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Opis: Purpose: The purpose of this paper is to investigate the effectiveness of a hiring pipeline designed to be cost effective and improve customer experience (CX)—with an emphasis on candidate experience—to increase time to hire, candidate satisfaction, and eventual first year retention across supporting functions in sales, support, and operations in high-volume hiring firms. Design/methodology/approach: A mixed-methods design was utilized and was derived from ATS, CRM logs, industry standards, and AI simulations. Quantitative information was based on a before-and-after quasi-experimental design. In contrast, qualitative information was based on natural language processing (NLP) of recruiter-candidate exchanges using total AI and anonymized candidate surveys. Human-in-the-loop controls and bias checks (metrics) assured flexibility in AI deployment. Findings: Implementation of AI resulted in significant operational and experiential gains. Time to hire decreased from 28.4 to 14.7 days (−48.2%), candidate satisfaction was increased by 40% (6.2 to 8.7), and first-year retention was increased by 19% (72.5% to 86.3%). Qualitative data confirmed operational efficiencies, personalization, and increased perceived fairness. Research limitations/implications: The study was limited to a single large service-focused company, which is based on a pre–post design, without a randomized control group design, and therefore, the findings are not generalizable. Future research should examine AI-driven CX-enhanced hiring in more diverse organizational contexts and longitudinal or controlled experimental designs. Practical implications: With proper AI governance (e.g., bias audits, oversight checkpoints, and transparency), large volume hiring organizations can reduce hiring cycle time; improve retention; and reduce cost via AI-CX. Originality/value: This study demonstrates how AI can jointly improve efficiency and the candidate experience and identifies governance practices needed for ethical and sustainable adoption at scale.
Ključne besede: Artificial Intelligence, Customer Experience, High Volume Hiring, Talent Acquisition, First Year Retention, Human in the Loop
Objavljeno v ReVIS: 19.09.2025; Ogledov: 680; Prenosov: 8
Celotno besedilo (835,48 KB)
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Opis: Customer knowledge as an influence on service provider’s business processes during emergencies is an interesting and relevant research topic. The aim of this research was to identify possible emergency response process improvements based on existing learning processes, and possible future knowledge exchange improvements. I reached the predefined objective, i.e. to identify how customer knowledge influences providers’ business processes and consequently triggers social impact, by conducting extensive work on all five parts of the thesis. I confirmed that the customer-provider relation based on customer knowledge exists and appears in several different forms. Finally, I identified possible improvements of the research and possibilities for further research by applying the designed methodological framework network analysis on a broader geographical scale. A significant contribution of this thesis is the integration of three fields of management: business process management, knowledge management, and disaster management. The research focuses on identifying knowledge-based customer-provider relations by emphasizing customer knowledge as an influence on provider’s business processes and possible consequential social impact. By studying these relations, I went beyond the usual comfort zone of conventional formal organizations and employed a loosely coupled system which emerges as a flood response mechanism during flood events.
Ključne besede: business process management, knowledge management, disaster management, public safety, loosely coupled systems, customer knowledge, flood events, doctoral dissertation
Objavljeno v ReVIS: 22.08.2018; Ogledov: 3986; Prenosov: 167
Celotno besedilo (5,32 MB)