CCR or BCC: what if we are in the wrong model?

The CCR model by Charnes et al. (Eur J Oper Res 2:429–444, 1978) together with the BCC model by Banker et al. (Manag Sci 30:1078–1091, 1984) are the most popular approaches of measuring efficiency among a group of decision making units, DMUs, in data envelopment analysis, DEA. The right choice of a DEA model—CCR or BCC—often, if not always, is a difficult decision. To evaluate a DMU’s efficiency for both models might be helpful, but it does not always capture the essential issues at stake. In this paper we propose a comparative analysis of both concepts: How does activity scaling under constant BCC-efficiency influence CCR-efficiency. And inversely, how does BCC-efficiency behave when activity scaling under constant CCR-efficiency is applied. Such findings of mutual effects improve a DMU’s ability to reassess upsizing and downsizing of activities. Moreover, it allows for exact calculations of the resulting economic effects, and these effects give new insights beyond classical DEA. Finally, scale efficiency turns out to be the ideal concept to control these activity changes, rather than just CCR- or BCC-efficiency. We use a little numerical example to emphasize advantages of the new concept and sketch the new findings for a theater scenery.     

Basic notions for the analysis of large two-mode networks

Many large real-world networks actually have a two-mode nature: their nodes may be separated into two classes, the links being between nodes of different classes only. Despite this, and despite the fact that many ad hoc tools have been designed for the study of special cases, very few exist to analyse (describe, extract relevant information) such networks in a systematic way. We propose here an extension of the most basic notions used nowadays to analyse large one-mode networks (the classical case) to the two-mode case. To achieve this, we introduce a set of simple statistics, which we discuss by comparing their values on a representative set of real-world networks and on their random versions. This makes it possible to evaluate their relevance in capturing properties of interest in two-mode networks.     

Authors’ response: on the role of data,statistics and decisions in a pandemic

AStA Advances in Statistical Analysis -     

How is My Partner Feeling in Different Daily-Life Settings? Accuracy of Spouses' Judgements about Their Partner's Feelings at Work and at Home

How accurately do spouses know their partner's feelings when the partneris not physically present, but in a specific setting (at work, or at home)?This question addresses a special kind of empathic inference that relies mainly on content knowledge and projection rather than perception. We answered this question using a computer assisted diary approach. A total of 190 husbands and wives outof 95 couples simultaneously recorded how they were feeling and what they thought their partner was feeling, six times each day during an ordinary week. They also recorded where they were, who they were with, and where they thought their partner was. This enabled us to assess measures of accuracy and assumed similarity under natural conditions in spouses' daily lives. Results showed that the spouses' judgements of the absent partner's feelings relied on their own feelings (assumed similarity). Despite this they were often quite accurate, even when assumed similarity was controlled. In general, our findings indicate that spouses have a basic knowledge about their partner's feelings when they are apart. However, the specific situation, the items being judged, and the gender of the spouses also need to be taken into account.     

Suicide Prevention Training Program for Gatekeepers Working in Community Hospice Settings

Gatekeepers in community hospice settings encounter patients and caregivers struggling with suicidal thoughts. Limited guidance is available for training staff on the prevention of suicide in hospice care. This study evaluated one promising, evidence-based, suicide prevention program with a behavioral rehearsal practice session. A pre- and post-, one group design, was utilized to measure the training impact and educational needs of staff working in community hospice settings (N =39). Training increased awareness of the risk factors for suicide, as reported by nearly 80% of participants. Self-efficacy scores showed a statistically significant Increase, t(df = 35), ?9.59, p= .00 (two-tailed), from pretraining (n=36, M=2.21, SD= .65) to posttraining (n=36, M=3.03, SD=.56). Satisfaction and the need for additional devoted time for suicide prevention training were highly rated. Suicide prevention training programs can enhance self-efficacy, knowledge, and skills for gatekeepers working in community hospice settings.