Search results

1 – 8 of 8
Per page
102050
Citations:
Loading...
Access Restricted. View access options
Article
Publication date: 28 September 2023

Depeng Zhang, Zhongxiang Li and Jiaxin Ma

Managing the growing word-of-mouth (WOM) of brand fans has become a new challenge for companies in the fan economy era. The purpose of this paper is to examine the effect of…

402

Abstract

Purpose

Managing the growing word-of-mouth (WOM) of brand fans has become a new challenge for companies in the fan economy era. The purpose of this paper is to examine the effect of language intensity of brand fan WOM on customers' willingness to adopt WOM based on psychological resistance theory and to reveal the underlying mechanism of this process.

Design/methodology/approach

A research model was developed to test the proposed hypotheses. Two experiments were conducted on an online platform using data from 708 participants. The independent samples t-test and analysis of variance were used to analyze the data.

Findings

The results show that, in the context of WOM among brand fans, high-intensity language leads to a lower willingness to adopt than low-intensity language and threats to freedom mediate this effect. Moreover, the restoration postscript moderates the effect of language intensity on threats to freedom and customers' willingness to adopt WOM.

Originality/value

Unlike previous studies that focused on electronic word-of-mouth (eWOM) language content, this paper focuses on language intensity to reveal the psychological process of customers' willingness to adopt brand fan WOM. The findings not only enrich the research related to the language effect in eWOM, but also deepen the understanding of the influence effect on brand fan WOM, providing effective guidance for brands to manage fan WOM.

Details

Asia Pacific Journal of Marketing and Logistics, vol. 36 no. 3
Type: Research Article
ISSN: 1355-5855

Keywords

Access Restricted. View access options
Article
Publication date: 18 November 2024

Shangjie Feng, Buqing Cao, Ziming Xie, Zhongxiang Fu, Zhenlian Peng and Guosheng Kang

With the continuous increase in Web services, efficient identification of Web services that meet developers’ needs and understanding their relationships remains a challenge…

19

Abstract

Purpose

With the continuous increase in Web services, efficient identification of Web services that meet developers’ needs and understanding their relationships remains a challenge. Previous research has improved recommendation effectiveness by using correlations between Web services through graph neural networks (GNNs), while it has not fully leveraged service descriptions, limiting the depth and diversity of learning. To this end, a Web services recommendation method called LLMSARec, based on Large Language Model and semantic alignment, is proposed. This study aims to extract potential semantic information from services and learn deeper relationships between services.

Design/methodology/approach

This method consists of two core modules: profile generation and maximizing mutual information. The profile generation module uses LLM to analyze the descriptions of services, infer and construct service profiles. Concurrently, it uses LLM as text encoders to encode inferred service profiles for enhanced service representation learning. The maximizing mutual information model aims to align the semantic features of the services text inferred by LLM with structural semantic features of the services captured by GNNs, thus achieving a more comprehensive representation of services. The aligned representation serves as an input for the model to identify services with superior matching accuracy, thereby enhancing the service recommendation capability.

Findings

Experimental comparisons and analyses were conducted on the Programmable Web platform data set, and the results demonstrated that the effectiveness of Web service recommendations can be significantly improved by using LLMSARec.

Originality/value

In this study, the authors propose a Web service recommendation approach based on Large Language Model and semantic alignment. By extracting latent semantic information from services and effectively aligning semantic features with structural features, new representations can be generated to significantly enhance recommendation accuracy.

Details

International Journal of Web Information Systems, vol. 21 no. 1
Type: Research Article
ISSN: 1744-0084

Keywords

Available. Open Access. Open Access
Article
Publication date: 11 March 2020

Kun Wang, Weihua Zhang, Zhongxiang Feng and Cheng Wang

The purpose of this paper is to perform fine classification of road traffic visibility based on the characteristics of driving behavior under different visibility conditions.

1938

Abstract

Purpose

The purpose of this paper is to perform fine classification of road traffic visibility based on the characteristics of driving behavior under different visibility conditions.

Design/methodology/approach

A driving simulator experiment was conducted to collect data of speed and lane position. ANOVA was used to explore the difference in driving behavior under different visibility conditions.

Findings

The results show that only average speed is significantly different under different visibility conditions. With the visibility reducing, the average vehicle speed decreases. The road visibility conditions in a straight segment can be divided into five levels: less than 20, 20-30, 35-60, 60-140 and more than 140 m. The road visibility conditions in a curve segment can be also divided into four levels: less than 20, 20-30, 35-60 and more than 60 m.

Originality/value

A fine classification of road traffic visibility has been performed, and these classifications help to establish more accurate control measures to ensure road traffic safety under low-visibility conditions.

Details

Journal of Intelligent and Connected Vehicles, vol. 3 no. 1
Type: Research Article
ISSN: 2399-9802

Keywords

Access Restricted. View access options
Book part
Publication date: 13 March 2012

MaryJo Benton Lee, Li Hong and Luo Lihui

A strong relationship exists in many cultures between ethnic identity and educational success. This study was conducted at a teacher training university in Southwest China in…

Abstract

A strong relationship exists in many cultures between ethnic identity and educational success. This study was conducted at a teacher training university in Southwest China in 1997. It examines how ethnic minority students, through a series of micro-level interactions, construct “scholar selves” within their families, villages, and schools. The study also looks at how macro-level structural supports, built into the Chinese education system, help minority students overcome obstacles to academic success. These supports include special schools and classes for ethnic students, training teachers for nationality areas, financial support for minority education and additional points awarded on national examinations. The chapter suggests what scholars and practitioners might learn from an educational system that demonstrates the characteristics of flexibility, inclusiveness and cohesiveness.

Details

As the World Turns: Implications of Global Shifts in Higher Education for Theory, Research and Practice
Type: Book
ISBN: 978-1-78052-641-6

Keywords

Access Restricted. View access options
Article
Publication date: 17 October 2024

Zhongxiang Fu, Buqing Cao, Shanpeng Liu, Qian Peng, Zhenlian Peng, Min Shi and Shangli Liu

With the exponential growth of mobile applications, recommending suitable mobile applications to users becomes a critical challenge. Although existing methods have made…

24

Abstract

Purpose

With the exponential growth of mobile applications, recommending suitable mobile applications to users becomes a critical challenge. Although existing methods have made achievements in mobile application recommendation by leveraging graph convolutional networks (GCNs), they suffer from two limitations: the reliance on a singular acquisition path leads to signal sparsity, and the neighborhood aggregation method exacerbates the adverse impact of noisy interactions. This paper aims to propose SMAR, a self-supervised mobile application recommendation approach based on GCN, which is designed to overcome existing challenges by using self-supervised learning to create an auxiliary task.

Design/methodology/approach

In detail, this method uses three distinct data augmentation techniques node dropout, edge dropout and random walk, which create varied perspectives of each node. Then compares these perspectives, aiming to ensure uniformity across different views of the same node while maintaining the differences between separate nodes. Ultimately, auxiliary task is combined with the primary supervised task using a multi-task learning framework, thereby refining the overall mobile application recommendation process.

Findings

Extensive experiments on two real datasets demonstrate that SMAR achieves better Recall and NDCG performances than other strong baselines, validating the effectiveness of the proposed method.

Originality/value

In this paper, the authors introduce self-supervised learning into mobile application recommendation approach based on GCNs. This method enhances traditional supervised tasks by using auxiliary task to provide additional information, thereby improving signal accuracy and reducing the influence of noisy interactions in mobile application recommendations.

Details

International Journal of Web Information Systems, vol. 20 no. 5
Type: Research Article
ISSN: 1744-0084

Keywords

Access Restricted. View access options
Article
Publication date: 2 June 2020

Zhongxiang Zhou, Liang Ji, Rong Xiong and Yue Wang

In robot programming by demonstration (PbD) of small parts assembly tasks, the accuracy of parts poses estimated by vision-based techniques in demonstration stage is far from…

240

Abstract

Purpose

In robot programming by demonstration (PbD) of small parts assembly tasks, the accuracy of parts poses estimated by vision-based techniques in demonstration stage is far from enough to ensure a successful execution. This paper aims to develop an inference method to improve the accuracy of poses and assembly relations between parts by integrating visual observation with computer-aided design (CAD) model.

Design/methodology/approach

In this paper, the authors propose a spatial information inference method called probabilistic assembly graph with optional CAD model, shorted as PAGC*, to achieve this task. Then an assembly relation extraction method from CAD model is designed, where different assembly relation descriptions in CAD model are summarized into two fundamental relations that are colinear and coplanar. The relation similarity, distance similarity and rotation similarity are adopted as the similar part matching criterions between the CAD model and the observation. The knowledge of part in CAD is used to correct that of the corresponding part in observation. The likelihood maximization estimation is used to infer the accurate poses and assembly relations based on the probabilistic assembly graph.

Findings

In the experiments, both simulated data and real-world data are applied to evaluate the performance of the PAGC* model. The experimental results show the superiority of PAGC* in accuracy compared with assembly graph (AG) and probabilistic assembly graph without CAD model (PAG).

Originality/value

The paper provides a new approach to get the accurate pose of each part in demonstration stage of the robot PbD system. By integrating information from visual observation with prior knowledge from CAD model, PAGC* ensures the success in execution stage of the PbD system.

Details

Assembly Automation, vol. 40 no. 5
Type: Research Article
ISSN: 0144-5154

Keywords

Access Restricted. View access options
Article
Publication date: 1 October 2024

Kehinde Peter Alabi, Ayoola Patrick Olalusi, John Isa, Kehinde Folake Jaiyeoba and Michael Mayokun Odewole

Fresh fruits and vegetables (FV) are crucial global food resources, but the presence of heat loads during harvest adversely impacts their shelf life. While freezing technology…

20

Abstract

Purpose

Fresh fruits and vegetables (FV) are crucial global food resources, but the presence of heat loads during harvest adversely impacts their shelf life. While freezing technology provides an effective means of removing heat loads, it is an energy-intensive process and may consequently prove too costly for practical business viability. The growing interest in utilizing magnetic field (MF) technology during the freezing of fresh FV enhances the freezing rate and rapidly removes the heat loads of products.

Design/methodology/approach

In the present study, pulsed magnetic field (PMF) pretreatment employing specific field strengths (9 T, 14 T and 20 T) was examined as a preliminary step before freezing mango and tomato and compared to the conventional freezing method (untreated) at − 18 °C.

Findings

PMF pretreatment prior to freezing demonstrated a noteworthy enhancement in freezing rate by around 10 and 12% when compared with the conventional (untreated) freezing, which exhibited freezing rates of −0.08 °C/min and −1.10 °C/min for mango and tomato, respectively. The PMF pretreatment (at 20 T) provided a higher freezing rate (at p = 0.05) than the conventional freezing method reduced heat loads amounting to 1.1 × 107 J/kg oC and 2.9 × 106 J/kg oC, significantly (at p = 0.05) from mango and tomato, respectively. These reductions in heat loads were approximately more than 5% of the calculated heat loads removed during conventional freezing.

Research limitations/implications

Mango and tomato samples were only tested; the results may lack generalizability. Therefore, researchers are encouraged to test for other products for further studies.

Practical implications

The paper includes implications for the development of a rapid freezing technique, the development of “pulsed magnetic field” and for eliminating the problem associated with conventional (slow) freezing.

Originality/value

The study holds significance for the production of postharvest freezing technology, providing insightful information on the PMF-assisted freezing of cellular foods.

Details

British Food Journal, vol. 126 no. 12
Type: Research Article
ISSN: 0007-070X

Keywords

Access Restricted. View access options
Article
Publication date: 7 August 2009

Sifeng Liu, Jeffrey Forrest and Robert Vallee

The purpose of this paper is to present the scientific background from which grey systems theory came into being, the astonishing progress that grey systems theory has made in the…

1189

Abstract

Purpose

The purpose of this paper is to present the scientific background from which grey systems theory came into being, the astonishing progress that grey systems theory has made in the world of learning and its wide‐ranging applications in the entire spectrum of science.

Design/methodology/approach

The grey uncertainty is compared with other kinds of uncertainty such as stochastic uncertainty, unascertainty, fuzzy and rough uncertainty.

Findings

The advances in grey systems theory and its various successful applications are introduced individually by algorithms of grey numbers and grey algebraic systems, grey dynamic models and grey predictions, grey optimization analysis for decision making, grey control models.

Research limitations/implications

Many scientific theories require the unremitting efforts of several generations of people and have gone through hundreds of years before reaching maturity and perfection. Grey systems theory is still in its growth period. So, it is unavoidable that there exist immature and imperfect parts in the theory.

Originality/value

Grey systems theory is a new method for studying problems of uncertainty with few data points and poor information. This new theory studies small samples and systems with poor information, which have partial information known, partial information unknown. It describes adequately and monitors effectively systems' operations and evolutions through extracting valuable information from the little known information. Grey systems theory comes into being along with the development of modern systems science and uncertainty systems theories and methods. It is also a result of deepened perceptivity about uncertain systems.

Details

Kybernetes, vol. 38 no. 7/8
Type: Research Article
ISSN: 0368-492X

Keywords

1 – 8 of 8
Per page
102050