关于信访稳定工作的几点思考

信访稳定工作是构建和谐企业的基础性工作。文章就如何全过程抓好信访稳定工作、有力有效维护企业稳定进行思考,并针对历史遗留问题和电力体制改革过程中出现的新问题,结合实际提出对策。     

Analysing complaint intentions in online shopping: the antecedents of justice and technology use and the mediator of customer satisfaction

Complaint behaviours are the key to the competition in an online market when service quality is a major concern of consumers. An understanding of complaint intentions can provide insight into a negative service experience and in turn, effectively redress consumer's problems. It is our purpose to examine the determinants of complaint intentions in the online shopping. When online consumers essentially involve the purchase of products/services and the use of web-based technologies, two major issues particularly arise in this context, exchange behaviour and technology use. This study thus integrates justice perception and expectation–confirmation model (ECM) of information system continuance to understand customer satisfaction and in turn, complaint intentions. Data were collected for online consumers with negative service experiences. The results of testing the structural model indicated that distributive and interactional justices significantly contribute to customer satisfaction and complaint intentions, but procedural justice does not. ECM-based features, such as perceived usefulness, are all important in determining customer satisfaction and complaint intentions. The implications for managers and scholars are further discussed.     

S中国销售公司投诉流程优化仿真

业务流程决定了企业运营的效率,其涵盖了采购、制造、销售等一系列的生产环节,因此对流程的分析和优化对于企业管理来说有着十分重要的作用。投诉,在日常生活中是商家和客户关系中最常见却又最敏感的问题,投诉问题处理好坏直接关系到商家的信誉和品质,应该引起足够的重视。本文分析了现有的S中国销售公司的投诉流程,发现其流程在时间成本和费用成本的消耗上都存在问题,需改进。利用Witness仿真软件对投诉流程系统进行建模和仿真,提出了投诉流程的优化方案,仿真结果证明了改进后方案的可行性和有效性,为流程的优化提供了一种有效的定量分析技术。     

面向中小型旅行社的客服系统构建

通过分析中小旅行社的特点,以及客户服务中存在的问题,本文针对这些存在的问题与特点,采用．NET2．0技术,三层架构体系来构建适合中小型旅行社的客服系统,优化投诉流程,协同化解决问题,并建立起相应的客户信息库,投诉处理规则库,监控工作业务流程,用以改善旅行社的客服质量水平,应用规则处理,提高客户投诉处理的效率,利用客户信息库对客户进行分析,从而形成相关的知识库,最终实现较为初级的客户关系管理。     

基于无线信令指标的用户投诉定位方法

针对4G网络投诉数量骤增,用户投诉原因追溯难的问题,提出一种基于端到端网络业务质量评估模型的用户投诉原因精准定位方法。首先,针对用户投诉数据不平衡性的问题,在对LTE无线侧信令进行数据重构和稀疏特征提取的基础上,采用主动学习框架扩充用户感知数据库,为端到端网络业务质量评估模型提供数据基础;其次,采用BP神经网络关联用户投诉原因和无线侧信令指标,构建端到端网络业务质量评估模型;最后,基于端到端网络业务质量评估模型的结果,挖掘影响投诉原因的关键无线侧信令指标,获取关键无线侧信令指标的触发告警阈值,实现用户投诉原因的精准定位。实验证明,提出的方法具有一定的扩展性。     

联通移动网络投诉预处理系统设计构想

本文通过分析目前的联通移动网络投诉处理流程及现状着手,从移动网络投诉预处理系统的建设目标、建设与构想、评估与考核、效果分析假设几个方面设计了一整套集优化、集成、完整、便捷的预处理系统,该系统实施后将实现企业服务与用户感知双提升的深远意义与价值。     

一种粗糙地形下四足仿生机器人的柔顺步态生成方法

传统以刚体动力学为基础的四足机器人运动控制方法对地形误差敏感,无法适应粗糙复杂地形,因此提出一种基于虚拟模型的运动控制方法用于实现四足机器人在粗糙地形下的行走.建立了以足底接触力为约束的高层步行任务和底层运动控制的映射关系.采用弹簧-阻尼-质量虚拟模型对四足机器人进行建模,将四足机器人的步行任务用一系列作用于机体质心的虚拟力去表征,基于各足等效力矩平衡的原则,将笛卡儿空间的虚拟力矢量分配到各支撑足,利用雅可比矩阵把足端力矢量转换为机器人关节空间的关节转矩.针对崎岖的空间3维粗糙地形,建立了机器人躯干姿态与地形的关联参数,通过调整躯干姿态有效扩大了机器人对粗糙地形的适应程度.运动仿真结果表明,机器人可以实现粗糙地形下稳定连续的行走,足底接触力平稳、无冲击,证明了该柔顺步态生成方法的合理性和有效性.     

基于时间序列建模的电力营销客户交易行为分析

针对电力系统对客户服务的效率低、针对性差的问题,提出了一种采用云模型、离散余弦变换和反向传递神经网络的客户分类算法.通过云模型提取价格敏感度、投诉率、欠费率、销售变现天数以及忠诚度的变化波动情况的云测度,结合余弦变换计算得到特征向量,输入反向传递神经网络训练,从而得到自动客户分级识别的模型.结果表明,提出的模型可以有效实现客户分级以及销售状况评估,其平均检测精确度可达95%以上.     

Responses of psychologists to complaints filed against them with a state licensing board.

Psychologists are well aware of the possibility of complaints to licensing boards by clients, interns, employees, and others. As many as 11% of psychologists may have to respond to a complaint during their careers. Data collected by a licensing board from psychologists who had complaints filed against them were analyzed. Those who were found to have committed a violation were compared with those who were found to have committed no violation. The violation group (a) reported many more sequelae, including the expenditure of more time and money and the occurrence of more medical and psychological problems and (b) perceived the process and outcome as less fair. These findings suggest that review and modification of the complaint process are needed and that psychological and professional services may be helpful during and after complaint adjudication. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

基于局部线性嵌入和深度森林算法的电力客户投诉预测模型

由于电力市场竞争日益激烈,用户对服务质量的要求不断提高,用户投诉量持续上升。在基于大数据的电力客户投诉预测模型的体系结构基础上,提出一种基于局部线性嵌入和深度森林算法的电力客户投诉预测方法。采用局部线性嵌入算法对客户投诉预测模型的输入特征向量进行降维处理,减少计算量和避免陷入局部最优解;对降维后的投诉预测特征向量进行多粒度扫描,提高其表征学习能力;基于级联森林建立深度森林算法模型,实现客户投诉预测。实际数据的仿真结果表明,与不进行降维处理及其他预测模型相比,文中所提出的预测模型可以更准确地预测客户投诉趋势,为电力企业客户投诉分析和预测提供了参考依据。