Lack of viable leadership succession has plagued family businesses and contributed to the high failure rate of these businesses (Cabrera-Suarez, 2005; Grote, 2003). Perhaps as a response to this challenge, more family businesses are installing Co-CEOs/Co-Presidents as they make the transition from generation to generation. This study explores the phenomenon of family member Co-CEOs in a family business that has successfully made the transition from founder to sibling ownership and management. While Co-CEOs are considered to be "a special case of shared leadership-the two person case" (Pearce & Conger, 2003, p. 14), the context of a family business introduces further considerations as does the issue of dyadic interaction between the two co-leaders. The family business context is investigated using the concept of internal family social capital which is unique to families and appropriable into family businesses. / This exploratory case study researches the nature of shared leadership between a pair of Co-CEOs in a family business and additionally asks about the role of internal family social capital in the implementation and functioning of the leadership structure. This case study examines a 32 year old hospitality business that is led by brother Co-Presidents. Data were gathered from interviews of company employees, external stakeholders and family members; observations and documents. The findings reveal that the success of this leadership arrangement is due in no small measure to the close knit and value driven nature of the owning family. Strong internal family social capital is an indicator of achieving shared leadership in the top post of a family business. The duo of leaders implement role overlap; practice open communication and conflict resolution; have trust in and respect for each other and use external support as a lubricant to the relationship. / Key words: Co-CEOs, family social capital, shared leadership, co-leadership.

This paper examines the influence of increasing access to the Internet and increasing online purchasing on sales tax competition among the states. Prior research indicates that the tax rates set by a state’s geographical neighbors influence the tax rate set by the home state. As consumers gain access to the Internet and begin to participate in online shopping, their opportunity cost to participate in cross-border shopping decreases and their “mobility” may increase due to the ease of purchasing from vendors lacking nexus in the consumer’s home state. Thus, states may begin to respond less to the sales tax changes of their geographic neighbors and may begin to define competitors differently. I find that increases in both the percentage of the population having Internet access and the percentage of the population making online purchases influence the response of a state to its neighbors’ tax rates. Specifically, states with higher percentages of either of these measures have more positive response functions when examining the “effective Internet tax rate” definition of neighbor. States appear to respond only slightly to changes in the tax rates of their geographic neighbors. This paper also examines the influence of Internet usage on the sales tax revenues of the states by separating the influences of cross-border shopping through traditional means and through the Internet. Research finds that consumers who live near physical borders are more responsive to tax differences than are consumers who live farther from physical borders. As more consumers access the Internet and begin to purchase goods online, all consumers may become as responsive to tax differences as are those who live near physical borders. Thus, both traditional means of cross-border shopping and cross-border shopping through use of the Internet would be expected to influence the sales tax revenues of a state. Surprisingly, I find that sales tax revenue per capita appears to increase with an increase in my measure of Internet-based cross-border shopping. This may indicate that online shopping does not act entirely as a substitute for local forms of shopping but rather represents an increase in consumption.

In statistical modeling, an overparameterized model leads to poor generalization on unseen data points. This issue requires a model selection technique that appropriately chooses the form, the parameters of the proposed model and the independent variables retained for the modeling. Model selection is particularly important for linear and nonlinear statistical models, which can be easily overfitted. Recently, support vector machines (SVMs), also known as kernel-based methods, have drawn much attention as the next generation of nonlinear modeling techniques. The model selection issues for SVMs include the selection of the kernel, the corresponding parameters and the optimal subset of independent variables. In the current literature, k-fold cross-validation is the widely utilized model selection method for SVMs by the machine learning researchers. However, cross-validation is computationally intensive since one has to fit the model k times. This dissertation introduces the use of a model selection criterion based on information complexity (ICOMP) measure for kernel-based regression analysis and its applications. ICOMP penalizes both the lack-of-fit and the complexity of the model to choose the optimal model with good generalization properties. ICOMP provides a simple index for each model and does not require any validation data. It is computationally efficient and it has been successfully applied to various linear model selection problems. In this dissertation, we introduce ICOMP to the nonlinear kernel-based modeling areas. Specifically, this dissertation proposes ICOMP and its various forms in the area of kernel ridge regression; kernel partial least squares regression; kernel principal component analysis; kernel principal component regression; relevance vector regression; relevance vector logistic regression and classification problems. The model selection tasks achieved by our proposed criterion include choosing the form of the kernel function, the parameters of the kernel function, the ridge parameter, the number of latent variables, the number of principal components and the optimal subset of input variables in a simultaneous fashion for intelligent data mining. The performance of the proposed model selection method is tested on simulation bench- mark data sets as well as real data sets. The predictive performance of the proposed model selection criteria are comparable to and even better than cross-validation, which is too costly to compute and not efficient. This dissertation combines the Genetic Algorithm with ICOMP in variable subsetting, which significantly decreases the computational time as compared to the exhaustive search of all possible subsets. GA procedure is shown to be robust and performs well in our repeated simulation examples. Therefore, this dissertation provides researchers an alternative computationally efficient model selection approach for data analysis using kernel methods.

For many years, academics generally viewed uptick rules as short sale constraints that contribute to stock overvaluation and hamper stock price efficiency. Recently adopted Regulation SHO provides us with a natural experiment to study the impact of the suspension of uptick rules on various market quality measures in a controlled environment. In the first essay, I investigate the impact of removing short sale price test rules on stock returns and find that on the NYSE, removing the tick-test rule mitigates stock overvaluation. On the NASDAQ, however, lifting the bid-test rule goes beyond correcting such overvaluation. It shows that prices of high-dispersion stocks tend to be depressed relative to prices of low-dispersion stocks. I also examine the relationship between daily short selling activities and stock returns and find that on average short sellers are more likely to be value-driven “contrarians” who short sell following high stocks returns. In the second essay, I examine the information content of short selling around the release of analyst recommendations. By looking at the magnitude and the speed of price response to analyst downgrade recommendations, I provide intra-day evidence supporting the documented assertion that suspension of the uptick rule helps improve stock price efficiency. For after-hour downgrades, pilot stocks respond quickly, with virtually all of the price response incorporated by the following open, while control stocks take an extra half hour after opening to fully reflect the new information. For downgrades that occur during normal trading hours, downgrade information is partially incorporated into pilot stock prices up to two hours before the recommendation is released, while control stocks take up to an hour and a half after the recommendation release to impound the information into stock price. Finally, short selling activities prior to the release of analyst recommendations indicate that short sellers capitalize on their private information associated with upcoming downgrades in the control sample, but such behavior seems to disappear in the pilot sample. I conjecture that, during the pilot program, short sellers were aware of the SEC’s regulatory scrutiny of pilot stocks and thus avoided trading on their private information in those stocks.

We study the effect of entrepreneurs’ wealth allocations on their firm level capital structure by using a sample of small privately owned firms from the 2003 Surveys of Small Business Finance. We find that financial leverage decreases as entrepreneurs allocate more wealth on their firm investments. We also find that wealth allocation only affects capital structure in limited liability firms. Lastly, we show that the effect of wealth allocation on capital structure does not disappear after adjusting for collateral and personal guarantees.

Direct to consumer advertising of prescription drugs (DTCA) accounts for approximately $5 billion in advertising spending in the US. Critics of this controversial practice cite confusing and misleading information negative effects on the physician-patient relationship as reasons to restrict or even ban DTCA, while proponents claim it empowers patients and facilitates discussions between physicians and patients that may improve overall health. An ethnography of consumers in the most prominent target market for DTCA initially seeks to understand the meaning of DTCA among middle age adults in the US with chronic conditions. Participants in the study are skeptical about this category of advertising, and describe DTCA as being “good and bad.” They see ads as being helpful reminders about conditions, however, they rarely remember the brand names represented. For them, the downside is that the ads are pervasive and don‟t provide enough useful information. Discussion of their interactions with DTCA acts as a keyhole into the life world of patients with chronic conditions as consumers, whose information search efforts amount to “becoming little doctors.” Through emergent design, exploring an expanded set of research questions yields a description of patients as consumers. The process of adjusting to a chronic condition among participants occurs in stages and involves diagnosis, learning and management phases. Information search and social networks play a large part in the adjustment process, as patients consume health care services, information and often, prescription drugs. Implications for marketers, health care professionals and public policy makers are discussed.

This study examines the impact of Sarbanes-Oxley on CEO compensation and director compensation for banks. The presence of pre-SOX regulation in the banking industry, particularly, FIRREA and FDICIA, suggests that SOX may affect banks differently than other industries. Specifically, this study examines the changes in the trends for CEO compensation and for director compensation for banks over time. The results indicate that compensation for directors and CEOs has changed for all firms over time, but the sign and the significance of the change varies with respect to the type of compensation. Additionally, the differences in director/CEO compensation for banks and industrial firms have also changed over time. Whether or not the changes in the gap between compensation for banks and industrials is a consequence of banks being financial firms or banks being regulated firms varies depending on the type of compensation. The results show that bank directors are paid more cash compensation, more total compensation, and less in levels but not proportions of equity-based compensation after SOX when compared to before SOX levels. Additionally, all forms of compensation are lower for banks than non-banks after SOX. Director cash, equity, and total compensation increased for all firms from before to after SOX. There is no significant change in the difference of any form of director compensation from before to after SOX. Similar to the director compensation results, the results for CEO compensation indicate that bank CEOs are paid less cash compensation, less total compensation, and less in levels of equity-based compensation and less in percent of equity after SOX. Additionally, the level of equity compensation and total compensation are lower for banks than non-banks after SOX. However, there is no difference in cash or percent equity compensation between banks and non-banks after SOX. The results suggest that the gap between bank CEO compensation and industrial CEO compensation for equity and total compensation is widening and it may be driven by the fact that banks are financial firms. The evidence also supports the notion that the widening gap between CEO compensation between banks and industrials may be driven by bank regulation

Online product recommendation agents are gaining greater strategic importance as an innovative technology to deliver value-added services to consumers. Yet the active role of consumers as the participants in using this technology is not well understood. This dissertation builds on the technology-based self-service (TBSS) literature, consumer participation literature, the service-dominant logic, and the trust literature on recommendation agents to develop a research framework that explains the role of consumer participation in using online product recommendation agents. The objective of this dissertation is three-fold: (1) to examine the effects of consumer participation and privacy/security disclosures in using online product recommendation agents, (2) to explore the mediating effects of trust, perceived control, and perceived risk in providing personal information, and (3) to test the trust transference process within the current research context. A field experiment using existing recommendation agents was conducted with multiple sessions in computer labs to collect data from university students, a representative sample of the online population. 67 undergraduate students participated in the pretest, and 117 participated in the main study. Structural equation modeling with AMOS 7.0 was used to test the research hypotheses. The results showed that consumer participation was a contributing factor in building consumers’ trust in recommendation agents and that privacy/security disclosures decreased consumers’ perceived risk in providing personal information. Moreover, the trust transference process was validated among the three different types of consumer trust within the agent-mediated environment, that is, trust in the recommendation agent, trust in the Web site, and trust in recommendations. Finally, perceived control was shown to be a salient factor in increasing consumers’ trust and motivating consumers to reuse the recommendation technology

Gaining competitive advantage in today’s fragmented markets is a powerful incentive for marketers to create superior customer value to. Multiple research streams were carried out to understand the meaning of customer value and determine the most effective ways to provide it. A review of the extant literature revealed that these research streams fall into in four different categories, namely cultural values of the customer, customer value as a trade off, customer value as a process, and customer value as an experience. This dissertation research focuses on the third path, which uses means-end theory to understand customer value by exploring the meanings attached to the consumption of services. . This dissertation posits that a service provides superior value to customers if it contributes more towards the attainment of customer goals more than competitors. Although there is a great deal of research on means-end theory with products, limited empirical research has been conducted on services. Recently, some studies have been conducted using quantitative methods to explicate customer value hierarchies. However, means-end theory and its hierarchical framework of attributes, consequences and goals have not been tested using quantitative methods. This dissertation fills this gap by successfully testing the means-end theory in the context of an educational service. The hierarchical framework was analyzed using structural equation modeling to simultaneously test the proposed four hypotheses. The fit of the model was good and all the hypothesized paths were significantly correlated. In sum, this dissertation presents a completely quantitative approach for analyzing dominant paths among many important goals, consequences and attributes in the presence of high multicollinearity. Using this approach, it is possible to measure the types of customer value that may be created by the consumption of services and products.

Global business executives recently highlight the importance of understanding the sources of value creation for customers around the world. Beyond a push to better grasp what customers currently value, firms interact with dynamic customers whose needs do not stand still. In response, managers are searching for innovative ways to sense ongoing changes in customers’ desires and effectively adapt their company’s value propositions. Yet, an extensive research review suggests there is little, if any, evidence that managers can rely on to understand how business customers are changing what they value across global markets – or what these changes mean for fostering loyalty in those relationships. This global study responds to these challenges through exploring the sources of value creation and the effects of value change for 939 customers of business services in the United States, Sweden, India, Singapore, and the United Kingdom. A theoretical framework is proposed that builds on research in customer value, international buyer behavior, and buyer-seller relationships and tests 22 hypotheses across three models. Two new constructs are developed, value change responsiveness and value change anticipation, which demonstrate significant effects on customer value. Significant results and close fit across three models tested with structural equation modeling generate a number of interesting implications for global and domestic managers. For executives and strategists who are concerned about growing a profitable base of loyal customers, this study provides insights for how customers in different market segments around the world are changing what they value, and specifically the role that this change plays in their perceptions of satisfaction and loyalty.