Formal strategic planning long range forecasting

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Formal strategic planning Long range forecasting Product Costing (α = 0.719) ABC Cost of quality Cost modelling Kaizen costing Target costing Throughput accounting Conventional Performance Evaluation (α = 0.854) Budgeting variance analysis CFROI Controllable profit Divisional profit Residual income (e.g. interest adjusted profit) Return (profit) on investment Advanced Performance Evaluation (α = 0.803) BSC Customer satisfaction surveys Team performance 5.5.1 Multiple Regression Analysis Testing for a Relationship between the Use of MAPs and Organisational Performance In this section, the multiple regression analysis seeks to answer the research questions which address the third objective of this study “ to evaluate the impact on organisational performance of adoption of MAPs, integrated information”. The multiple regression model is used to facilitate the analysis using OP as dependent variables and groups of MAP adoption as independent variables. Factor analysis is applied to classified OP into four groups: financial performance before/after IIS implementation and non-financial before/after IIS implementation. Then, all variables which will be used in regression analysis are put into correlation analysis to explore the correlations amongst variables. The number of MAP adoption as independent variables are categorised into six groups: B, DSS, LTP, PC, CPE and APE. The dependent variable, OP, is measured as financial
145 performance and non-financial performance using exploratory factor analysis (Hyvönen, 2007; Chapman and Kihn, 2009). Correlation Analysis for Multiple Regression Analysis Spearman correlation analysis in table 5.8 show the relation between groups of MAP adoption and OP before implementations of IISs. The results show positive associations between pairs of variables. Correlation coefficients show a weak relationship with a correlation coefficient less than 0.4. Most groups of MAP adoption: B, DSS, LTP, CPE and APE are positively associated with financial performance of organisations whereas there is no significant relationship between a group of PC and organisational financial performance. All groups of MAP adoption are associated with non-financial performance of organisations which have not implemented IIS yet. After IIS was implemented, the relationships between groups of MAP adoption and organisational performance are shown in table 5.9. IIS implementation and the number of MAP adoption in four groups of MAP adoption namely B, LTP, CPE and APE are positively associated with financial performance of organisations. On the other hand, IIS implementation and the number of MAP adoption in LTP and CPE are positively associated with non- financial performance of organisations. A possible explanation for non-significant correlation coefficients between all groups of MAP adoption and non-financial performance after IIS implementation is that none of the MAP adoption have a linear relationship with the perceived benefits from non-financial performance of organisations.

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