Open research questions in Digital Economy and Work Transformation
80 unresolved questions extracted from the limitations and future-work sections of 2,673 Digital Economy and Work Transformation papers in our library. Each links back to the study that raised it.
What the literature leaves open
While this study offers meaningful insights, it has several limitations that present opportuni- ties for future research. First, our data were collected solely from mainland China, which may limit the generaliz- ability of our findings. Future research should test our model in different cultural contexts, particularly in Western countries, to enhance its external validity. Second, while our three-wave design mitigates common method variance, our data remain self-reported. Future studies could employ a strictly longitudinal design to bet- ter capture causal relationships over time or use multi-source data (e.g., leader-employee dyads) to further reduce potential reporting bias. Third, in direct response to the complexity of emerging technologies, a notable limita- tion concerns the measurement of generative AI application. The current study primarily captures the frequency and pervasiveness of AI use. While this serves as a useful starting point, it may not fully capture the qualitative nuances of human-AI interaction. However, this high quantity of use logically justifies our dual-path findings because it reflects the deep integration of generative AI into employee workflows. Deep integration streamlines com- plex tasks as a resource while simultaneously creating adaptational pressure and technical dependency as a demand. Future research must address this by developing more nuanced and multidimensional scales that differentiate between specific types of generative AI use. Finally, our measurement of bootleg innovation relied on a scale with mild wording (e.g., unofficial projects) to reduce respondent aversion. This may have created a slight gap between the measured construct and the strictly non-procedural nature of bootlegging. Future research could develop or adapt scales that more directly capture the unauthorized characteristics of this behavior. Author Contribution Aiwen Xie：Data curation; Investigation; Methodology; Software and Writing. Qing- zhi Zhang: Carding logic; review; language editing. Zhiyuan Yu ：Carding logic; review; editing. Lingfeng Yi: Conceptualization; Funding acquisition Funding National Natural Science Foundation of China, Grant/Award Number: 71972074 Data Availability The data remains confidential for ongoing research as the overall project has not yet con- cluded. However, data that support the findings of the study are available from the corresponding author upon reasonable request.
Stealing Fire or Burning Out? The Dual Impact of Generative AI on Employee Bootleg Innovation · 2026 · DOIAlthough the study provides valuable insights into the role of HR in managing gig workers and freelancers, it is subject to certain limitations. Firstly, the sample size used in the study is relatively small, consisting of only 59 respondents. A larger sample size could have provided more comprehensive and generalizable results. Secondly, a significant proportion of respondents were students. While students may have awareness about gig work, their limited professional experience may affect the depth of insights related to organizational HR practices. Another limitation is the geographical constraint of the study. The research primarily focuses on respondents associated with specific regions and organizations, which may not fully represent the global or national gig workforce. Additionally, the study relies largely on self-reported data collected through questionnaires and surveys. Such responses may sometimes be influenced by personal perceptions or biases. Time constraints also limited the scope of the research. A longer research period could have allowed for deeper analysis and more extensive interaction with HR professionals and gig workers. Finally, since the gig economy is rapidly evolving, HR practices and policies related to gig workers may continue to change over time. Therefore, the findings of this study represent the situation during the specific period in which the research was conducted. © 2026, IJSREM | https://ijsrem.com DOI: 10.55041/IJSREM59040 | Page 10 International Journal of Scientific Research in Engineering and Management (IJSREM) Volume: 10 Issue: 04 | April - 2026 SJIF Rating: 8.659 ISSN: 2582-3930 10. Suggestions / Recommendations Based on the findings of the study, several recommendations can be proposed to improve the • management of gig workers and freelancers within organizations. • First, organizations should develop clear and structured HR policies specifically designed for gig workers. These policies should address recruitment, compensation, performance evaluation, and communication to ensure transparency and consistency. • Second, HR departments should implement structured performance management systems that allow organizations to monitor the productivity and quality of work delivered by gig workers. Clear performance indicators and feedback mechanisms can help maintain accountability and improve project outcomes. • Third, organizations should strengthen communication channels between HR teams and gig workers. Regular check-ins, virtual meetings, and digital communication platforms can help maintain engagement and ensure that gig workers remain aligned with organizational objectives. • Fourth, companies should provide more opportunities for training and skill development to gig workers. Even though gig workers are engaged on a temporary basis, providing learning opportunities can enhance their productivity and build a more capable workforce. • Fifth, organizations should ensure fair and timely compensation for gig workers. Transparent payment systems and well-defined contracts can help build trust and strengthen long-term relationships with freelance professionals. • workers will allow organizations to quickly access qualified professionals when new projects arise. • Finally, organizations should focus on building an inclusive work culture where gig workers feel valued and respected. Recognizing their contributions and involving them in organizational communication can improve engagement and encourage continued collaboration. Sixth, HR departments should create a structured gig talent database.
While we worked with our partners for over two years and gained an understanding of the gradual build-up leading workers from an isolated experience of surveillance exposure to greater vicarious experience through the sharing of stories and sensitization, we lack longitudinal data at the level of the worker. Future research following workers over the course of several years would shed finer light on the temporal dynamics of this process and, in particular, if there is a tipping point at which workers take action. Regarding our sample: our study is representative of the three main union federations in Quebec, and as a result, participants worked mostly in the public and para-public sectors (e.g., education, health and social services, public administration, energy). Future studies should survey non-unionized employees and other industries in the private sector. Moreover, additional research with IT and HR departments is needed to further document the detailed prevalence and use of surveillance technologies, as these data are difficult to obtain from unions or workers.
Making Sense of Workplace Surveillance: How Workers and Union Representatives Experience, Imagine, and Resist Surveillance Exposure · 2026 · DOIAs there is no consensus among researchers on the impact of the increasing share of platform work on the economic status of individuals, some scholars argue that platform work acts as a stabilizer that narrows the gap in unequal incomes, while others argue that platform work increases employment insecurity.
Categories and type of guidance Each sequence of assessment and decision leads to different categories and ‘types’ of guidance for technologies with differing characteristics, indications and target populations, that is, each sequence of ‘yes’ or ‘no’ judgements in the checklist defines a single pathway leading to a particular type and category of guidance (see Table 32, Appendix 4). The different types of apparently similar guidance illustrate how the same category of guidance (e.g. approve, AWR, OIR or reject) might be arrived at in different ways, helping to identify the particular combinations of considerations that might underpin guidance, contributing to the transparency of the appraisal process. There was a general view that the application of the checklist would improve transparency in communicating the considerations that underpin guidance but that this alone would not be sufficient, especially in situations in which OIR guidance was made for a technology that was, on balance, expected to be cost-effective. Evidence of how, not just what, assessments and judgements were made would be required (see What additional information and analysis might be required?). These principles suggest that the categories of guidance available to NICE have wider application than is reflected in previous guidance (see the review of NICE guidance in Chapter 4). For example, there are five different types of OIR guidance that may be appropriate when a technology is expected to be cost-effective (see Table 1). Indeed, OIR may be appropriate even when research is possible with approval if there are significant irrecoverable costs. AWR can be considered only when research is possible with approval but reject remains a possibility even for a cost-effective technology if there are irrecoverable costs. Therefore, the full range of categories of guidance (OIR and reject as well as AWR and approve) ought to be considered for technologies that, on the balance of existing evidence and current prices, are expected to be cost-effective. It DOI: 10.3310/hta16460 Health Technology Assessment 2012; Vol. 16: No. 46 93 is only approval that can be ruled out if a technology is not expected to be cost-effective, that is, cost-effectiveness is necessary but not sufficient for approval but lack of cost-effectiveness is neither necessary nor sufficient for rejection. Scope of ‘only in research’ recommendations Importantly, which category of guidance will be appropriate depends only partly on an assessment of expected cost-effectiveness and hence this assessment should be regarded only as an initial step in formulating guidance.
Futures of Transit Work: Contesting Devaluation and Neoliberal Automation in Bus Transit · 2026 · DOIAmong the appraisals with OIR/AWR recommendations in the final guidance, 10 were later reviewed by NICE, including two that were incorporated into NICE clinical guidelines. Table 9 provides details of the appraisals and whether or not additional evidence was provided and the change to the OIR/AWR recommendation (new evidence for other recommendations included within the guidance is not noted in the table). In the majority of reviewed appraisals (n = 7), new evidence informing the OIR/AWR recommendation was available for the review. In four of these reviews, the OIR or AWR restriction was removed and the technology was recommended routinely. In two cases the additional evidence was considered insufficient to warrant a change in the OIR recommendation. In the remaining appraisal the OIR was revised so that some technologies within the class were recommended routinely whereas OIR recommendations were issued for others (TA5196 on CCBT). In all cases the changes in the guidance were owing to the new data relating to the evidence gap identified in the OIR/AWR recommendation. In three cases no new evidence was provided on the OIR/AWR indication. For the review of TA6,105 no new RCT data were available for the OIR recommendation, which was made more restrictive in the review guidance. New evidence on clinical effectiveness was not available for the review of TA33,106 but further information on adverse effects was provided. This was considered inadequate and no change was made to the OIR recommendation. The OIR recommendation was removed from the review of TA37100 despite a lack of new evidence presented. The documents state that the reasons for this were a reduction in demand for the drug in this setting (it had since become licensed and NICE approved for treatment of an earlier stage of disease) and concerns about the feasibility of future data collection. © Queen’s Printer and Controller of HMSO 2012. This work was produced by Claxton et al. under the terms of a commissioning contract issued by the Secretary of State for Health. This issue may be freely reproduced for the purposes of private research and study and extracts (or indeed, the full report) may be included in professional journals provided that suitable acknowledgement is made and the reproduction is not associated with any form of advertising. Applications for commercial reproduction should be addressed to NETSCC.
Futures of Transit Work: Contesting Devaluation and Neoliberal Automation in Bus Transit · 2026 · DOIPrice changes or discounts featured in two of the appraisals including OIR/AWR recommendations. A patient access scheme was incorporated into TA129103 and the guidance changed from reject to approval. This appraisal had previously included an OIR recommendation in draft guidance but was changed to reject prior to the offer of the access scheme as described in the previous section. In the second appraisal, an OIR recommendation was revised to approval after the committee revised their estimates of cost-effectiveness based on discounted prices of the technology along with further information on quality-of-life improvements (TA166104 on cochlear implants).
Futures of Transit Work: Contesting Devaluation and Neoliberal Automation in Bus Transit · 2026 · DOIEach piece of NICE guidance is considered for review at a specified length of time after publication (usually 3 years). To examine the impact of OIR/AWR recommendations on evidence collection and future guidance we considered guidance that included OIR/AWR recommendations and that had been updated by NICE. The documents were examined for changes in the evidence base available between original appraisal and review that were considered by the committee, and for changes to the decisions reflected in the guidance.
Futures of Transit Work: Contesting Devaluation and Neoliberal Automation in Bus Transit · 2026 · DOIGenerally speaking, the benefit of attaching research conditions to NICE recommendations is an improved evidence base for resource allocation decisions in the future. The beneficiaries of the research are members of future populations who will profit from better informed allocation decisions. But achieving this benefit can impose significant opportunity costs on current patients. This is true for some OIR decisions and some AWR decisions. To be clear about when a research condition does impose an opportunity cost on the present population, and how significant this is, two issues need to be carefully considered. The first is DOI: 10.3310/hta16460 Health Technology Assessment 2012; Vol. 16: No. 46 27 what is meant by present and future populations. For the purposes of this discussion the present population comprises people whose interests are directly affected by a NICE recommendation (e.g. they receive an innovative treatment approved by NICE, or benefit from resources made available because NICE rejects an innovative treatment). Future populations comprise people whose interests are indirectly affected by decisions, in particular by the subsequent research results that improve the evidence base for future NICE judgements. It is important to note that on these definitions some people – specifically patients with a chronic condition who live sufficiently long – will be members of both the present and the future populations. Thus, some individuals in the present population may benefit from the research condition because they will also be members of the future population. This will not be true of all, so the issue of balancing the interests of some individuals in the present population against some individuals in the future population remains. The second issue is under what circumstances the present population is disadvantaged by the research condition compared with the alternative recommendation that NICE might make. This will depend both on what the alternative recommendation would be and on the level of current evidence about cost-effectiveness for the intervention. Three general types of situation might arise: 1. The evidence concerning the cost-effectiveness of a new treatment compared with standard treatment is genuinely balanced such that the likelihood of a new treatment turning out to be less cost-effective than standard treatment is the same as the likelihood of that new treatment turning out to be more cost-effective than standard treatment. Under these conditions it makes no difference to the present population whether a research-conditional recommendation is made or not. Indeed it makes no difference whether the new intervention is accepted or rejected. Future populations, however, will benefit from the research. Some current patients will be members of both present and future populations and will therefore benefit from research. 2.
Futures of Transit Work: Contesting Devaluation and Neoliberal Automation in Bus Transit · 2026 · DOIThe GigFlow initiative offers a new framework to improve trust, transparency, and the authenticity of skills in the growing gig economy. It focuses on the expanding Indian market and implements a strict AI Mastery Vetting Model. This model addresses major issues related to generative AI, particularly the widening skills gap and the declining credibility of freelancers' abilities. Through its thorough vetting process, GigFlow ensures that professionals show both skill in AI tools and human-level analytical abilities. This confirms their capability to debug, refine, and improve AI-generated results. This approach matches the current economic trend toward non-routine cognitive tasks. It guarantees that verified freelancers consistently deliver high-quality results. On the technical side, GigFlow uses a Python/Next.js framework and a dual-database system that includes PostgreSQL and MongoDB. This setup is optimized for performance, flexibility, and easy integration of AI. The step-by-step cloud deployment plan starts with GCP for the minimum viable product phase and moves to AWS for scalable growth. This shows operational efficiency and readiness for enterprise-level IJFMR260379524 Volume 8, Issue 3, May-June 2026 8 International Journal for Multidisciplinary Research (IJFMR) E-ISSN: 2582-2160 ● Website: www.ijfmr.com ● Email: [email protected] expansion. The future introduction of proprietary Large Language Models (LLMs) for personalized matching and AI-based contract analysis will elevate GigFlow from a standard marketplace to a fullfledged AI technology ecosystem. The next phase of GigFlow will focus on four main areas: • Empirical Validation – Finding the connection between the AI Mastery Vetting Score and actual project success metrics. • Ethical AI and Bias Mitigation – Ensuring fairness and transparency in LLM-based matching and contract analysis. • Financial Model Optimization – Improving GigFlow’s hybrid monetization strategy through a comparison with global platforms. • Backend and AI Integration – Completing backend development to include LLM inference, smart contracts, and real-time vetting analytics.
Ignoring the Employers’ Obligations: In the case of these platform companies, they are not considered official employers who are responsible for the safety at their workplace. Ignorance of Workplace Safety Standards: There are no standards that relate to safety at the workplace, which could assist in reducing the risks faced by the delivery men, drivers, and other gig workers, like accidents, long shifts, and severe weather conditions. Non-compliance with Regulations: Unlike the conventional working scenario, there is no mechanism in place where the standards could be enforced on the gig workers. Lack of Health Care Facilities: Gig workers do not have access to any health care facility or medical examinations, besides the lack of compensation for workplace injuries. The Code on Occupational Safety, Health and Working Conditions, 2020, represents one such initiative towards the process of codification of occupational safety and health laws. The Code cannot be termed as comprehensive due to the very fact that it is specific to industries and organizations. The Code does not address the fragmented and digitalized nature of gig work. As a result, gig workers are left unprotected under the occupational safety and health laws. Antu Rani Majumdar, Dr. Malay Adhikari, Prof. (Dr.) Pradeepta Kishore Sahoo Page | 764 The Academic Volume 4 | Issue 4 | April 2026 7. EMERGING CHALLENGES UNDER INDIAN LABOUR LAW Many challenges have emerged due to the advent of the Gig Workers within the labour law regime of India. One of the primary reasons for these challenges is the absence of any employer-employee relationship. Some of the other important challenges include the following: 7.1. Misclassification of Employees One of the major issues facing the Gig Workers is the misclassification of employees as independent contractors. This is seen especially in ride-hailing and delivery services companies through their online platforms. Platforms classify their workers as either “partners” or “service providers,” thus escaping any form of liability that may arise from such employment. Consequently, the platforms do not need to fulfill their responsibility financially or socially towards ensuring that minimum wage, social security benefits, paid leaves, and anti-displacement rights are provided to their workers. Legally, there is an overlap where employees perform critical tasks without being employees. 7.2. Absence of Minimum Wage Protection They get paid depending on how much work they can do or on the basis of each individual job that they deliver, unlike the other employees who are entitled to a fixed monthly pay.
While we present a decentralized, protocol-based approach as an alternative future for delivery work, future work guiding imple- mentation and adoption are crucial to make this future viable. Here we highlight two key areas. 5.1 Designing a Governance Model A decentralized network introduces unpredictable dynamics of competition and collaboration among platforms. We believe the governance model of such a decentralized network would require exploration in the following perspectives: 1) How do instances man- age themselves? E.g., Instances need to decide how to protect in- dividual couriers from harm, as well as how to deal with couriers who break collective rules. They must also set processes for setting, enforcing, and revising any such norms. 2) How do instances manage interactions with one another? E.g., Instances may be geographically adjacent and even overlap in workers, but have different pay poli- cies that lead to conflict and unhealthy competition. 3)How does the network manage its registry of courier collectives? E.g., the network needs to set rules and processes to safeguard against instances pro- viding illegal or harmful services and that couriers operating in bad faith are not simply hopping from instance to instance. 5.2 Community Adoption and Adaptation of the Protocol A key challenge for any network is attracting a sufficient number of adopters. Many indie platforms already operate with established infrastructures for order management, task assignment, and pay- ment processing. Joining the decentralized network requires them to adapt or extend their systems to support the open protocol. One promising path is the development of dynamic adaptors that trans- late between existing endpoints in the white-label software and the protocol, avoiding the need for wholesale system replacement and lowering integration barriers. Such adaptors could also enable interoperability across multiple protocol-based networks in the future. Similar tools already exist in decentralized social media—for example, BridgyFed and Nipy-Bridge [6, 42]—which connect oth- erwise incompatible protocols. By reducing adoption friction and demonstrating practical interoperability, adapters can accelerate the growth of the decentralized network that supports shared gov- ernance and worker-centered design. Broadly, the sustainability of this network also requires enough consumers moving to platforms that operate as part of it, away from or in addition to existing centralized platforms. Future work must also consider how consumer-facing systems might integrate into this ecosystem of delivery work.
Envisioning Alternative Futures for Delivery Work: Toward a Decentralized Network Built on the OpenCourier Protocol · 2026 · DOIDriver negotiation power over individual gig income at Biila is noted as exceptional but the study does not quantify the scope of this negotiation (e.g., percentage of gigs negotiable, typical price ranges offered), measure actual use of this feature among drivers, or assess how perceived versus actual negotiation power affects distributive justice experience.
Organisational Justice Among Gig Drivers: A Case of a Transport Platform Company in Finland · 2026 · DOIThe paper reports that 11% of Biila drives require support, but does not categorize the types of problems drivers encounter or analyze whether different problem categories (technical, safety, payment disputes, navigation) correlate differently with fairness perceptions through the lens of organisational justice dimensions.
Organisational Justice Among Gig Drivers: A Case of a Transport Platform Company in Finland · 2026 · DOIBiila's management indicates the company could expand driver community support via their Telegram messaging service but must balance this against EU platform work legislation compliance. The study does not specify which legislative provisions constrain community-building efforts or provide empirical data on how increased community engagement affects organisational justice perceptions and retention.
Organisational Justice Among Gig Drivers: A Case of a Transport Platform Company in Finland · 2026 · DOIThe finding that organisational justice adequately explains fairness perception regardless of full-time versus part-time employment status contradicts prior studies (Schor et al., 2020; Myhill et al., 2021). This requires comparative validation across multiple platform companies and transport sectors to determine whether this result is specific to Biila's Finnish context or generalizable to gig transport platforms in other geographic and regulatory jurisdictions.
Organisational Justice Among Gig Drivers: A Case of a Transport Platform Company in Finland · 2026 · DOIThe paper identifies that algorithm transparency is partially achieved through driver involvement in platform app development, but does not specify which algorithmic decisions (e.g., pricing, gig assignment, rating mechanisms) drivers are actually involved in developing or how transparency levels differ across these specific algorithmic functions.
Organisational Justice Among Gig Drivers: A Case of a Transport Platform Company in Finland · 2026 · DOISupport availability for gig drivers at Biila is limited to certain hours, with drivers requiring support in approximately 11% of their drives. The study does not investigate what specific support gaps occur during off-hours or how the timing and accessibility of support services affects the perceived fairness experience across different driver shifts and geographic locations.
Organisational Justice Among Gig Drivers: A Case of a Transport Platform Company in Finland · 2026 · DOIHowever, this literature is fragmented with scholars disagreeing on the conceptualization and measurement of AM, as well as a lack of consensus on the dimensions of AM influencing various gig worker‐related outcomes, the mechanisms through which these influences are exerted, and the relevant boundary conditions.
Algorithmic management in the gig economy: A systematic review and research integration · 2024 · DOITherefore, the sample size of countries should be expanded in future studies, and the possible heterogeneity of AI should be explored and compared by classifying different countries according to their stage of development. First, only the effect and mechanism of AI in promoting employment from a macro level are investigated in this study, which is limited by the large data particles and small sample data that are factors that reduce the reliability and validity of statistical inference.
Their growing popularity has revealed institutional vulnerabilities, particularly with regard to the weak position of platform workers, related to their ambiguous status, controversial regulations of labour platforms including algorithmic control of tasks performed, the rate and method of payment for services rendered, insufficient knowledge of how platforms operate.
By using this scheme in a study of 11 intermediaries of knowledge-intensive work in Norway, we found that self-service platforms are insufficient and must be supplemented with active client involvement during several stages of the allocation process.
In recent years, more empirical studies have become available for clarifying open questions, and this paper presents three main results from one such study based on case investigations in 10 German industrial firms.
Digitized Industrial Work: Requirements, Opportunities, and Problems of Competence Development · 2020 · DOIOutsourcing is the kind of difficult collective choice – highly complex with strong uncertainty, limited information feedback, and mixed motivations ‐ well suited for the SMM framework.
The typical satisfied stenographer was happy as a child, played girls’ games, seldom argued or fought, did not resent authority, and was content to follow the leadership of others, She received only average grades in school and her educa- tion was limited to a short commercial course after high school graduation.
Most-cited papers in Digital Economy and Work Transformation
- <scp>Work‐from‐anywhere</scp> : The productivity effects of geographic flexibility · Strategic Management Journal · 2020 · 499 citations
- Automated pastures and the digital divide: How agricultural technologies are shaping labour and rural communities · Journal of Rural Studies · 2019 · 433 citations
- Productive employment and decent work: The impact of AI adoption on psychological contracts, job engagement and employee trust · Journal of Business Research · 2020 · 351 citations
- The Society of Algorithms · Annual Review of Sociology · 2021 · 345 citations
- Algorithmic Surveillance in the Gig Economy: The Organization of Work through Lefebvrian Conceived Space · Organization Studies · 2020 · 323 citations
- Conceptualizing human resource management in the gig economy · Journal of Managerial Psychology · 2019 · 263 citations
- Employment 5.0: The work of the future and the future of work · Technology in Society · 2022 · 210 citations
- The impact of artificial intelligence on employment: the role of virtual agglomeration · Humanities and Social Sciences Communications · 2024 · 175 citations
- ‘I’m my own boss…’: Active intermediation and ‘entrepreneurial’ worker agency in the Australian gig-economy · Environment and Planning A Economy and Space · 2020 · 168 citations
- Making gigs work: digital platforms, job quality and worker motivations · New Technology Work and Employment · 2020 · 166 citations
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