Socio-demographics,political attitudes and informal sector employment: A cross-country analysis

In this paper, we empirically investigate the relationship between informal sector employment and micro-level socio-demographic characteristics, political acts and attitudes, and individual norms. Using self-reported individual micro-level data from the World Values Survey for seven developing countries (China, Ecuador, Egypt, Mexico, Peru, South Africa and Yemen), our cross-country regressions and principal component analysis reveal that socio-demographic characteristics of individuals are strong predictors of their informal sector employment. Our estimations further document that individual preferences for an economically strong, interventionist and egalitarian state and confidence in state and political institutions are positively and significantly correlated with informal sector employment, whereas variables associated with confidence in free market institutions and support for competition are negatively and significantly correlated with informal sector employment. We also show that individuals who participate either actively or inactively in peaceful and lawful political processes are significantly less likely to work in the informal sector. Finally, we document that individual norms, such as religiosity and tax morale, are negatively correlated with informal sector employment. Throughout our analysis, instead of having to rely on ad-hoc informality categorizations of third parties, we base our measurement of informal sector employment directly on the self-evaluation of individuals, who have the best information on the degree of their informality.     

The power of positivity? The influence of positive psychological capital language on crowdfunding performance

We extend the entrepreneurship literature to include positive psychological capital — an individual or organization's level of psychological resources consisting of hope, optimism, resilience, and confidence — as a salient signal in crowdfunding. We draw from the costless signaling literature to argue that positive psychological capital language usage enhances crowdfunding performance. We examine 1726 crowdfunding campaigns from Kickstarter, finding that entrepreneurs conveying positive psychological capital experience superior fundraising performance. Human capital moderates this relationship while social capital does not, suggesting that costly signals may, at times, enhance the influence of costless signals. Post hoc analyses suggest findings generalize across crowdfunding types, but not to IPOs.     

Inequality and entrepreneurial thresholds

We explore the relationship between inequality and entrepreneurial activity. Drawing on cross-sectional data from a largescale survey of the economic conditions of individuals across India, we develop a number of dimensions of inequality to explore empirically how inequality interacts with entrepreneurship, operationalized as self-employment or as employing other people. We find compelling evidence that there are thresholds to becoming self-employed, and even more so to assembling the combinations of resources and personal attributes required to become an employer. Greater inequality leaves more people unable to make the transition to self-employment, leaving casual laboring as the occupation of necessity. At the same time, inequality increases the number of employers in a society, by concentrating resources - particularly land and finance - enough for significant numbers of people to be able to cross this higher threshold. Lastly, greater differentiation into social or religious groups curtails the ability to cross either entrepreneurial threshold, presumably by limiting the extent and benefits of social networks of value for entrepreneurship.     

Blockchain in Additive Manufacturing and its Impact on Supply Chains

Additive manufacturing (AM) appears to be a particularly attractive use case for blockchain. This research combines inductive in‐depth interviews with the Delphi method to explore what potentials blockchain technology in AM creates, which adoption barriers firms need to overcome, and how supply chains will be affected by the integration of these two potentially disruptive technologies. The results suggest opportunities that are related to intellectual property (IP) rights management, the monitoring of printed parts throughout their lifecycle, process improvements, and data security. The most important barriers for blockchain adoption in AM are an absence of blockchain‐skilled specialists on the labor market, missing governance mechanisms, and a lack of firm‐internal technical expertise. By addressing important limitations of AM, blockchain is expected to improve the competitiveness of AM in parts’ production, catalyzing the trend toward more decentralized manufacturing resulting in more agile, resilient, and flexible supply chains and reduced logistics costs. Beyond that, blockchain‐based AM platforms are expected to enhance supply chain visibility, drive supply chain digitalization, support supply chain finance, and contribute to the emergence of shared factory systems.     

Cultural Baggage: Do Immigrants Import Corruption?

Do immigrants undermine culture in a way that destroys productivity in destination countries? Some scholars have argued that because immigrants come from countries with dysfunctional social capital—norms and institutions—they will import it and pollute the social capital in destination countries. One potential channel through which this could occur is corruption. We examine stocks and flows of immigrants over a 20‐year time period to see if corruption increased in destination countries. We generally find that immigration is not associated with increases in corruption. Additionally, we find that immigration tends to decrease corruption in destination countries with low levels of corruption or high levels of economic freedom.     

We Eat First with Our (Digital) Eyes: Enhancing Mental Simulation of Eating Experiences via Visual-Enabling Technologies

This research examines how consumers’ intentions to purchase food change depending on the visualisation mode (3D vs. AR) and product format (served vs. packaged). In three studies, we demonstrate that mental simulation of eating experiences (process and outcome) mediate these effects. Study 1 shows that AR visualisation of a served food improves simulation of the eating process over 3D visualisation, with a positive effect on purchase intention. Study 2 reveals that 3D visualisation improves purchase intention for packaged products (high instrumental properties) over served products (low instrumental properties) while the opposite is true for AR visualisation. In addition, interactivity and immersion mediate the effects of 3D (vs. AR) on mental simulation of the eating process for packaged products. Study 3 extends these results by showing that 3D increases purchase intention by eliciting mental simulation of the eating outcome, when the food is visible due to transparent (vs. opaque) packaging (displaying both sensory and instrumental properties), but that no such differences emerge for AR. This research highlights the importance of using different visualisation modes to promote food depending on the product format. The findings have important implications for both offline and online retailers.     

Perceptions of the benefits of the A3 planner in facilitating project-based learning in accounting education

This paper evaluates ways of instilling project management skills into accounting-based learning by the use of an iterative A3 planner to plan, monitor and review assignment progress. The application of an A3 planner to facilitate a project-based learning (PBL) group assignment in undergraduate accounting education has been critically evaluated in terms of both the student and tutor experience. The study uses a mix of qualitative and quantitative data. Quantitative data assisting exploration of perceptions were collected through 100 undergraduate students. A series of focus group discussions were carried out to investigate students’ engagement and tutors’ teaching experiences regarding the adoption of the A3 planner. The results suggest that the A3 planner promotes active planning and effective management of a PBL group assignment. It makes students’ thought processes more visible thereby facilitating and enhancing the tutoring/mentoring process. Moreover a more interactive and transparent approach by doing assignment via the use of an iterative A3 planner has ensured more feedback points and action based efficiency in the doing approach for learners.     

Best classification algorithms in peer-to-peer lending

A proper credit scoring technique is vital to the long-term success of all kinds of financial institutions, including peer-to-peer (P2P) lending platforms. The main contribution of our paper is the robust ranking of 10 different classification techniques based on a real-world P2P lending data set. Our data set comes from the Lending Club covering the 2009–2013 period, which contains 212,252 records and 23 different variables. Unlike other researchers, we use a data sample which contains the final loan resolution for all loans. We built our research using a 5-fold cross-validation method and 6 different classification performance measurements. Our results show that logistic regression, artificial neural networks, and linear discriminant analysis are the three best algorithms based on the Lending Club data. Conversely, we identify k-nearest neighbors and classification and regression tree as the two worst classification methods.     

Unemployment insurance benefits and income smoothing

Labor unemployment insurance reduces unemployment concerns. We argue that these benefits moderate incentives to smooth earnings to reduce employees’ concerns about unemployment risk. Using exogenous variations in unemployment insurance benefits, we find evidence consistent with this argument. We also find that the link between unemployment insurance benefits and income smoothing is stronger when there is higher unemployment risk and when the firm is likely to employ more low-wage workers, who find unemployment insurance benefits especially useful. Our paper contributes to the literature by showing that public policy decisions such as unemployment insurance have significant, albeit probably unintended, externalities on corporate financial reporting.     

Underemployment in Australia: a panel investigation

This 2001–2013 panel study finds 33% of part-time employees to be underemployed, disproportionately affecting males, immigrants, youth, the blue-collared and new to our study, those on casual contracts. Within the underemployed sample, we report that the gap between preferred and actual hours (working hour tension) also varies by personal and labour characteristics, largely consistent with that found for the determinants of underemployment. The continued growth of part-time employment and casualization in recent years has been more pronounced among males, raising their rates of underemployment as they disproportionately prefer to work more hours vis-à-vis their part-time female peers.