Impacts of COVID-19 on Coworking Spaces in Bangkok

Abstract

The impact of COVID-19 on urban workplaces has led to an increasing demand for coworking spaces (CWSs) in Bangkok and has expanded CWSs into suburban areas. This study examines the impacts of COVID-19 on CWSs and focuses on the spatial pattern of CWSs in Bangkok. It seeks to answer the following question: Does the business operation of CWSs in Bangkok have a clustered pattern? Moran's I statistic was employed to investigate the spatial autocorrelation of CWSs in Bangkok before and during COVID-19. The locations and the business operational statuses of CWSs are the main variables.The results of spatial autocorrelation analysis of the CWSs in Bangkok show that before COVID-19, the overall CWSs in Bangkok were spatially clustered patterns with nearby CWSs. Surviving CWSs may not have been spatially related during the pandemic, while closed CWSs were spatially clustered patterns. Key findings show that the operational status of the overall CWSs and closed CWSs influenced nearby CWSs. However, the operational status of surviving CWSs may not have influenced nearby CWSs.The discussion of CWS spatial patterns and the impact of COVID-19 suggests that the spatial patterns of CWSs challenge the location theory. They blur the traditional workplace usage boundaries, particularly redefining the concept of third places, as people can now work from anywhere with flexibility. Furthermore, these patterns could influence future strategies for the development of urban workspace, infrastructure, and transportation network.

Introduction

Before the COVID-19 pandemic, most workplaces were concentrated in urban centers or central business districts (CBD) where people worked at offices (Ceinar and Mariotti, 2021). However, the pandemic affected urban workspaces globally. Numerous countries have adopted social distance and work-from-home (WFH) arrangement instead of commuting to crowded workplaces in the city.

The pandemic has rapidly changed the way people work and their workplaces (Reuschke and Ekinsmyth, 2021). People adapted to the new normal by working flexibly from home and the workplace. In spite of the adaptations, sustaining enough workplace distancing remained a challenge due to limited space (Umishio, Kagi et al., 2022). The demand for flexible workplaces is increasing, leading to higher demand for coworking spaces (CWSs) as people seek temporary work in different locations (Ceinar and Mariotti, 2021).

CWSs are alternative workplaces where individuals work together in a shared office space (Spinuzzi, 2012). They offer a better working environment than working from home or traditional offices (Parrino, 2015). These spaces provide workers with physical and social proximity (Mayerhoffer, 2021; Porceddu and Mansour, 2021).

The COVID-19 pandemic has impacted an unprecedented global crisis, disrupted large-scale travel (Chen, 2022), and shifted work from office settings to remote environments, leading to an increased demand for CWSs as alternative workplaces (Ceinar and Mariotti, 2021; Kitika and Suwatcharapinun, 2024). People are adapting to remote working, rethinking management workplaces, and redesigning workplaces (Hu, 2020). Remote workers rely more on communication technology, welcoming the shift to remote working (He, Meng et al., 2022; Tagliaro and Migliore, 2022).

Remote working and CWSs are highly recognized as they promote collaboration, flexibility, and cost-effectiveness (Apsari and Ronim Azizah, 2019). Remote working improves work effort, well-being, and work-life balance. The approaches to remote working depend on 'flexible working' concepts, referring to work duration, location, and timing to support workers' needs . CWSs can support remote working because they provide users with the communications technology infrastructure and network information (Jeske and Ruwe, 2019).

In 2005, the first CWS emerged in San Francisco. CWSs have gained popularity in developed countries because they promote entrepreneurship, innovation, community-building, and economic growth in urban areas (Gandini and Cossu, 2021; Porceddu and Mansour, 2021; Sutriadi and Fachryza, 2021). CWSs offer flexible and affordable professional workspaces with amenities (Bouncken, Ratzmann et al., 2020; Howell, 2022; Kraus, Bouncken et al., 2022). They serve as knowledge hubs, support collaborative networks, and provide an alternative to traditional organizational structures (Orel, Mayerhoffer et al., 2022). Moreover, CWSs alter dramatically traditional work attitudes to work with more freedom (Green, 2014).

In metropolitan areas, such as São Paulo, Brazil, CWSs in developed countries serve as incubators, supporting startup companies and contributing to innovative urban ecosystems (Nakano, Shiach et al., 2020). CWSs have revitalized downtown areas in Toronto, Canada, stimulated investment and employment, and supported local economic development (Jamal, 2018). These examples highlight the role of CWSs in urban and community economies enhancement.

The COVID-19 pandemic has induced a more flexible approach to workplaces, bringing the role of CWSs into the mainstream of alternative workplaces (Reuschke and Ekinsmyth, 2021). Workers have shifted from office to home (Umishio, Kagi et al., 2022). Some workers chose to work at temporary locations near their homes to reduce their commute to the city (Cuerdo-Vilches, Navas-Martín et al., 2021).

The pandemic accelerated the growth of CWSs in suburban areas. This phenomenon could potentially transform the urban workplace landscape. Many countries are currently studying the impact of COVID-19 on urban workspaces (Mariotti, Akhavan et al., 2023; Mayerhoffer, 2021; Tomaz, Moriset et al., 2022).

Due to the pandemic, many governments are more interested in temporary workplaces, such as CWSs, to support remote working. For example, the European Foundation for the Improvement of Living and Working Conditions in Ireland has created a national remote working strategy to establish remote work as a permanent option after the pandemic (The European Foundation for the Improvement, 2021). Vietnam has also used CWSs for startup businesses and real estate development (Müller-Runte, 2021).

Among the developing countries in Southeast Asia, Bangkok has the highest number of CWSs (Howell, 2022). Previous studies primarily concentrated on CWSs near transit systems, educational institutions, and CWS user behavior. Conversely, these studies were conducted before the pandemic (Nithikulwanit, 2020). Some research also examined the demand for CWS services in Bangkok (Nanthaphol, 2020; Pakpoom, 2017).

Several studies during the pandemic revealed a reduced travel trips between residences and workplaces in Bangkok (Inthisorn and Puttanapong, 2022). Many employees shifted to remote working, some changed their workplaces, and others sought alternative workspaces (Lordthong, 2021). Likewise, many office organizations have conveyed satisfaction with the adoption of CWSs as workstations since the pandemic (Riratanaphong and Narmwiset, 2023).

CWSs are gaining popularity in Bangkok’s real estate market as an alternative workplace, addressing the that caters to the needs of some workers in the new average life era (Colliers, 2021). The proportion of flexible workspaces in Bangkok increased by 80% compared to the year before the pandemic (JLL, 2023). Furthermore, real estate developers tend to invest in developing CWSs in suburban, capitalizing for flexible work arrangements (CBRE, 2022).

Despite its substantial demand, CWSs in Bangkok have acquired scant research attention, specifically regarding their challenges and impact before and during the pandemic. Moreover, there are few studies on the increasing number of alternative workplaces in suburban areas. Therefore, this study needs to consider the overall landscape of CWSs in Bangkok and provide more empirical spatial perspectives. These studies contribute to placemaking, a people-focused strategy prioritizing social interactions in public spaces for sustainable development.

In this study, the authors gathered data revealing overall CWSs in Bangkok. The first CWS in Bangkok appeared in 2009 and continues to grow even during the peak of the pandemic in 2022. There were 228 CWSs operated in Bangkok, as shown in Figure 1. Bangkok is divided into three zones: the Inner Zone (CBD), the Middle Zone, and the Outer Zone (Thammapornpilas, 2015). Before COVID-19, CWSs likely clustered along the mass transit system in the CBD. However, during COVID-19, some new CWSs have emerged in the outer CBD. CWS locations in Bangkok have been trending toward decentralization to the suburbs, as shown in Figure 2. These phenomena represent the spatial transformation of urban workplaces.

Figure 1. Numbers of coworking spaces in Bangkok

Figure 2. The locations of coworking spaces in Bangkok before and during COVID-19

Due to the pandemic, many businesses and workplaces in Bangkok were shut down (Krungsri Research, 2022; Thaipublica, 2023). On the contrary, some CWSs survived, while others closed. The operational statuses of these CWSs before and during the pandemic need to be explored. Understanding the operational status patterns of these CWSs could contribute to their contribution to these alternative workplaces.

Interestingly, this study is the first to examine the operational patterns of CWS in Bangkok. This aims to analyze the spatial patterns of CWS's business statuses before and during the pandemic. Its main question is as follows: Does the business operation of CWSs in Bangkok have a clustered pattern? The spatial autocorrelation analysis was proposed for this study. This study provides significant results for the future development of CWSs and infrastructure, supporting alternative workplaces.

Literature Review

What are coworking spaces?

Coworking spaces (CWSs) are “the third place” (Moriset, 2017). They serve as community workspaces and shared workplaces (Gandini and Cossu, 2021; Spinuzzi, 2012). They are a new form of urban social infrastructure that fosters collaborations among people, ideas, and places (Bialski, Derwanz et al., 2015). These workplaces operate as a service industry in the city, impacting urban dynamics by encouraging collective work participation (Mariotti, Pacchi et al., 2019).

The rise of CWSs is driven by dissatisfaction with traditional workplaces, prompting a search for innovative societal, environmental, and office paradigms (Akhavan, Mariotti et al., 2018). They contribute to economic and social improvements and influence urban real estate development (Ceinar and Mariotti, 2021; Sutriadi and Fachryza, 2021).

Before the pandemic, CWSs provide shared spaces for knowledge workers, offering workplaces between traditional office and freelance work (Gandini and Cossu, 2021). User categories in CWS include coworkers, freelancers, entrepreneurs, organization members, mentees, networkers, motivators, soloists, utilizers, socializers, and learners (Yang, Bisson et al., 2019).

During the pandemic, CWSs provided flexible workplaces for remote working, serving freelancers, startups, office workers, and companies seeking a professional workspace. These workspaces are adapted to social distancing and safety requirements (Cabral and van Winden, 2022; Seong, Brouwer et al., 2022).

The concepts and theories related to coworking spaces

Third place and coworking spaces

Oldenburg (1999) coined the concept "third place", referring to social spaces separate from home (first place) and work (second place) where people interact. Researchers like Gandini and Cossu (2021) and Tomaz, Moriset et al. (2022) consider CWSs as modern third places, offering temporary work environments and supporting activities beyond home and traditional workplaces.

Cafes, coffee shops, and libraries also serve as third places. However, they usually provide limited operational support compared to CWSs (Yang, Bisson et al., 2019). CWSs offer collaborative workspaces, facilities, and cost-effective environments for flexible workers (Apsari and Ronim Azizah, 2019). They provide various workspace types and services not found in traditional offices or other third places (Spinuzzi, 2012), such as private meeting rooms, dedicated desks, comprehensive IT services, networking opportunities, extended hours, and flexible pricing based on user needs (Gandini and Cossu, 2021; Tomaz, Moriset et al., 2022).

During the pandemic, many workers shifted from traditional workplaces to working from home. Some optimized CWSs as flexible and safe alternatives (Ceinar and Mariotti, 2021). While flexible work policies have become more common, not all home environments are suitable for work (Umishio, Kagi et al., 2022). Additionally, people have grown accustomed to working from anywhere (Cuerdo-Vilches, Navas-Martín et al., 2021), increasing the demand for temporary workplaces like CWSs (Cabral and van Winden, 2022).

The Global Coworking Growth Study 2020 reported that the market for CWSs experiences rapid growth in large cities. Conversely, CWS operators also consider investing in local areas (Mayerhoffer, 2021). This trend is also supported by the study conducted by Ceinar and Mariotti (2021), which highlights the increasing demand for CWSs globally and their expansion into the suburbs.

Location theory and workplaces

Workplaces choose locations based on location theory, considering factors like accessibility, transportation costs, labor supply, and market demand for efficiency. They prefer being near transportation hubs, skilled labor, and other businesses in CBDs (Wheatley, 2021).

CBDs are cluster locations of workplaces that provide goods, services, and ICT infrastructure, supporting businesses and boosting urban economies (Wheatley, 2021). Proximity in CBDs fosters social bonds and information sharing, leading to workplace growth (Howell, 2022).

Geographers and urban planners have extensively studied how workplaces and residential areas are distributed (Stevens and Shearmur, 2020). Before the pandemic, people often lived far from where they worked, leading to long commutes from suburbs to CBDs (Kelly, Strazdins et al., 2010; Tomaz, Moriset et al., 2022).

During the pandemic, workplaces shifted to non-traditional locations, enabling remote work from anywhere using ICTs (Wheatley, 2021). Changes in workplace location influence policies, economic conditions, industry trends, labor markets, and lifestyle shifts (Divigalpitiya and Handayani, 2015; Reuschke and Ekinsmyth, 2021).

Location theory and coworking spaces

Traditionally, CWSs were located in urban areas (Ceinar and Mariotti, 2021). However, the pandemic has increased remote work adoption and new CWSs in suburban (Al-Rashid, Nadeem et al., 2021; Tomaz, Moriset et al., 2022). The clustering of new CWSs in local neighbourhoods creates a new spatial agglomeration of workplaces (Tomaz, Moriset et al., 2022).

The pandemic has intensified workers’ concerns about workplace safety, resulting to reduced traveling for work to city centers. Alternative workplaces such as CWSs close to residential areas or easily accessible by private cars are preferable (Ceinar and Mariotti, 2021; Robelski, Keller et al., 2019). Thus, CWS operators had to adapt and choose locations that catered to customer needs (Lekić Glavan, Nikolić et al., 2022).

COVID-19 and coworking spaces

CWSs have been popular workplaces, with sustained growth surging during the pandemic (Elsafty and AlNawaly, 2020; Gandini and Cossu, 2021). CWSs are usually in metropolitan areas with good infrastructure, transportation, customers, workers, and proximity to educational institutions (Ceinar and Mariotti, 2021; Howell, 2022).

Work-from-home policies during the pandemic have enabled flexible work schedules and locations (Cabral and van Winden, 2022). Entrepreneurs now seek flexible virtual workplaces that offer reasonable fees, social distancing, and collaboration support (Elsafty and AlNawaly, 2020). Some workers need flexible workspaces due to unconducive home environments, and CWSs can meet these needs (Ceinar and Mariotti, 2021; Umishio, Kagi et al., 2022).

The pandemic fueled demand for CWSs in suburban areas, driven by their proximity to residential areas and lower investment costs compared to CBDs (Ceinar and Mariotti, 2021; Sutriadi and Fachryza, 2021). They support local startups and community engagement and reduce commuting (Tomaz, Moriset et al., 2022), reflecting urban spatial transformations (Fezzai, 2024).

Governments worldwide, such as Germany, Malaysia, Indonesia, and Vietnam, recognize the importance of CWSs in acquiring local economic development and supporting entrepreneurs post-pandemic, incorporating them into urban development policies to foster innovation and cooperative networks (Knaus, Margies et al., 2021; Seong, Brouwer et al., 2022).

Research Methodology and Data

This study uses a spatial autocorrelation analysis to examine the spatial relationship of the business operational statuses of CWSs in Bangkok. This analysis assesses the extent of spatial dependence or clustering in variable values, revealing the underlying spatial patterns. Moran's I statistic serves as a tool to analyze the spatial autocorrelation of the business operational statuses of CWSs in Bangkok.

The analysis was conducted using the ArcGIS Pro software program. The spatial autocorrelation analysis of the business operation statuses of CWSs can contribute new knowledge about alternative workplaces in Bangkok.

The principles of spatial autocorrelation

Spatial autocorrelation, based on Tobler's first law that "everything is related to everything else, but near things are more related than distant things" (Tobler, 1970), occurs when the presence of a substance in neighboring counties affects its probability in a given county (Cliff and Ord, 1970). This concept leads to correlated data among neighboring areas, influencing spatial analysis (Miller, 2004; Warf, 2014) and resulting in spatial patterns where nearby places share similar characteristics (Griffith and Lea, 2005). These spatial patterns represent the distribution and organization of features based on location (Jaber, Hussein et al., 2022; Warf, 2014).

Model-based statistical inference is often used to analyze this spatial correlation. However, this approach relies on assumptions and a population mixed through randomness (Warf, 2014). Global Moran's I is a statistical model to measure the total geographical data clustered. It is described as follows (Moran, 1950; Su, Zhang et al., 2012):

  

$$I=\frac{n\sum _i^n\sum _j^n{w}_{ij}(x_i-\overline{x})(x_j-\overline{x})}{W\sum _i^n({x_i-\overline{x})}^2}$$

Where;

$n$ is the number of spatial units indexed by $i$ and $j$ ,

$x$ is the variable of interest,

$\overline{x}$ is the mean of $x$ ,

$w$ _ij are the elements of a matrix of spatial weights with zeroes on the diagonal (i.e., $w$ _ij = 0), and

W is the sum of all $w$ _ij (i.e., ${\sum }_{i=1}^N{\sum }_{j=1}^N{w}_{ij}$ )

Moran's I measures spatial autocorrelation by assessing the proximity of locations with similar features, indicating patterns of clustering, dispersion, or randomness. A positive Moran's I (close to +1) shows spatial correlation, while a negative value (close to -1) indicates dispersion. Under the null hypothesis of no spatial autocorrelation, Moran's I suggests a random distribution of attributes (Jaber, Hussein et al., 2022; Moran, 1950).

This study applies Moran's I to analyze the spatial autocorrelation of the business operation statuses of CWSs in Bangkok. The overview suggests that CWSs in Bangkok are clustered in the CBD. However, whether their business operation statuses exhibit a similar clustering as visually observed has not been confirmed. This analysis considers the proximity of the similar business operation statuses of nearby CWSs during COVID-19.

Research questions and hypotheses

Research questions

The study aims to answer the following questions:

Q1: Are the business operations of CWSs in Bangkok clustered?

Q2: Are the surviving CWSs during COVID-19 clustered?

Q3: Are the closed CWSs during COVID-19 clustered?

The hypotheses

The hypotheses of this study are as follows:

H1: The business operations of CWSs in Bangkok are spatially correlated in a clustered pattern.

H2: The surviving CWSs during COVID-19 are spatially correlated with surviving CWSs nearby in a clustered pattern.

H3: The closed CWSs during COVID-19 are spatially correlated with closed CWSs nearby in a clustered pattern.

The hypotheses of Moran's I statistic to test H1 are as follows:

H₀: The business operations of CWSs in Bangkok are not spatially correlated in a clustered pattern.

H₁: The business operations of CWSs in Bangkok are spatially correlated in a clustered pattern.

The hypotheses of Moran's I statistic to test H2 are as follows:

H₀: The surviving CWSs during COVID-19 are not spatially correlated with similar surviving CWSs nearby in a clustered pattern.

H₁: The surviving CWSs during COVID-19 are spatially correlated with similar surviving CWSs nearby in a clustered pattern.

The hypotheses of Moran's I statistic to test H3 are as follows:

H₀: The closed CWSs during COVID-19 are not spatially correlated with similar closed CWSs nearby in a clustered pattern.

H₁: The closed CWSs during COVID-19 are spatially correlated with similar closed CWSs nearby in a clustered pattern.

Based on the principles of Moran’s I statistic, the null hypotheses state that there is no spatial autocorrelation in the business operations of CWSs in Bangkok, the surviving CWSs, and the closed CWSs during COVID-19 at a significance level of 95%.

Data collections

This study collected data on CWSs in Bangkok from January 2020 to December 2022. The main variables are CWS locations and business operational statuses, as described in Table 1. The data of CWSs is collected from the operational statuses of business registration statistics by province in Thailand. The data was sourced from the Department of Business Development (DBD) from 2018 to 2022, including data from before and during the pandemic's peak.

Website checks were conducted to verify the operational statuses of CWSs during the pandemic. The operational statuses are divided into opening status and closed status. CWSs with an open status are the surviving CWSs. CWSs with closed status are closed CWSs. The business operational statuses of CWSs are determined by their operating days, ranging from one to seven days per week. Examining the spatial distribution of CWS operational statuses before and during the peak of the pandemic presents vital insights into business operational patterns. This analysis helps us deep understanding on the spatial patterns of surviving and closed CWSs during the pandemic.

Table 1. Descriptions of the variables

Variables	Description	Source
Locations of CWSs	- Location points of CWSs in Bangkok. - Location points of surviving CWSs during COVID-19. - Location points of closed CWSs during COVID-19.	- DBD (2018-2022) - Google Maps websites (2022) - CWS's websites (2022)
The business operational statuses of CWSs	- Open operational status (surviving CWSs) - Closed operational status (closed CWSs)	- Collected data from CWS's websites (2022)

Table 2. Descriptive statistics of coworking spaces' operational status distribution data

Business operational statuses of the CWSs	No. of CWSs	Mean	Std.Dev.	Max.	Min.
All operational CWSs before COVID-19	228	5.939	1.549	7	1
Surviving CWSs during COVID-19	196	6.184	1.177	7	1
Closed CWSs during COVID-19	32	4.438	2.449	7	1

Before COVID-19, there were 228 CWSs in Bangkok. During the pandemic, the business operational statuses of CWSs were surviving and closed. 196 CWSs are surviving and have continued their business operational statuses as usual working days. Meanwhile, 32 CWSs closed their business operational statuses. These data were used as variables with Moran’s I statistical analysis to understand the spatial autocorrelation pattern of their business operational statuses before and during COVID-19.

Results of The Spatial Autocorrelation Analysis of Coworking Spaces in Bangkok

This study explores the main question, "Does the business operation of CWSs in Bangkok have a clustered pattern?" This section presents the results of the spatial autocorrelation analysis, based on Moran's I statistic, to examine the business operational statuses of CWSs. This analysis covered the periods before and during COVID-19; the findings are summarized in Table 3.

Table 3. The global Moran’s I result

Operational Statuses of CWSs	Moran's Index	z-score	p-value
Overall operational CWSs before COVID-19	0.081875	3.908147	0.000093
Surviving CWSs during COVID-19	0.028221	1.327236	0.184431
Closed CWSs during COVID-19	0.265017	2.929284	0.003397

Results of spatial autocorrelation of overall coworking spaces before COVID-19

The spatial autocorrelation analysis of overall CWSs in Bangkok found that Moran's I index was 0.081875, the z-score was 3.908147, and the p-value was 0.000093. The positive Moran's I value indicates spatial correlation. The z-score presents a pattern of spatial autocorrelation among surrounding CWSs in Bangkok with a clustered distribution pattern. Moran's I was statistically significant at the 95% confidence level, as shown in Figure 3. Therefore, the first hypothesis of Moran's I statistic is rejected. These findings suggest that the overall CWSs in Bangkok before the pandemic may be spatially related to similar business operational statuses of nearby CWSs in a clustered pattern. This result indicates that neighboring CWSs likely influenced each other's operational status.

Figure 3. Results of the spatial autocorrelation analysis of overall operational CWS in Bangkok

Results of spatial autocorrelation of surviving coworking spaces during COVID-19

The results of the spatial autocorrelation analysis of surviving CWSs during COVID-19 found that the Moran's I index was 0.028221, the z-score was 1.327236, and the p-value was 0.184431. Moran's I was statistically significant at the 95% confidence level, as shown in Figure 4. The z-score presents the pattern as not significantly different from random. The p-value is higher than the significance level. Surviving CWSs during the pandemic may not be spatially related. They likely did not influence the survival of nearby CWSs, so the second hypothesis remains unconfirmed.

Figure 4. Results of the spatial autocorrelation analysis of the surviving CWSs in Bangkok

Results of spatial autocorrelation of closed coworking spaces during COVID-19

The results of the spatial autocorrelation analysis of closed CWSs during COVID-19 found that the Moran's I index was 0.265017, the z-score was 2.929284, and the p-value was 0.003397. The positive Moran's I value indicates spatial correlation. The z-score presents a pattern of spatial autocorrelation among surrounding closed CWSs and has a clustered distribution pattern. Moran's I was statistically significant at the 95% confidence level, as shown in Figure 5. Therefore, the third hypothesis of Moran's I statistic is rejected. The operational statuses of closed CWSs during the pandemic may be spatially related to similar operational statuses of nearby closed businesses in a clustered pattern. In other words, the results indicate that nearby closed CWSs likely influenced each other's closed operational status.

Figure 5. Results of the spatial autocorrelation analysis of the closed CWSs in Bangkok

Results of the Spatial Pattern of Coworking Spaces in Bangkok Before and During COVID-19

The results of the study do not reject H1 and H3. H1 suggests that the business operational statuses of CWSs in Bangkok before COVID-19 were spatially correlated in a clustered pattern. Similarly, H3 suggests that the closed CWSs during COVID-19 are spatially correlated with closed CWSs nearby in a clustered pattern. However, the analysis could not confirm H2, which states that the surviving CWSs during COVID-19 are spatially correlated with surviving CWSs nearby in a clustered pattern. The surviving CWSs during COVID-19 do not appear spatially related to similar surviving CWSs nearby.

The spatial analysis of the CWSs in Bangkok reveals patterns that are consistent with the third places and location theory concept outlined in Sections 2.1-2.3. Before COVID-19, CWSs in Bangkok exhibited a clustered spatial distribution, indicated by a positive Moran's I index and a significant z-score. This clustering result highlights the role of CWSs as "third places" and their function as urban social infrastructures that foster collaboration. The concentration of CWSs in certain areas aligns with location theory, which proposes that businesses choose locations based on accessibility, proximity to resources, and market demand. These clusters were primarily in urban centers or CBDs, providing the necessary infrastructure and connectivity.

During the COVID-19 pandemic, the study found that closed CWSs also showed a clustered pattern, suggesting that the impacts of pandemic were spatially concentrated. This result stems from higher operational costs in clustered urban areas and decreased demand as workers shifted to remote work or sought safer, less crowded environments.

Conversely, surviving CWSs did not exhibit spatial autocorrelation, indicating that their survival was not dependent on proximity to other CWSs. This lack of spatial clustering among surviving CWSs suggests that non-geographic factors played a vital role in their continued operation. The spatial dispersion implies that the survival of these CWSs was influenced more by other factors than their spatial context.

The key finding is that the overall operational of CWSs in Bangkok was clustered pattern before COVID-19. During the pandemic, the operational of closed CWSs was also clustered pattern nearby. However, the operational of surviving CWSs may not be related to CWSs nearby. Moreover, the findings highlight the importance of location theory in understanding the spatial dynamics of CWSs. The shift from clustered urban centers to more dispersed or suburban locations indicates a transformation in workspace location decision-making, influenced by changing worker needs and external factors like the pandemic.

This study has limitations in time. For example, it involves a relatively short data collection period. However, it still provides substantial evidence. There is a growing demand for CWSs in Bangkok, even during the COVID-19 pandemic.

Discussion of The Coworking Spaces Spatial Patterns and Covid-19 Impact

New coworking spaces may impact on location theory and urban workplace morphology

The COVID-19 pandemic has disrupted the traditional location theory by highlighting the work-from-anywhere trend. It has also driven the emergence of new CWSs in the suburbs, not just in the CBDs. This phenomenon has shifted the urban workplace morphology patterns. Remote work and digital technologies are moving work from fixed locations to a more person-based approach. Location theory emphasizes, the concept of workplaces as evolving and may be less centered on traditional models. This shift opens up new opportunities for understanding workplace distribution and the factors influencing it.

Coworking spaces blurring of the third place concept

The pandemic has amplified the blurring of boundaries of the third place, as remote working becomes progressively prevalent. People can work from anywhere. Oldenburg’s concept of third place became blurred during the pandemic. Workplaces (second place) and homes (first place) have almost merged into one space, while CWSs (third place) have served as workplaces (second place). This trend of using workspace from three places in Bangkok is consistent with the ideas presented by Ceinar and Mariotti (2021), who highlight a paradigm shift from traditional offices (second place) to CWSs (third place), reflecting workers’ preference for flexible work arrangements.

Growth and challenges of CWSs during the pandemic

During the peak of the pandemic, CWS businesses in Bangkok have growth in both CBD and suburban areas. This growth reflects the demand for alternative workspaces close to people's homes. However, most residences in Bangkok are characterized small, dense, old structures or have many members in their homes. These factors cause great challenges for establishing comfortable, efficient, and productive personal workspaces at home. This phenomenon is consistent with the findings of Umishio, Kagi et al. (2022), which highlighted that some workers’ homes may not facilitate suitable and conducive work environments and may require alternative workspaces.

Implications for urban development and infrastructure

The results of this study suggest that the surviving CWSs and the emergence of new ones during the pandemic may indicate a demand for flexible workspaces in those neighbourhood areas. Therefore, organizations related to the development of urban, infrastructure, and transportation system should incorporate plans and strategies to support the expansion of these workplaces. For example, the guidelines should promote mixed-use zones that integrate residential areas with workplaces, thereby reducing commuting time and ensuring easy workplace access. Supporting renewable energy, electricity, and internet services is crucial to enable remote work capabilities.

Impact on employment and business management

The impact of COVID-19 led to dynamic transitions in the job market, with some formal workers becoming informal workers and some altering their jobs and workplaces. Therefore, the Ministry of Labour of Thailand faces challenges in preparing the plan to support welfare services and flexible workplaces for informal workers. On the other hand, the Department of Business Development should prepare to manage the database system of CWSs, which is the source of business networks. This database will effectively augment business group network promotion.

Future research directions

This study had a limited in timeframe. However, studying the impact of COVID-19 on CWSs reveals several other exciting dimensions. The spatial correlation result of CWSs with a clustered pattern may lead to further studies. Future studies should utilize other variables or methods different from this study, such as a study about factors affecting CWSs' survival or closure during COVID-19 or a survey about the impact of new CWSs emerging during COVID-19.

Conclusions

CWSs in Bangkok remained operational during the pandemic, and some new CWSs emerged outside the CBD. However, the spatial relationship of CWSs in Bangkok before and during the pandemic still needs to be studied. as this will support future urban development planning.

The study found that CWSs in Bangkok before the pandemic had a clustered pattern of business operations. Surviving CWSs during the peak of the pandemic were not spatially correlated. Closed CWSs were found to be related to nearby closed CWSs in a clustered pattern. In contrast with location theory, CWSs in Bangkok are booming outside CBD areas, fostering opportunities for suburban growth and easy access to transportation systems.

COVID-19 led CWS locations in Bangkok to expand beyond the CBD, bringing workplaces closer to homes and reducing travel to the CBD. As CWSs are replacing traditional offices, the area between the suburbs and the CBD needs strategic planning. Policies for transportation, facilities, and CWS businesses need development. Future studies can explore alternative variables or methods to yield better results.

Author Contributions

Conceptualization, S.A., and S.S.; methodology, S.A., and S.S.; software, S.A., and S.S.; data curation, S.S.; writing—original draft preparation, S.A., and S.S.; writing—review and editing, S.A., and S.S.; supervision, S.A. All authors have read and agreed to the published version of the manuscript.

Ethics Declaration

The authors declare that they have no conflicts of interest regarding the publication of the paper.

References

•  Akhavan,  M.,  Mariotti,  I., et al. (2018). "Coworking Spaces and New Social Relations: A Focus on the Social Streets in Italy". Urban Science, 3(1), 2. doi: https://doi.org/10.3390/urbansci3010002.
•  Al-Rashid ,  M. A.,  Nadeem, M., et al. (2021). "An Integrated Approach to Analysing the Urban Growth Patterns: The Case of Sialkot, Punjab, Pakistan". International review for spatial planning and sustainable development, 9(4), 116-138. doi: https://doi.org/10.14246/IRSPSD.9.4_116.
•  Apsari , Z. N. and  Ronim Azizah,  S. (2019). "Solo Baru Coworking Space Pendekatan Pada Arsitektur Modern". Universitas Muhammadiyah Surakarta.
•  Bialski,  P.,  Derwanz,  H., et al. (2015). "‘Saving’the City: Collective Low‐Budget Organizing and Urban Practice". Ephemera: Theory & Politics in Organization, 15(1), 1-19.
•  Bouncken,  R.,  Ratzmann,  M., et al. (2020). "Coworking Spaces: Empowerment for Entrepreneurship and Innovation in the Digital and Sharing Economy". Journal of Business Research, 114, 102-110. doi: https://doi.org/10.1016/j.jbusres.2020.03.033.
•  Cabral,  V. and  van Winden,  W. (2022). "The Reaction of Coworking Spaces to the Covid-19 Pandemic. A Dynamic Capabilities Perspective". Service Business, 16(2), 257-281. doi: https://doi.org/10.1007/s11628-022-00489-6.
•  CBRE . (2022). "Real Estate Market Trends". Retrieved from http://cbre.vo.llnwd.net/grgservices/secure/Thailand-Real-Estate-Market-Outlook-2022-TH_8wLX.pdf?e=1654557759&h=27326508e48d9c94acba222084e1723e |on November 11, 2023.
•  Ceinar ,  I. M. and  Mariotti, I. (2021). "The Effects of Covid-19 on Coworking Spaces: Patterns and Future Trends". Research for Development, April, 277-297. doi: https://doi.org/10.1007/978-3-030-63443-8_15.
•  Chen,  Y. (2022). "The Future of Mega-Events, Post-Covid-19 Pandemic". International review for spatial planning and sustainable development, 10(2), 168-178. doi: https://doi.org/10.14246/irspsd.10.2_168.
•  Cliff , A. D. and  Ord,  K. (1970). "Spatial Autocorrelation: A Review of Existing and New Measures with Applications". Economic Geography, 46(sup1), 269-292. doi: https://doi.org/10.2307/143144.
•  Colliers . (2021). "Report of Offices Market in Bangkok". Retrieved from https://www.colliers.com/-/media/files/asia/thailand/research-q2-2020/thailand-industrial-estate-q2-2021_th.ashx?la=en&bid=8ee877598c434bc6a8c1916ec45bdd44&sc_lang=en-th&hash=C3D14FD1ECD94E01B18F80B194043E3B |on November 11, 2023.
•  Cuerdo-Vilches,  T.,  Navas-Martín , M. Á., et al. (2021). "Working from Home: Is Our Housing Ready?". International Journal of Environmental Research and Public Health, 18(14), 7329. doi: https://doi.org/10.3390/ijerph18147329.
•  Divigalpitiya,  P. and  Handayani , K. N. (2015). "Measuring the Urban Expansion Process of Yogyakarta City in Indonesia Urban Expansion Process and Spatial and Temporal Characteristics of Growing Cities". International review for spatial planning and sustainable development, 3(4), 18-32. doi: https://doi.org/10.14246/irspsd.3.4_18.
•  Elsafty,  A. and  AlNawaly,  A. (2020). "Role of Co-Working Spaces’ Services in Entrepreneurs Growth in Upper Egypt: The Case of Step Co-Working Space". Business and Management Studies, 6(2), 114-114. doi: https://doi.org/10.11114/bms.v6i2.4898.
•  Fezzai,  S. (2024). "Assessment of Patterns of Spatial Transformations a Comparative Study of Three Historic City Centres in Algeria". International review for spatial planning and sustainable development, 12(1), 173-195. doi: https://doi.org/10.14246/IRSPSD.12.1_173.
•  Gandini,  A. and  Cossu,  A. (2021). "The Third Wave of Coworking:‘Neo-Corporate’model Versus ‘Resilient’practice". European Journal of Cultural Studies, 24(2), 430-447. doi: https://doi.org/10.1177/1367549419886060.
•  Green,  R. (2014). "Collaborate or Compete: How Do Landlords Respond to the Rise in Coworking?". Retrieved from https://api.semanticscholar.org/CorpusID:152555164 |on November 10, 2023.
•  Griffith , D. A. and  Lea , A. C. (2005). "Locational Decision Making". Encyclopedia of Social Measurement. doi: https://doi.org/10.1016/B0-12-369398-5/00344-3.
•  He, X.,  Meng,  X., et al. (2022). "The Impact of Covid-19 on Various Aspects of Remote Work Software and Future Development". Proceedings of 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022), Atlantis Press 2761-2767. doi: https://doi.org/10.2991/aebmr.k.220307.450.
•  Howell,  T. (2022). "Coworking Spaces: An Overview and Research Agenda". Research Policy, 51(2), 104447. doi: https://doi.org/10.1016/j.respol.2021.104447.
•  Hu, R. (2020). "Covid-19, Smart Work, and Collaborative Space: A Crisis-Opportunity Perspective". Journal of Urban Management, 9(3), 276-280. doi: https://doi.org/10.1016/j.jum.2020.08.001.
•  Inthisorn,  P. and  Puttanapong,  N. (2022). "Associations between Mobility Indices and the Covid-19 Pandemic in Thailand". Nakhara: Journal of Environmental Design and Planning, 21(2), 215-215.
•  Jaber , A. S.,  Hussein , A. K., et al. (2022). "A Moran's I Autocorrelation and Spatial Cluster Analysis for Identifying Coronavirus Disease Covid-19 in Iraq Using Gis Approach". Caspian Journal of Environmental Sciences, 20(1), 55-60. doi: https://doi.org/10.22124/CJES.2022.5392.
•  Jamal , A. C. (2018). "Coworking Spaces in Mid-Sized Cities: A Partner in Downtown Economic Development". Environment and Planning A: Economy and Space, 50(4), 773-788. doi: https://doi.org/10.1177/0308518X18760857.
•  Jeske,  D. and  Ruwe,  T. (2019). "Inclusion through Use and Membership of Co-Working Spaces". Journal of Work-Applied Management, 11(2), 174-186. doi: https://doi.org/10.1108/jwam-06-2019-0021.
•  JLL . (2023). "Flex Space Is Reshaping Bangkok’s Commercial Real Estate. ". Retrieved from https://www.jll.co.th/en/trends-and-insights/research/flex-space-is-reshaping-bangkoks-commercial-real-estate |on Decembe 13, 2023.
•  Kelly,  M.,  Strazdins,  L., et al. (2010). "Thailand's Work and Health Transition". International Labour Review, 149(3). doi: https://doi.org/10.1111/j.1564-913X.2010.00092.x.
•  Kitika,  C. and  Suwatcharapinun,  S. (2024). "Smart District with the Comparison on Urban Studies of Internet Infrastructure and New Digital Activities a Case Study of Chiang Mai Old City, Thailand". International review for spatial planning and sustainable development, 12(3), 200-217. doi: https://doi.org/10.14246/irspsd.12.3_200.
•  Knaus,  K.,  Margies,  N., et al. (2021). "Thinking the City through Work: Blurring Boundaries of Production and Reproduction in the Age of Digital Capitalism". City, 25(3-4), 303-314. doi: https://doi.org/10.1080/13604813.2021.1939966.
•  Kraus,  S.,  Bouncken , R. B., et al. (2022). "Coworking Spaces and Makerspaces: Mapping the State of Research". Journal of Innovation and Knowledge, 7(1), 100161. doi: https://doi.org/10.1016/j.jik.2022.100161.
•  Krungsri  Research. (2022). "Monthly Economic Impact. ". Retrieved from https://www.krungsri.com/getmedia/182dac0e-07d0-4462-9942-97ffcc30cde6/MB_Bulletin_220919_EN.pdf.aspx |on December 10, 2023.
• Lekić Glavan, O., Nikolić, N., et al. (2022). "Covid-19 and City Space: Impact and Perspectives". Sustainability, 14(3), 1885. doi: https://doi.org/10.3390/su14031885.
•  Lordthong,  W. (2021). "Satisfaction on Work from Home for Employees Generation X and Generation Yin in Retail Business". Retrieved from https://archive.cm.mahidol.ac.th/bitstream/123456789/3948/1/TP%20MS.017%202564.pdf |on December 10, 2023.
•  Mariotti,  I.,  Akhavan,  M., et al. (2023). "The Preferred Location of Coworking Spaces in Italy: An Empirical Investigation in Urban and Peripheral Areas". European Planning Studies, 31(3), 467-489. doi: https://doi.org/10.1080/09654313.2021.1895080.
•  Mariotti,  I.,  Pacchi,  C., et al. (2019). "Co-Working Spaces in Milan: Location Patterns and Urban Effects". New Urban Geographies of the Creative and Knowledge Economies (pp. 47-66). Routledge. doi: https://doi.org/10.1080/10630732.2017.1311556.
•  Mayerhoffer,  M. (2021). "The Impact of Covid-19 on Coworking Spaces: Evidence from Germany". Journal of Corporate Real Estate, 23(3), 170-185. doi: https://doi.org/10.1108/JCRE-10-2020-0044.
•  Miller , H. J. (2004). "Tobler's First Law and Spatial Analysis". Annals of the association of American geographers, 94(2), 284-289. doi: https://doi.org/10.1111/j.1467-8306.2004.09402005.x.
•  Moran , P. A. (1950). "Notes on Continuous Stochastic Phenomena". Biometrika, 37(1/2), 17-23. doi: https://doi.org/10.2307/2332142.
•  Moriset,  B. (2017). "Building New Places of the Creative City: The Rise of Coworking Spaces". Territ. Mov. J. Geogr. Plan.
•  Müller-Runte,  C. (2021). "The Proliferation of Coworking Spaces in Vietnam’s Transitional Urban Economy–Moving Towards Adaptation or Resistance?". Lund University.
•  Nakano,  D.,  Shiach,  M., et al. (2020). "Coworking Spaces in Urban Settings: Prospective Roles?". Geoforum, 115, 135-137. doi: https://doi.org/10.1016/j.geoforum.2020.04.014.
•  Nanthaphol,  K. (2020). "Factors Determining the Behaviors of Using Coworking Space among Consumers in Pathumwan, Bangrak, and Wattana Districts". Mahidol University.
•  Nithikulwanit,  P. (2020). "Exportation and Decision-Making Process for Using Coworking Space of Independent Careers in Bangkok". Mahidol University.
•  Oldenburg,  R. (1999). The Great Good Place: Cafes, Coffee Shops, Bookstores, Bars, Hair Salons, and Other Hangouts at the Heart of a Community. Da Capo Press.
•  Orel,  M.,  Mayerhoffer,  M., et al. (2022). "Coworking Spaces as Talent Hubs: The Imperative for Community Building in the Changing Context of New Work". Review of Managerial Science, 16(5), 1503-1531. doi: https://doi.org/10.1007/s11846-021-00487-4.
•  Pakpoom,  W. (2017). "Behaviors and Factors Influencing Coworking Space's Users in Bangkok Metropolitan". Mahidol University.
•  Parrino,  L. (2015). "Coworking: Assessing the Role of Proximity in Knowledge Exchange". Knowledge Management Research and Practice, 13(3), 261-271. doi: https://doi.org/10.1057/kmrp.2013.47.
•  Porceddu,  E. and  Mansour,  O. (2021). "The Role of I.T. And Space in Community-Driven Coworking Spaces". Jonkoping University.
•  Reuschke,  D. and  Ekinsmyth,  C. (2021). "New Spatialities of Work in the City". Urban Studies, 58(11), 2177-2187. doi: https://doi.org/10.1177/00420980211009174.
•  Riratanaphong,  C. and  Narmwiset,  N. (2023). "Employees’ Appraisal of Workplace Changes During Covid-19: Findings from a State-Owned Oil and Gas Company". Nakhara: Journal of Environmental Design and Planning, 22(1), 306-306. doi: https://doi.org/10.54028/NJ202322306.
•  Robelski,  S.,  Keller,  H., et al. (2019). "Coworking Spaces: The Better Home Office? A Psychosocial and Health-Related Perspective on an Emerging Work Environment". International Journal of Environmental Research and Public Health, 16(13), 2379. doi: https://doi.org/10.3390/ijerph16132379.
•  Seong,  M.-H.,  Brouwer , A. E., et al. (2022). The Covid-19 Pandemic and the Future of Working Spaces. Taylor & Francis. doi: https://doi.org/10.4324/9781003181163-17.
•  Spinuzzi,  C. (2012). "Working Alone Together: Coworking as Emergent Collaborative Activity". Journal of business and technical communication, 26(4), 399-441. doi: https://doi.org/10.1177/1050651912444070.
•  Stevens,  L. and  Shearmur , R. G. (2020). "The End of Location Theory? Some Implications of Micro-Work, Work Trajectories and Gig-Work for Conceptualizing the Urban Space Economy". Geoforum, 111, 155-164. doi: https://doi.org/10.1016/j.geoforum.2020.02.010.
•  Su, W.,  Zhang,  C., et al. (2012). "Analysis of Wavelet Packet and Statistical Textures for Object-Oriented Classification of Forest-Agriculture Ecotones Using Spot 5 Imagery". International Journal of Remote Sensing, 33(11), 3557-3579. doi: https://doi.org/10.1080/01431161.2010.532823
•  Sutriadi,  R. and  Fachryza , D. M. (2021). "A Phenomenon in Urban Disruption: The Emergence of Coworking Spaces in Bandung". Heliyon, 7(7). doi: https://doi.org/10.1016/j.heliyon.2021.e07663.
•  Tagliaro,  C. and  Migliore,  A. (2022). "“Covid-Working”: What to Keep and What to Leave? Evidence from an Italian Company". Journal of Corporate Real Estate, 24(2), 76-92. doi: https://doi.org/10.1108/JCRE-10-2020-0053.
•  Thaipublica . (2023). "Eic Analyzes “Business Recovery after Covid Who Said Size Does Not Matter?". Retrieved from https://thaipublica.org/2023/01/eic-business-recovery/ |on December 10, 2023.
•  Thammapornpilas,  J. (2015). "Urban Spatial Development to Mitigate Urban Heat Island Effectin the Inner Area of Bangkok". NAKHARA, 11(1), 29-40. doi: https://ph01.tci-thaijo.org/index.php/nakhara/article/view/104849/83402.
• The European Foundation for the Improvement. (2021). "National Remote Work Strategy Aims to Make Remote Working a Permanent Option after the Pandemic". Retrieved from https://static.eurofound.europa.eu/covid19db/cases/IE-2021-3_1855.html |on December 10, 2023.
•  Tobler , W. R. (1970). "A Computer Movie Simulating Urban Growth in the Detroit Region". Economic Geography, 46(sup1), 234-240. doi: https://doi.org/10.2307/143141.
•  Tomaz,  E.,  Moriset,  B., et al. (2022). "Rural Coworking Spaces in the Covid-19 Era: A Window of Opportunity?". The Covid-19 Pandemic and the Future of Working Spaces (pp. 122-135). Routledge.
•  Umishio,  W.,  Kagi,  N., et al. (2022). "Work Productivity in the Office and at Home During the Covid‐19 Pandemic: A Cross‐Sectional Analysis of Office Workers in Japan". Indoor air, 32(1), e12913. doi: https://doi.org/10.1111/ina.12913.
•  Warf,  B. (2014). "Spatial Autocorrelation". Encyclopedia of Geography, 3. doi: https://doi.org/10.4135/9781412939591.n1055.
•  Wheatley,  D. (2021). "Workplace Location and the Quality of Work: The Case of Urban-Based Workers in the Uk". Urban Studies, 58(11), 2233-2257. doi: https://doi.org/10.1177/0042098020911887.
•  Yang,  E.,  Bisson,  C., et al. (2019). "Coworking Space as a Third-Fourth Place: Changing Models of a Hybrid Space in Corporate Real Estate". Journal of Corporate Real Estate, 21(4), 324-345. doi: https://doi.org/10.1108/JCRE-12-2018-0051.