Evaluating,Comparing, Monitoring,and Improving Representativeness of Survey Response Through R‐Indicators and Partial R‐Indicators

Non‐response is a common source of error in many surveys. Because surveys often are costly instruments, quality‐cost trade‐offs play a continuing role in the design and analysis of surveys. The advances of telephone, computers, and Internet all had and still have considerable impact on the design of surveys. Recently, a strong focus on methods for survey data collection monitoring and tailoring has emerged as a new paradigm to efficiently reduce non‐response error. Paradata and adaptive survey designs are key words in these new developments. Prerequisites to evaluating, comparing, monitoring, and improving quality of survey response are a conceptual framework for representative survey response, indicators to measure deviations thereof, and indicators to identify subpopulations that need increased effort. In this paper, we present an overview of representativeness indicators or R‐indicators that are fit for these purposes. We give several examples and provide guidelines for their use in practice.     

Selecting Adaptive Survey Design Strata with Partial R‐indicators

Recent survey literature shows an increasing interest in survey designs that adapt data collection to characteristics of the survey target population. Given a specified quality objective function, the designs attempt to find an optimal balance between quality and costs. Finding the optimal balance may not be straightforward as corresponding optimisation problems are often highly non‐linear and non‐convex. In this paper, we discuss how to choose strata in such designs and how to allocate these strata in a sequential design with two phases. We use partial R‐indicators to build profiles of the data units where more or less attention is required in the data collection. In allocating cases, we look at two extremes: surveys that are run only once, or infrequent, and surveys that are run continuously. We demonstrate the impact of the sample size in a simulation study and provide an application to a real survey, the Dutch Crime Victimisation Survey.     

Panel design effects on response rates and response quality

To understand changes in individuals' opinions and attitudes, it would be best to collect data through panels. Such panels, however, often cause irritation among respondents, resulting in low response rates and low response quality. We address whether this problem can be alleviated by designing a panel survey in an alternative way. For this purpose, we perform two field studies where we measure the effects of several panel design characteristics on response rates and response quality. These characteristics include the number of waves and the time between subsequent waves, which may be either fixed or random. Our findings suggest that response rates and response quality can be improved significantly by surveying at random time intervals. It is then crucial that panel members are not informed about the dates they will be surveyed, because in this case, respondents are less likely to develop expectations as to when they will be surveyed again. The methodology we put forward can be used to improve the efficiency of a panel study by carefully calibrating the studies' panel design parameters.     

COMBINING REVEALED AND STATED PREFERENCE DATA TO ESTIMATE THE NONMARKET VALUE OF ECOLOGICAL SERVICES: AN ASSESSMENT OF THE STATE OF THE SCIENCE

Abstract This paper reviews the marketing, transportation and environmental economics literature on the joint estimation of revealed preference (RP) and stated preference (SP) data. The RP and SP approaches are first described with a focus on the strengths and weaknesses of each. Recognizing these strengths and weaknesses, the potential gains from combining data are described. A classification system for combined data that emphasizes the type of data combination and the econometric models used is proposed. A methodological review of the literature is pursued based on this classification system. Examples from the environmental economics literature are highlighted. A discussion of the advantages and disadvantages of each type of jointly estimated model is then presented. Suggestions for future research, in particular opportunities for application of these models to environmental quality valuation, are presented.     

Applications of calendar instruments in social surveys: a review

Retrospective reports in survey interviews and questionnaires are subject to many types of recall error, which affect completeness, consistency, and dating accuracy. Concerns about this problem have led to the development of so-called calendar instruments, or timeline techniques. These aided recall procedures have been designed to help respondents gain better access to long-term memory by providing a graphical time frame in which life history information can be represented. In order to obtain more insights into the potential benefits of calendar methodology, this paper presents a review of the application of calendar instruments, their design characteristics and effects on data quality. Calendar techniques are currently used in a variety of fields, including life course research, epidemiology and family planning studies. Despite the growing interest in these new methods, their application often lacks sufficient theoretical foundation and little attention has been paid to their effectiveness. Several recent studies however, have demonstrated that in comparison to more traditional survey methods, calendar techniques can improve some aspects of data quality. While calendar instruments have been shown to be potentially beneficial to retrospective data quality, there is an apparent need for methodological research that generates more systematic knowledge about their application in social surveys.     

内部控制质量与权益资本成本关系研究述评与展望

近年来,内部控制质量对公司权益资本成本的影响关系逐渐成为了学者们关注的焦点问题。本文对国内外现有的相关研究文献进行了有机梳理,分别从直接作用路径和间接作用路径两个角度介绍了内部控制质量影响公司权益资本成本的作用机理及其相关的经验证据,并对现有研究成果进行了系统而简要的述评与总结。最后,针对现有研究的不足和存在的问题,本文对未来的研究方向进行了展望。     

ECONOMIC EXPERIMENTS,HYPOTHETICAL SURVEYS AND MARKET DATA STUDIES OF INSURANCE DEMAND AGAINST LOW‐PROBABILITY/HIGH‐IMPACT RISKS: A SYSTEMATIC REVIEW OF DESIGNS,THEORETICAL INSIGHTS AND DETERMINANTS OF DEMAND

This paper provides a systematic review of the literature on 80 experimental, hypothetical survey and market data studies of insurance demand against low‐probability/high‐impact risks. The objective of the review is to extract lessons from these studies and to outline an agenda for future research. We contrast the results of experimental and survey studies to findings from market data. We focus on experimental design methods, insurance characteristics, as well as results about theories, heuristics, behavioural biases and explanatory variables. Lessons for policymakers are drawn which can facilitate disaster preparedness.     

Manager impacts on worker performance in American football: Do offensive coordinators impact quarterback performance in the National Football League?

Ample research in nonsports labor markets suggests that managerial quality significantly impacts worker productivity; however, studies using sports data have been less likely to find such evidence supporting the importance of managers/coaches. We examine the impact of offensive coordinators on quarterback performance in football. While we find that various offensive coordinator characteristics have little impact on quarterback performance, we show that individual offensive coordinators do seem to play a role in quarterback development. Consistent with research on manager effects outside of sports, this suggests that elite and poor offensive coordinators do significantly impact the productivity of the quarterbacks they manage.     

大学生艾滋病预防教育情况研究报告

本报告针对大学生艾滋病预防教育问题,以问卷调查的定量分析、卷宗整理的定性剖析和文献资料的索引为主要方法,在对问卷、卷宗进行统计分析和对文献资料进行整理汇总的基础上,运用社会学、教育学、心理学等多学科理论进行分析研究.     

Toward a more complete understanding of offshoring: bringing employees into the conversation

The rapid increase in the practice of offshoring over the past decade has generated considerable debate about the consequences of this trend for the economy and for labor. A burgeoning literature examines a variety of issues related to offshoring; however, the majority have focused primarily on macro-level issues such as why organizations decide to offshore or why some ventures succeed and some fail. Very little research has examined the impact of exporting work on the attitudes and behaviors of employees in the destination country who are performing the work. We seek to address this gap in the literature by identifying the distinguishing characteristics of the offshore work environment and developing a theoretical framework for understanding destination workers' experiences and responses in this environment. Drawing on social identity theory and related research, we develop a multilevel model for explaining the antecedents and consequences of the identity conflicts that often arise among destination workers employed in voice-based service work.     

吉林旅游地域文化特征对旅游工艺品设计的影响

对旅游地域文化特征的研究,有助于旅游工艺品设计开发和提升旅游工艺品质量,是旅游工艺品有序开发、深度加工及体现品质特色、文化内涵的有效途径。本文结合吉林省旅游业的现状重点分析了旅游地域文化特征,并对吉林旅游工艺品现状及存在的问题进行了深入解析,阐述了旅游地域文化特征对旅游工艺品设计的影响,突显了旅游工艺品的文化价值和设计价值。     

我国煤炭物流研究综述

文中采用时间趋势分析和分类研究两种方法,对近年来我国学者在煤炭物流领域的研究进行总结和分析。文中主要回顾煤炭物流的相关文献,讨论目前的进展。     

On scales and decision-making based on arithmetic mean

The scales used in schools for the purpose of student assessment are ordinal. The average of ordinal values is often used for the evaluation and comparison of overall student performance. We demonstrate a theorem for the selection of scales invariant with respect to rank of average and compare scales according to this property. A uniformity criterion is also defined for the choice of the scale on which to calculate the average. Concatenated sets of grades from scales not belonging to the same category may bring about errors of rank and absurd averaging, which may have a heavy impact on related decision-making processes.     

Unlocking the potential of advanced manufacturing technologies

This research examines whether investments in advanced manufacturing technologies (AMTs) such as flexible manufacturing systems (FMS), computer aided design (CAD), computer aided manufacturing (CAM), robotics, etc., are more likely to lead to improved performance if they are supported by improvements in the manufacturing infrastructure of the company. This question is evaluated using data gathered from 202 manufacturing plants chosen from industries generally considered to have relatively high investments in technology.Multiple item scales are developed and adapted from sources in the literature to measure investments in technology, infrastructure, and the performance of the plant. Evidence supporting the reliability and validity of these scales is provided. Hierarchical regression is used to analyze the relationship between technology, infrastructure, and performance. The results suggest that there is an important interaction between the adoption of advanced manufacturing technologies and investments in infrastructure. Firms that invest in both AMTs and infrastructure perform better than firms which only invest in one or the other. Separate analyses on sub-samples of firms with the highest and lowest investments in AMTs show that infrastructural investments have a stronger relationship with performance in the high investment group. Thus, the data indicate that infrastructural investments provide a key to unlocking the potential of advanced manufacturing technologies.     

Factor extraction using Kalman filter and smoothing: This is not just another survey

Dynamic factor models have been the main “big data” tool used by empirical macroeconomists during the last 30 years. In this context, Kalman filter and smoothing (KFS) procedures can cope with missing data, mixed frequency data, time-varying parameters, non-linearities, non-stationarity, and many other characteristics often observed in real systems of economic variables. The main contribution of this paper is to provide a comprehensive updated summary of the literature on latent common factors extracted using KFS procedures in the context of dynamic factor models, pointing out their potential limitations. Signal extraction and parameter estimation issues are separately analyzed. Identification issues are also tackled in both stationary and non-stationary models. Finally, empirical applications are surveyed in both cases. This survey is relevant to researchers and practitioners interested not only in the theory of KFS procedures for factor extraction in dynamic factor models but also in their empirical application in macroeconomics and finance.     

The use of quasi-experiments in the social sciences: a content analysis

This article examines the use of various research designs in the social sciences as well as the choices that are made when a quasi-experimental design is used. A content analysis was carried out on articles published in 18 social science journals with various impact factors. The presence of quasi-experimental studies was investigated as well as choices in the design and analysis stage. It was found that quasi-experimental designs are not very often used in the inspected journals, and when they are applied they are not very well designed and analyzed. These findings suggest that the literature on how to deal with selection bias has not yet found its way to the practice of the applied researcher.     

XX民宿财务风险分析与评价研究

论文聚焦民宿与民宿财务风险之间的关系,以XX民宿为研究对象,以问卷形式进行调查研究。研究结果表明:第一,民宿边缘创新规模对投资风险有负向影响;第二,民宿融资渠道规模对筹资风险有负向影响;第三,民宿财务人员素质的高低对资金回收风险有负向影响;第四,民宿商业模式对筹资风险没有明显的影响。     

中国城市社区公共服务研究述评

在综合分析大量有关城市社区公共服务文献的基础上,对城市社区公共服务的概念、类型、存在问题及解决对策、社区公共服务模式等方面进行了回顾和总结。大量研究表明,目前我国城市社区公共服务的研究还停留在解释其内涵、外延、分类、个案等基本问题上,研究细节有余而整体不足,至今还停留在初步学理探讨阶段。最后,在分析比较的基础上对其进行简要述评,其目的在于为进一步研究城市社区公共服务理论指明方向,也为我国城市社区公共服务实践部门提供决策依据。     

顾客参与对行为意向的影响研究

本文基于顾客参与理论及相关研究文献,以美发业为分析单位,建立顾客参与对行为意向影响的关系模型,在问卷调查的基础上得出数据,并运用SPSS15．0和LISREL软件进行结构方程模型等分析以验证假设检验。实证分析结果表明：顾客参与的信息分享维度对服务质量和行为意向的影响不显著;顾客参与的责任行为维度对服务质量和行为意向分别产生正向显著影响;顾客参与的人际互动维度对服务质量产生直接影响,并以服务质量为中介变量影响行为意向。因此,建议服务企业鼓励顾客参与服务传递过程、加强关系营销并不断提高服务质量。