16 resultados para value and price

em Digital Commons at Florida International University


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Online learning systems (OLS) have become center stage for corporations and educational institutions as a competitive tool in the knowledge economy. The satisfaction construct has received extensive coverage in information systems literature as an indicator of effectiveness but has been criticized for lack of validity; yet, the value construct has been largely ignored, although it has a long history in psychology, sociology, and behavioral science. The purpose of this dissertation is to investigate the value and satisfaction constructs in the context of OLS, and their perceived by learners relationship for implied effectiveness of OLS. ^ First, a qualitative phase is employed to gather OLS values from learners' focus groups, followed by a pilot phase to refine a proposed instrument, and a main phase to validate the survey. Responses were received from 75 students in four focus groups, 141 in the pilot, and 207 the main survey. Extensive data cleaning and exploratory factor analysis were done to identify factors of learners' perceived value and satisfaction of OLS. Then, Value-Satisfaction grids and the Learners' Value Index of Satisfaction (LeVIS) were developed as benchmarking tools of OLS. Moreover, Multicriteria Decision Analysis (MCDA) techniques were employed to impute value from satisfaction scores in order to reduce survey response time. ^ The results provided four satisfaction and four value factors with high reliability (Cronbach's α). Moreover, value and satisfaction were found to have low linear and nonlinear correlations, indicating that they are two distinct uncorrelated constructs. This is consistent with the literature. Value-Satisfaction grids and the LeVIS index indicated relatively high effectiveness for technology and support characteristics, relatively low effectiveness for professor's characteristics, while course and learner characteristics indicated average effectiveness. ^ The main contributions of this study include identifying, defining, and articulating the relationship between value and satisfaction constructs as assessment of users' implied IS effectiveness, as well as assessing the accuracy of MCDA procedures to predict value scores, thus reducing by half the survey questionnaire size. ^

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The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. ^ For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver.^ The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. ^ The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.^

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The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver. The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.

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This case study examines the factors that shaped the identity and landscape of a small island-urban-village between the north and south forks of the Middle River and north of an urban area in Broward County, Florida. The purpose of the study is to understand how Wilton Manors was transformed from a “whites only” enclave to the contemporary upscale, diverse, and third gayest city in the U.S. by positing that a dichotomy for urban places exists between their exchange value as seen by Logan and Molotch and the use value produced through everyday activity according to Lefebvre. Qualitative methods were used to gather evidence for reaching conclusions about the relationship among the worldview of residents, the tension between exchange value and use value in the restructuration of the city, and the transformation of Wilton Manors at the end of the 1990s. Semi-structured, in-depth interviews were conducted with 21 contemporary participants. In addition, thirteen taped CDs of selected members of founding families, previously taped in the 1970s, were analyzed using a grounded theory approach. My findings indicate that Wilton Manors’ residents share a common worldview which incorporates social inclusion as a use value, and individual agency in the community. This shared worldview can be traced to selected city pioneers whose civic mindedness helped shape city identity and laid the foundation for future restructuration. Currently, residents’ quality of life reflected in the city’s use value is more significant than exchange value as a primary force in the decisions that are made about the city’s development. With innovative ideas, buildings emulating the new urban mixed-use design, and a reputation as the third gayest city in the United States, Wilton Manors reflects a worldview where residents protect use value as primary over market value in the decisions they make that shape their city but not without contestation.^

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The Mara River Basin (MRB) is endowed with pristine biodiversity, socio-cultural heritage and natural resources. The purpose of my study is to develop and apply an integrated water resource allocation framework for the MRB based on the hydrological processes, water demand and economic factors. The basin was partitioned into twelve sub-basins and the rainfall runoff processes was modeled using the Soil and Water Assessment Tool (SWAT) after satisfactory Nash-Sutcliff efficiency of 0.68 for calibration and 0.43 for validation at Mara Mines station. The impact and uncertainty of climate change on the hydrology of the MRB was assessed using SWAT and three scenarios of statistically downscaled outputs from twenty Global Circulation Models. Results predicted the wet season getting more wet and the dry season getting drier, with a general increasing trend of annual rainfall through 2050. Three blocks of water demand (environmental, normal and flood) were estimated from consumptive water use by human, wildlife, livestock, tourism, irrigation and industry. Water demand projections suggest human consumption is expected to surpass irrigation as the highest water demand sector by 2030. Monthly volume of water was estimated in three blocks of current minimum reliability, reserve (>95%), normal (80–95%) and flood (40%) for more than 5 months in a year. The assessment of water price and marginal productivity showed that current water use hardly responds to a change in price or productivity of water. Finally, a water allocation model was developed and applied to investigate the optimum monthly allocation among sectors and sub-basins by maximizing the use value and hydrological reliability of water. Model results demonstrated that the status on reserve and normal volumes can be improved to ‘low’ or ‘moderate’ by updating the existing reliability to meet prevailing demand. Flow volumes and rates for four scenarios of reliability were presented. Results showed that the water allocation framework can be used as comprehensive tool in the management of MRB, and possibly be extended similar watersheds.

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Three new technologies have been brought together to develop a miniaturized radiation monitoring system. The research involved (1) Investigation a new HgI$\sb2$ detector. (2) VHDL modeling. (3) FPGA implementation. (4) In-circuit Verification. The packages used included an EG&G's crystal(HgI$\sb2$) manufactured at zero gravity, the Viewlogic's VHDL and Synthesis, Xilinx's technology library, its FPGA implementation tool, and a high density device (XC4003A). The results show: (1) Reduced cycle-time between Design and Hardware implementation; (2) Unlimited Re-design and implementation using the static RAM technology; (3) Customer based design, verification, and system construction; (4) Well suited for intelligent systems. These advantages excelled conventional chip design technologies and methods in easiness, short cycle time, and price in medium sized VLSI applications. It is also expected that the density of these devices will improve radically in the near future. ^

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This dissertation examines the behavior of the exchange rate under two different scenarios. The first one is characterized by, relatively, low inflation or a situation where prices adjust sluggishly. The second is a high inflation economy where prices respond very rapidly even to unanticipated shocks. In the first one, following a monetary expansion, the exchange rate overshoots, i.e. the nominal exchange rate depreciates at a faster pace than the price level. Under high levels of inflation, prices change faster than the exchange rate so the exchange rate undershoots its long run equilibrium value.^ The standard work in this area, Dornbusch (1976), explains the overshooting process in the context of perfect capital mobility and sluggish adjustment in the goods market. A monetary expansion will make the exchange rate increase beyond its long run equilibrium value. This dissertation expands on Dornbusch's model and provides an analysis of the exchange rate under conditions of currency substitution and price flexibility, characteristics of the Peruvian economy during the hyper inflation process that took place at the end of the 1980's. The results of the modified Dornbusch model reveal that, given a monetary expansion, the change in the price level will be larger than the change in the exchange rate if prices react more than proportionally to the monetary shock.^ We will expect this over-reaction in circumstances of high inflation when the velocity of money is increasing very rapidly. Increasing velocity of money, gives rise to a higher relative price variability which in turn contributes to the appearance of new financial (and also non-financial) instruments that report a higher return than the exchange rate, causing people to switch their demand for foreign exchange to this new assets. In the context of currency substitution, economic agents hoard and use foreign exchange as a store of value. The big decline in output originated by hyper inflation induces people to sell this hoarded money to finance current expenses, increasing the supply of foreign exchange in the market. Both, the decrease in demand and the increase in supply reduce the price of foreign exchange i.e. the real exchange rate. The findings mentioned above are tested using Peruvian data for the period January 1985-July 1990, the results of the econometric estimation confirm our findings in the theoretical model. ^

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This investigation studied the differences in learning styles among ethnically diverse secondary science students from a multicultural urban high school. It examined whether there were learning style differences among samples based on ethnicity, gender, academic grouping, and academic achievement. The learning style elements were based on scores of the Dunn, Dunn, and Price Learning Style Inventory (LSI) (1997). The sample (n = 476) consisted of students enrolled in Life Science courses. The analyses of data were made by one way analysis of variance (ANOVA) and multivariate analysis of variance (MANOVA). ^ Significant differences were found among students for three of the four groups tested. The largest numbers of differences in learning style element preference were in academic grouping, with eight significant differences showing small or medium effect sizes. There were four significant differences between genders and one significant difference among ethnic groups. Effect size was small. The data analyses showed that individual differences have a much bigger effect than group differences on learning style, and that proportions in learning style element categories reveal more information than means of groups. ^ This study implied the need to increase awareness of differences in learning styles among students and help educators to understand them. Other predictors of learning styles might account for a large amount of the unexplained variation. Overall, this study reinforces the body of existing literature. ^

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Entrepreneurial opportunity recognition is an increasingly prevalent phenomenon. Of particular interest is the ability of promising technology based ventures to recognize and exploit opportunities. Recent research drawing on the Austrian economic theory emphasizes the importance of knowledge, particularly market knowledge, behind opportunity recognition. While insightful, this research has tended to overlook those interrelationships that exist between different types of knowledge (technology and market knowledge) as well as between a firm’s knowledge base and its entrepreneurial orientation. Additional shortfalls of prior research include the ambiguous definitions provided for entrepreneurial opportunities, oversight of opportunity exploitation with an extensive focus on opportunity recognition only, and the lack of quantitative, empirical evidence on entrepreneurial opportunity recognition. ^ In this dissertation, these research gaps are addressed by integrating Schumpeterian opportunity development view with a Kirznerian opportunity discovery theory as well as insights from literature on entrepreneurial orientation. A sample of 85 new biotechnology ventures from the United States, Finland, and Sweden was analyzed. While leaders in all 85 companies were interviewed for the research in 2003-2004, 42 firms provided data in 2007. Data was analyzed using regression analysis. ^ The results show the value and importance of early market knowledge and technology knowledge as well as an entrepreneurial company posture for subsequent opportunity recognition. The highest numbers of new opportunities are recognized in firms where high levels of market knowledge are combined with high levels of technology knowledge (measured with a number of patents). A firm’s entrepreneurial orientation also enhances its opportunity recognition. Furthermore, the results show that new ventures with more market knowledge are able to gather more equity investments, license out more technologies, and achieve higher sales than new ventures with lower levels of market knowledge. Overall, the findings of this dissertation help further our understanding of the sources of entrepreneurial opportunities, and should encourage further research in this area. ^

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We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statistically significant. Specification tests using the correlogram and cross-spectral analyses prove the reliability of the autoregressive conditional filtering process. In essay 2 we develop a new methodology to decompose return variance in order to examine the informativeness embedded in the return series. The variance is decomposed into the information arrival component and the noise factor component. This decomposition methodology differs from previous studies in that both the informational variance and the noise variance are time-varying. Furthermore, the covariance of the informational component and the noisy component is no longer restricted to be zero. The resultant measure of price informativeness is defined as the informational variance divided by the total variance of the returns. The noisy rational expectations model predicts that uninformed traders react to price changes more than informed traders, since uninformed traders cannot distinguish between price changes caused by information arrivals and price changes caused by noise. This hypothesis is tested in essay 3 using intraday data with the intraday seasonal volatility component removed, as based on the procedure in the first essay. The resultant seasonally adjusted variance series is decomposed into components caused by unexpected information arrivals and by noise in order to examine informativeness.

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The profitability of momentum portfolios in the equity markets is derived from the continuation of stock returns over medium time horizons. The empirical evidence of momentum, however, is significantly different across markets around the world. The purpose of this dissertation is to: (1) help global investors determine the optimal selection and holding periods for momentum portfolios, (2) evaluate the profitability of the optimized momentum portfolios in different time periods and market states, (3) assess the investment strategy profits after considering transaction costs, and (4) interpret momentum returns within the framework of prior studies on investors’ behavior. Improving on the traditional practice of selecting arbitrary selection and holding periods, a genetic algorithm (GA) is employed. The GA performs a thorough and structured search to capture the return continuations and reversals patterns of momentum portfolios. Three portfolio formation methods are used: price momentum, earnings momentum, and earnings and price momentum and a non-linear optimization procedure (GA). The focus is on common equity of the U.S. and a select number of countries, including Australia, France, Germany, Japan, the Netherlands, Sweden, Switzerland and the United Kingdom. The findings suggest that the evolutionary algorithm increases the annualized profits of the U.S. momentum portfolios. However, the difference in mean returns is statistically significant only in certain cases. In addition, after considering transaction costs, both price and earnings and price momentum portfolios do not appear to generate abnormal returns. Positive risk-adjusted returns net of trading costs are documented solely during “up” markets for a portfolio long in prior winners only. The results on the international momentum effects indicate that the GA improves the momentum returns by 2 to 5% on an annual basis. In addition, the relation between momentum returns and exchange rate appreciation/depreciation is examined. The currency appreciation does not appear to influence significantly momentum profits. Further, the influence of the market state on momentum returns is not uniform across the countries considered. The implications of the above findings are discussed with a focus on the practical aspects of momentum investing, both in the U.S. and globally.

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In the article - Menu Analysis: Review and Evaluation - by Lendal H. Kotschevar, Distinguished Professor School of Hospitality Management, Florida International University, Kotschevar’s initial statement reads: “Various methods are used to evaluate menus. Some have quite different approaches and give different information. Even those using quite similar methods vary in the information they give. The author attempts to describe the most frequently used methods and to indicate their value. A correlation calculation is made to see how well certain of these methods agree in the information they give.” There is more than one way to look at the word menu. The culinary selections decided upon by the head chef or owner of a restaurant, which ultimately define the type of restaurant is one way. The physical outline of the food, which a patron actually holds in his or her hand, is another. These descriptions are most common to the word, menu. The author primarily concentrates on the latter description, and uses the act of counting the number of items sold on a menu to measure the popularity of any particular item. This, along with a formula, allows Kotschevar to arrive at a specific value per item. Menu analysis would appear a difficult subject to broach. How does a person approach a menu analysis, how do you qualify and quantify a menu; it seems such a subjective exercise. The author offers methods and outlines on approaching menu analysis from empirical perspectives. “Menus are often examined visually through the evaluation of various factors. It is a subjective method but has the advantage of allowing scrutiny of a wide range of factors which other methods do not,” says Distinguished Professor, Kotschevar. “The method is also highly flexible. Factors can be given a score value and scores summed to give a total for a menu. This allows comparison between menus. If the one making the evaluations knows menu values, it is a good method of judgment,” he further offers. The author wants you to know that assigning values is fundamental to a pragmatic menu analysis; it is how the reviewer keeps score, so to speak. Value merit provides reliable criteria from which to gauge a particular menu item. In the final analysis, menu evaluation provides the mechanism for either keeping or rejecting selected items on a menu. Kotschevar provides at least three different matrix evaluation methods; they are defined as the Miller method, the Smith and Kasavana method, and the Pavesic method. He offers illustrated examples of each via a table format. These are helpful tools since trying to explain the theories behind the tables would be difficult at best. Kotschevar also references examples of analysis methods which aren’t matrix based. The Hayes and Huffman - Goal Value Analysis - is one such method. The author sees no one method better than another, and suggests that combining two or more of the methods to be a benefit.

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In the discussion - Indirect Cost Factors in Menu Pricing – by David V. Pavesic, Associate Professor, Hotel, Restaurant and Travel Administration at Georgia State University, Associate Professor Pavesic initially states: “Rational pricing methodologies have traditionally employed quantitative factors to mark up food and beverage or food and labor because these costs can be isolated and allocated to specific menu items. There are, however, a number of indirect costs that can influence the price charged because they provide added value to the customer or are affected by supply/demand factors. The author discusses these costs and factors that must be taken into account in pricing decisions. Professor Pavesic offers as a given that menu pricing should cover costs, return a profit, reflect a value for the customer, and in the long run, attract customers and market the establishment. “Prices that are too high will drive customers away, and prices that are too low will sacrifice profit,” Professor Pavesic puts it succinctly. To dovetail with this premise the author provides that although food costs measure markedly into menu pricing, other factors such as equipment utilization, popularity/demand, and marketing are but a few of the parenthetic factors also to be considered. “… there is no single method that can be used to mark up every item on any given restaurant menu. One must employ a combination of methodologies and theories,” says Professor Pavesic. “Therefore, when properly carried out, prices will reflect food cost percentages, individual and/or weighted contribution margins, price points, and desired check averages, as well as factors driven by intuition, competition, and demand.” Additionally, Professor Pavesic wants you to know that value, as opposed to maximizing revenue, should be a primary motivating factor when designing menu pricing. This philosophy does come with certain caveats, and he explains them to you. Generically speaking, Professor Pavesic says, “The market ultimately determines the price one can charge.” But, in fine-tuning that decree he further offers, “Lower prices do not automatically translate into value and bargain in the minds of the customers. Having the lowest prices in your market may not bring customers or profit. “Too often operators engage in price wars through discount promotions and find that profits fall and their image in the marketplace is lowered,” Professor Pavesic warns. In reference to intangibles that influence menu pricing, service is at the top of the list. Ambience, location, amenities, product [i.e. food] presentation, and price elasticity are discussed as well. Be aware of price-value perception; Professor Pavesic explains this concept to you. Professor Pavesic closes with a brief overview of a la carte pricing; its pros and cons.

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Entrepreneurial opportunity recognition is an increasingly prevalent phenomenon. Of particular interest is the ability of promising technology based ventures to recognize and exploit opportunities. Recent research drawing on the Austrian economic theory emphasizes the importance of knowledge, particularly market knowledge, behind opportunity recognition. While insightful, this research has tended to overlook those interrelationships that exist between different types of knowledge (technology and market knowledge) as well as between a firm’s knowledge base and its entrepreneurial orientation. Additional shortfalls of prior research include the ambiguous definitions provided for entrepreneurial opportunities, oversight of opportunity exploitation with an extensive focus on opportunity recognition only, and the lack of quantitative, empirical evidence on entrepreneurial opportunity recognition. In this dissertation, these research gaps are addressed by integrating Schumpeterian opportunity development view with a Kirznerian opportunity discovery theory as well as insights from literature on entrepreneurial orientation. A sample of 85 new biotechnology ventures from the United States, Finland, and Sweden was analyzed. While leaders in all 85 companies were interviewed for the research in 2003-2004, 42 firms provided data in 2007. Data was analyzed using regression analysis. The results show the value and importance of early market knowledge and technology knowledge as well as an entrepreneurial company posture for subsequent opportunity recognition. The highest numbers of new opportunities are recognized in firms where high levels of market knowledge are combined with high levels of technology knowledge (measured with a number of patents). A firm’s entrepreneurial orientation also enhances its opportunity recognition. Furthermore, the results show that new ventures with more market knowledge are able to gather more equity investments, license out more technologies, and achieve higher sales than new ventures with lower levels of market knowledge. Overall, the findings of this dissertation help further our understanding of the sources of entrepreneurial opportunities, and should encourage further research in this area.

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The profitability of momentum portfolios in the equity markets is derived from the continuation of stock returns over medium time horizons. The empirical evidence of momentum, however, is significantly different across markets around the world. The purpose of this dissertation is to: 1) help global investors determine the optimal selection and holding periods for momentum portfolios, 2) evaluate the profitability of the optimized momentum portfolios in different time periods and market states, 3) assess the investment strategy profits after considering transaction costs, and 4) interpret momentum returns within the framework of prior studies on investors’ behavior. Improving on the traditional practice of selecting arbitrary selection and holding periods, a genetic algorithm (GA) is employed. The GA performs a thorough and structured search to capture the return continuations and reversals patterns of momentum portfolios. Three portfolio formation methods are used: price momentum, earnings momentum, and earnings and price momentum and a non-linear optimization procedure (GA). The focus is on common equity of the U.S. and a select number of countries, including Australia, France, Germany, Japan, the Netherlands, Sweden, Switzerland and the United Kingdom. The findings suggest that the evolutionary algorithm increases the annualized profits of the U.S. momentum portfolios. However, the difference in mean returns is statistically significant only in certain cases. In addition, after considering transaction costs, both price and earnings and price momentum portfolios do not appear to generate abnormal returns. Positive risk-adjusted returns net of trading costs are documented solely during “up” markets for a portfolio long in prior winners only. The results on the international momentum effects indicate that the GA improves the momentum returns by 2 to 5% on an annual basis. In addition, the relation between momentum returns and exchange rate appreciation/depreciation is examined. The currency appreciation does not appear to influence significantly momentum profits. Further, the influence of the market state on momentum returns is not uniform across the countries considered. The implications of the above findings are discussed with a focus on the practical aspects of momentum investing, both in the U.S. and globally.