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The purpose of this paper is to examine the interaction effects of spokes-character dynamism (high vs low) and brand personality (sincere vs competent) on consumers’ evaluation and the mediating role of processing fluency.

Two experiments were conducted to test the hypotheses. Study 1 establishes the interaction effect between evoked spokes-character dynamism and brand personality on brand trust and examines the mediating role of processing fluency. By introducing a control group and using purchase intention as the dependent variable, Study 2 further extends the results of Study 1.

The results of Studies 1 and 2 show that for sincere brands, spokes-characters with high dynamic imagery contribute to significantly higher consumer evaluation than the control group and the group of spokes-characters with low dynamic imagery. However, for competent brands, spokes-characters with low dynamic imagery contribute to significantly higher consumer evaluation than the control group and the group of spokes-characters with high dynamic imagery. In addition, processing fluency mediates the interaction effect between evoked spokes-character dynamism and brand personality on consumers’ evaluation.

The studies considered only one method, “frozen motion,” to evoke perceived movement. Further studies using other methods are needed to allow for generalization.

The discerning use of dynamic imagery in spokes-character design involving advertisements may aid marketers in maximizing spokes-characters’ effect on consumers’ evaluation.

The perceived movement of spokes-characters is integrated into the cognition of brand personality. Marketers should take into account how the match between spokes-character dynamism and brand personality may influence consumers’ evaluation of the brand.

The purpose of this paper is to identify salient topic categories and outline their evolution patterns and temporal trends in microblogs on a public health emergency across different stages. Comparisons were also examined to reveal the similarities and differences between those patterns and trends on microblog platforms of different languages and from different nations.

A total of 459,266 microblog entries about the Ebola outbreak in West Africa in 2014 on Twitter and Weibo were collected for nine months after the inception of the outbreak. Topics were detected by the latent Dirichlet allocation model and classified into several categories. The daily tweets were analyzed with the self-organizing map technique and labeled with the most salient topics. The investigated time span was divided into three stages, and the most salient topic categories were identified for each stage.

In total, 14 salient topic categories were identified in microblogs about the Ebola outbreak and were summarized as increasing, decreasing, fluctuating or ephemeral types. The topical evolution patterns of microblogs and temporal trends for topic categories vary on different microblog platforms. Twitter users were keen on the dynamics of the Ebola outbreak, such as status description, secondary events and so forth, while Weibo users focused on background knowledge of Ebola and precautions.

This study revealed evolution patterns and temporal trends of microblog topics on a public health emergency. The findings can help administrators of public health emergencies and microblog communities work together to better satisfy information needs and physical demands by the public when public health emergencies are in progress.

The purpose of this paper is to theoretically and empirically analyze the impact of the types of micro-innovation on innovation performance and the choice of micro-innovation strategies in different contexts on the basis of an examination of the basis and standards of micro-innovation categorization.

The authors collected and analyzed 206 survey samples from the Zhejiang Province in China; there were 68, 63 and 75 enterprises at inception, high growth and maturity stages, respectively, and there were, in total, 53, 90 and 63 low-tech manufacturing small and medium enterprises (SMEs), technology-intensive manufacturing SMEs and service-oriented SMEs, respectively. Multiple regression analysis was used to test the hypotheses.

The analysis results suggest that SMEs at the embryonic stage should choose strategies of imitative innovation, whereas SMEs at growth stage should use continued micro-innovation and independent micro-innovation as the optimal choices; it is better for the SMEs at the mature stage to resort to independent micro-innovation. Low-tech manufacturing SMEs should opt for the continued micro-innovation strategy, and technology-intensive manufacturing SMEs should adopt independent micro-innovation, whereas service-oriented SMEs should choose both continued and independent micro-innovation strategies.

This study sets up a classification framework of micro-innovation and addresses its category and sources, thus extending the micro-innovation research results. The conclusion also supports and enriches the view of open innovation in the innovation theory. Hidden behind the phenomenon that internal and external factors play vital roles, it is a basic rule that innovation activities must be subject to various related factors.

The purpose of this research is to achieve automatic and accurate book purchase forecasts for the university libraries and improve efficiency of manual book purchase.

The authors presented a Book Purchase Forecast model with A Lite BERT(ALBERT-BPF) to achieve their goals. First, the authors process all the book data to unify format of books' features, such as ISBN, title, authors, brief introduction and so on. Second, they exploit the book order data to label all books supplied by booksellers with “purchased” or “non-purchased”. The labelled data will be used for model training. Last, the authors regard the book purchase task as a text classification problem and present a model named ALBERT-BPF, which applies ALBERT to extract text features of books and BPF classification layer to forecast purchased books, to solve the problem.

The application of deep learning in book purchase task is effective. The data the authors exploited are the historical book purchase data from their university library. The authors’ experiments on the data show that ALBERT-BPF can seek out the books that need to be purchased with an accuracy of over 82%. And the highest accuracy reached is 88.06%. These indicate that the deep learning model is sufficient to assist the traditional manual book purchase way.

This research applies ALBERT, which is based on the latest Natural Language Processing (NLP) architecture Transformer, to library book purchase task.

There are different views on how to gain a sustainable competitive advantage (SCA) for firms. This topic has become an important research area in strategic management. The purpose of this paper is to provide an approach for Chinese firms to use as a springboard to identify sources of SCA through marketing innovation.

Based on a cursory review of the generic literature on how to gain SCA, this paper considers innovation as a primary source of a firm's competitive advantage. From a practical viewpoint, marketing innovation is identified as a significant source of SCA, especially for those firms operating in the dynamic and competitive Chinese economic environment. Through an analysis of marketing innovations at the Huawei Technologies Co. Ltd in China, an approach is developed to help managers identify their unique sources of SCA through marketing innovation.

This study reveals marketing innovation results from a considered analysis of the various marketing factors in the environment and the inter‐relationships between these factors. Subsequently, new sources of SCA can be identified, based on a firm's previous sources of competitive advantage. In this process, different types of competitive advantage are viewed in a holistic framework, which provides the basis for improving firm performance.

The approach developed in this paper offers a basis for managers to identify their firm's unique SCA through marketing innovation.

The paper provides insights for academics and professionals in the field and adds to the literature on emerging economies and SCA.

A novel fault-tolerant control (FTC) method is proposed to assure the stability of the remote-operated vehicle (ROV) by considering the thruster failure-induced model perturbations. The stability of the ROV with failures is guaranteed and optimized with the determined model perturbation set. The effectiveness of the double-boundary interval fault-tolerant control (DBIFTC) is verified through the experiments and proves that the stability is well maintained, which demonstrates a decent performance.

This paper studies a control problem for a multi-vector propulsion ROV by using the DBIFTC method in the presence of thruster failure and external disturbances. The ROV kinematics and dynamical models with multi-vector-arranged thruster failure are investigated and formulated for control system design.

In this paper, the authors address the FTC problem of ROV with multi-vector thrusters and propose a DBIFTC scheme. The advantage is that as the kinematic system model of ROV is preanalyzed and identified, the DBIFTC becomes more effective. The mathematical stability of the system under the proposed control scheme can be guaranteed.

The ROV model used in this paper is based on the system identification of experimental data. Although this model has real experimental value and physical significance, the accuracy can be further improved.

Cable-controlled underwater ROVs are widely used in military missions and scientific research because of their flexibility, sufficient load capacity and real-time information transmission characteristics. The DBIFTC method proposed in this paper can effectively reduce the problem of underwater vehicle under propeller failure or external disturbance and save unnecessary cost.

The DBIFTC method proposed in this paper can ensure the attitude stability of ROV or other underwater equipment operating in the event of propeller failure or external disturbance. In this way, the robot can better perform undersea work and tasks.

The kinematics and failure mechanisms of the ROV with multi-vector propulsion system are investigated and established. An optimized DBIFTC scheme is investigated to stabilize ROV yaw attitude under the thruster failure condition. The feasibility and effectiveness of the DBIFTC is experimentally validated.

The purpose of this paper is to establish a dynamic model considering the actual operating conditions of the train and to study the dynamic performance and vibration characteristics of axle box bearings under different operating conditions.

In this paper, based on the internal contact characteristics of double-row tapered roller bearings, a dynamic model considering the actual operating conditions of the train is established. The correctness of the model is verified by the vibration test of the bearing. Comparative analysis was conducted on the effects of axial force, radial force and rotational speed on the angular velocity of the cage, slip rate and vibration acceleration level of the inner ring.

As the force increases, the slip rate of the cages on both sides decreases, and the vibration acceleration level of the inner ring increases. With the increase of rotational speed, the cage slip rate of the axle box bearing increases and the vibration acceleration level of the inner ring increases.

A dynamic model is established considering the actual operating conditions, and the dynamic performance and vibration characteristics of the axle box bearing under different operating conditions are analyzed by numerical method. The research content can provide reference for the parameter design of high-speed railway bearings.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0085/

Scholars have examined the relationship between sports and urban development and proposed to use sport programs and events as a catalyst to revitalize communities, upgrade urban infrastructure, promote city image, shift economic structure, nurture an active lifestyle, and enhance societal harmony and solidarity. Yet, previous studies were usually focused on mega sport events and were typically conceptual, theoretical and lack of practical applications. This study was designed to attain in-depth understanding on how a specific sport, table tennis, can be systematically organized and utilized to influence urban development through a qualitative research injury.

This investigation was carried by conducting in-depth interviews of the executive director of the Shanghai Table Tennis Association, on-site observations and comprehensive review of literature. Development of interview questions took into consideration the conceptual framework postulated by Preuss (2007) that contains six structures of urban development through sports. Triangulation analyses were conducted to cross validate the three information sources to generate themes and assertions.

While the identified practices were consistent with Preuss' (2007) framework, specific management activities earnestly practiced in Shanghai are centered on utilizing cultural and historical heritage, star power, branding strategies, staging tournaments, hallmark events, technical innovation and government relations to achieve the objectives of table tennis as a sport and the objectives of urban development through table tennis.

The findings of this study help fill the void that a theory usually cannot specify, namely, detailed, unambiguous practices. While table tennis may be a viewed as a small sport in many parts of the world, it has a strong, unprecedented historical heritage in Shanghai. This city has made a prudent choice and investment in this sport, which has proved to be effective. Other cities in the world should look into their own social, cultural and historical heritage and develop sport strategies, operations and programs accordingly.

With the rapid development of social media, the occurrence and evolution of emergency events are often accompanied by massive users' expressions. The fine-grained analysis on users' expressions can provide accurate and reliable information for event processing. Hence, 2,003,814 expressions on a major malignant emergency event were mined from multiple dimensions in this paper.

This paper conducted finer-grained analysis on users' online expressions in an emergency event. Specifically, the authors firstly selected a major emergency event as the research object and collected the event-related user expressions that lasted nearly two years to describe the dynamic evolution trend of the event. Then, users' expression preferences were identified by detecting anomic expressions, classifying sentiment tendencies and extracting topics in expressions. Finally, the authors measured the explicit and implicit impacts of different expression preferences and obtained relations between the differential expression preferences.

Experimental results showed that users have both short- and long-term attention to emergency events. Their enthusiasm for discussing the event will be quickly dispelled and easily aroused. Meanwhile, most users prefer to make rational and normative expressions of events, and the expression topics are diversified. In addition, compared with anomic negative expressions, anomic expressions in positive sentiments are more common. In conclusion, the integration of multi-dimensional analysis results of users' expression preferences (including discussion heat, preference impacts and preference relations) is an effective means to support emergency event processing.

To the best of the authors' knowledge, it is the first research to conduct in-depth and fine-grained analysis of user expression in emergencies, so as to get in-detail and multi-dimensional characteristics of users' online expressions for supporting event processing.