A methodology to measure coordination of business processes

Coordination of business processes is the management of dependencies where dependencies constrain how the tasks are performed. It has been traditionally done in an intuitive fashion, without paying much attention to the coordination load. Coordination load is being defined as the ratio between the time spent on coordination activities and the total task time. Previous efforts to understand and analyze coordination have resulted in mostly qualitative approaches to categorize and recommend coordination strategies. This research seeks to answer two questions: (1) How can we analyze process coordination problems to improve overall performance? (2) What guidance can we provide to reduce the coordination load of the process and consequently improve the organization's performance? Thus, this effort developed a quantitative measure for coordination load of business processes and a methodology to apply such measure. ^ This effort used a management simulation game to have a controlled laboratory environment enabling the manipulation of the task factors variability, analyzability, and interdependence to measure their impact on coordination load. The hypothesis was that the more variable, non-analyzable, and interdependent a process, the higher the coordination load, and that a higher coordination load would have a negative impact on performance. Coordination load was measured via the surrogate coordination time, and performance via profit. ^ A 22 x 31 full factorial design, with two replicates, was run to observe the impact on the variables coordination time and profit. Properly validated spreadsheets and questionnaires were used as data collection instruments for each scenario. The experimental results indicate that lower task analyzability (ρ=0.036) and higher task interdependence (ρ=0.000) lead to higher coordination load, and higher levels of task variability (ρ=0.049) lead to lower performance. However, contrary to the hypotheses postulated by this work, coordination load did not prove to be strong predictor of performance (correlation of -0.086). ^ These findings from the laboratory experiment and other lessons learned were incorporated to develop a quantitative measure, a tool (survey) to use to gather data for the variables in the measures, and a methodology to quantify coordination load of production business processes. The practicality of the methodology is demonstrated with an example.^

A study of stock market fluctuations and their relation to business conditions

Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubblelike deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the nonfundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.

Effects of computer self efficacy and positive mood in business -to -business service encounters

Attempts to improve the level of customer service delivered have resulted in an increased use of technology in the customer service environment. Customer-contact employees are expected to use computers to help them in providing better service encounters for customers. This research study done in a business-to-business environment explored the effects of customer-contact employees' computer self efficacy and positive mood on in-role customer service, extra-role customer service and organization citizenship. It also examined the relationship of customer service to customer satisfaction and customer delight. ^ Research questions were analyzed using descriptive statistics, frequency distributions, correlation analysis, and regression analysis. Results indicated that computer self efficacy had a greater impact on extra-role customer service than it did on in-role customer service. Positive mood had a positive moderating influence on extra-role customer service but not on in-role customer service. ^ There was a significant relationship between in-role customer service and customer satisfaction but not between extra-role customer service and customer satisfaction. There was no significant relationship between in-role customer service and customer delight nor between extra-role customer service and customer delight. There was a statistically greater positive relationship between joy experienced by clients and customer delight than between pleasant surprise and customer delight. ^ This study demonstrated the importance of facilitating customer-contact employee positive mood on the job in order to improve the level of extra-role customer service delivered. It also showed that increasing the level of customer service does not necessarily lead to higher levels of customer satisfaction. ^

A Study of Stock Market Fluctuations and their Relations to Business Conditions

Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubble-like deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the non-fundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.

A study to identify the motivation compelling the business traveler to choose a specific airline in the Miami to Atlanta market and to develop a marketing strategy

The purpose of this study was to determine if the business traveler's behavior is influenced by brand loyalty. This brand loyalty, which became evident through the use of a survey, was then to be thoroughly evaluated. In order for this information to be best understood and utilized as the basis of future marketing strategies, much research was undertaken and its significance explained in relation to the airline industry as it exists at present. The results and conclusions of this study indicate that the airline industry is, for the most part, taking a successful approach in attracting business travelers. These travelers' business is highly valued due to the frequency with which they pay full-fare rates. The airlines view business travelers as a potential for great profit and their actions are in line with these philosophies.