Download - Presentation Lanzini - Seminar ESAG/UDESC
Commuters and sustainable mobility: a research project on the determinants of travel mode choice in urban setting
Florian March 14th 2016
Prof. Pietro Lanzini, PhD
Prof. Pietro Lanzini, PhD
Department of Management, Cà Foscari University (Venice) Faculty member (CompeCCve Analysis; Principles of Business AdministraCon; Theories and Techniques in Management) Previous work experiences:
Bocconi University (Milan, Italy) United NaCons Headquarters (New York City, USA) Aarhus University (Aarhus, Denmark)
Fields of research: Sustainability; Consumer Behavior; Mobility; Pro-‐environmental Spillover
Within the transport sector, private mobility (that is, each and every one of us) is the main responsible, contribuKng to more than 50% of all
transport-‐related emissions
Many actors are involved in the shiQ to a new, environment-‐friendly paradigm: -‐ InternaConal bodies (legislaKon, standards, etc.)
-‐ Local PAs (SUMPS, etc.)
-‐ Industry (innovaKon, R&D, etc.)
-‐ NGOs, media (awareness campaigns, etc.)
-‐ CiCzens (the main actor: no public policy or measure can be successful without the acCve involvment of ciCzens)
Current mobility trends are clearly un-‐sustainable
InvesCgaCng the determinants of travel mode choice in urban seVngs:
an extension of the TPB model
-‐ Income, prices and economic consideraKons
-‐ Infrastructures and convenience of different transport systems
-‐ Psychological correlates of car/alternaKve modes use
RQ 1-‐ What are the drivers spurring travel mode choices and the adop4on of mobility alterna4ves, when available?
RQ 2-‐ What are the mutual influences with other behavioural domains?
RQ 3-‐What is the role played by past behavioural pa<erns in terms of habits strength?
RQ 4-‐ What type of rewards would be more efficient in modifying long-‐established behavioural pa<erns coherent with mobility policies goals?
-‐ Extensive literature review on the theoreKcal and empirical evidence on the determinants of travel mode choice (150 contribuKons)
-‐ Meta-‐analysis for a quanKtaKve systemaKzaKon of the evidence (61 papers)
-‐ Empirical invesCgaCon with primary data (Italian sample= 250 grad students)
-‐ Proposal of a new theoreCcal framework (habits, spillover)
-‐ TesCng in Italy and Brazil with SEM technique
Dependent variables: travel mode in terms of both actual behaviors and intenKons (gap) i) car (b) ii) non-‐car (b) iii) car (i) iv) non-‐car (i)
Predictors: SubjecKve norms; descripKve norms; injuncKve norms A_tudes Perceived behavioral control Personal/moral norms Environmental values Habits Awareness of consequences AscripKon of responsibility …
-‐ Only papers with empirical invesKgaKons and available correlaKon matrixes are considered (61/150) -‐ The effect size is based on Person’s R coefficient of correlaKon of different
studies
-‐ Fischer Z transformaKon to weight the sample size
-‐ Χ2 and I2 tests of homogeneity
Meta-‐analysis
It is a secondary staKsKcal research tool, that synthesizes evidence coming from a number of primary studies. We have many empirical studies on travel mode choice. For instance, some say that environmental values are very important, some say they have liPle impact, some say they are irrelevant. How can we synthesize this informaAon?
We want to collect and analyze also primary data
Center for Research in Social InnovaAon in the Public Sphere
Online survey (Italy and Brazil) We consider all the main predictors of travel-‐mode choice (TPB, values, habits, VBN, etc.) Goal: 600 respondents from the two Countries
-‐ Need for a holisKc approach
-‐ Habits (in the survey)
-‐ Spillover (future steps)
-‐ IncenKves (future steps)
Refinements and extensions of previous methodological frameworks
A step forward in research:
Habits: learned sequences of acts that have become automaKc responses to specific cues, and are funcKonal in obtaining certain
goals or end-‐states’
Carrying out the XYZ acCvity is something:
(1=totally disagree; 5= enArely agree) I do frequently. I do automaKcally. I do without having to consciously remember. That makes me feel weird if I do not do it. I do without thinking. Would require effort not to do it. That belongs to my (daily, weekly, monthly) rouKne. I start doing before I realize I’m doing it. I would find hard not to do. I have no need to think about doing. That’s typically ‘me’. I have been doing for a long Kme.
I refer to spillover as to the phenomenon (and related mechanisms) for which adopKng an environmentally sound behavior in one
domain spills over in different environmental domains
Are sustainable behaviors correlated with eachother?
• self-‐perception theory (Bem, 1972) • cognitive dissonance theory (Festinger, 1957) • learning theories (Nigg et al., 1999)
Theories suggesCng a posiCve spillover
… or a negaCve one
• Moral licensing (Khan & Dhar, 2006) • Contribution ethics (Guagnano, Dietz, & Stern, 1994)
• Self-‐serving bias
How to study spillover effects? i) IntervenKon study (survey at Kme 0, then you implement an
experimental intervenKon, then second round of survey on the same sample)
ii) Real-‐world intervenKons
The final step is the proposal of a new theoreCcal framework, and the tesCng of its predicCve capability
We depart from Theory of Planned Behavior, and add correlates of travel mode that according to i) the metanalysis and ii) our empirical invesKgaKon seem to be good candidates for inclusion
WHY?
-‐ Need to have a holisKc approach, and focus on determinants envisaged by different theoreKcal frameworks
-‐ Need to consider the specificiKes of the behavioral domain (e.g. commuKng is oQen carried out repeKKvely, in a stable context, so
that habits might play a bigger role than in other domains)
-‐ Social pressure is not as high as in other domains (e.g. recycling)
A_tudes (YES) SubjecKve norms (NO) Behavioral control (YES) + Habit strength Proneness to spillover …
For example, I might speculate that the new theoreKcal framework might be based on the
following predictors of travel mode:
-‐ Build up of new theory -‐ Second survey circulated, focusing on those elements that are hypothesized to be relevant
-‐ StaKsKcal tesKng of the predicKve capability of the new model (we want it to be able to predict travel mode choice be1er than tradiKonal TPB)
-‐ SEM technique (causal modeling, or path analysis, which hypothesizes causal
relaKonships among variables and tests the causal models with a linear equaKon system)
The project in a nutshell: -‐ The determinants of travel choices: state of the art, and synthesis of exisKng evidence (meta analysis)
-‐ Preliminary survey in Italy and Brazil on the determinants of travel mode
-‐ Theory building: based on this informaKon, we propose a new, more sophisKcated model
-‐ We test it adopKng the SEM staKsKcal technique
-‐ CiKzens are the key actor for any policy aimed at shiQing to more sustainable mobility pa1erns
-‐ Since “we cannot manage what we do not know”, it is crucial to understand individual choices
-‐ The results of the project can provide the informaKve background for policy makers and public authoriKes to organize sound policy measures, communicaKng effecKvely with ciKzens (e.g. incenKves, habit disrupKon, etc.)