Independent creators strive to attract an audience but often find themselves struggling to manage expectations and opinions once their work gains widespread appeal. We want to trust expert estimations and forecasts but shouldn’t take aggregated estimates at face value. 

In other research featured this month, INSEAD faculty unveil fresh insights on charge anxiety – the new range anxiety – in the adoption of electric vehicles (EVs) and how the market rewards companies that invest in AI and advanced analytics.

From range anxiety to charge anxiety

Is range anxiety still the main factor limiting EV adoption? Charge anxiety seems to have taken over. It arises from five factors: 

1. Hardware: Will the charger’s plug fit my vehicle, and does it work?
2. Software: Will my app or card work at the specific charger?
3. Location: Is a charger conveniently located?
4. Time: How long will charging take?
5. Price: How much will it cost? 

Anton S. Ovchinnikov and his collaborator present three empirically grounded analytical models, each fitted to real data from industry partners, to analyse key issues in the current state and potential trajectory of public EV charging infrastructure. In particular, they focus on the speed of fast charging, the scale of a fast-charging station and driver arrival patterns.

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How independent creative workers negotiate audience relationships

Independent creative workers, from visual artists to musicians, need to achieve widespread appeal. But once they do, managing the relationship with their audience is the next challenge. In a study of independent creators who share their work on digital platforms, Spencer Harrison and his co-authors discovered that after attaining a substantial audience, they get deeply “entangled” with their audience, which then affects their approach to creating. 

This dysfunctional entanglement is characterised by an oppressive dependence on audience reactions, struggling with platform volatility and experiencing distressing emotions. But all’s not lost. Strategies such as distancing themselves from audience input, depersonalising audience critiques and connecting more deeply with their own ideals can help creators move towards a better state, allowing them to once again capture meaning from their audience and to view platform work as sustainable.

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Should you aggregate expert estimates and forecasts?

How frequent are large disagreements in human judgement? Miguel Sousa Lobo and his co-author found that the frequency with which an individual judgement differs substantially from the consensus looks less like a bell curve (or a normal distribution, as widely claimed), but instead is asymmetrical (fat-tailed distribution). 

The findings have important implications for the aggregation of expert estimates and forecasts, highlighting why we cannot simply rely on averaging. The researchers propose a simple heuristic, which performed well for the range of distributions they studied: 73 data sets from four different sources that included over 169,000 estimates and forecasts.

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How the market values AI and advanced analytics investments

How do capital markets respond when firms in traditional industries integrate AI and advanced analytics (AIAA)? Having analysed stock market reactions to 397 announcements by biopharmaceutical firms between 2001 and 2020, Michael Freeman and his co-authors found that average returns following the integration are modest, at 0.58 percent. 

But the average masks variations arising from firms’ characteristics and deal attributes. For instance, are the firms positioned to capture value or are they destroying wealth? Are they organisationally ready, as suggested by their R&D intensity and asset turnover? Are the investments focused on opportunity discovery or simply optimising current operations? The findings highlight the nuanced relationship between AIAA deals and market valuation.

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