Multi-source Statistics: Basic Situations and Methods

Many National Statistical Institutes (NSIs), especially in Europe, are moving from single-source statistics to multi-source statistics. By combining data sources, NSIs can produce more detailed and more timely statistics and respond more quickly to events in society. By combining survey data with already available administrative data and Big Data, NSIs can save data collection and processing costs and reduce the burden on respondents. However, multi-source statistics come with new problems that need to be overcome before the resulting output quality is sufficiently high and before those statistics can be produced efficiently. What complicates the production of multi-source statistics is that they come in many different varieties as data sets can be combined in many different ways. Given the rapidly increasing importance of producing multi-source statistics in Official Statistics, there has been considerable research activity in this area over the last few years, and some frameworks have been developed for multi-source statistics. Useful as these frameworks are, they generally do not give guidelines to which method could be applied in a certain situation arising in practice. In this paper, we aim to fill that gap, structure the world of multi-source statistics and its problems and provide some guidance to suitable methods for these problems.     

The Impact of Human and Social Capital on Entrepreneurs’ Knowledge of Finance Alternatives

Building upon prior research that demonstrates how the limited knowledge of finance alternatives of entrepreneurs may cause suboptimal finance decisions, this paper examines how entrepreneurs’ human and social capital influence their knowledge of finance alternatives. For this purpose, we use survey data from 103 Belgian start‐ups. Results demonstrate that entrepreneurs with a business education and entrepreneurs with experience in accountancy or finance have a broader knowledge of finance alternatives. Having a strong network in the financial community is further positively associated with the knowledge of finance alternatives. However, generic human capital, including higher education, industry experience, and management experience, is almost not related with the knowledge of finance alternatives.     

Forward recursion for markov decision processes with skip-free-to-the-right transitions part ii: non-standard applications

This paper is the sequel to Wijngaard and Stidham (1986). The topic is a countable state average reward semi-Markov decision process with a transition mechanism that is skip-free to the right. The applications are controlled GI /M/1 queues. Skip-free to the right means that state n cannot be reached from the states i (< n ) without reaching first state n −1. In such decision processes the reversed optimality equation can be used to estimate the optimal average reward by bi-section. Wijngaard and Stidham (1986) show that it is possible to use upper and lower bounds on the value function for this bi-section. This paper considers queueing problems where this bi-section can not be used in a standard way. Instead of an upper bound on the value function is is possible now to use the character of the optimal strategy.     

Lean planning in the semi-process industry, a case study

The lean approach is an idealizing improvement approach that has an enormous impact in the field of operations management. It started in the automotive industry and has since been widely applied in discrete manufacturing. However, extensions to the (semi-) process industry have been much slower. Resource characteristics of the (semi-) process industry obstruct a straightforward application. The notion of the point of discretization for the (semi-) process industry is helpful here. This notion builds on the fact that in most (semi-) process industries there is a point in production where process production turns into discrete production. Downstream of this point lean principles are applicable in a straightforward manner, while upstream lean needs to be interpreted in a more liberal way. In this article we address this issue by a case study. The study considers how the principles of ‘flow’ and ‘pull’ production - suggesting a regular, demand-driven product flow - may be implemented for the (semi-) process industry by introducing cyclic schedules. The conjectures guiding the case study are: (i) Cyclic schedules fit in a lean improvement approach for the semi-process industry, (ii) Cyclic schedules help to improve production quality and supply-chain coordination and (iii) Discrete event simulation is a useful tool in facilitating a participative design of a cyclic schedule. The case study is extensively described to be able to judge how the context of the changes and the intervention process contribute to the results of the intervention.     

Regen, een toepassing van dynamische programering

Veel mensen zal het wel eens overkomen zijn dat ze tijdens een wandeling overvallen werdcn door een regenbui. De eerste reactie in zo'n situatie is in de regel, hard te gaan lopen teneinde zo droog mogelijk thuis te komen. Bij sommigen echter zal ongetwijfeld wel eens de vraag zijn opgekomen hoeveel effect dat harde lopen nu heeft; als je hard loopt ben je weliswaar eerder thuis maar je vangt ook meer regen per tijdseenheid, en stel je voor dat het al gauw ophoudt met regenen. In dit verhaaltje wordt het probleem van de optimale strategie aan de orde gesteld, wat is de optimale snelheid in verschillende omstandigheden. Als criterium gebruiken we de (verwachte) totale hoeveelheid opgevangen regen. Daarbij gaan we er van uit dat de regen recht naar beneden valt en homogeen verdeeld is over de ruimte. In paragraaf 1 wordt aangenomen dat het blijft regenen. In paragraaf 2 wordt rekening gehouden met de mogelijkheid dat het ophoudt met regenen en daarna droog blijft. In paragraaf 3 nemen we aan dat het steeds opnieuw kan gaan regenen.     

Extrapolating understanding of food risk perceptions to emerging food safety cases

Important determinants of risk perceptions associated with foods are the extent to which the potential hazards are perceived to have technological or naturally occurring origins, together with the acute vs. chronic dimension in which the potential hazard is presented (acute or chronic). This study presents a case study analysis based on an extensive literature review examining how these hazard characteristics affect people’s risk and benefit perceptions, and associated attitudes and behaviors. The cases include E. coli incidences (outbreaks linked to fresh spinach and fenugreek sprouts), contamination of fish by environmental pollutants, (organochlorine contaminants in farmed salmon), radioactive contamination of food following a nuclear accident (the Fukushima accident in Japan), and GM salmon destined for the human food chain. The analysis of the cases over the acute vs. chronic dimension suggests that longitudinal quantification of the relationship between risk perceptions and impacts is important for both acute and chronic food safety, but this has infrequently been applied to chronic hazards. Technologies applied to food production tend to potentially be associated with higher levels of risk perception, linked to perceptions that the risk is unnatural. However, for some risks (e.g. those involving biological irreversibility), moral or ethical concerns may be more important determinants of consumer responses than risk or benefit perceptions. (Lack of) trust has been highlighted in all of the cases suggesting transparent and honest risk–benefit communications following the occurrence of a food safety incident. Implications for optimizing associated risk communication strategies, additional research linking risk perception, and other quantitative measures, including comparisons in time and space, are suggested.