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1 – 5 of 5Xueju Li, Danguang Pan and Ying Huang
The main objectives of this paper are to develop a novel perturbation method (PM) to solve the complex-orthogonal eigenvalue problem and further propose an exact complex mode…
Abstract
Purpose
The main objectives of this paper are to develop a novel perturbation method (PM) to solve the complex-orthogonal eigenvalue problem and further propose an exact complex mode superposition method (CMSM) for the non-proportionally rate-independent damped systems.
Design/methodology/approach
A novel PM is developed to solve the eigenvalue problem. The PM reduced the N-order generalized complex eigenvalue problem into a set of n algebraic equations by the perturbation theory. The convergence and accuracy of the PM are demonstrated by several numerical examples. Further, an exact CMSM is presented. The influences of the imaginary part response of the modal coordinate and the off-diagonal elements of the damping matrix as well as the modal truncation on the solution by CMSM are discussed to illustrate the effectiveness of the developed CMSM.
Findings
The eigenvalues obtained by PM would converge to the exact ones with the increase of the modal numbers. For seismic response, the influence of the imaginary part solutions of the modal coordinate would increase with the increase of the coupling factor. The contribution of higher modes to acceleration response is greater than that to the displacement. The cumulative mode contribution coefficient of acceleration is developed to estimate the numbers of the complex modes for the acceleration seismic response by the CMSM.
Originality/value
1. An eigenvalue perturbation method for a rate-independent damped system is proposed. 2. PM is carried out by the real mode and accomplishes the reduction of the matrix. 3. CMSM is established for rate-independent damped systems. 4. CMSM considers the effect of imaginary part solutions of the modal coordinate. 5. Modal truncation index is developed to estimate the complex mode number for CMSM.
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The purpose of this study is to examine the impact of cross-ownership on corporate digital innovation and their specific mechanisms. Cross-ownership, who hold equity in two or…
Abstract
Purpose
The purpose of this study is to examine the impact of cross-ownership on corporate digital innovation and their specific mechanisms. Cross-ownership, who hold equity in two or more companies simultaneously, have two different types of governance effects in the capital market: governance synergistic effects and competitive collusion effects.
Design/methodology/approach
This paper uses a panel model, selecting A-share company data from 2011 to 2021 in China. In total, 23,853 valid data were obtained, which came from the CSMAR database and Wind database. For some missing data, they were manually supplemented by consulting the company's annual report and Sina Finance. Data processing was conducted using EXCEL and Stata16.0 software.
Findings
The results show that cross-ownership promote corporate digital innovation by leveraging governance synergies. Further grouping tests show that the synergistic effects of cross-ownership are significant in non-state-owned, high-tech, weakly competitive and higher analyst attention enterprises. Mechanism testing shows that cross-ownership can empower corporate digital innovation in three ways: reducing information asymmetry, alleviating financing constraints and improving corporate governance.
Originality/value
The conclusion of this paper provides new empirical evidence for a comprehensive understanding of the role of cross-ownership in corporate development, enriches the economic consequences research of chain institutional investors in China and broadens the research perspective of corporate digital innovation. It also provides important references for the digital transformation of enterprises and the healthy development of the capital market.
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Ali Vafaei-Zadeh, Davoud Nikbin, Shin Ling Wong and Haniruzila Hanifah
Artificial intelligence (AI) customer service has grown rapidly in recent years due to the emergence of COVID-19 and the growth of the e-commerce industry. Therefore, this study…
Abstract
Purpose
Artificial intelligence (AI) customer service has grown rapidly in recent years due to the emergence of COVID-19 and the growth of the e-commerce industry. Therefore, this study employs the integration of the stimuli–organism–response (SOR) and the task-technology fit (TTF) frameworks to understand the factors that affect individuals’ intentions towards AI customer service adoption in Malaysia.
Design/methodology/approach
The study utilised a survey-based research approach to investigate the factors that affect individuals’ intentions towards AI customer service adoption in Malaysia. The data were collected by conducting an online survey targeting individuals aged 18 or above who had prior customer service interaction experience with human service agents but had not yet adopted AI customer service. A sample of 339 respondents was used to evaluate the hypotheses, adopting partial least squares structural equation modelling as a symmetric analytic technique.
Findings
The PLS-SEM analysis revealed that social influence and anthropomorphism have a positive direct relationship with emotional trust. Furthermore, communicative competence, technology characteristics and perceived intelligence were positively correlated with TTF. Moreover, emotional trust significantly impacts AI customer service adoption. In addition, AI readiness positively moderates the association between task technology fit and AI customer service adoption.
Practical implications
The study provides insights to individuals, organisations, the government and educational institutions to improve the features of AI customer service and its development in Malaysia.
Originality/value
The originality of this study is found in its adoption of the SOR theory and TTF to understand the factors affecting AI customer service adoption. Additionally, it incorporates moderating variables during the analysis, adding depth to the findings. This approach introduces a new perspective on the factors that impact the adoption of AI customer service and offers valuable insights for practitioners seeking to formulate effective strategies to promote its adoption.
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Chen Yang, Lu Zhang, Xuehang Ling, Xin Qin and Mingyue Li
Digital product and service innovations (DPSI) has attracted widespread attention from both management scholars and practitioners. Previous studies have documented that…
Abstract
Purpose
Digital product and service innovations (DPSI) has attracted widespread attention from both management scholars and practitioners. Previous studies have documented that information technology (IT) capability and digital orientation positively influence DPSI performance. However, the question of whether and how digitalization capability can facilitate DPSI performance remains unresolved. This paper fills these gaps by investigating the mediating role of improvisation capability and the moderating role of technological turbulence.
Design/methodology/approach
This study used two-wave data from 240 matched digital transformation department leaders and senior managers from Chinese firms and examined the hypotheses deploying hierarchical regression and bootstrapping.
Findings
Our analyses reveal positive, significant links between digitalization capability and improvisation capability and between improvisation capability and DPSI performance. The findings further show that the effect of digitalization capability on DPSI performance is partially mediated by improvisation capability and that technological turbulence strengthens the indirect relationship between digitalization capability and DPSI performance through improvisation capability.
Originality/value
Integrating resource-based view, this research provides evidence that the extent to which improvisation capability mediates the relationship between digitalization capability and DPSI performance depends on technological turbulence. It provides a new direction for digitalization capability and DPSI performance.
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MohammedShakil S. Malek and Viral Bhatt
Managing mega infrastructure projects (MIPs) is more complex because of time, size, social, environmental and financial implications. This study aims to address the management…
Abstract
Purpose
Managing mega infrastructure projects (MIPs) is more complex because of time, size, social, environmental and financial implications. This study aims to address the management approaches, complexity and risk factors involved in MIPs. The study focuses on project success criteria and their individual effects on the success of MIPs.
Design/methodology/approach
To address the challenges and identify the most influencing factor for the success of MIPs, the study deployed a cross-sectional survey approach. Six hundred eighty-two usable samples were collected from the respondents to understand the impact of predetermined factors on the success of MIPs. The structural equation model and artificial neural network approach were used to derive the importance of factors affecting the success of MIPs.
Findings
The study's outcome confirms that all three influencing factors: feasibility studies, community engagements and contract selection, have a significant positive impact on the success of MIPs. Community engagement amongst all three has the most influential predictor for the success of MIPs.
Originality/value
The developed model will enable practitioners and policymakers from Indian construction companies and other emerging nations to concentrate on recognized risk reduction variables to enhance project success criteria and project management success, especially for MIPs.
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