Human Factors Analysis for Maritime Accidents Based on a Dynamic Fuzzy Bayesian Network

Human factors are widely regarded to be highly contributing factors to maritime accident prevention system failures. The conventional methods for human factor assessment, especially quantitative techniques, such as fault trees and bow-ties, are static and cannot deal with models with uncertainty, which limits their application to human factors risk analysis. To alleviate these drawbacks, in the present study, a new human factor analysis framework called multidimensional analysis model of accident causes (MAMAC) is introduced. MAMAC combines the human factors analysis and classification system and business process management. In addition, intuitionistic fuzzy set theory and Bayesian Network are integrated into MAMAC to form a comprehensive dynamic human factors analysis model characterized by flexibility and uncertainty handling. The proposed model is tested on maritime accident scenarios from a sand carrier accident database in China to investigate the human factors involved, and the top 10 most highly contributing primary events associated with the human factors leading to sand carrier accidents are identified. According to the results of this study, direct human factors, classified as unsafe acts, are not a focus for maritime investigators and scholars. Meanwhile, unsafe preconditions and unsafe supervision are listed as the top two considerations for human factors analysis, especially for supervision failures of shipping companies and ship owners. Moreover, potential safety countermeasures for the most highly contributing human factors are proposed in this article. Finally, an application of the proposed model verifies its advantages in calculating the failure probability of accidents induced by human factors.     

Capitalizing the Crisis? Explanatory Factors for the Design of Short‐time Work across Organisation for Economic Co‐operation and Development Countries

This article looks at the financial and economic crisis 2008–10 in 18 Organisation for Economic Co‐operation and Development states and seeks to investigate explanatory paths for the subsidization of further education within short‐time work programmes. Several hypotheses are put to the test: first, a classical partisan difference argument; second, a varieties of capitalism approach proposing a successful joint rallying of employers and employees for subsidization in coordinated market economies; and, lastly, the merged hypothesis that right‐wing parties in a coordinated economic context might subsidize feeling the pressure to overcompensate an ‘issue ownership’ of left parties in the field of employee‐friendly policies. We identify four explanatory paths: coordinated economies in the sample subsidized when they were economically closed or highly indebted. The results also support our combined hypothesis, that New Zealand – a left‐governed liberal market economy – and right‐governed coordinated market economies of the non‐Scandinavian type subsidized.     

Assessment of supplier performance based on product-development strategy by applying multi-granularity linguistic term sets

Measuring supplier performance possesses the properties of multi-dimension and multi-scale, it increases the complexity of the aggregation and assessment process. A focal company must develop an effective procedure for overcoming the complexity of performance measurement. Furthermore, the assessment of supplier performance must conform to the product-developed strategy of the focal company. This study is a further research deeper into the concept already introduced in Chang et al. [1] [Applying fuzzy linguistic quantifier to select supply chain partners at different phases of product life cycle. International Journal of Production Economics 2006; 100(2):348–59]; using multi-granularity linguistic variable and numerical ration scale to represent the overall supply performance. By unifying the derived information, the measurement complexity could be resolved. The fuzzy preference was constructed to adjust the consistent direction and transform information into fuzzy relationship. Finally, fuzzy linguistic quantifier guided ordered weighted aggregation (FLQG-OWA) operator with maximal entropy was computed and aggregated with all indicators to meet the current policy of the focal company.     

基于产业链视角的物联网产业发展策略研究

物联网(IOT)作为新一代的信息技术,被认为是继计算机和互联网之后世界信息产业发展的第三次浪潮,是未来推动世界经济增长的重点新兴产业之一。为了全面、系统地认识物联网产业,更好地指导和推动物联网产业实践的发展,有必要以产业的视角,对物联网产业链的基本结构、影响产业链发展的关键环节进行深入研究,寻找物联网产业发展的关键点。通过对物联网体系结构的分析,发现我国物联网产业链主要由传感器/芯片制造商、软件提供商、物联网平台提供商、系统集成商、应用服务提供商、网络服务提供商、运营服务提供商和用户等环节构成,进一步运用模糊德尔菲法,得出用户和传感器/芯片制造商是我国物联网产业发展的关键环节,并据此提出了相关政策建议。     

丹东市五龙背镇乡村旅游资源AHP-Fuzzy法评价

选取AHP-Fuzzy法对丹东市五龙背镇的乡村旅游资源定量评价结果表明,该地区的评价分值为6.057分,属于有潜力开发范围。五龙背镇乡村旅游资源丰富,根据对该地区的调查评价结果分析,指出五龙背地区在地热资源开发上的不足与开发方向的偏差,五龙背镇应当重点建设温泉水资源项目,突出旅游地的康疗保健功能,同时对资源进行全面整合,提升乡村旅游服务的档次。     

基于模糊物元模型的雇主吸引力比较研究——以环渤海地区高新区为例

文章在以往有关雇主吸引力构成维度研究成果的基础上,结合高新区特点,构建了其雇主吸引力评价指标体系。并在物元分析的基础上,运用模糊集合理论和欧氏贴近度的概念,建立了高新区雇主吸引力的评价模型,对环渤海地区九个高新区进行实证研究,从而为高新区提高雇主吸引力、吸引目标人才提供了科学的依据。     

ANP-Fuzzy方法在电力企业绩效考核中的应用研究

本文针对我国电力企业绩效考核指标间具有相互影响关系,且大多定性指标难以精确界定的特点,给出了一种ANP-Fuzzy的综合评价法。首先,建立系统的绩效考核指标体系及具体的考核标准,为考核员工提供规范化的评价框架。其次,设计能够准确反映考核指标间相互关系的ANP网络结构,以此确定具有联系性的指标权重。在此基础上,设计能够精确界定定性指标的Fuzzy多层次评价结构,以此评价具有模糊性的员工绩效。最后,运用Super Decisions软件和Matlab软件,给出了基于ANP-Fuzzy方法的电力企业员工绩效考核实证研究。结果表明,该方法合理可行,能够真实反映员工绩效,并且能够有效区分员工自身不同方面的绩效差异以及员工之间的绩效差异。这对帮助员工发现绩效改进空间,不断提升自身绩效具有明显效果。同时,该方法可以借助软件实现,将其应用于电力企业绩效考核具有较强的操作性。     

模糊评价模型在食品供应链管理风险中的应用

基于食品供应链风险评价指标体系,建立模糊评价模型,并运用该模型对食品供应链风险进行综合评价,实证分析得出:快餐巨无霸麦当劳在供应链管理中的风险较低。