When Nonprofit Organizations Meet Information and Communication Technologies: How Organizational Culture Influences the Use of Traditional,Digital, and Sharing Media

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - In contrast to previous studies that emphasized how resources and institutional forces influence nonprofit organizations...     

A robust automatic clustering algorithm for probability density functions with application to categorizing color images

This study develops a robust automatic algorithm for clustering probability density functions based on the previous research. Unlike other existing methods that often pre-determine the number of clusters, this method can self-organize data groups based on the original data structure. The proposed clustering method is also robust in regards to noise. Three examples of synthetic data and a real-world COREL dataset are utilized to illustrate the accurateness and effectiveness of the proposed approach.     

Estimation of the cumulative incidence function under multiple dependent and independent censoring mechanisms

Competing risks occur in a time-to-event analysis in which a patient can experience one of several types of events. Traditional methods for handling competing risks data presuppose one censoring process, which is assumed to be independent. In a controlled clinical trial, censoring can occur for several reasons: some independent, others dependent. We propose an estimator of the cumulative incidence function in the presence of both independent and dependent censoring mechanisms. We rely on semi-parametric theory to derive an augmented inverse probability of censoring weighted (AIPCW) estimator. We demonstrate the efficiency gained when using the AIPCW estimator compared to a non-augmented estimator via simulations. We then apply our method to evaluate the safety and efficacy of three anti-HIV regimens in a randomized trial conducted by the AIDS Clinical Trial Group, ACTG A5095.     

A penalized likelihood method for nonseparable space–time generalized additive models

In this paper, we study space–time generalized additive models. We apply the penalyzed likelihood method to fit generalized additive models (GAMs) for nonseparable spatio-temporal correlated data in order to improve the estimation of the response and smooth terms of GAMs. The results show that our space–time generalized additive models estimated response and smooth terms reasonable well, and in addition, the mean squared error, mean absolute deviation and coverage intervals improved considerably compared to the classic GAM. An application on particulate matter concentration in the North-Italian region of Piemonte is also presented.     

Acceptance of automation manufacturing technology in China: an examination of perceived norm and organizational efficacy

Abstract

With a shift to more automation technology, social acceptance of technology plays an important role in the manufacturing sector. To what extent this occurs, and affects the adoption of technology, has been less researched, but is important in deciding how such technology is introduced, and the nature of the shift from labour-intensive manufacturing to automation. This research applies the revised technology acceptance model (TAM) to examine the impact of social and individual antecedents on the acceptance of automation manufacturing technology. Survey data are collected from 258 Chinese manufacturers. Results suggest that perceived norms significantly affect organizational intention to use automation manufacturing technology both directly and via perceived usefulness; organizational efficacy explains the intention to use via mediating effect of perceived usefulness and perceived ease of use. This research is one of the first extending and applying TAM from individuals to organizations.     

What makes hybrid insourcing successful: A new public–private partnership model for social welfare services

Outsourcing has been a key policy tool for delivering a range of social services, and regarded as more effective than insourcing or direct government provision. At the same time, it has also caused many delivery issues such as principal‐agent problems, a lack of policy coordination, and poor‐quality welfare services. While the pendulum continues to swing between insourcing and outsourcing, we aim to propose a new public–private partnership model called the “hybrid insourcing model” and examine which factors influence the performance of the model. In South Korea, around 2010, the local government in Namyangju City was the first to implement the “Hope Care Center model,” a kind of hybrid insourcing model, which has been praised for its innovation and widely emulated by central and local governments. Our analysis utilizes data collected between December 2017 and January 2018 from public sector employees and civilian staff in Namyangju and a comparable city, A. From this, we draw a number of implications, both for theory and for policy. We argue that, for public–private partnerships, active cooperation and equality are the biggest factors in contributing to positive performance. These work alongside leaders with a clear vision and with employees' positive attitude.     

Cultivating employee creativity through strategic internal communication: The role of leadership,symmetry, and feedback seeking behaviors

Using a survey of 405 full-time employees, this study examined how organizations’ internal communication influenced by leadership communication at the supervisory- and senior-levels impacts employee creativity and how employees’ feedback-seeking behaviors mediate these relationships. The results suggest that leadership communication at the supervisory and senior levels positively influence symmetrical internal communication system. The analysis also shows that symmetrical internal communication and leadership communication cause employees to seek more feedback from different interpersonal sources including supervisors, coworkers, and peers in other departments, which in turn enhances creativity. This paper concludes with a discussion of the theoretical and practical implications of these findings for public relations and internal communication.     

The Intersubjective Experience of the Physical Body in the Clinical Setting of Eating Disorders

This paper will illuminate one dimension of self-disclosure as it relates to the inescapable presence of the body in treatment, and the female clinician’s ability to bring her physical body into clinical discussions during an encounter with a female client with an eating disorder. Although the clinical literature on eating disorders validates that transference and countertransference issues are particularly powerful, it generally neglects the exploration of these issues specific to the body’s physical presentation. Since body dissatisfaction is increasingly normative for women today, female clinicians need to have a theoretical road map on which to rely when they encounter a shared body experience. Thus, in order to encourage discussions of the therapist’s body in clinical social work practice, the body needs to be situated in a larger theoretical framework within which it can be explained and located; this framework is object relations theory viewed through an intersubjective lens. Concepts from object relations theory will demonstrate the importance of the body in the clinical exchange by highlighting the parallel between Winnicott’s ‘good enough’ mother and the ‘good enough’ therapist’s body. When the therapist is able to judiciously invite discussions of her body into the clinical arena, the client is given the opportunity to move from object relating to object usage. A case presentation exemplifies how this conceptual framework can be applied to clinical social work practice, strengthening the relationship between knowing and doing.     

Simultaneous edit-imputation and disclosure limitation for business establishment data

Business establishment microdata typically are required to satisfy agency-specified edit rules, such as balance equations and linear inequalities. Inevitably some establishments' reported data violate the edit rules. Statistical agencies correct faulty values using a process known as edit-imputation. Business establishment data also must be heavily redacted before being shared with the public; indeed, confidentiality concerns lead many agencies not to share establishment microdata as unrestricted access files. When microdata must be heavily redacted, one approach is to create synthetic data, as done in the U.S. Longitudinal Business Database and the German IAB Establishment Panel. This article presents the first implementation of a fully integrated approach to edit-imputation and data synthesis. We illustrate the approach on data from the U.S. Census of Manufactures and present a variety of evaluations of the utility of the synthetic data. The paper also presents assessments of disclosure risks for several intruder attacks. We find that the synthetic data preserve important distributional features from the post-editing confidential microdata, and have low risks for the various attacks.