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The purpose of this paper is to analyse innovation policies in India from 1958 to 2020. A policy tools framework was developed to compare the innovation policies in India. India developed and implemented four innovation policies from 1958 to 2013. The recent policy change was brought in the year 2020 with releasing the draft of the Science, Technology and Innovation Policy (STIP 2020). The authors analysed the recent draft of STIP 2020 with the earlier four innovation policies.

Innovation policies implemented from 1958 to 2013 in India were studied and analysed in the “text as a data approach” and a comparative policy analysis tool was designed for this purpose. The recent draft of STIP 2020 was evaluated and the provisions of the fifth draft of STIP 2020 were compared with the previous four innovation policies' design and formulation. The CPA tool design consists of five broad themes Awareness and capacity building; Finance and infrastructure; Resource management and governance; Outreach and networking; and Policy implementation and evaluation.

Draft STIP 2020 has many features similar to earlier policies. However, policy has focused on bringing in more clarity about national challenges, goals and objectives, yet it needs better implementation to achieve stated outcomes more effectively and efficiently. New initiatives include strengthening the innovation system with open science, improving STI education, expanding the financial landscape, establishing national STI observatory acting as a central repository of all data related to the STI ecosystem and accountable research ecosystem, promoting translational and foundational research of global standards, promoting entrepreneurship, self-reliance, mainstream science communication and public engagement and decentralised institutional mechanisms. Thus, the STIP 2020 is ambitious in its approach to promoting STI in India and needs a supportive mechanism to achieve the stated objectives.

Current comparative policy analysis focused only on identifying similarities and differences among innovation policies implemented in India from 1958 to 2020 and its evolutionary changes in policy and its instruments choice. The recent draft STIP 2020 is not approved and has no update regarding its approval and implementation by the government. The revised and yet to implement STIP 2020 may have variances in the policy instruments. The earlier policies are so broad and without specific problem statements. They were released as statements and resolutions which makes it is challenging to understand the impact of each policy. Similar policy tools in STI 2013 and STIP 2020 were only considered to observe the policy instrument choice. The achievements of the innovation policies implemented before STIP 2020 are not included. Evolutionary changes in the problem statements and policy tools prescribed in innovation policies are studied.

Department of Science and Technology, Government of India, released a draft of STIP in 2020. The draft of STIP was evaluated with previous Innovation Policies. To the authors’ understanding, this is the first attempt to evaluate the STIPs of India using the “text as a data” approach. The tool can be validated by using it for CPA of innovation policies of other emerging, developed and least developed economies to understand cross-country variations in policy instrument choice by policymakers.

This paper aims to use text mining methods to explore the similarities and differences between countries’ national digital transformation (DT) and Industry 4.0 (I4.0) policies. The study examines the applicability of text mining as an alternative for comprehensive clustering of national I4.0 and DT strategies, encouraging policy researchers toward data science that can offer rapid policy analysis and benchmarking.

With an exploratory research approach, topic modeling, principal component analysis and unsupervised machine learning algorithms (k-means and hierarchical clustering) are used for clustering national I4.0 and DT strategies. This paper uses a corpus of policy documents and related scientific publications from several countries and integrate their science and technology performance. The paper also presents the positioning of Türkiye’s I4.0 and DT national policy as a case from a developing country context.

Text mining provides meaningful clustering results on similarities and differences between countries regarding their national I4.0 and DT policies, aligned with their geographic, economic and political circumstances. Findings also shed light on the DT strategic landscape and the key themes spanning various policy dimensions. Drawing from the Turkish case, political options are discussed in the context of developing (follower) countries’ I4.0 and DT.

The paper reveals meaningful clustering results on similarities and differences between countries regarding their national I4.0 and DT policies, reflecting political proximities aligned with their geographic, economic and political circumstances. This can help policymakers to comparatively understand national DT and I4.0 policies and use this knowledge to reflect collaborative and competitive measures to their policies.

This paper provides a unique combined methodology for text mining-based policy analysis in the DT context, which has not been adopted. In an era where computational social science and machine learning have gained importance and adaptability to political and social science fields, and in the technology and innovation management discipline, clustering applications showed similar and different policy patterns in a timely and unbiased manner.

Korea’s Institute for Basic Science (IBS), the first research institute dedicated to basic science in Korea, started ten years ago as part of a science policy called the Science Belt. It is noteworthy that Korea, with a short history of basic science, established such a research institute exclusively for basic science within a short period of time and made it one of the representative institutions of basic science in Korea. This paper aims to uncover the impetuses and constraints surrounding the policy of Science Belt, centering on the IBS.

Kingdon’s stream theory is used to clarify the factors that acted as impetuses or constraints for the Science Belt. For the analysis, in-depth interviews with the active policy participants were conducted in addition to the thorough literature review. The interviews enabled an in-depth understanding of the underlying factors for the Science Belt and the actual procedures of the policy decision.

This study found that the most powerful impetus in the Science Belt policymaking process was the President and a small group composed of a few scientists who played a leading role in the political stream. The constraint of the Science Belt was that the participation of scientist experts and governmental officials, the so-called invisible participants of Kingdon, was insignificant. In particular, there was no system in place to select policy alternatives for basic science through discussion between scientists and governmental officials.

The temporal scope of this study was limited to policy formation, that is, until the establishment of IBS. Therefore, future studies shall conduct a research on the implementation of the actual policy, IBS’s achievements and IBS’s impact of Korea’s basic science community.

This study applied both a theoretical framework and in-depth interviews along with the literature overview to understand a policymaking process from various angles.

This chapter is devoted to sustainable human resource management that leads to sustainable competitiveness. It features the ways human resources can be managed to carry out sustainable goals and the impact of sustainability on employees' attitudes and behaviours. The aim of this study is to explore the complex objectives of sustainability and human resource management and empirically investigate the dynamic relationship between human resources in science and technology and sustainable competitiveness in the case of 35 European countries. Our contribution emphasizes this interrelationship and its causality. For this research, we applied a vector auto-regression (VAR) model, and the Granger causality method to examine the relationship between human resources in science and technology and sustainable competitiveness. A panel data included 314 observations between 2012 and 2021. The panel VAR for analysing the impulse response function was enriched with the 5% and 95%, using Monte Carlo simulations. The research results revealed bidirectional causality in the European countries between human resources in science and technology and sustainable competitiveness. Human resources in science and technology trigger sustainable competitiveness and vice versa. As an element of originality, our study demonstrates that human resources in science and technology contribute to sustainable performance, and, on the other hand, a more competitive and sustainable environment contributes to the development of human resources in science and technology. Thus, the chapter outlines the role of human resources in science and technology with regard to sustainable human resource management (HRM), and how to navigate these objectives so that they can positively influence sustainable competitiveness.

This paper aims to understand the current development situation of scientific data management policy in China, analyze the content structure of the policy and provide a theoretical basis for the improvement and optimization of the policy system.

China's scientific data management policies were obtained through various channels such as searching government websites and policy and legal database, and 209 policies were finally identified as the sample for analysis after being screened and integrated. A three-dimensional framework was constructed based on the perspective of policy tools, combining stakeholder and lifecycle theories. And the content of policy texts was coded and quantitatively analyzed according to this framework.

China's scientific data management policies can be divided into four stages according to the time sequence: infancy, preliminary exploration, comprehensive promotion and key implementation. The policies use a combination of three types of policy tools: supply-side, environmental-side and demand-side, involving multiple stakeholders and covering all stages of the lifecycle. But policy tools and their application to stakeholders and lifecycle stages are imbalanced. The development of future scientific data management policy should strengthen the balance of policy tools, promote the participation of multiple subjects and focus on the supervision of the whole lifecycle.

This paper constructs a three-dimensional analytical framework and uses content analysis to quantitatively analyze scientific data management policy texts, extending the research perspective and research content in the field of scientific data management. The study identifies policy focuses and proposes several strategies that will help optimize the scientific data management policy.

The online Question and Answer community is full of a large number of science and technology topics, the discussion and dissemination of which play an important role in promoting the popularization of new technologies and cultivating public enthusiasm for science. However, the spread of false information and rumors weakens the community's positive effect, making the community more difficult for people to obtain useful information on such topics. Research on the influencing factors and governance of the spread of false information on science and technology topics has become the key to the spread of popular science.

Therefore, this paper uses the Elaboration Likelihood Model as the theoretical framework to examine the role of the factors influencing the spread of false information on science and technology topics in Zhihu community on the information persuasion and the impact on public behavior attitude from the core path and the edge path. This paper compiles a crawler program to capture 12,893 response information under the “Metaverse” topic in Zhihu community as an empirical sample and uses text mining and conducts visual correlation analysis to explore the key factors affecting the persuasive transmission path of information on science and technology topics.

The research finds that the content specialization, content consistency and content coherence of science and technology topics affect personal judgment from the aspect of information content through the core path and have a positive correlation with information persuasion; the number of comments, the length of the text and the publishing authors' influence from the edge image characteristics through the edge path are positively correlated with the information persuasion. Then, from the perspective of topic platform, government and topic participants, this paper puts forward a general plan to improve the information persuasion of science and technology topics so as to deal with false information.

Compared with the small data set of the traditional questionnaire survey, the research based on community empirical big data is more reliable. The model takes into account the attitude and behavior of users and is more suitable for the research on the transmission path of scientific and technological information in the internet era. This research provides a direction for analyzing the text characteristics and development trends of information in the field of science and technology and is conducive to promoting the optimization of the network information environment and building a good ecology, with the spread of rumors about science and technology topics curbed and the governance of false information strengthened.

The purpose of this chapter is to illustrate the role of higher education establishments in Middle Eastern countries specifically Saudi Arabia. The contributions of higher education establishments are particularly significant in relation to regional and national innovation system, which have been earmarked as engine for growth of the local economy across the region. Our study has chartered the dynamic nature of higher education in the region and their networking capabilities in order to be recognized as key stakeholders of the emerging economy. The study is informed by theoretical dimensions of “open innovation” and how the framework can accommodate the dynamic nature of higher education establishments in order to provide further impetus to ambitious projects such as Vision 2030 in Saudi Arabia. Our study is limited by further empirical evidence but has implication for the region in offering new insights around the evolving conceptualization of entrepreneurial universities and national innovation system.

The purpose of this paper is to identify the historical trends and status of the national development of artificial intelligence (AI) from a nationwide perspective and to enable governments at different administrative levels to promote AI development through policymaking.

This paper analyzed 248 Chinese AI policies (36 issued by the state agencies and 212 by the regional agencies). Policy bibliometrics, policy instruments and network analysis were used to reveal the AI policy patterns. Three aspects were analyzed: the spatiotemporal distribution of issued policies, the policy foci and instruments of policy contents and the cooperation and citation among policy-issuing agencies.

Results indicate that Chinese AI development is still in the initial phase. During the policymaking processes, the state and regional policy foci have strong consistency; however, the coordination among state and regional agencies is supposed to be strengthened. According to the issuing time of AI policies, Chinese AI development is in accordance with the global situation and has witnessed unprecedented growth in the last five years. And the coastal provinces have issued more targeted policies than the middle and western provinces. Governments at the state and regional levels have emphasized familiar policy foci and played the role of policymakers, along with regional governments that also functioned as policy executors as well. According to the three-dimension instruments coding, the authors found an uneven structure of policy instruments at both levels. Furthermore, weak cooperation appears at the state level, while little cooperation is found among regional agencies. Regional governments cite state policies, thus leading to the formation of top-down diffusion, lacking bottom-up diffusion.

The paper contributes to the literature by characterizing policy patterns from both external attributes and semantic contents, thus revealing features of policy distribution, contents and agencies. What is more, this research analyzes Chinese AI policies from a nationwide perspective, which contributes to clarifying the overall status and multi-level relationships of policies. The findings also benefit the coordinated development of governments during further policymaking processes.