Browsing by Subject "Labor productivity"
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Item Analysis of clean room conditions impact on labor productivity : case study(2012-05) Woo, Jeyoung; Borcherding, John D.; O'Connor, James ThomasThe semiconductor industry follows what is known as Moore’s Law. Moore’s Law says that every 18 months computer chip storage capacity doubles and the intervals between developments in chip design become shorter and shorter. This is also true for the set dates for construction which are dictated by the semiconductor industry’s needs and production schedule. This paper analyzes the impact of a clean room environment. It scrutinizes daily reports and interviews, based on two data sets that focus on a semiconductor wafer fabrication facility (FAB) construction project. Both data sets involve the same crew working on a FAB construction project in the U.S. Room conditions, however, differ. Aside from such working conditions, all elements for both groups are the same (crew skill level, weather, and season). This research is based on the installation, from February 2010 to January 2011 in Austin, Texas, of an access floor in a semiconductor FAB construction project. The total cost of the project was US$3.6 billion. Generally, a semiconductor FAB has raised access floors because cables and pipes are laid under the floors for maintenance and operation purposes. The data for this paper is derived from the access floor installation. The project manager’s daily progress record documented the changes in labor productivity. The data on the number of crew and work-hours is computed based on this information. Labor productivity is defined here as the relationship between output and the labor time for its production. The formula is as follows: Labor productivity = Output(Quantity) / Input(Work-hours) Eq. (1) This study used Eq. (1) to measure labor productivity for two conditions (working in general conditions and working in a clean room conditions). Labor productivity was computed as follows: the unit of output (quantity) is sq. ft., and the unit of input (work-hours) is hours. The questionnaires and interviews attempted to identify the factors affecting project performance: rework, crew interference, overcrowded work areas, and overtime (Garner, et al., 1979; Tucker, et al., 1980). Each section consisted of yes/no questions and one question seeking the interviewee’s opinion about how each problem was solved. The responses are summarized as follows: The results indicate that, in the clean room environment, labor productivity fell by 28.85%. For future projects, this drop represents additional time and money that should be taken into account in the estimate of costs and the schedule duration. The interviews indicate that labor productivity was affected by other factors such as rework, tool availability, other crews not being finished, overcrowded work areas, as well as access to work area.Item Essays in applied econometrics(2015-05) Senturk, Rifat Ozan; Trejo, Stephen J., 1959-; Dusansky, Richard; Heinrich, Carolyn; Kline, Brendan; Oettinger, Gerald SThis dissertation consists of three essays in applied econometrics that analyze the strategic interactions between individuals and institutions. The first chapter examines the relationship between employee benefits and the performance of startups. Using national longitudinal data on startups, I find that an increase in the share of employee benefits in total compensation packages leads to increased productivity of startups. Results indicate that a 10 percent increase in the share of employee benefits leads to an increase ranging from 1.5 to 3.9 percent in productivity even if the returns to the employee benefits are heterogeneous across startups. I also find that an increase in the share of employee benefits increases the chance of survival of startups. The second chapter investigates the dynamics of employee screening and transitions from temporary to permanent employment. I analyze unique German data that contains specific information about the dynamics of the transition from temporary to permanent employment, I find that employers screen the abilities of employees only before they hire them. I find no evidence that employers screen the cognitive ability of employees during temporary employment. The third chapter examines the relationship between housing prices and the availability of curbside parking. Using a policy change in Istanbul as a quasi-experiment, this chapter explores the effect of Istanbul’s switch from informal and free curbside parking to formal and paid curbside parking on housing prices. In a differences-in-differences model coupled with a propensity score matching, we find that an exogenous change in the availability of parking leads to a statistically significant decrease in house prices. We estimate that house prices per square meter decrease by 13 percent in the neighborhoods where the city starts charging curbside parking spaces. However, rents stay the same compared to the other neighborhoods.Item Motivation and productivity in small, task-oriented groups(Texas Tech University, 1986-12) McDonald-Pierce, Linda GThe Worker Motivation Scale (WMS) was developed to assess the interactional styles of individuals in groups (Johnson, McDonald, & George, 1984). Three styles were identified. These were Team Motivation (TM), Prominence Motivation (PM), and Affiliation Motivation (AM). TM scores have been used successfully to predict helping behavior among group members. Members high in TM were more helpful than members low in TM. Group cohesion level and group norms have also been proposed as important helping behavior predictors. The present experiment was designed to examine the relationship among TM, cohesion, and norms for predicting helping behavior in small, task-oriented groups. Two students and one confederate participated in an interdependent task. The confederate, working slowly, created the situation in which help was needed. Students could increase group productivity by choosing to help the confederate, or choose not to help and continue to work on their own portion of the task. Results indicate, that regardless of TM or normatively prescribed behavior, students in highly cohesive groups were more helpful than students in groups low in cohesion [F(l, 76) = 3.74, p < .05, one tail]. These unexpected results were due to several factors. The designed task was too difficult. Only students extremely skilled at operating a calculator had the ability to improve the group's productivity. The selection procedure used created an artifactual negative correlation between TM and PM in the students chosen. Research has shown these scales to be independent. Choosing students in such a way as to produce the negative relationship between TM and PM negated the effect of TM. Finally, students assigned to the high TM, low cohesion condition were higher in AM than students in the other conditions. Theoretically, students high in AM are more affected by cohesiveness than are students moderate or low in AM. The effects of varying levels of TM, PM, and AM on group members' behavior is not fully understood. Future researchers will need to beware of possible differential effects. It is clear, however, that group cohesion is an important predictor of group effectiveness.Item Rapid and contextual activity analysis : a semi-automated activity category, time, location, and video data collection and analysis methodology(2015-08) Kim, Jung Yeol; Caldas, Carlos H.; Borcherding, John D; Leite, Fernanda; Grauman, Kristen; Zhang, ZhanminThe performance of construction projects is significantly impacted by on-site labor and the productivity thereof. Despite the benefits from technological advancements in recent decades, construction projects are still labor intensive, and labor is one of the most flexible and largest cost factors in a construction project. Thus, a major concern of construction project management has been labor productivity and its improvement. To improve it, labor productivity must be measured and analyzed. One way of doing so is through activity analysis - known as an extension of traditional work sampling. Activity analysis measures the efficiency of the workers' time usage at a construction site. Increasing labor efficiency usually has a positive relationship with higher construction labor productivity. Therefore, activity analysis is considered a major labor performance assessment technique in this research. The objective of this research is to develop a semi-automated data collection and analysis methodology to enable fast and contextual activity analysis. More specifically, this research focuses on the man-machine balanced on-site data collection and the automated data analysis with abundant contextual information to support the interpretation of analysis results for labor productivity improvement study. The prototype of the proposed methodology is implemented and validated with actual datasets from different construction sites. The prototype system proves capable of collecting data efficiently at construction sites and to analyze it in an automatic fashion. This system is shown to provide abundant contextual information related to the activity analysis results. A project manager can quickly and easily find issues related to their high or low labor performance with various scenarios. The indexed videos also successfully provide information about what/how construction workers were performing work at that point. This information can support productivity improvement planning and expedite the continuous evaluation and improvement process of activity analysis to improve labor productivity.