Surface enhanced Raman spectroscopy based biosensor with a microneedle array for minimally invasive in vivo glucose measurements

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The many transitory changes in China have raised the intensity level of competition among construction firms. Despite having a high growth economy, some construction firms continue to suffer from low profitability. Meanwhile, practical cases and empirical findings related to Chinese construction firms remain lacking. This research develops a conceptual model for improving the competitiveness of large construction firms in China. The model integrates two main streams of strategic management theories—the industrial organisation theories, and the resource-based and competence-based views. Critical variables that form the model are initially identified from an environmental analysis and the case studies of 12 large Chinese construction companies. The relationships between competitive strategies, important resources and competencies, and competitive advantage are then verified using survey results. The statistical findings suggest that two strategies—differentiation and market/product diversification, and three important resources and competencies—technological innovative capabilities, financial capabilities and guanxi (relationship), directly affect firm performance as measured by revenue and profit growth.China, competence, competitiveness, construction companies, strategic analysis,

Chapter 2 Literature Review …………………………………………10 2.1 Overview of the Schools of Thoughts in Strategy ………………………10 2.2 Strategy Theories in the Construction Context …………………………18 2.3 Literature related to the Chinese Construction Industry ……………….22 2.4 Theoretical Foundations for Building a Conceptual Model Tailored for the Chinese Construction Industry ………….……………………….25

Automating the development of construction schedules has been an interesting topic for researchers around the world for almost three decades. Researchers have approached solving scheduling problems with different tools and techniques. Whenever a new artificial intelligence or optimization tool has been introduced, researchers in the construction field have tried to use it to find the answer to one of their key problems-the "better" construction schedule. Each researcher defines this "better" slightly different. This article reviews the research on automation in construction scheduling from 1985 to 2014. It also covers the topic using different approaches, including case-based reasoning, knowledge-based approaches, model-based approaches, genetic algorithms, expert systems, neural networks, and other methods. The synthesis of the results highlights the share of the aforementioned methods in tackling the scheduling challenge, with genetic algorithms shown to be the most dominant approach. Although the synthesis reveals the high applicability of genetic algorithms to the different aspects of managing a project, including schedule, cost, and quality, it exposed a more limited project management application for the other methods.