Determinants of Shared Workspace Selection by User Attributes in Seoul: Regional, Business and Industrial Type^*

The nature of work is changing with the workplace. These changes offer incredible potential for economic, social, cultural, and environmental progress in the coming years. While various forms of shared workspace have been around for decades, the idea of shared workspace as a unique field of practice is more recent, and the past few years have seen a dramatic rise in the number of shared workspaces and in the interconnections among them(Zhai, 2017). As the global shared workspace trend is expected to continue indefinitely but the competition will more cutthroat at the same time, the industries providing and managing shared workspace are seeking changes to enhance the sustainability of its business model.

This study will explore the factors contributing to determination of shared workspace selection and perform the specific analysis of those factors based on survey by shared workspace user attributes. Accordingly, this study is to provide insights and resources to shared workspace operators for a practical business strategy and developers for optimal planning for shared workspace development project by embracing the needs and expectations of the current shared workspace industry.

In order to identify the factors affecting the selection decision of shared workspace and analyze their weights, this study implemented the Fuzzy system and Analytic Hierarchic Process(AHP) methodologies in accordance with relative pairwise and absolute comparison. Data collection for this analysis has performed based on the questionnaire survey.

The spatial scope for the survey was in line with the general survey of normal workspaces and shared workspaces located in Seoul. Survey respondents were total 153 with composition of approximately 50% of users who are working in shared workspaces and other 50% individuals who are not using shared workspaces but work in various types of offices and businesses. It was distributed to various layers with intention to utilize this research for various purposes. The analysis was summarized based on the responses of the survey and interpretation of meaning through in depth discussion with experts.

This study is developed as follows. First, the major determinants of the shared workspaces were derived through theoretical review, previous researches, newspaper articles, field observation of shared workspaces and case study. Second, the preliminary questionnaire items were developed through discussion and interviews with the research expert group composed of the working professionals of operators and users of shared workspaces. Third, surveys were conducted on office workers who are currently working in the shared workspaces or those who are potential users in the future. Fourth, the relative importance of the upper and lower hierarchy for the shared workspace selection were derived by the Fuzzy and AHP analysis techniques. Fifth, the results of this study are presented together with limitation and future challenges.

The shared workspace is a working environment, shared by professionals with similar community values, who work independently as well as collaboratively. The shared workspaces for more established businesses as well as enterprises with more equipped professional work environment and flexible offices are a little bit different from coworking spaces for start-up businesses and entrepreneurs with casual setting.

At a shared workspace, workers can rent a workspace equipped with all the necessary technologies, and also use other additional services which are commonly available at such spaces. As a way of independent work, the shared workspace has great impact on the changes of the labor market since it encourages other opportunities for independent flexible creative work. It accommodates new working ways such as remote working and flexi-time, also facilitates knowledge sharing, the most important components of knowledge economy(Soerjoatmodjo et al., 2015). Demand for shared workspace has been driven by the growth of creative and tech industries as well as the changing nature of work. Mobile technologies and personal devices have made working remotely from a variety of locations much easier. While this has fuelled the growth in home working, companies and their employees increasingly see the value of being part of a collaborative environment which is at the core value of coworking(Gandini, 2015).

A recent study by CBRE indicated that commercial real estate departments across large corporations will utilize more flexible office space over the coming years. Currently, 44% of corporations are already using some form of flexible office solution. According to the CBRE survey results, this number is expected to rise to 65% by 2020 in America.

In Korea, shared workspace business has been rapid expansion past a few years since the IMF bailout crisis in 1997, a major trigger on the emergence of shared workspace business. The rapid growth of flexible office space, especially shared workspaces, in Seoul is being driven by fundamental shifts in technology, the economy and corporate behaviour(CBRE 2018).

In order to examine the shared workspace business, the various prior literatures on the direction of business strategy and the correlation of influential factors have been examined.

Based on the review of prior studies, this study differs in the following aspects. Though shared workspace business has been growing and positioning well as a category of office option for past a few years, it is hard to find researches that analyzed the importance of major determinants for shared workspace selection based on the expectations or preference from shared workspaces users or potential users groups in contrast with others which focused and analyzed on the spaces and services components of shared workspaces.

This study will introduce different aspects of shared workspace users upon respondent characteristics and analyze the importance of the major determinants of shared workspace selection. Moreover by analyzing correlations between major determinants and respondents characteristics, it will benefit to shared workspace providers to develop realistic strategies for their future business success based on this importance analysis.

In order to identify the determinants that influence the decision to enter the shared workspace, the hierarchical structure of four upper hierarchy: ‘Location Condition’, ‘Business Environment’, ‘Qualitative Value’ and ‘Economic Feasibility’, and associated three lower hierarchy in each upper hierarchy are respectively classified as shown in <Table 2> through brainstorming of the expert group based on the prior studies.

In this study, AHP(Analytic Hierarchy Process) and fuzzy theory have been implemented to quantify the importance of shared office determinants. The AHP is a general theory of measurement, which is used to derive ratio scales from both discrete and continuous paired comparisons(Satty, 1980). Based on subjective pairwise comparisons of each evaluation, it cam lead that the individual attribute of evaluation items. The fuzzy theory proposed by Lofti A. Zadeh is based on the intuitive reasoning by taking into account the human subjectivity and imprecision. It is not an imprecise theory but a rigorous mathematical theory which deals with subjectivity and/or uncertainty which are common in the natural language. The natural language is a very complicated structure which is fundamental, not only in the human communication, but also in the way human beings think and perceive the surrounding world. And the fuzzy theory can capture the vagueness of the human thinking and express it with appropriate mathematical tools based on the intuitive reasoning by taking into account the human subjectivity and imprecision. So it can provide a mathematical power for the emulation of the higher order cognitive functions, the thought and perception(Werro, 2015).

As the shared workspace decision in business requires more objective judgement than subjective in decision making process, it is necessary to complement not only the comparison by pair comparison but also the individual attributes possessed by the evaluation item through an absolute measurement index. Accordingly, the fuzzy theory is applied based on the results of AHP analysis to quantify the importance of shared office determinants by Sugeno fuzzy inference system.¹⁾

To determine the weights of shared workspace components, survey was distributed to the current users and potential users of the shared workspace. The general information of survey respondents are as follows:

The weights of determinants for shared space selection are developed in a hierarchy of upper and lower components by the AHP and Fuzzy analysis as shown in <Table 4>.

In upper categories, the ‘Location condition’ is identified as the most important factor for shared workspace selection followed by ‘Economic feasibility’, ‘Business environment’ and ‘Qualitative value’ in order. In lower categories, it is found that the ‘Public transportation’ is the most important determinant of shared workspace selection. And ‘Employee benefits’ which stands for good services and work environment ranked as 2nd important determinant, followed by ‘Cost benefit for expansion’, ‘Operational cost saving’, and ‘Flexible rental condition’ as top five determinants. It is noteworthy that the most primary criteria for office selection are mainly for not only shared office but also general real estate decision.

The relative importance of the upper and lower hierarchy components by business type are determined. In order to show the analyzed results by all business types in one table, the business type of ‘Start-up’ is displayed as A1, ‘Freelancer’ as A2, ‘Small and medium company’ as A3, ‘Foreign company’ as A4, and ‘Large Korean company’ as A5 respectively in <Table 5>.

In upper categories, the ‘Location condition’ is identified as the most important factor in general and ‘Economic feasibility’ is the second. However, for ‘Start-up,’ the ‘Business environment’ and ‘Qualitative value’ are higher than ‘Economic feasibility’ and for other business types such as ‘Small and medium company’, ‘Foreign company’ and ‘Large Korean company’, the ‘Qualitative value’ are turned out to be the least important components. The relative importance of the lower hierarchy components by business type are aligned to upper hierarchy rank but shows more details. It is noted that ‘Public transportation’ is the absolutely important component and ‘Creating healthy culture’ is the least important component based on the results sorted by business type.

The analyzed results of by all job areas as functions are displayed as follows: ‘Operations’ as B1, ‘Finance’ as B2, ‘Human resource’ as B3, ‘Marketing’ as B4, and ‘Sales’ as B5 respectively in <Table 6>.

The relative importance of the upper hierarchy components by job area is as follows. The ‘Location condition’ is the most important determinant for ‘Operation’, ‘HR’ and ‘Marketing,’ while for ‘Finance’ and ‘Sales’, ‘Economic feasibility’ is the most important determinant which is considered resonable in general functional perception. It is notable that between ‘Business environment’ and ‘Qualitative value’, the ‘Operation’ and ‘HR’ functions rated ‘Qualitative value’ higher than ‘Business environment’ and the other functions rated ‘Business environment’ higher than ‘Qualitative value.’

As a result of the relative importance of the lower hierarchy components by job area, regardless functions, ‘Public transportation’ is the most important determinant, and then ‘Operational cost saving’ and ‘Flexible rental condition.’ From the analysis of the survey characteristics job area, ‘Operation’ was the highest(43.1%) among respondent group, therefore the final result was possibly biased by operation point of view, which is the location as the most important determinant followed by ‘Economic feasibility’, ‘Qualitative value’ and ‘Business environmen’.

In order to show all analyzed results by industry types, the ‘Finance’, ‘IT technologies’, ‘Medical health’, and ‘Fashion and beauty’ industries are displayed as C1, C2, C3, C4 in <Table 7>. The relative importance of the upper hierarchy components by industry type indicates that the ‘Location condition’ is most important and then ‘Economic feasibility,’ ‘Business environment’ and ‘Qualitative value.’ It is especially interesting finding that from ‘Fashion’ and beauty’ industry, they rated ‘Location condition’ extremely important than other components likely over 50% than the other three.

The relative importance of the lower hierarchy components by industry type was aligned to upper hierarchy rank but shows more details. The ‘Public transportation’ and ‘Operational cost saving’ are important top two components here as well and ‘Improving company reputation’ and ‘Creating healthy culture’ were relatively less important components based on the data from industry type.

The relative importance of the upper hierarchy components by office location are as follows. CBD and GBD workers rated ‘Location condition’ as the most important component, however YBD workers rated ‘Economic feasibility’ as the most important component and the importance is very distinctive from other areas. It is noteworthy that YBD workers rated ‘Location condition’ as third important determinants which informs they don’t mind location as much as other locations.

The relative importance of the lower hierarchy components by office location was aligned to upper hierarchy rank but showed more details. The ‘Public transportation’ and ‘Operational cost saving’ are the most important top two components here and ‘Improving company reputation’ and ‘Creating healthy culture’ are relatively less important but ‘Employee benefit’ and ‘Attracting investors and clients’ ware fairly important components based on the data from office location.

The relative importance of the upper hierarchy components by office type are as follows. Both shared workspace workers and general office workers rated ‘Location condition’ as the most important components and ‘Economic feasibility’ as second for office selection. On the other hand, for shared workspace workers rated ‘Qualitative value’ as the least important component but for general office workers rated as second important component.

The relative importance of the lower hierarchy components by office type were aligned to upper hierarchy rank but shows more details. The ‘Public transportation’ and ‘Operational cost saving’ are important top two components here and ‘Improving company reputation’ and ‘Creating healthy culture’ are less important components but between the lower hierarchy of ‘Qualitative value’, employee benefit was considered as the most important component.

This study explored the importance of the major determinants for shared workspace selection based on an analysis of survey conducted in accordance with respondents’ characteristics from shared workspace users and potential users. The conclusion from this study is as follows.

First, the major determinants of shared workspace selection are determined through previous research review and in-depth interviews of professionals who are in charge of office selection and operation. To form a framework for the analysis, the determinants are identified into four major components : ‘Location condition’, ‘Business environment’, ‘Qualitative value’ and ‘Economic feasibility’ as upper hierarchy components with three sub-components as lower hierarchy components. In order to obtain a meaningful conclusion of the study, the respondents are intentionally composed of approximately 50:50 of the current and potential shared workspace users from different background such as business type, industry type and office type, etc. The survey was conducted with the questionnaires for AHP and Fuzzy analysis. Unlike previous researches which were focused on the analysis of the importance of the shared workspace components from mainly shared workspace users, it is meaningful to analyze the major determinants of the shared workspace as a category of the office selection.

Second, as a result of analyzing the general questionnaires, the following conclusions are drawn according to characteristics of office location and type and characteristics of respondents based on shared workspace user group. Given that the office location are divided into CBD, GBD and YBD, based on their current office location, their preference for GBD is the highest, followed by CBD and YBD. And the data shows some of the people working at the CBD or YBD consider moving their offices to the GBD in the future. In terms of office type, the proportion of general office is higher than shared workspace in CBD and the shared workspace users prefer to work at shared workspace and in GBD the most.

Third, as a result of analyzing the characteristics of shared workspace users, majority users are pretty young under 35 and work experiences vary. From the correlations of age, work experience and business type, many young graduates start their careers in startups or as a freelancer in shared workspaces. From the industry perspectives, most of shared workspace users are pretty diverse in general but relatively unconventional industries such as IT, art or leisure and travel companies.

Fourth, as a result of analyzing the upper hierarchy, it is concluded that the ‘Economic feasibility’ is the most important determinants, followed by the ‘Location condition’, ‘Qualitative value’ and the ‘Business environment.’ The noteworthy is the importance between the four determinants is not so significant and especially the ‘Qualitative value’ is fairly close to the other top two determinants including the least determinant ‘Business environment.’ This mean that the four components are almost equally important for shared workspace selection and it is aligned to the other upper hierarchy components analysis in different areas such as business type, job area, industry type, office location and office type, etc.

Finally, the analysis of importance of lower hierarchy components accurately shows the importance and correlation of the upper hierarchy components. The most important components among the 12 lower hierarchy components is ‘Public transportation’ and the least important component is ‘Improving company reputation.’ The lower hierarchy components analyzed by areas are divided into business type, industry type, job area, office location and office type. The importance of ‘Public transportation’ was the most important factor for all the areas and the second was ‘Operating cost saving.’ Unlike CBD and GBD, YBD workers consider ‘Operating cost saving’ as the most important determinant of shared workspace selection. Especially, it is most noteworthy that the ‘Business environment’ and ‘Qualitative value’ were not strongly introduced in the past and not considered as important determinants in traditional office market. However, this study revealed that they are becoming as important as the other two key traditional determinants now and will be more important in the future with needs and expectations.

The shared workspace is growing rapidly in the office market due to the social environment change as well as the growth of the sharing economy. This study intends to give insights and resources for shared workspace strategies to help shared workspace operators be able to more readily facilitate and succeed, and shared workspace providers be able to embrace rapid demand and expectation and build competitive strategies which foster the four key determinants and associated sub determinants in a good balance for their business success. It is expected to provide the guide for the practical real estate strategy so that the shared workspace industry can solidify itself as a viable, sustainable segment of the future office market in Seoul.

This study has the following limitations and future study expected accordingly. Most of all, this study is geographically limited to Seoul city. And in terms of surveying, in order to keep consistency and extract the meaningful data, quite a lot of responses were discarded due to the inconsistency, which could require the more accurate results with more valid responses in the future. And this study was originally planned to compose approximately 50:50 ratio of the shared workspace users and potential users. However, due to the consistency check for valid analysis, more number from non-shared workspace users were considered, which might lead the result to be biased. And also the respondents of the shared workspace users were very limited to large scale of shared workspaces not covering various forms of the shared workspaces such as business center, startup support centers, small and medium shared workspaces etc. Accordingly, in terms of diversity this study might be insufficient.