یک مدل توسعه یافته از عوامل مؤثر بر پذیرش و کارآیی سیستم های مدیریت منابع انسانی الکترونیکی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|10500||2009||10 صفحه PDF||سفارش دهید||7281 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Human Resource Management Review, Volume 19, Issue 2, June 2009, Pages 134–143
Despite the widespread use of eHR systems, surveys show that there may be a number of problems associated with their design and implementation [CedarCrestone (2007). CedarCrestone 2007–2008 HR systems survey: HR technologies, service delivery approaches, and metrics. Available at www.cedarcrestone.com/research.php. Retrieved July, 2008]. In an effort to overcome these problems we expanded the model of eHR acceptance and effectiveness developed by Stone, Stone-Romero, & Lukaszewski [Stone, D. L., Stone-Romero, E. F., & Lukaszewski, K. (2006). Factors affecting the acceptance and effectiveness of electronic human resource systems. Human Resources Management Review, 16, 229-244]. The expanded model provides a more detailed discussion of the communication processes underlying these systems including the effects of media and message characteristics. In addition, we offer a number of testable hypotheses based on the model that can be used to guide future research on eHR systems.
Technology is having a profound effect on the field human resource management (HR), and propelling it in some entirely new directions. For instance, almost all large organizations use electronic human resource (eHR) systems to attract job applicants (Stone, Lukaszewski, & Isenhour, 2005). In addition, they are increasingly using these systems to deliver training, manage employee performance, and administer compensation and benefit systems (Gueutal and Stone, 2005 and Strohmeier, 2007). To date, research has suggested that eHR systems typically increase the efficiency of HR processes, reduce administrative costs, and decrease transaction times (e.g., time to replace employees) (Gueutal & Stone, 2005). However, results of recent surveys show that only 14% of companies report that they have enabled them to make better HR decisions (CedarCrestone, 2007). As a result, there may be problems with the design or implementation of these systems that preclude them from achieving their intended goals (Stone, Stone-Romero, & Lukaszewski, 2003). For instance, electronic HR systems may be less engaging than traditional HR systems, and less likely to capture individuals' attention. Similarly, the messages in electronic systems may lack the richness of face-to-face communication, and prevent individuals from understanding important HR information (e.g., HR rules and procedures, safety guidelines). In an effort to overcome system-related problems organizations have begun to establish HR metrics or standardized criteria that can be used to assess system effectiveness (Cascio & Boudreau, 2008). Some commonly used HR metrics include: (a) system impact (e.g., new hire quality, turnover of high performers), (b) system effectiveness (e.g., vacancies filled internally, grievances resolved successfully), and (c) system efficiency (e.g., time to fill vacancies) (CedarCrestone, 2007). Although establishing criteria for measuring the success of systems is an important first step, this strategy may not always help organizations enhance system effectiveness. For instance, knowing that new hire quality is low does not show organizations how to improve their e-recruiting practices (Chapman and Webster, 2003 and Galanaki, 2002). Thus, we believe that a better understanding of the processes underlying eHR systems may help organizations increase their acceptance and effectiveness. Given that the primary goals of eHR systems are to collect, store, and disseminate information about individuals, we developed a model to advance our understanding of the factors affecting system acceptance and effectiveness (Stone, Stone-Romero, & Lukaszewski, 2006). This model argued that eHR systems modify information flows, social interaction patterns, and communication processes. For example, recruiting systems now use websites rather than face-to-face meetings with recruiters to communicate job-related information (Rozelle & Landis, 2002). Similarly, self-service intranet systems are used to convey benefits information rather than traditional meetings with HR professionals (Marler & Dulebohn, 2005). In view of these changes, some research has focused on the overall effectiveness of eHR systems, and has primarily examined changes in recruiting and training processes (Gueutal & Stone, 2005). However, relatively little research has assessed changes in the processes underlying these systems (e.g., changes in communication or social interaction processes) (Stone et al., 2006). Thus, the primary purposes of the present paper are to (a) extend the current model of eHR to highlight the effects of these systems on communication processes (Stone et al., 2006), (b) consider the extent to which changes in communication may affect the acceptance and effectiveness of key eHR processes (e.g., e-recruitment, e-performance management), and (c) offer directions for future research and practice on eHR systems. Prior to discussing the impact of eHR systems on communication processes, we consider several social psychological models of communication (Hovland et al., 1953, Hovland and Janis, 1959 and Hovland and Rosenberg, 1960). Then, we use elements in these models to expand the current model of eHR system acceptance and effectiveness (Stone et al., 2006).
نتیجه گیری انگلیسی
Despite the widespread use of eHR systems, surveys show that only 14% of organizations report that they have helped them make better HR decisions (CedarCrestone, 2007). Thus, there may be a number of problems associated with the design and implementation of these systems. In an effort to overcome these problems we expanded the model of eHR acceptance and effectiveness developed by Stone et al. (2006). Our expanded model incorporated a more detailed discussion of communication processes including the effects of media and message characteristics on individuals' attention, comprehension, and attitudes. In addition, we offered a number of testable hypotheses based on the model that can be used to guide future research on eHR systems. We hope that our expanded model generates increased interest in research on eHR systems. Furthermore, we believe that it should help organizations develop new systems that meet their needs, and those of their potential and actual employees.