Motivational profiles of sport event volunteers.

Aim of the study Due to the valuable contribution made by volunteers to sporting events, a better understanding of volunteers’ motivation is imperative for event managers in order to develop effective volunteer re-cruitment and retention strategies. The adoption of working conditions and task domains to the mo-tives and needs of volunteers is one of the key challenges in volunteer management. Conversely, an ignorance of the motives and needs of volunteers could negatively affect their performance and attitude, which will have negative consequences for the execution of events (Strigas & Jackson, 2003). In general, the motives of volunteers are located on a continuum between selflessness (e.g. helping others), and self-interest (e.g. pursuing one’s own interests). Furthermore, it should take into account that volunteers may be motivated by more than one need or goal, and therefore, configure different bundles of motives, resulting in heterogeneous types of motives for voluntary engagement (Dolnicar & Randle, 2007). Despite the extensive number of studies on the motives of sport event volunteers, only few studies focus on the analysis of individual motive profiles concerning volun-teering. Accordingly, we will take a closer look at the following questions: To what extent do volun-teers at sporting events differ in the motives of their engagement, and how can the volunteers be ade-quately classified? Theoretical Background According to the functional approach, relevant subjective motives are related to the outcomes and consequences that volunteering is supposed to lead to and to produce. This means, individuals’ mo-tives determine which incentives are anticipated in return for volunteering (e.g. increase in social contacts), and are important for engaging in volunteering, e.g. the choice between different oppor-tunities for voluntary activity, or different tasks (Stukas et al., 2009). Additionally, inter-individual differences of motive structures as well as matching motives in the reflections of voluntary activities will be considered by using a person-oriented approach. In the person-oriented approach, it is not the specific variables that are made the entities of investigation, but rather persons with a certain combination of characteristic features (Bergmann et al., 2003). Person-orientation in the field of sports event volunteers, it is therefore essential to implement an orientation towards people as a unit of analysis. Accordingly, individual motive profiles become the object of investigation. The individ-ual motive profiles permit a glimpse of intra-individual differences in the evaluation of different motive areas, and thus represent the real subjective perspective. Hence, a person will compare the importance of individual motives for his behaviour primarily in relation to other motives (e.g. social contacts are more important to me than material incentives), and make fewer comparisons with the assessments of other people. Methodology, research design and data analysis The motives of sports event volunteers were analysed in the context of the European Athletics Championships 2014 in Zürich. After data cleaning, the study sample contained a total of 1,169 volunteers, surveyed by an online questionnaire. The VMS-ISA scale developed by Bang and Chel-ladurai (2009) was used and replicated successfully by a confirmatory factor analysis. Accordingly, all seven factors of the scale were included in the subsequent cluster analysis to determine typical motive profiles of volunteers. Before proceeding with the cluster analysis, an intra-individual stand-ardization procedure (according to Spiel, 1998) was applied to take advantage of the intra-individual relationships between the motives of the volunteers. Intra-individual standardization means that every value of each motive dimension was related to the average individual level of ex-pectations. In the final step, motive profiles were determined using a hierarchic cluster analysis based on Ward’s method with squared Euclidean distances. Results, discussion and implications The results reveal that motivational processes differ among sports event volunteers, and that volunteers sometimes combine contradictory bundles of motives. In our study, four different volunteer motive profiles were identified and described by their positive levels on the individual motive dimension: the community supporters, the material incentive seekers, the social networkers, and the career and personal growth pursuers. To describe the four identified motive profiles in more detail and to externally validate them, the clusters were analysed in relation to socio-economic, sport-related, and voluntary work characteristics. This motive-based typology of sports event volunteers can provide valuable guidance for event managers in order to create distinctive and designable working conditions and tasks at sporting events that should, in relation to a person-oriented approach, be tailored to a wide range of individ-ual prerequisites. Furthermore, specific recruitment procedures and appropriate communication measures can be defined in order to approach certain groups of potential volunteers more effectively. References Bang, H., & Chelladurai, P. (2009). Development and validation of the volunteer motivations scale for international sporting events (VMS-ISE). International Journal Sport Management and Market-ing, 6, 332-350. Bergmann, L. R., Magnusson, D., & El-Khouri, B. M. (2003). Studying individual development in an interindividual context. Mahwah, NJ: Erlbaum. Dolnicar, S., & Randle, M. (2007). What motivates which volunteers? Psychographic heterogeneity among volunteers in Australia. Voluntas, 18, 135-155. Spiel, C. (1998). Four methodological approaches to the study of stability and change in develop-ment. Methods of Psychological Research Online, 3, 8-22. Stukas, A. A., Worth, K. A., Clary, E. G., & Snyder, M. (2009). The matching of motivations to affordances in the volunteer environment: an index for assessing the impact of multiple matches on volunteer outcomes. Nonprofit and Voluntary Sector Quarterly, 38, 5-28.

Mining tissue microarray data to uncover combinations of biomarker expression patterns that improve intermediate staging and grading of clear cell renal cell cancer

PURPOSE: Tumor stage and nuclear grade are the most important prognostic parameters of clear cell renal cell carcinoma (ccRCC). The progression risk of ccRCC remains difficult to predict particularly for tumors with organ-confined stage and intermediate differentiation grade. Elucidating molecular pathways deregulated in ccRCC may point to novel prognostic parameters that facilitate planning of therapeutic approaches. EXPERIMENTAL DESIGN: Using tissue microarrays, expression patterns of 15 different proteins were evaluated in over 800 ccRCC patients to analyze pathways reported to be physiologically controlled by the tumor suppressors von Hippel-Lindau protein and phosphatase and tensin homologue (PTEN). Tumor staging and grading were improved by performing variable selection using Cox regression and a recursive bootstrap elimination scheme. RESULTS: Patients with pT2 and pT3 tumors that were p27 and CAIX positive had a better outcome than those with all remaining marker combinations. A prolonged survival among patients with intermediate grade (grade 2) correlated with both nuclear p27 and cytoplasmic PTEN expression, as well as with inactive, nonphosphorylated ribosomal protein S6. By applying graphical log-linear modeling for over 700 ccRCC for which the molecular parameters were available, only a weak conditional dependence existed between the expression of p27, PTEN, CAIX, and p-S6, suggesting that the dysregulation of several independent pathways are crucial for tumor progression. CONCLUSIONS: The use of recursive bootstrap elimination, as well as graphical log-linear modeling for comprehensive tissue microarray (TMA) data analysis allows the unraveling of complex molecular contexts and may improve predictive evaluations for patients with advanced renal cancer.

From big smartphone data to worldwide research: The Mobile Data Challenge

This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of mobile data analysis methodologies. First, we review the Lausanne Data Collection Campaign (LDCC), an initiative to collect unique longitudinal smartphone dataset for the MDC. Then, we introduce the Open and Dedicated Tracks of the MDC, describe the specific datasets used in each of them, discuss the key design and implementation aspects introduced in order to generate privacy-preserving and scientifically relevant mobile data resources for wider use by the research community, and summarize the main research trends found among the 100+ challenge submissions. We finalize by discussing the main lessons learned from the participation of several hundred researchers worldwide in the MDC Tracks.

Index Tracking Using Data-Mining Techniques and Mixed-Binary Linear Programming

Index tracking has become one of the most common strategies in asset management. The index-tracking problem consists of constructing a portfolio that replicates the future performance of an index by including only a subset of the index constituents in the portfolio. Finding the most representative subset is challenging when the number of stocks in the index is large. We introduce a new three-stage approach that at first identifies promising subsets by employing data-mining techniques, then determines the stock weights in the subsets using mixed-binary linear programming, and finally evaluates the subsets based on cross validation. The best subset is returned as the tracking portfolio. Our approach outperforms state-of-the-art methods in terms of out-of-sample performance and running times.