Search results

Within the current institutional landscape, characterized by increased societal and governmental emphasis on environmental preservation, there is growing interest in the potential of digital transformation (DT) to advance the circular economy (CE). Nonetheless, the empirical substantiation of the connection between DT and CE remains limited. This study seeks to investigate the impact of DT on CE at the organizational level and examine how various institutional factors may shape this relationship within the Chinese context.

To scrutinize this association, we construct a research framework and formulate hypotheses drawing on institutional theory, obtaining panel data from 238 Chinese-listed high-tech manufacturing firms from 2006 to 2019. A regression analysis approach is adopted for the sample data.

Our regression analysis reveals a positive influence of DT on CE performance at the organizational level. Furthermore, our findings suggest that the strength of this relationship is bolstered in the presence of heightened regional institutional development and industry competition. Notably, we find no discernible effect of a firm’s political connections on the DT–CE performance nexus.

This study furnishes empirical evidence on the relationship between DT and CE performance. By elucidating the determinants of this relationship within the distinct context of Chinese institutions, our research offers theoretical and practical insights, thus laying the groundwork for subsequent investigations into this burgeoning area of inquiry.

In this case study, we examine how a citrus peel valorising company based in the Netherlands was able to adopt a circular business model while navigating regulatory, managerial, and supply chain-related barriers.

In-depth, semi-structured interviews with key personnel in the company, notes from field observations, photographs of the production process, and documents from a legal judgement served as data for this single, qualitative case study. Data were coded inductively using the in vivo technique and were further developed into four themes and a case description.

Results from our study indicate that the regulatory and political contexts in the Netherlands were critical to the company’s success. Like in the case of most fruitful industrial symbioses, partnerships founded on mutual trust and economically appealing value propositions played a crucial role in ensuring commercial viability. Collaborating with larger corporations and maintaining transparent communication with stakeholders were also significant contributing factors. Lastly, employees’ outlook towards circularity combined with their willingness to learn new skills were important driving factors as well.

In addition to expanding the scholarship on the adoption of circular business models, this research offers novel insights to policymakers and practitioners. It provides empirical evidence regarding the importance of public awareness, adaptable legislation, and harmonised policy goals for supporting sustainable entrepreneurship in the circular economy.

Corruption perception is essential to study because it can shape people’s attitudes toward the government. Thus, the purpose of this paper is to address this key question: what factors are associated with a non-expert’s judgment of whether Canada is corrupt?

This study uses the World Value Survey conducted in Canada in October 2020. This survey is based on a nationally representative sample of a cross-section of adult Canadian residents, including Canadian citizens and permanent residents and those who are neither Canadian citizens nor permanent residents.

Based on this study, some conclusions can be made. First, people accessing corruption news from the traditional news media are less likely than those receiving information from the new media to perceive the state (in this case, Canada) as corrupt. Second, people who have less confidence in public institutions are more likely to perceive a country as corrupt. Third, people who participate in electoral and non-electoral forms of political participation are more likely to perceive the state and its public officials as corrupt. Fourth, regardless of which political party is in power, individuals who lean right politically are more likely than those on the left to perceive the state as corrupt. Finally, immigrants are less likely than those born in Canada to perceive the state as corrupt. This work enriches the literature on the substantive understanding of the factors associated with corruption perception.

Studies investigating factors associated with public perception of corruption tend to focus on developing countries. The current study contributes to filling this gap in knowledge by examining correlates of corruption perception in Canada. As a result, this study contributes to the literature on factors associated with corruption perception, especially in the developed country context.

This study aims to examine how the starting of business by females can be promoted by assessing critical levels of microfinance institutions (MFIs) penetration that policymakers must endeavor to maintain and/or attain in order for female unemployment not to represent a constraint in the doing of business. A constraint in doing business is understood in terms of the procedure that a woman has to go through to start a business.

The focus of the study is on 44 countries in Sub-Saharan Africa for the period 2004–2018, while the empirical evidence is based on interactive quantile regressions.

The following findings are established. The validity of tested hypotheses is exclusively apparent in the lowest and highest quantiles of the conditional distribution of the procedure women have to go through to start a business. MFI penetration levels needed to reverse the unfavorable incidence of female unemployment in doing business are provided. These are minimum MFIs penetration thresholds that are required in order for female unemployment not to negatively affect the procedure that a woman should go through to start a business.

The study complements the extant literature by assessing critical microfinance penetration levels that are needed to promote female doing of business, contingent on existing levels of female doing of business.

This paper aims to define a hierarchical and multi-criteria framework based on pillars of the Modernization of Higher Education to evaluate European Accounting Doctoral Programmes (EADE-Model).

The authors applied a quali-quantitative methodology based on the analytic hierarchy process and the survey approach. The authors conducted an extensive literature and regulation review to identify the dimensions affecting the quality of Doctoral Programmes, choosing accounting as the relevant and pivotal field. The authors also used the survey to select the most critical quality dimensions and derive their weight to build EADE Model. The validity of the proposed model has been tested through the application to the Italian scenario.

The findings provide a critical extension of accounting ranking studies constructing a multi-criteria, hierarchical and updated evaluation model recognizing the role of doctoral training in the knowledge-based society. The results shed new light on weak areas apt to be improved and propose potential amendments to enhance the quality standard of ADE.

Theoretical and practical implications of this paper are directed to academics, policymakers and PhD programmes administrators.

The research is original in drafting a hierarchical multi-criteria framework for evaluating ADE in the Higher Education System. This model may be extended to other fields.

Reverse logistics services are designed to move goods from their point of consumption to an endpoint to capture value or properly dispose of products and materials. Artificial intelligence (AI)-based reverse logistics will help Micro, Small, and medium Enterprises (MSMEs) adequately recycle and reuse the materials in the firms. This research aims to measure the adoption of AI-based reverse logistics to improve circular economy (CE) performance.

In this study, we proposed ten hypotheses using the theory of natural resource-based view and technology, organizational and environmental framework. Data are collected from 363 Indian MSMEs as they are the backbone of the Indian economy, and there is a need for digital transformation in MSMEs. A structural equation modeling approach is applied to analyze and test the hypothesis.

Nine of the ten proposed hypotheses were accepted, and one was rejected. The results revealed that the relative advantage (RA), trust (TR), top management support (TMS), environmental regulations, industry dynamism (ID), compatibility, technology readiness and government support (GS) positively relate to AI-based reverse logistics adoption. AI-based reverse logistics indicated a positive relationship with CE performance. For mediation analysis, the results revealed that RA, TR, TMS and technological readiness are complementary mediation. Still, GS, ID, organizational flexibility, environmental uncertainty and technical capability have no mediation.

The study contributed to the CE performance and AI-based reverse logistics literature. The study will help managers understand the importance of AI-based reverse logistics for improving the performance of the CE in MSMEs. This study will help firms reduce their carbon footprint and achieve sustainable development goals.

Few studies focused on CE performance, but none measured the adoption of AI-based reverse logistics to enhance MSMEs’ CE performance.

This study aims to develop an entrepreneurial business model capable of addressing and preventing the exploitation and inequality that traditionally have resulted from entrepreneurship, particularly in emerging economies.

The research uses systems thinking, the first law of cybernetics, and the principles of harmony to formulate a systemic solution to the problem, which it exemplifies via six purposefully selected short cases drawn from diverse industry sectors and economies.

This paper demonstrates how the conventional model of entrepreneurship, often associated with colonial exploitation and resultant inequalities, can be transformed into a triple bottom line model—harmonious entrepreneurship – that integrates the traditional economic, eco-, humane, and social approaches and creates a synergy where profit, planet, and people are in harmony. The model challenges the profit maximisation/shareholder value doctrine of business success.

Only six cases are presented here, and there is a need for further research in different political-economic contexts and industry sectors. Also, the way entrepreneurship is taught needs to change so that it addresses the sustainability challenge in general and the problem of inequality in particular.

There needs to be a change in the entrepreneurial mindset and the way entrepreneurship is taught and potential entrepreneurs are trained if entrepreneurship is to address the sustainability challenge in general and the problem of inequality in particular.

This is a novel approach to the study of entrepreneurship and its impact on inequality that shows how it can ameliorate and/or prevent inequality, particularly in emerging economies, by adopting a more holistic approach to business success and supplanting “having and needing” with “being and caring”.

There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework for structurally identifying production functions to a more general case when latent firm productivity is multi-dimensional, with both factor-neutral and (biased) factor-augmenting components. Unlike alternative methodologies, the proposed model can be identified under weaker data requirements, notably, without relying on the typically unavailable cross-sectional variation in input prices for instrumentation. When markets are perfectly competitive, point identification is achieved by leveraging the information contained in static optimality conditions, effectively adopting a system-of-equations approach. It is also shown how one can partially identify the non-neutral production technology in the traditional proxy variable framework when firms have market power.

The purpose of this study is to create a methodological approach for identifying priority areas for science and technology (S&T) development and its empirical application within the city of Moscow. This research uncovers a wide range of multicultural and multidisciplinary global trends that will affect the development of major cities in an era of complexity and uncertainty, including the inherent complexity of urban contexts, demographic and socioeconomic trends, as well as scientific and ecological factors.

The methodological approach is based on classic foresight instruments. Its novelty lays in the blending of qualitative and quantitative methods specially selected as the most appropriate for the identification of S&T areas in an era of complexity and uncertainty, including horizon scanning, bibliometric analysis, expert surveys and the construction of composite indexes with respect to the scope and resources of the research and the selected object for empirical application – Moscow, which is one of the world’s largest megacities. The analysis was performed for the period of 2009–2018 and expert procedures took place in 2019.

As a result, 25 global trends were identified, evaluated and discussed over the course of an expert survey and subsequent expert events. Ten priority areas of S&T development were determined, including 62 technological sub-areas within them and the most important market niches for all identified technological sub-areas, which could be useful for the world’s megacities. The results of this study are illustrated using the construction sector. Based on the conducted research and results, a list of recommendations on S&T policy measures and instruments were suggested, including the creation of the Moscow Innovation Cluster, which by the end of 2023 contained more than 6,000 projects and initiatives, selected using the findings of this investigation.

This research contributes to the existing literature and research agenda of setting priorities for S&T development and shows how it can be done for a megacity. The blended foresight methodology that was created within the study satisfies the criteria of scientific originality, is repeatable for any interested researcher, is applicable to any other city in the world and demonstrates its high efficiency in empirical application. It could be used for creating new agenda items in S&T policy, setting S&T priorities for a megacity and integrating the results into decision-making processes. This study provides recommendations on the further implementation of the designed methodology and results into a policymaking system. Moreover, the example of the Moscow Innovation Cluster, which was created based on the results of our research, demonstrates these recommendations’ practical significance in real life, which is quite valuable. The limitation of this study is that it is not devoted to urban planning issues directly or the promotion of R&D areas; it is about setting promising S&T priorities in an era of complexity and uncertainty for megacities.