Trust Erosion During Industry-Wide Crises: The Central Role of Consumer Legitimacy Judgement

Journal of Business Ethics - Widespread unethical corporate misconduct in an industry triggers industry-wide crises. This research investigates how industry misconduct affects consumers’...     

Entrepreneurial aesthetics

The Review of Austrian Economics - This paper examines the aesthetic dimension of innovative entrepreneurship. It treats markets as aesthetic systems that involve the creation, interpretation and...     

A regularity theory of causality for the social sciences

Quality & Quantity - This article discusses a regularity theory of causality (RTC) for the social sciences. With RTC, causality is a relationship between X and Y characterized by three...     

Expert and entrepreneur: the unique research domain of professional service entrepreneurs

Professionals are knowledge experts who create customized solutions for clients. Many professionals practice in the context of strong professional institutions that prescribe intense socialization and codes and norms. While some professionals work as employees, many start their own firms in order to practice. Firm start-up for professionals is more prevalent than for most other occupations. While professional institutions often constraint their activities, firm start-up for professional service entrepreneurs (PSEs) involves similar entrepreneurial activities as other entrepreneurs, creating an interesting paradox worth investigating. This paper explores the uniqueness of PSEs and the firms they start, and the distinctiveness and value of research in the context of PSEs and professional service firms.     

Review: Chinese public administration and finance—a call for a new theory,research and dialogue

In implementing its national strategy to achieve global leadership, China needs a new public administration theory that integrates political administration, economic management and social regulation. Even so, China has already started to promote its brand of political and economic development abroad. Therefore new comparative research and dialogue is called to explore the universality of Chinese and Western public administration ideas.     

The role of accounting and the accountancy profession in economic development: A research agenda

A widely held view in the accountancy profession and the donor community is that accounting and the accountancy profession play an essential role in economic development. However, our review of the academic literature finds limited empirical research evidence on the relation between accounting and the accountancy profession and economic development, including specifically whether any such relation is causal, and if so, the direction of the causality. Entities, including those comprising the donor community, policymakers, and professional accountancy organizations (PAOs), need evidence on the question of whether and how the accountancy profession contributes to economic development. Such research could assist donors in evaluating the outcomes of interventions aimed at building the capacity of PAOs in emerging and developing economies and inform future interventions. We summarize the limited academic research addressing the relation between PAOs and economic development and present insights from two roundtables facilitated by the International Association for Accounting Education and Research. We identify research opportunities and research design considerations. We hope our paper will stimulate accounting researchers to advance this literature.     

Determinants of Fair Trade Product Purchase Intention of Dutch Consumers According to the Extended Theory of Planned Behaviour

The study reported in this paper investigated the determinants of fair trade (FT) product purchase intention among Dutch consumers according to the extended Theory of Planned Behaviour and determined whether the effects of those determinants differ between male and female consumers. To test the various research hypotheses, an online survey with 499 respondents from a Dutch research panel was employed. Results of the multi-group analysis using a structural equation modelling approach reveal that FT product purchase intention of both male and female consumers are predicated on moral obligation and self-identity. The impact of subjective norm on purchase intention is statistically significant for male consumers only. Analyses reveal that, indeed, the impact of subjective norm on FT product purchase intention is moderated by consumers’ gender.     

Russian Nanotechnology Market: High-Technology Industry or Statistical Phenomenon

This article presents a medium-term forecast of the development of the Russian nanoindustry, taking into account the assumed transition of the industry from the formation stage to the investment growth stage. Problems associated with the estimated output volumes of products in the Russian nanoindustry are considered, since the trends recorded in the primary statistical data are very far from reflecting the real situation due to the imperfection of the system of statistics of nano-containing products, as well as a reduction of state funding and a decline in the intensity of research in the industry. It is concluded that a full-fledged industry has not been yet completely formed in Russia and it actually exists only as a statistical phenomenon; in addition, the project really set different objectives from the declared creation of a breakthrough high-technology branch.     

Predicting credit card delinquencies: An application of deep neural networks

The objective of this paper is twofold. First, it develops a prediction system to help the credit card issuer model the credit card delinquency risk. Second, it seeks to explore the potential of deep learning (also called a deep neural network), an emerging artificial intelligence technology, in the credit risk domain. With real-life credit card data linked to 711,397 credit card holders from a large bank in Brazil, this study develops a deep neural network to evaluate the risk of credit card delinquency based on the client's personal characteristics and the spending behaviours. Compared with machine-learning algorithms of logistic regression, naive Bayes, traditional artificial neural networks, and decision trees, deep neural networks have a better overall predictive performance with the highest F scores and area under the receiver operating characteristic curve. The successful application of deep learning implies that artificial intelligence has great potential to support and automate credit risk assessment for financial institutions and credit bureaus.