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This paper proposes an innovative approach to decision-making processes for urban freight planning that could easily be transferred across cities while capable of jointly taking into account: (1) all the conceivable and updated urban freight transport (UFT) measures that should apply to the specific city culture, structure and evolution, (2) all the relevant stakeholders and successfully involve them from the beginning, (3) behavioural, technical, operational, organisational and financial issues.
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Smart urban freight planning process: integrating desk, living lab
and modelling approaches in decision-making
Vale r i o G a t t a
&Edoardo Marcucci
&Michela Le Pira
Received: 16 August 2016 /Accepted: 9 May 2017
#The Author(s) 2017. This article is an open access publication
Purpose This paper proposes an innovative approach to
decision-making processes for urban freight planning that
could easily be transferred across cities while capable of joint-
ly taking into account: (1) all the conceivable and updated
urban freight transport (UFT) measures that should apply to
the specific city culture, structure and evolution, (2) all the
relevant stakeholders and successfully involve them from the
beginning, (3) behavioural, technical, operational,
organisational and financial issues.
Methods The methodology is organised and deployed in three
phases, following three different approaches, i.e.: a Bdesk
approach^for data acquisition and knowledge-based policy
rankings; a Bliving lab approach^to foster stakeholdersen-
gagement in co-creating policies; a Bmodelling approach^to
evaluate policies and find/define an optimised mix of shared
applicable/effective policies.
Results The three-phase methodology supports public author-
ities in: (a) increasing knowledge and understanding of the
most innovative context-specific UFT policies; (b) integrating
UFT policies in strategic urban planning via collaborative
participation/governance processes; (c) developing an ex-ante
behaviourally consistent, financially robust and technically
compatible assessment of shared UFT policy mixes while
providing appropriate instruments to facilitate policy adoption
and deployment.
Conclusions The proposed methodology contributes to the
identification and development of effective UFT solutions.
Bringing together knowledge acquisition, policy co-creation,
behaviour change analysis within a single methodological ap-
proach, aimed at identifying an optimised policy package, is
both new and needed.
Keywords Citylogistics .Urban freighttransport .Innovative
solutions .Behavioural models
1 Introduction
The European Union (EU) is largely urbanised.
Urban freight
transport (UFT) is an increasingly relevant part of modern city
life determining ec.onomic advantages and contributing to
well-being while, also, generating relevant social costs.
Managing UFT requires local policy-makers striking a balance
between throughput, liveability, safety and sustainability. The
complexity characterising the UFT framework aggravates this
daunting task. Heterogeneous stakeholders living in cities, in
fact, interact, both competing and cooperating, and, often, are
characterised by contrasting objectives. Stakeholders can be
generally defined as those who hold an interest in the decision
to be made, even if they have no formal role in the decision-
making process (i.e. they are not the finaldecision-makers) [2].
The main UFT actors pertain both to the private and public
sphere and they can be categorised in: (1) shippers; (2) freight
carriers; (3) receivers; (4) residents; (5) planners and regulators
72% of the total population live in cities, reaching 80% by 2020 [1].
This article is part of Topical Collection on The role of planning towards
sustainable urban mobility
*Michela Le Pira
Department of Political Sciences, University of Roma Tre,
Rome, Italy
Department of Logistics, Molde University College, Molde, Norway
Department of Civil Engineering and Architecture, University of
Catania, Catania, Italy
Eur. Transp. Res. Rev. (2017) 9:32
DOI 10.1007/s12544-017-0245-9
[3,4]. Shippers generate freight demand, freight carriers orga-
nise freight transport from shippers to receivers and they are all
driven by private interests. Planners/regulators have to define
the overall framework under which transport providers per-
form the delivery tasks so to minimise the negative impacts
UFT has on cities and residents. All these categoriesinterests
need to be taken into account when deciding about UFT pol-
icies. Besides, any innovative solution should explicitly con-
sider and account for its behavioural implications when iden-
tifying the levers used to influence present trends so to address
the sustainability challenges UFT poses to modern cities [57].
Under this respect, freight behaviourresearchis a fundamental,
yet understudied, subject [8].
Specific trends within UFT (e.g. e-commerce growth) in-
fluence both the type and dimension of the challenges policy-
makers will be confronted with in the near future. Various
measures have been considered (regulatory; market-based;
land use planning and infrastructure; new technologies) and
there is hefty evidence that no single solution can address and
solve all UFT problems [9]. Rather, an integrated policy pack-
age approach is needed [10]. Furthermore, ever-increasing
demand for a better city-life quality suggests promoting a
greater integration among freight activities within the urban
transportation system. At the same time, however, the pecu-
liarities of various cities in terms of legislation, regulation,
infrastructures, network, urban configuration and social habits
call for context-specific UFT measures [11].
It is necessary to understand the root causes that produce
UFT related problems and this can lead to more appropriate
and, therefore, effective solutions [12]. In general, serving
local businesses and homes in cities is inefficient mainly be-
cause of multiple non consolidated deliveries to many
destinations and also because of the constraints on routing
and scheduling posed by restrictions to certain routes or time
periods. Besides, home deliveries is even more inefficient due
to several reasons, among which the spatial dispersion of res-
idences and the frequency of failed deliveries [13].
UFT policy interventions sometimes grind to a halt or pro-
duce unintended results also due to the decision-making pro-
cess adopted for their selection. In fact, the often too typical
Bdecide and defend^approach, but also participatory
decision-making processes, when void of both behavioural
impact and ex-ante business model assessment, do not consti-
tute a robust base for an optimised policy selection capable of
guaranteeing the desired results. To produce long-lasting ef-
fects one should, coherently and co-ordinately, evaluate se-
lected policies accounting for the pre-existing city planning
The main shortcomings motivating the methodological ap-
proach proposed in this paper refer to: 1) incomplete under-
standing of UFT problems and challenging solutions, 2) scant
coordination between urban transport and logistics stake-
holders, 3) lack of information/understanding related to
behavioural issues and, 4) insufficient and uncoordinated ur-
ban logistics strategies among local policy-makers producing
a limited integration of UFT policies with the overall urban
mobility system.
This paper proposes an innovative decision-making pro-
cess for urban freight planning, easily transferable across cities
and capable of jointly: (a) accounting for conceivable UFT
measures applicable to the specific city culture, structure and
their likely evolutions, (b) considering and involving all rele-
vant stakeholders in the planning process, (c) integrating be-
havioural, technical, operational, organisational and financial
Three distinct yet complementary phases constitute the
backbone of the methodology, which is innovative since it is
a well-thought-out combination of well-established methods
in a single integrated methodological framework. Outcomes
of cutting-edge UFT research and innovative initiatives repre-
sent its main inspirations. More in detail:
&Phase 1 Bdesk approach^produces a preliminary logistic
city profile [14]. This task is performed using info on city,
stakeholders and freight characteristics. Subsequently, an ex-
ante and context-specific policy ranking is defined via prob-
lem capture techniques cross-referenced to a policy database.
&Phase 2 - Bliving lab approach^[15] refines the policies
selected, improves and transforms them, using a collabo-
rative governance model approach so to include them
within a sustainable urban mobility plan (SUMP) frame-
work, thus defining a shared policy subset thanks to an
active/fruitful involvement of relevant stakeholders in a
long-lasting/integrated planning process.
&Phase 3 - Bmodelling approach^focuses on the most ap-
propriate behavioural stimuli capable of favouring policy
implementation/adoption, based on differentiated yet inte-
grated state-of-the-art policy assessment methodologies
(e.g. behavioural and business model analysis) coupled
with ITS/gamification tools, and it provides policy-
makers with an efficient, effective and innovative
decision-support system.
The three-phase methodology is intended for experts to
support local public authorities (i.e. the decision-makers) by:
1) increasing knowledge and understanding of the most inno-
vative, promising context-specific UFT policies; 2) integrat-
ing UFT policies in strategic urban planning via collaborative
participation/governance processes; 3) developing an ex-ante
behaviourally consistent, financially robust and technically
compatible assessment of shared UFT policy mixes while
providing appropriate instruments to facilitate policy adoption
and deployment (Fig. 1).
The organisation of the paper is the following: section 2)
reviews the state of the art of current approaches to UFT
policy-making with a focus on recent and significant UFT
32 Page 2 of 11 Eur. Transp. Res. Rev. (2017) 9:32
innovative research streams and initiatives; section 3)presents
the main elements and steps of the proposed methodological
approach; section 4) derives relevant implications for UFT
policy-making, discussing the potential of the integrated ap-
proach; section 5) concludes summarizing the main concepts.
2 Literature review
The traditional planning approach related to urban transport
relies on studying transport demand to find and support solu-
tions mainly related to passenger mobility. This is, in fact, the
predominant component of overall mobility while freight is
often neglected [16]. Lately, a fast-growing awareness of the
strategic importance UFT plays and the related negative im-
pacts it causes at city level has produced an increase in the
research efforts made to define and implement sustainable
UFT solutions. UFT planning should be considered within
the overall urban mobility framework, as suggested by the
Sustainable Urban Mobility Plan (SUMP) approach [17].
UFT planning and Sustainable Urban Logistic Plans
(SULPs) are to be included as essential components of
SUMPs [1820].
Over the past 15 years, a range of UFT research and
innovation initiatives have proposed solutions to tackle
the problems caused by urban freight deliveries (e.g.
CIVITAS I, II, PLUS, PLUS II). Several projects have
also been devoted to collecting and deploying UFT best
practices (e.g. BESTUFS I, II, BESTFACT, TIDE,
SUGAR). Nevertheless, there is a general lack of detailed
knowledge needed to address UFT issues by local policy-
makers and substantial opportunities for improvement still
persist. In fact, a fair amount of UFT-related programmes
has been characterised by a non-negligible failure rate.
This is mainly attributable to the insufficient commitment
from relevant stakeholders. Involving stakeholders early
on in the process, on the contrary, usually produces better
results [21]. Unsatisfactory results also derive from re-
search projects based on real-life implementations of in-
novative UFT solutions. Although many initiatives proved
successful in pilots and demonstrations, large-scale adap-
tations did not take place. The reasons for failures differ.
However, one common feature is that only few initiatives
consider all stakeholders and jointly test all possible so-
lutions. In some cases, the implementations terminate
shortly after public funding comes to an end [11]. These
considerations call for an in-depth investigation, often not
performed, of the financial sustainability of the solutions
Besides, innovative and well-grounded decision-support
systems (DSS) are necessary to deal with the complexity
characterising UFT environment and participatory decision-
making. Three elements are fundamental and strictly inter-
laced to make a DSS effective and efficient: data, models
and simulations. Understanding, predicting and interpreting
stakeholdersbehaviours to policy interventions requires data
and models to produce suitable hypothetical scenarios simu-
lations and ex-ante evaluations of their likely acceptability and
effects. Under this respect, an innovative approach promotes
the combination of disaggregate behavioural freight models
(e.g. discrete choice models - DCMs), and dynamic simula-
tions (e.g. agent-based modelling - ABM). In fact, while
DCMs can adequately elicit stakeholdersindividual prefer-
ences based on sound microeconomic theory [9,22,23],
Sustainable Urban Mobility Plans (SUMPs) aim at devising and developing
Bmeasures to improve the efficiency of urban logistics, including urban freight
delivery, while reducing related externalities like emis sions of GHG, pollutants
and noise^[17].
Fig. 1 Framework of the
proposed decision-making
Eur. Transp. Res. Rev. (2017) 9:32 Page 3 of 11 32
ABMs can simulate and reproduce interaction in a participa-
tory decision-making process where stakeholders can influ-
ence each othersdecisions[2426].
Behaviour change is an important aspect policy-makers
should focus on to boost the success probability of the strategies
adopted. Indeed, freight demand strategies
mostly concentrate
on changing receiversbehaviour, those who generate transport
demand[27]. This has a greater potential for improving the
economic, social, and environmental performance of urban
freight systems [8].
While incentives are useful to foster UFT
behaviour change, a recent trend aims at engaging and promot-
ing sustainable behaviours using Bgamification^techniques, i.e.
the use of game design elements in nongame contexts [28].
Gamification is gaining popularity in the mobility domain
(e.g. [2933]). However, to be effective, it needs to be appro-
priately conceived, deployed and managed. A user-centred,
behaviourally consistent design approach is desirable. One
can pursue this by using stated choice experiments and
DCMs to combine game characteristics and tailor them to the
gamified context, thus aligning them with agentspreferences
and expectations [33]. This will maximise each agent-type en-
gagement and behaviour change potential. In this respect,
gamification can stimulate sustainable UFT behaviours.
Another key issue is finding effective ways to improve
freight movement and logisticsactivities efficiency. The con-
cept of BPhysical Internet^[34], as a metaphor of the Digital
Internet, has been recently introduced Bto propose a vision for
a sustainable and progressively deployable breakthrough so-
lution to global problems associated with the way we move,
handle, store, realise, supply and use physical objects all
around the world^(from the Physical Internet Manifesto
[35]). Physical Internet aims at developing a BHyper-connect-
ed City Logistics^, a conceptual framework for designing sig-
nificantly more efficient and sustainable urban logistics and
transportation systems assuming full-fledged interconnected
cities and logistics activities [34].
Considering all the discussed issues and concepts together,
it is evident the need of a comprehensive and innovative ap-
proach to decision-making in urban freight planning. To this
end, this paper proposes, discusses and illustrates a set of
procedures, models and tools to select an optimised mix of
shared, applicable, effective and financially sustainable UFT
policy measures, aimed at improving city logistics efficiency
while accounting for agentsheterogeneous preferences and
deep-rooted interactions characterising this complex
3 Methodology
3.1 Desk approach to understand cities
Desk approach is core to the first phase and focuses on
providing a preliminary well-thought list of city-specific
candidate policies representing the starting point for further
stakeholdersevaluation (Fig. 2). City logistic profiles are
acquired on the base of specific city, stakeholders and freight
characteristics [14] that, all together, allow to define the root
causes that produce the problems to be solved (as explained
in section 1) and the objectives the policy-maker should aim
at. The profiles characterise the logistic vocation, e.g. large
commercial stores, business centre, residential areas with
local trade [14]. Then, thanks to scientific knowledge, prob-
lems are captured and cross-referenced with a policy data-
base that draws on urban freight best practices, producing an
ex-ante context-specific policy ranking.
The main tools available are:
1. Open data sources:Bopen^data sources are used to com-
plement city-provided data to enhance knowledge and
improve modelling inputs. This compensates for the gen-
eral lack of data representing one of the main factors hin-
dering the development of next-generation UFT models
which, in turn, may limit effective policy-making and
operations management.
2. Scientific knowledge: it consists of performing and peri-
odically updating a wide-ranging and well-structured sci-
entific literature survey concerning UFT policy covering:
measures, effects, controversial issues, interactions, etc.
This will provide a consistent, updated, interdisciplinary,
relevant, possibly exhaustive mapping of the contribu-
tions appearing in scientifically well-respected journals.
3. Urban freight best practices:measuresadoptedandgoals
expected from UFT real-life implementation are classified
and evaluated according to: a) temporal reference scale
(strategic, tactical, and operative), b) decision-makers in-
volved, c) number and type of goals pursued.
4. Policy database matching: it includes two activities: a)
creating an extensive and typified policy database based
on the results obtained in EU-funded projects (e.g.
NICHES; SMARTSET; etc.), as well as in national and
regional ones, and drawing on the urban freight best prac-
tices previously acquired; b) developing a matching
algorithm/software to determine the best possible
Holguín-Veras and Sánchez-Díaz [8] definefreight demand strategies as Bthe
area of transportation policy that seeks to induce the demand generator to enact
changes indemand patterns to increase economic productivity and/or efficien-
cy; and/or enhance sustainability,quality of life, and/or environmental justice.^
BExamples include: off-hour delivery programs that incentivize receivers to
accept deliveries in the off-hours; staggered pick-up/delivery programs that
induce receivers to spread their deliveries throughout the day; and Receiver-
Led Consolidation programs that encourage receivers to reduce their Freight
Trip Generation^[8].
e.g. CIVITAS Training: Influencing behavior through gamification (http://
32 Page 4 of 11 Eur. Transp. Res. Rev. (2017) 9:32
combination between policy database and outputs of the
previous activities (i.e. logistic profiles and problems
3.2 Living lab approach for policy planning
The second phase relies on a Bliving lab approach^,where
cities operate as innovation promoting contexts to stimulate
implementation processes for public and private measures to
contribute to increased efficiency and sustainable urban logis-
tics [15]. A living lab is defined as a dynamic environment
built to test project solutions in real-life contexts (e.g. cities)
where several implementations performed by different stake-
holders run in parallel [36]. A city logistics living lab environ-
ment comprises three layers: strategic, practical and ex-post
results observation, enabling a Bfeedback loop^to decide for
new directions and possibilities of the living lab [37].
Following the living lab concept, the policies selected in
phase 1 are refined adopting a collaborative governance mod-
el approach supporting their consideration for inclusion within
SUMPs. The sub-set of shared policy measures is obtained
thanks to an active and fruitful promotion of relevant stake-
holdersinvolvement in a long-lasting/integrated planning
process (Fig. 3).
The two main pillars are:
1. Stakeholder engagement: it is the prerequisite for a suc-
cessful setup of a living lab environment [38]capableof
producing jointly desirable solutions, departing from the
consolidated Asian Development Bank methodology
[39]. Actions needed are: a) clarify stakeholder involve-
ment purposes; b) define stakeholders to involve; c)
motivate the previous point); d) discuss methods for
achieving involvement; e) explain who should organise
the process. Appropriate tools, such as Multi-Actor
Multi-Criteria Analysis, can be used to account for stake-
holderspreferences in evaluating alternatives [40,41].
2. Integrated planning: it consists of coordinating spa-
tial, temporal and technical planning activities to pro-
mote the achievement of the goals set. The process
focuses on methods to integrate collaborative gover-
nance model outputs into SUMP while also consider-
ing the specific city planning status quo situation.
SUMP standard cycle [42] constitutes the starting
point for the integration of different planning and
stakeholder engagement activities.
3.3 Modelling approach for policy evaluation
and facilitation
The last phase consists of policy evaluation via differentiated
yet integrated policy assessment methodologies and facilita-
tion, providing the most appropriate behavioural stimuli capa-
ble of favouring policy implementation developed thanks to
innovative ICT-based tools, thus supporting local policy-
makersdecisions via a reliable and innovative DSS (Fig. 4).
The objective is to collate a well-balanced set of integrated
assessment methods capable of facilitating the coherent and
successful deployment of effective, applicable and, possibly,
financially sustainable solutions. This set of activities could
include a variety of tools both aimed at policy assessment
(points 1, 2, 3 and 4 of the list reported below) and policy
implementation with the final goal of promoting relevant be-
havioural changes (points 5 and 6):
Fig. 2 Description of the first
phase Bdesk approach^
Eur. Transp. Res. Rev. (2017) 9:32 Page 5 of 11 32
1. Innovative data collection: it complements previous anal-
ysis providing additional data for UFT modelling/evalua-
tion. It integrates actively acquired, behaviourally relevant
observational data (e.g. face-to-face/internet-based stated
preference) with innovative passive data collection meth-
odologies, based on pervasive/low-cost sensing technolo-
gies (e.g. GPS and smartphones), producing unprecedent-
ed high quality and quantity datasets for model estimation
and validation (e.g. [4345]).
2. Transport Network analysis and simulation: it supports and
complements the shared policy sub-set evaluation through
a set of simulation models considering performances and
flows deriving from the interaction between stakeholders
choices (i.e. the demand generator of freight transport) and
transport infrastructures/services (i.e. the supply) [46].
Models allow performing specific assessment tasks, e.g.
gauging energy dependence in UFT as already performed
with respect to passenger transport analysis [47].
3. Behavioural & Business Model analysis:itconsistsof(a)
behavioural and (b) economic models to assess stake-
holderspolicy acceptability and financial viability.
Point (a) can be performed using DCM, ABM and a com-
bination of DCM with ABM (see section 2)toconsider
heterogeneous stakeholderspreferences, explicitly
Fig. 4 Description of the third phase BModelling approach^
Fig. 3 Description of the second
phase BLiving Lab approach^
32 Page 6 of 11 Eur. Transp. Res. Rev. (2017) 9:32
accounting for stakeholdersinteractions and ex-ante sim-
ulated policy effects [26]. An example of the integration of
stakeholders' behavioural analysis within the living lab ap-
proach can be found in [48]. Point (b) uses Business Model
Canvas techniques [49], providing a clear overview of the
most important costs, key resources and activities to ex-
ploit, necessary to assess financial viability of the solutions
under evaluation. In this respect, the core areas of a
Business Model (i.e. infrastructure management, product,
customer interface and financial aspects) can be easily
transferred to urban logistics, since it implies a business
with products/services to be delivered from producers/
suppliers to customers, and the Business Model Canvas
can be adapted accordingly, as reported in [14].
4. Key Performance Indicators (KPI) and impact
assessment: it consistently describes policy alternatives
using suitable and relevant indicators [50]toassessnor-
malised impacts by defining weight criteria, visualising
and interpreting results, performing sensitivity analysis
and producing an BOverall Joint Satisfaction Index^.
Typical KPI related to UFT are (increased) load factor,
(reduced) vehicle movements, but also financial, social
and process indicators (e.g. costs and benefits, new job
possibilities generated, customer satisfaction).
5. Gamification: it facilitates behaviour change and is com-
plementary to the planning phases. Context-specific
game-design/mechanisms and elements have to be iden-
tified early on to boost participation and engagement
and the potential impact of a well-thought gamification
process on the success of the policy should be assessed
in the evaluation phase, i.e. before implementation [33].
Gamification contributes to increase eco-logistics aware-
ness (e.g. eco-labelling, eco-driving, anti-idling) and
stimulates pro-active behaviours via a smart use of
social media. 6. Intelligent Transport Systems (ITS):
they improve logistics flows effectiveness (high ser-
vice levels) and efficiency (cost reduction) while re-
ducing negative externalities, and their potential effect
should be taken into consideration during the evalua-
tion phase [51,52].
If assessment results are not satisfactory, the process will go
back to phase 2 to start a new cycle of the living lab approach
and define different policy packages. On the contrary, in case
of satisfactory results, the process ends with the definition of
an optimised policy mix, derived from a continuous refine-
ment procedure where policies are evaluated via non-
correlated and complementary evaluation tools. This policy
mix is likely to be shared (thanks to stakeholder engagement),
is applicable/effective, financially sustainable (checked via the
assessmentresults) and easily deployed and adopted (based on
behaviour change facilitation tools).
4 Implications for UFT policy-making
UFT policy-making is inherently complex. There are no simple
solutions to complex problems. Different actors would need to
collaborate and coordinate their actions to fine tune the meth-
odology proposed with the aim of producing relevant results
and practically demonstrate its flexibility, reliability, compre-
hensiveness and effectiveness. In this respect, the living lab
model, with different layers and feedback loops is fundamental
to assure a continuous communication and coordination among
actors and a step-by-step decision-making process.
The potential of the proposed methodological approach,
still to be practically demonstrated, should be contrasted
with the approaches presently used. It is the Authorscon-
jecture that the methodological approach proposed has a
great potential when compared to the disjoint use of the
techniques. In fact, it should overcome the main drawbacks
of present approaches, by jointly: (1) addressing the prob-
lems of incomplete understanding of UFT problems/solu-
tions, scarce coordination between stakeholders and different
planning sectors, and lack of ex-ante policy evaluation or,
more in general, scant information/understanding of behav-
ioural issues; (2) producing added value in identifying an
optimised policy package capable of deploying and
supporting cost-effective, shared and environmentally sus-
tainable UFT solutions (Table 1).
Tabl e 1 Comparison of different approaches to UFT policy-making and added value of the proposed integrated framework
Approach Problem addressed Outcome Effort Potential of success
1 Desk Incomplete understanding of UFT
problems and solutions
Deep well-grounded
context-embedded knowledge
2 Living laboratories Scant coordination between stakeholders
and different planning sectors
Collaborative and integrated planning ++ ++
3 Modelling Lack of ex-ante policy evaluation
and scant information/understanding
of behavioural issues
Evaluation by using different methods
and performing sophisticated analyses
++ ++
4 (1) + (2) + (3) Identifying an optimised policy package
and supporting the deployment of
cost-effective UFT solutions
Bringing together knowledge acquisition,
policy co-creation, technical and behaviour
change analysis
+++ +++
Eur. Transp. Res. Rev. (2017) 9:32 Page 7 of 11 32
It is important to underline that the methodological ap-
proach proposed in this paper innovates in the joint, coordi-
nated and correctly sequenced use of well-accepted and de-
veloped techniques that have gained a substantial consensus
among researchers and practitioners. The main innovation of
the methodological proposal in this paper lies in the selection,
sequence and interconnected use of the techniques. This, in
fact, innovates while using well-established tools. The main
implication for policy-making is guaranteeing both positive
impacts for society, short-term policy acceptability and long-
term social, environmental and economic sustainability. The
sequence of methods proposed, reported in Fig. 5,allowsfor:
&(stage 1) a pre-selection of policies that accounts for the
specific city characteristics and previous policy experi-
ences conducted elsewhere;
&(stage 2) policy co-development, via a living lab approach
that refines the set of previously individuated policies also
Fig. 5 Framework of the overall
methodological approach
32 Page 8 of 11 Eur. Transp. Res. Rev. (2017) 9:32
allowing for changes, active stakeholder engagement,
stimulating a pro-active and inclusive participation of all
relevant actors;
&(stage 3) active circular and interrelated policy assessment
(see Fig. 4); if the policy mix implemented is not consid-
ered satisfactory phase 2 will be re-iterated.
It is clear that an integrated approach requires more effort
with respect to using just one technique alone (see Table 1).
This is even truer for the desk approach. On the other hand,
however, it has a greater potential for success being capable, at
least in principle, to overcome the drawbacks single ap-
proaches have in identifying an optimised policy package ca-
pable of supporting the deployment of effective UFT solutions.
This paper proposes and discusses a prototypical integrated DSS
for local policy-makers and describes a set of procedures, models
and tools to select an optimised mix of shared, applicable, effec-
tive and financially neutral UFT policy measures, accounting for
agentsheterogeneous preferences and deep-routed interactions
characterising this complex environment. The three-phase frame-
work proposed integrates diverse approaches/methods and ex-
plicitly considers the heterogeneous actors involved. It brings
together, within a single methodological approach:
&knowledge acquisition, including all conceivable and up-
dated UFT measures that could apply to the specific city
culture, structure and evolution (desk approach);
&policy co-creation, considering all relevant stakeholders
and successfully involving them from the beginning (liv-
ing lab approach);
&behavioural, technical, operational, organisational and fi-
nancial analysis, identifying the optimised policy package
and bringing together all these issues within a single meth-
odological framework (modelling approach).
Local authorities, when dealing with the complexity of
urban freight transport policy-making, could use the method
proposed as a strategic level DSS since it overcomes the limits
of the methods previously used.
Acknowledgements This work was supported by and developed with-
in the framework of the EU H2020 CITYLAB project (grant agreement
no. 635898).
Open Access This article is distributed under the terms of the Creative
Commons Attribution 4.0 International License (http://, which permits unrestricted use,
distribution, and reproduction in any medium, provided you give appro-
priate credit to the original author(s) and the source, provide a link to the
Creative Commons license, and indicate if changes were made.
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... Usually in decision-making, what we have to consider is not only the individual's evaluation of all aspects of the problem (criteria), at the same time, but also weigh each person's preferences (weights) considered for different criteria. At present, decision-making is widely used in urban planning [1]- [4], company operations [5]- [7] and many other fields [8]- [14]. Sound decision-making plans are aimed at maximization of benefits and reducing unavoidable risks and losses. ...
... Step 5: Finally, the vector of preferences of alternatives is constructed by combining intervalvalued fuzzy sets [$] with weights [$] as described by (1). In addition, for triangular fuzzy sets, the weighted sum is computed by the transformation format of (1) as follows, then we obtain the result • as below. ...
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In this study, we introduce and develop a novel decision-making model that provides an original solution to problems of renewable energy site planning. The main idea is to construct a comprehensive and systematic methodology of ranking alternatives encountered in the environment of multicriteria group decision making. The proposed framework is systematically structured with the aid of information granules, in particular, intervals and fuzzy sets. An overall architecture is developed in a comprehensive manner. The inherent facet of uncertainty, it is formalized and processed with the aid of information granules. The two main design phases involve the determination of preference degrees of alternatives with respect to the set of criteria and the weights of the corresponding criteria. The underlying estimation process is realized with the use of the pairwise comparison method (analytical hierarchy process-AHP) resulting in information granules (fuzzy sets) quantifying degrees of preference and relevance of the weights. In light of the group nature of the decision process and diversity of views and opinions conveyed by the individual decision-makers, the results provided by them are aggregated and the diversity (variability) in the individual assessments is captured through information granules of type-2. Finally, a variety of ranking procedures is analyzed and carefully assessed. A case study of selection of solar site is provided to demonstrate the usefulness of the developed approach. Compared with the existing decision-making scenarios, we show that the new model exhibits a significant level of reliability and is characterized by better interpretability.
... It assists tourist movement (Masiero and Zoltan, 2013), provides employment to the local community (Williams and Ponsford, 2009), as well as enhances commercial and business activity by providing the required connectivity (Leiper, 2004;Lew and Mckercher, 2006). Therefore, transportation has been given much emphasis in government planning policies as it is a major influence on any tourist destination (Gatta et al., 2017;Peeters and Schouten, 2006). ...
... Although Gatta, Marcucci and Le Pira (2017) and Peeters and Schouten (2006) prove that transportation has been greatly emphasized in government planning policies, considering its major influence on any tourist destination, the thorough analysis of the various means of transportation in relation to the geographical origin of a visitor to a national park has not been performed until now. It is especially important when elaborating tourism policies to be able to segment visitors into residents and non-residents. ...
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This paper considers the most suitable market segment(s) from an environmental and local economic development perspective in the specific context of visits to natural environments. More specifically, the paper explores the distinctions and differences between tourists (non-residents) and residents with regard to visit behavior at natural attractions. By using the CHAID algorithm, a decision tree is constructed for means of transportation which serves as a key factor in the segmentation process. However, such a tree for visitors' resident or non-resident status cannot be built as a first explicative variable, unless it is statistically forced. Once it is forced, the tree opens in several sub-segments, for non-residents and residents alike. Finally, it allows understanding of the means of transportation used by visitors according to their geographical origin as well as a set of added independent variables: accommodation establishment, length of stay, season, and other demographic variables (educational level, gender, and age). Also, more importantly, we have obtained segments with no overlap configured according to all the aforementioned variables. This is a very strong result from a methodological point of view and for policy makers in destination settings.
... Living lab is suggested for modelling the technology disruptions and transformations in a complex sociotechnical system such as city logistics [40,41]. The living lab in the city logistics aimed at continuously revising and improving the logistics performance via modelling 1) collaborative participation, 2) government processes, and 3) technology disruptions. ...
... An inventory of the urban mobility, logistics and automotive living labs in Europe performed by Nesterova et al., (2021) resulted in 201 initiatives, including living labs, test beds, and other initiatives containing living lab elements but not labelled presently as such, from which 22 have/had logistics identified as a main topic of the experiments. Therefore, the living lab movement is being progressively recognised as a driving force addressing the challenges of the urban freight transport system (Gatta et al., 2017). ...
... On the other hand, various city stakeholders communicate, struggle, and collaborate and are usually defined by conflicting purposes. Stakeholders can be commonly described as those interested in the decision-making process, even if they have no legal role (Gatta, Marcucci, & Le Pira, 2017). However, actor networks are transforming while technological improvements. ...
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Urban technologies and smart city applications show that a new era has started in urban planning, and a new structure has been formed because of endless information flow and distribution. The participation process has also carried on a new structure with the changes. Urban living labs (ULL) is a form of experimental governance which can offer creative solutions for the problems that cities face today. The research is aimed to determine the new actors in a new era in the process of transformation while interviewing two ULLs in Turkey. Through interviews, decision-making, actualization, collaboration, and participation, processes were established. Moreover, analysis shows that the technological transformation process is currently in the digital environment rather than redound on the spatial environment in Turkey. While ULLs provide opportunities to adapt to technology, they have not become widespread or have not been identified yet to show limitations in cooperation and application.
... Note that FQPs are collaborative networks of freight partners that work together on logistics operation issues, share information and experiences, and develop a common freight strategy [44]. A Living Lab, on the other hand, is a dynamic environment where solutions are developed and tested in real contexts (in our case cities) with multiple implementations by different stakeholders in parallel [47]. ...
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City logistics is subject to constant development, generated by new logistics trends and high customers’ expectations. With the aim of creating an effective, acceptable, and sustainable city logistics policy, it is therefore essential to understand logistics trends and their expected impact on the development of urban freight transport in the future. In this paper, we explore and compare the expectations of public authorities, business, and academia regarding the short-, medium-, and long-term impacts of different logistics trends on urban logistics. Following a literature review, the expert survey was used to assess the expected impact and time horizon. According to the respondents, “e-commerce”, “automated vehicles”, “electric vehicles”, “grey power logistics”, “omni-channel logistics”, and the “desire for speed” will have the greatest impact on urban freight transport in the future. An interesting observation concerns some differences of opinion between public and private stakeholders. In general, the business community believes that the identified trends will have a greater impact on urban logistics in a shorter period of time, while public authorities believe that the mentioned trends will have a less strong impact on urban logistics in a longer time scale. This shows the need for more active collaboration between them in the policy-making process.
... Noise pollution is also a serious problem for citizens, with mobility being responsible for 3 54% of noise in cities. According to Air Visual, which monitors air quality, Uzbekistan ranked 16 th in the ranking of countries with the most polluted air [9]. The result: 54% of Tashkent citizens are exposed to noise levels higher than those recommended by the WHO and 72% consider that they live in noisy environments. ...
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New mobility technologies and solutions are revolutionizing the way people and goods move around cities. However, due to their lack of maturity, they are not able to respond to the growing needs and challenges of urban public mobility and are adding even more pressure. As a result, the urban mobility model remains under stress, with increasing levels of congestion, pollution and accidents. This stress will be further increased by increased urban concentration and economic activity resulting from new consumption patterns. In this article, solutions and initiatives are proposed that will enable Uzbekistan cities to be equipped with an integral model of social and sustainable mobility.
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The rapid technological and regulatory evolution in the field of autonomous unmanned aerial vehicles (UAV or drones) may soon open the way for their deployment in the last mile delivery of products. This has the potential to decrease delivery costs, reduce transport externalities caused by road traffic and reduce missed-deliveries. It could thus become a disruptor to the parcel delivery industry and for this reason several transport and delivery companies are piloting experiments involving drones. Yet a detailed analysis of the market potential of this system is still only partly available in the literature. To bridge this gap, this paper tries to quantify the proportion of the population, both in Europe and the USA that could benefit from drone-delivery services. Results indicate that under the conditions considered drone delivery services could be financially viable in the Europe and in the USA, where they could serve between 16 and 43% and between 32 and 60% of the population respectively. These results indicate the viability of this industry in the near future, highlighting that the existing geographical distribution of populations has a significant influence and will likely drive the choice of the first deployments.
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In recent research work (FP7 CONDUITS) a performance evaluation framework for traffic management and Intelligent Transport Systems was developed. The new framework consists of a set of Key Performance Indicators (KPIs) for the strategic themes of traffic efficiency, safety, pollution reduction and social inclusion, and the last stages of the project saw its validation through its application to four case studies. Following up from this work, this paper presents the extension of the framework for use as a prediction tool enabling urban transport authorities to assess the impacts of relevant policies and technologies before implementing them. Focussing on pollution reduction, a tool (CONDUITS-DST) integrating the respective KPIs with microsimulation modelling is developed. The paper describes the integration process, including the model chosen for calculating the emissions levels of a number of scenarios, presents the results of the application to a case study in the city of Brussels, and outlines future developments targeted at broadening the integration of the KPIs into decision-making
A recent trend to engage and promote sustainable behaviors in transport foresees gamification, i.e. the use of game design elements in nongame contexts. To foster the expected behavior change, one should appropriately conceive, deploy and manage gamification. The paper addresses the problem of gamification design by proposing an advanced user-centered approach accounting for players’ heterogeneous preferences. This is performed using stated preference methods and is applied to a reverse logistics case study. By comparing the results obtained with the proposed approach to those derived from the traditionally adopted ones, the paper shows that the former would provide considerable new insights with respect to players’ heterogeneous preferences, thus, possibly, increasing the chance of achieving satisfactory results. The paper suggests that, whenever designing gamification to foster engagement and behavior change in transport, one should adopt a user-centered approach based on stated choice experiments to maximize its probability of success.
Abstract This paper proposes a novel approach to support participatory decision-making processes in the context of urban freight transport through the integration of discrete choice modeling and agent-based modeling. The methodology is based on an innovative multilayer network and opinion dynamics models and applied to the case study of Rome’s limited traffic zone. Simulation results produce a ranking of plausible policies that maximize consensus building while minimizing utility losses due to the negotiation process. These results can be used to support real participatory decision-making processes on freight-related policies accounting both for stakeholders’ heterogeneous preferences and their interaction effects.
This paper investigates the potential for off-hour deliveries in the city of Rome. It focuses on retailers that play a fundamental role in the decision making process often determining delivery times. It explores their preferences for three off-hour delivery prototypes and inquires retailers' willingness to adopt them, both with and without the provision of dedicated incentives. Finally, it analyses retailers’ reactions to a hypothetical scenario where a mandatory off-hour delivery policy is imposed. The overall results show a good inclination towards off-hour deliveries. This induces optimism with respect to their potential introduction as well as skepticism about the lack of attention local decision makers have, so far, paid to this policy option.
Overview: Transportation analysts are constantly faced with the challenge of understanding new services, modes or mobility solutions, typically at early stages of conception and in the absence of market data. The IATBR workshop organized by Amanda Stathopoulos and Cinzia Cirillo aimed to discuss emerging methods to theorize, model and collect data to help our understanding of adoption paths for transportation innovations. Over sixty participants attended the workshop, emphasizing interaction and joint discussions on adoption in the context of various innovative scenarios.
Abstract We address the problem of a participatory decision-making process where a shared priority list of alternatives has to be obtained while avoiding inconsistent decisions. An agent-based model (ABM) is proposed to mimic this process in different social networks of stakeholders who interact according to an opinion dynamics model. Simulations’ results show the efficacy of interaction in finding a transitive and, above all, shared decision. These findings are in agreement with real participation experiences regarding transport planning decisions and can give useful suggestions on how to plan an effective participation process for sustainable policy-making based on opinion consensus.