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This paper aims to propose an interpretive framework to understand how machine learning (ML) affects the way companies interact with their ecosystem and how the introduction of digital technologies affects the value co-creation (VCC) process.

This study bases on configuration theory, which entails two main methodological phases. In the first phase the authors define the theoretically-derived interpretive framework through a literature review. In the second phase the authors adopt a case study methodology to inductively analyze the theoretically-derived domains and their relationships within a configuration.

ML enables multi-directional knowledge flows among value co-creators and expands the scope of VCC beyond the boundaries of the firm-client relationship. However, it determines a substantive imbalance in knowledge management power among the actors involved in VCC. ML positively impacts value co-creators’ performance but also requires significant organizational changes. To benefit from VCC via ML, value co-creators must be aligned in terms of digital maturity.

The paper answers the call for more theoretical and empirical research on the impact of the introduction of Industry 4.0 technology in companies and their ecosystem. It intends to improve the understanding of how ML technology affects the determinants and the process of VCC by providing both a static and dynamic analysis of the topic.

This paper considers locating congested fast charging stations (FCSs) and deploying chargers in a stochastic environment, while the related studies have predominantly focused on problems in deterministic environments. Reducing the inconvenience caused by congestion at FCSs is an important challenge for FCS service provider. This is the underlying motivation for this study to consider a problem for FCS network design with the congestion restriction in a stochastic environment. We proposed a maximal coverage problem subject to budget constraints and a congestion restriction in order to maximize the demand coverage. With the derivation of the congestion restriction in the considered stochastic environment, the problem is formulated into an integer programming model. A real-life case study is conducted and managerial implications are drawn from its results.

This research paper aims to explore the impact artisan cooperatives have upon women employed in Sub-Saharan Africa. Impacts were detailed using the theoretical framework of social capital theory to demonstrate the networks within artisan cooperatives that connect to greater opportunities for social and economic benefits.

A phenomenological approach was used for this study based upon the shared experiences of women who were leading artisan cooperatives in Sub-Saharan Africa. This study included semi-structured interviews over Zoom with Chief Entrepreneur Founders of artisan cooperatives located in Sub-Saharan Africa. Documents from the cooperatives were analyzed to triangulate the cooperatives’ current projects and efforts.

Three prevalent themes emerged: (1) key partnerships, (2) benefits of the cooperative and (3) change and growth among the women and communities. Empowerment was felt through both economic and social impacts upon the women.

This article captures the perspective of the Chief Entrepreneur Founders and their observations and experiences the women shared with them. Emic perspectives from the women who participate in the artisan cooperatives is the focus of future research.

These social enterprises serve as exemplary models for other cooperatives to provide dignified and sustainable work to impact the lives of women serving in these communities.

This study contributes research on social entrepreneurship within artisan cooperatives. It provides a baseline for further research on the artisan sector specifically for the sustainable development goals of gender equality, decent work and economic growth.

Though an accumulating body of study has analysed monetary policy transmission in India, there are few studies examining the differential impact of monetary policy action. Against this backdrop, this study aims to analyse the differential impact of monetary policy on aggregate demand, aggregate supply and their components along with the general price level in India.

The study develops a structural macroeconometric model, which is primarily aggregate and eclectic in nature. The generalized method of movements is used for estimation of behavioural equations, while a Gauss–Seidel algorithm is used for model simulation purposes.

The paper presents the results of two policy simulations from the estimated model that highlight the differential impact of monetary policy. The first one, hike in the policy rate by 5% and second is a reduction in bank credit to the commercial sector by 10%. The results from the first policy simulation experiment reveal that interest hike has a significant negative impact on aggregate demand, aggregate supply and general price level. However, the maximum impact is borne by investment demand and imports followed by private consumption. While as among the components of aggregate supply maximum impact is born by infrastructure output followed by the manufacturing and services sector with the agriculture sector found to be insensitive in nature. The results from the second policy simulation experiment revealed that pure monetary shocks have a significant negative impact on aggregate demand, aggregate supply and general price level. However, the maximum impact is born by private consumption and imports followed by investment demand. While as among components of aggregate supply maximum impact is borne by infrastructure followed by the manufacturing and services sector with the agriculture sector found to be insensitive in nature. From both policy simulation experiments, the study highlighted the relative importance of the income absorption approach as opposed to the expenditure switching effect.

The results obtained in this study provides a strong framework for design the monetary policy framework. The results are in a view of the differential impact of monetary policy action among the components of both aggregate demand and aggregate supply. This reflection of differential impact has immense significance for the macroeconomic stabilization as the central bank will have to weigh the varying repercussion of its actions on different sectors. For instance, the decline in output after monetary tightening might be conceived as mild from an overall perspective, but it can be appreciable for some sectors. This differential influence will have an implication for policy design to care for distributional aspects, which otherwise could be neglected/disregarded. Similarly, the output decline may be as a result of either consumption postponement or a temporary slowdown in investment. However, the one emanating due to investment decline will have lasting growth implications compared to a decline in consumer demand. In addition, the relative strength of expenditure changing or expenditure switching policies of trade balance stabilization may have varying consequences in the aftermath of monetary policy shock. Accordingly information on the relative sensitiveness/insensitiveness of different sectors/ components of aggregate demand towards monetary policy actions furnish valuable insights to monetary authorities in framing appropriate policy.

The work carried out in the present paper is motivated by the fact that although a number of studies have examined the monetary transmission mechanism in India, a very few studies examining the differential impact of monetary policy action. However, to the best of the knowledge, there is no such studies, which have examined the differential impact of monetary policy in the structural macro-econometric framework. The paper will enrich the existing literature by providing a detailed account of the differential impact of monetary policy among the components of both aggregate demand and aggregate supply in response to an interest rate hike, as well as a decrease in the money supply.