4.2.2. Adoption Network Exposure

decide upon it, they are referred normally as laggards, or there is also these early majority and the late majority. Here, we are talking about I found this really awesome tool because they will just tried it but then you know at this stage I wish I do try it using this earlier, it is great so you know, they sometimes repent, better we have not tried it before it has been a successful you know, so like that these laggards, this is how there is also we talked about the micro level network which has to do with the personal and direct diffusions.

In this chunk, we explore different types of adopters in the innovation adoption cycle. Laggards are individuals who are the last to adopt new innovations, often influenced by the earlier groups like early majority and late majority. The text emphasizes the feeling of regret laggards might have for not adopting a successful innovation sooner. The focus also shifts to the micro-level network, which refers to personal or direct interactions that can influence an individual's decision to adopt an innovation.

Think of a new smartphone model released. The 'laggards' are those who wait until the phone has been out for years, hearing from friends (who might be in the early or late majority) about its success. They might eventually end up buying it but often feel they should have gotten it sooner, missing out on features that were beneficial earlier.

And the second one is with a 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 and this is where the macro level networks, it goes along with a very different indirect networks as well.

This chunk contrasts micro-level networks, which involve close, personal interactions, with macro-level networks where the influence is more indirect and widespread. For instance, a new technology adopted in Delhi can spread to other cities through various indirect means, such as social media or news reports. Macro-level networks tend to reach larger audiences at a greater distance, whereas micro-level networks focus on intimate, personal connections.

Imagine social media. A trend may start locally in a group of friends (micro-level) but then spread widely through shares, likes, and news articles, reaching thousands outside the original circle (macro-level). The people in larger cities eventually learn about the trend through channels that are not personal but widely distributed.

So, similarly when you are looking at a larger picture that is again the macro level networks whether it has been implemented in Delhi, whether implemented in Roorkee you know so this is how we looked at it. 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. And then, whereas in the person D, he is still in a conservative but his; all his surroundings still relying on his own ways of thinking though his network have started erupting, he takes time to think about it.

This chunk introduces the concept of individual differences within networks. For instance, person A represents an innovator, as he is willing to take risks and try new ideas, influencing his friends. In contrast, person D is described as conservative, hesitant to change despite seeing changes around him. This example illustrates how innovative and conservative tendencies coexist within social networks, impacting the diffusion of innovations.

Consider a new workout trend. Person A eagerly joins group classes and shares experiences proudly with friends, influencing them to join too. Person D, however, prefers sticking to traditional exercises and is hesitant to change, despite seeing friends enjoying the new trend. This shows how individual comfort zones affect the adoption of new ideas.

There is also the second argument of it is how in time, how the exposure and the threshold you know how it varies, in time 1, like you have that there are 2 reference points which we are referring in this small example, one is A and one is B. And A has again the 5 friends and B has 5 friends and they have their own networks...

This chunk discusses the dynamics of innovation adoption over time between two individuals, A and B, within their respective networks. Initially, A has a higher exposure to innovation due to his friends already adopting it. In contrast, B's network hasn't adopted anything. Over time, these dynamics can shift, as the adoption spreads from one network to another. This highlights how timing and individual circumstances contribute to the adoption process.

Think of a viral video. At first, only a few people (like A) watch it and share it with friends. Over time, more and more people (like B) see their friends engaging with it, and eventually, B may watch it as well when it becomes widely discussed. The difference in exposure at the start is crucial in determining who adopts first.

So, what are the adopter categories, this is a bell-shaped curve which shows the individual innovativeness and percentages in each category... So, this is how they configured.

This chunk defines different adopter categories as part of the innovation adoption curve, which illustrates the distribution of various types of adopters. These include innovators, early adopters, early majority, late majority, and laggards. By establishing thresholds for each category based on standard deviation, this classification helps researchers understand how innovations spread within social networks.

Think of a new video game. The 'innovators' are the hardcore gamers who buy it on release day. Then come the 'early adopters,' who wait a bit but still get it soon. The 'early majority' are those who buy it when they see others enjoying it. The 'late majority' wait until it’s on sale or very popular, and 'laggards' are those who avoid it altogether or only play it years later when there's no hype. This categorization helps game developers strategize marketing efforts.

And with the micro level or the neighbourhood level, as I told you that there is a very low threshold, low threshold, high threshold and the laggards, so you have the personal network threshold which is defined as an adoption network exposure at the time of adoption...

This chunk delves into the concept of threshold in personal networks during adoption. It addresses how individuals within a network have varying influences on each other. The adoption thresholds can be classified into very low, low, high, and extremely high. Individuals with very low thresholds are affected easily, while those with high thresholds require more persuasion or influence before adopting new innovations.

Consider getting a new app. Some friends (low threshold) might download it just because you've recommended it, while others (high threshold) might take weeks to decide, needing substantial proof from others using it first. This relates to how easily different people within a social circle adopt new technologies or products based on their threshold.

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