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A dual transportation analysis is considered as a strategic matter for plant facility expansion/contraction decision making in manufacturing operations. The primal-dual problem is presented in a generalized mathematical form. A practical technique of generating the dual solution is illustrated with a plant facility expansion/contraction example as a tutorial. Demand forecasting is performed based on the time series data with seasonal variation adjustments. The dual solution helps facilitate operations decision making by providing useful information.

Big data have rapidly developed as a viable solution to many problems faced in engineering industries. Specifically, in the industry of water resource engineering, where there is a tremendous amount of data, various big data techniques could be applied to achieve innovative and efficient solutions for the industry. This study reviewed the proposal of big data as potential approaches to solve various difficulties encountered in managing water resources and related applications in Malaysia. The advantages and disadvantages of big data applications have also been discussed along with a brief literature review and some examples of case studies.

First, dynamic theorizing requires a degree of recognition, and a willingness to confront “reality” that it would not occur to most social scientists is either possible or necessary, for each of the social sciences to take steps toward actualizing the purposes that are posed by their subject matter, respectively. This problem is most evident in economics as a mainstream discipline. Its proponents are less concerned with doing justice to the nature of economic processes, and especially the gravity they exert in modern societies, on politics, culture, and society. Rather, mainstream economists are preoccupied with refining frameworks and tools that bear the stamp of legitimacy and respectability, within the confines of their discipline. The question of whether or not those frameworks and tools relate directly to processes in modern societies is not only part of their professional concerns. Instead, it is largely immaterial, since reaffirming the boundaries and analytical imperatives of economics as an established and increasingly powerful discipline is a precondition of membership in an exclusive club whose importance and legitimacy is widely recognized, and rarely closely examined. In this sense, economics is an example and illustration par excellence for the day-to-day operations and practices of science verging on ideology (in the sense of moral, intellectual, or political frameworks whose basic assumptions and relationship to legitimating claims must not be identified, and especially not questioned), and of always being in danger of turning into an ideology.

This paper studies the event-history approach to microeconometric program evaluation. We present a mixed semi-Markov event-history model, discuss its application to program evaluation, and analyze its empirical content. The results of this paper provide fundamental insights into what can be learned from longitudinal microdata about, for example, the effects of training programs for the unemployed on their unemployment durations and subsequent job stability. They can guide the choice of particular models and methods for the empirical analysis of such effects.