1. Introduction
After building a moderately prosperous society in all respects and eliminating absolute poverty, China has embarked on the path of relative poverty alleviation. The alleviation of relative poverty is conducive to raising the level of human capital and ensuring the rational use of resources, and it is an important issue for sustainable economic dynamics. At present, a large amount of literature focuses on the issue of relative poverty in rural areas, and there are studies that have found the important role played by the increasing digitalization of the population in rural poverty reduction. However, with the spread of interconnected sharing of production and convenience of consumption in the digital economy [
1], the governance of poverty in China in the new era is no longer limited to rural areas, and the governance of relative poverty needs to focus on both urban and rural areas [
2].
The pressure to survive and the struggles of the less fortunate can lead to social unrest and conflict, which can undermine social harmony and have a negative impact on regional economic growth. Scholars have long been concerned with the issue of relative poverty in urban and rural areas. Research has shown that entrepreneurship policies play a crucial role in reducing poverty among low-income urban populations [
3]. Additionally, the inadequacy of low-income insurance policies exacerbates urban poverty [
4], and the urban and rural dichotomy further contributes to this issue [
5]. Precision poverty alleviation have been identified as an effective means of reducing poverty and narrowing the income gap between urban and rural households [
6]. Overall, fewer studies have focused on the impact of the digital divide created by the development of digital technology on the relative poverty of urban households.
In recent years, scholars have conducted several studies on the issue of the urban digital divide. Scholars shifted the focus of the digital divide from rural and urban to intra-city and found that the problem of the digital divide within the city cannot be ignored due to geographic and economic limitations [
7]. Secondly, regarding the impacts of the digital divide, a study on unemployed workers in Singapore found that the use of information technology is a crucial factor affecting the employment of urban residents [
8]. Similarly, a survey conducted on low-income individuals in urban communities in the United States revealed that disconnection among the urban poor is significant and can directly impact information access and employment [
9]. Current research on relative poverty in China’s towns and cities, such as the study of relative poverty among indigenous and migrant households, has not yet addressed the impact of digital technology adoption on poverty rates. The study found that most of the households that fell into poverty after 2018 were indigenous households in towns and cities [
10]. It is important to consider the role of digital technology adoption in future research on poverty in China.
Digital technologies, such as Big Data, cloud computing, blockchain, artificial intelligence and 5G, are causing a digital transformation in various industries. This transformation is characterized by changes in production processes. In recent years, digital technologies have rapidly developed and can be integrated into numerous industries [
11], becoming a key factor when influencing sustainable economic dynamics. They are also considered key core technologies, and subsequent empirical evidence uses the proportion of word frequency of digital technologies in government reports and patents for digital technology inventions to represent digital technology development. Digital technology development has created a new form of poverty-causing factor known as the digital skills divide. Acquiring digital skills can act as a catalyst for individuals to escape poverty [
12]. Regarding the division of individual skills, individuals who work with computers generally possess higher digital skills compared to those who only use mobile phones to access the Internet [
13]. This is because computers offer the necessary space to read, write and create complex content, whereas the mobile phone’s Internet interface has limited access to important content [
14]. This paper’s micro-study of the digital skills divide focuses on the acquisition of basic ICT skills, specifically access to computers and mobile phones.
This paper’s potential contributions are two-fold. Firstly, it includes both government and enterprise levels in its portrayal of digital technology development. This is achieved by using the frequency of key digital technology words in the government’s work report to represent the intensity of digital technology development, and the number of digital technology invention patents of enterprises to represent the breadth of digital technology development. Secondly, this paper conducts a robustness test mainly using the latter measure. The second contribution serves to verify the positive relationship between the development of digital technology and urban relative poverty from the micro household perspective. This complements the inadequacy of existing studies that focus solely on the relative poverty of rural households. The third contribution is the construction of a systematic framework for analyzing the digital divide. This framework specifically measures the horizontal digital divide between industries and the vertical digital divide formed between the government and households. The aim is to explain how digital technology development externally affects the relative poverty of urban households. The fourth contribution is to explore the internal mechanisms by which the development of digital technology affects the relative poverty of urban households, from the perspective of income inequality among households.
This study is structured as follows:
Section 2 reviews the existing research literature to identify the impacts and mechanisms of digital technology development on the relative poverty of urban households.
Section 3 presents the model construction and indicator selection.
Section 4 presents the results of the empirical analyses, including a discussion of robustness and heterogeneity.
Section 5 analyzes the impact mechanism, which is divided into two dimensions: the divide in digital technology application and inter-household income inequality.
Section 6 presents the study’s conclusions and implications.
5. Analysis of the Influence Mechanism
A digital development orientation led by the government will inevitably result in the application of advanced production technologies, leading to the digital transformation of market players, including businesses and households. The attributes of enterprises in different industries vary greatly, which may result in varying degrees of digital transformation and an inter-industry gap in the application of digital technology. The level of digital technology application among household members is determined by their specificity. Low digital technology application levels may result in digital poverty, making such households the primary target of government governance. The government is responsible for building digital platforms and implementing digital governance. However, households may struggle to adapt to the government’s digital governance in a timely manner, resulting in a vertical digital technology divide between the management level and the target level. Furthermore, the digital development orientation can affect inter-regional income inequality. This paper explores the impact of digital technology on the relative poverty of urban households, focusing on the digital technology adoption divide and regional income inequality.
5.1. Digital Technology Application Divide
Digital technology orientation creates a favorable environment for the application of digital technology in both production and daily life. The industrial and service sectors have made significant progress in digital transformation, with the former showing a higher ratio of digital technology application compared to the latter. This highlights the existing gap in digital technology application between industries. On the one hand, the construction of digital platforms and the increased application of digital technology at the government level have led to an improvement in digital governance. On the other hand, whether families can adapt to the digital transformation trend of the government and improve their digital skills in daily life depends more on the inherent characteristics of the family members. Therefore, the ratio of the government’s digital governance level to the family’s digital skill application level can be used to express the management level and the target level of the vertical digital divide. This section examines how digital development orientation affects the divide in vertical and horizontal digital skills adoption, and how this divide leads to relative household poverty (
Table 12).
Table 12 displays the results. Column (1) indicates that digital technology development widens the horizontal digital technology adoption divide between industries, mainly because industry is much more digitally transformed than services. Column (2) demonstrates that a 1% increase in the horizontal adoption divide of digital technology leads to a 0.0348% increase in the probability of relative poverty occurring in towns and cities. This result is significant at the 10% level. The adoption of urban digital technology for poverty reduction fails, and the inter-industry digital technology divide creates gaps in industry development. This can impact the income disparity of the urban labor force working in different industries and exacerbate the likelihood of urban households falling into relative poverty. In contrast, column (3) demonstrates a positive correlation between digital technology development and the vertical inter-sector and inter-household divide in digital technology adoption. Specifically, for every percentage point increase in digital technology progress, the vertical digital technology adoption divide may widen by 0.0732 per cent. Column (4) demonstrates that a rise in the vertical digital divide results in a significant increase in the likelihood of urban households experiencing relative poverty. Specifically, a 1% increase in the vertical digital divide leads to a 107.1% increase in the probability of urban households being relatively poor. Specifically, a 1% increase in the vertical digital divide leads to a 107.1% increase in the probability of urban households being relatively poor. It is evident that digital technology development may increase the likelihood of urban households experiencing relative poverty due to both horizontal and vertical divides in digital technology application. Of particular concern is the impact of the vertical divide in digital technology application on urban households’ relative poverty. If households fail to adjust to the digital lifestyle promptly, they may fall into the relative poverty trap.
5.2. Inequality in Income Distribution
Digital technology is a significant factor in driving total factor productivity. The digital divide resulting from differences in digital technology development not only widens the gap in digital application between industries but also creates a divide in digital application at various levels, resulting in productivity differences and a loss of efficiency in government management. The income inequality of industries widens due to differences in total factor productivity, while the inability of some families in need to come out of poverty reflects the loss of government management effectiveness. To analyze the negative impact of the digital technology application gap, we use the Gini coefficient to test the impact of digital technology development on the relative poverty of urban households from the perspective of income inequality. This includes the inter-household Gini coefficients of household disposable income, wage income and business income. Only the impact of digital technology development on income inequality is examined, as shown in
Table 13. Income inequality is a direct cause of households falling into relative poverty.
The table above displays the impact of digital technology development on the Gini coefficient of total income, wage income and business income in columns (1), (2) and (3), respectively. The results indicate a positive and statistically significant correlation between digital technology development and all three coefficients. A one-percentage-point increase in digital technology development as the greatest impact on wage income inequality, leading to a 9.33 percentage point increase. Business income inequality is about 8.87 percentage points greater as a result of digital technology progress. The impact on overall income inequality is slightly smaller, at 5.27 percentage points. The digital technology development has led to an increase in income distribution inequality, which poses a potential risk for the occurrence of relative poverty among urban households.
6. Conclusions and Suggestions
6.1. Conclusions and Contribution
The goal of achieving common prosperity has been proposed, and the development of the digital economy has been identified as an important means of promoting a sustainable economic dynamic. While previous studies have primarily examined the impact of digital economic development on reducing rural poverty, this paper moves the perspective to the urban side and focuses on the impact of digital technology development on the relative poverty of urban households, which not only expands the scope of the research on relative poverty, but also reveals the external mechanism of the impact of digital technology development on the relative poverty of urban households in terms of the digital technology application gap dimension, enriching the research content of relative poverty in the new era. Furthermore, this study examines the relationship between poverty and income inequality and explores the issue of income inequality resulting from the gap in digital technology application. This forms a progressive logical system that delves into the distributional effects of digital technology at the microfamily level.
This study’s results indicate that the intensification of digital technology development increases the likelihood of relative poverty in urban areas. Specifically, digital technology-induced poverty is prevalent among households in economically developed and highly urbanized areas with low levels of education among the heads of household and high household dependency ratios. The analysis of impact mechanisms reveals that the development of digital technology affects the relative poverty of urban households due to the horizontal and vertical divide in digital technology adoption, as well as to the unequal distribution of income among households.
6.2. Policy Implications
All of the research results offer insights for promoting a sustainable economic dynamic in China. First of all, urban households have more complex characteristics and require greater attention regarding relative poverty. In economically developed provinces, low-income households should be cautious of digital poverty resulting from economic poverty and the risk of falling into a cycle of relative poverty. Secondly, the proliferation of key digital technology applications should be balanced to prevent the emergence of horizontal and vertical digital divides. In regions with low initial levels of digital technology application, industries should undergo digital transformation in a layered manner. This will accelerate the promotion of digital technology applications and help to alleviate the digital development gap between regions. Simultaneously, the central government should enhance the vertical digital assistance mechanism to aid localities and families in a timely manner. This can be achieved by improving the vertical penetration performance of digital technology through the provision of training courses and organizing technology exchange conferences. Additionally, stimulating and maintaining a digital-friendly atmosphere in families through economic and cultural means can promote the establishment of an intrinsic feeder mechanism in families. This will help to narrow the negative impact of the vertical digital divide on the income increase in urban families. Thirdly, it is important to consider the external environment when developing a digital economy. It is necessary to guide the development of small and medium-sized digital enterprises in a reasonable and orderly manner, while also optimizing the entrepreneurship and employment market environment. The government’s focus on digital technology is likely to lead to increased competition within the industry. Therefore, it is important to guard against the potential monopoly effect of platforms, which could trigger competitive chaos and damage the ecological environment of digital economic development. We will provide support and assistance to new small and medium-sized digital enterprises to enable them to fully utilize their job creation function. Additionally, we will assist individual entrepreneurs in upgrading their digital skills in a timely manner and carrying out their business dealings with digital platforms smoothly. This will lay a solid foundation for stable digital employment in various regions.
6.3. Limitations and Suggestions for Future Research
Measuring the development of digital technology is a challenging task. This study employs the prevalent text analysis method and the number of patent applications related to digital technology to characterize its development. Additionally, it explores the impact of digital technology on the income of urban residents. Future research should aim to reflect the development of digital technology with specific and detailed indicators. The focus should be on the penetration of digital technology into the field of sustainable economic development and its far-reaching impact on various production factors and economic activity participants. Simultaneously, numerous digital technology factors impact the relative poverty of urban residents. Future research should focus on exploring micro-level digital technology factors.