Search results

The convergence of industries exposes the involved firms to various challenges. In such a setting, a firm's response time becomes key to its future success. Hence, different approaches to anticipating convergence have been developed in the recent past. So far, especially IPC co-classification patent analyses have been successfully applied in different industry settings to anticipate convergence on a broader industry/technology level. Here, the aim is to develop a concept to anticipate convergence even in small samples, simultaneously providing more detailed information on its origin and direction.

The authors assigned 326 US-patents on phytosterols to four different technological fields and measured the semantic similarity of the patents from the different technological fields. Finally, they compared these results to those of an IPC co-classification analysis of the same patent sample.

An increasing semantic similarity of food and pharmaceutical patents and personal care and pharmaceutical patents over time could be regarded as an indicator of convergence. The IPC co-classification analyses proved to be unsuitable for finding evidence for convergence here.

Semantic analyses provide the opportunity to analyze convergence processes in greater detail, even if only limited data are available. However, IPC co-classification analyses are still relevant in analyzing large amounts of data. The appropriateness of the semantic similarity approach requires verification, e.g. by applying it to other convergence settings.

In search for new ideas outside the firm's boundaries most companies choose to implement cooperation in the form of discrete projects, increasing the importance of project management. As research in this area so far mainly dealt with formalized instruments of process control, the purpose of this paper is to focus on personal aspects, particularly on the role of project leadership.

A sample of 84 biotechnological projects were analyzed. A standardized questionnaire was developed and sent out to research and development managers from the chemical, pharmaceutical and biotechnological industry. The level of analysis for the survey were single cooperative projects and basically regression statistics were employed.

It was found that the requirement for a stronger project leader is highly dependent on the degree of trust among team members and the administrative activity. In contrast, other factors, like the risk associated with a cooperative project, or the extent of upper management support are not significantly related to a stronger leader.

As only biotechnological projects were analyzed, other studies investigating the required project leadership style in other industries would be necessary to be able to generalize. Furthermore, there are several factors with a potential influence that could not be examined in this study.

The findings would suggest to companies involved in cooperative projects that more emphasis should be put on the human factors of project management and not only on efficient instruments.

This paper focuses on the required strength of a project leader and should thus be of interest to managers trying to set up effective cooperative projects.

The purpose of this paper is twofold: first, to present a bibliometric analysis and systematic literature review of industry convergence and value innovation to understand the current research status; second, to provide a coherent theoretical research framework for future research.

This study adopts a two-step analysis approach by combining bibliometric analysis and systematic literature review to explore the research topic of industry convergence and value innovation. Besides, two bibliometric tools, HistCite and VOSviewer, were applied to this study.

This study found that Stefanie Bröring and Fredrik Hacklin are the top two most influential authors among all authors in the sample publications. Technological Forecasting and Social Change is one of the top-ranking journal that often publishes this topic of articles. Germany and the University of Munster are the most influential country and institutions, respectively. Besides, five core research themes were identified based on keywords co-occurrence map, theoretical lenses, factors promoting industry convergence, indicators of industry convergence, the impact of industry convergence and emerging research directions. Based on the above analysis, this paper constructed a theoretical research framework of industry convergence and value innovation.

This paper only draw data from one database – Web of Science – which cannot provide broad coverage of the research topic. Besides, the bibliometric method of this paper is based on high local citation score and high-frequency words, articles in the skirting subjects’ area may not be analyzed.

With the rapid development of technology, such as nanotechnology, radio - frequency identification (RFID), etc., the iterative upgrading of products also comes. As a result, the boundary between industries is gradually blurred, and the phenomenon of industry convergence appears. Therefore, managerial decision-makers are facing challenges of how to respond to the convergence phenomena. From the firm level, firms are facing the problem of value innovation of the existing product, new product development and core competence improvement. Industries are facing the problem of transformation and upgrading. This paper provides certain theoretical insights for both firms and industries to guide the practice accordingly.

This paper is the first to use a bibliometric method to examine the topic of industry convergence and value innovation. In addition, this paper presents an in-depth analysis of this topic and provides a comprehensive theoretical research framework for future study.

The purpose of this paper is to investigate knowledge sharing of Chinese and German scientists collaborating in a cross‐cultural nanotechnology R&D project. Particularly, the authors analyze cultural differences that might indirectly influence the scientists' intention to share knowledge.

Quantitative data were gathered from professors and PhDs working in academic Chinese‐German nanotechnology collaboration regarding influencing factors of their intention to share knowledge like subjective norms, anticipated extrinsic rewards and image. Moderated regression analysis was used to identify how nationality influences the relationships between independent variables and the intention to share knowledge.

The findings show that the analyzed variables generally constitute important influencing factors of the intention to share knowledge. However, moderation analysis suggests that the proposed differences between the Eastern and Western cultures do not significantly affect influencing factors of the intention to share knowledge.

The focus of this study is on an academic environment, limiting the generalizability of the results. It promises to be a worthwhile endeavor to investigate possible influencing factors and effects of organizational culture in cross‐cultural collaboration projects more thoroughly in the future, further deepening our understanding of knowledge sharing in collaborative R&D projects.

Cultural differences between Chinese and German researchers might have diminished over the past decades. Both in China and Germany, academic scientists can be expected to largely share the same values, beliefs, assumptions and expectations with regard to their work.

The study at hand is the first analysis of an academic Chinese‐German nanotechnology collaboration.

There are several approaches trying to explain the diffusion of renewable energy technologies (RET). The most commonly used instruments are learning and experience curves, followed by further economic, policy- and barrier-related analyses. In order to gain a more comprehensive understanding, additional influence factors on RET diffusion have to be studied. This paper aims to contribute to research on RET diffusion by adding the raw material price perspective.

The authors develop a regression model to test the influence of raw material prices on RET diffusion, using investments in RET capacities as indicators of diffusion, and crude oil and natural gas prices as well as public R&D subsidies as main independent variables. The model is then applied to emerging RET (wind and solar power) for electricity generation in 18 OECD-countries.

In the case of wind power, the model shows an adequate fit and a highly significant impact of oil as well as gas prices on investments in RET capacity. In the case of solar power, the impact of raw material prices proves to be highly significant as well, but the weak model fit demands further adjustments of the parameters.

Theoretical implications include the expansion of existing RET diffusion models to a raw material price component. From a practical point of view, the authors provide a starting basis for the systematic integration of raw material price developments into companies' planning and forecasting processes.