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How Can We Develop High Quality Smart Cities in the Digital Era?

Prepared by Zhao Zhijuan, Smart City Solution Department, Enterprise Business Group, Huawei Technologies Co., Ltd.

Yang Xueshan, Former Vice Minister of Industry and Information Part-Time Professor at Peking University

Former Vice Minister of the Ministry of Industry and Information Technology, Yang retired in February 2015. Yang’s research fields include Chinese character information processing, information system and network design and development, information economics, information law science and national informatization development strategy. Since 1981, Yang has published more than 150 academic theses.

Shan Zhiguang, Director of the Information and Industry Development Department of the State Information Center, Director of the Smart City Development Research Center

Shan is a national candidate for the New Century Talent Project, a member of the Beijing Informatization Advisory Committee, and Secretary General of the Smart City Development Research Center of China. Shan’s research areas include ICT strategic planning and development policies, as well as overall Smart City planning and top-level design.

Zhang Guohua, Director of the Urban Center Integrated Transportation Planning Institute of the National Development and Reform Commission

Zhang has a doctor’s degree and is a professor and senior planner. His research focuses on new urbanization fields, such as the new collaborative planning technology system of industry, space, and transportation, new space economic theory and new system economic theory based on transportation, development planning of the multi-level rail transportation system, and Smart City planning.

The digital economy is growing rapidly. According to Huawei’s 2018 Global Connectivity Index (GCI) study, the growth rate of the global digital economy in the past 15 years is 2.5 times that of the global Gross Domestic Product (GDP). As the Industrial Internet develops, and various industries are integrated with digital and smart processes, it is estimated that the global digital economy will account for 24.3 percent of the world’s GDP by the end of 2025.

In the future, the digital economy will be the main driving force for economic development. Therefore, measuring the output and benefits of the digital economy is crucial. In the next 10 years, all industries and countries will be concerned with seizing the opportunities provided by the digital economy to maximize their growth.

City development is the epitome of social progress in a country. A Smart City’s construction can serve as an important carrier for developing the digital economy in a country, while also integrating the digital economy with physical industries, allowing us to better measure the output and benefits of the digital economy.

Why is the digital economy considered a reconstruction of productivity? How can we measure its role in economic development?

Yang Xueshan: With changes to traditional production models, the digital economy has become more prominent. Digital technology, as a new factor of production, shares similarities (while also having differences) with traditional production factors, such as capital and management. It is important to remember that digital technology must be combined with specific economic activities before it can create value. However, this is also true of other production factors. The difference is that the adoption of digital technologies brings a whole new field — that is, the information field — providing a new foundation for the optimization of economic activities and processes.

The measurement of the digital economy, whether by international or Chinese organizations, is generally performed from the macroeconomic perspective. According to the Organization for Economic Co-operation and Development (OECD) and the United Nations Commission on International Trade Law (UNCITRAL), the digital economy accounts for about 6 percent of China’s total GDP. However, according to the China Academy of Information and Communications Technology (CAICT), China’s digital economy accounted for 32.9 percent of its total GDP in 2017. Why is there such a big gap between the two figures?

Actually, the digital economy consists of two parts: the core part of Information and Communications Technology (ICT), and the extended part, also called the convergence part. In terms of the core part, every country has its own strict measurement indicators, but there are currently no indicators for gauging the convergence part. The statistics previously mentioned, from the OECD and UNCTAD, contain only the core part, while the CAICT contains both parts in their review — therein lies the problem.

This explains why the CAICT has proposed two concepts, namely digital industrialization and industry digitization. Digital industrialization refers to the market-oriented application of Information Technologies (IT), including Internet-based software, hardware, and information services, accounting for less than 5 percent of China’s GDP; while industry digitization is the all-around, all-perspective, full-chain transformation of traditional industries using advanced information technologies. The latter accounts for more than 25 percent of China’s GDP, and more than 50 percent of the GDP in the US. A city’s development will be centered entirely on industry digitization.

Shan Zhiguang: When restructuring productivity in a digital economy, productivity development is essential to drive social and economic transformation. In an agricultural or industrial society, it is labor and capital that are the main production factors, respectively. But in the digital age, it is data that is the major production factor. With that being said, I don’t think data’s significance has impacted productivity yet. Neither has digital technology become a true force in modern economies, at least not as dominant as capital and labor in the industrial and agricultural ages, but the trend is still very clear. Indeed, data is becoming an invaluable resource, however, how these resources become assets and how these assets become capital is still unclear. Currently, we are trying to find a good model to address these challenges.

“Industry digitization is the all-around, all-perspective, and full-chain transformation of traditional industries using information technologies. For all economic sectors, the shift from quantitative growth to qualitative upgrade happens as a result of industry digitization. Industry digitization will be key to future development.”

— Yang Xueshan, Former Vice Minister of Industry and Information, Part-Time Professor at Peking University

Smart City construction is crucial to developing a digital economy. As such, what are the challenges faced when constructing a Smart City?

Yang Xueshan: In China, currently, the biggest challenge facing Smart City construction is not the country’s social and economic development — which is being transformed at a rapid pace — rather it is the challenge of transforming people’s mindsets to keep up with the country’s Smart City development.

Let’s look at two reports as examples. Firstly, the China Artificial Intelligence (AI) Industry Index 2018, released by the Cheung Kong Graduate School of Business, found that there were more than 400 active enterprises in the AI sector in China during 2016. By 2018, most of these enterprises had disappeared. According to another report, out of more than 800 surveyed enterprises that emerged before 2016 in China, most of these enterprises — related to AI, big data, Industrial Internet, Internet of Things (IoT), and blockchain — have now vanished. We need to ask the question, why are these enterprises disappearing so suddenly? There must be something wrong with our mindset. We need to explore the reasons from the perspective of network, data and intelligence.

In regards to the Internet, Metcalfe’s Law states that the more nodes the network has, the more value it creates. However, this rule does not apply in the IoT field, as IoT nodes are mostly passive. Any additional nodes or information are a waste. As such, the Internet and IoT can be considered quite different. Although many people have tried to neglect the differences between the two, and apply Internet models to the development of IoT, they have all suffered the same fate — failure.

Many people, instead, regard data as king. During Smart City construction, city data is aggregated. But what happens after data aggregation? Unfortunately, Smart City planners have placed too much emphasis on managing the enormous amount of data we gather, but not actually on how we can use the data to benefit a city’s residents. The concept of big data leads many people into thinking that large amounts of data inherently bring productivity and value. However, this is wrong because data, as a production factor, must be used in specific economic activities to create value.

And finally, in terms of intelligence, almost everyone equates algorithms and data to AI, but this is wrong. There have been countless AI enterprises in China that have disappeared in the past three years, and all were led by world-class algorithm scientists. These enterprises had all conducted deep neural networking as well as machine learning research, based on multiple algorithms and open datasets. Yet, these enterprises have all disappeared. Why did they fail? Because data research alone cannot solve real world problems. AI needs to be used to solve real world problems, including improving the management processes of those in the government, manufacturing, and medical sectors. And when constructing Smart Cities, we need to answer the same question: What role can smart applications play in the development of cities in the next three, five, or even ten years?

Shan Zhiguang: Enabled by alternative technologies, Smart Cities represent a new model for urban areas. The development of Smart Cities must keep pace with the development of society. The fundamental problem is deciding whether Smart City solutions are synchronized with a city’s economic or social development. Today, Smart City assessment is being performed at a superficial level, and this is a problem. The solutions should not be too futuristic, nor should they lag behind the times. However, we often forget that Smart City solutions are scenario-based, and cannot be applied to all peoples and all economies around the world. A Smart City’s management is of the utmost importance.

When constructing a Smart City, the ultimate goal is to improve city management and governance. To achieve these goals, it is simple — a city’s management must improve. Therefore, Smart City construction is not only about the informatization of cities, but also the smartification of city development models. Currently, Smart Cities are assessed in terms of the technology used: devices, networks and cloud. However, this appraisal does not include the fundamental changes that are necessary to the successful construction of a Smart City. As such, these rigid technical evaluation indicators are obstructing Smart City development.

Furthermore, cities are the epitome of social progress. A Smart City should be a means of social progress, and should be oriented toward social progress. In the past, Smart City construction has focused on urbanized areas rather than rural counties and townships, widening the economic gap between urban and rural areas. In the future, more attention should be placed on ensuring an entire city is developed equally, and neither urban, nor rural areas, are left behind.

Although Smart City construction currently faces multiple challenges, I am optimistic about its future. There have been positive achievements recently that are very encouraging, and there are signs of intelligent social development in China. Many cities in China are showing signs of intelligence in their development and governance. A number of authentic Smart Cities can be expected in the next three to five years.

“Building an effective evaluation system is critical to guiding and promoting a Smart City’s development. However, a Smart City’s assessment is still at the superficial and technical level, and fails to address the fundamental issue of improving city management and governance.”

“Building an effective evaluation system is critical to guiding and promoting a Smart City’s development. However, a Smart City’s assessment is still at the superficial and technical level, and fails to address the fundamental issue of improving city management and governance.”

Do you have any suggestions to improve Smart City development models in the future, or for participants in Smart City construction?

Zhang Guohua: There are two relationships that matter when building Smart Cities: the relationship between the past and future; and the relationship between the government and market. In regards to the past and future, let’s think about the traffic control centers in Chinese cities — they are some of the most advanced in the world. However, we are yet to see considerable improvement in these cities. Why? Because in the past, the government focused on a Smart City’s economic benefits — revenue from taxes and fines — rather than the benefits a Smart City can provide to its citizens. In the future, Smart City construction should return to its goal of improving people’s lives.

The other relationship is between the government and the market. What is considered an appropriate division of labor between the government and market? What should be done by the government and what should be left to the market to decide? We need to learn from the leading Smart Cities around the world, and avoid making similar mistakes. In my opinion, the most successful Smart City projects have adopted the UK’s development model. Its model proves that the role of the government is weakening, and that many Smart City problems can be addressed by the market. The UK’s model needs to be studied, understood, and then adapted after considering China’s own challenges.

Shan Zhiguang: In current Smart City models, a city’s operations are its biggest weakness. In the future, Smart Cities will be application-oriented, and the industry ecosystem will be focused on Software as a Service (SaaS). A city’s operations will be key to building a successful Smart City. I believe a city- or social-level operations service industry will emerge in the future, and may replace Baidu, Alibaba, and Tencent, becoming a leader in the next-generation new economy. As such, the relationship between the government and an enterprise will have to evolve. What role should enterprises play in a Smart City’s development? I think enterprises should adopt a long-sighted mindset and establish long-term, sustainable cooperation with the government. Enterprises need to be future-oriented in order to keep pace with the times.

“How can we learn from the world’s most advanced Smart City development model and carve out a high-quality development path based on China’s actual conditions? The answer lies in properly handling the relationship between the past and the future, and that between the government and the market.”

— Zhang Guohua, Director of the Urban Center Comprehensive Transportation Planning Institute of the National Development and Reform Commission

(This article was prepared based on the discussion on the topic of Digital Economy Drives the Development of Smart Cities at the 2019 Smart City Salon in Beijing.)

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