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Dilip Soman, Professor of Marketing at the University of Toronto's Rotman School of Management, & Bing Feng, Manager of Behavioural Finance at TD Wealth.
In our second episode on the Behaviourally Informed Organizations partnership, Dilip Soman and Bing Feng tell us about international collaborations to reduce sludge in governments and work applying behavioural science to poverty reduction. Throughout, Dilip and Bing highlight the power of partnerships, the importance of context, new areas of research and application for behavioural science, and (of course) advice for embedding BI into organizations.
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ตอนอื่นๆ ใน PODCAST นี้
Yann Cornil, Associate Professor of Marketing and Behavioural Science at UBC Sauder School of Business.
As a French food researcher, Yann Cornil was surprised by North American eating habits and messaging about good vs. bad foods. Yann's research with Pierre Chandon suggests that we eat less a…
Julie Szabo, Principal at Capulet.
At Capulet, Julie Szabo has worked on a wide variety of online communication campaigns. In addition to sharing general wisdom for creating social media campaigns and measuring their impact, Julie tells us about recent projects promoting HPV vaccines in Bangladesh,…
Kieran Findlater, Lead for Behavioural and Data Science at the Impact and Innovation Unit.
Kieran Findlater shares how his cross-disciplinary background prepared him to work at the Canadian federal government's Impact and Innovation Unit (IIU). Kieran explains the IIU's approach to projec…
Clea Stone, Associate Director at The Sound.
Because Clea Stone recently completed the Advanced Professional Certificate in Behavioural Insights to complement her existing skillset from a decade of work in market research, she's perfectly equipped to help us explore the intersection of market …
Takuro Ishikawa, Senior Behavioural Scientist with the BC Behavioural Insights Group (BC BIG).
Tak Ishikawa returns to the podcast to help us understand the recent "debate" about boosts and nudges. To help ground the conversation, we disentangle terms like heuristics, biases, nudges, and …
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