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A firm will seek an optimal balance between internal R&D and technology outsourcing when formulating its innovation strategy. This paper aims to provide a review of the determinants of firm's innovation strategy, and performs an empirical study on a sample from Chinese high‐tech industry, with the purpose of identifying two aspects of the issue: the choice patterns of Chinese firms over innovation strategy, and the innovation effect elasticity of different strategies.

The development of a multiple regression model supported by data from industry level and a statistic analysis.

Outsourcing is the major innovation strategy adopted by most Chinese high‐tech firms, especially technology import, which implies the imperfection of Chinese innovation service system. The empirical analysis also indicates the insufficiency of internal R&D expenditure and the weakness of absorptive capacity in Chinese high‐tech firms. Although, Chinese high‐tech firms prefer the outsourcing strategy in their innovation, the contribution of outsourcing is much smaller than that of internal R&D. When expenditures are increased by the same rate, the innovation output form internal R&D is twice the output of outsourcing. For improving Chinese firms' innovation efficiency, the reform of innovation service system is needed on the macro‐level, while on the micro‐level, it calls for firms to readjust their innovation strategy portfolio.

This paper will make up for the deficiency in current researches on innovation, which often apply firm samples in developed countries, and lack evidences from firm samples in developing countries. In addition, it will provide the decision‐making basis for Chinese Government's current actions in constructing and improving China's innovation service system.

This editorial aims at providing a general framework for papers in this special issue. The main theme is to understand the organizational effectiveness from recent developments in technology innovation and human resources strategies.

The editorial first describes the need for technology innovation and HRM integration. A three‐strategy model for global technology innovation and organizational development was adopted: personnel strategy, system strategy, and organizational strategy.

The personnel strategy could play a crucial role in enhancing the effects of human resources management (HRM) and entrepreneurship by supporting the main dimensions of HRM. The system strategy was used to facilitate technology innovation through knowledge management while the organizational strategy was adopted to create positive organizational culture and high performance systems.

The paper suggests that globally distributed engineering and international technology entrepreneurship be new area for theory building. The strategies from this special issue have implications for the study of new information technology innovation and e‐HR developmental approaches as well as professional service, customer relations modeling and strategic HRM.

The present research aims to explore the drivers of generative artificial intelligence (GEN AI)-based innovation adoption in the hospitality industry in Jordan.

To address the research gap and achieve the research work objectives, the Technology-Organization-Environment (TOE) lens and the structural equation modeling (SEM) approach were employed to analyze the sample data collected (n = 221) from the hospitality industry.

The findings indicate that relative advantage, top management support, organizational readiness, organizational culture, competitive pressures, government regulations support and vendor support significantly influence the GEN-AI-based innovation adoption, while the technological complexity is negatively associated with GEN-AI-based innovation adoption. Furthermore, the results showed there is no significant effect of cost on GEN-AI-based innovation adoption.

The paper analyses the TOE framework in a new technological setting. The paper also provides information about how GEN-AI-based innovation adoption may influence hospitality industry performance. Overall, this article provides new insights into the literature concerning AI technologies and through the TOE lens.

This paper aims to address the gaps in current research by exploring how blockchain technology influences corporate green innovation.

This study investigates the potential of blockchain technology to stimulate the green innovation of companies using the difference-in-difference model with a panel data set of 1,803 Chinese listed companies from 2012 to 2019.

The application of blockchain significantly increases the number of green invention patents obtained by companies but has no significant impact on green utility model patents, that is, blockchain applications improve the quality rather than the quantity of green innovation. The role of blockchain in promoting green innovation is particularly pronounced in state-owned enterprises, non-heavily polluting industries and older companies. The use of blockchain technology helps reduce sales costs and boosts research and development investments, thereby encouraging green innovation. Additionally, a company’s internal control quality plays a moderating effect.

Firstly, previous research on blockchain has primarily centered on its relationship with supply chain management. This article empirically tests the impact of blockchain applications on the green innovation of companies using the DID method. Secondly, current studies mainly explore the influencing factors on green invention patents. This article examines the impact of blockchain applications on both green invention patents and green utility model patents and identifies distinct influencing effects. Finally, this article introduces the internal control mechanism of enterprises into the DID model and explores the potential impact of the quality of internal control on the relationship between blockchain and green innovation.

This paper aims to investigate the relationship linking hard technology innovation with the high-quality development (HDP) of SRDI firms. SRDI firms are typically classified as medium-sized to moderately scaled businesses renowned for their specialized, refinement, differentiation and innovation (SRDI), with a focus on providing exceptional products or services to gain a competitive advantage in specific market segments. These firms are dedicated to expanding market share and enhancing innovation capacities both locally and globally. The research also aims to scrutinize the contextual effects of digital transformation within this framework.

Hard technology innovation consists of three essential components: innovative characteristics, newly developed technology-based intellectual property rights and the volume of R&D initiatives. The evaluation of HDP was performed utilizing the entropy method, with a specific emphasis on assessing value creation and value management capabilities. Subsequently, this study explores the impact of technological innovation on the HDP of firms using a dual-dimension fixed effects model.

Every aspect of hard technology innovation is essential for promoting the HDP of businesses. The digital transformation of businesses exerts a heterogeneous moderating influence in this process. This is evident in the constructive impact on the connection between innovation attributes and the volume of fruitful R&D initiatives, as well as the HDP of firms. Conversely, the moderating effect is deemed insignificant in the association between new technology-based intellectual property and HDP.

This research delves deeper into the underlying mechanisms that underlie the promotion of HDP through hard technology innovation, thereby expanding the scope of our exploration on the HDP of SRDI firms. It establishes a theoretical framework and practical directives for achieving enhanced development quality amidst the evolving landscape of digital transformation within firms.

The paper investigates how visibility, information technology and innovation management impact sustainability performance. It proposes a framework explaining the role of visibility in driving firms' sustainable performance and the relevance of innovation management and information technologies in enhancing organisational visibility. This study intends to add to the discussion within the management literature about the potential of innovation management to drive sustainability. It seeks to provide insight into the practices that small and medium-sized enterprises (SMEs) can adopt to improve their sustainable performance.

Using empirical methods, the study investigates SMEs in central Mexico. The demographic information in the dataset includes 15 years as an average length of service from firms. Of the surveyed firms, 70% were from the manufacturing sector and 30% were from the service sector, as these are the most representative sectors of the productive region. A variance-based structural equation model approach was used to test the hypotheses, processed with the partial least squares (PLS) regression method.

The research results show that visibility significantly impacts sustainability performance. Innovation management has a higher influence on visibility than information technologies, emphasising the need to improve the quality of information in firms, not just the tools. The findings support managers in comprehending the crucial importance of visibility in aiding firms to achieve higher sustainability performance.

The study only examined a sample of Mexican SMEs; therefore, the findings' generalizability must be considered within this context. Secondly, the survey only focused on services and manufacturing firms and a more detailed analysis of the sector could provide further clarity on the relationships between variables. As a result, future research should consider these limitations and explore additional contexts to improve the overall understanding of the topic. Moreover, the scale used to measure the variables was adapted from other researchers with similar context research and reflective variables.

The results provide helpful information for SME managers about the importance of focusing on innovation management processes and employing information technologies as crucial managerial strategies. This will aid in increasing visibility and supporting the development of sustainability performance in firms.

The world red-code, among others, with climate change and social gaps, has generated the need to contribute to sustainable development, and it has mobilised people on all levels all over the world for the simple purpose of preserving life. Therefore, society, as a crucial group that affects and is affected by this red-code situation, should act in favour of visibility, the use of high-quality information (e.g. transparent, accessible and relevant) and information technologies to promote sustainable practices. This could mean that society should be prepared to incorporate new capabilities and spaces to interchange knowledge as a participatory community that can contribute to better sustainable dynamics that could expand its participation in public decisions. Also, the government should encourage digital democracy (e.g. develop social participation platforms), opening and harmonising rules and mechanisms combining high-quality information with IT to provide flexible and adequate services that support sustainable development, such as efforts towards constructing sustainable and smart cities.

This study explores how innovation management can drive firms' sustainability performance, which is crucial for improving competitiveness. The question of how to enhance sustainability performance through managerial drivers is a critical one. This study empirically investigates the nexus of visibility and sustainability performance, innovation management and information technology with visibility.

Using AI to strengthen creativity and problem-solving capabilities of professionals involved in innovation management holds huge potential for improving organizational decision-making. However, there is a lack of research on the use of AI technologies by innovation managers. The study uses the theory of appropriation to explore how specific factors – agile leadership (AL), innovation orientation (IO) and individual creativity (IC) – impact innovation managers' use of generative AI tools, such as ChatGPT (CGA).

The research model is tested through a large-scale survey of 222 Italian innovation managers. Data have been analyzed using structural equation modeling following a two-step approach. First, the measurement model was assessed to ensure the constructs reliability. Subsequently, the structural model was analyzed to draw the conclusions on theorized model relationships and their statistical significance.

The research findings reveal positive associations between IO and IC with CGA, demonstrating that innovation managers who exhibit strong innovation orientations and higher Individual Creativity are more likely to adopt and personalize ChatGPT. However, the study did not confirm a significant association between AL and CGA.

Our findings have important implications for organizations seeking to maximize the potential of generative AI in innovation management. Understanding the factors that drive the adoption and customization of generative AI tools can inform strategies for better integration into the innovation process, thereby leading to enhanced innovation outcomes and improved decision-making processes.

With technological innovation elements and the competitive market environment becoming increasingly complex, numerous firms utilize network embeddedness to achieve and sustain innovation. However, empirical research has not conclusively established which form of network embeddedness more effectively facilitates corporate innovation. Drawing on the heterogeneous network resources perspective, this study explores the impact of market network embeddedness, technology network embeddedness and their synergy on the green innovation performance of manufacturing small and medium-sized enterprises (SMEs). Furthermore, it investigates the moderating role of resource orchestration capability in these relationships.

Through an online questionnaire survey of Chinese manufacturing SMEs, 293 sample data were collected, and the hierarchical regression analysis was conducted to test the hypothesis.

The results indicate that market and technology network embeddedness significantly enhance green innovation performance, with the former exerting a more significant impact. Furthermore, the synergy between market and technology network embeddedness positively influences green innovation performance. Additionally, resource orchestration capability strengthens the positive effects of both market and technology network embeddedness on green innovation performance, while the moderating effect of resource orchestration capability on the relationship between the synergy of the two and green innovation performance was insignificant.

The study faced many limitations, such as collecting primary data, which relied on a questionnaire only, using cross-sectional data and examining only manufacturing SMEs.

Based on the heterogeneous network resources perspective and integrating social network theory and resource orchestration theory, this study explores the impact of network embeddedness on the green innovation performance of manufacturing SMEs, which sheds new light on the network embeddedness research framework and also enriches the antecedents of green innovation. In addition, this study provides implications on how manufacturing SMEs effectively utilize network embeddedness and resource orchestration capability to enhance green innovation performance.

The purpose of this study is to empirically investigate the role of dynamic capabilities, specifically the sequence of sensing, seizing, and transforming capabilities, in highly uncertain, emerging technology environments. Focusing on the extended reality industry, the study aims to understand the antecedents to these dynamic capabilities, their sequential nature, and their subsequent impact on innovation and company performance.

Based on a survey of 130 German companies in the extended reality sector, we built a structural equation model that explores the relationship between dynamic capabilities, their antecedents, and their effect on innovation and company performance.

The analysis suggests that sensing capabilities positively influence seizing and transforming capabilities, while seizing directly contributes to transforming. Transforming capabilities are linked to improved innovation performance, which in turn boosts company performance. Organizational ambidexterity, market orientation, and technology orientation are found to be crucial antecedents, accounting for 33.1% of the variance in sensing capabilities.

This research illuminates the interdependence of dynamic capabilities in highly uncertain business environments, such as emerging technology markets. It contributes original insights by elucidating the sequential nature of dynamic capabilities and identifying their vital antecedents. It also enlarges the understanding of how dynamic capabilities impact firms’ innovation performance.

The main purpose of examining innovation development (ID), technology management (TM) and big data analytics capability (BDAC) from the perspective of information technology companies is to help these companies optimize their business strategies and increase their competitiveness. When these concepts are considered together, it is aimed to present suggestions that information technology companies can increase their innovation capacities, optimize their technology portfolios and develop their big data analytics capacities.

Data were collected from information technology companies working on big data analytics in technoparks in Istanbul. In the research, the Marmara region of Turkey was preferred because it is the region where the information technology sector is most common. In total, 503 questionnaires were collected. SmartPLS (4.0.8.4) licensed software was used in the research, and the results are presented with tables and figures.

As a result of the analysis of the data, it is supported by hypotheses that ID and TM have positive effects as independent variables and BDAC has positive effects as both independent and mediation variables.

In terms of the limitations of the research, since the data were collected only from the information technology companies in the technoparks in Istanbul, it would not be correct to generalize the analysis results. For this reason, it is recommended to develop a research model and contribute to the literature by considering this limited situation for similar studies to be conducted in the future.

By focusing on ID, it is important for companies to analyze their innovation processes and increase their ID capacity. On the subject of TM, analyses help companies identify their current technological infrastructure and development needs and optimize their technology portfolios. Big data analytics is an important tool that companies can use in their decision-making processes. Therefore, analyses of big data analytics can evaluate companies' current data analytics capacities and offer improvement suggestions.

So why are ID, TM and BDAC important? Why should a research model be developed to examine the effects of these variables? This situation can be understood by looking at the investments made by two world-class companies with headquarters in Istanbul/Turkey. L'Oréal Turkey integrates big data, cloud computing, artificial intelligence and digital platforms into its business processes by investing in new technologies and also makes a difference with innovation in environmental sustainability and social responsibility. PepsiCo, on the other hand, placed a great emphasis on innovation by opening its third Design and Innovation Center in Turkey and Europe in Istanbul. For this reason, examining the effects of ID, TM and big data analytics together in the research is important for the originality of the research. Examining these variables by focusing on their interactions and effects increases the originality of the subject.