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{{Paper
|id=Vol-2637/pape10
|storemode=property
|title=Motivational technology as a way of enhancing transportation safety – A systematic review of previous research
|pdfUrl=https://ceur-ws.org/Vol-2637/paper10.pdf
|volume=Vol-2637
|authors=Eetu Wallius,Juho Hamari
|dblpUrl=https://dblp.org/rec/conf/gamifin/WalliusH20
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==Motivational technology as a way of enhancing transportation safety – A systematic review of previous research==
https://ceur-ws.org/Vol-2637/paper10.pdf
Copyright © 2020 for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Motivational technology as a way of enhancing transpor-
tation safety – A systematic review of previous research
Eetu Wallius1[0000-0003-3251-7314] and Juho Hamari1 [0000-0002-6573-588X]
1Tampere University, Tampere Finland
eetu.wallius@tuni.fi
juho.hamari@tuni.fi
Abstract. Motivational technologies have been studied and applied in various do-
mains to encourage sustainable behaviors. One of such domains is safety of trans-
portation systems. This paper presents a review of current research literature cov-
ering gamification, serious games and persuasive technology in the domain of
transportation safety. A total of 46 records were reviewed, 32 of which were em-
pirical records studying the effects or user perceptions of motivational technolo-
gies. Most of the current body of literature is in the area of road safety, followed
by aviation. The results reported in the reviewed records indicate that applying
motivational technologies is a promising approach for enhancing safety in different
transportation domains. We have, however, identified shortcomings, thematic gaps
and direction of future research which we discuss in this paper.
Keywords: motivational technology, gamification, persuasive technology, seri-
ous games, transportation safety, literature review.
1 Introduction
There is an increasing interest in academia and industry in how motivational technolo-
gies, i.e. gamification, serious games and persuasive technology, can be used to affect
human behavior in various domains, such as in transportation, education or health man-
agement [9]. Transportation, be it of people or goods, is one of the cornerstones needed
for the functioning of organizations and societies. There is a variety of different trans-
portation systems such as land transport (e.g. roads, railways), aviation, maritime and
inland waterway transport. One of the most persistent issues across all these domains
of transportation is safety. While accidents related to transportation claim thousands of
lives yearly in the EU alone, the differences between levels of safety in different modes
of transportation are substantial (see e.g. [5]). Aviation and western railroads are con-
sidered highly regulated, ultra-safe systems with extremely low accident rates whereas
road transportation is less regulated and has higher accident rates [1]. Typically, acci-
dents in ultra-safe systems happen as a result of a combination of factors that alone
could not cause an accident [1] while for example in driving, single factors, such as
sleepiness, by itself can significantly increase the likelihood of a crash (see e.g. [3]).
Also, the severity of accident consequences varies between different modes of trans-
portation; whereas in road transportation, individual accidents typically do not claim
multiple lives, the consequences of an aviation or a railroad accident can be catastrophic
(see e.g. [5]).
GamiFIN Conference 2020, Levi, Finland, April 1-3, 2020 (organized online) 92
Although safety is a systemic property, human behavior is one of the key factors
when discussing the emergence of accidents. Safety measures, such as automation, in-
formation campaigns and safety trainings have been implemented as a way of enhanc-
ing transportation safety. However, as road transportation alone continues to claim
more than a million lives yearly [12], there is a need for developing novel ways of
enhancing transportation safety. To increase compliance with safety regulations, sup-
port safety behavior and enhance safety training, motivational technologies are increas-
ingly applied in safety management to combat the issues stemming from the ‘human
factor’. Motivational technologies [9] primarily include gamification ([4], [6], [8]), se-
rious games [2] and persuasive technology [10] that engage individuals with activities
that are commonly considered mundane such as attending a safety training. Whereas
gamification refers to transforming systems, services, products, organizational struc-
tures or practically any activities to afford similar experiences as games do using game
design [6], serious games commonly represent full games designed for purposes other
than pure entertainment [4]. Persuasive technology on the other hand, similarly to gam-
ification, commonly refers to the addition of a type of design onto an existing practice.
However, persuasive design as a term did not emerge from game research.
Although research on the use of these motivational technologies in the transportation
safety domain has started to appear, the body of literature remains fragmented. This
review aims at synthesizing the existing research that has been conducted on motiva-
tional technology in the domain of transportation safety. We present a comprehensive,
descriptive review including various modes of transportation, safety measures and
types of motivational technologies. The results implicate that most of the current body
of research focuses on road safety, followed by aviation. Moreover, gamification in
transportation safety is mostly aimed at enhancing safety at an individual level (gami-
fying or teaching safety behavior). However, transportation safety is affected by a va-
riety of behaviors of different stakeholders making it thus a prominent context for fur-
ther gamification research.
2 Materials and methods
In order to compile a comprehensive body of literature on the use of motivational tech-
nology in transportation safety we conducted a systematic literature search. Scopus da-
tabase was chosen for the literature search since it indexes most other relevant data-
bases. Moreover, the search was conducted only in one database for clarity and repli-
cability of the search and selection process. The search was conducted in August 2019
over records’ titles, abstracts and keywords in order to include only records which focus
was improving safety using motivational technologies. The used search terms were
(gamif* OR “persuasive technolog*” OR “simulation gam*” OR “serious gam*”) AND
(safety OR accident OR emergency OR security OR “risk management”). Types of
records included in the search were conference papers, articles and book chapters.
A total of 873 records were obtained with the used search query. After the search,
the titles and abstracts were examined. 11 records were excluded for not being available
in English. A total of 103 records were identified as not being related to gamification,
serious games or persuasive technology based on the titles and abstracts and thus ex-
cluded from further analysis. Of the remaining records, 715 were excluded based on
GamiFIN Conference 2020, Levi, Finland, April 1-3, 2020 (organized online) 93
the titles and abstracts as they were not focused on transportation safety. Six records
were not fully accessible to the authors using Scopus or Google Scholar. After screen-
ing the titles and abstracts, a total of 38 transportation or traffic safety related records
were included in the review. Two additional records were identified using forward
search and six using backward search. Thus, a total of 46 records were included.
3 Results
3.1 General description of the reviewed research
Although the differentiation between different types of motivational technologies can
be ambiguous, we categorized the records according to whether the technology de-
scribed in them matched with definitions of motivational technologies outlined in the
introduction section. Papers that used parallel terms to serious games such as ‘simula-
tion games’, or ‘learning games’ were categorized as serious games in this study. Fur-
thermore, gamified simulators, learning platforms and training applications were cate-
gorized as ‘serious games’ as they provide a separate learning or training environment
instead of gamifying behaviors, such as safe driving, in the ‘field’. The categorization
between persuasive technology and gamification was conducted according to the brand-
ing used by the authors of each manuscript. Of the 46 records included in this review,
28 focused on serious games, 15 on gamification and three on persuasive technology.
Furthermore, we analyzed the contexts of all 46 records that met the inclusion criteria
(table 1).
Table 1. Contexts of the records
All records (n=46) Empirical records (n=32)
Frequency Records Frequency Records
Road safety 35 (76.1 %) 24 (75%)
Driving 21 (45.7 %) A1, A2, A4, A6, A7, A18, 14 (43.8 %) A1, A4, A7, A18, A20,
A20, A25, A30, A31, A32, A25, A30, A33, A35, A39,
A33, A35, A36, A37, A38, A40, A41, A45, A46
A39, A40, A41, A45 A46
Pedestrian 7 (15.2 %) A3, A10, A17, A19, A28, 6 (18.8 %) A10, A17, A19, A28, A29,
A29, A43 A43
Bicycle 3 (6.5 %) A23, A24, A44 3 (9.4 %) A23, A24, A44
Other 4 (8.7 %) A5, A8, A22, A34 1 (3.1 %) A8
Aviation safety 9 (19.6 %) A9, A11, A12, A13, A14, 8 (25%) A9, A11, A12, A13, A14,
A15, A16, A21, A27 A15, A16, A21
Maritime safety 2 (4.3 %) A26, A42 0 -
The body of literature described various gamified safety measures and approaches
for enhancing transportation safety. Records concerned with road safety mostly focused
either on teaching safe or compliant behavior using serious games or gamifying safe
driving such as not speeding, mostly with the aim of preventing undesirable outcomes,
such as collisions. Also, other safety measures were considered; e.g. one of the records
[A22] described a gamified application to make the reporting of road accidents more
GamiFIN Conference 2020, Levi, Finland, April 1-3, 2020 (organized online) 94
engaging. Of the records that were in the context of driving safety, only one [A20]
explicitly aimed at enhancing safety of freight transportation.
In the aviation context, the reviewed body of literature predominantly concentrated
on safety measures that aim at reducing harmful consequences in case of an emergency.
The emphasis on emergency management is understandable due to the nature of com-
mercial aviation where accidents are typically extremely rare but can potentially have
catastrophic consequences (see e.g. [1]). The records described gameful learning inter-
ventions that teach the passengers safety measures normally taught using safety cards
or pre-flight demonstrations such as correct evacuation behavior, assuming brace posi-
tion in case of forced landing and life preserver donning. One record [A21] described
a solution which focused on training aircraft pilots instead of passengers. In the aviation
context, serious gaming type of interventions were prevalent.
Two non-empirical studies related to maritime safety were identified and analyzed.
In the maritime safety context, the reviewed records described serious game solutions
which aimed at teaching situation awareness to submarine users using virtual reality
[A42] and safe maritime cargo transportation to maritime specialists [A26].
32 of the reviewed records were empirical studies (i.e. studies involving data com-
posed of observation of reality and its analysis), while 14 were non-empirical (i.e. re-
torted to conceptually treat the phenomenon). Design science papers were not consid-
ered empirical unless they included a type of evaluation that would inform about the
effect of motivational technology. Moreover, studies that included secondary data or
data that was used as background information in design science projects were not con-
sidered empirical as these studies do not inform us about the effects of the intervention
on psychological states or behavioral and organizational outcomes. Therefore, the re-
viewed non-empirical records were mainly conceptual or framework papers and pre-
liminary descriptions of gamified applications without an evaluation of the effects of
motivational intervention. Additionally, one record [A2] studied perceptions related to
safe gamified driving.
The reviewed empirical records included a description of a design process or devel-
oped application followed by a user evaluation or an experimental study to test the
designed solution. 24 of the 32 empirical records applied a serious game solution. Eight
of the empirical records described a gamification or persuasive technology approach
that does not take the user to a separate learning or training environment. All such so-
lutions were applied to enhance safe driving by reducing boredom and fatigue or by
persuading for safe driving and making it more engaging. In order not to distract the
driver, the feedback in gamified driving solutions was often implemented using ambi-
ent colors and audio or given post-drive.
3.2 Motivational affordances and outcomes in empirical studies
We examined the motivational affordances reported in the reviewed empirical manu-
scripts (table 2). Most applied affordances were forms of performance feedback, which
include e.g. visual demonstration of in-game behavior consequences, textual feedback,
praise or rebuke by in-game characters, forms of ambient audio or visual feedback and
performance reports. The ‘Other, misc.’ category includes rarely applied affordances,
such as avatar levels, motion tracking, physical boards and puzzles.
GamiFIN Conference 2020, Levi, Finland, April 1-3, 2020 (organized online) 95
Table 2. Motivational affordances in empirical studies
Affordance Records Frequency
Performance feedback A9, A12, A13, A14, A15, A16, A17, A18, 21
A23, A24, A29, A30, A33, A39, A40 (solu-
tions 1 & 2), A41, A43, A44, A45, A46
Game world, 3D world, virtual world, A1, A8, A9, A12, A13, A14, A15, A16, 15
simulation world A17, A19, A21, A30, A35, A43, A44
Challenges, quests, missions, tasks, clear A1, A7, A11, A15, A16, A18, A19, A21, 14
goals, objectives A23, A24, A35, A39, A40 (solution 1), A41
Avatar, character A8, A9, A10, A11, A12, A13, A14, A16, 13
A19, A28, A29, A35, A46
Score, points A1, A4, A7, A18, A19, A20, A21, A23, 12
A24, A29, A44, A45
Game levels, scenarios, sections A1, A10, A11, A14, A18, A20, A21, A25, 10
A35, A43
Narrative, storytelling, plot A8, A9, A15, A19, A21, A25, A35, A43, 9
A46
Assistance, helpers, instructions, hints A1, A9, A12, A13, A15, A16, A17, A43 8
In-game rewards, virtual items A4, A7, A19, A20, A44, A46 6
Timer, time pressure A1, A8, A11, A16, A29 5
Increasing difficulty A1, A10, A11, A21, A43 5
Co-op, teams, social collaboration, so- A4, A7, A19, A28 4
cial networking
Badges, achievements, medals, trophies A4, A20, A29, A46 4
Progress visualization A7, A18, A29, A40 (solution 1) 4
Leaderboard, high score list, ranking A7, A18, A20 3
Quiz, questions A18, A29, A45 3
Other, misc. A7, A10, A19, A25, A28, A43, A45 7
27 of the empirical records reported studying one or more psychological outcomes
(table 3). Outcomes related to usability, perceived enjoyment and perceived usefulness
or effectiveness of the gamified system were the most studied similarly to gamification
research generally [9].
Table 3. Empirically studied psychological outcomes
Outcome Records Frequency
Enjoyment, fun, entertainment, flow A1, A10, A11, A18, A21, A23, A24, A30, 11
A35, A39, A40
Perceived usefulness/effectiveness/learning/per- A7, A13, A16, A18, A19, A20, A23, A30, 10
formance A33, A41
Ease of use, perception of use, user experience A1, A4, A7, A21, A30, A39, A40, A41, A43 9
Engagement, motivation A9, A11, A15, A16, A18, A21, A40 7
Self-efficacy, locus of control A9, A11, A12, A13, A14, A16 6
Perceived vulnerability A11, A12, A14 3
Perceived severity A11, A12, A14 3
Presence A8, A9, A30 3
Perceived challenge, effort, gameplay difficulty A23, A24, A35 3
Behavior agreement, attitude A11, A19, A28 3
Perceived reality, realism, parallels with reality A1, A21, A44 3
Fatigue, boredom, arousal A15, A30, A41 3
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Fear, risk perception A13, A15 2
25 of the records reported studying one or more behavioral or learning outcome. 17
records reported studying forms of learning or knowledge gain. Four records studied
forms of safe behavior, all of which were related to the task of driving. Other studied
behavioral outcomes were related to e.g. game performance and system usage time.
Most of the empirical records (26 records) reported mainly positive results in the
forms of knowledge acquisition or positive learning outcomes resulting from motiva-
tional technology interventions (14 records), positive user feedback (9 records) and in-
crease in compliant or safe driving (4 records). However, in many of the records that
reported positively oriented results, they were mixed with null results.
4 Discussion and avenues for further research
Most of the reviewed studies approach transportation safety from a perspective that
equates safety with compliance or safe behavior of individuals and the body of research
is leaning towards a single player serious gaming approach. However, safety is often
dependent on the interaction between multiple actors and includes e.g. successful team-
work and communication (see e.g. [7]). Thus, in future research, especially social as-
pects of gamification and their effects on safety-behavior should be studied. Addition-
ally, a prominent direction for future research is to examine how gamification can be
utilized at societal level, e.g. by encouraging participation in traffic safety related
crowdsourcing, such as reporting potential dangers, in order to effectively collect and
analyze early-warning indicators and further enhance transportation infrastructure
safety e.g. by urban planning and policymaking.
Majority of the reviewed research is related to road safety which is understandable
as road transportation is more accident prone than e.g. aviation and railroad transporta-
tion [1]. However, other modes of transportation offer distinct settings and safety-re-
lated problems that gamification could potentially tackle. For example, the absence of
research in the domain of railroad safety is surprising as operating a train is a highly
automated and monotonous task which yet requires a high level of sustained attention
(e.g. [11]) thus making it a prominent target for studying gamification aimed at enhanc-
ing task engagement or alertness. Moreover, railroads are complex systems in which
safe functioning requires seamless co-operation of multiple actors and thus we suggest
that railroad safety might be a suitable context for studying collaborative aspects of
gamification which according to our findings are rarely studied in transportation safety
contexts.
All the empirical records that studied gamification in the ‘field’ were related to the
task of driving. The nature of driving, where single factors such as sleepiness can have
a significant effect on safety (see e.g. [3]), makes it a natural context for such interven-
tions. However, more research is needed on how the feedback in gamified driving
should be presented in order not to distract the driver. Feedback given post-drive does
not distract the driver but might however have limitations as it does not provide the
driver a possibility to adjust the behavior real-time based on the feedback.
Moreover, the reviewed studies examined the effects of gameful interventions on
short-term outcomes such as engagement, learning or forms of safe driving. The body
GamiFIN Conference 2020, Levi, Finland, April 1-3, 2020 (organized online) 97
of research thus lacks long-term studies that examine the effect of gamification on
safety metrics, such as accident rates. Future research should also further address the
issue of technology acceptance and integration of gameful interventions to work and
other practices in organizational settings, which is a topic barely covered by the current
body of research.
5 Limitations
In this study, we reviewed research that studied various forms of motivational technol-
ogy in the context of transportation safety. In the literature search, we used the key
terms derived from gamification, serious games, simulation games and persuasive tech-
nology. Thus, records that have not used the previous terms to describe their research
focus were not included even if they studied motivational technology. Moreover, as we
used safety-related search terms, records that did not use these terms to describe their
focus were not reviewed. We limited the literature search to Scopus database and alt-
hough it indexes most relevant databases, using only one database might have resulted
in missing out some relevant records. Moreover, we analyzed the applied affordances
based on the descriptions of applied motivational technologies reported by the authors
of each manuscript. However, it is possible that some of the implemented affordances
remained unreported and therefore not included in our manuscript.
Acknowledgements
This work was supported by European Union Regional Development Fund and con-
ducted as a part of the Satadilogis project (A74723).
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