Marketing Seminars Fall 2024
Fall 2024, Academic year 2024 -25, Semester A
Note all seminars are scheduled for face-to-face between 13:00-14:00
| Date | Speaker/Affiliation | Presentation |
|---|---|---|
| nov-5 |
|
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| nov-12 |
Ido Erev Technion |
On conceptions (קונספציות), rationality, and populisms |
| Nov-19 | COLLER FACULTY MEETING (no seminar) | |
| Nov- 26 |
SJDM CONFERENCE (no seminar) |
|
| Dec-3 |
Vered Kurtz David NYU |
(Neuro)Cognitive Constraints in Decision-Making: From Consumer Behavior to Strategic Choice.
The human mind has finite computational cognitive capacity. First, I will briefly discuss how specific neurobiologically defined cognitive limitations can yield improved behavioral models of inconsistencies and context-effects in individual decision-making and in consumer choice. Then, I will devote the bulk of the talk to a similar analysis of strategic choice. Classical game theory assumes that players reason their way to Nash Equilibrium. This assumption has been challenged by behavioral data and models showing that humans tend to employ other strategies. Here, I seek to explain deviation from classical theory by introducing a newneurobiologically-inspired measure of game-complexity, which decomposes each interaction into social and non-social arithmetic cognitive demands. Utilizing the economic concept of production functions, I develop a psychophysical approach that models strategic sophistication as the product of a subject’s capabilities on each of these dimensions. In three studies, I show that social and arithmetic demands are contextual factors for sophistication that behave lawfully with psychophysical regularity, that subjects trade-off these capabilities as game-complexity varies, and that performance is a saturating function of processing time and monetary incentives. My results are a hybrid, applying concepts from neuroscience and psychology to strategic choice using the powerful, flexible and predictive formalism of the production function. My findings lay the ground for a detailed neurocognitively-inspired model for strategic choice and suggest several applications for the managerial studies.
|
| Dec-10 |
Liat Levontin Technion |
Mindsets and other-focused behaviors
Does a growth mindset positively influence other-focused behavior, such as prosocial behavior? This relationship is puzzling as although people tend, intuitively, to connect prosocial behavior, therapy sessions and willingness for compromises with outgroups with making a change (e.g., “Give Well - Your donation can change someone's life”; “Time for change foundations”), mindsets theory and empirical findings suggest and show mixed results, including positive and negative relationships, between growth (vs. fixed) mindset and pro-others behavior, including prosocial behavior. I will discuss theory – some conflicting hypotheses, findings from my own research and the results of two meta-analyses that were conducted to synthesize the findings. Results suggest that both growth and fixed mindsets may lead to other-focused behavior, depending on the context. I will discuss some theoretical and managerial implications for the encouragement of prosocial behaviors.
|
| Dec-24 | ||
| Dec-30 | MARKETING IN ISRAEL - BAR ILLAN UNIVERSITY (no seminar) |
|
| Dec-31 |
Moshe Glickman UCL |
How human–AI feedback loops alter human perceptual, emotional and social judgments
Artificial intelligence (AI) technologies are rapidly advancing, enhancing human capabilities across various fields spanning from finance to medicine. Despite their numerous advantages, AI systems can exhibit biased judgements in domains ranging from perception to emotion. Here, in a series of experiments (n = 1,401 participants), we reveal a feedback loop where human–AI interactions alter processes underlying human perceptual, emotional and social judgements, subsequently amplifying biases in humans. This amplification is significantly greater than that observed in interactions between humans, due to both the tendency of AI systems to amplify biases and the way humans perceive AI systems. Participants are often unaware of the extent of the AI’s influence, rendering them more susceptible to it. These findings uncover a mechanism wherein AI systems amplify biases, which are further internalized by humans, triggering a snowball effect where small errors in judgement escalate into much larger ones.
|
| Jan-7 |
Yaniv Dover HUJI |
Cancelled |
| Jan-14 |
Uriel Haran BGU |
Trust Is a Two-Way Street: Why Advisors Who Trust Others Are More Persuasive
Trust is essential for effective collaboration. In advice settings, decision makers’ trust in their advisors determines their willingness to follow advice. We propose that trust in the opposite direction, that is, the trust of the advisor in the decision maker, can affect advice taking. Specifically, we suggest that advisors can increase the influence of their advice by first showing trust in decision makers. In a series of lab studies, we find that initial displays of trust by advisors result in greater acceptance of their advice. This effect persists across different levels of advice quality, attenuating the underutilization of high-quality advice but also exacerbating overreliance on low-quality advice. Decision makers not only follow the advice of advisors who trust them, but also respond similarly to advisors who display trust in other people. We find that people perceive trusting advisors as more accurate and competent than distrusting advisors. They also report an obligation to reciprocate the advisor’s behavior, which results in greater advice taking even when the trusting advisors are not perceived as more accurate. Our findings shed light on the dynamics of trust and persuasion in advice relationships and provide insight for advisors who wish to maximize the effectiveness of their input.
|
| Jan-21 |
Yonatan Vanunu TAU |
Coping With Complexity: A Selective Sampling Account of Consideration Set Formation for Product Bundles |
| Jan-28 | ||
