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This paper will contribute to extending Service-Dominant Logic (Vargo and Lusch (2004a, b), in helping marketing managers and academia with constructing Value Proposition (Lanning and Michaels (1988)) from an Outside-In approach. Extending Service-Dominant Logic to create a communication plan for marketing managers to communicate Value Proposition to customers. Construct and communicate the value proposition, in the context of ‘Gig Economy,’ for firms that run or are planning to build an Online Talent Platform. Online Talent Platform is a platform where enterprises can advertise Independent Work, and individuals can find Independent Work.
The Covid-19 pandemic situation has impacted enterprises, individuals, and families since December 2019. The ‘New Normal’ (Peter M. Sandman and Jody Lanard) is leading enterprises and individuals to learn and adapt, build resilience, and re-draw way-forward. Against this backdrop, the ‘gig economy’ or ‘Platform economy’ (Professor Carliss Y. Baldwin and Dr. C. Jason Woodard) has received attention from enterprises and individuals. With individuals first moving remote and starting to work from home (WFH) to then seeking Work Online on these ‘gig’ Platforms. Enterprises are also looking at new business models of engaging with the remote workforce and also seeking opportunities that may now exist in the ‘New Normal.’ Start-ups have cashed in on this situation, and there is a burgeoning of Online ventures. Online on portals and also on mobile applications. There are also start-ups and enterprises building new ‘gig’ Platforms for B2B and B2C to engage and search skills, find Work and earn from home. There is also an increase in Online workers on the ‘gig’ Platforms, including first time Online workers. The demographics of Online workers are also seeing an impact on women and seniors (over 50 years) taking to ‘gig’ Platforms for Work and income. This, in addition to youth (25 years or below) looking at these Platforms for part-time Work and extra income. Against this backdrop, this paper extends Service-Dominant Logic to understand it’s relevance and application to building a ‘gig’ Platform.
Creation of Value
Service-Dominant Logic (Vargo and Lusch (2004a, b) propagate that Service is the appropriate Logic for marketing (Vargo and Lusch (Journal of Marketing, 68:1–17, 2004a, Journal of Service Research, 6:324–335, b)). It is a process where the participants, an enterprise, and it’s a customer or an enterprise. Another enterprise (e.g., producer /manufacturer and it’s supplier /vendor) engage with each other to do something for the other (Vargo and Lusch (Journal of Marketing, 68:1–17, 2004a, Journal of Service Research, 6:324–335, b)) that is valued by both. And this, therefore, creates a business relationship. Service-Dominant Logic (S-D Logic) states that Value is not created when the exchange happens between, say a producer of goods, and the customer who buys it. Value is created when the customer uses the product. Therefore, Value is not created at the point of exchange, but the Value is created in use (Alderson 1957; Danner 1976; Grönroos 2000; Holbrook 1999). This has far-reaching implications, including a paradigm shift from our traditional goods-dominated Logic of marketing. Where we defined Value being created by enterprises (e.g., a producer/manufacturer of goods – with its product features and functionalities) and when sold, the customer weighs the benefits to cost (price) paid for the product/goods and Value is created. Service-Dominant Logic (S-D Logic), however, now states that enterprises cannot create Value at exchange. They can only provide a value proposition. This implies enterprises that produce goods actually do not create Value in exchange when the goods are sold. Prior to the industrial age, individuals and families used to produce goods (e.g., grow food, make clothing, tools) and used to either sell to local communities and/or consume it themselves. Or barter in most cases. So the producer (individuals, group of individuals, and families) and consumers were one and the same or at very close proximity. Skills were available with individuals, and they brought complementary skills. Farming skill versus textile skill. And they would leverage each other’s skills. (Toffler (1980)) The industrial revolution built large production and manufacturing facilities. They hired the skills and made them available at one place within the manufacturing facility. And with this, the producer was separated or distanced from the consumer. Marketing bridged the distance between producer and consumer, enabling exchange. And with this, the goods that were produced by individuals or families or groups of individuals for their personal use now had marketable exchange value (Smith 1759/2002, 1776/1970). So with the industrial revolution, we moved to value in exchange. And the basic premise of Goods Dominant Logic (see Dixon, 1990) in Marketing.
Co-Creation of Value
The participants’ role, for example, supplier and producer, is now to provide goods as a means to service the customer and create Value through the use of that product. So now supplier and producer will work closely with the customer to create Value as they use the product. Opportunities to create Value now exist with the customer and not with the producer. So now, suppliers and producers work closely with their customers and take their feedback from usage. This leads to another key concept within the S-D Logic of co-creation of Value (Ballantyne, D. and Varey, R.J., 2008). Co-creation (Lusch and Vargo 2006b ) of Value in S-D Logic is an important aspect to be differentiated from terms like co-production and collaboration. Co-creation leads to the creation of a unique Value. In contrast, co-production is using known resources and capabilities. Another important aspect of co-creation in S-D Logic is it is created when the customer uses the goods, so co-creation is dynamic (Ballantyne and Varey 2006b). For co-creation to succeed, it implies the ‘supply chain’ of suppliers, producers, and the customers need to work together. This then means the traditional ‘supply chain’ will no longer be linear (Grönroos (2000: 48), where each participant plays a role in the chain, and Value is created in steps. Under the backdrop of co-creation of Value, the role of the market will need to be reviewed as value creation happens at customers’ end with their usage. Moreover, the marketing imperative will now be whom enterprises will serve and build relationships with; and who will serve them (Ballantyne, D. and Varey, R.J., 2008).
- As we have seen in the earlier sections, Service is now the common denominator in Service-Dominant Logic. And the key to co-creating value is a high level of interaction between participants. In the 1800s, we have the Goods Dominant Logic that ultimately had an economic orientation (Robert F. Lusch, Stephen L. Vargo). Then we moved to Services Marketing in the 1980s and now the Service-Dominant Logic. The transition (Goods to Service Marketing to Service-Dominant Logic) may be understood with the following (Robert F. Lusch, Stephen L. Vargo): (1) the transition from goods to services to Service (2) the transition from products to offerings to experiences (3) the transition from features to benefits to the solution (4) Value add to co-production to co-creation (5) Price to value delivery to Value Proposition
As we discussed on the co-creation of Value, participants will have to give up their traditional roles as suppliers, producers, and not have the ‘supply chain’ create Value at each step, serially. S-D Logic, therefore, propagates each participant to engage in service provision. Service for Service (S.L. Vargo, R.F. Lusch). This then also questions the traditional roles of the seller, buyer, producer, and also marketer. S-D Logic service ecosystem can, at best, be referred to as an A2A (Actor to Actor). And the marketer as an integrator (S.L. Vargo, R.F. Lusch). The network of participants or actors will, in a sense, therefore, work towards the welfare of the individual and, ultimately, the wellbeing of the entire ecosystem of participants or actors.This implies the service ecosystem has a purpose (S.L. Vargo, R.F. Lusch). This is the underlying aspect that will be understood and applied to the ‘gig’ economy to understand how enterprises who plan to build and grow a ‘gig’ Platform create a Platform of purpose, leading to value co-creation. A Platform that adapts and grows.
Review of ‘Gig’ Economy or ‘Platform’ economy literature
‘Gig’ or Independent Work is characterized by (1) high degree of autonomy, (2) payment/income is generated assignment-wise (3) the assignment is short duration. This means ‘gig’ or Independent Work leads to part-time or short-term Work, and you are paid for the Work you do and not a regular salary. The participants, individuals who typically engage in the ‘gig’ economy, are shown in Figure 1 below.
Figure 1: Individual categories in the ‘Gig’ economy
See Figure 2 (McKinsey Oct 2016)
Figure 2: Break-up of independent workers
‘Platform’ economy is characterized by (1) employers and workers using Online Platforms to advertise and find Work, (2) Work may be carried out offline or Online or in rare cases at the office location, (3) nature of Work could span low-skilled Work (like click-work- where you are typing medical transcripts or doing data entry) to specialized and complex Work (e.g., coding and building a BoT). Enterprises are also re-inventing themselves looking at levers that can provide them with better access to Talent, improve the productivity of their teams (especially when they are remote), and how to ensure costs like office rental is significantly reduced. Enterprises are now looking at shared office space (e.g., We Work) where they pay per use and thereby making it easier for them to reach larger geography without having to invest in office space and thereby paying high rental costs. By moving to shared space and slowly allowing the workforce to work remotely or from their homes, enterprises are able to reach a larger number of prospective Talent and engage. Improve their productivity as individuals spend less time traveling to Work. And also significantly, if not completely reducing their cost on office rental to zero.
Figure 3: How enterprises are realizing the benefits of a remote workforce (McKinsey Jul 2020)
Online Labour Index
At this juncture, it is important to highlight the efforts made by researchers at the Oxford University through the iLabour project. This Online Labour Index is an index that measures the utilization of Online labour Platforms over time and across countries and occupations.
Figure 4: A typical chart that is updated and available on iLabour (https://ilabour.oii.ox.ac.uk/)
(registered user accounts in the USA relative to start of the year)
Datasets are available free for the last four years and updated on a daily basis. This site has identified the following six occupations as the most active for Independent Work: (1) Software development and tech, (2) Creative and multimedia, (3) Professional Services, (4) Sales and marketing support, (5) Writing and Translation (6) Clerical and data entry. This paper utilizes these six categories to sample and interview it’s focus group. The other aspect, while reading literature in this area, was the impact of Covid-19 (post-March 2020) on Independent Work. As we see in Figure 4, except for ‘Software development and tech’ and ‘Creative and multimedia’ occupations, the others have taken a dip since March 2020. As long as Online and remote Work are a substitute for on-premise. Reduce Cost (e.g., real estate cost, cheaper resource rates Online). And External environment (e.g., job losses driving individuals to independent Work, Online, and remote Work). Then the ‘gig’ or ‘Platform’ economy will continue to show growth. However, there is also an impact, referred to as distancing loss, where enterprises are cutting down on non-essential expenditure. The ‘gig’ or ‘Platform’ economy will face the brunt, as is apparent from certain occupations in Figure 4, that were hit post-COVID-19 (post-March 2020). This has motivated the researcher to also gauge the sentiment of respondents in the focus group regarding the impact of Covid-19 on the job market, especially in terms of job security and incomes.
Review of ‘Independent Work’ Market literature
Market and Market actors
The top 10 players (https://ilabour.oii.ox.ac.uk/) in the market who run an Online Platform include UpWork, Flexingit, TaskRabbit, Guru, Desicrew, ODeskwork, GharSeNaukri, Truelancer, Freelancer, and Fiverr. Interest in remote working and related search terms tripled post-March 2020 (post-COVID-19 impact) (https://ilabour.oii.ox.ac.uk/) The global market for Online labor has grown approximately at 50% Y-o-Y from 2015 to 2018 (https://ilabour.oii.ox.ac.uk/). It is estimated that the Online Talent Platforms have the potential to add $2.7 trillion to global GDP by 2025 (2% GDP). Adding 72 million FTE (full-time equivalents) by 2025. Over 540 million individuals will be impacted by Online Platforms due to the value proposition these Platforms can bring to individuals and small enterprises (B2C and B2B, respectively). The 540 million addition will also be due to more Online hours being added.
Figure 5: The percentage share of global Online labor demand in 2020
Figure 6: World Map
850 million people in the United States, the United Kingdom, Germany, Japan, Brazil, China, and India are unemployed, inactive, or working only part-time (30-45% of the working-age population). 37% of global respondents to a recent survey of job seekers conducted by LinkedIn said their current job does not fully utilize their skills or provide enough challenge.
Figure 7: India Map
From an India perspective on independent Work, the impact is 1.9% of GDP by 2025 (1.2% due to new Online opportunity seekers, 0.4% due to the value proposition of Online Talent Platforms). In 2016 15 million freelancers were from India (40% of total freelance jobs offered worldwide). ASSOCHAM puts the annual growth rate of the gig economy at 17 percent and predicts that it will touch $455 billion by 2023. At this juncture, the researcher has also reviewed the demographic data for India to understand the shift and the possible impact it may have on enterprises wanting to build a ‘gig Platform.’ By 2028 the working-age population of India is projected to be 971 million. By 2025, 35% of the population will be in urban areas of the total population of 1.4 billion in 2025. Most importantly, India will bring 68 million more women into the workforce by 2025 (21 million in urban – working in occupations including computers and healthcare- occupations that could potentially look at Online gig). And lastly, 25% of India’s population will be Seniors between the age of 50-65 years.
Review of Value Proposition literature
As we had seen in the previous section on Service-Dominant Logic, we have seen a transition from the Goods-Dominant Logic to Service Marketing to S-D Logic. Especially how there has been a transition from Price to Value Delivery to Value Proposition. Value Proposition being aligned with Service-Dominant Logic. The origin of the Value proposition is the 1988 work at McKinsey & Co. of their consultants Lanning and Michaels. They combined the Harvey Golub and Jane Henry in 1981 on mapping value to price for industries whose products have a sizeable share of intangible or subjective Value. They proposed a Value Delivery System that proposed (1) identification of Value, (2) Provide the Value, (3) Communicate Value to the customer. As we see in Service-Dominant Logic, firms can only create Value Proposition, and they do not create Value. Moreover, previous literature of Value Proposition shows Value is created by an organization, inside the organization and communicated to customers. With S-D Logic of Co-Creation, Value creation happens at the client end through use. Therefore as a critical input to Value Proposition, it is important that firms listen to customers on what they want and then build the Value Proposition focused on the customer. An Outside-In Approach to creating Value Proposition instead of a traditional Inside-Out approach. The researcher, therefore, through focus group interviews, identifies what customers list as reasons for looking for independent Work on Online Talent Platform and provide a construct that may be utilized by firms to create their Value Proposition, aligned with the customer.
Research design method
The research methodology has been designed to: (1) Review literature on Service-Dominant Logic and understand the concept of value co-creation (2) Review literature on ‘gig’ or ‘Platform’ economy or Online Talent Platform to understand Independent Work, Participants in this ecosystem, Market Overview- global and India, Demographics of Online workforce including occupations that fit well in this ecosystem (3) Review work is done on Value Proposition and how it is built extending Value Proposition. (4) Focus group interviews to hear the voice of individuals who participate in the Online Talent Platform and what are the top few criteria that motivates them to look for independent Work and engage on these Platforms. (5) Analysis of data to construct Value Proposition for firms venturing into the ‘gig’ or ‘Platform’ or Online Platform business (6) Contribute to the knowledge of constructing Value Proposition by extending Service-Dominant Logic of Co-Creation of Value
Data collection method
- Data on the Online Talent Platform was available from https://ilabour.oii.ox.ac.uk/ and research papers published by the Oxford University research team working on the iLabour project. Data was also collected from secondary sources like research papers on Independent Work in India and Globally, including a forecast of the impact of the Online Talent Platform.
- India demographic data, working population projections, independent work data were available from secondary data through research papers and articles.
- A Focus group interview was conducted for 80 individuals: Focus group participants were selected to include individuals who have delivered independent Work and also those who are planning to onboard Online Talent Platforms. Gender considerations. Age groups 25 or less (Youth), 25-50, 50+ (Seniors). Marital Status (Married or Single). Occupations as classified by https://ilabour.oii.ox.ac.uk/ Software and tech, Creative and multimedia, professional services. The Top 3 occupations that are Online for independent Work
- Data was collected from Focus Group on their motivations to opt for Independent Work and be engaged on Online Talent Platform, as critical inputs to constructing Value Proposition for firms venturing into the businesses of building an Online Talent Platform
- Also collected feedback from respondents on their sentiment regarding the current Covid-19 (Mar 2020 onwards) pandemic impact on job security and income, as another input to constructing Value Proposition for firms venturing into the businesses of building an Online Talent Platform
Data analysis method
- The interview data from the Focus group was analyzed through Cross-Tabulation to map: (a) Occupation (referred to in the interview as Skill), Age Cross-Tabulation with the seven motivating reasons for individuals to opt for independent Work and find independent Work online (b) Age, Occupation, Gender Cross-Tabulation with the choice of Independent Work as Primary Income versus Independent Work as Extra Income
- Data Analysis in SPSS: (a) Correlation between all the seven motivating reasons for individuals to opt for independent Work and find independent Work online (b) Correlation of Age, Gender, Occupation, Marital Status with all the seven motivating reasons for individuals to opt for independent Work and find independent Work online (c) Frequency Means analysis across all seven motivating reasons selected by respondents.
- Sentiment Analysis in NVIVO. (a) Overall Sentiment analysis of the Focus Group (Negative, Positive or Neutral) to Covid-19 impact on job security and income, as an input to the creation of Value Proposition (b) Review of the 80 transcripts and coding them into Word Clouds, TreeMap, Hierarchy charts
Focus Group & Interview Flow
The following interview was conducted with 80 respondents:
Table 1: 80 respondent demographics
- Discussion to understand their motivations in opting for Independent Work and find Independent Work Online: (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 (e) Be your own boss (f) Level of income (g) Recognition
- Discussion on “What is your assessment of current COVID-19 situation on the job market in terms of job security and income?”
Transcript – Sentiment Analysis
80 transcripts were collected from the respondents, where they expressed their motivating reasons for opting for Independent Work and also their sentiments on the COVID-19 situation.
Table 2: NVIVO import of all 80 transcripts
- 421 words were coded by: Rolling up words stemmed words (e.g., Talk with Talking). Rolling up further with synonyms (e.g., Talk with Speak). Rolling up further with specialization (e.g., Talk with Whisper). And final Rolling up with generalization (e.g., Talk with Communicate)
- Word Count in Shown in Table 3. Limited to top few with weightage close to 1
- In Business terms, the word count can point towards the following three key inputs to constructing Value Proposition. This is based on an expert abstraction of translating the voice of respondents and their sentiment analysis in business terms: Quick Search (ability to search jobs quickly online). Team-rooms online (collaboration online). Learning new skills and training (online)
- Word Cloud from NVIVO depicts the most used word. Larger the font, the larger the usage:
Table 4: Word Cloud
- TreeMap view of Word count. Larger the box, the larger the usage
Table 5: TreeMap
Sentiment analysis shown below reflects a mixed bag of neutral, negative, and mixed sentiments—overall, a gloomy picture.
Table 6: Overall Sentiment Analysis of all 80 transcripts put together
Table 7: Sentiment of the individual transcript, a total of 80 transcripts
Correlation and Frequency Mean Analysis of Motivational reasons – SPSS
Frequency Analysis was performed in SPSS software to understand each motivational reason selected by the respondents to identify the voice of the customer and build a Value Proposition for the firm venturing into building an Online Talent Platform.
Table 8: Frequency Mean Analysis- SPSS on each motivational reason selected by the respondent
Table 9: Frequency Mean Analysis – SPSS – for individual Motivational reason
- The correlation was performed between the Motivational reasons to crystallize the Value Proposition and also impact Value communication to individuals.
Table 10: Correlation between the seven motivational reasons for opting for independent work
- “Ability To Choose Working hours,” ‘Work-Life Balance,” “Flexibility to work online and remote,” and “Level Of Income” came out as Motivational reasons that could be the basis for the creation of Value Proposition across individuals.
Cross-Tabulation Analysis – MS EXCEL- PIVOT & GRAPHS
Table 11: Occupation Map to Motivational reason for opting Independent Work
- ‘Creative and multimedia’ – which constitute 28% of the respondent population, chose “Independence to choose what kind of work you would like to do.”
- Professional Services’ – which constituted 35% of the respondent population, chose “Level of Income.”
- “Software development and tech”- which constituted the balance 38% chose “Flexibility to work online and remote.”
Table 12: Age Map to Motivational reason for opting Independent Work
- Youth (age less than 25) chose “Flexibility to work online and remote.”
- Seniors (age 50+) chose “Level of Income” and “Recognition.” This could point towards the impact of COVID-19, loss of a job, and pay-cuts. But needs to be probed further in subsequent research.
Table 13: Age, Gender, Marital Status- Map to Freelance (Primary Income) to Income Top-Up (Extra Income)
- Youth and Seniors preferred Independent Work as a Primary Source of Income.
- Females and Unmarried respondents – up to 50% preferred Independent Work as Primary Source of Income
Table 14: Occupation Map to Freelance (Primary Income) to Income Top-Up (Extra Income)
- Software development and tech – chose Independent Work as Primary Source of Income.
Table 15: Break-up between Freelance (Primary Income) to Income Top-Up (Extra Income)
- Almost 42% of respondents expressed their preferred choice of Independent Work as a primary income, meaning they would prefer Freelance Work.
Summary & conclusions
Extend Service-Dominant Logic to construct Value Proposition
- Service-Dominant Logic propagates the Co-creation of Value. This requires suppliers, producers, and customers to work closely to create Value in use. This implies the creation of a value constellation, or service ecosystem, a network of participants where we have Actor-To-Actor engagement to Co-create Value.
- Online Talent Platforms are driven by digital technologies and therefore allows such level of interactions in a service ecosystem. Co-creation of Value is a concept from Service-Dominant Logic that can be extended to ‘Gig’ or ‘Platform’ or Online Talent Platform.
- Service-Dominant Logic also propagates that firms create a Value Proposition. But the Value Proposition is not created by the firm and communicated to the customer. But it involves listening to the customer, understanding their requirements, and then constructing a Value Proposition.
- Extending Service-Dominant Logic, we have therefore added to the knowledge of Value Proposition creation using Service-Dominant Logic thru a Focus Group interview and analysis. This paper has provided a method of listening to the customer and their sentiments to construct a Value Proposition as a firm centered around the customer.
- Seven Motivational reasons were identified for individuals to opt for Independent Work, and we reviewed that (Table 10- Correlation Analysis) (a) “Ability To Choose Working hours.” (b) ‘Work-Life Balance” (c) “Flexibility to work online and remote.” (d) and “Level Of Income.” came out as Motivational reasons that could be the basis for the creation of Value Proposition across individuals
- Based on Sentiment Analysis, we identified that the following are key inputs to the Value Proposition of ‘Gig’ or ‘Platform’ or Online Talent Platform (Table 3): (a) Quick Search (ability to search jobs quickly online) (b) Team-rooms online (collaboration online) (c) Learning new skills and training (online)
Extend Service-Dominant Logic to communicate Value Proposition
- Based on Cross-Tabulation analysis, we identified the key communication that can be designed to communicate Value Proposition to individuals (Table 11 to 14): (a) For specific occupations, for example: ‘software development and tech’ run communication and campaign around the merits and advantages of “flexibility to work online and remote.” (b) Similarly, age-wise communication: for example: “Freelance” work merits to Youth and Seniors.
Homburg, C., & Jensen, O. (2007). The thought worlds of marketing and sales: Which differences make a difference? In Journal of Marketing. https://doi.org/10.1509/jmkg.71.3.124
Lawson, R., & Wooliscroft, B. (2004). Human nature and the marketing concept. Marketing Theory. https://doi.org/10.1177/1470593104047641
Sivakumar, K., & Nakata, C. (2001). Instituting the Marketing Concept in a Multinational Setting: The Role of National Culture. Journal of the Academy of Marketing Science.
Ballantyne, D., & Varey, R. J. (2008). The service-dominant logic and the future of marketing. Journal of the Academy of Marketing Science. https://doi.org/10.1007/s11747-007-0075-8
Viswanathan, M., Rosa, J. A., & Ruth, J. A. (2010). Exchanges in Marketing Systems: The Case of Subsistence Consumer–Merchants in Chennai, India. Journal of Marketing. https://doi.org/10.1509/jmkg.74.3.001
Vargo, S. L., & Lusch, R. F. (2006). Service-dominant logic: Reactions, reflections, and refinements. Marketing Theory.
Vargo, S. L., & Lusch, R. F. (2004). Evolving to a New Dominant Logic for Marketing. Journal of Marketing. https://doi.org/10.1509/jmkg.184.108.40.20636
Vargo, S. L., & Lusch, R. F. (2008). Service-dominant logic: Continuing the evolution. Journal of the Academy of Marketing Science. https://doi.org/10.1007/s11747-007-0069-6
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