The use of Analytic Hierarchy Process to identify value communication for independent workers on ‘Gig’ Economy

The ‘gig economy’ or ‘platform economy’ has seen unprecedented growth in certain occupations, and individuals and enterprises are registering on these platforms to find independent work and look for remote workers respectively. Especially since March 2020 with the COVID pandemic. There are also businesses or start-ups that are planning to or have already started to build such online platforms to enable ‘gigs’ online. This paper will contribute in the following 2 areas (and 3 stakeholders): (1) Use Descriptive Analytics, Cross-Tabulation, to provide Decision Support to senior leadership in the marketing function who are planning to or have recently started to build an online ‘gig’ platform to understand the ‘gig’ economy (2) use Analytic Hierarchy Process (AHP) to help marketing practitioners and research scholars on how to quantitatively identify motivations why firms and individuals (e.g. freelancers) seek remote workers and independent work, respectively, on ‘gig’ platforms. The author has identified a gap through research literature review and surveys with over ten firms and 40 professionals in applying quantitative techniques to identify motivations for joining the ‘gig’ platform. Current methods are qualitative. This paper will plug the gap in practitioners and academia in providing clarity to their marketing team or third-party advertisers, creative agencies on how to devise go to market communication based on the, now, quantitatively identified motivations. It will also help marketing practitioners and academia to understand the ‘gig’ platform – occupations, country-wise potential, the year-wise trend over the last 4 years (2017- 2020).

Introduction

Over the last decade, there has been a shift in the workforce to online, seeking work which they can deliver from the comforts of their home or remote. This is the beginning of what is referred to as a ‘gig’ platform. The nature of work is referred to as Independent Work. Work that is characterized as (1) High degree of autonomy (2) Payment by assignment (3)  Short-term duration. Contract workforce is not included in Independent Work as they are covered under labor contracts. They typically work like full-time employees, though they are not so technically. To enable the participants to engage, there has been a rise in ‘Platforms’ – digital platforms that enable firms and individuals to find each other online, and handshake for business. The work may be delivered by individuals remotely. They may work online or finish work offline and submit work online. And payments are made by the firm to the individual. The are several motivations why individuals and firms register on these platforms to transact and complete work.

Gig economy

‘Gig’ economy or ‘Platform’ economy if for independent work alone and not for full-time work hence the term ‘gig’. Independent work is short-term work and you are paid on basis of work completed and delivered. No work. No Pay. To differentiate from regular work/job and a regular salary. Secondly, independent workers usually work remotely; in fact, they may be working in another country. For example, in the USA, a firm may look for software development expertise for say a period of 1 month and may seek a remote worker working as gar as in India. Individuals may be grouped into 4 categories as shown in Figure 1.

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Figure 1: Individual participants seeking independent work online

There are 2 triggers for individuals to come online (1) wanting to earn through independent work as a source of primary income or (2) wanting to earn from independent work as a stop-gap arrangement till you are able to find full-time position. Within these two triggers, there are additionally two further sub-categories.

  • Freelance: these are independent workers who come have chosen the ‘gig’ platform and independent work as a preferred choice. They earn their primary income from the ‘gig’ economy and through the delivery of independent work
  • Income Top-up: these are independent workers who do not necessarily need an income (e.g. students or pensioners or seniors – above the age of 65) who seek independent work to have an income to pursue their aspirations or goals. And they also come online to these platforms as a preferred choice of employment and income.
  • Job Loss: these are individuals who have lost their job and while they look for a full-time job, they take up independent work out of necessity. And this becomes their primary source of income
  • Making Ends Meet: these are individuals who have been through a salary cut or their current salary is unable to make ends meet. Hence they chose this take up independent work to bridge the gap in their income. Till such time they are able to find a job that pays to their expectations and needs.

A few Oxford researchers built a site (http://ilabour.oii.ox.ac.uk/online-labour-index/) to track activities on such platforms and according to their study conducted in 2016 across Spain, France, Sweden, Germany, and the USA, they estimated that 30% of the independent workers were Freelancers and 40% were Income Top-up. Implying 70% of the independent workers belong to this category. Moreover, as we discussed, these two categories of independent workers are online on these platforms as a preferred choice. Unlike the other two types which are there out of necessity. This paper, therefore, restricts the research to Freelancers and Income Top-Up, categories of independent workers as they are a more stable set of participants on these platforms earning income from these platforms as a primary source.

See Figure 2 (Source: McKinsey 2016)

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Figure 2: Break-up of independent workers

Figure 2 shows, as per research conducted in 2016 across the USA, Germany, France, Sweden, and Spain, independent works were a good 30% of the working-age population in those countries. Out of these independent workers, women were a good 50% of the separate works, followed by Youth (less than 25 years of age) at 20%, Low Income (20%), and Seniors (greater than 65 years of age) at 10%. This paper carefully tries to include women, youth, and seniors into the survey sample. Low Income is excluded from research, as they are on online platforms out of necessity. And as we discussed the two categories of ‘Job Loss’ and ‘Making Ends Meet’ have been excluded from this research.

The online platform and the platform Economy

‘Platform’ economy is characterized by firms advertising independent work opportunities and individuals finding such work. Work may be delivered online or offline and subsequently submitted online. There are several types of work that are available online, from very simple to very complex. Work that may be completed by an individual or intricate work that may require a remote team to work together to complete. This paper will focus only on individual work and the motivations of these individuals to seek independent work. And team-related work has been excluded from this study. Simple work includes examples like click-work – typing medical transcripts or delivery of data entry work. Examples of other kinds of skills or work that deliver on these platforms include professional services like those performed by a remote finance professional or an accountant working through your tax filing. On the demand side, we have firms that are advertising independent work online. On the study of literature to understand their motivations and transition to such online platforms, it is found that firms are also working through their constraints of finding the right skills as and when they need them and all this is keeping an eye on cost. Access to skills is largely limited to how they operate, especially in terms of geographic spread. Figure 3 shows how firms transition thru these constraints and the motivating reasons for them coming online.

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Figure 3: Transition for firms to a near 100% remote workforce model

This paper interviewed 10 large organizations across industries to also understand from them the motivations, as per their experience, on why individuals chose to come online on these platforms seeking independent work.

Independent worker index

At this juncture, it is important to highlight the efforts made by researchers at Oxford University through the iLabour project. This Online Labour Index is an index that measures the utilization of Online labor Platforms over time and across countries and occupations.

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Figure 4: Online Independent work running graph

(registered user accounts in the USA relative to start of the year)

After March 2020, we see a fall in some occupations. This is an important insight and we will discuss this during the data analysis stage in a subsequent section. This paper looks at the dataset from 2017 to 2020 and using cross-tabulation presents models and views that can help academia, researchers, and marketing practitioners to understand the ‘gig’ economy.

‘Independent Work’ Market

Market and Market actors

The leading online platforms (https://ilabour.oii.ox.ac.uk/) selling gig through their platform include brands like UpWork, Flexingit, Guru, Freelancer, and Fiverr. Some key statistics of the market are shown in the following figure:

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Figure 5: The percentage share of global Online labor demand in 2020

Value communication

Value communication is the process of how a firm or a business communicates it’s value proposition to its customers. In this paper this communication is studied from the perspective of a ‘gig’ platform business, and how do they communicate their value proposition to individuals. As we discussed, individuals would be limited to the two categories of Freelance and Income Top-Up. And how the ‘gig’ platform should communicate it’s a value proposition to these individuals. As a first step to doing this, the ‘gig’ platform should understand the motivations for an individual to come online seeking independent work. And next since this paper studies two categories of independent workers, are the identified motivations similar for them, or is that a difference in their needs.

 Methodology

 Research design method

The research methodology has been designed to:

  • Review literature on the ‘gig’ economy to understand the firms that engage, the type of individuals (e.g. freelance) who seek independent work, and also understand the potential for India businesses wanting to build a ‘gig’ platform
  • Review literature and systematic study of the ‘platform’ economy to understand the services, user experience journey on these platforms to identify their value proposition. Data were then analyzed for the period 2017-2020 using cross-tabulation to build decision models.
  • Survey of firms, across a spectrum of industries – in India (including global organizations that have an India presence) who are registered on ‘gig’ platforms to review the value proposition identified by our literature review & system study of existing online platforms
  • Three surveys were conducted: (a) 10 firms were surveyed to understand how they compare the 4 motivational reasons identified based on a literature review. The comparison was subsequently analyzed using Analytic Hierarchy Process (AHP) (b) 20 Freelancers were surveyed to understand how they compare the 4 motivational reasons for them to register online on the ‘gig’ platforms. The comparison was subsequently analyzed using Analytic Hierarchy Process (AHP) (c) 20 Income Top-up individuals were surveyed to understand how they compare the 4 motivational reasons for them to register online on the ‘gig’ platforms. The comparison was subsequently analyzed using Analytic Hierarchy Process (AHP)
  • The AHP results were studied to identify the value propositions for Freelancers and Income Top-up professionals. To help build value communication.

 Data collection method

  •  Four-year data from 2017 to 2020 was collected from https://ilabour.oii.ox.ac.uk/. (a) Dataset pertaining to Country- Occupation – Number of independent workers (b) Dataset pertaining to Continent-wise Countries included (c) Dataset pertaining to Country- Occupation – Number of Projects
  • Four motivations were identified, which was used to compare by firms, freelancers, and Income Top-Up professionals: (a) Work-Life Balance (b) Flexibility to work online and remote (c)  Independence to choose what kind of Work you would like to do (d)  Ability to choose working hours
  • First Survey of 10 firms. The firms cut across the following industries: (a) Financial Services (b)  Life Sciences (c)  Media & Entertainment (d)  Retail (e) Services
  • Second Survey of 20 Freelancers. (a) Occupations surveyed – (i) Creative and multimedia (ii) Writing and translation (iii) Software Development and Technology (b) Age Groups surveyed – (i) 25 or less (ii) 25 – 50 years (iii) 50+ years
  • Third Survey of 20 “Income Top-Up” professionals. (a) Occupations surveyed – (i) Creative and multimedia (ii) Professional Services (iii) Software Development and Technology (b) Age Groups surveyed (i)  25 or less (ii)  25 – 50 years (iii) 50+ years

Data analysis method

  •  Cross-tabulation to build decision models using 2017-2020 data: (a)  Country-wise breakup of Top Occupations (based on number of independent workers) (b) Country-wise breakup of Top Occupations (based on number of projects) (c) Top N Countries for Independent work (d) Top N Occupations for Independent work (e) Growth of workers Year-on-Year for Top N countries
  • Analytic Hierarchy Process (AHP) comparison for motivation reasons, as compared by 10 firms (a) Compare and identify top motivation reasons for individuals to come on ‘gig’ platform (b) Calculate Consistency Index and Consistency Ratio
  • Analytic Hierarchy Process (AHP) comparison for motivation reasons, as compared by 20 freelancers (a)  Compare and identify top motivation reasons for freelancers to come on ‘gig’ platform (b)  Calculate Consistency Index and Consistency Ratio
  • Analytic Hierarchy Process (AHP) comparison for motivation reasons, as compared by 20 Income Top-Up (a) Compare and identify top motivation reasons for Income Top-Up to come on ‘gig’ platform (b) Calculate Consistency Index and Consistency Ratio

Preliminary Data

Decision Model for ‘Gig’ Economy

  • 2017-2020, the four-year dataset was available from https://ilabour.oii.ox.ac.uk/. The dataset analyzed (a) Number of countries: 191 (b) Number of workers: 316 million (c) Number of occupations: 6
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Table 1: Top 10 countries based on # independent workers

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Table 2: Top 10 countries based on # projects

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Table 3: Occupations based on # of workers

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Table 4: Occupations based on # of projects

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Table 5: Top 4 countries Y-o-Y growth in independent workers

  • Against this analysis of data, we notice that the Top occupations are: (1) Software development and technology (2) Creative and multimedia (3) Sales and marketing support (4) Writing and translation
  • An important decision for further analysis: From Figure 4 we notice that post-Covid, firms have cut on non-essential expenses, and therefore Sales and marketing support has been impacted. Therefore the research study has limited to survey freelancers and Income Top-Up for the following occupations: (a) software development and technology (b) Creative and multimedia (c) Writing and translation

Identifying motivating reasons – a survey of firms

  • Ten firms were identified
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Table 6: Industry composition of firms interviewed

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Table 7: Type of business operations

  • Survey was conducted to compare: (a) Work-Life Balance (b) Flexibility to work online and remote (c) Independence to choose what kind of Work you would like to do (d) Ability to choose working hours. The survey is depicted in Table 8
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Table 8: survey for comparison of motivating reasons to register for independent work

  • STEP 1 of AHP: comparison made by 10 firms (Table 9)
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  • STEP 2 & 3 of AHP: Normalize and Eigen Vector calculation (Table 10)
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  • STEP 4 of AHP: calculate Principle Eigen Value = 4.23
  • STEP 5 of AHP: Consistency Index = 0.07763
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  • STEP 6 of AHP: Random consistency index (considering n=4) = 0.9
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  • STEP 7 of AHP: Consistency ratio (considering n=4): CI/RI = 9%
  • Final comparison by firms on motivating reasons why individuals seek independent work on ‘gig’ platform (Table 11)
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Freelancers – Survey to compare their motivating reasons for seeking independent work

  • 20 freelancers were surveyed.
  • The second Survey was conducted using a similar questionnaire as shown in Table 8
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Table 12: Age-wise occupation break-up for freelancers

  • STEP 1 of AHP: comparison made by 20 freelancers (Table 13)
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  • STEP 2 & 3 of AHP: Normalize and Eigen Vector calculation (Table 14)
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  • STEP 4 of AHP: calculate Principle Eigen Value = 4.2372
  • STEP 5 of AHP: Consistency Index = 0.07907
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  • STEP 6 of AHP: Random consistency index (considering n=4) = 0.9
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  • STEP 7 of AHP: Consistency ratio (considering n=4): CI/RI = 9%
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  • Final comparison by firms on motivating reasons why individuals seek independent work on ‘gig’ platform (Table 15)
  • “Work-Life Balance” is 1st choice for Freelancers followed by “Flexibility to work From Home”.
  • “Ability to choose working hours” and “Independence to chose the kind of work I would like to do” are too small

Income Top-Up – Survey to compare their motivating reasons for seeking independent work

  • 20 Income Top-Up professionals were surveyed. The third Survey was conducted using a similar questionnaire as shown in Table 8
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 Table 16: Age-wise occupation break-up for income top-up

  •  STEP 1 of AHP: comparison made by 20 Income Top-Up professionals (Table 17)
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  • STEP 2 & 3 of AHP: Normalize and Eigen Vector calculation (Table 18)
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  • STEP 4 of AHP: calculate Principle Eigen Value = 4.2094
  • STEP 5 of AHP: Consistency Index = 0.0698
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  • STEP 6 of AHP: Random consistency index (considering n=4) = 0.9
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  • STEP 7 of AHP: Consistency ratio (considering n=4): CI/RI = 8%
  • Final comparison by firms on motivating reasons why individuals seek independent work on ‘gig’ platform (Table 19)
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Summary & conclusions

Conclusion regarding ‘gig’ economy

  •  The top countries supplying independent workers among the 191 studied across 4 years 2017 – 2020 are:
  • In terms of number of workers (1) India (2) Bangladesh (3) Pakistan
  • In terms of number of projects (1) India (2) United States (3) Canada
  • The Top occupations are: (1) Software development and technology (2) Creative and multimedia (3) Sales and marketing support (4) Writing and translation
  • However, it was noted that firms are reducing non-essential expenses, post-Covid 19 and therefore occupation like ‘Sales and marketing support” has taken a dip since March 2020.

Motivating factors for Freelancers to seek independent work

  • “Work-Life Balance” is 1st choice for Freelancers followed by “Flexibility to work From Home”
  • Value communication may therefore be created around these two motivating factors by ‘gig’ platforms

Motivating factors for Income Top-Up to seek independent work

  •  “Ability to choose working hours” is 1st choice for Income Top-Up followed by “Flexibility to work From Home”.
  • Value communication may therefore be created around these two motivating factors by ‘gig’ platforms

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