NetLogo User Community Models

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## WHAT IS IT?

This model explores the dynamics of a new brand expansion on a market dominated by an incumbent brand, focusing particularly on sectors where trust and reputation critically influence consumer choices, like the banking sector.
It demonstrates the key factors determining whether a new brand can successfully penetrate the market or when its growth will be hindered.

## HOW IT WORKS

Our model sets up a scenario with customers choosing between two brands: Blue and Red.

It consists of a network of customers and brand ambassadors where each link has a `trust` property, influencing how much weight a peer's opinion has.

Initially, almost everyone uses the Red brand and isn't aware of the Blue brand, except for one brand ambassador who's out there spreading the word about Blue and criticizing the Red brand.

Each agent has `experience-brand-red` and `experience-brand-blue` properties, which reflect their satisfaction with each brand. Their `social-score-brand-red` and `social-score-brand-blue` represent the collective opinion of their peers about each brand.

When a customer's satisfaction with their current brand dips below the `abandonment-threshold`, they start looking for better options. If they find a better brand with a good enough reputation (`social-score > adoption-threshold`), they'll make the switch.

As customers continue to engage with a brand, their experience evolves. In the current version of the model, we are using the normal distribution of experiences where `global-experience-brand-blue` and `global-experience-brand-red` set the expected value of the distribution for each brand.

## HOW TO USE IT

The model visualizes customers' brand preferences with colors — blue for Blue brand customers and red for Red brand customers.

- The `setup` button creates a new network structure

- The `reset-adoption` button resets the network to its initial state, keeping the current network structure but reverting all customers to the Red brand.

- `adoption-threshold` sets the minimum social score needed for a brand to allow customers to consider it when switching brands.

- `abandonment-threshold` controls the minimum experience value the brand should maintain to keep its customers from reconsidering their purchase decision.

– `global-experience-brand-blue` and `global-experience-brand-red` determine the mean experience customers have with each brand.

– `market-size` and `network-density` allow you to control the size and the structure of the network

Every time when you click `setup` or `reset-adoption` one of the peers of the Blue brand ambassador is chosen as a `monitored-customer`. You can manually select other monitored customer by entering their ID into the input.

On the right, there are plots for brand adoption by time, a histogram of experience for each brand among the customer base, and an average social score that allows you to see the current state of the whole market. On the average social score plot there is a black line that shows the `adoption-threshold` to highlight the critical points of the system.

You can click the `inspect` button to inspect the monitored customer. Additionally, the plots of the monitored customer's experience and a list of his peers are available for detailed exploration.

At the bottom, you can find several buttons with preset global values. The related presets are described below.

## THINGS TO NOTICE

When `abandonment-threshold` is at a minimum, no one will change their brand, as customers are not sensitive to their experience with the brand.

Conversely, if `abandonment-threshold` is high, only a slight advantage in experience can prompt customers to switch brands.

Initially, nobody knows about the Blue brand, and the Red brand dominates the market. However, once the Blue brand gets introduced to a customer by the ambassador, its spread largely depends on how its experience, customers' abandonment, and adoption thresholds.

## THINGS TO TRY

Due to the randomness of the model, it is suggested to try running the scenarios several times to see the most common outcomes.

Try the following cases by choosing the corresponding presets on the interface tab:

- **Case 1**: when the Blue brand matches the Red in quality, how easy is it for a newcomer brand to penetrate the market? What values for `adoption-threshold` and `abandonment-threshold` make it easier for a newcomer to take its share of the market? Try to increase speed and see how far the Blue brand will get in the long run.

- **Case 2**: The blue brand significantly outperforms its competitor in quality, abandonment threshold is low (customers are not sensitive to the quality of experience). Try to gradually increase the threshold and see how it influences the distribution of the Blue brand across the market.

- **Case 3**: The blue brand is slightly better, abandonment threshold is high (customers are sensitive to the quality of experience). Try to gradually decrease the threshold and see how it influences the distribution of the Blue brand across the market.

Can the Blue brand spread across the market if its social score among the customers connected to the brand ambassador falls below the `adoption-threshold`?

## EXTENDING THE MODEL
In our current model customers decide on their brand based on the experience of their peers. The customer makes a reconsideration only when their own experience with the brand falls below the threshold. Customer experience with the brand changes based on constant fluctuations generated by the normal distribution.

The model can be extended by considering more factors that influence brand choices, like marketing campaigns, pricing strategies, perceived product security, variety of offerings, and changes in the company's ethics. Integrating these into the model can make it more relevant and powerful for specific market analyses.

Additionally, tweaking how customer experiences evolve to reflect more realistic, occasional changes could offer a more accurate view of consumer behavior.

## NETLOGO FEATURES

Breeds are used to differentiate the behavior of customers and brand-ambassador.

We are using `random-normal` function to produce a normal distribution of customer brand experience.

`nw:generate-preferential-attachment` is used to generate the network of customers.

`[other-end] of my-in-links` is used to get to the peers of the current customer

## RELATED MODELS

[Informaion Diffusion](https://s3.amazonaws.com/complexityexplorer/ABMwithNetLogo/model-7.nlogo) model from [Introduction to Agent-Based Modeling](https://www.complexityexplorer.org/courses/183-introduction-to-agent-based-modeling) course of Complexity Explorer

## CREDITS AND REFERENCES

© 2024 Alex Bazhanau
https://bazhanau.net

This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License
https://creativecommons.org/licenses/by-sa/4.0/