Abstract: The objective of this study is to provide a quantitative technique by using Personnel adjusted Added Value (PAV) to help managers make decisions by objectively evaluating their Human Capital Management (HCM) and projecting profit increase generated by HCM. The approach of this study is divided into three steps. In the first step, PAV is defined as the corporate output. The data are classified into two groups by Cluster Analysis. In the second step, the factors which represent HCM practices are selected and formulated using Principal Component and Factor Analysis. In the third step, the multiple regression model is constructed to identify the HCM factors which influence PAV. This process establishes the model for objectively judging the success of HCM.

• Publication Date: 29-Dec-2015
• DOI: 10.15224/978-1-63248-085-9-57
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Abstract: The agricultural issue is always the critical factor to achieving the sustainability of a country. Due to the growing of plants is affected by weather, season, and lots of external influences, the harvest of crops is unstable and might cause the imbalance between supply and demand in the market. Therefore, the precise prediction of demand in the crops transaction market is important. It is helpful to the farmers to make the cultivating plan and also beneficial to the development of agriculture. In our research, we apply back propagation neutral network (BPNN) to develop a time-series prediction model. The model is used to predict the trading volume of cherry tomatoes in the fruit transaction market in Taiwan. The trading volume indicates the demand in the market, for that reason, the farmers and government can make cultivating plan effectively by the prediction results. We collected the transaction information of cherry tomatoes from 2011 to 2014. The transaction information is used to

• Publication Date: 29-Dec-2015
• DOI: 10.15224/978-1-63248-085-9-58
• Views: 0
• Downloads: 0