Mapping Sustainable Development Activity; Its Evolution and Impact in Science, Technology, Innovation and Businesses
INTRODUCTION
Innovation policy is quickly moving to extend the measurement of innovation outcomes beyond economic gains (e.g. productivity). In this, the United Nations Sustainable Development Goals (SDGs) are quickly emerging as the de facto framework to measure the broader impacts of innovation, but measuring them is extremely challenging. This project aims to capture the sustainable development activities by an empirical Artificial Intelligence (AI) based model which enables measuring wide spectrum actions against the SDG framework, would these result out of R&D research, public funding and ecosystem collaborations of any entity (businesses, regional, national and international level). This project couples close interaction with businesses to apprehend their impact and vision for sustainability, which results in guidelines for established businesses, startup entrepreneurs, and actionable information for policymakers to enhance the driving forces; as well as revealing future research directions for researchers. The project will ultimately deliver a measure of the state of sustainability in Finland, a method to implement the measure at scale and evidence that validates the measure and method. The project is formed in four main working packages: 1) Conceptual framework of sustainable activity. 2) Developing a measuring model utilizing artificial intelligence methods. 3) Understanding companies incentives and barriers to sustainable development transition in Finland. 4) Formulating the best practices and a road map for sustainable development transition.
This project aims to identify the driving forces of sustainability and low carbon economy for the innovation ecosystem, create knowledge of the public policies impact, and provide guidelines for businesses. Exploring the driving forces of sustainable development requires a conceptual understanding of the sustainable development activities within science, technology, innovation and businesses. This important identification and classification task will be carried out with an advanced systematic literature review (SLR) process involving field experts. The SLR process will incorporate all documented science, technology and innovation artefacts, public policy documents and reports in order to generate a global and national “Concept Map” of sustainable development. This taxonomy informs the project on the measurement practices, guidelines and main indicators for measuring the spectrums of sustainable development activities.
An empirical methodological practice will utilize the identified data points regarding sustainable development activities and accordingly the criteria regarding their sustainability aspects to an AI model. The compiled AI model is capable of identifying sustainability-oriented aspects and the spectrum of it on any documented artefact. Coupling the AI model with the prior art “Net Impact” calculated measure of (sustainability) impacts on a company level; we can scale to recognize sustainability-oriented activities on business/sector level with the capability to put regions, nations and sectors into comparison.
Comprehending the sustainable-oriented activity on macro scales, we proceed to individual company cases with the purpose of identifying the sustainable development driving forces and obstacles. This investigation will happen with close interaction with company cases at three levels: organizational (business model), sectoral (ecosystem), externalities (global practices, policy and regulations). The close interaction with business requires a tested approach for identifying the sustainable development activity, impact and goals. We will acquire methods such as “Carbon Handprint Calculation” and “Life Cycle Sustainability Analysis (LCSA)” with the purpose of encapsulating aspects such as material use, energy use, lifetime and performance of product/services, waste and ways of carbon capture and storage. Based on the processing of individual company case interviews and comprehensive data collection via surveys, we can provide an integrative model for sustainable development indicating the driving forces and challenges ahead.
UTILIZATION ROADMAP
WP1: Comprehending the “sustainable development” aspects in Science Technology and Innovation as well as Business activities. M1, M2
- T1.1. Monitoring the introduction of sustainable products and services, and public actors’ initiatives and support for sustainable R&D.
- T1.2. Identifying the measurement practices/guidelines and main indicators for measuring the spectrums of sustainable development activities.
- T1.3. Capturing the collaborative innovation ecosystem environment (University-Government-Industry collaboration) regards to sustainable development artefacts.
- T1.4. Global understanding of public policy instruments for facilitation in the phase of transitions to sustainable development.
- T1.5. Studying the public policy intervention (e.g. Missions, Financing) in regulating incentives to mobilize innovation’s system capabilities to encourage sustainable change.
WP2: Developing measuring model for capturing of “sustainable development” oriented activities on business/sector level with capability to put regions and nations into comparison. M3, M4, M5
- T2.1. Continuous data monitoring and retrieving will be set up and targeted at selected sources of STI and Business activities such as patent, scientific publications, trade journals, businesses annual reports, SWOT documents, news feed, social media and reposted databanks at international organizations (OECD, UN, EC, World Bank).
- T2.2. Design an empirical methodology utilizing Machine Learning (ML) methods to learn “sustainable development” dimensions by incorporating the major data points. The compiled AI method from the ML model will be operationalized to detect sustainable-oriented activity spectrum on any documented artefact. These model results are coupled with the prior art “Net Impact” calculated measure on company level sustainable activity.
- T2.3. Interesting cases will be selected for further analysis to find out how the new sustainable oriented innovations came about (what kind of companies and innovators, links to research programs, local circumstances, public funding support). This analysis is based on a proprietary, rich historical dataset of 5000+ significant Finnish innovations, economic data, and data collected at VTT on public support.
- T2.4. Investigating the role of public funding in creating momentum for “sustainable development” activity on a regional level. An econometric analysis will be performed to define the intensity and effect of the funding and policy instrument accounting for regional differences and the nature of sustainable-oriented artefacts.
WP3: Understanding of “sustainable development” oriented activity with businesses. M6, M7
- T3.1. Surveys, interviews, data collection sheets and collaboration workshop to understand companies’ challenges and needs (Organizational, Business model, technical, economic, collaborating ecosystem).
- T3.2. Using methods such as “Carbon Handprint Calculation” and “Life Cycle Sustainability Analysis (LCSA)” with the purpose of encapsulating companies’ activities such as: material use, energy use, lifetime and performance of product/services, waste and ways of carbon capture and storage.
- T3.3. Processing company extracted information for categorising incentives and barriers to “sustainable development” transitions for Finnish companies.
WP4: Recommendations and dissemination. M8, M9
- T4.1. Identifying the possible points of collaboration and hindrance between society and business sector for sustainable development. This will be achieved by looking at best practices and evaluation of implementing them for Finnish society.
- T4.2. Transferring lessons learned and policy implications to stakeholder’s trough Public actors’ actions, frameworks, Policy briefs and Road maps. This will be facilitated by forums for transition such as SDG booster workshops.
- T4.3. Infographic and data visualization toolkits for easy and impactful transition
