Personal values and mall shopping behavior: The mediating role of attitude and intention among Chinese and Thai consumers

Australasian Marketing Journal 20 (2012) 37–47

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Personal values and mall shopping behavior: The mediating role of attitude and intention among Chinese and Thai consumers Yuanfeng Cai ⇑, Randall Shannon 1 College of Management, Mahidol University, 69 Vipawadee Rangsit Road, Din Daeng, Bangkok 10400, Thailand

a r t i c l e

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Article history: Available online 13 November 2011 Keywords: Personal values Mall attitude Mall attributes Shopping intention Mall shopping behavior Retailing

a b s t r a c t Personal values are important determinants of consumer behavior. While previous research has identified values (i.e., openness to change and self-enhancement) which guide consumers’ mall shopping behavior, they have been set in a Western cultural context. By adopting a value–attitude–behavior (VAB) model, this study examines what and how personal values influence consumers’ mall shopping behavior in two non-Western countries, namely China and Thailand. The results confirm the existence of the causal flow of VAB. Chinese are guided by self-transcendence and self-enhancement values, whereas Thais are guided by openness to change values. Shopping intention is found to mediate the attitude–behavior link in the Chinese sample and improves the predictive power of values towards behavior. Although a relatively weaker mediating effect is found in the Thai sample, shopping intention does not lead to stronger predictive power of values. Ó 2011 Australian and New Zealand Marketing Academy. Published by Elsevier Ltd. All rights reserved.

1. Introduction Over the decades, it has widely been acknowledged that personal values can serve as grounds for behavioral decisions in consumption behavior (Costa et al., 2004; Tai, 2008; Koo et al., 2008; Doran, 2009; Durvasula et al., 2011). Consumption behaviors are viewed as a means to achieving desired end-states or values (Michon and Chebat, 2004; Wagner, 2007). However, the major criticism of examining a simple relationship between values and behavior is that values are relatively abstract, thus are viewed as distal determinants of behavior that can only affect behavior through a number of less abstract or more proximal determinants, like attitudes and beliefs (e.g., Homer and Kahle, 1988; McCarty and Shrum, 1994; Thogersen and Grunert, 1997; Shim and Eastlick, 1998; Shim and Maggs, 2005; Hartman et al., 2006). Accordingly, a value–attitude–behavior (VAB) hierarchy was developed and has been validated in healthy food consumption (Homer and Kahle, 1988; Grunert and Juhl, 1995), environmental behavior (McCarty and Shrum, 1993; Thogersen and Grunert, 1997), and more recently, e-shopping behavior (Jayawardhena, 2004). However, the testing of the model in a mall setting is relatively new and has been limited (Shim and Eastlick, 1998). Although several researchers have identified what underlying values may determine consumers’ mall shopping behavior (Roy, 1994; Shim and ⇑ Corresponding author. Tel.: +86 159 593 68508. E-mail addresses: [email protected] (Y. Cai), (R. Shannon). 1 Tel.: +66 2 206 2000.

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Eastlick, 1998; Swinyard, 1998; Thompson and Chen, 1998; Erdem et al., 1999; Stoel et al., 2004), few have systematically articulated how these values influence mall shopping behavior with theoretical support. Additionally, as the findings of these studies are mainly derived from a Western context, it is unclear whether similar values and patterns in which values influence behavior will be found in a non-Western context. It is also unclear whether similar findings will be found across two nations that share similar cultural backgrounds. In their study, Shim and Eastlick (1998) replicate Homer and Kahle’s (1988) work, and find that compared with the previous study, the link between attitude and behavior is weaker in a mall setting, which implies the existence of additional factors which may influence this relationship, given the contextual nature of mall shopping behavior. Therefore, in an attempt to bridge these gaps, this study tests the previously developed VAB model to examine what and how personal values influence consumers’ mall shopping behavior in China and Thailand. This study seeks to improve the VAB model by exploring the mediating effect of shopping intention and attitudes. This study contributes to the existing mall shopping literature at the theoretical and practical levels in the following ways. First, this study tests the theory developed in the West in two nonWestern countries (i.e., China and Thailand). Second, although previous studies have examined the attitude–intention (Bagozzi et al., 2000; Ajzen, 2008) and attitude–behavior/intention relations (Teng et al., 2007; Kim and Chung, 2011), to the best knowledge of the authors, no study has put personal values, attitude, intention and behavior into the same model in a mall setting. Third, no study has investigated differences in mall shopping behavior among

1441-3582/$ - see front matter Ó 2011 Australian and New Zealand Marketing Academy. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.ausmj.2011.10.013

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Y. Cai, R. Shannon / Australasian Marketing Journal 20 (2012) 37–47

consumers in China and Thailand, two countries which share a similar cultural background. Fourth, the findings of this study can help mall managers to craft effective competitive marketing strategies by meeting consumers’ wants and needs at a deeper level. Bachrach (1995) proposes that understanding the underlying personal values that guide consumers’ mall shopping behavior will enable mall managers to win their shoppers emotionally and gain their trust relatively more easily. 2. Theoretical background and hypotheses A previous study in a Western context suggests that personal values are determinants of consumers’ mall shopping behavior, however, values only influence behavior indirectly through the mediating effect of attitude (Shim and Eastlick, 1998). Values are culturally determined (Rokeach, 1973), thus it is proposed that although a similar causal flow will be found in a non-Western context, values that predict mall shopping behavior of Western shoppers may be different from the ones that predict Chinese and Thai shoppers’ behavior, given their sharp differences in cultural backgrounds. It is argued that in addition to attitude, other factors may also exist to influence the value–behavior relationship, as mall shopping is a contextual-driven behavior (Shim and Eastlick, 1998). Extant literature suggests that compared with attitude, shopping intention is a closer cognitive antecedent of behavior (e.g., Fishbein and Ajzen, 1975; Fisher and Fisher, 1992; Gollwitzer, 1993). Therefore, it is argued that the VAB model may be improved by considering the mediating effect of shopping intention. Accordingly, a hypothesized model is developed. As shown in Fig. 1, the model outlines the indirect relationship between personal values and mall shopping behavior through the mediating effect of attitude and shopping intention. In the following section, the relationship between each pair of constructs and relevant hypotheses will be discussed. 2.1. Value, attitude and behavior A value is defined as ‘‘an enduring belief that a specific mode of conduct or end-state of existence is personally or socially preferable to an opposite or converse mode of conduct or end-state of existence’’ (Rokeach, 1973, p.5). Consistent with the notion that ‘‘all shopping centers are to some degree leisure centers’’ (Howard, 2007, p.668), Western consumers’ mall shopping behavior has been found more likely to be motivated by social and/or recreational needs (Sit et al., 2003; Ruiz et al., 2004; De Nisco and Napolitano, 2006; Maronick, 2007; Lotz et al., 2010). Driven by these needs, Roy (1994) proposes that affiliation, power, or stimulation are specific values that are positively correlated with mall shopping

Selftranscendence H1

Conservation

H1 H1, H2

Attitude

Behavior

H2

Openness to change

H3, H4

H3, H4

H2

Selfenhancement

Intention

Fig. 1. Hypothesized model.

behavior. In a more systematic study, Shim and Eastlick (1998) find consumers who exhibit stronger social affiliation (i.e., fun and enjoyment and friendly relationship) and self-actualizing values (i.e., self-fulfillment, sense of accomplishment and self-respect) are more likely to stay longer and spend more money in the mall. Similarly, Swinyard (1998) argues that frequent mall shoppers tend to place more importance on both self-actualizing and social affiliation values (i.e., ‘sense of belonging’, ‘warm relationships’, ‘security’ and ‘excitement’ values). More recently, Michon and Chebat (2004) find French-speaking and English-speaking Canadian mall shoppers are guided by hedonic values. Other researchers propose a positive effect of hedonic values on perceived mall image (Thompson and Chen, 1998; Erdem et al., 1999) and shopping intention (Stoel et al., 2004). In terms of Schwartz’s (1992) value scale, the social affiliation dimension of values (fun and enjoyment and friendly relationship) are similar to the openness to change dimension (self-direction, stimulation and hedonism); while the self-actualizing dimension (self-fulfillment, sense of accomplishment and self-respect) are similar to the self-enhancement dimension of values (power and achievement). In terms of Schwartz’s (1992) value scale, Western consumers’ mall shopping behavior is more likely to be influenced by openness to change and self-enhancement values. Western countries tend to share individualistic cultural values (Hofstede, 1980). Several scholars propose that consumers from individualistic cultures are more hedonic than individuals from collectivistic cultures (Schwartz, 1992; Triandis, 1993; Kacen and Lee, 2002). Given that values are culturally determined (Rokeach, 1973), as a collectivist country, it is reasonable to assume that the openness to change and self-enhancement values may not be used to determine Chinese consumers’ mall shopping behavior. Schwartz (1992, 1994) and Triandis (1993) suggest that members of collectivistic societies tend to place the highest value on selftranscendence and conservation values (the two dimensions that are conflicting with the self-enhancement and openness to change dimensions of values respectively). Roth (1995) argues that markets with low individualism value products to fulfill social or functional needs to reinforce group membership and affiliation or reduce the risk of not being accepted. Chinese mall shoppers are more likely to shop for a singular utilitarian reason rather than hedonic or social reasons (Tse et al., 1989; Tse, 1996; Li et al., 2004). Thus, Chinese shoppers may view shopping at the mall as a utilitarian task, rather than a place for leisure activities. Therefore, Chinese shoppers will be more likely to be guided by self-transcendence and conservation values, the two values that are more likely to guide the utilitarian-oriented shopping behavior. Similarly, as a collectivistic oriented country, Thai consumers’ mall shopping behavior should also be guided by self-transcendence and conservation values. However, based on an ethnographic study, Phillips (1966) proposes that mai pen rai and sanuk, as two important Thai values, have made Thais more individualistic than they are widely assumed. This is supported by Punyapiroje (2002), who finds individualism exists within Thai culture. The value of mai pen rai (literally, something doesn’t matter) suggests that adverse outcomes will get better eventually, so one should not worry about them (Warner, 2003). The value of sanuk (literally, fun and joy) reflects that Thais tend to view life as full of fun and joy and not to be taken too seriously, even in the context of work (Warner, 2003). In addition, influenced by Buddhist teachings, Thais exhibit a strong present orientation. Several scholars have noted their tendency to seek present or immediate gratification (Skinner, 1962; Slagter and Kerbo, 2000). Chetthamrongchai and Davies (2000) propose that hedonic shoppers score relatively high on present orientation, indicating that they are more concerned with what is happening now than in the past or in the future. Taken together, it is suggested that while Thailand is also a

Y. Cai, R. Shannon / Australasian Marketing Journal 20 (2012) 37–47

collectivistic culture, Thai shoppers may view shopping at the mall as a leisure activity rather than a chore. Therefore, Thai consumers’ mall shopping behavior will be more likely to be guided by openness to change and self-enhancement values. Extant literature suggests that values, given its abstract nature, only influence consumer behavior indirectly through some less abstract mediating factors (e.g., Kahle, 1980; Homer and Kahle, 1988; Shim and Eastlick, 1998). Attitudes have been found to be mediating factors which help explain the value–behavior link (Kahle, 1980; Pitts and Woodside, 1983; Homer and Kahle, 1988; Shim and Eastlick, 1998). In the present study, attitude refers to consumers’ attitude toward salient mall attributes; shopping behavior refers to shopping frequency, money spent in the mall and time spent in the mall during the mall visit. It is hypothesized that: H1: In the Chinese sample, the influence of personal values (i.e., self-transcendence and conservation) on consumers’ shopping frequency (H1a), money spent in the mall (H1b), and time spent in the mall (H1c) is mediated by their attitude toward salient mall attributes. H2: In the Thai sample, the influence of personal values (i.e., openness to change and self-enhancement) on consumers’ shopping frequency (H2a), money spent in the mall (H2b), and time spent in the mall (H2c) is mediated by their attitude toward salient mall attributes. 2.2. Attitude, intention and behavior Although the mediating effect of attitude on the value–behavior link has been verified (Pitts and Woodside, 1983; Homer and Kahle, 1988; Shim and Eastlick, 1998), a number of theorists have proposed that the intention to perform a behavior, rather than attitude, is the closest cognitive antecedent of actual behavioral performance (e.g., Fishbein and Ajzen, 1975; Fisher and Fisher, 1992; Gollwitzer, 1993). This is because the performance of a specific behavior can perhaps be best explained by considering the proximal attitude toward the behavior rather than more distal attitude toward the object at which the behavior is directed (Shim and Maggs, 2005; Hartman et al., 2006). Warshaw and Davis (1985) define intention as ‘‘the degree to which a person has formulated conscious plans to perform or not perform some specified future behavior’’ (p. 214). Several metaanalyses of the empirical literature have provided evidence to show that intention can be predicted with considerable accuracy from measures of attitude toward the behavior (e.g., Sheppard et al., 1988; Ajzen, 2008). Evidence concerning the relationship between intentions and behaviors/actions has been collected with respect to many different types of behaviors (see Sheppard et al., 1988, for a comprehensive review). Meta-analyses covering diverse behavioral domains have reported mean intention–behavior correlations of .47 (Notani, 1998; Armitage and Conner, 2001), .53 (Sheppard et al., 1988), .45 (Randall and Wolff, 1994), and .62 (van den Putte, 1993). The literature review above suggests that attitude can either directly or indirectly (through intention) influence behavior. In order to further understand this enigmatic phenomenon, Bagozzi et al. (1990) identify specific conditions that cause intention to mediate the attitude–behavior relation through an experimental method. They find that the level of effort needed to perform a behavior moderates the role of intention in the attitude–behavior relationship. When a specific behavior requires a high level of effort, the mediating effect of intention is strong, thus no direct relationship could be found between attitude and behavior. On the other hand, when the level of effort required for the behavior is little, the mediating role of intention reduce, attitude could directly predict the behavior (Bagozzi et al., 1990). The findings are further supported by Schultz and Oskamp (1996) in their study about general

39

environmental concern and recycling and also the study conducted by Bagozzi and Yi (1989). Chinese mall shoppers have been found more likely to be utilitarian-driven (Tse et al., 1989; Tse, 1996; Li et al., 2004). Utilitarian shoppers tend to view shopping as work or a burden rather than fun (Rao and Monroe, 1989; Sherry, 1990; Nicholls et al., 2000), and they are more time conscious than recreational shoppers (Hansen and Deutscher, 1977/78; Bellenger and Korgaonkar, 1980; Wilson and Holman, 1984). Thus, it is assumed that deliberate conscious evaluation concerning the mall visit will be required for them to make the visit decision. Consequently, the intention to shop will be more likely to form as the end result of the evaluation of the behavior. H3: In the Chinese sample, the influence of consumers’ attitude toward mall attributes on their shopping frequency (H3a), money spent in the mall (H3b), and time spent in the mall (H3c) is mediated by their shopping intention. As more hedonic-driven shoppers, Thais may view shopping more as fun rather than a burden, thus less effort will be required for making the mall visit decision. Thus: H4: In the Thai sample, the influence of consumers’ attitude toward mall attributes on their shopping frequency (H4a), money spent in the mall (H4b), and time spent in the mall (H4c) is not mediated by their shopping intention. 3. Research methodology 3.1. Questionnaire development A survey questionnaire was developed based upon a comprehensive review of related literature. The questionnaire was written in English and translated into Chinese and Thai and then backtranslated into English by three independent, professional, bilingual translators to ensure consistency and translation equivalence (Douglas and Craig, 1983; Hui and Triandis, 1985). Original and back-translated versions were compared for equivalence and measures were refined where necessary (Frey, 1970). The questionnaire was then pre-tested using a convenience sample of 30 respondents in each country. After completion, suggestions and comments were collected from respondents to identify potential errors in terms of the wording, phrasing and sequencing of questions, which were then corrected. Items with similar meaning which could not be clearly distinguished across both Chinese and Thai were also eliminated. The 30 respondents in the pilot test were then excluded from the final data set. 3.2. Measures Previous studies have adopted the list of values (LOVs) to measure personal values (e.g., Homer and Kahle, 1988; Shim and Eastlick, 1998). Nevertheless, LOV has been criticized for not being a stable instrument when applied across cultures (Watkins and Gnoth, 2005). It is too broad to measure specific shopping behavior (Hansen, 2008). Therefore, this study adopts the Schwartz Value Survey (SVS) (Schwartz, 1992) to measure personal values as it (1) exhibits both external and convergent validity (Bond and Smith, 1996); (2) uses both Western and non-Western sources to derive cultural value dimensions; (3) controls for meaning equivalence (Schwartz, 1999). Due to space constraints, a shortened version of Schwartz’s Value Survey was adopted in the present study. Twenty-two items were selected from the original 57-item Schwartz Value Survey (SVS) (Schwartz, 1992) to measure personal values. The SVS can be categorized into two value dimensions with ten value types: self-enhancement (power, achievement) to self-transcendence

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Y. Cai, R. Shannon / Australasian Marketing Journal 20 (2012) 37–47

(universalism, benevolence), and openness to change (stimulation, hedonism, self-direction) to conservation (tradition, conformity, security). The 22 values chosen for the shortened survey were employed from a pro-environmental study (Kim, 2002), which was developed based on three previous studies (Maio and Olson, 1995; Stern et al., 1995; Schultz and Zelezny, 1998). Respondents were asked to rate each item on a 9-point unipolar scale with the end points ‘‘not important at all’’ and ‘‘of decisive importance as a guiding principle in my life.’’ The respondents were instructed to read the list of values first, then list out the value that was most important to them, and then list out the value most opposed to their values. They were then required to rate the remaining values based on their importance. Consistent with a previous study (Shim and Eastlick, 1998), attitude was assessed using the multivariate attribute model (Fishbein and Ajzen, 1975). Based on the comprehensive literature review (e.g., Bellenger et al., 1977; Wong et al., 2001; Sit et al., 2003) and the results of a focus group among five respondents in China, 22 salient mall attributes were selected to measure respondents’ attitude toward shopping malls. Due to time and budget constraints, a focus group was not conducted in Thailand, but respondents in the pilot test were interviewed briefly to gain their comments regarding the mall attributes list. No additional attributes were required to add to the existing list. These attributes cover categories like merchandising, service, accessibility, entertainment, and atmospherics. Based on mean ratings, the ten most important attributes were selected to represent the most salient attributes (Engel et al., 1993; Shim and Eastlick, 1998). Respondents were first asked to indicate the importance of each mall attribute, using a 6-point scale (1 = extremely unimportant; 6 = extremely important), they were then asked to indicate the extent to which the mall that they shop at the most frequently was perceived to be similar or different for each of these characteristics along another 6-point scale (1 = strongly disagree; 6 = strongly agree). A six-point scale was adopted because of the potential problem of courtesy-bias on the part of Asian respondents (Ayer, 1970), who tend to select the middle path to maintain harmony, which can result in a high number of neutral responses. Belief ratings for each attribute were multiplied by respective importance ratings to provide an expectancy-performance measure of each attribute (i.e. attitude toward mall attributes). This approach has a basis in theory proposed by Fishbein and Ajzen (1975, p. 223), which states ‘‘attitudes are based on the total set of the person’s salient beliefs and the evaluations associated with those beliefs.’’ Based on a meta-analysis on 87 studies, Sheppard et al. (1988) suggest that the intention–behavior relation is stronger when an estimation measure (e.g., It is likely/unlikely that I will do X) is used. Individual’s estimates are likely to include some consideration of needed resources, abilities, skills and experience, the cooperation of others, and so on. It appears that individuals do well when they try to estimate their own future performance of various goals, because intervening factors are taken into account as they attempt to estimate whether they will achieve their goals (Sheppard et al., 1988). Therefore, as an estimation measure for intention, Macintosh and Lockshin’s (1997) four items were employed in the present study. After the pilot test, one item was removed due to its similar meaning with other items. An example being ‘‘In the future, my shopping at this mall will be very likely.’’ In a previous study (Shim and Eastlick, 1998), shopping behavior is operationalized by calculating the average monthly expenditure at the mall. In this study, shopping behavior was assessed by examining consumers’ shopping frequency, money and time spent in the mall. It is expected that by doing so, the effect of personal values on specific types of shopping behavior can be examined, thus provide further insights to the researchers.

3.3. Sampling and data collection Given that the objective of this study is to derive theoretical generalizability, but not population generalizability, convenience sampling was employed. As street intercept surveys are prohibited in China, this study mainly utilized an online survey when collecting the data. The website of the questionnaire was posted at several big online communities in each country, where a large number of potential respondents could be accessed. In order to encourage participation, a cash drawing was provided. A smaller number (around 25%) of hard-copy surveys were distributed at the same period of time to minimize potential sampling bias (Schaefer and Dillman, 1998; Illieva et al., 2002). A total of 643 usable questionnaires were obtained, with 320 in China, and 323 in Thailand, for a response rate of 30–40% in each country. Fewer usable surveys were obtained in China because many respondents did not understand what a shopping mall is, confusing it with other shopping venues such as department store, great merchandiser or anchor supermarket within a shopping mall, likely because the format is relatively new. After cleaning and editing the data, the final number of questionnaires with no missing values for all variables under analysis was 305 in China, and 308 in Thailand. 3.4. Respondent characteristics As shown in Table 1, two-thirds of the respondents in both countries are female and single. A large proportion of them (90%) fall between the 20 and 38 year age range. More than half the respondents have a bachelor’s degree or higher and hold white-collar positions. Around 45% of respondents have moderate monthly income between 2000 and 6000 Yuan (or 10,000–30,000 Baht). Compared with Chinese respondents, Thai respondents are slightly older (p = .000), as about half (57%) of Chinese respondents are aged between 20 and 26, while half (53%) of Thais are aged between 27 and 38. As Thai respondents are relatively older than their Chinese counterparts, perhaps they are also better educated and more affluent than Chinese respondents (p = .000). 4. Results Before running the measurement model, a principal component factor analysis using varimax rotation was first conducted to identify underlying dimensions of personal values (Homer and Kahle, 1988; Shim and Eastlick, 1998; Jayawardhena, 2004). This was due to three reasons: (1) the importance of personal values dimensions tend to vary due to situational factors in different contexts (Kahle, 1983; Homer and Kahle, 1988; Beatty et al., 1991); (2) it is suggested that resultant factors should be used in a causal modeling technique (Kahle and Kennedy, 1989) to avoid single-item measurements that are frequently raised in value surveys (Braithwaite and Scott, 1991); (3) the running of EFA is regarded as a necessary procedure prior to assessing reliability of multi-item constructs (Anderson and Gerbing, 1988). Three and four factors were extracted from the factor analysis results, explaining 54.8% and 56% of variance for the Chinese and Thai samples, respectively. 4.1. Measurement model results SPSS 16.0 and structural equation modeling via AMOS 17.0 were used to test the hypotheses for both countries. Before proceeding with structural equation modeling (SEM), confirmatory factor analysis (CFA) was performed initially to validate the scales measuring the constructs (Hair et al., 2006). As shown in Tables 2 and 3, the results of the measurement model in both samples indicate that

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Y. Cai, R. Shannon / Australasian Marketing Journal 20 (2012) 37–47 Table 1 Respondent profiles. Characteristic

China

Thailand

Gender (%) Male Female

33.8 66.2

28.2 71.8

56.7 38.7 3.9 0.7

31.8 52.9 10.1 5.2

65.9 31.1 0.3 2.6

77.3 21.4 1.0 0.3

Age (%) 20–26 years 27–38 years 39–50 years 51–67 years

old old old old

Marital Status (%) Single Married Divorced Others

Characteristic Education (%) Junior high and below High school Diploma Bachelor Master PhD Occupation (%) White collar Blue collar Student Private business Retired Unemployed Income (%) Under 2000 Yuan/10,000 Baht 2,000–4000 Yuan/10,000–20,000 Baht 4001–6000 Yuan/20,005–30,000 Baht 6001–8000 Yuan/30,005–40,000 Baht 8001–10,000 Yuan/40,005–50,000 Baht Above 10,000 Yuan/50,000 Baht

China

Thailand

0.7 5.9 23.9 62.0 5.6 2.0

0.3 1.0 2.9 52.9 41.6 1.3

67.2 3.9 19.3 4.6 0.3 4.6

64.3 0.6 19.2 13.6 0.3 1.9

31.8 30.8 20.3 6.2 6.2 4.6

17.2 23.7 15.6 13.6 8.8 21.1

Table 2 Factor loadings, reliability and related information for CFA (China, n = 305).

ST

Cronbach’s Alpha

Composite reliabilityb

AVEc

0.80

0.78

0.42

CON2 ST4 ST3 ST2 ST1 SE

0.62

0.66

0.62 OPEN3 OPEN2 OPEN1

ATT

0.62

0.82

0.79

0.83

–

0.599d 0.655 0.564 0.709 0.688

– 0.108 0.114 0.126 0.104

– 8.536 7.686 8.962 8.805

0.860d 0.522

– 0.166

– 3.874

0.637d 0.561 0.589

– 0.136 0.157

– 6.339 6.456

0.557d 0.698 0.646 0.685 0.592 0.687 0.655

– 0.130 0.158 0.154 0.148 0.150 0.141

– 8.738 8.335 8.637 7.875 8.654 8.403

0.668d 0.822 0.796

– 0.093 0.095

– 11.025 10.944

0.499 0.630 0.351

– – –

– – –

0.42

0.81

0.59

INTEN1 INTEN2 INTEN3 Behavior

Critical ratio (t value)a

0.36

ATT_MER1 ATT_MER3 ATT_MER4 ATT_SER5 ATT_ATM2 ATT_ATM6 ATT_ATM7 Intention

Std. error

0.51

SE4 SE3 OPEN

Std. factor loading

–

Frequency Money Time

–

ST: self-transcendence, SE: self-enhancement, OPEN: openness to change. a All t-tests were significant at p < .001. b Composite reliability assesses the internal consistency of items in a scale (Hatcher, 1994; Netemeyer et al., 2003). c Average Variance Extracted (AVE) assesses the amount of variance captured by an underlying construct in relation to the amount of variance resulting from measurement error (Hatcher, 1994). d The first k path for each construct was set to 1, therefore, no SEs or t-values are given.

the factor loadings of the latent variables are generally high and statistically significant (i.e., >.50, p < .001). The fact that all t-tests are significant indicates that all items are measuring the construct they are associated with. Convergent validity may be further evidenced if each indicator’s standardized loading on its posited latent construct is greater than twice its standard error (Anderson and

Gerbing, 1988). The results indicate that all items under investigation meet this requirement. Discriminant validity is demonstrated if both AVEs are greater than the squared correlation (Hair et al., 2006), and was met by both samples. As shown in Tables 2 and 3, the AVE for several variables are below .50 for both samples. Hatcher (1994) notes that ‘‘very often

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Y. Cai, R. Shannon / Australasian Marketing Journal 20 (2012) 37–47

Table 3 Factor loadings, reliability and related information for CFA (Thailand, n = 308). Cronbach’s alpha

Composite reliabilityb

AVEc

ST&CON ST1 ST2 CON1

0.69

0.70

0.44

SE SE2 SE3 SE4

0.66

OPEN OPEN1 OPEN2 OPEN3 OPEN5

0.70

ST ST3 ST6

0.63

Attitude ATT_SER2 ATT_MER3 ATT_MER2 ATT_ATM3 ATT_ATM7 ATT_ATM5 ATT_ATM6 ATT_MER4 ATT_SER5

0.86

Intention INTEN1 INTEN2 INTEN3

0.77

Behavior Frequency Money Time

–

0.67

0.70

0.65

0.86

0.79

Std. factor loading

Std. error

Critical ratio (t value)a

0.693d 0.660 0.627

– 0.136 0.149

– 7.819 7.701

0.531d 0.600 0.764

– 0.175 0.214

– 6.584 6.419

0.656d 0.526 0.681 0.560

– 0.115 0.139 0.124

– 6.861 7.841 7.158

0.556 0.819d

0.284 –

4.823 –

0.667 0.616 0.569 0.684d 0.669 0.651 0.668 0.548 0.714

0.115 0.098 0.088 – 0.089 0.100 0.096 0.114 0.097

10.378 9.664 8.978 – 10.406 10.161 10.394 8.669 11.028

0.522d 0.840 0.848

– 0.195 0.191

– 8.654 8.637

0.513 0.630 0.346

–

–

0.41

0.37

0.49

0.42

0.57

ST&CON: self-transcendence and conservation, ST: self-transcendence, SE: Self-enhancement, OPEN: openness to change. a All t-tests were significant at p < .001. b Composite reliability assesses the internal consistency of items in a scale (Hatcher, 1994; Netemeyer et al., 2003). c Average Variance Extracted (AVE) assesses the amount of variance captured by an underlying construct in relation to the amount of variance resulting from measurement error (Hatcher, 1994). d The first k path for each construct was set to 1, therefore, no SEs or t-values are given.

variance extracted estimates will be below .50’’ (p.331). Fortunately, AVE is not the only diagnostic measures to assess convergent validity. Given their acceptable composite reliability values (>.60) (Bagozzi and Yi, 1988), and item loadings (>.50), the convergent validity of the scales was established. Note that shopping behavior was operationalized by shopping frequency, money spent and time spent, which were all measured by single-item scale in the model, therefore, it was adjusted to reflect estimated variance. Using the level of reliability (.85) employed in previous studies (Joreskog and Sorbom, 1993; Shim and Eastlick, 1998), the error variance for the scale was estimated at .15 (1-reliability) (Hair et al., 2006, p.857). 4.2. Structural equation model results The value–attitude–behavior model was tested initially for the Chinese sample, the results indicated that the model demonstrates a moderately acceptable fit with the data (v2 = 372.941, df = 166, v2/df = 2.247, p = .000, GFI = .89, CFI = .86, RMSEA = .064). As shown in Fig. 2, after deleting the non-significant paths, the model yielded a v2 value of 237.220 (p = .000) with 117 degrees of freedom, v2/df of 2.028, and a GFI of .92, CFI of .91, RMSEA of .058. Both the GFI and CFI value were larger than the suggested cutoff of 0.9 (Hu and Bentler, 1999), the ratio of chi-square to degrees of freedom (v2/df) of 2.028 indicated a good model fit (Hair et al.,

Shopping frequency Self-transcendence

β = .23** γ = .57***

Mall attitude Self-enhancement

β = .18*

γ = .17*

Money spent β = .38***

Time spent Model of Fit

R 2 of Constructs χ2(df)

237.220 (117)***

Attitude

0.35

χ2/df

2.028

Money

0.17

GFI

0.92

Frequency

0.05

CFI

0.91

RMSEA

0.06

* p<.05

** p<.01

***p<.001

Fig. 2. Final structural model of the influence of values on, attitudes and mall shopping behavior (China, n = 305).

2006). A root mean square error of approximation (RMSEA) of 0.058 indicated an acceptable fit. According to Browne and Cudeck

Y. Cai, R. Shannon / Australasian Marketing Journal 20 (2012) 37–47

(1993), a RMSEA value of .05 indicates a close fit, and values up to .08 suggest reasonable fit. Overall, the model demonstrates an acceptable fit with the data. As hypothesized, personal values (i.e., self-transcendence and self-enhancement) have a positive influence on consumers’ attitude toward salient mall attributes (cST = .57, p < .001, cSE = .17, p = .018), and attitude in turn, has a positive effect on total money spent in the mall (bATT = .18, p = .025) and shopping frequency (bATT = .23, p = .002) (see Fig. 2). However, attitude does not have any effect on consumers’ time spent in the mall. The more Chinese consumers have favorable attitude toward salient mall attributes, the more likely they will visit the mall frequently and spend more money during their visit, but it is not likely that they will stay longer in the mall. It is found that consumers’ time spent in the mall has a positive influence on the amount of money spent during their visit (b = .38, p < .000). Compared with attitude (b = .18, p = .025), time spent in the mall has a stronger effect on consumers’ money spent in the mall. Therefore, H1a and H1b are supported, but H1c is not supported. In the Thai sample, the test of the value–attitude–behavior model indicated that the model yielded a v2 value of 423.916 (p = .000) with 246 degrees of freedom, a v2/df value of 1.723, and a GFI of .89, CFI of .89, RMSEA of .049. As can be seen from Fig. 3, after deleting non-significant paths, the model yielded a v2 value of 188.881 (p = .000) with 88 degrees of freedom, a v2/df value of 2.146, and a GFI of .92, CFI of .92, RMSEA of .06, which demonstrated an acceptable fit with the data. The significant path coefficients indicate that personal value (openness to change) has a positive effect on attitude (c = .18, p = .002), attitude, in turn, has a positive influence on money and time spent in the mall (bmoney = .21, p = .007; btime = .14, p = .04). However, attitude does not have any effect on shopping frequency. According to the results, attitude has stronger effect on consumers’ money expenditure rather than their time spent in the mall. In addition, it is found that similar to the Chinese sample, time spent in the mall also has a positive effect on money spent in the mall (b = .25, p = .001). Based on these results, the total effect of attitude on money spent (bmoney + btimebtime?money = .25) is greater than its direct effect (.21). Baron and Kenny’s (1986) procedure was then applied to formally test the mediating effect of attitude, the results suggested a complete mediation of attitude on money and time spent. Therefore, H2b and H2c are supported, while H2a is not supported. The value–attitude–intention–behavior model was then tested to justify hypothesis 3 for the Chinese sample. The final model yielded a v2 value of 486.214 (p = .000), with 225 degrees of freedom, GFI of .88, CFI of .86, RMSEA of .062. After deleting the non-significant paths, the model yielded a v2 value of 338.115 (p = .000), with 167 degrees of freedom, GFI of .90, CFI of .90, RMSEA of .058

γ =.18*

Openness To Change

Mall Attitude

β =.21**

β =.14*

Money Spent β =.25** Time Spent

Model of Fit R2 of Constructs χ2(df)

188.881

88

** *

Attitude

0.03

χ2/df

2.146

Time

0.02

GFI

0.92

Money

0.12

CFI

0.92

RMSEA

0.06

* p<.05 ** p<.01

*** p<.001

Fig. 3. Final structural model of the influence of values on, attitudes and mall shopping behavior (Thailand, n = 308).

43

(see Fig. 4). The model demonstrated an acceptable fit to the data. As hypothesized, attitude has a positive effect on consumers’ shopping intention (b = .47, p < .001), shopping intention has a positive influence on total money spent in the mall (b = .20, p = .009) and shopping frequency (b = .27, p < .001) (See Fig. 4). However, shopping intention has no effect on time spent in the mall. The results of the analysis suggest that the stronger the consumers’ intention to shop, the more likely they will visit the mall frequently and spend more money during their mall visit, but it is unlikely that they will stay longer in the mall. In order to formally examine the mediating effect of shopping intention, Baron and Kenny’s (1986) three-step procedure was adopted. Baron and Kenny’s (1986) procedure suggests researchers should test: (1) Y = f(X); (2) M = f(X); and then (3) Y = f(M,X), to examine if X’s effect on Y is mediated by M. The first step shows that attitude has a positive effect on shopping frequency (p < .001) and money spent (p < .05), given the absence of shopping intention. The second step shows that attitude has a positive effect on shopping intention (p < .001). Step three shows that shopping intention has a positive effect on shopping frequency (p < .001) and money spent (p < .05). However, a direct relationship between attitude and shopping frequency and money spent became insignificant, given the presence of shopping intention. The results confirm a complete mediation of shopping intention between attitude and shopping frequency and money spent. Therefore, H3a and H3b are supported, while H3c is not supported. Compared with the previous model, it can be found that the presence of shopping intention enhances the relationship between attitude and consumers’ shopping frequency (b = .23–.27) and money spent in the mall (b = .18–.20), although such effect is slightly stronger on shopping frequency than on money spent. In a Thai context, the final V-A-I-B model yielded the following values: v2 = 554.582, p = .000, df = 317, GFI = .88, CFI = .88, RMSEA = .049. After deleting the non-significant paths, the model yielded a v2 value of 285.128 (p = .000), with 133 degrees of freedom, GFI of .91, CFI of .90, RMSEA of .06, which demonstrates an acceptable fit with the data (see Fig. 5). The results reveal that attitude has a positive influence on shopping intention (bATT = .38, p < .001). Although no relationship is found between shopping intention and shopping frequency and money spent in the mall, shopping intention is found have a positive effect on time spent in the mall (binten = .13, p = .05). In addition, time spent in the mall is again found to positively influence money spent in the mall (btime = .28, p < .001). Therefore, the indirect effect of shopping intention on money spent is .17 (binten = .13 + binten = .13 btime = .26), which is greater than its direct effect on time spent in the mall. By following Baron and Kenny’s (1986) three-step procedure, it was found that in step one, attitude significantly influenced time spent in a positive way (p < .05), given the absence of shopping intention. In step two, attitude had a positive effect on shopping intention (p < .001). In step three, shopping intention had a positive influence on time spent (p < .05). However, the direct influence of attitude on time spent became insignificant, given the presence of shopping intention. The results confirm that shopping intention completely mediates the relationship between attitude and time spent. Therefore, H4a and H4b are supported, while H4c is not supported. A comparison between the two models (see Figs. 3 and 5) within the Thai sample suggests that the presence of shopping intention does not improve the relationship between attitude and shopping behavior.

5. Discussion and conclusions Previous studies based on Western cultures suggest that selfactualizing (i.e., self-enhancement values in terms of Schwartz Value scale) and social affiliation values (i.e., openness to change

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Y. Cai, R. Shannon / Australasian Marketing Journal 20 (2012) 37–47

Shopping Frequency Self-transcendence

β = .27***

γ = .56*** β = .47***

Mall Attitude

Self-enhancement

Intention

β = .20*

γ = .18*

Money spent β = .38***

Time spent

Model of Fit

R2 of Constructs χ2(df)

338.115(167)***

Attitude

0.34

χ2/df

2.025

Intention

0.22

GFI

0.90

Money

0.18

CFI

0.90

Frequency

0.08

RMSEA

0.06

* p<.05

** p<.01

***p<.001

Fig. 4. Final structural model of the influence of values on attitudes, shopping intention and mall shopping behavior (China, n = 305).

Openness To Change

γ = .18*

Mall Attitude

β = .38***

Intention

β = .13*

Time Spent β = .28*** Money Spent

Model of Fit R2 of Constructs 2(df) 2/df

285 .12 9

133

GFI

0.91

CFI

0.90

RMSEA * p<.05

***

2.144

Attitude

0.03

Intention

0.15

Time

0.02

0.06 ** p<.01

*** p<.001

Fig. 5. Final structural model of the influence of values on attitudes, shopping intention and mall shopping behavior (Thailand, n = 308).

values in terms of Schwartz Value scale) are two significant predictors toward consumers’ favorable attitude toward malls. Between the two values, social affiliation value has stronger power to predict attitude (Shim and Eastlick, 1998). However, the results of the analysis in the present study suggest that previous findings, which are based in a Western context, may not be completely applied to explain Chinese consumers’ mall shopping behavior. It is found that Chinese who place more importance on self-transcendence and self-enhancement values are more likely to have a favorable attitude toward malls. Moreover, the predictive power of self-transcendence exceeds the self-enhancement value. A number of scholars argue that people shop for the benefit of value fulfillment (i.e., Kahle and Kennedy, 1989; Shim and Eastlick, 1998). Matching with the self-transcendence value, it is likely that Chinese consumers may shop to satisfy their functional needs. The self-enhancement value is also found to shape Chinese consumers’ mall shopping behavior. Shim and Eastlick (1998) suggest that people who value self-enhancement may be fulfilling their intrinsic needs for respect, self-fulfillment, and sense of accomplishment through shopping in the malls which provide higher-order goods. In China, it is possible that some shoppers may consider shopping in a mall, which is frequently positioned with a luxury image, as a way to demonstrate their face or social status. Thus, while variety and superb quality of merchandise remain critical to attract Chinese shoppers, the services tailored for meeting their symbolic needs may enhance the attractiveness of the mall.

While the openness to change value does not influence Chinese shoppers, it is the only value that guides Thai shoppers’ behavior. The result is partially consistent with previous findings based on Western culture (Shim and Eastlick, 1998). The dominance of this hedonic-driven value may be derived from the influence of several authentic Thai cultural values, namely mai pen rai, sanuk and being present oriented. Thais may consider shopping at the malls mostly a leisure activity, full of fun and enjoyment. The previous study suggests an indirect relationship between personal values and mall shopping behavior. Personal values directly influence consumers’ attitude toward salient mall attributes, these attitude, in turn, influence consumers’ shopping behavior (Shim and Eastlick, 1998). The results of the present study lend support to this finding. In the Chinese sample, the more favorable attitude the consumers have toward the salient mall attributes, the more likely they will visit the mall frequently and spent more money in the mall. The absence of an attitude–time spent relationship may be explained that as Chinese are more utilitarian-driven shoppers, they tend to spend less time in the mall (Tsang et al., 2003). Their main task is to buy, thus once they finish the purchase, they are more likely to leave quickly. There are several possible reasons for their frequent visits. As the majority of the Chinese respondents are relatively young, they may have less time constraints, or they may be trying to minimize expenditures in any given trip. The broader range of goods and services provided by the mall compared to other shopping venues (e.g., supermarket,

Y. Cai, R. Shannon / Australasian Marketing Journal 20 (2012) 37–47

department store) may induce them to visit the mall frequently in order to update or collect the product information. This may be especially true when they exhibit strong intention to shop, they may visit the mall even more frequently to gather information about the product or services prior to their purchase. With an intention to shop in their mind, together with the rich product information, there is no doubt they will spend more money eventually, but will shop efficiently in the mall. In the Thai sample, consumers who have favorable attitude toward salient mall attributes are more likely to spend more money and time in the mall. However, the favorable attitude does not lead to higher shopping frequency. One possible reason may be that the majority of Thai respondents are relatively older than Chinese respondents. They may have jobs, thus have less time available. Driven by their hedonic needs, they may choose to visit the mall less frequently but stay relatively longer. Shopping intention is not likely to influence their shopping behavior significantly, given that their main goal is to relax and have fun in the mall, which does not require advanced preparation. In sum, although sharing similar cultural backgrounds, different underlying values are found to guide Chinese and Thai consumers’ mall shopping behavior. The results are inconsistent with previous findings, which suggest that consumers from similar cultures tend to be guided by similar values in their behavior (Kim et al., 2002; Bjerke and Polegato, 2006). Therefore, the findings imply that culture alone, as a variable from the national level, may not be enough to understand consumer behavior. As several values in Thai culture are found to differ from Chinese, researchers may consider more caution when labeling cultures, such as individualistic and collectivistic. Social adaptation theory (Kahle, 1983; Piner and Kahle, 1984) suggests that values are a type of social cognition that function to facilitate adaptation to one’s environment (Homer and Kahle, 1988). Thus, in addition to culture, personal values, as variables from the individual level may serve as an additional basis to understand consumer behavior. The underlying values that guide Chinese and Thai shoppers diverge from the values which guide Western shoppers. Consistent with previous findings (Shim and Eastlick, 1998), as more hedonic-driven shoppers, a value–attitude–behavior model can be used to understand Thai consumers’ mall shopping behavior. However, as more utilitarian-driven shoppers, a value–attitude–intention– behavior model works better to predict Chinese consumers’ mall shopping behavior.

6. Implications and directions for future research Although this study is primarily theoretical, it is believed that the conceptual relationships between personal values and other variables may provide a useful framework for managerial decision-making and problem diagnosis. First, rather than just answering how consumers are different, this study helps mall managers to understand why consumers are different, by learning their value orientations. Mall managers can stress those underlying values in all respects of their marketing strategies. For example, promotional strategies built upon selftranscendence and self-enhancement values may be more effective to appeal to Chinese rather than Thais. In contrast, promotional strategies built upon openness to change values may be more attractive to Thais than Chinese. Second, personal values orientation could be used as an alternative segmentation basis. By identifying underlying personal values that determine consumers’ mall shopping behavior, mall managers can gain insightful understanding about why consumers are different in their shopping behavior. Value systems are found to provide richer and more meaningful descriptions of the underlying

45

motivations that drive each segment (Kahle and Kennedy, 1989; Kamakura and Novak, 1992). Theoretically, different cultural values may influence shopping motivations and behavior. Howard (1997) proposes that grouping consumers with similar values will provide segments with similar choice criteria and behaviors. In aggregate, Chinese shoppers appear to be more utilitarian, while Thais seem to be more hedonic shoppers. Thus, international mall managers should realize that values and behavior may differ, but it may also be possible to standardize their marketing strategies when targeting segments that share similar value orientations. Third, this study provides a practical guideline for managers to develop effective positioning strategies. According to the results of this study, a unique and favorable mall image could be positioned by corresponding to target consumers’ value orientations and focusing on their preferred mall attributes. By identifying target consumers’ underlying personal values that determine their shopping behaviors, managers will gain an inner-oriented understanding of their shoppers, thus helping win them emotionally and enhance their patronage. For instance, given their emphasis on hedonic values, an entertainment-driven image may be more attractive to Thai shoppers; whereas an image that stresses the variety of products and services may be more likely to attract Chinese shoppers. On the other hand, the mediating role that attitude play implies that by focusing on salient mall attributes that are favored by the target consumers, mall managers will be able to position a mall image to attract them functionally. Putting these together, a unique image that mirrors both emotional and functional needs and wants of consumers could create a competitive advantage that is more difficult to be duplicated by competitors. In addition, mall managers can evaluate their positioning strategies by checking whether they focus on the appropriate values and mall attributes. Fourth, the predictive power of favorable attitude toward salient mall attributes for shopping behavior can help mall managers make appropriate investment decisions and help them to predict the return of such investments. That is, mall managers will be able to figure out whether a new attribute should be developed and how the new investment would likely affect consumers’ shopping behavior. Fifth, given the important role that shopping intention plays in mediating the attitude–behavior link for the Chinese sample, mall managers may want to try to help Chinese shoppers form their shopping intentions. One of the ways to stimulate shopping intention is to establish favorable atmospherics (Darden et al., 1983; Schlosser, 1998). Among many elements that contribute to atmospherics, mall managers can focus on music, as it can increase shoppers’ excitement (Wakefield and Baker, 1998), and it is one that can be easily controlled, inexpensive to produce and can be predicted based on shoppers’ age or lifestyle (Yalch and Spangenberg, 1993). A recent study reveals that happy music liked by consumers can effectively stimulate female shoppers’ shopping intention (Broekemier et al., 2008). Moreover, a number of researchers propose that highly satisfied shoppers are more likely to form positive repurchase intentions (Stoel et al., 2004; Grace and O’Cass, 2005). It is likely that Chinese consumers’ satisfaction levels may derive from their evaluation of the functional aspects of the mall attributes. Mall managers may identify these attributes by studying the gap between customer expectations towards these attributes versus their mall’s actual performance. Finally, a consistent finding across two countries indicates a positive influence for time spent on money spent in the mall. Therefore, it is vital to keep the shoppers staying in the mall longer. In Thailand, this may be accomplished by focusing on social and recreational aspects of mall attributes. In addition to basic recreational facilities such as cinemas and restaurants, other aspects of entertainment such as theme parks or special events and shows, can also be added to encourage Thais to stay in the mall longer.

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Mall managers can also provide additional facilities for shoppers to rest or spend time meeting with their friends. As Chinese are more likely to shop for utilitarian reasons, recreational facilities may be less attractive. Mall managers can diversify the goods and services provided in the mall, such as adding bookstores, beauty salons, post office, banks, clinics, laundry services, tutorial schools and so onto provide shoppers with more convenience and reasons to stay in the mall longer. Future researchers may wish to examine how the embedding of personal values within marketing communications for malls affects consumers’ responses (such as attitude, preference or visitation). Researchers may also try to segment mall shoppers based on their underlying values, if not culturally, then perhaps by generational cohort or other psychographic groupings to explore relationships between values, attitude and behaviors. In addition, it would be beneficial to identify underlying factors that contribute to Chinese mall shoppers’ shopping intention. Previous studies reveal that attitude–intention (Bagozzi et al., 2000; Lee, 2000) and attitude–behavior relation (Kashima et al., 1992; Kacen and Lee, 2002) are weaker in collectivistic than individualistic cultures. Future studies may test the two models in this study between China/ Thailand with other Western countries to explore differences. Additionally, future studies could contrast similarities or differences between other countries within Asia, or within the EU or South America, to further explore differences between similar cultures, such as those labeled collectivistic or individualistic. A more comprehensive model that includes the moderating effect of level of effort required to conduct the behavior might be added into the value–attitude–intention–behavior model in the Chinese sample, which may help researchers gain further insight into the value– behavior relationship. The R2 value of attitude is 3% in both models in the Thai sample (see Figs. 3 and 5), indicating that less than 10% of total variance of attitude is explained with the structural model. One possible reason for the low R2 is that the personal values construct may be poorly measured, given its abstract nature. Additionally, the direct translation of English to the Thai version of the questionnaire may distort the original meaning of the items. While the translation may help Thais to understand the literal meaning of an item, the meaning may be irrelevant and less meaningful to the respondents (Craig and Douglas, 2005). Future studies should avoid such direct translation by providing an item-equivalence translation. Finally, future studies may adopt a probability sampling method to improve the generalizability of the results and control the variant demographic background in this cross-national comparison. References Ajzen, I., 2008. Scaling and testing multiplicative combinations in the expectancy – value model of attitudes. Journal of Applied Social Psychology 38 (9), 2222– 2247. Anderson, J.C., Gerbing, D.W., 1988. Structural equation modeling in practice. a review and recommended two-step approach. Psychological Bulletin 103, 411– 423. Armitage, C.J., Conner, M., 2001. Efficacy of the theory of planned behavior: a metaanalytic review. Britisb Journal of Social Psychology 40, 471–499. Ayer, F., 1970. Quantifying Thai opinions. In: Anderson, Dole A. (Ed.), Marketing and Development, The Thailand Experience. Michigan State University, pp. 181– 187. Bachrach, B., 1995. How to influence human behavior. Executive Excellence 12 (1), 12–13. Bagozzi, R.P., Yi, Y.J., 1988. On the evaluation of structural equation models. Journal of the Academy of Marketing Science 16 (Spring), 74–94. Bagozzi, R.P., Yi, Y.J., 1989. The degree of intention formation as a moderator of the attitude–behavior relationship. Social Psychology Quarterly 52 (4), 266–279. Bagozzi, R.P., Yi, Y.J., Baumgartner, J., 1990. The level of effort required for behavior as a moderator of the attitude–behavior relation. European Journal of Social Psychology 20, 45–59. Bagozzi, R.P., Wong, N., Abe, S., Bergami, M., 2000. Cultural and situational contingencies and the theory of reasoned action: application to fast food restaurant consumption. Journal of Consumer Psychology 9 (2), 97–106.

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