Opportunities for China’s Agricultural Heritage Systems under the “Digital Nomadism” Trend—A Stakeholder-Weighted Approach

Abstract

Agricultural heritage systems are appreciated worldwide for their significant environmental and cultural values. However, the sustainability of these systems has been compromised by environmental issues due to intensive human activities and socio-economic changes. Research has noticed that “digital nomadism” is providing a new opportunity for the sustainable development and transformation of these systems, regarded as “digital nomad-friendly” destinations. Nevertheless, comprehensive research on this new trend has been limited except for a few individual case studies. This study is the first to investigate the sustainable development of agricultural heritages considering the growing phenomenon of digital nomadism on a large scale. Based on in-depth stakeholder interviews, we introduced the Digital Nomad-Friendly (DNF) score—a comprehensive indicator system chosen and weighted by stakeholders. The DNF scores of 189 China National Important Agricultural Heritage System (China-NIAHS) sites were evaluated, and their distributions were analyzed on a national scale in China. The results highlight the importance of natural landscape and cultural value in the eyes of digital nomads, particularly emphasizing aesthetic landscape features, climatic suitability, and a community atmosphere. Sites with the highest DNF scores are located mostly in the Zhejiang and Yunnan provinces, sharing characteristics that appeal to digital nomads. The DNF scores exhibit regional variations, with high-DNF-score sites being concentrated in southwestern and southeastern China. By enhancing our understanding of digital nomads’ preferences and the influencing factors, this study provides valuable insights for the environmental management, policymaking, and sustainable development of China-NIAHS sites considering contemporary environmental and social changes.

1. Introduction

Digital nomads are people who sustain a nomadic lifestyle by earning income through online work while enjoying the benefits of cost-effective living and picturesque landscapes. This concept first appeared in the book “Digital Nomad” published in 1997 [1]. There has been a rapid growth in the number of digital nomads due to the profound shifts in employment and lifestyle preferences, including the diverse income opportunities supported by internet, rising youth unemployment, and the increasing amount of remote work in the post-pandemic era [2]. Reports indicate that the global population of digital nomads reached 35 million by 2022 [3], and will exceed the estimated number of one billion by 2035 [4]. Currently, over 25 countries have introduced digital nomad visas [5]. China is actively embracing the global trend of the rise of digital nomadism. According to the “2022 Employment Trends Report” jointly published by the Peking University National Development Institute and the Zhilian recruitment platform, 76.4% of the post-2000 generation in China are willing to become digital nomads [6], with demand for entry into the digital nomad communities consistently exceeding availability. More than remotely working online, digital nomads are known for “roaming” freely with an alternative lifestyle while working and traveling [7]. Due to the rapid growth of digital nomadism, international attention is growing to satisfy their demands with far-off destinations for co-living experience.

Although digital nomads are not the only professionals to work remotely, they pursue a lifestyle of perpetual travel by choice instead of being forced by work. With the limited availability of co-living destinations in big cities [8], digital nomads are seeking out rural areas with rich cultural heritage as destinations for their well-being [9], appreciating the naturalness and tranquility they offer. Unlike urban areas that can quickly adapt to these emerging demands due to their existing infrastructure, agricultural heritage sites in rural regions, lacking a sufficient pre-existing infrastructure, have entered the game without much preparation. Appreciated worldwide for their significant natural and cultural values [10,11], agricultural heritage landscapes are significantly advantageous alternatives that provide a balance between work, home, and social needs. China’s National Important Agricultural Heritage Systems (China-NIAHS) proposed by China’s Ministry of Agriculture and Rural Affairs are outstanding representatives among them based on long-term survey throughout China [12]. So far, there are 189 sites identified in the China-NIAHS. These China-NIAHS sites are regarded as “digital nomad-friendly” destinations, offering ideal conditions for both living and working. However, in recent decades, both global and China’s agricultural heritage systems have undergone a profound transition marked by agricultural abandonment, unsustainable local livelihoods, and degraded landscape values [13,14,15,16,17]. The sustainability of these systems is being challenged by intense human activities and socio-economic changes, particularly hyper urbanization, extensive urban expansion, and the demographic shift from rural to urban areas [18,19,20].

With the rapid urbanization of China, the dynamic preservation and adaptive management of agricultural heritage sites have emerged as a critical research area, posing significant challenges. The concept of “dynamic conservation” is founded on the belief that opportunities for agricultural heritage conservation primarily reside in fulfilling the needs and aspirations of the users. Some research has been carried out to explore these new solutions for living circumstances and their relationships with the digital nomads’ lifestyle [21,22,23]. The digital nomads’ lifestyle could, on the other hand, contribute significantly to the sustainable development of agricultural heritage sites by generating a growth in tourism (produced by either short-term vacations or the long-term residence of digital nomads), digital agriculture (connecting with the market to help sell agricultural products through the internet), and spatial practices for local communities (some community-based public space construction has been carried out by digital nomads) [24,25,26,27]. Specifically, the influx of creative and entrepreneurial digital nomads has proven to be instrumental in revitalizing villages that suffered from a loss of visitors due to the pandemic [21]. While some livable cities like Dali and Anji have attracted them by offering digital nomads shared workspaces and like-minded communities for remote living, both practical studies and research on digital nomads’ experiences in agricultural heritage sites have been scarcely carried out considering their surprisingly large number.

The significant increase in the population of digital nomads calls for a thorough examination of the viability of the mobility of digital nomads driven by individual motivations and preferences [28,29,30]. Studies on the factors influencing the migration of digital nomads have mainly focused on certain urban destinations [28,31]. The methods employed in these studies often involve descriptive literature review [32], case comparisons [33], and qualitative research, such as in-depth interviews within the digital nomad community [34,35]. However, comprehensive research on this new trend has been limited, except for a few individual case studies, and a theoretical framework or evaluation system has not yet been established. Additionally, although there have been some suitable methods and specific techniques for the assessment of the sustainability of agricultural heritage, most studies, limited to individual cases [36,37], are primarily focused on production and ecological functions [8,38]. There has been a lack of examination of the sustainability and impact of digital nomads’ choice of destinations on agricultural heritage in rural areas, especially on a transregional or national scale with a larger sample size.

Due to the lack of quantitative literature on digital nomads’ preferences for destinations and the absence of large-sample comprehensive sustainability evaluations for agricultural heritage, this study is the first to investigate the sustainable development of agricultural heritage considering the growing phenomenon of digital nomadism on a large scale, with attempt to explore the mutual promotion between them. A better knowledge of digital nomads’ preferences for landscape sites and their influencing factors may offer inspiration for future decisions about the sustainable development of agricultural heritage. This study aims to explore to what extent agricultural heritage sites satisfy the needs of digital nomads in China. Specifically, the objectives of this study include: (1) introducing the Digital Nomad-Friendly (DNF) score—a comprehensive indicator system integrating natural, cultural, and socioeconomic factors, chosen and weighted by stakeholders based on in-depth interview; (2) evaluating the DNF of 189 China-NIAHS sites, and identifying a list of DNF agricultural heritage sites in China; and (3) analyzing the distribution of these sites on a national scale in China to provide recommendations for planning and policymaking. The implications of this study extend beyond individual-level preferences. It situates the digital nomads within the contemporary context of significant social–economic shifts, contributing to the sustainable development of China-NIAHS.

2. Materials and Methods

Three research phases were conducted to assess digital nomads’ preferences for landscape sites and explore to what extent agricultural heritage areas satisfy the needs of digital nomads China (Figure 1):

• Data collection of overall, detailed information about China-NIAHS sites;
• Establishment of the indicator system to assess the Digital Nomad Friendliness (DNF) of China-NIAHS sites based on stakeholder interviews;
• Evaluation of the Digital Nomad Friendliness (DNF) of China-NIAHS sites;
• Spatial and statistical analysis of Digital Nomad Friendliness (DNF) of China-NIAHS sites.

2.1. Basic Information Collection

There are 189 agricultural heritage landscapes that have been officially designated by the Ministry of Agriculture in China up until August 2023. In the first phase, the study reviewed all the data and detailed information derived from the application files for those agricultural heritage landscapes. This information was sourced from application files that are accessible through the China-NIAHS Digital Resource website and the FAO GIAHS website [12,39,40], including names, locations, cultivation history, agricultural systems, landscape features, ethnic groups, etc. In addition to these authoritative platforms, an extensive examination of the literature within this field was conducted, encompassing detailed descriptions, research findings, and photographic materials from a wide array of sources (Figure 1).

In this study, precise geographical coordinates (latitude and longitude) of the China-NIAHS sites were acquired, pinpointed, and recorded in the ESRI ArcGIS 10.8 software, resulting in the creation of a comprehensive GIS database (Figure 1). This laid the foundation for the next phrase, involving assigning scores to various factors that influence digital nomads’ destination choices at the national spatial scale.

2.2. Establishment of the Stakeholder-Weighted Indicator System for Digital Nomad Friendliness (DNF) of China-NIAHS Sites

2.2.1. Identification of Influencing Factors and Selection of Indicators through Interviews

Stakeholder engagement has played a crucial role in this research, which is primarily qualitative and adaptable rather than a purely statistical process. On 23 August 2023, an online workshop was held with 35 digital nomad participants who were interviewed. This diverse group included self-media professionals (such as travel bloggers, design and photography bloggers, and food bloggers), writers, programmers, psychological counselors, designers, and investors. The focus of the discussion primarily revolved around the factors influencing digital nomads’ destination choices and their preferences. In addition to the workshop, several in-depth discussions were conducted with the digital nomads to seek their assistance and feedback during the development of the indicator system.

After the literature review and interview, we observed that digital nomads primarily consider a range of factors when choosing a destination. Some of the key characteristics that digital nomads most favor in their preferred destinations include the local climate, natural landscapes, cost of living, unique cuisine, infrastructure, cultural experiences, transportation, and internet services. Furthermore, while digital nomads are adventurous, those who travel or reside alone tend to seek like-minded individuals to form communities and often require a coworking environment where they can collaborate together. Considering multiple factors, the study selected comprehensive DNF assessment indicators that are well-matched with the environmental, socio-economic, and cultural needs of digital nomads, making the indicator system more comprehensive.

• Natural Landscape Value:

  (1)

  Favorable and stable weather conditions; that is climatic suitability (annual average for climatic suitability, duration of comfortable weather period).

  (2)

  Landscapes diversity (agricultural biodiversity, biodiversity intactness, biological abundance index).

  (3)

  Aesthetic landscape features (uniqueness, scenery, visuality of agricultural heritage landscape).

  (4)

  Surface comfort (forest landscape integrity, water coverage).

• Economic and Social value:

  (1)

  Affordable short-term local living cost (consumer price index, level of commodities price, average accommodation price).

  (2)

  Accessibility to external transportation (passenger volume, number of flights, number of trains).

  (3)

  Convenience of internal transportation (number of taxis, number of public transportation services, availability of subway/metro).

  (4)

  Infrastructure (public services, safety, degree of digital rural development).

• Cultural Value:

  (1)

  Community atmosphere (existing digital nomad communities, number of public libraries for every 10,000 people).

  (2)

  Tourism resources (abundance of tourism resources, abundance of leisure resources).

  (3)

  Cultural resources (cultural villages, cultural heritage, non-material cultural heritage).

2.2.2. Data Sources for Indicators

The selection of indicators was driven by considerations of data accessibility, making data collection an operable and straightforward process with highly reliable sources, as shown in Table 1. The majority of our data were sourced from a national data map across authoritative platforms collected by the China National Bureau of Statistics [41], for a range of economic and social indicators such as the consumer price index, level of commodities price, average accommodation price, passenger volume, number of flights, trains, taxis, buses, and subways, as well as cultural indicators like community atmosphere, including existing digital nomad communities and number of public libraries per 10,000 people.

Apart from these authoritative platforms, we extensively reviewed the databases available on platforms from various multidisciplinary institutions in order to enhance the validity of the evaluation results. For instance, Chinese traditional villages data and the biological abundance index values were both collected from the Global Change Research Data Publishing and Repository [42,43]. This study acquired a land cover map provided by the European Space Agency (as outlined in Table 1). This map was specifically utilized to extract information related to water coverage. Tree cover and forest landscape intactness data were sourced from the Global Forest Watch platform. We also referred to relevant research literature. For example, indicators such as annual average of climatic suitability and duration of comfortable weather period were used to assess climatic suitability; in addition, public services and the degree of digital rural development were assessed to evaluate infrastructure, and indicators related to tourism and leisure resources, cultural villages, and non-material cultural heritage were derived from existing research findings. These sources were cross-referenced with multiple similar studies to minimize bias. Furthermore, the utilization of a diverse array of data sources helps prevent oversimplification, allowing for a more comprehensive assessment of China-NIAHS’s DNF.

Table 1. Detailed description of data source of the DNF indicators for the China-NIAH sites.

	Factor	Indicator	Source
Natural Landscape Value	Climatic suitability	Annual average of climatic suitability	Shi Z.Y. 2016 [44]; Terjung W.H. 1966 [45]
		Duration/months of comfortable weather period	Tang Y., Feng Z.M., Yang Y.Z. 2008 [46]; Shi Z.Y. 2016 [44]
	Landscape diversity	Agricultural biodiversity	https://www.fao.org/giahs/en/ (accessed on 1 November 2023); https://www.ciae.com.cn/list/zh/agricultural_heritage/video.html (accessed on 1 November 2023)
		Biodiversity intactness	https://www.globalforestwatch.org/ (accessed on 1 November 2023)
		Biological Abundance Index	https://www.geodoi.ac.cn/WebEn/doi.aspx?Id=185 (accessed on 15 November 2023)
	Aesthetic landscape features	Uniqueness, scenery, visuality of agricultural heritage landscape	https://www.fao.org/giahs/en/ (accessed on 1 November 2023); https://www.ciae.com.cn/list/zh/agricultural_heritage/video.html (accessed on 1 November 2023)
	Surface comfort value	Tree cover and forest landscape intactness	https://www.globalforestwatch.org/ (accessed on 20 November 2023)
		Water coverage	http://maps.elie.ucl.ac.be/CCI/viewer/index.php (accessed on 20 November 2023)
Economic and Social value	Local living cost	Consumer price index	https://data.stats.gov.cn/easyquery.htm?cn=E0103 (accessed on 3 December 2023)
		Consumer expenditure/level of commodities price
		Average accommodation price
	External transportation	Passenger volume	https://data.stats.gov.cn/easyquery.htm?cn=E0103 (accessed on 3 December 2023)
		Number of flights
		Number of trains
	Internal transportation	Number of taxis	https://data.stats.gov.cn/easyquery.htm?cn=E0103 (accessed on 3 December 2023)
		Public transportation services
		Availability of subway/metro
	Infrastructure	Public services	Jia W., Liu L. 2023 [36]
		Degree of digital rural development	Li Y, Wen X, 2023 [47]
Cultural Value	Community atmosphere	Existing digital nomad community	https://data.stats.gov.cn/easyquery.htm?cn=E0103 (accessed on 3 December 2023)
		Number of public libraries for every 10,000 people	https://data.stats.gov.cn/easyquery.htm?cn=E0103 (accessed on 3 December 2023)
	Tourism resources	Abundance of tourism resources	Wang K, 1999 [48]
	Leisure resources	Abundance of leisure resources	Zhang GH, Zhang LL, 2018 [49]
	Cultural resources	Cultural village	Bian J. et al. 2022 [50]; Li Y. et al. 2020 [51]
		Non-material cultural heritage	Guo Y. et al. 2022 [52]

Table 1. Detailed description of data source of the DNF indicators for the China-NIAH sites.

	Factor	Indicator	Source
Natural Landscape Value	Climatic suitability	Annual average of climatic suitability	Shi Z.Y. 2016 [44]; Terjung W.H. 1966 [45]
		Duration/months of comfortable weather period	Tang Y., Feng Z.M., Yang Y.Z. 2008 [46]; Shi Z.Y. 2016 [44]
	Landscape diversity	Agricultural biodiversity	https://www.fao.org/giahs/en/ (accessed on 1 November 2023); https://www.ciae.com.cn/list/zh/agricultural_heritage/video.html (accessed on 1 November 2023)
		Biodiversity intactness	https://www.globalforestwatch.org/ (accessed on 1 November 2023)
		Biological Abundance Index	https://www.geodoi.ac.cn/WebEn/doi.aspx?Id=185 (accessed on 15 November 2023)
	Aesthetic landscape features	Uniqueness, scenery, visuality of agricultural heritage landscape	https://www.fao.org/giahs/en/ (accessed on 1 November 2023); https://www.ciae.com.cn/list/zh/agricultural_heritage/video.html (accessed on 1 November 2023)
	Surface comfort value	Tree cover and forest landscape intactness	https://www.globalforestwatch.org/ (accessed on 20 November 2023)
		Water coverage	http://maps.elie.ucl.ac.be/CCI/viewer/index.php (accessed on 20 November 2023)
Economic and Social value	Local living cost	Consumer price index	https://data.stats.gov.cn/easyquery.htm?cn=E0103 (accessed on 3 December 2023)
		Consumer expenditure/level of commodities price
		Average accommodation price
	External transportation	Passenger volume	https://data.stats.gov.cn/easyquery.htm?cn=E0103 (accessed on 3 December 2023)
		Number of flights
		Number of trains
	Internal transportation	Number of taxis	https://data.stats.gov.cn/easyquery.htm?cn=E0103 (accessed on 3 December 2023)
		Public transportation services
		Availability of subway/metro
	Infrastructure	Public services	Jia W., Liu L. 2023 [36]
		Degree of digital rural development	Li Y, Wen X, 2023 [47]
Cultural Value	Community atmosphere	Existing digital nomad community	https://data.stats.gov.cn/easyquery.htm?cn=E0103 (accessed on 3 December 2023)
		Number of public libraries for every 10,000 people	https://data.stats.gov.cn/easyquery.htm?cn=E0103 (accessed on 3 December 2023)
	Tourism resources	Abundance of tourism resources	Wang K, 1999 [48]
	Leisure resources	Abundance of leisure resources	Zhang GH, Zhang LL, 2018 [49]
	Cultural resources	Cultural village	Bian J. et al. 2022 [50]; Li Y. et al. 2020 [51]
		Non-material cultural heritage	Guo Y. et al. 2022 [52]

2.2.3. Indicator Weight Assignment

The weight of evaluation indicators was determined through incorporating both subjective and objective approaches. We used the Delphi Method (DM) and Analytic Hierarchy Process (AHP) to calculate these weights [53,54]. Qualitative questionnaires were distributed individually to twelve digital nomads via the DM. The study used AHP to determine the relative degree of importance of each indicator based on the feedback received from digital nomads. After an iterative process involving five rounds of anonymous consultations and adjustments based on feedback, a high level of consensus was achieved, with consistency test results ranging from 0.011 to 0.057 (<0.10) [55].

2.3. Evaluation of the Digital Nomad Friendliness (DNF) of China-NIAHS Sites

The third phase is to measure and evaluate the digital nomad friendliness (DNF) of China-NIAHS sites. To assess a more accurate and objective value, two measures were taken:

As Table 1 shows, this study primarily used valid quantitative datasets with less bias as the data source. Some of those quantitative datasets have been either examined using an authoritative platform, others were produced by scholars qualified in this field. However, for some indicators that cannot be measured quantitatively, we manually converted the descriptive and graphic data into quantitative indicators, as demonstrated in

Table 2. Examples of score standard for DNF indicator of China-NIAHS sites.

Name of China-NIAHS	Interpretation of Indicator	Agricultural Biodiversity	Aesthetic Landscape Features
Huzhou Mulberry-dyke and Fish-pond System, Zhejiang	Ponds with mulberry trees planted on the banks, and leaves for silkworms; silkworm waste is used to feed fish; rich in silkworm culture, festivals, tourism, silk production, freshwater aquaculture.	1	0.8
Xinghua Duotian Agrosystem, Jiangsu	“Integrated production of forests, crops, ponds, and fish; unique landscapes and tourism.	0.6	1
Zhangqiu Onion cultivation system, Shandong	Traditional cultivation involves the rotation of scallions and wheat for two years or more.	0.4	0.2

, where relative degrees were scored on a consistency scale ranging from 0 to 1 for all sites [56].

For ease of comparison, the data for each indicator in the China-NIAHS sites were presented as percentages. Subsequently, the indicator data were then transformed into standardized values between 0 and 1 through a linear adjustment formula, as follows:

$$x^{\mathrm{\prime }}=\frac{x-lower\left(x\right)}{upper\left(x\right)-lower\left(x\right)}\mathrm{\ast }5$$

2.4. Digital Nomad Friendliness (DNF) Spatial Analysis of China-NIAHS Sites

In this study, after acquiring the precise geographical coordinates of the China-NIAHS sites to establish a base map, GIS and statistical methods were applied to depict the spatial distribution of the China-NIAHS sites.

3. Results

3.1. Indicator Weight Analysis

Table 3. DNF assessment indicator system for the China-NIAHS using the DM and AHP.

Goal Level		Weight	Factor	Weight	Indicator	Weight
Digital Nomad Friendly (DNF) assessment	Natural Landscape Value	0.493	Climatic suitability	0.255	Annual average of climatic suitability	0.500
					Duration/months of comfortable weather period	0.500
			Landscape diversity	0.057	Agricultural biodiversity	0.333
					Biodiversity intactness	0.333
					Biological Abundance Index	0.333
			Aesthetic landscape features	0.590	Uniqueness, scenery, visuality of agricultural heritage landscape	1.000
			Surface comfort value	0.098	Tree cover and forest landscape intactness	0.500
					Water coverage	0.500
	Economic and Social value	0.196	Local living cost	0.509	Consumer price index	0.333
					Level of commodities price	0.333
					Average accommodation price	0.333
			External transportation	0.065	Passenger volume	0.333
					Number of flights	0.333
					Number of trains	0.333
			Internal transportation	0.127	Number of taxis	0.333
					Public transportation services	0.333
					Availability of subway/metro	0.333
			Infrastructure	0.299	Public services	0.500
					Degree of digital rural development	0.500
	Cultural Value	0.311	Community atmosphere	0.540	Existing digital nomad community	0.500
					Number of Public libraries for every 10,000 people	0.500
			Tourism resources	0.295	Abundance of tourism resources	1.000
			Leisure resources	0.103	Abundance of leisure resources	1.000
			Cultural resources	0.062	Cultural village	0.500
					Non-material cultural heritage	0.500

and Figure 2 depict the weights assigned to the twelve DNF indicators, which were derived from interviews and consensus among digital nomads using the DM.

From a factor-level perspective, the indicator system prioritized “Natural Landscape Value” (0.493) and “Cultural Value” (0.311), compared to “Economic and Social Value” (0.196). This emphasis can be attributed to the limited availability of natural landscapes in the busy and developed cities where digital nomads typically reside. Similarly, cultural attributes, although present in specific cities, are relatively rare in many urban areas. This scarcity prompts digital nomads to be more inclined towards travel destinations that offer a blend of ecological livability and cultural charm. Additionally, the lower cost of living in China-NIAHS sites, in contrast to the cities where digital nomads usually base themselves, accentuates the importance of “Natural Landscape Value” and “Cultural Value” in the eyes of digital nomads.

In terms of indicator importance at the indicator level, digital nomads placed a high priority on “Aesthetic landscape features” (0.291). This is largely because, apart from the limited natural beauty found in larger cities, digital nomads heavily rely on the internet when selecting a destination. This reliance amplifies the visual appeal of a place, making it a key factor in their decision-making. They also gave significant importance to “Climatic suitability” (0.126) due to their preference for comfortable working and living environments that enhance their productivity and overall well-being. “Community atmosphere” (0.168) was another essential consideration for digital nomads, as they often seek recognition and social interaction, which can be facilitated by well-developed digital nomad communities. Digital nomads also favored China-NIAHS sites with a higher density of “Tourism resources” (0.092) because of their open-mindedness and adventurous spirit, which attracts them to areas with a wealth of tourism opportunities. For digital nomads in urban areas, the relatively lower “Local living cost” (0.100) was emphasized, as it directly contributes to cost savings and allows them to take advantage of geographical arbitrage.

3.2. A DNF List of China-NIAHS Sites

Table 4. A list of the top ten DNF China-NIAHS sites.

Ranking	Name	Province	Location	Agricultural Zones	DNF
1	Hani Rice Terrace System, Honghe, Yunnan	Yunnan	Honghe	Yunnan-Guizhou Plateau Region	0.801951
2	Nanxun Mulberry-Fish Pond System, Huzhou, Zhejiang	Zhejiang	Nanxun	Middle and Lower Reaches of Yangtze River Region	0.78434
3	Terraced Tea Gardens System, Xi County, Anhui	Anhui	Xi County	Middle and Lower Reaches of Yangtze River Region	0.783723
4	Qingtian Rice-Fish Symbiotic System, Zhejiang	Zhejiang	Qingtian	Middle and Lower Reaches of Yangtze River Region	0.776847
5	Anji Bamboo Culture System, Zhejiang	Zhejiang	Anji	Middle and Lower Reaches of Yangtze River Region	0.77165
6	Wuxing Lougang Weir Field Agriculture System, Zhejiang	Zhejiang	Wuxing	Middle and Lower Reaches of Yangtze River Region	0.747948
7	Puer Ancient Tea Gardens and Tea Culture System, Yunnan	Yunnan	Puer	Yunnan-Guizhou Plateau Region	0.726981
8	Yangbi Walnut-Crop Complex System, Yunnan	Yunnan	Yangbi	Yunnan-Guizhou Plateau Region	0.725055
9	Pidu Linpan Agricultural Culture System, Sichuan	Sichuan	Pidu	Sichuan Basin Region	0.719053
10	West Lake Longjing Tea Culture System, Zhejiang	Zhejiang	West Lake	Middle and Lower Reaches of Yangtze River Region	0.708759

provides a list of the top ten DNF China-NIAHS sites, all of which have earned a DNF score exceeding 0.708. The table includes their rankings, heritage names, DNF scores, and geographical locations, which encompass agricultural zoning and the respective provinces to which they belong. Notably, certain regions exhibit a strong appeal to digital nomads, with five of the top ten sites being located in Zhejiang province and three in Yunnan.

Upon analyzing the scores of various DNF indicators for the top ten sites (Figure 3), it becomes evident that they share certain commonalities and excel in specific areas. For instance, in terms of the “Natural Landscape Value”, the “Aesthetic landscape features” indicator consistently scores above 0.75 for all of the top ten sites. The majority of these sites exhibit high values exceeding 0.7 for “Climatic suitability” and “Surface comfort value.” Even though “Landscape diversity” carries a lower weight, the majority of sites score above 0.66. In terms of “economic and social value,” their “Community atmosphere” indicators consistently surpass 0.8, and “Local living cost” exceeds 0.51. When considering “Cultural Value”, “Tourism resources” are no lower than 0.6. While not every site possesses a high “Cultural resources” score, half of them have “Cultural resources” scores greater than 0.82. These shared characteristics emphasize the appeal of these sites to digital nomads and reflect the importance of specific factors.

3.3. Spatial Distribution of and Variations in DNF of China-NIAHS Sites

Figure 4 illustrates the DNF map of the 189 China-NIAHS sites on a national scale. The majority of the China-NIAHS sites are situated in southeastern China, characterized by densely populated hills and plains, which can be attributed to the monsoon climate in the region. In contrast, there is a notable absence of China-NIAHS sites in northwest China, where sparsely populated grasslands and deserts prevail due to the arid and semi-arid climate.

The China-NIAHS sites with lower digital nomad friendliness are primarily concentrated in northwest, northeast, and central China, while those with higher digital nomad friendliness are dispersed across the southwestern region and clustered in the southeastern coastal areas (Figure 4).

Given the extensive spatial variation in the natural and cultural contexts across the 189 China-NIAHS sites, this study conducted an analysis of their DNF scores within specific contexts. This analysis was based on the DNF distribution within the nine agricultural zonings, revealing variations in the DNF of China-NIAHS sites across different regions (Figure 5a).

Regions such as the Yunnan-Guizhou Plateau, the middle-lower reaches of the Yangtze River, the Sichuan Basin, and Southern China have received relatively high DNF scores. In comparison, the DNF scores in areas like the Loess Plateau, arid and semi-arid northern China, the Northeast Plain, and the Qinghai-Tibet Plateau are relatively lower.

Furthermore, the DNF of China-NIAHS sites demonstrates significant variation among different provinces (Figure 5b). Among the top ten sites in the DNF list of China-NIAHS sites, five are located in the Zhejiang province.

This study further examined the distinctive regional variations in DNF characteristics among China-NIAHS sites. As in Figure 6, four regions—the Yunnan-Guizhou Plateau, the middle-lower reaches of the Yangtze River, southern China, and the Sichuan Basin—stand out for their robust DNF performance. They excel in three comprehensive aspects: Natural Landscape Value, Economic and Social Value, and Cultural Value, showcasing a balanced development. The natural and cultural aspects in these regions are particularly strong.

In contrast, regions with lower DNF, such as the Loess Plateau, arid northern China, the Northeast Plain, and the Qinghai-Tibet Plateau, display imbalances across natural, economic and social, and cultural aspects. The Natural Landscape Value gradually declines compared to regions with a high DNF, with a more significant decrease in Cultural Value (Figure 6). Economic and Social Value tends to be higher, possibly due to these areas being less developed with lower living costs, which can attract some digital nomads.

4. Discussion

4.1. Trade-Offs in Indicators Resulting in Relatively Low DNF

In this study, we observed that the DNF scores were not very high, with the highest score being only 0.802. This is partly because a China-NIAHS site often struggles to meet all the diverse needs of digital nomads. Additionally, the relatively low scores can be attributed to the trade-offs between different indicators. Through the Pearson correlation analysis of various DNF indicators (Figure 7), this study identified a significant negative correlation between some or all of the local living cost indicators (including the consumer price index, level of commodities price, and average accommodation price) related to cultural resources (non-material cultural heritage) and community atmosphere (existing digital nomad community) (−0.7 < p < −0.448). This indicates that China-NIAHS sites with lower living costs and corresponding facilities (higher score in local living costs indicators) tend to have less developed economies. Consequently, they may have relatively inconvenient transportation, limited access to public services, and a lack of allocated funds for the preservation of cultural and tourism resources, as well as for the development of digital nomad communities (given the high weightage of the community atmosphere indicator at 0.168). For example, the majority of agricultural cultural heritage sites in the Xinjiang and Tibet provinces have local living cost indicators scoring above 0.8, yet their overall scores remain generally low due to the above-mentioned reasons. On the other hand, economically developed China-NIAHS sites in the Fujian and Zhejiang provinces do not face these issues, but they have higher commodity prices and accommodation costs, which result in lower local living cost scores. Thus, it is challenging to strike a balance.

4.2. Suggestions for China NIAHS Sustainable Development and Rural Policy

In this study, a stakeholder-weighted DNF evaluation based on in-depth interviews with digital nomads offers promising opportunities for the sustainable development of China’s NIAHS sites. The method provides a spatial quantitative reference for a future development path, has been recognized as a vital link between theory and practice, and also as an effective approach to “research through design.” Current planning and management of agricultural heritage landscapes often rely on top-down perspectives led by experts and governments, or bottom-up interviews conducted aiming to capture the micro-level preferences of local residents. Consequently, there exists a gap in the integration of bottom-up mechanism research with top-down planning implementation. This study bridges the top-down and bottom-up approaches through a stakeholder-weighted sustainability assessment. By effectively translating the evaluation results into direct guidance for planning and management, we aim to provide valuable policy recommendations for the systematic and holistic dynamic protection of agricultural heritage.

While DNF reflects travel destination preference of a specific group, digital nomads, it also, to some extent, sheds light on the tourism potential of China-NIAHS sites and their spatial distributions. The findings assist in identifying China-NIAHS sites with a high tourism appeal or those at risk of losing visitors.

A significant number of China-NIAHS sites at risk of losing visitors are located in northwest, northeast, and central China. To address this issue, effective policies, subsidies, and regional or even national-level plans should be implemented. As a result, this study offers a comprehensive view of China-NIAHS sites through the DNF list, and at the same time, provides valuable insights into future development strategies and policymaking for these sites.

4.2.1. Agritourism-Oriented Development for China NIAHS with High DNF

Among various economic development pathways, agritourism has consistently proven effective for the sustainability of agricultural heritage landscapes [57], as exemplified by initiatives like the Qingtian rice–fish symbiotic system [58,59].

In our analysis of DNF scores, we found that high-DNF China-NIAHS sites often cluster near cultural villages and non-material cultural heritage areas. This underscores the value of cultural and leisure elements in contributing to agricultural heritage tourism, benefiting both the local economy and heritage preservation [60,61]. Thus, the value of cultural diversity in attracting and holding heritage tourism might be useful to address the issue of China NIAHS sustainable development by expanding related measures for heritage communities.

This observation aligns with Figure 6, which shows a balanced development of Natural Landscapes, Socio-economic Value, and Cultural Value in high-DNF China-NIAHS sites. These sites, rich in both cultural and natural assets, are well-suited for tourism development and can be seamlessly integrated into the broader tourism chain [62,63].

4.2.2. Agri-Product-Oriented Development for China NIAHS with Low DNF

For China-NIAHS sites with low DNF scores, several key factors contribute to their challenges. First, the climatic suitability (weight 0.126) of these northwest and northeast sites displays some seasonality due to their limited length of favorable weather, making them unable to stably support tourism. Consequently, China-NIAHS sites with relatively low values in climatic suitability (<0.54) often exhibit a low DNF (<0.5). Second, community atmosphere, a factor with significant weight (0.168), is closely correlated to several indicators such as climatic suitability (0.434), cultural villages (0.404), and affordable short-term local living costs (−0.530 to −0.326) (Figure 7). This is consistent with what Figure 6 shows: China NIAHS sites with lower DNF display imbalances across natural, economic and social, and cultural aspects, resulting in a limitation of agritourism.

Low-DNF China-NIAHS sites with tourism problems situated in the northwest, northeast, and central regions of China are scarce on the geographical distribution map. It is imperative to conduct a comprehensive survey of agricultural heritage to thoroughly understand its resources and distribution. Unlike high-DNF China-NIAHS sites with potential agritourism for local economy, those sites, such as the Ningxia irrigation agricultural system, Jilin Wuguantun tribe rice cultivation system and South Tianjin rice planting system, are suitable for agri-product-oriented development paths. This is a stable and long-term development approach for producing high-quality agricultural products and related processing chains [38,64], which involves combining modern elements (such as well-established rural logistics, service networks, and e-commerce) with traditional farming practices. More importantly, targeted policies and subsidies should be tailored to the economic, ecological, and cultural conditions of each China-NIAHS site.

4.3. Mutually Supportive Pathways for Digitasl Nomadism and China NIAHSs

The natural beauty, cultural charm, and cost-effective living experiences in agricultural heritage landscapes are attracting an increasing number of digital nomads to settle in rural areas, bringing new opportunities for China’s “rural revitalization”. These talented digital nomads, including tech workers, artists, and entrepreneurs, connect urban and global resources to rural areas by establishing studios, training centers, and entrepreneurial towns.

To maximize the positive impact of digital nomads on rural revitalization, several steps are essential. First, it is crucial to emphasize the authenticity of agricultural heritage landscapes, both in terms of their natural and cultural attributes (as reflected in the DNF assessment, where Natural Landscape Value holds a weight of 0.493 and Cultural Value has a weight of 0.311). Second, their integration should be further facilitated through the creation of digital nomad communities, tourism promotion, and infrastructure development. Finally, collaborative efforts are needed, involving relevant regulations, policies, platforms, and established mechanisms, to promote mutual benefits between digital nomads and the local villages and residents.

4.4. A Stakeholder-Weighted Universal Approach: Advantages, Limitations and Outlook

4.4.1. Advantages

Compared to a site-specific approach [11,65], this study has provided general knowledge and developed a comprehensive model that integrates natural, socioeconomic and cultural factors to evaluate the DNF of China-NIAHS sites. It also examines the spatial distribution characteristics of these sites. Through a quantitative assessment of China-NIAHS sites, this study provides the Most Popular DNF List. This not only creates scientific evidence for the sustainable management of agricultural heritages and rural development but also identifies potential links between the development of agricultural heritage landscapes and the establishment of digital nomad communities.

Furthermore, the scope of this study essentially extends beyond individual-level differentiating choices, instead situating the digital nomad population within the contemporary context of profound changes in rural sustainable development, economics, and politics. The methodology and framework employed in this study, which bridges certain stakeholders and certain types of sites, can be adapted and applied to other fields, such as cultural villages and biosphere reserves. Its universality and robustness make it a valuable approach for diverse fields.

4.4.2. Limitations

This DNF evaluation approach significantly contributes to a collaborative platform for interdisciplinary research on China-NIAHS sites, spanning regions and national boundaries. However, it seems a bit overgeneralized. Digital nomads cannot always generate considerable gains for various sectors and support the sustainable development of agricultural heritage due to different cultures, technologies, and time spaces. And there remain imperfections in the data and objectivity.

First, although the study is grounded in a comprehensive investigation of various data sources, owing to the unclear boundaries of China-NIAHS sites, the inherent ambiguity in the boundaries of China-NIAHS sites and the absence of more precise indicators along with site-specific spatial data unavoidably introduce constraints to the quantitative model. Consequently, some indicators’ data were primarily determined through manual qualitative assessment, introducing a degree of subjectivity into the results. In the future, we aim to incorporate additional spatialized indicators for a more accurate model and conduct more in-depth research.

Second, the choice of the destination for the digital nomads is sometimes quite subjective and influenced by temporary factors, so this assessment’s results only represent a general trend and may not necessarily correspond to the actual situation.

Third, due to the interrelations among these indicators, the DNF indicators exhibit a certain degree of synergy and tradeoffs, which inevitably leads to situations of either redundant or underrepresented calculations, thus introducing a certain level of bias into the results. However, in the real world, there exist intricate and diverse connections among various elements, and as such, it is impractical to select completely unrelated indicators.

While the study focused on the choice of digital nomads’ destinations, sometimes we have to use national-scale data rather than site-specific data. This is because of the following two reasons: on the one hand, handling a huge number of sites made it difficult to conduct on-site surveys and interviews. On the other hand, there is a knowledge gap between the intangible cultural factors and the tourism, which is difficult to measure quantitatively. Therefore, it is imperative to consider site-specific case studies that involve in-depth investigations in the future to address this knowledge gap effectively.

4.4.3. Outlook

Since China-NIAHSs represent unique regional conjunctions of landscape conservation, local livelihood, tourism, and cultural interchange, different contexts should be considered on a trans-national, national, and regional scale. Although we found that the sustainability of China-NIAHS could be applied to different agricultural zonings, future research is needed to investigate this spatial variability at finer scales in response to comprehensive contexts (biological abundance, habitat condition, water system, socio-economic situation, labor migration, distribution of traditional villages, etc.). This could help with targeted agricultural sustainability and rural planning strategies.

Moreover, numerous scholars have underscored the vast potential of the digital transformation in propelling sustainable development [66,67]. While it can both facilitate and, in some instances, pose challenges to this process, its inherent mobility and adaptability offer significant advantages in adopting new technologies and approaches. However, challenges such as uncertainty, connectivity issues, and infrastructural limitations can act as barriers. Therefore, exploring how digital nomadism can contribute to this objective remains a pivotal aspect of future research endeavors.

5. Conclusions

This study adopted a stakeholder-weighted, comprehensive approach to assess the extent to which agricultural heritage landscapes satisfy the needs of digital nomads on a large, national scale. The evaluation framework and the assigned weights of the indicators reflect the significance of Natural Landscapes and Cultural Value in the perspective of digital nomads. The resulting DNF list identifies the top ten sites that are most suitable for digital nomads. The DNF spatial distribution map of China-NIAHS sites exhibits regional variations, with southwest and southeast China emerging as standout regions due to their strong performance on three comprehensive aspects including Natural Landscape, Economic and Social Value, and Cultural Value, thus showing balanced development. The results of this study indicate that incorporating digital nomads’ preference and sustainability evaluation into the agricultural heritage plan should be highly encouraged. The approach employed in this research can be extended to enhance our understanding of various stakeholders’ preferences and applied to other heritage sites or landscapes. This offers a cost-effective and reliable means to quantify spatial opportunities for China-NIAHS sites, thereby providing valuable insights for policymakers and planners.