Suchergebnisse

In this text some fundamental issues concerning the strategic impact of vertical structures of firms are discussed in a successive oligopoly model. Vertical integration strategy has been identified as one of the key strategies which determine the success or failure of enterprises. Many studies on vertical integration are based on business experiences and interviews with managers. However, the extensive application of game theory in business economics allows this study on vertical integration to be based on sound theoretic ground. Moreover, the significance of public enterprises in some Western

Factorial design plays a fundamental role in efficient and economic experimentation with multiple input variables and is extremely popular in various fields of application, including engineering, agriculture, medicine and life sciences. Factorial experiments are often used in case studies in quality management and Design for Six Sigma (DFSS). The last twenty years have witnessed a significant growth of interest in optimal factorial designs, under possible model uncertainty, via the minimum aberration and related criteria. The present book gives, for the first time in book form, a comprehensive and up-to-date account of this modern theory. Many major classes of designs are covered in the book. While maintaining a high level of mathematical rigor, it also provides extensive design tables for research and practical purposes. In order to equip the readers with the necessary background, some foundational concepts and results are developed in Chapter 2. Apart from being useful to researchers and practitioners, the book can form the core of a graduate level course in experimental design. It can also be used for courses in combinatorial designs or combinatorial mathematics.

Current environmental issues and government requirements, together with pressure from the market and other stakeholders, emphasize the importance of partner selection in constructing and operating sustainable supply chains. Strategic items, which carry both high supply risk and high importance of purchase, are particularly important in sustainable supply chains. This paper presents an integrated decision-making model, which aims to solve the partner selection and order allocation problem for strategic items in sustainable supply chains. In the proposed model, weightings of different decision-makers are first calculated using Trapezoidal Fuzzy Numbers. Then, Taguchi loss function is used to evaluate the relative importance of potential partners, with the weighting results of criteria by Best-Worst Method. Finally, considering the weights of different potential partners, Particle Swarm Optimization (PSO) is used to solve the multi-objective programming problem, and Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) is applied to identify the most appropriate Pareto solution for sustainable partner selection and order allocation of strategic items. An illustrative application of the proposed model is undertaken in a leading Chinese LED lighting manufacturer to show its effectiveness and applicability.

Due to an increased awareness of ecological protection and resultant stringent legislations, business organizations are highly motivated to improve the sustainable performance of their supply chain in order to achieve sustainable development goals. The chemical industry is a high-risk, high-pollution, and high-efficiency industry, that would benefit from a systematic and sustainability focused evaluation system for supplier selection. Yet, to date, few studies have conducted the necessary in-depth analysis of the characteristics of this industry from the economic, social, and environmental perspectives. Despite the many methods and models that have been proposed to resolve the sustainable supplier selection (SSS) problem, no research has yet considered the different characteristics of each triple bottom line dimension. Accordingly, this paper addresses this problem by proposing a hybrid multi-method and multi-criteria decision-making framework for SSS in the chemical industry. Based on specific characteristics of the chemical industry, this study applies Fuzzy Grey Relational Analysis (FGRA), Failure Mode and Effects Analysis (FMEA), and cloud computing-entropy weight method (EWM) to analyze the economic, social, and environmental dimensions, respectively. Finally, this study integrates the evaluation results of the three dimensions using the Decision-making Trial and Evaluation Laboratory (DEMATEL). The proposed approach and decision-making model can help managers of sustainable supply chains in the chemical industry to choose more sustainable suppliers, respond to market demands quickly, and maintain high competitiveness in the market. An illustrative application of the proposed framework and model is undertaken in one of the biggest Chinese petrochemical companies to verify its practicality and reliability.

Abstract. Landslide spatial, temporal, and size probabilities were used to perform a landslide hazard assessment in this study. Eleven intrinsic geomorphological, and two extrinsic rainfall factors were evaluated as landslide susceptibility related factors as they related to the success rate curves, landslide ratio plots, frequency distributions of landslide and non-landslide groups, as well as probability–probability plots. Data on landslides caused by Typhoon Aere in the Shihmen watershed were selected to train the susceptibility model. The landslide area probability, based on the power law relationship between the landslide area and a noncumulative number, was analyzed using the Pearson type 5 probability density function. The exceedance probabilities of rainfall with various recurrence intervals, including 2, 5, 10, 20, 50, 100 and 200 yr, were used to determine the temporal probabilities of the events. The study was conducted in the Shihmen watershed, which has an area of 760 km2 and is one of the main water sources for northern Taiwan. The validation result of Typhoon Krosa demonstrated that this landslide hazard model could be used to predict the landslide probabilities. The results suggested that integration of spatial, area, and exceedance probabilities to estimate the annual probability of each slope unit is feasible. The advantage of this annual landslide probability model lies in its ability to estimate the annual landslide risk, instead of a scenario-based risk.