Contractor Accreditation: A Probabilistic Model

The selection of competent contractors is a critical function in all business organizations. In contrast to other types of vendors (e.g., distributors, manufacturers, etc.), contractors are typically accredited before any business transaction takes place. In such situations, there is often a considerable amount of uncertainty associated with the accreditation process. This research presents a probabilistic model for accrediting contractors. We discuss a methodology in which probability measures are used to capture the uncertainty inherent in the decision process. These probabilities are estimated from data on (i) past applicants and (ii) their eventual performance, if accredited. Furthermore, these probabilities are used to determine when additional information about an applicant should be collected, as well as what kind of information would be most relevant for the vendor under consideration.     

Organizational change and rigidity during crisis: A review of the paradox

When and how do existential crises, threatening business continuity, stimulate organizational change or cause the opposite—rigid preservation of established business practices? This question remains unresolved, despite three decades of deliberations in the academic literature, which still yields contradicting theoretical arguments and empirical results. One view argues and finds support for the hypothesis that posits an amplified propensity to change within threatened organizations. The other view supports the threat-rigidity thesis, implying reinforcing habitual practices. In this paper, we provide a novel holistic typology of organizational crises and then review the literature on the topic, summarizing existing insights within a theoretical framework comprising three interrelated sequential processes: organizational cognition, decision-making, and implementation. We analyze the gaps in the field's knowledge within each process and propose a research agenda to address these voids.     

The likelihood ratio test foe the homogeneity of the variances in a covariance matrix with block compound symmetry

For the problem of testing the homogeneity of the variances in a covariance matrix with a block compound symmetric structure, the likelihood ratio test is derived in this paper, A modification of the test that allows its distribution to be better approximated by the chi-square distribution is also considered, Formulae for calculating approximate sample size and power are derived, Small sample performances of these tests in the case of two dependent bivariate or trivariate normals are compared to each other and to the competing tests by simulating levels of significance and powers, and recommendation is made of the ones that have good performance, The recommended tests are then demonstrated in an illustrative example.     

Monte Carlo Approximation of Bootstrap Variances

It is widely believed that the number of resamples required for bootstrap variance estimation is relatively small An argument based on the unconditional coefficient of variation of the Monte Carlo approximation, suggests that as few as 25 resamples will give reasonable results. In this article we argue that the number of resamples should, in fact, be determined by the conditional coefficient of variation, involving only resampling variability. Our conditional analysis is founded on a belief that Monte Carlo error should not be allowed to determine the conclusions of a statistical analysis and indicates that approximately 800 resamples are required for this purpose. The argument can be generalized to the multivariate setting and a simple formula is given for determining a lower bound on the number of resamples required to approximate an m-dimensional bootstrap variance-covariance matrix.     

Predicting profitability using advice branch bank networks

The literature on social networks and their analysis has undergone explosive growth in the past decade. Network models have been used to study structures as diverse as the interaction of monks in a monastery, the links across the World Wide Web, and the structure of organizations. In much of this literature the network itself is viewed as the object of interest, and models are used to elucidate its structure. In this paper, we adopt a different perspective and we explore the role of network structure of organizations for prediction purposes. In particular, we work with data gathered on the advice-seeking habits of employees in 52 branches of a major North American bank corporation. We then use the network structure within each branch discovered via various exploratory analyses to predict the profitability of the individual branches.     

Visualizing Mean,Median, Mean Deviation,and Standard Deviation of a Set of Numbers

We review the existing visualizations of the mean and the median of a given set of numbers. Then we give an alternative visualization of the mean using the empirical cumulative distribution function of the given numbers. Next, we visualize the mean deviation (MD) and the mean square deviation (MSD) of the given numbers from any arbitrary value, including the variance. In light of these new visualizations, we revisit the well-known optimal properties of the MD from the median and the MSD from the mean. We also give a more elementary explanation of why the denominator of the sample variance of a set of numbers is one less than the sample size.     

Gender Disparities in Educational Trajectories in India: Do Females Become More Robust at Higher Levels?

Studies on educational attainments have tended to focus on attainments at a specific level of education. The change in disparities in attainment over the educational life cycle, however, has been neglected in literature—in India, for instance, the only exceptions are Vaid (2004) and Desai and Kulkarni (2008). This paper uses unit level National Sample Survey data (2004–2005) to examine gender disparities at different educational levels up to the high school level. Bi-variate analysis of gender disparities computed using the Sopher-Kundu index indicates that although there are substantial gender disparities at lower levels of education, this gets reversed at higher levels in several states. At the all-India level, too, in recent years, a reversal of disparity may be observed in urban areas. Econometric analysis using the variable parameter variant of the generalized ordered logit model reveals that robustness of females increase over the educational life cycle, though disparity remains, after controlling for socio-economic traits.     

A new graph parameter and a construction of larger graph without increasing radio <Emphasis Type="Italic">k</Emphasis>-chromatic number

For a positive integer \(k\ge 2\), the radio k-coloring problem is an assignment L of non-negative integers (colors) to the vertices of a finite simple graph G satisfying the condition \(|L(u)-L(v)| \ge k+1-d(u,v)\), for any two distinct vertices u, v of G and d(u, v) being distance between u, v. The span of L is the largest integer assigned by L, while 0 is taken as the smallest color. An \(rc_k\)-coloring on G is a radio k-coloring on G of minimum span which is referred as the radio k-chromatic number of G and denoted by \(rc_k(G)\). An integer h, \(0<h<rc_k(G)\), is a hole in a \(rc_k\)-coloring on G if h is not assigned by it. In this paper, we construct a larger graph from a graph of a certain class by using a combinatorial property associated with \((k-1)\) consecutive holes in any \(rc_k\)-coloring of a graph. Exploiting the same property, we introduce a new graph parameter, referred as \((k-1)\)-hole index of G and denoted by \(\rho _k(G)\). We also explore several properties of \(\rho _k(G)\) including its upper bound and relation with the path covering number of the complement \(G^c\).