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The challenges faced by China's high-end equipment manufacturing (HEEM) industry are becoming clearer in the process of global supply chain (GSC) reconfiguration. The purpose of this study is to investigate how China's HEEM industry has been affected by the GSC reconfiguration, as well as its short- and long-term strategies.

The authors adopted a multi-method approach. Interviews were conducted in Phase 1, while a three-round Delphi survey was conducted in Phase 2 to reach consensus at the industry level.

The GSC reconfiguration affected China's HEEM supply chain (SC). Its direct effects include longer lead times, higher purchasing prices and inconsistent supply and inventory levels of key imported components and materials. Its indirect effects include inconsistent product quality and cash flows. In the short term, China's HEEM enterprises have sought to employ localized substitutes, while long-term strategies include continuous technological innovation, industry upgrades and developing SC resilience.

This study not only encourages Chinese HEEM enterprises to undertake a comprehensive examination of their respective industries but also provides practical insights for SC scholars, policymakers and international stakeholders interested in how China's HEEM industry adapts to the GSC reconfiguration and gains global market share.

Resource reconfiguration enables firms to adapt in dynamic environments by supplementing, removing, recombining, or redeploying resources. Whereas prior research has underscored the merits of resource reconfiguration and the modes for implementing it, little is known about the antecedents of this practice. According to prior research, under given industry conditions, resource reconfiguration is prompted by a firm’s corporate strategy and by characteristics of its knowledge assets. We complement this research by identifying learning from performance feedback as a fundamental driver of resource reconfiguration. We claim that performance decline relative to aspiration motivates the firm’s investment in knowledge reconfiguration, and that this investment is reinforced by the munificence of complementary resources in its industry, although uncertainty about the availability of such resources limits that investment. Testing our conjectures with a sample of 248 electronics firms during the period 1993–2001, we reveal a clear distinction between exploitative reconfiguration, which combines existing knowledge elements, and exploratory reconfiguration, which incorporates new knowledge elements. We demonstrate that performance decline relative to aspiration motivates a shift from exploitative reconfiguration to exploratory reconfiguration. Moreover, munificence of complementary resources mitigates the tradeoff between exploratory and exploitative reconfigurations, whereas uncertainty weakens the motivation to engage in both types of reconfiguration, despite the performance gap. Nevertheless, codeployment, which extends the deployment of knowledge assets to additional domains, is more susceptible to uncertainty than redeployment, which withdraws those assets from their original domain and reallocates them to new domains. Our study contributes to emerging research on resource reconfiguration, extends the literature on learning from performance feedback, and advances research on balancing exploration and exploitation.

Strategic management research has shown growing interest in understanding the dynamic resource reconfiguration processes through which firms grow, evolve, and sustain profitability. The goal of our study is to understand how dynamic resource reconfigurations enable firms to pursue growth opportunities. We use the methods of inductive theory building from case studies to elaborate current theoretical understanding about how firms draw on both internal and external resources in the pursuit of growth. We examine the patterns of resource reconfigurations through which Yahoo and Google powered their early growth strategies in their first 10 years of existence. We analyze a total of 192 new product launches in 43 markets by the two firms to capture how they reconfigured resources dynamically. Our analysis reveals that both firms developed highly dynamic strategies exhibiting both surprising similarities and differences. These similarities and differences provided the basis for our theoretical insights about the development of what we term “dynamic resource platforms,” comprising of (a) dynamic resource shifts; (b) targeted resource orchestration; and (c) complementary processes balancing dynamism and capability development. These ideas contribute novel theoretical insights to current strategic management research on dynamic capabilities and on resource reconfiguration and redeployment.

Firms operate in a market for their corporate assets, wherein important assets being bought and sold are business units. This market is therefore a primary mechanism for firm reconfiguration, and offers the opportunity for firms to gain performance advantage as they prepare for and engage in their boundary-changing moves. This paper focuses on resource reconfiguration between firms, and examines internally and externally driven sources of performance heterogeneity in firms’ use of the market for firm reconfiguration. Viewing between-firm resource reconfiguration through three theoretical lenses surfaces several potential avenues for firm differentiation. For one, the necessity of firms’ possessing capabilities to execute both sides of the external resource reconfiguration transaction – acquisition and divestiture capabilities – is revealed. For another, the institutional prerequisites that are needed in the operating environment for a firm to build a sustainable resource reconfiguration strategy are brought to the fore, and are well illustrated by the private equity industry. Lastly, the potential benefits of using the transactional view of firm scope to animate the study of external resource reconfiguration are raised. Taken together, these elements lead to a research agenda around resource reconfiguration across firm boundaries.

To achieve digital transformation, organizations have continued to rely on integrating the capabilities of information technology (IT) to facilitate decision-making and developing their reconfiguration capability to enhance agile operations. The pressure imposed by digital transformation necessitates investigations on leveraging different IT capabilities to attain substantial organizational agility in an optimal configuration. This study aims to provide a new perspective on balancing IT structural capabilities and proposes a framework for evaluating their coalignment and complementary returns based on resource orchestration theory.

A multi-method approach is used to evaluate the research model. This study tests hypotheses and explores the potential coalignment and complementary returns of balance in structural models and response surface analysis. Then, it analyzes the qualitative data and provides complementary findings to corroborate and confirm complex relationships.

Balanced structural IT capabilities facilitate organizational agility but cooperate differently with internal (e.g. IT proactive stance) and external (e.g. environmental volatility) environmental factors. Balance between IT integration and reconfiguration must be maintained from several approaches during search/selection and configuration/deployment.

This study theorizes and empirically investigates the interactive mechanisms of two IT capabilities in influencing organizational agility under different boundary conditions. It enriches the understanding of balancing capabilities for organizational agility in digital transformation.

The purpose of this paper is to develop the methodology which can facilitate the concept of reconfiguration in the manufacturing system.

Design methodology includes the calculation of similarity matrix, formation of part family, and selection of part family. ALC algorithm has been used for part family formation and three criteria have been considered for the selection of part family. These criteria are reconfiguration effort, under-utilization cost, and floor space cost. AHP has been used to calculate the weights of criteria and reference ideal method has been used for the selection of alternatives.

In the manufacturing system, machines should be grouped on the basis of reconfiguration cost. When the time period is less, light machines and Group 1 machines are added and removed. In the case study, the concept of reconfiguration is useful for families (A, B, C, D). Machines can be reused by adding/removing some modules of machines. The concept of reconfiguration becomes more useful when it is implemented with lean manufacturing. Lean manufacturing techniques Jidoka and Poka-yoke are used to increase the diagnosability of the system.

Industrial case study has been considered.

Market competition is increasing rapidly and it increases the demand and variety of products, due to which manufacturing enterprises are forced to adapt a manufacturing system which can adjust its capacity and functionality quickly at low cost. To reconfigure manufacturing system from one product/product family to another product/product family, changes can be done in hardware and/or software components in response to sudden changes in the market or in regulatory requirements.

An integrated approach for reconfiguration has been proposed considering the industrial application. It includes weighted Jaccard function, ALCA, AHP, RIM. The methodology for calculation of reconfiguration effort, under-utilization cost, and floor space cost has been presented for industrial case.

The purpose of this paper is to examine the determinants of the reconfiguration capability from a multilevel organizational perspective including interfirm collaboration, intrafirm collaboration, individual‐, group‐ and organization‐level learning.

Using a questionnaire survey, the paper is based on data collected from 83 British software firms. Reliability and item total correlation analyses have been undertaken to ensure the internal consistency of the applied measures. A principal component analysis and multiple regression analysis have been applied to examine determinants of the reconfiguration capability.

The findings indicate that interfirm collaboration positively relates to the implementation of effective reconfiguration. In addition, the findings have revealed that group‐level learning is a successful technique for improving a firm's ability to recombine knowledge streams. Finally, the paper emphasizes the role of organization‐level learning in creating the strategic and structural context from which reconfiguration capability operates.

The paper provides some empirical evidences, which have identified the factors that affect the implementation of the reconfiguration capability.

The purpose of this paper is to discuss an example of modelling with experiments of robot prototype with dependent joint concept, including a full description of related functionalities. Reduction in active degrees of freedom in a machine can lead to improved accuracy, improved reliability and lower cost. The reconfiguration of machines and systems is a key technology for future responsive manufacturing systems. The concept of dependent joints helps to implement much specified sub-workspaces depending on functional needs in the machine.

This is inherently made possible using smart mechanical concepts having embedded sensors and reconfigurable control systems. This paper introduces structural reconfiguration systems and discusses a sample approach to functional reconfiguration.

A successful manipulator design with extended features when considering reduction in active degrees of freedom in a machine would lead to specific sub-workspace with improved accuracy, improved reliability and lower cost.

Reduction in active degrees of freedom in a machine can lead not only towards a dedicated functional workspace but also towards improved accuracy, improved reliability and lower cost.

This paper is of value to engineers and researchers developing robotic manipulators for use in various aspects of industry.

The purpose of this paper is to propose a “Reconfiguration Methodology” in manufacturing systems that they can become more economically sustainable and can operate efficiency and effectively. This methodology will allow customized flexibility and capacity not only in producing a variety of products (parts) and with changing market demands, but also in changing and reengineering the system itself.

Reconfigurable manufacturing system (RMS) is a philosophy or strategy which was introduced during the last decade to achieve agility in manufacturing systems. Until now, the RMS philosophy was based changing activities such routing, planning, programming of machines, controlling, scheduling, and physical layout or materials handling system. But the RMS concept can be based on the needed reconfiguration level (NRL), operational status of production systems, and new circumstances (NC). The NRL measure is based on the agility level of the manufacturing systems which is based on technology, people, management, and manufacturing strategies. The components of the manufacturing system design (MSD) consist of production system design, plant layout system, and material handling system. Operational status of production systems includes machine capability (flexibility) and capacity (reliability), production volume or demand, and material handling equipment in addition to the plant layout. The NC are also consisting of new product, developing the existing ones, and changing in demand.

Reconfiguration manufacturing systems from one period to another period is highly desired and is considered as a novel manufacturing philosophy and/or strategy toward creating new sustainable manufacturing systems. A new reconfiguration methodology for the manufacturing systems will be analyzed and proposed. Two Case studies will be introduced.

The suggestion of a new methodology of reconfiguration including the NRL (configurability index) and the operational status of manufacturing systems with respect to any circumstance is highly considered. The reconfiguration methodology also provides a framework for sustainability in the manufacturing area which mainly focussed on manufacturing systems design.

The purpose of the paper is to examine the coevolutionary dynamics between multistage overseas mergers and acquisitions (M&A) integration and knowledge network reconfiguration and the impact of this coevolution on industrial technology innovation.

This paper builds a coevolution analysis framework in stages and constructs structural equation models for empirical tests using the Chinese technology-sourcing overseas M&A events that occurred from 2001 to 2012.

Overseas M&A integration and knowledge network reconfiguration are in a coevolutionary relationship, driving industrial technology innovation. The acquirer adopts initial integration degree that matches the resource relatedness between the acquiring and acquired parties, promoting initial industrial technology innovation through initial knowledge network reconfiguration. Initial knowledge network reconfiguration will feed back to the M&A integration decision in the mid-to-late stage through increasing knowledge similarity and narrowing network position difference. The higher the improvement of mid-to-late integration degree, the more it can drive mid-to-late industrial technology innovation through mid-to-late knowledge network reconfiguration.

Future research can accurately classify overseas M&A integration stages through case tracking and explore other network attributes.

Practical guidelines are provided for managers on how to implement a multistage overseas M&A integration strategy, optimize knowledge network reconfiguration and promote industrial technology innovation. Significant practical implications are presented, especially in academia, society and quality of life.

Different from the previous research considering M&A integration as a single-stage decision, this paper emphasizes the dynamics of the M&A integration process and explores the coevolution mechanism of multistage overseas M&A integration and knowledge network reconfiguration.