 Now, we will look at how different functions of HR will look like in gig economy form. So, first is a workforce planning. Workforce planning in a way is the core HR work for any gig economy form. Because intermediary platform forms must know when the demand will come, where demand can come, how to engage requesters and how to engage the service provider. In order to scaling up, that is what they need to know because the scaling up for the gig economy form is nothing but enhancing their network. And enhancing their network, nothing but identifying the requesters and tracing, looking at the chain where the maximum requesters are available or in which season or for which particular service requesters are available and the customers are available. They use the services, they make use of the intermediary services and they have certain ways of managing the workforce planning and drawing the benefit of appropriate workforce planning. One is search price. If on certain time of the day, the demand of the taxis or demand of the Zomato service provider increases, they can increase the price for that particular point of time. That has potential to impact both the demand and supply of the requesters and service providers and customers. They do workforce planning and in strengthen their workforce by marketing campaign. So, initially they give lot of offers. In fact, many very famous effective gig economy firms are actually loss making, they keep making losses for many years or for few years till the time people become habitual of their services. Then they also use the techniques of the temporary price reduction. This generally happens in the time of the slack or in the time of entry into the market. Once people are familiar, they experience the convenience provided by the platform, then they can increase the price. So, seen from the ecosystem perspective, this creates a multilateral value benefiting all ecosystem actors involved. So, all these three things eventually help all three entities of the gig economy firm. Second is recruitment and selection. Seen from the ecosystem perspective, it is important that the recruitment of both actors run in parallel to avoid mismatches in the supply or demand of the labor. So, they need to recruit the service providers. They also need to recruit the end customers. In some cases, the careful recruitment is required. In some cases, general recruitment process is good enough. For example, Uber, the task is very structured. You check the availability of the driving license and anyone can become the Uber partner. But if click worker has to ensure that they properly match the software developers or web designers with the customer who approach their platform, they must know the capacity or competence level of their requesters. So, they need to do the conscious selection of the requesters for a particular task offered by a customer. So, they need to in fact do the grading as well. What is the level of that complexity one requestor can handle in comparison to another one? And accordingly, they need to connect the customers and the requestors. Training and development is also like that. It is done extensively. Sometimes, it has to be done extensively sometime to ensure that service delivery remains at a optimum level. So, training for gig workers and training for the requesters both are important. Training for the gig workers example is of the Uber driver. They are offered instructions on how to improve their passenger ratings and earnings while online intermediaries may offer pre-employment training to enter in project managers. So, Uber drivers, they are the gig workers, they can be, they many times are required to provide the training so that they can satisfy their customer better. Another example is in the New York City, Uber does require poor performing taxi drivers to attend training sessions. You must have noticed that there is some basic training is given even to the drivers, even to the Zemato gig workers about the courtesy, about their customer interaction, about the process they have to follow. Training and development is not only required for the gig workers, it is required for the requestors as well. For instance, a meal delivery platform like Delivery or Uber Eats, they instruct their requestors and who are the requestors? Requestors are the restaurant. So, they train the restaurant on working on the algorithm to ensure that meals are ready on time when the gig worker approach them so that the gig workers time is not wasted and this restaurant can also serve large number of customers. So, training is required for gig worker as well as the requestors. Performance management, now performance management in most cases is achieved by setting of the performance levels and using the requestor feedback to rate the gig worker performance. It works in two ways, first the star rating, so that helps in tracking the performance. Second gig worker create the value for the requestor and requestor is given some autonomy to release the payment of the gig worker only after ensuring that desired service is offered, services service is delivered, product is delivered of the desirable quality. So, a star rating often add to the reflect the gig workers online reputation which locks the gig worker into the ecosystem and generally ecosystem cannot take their online reputation to another platform. So, for example, on Uber some driver has accumulated certain reputation in the form of rating. So, this remains locked for the for a particular company pertaining to one requestor. Second performance rating should ensure that gig workers create value for requestor because these rating are used to allocate future gig as a basis for refusal or access to the platform ecosystem. So, this rating decide whenever the next service opportunity occurs who amongst the available gig workers get that opportunity, so that is a very stringent performance management system because it is constantly given by the customers and user or the requestor. Rating is not only given to the gig worker or the requestor. Ratings are also done for the requestors and for the end user as well. The rating is not only given to the gig worker requestor, but it can also be given to the end customer. In the example of Uber end customer and requestor are the same the gig worker is the driver. They have in 2008 applied for a patent based on some artificial intelligence technology to check whether the customer of the Uber has consumed excessive level of alcohol or not. And they did it with the use of the way customer is holding the phone has held the phone while booking the taxi or how many mistakes he has done while feeding the information to book the taxi so on and so forth. So, they have identified some indicators and using the artificial technology artificial intelligence technology. They developed a patent patentable IPR to check the rating to check the this aspect of the consumer and based on that they can give rating to the end user. That happens in the OLA as well because it is not only us who give rating to the driver, driver also gives rating to the customer compensation and benefit that is a most perhaps the most crucial aspect it is the reason why people engage with the platforms. So, in terms of the compensation requestor's compensate for service provided by gig worker and for the effort spent by intermediary to match supply and demand for the labor. To ensure that gig workers live up to the requestor's expectation intermediary platform firms may grant requestor the possibility to hold back payment from gig worker when they feel gig worker's performance is below par. There is another way of ensuring control through compensation from the ecosystem perspective it is important that gig workers find the level of compensation beneficial and appropriate and that is why some platforms are ensuring that their gig workers get at least the minimum level of the wage. Intermediary firm may also ask requestor to provide gig workers with secondary benefit. For example, the delivery ecosystem restaurant they provide coupons and discount to the gig workers in return for their active contribution in the ecosystem. So, that becomes another form of compensation for the gig worker. So, compensation and benefit also you can see is affected by it is controlled by not only the platform, but by the requestor as well. What are the competencies required for HR to carry out these processes effectively? Number one workforce analytics and insights they lead to better decision system and they lead to more personalized experience and personalized treatment and that is the very important competency HR need to have. They need to incorporate multi and cross-disciplinary perspective. So, they need to understand marketing, supply chain, technology mediation, customer behavior, stakeholder management in order to carry out any HR activity. Whether it is benefits whether it is compensation or benefits performance management recruitment they need to understand this whole phenomena. They need to understand the nature of their ecosystem, the nature of their market from the multi-disciplinary perspective. So, even if even the Zomato has to look at their demand occurring in particular time in particular area, they need to use the econometric model, they need to know what are the social gatherings or what are the social functions going to be organized during that time. They need to know are they are going to be major festivals at that time. They need to market their services according to those occasions. This is pretty cross-disciplinary work which HR has to be aware of. Challenge for HR is how to how do people create an ecosystem in which they learn continuously and still be productive. There is so much data is being created because of the coordination and collaboration involved in the gig economy firms that they need to constantly churn the data and constantly track the taste of the customers, nature of the technology, availability of the product, so on and so forth to remain relevant in the marketplace. Because one improvement, one major improvement by the competitor can make one platform, another platform redundant, so they have because all this is based on the IT based technology. An IT based technology, the beauty is that it can be changed very fast. One major innovation can make all other apps redundant in a particular industry, in a particular segment. So, HR need to be constantly looking at the best practices and constantly observing the trained and accordingly manage the HR processes which we mentioned a short while ago. Managing change is very important ability for the HR to perform well in the gig economy firm. HR professional in because of these features have to be very highly digitally savvy. They also need to have the data fluency. The data fluency is explained as a capability to recognize the emotion and take decision based on data. So, you need to recognize if there is dissatisfaction, if there is a complaint, if there is a grievance of a gig worker or requester. But the resolution can be done based on the data and managing data as well as acknowledging and recognizing the emotions of the requester or the customer is very important capability for the HR to perform optimally in the gig economy firm. Third and equally important thing is coaching, maintaining and guidance, developmental conversations. They need to engage with gig workers and requesters. They do not have the platform owners, do not have the formal authority over gig workers or the requesters. So, if they want these people, these partners, these entities to perform well so that whole system can be benefited, they cannot exercise their authority. They need to engage with them in a developmental way and that is why coaching, mentoring, guidance is the only way they can influence the behavior of the requesters or the end customers. So, HR activities in gig economy are designed to control and ultimately uphold the multilateral exchanges among gig workers, requesters and intermediary platform firms such that all actors are subject to HRM activities. You can see different HRM activities are performed by different actors in the ecosystem. Now towards the end of this session, I would like to highlight, basically these are highlighted by the researchers whose reference I have shown in the beginning of the session. So, I would like to mention about these special issues related to HRM in gig economy forms. First issue is about the life cycle. Life cycle of a platform has a major influence on the relationship or the quality of relationship they have with the gig worker and the requester. When a platform is launched, generally they adopt very friendly policies for the gig workers and requesters. As they reach to the level of maturity, as their network increases, their network effect also increases and they are able to get more income and more profit. In that process, their relationship and their power over gig worker and requester also changes. In the beginning of the launch, most of the gig economy firms invest hugely and they do not incur profit. As the network grows, network effect grows and their prosperity and their profit grows. In that situation, what is the optimum level of profiteering that is unresolved question. Another aspect is of the hybridization of the HRM activities. We in the previous slide also explained different HR activities is conducted by different entities in the ecosystem of these kinds of forms. So, customer give feedback to the driver, driver give feedback to the customers, restaurant give feedback to the gig worker, gig worker give feedback about the restaurant. Platform compile this data, sometimes platform also evaluates the efficiency of the requester and they also look at how much business is given by the requester to the platform and accordingly, they design a differential treatment. So, you can see a lot of HR activities related to benefit in compensation or performance management, they are conducted by different actors. How to integrate these, how to keep these justified and ethical, these are the unresolved questions. A special case of search price on a particular time of the day Uber increases their price. Now, that increase in the price of the taxi or price of the ride, what should be the percentage of the sharing of that between the requester and the platform? Both have their different logic. Someone can say 50-50, but then company may say that we invested a lot in the beginning to build the network and eventually network is beneficial to all the people. Why should not we take major chunk of the search price because that is my pure profit. Driver will say that you have built up network, but it is me who is the requester who is providing the service. So, I am also equally important. So, why you should keep the biggest chunk? Likewise, these are some special cases which need resolution and HR has to work actively in resolving these issues in all the gig economy forms. HRM activities or bundle thereof are used to uphold the different types of ecosystem. So, Uber's ecosystem is different, Zomato's ecosystem is different, Baiju's ecosystem is different. What are the good HR activities? Are their activities, good HR activities relevant to all major platforms or which are the special HR activities especially relevant for a particular platform that needs to be studied. Lock in gig workers for a certain period to ensure that they continue taking part in the multilateral exchange. How it can be dealt ethically? This is also an answered question and each company has to figure out their own solution pertaining to locking in the gig workers. So, in this session we looked at the nature of the gig work, gig economy firms and what are the challenges of the HRM? How the different functions of HRM have changed drastically in these firms and what are still undissolved issues in that and what is the perspective, the systems perspective what we discussed likely to be useful in addressing some of the HR related issues in the gig economy firms.