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Digital platforms (DP) are transforming service delivery and affecting associated actors. The position of DPs is impacted by the regulations. However, emerging economies often lack the regulatory environment to support DPs. This paper aims to explore the regulatory developments for DPs using the multi-level perspective (MLP).

The paper explores regulatory developments of ride-hailing platforms (RHPs) in India and their impacts. This study uses qualitative interview data from platform representatives, bureaucrats, drivers, experts and policy documents.

Regulatory developments in the ride-hailing space cannot be explained as a linear progression. The static institutional assumptions, especially without considering the multi-actors and multi-levels in policy formulation, do not serve associated actors adequately in different times and spaces. The RHPs regulations must consider the perspective of new RHPs and the support available to them. Non-consideration of short- and long-term perspectives of RHPs may have unequal outcomes for established and new RHPs.

This research has implications for the digital economy regulatory ecosystem, DPs and implications for policymakers. Though the data from legal documents and qualitative interviews is adequate, transactional data from the RHPs and interviews with judiciary actors would have been insightful.

The study provides insights into critical aspects of regulatory evolution, governance and regulatory impact on the DPs’ ecosystem. The right balance of regulations according to the business models of DPs allows DPs to have space for growth and development of the platform ecosystem.

This research shows the interactions in the digital space and how regulations can impact various actors. A balanced policy can guide the paths of DPs to have equal opportunities.

DP regulations have a complex structure. The paper studies regulatory developments of DPs and the impacts of governance and controls on associated players and platform ecosystems.

Social media platforms play a key role in information propagation and there is a need to study the same. This study aims to explore the impact of the number of close communities (represented by cliques), the size of these close communities and its impact on information virality.

This study identified 6,786 users from over 11 million tweets for analysis using sentiment mining and network science methods. Inferential analysis has also been established by introducing multiple regression analysis and path analysis.

Sentiments of content did not have a significant impact on the information virality. However, there exists a stagewise development relationship between communities of close friends, user reputation and information propagation through virality.

This paper contributes to the theory by introducing a stagewise progression model for influencers to manage and develop their social networks.

There is a gap in the existing literature on the role of the number and size of cliques on information propagation and virality. This study attempts to address this gap.

The pandemic COVID-19 brought in large challenges globally among the workforce. There were reports of how employee layoffs and pay-cuts were gradually becoming prominent across industries based on media reports. However, there were no attempts to develop a typology of challenges faced by the workforce.

This study mined user-generated content from Twitter to bring out a typology of challenges due to the sudden turbulence that is faced from the pandemic. A case study has also been conducted by taking in-depth interviews in the academic sector to deep dive into the nature of these problems.

The study findings indicate that these challenges are basically stemming from challenges surrounding infrastructure readiness, digital readiness, changing nature of deliverables, workforce demand versus supply problems and challenges surrounding job losses.

There is a need to explore the linkages through inferential research infrastructure readiness, digital readiness, changing nature of deliverables, workforce demand versus supply problems and challenges surrounding job losses on employee welfare during pandemics.

The authors provide inductive insights based on a data-driven research methodology surrounding the sudden challenges faced and possible mechanisms to address these issues faced by a stressed workforce catering to multiple stakeholders.

Big Data has become crucial for fulfilling the vision of smart cities; however, there are several challenges associated with its use. This study aims to provide a holistic view of challenges of using Big Data in smart cities and the solutions to deal with them by systematically selecting, reviewing and synthesizing the literature in this area.

A systematic literature review was conducted by following a rigorous search protocol that identified a total of 310 peer-reviewed academic research papers. These papers were subsequently filtered and finally 38 relevant papers were selected.

A number of major challenges (human dynamics, privacy, security, volume, velocity, variety, veracity and value) associated with Big Data in a smart city and the respective solutions to address them were identified. This study primarily contributes in providing the process of effectively managing Big Data in smart cities.

The study provides valuable information to the Big Data practitioners by illustrating the process of effective management of Big Data in smart cities. This study further provides the directions to the future researchers.

The study is original and is based on the existing literature and its interpretation.

The importance and criticality of sustainable development goals is witnessed by 195 member countries. For its full-fledged adoption and implementation, it needs to be understood by masses and political leaders are critical agents those engage diverse communities through social media such as twitter. Therefore, in this study focuses on how political leaders can influence the sustainable development goals through Twitter.

This study examines the social media conversations of political leaders on Twitter. Social media analytics methods such as sentiment mining, topic modelling and content analysis-based methods have been used.

The findings indicate that most political leaders are primarily discussing the sustainable development goals (SDGs) “partnership for goals” and “peace, justice and strong institutions”. Many other goals such as “clean water and sanitation”, “life below water”, “zero hunger”, “no poverty” and “educational quality” are not being focused on.

This study offers implications in terms of collective decision making and the role of policy makers towards the goals of promoting SDGs. The authors highlight how political leaders need to involve key stakeholders in this journey.

This study scores and provides a cohort-specific prioritization of the leadership within these countries with regard to SDGs, which could be beneficial to the society.

This conceptual article’s primary aim is to identify the significant stakeholders of the digital identity system (DIS) and then highlight the impact of artificial intelligence (AI) on each of the identified stakeholders. It also recommends vital points that could be considered by policymakers while developing technology-related policies for effective DIS.

This article uses stakeholder methodology and design theory (DT) as a primary theoretical lens along with the innovation diffusion theory (IDT) as a sub-theory. This article is based on the analysis of existing literature that mainly comprises academic literature, official reports, white papers and publicly available domain experts’ interviews.

The study identified six significant stakeholders, i.e. government, citizens, infrastructure providers, identity providers (IdP), judiciary and relying parties (RPs) of the DIS from the secondary data. Also, the role of IdP becomes insignificant in the context of AI-enabled digital identity systems (AIeDIS). The findings depict that AIeDIS can positively impact the DIS stakeholders by solving a range of problems such as identity theft, unauthorised access and credential misuse, and will also open a possibility of new ways to empower all the stakeholders.

The study is based on secondary data and has considered DIS stakeholders from a generic perspective. Incorporating expert opinion and empirical validation of the hypothesis could derive more specific and context-aware insights.

The study could facilitate stakeholders to enrich further their understanding and significance of developing sustainable and future-ready DIS by highlighting the impact of AI on the digital identity ecosystem.

To the best of the authors’ knowledge, this article is the first of its kind that has used stakeholder theory, DT and IDT to explain the design and developmental phenomenon of AIeDIS. A list of six significant stakeholders of DIS, i.e. government, citizens, infrastructure providers, IdP, judiciary and RP, is identified through comprehensive literature analysis.

Aligning business innovation with the sustainable development goals (SDGs) creates immense opportunities to solve societal challenges along with business growth and productivity. This study aims to understand the evolution of Fortune firms' strategic addressing of SDG on social media as a step towards post-pandemic recovery. Using attribution theory as a theoretical lens, the authors try to investigate how entrepreneurial orientation (EO) and SDG orientation evolve with the crisis and affect the appreciation and advocacy of the SDG-related posts.

A mixed methodology of machine learning and Social media analytics such as content analysis, sentiment analysis and space–time analysis have been used, followed by multivariate analysis to validate the findings.

An evolution in CEOs’ strategic focus surrounding SDG dimensions was found, from economic in pre-pandemic phase to social and environment during the pandemic. The SDG disclosure on social media by the Fortune CEOs seems to have an influence on their social media reputation, whereas EO has no impact on social media reputation.

Wise practice of EO in information diffusion by CEOs on social media may lead to a healthy relationship with the stakeholders and better firm performance. The SDG adoption at organisation level contributes towards a sustainable society and helps tackling the challenges faced during the pandemic.

This study analyses the contribution of the Fortune firms to achieve a sustainable society in a pandemic environment by strategic adoption of SDGs and effective use of digital platforms.

The purpose of this paper is to identify the factors influencing the citizens of India to prevent cybercrimes in the proposed Smart Cities of India.

A conceptual model has been developed for identifying factors preventing cybercrimes. The conceptual model was validated empirically with a sample size of 315 participants from India. Data were analyzed using structural equation modeling with SPSS and AMOS softwares.

The study reveals that the “awareness of cybercrimes” significantly influences the actual usage of technology to prevent cybercrimes in Smart Cities of India. The study reveals that government initiative (GI) and legal awareness are less influential in spreading of the awareness of cybercrimes (AOC) to the citizens of the proposed smart cities.

The conceptual model utilizes two constructs from the technology adoption model, namely, perceived usefulness and ease of use. The study employs other factors such as social media, word of mouth, GIs, legal awareness and organizations constituting entities spreading awareness from different related literature works. Thereby, a comprehensive theoretical conceptual model has been proposed which helps to identify the factors that may help in preventing cybercrimes.

This study provides an insight to the policy maker to understand several factors influencing the AOC of the citizens of the proposed Smart Cities of India for the prevention of cybercrimes.

There are few existing studies analyzing the effect of AOC to mitigate cybercrimes. Thus, this study offers a novel contribution.

The purpose of this study is to consolidate the state of research in mobile commerce (m-commerce) technology adoption from 2008 to 2017. This study not only reviews the evolution of m-commerce literature but also highlights the significant contribution of authors and their productive collaborations in the development of this area.

A total of 184 peer-reviewed articles focusing on m-commerce adoption were obtained after applying search criteria on Scopus database. After using inclusion and exclusion criteria to achieve the objective of this study, 86 journals were shortlisted. The study further discusses the dispersion of various m-commerce applications being explored in m-commerce literature. In addition, dominating technology adoption theories and the most used keywords have also been identified and discussed in this study.

This study indicates that technology acceptance model and unified theory of acceptance and use of technology are the most exploited technology adoption theories. Moreover, the dominating constructs in literature are perceived usefulness, ease of use social influence/social norm on behavior intention, attitude intention followed by performance expectancy, facilitating condition and effort expectancy influence on intention.

This study presents a detailed association rule mining and community analysis to show the association among constructs such as usefulness, ease of ease, social influence and intention as dominant group in this area. The study also identifies lesser explored constructs and indicates possible future research to validate and strengthen their understanding further.

Global trade depends on more complex, prolonged and larger port systems, where port logistics is a backbone for such operations. Ports are responsible for transferring more than 80 percent of the global trade. Port logistics are prone to being risk-oriented. The study proposes a model to study various port logistics barriers and their associated risks for emerging economies in the Industry 4.0 era.

The study develops a framework by integrating the fuzzy set theory, the evidential reasoning approach and the expected utility theorem for identifying the severity value of port logistics barriers under the Industry 4.0 era for emerging economies and prioritize them based on various perspectives. The study identifies multiple risks associated with the barriers, and intensity-based categorization of the risks is performed for risk profiling.

The study reveals that poor infrastructure, nonsupportive policy ecosystem, and lack of research and development are the top barriers that need immediate attention. A new approach has been proposed that changes the importance of perspectives, and 192 analytical experiments were done to study the changing behavior of barriers. The study also presents various types of risks associated with the selected barriers.

In future studies, other barriers can be discovered and studied to develop such models. To cover the entire spectrum of possibilities, belief degrees of the barriers could be used to study the barriers instead of changing the weights.

This study presents a quantification model to prioritize the barriers based on environmental, economic and operational perspectives. Further, the model helps create scenarios for decision-makers to improve port logistics performance and achieve sustainability. The study identifies various risks associated with port logistics barriers and allows decision-makers to take proactive actions.

This study contributes significantly to the literature on port logistics by developing a framework for determining the severity of the barriers in the Industry 4.0 era for emerging economies. Further, the study pinpoints various risks associated with port logistics, and risk profiling is carried out.