1.2. Macro Level Networks

Here, we are talking about macro level networks which has an indirect networks, how from what we are using in Delhi and how it spreads to different cities or different communities across.

Macro level networks refer to the broader systems that enhance the diffusion of innovations across larger populations and regions. Unlike micro level networks, which involve direct, personal interactions (such as friends influencing each other), macro level networks work through indirect connections. For example, if a new technology is adopted in Delhi, it may reach neighboring cities and communities through various communication channels, demonstrations, public reports, etc.

Imagine a popular movie that comes out in a big city like New York. Initially, it's not just the locals who watch it, but through media coverage, reviews, and word-of-mouth, people from neighboring cities like Boston and Philadelphia begin to hear about it, leading to increased viewership across the region. This is similar to how innovations spread through macro level networks.

So, these two contribute at different levels of diffusion, one is in a very close in a more reliable so because someone can come and check it even in a place like IIT, someone is buying a computer so, I keep getting calls that you bought that that how is the feedback so, shall I take it, what is the prize, how did you; how this facility is there or not there so, all this aspect has been discussed.

There are important differences in how innovations undergo diffusion on micro and macro levels. Micro level diffusion tends to involve personal experiences and direct recommendations. For instance, an individual may inquire about a product's performance from a friend who recently purchased it, leading to a reliable source of information. In contrast, macro level diffusion deals with broader influences, such as surveys and market research, which register trends over wider areas.

Think about how people buy new smartphones. A person might consult friends and read direct reviews online to make a decision (micro level), while at the same time, the smartphone brand's ads and market performance reports affect how many people buy the phone in different regions (macro level).

Now, if we take the perception of the most innovative and the conservative, if you see an example now, here a person A who have a group of 5 friends and he is the one who have actually taken the risk of starting it.

This chunk focuses on how different types of individuals within a network influence innovation adoption. The 'innovators' are the early adopters like Person A, who takes risks and experiments with new ideas. On the other hand, more conservative individuals, like Person D, might take longer to adapt, sticking to their familiar routines even as their peers experiment with new options. Eventually, these dynamics influence the broader community's adoption of innovations.

Consider a new video game. The first group of friends (like Person A) excitedly plays it and shares their experiences, while a more cautious friend (like Person D) hesitates. Over time, the enthusiastic play encourages the hesitant friend to give it a try, leading to wider adoption among their circle.

There is also the second argument of it is how in time, how the exposure and the threshold you know how it varies.

Exposure plays a critical role in whether someone adopts an innovation. Person A, who is surrounded by many users of a new technology, is more likely to adopt it due to higher exposure. In contrast, Person B, who has minimal exposure to the same innovation, may remain hesitant. As time progresses and more people around the individuals adopt the innovation, the likelihood of adoption increases. This highlights the importance of social networks in shaping innovation trajectories.

Imagine a new fitness trend, like yoga. If most of your friends are participating and sharing positive experiences, you are more likely to join in due to social influence and exposure. Conversely, if none of your friends try it or share negative views, you might be less inclined to adopt it.

And what are the adopter categories, this is a bell shaped curve which shows the individual innovativeness and percentages in each category.

Adopters of innovations can be categorized into five groups based on their time of adoption in relation to others: innovators, early adopters, early majority, late majority, and laggards. Each group represents a different mindset towards novelty, where innovators are typically the first to embrace change and laggards are the last. This bell-shaped curve highlights how adoption frequency typically follows a predictable pattern within a population.

Consider the adoption of electric cars. Innovators are the first buyers, often tech enthusiasts. Early adopters follow, attracted by the latest technology, while the early majority waits for more validation. The late majority only makes the switch when electric cars become common and socially accepted. Laggards remain hesitant until it becomes universally recognized and readily available.

And similarly, and who are these early adopters; these at a macro level or regional level these are the individuals whose time of adoption was greater than one standard deviation earlier than the average time of adoption.

The concept of thresholds in adoption refers to the point at which individuals feel compelled to adopt an innovation based on the proportion of their peers who have already done so. For example, if an individual's social network consists of mostly early adopters, they might be encouraged to adopt earlier themselves. Understanding these thresholds is crucial for strategizing the diffusion of innovations.

If a new social media platform is introduced, individuals working in a tech-savvy environment may adopt it quickly if their colleagues are already using it. However, in a more traditional workplace where few use the platform, the same individual might delay adoption.

--