Greener last-mile delivery technologies and regional development in Latvia: input-output approach

Abstract

The European Green Deal targets to limit emissions by applying sustainable and greener technologies in transport, including last-mile delivery services. The aim is to estimate the potential impact of application of greener last-mile delivery technologies in the companies on sectoral and regional development in Latvia, using the input-output approach applying the latest data set of 2020 for Latvia. The economy is disaggregated according to the NACE 2-digit level into 64 economic activities and regional development additionally into 5 regions (Riga, Vidzeme, Kurzeme, Zemgale, and Latgale). The bottom-up approach is used. According to NACE, postal and courier services (H53) are selected as the main focus in the research reflecting last-mile delivery services. Sweden is used as a benchmark country as Sweden is already having one of the greenest transport sectors. Modelling results argue that if the postal and courier services in Latvia apply a greener technology that already exists (possible, achievable technology, not just in theory), then the total value added declines by -0.1% due to lower intermediate consumption for manufactured products. The most positive impact is on services (as warehouse services, employment services, wholesale trade services), however, the services auxiliary to financial services and insurance services, air transport services, paper and its products have the most negative impact. The modelled regional results claim that the major negative impact is in the metropolitan areas (Riga region), medium – Kurzeme and Latgale, minimal impact – Vidzeme and Zemgale. The findings are valuable to the companies in the industries that might be affected due to the shift towards other technologies and practices, as well as for the national government and EU institutions in policymaking.

Full text

ENGINEERING FOR RURAL DEVELOPMENT Jelgava, 22.-24.05.2024.
414
GREENER LAST-MILE DELIVERY TECHNOLOGIES
AND REGIONAL DEVELOPMENT IN LATVIA: INPUT-OUTPUT APPROACH
Astra Auzina-Emsina
Riga Technical University, Latvia
astra.auzina-emsina@rtu.lv
Abstract. The European Green Deal targets to limit emissions by applying sustainable and greener technologies
in transport, including last-mile delivery services. The aim is to estimate the potential impact of application of
greener last-mile delivery technologies in the companies on sectoral and regional development in Latvia, using the
input-output approach applying the latest data set of 2020 for Latvia. The economy is disaggregated according to
the NACE 2-digit level into 64 economic activities and regional development additionally into 5 regions (Riga,
Vidzeme, Kurzeme, Zemgale, and Latgale). The bottom-up approach is used. According to NACE, postal and
courier services (H53) are selected as the main focus in the research reflecting last-mile delivery services. Sweden
is used as a benchmark country as Sweden is already having one of the greenest transport sectors. Modelling results
argue that if the postal and courier services in Latvia apply a greener technology that already exists (possible,
achievable technology, not just in theory), then the total value added declines by -0.1% due to lower intermediate
consumption for manufactured products. The most positive impact is on services (as warehouse services,
employment services, wholesale trade services), however, the services auxiliary to financial services and insurance
services, air transport services, paper and its products have the most negative impact. The modelled regional results
claim that the major negative impact is in the metropolitan areas (Riga region), medium – Kurzeme and Latgale,
minimal impact – Vidzeme and Zemgale. The findings are valuable to the companies in the industries that might
be affected due to the shift towards other technologies and practices, as well as for the national govern ment and
EU institutions in policymaking.
Keywords: last-mile delivery, input-output analysis, technological change, greener transport, regional
development, policymaking.
Introduction
Last-mile delivery has a growing scientific interest from various audiences. Greener transport
involves studies on major trends as application of smart data and circular economy [1], sustainable
mobility [2], also specific relatively innovative recent trends such as car sharing [3], e-scooter sharing
[4], gender-specific influence on choices [5], age factor in greener choices [6]. Greener last-mile
delivery frequently overlaps with technical, socio-economic aspects, and economic (costs-gains) factors,
at the same time with personal and non-economic factors.
The European Green Deal has tight targets in the near future. Sweden has the second-best European
Green Deal performance, following the Netherlands [7]. Concerning public transportation, revealing
accessibility problems within the transport system and supporting the planning of smart and sustainable
mobility networks, first-mile and last-mile issues are examined in urban areas (as in Stockholm, Sweden
by [8] ). Another study from Sweden argues that a company’s size matters when retailers design last
mile back-end fulfilment (LMBF) and last mile delivery (LMDe), while last mile consumer
steering (LMCS) practice does not appear to differ based on size, in result, larger retailers have a more
advanced LMDe and LMBF set-up than their SME counterparts [9]. At the same time, home delivery is
the preferred method of last-mile delivery and exists the lack of provided home delivery services in
Sweden [10]. Greener transport includes also lower emissions and reduced carbon dependency, policy
steps are expected as much air travel is induced by its low cost [11]. The research on collection-delivery
points argues that 22.5% reduction of vehicle kilometres travelled from collection-delivery trips by
relocating 5% collection-delivery points from urban areas to suburban and rural areas is applied as
greener last mile alternative in Sweden [12]. The literature review indicates that greener transport
technologies involve various or even multiple activities at the same time, not limited to one or few steps
required by policy measures.
The aim is to estimate the potential impact of application of greener last-mile delivery technologies
in the companies on sectoral and regional development in Latvia, using the input-output approach. The
focus of the study is to analyse existing technologies, hence a greener last-mile delivery country
(Sweden) has been detected rather as theoretically greener, however not applied yet in any country in
broad scale.
DOI: 10.22616/ERDev.2024.23.TF078

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Definitely, many researches and assessments by scientists and companies had been implemented,
and in near future, the shift towards greener technologies due to legislation and regulatory norms are
going to continue in the EU caused by the European Green Deal targets.
Materials and methods
The data are extracted from the following databases: Eurostat [13] and Central Statistical Office of
Latvia [14]. Potential development is modelled by applying an input-output approach using the latest
data set of 2020 for Latvia. Sweden is used as a benchmark country as Sweden is already having one of
the greenest transport sectors. The Netherlands had the best European Green Deal performance which
was followed by Sweden [7], by reducing fossil fuel dependence and becoming a global climate
transition leader [15].
Symmetric input-output tables (product-by-product approach) in current prices in 2020 (exception
is Sweden, the latest available on 2019 is used) by 64 CPA/NACE elements form the core dataset
representing technologies and intersectoral linkages. However, regional economic activity by value
added (NACE 20 aggregated groups) by 5 planning regions in 2020 [14] is used as the data by 64
CPA/NACE in the applied regional disaggregation was not available. As Latvia applies the product-
by-product approach to input-output statistics then countries that apply the same are analysed: Czechia,
Germany, Estonia, Ireland, Spain, France, Croatia, Italy, Cyprus, Latvia, Lithuania, Hungary, Austria,
Portugal, Slovenia, Slovakia, Sweden. Other EU countries apply the industry-by-industry approach.
Last-mile delivery is a concept outside traditional economic activity and product classifications
applied in statistics, hence courier and postal services (H53) are selected as representative economic
activity. Definitely, courier and postal services cover partially all aspects that in the literature had been
assigned and analysed concerning last-mile delivery technologies, development, applications, social
acceptance etc. aspects. These elements are outside the scope of this modelling.
Modelling the impacts of global consumption trends [16], policy measures during COVID-19 [17]
and greener technologies [18] on transportation in Latvia were also based on the input-output approach
and its adaptations. There is a long-standing expertise in the application of input-output based models
or models including input-output linkages in Latvia and other countries, as estimation of carbon footprint
[19], pollution by transport (in France [20], Spain [21] ), new technologies on road transport (as CGE
model for road transport electrification in the EU [22]).
The sequence of modelling:
1. Latvia’s input-output model (demand-driven approach) elaboration and calibration for 2020 data.
2. International analysis of H53 input coefficients (17 EU countries), justification of selected
benchmark country for greener already existing last-mile delivery technologies.
3. Modelling applying these selected greener last-mile delivery technologies in H53, other input
coefficients of 63 products are hold constant (only H53 is changed), resulting in sectoral impact on
64 economic activities output, value added and final demand. The main focus is paid to the value
added indicator. Results are computed in euros and relative changes in percentage are computed.
4. The bottom-up approach is used, aggregating values of 64 into 20 groups of economic activity as a
regional (regions) bridge matrix is not available for 64 economic activities.
5. Computations of absolute values and the relative impact on regional economic activity by 5
planning regions.
6. Modelling results and findings comparison to the existing studies.
Input-output model is based on classic identities that total supply is identical to total use. Any
product supplied is domestically produced (Xj) or imported (IMi), meanwhile any demanded (or used
product) is consumed in intermediate consumption (Xij) or final demand (Yi) domestically or exported
minus imported value (in other words, net final demand). Each input structure of a product (good or
service) consists of costs for products of other industries (intermediate consumption expenses Xij) and
added value (see Formula (1)):
(1)
where Xj – j industry’s output,
Xij – intermediate consumption of i products in j industry,

ENGINEERING FOR RURAL DEVELOPMENT Jelgava, 22.-24.05.2024.
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VAj – added value of j industry.
Direct input coefficients illustrate the input vector of a specific economic sector, i.e. what and how
many products of other sub-sectors and payments for labor, capital and other production resources are
required to produce one unit of the specific sub-sector’s products, representing the technological
requirements (Aij) (see Formula (2)):
. (2)
By comparing direct input coefficients in two or more time periods, the changes in technologies
and technological requirements are identified. Additionally, the coefficients of the added value vj can
be computed (see Formula (3)).
. (3)
On the other hand, any product produced in the economy, depending on various factors, may be
used in the production of other products (as an intermediate product), consumed (as a final product),
invested, exported (as an export product) (see Formula (4)):
(4)
where FDi – final consumption of households and government (including changes in stocks),
Ii – investments (or gross capital formation),
EXi – export,
IMi – import.
Regardless of the aspect in which economic activity is viewed, the output of industries is the same:
. (5)
The impact of the application of the greener last-mile delivery technology has been modelled by
replacing the existing Ai vector for postal and courier activities with benchmark technology.
In baseline modelling, the technology is believed to be changed but the final demand elements are
hold constant to assess the impact of greener technologies. Next, the value added is the calculation
quantity of the value added coefficient and the product of the calculation output:
. (1)
Therefore, it is also possible to model changes in industry technologies (changes in the values of
direct cost coefficients Aij) or changes in the part of added value, thus using the corresponding values
of added value coefficients in the calculations. If regional allocation of economic activity is introduced,
then also regional effect is being computed. At present, five planning regions (close to NUTS-3) are
being used, determined by data availability.
Computed direct input coefficients for postal and economic activity for 17 countries (see Table 1)
lead to the finding that value added share in one unit produced (ratio of value added to output) (vj) varies
significantly and at three subgroups:
• high value added to output (Croatia, Hungary, France, Ireland, Cyprus, Slovenia, Sweden),
• medium (Austria, Portugal, Lithuania, Czechia, Slovakia, Spain) and
• low (Latvia, Germany, Italy, Estonia).
In Latvia, to produce one euro worth of postal and economic activity, 0.59 euro is spent on other
products and services and 0.02 on product taxes; the value added is relatively low – 0.38 euro and this
is below the national average in 2020 (0.49).
It leads to the necessity to model the economic effect if a greener (according to industry and
consumer perspective) technology that is possible in real conditions (already existing in alike benchmark
country) is applied in Latvia, hence Sweden is selected as the benchmark country.

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Table 1
Direct input coefficients of postal and courier economic activity (H53)
in the EU* countries in 2020
Country
A_B
C_E
F
G
H
I_U
IC
Taxes**
Value
added
Output
Croatia
0.00
0
0.01
5
0.00
0
0.00
6
0.09
9
0.02
4
0.14
5
0.000
0.855
1.000
Hungary
0.00
2
0.05
8
0.00
2
0.03
2
0.07
7
0.14
2
0.31
3
0.058
0.630
1.000
France
0.00
0
0.06
6
0.00
3
0.01
6
0.07
0
0.20
3
0.35
8
0.045
0.597
1.000
Ireland
0.00
0
0.03
9
0.00
0
0.01
5
0.16
9
0.13
7
0.41
1
0.022
0.567
1.000
Cyprus
0.00
0
0.08
6
0.00
6
0.02
9
0.10
6
0.20
4
0.43
1
0.028
0.541
1.000
Slovenia
0.00
1
0.03
4
0.00
4
0.01
9
0.27
5
0.10
5
0.43
8
0.039
0.523
1.000
Sweden***
**
0.00
0
0.02
8
0.00
8
0.03
3
0.17
2
0.23
6
0.47
7
0.011
0.512
1.000
Austria
0.00
0
0.02
0
0.01
5
0.00
8
0.40
9
0.09
8
0.55
1
0.010
0.439
1.000
Portugal
0.00
0
0.02
0
0.00
8
0.00
5
0.39
2
0.11
7
0.54
2
0.020
0.438
1.000
Lithuania
0.00
0
0.06
9
0.00
3
0.01
2
0.26
1
0.14
6
0.50
3
0.062
0.435
1.000
Czechia
0.00
5
0.05
4
0.01
2
0.02
3
0.30
9
0.13
2
0.53
5
0.033
0.432
1.000
Slovakia
0.00
1
0.03
7
0.00
5
0.01
1
0.42
7
0.09
2
0.57
4
0.008
0.418
1.000
Spain
0.00
0
0.03
1
0.00
7
0.00
6
0.39
6
0.12
4
0.56
5
0.018
0.417
1.000
Latvia
0.00
0
0.03
7
0.00
1
0.00
9
0.33
7
0.20
4
0.58
8
0.021
0.391
1.000
Germany
0.00
0
0.03
9
0.01
4
0.09
5
0.30
0
0.15
5
0.60
4
0.021
0.376
1.000
Italy
0.00
1
0.06
5
0.00
4
0.01
1
0.40
4
0.13
5
0.62
0
0.024
0.356
1.000
Estonia
0.00
1
0.04
4
0.00
8
0.03
0
0.42
8
0.14
5
0.65
7
0.006
0.337
1.000
* EU countries that publish input-output table set in product-by-product approach (in Eurostat)
** Taxes less subsidies on products (D21_D31)
***data on 2019
Source: the author’s calculations, on the basis of [13]
Results and discussion
The modelling results argue that if the postal and courier services in Latvia apply a greener
technology that already exists (possible, achievable technology, not just in theory), then the total value
added declines by -0.1% due to lower intermediate consumption for manufactured products. The greener
technology demands fewer manufactured products.
The findings claim that the largest positive impact is on services (as warehouse services,
employment services, wholesale trade services) (see Table 2), however, the services auxiliary to
financial services and insurance services, air transport services, paper and its products have the most
negative impact (see Table 3).
Table 2
Modelling results on the most positively affected economic activities
in the case of a greener last-mile delivery technology in Latvia
NACE economic activities
Change, in % (compared
to pre-scenario situation)
H52 Warehousing and support services for transportation
1.2%
N78 Employment services
0.9%
L68A Imputed rents of owner-occupied dwellings
0.5%
G45 Wholesale and retail trade of motor vehicles
0.5%
S95 Repair services
0.5%
K65 Insurance
0.4%
J62_J63 Computer programming, consultancy and related
services
0.4%
E36 Natural water; water treatment and supply services
0.4%

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Table 2 (continued)
NACE economic activities
Change, in % (compared
to pre-scenario situation)
M71 Architectural and engineering services
0.3%
N80-N82 Security and investigation services; etc. support
services
0.2%
Source: the author’s calculations
The most negative impact is detected in the same postal and courier services as the postal and
courier services consumes less the same services from other companies in this economic activity, also
less air transport is used, less land transport, but more warehouses, leading to more optimised solutions
in route planning.
Table 3
Modelling results on the most negatively affected economic activities in the case
of a greener last-mile delivery technology in Latvia
NACE economic activities
Change, in % (compared to
the pre-scenario situation)
H53 Postal and courier services
-20.5%
K66 Services auxiliary to financial services and insurance
services
-10.8%
H51 Air transport services
-5.3%
N77 Rental and leasing services
-1.5%
C17 Paper and paper products
-1.4%
N79 Travel agency, tour operator and other reservation services
-0.6%
C20 Chemicals and chemical products
-0.6%
C33 Repair and installation services of machinery and
equipment
-0.5%
C13-C15 Textiles, wearing apparel and leather products
-0.4%
H49 Land transport services
-0.3%
Source: the author’s calculations
The bottom-up approach is used, aggregating values of 64 into NACE 20 groups of economic
activity for further regional impact modelling, however, the absolute values computed compared to the
pre-scenario state result in growth rate per aggregated group (see Table 4). Many economic activities in
this level of disaggregation show no affect from the greener technology applied in last-mile delivery.
However, the companies in financial and insurance activities (K) and administrative and support service
activities must have in strategic plans activities to limit this negative impact by diversifying or other
strategies considered. Greener technologies results are more responsible attitude and actions concerning
waste, effective digital and ICT application and real estate services.
Table 4
Modelling results on aggregated impact in the case
of a greener last-mile delivery technology in Latvia
NACE aggregated groups
Change, in % (compared to
the pre-scenario situation)
A Agriculture, forestry and fishing
0.0%
B Mining and quarrying
0.0%
C Manufacturing
-0.1%
D Electricity, gas, steam and air conditioning supply
-0.1%
E Water supply, sewerage, waste management
0.2%
F Construction
0.0%
G Wholesale and retail trade, repair of motor vehicles
0.0%
H Transportation and storage
-0.3%
I Accommodation and food service activities
0.0%
J Information and communication
0.2%

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Table 4 (continued)
NACE aggregated groups
Change, in % (compared to
the pre-scenario situation)
K Financial and insurance activities
-2.1%
L Real estate activities
0.3%
M Professional, scientific and technical activities
0.0%
N Administrative and support service activities
-0.5%
O Public administration and defence, social security
0.0%
P Education
0.0%
Q Human health and social work activities
0.0%
R Arts, entertainment and recreation
0.0%
S Other service activities
0.1%
T Activities of households as employers
0.0%
TOTAL
-0.1%
Source: the author’s calculations
The modelled regional results claim that the major negative impact is in the metropolitan areas
(Riga region), medium – Kurzeme and Latgale, but the minimal impact – Vidzeme and Zemgale.
Table 5
Modelling results on regional impact in the case of a greener last-mile delivery technology
(change, in % (compared to pre-scenario situation)) in Latvia
Planning
regions
Latvia
Riga
planning
region
Vidzeme
planning
region
Kurzeme
planning
region
Zemgale
planning
region
Latgale
planning
region
TOTAL
-0.06%
-0.08%
-0.01%
-0.02%
-0.01%
-0.02%
Source: the author’s calculations
Regional development in multi-country studies in the EU mainly applies NUTS-2 level of
disaggregation (as [23] for 272 regions in the EU), the applied statistical regional disaggregation for
Latvia is closer to NUTS-3 level, as Latvia is one region in NUTS-2 level. The study on faster delivery
services in busy metropolitan areas if a specially-developed algorithm applied claims that the overall
cost savings to the carrier were estimated to be in the range 34-39% [24]; highlighting the potential for
improvements even in intensive areas that are believed to be used most intensively with minor
ineffectiveness compared to less intensive urban or even rural areas. The policymaking process is linked
to the territorial reform in Latvia and expected urban-rural cohesion [25].
A further study could assess the long-term effects of greener technologies as, definitely, demand
pattern changes over time, including last-mile services for households (B2C) (as private consumption)
and B2B solutions, and any hybrid or alternative form that might occur in future. The findings suggest
several courses of action for policymakers and have a number of practical implications. More frequently
updated input-output data set is required due to its importance for monitoring and proactive and on-time
policy measures elaboration for targeted and notable results towards the EU Green Deal targets; if only
available on every five years, then proactive actions are limited or suitable.
Conclusions
1. Greener technologies in transport result in lower demand for intermediate consumption for other
transport services (less air transport, less land transport), lower demand for manufactured items and
financial service. The companies operating in these economic activities can foresee the future
development and take steps to diversify the business or gradually switch to other.
2. Less land transport leads to larger demand for storage places and warehouses and hence an increased
demand is modelled.

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3. The modelled greener technologies lead to larger demand for repair services and insurance. Use the
same equipment, tools and vehicles longer.
4. The findings are valuable to the companies in the industries that might be affected due to the shift
towards other technologies and practices, as well as for the national government and EU institutions
in policymaking ensuring balanced economic development.
Acknowledgements
This research was funded by the Latvian Science Council’s fundamental and applied research
programme, project “Development of Model for Implementation of Sustainable and Environmentally
Friendly Last Mile Distribution Transportation Services in Latvia” (TRANS4ECO), project No. lzp-
2022/1-0306, 01.01.2023.- 31.12.2025.
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