Mobile diaries – Benchmark against metered measurements: An empirical investigation

Researchers seeking to study the relationships between consumers' communications, attitudes, and behaviors could benefit from monitoring consumers over time, across multiple locations and channels, and in a way that reflects consumers' subjective perceptions. Diaries on smartphones (mobile diaries) can be used as a research tool for such purposes. A mobile diary is a self-report instrument whereby people use their mobile handset to repeatedly report experiences of interest. Mobile diaries are increasingly used in psychology, geography, medicine, and commercial marketing. Yet they have rarely been used for quantitative marketing research, and were not benchmarked against best-practice metrics in marketing.In this study, we aim to set the ground for using mobile diaries in quantitative marketing research. We first lay out the theoretical infrastructure for the usage of mobile diaries, and describe possible respondent reporting concerns, including concerns related to non-reporting, reporting over time, and concerns stemming from individual-level heterogeneity.We demonstrate the potential of mobile diaries, as well as the importance of the various concerns, using a benchmark test case in the context of primetime TV viewing. Our benchmark uses a sample of respondents with both mobile diary viewing reports and Nielsen People Meter (NPM) records. Our analysis reveals that averaging across all conditions, 47.4%–64.7% of the NPM records are reported by the diary. The major sources for mismatch are random time periods without alarms, short viewings, and periodic reporting inactivity (pulsing). Concerns such as a decrease in reporting rates over time (e.g., fatigue), smartphone ownership, and demographic variation across individuals have relatively small effects on reporting likelihood. Analyzing the cases in which diary reports do not have a matching NPM record, we find many of them can be attributed to out-of-home viewing and viewing on non-metered devices. This finding demonstrates how mobile diaries can complement metered measurements. Overall, aggregate diary-based ratings have a 0.90 correlation with NPM ratings.We discuss implications for designing and using mobile diary studies in marketing.     

Demystifying residents' walking behaviors: Active transport in South East Queensland,Australia

This study investigates the correlates of a resident's walking behaviors and aims to shed light on mechanisms through which walking may be encouraged. The results of this investigation paint a complex and nuanced picture of the residents’ walking behaviors in South East Queensland, Australia. The results suggest that sociodemographic characteristics separately may contribute greatly to whether or not one engages in walking behaviors. Further, cumulatively these differences might be greater for some groups of residents compared to others. One of the most prominent findings of the study is that the purpose, the characteristics of the origin, and the characteristics of the destination of a trip tended to be similar in the heterogeneity they exhibit over the distribution of time spent walking. For example, pick something up, undertake work, or engage in personal business, move to or from a workplace, shop, or social place are activities that tend to be associated with walking as a main mode of transport and a higher number of walking episodes. However, these trips tended to be short.     

What do professional forecasters actually predict?

This paper studies what professional forecasters predict. We use spectral analysis and state space modeling to decompose economic time series into trend, business cycle, and irregular components. We examine which components are captured by professional forecasters by regressing their forecasts on the estimated components extracted from both the spectral analysis and the state space model. For both decomposition methods, we find that, in the short run, the Survey of Professional Forecasters can predict almost all of the variation in the time series due to the trend and the business cycle, but that the forecasts contain little or no significant information about the variation in the irregular component.     

Five dimensions of the uncertainty–disagreement linkage

We analyze the relationship between forecaster disagreement and macroeconomic uncertainty in the Euro area using data from the European Central Bank’s Survey of Professional Forecasters for the period 1999Q1–2018Q4 and find that disagreement is generally a poor proxy for uncertainty. However, the strength of this link varies with the dispersion statistic employed, the choice of either the point forecasts or the histogram means for calculating disagreement, the outcome variable considered and the forecast horizon. In contrast, distributional assumptions do not appear to be very influential. The relationship is weaker in subsamples before and after the outbreak of the Great Recession. Accounting for the forecasters’ entry to and exit from the survey has little impact on the results. We also show that survey-based uncertainty is associated with overall policy uncertainty, whereas forecaster disagreement is related more closely to the expected fluctuations on financial markets.     

Business values dimensions: A cross-culturally developed measure of workforce values

Using a stratified random sample drawn from 11,709 business professionals’ survey responses across 26 societies, we investigated and failed to find support for the construct validity of the Schwartz Values Survey’s (SVS) a priori 10-factor circumplex model of human values, originally developed from student and teacher responses. Subsequent exploratory factor analysis estimated an initial five-factor solution, the Business Value Dimensions (BVD) model. In turn, CFA supported the cross-cultural validity of this alternative configuration of values for business professionals. Internal consistency reliabilities for these five values factors are reported for the 26 societies plus an additional 25 societies that did not meet sample size criteria to be included in the analyses. As a result, findings are provided for a total of 51 societies (14,724 business professionals). We present the five-factor BVD model for use in future international research with business professional populations.     

Does tourism really cause stress? A natural experiment utilizing ArcGIS Survey123

ABSTRACT

Tourism related stress has recently been revealed as an issue for tourism host community residents. Prior studies have relied on directly asking residents if tourism caused them stress, resulting in possible participant priming. This study utilized the ArcGIS Survey123 app to collect data on resident stress from a community with high levels of tourism visitation and a community with low levels of tourism visitation. During the study, researchers never mentioned tourism. Half of study participants in the community with high tourism visitation discussed tourism directly as a stressor, accounting for almost 5% of all stressful experiences, while no participants in the community with low tourism visitation mentioned tourism as a stressor. Geospatial data revealed that tourism related stressors occurred outside of the ‘tourism zone’ in the community with high tourism visitation, and tourism related stressors mirrored perceived tourism impacts measured in a post experiment survey of study participants.     

PITFALLS IN CROSS‐SECTION STUDIES WITH INTEGRATED REGRESSORS: A SURVEY AND NEW DEVELOPMENTS

In cross‐section studies, if the dependent variable is I(0) but the regressor is I(1), the true slope must be zero in the resulting “unbalanced regression.” A spuriously significant relationship may be found in large cross‐sections, however, if the integrated regressor is related to a stationary variable that enters the DGP but is omitted from the regression. The solution is to search for the related stationary variable, in some cases the first difference of the integrated regressor, in other cases, a categorical variable that can take on limited number of values which depend on the integrated variable. We present an extensive survey, new developments, and applications particularly in finance.     

How reliable and consistent are subjective measures of welfare in Europe and Central Asia?

This paper analyses the reliability and consistency of subjective well‐being measures, using the Life in Transition Survey. Drawing on two life satisfaction questions with alternative scales, our results do not reveal substantial biases in accounts of life satisfaction due to framing. Subjective individual assessments of household relative income position, on the other hand, do not appear to be reliable predictors of objective poverty or wealth. We find that subjective relative income position is only weakly correlated with objective welfare measures. There are differences in evaluations of the household's relative standing across different household members, and these differences are correlated with respondent characteristics.     

Professional forecasters and real-time forecasting with a DSGE model

This paper analyses the real-time forecasting performance of the New Keynesian DSGE model of Galí, Smets and Wouters (2012), estimated on euro area data. It investigates the extent to which the inclusion of forecasts of inflation, GDP growth and unemployment by professional forecasters improve the forecasting performance. We consider two approaches for conditioning on such information. Under the “noise” approach, the mean professional forecasts are assumed to be noisy indicators of the rational expectations forecasts implied by the DSGE model. Under the “news” approach, it is assumed that the forecasts reveal the presence of expected future structural shocks in line with those estimated in the past. The forecasts of the DSGE model are compared with those from a Bayesian VAR model, an AR(1) model, a sample mean and a random walk.     

霍夫斯坦特国家文化模型与世界价值观调查的比较研究

本文通过对世界价值观调查的研究评介,与霍夫斯坦特国家文化模型进行对比,回顾了二十年来运用世界价值观调查进行研究取得的部分成果,对其研究方法作以探索,以期对未来跨文化比较管理的研究起到借鉴作用。