Multiperiod Stochastic Resource Planning in Professional Services Organizations

Solomon, Stanislaus; Li, Haitao; Womer, Keith; Santos, Cipriano

doi:10.1111/deci.12370

Cited by 4 publications

(2 citation statements)

References 51 publications

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“…Unlike us, they did not consider competition between multiple IT service providers to win the second-period contract from the client firm. Solomon, Li, Womer, and Santos (2019) studied the vendor firm's stochastic resource planning problem under uncertainty to secure the client's project in bidding competition and stochasticity in resource availability. Unlike them, in our article, we do not consider the vendor's capacity management problem in the IT outsourcing industry.…”

Section: It Outsourcing Literaturementioning

confidence: 99%

IT Outsourcing and Vendor Cost Improvement Strategies under Asymmetric Information

2020

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In this article, we study the scenario under which two information technology (IT) vendor firms compete for the outsourcing requirements of a client firm. The vendors' cost structures are private information. In addition, the vendors can improve their unit costs through learning-by-doing and by making investments in process improvement, that is, induced learning. We study the impacts of vendor-based learning and process improvement in the asymmetric cost setting on the client firm's outsourcing strategy and the vendor firms' process improvement investments. Our analysis reveals that the client firm may adopt the single-sourcing strategy or a combination of dual and single-sourcing strategies depending on the learning efficiency of the vendor base. We also find that high heterogeneity in the vendor cost structure increases the first-period outsourcing requirements of the client firm. Our findings provide interesting managerial implications for the IT outsourcing industry. [

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Section: It Outsourcing Literaturementioning

confidence: 99%

IT Outsourcing and Vendor Cost Improvement Strategies under Asymmetric Information

2020

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“…Therefore, in this paper, we first theoretically model the recruitment quota allocation with the consideration of the impact of the potential applicants. Then, the recruitment quota allocation problem is formulated using a Markov decision process approach [19], which has also been utilized in manpower planning [20] and resource planning [21] in organizations to utilize resources efficiently. Traditionally, a simple recruitment quota allocation scheme, which equally allocates total recruitment quotas among each phase and then allocates the recruitment quotas available in each phase to different departments according to their need, is generally adopted.…”

Section: Introductionmentioning

confidence: 99%

Optimization of the Recruitment Quota Allocation in Intra-Organizational Networks

et al. 2022

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In a decentralized organization such as a university, recruitment is critical for the development of departments. With the limited resources for recruitment, how to allocate the recruitment quotas to different departments is an essential problem for the human resource management center of the organization. Specifically, for a recruitment process that includes multiple phases, a proper number of quotas should be allocated to different departments at each recruitment phase to guarantee the recruitment performance of the whole organization. However, it is difficult since the performance of the whole recruitment process is prior unknown at each recruitment phase. Traditionally, a recruitment quota allocation scheme based on requirements raised by departments is generally adopted, which is somewhat subjective and may not achieve satisfying recruitment performance. To address the above problem, a recruitment quota allocation scheme is proposed in this paper, which is based on the theoretical modeling and optimization of the recruitment process, aiming to provide a more objective and theoretical method that may achieve optimal performance. We first define the recruitment utility as the performance metric for the recruitment process. The recruitment quota allocation problem is formulated using the Markov decision process approach, where the effect of the information of potential applicants is innovatively taken into account. Then, the recruitment quota allocation is optimized by maximizing the recruitment utility to achieve optimal recruitment performance. In addition, a recruitment quota allocation scheme based on the requirements of departments, which is traditionally adopted in the recruitment of a university, is used for comparison with the optimized scheme of the paper. Simulation results show that the proposed scheme can improve the efficiency of recruitment quota allocation significantly.INDEX TERMS Recruitment, quota allocation, organizational network, Markov decision process.

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