A simulation-based decomposition approach for two-stage staffing optimization in call centers under arrival rate uncertainty

Ta, Thuy Anh; Chan, Wyean; Bastin, Fabian; L’Ecuyer, Pierre

doi:10.1016/j.ejor.2020.12.049

Cited by 6 publications

(1 citation statement)

References 34 publications

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“…They are normally commissioned by various commercial, governmental, or research entities to engage in a variety of commerce-and research-based activities from sales to customer support to marketing (see Gans, Koole & Mandelbaum, 2003). Centers have employed a variety of strategies to improve efficiency and maximize profits, including 24-hour staffing, just-intime performance evaluations, incentive programs for rapid or high-quality output, and optimized cueing (see, Ta, et al, 2021;Borst, Mandelbaum & Reiman, 2004). More recently, call center performance has been enhanced and expanded via machine learning, AI, and deep learning processes (see, e.g., Woodcock, 2022;Deschamps-Berger, Lamel & Devillers, 2021).…”

Section: Industrialized Fraud: Asian African and Latin American Call ...mentioning

confidence: 99%

The Cyber-Industrialization of Catfishing and Romance Fraud

Wang,

Topalli

2023

CrimRxiv

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We examine a new form of online fraud closely related to traditional online romance fraud and catfishing, but which is "industrialized" through enterprise business practices, software platforms, and customer service processes. We conducted an inductive analysis of publicly available testimonial and review data provided by current and prior employees of a specific company in the online customer service contract space. Companies hire individuals online to work as "chat moderators" or "customer service providers" who are told that they are to advance engagement on social media platforms. In fact, they are being recruited as "sexting" workers, paid on a per-text basis to engage in intimate chatting with clients led to believe the workers are female participants on a dating site. The process is mediated via client management processes that monitor employee productivity and monetize all interactions between "clients" and "workers." The company executes these processes with great efficiency by algorithmically assigning multiple workers to individual clients and assembling background files on clients in real time. We refer to this corporatized form of fraud as Intimacy Manipulated Fraud Industrialization (IMFI) and find that workers serve as both exploiters of their clients as well as victims of the company they work for.

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