The importance of entertainment in the shopping center experience: Evidence from Singapore

Introduction

Over the years, the competition between shopping malls has increased significantly possibly due to the overbuilding of retail centers and changing consumer shopping activities. Advancement in the transportation system has further accelerated the level of competition. Another contributing factor is the similarity of the attributes of most shopping malls, with too many stores offering too much of the same merchandise (Ashley, 1997; and Templin, 1997).

Given the apparent similarity in shopping center attributes, shoppers will probably choose to visit the nearest shopping mall when faced with the existence of more than one shopping mall within `reasonable' traveling distance. However, not all shoppers seem to conform to such normative behavior. Past research has revealed that many consumers make a decision regarding where to shop based on their attitude toward a mix of stores, the shopping center environment and entertaining shopping experience (Finn and Louviere, 1990; Donovan, Rossiter, Marcoolyn and Nesdale, 1994; Burns and Warren, 1995; and Jones, 1999).

This study represents a replication and extension of the exploratory research carried out by Jones (1999). Adopting the critical incidence technique, two broad factors-retailer and customer-were found to be characteristic of entertaining shopping experiences. Retailer factors include selection, prices, store environment and salespeople, while customer factors include social, task, time, involvement and financial resources.

In Singapore (Exhibit 1), rapid development and modernization of the retail sector started in the late 1960s. The development of retail centers continued into the 1970s and 1980s with more centers built in the Orchard Road area. To avoid overcrowding of the central area, the 1991 Revised Concept Plan set out the development of regional centers and sub-regional centers. This brought about tremendous change in the retail sector in the 1990s. In addition to Singapore, urban sprawl and the sprouting of regional shopping centers and suburban office parks has been documented in many other major cities. In the case of Singapore, this development has been accelerated and guided by the Mass Rapid Transit (MRT) system and the development of the surface road infrastructure.

Over the years, suburban shopping malls have grown larger and their one-stop convenience has extended to include service outlets and entertainment providers. By using creative merchandising and aggressive marketing promotions that take advantage of consumer trends, suburban malls are positioning themselves to attract recreational shoppers beyond their immediate retail trade area. The challenge to both the downtown and suburban shopping malls is to retain their share of shoppers. The underlying determinants of retail patronage are key in helping retailers to understand the critical success factor unique to their trade area. Therefore, it is important for retailers to identify their market niche in order to transform the shopping experience in their realm into something extraordinary.

Literature Review

Retailing Literature

There are many studies that document that consumers may view either shopping in general or specific shopping experiences as entertainment or recreational (eg., Bellenger and Korgaonkar, 1980; and Babin, Darden and Griffin, 1994). Generally, studies involving shopping and entertainment can be categorized into two research streams: (1) as an enduring tendency or trait; or (2) as a motive for a particular shopping trip.

Enduring Tendency or Trait

One consideration in people's orientation toward shopping is their view of alternative uses and expenditure of time. Do they enjoy spending time shopping, or do other alternative uses of their time have higher priority? Previous research into shopper orientation has typically created a category reflecting an entertainment orientation supporting the notion that some shoppers have an enduring tendency to shop for entertainment purposes.

Stone (1954) identified four types of shoppers in his exploratory research, namely, the economic shopper, the personalizing shopper, the ethical shopper and the apathetic shopper. Stone's typology still has considerable merit, however the changing consumers, as well as the changing environment may have altered these basic orientations. Bellenger, Robertson and Greenberg (1977) suggested that much could be learned about retail patronage behavior from the study of consumers' general shopping orientations. They introduced the dichotomy of recreational and economic shopping. Bellenger and Korgaonkar (1980) contributed additional insights into the characteristics of recreational shoppers. They defined recreational shoppers as those who enjoy shopping as a leisuretime activity. While economic shoppers dislike shopping or are neutral toward it.

Lesser and Hughes (1986) found, both in their multi-market study and in their review of shopper typology literature, that the two types of shoppers that appear most often are the active shopper and the inactive shopper. Recreational shopping (Bellenger and Korgaonkar, 1980) and purchasing involvement (Slama and Tashchian, 1985) are two traits that distinguish active shoppers from inactive shoppers, and both traits have proven to be important predictors of consumer behavior. This stream of research emphasizes that shoppers possess general tendencies regarding the shopping process that are consistent across situations. This research vein on shopper orientations has identified an array of shopper types ranging from those who 'like' to shop to those who 'dislike' shopping (Exhibit 2).

Motives for a Shopping Trip

Besides consumer orientations, another research stream has focused on consumer motivations for specific shopping trips. In contrast with the shoppers' enduring tendencies to enjoy the shopping process, the typologies focusing on consumer shopping motivations are more situational specific. The variety of shopping motives that have been suggested (eg., Tauber, 1972) are summarized and framed by the motivational typology described by Westbrook and Black (1985). This typology postulates that shopping motives can be grouped into three categories: product-oriented, experiential and a combination of product and experiential. In the first case, a store visit is motivated by purchase needs or the desire to acquire product information. The experiential motive has a hedonic or recreational orientation-the store or mall visit is made for the pleasure inherent in the visit itself. The last motive category occurs when the shopper seeks to satisfy a purchase need, as well as enjoying a pleasurable recreational experience.

Likewise, Dawson, Bloch and Ridgway (1990) stated that some consumers have experimental motives for shopping that result from hedonic or recreational motivations. Their results from a survey of visitors to a large outdoor crafts market show that consumer with strong product or experiential motives report the most pleasure and arousal in the marketplace. Thus, consumers who purposely come to the market to experience sights, sounds and people reported higher arousal and pleasure than those who did not have strong experiential motives. Thus, it appears that a positive emotional state that consists of high levels of pleasure and arousal may be a key part of the shopping experience.

Researchers have found that people typically shop for both hedonic, or recreational purposes, and utilitarian reasons, and that a positive mood can result from consumers pursuing either type of shopping (Martineau, 1958; and Babin, Darden and Griffin, 1994). Hedonic shopping motives are based on the quality of the shopping experience itself rather than towards information gathering or on purchasing products (Jarboe and McDaniel, 1987; and Boedeker, 1995). Finally, Bloch, Ridgway and Dawson (1994) found that consumers view malls as a place not only for shopping, but also for other activities, such as entertainment, socializing with friends and browsing with no intention of buying. These multiple motives inherent within a single shopping trip clearly indicate the entertaining capabilities of shopping.

Factors Inducing an Entertaining Shopping Experience

Several characteristics of an entertaining shopping experience have been previously investigated, for example, browsing (Bloch, Ridgway and Sherrell, 1989), the retail environment (Kotler, 1973; and Donovan, Rossiter, Marcoolyn and Nesdale, 1994), social interactions (Bloch, Ridgway and Dawson, 1994) and bargains (Schindler, 1989). However, a first attempt at organizing a framework to help further understand an entertaining shopping experience was carried out by Jones (1999). He adopted the critical incident technique to identify the factors that contribute to the entertaining nature of shopping. He identified two broad groups including nine unique factors that are characteristic of entertaining shopping experiences. The two broad groups were retailer factors and customer factors. Retailer factors include selection, prices, store environment and salespeople, while customer factors include social, task, time, involvement and financial resources. Interestingly, customer factors were mentioned more often than retailer factors in respondents' descriptions of entertaining shopping experiences.

Shopping and Traveling Literature

Although earlier shopping center choice models, such as Reilly's Law of Retail Gravitation and Spatial Interaction, have dealt with the transport element (eg., distance, travel time and cost), linkages between traveling and the retail experience have been neglected. Most of the studies have not investigated the travel component comprehensively. Additional variables need to be added to a shopping choice model, namely effort, tension and comfort should be included to improve the accuracy.

Spiggle and Sewall (1987) suggested that studies of retail selection have focused on three conceptually distinct, though not mutually exclusive constructs. In their model, retail patronage, choice and preference are influenced by retail features such as distance, assortment, travel time, consumer psychological states and consumer characteristics. It illustrated that most of the models and theories have used distance, travel cost and travel time as the deterrent factors. However, it must be acknowledged that travel attributes comprise many other factors, which may be more important than the conventional measures. These include the effort, tension, reliability, comfort, safety, etc. of the available modes of transportation to each retail facility.

In another study, Gautschi (1981) explored the probable specification biases of conventional patronage models that result from the omission of two important constructs: descriptors of retail centers and descriptors of transportation conditions. His survey asked people to evaluate ten shopping centers and various transportation characteristics. Testing on a set of planned suburban shopping centers and traditional, unplanned shopping centers, he found that when the respondents considered both the transportation and center attributes together, they engaged in a rather complex evaluation of the patronage alternatives.

In addition to the shopping center attributes, McCarthy (1980) attempted to include transport mode/travel attributes in studying the role of the qualitative characteristics that influence the choice in shopping destination. Using the factor analytical technique, five sets of qualitative generalized attributes were generated. These generalized attributes include trip convenience, trip comfort, trip safety, shopping area attraction and shopping area mobility. He found that these generalized attributes, which were obtained from attitudinal information, are significant in an individual's choice of shopping area.

Utilizing a form of methodological triangulation, Ibrahim (2000) evaluated the significance of transport mode/travel attributes in shopping center choice in a suburban/decentralized environment with public transport options. Using the discrete choice (multinomial logit) modeling technique, the study found that a composite model, which includes traditional measures of deterrence (i.e., travel time, travel cost and distance), as well as other transport mode/travel factors, recorded higher predictability and better fit than models that only adopt the traditional factors of deterrence. In addition, the study concluded that transport mode/travel attributes are significant in respondents' choices of shopping center in a suburban/decentralized region with public transport options.

The review of the literature shows two significant conclusions. First, research on the shopping experience as entertainment has generally been well covered. However, other than Jones (1999), there have been few studies on the factors that affect the shopping experience. Second, the majority of researchers have identified the existence of the shopping experience as entertainment (eg., Bellenger and Korgaonkar, 1980; Babin, Darden and Griffin, 1994; Burns and Warren, 1995; and Jones, 1999), however little attention has been paid to how travel affects an entertaining shopping experience. This study examines how retailer, customer and transport mode/travel attributes affect a shopper's entertaining shopping experience in Singapore. In addition, it also investigates how shoppers with different socioeconomic backgrounds perceive the entertainment effects of the respective factors.

Research Methodology

Mixed Method Designs

This study employs a two-phase sequential design. Initially, a qualitative data collection and analysis on a relatively unexplored topic was conducted. The results were used to design the quantitative phase of the study. This form of methodological triangulation enhances the internal validity of the research findings (Tashakkori and Teddlie, 1998).

Qualitative Research Phase

In-depth interviews were conducted with shoppers before undertaking the quantitative research. The findings of the qualitative research helped to refine the scope of the research, as well as to guide the development of the questionnaire. In this phase, convenience samples of thirty shoppers were asked to answer open-ended questions on a standard form. Walker (1985) states that between twenty and forty in-depth interviews are necessary for the qualitative studies that are undertaken prior to quantitative studies. The interviewed shoppers were segmented according to the respective classes of shopping centers. The classes include centers in the downtown, regional center, sub-regional center/town center, neighborhood center and precinct shop. The following issues were discussed:

1. Description of a recent shopping trip that was very entertaining.

2. What factors affect entertaining shopping experience?

3. Role of transport mode/travel attributes in entertaining shopping experience.

The data was thoroughly examined prior to analysis. Next, the data sets were identified and labeled according to the general concepts and themes that pertained to the research. The categorization of the data sets into individual incidents requires insight, experience and judgment (Flanagan, 1954). No simple rules are available, and the quality and usability of the final product are largely dependent on the skill and sophistication of the formulator. However, to gain objectivity, the tentative categories were reviewed by others. After the categories were established, each was given a brief definition. During this process, some redefinition and recategorization occurred.

Quantitative Research Phase

Using cluster sampling, a total of 300 shoppers were surveyed in Jurong East New Town, a typical new town in Singapore. A questionnaire was used to measure the importance of the retailer, customer and transport/travel attributes in contributing to a shopper's entertaining experience. These attributes are operationalized on a seven-point Likert scale, where 1 = Not important at all, 4 = Neutral and 7 = Very important. Demographic information was also collected on the respondents. The principal component analysis, independent sample t-test and Analysis of Variance (ANOVA) were used to analyze the data. Factor analysis was used to reduce the variables to a number of factors, to concisely describe (and perhaps understand) the relationships among the observed variables. Factor analysis was also used to identify the relevant factors that affected the entertaining shopping experience. Comrey and Lee (1992) regard a sample size of 300 to be good enough for factor analysis.

Findings of Qualitative Research

Three broad groups and a total of thirty-four attributes emerged from the categorization procedure (see Exhibit 3). It should be noted that all of the attributes did not appear in each reported experience. The findings indicate that an entertaining shopping experience is influenced by three broad categories: retailer attributes, customer attributes and the transport/travel attributes. The general model for an entertaining shopping experience is shown in Exhibit 4. The transport/travel attributes are an addition to the model developed by Jones (1999).

Results

Importance Rating

Respondents were asked to rate the importance of the attributes (see Exhibit 5). Twenty-eight of the thirty-four attributes have mean scores of more than 4. This implies the importance of these variables in influencing respondents' entertaining shopping experience.

The mean scores range from 3.03 to 5.28. The variable "availability of financial resources" has the highest importance mean score in influencing respondents' entertaining shopping experience. Given the high standard of living in Singapore, it may seem intuitive that possessing the means to make purchases greatly influences shoppers' enjoyment. However, the other customer attributes have relatively low mean scores probably due to their sensitivity to the specific characteristic.

Interestingly, seven variables with mean scores above 5 belong to transport/travel attributes. These variables are mainly concerned with time issues and the comfort level during the journey to the shopping center. It is not surprising that these variables have high mean scores due to the humid weather in Singapore and the perception of time poverty among Singaporeans. Relating to the rest of the transport attributes, most have mean scores above 4 while "absence from stress" and "enjoyment of travel" scores a low 3.99 and 3.74, respectively.

Relating to the retailer attributes, the variables "high quality sales service," "availability of sale, promotion, discount and bargain," "wide variety of stores" and "availability of food-court/restaurants" top the list of importance ratings. Most of the variables relate to the atmosphere of the shopping center, such as "spaciousness of internal layout of shopping center," "good air quality in shopping center," etc., appear in the middle of the list. Variables such as the "availability of entertainment facilities," "availability of celebrations, activities and functions," "availability of unique store design" and "ease of finding car parking lot" have relatively low mean scores. However, these variables might be directly related to specific characteristics of the respondents.

Factor Analysis

Logically, it is important that all relevant attributes are included in the modeling of entertaining shopping experience. However, the problem of multi-collinearity among the attributes may pose a serious threat to its interpretation. Factor analysis serves two specific purposes. First, it links correlated variables into factors. Second, it serves as a solution for multi-collinearity so as to provide a better understanding of the underlying dimensions that influence the entertaining shopping experience. Exhibits 6-8 summarize the principal component analysis of the retailer, customer and transport mode/travel attributes.

Bartlett's test of sphericity and KMO are employed to determine the appropriateness of the data set for factor analysis (Kline, 1994; and Malhotra, 1996). High values (between 0.5 and 1.0) indicate that factor analysis is appropriate, while values below 0.5 imply that it may not be appropriate. On the other hand, the alpha value measures the reliability of the attributes in contributing to each factor (Cronbach, 1951). The latent root criterion (eigenvalues greater than one) has been adopted as the main method in extracting the number of factors for the analysis. Hair, Anderson, Tatham and Black (1998) regard the latent root criterion as the most appropriate and reliable method when there are twenty to fifty variables in the factor analysis.

Relating to the issue of factor loadings, which would be regarded as an important consideration in the factor analysis, Hair, Anderson, Tatham and Black (1998) state that factor loadings of 0.30 are considered significant if the sample size is 350 or greater. Thus, the attributes listed in association with each factor are those loading at or above 0.30. In analyzing the factor solutions, there are attributes that load more than 0.30 on more than one factor. These are indicated the lower loading by an asterisk next to the factor loading of the attribute. Finally, in most instances, the labels given to the factors are chosen to reflect the properties shared by the set of attributes loading above 0.30 within each factor.

Retailer Factors. The values of the Bartlett's test of sphericity (.000) and KMO (.695) indicate that the data are appropriate for factor analysis. Factor analysis (principal component) using varimax rotation yielded four retailer factors with eigenvalues greater than 1. These accounted for 21.61%, 19.69%, 12.57% and 9.87%, respectively, of the variance. In the (varimax-rotated) factor solution, factor 1 consists solely of shopping center features. Factor 2 consists of variables that are related to the atmosphere of the shopping while factor 3 could be labeled as value-added features. Factor 4 principally relates to ancillary facilities in the shopping center. The last factor was dropped in view of the low proportion of variance and low coefficient alpha accounted for by the fourth dimension. All in all, the three factors account for 53.88% of the variance within the original variables. Coefficient alpha estimates for the three factors exceed 0.65, which indicate acceptable reliability. Dawson, Bloch and Ridgway (1990) stated that the coefficient alpha must exceed 0.65 to yield reliability.

Customer Factors. The values of the Bartlett's test of sphericity (.000) and KMO (.616) indicate that the data are appropriate for factor analysis. Factor analysis using varimax rotation yielded two customer factors with eigenvalues greater than 1, and the cumulative percentage of variance amounts to 53%. Coefficient alpha estimates for the two factors are 0.73 and 0.66 respectively, which indicate acceptable reliability. Factor 1 accounts for 29.68% of the variance within the original set of variables and comprises variables that relate to hedonic shopping values. This value results more from fun and enjoyment than pure task completion. Factor 2 includes the variables that could be labeled as utilitarian oriented. Utilitarian value has been described as task-related or some type of conscious pursuit of an intended consequence (Babin, Darden and Griffin 1994). It accounts for 21.71% of the variance within the original set of variables.

Transport Mode/Travel Attributes

Factor analysis using varimax rotation yielded five transport mode/travel factors with eigenvalues greater than 1. Exhibit 7 shows that the five factors extracted account for 64.77% of the variance. The values of the Bartlett's test of sphericity (.000) and KMO (.733) indicate that the data are appropriate for factor analysis. Coefficient alpha estimates for the five factors exceed the desirable level therefore indicating acceptable reliability.

Factor 1 comprises variables relating to the physical and mental efforts that shoppers need to make during a shopping trip. It accounts for 17.66% of the variance within the original set of variables. Factor 2 consists of variables that are related to the degree of protection of the shoppers from undesirable elements during the shopping trip. It accounts for 12.55% of the variance within the original set of variables. Factor 3 consists solely of variables that influence shopper's comfort level in the shopping trip; 12.19% of the variance is accounted for by the third dimension. Factor 4 accounts for 11.44% of the variance within the original sets of variables and comprises variables that relate to the enjoyment of travel. Factor 5 incorporates variables that affect the level of tension of the shoppers during their shopping trip. It accounts for 10.93% of the variance within the original sets of variables.

Weighted Factor Rating IMAGE FORMULA 83IMAGE FORMULA 84

Analysis of Factor Ratings by Demographics

The null hypothesis (Ho) states that there is no statistically significant difference in the mean scores of the various groups of respondents in the sample. On the other hand, the alternative hypothesis (HI) indicates that there is significant difference in the means. Exhibits 9-11 present the findings.

Exhibit 9 summarizes the research findings for the analysis of retailer factors by the various socioeconomic groups. At the 0.05 level of significance, the t-test and ANOVA procedures indicate that thirteen of the twenty-four cases show a statistically significant difference. For mean score ratings of "shopping center feature" and "atmosphere," the differences occur in marital status, age, personal monthly income, occupation, transport ownership and gender. The findings also demonstrate that a significant difference in the mean score ratings for "value added features" occurs when respondents are grouped by room type. The comparative analysis for the rest of the socioeconomic factors shows no significant difference in the mean score ratings.

Exhibit 10 summarizes the research findings for the analysis of customer factors by the various socioeconomic groups. At the 0.05 level of significant, the t-test and ANOVA procedures indicate that seven of sixteen cases reveal a statistically significant difference. For mean score ratings of "hedonic oriented," the differences occur in marital status, age, occupation, transport ownership and gender. However, a significant difference in the mean score rating for "utilitarian oriented" occurs in occupation and gender.

Exhibit 11 summarizes the research findings for the analysis of transport/travel factors by the various socioeconomic groups. At the 0.05 level of significance, the t-test and ANOVA procedures indicate that twenty of forty cases display a statistically significant difference. For mean score ratings of "effort," the differences occur in room type, age and gender. For mean score ratings of "protection," the differences occur in marital status, age, occupation and transport ownership. The "comfort" mean score ratings for the various socioeconomic groups show significant differences in room type, personal monthly income, occupation, transport ownership and gender. The findings also demonstrate that a significant difference in the mean score ratings for "enjoyment" occurs when respondents are grouped by marital status, age and occupation. However, a significant difference in the mean score rating for "tension" occurs in room type, age, personal monthly income, occupation and transport ownership.

Conclusion

Three retailer factors, two customer factors and five transport mode/travel factors were extracted from the inventory set of attributes. Exhibit 12 presents a model of the factors. This study found that apart from the retailer and customer factors, transport mode/travel factors also contribute to an entertaining shopping experience. This research has attempted to replicate Jones (1999) exploratory investigation in the context of Singapore. It identified and analyzed the factors that significantly affect an entertaining shopping experience in Singapore. In addition, it has extended the research by exploring how travel attributes affect an entertaining shopping experience.

The quantitative research supported the hypothesis that retailer attributes, customer attributes and transport mode/travel attributes significantly affect an entertaining shopping experience. In addition, this study found that twenty-eight of the thirty-four attributes have importance mean scores of more than 4. This implies that these variables influence an entertaining shopping experience. In particular, survey respondents placed high importance on the transport mode/travel attributes such as "absence of waiting time" (5.17), "absence of congestion" (5.17), "absence of crowd in transport mode" (5.15), "traveling time to shopping center" (5.15), "directness of travel to shopping center" (5.15) and "safety of travel" (5.13). This indicates that travel attributes significantly affect an entertaining shopping experience. Finally, numerous independent t-tests and ANOVA tests analyzed the effect of the various socioeconomic groups on the mean importance ratings of the respondents. Respondents with different socioeconomic characteristics considered the importance of the factors that affect an entertaining shopping experience differently.

From a theoretical perspective, this study broadens the literature by demonstrating that transport mode/travel factors significantly affect an entertaining shopping experience. Other than customer factors that are unique to each individual, retailer and shopping center management could focus on the retailer and transport mode/travel factors when creating an entertaining shopping experience. The findings indicate that an entertaining shopping experience derived from retailer and transport mode/travel factors significantly affects patronage behavior. One implication is for retailer and shopping center managers to examine the underlying attributes in their facilities so as to develop competitive marketing strategies that attract shoppers. It is imperative that there are sales and marketing promotions, discounts, a wide variety of products and stores to facilitate an entertaining shopping experience in Singapore. The findings also indicate the importance of travel in contributing to an entertaining shopping experience. Therefore, shopping center management should also consider store location, as well as the design of the transportation facilities, so that they facilitate an enjoyable shopping experience. For example, to reduce the tension and effort in grocery shopping, supermarkets should be located close to the carpark and other transportation facilities. Similarly, appropriate safety features, shelter and other features to ease travel should be provided. These arrangements would involve collaborations among the shopping center management, local councils and the relevant planning agencies. This calls for greater integration in the land use and transport planning process.

As socioeconomic groups differ in their preference, shopping center management should focus on those factors that are important to their target audience. For example, shoppers of different age groups and marital status seem to have different retailer preferences, particularly the features of the shopping centers and their environments. Therefore, the shopping center management should apply different marketing strategies for store location and tenant selection that address the needs of their entire audience.

Future research should investigate entertaining shopping experiences in other types of retail outlets or centers, such as hypermarkets, specialty "theme" centers, "power" centers or warehouse clubs. Future studies might also explore the entertainment value of Internet shopping and on-site shopping. As this research focused only on the factors that affect an entertaining shopping experience, future research should examine the factors that affect a non-entertaining shopping experience. Hopefully, this research will stimulate future research that will provide a better understanding of this important retail phenomenon.