The nearest neighbor Spearman footrule distance for bucket, interval, and partial orders

Comparing and ranking information is an important topic in social and information sciences, and in particular on the web. Its objective is to measure the difference of the preferences of voters on a set of candidates and to compute a consensus ranking. Commonly, each voter provides a total order of all candidates. Recently, this approach was generalized to bucket orders, which allow ties. In this work we further generalize and consider total, bucket, interval and partial orders. The disagreement between two orders is measured by the nearest neighbor Spearman footrule distance, which has not been studied so far. For two bucket orders and for a total and an interval order the nearest neighbor Spearman footrule distance is shown to be computable in linear time, whereas for a total and a partial order the computation is NP-hard, 4-approximable and fixed-parameter tractable. Moreover, in contrast to the well-known efficient solution of the rank aggregation problem for total orders, we prove the NP-completeness for bucket orders and establish a 4-approximation.     

A Review of Theory in Family Business Research: The Implications for Corporate Governance

In recent years, increasing scholarly attention has been directed toward the field of family business research. Based on an exhaustive sample of 235 publications, this article provides a comprehensive review and a critical assessment of the theoretical underpinnings and corporate governance issues in family business research. Three predominant theoretical perspectives, namely principal–agent theory, stewardship theory and the resource‐based view of the firm, have emerged and provide empirical evidence that family businesses significantly differ from non‐family firms in important dimensions such as agency costs, competitive advantages or corporate governance structure. On their own, none of the aforementioned perspectives succeeds in addressing all complexities associated with family businesses and their corporate governance. Accordingly, joint approaches combining different theoretical frameworks can help to improve understanding of the family business. The article concludes by discussing possible directions for future research that might further contribute to building a comprehensive theory of the family business and its corporate governance.     

基于创业学习视角的大学生创业教育

创业学习是当前创业学领域最前沿的研究方向。从创业学习视角出发,针对我国大学生创业教育现状,结合心理学、管理学和社会学理论,提出“政府引导、高校主导、社会主体”的多元利益相关者参与,开放式创业教育体系,促进我国大学生创业教育的改革和发展。     

Scheduling Support Times for Satellites with Overlapping Visibilities

We consider the scheduling of ground station support times to low Earth orbit (LEO) satellites with overlapping visibilities. LEO satellites typically complete a revolution around the Earth in less than four hours at an altitude of a few hundred miles and are part of the critical infrastructure for natural resource management, crop yield estimation, meteorology, flood control, communication, and space research. Because these satellites are quite expensive to launch and operate, utilizing them in the best possible manner is of paramount importance for the agencies that own them. A ground station provides support time to a satellite to perform a variety of tasks when the satellite is visible to the station over a prespecified planning horizon; the payoff from providing such support is a function of the support time. When two or more satellites pass over the ground station, their visibility time windows may overlap. Thus, under overlapping visibilities, a relevant problem is that of scheduling ground station support time for each satellite with the objective of maximizing the total utility generated from supporting the satellites. We propose four basic scheduling models to address a variety of scenarios and investigate their computational complexities. For each model, we also identify special cases that are polynomially solvable.     

Nearest neighbor hazard estimation with left-truncated duration data

Duration data often suffer from both left-truncation and right-censoring. We show how both deficiencies can be overcome at the same time when estimating the hazard rate nonparametrically by kernel smoothing with the nearest-neighbor bandwidth. Smoothing Turnbull’s estimator of the cumulative hazard rate, we derive strong uniform consistency of the estimate from Hoeffding’s inequality, applied to a generalized empirical distribution function. We also apply our estimator to rating transitions of corporate loans in Germany.     

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.     

Fully observed INAR(1) processes

The innovations of an INAR(1) process (integer-valued autoregressive) are usually assumed to be unobservable. There are, however, situations in practice, where also the innovations can be uncovered, i.e. where we are concerned with a fully observed INAR(1) process. We analyze stochastic properties of such a fully observed INAR(1) process and explore the relation between the INAR(1) model and certain metapopulation models. We show how the additional knowledge about the innovations can be used for parameter estimation, for model diagnostics, and for forecasting. Our findings are illustrated with two real-data examples.     

An algorithm for discriminating populations with unequal variance matrices

A geometrical approach is considered to the problem of discriminating between any two multivariate normal populations, in particular, those with unequal variance matrices. This approach guarantees the existence of a linear discriminant function and provides a simple algorithm to derive the equation of this line. A numerical example is provided.