Dynamic Analysis of Customer Demand Based on Intuitionistic Fuzzy Number in Product Planning

To address the fuzziness and variability in determining customer demand importance,a dynamic analysis method based on intuitionistic fuzzy numbers is proposed.First,selected customers use intuitionistic fuzzy numbers to represent the importance of each demand.Then,the preference information is aggregated using customer weights and time period weights through the intuitionistic fuzzy ordered weighted average operator,yielding a dynamic vector of the subjective importance of the demand index.Finally,the feasibility of the proposed method is demonstrated through an application example of a vibrating sorting screen.

Application of a Bayesian Network Complex System Model Examining the Importance of Customer-Industry Engagement to Peak Electricity Demand Reduction

This paper explores the importance of customer-industry engagement (CIE) to peak energy demand by means of a newly developed Bayesian Network (BN) complex systems model entitled the Residential Electricity Peak Demand Model (REPDM). The REPDM is based on a multi-disciplinary perspective designed to solve the complex problem of residential peak energy demand. The model provides a way to conceptualise and understand the factors that shift and reduce consumer demand in peak times. To gain insight into the importance of customer-industry engagement in affecting residential peak demand, this research investigates intervention impacts and major influences through testing five scenarios using different levels of customer-industry engagement activities. Scenario testing of the model outlines the dependencies between the customer-industry engagement interventions and the probabilities that are estimated to govern the dependencies that influence peak demand. The output from the model shows that there can be a strong interaction between the level of CIE activities and interventions. The influence of CIE activity can increase public and householder support for peak reduction and the model shows how the economic, technical and social interventions can achieve greater peak demand reductions when well-designed with appropriate levels of CIE activities.

Managing Channels of Distribution Under the Environment of Electronic Commerce

Business Marketing Management over the Internet has been receiving a“lot of ink”in current periodicals and to a lesser degree in academic literature.Practice changes so rapidly that principles emerging from last month’s successes may need revi- sion before they are derived and printed.The emergence of electronic commerce has created a new business paradigm,one that pre- sents marketers with noteworthy opportunities and challenges.Perhaps the greatest impact is in the area of channel management. The top issue for many business-to-business (B2B) firms today is channel conflict.In this paper,we analyze the weakness of traditional place model at first.On the basis of it,we set forth the processes and advantages of direct place and indirect place un- der the environment of electronic commerce.Then this paper presents that we should develop association net,express net,service net and production net in order to create place advantage under the environment of electronic commerce.

Influence of Customized Demand Generation as a Strategy to Increase Uptake of Voluntary Counseling and Testing Services amongst Sex Workers in Mumbai and Thane

Background: To demonstrate that customized demand generation leads to increased voluntary HIV counseling and testing (VCT) among Sex Workers (SWs). Methods: FHI 360 Aastha implemented Vivek intervention among SWs in Mumbai and Thane, India using customized demand generation through outreach services for VCT. Program monitoring data and integrated counseling and testing center tracking sheets were used to assess the intervention effect. Results: Higher proportion of registered SWs tested during: 1) Vivek months than other months (17% vs. 5%, p < 0.001);2) Post-initiation non-Vivek months than pre-Vivek months (4.7%, vs. 1.5% p < 0.001). Conclusions: Customized demand generation approach is successful in increasing HIV testing.

Respecting Each Other and Being Loyal to ZTE Career Providing Refined Service and Focusing on Customers' Requirements Working Hard to Create Famous ZTE Brand Improving ZTE Efficiency with Scientific Management

ZTE Corporation is China’s largest listedtelecommunications equipment provider spe-cialized in offering a full range of tailor-madesolutions for customers in high-,middle-andlow-end markets.

Analysis of the Evolution and Influence on the Industrial Value Chain in Telecommunications

This paper discusses the evolution of telecommunication industrial value chain （TIVC）, analyzes the influence of technical innovation and customer demand on TIVC, and establishes the model. The appearance of the circuit switching technology and packet switching technology together with the diversity of the demand of customers change the structure of TIVC, causing vibration in value creation and distribution systems. With changes of the TIVC, enterprises in the chain will accordingly alter their business models, products （services） and the internal organizational structures. All these changes will lead to the reconstruction and optimization of the TIVC, and consequently, promote the development of the telecommunication industry.

The Relationship between Customer Knowledge Management and Performance of Agricultural Product Innovation

This paper takes an overview of the CKM and the performance of agricultural product innovation from contents of agricultural product innovation and customer knowledge management (CKM) ,the relation between CKM and agricultural product innovation. On the basis of the overview, it builds the theoretical framework of CKM and agricultural product innovation. It points out that enterprises can satisfy demands of customers through acquisition,share,utilization and innovation of customer knowledge,and improve performance of agricultural product innovation through speeding up agricultural product innovation.

Study on Customer Demands for Product Innovation

In order to improve the satisfaction degree of customers’individual demands for products and reduce the risk of the product innovation,the characteristics of customer demands for product innovation are analyzed,and the type and content of customer demands are discussed.Then the framework of customer demands acquisition for product innovation is established.Final- ly,the prototype system of customer demands information acquisition and product customization for product innovation which takes mobile phone as the example is developed successfully.

Study on Customer Demands for Product Innovation

In order to improve the satisfaction degree of customers’ individual demands on products and reduce the risk of the product innovation,the characteristics of customer demands for product innovation are analyzed,and their type and content are discussed. Then the framework of customer demands acquisition for product innovation is established. Finally,the prototype system of customer demands information acquisition and product customization for product innovation which takes mobile phone as the example is developed successfully.

Clustering-based Demand Response for Intelligent Energy Management in 6G-enabled Smart Grids

As a typical industrial Internet of things(IIOT)service,demand response(DR)is becoming a promising enabler for intelligent energy management in 6 G-enabled smart grid systems,to achieve quick response for supply-demand mismatches.How-ever,existing literatures try to adjust customers’load profiles optimally,instead of electricity overhead,energy consumption patterns of residential appliances,customer satisfaction levels,and energy consumption habits.In this paper,a novel DR method is investigated by mixing the aforementioned factors,where the residential customer cluster is proposed to enhance the performance.Clustering approaches are leveraged to study the electricity consumption habits of various customers by extracting their features and characteristics from historical data.Based on the extracted information,the residential appliances can be scheduled effectively and flexibly.Moreover,we propose and study an efficient optimization framework to obtain the optimal scheduling solution by using clustering and deep learning methods.Extensive simulation experiments are conducted with real-world traces.Numerical results show that the proposed DR method and optimization framework outperform other baseline schemes in terms of the system overhead and peak-to-average ratio(PAR).The impact of various factors on the system utility is further analyzed,which provides useful insights on improving the efficiency of the DR strategy.With the achievement of efficient and intelligent energy management,the proposed method also promotes the realization of China’s carbon peaking and carbon neutrality goals.

考虑需求响应和用户满意度的主动配电网优化调度

为提高主动配电网(active distribution network,ADN)运行经济性和用户满意度,提出一种考虑需求响应和用户满意度的ADN优化调度方法。综合考虑ADN运行过程中的购电成本、发电成本、维护成本和需求响应成本,建立了以ADN总运行成本最小为目标函数的优化调度模型。利用混沌映射、莱维飞行和收敛因子非线性变化等策略对斑点鬣狗优化算法(spotted hyena optimization,SHO)进行优化,以提高斑点鬣狗算法的优化性能。采用改进斑点鬣狗优化算法(ISHO)对ADN优化调度模型进行求解,算例分析结果表明,ISHO算法的优化效果优于其他算法,2种需求响应同时参与系统调度时的ADN总运行成本最小,经济性更好。

客户风险投资的供应链溢出效应——上游企业双元创新视角

本文以A股上市公司供应链关系数据为研究对象,考察客户风险投资对上游企业双元创新的影响。研究发现:客户风险投资具有供应链溢出效应,显著提高了上游企业的双元创新水平。机制检验表明,溢出效应主要通过企业学习机制与市场需求响应机制影响上游企业双元创新。此外,共同股东与客户集中度分别对上述关系起到正向调节作用。异质性检验结果表明,当上游企业客户关系良性程度较高以及融资约束较弱时,溢出效应对双元创新的促进作用更为明显;而当上游企业属于高科技行业时,溢出效应对探索式创新的促进作用更为明显。本文从风险投资供应链溢出视角出发,为企业双元创新提升的新路径提供了理论依据和政策启示。

面向内部客户需求的人力资源管理成熟度模型

人力资源管理成熟度是评价公司人力资源管理水平的重要工具。目前国内外人力资源管理成熟度模型普遍存在两点不足:缺乏内部客户思维、指标过多导致操作繁琐。本研究以公司高层管理者工作的典型需求为依据,精简评价指标,设计了新的人力资源管理成熟度模型,可以较好改善上述不足,并且具有较好的实践价值。

考虑需求密度和客户满意度的城市末端服务网点选址问题

为解决“最后一公里”的配送问题,结合城市末端配送需求的服务网点特点,考虑需求密度和客户满意度,建立了以时间满意度最大化、利润最大化和需求密度最大化为目标的多目标选址模型。设计了基于线性加权法的改进自适应遗传算法,采用自适应算子处理变异概率和交叉概率,并设计三种不同的交叉算子,扩大搜索邻域。在改进算子的基础上设计了多目标遗传算法,使用快速非支配排序法去除权重系数取值对选址结果的影响。利用北京市海淀区的快递服务网络数据进行实例分析,使用设计的两种遗传算法分别求解选址模型的全局最优解和帕累托前沿解;并将改进自适应遗传算法与传统遗传算法、自适应遗传算法的求解结果进行比较。结果显示:改进自适应遗传算法比传统遗传算法和自适应遗传算法收敛速度更快、搜索能力更优;若无法确定改进自适应遗传算法的权重,使用改进后的多目标遗传算法同样可以求到最优解。

虚拟电厂两阶段准线型需求响应优化及收益共享-风险共担决策方法

末端分散式资源的需求响应(demand response,DR)是支撑电力系统灵活调节的重要形式,但末端资源通常规模大且单体容量小,迫切需要虚拟电厂(virtual power plant,VPP)等市场主体进行聚合代理,从而间接参与电网公司的调节服务。聚焦于准线型需求响应这一新兴的响应模式,重点研究VPP内部分散式资源的利益-风险互动协调策略,提出面向准线型DR的VPP两阶段优化及收益共享-风险共担决策方法,构建VPP与电网、内部用户互动协调新模式。首先,在准线型激励下VPP以整体收益最大化为目标,考虑柔性负荷响应积极度与新能源准确度因子,进行日前-日内两阶段DR优化;其次,在收益共享-风险共担决策方法下,VPP与柔性负荷共享准线型激励、与新能源共担不确定性风险,并以改进的Shapley法对内部柔性负荷进行利益分配。仿真结果表明,相较于传统DR,准线型DR给出全时段响应目标,更具有优越性;共享-共担决策吸引柔性负荷参与VPP调节,促使VPP与用户双赢。

工业用户连续参与需求响应的用户基线负荷精准计算方法

提出了一种将K-means聚类分析与长短期记忆神经网络算法结合,通过工业同源组信息进行迁移学习优化的计算方法。该方法实现了对长时间连续参与需求响应的工业用户基线负荷的精准计算,提高了工业用户需求响应效果评价的准确性。通过城市级虚拟电厂平台采集的参与需求响应实践的工业用户电力负荷数据,验证了该方法的有效性。

基于负荷准线的5G基站虚拟电厂优化控制方法

在新型电力系统中,亟待深度挖掘需求侧资源以提升系统灵活性和新能源消纳能力。在“新基建”背景下,5G基站作为一种新型需求侧资源正迅速发展。研究如何在保证基站备用需求的前提下,由铁塔公司组建含大规模5G基站的虚拟电厂(virtual power plant,VPP)并常态化参与需求响应。首先,提出了考虑储能动态备用容量的5G基站运行可行域构建方法,建立了5G基站VPP的聚合模型。然后,建立了5G基站VPP响应负荷准线的日前优化模型,提出了适合对大规模5G基站进行协调控制的日内解聚合方法。最后,建立了含高比例新能源的区域电网仿真算例。仿真结果表明,聚合大规模基站参与准线型需求响应,可以显著降低5G基站的运行成本,同时提高电网的新能源消纳能力。

论生成式AI时代的用户需求与表达范式——从分众匹配到层级递进的要素融合网络

生成式人工智能时代的用户需求与表达发生了极大的改变。相较于互联网媒介时代,生成式人工智能时代的用户需求表现为“基底需求—需求要素补充”的生成机制,呈现出“过程性”“渐进稳态性”和“要素融合下的细描微调”的新特点。用户需求的表达方式趋向“自然交互”,表达逻辑趋向“理性和非理性要素融合”,表达粒度也趋向“细粒度”。用户需求和需求表达方式的变化,本质上是用户需求个性化趋势驱动下的内容生产、分发和消费的自组织,这也意味着分众策略逐步失灵,整个新闻传播业态将迎来“自组织式”的质变。在生成式人工智能技术时代下把握用户需求和需求表达,需要关注新闻传播的自组织价值创生范式,这与用户的个性化需求相匹配。此外,用户深层心理机制可能是未来媒介产品开发的需求蓝海。

考虑准线需求响应的高比例新能源电力系统调度优化

随着新能源装机容量与发电量占比的快速攀升,传统火电机组装机容量大幅降低,为平移新能源出力的随机性和波动性,迫切需要将负荷侧纳入调度优化。为此,提出一种考虑准线需求响应的高比例新能源电力系统调度模型。首先,构建考虑新能源出力存在极端出力和极端爬坡情况的不确定性场景集;其次,根据各节点负荷结构特点,刻画节点负荷响应能力差异,并加入正则化项对准线形状进行约束,在此基础上提出了考虑负荷响应能力的节点负荷准线模型;再次,将准线需求响应引入日前调度,建立高比例新能源电力系统两阶段调度优化模型;最后,通过对IEEE-30节点系统的算例分析表明,所提调度方法能够有效抑制新能源的不确定性,增强高比例新能源电力系统的新能源消纳能力和电力可靠供应能力。

基于QFD的可伸缩式登船栈桥设计方法

针对可伸缩式登船栈桥设计流程,以客户需求为导向,构建了基于质量功能展开法的设计思路和方法。运用实景体验和场景打分的方法,深度挖掘5个维度的客户需求、关键质量特性和关键物料特性,通过AHP等方法进行权重分析,构建可伸缩栈桥分析的一阶质量屋和二阶质量屋,开展关键物料的重要度-成本分析,有效满足了客户需求和规范要求,形成可伸缩栈桥设计开发新模式。