An Analytical Model of E Recruiting Investment Decision An Economic Employment Approach in Python

The online recruiting market is one of the most rapidly growing e-commerce areas. Since the mid-1990s, a number of e-recruiting methods such as job boards, corporate career Web sites, and e-recruiting consortia have been introduced into the labor market. Among them, e-recruiting with the use of a corporate career Web site has been touted as the most efficient and cost-effective recruiting method. While the corporate career Web sites have experienced a phenomenal growth, no formal economic models have been developed for the analysis and assessment of investment decisions in various e-recruiting technologies. In this paper, a mathematics-based economic decision model for e-recruiting technology investment is introduced to evaluate the economic impact of various e-recruiting technologies. A classical economic order quantity (EOQ) model was extended to include costs uniquely associated with recruiting activities such as staffing and coordination costs. We derive a minimum employment level for an optimal investment in e-recruiting technologies. The model suggests that the optimal investment cost increases rapidly near the minimum number of employees to be recruited, but the growth of the optimal investment cost slows down as the total number of employees becomes greater than the minimum number of employees to be recruited.