Businesses in 21st century operate in ultracompetitive, dynamic and effervescent economies enabled by powerful machines & technology gadgets. The very existence of organizations in this digital maze depends on translating incredible amounts of data into powerful knowledge for decision making through scientific methods & statistical innovations. The job of advanced statistical techniques such as Multivariate Analysis is to illuminate, organize and interpret complex data with relative ease & luxury. This research uses the concept of Internal marketing to understand application of Principal Component Analysis (PCA). The study empirically tests data collected of 322 respondents through structured survey in 60 branches of 8 leading commercial banks in the region. The questionnaire was developed using 20 items based on extensive literature review. The results confirm the performance of proposed framework which can be utilized as statistical & managerial tool for employee development & organizational effectiveness. The components extracted are; motivation, understanding & differentiation, dissemination of information, strategic reward, training and inter-functional coordination.  Index Terms-factor analysis, principal component analysis, internal marketing, employee development, statistical package for social sciences (SPSS)

This study explores firms’ leverage behavior and speed of adjustment in the context of selected performance indicators in Pakistan’s manufacturing industry. Leverage behavior is predicted using ordinary least squares, based on four performance indicators: profitability, tangibility, size and growth. The speed of adjustment of leverage is estimated using a general linear model and partial adjustment model. We find that profitability, tangibility and growth play a significant role in leverage behavior and the speed of adjustment, although both differ across sectors. Moreover, exponential leverage adjustment appears to be better than linear leverage adjustment.