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ISSN : 2288-4637(Print)
ISSN : 2288-4645(Online)
The Journal of Asian Finance, Economics and Business Vol.2 No.1 pp.29-36
DOI : https://doi.org/10.13106/jafeb.2015.vol2.no1.29.

Antecedents of Acceptance of Social Networking Sites in Retail Franchise and Restaurant Businesses

Jung Wan Lee*, Michael Kwag**, Rajasekhara Mouly Potluri***
*First author, Assistant Professor, Administrative Sciences Department, Metropolitan College, Boston University
**Professor, School of Hospitality Administration, Boston University
***Corresponding author, Professor, Department of Management Studies, Nimra Institute of Science & Technology
***Corresponding Author : prmouly@yahoo.co.in
December 5, 2014 February 15, 2015 February 19, 2015

Abstract

The paper examines the antecedents of acceptance of social networking sites in retail franchise and restaurant businesses. The success of retail franchise and restaurant business oper-ators via social networking sites depends not only on organiza-tional benefits but also on their behavioral intentions of using it. Three hundred and twenty four samples collected from South Korean retail franchise and restaurant employees are analyzed using factor analysis, structural equation model techniques and one-way analysis of variance. The results of the study identify the three constructs of organizational benefits, perceived tangible assets and perceived intangible assets as for important ante-cedents to accept social networking sites for their business use. Moreover, higher position employees tend to have more favor-able perception of tangible assets and acceptance of social net-working sites for their business use.

초록


 1. Introduction

 The Internet is developing in a fast speed globally because of its increased availability, usability and its ability to transfer in-formation, products and services. This trend provides more spaces for the growth of electronic commerce (e-commerce), es-pecially online retailing services. Online retailing is a form of e-commerce that allows consumers to purchase products and services directly either from a retailer through e-commerce web-sites or social networking sites. The retail franchise and restau-rant social networking site defines as a community that provides any combination of consulting, promoting, sharing and providing retail franchise and restaurant information via social networking sites. Actually social networking sites have become an indis-pensable new shopping channel connecting customers and ma-jority of online retailing and restaurant websites.  Nowadays, not only can consumers find a product of interest by visiting the web-site of retailers and restaurants directly, but also they can find it by searching among alternative vendors using social networking sites. Therefore, a relatively new topic about how and why retail franchise and restaurant business operators intend to use social networking sites in promoting and sharing retail franchise and restaurant information has grown to be a dominant theme today. Despite many studies of e-commerce and online retailing (e.g., Hernández, Jiménez, & Martín, 2010; Papatla, 2011), there are few analyses regarding both the effects of social networking sites on retail franchise and restaurant businesses and organizational in-tention to use social networking sites. This paper will discuss these critical issues related to retail franchise and restaurant business op-erators’ organizational intention to use social networking sites.

2. Literature Review

2.1. Tangible Assets of Retail Franchise and Restaurant Social Networking Sites

 In traditional environments, consumers who observe service providers’ facilities, employees and equipment typically generate physical appearance, that is, tangible assets. Consumers eval-uate this appearance separately from other service quality dimensions. A lot of research has been dedicated to the study of the physical environment’s influence on consumers’ behaviors (e.g., Bonnin, 2009; Lee & Mendlinger, 2011). These studies have shown that service providers’ atmosphere can influence consumers’ purchase behaviors, evaluations and decision processes. Researchers have studied service quality and custom-er satisfaction in physical environments that involve face-to-face interactions between service personnel and consumers for many years, as defined in SERVQUAL (e.g., Parasuraman, Zeithaml, & Berry, 1988). However, tangibles in an online environment grow out of consumer perception with e-commerce provider environ-ment due to the absence of human physical interaction. For ex-ample, dimensions such as tangibles are less applicable since the physical appearance of facilities, employees and equipment is unobservable in an online environment.

 A retailer’s corresponding resource capabilities may enable the retailer to be more efficient to utilize a modern technology compare to its competitors (Varadarajan et al., 2010).  Pantano and Naccarato (2010) reported that the presentation of in-novative technologies in stores modified the appearance of the point of sales, increased shopping interests by providing exciting entertainment elements and encouraged consumer purchasing behaviors. Gil-Saura, Berenguer-Contrí and Ruiz-Molina (2009) reported that higher levels of technologies that are more ad-vanced are better than lower levels of technologies in terms of consumer satisfaction. Online marketers exercise considerable latitude in designing their website interface and other online of-ferings that enable consumers to engage in search and ex-change activities (Montoya-Weiss, Voss, & Grewal, 2003). In this regard, they recommend that retailers should continuously invest in Internet technologies, especially those that display a sig-nificant effect on customer satisfaction such as payment facilities and website design. 

 A factor that is visible to consumers can affect the service experience. This is the environment in which the service is de-livered and where firms and consumers interact. It can directly be influential in initiating the service experience, enhancing the perceptions of service benefits, and promoting user behavioral intentions (Bonnin, 2009; Lee, Brahmasrene, & Kim, 2009). There is a steady stream of research on the influence of tangi-ble assets like physical environment on the service experience in the retailing literature (e.g., Chebat & Robicheaux, 2001; Hoffman & Turley, 2002; Turley & Milliman, 2000). However, on-ly a few attempts to investigate the impact of physical environ-ment (tangible assets) of Internet websites such as social net-working sites on the service experience (e.g., Bonnin, 2009; Lee, Brahmasrene, & Kim, 2009). The empirical research has shown that the physical environment cues can affect consumer internal states and their purchase related behaviors. 

 Tangible assets of retail franchise and restaurant social net-working sites affect its service evaluation by customers and their future behavior of using the social networking sites. Comparing with the definition of tangible assets of traditional shopping place, the tangible assets of social networking sites means web-site design including the external surrounding and conditions in which something visual. The examples of tangible assets are use of modern equipment and technology, visual appealing of websites and professional appearance of service personnel for the social networking sites. In this sense, in order to draw large number of customers’ attention, social networking websites make efforts on website design, online offerings and new technology etc. In summary, the following hypotheses are generated for verification based on the discussion raised above:

 Hypothesis 1: Organizational benefits are positively associated with the perceived value of tangible assets of social networking sites.

 Hypothesis 2: Tangible assets have a positive effect on organ-izations’ acceptance of social networking sites.

2.2. Intangible Assets of Retail Franchise and Restaurant Social Networking Sites

 The SERVQUAL study suggests that reliability and com-petence are key dimensions of which services are evaluated for quality (Parasuraman, Zeithaml, & Berry, 1988). Online service providers will potentially be able to provide more timely trades and feedback. Rapid execution and feedback provide consumers with instant gratification, which is a key component of utility de-rived from Internet websites and social networking sites (Bonnin, 2009; Lee, Brahmasrene, & Kim, 2009). The act of observing the social networking site’s execution of transactions and the ability to communicate instantly to make decisions can lead to consumers’ engagement and satisfaction. It can directly be influ-ential in initiating the service experience, enhancing the percep-tions of service benefits and promoting user behavioral in-tentions (Bonnin, 2009; Lee, Brahmasrene, & Kim, 2009).  

 Shopping relevance and production quality, regarded as an-other part of intangible assets of online retailers, have significant influence on customers’purchasing behavior. Baier and Stüber (2010) reported that shopping relevance and production quality had an influence on consumer acceptance of online purchasing. Oestreicher and Sundararajan (2012) reported that on average the explicit visibility of a co-purchase relationship could cause up to an average three times amplification of the influence that complementary products have on the demand levels. O’Cass and Fenech (2003) reported that online shopping customer behavior would be influenced differently by web shopping compatibility, perceived web security, satisfaction with websites and shopping orientation. They suggest that online retailers should focus on the opinion leadership trait, web shopping compatibility and sat-isfaction to certify complete perceptions of usefulness of online retailing. Griffis, Rao, Goldsby and Niranjan (2012) reported that the returns management process in online retailing could pos-itively affect repurchase behavior. Hence, retailers should put cer-tain customers in the prioritizing position in the returns process.

 More and more studies proved the influence of intangible as-sets to consumer behavior in the retail sector (e.g., Baier & Stüber, 2010; Griffis et al., 2012). There are growing interests in understanding how word-of-mouth on the Internet is generated and how it influences consumer purchase decisions at the on-line retailing environment. Through researching the movie in-dustry, Duan, Gu and Whinston (2008) reported that word-of-mouth was significantly impact both box offices’ revenue and volume, which consequently caused higher box office sales and created better retail profit. A unique aspect of the word-of-mouth effect is the presence of a positive feedback mechanism between word-of-mouth and retail sales. Ahn, Ryu and Han (2007) reported that playfulness was very important in improving users’opinions and behaviors to explore a website. Additionally, they reported that web quality and information and service quality played an important role on the perceived play-fulness in web-based online retailing. Laroche (2010) reported that privacy concerns, trust and attitudes toward a retail com-pany’s website played an important role on the perceived value in web-based online retailing. 

 The intangible assets of social networking sites mostly refer to perceived service quality, such as prompt service, positive feedback mechanism, reputation, word-of-mouth, trust, security and privacy etc. Thus, the current study assumes that organiza-tional benefits are positively associated with the perceived value of intangible assets, and thus the perceived intangible assets have a positive effect on organizations’ acceptance of social networking sites. In summary, the following hypotheses are gen-erated for verification based on the discussion raised above:

 Hypothesis 3: Organizational benefits are positively associated with the perceived value of intangible assets of social networking sites.

 Hypothesis 4: Intangible assets have a positive effect on organ-izations’acceptance of social networking sites.

 Hypothesis 5: Organizational benefits have a positive effect on or-ganizations’ acceptance of social networking sites.

3. Research Method

3.1. Survey and Sample Characteristics

 An initial structured questionnaire was developed based on a study of existing literature (e.g., Bonnin, 2009; Lee, Brahmasrene, & Kim, 2009; Parasuraman, Zeithaml, & Berry, 1988) and the model’s hypotheses with 13participants of focus group interviews. The initial questionnaire included 23 items re-lated to various constructs discussed in this study and 6 items that capture information of respondent demographics such as gender, age, retail franchise and restaurant location, job position title, work experience in the retail franchise and restaurant in-dustry, and experience of using social networking sites. To measure employees’perceptions and their behavioral intention in acceptance of social networking sites, a seven-point Likert type scale is used in this study. Hence, the response options in this research are ranging from (1) strongly disagree, and (4) neutral, to (7) strongly agree, see Appendix. 

 A web-based survey was conducted with the Korea Franchise Association. The questionnaire was electronically mailed to 1000 recipients from an email list of the Korea Franchise Association (253 member franchises are registered to the Association as of December 31, 2011). Of 484 filled in questionnaires in the web-based survey, 160 cases were removed from the dataset because they have missing data or outliers. The final sample size was 324 cases that have no missing data and they were used for following analyses. Table 1 presents descriptive sta-tistics of survey and sample characteristics. 

 

<Table 1> Survey and Sample Characteristics

 

3.2. Factor Analysis and Internal Consistency Reliability Test

 Evidence of the effectiveness of a scale for its purpose is examined. Construct validity embraces a variety of techniques for assessing the degree to which an instrument measures the concept that it is designed to measure. In order to ensure the construct validity of the measurement instrument, factor analysis was employed in a two-stage process. First, exploratory factor analysis with a varimax rotation procedure was employed to identify underlying predictors based on an eigenvalue cut-off of one. Second, confirmatory factor analysis using structural equa-tion modeling techniques was employed to confirm that the identified predictors are fitted the items correctly and reliably.  

 To identify underlying predictors of acceptance of social net-working sites, factor analysis with a varimax rotation procedure was employed. The component factor analysis was used to un-cover the underlying structure of a large set of items and identi-fied four components: component one with five items (eigenvalue = 3.815), component two with five items (eigenvalue = 3.447), component three with four items (eigenvalue = 3.197), and component four with four items (eigenvalue = 2.255). This resulted in the retention of 18 items, which represented the four components. Afterward, the four components were used for fol-lowing analyses. To test the appropriateness of the factor analy-sis, the two measures - the Kaiser-Meyer-Olkin and the Bartlett’s test - were used. The Kaiser-Meyer-Olkin overall meas-ure of sampling adequacy of 0.881 falls within the acceptable significant level at p < 0.01. The Bartlett’s test of sphericity of 3804.820 at 153 degree of freedom shows a highly significant correlation among the survey items at p < 0.01. The sums of squared loadings from the four components have the cumulative value of 70.629 percent in explaining the total variance of the data. The results of exploratory factor analysis using principal component analysis extraction method are reported in Table 2.

 Internal consistency reliability is a measure of how well a test addresses different constructs and delivers reliable scores.  For example, in a series of questions that ask the subjects to rate their response between one and seven, Cronbach’s alpha gives a score between zero and one, with 0.7 and above being reliable.  The test also takes into account both the size of the sample and the number of potential responses. The Cronbach’s alpha test is preferred in this study due to the benefit of aver-aging the correlation between every possible combination of split halves and allowing multi-level responses. For example, the sur-vey items are divided into the four constructs. The internal con-sistency reliability test provides a measure so that each of these particular constructs is measured correctly and reliably. The results of internal consistency reliability tests for the four constructs of acceptance of social networking sites are reported as follow: tangible assets (4 items, α = 0.776), intangible assets (5 items, α = 0.899), organizational benefits (5 items, α = 0.882), and acceptance of social networking sites (4 items, α = 0.892). The detailed results of internal consistency reliability tests, including item-total correlation coefficient values, are re-ported in Table 2.

 In addition, confirmatory factor analysis using structural equa-tion modeling techniques was employed to confirm that the identified predictors are fitted the items correctly and reliably. The results of confirmatory factor analysis indicated that a single factor solution fitted the items acceptably and the corrected item-total correlation value of each item to the construct is pre-sented in Table 2.

 

<Table 2> Results of Factor Analysis for Survey Question Items

 

<Table 3> Structural Equation Model Estimates

Note: Numbers in the cells are standardized coefficient values.
         Probability values for rejection of the null hypothesis of zero coefficient are employed at the 0.05 level (*** p < 0.01).

 

4. Results

4.1. Structural Equation Model Estimates and Path Diagram

 The analysis of moment structures was used for an empirical test of the structural model. The maximum likelihood estimation was applied to estimate numerical values for the components in the model. In the process of identifying the best fit model, multi-ple models were analyzed because the researchers were testing competing theoretical models. From a predictive perspective, we determine which model fits the data best, but sometimes the dif-ferences between the models appear small on the basis of the fit indexes. When comparing non-nested models, the Akaike in-formation criterion fit index is used as our first choice because the difference in the Chi-square values among the models can-not be interpreted as a test statistic (Kline, 2005), the root mean square of approximation fit index as our second choice, and then the goodness of fit index as our third choice. 

 The results of the analysis of moment structures generally achieve acceptable goodness-of-fit measures, see Table 3. For example, the index of the goodness of fit index (= 0.929) in-dicates that the fit of the proposed model is about 93% of the saturated model (the perfectly fitting model). The index of the normed fit index (= 0.941) indicates that the fit of the proposed model is about 94%. Table 3 displays the estimates of accept-ance of social networking sites using the structural equation model. The other goodness-of-fit measures are as follow:

 Model fit summary: the minimum value of the sample discrep-ancy, CMIN (=639.241), degree of freedom, DF (= 131), CMIN/DF (= 4.880). 

 Model fit measures: the goodness of fit index, GFI (= 0.929), the adjusted goodness of fit index, AGFI (= 0.917), the parsi-mony goodness of fit index, PGFI (= 0.897), the root mean square residual, RMR (= 0.036), the root mean square of ap-proximation, RMSEA (= 0.025).

 Baseline comparisons measures: the Bentler-Bonett normed fit index, NFI (= 0.941), the Bollen’s relative fit index, RFI (= 0.925), the Tucker-Lewis coefficient index, TLI (= 0.947), the comparative fit index, CFI (= 0.969). 

 Parsimony-adjusted measures: the parsimony ratio, PRATIO (= 0.916), the parsimony normed fit index, PNFI (= 0.828), the parsimony comparative fit index, PCFI (= 0.844). 

 The estimate of the non-centrality parameter, NCP (= 508.241), the Akaike information criterion, AIC (= 719.241), the Browne-Cudeck criterion, BCC (= 724.241) and the Bayes information criterion, BIC (=870.472).

 In testing hypothesis 1 that there is relationship between or-ganizational benefits and tangible assets, Table 3 shows that there is a positive relationship between perceived organizational benefits and perceived tangible assets, which shows statistically significant at a 95% confidence level (p < 0.01). This suggests that perceived organizational benefits have a positive and direct effect on the perceived value of tangible assets of social net-working sites. The hypothesis 2 tests a relationship between tangible assets and acceptance of social networking sites. Table 3 shows that there is a positive relationship between perceived tangible assets and acceptance of social networking sites, but is insignificant (p > 0.05). This suggests that perceived organiza-tional benefits have a positive effect on the perceived value of tangible assets of social networking sites, but does not directly affect organizations’ acceptance of social networking sites.

 In testing hypothesis 3 that there is relationship between or-ganizational benefits and intangible assets, Table 3 shows that there is a positive relationship between perceived organizational benefits and perceived intangible assets, which shows statisti-cally significant at a 95% confidence level (p < 0.01). The hy-pothesis 4 tests a relationship between intangible assets and acceptance of social networking sites. Table 3 shows that there is a positive relationship between perceived intangible assets and acceptance of social networking sites, and is statistically significant at a 95% confidence level (p < 0.01). This suggests that perceived organizational benefits have a positive and direct effect on the perceived value of intangible assets and thus the perceived intangible assets have a positive and direct effect on organizations’ acceptance of social networking sites.

 The hypothesis 5 testing of relationship between perceived organizational benefits and acceptance of social networking sites shows a significant positive relationship at a 95% confidence level (p < 0.01). This means that perceived organizational benefits have a positive propensity towards acceptance of social networking sites in their marketing activity. Overall, perceived or-ganizational benefits and perceived intangible assets of social networking sites serve as important antecedents of acceptance of social networking sites. Figure 1 displays a path diagram of acceptance of social networking sites. 

 

<Table 4> One-way Analysis of Variance by Job Position Titles

Note: Numbers in the cells are standardized mean values.
         Probability values for rejection of the null hypothesis of no mean difference are employed at the 0.05 level (** p < 0.05).

 

Note: Coefficient is statistically significant at a 95% confidence level (*** p < 0.01).
<Figure 1> Path Diagram of Acceptance of Social Networking Sites

 

4.2. Demographic Differences in Acceptance of Social Networking Sites

 One-way analysis of variance was conducted to compare means of the four constructs by job position titles. Table 4 re-veals statistically significant mean differences between job posi-tion titles in their perception of tangible assets and acceptance of social networking sites (p < 0.05), whereas it shows insignif-icant mean differences (p > 0.05) in terms of their perception of organizational benefits and intangible assets. Further, the result shows that retail and restaurant employees with higher position titles have a positive propensity in perceiving highly tangible as-sets and their acceptance of social networking sites. 

5. Discussion and Conclusion

 The results from an empirical analysis support most of the hypotheses. First conclusion from current study indicates that the organizational benefits have significant influence on the per-ceived value of tangible assets and intangible assets of social networking sites. In reality, social networking sites are rapidly emerging as popular sources of retail franchise and restaurant information especially for teens and young adults. Marketing ac-tivities via social networking sites carry out the advantages of low cost, rapid transmission through a wide community, increas-ing opportunities of customer involved marketing communication and customer interaction. For example, online customer service or the hot lines of social networking sites are major tools for re-tail franchise and restaurant social networking site operators to collect customer expectations. Retail franchise and restaurant business operators should recognize the importance of social networking sites and their potential usefulness for disseminating retail franchise and restaurant information. Much more needs to be known and shared about how best to use social networking sites to achieve marketing promotion outcomes.

 Second, the current study shows that organizational benefits and the perceived value of intangible assets should be viewed as important antecedents explaining behavioral intentions to use social networking sites. Nowadays, the major part of intangible assets of social networking sites, such as trust, privacy of per-sonal information and internet information security, play an im-portant role when consumers choose social networking sites. Accordingly, consumers would choose social networking sites as a tool for gathering information for retail franchise and restaurant information only if they trust the information provider. In addition, consumers should rest assured that they receive full information in a safe and timely manner that complies with current practice guidelines. A lot of people use Facebook.com and Yelp.com, which are the largest social networking sites because of the ef-ficiency and trust of the information sharing. So it is under-standable that intangible assets of social networking sites have a significant impact on the customer behavioral intention. 

 Further, the result shows that employees with higher position titles have a positive propensity in perceiving highly the value of tangible assets of social networking sites and their behavioral intention to accept social networking sites. They usually pursue higher quality of personal life with high efficiency and quality of information collecting and sharing. People with higher position ti-tle have such a tendency to catch up with the updated wave of technology. As a result, they have higher request of modern technology using tangible assets of social networking sites when accepting social networking sites.

 The finding of this research shows that the success of retail franchise and restaurant business operators via social network-ing sites depends not only on the perceived value of organiza-tional benefits and intangible assets but also on their behavioral intention of accepting social networking sites. However, future research to generalize these findings is required to determine whether there is a consistent pattern. 

Figure

Table

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