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postgraduate thesis: Deceived by what? : evidence from telecom fraud dissuasive calls
| Title | Deceived by what? : evidence from telecom fraud dissuasive calls |
|---|---|
| Authors | |
| Issue Date | 2024 |
| Publisher | The University of Hong Kong (Pokfulam, Hong Kong) |
| Citation | Chen, X. [陈孝良]. (2024). Deceived by what? : evidence from telecom fraud dissuasive calls. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. |
| Abstract | As telecom fraud has rapidly evolved and skyrocketed in China, this paper addresses why people are deceived by telecom fraud and how to effectively reduce its social costs. By analyzing detailed call records along with personal characteristics from the Beijing Anti-Fraud Dissuasion System between August 2021 and February 2023, we provide empirical evidence that cognitive variations contribute to susceptibility to deception. Using extreme weather and pollution as exogenous shocks affecting cognitive variations, we employed advanced economic analysis tools, including multidimensional fixed effects models and comparative analysis using survey data, to ensure the robustness and validity. Our analysis shows that the risk of being deceived significantly increases in environments with extreme heat and severe air pollution, and this effect is nonlinear demonstrated a clear U-shaped relationship, with the risk of deception rising sharply under more extreme conditions. Furthermore, we find that anti-fraud dissuasion calls, utilizing specific verbal and vocal traits, can effectively reduce the social costs caused by telecom fraud.
|
| Degree | Doctor of Business Administration |
| Subject | Fraud - China Computer crimes - China |
| Dept/Program | Business Administration |
| Persistent Identifier | http://hdl.handle.net/10722/356442 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Chen, Xiaoliang | - |
| dc.contributor.author | 陈孝良 | - |
| dc.date.accessioned | 2025-06-03T02:17:41Z | - |
| dc.date.available | 2025-06-03T02:17:41Z | - |
| dc.date.issued | 2024 | - |
| dc.identifier.citation | Chen, X. [陈孝良]. (2024). Deceived by what? : evidence from telecom fraud dissuasive calls. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. | - |
| dc.identifier.uri | http://hdl.handle.net/10722/356442 | - |
| dc.description.abstract | As telecom fraud has rapidly evolved and skyrocketed in China, this paper addresses why people are deceived by telecom fraud and how to effectively reduce its social costs. By analyzing detailed call records along with personal characteristics from the Beijing Anti-Fraud Dissuasion System between August 2021 and February 2023, we provide empirical evidence that cognitive variations contribute to susceptibility to deception. Using extreme weather and pollution as exogenous shocks affecting cognitive variations, we employed advanced economic analysis tools, including multidimensional fixed effects models and comparative analysis using survey data, to ensure the robustness and validity. Our analysis shows that the risk of being deceived significantly increases in environments with extreme heat and severe air pollution, and this effect is nonlinear demonstrated a clear U-shaped relationship, with the risk of deception rising sharply under more extreme conditions. Furthermore, we find that anti-fraud dissuasion calls, utilizing specific verbal and vocal traits, can effectively reduce the social costs caused by telecom fraud. | - |
| dc.language | eng | - |
| dc.publisher | The University of Hong Kong (Pokfulam, Hong Kong) | - |
| dc.relation.ispartof | HKU Theses Online (HKUTO) | - |
| dc.rights | The author retains all proprietary rights, (such as patent rights) and the right to use in future works. | - |
| dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
| dc.subject.lcsh | Fraud - China | - |
| dc.subject.lcsh | Computer crimes - China | - |
| dc.title | Deceived by what? : evidence from telecom fraud dissuasive calls | - |
| dc.type | PG_Thesis | - |
| dc.description.thesisname | Doctor of Business Administration | - |
| dc.description.thesislevel | Doctoral | - |
| dc.description.thesisdiscipline | Business Administration | - |
| dc.description.nature | published_or_final_version | - |
| dc.date.hkucongregation | 2024 | - |
| dc.identifier.mmsid | 991044958444403414 | - |
