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The purpose of this paper is to investigate alliance partner diversity (APD) as a driving force that potentially enhances firms’ innovation generation (IG) in interfirm open alliance contexts. The authors propose that APD enhances IG but that the effects depend on both alliance network position and the double-edged external knowledge search strategy. Building on the knowledge-based view and social capital theory, the authors formally model how external knowledge search strategies can lead to productive or destructive acquisitions of external knowledge in interfirm open alliance networks. The authors theorize that when an individual firm adopts a central position in a complex interfirm open alliance network, its propensity toward beneficial IG depends on its knowledge search strategy (i.e. its breadth and depth) due to the joint influence of network position and knowledge search strategy on innovation.

Using an original large-scale survey of high-tech firms, this study shows that the relationship between partner diversity and IG is contingent on a firm’s network position and knowledge search strategy. The authors also offer an original analysis of how knowledge search strategy (i.e. its breadth and depth) in network centrality (NC) affects the efficacy of knowledge acquisition in interfirm open alliance networks. Empirically, the authors provide an original contribution to the open innovation literature by integrating social capital and knowledge-based theory to rigorously measure firm IG.

Overall, our findings suggest that the knowledge search strategy imparts a double-edged effect that may promote or interfere with external knowledge in IG in the context of the diversity of alliance partners.

The work has important limitations, such as its analysis of a single industry in the empirical models. Therefore, further studies should consider multiple industries that may provide useful insights into innovation decisions.

External knowledge search is valuable, particularly in the high-tech industry, as external knowledge acquisition generates innovation output. This study serves to raise managers’ awareness of various approaches to external knowledge searches and highlights the importance of network position in knowledge acquisition from interfirm open alliance collaborations.

This paper is the first to investigate the double-edged effect of knowledge search on interfirm open alliance networks. It also contributes to the theoretical and practical literature on interfirm open alliance networks by reflecting on external knowledge search and underlying network centrality and APD factors.

Business management, entrepreneurship, strategic management and business environment.

Undergraduate and Masters level business and management programmes.

This case features a small labour intensive Chinese company, Bags of Luck (BoL), located in the south-eastern Fujian province. BoL makes ladies fashion handbags, unisex fashion backpacks and trendy lightweight cases for laptop and netbook computers for export to the US market. BoL have done very well over the years as a small private enterprise focusing on low-tech manufacturing and have managed to stay afloat through the most difficult period of the recent world recession. Currently troubled by fast changing market trends, rising material and employment costs, continuing appreciation of the Chinese currency, severe labour shortage, declining production volume and profitability, dated machinery, passive and reactive nature of business model, ineffective management structure and a complete lack of strategic vision, BoL is in deep crisis with its fate now hanging on the balance.

The case provides encourages students to: research into a range of current business management issues; analyse the impact of environmental changes on the survival and growth of a business organisation; develop their strategic thinking informed by real life and real-time research and assess the impact of exchange rate changes on the Chinese economy and the sustainability of Chinese model of economic growth.

Teaching note.

Incentive policies have been emphasized by many governments as one of the major policy tools to promote economic development in their societies. For this paper I have examined the application of incentive policies in China to improve economic performance during China’s reform years. In the paper are theoretical reviews about various types of incentive policies and different arguments about their effects. The development of Chinese incentive policies is introduced and analysis of their achievements in improving economic growth and attracting foreign investment is presented. Challenging issues of incentive policies have been related to concerns about effectiveness and equity, accountability and transparency, as well as economic upgrade and balance. Implications of the Chinese development experience are provided for future study of incentive policies.

This purpose of this study is to perfrom the analysis of COVID-19 with the help of blood samples. The blood samples used in the study consist of more than 100 features. So to process high dimensional data, feature reduction has been performed by using the genetic algorithm.

In this study, the authors will implement the genetic algorithm for the prediction of COVID-19 from the blood test sample. The sample contains records of around 5,644 patients with 111 attributes. The genetic algorithm such as relief with ant colony optimization algorithm will be used for dimensionality reduction approach.

The implementation of this study is done through python programming language and the performance evaluation of the model is done through various parameters such as accuracy, sensitivity, specificity and area under curve (AUC).

The implemented model has achieved an accuracy of 98.7%, sensitivity of 96.76%, specificity of 98.80% and AUC of 92%. The results have shown that the implemented algorithm has performed better than other states of the art algorithms.