Examining the Impact of Interorganizational Systems on Process Efficiency and Sourcing Leverage in Buyer–Supplier Dyads

Manufacturing firms are increasingly seeking cost and other competitive advantages by tightly coupling and managing their relationship with suppliers. Among other mechanisms, interorganizational systems (IOS) that facilitate boundary‐spanning activities of a firm enable them to effectively manage different types of buyer–supplier relationships. This study integrates literature from the operations and information systems fields to create a joint perspective in understanding the linkages between the nature of the IOS, buyer–supplier relationships, and manufacturing performance at the dyadic level. External integration, breadth, and initiation are used to capture IOS functionality, and their effect on process efficiency and sourcing leverage is examined. The study also explores the differences in how manufacturing firms use IOS when operating under varying levels of competitive intensity and product standardization. In order to test the research models and related hypothesis, empirical data on buyer–supplier dyads is collected from manufacturing firms. The results show that only higher levels of external integration that go beyond simple procurement systems, as well as who initiates the IOS, allow manufacturing firms to enhance process efficiency. In contrast, IOS breadth and IOS initiation enable manufacturing firms to enhance sourcing leverage over their suppliers. In addition, firms making standardized products in highly competitive environments tend to achieve higher process efficiencies and have higher levels of external integration. The study shows how specific IOS decisions allow manufacturing firms to better manage their dependence on the supplier for resources and thereby select system functionalities that are consistent with their own operating environments and the desired supply chain design.     

Multiple imputation for gamma outcome variable using generalized linear model

We used a proper multiple imputation (MI) through Gibbs sampling approach to impute missing values of a gamma distributed outcome variable which were missing at random, using generalized linear model (GLM) with identity link function. The missing values of the outcome variable were multiply imputed using GLM and then the complete data sets obtained after MI were analysed through GLM again for the estimation purpose. We examined the performance of the proposed technique through a simulation study with the data sets having four moderate and large proportions of missing values, 10%, 20%, 30% and 50%. We also applied this technique on a real life data and compared the results with those obtained by applying GLM only on observed cases. The results showed that the proposed technique gave better results for moderate proportions of missing values.     

Disabled people, the reserve army of labour and welfare reform

This paper is concerned with explaining why in contemporary society there has been a number of changes to income maintenance and labour market policy for disabled people. Taking a regulation approach theoretical framework it engages with the debate about whether disabled people can be considered to be part of the reserve army of labour. Rejecting previous broad-brush approaches that seem to suggest that all disabled people are part of the reserve army, it argues that the policy changes have been aimed at reconstructing non-employed disabled people as an important part of the reserve army in a period when labour markets are becoming tighter. In this sense disabled people are crucial to New Labour's regulation of neo-liberal accumulation that is structured through a contradiction between economic stability and increasing participation in paid employment.     

Bigamy: Neither Love nor Marriage,but a Threat to the Nation?

In a computer search of 18 national newspapers over a three-year period (1993–1945) 420 mentions of bigamy were identified. 110 items (or 26 per cent) referred to 26 current criminal cases involving bigamy. Seven cases attracted 70 per cent of the coverage. The comments of the presiding judge were widely reported in five of these cases together with titillating detail. Two other cases included comments by judges. Using Phoenix's (1996) distinction between threats to the nation-state from 'inside' and 'outside', the analysis indicates that two issues of wider socio-political importance – familism and immigration – were central to the judges' comments reported in the press and produced an important counterpoise to the titillating features of these cases. It is argued that the newspaper reporting of bigamy constructs bigamists as being a threat to Britain from 'inside' to the institution of marriage, while the threat from 'outside' is from minority ethnic men marrying female bigamists to gain residential status in Britain. It is the latter challenge which brings the most significant condemnation.     

On approximate least squares estimators of parameters of one-dimensional chirp signal

Chirp signals are quite common in many natural and man-made systems such as audio signals, sonar, and radar. Estimation of the unknown parameters of a signal is a fundamental problem in statistical signal processing. Recently, Kundu and Nandi [Parameter estimation of chirp signals in presence of stationary noise. Stat Sin. 2008;75:187–201] studied the asymptotic properties of least squares estimators (LSEs) of the unknown parameters of a simple chirp signal model under the assumption of stationary noise. In this paper, we propose periodogram-type estimators called the approximate least squares estimators (ALSEs) to estimate the unknown parameters and study the asymptotic properties of these estimators under the same error assumptions. It is observed that the ALSEs are strongly consistent and asymptotically equivalent to the LSEs. Similar to the periodogram estimators, these estimators can also be used as initial guesses to find the LSEs of the unknown parameters. We perform some numerical simulations to see the performance of the proposed estimators and compare them with the LSEs and the estimators proposed by Lahiri et al. [Efficient algorithm for estimating the parameters of two dimensional chirp signal. Sankhya B. 2013;75(1):65–89]. We have analysed two real data sets for illustrative purposes.     

Estimation of hazard of death in vertically transmitted HIV-1-infected children for doubly censored failure times and fixed covariates

This work estimates the effect of covariates on survival data when times of both originating and failure events are interval-censored. Proportional hazards model [16] along with log-linear models was applied on a data of 130 vertically infected HIV-1 children visiting the paediatrics clinic. The covariates considered for the analysis were antiretroviral (ARV) therapy, age at diagnosis, and change in CD4+T cell count. Change in CD4+T cell count was the difference in the last and first count in non-ARV therapy group, while in the ARV therapy group the same was considered after the start of the treatment. Our findings suggest that children on ARV therapy had significantly lower risk of death (p<0.001). We further investigated the effect of age and change in CD4+T cell count on risk of death. These covariates exhibited a possible association with risk of death by both the procedures (p<0.0001). The effect of number of years under ARV therapy with diagnosis year as a confounding factor was directly related to longevity. The results obtained by the two procedures gave reasonable estimates. We conclude that when the lengths of intervals are narrow, we can opt for parametric modeling which is less computationally intensive.