Reconsidering the Connection between Capacity and Governance

Public Organization Review - High levels of sub-national policy experimentation and public cynicism about politics and government, combined with significant challenges and opportunities for...     

Competence and Competitive Advantage: Towards a Dynamic Model

Over the last ten years the concept of ‘competence’ has emerged as a central concept for competitive strategy. Several rich theoretical streams have contributed an extensive array of frameworks, definitions and papers using the concept. There is now a need to integrate these many contributions. Indeed, some of the frustration expressed recently by academics may be due to the large volume of conversation and the low level of integration. A concept that is considered so useful that many writers have incorporated it in their work will be of little value if it takes on different meanings for every use. If competence is to be used to explain relationships among variables and to build richer understandings of the roots of competitive advantage, then the field needs to engage in a serious conversation that attempts to focus this concept. Competence needs to be understood in a way that is faithful to its theoretical roots, allows the multiple dimensions that underpin competitive advantage to be meaningfully integrated and is specific enough that meaningful differences can emerge when used as a variable in empirical research. This paper seeks to begin a conversation toward that end by presenting a conceptualization that meets all of these requirements. The paper builds its conceptualization around satisfying the elements of a dynamic model of the relationship between competence and competitive advantage.     

Simulation for the complex Bingham distribution

The complex Bingham distribution is relevant for the shape analysis of landmark data in two dimensions. In this paper it is shown that the problem of simulating from this distribution reduces to simulation from a truncated multivariate exponential distribution. Several simulation methods are described and their efficiencies are compared.     

The rescission of behaviors: Inconsistent responses in adolescent sexuality data

In longitudinal survey research, certain questions can be rescinded illogically. For instance, respondents who at Time 1 report having had sexual intercourse may at Time 2 report never having done so. This paper reports measurement techniques and analyses of these types of inconsistencies from an ongoing longitudinal adolescent sexuality project. Inconsistencies in intercourse, masturbation, and other sexual behaviors are reported and compared to rates from other studies and other less sensitive behaviors within the same study. Three conclusions are presented: (1) inconsistencies should be considered a natural part of any longitudinal survey process and should be incorporated into the response model; (2) inconsistency rates in these particular data support the contention that adolescent sexuality data of appropriate quality for analytical purposes can be obtained; and (3) inconsistency rates in fact contain substantive information concerning the processes under consideration.     

Testing for qualitative interaction of multiple sources of informative dropout in longitudinal data

Longitudinal studies suffer from patient dropout. The dropout process may be informative if there exists an association between dropout patterns and the rate of change in the response over time. Multiple patterns are plausible in that different causes of dropout might contribute to different patterns. These multiple patterns can be dichotomized into two groups: quantitative and qualitative interaction. Quantitative interaction indicates that each of the multiple sources is biasing the estimate of the rate of change in the same direction, although with differing magnitudes. Alternatively, qualitative interaction results in the multiple sources biasing the estimate of the rate of change in opposing directions. Qualitative interaction is of special concern, since it is less likely to be detected by conventional methods and can lead to highly misleading slope estimates. We explore a test for qualitative interaction based on simultaneous confidence intervals. The test accommodates the realistic situation where reasons for dropout are not fully understood, or even entirely unknown. It allows for an additional level of clustering among participating subjects. We apply these methods to a study exploring tumor growth rates in mice as well as a longitudinal study exploring rates of change in cognitive functioning for Alzheimer's patients.     

Borrowing Information across Populations in Estimating Positive and Negative Predictive Values

A marker's capacity to predict risk of a disease depends on disease prevalence in the target population and its classification accuracy, i.e. its ability to discriminate diseased subjects from non-diseased subjects. The latter is often considered an intrinsic property of the marker; it is independent of disease prevalence and hence more likely to be similar across populations than risk prediction measures. In this paper, we are interested in evaluating the population-specific performance of a risk prediction marker in terms of positive predictive value (PPV) and negative predictive value (NPV) at given thresholds, when samples are available from the target population as well as from another population. A default strategy is to estimate PPV and NPV using samples from the target population only. However, when the marker's classification accuracy as characterized by a specific point on the receiver operating characteristics (ROC) curve is similar across populations, borrowing information across populations allows increased efficiency in estimating PPV and NPV. We develop estimators that optimally combine information across populations. We apply this methodology to a cross-sectional study where we evaluate PCA3 as a risk prediction marker for prostate cancer among subjects with or without previous negative biopsy.     

Industry and the environment: a case study of cleaner technologies in selected European countries

The aim of this case study is to discuss the role of technology in addressing environmental problems. The paper tries to scratch beneath the surface of the increasingly frequent ‘quick-fix’ solutions to the present environmental problems, based on such beguiling catchwords as Cleaner Technologies, Best Available Technologies, and Best Available Technologies Not Exceeding Excessive Costs, etc., in an attempt to discover whether there is any substance in them, or whether they are just full of hot air. Recent data from case studies performed by the author in Germany and Finland as well as a postal questionnaire in Denmark are presented. The paper analyses and discusses the roles and responsibilities of designers, industrialists, and government policy-makers. It is argued that existing regulatory regimes, supranational industrial structures, and market mechanisms do not favour the development of cleaner technologies, nor do they promote a reduction in consumption patterns. Evidence from ongoing empirical research in Northwest Europe suggests that industry is far from developing and/or implementing cleaner technologies. The paper closes with a discussion of some of the policy implications involved and some examples of urgently needed further research.     

Estimating Individual-Level Risk in Spatial Epidemiology Using Spatially Aggregated Information on the Population at Risk

We propose a novel alternative to case-control sampling for the estimation of individual-level risk in spatial epidemiology. Our approach uses weighted estimating equations to estimate regression parameters in the intensity function of an inhomogeneous spatial point process, when information on risk-factors is available at the individual level for cases, but only at a spatially aggregated level for the population at risk. We develop data-driven methods to select the weights used in the estimating equations and show through simulation that the choice of weights can have a major impact on efficiency of estimation. We develop a formal test to detect non-Poisson behavior in the underlying point process and assess the performance of the test using simulations of Poisson and Poisson cluster point processes. We apply our methods to data on the spatial distribution of childhood meningococcal disease cases in Merseyside, U.K. between 1981 and 2007.     

A NEW SHORT EXACT GEOMETRIC CONFIDENCE INTERVAL

For discrete distributions, the standard method of producing a two‐sided confidence interval generates an interval that is exact but conservative. This paper proposes a new algorithm to produce a short exact geometric confidence interval with proven properties, and compares the new interval with the standard interval.