Houzhe Zhang, Defeng Gu, Xiaojun Duan, Kai Shao and Chunbo Wei
The purpose of this paper is to focus on the performance of three typical nonlinear least-squares estimation algorithms in atmospheric density model calibration.
Abstract
Purpose
The purpose of this paper is to focus on the performance of three typical nonlinear least-squares estimation algorithms in atmospheric density model calibration.
Design/methodology/approach
The error of Jacchia-Roberts atmospheric density model is expressed as an objective function about temperature parameters. The estimation of parameter corrections is a typical nonlinear least-squares problem. Three algorithms for nonlinear least-squares problems, Gauss–Newton (G-N), damped Gauss–Newton (damped G-N) and Levenberg–Marquardt (L-M) algorithms, are adopted to estimate temperature parameter corrections of Jacchia-Roberts for model calibration.
Findings
The results show that G-N algorithm is not convergent at some sampling points. The main reason is the nonlinear relationship between Jacchia-Roberts and its temperature parameters. Damped G-N and L-M algorithms are both convergent at all sampling points. G-N, damped G-N and L-M algorithms reduce the root mean square error of Jacchia-Roberts from 20.4% to 9.3%, 9.4% and 9.4%, respectively. The average iterations of G-N, damped G-N and L-M algorithms are 3.0, 2.8 and 2.9, respectively.
Practical implications
This study is expected to provide a guidance for the selection of nonlinear least-squares estimation methods in atmospheric density model calibration.
Originality/value
The study analyses the performance of three typical nonlinear least-squares estimation methods in the calibration of atmospheric density model. The non-convergent phenomenon of G-N algorithm is discovered and explained. Damped G-N and L-M algorithms are more suitable for the nonlinear least-squares problems in model calibration than G-N algorithm and the first two algorithms have slightly fewer iterations.
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Xiaojun Duan and Yi Lin
Model description, observations, and prior knowledge are the three main sources of information that are used for the evaluation and estimation of complex systems. Here, model…
Abstract
Purpose
Model description, observations, and prior knowledge are the three main sources of information that are used for the evaluation and estimation of complex systems. Here, model description is given based on the physical mechanism and dynamics of the system. Observational data represent a very important method of verification and can be applied to validate the model. Prior knowledge can help to provide additional information when observation data are not sufficient. On the basis of clearly carding the relationship between a system's observational quantities and the ultimate indices of the observation, the purpose of this paper is to establish the systemic yoyo model for systems evaluation.
Design/methodology/approach
Recent advances in systems science in general and the systemic yoyo model in particular are employed in this research as the fundamental logic of reasoning and thread of thinking.
Findings
After analyzing the characteristics and connections between the three main sources of information – model description, prior knowledge, and observational data – used in system evaluation and estimation, the authors derive the conservation law of information for system evaluation and estimation and analyze the transitional direction of the process of system evaluation and estimation.
Practical implications
This work lays down the theoretical basis for why certain procedures widely applied in system evaluations and estimations are correct and sound, on which reliable scientific conclusions can be drawn.
Originality/value
This work is the first of its kind that investigates the systemic foundation underlying the commonly applied procedures of system evaluations and estimations.
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Rui Gao and Xiaojun Du
How to support the rapid internationalization of multinational enterprises (MNEs) is a hot topic in academia and industry. The main purpose of this work is to study the role of…
Abstract
Purpose
How to support the rapid internationalization of multinational enterprises (MNEs) is a hot topic in academia and industry. The main purpose of this work is to study the role of relational assets (R-assets) in promoting the speed of internationalization of MNEs, and to explore the moderating effect of environmental uncertainty (institutional environment and industry environment) on the relationship between R-assets and internationalization speed of MNEs.
Design/methodology/approach
This study uses the outward foreign investment data of China’s A-share listed enterprises from 2009 to 2021, and employs the Cox proportional hazards model to empirically test the research hypothesis.
Findings
The empirical results revealed that R-assets can promote enterprise internationalization speed. In addition, the study also finds that the institutional uncertainty of host countries weakens the promotion effect of R-assets on internationalization speed of MNEs, while the industry uncertainty strengthens the promotion effect of those. Heterogeneity analysis illustrates that, compared with state-owned enterprises, non-state-owned enterprises have a more significant effect on the above conclusions.
Originality/value
This study enriches the literature on internationalization speed of MNEs by focusing on the determinants of internationalization speed through R-assets. From the perspective of knowledge, the work also provides a theoretical reference whereby MNEs can use host country R-assets to accelerate knowledge acquisition and then internationalization practice. In conclusion, this study provides valuable insights for managers aiming to develop effective strategies through R-assets to achieve rapid internationalization, contributing to an emerging literature stream on catch-up for emerging-market MNEs.
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Wu He, Jiancheng Shen, Xin Tian, Yaohang Li, Vasudeva Akula, Gongjun Yan and Ran Tao
Social media analytics uses data mining platforms, tools and analytics techniques to collect, monitor and analyze massive amounts of social media data to extract useful patterns…
Abstract
Purpose
Social media analytics uses data mining platforms, tools and analytics techniques to collect, monitor and analyze massive amounts of social media data to extract useful patterns, gain insight into market requirements and enhance business intelligence. The purpose of this paper is to propose a framework for social media competitive intelligence to enhance business value and market intelligence.
Design/methodology/approach
The authors conducted a case study to collect and analyze a data set with nearly half million tweets related to two largest retail chains in the world: Walmart and Costco in the past three months during December 1, 2014-February 28, 2015.
Findings
The results of the case study revealed the value of analyzing social media mentions and conducting sentiment analysis and comparison on individual product level. In addition to analyzing the social media data-at-rest, the proposed framework and the case study results also indicate that there is a strong need for creating a social media data application that can conduct real-time social media competitive intelligence for social media data-in-motion.
Originality/value
So far there is little research to guide businesses for social media competitive intelligence. This paper proposes a novel framework for social media competitive intelligence to illustrate how organizations can leverage social media analytics to enhance business value through a case study.
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Xiaojun Fan, Huiyao Li and Xinyu Jiang
Interactivity is the key to developing digital branding. However, existing research on brand interactivity outcomes is inconsistent and fragmented, lacking a systematic empirical…
Abstract
Purpose
Interactivity is the key to developing digital branding. However, existing research on brand interactivity outcomes is inconsistent and fragmented, lacking a systematic empirical exploration of its effects on consumer responses in the digital context.
Design/methodology/approach
Drawing upon the cognition-affection-conation (CAC) framework as our theoretical compass, a meta-analysis was conducted to synthesize and analyze empirical evidence from 144 samples involving 57,952 participants to assess how and when digital brand interactivity influences consumers’ multilevel responses.
Findings
Our narrative unfolds with digital brand interactivity as the catalyst, fostering positive consumer behaviors – brand loyalty and purchase intention – through a sequential dance of cognitive mindset shifts (brand experience, engagement and attitude) and affective resonance (trust and emotional attachment). A moderation analysis adds depth, revealing stronger effects in B2C settings for lesser-known brands with hedonic interaction content and among individuals with a collectivist orientation.
Practical implications
Our findings serve as a roadmap for targeted digital marketing strategies, guiding brands, consumers and contextual aspects to optimize the performance of digital branding by harnessing the full potential of digital interactivity.
Originality/value
This study introduces a framework combining CAC and brand-consumer psychology to understand how interactivity affects consumer responses in digital contexts. It delves into dynamic shifts moderated by brand characteristics, consumer traits and contextual factors, offering a holistic view of digital branding’s impact on interactive marketing.
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Dong Qian, Xuejing Wei, Guoqi Zhu, Xurong Ma, Beibei Hu and Xiaojun Pang
This study aims to investigate the mechanism of the influence of paradoxical thinking (PT), which characterizes the ability of college students to balance and integrate the…
Abstract
Purpose
This study aims to investigate the mechanism of the influence of paradoxical thinking (PT), which characterizes the ability of college students to balance and integrate the conflict between hedonic and normative goals, on their campus low-carbon behaviors.
Design/methodology/approach
The conceptual model of “PT − Paradoxical salience (climate change concern, CCC) − Paradoxical acceptance (support for low-carbon behavioral norms, SN) − paradoxical resolution (campus low-carbon intentions and behaviors, CLCIs and CLCBs)” was developed. Then, it was tested by PLS-SEM using survey data obtained from 501 Chinese college students, and the relative importance of each factor of CLCBs was determined by the importance-performance map analysis method. Finally, a mechanistic difference analysis was conducted.
Findings
PT, CCC and SN have the potential to influence the CLCBs of college students, with each of the three factors showing approximately 40% room for improvement in their impact. There exists an influential pathway of “PT → CCC → SN → CLCIs → CLCBs.” Notably, PT exhibits a stronger direct influence on college students’ private-sphere CLCBs compared to the public-sphere CLCBs.
Practical implications
Colleges should integrate the development of PT into the foundational framework of the entire education for sustainable development curriculum, while emphasizing the provision of opportunities for training in PT through pedagogical methods, and PT training can be integrated across various social levels.
Originality/value
This study offers a paradox theoretical framework for comprehending and elucidating the decision-making process underlying personal low-carbon behaviors, and advances the quantitative research of microindividual paradox processing by effectively conceptualizing and measuring paradoxical salience and acceptance.
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Mengxi Yang, Wansi Chen, Qingyu Zhou, Baiyin Yang and Cheng Xu
China after 1949, especially since entering the 21st century, significant progress has been made in leadership research under Chinese context. However, so far there has been no…
Abstract
Purpose
China after 1949, especially since entering the 21st century, significant progress has been made in leadership research under Chinese context. However, so far there has been no systematic review and prospect of China's leadership research in the past 70 years. Therefore, with the help of scientific visualization software Citespace, this paper analyzes the research papers on leadership in the context of China from the top international journals of management science and applied psychology (1949–2018), supplemented and verified the previous research conclusions based on qualitative review, and quantitatively demonstrated the research evolution of leadership field.
Design Methodology Approach
Using a scientific visualization tool CiteSpace and 145 international leadership works, which were published in 64 top international journals and collected from the Web of Science database, and 852 domestic works which were published in 28 top domestic journals and collected from the CNKI database from 1949 to 2018, we draws keyword co-occurrence knowledge graph and keyword strategy map to visualize the landscape and evolution of leadership research and analyze the hot topics and research trends in the field of leadership.
Findings
The research found that: (1) Before 2002, there were only 7 articles published in 64 international top journal, mainly focusing on Western leadership theories such as transformational, cross-cultural comparison and the adaptability in Chinese context; (2) From 2003 to 2012, scholars had begun to introduce mainstream quantitative research paradigm in international academic community; (3) From 2013 to 2018, researches tended to be synchronized, with 461 and 99 papers published respectively. How emerging leaderships (such as ethical leadership) affect on various emerging outcome variables (such as creativity, voice behavior, unethical pro-organizational behavior etc.) is hot topic for future research.
Originality Value
Different from the previous qualitative reviews on organizational culture research, this paper, for the first time, uses bibliometric research methods to systematically analyze the evolution path of leadership research during the 70 years of China(1949–2018, and puts forward the future research prospects.
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Liang Ding, Gianluca Antonucci and Michelina Venditti
This study aims to explore the impact of artificial intelligence-powered personalised recommendations (AI-PPRs) on user engagement, browsing behaviour and purchase intentions on…
Abstract
Purpose
This study aims to explore the impact of artificial intelligence-powered personalised recommendations (AI-PPRs) on user engagement, browsing behaviour and purchase intentions on TikTok (Douyin in China), focusing on how these recommendations affect user satisfaction and purchase intention, while also addressing potential privacy concerns. In addition, the research investigates the influence of AI-recommended product presentation, timing and placement, as well as social factors such as key opinion leaders’ (KOLs) influence on consumer decision-making.
Design/methodology/approach
Using the expectancy-value theory and the stimulus-organism-response model, this research used a qualitative methodology through interviews with Douyin users to explore their experiences and perceptions of AI-PPRs.
Findings
The findings indicate that Douyin’s proactive “push” mechanism of AI-PPRs enhances user engagement by effortlessly integrating product discovery into the entertainment experience. Content-driven AI-PPRs align with user preferences, decrease search time and increase satisfaction and purchase intentions through engaging short videos and live streaming. However, privacy concerns emerge when personalisation is perceived as excessively intrusive, leading to negative emotions and avoidance behaviours. Recommendation timing and cultural context significantly influence receptiveness, with inappropriate timing (e.g. during holidays) causing negative reactions. Technical challenges, such as network issues during live streaming, negatively impact user experience and engagement. Content quality is crucial, and poor or irrelevant content leads to negative perceptions and disengagement. While KOLs face scepticism due to perceived commercialisation, endorsements from trusted figures and authentic influencers are better received. Innovative payment methods, like “Douyin Monthly Payment”, enhance financial flexibility and promote customer loyalty. This study highlights the need to balance personalisation with privacy, emphasising the importance of content quality and authenticity in influencer marketing. For businesses using AI-PPRs, maintaining this balance is essential for preserving trust and sustaining consumer engagement and loyalty.
Originality/value
This study contributes valuable insights to the field by unravelling the intricate dynamics between AI-PPRs, user preferences and social influences. The findings provide practical implications for companies aiming to optimise personalised recommendation algorithms and enhance user engagement, thereby facilitating business growth in the dynamic short video e-commerce market.
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This paper aims to study the contact between rough cylindrical surfaces considering the elastic-plastic deformation of asperities.
Abstract
Purpose
This paper aims to study the contact between rough cylindrical surfaces considering the elastic-plastic deformation of asperities.
Design/methodology/approach
The elastic deformation of the nominal surface of the curved surface is considered, the contact area is discretized by the calculus thought and then the nominal distance between two surfaces is obtained by iteration after the pressure distribution is assumed. On the basis of the Zhao, Maietta and Chang elastic-plastic model, the contact area and the contact pressure of the rough cylindrical surfaces are calculated by the integral method, and then the solution for the contact between rough cylindrical surfaces is obtained.
Findings
The contact characteristic parameters of smooth surface Hertz contact, elastic contact and elastic-plastic contact between rough cylindrical surfaces are calculated under different plastic indexes and loads, and the calculation results are compared and analyzed. The analysis shows that the solution considering the elastic-plastic deformation of asperities for the contact between rough cylindrical surfaces is scientific and rational.
Originality/value
This paper provides a new effective method for the calculation of the contact between rough cylindrical surfaces.
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Neelam Rani, Muhammad Zafar Yaqub, Nidhi Singh and Pierpaolo Magliocca
The purpose of this paper is to review how knowledge transfer, including knowledge integration, absorptive capacity and reverse knowledge transfer (RKT) in cross-border…
Abstract
Purpose
The purpose of this paper is to review how knowledge transfer, including knowledge integration, absorptive capacity and reverse knowledge transfer (RKT) in cross-border acquisitions, is examined in existing research work. The authors also propose directions to advance research in cross-border acquisitions.
Design/methodology/approach
A systematic literature review is conducted, and related propositions are advanced based on scientometric and bibliometric analysis of 146 papers published over 10 years about tacit knowledge transfer, innovation activities, industrial policy effect on merger decisions, top management experience and value creation in cross-border acquisition. First, the authors searched major themes with the help of Scopus, and later, the authors analysed all received literature with the help of VOS Viewer.
Findings
This review facilitates us to identify six clusters and main author keywords. These six clusters are the underlying six research streams, including RKT, cultural distances, value creation, absorptive capacity, innovation and reference to India and China.
Originality/value
Despite knowledge transfer constituting important antecedents and critical factors for the success of cross-border acquisitions, knowledge management in the acquired company through proper knowledge transfer and knowledge integration is not given enough attention. Current literature still fails to provide a holistic picture of how firms strategically manage knowledge post-acquisition. To the best of the authors’ knowledge, this study is the first to analyse the dynamics of knowledge transfer in cross-border acquisitions. The study is a novel attempt to relate current research themes to emerging areas of cross-border acquisitions.