More (new) products,more problems? A systems perspective on increased capability deployment and organizational errors

The capabilities-based view postulates that organizational capabilities are a key driver of competitive advantage. However, while increasing the pace of deploying organizational capabilities, such as new product development (NPD), may enable alignment with changing environments, it may also have unintended consequences. In this study, we advance theory on these unintended consequences by investigating how the increased deployment of NPD capability leads to organizational errors. Borrowing from organizational research employing systems theory, we argue that an increase in NPD deployment may increase the likelihood of routine discoordination and, thus, the incidence of intra-firm and interfirm errors. However, we also proffer that firms can mitigate errors from increases in NPD capability deployment by engaging in distinct internal and external activities that enable the accumulation of knowledge on how to coordinate systemic change. We distinguish between internal and external errors, demonstrating that in the context of increased NPD deployments, internal voluntary investigations ameliorate internal manufacturing errors, while supplier alliances mitigate outsourced component errors. We find support for our predictions using data from new product introductions and recalls in the U.S. automotive industry. This study sheds light on the tension inherent to accelerating the deployment of patterned organizational activities and suggests that the outcomes of deploying an organizational capability are best viewed holistically within the milieu of organizational systems the capability spans.     

Housestaff coverage in a nonteaching community hospital

In August 1992, a project team of senior medical and administrative personnel was formed (Housestaff Coverage Project Team) at the Park Ridge Health System, Rochester, N.Y.. The team was given a mandate to address housestaff coverage, primarily from an economic standpoint. Through total quality management (TQM), the project team sought to develop a house coverage plan that was sustainable, efficient, and effective. A plan was developed that includes three layers of service. A minimum "standard hospital coverage" would be available to all physicians and their patients and cover the basic needs of admission, crisis intervention, and issues of length of stay. A complete level of service would be available under the title of "case management" and would consist of total patient management, under the direction of the attending physician, from admission through discharge. The third level of service available to both "standard" and "case managed" patients would be a "consultative service." The latter would function as a traditional in-house medical service and would bill for its services. Park Ridge Hospital believes it has developed a system of housestaff coverage that is sustainable, efficient, and effective. An evaluation mechanism, primarily addressed at length of stay, will tell if we are correct in this assumption.     

An empirical comparison of two approaches for CDPCA in high-dimensional data

Statistical Methods & Applications - Modified principal component analysis techniques, specially those yielding sparse solutions, are attractive due to its usefulness for interpretation...     

The MIMIC–CUB Model for the Prediction of the Economic Public Opinions in Europe

Social Indicators Research - To study the Europeans’ perception on the economic conditions, a model that combine Multiple Indicators Multiple Causes (MIMIC) and Combination of Uniform and...     

Socio-Economic Indicators for Performance Evaluation and Quality Assessment: Statistical Methods and Applications

Social Indicators Research -     

How biology became social,and what it means for social theory

In this paper I first offer a systematic outline of a series of conceptual novelties in the life‐sciences that have favoured, over the last three decades, the emergence of a more social view of biology. I focus in particular on three areas of investigation: (1) technical changes in evolutionary literature that have provoked a rethinking of the possibility of altruism, morality and prosocial behaviours in evolution; (2) changes in neuroscience, from an understanding of the brain as an isolated data processor to the ultrasocial and multiply connected social brain of contemporary neuroscience; and (3) changes in molecular biology, from the view of the gene as an autonomous master of development to the ‘reactive genome’ of the new emerging field of molecular epigenetics. In the second section I reflect on the possible implications for the social sciences of this novel biosocial terrain and argue that the postgenomic language of extended epigenetic inheritance and blurring of the nature/nurture boundaries will be as provocative for neo‐Darwinism as it is for the social sciences as we have known them. Signs of a new biosocial language are emerging in several social‐science disciplines and this may represent an exciting theoretical novelty for twenty‐first social theory.     

Job quality,industrial relations and the crisis in Europe

This paper reports results from recent Eurofound research on the impact of the crisis on industrial relations and working conditions in Europe, based on the output of Eurofound's European Working Conditions Observatory and European Industrial Relations Observatory and data from the European Working Conditions Survey. Overall, the crisis – even if it is sometimes difficult to separate the effect of the crisis from megatrends in working conditions and industrial relations – seems to have had an impact on both domains. With reference to industrial relations, the impact of the crisis has influenced actors, processes, and outcomes. Regarding working conditions, the results appear to be in line with the literature on the topic, which relates the crisis to an increase in job insecurity, a decrease in work intensity, in working hours, and in anti-social working time arrangements, and a general improvement in terms of health risks and related outcomes.     

Adaptive multiple importance sampling for Gaussian processes

In applications of Gaussian processes (GPs) where quantification of uncertainty is a strict requirement, it is necessary to accurately characterize the posterior distribution over Gaussian process covariance parameters. This is normally done by means of standard Markov chain Monte Carlo (MCMC) algorithms, which require repeated expensive calculations involving the marginal likelihood. Motivated by the desire to avoid the inefficiencies of MCMC algorithms rejecting a considerable amount of expensive proposals, this paper develops an alternative inference framework based on adaptive multiple importance sampling (AMIS). In particular, this paper studies the application of AMIS for GPs in the case of a Gaussian likelihood, and proposes a novel pseudo-marginal-based AMIS algorithm for non-Gaussian likelihoods, where the marginal likelihood is unbiasedly estimated. The results suggest that the proposed framework outperforms MCMC-based inference of covariance parameters in a wide range of scenarios.