No open-access location is known for this record yet.
No open-access location is known for this record yet.
The Judge-Advisor System (JAS) highlights the importance of advice within the\ndecision making process. Past JAS literature has focused on ways in which to improve\nadvice utilisation and clients’ decision outputs. The aim of this thesis was to focus on an\nunder researched area within the JAS literature: the advice giver. It predominantly\naimed to explore three main input areas in relation to what makes a good advice giver:\ncharacteristics of the advice giver, the quality of advice, and how the advice is given. It\nbegan by identifying individuals’ implicit understanding of what characteristics are\nimportant for a good advisor. A three-factor framework was developed, which relates to\nadvisors’ affect, behaviour, and cognition. Further, it explored whether two external\nmotivators (the type of advisors’ financial incentive and competition between advisors)\nimpacted advice quality (the accuracy of recommendations, amount of advice provided,\nand amount of information acquired) and how the advice is given (how confident the\nadvisor appeared to their client). The type of advisors’ financial incentive impacted\nadvisors’ input within an estimation task, but was not consistent within a choice task.\nCompetition alone was found to have no impact on the advisors’ input. When\ncompetition and the advisors’ incentive (financial or quality) were explored together,\ncompetition, not the advisors’ incentive, impacted advice quality. A combination of\nboth competition and a financial incentive was found to increase advisors’ public\nconfidence. Finally, as advice-giving is an interactive process, the impact on the client\nwas also explored. Clients’ ratings of their advisors’ trustworthiness were found to\npredict advice utilisation which increased clients’ decision accuracy but did not predict\nclients’ decision confidence. The thesis has begun to explore optimal characteristics of\ngood advice givers and how external factors influence advisors’ inputs. Implications of\nthe findings are discussed.
Loading…
Stored only when both papers are in the corpus — 1 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.