基于多元智商的外派经理评价指标与选择方法

针对跨国公司外派经理的选择问题,给出了一种实用的决策分析方法。首先,借鉴已有的研究成果,建立了一套基于多元智商的外派经理评价指标体系;然后,考虑指标的主观判断因素,引入了模糊数的概念,并基于理想点法给出了一种多指标决策方法;最后,通过一个算例说明了方法的应用。     

基于模糊相对势的MIS事前评价方法

针对信息系统事前评价指标的不确定性,提出使用三角模糊数值对指标进行评价,并给出了一种基于模糊相对势的管理信息系统事前评价方法.由于权重信息完全未知,通过计算每个决策方案与正负理想方案之间的模糊相对势,比较每个方案之间的模糊相对势的大小对方案进行择优.该方法的优点是不需要知道属性权重的大小,从而为信息化建设提供了一种客观评价方法.     

外派人员跨文化沟通能力对工作绩效的影响研究：专业知识学习的中介效应

本文旨在研究如何促进海外派遣人员（简称外派人员）的专业知识学习以顺利完成外派任务.对355位外派人员的实证结果发现： 跨文化沟通能力是外派人员学习战略性隐性专业知识的重要影响因素.当外派人员所学的专业知识隐性程度增加时,跨文化沟通能力通过促进专业知识学习从而提升任务绩效的间接效应增加;只有在知识隐性程度低、文化距离大的情况下,跨文化沟通能力对任务绩效才有显著的直接影响效应.本文的研究结论丰富了跨国公司知识转移和外派人员管理相关研究成果,对跨国公司的外派人员选拔和培训也有较好的借鉴作用.     

TOPSIS法及其QBasic编程实现

文章给出了一种基于TOPSIS的多属性决策方法,并通过实例检验了该方法的有效性.同时利用QBasic语言进行编程,得到通用程序,它可以适用于任意有限个评价对象和多属性类型的评价指标的综合评价.     

利用二级模糊综合评判进行大学体育教师综合素质评估

将二级模糊综合评判引入大学体育教师的综合素质评估,选取了评估指标及测度方法;随后,建立了一种开放的评估模型;最后,结合实际数据给出应用实例.实践证明了本文方法可行性.     

基于贝叶斯网络的工程项目经理胜任力评价研究

工程项目建设过程中,项目经理胜任力指标随着工程项目的推进而动态变化,因而对传统的工程项目经理胜任力静态评价方法提出了挑战。基于贝叶斯网络适用于动态、不确定性问题推理的特性,提出了基于贝叶斯网络的工程项目经理胜任力评价模型。实例应用表明,该方法适用于工程项目经理胜任力评价,具有较好的应用前景。     

基于BP神经网络的经理管理防御程度测评模型

提出一种基于主成分分析的BP神经网络模型,用于对经理人员的管理防御程度进行综合测评.首先采用主成分分析方法对10个影响因素进行降维处理,在此基础上构建管理防御程度的BP神经网络测评模型.实际测评结果显示,该模型不仅可以有效测评经理人员的管理防御程度,并且可以减少原始指标间的信息冗余从而减少了神经网络的训练和测试时间,此外还具有较高的合理性和适用性.     

外派技术人员社会资本对企业间知识转移的影响机制研究

外派技术人员是企业间知识转移的重要载体,也是企业从外部获取知识的有效途径。基于个体社会资本的角度,结合外派技术人员的工作特征与社会网络特征,探讨外派技术人员的社会资本及其对企业间知识转移的影响机制,指出外派技术人员的社会资本三维度(结构、关系和认知)分别对企业间知识迁移的方向、载体和内容的影响,为下一步实证研究提供理论框架,并为企业在外派技术人员管理、推动企业间知识转移方面提出对策。     

基于术语指标的电子商务系统安全评价模型

在电子商务系统安全性评价过程中,采用量化方法可以使结果更精确。通过提出一种基于术语指标的电子商务系统安全评价方法,对电子商务系统安全评价过程中以语言形式给出的评估术语进行定义,利用评估标度中术语与其指标之间的函数关系,以及加权算术平均算子和混合集结算子,提出了一种基于术语指标群决策方法的电子商务系统安全评价模型。最后通过实证研究,证实了该方法的科学性与实用性。     

基于语言评价的政府服务质量测评方法及实证分析

科学的政府服务质量测评方法对于服务型政府的建设具有重要作用.根据政府服务及其质量测评的内在特点,提出了一种政府服务质量测评方法.并进行了实证研究.该方法在充分考虑了人类思维的模糊性的基础上,采用语言评价采集指标测评数据,并利用模糊数学方法将指标测评数据集结为用语言表达的总体测评结果;利用该方法得到的测评结果不仅能给出政府服务质量的总体评价,而且能给出单个测评维度以及指标上的具体评价,从而能为政府部门改善服务提供依据.     

Modelling information flow for organisations: A review of approaches and future challenges

Modelling is a classic approach to understanding complex problems that can be achieved diagrammatically to visualise concepts, and mathematically to analyse attributes of concepts. An organisation as a communicating entity is a made up of constructs in which people can have access to information and speak to each other. Modelling information flow for organisations is a challenging task that enables analysts and managers to better understand how to: organise and coordinate processes, eliminate redundant information flows and processes, minimise the duplication of information and manage the sharing of intra- and inter-organisational information.     

员工外派的绩效评测与功效:一个社会调查的结果

从绩效评测角度对员工外派的管理问题进行了理论探讨,并基于122家企业的调查数据进行实证检验,检验的结果表明:(1)评测信息渠道的多元化不仅有助于改进企业的非财务绩效,同时也有助于提高企业的财务绩效; (2)及时的、面对面的反馈与沟通机制以及员工外派绩效评测过程中的弹性化,将有助于改进企业的非财务绩效,但对财务绩效的影响不太显著和稳健;(3)基于行为导向的绩效评测工具有助于改进企业的财务绩效,但对非财务绩效的影响并不显著。     

Knowledge networks: Dilemmas and paradoxes

After defining knowledge networks and the basic concepts of paradox and dilemmas, I analyze a sample of paradoxes/dilemmas commonly associated with them involving culture, structure, cognition, and actionable knowledge. In doing this I focus on how one side of the dilemmas is often associated with negative connotations that drive managers away from that choice. So, for example, hoarding, while it clearly benefits individuals in certain contexts, is typically viewed as a selfish act that hurts the collective. I conclude this essay with a discussion of the need for managers to deliberately confront dilemmas.     

A twin data-driven approach for user-experience based design innovation

Data-driven innovation has received increasing attention, which explores big data technologies to gain more insights and advantages for product design. In user experience (UX) based design innovation, user-generated data and archived design documents are two valuable resources for various design activities such as identifying opportunities and generating design ideas. However, these two resources are usually isolated in different systems. Additionally, design information typically represented based on functional aspects is limited for UX-oriented design. To facilitate experience-oriented design activities, we propose a twin data-driven approach to integrate UX data and archived design documents. In particular, we aim to extract UX concepts from product reviews and design concepts from patents respectively and to discover associations between the extracted concepts. First, a UX-integrated design information representation model is proposed to associate capabilities with key elements of UX at the concept, category, and aspect levels of information. Based on this model, a twin data-driven approach is developed to bridge experience information and design information. It contains three steps: experience aspect identification using an attention-based LSTM (Long short-term memory) network, design information categorization based on topic clustering using BERT (Bidirectional Encoder Representations from Transformers) and LAD (Latent Dirichlet allocation) model, and experience needs and design information integration by leveraging word embedding techniques to measure concept similarity. A case study using healthcare-related experience and design information has demonstrated the feasibility and effectiveness of this approach.     

深基坑支护方案的综合评价方法

分析了深基坑支护方案评价的影响因素,利用未确知测度模型对其进行综合评价,建立了一种适用于深基坑支护方案综合评价的未确知优化理论模型。为决策者提供了一种科学有效的评判方法。应用一个实际例子说明了此模型的应用。     

Interpretable machine learning-based approach for customer segmentation for new product development from online product reviews

For new product development, previous segmentation methods based on demographic, psychographic, and purchase behavior information cannot identify a group of customers with unsatisfied needs. Moreover, segmentation is limited to sales promotions in marketing. Although needs-based segmentation considering customer sentiments on product features can be conducted to develop a new product concept, it cannot identify commonalities among customers owing to their diverse preferences. Therefore, this paper proposes an interpretable machine learning-based approach for customer segmentation for new product development based on the importance of product features from online product reviews. The technical challenges of determining the importance of product features in each review are identifying and interpreting the nonlinear relations between satisfaction with product features and overall customer satisfaction. In this study, interpretable machine learning is used to identify these nonlinear relations with high performance and transparency. A case study on a wearable device is conducted to validate the proposed approach. Customer segmentation using the proposed approach based on importance is compared with that employing a previous approach based on sentiments. The results show that the proposed approach presents a higher clustering performance than the previous approach and offers opportunities to identify new product concepts.     

Big data management in healthcare: Adoption challenges and implications

The computerized healthcare information system has undergone tremendous advancements in the previous two decades. Medical institutions are paying further attention to the replacement of traditional approaches that can no longer handle the increasing amount of patient data. In recent years, the healthcare information system based on big data has been growing rapidly and is being adapted to medical information to derive important health trends and support timely preventive care. This research aims to evaluate organization-driven barriers in implementing a healthcare information system based on big data. It adopts the analytic network process approach to determine the aspect weight and applies VlseKriterijumska Optimizacija I Kzompromisno Resenje (VIKOR) to conclude a highly appropriate strategy for overcoming such barriers. The proposed model can provide hospital managers with forecasts and implications that facilitate the withdrawal of organizational barriers when adopting the healthcare information system based on big data into their healthcare service system. Results can provide benefits for increasing the effectiveness and quality of the healthcare information system based on big data in the healthcare industry. Therefore, by understanding the sequence of the importance of resistance factors, managers can formulate efficient strategies to solve problems with appropriate priorities.     

基于论文题名的知识驱动关系分析方法研究——以信息与知识传播研究领域为例

[研究目的]基于论文题名快速梳理特定研究领域中的概念,并确定概念所代表的知识之间驱动关系,有助于科学了解研究领域状况,为进一步寻找研究方向提供可能。[研究方法]以信息与知识传播研究领域为例,收集整理题名中包含“知识”研究论文元数据,在Stanford Parser的短语结构分析结果基础上,对驱动关系进行人工审定,并做边界调整、拆分和规范化,得到概念间的真实驱动关系数据,定义若干分析指标,以上述数据为基础构建加权有向图,并基于复杂网络分析和可视化技术分析展示在知识驱动方面具有不同特点的概念及驱动路径。[研究结论]该研究借鉴和发展共词分析方法,提出并实现了一种能够揭示研究领域概念之间有方向的知识驱动关系的方法,利用本方法可以发现不同概念在某一领域的驱动强度大小、特定的驱动路径和若干稳定或脆弱的概念团组。