A Novel Service Provision Mode for Sustainable Development of the Telecom Industry

Abstract

The deepening integration of telecommunication technology into other industries has giving birth to a variety of new applications, such as self-driving, telemedicine, and intelligent manufacturing. Whether the telecom service is traditional or new, users put forward personalized and multidimensional requirements for performance, which results in a conflict between their requirements for customized service and the failure of telecom enterprises to meet every requirement. This contradiction directly influences the sustainability and stable development of the telecom industry. To address this problem, this paper carried out systematic research into collaboration and adaptation between business-model and technological innovation. From the view of business-model innovation, this paper proposes a novel service provision mode named Multidimensional Customization of Telecom Services for Each User to analyze the value of the business model and the factors that influence it. From the view of technological innovation, it will design an implementation scheme corresponding to the business model, and verify its advantages in network-carrying capacity and significance to enterprises’ business value through a simulation experiment. The research shows that the novel mode is beneficial both to telecom users and telecom enterprises. In addition, it addresses this novel mode’s impact on environmental sustainability and the regulation of the telecom industry, as well as the limitations of this research and future research directions.

1. Introduction

Today, achieving sustainable development has become a major global goal [1], especially in the electronic communications industry. It is challenging traditional competitive priorities, and companies are increasingly having to integrate sustainability priorities into their development and business strategies [2]. As an important part of electronic communications, telecommunication removes the barrier of geographic distance, and is the key factor towards the information society [3]. Therefore, it is of great significance to study the sustainability of the telecom industry.

The deepening integration of telecom technologies into other industries [4,5] has given birth to a variety of new applications such as self-driving, telemedicine, intelligent manufacturing, virtual reality (VR), and intelligent agriculture. Telecom networks are involved in increasingly varied fields, with different characteristics and requirements. For example, Ultra-High Definition (UHD) video and VR have high requirements for bandwidth; self-driving and intelligent manufacturing have high requirements for time-delay; and intelligent agriculture and sensor networks have high requirements for connection density but low requirements for bandwidth and time-delay. Even for the same service, different users have different requirements. Therefore, network performance requirements need to be personalized and multidimensional. Unfortunately, at present, telecom enterprises are far from being able to provide customized services, which hinders the sustainable and harmonious development of the telecom industry.

In response to the above problem, this paper proposes a novel service provision mode to meet users’ customization requirements, which is named Multidimensional Customization of Telecom Services for Each User. Under this mode, each user can customize the service in multiple performance dimensions according to their real requirements, and the telecom enterprises will provide services according to each user’s customized details. On the one hand, this new mode will bring better service experience and satisfaction to users; on the other hand, it will help the telecom industry lengthen its value chain through growing integration with other industries. Due to the diversified requirements of different fields, a refined and on-demand customization mode is of great significance for expanding the types and quantity of telecom services and bringing better development opportunities to telecom enterprises.

From recent research, scholars found that enterprise innovation is an organic whole made up of many parts, among which business model innovation and technological innovation are the most important [6]. They have a close relationship of collaboration and adaptation [7,8]: business model innovation provides direction and value creation for technological innovation, while technological innovation provides a foundation and impetus for business model innovation. Therefore, telecom enterprises should pay attention to the adaptation, innovation coordination, and mutual promotion between business model and technological realization. From the perspective of collaboration and adaptation, this paper conducted in-depth theoretical research and a simulation experiment on the proposed novel mode, Multidimensional Customization of Telecom Services for Each User.

In addition, modern society requires companies to respect nature and take responsibility for their business activities [9]. The Sustainable Development Goals (SDGs) were designed to reconcile environmental protection with socioeconomic development [10]. For the SDGs, more and more attention should be paid to eco-innovation, which effectively ensures the simultaneous achievement of economic, environmental, and social objectives [11,12]. Based on this viewpoint, from the economic perspective, Section 3 discusses the business value as well as the influence factors of the novel service provision mode, and the simulation results in Section 4 correspond with the influence factors of the business value mentioned in Section 3, reflecting the advantages of this mode. Section 4 also discusses the applicability of the novel mode to the new characteristics of people’s work and lifestyle in the context of the COVID-19 pandemic [13]. From the perspective of the environment, Section 5 discusses the relationship between the novel service provision mode and environmental sustainability, and from the perspective of social objectives, Section 5 also discusses the new issues that should be considered in the telecom industry regulations under the novel mode.

2. Challenge and Strategy of Telecom Service Provision Mode

Business model innovation is considered to be a potential way for enterprises to enhance their sustainable development capability and performance [14], and is closely related to strategic goals of enterprises [15,16]. An enterprise’s business model refers to its operational and profit-making strategies, value creation processes, and technological and economic transformation [17,18]. There are some key components of business models, including customer relations, marketing, and service provision. [19]. As a service industry, the means and process of providing services to users is obviously fundamental and an important part of the business model for telecom enterprises.

2.1. Historical Changes and Challenge of Telecom Service Provision Mode

The lifeline of telecom enterprises, as a service industry, depends on whether they can provide users with satisfactory services. Influenced by many factors such as productivity, production costs, and benefits, the telecom service provision mode has evolved from Standardized Supply into Mass Customization. Next, from the perspective of development history of the telecom industry [20,21,22], the changes of the telecom service provision mode and the challenges it faces are analyzed as follows:

• In the early stage of the telecom industry, the production capacity of telecom enterprises was very limited. Due to the distinct characteristics of scale economy of the telecom industry [23], considering the factors of costs and benefits, telecom enterprises would only sell limited services to a small number of users who could afford the high prices. The service provision mode in this stage is Standardized Supply, which means that users can only passively accept what the telecom enterprises produce, without the choice of customized services;
• In the mid-stage of the telecom industry, with the development of technologies and productivity, the carrying capacity of telecom networks grew rapidly, driving the industry into the stage of mass production. In this stage, under the influence of Long-Tail Theory and universal service regulations of the telecom industry [24,25], a large number of ordinary users gained access to telecom services. The characteristic of the service provision mode in this stage was much the same as the early stage, but users’ requirements for personalized services continuously grew;
• At present, with the rapid improvement of telecom technologies and fast growth of productivity, the number of users, the types of service, and users’ personalized requirements grow rapidly accordingly, giving birth to a new service provision mode named Mass Customization. This is a mode combining users’ personalized requirements with mass production [26,27], giving consideration to both the production costs and the differences of users’ requirements. It partially meets users’ requirements for personalized customization. In this stage, users can choose their favorite from several service levels. For example, a broadband user can choose a relatively suitable bandwidth they prefer from several levels of choice.

The relationship among the telecom service provision mode, the degree of customization, and the development stage of the telecom industry are shown in Figure 1.

From Standardized Supply to Mass Customization, the change of service provision mode shows both the growth of users’ requirement for personalized customization and the efforts made by telecom enterprises to meet this requirement of users. At the moment, with the growth of the variety of telecom services and the personalized requirements of users for differentiated services, the Mass Customization mode is more and more unsuitable for the telecom industry’s further development and urgent innovation is needed. According to the historical development trends, the future telecom service provision mode ought to meet users’ requirements for service customization more thoroughly.

2.2. Strategy for the Challenge

With the emergence of a large number of various applications requiring telecom services, different services have personalized requirements in multiple dimensions for network performance. Bandwidth and time-delay are the most commonly used performance dimensions. According to the application requirements report of the Internet of things (IoT) released by Forrester [28], the differential requirements for bandwidth and time-delay of some emerging telecom services are shown in Figure 2.

Although the mode of Mass Customization has taken an important step to meet users’ personalized requirements, the options of customization are very limited. Under the trend toward the diversification of telecom services, the mode of Mass Customization is becoming increasingly unsuitable in the face of increasing requirements for multidimensional and personalized service customization from users. Aiming at solving the contradiction between users’ requirements for delicate and differentiated customization of services and the fact that current telecom enterprises cannot meet users’ every requirement, based on intelligence-related technologies, this paper proposes a novel service provision mode to meet users’ customization requirements to the maximum extent, named Multidimensional Customization of Telecom Services for Each User.

The quantitative definition of this mode is as follows. Supposing that a telecom enterprise can provide $m$ options for a telecom service, while all users have $n$ requirements for this service, then the degree of customization of this service is: $y=\frac{m}{n}$,$y\in \left[\frac{1}{n},1\right]$. Obviously, the higher the value of $y$, the more customizable the service is. When $y=\frac{1}{n}$, users have no choice to customize, and in this case, the service provision mode is Standardized Supply. When $y=1$, users’ customization requirements can be fully met, and in this case, if the customizable metrics are distributed in multiple dimensions, the service provision mode is called Multidimensional Customization of Telecom Services for Each User, which is proposed by this paper.

In the field of manufacturing industry, the One-of-a-Kind Production mode has been studied and partially applied [29,30], although in the field of the telecom industry, there are few studies about how to meet the customization requirements of each user. Based on the general view that it is easier for the service industry to realize customization than the manufacturing industry, and that the applications of intelligence-related technologies bring about many changes in almost all walks of life, this paper carried out studies on the novel service provision mode of Multidimensional Customization of Telecom Services for Each User. Whether this mode can be pushed forward smoothly is constrained by the business value it can bring, as well as the feasibility and advantage of technical realization. Next, theoretical research and simulation experiments on these two decisive factors is presented.

3. Business Value and Influencing Factors

Profit is the lifeline of an enterprise and the key driving force for innovation activities. Telecom enterprises are increasingly focused on profitability and rapid growth due to fast-growing technologies and high competition within the industry [31,32]. Therefore, whether the novel mode can be adopted is closely related to whether it can bring predictable profits to telecom enterprises.

According to Profit Theory [33], the relationship among profit ($\pi$), income ($S$) and cost ($C$) is: $\pi =S-C$. The customization degree of Mass Customization is in the middle stage of Standardized Supply and Multidimensional Customization of Telecom Services for Each User; therefore, in order to simplify the calculation, this paper studied the variation laws of profit after making the mode “innovation of service provision”, by comparing only with the traditional mode of Standardized Supply.

• The profit function under the mode of Standardized Supply: supposing that there is only one level for telecom service $M$, its unit cost is $c_1$, unit price is $p_1$, number of users is $n_1$, then the profit is: ${\pi }_1=(p_1-c_1)n_1$;
• The profit function under the novel mode: supposing that telecom users’ customization requirements for the service $M$ are divided into $n$ levels, the corresponding service aggregate is $\left\{M_1,M_2,\dots ,M_n\right\}$. Let $p_{2i}$, $c_{2i}$, $n_{2i}$ represent the unit price, the unit cost, and the number of users of the service degree $i$, respectively. Then, the average unit cost of all the service levels is: $c_2=\frac{{\displaystyle \sum _{i=1}^n{c}_{2i}\cdot n_{2i}}}{{\displaystyle \sum _{i=1}^n{n}_{2i}}}$; the average unit price is: $p_2=\frac{{\displaystyle \sum _{i=1}^n{p}_{2i}\cdot n_{2i}}}{{\displaystyle \sum _{i=1}^n{n}_{2i}}}$; the number of users of the service is: $n_2={\displaystyle \sum _{i=1}^n{n}_{2i}}$; therefore, the profit is: ${\pi }_2={\displaystyle \sum _{i=1}^n\left(p_{2i}-c_{2i}\right)}{n}_{2i}=(p_2-c_2)n_2$;
• Change in the profit: $\mathrm{\Delta }\pi ={\pi }_2-{\pi }_1=(p_2-c_2)n_2-(p_1-c_1)n_1$. Let $\mathrm{\Delta }c=c_2-c_1$, $\mathrm{\Delta }p=p_2-p_1$, then:

  $$\mathrm{\Delta }\pi =(p_1-c_1)\mathrm{\Delta }n+(\mathrm{\Delta }p-\mathrm{\Delta }c)n_2=(p_1-c_1)\mathrm{\Delta }n+(\mathrm{\Delta }p-\mathrm{\Delta }c)(n_1+\mathrm{\Delta }n)$$

  (1)
• Analysis of the influencing factors.$p_1$, $c_1$ and $n_1$ are the price, the cost, and the number of users of the traditional mode of Standardized Supply, respectively. They are set as constants and $p_1\ge c_1$. According to Equation (1), the value of $\mathrm{\Delta }\pi$ depends on the value of $\mathrm{\Delta }n$ as well as the difference between $\mathrm{\Delta }p$ and $\mathrm{\Delta }c$. After adopting the novel mode, the greater the value $\mathrm{\Delta }n$ and $\mathrm{\Delta }p$, and the smaller the value $\mathrm{\Delta }c$, then the greater the profit will be. Analysis for the decisive factors of $\mathrm{\Delta }p$, $\mathrm{\Delta }c$ and $\mathrm{\Delta }n$ is shown as follows:
  • Decisive factor of $\mathrm{\Delta }p$. As network products, in addition to the general characteristics of ordinary products, telecom services also have a strong network effect [34], which plays an important role in influencing service value and price. Referring to Hoernig’s modeling idea on network effect [35], the price function of a telecom service can be assumed as: $p=a-bq+\lambda m+\mu q^e$. In this function, $a$ represents the reservation price, $b$ represents the influence coefficient of the service quantity $q$, $\lambda$ represents the influence coefficient of the service quality $m$, $\mu$ represents the influence coefficient of the strength of network effect, and $q^e$ represents users’ expectation of the market scale of the service. Regardless of the common factor of quantity, the action principle of other factors in the function is as follows. The degree of customization is one of the indicators to measure the quality of a telecom service. The higher the degree of customization, the higher the users’ satisfaction with the service will be, and thus the greater the value of $\lambda m$. The stronger the network effect, the greater the $\mu q^e$. The increases in the values of $\lambda m$ and $\mu q^e$ brings greater values of $p$ and $\mathrm{\Delta }p$. Under the novel service provision mode, it is suitable to adopt a differential pricing strategy for telecom enterprises. For services with a high level of requirements, a higher pricing strategy can be adopted, while for services with common requirements, a lower pricing strategy should be adopted. In this way, telecom enterprises can achieve more profits through improving service quality and users’ satisfaction, without violating one of the key principles of telecom regulation, of “protecting the interests of users”;
  • Decisive factor of $\mathrm{\Delta }c$. Personalized customization will undoubtedly increase the costs of customization, which can be divided into fixed costs $C_0$ and variable costs $C_v$. According to the design of the technological implementation scheme in Section 4, the novel mode is based on intelligence-related technologies and is completed automatically, therefore the increased costs can be approximated as fixed costs. In addition, compared with the traditional mode, the automatic process of the novel mode greatly reduces the labor costs of customization and maintenance, which is represented by $C_l$ here. Then, the increased average costs per user is: $\mathrm{\Delta }c=\frac{C_0+C_v-C_l}{n}\approx \frac{C_0-C_l}{n}$. Obviously, the greater the value of $C_l$, the smaller the value of $\mathrm{\Delta }c$; $\mathrm{\Delta }c$ could even turn negative. Even if $C_0>C_l$, the value of $\mathrm{\Delta }c$ can be reduced by increasing the user number $n$. In the most extreme case, if $n\to +\infty$, then $\mathrm{\Delta }c\to 0$. The decrease in $\mathrm{\Delta }c$ is beneficial to reducing the average service price, bringing benefits to users, and improving social welfare at the same time;
  • Decisive factor of $\mathrm{\Delta }n$. From Equation (1) and the expression of $\mathrm{\Delta }c$, it can be concluded that the business value of the novel service provision mode is closely related to the number of users, demonstrating a significant characteristic of the telecom industry, which is called the economies of scale. If the novel mode can bring about an obvious increase in the number of users, it will bring considerable potential profits to telecom enterprises. There are two ways to increase the value of $\mathrm{\Delta }n$: one is to increase the number of users by better meeting their requirements, while the other way is to improve the carrying capacity of the network through expanding the utilization of network resources. The novel service can obviously better meet users’ requirements because it focuses on users’ personalized requirements. To expand the utilization of network resources relates to technological implementation schemes and the resources allocation method. For this purpose, the designed technological implementation scheme of the novel service provision mode and the variation laws of the resource utilization under the proposed scheme, verified by simulation experiment, are presented in Section 4.

4. Technological Solution and Simulation Experiment

4.1. Technological Implementation Scheme

Nowadays, except for Mass Customization, other personally customized telecom services are mostly beyond manual work. The customization mode entailing manual work is only suitable for services of a small scale. Once the customization scale becomes too large, the labor costs, material costs, and time costs will be astronomical, and the goal will be hard to reach. The mode of Multidimensional Customization of Telecom Services for Each User aims to provide on-demand customized service for each user, resulting in a large scale of customization. Therefore, intelligent means are required to reduce customization costs and improve efficiency. The development of intelligence-related technologies, such as big data, cloud computing, artificial intelligence, etc., is driving human beings into an era of intelligence, and meanwhile adjusting the mode of Multidimensional Customization of Telecom Services for Each User from unimaginable to feasible.

Haddadin proposed that a tactile robot network, as a multidimensional agent of the human virtual world, can collect and recognize human’s intentions in various tactile ways [36]. Artificial intelligence technology can adjust to new inputs and implement human-like tasks [37,38], and incorporate impromptu thinking as well as empathetic customer service [39,40]. The technological implementation scheme of the novel service provision mode requires a system which can automatically identify various types of network access requests, intelligently collect and analyze users’ requirement information and network resource data, finely respond to users’ customization requests, gather and allocate network resources in real time, and realize intelligent service processing in the form of artificial intelligent agent [41].

Meanwhile, the variety of the telecom services is continuously increasing. Different services or different users of the same service have different requirements for network performance on bandwidth, time-delay, connection density, etc. In order to carry all kinds of services with different requirements, building corresponding physical networks is not practical because of the huge costs. This study applied the latest technology, network slicing technology [42,43] in the telecommunication field, to solve this problem. Network slicing technology divides the same physical network into different virtual logical networks to meet the differentiated requirements of various types of services.

For the two key issues above, this study designed technical architecture to realize the mode of Multidimensional Customization of Telecom Services for Each User. According to the modular design concept, the architecture comprised four core functional modules: intelligent cloud management and a control platform, an access network, a transmission network, and a big data repository. The big data repository consisted of user big data and resource big data. Network slicing technology is applied in end-to-end service transmission, as shown in Figure 3.

The key functions of the four core modules in Figure 3 are as follows:

• The intelligent cloud management and control module ensures the automatic process of service customization;
• The access network module has strong capability for integrated service access, for either wireline services or wireless services;
• The big data repository module collects all the historical and real-time data of users as well as network resources to provide data basis for intelligent service processing;
• The transmission network module carries service connections and transfers user data.

The following example describes the customization process of some kinds of service under the architecture shown in Figure 3. Supposing telecom user A wants to customize a VR game service, the customization process is as follows:

• User A sends the service customization request to the intelligent cloud management and control platform through the access network;
• Referring to user big data and network resource big data, the intelligent cloud management and control platform interacts with user A to confirm the details and price of the customization until an agreement is reached;
• After the agreement, user A pays for the service, and the platform generates strategies of service connection according to the user’s customized content;
• Under the control of the intelligent cloud management and control platform, with the participation of network slicing technology, the system allocates network resources and sets up traffic connections;
• User A starts to use the VR game service customized under the intelligent process.

The above process is shown in Figure 4.

Particularly, in the context of a pandemic such as the current COVID-19 crisis, people increasingly want to conduct their work and entertainment on online platforms as much as possible, rather than dealing with them in offices, supermarkets, cinemas, or other places [13]. The intelligent accomplishing process of the novel service provision mode is very suitable for meeting social needs in the special context of a pandemic.

4.2. Simulation Experiment and the Analysis

Based on the technological framework shown in Figure 3, the process of personalized service customization will span all four core functional modules. Among them, the transmission network module-carrying service connections play a key role in whether the service performance indicators customized by users can be achieved. According to the discussion of Equation (1) in Section 3, improving the utilization rate of network resources is helpful to expand the capacity of the network for services as well as the number of users, and bring more business value to telecom enterprises at the same time. This section will present the law on how different service customization modes influence the utilization of network resources through transmission simulation experiments. The utilization rate of network resources is inversely proportional to the blocking rate; therefore, we chose the blocking rate to measure the utilization rate of network resources in this simulation experiment.

NSFNET and USNET are commonly used topologies for transmission network simulations. For this simulation, NSFNET was selected as the transmission network topology, JDK1.8.1 and Eclipse as the software development environment. Bandwidth and time-delay are the two most commonly used factors to indicate the service performance, therefore they were chosen as the customization dimensions in the simulation experiment. The bandwidth level was expressed by the number of wavelengths occupied by the service. The more wavelengths occupied by the service, the greater the service’s bandwidth. The time-delay level is expressed by the shortest path hops in end-to-end service connection. The fewer the number of hops, the shorter the time-delay. The first hit algorithm was adopted for bandwidth allocation [44,45], and the KSP algorithm was adopted for time-delay grading [46,47]. The simulation process was consistent with the service customization process shown in Figure 4. The service requests with different customization requirements were generated randomly under Poisson Flow between all possible pairs of nodes. If a certain service requirement can be satisfied by the current network, the service will be deployed; otherwise, the service request will be blocked.

Four types of service customization were set up for the simulation experiment and comparison. In the first case, there was no service customization. Therefore, if all levels of the simulated service need to be served, network performance values should only be set to the highest level of all the requirements. In the second case, service customization was only allowed in bandwidth dimension. Moreover, in bandwidth dimensions, the service could be customized into several levels, but in time-delay dimensions, the network performance value was set to the highest level of all the requirements. In the third case, service customization was only allowed in the time-delay dimension, while the bandwidth value was set to the highest level of all the requirements. In the fourth case, service customization was allowed in both bandwidth and time-delay dimensions.

The distributions of the simulated services were divided into two types: one was Uniform Distribution, which means that different levels of the customized services occurred at the same probability; the other was Pyramidal Distribution, which means that the higher the customized level, the lower the occurrence probability of the services, and the lower the customized level, the higher the occurrence probability of the services. The customized levels of the service fall into two cases: 3 and 5. The simulation parameters are shown in

Table 1. Simulation parameters.

Parameter Name	Parameter Value	Parameter Name	Parameter Value
Customization Dimensions	Bandwidth, Time-delay	Service Distribution	Uniform Distribution, Pyramidal Distribution
Customization Types	4	Service Flow	Poisson Flow
Customization Levels	3, 5	Service arrival rate	Negative Exponential Distribution: variable λ
Number of the Service	500,000	Service Duration	Negative Exponential Distribution: µ = 1
Number of Nodes	14	Number of Links	22
Number of Link Wavelengths	80 per Round Trip

.

When the number of customized levels is 3, in the case of Uniform Distribution, the simulation result is shown in Figure 5, and under Pyramidal Distribution, the simulation result is shown in Figure 6. The x-axis represents traffic load, and the y-axis represents blocking rate.

When the number of customized levels is 5, in the case of Uniform Distribution, the simulation result is shown in Figure 7, and under Pyramidal Distribution, the simulation result is shown in Figure 8. The x-axis represents traffic load, and the y-axis represents blocking rate.

According to the simulation results, analysis of the influencing factors and the law on how different service customization modes influence the utilization of network resources and user capacity is as follows:

• Factor of service customization dimension. There are four simulation curves in each graph from Figure 5, Figure 6, Figure 7 and Figure 8. The highest blocking rate occurs in the case of no customization; the lowest blocking rate occurs in the case of customization in both bandwidth and time-delay dimensions; the middle blocking rate occurs in the case of customization only in one dimension. The conclusion is that the more customization dimensions there are, the lower the blocking rate. In other words, the more customization dimensions there are, the greater the utilization of network resources, and more users can be held in the same network;
• Factor of service distribution. Comparing Figure 5 with Figure 6 (or Figure 7 with Figure 8), it can be seen that without customization, the blocking rate under Uniform Distribution is equal to that under Pyramidal Distribution. However, with customization, the blocking rate under Pyramidal Distribution is lower than that in the case of Uniform Distribution. The conclusion is that if the actual service distribution pattern is closer to Pyramidal Distribution, the blocking rate can be reduced to a greater extent in the case of customization. In other words, if the actual service distribution pattern is closer to Pyramidal Distribution, the utilization of network resources can be improved to a greater extent and more users can be held in the case of customization;
• Factor of the number of customization levels. There are three customization levels in Figure 5 and Figure 6, and five levels in Figure 7 and Figure 8. Through comparing, it can be seen that as the number of customization levels increases, the blocking rate increases correspondingly; however, as the number of customization dimensions increases from no customization to customization in a single dimension and then to multiple dimensions, the impact of the increase in customization levels on blocking rate decreases gradually. In other words, with the increasing customization levels, the utilization of network resources decreases. The increase in customization dimensions can reduce the above effects to a certain extent.

Through the above analysis regarding simulation results, it can be seen that the mode of Multidimensional Customization of Telecom Services for Each User realizes on-demand allocation of network resources, which can significantly reduce the network blocking rate. The more customization dimensions there are, the more obvious the effect will be. According to Equation (1) in this paper, the novel customization mode can not only better satisfy users with on-demand service, but also help to improve the utilization of network resources to carry more services and hold more users. In conclusion, from the dual perspective of telecom users and enterprises, the novel service provision mode is beneficial to the sustainable development of the telecom industry.

5. Discussion and Limitations

Our results convey theoretical and practical implications for the development of the telecom industry. The development of emerging technologies such as big data, cloud computing, and artificial intelligence is driving human society into an era of intelligence. The integration of intelligence-related technologies and various industries not only means a leap in technology, but also brings about a revolutionary change in business model. Intelligence-related technologies can play an extremely important role in achieving the automatic processes, which are beneficial to realize personalization to a large extent, whether for the telecom industry or other industries. Therefore, the telecom industry must integrate with the emerging intelligence-related technologies to meet the requirements of the times and achieve sustainable development. The novel mode of Multidimensional Customization of Telecom Services for Each User proposed by this paper is realized based on intelligence-related technologies. The research results show that the novel mode not only better satisfies users, but also helps to improve the utilization rate of network resources, bring opportunities to carry out richer services and achieve more business profit for telecom enterprises; thus, it is beneficial to realize win–win results between users and telecom enterprises.

From the perspective of the telecom industry itself, the research results show that the novel service provision mode is beneficial to the sustainable development of the telecom industry. Meanwhile, in the context of global environmental challenges, except for concentrating on their own business operation and development, companies must take the natural environment into consideration as an important part of their efficient operation [10,13,48,49]. Companies have faced increasing pressure over the past decade to report more information about their environmental impacts [50]. In some sectors, such as the transportation industry or entertainment industry, the improvement of the degree of personalized customization will bring more carbon emissions, which is unfavorable to environmental sustainability. Taking the transportation industry as an example, compared with special car and plane services for individuals, non-personalized transportation for the public, such as buses or subways, can effectively reduce carbon emissions and promote environmental sustainability. However, the personalized customization of telecom services is far from this kind of situation. Compared with the traditional service provision mode, the novel mode proposed in this paper will only increase the data flow of service customization and service control in the network and the energy consumption of the related equipment. Moreover, with the help of intelligent service processes, related activities in the telecom service customization process will be greatly reduced. Overall, if the novel mode can be implemented on a large scale, it will be beneficial for reducing carbon emissions and will have a positive impact on environmental sustainability.

Due to its natural monopoly property, the telecom industry is generally regulated worldwide [51,52,53]. The regulations propose rules that telecom enterprises ought to obey, concentrating on universal service [24,25], price control [54,55], and so on. The novel telecom service provision mode reduces labor costs by means of intelligent process, which is helpful to realize the regulation goal of universal service. On the other hand, the service process of this mode is accomplished on networks. In order to protect the interests of users, privacy protection should be strengthened [56,57], and the transaction data should be monitored to reasonably ensure pricing.

Although our research contributes something valuable, we would also like to acknowledge the limitations in our study and suggest possible directions for future research. The theoretical research and simulation experiment carried out in this study have a certain guiding significance for further development of the telecom industry, although the practical applications will be more complex, and more specific implementation schemes need to be studied. In addition, the simulation experiment of this research was carried out in the transmission network module. As we know, the end-to-end connection of a telecom service includes not only the transmission network module, but also the access network module. Constrained by the research scope of the authors, this study did not carry out a simulation experiment on the access network module.

6. Conclusions

The rapid development of science and technology is giving birth to more and more new telecom services. Meanwhile, services belonging to different fields and different users put forward multidimensional and personalized customization requirements for network performance. The traditional service provision mode with a low degree of personalization can no longer suit the new characteristics and trends of telecom services.

Starting from an analysis of the outstanding problems existing in current telecom service provision mode, this paper proposed a novel mode called Multidimensional Customization of Telecom Services for Each User, to solve the predicament of service customization faced by the telecom industry. In order to test the feasibility of the solution, from the perspective of collaboration and adaptation between business model innovation and technological implementation innovation, on the one hand, this paper analyzed the business value and the influencing factors of the novel mode; on the other hand, considering the above influencing factors, on the basis of designing the technical implementation scheme of the novel mode, this paper verified the effects and advantages of the novel mode in service transmission by a simulation experiment. The research showed that the novel mode can both realize on-demand customization from users’ point of view and the on-demand resource allocation of network resources. It can not only improve users’ satisfaction, but also expand the types of services that can be carried out and the quantity of services that can be carried in the network, therefore it is helpful to realize win–win results between users and telecom enterprises, and also helpful for the telecom industry to break the bottleneck and realize further sustainable and stable development. At the same time, with the help of intelligent process, the novel service provision mode reduces the related activities in service customization, which can make a positive contribution to green development and the environmental sustainability.