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The purpose of this paper is to examine the relationship between competitive personality (CMP) and rationalized knowledge hiding (KH) and to explore the mediating effects of knowledge-based psychological ownership (KPO) and organization-based PO (OPO) by developing a mediating framework.

Data were collected from the ordinary employees of listed companies in China (2022) via a Web-based survey. The total number of valid samples was 337. Confirmatory factor analysis was used to test the reliability and validity of the constructs, and structural equation modeling was used to verify the direct and mediating effects.

The findings revealed a positive relationship between CMP and rationalized KH (RKH). KPO plays a positive mediating role between CMP and RKH, whereas OPO plays a negative mediating role between CMP and RKH.

First, although the questionnaire collection is split into two sessions to reduce common method variation, there is inevitably some risk, as the questionnaires are all reported by the same respondent. Second, this study examined the effects of CMP on RKH based on the Chinese cultural context, but the applicability of this finding to cross-cultural contexts warrants further study. In the future, researchers can conduct cross-cultural comparisons to determine the generalizability of the findings.

This study helps managers to better identify the RKH behaviors that exist in organizations, understand the reasons and processes behind employees’ KH and facilitate more effective knowledge management by managers.

This study uses CMP as an important indicator of employees’ RKH behavior, enriches the research related to the antecedent variables of RKH and reveals the influence mechanism between CMP and RKH from the perspective of PO, and the findings can help researchers and managers understand the process and antecedents of RKH so that timely interventions can be implemented.

The paper aims to present a tracked robot comprised of several biochemical sampling instruments and a universal control architecture. In addition, a dynamic motion planning strategy and autonomous modules in sampling tasks are designed and illustrated at length.

Several sampling instruments with position tolerance and sealing property are specifically developed, and a robotic operation system (ROS)-based universal control architecture is established. Then, based on the system, two typical problems in sampling tasks, i.e. arm motion planning in unknown environment and autonomous modules, are discussed, implemented and tested. Inspired by the idea of Gaussian process classification (GPC) and Gaussian process (GP) information entropy, three-dimensional (3D) geometric modeling and arm obstacle avoidance strategy are implemented and proven successfully. Moreover, autonomous modules during sampling process are discussed and realized.

Smooth implementations of the two experiments justify the validity and extensibility of the robot control scheme. Furthermore, the former experiment proves the efficiency of arm obstacle avoidance strategy, while the later one demonstrates the time reduction and accuracy improvement in sampling tasks as the autonomous actions.

The proposed control architecture can be applied to more mobile and industrial robots for its feasible and extensible scheme, and the utility function in arm path planning strategy can also be utilized for other information-driven exploration tasks.

Several specific biochemical sampling instruments are presented in detail, while ROS and Moveit! are integrated into the system scheme, making the robot extensible, achievable and real-time. Based on the control scheme, an information-driven path planning algorithm and automation in sampling tasks are conceived and implemented.

With the ever-expanding online shopping, electronic word-of-mouth (eWOM) has become a significant factor affecting the consumer decision-making behaviour. This is specially the case when considering Generation Y (Millennials), who are old enough to be independent buyers and young to be almost immersed in online living. This article aims to assess the impact of eWOM on purchase intention by developing a conceptual model of hypotheses encompassing a multitude of factors that may be associated with this relationship.

The researcher investigates what factors impact eWOM credibility and make the consumer may adopt it when making a purchase. To examine our research model, a quantitative approach is employed for this purpose using a sample through online survey from Thailand – where there is a large number portion Generation Y consumer base.

It was found that source style as a visual attribute information is the most significant factor that may impact eWOM credibility in addition to source credibility, argument quality and source homophily, respectively.

From a practical point of view, it helps firms to understand what needs to be taken into consideration when building their marketing strategy.

This is believed to add significant insights into the eWOM literature by identifying its route of impact toward the purchase intention on Generation Y.

The purpose of this paper is to investigate the mediating effect of information sharing (IS) on the link between supply chain integration (SCI) practices (internal, customer and supplier) and internal process performance (IPP) by using selected agribusiness firms from an emerging economy, Ghana.

To determine the effect of IS on the nexus between SCI practices and IPP, a research framework was developed and tested using data amassed from 156 agribusiness firms for the study. The data set was assessed and hypotheses were tested using structural equation modelling.

The outcomes revealed that both INI and CI positively and significantly influenced IS. However, the results disclosed that SI has no significant positive effect on IS among the Ghanaian agribusiness firms. The findings of the study further discovered that IS fully mediates the relationship between INI, CI and IPP, whereas SI has a direct interaction with IPP.

This study contributes to the existing supply chain management research by empirically authenticating IS as the mediator between SCI practices and IPP. From the viewpoint of a developing economy, this paper identifies the significant connection that exists between SCI practices, IS and IPP. The outcomes recommend that IS is a core driving facilitator to reinforce the correlation between SCI practices and IPP.

Social media influencers (SMIs) play an increasingly important role in influencing youth and their shopping behaviours in digital marketing. Research has examined various but fragmented SMIs, which cause inconsistency in empirical results. This research seeks to categorise the most popular SMIs in luxury fashion and examine their distinctive effects on Gen Z consumption in China.

The authors categorise SMIs into four groups based on two dimensions, i.e. network interactivity vs social connectedness. Drawing on the social network theory, the authors develop the research model. A sample of 400 survey data is collected and analysed using the PLS-SEM technique.

The empirical results suggest that among the four popular SMIs groups, the effects of celebrities, opinion leaders and friends and peers on luxury fashion consumption of Gen Z are statistically significant while that of advertisers are insignificant; that friends and peers have the most substantial effect among the others.

The study contributes to understanding SMIs and consumer behaviour in digital emerging markets. By categorising SMIs, this study reconciles inconsistencies in the concept. This study contributes to a better understanding of SMIs and their roles in the digital marketing of luxury fashion consumption.

The purpose of this study aims to modify a self-mixing laser mouse as an extremely cost-effective displacement sensor to measure the mechanical oscillation of a commercial shaker and a nano-positioning stage.

This kind of laser mouse, mostly consisting of a pair of vertical cavity surface emitting lasers, two photodiodes and an integrated signal processing unit, is capable of directly giving the x-axis and y-axis components of the measured vibrating displacement. Based on the laser self-mixing interference, the velocity of the object is coded into the Doppler frequency shift of the feedback light, which allows accurate determination of the vibration of the object.

A commercial shaker has been used to provide standard harmonic oscillation to test the displacement sensor. Within a vibrating frequency range of 110 Hz, the experimental results show that the micrometer scale resolution has been achieved at the velocity of up to 2 m/s, which is much improved compared with the image-based optical mouse. Furthermore, the measurements of the two dimensional displacement of a nano-positioning stage are performed as well. The minimum measurable velocity limit for this sensor has been discussed in detail, and the relative measurement error can be greatly reduced by appropriate selection of the modulation frequency of the triangular injection current.

These results demonstrate the feasibility of this device for the industrial vibration sensing applications.

The purpose of this paper is to present a new model which combines the non-equidistant GM(1,1) model with GCHM_WBO (generalized contra-harmonic mean (GCHM); weakening buffer operator (WBO)). The authors use the model to solve the deadlock that for a large number of non-equidistant corrosion rate, it is difficult to establish a reasonable prediction model and improve the prediction accuracy.

This research consists of three parts: non-equidistant GM(1,1) model, GCHM_WBO operator, and the optimization of morphing parameter (contained in GCHM, control the intensity of the weakening operator). The methodology is explained as follows. First, the authors built a non-equidistant GM(1,1) model with GCHM_WBO weakened data, of which morphing parameter was randomly selected. Next, the authors calculated the error between prediction data of model and the real data, and adjusted the morphing parameter according to the error and property of GCHM. Then, the authors generated a new non-equidistant GM(1,1) based on new morphing parameter, and repeated the previous step until the termination condition was satisfied. Finally, the model with appropriate morphing parameter was used to implement the prediction of new data.

This paper finds a property of GCHM, which is a monotonic increasing function of morphing parameter in some specific conditions. Based on the property and the fixed point axiom of WBO, an algorithm was designed to search an appropriate morphing parameter. The appropriate morphing parameter was implemented for the purpose of improving the accuracy of the model. The model was applied to predict the corrosion rate of six steels at Guangzhou experimental station. The results showed that the proposed method can get more accuracy in prediction capability compared to the models with the original data and AWBO weakened data. The method is applicable to long-term forecasts in case of data scarcity.

Corrosion will cause huge economic loss to a country; therefore, it is important to judge the remaining useful life of a material or equipment; the foundation for judgement of which is the prediction of material corrosion rate. However, the prediction of corrosion rate is very difficult because of corrosion data’s features, such as small sample size, non-equidistant, etc. The proposed method can be used to implement long-term forecast of corrosion data with only one sample and non-equidistant samples.

This paper presented a model which combines the non-equidistant GM(1,1) model with GCHM_WBO to handle the problem of long-term forecasting of corrosion data. In the modelling process, the proposed morphing parameter searched through algorithm can improve the prediction accuracy of the model. Therefore, the model can provide effective and reliable result when data are of a small sample size and non-equidistant.

This paper aims to identify distinct consumption patterns among Asian consumers and examine how these relate to cultural antecedents and key human values.

This study uses a large, representative sample of almost 7,000 Asian consumers in 10 culturally varying markets, using latent profile analysis (LPA) to identify the consumption profiles.

The findings empirically demonstrate that the two profiles are “inner-directed nationalistic frugals” (IDNF) and “outer-directed self-eekers” (ODSS). IDNF consumers spend more time and money on education and prefer ethnocentric consumption. ODSS consumers emphasize individuality, self-expression, seeking novelty and impressing others. Consumers with more collective values in Schwartz's typology tend to demonstrate the IDNF pattern; those with more individualistic values demonstrate the ODSS pattern. The distribution of IDNF and ODSS profiles is influenced by demographics, religion and geographical region: IDNF is greater than ODSS in Southeast Asia; ODSS is greater than IDNF in East Asia; IDNF is roughly equal to ODSS in Northeast Asia. IDNF tends to be found among older and more religious consumers, while ODSS is the opposite. Importantly, in the more religious Southeast Asian countries, even younger consumers are more IDNF than ODSS.

This research uses an exploratory and discovery-oriented approach; future research can use more confirmatory approaches to systematically examine the relationship between cultural dimensions (e.g. individualism-collectivism) and consumption patterns.

For their brands to grow in Asian markets, marketing practitioners are advised to use multiple brands to segment Asian consumers based on their values, demographics, geographical location and what religious/faith traditions they follow.

This is the first paper to identify consumption profiles in Asian markets using LPA without prior conceptual biases and relate them to cultural values and demographic variables.

The purpose of this study is to construct a scale that is contextually suitable for measuring early childhood leadership in China.

Following a standard scale development procedure, both qualitative and quantitative research approaches were addressed. Qualitative data was collected from 21 semistructured interviews with formal and informal teacher leaders in Xiamen City, China. Using survey data of 120 respondents and 305 respondents, an exploratory factor analysis was conducted twice to determine the underlying factorial structure of the scale. A further sample of 317 respondents were used to test the latent structure and validity of the scale using confirmatory factor analysis.

Based on the results from reliability and validity tests, this study indicates that the scale demonstrates sound psychometric properties. A three-factor model was determined, including staff management and development, peer learning and support and communication with parents.

The scale is the first of its kind for measuring early childhood leadership in China.

The purpose of this study is to examine the effects of executives’ overseas education and work experience on enterprise digital as executives’ overseas background is critical to the development of enterprises. It also explored the mediating role of enterprise digital transformation on the relationship between executives’ overseas background and enterprise growth.

Chinese A-share companies listed on the Shanghai and Shenzhen Stock Exchanges for the period 2018–2020 were analyzed using regression analysis and bootstrapping to verify hypothesized relationships.

Executives’ overseas study and work experience both enhanced enterprise digital transformation significantly, thus improving enterprise growth. The level of employee education moderated the mediating role proposed in the theoretical model. Moreover, the promoting effect of executives’ overseas background on enterprise digital transformation was more significant for non-state-owned enterprises and those in eastern China.

The findings provide reference for the formulation and optimization of companies’ human resource structure and have implications on the improvement of enterprise digital transformation and enterprise growth.

This study explored the factors influencing enterprise digital transformation at the microlevel of corporate human capital, thereby providing microlevel empirical evidence for research on the factors influencing enterprise digital transformation. Its findings shed light on the mechanism and context under which executives with overseas backgrounds may enhance enterprise digital transformation and growth.