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This study aims to identify the key enablers for the adoption of Industry 4.0 (I4.0) in the automobile industry of India, which has been severely impacted by COVID-19. Adopting I4.0 will provide organizations greater flexibility and resilience during the COVID-19 pandemic.

Based on the literature review and experts’ opinions, 21 enablers were identified. Further, contextual relationships among the identified factors and a hierarchical digraph was developed by using the total interpretive structural modelling (TISM) technique. Finally, fuzzy cross-impact matrix multiplication applied to classification (MICMAC) analysis was conducted to classify the enablers into different categories based on their dependence and driving power.

The results indicate that top management support, clarity on government policy, strategic vision on I4.0 and development of new industrial policy are the most influential factors, with the highest driving power placed at the bottom of the TISM hierarchical model. Furthermore, agile workforce, smart HR practices and IT standardization and security are identified as linkage enablers with the most driving and dependency power.

The hierarchical TISM model and fuzzy MICMAC approach provide a comprehensive understanding of the I4.0 implementation process through a visual, logical structure to the managers. It will help the researchers and practitioners understand the contextual relationship among various enablers in fostering the I4.0 adoption process and digital reorganization in the automobile industry during the COVID-19 pandemic.

This study provides a holistic TISM hierarchical framework on I4.0 adoption that will elevate the next maturity level of innovation adoption and may act as a blueprint for automobile industries during the COVID-19 pandemic.

The purpose of this study is to understand the specific reasons why developed countries could easily start implementing innovative alternative fuel vehicles (e.g. electric vehicles or EVs) while the implementation in developing countries looks so far-fetched, with respect to infrastructure and downstream activities, and suggest the steps that can be taken to effectively address these issues.

This research undertakes case study – Tesla (USA), Mahindra and Mahindra (India) and Tata Motors to bring out the problems being faced by manufacturers from developing countries vis-a-vis the developed countries. The consumers’ side has been adequately represented though an in-depth survey. An analysis is also carried out as to how Tesla has accrued competitive leverage by innovating and vertical integration of up as well as downstream systems.

EV infrastructure remains grossly inadequate in developing countries like India. Two key areas that remain significantly unexplored are the installation of charging stations at parking lots and at the housing clusters and lack of competitive leverage in the services, processes and other downstream systems due to limited research and development capabilities. The performance metrics of domestic EVs lag those of conventional vehicles as well as foreign competitors like Tesla. Range anxiety is ranked as number one in the major concerns among the potential mass buyers of electric vehicles in India.

The value of the paper lies in an in-depth analysis of the relationship between horizontal and vertical perspectives as well as the impact of the product eco-system innovation on both the upstream as well as downstream nodes in the supply chain. Whereas the consumer attitudes and perspectives on e-mobility are inferred from a survey, the impact analysis matrix is used for analyzing the competitive leverage of Tesla through several features in the upstream, downstream and servitization.

This paper intends to explore and appraise the humanitarian supply chain management enablers (HSCMEs) for efficient and effective humanitarian operations. This research aims to analyze the interaction of enablers for humanitarian supply chain management (HSCM) using a proposed hybrid framework consists of fuzzy Delphi (FD), interpretive structural modeling (ISM)–matriced impacts croises multiplication appliquee a un classement (MICMAC) and revised Simos approach.

This research is deliberate to identify 28 HSCMEs through a literature review and experts' opinions; out of which 20 HSCMEs are selected using FD. ISM is applied to know contextual relationship among the selected HSCMEs for developing a hierarchical model. The MICMAC analysis classifies the HSCMEs based on driving power and dependence power to validate the developed hierarchical ISM structure. The revised Simos technique is used to prioritize the HSCMEs to access its relative significance in humanitarian operations.

The finding of the analysis suggests that government policy and leadership support obtained the highest priority, having high driving power and low dependence power is significantly strategic and emerged as the leading driver for the HSCM implementation.

ISM model presents an insight into interrelationship among HSCMEs, but this cannot quantify the impact of each HSCMEs.

Disaster relief aid agencies and stakeholders may focus on the enablers having high driving power and higher weight in designing and executing an effective and efficient humanitarian supply chain and to improve their activities and strategies of HSCM.

This research helps humanitarian logisticians and humanitarian organizations to make better decisions to improve their operational performance in pre and postdisaster phases.

This paper explores the application of proposed hybrid framework to analyze the HSCMEs that can be considered as the original contribution.

The purpose of this study is to examine the factors that drive superior social enterprise performance for women-led social enterprises. The authors examined the role of individual entrepreneur cognitive characteristics contributing to social enterprise performance and recommended a framework for women's social entrepreneur development.

The authors conducted an exploratory qualitative study of 22 women founders of social enterprises using a semi-structured questionnaire. In-depth interviews were conducted, and the transcripts were analyzed using thematic content analysis.

This study found a significant impact of self-efficacy on the performance of social enterprises among the studied subjects. Social support in the form of material, information and emotional support enhanced the ability of women social entrepreneurs to better achieve business sustenance and continuance of operations. The business skills of the women social entrepreneurs led them to move from just social impact generators to becoming thought leaders. The strong prosocial motivation of the founders contributed to building their resilience in the face of adversity.

This study extended the existing theories on social entrepreneurship by bringing the dimensions of entrepreneurial resilience in driving social enterprise performance along with business skills. Thus, it provided an enhanced explanation to the existing body of knowledge on contributors to superior social enterprise performance.

This study gathered insights into the role of entrepreneurship education focused on business skills, especially for women social entrepreneurs in achieving superior performance for their social ventures. This also reconfirmed the role of social support and how structurally this could be provided by educational systems to aspiring women social entrepreneurs.

The practice of social entrepreneurship by women social entrepreneurs has been growing. Its importance in developing economies because of its ability to make grassroots changes at the lower levels of society was substantive. Women have shown more inclination toward social business with an affinity for prosocial contribution. By focusing on nurturing these social enterprises, governments as well as global agencies like the United Nations and the World Economic Forum could accelerate social change. Furthermore, support for the current women social entrepreneurs as change-makers making a difference in society could be achieved.

To the best of the authors’ knowledge, this research study was one of the first studies on women social entrepreneurs focusing on the factors of self-efficacy, social support and entrepreneurial resilience contributing to social enterprise performance. This study combined the social entrepreneurship intention theory with entrepreneurial resilience and business skills to understand the factors leading to successful social enterprise performance for women social entrepreneurs.

The world's energy markets remain uncertain, with no accurate, optimistic forecasts. The authors of the research note that the energy crisis has a cumulative effect; its beginning has changed the rules of energy cooperation in the market. This contributed to increased demand, prices and competition. The European Union (EU) is a major market participant whose policies affect all energy connections. Russia is an energy core that offers its energy sources to balance the market. This is the economy; there is no talk of ‘political pressure.’ As a result, the authors conclude that the project ‘Nord Stream-2’ is not a political project but a purely commercial one, which will help reduce even spot prices in the European gas market because all other countries that extract gas cannot meet the growing energy needs of European countries.

Since Hayek’s pioneering work in the 1930s, the Austrian business cycle theory (ABCT) has been presented as a disequilibrium theory populated by less-than-perfectly rational agents. In contrast, we maintain that (1) the Austrian business cycle theory is consistent with rational expectations and (2) the post-boom adjustment process can be understood in an equilibrium framework. Hence, we offer a new interpretation of the existing theory. In doing so, we also address concerns raised with Garrison’s (2001) diagrammatic approach, wherein the economy moves beyond the production possibilities frontier. Our interpretation might accurately be described as a monetary disequilibrium approach grounded in an implicit general equilibrium framework with positive costs of reallocation.

Lester and Wolff (2013) find little empirical support for the Austrian business cycle theory. According to their analysis, an unexpected monetary shock does not alter the structure of production in a way consistent with the Austrian view. Rather than increasing production in early and late stages relative to middle stages, they find the opposite – a positive monetary shock typically decreases production in early and late stages relative to middle stages. We argue that the measures of production and prices employed by Lester and Wolff (2013) are constructed in such a way that makes them inappropriate for assessing the empirical relevance of the Austrian business cycle theory’s unique features. After describing how these measures are constructed and why using ratios of stages is problematic, we use a structural vector autoregression to consider the effects of a monetary shock on each stage of the production process. We show that, with a clearer understanding of what is actually being measured by the stage of process data, the results are consistent with (but not exclusive to) the Austrian view.

A vector autoregression model estimated on US data before and after 1980 documents systematic differences in the response of short- and long-term interest rates, corporate bond spreads and durable spending to news total factor productivity shocks. Interest rates across the maturity spectrum broadly increase in the pre-1980s and broadly decline in the post-1980s. Corporate bond spreads decline significantly, and durable spending rises significantly in the post-1980 period while the opposite short-run response is observed in the pre-1980 period. Measuring expectations of future monetary policy rates conditional on a news shock suggests that the Federal Reserve has adopted a restrictive stance before the 1980s with the goal of retaining control over inflation while adopting a neutral/accommodative stance in the post-1980 period.

We investigate in this paper whether income growth has played any role on inequality in all nine young South American democracies during the 1970–2007 period.

Given the nature of our dataset, the methodology is based on dynamic panel time-series analysis.

The results suggest that income growth has played a progressive role in reducing inequality during the period. Moreover, the results suggest that this negative relationship is stronger in the 1990s and early 2000s, a period in which the continent achieved macroeconomic stabilization, political consolidation, and much improved economic performance. On the contrary, during the 1980s (the so-called “lost decade”), the negative income growth experienced by the continent at the time has hit the poor the hardest (the poor usually are the ones to lose their jobs first in recessions), which has consequently led to an increase in inequality.

All in all, we suggest that consistent growth, and all that it encompasses, is an important equalizer that affects the poorer progressively and it should not be discarded as a plausible option by policy makers interested in a more equal income distribution.

The authors estimated the hidden overhead (capital diversion or wasteful use of capital) of Vietnam state-owned enterprises (SOEs).

The authors used a panel data set of 10,200 Vietnam SOEs observed over the period 2010–2018. The authors modeled and estimated the hidden overhead by using a stochastic production frontier. The hidden overhead parameter is modelled as the technical inefficiency in the production function.

Vietnam SOEs are very capital intensive. The hidden overhead (or the wasteful use of capital) is very high with an average rate of 69%.

Alternative estimation methods should be used to account for endogeneity in production inputs. Lack of comparison with the Vietnam private firms.

The paper proposes an original way to quantify hidden overhead (or capital diversion) in the Vietnam SOEs. The finding (a capital diversion rate of 69% on average) is astonishing. It calls for an urgent and profound reform of the Vietnam SOEs.