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Article

The Resilience Capabilities of Yumcha Restaurants in Shaping the Sustainability of Yumcha Culture

School of Tourism Management, Sun Yat-sen University, Guangzhou 510275, China
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Author to whom correspondence should be addressed.
Sustainability 2018, 10(9), 3304; https://doi.org/10.3390/su10093304
Submission received: 21 August 2018 / Revised: 7 September 2018 / Accepted: 13 September 2018 / Published: 15 September 2018
(This article belongs to the Section Tourism, Culture, and Heritage)

Abstract

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This study investigates the sustainability of food heritage in the modern world. The city of Guangzhou in Guangdong province has quickly changed to become a large metropolis within 40 years after China’s opening policy. Using Guangzhou’s Yumcha heritage as the case, we propose that Yumcha restaurants’ resilience has enhanced Yumcha heritage sustainability, and their dynamic capabilities have had a positive influence on both Yumcha restaurants’ resilience and the sustainability of Yumcha heritage. The study focuses on (1) the influence of social–cultural changes on the sustainability of Yumcha culture, (2) the influence of restaurant dynamic capabilities on Yumcha heritage sustainability, (3) Yumcha restaurants’ resilience-mediating effect, and (4) the moderating effects of social-cultural changes. The findings contribute to our understanding from four aspects: (1) Social–cultural changes negatively impact on Yumcha heritage; (2) the dynamic capability of Yumcha restaurants has a direct positive impact on Yumcha heritage; (3) the dynamic capabilities of Yumcha restaurants and social–cultural changes enable Yumcha heritage to become more resilient and improve the sustainability of Yumcha heritage; and (4) social–cultural changes moderate the indirect effects of proactive behavior on Yumcha heritage sustainability via Yumcha restaurant resilience.

1. Introduction

This article explores the social and cultural factors that may affect local food heritage and how local food heritage copes with these changes and becomes more resilient. In an era of globalization, urbanization, and mobility [1], local and traditional culture faces multiple shocks caused by social and cultural changes [2]. How to protect local cultural heritage in the modern world is a major challenge [3]. Food represents a kind of cultural heritage. Food is not only associated with providing physical nutrition for humans, but it is also a marker of local culture [4,5,6,7,8].
Disruptions from the modern world to food heritage are enormous [3]. Why and how are some food heritages reserved, thriving, and emerging as more sustainable? This study uses Yumcha (饮茶) heritage as an example to examine how local heritage can be conserved sustainably and how it becomes resilient in the fast-changing modern world. Yumcha, of which the literal translation is ‘drinking tea’, originated in the Qing Dynasty. In this practice, people not only drink tea but also eat dim sum [9]. In 2007, Yumcha culture was designated as one of the intangible cultural heritages of Guangzhou [10]. Although experiencing many challenges and strikes, Yumcha is still popular in Guangdong province and surrounding regions, such as Guangxi province and Hong Kong [11]. Thus, Yumcha is a good example to illustrate the resilience of food heritage.
Several scholars have studied the sustainability of local cultural heritage. Related studies have mainly focused on general cultural heritage [3]. Main research topics involve the demand side, such as food-consumption changes and consumers’ value changes [3]. However, enterprises, as the main carriers of local heritage, are seldom investigated. Specifically, in the food-heritage context, restaurants have considerable influence on the survival of food heritage.
From an enterprise perspective, the question remains on how food heritage can become resilient in encounters with different types of disruptions in modern cities. Little research has explored the sustainability of local food heritage from restaurant studies, with some exceptions. For example, Larsson et al. investigated the resilience of a nonprofit firm in promoting a local food system [12]. Research on restaurants has focused more on restaurant innovation [13]. Some studies have explored the paradox between authenticity and standardization of restaurants [14]. There is always a tension between commodification and heritage preservation [15]. Business and commercialization are usually thought of as causing negative effects on the authenticity of cultural heritage [16,17]. However, the positive effects of the resilience of restaurants in building sustainable food heritage when facing disruptions and opportunities in the modern world have not been examined. This study attempts to prove that successful businesses could also contribute to the sustainable development of cultural heritage.
When referring to enterprise resilience, recent research has paid more attention to the dynamic capabilities of enterprises [18]. Dynamic capabilities are a firm’s high-level capabilities. However, it is complicated to reveal the relationship between resilience and dynamic capabilities. Specifically, in the context of local food-heritage sustainability, which kind of dynamic capabilities enhance restaurant resilience and, thus, food-heritage sustainability, and how?
This paper empirically analyzes the sustainability of Yumcha heritage when facing disruptions and opportunities in a changing social–cultural metropolitan city. Based on resilience theory, following a dynamic-capabilities perspective [19], this study tries to reveal how specific dynamic capabilities, such as restaurant innovation and disruption orientation, influence Yumcha restaurants’ resilience and, in turn, the sustainability of Yumcha heritage.

2. Literature Review

In this study, we postulate that a Yumcha restaurant with high dynamic capacity enhances its resilience to disruptions and, in turn, enhances the sustainable conservation of Yumcha culture. The level of disruption the firm faces may moderate this effect. The conceptual model is illustrated in Figure 1.

2.1. Restaurant Resilience and Local Food-Heritage Sustainability

Sustainable development is defined as “development that meets the needs of the present without compromising the ability of future generations to meet their own needs” [20] (p. 43). Throsby revealed that cultural sustainability includes the preservation of cultural valuations and cultural activities for the next generations [21]. The sustainability of food heritage should be based on the protection of dining activities and food cultural valuations.
The sustainability of cultural heritage relates closely to its instrumental value as a driver in developing the economy, creating jobs, and eliminating poverty [22,23]. The development of Yumcha restaurants plays a crucial role in the preservation of Yumcha food heritage. In a world full of change and uncertainty, only when restaurants are resilient can they keep providing Yumcha services and promoting the values behind the activity.
Recent studies of resilience have shifted from exploring ecological resilience to investigating social resilience [24,25], including firm resilience. Roundy, Brockman, and Bradshaw defined firm resilience as a firm’s capability to recover from and adapt to shocks and disruptions [26]. Within the context of Yumcha culture, we focused on restaurants where customers can enjoy the Yumcha experience. The Yumcha experience is complex. People drink tea, eat dim sum, chat with others, and communicate with employees. Traditionally, people can drink tea and eat dim sum from morning until night. However, in modern times, the culture has shrunk to some degree; today, only the practice of drinking “morning tea” exists widely. In fact, many restaurants in Guangzhou only provide morning-tea services. Thus, this article focuses on morning-tea restaurants to explore the strikes to and the resilience of local food heritage. We define restaurant resilience as the general morning-tea restaurant’s ability to be flexible, bear pressure, and recover from and adapt to shocks and disruptions. Thus, we hypothesize:
Hypothesis 1 (H1).
Yumcha restaurant resilience positively affects the sustainability of Yumcha culture.

2.2. Dynamic Capability

Dynamic capability has only recently been developed as a perspective from which to view resilience [27]. Van de Vegt et al. noted that “to identify the capabilities of the system, and to understand how they communicate with others and with their environment, is important to understand a system’s resilience and to predict key performance outcomes” [27] (p. 973). Dynamic capabilities are essential to a system’s (within this food-heritage context, the morning-tea restaurant) adaptation process and therefore the sustainability of Yumcha culture. Thus, we can assume that dynamic capabilities positively affect Yumcha restaurants’ resilience, dynamic capabilities have a positive impact on the sustainability of Yumcha culture, and dynamic capabilities have an indirect positive effect on Yumcha heritage sustainability via Yumcha restaurant resilience.
Dynamic capability refers to that firm that has the capacity to “integrate, build, and reconfigure internal and external competences to address rapidly changing environments” [19] (p. 516). Dynamic capabilities have many characteristics: (1) generate organizational learning, (2) produce new incorporations of assets, and (2) update operational (or ordinary) capabilities [28,29].
As dynamic-capability research is quite new, researchers have explored the meaning of dynamic capability from diverse perspectives. Based on the characteristics of capacity, dynamic capacities include three dimensions: sensing, seizing, and reconfiguring [30]. Based on the characteristics of response behavior, Parker and Ameen explored dynamic capacities from the following aspects: disruption orientation, investment in risk-prevention infrastructure, resource reconfiguration, and proactive risk management [18]. The context of the Yumcha restaurant is relatively narrow and concrete. The dynamic capacities for a restaurant to survive in a changing social–cultural world include two dimensions, uncertainty orientation and proactive behavior.

2.2.1. Uncertainty Orientation

Uncertainty orientation helps to enhance firms’ ability to identify disruptions and opportunities. It serves as a kind of sensing capability [30], monitoring external social–cultural changes, interpreting the potential impact, and searching for and identifying market opportunities. Research has explored disruption orientation to immediate shocks.
Disruption orientation refers to “when the business environment is full of uncertainty, a firm’s general consciousness and awareness of, concerns about, seriousness toward, and recognition of the opportunity to learn from a broader range of disruptions” [18] (p. 873). Within the Yumcha context, disruption may refer not only to immediate shocks but also to gradual social–cultural changes [25]. The concept of uncertainty orientation measures an adaptation to a broader range of uncertainty, including both disruption and opportunities that affect the firm. It is more possible for firms with an uncertainty orientation to become resilient during disruptions. Thus, we suggest:
Hypothesis 2 (H2a).
Uncertainty orientation has a positive relationship with resilience.
Hypothesis 2 (H2b).
Uncertainty orientation has a positive relationship with sustainability of Yumcha culture.

2.2.2. Proactive Behavior

After identifying disruptions and opportunities, firms need to implement proactive behaviors to respond to disruptions and to seize opportunities. Proactive behavior measures a firm’s actions to create value from external opportunities, make new strategies, and adjust business models and value chains [31]. Proactive behaviors also refer to behaviors to orchestrate firms’ asset base, process innovative valuable combinations, and learn to build creative capabilities [30]. Within this study’s context, proactive behavior is defined as the behavior to reconfigure resources in response to uncertainties. Active Yumcha restaurants would need to constantly be vigilant with regards to external social–cultural changes, and respond actively to potential disruptions and opportunities, seizing the time and resources to learn and to accumulate knowledge from past experience and grabbing opportunities [18]. Thus, we give the following hypotheses:
Hypothesis 3 (H3a).
Proactive behavior has a positive relationship with resilience.
Hypothesis 3 (H3b).
Proactive behavior has a positive relationship with the sustainability of Yumcha culture.
Proactive behaviors in the restaurant industry mainly stem from innovation, including product innovativeness, service innovativeness, technological innovation, environmental innovation, and experiential innovativeness [13].
Product innovativeness has two meanings: (1) to provide new offerings, different from previous ones [32,33], and (2) to provide new perceptions of value, utility, and meaning for an old offering among consumers [34]. In the food-service industry, product innovativeness includes adding new items to the menu [35]. Specifically, when faced with rapid changes in consumer taste, improving the taste and diversity of dim sum may help Yumcha restaurants attract more consumers.
Service innovativeness is described as performance-enhancement activities that offer a creative benefit or sufficient appeal. Service innovativeness would intensely influence consumers’ and competing companies’ behavior [36]. Service innovativeness includes new technology in the services’ delivering processes [37]. In a Yumcha restaurant, new technology, such as an app for ordering from the menu or online ordering tools, can be integrated into customers’ dining experience and help enhance the delivery process.
Experiential innovativeness is defined as the behaviors to create a customized and personalized experience for customers [38]. First, experiential innovativeness includes a creative or fantasy environment and circumstances in which consumers can engage [39,40]. Providing communal tables encourages a social interactive atmosphere. Traditionally, the Yumcha restaurant is a place for customers to chat. Recently, Yumcha restaurants have begun to design the restaurant’s atmosphere and add cultural elements to its environment. Second, experiential innovativeness in the hospitality industry focuses on employee–customer interactions [41], a typically people-oriented sector. Yumcha restaurants generally encourage their employees to interact with customers.
Promotion is a firm’s marketing method to introduce its products and services to targeted customers [42]. Promotional methods can be creative, such as using digital, mobile, and social media in marketing communications [43,44], creating a new product mix and new ways of giving discounts and gifts [45]. In a Yumcha restaurant, promotional innovation includes various rewards (membership programs), innovative marketing, and advertising strategies. In general restaurants, providing Yumcha products in the morning has become a method of promotion.

2.3. Impact of Globalization

The tension between globalization and localization results in rapid sociocultural changes and shocks to local food heritage, and the prospective impact of disruptions may stir restaurants’ motivation to respond [46]. More severe external changes and interruptions may greatly motivate restaurants to response, restore stability, and enhance resilience. Harvey employed “time–space compression” to describe recent social changes [2]. In terms of space, the world is experiencing a globalized process [1]. In the food context, the spread of fast-food culture is considered damaging to various traditional food cultures [47]. Homogenization is an expected consequence of globalization, meaning everything becomes the same [48]. Thus, the force of globalization may decrease the diversity of local culture [49]. In terms of time, modern people complain more about the fast pace of life and spend less time in eating, sleeping, and playing [50]. Social acceleration may cause people to reduce their consumption of local food. Thus, we suggest:
Hypothesis 4 (H4).
Sociocultural change negatively affects the sustainability of Yumcha culture.
Second, however, social and cultural changes usually occur slowly, which does not destroy enterprises immediately; rather, it gives them more time and space to adapt to the changes. In the process of adapting, the enterprises obtain more abilities to cope with external challenges and become more resilient to strikes. As a result, social and cultural change can be beneficial to restaurants. Therefore, we hypothesize:
Hypothesis 5 (H5).
Sociocultural change positively enhances Yumcha restaurants’ resilience.
The relationship between dynamic capabilities and restaurant resilience is complex [51]. Contextual factors like rapid sociocultural change may moderate the association. Previous studies have suggested that, in rapidly changing environments, firms with high dynamic capabilities are more resilient [31]. However, when business environments are relatively stable, the benefits created by dynamic capabilities may be overturned by the costs required to develop and maintain such competences [52]. Therefore, we propose:
Hypothesis 6 (H6).
Sociocultural change moderates the relationship between dynamic capabilities and Yumcha restaurant resilience.
Based on the previous hypotheses, this research further proposes that the indirect effect of proactive behavior and uncertainty orientation on Yumcha heritage sustainability through Yumcha restaurant resilience should change with different levels of impact. That is to say, the impact should moderate the sequentially mediating effect of Yumcha restaurant resilience in the relationship between proactive behavior, uncertainty orientation, and Yumcha heritage sustainability. Thus:
Hypothesis 7 (H7).
Social–cultural impact moderates the indirect effects of proactive behavior and uncertainty orientation on Yumcha heritage sustainability via Yumcha restaurant resilience.

3. Methods

3.1. Sample, Data Collection, and Research Context

We conducted a survey based on employees’ perceptions. We collected data from Yumcha restaurants in Guangzhou. A pilot survey was conducted with six managers in Yamcha restaurants and two academic experts. The pilot respondents were required to provide comments on the measurement scales’ content validity. Based on respondents’ comments, we revised the questionnaire until the questionnaire was easy to understand and sufficiently clear.
The survey was conducted in the Haizhu and Yuexiu districts in Guangzhou, Guangdong, China. Yumcha culture originated in the Qing dynasty, between 1862 and 1874, in Guangzhou, Guangdong, China. Early Yumcha restaurants usually had a signboard with the letters “Cha Hua” (茶话). “Cha” (茶) means to drink tea and “Hua” (话) means to talk. This kind of restaurant generally provided several tables and benches for customers to sit, drink tea, and eat snakes (dim sum). Later, much larger Yumcha restaurants opened and Yumcha cultural became popular. In Guangdong, going to a Yumcha restaurant to drink tea and eat dim sum is also called “Tan Cha” (叹茶). “Tan” (叹) has a meaning of enjoyment, and “Tan Cha” is similar to a kind of pleasant recreation activity. In ancient times, Yumcha restaurants provided Yumcha products throughout the day. Yumcha services were its main products. In modern society, some restaurants only provide Yumcha products in the morning. Yumcha services are subsidiary products. Both kinds of restaurants were included as cases in this study.
We used both electronic and hard-copy questionnaires. We used wjx.com to develop the electronic questionnaires. Three university students collected the data between 14:00 and 17:00 every weekend from 16 May to 26 July 2018. Students collected the data mainly in the Haizhu and Yuexiu districts of Guangzhou. Haizhu and Yuexiu are the traditional districts in Guangzhou. Students investigated all the main streets. When they found a Yumcha restaurant, they walked in to introduce our research to the manager of the restaurant and to ask if they and their employees would fill a questionnaire. Students were trained in administering the questionnaire and introducing the questionnaire’s background. Questionnaires were administered face to face using the hard-copy edition. If the targeted respondents were working, students asked them if they would complete the electronic questionnaire later. Respondents were offered a chance to win an average 2 RMB bonus in a draw if they completed the electronic survey. To ensure the participants qualified for the study, a screening question was set in the beginning of the survey by asking what kind of food the restaurant in which they work provides.
The number of responses was 262. 14 responses in the electronic version were eliminated because their completion time was less than 2 minutes or their answers were all the same, yielding 248 usable samples. The effective response rate was 94.66%. As the data analysis technique we used was the maximal likelihood method, this sample size was sufficient [53]. By comparing employees’ characteristics (i.e., sex, age, and position) of early versus late respondents, nonresponse bias was tested. There were no significant difference.
In the formal survey, the sample characteristics demonstrated that 46% of the participants were female and 64.7% were older than 21 years old. Just 36% of the participants had a high-school degree or above. 45% of the participants were single and 45% were born in Guangzhou. Most of the participants (71.1%) had lived in Guangzhou for more than 10 years, and 45% had worked in Yumcha restaurants for more than 5 years.

3.2. Measures

In this section, variable definitions are presented. The measures of our study were based on previous studies [54], all using a 7-point Likert scale (1 means strongly disagree, 7 means strongly agree). Table 1 and Table 2 present all the measurement items. The variables included proxies for sustainability, resilience, impacts, and dynamic capabilities.
Yumcha heritage sustainability used a 5-item measurement scale. The items were adapted from Jantunen, Tarkiainen, Chari, and Oghazi [52]. The measure of sustainability of Yumcha culture considered the persistence of Yumcha activity and the continuous appreciation of the value involved in the activity. Within the Yumcha heritage context, it measures the continuous appreciation of the value of the Yumcha restaurant industry.
Yumcha restaurant resilience was adapted from Ambulkar et al. [55]. This scale assessed Yumcha restaurants’ capability to cope with disruptions and adapt to uncertainties.
The impact of social–cultural changes has two aspect factors, impact from demand-side changes and impact from market-side changes. Each impact factor of social–cultural changes was measured based on a 3-item scale that was originally from Bode et al. [46]. A revised version was developed for the purposes of this study based on interviews with restaurant managers, academic experts, and members of the Food and Beverage Association of Guangzhou. This variable measured the extent to which the Yumcha restaurant was affected by demand and market changes.
Dynamic capabilities include two aspects, uncertainty orientation and proactive behavior. Measurement items for the uncertainty-orientation dimension incorporated two factors, uncertainty orientation toward demand change, and uncertainty orientation toward market change. It measured the restaurants’ alertness to social disruptions. The uncertainty-orientation scale was adapted from Bode et al. [46].
Proactive behavior includes innovations and activities for knowledge and resource acquisition, as well as exploration facilitating resistance to social changes [53]. In the context of Yumcha culture, it includes 4 factors: product innovativeness, service innovativeness, experiential innovativeness, and promotional innovation.

3.3. Measure Assessment

A 2-stage procedure was implemented to evaluate measurement scales. In the first stage, exploratory factor analysis was conducted to measure the proactive behavior’s structure. Proactive behavior is a second-order construct. Exploratory factor analysis was to test whether items formed the expected proactive behavior factors. Factor analysis used the oblique-rotation method. Items with a low factor loading of 0.5 were abandoned. The reserved items’ factor loadings were all greater than 0.6 on their corresponding factors. We considered all factor loadings as significant [56]. Next, confirmatory factor analysis was performed to assess the convergence. Four factors (product innovativeness, service innovativeness, experiential innovativeness, promotional innovation) were included in the proactive-behavior construct.
The second stage was assessing the convergent and discriminant validity of the 5 key constructs with confirmatory factor analysis (Table 2). We used software package Mplus 7.0 [57] and employed the maximum-likelihood (ML) estimator, which is the default estimator in Mplus recommended by Henseler, Ringle, and Sarstedt [58]. All of the factor loadings were significant and higher than 0.6. Cronbach’s α and composite reliability (CR) for each measure was computed to assess the reliability and convergent validity of the scales. Factor loadings of all items were greater than 0.7. It showed that reliability and convergent validity was indicated [59]. The average variance extracted (AVE) was further computed to assess validity. AVE was higher than 0.5 [57] for all measures.
To further evaluate the discriminant validity of the 5 constructs, we followed strict procedures adopted from advanced research [60]. We compared the 5-factor key structure model with alternative plausible models. Table 3 shows the results. Based on the results, the proposed 5-factor model provided a better fit to the data (χ2(125) = 193.491, p < 0.01; the comparative fit index (CFI) = 0.967; the Tucker-Lewis index (TLI) = 0.960; Root Mean Square Error of Approximation (RMSEA) = 0.047; standard root mean square residual (SRMR) = 0.037) [61]. Thus, the discriminant validity of the five-factor key structure was confirmed.

4. Results

4.1. Descriptive Statistics

Table 4 reports the correlation of all the variables in this study. Results suggest that the sustainability of Yumcha culture is positively correlated with proactive behavior (r = 0.793, p < 0.01), uncertainty orientation (r = 0.707, p < 0.01), social–cultural changes (r = 0.24, p < 0.01), and Yumcha restaurant resilience (r = 0.645, p < 0.01). Moreover, Yumcha restaurant resilience is positively correlated with proactive behavior (r =0.712, p < 0.01), uncertainty orientation (r = 0.746, p < 0.01), and social–cultural changes (r = 0.599, p < 0.01). In addition, social-cultural changes are positively correlated with proactive behavior (r =0.397, p < 0.01) and uncertainty orientation (r = 0.502, p < 0.01).

4.2. Hypothesis Test

Structural equation modeling (SEM) was chosen as the analyzing method to test the hypothesized model. SEM helps provide a comprehensive examination of all paths and the overall fit of data in the model [62]. To estimate the single-item measures, the measurement path was set as one and assumed no error [63]. Following previous studies’ approach [64], the error and measurement path of the interaction was set. Two methods were used to measure the hypothesized model (with moderate effect), the product-indicator approach [65] and latent moderated structural equations (LMS) approach. The results of the product-indicator approach are shown in M1 of Table 5. The results of LMS are shown in M2 of Table 5.

4.3. Model Comparison

Five alternative plausible models were constructed to compare with the hypothesized model measured by the product-indicator approach (M1) utilizing the test of χ2 statistics [66]. Two of the alternative models were without moderate effect (M3 and M4). M5 is an alternative partial mediation model, and estimated the hypothesized model without links from uncertainty orientation to the sustainability of Yumcha culture. M6, an alternative full model, estimated the hypothesized model with the link from proactive behavior × social–cultural changes to the sustainability of Yumcha culture. M7, an alternative full-mediation model, estimated the hypothesized model without links from proactive behavior, uncertainty orientation, and social–cultural changes to the sustainability of Yumcha culture. M8, a model without mediation, estimated the hypothesized model without links from proactive behavior, uncertainty orientation, and social–cultural changes to Yumcha restaurant resilience.
The results of the changes in χ2 tests are shown in Table 5. The result of M1 indicates that the hypothesized model provides the best fit in the data compare to models M5–M8 (χ2 (175) = 397.521; CFI = 0.943; TLI = 0.932; Root Mean Square Error of Approximation (RMSEA) = 0.072; Standardized Root Mean Square Residual (SRMR) = 0.045). The goodness of fit of the M4 result, which is an alternative model without moderate effect, is slightly higher than the hypothesized model. However, we argue that our hypothesized model is the best for two reasons. First, the moderate effect in M1 is significant. Second, the Akaike Information Criteria (AIC) and Sample-Size Adjusted Bayesian Information Criteria (ABIC) of M2, which is the hypothesized model estimated by LMS, are lower than M4. AIC and ABIC are the goodness of fit indices used to compare the results between the LMS approach and the product-indicator approach.

4.4. Hypothesis Testing

Results of structural equation modeling analysis are presented in Figure 2. In support of Hypothesis 1, Yumcha restaurant resilience is confirmed to be positively related to the sustainability of Yumcha culture (β = 0.212, p < 0.05). Proactive behavior (β = 0.374, p < 0.01) and uncertainty orientation (β = 0.363, p < 0.01) are positively related to Yumcha restaurant resilience, thus supporting Hypotheses 2a and 3a. Proactive behavior (β = 0.544, p < 0.01) and uncertainty orientation (β = 0.244, p < 0.01) are positively related to the sustainability of Yumcha culture, thus supporting Hypotheses 2b and 3b. Sociocultural change (β = 0.234, p < 0.05) is negatively related to the sustainability of Yumcha culture, thus supporting Hypothesis 4. Sociocultural change (β = 0.234, p < 0.05) and proactive behavior × sociocultural change (β = 0.163, p < 0.05) are positively associated to Yumcha restaurant resilience, thus supporting Hypotheses 5 and 6.
Interaction effects are plotted in Figure 3 using Aiken and West’s procedure [67]. Figure 3 shows that the association between proactive behavior and Yumcha restaurant resilience is stronger when social–cultural changes are high (β = 0.218, p < 0.01) rather than low (β = 0.164, p < 0.05). Thus, Hypothesis 7 receives further support.
Hypothesis 5 proposed that Yumcha restaurant resilience mediates the relationships among proactive behavior, uncertainty orientation, impacts, proactive behavior × impact, and the sustainability of Yumcha culture. The model with a direct path from proactive behavior, uncertainty orientation, impact, proactive behavior × impact, to the sustainability of Yumcha culture did not show a significantly better fit than the hypothesized model. The mediation effect in Hypothesis 5 finds support.
Moderated path analysis was evaluated in Mplus 7.0 using the Bayes estimator with four Markov chain Monte Carlo (MCMC) chains to test Hypothesis 7 [68]. As displayed in Table 6, the indirect effect of proactive behavior on the sustainability of Yumcha culture via Yumcha restaurant resilience varies significantly across different levels of social–cultural changes (Δβ = 0.086, p < 0.05). Hence, Hypothesis 7 receives support. Specifically, the indirect effect of proactive behavior on the sustainability of Yumcha culture was stronger when the level of impact is high (β = 0.247, p < 0.01) rather than low (β = 0.155, p < 0.05). This provides further support for Hypothesis 7. Therefore, all the hypotheses in our study receive full support.

5. Conclusions and Discussion

5.1. Conclusions

This study shed light on the sustainability of food heritage under sociocultural changes from a restaurant perspective. Guangzhou quickly changed from a small city to a large metropolis within 40 years after China’s opening policy. Choosing Guangzhou’s Yumcha heritage as the case, we proposed that Yumcha restaurant resilience enhances Yumcha heritage sustainability. Dynamic capabilities were proposed having positive influence on the sustainability of Yumcha heritage via Yumcha restaurant resilience in the modern world. These hypotheses draw on the resilience perspective. The findings make contributions in three aspects: (1) Yumcha restaurant resilience positively affects Yumcha heritage sustainability, (2) business resilience mediates the effects between restaurants’ dynamic capability and food-heritage sustainability, and (3) the effects from dynamic capabilities to heritage sustainability are modified by social–cultural impact.
This research makes four theoretical contributions. First, this study expands the culture-heritage literature by focusing on the effect of business resilience of restaurants in heritage sustainability, where the restaurants’ dynamic capability is prevalent and may generate important influence, but its effects have not been fully investigated [14]. This research suggests that business resilience could contribute to heritage sustainability. Such findings provide evidence for the positive impact of business resilience on building food-heritage sustainability. Previous research tends to regard the commodification of heritage as damage to the authenticity of heritage [16,69]. This study proves that business with resilient capabilities can enhance the surviving ability of cultural heritage. These findings are not only effective in the conservation of food culture, but also in other types of cultural heritage. For instance, Dai and Xu found that business brought by tourism development would benefit the protection of tangible-architecture heritage in ancient towns in China [70].
Second, this research made contributions to current business-resilience research. Existing research mainly evaluates business resilience with business performance [52]. This study enhances the understanding of the power of business resilience by focusing on its contributions in preserving heritage. Existing business-resilience research on dynamic capabilities is also constrained. Our study extends the scope to examine specific dynamic capability in the restaurant industry. Five innovations were examined to measure the proactive behavior in building business dynamic capabilities. The advantages caused by enterprise development should not only be measured by the economic gains, but also by the benefits to cultural preservation.
Third, this study unraveled the mediating mechanisms between restaurants’ dynamic capability and food-heritage sustainability. Although research about business dynamic capabilities is a recent hot topic [18,52], the process through which capability may influence business resilience and the mediating mechanisms of business resilience have not yet been sufficiently studied, and this paper provide a vivid context to explain the mechanisms [18]. This paper highlights the mediating effects of business resilience in restaurant innovation in helping conserve sustainable food heritage. Business resilience as a mediator links the dynamic capability of enterprises with the sustainability of culture. Various innovations in cultural commodification are crucial means to obtain cultural sustainability.
Fourth, our study further tests the moderating effect of impact. This result supports that effects from dynamic capabilities on heritage sustainability may be modified by impact, consistent with previous research [18]. We therefore expand previous research and argue that impacts provide challenges for business resilience; however, on the other hand, impacts may augment the positive effects from dynamic capability to business resilience. The study argues that identification of social–cultural changes’ moderating effect can alleviate their negative effects [18].

5.2. Practical Implications

There are several implications for sustainable food-culture conservation according to the research results and conclusions.
This research suggests that business resilience is crucial for heritage sustainability. This is especially true for restaurants in preserving food heritage, which has been categorized as a tangible heritage. Traditional food-heritage articles appeal for adjustments in human behavior to adopt traditional food. For instance, many studies advocate that people change their dining preferences to choose slower food [71,72]. Our results show that these slow-food activists just try to “return to a primitive, preindustrial economy” [72] (p. 168), which is unrealistic in modern society. However, our study indicates that to preserve food heritage, resilient capacities of restaurants are key factors. If restaurants implement more innovation, they tend to have high levels of business resilience, which helps them survive when facing social–cultural changes. Thus, in the case of European slow food, it is more resilient to make innovations to improve local culinary heritage rather than stick to the authenticity and resist any change. Helping food-heritage restaurants be more resilient may contribute to food-heritage sustainability. For restaurants managers, it is crucial to change minds to make changes and innovations and become more resilient. For instance, many Yumcha restaurants use traditional cooking techniques to create new cuisines to meet new market demands. Some of them also adopt automatic ordering systems to reduce costs and meet younger people’s consuming preferences. Government officials should take measures for the spillover effect of food-heritage restaurants when developing food-heritage sustainability strategies. The government should encourage restaurants to innovate with policy and financial support, for instance, by providing innovation funds or low-interest loans for restaurants.
Shocks can push enterprises to innovate. Usually, innovation follows awareness of its necessity. However, this study shows that sometimes internal innovation consciousness does not emerge naturally; external shocks can make enterprises generate the demand for innovation. Research results illustrate that, when external shocks are at a low level, the benefits generated from innovation are fewer. A stronger shock can create increasing innovation desire and more profits. For managers, it is important to be sensitive to external shocks and seize every chance to make innovations.
It is common to emphasize cultural authenticity in the sustainable conservation of cultural heritage. However, in our research, restaurant innovation has a strong positive influence on food-heritage sustainability. This means the change and innovation of cuisines can also contribute to the sustainability of food heritage. In China, people usually do not evaluate food by the authenticity of its taste. People can accept innovative tastes if the new tastes produce a high-quality experience. Therefore, we argue that it is also important to change the food culture according to social and cultural change to conserve the intangible food heritage.

5.3. Limitations and Future Research

The first limitation is considering other types of cultural heritage less. Examining different kinds of food heritages, such as Western food heritage, would be interesting for future research. The second limitation is that the data were derived just from a single questionnaire, so future studies could do a cross-sectional survey or a longitudinal study to assess the sustainability of food heritage over time. In terms of research method, it would also be beneficial to use qualitative methods to deeply explore business firms’ capabilities and their influence on firm resilience and cultural sustainability. Finally, examining the conclusions from this research in a broader range of social and cultural contexts would show comprehensive mechanisms of how specific business capabilities influence cultural sustainability in different social–cultural environments.

Author Contributions

Conceptualization, S.D., Q.C. and H.X.; Methodology, S.D.; Software, S.D.; Validation, S.D. and H.X.; Formal Analysis, S.D.; Investigation, S.D.; Resources, H.X.; Data Curation, S.D.; Writing—Original Draft Preparation, S.D., Q.C.; Writing—Review and Editing, S.D., Q.C.; Visualization, S.D.; Supervision, H.X.; Project Administration, Q.C., H.X.; Funding Acquisition, S.D.

Funding

This research was funded by National Natural Science Foundation of China, grant number [41601611].

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Robertson, R. Globalization: Social Theory and Global Culture; Sage: London, UK, 1992. [Google Scholar]
  2. Harvey, D. The Condition of Postmodernity; Blackwell: Oxford, UK, 1990. [Google Scholar]
  3. Tan, S.K.; Tan, S.H.; Kok, Y.S.; Choon, S.W. Sense of place and sustainability of intangible cultural heritage–The case of George Town and Melaka. Tour. Manag. 2018, 67, 376–387. [Google Scholar] [CrossRef]
  4. Long, L.M. Culinary tourism: A folkloristic perspective on eating and otherness. South. Folklore 1998, 55, 181. [Google Scholar]
  5. Henderson, J.C. Food as a tourism resource: A view from Singapore. Tour. Recreat. Res. 2004, 29, 69–74. [Google Scholar] [CrossRef]
  6. Jiménez-Beltrán, F.J.; López-Guzmán, T.; González Santa Cruz, F. Analysis of the relationship between tourism and food culture. Sustainability 2016, 8, 418. [Google Scholar] [CrossRef]
  7. Broadway, M.J. ‘Putting place on a plate’ along the West Cork Food Trail. Tour. Geogr. 2017, 19, 467–482. [Google Scholar] [CrossRef]
  8. Dimitrovski, D.; Vallbona, M.C. Urban food markets in the context of a tourist attraction—La Boqueria market in Barcelona, Spain. Tour. Geogr. 2018, 20, 397–417. [Google Scholar] [CrossRef]
  9. Tam, S.M. Heunggongyan forever: Immigrant life and Hong Kong style Yumcha in Australia. In The Globalization of Chinese Food; Wu, D.Y.H., Cheung, S.C.H., Eds.; University of Hawaii Press: Honolulu, HI, USA, 2002; pp. 131–151. [Google Scholar]
  10. Chen, L. Tea and Dim Sum: Cantonese Style Morning Tea; Guangdong Education Press: Guangzhou, China, 2009. [Google Scholar]
  11. Song, S. The impacts of Guangdong Zaocha culture on table manners and modern lifestyles. Mod. Commun. 2018, 6, 103–105. [Google Scholar]
  12. Larsson, M.; Milestad, R.; Hahn, T.; Von Oelreich, J. The resilience of a sustainability entrepreneur in the Swedish food system. Sustainability 2016, 8, 550. [Google Scholar] [CrossRef]
  13. Kim, E.; Tang, L.R.; Bosselman, R. Measuring customer perceptions of restaurant innovativeness: Developing and validating a scale. Int. J. Hosp. Manag. 2018, 74, 85–98. [Google Scholar] [CrossRef]
  14. Zeng, G.; Zhao, Y.; Sun, S. Sustainable development mechanism of food culture’s translocal production based on authenticity. Sustainability 2014, 6, 7030–7047. [Google Scholar] [CrossRef]
  15. Prideaux, B. Commodifying Heritage: Loss of Authenticity and Meaning or an Appropriate Response to Difficult Circumstances? Int. J. Tour. Sci. 2003, 3, 1–15. [Google Scholar] [CrossRef]
  16. Bao, J.; Lin, M. Study on control of tourism commercialization in historic town and village. Acta Geogr. Sin. 2014, 69, 268–277. [Google Scholar]
  17. Su, J. Understanding the changing Intangible Cultural Heritage in tourism commodification: The music players’ perspective from Lijiang, China. J. Tour. Cult. Chang. 2018. [Google Scholar] [CrossRef]
  18. Parker, H.; Ameen, K. The role of resilience capabilities in shaping how firms respond to disruptions. J. Bus. Res. 2017, 88, 535–541. [Google Scholar] [CrossRef]
  19. Teece, D.J.; Pisano, G.; Shuen, A. Dynamic capabilities and strategic management. Strateg. Manag. J. 1997, 18, 509–533. [Google Scholar] [CrossRef] [Green Version]
  20. WCED. Our Common Future; Oxford University Press: Oxford, UK, 1987; p. 43. [Google Scholar]
  21. Throsby, D. Sustainability and culture some theoretical issues. Int. J. Cult. Policy 1997, 4, 7–19. [Google Scholar] [CrossRef]
  22. Coben, L.S. Sustainability and Cultural Heritage. In Encyclopedia of Global Archaeology; Smith, C., Ed.; Springer Reference: New York, NY, USA, 2014; pp. 7155–7157. [Google Scholar]
  23. Daskon, C.D. Cultural resilience—the roles of cultural traditions in sustaining rural livelihoods: A case study from rural Kandyan villages in Central Sri Lanka. Sustainability 2010, 2, 1080–1100. [Google Scholar] [CrossRef]
  24. Guo, Y.R.; Zhang, J. Research progress and themes of geography on community resilience. Prog. Geogr. 2015, 34, 100–109. [Google Scholar]
  25. Lew, A.A. Scale, change and resilience in community tourism planning. Tour. Geogr. 2014, 16, 14–22. [Google Scholar] [CrossRef]
  26. Roundy, P.T.; Brockman, B.K.; Bradshaw, M. The resilience of entrepreneurial ecosystems. J. Bus. Ventur. Insight 2017, 8, 99–104. [Google Scholar] [CrossRef]
  27. Van Der Vegt, G.S.; Essens, P.; Wahlström, M.; George, G. Managing risk and resilience. Acad. Manag. J. 2015, 58, 971–980. [Google Scholar] [CrossRef]
  28. Helfat, C.E.; Winter, S.G. Untangling dynamic and operational capabilities: Strategy for the (N)ever-changing world. Strateg. Manag. J. 2011, 32, 1243–1250. [Google Scholar] [CrossRef]
  29. Winter, S.G. Understanding dynamic capabilities. Strateg. Manag. J. 2003, 24, 991–995. [Google Scholar] [CrossRef] [Green Version]
  30. Jantunen, A.; Puumalainen, K.; Saarenketo, S.; Kyläheiko, K. Entrepreneurial orientation, dynamic capabilities and international performance. J. Int. Entrep. 2005, 3, 223–243. [Google Scholar] [CrossRef]
  31. Teece, D.J. Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strateg. Manag. J. 2007, 28, 1319–1350. [Google Scholar] [CrossRef]
  32. Ali, A.; Krapfel, R.; LaBahn, D. Product innovativeness and entry strategy: Impact on cycle time and break-even time. J. Prod. Innov. Manag. 1995, 12, 54–69. [Google Scholar] [CrossRef]
  33. Garcia, R.; Calantone, R. A critical look at technological innovation typology and innovativeness terminology: A literature review. J. Prod. Innov. Manag. 2002, 19, 110–132. [Google Scholar] [CrossRef]
  34. Rubera, G.; Ordanini, A.; Griffith, D.A. Incorporating cultural values for understanding the influence of perceived product creativity on intention to buy: An examination in Italy and the US. J. Int. Bus. Stud. 2011, 42, 459–476. [Google Scholar] [CrossRef]
  35. Feltenstein, A. An intertemporal general equilibrium analysis of financial crowding out: A policy model and an application to Australia. J. Public. Econ. 1986, 31, 79–104. [Google Scholar] [CrossRef]
  36. Berry, L.L.; Shankar, V.; Parish, J.T.; Cadwallader, S.; Dotzel, T. Creating new markets through service innovation. MIT Sloan Manag. Rev. 2006, 47, 56–63. [Google Scholar]
  37. Reid, R.D.; Sandler, M. The use of technology to improve service quality: A look at the extent of service improvements to be gained through investments in technology and expanded facilities and programs. Cornell Hosp. Q. 1992, 33, 68–73. [Google Scholar]
  38. Prahalad, C.K.; Ramaswamy, V. The new frontier of experience innovation. MIT Sloan Manag. Rev. 2003, 44, 12–18. [Google Scholar]
  39. Sashi, C.M. Customer engagement, buyer-seller relationships, and social media. Manag. Decis. 2012, 50, 253–272. [Google Scholar] [CrossRef]
  40. Sipe, L.J. How do senior managers influence experience innovation? Insights from a hospitality marketplace. Int. J. Hosp. Manag. 2016, 54, 75–83. [Google Scholar] [CrossRef]
  41. Jernsand, E.M.; Kraff, H.; Mossberg, L. Tourism experience innovation through design. Scand. J. Hosp. Tour. 2015, 15, 98–119. [Google Scholar] [CrossRef]
  42. Grewal, D.; Ailawadi, K.L.; Gauri, D.; Hall, K.; Kopalle, P.; Robertson, J.R. Innovations in retail pricing and promotions. J. Retail. 2011, 87, 43–52. [Google Scholar] [CrossRef]
  43. Doherty, N.F.; Ellis-Chadwick, F. Internet retailing: The past, the present and the future. Int. J. Retail Distrib. Manag. 2010, 38, 943–965. [Google Scholar] [CrossRef] [Green Version]
  44. Shankar, V.; Inman, J.J.; Mantrala, M.; Kelley, E.; Rizley, R. Innovations in shopper marketing: Current insights and future research issues. J. Retail. 2011, 87, 29–42. [Google Scholar] [CrossRef]
  45. Lin, C.Y.; Marshall, D.; Dawson, J. How does perceived convenience retailer innovativeness create value for the customer? Int. J. Bus. Econ. 2013, 12, 171–179. [Google Scholar]
  46. Bode, C.; Wagner, S.M.; Petersen, K.J.; Ellram, L.M. Understanding responses to supply chain disruptions: Insights from information processing and resource dependence perspectives. Acad. Manag. J. 2011, 54, 833–856. [Google Scholar] [CrossRef]
  47. Gaytán, M.S. Globalizing resistance: Slow Food and new local imaginaries. Food Cult. Soc. 2004, 7, 97–116. [Google Scholar] [CrossRef]
  48. McManus, R. Homogenization. In Globalization: The Key Concepts; Mooney, A., Evans, B., Eds.; Routledge: London, UK, 2007; pp. 123–124. [Google Scholar]
  49. Ritzer, G.; Ryan, M. The globalization of nothing. Soc. Thought Res. 2002, 25, 51–81. [Google Scholar] [CrossRef]
  50. Rosa, H. Social Acceleration: A New Theory of Modernity; Columbia University Press: New York, NY, USA, 2013. [Google Scholar]
  51. Fainshmidt, S.; Pezeshkan, A.; Lance Frazier, M.; Nair, A.; Markowski, E. Dynamic capabilities and organizational performance: A meta-analytic evaluation and extension. J. Manag. Stud. 2016, 53, 1348–1380. [Google Scholar] [CrossRef]
  52. Jantunen, A.; Tarkiainen, A.; Chari, S.; Oghazi, P. Dynamic capabilities, operational changes, and performance outcomes in the media industry. J. Bus. Res. 2018, 89, 251–257. [Google Scholar] [CrossRef]
  53. Zikmund, W.G.; Babin, B.J.; Carr, J.C.; Griffin, M. Business Research Methods, 9th ed.; Cengage Learning: Boston, MA, USA, 2013. [Google Scholar]
  54. Churchill, G.A., Jr. A paradigm for developing better measures of marketing constructs. J. Mark. Res. 1979, 16, 64–73. [Google Scholar] [CrossRef]
  55. Ambulkar, S.; Blackhurst, J.; Grawe, S. Firm’s resilience to supply chain disruptions: Scale development and empirical examination. J. Oper. Manag. 2015, 33, 111–122. [Google Scholar] [CrossRef]
  56. Hair, J.F.; Black, W.C.; Babin, B.J.; Anderson, R.E.; Tatham, R.L. Multivariate Data Analysis; Prentice Hall: Upper Saddle River, NJ, USA, 1998. [Google Scholar]
  57. Muthén, L.K.; Muthén, B. Mplus User’s Guide; Muthén & Muthén: Los Angeles, CA, USA, 2014. [Google Scholar]
  58. Henseler, J.; Ringle, C.M.; Sarstedt, M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J. Acad. Mark. Sci. 2015, 43, 115–135. [Google Scholar] [CrossRef]
  59. Bagozzi, R.P.; Yi, Y. Multitrait-multimethod matrices in consumer research. J. Consum. Res. 1991, 17, 426–439. [Google Scholar] [CrossRef]
  60. Zhu, H.; Lyu, Y.; Deng, X.; et al. Workplace ostracism and proactive customer service performance: A conservation of resources perspective. Int. J. Hosp. Manag. 2017, 64, 62–72. [Google Scholar] [CrossRef]
  61. Hair, J.; Hult, G.; Ringle, C.; Sarstedt, M. A Primer on Partial Least Squares Structural Equation Modelling (PLS-SEM); Sage: Los Angeles, CA, USA, 2014. [Google Scholar]
  62. Byrne, B.M. Structural Equation Modeling with EQS and EQS/Windows: Basic Concepts, Applications, and Programming; Sage: Thousand Oaks, CA, USA, 1994. [Google Scholar]
  63. Seibert, S.E.; Kraimer, M.L.; Liden, R.C. A social capital theory of career success. Acad. Manag. J. 2001, 44, 219–237. [Google Scholar]
  64. Cortina, J.M.; Chen, G.; Dunlap, W.P. Testing interaction effects in LISREL: Examination and illustration of available procedures. Organ. Res. Methods 2001, 4, 324–360. [Google Scholar] [CrossRef]
  65. Saris, W.E.; Batista-Foguet, J.M.; Coenders, G. Selection of indicators for the Interaction term in structural equation models with interaction. Qual. Quant. 2007, 41, 55–72. [Google Scholar] [CrossRef]
  66. Bentler, P.M.; Bonnet, D.C. Significance tests and goodness of fit in the analysis of covariance structures. Psychol. Bull. 1980, 88, 588–606. [Google Scholar] [CrossRef]
  67. Aiken, L.S.; West, S.G. Multiple Regression: Testing and Interpreting Interactions; Sage: Thousand Oaks, CA, USA, 1991. [Google Scholar]
  68. Edwards, J.R.; Lambert, L.S. Methods for integrating moderation and mediation: A general analytic framework using moderated path analysis. Psychol. Methods 2007, 12, 1–22. [Google Scholar] [CrossRef] [PubMed]
  69. Ye, S.; Xiao, H.; Zhou, L. Commodification and perceived authenticity in commercial homes. Ann. Tour. Res. 2018, 71, 39–53. [Google Scholar] [CrossRef]
  70. Dai, S.; Xu, H. A system dynamics approach to explore sustainable policies for Xidi, the world heritage village. Curr. Issues Tour. 2012, 15, 441–459. [Google Scholar]
  71. Chrzan, J. Slow food: What, why, and to where? Food Cult. Soc. 2004, 7, 117–132. [Google Scholar] [CrossRef]
  72. Simonetti, L. The ideology of slow food. J. Eur. Stud. 2012, 42, 168–189. [Google Scholar] [CrossRef]
Figure 1. Conceptual model of this study.
Figure 1. Conceptual model of this study.
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Figure 2. Results of path analysis. Note: N = 248; *** p < 0.01; ** p < 0.05. It is a simplified version of the proposed model. Error terms, indicators, exogenous factor variances, and correlations among exogenous factors are not shown.
Figure 2. Results of path analysis. Note: N = 248; *** p < 0.01; ** p < 0.05. It is a simplified version of the proposed model. Error terms, indicators, exogenous factor variances, and correlations among exogenous factors are not shown.
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Figure 3. The moderating effect of social–cultural changes on the relationship between proactive behavior and resilience.
Figure 3. The moderating effect of social–cultural changes on the relationship between proactive behavior and resilience.
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Table 1. Exploratory and confirmatory factor analysis for proactive behavior.
Table 1. Exploratory and confirmatory factor analysis for proactive behavior.
No.FactorMSDSkewKurtEFLCFL
Product innovativeness (Cronbach’s α: 0.897, CR: 0.897; AVE: 0.702) 18.6% a
At1Yumcha restaurants offer new flavors.5.411.417–0.654–0.0240.7500.794
At2Yumcha restaurants offer new combinations of food.5.311.450–0.7220.2270.8070.869
At3Yumcha restaurants offer innovative presentation of food.5.341.391–0.5950.0320.7470.849
At4Yumcha restaurants introduce new menu items.5.591.431–0.761–0.0590.7660.8
Service innovativeness (Cronbach’s α: 0.853, CR: 0.857; AVE: 0.667) 14.9% a
As1Yumcha restaurants’ procedure for ordering menu items is innovative.5.581.412–0.7830.2230.8600.835
As2Yumcha restaurants integrate innovative technologies in new processes for offering their services.5.201.359–0.371−0.1900.6510.762
As3Yumcha restaurants’ apps or online ordering tools make Yumcha restaurants make it easier for customers to order one-of-a-kind menu items compared to its competitors5.421.474–0.7280.1440.8150.851
Experiential innovations (Cronbach’s α: 0.929, CR: 0.93; AVE: 0.72) 20.0% a
Ae1Yumcha restaurants offer unique characteristic features that set it apart from its competitors.5.301.371–0.6160.1520.9210.823
Ae2Traditional culture is integrated into Yumcha restaurants5.651.375–0.7920.1440.7790.812
Ae3The characteristics of Yumcha restaurants provide an innovative environment that makes them unique.5.371.428–0.6420.0220.7630.896
Ae4The characteristics of Yumcha restaurants provide an innovative design that differentiates them from their competitors.5.231.361–0.406–0.2300.6800.85
Ae5Yumcha restaurants are well-known for innovative custom events.5.421.383−0.590–0.1340.7900.873
Promotional innovativeness (Cronbach’s α: 0.919, CR: 0.92; AVE: 0.70) 21.9% a
Ap1Yumcha restaurants are always thinking of ways to expand and offer new benefits to its customers in order to give them a better experience.5.121.397–0.397–0.3260.7130.837
Ap2The way Yumcha restaurant employees interact with their customers is innovative.5.091.394–0.4310.0040.7820.803
Ap3Yumcha restaurants have an innovative rewards (membership) program.5.111.394–0.4690.2000.9210.86
Ap4Yumcha restaurants implement new advertising strategies not currently used by their competitors.5.251.368–0.376–0.2620.7660.843
Ap5Yumcha restaurants adopt novel ways to market themselves to customers.5.081.349–0.275–0.1680.7330.817
Cumulative validity75.4% a
Note: Kaiser–Meyer–Olkin measure of sampling adequacy is 0.942, approx. chi-square of Bartlett’s test of sphericity is 3636.240 (df = 153). a denotes for variance contribution rate. EFL, exploratory factor loadings; CFL, confirmatory factor loadings.
Table 2. Confirmatory factor analysis for resilience and sustainability.
Table 2. Confirmatory factor analysis for resilience and sustainability.
FactorMeanSDSkewnessKurtosisC Factor Loading
Proactive behavior (Cronbach’s α: 0.880, composite reliability (CR): 0.89; average variance extracted (AVE): 0.67)
P1Product innovativeness5.411.243–0.7890.6410.780
P2Service innovativeness5.401.245–0.6440.4490.755
P3Experiential innovativeness5.391.221–0.6190.3360.883
P4Promotional innovation5.131.201–0.3410.2810.85
Uncertainty orientation of demand change (Cronbach’s α: 0.880, CR: 0.88; AVE: 0.65)
U1Various social changes have highlighted the fragility of Yumcha restaurants and demonstrated improvements to Yumcha restaurants. 4.961.286–0.151–0.0570.719
U2Yumcha restaurants recognize the impact of social change at any time. 5.041.251–0.106–0.2010.819
U3Yumcha restaurants have done a lot to better cope with social changes. 5.151.243–0.095–0.2990.827
U4The impact on Yumcha restaurants is constantly reviewed. 5.171.272–0.306–0.1680.859
Social–cultural changes (Cronbach’s α: 0.859, CR: 0.86; AVE: 0.62)
Im1Social change affects the Yumcha restaurant industry 4.821.526–0.490–0.0470.600
Im2Customer tastes change increasingly faster, affecting the morning-tea industry. 4.641.589–0.409–0.1160.842
Im3The way of life is getting increasingly faster in the Yumcha restaurant industry 4.541.545–0.356–0.1230.881
Im4All kinds of catering enterprises continue to increase, affecting the morning-tea industry. 4.501.574–0.448–0.0590.803
Yumcha heritage resilience (Cronbach’s α: 0.898, CR: 0.90; AVE: 0.69)
R1Yumcha culture can adapt to the impact of various shocks. 4.841.285–0.077–0.1100.832
R2Yumcha restaurants can respond quickly to the impact of various shocks. 4.731.2980.002–0.0870.854
R3Yumcha restaurants have enough capacity to adapt to all kinds of impact. 4.801.388–0.3390.1930.818
R4Yumcha restaurants can quickly adjust business operations to cope with all kinds of impact. 4.831.304–0.1310.0910.814
Sustainability of Yumcha culture (Cronbach’s α: 0.901, CR: 0.91; AVE: 0.76)
Fu1I am full of confidence in the Yumcha restaurant industry 5.381.386–0.629–0.0070.915
Fu2I think the Yumcha restaurant industry has a good future5.361.373–0.6010.1120.903
Fu3I’d be happy to work in the Yumcha restaurant industry5.331.499–0.644–0.1940.795
Table 3. Results of the confirmatory factor analysis for the measurement scales.
Table 3. Results of the confirmatory factor analysis for the measurement scales.
χ2DfRMSEASRMRCFITLI
1Five-factor model193.4911250.0470.0370.9670.960
2Four-factor model: dynamic capability and uncertainty orientation were combined into one factor.301.3391290.0730.0510.9180.903
3Three-factor model: Dynamic capability, uncertainty orientation, and impact were combined into one factor527.9361320.1100.0910.8110.781
4Two-factor model: dynamic capability, uncertainty orientation, impact, and business resilience were combined into one factor625.7291340.1220.0940.7660.732
5All variables were combined into one factor757.6911350.1360.1020.7030.664
Table 4. Correlation matrix.
Table 4. Correlation matrix.
1234
1Proactive behavior1
2Uncertainty orientation0.7661
3Social–culture changes0.3970.5021
4Yumcha restaurant resilience0.7120.7460.5991
5Yumcha culture sustainability0.7930.7070.240.645
Table 5. Comparison of structural equation models.
Table 5. Comparison of structural equation models.
M1M2M3M4M5M6M7M8
R->S0.212 **0.215 *0.706 ***0.208 *0.294 ***0.235 **0.690 **0.198 **
behavior->R0.374 ***0.361 ***0.396 ***0.331 **0.358 ***0.413 ***0.422 ***
Orientation->R0.363 ***0.359 ***0.473 ***0.344 **0.378 ***0.420 ***0.377 ***
Chang->R0.234 ***0.248 *** 0.295 ***0.235 ***0.181 ***0.190 ***
Behavior * Change->R0.163 ***0.110 * 0.162 ***0.076 ***0.156 ***
Behavior->S0.544 ***0.532 *** 0.544 ***0.674 ***0.729 *** 0.557 ***
Orientation->S0.244 ***0.247 ** 0.249 ** 0.347 *** 0.253 ***
Change->S–0.224 ***–0.219 *** −0.226 ***−0.201 ***−0.212 *** −0.231 ***
Behavior * Change->S 0.014 0.025
χ2397.521 287.555325.586404.171397.298493.051397.298
Df175 86157176174178174
Δχ2Df) 110 (89)–72 (18)6 (1)–0.3 (1)104 (3)–0.23 (1)
RMSEA0.072 0.0970.0660.0720.0720.0840.072
SRMR0.045 0.0760.0490.0470.045 0.045
CFI0.943 0.9290.9490.9420.9430.9200.943
TFI0.932 0.9130.9390.9310.9310.9050.931
AIC15,065.9512,165.869912.3212,172.4415,070.6015,067.7215,155.4815,067.72
ABIC15,085.1812,188.539929.1512,194.4215,089.4815,087.3015,173.6815,087.30
Note: R: Yumcha restaurant resilience; S: Yumcha culture sustainability; Behavior: proactive behavior; Orientation: uncertainty orientation; Change: social–cultural changes; RMSEA: Root Mean Square Error of Approximation; SRMR: Standardized Root Mean Square Residual; AIC: Akaike Information Criteria; ABIC: Sample-Size Adjusted Bayesian Information Criteria. *, **, *** denote significant results at the 0.10, 0.05, and 0.01 confidence levels, respectively.
Table 6. Summary of conditional indirect effects.
Table 6. Summary of conditional indirect effects.
PathClassCoefficientPosterior S.D.95% Confidence Intervals
LowerHigher
behavior->RHigher social–cultural changes1.0190.0920.8371.194
Lower social–cultural changes0.6490.0870.4770.817
Difference in direct effect 0.3710.1230.1230.611
indirect effectHigher social–cultural changes0.2470.0780.1030.412
Lower social–cultural changes0.1550.0520.0630.268
Difference in indirect effect0.0860.0410.0220.185
Notes: sample size of the higher social–cultural-change category is 91; sample size of the lower social–cultural-change category is 154; all the coefficients are unstandardized. The conditional indirect-effect tests were estimated using Bayes estimator with four Markov chain Monte Carlo (MCMC) chains. Fixed number of iterations for each MCMC chain was 1000.

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Dai, S.; Cui, Q.; Xu, H. The Resilience Capabilities of Yumcha Restaurants in Shaping the Sustainability of Yumcha Culture. Sustainability 2018, 10, 3304. https://doi.org/10.3390/su10093304

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Dai S, Cui Q, Xu H. The Resilience Capabilities of Yumcha Restaurants in Shaping the Sustainability of Yumcha Culture. Sustainability. 2018; 10(9):3304. https://doi.org/10.3390/su10093304

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Dai, Shanshan, Qingming Cui, and Honggang Xu. 2018. "The Resilience Capabilities of Yumcha Restaurants in Shaping the Sustainability of Yumcha Culture" Sustainability 10, no. 9: 3304. https://doi.org/10.3390/su10093304

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