25 resultados para Market Study

em Digital Commons at Florida International University


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The purpose of this research is to study the commercialization of Fairtrade and Organic coffee in the Bolivia. Fairtrade and Organic coffee are alternative trade systems designed to promote the equitable and environmentally sustainable production of coffee. However, these alternative trading systems often fail to meet these goals. The producers and environment these systems are intended to protect remain marginalized. These failures are due to a number of local institutions. In order to better understand these institutions, this research conducted interviews of various stakeholders including producers, cooperative leaders, organic/Fair Trade certifiers, government agencies and private buyers. All these stakeholders influence the success of the alternative trade systems. By better understanding how these stakeholders impact the commercialization of coffee in Bolivia; new policies can be develop to improve the outcomes of alternative trade, to benefit both producers and the environment. This is especially critical in Bolivia because of the environmentally sensitive area in which coffee is grown, the potentially damaging impact of coca on the region and, the devastating economic impact to farmers.

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This study examines the role of race, socioeconomic status, and individualism-collectivism as moderators of the relationship between selected work and family antecedents and work-family conflict and evaluates the contribution of energy-based conflict to the work-family conflict (WFC) research. The study uses data obtained from a survey questionnaire given to 414 participants recruited from an online labor market. Study hypotheses were tested through structural equation modeling. The results indicate that while moderating effects were slight, a proposed model where energy-based conflict is included outperforms traditional time/strain/behavior-based models and that established variables may drop to non-significance when additional variables are included in prediction. In addition, novel individual difference variables such as individualism and collectivism were demonstrated to have effects beyond moderating antecedent-outcome relationships in the model. The findings imply that WFC models would benefit from the inclusion of variables found in the current study.

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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.

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Bankruptcy prediction has been a fruitful area of research. Univariate analysis and discriminant analysis were the first methodologies used. While they perform relatively well at correctly classifying bankrupt and nonbankrupt firms, their predictive ability has come into question over time. Univariate analysis lacks the big picture that financial distress entails. Multivariate discriminant analysis requires stringent assumptions that are violated when dealing with accounting ratios and market variables. This has led to the use of more complex models such as neural networks. While the accuracy of the predictions has improved with the use of more technical models, there is still an important point missing. Accounting ratios are the usual discriminating variables used in bankruptcy prediction. However, accounting ratios are backward-looking variables. At best, they are a current snapshot of the firm. Market variables are forward-looking variables. They are determined by discounting future outcomes. Microstructure variables, such as the bid-ask spread, also contain important information. Insiders are privy to more information that the retail investor, so if any financial distress is looming, the insiders should know before the general public. Therefore, any model in bankruptcy prediction should include market and microstructure variables. That is the focus of this dissertation. The traditional models and the newer, more technical models were tested and compared to the previous literature by employing accounting ratios, market variables, and microstructure variables. Our findings suggest that the more technical models are preferable, and that a mix of accounting and market variables are best at correctly classifying and predicting bankrupt firms. Multi-layer perceptron appears to be the most accurate model following the results. The set of best discriminating variables includes price, standard deviation of price, the bid-ask spread, net income to sale, working capital to total assets, and current liabilities to total assets.

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My dissertation investigates the financial linkages and transmission of economic shocks between the US and the smallest emerging markets (frontier markets). The first chapter sets up an empirical model that examines the impact of US market returns and conditional volatility on the returns and conditional volatilities of twenty-one frontier markets. The model is estimated via maximum likelihood; utilizes the GARCH model of errors, and is applied to daily country data from the MSCI Barra. We find limited, but statistically significant exposure of Frontier markets to shocks from the US. Our results suggest that it is not the lagged US market returns that have impact; rather it is the expected US market returns that influence frontier market returns The second chapter sets up an empirical time-varying parameter (TVP) model to explore the time-variation in the impact of mean US returns on mean Frontier market returns. The model utilizes the Kalman filter algorithm as well as the GARCH model of errors and is applied to daily country data from the MSCI Barra. The TVP model detects statistically significant time-variation in the impact of US returns and low, but statistically and quantitatively important impact of US market conditional volatility. The third chapter studies the risk-return relationship in twenty Frontier country stock markets by setting up an international version of the intertemporal capital asset pricing model. The systematic risk in this model comes from covariance of Frontier market stock index returns with world returns. Both the systematic risk and risk premium are time-varying in our model. We also incorporate own country variances as additional determinants of Frontier country returns. Our results suggest statistically significant impact of both world and own country risk in explaining Frontier country returns. Time-variation in the world risk premium is also found to be statistically significant for most Frontier market returns. However, own country risk is found to be quantitatively more important.

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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.

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Introduction: The United States today has become "meeting-conscious." The complexity of conducting business has led to the need for sophisticated coordination of decision-making processes on all levels of the organization. Company meetings have played an increasingly important role in the success and future of many companies. Strategies and decisions are developed at meetings that can determine future policies of crucial importance. Executive training can mean the difference in whether the company will even survive. Large and growing companies have increased their off-premise meeting budgets annually in spite of the state of the economy. however, the rising costs of travel and lodging have made management monitor these budgets more closely than ever. Thus, the need to use every dollar efficiently has compelled companies to examine newer methods of running meetings and alternatives to the usage of typical off-premise meeting facilities. The importance of off-premise meetings in the United States economy has greatly increased due to the billions of dollars spent annually. These factors make it vital to explore the effectiveness of time and monetary expenditures. Up until the mid-1960's, company meetings were held in facilities of various design and purpose, none of which were specifically designed for the small to medium corporate meeting. Upon gathering information concerning the meetings market and the corporate meeting planner, certain individuals endeavored to change the situation. This study is designed to investigate this new concept, which will hereafter be referred to as "conference center." For the purpose of this study, the following two definitions will be used. 1. Conference center - that meeting facility primarily marketing its facilities for the small to medium-sized corporate meeting. The center is operated by specialists aware of market needs in as much detail as are those people working for the company involved. On-premise sleeping rooms are not mandatory provided such facilities are within easy access. 2. Meeting planner - that person within an organization who has primary responsibility for arranging off-premise meetings and all other related items necessary for meeting effectiveness. This person may spend anywhere from 10 to 100l of his time in this capacity. The conference center has effectively satisfied the need for specialized corporate meeting facilities. This study will show the depth of the corporate meetings market and trace the growth and development of this relatively new conference center concept. Information will also be compiled on the top centers in the country. It is hoped that by presenting this research meeting planners will become more aware of the nature and location of these centers, especially for use by the small to medium-sized company. Such exposure of the centers will hopefully increase existing demand and enable the construction of new, innovative centers.

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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.

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This dissertation analyzes how marketers define markets in technology-based industries. One of the most important strategic decisions marketers face is determining the optimal market for their products. Market definition is critical in dynamic high technology markets characterized by high levels of market and technological uncertainty. Building on literature from marketing and related disciplines, this research is the first in-depth study of market definition in industrial markets. Using a national, probability sample stratified by firm size, 1,000 marketing executives in nine industries (automation, biotechnology, computers, medical equipment and instrumentation, pharmaceuticals, photonics, software, subassemblies and components, and telecommunications) were surveyed via a mail questionnaire. A 20.8% net response rate yielding 203 surveys was achieved. The market structure-conduct-performance (SCP) paradigm from industrial organization provided a conceptual basis for testing a causal market definition model via LISREL. A latent exogenous variable (competitive intensity) and four latent endogenous variables (marketing orientation, technological orientation, market definition criteria, and market definition success) were used to develop and test hypothesized relationships among constructs. Research questions relating to market redefinition, market definition characteristics, and internal (within the firm) and external (competitive) market definition were also investigated. Market definition success was found to be positively associated with a marketing orientation and the use of market definition criteria. Technological orientation was not significantly related to market definition success. Customer needs were the key market definition characteristic to high-tech firms (technology, competition, customer groups, and products were also important). Market redefinition based on changing customer needs was the most effective of seven strategies tested. A majority of firms regularly defined their market at the corporate and product-line level within the firm. From a competitive perspective, industry, industry sector, and product-market definitions were used most frequently.

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Extreme stock price movements are of great concern to both investors and the entire economy. For investors, a single negative return, or a combination of several smaller returns, can possible wipe out so much capital that the firm or portfolio becomes illiquid or insolvent. If enough investors experience this loss, it could shock the entire economy. An example of such a case is the stock market crash of 1987. Furthermore, there has been a lot of recent interest regarding the increasing volatility of stock prices. ^ This study presents an analysis of extreme stock price movements. The data utilized was the daily returns for the Standard and Poor's 500 index from January 3, 1978 to May 31, 2001. Research questions were analyzed using the statistical models provided by extreme value theory. One of the difficulties in examining stock price data is that there is no consensus regarding the correct shape of the distribution function generating the data. An advantage with extreme value theory is that no detailed knowledge of this distribution function is required to apply the asymptotic theory. We focus on the tail of the distribution. ^ Extreme value theory allows us to estimate a tail index, which we use to derive bounds on the returns for very low probabilities on an excess. Such information is useful in evaluating the volatility of stock prices. There are three possible limit laws for the maximum: Gumbel (thick-tailed), Fréchet (thin-tailed) or Weibull (no tail). Results indicated that extreme returns during the time period studied follow a Fréchet distribution. Thus, this study finds that extreme value analysis is a valuable tool for examining stock price movements and can be more efficient than the usual variance in measuring risk. ^

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The purpose of this dissertation is to examine the role played by merchants in the shaping of South Carolina plantation society in its early stages of development. In 1700 South Carolina was on the fringes of the British Empire. By mid-century the colony had become an integral part of the British Atlantic system. This dissertation addresses merchants' activity in the shaping of plantation society through their involvement in the Atlantic slave trade. Records of the British and South Carolina governments, and petitions from merchants on both sides of the Atlantic have been extremely valuable in understanding the complex and rapidly changing political affiliations of merchants on both sides of the Atlantic. These sources are valuable to this study since they illustrate the merchants' strategy of utilizing government policies to acquire the absolute best terms of trade. Records such as wills and inventories yielded valuable information on merchants' economic portfolios and provided valuable insight into their personal lives. The data shows that the integration of Colonial South Carolina into the global economy can be attributed to its merchant class, who actively sought out business opportunities in the global economy while working within the framework of British mercantilism.

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The increase in the number of financial restatements in recent years has resulted in a significant decrease in the amount of market capitalization for restated companies. Prior literature did not differentiate between single and multiple restatements announcements. This research investigated the inter-relationships among multiple financial restatements, corporate governance, market microstructure and the firm’s rate of return in the form of three essays by differentiating between single and multiple restatement announcement companies. First essay examined the stock performance of companies announcing the financial restatement multiple times. The postulation is that prior research overestimates the abnormal return by not separating single restatement companies from multiple restatement companies. This study investigated how market penalizes the companies that announce restatement more than once. Differentiating the restatement announcement data based on number of restatement announcements, the results supported the non persistence hypothesis that the market has no memory and negative abnormal returns obtained after each of the restatement announcements are completely random. Second essay examined the multiple restatement announcements and its perceived resultant information asymmetry around the announcement day. This study examined the pattern of information asymmetry for these announcements in terms of whether the bid-ask spread widens around the announcement day. The empirical analysis supported the hypotheses that the spread does widen not only around the first restatement announcement day but around every subsequent announcement days as well. The third essay empirically examined the financial and corporate governance characteristics of single and multiple restatement announcements companies. The analysis showed that corporate governance variables influence the occurrence of multiple restatement announcements and can distinguish multiple restatements announcement companies from single restatement announcement companies.

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This study describes the case of private higher education in Ohio between 1980 and 2006 using Zumeta's (1996) model of state policy and private higher education. More specifically, this study used case study methodology and multiple sources to demonstrate the usefulness of Zumeta's model and illustrate its limitations. Ohio served as the subject state and data for 67 private, 4-year, degree-granting, Higher Learning Commission-accredited institutions were collected. Data sources for this study included the National Center for Education Statistics Integrated Postsecondary Data System as well as database information and documents from various state agencies in Ohio, including the Ohio Board of Regents. ^ The findings of this study indicated that the general state context for higher education in Ohio during the study time period was shaped by deteriorating economic factors, stagnating population growth coupled with a rapidly aging society, fluctuating state income and increasing expenditures in areas such as corrections, transportation and social services. However, private higher education experienced consistent enrollment growth, an increase in the number of institutions, widening involvement in state-wide planning for higher education, and greater fiscal support from the state in a variety of forms such as the Ohio Choice Grant. This study also demonstrated that private higher education in Ohio benefited because of its inclusion in state-wide planning and the state's decision to grant state aid directly to students. ^ Taken together, this study supported Zumeta's (1996) classification of Ohio as having a hybrid market-competitive/central-planning policy posture toward private higher education. Furthermore, this study demonstrated that Zumeta's model is a useful tool for both policy makers and researchers for understanding a state's relationship to its private higher education sector. However, this study also demonstrated that Zumeta's model is less useful when applied over an extended time period. Additionally, this study identifies a further limitation of Zumeta's model resulting from his failure to define "state mandate" and the "level of state mandates" that allows for inconsistent analysis of this component. ^

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This research examined the factors contributing to the performance of online grocers prior to, and following, the 2000 dot.com collapse. The primary goals were to assess the relationship between a company’s business model(s) and its performance in the online grocery channel and to determine if there were other company and/or market related factors that could account for company performance. ^ To assess the primary goals, a case based theory building process was utilized. A three-way cross-case analysis comprising Peapod, GroceryWorks, and Tesco examined the common profit components, the structural category (e.g., pure-play, partnership, and hybrid) profit components, and the idiosyncratic profit components related to each specific company. ^ Based on the analysis, it was determined that online grocery store business models could be represented at three distinct, but hierarchically, related levels. The first level was termed the core model and represented the basic profit structure that all online grocers needed in order to conduct operations. The next model level was termed the structural model and represented the profit structure associated with the specific business model configuration (i.e., pure-play, partnership, hybrid). The last model level was termed the augmented model and represented the company’s business model when idiosyncratic profit components were included. In relation to the five company related factors, scalability, rate of expansion, and the automation level were potential candidates for helping to explain online grocer performance. In addition, all the market structure related factors were deemed possible candidates for helping to explain online grocer performance. ^ The study concluded by positing an alternative hypothesis concerning the performance of online grocers. Prior to this study, the prevailing wisdom was that the business models were the primary cause of online grocer performance. However, based on the core model analysis, it was hypothesized that the customer relationship activities (i.e., advertising, promotions, and loyalty program tie-ins) were the real drivers of online grocer performance. ^

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For producers motivated by their new status as self-employed, landowning, capitalist coffee growers, specialty coffee presents an opportunity to proactively change the way they participate in the international market. Now responsible for determining their own path, many producers have jumped at the chance to enhance the value of their product and participate in the new "fair trade" market. But recent trends in the international coffee price have led many producers to wonder why their efforts to produce a certified Fair Trade and organic product are not generating the price advantage they had anticipated. My study incorporates data collected in eighteen months of fieldwork, including more than 45 interviews with coffee producers and fair trade roasters, 90 surveys of coffee growers, and ongoing participant observation to understand how fair trade certification, as both a market system and development program, meets the expectations of the coffee growers. By comparing three coffee cooperatives that have engaged the Fair Trade system to disparate ends, the results of this investigation are three case studies that demonstrate how global processes of certification, commodity trade, market interaction, and development aid effect social and cultural change within communities. This study frames several lessons learned in terms of (1) socioeconomic impacts of fair trade, (2) characteristics associated with positive development encounters, and (3) potential for commodity producers to capture value further along their global value chain. Commodity chain comparisons indicate the Fair Trade certified cooperative receives the highest per-pound price, though these findings are complicated by costs associate with certification and producers' perceptions of an "unjust" system. Fair trade-supported projects are demonstrated as more "successful" in the eyes of recipients, though their attention to detail can just as easily result in "failure". Finally, survey results reveal just how limited is the market knowledge of producers in each cooperative, though fair trade does, in fact, provide a rare opportunity for producers to learn about consumer demand for coffee quality. Though bittersweet, the fair trade experiences described here present a learning opportunity for a wide range of audiences, from the certified to the certifiers to the concerned public and conscientious consumer.