At a midwestern university, 1,805 undergraduate students completed a student satisfaction survey that used Likert-type scales and provided, for each item, an importance score for college experiences, a satisfaction score, and a performance gap score determined by subtracting the performance score from the satisfaction score for each individual item. The survey offered greater diagnostic value than alternative surveys that ask for simple "yes" or "no" responses. Stepwise regression analysis revealed that most strongly related to student satisfaction with university performance were excellence of instruction in major, ability to get desired classes, knowledgeable adviser, knowledgeable faculty, overall quality of instruction, perception that tuition paid was a worthwhile investment, approachable adviser, safe and secure campus, clear and reasonable requirements for major, availability of adviser, adequate computer labs, fair and unbiased faculty, and access to information. (15 ref)-

Recognizing the drawbacks associated with the traditional approach of measuring customers' overall satisfaction, which simply relies on a single-item measurement of overall satisfaction, an alternative approach is presented. The proposed approach utilizes: all product/service attributes, each customer's varying degree of satisfaction with the attributes, and the relative importance of each attribute obtained and analyzed from all customers who participated in the survey. Each customer's overall satisfaction is then determined by a weighted average of the gap between a customer's expectation of performance (importance rating) and actual experience (performance rating) for each attribute, and the relative importance of each attribute as perceived by the total customer group. A comparison between a singleitem approach and multi-attributes approach along with an illustrated example is also presented using the customer satisfaction data from the airlineindustry.[ArticlecopiesavailableforafeefromTheHaworthDocument DeliveryService: 1-800-342-9678. E-mail address: Website:E2001byTheHaworthPress, Inc. All rights reserved.]

Since the advent of group technology (GT) as a primary manufacturing tool for reducing setup times and improving production efficiencies, its central theme has been the grouping of similar parts into part families and machines into machine cells. Although the formation of machine-part manufacturing cells is the essence of GT, its full benefits cannot be gained without forming 'human' cells in such a way that machine operators with similar expertiseand skills are brought together to produce similar part families. Nevertheless, much of the existingGT literature overlooks the behavioural issues associated with a group of workers in the machine cell. This paper addresses such issues by simultaneously forming both machine and compatible human cells. In so doing, we develop a multiple objective model that enables us to analyse the tradeoff between economic and behavioural benefits.

No abstract

Recognising the enormous potential of just‐in‐time (JIT) concepts for boosting productivity and quality, an increasing number of US and European firms consider adopting JIT concepts in manufacturing. However, the transfer of a manufacturing policy from traditional to JIT always requires radical structural changes in a production line design. One typical example of these changes is uniform assembly which does not allow high variability in the production schedules. Consequently, major hindrance to uniform assembly is a random fluctuation of task processing times in assembly line balancing. This article proposes a heuristic which takes into account stochastic task processing times and further develops a work assignment with the lowest expected total cost as well as an assignment with the highest work completion probability crucial for the success of JIT manufacturing.