Identifying patterns of alumni commitment in key strategic relationship programmes

Higher education institutions (HEIs) need to understand their alumni when drawing strategic relationship programmes. This paper aims to identify clusters of alumni based on their commitment relationship and to analyse factors influencing their intention to collaborate with the HEI. The study took place at a Portuguese university, considering a dataset of 1075 of alumni asserting intention to collaborate. First, a cluster analysis was conducted to identify patterns of commitment relationship. Secondly, a logistic regression was run to identify determinants of intention to collaborate. Both techniques revealed the decisive role of HEI commitment in the process. Relationship advantages and positive feelings towards the HEI were also pointed out as important. Alumni asserted recommendations, further training, sharing experiences and giving help as ways to collaborate with HEI. Regression results suggest that sociodemographic variables such as gender, marital status and volunteering are significantly associated with a probability to collaborate. Results also show that affiliation in sororities/fraternities and participation in extracurricular activities are significantly associated with that collaborative intention. The findings provide clues to support strategic relationship programmes based on consistent marketing campaigns, while bringing value to the literature in the European context, where alumni culture requires real insights to evolve.info:eu-repo/semantics/publishedVersio

Comparative Evaluation of Some Crop Yield Prediction Models using Tropical Cowpea Yield-Weather Data

A computer program was adopted from the work of Hill et al. (1982) to calibrate and test three of the existing yield prediction models using tropical cowpea yieldÐweather data. The models tested were Hanks Model (first and second versions). Stewart Model (first and second versions) and HallÐButcher Model. Three sets of cowpea yield-water use and weather data were collected. The first one was used for calibration and the other two for validation. The results obtained from the models were compared with field values using correlation coefficient and mean error of deviation. Stewart first model had r-values of 0.93 and 0.74 and mean error of deviation of 0.1 and 0.15. The second model had r-values of 0.92 and 0.86 and mean error of deviation of 0.05 and 0.11. Hanks first model had r-values of 0.94 and 0.89 and average mean error of deviation of 0.03 and 0.10, the second model had r values of 0.93 and .096 and average mean error of deviation of 0.05 and 0.03. The r-values for Hall-Butcher model were 0.76 and 0.96. The mean errors of deviation were 0.14 and 0.03. Generally, Hanks model predicted better than the other models but may still need to be further modified to be able to predict well for tropical conditions. Keywords: Prediction model, yield prediction, yield parameters, Hanks model, Stewart model, Hall Ð Butcher model, cowpea yield, tropical climatic conditionsDiscovery and Innovation Vol. 19 (2) 2007: pp. 89-9

Effect of animal manure incorporation on erosion indices of two Nigerian agriculture soils

No Abstract. Discovery and Innovation Vol. 17(3&4) 2005: 138-14