How do I get my way? A meta-analytic review of research on influence tactics

Despite considerable research investigating the role of influence tactics on work-related outcomes in organizations, consensus on the effectiveness of influence tactics has been elusive. Specifically, there is a lack of integration concerning the relationships between proactive influence tactics and their outcomes. We investigate the effectiveness of 11 influence tactics from a comprehensive perspective using meta-analytic techniques. In particular, the current study focuses on relationships between each of the 11 influence tactics (i.e., rational persuasion, exchange, inspirational appeal, legitimating, apprising, pressure, collaboration, ingratiation, consultation, personal appeals, and coalition) and task- and relations-oriented outcomes. In addition, we investigate the moderating effects of the direction of influence tactics, measurement of influence tactics, singular influence tactic (versus use of a combination of influence tactics), independence of data sources, and study setting involved in the study. Regardless of task- and relations-oriented outcomes, based on 49 independent samples (N = 8987), our results show positive relationships between outcomes and rational persuasion, inspirational appeal, apprising, collaboration, ingratiation, consultation, and a negative relationship between pressure and outcomes. Rational persuasion is the only tactic which held stable positive relationships with both categories of outcomes regardless of moderating factors. Implications and directions for future research in the area of influence tactics are discussed.     

Statistical estimation of internal available bandwidth

This paper presents a method for using end-to-end available bandwidth measurements in order to estimate available bandwidth on individual internal links. The basic approach is to use a power transform on the observed end-to-end measurements, model the result as a mixture of spatially correlated exponential random variables, carryout estimation by moment methods, then transform back to the original variables to get estimates and confidence intervals for the expected available bandwidth on each link. Because spatial dependence leads to certain parameter confounding, only upper bounds can be found reliably. Simulations with ns2 show that the method can work well and that the assumptions are approximately valid in the examples.     

Bivariate symbolic regression models for interval-valued variables

Interval-valued variables have become very common in data analysis. Up until now, symbolic regression mostly approaches this type of data from an optimization point of view, considering neither the probabilistic aspects of the models nor the nonlinear relationships between the interval response and the interval predictors. In this article, we formulate interval-valued variables as bivariate random vectors and introduce the bivariate symbolic regression model based on the generalized linear models theory which provides much-needed exibility in practice. Important inferential aspects are investigated. Applications to synthetic and real data illustrate the usefulness of the proposed approach.     

Turning Doctoral Students into Faculty in Gerontological Social Work: The AGESW Experience

ABSTRACT

Developing faculty interested in aging may help social work meet the needs of our growing aging population. However, doctoral students need a variety of supports to complete PhDs and become gerontological social work faculty. This study explored one program’s role in supporting the development of social work doctoral students to faculty in gerontology. An e-mail invitation was sent to all former participants (2010–2016 cohorts) of the Association for Gerontology Education in Social Work (AGESW) Pre-Dissertation Fellows Program (PDFP). The 38-question online survey consisted of Likert-type scales, multiple answers, and one open-ended question per section about the program’s impacts on their academic career development in teaching, research, mentoring, and support. Forty-five respondents, representing all six cohorts, completed the survey. More than half reported that the PDFP contributed to their ability to publish their research (64.4%, n = 29), grow their professional network (86.7%, n = 39, and teach (55.5%, n = 25). Doctoral programs provided different experiences than the PDFP, including mentoring, methodological training, professional development, networking, and peer support. Results suggest the PDFP provides content recipients value that supplements instruction received in their institutions. The program’s ability to connect students to each other and to national leaders enhances their career development and socialization into academic roles.     

The Box–Cox Transformation and Non‐Iterative Estimation Methods for Ordinal Log‐Linear Models

Recently Beh and Farver investigated and evaluated three non‐iterative procedures for estimating the linear‐by‐linear parameter of an ordinal log‐linear model. The study demonstrated that these non‐iterative techniques provide estimates that are, for most types of contingency tables, statistically indistinguishable from estimates from Newton's unidimensional algorithm. Here we show how two of these techniques are related using the Box–Cox transformation. We also show that by using this transformation, accurate non‐iterative estimates are achievable even when a contingency table contains sampling zeros.     

BL-GARCH models with elliptical distributed innovations

In this work, we discuss the class of bilinear GARCH (BL-GARCH) models that are capable of capturing simultaneously two key properties of non-linear time series: volatility clustering and leverage effects. It has often been observed that the marginal distributions of such time series have heavy tails; thus we examine the BL-GARCH model in a general setting under some non-normal distributions. We investigate some probabilistic properties of this model and we conduct a Monte Carlo experiment to evaluate the small-sample performance of the maximum likelihood estimation (MLE) methodology for various models. Finally, within-sample estimation properties were studied using S&P 500 daily returns, when the features of interest manifest as volatility clustering and leverage effects. The main results suggest that the Student-t BL-GARCH seems highly appropriate to describe the S&P 500 daily returns.     

Dependency and truncated forms of combinations in multivariate combination-based permutation tests and ordered categorical variables

ABSTRACT

Quite an important problem usually occurs in several multi-dimensional hypotheses testing problems when variables are correlated. In this framework the non-parametric combination (NPC) of a finite number of dependent permutation tests is suitable to cover almost all real situations of practical interest since the dependence relations among partial tests are implicitly captured by the combining procedure itself without the need to specify them [Pesarin F, Salmaso L. Permutation tests for complex data: theory, applications and software. Chichester: Wiley; 2010a]. An open problem related to NPC-based tests is the impact of the dependency structure on combined tests, especially in the presence of categorical variables. This paper’s goal is firstly to investigate the impact of the dependency structure on the possible significance of combined tests in cases of ordered categorical responses using Monte Carlo simulations, then to propose some specific procedures aimed at improving the power of multivariate combination-based permutation tests. The results show that an increasing level of correlation/association among responses negatively affects the power of combination-based multivariate permutation tests. The application of special forms of combination functions based on the truncated product method [Zaykin DV, Zhivotovsky LA, Westfall PH, Weir BS. Truncated product method for combining p-values. Genet Epidemiol. 2002;22:170–185; Dudbridge F, Koeleman BPC. Rank truncated product of p-values, with application to genomewide association scans. Genet Epidemiol. 2003;25:360–366] or on Liptak combination allowed us, using Monte Carlo simulations, to demonstrate the possibility of mitigating the negative effect on power of combination-based multivariate permutation tests produced by an increasing level of correlation/association among responses.     

Introduction: What does the future promise for work,employment and society?

In introducing this double Special Issue, the authors draw on the articles contained therein to highlight the main areas for consideration in research on the future of work. They present the fast‐paced changes affecting the world of work as offering an opportunity to move towards equality‐inducing growth, while warning of the dangers posed by mismanaged technological change, inequalities (highlighting the persistent and intersectional nature of gender inequality), global supply chains and opportunities for social dialogue. In this light, they also propose policy recommendations focusing on strengthening worker protection and representative institutions, rethinking regulatory frameworks and taxation systems, and ensuring just transitions.     

Horses and baseball: social work’s cultivation of one’s ‘third eye’

Active self-reflection is a sophisticated and subtle, multi-layered process that requires learning the capacity to constantly self-monitor. These fundamental interactive skills, the core of a competent social worker, are important to work in any context. Using two distinct metaphors, one relating to horses, the other to baseball, the article will explore the importance of developing competency skills and utilize a ‘third eye.’ In current social work education curricula the use of self may not be prioritized, practiced, or well understood. Evidence from human and veterinary medicine as well as social work, are discussed. An example of an undergraduate BSW course using simulated clients and standardized measures is discussed. The paper includes a brief review of the preliminary findings for a small pilot study and the relevance to future research is considered.     

Do flexible work schedules reduce turnover in U.S. federal agencies?

Agency theory suggests that when agencies adopt flexible work schedules, employees will be more likely to remain with the organization, because these programs demonstrate that the organization cares about their well-being in that flexible work schedules give them more flexibility regarding when, where, and how they perform their work. To test this proposition, cross-sectional panel data at the agency level were obtained from two federal government sources: Federal Employee Viewpoint Survey and FedScope. Furthermore, transfers and quits were the two forms of turnover examined. After lagging the independent variables behind turnover over several years so as to provide a robust test of causality, the results show only limited support for agency theory. Specifically, teleworking was found to lower quits. However, teleworking was not found to reduce transfers or turnover, in general. Furthermore, alternative work schedules were not found to have an impact on quits, transfers, or turnover generally.