Customer Engagement With Online Restaurant Community During COVID-19–Model Inventory

Abstract

The Customer Engagement With Online Restaurant Community During COVID-19–Model (Liu et al., 2023) was developed for a study exploring how mutual disclosures between servers and customers impact customers’ social influence and knowledge-sharing engagement, mediated by customer trust and swift guanxi. This model is grounded in social penetration theory and social exchange theory. The proposed items were adapted from previous research (i.e., Hwang et al., 2015; Fu et al., 2022; Lin et al., 2018; Li et al., 2021). The study was conducted in China with Chinese subjects, and a rigorous translation and back-translation process was employed (Brislin, 1980). The measure was evaluated using structural equation modeling and confirmatory factor analysis and administered to a sample of consumers. The study reported on the reliability and validity of the measure.

Keywords
Server Disclosure; Customer Disclosure; Customer Trust; Swift Guanxi; Customers’ Social Influence Engagement; Customers’ Knowledge-Sharing Engagement; COVID-19 Pandemic; Customer Engagement; Online Restaurant Community; Social Penetration Theory; Social Exchange Theory

Authors
Liu, Min; Xu, Jie; Li, Shuhao; Wei, Min

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Purpose

The purpose of this measurement model is to assess customer engagement with an online restaurant community during the COVID-19 pandemic.

Validity

Convergent and Discriminant Validity: The factor loadings of all items were statistically significant at the 0.001 level and exceeded the threshold of 0.60 (Anderson & Gerbing, 1988). Furthermore, most of the Average Variance Extracted (AVE) values were above 0.5, indicating satisfactory convergent validity (Fornell & Larcker, 1981; Lam, 2012). Additionally, the correlation coefficients between the constructs were lower than the squared root of the AVEs of the related variables, suggesting satisfactory discriminant validity (Fornell & Larcker, 1981).

Reliability

Internal Consistency: The internal consistency of the constructs, as measured by Cronbach’s alpha and Composite Reliability (CR) values, ranged from 0.670 to 0.924 and 0.762 to 0.938, respectively.

Factor Analysis

Common Method Variance: Harman’s single-factor method was utilized to assess common method variance using SPSS 26.0. The results revealed six factors with eigenvalues greater than 1. The first factor explained 40.3% of the total variance, indicating that common method variance was not a significant concern (Podsakoff et al., 2003).

Confirmatory Factor Analysis: The goodness-of-fit indices (χ2 = 528.682, df = 215, χ2/df = 2.459, GFI = 0.869, NFI = 0.893, IFI = 0.934, TLI = 0.921, CFI = 0.933, RMSEA = 0.066, RMR = 0.114) demonstrated a good model fit (Hu & Bentler, 1999).

Instrument: Customer Engagement With Online Restaurant Community During COVID-19–Model

Test Type: Original
Format: Items are rated using a seven-point Likert scale.
Language Available: Chinese
Population Group: Human; Male; Female
Age Group: Adulthood (18 yrs & older); Young Adulthood (18-29 yrs); Thirties (30-39 yrs); Middle Age (40-64 yrs)
Population Details: Location: China, Respondents: Consumers
Test Methodology: Test Validity; Convergent Validity; Discriminant Validity; Test Reliability; Internal Consistency; Factor Analysis; Confirmatory Factor Analysis; Measurement Model; Structural Equation Modeling

Keywords

Customer Engagement; COVID-19; Online Restaurant Community

Authors

Author ORCID Identifier:
Liu, Min: http://orcid.org/0000-0002-5696-5405
Xu, Jie: http://orcid.org/0000-0002-1964-0820
Wei, Min: http://orcid.org/0000-0002-8441-4600

Affiliation:
Liu, Min: Xiamen University School of Management
Xu, Jie: Xiamen University School of Management
Li, Shuhao: Qingdao University School of Tourism and Geography Science
Wei, Min: Xiamen University School of Management

Email Addresses:
Liu, Min: [email protected]
Xu, Jie: [email protected]
Li, Shuhao: [email protected]
Wei, Min: [email protected]

Correspondence Address:
Xu, Jie: Xiamen University, School of Management, 422 South Siming Road, Xiamen, China, 361005, [email protected]

Permissions & Fee and Test Year

Permissions: May use for Research/Teaching
Commercial: No
Fee: No
Test Year: 2023

References

Liu, M., Xu, J., Li, S., & Wei, M. (2023). Engaging customers with online restaurant community through mutual disclosure amid the COVID-19 pandemic: The roles of customer trust and swift guanxi. Journal of Hospitality and Tourism Management, 56, 124–134. https://doi.org/10.1016/j.jhtm.2023.06.019

Items of the Customer Engagement With Online Restaurant Community During COVID-19–Model

This is a 25-item measure. The constructs assessed include Server disclosure; Customer disclosure; Customer trust; Swift guanxi; Customers’ social influence engagement; Customers’ knowledge-sharing engagement. Specific items are available in the source reference: Liu, M., Xu, J., Li, S., & Wei, M. (2023). Engaging customers with online restaurant community through mutual disclosure amid the COVID-19 pandemic: The roles of customer trust and swift guanxi. Journal of Hospitality and Tourism Management, 56, 124–134. https://doi.org/10.1016/j.jhtm.2023.06.019, specifically in Table 2, Page 129.

Server disclosure

• When (If) there are mistakes during the services delivery process, the employee of this restaurant tells (would tell) me in the WeChat Group.

• The employee of this restaurant tells me about his/her personal opinion (e.g., food taste, food price, portion size) in the WeChat Group.

• The employee of this restaurant gives appropriate advice to my menu choice in the WeChat Group.

• The employee of this restaurant shares food information with me in the WeChat Group.

Customer disclosure

• I express thanks to the employee of this restaurant for his/her services on the WeChat Group.

• I tell the employee of this restaurant about my preference (e.g., food taste, food price, portion size) on the WeChat Group.

• I tell the employee of this restaurant that I am a regular customer of this restaurant on the WeChat Group.

• I share personal information with the employee of this restaurant (e.g., food allergy, vegetarian) in the WeChat Group.

Customer trust

• I think the employee of this restaurant is reliable.

• I have confidence in the employee of this restaurant.

• The employee of this restaurant is trustworthy.

• I think the employee of this restaurant has high integrity.

Swift guanxi

• The employee of this restaurant in the WeChat Group and I can understand each other.

• The employee of this restaurant in the WeChat Group and I treat each other as we treat our friends.

• The employee of this restaurant in the WeChat Group and I have harmonious relationships.

Customers’ social influence engagement

• I will talk about my positive experience at this restaurant with others.

• I will discuss the benefits that I get from this restaurant with others.

• I will actively mention this restaurant in my conversations.

• I will actively discuss this restaurant on different media platforms.

Customers’ knowledge-sharing engagement

• I am willing to provide feedback about my experience with this restaurant.

• I am willing to provide suggestions for improving the performance of the restaurant’s products/services.

• I am willing to provide suggestions/feedback about the new product/services to this restaurant.

• I am willing to provide feedback/suggestions for developing new products/services for this restaurant.

Note. Items are rated using a 7-point Likert scale (1 = extremely disagree; 7 = extremely agree).