Undeclared Work in Non-Profit Sports Clubs: A Mixed Method Approach for Assessing the Size and Motives

Non-market economy including volunteer work is often ignored in estimations of the shadow economy because no money changes hands. Whilst volunteers stricto sensu are not paid for their activities, a tendency is noted that legal frameworks do allow for reimbursement for actual expenses incurred. However, if the latter receive reimbursements beyond the scope of regulations and labour law this can also be regarded as undeclared work. In this article, the size and motives of this type of undeclared work in non-profit sports clubs in Flanders (Belgium) are explored. As this kind of informal work, by its nature, is difficult to measure, a mixed method approach was used. The results show that at least 10% of volunteers can be considered as undeclared workers. The tax and social security contribution burdens are considered as the main causes for this undeclared work. It is argued that a new employment status for paid volunteers in sports is necessary to guarantee the provision of qualitative sports services.     

Monitoring the complexities: Nuclear power and public opinion

Interaction between organizations and stakeholders today takes place on virtual and physical ‘issue arenas’. This study examined opinions on nuclear power and asked who are the players discussing nuclear power in Finland? Through content analysis, surveys and interviews, the study concluded that politicians, power companies and regulators were the ones with voice, as NGOs and citizens were hardly heard. The paper suggests the future role of PR practitioners to be to find the right issue arenas and facilitate corporate voice and reputation on those arenas.     

PROBLEMS WITH BINOMIAL TWO-SIDED TESTS AND THE ASSOCIATED CONFIDENCE INTERVALS

Confidence intervals for parameters of distributions with discrete sample spaces will be less conservative (i.e. have smaller coverage probabilities that are closer to the nominal level) when defined by inverting a test that does not require equal probability in each tail. However, the P‐value obtained from such tests can exhibit undesirable properties, which in turn result in undesirable properties in the associated confidence intervals. We illustrate these difficulties using P‐values for binomial proportions and the difference between binomial proportions.     

Scenario Tree Modeling to Analyze the Probability of Classical Swine Fever Virus Introduction into Member States of the European Union

The introduction of classical swine fever virus (CSFV) into a country free of disease without vaccination may have huge consequences in terms of both disease spread and economic losses. More quantitative insight into the main factors determining the probability of CSFV introduction (PCSFV) is needed to optimally use resources for the prevention of CSFV introduction. For this purpose a spreadsheet model was constructed that calculates the annual PCSFV into member states of the European Union (EU). The scenario pathway approach was used as most probabilities in the model are very small. Probability distributions were used to take into account inherent variability of input parameters. The model contained pathways of CSFV introduction including the import of pigs and pork products, returning livestock trucks, and contacts with wild boar. All EU member states were included as possible sources of CSFV. Default results for the Netherlands showed a mean overall annual PCSFV of approximately 0.06, indicating that the Netherlands can expect CSFV introduction on average once every 18 years from the pathways and countries included in the model. Almost 65% of this probability could be attributed to the pathway of returning livestock trucks. The most likely sources of CSFV introduction were Germany, Belgium, and the United Kingdom. Although the calculated probabilities were rather low when compared with expert estimates and recent history, the most likely causes of CSFV introduction indicated by the model were considered to be realistic. It was therefore concluded that the model is a useful tool to structure and analyze information for decision making concerning the prevention of CSFV introduction.     

Change agent's contribution to recipients' resistance to change: A two-sided story

In the change management literature, most studies on recipients' resistance to change include only the views of agents or of recipients, thereby ignoring that these parties may have different perceptions. In this quantitative study, we include the perceptions of both parties in studying the recipients' resistance and the impact of the agent's leadership behavior. In a sample of 117 agent-recipients groupings, covering 110 different change projects in 90 organizations, we found that agents perceive higher levels of recipients' resistance than do the recipients themselves. Additionally, we found that agents who create space to enable recipients to think and act differently (by employing creating behavior) report higher levels of recipients' resistance, whereas recipients perceive their resistance to be lowered when agents facilitate an emotional connection to the change (framing behavior). The depth of the change appeared to moderate the relationship between agent's leadership behavior and recipients' resistance, indicating that agents and recipients differ in which change leadership behaviors they perceive as increasing or decreasing resistance at different levels of change depth. These findings imply to reconsider the relationship between agent and recipients and we propose some promising avenues for future studies in resistance research.     

A Parametric Estimation Procedure for Relapse Time Distributions

In a relapse clinical trial patients who have recovered from some recurrent disease (e.g.,ulcer or cancer) are examined at a number of predetermined times. A relapse can be detected either at one of these planned inspections or at a spontaneous visit initiated by the patient because of symptoms. In the first case the observations of the time to relapse, X, is interval-censored by two predetermined time-points. In the second case the upper endpoint of the interval is an observation of the time to symptoms,Y . To model the progression of the disease we use a partially observable Markov process. This approach results in a bivariate phase-type distribution for the joint distribution of (X,Y). It is a flexible model which contains several natural distributions for X, and allows the conditional distributions of the marginals to smoothly depend on each other. To estimate the distributions involved we develop an EM-algorithm. The estimation procedure is evaluated and compared with a non-parametric method in a couple of examples based on simulated data.