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Because of the complexity of technological innovation and the dynamics of the technological environment, it is impossible for a single firm to have all knowledge needed for technological innovation, making it essential for firms to conduct cross-border knowledge search and integration. However, it is very difficult for firms to acquire and assimilate cross-border knowledge. The purpose of this paper is to explore how an open innovation platform (OIP) helps firms to effectively search and integrate cross-border knowledge, and to understand the key roles that OIP plays during the cross-border knowledge search and integration processes.

This paper takes the case analysis method, which provides a comprehensively understanding on the complex process of cross-border knowledge search and integration as well as the internal mechanism. Drawing on the research paradigm of Eisenhardt (1989), Bakker and Akkerman (2014), this paper analyzes and verifies the mechanism of OIP cross-border knowledge search and integration based on extensive interviews.

First, this paper analyzes the process of cross-border knowledge search and integration through Haier open partnership ecosystem (HOPE), which is theoretically divided into three stages, including motivation formation, cross-border knowledge search and integration. These three stages have been further decomposed into the following seven steps: demands discovery, problems definition, problems decomposition, resource search, resource evaluation, technology redevelopment and test. In addition, this study investigates the manifestation of interrelationships among these stages and steps, depicting the pathways through which HOPE facilitates the firm’s cross-border knowledge search and integration. The conclusions indicate that OIP timely discovers the consumer demands during the motivation formation stage, effectively decomposes problems and find related technology resources during the search stage and improves the efficacy of integration stage.

This study reveals the mechanism of OIP cross-border knowledge search and integration and draws some valuable conclusions, which contribute to the literature on cross-border knowledge search, enrich the research on problem-solving and also propose a new perspective to study the roles of OIP on innovation. However, there are still some limitations. First, this study is built on a single platform (HOPE), further studies may focus on more platforms to ensure the conclusions of this paper. Second, this study conducts data analysis using a simple encoding analysis, so it is possible that some critical information is emitted while collating and analyzing data. Meanwhile, for the research methods, qualitative and quantitative methods can be combined to analyze related issues, then the correlation and corresponding mechanism can be incorporated into the same framework to further verify the conclusions and generalize the results.

This paper theoretically analyzes how and why HOPE helps firms search and integrate cross-border knowledge. It provides not only a reference for OIP but also a proven and effective way for companies’ acquiring and integrating cross-border knowledge. Then it will further improve firms’ innovative abilities, especially disruptive innovation abilities.

Technological innovation, especially disruptive innovation is not only a driving force of firms’ sustainable development but also a vital driver of national development. This paper clarified that OIP can help firms conduct successful disruptive innovation through cross-border knowledge search and integration, which will further increase national innovative competence and improve social welfare.

This paper extends the literature on the process of cross-border knowledge search and integration, as well as the roles of OIP. From a managerial standpoint, the conclusions have practical implications for firms to successfully acquire and integrate cross-border knowledge.

The purpose of this paper is to examine whether Fama–French common risk-factor portfolio investors herd on a daily basis for five developed markets, namely, Europe, Japan, Asia Pacific ex Japan, North America and Globe.

To examine the herd behavior of common risk-factor portfolio investors, this paper utilizes the cross-sectional absolute deviations (CSAD) methodology, covering a daily data sampling period of July 1990 to January 2019 from Kenneth R. French-Data Library. CSAD driven by fundamental and non-fundamental information is assessed using Fama–French five-factor model.

The results do not provide evidence for herding under normal market conditions, either when reacting to fundamental information or non-fundamental information, for any region under consideration. However, Fama–French common risk-factor portfolio investors mimic the underlying risk factors in returns related to size and book-to-market value, size and operating profitability, size and investment and size and momentum of the equity stocks in European and Japanese markets during crisis period. Also, no considerable evidence is found for herding (on fundamental information) under crisis and up-market conditions except for Japan. Ancillary findings are discussed under conclusion.

Further research on new risk factors explaining stock return variation may help improve the model performance. The performance can be improved by adding new risk factors that are free from behavioral bias but significant in explaining common stock return variation. Also, it is necessary to revisit the existing common risk factors in order to understand behavioral aspects that may affect cost of capital calculations (e.g. pricing errors) and valuation of investment portfolios.

This is the first paper that examines the herd behavior (fundamental and non-fundamental) of Fama–French common risk-factor investors using five-factor model.