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The purpose of this study is to define and develop a new technological development path for latecomer firms in developing countries.

An analytical framework for development based on the technological capability (TC) dimensions is developed and examined in the drilling sector. Since the process of TC accumulation is dynamic, the case study approach is the best method for an exploratory theory-building study. Through a comparative case study of two Iranian drilling contractors, a new path for the technological development of latecomer oil service companies is proposed.

The study of two cases indicates that despite having similar scope and levels of TC, one of them demonstrated superior technical performance. To address this difference, the concept of operational efficiency is introduced which is considered the outcome of increasing the depth of TC.

Although upgrading the level of technological and innovation capability is an important path for technological development, latecomers that suffer from various disadvantages can perform their routine activities with superior performance and develop through their basic operational/production capabilities. Also, specialized indicators designed for assessing the level and depth of TC in the drilling industry have important insights for evaluating the technological and competitive position of oil service companies.

To the best of the author’s knowledge, this study takes the first step in defining and elaborating on the concept of depth of TC as a development path for latecomers. It also introduced a novel approach to the global operational/production efficiency frontier as a target for their catch-up.

This study aims to evaluates a public policy program that finances projects for the development of innovative technological solutions. This paper analyzed the influence of human and social capital on the development of the projects, under the perspective of the policy’s effectiveness and efficiency. This specific policy adopted the funding model of economic subsidy by means of grants, which shows the significant engagement of the public sector in applying nonrefundable resources more directly through loans, assuming the role of an entrepreneurial state, according to Mazzucato (2011, 2018) and Tavani and Zamparelli (2020).

This is a quantitative-descriptive study, according to Marconi and Lakatos (2017). This study is descriptive, for presenting information on innovation projects funded by FUNCAP (Ceará Foundation for Support to Scientific and Technological Development). In addition, this study is quantitative, by establishing multivariate relationships among the variables that relate to human capital and social capital, which are relevant to technological and innovative development, and by introducing variables on technological evolution, proposed as measures of the program’s effectiveness (DTRL, MkTRL) and efficiency (ETRL).

This paper sought to contribute on public policies for innovation, more specifically on analyzing variables that may affect the development of technological and innovative projects in knowledge-intensive companies. The authors studied capitals potentially important for these companies in the development of innovative projects. Specifically, the authors sought to understand the importance of human capital and how it reflects in technical and scientific knowledge of the project team and of social capital and how it reflects the connection and social relationship among different team members. The results presented that the degree of efficiency of the public funding program depends on how much the teams of the benefited projects have accumulated knowledge, skills and technical capacities – the so-called teams’ human capital.

It is important to address the research sample as a research limitation, which had 72 responses obtained, from a submission rate of 284. Another study limitation is on the qualitative analysis of the topics addressed from the companies and policymakers perspectives, considering that the quantitative nature of the study does not allow for a deeper understanding of the qualitative perspective of the actors involved in the phenomenon studied. As recommendations for future studies, it is suggested to conduct qualitative studies on the aspects studied here. In this sense, it is possible to conduct case studies for specific companies, or policymakers, to clarify and deepen the relationships between the themes addressed here.

As for the practical implications of the research, both for managers of public funding programs and for company managers, the benefits of human capital, related to innovative project development teams, are important in programs that deal with technological development projects. In practice, this means that the greater the human capital of academic background of the members of the supported project teams, the more efficient the projects are in the process of developing their technologies by using the resources provided (Ashford, 2000; Chen et al., 2008; Lerro et al., 2014).

Hence, the authors conclude that the evaluated innovation-funding program through grants achieved acceptable results in terms of promoting the technological evolution of the benefited projects and bringing the technologies closer to the market. Its efficiency was the least favorable result, showing that the program needs to focus on improving this specific aspect. Within the investigated program, the issue that needs enhancement (efficiency – ETRL) was the one that presented significant relationships with the human and social capital of the benefited projects’ teams. Thus, it is possible that, by selecting more projects that have teams with high capital, the efficiency of the public policy, in this case the development of projects with high technological and innovative potential, will be possibly reached.

The findings strengthen the need for innovation public policies designed and implemented in a systemic way in the science, technology and innovation ecosystem, to provide a technological infrastructure and human capital necessary for developing projects with high technological and innovative potential (Ergas, 1987; Audretsch and Link, 2012; Caloghirou et al., 2015; Edler and Fagerberg, 2017; Silvio et al., 2019).

This study aims to predict artificial intelligence (AI) technology development and the impact of AI utilization activity on companies, to identify AI strategies dealing with the broad innovation activity of AI, and to construct the strategic decision-making framework of AI strategies for a small- and medium-sized enterprise (hereafter SME), to improve strategic decision-making practices of AI strategy in SMEs.

This study used the multiple methods on the design of two data collection stages. The first stage is an expertise-based approach. It organized the three groups of expert panels and conducted the Delphi survey on them in combination with the brainstorming of technology, innovation and strategy in the fourth industrial revolution. The second stage is in the complement approach of expertise-based results. It used the literature review to involve the analysis of academic and practical papers, reports and audio materials relating to technology development, innovation types and strategies of AI. Additionally, it organized the four semi-structured interviews. Finally, this study used the mind-map and decision tree to conduct each analysis and synthesize each analytical result.

This study identifies the precondition and four paths of AI technological development classifying into specialized AI, AI convergence with other technologies, general AI and AI control methods. It captures the impact of non- and technological innovation through AI on companies. Second, it identifies and classifies the six types of AI strategy: the bystander, capability-building, capability-holding, management-enhancing, market-enhancing and new-market-creating strategy. By using the decision tree, it constructs the strategic decision-making framework containing six AI strategies. Actionable points, strategic priorities and relevant instruments are suggested.

The strategic decision-making framework covering from AI technology development to utilization in a SME can help understand the strategic behaviours in SMEs. The typology of six AI strategies implies the broad innovation behaviours in SMEs. It can lead to further research to understand the pattern of strategic and innovation behaviour on AI.

This practical study can help executives, managers and engineers in SMEs to develop their strategic practices through the strategic decision framework and six AI strategies.

This practical study elicits the six types of AI strategy and constructs the strategic decision-making framework of six AI strategies from AI technology development to utilization. It can contribute to improving the practices of strategic decision-making in SMEs.

The purpose of this study is to create a methodological approach for identifying priority areas for science and technology (S&T) development and its empirical application within the city of Moscow. This research uncovers a wide range of multicultural and multidisciplinary global trends that will affect the development of major cities in an era of complexity and uncertainty, including the inherent complexity of urban contexts, demographic and socioeconomic trends, as well as scientific and ecological factors.

The methodological approach is based on classic foresight instruments. Its novelty lays in the blending of qualitative and quantitative methods specially selected as the most appropriate for the identification of S&T areas in an era of complexity and uncertainty, including horizon scanning, bibliometric analysis, expert surveys and the construction of composite indexes with respect to the scope and resources of the research and the selected object for empirical application – Moscow, which is one of the world’s largest megacities. The analysis was performed for the period of 2009–2018 and expert procedures took place in 2019.

As a result, 25 global trends were identified, evaluated and discussed over the course of an expert survey and subsequent expert events. Ten priority areas of S&T development were determined, including 62 technological sub-areas within them and the most important market niches for all identified technological sub-areas, which could be useful for the world’s megacities. The results of this study are illustrated using the construction sector. Based on the conducted research and results, a list of recommendations on S&T policy measures and instruments were suggested, including the creation of the Moscow Innovation Cluster, which by the end of 2023 contained more than 6,000 projects and initiatives, selected using the findings of this investigation.

This research contributes to the existing literature and research agenda of setting priorities for S&T development and shows how it can be done for a megacity. The blended foresight methodology that was created within the study satisfies the criteria of scientific originality, is repeatable for any interested researcher, is applicable to any other city in the world and demonstrates its high efficiency in empirical application. It could be used for creating new agenda items in S&T policy, setting S&T priorities for a megacity and integrating the results into decision-making processes. This study provides recommendations on the further implementation of the designed methodology and results into a policymaking system. Moreover, the example of the Moscow Innovation Cluster, which was created based on the results of our research, demonstrates these recommendations’ practical significance in real life, which is quite valuable. The limitation of this study is that it is not devoted to urban planning issues directly or the promotion of R&D areas; it is about setting promising S&T priorities in an era of complexity and uncertainty for megacities.

Using the industrial data between 2000 and 2016, this study analysed the process of coupling and coordinated development of technological innovation and standardisation. Accordingly, the study considered the high-tech industry (five sub-sectors) in China as the research object.

Based on the summary of innovation and standardisation literature review, this study constructed a theoretical model of the influence of technological innovation and standardisation on industrial development from the perspective of the coupling system. Furthermore, the study employed multivariate linear regression analysis to explore coupling coordination relationships.

The study results revealed that high coupling coordination between technological innovation and standardisation is highly conducive to industrial development. Moreover, requirements for standardisation levels differ owing to different stages and characteristics in each segmented industry.

This study primarily contributes to the literature by using a bibliometrics tool to summarise related literature on innovation and standardisation and provides a new perspective of reviewing, and it also offers new evidence on the coupling coordination relationship between innovation and standardisation in the high-tech industry.

This study aims to examine the dimensions of technological innovation capability (TIC) and associated factors from the perspectives of sustainability.

The authors have systematically reviewed publications by synthesizing and comparing the findings and arguments from previous studies.

The study locates a wide-ranging advance of sustainable TIC as a construct by demonstrating the leading dimensions and key factors interrelated to the sustainable TIC. The foremost IC that has been addressed includes process, product, marketing, R&D and knowledge ICs.

Future research should test the extent of the contribution of TIC in intensifying the determining factors toward enhancing performance and sustainability. Besides, the undermined external aspects such as social responsibility and the natural environment should be addressed by future researchers to develop a comprehensive sustainable TIC.

This study reviews the various researches in the subject matter of sustainable TIC to show the developments as well as to provide comprehensive understandings in the subject.

This study aims to empirically analyze the impact of technological innovation on the quantity and quality of employment in the hospitality industry.

Using the data of 30 provinces in China from 2010 to 2020, this paper makes an empirical analysis through the fixed effect model.

The results show that process innovation has a significant positive impact on employment quantity, while product innovation has a significant negative impact on employment quantity. The creative effect of process innovation and the substitution effect of product innovation offset each other, so in the long run, the impact of technological innovation on employment quantity is not significant. However, technological innovation has significantly improved the employment quality of the hospitality industry.

Because technological innovation has replaced part of the labor force, hospitality could guide the labor force in a positive direction. To promote innovation and retain talents, hotels should train employees’ digital thinking and attract high-skilled talents.

This research is unique in using process innovation and product innovation as the main measurement indicators of technological innovation, unlike previous studies that often relied on technological progress to conclude.

Technology is an important factor contributing to the economic development of countries. In the context of the 4th industrial revolution, a country's success lies in its ability to grasp and absorb the level of technology into production and economic development. This aims of this research are to evaluate the impact of the tourism and technological contribution on economic growth in East Asian countries in the period of 2010–2019.

This research uses the feasible generalised least squares (FGLS) to revise the diagnostic problems and other advanced techniques to check the robustness; the research results confirm that there is no impact between tourism and economic growth.

The main driving force behind economic comes from: technological contribution, financial development and foreign direct investment inflows.

The research confirms that there is a significant and negative relationship between exchange rate and economic growth.

The pandemic has brought to light the importance of quickly adopting new technologies and building resilient organisations. Also, the Sustainable Development Goals (SDGs) can be addressed in large part through technological innovations. The development of smart systems which are linked with the Internet of Things (IoT) can create different opportunities to strategically face the barriers linked with the SDGs and make sure that there is an environmentally sustainable, equitable and healthy society. This study has utilised secondary and qualitative data and has adopted the interpretative and deductive approaches. It has given significance to several aspects of the SDGs and has linked them with digital technology such as accessibility to safe and clean portable water, production of sustainable food along with the generation of green energy and its utilisation. This study has evaluated the advantages of digitalisation so that it can catalyse the transition towards SDGs and improve the health of the citizens by giving digital accessibility specifically to the underserved community. The research has selected the most essential themes which are linked to the context of SDGs and has deeply evaluated a lot of information obtained from authentic secondary resources. At last, it provides a conclusion and recommendations where it has suggested several initiatives which could be made for enhancing the overall scenario and has also disguised the limitations that were identified while completing the study.

With the deep development of the new technological revolution and industrial transformation, the development, application, expansion and integration of digital technology provide opportunities for transforming the manufacturing industry from traditional manufacturing to intelligent manufacturing. However, little research currently focuses on analyzing the influencing factors of intelligent development in this field. There is a lack of research from the perspective of the digital innovation ecosystem to explore the intrinsic mechanism that drives intelligent development. Therefore, this article starts with high-end equipment manufacturing enterprises as the research subject to explore how their digital innovation ecosystem promotes the effectiveness of enterprise intelligent development, providing theoretical support and policy guidance for enterprises to achieve intelligent development at the current stage.

This article constructs a logical framework for the digital innovation ecosystem using a “three-layer core-periphery” structure, collects data using crawling for subsequent indicator measurement and assessment and uses the fuzzy set Qualitative Comparative Analysis method (fsQCA) to explore how the various components of the digital innovation ecosystem in high-end equipment manufacturing enterprises work together to promote the development of enterprise intelligently.

This article finds that the various components of the digital innovation ecosystem of high-end equipment manufacturing enterprises, through mutual coordination, can help improve the level of enterprise intelligence. Empirical analysis shows four specific configuration implementation paths for the digital innovation ecosystem of high-end equipment manufacturing enterprises to promote intelligent development. The core conditions and their combinations that affect the intelligent development of enterprises differ in each configuration path.

Firstly, this article discusses the practical problems of intelligent transformation and development in the manufacturing industry and focuses on the intelligent development effectiveness of various components of the digital innovation ecosystem of high-end equipment manufacturing enterprises in the context of digitalization. Secondly, this article uses crawling, text sentiment analysis and other methods to creatively collect relevant data to overcome the research dilemma of being limited to theoretical analysis due to the difficulty in obtaining data in this field. At the same time, based on the characteristics of high-end equipment manufacturing enterprises, the “three-layer core-periphery” digital innovation ecosystem framework constructed in this article helps to gain a deep understanding of the development characteristics of the industry's enterprises, provides specific indicator analysis for their intelligent development, opening the “black box” of intelligent development in the industry's enterprises and bridging the gap between theory and practice. Finally, this study uses the fsQCA research method of configuration analysis to explore the complexity of the antecedents and investigate the combined effects of multiple factors on intelligent development, providing new perspectives and rich research results for relevant literature on the intelligent development of high-end equipment manufacturing enterprises.