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Having read previous literature about vortex pump, we noticed that mechanisms of circulating flow and its relationship with energy transition remain unclear yet. However, this mechanism, which should be clarified, significantly influences the pump’s efficiency. To comply with the aim of investigating it, the 150WX-200-20 type pump is selected as study object in our present work.

Numerical simulation is conducted to formulate interactions between flow rate and geometric parameters of circulating flow with certain types of blade while experiments on inner flow are served as a witness to provide experimental confirmation of numerical results. Based on these, we coupled some parameters with the pump’s external performance to study their internal connections.

It is concluded that separatrix between circulating flow and other turbulent forms is not that clear under low flow rate. With flow increases, hydraulic losses coming of it will be dominant within the front chamber. Besides, we analogized circulating flow to vortices so as to make a quantitative analysis on its progressive evolution with changing flow, and vortices speaking for circulating flow can be divided into two groups. One is called main circulating flow vortex (hereinafter referred to as MCFV), which occurs all the time while subsidiary circulating flow vortices (hereinafter referred to as SCFV) appear in certain conditions. This context discusses the primary phase of our work with intent to follow up further with circulating flow characterized by vortices (hereinafter referred to as CFV). We confirmed that MCFV Vortex 1 (Vor1) directly influences the efficiency while SCFVs only play helping. As the flow goes to the given working condition, fluids in this pump tend to be steady with the size of CFVs getting larger and their shape being regular. Meanwhile, for MCFV Vor2 and Vor4, their geometric parameters are the key factors for efficiency. When CFVs become steady, they absorb other vortices nearby, as they have higher viscosity with the efficiency reaching its maximum.

The research results explore a new way to measure the circulating flow and help work out the causation of this flow pattern, which may be used to improve the vortex pump’s efficiency.

Social media commerce provides a convenient way for users to share information and interact with each other. Few studies, however, have examined the effect of marketing messages and consumer engagement behaviors on the economic performance of marketing. This study, therefore, explored the economic performance of social media in terms of marketing messages and consumer engagement.

Using ordinary least squares regression and data collected from Weibo and Maoyan, this study analyzed the effects among marketing messages, consumer engagement and movie ticket sales.

The results indicated that marketing messages on Weibo had a positive effect on box office revenues, while consumer engagement behavior (whether personal or interactive) did not affect box office revenues. The results suggested that marketing messages on social media have more salient effects for predicting economic performance than consumer engagement behaviors.

This study underscores the importance of social media in consumer purchasing behavior. The findings also extend the literature related to commerce and product message design on social media platforms.

Employee gratitude is often associated with positive customer-related benefits. However, our understanding of employee gratitude is notably underdeveloped within the service literature. To address this issue, this study aims to position employee gratitude within the service profit chain (SPC) framework as a complementary mediator. Further, the authors empirically examine service climate as a central antecedent to employee gratitude and employee customer-oriented behavior as an outcome that triggers an internal and external reciprocal social exchange.

The examination of the research questions was done across two studies, using employee self-reported data (Study 1) and employee–customer dyadic data (Study 2). In Study 1, the authors investigate how employee gratitude mediates the relationship between service climate and customer-oriented behavior, with employee interpersonal influence functioning as a moderator. In Study 2, the authors examine how customer-oriented behavior, an outcome of Study 1, influences customer satisfaction and customer avoidance, with customer gratitude functioning as a mediator.

Results from both Study 1 and Study 2 support the proposed relationships. These studies contribute to the service literature by evaluating how and why employee gratitude functions as a significant factor in determining employee and customer behavior within the service context.

This work enriches the gratitude literature by empirically testing a novel theoretical perspective on employee and customer gratitude in service encounters. In doing so, the authors provide a more nuanced understanding of how internal and external processes are connected and potentially reinforced in SPC.

This study uses a systematic review to explore the potential causes of previous findings related to e-government acceptance research. By identifying the most frequently used, best, promising or worst factors that affect the acceptance of e-government, this research presents a research agenda for e-government researchers.

Through conducting a systematic review following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) procedure, this research first selected 109 papers. Subsequently, this research analyzed the predictors and linkages of e-government acceptance by adopting a weight-analysis method proposed by Jeyaraj et al. (2006).

The results first revealed the five most frequently used predictors and five best predictors of e-government acceptance at a comprehensive level. Furthermore, this study summarized the best predictors affecting the acceptance of e-government from the perspectives of adopter types and e-government stages. The results also illustrated the promising and the worst predictors influencing e-government acceptance.

The contribution of this research is twofold. First, this study identified the linkages between e-government acceptance at the individual and organizational levels and between different e-government development stages. Second, this research provided a research direction that could offer useful insights for future e-government studies.

This study examines how consumers' self-construal moderates consumers' buying behavior in situations requiring consumers to buy larger-than-expected clothing sizes. The authors explore the potential effectiveness of two distinct communication strategies – emotional versus informational ad appeals – to mitigate the negative effects of sizing discrepancies.

A total of three experiments were conducted to examine the proposed framework. Studies 1 and 2 investigate whether self-construal moderates the relationship between sizing discrepancy and purchasing intentions. Study 3 examines the effectiveness of communication strategies in reducing the detrimental effects of sizing discrepancy.

When encountering sizing discrepancies, the authors find that consumers with an interdependent self-construal have lower purchase intentions than those with an independent self-construal. The authors demonstrate that an emotional communication strategy is more effective for consumers with an interdependent self-construal, whereas an informational communication strategy is more effective for consumers with an independent self-construal.

With the lack of a universal sizing system, consumers often struggle to find clothes that fit as expected. However, extant research has not explored cross-cultural differences in how consumers respond to sizing discrepancies and how managers can reduce any potential negative effects.

This paper aims to investigate the influence of sinusoidal texture (ST) with different morphology parameters on the corresponding tribological effects.

The STs with different amplitudes, ranging from 0.05 to 0.3 mm, and frequencies, ranging from 5 to 17.5, are fabricated using nanosecond pulsed laser equipment. The friction experiments and the finite element analysis method are combined to investigate the tribological properties, under dry friction conditions.

Test results show that when the amplitude is 0.15 mm and frequency is 10, ST surface has the lowest friction coefficient of 0.373, and exhibits great anti-friction effect. It also possesses a complete texture edge after friction. The friction reduction effect of ST with larger or smaller amplitude and frequency is worse.

The results of this study can provide a guidance for the design optimization of ST of reciprocating sliding contact surfaces, under dry friction conditions.

Since institutions are typically conceptualized as “the rules of the game in a society” (North 1990: 3; Scott 1995), “institutional transitions” are defined as “fundamental and comprehensive changes introduced to the formal and informal rules of the game” (Peng 2003: 275). One of the most dramatic sets of institutional transitions in the last two decades has been the political, economic, and social changes sweeping across Central and Eastern Europe (CEE), the newly independent states (NIS) of the former Soviet Union, and the East Asian countries of China and Vietnam. In fact, these institutional transitions are so profound that these countries, formerly known as the Eastern bloc, have now been collectively labeled “transition economies.”

The purpose of this study is to explore the relationship between self-congruence and attendee engagement in explaining emotional attachment in the context of cultural events.

Structural equation modelling with partial least squares analysis has been applied. Data were collected from 421 respondents through an onsite survey during the Yi Peng and Loy Krathong festive week in Thailand.

The findings revealed that self-congruence (i.e. actual self-congruence and ideal self-congruence) has a positive influence on attendee engagement. When attendees' actual self and ideal self-match with the event image, they are more likely to actively engage in the event activities.

The findings offer insights into one type of events, the cultural event, which is a common event in Thailand. This study is also one among a handful works that investigates the moderating role of perceived crowding on the relationship between attendees' actual and ideal self-congruence and engagement with the event. Although the findings do not suggest a significant moderating effect, this study provides preliminary insight into how perceived crowding shapes the perception of tourists in a cultural event context.

The objective of this paper is to find an effective approach for enabling real estate firms to understand their competitiveness and identify the core competitiveness indicators (CCIs) that influence the development of developers with particular reference to the Chinese real estate business environment.

A combined method including Monte Carlo simulation (MCS) and the fuzzy set method was used to identify CCIs. Research data used for analysis were collected from a questionnaire survey in the Chinese real estate industry.

Analysis results suggest core indicators for assessing real estate developers' competitiveness include: good corporate brand awareness and sufficient resources for expansion, have access to a diverse range of capital, appropriate annual land reserve, excellent entrepreneurship, proper risk assessment and response capacity, and green development strategy.

The examination of the CCIs furnishes real estate firms with core indicators to assess their competitiveness, thus adopt appropriate strategies to enhance their competitiveness in the real estate market. The findings offer new insights and references for studying similar topics in other industries and countries.

The paper chooses an effective approach to identify the competitiveness indicators for real estate firms by using a combined method including MCS and the fuzzy set method.

The purpose of this paper is to define a new method (grey relational analysis (GRA)) for extracting pattern samples of dissolved gases in power transformer oil, then a hybrid algorithm of the back‐propagation (BP) network and fuzzy genetic algorithm‐artificial neural network (FGA‐ANN) is used to power transformer fault diagnosis based on extracted pattern samples.

The existing manners (e.g. international electro technical commission triple‐ratio method), in practice, have certain faultiness due to the ambiguity of the inference and insufficient standard for judgment. So GRA method is chosen to solve a problem of optimal pattern samples data, then a hybrid algorithm of the BP network and FGA‐ANN is developed to optimize initial weights and to enable fast convergence of the BP network, and lastly, this algorithm is applied to the classification of dissolved gas analysis (DGA) data and power transformer fault diagnosis.

If possible, the results should be accompanied by significance. For comparative studies, the proposed scheme does not require the three ratio code and high diagnosis accuracy is obtained. In addition, useful information is provided for future fault trends and multiple faults analysis.

Accessibility and availability of data are the main limitations which model will be applied.

This paper provides useful advice for power transformer fault diagnosis method based on DGA data.

The new method of optimal choice of options of pattern samples due to GRA. The paper is aimed at optimized samples data classified and abandons the traditional ratio method.