1 Introduction

Migration to a foreign country for better employment and standard of living is very common for the people of any developing country as the remittance comes from the migrated workers for those developing countries. On the other hand, globalization is one of the important factors for labor migration which is necessary for organizations because the traditional labor market has some limitations (Jäger et al., 2019). Almost 281 million people lived outside the borders of their countries in 2020 (UN, 2023) and there were 169 million migrant workers all over the world in 2019 (ILO, 2021a). According to The International Convention on the Protection of the Rights of All Migrant Workers and Members of Their Families (ICRMW), a migrant worker is a self-employed person who works for another country for better pay (ILO, 2023). High-skilled migrants are those workers who have educational qualifications or specific occupations with advanced training or soft skills (Nathan, 2014). As a result, a mixed background of people is available for migrant workers where different income levels, skills, employment status, areas of work and others are in their backgrounds (ILO, 2023).

Working online is necessary for migrated workers when conflict between countries arises and the internal environment of the countries becomes hostile (Lynn et al., 2021). Furthermore, the nature of work is changing fast with the help of digital collaborations which leads to the growth of a new economy of online platforms like crowdsourcing or gig economy (Harris & Krueger, 2015; Mainka et al., 2023; OECD, 2018) that has created a new form of work that can be done from remote places (Bazaluk et al., 2022; Kenney & Zysman, 2019). Crowdwork and work-on-demand via apps are the two main streams of the gig economy and workers can work on these two streams with flexible workloads and work schedules (De Stefano, 2016; Smith and Leberstein, 2015; Olejarz et al., 2018). Most of the crowdworkers need adequate soft skills and educational qualifications to complete tasks in the crowdsourcing platforms (Margaryan, 2019). Here, crowd workers are more specifically known for performing small and simple tasks or microtasks of a large independent project through the Internet (Berg et al., 2018; Cantarella and Strozzi, 2021, Zayed et al., 2022a). However, the use of an Internet platform is necessary for crowdwork where a large number of individuals and organizations around the world are connected to this platform connecting workers and clients (De Stefano, 2016). Moreover, workers in crowds are connected through online platforms where employers can solve their problems in a cheaper way (Prassl and Risak, 2015).

The new term “crowdsourcing” originated in the last decade to make outsourcing into a focused area. Jeff Howe, for the first time, used the word “crowdsourcing” in a Wired Magazine article in June 2006. Howe (2006) described it as “the act of taking a job traditionally performed by a designated agent (usually an employee) and outsourcing it to an undefined, generally large group of people in the form of an open call”. The definition of crowdsourcing given by Jeff Howe is very clear at the initial stage. Later on, the understanding and definition of crowdsourcing become unclear among the researchers within a few years after the definition given by Howe (Estellés-Arolas and González-Ladrón-de-Guevara, 2012). As a result, they have done a systematic review of the literature and used the Delgado approach to find out a clearer and wider definition of crowdsourcing covering the maximum crowdsourcing processes that existed in the literature. According to Estellés-Arolas and González-Ladrón-de-Guevara (2012), crowdsourcing means an organization or individual offers voluntary tasks to a group of individuals having different backgrounds and locations through online participative activity by open call. However, Xu et al. (2015) conducted an empirical study to show that the organizations which were using crowdsourcing technologies had better performance. Finally, it was very clear that crowdsourcing would help the organizations to improve the quality as well as quantity of work.

Hosseini et al. (2014) identified four important things in crowdsourcing after reviewing the literature on crowdsourcing which are the crowdworkers, the crowdsourcer, the crowdsourcing task, and the crowdsourcing platform. Crowdworkers are those workers who are unknown on the Internet to complete outsourced tasks (Walter et al., 2022). The success of crowdsourcing depends on the performance of crowdworkers (Behl, 2020). The number of crowdworkers increased exponentially because of crowdsourcing platforms (Meijerink and Keegan, 2019). Approximately 4.8 million workers were active on crowdsourcing platforms by the end of 2013 (Kuek et al., 2015), and around 19 million crowd workers were connected to crowdsourcing platforms actively at the end of 2020 (Kässi et al., 2021). Here, the growth of crowd workers was significant for the total labor force. The necessity of crowdworkers reached a peak during COVID-19 when working from home became a must for the workers (Stephany et al., 2020).

Few systematic literature reviews on crowdsourcing have been done in the past. The scope of those reviews was very wide and covered almost all areas of knowledge. For example, Hossain and Kauranen (2015) took 346 articles on crowdsourcing to conduct a comprehensive review and found that Scholars from Germany and the USA had made the highest contribution to crowdsourcing, whereas some developing countries, like China and Brazil, have some activities regarding crowdsourcing in the literature. If we limit the scope to crowdworkers or migrant workers, we will get very few works in literature. Therefore, the objective of this paper is to explore the research trends on online migrant workers in the crowdsourcing literature with research gaps, opportunities and challenges associated with the utilization of high-skilled migrant workers in crowdsourcing platforms. Moreover, this study has made several contributions to researchers, employers, and policymakers. First, this study shows the initial stage and current stage of work for crowdsourcing from the perspective of online migrant workers. Second, this study provides suggestions related to online high-skilled migrant workers for future researchers in crowdsourcing platforms. Third, policymakers and employers can utilize the opportunities and face the risks connected with the high-skilled migrant workers in crowdsourcing platforms.

This study has been conducted to analyze the current literature on crowdworkers and migrant workers of crowdsourcing. A total of 28 research papers were selected for extensive analysis on crowdworkers from the top six databases of journals. The research questions for this study are:

Q1) What are the research trends on crowdworkers or migrated workers of crowdsourcing in literature?

Q2) What are the main concentrations and connections between papers on that specific topic in literature?

This study has several parts, where the first part depicts the selection process of papers for review. The second part explains the historical background of “Crowdsourcing” followed by definitions of “Crowdsourcing”. In the next part, frequencies of words in the abstracts of the papers are shown, and five clusters of research are discussed after reviewing the research papers on the selected topic. In the fourth part, future directions for the researchers are revealed in the discussions. Finally, the conclusion illustrates the contributions to policymakers, businesspersons, and researchers.

2 Methodology

A systematic review of existing literature is the best way to know the present work done by the researchers and the research gaps in the current literature (Kraus et al., 2021). Kunisch et al. (2018) explained that a systematic literature review should have five areas: (1) types of review and purposes (2) selection of data (3) evaluation and summary (4) use of findings and (5) validation and evaluation. In the first area, a pure systematic literature review has been used in this study to reduce the bias. In the next area, literature has been collected from six good quality databases of journals such as Springer, Taylor & Francis Online, Emerald, JSTOR, Wiley Online Library and ScienceDirect accessed on December 30, 2022. The following keywords were used to search research papers: “crowdsourcing” AND (“migration” OR “migrated worker” OR “crowd worker” OR “crowdworker”) AND (“Business” OR “Management” OR “Economics”). “Crowdsourcing” was the main keyword for searching articles with “Crowdworker” as the specific area of crowdsourcing and only those articles that were selected which are relevant to management and economics. 5067 listings were found in total after searching the specific keywords in these six different databases. Finally, 28 articles (only 0.55% of an initial number of listings) were selected for assessment and synthesis purposes after considering journal papers, subject area, English language, titles and abstracts (Table 1).

Table 1 Papers collected from different databases with selection criteria
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In the third area, Voyant Tool program was used to represent high-frequency words in the literature and the literature review map was created based on a thematic analysis of the existing literature. This map is an important tool for the SLR process to explain the connection between thoughts and ideas of the researchers (Kraus et al., 2020; Suchek et al., 2021). In the fourth area, future directions for the researchers, policymakers and entrepreneurs were given. In the fifth area, the selection process of articles for review is shown in detail so that other researchers can verify when necessary.

3 Origin and the concept of crowdsourcing

The people of the world are connected with web technologies where frequent communication is very common. One of the recent buzzwords in web technologies is “Crowdsourcing”, and that word is gaining popularity day by day. The idea of “Crowdsourcing” first came into the mind of Jeff Howe, a contributor to Wired Magazine as well as an assistant professor at Northeastern University in the USA, who published an article named “The Rise of Crowdsourcing” in Wired Magazine in June 2006. Howe (2006) explained the term as assigning organizational works to an undefined group of people who are connected within the network. Howe’s definition was quite clear at the early stage. He again published a book named “Crowdsourcing: How the Power of the Crowd is Driving the Future of Business” to explain deeply about his new concept in 2008, and that book was translated into ten languages for the dissemination of the new concept.

Researchers have been showing interest in this particular field since the inception of the new concept developed by Jeff Howe. We have seen many empirical and conceptual studies on crowdsourcing by researchers for the last ten years (Ghezzi et al., 2018). Figure 1 describes the connections among concepts and ideas presented by the researchers overtime at the early stage of literature.

Fig. 1
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Literature review map (early stage)

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4 Current studies on crowdsourcing in the light of crowdworkers

Researchers have done some studies on different issues regarding crowdsourcing and crowd workers from the inception of these ideas. Some researchers studied on features of basic elements of crowdsourcing, strong and weak points of the literature, factors of the crowdsourcing model, performances and benefits of the organizations using the crowdsourcing model, risks of crowdsourcing, the satisfaction of crowdworkers, ethics of users of the crowdsourcing platform and many more (Fig. 2). Figure 3 describes the highly frequent words on the selected topic occurring in the abstracts of these 28 articles. The most frequent words are: work (73); workers (48); crowdsourcing (39); crowdworkers (37); platforms (28).

Fig. 2
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Literature review map (current stage)

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Fig. 3
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Frequency of words in the abstracts

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4.1 Basic components of crowdsourcing

Initially, researchers researched to find out the basic components or elements of crowdsourcing. Saxton et al. (2013) explained that crowdsourcing is the combination or intersection of three components such as crowd, outsourcing, and social web. Afterward, Hosseini et al. (2014) identified four basic cornerstones in crowdsourcing after reviewing the literature on crowdsourcing such as the crowd, the crowdsourcer, the crowdsourcing task, and the crowdsourcing platform. They have identified features or attributes of these four cornerstones of crowdsourcing. Again, Zakariah et al. (2016) considered crowdsourcer, crowdworker, and crowdsourcing platforms as components when they developed a model to show the factors of the crowdsourcing model. They found many factors under the crowdworker’s perspective, such as motivation to participate, regulations for protecting crowdworkers from any kind of injustice, infrastructure in crowdsourcing, knowledge, skills and experience in ICT, payment and incentives, trust towards platform and quality of task completed.

4.2 Factors affecting performance of crowdworkers

Karim et al. (2017) analyzed all the constructs of past literature that can affect the performance of crowd workers and ranked all the determinants of the crowdworker’s performance. They conducted two types of factor analyses that are exploratory factor analysis and confirmatory factor analysis to get results from the analysis. Their study will help researchers to develop a managerial control system (MCS) that is related to the expectancy theory of motivation to find out the motivation and capability of crowd workers toward performance. Subsequently, Hornuf and Vrankar (2022) conducted a meta-analysis to know the hourly wages of crowdworkers in different categories. Ye et al. (2017) investigated the relationship between payments of crowdworkers and qualities of performance using the concept of PFP (Perceived Fairness in Pay) by using ANCOVA, MANCOVA, and Sobel test. Their study explained that increased payment had an indirect impact on the quality of performance of the crowdworkers. But the major limitation is they had considered one crowdsourcing platform and very specific crowdworkers in the United States only. As a result, cultural differences and real explanations are ignored in the study. Davis et al. (2014) conducted an empirical study on 6000 online freelancers in Russia who were teleworkers as well as independent contractors to know about satisfaction in the working environment. They found that workload is negatively influencing satisfaction, less responsibility in the family drive to high satisfaction, and these conclusions are somewhat subjected to gender. Furthermore, Deng and Joshi (2016) took 55 crowd workers from Amazon Mechanical Turk (MTurk) by applying the revealed causal mapping method to know the perceptions of crowd workers. They found seven constructs are important for the crowd workers’ participation in the crowdsourcing work environment. The seven constructs are crowd work context, crowdsourcing task characteristics, crowd worker needs, digital work control, hedonic outcome, work value outcome, and CS satisfaction outcome. They have only considered micro tasks from one crowdsourcing platform, which is the major limitation of the study.

Bucher et al. (2019) showed that the work engagement of crowd workers is positively connected with the importance of crowd workers where interaction, reliance, and social recognition are less connected. Moreover, Behl et al. (2021) showed the productivity of crowdworker increases when a higher quality of information is provided through game elements in work. Wong et al. (2021) did research to show the relationship between online feedback and the creative performance of a crowdworker. On the other hand, Ma et al. (2021) demonstrated how and why earnings and the long-term relationship of a crowdworker are connected with participation behavior within the community. Then, Osterbrink and Alpar (2021) conducted a study to explain the reasons for the silence of crowdworkers in online feedback systems and the impact of silence on the quality of work.

4.3 Ways of receiving benefits from crowdsourcing

Identifying the required skill sets for crowdworkers is the precondition for better crowdsourcing performance. Few researches have already done on crowdsourcing to find out the required skills of freelancers. Good intention and behavior are a must for freelancers in crowdsourcing. Yusoff et al. (2016) described the roles of integrity and ethics on successful freelancers and entrepreneurs based on an extensive literature review of 121 articles and other sources. They described three forms of integrity: professional integrity, personal integrity and moral integrity. They defined ethics as a set of codes within which a person works, whereas integrity is one attribute of a person. Their literature review explained that success is achieved by ethics and integrity agreed upon by businessmen, institutions and philosophers. At the same time, Durward et al. (2016) were concerned about the ethical issues of crowdsourcing based on existing literature where they followed privacy, accuracy, property and accessibility of information (PAPA) concept. They mainly focused on crowdworkers where individual benefits, ethical issues and conditions are prioritized.

Task assignments are important to get benefits from crowdsourcing. Yin et al. (2017) studied how to assign work considering different skill levels of workers, varying budgets and quality requirements of work. They have designed an algorithm for matching many-to-one situations with high and low quality and budget requirements to get stable outcomes from the workers. They have shown a success rate of completing jobs and achieving the happiness of workers, which is not possible in the existing algorithms.

Risks can be raised in crowdsourcing platforms that can lead to lower performance of crowdsourcing. Liu et al. (2016) did a quantitative analysis of 136 crowdsourcing participants in China to validate the risk of crowdsourcing and examine relationships between crowdsourcing performance and risks. The result was technical system risks and social system risks negatively impact the performance of crowdsourcing. On the other side, Perera and Perera (2014) did a quantitative study on two leading outsourcing providers in the world: one is China (manufacturing sector) and the other one is India (service sector). They urged the necessity of policies and strategies to get proper benefits of crowdsourcing by considering the macroeconomic factors and outcomes of individual participants in the crowdsourcing market, as these two countries will play big roles in the future global economy.

4.4 Suggestions to improve performance of crowdsourcing

Salimun et al. (2015) studied the influence of job providers, crowd workers and platforms on tasks, as these three things are the main components of crowdsourcing to improve the quality of the crowdsourcing industry in Malaysia. According to them, the description of the task affects the quality of the work when we consider the perspective of the job provider. Facilities and design of the task are influencing significantly on the quality of crowdsourcing work from a platform perspective. Again profiles of the crowd workers greatly impact on quality of the work in crowdsourcing when we consider crowd workers’ perspective. So quality is playing a leading role in the growth of the crowdsourcing industry. Kohler and Nickel (2017) found that a large number of organizations are converting their old closed business models into crowdsourcing business models. They closely observed Quirky and Threadless and got the conclusion that the companies face challenges by choosing appropriate value creations from the contributions of a large community. Analyzing these two organizations, they found that recognition is the main motivator in the online crowd and qualities of the value creations are important. They described that co-creating and co-capturing value with the online crowd should be done by logically designing all required components of the business models. They provided seven lessons to the crowdsourcers or the organizations that want to participate in the crowdsourcing market.

Participation of crowd workers will be increased when extrinsic motivation and intrinsic motivation are ensured (Wu and Gong, 2020; Liu et al., 2022). Afterward, Schmidt et al. (2023) explained that crowd workers prefer third-party websites when they work to become comfortable with their identities and to escape any kind of exploitation. Again, Gegenhuber et al. (2022) found that a group of crowdworkers can work together under a specific website to achieve average performance.

4.5 Creating skilled migrant workers through crowdsourcing

Due to the civil wars and political unrest, there has been an increase in forced migration in recent years. It has happened historically before, and the current humanitarian crisis in Ukraine is its most recent manifestation. As a result, even though forced migration is a common historical occurrence, one can argue that current migration events are distinct in that they develop in a context that is rich in information and frequently involves participation (Curry et al., 2019). So, the use of crowd generated data informs people on the migration process and then views such events through an entirely new lens. Crowdsourcing is a method of creating highly skilled individuals in poor countries. Therefore, crowdsourcing may impact both migration patterns and the potential for highly skilled migrants to acquire skills even before they reach the host nation. The contribution of innovative, skilled migrants in promoting a different technology use favors a sustainable smart city (Monachesi & Witteborn, 2021). Although skilled migrants are viewed as rootless commercial sojourners (Cheah, 2001: 135) or as cosmopolitans who are essentially unconcerned with their place of residence. But creative skilled migrants firmly believe in the use of crowdsourcing platforms to create sustainable growth in society.

The accurate number of migrant workers around the world on crowdsourcing platforms is not well informed. A survey conducted by the International Labor Organization (ILO) revealed that 70% of workers in delivery sectors in online platforms or crowdsourcing are migrant workers in Chile and Argentina (ILO, 2021b). On the other hand, many skilled migrants face structural, complex, and systematic difficulties during career development when they migrate to the northern part of the globe (Abkhezr and McMahon, 2022; Zayed et al., 2022b). From this perspective, skilled migrant workers choose the easiest route to start and develop their careers through crowdsourcing platforms or app-based online platforms (Pautuzzi & Benton, 2019). For example, Lam and Triandafyllidou (2022) found that migrants in Canada face many obstacles to enter the labor market though it has the most educated and skilled migrants in the world. As a result, the percentage of migrant workers connected with online platforms is higher in Canada (Lam and Triandafyllidou, 2022). World Bank (2023) has identified 545 online-based platforms for migrant workers where headquarters are situated in 63 countries and clients and workers are situated in 186 countries (Table 2). At least 154 million unique and 52 million active online workers are available around the globe whereas one-third of them have considered online platforms as their main source of income (World Bank, 2023). However, online workers are more educated and more skilled than workers working in the informal sectors. Time management skills, communication skills, negotiation skills, self-confidence skills, and technical digital skills are the important skills required for digital workers to work with online platforms or crowdsourcing platforms (World Bank, 2023).

Table 2 Number of online platforms for migrant workers
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A few popular crowdsourcing platforms have been taken here to study the migration worker rate. Table 3 shows the rate of migrant workers with the total number of online workers for each of the renowned online platforms in crowdsourcing. More than 60% of workers are migrants for the platforms except Upwork.com which has only 34% migrant workers globally and more than 100 nationalities are available for each of the platforms except Guru.com (Table 3). Again, millions of migrant workers are working continuously on these crowdsourcing platforms. The global crowdsourcing economy was $355 billion in 2021 and this figure will become $1.8 trillion by the end of 2031.

Table 3 Popular online platforms for migrant workers
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Language is an important barrier for online high-skilled migrant workers in crowdsourcing platforms (World Bank, 2023). According to the World Bank (2023), the migrant workers of online platforms in China, Ukraine, Venezuela, Argentina, Morocco, and other countries face difficulties communicating in the English language. Additionally, online platforms are dominated by young workers because young workers spend time learning new skills (World Bank, 2023). As a result, middle-aged workers are facing hurdles to cope with new skills in crowdsourcing platforms. On the other hand, most of the web-based platforms don’t offer social protection by insurance coverage, pension coverage and legal issue resolution for their workers (World Bank, 2023; ILO, 2021b; ILO, 2023). Moore (2018) treated crowdsourcing jobs as degraded jobs because she noticed that the workers in online platforms do not have any income security, minimum wage, or regulations towards workers if any problem arises. Moreover, interaction problems between humans, computers, and agents pose a multidisciplinary challenge (Buettner, 2015).

Online workers can earn a significant amount of extra money just by spending 10–19 h a week and around 25% of workers in the crowd worldwide consider online platforms as their main source of income (World Bank, 2023). On the contrary, organizations are emphasizing online labor platforms to attract skilled workers, monitor the activities of workers, and pay the workers (Kässi and Lehdonvirta, 2018; Babu, 2022; Svyrydenko et al., 2023). The demand for online workers is high in developed countries and the demand for crowd workers is growing day by day in developing countries where small, large, and medium organizations use online platforms for online workers (World Bank, 2023).

Scholars in a variety of disciplines, including business and economics, have begun to pay more and more attention to crowdsourcing (Cricelli & Vermicelli, 2022). Migrant Workers' Rights Network in the UK has used crowdsourcing to collect data on migrant worker exploitation and to provide support and advice to workers (Migrants’ Data Rights, n.d.). MigrEntrepreneur (MigrEnt) project in Spain used crowdsourcing to develop an online platform for language learning and cultural exchange among migrant entrepreneurs (Entrepreneurship Development for Highly Skilled Migrants, n.d.). Techfugees organization has also used crowdsourcing to develop and deliver coding and digital skills training to refugees and migrant workers in Europe (Techfugees, n.d.). However, crowdsourcing has been used in various ways to support and empower migrant workers and communities over the years throughout the world.

Some gaps in present research should be addressed in the future. Firstly, the social, economic, demographic, and psychological factors that are influencing the earnings of a high-skilled migrant worker in crowdsourcing platforms need to be addressed. There are significant variations among earnings of high-skilled migrant workers in online platforms. Previous researchers have taken only country-specific data to explore influencing factors of all online workers in crowdsourcing platforms and ignored the data from highly skilled migrant workers. Secondly, a comparison of the performance of high-skilled migrant workers and local workers should be addressed in future literature. It is not clear from the present literature about the performance of high-skilled migrant workers in digital platforms as high-skilled migrant workers comprise more than two-thirds of all crowd workers in crowdsourcing platforms. Finally, the steps and requirements to improve the performance of high-skilled migrant workers in crowdsourcing platforms need to be clarified because the performance relates to the level of income of a migrant worker. Because the requirements and steps are not the same for local workers and migrant workers.

5 Discussions

Ghezzi et al. (2018) found out that crowdsourcing has evolved from two disciplines such as innovation and management. Some researchers have discussed three components, and some researchers have found a maximum of four components of crowdsourcing as crowdworker, the crowdsourcer, the crowdsourcing task and the crowdsourcing platform. However, a skilled migrant worker is not so different from a crowd worker because both of them have educational skills, soft skills and intention to work for international organizations. Furthermore, researchers have found social, web and innovation as the major terms described in past literature when crowdworkers come. Managing these three things is important to implement successful crowdsourcing.

Based on past research, several factors are affecting the performance of crowd workers or online workers. Facilities and designs of the tasks and recognitions of the workers are the driving forces to improve the performance of online migrant workers. In other words, payment of the workers, responsibility towards family members, context and characteristics of the task are important factors to influence crowdsourcing success. In addition, Hossain and Kauranen (2015) made some statements such as motivations of crowdworkers are influential for successful crowdsourcing, low-income people can get extra income by micro-tasking, easy access to the Internet is helpful for crowdsourcing, and disaster management is successful due to the use of crowdsourcing. However, adequate skills like good intention and behavior, ethics of crowdworkers such as different types of integrities, assignments of different tasks based on required skills, and policies and strategies to overcome risks associated with crowdsourcing are really important to get proper benefits from crowdsourcing platforms.

Skilled migrant workers can earn competitive amounts on crowdsourcing platforms so that they can overcome economic hurdles and maintain a better standard of living (Chang & Impara, 2022). Skilled migrant workers in crowdsourcing platforms are not dependent on turbulence within the country or the bad situation of the country. The economy of the country where the skilled migrant workers stay receives a positive impact from those migrant workers. Normally, the workers in online platforms are hard workers and disciplined people which will impact society positively. For that reason, the range of crowdsourcing applications and the various types of crowd works introduced to migratory workers. In conclusion, people from all social classes, ages, and geographic locations choose to work online as migrants. Competitive incentives, motivation, challenging tasks, scalability, and integrity are the major challenges for migrant workers (Moradi, 2019). In addition, language, security, regulations, and adaptiveness are creating problems for migrant workers in digital platforms or crowdsourcing platforms. However, with the increase in crowd work, some several opportunities and risks can be seen for migrant workers and need to be addressed. Findings suggest that crowdsourcing can be a valuable tool for supporting and empowering migrant workers and communities. Nevertheless, crowdsourcing is not a common or established practice of migration research directions for scholars. As a result, a direct connection between crowdsourcing and skilled migrant workers is missing in the literature.

6 Conclusion

The interest in crowdsourcing and the impact of crowdsourcing is growing day by day as we can see the number of articles is increasing year by year from the inception of the new concept developed by Jeff Howe. All researchers agreed that the crowdsourcing model will increase the performance of the business organization with co-creation and co-innovation techniques. Some researchers argued about the policies and strategies need to be improved to cope with the future demands of the world. Some researchers showed some problems in the crowdsourcing arena and also suggested some suggestions to improve the conditions as well. Furthermore, crowdsourcing can help to address some of the challenges and barriers that migrant workers face in accessing education, training, and employment opportunities though no link is explored till to date in studies. As a result, policymakers and entrepreneurs will get a clear idea about how crowdsourcing will help to overcome challenges faced by migrant workers.

In the next few years, we will get the proper implementations of the “crowdsourcing” concept with minimum limitations as there is nothing without limitations in this world. As a result, new and potential crowdworkers or online service providers will require detailed suggestions to overcome initial or future problems in the crowdsourcing market.