Shiguang Qiu, Yunfei Yang, Xiumin Fan and Qichang He
– The paper aims to propose a systematic approach for human factors (HFs) automatic evaluation for entire maintenance processes in virtual environment.
Abstract
Purpose
The paper aims to propose a systematic approach for human factors (HFs) automatic evaluation for entire maintenance processes in virtual environment.
Design/methodology/approach
First, a maintenance process information model is constructed to map real maintenance processes into computer environment. Next, based on this information model, the automatic evaluation methods for visibility, operation comfort and reachability are presented. All evaluation results are weighted and added up to establish a comprehensive HFs evaluation model. Then, the methods mentioned above are realized as an HFs evaluation module, which is integrated into virtual maintenance simulation platform, software developed by our lab.
Findings
An application in HFs evaluation of repairing hydraulic motor on container spreader is implemented, and an on-site survey is carried out. The comparison between the result from the survey and the result we get using the presented methods shows that our solution can support HFs fast assessment accurately and effectively.
Practical implications
Through evaluating maintenance operation processes, engineers can better analyze and validate the maintainability design of complex equipment, and some potential ergonomic issues can be found and dealt earlier.
Originality/value
The paper contributes to present a systematic approach to achieve HFs fast and accurate evaluation for entire maintenance processes, rather than for a few maintenance postures.
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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.
Abstract
Purpose
This paper aims to reveal how different types of events and top management teams' (TMTs’) cognitive frames affect the generation of breakthrough innovations.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
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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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
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Tianyu Ren, Yunfei Dong, Dan Wu and Ken Chen
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Practical implications
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.
Originality/value
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.
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Yunfei Liu, Jun Lv and Xiaowei Gao
The purpose of this paper is to introduce a new method called simultaneous elimination and back-substitution method (SEBSM) to solve a system of linear equations as a new finite…
Abstract
Purpose
The purpose of this paper is to introduce a new method called simultaneous elimination and back-substitution method (SEBSM) to solve a system of linear equations as a new finite element method (FEM) solver.
Design/methodology/approach
In this paper, a new technique assembling the global stiffness matrix will be proposed and meanwhile the direct method SEBSM will be applied to solve the equations formed in FEM.
Findings
The SEBSM solver for FEM with the present assembling technique has distinct advantages in both computational time and memory space occupation over the conventional methods, such as the Gauss elimination and LU decomposition methods.
Originality/value
The developed solver requires less memory space no matter the coefficient matrix is a typical sparse matrix or not, and it is applicable to both symmetric and unsymmetrical linear systems of equations. The processes of assembling matrix and dealing with constraints are straightforward, so it is convenient for coding. Compared to the previous solvers, the proposed solver has favorable universality and good performances.
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Farman Afzal, Shao Yunfei, Muhammad Sajid and Fahim Afzal
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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.
Practical implications
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.
Originality/value
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.
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Farman Afzal, Shao Yunfei, Mubasher Nazir and Saad Mahmood Bhatti
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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.
Practical implications
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.
Originality/value
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.
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Farman Afzal, Shao Yunfei, Danish Junaid and Muhammad Shehzad Hanif
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Practical implications
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.
Originality/value
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.
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Carl Ajjoub, Thomas Walker and Yunfei Zhao
This paper explores the effects of US President Donald Trump's Twitter messages (tweets) on the stock prices of media and non-media companies.
Abstract
Purpose
This paper explores the effects of US President Donald Trump's Twitter messages (tweets) on the stock prices of media and non-media companies.
Design/methodology/approach
The authors’ empirical analysis considers all Twitter messages posted by Donald Trump from May 26, 2016 (the date he passed the threshold of 1,237 delegates required to guarantee his presidential nomination) to August 30, 2018. The authors accessed President Trump's tweets through http://www.trumptwitterarchive.com, which provides links to all Twitter messages the President has ever posted. Of the 6,983 presidential tweets during our sample period, the authors select 513 messages that mention companies that are publicly traded in the United States for this study. The selected messages are then classified as having a positive, neutral or negative sentiment. The authors employ a series of univariate and multivariate tests as well as Heckman two-step regressions and partial least squares regressions to examine the effect of the President's tweets on the stock prices of the firms he tweets about.
Findings
For media firms, the authors find that positive tweets have a pronounced positive stock price impact, whereas negative and neutral tweets have little or no effect. For non-media firms, the authors observe the opposite: negative tweets tend to be associated with significant stock price declines, whereas neutral and positive tweets incur weakly positive stock price reactions. To a large extent, these stock price declines reverse on the following day. The authors further find that the President's reiteration of information that is already known by the market incurs an additional stock price reaction. The President's attitude towards the news appears to play a major role in this context.
Originality/value
The authors contribute to the literature by offering various new insights regarding the effect social media has on the stock markets. In addition, this paper expands the emerging strand of literature that explores how President Trump affects the stock prices of firms he tweets about. This paper differs from prior studies in this area by considering a broader range of tweets, by controlling for potential selection biases, by differentiating between Trump's tweets about media and non-media firms and by exploring the impact of “old” vs “new” news based on whether the President repeats information that is already known to the market. If social media posts by single influential people are found to affect markets, they may create trading opportunities for investors and financial managers and risk arbitrage opportunities for arbitrageurs. In the political science field, the findings of this research provide valuable insights into how politicians can employ social media platforms to affect the public, and the differential influence of nominees and politicians in office. Finally, our study gives corporations that wish to back a certain campaign or a candidate in an election a better idea of the possible risks and benefits of their actions, considering that candidates or politicians could post negative messages on social media platforms targeting companies that backed their opponents.
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Fangyong Niu, Dongjiang Wu, Yunfei Huang, Shuai Yan, Guangyi Ma, Chaojiang Li and Jun Ding
Direct additive manufacturing of ceramics (DAMC) is a highly promising ceramics preparation technology because of its simple process and rapid response capability, but the…
Abstract
Purpose
Direct additive manufacturing of ceramics (DAMC) is a highly promising ceramics preparation technology because of its simple process and rapid response capability, but the cracking issue prevents its industrial application. The purpose of this paper is to propose aluminum titanate (Al2TiO5) with low coefficient of thermal expansion (CTE) to suppress cracks during the DAMC.
Design/methodology/approach
Al2O3/Al2TiO5 (A/AT) composite ceramic samples with different compositions were in-situ synthesized from Al2O3/TiO2 (A/T) powder in a directed laser deposition (DLD) process. The relationship between the content of TiO2 and cracking characteristics of fabricated sample was discussed. Phase composition, microstructure and properties of the fabricated samples were also investigated.
Findings
The results of this paper show that the doping of TiO2 can obtain Al2TiO5 synthesized in situ by reaction with Al2O3 and effectively suppress cracks during DAMC. When the content of TiO2 reaches 30 wt.per cent, cracks hardly occur even under conditions of slow deposition. Crack-free structures such as vane, cone and pyramid were successfully prepared, with a maximum cross-sectional dimension of 30 mm and maximum length of 150 mm. A continuous matrix phase formed of the low CTE of Al2TiO5 is the major cause of crack suppression. The dispersed distribution of a-Al2O3 columnar dendrites has the effect of increasing the strength of the matrix. Under current process conditions, the prepared sample with 10 wt.per cent TiO2 has micro-hardness of 21.05 GPa and flexural strength of 170 MPa.
Originality/value
This paper provides a new method and inspiration for direct additive manufacturing of large-sized crack-free ceramics, which has the potential to promote practical application of the technology.