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Chun Ngai (James)

6 June 2022 - 12 June 2022
MA 2022
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About

Hi, I am James, and I am a service designer and UX designer who is interested in co-creation, economy and social innovation. Having precise instincts on data analysis, business strategy and North Star Metric. Currently, I am a year-2 student at RCA, major in Service Design.

Final Project 2022

WIP project 2022

To meet the climate goals, over half of the cars on the UK's roads need to be EVs by 2032. We intend to design a platform that will allow residents to apply for the installation of public charging points.  The platform will act as a bridge between the residents and the council. Although most UK councils already have similar application channels, different councils have different platforms, processes and criteria, which causes confusion for users. In the service ecosystem built under the prototype and vision we have designed, users will be able to add an application directly on a map with a click, and the council will share the results of the data collection. Ultimately, users will have a unified platform for applications, communication, checking progress and viewing technical and legal constraints.


We hope to convince councils to adopt this platform, with the potential benefits of increasing insightful feedback by weakening barriers of requesting and reducing the cost of dealing with user enquiries and complaints by increasing transparency of information. EV & potential EV users are very keen to co-creatively participate in the planning of public charging points. With proper guidance, people are immeasurably creative.

FINAL PROJECT PROPOSAL

Perception and regulation of collective emotions in the office environment

The moods and feelings of employees often influence the atmosphere of the office environment and have various effects on productivity. In some large companies, it is relatively difficult and costly for entrepreneurs to perceive the emotions, stress and true feelings of employees within a particular unit. How can we help entrepreneurs to efficiently perceive the moods of employees in multiple departments so that they can intervene and adjust and indirectly improve productivity?