Managerial Responses to Online Reviews: A Text Analytics Approach

This study tests the effects of online managerial responses and returning customers’ future satisfaction (measured as review ratings) by performing social media text analytics on a hotel sample. Essentially, this paper provides insight into meaningful differences in future ratings between responding and non‐responding hotels, as well as differences in response styles between ratings improvement and non‐improvement. The results indicate that: (1) subsequent ratings are higher if customers receive responses to their previous online reviews; (2) increase in ratings is more significant among low‐satisfaction customers, and a decrease in ratings is mitigated if responses are provided; (3) responding to loyal customers – those who have visited and rated the same hotel more than three times – has a limited impact on ratings; (4) responses are longer and sentiment is slightly lower in scenarios where subsequent ratings are improved, but there is no significant difference in the effect of response speed between the two groups; (5) changes in ratings also affect styles of responding to current reviews – if customer satisfaction has improved, response length tends to be shorter and sentiment level tends to be higher. The findings offer both theoretical and managerial implications by demonstrating the utility of social media text analytics.     

Big Data‐Savvy Teams’ Skills,Big Data‐Driven Actions and Business Performance

Prior studies on big data analytics have emphasized the importance of specific big data skills and capabilities for organizational success; however, they have largely neglected to investigate the use of cross‐functional teams’ skills and links to the role played by relevant data‐driven actions and business performance. Drawing on the resource‐based view (RBV) of the firm and on unique data collected from 240 big data experts working in global agrifood networks, we examine the links between the use of big data‐savvy (BDS) teams’ skills, big data‐driven (BDD) actions and business performance. BDS teams depend on multi‐disciplinary skills (e.g. computing, mathematics, statistics, machine learning and business domain knowledge) that help them turn their traditional business operations into modern data‐driven insights (e.g. knowing real‐time price changes and customer preferences), leading to BDD actions that enhance business performance. Our results, raised from structural equation modelling, indicate that BDS teams’ skills that produce valuable insights are the key determinants for BDD actions, which ultimately contribute to business performance. We further demonstrate that those organizations that emphasize BDD actions perform better compared to those that do not focus on such applications and relevant insights.     

Why bother to ‘downshift’? The characteristics and satisfaction of downshifters in the Brisbane-South East Queensland region,Australia

Using the data collected as part of a Quality of Life (QoL) survey in the Brisbane-South East Queensland region (SEQ) of Australia, this paper examines differences in satisfaction levels between downshifters and non-downshifters, and identifies socio-economic predictors of the downshifting phenomenon. Almost 30% of survey respondents are classified as downshifters. Multivariate Analysis of Covariance reveals significant differences between downshifters and non-downshifters in a number of life-satisfaction domains, although the degree to which they were satisfied with their life before downshifting is unknown. Analysis of Covariance shows that downshifters reported a significantly lower level of satisfaction than non-downshifters, especially with respect to satisfaction with the amount of money available to them, independence or freedom, and employment. Multivariate logistic regression analysis reveals that post-secondary education and employment were positively associated with downshifting, while age was significantly associated with downshifting. It is argued that if downshifting is associated with lower levels of satisfaction, intervention may be required to initiate programs to engage downshifters more fully in the workforce by facilitating more flexible work arrangements and an improved working environment.     

Designing of a control chart using belief statistic for exponential distribution

A new control chart is proposed by using the belief statistic for the exponential distribution. The structure of the proposed control chart is given to measure the average run length for the shifted process. The comparison of the proposed chart is given with the existing charts in terms of the average run lengths, which shows the outperformance of the proposed chart. The performance of the proposed control chart is also discussed with the help of simulated data.     

Testing equality of two intercepts for the parallel regression model with non sample prior information

This paper proposes tests for equality of intercepts of two simple regression models when non sample prior information is available on the equality of two slopes. For three different scenarios on the values of the slope, namely (i) unknown (unspecified), (ii) known (specified), and (iii) suspected, we derive the unrestricted test (UT), restricted test (RT), and pre-test test (PTT) for testing the equality of intercepts. The test statistics, their sampling distributions, and power functions of the tests are obtained. Comparison of power function and size of the tests reveals that the PTT has a reasonable dominance over the UT and RT.     

Perturbed robust linear estimating equations for confidentiality protection in remote analysis

National statistical agencies and other data custodians collect and hold a vast amount of survey and census data, containing information vital for research and policy analysis. However, the problem of allowing analysis of these data, while protecting respondent confidentiality, has proved challenging to address. In this paper we will focus on the remote analysis approach, under which a confidential dataset is held in a secure environment under the direct control of the data custodian agency. A computer system within the secure environment accepts a query from an analyst, runs it on the data, then returns the results to the analyst. In particular, the analyst does not have direct access to the data at all, and cannot view any microdata records. We further focus on the fitting of linear regression models to confidential data in the presence of outliers and influential points, such as are often present in business data. We propose a new method for protecting confidentiality in linear regression via a remote analysis system, that provides additional confidentiality protection for outliers and influential points in the data. The method we describe in this paper was designed for the prototype DataAnalyser system developed by the Australian Bureau of Statistics, however the method would be suitable for similar remote analysis systems.     

Understanding the Financial Knowledge Gap: A New Dimension of Inequality in Later Life

ABSTRACT

To understand individuals’ financial behaviors, it is important to understand the financial knowledge gap – the distance between one’s objective and subjective financial knowledge. Overestimating one’s financial knowledge can lead to risky financial behaviors. To date, limited empirical work has examined how financial knowledge gap varies across age groups. We analyze the size and nature of the financial knowledge gap and its variation across age groups. Using nationally representative data, we find robust evidence that older adults overestimate their financial knowledge. Social workers can assess the financial knowledge gap and educate their clients to protect from financial fraud, exploitation, and abuse.     

Factors related to the intention to have additional children in the United States: A reanalysis of data from the 1965 and 1970 national fertility studies

Reproductive intentions of white mothers with no more than three children in 1965 and in 1970 were analyzed for their stability and change with respect to such factors as parity, age of the youngest child, wife’s employment, and husband’s education. Parity and age of the youngest child were found to have a much more important effect on the intent to have additional children than were such socioeconomic variables as wife’s employment and husband’s education. Parity and the interval since the latest birth (or the age of the youngest child) were found to have a nonlinear effect and to interact in affecting the reproductive intention. This suggests a convergence to a twochild family as the threshold size and that the length of childspacing is contingent on the parity. Change during 1965–1970 in this direction was found to be greater among mothers with husbands having college or higher educations.