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This study aims to examine the public’s acceptance of film-induced tourism and develops the relationship among placement marketing, involvement, place attachment and travel intention. The film Your Love Song shot in the Hualien and Taitung regions in Taiwan was selected as the case study.

An online sample survey was conducted using a structured questionnaire, and statistical tests and overall structural equation modeling analysis using the SPSS and AMOS statistical software packages, respectively, were performed.

This study results demonstrate that destination placement marketing has a significant positive effect on the level of destination involvement, place attachment and travel intention of viewers. Moreover, the level of involvement has some intermediary effect on the interrelationship between placement marketing and travel intention. Hence, this study suggests that relevant government agencies and tourism operators should promote local tourism through films and television shows and attract more tourists by retaining the original shooting scenes.

While previous studies have only analyzed two or three of the four concepts of film-induced tourism, placement marketing, travel intention, involvement and place attachment, this study completely integrates these four concepts and proves the correlation between them.

This study aims to use emotions-as-social information theory to investigate how physical (customer perceived store atmosphere) and social servicescapes (customer information searching) influence the effects of employees’ positive affective displays on customer outcomes via customer positive moods and positive expectation disconfirmation.

This research included two studies, each using a distinct research design, to empirically test the proposed model. Study 1 involved 200 observational data points on objective purchase amounts from designer watch shops. In Study 2, data were collected from 230 customers in designer jewelry stores.

The results of path analyses revealed that: employee positive affective displays are positively associated with customer purchase outcomes; employee positive affective displays had positive indirect effects on customer purchase outcomes by enhancing customer positive moods and positive expectation disconfirmation; these positive indirect effects were strengthened when customers engaged in information search behaviors; and these positive indirect effects were attenuated when customers perceive store atmosphere as favorable, indicating a substitution effect of customer perceived store atmosphere.

Previous research has not thoroughly examined the role of the servicescape in moderating the effects of employees’ positive affective displays on customer purchase outcomes. This present study not only clarified the affective and cognitive mechanisms that link employees’ positive affective displays on purchase outcomes but also identified servicescape as a critical boundary condition of these effects.

This research explores how individual factors drive early-stage strategic entrepreneurship (SE) in Vietnam and Taiwan. The authors extend SE and integrate knowledge spillover theory to gain insights into the relationship between individual factors and SE. The research highlights the importance of a dual process, which involves advantage-creating by innovation, as value creation and capture, and advantage-leveraging by growth and international expansion, as value retention and capture.

Innovation-oriented SE (ISE), growth-oriented SE (GSE) and internationalization-oriented SE (ITSE) are identified as new measures of SE. There are six hypotheses containing the effect of six personal characteristics have on SE. The authors employed logit regression to estimate the effect of independent variables on SE based on a pooled cross-sectional dataset drawn from Global Entrepreneurship Monitoring (GEM) in Vietnam and Taiwan during 2013–2018.

Opportunity sensing, education, self-funding ability, startup knowledge and skills and startup experience are crucial to the engagement of at least one type of SE in Vietnam. In contrast, education, self-funding ability and start-up knowledge and skills are key factors in Taiwan.

This study contributes to the extension of SE at the individual level in the early phase of new venturing and the integration of knowledge spillover theory. In order to drive early-stage SE further, the authors recommend to prioritize learning from spillovers within and among organizations, industries and communities, as well as through quality institutions, in addition to the individual drivers.

During the current global epidemic, e-learning and mobile learning have been rapidly developed in the field of entrepreneurship education. The effect of these learning methods remains to be confirmed. The purpose of this paper is to explore the effect of mobile business simulation games in entrepreneurship education.

From May 2020 to July 2020, the authors adopted a quasi-experimental design to explore the effect of mobile business simulation games in entrepreneurship education. The authors set up an experimental group to participate in mobile business simulation games, with a total of 105 students, and set up a control group of 100 students. At the beginning and end of the experiment, data on entrepreneurial attitude, self-efficacy, entrepreneurial intention and other related variables were collected. Paired sample T-test and regression analysis were used to analyze the results.

The authors found that mobile business simulation games can improve entrepreneurial attitudes and self-efficacy, but cannot change entrepreneurial intentions. The paired sample T-test in the experimental group showed that the entrepreneurial attitude and entrepreneurial self-efficacy of the participants were significantly improved, but the entrepreneurial intention did not change significantly. The above three variables did not change significantly in the control group. The research results also show that flow experience is very important in mobile business simulation games, which can improve entrepreneurial attitude and entrepreneurial self-efficacy.

The authors’ findings confirm the positive effects of mobile business simulation games in entrepreneurship education, which can improve entrepreneurial attitudes and entrepreneurial self-efficacy. But the disadvantage of mobile business simulation games is that they cannot increase entrepreneurial intention. In addition, the flow experience needs to be valued in mobile business simulation games. The research in this paper has implications for how mobile learning can be used in entrepreneurship education during the COVID-19 pandemic. In addition, research is of great value on how mobile business simulation games can be improved.

Based on the model of Big-Five personality traits and theories of person–environment interaction, this study aims to investigate the moderating effects of personality traits on innovativeness through knowledge sharing (KS).

A sample of 318 Vietnamese employees was collected. The hypothesized model was tested by using partial least squares structural equation modelling.

The results indicate that extraversion, agreeableness, conscientiousness and openness to experience have relationships with innovativeness through the mediating effect of KS. Furthermore, transformational leadership (TL) mitigates the positive relationship between agreeableness and openness to experience and innovativeness.

Based on the research results, the authors suggest several practical implications for enhancing employees' innovative organizational behaviours. Transformational leaders should be aware of and control the relationships with employees high in agreeableness and open to experience to ensure that employees' innovativeness can be freely developed.

This research systematically investigates the effect of each personality on employees' innovativeness. Furthermore, this study contributes to the leadership literature by suggesting the dark side of TL that can negatively influence the innovative ability of employees with certain personality traits.

The type 120 emergency valve is an essential braking component of railway freight trains, but corresponding diaphragms consisting of natural rubber (NR) and chloroprene rubber (CR) exhibit insufficient aging resistance and low-temperature resistance, respectively. In order to develop type 120 emergency valve rubber diaphragms with long-life and high-performance, low-temperatureresistant CR and NR were processed.

The physical properties of the low-temperature-resistant CR and NR were tested by low-temperature stretching, dynamic mechanical analysis, differential scanning calorimetry and thermogravimetric analysis. Single-valve and single-vehicle tests of type 120 emergency valves were carried out for emergency diaphragms consisting of NR and CR.

The low-temperature-resistant CR and NR exhibited excellent physical properties. The elasticity and low-temperature resistance of NR were superior to those of CR, whereas the mechanical properties of the two rubbers were similar in the temperature range of 0 °C–150 °C. The NR and CR emergency diaphragms met the requirements of the single-valve test. In the low-temperature single-vehicle test, only the low-temperature sensitivity test of the NR emergency diaphragm met the requirements.

The innovation of this study is that it provides valuable data and experience for future development of type 120 valve rubber diaphragms.

Traditional multivariable grey prediction models define the background-value coefficients of the dependent and independent variables uniformly, ignoring the differences between their physical properties, which in turn affects the stability and reliability of the model performance.

A novel multivariable grey prediction model is constructed with different background-value coefficients of the dependent and independent variables, and a one-to-one correspondence between the variables and the background-value coefficients to improve the smoothing effect of the background-value coefficients on the sequences. Furthermore, the fractional order accumulating operator is introduced to the new model weaken the randomness of the raw sequence. The particle swarm optimization (PSO) algorithm is used to optimize the background-value coefficients and the order of the model to improve model performance.

The new model structure has good variability and compatibility, which can achieve compatibility with current mainstream grey prediction models. The performance of the new model is compared and analyzed with three typical cases, and the results show that the new model outperforms the other two similar grey prediction models.

This study has positive implications for enriching the method system of multivariable grey prediction model.

In this study, an indoor sensor information fusion positioning system of the quadrotor unmanned aerial vehicle (UAV) was investigated to solve the problem of unstable indoor flight positioning.

The presented system was built on Light Detection and Ranging (LiDAR), Inertial Measurement Unit (IMU) and LiDAR-Lite devices. Based on this, one can obtain the aircraft's current attitude and the position vector relative to the target and control the attitudes and positions of the UAV to reach the specified target positions. While building a UAV positioning model relative to the target for indoor positioning scenarios under limited Global Navigation Satellite Systems (GNSS), the system detects the environment through the NVIDIA Jetson TX2 (Transmit Data) peripheral sensor, obtains the current attitude and the position vector of the UAV, packs the data in the format and delivers it to the flight controller. Then the flight controller controls the UAV by calculating the posture to reach the specified target position.

The authors used two systems in the experiment. The first is the proposed UAV, and the other is the Vicon system, our reference system for comparison purposes. Vicon positioning error can be considered lower than 2 mm from low to high-speed experiments. After comparison, experimental results demonstrated that the system could fully meet the requirements (less than 50 mm) in real-time positioning of the indoor quadrotor UAV flight. It verifies the accuracy and robustness of the proposed method compared with that of Vicon and achieves the aim of a stable indoor flight preliminarily.

Vicon positioning error can be considered lower than 2 mm from low to high-speed experiments. After comparison, experimental results demonstrated that the system could fully meet the requirements (less than 50 mm) in real-time positioning of the indoor quadrotor UAV flight. It verifies the accuracy and robustness of the proposed method compared with that of Vicon and achieves the aim of a stable indoor flight preliminarily.

With the development of data mining technology, diverse and broader domain knowledge can be extracted automatically. However, the research on applying knowledge mapping and data visualization techniques to genealogical data is limited. This paper aims to fill this research gap by providing a systematic framework and process guidance for practitioners seeking to uncover hidden knowledge from genealogy.

Based on a literature review of genealogy's current knowledge reasoning research, the authors constructed an integrated framework for knowledge inference and visualization application using a knowledge graph. Additionally, the authors applied this framework in a case study using “Manchu Clan Genealogy” as the data source.

The case study shows that the proposed framework can effectively decompose and reconstruct genealogy. It demonstrates the reasoning, discovery, and web visualization application process of implicit information in genealogy. It enhances the effective utilization of Manchu genealogy resources by highlighting the intricate relationships among people, places, and time entities.

This study proposed a framework for genealogy knowledge reasoning and visual analysis utilizing a knowledge graph, including five dimensions: the target layer, the resource layer, the data layer, the inference layer, and the application layer. It helps to gather the scattered genealogy information and establish a data network with semantic correlations while establishing reasoning rules to enable inference discovery and visualization of hidden relationships.

This paper aims to discuss the firm productivity premium for servitized firms. It discusses servitization across the product value chain and estimates the effects of the range and extent of servitization on productivity premium in manufacturing firms.

This paper develops a conceptual framework and tests the hypotheses on the effects of servitization on productivity premium using linear regression models with a sample of 20,837 Russian manufacturing firms gathered from the Ruslana Bureau van Dijk database and the Russian customs service.

Servitized firms exhibit higher total factor productivity and labor productivity. The labor productivity premium increases with the number of services offered. However, the impact of services on productivity varies along the product value chain: postmanufacturing and postsales services enhance productivity premium, while manufacturing and back-office services diminish them. The effect of establishment services remains ambiguous.

This paper offers an analytical framework for firms to assess their servitization strategies. These strategies should be gradual, focused on enhancing firm efficiency rather than being an end goal. Firms should initiate the process by introducing services at the postproduction and postsales stages of the product creation chain to achieve productivity premium.

The paper extends the evidence on firm-level productivity drivers and contributes to the servitization theory. A servitization strategy should be portfolio-based, considering both the potential gains and losses in productivity resulting from the implementation of specific services.