Digitalization to Achieve Technology Innovation in Climate Technology Transfer

Abstract

Technology Innovation has the potential to play a strategic role in improving the effectiveness and efficiency of national efforts to address climate change. The United Nations (UN) Climate Technology Centre and Network (CTCN) is mandated to support developing countries’ climate change responses through innovative technologies to achieve the goals of the Paris Agreement. In order to enhance the role of the CTCN as an innovation matchmaker, it is important to explore and leverage the implementation potential of new digital technologies and their transformational impact. Thus, in this research, to engage digitalization as an innovative tool with the environment, we first explored digitalization during the climate technology transfer processes by comprehensively reviewing CTCN Technical Assistance (Digitalization Technical Assistance, D-TA) activities in three climate sectors of risk prediction, policy decision making, and resource optimization. Then, by applying analytical methodologies of in-depth interviews with major digital-climate stakeholders and a staged model for technology innovation, we propose future strategies for enhancing the role of CTCN as an innovation matchmaker in the three digitalization cases of digital collection, digital analysis, and digital diffusion.

1. Introduction

Groundbreaking technological innovation is critical for an effective, long-term global response to climate change and for promoting sustainable economic development [1]. To achieve the goals of the Paris Agreement, there is a need to accelerate and strengthen technology innovation while delivering cost-effective and better-performing climate technologies at a larger and more widespread scale. The United Nations (UN) Climate Technology Centre and Network (CTCN) has a mandate to provide technology innovation as a “matchmaker for climate technology transfer” by supporting developing countries’ climate change responses through various emerging frontier technologies. As key enablers of smartness, sustainability, and environmental resilience in technology innovation, digital technologies including artificial intelligence (AI), the Internet of Things (IoT), Cloud computing, 5G, digital twins, and Big Data, etc., have become more crucial in intensively utilizing new smart applications and devices. Digitalization benefits industry in various ways: greater convenience, lower prices, variety of choice, better information, enhanced sustainability, and the profitability of existing business models and investments [2].

Many UN agencies, the scientific community, and academia have been leading global efforts to encourage the use of digitalization in tackling climate change. Recently, the International Telecommunication Union (ITU) reported the vast potential of digital technologies to help assess, mitigate, and adapt to climate change [3]. Leveraging these technologies to address climate change represents a significant opportunity to accelerate the achievement of the Sustainable Development Goals—in particular, SDG 13 to ‘Take urgent action to combat climate change and its impacts.’ In this article, emphasis is placed on several key areas in which digital technologies can effectively address climate change in real-time monitoring, mitigation, and adaptation, e.g., remote sensing for monitoring natural disasters, improved communications to help deal with natural disasters more effectively, and satellite and surface-based remote sensors for long-term environmental observation [4].

However, it is important to note from the onset that despite the potential of digital tools to enable developing countries to overcome climate change challenges, the digital divide—‘the gap between those who do and those who do not have access to new forms of information technology’ [5]—has been widening, not only between developed and developing countries but also between developing countries, as well as between rural and urban areas [6]. Thus, the transfer and transmission of innovation may not occur in climate technology processes because of limited digital knowledge and resources in many developing countries.

In this work, we firstly engaged two global trends of environment and digitalization in view of innovation policy. In order to understand the latest digitalization innovation approaches in climate technology transfer from developed to developing countries, this study examined the best CTCN Technical Assistance cases of digital technology convergence with three climate sectors of risk prediction, climate policy decision making, and resource optimization based on the staged innovation model [7]. Then, future digitalization strategies are proposed to enhance climate technology transfer and innovation by considering various CTCNs’ roles as innovation matchmakers between technology providers and users in the three digitalization stages of digital collection, digital analysis, and digital diffusion.

2. Methodology

2.1. Analysis of Digitalization during CTCN Technical Assistance Based on the Staged Innovation Model

To analyze technology innovation induced by digitalization, we reviewed several case studies of digitalization among previous CTCN Technical Assistance activities, based on the staged innovation model during climate technology transfer processes of technology outsourcing, demonstration, and diffusion. In the context of climate change, the term ‘digitalization’ can be defined as “the use of digital technologies to provide new digital solutions for tackling climate issues”.

The CTCN Digitalization Technical Assistances (D-TAs) mainly focused on three digital system outputs for tacking climate issues: (1) early warning systems (EWS) for various climate risks’ prediction, (2) environmental information system (EIS) for climate policy decision making, and (3) resource management system (RMS) for efficient optimization of various resources such as water, food, energy, greenhouse gases (GHG) emission, materials, wastes, etc.

Table 1. Examples of the CTCN Digitalization Technical Assistances.

Climate Issues	Digitalization Technical Assistance (D-TA) Examples	Usage of Digital Technologies
Risk prediction (4)	Hydrodynamic modelling for flood reduction and climate resilient infrastructure development pathways in Jakarta (Indonesia)	Flood hazard mapping, hydrodynamic modelling
	Promoting data for climate change, drought, and flood management in Myanmar	Web-based portal for climate change monitoring
	Strengthening Bangkok’s Early Warning System to respond to climate induced flooding (Thailand)	Flood forecast modeling, urban flood early warning system
	Assessment of Suitable Flood Mitigation Measures in Georgia	Hydrological/climate change/hydraulic modelling, flood mapping
Climate policy decision-making (3)	Strengthening the climate change information system for decision making in Guatemala	Web-Geographical Information System (GIS) mapping and analysis systems, satellite data integration and analysis platforms
	Strengthening decision making to address climate change through the design of an environmental information system in Côte d’Ivoire	Climate data integration systems, community-based monitoring platforms
	Development of a National Metrics System for Climate Change	Climate change monitoring and integration system
Resource Optimization (3)	Technology development for climate resilience and efficient use of resources in the agricultural sector in Thailand	Remote sensing and GIS, precision agriculture, irrigation efficiency, and information systems
	Improving resiliency of crops to drought through strengthened early warning within Ghana	Satellite data (crop, climate, soil moisture condition)
	Improvement of water supply management through GIS-based monitoring and control system for water loss reduction (Grenada)	Remote sensing and GIS software (monitor and manage clean water resources), data management software, digital twin, Integrated Water Resources Management (IWRM)

summarizes CTCN D-TA examples representing three climate sectors with specific digitalized systems.

2.2. Interviews with Major Digital-Climate Stakeholders

In order to identify the major barriers to digitalization for climate technology transfer and innovation to developing countries, in-depth interviews were conducted during the Vienna Energy Forum (VEF) 2021 (Held on July 6 2021, CTCN leveraging Frontier Technologies to facilitate the Climate Technology Transfer, https://youtu.be/YdY2wJqxbCo, accessed on 19 December 2021) from the digital technology stakeholders’ viewpoints. Target interviewees included specialists from academia, research institutions, private sector, as well as government representatives from developing countries who have experience in digital convergence of climate technologies and relevant policies. Key questions for the interviewees focused on (1) best practices and lesson learned on the benefits of digitalization, (2) barriers to digitalization, and (3) strategical recommendations for enhancing digitalization in climate sectors.

3. Results

3.1. Early Warning System (EWS) for Various Climate Risks Prediction

An Early Warning System (EWS) for prediction of climate induced risks, e.g., heat waves, droughts, and floods, is an integrated system of digital technologies or tools that guide the detection of and coordinates the response to emergencies by employing the tasks of data acquisition, decision making, and information dissemination [8]. A properly designed EWS to take protective measures prior to the occurrence of risks has four interconnected components, namely: (1) Risk knowledge: risk assessment exercises provide essential information in order to set priorities for mitigation and prevention strategies and designing EWS; (2) Monitoring and forecasting: systems with monitoring and forecasting capabilities provide timely estimates of the potential risk faced by communities; (3) Dissemination: communication systems are needed for delivering warning messages to the potentially affected locations; and (4) Response: coordination, good governance, and appropriate action plans are key points in effective early warning [9].

Therefore, many countries vulnerable to natural hazards are implementing EWS to minimize the impacts of climate change. Jakarta is one example of those increasingly threatened by flooding from a combination of land subsidence, rising sea levels due to the spring tide cycle and increasing rainfall intensity, and land use changes within the catchment areas. Hence, the CTCN delivered D-TA to Jakarta in developing a complete and effective EWS with a high-resolution hydrodynamic model at a pilot project site, one of the most flood-prone regions. Generally, these regions are selected as “hot-spots” by considering various geographical, hydrological, hydraulic, and climate factors.

In order to divide the digitalization stage for climate risk prediction during the D-TA activities, a digitalization flow for ‘Risk Knowledge’ and ‘Monitoring and forecasting’ was developed as shown in Figure 1 [10].

Then, to ensure that challenges were handled in a sustainable way, capacity-building D-TA activities were conducted through a series of technology transfer workshops to increase local capacity in high-resolution hydrodynamic modeling and use of the model for ‘Dissemination’, and the resultant policy and planning recommendations were used to reduce flood hazards, risk, and vulnerability for the ‘Response’ component [11].

3.2. Environmental Information System (EIS) for Policy Decision Making

Various climate data, including environmental and socio-economic information, are exploited for decision making and public policy making [12]. However, this is often limited due to the gaps between technological supply and stakeholder demand to translate information into climate action. Timely, predictable, and effective information is a powerful tool for government agencies and other private sector entities to make informed and timely decisions. Therefore, some countries, such as Guatemala [13] and Côte d’Ivoire [14], requested the CTCN to develop the feasible environmental information system (EIS) for providing quick and efficient access to important data from all environmental, societal, and economic sectors and also for establishing a strategy design of climate change mitigation and adaptation. An EIS is an information technology solution for collecting and tracking environmental data as part of an overall environmental management system.

For governments and private sectors in developing countries to make better decisions on mitigation and adaptation strategies to climate change, EIS relies on the collection of environmental data gathered from all national sources holding or producing this information and translating it into proposed indicators that are useful for decision making. Figure 2 illustrates a conceptual framework to integrate data from different sources to identify the set of indicators in case of Guatemala D-TA. The CTCN proposed a sustainable data collection strategy from different sectors (agriculture, energy, water, etc.) in order to identify a collection of socio-economic indicators: a contact list of stakeholders or a list of resources that are used in the climate activity cycle.

After performing this D-TA, the final EIS output can be a set of data files, or a highly integrated information system in support of assessing climate and environmental impacts, monitoring emissions of GHG and other environmental pollutants, measuring economic effects of changing environmental conditions, and developing policies and measures to regulate and improve the environmental performance of businesses, sectors, and administrative units. Through its features, public and private policy makers, according to their profile, can (1) lead and share their strategies, policies, and environmental analyses; (2) monitor the performance and associated actions; and (3) control the communication based on accurate and verified data.

3.3. Resource Management System (RMS) for Optimization

Climate change endangers the quality and availability of some resources such as food and water. More and more African countries will experience increased crop yields and water stress. Hence, the first step to address the security of resources is to systematically monitor world resources supplies, including the mapping of their production and shortages utilizing digital technologies [4] such as: (1) machine-to-machine (M2M) connectivity that supports remote sensing infrastructure, with high-resolution radiometers and moderate-resolution imaging spectrometers used to monitor food and water resources; (2) computers, mobile devices, servers, mainframes, and network databases used for resources security analysis, modelling, and mapping; and (3) communications infrastructure including the Internet to distribute information to producers and consumers.

As an illustration, more than 40% of the labor force (39 million people) in Thailand is engaged with the agricultural sector. Under the impact of climate change, it is necessary for Thai stakeholders to enhance the application of agricultural technologies for optimal crop productivity. Thus, the CTCN designed a D-TA project to apply real-time digital technologies for the efficient management of agricultural resources, such as integrated pest control, irrigation system, and fertilizer management [15].

In addition, in Grenada, it is predicted that rainfall will continue to reduce, lowering to between 25 and 30 percent of the current values by the end of the century. At the same time, water demands are expected to rise, which increases the pressure upon available future water supplies across the island. Accordingly, the CTCN D-TA helped to reduce levels of non-revenue water by strengthening the capability of the national water and sewerage authority of Grenada staff to monitor and address water losses due to leakages (physical loss) and unauthorized consumption (commercial loss), unbilled authorized consumption (metered, unmetered), and billed unmetered consumption [16].

Finally, the CTCN established a server-based ‘audit’ RMS using GIS structure and procedures for better water resources monitoring and management. Figure 3 describes the distribution network of the estimated water pipelines (red line) and data gathering points (yellow dot) for water audit information around two districts in Grenada. In the above two D-TAs, the use of satellite imaging and Global Positioning Systems (GPS) in new RMS products for monitoring environmental conditions made the management of food and water more effectively controllable.

4. Discussion

4.1. Three-Staged Digitalization from the Innovation Perspective

On the staged innovation model proposed in our previous work [7], we reviewed different innovation features during climate technology transfer processes in three stages: (1) outside-in innovation during the first technology outsourcing, (2) coupled innovation during the second technology demonstration, and (3) inside-out innovation for the third technology diffusion. Similarly, digitalization processes during the climate technology transfer were also analyzed in this study in terms of innovation, such as the first stage for digitalized data collection from outside (outside-in), the second stage for the inclusive analysis of the acquired data (coupled), and the third for the diffusion of digital outputs (inside-out).

4.1.1. First Stage of Digitalization for Outside-in Innovation: Digital Collection Stage

Generally, during the first digital collection stage, for climate technology transfer implementors to initiate the digitalization, the upstream information flow happens inward from different stakeholders such as CTCN Network members, local agencies, or various remote sources. As shown in the previous D-TA example of Jakarta [11], in order to assess suitable flood mitigation measures to reduce flooding, various data were collected from diverse outward data resources: hydrological data such rainfall, river level as flow time-series from the national meteorological agency, tidal data from the Danish hydraulic institute (DHI), the land subsidence data from literature by Budiyono et al. (2016) [17], and some satellite images. Then, a free open-source software for EWS is used to undertake various data management, analysis, and mapping tasks in order to provide a structured and repeatable method for the future assessment.

In addition, as reliable data sources, various sensor systems are responsible for monitoring environmental phenomena related to climate change in developing conducive EIS and RMS outputs [13,14,15,16]. For example, in the Thailand D-TA, geo-informatics were applied to identify soil moisture, to estimate crop yield, and to detect nutrient deficiency for the digitalization of agricultural sector. For digitalization in pest control to optimize the fertilizer and land examination, a satellite remote sensing system was utilized by combining GIS data from stationary and circular orbit satellite images, the remote sensing of spectral reflectance, and digital imaging processing from Google Earth.

Therefore, in summary, during the digital collection stage, it should be mentioned that digital data are always outsourced from Network members as technology providers, local users in developing countries, and external digital sources, which initiates new digitalization from outside into the climate technology transfer and innovation processes. This can be referred as an “outside-in” open innovation process [7,18].

4.1.2. Second Stage of Digitalization for Coupled Innovation: Digital Analysis Stage

During the second digital analysis stage, collected data in the first stage needs to be translated into information or knowledge by combining with various analytic software technologies and tools such as high-resolution modelling, dynamic risk mapping, and simulation. For example, in Georgia’s and Jakarta’s D-TA projects, various flood scenarios indicating different real environments were designed to exhibit dynamic local flooding data from different rainfall intensities, climate change factors and land subsidence conditions with time [9,11]. After that, through various software modelings analyzed by hydrological, climate change, and hydraulic data collected for flood mapping and mitigation activities, the 11 flood prone areas or “hotspots” have been successfully identified as shown in Figure 4 and

Table 2. Identified flood hotspots.

Flood Prone Area No.	Issue
1	Flooding in downstream urban area
2	Flooding on road and on property in house upstream botanical gardens
3	Flooding at large new building
4	Road flooding—insufficient culvert capacity
5	Road flooding—insufficient culvert capacity
6	Road flooding—insufficient culvert capacity resulting in breakout flow to the north
7	Road flooding—insufficient culvert capacity
8	Road flooding—insufficient culvert capacity
9	Road flooding—insufficient culvert capacity and flow out of catchment to adjacent river
10	Road flooding—insufficient culvert capacity resulting in breakout flow to the north
11	Road flooding—insufficient culvert capacity resulting in breakout flow to the south

.

In general, the technology scale-up or demonstration process is repeatedly carried out for the validation of the new technology through prototype tests or enhanced numerical analysis, resulting in satisfactory performances with reliable and reproducible data in actual operational environments. Likewise, during the digital analysis stage, the input ‘data’ are repetitively evaluated by various digital analytics such as modeling, mapping, or simulation to yield the best output ‘information’ or ‘knowledge’, which is the key resource for the next digitalization stage: digital diffusion using different outputs of the three climate sectors of EWS, EIS, and RMS.

After all, in the digital analysis stage, it is certain that “coupled or inclusive” innovation dominates because the ‘outside-in’ data from various resources, can be integrated with other digital technologies and analytic software tools, to map digitally demonstrated ‘inside-out’ information, by collaborations such as strategic alliances between D-TA implementors from academia, research institutions, private sectors, and local countries [7].

4.1.3. Third Stage of Digitalization for Inside-Out Innovation: Digital Diffusion Stage

Finally, during the third digital diffusion stage, the downstream information flow out of the digital outputs, such as a web portal EWS, EIS, or RMS, is directed to dedicated customer groups, including climate solution users, public policy makers, and local technology recipients. Sometimes, this digital diffusion includes knowledge sharing for local end-users with similar digital and climate environments. As an illustration, Ghana requested the CTCN D-TA to establish a web-based EWS portal for strengthening management of flood and drought and increasing adaptation to climate variability and climate change [19]. Finally, one of the CTCN network partners, DHI, produced a web-based platform (https://www.flooddroughtmonitor.com/home?register=true&ug=CTCN, accessed on 10 November 2021) for flood and drought data processing routines and assessments, which allows relevant customers such as decision makers, planners, and managers at the government level, as well as the academic community, to utilize the data, information, and tools without the installation of any software.

Furthermore, D-TA outputs were extended to transfer resultant policy and planning recommendations to overcome other local countries’ digital technology delay in dealing with similar flood hazards, risk, and vulnerability. In another example, Grenada D-TA provided a south–south knowledge sharing network through a learning event with the Caribbean water management community, who has developed a more comprehensive GIS monitoring and assessment system [15]. The key objective of this meeting was to enable the face-to-face transfer of digital information for water and sewerage authority staffs between Granada and Trinidad and Tobago.

In addition, in order to disseminate successful RMS outputs from D-TA projects, south–south collaboration between Thailand and Bhutan was held through a CTCN’s technology transfer workshop [20]. This workshop provided Bhutan’s participants with an overview of Thai intelligent transport system (ITS) for reducing GHG emissions, established to minimize traffic congestion, increase road safety, and improve efficiency of logistic system in Thailand. This ITS system collects high-quality, real-time public traffic data from both government and private sources in order to propose emission reduction strategies such as low-carbon fuels, energy efficient vehicles, and public and non-motorized transport. Through practical examples and case studies, the workshop enhanced the spread of participants’ knowledge on relevant digital technologies.

As shown in the above D-TA examples, it can be stated that digital diffusion stage leads to “inside-out” innovation because it externalizes and leverages the digital outputs such as digital products or knowledge in order to bring them to diffuse faster than local customers can do by themselves through internal transport. To sum up, based on our staged model for technology innovation, we successfully identified a three-stage process framework to facilitate the digitalization of climate technology transfer, indicating digital collection, digital analysis, and digital diffusion. This is well demonstrated in Figure 5 in terms of the respective innovation feature during each stage.

4.2. Insights for Digitalization during Climate Technology Transfer

By interviewing various stakeholders from government, the private sector, and universities on current digitalization issues in climate sectors, we found that there are still several challenges in supporting the digitalization for climate technology transfer to developing countries as follows: (1) a lack of climate datasets from potential digital technology suppliers such as CTCN Network members, academia/research institutions, or from local technology recipients; (2) the digital divide (infrastructure or technology) between developed and developing countries; and (3) a lack of incentives (e.g., marketplace, platform, funding, etc.) for new digital service businesses/markets. The interviewees and their answers are summarized as keywords in

Table 3. Key barriers to the digitalization from various stakeholders’ viewpoints.

Interviewee (Stakeholders)	Stage	Answers	Key Barriers
CTCN Network members, academia/research institutions	Digital Collection	Lack of incentives to engage new D-TA implementors, Lack of climate datasets from various digital technology providers and local users	Digital Datasets
Government officials from developed and developing countries	Digital Analysis	Lack of digital infrastructure, technology, capacity, etc., in developing countries	Digital Divide
Private sectors	Digital Diffusion	Lack of incentives for new digital market creation	Digital Platform

.

4.3. Future Strategies for Boosting Digitalization in Climate Technology Transfer

In this chapter, some strategic recommendations for utilizing digitalization to facilitate climate technology transfer are proposed in view of technology innovation, considering the different roles of the CTCN as an innovation matchmaker in three digitalization stages of digital collection, digital analysis, and digital diffusion.

4.3.1. Digital Collection Stage: The Role of CTCN as a Digital Source

To initiate digitalization in the first digital collection stage, it seems obvious that the CTCN, as an innovation matchmaker for climate technology transfer, should be concerned about how to efficiently leverage and complement existing data collection efforts. This can be gradually accomplished by three steps of: (1) categorizing digital data from various climate stakeholders, (2) partnerships with pre-existing global climate databases, and (3) engagement of state-of-the-art digital data collection technologies providers as new CTCN Network members.

As the first step in our categorization, it is worthwhile to mention that various data sources such as climate/digital technologies, analytic tools, and local technology needs, can be categorized or mapped from different climate sector stakeholders such as Network members including academia, private sectors, etc., and local governments. Recently, the UNFCCC Technology Executive Committee (TEC) published a report providing a categorization of the emerging technologies, their state of play, and potential climate change mitigation and adaptation impacts in the energy supply sector [21]. Likewise, the CTCN has been exploring and constantly gathering climate technology needs information from various developing countries with the aim of proactively “scouting” new relevant digital data providers into its climate sectors [22].

In addition, high-quality datasets can be established by networking with numerous global public and private organizations working with climate databases and data centers during the second step of partnership, as indicated in the UNEP global environmental data resources (https://www.unep.org/data-resources, accessed on 15 October 2021). This partnership gives plenty of real-time climate data such as Nature Map Earth (https://naturemap.earth/, accessed on 30 October 2021) to the CTCN D-TA implementors.

The final step for facilitating data collection in this stage is to recruit more private sector companies with innovative digital data collection technologies into the CTCN Network of technology service providers to explore the potential of their expertise to bridge the gap in climate change data collection in implementing D-TA projects. A main element of the CTCN is its Network members, involving a variety of climate technology experts and institutions that can join in the CTCN’s activities to bring climate solutions at the request of developing countries using their technical knowledge and expertise.

Given the data gaps in climate action tracking, the emergence of new digital data collection technologies, such as earth observation (e.g., remote sensing satellite, unmanned aerial vehicles, generally from space) and IoT (e.g., smart meters and sensors, generally from the ground), promises to provide new advances in data collection and monitoring for the SDGs, particularly where traditional means of data collection, such as government-led statistical census efforts, are costly and time consuming [23]. Among the present 663 Network members as of September 2021, less than 10 organizations deal with digital data collection technologies in climate sectors such as flood forecasting systems, water treatment systems, water reservoir operations, energy savings in buildings, daylight harnessing, urban digitalization, etc.

Therefore, through the above three steps, it can be stated that fully supporting newly engaged innovative digital technology providers (third step) with numerous datasets from climate sector stakeholders (first step) and global database partners (second step) is a key accelerant strategy for digitalization during the climate technology transfer processes.

4.3.2. Digital Analysis Stage: The Role of CTCN as Digital Incubator

During this stage, it is important to consider how to overcome the barrier of the digital divide between the digital technology providers and local users in order for both parties to smoothly work together in increasing the number of D-TA requests from the developing countries and in preparing the best D-TA proposals for climate solutions, particularly in terms of digitalization. This can easily occur by joining the CTCN’s two-sided networks and participating in “co-creation processes through an inclusive approach” offered by the CTCN [24].

As a good example of the CTCN’s co-creation process, there is a Small Medium Enterprise (SME) clinic program for developing countries. During this program, digital technology or software tool providers and local SME partners from developing countries are invited to co-create processes together. Through this co-creation process, various digital technology providers can “incubate” the D-TA requests successfully aligned with local climate objectives and then “transform” the digitally collected data into valuable information or knowledge by various digital analyses for the best climate solution.

In addition, the CTCN operates the Youth Climate Innovation Labs [25], which aim to support countries in incentivizing innovation by applying digitalization. For example, two virtual Youth Climate Innovation Labs (one in Africa and one in Asia-Pacific) took place in November and December 2020, and they attracted more than 800 participants from more than 50 countries. The innovation Labs focused on developing solutions to CTCN partner SMEs’ identified needs and challenges through youth engagement and digitalization processes, such as early analysis tools for green wall design (https://www.ctc-n.org/youth-climate-innovation/case-study/nirwallna, accessed on 31 August 2021) and a carbon footprint platform (https://www.ctc-n.org/youth-climate-innovation/case-study/afri-carbon-pay, accessed on 15 September 2021).

By participating in these innovative activities as climate technology incubators, various digital private network members can transfer their cutting-edge digital technologies and skills to the local SMEs and university youth within target countries.

Hence, through this inclusive incubation during the digital analysis stage, it is clear that the CTCN implements a “coupled” innovation approach through various co-creation strategies such as SME clinics and Youth Climate Innovation Labs by digitally incubating local partners through collaborations with D-TA implementors from academia, research institutions, and the private sectors to provide “inside-out” D-TA requests, digital information, or digital knowledge from the collected “outside-in” data.

4.3.3. Digital Diffusion Stage: The Role of CTCN as a Digital Platform

Creating new real-time and high-quality climate data and inclusive analyses for information is not enough for tactical digitalization. Through a disseminating tool or platform for public communication, it becomes even more necessary that the output information must be transformed into actionable insights that can be easily digested by climate product users, policy decision makers, investors, local private consumers, and citizens. Currently, the CTCN has an online knowledge-sharing platform (www.ctc-n.org, accessed on 19 December 2021) with thousands of different information resources from a broad array of international climate sources (publications, case studies, tools, national climate plans and policies, climate technology and product descriptions, webinar videos, etc.).

For more efficient digitalization at the final digital diffusion stage, the convergence of the existing platform with various digital technologies is obviously a motivational driver to keep the current Network members engaged and to encourage new digital solution customers to seek digitally collaborative works with the CTCN. Via this digitalized platform, firstly, the CTCN may provide an online marketplace for various D-TA outputs of EWS, EIS, and RMS as one of the incentives for D-TA implementors overcoming the new digital market creation barrier. For example, these digitalized climate system outputs can be rapidly transformed to various types of outcomes on the platform, e.g., innovative web-based products of online pay-as-you-go applications or SaaS (Software as a service) such as cloud server-based waste-to-energy simulation tools, mobile climate monitoring applications, coastal hazard risk management system software, etc.

Second, there is online dissemination of the successful D-TA results or latest digital technology information for virtual capacity building through webinar video streaming or knowledge-sharing methods. For example, the CTCN supported a five-week interactive online education course focusing on blockchain solutions and other emerging technologies for global climate action [26]. This is a good illustration of how to build digital analytics competency for developing countries to overcome their digital technology lag. More specifically, this course aims to highlight blockchain as a decentralizing technology platform that has the potential to increase efficiency and security, reduce costs, and simplify data management in the context of climate change mitigation and adaptation. During the course, discussions were held around real-world problems related to climate change such as renewable energy, deforestation, carbon markets, and green finance.

Figure 6 depicts the schematic for summarizing this research on digitalization of the CTCN with three steps of the digitalization review, the innovation analysis, and the strategy suggestion. Recognizing that the CTCN should play role as a digital data source, incubator, and platform for innovative digitalization, eventually, the CTCN itself can be regarded as a convener and trustworthy global institution to form a digital ecosystem, such as the one proposed by UNEP [27], which provides open source to high quality climate data, inclusive analytical incubation, and policy insights for digital diffusion.

Furthermore, in order to make an ecosystem functional, the CTCN can distribute more transparent and digitally automated services through the proactive interactions and linkages with various stakeholder groups by applying the future plausible digital methodologies for: (1) online requests from developing countries, (2) automatically reviewing and selecting the best technology implementors for response plans, (3) automatic matchmaking based on AI for analyzing or executing the digitally collected data (on innovative technologies, analytic tools, climate issues, local contexts, etc.) from both technology providers and users, (4) co-creation for incubation from laboratory technologies to new digital business items with further financial supports, and (5) the online marketing of digital products or digital knowledge diffusion through the digitalized platform.

5. Conclusions

In this paper, the innovative digitalization features during climate technology development and transfer processes were successfully identified by analyzing the previous Technical Assistances provided by CTCN and their convergence with various digital technologies (D-TAs) on the basis of staged innovation. As the first step, we reviewed various digitalization projects for three climate sectors: risk prediction, policy decision making, and resource optimization.

After that, we identified the major barriers to digitalization through in-depth interviews with major digital-climate stakeholders, and then, based on a staged innovation model proposed in our previous study, we clearly proposed three digitalization stages of digital collection, digital analysis, and digital diffusion within the context of outside-in, coupled, and inside-out innovation models during various CTCN D-TA activities.

Finally, based on the findings in this analytical study, future strategies to enhance digitalization during climate technology transfer were proposed to enhance the matchmaking role of the CTCN between technology providers and users. First, as a digital data source for various Network members, the CTCN can establish some datasets of digital information from climate sector stakeholders and global partners at the first digital collection stage. Then, the CTCN can take an inclusive co-creation approach with local partners for the collaborative design of new D-TA requests, the preparation of the best analytic methodologies, and the incubation of their digital endogenous capacities at the second digital analysis stage. Finally, at the third digital diffusion stage, enhanced IT connectivity to the CTCN website platform can be undertaken as an efficient digitalization strategy for further digital market-friendly innovation.