ارزیابی اثرات هوشمند مدیریت منابع انسانب به ارزش سهامداران

Despite the extensive research in human capital management and performance measurement, intelligent treasoning mechanisms, which integrate human resource (HR) practices into strategic-level shareholder decisions, are still emerging. This paper discusses a novel approach of designing a decision-modeling tool, which assesses the impact of contemporary human resource management (HRM) practices to the shareholder value and satisfaction. The underlying research addresses the problem of establishing HRM interrelationships in order to drive the overall business performance from the shareholder value perspective. The proposed methodology tool utilizes the fuzzy causal characteristics of fuzzy cognitive maps (FCMs) to generate a hierarchical and dynamic network of interconnected HR performance drivers. The intelligent computing characteristics of FCMs are also employed to establish a dynamic feedback and bi-directional alignment of HRM practices and strategic improvement. Finally, this research provides a practical insight on the applicability of soft approaches in capturing and illustrating the effect of HRM practices.

Enterprises are evolving in turbulent and equivocal environments (e.g. Drucker, 1993, Grove, 1999 and Kellys, 1998). This requires enterprises to be alert and watchful for the detection of weak signals (e.g. Ansoff, 1975) or discontinuities of emerging threats and to initiate further probing based on such detection (Walls et al., 1992). Enterprises today face critical business challenges (Ulrich, 1998) like globalization, profitability through growth, technology integration, intellectual capital management, continuous change, etc. Such challenges require organizations to build new capabilities, but it is not always apparent who should be responsible for developing those capabilities. Perhaps, everyone and no one, but in any case this is a unique HR’s opportunity to play a leadership role in enabling organizations to meet such competitive challenges. Ensuring that human resource (HR) strategies are in place to deal with these challenges is increasingly recognized as critical to success (Leopold et al., 1999). Human resource management (HRM) in the literature has been considered a second- or third-order strategy, largely related to implementation rather than shareholder level decision-making. The process of HR strategy formulation and evaluation had not been widely conceptualized until recently. Moreover, the impact of HRM practices to the shareholder strategic value is not modeled adequately, despite the utilization of sophisticated performance evaluation mechanisms at the employee level. The evidence that HR issues are fundamental to business is compelling at the level of unit labor costs, but whether they are fundamental to the strategy process remained highly questionable until recent years (Ritson, 1999). This can be attributed to the fact that contemporary performance evaluation mechanisms focus on analyzing the operational effectiveness of the human capital rather than addressing the issue of strategic alignment. This paper addresses the problem of designing a novel modeling methodology tool to act as an intelligent decision support mechanism for evaluating the impact of HRM practices to the shareholder value and satisfaction. This attempt focuses on bridging the gap between the operational characteristics of HRM practices and the strategic decisions at the shareholder level. The proposed methodology tool utilizes the fuzzy causal characteristics of fuzzy cognitive maps (FCMs) to generate a hierarchical and dynamic network of interconnected HR performance drivers. By using FCMs, the proposed novel mechanism simulates the operational efficiency of HR models with imprecise relationships and quantifies the impact of HRM activities to the overall shareholder satisfaction model. This research builds on contemporary HRM experience to establish a “soft computing” approach on how to interrelate HRM activities and shareholder value. The FCM approach does not pose as a substitute of traditional HRM operations nor does it offer an alternative to HR performance evaluation. It presents an intelligent decision-making framework for strategic-level HRM based on scenario building and ex ante impact assessment. Primarily, the proposed model targets the principle directors and stakeholders of HRM projects (e.g. HR department, change management leaders, business strategy leaders, etc) assisting them to reason effectively about the status of strategic-level performance metrics, given the (actual or hypothetical) implementation of a set of HR practice changes. However, the holistic nature of the proposed model may couple effectively with other strategic performance evaluation systems. Given the demand for effective shareholder positioning, such a succinct mechanism of conveying the essential dynamics of HR practices is believed to be useful for anyone contemplating or undertaking a strategy formulation exercise. Nevertheless, the explanatory nature of the mechanism can prove to be useful in a wider educational setting.

This paper presented an intelligent decision-modeling technique, which assessed the impact of contemporary HRM practices to the shareholder value. This research addressed the problem of establishing HRM interrelationships in order to drive the overall business performance from the shareholder value perspective. The proposed methodology offered an alternative approach to HRM based on shareholder value modeling. The underlying research addressed the problem of performance capture and representation in order to provide an implementation of an integrated HRM framework. The proposed methodology utilized the fuzzy causal characteristics of FCMs to generate a hierarchical and dynamic network of interconnected HR performance decision concepts. Also, generic maps that supplemented the decision process presented a roadmap for integrating hierarchical FCMs into HR performance management techniques. The application of FCMs as an intelligent (though soft) modeler of HR knowledge is believed to be novel. This paper extended typical FCM algorithms to adapt to the distributed nature of typical HR activities. Also, this research adopted a new qualitative approach to interpret fuzzy linguistic variables to weight and concept values in order to support further the soft computing characteristics of the technique. It is the belief of this paper that the intelligent reasoning capabilities enhanced considerably the usefulness of the mechanism while reducing the effort of identifying quantitative impact measurements. The proposed mechanism should not be regarded only as an effective decision modeling support tool. Its main purpose is to drive HR change activities rather than limit itself to qualitative simulations. Moreover, the proposed mechanism should not be seen as an “one-off” decision aid. It should be a means for setting a course for continuous improvement (Langbert & Friedman, 2002).