Search results

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.

Building on the arguments of expectancy theory and social exchange theory, the present study provides insights into the process by which pay-for-performance (PFP) impacts employee job performance.

Based on a sample size of 226 employees working in a technology company in India, the study examines the relationships between PFP, procedural justice, organizational citizenship behavior (OCB) and employee job performance. Data on perceptions of PFP and procedural justice were collected from the employees, data on OCB were collected from the supervisors and the data on employee job performance were collected from organizational appraisal records.

The study found support for the positive relationship between PFP and job performance and for the sequential mediation of the relationship between PFP and job performance via procedural justice and OCB. Further, procedural justice was found to mediate the relationship between PFP and OCB.

The study was cross-sectional, so inferences about causality are limited.

The study tests the relationship between PFP and employee job performance in the Indian work context. The study shows that the existence of PFP is positively related to procedural justice which, in turn, is positively related to OCB. The study found support for the sequential mediation of PFP-job performance relationship via procedural justice and OCB.

The study provides an insight into the underlying process through which PFP is related to employee job performance. To the best of our knowledge, such a study is the first of its kind undertaken in an organizational context.

The objective of this research work is to design a data-based solution for administering traffic organization in a smart city by using the machine learning algorithm.

A machine learning framework for managing traffic infrastructure and air pollution in urban centers relies on a predictive analytics model. The model makes use of transportation data to predict traffic patterns based on the information gathered from numerous sources within the city. It can be promoted for strategic planning determination. The data features volume and calendar variables, including hours of the day, week and month. These variables are leveraged to identify time series-based seasonal patterns in the data. To achieve accurate traffic volume forecasting, the long short-term memory (LSTM) method is recommended.

The study has produced a model that is appropriate for the transportation sector in the city and other innovative urban applications. The findings indicate that the implementation of smart transportation systems enhances transportation and has a positive impact on air quality. The study's results are explored and connected to practical applications in the areas of air pollution control and smart transportation.

The present paper has created the machine learning framework for the transportation sector of smart cities that achieves a reasonable level of accuracy. Additionally, the paper examines the effects of smart transportation on both the environment and supply chain.

Technostress is becoming one of the main challenges among employees in the increasingly digital work context. Following the job demands-resources (JD-R) theory, this study aims to understand how technostress (e.g. techno-overload, techno-complexity, techno-insecurity and techno-uncertainty) decreases employees’ work well-being through exhausting one’s emotional and physical resources (i.e. work exhaustion), and to what extent workplace knowledge diversity could buffer this relationship.

The authors collected three-wave data of 235 employees from three manufacturing companies in China. They conducted a moderated mediation model to test their hypotheses.

The results showed that work exhaustion mediated the relationship between technostress and employee work well-being and that perceived workplace knowledge diversity buffered this indirect effect.

This study might be one of the first attempts using the JD-R theory together with a three-wave longitudinal survey design to empirically examine the mediating role of work exhaustion and the moderating role of workplace knowledge diversity. The authors contribute to the information and technology management literature by underscoring the importance of being aware of technostress and managing technology-induced work exhaustion. They highlight that a knowledge-diverse work environment is an essential context that can help employees to handle difficult and complex tasks presented by various technologies and alleviate experienced technostress.

This study aims to know the tactician role of financial technology (FinTech) in the field of accounting and auditing through contextualized systematic literature review by using bibliometric analysis.

The qualitative bibliometric analysis includes studies from 2017 to 2021 using the Scopus and Web of Science databases, which yielded 277 published papers with the keywords, FinTech accounting and auditing. The contextualized systematic literature review greatly helped in clarifying the content within each cluster.

The study identified the tactician role of fintech primarily in the accounting and auditing professional field. Fintech is still in its inception, with continual development and implementation taking place especially, in the auditing field. The findings also confirm that FinTech can produce a confluence between various research areas, including accounting, auditing, business finance, economics, management and business field.

The study describes the tactician role of FinTech and its huge possibility for future study in the accounting and auditing field among professionals, academics and regulators.

This study be able to help accounting professionals, policymakers and government regulators to establish policy development, as this research emphasizes the tactician role of FinTech in the accounting and auditing field.

FinTech in accounting and auditing might add to the existing field of FinTech in the IR4.0 era that give benefits to different players such as policymakers, governments, researchers, FinTech entrepreneurs and practicing professionals.

To the best of the author’s knowledge, little focus has been given about FinTech in the accounting and auditing field using bibliometric analysis. The insights of systematic literature review provide researchers on FinTech among practicing professionals and offer opportunities for further scientific endeavours.

Space tourism is fairly neglected in academic research and requires further exploration. Public reaction on social media offers great insights to understand the patterns of behaviour but is often ignored as a potential data source. Thus, this study aims to fill the gap by add to the literature on space tourism, social media analytics and behaviour.

The study adopts a qualitative approach and uses Twitter data for drawing conclusions. An exploratory design is used by analysing 10,000 tweets through unsupervised machine learning and two sets of analysis were conducted. First, sentiment analysis is performed using NRC Emotion Lexicon, which classifies the data as per eight basic emotions and polarity as positive and negative. The findings are complemented with a comparison cloud. Second, LDA Topic modelling using Gibbs Method is used to find ten broad topics that are used for discussions in space tourism tweets. Data visualisation technique is used to depict results using R language on RStudio.

A total of 21,784 emotions have tapped using the NRC Emotion Lexicon. Results indicate the dominance of positive sentiments (25%) with it surpassing the negative sentiments by many folds. The top emotions include trust and anticipation. The LDA-based Topic modelling identified seven correlated topic models that have been grouped by the author as space tourism in media, aspirations, ethical issues, criticism, descriptive, symbolism and miscellaneous.

To the best of the author’s knowledge, no study has attempted to study the response of space tourism on social media by tapping discussions in the form of Tweets. Thus, this study adds extensively and acts as a preliminary investigation on the public sentiments of space tourism on social media.