Search results

Network embeddedness has been widely considered in enterprise innovation as an effective means of overcoming resource dilemmas. However, while focussing on acquiring external innovation resources, the existing research often ignores the vital role of internal routine updates. Therefore, this study explores the mechanism by which network embeddedness affects innovation performance of enterprises from the perspective of organisational routine updating.

This paper proposes a theoretical model based on social network theory and organisational routines–immune response theory. A total of 328 pieces of research data on high-tech enterprises in China were collected, and the hypotheses were verified using hierarchical regression analysis.

The results show that the two forms of network embeddedness – structural embeddedness and relational embeddedness, have a positive effect on enterprise innovation performance and a significant positive effect on organisational routine revision and organisational routine creation. Both organisational routine revision and organisational routine creation positively affect enterprise innovation performance and partially mediate the relationship between network embeddedness and enterprise innovation performance.

This conclusion provides a new perspective on the impact of network embeddedness on enterprise innovation performance and expands the related research on organisational routine updating. This study provides a theoretical reference for high-tech enterprises to improve their competitiveness and innovation performance through network embeddedness and organisational routine updating.

This paper seeks to present a new solution algorithm for updating of finite element models in structural dynamics. A random search method is applied to improving the correlation between the numerical simulation and the measured experimental data.

Dynamic finite element model updating may be considered as an optimization process. It is solved using modified accelerated random search (MARS) algorithm. The effectiveness of the approach is first tested on benchmark problems. Next, several objective function formulations for dynamic model updating in modal and frequency domains are investigated for numerically simulated vibrating beam. Finally, the algorithm is applied to a real beam‐like structure using measured modal data.

The MARS algorithm is able to provide very good results in a reduced time even for hard optimization problems. It behaves very well also for the FE dynamic model updating, highly coupled problems. The efficient updating criterion has been proposed and the approach has been validated experimentally.

The method is supposed to be time consuming for large size or complicated objective function problems but the choice of optimization parameters can accelerate the convergence.

The MARS algorithm can be applied to model updating in civil and mechanical engineering.

This paper is the first to apply the MARS algorithm to the problem of FE model updating in dynamics and enables one to obtain very good results. Efficient criteria for model updating have been proposed.

This paper aims to measure the sensitivity of the structure’s deformation numerical model (NM) related to the various types of the design parameters, which is a suitable method for parameter selection to increase the time of model-updating.

In this research, a variance-based sensitivity analysis (VBSA) approach is proposed to measure the sensitivity of NM of structures. In this way, the contribution of measurements of the structure (such as design parameter values and geometry) on the output of NM is studied using first-order and total-order sensitivity indices developed by Sobol’. In this way the generated data set of parameters by considering different distributions such as Gaussian or uniform distribution and different order as input along with, the resulted deformation variables of NM as output has been submitted to the Sobol’ indices estimation procedure. To the verification of VBSA results, a gradient-based sensitivity analysis (SA), which is developed as a global SA method has been developed to measure the global sensitivity of NM then implemented over the NM’s results of a tunnel.

Regarding the estimated indices, it has been concluded that the derived deformation functions from the tunnel’s NM usually are non-additive. Also, some parameters have been determined as most effective on the deformation functions, which can be selected for model-updating to avoid a time-consuming process, so those may better to be considered in the group of updating parameters. In this procedure for SA of the model, also some interactions between the selected parameters with other parameters, which are beneficial to be considered in the model-updating procedure, have been detected. In this study, some parameters approximately (27 per cent of the total) with no effect over the all objective functions have been determined to be excluded from the parameter candidates for model-updating. Also, the resulted indices of implemented VBSA were approved during validation by the gradient-based indices.

The introduced method has been implemented for a circular lined tunnel’s NM, which has been created by Fast Lagrangian Analysis of Continua software.

This paper plans to apply a statistical method, which is global on the results of the NM of a soil structure by a complex system for parameter selection to avoid the time-consuming model-updating process.

The present paper aims to describe the model updating of a small aircraft dynamic finite element model (FEM) to improve its agreement with ground vibration test (GVT) data.

An automatic updating method using an optimization procedure is carried out. Instead of using dedicated updating tools, the procedure is implemented using standard MSC/NASTRAN because of wide availability of the software in small aircraft industries. The objective function is defined to minimize the differences in the natural frequency and the differences in the mode shape between the analytical model and the GVT data. Provision has been made to include the quantification of confidence in both the GVT data and in the initial model. Parameter grouping is carried out to reduce the number of design parameters during the optimization process.

The optimization module of standard finite element (FE) software can be effectively used to reduce the differences between the GVT and the FEM in terms of frequency and mode shape satisfactorily. The strategy to define the objective function based on minimizing the mode shape error can reduce the improvement in the frequency error. The required user interference can be kept low.

The most important contribution of the present paper concerns the combination of strategies to define the objective function and selection of the parameters.

Most current condition‐based maintenance (CBM) systems using proportional hazards model (PHM) assume that enough historical data are available. However, in many practical cases, it is usually costly to collect much historical data prior to real practice (model implementation). This paper aims to focus on the necessity and benefits of updating a PHM with new samples generated in the process of model implementation.

First, an updating scheme is presented and embedded into the entire cycle of PHM establishment, its application/implementation, and its updating. Next, a simulation evaluation is conducted based on a typical degradation model.

By updating a PHM using newly generated samples, the precision and reliability of residual life (RL) prediction can be improved, especially close to system failure.

The current version of PHM is typically for non‐repairable systems or those systems only receiving renewal maintenance. Further research should focus on the inclusion of the effect of imperfect maintenance.

The updating scheme enables maintenance practitioners to more precisely and reliably predict the RL of an in‐operation system, and enhances further CBM decision making.

This paper highlights the necessity and benefits of updating a PHM using emerging new training resources, which has not received enough attention in existing research/practice of a PHM.

In a wide spectrum of applications, it is desirable to manipulate semistructured information that may present variations according to different circumstances. Multidimensional XML (MXML) is an extension of XML suitable for representing data that assume different facets, having different value and/or structure under different contexts. The purpose of this paper is to develop techniques for updating MXML documents.

Updating XML has been studied in the past, however, updating MXML must take into account the additional features, which stem from incorporating context into MXML. This paper investigates the problem of updating MXML in two levels: at the graph level, i.e. in an implementation independent way; and at the relational storage level.

The paper introduces six basic update operations, which are capable of any possible change. Those operations are specified in an implementation independent way, and their effect explained through examples. Algorithms are given that implement those operations using SQL on a specific storage method that employs relational tables for keeping MXML. An overview is given of multidimensional XPath (MXPath), an extension of XPath that incorporates context, and show how to translate MXPath queries to “equivalent” SQL queries.

Though the proposed operations solve the problem of updating MXML documents, several problems, such as formally define MXPath and its translation to SQL, remain to be investigated in the future in order to implement a system that stores, queries and updates MXML documents through a relational database infrastructure.

MXML is suitable for representing, in a compact way, data that assume different facets, having different value or structure, under different contexts. In order for MXML to be applicable in practice, it is vital to develop techniques and tools for storing, updating and querying MXML documents. The techniques proposed in this paper form a significant step in this direction.

This paper presents a novel approach for updating MXML documents by proposing update operations on both, the graph level and the (relational) storage level.

Roadmapping has been used as an approach to support market, product and technology-integrated planning, resulting in a document commonly known as a roadmap. Despite the gains made in relation to the technique, recent studies indicate that most users leave or have difficulties in sustaining the process (i.e. maintaining the updated roadmaps). This paper aims to present a framework for continuous roadmap updating that incorporates principles from agile management fields.

The framework was developed through action research in a manufacturing firm in the construction industry.

The results demonstrate a positive impact on the degree of continuous information monitoring, roadmap credibility and use of the roadmap during innovation strategy decisions.

The key contribution of this framework is the demonstration of a new strategy for carrying out the maps in which information is internalized by the organization itself, using agile teams, without commissioned specialists and as part of the work standards.

The purpose of this study is developing the minimum parameter learning law for the weight updating, which reduces the updating of neural network (NN) weight only at triggering instants and makes a trade-off between the estimation accuracy and triggering frequency such that the computing complexity can be decreased. Besides that, a novel “soft” method is first constructed for the control updating at the triggered instants, to reduce the chattering effect of discontinued renewal of control. Addressing to the proposed control and updating method, a novel dead-zone condition with variable boundary about the triggered control signal is derived to ensure the positivity of adjacent execution intervals.

In this paper, to achieve the motion tracking of manipulator with uncertainty of system dynamics and the communication constraints in the control-execution channel, an adaptive event-triggered controller with NN identification is constructed to improve the transmission efficiency of control on the premise of the guaranteed performance. In the proposed method, the NN with intermittent updating is proposed to perform the uncertain approximation with the saved computation, and the triggered mechanism is constructed to regulate the transportation of the signal in the channel of controller-to-actuator.

According to the impulsive Lyapunov function, it can be proved that all the signals are semi-global uniformly ultimately bounded, and the positivity of adjacent execution intervals is also guaranteed by the proposed method. In addition, the chattering effect of control updating at the jumping instants can be relieved by the proposed “soft” mechanism, such that the control accuracy and stability can be guaranteed. Experiments on the JACO2 real manipulator are carried out to verify the effectiveness of the proposed scheme.

To the best of the author’s knowledge, this study is firstly to propose a “soft” method to reduce the chattering effect caused by discontinuous updating. Addressing to the updating method designed above, a novel dead-zone condition with variable threshold and boundary is first constructed to ensure the positivity of execution intervals.

This study aims to explore whether digital platform capabilities (integration and reconstruction) affect technological innovation through knowledge bases in the dimensions of breadth and depth and the moderating role of organisational routines updating.

Hierarchical regression, mediation effect test macro and bootstrap were conducted to empirically analyse two waves of longitudinal survey data from 179 Chinese technology firms.

Results confirmed that knowledge bases (breadth and depth) mediated the effect of digital platform capabilities (integration and reconstruction) on technological innovation and that updating of organisational routines moderated the relationship between knowledge bases and technological innovation.

These findings offer guidance to firms that aim to achieve technological innovation and advantages, highlighting the importance of digital platform capabilities, knowledge bases and organisational routines updating.

Advancing from existing digital strategies and firm innovation literature, the authors provide a new perspective (knowledge bases) to respond to the information technology (IT) paradox and understand the role of digital platform capabilities in improving technological innovation.

The purpose of this paper is to analyze the role of four different incentives in improving hedging effectiveness and propose an alternative regulatory mechanism for China’s futures market.

The research method that this study uses is a laboratory experiment, and this study follows the basic norms of experimental research. In addition, this paper designs and conducts a game experiment between hedgers and futures brokerage firms (FBFs) under different incentive mechanisms.

By analyzing the experimental data, it is found that compared with other incentive mechanisms, hedgers’ willingness to hedge and FBFs’ regulatory intention are both significantly higher for the dynamic linkage updating mechanism, indicating that hedgers have a stronger willingness to follow their hedging plan, and FBFs are more responsible for their regulatory behaviors. Additionally, the dynamic linkage updating mechanism has a long-term impact on effective hedging in the futures market.

The findings suggest that the dynamic linkage updating mechanism is beneficial for effectively restricting both hedgers’ over-speculation and FBFs’ regulatory slack and improving the hedging efficiency of the futures market.

To solve the problem of inefficient hedging in China’s futures market, i.e., hedgers’ over-speculation and FBFs’ passive collusion with hedgers, the regulators of China’s futures market should reform the existing incentives and adopt a dynamic linkage updating mechanism to encourage all the participants to actively improve hedging effectiveness.

This paper analyzes and verifies, for the first time, the role of the dynamic linkage updating mechanism in the investing behaviors of hedgers and the regulatory behaviors of future brokerage firms. The futures market experiment that was designed and used in this study is a pioneering and exploratory experiment that applies game theory and mechanism design theory to the field of behavioral finance.