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The purpose of this paper is to study the following two issues regarding blockchain crowdsourcing. First, to design smart contracts with lower consumption to meet the needs of blockchain crowdsourcing services and also need to design better interaction modes to further reduce the cost of blockchain crowdsourcing services. Second, to design an effective privacy protection mechanism to protect user privacy while still providing high-quality crowdsourcing services for location-sensitive multiskilled mobile space crowdsourcing scenarios and blockchain exposure issues.

This paper proposes a blockchain-based privacy-preserving crowdsourcing model for multiskill mobile spaces. The model in this paper uses the zero-knowledge proof method to make the requester believe that the user is within a certain location without the user providing specific location information, thereby protecting the user’s location information and other privacy. In addition, through off-chain calculation and on-chain verification methods, gas consumption is also optimized.

This study deployed the model on Ethereum for testing. This study found that the privacy protection is feasible and the gas optimization is obvious.

This study designed a mobile space crowdsourcing based on a zero-knowledge proof privacy protection mechanism and optimized gas consumption.

In order to meet the different quality of service (QoS) requirements of vehicle-to-infrastructure (V2I) and multiple vehicle-to-vehicle (V2V) links in vehicle networks, an efficient V2V spectrum access mechanism is proposed in this paper.

A long-short-term-memory-based multi-agent hybrid proximal policy optimization (LSTM-H-PPO) algorithm is proposed, through which the distributed spectrum access and continuous power control of V2V link are realized.

Simulation results show that compared with the baseline algorithm, the proposed algorithm has significant advantages in terms of total system capacity, payload delivery success rate of V2V link and convergence speed.

The LSTM layer uses the time sequence information to estimate the accurate system state, which ensures the choice of V2V spectrum access based on local observation effective. The hybrid PPO framework shares training parameters among agents which speeds up the entire training process. The proposed algorithm adopts the mode of centralized training and distributed execution, so that the agent can achieve the optimal spectrum access based on local observation information with less signaling overhead.

Although the phenomenon of the corporate social responsibility disclosure (CSRD) has derived the interest of several scholars, in recent years, the comparative studies between Islamic banks (IBs) regarding CSRD quantity versus quality have not been the subject matter of studies till now. In this perspective, this chapter aims to investigate the importance given by IBs to the quality and quantity disclosure of CSR. Moreover, it seeks to explore the impact of CSRD quality and quantity on the IBs' financial performance (FP). To meet these objectives, we used a sample of 59 IBs from 2011 to 2016 in the Arab world and non-Arab world. Then, by adopting the content analysis approach, the authors constructed two CSRD indexes (quality and quantity). The empirical results indicated that IBs give more importance to the qualitative disclosure than the quantitative. Our findings will be very helpful for the policymakers and the managers of IBs because maintaining a good CSRD policy increases the capacity of IBs to deal with possible reputational events, thus protecting their profits and financial results. As far as the comparison between the Arabian and non-Arabian IBs, based on financial reports and Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI) governance standard N°7 is concerned, our study is among the first studies that provides two new CSRD indexes (quantity and quality).

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.

This study aims to analyse in the health access of Indonesian illegal migrant workers in Malaysia, during which time they were not covered by Indonesia’s national social health insurance.

This study adopted a sociolegal approach, the research approach is conducted to understand the effect of a law, policy and regulation on access to health-care access among Indonesian migrant workers working illegally in Malaysia. This research involved 110 respondents who work illegally in Malaysia. The research explored the perceptions of respondents concerning to health access services of illegal migrant workers.

The study demonstrated the weakness of provisions intended to guarantee the health access to health care of migrant workers from Indonesia illegally working in Malaysia. A decline in health status was observed, but it was not significant. Bilateral cooperation between Indonesia and Malaysia is necessary to provide a framework for Indonesia providing health care to its citizens working in Malaysia, regardless of their legal status.

This paper concerns on the Indonesia illegal migrant workers experiencing illness and the access to the health service in Malaysia, and also the implementation of international regulation to protect Indonesian illegal migrant workers in Malaysia under ASEAN Consensus on the Protection and Promotion of the Rights of Migrant Workers.

Clean energy is the most demanding issue for sustainable development, especially in post-COVID-19 scenario. The Government of India (GOI) has adopted various reform policies in the energy sector focusing on Sustainable Development Goal 7 (SDG 7). India has taken initiative on SDG 7 to ensure access to sustainable energy for all. The core interest area of this paper is to analyse recent energy reform policies in energy sectors covering power generation, transmission, distribution and consumption and discusses mechanism SDG target achievement within 2030 in India. In the COVID-19 pandemic scenario, every country faces a major issue of energy security since the undisrupted energy security is related to energy demand. In the time period of pandemic, industrial energy demand goes down rapidly all over the world, especially in India. Though in the eve of festive season in India the difference between the energy supply and demand slightly overcomes. In the year 2003, GOI through Electricity Act opened electricity market for private participation to increase efficiencies. In the COVID-19 pandemic scenario, every country faces a major issue of energy security since the undisrupted energy security is related to energy demand. Further, the Ministry of Power has taken several policies such as National Electrification Policy in 2005, National Tariff Policy, Rural Electrification Policy in 2009 and Integrated Energy Policy. This policy brief paper highlights the progress of clean energy in India and provides their future trajectory towards achieving SDG targets, especially in the period of COVID-19 pandemic.

This is an acceptable fact that firms put efforts to maximize shareholders wealth but there is growing demand that firms are also accountable to various stakeholders associated directly or indirectly with the firms' business activities. Investors now evaluate firm's performance not only from financial perspective but also consider environment, social, and governance (ESG) factors when taking investment decision. ESG is not visible in firm's annual financial reports but investors do not deny its significance when valuing firms. There are increasing interests in ESG by communities, professionals, and government bodies, and all are interested to keep it as part of firms' regular activity and have to relate it with firm performance and efficiency that affects firm value. Still, there are difficulties in integration of ESG factors into investment decision-making, but efforts are being put to overcome all the issues. Firms which consider ESG are in a good position to achieve their long-term financial goals as they are likely to attract capital, lower borrowing costs, mitigate risks, and maximize shareholders value.

This study investigates theoretical relationships among personality characteristics, preferences for different types of rewards and the propensity to choose a job in auditing by management-related higher education students. Specifically, the authors consider motivation, locus of control (internal and external) and self-efficacy (SE) as personality characteristics and financial, extrinsic, support and intrinsic as types of rewards.

Data were collected through a questionnaire targeted at management-related higher education students in Portugal. Partial least squares structural equation modelling was used to analyse the data.

The full sample results show that different types of motivation, locus of control and SE are related to different reward preferences. The authors also find a positive association between a preference for extrinsic rewards and the propensity to choose a job in auditing. Moreover, when the authors consider the role of working experience in the model, the authors find that the reward preferences that drive the choice of an auditing job differ according to that experience.

This study enriches the literature by assessing preferences for different types of rewards, considering multiple personality characteristics and a comprehensive set of rewards. Furthermore, the authors identify the reward preferences that drive the choice of an auditing career. This knowledge empowers auditing firms to devise recruitment strategies that resonate with candidates’ preferences, which boosts the capacity of these companies to attract new auditors.

Different external supply scenarios faced by the retailers will affect their choice of strategy when supply is disrupted and becomes far less than demand, urgently. This study focuses on analyzing both demand and supply side response strategies to meet customer demand and reduce the impact of the shortage during supply disruptions.

According to the quantity of products that the external market can provide, the external supply scenarios were divided into sufficient-type external supply and learning-type external supply. A two-echelon perishable goods supply chain was analyzed, and three kinds of contingency strategy models for downstream retailers were investigated. First, in the sufficient external supply scenario, the optimal price and transshipment quantity to maximize retailer's profits is discussed. Second, in the scenario of learning-type external supply, this study analyzes the optimal decision in three mechanisms of the hybrid strategy and their application: price priority mechanism, quantity priority mechanism and price–quantity balance mechanism. Furthermore, the influence of penalty cost and supply on the priority orders of different mechanisms was studied.

Results show that comparing the two pure strategies (pricing strategy and transshipment strategy)it was noted that the hybrid strategy produces the best results in sufficient-type external supply scenario. In the learning-type external supply scenario, a numerical study has shown the existence of three areas in case of penalty cost and supplier's capacity, and each areas has different priority orders of the three mechanisms. Under the situation of learning external supply, the retailer's optimal strategy is affected by parameters such as penalty cost and supply volume.

The main innovation of the work lies in the following: First; the external supply situation was divided into sufficiency type and learning type, which improves the external situation faced by retailers after the outbreak of emergencies, helps retailers understand the external situation, conforms to the actual situation and has certain practical application value. Second; in the context of learning external supply, there are three coping strategies for retailers, including: Price priority mechanism, Quantity priority mechanism and Pricing and transshipment balance mechanism. This will help retailers make strategic choices, make more scientific management decisions and improve the supply chain emergency management theory. Third; the demand side response was managed through the change of external supply during supply side recovery period and supply disruption. The proposed model enables managing and analyzing supply disruption efficiently and effectively via handling uncertainty by considering all aspects of decision-making process. The proposed model can be applied in various fields such as vegetable and fruit, fresh food, etc.

The purpose of this paper is to help better understand the translation process of the management control system (MCS) of privatised solid waste management (SWM) towards creating a stable network.

Drawing on the actor network theory (ANT), the case of a privatised SWM was studied. Data were collected from all entities involved in the privatisation process of SWM, which include Department A, Corporation X and the private sector concessionaire. Six documents were reviewed, 20 interviews were conducted and two observations were carried out.

The findings reveal that the control mechanism of SWM is complex, involving the interaction between human and non-human actors. Non-human actors include the key performance indicators (KPIs) and the concessionaire agreement (CA), which are the main control mechanisms towards creating a stable SWM network. Essentially, stability is achieved when the KPIs and CA can influence the activities of both intra- and inter-organisational relationships.

This paper provides a better understanding of the translation process of the MCS that adds to the stability of the network of a privatised SWM from the lens of the ANT.