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This paper examines the different features of China's economic development in different stages of economic globalization. The study finds that the investment- and export-based growth model drove China's high-speed economic growth between 2000 and 2007, which came into existence around 2000 when China plugged into the global production network.

This paper also finds that China slowed down to the New Normal because of the disruption to the socio-economic underpinnings of this growth model. As China adapts to and steers the New Normal, supply-side structural reforms can channel excess capacity to the construction of underground pipe networks in rural areas of central China and fix capital while advance rural revitalization.

At the same time, enterprises must strive to build a key component development platform for key component innovation and the standard-setting power in global manufacturing.

The establishment of a domestic production network integrating the integrated innovation-driven core enterprises and modular producers at different levels can satisfy the dynamic demand structure of China in which standardized demands and personalized demands coexist.

Micro and small enterprises (MSEs) play a crucial role in the development of any country by generating innovative ideas. However, they face inherent restrictions that hinder their innovation capabilities. It is essential to support innovation policies to overcome these barriers and foster innovation. This study aims to explore how innovation policies can reduce barriers to innovation in MSEs using the lens of innovation capabilities.

Through a multiple case study, the authors examined eight MSEs in São Paulo (Brazil) and five in Florence (Italy) to conduct this study. These countries share a similar level of importance when it comes to MSEs.

Current innovation policies could be more effective for MSEs if certain barriers they encounter are faced and resolved, such as limited financial resources and a scarcity of qualified workers. These barriers directly affect two key elements of their innovation capability: financial resources and human resources. Therefore, it is essential to develop innovation policies that target these elements directly to enable MSEs to overcome these obstacles and thrive.

This study aims to enhance the knowledge of how innovation policies can help alleviate obstacles to innovation and how they can influence the various components that comprise the innovation capability of MSEs. This research can be valuable for policymakers as it provides insight into which innovation policies impact each aspect of innovation capability, enabling them to choose the most suitable policy based on the specific needs and local circumstances of the MSEs.

This paper aims to identify the factors that are constraining technological innovation to support the development of coalbed methane in China.

The analysis applies ideas relating to national and sector systems of innovation to explain why China’s strategies to support research and technological innovation have failed to stimulate the desired progress in coalbed methane production. It also provides a counter-example of the USA that implemented a number of measures in the 1970s that proved very effective.

The deficiencies of China’s research and development strategies in support of coalbed methane development reflect the national and sectoral systems of innovation. They are exacerbated by the structure of the national oil and gas industry. Key constraints include the excessively top-down management of the national R&D agenda, insufficient support for basic research, limited collaboration networks between companies, research institutes and universities and weak mechanisms for diffusion of knowledge. The success of the USA was based on entirely different systems for innovation and in quite a different industrial setting.

The originality of this analysis lies in placing the challenges facing research and innovation for China’s coalbed methane development in the context of the national and sectoral systems for innovation and comparing with the approach and success of the USA.

Adopting additive manufacturing (AM) on a large-scale requires an adoption in company value chains. This may happen through product innovation and require interorganizational cooperation, but the value-adding potential of cooperation and application recognition is still poorly understood. This study aims to investigate the progress of AM adoption in innovation projects featuring AM application recognition and interorganizational cooperation in the value chain.

A multiple-case study was implemented in successful metallic AM adoption examples to increase the understanding of AM adoption in value chains. Primary data were collected through interviews and documents in three AM projects, and the data were analyzed qualitatively.

All three AM projects showed evidence of successful AM value chain adoption. Identifying the right application and the added value of AM within it were crucial starting points for finding new value chains. Interorganizational collaboration facilitated both value-based designs and experimentation with new supply chains. Thereby, the focal manufacturing company did not need to invest in AM machines. The key activities of the new value chain actors are mapped in the process of AM adoption.

The cases are set in a business-to-business context, which narrows the transferability of the results. As a theoretical contribution, this paper introduces the concept of AM value chain adoption. The value-adding potential of AM is identified, and the required value-adding activities in collaborative innovation are reported. As a practical implication, the study reveals how companies can learn of AM and adopt AM value chains without investing in AM machines. They can instead leverage relationships with other companies that have the AM knowledge and infrastructure.

This paper introduces AM value chain adoption as a novel, highly interactive phase in the industry-wide adoption of metallic AM. AM value chain adoption is characterized in multi-company collaboration settings, which complements the single-company view dominant in previous research. Theory elaboration is offered through merging technology adoption with external integration from the information processing view, emphasizing the necessity of interorganizational cooperation in AM value chain adoption. Companies can benefit each other during AM adoption, starting with identifying the value-creating opportunities and applications for AM.

This paper provides remarkable insight into the structural components of a firm's core competence and its development via research and development (R&D) activities for innovation and exporting activities.

The authors have used a positivist design and a deductive methodology. The authors have examined the extant literature developing a theoretical framework to empirically investigate the relationships between a firm's core competence, organisational learning (OL), tacitness, dynamic capability and R&D activities. To carry out this investigation, the authors have collected stratified sample data from 330 firms operating in North East England, a peripheral region of England.

The authors have found that there are indeed significant statistical relationships between these structural components, R&D activities and a firm's core competence, and this nexus is pertinent to innovation and exporting. Furthermore, it is found that North East England is significantly constrained by the lack of finance, technological capability, experts and brain drain. Based on these findings, the authors propose a cooperative R&D framework to narrow down these constraints to assist firms in developing core competencies for innovation and exporting in peripheral regions.

There is an urgent need to investigate the incidence of knowledge-driven activities, R&D, the extent of innovation and exporting activities of firms operating in North East England, a peripheral region of the United Kingdom (UK).

This study provides an original and systematic investigation of the firm's core competence and its formation via key structural components for innovation and exporting within an empirical framework.

Digitalization accelerates the need of tourism and hospitality ecosystems to reframe business models in line with a data-driven orientation that can foster value creation and innovation. Since the question of data-driven business models (DDBMs) in hospitality remains underexplored, this paper aims at (1) revealing the key dimensions of the data-driven redefinition of business models in smart hospitality ecosystems and (2) conceptualizing the key drivers underlying the emergence of innovation in these ecosystems.

The empirical research is based on semi-structured interviews collected from a sample of hospitality managers, employed in three different accommodation services, i.e. hotels, bed and breakfast (B&Bs) and guesthouses, to explore data-driven strategies and practices employed on site.

The findings allow to devise a conceptual framework that classifies the enabling dimensions of DDBMs in smart hospitality ecosystems. Here, the centrality of strategy conducive to the development of data-driven innovation is stressed.

The study thus developed a conceptual framework that will serve as a tool to examine the impact of digitalization in other service industries. This study will also be useful for small and medium-sized enterprises (SMEs) managers, who seek to understand the possibilities data-driven management strategies offer in view of stimulating innovation in the managers' companies.

The paper reinterprets value creation practices in business models through the lens of data-driven approaches. In this way, this paper offers a new (conceptual and empirical) perspective to investigate how the hospitality sector at large can use the massive amounts of data available to foster innovation in the sector.

The purpose of this paper is to explore the emergence of innovation in smart service systems to conceptualize how actor’s relationships through technology-enabled interactions can give birth to novel technologies, processes, strategies and value. The objectives of the study are: to detect the different enablers that activate innovation in smart service systems; and to explore how these can lead dynamically to the emergence of different innovation patterns.

The empirical research adopts an approach based on constructivist grounded theory, performed through observation and semi-structured interviews to investigate the development of innovation in the Italian CTNA (Italian acronym of National Cluster for Aerospace Technology).

The identification and re-elaboration of the novelties that emerged from the analysis of the Cluster allow the elaboration of a diagram that classifies five different shades of innovation, introduced through some related theoretical propositions: technological; process; business model and data-driven; social and eco-sustainable; and practice-based.

The paper embraces a synthesis view that detects the enabling structural and systems dimensions for innovation (the “what”) and the way in which these can be combined to create new technologies, resources, values and social rules (the “how” dimension). The classification of five different kinds of innovation can contribute to enrich extant research on value co-creation and innovation and can shed light on how given technologies and relational strategies can produce varied innovation outcomes according to the diverse stakeholders engaged.