服务产品多营销渠道下顾客渠道选择的量化分析

在全球服务经济迅速发展的背景下,以数字化为基础、互联网为纽带的新经济革命的到来,为服务产品如酒店客房的销售从传统的单一店面销售模式走向多营销渠道销售模式提供了强有力支持。本文首先对新技术环境下酒店客房销售模式进行了介绍,主要有实体门店销售、实体店官网销售、实体旅行社及在线旅行社四种模式,并针对不同年龄段顾客就这四种销售方式的选择趋势采用多属性决策方法进行了排序,且对排序结果作了解释。酒店在进行客房预订销售时,可以根据历史入住顾客年龄段分布情况,适时合理调整酒店的营销战略。     

带时间窗的应急救助物资配送车辆路径优化模型研究

在自然灾害突发后,必须将救助物资在规定的时间内运送到受灾点。针对带有时间窗的应急救助物资配送车辆路径优化问题进行研究,建立车辆路径优化模型并运用了蚁群算法进行求解,取得了较好的效果。     

Distributed ARIMA models for ultra-long time series

Providing forecasts for ultra-long time series plays a vital role in various activities, such as investment decisions, industrial production arrangements, and farm management. This paper develops a novel distributed forecasting framework to tackle the challenges of forecasting ultra-long time series using the industry-standard MapReduce framework. The proposed model combination approach retains the local time dependency. It utilizes a straightforward splitting across samples to facilitate distributed forecasting by combining the local estimators of time series models delivered from worker nodes and minimizing a global loss function. Instead of unrealistically assuming the data generating process (DGP) of an ultra-long time series stays invariant, we only make assumptions on the DGP of subseries spanning shorter time periods. We investigate the performance of the proposed approach with AutoRegressive Integrated Moving Average (ARIMA) models using the real data application as well as numerical simulations. Our approach improves forecasting accuracy and computational efficiency in point forecasts and prediction intervals, especially for longer forecast horizons, compared to directly fitting the whole data with ARIMA models. Moreover, we explore some potential factors that may affect the forecasting performance of our approach.     

Filtration enlargement-based time series forecast in view of insider trading

This survey reviews filtration enlargement models in view of insider trading. Although filtration enlargement aptly models insiders' informational advantage, the theoretical results have not attracted the attention of the empiricists, owing mainly to the lack of a bridge transforming the results to testable hypotheses, and/or the absence of econometrics method linking the hypotheses and the data. This survey provides a feasible avenue to estimate insider information and to detect trading from a relatively sophisticated theoretical model, where the dynamics of publicly available data (e.g., stock price) implies insider information before the information is completely digested. We complete the survey with an empirical illustration based on simulated data.     

Towards a real-time prediction of waiting times in emergency departments: A comparative analysis of machine learning techniques

Emergency Departments (EDs) can better manage activities and resources and anticipate overcrowding through accurate estimations of waiting times. However, the complex nature of EDs imposes a challenge on waiting time prediction. In this paper, we test various machine learning techniques, using predictive analytics, applied to two large datasets from real EDs. We evaluate the predictive ability of Lasso, Random Forest, Support Vector Regression, Artificial Neural Network, and the Ensemble Method, using different error metrics and computational times. To improve the prediction accuracy, new queue-based variables, that capture the current state of the ED, are defined as additional predictors. The results show that the Ensemble Method is the most effective at predicting waiting times. In terms of both accuracy and computational efficiency, Random Forest is a reasonable trade-off. The results have significant practical implications for EDs and hospitals, suggesting that a real-time performance monitoring system that supports operational decision-making is possible.     

旅游形象认知的时间顺序对旅游目的地形象认知的影响研究--以银川沙湖与榆林红碱淖为例

旅游者对旅游目的地的形象认知是影响旅游活动的重要因素,对旅游目的地形象定位和市场营销策略的选择都具有重要的参考价值。许多因素对旅游目的地形象认知都产生影响,其中认知的时间特征对旅游目的地形象认知的影响是一个值得关注的新课题:旅游者对不同旅游目的地形象认知的先后顺序对旅游目的地形象认知是否产生影响以及这种影响的程度如何。文章以银川沙湖与榆林红碱淖为例,对旅游者对旅游目的地形象认知中的“先入为主”与“既成事实”效应进行了分析,初步证明旅游者对不同旅游目的地形象感知的先后顺序对旅游目的地形象认知产生影响,并针对案例景区的情况,强调了旅游形象定位与市场营销中的先发优势,提出了自己的观点。     

美国行政中心空间与规模特征及其成因研究

行政中心是行政区划的基本要素之一,行政中心尽量靠近地理中心对行政管理和促进区域发展平衡有积极的理论和现实意义。文章提出了行政中心与地理中心偏差的计算公式,运用空间统计分析方法结合Ar-cGIS软件,以美国为例,分析了美国县治与地理中心地理偏差的空间分布和数据特征以及州府与州最大城市的人口规模关系特征,总结了产生以上特征的自然、历史和政治上的原因,并运用空间可视化方法直观地显示分析结果。分析结果表明：①美国的县治普遍比较接近地理中心,其接近程度有由东部向西部递减的趋势且存在一定的空间集聚;②州府大多数并非州最大城市,人口较少。最后从行政中心区位选择和区域发展平衡两方面得出对中国的启示,为中国行政区划改革和区域经济发展提供借鉴。     

上市公司财务危机实时预警系统研究

我国加入WTO后，在给上市公司带来良好机遇的同时，也使其面临着严峻的挑战。笔者认为建立上市公司财务危机实时预警系统已势在必行。本文首先阐述了上市公司财务危机实时预警的基本前提，接着就如何架构上市公司财务危机实时预警的模式和机制作了探讨，并提出了相关的建议。     

基于JIT方式的中小企业在制品管理问题研究

在制品管理是中小企业生产过程中困扰已久的问题之一,尤其是在多工序、多品种制造业企业中。由于企业产品特征导致在制品管理的难度,JIT方式难以付诸实践。结合JIT思想与ERP系统,实现对在制品的物流与信息流有效控制,对提高生产效率、降低物流成本具有重要的意义。针对中小企业物料管理存在的问题及局限性进行分析,从而提出相关的改进建议。     

区域分工视域下产业协调发展研究——以环首都经济圈为例

从区域产业分工角度出发,明确河北省的产业承接优势是推进环首都经济圈建设的当务之急。文章运用区位熵方法对区域产业的专业化程度进行衡量,并在系统分析产业比较优势基础上,运用区域分工理论探索了产业分布新格局,提出了区域经济协调发展的政策建议,以期实现环首都经济圈内相关产业的健康稳定发展。