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1 – 10 of 161Binh Tan Mai, Phuong V. Nguyen, Uyen Nu Hoang Ton and Zafar U. Ahmed
COVID-19 has made businesses increasingly dependent on technology to be competitive and efficient. Small and medium enterprises (SME) digitalisation and innovation research are…
Abstract
Purpose
COVID-19 has made businesses increasingly dependent on technology to be competitive and efficient. Small and medium enterprises (SME) digitalisation and innovation research are widespread. SME digital transformation and innovation require government policies, initiatives and assistance. How the government can help SMEs achieve these goals is unclear. So, this paper aims to investigate how government policy may assist Vietnamese SMEs to boost innovation performance and digital transformation.
Design/methodology/approach
The study will take a quantitative approach, with questionnaires distributed to 659 respondents from SMEs in Vietnam through snowball and convenience sampling procedures. The structural equational modelling method is used for data analysis.
Findings
The study indicated that government policies supported Vietnamese SMEs’ innovation and information technology (IT) capabilities. Government policy assistance also boosted IT capabilities and innovation. Furthermore, mediation effects show that digital transformation fully mediates the relationship between innovativeness and firm performance, whereas IT capabilities partially mediate this relationship.
Research limitations/implications
Further research that replicates the findings and analyses contextual heterogeneities between nations is advised because Vietnam’s pandemic setting was both similar and dissimilar.
Practical implications
The study demonstrated government-company interactions through supportive policy. It investigated whether SMEs seeking digital transformation and innovativeness might gain competitive benefits by implementing effective knowledge management and enhancing their IT capabilities.
Originality/value
A resource-based theoretical framework is extended to study how innovation, public policy and digital transformation for SMEs interact. The study confirms government policy strongly influences enterprises’ digital development. Specifically, the new mediating effects of IT capabilities and digital transformation are explored and provide new insights into the existing literature.
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Dexin Chen, Hongyuan He, Zhixin Kang and Wei Li
This study aims to review the current one-step electrodeposition of superhydrophobic coatings on metal surfaces.
Abstract
Purpose
This study aims to review the current one-step electrodeposition of superhydrophobic coatings on metal surfaces.
Design/methodology/approach
One-step electrodeposition is a versatile and simple technology to prepare superhydrophobic coatings on metal surfaces.
Findings
Preparing superhydrophobic coatings by one-step electrodeposition is an efficient method to protect metal surfaces.
Originality/value
Even though there are several technologies, one-step electrodeposition still plays a significant role in producing superhydrophobic coatings.
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Jianhua Zhang, Jiake Li, Sajjad Alam, Fredrick Ahenkora Boamah and Dandan Wen
This study examines the relationship between higher education improvement and tacit knowledge importance. In this context, the scarcity of empirical and theoretical studies on…
Abstract
Purpose
This study examines the relationship between higher education improvement and tacit knowledge importance. In this context, the scarcity of empirical and theoretical studies on acquiring tacit knowledge to enhance academic performance in higher education suggests that this research area holds significant importance for experts and policymakers. Consequently, this study aims to explore the factors that influence academic research performance at Chinese universities by acquiring tacit knowledge.
Design/methodology/approach
To achieve the study aims, the current approach utilizes the research technique based on the socialization, externalization, internalization and combination (SECI) model and knowledge management (KM) theory. To analyze the study objective, the authors collected data from post-graduate students at Chinese universities and analyzed it using structural equation modeling (SEM) to test the model and hypotheses.
Findings
The results indicated that social interaction, internalization and self-motivation have a positive impact on academic research performance through the acquisition of tacit knowledge. Furthermore, the findings suggest that academic researchers can acquire more knowledge through social interaction than self-motivation, thereby advancing research progress.
Originality/value
This study addresses the critical issues surrounding the acquisition of tacit knowledge and presents a comprehensive framework and achievements that can contribute to achieving exceptional academic performance.
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Longchang Zhang, Qi Chen, Yanguo Yin, Hui Song and Jun Tang
Gears are prone to instantaneous failure when operating under extreme conditions, affecting the machinery’s service life. With numerous types of gear meshing and complex operating…
Abstract
Purpose
Gears are prone to instantaneous failure when operating under extreme conditions, affecting the machinery’s service life. With numerous types of gear meshing and complex operating conditions, this study focuses on the gear–rack mechanism. This study aims to analyze the effects and optimization of biomimetic texture parameters on the line contact tribological behavior of gear–rack mechanisms under starvation lubrication conditions.
Design/methodology/approach
Inspired by the microstructure of shark skin surface, a diamond-shaped biomimetic texture was designed to improve the tribological performance of gear–rack mechanism under starved lubrication conditions. The line contact meshing process of gear–rack mechanisms under lubrication-deficient conditions was simulated by using a block-on-ring test. Using the response surface method, this paper analyzed the effects of bionic texture parameters (width, depth and spacing) on the tribological performance (friction coefficient and wear amount) of tested samples under line contact and starved lubrication conditions.
Findings
The experimental results show an optimal proportional relationship between the texture parameters, which made the tribological performance of the tested samples the best. The texture parameters were optimized by using the main objective function method, and the preferred combination of parameters was a width of 69 µm, depth of 24 µm and spacing of 1,162 µm.
Originality/value
The research results have practical guiding significance for designing line contact motion pairs surface texture and provide a theoretical basis for optimizing line contact motion pairs tribological performance under extreme working conditions.
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This paper aims to focus on solving the path optimization problem by modifying the probabilistic roadmap (PRM) technique as it suffers from the selection of the optimal number of…
Abstract
Purpose
This paper aims to focus on solving the path optimization problem by modifying the probabilistic roadmap (PRM) technique as it suffers from the selection of the optimal number of nodes and deploy in free space for reliable trajectory planning.
Design/methodology/approach
Traditional PRM is modified by developing a decision-making strategy for the selection of optimal nodes w.r.t. the complexity of the environment and deploying the optimal number of nodes outside the closed segment. Subsequently, the generated trajectory is made smoother by implementing the modified Bezier curve technique, which selects an optimal number of control points near the sharp turns for the reliable convergence of the trajectory that reduces the sum of the robot’s turning angles.
Findings
The proposed technique is compared with state-of-the-art techniques that show the reduction of computational load by 12.46%, the number of sharp turns by 100%, the number of collisions by 100% and increase the velocity parameter by 19.91%.
Originality/value
The proposed adaptive technique provides a better solution for autonomous navigation of unmanned ground vehicles, transportation, warehouse applications, etc.
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Meenal Arora, Jaya Gupta, Amit Mittal and Anshika Prakash
Considering the swift adoption of innovative sustainability practices in businesses to accomplish sustainable development goals (SDGs), research on corporate sustainability has…
Abstract
Purpose
Considering the swift adoption of innovative sustainability practices in businesses to accomplish sustainable development goals (SDGs), research on corporate sustainability has increased significantly over the years. This research intends to analyze the published literature, emphasizing the existing, emerging and future research directions on achieving the SDGs through corporate sustainability.
Design/methodology/approach
This research analyzed the growing trends in corporate sustainability by incorporating 2,038 Scopus articles published between 1999 and 2022 using latent Dirichlet allocation (LDA) topic modeling, bibliometrics and qualitative content analysis techniques. The bibliometric data were analyzed using performance and science mapping. Thereafter, topic modeling and content analysis uncovered the topics included under the corporate sustainability umbrella.
Findings
The findings indicate that investigation into corporate sustainability has considerably increased from 2015 to date. Additionally, the majority of studies on corporate sustainability are from the United States of America, the United Kingdom and Germany. Besides, the USA has the most collaboration in terms of co-authorship. S. Schaltegger was considered the most productive author. However, P. Bansal was ranked as the top author based on a co-citation analysis of authors. Further, bibliometric data were evaluated to analyze leading publications, journals and institutions. Besides, keyword co-occurrence analysis, topic modeling and content analysis highlighted the theoretical underpinnings and new patterns and provided directions for further research.
Originality/value
This study demonstrates various existing and emerging themes in corporate sustainability, which have various repercussions for academicians and organizations. This research also examines the lagging themes in the current domain.
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Minglong Li, Xiaoyang Sun, Yu Zhu and Hailian Qiu
An increasing number of immersive technologies have been adopted in museum tourism in response to shifting consumer habits in the digital era. In contrast, the authenticity…
Abstract
Purpose
An increasing number of immersive technologies have been adopted in museum tourism in response to shifting consumer habits in the digital era. In contrast, the authenticity experience of museum tourists relies on genuine relics, the environment and activities, which are ancient or traditional. This raises the question of whether tourists can perceive authenticity in immersive technology-based museum tourism. To address this question, this study aims to explore the impact of virtual reality (VR) attributes on tourists’ presence, tourism authenticity and subsequent behavioral intentions in virtual museums.
Design/methodology/approach
Data were collected via scenario-based surveys of participants who had taken virtual museum tours based on VR. A total of 174 effective questionnaires were collected for exploratory factor analysis via SPSS 25. Afterward, 597 questionnaires were obtained for confirmatory factor analysis and path analysis via Mplus 7.4.
Findings
A conceptual model of how VR attributes influence presence, authenticity and visit intention was developed. There is a chain intermediary between presence and visit intentions, from original authenticity to interactive authenticity and then to emotional authenticity. Technology readiness and museum familiarity moderate some relationships between VR attributes and presence.
Practical implications
The findings can guide museums in improving the use of VR. For example, managers can improve the quality of virtual systems and adopt various interactive forms to enhance tourists’ participation experiences.
Originality/value
These research findings contribute to the research area of immersive technology adoption, enhance the understanding of tourism authenticity in the new context of technology application and extend the presence-emotion-intention theory.
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Yan Gao, Qiubo Li, Wei Wu, Qiwei Wang, Yizhe Su, Junxi Zhang, Deyuan Lin and Xiaojian Xia
The purpose of this paper is to study the effect of current-carrying condition on the electrochemical process and atmospheric corrosion behavior of the commercial aluminum alloys.
Abstract
Purpose
The purpose of this paper is to study the effect of current-carrying condition on the electrochemical process and atmospheric corrosion behavior of the commercial aluminum alloys.
Design/methodology/approach
Potentiodynamic polarization tests were performed to study the electrochemical process of the aluminum alloys. Salt spray tests and weight loss tests were carried out to study the atmospheric corrosion behavior. The corrosion morphology of the alloys was observed, and the products were analyzed.
Findings
The corrosion process of four aluminum alloys was accelerated in the current-carrying condition. Moreover, the acceleration effect on A2024 and A7075 was much stronger than that on A1050 and A5052. The main factors would be the differences in microstructure and corrosion resistance between these alloys. As the carried current increased, the corrosion rate and corrosion current density of the aluminum alloys gradually increased, with the protection of the corrosion product film decreasing linearly.
Originality/value
This is a recent study on the corrosion behavior of conductors under current-carrying condition, which truly understands the corrosion status of power grid materials. Relevant results provide support for the corrosion protection and safe service of aluminum alloy in power systems.
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Xiaoyong Wei, Anwei Huang, Ruoyi Chen and Jiyue Yang
Retailers have recently leveraged store-loyal customers’ store attachment to maintain customer relationships and motivate patronage intentions. However, the COVID-19 outbreak has…
Abstract
Purpose
Retailers have recently leveraged store-loyal customers’ store attachment to maintain customer relationships and motivate patronage intentions. However, the COVID-19 outbreak has driven customer migration from offline to mobile channels. Mobile retail applications (APPs) have been used by numerous retailers to reach their customers. Nonetheless, it has yet to be determined (1) whether store attachment can facilitate (or impede) the adoption of mobile retail APPs and (2) whether store-loyal customers will continue visiting offline stores in the post-pandemic era. To address these questions, we propose a theoretical account using integrated theories on trust transfer and store attachment.
Design/methodology/approach
We conducted multi-stage, longitudinal field surveys in two cities of mainland China: Beijing and Guangzhou. From two rounds of data collection, 237 and 103 responses were obtained in March 2022. Hypotheses were tested by partial least squares – structural equation modelling (PLS–SEM).
Findings
Results showed that customer trust in an offline retailer can be transferred to the retailer’s mobile APP at the pre-adoption stage, facilitating APP adoption. Notably, store-loyal customers who exhibited a strong attachment to the physical store of a retailer were more inclined to transfer their trust to the mobile APP of the retailer. This occurrence leads to an increased adoption rate, enhanced post-adoption satisfaction and increased inclination to continue (rather than discontinue) usage.
Originality/value
This study is the first to investigate the changes in store-loyal customers' shopping behaviour in the mobile retail era and in the post-COVID-19 pandemic recovery. Our findings elucidate the role of physical store attachment in the trust-transfer mechanism. Furthermore, store attachment may not prevent customers’ channel migration behaviour. Retailers may have to re-consider how to manage channel cannibalisation issues in the post-pandemic recovery.
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Ziwen Gao, Steven F. Lehrer, Tian Xie and Xinyu Zhang
Motivated by empirical features that characterize cryptocurrency volatility data, the authors develop a forecasting strategy that can account for both model uncertainty and…
Abstract
Motivated by empirical features that characterize cryptocurrency volatility data, the authors develop a forecasting strategy that can account for both model uncertainty and heteroskedasticity of unknown form. The theoretical investigation establishes the asymptotic optimality of the proposed heteroskedastic model averaging heterogeneous autoregressive (H-MAHAR) estimator under mild conditions. The authors additionally examine the convergence rate of the estimated weights of the proposed H-MAHAR estimator. This analysis sheds new light on the asymptotic properties of the least squares model averaging estimator under alternative complicated data generating processes (DGPs). To examine the performance of the H-MAHAR estimator, the authors conduct an out-of-sample forecasting application involving 22 different cryptocurrency assets. The results emphasize the importance of accounting for both model uncertainty and heteroskedasticity in practice.
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