Sustainability as global attractor: the greening of the 2008 Beijing Olympics

If one interprets sustainability as an attractor, it means that across time and place notions and ideas of sustainability structure, order and pattern institutions and practices. One can effectively explore the idea that sustainability is turning into a global attractor through mega events. As high profile and very visible happenings that attract worldwide attention, it is difficult to ignore common and widely shared norms on sustainability in the route towards such events. In investigating the 2008 Beijing Olympics I conclude that sustainability norms indeed restructured and patterned this global mega event. Moreover, these sustainability norms are crystallized, institutionalized and fixed in material and social structures, and thus will likely have some permanency.     

PROGRAMMED DECISION STRUCTURES - FUNCTIONAL APPROACH TO QUANTITATIVE UNDERGRADUATE CORE

Administrators and professionals must make social decisions within the environment of the computer revolution. This means that precise skills of logical problem solving and quantitative methods may assume an increasingly prominent place in college preparation for business and social sciences. At the same time, colleges are under pressure not to “select out” persons who are disadvantaged in quantitative areas. With a widening “quantitative gap,” major surgery of existing math and stat courses is unlikely to meet the challenge of this new social environment. Programmed Decisions Structures (PDS) is experimental coursework in a quantitative undergraduate core for business and social sciences. Particular features of PDS were developed to emphasize (1) motivation of the student, (2) credible simulation of realistic business and social environment, (3) awareness of logically developed structures, and (4) principles of applied scientific method. Constructed around the above four points, it is hoped that PDS will close the “quantitative gap” more effectively than the 20 quarter hours of conventional math, stat and computer courses which it replaces.     

OPTIMAL ORDERING IN A DUAL‐SUPPLIER SYSTEM WITH DEMAND FORECAST UPDATES

We study how an updated demand forecast affects a manufacturer's choice in ordering raw materials. With demand forecast updates, we develop a model where raw materials are ordered from two suppliers—one fast but expensive and the other cheap but slow—and further provide an explicit solution to the resulting dynamic optimization problem. Under some mild conditions, we demonstrate that the cost function is convex and twice‐differentiable with respect to order quantity. With this model, we are able to evaluate the benefit of demand information updating which leads to the identification of directions for further improvement. We further demonstrate that the model applies to multiple‐period problems provided that some demand regularity conditions are satisfied. Data collected from a manufacturer support the structure and conclusion of the model. Although the model is described in the context of in‐bound logistics, it can be applied to production and out‐bound logistics decisions as well.     

Nonresponse Bias for Attitude Questions

By separating respondents in a survey of farmers into thosewho refused to be interviewed and were converted, those whowere hard to reach, and those who gave no problems, we can estimatenonresponse bias from refusers not converted and respondentsnot reached. We show that for attitude questions the refusalbias is serious, ranging from 2 to 4 percent on many attitudes,and very often larger than the standard error in surveys ofordinary size.