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Article
Publication date: 27 June 2019

Yen-Cheng Chen, Pei-ling Tsui, Ching-Sung Lee and Guan-lin Chen

This study used the colours of plates as atmospheric stimulus factors in the Mehrabian–Russell model of environmental influence, which served as the study’s basic background…

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Abstract

Purpose

This study used the colours of plates as atmospheric stimulus factors in the Mehrabian–Russell model of environmental influence, which served as the study’s basic background theory, to explore how plate colour affects consumer appetite preference and dining emotions in Chinese fine dining restaurants. The paper aims to discuss this issue.

Design/methodology/approach

The study used quantitative surveys and employed purposeful sampling and rolling snowball surveys of consumers in Chinese fine dining restaurants in Taipei; 581 effective surveys were collected from the test subjects. The research tools included a plate colour appetite preference scale and a dining emotion scale.

Findings

There were significant differences in age and gender in terms of appetite preference and plate colour. The plate colours with the highest appetite preference were gold, white and black. There were significant differences in plate colour appetite preference in terms of dining mood, with white and gold plates eliciting positive dining moods.

Originality/value

Most academic papers have focused on studying plates in Western dining, while very few studies have focused on the colour of Chinese dining plates. The greatest contribution and value of this study is its discovery of the colour combination of dining plates that can elicit appetite preferences and positive dining emotions among diners in Chinese fine dining restaurants. This information can be used to stimulate positive dining emotions among consumers and help restaurateurs improve the level of dining aesthetics.

Details

Asia Pacific Journal of Marketing and Logistics, vol. 32 no. 1
Type: Research Article
ISSN: 1355-5855

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Article
Publication date: 25 January 2013

Guan‐Lin Chen, Shu‐Chen Yang and Shung‐Ming Tang

The aim of this paper is to employ the perspectives of uses and gratification theory and experiential marketing to investigate the antecedents of virtual community (VC) members’…

3177

Abstract

Purpose

The aim of this paper is to employ the perspectives of uses and gratification theory and experiential marketing to investigate the antecedents of virtual community (VC) members’ attitude formation and knowledge‐contribution intention through the sense of virtual community (SOVC) and the interaction between their motivations and experiences in a peer‐to‐peer problem solving (P3) VC.

Design/methodology/approach

This study chose a well‐known professional IT VC in Taiwan, the ITHelp community, as the target for data collection. An online survey linked from the homepage of this community was used through the cooperation of the vendor of this community. This study employs the partial least squares (PLS) method to examine the research model.

Findings

The results show that members’ attitudes toward their VCs are determined by the interaction between their motivations for and experiences with P3 VC usages. Moreover, SOVC plays full mediating roles in the relationship between attitude toward P3 VC and knowledge‐contribution intention.

Research limitations/implications

VC managers need to aim at creating pleasant experiences for their members and foster their belongingness and consciousness to form higher SOVC. The conclusions are restricted to a VC that involves IT‐related issues, which focuses problem solving rather than being socially oriented. Members of IT P3 VCs are usually highly innovative and enthusiastic about new IT products, which is quite different from the membership of other P3 VCs.

Originality/value

Extant studies seldom considered the effects of SOVC and members’ experiences on knowledge‐contribution behavior. The mediating role of SOVC and the interaction between motivations and experience can enhance our understanding about online knowledge‐contribution behavior.

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Article
Publication date: 7 December 2020

Amir Zaib Abbasi, Muhammad Asif, Linda D. Hollebeek, Jamid Ul Islam, Ding Hooi Ting and Umair Rehman

This study aims to propose a model for predicting consumers’ esports videogame engagement on their ensuing consumption behaviors, which remains nebulous to date.

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Abstract

Purpose

This study aims to propose a model for predicting consumers’ esports videogame engagement on their ensuing consumption behaviors, which remains nebulous to date.

Design/methodology/approach

After approaching esports consumers in different gaming zones in Pakistan, this paper collected data from 364 videogame-based esports consumers. This paper deployed SmartPLS 3.2.8 software to perform the partial least squares-structural equation modeling-based analyzes.

Findings

The structural model results show that consumers’ affective and behavioral esports videogame engagement positively affects their consumption behavior, including heightened community engagement, purchase intent, coproduction, word-of-mouth and new player recruitment. However, while consumers’ cognitive esports engagement was found to positively impact community engagement, new player recruitment and coproduction, it failed to predict consumers’ esports-related purchase intent or word-of-mouth behaviors.

Practical implications

The findings reveal that a strategic focus on consumers’ esports game engagement will enable practitioners to nurture desirable consumer behaviors, including enhanced purchase intent, coproduction, word-of-mouth and new player recruitment behaviors, thus warranting consumer engagement’s strategic value as a key esports gaming metric.

Originality/value

Empirical research into the role of consumers’ esports videogame engagement on their ensuing consumption behaviors remains scant to date. Based on this gap, this study offers a timely contribution by exploring and validating a model that gauges the effect of consumers’ cognitive, emotional and behavioral esports videogame engagement on their community engagement, purchase intention, coproduction, word-of-mouth and new player recruitment. It, thus, offers important insight into the rapidly advancing field of digital esports games.

Details

Journal of Product & Brand Management, vol. 30 no. 8
Type: Research Article
ISSN: 1061-0421

Keywords

Available. Open Access. Open Access
Article
Publication date: 17 May 2023

Amir Zaib Abbasi, Muhammad Asif, Amjad Shamim, Ding Hooi Ting and Raouf Ahmad Rather

The purpose of this study is to present a conceptual model where consumer electronic sports (eSports) engagement (CeSE) acts a predictor for gamers’ online engagement in…

6589

Abstract

Purpose

The purpose of this study is to present a conceptual model where consumer electronic sports (eSports) engagement (CeSE) acts a predictor for gamers’ online engagement in eSports-related products/firm either through direct contribution (purchase intention) or indirect contribution (co-production, community engagement, word-of-mouth and recruitment).

Design/methodology/approach

Data from 262 eSports consumers aged 18–24 years were collected and analyzed through WarpPLS 8.0.

Findings

The findings of this study confirm that CeSE significantly influences all dimensions of the consumption behaviors (purchase intention, co-production, community engagement, word-of-mouth and recruitment).

Originality/value

This study provides empirical support for a conceptual framework developed through the social exchange theory and engagement theory. Besides, hierarchical component model approach is applied to estimate the composite model of CeSE.

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Article
Publication date: 10 December 2024

Abdellatif Selmi and Ali Raza

The aim of the current study is to recommend and compare the estimates of finite element model (FEM), analytical model, and artificial neural networks (ANN) model for capturing…

8

Abstract

Purpose

The aim of the current study is to recommend and compare the estimates of finite element model (FEM), analytical model, and artificial neural networks (ANN) model for capturing the LCC of FCSC members. A database comprising 325 FCSC columns was constructed from previous studies to propose FEM and ANN models while the analytical model was proposed based on a database of 712 samples and encasing mechanics of steel tube and FRP wraps. The concrete damage plastic model was used for concrete along with bilinear and linear elastic models for steel tube and FRP wraps, respectively. Analytical and ANN models effectively considered the lateral encasing mechanism of FCSC columns for accurate predictions.

Design/methodology/approach

The study aimed to compare the prediction accuracy of finite element (FEM), analytical, and artificial neural network (ANN) models for the load-carrying capacity (LCC) of fiber reinforced polymer (FRP)-encased concrete-filled steel tube (CFST) compression members (FCSC). A database of 325 FCSC columns was developed for FEM and ANN models, while the analytical model was based on 712 samples, utilizing encasing mechanics of steel tube and FRP wraps. FEM used a concrete damage plastic model, bilinear steel tube, and linear elastic FRP models. Statistical accuracy was evaluated using MAE, MAPE, R², RMSE, and a 20-index across all models.

Findings

Based on the experimental database, the FEM presented the accuracies in the form of statistical parameters MAE = 223.76, MAPE = 285.32, R2 = 0.94, RMSE = 210.43 and a20-index = 0.83. The analytical model showed the statistics of MAE = 427.229, MAPE = 283.649, R2 = 0.8149, RMSE = 275.428 and a20-index = 0.73 while ANN models portrayed the predictions with MAE = 195, MAPE = 229.67, R2 = 0.981, RMSE = 174 and a20-index = 0.89 for the LCC of FCSC columns.

Originality/value

Although various investigations have already been performed on the prediction of the load-carrying capacity (LCC) of fiber reinforced polymer (FRP)-encased concrete-filled steel tube (CFST) compression members (FCSC) using small and noisy data, none of them compared the accuracy of prediction of different modeling techniques based on a refined large database.

Details

Multidiscipline Modeling in Materials and Structures, vol. 21 no. 2
Type: Research Article
ISSN: 1573-6105

Keywords

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