d2.1: report on trends and key factors · d2.1: report on trends and key factors 5 automated guided...

Project ID: 768884

H2020-NMBP-CSA-2017 Mapping a path to future Supply Chains

Next generation Technologies for networked Europe

D2.1: Report on trends and key factors

Disclaimer:

The NEXT-NET project is co-funded by the European Commission under the Horizon 2020 Framework

Programme. This document reflects only authors’ views. EC is not liable for any use that may be done of the

information contained therein.

WP: WP2-Industrial future scenarios for SCs

Task: T2.1- Identification of trends and key factors

Partner responsible: Dimitra Kalaitzi and Aristides Matopoulos (Aston

University)

Contributors:

Rosanna Fornasiero, Andrea Zangiacomi and Irene

Marchiori (CNR-ITIA), Ana Cristina Barros, Kerley Pires,

Pedro Campos, Vasco Amorim (INESC TEC), Victoria

Muerza (ZLC), Saskia Sardesai, Denis Daus and

Markus Witthaut (Fraunhofer IML), Luk Aerts and

Sébastien Balech (PNO)

Status: Final

Date: 31/01/2017

Version: 1.0

Classification: Public

Ref. Ares(2018)596974 - 31/01/2018


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NEXT-NET Project Profile

Project ID: 768884; H2020-NMBP-CSA-2017

Acronym: NEXT-NET

Title: Next generation Technologies for networked Europe

URL: https://nextnetproject.eu/

Start Date: 01/10/2017

Duration: 24 Months


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Document History

Version Date Author (Partner) Remarks

0.1 6/11/2017 Aston University Version submitted to

consortium members

0.2 10/11/2017 CNR-ITIA, INESC

TEC, ZLC,

Fraunhofer IML, PNO

Version with

comments

0.3 22/11/2017 Aston University Version submitted to

consortium members

0.4 15/12/2017 Aston University Updated list of

megatrends and

trends submitted to

consortium members

0.5 3/01/2018 Aston University Updated version

submitted to

consortium members


TEC, ZLC,

Fraunhofer IML,

PNO

Version with

Comments

0.8 16/01/2018 Aston University Document submitted

for review

0.9 22/01/2018 PNO Internal review


TEC, ZLC,

Fraunhofer IML

Version with

comments

1.0 31/01/2018 Aston University Final document for

submission

Final 31/01/2018 CNR-ITIA Submitted


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Executive Summary

This report is the Deliverable 2.1 entitled “Report on trends and key factors” of the Next-net

project. The aim of the project is to put in place a cross-sectoral and cross-technological

initiative at European level to increase integration between production and distribution

proposing research and innovation priorities for the future of supply chain. The Deliverable 2.1

focuses on identifying and providing a comprehensive list of megatrends and associated

trends that address critical aspects of several domains of analysis (e.g. political).

The research design adopted follows two sequential phases of data collection namely

literature review and experts workshop. The methodological approach of the first phase is

guided by PESTLE (Political, Economic, Social, Technological, Legal and Environmental)

framework, which examines political, economic, social, technological, legal and environmental

megatrends and trends that can shape the landscape of the discrete manufacturing, process

manufacturing and the logistics industry. NVivo software was used for content analysis of the

collected reports and articles for recognising recurring themes, namely megatrends and their

associated trends. Regarding phase two, Aston University, with the support of all project

partners, organised and conducted a workshop with 18 experts on December 5, 2017 in

Birmingham, United Kingdom.

In the political dimension 3 megatrends emerged namely protectionism (4 trends: import

tariffs, quotas, different tax structures and subsidies), political stability (2 trends:

terrorism/conflict and social unrest), and supranationalism (2 trends: trade agreements and

free movement). There also 3 megatrends under the economic dimension: global trade

shift (6 trends: economic growth in emerging economies, export growth, investment,

globalisation, glocalisation and emergence of born-global firms), digital economy (2 trends:

sharing economy and from an economy of goods to an economy of services) and financial

innovation (3 trends: digital currencies, cashless payment and the financial technologies

(Fintech) revolution). Regarding the social dimension, 7 megatrends emerged namely

population growth (2 trends: population boom in the developing countries and growing

demand of resources), demographic change (4 trends: ageing population boom in developing

countries, young population boom in developing countries, migration flows and labour

shortages), urbanisation (2 trends: megacities and smart cities), change in consumption

pattern (3 trends: middle-class explosion, healthy diets and lifestyles and consumerism),

individualism (3 trends: new customer relationship, new shopping experience and increase

customisation), digital natives (3 trends: change of communication patterns, change of

purchasing patterns and reshaping the workplace) and knowledge based economy (3 trends:

increase demand for high-qualification jobs, emerging skills required and continuous learning

culture).

In the technological dimension there are 4 megatrends: digital transformation (5 trends:

big data analytics, artificial intelligence, cloud based computer systems, blockchain, Internet

of Things), technology development and automatization (8 trends: robots, augmented reality

and virtual reality, 3D printing/additive manufacturing, drones. autonomous systems,


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automated guided vehicles, wearable devices and cyber-physical system, transport

electrification (3 trends: battery electric vehicles, hydrogen fuel cell electric vehicles, hybrid

vehicles) and renewable energy sources (2 trends: production and storage of clean energy

and application to transportation and industry and renewable energy for industrial processes).

Concerning the legal dimension, consumer protection laws (4 trends: cross-border

payments, return products free of charge or under warranty, product safety regulations and

privacy), intellectual property law (2 trends: patents and data sovereignty) and social and

environmental regulations (3 trends: corporate social responsibility, emissions control

regulations and waste and resources management regulations) are the 3 megatrends that

emerged from the data and the workshop. Last but not least, 2 megatrends emerged under

the environmental dimension namely climate change (1 trend: pollution) and resource

scarcity (2 trends: lack of resources and waste increase). These megatrends and trends will

provide a robust set for generating the scenarios in Task 2.2.


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Table of Contents

1 Introduction ...................................................................................... 13

2 Methodology ..................................................................................... 15

3 PESTLE analysis .............................................................................. 18

Overview .................................................................................................... 18

Political ....................................................................................................... 21

3.2.1 Protectionism ................................................................................... 21

3.2.2 Political stability ................................................................................ 24

3.2.3 Supranationalism ............................................................................. 27

Economic ................................................................................................... 29

3.3.1 Global trade shift .............................................................................. 29

3.3.2 Digital economy................................................................................ 34

3.3.3 Financial Innovation ......................................................................... 37

Social .......................................................................................................... 42

3.4.1 Population growth ............................................................................ 45

3.4.2 Demographic change ....................................................................... 47

3.4.3 Urbanisation ..................................................................................... 50

3.4.4 Change in consumption pattern ........................................................ 55

3.4.5 Individualism .................................................................................... 60

3.4.6 Digital natives ................................................................................... 64

3.4.7 Knowledge based economy ............................................................. 65

Technological ............................................................................................ 67

3.5.1 Digital Transformation ...................................................................... 68

3.5.2 Technology development and automatisation .................................. 75

3.5.3 Transport electrification .................................................................... 86

3.5.4 Renewable energy sources .............................................................. 88

Legal ........................................................................................................... 91

3.6.1 Consumer protection laws ................................................................ 92

3.6.2 Intellectual property law .................................................................... 93

3.6.3 Social and Environmental regulations .............................................. 98

Environmental .......................................................................................... 101

3.7.1 Climate change .............................................................................. 102


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3.7.2 Resource scarcity ........................................................................... 109

4 Conclusion .................................................................................... 123

References ............................................................................................. 125

Annex A: List of Acronyms ............................................................... 148


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List of Figures

Figure 1-1: Impact and time horizon of megatrends ............................................................................ 13

Figure 1-2: Examples of megatrends and trends ................................................................................. 13

Figure 3-1: Geographical breakdown of trade and investment barriers, 2016 (* - G20 countries) ...... 22

Figure 3-2: Simple Average Price of the Most Sold Brand, Excise Tax per pack ................................ 23

Figure 3-3: Tax structure by country [53] .............................................................................................. 23

Figure 3-4: Pre-tax subsidies and post-tax energy subsidies ............................................................... 24

Figure 3-5: Global political violence score vs year .............................................................................. 25

Figure 3-6: Number of terrorist attacks in 2016 ................................................................................... 26

Figure 3-7: Social unrest ...................................................................................................................... 26

Figure 3-8: Unemployment, vulnerable employment and working poverty trends ............................... 27

Figure 3-9: Global exports and trade agreements ............................................................................... 27

Figure 3-10: Free movement and migration ......................................................................................... 28

Figure 3-11: Free movement and migration ......................................................................................... 28

Figure 3-12: Projected GDP growth by region ..................................................................................... 30

Figure 3-13: Global trade patterns ....................................................................................................... 31

Figure 3-14: The growth gap ................................................................................................................ 31

Figure 3-15: Contributions to world trade volume growth by region, 2011-2016 ................................. 32

Figure 3-16: Growth in world trade volume (good and services) ......................................................... 32

Figure 3-17: Inward and outward foreign direct investment stocks of the EU relative to the rest of the world as a percentage of GDP, EU-28, 2008-2015 ............................................................................. 33

Figure 3-18: Glocalisation .................................................................................................................... 33

Figure 3-19: Number of born global firms ............................................................................................ 34

Figure 3-20: Sharing economy revenues in Europe ............................................................................. 35

Figure 3-21: Sharing economy in five sectors in Europe ..................................................................... 35

Figure 3-22: Sharing economy in Europe ............................................................................................ 36

Figure 3-23: A Stream Runs Through It ................................................................................................ 37

Figure 3-24: Usage of cryptocurrencies in the past 12 months .......................................................... 38

Figure 3-25: Potential impact of digital currency on the financial services industry and other areas . 38

Figure 3-26: Blockchain and cryptocurrency open the door to other revolutionary possibilities ......... 39

Figure 3-27: Non-cash transactions worldwide (billion) 2010–14 ........................................................ 39

Figure 3-28: Digital growth journey ...................................................................................................... 40

Figure 3-29: Number of FinTech tripled ............................................................................................... 40

Figure 3-30: Challenges for FinTech companies and incumbents .................................................... 41

Figure 3-31: FinTech and disruptive entities ....................................................................................... 42

Figure 3-32: Trends in FS ranked by importance and likelihood to respond ...................................... 42

Figure 3-33: Population of the world .................................................................................................... 45

Figure 3-34: World population by major area, 2010-2100 ................................................................... 46

Figure 3-35: Area of arable land per person ........................................................................................ 46

Figure 3-36: Annual growth in consumption for key commodity groups, 2007–16 and 2017–26 ........ 47

Figure 3-37: Population aging patterns ................................................................................................ 48

Figure 3-38: Population aging patterns by region ................................................................................ 48

Figure 3-39: Selected net migration 2000-2015 vs. 2015-2030 [m] .................................................... 49

Figure 3-40: Development of international migrants and refugees [m] ................................................ 49

Figure 3-41: Projected change in working age population from 2015 till 2030 .................................... 50


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Figure 3-42: Labour shortages ............................................................................................................. 50

Figure 3-43: Urban and rural populations’ projections ......................................................................... 51

Figure 3-44: Urbanisations rates by region .......................................................................................... 51

Figure 3-45: The world's top megacities and their population growth ................................................. 52

Figure 3-46: An ideal smart city strategy ............................................................................................. 52

Figure 3-47: Infographic cities at a tipping point .................................................................................. 53

Figure 3-48: Global market size for smart city solutions [USD billion] .................................................. 54

Figure 3-49: Smart City Market by Segments 2025 .............................................................................. 54

Figure 3-50: Middle class by region ..................................................................................................... 56

Figure 3-51: Middle class by region ..................................................................................................... 56

Figure 3-52: Change in eating habits since last year, by age .............................................................. 57

Figure 3-53: Global functional foods market revenue by region, 2014 - 2024 (USD Million) .............. 57

Figure 3-54: Global functional foods market revenue by product, 2015 & 2024 (USD Billion) ............ 58

Figure 3-55: U.S. healthy food market revenue, by product type, 2014 - 2025, (USD Million) ........... 58

Figure 3-56: Consumption growth ........................................................................................................ 59

Figure 3-57: Household expenditure by consumption purpose - COICOP, EU-28, 2015, share of total .............................................................................................................................................................. 59

Figure 3-58: Caloric intake per capita in least developed, other developing and developed countries .............................................................................................................................................................. 60

Figure 3-59: The percentage of global consumers who shop in-store at least once a week .............. 61

Figure 3-60: the gap between what is important to consumers in-store, versus their satisfaction levels .............................................................................................................................................................. 61

Figure 3-61: Total worldwide e-commerce sales ................................................................................. 62

Figure 3-62: percentage of customers who purchased from an overseas retailer .............................. 62

Figure 3-63: Online purchases ............................................................................................................. 63

Figure 3-64: Global practices for payments ......................................................................................... 63

Figure 3-65: Social media influence ..................................................................................................... 65

Figure 3-66: Skills supply and demand in Europe ............................................................................... 66

Figure 3-67: Employment developments patterns by occupational category in EU ............................ 66

Figure 3-68: Percentage of enterprises analysing big data from any data source .............................. 69

Figure 3-69: Top 5 big data analytics industries .................................................................................. 69

Figure 3-70: Artificial intelligence revenue ........................................................................................... 70

Figure 3-71: Top 10 use cases ............................................................................................................ 71

Figure 3-72: Percentage of enterprises which buy cloud computing services used over the internet, 2016 ..................................................................................................................................................... 72

Figure 3-73: Blockchain functionality ................................................................................................... 73

Figure 3-74: Overview of Use Case Exemplars ................................................................................... 73

Figure 3-75: IoT growth ........................................................................................................................ 74

Figure 3-76: Device shipments by sector ............................................................................................. 74

Figure 3-77: IoT market by 2020 .......................................................................................................... 75

Figure 3-78: Global robot market ......................................................................................................... 75

Figure 3-79: Three main components of cyber-physical system ......................................................... 76

Figure 3-80: Network of smart embedded devices .............................................................................. 77

Figure 3-81: Global AR Revenues 2012 to 2017 by market segment ................................................. 77

Figure 3-82: Virtual reality revenues by market segment .................................................................... 78

Figure 3-83: Worldwide 3d printing industry (billions) .......................................................................... 78

Figure 3-84: 3D printing usage ............................................................................................................ 79


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Figure 3-85: Global drone market ........................................................................................................ 80

Figure 3-86: Drone services market ..................................................................................................... 80

Figure 3-87: New vehicles market ....................................................................................................... 81

Figure 3-88: Sales of AVs .................................................................................................................... 82

Figure 3-89: Total Sales by Volume of Units ...................................................................................... 82

Figure 3-90: Unmanned autonomous vessels ..................................................................................... 83

Figure 3-91: Wearable devices market ................................................................................................ 84

Figure 3-92: Smart Clothing and Body Sensor Unit Shipments, World Markets: 2013-2020 .............. 84

Figure 3-93: Smart Clothing and Body Sensor Device Revenue, World Markets: 2013-2020 ............ 84

Figure 3-94: Wearable devices and data sharing ................................................................................ 85

Figure 3-95: Wearable technology and social media ........................................................................... 85

Figure 3-96: Premium light vehicle sales by propulsion system design and fuel type, 2016–26 ........ 86

Figure 3-97: Alternative powertrains in EU cities ................................................................................. 87

Figure 3-98: Final energy consumption, 2013 and 2050 ..................................................................... 89

Figure 3-99: Storage: Technology overview ........................................................................................ 90

Figure 3-100: Total hydrogen use, 2015 estimate ............................................................................... 90

Figure 3-101: Total Data exchange between companies as an essential feature of digitisation ......... 94

Figure 3-102: Data exchange currently carried out by companies with other companies or institutions .............................................................................................................................................................. 94

Figure 3-103: 10 types of company currently involved in data exchange ............................................ 95

Figure 3-104: Regularity of data exchange with other companies according to company size ........... 95

Figure 3-105: Opportunities provided by the present possibilities for cross-company data exchange 96

Figure 3-106: Obstacles which mean companies do not approve of data exchange ........................... 97

Figure 3-107: Growth in reporting since 1993 ...................................................................................... 99

Figure 3-108: % of companies with CR reports .................................................................................... 99

Figure 3-109: Growth in independent assurance of CR information ................................................... 99

Figure 3-110: Reporting carbon emissions ........................................................................................ 100

Figure 3-111: Global e-waste management market .......................................................................... 101

Figure 3-112: Natural disasters in EEA member countries ................................................................ 103

Figure 3-113: Air, water, soil pollutions .............................................................................................. 103

Figure 3-114: Carbon dioxide emissions from fossil-fuel use and industry ........................................ 104

Figure 3-115: Global CO2 emissions, 2000-2017 ............................................................................. 104

Figure 3-116: Greenhouse gas emissions per capita, by country, 2005 and 2015 ............................ 105

Figure 3-117: Greenhouse gas emissions and projections, 1990–2050 ........................................... 105

Figure 3-118: % of samples with concentrations above the threshold value in all the LUCAS samples ............................................................................................................................................................ 106

Figure 3-119: Change in global mean sea level ................................................................................ 107

Figure 3-120: Global average temperature change .......................................................................... 108

Figure 3-121: Projections of extreme high temperatures ................................................................. 108

Figure 3-122: Projected change in minimum river flow .................................................................... 109

Figure 3-123: Projected growth in global water consumption by sector ............................................ 110

Figure 3-124: Water consumption patterns by sector and regions .................................................... 110

Figure 3-125: Worldwide evolution of land use .................................................................................. 111

Figure 3-126: Evolution of per capita food consumption (kcal/person/day) ....................................... 111

Figure 3-127: Food price development and its relation to water and climate change ....................... 111

Figure 3-128: EU food waste per year (tonnes) ................................................................................ 112

Figure 3-129: Waste per person by food type .................................................................................... 112


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Figure 3-130: Energy demand by sector ............................................................................................ 113

Figure 3-131: Global transportation demand ..................................................................................... 113

Figure 3-132: Global Commercial transportation demand by different modes of transportation ........ 114

Figure 3-133: Energy demand by region ........................................................................................... 114

Figure 3-134: Crude oil price projection ............................................................................................. 115

Figure 3-135: World energy consumption by energy source ............................................................. 115

Figure 3-136: Global demand for REO from clean technologies ....................................................... 116

Figure 3-137: The distribution of global rare earth resources by principle deposit type and country 116

Figure 3-138: First 10 European countries for generation of waste in 2014 (tons) ........................... 117

Figure 3-139: kilograms per capita of waste generated by the first 10 European countries ............. 117

Figure 3-140: Municipal Waste Treatment, EU-27 (kg per capita) ) ................................................... 117

Figure 3-141: Waste generation projection for 2025 by region, 2012 ............................................... 118

Figure 3-142: Waste Collection Rates by Region, 2012 .................................................................... 119

Figure 3-143: Recycling rate of all waste excluding major mineral waste ......................................... 120

Figure 3-144: Global WEEE generated and estimated ...................................................................... 121

Figure 3-145: WEEE collected in Europe (EU28) .............................................................................. 121

Figure 3-146: First 10 countries per total WEEE ............................................................................... 122

Figure 3-147: WEEE by categories in the first 10 countries ............................................................... 122

Figure 4-1: Megatrends and trends ..................................................................................................... 123


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List of Tables

Table 2-1: PESTLE dimensions definition ............................................................................................ 16

Table 2-2: Data structure of the political dimension .............................................................................. 17

Table 3-1: Megatrends and trends identified ........................................................................................ 18

Table 3-2: Megatrends and trends in the political dimension ............................................................... 21

Table 3-3: Megatrends and trends in the economic dimension ............................................................ 29

Table 3-4: Megatrends and trends in the social dimension .................................................................. 43

Table 3-5: Megatrends and trends in the technological dimension ...................................................... 67

Table 3-6: Megatrends and trends in the legal dimension .................................................................... 91

Table 3-7: Megatrends and trends in the environmental dimension ................................................... 101

Table 3-8: Rate of waste collected by region, 2012 [355] ................................................................. 119


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1 Introduction

Work package 2 (WP2) aims to develop and assess future industry specific supply chain

scenarios, which are shaped by various socio-economic, political and technological

megatrends. This deliverable for task 2.1 has the objective to identify the key factors and their

associated trends. Key factors1 or megatrends (non-sector specific) drive trends and due to

their slow but continual progress possible future scenarios and hypotheses could be derived

about how specific industries might evolve [1]. From now on in this report instead of the word

“key factors” we will adopt the use of the word “megatrends”. Megatrends are “large, social,

economic, political, environmental or technological changes that are slow to form”.

Megatrends are especially useful for developing forecasts about the future of the discrete

manufacturing, process manufacturing and the logistics industry [2]. Megatrends are observed

over decades (see Figure 1-1), affect almost all world regions and have a profound impact on

business, economy, society, cultures and personal lives (Figure 1-2).

Figure 1-1: Impact and time horizon of megatrends [3]

Figure 1-2: Examples of megatrends and trends [4]

1 Factor is “a fact or situation that influences the result of something” [7].


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Trend can be defined as the general direction in which something is going to move, develop

or change ([5], [6]). For example, the megatrend aging population will have implications on the

workforce and a trend can be “workforce gaps”. Until now there is no comprehensive study

with the list of megatrends and associated trends that address critical aspects of several

domains of analysis such as economic, legal taking into account the manufacturing

processing, distribution and logistics sectors. This report describes the work involved in and

findings from task 2.1. This task establishes the theoretical basis for understanding the

megatrends and trends by reviewing existing information namely 349 reports, journal papers

and studies. Our approach in this task draws on the PESTLE analysis to enable us to capture

a wide range of direct trends (e.g. for sectors under investigation) and indirect trends (e.g.

changes at the consumer level, buying patterns). All megatrends and trends provide a basis

for T2.2 future scenarios generation. Thus, these findings will provide the basis for the

scenario generation which make T2.1 report one of the most important deliverable of the

project. The next section presents the methodology that applied and section 3 presents the

findings. The last section presents the summary of the findings and future research.


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2 Methodology

This research is based on two complementary phases that have been held during the initial

part of the project:

Systematic literature review

Workshop with experts

During the first phase, megatrends and trends were identified by reviewing existing information

with a focus on recent publications and grey literature2. The relevant papers were found by

searching online major scientific databases Science Direct, Emerald and Google Scholar. The

following keywords and phrases were used to identify the relevant papers for review:

• (logistics) OR (supply chain management) OR (manufacturing) OR (process

manufacturing) OR (distribution) OR (transportation) AND (trends or megatrends)

• (future supply chain) OR (next generation supply chains) AND (trends or megatrends)

• (protectionism) OR (political stability) OR (supranationalism) AND (trends or

megatrends)

• (global trade shift) OR (sharing economy) OR (financial Innovation) AND (trends or

megatrends)

• (population growth) OR (demographic change) OR (urbanisation) OR (change in

consumption pattern) OR (individualism) OR (digital natives) OR (knowledge based

economy) AND (trends or megatrends)

• (big data analytics) OR (artificial intelligence) OR (cloud based computer systems)

OR (blockchain) OR (Internet of Things) AND (trends or megatrends)

• (robots) OR (augmented reality and virtual reality) OR (3D printing) OR (drones) OR

(automated vehicles) OR (wearable devices) OR (cyber-physical system) AND (trends

or megatrends)

• (consumer protection laws) OR (intellectual property law) OR (environmental

regulations) AND (trends or megatrends)

• (climate change) OR (resource scarcity) AND (trends or megatrends)

Overall, 349 reports, grey literature and papers were selected and analysed. PESTLE analysis

analysis is used to identify and characterise different megatrends and trends. PESTLE

analysis is an evolution of the STEEP (Social, Technological, Economical, Environmental and

Political) analysis since it allows to take into account also the legal dimension. Based on the

2 Grey literature is produced on all levels of government, academics, business and industry

in print and electronic formats, but it is not controlled by commercial publishers [8].


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dimensions changes will be identified and the potential and direction of future activities will be

defined [9]. The explanation of each dimension is given in the Table 2-1 below.

Table 2-1: PESTLE dimensions definition

Dimension Description

Political The political dimension includes megatrends/trends such as

government policy (e.g. tax policy, foreign trade, copyright and

property law enforcement, environmental regulations, competition

regulation), political stability or instability in domestic and overseas

markets.

Economic The economic dimension includes megatrends/trends such as inflation

rate, taxation, interest rates, foreign exchange rates, economic growth

patterns etc. influencing the demand, supply of the product or service.

Social The social dimension contains social megatrends/trends such as

cultural trends, demographics, and population analytics.

Technological The technological dimension incorporates the current state and

developments in technology (e.g. government spending on

technological research, adoption rates of new technologies and the

impact of potential information technology changes) that may affect the

operations of the industry and the market favourably or unfavourably.

Legal Legal megatrends/trends contain antitrust law, health and safety, equal

opportunities, advertising standards, consumer rights and laws,

product labelling and product safety.

Environmental Environmental megatrends/trends take into account climate, weather,

and carbon footprint, impact of using specific raw materials, natural

resource scarcity, and geographical location (e.g. environmental

regulation, pollution concern and disaster quotient).

Data were analysed by using the NVivo software that helps to draw out themes emerged from

the data. Thematic analysis was adopted. The analysis began by using ‘open coding’ to collect

trends from the chosen sources in order to create the first-order themes. According to Collis

and Hussey [10] “The codes are labels which enable the qualitative data to be separated,

compiled and organised”. The second step consisted of integrating/ connecting first-order

themes and creating second-order themes which are the megatrends by axial coding (i.e.

more abstract coding of data into theoretical categories). The final step enabled us to link the

various concepts that emerged from the data by choosing the aggregate dimension (i.e.

PESTLE dimensions) to be the core category and relating all other second-order themes to

that category. For example, in the political dimension (see table 2-2) as an aggregate


17

dimension we have identified two second-order themes namely protectionism (first-order

themes: import tariffs, quotas, different tax structures) and political stability

(terrorism/conflicts). Each sub-section of the section 3 is organised with the description of the

trends (i.e. some examples of trends based on literature or statistics from international and

national statistical sources such as the Eurostat database). Some megatrends/trends were

easy to measure by using the variable of interest (e.g. the megatrend population growth),

whereas we used some proxy variables when that variable of interest could not be measured

directly. The criteria that applied to choose the proxy variables were the following: 1) the

variables must have a close correlation with the variable of interest, 2) the variables have been

frequently used from other studies and 3) there are available data/references for the proxy

variable which are recent. Although other variables could be used due to time constraints we

focus on a few variables that meet these constraints.

Table 2-2: Data structure of the political dimension

Second-order themes First-order themes Aggregate dimension

Megatrends Trends Dimension

Protectionism Import tariffs Political

Quotas

Different tax structures

Political Stability Terrorism/conflicts

Social unrest

In the second phase a workshop was held at Aston University (Birmingham, United Kingdom)

on Tuesday 5th December 2018. A mind mapping software was used to facilitate group

discussion and incorporate expert ideas into a visual image. The workshop brought together

experts from both the academic and practitioner domains to discuss, refine, and extend the

findings and insights gained from the literature review. Whilst there was an opportunity to

conduct a Delphi research, at the end it was decided that the experts workshop was more

appropriate for the following reasons: 1) maximise the compilation of information thus lead to

richness of information, 2) active participation by experts, 3) cost-effective and time efficient

method since it gathered all experts at the same time and location.


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3 PESTLE analysis

Overview

In this report 22 megatrends and 66 trends are identified (see table 3-1) through the literature

review and the workshop, which are discussed in the following sub-sections.

Table 3-1: Megatrends and trends identified

Dimensions Megatrends Trends

Political Protectionism Import tariffs

Quotas

Different tax structures

Subsidies

Political stability Terrorism/conflict

Social unrest

Supranationalism Trade agreements

Free movement

Economic Global trade shift Economic growth in emerging economies

Export growth

Investment

Globalisation

Glocalisation3

Emergence of born-global firms

Digital economy Sharing economy

From an economy of goods to an economy of

services

Financial Innovation Digital currencies

Cashless payment

The financial technologies (Fintech) revolution

Social Population growth Population boom in the developing countries

3 Glocalisation involves marketing of services and products to local markets Errore.

L'origine riferimento non è stata trovata..


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Growing demand of resources (e.g. land)

Demographic

change

Ageing population boom in developing countries

Young population boom in developing countries

Migration flows

Labour shortages

Urbanisation Megacities

Smart cities

Change in

consumption pattern

Middle-class explosion

Healthy diets and lifestyles

Consumerism

Individualism New customer relationship

New shopping experience

Increase customisation

Digital natives Change of communication patterns

Change of purchasing patterns

Reshaping the workplace

Knowledge based

economy

Increase demand for high-qualification jobs

Emerging skills required

Continuous learning culture

Technological Digital

transformation

Big data analytics

Artificial intelligence

Cloud based computer systems

Blockchain

Internet of Things

Technology

development and

automatisation

Robots

Cyber-physical system

Augmented reality and virtual reality

3D printing/additive manufacturing

Drones


20

Autonomous systems

Automated guided vehicles

Wearable devices

Electrification of

transport

Battery electric vehicles

Hydrogen fuel cell electric vehicles

Hybrid vehicles

Renewable energy

sources

Production and storage of clean energy and

application to transportation and industry

Renewable energy for industrial processes

Legal Consumer

protection laws

Cross-border payments

Return products free of charge or under warranty

Product safety regulations

Privacy

Intellectual property

law

Patents

Data sovereignty

Social and

environmental

regulations

Corporate social responsibility

Emissions control regulations

Waste and resources management regulations

Environmental Climate change Pollution

Resource scarcity

Lack of resources such as water, land, energy,

food and rare earth elements

Waste increase


21

Political

Three megatrends emerged under the political dimension namely protectionism, political

stability and supranationalism. Table 3-2 provides the megatrends with the respective

definition, references, and list of trends.

Table 3-2: Megatrends and trends in the political dimension

Megatrends Megatrends definition Megatrends

References

Trends

Protectionism Protectionism is a policy of

protecting domestic industries

against foreign competition and

entails several trade policies

such as tariffs, import quotas, or

other restrictions on the imports

of foreign competitors [11].

[12];[13];[14];

[15];[16];[17]

[18];[19];[20];

[21];[22];[23];

[24];[25];[26];

[27]

Import tariffs

Quotas

Different tax

structures

Subsidies

Political stability Political stability means

government stability, which is in

contrast with political instability

that include terrorism/conflicts

such as wars, government

crises and the social unrest

such as anti-government

demonstrations, riots, strikes

[28].

[12]; [27];

[29];[30];

[31];[32];[33];

[34];[35];[36];

[38]

Terrorism/conflict

Social unrest

Supranationalism Supranationalism is an

approach to international

integration under which national

governments cede sovereignty

over certain matters to

transnational institutions [39].

[40];[42];[43];

[44]

Trade agreements

Free movement

3.2.1 Protectionism

Protectionism is one of the megatrends that emerged under the political dimension and its

trends are import tariffs, quotas, different tax structures and subsidies.

The most common barrier to trade is a tariff, a tax on imports. Import tariffs (or taxes) are

imposed on imported goods and usually vary according to the type of goods imported. For


22

example, for cars the EU duty on imports from the US is 10% and the US duty on imports from

the EU is only 2.5% [45]. China's tariff on imported cars is 25% of the wholesale price, which

lead automotive companies to set up factories in China. Exporters in Europe reported a 10 %

growth in the number of trade barriers [42]. 36 new trade and investment barriers were put in

place (see Figure 3-1). Russia, Brazil, China and India have implemented the highest number

of new trade barriers [42]. According to BVL [12] Western companies have been vertically

integrated with domestic companies from Brazil, Russia, India, China and South Africa (BRIC)

to have access to their distribution networks. Regarding the logistics industry, there are many

restrictions (e.g. in Brazil), so it is difficult for a transportation company to operate there with

huge regulatory issues.

Figure 3-1: Geographical breakdown of trade and investment barriers, 2016 (* - G20 countries) [42]

Brexit and Trump's election seem to create “a new and less certain context to logistics and the

outcome of the negotiations will profoundly affect operations, planning and policy” [32]. For

example, increasing geographic, political and price barriers to shipping in different parts of the

world and U.S.; manufacturing companies with plants in Mexico and China may face huge

issues under the weight of increased import duties and tariffs [35]. Regarding Brexit, 32% of

the UK companies will substitute their EU suppliers with British suppliers and 46% of European

businesses will not use many UK suppliers [47]. The European Union (EU) also set duties to

protect its members, for example, on hot-rolled steel from countries such as Brazil, Iran, and

Russia after a complaint by EU manufacturers that the product was sold at excessively low

prices. The EU has also imposed import duties of up to 28.5% on certain Chinese corrosion-

resistant steels [48].

Another important trend is the on-going use of quotas in international trade. Quota is a trade

restriction that sets a limit on the quantity of a good/service that can be imported into a country

during a particular period of time [49]. For example, the Chinese government recognised rare

earths as a strategic mineral and foreign firms are banned from all mining activities, unless


23

foreign companies form a joint venture with a Chinese company. The quotas that have been

enforced by the Chinese governments from 2005 onwards. Quotas were reduced from about

65,000 tons per annum in 2005 to about 30,000 tons per annum in 2010. Quotas remained

steady in 2013 [50]. China ended its export quotas of rare-earth and until October 2015, China

had exported 26,800 tons of rare-earth materials.

There are different tax structures in different countries that consist of direct or indirect taxes.

“Country’s tax structure indicates relative distribution of taxes into different tax types and

over taxation bases” [51]. The total tax share in consumers’ prices are different across

countries grouped by income and regions. For example, the highest average price per pack

of cigarettes in $ declines by income group (Figure 3-2). In Figure 3-3 the tax structures of 17

countries are presented. For example, in Bangladesh, tiers are based on retail prices and in

India tiers are based on cigarette length [53].

Figure 3-2: Simple Average Price of the Most Sold Brand, Excise Tax per pack [52]

Figure 3-3: Tax structure by country [53]


24

Subsidies offered by governments (e.g. cheap loans) are given to local firms that cannot

compete well against foreign imports [54]. For example, the EU provides more than €112

billion a year in fossil fuel subsidies, mainly towards the transport sector [55]. Fossil-fuel

consumption subsidies worldwide amounted to $409 billion in 2010, and the cost of fossil-fuel

subsidies will reach $660 billion in 2020, or 0.7% of global GDP [57]. Post-tax energy

subsidies were estimated at $4.9 trillion in 2013, increasing in 2015 to $ 5.3 trillion in 2015

(see Figure 3-4).

Figure 3-4: Pre-tax subsidies and post-tax energy subsidies [58]

3.2.2 Political stability

Political stability is one of the megatrends that emerged under the political dimension and its

trends are terrorism/conflict and social unrest.

There is a growth in political violence risks worldwide (see Figure 3-5). In fact, 126 countries

were exposed to civil unrest risk, 87 countries to terrorism and sabotage, and 70 to war in

2017 [59].


25

Figure 3-5: Global political violence score vs year [59]

Terrorism/conflict can be defined as “the unlawful use of violence and intimidation,

especially against civilians, in the pursuit of political aims” [60]. It can cause instability and

lead to more security regulations especially at borders. After 9/11/2001 terrorist attack,

companies have faced unexpected disruptions in global supply chains, for instance, Ford had

to shut down five of its U.S. plants as there were not enough parts from suppliers in Canada.

This caused a 13 % drop in their production rates in that quarter [61]. Several countries have

reacted by means of regulations or trade agreements such as the Customs-Trade Partnership

against Terrorism (C-TPAT) program, which is a voluntary initiative designed by U.S. Customs

and Border Protection (CBP). This initiative enables certified C-TPAT partners to reduce the

number of inspections and border wait times [62].

The total number of terrorist attacks in 2016 decreased by 9% and total deaths due to terrorist

attacks decreased by 13%, compared to 2015. In addition, 142 (failed, foiled and completed)

attacks were reported by eight EU Member States (i.e. United Kingdom, France, Italy, Spain,

Greece, Germany, Belgium and the Netherlands) in 2016 [63]. The highest number of such

incidents in Europe occurred in the United Kingdom with 76 terrorist attacks in 2016 (see

Figure 3-6).

.


26

Figure 3-6: Number of terrorist attacks in 2016 [64]

The risk of social unrest is high across almost all regions in the world (see Figure 3-7). There

are only three regions that faced a decline in the index between 2015 and 2016, most notably

Northern Africa while eight regions experienced increases (e.g. Arab States, sub-Saharan

Africa and Eastern Asia). Labour issues such as labour dispute can affect the manufacturing

and logistics industry. For example, in the USA, “labor issues at West Coast container ports

disrupted service in 2015, drove volumes to other ports, and altered seasonal patterns” [65].

According to PwC [34] “the number of recorded cases of counterfeit, stolen or illegally diverted

medicines has already soared nearly nine-fold since 2002”.

Figure 3-7: Social unrest [68]


27

According to ILO [68] social unrest is projected to grow in Europe due to steep welfare cuts

and high unemployment. Global unemployment will increase to 5.8 % in 2018 compared with

2016 due to deteriorating labour market conditions in emerging countries (see Figure 3-8).

Unemployment rates will decrease in developed countries in 2018 [68]. The total number of

workers in vulnerable employment is estimated to increase by 11 million per year. These may

lead to more social unrest as these workers have less access to social dialogue and are less

likely to exhibit job security. Working poverty rates have continued to decrease. In 2016, there

were a total of 783 million working poor which is expected to increase by close to 3 million per

year in developing countries until 2018 [68].

Figure 3-8: Unemployment, vulnerable employment and working poverty trends [68]

3.2.3 Supranationalism

The last megatrend emerged under the political dimension is supranationalism and its trends

are trade agreements and free movement.

There are approximately 420 regional trade agreements but not all of them are free trade

agreements [40] (see Figure 3-9).

Figure 3-9: Global exports and trade agreements [40]


28

The OECD [41] defines a free trade area as a group of “countries within which tariffs and non-

tariff trade barriers between the members are generally abolished but with no common trade

policy toward non-members”. For example, EU Member States act as a single economic area

that promotes the free movement of goods, services, capital and people by removing tariffs

and quotas and ‘non-tariff barriers’. EU has developed trade agreements with non-EU

countries such as Canada, Japan, Ukraine, and Serbia. 90% of global consumer demand

growth will be outside Europe over the next 15 years, thus EU countries have to negotiate with

these countries.

For what concerns free movement, European internal mobility remained modest. Europeans

mainly move permanently in another Member State to find work. Most mobile workers (see

Figure 3-10) in the Union (58%) come from Central and Eastern Europe while Germany and

the UK are the two main destination countries [69]. Free movement of capital, goods and

services is also important (see Figure 3-11).

Figure 3-10: Free movement and migration [43]

Figure 3-11: Free movement and migration [44]


29

Economic

Three megatrends emerged under the economic dimension namely global trade shift, digital

economy, and financial Innovation. Table 3-3 provides the megatrends with the respective

definition, references, and list of trends.

Table 3-3: Megatrends and trends in the economic dimension


References

Trends

Global trade

shift

Global trade shift

incorporates the shift in trade,

export growth and GDP

growth from advanced

economies towards emerging

market economies.

[1];[12];[13];[16];

[20];[21];[22];[25];

[26];[27];[29];[31];

[34];[36];[37];[38];

[65];[70];[71];[72];

[73];[74];[75];[76];

[77];[78];[79];[80];

[81];[82]; [83]; [84];

[85];[86]; [87]; [88];

[89];[90];[91]

Economic growth in

emerging economies

Export growth

Investment

Globalisation

Glocalisation

Emergence of born-

global firms

Digital

economy

Digital economy is the

economic activity that results

from billions of everyday

online connections among

people, businesses, devices,

data, and processes [93].

[74];[92] Sharing economy

From an economy of

goods to an economy

of services

Financial

Innovation

Advances over time in the

financial instruments and

payment systems used in the

lending and borrowing of

funds [94].

[94];[96];[97] Digital currencies

Cashless payment

The financial

technologies (Fintech)

revolution

3.3.1 Global trade shift

Global trade shift is one of the megatrends that emerged under the economic dimension and

its trends are economic growth in emerging economies, export growth, investment,

globalisation vs glocalisation and emergence of born-global firms.

China to overtake the US in 2028 despite its projected growth slowdown. There is high

economic growth in emerging economies such as China while economic activity across

advanced economies remains weak. The world economy will increase at an average of just


30

over 3% per annum from 2014 to 2050. Specifically, based on the average annual Gross

Domestic Product (GDP) growth rates China is projected to be the largest economy by 2030,

while India would be the third largest economy in the world in 2050 (see Figure 3-12).

However, there will be a lower growth rate for China after 2020 due to several issues such as

ageing population, rising labour costs and pollution. The world’s GDP in terms of purchasing

power parity (PPP) in China will grow from 16.5% (in 2014) to 20% (in 2030) and then it will

decline at 19.5% in 2050 [98]. In 2014 China has overtaken in terms of purchasing power

parity (PPP2). Regarding market exchange rate (MER) terms, China will overtake the US in

2028 [98]. In Europe there will be an average growth around 1.5-2% per annum to 2050, thus

the overall share of world GDP will decrease from 17.5% in 2015 to 12% by 2050 [98].

Figure 3-12: Projected GDP growth by region [98]

BRICS (Brazil, Russia, India, China and South Africa) countries’, have recorded important

growth in terms of GDP but the slowing down of their economies have shifted the interest of

operators to new emerging economies, namely the MINT countries (Mexico, Indonesia,

Nigeria, Turkey) [100]. The seven largest emerging market economies, collectively are

referred as E7 (China, India, Brazil, Russia, Indonesia, Mexico and Turkey) [98]. Specially,

Mexico was the 14th world economy, Indonesia 16th, Turkey 17th, and Nigeria 39th in 2016. It

is projected that that Mexico will be the 8th economy of the world, Indonesia 9th, Nigeria 13th,

and Turkey 14th by 2050 [99]. According to PwC [98] new emerging economies such as

Mexico and Indonesia will be larger than the UK and France by 2030 (in PPP terms). Turkey

could be larger than Italy. The fastest growing economies over the period to 2050 could be

Nigeria and Vietnam.

International trade in goods (Figure 3-13) has reached an all-time high of $38 trillion in 2014.

International trade in services especially transport of passengers and freight has a strong

growth [65]. However, trade in goods has declined as a share of global GDP every year since

2011 (worldwide recession) and it forecasted that it would remain modest. Exports recorded

modest growth in developed (1.4%) and developing countries (1.3%). World merchandise

exports were $15.46 trillion, down 3.3% from the previous year. Europe recorded the smallest

drop in exports, (i.e. -0.3%), while the Commonwealth of Independent States had the largest,

(i.e. -16.2%). The growth gap between emerging markets and advanced economies, after


31

falling to less than 2% in 2015 for the first time since the start of the current century, is expected

to widen again and the world growth will gradually grow to 3.8% by 2021 (see Figure 3-14).

Figure 3-13: Global trade patterns [65]

Figure 3-14: The growth gap [66]

The slowdown of trade is also evident in volume terms. Different parts of the world were

influenced by the slump in trade in 2016 (see Figure 3-15). Figure 3-16 shows the world trade

growth is estimated to be between 1.8% and 3.6% in 2017 and between 2.1% and 4.0% in

2018 [101].


32

Figure 3-15: Contributions to world trade volume growth by region, 2011-2016 [101]

Figure 3-16: Growth in world trade volume (good and services) [102]

Investments were identified as a trend that emerged in the reports and papers. For example,

ports have to develop their port infrastructure in order to facilitate growth in global trade. In

supporting the ongoing growth of trade volumes in China, new infrastructure links have been

continuously added e.g. the high-speed rail network, comprising over 15,000 miles upon full

completion by 2020 [22]. Figure 3-17 shows that between 2008 and 2015 the direct investment

stocks in the EU grew steadily relative to the GDP (imports). The number of outward


33

investments was higher than inward investments (exports); that is, it shows the EU's role as a

net investor in the world.

Figure 3-17: Inward and outward foreign direct investment stocks of the EU relative to the rest of the world as a

percentage of GDP, EU-28, 2008-2015 [103]

Globalisation has allowed manufacturing companies to realise benefits such as lower

production costs, shifting associated emissions by outsourcing the production to developing

countries. Goods exports are growing due to the increasing cross-border trade; thus, logistics

volumes could experience high growth. Logistics companies followed manufacturing

companies that have employed offshoring strategies [105]. A countertrend - i.e. a trend that

is contrary to the established or perceived trend [103] - of globalisation is glocalisation (see

Figure 3-18). Glocalisation is a combination of globalization and localization and is the

situation where international products adapted to the local culture in which they are sold [107].

Glocalisation is more suitable for organisations with decentralised authority [108]. For

example, McDonald's has introduced new rice meals in India and China [109].

Figure 3-18: Glocalisation [104]


34

Due to events such as the “Brexit” implementation in the United Kingdom or the withdrawal of

the United States from the Trans-Pacific Partnership (TPP), there are calls for localisation.

Multinational companies will compete with local players by recognising differences in local

taste and custom. For example, fast-food chains usually have global, iconic brands but also

local menu options. Digitisation helps SMEs and start-ups to participate in the global arena as

it used in the past to be only for large multinational corporations. Thus, new competitors can

emerge from different parts of the world [82]. Born-global firms export their products or

services within a couple of years after their founding and export high percentages of their total

production. Innovation has an important role in the emergence of the born-global firm and it is

often developed prior to the establishment of such companies [110]. Born-global firms should

be innovative in all areas of value creation both technological and non-technological [111].

The number of these 'born globals' has increased over time (see Figure 3-19).

Figure 3-19: Number of born global firms [112]

3.3.2 Digital economy

The emergence of the digital economy is another megatrend and its trends are the sharing

economy and from an economy of goods to an economy of services.

Regarding sharing economy, customers use the internet to create online platforms (e.g.

Airbnb, Uber) which facilitate the process of sharing. Sharing economy industry worth £7 billion

a year industry and it will be £140 billion in the UK by 2025 [113]. Thus, it is estimated that

sharing economy will rise by 35% per year, leading to €0.5 trillion of total commerce by 2025

i.e. over €80 billion in potential revenues (see Figure 3-20).


35

Figure 3-20: Sharing economy revenues in Europe [114]

Peer-to-peer transportation is the biggest sector of Europe’s sharing economy and peer-to-

peer accommodation facilitated transactions totalling €15 billion in 2015 (see Figure 3-21).

The sharing economy will also change other aspects of the transportation industry. Car-

pooling platforms can be used instead of car ownership and car rentals. This concept can be

applied to inter / intra- city logistics and movement of goods.

Figure 3-21: Sharing economy in five sectors in Europe [114]

By 2025, peer-to-peer transportation will still be the largest sharing economy sector (40% of

total revenues within the five sectors). On-demand household services will be the fastest

growing of the five sectors with higher revenues about 50% per year to 2025 (Figure 3-22).

Collaborative finance models such as peer-to-peer lending and crowdfunding will continue to

grow strongly by 2025.


36

Figure 3-22: Sharing economy in Europe [114]

It is expected that providers, such as Uber, Airbnb will grow their revenue from $6.4 billion in

2015 triple to $20.4 billion by 2020 [115]. Shared mobility will have an impact on overall global

car sales. More specifically, vehicle unit sales will grow but at a lower annual rate of about 2%

by 2030 [84]. In the logistics industry companies can share transport capabilities by ride-

sharing or by truck-sharing [116].

Concerning the trend from an economy of goods to an economy of services, media

consumption is increasingly happening in digital formats. For example, media consumption

has increased tremendously (see Figure 3-23) especially from traditional media to digital

media such as Netflix, Hulu, Amazon, Apple TV, Spotify etc. [117]. The global audio and video

traffic combined is expected to reach 82% of all internet traffic by 2018 [117]. Global

subscription spending on Netflix and other over the top subscription video-on-demand

services raised by 33.8% in 2014 and 32.3% in 2015 overall a 77% in 2 years [118]. For

example Netflix's share of home entertainment revenue has gone from 0% to over 30% of total

home entertainment revenue in the past 10 years [122].


37

Figure 3-23: A Stream Runs Through It [118]

This trend is also about the introduction of new selling platform or new, upcoming internet

services. For example, Amazon and Alibaba have introduced a grocery store that has both a

virtual and physical presence.

3.3.3 Financial Innovation

The emergence of the financial innovation is another megatrend and its trends are digital

currencies, cashless payment and the financial technologies (Fintech) revolution.

Digital currencies as well as cryptocurrencies are gaining attention particularly in e-

commerce. A cryptocurrency is a medium of exchange such as the US dollar but it has no

physical form. There are more than 800 different types of digital currency and the most notable

currency at the moment is the bitcoin. Another example is the petro or petromoneda a

cryptocurrency proposed to be adopted by Venezuela which would be backed by the country's

oil and mineral reserves [119]. According to PwC’s 2015 [120] consumer cryptocurrency

survey (see Figure 3-24) cryptocurrencies are used mostly (81%) in the online shopping,

online gaming (17%) and payment of credit card bills (14%). It is supported also that the

cryptocurrency protocol may lead to major changes of government, financial services, and

retail industry [120]. For example, purchases in retail will be easier (see Figure 3-25).


38

Figure 3-24: Usage of cryptocurrencies in the past 12 months [120]

Figure 3-25: Potential impact of digital currency on the financial services industry and other areas [120]

The blockchain is the technology underlying cryptocurrencies and has the potential to disrupt

a wide variety of transactions such as stocks and other financial assets for which records are

stored digitally[120] (see Figure 3-26).


39

Figure 3-26: Blockchain and cryptocurrency open the door to other revolutionary possibilities [120]

The use of physical cash continues to decline in many markets (see Figure 3-27). The use of

physical cash continues to decline in many markets (see Figure 3-29). The volumes of digital

transactions are growing while the ratio of cash-to-card and electronic transactions has

decreased especially in some regions such as UK and Scandinavia [97].

Figure 3-27: Non-cash transactions worldwide (billion) 2010–14 [97]


40

According to the current trends in the cashless payments, it is expected an increase in global

digital payments volumes by an average 10.9% through to 2020, reaching nearly 726 billion

transactions [96]. Non-cash transactions will increase 40% by 2020 and 59% by 2025. Digital

payments will contribute 26% by 2020 and 37% by 2025 (see Figure 3-28). Digitisation of cash

will accelerate, and non-cash transactions will be overtaking cash transactions by 2023.

Figure 3-28: Digital growth journey [94]

The use of digital transactions is supported by the emerging financial technologies (Fintech)

revolution. FinTech is a dynamic segment where technology-focused start-ups and new

market entrants provide innovative products and services that currently offered by the

traditional financial services industry. Known examples are paypal, paytm which is owned by

One97 Communications Ltd. There are 12,000 FinTech companies worldwide flourishing in

different financial services from payments to lending, wealth management and capital markets

(see Figure 3-29).

Figure 3-29: Number of FinTech tripled [94]


41

The most common challenge that FinTech companies and incumbents have is the regulatory

uncertainty. More specifically 86% of financial services CEOs are worried about the

implications of over regulation on their prospects for growth (see Figure 3-30). Small players

are struggling to survive as they try to understand and copy with the ever-increasing

regulations.

Figure 3-30: Challenges for FinTech companies and incumbents [94]

According to PwC innovation is coming from outside financial services such as tech

companies, e-retailers, and social media platforms (see Figure 3-31). 80% of financial

institutions believe business is at risk to innovators and 56% have put disruption at the heart

of their strategy [121]. Figure shows the main trends in the Asset and Wealth Management,

Banking, Insurance, and Transactions and Payments Services industries till 2022 [121]. For

example, only 30% of Asset and Wealth Managers engaging in partnerships with FinTechs

[121]. Asset and Wealth Managers may invest in technologies that will improve operational

efficiency, analytical capabilities which will lead to better decision making (see Figure 3-32).


42

Figure 3-31: FinTech and disruptive entities [121]

Figure 3-32: Trends in FS ranked by importance and likelihood to respond [121]

Social

Seven megatrends emerged under the social dimension namely population growth,

demographic change, urbanisation, change in consumption pattern, individualism,


43

digital natives and knowledge based economy. Table 3-4 provides the megatrends with

the respective definition, references, and list of trends.

Table 3-4: Megatrends and trends in the social dimension


References

Trends

Population

growth

The increase of the

number of “all the

people living in a

particular country, area,

or place” [123].

[13];[15];[22];[70];

[71];[74];[78];[85];

[91];[124];[125];[126]

;[127];[128];[129];

[130]; [131];[132]

Population boom in the

developing countries

Growing demand of

resources (e.g. land)

Demographic

change

Demographic change is

the change in “the

number and

characteristics of

people who live in a

particular area or form a

particular group” [144].

[12]; [17]; [23]; [26];

[27]; [31]; [32]; [33];

[36];[38]; [65]; [70];

[72];[76]; [78]; [81];

[83];[85]; [86]; [90];

[127]; [125];[128];

[131];[133]; [134];

[135]; [136]; [137];

[138]; [139]; [140];

[141]; [142]; [143]

Ageing population

boom in developing

countries

Young population

boom in developing

countries

Migration flows

Labour shortages

Urbanisation “Urbanisation is the

process by which more

and more people leave

the countryside to live in

cities” [160].

[1];[13];[15];[18];

[20];[22];[24];[25];

[30];[33][37];[38];

[70];[71];[74][75];

[78];[79];[80];[83];

[85];[89];[90];[91];

[116];[129];[130];

[131];[132];[133];

[135];[136];[145];

[146];[147];[148];

[149];[150];[151];

[152];[153];[154];

[155]

Megacities

Smart cities

Change in

consumption

pattern

“Consumption means

the goods

(commodities), their

uses, and services

consumed e.g. Food,

clothing, and child care.

[1];[12];[14];[15];

[23];[29];[65];[73];

[75];[77];[124];

[145];[150];[156];

[157]; [158]; [159]

Middle-class explosion

Healthy diets and

lifestyles

Consumerism


44

Consumption pattern is

the way elements of

consumption are

combined to form level

of consumption as a

whole” [161].

Individualism “Individualism is the

idea that freedom of

thought and action for

each person is the most

important quality of a

society, rather than

shared effort and

responsibility” [167].

[1];[12];[13];[15];

[19];[20];[24];[29];

[30];[34];[36];[38];

[65];[[74];[75];[76];

[77];[78];[81];[83];

[116];[126];[131];

[135];[136];[145];

[147];[154];[157]

[162];[163];[164];

[165];[166];[167]

New customer

relationship

New shopping

experience

Increase customisation

Digital natives Digital natives have

been using technology

all their lives and have

grown to being able to

work and play at this

rapid pace [168].

[85] Change of

communication

patterns

Change of purchasing

patterns

Reshaping the

workplace

Knowledge

based

economy

“The knowledge

economy spans all

areas of human activity

and can be defined as

“an expression coined

to describe trends in

advanced economies

towards greater

dependence on

knowledge, information

and high skill levels, and

the increasing need for

ready access to all of

these by the business

and public sectors”

[170].

[56];[171];[172] Increase demand for

high-qualification jobs

Emerging skills

required

Continuous learning

culture


45

3.4.1 Population growth

Population growth is one of the megatrends that emerged under the social dimension from the

data analysis. One of the trends is the boom in the developing countries. In fact, world

population is estimated to increase more than one billion people and to reach 8.5 billion in

2030 and 9.7 billion in 2050 (see Figure 3-33). The rate of population growth has slowed due

to population ageing and the decline in global fertility rates i.e. 2.5 children per woman in 2010-

2015 to 2.4 in 2025-2030 to 2.25 in 2045-2050 [173]. The rate of the population growth was

1.2% (or 83 million people) between 2000 and 2015 and it is projected to decline below 1%

(or 78 million people) per annum between 2015 and 2030 [129]. Developed regions population

will increase slightly by 2.9% from 2015 to 2030 while developing regions population will

increase by 18.5% reaching 7.3 billion people in 2030 [129]. The largest contributors to the

global population growth will be Africa and Asia followed by Northern America, Latin America

and the Caribbean and Oceania [174]. The population in Europe is expected to slightly

decrease in 2050 (i.e. 739 million) compared to the population (i.e. 742 million) in 2017 (see

Figure 3-34). India, Nigeria and Pakistan will have approximately 30% of the worldwide

population growth between 2015 and 2030 [129].

Figure 3-33: Population of the world [174]


46

Figure 3-34: World population by major area, 2010-2100 [174]

Land and food demand will grow substantially due to population growth by 2050. In fact,

another important trend is related to growing demand of resources (e.g. land).

For example, agricultural land is expected to increase to fulfil the needs of a growing

population. As we can see in the Figure 3-35 below by 2050, 13 countries will have less than

0.1 hectares of arable land per person. By 2025 66% of the land in Africa will be desert; thus

60% people may move towards Europe, and worldwide by 2020 [175].

Figure 3-35: Area of arable land per person [175]

There will be a decline in average prices of cereals, meats and dairy products while oilseeds,

vegetable oils, and sugar saw a slight rebound in 2016. The last decade, the demand growth

for meat and fish (mainly from China) caused the consumption of feed to grow by almost 8%

per year. Figure 3-36 shows the annual growth in consumption. The population growth


47

calculated by considering the per capita demand as constant at the level of the year preceding

the decade and growth rates refer to total demand i.e. food, feed and other uses.

Figure 3-36: Annual growth in consumption for key commodity groups, 2007–16 and 2017–26 [176]

3.4.2 Demographic change

Demographic change is another megatrend that emerged under the social dimension and few

trends are reported as important for the next years: ageing population boom in developing

countries, young population boom in developing countries, migration flows, and labour

shortages.

Population ageing is the increase of older persons in the population and has been identified

as another megatrend. In 2015 there were 901 million people aged 60 years or over, which is

a 48% increase compared to the 607 million older persons globally in 2000 [174]. The world

aged 60 years or over is projected to grow by 56% (1.4billion) in 2030 compared to 2015 (see

Figure 3-37). The older persons in the population are expected to be more than double its size

in 2050, reaching nearly 2.1 billion since 2015 [174]. In the developed regions the

megatrend of ageing populations is projected to grow reaching 375 million in 2030 [174].

From now till 2030, Latin America and the Caribbean will have the highest number of people

who will be 60 years or over, followed by Asia and Africa [174]. In the developing countries

there will be a young population boom namely in Sub-Saharan Africa, Niger, the United

Republic of Tanzania, the Democratic Republic of Congo and Uganda [129]. Population

ageing in Europe and Northern America will face a decline compared to other regions. For

example in Europe older persons are estimated to reach 217 million in 2030, representing a

23% growth compared to older persons in 2015 but in comparison to other regions will be

decline of 16% in 2030 (see Figure 3-38). Due to a low fertility rate in the past decades, the

inflow of young people into the labour force may be smaller than the outflow of older workers

who retire, resulting in a natural decline of the population of working-age. In the future this will

result in a reduction of the number of people in the labour force, which may cause a tight

labour market in which labour demand exceeds labour supply [177].


48

Figure 3-37: Population aging patterns [174]

Figure 3-38: Population aging patterns by region [174]

The next trend that emerged under the demographic change megatrend is migration flows.

Conflicts in several regions and lack of employment opportunities lead people to move to

different places to seek better lives. Inflows of migrant workers continue to be important for

most OECD economies. International migrants have reached 244 million in 2015 [174].

Migration also helps specifically developed countries with a shrinking population lack of

qualified employees. A high percentage of immigrants to developed countries is highly

qualified [129]. Immigrants also can help companies to attract local customer needs in their

countries. Between 2015 and 2030 35 million people will move from less developed countries

to developed ones with nearly 40% of these coming from least developed countries [129].

Figure 3-39 below shows that the net immigration between 2015 and 2030 for North America


49

(+18 million), Europe (+14 million) and Oceania (+2 million) will experience net immigration,

while Asia (-23 million), Latin America and the Caribbean (-4 million) and Africa (-7 million) will

experience net emigration [129]. Europe's international migration will slow down to +14 million

between 2015 and 2030.

Figure 3-39: Selected net migration 2000-2015 vs. 2015-2030 [m] [129]

From the 243.7 million international migrants in 2015, 8.7% (21.3 million) were refugees and

16.1 million refugees were under United Nations High Commissioner for Refugees mandate

(see Figure 3-40). 54% of these refugees came from three countries Syria, Afghanistan and

Somalia.

Figure 3-40: Development of international migrants and refugees [m] [129]

Last but not least, labour shortages is another trend that emerged through the literature and

the workshop. For example, China’s labour pool begins to dwindle, since manufacturing wages

could increase which is called Lewis Turning Point between 2020 and 2030 [178]. In the

logistics industry there is a limited supply of truck drivers as well as labour in the planning and

controlling function. The age of the average truck driver has increased more rapidly than the

age of the average worker due to fewer young workers entering the industry [128]. The

demand for truck drivers will rise e.g. it is estimated that there will be a gap between the supply

and demand of drivers almost 25,000 by 2020 in Canada [179]. In the developed countries

the working age population (see Figure 3-41) will decline from 66% in 2015 to 61% in 2030


50

whereas in the developing countries will rise by 725 million people by 2030 [129]. For example,

the working age population in sub-Sahara will exceed the global working age population by

2035, it is expected to increase to 2 billion by 2050 and to 3.7 billion by 2100. Ageing

population will also have a large impact on skilled labour e.g. in the UK up to 70% of current

high-skilled employees in the nuclear industry will retire by 2025 [171]. It is also projected that

between 2010 and 2030, Europe will face a decline of 9%, thus a slowdown in working age

population growth. Figure 3-42 shows the talent shortages in a few countries as well as the

top 10 jobs with shortages in 2016.

Figure 3-41: Projected change in working age population from 2015 till 2030 [129]

Figure 3-42: Labour shortages [129]

3.4.3 Urbanisation

The megatrend urbanisation emerged under the social dimension and its trends are

megacities and smart cities.

Megacities can be defined as an urban area with over 10 million inhabitants [180]. Over 50%

of the global population lives in urban cities (see Figure 3-43) which is expected to increase

by 66% in 2050 ([181]; [182]). The global urban population is projected to increase 1.63% per

year between 2020 and 2025 and 1.44% per year between 2025 and 2030 [183]. High levels

of urbanisation (approximately 80%) are found at the moment in regions such as Latin


51

America, the Caribbean and Northern America (Figure 3-44). 40 megacities of more than 10

million inhabitants will be in 2030.The highest rates of urbanisation are projected to be in Asia

and Africa 64 and 56% respectively by 2050 [181]. Over 80% of the population will live in

urban cities in Europe by 2050 [182].

Figure 3-43: Urban and rural populations’ projections [182]

Figure 3-44: Urbanisations rates by region [182]

Rapid urbanisation lead to the emergence of megacities (see Figure 3-45). Megacities

accounted for 9%of the world's US $59.4 trillion gross domestic product in 2009. By 2020

there will be a 4.9% GDP increase on average per year across 22 megacities which will

account $9.4 trillion of the total GDP [184].


52

Figure 3-45: The world's top megacities and their population growth [185]

Regarding the trend smart cities, smart city is a new concept and a new model, which applies

the new generation of information technologies, such as the Internet of Things, cloud

computing, big data and space/geographical information integration, to facilitate the planning,

construction, management and smart services of cities [186]. In Figure 3-46 a smart city is

illustrated which is a city with free Wi-Fi in all public spaces, where children learn how to

program apps in elementary school, people shop online goods are delivered to their home

within hours, street lighting is provided on demand, uses smart sensors and uses smart

algorithms to coordinate hospital and vaccination capacities [187].

Figure 3-46: An ideal smart city strategy [187]

A city is smart when investments in (i) human and social capital, (ii) traditional infrastructure

and (iii) disruptive technologies fuel sustainable economic growth and a high quality of life,

with a wise management of natural resources, through participatory governance (see Figure

3-47) [188]. 51% of Europe’s 468 cities are smart cities but only 28% have fully launched a

smart city initiative [189]. 54% of the world’s population live in cities which it will rise to 66%

by 2050. 73% of the population live in cities In Europe [189]. Cities have to adopt new smart

technologies and processes however there is not much funding. The lack of investment is the

greatest obstacle to the roll-out of intelligent transport systems. Public private partnerships will


53

be initiated to enable smart infrastructure programmes [189]. According to the OECD [191],

the global annual investment required for all infrastructure projects in the period between 2010

and 2030 will be about $1.8 trillion and a large portion of this total will be invested in cities.

Figure 3-47: Infographic cities at a tipping point [188]

OECD estimates suggest that metropolitan areas with more than 500,000 residents drive 55%

of GDP and more than 60% of economic growth in OECD countries. IESE Business School

ranked the smart cities in 2017bbased on the model “cities in motion”: a set of steps that

include diagnosis of the situation, the development of a strategy, and its subsequent

implementation and the first step to giving a good diagnosis is to analyse the status of 10 key

dimensions [192]. The dimensions are: human capital, session cohesion, economy, public

management, governance, environment, mobility and transportation, urban planning,

international outreach and technology [192]. The results show that almost all of the dimension

measured in the ranking are led by 9 European, 11 North American, 3 Asian, and 2 from

Oceania cities [192].

The market for smart city solutions is growing driven by demographic change, resource

scarcity, and climate change [187]. The global market for smart city solutions (see Figure 3-

48) will grow by 13% per year over the coming decade, under $ 13 billion in 2017 to a forecast

$ 28 billion in 2023 [187]. The Asia-Pacific region (see Figure 3-49) will grow fastest at an

average 16% a year, nearly quadrupling in size through 2023 while Europe will have more


54

moderate growth at around 13% [187]. Smart cities will create great business opportunities

with a market value of $1.5 trillion in 2020.

Figure 3-48: Global market size for smart city solutions [USD billion] [187]

Figure 3-49: Smart City Market by Segments 2025 [193]


55

Manufacturing companies need to be in the metropolitan areas, but they face a significant

squeeze on space, affecting where and how they grow and manufacture. More than 60% of

the world population will live in urban cities by 2025 [182]. In emerging economies,

urbanisation will lead to massive investments in smart infrastructure [85]. Logistics providers

at the moment compete for the street and parking space which may lead them to coordinate

with other companies and retailers which is called “re-logistification” of retail. Logistics sprawl

is another phenomenon of relocation and concentration of logistics facilities towards suburban

areas. Another implication of the urbanisation for the logistics industry is the “flexible

distribution centres whereby a fleet of mobile warehouses are parked at strategic locations

throughout the city” [148] or multi-floor logistics facilities. Last but not least, new technologies

such as underground cargo transporters were introduced in pioneering cities and, after they

proved a success, implemented widely [30].

3.4.4 Change in consumption pattern

Change in consumption pattern is an important megatrend reported in many survey and can

be classified under the social dimension of the PESTLE analysis with some specific trends

such as middle-class explosion, healthy diets and lifestyles, and consumerism.

The middle class is “a social group that consists of well-educated people, such as doctors,

lawyers, and teachers, who have good jobs and are neither very rich nor very poor 4” [194].

The middle class was 1.8 billion people in 2009 from which the highest percentage was in

Europe (664 million), Asia (525 million) and North America (338 million). By 2015, the global

middle-class count exceeded 3 billion people, of whom almost half lived in Asia (see Figure 3-

50). India middle class population is expected to increase as well, and China and India

together are expected to form 40% of the global middle class population by 2030. Figure 3-51

below shows that around 2020, the middle class will become a majority of the global population

for the first time ever.

4 The annual income for a four-person middle-class household is $14,600 to $146,000 [195].


56

Figure 3-50: Middle class by region [195]

Figure 3-51: Middle class by region [195]

The middle class growth accounts for 64% of total consumption worth over $ 9.5 trillion [196].

At the moment the middle class population spend $35 trillion annually and they will spend $29

trillion more by 2030, accounting for roughly a third of projected GDP growth (in PPP terms)

[195]. According to Mckinsey [81] over 70% of the middle-income groups in China has

Westernised i.e. buy well-known international brands and account for over 70% of the luxury-

goods market (around £500-£1,000 per item) and they are willing and eager to try new product

such as personal digital gadgetry. Younger generations believe that foreign brands are more

capable of supplying high quality goods that are increasingly in demand” [75]. However, the

trend of rising wages leads to rising costs in “low-cost” locations are increasing the importance

of nearshoring [13].

Regarding the trend healthy diets and lifestyles, healthy eating is considering an important

aspect especially for millennials leading the charge (see Figure 3-52), and over the past year,

nearly half (47%) of the 18-34 age-group surveyed had changed their eating habits towards a

healthier diet, as compared to just 23% of those aged over 55 [197]. This survey took place

across England, Scotland, Wales and Northern Ireland in July 2016.


57

Figure 3-52: Change in eating habits since last year, by age [197]

The global functional foods market size was $129.39 billion in 2015. Functional foods deliver

enhanced benefits regarding their basic nutritional value [198]. Growing consciousness

among consumers regarding their health and proper diet is expected to aid the overall industry

over the next eight years especially in Asia Pacific, North America and Europe (see Figure 3-

53). The market revenue is expected to be high especially for products such as dietary fibers,

minerals, and vitamins (see Figure 3-54).

Figure 3-53: Global functional foods market revenue by region, 2014 - 2024 (USD Million) [199]


58

Figure 3-54: Global functional foods market revenue by product, 2015 & 2024 (USD Billion) [199]

The demand for healthy snacks is growing due to evolution of on-the-go lifestyle as these

snacks can provide adequate nutrition (see Figure 3-55). Healthy snack market size was

accounted for $21.1 billion in 2016 and it will grow at a CAGR of 5.1% over 2014 – 2025 due

to changing lifestyle and rising awareness about healthy food consumption in between meals.

Figure 3-55: U.S. healthy food market revenue, by product type, 2014 - 2025, (USD Million) [199]

The last trend identified under the megatrend change in consumption pattern is consumerism.

“Consumerism is the state of an advanced industrial society in which a lot of goods are bought

and sold” [200]). Consumption is expected to grow of 9% per year (see Figure 3-56) in 2020

in China and the overall consumer economy will grow by 55% ($6.5 trillion). In the EU

household consumption in terms of volumes during the period 2005-2015 increase of 7.8%,

and the largest increases were for communications (42.5%), health (23.5%) and recreation

and culture (19.9%), and the largest decreases for alcoholic beverages, tobacco and narcotics

(-10.4%) and 'transport' (-0.2%).


59

Figure 3-56: Consumption growth [201]

More specifically 24.4% of total or 13.4% of GDP was devoted to 'Housing, water, electricity,

gas and other fuels', then 13.0% of total or 7.1% of GDP and 12.3% of total or 6.7% of GDP

was devoted for Transport and Food and non-alcoholic beverages (see Figure 3-57).

Figure 3-57: Household expenditure by consumption purpose - COICOP, EU-28, 2015, share of total [202]

Rising incomes and increasing urbanisation have led to dietary diversification e.g. cereals

currently represent only 37% of total caloric intake obtained from commodities in developed

countries but cereals still sourced by 71% in developed countries and 54% in the other

developing countries (Figure 3-58). Total caloric intake will rise by 6% between 2014 and

2024.


60

Figure 3-58: Caloric intake per capita in least developed, other developing and developed countries [176]

3.4.5 Individualism

The megatrend individualism emerged under the social dimension and its trends are new

customer relationship, new shopping experience and increase customisation.

Regarding new customer relationship and personalising the shopping experience

trends, according to Nielsen [204] 62% support that they will buy more and/or more often when

they receive a personalised retail experience. According to a survey by Synchrony Financial

[205], 4 key experiences are most valued by customers:

1. Pick your own sale items – enjoy a discount on the items you select: it is about

giving shoppers the control to personalize their experiences based on their unique

needs and wants.

2. Hassle-free returns: retail brands with generous return policies are highly

regarded. Some of the favourite benefits are: no time limit on returns, no need for

a receipt with a return or free postage on returns.

3. No coupons needed to always get the sale price: receiving the lowest price without

working for it reduces stress for customers. Retail credit card value propositions

sometimes include “best price” programs so customers don’t need to clip coupons

to automatically get the sale price.

4. Earn points on purchases to redeem for extra savings: customers love points-

based programs and they drive loyalty behaviour for retailers.

Customers’ appreciate also the free standard shipping, the delivery in two days without extra

cost and an automatic price checker (an app which can check the price and can alert the

customer when the price goes below a certain amount). 53% of shoppers would pay a higher

price for the customer experiences they value most and 77% of shoppers would be more loyal

to stores that provided their personal top three customer experience benefits. 41% of

consumers make purchases inside a physical store at least once a week whereas just 27% of

consumers do the same online [206] (see Figure 3-59).


61

Figure 3-59: The percentage of global consumers who shop in-store at least once a week [206].

For these customers the most important attribute (78%) in relation on the shopping experience

is the “sales associates with a deep knowledge of the product range” and then the associate’s

familiarity with the store’s products, systems, technology and store network (see Figure 3-60).

Another point is the desire for real-time offers, which 59% of the sample thinks that it is

important. The data related to the customer’s purchases rarely gets turned into an appropriate,

personalised in-store offer sent as an email or a text: a complete picture of the consumer is a

“to-do” in which retailers understand the need to invest. The retailers have to invest not only

on the competences of associates but also on digital and social aspects [206]. They also have

to reinforce the digital and operations talent in the retailer C-suite to manage more complicated

supply chains and keep currently loyal customers.

Figure 3-60: the gap between what is important to consumers in-store, versus their satisfaction levels [206].

Customers anticipate from companies much more than mere product features, so successful

companies could use a Human-Centred Design. Human-Centred Designed organisations

have customers in the centre, so companies can offer products and services that meet users’

evolving needs. The “test-and-learn” approach allows a quick reaction to feedback from

anywhere - often, in real time. This way, the months it traditionally takes to deliver new

solutions are collapsed into days. Human-Centred Design allows to explore the interactions

that deeply affect the perception of the brand and its loyalty, to strengthen the relationship and


62

create unique experiences [207]. Companies need to act fast and bring value to their

customers through experience by adopting attributes such as creativity, speed, bias for action,

flexibility, and radical collaboration. In these days, personalising the user experience is

becoming increasingly important not only in the store but also during shopping on-line whose

growth rate is increasing. The largest online volumes will be from the clothing and footwear

sales nearly 50% between 2013 and 2018 [38]. There will be a radically increase (246.15%)

in the e-commerce sales worldwide (see Figure 3-61) from $1.3 trillion in 2014 to $4.5 trillion

in 2021[208].

Figure 3-61: Total worldwide e-commerce sales [208]

According to e-Marketer projects (2016) more than half of customers ordered online products

in the past six months say from an overseas retailer (57%). Approximately three-quarters who

purchased online in the past six months In India was from an overseas retailer (74%) while

the highest percentages of customers that purchase from an oversea retailers located in Italy

and in Germany (see Figure 3-62).

Figure 3-62: percentage of customers who purchased from an overseas retailer [204].

Durable goods tend to be purchased online more than the consumables (see Figure 3-63).

Among all the categories purchased online is clothing in every region except North America

(the U.S. and Canada). About 50% of the respondents have purchased books/


63

music/stationery online. In general, the practices for online payments vary around the world.

We see below in Figure 3-64 the payments practices that European consumers follow.

Figure 3-63: Online purchases [204]

Figure 3-64: Global practices for payments [204]

The inability to inspect goods poses one of the biggest barriers for consumable and durable

products: the consumer desires to inspect the goods to test the quality. The consumer is also

concerned about the delivery of the products when he isn’t at home and the returns policy of

the goods. More than half of all online respondents in the study (57%) have doubts that e-

commerce sites will keep their personal information secure and confidential. Another issue is

telecommunications infrastructure and technology adoption, which varies greatly around the


64

world. Many developing regions still face significant infrastructure challenges, including low

Internet penetration, high access costs and unreliable connections. Nearly one third of online

respondents in the study (32%) say their connection is not stable enough to make them

comfortable buying online. The e-commerce will lead to the growth in the parcel market and

in the last-mile delivery and reverse logistics services. Retailers may insource portions of their

logistics function and build their own networks e.g. Amazon [34]. Last but not least, product

customisation is enabled by new technologies such as 3D printing, so customers can directly

be involved in the process of designing a product as a co-designer [209].

One trend of this megatrend is customisation i.e. customer-oriented and individualised

production. Customers want tailor-made solutions in order to fit their own personality [203].

According to Deloitte [14] 36% of customers are interested in personalised products or

services. Holidays (25% of customers), clothing (19%) and furniture (18%) are the three

categories that customers make personalised purchases. Companies try to postpone their

production until the latest point possible to allow individual customisation. Companies have to

understand differences in consumer preferences in distinct regions to manufacture products

that meet specific needs. Companies in the pharmaceutical industry are developing products

specifically for people living in the developing economies. Customers are more willing also to

buy products that have been manufactured locally. Companies have to “develop new business

models and flexible manufacturing systems capable of producing relatively small batches of

customised products at competitive costs that mimic mass production prices” [154]. 3D printing

enables customisation and personalisation of products across multiple sectors [210]. 10% of

companies will include 3D printers in their manufacturing processes by 2020 [211]. Wearable

devices Apple Watch may bring about more tailored and personalised food and vitamins.

Thus, manufacturers are trying to sell more than the product itself, but they want to provide a

more comprehensive offering of products and related services [36]. In the logistics sector,

dedicated fleets are used ensure service requirements are met. Individualisation leads to

decentralised production structures e.g. food with a short shelf life due to the increasing

demand for healthy lifestyle i.e. fresh, healthy, unprocessed foods [80].

3.4.6 Digital natives

The megatrend digital natives emerged under the social dimension and its trends are change

of communication patterns, change of purchasing patterns and reshaping the

workplace. Digital natives such as millennials are truly digital generation.

Regarding the trends change of communication patterns and change of purchasing

patterns, purchasing decisions are linked with the social commerce. 90% of millennials search

products online and 79% of them use social media such as Facebook, Twitter. Social media

posts have an impact on them and 68% of millennials will buy specific products or services

based on friends’ social media [212]. 23,000 online shoppers, 73% of respondents will go

online while in a brick-and-mortar location, millennials account for 42% [213]. 45% of digital

buyers worldwide said that reading reviews, comments and feedback on social media have


65

an impact on their digital shopping behaviour (see Figure 3-65). 44% of respondents support

that receiving promotional offerings influence their shopping behaviour.

Figure 3-65: Social media influence [213]

Customers are also using their mobile phones while being in-store. Customer uses the mobile

phone for several reasons linked to the purchasing patterns, some of which were not possible

till few years ago it is clear that retailers who target their customers with promotions and offers

while in-store, have to offer up-to-date information on their mobile websites, and facilitate

mobile payments [213]. Another important trend related with megatrend digital natives is the

reshaping of the workplace. According to recent studies, 75% of the workforce by 2030 will

be millennials and it is expected that they want flexibility at work e.g. 60% of millennials

support that they are more productive at home versus in an office and they want regular

feedback and encouragement [214].

3.4.7 Knowledge based economy

The megatrend knowledge based economy emerged under the social dimension and its trends

are increase demand for high-qualification jobs, emerging skills required and

continuous learning culture.

Between 2010 and 2020 some 80 million job opportunities will arise for the EU countries from

which the net employment rise is anticipated to occur in higher-level occupations (Figure 3-

66). High-qualification jobs is projected to grow from 29 to 35% and jobs with low

qualifications will decline from 21% to 15% [215]. For example, for the manufacturing sector,

by 2025 the number of jobs requiring high-level qualifications is projected to rise by 1.6 million

(21%); in the automation of production processes the number of low-and medium-skilled jobs

will decrease by over 2.8 million [216].


66

Figure 3-66: Skills supply and demand in Europe [215]

There are only 90,000 science, engineering, technology and mathematics (STEM) graduates

annually and more than 800,000 technology posts will be unfilled due to the skills gap by 2020.

Europe also does not attract enough high-skilled workers that prefer other regions such as

US, Canada and Australia. The projected employment developments for Europe is depicted

in the below Figure 3-67 for the period 2010-2020.

Figure 3-67: Employment developments patterns by occupational category in EU [171]

The shortage of skilled labour is one of the most challenging issues. It is highlighted that

the technological evolution of manufacturing is transforming the skills needs e.g. mechanics,

electronics and software knowledge and programming skills. The perception is that this

shortage in skilled workers and planners will continue to escalate and will need to find more

than 17 million more workers over the next 10 years [56]. To fill the skill gap, the working

environment needs to be tailored especially in less traditional segments of women labour. 55%


67

of women are employed mostly as secretaries and administrative assistants but also as

architects, production workers and machine operators [217]. As the number of working women

increases, it is expected that deliveries at home will increase too but also the cost will increase

due to unsuccessfully delivery on the first attempt [217]. Companies have to rethink the way

they manage careers and deliver always-on learning and development (L&D) opportunities.

Employees themselves are pushing for continuous skill development and dynamic careers

e.g. for millennials, the “ability to learn and progress” is now the principal driver of a company’s

employment brand [56]. 90% of CEOs support that their company is facing disruptive change

driven by digital technologies, and skills are becoming obsolete at an accelerating rate. For

instance, software engineers, professionals in marketing, sales, manufacturing, law,

accounting, and finance have to redevelop skills every 12–18 months [56].

Technological

Four megatrends emerged under the technological dimension namely digital transformation,

technology development and automatisation, transport electrification and renewable

energy sources. Technological advances have driven dramatic increases in industrial

productivity and now we are in the midst of the rise of new digital industrial technology known

as Industry 4.0 which is powered by several technological advances such as big data analytics

and robots [240]. Table 3-5 provides the megatrends with the respective definition, references,

and list of trends.

Table 3-5: Megatrends and trends in the technological dimension


References

Trends

Digital

transformation

Digital transformation

(DT) – the use of

technology to radically

improve performance

or reach of enterprises

[219].

[1];[12];[13];[16];

[20];[21];[22];[24];

[25];[27];[29];[30];

[32];[33];[34];[36];

[65];[74];[75];[76];

[77];[78];[81];[82];

[84];[85];[87];[88];

[89];[90];[116];[125];

[126];[130];[131];

[132];[133];[134];

[136];[137];[139];

[140];[141];[143];

[145];[146];[148];

[150];[151];[152]

[154];[155];[156];

[157];[158];[159];

Big data analytics

Artificial intelligence

Cloud based

computer systems

Blockchain

Internet of Things

Technology

development

and

automatisation

The systematic use of

scientific, technical,

economic and

commercial knowledge

to meet specific

business objectives or

requirements as well to

Robots

Cyber-physical

system

Augmented reality

and virtual reality

3D printing/additive

manufacturing


68

make a process, etc.

automatic [235].

[164];[165];[166];

[167];[218];[219];

[220];[221];[222];

[223];[224];[225];

[226];[227];[228];

[229];[230];[231];

[232];[233];[234]

Drones

Autonomous

systems

Automated guided

vehicles

Wearable devices

Transport

electrification

“The process of making

a machine or system

operate using electricity

when it did not before”

[236].

[237];[238];[295];[296];

[296];[298];[299];[300];

[301];[303]

Battery electric

vehicles

Hydrogen fuel cell

electric vehicles

Hybrid vehicles

Renewable

energy sources

“Renewable energy is

energy produced by

wind, sun, and other

sources that will never

run out.”[239].

[238];[235] Production and

storage of clean

energy and

application to

transportation and

industry

Renewable energy

for industrial

processes

3.5.1 Digital Transformation

Digital transformation is the changes associated with digital technology application and

integration into all aspects of human life and society [241]. The trends of digital transformation

are big data analytics, artificial intelligence, cloud based computer systems, blockchain

and Internet of Things.

3.5.1.1 Big Data Analytics

Big Data Analytics is the application of advanced statistics to any kind of stored electronic

communication such as “messages, updates, and images posted to social networks, readings

from sensors, and GPS signals from cell phones” [243]. According to [235], the main types of

Big Data Analytics are Prescriptive, Predictive, Diagnostic, and Descriptive. Big data and

analytics software sales will grow to $70 billion by 2020. Big data and analytics software sales

will grow to $70 billion by 2020. $72.4 billion will be spend on big data and analytics software

in the banking, discrete manufacturing, federal and central government, and professional

services sectors. Figure 3-68 shows how many companies per countries in 2016 conducted

different analyses from big data. There is a comparison between all the sectors and the

companies from the manufacturing sector. Banking, discrete manufacturing, and process


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manufacturing companies will invest more than other companies in big data and analytics

solutions from 2016 to 2020 (see Figure 3-69).

Figure 3-68: Percentage of enterprises analysing big data from any data source [244]

Figure 3-69: Top 5 big data analytics industries [245]

Big data analytics have been used in various industries. For example, pharmaceutical

companies are using predictive analytics to detect demand spikes and ramp up production,

stocks and delivery resources ahead of time [21]. Specifically, big data from climate change

and global weather trends are used by Bayer AG uses to predict hayfever occurrences [21].

Another example of application is for the logistics companies. Big data is playing a larger role

in the last-mile challenge [148]; by providing creative solutions for industrial operators, such

as route optimisation and real-time tracking of resources. Predictive analytics use big data to

identify past patterns to predict the future. For example, some companies are using predictive

analytics for sales lead scoring [242]. The market of predictive analytics will grow from $2.74

billion in 2015 to $9.2 billion by 2020 with an annual rate of 27.4%. For example, when a bank

notifies a customer of potentially suspicious activity, it is highly likely that a statistical model

has been used to predict future behaviour based on past transactions.

0 5 10 15 20

Belgium

Germany

Hungary

Croatia

France

Slovakia

Estonia

Finland

Netherlands

all enterprise manufacturing


70

3.5.1.2 Artificial intelligence

Artificial intelligence includes software algorithms for decision-making tasks in order to mimic

the human thought processes and senses. It can be used for assessing car damage; and

security companies trading clunky typed passwords for voice recognition. The revenue

generated from the direct and indirect application of artificial intelligence software is estimated

to grow from $643.7 million in 2016 to $36.8 billion by 2025 an annual growth rate (CAGR) of

56.8% (see Figure 3-70). The top use case of artificial intelligence is algorithmic trading (see

Figure 3-71). Investment banks and hedge fund firms are already using it.

Figure 3-70: Artificial intelligence revenue [246]


71

Figure 3-71: Top 10 use cases [246]

3.5.1.3 Cloud based computer systems

Cloud computing is a method for delivering information technology (IT) services in which

resources are retrieved from the Internet through web-based tools and applications, as

opposed to a direct connection to a server [247]. Cloud computing spending is growing at 4.5

times the rate of IT spending since 2009 and is expected to grow at better than 6 times the

rate of IT spending from 2015 through 2020. According to IDC, worldwide spending on public

cloud computing will increase from $67B in 2015 to $162B in 2020 attaining a 19% compound

annual growth rate (CAGR). The trend of mobile devices also leads 38% of vendors to develop

logistics software programs for mobile devices [15]. Software competence is increasingly

becoming one of the most important trends for other industries as well such as the automotive

industry. Smartphone applications could be used by customers for testing and digital recording

of blood sugar values for diabetic patients. More than 50% of the orders for e-commerce are

generated via mobile apps. Mobile devices are used from manufacturing companies to

transmit data. Also, drivers and customers are using smartphones and tablets to have real-

time updates and tracking of the delivery status [15]. In the future these devices could supply

3D scan data to document cargo during delivery [15]. The following graph, 3-72 shows the

percentages of companies, per each European country, which bought in 2016 cloud computer

services. It shows also the percentages related to the companies in the manufacturing sectors.


72

Figure 3-72: Percentage of enterprises which buy cloud computing services used over the internet, 2016 [248]

3.5.1.4 Blockchain

Blockchain can be defined as a “distributed, shared, encrypted database that serves as an

irreversible and incorruptible repository of information” [249]. Blockchain can be used to

increase transparency through systematic and instant information exchange across different

stakeholders and regions. Blockchain can be used with big data analytics to ensure that the

data is original [250]. It is useful in the logistics industry to maintain precise and timely

information and validating data about each transit segment or point of interaction e.g. transfer

of shipping documents or orders and order confirmations [250]. Blockchain can be used for

developing smart contracts (i.e. ‘electronic’ contracts based on automated actions e.g. for

automated execution of payments in case of an in-quality and on-time delivery). According to

PwC 9% of the financial services firms make substantial investments in blockchain, while 36%

expected to do so within the next three years [251]. 20% of trade finance globally will

incorporate blockchain ledger technology [251]. Blockchain technologies are more capable to

support good integration for ledger and smart contract because it does not offer a data model

to solve end-to-end integration (see Figure 3-73).


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Figure 3-73: Blockchain functionality [252]

According to Hackius and Petersen’s [253] survey, 80% of the participants support that the

main industries that will have an advantage from blockchain is the logistics service providers,

senders, receivers, and technology providers to benefit. 43% do not consider Blockchain yet,

37% of the participants try to find ways to use it and just 20% have implemented first

Blockchain solutions. In the field of supply chain management and logistics, blockchain can

be used for ease paperwork processing in ocean freight, identify counterfeit products, facilitate

origin tracking and operate the Internet of Things (see Figure3-74). For example, Walmart

granted a patent to improve last mile logistics by connecting delivery drones to the Blockchain

[253].

Figure 3-74: Overview of Use Case Exemplars [253]

3.5.1.5 Internet of Things

“The Internet of Things (IoT) is a network of physical objects—devices, vehicles, appliances—

embedded with sensors, software, network connectivity, and computer capability enabling

them to collect, exchange, and act on data, usually without human intervention” [254]. The

use of IoT in the manufacturing and industrial sectors is called industrial IoT or Industry 4.0.

Almost 20.4 billion connected physical objects will be in use worldwide by 2020. 67% of the


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overall use of IoT will be in Greater China, North America and Western Europe. There will be

a massive growth regarding the number of business-to-business IoT connections more than

quadrupling over the next five years (see Figure 3-75).

Figure 3-75: IoT growth [255]

Manufacturing industry has seen the biggest increase in machine-to-machine operations,

followed by finance and insurance with a 128% increase. For example, the logistics industry

is becoming connected (i.e. where other vehicles are, who is the driver, mechanical is or other

problems). Connected-home device shipments will grow at 67% annual rate over the next five

years (see Figure 3-76) and smart appliances shipments are the lowest due high prices [256].

IoT will increase in revenue across multiple industries (see Figure 3-77).

Figure 3-76: Device shipments by sector [246]


75

Figure 3-77: IoT market by 2020 [257]

3.5.2 Technology development and automatisation

The trends of technology development and automatisation are robots, cyber-physical

system, augmented reality and virtual reality, 3d printing/additive manufacturing,

drones, autonomous systems, automated guided vehicles (AGV), and wearable

devices.

3.5.2.1 Robots

Robots are machines with superior sensing, control, and intelligence to automate or assist

human activities. By 2019, 30% of commercial service robotic applications will be in the form

of a robot-as-a-service (RaaS) business model (see Figure 3-78). Between 2014 and 2020, 3

million additional jobs especially in consumer electronics and the electric vehicle industry will

be created, however 1.4 million robots will be installed in factories worldwide by 2019 and 21

million human jobs will potentially be replaced by machines. Robotics market is projected to

hit around $40 billion in investments by 2020 [258].

Figure 3-78: Global robot market [258]


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Robotics developments play lead to ‘reshoring’: reintroducing domestic manufacturing to a

country. For example, Adidas sportswear manufacturer brings shoe production back to

Germany from China by having an automated facility that makes use of “intelligent robotic

technology”. Cobotics (or collaborative robots are robots that physically interact with humans

in a shared workspace) are also widely used on specific ergonomically challenging tasks within

the aerospace and automotive industries. Artificial intelligence (AI) will also influence the

labour market (especially benefiting countries with an aging population) in the next few years,

e.g. companies build factories where robots will replace 90% of human workers in China [143].

For example, Starship robots have been designed to operate 99% autonomously and deliver

groceries within a maximum delivery time of 30 minutes [79].

3.5.2.2 Cyber-physical system

A cyber-physical system is controlled or monitored by computer-based algorithms and is

integrated with the Internet and its users. Cyber-physical systems integrate computing and

physical processes where the key focus is on link between computational and physical

elements [292]. Cyber-physical system parts exchange information with each other (see

Figure 3-79) and are denoted by the symbol C3 (Computation, Communication and Control)

[292].

Figure 3-79: Three main components of cyber-physical system [292]

Applications of cyber-physical system have been active in transportation, smart home, robotic

surgery, aviation, defence, critical infrastructure, etc. and also positively affected

manufacturing in form of cyber-physical production systems in process automation and control

[293]. For example, SOCRADES components entail a cyber-physical system by using a

service bus that supports forming a network of smart components/objects (see Figure 3-80).

Physical components (hardware/software) are having its cyber-shadow represented in a

service-cloud and devices can be accessed from any node of the network or any

member/component of the cloud.


77

Figure 3-80: Network of smart embedded devices [294]

3.5.2.3 Augmented reality and virtual reality

Augmented Reality (AR) uses contextualised digital information to enhance the viewer’s real-

world view. AR market will increase to USD 5.2 billion by 2017 especially for games and

multimedia & entertainment (see Figure 3-81).

Figure 3-81: Global AR Revenues 2012 to 2017 by market segment [259]

An application of AR in manufacturing aims to help the operator by projecting assembly

instructions. AR can be used in the 1) picking optimisation e.g. calculation of the most efficient

path through the warehouse, 2) facility planning e.g. warehouse visualisation, 3) freight /

container loading e.g. replace the need for a physical cargo list 4) dynamic traffic support and

transportation optimisation e.g. heads-up and windshield displays usage for efficient re-route

shipments, show critical information such as temperature [260]. Apart from augmented reality

that delivers virtual elements as an overlay to the real world there is also a virtual reality that

offers a digital recreation of a real life setting. Specifically, virtual reality helps by generating

simulation of a three-dimensional image and it can be used in the Gaming and Entertainment

industries as well in the work environment to train employees. The global virtual reality market

will worth approximately $38 billion by 2020 (see Figure 3-82).


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Figure 3-82: Virtual reality revenues by market segment [261]

3.5.2.4 3D printing/Additive manufacturing

3D printing is a methodology using three-dimensional CAD data sets for producing 3D haptic

physical models [262]. The 3D printing industry (see Figure 3-83) will grow from $3.07 billion

in revenue in 2013 to $21 billion by 2020 [263]. Companies tend to use this technology for

prototyping (24.5%), product development (16.1%) and innovation (11.1%) (see Figure 3-84).

According to PwC [264], 52% of manufacturers support that they will use 3D printing for high-

volume production in the next 3-5 years. In the next 3-5 years over half of US manufacturers

(52.8%) believe that 3D printing will be used more in producing after-market parts or products.

The automotive industry’s adoption of 3D printing will increase from $365.4M in 2015 to $1.8B

in 2023 and in aerospace industry it will increase from $723M in 2015 to $3.45B in 2023 [265].

However, there are several issues in adopting the 3D printing namely cost and lack of talent

and current expertise, uncertainty of quality of the final product and printer speed.

Figure 3-83: Worldwide 3d printing industry (billions) [265]


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Figure 3-84: 3D printing usage [265]

3D printing or additive manufacturing as a genuinely disruptive technology is another trend

and it is used to manufacture parts and reduce design-to-manufacturing cycle times. For

example, BAE Systems use 3D printing for one plastic part when it could no longer be provided

from regional jetliner. 3D printing supports personalisation and minimises waste as well as

enables the more efficient use of resources [266]. Manufacturing activities will gradually move

closer to the final customers. This relocation will lead to the reformation of logistics facilities

and it will change the relationships with the suppliers who provide the materials [267]. By 2025,

it is estimated that 3D printing will reach a global value between $180 billion and $490 billion

[125]. However, studies have highlighted that centralised factories are preferable for high-

volume, low-added-value production [266]. 3D printing could lead to competition e.g. new

entrants, small maker businesses that could be funded through crowdsourcing, and compete

in niche markets for a very small group of customers [269]. This technology will have

implications on the warehousing industry as well. Specifically, products could be stored

digitally thus reducing the inventory in the warehouses [159]. Regarding distribution, there will

be a reduction in shipping, but raw materials are still needed [267].

Beyond 3D printing technology, there are a series of recent and complementary innovations

in materials, manufacturing, and processes industry challenging traditional manufacturing

techniques. Additive manufacturing processes are usually used to produce prototypes and

small metal parts, hybrid manufacturing combines additive manufacturing “with metal

machining processes on a single machine tool, unlocking new opportunities to make

production-quality parts with the same additive-like flexibility” [270]. Another advanced

manufacturing technology is the selective laser melting (SLM) which offers an ideal platform

for producing components with almost no geometric constraints [271]. Lasers are being used

more and at a growing range of scales; and, the global market for lasers is forecast to be $16.0


80

billion in 2020 [272]. Also, additive manufacturing has been enhanced with the appearance of

innovative and high- performance materials, such as nanobased composites and ceramics.

Nano-based composites have electrical and thermal properties and can therefore be used as

a replacement when high stability is required [273] .

3.5.2.5 Drones

A drone is an unmanned aerial vehicle (UAV) that is remotely controlled or can fly

autonomously through software-controlled flight plans [274]. The commercial/civilian market

of drones will increase with an annual growth rate of 19% between 2015 and 2020. The military

side will have just a 5% growth (see Figure 3-85). A report by Tractica [275] forecasts that

revenue from commercial UAV services will grow to $8.7 billion by 2025. The global market

revenue for drones will be at least $127 billion by 2020 [276].

Figure 3-85: Global drone market [275]

A 39% increase (nearly 3 million drones) of drones’ production occurred between 2016 and

2017 [277]. Drones will be used mainly in infrastructure ($45.2 billion by 2020), agriculture

(e.g. gather and analyse crop data quickly), as well as in the transportation industry (see

Figure 3-86).

Figure 3-86: Drone services market [276]


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Drones are expected to be used for quick delivery, internal delivery and for tracking inventory

[224]. Rapid urbanisation and population growth megatrends lead to congested roads and

pollution, thus there are delays in the flow of goods. Drones can be used to minimise the traffic

in the roads. Drones can be important in intralogistics especially in specific industries such as

the automotive industry. For example, drones can be used to support intraplant transport

which is today performed by helicopter. However, there are still issues such as regulations

and public concern regarding the unmanned aerial vehicle [224].

3.5.2.6 Autonomous systems

One major area of autonomous systems development concerns the fully autonomous cars,

i.e. vehicles that are able to perceive its environment, decide what route to take to its

destination, and drive it [278]. It is not likely that fully autonomous vehicles will be commercially

available before 2020 while advanced driver assistance systems (ADAS) will be important in

“preparing regulators, consumers, and corporations for the medium-term reality of cars taking

over control from drivers” [279]. Up to 15% of all new vehicles sold in 2030 would be fully

autonomous (see Figure 3-87).

Figure 3-87: New vehicles market [279]

It is projected that over a million automated vehicles (see Figure 3-88) will be in use worldwide

in less than ten years [280]. China will be the world’s largest market for AVs after 2035 (exceed

6 million vehicles annually).The highest sales by volume will be in the USA and the rest will

be split roughly evenly between Europe and the Middle East, Asia and the Pacific, and the

rest of the world (see Figure 3-89). 51% of the industry is expecting driverless trucks by 2025

[226]. Once technological and regulatory concerns have been solved, autonomous vehicles

could represent as much as 25% of vehicle production by 2030 [280].


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Figure 3-88: Sales of AVs [281]

:

Figure 3-89: Total Sales by Volume of Units [281]

Another important element of the autonomous systems will be the autonomous vessels. An

important element of this technology will be the advanced navigation system e.g. detect and

adapt to changing sea and weather conditions, avoid collisions [280]. Inland waterway

transport and short-distance ferries will be adopted mainly in the early phase of this

technology. Rolls-Royce aims to launch a remotely operated local vessel by 2020 (see Figure

3-90).


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Figure 3-90: Unmanned autonomous vessels [283]

In 50 years, containerships will operate autonomously and will be nearly three times the size

of the largest current vessels. In the future there will be only three or four major liner

companies, operating either as digitally enabled independents or as small units [284]. Loading,

stowage, and sailing will be fully autonomous to unloading directly onto autonomous trains

and trucks and drones [284]. Autonomous 50,000- twenty-foot equivalent unit (TEU) ships will

flow the seas two to five times greater than it is today. There will be an increase on short-haul

intraregional traffic due to automation, and robotics disperse manufacturing footprints [284].

3.5.2.7 Automated guided vehicles

Automated guided vehicle (AGV) is a driverless mobile robot that can be controlled and

navigated remotely [285]. AGVs can be used for the production intralogistics application,

warehouse intralogistics, e-commerce intralogistics and to transport products from one place

to another e.g. in urban cities [286]. The automotive industry was initially the leader in adopting

AGVs, however other industries such as tobacco industry, electric field and e-commerce

industry are also using it. The AGV market is expected to reach $1.5 billion by 2024 [287]. The

Asia Pacific region was valued at over $ 320.6 million in 2015 regarding AGVs, and it is

expected to expand at a CAGR of 7.6% from 2016 to 2024, which is influenced by the

increasing manufacturing and logistics activities in the emerging countries such as China and

India [287]. For instance, Amazon uses Kiva AGVs at its warehouse to effectively manage

logistics activities in China [287].

3.5.2.8 Wearable devices

A wearable device can be defined as a device that is autonomous, that is non-invasive, and

that performs a specific function such as monitoring or support over a prolonged period of

time. The term ''wearable'' implies that the support environment is either the human body or a

piece of clothing [288]. Worldwide wearable device shipments will grow from 19.6 million units

in 2014 to 126.1 million units by 2019. The market’s growth will be based mainly on smart

watches and wrist-worn fitness trackers (see Figure 3-91).


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Figure 3-91: Wearable devices market [289]

Smart clothing shipments will increase from 140,000 units in 2013 to 10.2 million units in 2020

with 84.6% compound annual growth rate (see Figure 3-92) [290]. Smart clothing represents

has one of the highest growth rates. Smart clothing revenue will raise from $17.2 million in

2013 to $603 million by 2020 mainly from sports applications (see Figure 3-93) [290].

Figure 3-92: Smart Clothing and Body Sensor Unit Shipments, World Markets: 2013-2020 [290]

Figure 3-93: Smart Clothing and Body Sensor Device Revenue, World Markets: 2013-2020 [290]


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Wearable technology device access consumer information such as health readings and

physical location [291]. Millennials are more willing to share these information anonymously

than non-Millennials with the government (40% vs. 25%), anyone on the Internet (35% vs.

20%), or their employer (30% vs. 16%) [291]. High percentage of millennials are happy to

share data with their online network such as of the music they are listening and the stores they

visit (see Figure 3-94) [291]. Consumers are also happy to exchange information (see Figure

3-95) for rewards when they enter a store (19%) and notifications about deals when they’re in

a store (19%) [291].

Figure 3-94: Wearable devices and data sharing [291]

Figure 3-95: Wearable technology and social media [291]


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3.5.3 Transport electrification

The transport electrification market is driven by stringent emission and fuel efficiency

regulations across the globe. Asia-Oceania is projected to dominate the transport

electrification market. China, Japan, South Korea, and India contributed approximately 53%

to the global vehicle production in 2016 [295]. In Europe it is projected that battery electric

vehicle and plug-in hybrid electric vehicle scenarios will reach 20% sales share of the

European premium vehicle market (see Figure 3-96).

Figure 3-96: Premium light vehicle sales by propulsion system design and fuel type, 2016–26 [296]

The European Association for Hydrogen and fuel cells and Electro-mobility in European

Regions (HyER’s) is a membership-based network acting on the behalf of its members to

represent the interests of European regions and cities active in the field of hydrogen, fuel cell

technologies and electro mobility. HyER’s aim is to become the European point of reference

for hydrogen and electro mobility in EU regions, cooperating with key decision-members at

the EU level and assisting members effectively to develop their hydrogen and electro mobility

activities. Several projects in Europe were developed to increase of electrification, e-mobility

in society. As an example, the Emobility project aims at fully developing e-mobility potential in

European municipalities and businesses by developing e-mobility action plans for the

municipalities and consulting local businesses regarding the integration of e-mobility in their

corporate strategies [297]. The trends of electrification are battery electric vehicles,

hydrogen fuel cell electric vehicles and hybrid vehicles.

3.5.3.1 Battery Electric vehicles

In order to develop a portfolio of power-trains, several supply infrastructure systems are

required [298]. Electric vehicles are also introduced to minimise CO2 emissions especially in

urban areas (stricter environmental regulations). Large manufacturers like BMW, Hyundai,

Nissan, Renault and Tesla are selling Battery Electrical Vehicles. There is not much availability

and choice of electrified transport logistic vehicles in the logistics industry that that could lead

to energy efficiency and new materials will lead to reduction in the weight of vehicles thus

minimise cost due to fuel usage minimisation [299]. With the development of alternative

powertrains urban buses also can now contribute to decarbonising road transport and many


87

cities have already focused on cleaner public transport. However, problems could arise due

to the needed infrastructure e.g. location of charging stations [300].

3.5.3.2 Hydrogen Fuel Cell Electric vehicles

On the energy demand side, hydrogen molecules are a critical complement to electrons in the

challenge of far-reaching decarbonisation. The Hydrogen Council vision sees hydrogen

powering more than 400 million cars, 15 to 20 million trucks, and around 5 million buses in

2050, which constitute on average 20 to 25% of their respective transportation segments [238].

Since hydrogen plays a stronger role in heavier and long-range segments, this 20% of the

total fleet could contribute more than one-third of the total CO2 abatement required for the road

transportation sector in the two-degree scenario.

Hydrogen Fuel Cell Electrical Vehicles buses (FCEV buses), medium-sized cars, and forklifts

are commercially available today. The next five years will see the introduction of more models

in medium-sized and large cars, buses, trucks, vans, and trains, and it is likely that additional

segments such as smaller cars and minibuses will follow until 2030 [238]. It is expected that 1

in 12 cars sold in California, Germany, Japan, and South Korea should be powered by

hydrogen by 2030, when sales start ramping up in the rest of the world. More than 350,000

hydrogen trucks could be transporting goods, and 50,000 hydrogen buses, thousands of trains

and passenger ships could be transporting people without carbon and local emissions [238].

Meanwhile, Toyota, Hyundai, Honda, are selling Hydrogen Fuel Cell vehicles, while,

Mercedes, BMW, Lexus and others are intending to start sales in the next two years.

A coalition of 40 industrial companies and government organizations, financially supported by

the FCH JU, elaborated a technology neutral and fact-based comparative study on eight

different powertrain technologies for urban buses in Europe from 2012 to 2030 (see Figure 3-

97). According to the results of the study, only fully electric powertrain buses (based on

hydrogen, batteries or trolley system) have the potential to achieve zero local emissions by

drastically reducing well-to-wheel emissions [237].

Figure 3-97: Alternative powertrains in EU cities [237]


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3.5.3.3 Hybrid vehicles

Alstom unveiled the new train at InnoTrans, an annual trade show in Berlin this week. Starting

at the end of 2017, the train will run on the Buxtehude-Bremervörde-Bremerhaven-Cuxhaven

line in the north-western German state of Lower Saxony Lower Saxony's local transportation

authority has meanwhile ordered 14 trains of the type [301]. The Coradia iLint is the first low

floor passenger train worldwide powered by a hydrogen fuel cell, which produces electrical

power for the traction. This zero-emission train is silent and only emits steam and condensed

water. Coradia iLint is special for its combination of different innovative elements: a clean

energy conversion, flexible energy storage in batteries, and a smart management of the

traction power and available energy. Based on Alstom’s flagship Coradia Lint diesel train,

Coradia iLint is particularly suited for operation on non-electrified networks. It enables

sustainable train operation while maintaining high train performance [302].

Within the thematic group of EU agencies and bodies supporting EU businesses and

innovation, Shift2Rail contributes to smart and sustainable growth through its actions to foster

research and innovation in the railway sector. The purpose is to achieve a Single European

Railway Area (SERA); to enhance the attractiveness and the competitiveness of the European

railway system to ensure a modal shift from roads towards a more sustainable mode of

transport such as rail; and to sustain the leadership of the European rail industry on the global

market [303]. In the report of the Hydrogen Council presents a vision for 2050 in which

hydrogen also powers a fifth of locomotives on non-electrified tracks, and hydrogen-based

synthetic fuel powers a share of airplanes and freight ships [238]. Hydrogen can already lower

the total cost of ownership of trains and forklifts, and we expect all transportation segments to

be within a 10% range by 2030 [238].

3.5.4 Renewable energy sources

Hydrogen is a central pillar of the energy transformation required to limit global warming to

two degrees Celsius [238]. To achieve the two-degree scenario, the world will need to make

dramatic changes year after year and decrease energy-related CO2 emissions by 60% until

2050 (see Figure 3-98). And also as the population grows by more than 2 billion people and

billions of citizens in emerging markets join the global middle class. Hydrogen can play seven

significant roles in this transformation:

Enabling large-scale renewable energy integration and power generation

Distributing energy across sectors and regions;

Acting as a buffer to increase energy system resilience;

Decarbonizing transportation;

Decarbonizing industrial energy use;

Helping to decarbonise building heat and power;

Providing clean feedstock for industry.


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Figure 3-98: Final energy consumption, 2013 and 2050 [238]

The trends of alternative energy sources are storage of clean energy and application to

transportation and industry and renewable energy for industrial processes.

3.5.4.1 Production and storage of clean energy and application to transportation and

industry

As the energy system relies more heavily on renewables, hydrogen could also play a growing

role in the storage of renewable electricity and the production of clean electricity. Hydrogen

allows to store and transport renewable electricity efficiently over long periods of time and is

therefore a key enabler of the transition to renewable energy. By 2030, 250 to 300 TWh of

surplus renewable electricity could be stored in the form of hydrogen for use in other

segments. In addition, more than 200 TWh could be generated from hydrogen in large power

plants to accompany the transition to a renewable electricity system [238]. Hydrogen is

exceptionally well suited to store large quantities of energy for long durations (see Figure 3-

99). At a large scale, hydrogen can be stored in underground salt caverns in pure or

methanized form. Estimates put the cost at around $50 to 150 per MWh, which is significantly

less than other storage technologies for electricity. Only pumped hydro storage is even more

competitive, but its remaining untapped potential is subject to local geographic conditions

[238].


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Figure 3-99: Storage: Technology overview [238]

3.5.4.2 Renewable Energy for industrial processes

In industry, hydrogen is used for medium- and high-heat processes, for which electrification is

not an efficient option. Current uses of hydrogen as a feedstock are decarbonised through

clean or green production pathways. Also, hydrogen is used as renewable feedstock in 30%

of methanol and about 10% of steel production. The demand for hydrogen as feedstock is

rising. Chemical and petrochemical industries use about 25 EJ worth of fossil fuels as

feedstock each year – and about 8 EJ of hydrogen; most of which is produced from natural

gas, oil, or coal. Almost all the hydrogen is used in refineries and in the production of fertilizers

and other chemicals (see Figure 3-100). The total amount of hydrogen produced each year is

enough to power more than 100 million FCEVs and creates some 350 to 400 Mt of CO2 per

year.

Figure 3-100: Total hydrogen use, 2015 estimate [238]

As industry production rises globally, the demand for feedstock is likely to increase. By 2050,

the demand for hydrogen could rise to 70 million tons (10 EJ) in current applications alone,

driven by the growth in global chemicals production. If this hydrogen is produced from non-

clean sources, it would create emissions of about 500 Mt of CO2. For heat and power for

buildings and industry, hydrogen can make use of existing gas infrastructure and assets. For


91

buildings, low concentrations of green hydrogen could be blended into public natural gas

networks without any infrastructure upgrades. Alternatively, entire cities could be converted to

pure hydrogen heating. Both processes have already started and could start scaling up around

2030, with the equivalent of more than 5 million households connected to a gas network with

blended or pure hydrogen. A second wave of commercialization could start once the costs of

producing hydrogen have fallen enough to drive uptake in more cost-sensitive industry

segments. While hydrogen penetration may not reach the same rates in industry as in other

segments, industry’s large energy consumption implies substantial hydrogen demand beyond

2050. By 2030, up to 200 steel, chemical, and automotive plants could be pioneering the use

of hydrogen for heat and power [238].

Legal

Three megatrends emerged under the legal dimension namely consumer protection laws,

intellectual property law and social and environmental regulations. Table 3-6 provides

the megatrends with the respective definition, references, and list of trends.

Table 3-6: Megatrends and trends in the legal dimension


References

Trends

Consumer

protection laws

“Consumer protection

laws: laws and policies

designed to protect

consumers against

unfair trade and credit

practices” [306].

[304] Cross-border

payments

Return products

free of charge or

under warranty

Product safety

regulations

Privacy

Intellectual

property law

“Intellectual property

law deals with the rules

for securing and

enforcing legal rights to

inventions, designs,

and artistic works”

[307].

[305] Patents

Data sovereignty

Social and

environmental

regulations

“Social regulations

protect public interests

such as health, safety,

[20];[23];[27];[30];

[34];[65];[70];[71];

[79];[80];[83];[88];

Corporate social

responsibility

Emissions control

regulations


92

the environment, and

social cohesion” [309].

“Environmental

regulations can be

defined as an

combination of state

and federal statutes,

regulations, and

common-law principles

covering two things:

pollution control and

conservation

management” [308].

[124]; [131] ;[149];

[227]; [304];

Waste and

resources

management

regulations

3.6.1 Consumer protection laws

Consumer protection laws is one of the megatrends that emerged under the legal dimension

and its trends are cross-border payments, return products free of charge or under

warranty, product safety regulations and privacy.

General legislation has been adopted relating to cross-border payments. Regarding the

sharing economy, there is a lack of clarity of the existing legislation for certain activities and

transactions, and on regulations to protect customers and companies and vice versa e.g. taxi

metres have been made mandatory and Uber was forced to stop operating in Denmark [310].

In addition, there is regulatory uncertainty which could act as a barrier for the adoption of new

technologies like the Blockchain [311]. EU data protection rules will apply not only to European

companies, but also to foreign companies offering products and services to EU citizens. For

example, start-ups from around the world have to follow the same rules as start-ups from

Europe. Commercial legislations have increased and for example customers have the ability

to return products free of charge or under warranty [304].

For what concerns product safety regulations, in Europe there are laws which force

companies to recall their product if there are problems for the safety of the customer. For

instance, Toyota recalled 5.8 million vehicles because of faulty airbags [312]. In the food

industry these laws include preventing food fraud, reliable labelling of food origin, and

presence of allergens. In the pharmaceutical industry dedicated vehicles are used to monitor

the temperature and report any excursions. The requirements for the approval of new drugs

have been tightened [15]. In addition, regulations in the pharmaceutical industry are getting

more rigorous e.g. the European Medicines Agency (EMA) introduced a new approach to the

management of adverse reactions [34]. Regarding privacy, consumers are increasingly

concerned about this trend; the protection legislation of European countries (based upon

Directives from the EU) aims to protect the rights of individuals to ensure that their personal

information remains private and secure. The value of European citizens’ personal data may

grow to nearly €1 trillion annually by 2020. In these days, consumer protection in the digital


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single market is a key priority in Europe. For example, there are different directives regarding

electronic, i.e. Directive 2011/83/EU on consumer rights, Directive 95/46/EC on the protection

of individuals with regard to the processing and free movement of personal data.

3.6.2 Intellectual property law

Intellectual property (IP) law is one of the megatrends that emerged under the legal dimension

and its trends are patents and data sovereignty.

“Some industries such as pharmaceutical are expecting lower entry barriers (i.e. growing

completion) due to the high number of patent expirations between 2013 and 2018” [305].

Intellectual property law entails rules for securing rights to inventions but is a key challenge

for companies operating in China, Russia, and India. It is estimated that in China there were

nearly 80% IP thefts from U.S.-headquartered organizations in 2013, while in Europe the loss

of IP in China reduced potential profits by 20%. Currently, China has released a new plan on

protection of intellectual property rights for the period 2016-2020. 3D printing would also lead

to several issues regarding the intellectual property and when companies and governments

will solve it, this technology would bring large scale of open innovation [267].

Data exchange is considered to be a “big topic”. It is not about normal email correspondence

or just transferring financial and tax data to the authorities, but on a veritable exchange of data

between companies, for example, from within a supply chain like provisioning and inventory,

production processes, maintenance and the supply status of products. Information about

program source codes, construction drawings, requirement documents, simulation models,

data for forward quality planning and even commercial and contract documents are already

being exchanged between companies.

In addition, more than 80 % of the companies believe that digitisation will have a strong

influence on their company [268]. Currently, three out of four companies already exchange

data [268]. Furthermore, 74 % of the companies assume that the demand for data exchange

will increase in the medium term [268]. Data exchange is the basis for added value processes

today [268]. Regular or comprehensive data exchange at 63 % of companies. Moreover, 62

% of data exchange is done with companies other than customers and suppliers, 15 % of

which correspond to direct competitors (see Figure 3-101).


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Figure 3-101: Total Data exchange between companies as an essential feature of digitisation [268]

Large enterprises state even more often than SMEs that they exchange data with other

companies (see Figure 3-102). In large companies data exchange takes place in eight out of

ten companies. Regarding SMEs, numbers are not quite so high but it is still the majority at

seven out of ten companies.

Figure 3-102: Data exchange currently carried out by companies with other companies or institutions [268]

Inter-company data exchange, mainly occurs with customers and suppliers (see Figure 3-

103): eight out of ten companies that exchange data with other companies do it with their

customers (83 %). Furthermore, every second company that exchanges data with other

companies shares data with their suppliers (53 %).


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Figure 3-103: 10 types of company currently involved in data exchange [268]

Regarding the supply chain processes in the companies, the majority of company

representatives consider data exchange with customers, suppliers or other companies to be

regular or even comprehensive (63 %). The intensity and regularity of data exchange closely

correlate to the size of the companies. Regular or comprehensive data exchange with other

companies (see Figure 3-104) is conducted in 70 % of the large enterprises and in 61 % of

the medium-sized enterprises according to the respondents’ observations. In contrast, only

27% of the large enterprises carry out sporadic or no data exchange at all according to the

company representatives. In the medium-sized companies a good 38% of the respondents

answered that there is no, or at most, sporadic data exchange.

Figure 3-104: Regularity of data exchange with other companies according to company size [268]

With respect to the use of today’s possibilities for data exchange, mainly opportunities for

improved customer relations will emerge, according to the respondents’ point of view.

Respondents from the companies have very high expectations when it comes to optimising

company processes and increasing the efficiency of communication with suppliers. In the


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context of operative questions regarding customer relations, operational processes and

communication with suppliers, there is general agreement that data exchange provides

significantly improved opportunities (see Figure 3-105).

Figure 3-105: Opportunities provided by the present possibilities for cross-company data exchange [268]

The biggest obstacle for data exchange with other companies via conventional business

platforms is related to the fear that core data and business secrets could be exposed (see

Figure 3-106). The majority also consider problematic the impossibility to check who is going

to read the company’s own data in case they are uploaded to a conventional platform.

Particularly critical with respect to the two issues are security-sensitive companies which are

very much involved with looking into cyber security topics in general. Technology, IT and

communication companies and semi-governmental institutions tend to be represented more

while manufacturing companies were represented less than average in this group. In addition,

55 % of the respondents from the 210 companies and institutions perceive as a (very) big

obstacle the existence of no liability regulations in place to deal with cases of infringement 5.

The least relevant barriers out of the six predefined obstacles seem to be concerns that the

platforms are not able to achieve the desired cover and critical mass to make exchange an

interesting possibility. Practically every third (35 %) respondent awards only points 1 or 2 for

that on the scale.


97

Figure 3-106: Obstacles which mean companies do not approve of data exchange

on conventional platforms [268]

Data sovereignty refers to the concept that digital data is subject to the laws or legal

jurisdiction of the country where the cloud provider stores data. Many of the concerns

surrounding data sovereignty relate to the enforcement of privacy and compliance regulations,

including whether data stored in a foreign country can be subpoenaed by either the client’s or

the host country’s government [313]. For example, the impact of US legislation on data stored

in Europe came under discussion [314]. In the next 18 to 24 months, more companies will

begin working to find the right balance between control and accessibility as part of the growing

trend toward enterprise data sovereignty [315]. Companies will develop techniques for

managing, and unlocking the value of an increasingly vital enterprise asset [315]. For

example, the decentralised structure of blockchain ledgers and requires personal verification

methods such as biometrics [316]. Another important element of blockchain is its usage of

zero knowledge proofs to manage data [316]. Thus, users can disclose their ownership of

certain certifications while the data is hashed. For example, a use runs credit check while

handling credit history data in encrypted form, so if the data were stolen it would be useless

[316].

Industrial Data Space enables companies to share data with other market participants in a

simple, regulated and self-determined way so that the data providers do not have to expose


98

their sensitive or profitable data [268]. On the other side, data users can get access to data

they could not access otherwise and thus generate added value. Industrial Data Space is a

secure peer-to-peer data network, not a cloud. Every company that wants to participate can

become both a data provider and a data user. Networking with other participants in Industrial

Data Space is conducted via software (a secure gateway in a certain area of the internet), the

so-called connector, by means of which the search for other companies, data usage control

and the selection of the desired security level is conducted [268]. The Industrial Data Space

initiative is jointly funded by the worlds of politics, business (more than 100 companies from

12 countries) and research (at the centre is the Fraunhofer-Gesellschaft in Germany with 12

institutes and other European research institutions) and is organised and registered as an

open, non-profit association [268]. Industrial Data Space can only be used by companies that

have committed themselves beforehand to play by jointly defined rules with respect to security,

interoperability, data security and contract design. In case of infringements, there are clear

liability regulations. The data provider gets assurance that their data can only be used the way

they want it to be. So data users only gain access to the data according to the data provider’s

conditions [268]. Data sovereignty is guaranteed by the following three aspects: 1) Data

remain decentral at the connector of the respective data owner if desired, depending on the

application scenario and are not integrated in a joint data pool , 2) A precisely graded

certification concept according to the profile for each participant (as much security as

necessary) and 3) Security of infrastructure through new technological solutions and all

established security functions like encryption, access control, identity management and others

[268].

3.6.3 Social and Environmental regulations

Social and Environmental regulations is one of the megatrends that emerged under the legal

dimension and its trends are corporate social responsibility, emissions control

regulations, and waste and resources management regulations.

Corporate Social Responsibility aims to ensure that companies conduct their business in a

way that is ethical. This means taking account of their social, economic and environmental

impact, and consideration of human rights [317]. Over the last decade, corporate social

responsibility disclosure has increased dramatically. Almost 250 largest companies report on

corporate responsibility (see Figure 3-107). According to Standard & Poor's (S&P) 500, in

2015, 81% of the total companies were reporting and in 2017, just 18% of the S&P 500 were

not publishing sustainability reports (see Figure 3-108).

.


99

Figure 3-107: Growth in reporting since 1993 [318]

Figure 3-108: % of companies with CR reports [319]

63% the companies have their CR information independently assured (3-109). The scope of

assurance remained stable between 2013 and 2015, and 50% companies had external

assurance for the whole report, 34% have specific indicators assured and 5% have specific

chapters and 11% combination of chapters and indicators assured.

Figure 3-109: Growth in independent assurance of CR information [280]


100

For what concerns the second trend, emissions control regulations, EU legislation set

mandatory emission reduction targets for new cars sold in the EU specifically the fleet average

should be 130 grams of CO2 per kilometre (g/km) by 2015 and 95g/km by end of 2020. In

addition to this, there is a target to reduce the greenhouse gas intensity of fuels by 6% by 2020

and maritime transport should be cut by at least 40% from 2005 levels by 2050. Companies

in Germany and the UK have the highest rate of reporting on carbon emissions. German

companies score highest for quality of carbon reporting and Chinese companies score the

lowest (see Figure 3-110).

Figure 3-110: Reporting carbon emissions [280]

Another important branch for the environmental laws is waste and resources management

regulations. Europe aims to have 27% of its energy coming from renewable sources by 2030.

Pharmaceutical and chemical industries face increasing regulation regarding the usage and

disposal of resources [131]. The EU is setting the rules in order to secure rare earth metals by

boosting resource efficiency and promoting recycling. These concerns are also reflected in

the EU’s Raw Materials Initiative, as well as in several legislative efforts to address the rare

earths supply in the US (e.g. in the House, H.R. 761, the National Strategic and Critical

Minerals Production Act of 2013 or in the Senate, the Critical Minerals Policy Act of 2013-S.

1600). These regulations could lead to the relocation of carbon intensive companies and

specific industries to regions with not so strict regulations [105].

For what concerns management of WEEE, legislations in many countries have focused their

attention to this issue: in 2014, 44% of the world’s population was covered by legislation on

WEEE, now the percentage is increased to 66% but more efforts must be made to enforce,

implement, and encourage more countries to develop policies for WEEE treatment [358].

WEEE landfilling is still an issue across the globe in both developed and developing nations,

even if in the former the landfills are controlled whilst in the latter in many cases they probably

are not and in some cases, are actually open dumps. Hence, potential environmental impacts

are more acute in developing economies. A better understanding and better data on WEEE

will contribute towards the achievement of several goals of the 2030 Agenda for Sustainable

Development [358]. It will help address the Sustainable Development Goals (SDGs) related

to environmental protection (Goals 6, 11, 12, and 14) and health (Goal 3). It will also address

Goal 8 that focuses on employment and economic growth, since the sound management of

e-waste can create new areas of employment and drive entrepreneurship. The share of waste


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to be recycled would rise to 70% by 2030, from 44% today due to waste legislation. Currently

people do not know about the impacts of e- waste and there is a low number of recycling

activities almost all over the world (see Figure 3-111). The situation is gradually changing due

to strict regulatory frameworks.

Figure 3-111: Global e-waste management market [320]

Environmental

Two megatrends emerged under the environmental dimension namely climate change and

resource scarcity. Table 3-7 provides the megatrends with the respective definition,

references, and list of trends.

Table 3-7: Megatrends and trends in the environmental dimension

Megatren

ds

Megatrends definition Megatrends References Trends

Climate

change

Climate change can be defined

as a “a change in global or

regional climate patterns, in

particular a change apparent

from the mid to late 20th century

onwards and attributed largely to

the increased levels of

atmospheric carbon dioxide

produced by the use of fossil

fuels” [325]

[1];[13];[15];[24];[30];

[31];[37]; [70];[79];[83];

[91];[130];[132];[146];[151];

[152];[321];[322];[323]

Pollution

Resource

scarcity

Scarcity defines a resource that

is finite or limited (e.g. clean air,

copper), and it also can be

defined as “the lack of adequate

supply to meet demand” [326].

[1];[13]; [20]; [22]; [23];

[24];[25]; [27];[29];[30];

[31];[34];[65];[70]; [71];

[72]; [73]; [74];[75];[76];

[78]; [80]; [83];[85]; [87];

[88];[90];[91];[116];[124];

Lack of

resources

such as

water,

land,

energy,


102

[131]; [132]; [134]; [135];

[136]; [145]; [146]; [147];

[152]; [155]; [164]; [304];

[321]; [324]

food and

rare earth

elements

Waste

increase

3.7.1 Climate change

Climate change is linked with rising atmospheric CO2 concentration and thus rising

temperatures: in the last years this rising has been so relevant that the period 2011-2015 was

the hottest on record [326]. Climate-related disasters are escalating causing huge economic

damage and food insecurity. Sea level rise, extreme heat, heavy downpours, prolonged rains,

flooding along rivers, lakes and in cities are exceeding the limits of flood protection

infrastructures that were designed according to historical conditions. These climatic conditions

are affecting the capacity and reliability of transportation systems in many ways and damages

are projected to increase in the future with continued climate change [322]. The literature on

economic cost of climate change to the transportation sector is still scarce [322] albeit it is

rapidly evolving [323].

According to the European Environment Agency (EEA) [323], the potential climate impacts on

the transport infrastructure were assessed by United Kingdom, Spain, Germany and

Switzerland. The evaluation in UK highlights extreme weather events as the main challenge

for the operation and maintenance of infrastructure. In the US the annual cost of highway

congestion is estimated about $100 billion and the weather accounts for about 15% of total

delay. The annual cost of airline delay is about $33 billion and weather accounts for more than

a third of the delays. The growth of the frequency of extreme events will increase traffic and

aviation delays [323]. The majority of natural disaster events in some countries in Europe are

storms, but flood and mass movements are also significant. Figure 3-112 presents the number

of loss events and fatalities, and the financial impact of natural disasters in EEA members

countries between 1980 and 2011 [323].


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Figure 3-112: Natural disasters in EEA member countries [323]

Pollution is the main trend of climate change. Pollution is the addition of any substance (e.g.

liquid) or any form of energy (e.g. heat) to the environment at a rate faster than it can be

dispersed or stored in harmless form [328]. The major kinds of pollution are air pollution, water

pollution, and land pollution. Air, water, soil pollutions are interlinked (see Figure 3-113).

Figure 3-113: Air, water, soil pollutions [329]

The major causes of air pollution are the release of carbon dioxide and greenhouse emissions

into the atmosphere. “Carbon dioxide (CO2) is a colourless, odourless and non-poisonous gas

formed by combustion of carbon and in the respiration of living organisms and is considered

a greenhouse gas”. Emissions represent “the release of greenhouse gases and/or their

precursors into the atmosphere over a specified area and period of time” [330]. Global


104

greenhouse gas emissions reached approximately 52.7 gigatonnes CO2 and over the past

decades will increase with small variations [331]. Global CO2 emissions from fossil fuels and

industry (account for about 68 %) are the major sources (see Figure 3-114) of total global

greenhouse gas emissions [331].

Figure 3-114: Carbon dioxide emissions from fossil-fuel use and industry [331]

The global emissions from fossil fuels and industry are projected to grow 2% by 2017 (see

Figure 3-115). Chinese emissions are projected to rise by 3.5% in 2017 (responsible for

around 28% of the global total emissions) whereas U.S. emissions are projected to decline by

0.4% [332].

Figure 3-115: Global CO2 emissions, 2000-2017 [332]

Luxembourg achieved the highest reduction in per capita emissions between 2005 and 2015

but also other countries achieved high reductions such as Ireland, Denmark, Greece, Belgium,


105

Finland and Cyprus [333]. Emissions were lowest in some eastern and southern European

countries as well as in Sweden (see Figure 3-116).

Figure 3-116: Greenhouse gas emissions per capita, by country, 2005 and 2015

(Tonnes of CO2 equivalent) [333]

It is projected that greenhouse gas (GHG) emissions in the EU will exceed the 2020 target

(see Figure 3-117), thus existing and already planned measures are not enough to meet

2030 target, minimise greenhouse gas emissions by 40 % by 2030 [333].

Figure 3-117: Greenhouse gas emissions and projections, 1990–2050 [333]

As mentioned before, another type on pollution is the soil contamination. A “contaminated soil

has exceeded its capacity for natural attenuation for one or more substances, and

consequently passes from acting as a protector to cause adverse effects to the water system,

the atmosphere, and organisms” [334]. Soil contaminants can be organic and inorganic or


106

particulate contaminants [334]. Municipal and industrial wastes account for (37%) the highest

percentage for soil contamination, followed by the industrial/commercial sector (33%). Mineral

oil and heavy metals contribute the highest percentage around 60% to soil contamination.

Concentration of heavy metals in soil assessed in EU from LUCAS soil survey and it is found

that 6.24% agricultural soils estimated to require local assessment and eventual remediation

[335]. Figure 3-118 shows that most regions in the EU have high percentages of samples

which are above the investigation thresholds.

Figure 3-118: % of samples with concentrations above the threshold value in all the LUCAS samples [335]

The main impacts of climate change are permafrost damage, sea level rise and storm surge;

heavy downpours, prolonged rains and floods; extreme heat; low water level, droughts and

wildfire.

The global mean sea-level rise (see Figure 3-119) is around 1.7 mm/year over the 20th century

and satellite measurements show a rise of around 3 mm/year over the last two decades [323].

The most glaciers in the European glacial regions are in retreat. In the European Alps, glaciers

have lost approximately two thirds of their volume since 1850, and there is a clear acceleration

since the 1980s. European permafrost has shown a general warming trend in the past 10–20

years, and the greatest warming is in Scandinavia and Svalbard [323]. In the 1990s, the

Greenland ice sheet was losing about 100 billion tonnes of ice per year. The ice losses

increased and were, in average, 250 billion tonnes a year between 2005 and 2009. The

melting of the Greenland Ice Sheet in recent years contributed up to 0.7 millimetres a year to

global sea-level rise, representing approximately one quarter of the total sea-level rise [323].

Rising sea level intensify storm surge and coastal flooding, posing risks to the reliability and

capacity of coastal transportation infrastructure, including temporary or permanent flooding of

airports, ports and harbours, roads, rail lines, tunnels and bridges [322].Some impacts of rising

sea level for ports include bridge clearance, that may not be appropriate to allow safe passage

of large vessels and the inundation of the main access roads to the ports [323].


107

Figure 3-119: Change in global mean sea level [323]

Severe precipitation events, hail and flooding may damage transportation infrastructure such

as roads, bridges, and rail systems, and also the vehicles that use them [322]. In Europe,

precipitation changes show more spatial and temporal variability than temperature (see Figure

3-120 and Figure 3-121). Since the middle of the 20th century, annual precipitation has been

increasing across most of northern Europe, most notably in winter. At the same time, annual

precipitation is decreasing in parts of southern Europe [323]. Changes in precipitation patterns

affect transportation systems and streamflows based on more frequent and intense rainfall

could increase the likelihood of bridge damage [322]. There are many problems caused by

intense rainfall: the obstruction of drainage systems for highways, tunnels, airports, and city

streets, the increase of the river flows can potentially weaken bridge foundations, there is the

risk of more accidents and delays in the roads, as well as cancelation and delays of airline

and road traffic [322].

In the next decades, all modes of transportation will be affected by increasing temperatures

and the impact would be severe. Climate models project that extreme heat will become

longer lasting, more frequent and more intense [322]. Some consequences of higher

temperature on infrastructures are: asphalt deterioration, buckling of pavements and rail lines

and damage of the expansion joints on bridges and highways. High air temperatures can affect

aircraft performance and reduce air craft operation [322]. Heat waves have increased in

frequency and length in Europe, and the average temperature for the European land area

between 2002 and 2011 is 1.3 °C above the pre-industrial level. This is the warmest decade

on record [323].


108

Figure 3-120: Global average temperature change [323]

Figure 3-121: Projections of extreme high temperatures [323]

As an example of related impact, the average annual welfare loss due to low water levels on

the Rhine was calculated at EUR 28 million over a period of 20 years (see Figure 3-122). The

year of 2003 was an extreme low-water year and it was associated with a welfare loss of EUR

91 million [323]. Drought increases the probability of wildfires, intensifying air pollution and

affecting the visibility severely enough to close roads and airports. Drought can disrupt barge

traffic and lower vessel drafts on navigable rivers [322].


109

Figure 3-122: Projected change in minimum river flow [323]

3.7.2 Resource scarcity

The megatrend of resource scarcity is influenced by the global population, increasing demand

for resources from affluent consumers in countries such as China and India [336]. Lack of

resources such as water, food (also land), oil (energy scarcity), and rare earth elements

and increase of waste are the main trends of resource scarcity.

3.7.2.1 Water scarcity

Water scarcity has been identified as a higher risk than oil [337]. Water scarcity is when the

annual renewable water supplies are less than 1,000 cubic meters per person. 1.1 billion

people worldwide lack access to water, and a total of 2.7 billion find water scarce for at least

one month of the year [338]. Around 700 million people face the issue of water scarcity and

1.8 billion people are estimated to be in countries or regions with absolute water scarcity by

2025 [339]. As population grows, more people will require food, which means more water.

Demand for freshwater is projected to be 40% above current water supplies by 2030. Demand

from manufacturing industry accounts for 22% of global freshwater withdrawal (see Figure 3-

123), and with significant growth in manufacturing activities, particularly within developing

countries, global manufacturing water consumption will grow more than 5% by 2050, over a

year 2000 baseline, from 245 to 1552 billion m3 [340]. Agriculture accounts for roughly 70%

of total water consumption which will increase by 60% by 2050, over 2005-2007 levels [339].

Water demand also for energy will also grow by 85%, as energy demand is expected to grow

as much as 20% by 2030 [339].


110

Figure 3-123: Projected growth in global water consumption by sector [340]

Almost 50% of the people suffering from water scarcity live in India and China (see Figure 3-

124). 14 of the 33 countries that will suffer water shortages in 2040 are in the Middle East

such as Kuwait, the United Arab Emirates [341]. The population growth in these countries will

have an impact on water resources and the per capita water availability will decline by half by

2050. Even some European countries face occasional or local water stress [321]. Freshwater

resources show the largest availability per capita in the EU in Finland, Sweden and Slovenia

and the lowest in Cyprus, Belgium, Spain and Malta [342].

Figure 3-124: Water consumption patterns by sector and regions [343]

3.7.2.2 Land and food scarcity

Land scarcity has been identified as an issue especially in densely populated cities (see Figure

3-125). For example, the industrial land in Greater London declined from 8.3 thousand

hectares in 2001 to 7 thousand hectares in 2015 [148]. Demand for food will also increase,

mostly driven by population growth, better living conditions in developing countries and

changing eating habits (see Figure 3-126).


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Figure 3-125: Worldwide evolution of land use [321]

Figure 3-126: Evolution of per capita food consumption (kcal/person/day) [321]

Despite the rise in food demand by 2030 (+21%), the area of cropland will slightly increase

due to efficiency practices in agriculture (see Figure 3-128).

Figure 3-127: Food price development and its relation to water and climate change [321]

The EU wastes 89.2 million tonnes of food each year. The UK is the most wasteful country

while Malta is the least wasteful country (see Figure 3-128). Western countries have a far

higher ratio of personal waste. Waste for cereals, animal fats and cream are considered


112

avoidable, as they are edible, whereas avoidable food waste for fruit (49.41%), meat (53.10%)

and fish (51.03%) is relatively lower (see Figure 3-129).

Figure 3-128: EU food waste per year (tonnes) [354]

Figure 3-129: Waste per person by food type [354]


113

3.7.2.3 Energy scarcity

Growing population, GDP growth, increasing urbanisation and expanding middle class, drive

increase the energy demand [321]. The energy demand worldwide is forecasted to increase

by 28% between 2015 and 2040. Residential and commercial energy demand will grow 70%

from 2015 to 2040, whereas industrial energy demand will raise by 50% (see Figure 3-130).

Energy demand for transportation more than doubles between 2015 and 2040, however it

accounts only 2% of total energy use.

Figure 3-130: Energy demand by sector [344]

Demand growth for commercial transport will double in comparison with light-duty vehicles by

2040 (see Figure 3-131). From the commercial transport, the heavy-duty vehicles energy

demand will rise by 45% from 2014 to 2040 especially in China and in India. The energy

demand will increase for the ships, planes and trains that carry products to factories and to

markets by 65% from 2014 to 2040 (see Figure 3-132).

Figure 3-131: Global transportation demand [344]


114

Figure 3-132: Global Commercial transportation demand by different modes of transportation [344]

China and India will account for most 51% of the increase in energy demand by 4.0% or 3.6%

between 2015 and 2040 influenced by the rising income and growth [345]. Energy demand

will grow in Africa and the Middle East by 51% and 45%, respectively, between 2015 and 2040

[345]. The energy demand in Europe and Eurasia will increase only by is 2% due to the low

population growth in Russia. 2 billion people have no access to electricity (see Figure 3-133).

The developing world will account for 65% of the world’s energy consumption.

.

Figure 3-133: Energy demand by region [346]

Petroleum and other liquids continue to be the largest source of energy especially in the

industrial and transportation sector, but its world marketed energy consumption will decline

from 33% in 2015 to 31% in 2040 due to high oil prices. For example, liquid fuels usage for

China and India transportation is expected to grow by 36% and 142% respectively from 2015

to 2040. Countries such as the US, China, India, Brazil are the major crude oil consumers.


115

They account for 52% of the global oil demand. The oil demand is driven by strong economic

growth, political development in oil exporting countries and is expected that the oil price will

be $70 per barrel by 2020 (see Figure 3-134). By 2025, the price will rise to $86 per barrel and

$117 per barrel by 2050 [347]. Rising oil prices lead to higher logistics costs.

.

Figure 3-134: Crude oil price projection [347]

Renewables and nuclear power are expected to be the fastest-growing energy sources, with

an average increase of 2.3% and 1.5% per year respectively between 2015 and 2040 (see

Figure 3-135). There will be less hydropower projects due to less available resources and

environmental concerns which will lead to the decline of the hydropower share from 71% in

2015 to 53% in 2040. It is expected that the use of wind and solar as a renewable energy will

be high reaching 1.4 trillion kilowatt-hours in 2040 as technologies will be more cost

competitive. Natural gas usage will grow in the non-OECD countries where it will be used

mainly as a fuel for the electric power and for industrial purposes (e.g. chemical, refining

industries). The coal consumption declines and China is the largest consumer of coal in 2040

(i.e. about 73 quadrillion Btu).

Figure 3-135: World energy consumption by energy source [347]

3.7.2.4 Rare earth elements scarcity

Rare earth elements are used in high technologies, medical devices, and military defence

systems, in emerging clean energy, e.g. to produce electric vehicles, wind turbines, batteries,


116

and energy-saving lighting. For example, rare earth elements demand from clean technologies

(specifically dysprosium and neodymium) will reach 51.9 thousand metric tons in 2030, as

shown in Figure 3-136.

Figure 3-136: Global demand for REO from clean technologies [349]

While the EU is self-sufficient in construction minerals, it is dependent for rare earth elements

on other parts of the world. Supply risks stem from the fact that production is concentrated

mainly in China (see Figure 3-137).

Figure 3-137: The distribution of global rare earth resources by principle deposit type and country [349]

China’s dominance of the rare earth elements market and the implementation of tax and export

quotas, affected the availability, continuous supply and the prices of these resources [350].

Manufacturers, especially in the automotive and electronic/electrical industries, have to

compete in order to access resources such as rare earth elements since supplier countries

such as China are consuming more resources than previously and restricting their exports

[351]. For example, Honda recycles rare earth metals extracted from nickel-metal hydride

batteries [352]. Rare earth elements are critical components in consumer electronics such as

televisions, computers, cameras, and mobile phones and even if recycling technologies are

still in the early stages of development due the different challenged involved the limited

availability of these materials calls for a future increase in their reuse.


117

3.7.2.5 Waste increase

As countries get richer, they create more garbage. For instance in Europe countries such as

Germany and France were producing the highest percentage of waste (see Figure 3-138 and

Figure 3-139). Economic growth in emerging economies is raising living standards and

reducing poverty, but there are also side effects, such as more waste of all kinds [356]. To

deal with it, countries need to build up waste-management systems that can reduce the risks

to human and ecological health and curtail the degradation of urban and natural landscapes.

Municipalities in developing countries are already spending 20 to 50 % of their budgets on

solid-waste management [356].

Figure 3-138: First 10 European countries for generation of

waste in 2014 (tons) [357]

Figure 3-139: kilograms per capita of waste generated by the first

10 European countries [357]

Figure 3-140 shows the amount of hazardous waste generated annually in the EU from all

sectors of the economy, households and waste treatment (secondary waste) is included.

Figure 3-140: Municipal Waste Treatment, EU-27 (kg per capita) )[353]

0

50.000.000

100.000.000

150.000.000

200.000.000

250.000.000

300.000.000

350.000.000

400.000.000

450.000.000

0

5.000

10.000

15.000

20.000

25.000

30.000


118

According to the World Bank [355], cities generated about 1.3 billion tonnes of solid waste.

This volume is expected to increase to 2.2 billion tons by 2025 (see Figure 3-141). Moreover,

it is expected that waste generation rates will more than double over the next twenty years in

lower income countries. Globally, solid waste management costs will increase from today’s

annual $205.4 billion to about $375.5 billion in 2025. The global impacts of solid waste are

growing fast. Solid waste is a large source of methane, a powerful GHG that is particularly

impactful in the short-term. The recycling industry, with more than two million informal waste

pickers, is now a global business with international markets and extensive supply and

transportation networks. By 2025 the amount of municipal solid waste (see table 3-8 and

Figure 3-142) will likely increase to 4.3 billion urban residents generating about 1.42

kg/capita/day of municipal solid waste (2.2 billion tonnes per year).

Figure 3-141: Waste generation projection for 2025 by region, 2012 [355]


119

Table 3-8: Rate of waste collected by region, 2012 [355]

2012 2025

Region Acronym

region

Urban

population

(millions)

Waste

generation

(tons/day)

Urban

population

(millions)

Waste

generation

(tons/day)

Africa ARF 260 169.119 518 441.840

east Asia and

Pacific

EAP 777 738.958 1.229 1.865.379

Eastern and

Central Asia

ECA 227 254.389 239 354.810

Latin America

and Caribbean

LCR 399 437.545 466 728.392

Middle East and

North Africa

MENA 162 173.545 257 369.320

Organisation

for Economic

Co-operation

and

Development

OECD 729 1.566.286 842 1.742.417

South Asia SAR 426 192.410 734 567.545

Total 2.980 3.532.252 4.285 6.069.703

Figure 3-142: Waste Collection Rates by Region, 2012 [355]

The following Figure 3-143 represents the first 10 European countries per percentage of

recycled waste in 3 years (2010, 2012, and 2014). Most of the countries have increased the

recycling rate.


120

Figure 3-143: Recycling rate of all waste excluding major mineral waste [357]

According to United Nations University (UNU) [358] in 2016 the world generated 44.7 million

metric tonnes (Mt) of WEEE and only 20% was recycled through appropriate channels (see

Figure 3-144). The growing amount of e-waste is the result of several trends. The global

information society is growing at great speed. It is characterized by an increasing number of

users and rapid technological advances that are driving innovation, efficiency, social and

economic development. By 2017, close to half the world’s population uses the internet and

most people in the world have access to mobile networks and services and will have more

than one information and communication technology (ICT) device, and replacement cycles for

mobile phones and computers, and also for other devices and equipment, are becoming

shorter. At the same time, disposable incomes in many developing countries are increasing

and a growing global middle-class is able to spend more on electrical and electronic

equipment, consequently generating more e-waste. Current trends suggest that the amount

of e-waste generated will increase substantially over the next decades, and that better data to

track these developments are needed.

0

10

20

30

40

50

60

70

80

90

100

2010

2012

2014


121

Figure 3-144: Global WEEE generated and estimated [358]

To improve the environmental management of WEEE, to contribute to a circular economy and

to enhance resource efficiency, the improvement of collection, treatment and recycling of

electronics at the end of their life is essential. WEEE can be regarded as a resource of valuable

metals such as copper, aluminium and gold; when such resources are not recovered, raw

materials have to be extracted and processed to make new products, resulting in significant

loss of resources and environmental damage necessitated by mining, manufacturing,

transport and energy use. But only 20% of WEEE generated is documented to be collected

and recycled. The total value of all raw materials present in e-waste is estimated at

approximately 55 Billion Euros in 2016. Circular economy models need to be adopted to

encourage closing the loop of materials through better design of components, recycling,

reusing, etc., while mitigating the environmental pollution. Therefore, the circular economy

concept offers huge economic and employment opportunities for e-waste management. The

total amount of WEEE (ton) collected from 2011 to 2015 has increased (see Figure 3-145 and

Figure 3-146). In the second one, the first 10 countries in EU per amount of WEEE collected

in 2015.

Figure 3-145: WEEE collected in Europe (EU28) [353]

3.200.000

3.300.000

3.400.000

3.500.000

3.600.000

3.700.000

3.800.000

3.900.000

2011 2012 2013 2014 2015

ton

s


122

Figure 3-146: First 10 countries per total WEEE [353]

In the Figure 3-147 the most important categories of WEEE are presented and it can be seen

that large household appliances is the dominant product category in all countries.

Figure 3-147: WEEE by categories in the first 10 countries

per total WEEE collected, 2015 [353]

0

50.000

100.000

150.000

200.000

250.000

300.000

350.000

400.000

ton

s

Large householdappliances

Small householdappliances

IT andtelecommunications equipment

0100.000200.000300.000400.000500.000600.000700.000800.000

Ge

rman

y

Un

ited

Kin

gdo

m

Fran

ce

Spai

n

Po

lan

d

Ne

the

rlan

ds

Swed

en

Bel

giu

m

Au

stri

a

Cze

ch R

epu

blic

ton

s


123

4 Conclusion

The goal of this deliverable is to present an overview of the trends and megatrends that can

influence discrete manufacturing, process manufacturing and the logistics industry and thus

define the future of supply chains. In particular, on the basis of 6 specific dimensions of the

PESTLE analysis (i.e. political, economic, social, technological, legal, environmental), this

report has identified 22 megatrends and 66 related trends were also associated (see Figure

4-1). The identification of megatrends and their trends is critical for the generation of future

industrial scenarios which is the objective of the Task 2.2. More specifically, the

trends/megatrends will be further adapted/updated in T2.2 where the development paths will

be created based on them. The generation of such scenarios will forge a strategic research

agenda and policy recommendations to develop measures so that supply chains are able to

fulfil their full potential for contributing to European economic growth and prosperity.

Figure 4-1: Megatrends and trends

These trends and megatrends have been identified based on an extensive literature review

that was held with the support of all the partners. A systematic analysis of almost 350 reports

allowed to categorise the content along the six dimensions. The literature analysis was based

not only on scientific publications, but also on sectoral studies, other strategic roadmaps,

governmental reports, visionary insights and data from Eurostat. The analysis was also

supported by the expert workshop, an interactive session organised by Aston University where

further insights on the trends have been collected and merged.


124

Megatrends/ trends have different implications on the future of supply chains and each of them

could affect different aspects of the supply chain (e.g. climate change impacts on

infrastructures such as logistics and transportation, while pollution which is a trend of the

climate change leads to sustainable manufacturing processes, in the same way, for what

concerns the political dimension, e.g. an increase in custom duties can change both the goods

flow and the production location).

The next step towards the scenario formulation will be the creation of the development paths

for each megatrend or, if necessary, for the related trends in order to exploit, on the basis of

literature and other insights, the possible evolution of the megatrend itself and enable the

creation of new scenarios. The probability of occurrence of these paths for the year 2030 will

be then assessed and evaluated through evidences and specific surveys with experts.

Efforts have been made to produce a detailed and systematic analysis since the vast amount

of information available on these topics and the use of different terminology (often to describe

the same trend or concept) made the analysis challenging because of megatrends/trends

complementing or contradicting each other. Given the dynamic, complex and fast evolving

nature of modern supply chains it may be possible that certain trends may not have been (fully

or partially) included in this deliverable or they received less emphasis. Other

trends/megatrends could arise during the next steps and would be included in the future

analysis.

Besides its contribution for the next tasks of the project, this report can be useful for European

companies as they can use it as a framework for the identification of changes and

opportunities, as well as challenges and threats along the six dimensions, and consequently

improve the competitiveness of their future supply chain.


125

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Annex A: List of Acronyms

BRIC Brazil, Russia, India, China and South Africa

CBP Customs and Border Protection

C-TPAT Customs-Trade Partnership against Terrorism

PESTLE Political, economic, social, technological, legal and environmental