University of Warwick

About: University of Warwick is a education organization based out in Coventry, Warwickshire, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 26212 authors who have published 77127 publications receiving 2666552 citations. The organization is also known as: Warwick University & The University of Warwick.

Lean production and sustainable competitive advantage

Abstract: Today, “lean” may no longer be fashionable but its core principles (flow, value, pull, minimizing waste etc.) have become the paradigm for many manufacturing (and service) operations. Given this pre‐eminence, the paper seeks to establish what impact it has had on the overall competitive positions of adopter firms. Combining normative and critical theory (from lean production and resource‐based view of the firm literature) with empirical material drawn from three case studies, the paper argues that lean production can underpin competitive advantage if the firm is able to appropriate the productivity savings it creates. Similarly, the ambiguity of lean production in practice means that the implementation process can create strategic resources to underpin sustainable competitive advantage. Problematically, however, the paper also suggests that being “lean” can curtail the firm’s ability to achieve long‐term flexibility. It concludes with suggestions for further work.

Dynamic Generalized Linear Models and Bayesian Forecasting

Abstract: Dynamic Bayesian models are developed for application in nonlinear, non-normal time series and regression problems, providing dynamic extensions of standard generalized linear models. A key feature of the analysis is the use of conjugate prior and posterior distributions for the exponential family parameters. This leads to the calculation of closed, standard-form predictive distributions for forecasting and model criticism. The structure of the models depends on the time evolution of underlying state variables, and the feedback of observational information to these variables is achieved using linear Bayesian prediction methods. Data analytic aspects of the models concerning scale parameters and outliers are discussed, and some applications are provided. Dynamic Bayesian models are developed for application in nonlinear, non-normal time series and regression problems, providing dynamic extensions of standard generalized linear models. A key feature of the analysis is the use of conjugate prior and...