What shall I learn? Two-stage decision making under social influence on corporate E-learning platforms

Yiping Amy Song, Lingling Zhang, Liye Ma, Indranil Bose

Research output: Contribution to journalJournal


E-learning platforms have increasingly been adopted by corporate employees in the workplace. On these platforms, users typically follow a two-stage decision-making process: they first choose which content to learn and then decide how much to continue learning. The decisions of individual employee users are influenced by members of the same workplace organization (group influence) and general users on the platform from other organizations (mass influence). Extant research has not shown how different types of social influence impact different decisions. Using data from a corporate e-learning platform, this study examines how group influence and mass influence support employees' learning decisions, from the perspective of the elaboration likelihood model (ELM). The results reveal that mass users' past choices only influence low-elaborative choice decisions but not high-elaborative engagement decisions. In contrast, workgroup members' past choices influence both the low-elaborative choice and high-elaborative engagement decisions. Furthermore, positive synergy exists between the two types of social influence for the choice decision, but the synergy dissipates for the engagement decision. These findings can help online content platforms design appropriate information-sharing systems to influence users' choice and engagement decisions. The results can also help corporates take advantage of social influence to motivate employees to engage in work-related online learning.

Original languageEnglish
JournalDecision Support Systems
Publication statusPublished - 2023

Bibliographical note

Corporate employees;Corporates;Decisions makings;E-learning platforms;Elaboration likelihood models;Group influence;Learn+;Platform design;Social influence;Social influence information processing;


  • E-learning
  • Economic and social effects
  • Online systems
  • Personnel

Indexed by

  • ABDC-A*


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