The purpose of this paper is to explore how translation activities influence knowledge transfer across cultures in Chinese multinational enterprises (MNEs). Although translation…
Abstract
Purpose
The purpose of this paper is to explore how translation activities influence knowledge transfer across cultures in Chinese multinational enterprises (MNEs). Although translation is recognized as a critical instrument for MNEs to enhance cross-national knowledge flow, scholars have not put much emphasis on the importance of translation in international business research.
Design/methodology/approach
This paper proposes a novel hierarchical framework to delineate the five major boundary-spanning functions regarding translation for knowledge transfer in China (i.e. exchanging, linking, manipulating, facilitating and intervening). Due to the paucity of relevant literature, the authors used exploratory case studies investigating two large Chinese MNEs to illustrate how individuals as boundary spanners handle the translation requirements associated with cross-cultural knowledge transmission within a MNE’s business network. The data coding approach was used to examine the assumed model.
Findings
The findings demonstrate that translators indeed play a vital role in cross-border knowledge exchanging, linking people with crucial knowledge, manipulating the flow of knowledge for protecting confidentiality, facilitating the cross-cultural interaction of various knowledge sources and intervening to prevent the occurrence of misunderstanding in MNE contexts. The authors also reveal how translators overcome the three constraints of language interpretation concerning knowledge transfer (i.e. lack of equivalence, cultural interference and ambiguity). The proposed research framework was fully supported.
Research limitations/implications
The results provide insightful implications for MNEs to treat translation as a significant “re-codification” rather than a mundane task. Knowledge transfer within MNEs involves not only knowledge regarding products, technology and operations but also involves “whole organizations” including business models, organizational visions, missions and strategies.
Originality/value
The main value of this paper is to propose a novel model regarding the role of translation in cross-cultural knowledge transfer in China. Language is a container of contexts; the translation procedure in MNEs is actually dynamic and contingent in nature and can be seen as an act of knowledge creation per se.
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This chapter builds on the authors’ research into the internationalization of China’s higher education (HE) as soft power with “Chinese characteristics” (Lo & Pan, 2020). It…
Abstract
This chapter builds on the authors’ research into the internationalization of China’s higher education (HE) as soft power with “Chinese characteristics” (Lo & Pan, 2020). It rethinks the “Chinese characteristics” in contemporary China’s internationalization of HE as soft power, by contextualizing them in the historico-cultural rootedness that legitimizes the sense of Chinese exceptionalism in the Party-state’s global re-emergence. It also sheds light on the tension and paradox therein through analyzing the conflicts generated by the Party-state’s attempts at re-globalizing the Chinese world order alongside the Westphalian system. In addition to integrating the soft-power concepts coined by Joseph Nye (1990) with the dimensional perspectives on the internationalization of HE framed by Jane Knight (1997), this study also puts in China’s perspectives that stand in contrast to, and yet in confluence with, some of the current norms and values being espoused by the West. In so doing, it demonstrates the potentiality of employing comparative lenses that cut across times, spaces and cultures in the research into internationalization of HE as soft power with national characteristics.
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Wujuan Zhai, Florence Yean Yng Ling, Jiyong Ding and Zhuofu Wang
Megaprojects have large impact on the environment and stakeholders should take collective action to ensure that these projects are developed in a socially responsible manner…
Abstract
Purpose
Megaprojects have large impact on the environment and stakeholders should take collective action to ensure that these projects are developed in a socially responsible manner. Hitherto, it is not known whether group and subjective norms and social identity could compel stakeholders to take socially responsible collective actions in megaprojects. The aim of this study is to design and test a model to boost stakeholders' intention to take socially responsible collective action in the context of mega water transfer projects in China.
Design/methodology/approach
A quasi-experimental causal research design was adopted to establish cause–effect relationships among the dependent variable (we-intention) and independent variables (subjective norms, group norms, social identity and desire). This study adopts the belief–desire–intention model and social influence theory to empirically investigate how to boost the stakeholders' intention to participate in socially responsible collective action. An online questionnaire survey was conducted and data was collected from 365 respondents who were involved in mega water transfer projects in China. The partial least squares structural equation modeling technique was employed to analyze the data.
Findings
The results from partial least squares analyses indicate that the presence of subjective norms, group norms and social identity (collectively known as social influence process) could increase stakeholders' intention to take socially responsible collective action. In addition, the desire to be socially responsible also boosts stakeholders' intention to take collective action. Desire partially mediates the relationship between social influence process and intention to take socially responsible collective action.
Originality/value
This study adds to existing knowledge by discovering social influence process as an antecedent to taking socially responsible collective action in megaprojects. Strong group norms and subjective norms could propel stakeholders to be more socially responsible. The study also adds to knowledge by discovering that stakeholders' desire to fulfill social responsibility also leads them to take concrete actions. Implications and recommendations are provided on how to manipulate different types of social influence processes to facilitate stakeholders to adopt socially responsible collective action in the process of managing megaprojects.
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Wanping Yang, Muge Mou, Lan Mu and Xuanwen Zeng
Reducing carbon emissions in agriculture is vital for fostering sustainable agricultural growth and promoting ecological well-being in rural areas. The adoption of Low-Carbon…
Abstract
Purpose
Reducing carbon emissions in agriculture is vital for fostering sustainable agricultural growth and promoting ecological well-being in rural areas. The adoption of Low-Carbon Agriculture (LCA) by farmers holds great potential to accomplish substantial reductions in carbon emissions. The purpose of this study is to explore the farmers' preference and willingness to engage in LCA.
Design/methodology/approach
This study employs the Choice Experiment (CE) method to examine farmers' preferences and willingness to adopt LCA, using field survey data of 544 rural farmers in the Weihe River Basin between June and July 2023. We further investigate differences in willingness to pay (WTP) and personal characteristics among different farmer categories.
Findings
The empirical results reveal that farmers prioritize government-led initiatives providing pertinent technical training as a key aspect of the LCA program. Farmers' decisions to participate in LCA are influenced by factors including age, gender, education and the proportion of farm income in household income, with their evaluations further shaped by subjective attitudes and habits. Notably, we discovered that nearly half of the farmers exhibit indifference towards LCA attributes.
Originality/value
To the best of the authors' knowledge, this study is the first to investigate farmers' attitudes toward LCA from their own perspectives and to analyze the factors influencing them from both subjective and objective standpoints. This study presents a fresh perspective for advocating LCA, bolstering rural ecology and nurturing sustainable development in developing nations.
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Min Zhao, Wei He, Xiuyu He, Liang Zhang and Hongxue Zhao
Bionic flapping-wing aerial vehicles (FWAVs) mimic natural flyers to generate the lift and thrust, such as birds, bats and insects. As an important component of the FWAVs, the…
Abstract
Purpose
Bionic flapping-wing aerial vehicles (FWAVs) mimic natural flyers to generate the lift and thrust, such as birds, bats and insects. As an important component of the FWAVs, the flapping wings are crucial for the flight performance. The aim of this paper is to study the effects of different wings on aerodynamic performance.
Design/methodology/approach
Inspired by the wings structure of birds, the authors design four cambered wings to analyze the effect of airfoils on the FWAVs aerodynamic performance. The authors design the motor-driven mechanism of flapping wings, and realize the control of flapping frequency. Combined with the wind tunnel equipment, the authors build the FWAVs force test platform to test the static and dynamic aerodynamic performance of different flapping wings under the state variables of flapping frequency, wind speed and inclined angle.
Findings
The results show that the aerodynamic performance of flapping wing with a camber of 20 mm is the best. Compared with flat wing, the average lift can be improved by 59.5%.
Originality/value
Different from the traditional flat wing design of FWAVs, different cambered flapping wings are given in this paper. The influence of airfoils on aerodynamic performance of FWAVs is analyzed and the optimal flapping wing is obtained.
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Bin Lei, Zhuoxing Hou, Yifei Suo, Wei Liu, Linlin Luo and Dongbo Lei
The volume of passenger traffic at metro transfer stations serves as a pivotal metric for the orchestration of crowd flow management. Given the intricacies of crowd dynamics…
Abstract
Purpose
The volume of passenger traffic at metro transfer stations serves as a pivotal metric for the orchestration of crowd flow management. Given the intricacies of crowd dynamics within these stations and the recurrent instances of substantial passenger influxes, a methodology predicated on stochastic processes and the principle of user equilibrium is introduced to facilitate real-time traffic flow estimation within transfer station streamlines.
Design/methodology/approach
The synthesis of stochastic process theory with streamline analysis engenders a probabilistic model of intra-station pedestrian traffic dynamics. Leveraging real-time passenger flow data procured from monitoring systems within the transfer station, a gradient descent optimization technique is employed to minimize the cost function, thereby deducing the dynamic distribution of categorized passenger flows. Subsequently, adhering to the tenets of user equilibrium, the Frank–Wolfe algorithm is implemented to allocate the intra-station categorized passenger flows across various streamlines, ascertaining the traffic volume for each.
Findings
Utilizing the Xiaozhai Station of the Xi’an Metro as a case study, the Anylogic simulation software is engaged to emulate the intra-station crowd dynamics, thereby substantiating the efficacy of the proposed passenger flow estimation model. The derived solutions are instrumental in formulating a crowd control strategy for Xiaozhai Station during the peak interval from 17:30 to 18:00 on a designated day, yielding crowd management interventions that offer insights for the orchestration of passenger flow and operational governance within metro stations.
Originality/value
The construction of an estimation methodology for the real-time streamline traffic flow augments the model’s dataset, supplanting estimated values derived from surveys or historical datasets with real-time computed traffic data, thereby enhancing the precision and immediacy of crowd flow management within metro stations.
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Jieyu Li, Libang Ma, Tianmin Tao, Zhihang Zhu and Sixia Li
By analyzing the mechanisms by which rural infrastructure resilience (RIR) impacted population loss in Longxi County, this study proposes measures to improve RIR, which provides a…
Abstract
Purpose
By analyzing the mechanisms by which rural infrastructure resilience (RIR) impacted population loss in Longxi County, this study proposes measures to improve RIR, which provides a practical reference for realizing China's rural revitalization strategy, besides providing ideas for alleviating population loss in similar regions around the world.
Design/methodology/approach
This study considered 213 administrative villages in Longxi County in the Longzhong loess hilly region as the evaluation unit. Based on the construction of a multidimensional RIR evaluation system, the spatial spillover effect of RIR on population loss was determined using the spatial Durbin model (SDM).
Findings
The average resilience of each subsystem of rural infrastructure in Longxi County was low, and there were large differences in the spatial distribution. The mean RIR index value was 0.2258, with obvious spatial directivity and agglomeration characteristics. The population loss index of Longxi County had a value of 0.1759, with 26.29 of villages having a high loss level. The population loss was relatively serious and was correlated with the spatial distribution of RIR. The villages with larger RIR index values had lower population loss. The RIR had a significant spatial spillover effect on population loss. Productive infrastructure resilience and living infrastructure resilience (LIR) had negative spillover effects on population loss, and social service infrastructure resilience (SSIR) had a positive spillover effect on population loss.
Originality/value
By analyzing the mechanisms by which RIR impacted on population loss in Longxi County, this study proposes measures to improve RIR, which provides a practical reference for realizing China's rural revitalization strategy, besides providing ideas for alleviating population loss in similar regions around the world.
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Xiaoyan Jiang, Sai Wang, Yong Liu, Bo Xia, Martin Skitmore, Madhav Nepal and Amir Naser Ghanbaripour
With the increasing complexity of public–private partnership (PPP) projects, the amount of data generated during the construction process is massive. This paper aims to develop a…
Abstract
Purpose
With the increasing complexity of public–private partnership (PPP) projects, the amount of data generated during the construction process is massive. This paper aims to develop a new information management method to cope with the risk problems involved in dealing with such data, based on domain ontologies of the construction industry, to help manage PPP risks, share and reuse risk knowledge.
Design/methodology/approach
Risk knowledge concepts are acquired and summarized through PPP failure cases and an extensive literature review to establish a domain framework for risk knowledge using ontology technology to help manage PPP risks.
Findings
The results indicate that the risk ontology is capable of capturing key concepts and relationships involved in managing PPP risks and can be used to facilitate knowledge reuse and storage beneficial to risk management.
Research limitations/implications
The classes in the risk knowledge ontology model constructed in this research do not yet cover all the information in PPP project risks and need to be further extended. Moreover, only the framework and basic methods needed are developed, while the construction of a working ontology model and the relationship between implicit and explicit knowledge is a complicated process that requires repeated modifications and evaluations before it can be implemented.
Practical implications
The ontology provides a basis for turning PPP risk information into risk knowledge to allow the effective sharing and communication of project risks between different project stakeholders. It can also have the potential to help reduce the dependence on subjectivity by mining, using and storing tacit knowledge in the risk management process.
Originality/value
The apparent suitability of the nine classes of PPP risk knowledge (project model, risk type, risk occurrence stage, risk source, risk consequence, risk likelihood, risk carrier, risk management measures and risk case) is identified, and the proposed construction method and steps for a complete domain ontology for PPP risk management are unique. A combination of criteria- and task-based evaluations is also developed for assessing the PPP risk ontology for the first time.
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Chunhui Ma, Jie Yang, Lin Cheng and Li Ran
To improve the efficiency, accuracy and adaptivity of the parameter inversion analysis method of a rockfill dam, this study aims to establish an adaptive model based on a harmony…
Abstract
Purpose
To improve the efficiency, accuracy and adaptivity of the parameter inversion analysis method of a rockfill dam, this study aims to establish an adaptive model based on a harmony search algorithm (HS) and a mixed multi-output relevance vector machine (MMRVM).
Design/methodology/approach
By introducing the mixed kernel function, the MMRVM can accurately simulate the nonlinear relationship between the material parameters and dam settlement. Therefore, the finite element method with time consumption can be replaced by the MMRVM. Because of its excellent global search capability, the HS is used to optimize the kernel parameters of the MMRVM and the material parameters of a rockfill dam.
Findings
Because the parameters of the HS and the variation range of the MMRVM parameters are relatively fixed, the HS-MMRVM can imbue the inversion analysis with adaptivity; the number of observation points required and the robustness of the HS-MMRVM are analyzed. An application example involving a concrete-faced rockfill dam shows that the HS-MMRVM exhibits high accuracy and high speed in the parameter inversion analysis of static and creep constitutive models.
Practical implications
The applicability of the HS-MMRVM in hydraulic engineering is proved in this paper, which should further validate in inversion problems of other fields.
Originality/value
An adaptive inversion analysis model is established to avoid the parameters of traditional methods that need to be set by humans, which strongly affect the inversion analysis results. By introducing the mixed kernel function, the MMRVM can accurately simulate the nonlinear relationship between the material parameters and dam settlement. To reduce the data dimensions and verify the model’s robustness, the number of observation points required for inversion analysis and the acceptable degree of noise are determined. The confidence interval is built to monitor dam settlement and provide the foundation for dam monitoring and reservoir operation management.
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The purpose of this paper is to understand the critical factors associated with growing fertilizer usage culminating in contamination of soil/water in agriculturally intensive…
Abstract
Purpose
The purpose of this paper is to understand the critical factors associated with growing fertilizer usage culminating in contamination of soil/water in agriculturally intensive regions of Uttar Pradesh, India. The agriculture sector is seen as one of the major contributors in ensuring food security, however adoption of sustainable agriculture to protect water resources from contamination due to fertilizers and pesticides is becoming pressing to achieve long term environmental security.
Design/methodology/approach
A two staged study aimed at monitoring the soil quality status followed by stakeholder survey has been attempted. Attitude-behavior framework based on the theory of reasoned action has been tried to explain the fertilizer use behavior in the study. The results are analyzed through Analysis of variance.
Findings
Soil monitoring data showed nitrate and total nitrogen loadings beyond the permissible limit in the identified regions. A questionnaire aimed at determining farmer’s attitude toward fertilizer usage showed a significant influence of factors like net farm income, overall farm yield, extension services, farmer characteristics on one hand and risks associated with changing farming practices, costs of substitutes available, market-based instruments like subsidies and loans on the other. Divergent responses were observed with respect to farmer’s perceived risks from adopting to organic substitutes, linkages of fertilizer application with environmental degradation and the level of adoption of sustainable agricultural practices.
Research limitations/implications
The study can be scaled up to study the inter-regional differences by benchmarking regional responses. It would be interesting to extend the work to find solutions from the farmers as alternative fertility management strategies. The items used in questionnaire are self-made; hence there is still a possibility of enhancing the robustness of scale by applying advanced statistical techniques.
Practical implications
Results of the study indicate excessive nitrogen loadings in farm soils which is an indicator of potential future nitrate contaminated zones or vulnerable zones emerging in agricultural intensive regions. Findings reinforce the role of education, knowledge transfer and awareness for long-term agricultural sustainability. The paper highlights the urgency for reorientation of the support system by the government and policymakers.
Originality/value
The paper attempts to understand the linkage between the agricultural productivity and the environmental implications followed by the reasons culminating in the agri-environmental imbalance. On-site monitoring study followed by assessment of reasons culminating in this scenario has not been attempted earlier and this paper contributes to understanding at dual level. This paper emphasizes on the insights of stakeholder which is instrumental in ensuring agricultural sustainability or otherwise. It takes the position that the farmer’s farm management behavior is strongly influenced by factors like food security and income, keeping environmental quality at second place. It also identifies the barriers for organic farming and other alternative systems as well as explores the economic, social, and philosophical aspects of sustainable agriculture.