Week 23

Brief: Survey and analysis

Group Partners: Xin, Jae. Lulu, Chun

We have some theories and research analysis about trust-building, however, it's still hard for us to connect building trust and the real-life objects. Based on that, we decide to do a quantitative survey about trust.

Survey Results:

1. Game application got the lowest percentage of trust.

2. Compared with other two highest percentage applications, payment app and Location app. Participants trust them most mainly because they have used them for a long period of time.

3. 43% of participants do not want to be tracked, however, 35% will allow tracking when it’s necessary.

4. 57% of participants think allowing track will leak their privacy but they have no choice.

Data Analysis:

1. Building trust between mobile phone applications and users could depend on time.

2. Even though people realized that their privacy would be exposed, they will still conform to the requirements because they need to use the app.

Pain point:

1. According to the research’s data analysis, people do not trust the government system mainly because they don’t get represented by the political party.

2. People are forced to choose the application/system but do not build trust.

3. People are forced to expose their privacy by demands but do not build trust.

Purpose:

1. Letting people engage in the system increases the sense of participation.

2. Attracting people voluntarily choose the system/application, with the knowledge of exposing their privacy, but still have trust.

Target population:

potential acquaintance (e.g friend’s friend, middle schoolmates, with common/similar backgrounds)

Mechanism:

positive and negative reinforcement and punishment

(add a reward to increase the likelihood of the behavior, take away to increase the likelihood of the behavior; add a reward to decrease the likelihood of the behavior, take away to decrease the likelihood of the behavior)

Tutorial:

• Narrow down the research and survey questions, using qualitative methods instead of quantitative. The result of the survey is not for statistical research, it’s for exploring the answers of specific groups of people.

• The design outcome’s aim should not be changing people’s behavior.

• If the outcome is a game, it should have rules, voluntary, aims.

• Reciprocity of the data, trust-building sequence

• Technology as a medium for building trust

• The relationship between trust of people-people and people-technology

Revise:

Having interviews with participants, and asking some deep questions about how they build trust with brands, objects, systems.

Q: Do you have trust in the government system?

Q: Do you have any brands which you trust the most?

Q: Why do you trust it? Or Why don’t you trust it?

Having conversations with participants and listen to their explanations about ‘trust’

Interview Answers:

1. Most of them would like to trust the government because there is no other choice rather than trust them. Everything is controlled by the government.

2. If the demand does not matter, such as food, clothes, daily supplies; people would not care about whether they have trust.

3. Scandal is another key point for consumers, if any brand or system had been exposed to scandal, then consumers would mostly drop their trust level and look for other substitutes.

4. Brand loyalty. If the customers had used such a brand for a long period of time, then they will get used to choosing the same brand.

5. Physically uncomfortable places, never been to somewhere.

6. Stay with family, relatives, surrounded by police or official workers. Familiar places would let people feel trustable.

7. Places that have comfort decoration and interior would create a trustable environment.

8. Improving trust between individuals may have also improved trust in society.

9. Technology does not have the motivation and rational, more trustable than people.

10. The simpler the technology, the more willingness for people to trust.

11. When the technology gets tested in population and market, the trustability would be increased.

12. Simple technology-simple function, such as knife and fork

AEIOU:

A-Individuals may check on their mobile devices about the current density of the cafe shops. They can also check their own habits about preferences, such as how many times there in a year, which one is the favourite, which shop got the highest evaluation. Also individuals may take evaluations after they leave the shop.

E-Public space(cafe shop) which people would usually stay for 10min for purchasing a coffee or lunch. Sometimes they would also stay longer talking with friends, or connecting to the Internet and dealing with work.

I-Individuals go into the cafe shop, they may take an order and wait for a few minutes, or they may stay for longer. They may check the status of the cafe shop on the devices.

O-Any mobile devices with Bluetooth, the Bluetooth would be encoded as a sequence of codes, the user would be anonymous on the devices, and the cafe shop would only detect the code without any personal information.

U-Any individual who goes to cafe shops and has the habit of going to cafe shops. People who have the demands of purchasing coffee may have the request of building trust with the cafe shop. Also, the reciprocity of the data transparency would have benefits for both companies of learning customer’s habits and also for customers to evaluate the brand.

Storyboard: