DETECTING OPPORTUNITIES AND CHALLENGES FOR … · This report is the final report of the Detecting...

1 DETECTING OPPORTUNITIES AND CHALLENGES FOR AUSTRALIAN RURAL INDUSTRIES FINAL REPORT

DETECTING OPPORTUNITIES AND CHALLENGESFOR AUSTRALIAN RURAL INDUSTRIES

FINAL REPORT FEBRUARY, 2018

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© 2018 AgriFutures Australia. All rights reserved.

ISBN 978-1-74254-992-7 ISSN 1440-6845

Horizon Scan Final Report: Detecting opportunities and challenges for Australian rural industries Publication No. 18/009 Project No. PRJ-010512

The information contained in this publication is intended for general use to assist public knowledge and discussion and to help improve the development of sustainable regions. You must not rely on any information contained in this publication without taking specialist advice relevant to your particular circumstances.

While reasonable care has been taken in preparing this publication to ensure that information is true and correct, the Commonwealth of Australia gives no assurance as to the accuracy of any information in this publication.

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Researcher Contact Details

Name: Dr Grant Hamilton Address: QUT, GPO Box 2434, Brisbane, QLD 4001 Phone: +61 3138 2318 Email: [email protected]

In submitting this report, the researcher has agreed to AgriFutures Australia publishing this material in its edited form.

AgriFutures Australia Contact Details

Building 007, Tooma Way Charles Sturt University Locked Bag 588 Wagga Wagga NSW 2650

02 6923 6900 [email protected] www.agrifutures.com.au

Electronically published by AgriFutures Australia in April 2018 Print-on-demand by Union Offset Printing, Canberra at www.agrifutures.com.au or phone 1300 634 313

AgriFutures Australia is the trading name for Rural Industries Research & Development Corporation (RIRDC), a statutory authority of the Federal Government established by the Primary Industries Research and Development Act 1989.

Detecting Opportunities and Challenges for Australian Rural Industries, Final Report:

February, 2018. Report by Queensland University of Technology for Agrifutures Australia.

REPORT CONTRIBUTORSDr Grant Hamilton, Dr Levi Swann, Dr Sangeetha Kutty, Prof Greg Hearn, Assoc Prof

Richi Nayak, Dr Jared Donovan, Dr Debra Polson, Dr Markus Rittenbruch, and Prof

Roger Hellens.

ACKNOWLEDGMENTSThe research provider Queensland University of Technology acknowledges the financial

assistance of Agrifutures Australia in order to undertake this project.

The contributions of members of the Australian rural industries, who gave their time to

participate in surveys as part of this research, are also acknowledged.


TABLE OF CONTENTS

Executive Summary

Introduction

Summary of Watchlist

Impacts on Australian Rural Industries

Reflection on Approach

Conclusion

References

Appendix A: Approach and Project Streams

Appendix B: Focus Areas and Sub-focus Areas

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EXECUTIVE SUMMARY

This report is the final report of the Detecting Opportunities and Challenges for Australian

Rural Industries Project. The project was conducted as part of Agrifutures Australia’s

initiative to anticipate technologies that present potential opportunities and challenges

to Australian rural industries. Developing this capability is critical for managing risk and

informing future directions. Over the course of the project, a methodology was developed

in line with this initiative. It incorporated a mix of foresight methodologies, including data

mining, literature review, Delphi questionnaires and visualisation. Each of these methods

were used in an interactive approach that focused on detecting emerging technologies

from a range of different industries, and then through systematic assessment, reposition

and imagine those selected technologies in an Australian rural context. The effectiveness

of this methodology is evident in each of the Horizon Scans completed to date. These

have led to a watchlist of emerging technologies that offer potential opportunities and

challenges to Australian rural industries. The purpose of this final report is to summarise

the watchlists and communicate the potential impact that these technologies have for

Australian rural industries.

SUMMARY OF WATCHLISTA total of twenty four emerging technologies were identified during the Horizon Scans.

These technologies have origins in a diverse number of domains, including material

science, artificial intelligence, robotics, genomics, and energy. The following table

summarises the technologies on the watchlist and the technology groupings we have

used in this report:


DATA DRIVEN • Smart Dust• Augmented Reality• Digital Twin• Labour Tracking• LoRaWAN• Smart Contact Lenses

GENOMICS AND BIOTECHNOLOGY • Plant Genome Sequencing• CRISPR• Microbiome

ROBOTICS AND ARTIFICIALINTELLIGENCE

• Collaborative Robots• Context-aware Computing• Natural Language Interfaces• Computer Vision• Human-in-the-loop Machine Learning• Wearable User Interfaces

BUSINESS MODEL INNOVATION • Blockchain• Distributed Production

RENEWABLE ENERGY • Perovskite Solar Cells• Sodium-ion Batteries• Solar Retransmission• Moisture Harvesting

ADVANCED MATERIALS • Programmable Materials• Metamaterials• Graphene

IMPACTS ON AUSTRALIAN RURAL INDUSTRIESHorizon Scan reports 1 to 4 explored the potential impacts and functional capabilities

of each of these technologies. This report explores how the technologies align with

the critical needs of Australian rural industries. Technologies were framed in relation to

the focus areas of Australian rural industries that were developed during the scoping

workshop at the beginning of the project. This led to the identification of three areas

that the identified technologies have the greatest potential to impact: efficiency and

productivity, skills and knowledge, and new products and markets.

Efficiency and Productivity are essential capabilities for Agriculture and are directly

related to profitability and competitiveness. Developing capabilities to improve efficiency

and productivity will be essential to deal with challenges such as climate change,

diminishing resources and an increasing demand for food and fibre. The identified

technologies have greatest potential impact for efficiency and productivity in relation to

the following focus areas and sub-focus areas:


A. PRIMARY PRODUCTION INPUTS, PROCESSES AND PRACTICES

• Viable Alternatives to Reduce Costs• Genetic Improvement• Post-farm Gate Consideration

D. SUPPLY CHAIN LOGISTICS • Relationships and Connectivity• Disruptive Technology in the Supply Chain• Optimisation of the Supply Chain

E. INDUSTRY SUSTAINABILITY • Environmental• Economic

Skills and Knowledge development will be essential for Australian agriculture in the

coming decades. The current workforce is aging and declining, and automation will

impact a large percentage of agriculture jobs in the future. The identified technologies

have greatest potential impact for skills and knowledge in relation to the following focus

areas and sub-focus areas:


• Information and Skills to Support Decision-making

C. ADAPTIVE CAPACITY OF PRIMARY PRODUCERS AND SECTORS

• Leadership to Initiate and Respond to Change• Skills and Knowledge to Implement Change

E. INDUSTRY SUSTAINABILITY • Social License• Economic• Perception

New Products and Markets are emerging in both local and global contexts. Young

and affluent consumers are conscious of the environment and looking for local and

sustainably sourced food. Meanwhile, a growing Asian middle class is demanding more

and better quality food. The identified technologies have greatest potential impact for

skills and knowledge in relation to the following focus areas and sub-focus areas:


• Genetic Improvement• Post-farm Gate Consideration

B. MARKET AND CONSUMERPREFERENCES

• Relationships and Connectivity• Disruptive Technology in the Supply Chain• Optimisation of the Supply Chain

E. INDUSTRY SUSTAINABILITY • Social License• Economic

FUTURE WORKMuch of the work completed during this project has demonstrated the importance of

technology confluence. In this report, technology confluence is an underlying feature.

This begins in the summary of the watchlist where clear technology grouping are evident

and have been expressed. In identifying specific areas of Australian rural industries

that the technologies have greatest potential impact, technology confluence is again

evident. Plausible futures that are explored show how the different technologies can


complement one another and deliver capabilities to address future challenges. This

notion of technology confluence is where the future direction of this work lies. Although

technology confluence is cited as something that often happens without planning, it is

possible to foster and prepare for it with appropriate management and an interdisciplinary

approach [64]. This process has already begun with the preparation of a parallel report

that outlines potential technology-driven agriculture industries that have the capabilities

to address the future challenges facing Australian rural industries.


INTRODUCTION

Fostering technology innovation is important for the rural industries. Technology

development and integration are both drivers of efficiency and productivity [1], [2], and

is therefore an essential part of ensuring profitability and competitiveness [3]. A strong

track record of technology integration has been a key part of Australian rural industries’

long-term competitiveness and economic viability [4]. Despite this track record, the

future promises new and significant challenges. A growing global population means

that more food will need to be produced than ever before while relying predominantly on

existing resources [5], [6]. Changes to the world’s distribution of wealth, highlighted by

Asia’s growing middle class, mean that there is an increasing demand for protein, and

other high value and resource intensive foods [6], [7]. Environmental threats including

climate change and resource availability [8], [9] make these challenges significantly

more difficult to address. It might not be possible to rely on existing technologies and

their incremental improvement in this future.

This report is a response to this context of an uncertain world and the role that technology

has in it. It is the final report of the Detecting Opportunities and Challenges for Australian

Rural Industries project, which is part of Agrifutures Australia’s initiative to anticipate

technologies that present potential opportunities and challenges to Australian rural

industries. Developing this capability to anticipate technology advancements helps to

inform research and development priorities, manage risk, and enhance competitiveness

[10]–[12]. With the early identification of emerging technologies, organisations can

position themselves to turn potential disruption into new opportunities, as well as mitigate

threats that might be a catalyst to failure [13].


In each of the four Horizon Scans that have preceded this final report, a diverse range

of emerging technologies were scanned, evaluated and synthesised to assess their

potential impact for Australian rural industries. Through this process, a final watchlist of

twenty four technologies has been compiled. The first section of this report summarises

this watchlist by outlining key categories of emerging technologies that have the

potential to impact Australian rural industries. Following this, the potential impacts

of the technologies are framed in relation to the five focus areas of Australian rural

industries that were identified at the commencement of the project. In doing this, a

series of speculative, yet plausible, futures are outlined. These demonstrate how the

projected capabilities of the technologies, and their confluence, might impact Australian

rural industries in the future. The final sections of this report conclude the project by

reflecting on the overall foresight methodology process employed and possible next

steps to take.


SUMMARY OF WATCHLIST

During the Horizon Scans, a total of twenty four technologies were identified to offer

significant opportunities and challenges to Australian rural industries. In this section of

the report, each of the identified technologies has been categorised and assigned to a

group to provide an overall picture of the key technology domains that have the greatest

potential impact for the Australian rural industries. A brief overview of each technology

group’s value and future outlook presented. Finally, grouped technologies are plotted

on a matrix measuring their potential impact and novelty in the context of Australian

rural industries. These values were obtained during iterative Delphi questionnaires

that were completed by young and innovative experts working in the Australian rural

industries. Measuring the potential impact of a technology in the context of Australian

agriculture, and the novelty of a technology compared to what is currently used, provides

an indication of the disruptive potential of each technology.


DATA DRIVENThe technologies comprising the data driven group are: Smart Dust, Labour Tracking,

Digital Twin, LoRaWAN, Smart Contact Lenses and Augmented Reality.

Data driven technologies will deliver more data and better insights to improve efficiency

and decision-making [14]. Today’s prevalence of connected smart objects and sensors

make it possible to represent and monitor the performance of complex networks of objects

[15]. Over-time, these technologies will trend toward being smaller, more efficient, and

more accurate. In some cases, nanoscale sensors will permeate the environment [16].

These sensor networks will link into advanced software ecosystems that are designed

to process massive volumes of data and will deliver contextual and actionable insights

in-real time [14], [17]. Human workers will tap into these data streams with immersive

technologies resulting in the blurring of the physical and digital world [18].

Figure 1 plots each of the data driven technologies based on their average impact and novelty ratings given by rural industries experts. Smart dust and LoRaWAN technologies were perceived to have the highest impact by rural industries experts. These ratings reflect two critical needs of Australian agriculture: access to communications infrastructure and the availability of farm data. Developing these capabilities is likely to have significant impact in the rural industries. The high novelty rating of smart dust reflects that it is a speculative technology in very early stages of development.

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LoRaWAN Smart Dust

AugmentedReality

Smart Contact Lenses

Labour Tracking

Digital Twin

FIGURE 1. IMPACT - NOVELTY MATRIX FOR DATA DRIVEN TECHNOLOGIES


GENOMICS AND BIOTECHNOLOGYThe technologies comprising the genomics and biotechnology group are: Plant Genome

Sequencing, CRISPR and Microbiome.

Advances in genomics and biotechnology are providing deeper knowledge of plant and

animal organisms. Over just a short period of time, genome sequencing techniques have

become highly accessible, in terms of both cost and speed of process [19]. Microbiome

analysis is becoming similarly accessible [20]. As knowledge is developed across the

spectrum of plant and animal types, and the environments they are grown in, better

planning and decision-making will be possible [19], [21], [22]. The emergence of CRISPR

in recent years is poised to transform plant and animal breeding. Already it is showing its

value in gene edited plants that grow more efficiently, are more resilient to pathogens,

and taste better [23]. Looking further ahead, advances in genomics and biotechnology

present compelling possibilities for future food systems.

Figure 2 plots each of the genomics and biotechnology technologies based on their average impact and novelty ratings given by rural industries experts. Each of the technologies in the genomics and biotechnology group were perceived to be of very high impact. With CRISPR and plant genome sequencing technologies perceived to be of very high novelty, the results suggest that rural industries experts view these technologies to have transformative potential. This is consistent with views conveyed in the literature.

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CRISPRMicrobiome

Plant Genome Sequencing

FIGURE 2. IMPACT - NOVELTY MATRIX FOR GENOMICS AND BIOTECHNOLOGY TECHNOLOGIES


ROBOTICS AND ARTIFICIAL INTELLIGENCEThe technologies comprising the robotics and artificial intelligence group are: Wearable

User Interfaces, Natural Language Interfaces, Human-in-the-loop Machine Learning,

Computer Vision, Collaborative Robots and Context-aware Computing.

Robotics and artificial intelligence technologies are advancing rapidly. In particular,

artificial intelligence has become a key strategy for many technology companies [24]. It

is already common for people to talk and give instruction to intelligent devices that can

respond in meaningful ways [15]. The development of robotics technology is actively

incorporating artificial intelligence technologies, such as computer vision and machine

learning, to enhance the capabilities of robots [25]. This will drive new robots that are

not restricted to routine and repetitive labour tasks, but that can work collaboratively with

humans on increasingly complex work. This collaboration will be the winning formula

to provide strategic and creative problem solving, as well as highly efficient and safe

working environments [14]. As the future of work takes shape over the coming decades,

the technologies covered in this group will be essential in driving the transformation.

Figure 3 plots each of the robotics and artificial intelligence technologies based on their average impact and novelty ratings given by rural industries experts. Robotics and artificial intelligence technologies were perceived to be of mixed impact and similar novelty. The technologies that offer contextual awareness and facilitate collaboration with human workers were perceived to be of highest impact and novelty. This is in line with prevailing views on the importance of human and machine collaboration in workplaces of the future.

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Context-aware Computing

Human-in-the-loop MachineLearning

Collaborative RobotsNatural Language Interfaces

Computer Vision

Wearable User Interfaces

FIGURE 3. IMPACT - NOVELTY MATRIX FOR ROBOTICS AND ARTIFICIAL INTELLIGENCE TECHNOLOGIES


BUSINESS MODEL INNOVATIONThe technologies comprising the business model innovation group are: Distributed

Production and Blockchain.

Technology is a catalyst for business model innovation. Increasing availability of

technology such as sensors, robotics and growing lights is facilitating the emergence

of smaller and decentralised farming operations that are closer to urban centres [26].

Although decentralised production won’t replace large and centralised production in

the near future [27], [28], decentralised operations have several advantages; they are

resource efficient, have shorter supply chains, and are agile [29]. A recent innovation

that is facilitating decentralised business models is blockchain. This technology allows

peers to engage in transactions that have fewer intermediaries and thus fewer costs

[30]. For agriculture, blockchain promises the capability of transparency and traceability

[31], [32]. If it delivers on this promise, it will be transformative for large companies with

complex supply chains, as well as small producers who differentiate themselves with

locally sourced and ethical products.

Figure 4 plots each of the business model innovation technologies based on their average impact and novelty ratings given by rural industries experts. Both distributed production and blockchain technologies were perceived to be of high impact for Australian rural industries. Moderate novelty ratings suggest that the capabilities that these technologies offer are partially present in agricultural contexts. Opinion in the literature is that blockchain will be transformative in many industries. It will likely emerge as a platform in the rural industries.

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Distributed Production

Blockchain

FIGURE 4. IMPACT - NOVELTY MATRIX FOR BUSINESS MODEL INNOVATION TECHNOLOGIES


RENEWABLE ENERGYThe technologies comprising the renewable energy group are: Solar Retransmission,

Perovskite Solar Cells, Sodium-Ion Batteries and Moisture Harvesting.

New technology will be the driving force behind a smarter and more reliable energy

infrastructure [33]. The increasing availability of low cost and efficient electricity generation

and storage technologies will facilitate entirely new models of energy consumption. One

example of this is microgrids [33], [34]. These are independent from the main electricity

grid, and in many cases are democratically operated by the participants of the microgrid

[35]. Advances in renewable energy technologies are timely, and they will play a key

role in the short- and long-term future. Large volumes of sustainable energy generation

will be needed to reduce environmental impact and to power the electrification of

transportation and other equipment [33]. Beyond the immediate future, current interest

in harvesting energy from space and the development of novel ways to extract resources

indicates a willingness and capability to power future energy needs [36]–[38].

Figure 5 plots each of the renewable energy technologies based on their average impact and novelty ratings given by rural industries experts. Renewable energy technologies were generally perceived to be of high impact and novelty. This was particularly true for perovskite solar cells and moisture harvesting technology. If realised, these technologies will give farm operators access to resources that are sustainable and that facilitate greater self-sufficiency. This will reduce costs and also provide new revenue streams for farmers.

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Moisture Harvesting

Perovskite Solar Cells

Sodium-ion Batteries

Solar Retransmission

FIGURE 5. IMPACT - NOVELTY MATRIX FOR RENEWABLE ENERGY TECHNOLOGIES


ADVANCED MATERIALSThe technologies comprising the advanced materials group are: Programmable Materials,

Metamaterials and Graphene.

Material innovations permeate the technology landscape and they underlie many

technology advances. Graphene is perhaps one of the most hyped technologies in

recent years. It promises to improve many categories of consumer technology, as well as

technology essential for rural industries in the future. Perhaps the most notable of these

is sensor and renewable energy technologies [39]–[41]. Beyond improving existing

technology, material innovation will bring entirely new capabilities. This is highlighted in

the early capabilities of programmable materials and metamaterials. Although both are

in experimental stages of development, they bring the potential to drive new classes of

technology with entirely new functionalities [42].

Figure 6 plots each of the advanced materials technologies based on their average impact and novelty ratings given by rural industries experts. Each of the advanced material technologies were perceived to be of high impact and novelty. These technologies promise wide ranging capabilities in rural industries. Their impact, if realised, will be the improvement of many current technologies, and facilitating entirely new and potentially transformative capabilities.

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Metamaterials

Programmable Materials

Graphene

FIGURE 6. IMPACT - NOVELTY MATRIX FOR ADVANCED MATERIALS TECHNOLOGIES


IMPACTS ON AUSTRALIAN RURAL INDUSTRIES

Determining the disruptive potential of a technology to an organisation first requires the

identification of candidate technologies and then defining their functional capabilities

[13]. These stages of analysis reflect the key outcomes of the Horizon Scans that

preceded this report. With a watchlist of candidate technologies and an understanding

of their current and projected functional capabilities previously established, this section

of the report looks to develop ideas about the context of their impact for Australian

rural industries. Developing this context helps to understand how the characteristics of

the technologies align with the critical needs of Australian rural industries. It does not

intend to present definitive predictions about the implementation of technologies, but

rather plausible relationships between technologies and the needs of Australian rural

industries.

The following sections highlight three key areas of the Australian rural industries that

the identified technologies have the potential to impact. These areas of impact were

established based on the data analysed during each of the Horizon Scan stages,

including results generated from interactions with experts working in the Australian

rural industries. Each section begins with a brief overview of context. Following this,

the technologies that are likely to be of greatest impact are framed in relation to the

five focus areas that were identified at the beginning of this project (Appendix B). This

includes the presentation of plausible futures that describe technology implementations

in the context of the relevant focus areas.


EFFICIENCY AND PRODUCTIVITYIn agriculture contexts, efficiency and productivity are intrinsically linked; productivity

growth is often reflected in increases in efficiency [3]. A key driver within this relationship

between efficiency and productivity is technology [2]. Technology change and the

appropriate adoption of technology pushes operators toward the productivity

frontier [1], [43]. The closer to this frontier, the more efficient an operator is with their

inputs and processes [1].

While productivity and efficiency have been mainstays of importance in Australian

agriculture, there will be an ever increasing importance placed on both factors in the

coming decades. Efficiency and productivity are important mechanisms for ensuring

market competitiveness [3], and Australian agriculture is fully exposed to international

competition in both its domestic and global markets [3]. The intensity of competition on

both fronts is likely to increase as shifts in power and capabilities occur in the global

marketplace [44]. Australia is also vulnerable to the risks of climate change and declining

natural resources [9]. Inefficient use of inputs has negative environmental effects

and results in added costs for farmers [45]. It will be essential to deliver consistent

improvements in efficiency and productivity to maintain competitive in the future.


FRAMING TECHNOLOGY IMPACTSFive technology groups were identified to have impact on efficiency and productivity

in the context of Australian agriculture:

DATA DRIVEN • Smart Dust• Augmented Reality• Digital Twin• Labour Tracking• LoRaWAN


• Collaborative Robots• Context-aware Computing• Wearable User Interfaces• Computer Vision• Human-in-the-loop Machine Learning

RENEWABLE ENERGY • Perovskite Solar Cells• Sodium-ion Batteries• Solar Retransmission• Moisture Harvesting

GENOMICS AND BIOTECHNOLOGY • Plant Genome Sequencing• CRISPR• Microbiome

ADVANCED MATERIALS • Programmable Materials• Metamaterials

The potential impact of these technology groups can be framed in relation to the five

focus areas that were identified during the scoping workshop at the beginning of this

project (Appendix B). Three focus areas were identified to be potentially impacted by

these technology groups:

A. PRIMARY PRODUCTION INPUTS, • Viable Alternatives to Reduce CostsPROCESSES AND PRACTICES • Genetic Improvement

• Post-farm gate ConsiderationD. SUPPLY CHAIN LOGISTICS • Relationships and Connectivity

• Disruptive Technology in the Supply Chain• Optimisation of the Supply Chain

E. INDUSTRY SUSTAINABILITY • Environmental• Economic

Two plausible futures are presented on the following pages that highlight the relationships

among the above emerging technologies and focus areas of Australian rural industries.


FOCUS AREA A. PRIMARY PRODUCTION INPUTS, PROCESSES AND PRACTICESViable alternatives to reduce costs; Genetic Improvements; Post-farm gate considerations

As the cost and difficulty of finding labour in Australia increases, automation technologies will reach cost

parity in many food production processes. On-farm, small-scale robots equipped with computer vision

systems will replace and work alongside the existing workforce. These robots will be connected to data

collected from in-field sensors and precision agriculture technologies. They will work 24/7 and be able to

interpret threats that are likely to affect crops, as well as understand specific requirements of individual

plants. This will enable highly efficient use of pesticide, fertiliser and water inputs. On-farm microgrids will

fuel these robots and other smart machines as they become more prominent due to electrification.

Efficiency and productivity gains generated on-farm will originate from pre-farm gate research and

development and planned production programs. Central to this will be the genetic improvement of plants

to be more resistant to pathogens and more tolerant to drought and other effects of climate change. These

plants will require less water, fertiliser and pesticide inputs, and result in fewer negative environmental

externalities. Precise control over crop trait design will lead to the development of new location specific

crops. Availability of these options to farmers will enable accurate planning and yield forecasting, and

therefore reduce the financial risks associated with agriculture.

PLANNEDPRODUCTION

RESEARCH ANDDEVELOPMENT

IMPORT

EXPORT

MARKETING AND CONSUMER

ENGAGEMENT

CONSUMPTION

ON-FARMPROCESSING

ON-FARMPRODUCING

AGGREGATIONAND DISTRIBUTION

PROCESSING

DISTRIBUTIONDOMESTIC

SUPPLY

FIGURE 7. KEY STAGES OF THE SUPPLY AND VALUE CHAINS WHERE THE IDENTIFIED TECHNOLOGIES HAVE IMPACT


PLANNEDPRODUCTION


IMPORT

EXPORT


ENGAGEMENT

CONSUMPTION

ON-FARMPROCESSING

ON-FARMPRODUCING


PROCESSING


SUPPLY

FOCUS AREA D. SUPPLY CHAIN LOGISTICSRelationships and connectivity; Disruptive technology in the supply chain; Optimisation of the supply chain

Robots, AI and Data Driven technologies will spread throughout the supply- and value- chains to reduce

input costs and maximise productivity. Transportation, aggregation, distribution, processing, packaging and

domestic supply channels will all incorporate some level of automation and intelligence. As new technology

is embedded throughout these stages, inter-process communication will be made possible to ensure the

most efficient movement of product. This will reduce the downtime of transportation and processing assets,

and it will ensure that transportation shipments are optimised to reduce the number of partially-empty and

empty vehicles on the road.

Digitisation of agriculture information and the capacity to share this data will make detailed information

available for all stakeholders to improve the efficiency of the supply chain. This has the potential to identify

new areas for development and lead to new and disruptive agribusiness ventures. It will be possible for

farmers to have live interactions with customers and stakeholders and thus to develop market driven

production plans. This abundance of information will reduce market risk, uncertainty and poor decision-

making. Reducing these factors will benefit all involved parties and has the potential to support more

investment in agriculture ventures.


SKILLS AND KNOWLEDGEHuman resource availability will be a significant factor for the future of Australian

agriculture. The present trend in Australian agriculture is an ageing and declining

workforce. The median age of farm workers in Australia is currently 48 [46] and there

is no indication of where a younger generation of farm workers will come from. There

are more workers leaving the industry than are entering it, and the younger

generation is not showing an interest in agriculture careers. This is highlighted by

a considerable reduction in the number of students studying agriculture qualifications

over the last decade [47].

Alongside a declining workforce in Australian rural industries, it is uncertain what the

future workforce will look like. It is estimated that 60% of tasks performed in agriculture

jobs have the potential to be either fully or partially automated. These include routine

and non-routine manual labour, data collection and data analysis tasks [48]. Although

there is a strong sentiment that automation will negatively impact labour forces in many

industries, there is also a view that automation will create jobs. Importantly for Australian

rural industries, these newly created jobs will likely be skill- and knowledge-based [48]–

[51]. They will involve close collaboration with automation technologies, at all levels

of implementation. Humans will be required to design, program, install, service, repair

and interpret autonomous technologies [51]. With the expected pace of technology

development, life-long learning will need to be supported by appropriate training and

re-skilling opportunities [52].


FRAMING TECHNOLOGY IMPACTSThree technology groups were identified to have impact on skill and knowledge in the

context of Australian agriculture:

DATA DRIVEN • Augmented Reality• Digital Twin• Graphene• Labour Tracking• LoRaWAN


• Context-aware Computing• Wearable User Interface• Computer Vision• Human-in-the-loop Machine Learning

BUSINESS MODEL INNOVATION • Blockchain



project (Appendix B). Two focus areas were identified to be potentially impacted by



• Information and Skills to Support Decision-making

C. ADAPTIVE CAPACITY OF PRIMARY PRODUCERS AND SECTORS

• Leadership to Initiate and Respond to Change• Skills and Knowledge to Implement Change

E. INDUSTRY SUSTAINABILITY • Social License• Economic• Perception




PLANNEDPRODUCTION


IMPORT

EXPORT


ENGAGEMENT

CONSUMPTION

ON-FARMPROCESSING

ON-FARMPRODUCING


PROCESSING

DISTRIBUTIONDOMESTICSUPPLY

FOCUS AREA A. PRIMARY PRODUCTION INPUTS, PROCESSES AND PRACTICESInformation and skills to support decision-making

While agriculture has relied on the knowledge of highly experienced individuals, the future will rely on

human-technology collaboration to augment the capabilities of a new generation of agriculture workers.

Sensor networks and artificial intelligence enabled robotics deployed throughout the farm will deliver data

to sophisticated software platforms capable of modelling entire farm operations. Real-time measurement

of environmental conditions, input requirements and use, predicted outputs, worker status, and equipment

status will allow farm managers and decision-makers to be agile in response to change. With the collection

of this data overtime, it will be possible for farmers to run predictive models to inform their decisions before

they need to be made.

Workers in the field will collaborate with robotics and artificial intelligence technologies to perform tasks

more efficiently. Communication between humans, robotics technologies, and the environment will be

seamless. Augmented reality will provide field workers with an in-depth view of equipment and environment

status so that they can make more accurate decisions and allocate their attention to where it is needed

most. Similarly, Robotics equipped with computer vision and machine learning will be able to organise their

tasks around that of human workers and other robotics technologies. There will be passive and active

communication at all levels.



PLANNEDPRODUCTION


IMPORT

EXPORT


ENGAGEMENT

CONSUMPTION

ON-FARMPROCESSING

ON-FARMPRODUCING


PROCESSING

DISTRIBUTIONDOMESTICSUPPLY

FOCUS AREA C. ADAPTIVE CAPACITY OF PRIMARY PRODUCERS AND SECTORSLeadership and initiative to respond to change; Skills and knowledge to implement change

Technology innovation and digital transformation have the potential to incentivise a new generation of

workers and develop new leadership capabilities in Australian rural industries. A younger generation with

qualifications in technology fields and an interest in social enterprise will be equipped with the necessary

skills to tackle critical issues – many of which relate to the wold’s food production systems and their

capabilities to meet complex global challenges.

Technology innovations will empower the next generation of leaders to push for novel and innovative

business solutions. Business platforms built on blockchain will allow for a democratic and cost-effective

way for small operators to compete among the big corporations. Cost-effective operations will be powered

by small and agile teams of humans and robots. Immersive technologies, such as augmented reality will

provide new and engaging ways to connect with and create value for the next generation of consumers.


NEW PRODUCTS AND MARKETSThe world is undergoing rapid change. Climate change and declining natural resources

are expected to worsen in the coming decades [9]. A connected society in developed

nations is engaged and more informed about these issues than ever before [53]. The

‘experience economy’ is booming and young and affluent consumers are opting

to choose lifestyle and quality over cost and quantity [54]. This includes choosing

to buy local and sustainably sourced products [55]. Businesses are aware of this shift,

and many industries are positioning themselves to address these needs by supplying

convenient and customisable experiences [49]. As these become more available to

consumers, there will be an expectation that the same level of experience is present

throughout their interactions with businesses and organisations [56], [57].

In developing nations, particularly Asia, wealth creation is expanding the middle class.

As an expected 1 billion people shift out of poverty, there will be a dramatic increase

in food demand, particularly for higher quality produce and sources of protein [6], [7].

While this will create immense challenges for the world’s food systems, it will also

provide significant opportunities. In this context, technology innovation can help pursue

objectives of product quality, diversity, safety, sustainability and animal welfare [2].


FRAMING TECHNOLOGY IMPACTSTwo technology groups were identified to have impact on new products and markets

in the context of Australian agriculture:

GENOMICS AND BIOTECHNOLOGY • Microbiome• Plant Genome Sequencing• CRISPR

BUSINESS MODEL INNOVATION • Blockchain• Distributed Production



project (Appendix B). Three focus areas were identified to be potentially impacted by



• Genetic Improvement• Post-farmgate Consideration

B. MARKET AND CONSUMERPREFERENCES

• Relationships and Connectivity• Disruptive Technology in the Supply Chain• Optimisation of the Supply Chain

E. INDUSTRY SUSTAINABILITY • Social License• Economic




PLANNEDPRODUCTION


IMPORT

EXPORT


ENGAGEMENT

CONSUMPTION

ON-FARMPROCESSING

ON-FARMPRODUCING


PROCESSING


SUPPLY

FOCUS AREA A. PRIMARY PRODUCTION INPUTS, PROCESSES AND PRACTICESGenetic Improvements; Post-farm gate considerations

Pre-farm gate innovation is boosted by advances in microbiome, genome sequencing and precise gene

editing using technologies such as CRISPR. These technologies expand our understanding of crop and

environment traits dramatically. New varieties are designed to enhance the diversity of crops available to

farmers. This includes the design of crops suited to growing in Australian conditions but destined for sale

in expanding overseas markets. An increased diversity of cash crop varieties are also made available so

that farmers can maximise the value of their land between growing seasons.

Post-farm gate, blockchain technologies provide the means to target the emerging global markets while

maintaining brand integrity. As food products move through complex global supply chains, each transaction

is logged on the blockchain. Transparency of this process enables producers, distributors, sellers and

buyers to trace product through the entire process. For producers this ensures that their brand reputation

remains in-tact and price in ensured. For eventual customers, this provides the peace of mind that they are

getting safe and legitimate food products.



PLANNEDPRODUCTION


IMPORT

EXPORT


ENGAGEMENT

CONSUMPTION

ON-FARMPROCESSING

ON-FARMPRODUCING


PROCESSING


SUPPLY

FOCUS AREA B. MARKET AND CONSUMER PREFERENCESDifferentiated products

Gene editing and microbiome technology enable the possibility of designer and personalised foods. These

foods are mass customisable and targeted at specific people for very specific requirements. At the top of

this list are foods that address the increasing prevalence of chronic diet related illness such as obesity

and diabetes. It is possible that the design, production and distribution of these foods become integrated

in specialised health services.

Beyond health, emerging technologies such as blockchain and distributed production have the potential

to provide novel food experiences to consumers in the experience economy. A highly efficient and agile

network of distributed food production systems made up of automated urban farms produce local food and

deliver it fresh to consumers. These services target environmentally conscious consumers who are looking

for convenient, healthy and sustainable food options. This provides farmers the opportunity to grow value-

added niche crops and alleviates the reliance on commodity crops.


REFLECTION ON APPROACH

The format of this project was to conduct iterative Horizon Scans with the purpose

of developing a watchlist of emerging technologies that offer potential opportunities

and challenges for Australian rural industries. Regular intervals between each Horizon

Scan, and the integration of several methodological inputs necessitated their effective

management and planning. Therefore, evaluating the effectiveness of the overall process

requires reflection on the various methodological inputs and their contribution to each of

the stage-gates within the Horizon Scans.

At a macro-scale, Horizon Scans involved scanning information sources from a variety

of domains to identify emerging technologies and then understand their applicability

to Agriculture contexts. At a more granular level, this process comprised of several

stage-gates. Without meeting the outcome requirements of each stage-gate, it would

not be possible to move through the Horizon Scan process. In each of the Horizon

Scan reports, and included in Appendix A, three primary project streams are identified:

discovery, evaluation and consolidation. Each of these streams had specific outcomes to

achieve that formed the stage-gates of the project. These will be used as the framework

to reflect on the overall process.

DISCOVERYThe outcome of the discovery stream was to develop an initial list of candidate technologies

for evaluation. Achieving this outcome comprised the following stage-gates:


1. Identifying experts and compiling the data set

2. Identifying strong and weak signal technologies

3. Interpretation of signals

Our approach to discovery was to apply data mining techniques to a large volume of

Twitter data to extract information about emerging technologies being discussed by

technology experts on the platform. The data mining techniques employed demonstrated

significant value and were effective for retrieving signals of emerging technologies in

the Twitter data. This effectiveness, to a large degree, was because our data mining

technique mitigated the noise present in the data. Noise is typically a major concern

associated with using social media data as it can lead to the presentation of many

redundant topics [58].

The data mining techniques, while proving to be effective, did require notable human input

at different stages of implementation. This included the compilation of an expansive list

of target Twitter users prior to implementing the data mining technique. The identification

of these Twitter users was achieved by engaging with researchers and industry experts

working in the domains we were interested in scanning. These experts provided the

names and accounts of reputable Twitter users and accounts considered to be leaders

in their respective domains. This process was essential in limiting the noise present in

the dataset as it allowed us to only scan Twitter data relevant to emerging technologies.

Human input was also required following the extraction of data from the target Twitter

users. For strong signals of emerging technologies, this input was minimal. Trending

technologies were easily identified by individual ranking, which was based on the number

of times the technology was mentioned in the data. Weak signals, on the other hand,

required significantly more human input as they were often present much deeper in the

extracted data. Interpretation was required for both strong and weak signals. An important

factor contributing to the ease of interpretation was the structure of Tweets present in

the overall dataset. In data sets made up of Tweets containing ‘hashtags’, interpretation

was facilitated to some extent as less noise was present. Moreover, multiple hashtags

in a single tweet often identified similar category technologies and relevant contextual

information. Thus, we were able to identify technologies and the topics of interest around

them. In contrast, Tweets comprising only of sentences contained considerably more

noise, resulting in greater human input to identify meaningful content. As signals were

identified in the data, further interpretation involved the use of literature reviews to gain

an establish understanding of the technology, applications and context.

EVALUATIONHaving developed an initial list of candidate technologies, the outcome of the evaluation

stage was to refine the list of technologies to only those that offer clear opportunities

and challenges for Australian rural industries. Achieving this outcome comprised the

following stage-gates:


1. Evaluation of technologies’ potential impact in rural contexts

2. Narrowing down technologies

The evaluation stage of the project was the first step toward recontextualising the

technologies into the rural industries context. Where notable technology reporting

groups, such as Gartner and Forbes provide predominantly domain general analysis of

technologies, our approach aimed to provide technology insights tailored to the context

of rural industries. Therefore, it was important to be able to process domain general

information from the discovery stream and develop it to be specific to the domain or

rural industries.

This recontextualisation required the effective integration of methods based on attributes

of evidence, creativity and expertise. Key to this were Delphi questionnaires with rural

industries experts who had demonstrable understanding of innovation and technology in

agriculture. Delphi questionnaires are an expertise- and creativity-based method which

involves iterative and anonymous rounds of questionnaires. After each round, the results

are shared amongst participants and they are given the opportunity to revise and expand

on their original answers. The purpose of this is to structure a group communication to

deal with complex issues [59]–[61]. One of the challenges for this project was structuring

effective communication with rural industries experts about technologies they might

not be familiar with. Our strategy for this was to maximise the strengths of the expert

panel. This was done by developing questionnaire content that encouraged creative

outcomes and consideration of the plausible impact that the technologies might have

in the agriculture domain, which the experts have detailed knowledge of. We then relied

on evidence-based methods, data mining and literature review, to explore other aspects

of the technologies’ feasibility. This included breadth of applications, innovation trends

and forecast. Combining each of these approaches proved to be effective for narrowing

down the list of candidate technologies.

CONSOLIDATIONThe outcome of the consolidation stream was a final list of technologies offering potential

opportunities and challenges to Australian rural industries, accompanied by supporting

written and visual content. Achieving this outcome comprised of the following stage-

gates:

1. Evaluating the technologies’ potential applications in the rural industries

2. Synthesis of findings

3. Visualisation of findings

Just as the evaluation stage required integration of methods with attributes of evidence,


creativity, and expertise, so too did the consolidation stage. Data mining was effective for

exploring the application potential of each technology. As our previous dataset obtained

from Twitter contained little information about how the technologies are used, we used

each technology name as a topic of interest to scan patent databases. This approach

allowed us to explore and understand the broad range of applications each technology

was being developed for. Literature reviews were used to support and validate these

outcomes.

The outcomes of the data mining and literature reviews were used as content for the

second round Delphi questionnaires with rural industries experts. Open ended questions

were used to elicit the experts’ opinions about how the technology applications might

transfer to rural industries, and to provide specific examples of these applications. This

process facilitated the development of creative content to explore plausible applications

of the technologies. It also served as a method for evaluating the efficiency of the data

mining framework. Specifically, if our methodology was able to accurately and efficiently

capture sufficient detail to explore technology applications, and link in with the other

aspects of the methodology. The final stages of the consolidation stage were focused

on bringing together each of the inputs, including literature, questionnaire and data

mining inputs. This comprised of writing up technology overviews, and visualising data

from Delphi questionnaires and data mining outcomes.

FINAL METHODOLOGY STATEMENTThe effectiveness of our methodology was predicated on the capability to first detect

emerging technologies from a range of different industries, and then through systematic

assessment, reposition and imagine those selected technologies in an Australian rural

context. For effective technology foresight of this kind, is important that the approach

taken can account for the inherent complexity of researching and anticipating

technologies of the future [11], [12], [62], [63]. Our approach recognises this complexity

by incorporating a mix of foresight methodologies that provide balance and ensure that

no one method is dominant. This allows the short comings of any single method to be

covered by the strengths of the accompanying methods [12], [62]. In doing this, we

have demonstrated the capability to adapt to short-term trends that occur in technology

contexts, and then validate and extrapolate the findings by testing them amongst the

broader literature, and with experts working in the context of inquiry. While this method

has been employed to inquire about technology trends, it is expected to be transferrable

for the scanning and synthesis of other topics and trend areas.


CONCLUSION

Technology driven disruption is expected to experience exponential growth in the

coming decades [4]. With this, many existing industries will be transformed and entirely

new industries will be created [13]. Technologies with these transformative capabilities

are of great relevance to Australian rural industries. Development and access to

advanced agriculture technology has resulted in efficiency gains by decreasing inputs

and maximising outputs [1], [2]. The adoption of new innovations therefore plays a key

role in increasing farm productivity, profitability and competitiveness [3]. In the past,

Australian agriculture’s strong track record of technology integration has been a key

part of ensuring its long-term productivity and economic viability [4]. Despite this track

record, the increasing speed of technology innovation and the emergence of significant

global and domestic challenges makes the scanning and identification of high impact

technology a priority for Australian rural industries.

The Detecting Opportunities and Challenges for Australian Rural Industries project has

recognised this priority and has developed a capability to anticipate key technology

advancements through their early discovery, evaluation and synthesis. The resulting

outcomes have been presented in three iterative Horizon Scans. Each Horizon Scan

has employed a novel methodological approach involving the interaction of data

mining, literature review, Delphi questionnaires and visualisation methodologies. The

effectiveness of this approach has been demonstrated in its capability to first detect

emerging technologies from a range of different industries, and then through systematic

assessment, reposition and imagine those selected technologies in an Australian

agriculture context.


This report consolidates the work that has been completed over the duration of the

project, and in doing so presents opportunities and next steps for future work. The first

section of this report has provided a summary of the watchlist of emerging technologies

by outlining six technology domains that have potential impact for Australian rural

industries. Building on this watchlist and summary, the second section of this report has

framed the potential impact of the identified technologies in relation to five focus areas

of Australian rural industries. The discussion of potential technology impacts in relation

to these focus areas has shown plausible relationships between emerging technologies

and the critical needs of Australian rural industries. Moreover, the discussions have

focused on exploring technology confluence rather than isolated applications of

technology. Technology confluence has long been considered an important driver of

innovation [64]. The plausible futures discussed in this report illustrate the significant

potential of technology confluence in the context of Australian agriculture and the effect

that it might have if developed effectively.

The notion of technology confluence and its capability to address the future challenges

of Australian rural industries is where the future direction of this work lies. Although

technology confluence is cited as something that often happens without planning, it is

possible to foster and prepare for it with appropriate management and an interdisciplinary

approach [64]. This process has already begun with the preparation of a parallel report

that outlines potential technology-driven agriculture industries that have the capabilities

to address the future challenges facing Australian rural industries.


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APPENDIX A: APPROACH AND PROJECT STREAMS

This project employs a concurrent phase, iterative methodology to:

1. scan and extract data from a variety of sources;

2. synthesise this information to identify potential trends and innovations for further

investigation;

3. and, communicate these issues through visualisations.

Implementation of each respective project phase, led by data mining, synthesis, and

visualisation, occurs across three interactive streams: Discovery; Evaluation; and,

Consolidation. These streams are continuous over the course of the project requiring

different inputs from each project phase. These inputs from each phase, and their

interactivity is represented in Figure 2.

FIGURE 10. PROJECT INPUTS AND STREAM INTERACTION

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DISCOVERYEVALUATIONCONSOLIDATION

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DISCOVERYDiscovery focuses on scanning selected sources to extract relevant data and detect

signals of emerging and transformative technologies. Data sources are strategically

selected to ensure input from a diversity of domains within an international context. In the

current implementation of the discovery stream, sources included select twitter users,

patent databases, industry and market reports, and technology news media. Scanning of

these sources employs data mining and synthesis concurrently:

• Data mining focuses on scanning the twitter feeds of thought leaders and technology

experts in a range of technology and industry domains. These are selected based

on the recommendations of QUT experts working in relevant technology domains.

• Synthesis focuses on scanning a broad range of technology news publishers,

industry and market reports, and patent databases.

The confluence of data mining and synthesis outputs in the discovery stream results

in a list of technologies for further investigation in the subsequent evaluation and

consolidation streams.

EVALUATIONEvaluation focuses on filtering the signals identified in the discovery stream. Its

implementation leverages expertise from QUT, and Agrifutures Australia through the

provided list of innovative farmers, to assess the potential impact of a broad range of

emerging technologies. This process uses Delphi style surveys which are deployed in

successive rounds.

The initial round of surveys focuses on evaluating a large volume of technologies

identified in the discovery stream. This is achieved through presenting a series of simple

statements that describe the functionality of a technology, and asking for a rating based

on its perceived impact. From these ratings, a shortlist of technologies is compiled for

further investigation and ongoing monitoring. Successive survey rounds present a lower

volume of questions but require increasingly qualitative responses. It is through this

process that we narrow the scope of technologies that are included on the watchlist

and that will be monitored throughout future reporting periods. As the evaluation stream

progresses, we continue to develop an objective list of criteria to establish the possible

scale of impact of each transformative technology. These criteria are re-introduced in

successive discovery stages of the project to assist with filtering the large volume of

data.


CONSOLIDATIONConsolidation focuses on monitoring technologies on the initial watchlist, and providing

a detailed analysis of their potential impact for Australian rural industries. This involves

a detailed analysis of the technologies’ potential impact for Australian rural industries

and developing a rationale for why they should be monitored. This consolidation stream

utilises both data mining and synthesis to receive input from a broad range of data, and

gain the requisite detail.

Data mining focuses on eliciting deeper analysis of the technologies identified and

short-listed during the discovery and evaluation phase. Directed by specific technologies

and related keywords, data mining targets social media feeds and patent databases. The

outcome of this stage provides assessment of candidate technologies based on metrics

such as trends over time, associated keywords and industries to identify the contexts in

which the technology is active and where it is receiving innovation, and location.

The data gained from this stage of data mining, and from the evaluation stream, feeds into

and directs synthesis. With this direction, synthesis can focus on specific applications and

implementations of the technology to better understand and communicate its potential

impact for Australian rural industries. Visualisation is then used to bring together the

inputs of synthesis and data mining, as well as inputs from the evaluation stream. This

includes the development of infographics and scenarios to communicate the watchlist

issues and themes.


APPENDIX B: FOCUS AREAS AND SUB-FOCUS AREAS

The following are the focus areas and sub-focus areas identified during the workshop

attended by stakeholders of Australian rural industries, held on August 15, 2016.

A. PRIMARY PRODUCTION INPUTS, PROCESSES AND PRACTICES1. Information and skills to support decision making

2. Natural resources and other input costs

3. Viable alternatives to reduce costs (including practices)

4. Genetic improvement

5. Post-farm gate considerations

B. MARKET AND CONSUMER PREFERENCES, TRADE REQUIREMENTS1. Geopolitical landscape

2. Market characteristics (consumer preferences, size, affluence, access, intel)

3. Differentiated products – new and premium (safety, social responsibility, brands,

nutrition, provenance)

4. Commodity (exchange rates, supply, capacity, products, waste)

C. ADAPTIVE CAPACITY OF PRIMARY PRODUCERS AND SECTOR1. Leadership to initiate and respond to change (organisation, individual)

2. Skills and knowledge to implement change

3. Access to capital and financial tools

4. Regulation (encourage enabling regulation)

5. Organisational capacity to deal with change (structures, culture)

D. SUPPLY CHAIN LOGISTICS1. Relationships and connectivity

2. Market intelligence

3. Degree of vertical (degree of complexity in the value chain)

4. Disruptive technology in the supply chain

5. Optimisation of the supply chain (supply chain efficiency, cost reduction)

E. INDUSTRY SUSTAINABILITY – SOCIAL, ENVIRONMENTAL, ECONOMIC1. Social license (wellbeing, ethical employment, infrastructure, services, health)

2. Environmental (climate change mitigation, adaptation, opportunities, dealing with

variability, endemic and exotic threats)

3. Economic (infrastructure, energy, transport, labour, profitability)

4. Perception (domestic and global) and policy (how industry is perceived and

repercussions)

DETECTING OPPORTUNITIES AND CHALLENGES FOR … · This report is the final report of the Detecting...

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