Factors affecting couples' decisions to jointly shop

This paper explores the factors that influence individuals' decisions to jointly shop. Drawing from qualitative interviews and relevant theories, the researchers present a model of couple's likelihood of joint shopping. The model includes utilitarian motives (product purchase relevance and perceived financial risk), hedonic motives (expected shopping pleasure with one's partner), and a situational motive (time availability), along with two moderators (gender and relationship length). Online survey respondents answer questions relative to an experimental scenario involving the purchase of furniture or electronics. Results indicate that while all variables studied are influential, expected shopping pleasure and relevance of the purchase to both parties are the most influential aspects in the decision to shop together. Additionally, for males perceived financial risk has a stronger effect on their decision to jointly shop than it does for females.     

What Drives Household Choice of Organic Products in Grocery Stores?

This paper studies how households choose organic products on a given store visit. We develop a three-stage purchase incidence/brand choice/purchase quantity model for organic products. Shared random effects parameters link the three stages of the model. We empirically quantify the effects of category variables, marketing mix, and demographic variables on the purchase of organic products using a unique household panel dataset that includes actual organic purchase data from two markets, by over 4,500 households in 25 stores for the period between January 2004 and June 2009. First, we find that the purchase of organic products is greater among the high income, college educated, and older families as well as among consumers holding high-level occupations. Second, households tend not to purchase organic products when buying in concentrated categories. Third, on average, households tend to buy organic store brands more than the organic national brands. Promotions of organic brands (feature ad and display) are less likely to drive households to buy organic brands and so does the organic brand's distribution breadth. Finally, price has an inverted U-shaped effect. We discuss the implications of these results for retailers, manufacturers and researchers.     

Empathy as added value in predicting donation behavior

Past behavior and socio-demographics represent traditional predictors of charitable giving. The present study examines, in a real fundraising setting, whether measures of empathy (i.e., empathic concern and personal distress) can improve these predictions. The findings confirm the relevance of traditional predictor sets and the added value of including measures of empathy. Empathic concern positively affects the donation decision. In addition, empathy negatively affects the donor's generosity toward one charity. However, for people with high empathic concern, considering only generosity toward one charity could be misleading because such people are more likely to donate to different charities. This result has implications for overall generosity. Therefore, a clear distinction between both personality traits is necessary.     

Driving factors of post adoption behavior in mobile data services

Although research interest in post adoption behavior of ICT (Information and Communication Technology) users increases from year to year, few studies examine how motivational factors and service type influence post adoption behavior. This study investigates the antecedents of post adoption behavior in the Mobile Data Services (MDS) domain. The study conducted a nationwide online survey in Korea to verify the proposed research model that includes motivational factors and service type. Two extrinsic motivation factors (post usefulness and post monetary value) and two intrinsic motivation factors (post ease of use and post enjoyment) are the main components of the motivational factors. The results of the study reveal that the motivational factors and service type influence the post adopter type in the MDS context. The findings of this study help provide guidelines for MDS providers to select a target market and to devise a strategy that meets the stated objectives of the selected market.     

能源消费对经济增长影响研究-基于河南省1978～2008年时间序列数据的实证分析

运用计量经济学中的回归分析理论,基于河南省1978—2008年时间序列数据对能源消费对经济增长的影响进行实证研究。研究结果表明：河南省能源消费对经济增长的影响是显著的,能源消费增加1个百分点,GDP能增加2．006173个百分点。     

信用评级的新方法——多元自适应回归样条在民营企业信用评级中的应用

通过建立多元自适应回归样条模型,对民营企业是否违约进行两等级划分,结果表明总体正确率达95.9%,对第二类错误的判别正确率达80%,均高于多元判别分析模型和Logistic回归模型。因此可以证明,多元自适应回归样条模型应用于判别民营企业的信用等级具有较好的实践价值。     

Diagnostics analysis for log‐Birnbaum–Saunders regression models with censored data

This article develops influence diagnostics for log‐Birnbaum–Saunders (LBS) regression models with censored data based on case‐deletion model (CDM). The one‐step approximations of the estimates in CDM are given and case‐deletion measures are obtained. Meanwhile, it is shown that CDM is equivalent to mean shift outlier model (MSOM) in LBS regression models and an outlier test is presented based on MSOM. Furthermore, we discuss a score test for homogeneity of shape parameter in LBS regression models. Two numerical examples are given to illustrate our methodology and the properties of score test statistic are investigated through Monte Carlo simulations under different censoring percentages.     

我国林业行业资本结构优化研究

以我国林业行业的上市企业为对象,运用多元回归分析法,实证研究了林业企业的盈利能力、抵押能力、非债务税盾、有形资产、现金流量、股权结构、税收、资产流动性、企业规模、行业特征和企业成长性等11个因素与资本结构之间的关系,发现了有形资产、企业规模和资产流动性是影响林业行业资本结构的主要因素,同时,通过对林业行业资本结构的进一步优化研究,得到了林业行业资本结构的优化值。     

基于MR和TSA的成品油价格模型

通过对影响成品油价格的众多因素进行数据整理分析,首先建立了多元回归模型对其数据进行预测;然后建立了二次移动平均预测模型、三次指数平滑预测模型对其进行时间序列分析预测。综合三种方法对近15个时间片的油价预测值与统计值进行比较与误差分析,仿真结果表明,多元回归模型和时间序列分析的三次指数平滑预测达到了较好的效果。     

我国民用汽车拥有水平影响因素分析-多元二次回归法

准确预测未来汽车保有量,对产业调整、城市基建、车市调控和能源、环保策略等具有重要意思。根据主要省份的相关统计数据,采用各地区横向比较法分析人均GDP、基尼系数、公共交通、汽车成本对汽车拥有水平的影响,并以江西省为例,通过多元二次回归分析建立了基于人均GDP、汽车成本和城市万人拥有公交车数的民用汽车保有量预测模型,并对未来10年汽车拥有水平走势进行预测。