Search results

This paper adopts a multi-tier perspective and aims to explore challenges of small and medium-sized enterprises (SMEs) in collaborative manufacturing amid the emergence of dedicated B2B platforms. Original equipment manufacturers welcome formation of demand-driven collaborations between SME suppliers to facilitate ramp-up of production capacity. While being potentially beneficial to suppliers, such collaborations face various barriers.

An exploratory study of 17 suppliers within the European Union’s aerospace industry was undertaken. The study comprised two stages. In the first stage, suppliers’ answers to self-administered interviews were analysed using thematic analysis. In the second stage, interactions between the barriers were determined through interviews with experienced SME collaboration facilitators. The authors apply system dynamics modelling to analyse the links between barriers and identify re-enforcing and balancing loops of other factors.

The authors establish five major groups of barriers to collaboration impeding: market transparency, access to orders, partner trust, contracting and (e) data sharing and coordination. The authors model application of four enablers that facilitate barrier removal for technology-enabled supply chains: digital platforms, supplier development, smart contracts and Industry 4.0.

The study is limited by the data collection from the aerospace industry; validation of the models in other low-volume high-variability manufacturing sectors is needed.

The reader will learn about the barriers which impede demand-driven SME collaboration within manufacturing supply chains, interrelationships between these barriers and suggestions about how to remove them. SME cluster managers will find managerial implications particularly interesting as they will help them to overcome collaboration concerns and better prepare cluster members for Industry 4.0.

The models developed within this study can be used to explore the effects of intervening at critical points in the model to create virtuous improvement cycles between key barriers and related variables in the model. This can help decision-making and policymaking in the area of supply chain integration.

There is currently a lack of studies about how the existing barriers amplify and de-amplify themselves and what the managerial approaches to tackle the barriers are. It is unclear how far companies will go in terms of information sharing, given the trust levels, power dynamics and governance structures evident in supply chains. This study contributes by explaining the reinforcing interaction between the barriers and showing ways to overcome these using enablers.

To give an overview of the papers contained in this Special Issue.

Looks at how each of the papers reflects the theme of the Special Issue, “Complexity and IT design and evolution”.

The collection of papers in this Special Issue addresses complexity, drawing on multi‐faceted, multi‐theoretical lines of inquiry.

Frameworks from complexity science, institutional theory, social science, philosophy, and recent thinking in science and technology studies (STS) are used as theoretical lenses to conceptualize and analyze complexity in IS and to offer ways to mitigate it.

This conceptual paper aims to present a perspective on how to engineer sustainability through the prism of Industry 4.0 technologies and outline propositions to guide future research.

This study presents a literature review developing four research propositions, focusing on the nine leading technologies underpinning Industry 4.0 to engineer economic, environmental and social sustainability dimensions.

The authors derive benefits and challenges of Industry 4.0 technologies across all three business model elements: value creation, value delivery and value capture. The authors derive those for the economic, environmental and social dimensions of sustainability. Thereupon, we develop several propositions for future research.

The authors provide suggestions to practice how to better achieve value in all three sustainability dimensions through implementing a business model perspective, ecosystem thinking, societal demands and Data Governance and AI integration.

By linking societal aspects of Industry 4.0 technologies with environmental, and economic aspects, the authors provide several suggestions how to implement Industry 4.0. For instance, policymakers are recommended to support entire ecosystems than isolated solutions.

The paper contributes to extant literature by conceptualising how Industry 4.0 can leverage value in reaching sustainability in all three dimensions and produce broader ecosystems-wide impacts.