2 resultados para Business process performance
em University of Connecticut - USA
Resumo:
Many students are inspired to start their own business venture after taking some courses in school or simply just taking an idea and turning it into a business. The beginning process is usually most difficult in terms of establishing a functioning business, getting the right connections, and avoiding discouragement to follow through with the business. That is why many businesses fall into the categories of starting, failing along the process, or failing to get started. There is a lot to be learned from the process of starting a business venture. In addressing this issue, some of the questions this research study aims to explore and study are how people go about their new venture efforts? Second, what steps they undertake? Third, from whom do they get information? And fourth, how do they use that information? This study will seek a variety of insights that can help answer these questions and improve our understanding of why some businesses fail, succeed, or never get started.
Resumo:
Dua and Miller (1996) created leading and coincident employment indexes for the state of Connecticut, following Moore's (1981) work at the national level. The performance of the Dua-Miller indexes following the recession of the early 1990s fell short of expectations. This paper performs two tasks. First, it describes the process of revising the Connecticut Coincident and Leading Employment Indexes. Second, it analyzes the statistical properties and performance of the new indexes by comparing the lead profiles of the new and old indexes as well as their out-of-sample forecasting performance, using the Bayesian Vector Autoregressive (BVAR) method. The new indexes show improved performance in dating employment cycle chronologies. The lead profile test demonstrates that superiority in a rigorous, non-parametric statistic fashion. The mixed evidence on the BVAR forecasting experiments illustrates the truth in the Granger and Newbold (1986) caution that leading indexes properly predict cycle turning points and do not necessarily provide accurate forecasts except at turning points, a view that our results support.