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The purpose of this article is to develop a configurational approach based on the TOE framework (technology, organization and environment) to understand the degree of implementation of I4.0 technologies in manufacturing small- and medium-sized enterprises (SMEs). Specifically, the study considers technological infrastructure and competence, I4.0 integration capabilities, organizational agility and strategic flexibility, environmental dynamism and industry-specific forces as simultaneous pre-conditions for achieving an effective implementation of I4.0 technologies.

This study uses the fuzzy-set qualitative comparative analysis (fsQCA) methodology as it allows for asymmetric and configurational-focused testing of proposition and sound theoretical development. In total, 305 responses were collected through a survey administered to SME managers in Europe and the United Kingdom (UK).

The study examines the influence of technology, organizational and environmental aspects on I4.0 technologies implementation in SMEs. High I4.0 degree of implementation is structured around 5 configurations, while other 4 configurations are related to low levels of I4.0 implementation.

This study proposes a configurational approach for SMEs to become I4.0 ready and how they may successfully implement I4.0 technologies. Such findings represent an original and novel contribution to existing research, offering a broad view on the I4.0 implementation by manufacturing SMEs.

This study aims to explore customer perceived value (CPV) dimensions in the context of free mobile educational applications (EduApps) which are paramount in learning-based digital start-ups and are essential for the implementation of circular economy (CE). The purpose of the present study is to identify dimensions of CPV specifically for EduApps and propose a conceptual model that would assist the digital start-up decisions which in turn can be a catalyst in navigating to a CE.

The study uses the Netnography approach by analyzing online user-generated content. A total of 13,147 reviews posted on the Google play store after using top free education apps were coded using ATLAS.ti 9 software.

Major dimensions of context-specific CPV are identified as technical value, content value, pedagogical value, gamification value and learning value. Subdimensions and items are extracted for each of these dimensions.

The larger subscriber base drives sponsorships, advertisements and donations which underpin the business model of free EduApps. This can be obtained through an attractive value proposition. Identifying context-specific value dimensions would aid entrepreneurs in optimal value mix development decisions. The proposed framework can be utilized by both researchers (for scale creation, comparative studies and quantitative studies) and practitioners (for entrepreneurial decisions on better value propositions).

CPV successfully describes consumer decision-making, but less attention is paid to linking the theory to the setting of mobile learning apps, where the bulk of research is focused on techniques like TAM, UTAUT, etc. In addition, studies identifying CPV from mobile apps with a specific focus on EduApps are sparse. Extant literature in this context is either based on a foundation of in-store business value dimensions or dominated by technical aspects when focused on the context of mobile apps. The current study bridges this gap.

This study aims to recognize the role of information system (IS) model on young adults’ experience of housing and real estate chatbots. This model of IS takes into account the quality of information, the quality of system and the quality of service.

This study uses a sample frame for analysis which comprises young adult population in India, i.e. between the ages of 18 and 35. A questionnaire consisting of five components was used to collect information in a structured manner. The 386 responses thus collected were analysed using the structural equation model.

It was found that there is a significant influence of the quality of information, quality of system and quality of service on young adults’ experience of housing and real estate chatbots. The findings also showed that there is moderation role of effort expectancy between the quality parameters and young adults’ user experience of housing and real estate chatbots.

This study focusses exclusively on the young adults from various parts of India. Future research can consider larger population categories across age groups and across sectors employing chatbots.

This study will enable in-depth understanding of IS model – quality dimensions’ relation with the user experience. In particular, housing and real estate organisations will profit from the expanded usage of artificial intelligence through chatbots for user correspondence and communication.

To the best of the authors’ knowledge, this study is first of its kind, as it investigates how IS model – quality dimensions affect the young adults’ experience of housing and real estate chatbots in India. This study also ventures into identifying the moderation role of effort expectancy between the quality dimensions as per IS model and young adults’ experience of housing and real estate chatbots. This study will be useful for the stakeholders of housing and real estate industry.

This study aims to examine how the knowledge breadth and depth of a patent affect its likelihood of being pledged. It also seeks to explore whether these relationships change diversely in different technological environments.

A complementary log-log model with random effects was conducted to test the hypotheses using a unique data set consisting of 348,927 invention patents granted by the China National Intellectual Property Administration from 1985 to 2015 belonging to 74,996 firms.

The findings reveal that both knowledge breadth and depth of a patent positively affect its likelihood of being pledged. Furthermore, the knowledge breadth and depth entail different degrees of superiority in different technological environments.

This study focuses on the effect of an individual patent’s knowledge base on its likelihood of being selected as collateral. It does not consider the influence of the overall knowledge characteristics of the selected patent portfolio.

Managers need to pay attention to patents’ knowledge characteristics and the changes in technological environments to select the most suitable patents as collateral and thus improve the success rate of pledge financing.

This study explores the impact of multidimensional characteristics of knowledge base on patent pledge financing within a systematic theoretical framework and incorporates technological environments into this framework.

This article empirically tests the impact of risk appetite of the executive team on the re-innovation strategy after technological innovation failure using a panel regression model from the perspective of regional financial development level of enterprises.

By means of time series global principal component analysis and panel regression model method, the study validated and analyzed the impact of risk appetite of the executive team on the re-innovation strategy after enterprise technological innovation failure.

The research found that the higher the risk appetite of executive team, the more inclined the enterprise is to choose the “focusing on quantity, ignoring quality” re-innovation strategy after technological innovation failure. The better the financial development level of the region where the enterprise is located, the better it can effectively reduce the re-innovation strategy of “focusing on quantity, ignoring quality” of the enterprise due to the high risk appetite of the executive team.

The findings of this study are helpful in improving the financial development level of the region where the enterprise is located. It can help the executive team of the enterprise to more objectively choose the innovation strategy after technological innovation failure, and reduce the phenomenon that the executive team of the enterprise only pays attention to the quantity of re-innovation and underestimates the quality of re-innovation after technological innovation failure due to its high risk appetite.

This study aims to investigate the structural characteristics, spatial evolution paths and internal driving mechanisms of the knowledge transfer (KT) network in China’s patent-intensive industries (PIIs). The authors' goal is to provide valuable insights to inform policy-making that fosters the development of relevant industries. The authors also aim to offer a fresh perspective for future spatiotemporal studies on industrial KT and innovation networks.

In this study, the authors analyze the patent transfer (PT) data of listed companies in China’s information and communication technology (ICT) industry, spanning from 2010 to 2021. The authors use social network analysis and the quadratic assignment procedure (QAP) method to explore the problem of China’s PIIs KT from the perspectives of technical characteristics evolution, network and spatial evolution and internal driving mechanisms.

The results indicate that the knowledge fields involved in the PT of China’s ICT industry primarily focus on digital information transmission technology. From 2010 to 2021, the scale of the ICT industry’s KT network expanded rapidly. However, the polarization of industrial knowledge distribution is becoming more serious. QAP regression analysis shows that economic proximity and geographical proximity do not affect KT activities. The similarity of knowledge application capacity, innovation capacity and technology demand categories in various regions has a certain degree of impact on KT in the ICT industry.

The current research on PIIs mainly focuses on measuring economic contributions and innovation efficiency, but less on KT in PIIs. This study explores KT in PIIs from the perspectives of technological characteristics, network and spatial evolution. The authors propose a theoretical framework to understand the internal driving mechanisms of industrial KT networks.

Unlike traditional industries, the e-cigarette is an epoch-making innovative product originating in China and occupying an absolute competitive advantage in the international market. The traditional A-U model describes the laws and characteristics of technological innovation in developed countries. In contrast, the inverse A-U model depicts the process of “secondary innovation” in late-developing countries through digestion and absorption. This paper aims to find out that if the e-cigarette, as a “first innovation” industry in a late-developing country, conform to the A-U model or conform to the “inverse A-U model”.

This paper takes the patent data of e-cigarettes from 2004 to 2021 as the research object, and uses Python’s Jieba segment words to divide product innovation and process innovation, and then uses statistical analysis methods to conduct empirical analyses on these data.

Thus, an improved A-U model suitable for the e-cigarette industry is proposed. In this model, product innovation in the e-cigarette industry appeared earlier than process innovation, but the synchronous development of product and process innovation is not lagging. The improved A-U model in the e-cigarette industry is not only different from the traditional A-U model but also does not conform to the inverse A-U model.

It is conducive to expanding and clarifying the theoretical contribution and applicable boundaries of the A-U model and has sparked thinking and exploration of the A-U model in e-cigarettes and emerging industries.

On this basis, suggestions on the development path and countermeasures of the e-cigarette industry are put forward.

Based on the e-cigarette industry, this paper takes patents as the research object and provides the method of dividing product innovation and process innovation, and proposes an A-U model suitable for the e-cigarette industry on this basis. By comparing the traditional A-U model with the inverse A-U model in latecomer countries, the background and causes of e-cigarette A-U model heterogeneity are analyzed from different stages and overall morphology. Based on this, the heterogeneity characteristics of e-cigarette innovation are summarized and sorted out.

A new round of technological revolution is impacting various aspects of society. However, the importance of technology adoption in fostering firm innovation is underexplored. Therefore, this study aims to investigate whether robot adoption affects technological innovation and how human capital plays a role in this relationship in the era of circular economy.

Based on the robot adoption data from the International Federation of Robotics (IFR) and panel data of China's listed manufacturing firms from 2011 to 2020, this study uses regression models to test the impact of industrial robots on firm innovation and the mediating role of human capital.

The results demonstrate that the adoption of industrial robots can significantly promote high-quality innovation. Specifically, a one-unit increase in the number of robots per 100 employees is associated with a 13.52% increase in the number of invention patent applications in the following year. The mechanism tests show that industrial robots drive firm innovation by accumulating more highly educated workers and allocating more workers to R&D jobs. The findings are more significant for firms in industries with low market concentration, in labor-intensive industries and in regions with a shortage of high-end talent.

Due to data limitations, the sample of this study is limited to listed manufacturing firms, so the impact of industrial robots on promoting innovation may be underestimated. In addition, this study cannot observe the dynamic process of human capital management by firms after adopting robots.

The Chinese government should continue to promote the intelligent upgrading of the manufacturing industry and facilitate the promotion of robots in innovation. This implication can also be applied to developing countries that hope to learn from China's experience. In addition, this study emphasizes the role of human capital in the innovation-promoting process of robots. This highlights the importance of firms to strengthen employee education and training.

The adoption of industrial robots has profoundly influenced the production and lifestyle of human society. This study finds that the adoption of robots contributes to firm innovation, which helps people gain a deeper understanding of the positive impacts brought about by industrial intelligence.

By exploring the impact of industrial robots on firm innovation, this study offers crucial evidence at the firm level to comprehend the economic implications of robot adoption based on circular economy and human perspectives. Moreover, this study reveals that human capital is an important factor in how industrial robots affect firm innovation, providing an important complement to previous studies.

Energy conservation and environmental protection industry (ECEPI) is a strategic choice to promote energy conservation and emission reduction, develop green economy and circular economy. However, China’s ECEPI is still in the stage of rapid development and the overall scale is relatively small, what development periods have the ECEPI experienced? This study aims to contribute to a better understanding of collaborative innovation evolution based on social network analysis from the perspective of multi-dimensional proximity.

Methodologically, this study uses social network analysis method to explore the co-evolution of multidimensional collaboration networks. It divides China’s ECEPI into four periods based on national policies from 2001 to 2020. This contribution constructs collaborative innovation networks from geographical, technological and organizational proximity.

The results show that the collaborative innovation network was initially formed in the central region of China, gradually expanded to neighboring cities and the core positions of Beijing, Jiangsu and Guangdong have been continuously consolidated. C02F has been the core of the collaboration networks, and the research focus has gradually shifted from the treatment of wastewater, sewage or sludge to the separation field. Enterprises always occupy a dominant position in the collaboration networks.

This research investigates the dynamic evolution process of collaborative innovation network in China’s ECEPI from the perspective of multidimensional proximity, explores the community structure, important nodes and multidimensional proximity features in the network, expands the research perspective on evolution characteristics of innovative network and the research field of social network analysis. Theoretically, this study enriches collaborative innovation theory, social network theory and multi-dimensional proximity theory.

This study aims to analyze the determinants influencing Chinese manufacturing companies in implementing lean manufacturing (LM).

The determinants to be explored in this study consist of technological, organizational and environmental (TOE) dimensions. A questionnaire survey was conducted on Chinese manufacturing companies, and 208 samples were analyzed.

The findings show that the relative advantage of LM and organizational support have significantly positive effects on Chinese manufacturing firms’ adoption of LM. The complexity of LM, quality of human resources, organizational readiness, customer pressure, international situation, governmental support and environmental uncertainty do not have significant effects.

This paper contributes to the literature by using the TOE model to explore the factors influencing LM adoption in the Chinese manufacturing industry.