The diffusion and embeddedness of cyber technology and big data technology is recognized as an opportunity and infrastructure for firms to innovate and transform. But which digital strategies existed firms in manufacturing and other traditional industries can make is still a question under research. The paper pursues to answer this question from the perspectives of data ownership and key value propositions. From the dimension of data ownership and key value propositions, this research proposes a research framework to guide the analyses of digital transformation strategy. The four firms are used to identify five types of digital strategies, namely new product strategy, new value-added service strategy, customized strategy, product embedded in the platform, and platform service / product strategy based on the framework of digital transformation strategy decision. This research suggests that a firm can select the suitable strategy considering his key value proposition and ownership of data which the firm could use. The research contributes to the research and practices on the digitalization strategy and the digital transformation of firms, especially those in emerging economies.

In the past 20 years, there have been increasingly more studies on sustainable technology innovation (STI), possessing a significance for sustainable development. This paper aims to provide a research landscape, since the systematic understanding of STI is still inadequate. Through bibliometric analysis, it explores the literature distribution characteristics and the literature citation network. Based on the relevant literature data in the Web of Science (WOS), the study visually analyzes the development trend, topic distribution, burst literature, and co-citation network of the research literature, and extracts the evolution path of literature citation by using the main path analysis method. Through the analysis of co-citation and main path, 13 clusters in the co-citation network are found, which are further extracted as the main path network containing 82 nodes. Furthermore, this paper summarized the bibliometric landscape and discussed the frontier STI research topics. The comprehensive framework contributes to the understanding of STI themes and identifying future research agenda.

Patent protection is a critical aspect of sustainable technology innovation, which is currently facing the challenge of patent risk. This study aimed to help enterprises prevent and avoid patent risk in a global view of technology innovation, and to propose a systematic evaluation model for patent risk. By combining the entropy method with the analytic hierarchy process (AHP), this study constructed an analytic hierarchy model of patent risk. Some indexes in the model were selected based on the summary of prior literature, and other indexes were selected according to experts’ communication, which helped us to generalize the patent risk as comprehensively as possible. The AHP evaluation results determined the weight and relative materiality for each risk factor, which were contained in a criteria layer and a sub-criteria layer. The entropy method integrated the evaluation weights of different experts’ opinions. By dividing the risk factors into three categories, namely “high”, “medium”, or “low”, according to the priority degree, the risk priority ranking was obtained. Suggestions are discussed regarding support for enterprises in dealing with patent risk that may occur during international trade or other commercial activities.

Next generation of Information Technologies (IT), such as edging/cloud computing, cybersecurity, and artificial intelligence, has been in a rapid development and therefore concerned wide areas. Management of Intellectual Property Rights (IPR) plays an increasingly important role on knowledge design and engineering, innovation and patent management, intangible assets audition, R&D, and so forth; however, it also meets the challenges from proper platform and service provision, especially when large-scale mobile and distributed requirements become popular. In this paper, Intellectual Property Platforms and corresponding commercial tools have been collected, investigated, and reviewed, involving official platforms in China, USA, EU, and another 6 countries, as well as 12 intellectual property analysis tools commonly used online. Detailed comparison and discussion have been undertaken in order to find potential challenges and opportunities for improved service provision, for example, searching privacy preservation, cloud/edge-based service offloading and efficient distribution, and ontology-based intelligent IPR engineering, which can possibly be commercialised in the near future.