Adaptive estimation with soft thresholding penalties

We show that various robust nonparametric regression estimators, such as the least absolute deviations estimator, can be made adaptive (up to logarithmic factors), by adding a soft thresholding type penalty to the loss function. As an example, we consider the situation where the roughness of the regression function is described by a single parameter p . The theory is complemented with a simulation study.     

Multiproject scheduling: Analysis of scheduling strategies under unequal delay penalties

The multiproject scheduling problem is investigated under the assumption that delays corresponding to different projects carry different penalties. Five penalty functions are introduced that simulate typical business behavior. These are: 1) assigning the highest penalty to the project requiring the greatest amount of resources; 2) assigning the highest priority to the longest project; 3) assigning the highest priority to the project requiring the least amount of resources; 4) assigning the highest priority to the shortest project; and 5) random assignment. Justification for each case is provided.Two powerful project summary measures were used to generate the test problems. The first measure, average resource load factor (ARLF), identifies whether the location of the peak requirement of all (i.e., combined) resources is in the first or second half of the project's critical path. If each resource is expressed in terms of dollars, then ARLF identifies the location of the peak cash requirement. Since in practice the choice of the scheduling strategy is influenced by the location of the peak cash requirement, performance of the scheduling strategies is analyzed with respect to values of this measure. The second measure, average utilization factor (AUF), calculates the ratio of resource requirements to availabilities. It is shown that problems tested must have different AUF values in order to be classified different for purposes of experimental design. Thus a factorial model of the form, y = Strategy + Penalty + ARLF + AUF + ? was used to generate 385 problems, each requiring 2 to 4 resources, containing 3 to 5 projects and 34 to 63 activities.The computer program used in the study is based on a parallel method of scheduling in which priorities of the activities are determined when the activity is considered for scheduling. Ten scheduling strategies are tested. Some important ones are: 1) to schedule the shortest activity first; 2) to schedule the activity with minimum slack first; 3) to schedule the activity with maximum work content first (i.e., from the project with highest work content); 4) to schedule the shortest activity from the shortest project first; and 5) to schedule the activity with maximum penalty first. Shortest activity first and minimum slack first are popular strategies introduced by other researchers.Using number of times ranked first as our criterion, scheduling the activity with maximum penalty first provides the best results followed by the strategy of scheduling the activity with maximum work content. But when these results are analyzed with respect to existence of a very expensive project (i.e., dominance) in the problem, performance of the maximum penalty strategy improves. When the overall results are analyzed with respect to values of ARLF, a different picture emerges. Then the strategy of scheduling the activity with the highest penalty first provides the best results if the peak requirement is early. When the peak requirement is toward the middle of a project's unconstrained critical path, scheduling the activity with the highest work content provides the best results. When the peak requirement is late in a project's life, scheduling the shortest activity from the shortest project is the best strategy to adopt. These findings were tested for statistical significance by using nonparametric testing procedures and were found to be significant.     

Incentives and penalties as means of influencing attendance: a study in the UK public sector

Despite being the largest single source of lost productivity in business and industry, absence from work has not featured as prominently as might have been expected in studies in human resource management. But if, as a new discipline, human resource management is to stimulate fresh insights into perennial problems this matter should be addressed. Drawing upon data from the UK public sector, this article examines various aspects of absence from work with a view to placing the research in this broader context. It is concluded that the indiscriminate application of methods to reduce absence are often ineffective and some measures may actually change employees' work attitudes and perceived equity. This may, in turn, hinder effective human resource management.     

Endogenous debt constraints in collateralized economies with default penalties

The objective of the paper is to propose endogenous debt constraints that rule out Ponzi schemes and ensure the existence of equilibria in a model with limited commitment and (possible) default. We appropriately modify the definition of finitely effective debt constraints, introduced by Levine and Zame (1996) (see also Levine and Zame (2002)), to encompass models with limited commitment, default penalties and collateral. Along this line, we introduce in the setting of Araujo et al. (2002), Kubler and Schmedders (2003) and Páscoa and Seghir (2009) the concept of actions with finite equivalent payoffs. We show that, independent of the level of default penalties, restricting plans to have finite equivalent payoffs rules out Ponzi schemes and guarantees the existence of an equilibrium that is compatible with the minimal ability to borrow and lend that we expect in our model.     

Monitoring mortality: a state-space approach

"A state-space model is developed which provides estimates of decrements in a dynamic environment. The model integrates the actual unfolding experience and a priori or Bayesian views of the rates. The estimates of present rates and predicted future rates are continually updated and associated standard errors have simple expressions. The model is described and applied in the context of mortality estimation but it should prove useful in other actuarial applications. The approach is particularly suitable for dynamic environments where data are scarce and updated parameter estimates are required on a regular basis. To illustrate the method it is used to monitor the unfolding mortality experience of the retired lives under an actual pension plan."     

Immigration policy: a selective approach

Recommendations are offered concerning Japanese policy on the immigration of foreign workers. The author notes that even those countries that used to welcome such immigrants now restrict their entry. The need for a selective policy that would aid internationalization in Japan and strengthen controls on illegal immigrants by requiring employers to secure permits before hiring foreigners is stressed.     

Political regimes: a coalition formation approach

What leads to the stability of a particular regime and what causes its demise? With the aid of formal modeling, the paper illustrates the necessary and sufficient conditions for different political regimes to exist. The game involves two factions representing the differing interests of the civil society and the armed forces of a nation. We illustrate the emergence of political regimes that includes both unconstrained and constrained democracies, both military and civilian autocracies and an alliance formed by a segment of the civil society and the military.     

Preference through indifference: a topological approach

Two problems of consumer theory are approached topologically. An intrinsic topological characterization of transitivity of indifference is provided. Under very weak assumptions, indifference classes are proved to determine the continuous preference inducing them. Moreover, conditions, under which a given topology is the weakest making a preference continuous, are obtained.     

Strategic human resource management: a conceptual approach

In this paper conceptual issues associated with strategic human resource management are addressed. The rapidly expanding international interest in strategic human resource management is first highlighted. The article then explores some of the broader issues around the debate on SHRM that can inform thinking at a macro level. Firstly, the progress made towards understanding the meaning of SHRM is analysed, then a brief overview of the major models of SHRM to date is presented. This overview is used to highlight the key variables and interrelationships that need to be included in a model of SHRM, and a more detailed critical analysis of the contribution of the literature in each of these areas follows. A summary of the most important research questions arising out of the literature is followed by a model of the SHRM process, which attempts to remedy the major weaknesses in existing models of SHRM. The ways in which this model may be used as a basis for empirical research are then noted.

Strategic human resource management     

Modeling the International-Trade Network: a gravity approach

We investigate whether the gravity model (GM) can explain the statistical properties of the International Trade Network (ITN). We fit data on trade flows with a GM using alternative estimation techniques and we build GM-based predictions for the weighted topological properties of the ITN, which are then compared to the observed ones. Our exercises show that the GM: (i) may replicate part of the weighted-network structure only if the observed binary architecture is kept fixed; (ii) is not able to explain higher-order statistics that, like clustering, require the knowledge of triadic link-weight topological patterns, even if the binary structure perfectly replicates the observed one; (iii) performs very badly when asked to predict the presence of a link, or the level of the trade flow it carries, whenever the binary structure must be simultaneously estimated.     

Methods for analyzing decision-making: a framework approach

In political science an eternal question concerns how decisions and policies arise. Modern society, characterized by more uncertainty and complexity than before, increases the challenge of providing valid answers. However, the general lack of methodological concern in several previous studies in this area stresses the need for elaborations of more suitable approaches. In this article we add a methodological perspective that deals with this very question. By reviewing and analyzing earlier research on how decision-making is reached, the overall ambition of this article is to create a framework that can lay the methodological foundation for further studies. Such a framework, which takes into account both the complexity of modern multi-governance societies and adds methodological perspectives of macro and micro standpoints as well as of causal mechanisms, can be used in future research to achieve richer pictures of how decision-making is carried out. In addition, we show how a certain technique of analysis is highly compatible to this framework and that jointly these features provide solutions for a better understanding of the complexity of modern decision-making. All in all, applying this strategy can be used to better systematize complex causal chains that reflect different analytical levels and thereby increase leverage on how to understand and explain the process of political decisions.     

Networks in family business: a multi-rational approach

Current research on networks in family businesses has approached the topic from a mono-rational perspective where the family, business and social networks are each considered in relative isolation. This paper argues that multi-rational approaches, which accept that the three groups of networks interact and overlap, offer a useful alternative perspective. In proposing the case for multiple rationalities as a framework within which family business networking can be viewed – and in putting forward an initial model – the paper allows the interaction of the different networks within the family business to be more fully acknowledged. Evidence from the literature is presented as a basis for further exploration using empirical approaches and it is emphasised that further and empirical approaches are required.     

Measuring innovation and innovativeness: a data-mining approach

Despite substantial advances over the past decades, measuring innovation and innovativeness remains a challenge for both academic researchers and management practitioners. To address several key concerns with current indicators—such as their specialization and consequent one-sidedness, their frequent lack of theoretical foundations, and the fact that they may not really foster creativity and invention—this paper introduces some new metrics via one data-mining approach—formal concept analysis—which is increasingly used to represent and treat knowledge. This approach can adapt to particular needs and goals, incorporate various kinds of information (qualitative or quantitative) from different sources, and cope with several types of innovations. It also uncovers a logical route to novelty, which might enhance the generation of ideas and is used here to support the measurement of innovativeness.

     

A university budget problem: a priority-based approach

The budgeting problem in a university environment is considered, using the Analytic Hierarchy Process (AHP) developed by Saaty. This approach allows the priorization of all relevant budget considerations both from the benefit to the school's future evolution and from the cost of operation viewpoints. This approach allows using the derived priority structure to arrive at a budget allocation. In addition to the systematic manner by which this budget is determined, the approach also provides an “audit trail” that is very important in explaining the specific allocation.