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This study aims to explore how subsidiary capabilities collectively configure for performance. Additionally, it seeks to examine whether these configurations of capabilities can provide equifinal solutions through developing a comprehensive research framework that focuses on subsidiaries in China.

With a data set collected through a questionnaire from 172 Korean multinational enterprises (MNEs) in China, this study used a fuzzy-set qualitative comparative analysis to detect the capability conditions and configurations. These configurations represent combinations of various subsidiary capabilities linked to high performance.

This study identified several complex pathways with distinct configurations for high subsidiary performance. The findings demonstrate the importance of configurations over individual conditions. Thus, the results highlight that the effectiveness of diverse capabilities, which are widely believed to singularly contribute to the high performance of MNE subsidiaries, depends on how each combines with other capabilities. Overall, the findings provide a richer and fine-grained understanding of the role and relative importance of various forms of MNE subsidiary capabilities and how the joint effect of these subsidiaries contributes to high performance.

This study suggests that MNE managers should comprehensively understand how subsidiary capabilities are configured to produce subsidiary performance outcomes. This specifically illustrates the importance of understanding the mutually conflicting yet collectively exhaustive results of multi-selective solutions and aims to align with China’s industrial and regional heterogeneity.

By examining the role of MNE subsidiary capability configurations, which may collectively influence the subsidiary’s performance, this study contributes to the literature. It elucidates how MNE subsidiaries may achieve superior performance by developing and possessing various capabilities tailored to the local context.

Despite the knowledge transfer between projects has received increasing attention from scholars, few scholars still conduct comprehensive research on inter-project knowledge transfer from both horizontal and vertical perspectives. Besides, knowledge transfer is affected by multiple antecedent conditions, and these factors should be combined for analysis. Therefore, this paper aims to explore the key factors influencing knowledge transfer between projects using the fuzzy-set qualitative comparative analysis (fsQCA) method from both horizontal and vertical perspectives and how these factors combine to improve the effectiveness of knowledge transfer (EKT) between projects.

First, nine factors affecting knowledge transfer between projects were identified, which were from the four dimensions of subject, relationship, channel, and context, namely temporary nature (TN), time urgency (TU), transmit willingness (TW), receive willingness (RW), trust (TR), project-project transfer channels (PPC), project-enterprise transfer channels (PEC), organizational atmosphere (OA), and motivation system (MS). Then, the source of the samples was determined and the data from the respondents was collected for analysis. Following the operation steps of the fsQCA method, variable calibration, single condition necessity analysis, and configuration analysis were carried out. After that, the configurations of influencing factors were obtained and the robustness test was conducted.

The results of the fsQCA method show that there are five configurations that can obtain better EKT between projects. Configuration 3 (∼TN * ∼TU * TW * RW * TR * ∼PPC * PEC * MS) has the highest consistency, indicating that it has the highest degree of the explanatory variable subset. Configuration 1 (∼TN * ∼TU * TW * RW * PEC * OA * MS) has the highest coverage, meaning that this configuration can explain most cases. Also, the five configurations were divided into three types: vertical transfer, horizontal-vertical transfer, and channel-free transfer category.

Firstly, this study explores the key factors influencing knowledge transfer between projects from four dimensions, which presents the logical chain of influencing factors more clearly. Then, this study divided the five configurations obtained into three categories according to the transfer direction: vertical, horizontal-vertical, and channel-free transfer, which gives implications to focus on both horizontal knowledge transfer (HKT) and (VKT) when studying knowledge transfer between projects. Lastly, this study helps to realize the exploration of combined improvement strategies for EKT, thereby providing meaningful recommendations for enterprises and project teams to facilitate knowledge transfer between projects.

This paper aims to study passive control techniques for transonic flow over a backward-facing step (BFS) using square-lobed trailing edges. The study investigates the efficacy of upward and downward lobe patterns, different lobe widths and deflection angles on flow separation, aiming for a deeper understanding of the flow physics behind the passive flow control system.

Large Eddy Simulation and Reynolds-averaged Navier–Stokes were used to evaluate the results of the study. The research explores the impact of upward and downward patterns of lobes on flow separation through the effects of different lobe widths and deflection angles. Numerical methods are used to analyse the behaviour of transonic flow over BFS and compared it to existing experimental results.

The square-lobed trailing edges significantly enhance the reduction of mean reattachment length by up to 80%. At Ma = 0.8, the up-downward configuration demonstrates increased effectiveness in reducing the root mean square of pressure fluctuations at a proximity of 5-step height in the wake region, with a reduction of 50%, while the flat-downward configuration proves to be more efficient in reducing the root mean square of pressure fluctuations at a proximity of 1-step height in the near wake region, achieving a reduction of 71%. Furthermore, the study shows that the up-downward configuration triggers early spanwise velocity fluctuations, whereas the standalone flat-downward configuration displays less intense crosswise velocity fluctuations within the wake region.

The findings demonstrate the effectiveness of square-lobed trailing edges as passive control techniques, showing significant implications for improving efficiency, performance and safety of the design in aerospace and industrial systems.

This paper demonstrates that the square-lobed trailing edges are effective in reducing the mean reattachment length and pressure fluctuations in transonic conditions. The study evaluates the efficacy of different configurations, deflection angles and lobe widths on flow and provides insights into the flow physics of passive flow control systems.

This study aims to obtain governance strategies for managing the complexity of megaprojects by analyzing the impact of individual factors and their configurations using the fuzzy-set qualitative comparative analysis (fsQCA) method and to provide references for project managers.

With the continuous development of the economy, society and construction industry, the number and scale of megaprojects are increasing, and the complexity is becoming serious. Based on the relevant literature, the factors affecting the complexity of megaprojects are determined through case analysis, and the paths of factors affecting the complexity are constructed for megaprojects. Then, the fsQCA method is used to analyze the factors affecting the complexity of megaprojects through 245 valid questionnaires from project engineers in this study.

The results support the correlation between the complexity factors of megaprojects, with six histological paths leading to high complexity and seven histological paths leading to low complexity.

It breaks the limitations of the traditional project complexity field through a “configuration perspective” and concludes that megaproject complexity is a synergistic effect of multiple factors. The study is important for enriching the theory of megaproject complexity and providing complexity governance strategies for managers in megaproject decision-making.

This study aims to propose a combined effect framework to explore the relationship between research and development (R&D) team networks, knowledge diversity and breakthrough technological innovation. In contrast to conventional linear net effects, the article explores three possible types of team configuration within enterprises and their breakthrough innovation-driving mechanisms based on machine learning methods.

Based on the patent application data of 2,337 Chinese companies in the biopharmaceutical manufacturing industry to construct the R&D team network, the study uses the K-Means method to explore the configuration types of R&D teams with the principle of greatest intergroup differences. Further, a decision tree model (DT) is utilized to excavate the conditional combined relationships between diverse team network configuration factors, knowledge diversity and breakthrough innovation. The network driving mechanism of corporate breakthrough innovation is analyzed from the perspective of team configurations.

It has been discerned that in the biopharmaceutical manufacturing industry, there exist three main types of enterprise R&D team configurations: tight collaboration, knowledge expansion and scale orientation, which reflect the three resource investment preferences of enterprises in technological innovation, network relationships, knowledge resources and human capital. The results highlight both the crowding-out effects and complementary effects between knowledge diversity and team network characteristics in tight collaborative teams. Low knowledge diversity and high team structure holes (SHs) are found to be the optimal team configuration conditions for breakthrough innovation in knowledge-expanding and scale-oriented teams.

Previous studies have mainly focused on the relationship between the external collaboration network and corporate innovation. Moreover, traditional regression methods mainly describe the linear net effects between variables, neglecting that technological breakthroughs are a comprehensive concept that requires the combined action of multiple factors. To address the gap, this article proposes a combination effect framework between R&D teams and enterprise breakthrough innovation, further improving social network theory and expanding the applicability of data mining methods in the field of innovation management.

This paper aims to investigate the innovation pathway of gerontechnological enterprises under the market-organization-technology (MOT) perspective through configuration analysis.

Based on the analytical framework of technology, organization and market, this paper conducts configuration analysis on the cases of 55 elderly-friendly enterprises in China combined with fuzzy-set qualitative comparative analysis (fsQCA).

First, this study identifies the three first-level preconditions affecting innovation performance: organization's architectural innovation, technology adapting to aging and market environment attention on the innovation pathway of gerontechnological enterprises. These three first-level conditions include six sub-conditions. Second, this study investigates three innovation pathways by analyzing the configuration effects of preconditions: Configuration 1, technology-balanced type; Configuration 2, organization-market linkage type and Configuration, 3 balanced type. Third, there are differences in the distribution of different configuration types in subdivided industries. The technology-balanced configuration is mainly concentrated in design-driven innovative enterprises, the organization-market linkage configuration is mainly concentrated in medical auxiliary equipment enterprises and the balanced configuration is mainly concentrated in smart elderly care service platform enterprises empowered by digital technology. Fourth, there are differences in the innovation impact paths of the same configuration type. However, the essence lies in the high-level innovation performance formed by the coordinated evolution of technology, organization and market factors, reflecting the characteristics of the same goal through different routes.

The authors' study generates new insights for innovation managers of gerontechnological enterprises about the innovation pathway.

This research enriches innovation management by integrating the linkage adaptation relationship among market, organization and technology factors; further research studies on the different configuration types suitable for different types of enterprises, as well as differentiated innovation pathways under the same configuration type, could contribute to the study on the innovation pathway under a premise of MOT.

Members in the international joint ventures (IJVs) for high-speed rail (HSR) projects usually engage in coopetition interactions to create common benefits (CB) and simultaneously safeguard private benefits (PB). Previous studies of coopetition and performance using variance-based methods usually ignore the combinational influence of diverse coopetition constructs on performance, which can be effectively compensated by adopting a configuration perspective. Therefore, this research aims to ascertain various combinations of three coopetition constructs (coopetition relationship, coopetition capability and coopetition strategy) that lead to high IJVs’ performance through a configuration approach.

First, the research framework of coopetition configuration was established, and the key constructs were operationalized, which were validated by expert interviews. Then the information on 12 HSR IJVs was collected and quantified through nine rounds of interviews and a questionnaire survey. Later, the fuzzy-set qualitative comparative analysis (fsQCA) was applied to explore what coopetition configurations benefit the CB or PB achievement.

Configuration results indicate that six coopetition configurations lead to CB outcome and seven configurations lead to PB outcome. Based on the results, coopetition contexts are divided into four categories: firm-based coopetition, project-based coopetition, firm-project-based coopetition and none-based coopetition. Then, a selection scheme for coopetition strategies in various contexts has been developed. The results also show that the core conditions mostly appear in the coopetition relationships and coopetition strategies dimensions, and the optimal coopetition strategies vary in different contexts.

This study enhances the theoretical understanding of coopetition in HSR IJVs and assists relative HSR industrialists, as well as the mega infrastructure project managers, in IJVs’ implementation. The configuration perspective of this paper also contributes to a systemic and holistic view of coopetition in HSR IJVs.

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.

Driven by the dual-carbon target and the widespread digital transformation, leveraging digital technology (DT) to facilitate sustainable, green and high-quality development in heavy-polluting industries has emerged as a pivotal and timely research focus. However, existing studies diverge in their perspectives on whether DT’s impact on green innovation is synergistic or leads to a crowding-out effect. In pursuit of optimizing the synergy between DT and green innovation, this paper aims to investigate the mechanisms that can be harnessed to render DT a more constructive force in advancing green innovation.

Drawing from the theoretical framework of resource orchestration, the authors offer a comprehensive elucidation of how DT intricately influences the green innovation efficiency of enterprises. Given the intricate interplay within the synergistic relationship between DT and green innovation, the authors use the fuzzy-set qualitative comparative analysis method to explore diverse configurations of antecedent conditions leading to optimal solutions. This approach transcends conventional linear thinking to provide a more nuanced understanding of the complex dynamics involved.

The findings reveal that antecedent configurations fostering high green innovation efficiency actually differ across various stages. First, there are three distinct configuration patterns that can enhance the green technology research and development (R&D) efficiency of enterprises, namely, digitally driven resource integration (RI), digitally driven resource synergy (RSy) and high resource orchestration capability. Then, the authors also identify three configuration patterns that can bolster the high green achievement transfer efficiency of enterprises, including a digitally optimized resource portfolio, digitally driven RSy and efficient RI. The findings not only contribute to advancing the resource orchestration theory in the digital ecosystem but also provide empirical evidence and practical insights to support the sustainable development of green innovation.

The findings can offer valuable insights for enterprise managers, providing decision-making guidance on effectively harnessing the innovation-driven value of internal and external resources through resource restructuring, bundling and leveraging, whether with or without the support of DT.

The research findings contribute to heavy-polluting enterprises addressing the paradoxical tensions between digital transformation and resource constraints under environmental regulatory pressures. It aims to facilitate the simultaneous achievement of environmental and commercial success by enhancing their green innovation capabilities, ultimately leading to sustainability across profit and the environment.

Compared with previous literature, this research introduces a distinctive theoretical perspective, the resource orchestration view, to shed light on the paradoxical relationship on resource-occupancy between DT application and green innovation. It unveils the “black box” of how digitalization impacts green innovation efficiency from a more dynamic resource-based perspective. While most studies regard green innovation activities as a whole, this study delves into the impact of digitalization on green innovation within the distinct realms of green technology R&D and green achievement transfer, taking into account a two-stage value chain perspective. Finally, in contrast to previous literature that predominantly analyzes influence mechanisms through linear impact, the authors use configuration analysis to intricately unravel the complex influences arising from various combinatorial relationships of digitalization and resource orchestration behaviors on green innovation efficiency.

As a response to global population growth and increasing demand for food, farmers have been complementing traditional agriculture practices with vertical farming (VF) and indoor hydroponic systems. To facilitate the growth of the VF industry, this paper aims to identify business model elements and their configurations that lead to high firm performance.

The research goals were met by conducting literature reviews coupled with a fuzzy-set qualitative comparative analysis (fsQCA) on five business model elements, “superior” OR “strong” performance as two possible outcomes, and the top-ranked global VF growers listed in the Crunchbase Database.

From the fsQCA results, it was observed that several business model configurations lead to strong firm performance. Vertical farms growing in urban settings and having strong customer engagement platforms, coupled with a presence of business-to-business (B2B) sales channels, are more consistently associated with superior performance. These results imply that the decision configuration of location, along with customer engagement activity and sales activity are differentiating factors between good firm performance and superior firm performance in the case of vertical farms.

This paper contributes to expanding the knowledge of business model theory, business model configurations and VF management, providing specific guidelines for vertical farm owners and investors related to decision-making for higher firm performance, as well as positive environmental, social and economic impact.