Chunhsien Wang, Tachia Chin, Yuan Yin Chiew and Cinzia Capalbo
Drawing upon insights from knowledge-based theory and the learning perspective, this study aims to explore safeguarding strategies in open innovation. Geographic diversity and…
Abstract
Purpose
Drawing upon insights from knowledge-based theory and the learning perspective, this study aims to explore safeguarding strategies in open innovation. Geographic diversity and collaborative breadth can effectively protect proprietary innovations that limit knowledge leakage concerns.
Design/methodology/approach
Using a cross-industry sample from the Taiwanese Technological Innovation Survey III, which covered 1,519 firms, the authors investigate the conditions under which partnership portfolios affect radical innovation.
Findings
The findings suggest that the partnership portfolio has an inverted U-shaped influence on radical innovation and that this relationship is moderated by geographic diversity and collaborative breadth. This work identifies a balance in the tension between diverse partnership portfolios and knowledge leakage with regard to open innovation activities.
Practical implications
This study provides senior managers with an indication of the relationships between partnership portfolios and innovative knowledge protection, identifying the geographic diversity and collaborative breadth that serve as safeguards to prevent leakages of a firm’s innovative knowledge.
Originality/value
This study makes an original contribution to the empirical exploration of innovation knowledge protection and provides new insights into the field of open innovation. The authors, thus, balance the tension between partnership portfolios and knowledge leakage.
Details
Keywords
Noel Scott, Brent Moyle, Ana Cláudia Campos, Liubov Skavronskaya and Biqiang Liu
Jingkuang Liu, Yuqing Li, Ying Li, Chen Zibo, Xiaotong Lian and Yingyi Zhang
The purpose of this study is to discuss the principles and factors that influence the site selection of emergency medical facilities for public health emergencies. This paper…
Abstract
Purpose
The purpose of this study is to discuss the principles and factors that influence the site selection of emergency medical facilities for public health emergencies. This paper discusses the selection of the best facilities from the available facilities, proposes the capacity of new facilities, presents a logistic regression model and establishes a site selection model for emergency medical facilities for public health emergencies in megacities.
Design/methodology/approach
Using Guangzhou City as the research object, seven alternative facility points and the points' capacities were preset. Nine demand points were determined, and two facility locations were selected using genetic algorithms (GAs) in MATLAB for programing simulation and operational analysis.
Findings
Comparing the results of the improved GA, the results show that the improved model has fewer evolutionary generations and a faster operation speed, and that the model outperforms the traditional P-center model. The GA provides a theoretical foundation for determining the construction location of emergency medical facilities in megacities in the event of a public health emergency.
Research limitations/implications
First, in this case study, there is no scientific assessment of the establishment of the capacity of the facility point, but that is a subjective method based on the assumption of the capacity of the surrounding existing hospitals. Second, because this is a theoretical analysis, the model developed in this study does not consider the actual driving speed and driving distance, but the speed of the unified average driving distance and the driving distance to take the average of multiple distances.
Practical implications
The results show that the method increases the selection space of decision-makers, provides them with stable technical support, helps them quickly determine the location of emergency medical facilities to respond to disaster relief work and provides better action plans for decision makers.
Social implications
The results show that the algorithm performs well, which verifies the applicability of this model. When the solution results of the improved GA are compared, the results show that the improved model has fewer evolutionary generations, faster operation speed and better model than the intermediate model GA. This model can more successfully find the optimal location decision scheme, making that more suitable for the location problem of megacities in the case of public health emergencies.
Originality/value
The research findings provide a theoretical and decision-making basis for the location of government emergency medical facilities, as well as guidance for enterprises constructing emergency medical facilities.
Details
Keywords
Guangxing Ji, Zhizhu Lai, Dan Yan, Leying Wu and Zheng Wang
The purpose of this study is to assess the spatiotemporal patterns of future meteorological drought in the Yellow River Basin under different representative concentration pathway…
Abstract
Purpose
The purpose of this study is to assess the spatiotemporal patterns of future meteorological drought in the Yellow River Basin under different representative concentration pathway (RCP) scenarios.
Design/methodology/approach
Delta method is used to process the future climate data of the global climate models, then analyzed the spatiotemporal variation trend of drought in the Yellow River Basin based on standardized precipitation evaporation index (SPEI) under four RCP scenarios.
Findings
This research was funded by the National Natural Science Foundation of China (41901239), Soft Science Research Project of Henan Province (212400410077, 192400410085), the National Key Research and Development Program of China (2016YFA0602703), China Postdoctoral Science Foundation (2018M640670) and the special fund of top talents in Henan Agricultural University (30501031).
Originality/value
This study can provide support for future meteorological drought management and prevention in the Yellow River Basin and provide a theoretical basis for water resources management.