Market Research
A study on experience levels in co-working spaces – gauging for Service Quality by applying the Reverse Thinking Approach.
Max Lindner – 10621423, Bsc Thesis Eco Business Adminstration; 2015/2016
ABSTRACT
The present study seeks to define good, bad, great and respectively room for improvement performance of service quality in the co-working market. Adopting an occupier’s perspective, 30 co-working spaces and 20 online market places have been investigated on the basis of the “Reverse Thinking Approach”. The present qualitative structure allows making sense of large parts of industry information, which ultimately have been processed from open to axial and finally selective coding. Additionally, relationships between experience influencers were assessed on the basis of the Kendall’s tau-b correlation efficient, which was found to be very suitable for analysis of small sample sizes. Importantly, the present study presents a three-point performance grid that helps to gauge for customer experience levels. As a result, significant relationships in working environment, setup of place, transparency and collaboration have been demonstrated.
Supervisor: Dr. Ing. Meulemanns Word count: 15000
Statement of Originality
This document is written by Student Max Lindner who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
Table of Contents
1. Introduction ... 4
2. Theoretical Framework ... 6
2.1 The Reverse Thinking approach – A conceptual model ... 6
2.2 Independent variable: Customer Experience – A subjective experience ... 7
2.3 Measuring Service Quality (experience) ... 8
2.4 (Creative) Working environment ... 10
2.5 Co-working ... 12 2.6 Co-working Spaces ... 13 3. Research Design ... 15 4. Methodology ... 16 5. The Results ... 21 5.1 Sample ... 21
5.2 Results market data ... 21
5.2.1 Open-coding ... 22
5.2.1.1 Table1: Open coding process Market Data ... 22
5.2.2 Performance grid market data ... 27
5.2.3 Axial Coding ... 27
5.2.4 Statistical analysis of market data ... 28
5.2.5 Selective coding process ... 30
5.2.5.1 Table 2: Selective coding model ... 31
5.3 Results distribution data ... 32
5.3.1 Open coding ... 32
5.3.1.1 Table 3: Open coding process Distribution Data ... 32
5.3.2 Performance grid distribution data ... 36
5.3.2.1 Table 4: Performance Grid Distribution Data ... 36
5.3.3 Axial coding ... 38
5.3.4 Table 5: Selective code model Distribution Data ... 40
6. Discussion ... 41 6.1 Summary ... 41 6.1.1 Key findings ... 41 6.2 Discussion points ... 42 6.3 Positive points ... 43 6.4 Practical Implications ... 44 7. Conclusion ... 45 8. Bibliography ... 46 9. Appendix ... 51
1. Introduction
Co-working spaces are open plan offices that independent knowledge workers, who tend to be mobile, share as places of work (Waters-Lynch, Potts, Butcher, Dodson & Hurley, 2016). Recent developments in technology, connectivity and global integration of markets, show the general trend of work becoming increasingly less contingent on location, fixed work times and space (Kyrö & Artto, 2015). Still, employee’s cooperation and cross sharing of information and their competencies are key to future growth of a company (Bhalla, 2011). As a result, co-working spaces are becoming more and more popular all around the world. Working alone together is a complex social phenomenon, which is more than access to space and facilities, but is defined as (Spinuzzi, 2012).
Recently, research on co-working, respectively co-creation, has been very popular (McElroy & Morrow, 2010). Over the last few years and decades, co-working has progressed to a well-established field of research, focusing on a diverse range of social, environmental, technological and historical factors. As seen in Figure 1 in the Appendix co-working has never been more popular and trending than nowadays. Here, the horizontal axis represents the time (starting from 2004) and the vertical axis shows how many Google searches exist for the specific term co-working, relative to the total number of searches, globally. While there is a small peak in November 2004 with 25 out of 100 points, a steady increase is demonstrated over the years until now, reaching the 100-point maximum. Hence, co-working is very trending at this specific moment.
Now, consider this practical example: a recently founded Internet start-up is looking for a way to stimulate collaboration and co-working of its geographically dispersed employees. Currently, these colleagues hardly see each other and only correspond via common communication tools. The manager dislikes classic conference spaces provided by hotels because in his belief they are out-dated and tedious and therefore just not what they are looking for. To bring people together, the executives are now facing two options: rent a traditional single-occupancy office property, or implement a virtual platform, such as Intranets or Customer Relationship Management programs.
Physical offices present immediate advantages of direct interaction. Still, those are not only associated with a relatively high cost of rent, they are also inflexible and significantly formal in nature (Van Meel & Brinkø, 2014). On the other hand, employees who communicate with their colleagues mostly virtually, often lack a sense of community, due to meagre unstructured social contact with their co-workers (Johns & Gratton, 2013). Nevertheless, virtual tools like videoconferencing can be very helpful in daily work life, making employees more mobile (Kojo & Nenonen, 2014). Lumley (2013) states that the economy becomes increasingly knowledge driven. Thus, competencies such as critical
thinking, problem solving, creativity, communication and collaboration cannot fully be incorporated without learning them through social interaction and learning (Bilandzic & Foth, 2013). Still, Johns & Gratton (2013) classify direct consequences of virtual co-working to be decreased team unity and ultimately individual loneliness of the employee.
Henceforth, the company has to look out for other options that can best facilitate a rich collaboration of their employees. In the public eye, co-working establishments are mostly seen as places where geeks and nerds come together to work on a start-up idea. However, it is uncertain what advantages and respectively disadvantages flexible multi-purpose office spaces offer for the average man of business. Thus, a co-working space will probably not be the first and most preferred option by an average businesswoman or man.
Although, there are a lot of spaces already established which primarily focus on co-working, they are very diverse in their nature and show regional differences. According to Parasuraman, Zeithaml and Berry (1990) customers compare their expectations of experience with the likelihood of actual performance. Therefore, dissimilarity in product offerings and what is being promised lead to distraction of consumers when making a rational decision. In practice, this makes it difficult to compare and identify key success factors of the co-working market, and practically impossible to generalize for the whole population of co-working spaces. However, valuable insights on general market conduct can help to fill the gap between expectation of experience quality and what is actually being delivered from individual respondents.
Therefore, this paper will aim to investigate good, bad and great co-working market performance in and around Amsterdam, which should help to assess universal consumer experience. Using the Reverse Thinking approach will allow identify key characteristics of experience influencers, ultimately leading to a definition of optimal customer experience.
Hence, the scientific value of the present paper is to define market behaviour on the basis of Reverse Thinking, when conducting a market-, distribution- and pricing analysis to find out how the co-working market is actually performing
In order to fully understand the co-working industry the present paper repeatedly questions: “What do customers want?”
This leads to my Research Question (RQ): to what extent, can Reverse Thinking be applied in the design, distribution, pricing and selling of experience-based theme rooms?
2. Theoretical Framework
2.1 The Reverse Thinking Approach – A conceptual model
What is Reverse Thinking? – to put it simply: the Reverse Thinking approach is a learning- and development approach which helps (re)shape the landscape of customer experience (Performance Solutions, 2016, 5). In an increasingly changing business environment goods and services become more and more commoditized. As a result, corporations are facing difficulties to implement or endure a successful market position. In order to distinctively differentiate from market competitors, the managing partner of Performance Solutions, André Wiringa, inaugurated the Reverse Thinking model. He envisioned the model to separate the company’s business strategy from others by creating a revolutionary new customer approach, where individuals interact, learn and lead unconventionally (Performance Solutions, 2016, 2).
Why reverse? To answer this question I would like to propose a seemingly simple question: Why are some companies, or individuals, more innovative, more creative, more influential, and eventually more profitable than others?
According to Simon Sinek and his “Golden Circle” (2010) all great leaders and successful organizations operate and communicate in the same way. Namely, they clarify the following: “What is your purpose? What is your cause? What is your belief? Why does your organization exist? Why do you get out of bed in the morning? - And why should anyone care?” (Sinek, 2010).
Most of individuals, and all of the organizations, know what they do by focusing on the content, meaning looking at data, information and results. Further, the majority of individuals question themselves “how do we do things” by examining the company’s processes such as standards, procedures, systems and/or competencies (Sinek, 2010). If the company is reflective they also have a look on the differentiated value proposition. However, very few organizations, and likewise individuals, know Why they do what they do. Nonetheless, why cannot be simply answered by making a profit, because this is an outcome. Instead, according to Simon Sinek (2010), the reason for why companies do what they do needs to focus on the context of things. Namely, the context of organizations and people is their surroundings, reason for being, identity values and their experience.
Henceforth, the great majority of company is primarily busy with looking at the having or doing side of things. This means that they look at their organizations from an outside-in perspective. However, companies do best by thinking, acting and communicating from the inside out. Therefore, Reverse Thinking and questioning “why do we do things” will help to close the gap between what marketing promises and the actual service delivery that is expected.
So how does reverse thinking work, and how can it be effectively implemented in conducting market research on co-working spaces? Importantly, when thinking reverse we deliberately take ‘why’ and ‘who’ combined as starting point. The basic idea of the reverse approach is to clearly articulate why the organisation exists, beyond its products or services. Hence, analysis of who and why organisations exist should deliver effective reasoning on what they stand for and who individual companies represents in their level service quality.
Thereafter, the aspiration is to use the definition of the company’s purpose for existence to formulate identity, as well as the method to ‘create’ ultimate customer experience (Performance Solutions, 2016, 6). Here, reverse thinking aims to brand the desired experience, develop and implement it, and ultimately make it grow into a desired culture within the specific market. Though this is aspirational for the present paper
Reverse Thinking offers the opportunity to contribute to consistent and genuine experiences, ultimately leading to a community of raving fans (Performance Solutions, 2016, 3). Henceforth, Reverse Thinking will help the author to accurately gauge customer experience by answering the following questions: Why?, Who?, What?, How?.
In order to answer this I will add two sub-questions to my Research Question namely: 1) What is Reverse Thinking? – how can it be used for analysing the price/ market proposition; 2) In what ways can conference/ meeting spaces be re-designed around ultimate customer experience?
2.2 Independent variable: Customer experience – a subjective experience
Although, customer experience is a well-established and important source of competitive advantage, research is still scarce on the rewards and benefits that a focus on customer experience brings (Teixeira, Patrício, Nunes, Nóbrega, Fisk & Constantine, 2012). Due to the complexity and richness of individual customer experiences it is difficult to accurately incorporate changes in the service design.
Holbrok and Hirschman (1982) have been one of the first who recognized customers to work as rational decision makers and therefore apprehended the experiential and original concept of Customer Experience.
Customer experience is defined as the internal and subjective response, which customers have to any direct or indirect contact with an organization. According Gentile, Spiller and Noci (2007, p.397) “customer experience originates from a set of interactions between a customer and a product, a company, or part of its organization, which provoke a reaction. This experience is strictly personal and implies the customer’s involvement at different levels (rational, emotional, sensorial physical and spiritual”. In an evaluation
process, the customer contrasts his or her expectations with the stimuli received from the interaction with the company and their offerings (Gentile et al, 2007).
Following, customer experience is not designed by individual companies. Instead, it is co-created through customer interactions with various service elements across different touchpoints along the customer journey (Teixeira et al, 2012). According to Lemke, Clark and Wilson (2011) individuals note customer experience quality on the basis to its fair value. Hence customers judge good experience as superior or excellent performance. Therefore, implementing changes on the basis of customer experiences depends on grasping rich information across all customer interactions with the provider of goods and services.
2.3 Measuring Service Quality (experience)
Service quality measures compare customer’s expectations about a service with its actual performance (Parasuraman et al., 1991). For both researchers and corporations the measurement of experienced quality has long been a central issue to service quality (Hamer, 2003). When reviewing literature on service quality a variety of different approaches can be found, each one being suitable in given circumstances, with individual strengths and weaknesses.
The most eminent service quality assessment apparatus is the SERVQUAL framework, which was first published in 1977. Parasuraman et al. (1991) define two constructs as the main influencers of service quality: expectations of service quality and those perceptions of consumers on the delivered service. The authors developed the SERVQUAL scale with the primary intention to work as a universal tool to measure service quality on the basis of ten dimensions of quality (Hamer, 2003). The framework, which was later on simplified into RATER, assesses service quality on the basis of tangibles (physical appearance), reliability, responsiveness, assurance, and empathy (Zeithaml, Parasuraman & Berry, 1990, 25). Practically, this model suggests that consumers measure the difference in the performance of received service, against the expected quality of the service.
Realistically, the SERVQUAL scale has been found difficult to implement across different service settings (Babakus & Boller, 1992). Therefore, it failed its universal aim of being adaptive into any particular service background.
In addition, more service quality measurement scales exist such as the SERVPERF scale developed by Cronin and Taylor (1992). Nonetheless, most of the measurement scales, including the SERVPERF framework, are only a re-examination and extension of SERVQUAL. Thus, none of the measurement scales that exist are truly functioning in estimating consumer expectations.
Other than that, standard practice assumes customer expectations to be evaluated as distinct points by their users. In reality, consumers estimate the relative likelihood of a
quality in a distribution like manner, where all the possible performance values of the service will be examined (Rust, Inman, Jia & Zahorik, 1999). Here, it is essential to gauge the uncertainty and risk a consumer is facing with the level of service that he or she will receive. Thus, customers judge for performance of a product or service on the basis of their aggregate experience.
Hence, most of the prevailing assumptions about customer-perceived quality are inaccurate: firstly, it is not mandatory to exceed the expectation of customers to stimulate positive inclination (Rust et al, 1999). Secondly, when a customer receives a level of bad service, which she or he expected beforehand, it does not necessarily reduce preference. Thirdly, customers may still rationally choose an option with lower expected quality, even when all other features of the service or product are the same. Lastly, Rust et al. (1999) stated that it could potentially be inefficient to concentrate on customers that are already loyal and experienced with the product or service.
Recently, a trend emerged towards measuring customer satisfaction not only physically but also digitally, via questionnaires and surveys. An example of how easy customer feedback can be collected is “iFeedback”, where consumers rate their encountered experience on smartphones or iPads. A function like this offers real-time measurement of customer satisfaction, which only takes a few seconds to complete.
Notwithstanding, customer satisfaction measures have been challenged for their predictive ability. Reichheld (1996) argued while customers report perceived quality to be superior and also being highly satisfied with the product, there still might be the case that they switch to buy from a competitor. This can be explained by the unasserted amount of variance that usual customer experience scales usually fail to incorporate.
Finally, the Net Promoter Score (NPS) is a good way to assess the likelihood that the customer will recommend that product/service to others. Reichheld (2003) developed the scale in cooperation with a company based in the Silicon Valley, which specialized in customer experience management. The model’s strength is that, probably more than any other service quality measure, it gives an indication to how important it is for a company to cultivate enthusiastic customers for future growth strategies (Wisskirchen, Vater, Wright, De Backer & Detrick, 2006).
Commonly, companies were spending a lot of time and financial compensation when evaluating customer satisfaction with obscure tools. However, NPS is compromising by its simplicity (Hanson, 2011). Basically, the NPS uses a prevalent question: “Would you recommend this company to a friend?”, on a scale from 0-10. NPS scores are derived from the proportion of promoters (those who rated 9-10) subtracting the proportion of detractors (with the rating 0-6). Therefore, NPS assesses three types of respondent categories: ‘promoters’ (9-10) who would definitely recommend and experience the service again,
‘passives’ (7-8) who are generally happy but would not actively promote the service to friends or colleagues and ‘detractors’ who actively discourage others to make use of the service (Reichheld, 2003).
Today, NPS is widely used in the service industry due to its efforts of continuous improvement of customer experience and the ability to decrease the number of detractors (Hamilton, Lane, Gaston, Patton, MacDonald, Simpson & Howie, 2014). However, it is surprising how many companies who claim to be customer oriented either have no idea of the customer experience around their service, or use ineffective measures (Wylie, 2015). Still, measuring customer experience is not fully authentic but critical to any part of the business. Although, NPS can be blurry sometimes regarding the issue of in increasing the number of promoters respectively minimizing detractors, it is definitely an easy way to gauge for customer experience.
2.4 (Creative) working environment
Ever since the Hawthorne studies from the 1920s, working environments have been recognised as somewhat more than just a physical space (Roethlisberger & Dickson, 1939, 397). While Elton Mayo and Fritz Roethlisberger’s research was initially proposed to assess how satisfying and creative work environments can be constructed, its main findings later on accentuated into repercussion of the behavioural habitat on the efficiency and productivity of the workforce (Haynes, 2007).
However, Steele (1983) expanded research from just physical characteristics towards ecological linkages between space, organisational culture and work arrangements. Following, Bitner’s (1992) ‘servicescape’ framework inaugurated the impact of the physical environment on the behaviour and interaction of both employees and customers within companies who provide services. Here, three environmental dimensions are established which affect the behaviour of incumbents: within the physical surrounding dimension ambient conditions should provide comfort, while individual space and function is characterised by its layout; thirdly, signs, symbols and artefacts are recognised by individuals within the working space (Bitner, 1992). Here, personal artefacts have the ability to stimulate emotions or feelings towards the physical surrounding. Above all, the ‘servicescape’ framework delivers important information on how physical containers, meaning the setting, affect the duration and quality of behavioural patterns and social interactions between and among both customers and employees (Haynes, 2007).
In “Workplace by Design: Mapping the High-Performance Workscape”, Becker and Steele (1995) summarized the advantages of their “Organizational Ecology” concept to able to transform physical workplace surroundings and organizational culture. Practically, seeing
an organization as an ecological preservation should reinforce the businesses processes and ultimately help to support the businesses objectives. To implement organizational ecology a business has to be aware the following three components: decisions about physical setting, accord about processes used to plan and design the workplace system and “decisions about how space, equipment, and furnishings are allocated and used overtime” (Becker & Steele, 1995, p.12)
Traditionally, opinions about offices have been distracted with the physical environment, backing up the above-mentioned line of argumentation (Stallworth & Ward 1996) stated that. In the mean time, this lead to a poor judgment of the social environment and interaction within workplaces. Having acknowledged this, more and more literature has been produced which focused on the interactivity between work setting, behaviour and productivity. However, while Becker (1990) and Becker and Steele (1995) argue for a prescribed allocation of dedicated desks, the concept of temporary workplaces such as ‘hot-desks’ emerged in the late 1990s. These places are characterised by their flexibility and provide co-working areas with flexible work patterns, which do not specify an area for their own use only (Haynes, 2007). However, from an occupier’s perspective, this can be a good way to fulfil an individual’s need of expressing their identity and personality, through the modification and personalization of their workplace environment.
Today’s open office redesign efforts have the implications of a less formal and more innovative working environment. To the point, McElroy and Morrow (2010) stated that office redesign is an effective strategy for implementing organizational change. Specifically, their results demonstrate that employees faced with a modern, new and more open office surrounding show more collaboration than those incumbents working in ordinal workspaces. Furthermore, individuals who enjoy a flexible surrounding show greater empathy towards their co-workers and feel like that they can monitor and solve their own problems (McElroy & Morrow, 2010). This can have the desired effect to change perception of a company’s culture and also employee attitudes. Thus, a higher individual organization commitment and identification with a company might be achieved.
Henceforth, office environments today are not only physical spaces to work in, but can have advantageous characteristics of knowledge creation and transfer. Office design in the “new economy” promise attractive developments where workplaces are transformed into playgrounds and work into play (Van Meel & Vos, 2001). Therefore, a company does best by not only focusing on the efficiency of employees but also consider the desires and needs of employees. Van Meel and Vos (2001) revealed, that following these efforts should help a company to set them apart from ordinary organisations. To sum up, redesigning office space is a good way to implement organisational change, which will ultimately support the creativity of employees.
At this point, it is not far to seek that the working environment will act as a strong influencer of experience. Therefore, I predict that there will be a positive relationship between the dependent variable working environment and experience.
2.5 Co-working
Naturally, co-working is beneficial for networking and also creativity. Advocates of open-plan offices content that it will lead to increased communication within a company and also higher individual satisfaction with working quality (Sundstrom, Burt & Kamp, 1980).
Co-working refers to a group of individuals with heterogeneous backgrounds who come together to work in the same environment, in an attempt of co-localization (Spinuzzi, 2012; Kojo & Nenonen, 2014). Importantly, Bhalla (2011) articulated that co-working, co-creation and collaboration competencies are key essential to customer-driven innovations, which are critical to the imminent growth of a company.
However, McElroy and Morrow’s (2010) findings report that employees assigned to redesigned office workspace are exposed to more distraction than those who remained in an ordinary office compartment. Employee’s attention can be diverted due to ingenious design of workspaces, which mean that employees process more sensory images.
In a study conducted by Stokols, Clitheroe and Zmuidzinaz (2002) occupier viewpoints on the physical and social environment were collected using questionnaires. In a university and organization setting, the authors analysed “environmental distractions” and the “social climate” on the basis of encouragement for creativity, employee satisfaction and individual stress (or delight) ratings on the physical and social environment. According to Stokols et al. (2002) results, increased levels of environmental distraction were correlated to decreased creativity at the workplace. When an individual’s working surroundings has more sensory stimulations than in a plain working container, this might lead to more distraction of employees. However, a redesigned office can also bring about heightened genius and more novel ideas. Still, when a company wants to stimulate interaction within their workforce they have to keep environmental distraction at a minimum (Haynes, 2007).
Therefore, I will predict that there will be a positive relationship between the level of interaction and experience level.
2.6 Co-working spaces
In general, co-working spaces are community-based, inexpensive, convenient, and sustainable (Johns & Gratton, 2013). Similar spaces first emerged in the literature around the 1960s in the form of neighbourhood work centres, which provided shared workspaces and electronic facilities (Kojo & Nenonen, 2014). Since the original aim of those spaces was to shorten the time spent on travelling to work, they would usually be situated within walking distance of workers homes. Over time, technology and computers became more important for everyday work and life, which meant that the need for sharing those ICT facilities became increasingly popular. However, only in the 1990s shared office space started to be connecting to fun activities. Kojo and Nenonen (2014) described hotels in recreational areas to function as resort offices where shared office space was linked to the primary office, allowing for work to be mixed with sports and leisure activities.
However, today, co-working spaces are heavily dissimilar in their amenities, vision, location, ambience and proprietors (Spinuzzi, 2012). Additionally, their customers of business hold opposing views on how they define co-working, which ultimately changes the individual working climate.
The founder of co-working, Brad Neuberg, who is currently a Senior Software Engineer at Dropbox, “invented, started, and evangelized coworking, an international movement focused on collaborative workspaces that combine the freedom and independence of self-employment with the structure and community of traditional jobs” (Neuberg, 2005). Therefore, unlike a traditional office, co-working has been aimed at providing an office of a corporate job, but instead in a distinguishably unique approach (Neuberg, 2005).
Brad Neuberg (2005) established the first co-working space in August 2005 as “Coworking - Community for Developers Who Work From Home”. Neuberg (2005) did so, not in an attempt to make a business out of it, but instead to create the kinds of conditions where he would like to work in, and provide those for others. Still today, the majority of the people have two options: work at home alone, granting an individual independence, or working in an office for a company, providing employees community and structure. However, the freedom to work anywhere and anytime usually implies isolation and failure to build relationships and trust with others, due to the limited opportunities to network and collaborate with others (Spinuzzi, 2012).
Neuberg (2005) stated that habitually, society forces employees to choose between working alone, leading to an individual’s loneliness in the long run, or the latter, working at a normal 9-to-5 job, which harms individual’s freedom and flexibility. This is why, the founder formulated “coworking” as the alternative middle-path strategy, which should solve the
problem freelancers feeling too unstructured working in coffee shops or their homes, or too restrained in a corporate environment. In this way, co-workers can make use of smart people in their working environments to collaborate during normal work hours, and not be tempted to fall into distressing routines like working all night and sleeping through daytime (Neuberg, 2005).
The state-of-the-art co-working spaces of today show very similar key characteristics to the one’s described by its inventor in 2005. Similarly, nowadays co-working spaces show characteristics of membership, flexibility and collaboration. Following, Neuberg (2005) described co-working spaces as those where independent writers, programmers and entrepreneurs come together to set their personal and work intentions and share ideas within the community. Likewise, Kojo and Nenonen (2014) depicted co-working spaces as community spaces where variant groups of people get together in a mutually shared office space with the primary purpose to work on different projects for diverse companies. Although most of the co-workers work separately, importantly, leisure activities are a crucial part of a standard working day. Here, co-workers have lunch together as a group, take breaks together at the ‘watercooler’ or practice healthy activities such as yoga, meditation or taking a bike ride. Thus, “ending our work in a healthy, balanced way at the end of the day every day” (Neuberg, 2005).
Since 2005, co-working grew into a very lucrative business where companies follow the same basic formula as Neuberg has been outlining, such as ‘WeWork’. Those spaces match millennials appetite for alternative, hip and client pleasing facilities, which also foster collaboration. Generally, these offices feature private offices and additionally open communal workspaces. However, collaboration between members does not automatically strive, but instead does not happen unless someone handles everything around it.
Nowadays, online market places are already quite experienced in offering meeting rooms, respectively co-working spaces, online. This does not only lead to increased competition between individual venues, but also will increase the transparency of the co-working market. Therefore, I will predict that the use of distribution channels will lead to a more transparent market structure.
3. Research Design
Since this research is undertaken in an organizational setting, as part of Thesis Internship, it is quite clear I will follow an action research strategy. Hence, the purpose of this research will be research in action rather than research about action. This means that the present paper will describe an applied research to solve a real organizational problem. Here, the emergent and iterative process of inquiry is diagnosing, planning, taking action and evaluating. The following will have implications beyond the immediate project, by making use of different forms of knowledge. Thus, the results will not only have implications for the organization but also the informing other contexts, in this case the whole co-working industry.
As described above, co-working is universally relevant and its drivers and implications are very subjectivist in their nature. Since I am aiming to cover the whole market of co-working in and around Amsterdam it is difficult to estimate and clarify all the different variables before analysing and evaluating all the market data. Therefore, this research is aiming to identify those variables that show dependency on the independent variable customer experience.
However, according to Teixeira et al. (2012) the most relevant service functions when talking about customer experience are: Affordability, Engagement, Content, Convenience, Reliability, Reward and Speed.
Thus, I will investigate the generic market of co-working by examining the positive and negative aspects towards customer experience. The present paper adopts a subjectivist approach by holding assumptions about the way in which the world works. This means that social phenomena are created from the perceptions and consequent actions of those social actors concerned with their existence.
4. Methodology
In the last few years and decades a lot of research has been conducted on various aspects of co-working, ranging from psychological factors involved while working with others to optimal design of workspace. However, meeting places, or more in general: spaces where people co-work, are very diverse in nature, and over time, have seen great change. Therefore, the present paper will adopt a revolutionary approach, namely reverse: aiming to define a memorable and unique customer experience.
The objective of the present paper is to add insight knowledge for researchers and potentially come up with new product ideas for Performance Solutions. This inductive research will be undertaken by analysis and evaluation of current performance of major players on the co-working market. Similar to Simon Sinek (2010), who analysed influential persons and organizations such as Martin Luther King, Apple, and the Wright Brother, I will codify messages and performance behaviour of co-working entities. Using the Reverse Thinking Model will assist me to gauge what constitutes good-, bad- and respectively great performance.
One of the main propositions of the Reverse Thinking model is “context is decisive” (Performance Solutions, 2016, 1). To estimate conduct, classic performance measures are usually related to output. However, reverse thinking defines good performance as a practice of consistently delivering memorable experience. This is why I will repeatedly ask the following questions while assessing individual performance: “Why – what is your purpose?”; “Who – what is the desired identity?”; “ “How – does an organisation deliver services?”; “What – is the essence of what is being delivered?”. While ‘Why’ and ‘Who’ are intending to answer the question of what the lifeblood of an organisation looks like, ‘How’ is derived from asking ‘Who’ and ‘Why’ and incorporates the actions an organisation takes to fulfil the purpose. Subsequently, ‘What’ provides content by distinguishing between the conjunction of desired and actual experiences. Naturally, when a company does a good job at communicating these basic competencies they will be classified as performing well, since this will allow for a distinguishing customer experience. However, if a co-working space is not delivering a fair and honest service, they will hence have an unclear mission statement, and ultimately their performance will be classified as insufficient.
Clearly, this applied research is exploratory and subsequently I will choose a qualitative research structure, which is aimed at the use of knowledge to change or improve situations. Therefore, I will follow an inductive approach where the social phenomenon of co-working is explored in terms of good-, respectively bad-practice, and also identifying room for improvement. Those data are generated in order to find empirical patterns that can function as the beginning of theory.
The purpose of Qualitative methods is to look for the meaning people apply to events, situations, actions, and importantly experiences, by producing rich descriptive data. When doing market research, Kotler and Keller (2012) recommended qualitative methods for identifying new product ideas in order to gauge customer opinion. Due to its indirect nature, qualitative research can be more effective to get insights about customer perceptions, since consumer actions and beliefs do not always match survey question answers.
Qualitative research allows using flexible research methods to understand the particular context in which this phenomenon takes place. The goal of the present paper is to predict and explain market behaviour, whilst aiming to develop and build theory. Henceforth, the use of a Grounded Theory research strategy allows to generate and explain a theory around the central theme emerging from the data (Saunders, Lewis & Thornhill, 2009). Another great value of this qualitative research is that it allows understanding how meanings are formed and negotiated around phenomena, which ultimately should help to identify all unanticipated influences. Consequently, a qualitative nature of this research fits well with the Reverse Thinking model described above.
Being exploratory and inductive in nature, the data collection of the present paper follows a non-probability sampling technique. This basically means that the sample is being selected on the basis of the subjective judgement of the researcher. While this might seem inferior to a random selection of participants, when following a qualitative research design, purposive sampling provides the author with robust theoretical reasons for choosing individual cases. Drawing on academic literature, practice and initial advice of my company supervisor, a sample of 30 co-working spaces and 20 distribution channels was generated. Every participant of this sample was chosen with a specific purpose, namely, to accurately reflect the co-working market, in and around Amsterdam, as a whole.
While analysing and evaluating those 30 different product offerings, the author used a standard number of people and typical time range, meaning 9 a.m. – 5 p.m. In order to achieve the greatest comparability of individual offerings, the given time frame resembles an average full working day, and prices were compared for twelve respectively 30 people. According to internal knowledge, these participant numbers demonstrate the two most common group sizes when booking meeting spaces.
Further, a great effort was made to collect data in a standardized manner. The companies’ product offerings were collected and classified in the following three columns: “Name / Key characteristics”, “Prices” and “Extras”; in the same order. Following this type of data collection should grant a clear overview of information. Firstly, while doing Internet research, the individual’s key characteristics, meaning its value proposition and/or mission were examined. Time after time, I asked the following questions: ‘Why are participants doing what they are doing?’; ‘Who are the players?’; ‘How do they deliver services?’ and lastly
‘What is being delivered?’. Secondly, most of the meeting spaces’ pricing information were easily found on their website or as a pdf leaflet. However, if prices were not readily available on the individual website, a pricing request was sent out via Email with the same requirements as described above. Thirdly, individual product offering was scanned for peculiarities, which were then put into the “Extras” column for later analysis. Here, I examined the inclusivity, transparency, distribution, transport and service of the participants. In addition, I visited a selection of co-working spaces during company visits (Hyatt Place, The Thinking Hut, Holiday Inn, Crowne Plaza, Radisson Blu, Fletcher Hotel, A Lab, Spaces Zuidas, WeWork, Impact Hub) where in-depth information was contributed to the data set. In practice, following this exact form of data collection made it easier to look for patterns in the data, allowing the researcher to capture all necessary details of the co-working market.
After having started to collect market data on product offerings I continued with focusing on the second part of the present paper: distribution. Similarly, I analysed the main distribution channels in three distinct columns. First, in the “Name/ Key characteristics” column, the most important information about individual distribution channels was made easily visible. Here, information was added such as available languages, key quotations, or also if and how much commission they charge for renting out your meeting rooms. Secondly, the ”Clients” of individual distribution channels were investigated simply by looking into their database. Although I mostly concentrated on those distribution channels identified before, this was a very effective way to identify even more co-working spaces, fitting to my data set. Third, I studied the performance and value proposition of individual distribution channels, which mostly contained specific characteristics put into the “Extras” column. Hitherto, factors were investigated such as: search engine, map function and the advertisement of offerings.
The qualitative data of the present paper is analysed using coding. Basically, coding means classifying segments of data with short names (Boeije, 2010). At the same time, those names summarize and explain each for each piece of data. Boeije (2010) stated that using coding as the main research instrument allows the author to move beyond concrete statements in the data and induce cogent interpretations. Consequently, Saunders et al. (2009) stated that coding is the most efficient way of analysing qualitative data. There are three types of coding, which should be completed in the following order: open coding, axial coding and selective coding (Saunders et al., 2009).
Beginning with the explorative step of open coding, this is defined as the “process of breaking down, examining, comparing, conceptualizing and categorizing data” (Corbin & Strauss, 2015, p.220). In a process of reading and re-reading market data is disaggregated into fragments and provided with a label for each unit. Consequently, all units that are conceptually similar will be given the same label. Thus, this step gives evidence to delineate
subcategory fragments into “Good practice”, “Bad practice” and “Great/ Room for Improvement”. Hence, this step contributes to a clear organization of the data (Boeije, 2010). As a second step, axial coding refers to the process of looking for linkages between the categories of data emerged from open coding. Here, fragments assigned to a certain code are retrieved and compared, and subsequently put back together in new ways by recognizing relationships between categories (Boeije, 2010). Specifically, this means comparing similarities and differences in the dimensions of categories, whereby subcategories emerge. The prime purpose of this step is to reduce and reorganize the data set. In practice, performance is analysed by determining which elements in the market show good performance, which subcategories are thought to be demonstrate a less successful performance, and finally, which individual behaviour is assessed to show superior performance, respectively, what can still be improved.
Finally, during selective coding relationships between principal concepts are identified to make sense of what is happening in the field. The purpose of this step is to relate fragments to the core category, with the intention of integrating the research and developing a Grounded Theory (Saunders et al., 2009, p. 511). This step is intended to assist the author when answering the research question, by reassembling the data, and ultimately it should help to realise the research aim. Boeije (2010) stated that, here position findings are verified by comparing those with the existing literature, while thinking about answers for the research question and drawing conclusions. Similar to reverse thinking, answering the questions of “What is important for the description (What) and the understanding (Why) of the participant’s perspective and behaviour?” should help to understand how the pieces of data fit together (Boeije, 2010, p.116).
Essentially, I probed the effectiveness of the research strategy coding by starting with open coding of distribution data. After splitting up open data fragments and pairing those which are conceptually similar I went on to Axial coding. Here, I compared similarities and differences between those subcategory fragments and delineated performance into “Good”, “Bad” and “Great/Room for Improvement”. For example, “Easy Search Function” works as a axial code for good performance, while “INtransparent search” demonstrate bad performance and “Transparent search” stands for room for improvement, respectively great performance. Another example in the same order is “Network range”, “Thinking national” and finally “Grow your community”. Third, principal concepts have been identified to make sense of what is happening in the field.
After running a coding research strategy for distribution data I gained a lot of insightful experience, which led me to refine and modify some of my coding procedure. First of all, this knowledge assisted me in looking for key themes in the data, but also I learned how to effectively reorganize the information. Additionally, I picked up that jumping
backwards and forwards between data collection, data analysis and sampling, allows testing for accuracy of propositions about connections between certain phenomena (Boeije, 2010). Therefore, I learned how to effectively undertake coding and move beyond concrete statements and induce cogent interpretations.
Now I was ready to execute the same coding procedure for current market offerings. During axial coding “Good”, “Bad” and “Great/Room for Improvement” was classified into e.g. “Affordable packages”, “No package deals”, and “Delight”; or “Inclusivity”, “Pay for small details” and “Key to success”.
5. The Results 5.1 Sample
The sample of the present paper was purposively chosen to accurately reflect the co-working market. The study is specified to the geographic limitations of the Amsterdam Metropolitan Area, to be more precise, Amsterdam and Haarlemmer Meer. Since my initial task was to do a competitor’s analysis on the basis of price, setting, product offering and transparency I examined 30 co-working spaces that potentially operate as contestants for Performance Solutions.
A total of 34 Co-working spaces were investigated. However, only 30 participants were valid, while four co-working spaces, situated in Berlin, Germany, aided to the understanding of myself in what makes up good/ bad / great performance in the flexible workspace industry. Using “IBM SPSS software” I analysed Kendall’s tau-b correlation coefficient.
Additionally, I analysed 20 distribution channels, which operate in The Netherlands, and serve as marketplaces for work and meeting spaces.
5.2 Results market data
The results of the present paper resemble the key characteristics that influence individual’s experience level when consuming a service provided by a co-working entity. Hence, an effort was made to correctly assess market conduct by examining performance of the market’s main players. Importantly, good, bad and great/ room for improvement experience levels of consumers were defined on basis of the Reverse Thinking approach. Using open coding, specific performance first-hand information was gathered in a combination of Internet research on participant’s websites and additionally company visits. As described above, I analysed participant’s product and price offering while comparing and re-reading individual performance against other respondents on the basis of affordability, transparency of pricing and offering, standard equipment and offerings, setup of the space and appearance, value for money, service, transportation methods, experience, work environment and participants marketing strategy. Here, open codes emerged on the basis of what customer expect from services versus what they actually receive. In this way, I was able to define what constitutes a favourable, unfavourable and great service quality. For practicality, consider the following open coding example on product offering: “Transparent offerings”, “Non transparent offerings” and “Never Stupid surprises”.
5.2.1 Open-coding
Seen in Table 1 below, the process of open coding is illustrated. The first column indicates the specific open code name. Secondly, every single open code of market data is carefully defined from an occupier’s experience perspective. Based on the NPS score and also the Reverse Thinking approach’, I explained why certain characteristics of delivering services are estimated “Good”, “Bad” or respectively “Great - room for improvement” conduct. In the third column, spatial explanations for ‘promoters’ can be found in form of customer delight and great performance. ‘Detractors” represents customer dissatisfaction and therefore bad performance. However, NPS’ ‘passives’ are those who are in the middle of feeling delight and dissatisfaction, which blurs the light on good performance.
However, a fourth column filled with specific examples from participants, aided my comprehension of what constitutes performance level, which I left out here for simplicity.
5.2.2 Table 1: Open-coding Process Market Data
Open Codes Definition Reason for performance
Affordable packages Are there package deals in the market? If so – are they affordable? €41 – €80
Good – affordable package prices give a feeling of saving money to the customer → satisfaction
No affordable packages
Do participants offer package deals? If so – are they
expensive? €81 – €115
Bad – no/ unaffordable packages mean that there is no chance to make a good deal for the customer; if too expensive → feeling ripped off Package delight Is there good value for
money when choosing a package deal? – price/ value comparison must be greater than choosing a customized deal
Great/ Room for improvement – a good value for money deal is a strong stimulator for customer satisfaction and thus enables to deliver a great experience for participants → delight
Transparency of prices
Are price offerings
transparent? If so – they are flexible in nature and
communicated openly.
Good – honest, flexible and transparent pricing grants customer satisfaction since the
customer knows what to expect → plan ahead
Non transparent pricing
Are price offerings non-transparent non-transparent? If so – prices are not openly communicated and inflexible in nature.
Bad – when a participant is hiding prices; when being inflexible in pricing their pricing strategy this causes great customer dissatisfaction. When there is a big selection of options to select from this results in confusion of consumer → unclear, uncertain Authentic pricing Are price offerings authentic?
If so – pricing strategy is affordable, simple, flexible, specific and easily
Great/ Room for improvement – when there is a pricing strategy which is consistent with authentic pricing then consumers know exactly what they will receive in return for their
understood and hiding no extra costs.
financial compensation; no unfavourable surprises → delight
Transparent offerings Are product offerings
transparent? If so – offerings are honest, detailed, flexible and communicated openly.
Good – when offerings are transparent the customer knows what to expect before actually consuming the service → plan ahead, choose from competitors
Non transparent offerings
Are product offerings non-transparent? If so – offerings are unclear, dishonest, imprecise, inflexible and poorly communicated.
Bad – when offerings are dubious the customer does not know what to expect before actually consuming the service. Thus, potential
customers are irritated in the information which they are receiving. This makes it impossible to plan ahead and also distorts rational decision making in choosing from a variety of
competitors.
→ uncertainty, dissatisfaction Never stupid
surprises
Are product offerings fair, transparent and honest? If so – offerings are authentic in nature and also include a certain kind of inclusivity.
Great/ Room for improvement – when there are no unfavourable surprises for the consumer he or she will be very likely to recommend the service to others → delight
Free standard equipment (Wi-Fi + essentials)
Do participants charge for Wifi and essential
equipment? If not – all necessary work tools are included in the price, respectively for no financial compensation available.
Good – when there is no charge for equipment which is typically essential in a meeting setting customers feel inclusivity → consumer
satisfaction
Pay for standard Equipment
Do you have to pay for standard equipment? If so – high cost involved in renting a projector, flipchart, Wi-Fi etc.
Bad – since basic equipment, such as a projector, is key essential to holding a meeting consumers will feel ripped off if they have to pay for standard equipment → customer dissatisfaction
Flexible standard equipment
Is there a flexible strategy for using equipment? If so – participants must provide suitable service and arrangement around their equipment.
Great/ Room for Improvement – when a
meeting space entity allows flexibility in form of service or customization this delivers a feeling of simplicity for consumers. Care-free
environment → delight
Standard offerings What are standard product offerings? This code should identify what the market provides as standard offerings – only favourable offerings will be considered
Good – when complementary Wi-FI & equipment; flexible setup; unlimited water, coffee & tea; Welcome, morning & afternoon break; fruit; sandwich lunch and a possibility to extend package is provided → satisfaction
Unpleasant offerings/ pay for …
What are unpleasant offerings? If so – offering is inflexible, expensive,
Bad – when offerings are not in the interest of the customer the customer feels not properly treated → dissatisfaction
unhealthy, undesirable, mandatory.
What do people want? Do entities search for
customer needs? If so – they actively ask for customer feedback.
Great/ Room for Improvement – when a provider actively search for the customer’s option on what they prefer. This allows to deliver services to others which they desire before they even know. Care-free environment, surprise → customer delight
Convenient setup of space
What is a convenient setup of a space? If so – setup is, adjustable, modern, useful and including all the essentials.
Good – when the setup of workplaces is convenient this contributes towards a care-free environment → customer satisfaction
Inconvenient setup What are inconveniences for setup? If so – fixed,
antiquated, impotent and expensive working container.
Bad – when the setup of space is inconvenient it might decrease the performance and
efficiency of the service being provided → customer dissatisfaction
Sleek, stylish & fully connected
What is the optimal setup of space? If so – setup provides an inspirational, collaborative and care-free environment. E.g. daylight, plug & play, modern equipment
Great/ Room for improvement – when a participant provides state of the art equipment; is special, flexible, stylish, and fully connected in nature; provides daylight, soundproof rooms, useful accessories (e.g. speakers), ergonomic chairs, and a hospitable reception → customer delight
Good website Is the participant’s website appealing? If so – their
representative web address is clear, bright, insightful,
interesting and easy to use.
Good – when the website is appealing and informative the customer is more likely to find all the information he is looking for, which ultimately increases likelihood of booking the service → satisfaction
Operation failure Does the participant’s website have any operational
failures? If so – functions, such as picture galleries, fail to work. Further, navigation on the website is difficult.
Bad – when a website is faulty in its operation this delivers a bad impression on the customer. Ultimately, this decreases the likelihood of consumers choosing this specific entity → customer dissatisfaction
Networking Does the participant enable networking? If so – working space allows for easy networking, communication and collaboration.
Great/ Room for Improvement – when the participant offers spaces which are useful for networking and the collaboration between employees this increases consumers appreciation on the service delivered → customer delight
Inclusivity What elements of individual product offerings are inclusive? What is standard inclusivity? If so – participants provide free Wi-Fi, printing, projector, screen and flipchart
Good – when customers are offered inclusivity this delivers a feeling of saving money and effort for consumers. Inclusivity is an optimal form of service and therefore → customer satisfaction
service.
Pay for small details Do you have to pay for small details? If so – product offerings are intransparent.
Bad – paying for small details reduces
customer satisfaction due to a sense of getting ripped off. For example, paying for a market standard such as Wi-Fi causes heavy displeasure → customer dissatisfaction, detraction
More perks than losses
What is the key to success? This code should identify the key to success from market’s top performers. If so – they communicate more perks than losses.
Great/ Room for improvement – when a customer receives information on how individual product offering can save them money and WHY they offer the best deal then this causes a favorable position in consumers decision making → customer delight, room for improvement
Easy & approachable Service
What is easy service? If so – service is friendly,
welcoming, qualified, useful, transparent, approachable and flexible
Good – when participants help to do your job and create a friendly environment → customer satisfaction
Promises, promises … Do participants promise too much? If so – promising too much and also the impossible
Bad – when giving false promises this
increases the level of expectation consumers have for the service. Hence, this decreases the likelihood that customers will book the service again → customer dissatisfaction, detraction Operation is key: more
than just a place to work
What makes service
approachable & easy? What is more than just a place to work? If so – providing convenience, asking for needs of customers, feel like at home, vibrant community, source of inspiration.
Great/ Room for improvement – when
participants provide more than just a place to work where creativity is striving and
participation is high customers feel great
satisfaction. Due to surprisingly good service → customer delight is generated.
Easy transport Are there convenient transport methods? If so – working spaces are easily accessible by car or public transport. Further, there must be ample parking facilities with no charge for parking.
Good – when a participant is located close to a highway or transportation hub such as an airport this provides an ease of transportation to the consumer. Free parking also generates → customer satisfaction
Inconvenient transport Are there inconvenient transport methods in the market? If so – pay for parking and transport conveniency is limited by restricted transit and parking facilities.
Bad – when it is difficult to reach a certain participant due to parking limitations or also paying financial compensation for parking next to the workspace then this causes
inconvenience for the consumer. Ask €60 per day for parking → customer detraction, dissatisfaction
the workspace and others? If so – participants offer the possibility to expand
customer’s network and also allow comfortable travel.
have the possibility to expand their network while being present in participants workspace this causes a feeling of integrativeness for the consumer. Also easy travel can be very
convenient for consumers → customer delight, promoter to friends and colleagues
Experience What does customer
experience look like?
Experience can be generated in various ways, e.g. setup, food offering, simplicity. If so – the customer enjoys the service quality and receives a memorable experience.
Good – when customers’ beforehand
expectations about the quality of the service are fully met this delivers positive favor for the consumer. Meeting/ exceeding expectations creates positive inclinations → customer satisfaction
Ordinary What does ordinary
experience look like? If so – expensive, in transparent, dull setup, coporate like feeling.
Bad – when the service delivered is ordinary customers find out there is no experience involved in choosing this specific service. Therefore, this might lead to → detraction
Delight How do you consistently
create memorable experience to spread delight? If so – meet/ exceed expectations, surprise,, deliver a uniquely memorable experience.
Great/ Room for Improvement – delight is created when a participant’s top priority is to deliver experience for the consumer in a unique way → customer satisfaction, delight, promotion
Diverse environment How do participants create a diversified working
environment? If so – creativity, open access, collaboration, sharing of knowledge, key is in the people working there
Good – when co-working spaces host a diversified working environment they allow for open access by all kinds of different
backgrounds and concentrate on the knowledge creation within → customer satisfaction
Corporate environment
What size is too big? How to make real connections? If so – size of members is to big, selling culture where
everyone ignores each other and no real connections are made.
Bad – when co-working / workplaces create an environment which is similar to that of an ordinary corporation this creates a cold and impersonal atmosphere → customer
dissatisfaction, detraction
Balance Work & Play How to effectively balance work & play? If so – participants think beyond working environments, home feeling, inspiration, modern & fun setup of the space.
Great/ Room for improvement – when a co-working space successfully balances work & play within their space they go beyond ordinary working environment, In this informal setting you can hang out with people who are already the way you want to be → customer delight! Content marketing How does content marketing
look like? If so – participant’s marketing efforts
communicate their underlying
Good – when participants communicate their specific content in their marketing message this gives a good impression of what customers are likely to expect. Additionally, content marketing
idea, structure and content. is an effective way to acquire new customers → customer satisfaction
Ordinary marketing What is established
marketing? If so – they use ordinary marketing messages which can be exciting but still are not unique in nature.
Bad – when marketers communicate ordinary messages there is no memorable experience being promised which decreases the likelihood of consumers remembering their messages → customer dissatisfaction, detraction
WHY/ Authentic marketing
What is authentic marketing? If so – no false promises, transparent, unique,
communicating their reason for being, mission and logic behind their service.
Great/ room for improvement – when a
company communicates their reason for being (in a WHY kind of way) this delivers a great sense of importance to the consumer. Authentic content marketing → customer expectation → authentic service → customer delight → promotion
5.2.3 Performance grid market data
After defining experience levels for specific data fragments I processed the open codes into a performance level grid from 0 - 2. Here, 0 stands for “Bad”, 1 resembles “Good” and 2 exemplifies “Great/ Room for improvement” conduct. Thus, I gauged particular behaviour of participants in respect to individual service quality, respectively level of experience, on a three-point scale (see Table 6 in the appendix). Since this research has been exploratory and explanatory in nature, the definitions acted as groundwork’s for estimating co-working market conduct. Using this performance grid, in combination with the earlier described definitions of service quality, proved to work out as a simple but effective way to assess the frequency of participant’s individual performance.
5.2.4 Axial coding
Following, the next step in my data analysis required me to process open codes into axial codes. Here, open codes that show similarities in their meaning and influence on experience are grouped together (see Table 7 in the Appendix).
For example, the axial code “Service = providing convenience” is formed out of the open codes “More than just a place to work”, “Easy & approachable Service” ; “Convenient setup of space” “Inclusivity” and “More perks than losses”. While each of the open codes has a predefined meaning by itself, axial coding results in a categorization of experience influencers. Therefore, this allows identifying linkages between desirable, respectively unfavourable characteristics of experience quality. For instance, this axial code demonstrates the relationship between service and convenience, which leads to the result that greatest service that can be catered by participants, is to provide convenience. On the other hand, “Inconvenience delivers dissatisfaction” sums up unfavourable characteristics of
