No abstract

This study tests the explanatory power of three theoretical frameworks for the performance of cross-border affiliates, by examining the experience of 615 Hong Kong firms managing operations in mainland China. The frameworks tested are: the natural selection approach, focused on the influence of the environment; the strategic choice approach, focused on managerial action; and the contingency approach, which emphasises the ‘fit’ between environmental contingencies and internal organisation. The results show that natural selection and strategic choice have a role to play, even when controlling for each other. They also support a simple approach to contingency, but not a more complex version involving interactions. Although the business and institutional environments do have a significant influence on the performance of cross-border affiliates in a transition economy, performance can be improved through strategic managerial action. In particular, leveraging local resources by developing trust between parent and affiliate, and maintaining close control and integration with the parent, are associated with enhanced performance. Journal of International Business Studies (2003) 34, 242–254. doi:10.1057/palgrave.jibs.8400033

Globalisation has created both drivers and pressure for Chinese organisations to enhance their business performance as well as environmental performance. Green and lean practice is emerging as a critical approach for Chinese organisations to achieve sustainable development and improve organisational performance. By conducting empirical studies from 172 respondents on green and lean practice in different Chinese organisations, this research shows how green and lean practice affects organisational performance and how this association is affected by guanxi. The findings explain that guanxi between organisational partners improves the positive effect of green and lean practice on organisational performance. The results of this paper offer helpful insights into how managers should enhance their guanxi initiatives, in order to improve environmental and business performance over their supply chains. The paper also suggests the limitations of this research, as well as directions for future research.

Abstract:The current world of post industrial value generation sees companies increasingly analyzing their internal operations against their external organizations to identify supply/demand fluctuations along the supply chain. Within these integrated relationships between internal and external parties in the supply chain, knowledge and information have become very important production resources. The existence and success of an increasing number of organizations strongly depend on their capabilities to utilize knowledge and information for profit generation. By managing more efficient information sharing, the volume of company confidential information passing through the supply chain increases, and this brings about more incidences of knowledge leakage and information leakage. A survey by PricewaterhouseCoopers in 2014 shows information security spending over the next 12 months would increase 60.27 percent in Asia and 48.98 percent in all regions. This emphasizes the importance of information privacy and therefore the necessity to study the information and knowledge leakage in integrated supply chain. The objectives of this study are to investigate the factors triggering information and knowledge leakage and create a mitigation framework to soften the impact of leakages on performance. The above objectives will be met by formulating and examining several hypotheses of a conceptualized information leakage (IL) and knowledge leakage (KL) framework. A case study derived from a structured interview is adopted as a methodology in this research. As a result, this paper contributes a novel theoretical model that characterizes information and knowledge leakage in an integrated supply chain. Therefore, it also adds new knowledge of managing information and knowledge leakage to supply chain management.

Purpose-This paper suggests how firms could use big data to facilitate the product innovation processes, by shortening the time to market, improving customers' product adoption and reducing costs. Design/methodology/approach-Our research is based on a two-step approach. First, this research summarised and identified four potential key success factors for organisations to integrate big data in accelerating their product innovation processes. The proposed factors were further examined and developed by conducting interviews with different organisation experts and academic researchers. Then, a framework was developed based on the interview outputs. The framework sets out the key success factors involved in leveraging big data to reduce lead times and costs in product innovation processes. Findings-The three determined key success factors are: a) Accelerated innovation process; b) Customer connection; and c) Ecosystem of innovation. The developed framework based on big data we believe represents a paradigm shift. It can help firms to make new product development dramatically faster and less costly. Research limitations/implications-The proposed accelerated innovation processes demands a shift in traditional organisational culture and practices. It is, though, meaningful only for products and services with short product life cycles. Moreover, the framework has not yet been widely tested. Practical implications-This paper points to the vital role of big data in helping firms to accelerate product innovation processes. First of all, it allows organisations to launch new products to market as quickly as possible. Secondly, it helps organisations to determine the weaknesses of the product earlier in the development cycle. Thirdly, it allows functionalities to be added to a product that customers are willing to pay a premium for, while eliminating features they don't want. Last but not least, it identifies and then prioritises customer needs for specific markets. Originality/value-The research shows that firms could harvest external knowledge and import ideas across organisational boundaries. An accelerated innovation processes based on Page 1 of 28 Business Process Management Journal 2 big data is characterised by a multidimensional process involving intelligence efforts, relentless data collection and flexible working relationships with team members.