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This paper aims to reveal how different types of events and top management teams' (TMTs’) cognitive frames affect the generation of breakthrough innovations.

Drawing on the event system theory and upper echelon theory, this study chose a Chinese manufacturing enterprise as the case firm and conducted an exploratory single-case study to unpack how breakthrough innovation generates over time.

By conducting the in-depth case analysis, the study revealed that firms do not produce breakthrough innovation in the catch-up stage and parallel-running stage but achieve it in the leading stage. It also indicated that when facing proactive events in the catch-up stage, TMTs often adopt a contracted lens, being manifested as consistency orientation, less elastic organizational identity and narrower competitive boundaries. In addition, they tend to adopt a contracted lens when facing reactive and proactive events in the parallel-running stage. In the face of reactive and proactive events in the leading stage, they are more inclined to adopt an expanded lens, being manifested as a coexistence orientation, more elastic organizational identity and wider competitive boundaries.

First, by untangling how TMT's cognitive frame functions in breakthrough innovations, this paper provides a micro-foundation for producing breakthrough innovations and deepens the understanding of upper echelon theory by considering the cognitive dimension of TMTs. Second, by teasing out several typical events experienced by the firm, this paper is the first attempt to reveal how events affect the generation of breakthrough innovation. Third, the work extends the application of the event system theory in technological innovation. It also provides insightful implications for promoting breakthrough innovations by considering the role of proactive and reactive events a firm experiences and TMT's perceptions.

This study explores how firms develop innovation ecosystems through forming alliances with suppliers and the effects on innovation, economics and consumer welfare.

This study develops two game theory models to compare supply chain structures with and without ecosystem alignment. (1) A single supplier provides components to two competing manufacturers (one innovative and one non-innovative). (2) An innovative manufacturer (focal firm) aligns with a supplier that also supplies components to a competing manufacturer.

An ecosystem construction strategy that alliances use to reconfigure coopetitive relationships and ecosystem alignment is identified. A manufacturer aligning with a supplier will strengthen the monopoly of the alignment, which is beneficial to both Allies but always harmful to the competitor. Interestingly, such an ecosystem construction strategy may be beneficial to future innovation, the industry and consumers.

The findings raise several topics that warrant further exploration. For example, scenarios with multiple suppliers were not considered. Furthermore, the implementation of regulatory measures to mitigate the harmful effects of alignment on innovation should be investigated.

This paper provides a guide for enterprises seeking alignment and to the corresponding measures required to stimulate innovation within ecosystems. What’s more, the aligned firm should not always attempt to win the race but should instead take measures to encourage the competitor to share demand information.

Firstly, most research on supply chain management has focused on its economic impacts. There is a lack of research on the influence of ecosystem alignment on the innovation incentives of firms. Furthermore, the literature still lacks evidence of how ecosystem construction strategies can increase consumer welfare. In the present study, the authors model a complex market structure that includes a competitor, which is becoming increasingly common in high-tech markets. Thirdly, this paper is one of the few that examines the impacts of market-structure changes on innovation incentives. Most importantly, this study extends the current literature by studying coopetition in the ecosystem context.

The paper aims to explore the long-term prospects of mobile broadband adoption in a developing country. The supply-side and demand-side policy measures are recommended to counter the challenges to broadband adoption.

Methodologically, this study uses document analysis to explain secondary data including growth statistics, trade literature and previous scholarly research. Based on the growth statistics of broadband and the informed market insights, the research discusses the prevailing market threats and recommends counter measures to improve the long-term prospects of broadband propagation.

The growth of mobile broadband is settling down in Pakistan due to various barriers like cost, literacy, security and unavailability of local content. Collaborative efforts are required by the government, the service providers and the people to enhance the adoption of broadband service and secure economic benefits of the broadband.

The research offers useful implications for managers and policymakers in Asian and African developing countries; the policy measures discussed here may serve as guidelines for them in the design of their own policies regarding broadband supply and demand.

The study makes an effort to examine the broadband growth in a developing country on the basis of both quantitative and qualitative aspects. The research endeavors to fill the gap on the particular scholarship of research covering potential uptake of broadband services and the effects of constraining elements to broadband adoption in a developing country.

Cost overrun is inherent to project chaos, which is one of the key drivers of project failure. The purpose of this paper is to explore the critical elements of complexity-risk interdependency for cost-chaos in the construction management domain by utilizing a multi-criteria decision model.

A total of 12 complexity and 60 risk attributes are initially identified from the literature and using expert’s judgements. For the development of a structured hierarchy of key complexity and risk drivers, a real-time Delphi process is adopted for recording and evaluating the responses from experts. Afterwards, a pair-wise comparison using analytical network processing is performed to measure complexity-risk interdependencies against cost alternatives.

The findings of the integrated priority decision index (IPDI) suggest that uncertainties related to contingency and escalation costs are the main sources of cost overrun in project drift, along with the key elements such as “the use of innovative technology,” “multiple contracts,” “low advance payment,” “change in design,” “unclear specifications” and “the lack of experience” appear to be more significant to chaos in complexity-risk interdependency network.

This study did not address the uncertainty and vulnerability exit in the judgment process, therefore, this framework can be extended using fuzzy logic to better evaluate the significance of cost-chaos drivers.

These results may assist the management of cost overrun to avoid chaos in a project. The proposed model can be applied within project risk management practices to make better-informed technical decisions in the early phases of the project life cycle where uncertainty is high.

This research addresses the importance of cost overruns as a source of project chaos in dynamic systems where projects reach the edge of chaos and progress stops. A new IPDI index contributes toward evaluating the severity of complexity and risk and their interdependencies which create cost-chaos in infrastructure transport projects.

Drawing on the upper echelons theory, this study focuses on how top management team (TMT) heterogeneity affects breakthrough innovations and examines how strategic decision-making logic (including causation and effectuation) moderates the relationship between TMT heterogeneity and breakthrough innovation.

By conducting an empirical test of 227 sample firms in China, the authors applied linear hierarchical regression analysis to test the hypotheses on the TMT heterogeneityinnovation relationship and the moderating roles of causation and effectuation.

The empirical tests show that TMT heterogeneity positively affects breakthrough innovation, and both causation and effectuation positively moderate the positive relationship between TMT heterogeneity and breakthrough innovation. In addition, effectuation has a stronger moderating effect on the positive correlation between TMT heterogeneity and breakthrough innovation than causation.

This study extends the upper echelons theory to explain how the characteristics of TMTs affect firm innovation. Specifically, the authors explore the TMT heterogeneity–breakthrough innovation relationship from the perspectives of information processing and core competence and reveal the boundary condition of strategic decision-making logic in the correlation between TMT heterogeneity and breakthrough innovation. In this vein, the authors contribute to the literature by untangling the internal mechanisms between TMT heterogeneity and breakthrough innovation and extending the discussion on effectuation theory from the entrepreneurship domain to the innovation field. Furthermore, the research findings can provide helpful implications for TMTs to manage breakthrough innovation effectively.

Risk analysis plays a vital role in controlling and managing cost overruns in complex construction projects, particularly where uncertainty is high. This study attempts to address an important issue of cost overrun that encountered by metropolitan rapid transit projects in relation to the significance of risk involved under high uncertainty.

In order to solve cost overrun problems in metropolitan transit projects and facilitate the decision-makers for effective future budgeting, a cost-risk contingency framework has been designed using fuzzy logic, analytical hierarchy process and Monte Carlo simulation.

Initially, a hierarchical breakdown structure of important complexity-driven risk factors has been conceptualized herein using relative importance index. Later, a proposed cost-risk contingency framework has investigated the expected total construction cost in order to consider the additional budgeted cost required to mitigate the risk consequences for particular project activity. The results of cost-risk analysis imply that poor design issues, an increase in material prices and delays in relocating facilities show higher dependency and increase the risk of cost overrun in metropolitan transit projects.

The findings and implication for project managers could possibly be achieved by assuming the proposed cost-risk contingency framework under high uncertainty of cost found in this research. Furthermore, this procedure may be used by experts from other engineering domains by replacing and considering the complex relationship between complexity-risk factors.

This study contributes to the body of knowledge by providing a practical contingency model to identify and evaluate the additional risk cost required to compute total construction cost for getting stability in future budgeting.

In the past decades, artificial intelligence (AI)-based hybrid methods have been increasingly applied in construction risk management practices. The purpose of this paper is to review and compile the current AI methods used for cost-risk assessment in the construction management domain in order to capture complexity and risk interdependencies under high uncertainty.

This paper makes a content analysis, based on a comprehensive literature review of articles published in high-quality journals from the years 2008 to 2018. Fuzzy hybrid methods, such as fuzzy-analytical network processing, fuzzy-artificial neural network and fuzzy-simulation, have been widely used and dominated in the literature due to their ability to measure the complexity and uncertainty of the system.

The findings of this review article suggest that due to the limitation of subjective risk data and complex computation, the applications of these AI methods are limited in order to address cost overrun issues under high uncertainty. It is suggested that a hybrid approach of fuzzy logic and extended form of Bayesian belief network (BBN) can be applied in cost-risk assessment to better capture complexity-risk interdependencies under uncertainty.

This study only focuses on the subjective risk assessment methods applied in construction management to overcome cost overrun problem. Therefore, future research can be extended to interpret the input data required to deal with uncertainties, rather than relying solely on subjective judgments in risk assessment analysis.

These results may assist in the management of cost overrun while addressing complexity and uncertainty to avoid chaos in a project. In addition, project managers, experts and practitioners should address the interrelationship between key complexity and risk factors in order to plan risk impact on project cost. The proposed hybrid method of fuzzy logic and BBN can better support the management implications in recent construction risk management practice.

This study addresses the applications of AI-based methods in complex construction projects. A proposed hybrid approach could better address the complexity-risk interdependencies which increase cost uncertainty in project.

This paper aims to present a method for improving the state estimation of a robot in the presence of noise measurement, which can improve the performance of the robot controller.

In this work, a novel nonlinear tracking differentiator (NTD) was formulated to solve the problems of phase lag, low stability and amplitude attenuation faced by traditional tracking differentiators, which can be used for the state estimation of a robot. Based on the user-defined function stu() with linear and nonlinear characteristics, the authors establish a new acceleration function of NTD and confirm its global asymptotic stability by using the Lyapunov method and the system equivalence method. Phase plane analysis shows that the origin is its stable nodal point or focus point and uncovers the basic constraint conditions for parameter regulation. In addition, the convergence property and robustness performance against noises are studied by describing function method.

Comparative simulations, robot state estimation experiments and joint trajectory tracking experiments have indicated that NTD proposed integrates tracking rapidness, accuracy and transitional stability and has high approximation and filtering effects on generalized derivatives of the signal, which contribute to an excellent performance of robot controller in stability and response speed in practice.

The main contribution of this paper lies in the design of a novel NTD, which successfully improves the state estimation of a robot joint in noisy surroundings, the tracking performance of robot controller and the stability of the system.

The purpose of this paper is to present a simple yet effective force control scheme for collaborative robots by addressing the problem of disturbance rejection in joint torque: inherent actuator flexibility and nonlinear friction.

In this paper, a joint torque controller with an extended state observer is used to decouple the joint actuators from the multi-rigid-body system of a constrained robot and compensate the motor friction. Moreover, to realize robot force control, the authors embed this controller into the impedance control framework.

Results have been given in simulations and experiments in which the proposed joint torque controller with an extended state observer can effectively estimate and compensate the total disturbance. The overall control framework is analytically proved to be stable, and further it is validated in experiments with a robot testbed.

With the proposed robot force controller, the robot is able to change its stiffness in real time and therefore take variable tasks without any accessories, such as the RCC or 6-DOF F/T sensor. In addition, programing by demonstration can be realized easily within the proposed framework, which makes the robot accessible to unprofessional users.

The main contribution of the presented work is the design of a model-free robot force controller with the ability to reject torque disturbances from robot-actuator coupling effect and motor friction, applicable for both constrained and unconstrained environments. Simulation and experiment results from a 7-DOF robot are given to show the effectiveness and robustness of the proposed controller.

This paper aims to introduce the history and major achievement of the Chinese private enterprise survey (CPES), which is one of the most enduring large-scale nationwide sample surveys in China, providing important micro firm-level data for understanding and studying the development of Chinese enterprises and entrepreneurs over the past 26 years.

The main body of this paper is based on a bibliometric analysis of all literature using CPES until 2017.

This paper discusses problems that users may encounter during data mining. By doing so, it can assist other researchers to get a better understanding of what has been done (e.g. journals, topics, scholars and institutions) and do their research in a more targeted way.

As members of the survey project team, the authors also take a prospect of the future data design and use, as well as offer some suggestions about how to use the CPES data to improve high-quality development and business environment evaluation in China.

This paper is the first to provide an overall picture of academic papers in China and abroad that have used the CPES data.