Digital internal communication: An interplay of socio-technical elements

Digital transformation has become a research focus in recent years. Likewise, internal communication (IC) is one of the fastest-growing specialisations in public relations and communication management. This research explores digital internal communication (DIC) at the nexus between digital transformation and IC. We provide an integrative review of the literature; our thematic analysis of selected journal articles and other scholarly texts is guided by the concept of organisations as socio-technical systems. Furthermore, we create a template using NVivo software to organise the emerging themes and clusters following the logic of communication levels. This template allows us to explain the phenomenon of DIC in a socio-technical organisational system and discuss how the emerging themes are interrelated, people-focused, and linked to competency development and trust-building. As a contribution to theory, we offer a conceptual model which illustrates the dynamics of DIC as an interplay of socio-technical elements on three communication levels. This conceptual model can be further developed in scholarly discussions on DIC and by organisations reflecting on their IC use in a digital workplace environment.     

Reports of Conferences, Institutes, and Seminars

Late winter and early spring of 2009 was a busy conference time for librarians. Some of the conferences held during that time are reported herein: the American Library Association Midwinter Conference, January 23–28; Electronic Resources and Libraries (E&RL), February 9–12; the North Carolina Serials Conference, March 27; the New England Technical Services Librarians' (NETSL) Spring Conference, April 17; and the Technical, Electronic and Digital Services Interest Group (TEDSIG) Spring Meeting, April 24.     

CORE (Cost of Resource Exchange) Standard

This article describes the CORE (Cost of Resource Exchange) standard. CORE defines an XML schema to allow the exchange of financial information relating to library resources among library systems.     

Kendall's tau for serial dependence

The authors show how Kendall's tau can be adapted to test against serial dependence in a univariate time series context. They provide formulas for the mean and variance of circular and noncircular versions of this statistic, and they prove its asymptotic normality under the hypothesis of independence. They present also a Monte Carlo study comparing the power and size of a test based on Kendall's tau with the power and size of competing procedures based on alternative parametric and nonparametric measures of serial dependence. In particular, their simulations indicate that Kendall's tau outperforms Spearman's rho in detecting first‐order autoregressive dependence, despite the fact that these two statistics are asymptotically equivalent under the null hypothesis, as well as under local alternatives.     

Diagnostics for multivariate imputations

Summary.  We consider three sorts of diagnostics for random imputations: displays of the completed data, which are intended to reveal unusual patterns that might suggest problems with the imputations, comparisons of the distributions of observed and imputed data values and checks of the fit of observed data to the model that is used to create the imputations. We formulate these methods in terms of sequential regression multivariate imputation, which is an iterative procedure in which the missing values of each variable are randomly imputed conditionally on all the other variables in the completed data matrix. We also consider a recalibration procedure for sequential regression imputations. We apply these methods to the 2002 environmental sustainability index, which is a linear aggregation of 64 environmental variables on 142 countries.     

Flexible estimation of serial correlation in nonlinear mixed models

In the conventional linear mixed-effects model, four structures can be distinguished: fixed effects, random effects, measurement error and serial correlation. The latter captures the phenomenon that the correlation structure within a subject depends on the time lag between two measurements. While the general linear mixed model is rather flexible, the need has arisen to further increase flexibility. In addition to work done in the area, we propose the use of spline-based modeling of the serial correlation function, so as to allow for additional flexibility. This approach is applied to data from a pre-clinical experiment in dementia which studied the eating and drinking behavior in mice.