A New Model for Multivariate Markov Chains

We propose a new model for multivariate Markov chains of order one or higher on the basis of the mixture transition distribution (MTD) model. We call it the MTD‐Probit. The proposed model presents two attractive features: it is completely free of constraints, thereby facilitating the estimation procedure, and it is more precise at estimating the transition probabilities of a multivariate or higher‐order Markov chain than the standard MTD model.     

Markov-switching generalized additive models

We consider Markov-switching regression models, i.e. models for time series regression analyses where the functional relationship between covariates and response is subject to regime switching controlled by an unobservable Markov chain. Building on the powerful hidden Markov model machinery and the methods for penalized B-splines routinely used in regression analyses, we develop a framework for nonparametrically estimating the functional form of the effect of the covariates in such a regression model, assuming an additive structure of the predictor. The resulting class of Markov-switching generalized additive models is immensely flexible, and contains as special cases the common parametric Markov-switching regression models and also generalized additive and generalized linear models. The feasibility of the suggested maximum penalized likelihood approach is demonstrated by simulation. We further illustrate the approach using two real data applications, modelling (i) how sales data depend on advertising spending and (ii) how energy price in Spain depends on the Euro/Dollar exchange rate.     

Adaptive and Generative Learning: Implications from Complexity Theories

One of the most important classical typologies within the organizational learning literature is the distinction between adaptive and generative learning. However, the processes of these types of learning, particularly the latter, have not been widely analyzed and incorporated into the organizational learning process. This paper puts forward a new understanding of adaptive and generative learning within organizations, grounded in some ideas from complexity theories: mainly self‐organization and implicate order. Adaptive learning involves any improvement or development of the explicate order through a process of self‐organization. Self‐organization is a self‐referential process characterized by logical deductive reasoning, concentration, discussion and improvement. Generative learning involves any approach to the implicate order through a process of self‐transcendence. Self‐transcendence is a holo‐organizational process characterized by intuition, attention, dialogue and inquiry. The main implications of the two types of learning for organizational learning are discussed.     

Wachstumsbedingungen von Ein-Personen-Gründungen – Eine Längsschnittbeobachtung über acht Jahre

This study analyzes the growth potential of one-person startups on the basis of the framework model proposed by Gilbert, McDougall and Audretsch (2006) by postulating five key groups of enterprise growth predictors: entrepreneur characteristics, resources, strategy, industry, and organizational structures and systems. The framework model was adapted to suit the specific circumstances of one-person startups. The model was tested using a longitudinal data set comprising 188 Austrian one-person startups which were observed over a period of eight years. At the end of the observation period, the businesses included in the study had an average of 1.33 employees. The gender of the founder, capital requirements at the time of establishment, and growth strategy proved to be the most important predictors of growth. In addition, human capital resources also tended to have a positive impact. In summary, it is possible to draw empirically reliable conclusions about growth potential on the basis of the “seriousness” of an one-person startup project.     

An interactive decision support system for an aggregate production planning model based on multiple criteria mixed integer linear programming

In this paper, we present an aggregate production planning (APP) model applied to a Portuguese firm that produces construction materials. A multiple criteria mixed integer linear programming (MCMILP) model is developed with the following performance criteria: (1) maximize profit, (2) minimize late orders, and (3) minimize work force level changes. It includes certain operational features such as partial inflexibility of the work force, legal restrictions on workload, work force size (workers to be hired and downsized), workers in training, and production and inventory capacity. The purpose is to determine the number of workers for each worker type, the number of overtime hours, the inventory level for each product category, and the level of subcontracting in order to meet the forecasted demand for a planning period of 12 months. Additionally, a decision support system (DSS) based on the MCMILP model is proposed. It will help practitioners find the “best” solution for an APP problem without having to familiarize themselves with the mathematical complexities associated with the model. An example to illustrate the use of the DSS is also included.     

Data and projections of HIV/AIDS cases in Portugal: an unstoppable epidemic?

The size of the affected population with HIV/AIDS is a vital question asked by healthcare providers. A statistical procedure called Back-calculation has been the most widely used method to answer that question. Recent discussions suggest that this method is gradually becoming less appropriate for reliable incidence and prevalence estimates, as it does not take into account the effect of treatment. In spite of this, in the current paper that method and a worst-case scenario are used to assess the quality of previous projections and obtain new ones. The first problem faced was the need to account for reporting delays, no reporting and underreporting. The adjusted AIDS incidence data were then used to obtain lower bounds on the size of the AIDS epidemic, using the back-calculation methodology. A Weibull and Gamma distribution was considered for the latency period distribution. The EM algorithm was applied to obtain maximum likelihood estimates of the HIV incidence. The density of infection times was parameterized as a step function. The methodology is applied to AIDS incidence in Portugal for four different transmission categories (injecting drug users, heterosexual, homo/bisexual and other) to obtain short-term projections (2002–2005) and an estimate of the minimum size of the epidemic.     

Population Growth and the Local Provision of Services: The Role of Primary Schools in Portugal

Population Research and Policy Review - The shrinking population in many European regions has led to a debate on the relation between the local provision of services of general interest and the...     

The Experience of Learning EFT in Spanish-speaking Countries: A Multi-National Replication Study

This study is a multi-national follow-up to the original (Sandberg and Knestel (2011) Journal of Marital and Family Therapy, 37, 393–410) article on the process of learning Emotionally Focused Couples Therapy (EFT). A total of 102 clinicians from nine Spanish-speaking countries (Mexico, Costa Rica, Guatemala, Spain, Colombia, Argentina, Chile, Ecuador, and El Salvador) participated in the study. A comparison of results across the two studies revealed more similarities than differences. However, a few notable differences emerged from responses to qualitative questions, namely a heightened sense of appreciation for and resonance with the focus on core emotion in EFT and less frequent reports of difficulty learning and adapting to the model among Spanish-speaking therapists. These differences were consistent with common cultural values and forms of expression in Latin America and Spain. Results are discussed in terms of training, supervision, and future research as well.     

Urbanization homogenizes the interactions of plant-frugivore bird networks

Urban Ecosystems - Anthropogenic activities are the main cause of habitat loss and fragmentation, which directly affects biodiversity. Disruption in landscape connectivity among populations may...