Перейти к основному содержанию
AkademIndex

Продукты

Для разработчиков

AkademBaseскороОткрытый API экосистемы
Латиница
Русский
Статья

CONSTRUCTION OF A USER CONTINUOUS GROWTH GUIDANCE MODEL IN INTELLIGENT TALENT ASSESSMENT PLATFORMS: AN INTEGRATED STUDY BASED ON BEHAVIORAL DECISION-MAKING AND CONSUMER PSYCHOLOGY

Wang Biao"Silk Road" International University of Tourism and Cultural Heritage
ABI

Аннотация

Against the backdrop of rapid development in the knowledge payment industry and intelligent talent assessment platforms, the challenges of rising customer acquisition costs coupled with low user retention and repurchase rates have become critical constraints on sustainable platform development. Current practices often treat the one-time assessment and report delivery as the service endpoint, neglecting the systematic guidance of users’ subsequent behavioral decisions and long-term growth paths, leading to a massive exodus of users after the assessment. In response to this practical dilemma, this study systematically integrates consumer psychology and behavioral decision-making theories, employing a conceptual modeling approach within the design science research paradigm to construct a “User Continuous Growth Guidance Model”. The model delineates the user behavioral path into five interconnected stages—“Cognitive Trust Building,” “Emotional Identification and Value Alignment,” “Low-Threshold Behavior Initiation,” “Value Solution Presentation,” and “Growth Outcome Feedback and Reinforcement” and explicates the underlying psychological mechanisms and decision-making logic at each stage. Conceptually, the model suggests that by systematically embedding corresponding mechanisms into product design, platforms can transform one-time assessment relationships into long-term, growth-oriented partnerships, thereby significantly enhancing user lifetime value. This study not only provides an integrated framework for understanding user behavior in the assessment context but also formulates actionable guidelines for platform content structure design and operational strategy.

Темы

Идентификаторы

Цитирования и источники

Цитирований: 0Использованных источников: 0
Показатели — AkademScholar · Скоро