Law enforcement organizations have been facing a challenge with maintaining an adequate level of personnel due to an increased rate of employee turnover, which has been shown to have a negative impact on an agency's ability to reduce both property and violent crimes. The purpose of this cross-€sectional, quantitative study was to examine job embeddedness as a predictor of turnover intentions among municipal law enforcement officers by using the human capital theory as the theoretical foundation. To collect the data, a survey link was distributed to all personnel of a large, municipal law enforcement agency in the southeastern United States; only full-€time, commissioned law enforcement personnel were included in the study, which resulted in a sample size of 107. Linear regression was used to analyze the data. Job embeddedness and turnover intentions had a statistically significant and negative correlation (r = €.656, p < .001). In addition, the bivariate linear regression model significantly predicted turnover intentions, F(11, 106) = 79.135, p < .001); job embeddedness was responsible for 42.4% (adjusted R2 = .424) of the variance in turnover intentions. When job embeddedness decreases, turnover intentions increase, and when job embeddedness increases, turnover intentions decrease. The study has implications for positive social change as it established the relationship between job embeddedness and turnover intentions among law enforcement officers. The results provide support for using the concept of job embeddedness to inform retention programs aimed at reducing voluntary turnover. Reducing voluntary turnover has the potential to maximize the ability of an agency to meet its crime control mission and to reduce costs associated with recruitment and training new employees, which will allow for more funding to go directly to the provision of services.

Employee turnover is detrimental to organizational performance and profitability, leading to loss of diverse financial and intellectual resources and assets. Grounded in the motivation-hygiene theory, the purpose of this correlational study was to examine the relationship between employee turnover intention and job satisfaction, employee compensation, employee engagement, employee motivation, and work environment. The population consisted of low- to mid-level hospitality employees residing in Western Georgia, Central Mississippi, and North Central Texas, over the age of 18, and employed in the hospitality industry. A convenience sample of 156 participants completed the Compensation Scale, Job Satisfaction Scale, Utrecht Work Employee Engagement Scale, Work Extrinsic and Intrinsic Motivation Scale, Work Environment Scale, and Turnover Intention Scale via an online survey. Multiple linear regression analyses and Pearson-product correlation coefficients were used to predict employee turnover. The 5 predictors accounted for approximately 36% of the variance in turnover intention and the result was statistically significant, (R-² =.36, F (5, 105) = 11.57, p < .001). The correlation between motivation and turnover intention was not significant. The findings may contribute to positive social change by increasing the potential to provide hospitality leaders with a foundation for future research on job satisfaction, employee compensation, employee engagement, employee motivation, work environment, and turnover intentions. These improvements may lead to the formulation of strategies and policies of business practices to reduce turnover intentions.

The intention-behavior gap between receiving professional health information and transitioning to improved health behaviors prior to conception is not well understood. In order to improve preconception health across the board, a more integrative understanding of the problem must present itself. This study combined elements from the theory of planned behavior, self-determination theory, and the bioecological model of human development as it's foundation. Qualitative phenomenology and semistructured face-to-face interviews were used to gain a deeper understanding of the ways in which nine overweight and obese women described preconception intentions and beliefs and the bioecological experiences leading to those beliefs. Interpretation of the results suggested socio-environmental conditions that affect the development of beliefs, intentions, and attitudes toward preconception health. Key discoveries regarding planning intention and behavior included laissez faire attitudes toward preconception planning, advice-seeking methods, perceived need to change behaviors, and ability to navigate the healthcare system and social programs. Future recommendations include using the more complex bioecological view to improve the global preconception health imperative. This study's potential for positive social change includes opportunities to hold important conversations about preconception health by disseminating study results locally and the expansion of knowledge in a field dedicated to the improvement of women and infant health worldwide through publication.

Employees who want to leave their companies may exhibit low morale and commitment to organizations, which may affect the way employees interact with customers. The purpose of this correlational study was to examine the relationship between employees' affective, continuance, and normative commitment to their organizations and their turnover intentions. The target population consisted of individuals with 2 or more years of call center experience who resided in the United States. Meyer, Allen, and Smith's 3-component model of commitment provided the study's theoretical framework. A purposive sampling of participants, which included a targeted audience and individuals who accessed the survey from Facebook and LinkedIn, returned 81 usable surveys. Data were analyzed using multiple linear regression analysis. The overall regression model showed a statistically significant relationship between the 3 forms of commitment and turnover intentions, although normative commitment had the strongest relationship with turnover intentions. Study results provide additional evidence showing that employees' affective, continuance, and normative commitment to their organizations relate to their turnover intentions. These results may contribute to positive social change by helping leaders to better understand the relationship between employees' organizational affective, continuance, and normative commitment and turnover intentions. With this knowledge, leaders may be able to decrease turnover and turnover-related costs and increase firm performance. The money saved from turnover costs can be used to develop employees, invest in the company culture, or contribute to community-related programs.

This dissertation explores the demographic, economic, political, and environmental characteristics that have helped define the "New West," reviews studies on individual attitudes and participation in response to these changes, and presents findings and conclusions from an analysis of two study areas: Bear Lake and Star Valley. Results suggest that residency status is generally not a significant predictor of resident attitudes towards aspects of community change. Non-residency status factors, such as high levels of place attachment, knowledge about community affairs, values for property ownership, and community satisfaction, were generally more influential upon residents' attitudes. Significant predictors of resident involvement in community affairs differed based on how involvement was measured; self-reported involvement in political affairs was most strongly predicted by permanent resident status, local social connections, knowledge of community affairs, and place attachment, while resident intention to participate in community affairs was positively correlated with greater personal efficacy, knowledge of community affairs, past leadership recruitment, place attachment, and altruistic motivation. Predictors for intention to participate also differed based on whether participation was measured by action type or by issue. Measuring participation by the type of action focused predictors on the skills, incentives, and resources needed to achieve those actions. Grouping participation by the type of issue, however, focused predictors on the characteristics that differentiated residents with regard to issue relevance. Out-migration, as an alternative to participatory action, was only predicted by non-economic factors. Additionally, the relationship between attitudes and behavioral intentions was only weakly predicted based on attitude ambivalence and specific scenarios. Study results highlighted several methodological considerations for future attitude and participatory studies. Use of general attitudinal statements may have yielded inflated response scores and therefore may not translate to shared acceptability of specific management decisions or trade-offs. This study also explored the notion of behavioral intentions as a means of identifying residents' "ideal" tendency for involvement. Local community leaders may be able to improve resident public participation by utilizing these findings to provide a shared goal for action, identifying appropriate audiences for specific issues, and recognizing how different participatory methods may yield obstacles and opportunities for resident involvement.

This master thesis aims to investigate the possibilities of predicting purchase intentions of customers during their sales processes in the real estate sector. Also, the web activity of customers on a real estate company’s web site is used as the basis for the forecasting. A machine learning framework has been developed, where its compliance with the GDPR is also assessed.  Five supervised machine learning algorithms – logistic regression, k-nearest neighbors, decision tree, random forest, multilayer perceptron – have been utilized for predicting the classes of the customers: buyers and non-buyers. Three data sets were generated, which represented the total number of active customers at different points in time: at the same day as a sales process starts (day 0) and 10 and 20 days after it. The algorithms were applied and evaluated on these data sets to identify when it is suitable to predict the purchase intentions of customers. To increase the generalization capability of the algorithms, hyperparameter optimization along with data resampling by combining undersampling and synthetic minority over-sampling techniques, k-fold cross validation and mutual information, as feature selection, were applied. The results show that the number of visited web pages, sessions, searched projects (concerning accommodations) and searched locations were relevant for all three data sets. The average price (in total and per square meter) of the most frequently visited web page regarding projects were also included in all the data sets. In addition, the total number of registration of interests sent, and the total amount of time spent on the company’s web site were considered in the second (day 10) and third data set (day 20). Further, a multilayer perceptron – applied 10 days after the start of a sales process – was considered as the optimal model for classifying the purchase intentions of customers. Moreover, the developed machine learning framework is argued to be compliant with the GDPR. Further evaluation regarding the compliance needs to be conducted if the methodology of this machine learning framework would be implemented in practice.

Global Alliance of Marketing and Management Associations (GAMMA). The purpose of this study was to propose and empirically test a sport spectator behavioral model. The model presented here is a micro-level perspective of value creation in the context of live sporting events. This study used directional hypotheses to compare the influence of different value dimensions on specific customer behaviors in the setting of North American professional sport. Structural equation modeling was performed to examine path coefficients for the hypothesized relationships in the model. Organization-related value propositions were found to be stronger predictors of perceived economic, hedonic, and social value. One exception to this was customer density, which negatively impacted certain value perceptions. The hedonic value was found to have the strongest influence on customer in-role and extra-role behavior. The behavioral model tested here can be used in future studies to examine how sport organizations and their customers can create value in the live event setting and how the roles performed by each stakeholder influence future behavior. Findings suggest there are several actions marketers and managers can take to increase customer perceived value and prompt spectators to attend future events or act as advocates for the organization.

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The purpose of this study was to verify Mezirow's (1978) Transformative Learning Theory as a model to explain how study abroad participation facilitates efforts to internationalize students in higher education. Specifically this study used block-entry, logistic and linear regression models to explore the relationship between transformative learning processes and study abroad outcomes. Data were collected from business students (N =107) at Brigham Young University using a retrospective pretest method. Findings indicated transformative learning was occurring in short term study abroad settings and transformative learning phases were related to increases in Intercultural Competence. These findings were consistent between year cohorts suggesting the impacts were lasting.