Dissertation Research: Organizational Structure and Training Strategies: The Effect of Organizational Characteristics on Employee Training

小行星9600187 本博士论文的改进建议探讨了组织和环境因素对雇主在员工培训方面的投资的影响。 据推测，培训时数和提供/采取的培训课程的数量是正相关的子公司规模，环境的复杂性，劳动力市场的竞争，和利润。 研究人员将研究一家大型营利性公司、其子公司以及这些子公司的500名员工。 该组织的分支机构多种多样，地理位置分散，这将使调查人员能够探讨分支机构的具体组织特征如何影响培训的过程和结果。 将调查的三个基本问题是：（1）组织的环境和结构对组织提供的员工培训量有什么影响？(2)这些特征如何影响培训部门的结构？（3）组织结构、环境、员工个人特征与不同特征的员工接受培训的数量和类型之间的关系是什么？ 这项研究将为组织社会学以及组织和政府培训政策的理论和实证辩论提供信息。 %将通过对员工个人的调查、深入访谈、档案来源和参与者观察来收集数据。 组织和个人层面的数据将使用多层次的统计技术进行分析。

9600187 Reskin This doctoral dissertation improvement proposal examines the effects of organizational and environmental factors on employers' investments in employee training. It is hypothesized that the amount of training hours and the number of training courses offered/ taken are positively related to affiliate size, environmental complexity, labor market competition, and profits. The investigator will study a large for-profit corporation, its affiliates, and 500 employees within these affiliates. The diverse and geographically dispersed affiliates of this organization will permit the investigator to explore how affiliate-specific organizational characteristics affect the process and outcomes of training. The three basic questions that will be investigated are: (1) What effect does an organization's environment and structure have on the amount of employee training the organization provides?, (2) How do these features influence the structure of the training department? and (3) What is the relationship between the organizational structure, environment, characteristics of individual employees and the amounts and type of training that employees with different characteristics receive? This research will inform theoretical and empirical debate in the sociology of organizations as well as orgnizational and governmental training policies. %%% Data will be collected through surveys of individual employees, in-depth interviews, archival sources, and participant observation. Organizational- and individual- level data will be analyzed using multi-level statistical techniques.