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Fate of gig workers could turn on ballot question – Korea Times




When the pandemic struck Indonesia, urban gig workers were hit the hardest




“We know what can end poverty. But how come poverty never diminishes?” was the reply I received from Harry, who works as a gig worker in a city in Scotland when we were discussing poverty. The reason I specify his identity is because it is significant to what I am about to elaborate.

Indonesia’s rural poverty has always been higher than in the cities. In September 2019, urban and rural poverty hit 9.86 million and 14.93 million people, respectively. But when the pandemic struck, more households were plunged into poverty. As of March 2020, the urban and rural poor were already 11.16 million and 15.26 million, respectively.

The spike in rural poverty was not as high as in urban areas. Does this mean that urban communities are more prone to external shocks? Maybe. But we should dig deeper, deeper, and deeper. Based on the Statistics Indonesia (BPS) database, there is not much disparity in bi-annual poverty trends between urban and rural areas. Even though poverty is much higher in Indonesian villages than in cities, the pace is quite similar. So, what makes March 2020 different? Both areas were hit by the same pandemic, but why was the spike in urban poverty four times larger than in rural areas?

There might be a lot of plausible reasons behind this, but perhaps we should examine what has been sitting in front of our eyes: the unequal geography of the gig economy in Indonesia, which, in the case of COVID-19, protects rural areas from more poverty cases.

The gig economy is mainly concentrated in urban areas, where people are no longer in the process of catching up — they are already there. Gig workers represent 5% of Indonesia’s workforce. The majority of them work in urban areas. They were among the main recipients of the negative effects of COVID-19.

On the other hand, Indonesia still has much homework to do for its villages. It needs to improve infrastructure, education, access to health services — all of which can pave the way to ending poverty. The slow progress in meeting these needs leads to an automatic rejection — or slow absorption — of innovations in employment and economic activities. The low concentration of the gig economy in rural areas corresponds to a smaller presence of COVID-19 infections in rural households, whose incomes are slightly above the poverty line.

So, what does that tell us about the nature of the gig economy and poverty in Indonesia? The answers are threefold.

First, gig economy work in Indonesia is extremely fragile — it exposes workers to the risks of living in poverty after giving them a taste of heaven for a split-second. Gig workers can be independent contractors or contract workers at big firms, other forms of temporary workers, or online platform workers. The new poor in urban Indonesia mainly come from online platforms.

Digital labour platforms, such as ride-hailing services, were supposed to bring more job opportunities to low-income families. And that was at least what we thought had happened. Nevertheless, by seeing the concentration of digital innovation, it looks as if profit always outweighs any social motive.

Second, the disproportionate levels of the gig economy between rural and urban Indonesia makes the low innovation in rural Indonesia more evident. In the case of COVID-19, the lack of innovation acted as a buffer against poverty, but it might also be the reason behind rural Indonesia’s slow progress in reducing poverty. Innovation has a blank face. Whether it turns out to be good or bad depends on how we make use of it. Before intensifying innovation in rural areas, the government ought to design social protection policies for all kinds of gig labourers.

Third, it is time to put an end to the stigmatisation of rural communities implying that they are backward, with low ability to succeed, and that “rural” means poor. Regardless of country or province, “rural” is associated with third world nations. Looking at the unequal geography of the gig economy, prejudice is another reason why innovative projects rarely target rural areas.

This is our life now. The life we had prior to digital innovation has become history. We can study it, but we no longer live in that period. Whether we want it or not, temporary and remote working are becoming the new normal. That will eventually reach all Indonesian villages. But even if we already know what is going to happen, there is no harm in coming up with a plan. Because odds are, digital innovation in rural areas will intensify inequality of income and deepen poverty.

Local governments in rural areas must promote innovation, but they should also prepare the buffers that will protect gig workers from economic turbulence and smoothen the transition to the gig economy.

To begin with, local governments must build a foundation for employment innovation. This includes creating a mechanism to bring equality between gig and non-gig workers, such as establishing shared social protection responsibility between rural governments and employers in the case of workers coming from poor or low-income families.

Harry’s comment that poverty never decreases, although not entirely accurate, bears some truth. We know that education is key to poverty eradication, and access to finance can expand people’s mobility and improve their livelihood.  Yet the reason why poverty rates remain high is that policymakers fail to adapt poverty alleviation policies to contemporary forms of livelihood. Accurate poverty-targeting strategies are not merely about serving those who live below the poverty line; they are about understanding poverty. And the gig economy is one of the many faces of poverty.



  • This blog post is an edited version of an article that appeared first in The Jakarta Post, and is reproduced here with permission from the author and the newspaper.
  • The post expresses the views of its author(s), not the position of LSE Business Review or the London School of Economics.
  • Featured image by Fikri Rasyid on Unsplash
  • When you leave a comment, you’re agreeing to our Comment Policy

Namira Samir is a PhD candidate in human geography and urban studies at LSE.





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Bringing In a Seamless Technology-Based Hiring Programme for Gig Workers




5 min read

Opinions expressed by Entrepreneur contributors are their own.

You’re reading Entrepreneur India, an international franchise of Entrepreneur Media.

With the pandemic around the world restricting our movement and physical behavior, how do you ensure large-scale hiring of gig workers? Gig economy is one of the few sectors gaining demand and to match the supply it must have a quick and efficient on-boarding process.

The traditional hiring methodologies are passé, to speak the least as they don’t support the scale of hiring gig workers. The unstructured and manual verification processes cannot provide quality assessment of the on-boarded workers. This is true across the industry—cab aggregation, food delivery, logistics or professional service marketplace.

The challenge

Gig economy companies need to hire verified workers with clean background to mitigate risks of employee fraud or customer harassment. The challenge is that delay in on-boarding means potential business loss. And with pandemic around, the physical dependencies are making it more difficult to background check and onboard gig workers quickly.

Any future-ready organizations in gig economy must lay a strong foundation of on-boarding workforce that meets their dynamic needs at a large scale.

Automation is imperative to remain competitive in the current scenario

Authentication technology and digital workflows are solving this problem. A seamless integration of technologies delivered on an easy-to-use dashboard can do the trick. Real-time verification and process automation can be used to seamlessly digitize and allow remote and paperless on-boarding.

Background check: Organizations need to validate identity, criminal background and address of the candidates. Technologies such as AI/ML, facial recognition, OCR and deep search can deliver these verifications remotely.

Automation technology integrates databases, online document collection and verification. Once the IDs are verified and no criminal history is found, then the address of the worker is verified digitally via geo-coordinates.

Onboarding: Automation of document collection, data transfer and data enrichment can reduce on-boarding time drastically. This combined with electronic signatures means truly paperless processes and no redundant documentation.

Recent developments in recruitment technologies have effectively helped in managing the hiring processes better by focusing on these key points:

Enhanced visibility for better recruitment

With all the reports and the data stored online, it has become easy to not only manage the data over cloud, but it has brought in ease in the analysis domain. Now, the HR need not put in extra hours to first store the physical report and then digitalizing it in a suitable format and then analyzing the same. With the information filled in and stored digitally, the HR can design dashboards basis the desired inputs and can come with hiring based insights at a much faster pace and with minimum manual error possible.

Streamlining workflows to reduce turnaround time of processes

With the hiring process, background verification process and document storage now being online, it has made the whole hiring process digital and more in-sync. Earlier while the employee information gathering being online, it still had to go through a manual background verification process and physical document collection and storage process which not only resulted in drop in efficiency but also these process were difficult to manage as they were not synced up. But with all these processes online, their workflows can now be streamlined and synced together to give a more seamless experience.

Centralizing the whole recruitment process and mitigate risk

With the complete hiring process digital, streamlined and synced up on a common platform, it has helped in making the whole recruitment process centralized. This has not only helped in reducing the turnaround time in the various processes involved but has also helped in improving efficiency, making the data ready for analysis, reducing errors during manual handling and storage of physical data. With all the data stored online, it is easy to check the audit trail to verify the data handling process alongside making the processes to being integrated with future technologies that might come up in the domain.

One can say that big changes could be coming to the gig economy. With the ever-changing regulations in the sector, it becomes critical for the companies to pay close attention to whether their gig workers feel empowered or exploited. Effective workforce management, that includes employee onboarding as well, will become more important than ever. As more employees on and off-board, companies will want to keep a close eye on the constant alignment of talent supply and demand.

Cloud-based systems that put all that information in one place will continue to play a big role. And more than ever, employee experience will be a differentiator. With so much competition for talent, experience will be even more important. They will want to work in systems that use machine learning to understand to come up with insights that will help in managing and recruiting workforce in a better way. Gig workers have a myriad of opportunities at their fingertips, so anything companies can do to keep them on board will help build retention.

To say the least, technology is not only making the whole hiring process simple, it’s also delivering a seamless experience to hiring teams and candidates along with helping the HR in building stronger retention strategy.

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Gig worker employment fights like those in California pit flexibility against a livable wage – but ‘platform cooperatives’ could ensure workers get both




Voters in California will decide in November whether Uber drivers and other gig economy workers should be considered employees or contractors – a question that’s been debated and litigated for many years now.

On the surface, the issue pits the flexibility that comes with being independent against the higher incomes and benefits that employees tend to get. Uber, Doordash and others say the proposition they put on the ballot in California would split the difference by keeping them contractors – “with benefits.”

I’ve been studying gig labor for nearly a decade. Since 2013, I’ve led teams that have interviewed more than 200 workers on platforms such as TaskRabbit, Postmates, Uber and other apps to learn about their experiences, earning patterns, desires and constraints.

I believe there is a better way to marry flexibility with a livable wage.

What workers want

It’s true that gig workers want flexibility, autonomy and life without a boss. But my team and I also found that the lack of benefits and available work mean it’s almost impossible to earn a reliable primary income on these platforms.

Those who tried to earn a full-time living on the platforms typically made less than the official poverty line, even when their hourly wages were decent. A separate 2020 San Francisco study found that ride-hail drivers were earning US$360 per week, after expenses. That’s $9 an hour for a 40-hour work week – and even less for the majority who work more than that. Almost half of the ride-hail and delivery workers in that study could not cover a $400 expense without borrowing.

These poor conditions support our conclusion that succeeding on these platforms generally requires having at least one other job, often a conventional one that includes some benefits. In other words, the platforms seem to be free-riding on the backs of conventional employers.

But we also saw how good this kind of work could be – under the right circumstances.

Reluctant employees

To protect gig workers, California enacted a law last year that properly reclassified them from independent contractors to employees. It went into effect in January 2020.

Employment status makes the job more remunerative and less precarious by guaranteeing a minimum wage and numerous benefits. But the gig companies warn that it will eliminate the flexibility that workers like about gig work. Legal scholar Veena Dubal found that many workers came to support this reclassification as employees reluctantly, and only because conditions had become so dire.

In response, Uber and Lyft threatened to leave the state unless voters enact Proposition 22. If it passes, the proposition would exempt ride-hail and delivery workers from the California gig economy law but would also offer some benefits. It claims to guarantee pay equal to 120% of the California minimum wage, which is currently $13 an hour.

But independent researchers at the University of California at Berkeley have calculated that Proposition 22 would likely guarantee a wage of only $5.64 an hour, and many workers would be excluded from the various insurance benefits the proposition would provide.

A man checks his phone to locate his Lyft driver at Los Angeles International Airport
Lyft and Uber have threatened to leave California if they’re forced to make their drivers employees.
Al Seib/Los Angeles Times via Getty Images

Worker cooperatives

My own research points to a different approach that retains worker flexibility but also gives workers a say in how the business operates – not to mention a real financial stake in its success: the platform cooperative.

Like any cooperative, a platform co-op is an enterprise jointly owned and controlled by its workers. Platform means the workers use an app or website to connect with one another and organize services for users.

Sociology doctoral student Samantha Eddy and I conducted a study of a platform cooperative in Canada called Stocksy United. It’s a stock photography company in which the contributing photographers are considered independent contractors but also own shares in the cooperative. There’s a small management team, but major decisions are voted on by the artists.

Members told us they are far happier than when they worked for the “Uber” of their industry, Getty Images, and earn much more for each photo sold. One reason for their satisfaction is that, like many platforms, Stocksy hosts a wide range of collaboration styles, from hobbyists who contribute the occasional photograph to professionals who invest large sums in shoots. This gives members the freedom that many seek from platform work.

All members get a say in the company’s governance, though in practice only a few hundred of its roughly 1,000 members are active in the company’s forums, where issues are discussed and voted on.

A key component of Stocksy’s success is that its founders already had extensive industry experience and knew the platform model and its technology. Another element was that it began with a $1.3 million loan from the founders. Lack of financing is a chronic impediment to the establishment of cooperatives, whatever the industry.

[The Conversation’s science, health and technology editors pick their favorite stories. Weekly on Wednesdays.]

Another chronic problem in the gig economy is that too many workers chase too little work, a phenomenon that has been particularly acute among ride-hailing services. It arises in part because most platforms allow almost anyone to join. Our ongoing but unpublished interviews with gig shoppers and delivery workers find that this imbalance has intensified during the pandemic.

To avoid this problem, many co-ops, especially in driving, delivery and cleaning, limit membership and only expand with the market. That’s a major boon for workers who depend on their app-based incomes for rent, food and other basic expenses.

Platform cooperatives are a bit younger than the gig economy, which began around 2009. So there aren’t many yet. But there are examples in bicycle delivery, ride-hail services, cleaning and health care.

There’s no reason to expect the likes of Uber and Lyft to ever convert to a worker cooperative. But if they were to go that route, our interviews suggest workers would be better off.

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