The Role of Mere Exposure Effect on Ethical Tolerance: a Two-Study Approach

This paper reports on the results from two studies that were conducted eight years apart with different respondents. The studies examined the role of the Mere Exposure Effect on ethical tolerance or acceptability of particular business decisions. The results from Study 1 show there is a significant difference in ethical judgment for 12 out of 16 vignettes between those who have been exposed to such situations compared to those who have not been exposed to them. In those 12 situations, those who have been exposed to such situations adopted a more tolerant stance toward the ethically questionable behavior. The results from Study 2 show there is a significant difference in ethical judgment for 9 out of 16 vignettes between those who have been exposed to such situations compared to those who have not been exposed to them. Again, in those nine situations, those who have been exposed to such situations adopted a more tolerant stance toward the ethically questionable behavior. Interestingly, the 9 situations in Study 2 were 9 of the 12 situations found to be significant in Study 1, and in the same direction, suggesting that we have found consistency in our findings and support for the Mere Exposure Effect. Implications are provided for both higher education and practitioners.     

Does the sequence of presentations matter for academic conferences? An application of the peak-end rule in event management

Abstract

In psychology, the peak-end rule has been used to describe the effects of emotional factors on live experiences. However, it has yet to be examined in the contexts of events and conferences. This study investigated the influence of conference presentation order, excitement following peak experience, previous conference experience, and time since one’s last visit on conference satisfaction and loyalty. Although no significant differences in satisfaction and loyalty were found with regard to the order of presentations, previous experience and time since last visit were found to have significant effects on attendees’ outcomes. End-of-conference peak experiences exhibited the strongest influence on loyalty.     

基于大数据思维的隧道施工地表沉降预测方法

为研究城市地铁隧道施工引起地表沉降的分布规律,做好预测预控工作,基于大数据分析思维,利用隧道先期掘进段沉降数据资料分析Peck公式的适用性,在适用性得到验证的前提下,建立带有不确定参数的Peck公式的三维空间分布模型,对模型进行不确定参数的函数转换,根据函数转换条件运用最小二乘法对所求的解进行反转换得到确定性参数,代入Peck公式后即可得到完整的隧道施工地表沉降预测模型。以青岛地铁隧道施工的过程监测数据为例,运用上述方法得到的沉降预测模型计算监测点的预测沉降值,运用灰色预测理论中的后验差检验方法对地表沉降预测模型的精度进行检验评定,评定结果显示该模型所得沉降值和实测数据拟合精度合格率为100%,说明该方法所求参数与模型合理可行,可有效预测隧道施工过程中地表沉降值。     

What Are You Saying? Using topic to Detect Financial Misreporting

We use a machine learning technique to assess whether the thematic content of financial statement disclosures (labeled topic) is incrementally informative in predicting intentional misreporting. Using a Bayesian topic modeling algorithm, we determine and empirically quantify the topic content of a large collection of 10-K narratives spanning 1994 to 2012. We find that the algorithm produces a valid set of semantically meaningful topics that predict financial misreporting, based on samples of Securities and Exchange Commission (SEC) enforcement actions (Accounting and Auditing Enforcement Releases [AAERs]) and irregularities identified from financial restatements and 10-K filing amendments. Our out-of-sample tests indicate that topic significantly improves the detection of financial misreporting by as much as 59% when added to models based on commonly used financial and textual style variables. Furthermore, models that incorporate topic significantly outperform traditional models when detecting serious revenue recognition and core expense errors. Taken together, our results suggest that the topics discussed in annual report filings and the attention devoted to each topic are useful signals in detecting financial misreporting.     

一种并行化的改进型灰狼分簇算法

针对传统的分簇算法在解决超大规模数据集的分簇问题上不具有高效的时间和空间复杂度且易于陷入局部最优的问题，提出了改进型灰狼分簇算法（Improved Gray Wolf Clustering Algorithm，IGWCA），将灰狼行为规则与灰狼狩猎策略相融合，同时引入狄利克雷分布（Dirichlet Distribution）实现先验，在基准数据集上完成IGWCA与其他分簇算法的对比分析。实验结果表明IGWCA不仅具有较强的探索和开发能力，还具有较小的分散度。使用Hadoop框架的MapReduce模型实现IGWCA的并行化（IGWCA on MapReduce，IGWCA-MR），通过F-Measure和平均运行时间验证IGWCA-MR的分簇质量，并在真实数据集上验证了IGWCA-MR的运行时间和加速性能。实验结果证明，IGWCA-MR可以有效解决超大规模数据集的分簇问题，是一种高效的替代算法。     

Forecasting multiparty by-elections using Dirichlet regression

By-elections, or special elections, play an important role in many democracies – but whilst there are multiple forecasting models for national elections, there are no such models for multiparty by-elections. Multiparty by-elections present particular analytic problems related to the compositional character of the data and structural zeros where parties fail to stand. I model party vote shares using Dirichlet regression, a technique suited for compositional data analysis. After identifying predictor variables from a broader set of candidate variables, I estimate a Dirichlet regression model using data from all post-war by-elections in the UK (n=468). The cross-validated error of the model is comparable to the error of costly and infrequent by-election polls (MAE: 4.0 compared to 3.6 for polls). The steps taken in the analysis are in principle applicable to any system that uses by-elections to fill legislative vacancies.     

Prior investment outcomes and stock investment in defined contribution plans

In this study, we employ the 2001–2013 Survey of Consumer Finances to examine how prior investment outcomes affect portfolio allocation in defined contribution (DC) plans. Results show that investors with prior gains are more likely to invest all DC plan assets in stocks. Factors such as risk tolerance and investment horizon positively affect investors’ tendency to allocate all DC assets to stocks. These findings have important implications for investors, researchers and financial professionals.     

品牌关系质量与消费者遭遇产品伤害的反应特征研究——基于事前信念的视角

消费者对品牌的事前信念主观地影响着其对品牌危机事件的认知和判断。本文采用实验研究方法,将品牌关系质量设为品牌事前信念,研究在不同品牌关系质量下,消费者对产品伤害事件的反应特征及差异。研究结果显示,消费者在遭遇产品伤害后更加关注产品伤害事件的责任归属问题,而对事件发生企业的内部管理问题的关注程度相对较低。结论揭示出高品牌关系质量对偶然发生伤害事件的企业品牌起到暂时保护作用,低品牌关系质量会扩大企业品牌在伤害事件后的负面市场效应,有助于企业了解消费者的危机反应特征,为企业采取恰当的品牌危机管理策略提供指导。     

创业者先前经验、学习模式与新技术企业绩效—基于初始条件视角的实证研究

创业者先前经验是影响新技术企业绩效的重要初始条件.文章为此以科技企业孵化器在孵企业为样本,以创业学习模式为中介变量研究了创业者先前经验对新技术企业绩效的作用路径.结果表明,行业经验和创业经验对开发性学习具有显著正向影响,对探索性学习具有显著负向影响;职能经验对两种创业学习模式没有显著影响.开发性学习对新企业生存绩效和成长绩效具有显著正向影响;探索性学习对新企业生存绩效具有显著负向影响,对成长绩效没有显著影响.创业学习模式在创业者先前经验与新技术企业绩效间起到部分中介作用.