Publisher's Synopsis
The challenges of (AI) big data gather shapingthe future of retail for consumer industriesAnother challenge of (AI) big data gather is that how to shape the consumer behavior to let business owner to feel or know or predict. It means that how it express it's conclusion or opinion for every consumer behavior after it had gather all big data in any data gather period, e.g. three months, half year or one year consumer shopping model data gather period.Because every kind of industry, consumers will continue to demand price and quality change, with a wide range of convenient fulfilment options among of different kinds of products or services supply. Overall, the (AI) big data gather procedure gives opinion concerns every time retail experience will become more exciting, simple and convenient, depending on the consumer's ever-changing needs. So, I believe that (AI) big data gather every conclusion or result will be different, due to consumer's price and quality demand will often change to every kind of product or service supply in retail industry. So, how to shape (AI) big data gathering's analytical conclusion or result more clear. I shall recommend organizations need to build great understanding of and a stronger connection to increasingly empowered consumers before they plan and implement how to apply (AI) big data gather tool to predict consumer behavior as below: Firstly, (AI) is empowered by technology, the consumer is redefining value. The traditional measures of cost, choice and convenience are still relevant, but not control and experience are also important. Globally, consumers have access to more than 2 billion different products choice by a wide range of traditional competitors and dynamic new entrants, all experimenting with new business models and methods of client engagement.Underground train transportation needs to know passenger behaviour reasonsUnderstanding individual passenger behaviour is essential for the design MTR transportation, because who can choose to catch bus, taxi, tram, train ferry etc. different kinds of public transportation tools. Individual traveler who decides to catch which kinds of public transportation tools, it depends on whether the public transportation tool can provide real time travel information, liking link travel time schedule. So, MTR underground train needs to understand where it has terminal to give convenience to the local living areas of time travelers to choose to catch MTR easily. Although, MTR ticket fare is one factor to influence any passengers choice. But, those other factors can also influence them to choice. e.g. MTR any terminal location of convenience, short time travelling, none crowding in busy (peak) time, MTR platform waiting arrival time, none sudden MTR engineering machines broken accident events occurrence frequently etc. different factors, any one of these factors which can influence passengers who choose to catch MTR or other kinds of transportation tools. Why route choice can influence passenger behavioural choice ? Usually, the busy time passengers will regard the route choice as a coordination problem to influence them to choose to catch which kinds of transportation tools. The route choice is as an opportunity costs to influence any busy time passengers to decide to choose to catch which kind of transportation tool which is the best right choice in the right time among of them. In the short time, for example, it seems any busy time passengers will choose to catch bus to substitute MTR underground train transportation tool, due to who feels the bus can arrive any destinations to compare other kinds of transportation tools in the most short time. However even if the MTR can either charge cheaper ticket fare to sell full day or charge discount ticket fare to sell in the busy ( peak) time to compare to bus fare.