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Investigates communication and diffusion theory in the industrial sector, an area seldom considered. Examines the evidence from consumer markets and then goes on to extend these approaches for industrial marketing. States that the theory of diffusion of innovations should be modified for industry by the introduction of individual and economic factors; identification of forms of influence of the kind not requiring interpersonal interaction and their effect on the adoption decision; and the development of data. Concludes by questioning the relevance of diffusion to the industrial market if it is not proven to be a systematic predictable process.

The aim of this study is to investigate technological and innovation orientation contribution to the development and sustainability of the industrial sector.

The authors gathered the perspectives of many experts who were aware enough of their company’s technical and innovation orientations to participate in this study to understand how technology and innovation orientations may affect sustainability and development. These people included the company managers, accounting department heads, IT department workers and employees in the innovation department. This was accomplished by distributing a thorough questionnaire intended to gather their perspectives.

The study’s results highlight the significant positive relationship between technological and innovation orientation. Moreover, the study demonstrates that both technological and innovation orientation were found to positively impact the sustainability and development of the industrial sector.

This study provides practical insights for policymakers, industrial managers and innovation supporters in Jordan. Managers can use these insights to reassess technology adoption and innovation strategies. Additionally, investing in staff skills and technology readiness can boost efficiency, competitiveness and long-term growth.

To the best of the authors’ knowledge, this study is pioneering research to shed light on the connection between technological orientation, innovation orientation and sustainability and development in the industrial sector, providing valuable insights for policymakers and practitioners alike.

This study investigates whether and how place-based industrial relocation policy affects firm innovation.

By exploiting the establishment of China's National Industrial Relocation Demonstration Zones (NIRDZs) as a quasi-natural experiment in a difference-in-differences design, the authors examine the externalities of industrial policies that support sustainable development and growth from the perspectives of firms' patenting activities.

The study consistently finds that the NIRDZs policy significantly boosts local firm innovation, translating into a 60.46% increase in the patent applications of treated firms. The estimation results remain robust to a series of alternative specifications. Moreover, heterogeneity analysis suggests that the firms that benefited most were state-owned enterprises, firms with higher productivity, or firms in non-high-tech industries. Further, the authors find that the NIRDZs policy stimulates firm innovation mainly in the form of utility model patents, followed by designs and invention patents.

The results provide suggestions and implications for policymakers to improve the efficiency of state-led industrial policies and avoid “government failure” in policy implementation.

This study provides suggestions and implications for policymakers to improve the efficiency of state-led industrial policies and avoid “government failure” in the policy implementation.

This study fills the research gap by exploiting quasi-experiments to assess the effectiveness of state-led industrial policies for emerging economies. (2) The analysis sheds empirical light on how corporate innovation is motivated and financed by selective and functional industrial policies. (3) Theoretically, the results rationalize why state-led industrial relocation fuel innovation capabilities of localities from Marshall externalities and competition crowding-out effects.

The purpose of this paper is to analyse the development and evolution of industrial innovation ecosystems of Around-Tongji Knowledge Economy Circle from the three levels mentioned above, focusing on knowledge-producing populations, core populations and service-supporting populations, and to further develop this research framework by combining with the latest developments.

Based on the five-helix theory and economic census statistical data, this paper adopts geographic information system technology and examines the characteristics of the industrial innovation ecosystem and the synergistic evolution process in Around-Tongji knowledge economy circle.

The knowledge product populations lead the development of industries in Around-Tongji Knowledge Economy Circle. It contributes political capital output for the government. It innovates community cooperation and governance mode, and it improves the natural ecological environment. In the face of the changes and challenges in the development environment, the future development must be recognised from the height of the iterative development of the interaction mode between university knowledge production and economic and social development.

Based on the five-helix theory and economic census statistical data, this paper examines the characteristics of the industrial innovation ecosystem and the synergistic evolution process in Around-Tongji Knowledge Economy Circle. It further expands the research framework used to develop a synergistic evolution model, which reveals the interactive and synergistic relationship among the populations and the evolution characteristics of the entire industrial innovation ecosystem. This paper also provides useful perspectives for the study of the industrial innovation ecosystem.

The implementation of the innovation-driven development strategy is of practical significance for improving the quality and efficiency of economic growth and accelerating the transformation of economic development mode. The purpose of this paper is to study the impact of innovation-driven strategies on marine industry agglomeration and industrial transformation.

In traditional grey correlation analysis, when the positive and negative areas cancel each other out during the integration process, the calculation result of the correlation degree is often inconsistent with the qualitative analysis. For this reason, from the perspective of curve similarity, this paper constructs two response curves through the relative change area of the two curves and the relative area change ratio of similar degree, thus constructing an improved grey relational model.

The authors find that the innovation investment has a better correlation with marine industrial agglomeration. It also found that Guangdong Province has the highest degree of correlation between innovation indicators and marine industrial agglomeration. Much beyond the authors’ expectation, in the areas where marine industrial agglomeration is high, the synergistic effect is not obvious by using the location entropy method.

The improved grey correlation analysis method can effectively overcome the phenomenon that the positive and negative areas cancel each other in the integration process of the original algorithm, and it can also effectively measure the negative correlation between variables. This paper explores the impact of innovation drive on the agglomeration of marine industries, which is of great significance to the sustainable development of marine economy.

The authors observe the influence of intellectual capital (IC) on innovation performance with the mediating role of interorganizational learning (IOL) in the Pakistani automotive industry. Besides, industrial Internet of things (IoT) technology is used as moderating variables between IOL and innovation performance.

Structural equation modeling (SEM) presents scholars with extra flexibility and enhanced research conclusions. SEM is described as a statistical methodology and the best tool used for hypothesis testing. The authors used partial least squares SEM for testing hypotheses. The simple random sampling technique followed to collect data from respondents, and 492 questionnaires were used for analysis.

The outcomes reveal that IC enhances innovation performance and IOL. Moreover, IOL increases innovation performance. IOL significantly mediates between IC and innovation performance. Industrial IoT technology improves innovation performance. Finally, industrial IoT technology strengthens the positive association between IOL and innovation performance.

This study concentrates on the issue of how managers use IOL and industrial IoT technology to take higher advantage of IC that increases innovation performance.

This is the initial study that builds a theoretical framework to integrate IC, IOL, industrial IoT technology and innovation performance. Although prior researchers observe the association between IC and innovation performance, less concentration was paid to understand the role of interorganizational leadership and industrial IoT technology in leveraging organizational IC.

The purpose of this paper is to reveal the paradox between diversification and specialization from a dynamic perspective. More precisely, this paper will analyze the impact of diversification and specialization as well as their interaction on regional innovation in different development stages.

Based on the principles of new economic geography and innovation geography, data from 30 provinces from 2001 to 2017 was used to explore the relationship. Least squares regressions with fix effect were used to examine the hypotheses.

The results show that both diversification and specialization have a significant and positive impact on regional innovation. The interaction of diversification and specialization also significantly and positively impacts regional innovation. The effect of industrial agglomeration is heterogeneity under different development stages.

This paper verifies the positive role of diversification and specialization and their interaction in promoting regional innovation. The impact of industrial agglomeration on innovation is dynamic and changes with the regional development process. Emerging economies should make appropriate industrial agglomeration strategies according to their development stages.

This paper introduces diversification, specialization and their interaction into the research framework at the same time to analyze their impact on innovation performance which deepened the research of industrial agglomeration. Taking China as an example, this paper also examines the impact of industrial agglomeration on regional innovation in different development stages that expands the dynamic perspective of industrial agglomeration.

The purpose of this paper is to test the relationship between innovation performance and innovation spillover effects, innovation inputs, innovation outputs and industrial effects.

The analysis framework including variables such as innovation spillover effect, innovation input, innovation output and industrial effect was constructed. Through the investigation and analysis of the innovation activities of China’s GEM listed companies in 2014–2016, the innovation performance and the above factors were tested.

The research shows that enterprise performance has a significant positive correlation with innovation input and innovation output, but there is no significant correlation or even negative correlation with innovation environment and industry background such as government support and innovation opportunities, and the spillover effect is significant. The negative correlation is also negatively correlated with innovative human capital investment, company age and company Q.

Innovation is the real source of economic growth, and industrial innovation is the system integration of technological innovation, product innovation, market innovation, etc., which is the basic determinant of national competitiveness.

This paper aims to propose an assessment framework to evaluate companies' innovation capability in the context of industrial clusters.

The assessment framework was built based on the Graph-Theoretic Approach (GTA) to measure the influence of the factors and sub-factors of innovation capabilities. To quantify the level of interdependence between factors and sub-factors of innovation capability Delphi method was adopted. The authors developed five case studies in firms from an Information and Communications Technology and Creative Economy cluster in Northeastern Brazil to test the framework's applicability.

The results showed that identifying and evaluating the factors of innovation capability allows a larger understanding of what affects these capabilities to a greater or lesser extent and contributes to strategic decision-making.

The framework evaluates the innovation capability of each firm, not providing an index for the whole industrial cluster. Besides, the framework does not consider the innovations developed by the companies through the innovation's capabilities. As the Delphi technique was adopted to analyze the levels of influence or interdependence between factors and sub-factors of innovation capability, different experts may lead to different results.

Among the managerial implications, the authors can highlight the innovation capability index as a practical performance measure to stimulate improvement initiatives regarding innovations in industrial clusters. Besides, as the proposed framework is generic, research organizations, public institutions and regional governments can adopt it to analyze innovation capabilities in cluster-based companies.

Previous industrial cluster studies have concentrated on knowledge transfer as the main attribute influencing innovation capabilities. The literature also presents assessment frameworks focusing on qualitative analyses or innovation capabilities outcomes (patents and products). Differently, the authors proposed a quantitative assessment framework considering specific factors (and sub-factors) of innovation capabilities in industrial clusters.

This paper seeks to examine the relationships between working conditions, innovation activities and industrial relations in two local production systems located in the northern Italy, exploiting data collected through ad‐hoc surveys in 2004 and 2006.

The paper follows a recent stream of literature, which is still quite scanty, that addresses the issue of the implication for workers derived from the introduction of organizational changes. This topic is addressed and extended, taking into consideration both the role of firm level industrial relations and the role of other innovation activities that may influence working conditions.

The results seem to support the position maintained by the advocates of organizational changes. Job empowerment is spurred by the form of organizational changes usually defined as high performance workplace practices. However, such typology of changes in the organization does not seem to be linked with positive trends in safety/security and stress. At the same time the positive role of cooperative industrial relations on the working condition emerges, also as complementary elements to innovation activities.

This work confirms some relevant empirical results obtained in international literature about the linkages between organizational changes and working conditions. At the same time it provides an original perspective of analysis taking into account other influencing factors of workers' well being: good quality industrial relations at firm level and innovation activities such as technological innovation and ICT.