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TECHNOSOLUTIONISM [and AGE+GENDER] IN SMART MOBILITIES DISCUSSIONS

Tanu Priya Uteng, Ph.d.

Senior Researcher

Institute of Transport Economics

Oslo, Norway.

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The basics…..

1trip distance/duration/purpose2trip-chaining3secuirty4temporal54As6modes7role/time distribution 8smart ?9climate policy making? ...

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Next steps…..�Borrowing from�Social Practice Theory

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Source: https://katsdekker.wordpress.com/2015/10/17/wrestling-mental-elephants/

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Example 1: Oslo Bysykkel city-bike sharing scheme

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Spatialities. Route mapping vis-à-vis share of female employment �

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Spatialities. Multivariate analysis

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OLS Regression analysis (N=16,950 routes)
		B		t
(constant)		-19.938	**	-6.725
route attributes	𝚫 elevation in m	.018	**	4.368
	route distance in km	.966	**	9.580
origin bike station attributes	population density	-1.474	**	-4.829
(in a 250m buffer)	employment density	-.672	**	-5.350
	population female share	.349	**	8.752
	employment female share	.334	**	15.061
destination bike station attributes	population density	-.743	*	-2.475
(in a 250m buffer)	employment density	-.353	**	-2.920
	population female share	.193	**	4.951
	employment female share	.238	**	10.061
rail/metro access (<200m)	access at start and at end	-1.072	**	-2.847
(ref. = access neither at start	access at start, not at end	-1.492	**	-3.983
nor at end)	access at end, not at start	-2.852	**	-2.736
model fit: F = 94.244 **; R² = .074

Women - more concentrated on the outer fringes of the city, both in terms of residential and employment locations
High employment/residential density of women – high bike sharing
Access-egress – Men
Multi-purpose trips – Women

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Example 2: Materiality

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SUPERHIGHWAY!!!!!

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London

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Types of cyclists and trips

The importance of the “strong and fearless” and “enthused and confident” cyclist as well as the commuting and sports trips in policy and promotion.

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Risk tolerance (Dill & McNeil, 2012)

Strong and the Fearless
Enthused and Confident
Interested but Concerned
No Way No How

(Source: New Zealand Transit Agency)

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Imageries - Cycling (Bergen, Norway)

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Advert for cycle registering against theft

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STATIC + DYNAMIC = missing!!

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Emerging key words: kinetic elite, peak hour, commute, fixed employment, fixed areas…..�Electrification, EVs, high-speed cycling…..

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The ‘desired’ Target groups

Commuters

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Flexibile trips, trip-chaining, travelling with children, linking multiple, geographically spread low-end jobs…….???

The ‘undesired’ Target groups

Family with young children
Elderly
Shift workers
Women
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Example 3: Accessibility_bicycle / E-bike, and

growth potential for Stavanger, Sandnes and Sola

Source: INMAP

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Accessibility_bicycle / E-bike, and growth potential for Oslo

Figure 18: Accessibility bicycle and E-bike, and growth potential Stavanger, Sandnes and Sola

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Figure 20: Accessibility bicycle and E-bike, and growth potential Oslo

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Source: INMAP

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Gender budgeting vis-a-vis travel patterns

…the modal share by car would increase by 17 %

…CO₂ emissions from car traffic would increase by 31%

…the additional demand for driving and parking space would add up to 190 Möllevångstorget (standard town square)

If women were to adopt the travel patterns of today’s men…

Example 4: Gender-disaggregated data and gender budgeting

Source: City of Malmö Planning Office, Daniel Svanfelt | Strategy Officer

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Priya Uteng, T., Knapskog, M., Uteng, A. and Sæterøy Maridal, J. (2021) Addressing climate policy-making and gender in transport plans and strategies, The case of Oslo, in G.L. Magnusdottir and A. Kronsell (Eds.) Gender, Intersectionality and Climate Institutions in Industrialised States (Abingdon and New York: Routledge). https://doi.org/10.4324/9781003052821

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Example 5: Smart Mobility – station-based and flexible carsharing. Case- Germany

Loose 2010, Riegler et al. 2016

Users of …..

….. station-based carsharing

40% women – 60% men

….. free-floating carsharing

30% women – 70% men� age group up to 35y

living in 1-2 person households

above average formal education

above average income

Source: Lenz 2017

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Smart Mobility – ridesharing / ridehailing. Case- Germany

Source: ciscosolutions.com

Source: Lenz 2017

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Example 6: ACTIVE AGEING, DENSE RESIDENTIAL AREAS & DAILY MOBLITY

Spatial planning
Increase in high rise apartments near transit nodes, urban centers etc.
A parallel development - a vast majority of the elderly population, 65+ RELOCATING
National level policy on Active Ageing

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Spatial planning in the urban areas of Norway - (re-) densification in the last decade
Increase in high rise apartments near transit nodes, urban centers and in locations which are in close proximity of basic facilities like grocery, medical store, library etc.
A parallel development - a vast majority of the elderly population, 65 and above have sold their houses and moved to apartment blocks built near the transit nodes and urban centers.
The reason quoted often revolves around being in close proximity to basic daily facilities.
This development operates in tandem with the national level policy on Active Ageing which clearly states that elderly population should reside in their own homes and care, when needed, should be provided to them at their residences. Only in cases where continuous monitoring and care is needed, are the elderly population offered a place in the elderly homes.

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65+ : The ignored customer base for car sharing?

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	Walking	Car	PT
Daily shopping
Heavy shopping
Leisure activities
Visit friends
Weekend trips

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65+ : Meanings attached to car sharing

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scored on a scale of 1-7, 1=completely disagree, 7= completely agree.

***mean scores are significantly different for the two groups, p<.001.

Identifying performance gaps

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65+ : Factors which might lead to an increased use of car sharing schemes

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scored on a scale of 1-7, 1=to a lower extent, 7= to a greater extent.

***mean scores are significantly different for the two groups, p<.001.

Designing future interventions.
Plotting differences over a period of time

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Expanding the portfolio of micromobilities- �New modes as part of future planning?

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TARGETS

Sewing offers to the mobility needs of different age-groups and life-stages – for ex. Integrated solution with the housing blocks, shared spaces+sharedmobility.
Differential pricing – time, age, emloyment status, tax benefits etc.
Marketing – University crowd <25; ‘Young-kids’ stage 25-40; Independent / ‘low family-responsilbility’ stage 40-65; Elderly 65+
Location – center vs. periphery
Reaching the clients – app vs. Non-app, training, linking to elderly activity centers etc.

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SMART solutions mainstreaming @ Macro-Meso-Micro

Needs, power structures, negotiation processes
TRANSITIONS – Digitalisation -Smart Cities- Smart mobilities – What do they mean for different groups?
What are the systematic / financial benefits? etc. – demands further consideration.
What are the implications for climate policy making? Numbers, projections, policies, programmes.
SHARED SPACES + SHARED MOBILITIES

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Thank you!!

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