and biased.

RQSDUWLFLSDQWV·PHPRULHV)RUH[DPSOHLQWKH
moment approaches would seek to evaluate
journeys at the point of arrival, evaluate
shopping immediately after paying, evaluating
meals immediately after leaving the restaurant.
Because smartphones are with people 24/7,
because they are connected to the internet, andbecause they can be triggered via options such as
location, they are the ideal device (indeed the only
device) that can support and promote in the
moment research.
,,jiREfhHQHbHjjDU\_
Yes, mobile is necessary, almost everywhere in
the world. It is necessary for online surveys, for
CATI, for face-to-face surveys, for mobile only
surveys, and for a growing range of qualitative
projects (for example participatory ethnography).
In terms of online surveys (and in terms of CATI
studies) failure to facilitate mobile results insamples that are systematically biased. Studies
have shown that even the demographic
differences between an online sample and amobile sample are eradicated (e.g. income,education, age, etc.) there are still differences in
attitudes and beliefs. (Poynter et al, 2014).
These points can be highlighted by examples
and statistics relating to mobile market research.
In the United States, perhaps the mostrespected social research organization is the Pew
Research Center, by 2015 Pew were targeting
75% of their CATI interviews to be via
SDUWLFLSDQWV·PRELOHSKRQHVWRHQVXUHWKH\FROOHFW
representative samples (York & Poynter, 2017).
As long ago as 2014, it was estimated that 20%30% of all online surveys were completed from a
mobile device (Poynter et al 2014). The figures
since then have increased, partly because ofparticipant choice, partly because of the growthof mobile-only households.
Research by ESOMAR (2016) indicates that
86% of agencies who conduct face-to-faceresearch use mobile devices (typicallysmartphones and/or tablets) during datacollection.

::eDWcRHHjiREfhHDccDQcmeDWcRHjfW
WDgHDmD\_The shift to mobile has added many things to
WKH UHVHDUFKHUV· WRROER[ VXFK DV ORFDWLRQ-based
research and increased use of video, but it has
also removed some features from researchers·
toolbox.
The list of things that mobile has added islengthy, but it can be focused on four points:a) Smartphones are with people 24/7 ² thismeans mobile research can be lessdependent on memory, collecting
LQIRUPDWLRQ¶LQWKHPRPHQW·RUVRRQDIWHU
the moment.
b) Smartphones are advanced media
devices, including sound, video,
photography, and internet browsing.
c) Smartphones are equipped with passive
data collection capabilities (e.g. location
tracking, movement indicating etc.)d) Research activities via smartphones arecapable of being triggered in new ways,
such as geofencing and messaging. This
KDVRSHQHGXSWKHSRVVLELOLW\RI¶SXVKQRWLILFDWLRQ·UDWKHUWKDQ¶SXOOQRWLILFDWLRQ·
As well as adding new positives to the research
options, the arrival of mobile has also negatively
impacted some existing research practices/options.
In the early days of online surveys, for about
fifteen years from about 2000, the trend was tomake online questionnaires more engaging andmore visual. However, many of these engaging(and in some cases gamified options) are notsuitable for mobile surveys, especially when
FRPSOHWHGRQDVPDUWSKRQH)RUH[DPSOH¶GUDJDQG GURS· FDQ EH WRR ILGGO\ EUDQG OLVWV DQGquestions need to be shorter, and the ability to

Policy & Research No.15 (October 2018)

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

5HVHDUFK 1R 2FWREHU 

replicate full size images of products and adverts
has been diminished. There is also a widespread
belief that the completion time, for mobile
surveys, need to be shorter than the maximum
for personal computer-based surveys. There isdata that the drop out rates for mobile surveys ishigher than those associated with surveys
completed via personal computers (Poynter et al,2014). Increased drop out rates increases costs,
introduces time lags, reduces future co-operation,and reduces the ability of a sample to be
representative of the relevant population.
Examples of the changes that mobile has
required include:a) Surveys need to be shorter, because drop out
rates are usually higher when participants
take surveys on their mobile devices. This
problem is compounded by the finding thatsurveys tend to take longer to complete,
when compared with taking the survey on acomputer.
b) 6XUYH\V QHHG WR ILW RQ WKH PRELOH SKRQH·V
screen, which tends to mean shorter
question text, shorter answer lists, andfewer scale points.
c) 6XUYH\V FDQ·W XVH VRPH WHFKQLTXHV WKDWhave been developed for larger screen, forexample drag-and-drop ranking exercises
and methods of participants clicking onlarge images to express levels of interest.
d) Mobile First surveys will tend to be lessengaging than the best practices that weredeveloped for computer screens.
e) Grids have come under specific scrutiny
because mobile has exacerbated an existing
problem. Grids are liked by researchers,
because they provide data in a format very
suitable for analysis. However, even on
computer screens grids are associated withparticipant alienation and higher drop-out
rates. On mobile devices, grids are even lessaccepted (despite recent advances in how toadminister grids on mobile devices).
The arrival of mobile has raised questions about
the sort of changes that researchers need to makein their methods, for example:

Should we move away from grids ² if so, towhat?
xShould we move away from 10, 7 and 5point scales to 2 and 3-point scales?
xShould we move aware from scales to otheroptions, such as choices?
x
Should we move away from ranking toother options, such as choices?
Many of the methods that researchers use at the
moment to ask questions are very suitable for thesort of statistics and models that have beendeveloped over the last 100 years, i.e. metric,
linear, and based the normal distribution and on
random probability sampling. However, what
researchers have discovered is that we are trying
to make people fit our statistics, rather thantrying to fit statistics to the nature of how people
think and behave.
Perhaps the time has come to use models thatstart with people, that do not require normality,
nor metric variables, nor random probability
samples? Historically, we saw this change
happen in the world of conjoint analysis, where
there was a shift from ratings based conjoint andcard sorts (i.e. from ratings and rankings) to
choice-based conjoint (i.e. to choices). This change
entailed moving from continuous variables todichotomous variables, and from standard
regression to logit regression. A number of
researchers have shown the benefits of moving to
3-point scales (which fit well on a mobile device)(Barlas et al, 2017).

x

$$UHjkUlH\jjWfhhUHhHlDQW_
YES! Most of the visibly-expressed interest (inarticles, journals, and on conference platforms)
about mobile research covers methods such asvideo, biometrics, passive data, and apps.
However, the main utilization of mobile research
is via surveys. In most cases these surveys aretaken by people using the browser on theirsmartphone to take part in conventional email/online surveys.
Surveys are in decline, but they are not about todisappear. From 2010 to 2016 in terms of dollar

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ᨻ⟇࡜ㄪᰝࠉ➨ྕ㸦ᖺ᭶㸧spend, surveys declined from 56% of allquantitative research (by value) to 46% (Poynter,2017). However, surveys are expected to still be amajor part of research ten years from now (i.e.
over 20% of all quantitative research).
Surveys will change, they will utilize more
artificial intelligence, more text recognition,collect more unstructured data, but they remain
an important part of the research mix.
Surveys are important to researchers (andbeyond them to companies, governments,
academics etc.) because they allow research tofocus on specific questions. A good example of aquestion that is difficult to assess without
survH\VLV´:KDWZRXOG\RXGRLIZHFKDQJHGRUUHPRYHG ;"µ +RZHYHU VLQFH VXUYH\V DUH VR
important to research (and to the people who
commission research) we need to ensure that we
keep co-operation rates as high as possible.
::eDWDUHiREfhHHWefbj_As the recent scandals with Facebook andCambridge Analytica have shown, ethics do notstay the same over time. Ethics evolve andrespond to changes in technology and in responseto real-world events.
The first point about mobile and research is thatit has to conform to all of the establishedprinciples that have been developed for otherdata collection modes. The ICC/ESOMAR
International Code on Market, Opinion andSocial Research and Data Analytics summarizes
the concerns in terms of three fundamental
principles:
1. When collecting personal data from data
subjects for the purpose of research,
researchers must be transparent about the
information they plan to collect, thepurpose for which it will be collected, withwhom it might be shared, and in whatform.
2. Researchers must ensure that personal
data used in research is thoroughly
protected from unauthorized access andnot disclosed without the consent of thedata subject.
3. Researchers must always behave ethicallyand not do anything that might harm adata subject or damage the reputation ofmarket, opinion and social research.
In terms of mobile, the additional implications
include:a) Making sure participants understandwhat information you are accessing fromtheir phone, and that consent is sought.
b) That data remains secure, for example if
photos/videos are collected, who will see
them, how might they be used, when will
they be destroyed.
c) Harm refers to large and small harm.
Ensure that taking part in the research
GRHVQRWSXWDQ\ERG\·VOLIHLQGDQJHU HJ
do not do this mobile survey while driving).
But, also deal with issues such as not
UXQQLQJ WKH SDUWLFLSDQWV· EDWWHU\ GRZQ
and not leaving unwanted apps on theirdevice.
 :eHUHQHnWdRUiREfhH_The near future is all about smartphones.
Globally, the penetration of smartphones is stillon an upward path. Most CATI will be via
smartphone, most online surveys will be via
VPDUWSKRQHDQGWKHUHZLOOEHDJURZWKLQ¶PRELOH
RQO\·UHVHDUFKOther mobile devices will have an ongoing role,for example tablets, smart watches and devices
that are part of the Internet of Things, but these
are unlikely to represent more than a few
percentage points, even in five-to-eight years
from now.
Some trends that may impact the way mobile
develops are:x The use of messaging apps for research, e.g.
WeChat, Line, WhatsApp etc. Some ofthese platforms, for example WeChat in
China, seem to be major elements of the
future digital network.
x Developments in location-based approaches.

Policy & Research No.15 (October 2018)

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

5HVHDUFK 1R 2FWREHU The possibility of location-based-researchhas been around for a while, for example,
using GPS or beacons or Wi-Fi routers to
track people and initiate location-based
research. At some point there will be a
rapid growth in the frequency of using
these options.
x Growth in video, driven by apps and thegrowth in automated processing. This isalready happening, video is moving fromsmall numbers of qualitative artifacts tolarge amounts at quantitative levels.
x More expansion of qualitative, from autoethnography, to crowdsourcing, to using
tools such as Instagram and messaging.
Yes, there will also be developments inbiometrics, passive tracking, chatbots, andadaptive questionnaires ² but I think they will be
marginal to the big picture for the next few years.
Ever since the runaway success of Pokémon Go
there have been forecasts that augmented reality
will be the next big thing. However, time, money
and resource implications mean that augmented
reality is likely to be reserved for special problems,
where resources and time are not major
constraints.
] &KDOOHQJHVWR5HVHDUFKHUV̓0RGHOjjMany researchers are clinging to an idealized
model of how research is conducted. This
idealized model fits with the research tools wehave available, but this model does not fit wellwith the real world. The two key fallacies that too
many quantitative researchers subscribe to are:a) That data approximates to a random
probability sample. Today the vast majorityof research is collected from opt-in panels,
from low response rates general studies,and from unsophisticated customer lists.
This means that models based on random
probability are increasingly irrelevant, as
we saw with the polling debacle
surrounding the election of USA President
Trump.
b) That grids (for example brands byattributes, using a 5-point or 7-point scale)collect meaningful information. Grids
present two distinct problems. 1) Research
participants do not like grids and are more
likely to abandon surveys when theyencounter a grid ² which makes thecollected data less representative and more
expensive. 2) People do not have metric,
nicely spaced views about all the brands andon all the scales.
Dealing with these two issues requires different
strategies.
If the samples collected do not approximate torandom probability samples, there are
essentially two optionsi.
Make the sample a better approximation
to a random probability sample of the
population. For example, re-define thepopulation; i.e. create a random
probability panel by recruiting from thebroader population and by supplying
hardware/incentives where needed, or byadopting multi-mode approaches to widen
the range of people being contacted.
ii.
Use models and benchmarks to link
responses from non-probability samples tothe real world. The key challenges to theseapproaches is that whilst their past
performance can be measured, their future
performance cannot statistically be known
in advance. These models are essentiallyempirical, rather than being based on
established theories.
In terms of dealing with the measurement issues
raised by attribute batteries and metric scales ingeneral, and grids in particular, the key need is to
move aware from pretending that people are
metric creatures who can express their views,
opinions, and beliefs in terms of scales that betreated as integer scales (or even in some cases
treating it as if it were a ratio scale). Researchers
have pretended that people can do these tasks
because we have a wide arrange of statisticaltechniques, based on common and wellunderstood distributions.

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ᨻ⟇࡜ㄪᰝࠉ➨ྕ㸦ᖺ᭶㸧

The alternative to trying to fit people to statisticalmodels is to choose statistical models that match
people. For example, models based on choices
appear to match human behavior more closelythan scales, as demonstrated by the choicemodels demonstrated by Nobel Prize winnerDaniel McFaddon.

ཧ⪃ᩥ⊩
JA Annette, J Burton, MP Couper, C Lessof..
Participation in a mobile app survey to collectexpenditure data as part of a large-scale
probability household panel: response rates
andresponse
biases,2017
econpapers.repec.org
C Antoun, MP Couper, FG Conrad.. Effects ofmobile versus PC web on survey response
quality: A crossover experiment in aprobability web panel, Public Opinion
Quarterly, 2017 - academic.oup.com
F Barlas, N Buttermore & R Thomas. Making
Grid Questions Mobile Friendly - An
Impossible Dream?, European Research
Survey Association Conference, Lisbon,
Portugal 2017
M Bosnjak, R Bauer, KW Weyandt. Mixed
Devices in Online Surveys: Prevalence,
Determinants, and Consequences, Mobile
Research, 2018 - Springer
ESOMAR (2016), Global prices study.
Amsterdam: ESOMAR.
ESOMAR (2018a), Global Market Research
Report. Amsterdam: ESOMAR.
ESOMAR (2018b), Global Prices Study.
Amsterdam: ESOMAR.
ITU (2017), Measuring the Information Society
Report 2017, Volume 1,
https://www.itu.int/en/ITUD/Statistics/Documents/publications/misr2017/MISR2017_Volume1.pdf
Poynter, R. (2017), When will surveys
disappear? (2017 update),
https://www.linkedin.com/pulse/when-surveysdisappear-2017-update-ray-poynter
Poynter, R., Williams, N., & York, S. (2014). The
handbook of mobile market research: Tools andtechniques for market researchers. New
Jersey: Wiley.
York, S., The Journey from Device Agnostic to
Mobile First, European Research Survey
Association Conference, Lisbon, Portugal 2017^``fQDhREjHUlDWfRQjFor a long time, people were saying that mobile
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became the next big thing without most people
noticing it. The reason that the arrival of mobile
research was largely unremarked was that the
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location-based research that would automaticallyrecord voice and images) and the big impact waswhen mobile became the device of choice forconventional research (e.g. online surveys, CATI,
and in face³to-face research).
When we look at a developing technology, forexample mobile research, we need to look atwhere it is most widely adopted, not at where it
is most exciting. It is also important that we lookat the unintended consequences.
For mobile, the biggest area of adoption has
been for conventional surveys and the key
unintended consequence has been a move to
make surveys shorter, simpler, and less engaging² because of the limitations of the screen size,user dexterity, and time expectations.
The final observation is that for the foreseeable
future, the story of mobile and market and social
research is one of a journey, not a destination. We
are not moving towards a defined endpoint, weare evolving and the process favors not the strong,
not the fastest, but those who can adapt. As&KDUOHV 'DUZLQ VDLG ´,W LV QRW WKH VWURQJHVW
species that survive, nor the most intelligent, but
WKHRQHVPRVWUHVSRQVLYHWRFKDQJHµ(The Future Place)

Policy & Research No.15 (October 2018)

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