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Gig workers form the backbone of any crowdsourcing platform where they showcase their talent and choose a job of their choice and freedom. The study explores the role of information quality (IQ) and social-mediated dialogue (SMD) in evaluating gig worker engagement and productivity on crowdsourcing platforms. The authors also propose to understand how gig worker productivity could be improved under the moderating effect of game elements.

A conceptual model was developed and empirically tested by integrating media richness theory and dialogic public relation theory. Data were collected from gig workers that are involved in crowdsourcing activities for the past three years. An overall sample of 346 gig workers contributing to at least one of the crowdsourcing platforms was collected. The authors tested the hypotheses using Warp PLS 7.0. Warp PLS 7.0 uses partial least square (PLS) structured equation modeling (SEM) and has been used widely to test path analytical models.

Results reveal that the information quality plays an essential role in the SMD, thereby fostering gig workers' productivity and engagement, which could be improved in the presence of game elements due to their nature of supporting rewards. However, engagement in the platform leading to improved productivity was not supported.

The study lays practical foundations for crowdsourcing platforms as it sets the importance of both IQ and dialogic communication channels. The two-way communication between gig workers and the platforms via accurate, timely, valuable and reliable information forms the key to the task's success. The introduction of the right game element will help to achieve better engagement and productivity.

This study also offers a new dimension to media richness theory and dialogic public relation theory in crowdsourcing platforms. The results would help platform designers and gig employers understand gig workers' quality and performance in a platform economy. The study uniquely positions itself in the area of crowdsourcing platforms by using game elements.

Ethereum-based blockchain technology (EBT) affords members of the Enterprise Ethereum Alliance (EEA) a market advantage in deploying blockchain within their organizations, including cybersecurity and operational benefits, that leads firms to strategically invest in this nascent technology. However, the impact of such strategic investments in EBT has yet to be explored in the context of its relationship to firm value. Therefore, this study explores EBT-specific firm-level characteristics that result in a stock market reaction to announcements of strategic investments.

The authors use the event study methodology, strategic investment literature and signaling theory as contextualizing frameworks for their study. Additionally, the authors explore a new method for examining technology investments as a strategic counter to cybersecurity threats.

Firms that signal to the market their strong commitment to their strategic investment by developing an EBT proof of concept see significantly higher market returns. Firms that have had prior cybersecurity incidents are rewarded by the market for strategically investing in EBT, and when firms with large undistributed free cash flows utilize this cash for strategic EBT investment, the market is more likely to reward these firms, indicating the market views EBT investment positively in these circumstances.

The results of this study provide new evidence of the value impact of EBT for firms that suffered cybersecurity events in the past. The authors provide empirical evidence of firm-level characteristics that investors use to discern whether a strategic investment in EBT will drive organizational value. Likewise, the authors demonstrate how signaling affects investor perceptions of strategic information technology (IT) investments in EBT.

Which venture capital is more beneficial in the product innovation of entrepreneurial ventures? The authors study the drawbacks and different effects of corporate venture capital (CVC) and independent venture capital (IVC) on the effectiveness and efficiency of product innovation in entrepreneurial ventures to answer this question.

This study uses a panel dataset of 502 high-tech ventures and runs the Heckman model to correct potential endogeneity issues.

The authors find that CVC increases the product innovation effectiveness of entrepreneurial ventures, but decreases their efficiency. IVC reduces innovation effectiveness and enhances efficiency. However, CVC performs less positively, while IVC performs more positively in terms of innovation effectiveness and efficiency in the B2B market than in the B2C market.

This study provides insights into how to leverage venture capital to develop new products effectively and efficiently.

This study moves beyond the current understanding of the finance-marketing interface. It delineates the two faces of venture capital and reveals the joint effects of equity stakes and market stakes between different types of venture capital and transaction markets in product innovation.

The purpose of this paper to analyze the effect of Soret with heat and mass transfer on an unsteady two-dimensional Magnetohydrodynamics flow through a porous medium under the influence of the uniform transverse magnetic field in a rotating parallel plate is considered.

A mathematical model was developed using the slip conditions under unsteady state situations. Analytical expressions for the velocity, temperature and concentration profiles, wall shear stress, rates of heat and mass transfer and volumetric flow rate were obtained and computationally discussed with respect to the non-dimensional parameters. Further, the velocity reduces with increasing Hartmann number M and increases with Grashof number Gr and permeability parameter K.

It is observed that temperature reduces with an increase in Prandtl number Pr and ω. It is noted that the thermal radiation increases with increase in Soret number Sr, Schmidt number Sc, Prandtl number pr and ω.

Concentration decreases with an increase in radiation parameter R and chemical reaction parameter Kc.

The purpose of this study is to reveal the dynamics of house prices and sales in spatial and temporal dimensions across British regions.

This paper incorporates two empirical approaches to describe the behaviour of property prices across British regions. The models are applied to two different data sets. The first empirical approach is to apply the price diffusion model proposed by Holly et al. (2011) to the UK house price index data set. The second empirical approach is to apply a bivariate global vector autoregression model without a time trend to house prices and transaction volumes retrieved from the nationwide building society.

Identifying shocks to London house prices in the GVAR model, based on the generalized impulse response functions framework, I find some heterogeneity in responses to house price changes; for example, South East England responds stronger than the remaining provincial regions. The main pattern detected in responses and characteristic for each region is the fairly rapid fading of the shock. The spatial-temporal diffusion model demonstrates the presence of a ripple effect: a shock emanating from London is dispersed contemporaneously and spatially to other regions, affecting prices in nondominant regions with a delay.

The main contribution of this work is the betterment in understanding how house price changes move across regions and time within a UK context.

The authors study and compare the effects of three CEO compensation restricting policies issued by the Chinese government in 2009, 2012 and 2015. This paper aims to shed light on the conditions under which CEO compenstation can be effectively regulated without negatively affecting firm performance.

These policies targeted state-owned enterprises (SOEs), especially central state-owned enterprises (CSOEs). Using these policies as natural experiments, the authors investigate how their effects differ on CEO compensation, firm performance and two known performance-decreasing mechanisms: perk consumption and tunneling activities.

The authors show that restricting CEO pay does not necessarily backfire in terms of deteriorating firm performance. This non-decreasing firm performance can be achieved by restricting perk consumption and tunneling activities while introducing CEO pay regulations.

The authors exploit a powerful experimental setting in the context of China. The evidence contributes to the literature on CEO pay regulations and is relevant to the managerial decisions of policy makers and boards of directors.

Structural mentoring barriers are policies, practices and cultural norms that collectively disadvantage marginalized groups and perpetuate disparities in mentoring. This study aims to better understand structural mentoring barriers at the postdoctoral training stage, which has a direct impact on faculty diversity and national efforts to retain underrepresented groups in research careers.

A diverse sample of postdoctoral scholars (“postdocs”) from across the USA were asked to participate in focus groups to discuss their training experiences. The authors conducted five 90-min focus groups with 32 biomedical postdocs, including 20 (63%) women and 15 (47%) individuals from underrepresented racial/ethnic groups (URG).

A social-ecological framework was used to categorize both the upstream and downstream manifestations of structural mentoring barriers, as well as mentoring barriers, overall. Notable structural barriers included: academic politics and scientific hierarchy; inequalities resulting from mentor prestige; the (over) reliance on one mentor; the lack of formal training for academic and non-academic careers; and the lack of institutional diversity and institutional mentor training. To overcome these barriers, postdocs strongly encouraged developing a network or team of mentors and recommended institutional interventions that create more comprehensive professional development, mentorship and belonging.

For postdoctoral scientists, structural mentoring barriers can permeate down to institutional, interpersonal and individual levels, impeding a successful transition to an independent research career. This work provides strong evidence for promoting mentorship networks and cultivating a “mentoring milieu” that fosters a supportive community and a strong culture of mentorship at all levels.

The numerous spoil grounds brought about by mega transportation infrastructure projects which can be influenced by the ecological environment. To achieve better management of spoil grounds, this paper aims to assess their comprehensive risk levels and categorize them into different categories based on ecological environmental risks.

Based on analysis of the environmental characteristics of spoil grounds, this paper first comprehensively identified the ecological environmental risk factors and developed a risk assessment index system to quantitatively describe the comprehensive risk levels. Second, this paper proposed a comprehensive model to determine the risk assessment and categorization of spoil ground group in mega projects integrating improved projection pursuit clustering (PPC) method and K-means clustering algorithm. Finally, a case study of a spoil ground group (includes 50 spoil grounds) in a mega infrastructure project in western China is presented to demonstrate and validate the proposed method.

The results show that our proposed comprehensive model can efficiently assess and categorize the spoil grounds in the group based on their comprehensive ecological environmental risk. In addition, during the process of risk assessment and categorization of spoil grounds, it is necessary to distinguish between sensitive factors and nonsensitive factors. The differences between different categories of spoil grounds can be recognized based on nonsensitive factors, and high-risk spoil grounds which need to be focused more on can be identified according to sensitive factors.

This paper develops a comprehensive model of risk assessment and categorization of a group of spoil grounds based on their ecological environmental risks, which can provide a reference for the management of spoil grounds in mega projects.

Augmented Reality (AR) and Virtual Reality (VR) technologies possess the potential to transform the scenario of making real estate investment decisions through the immersive experience they offer. From the literature it was observed that the research in this domain is still emergent and there is a need to identify the latent variables that influence real estate investment decisions. Therefore, by examining the effects of these technologies on investment decision-making, the purpose of the study is to provide valuable insights into how AR and VR could be applied to enhance customers' property buying experiences and assist in their decision-making process.

From an extensive review of the literature four latent variables and their measure were identified, and based on these a survey instrument was developed. The survey was distributed online and received 300 responses from the respondents including home buyers, developers, AEC professionals and real estate agents. To validate the latent variables exploratory factor analysis was used whereas to establish their criticality second-order confirmatory factor analysis was used.

From the results, the four latent constructs were identified based on standard factor loadings (SFL) that is Confident Value Perception (CVP, SFL = 0.70), Innovative Investment Appeal (IIA, SFL = 0.60), Trusted Property Transactions (TPT, SFL = 0.58) and Effortless Property Engagement (EPE, SFL = 0.54), that significantly influence investor decision-making and property purchase experience.

This study contributes to the literature on real estate investment decisions by providing empirical evidence on the role of AR and VR technologies. The identified key variables provided practical guidelines for developers, investors and policymakers in understanding and leveraging the potential of AR and VR technologies in the real estate industry.

Financial inclusion is a critical component of financial development, which disseminates accessible financial services to benefit all parts of society and consequently promotes economic growth. The study explores the dynamic common correlated effects of financial inclusion on economic growth in Organization of Islamic Cooperation (OIC) countries.

The conventional econometric techniques overlook heterogeneity and cross-sectional dependence and provide false results. Hence, a unique methodology, ‘Dynamic Common Correlated Effects (DCCE)’, is used, which can efficiently tackle the above-mentioned issues.

The DCCE estimation indicates a positive and significant impact of financial inclusion on economic growth in overall and higher-income OIC economies. Moreover, in the lower-income OIC group, financial inclusion is inversely correlated with economic growth, which converts into a positive linkage by including an interaction term of financial inclusion and institutional quality.

Based on the research outcomes, it is recommended that policymakers and governments of OIC economies seek to increase financial inclusion to achieve sustainable, optimal and inclusive economic growth.

The DCCE technique in this study considers heterogeneity and cross-sectional dependence among countries and thus provides robust findings.