| This study was dedicated to the question of how to assess the organizational success of commercial firms. It developed a new framework called the Dynamic Multidimensional Performance Model (DMP), which is believed to improve the weaknesses of previous models, as well as test specific measures, which are relevant to different kinds of organizations.;Traditional measures of corporate success have been shown ambiguous and potentially poor indicators of future performance. Success in the short term is typically measured by last quarter's profitability and revenue growth, which are not necessarily valid metrics for long-term success. Recognition of this issue has resulted in recent attempts to develop non-financial measures of performance. However, numerous limitations exist with current measures (e.g., insufficient empirical validation, lack of human resource management perspective) and the theoretical literature has been slow in addressing these issues.;The multidimensional framework was developed by studying five relevant research streams: corporate entrepreneurship, strategy, process and product development, marketing, and economics/finance. They contributed to the development of a more dynamic, multidimensional model, which includes the following five dimensions: Financial, Market/Customer, Process, People Development, and Future.;The primary research questions were to (1) identify the most relevant success measures within each dimension; (2) understand the importance of different measures for different firm types and (3) determine if there are differences between relevant measures among the firm types.;The model was pre-tested with pilot interviews with ten CEOs to insure that all relevant measures are included, as well as provide a validation for the primary research instrument. A survey questionnaire with 180 respondents served as the primary empirical research instrument. Descriptive statistics were deployed to see if different organizational types (e.g., high-tech vs. low-tech, small vs. large, speed of life cycle) suggest different success measures. A principal components factor analysis was employed to determine if interpretable factors emerge.;The research suggested that organizational success is indeed multi-dimensional, and can not be defined by a limited number of variables. Organizations need many measures to assess organizational success. The research indicates that there are twelve baseline success measures that may be applicable to many firms. Furthermore, many specific success measures were found important for the varying firm types tested, with statistically significant differences between the demographic groups tested. The research provides empirical support for the premise that varying organizational types require different success measures. |
