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The study aims to investigate the impact of additive manufacturing (AM) on the performance of a spare parts supply chain with a particular focus on underlying spare part demand patterns.

This work evaluates various AM-enabled supply chain configurations through Monte Carlo simulation. Historical demand simulation and intermittent demand forecasting are used in conjunction with a mixed integer linear program to determine optimal network nodal inventory policies. By varying demand characteristics and AM capacity this work assesses how to best employ AM capability within the network.

This research assesses the preferred AM-enabled supply chain configuration for varying levels of intermittent demand patterns and AM production capacity. The research shows that variation in demand patterns alone directly affects the preferred network configuration. The relationship between the demand volume and relative AM production capacity affects the regions of superior network configuration performance.

This research makes several simplifying assumptions regarding AM technical capabilities. AM production time is assumed to be deterministic and does not consider build failure probability, build chamber capacity, part size, part complexity and post-processing requirements.

This research is the first study to link realistic spare part demand characterization to AM supply chain design using quantitative modeling.

This study aims to investigate how configurations of boundary objects (BOs) support innovation teams in developing innovative product concepts. Specifically, it explores the effectiveness of different artefact configurations in facilitating collaboration and bridging knowledge boundaries during the concept development process.

The research is based on data from ten undergraduate innovation teams working with an industry partner in a creative industry. Six categories of BOs are identified, which serve as tools for collaboration. The study applies fsQCA (fuzzy-set qualitative comparative analysis) to analyse the configurations employed by the teams to bridge knowledge boundaries and support the development of innovative product concepts.

The findings of the study reveal two distinct groups of configurations: product envisioning and product design. The configurations within the “product envisioning” group support the activities of visioning and pivoting, enabling teams to innovate the product concept by altering the product vision. On the other hand, the configurations within the “product design” group facilitate experimenting, modelling and prototyping, allowing teams to design the attributes of the innovative product concept while maintaining the product vision.

This research contributes to the field of innovation by providing insights into the role of BOs and their configurations in supporting innovation teams during concept development. The results suggest that configurations of “product envisioning” support bridging semantic knowledge boundaries, while configurations within “product design” bridge pragmatic knowledge boundaries. This understanding contributes to the broader field of knowledge integration and innovation in design contexts.

Vertical lift (VL) assets are vital and expensive resources in humanitarian missions. What and where supplies are needed evolves in short time following a disaster. The purpose of this paper is to offer analysis to understand the range of capabilities of these assets.

The authors use scenario analysis to investigate the tradeoff between two key capabilities of VL, agility and speed. The authors do this by generating loads and distances randomly, based on historical data. In post hoc analysis, based on different factors, the authors investigate the impact of configuration of Expeditionary Strike Force (ESG) on providing disaster relief.

The authors find the most effective deployment of VL in a HADR mission is in supplying essentials to victims in a focused region. Delivering sustainment requirements leads to substantial shortfall for survival needs. If the configuration of the ESGs were changed for HADR, it would better-meet the demand.

Cargo capacity is modeled assuming every aircraft type was equal, in terms of mean and variance of cargo-capacity utilization. Detailed information on cargo-bay configurations was beyond the scope of our model and data. However, this means the benefit of standardizing cargo load-outs and the variability associated with randomized load-outs may be understated in the results.

The analysis presents decision-makers with projections of VL asset performance in the early stages of disaster relief, to assist in planning and contingency planning.

This research deals exclusively with the most critical but expensive capabilities for HADR: VL. The in-depth analysis illustrates the limitations and benefits of this capability.

This study advocates the importance of taking an evolutionary perspective in the strategic configuration of closed-loop supply chains (CLSC) in the transition to a circular economy. Building on the supply chain management and industrial dynamics research domains, an evolutionary analytical framework was developed and applied in the empirical context of the ongoing industrial transition to e-mobility.

This study is designed as an in-depth exploratory case study to capture the multi-layer dynamic complexities and their interplay in CSLC development. The empirical investigation was based on two-year interactions between the authors and various departments in a leading European heavy vehicle manufacturer. The proposed evolutionary analytical framework was used for investigating the dynamics of four CLSC configurations through ten possible trajectories.

The findings demonstrate that the evolution of each CLSC configuration comes with multiple challenges and requirements and point out the necessity for the co-development of technologies, product design and production, and infrastructure through long-term relationships among key supply chain actors. However, this evolutionary journey is associated with multiple dilemmas caused by uncertainties in the market and technology developments. All these factors were properly captured and critically analyzed, along with their interactions, thanks to the constructs included in the proposed evolutionary analytical framework.

The proposed evolutionary framework is applicable for examination of SC transformation in the context of market and technology development, and is particularly relevant for transitioning from linear SC to CLSC. The framework offers a single actor perspective, as it does not directly tackle dynamics and effects of actions taken by SC actors.

The developed framework can support SC managers in identifying, framing, and comparing alternative strategies for CLSC configuration in the transition process.

This study proposes the framework for understanding and guiding the evolutionary process of CLSC development. Its uniqueness lies in the integration of concepts from innovation and evolutionary theories coming from industrial dynamics and SCM literature streams.

This paper presents first sight on the longitudinal control strategy for an aircraft in the tandem wing configuration. It is an aerodynamic strongly coupled configuration that needs a lot of detailed aerodynamic analysis which describes the mutual impact of the main parts of the aircraft. The purpose of this paper is to build the numerical model that allows to make an analysis of necessary flaps (front and rear) deflection and prepare the control strategy for this kind of aircraft.

Aircrafts’ aerodynamic characteristics were obtained using the MGAERO software which is a commercial computing fluid dynamics tool created by Analytical Methods, Inc. This software uses the Euler flow model. Results from this software were used in the static stability evaluation and trim condition analysis. The trim conditions are the outcome of the optimisation process whose goal was to find the best front and rear flap deflection to achieve the best lift to drag (L/D) ratio.

The main outcome of this investigation is the proposal of strategy for the front and rear flap deflection which ensured the maximum L/D ratio and satisfied the trim condition. Moreover, the analysis of the mutual impact of the front and rear wings and the analysis of the control surface impact on the aerodynamic characteristic of the aircraft are presented.

In terms of aerodynamic computation, MGAERO software uses an inviscid flow model. However, this research is for the conceptual stage of the design and the MGAERO software grantee satisfied accurate respect to relatively low time of computations.

The ultimate goal is to build an aircraft in a tandem wing configuration and to conduct flying tests or wind tunnel tests. The presented result is one of the milestones to achieve this goal.

The aircraft in the tandem wing configuration is an aerodynamic-coupled configuration that needs detailed analysis to find the mutual interaction between the front and rear wings. Moreover, the mutual impact of the front and rear flaps is necessary too. Obtaining these results allowed this study to build the numerical model of the aircraft in the tandem wing configuration. It allows to find the best strategy of flap deflection, which allows to obtain the maximum L/D ratio and satisfy the trim condition.

This study aims to investigate the organisational structure to exploit data analytics in the educational sector. The paper proposes three different organisational configurations, which describe the connections among educational actors in a national system. The ultimate goal is to provide insights about alternative organisational settings for the adoption of data analytics in education.

The paper is based on a participant observation approach applied in the Italian educational system. The study is based on four research projects that involved teachers, school principals and governmental organisations over the period 2017–2020.

As a result, the centralised, the decentralised and the network-based configurations are presented and discussed according to three organisational dimensions of analysis (organisational layers, roles and data management). The network-based configuration suggests the presence of a network educational data scientist that may represent a concrete solution to foster more efficient and effective use of educational data analytics.

The value of this study relies on its systemic approach to educational data analytics from an organisational perspective, which unfolds the roles of schools and central administration. The analysis of the alternative organisational configuration allows moving a step forward towards a structured, effective and efficient system for the use of data in the educational sector.

Recent studies have highlighted the importance of adopting a contingency approach to configuring omnichannel warehouses. Nonetheless, research on how various contextual factors influence the selection of warehouse configuration is scarce. This study fills this knowledge gap by exploring how and why certain configurations fit in different omnichannel contexts.

A case study is conducted with six leading Swedish omnichannel retailers. Focusing on outbound warehouse configurations, data are collected through interviews, on-site observations, and secondary sources. A multistep analysis is made, including both pattern matching and explanation building.

The qualitative analysis reveals 16 contextual factors, of which assortment range, requested online order fulfillment times, goods size and total transactions are the most influential. The study shows how contextual factors create different challenges, thereby influencing the choice of the configurations. In addition to market dynamics and task complexity, the study describes four categories of the factors and related challenges that are particularly important in omnichannels: speed, space, economies of scale and tied-up capital.

The findings highlight the importance of understanding context and imply that multiple challenges may require trade-offs when selecting configurations, for example, regarding what storage, processes and resources to integrate or separate. To confirm, extend, challenge and further operationalize the ideas and observations put forward in this paper, an agenda with future research issues is given for this accelerating, contemporary phenomenon.

Managers could leverage the frameworks proposed for the contextual profiling of their current and future positions. The frameworks provide support for understanding the important challenges and potential trade-offs and developing aligned configurations.

This study is original in the way it provides in-depth, case study findings about contextual factors and their influence on omnichannel warehouse configuration.

The paper aims to explore the value generated by a specific configuration of a smart city's infrastructure by proposing a comparison between a silos configuration versus a crowd configuration at the data storage and processing level.

A system dynamics simulation is adopted to determine and compare the value created by the two configurations of smart city's infrastructure. The simulation outlines the flow of data and their positive and negative feedback that reinforce and hinder the smart city value generation.

The results demonstrate the huge impact of the availability of data for App developers when crowdsourcing configuration is adopted. Furthermore, results unveil the potential in value generation of a crowdsourcing smart city platform configuration compared to a silos architecture.

The authors have proposed a comparison between two alternative smart city digital platform configurations. The paper seeks to test the magnitude of the pros and cons of a crowdsourcing approach in setting up a smart city digital platform. The paper provides new guidelines for improving the data management of smart cities.

The purpose of this paper is to investigate the interplay between configuration dimensions (network structure, network flow, relationship governance, and service architecture) of last-mile supply networks (LMSN) and the underlying mechanisms influencing omnichannel performance.

Based on mixed-method design incorporating a multiple embedded case study, mapping, survey, and archival records, this research involved undertaking in-depth within- and cross-case analyses to examine seven LMSNs, employing a configuration approach.

The existing literature in the operations management (OM) field was shown to provide limited understanding of LMSNs within the emerging omnichannel context. Case results suggest that particular configurations have intrinsic capabilities, and that these directly influence omnichannel performance. The study further proposes a taxonomy of LMSNs comprising six forms, with two hybrids, supporting the notion of equifinality in configuration theory. Propositions are developed to further explore interdependencies between configurational attributes, refining the relationship between LMSN types, and factors influencing omnichannel performance.

The findings provide retailers with a set of design parameters for the (re)configuration of LMSNs and facilitate performance evaluation using the concept of fit between configurational attributes. The developed model sheds light on the consequential effects when certain configurational attributes are altered, preempting managerial attention. Given the global trend in urbanization, improved LMSN performance would have positive societal impacts in terms of service and resource efficiency.

This is one of the first studies in the OM field to critically analyze LMSNs and their behaviors in omnichannel retailing. Additionally, the paper offers several important avenues for future research.

Using the Panel Study of Entrepreneurial Dynamics II dataset, we examine the role that household income plays in the emergence of consumer-oriented start-ups by individual (solo), family-based (family), and non-family based start-ups (team). In particular, we address the research question: Does household income impact firm emergence, and if so, is emergence impacted differently based on start-up configuration? Our results indicate that household income does have a significant impact on average firm emergence, as well as on emergence growth rates for solo and family firms, playing an especially significant role for family firms. Furthermore, we found that household income is not a significant predictor of start-up activity completion for teams. Results from our study reinforce the extant literature on the benefits of starting a firm with teams, and suggests that these enterprise types may provide a more stable platform on which to launch a start-up. Implications of these findings and opportunities for future research are offered.