1. Introduction

In the fast-developing high-teach era, big data technology has been developing rapidly. All industries need professional talents to improve technology informatization, marketing, and enterprise management [1]. In the era of big data, all data can be accurately analyzed and aggregated. For many enterprises, this is a good way to get an accurate picture of customers' consumption preferences. However, in many fields, big data has not yet been realized. For example, in the field of high-speed rail, which we are currently studying, we have not been able to allocate seats to consumers according to their environmental preferences. Our team is trying to outline how we intend to develop a platform. This platform will enable passengers to tailor their preferences and requirements during their high-speed rail journeys. Subsequently, using big data analytics, we will assign them to the most appropriate seats with the primary goal of enhancing the overall user experience. In this article, we discuss the market space for personalized platforms for high-speed rail seat selection.

2. Methodology

Jinglin Nan mentioned some of the improvements made to passenger comfort on passenger railways, including the introduction of nondisruptive services in carriages and the prohibition of uncivilized behaviors such as shuttle hawking that affect the rest of the passengers [2]. However, the behaviors prohibited by these measures are not the main factors affecting passenger comfort at present. The series of measures already in place have not accurately addressed the existing pain points in HSR operations. Therefore, in this study, our team first found out the existing pain points of this industry, such as noise disturbance from nearby passengers, crowded conditions, and lack of information about passengers' experiences on high-speed rail.

Thinking about the possibility of bringing this designed product to market, our team initiated the project with internet research to understand the existing landscape of the seat selection system.

In our study, we formulated certain hypotheses, speculating that passengers, when confronted with the aforementioned interruptions, would show an increased inclination to use our platform. Furthermore, we postulated that users' willingness to use our platform would be correlated with their frequency of high-speed rail use.

To test our hypotheses, we created a market research survey focused on a diverse demographic with latent needs, with the goal of gauging the public's sentiment toward integrating our platform to enhance their high-speed rail experience. The questionnaire was published online on popular social media platforms with a sample size of 66. It includes both quantitative and qualitative questions.

During this comprehensive survey, we initiated our inquiry by delving into various aspects of user demographics, geographic locations, motivations driving their selection of High-Speed Rail (HSR) as a preferred mode of travel, and the primary purposes underlying their HSR journeys. Our overarching objective is to construct a multifaceted user profile via meticulous data analysis. To discern the geographical distribution of respondents, we sought to ascertain whether they resided in regions endowed with extensive HSR networks. Furthermore, we inquired about the frequency with which respondents avail HSR services annually, with an intent to explore potential correlations between travel frequency and the inclination to utilize our seat selection platform.

Undesirable stimuli from outside (e.g., disturbances such as noisy and crowded carriage environment) will reduce passengers' comfort and easily stimulate passengers' negative emotions, which in turn will affect passengers' evaluation of and trust in the HSR and lead to bias in their evaluation of the HSR [3]. In the central segment of our study, our investigation centered on assessing whether participants had encountered interruptions during their HSR travels. We invited respondents to elucidate the types of disruptions they had most frequently experienced. Furthermore, we probed the significance of these disturbances from the users' perspective by asking them to elucidate the factors of paramount concern during their HSR journeys.

Our survey also delved into the realm of user preferences and willingness to pay for the features of the platform we have designed. We inquired whether respondents would be inclined to incur a fee for utilizing the platform and explored their preference between a fixed fee or a percentage-based charge linked to the ticket's face value. Additionally, we embarked on an exploration of the users' expectations regarding the additional features and functionalities they envisage in our platform. This multifaceted inquiry framework enables us to offer a comprehensive overview of the user landscape, their needs, and their attitudes toward the innovative HSR seat selection platform.

In conclusion, our survey is structured with a twofold purpose. Firstly, it is designed to gather fundamental customer details, including location and age group, in order to provide us with valuable insights into their preferences, dissatisfied experiences, and their receptiveness to enhancing their railway journeys through the acquisition of our products. Secondly, the survey encompasses a segmentation strategy where users are categorized by age group and the primary purpose of their high-speed rail travel. This division allows us to delve deeper into user pain points, which are subsequently utilized to inform the personalized seat allocation process based on individual preferences and needs, thereby aiming to optimize their overall railway experience.

3. Results

The 4P model, first summarized in McKinsey's book Basic Marketing, also known as the marketing mix, is a basic framework in marketing that consists of four key elements. If a company produces the right products, sets the right prices, uses the right distribution channels, and is supported by the right promotional activities, then the company will be successful [4]. We will illustrate our findings using this particular model.

Overall, 66 people have participated in our questionnaire survey. Since the aim of our product is to allocate passengers to the seats that would satisfy their needs to the maximum extent, this survey serves the purpose of better identifying the potential customers and their preferences. According to the results (see Appendix A), all our participants aged from 18 to 44 of which the majority seems to be between the ages of 18 to 24, accounting for 75.76%. Regarding locations(see Appendix B), results show that nearly 40% of our participants are located in more developed regions such as Shanghai and Zhejiang. It provides insight into the demographic profile and geographical distribution of our potential customers.

Our survey has found that almost half of the people who take high-speed trains are traveling. 24.24 percent took the train to visit relatives. (see Appendix C) 16.67% and 3.03% of those who use high-speed rail for commuting and business purposes, respectively. The remaining 9.09% of people take HSR most commonly for other purposes. Take high-speed rail for commuting and business purposes often take HSR frequency is relatively high, there are requirements for a good riding environment. People with business purposes, especially, usually want to have a quiet driving environment to facilitate their office. Most of the people who are used for tourism and leisure take a long time and need a more comfortable environment for them to rest. Through this data, we can roughly understand the needs of consumers so that we can better design our system.

The next question is about people's unpleasant experiences with high-speed rail. We asked if they had ever experienced disruptions on a high-speed rail trip. 71.21% of people have had such experiences, and only 28.79% have rarely had them (see Appendix D).

We also added a fill-in-the-blank question to find out what kinds of interruptions bothered them. It shows that these interruptions include noise from other passengers (e.g., children crying, a passenger talking loudly on the phone or playing a short video), passengers reclining their seats too far back, and rear passengers kicking the back of their seats(see appendix E). All of this demonstrates the need and importance of creating a personalized seat assignment system.

The product in the 4P model refers to the sum of things that people acquire through purchases that satisfy certain needs and wants. It includes both product units in concrete material form and benefits in intangible form. Our product is the service we provide to passengers through our system to select their seats based on their preferences. In order to determine the functions of our product, we must first investigate people's needs. We then asked what factors are most important to passengers when choosing a seat on an HSR, and we allowed participants to select more than one option from which to choose. We found that 81.82% of people think having a relatively quiet seat is most important; 59.09% think having enough room for their legs is important; 46.97% want to be closer to the charging station; 36.36% think it's important to have a nice view out the window; 19.7% think the price of the seat is the most important factor; 19. 7% want seats close to public services such as restrooms or food carts; 16.67% of respondents also think an aisle seat is important; only 4.55% cited accessible spaces, such as accessibility for passengers with mobility impairments, as the most important consideration(see appendix F). This shows that people are more concerned with physical comfort and their own experience on a high-speed rail journey.

Based on the survey results (see Appendix G), it is evident that 43% of the respondents are highly interested in our product, 50% are interested. In comparison, only 6.06% expressed general interest, with no respondents indicating disinterest. These survey findings strongly suggest that our product has a viable market.

In terms of user expectations for features, 75.76% of respondents chose "Select child-free seating," 65.15% selected "Choose seats near charging outlets," 66.67% preferred "Select spacious seats (e.g., front row)," and 50% opted for "Apply for seat change online to communicate with others."(see appendix H) The high proportion of respondents choosing these features indicates that our envisioned product features align well with public demand.

Furthermore, in the section where respondents could suggest additional features, some mentioned the need for "registering and labeling passengers with children" and suggested considering "implementing women-only carriages based on international precedents."(see Appendix I) These suggestions align with the previously identified sources of intervention and the gender distribution of our user base. These proposed features are highly relevant to the disturbances described by users in the earlier section, demonstrating that our product features can address some user pain points.

As for how to charge fees (see appendix J&K), 59.09% want to charge prices as a percentage of the face value, while the rest want to charge fees through a fixed price. We can see that most people still support charging a percentage of the face value as a more fair and reasonable way to set prices. According to the price in the 4P model, price refers to the amount that a customer must pay to obtain a product or service. It involves pricing strategy, discounts, payment terms, and many other decisions. At present, we have few competitors in the market, so there is no need to consider pricing based on competitors' prices. At present, our tentative plan is to charge 8% of the face price. As for discounts, we will also make some preferential policies for consumers. During some holidays, such as the Spring Festival and National Day, when people have more travel needs, we can provide this service for consumers free of charge. In terms of payment terms, we certainly support all domestic online payment methods, including but not limited to Alipay, WeChat, credit cards, etc.

4. Discussion

It is clear from this research that there is still a huge market for human comfort improvement in high-speed rail. The survey of high-speed rail passengers revealed that there are many problems in such a large market. For instance, there’s no way for passengers to choose a relatively ideal seat based on their own preferences or prevent themselves from being bothered by a crying infant or noisy children who sit next to them randomly all trip long. This blank space gives us the opportunity to enter the market and gives us an advantage. According to the placing strategy in the 4P model, the place refers to distribution channels. Our company does not directly face consumers but focuses on the cultivation of distributors and the establishment of sales networks, and the connection between enterprises and consumers is carried out through distributors. According to the monitoring report of China E-business, the yearly revenue in 2010 was 4500 billion RMB. The YOY growth is 22%. B2B revenue is 3800 billion RMB. The YOY growth is 15.8%. The total revenue from internet retail is 513 billion RMB. There are roughly 25,000 E-business vendors [5]. We, therefore, will use the selective distribution approach as a plug-in and collaborate with some main OTA platforms like XieCheng QvNaer, which have been used for a long time. This relates to the Place aspect of the 4P strategy and would definitely be a win-win approach. According to the survey, our plan to create such a seat selection system is well-received by most of people. And these OTA apps have already had a large customer base. Thus, our product will have easy access to our target customers, and these OTA platforms will enhance their customer satisfaction at the same time. The results of our group’s survey were then used to determine the price of our service and the potential functions or features that our system will have. The next step for our business is likely to develop to a stand-alone app from a simple plug-in system. This means that we will have greater autonomy and be able to control user data completely independently. It will also allow us to expand our business further, and we may consider collaborating with other travel services. However, in the course of our research, we found that even though we have partnered with a few major OTA platforms, it is still difficult for us to cover all HSR passengers, so there is a risk that passengers purchasing HSR tickets through OTA platforms that are not our partners will not be taken into account and controlled by our system, and will tend to upset our categorization and allocation of seats to known passengers. This is an issue we need to address in the future.

5. Conclusion

The product we launched is a high-speed rail personalized seat selection system attached to the high-speed rail ticket purchase software. According to consumers' different preferences, they can choose the most suitable seat for them to provide the most comfortable riding environment. Through our survey, we found that most people have unpleasant experiences on high-speed trains. This also allows us to determine that this pain point does exist in the current market. At the same time, we also found that our customers, who are mostly younger and in more developed regions, also expressed a great interest in our products. Regarding the charging of fees, most people also expressed the hope that fees could be charged by a percentage of the face value. These are all consistent with our assumptions. In terms of the contribution of products, our surveys played a crucial role, which has not only helped us further target specific customer groups but also consummate our online seat allocation algorithm, which aims to cater to our customers with the best possible seat that meets their requirements. Regarding the limitations, since there is a wide range of potential needs customers may be willing to fulfill, as well as the fact that each customer would come with a different combination of seat preferences, it seems that there needs to be a well-designed algorithm in place to ensure the effectiveness and usefulness. With the mission of constant improvement, one of the recommendations could be employing more expert technicians to upgrade and maintain the algorithm from time to time to assure product satisfaction.

Acknowledgement

Shuyao Zhou, Ziyi Zhou, Muhang Zou, and Yujie Zhang contributed equally to this work and should be considered co-first authors.