The Ecological Validity of Photographic Slides and Videotapes in Simulating the Service Setting

JOHN E. G. BATESON MICHAEL K. HUI*

In the study of consumers' evaluation of the service setting, laboratory experiments using environmental simulations provide researchers with a level of control that can otherwise be difficult to achieve in field studies. This article demonstrates that pho­tographic slides and videotapes, used as environmental simulations in testing a theory of crowding, have ecological validity. The same theoretical model is tested with data obtained from a field quasi-experimental study and with data from a lab­oratory study that used photographic slides and videotapes to simulate the service setting. Conditions that may constrain the applications of various kinds of environ­mental simulations in consumer research on services are also discussed.

T here is a general consensus that services can be viewed as the output of an interactive process in

which the consumer is an active or passive participant (Langeard et al. 1981). It is from the interpersonal (consumer and contact personnel) and person-environ­ment (consumer and physical service setting) interac­tions that consumers attempt to get their needs and wants satisfied. We draw the distinction here between the service experience, which is defined as the consum­er's emotional and behavioral responses to his/her in­teraction with the service setting and personnel, and the service encounter, which is commonly defined as the dyadic interaction between the consumer and the server (Czepiel, Solomon, and Surprenant 1985).

A growing number of researchers have become in­terested in understanding the service experience. Al­ternative theories have emerged to explain the experi­ence (see, e.g., Bitner 1990; Czepiel et al. 1985). Researching the service experience, however, poses a key methodological issue. It has long been argued within operations management that it is virtually impossible to standardize the service experience (Chase and Tansik 1983). The high people content of the process, involving both service personnel and consumers, introduces too

* John E. G. Bateson is senior vice president, MAC-Gemini, 22 Grafton Street, London WIX 3LD, England. Michael K. Hui is as­sistant professor of marketing, Concordia University, 1455 de Mai­sonneuve Blvd. West, Montreal, Quebec H3G 1M8, Canada. Both authors contributed equally to this article and they are listed alpha­betically. The authors are indebted to the editor and the three anon­ymous reviewers, who provided detailed and constructive comments on this article.

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much uncertainty. The variability in mood of all parties and the frailty of operating systems both compound this problem. For services, unlike the situation for goods, it is impossible to remove this variability in the "manufacturing" process before it reaches the con­sumer. Because services are real-time experiences, quality control cannot occur at the "factory gate."

Under such circumstances, testing theories in actual service settings poses real problems because each re­spondent may have a different set of interactions. The noise that is introduced into the results in this manner may preclude the accurate assessment of the impact of different features and events and, hence, the theory testing. One possible solution is to measure the potential confounding variables and control statistically their ef­fects on the dependent variables (Cook and Campbell 1979). Given the current level of understanding and the complex nature of the interaction between the con­sumer and the service setting, this alternative may re­quire an extremely large sample size to produce any significant, systematic effects.

At first sight, laboratory experiments would seem to be ideally suited to researching the service experience, especially when one's objective is theory testing (Calder, Phillips, and Tybout 1981). Experimental design offers high levels of control and the ability to manipulate variables individually. However, laboratory experi­ments should be conducted only when (a) researchers can effectively create realistic service settings in a lab­oratory and (b) the simulated service setting can pro­duce the same experience as the actual service setting. In environmental psychology, a similar set of arguments has been made and labeled as "ecological validity"

© 1992 by JOURNAL OF CONSUMER RESEARCH, Inc .• Vol. 19. September 1992 All rights reserved. 0093·5301/93/1902.()()()9$2.00

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(McKechnie 1977). Theorists in this field have long re­alized that the determination of the "media of repre­sentation," that is, how an environment should be pre­sented to respondents, is one of the key methodological considerations in the study of person-environment in­teractions (Craik 1971).

This article reviews the various types of environ­mental simulations and discusses the advantages of us­ing this technique to test theories of the service expe­rience. We also report the findings of a study that examines whether photographic slides and videotapes can adequately represent a simple service setting (a rail­way-station ticket office) in testing a theoretical model concerning the effects of consumer density (the number of consumers that are present in the setting) on the ser­vice experience. The theoretical model is first tested in a laboratory experiment using slides and videotapes as environmental simulations. The ecological validity of the instruments is then determined by comparing these results with those obtained from a field quasi experi­ment designed to test the same theoretical model. Con­ditions that may constrain the applications and ecolog­ical validity of various kinds of environmental simulations in consumer research on- services are also discussed.

ENVIRONMENTAL SIMULATIONS A common methodological problem facing environ­

mental psychologists is the need to investigate human responses to environments that have not yet been built (Bosselmann and Craik 1987; Hershberger and Cass 1974). For instance, a hospital may want to know the reactions of their patients toward the design of a new casualty ward before it is built so that they can modify their plan if necessary. The best means by which to examine responses is to bring respondents to the actual setting, but this approach is obviously unfeasible be­cause the setting does not yet exist. To overcome this difficulty, environmental simulations have been exten­sively employed "for replicating-or more precisely, previewing or otherwise anticipating-in the laboratory everyday environments that have not yet been built, modified, or otherwise actualized" (McKechnie 1977, p. 1(9).

McKechnie (1977) has suggested that environmental simulations can be classified according to two different dimensions. The first dimension refers to the fact that the information provided can be either perceptual or conceptual. Perceptual simulations are "concrete rep­licas or isomorphs or environments" (McKechnie 1977, p. 174), and they are intended to portray as much as possible the noticeable features of the actual environ­ment. Examples of perceptual simulations include photographic slides and videotapes. By contrast, there are simulations such as maps and floor plans that con­vey primarily functional and operational information (e.g., a highway network), which is usually difficult for

JOURNAL OF CONSUMER RESEARCH

a person to visualize, even when s/he is in the real­world setting.

The second dimension delineates dynamic (e.g., vid­eotapes and film produced from scale models of places) I or static (e.g., photographs) simulations. Static simu­lations portray only a single, unchanging description (static-conceptual) or view (static-perceptual) ofthe en­vironment. On the other hand, dynamic simulations allow continuously changing descriptions (dynamic­conceptual) or views (dynamic-perceptual) of the en­vironment. For example, an architectural model of hospital premises was made in a study that determined where a new entrance to the parking deck of a hospital should be built (Carpman, Grant, and Simmons 1985). A videotape was produced by moving a specially adapted videocamera around the model. The videotape, when shown on a monitor, gave images as if one were driving toward the parking deck. Respondents, while watching the videotape, were asked a number of ques­tions regarding the parking deck.

Environmental simulations not only resolve the methodological difficulty in predicting human responses to "not yet existing" environments, they also provide a number of other advantages. First, it becomes possible to study person-environment interactions in laboratory settings, and this allows researchers to exert tighter con­trol on any possible confounding variables (McKechnie 1977). Second, environmental simulations increase the cost-effectiveness of person-environment research (Er­oglu and Machleit 1990; Surprenant and Solomon 1987). For example, it took only two weeks to complete the hospital parking-deck study mentioned earlier, even though the responses of a large number of respondents were processed. Last, researchers may also study human reactions to some potentially dangerous or unpleasant environments. Without environmental simulations, these types of studies might raise serious ethical con­cerns.

Three types of simulations-written descriptions or scenarios, audio simulations, and photographic slides and pictures-have been used in consumer research on services. Written scenarios and audio simulations are used primarily to manipulate various social and situ­ational features of the service encounter. Researchers have used written scenarios to study how the explana­tions that contact personnel provide affect consumers' reactions to service failure (Bitner 1990). Researchers have also used audio simulations, in the form of a taped transaction, to manipulate service personalization (Surprenant and Solomon 1987). Photographic slides and pictures, on the other hand, are employed primarily to study consumers' reactions to the physical features of the retail or service setting (Bitner 1990; Eroglu and

'The technique originates from the Berkeley Environmental Sim­ulation Laboratory at the University of California, Berkeley. A more detailed description of the technique and the laboratory can be found in McKechnie (1977) and Bosselmann and Craik (1987).

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ECOLOGICAL VALIDITY

Machleit 1990; Hui and Bateson 1991). The employ­ment of these visual simulations allows researchers to manipulate environmental features such as consumer density (i.e., the number of consumers in a service set­ting; see H ui and Bateson 1991).

Drawing from the field of visual sociology (e.g., Becker 1981), researchers also rely heavily on various audiovisual tools in the naturalistic inquiry of consumer behavior (e.g., Belk, Sherry, and Wallendorf 1988). However, these tools are no longer used as environ­mental simulations. In these studies, pictures, slides, and videotapes are treated as raw data (Wallendorf and Arnould 1988) and are used to explore and investigate the sociocultural aspects of consumption behavior.

ECOLOGICAL VALIDITY

The use of environmental simulations, however, is justified only when they can adequately represent the environments (Craik 1971). Ecological validity, as de­fined by McKechnie (1977, p. 169), refers to "the ap­plicability of the results oflaboratory analogues to non­laboratory, real life settings." The development and validation of environmental simulations are important for the rapprochement of internal and external validity. Researchers should pay particular attention to factors that may influence the ecological validity of the various types of environmental simulations. For example, under what conditions can the use of slides and videotapes as environmental simulations be considered as appropriate and demonstrate sufficient ecological validity? When environmental simulations of high ecological validity are employed, laboratory experiments can be performed with reasonable internal and external validity.

In reviewing the whole area of ecological validity re­search, Bosselmann and Craik (1987) have reported substantial congruence between direct and simulation presentations. Perhaps the most complete test of validity was the study conducted by Hershberger and Cass (1974) to compare the ecological validity offive different representative media: 35-mm single-color slides, 35-mm multiple-color slides, super-8-mm color film, super-8-mm black-and-white film, and black-and-white video­tape. One hundred and twenty architectural students were randomly divided into six equally sized groups. One respondent group was brought to 12 prototypical housing examples and was asked to evaluate the houses on 30 semantic differential items, which primarily cap­tured the respondents' perceptual and emotional re­sponses. Each of the other five respondent groups was asked to evaluate the same 12 housing examples, but this time they were exposed to one of the five environ­mental simulations. Results of the study indicated that item ratings obtained from the real-environment group and the five environmental simulation groups were highly correlated, ranging from. 72 for color film to .79 for color slides.

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However, in environmental psychology, the primary interest is not in testing theories but in measuring re­actions. The typical measures used include descriptive­evaluative dimensions, free descriptions, evaluative judgments, behavioral intentions, and judgments of objecti ve properties. None of the studies performed to date have attempted to examine whether a theoretical relationship can be tested just as well with simulation presentations as with actual settings. Given the fact that such simulations are becoming more common in theory testing in consumer research, especially in the study of consumer reactions to the retail or service setting, it is essential to test the ecological validity of these tools before they can be used legitimately and before their utility in consumer research can be fully exploited.

AN EMPIRICAL STUDY

The purpose of this study is to test the ecological validity of two kinds of visual environmental simula­tions, slides and videotapes, in testing theories related to interactions between the consumer and the service setting. The same theoretical model is tested in three different manners, using slides, videotapes, and a field quasi experiment. Slides are included because they have been one of the most widely employed environmental simulations in consumer research on services. The in­clusion of videotapes allows us to test whether a slightly more dynamic representation of the service setting would produce different emotional and behavioral out­comes.2

The model was developed by Hui and Bateson (1991). It was selected because (a) one of the key exogenous variables of the model (consumer density, see our ex­planation later) is concerned with a physical dimension of the service setting and because (b) it is a model of reasonable complexity, so that the confirmation of the same model by three procedures would provide strong evidence for the ecological validity of the two types of environmental simulations in theory testing. Although the focus is on the ecological validity of slides and vid­eotapes, it is necessary first to outline the model being tested.

As shown in Figure 1, the detailed model to be tested suggests that two variables will influence the consumer's perceived control, a crucial dimension underlying the service experience. The first is the availability of con­sumer choice or, more precisely, whether the consumer has an alternative means to acquire the service. This is rooted in Averill's (1973) categorization of the different

2McKechnie (1977) has suggested that the dynamic-static dimen­sion in the classification of environmental simulations is a continuum. The videotapes used in this study, although not as dynamic as those produced by moving a videocamera around the real-world setting or a model of the setting, do show some motions and are therefore con­sidered to be relatively more dynamic than slides.

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274 JOURNAL OF CONSUMER RESEARCH

FIGURE 1

THE HYPOTHESIZED MODEL

Consumer Choice

(~)

types of control, of which perceived choice is one. The second factor is the density of people within the service setting. Stokols (1972), in an attempt to reconcile con­flicting experimental evidence on the impact of crowd­ing on individual response, drew the distinction between density and crowding. Density refers to the physical condition, "in terms of spatial parameters" (Stokols 1972, p. 275). On the other hand, crowding is a psy­chological experience characterized by stress. It has been argued in the literature that the incidence of the psy­chological state of crowding is determined by the in­dividual's perception of control in the setting (Schmidt and Keating 1979). The model hypothesizes that (a) density influences crowding both directly and indirectly through perceived control, hence testing the control theory of crowding, and (b) perceived control and crowding determine the consumer's emotional and be­havioral responses to the service setting. A more detailed

E 7

description of the model can be found in Hui and Bate­son (1991).

RESEARCH DESIGN Three different sets of data are necessary for testing

the ecological validity of slides and videotapes. The model just described must be tested using slides and videotapes to simulate the service setting. The model must also be tested in the actual service setting. Slides and videotapes can be judged to have ecological validity if the results obtained using them are similar to results obtained in the actual setting.

A Laboratory Study Using Slides and Videotapes

Consumer choice and consumer density were ma­nipulated independently using photographic slides and

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ECOLOGICAL VALIDITY

written scenarios. In addition to slides, we also used videotapes to simulate the chosen service setting-the ticket office of a major railway station in London, England. The slides and videotapes were taken between 4 P.M. and 7 P.M. on two weekdays. This period covered the peak rush hour, and large variations in the number of people in the setting were, therefore, available. On the first day, a photo camera with a 24-mm lens was fixed at one corner of the ticket office. On the average, one picture was taken every four to five minutes, and a total of 35 usable slides were obtained. Because the slides were shot by the same camera from the same lo­cation, the only difference between them is the number of passengers present in front of the ticket office. On the second day, 25 90-second, silent video sequences were taken by a videocamera, fixed at the identical spot.

The number of consumers shown in each slide and in each video sequence was then counted. Because con­sumers were continuously entering and exiting from the setting, the number of consumers shown by a video sequence varied over the 90-second period. Hence, the mean number of consumers (over the beginning, the middle, and the end of the period) was used. The three slides that showed the highest, the average, and the low­est number of consumers were used to simulate the high, medium, and low consumer density settings, respec­tively. Pictures developed from the three slides are shown in Figure 2. Three video sequences that showed the same consumer density levels as the three slides did were also selected. The position for the camera, in each case, gave a view as if one were just entering the setting.

The subjects consisted of 123 individuals, recruited from passersby on the streets of a coastal city in the south of England. These subjects were then divided into 24 groups of five to six people. Respondents were asked to participate in a study of "individual responses to daily social situations" and were paid the equivalent of $15 each for their participation. Each group was ran­domly assigned to one of the slides or video sequences. Before the subjects watched the slide (on a screen) or the video sequence (on a 21-inch color monitor), they were asked to read a scenario that described a situation occurring at the ticket office. Half of the subjects within a group were given a high-choice scenario, while the other half were given a low-choice scenario.

The high-choice scenario was as follows: "It is 10 o'clock in the morning and Mr. Y is going by train to visit his friend. Tickets are sold in the railway station through the ticket office and through an automatic ma­chine located next to the office. Mr. Y decides to buy the ticket from the ticket office. Of course, he can always change his mind and go for the machine. However, he sticks to his original decision throughout the process. The video/slide we are going to show you depicts the setting of the ticket office while Mr. Y is there."

The low-choice scenario was: "It is 10 o'clock in the morning and Mr. Y is going by train to visit his friend. Tickets are sold in the railway station through the ticket

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office and through an automatic machine located next to the office. However, the machine only sells normal fare tickets. Since Mr. Y wants a cheap day return, he can only buy it from the ticket office. The slide/video we are going to show you depicts the setting ofthe ticket office while Mr. Y is there."

As revealed by the content of the scenarios, the high­choice consumer can use the machine to get his ticket and, therefore, staying in the ticket office is the con­sumer's own choice. On the other hand, the low-choice consumer does not have the alternative and must use the ticket office, whether he likes it or not. Finally, role­taking scenarios (using a hypothetical figure, Mr. Y) were used because they are more effective in inducing respondent involvement and are more commonly used in consumer research than role-playing scenarios are (Eroglu 1987).

After reading the scenario and viewing the slides or video, respondents completed a questionnaire that measured all the key dependent variables included in Figure 1. A total of 119 usable cases resulted (60 for slides and 59 for videotapes).

A Field Quasi-experimental Study Passengers were intercepted for interviews between

1 :30 P.M. and 7:00 P.M. on three weekdays, when they exited the same ticket office used in the slides and vid­eotapes. Respondents were asked to complete a ques­tionnaire regarding their experience in the ticket office. If, however, they were unable to participate because of time pressure, they were asked to complete the ques­tionnaire on the train and mail it back to the researchers. Among the 92 useful cases, 19 of them were acquired through the latter mail method.

The number of people at the ticket office was recorded during the interview. This was categorized into three different levels and treated as an indicator of consumer density. As in the laboratory study, consumer choice is defined as whether a respondent could have used the ticket-vending machine in the station. However, in the field study, the variable was measured directly from the respondent rather than operationalized by experimental manipulations.

No significant difference in the gender of respondents was found across the three procedures: slides, video­tapes, and field (X2 = 4.62, dj = 2, NS). This was par­ticularly important because gender has been shown to influence reactions to crowding (see, e.g., Baum and Koman 1976). Minor but significant differences were found in age, education, and income level among the three groups.

Questionnaire The dependent variables were measured by the same

set of scales used in the laboratory and the field studies. Perceived control was measured with two different

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FIGURE 2

PICTURES REPRESENTING THE THREE LEVELS OF CONSUMER DENSITY

A. Low-Density Situation

B. Medium-Density Situation

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ECOLOGICAL VALIDITY 277

C. High-Density Situation

scales. The first (CTLl, a = .77) was a seven-point se­mantic differential scale consisting of six items selected from the "dominant" scale of Mehrabian and Russell (1974) and the "helplessness" scale of Glass and Singer (1972). Three of the nine items contained in the "dom­inant" and "helplessness" scales were excluded either because the item was inappropriate to the context of our study or because it had a negative contribution to the reliability (Cronbach's a) of the scale. The second perceived control scale (CTL2, a = .61) contained three seven-point Likert-type items ("I would feel that ev­erything is under my control"; "I would feel it difficult to get my own way"; and "I would feel able to influence the way things were").

Perceived crowding was also measured by two dif­ferent scales: (a) Bateson and Hui's (1987) semantic differential scale of perceived crowding (CRD1, a = .86) and (b) a three-item Likert-type scale (CRD2; a = .75; "I would not feel crowded"; "I would feel that there are too many people in the setting"; and "I would feel that there is no space for me in the setting"). Pleasure was measured with Mehrabian and Russell's (1974) se­mantic differential scale (PLE 1, a = .86). Respondents were also asked to evaluate the service experience (on a seven-point scale ranging from "not at all" to "ex­tremely so") according to a list of 27 emotional terms. A second pleasure score (PLE2) was computed from

the respondents' ratings and the pleasure/displeasure value of each emotional term, determined by Bush's (1972) successive interval scales of adjectives denoting feelings. 3 Approach/avoidance was measured by asking respondents to report their degree of preference (PREF) for the situation (Mehrabian and Russell 1974). One additional question, "Could you have used the ticket machine for the service?" was added to the field-study questionnaire to operationalize self-reported consumer choice.

RESULTS The hypothesized relationships and the given mea­

surement procedures can be represented by the struc­tural equation model shown in Figure 1. In the labo­ratory setting, consumer density and consumer choice are experimentally manipulated variables, and, in the field setting, consumer density is operationalized by field observation and consumer choice is measured by a questionnaire item.

3The equation that we used in the computation was PLE2 = r.Ri · Pi, where Ri is the respondent's rating of the ith emotional term, and Pi is the pleasure or displeasure value of the ith emotional term, deter­mined by the Bush (1972) successive interval scale.

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TABLE 1

CORRELATION MATRICES OBTAINED FROM THE THREE PROCEDURES

CRDl CRD2 CTLl CTL2

Slides (n = 60): CRDl 1.000 CRD2 .710 1.000 CTLl -.582 -.592 1.000 CTL2 -.424 -.428 .666 1.000 PLEl -.656 -.597 .785 .460 PLE2 -.560 -.515 .659 .537 PREF -.657 -.517 .424 .338 Density -.449 .493 -.204 -.134 Choice -.201 -.118 .230 .071

Videotapes (n = 59): CRDl 1.000 CRD2 .729 1.000 CTLl -.710 -.569 1.000 CTL2 -.548 -.527 .714 1.000 PLEl -.699 -.623 .785 .607 PLE2 -.642 -.713 .700 .568 PREF -.517 -.384 .673 .524 Density .423 .423 -.332 -.255 Choice -.032 -.219 .319 .325

Field (n = 92): CRDl 1.000 CRD2 .655 1.000 CTLl -.440 -.372 1.000 CTL2 -.401 -.521 .417 1.000 PLEl -.577 -.624 .605 .488 PLE2 -.530 -.630 .536 .432 PREF -.465 -.446 .274 .312 Density .353 .311 -.173 -.181 Choice -.070 -.094 .076

Ecological validity requires a test of comparability; that is, the data obtained from the three different pro­cedures should confirm or disconfirm the same theo­retical model. Three different correlation matrices of all the independent and dependent variables, one from each of the three procedures (slides, videotapes, and field), were first computed (Table 1). Multigroup LIS­REL analysis was first used to test the equality of the three correlation matrices (Joreskog and Sorbom 1989, p. 256). The analysis produced a chi-square value of 96.58 with 90 df (p = .299). In other words, the hy­pothesis that the three correlation matrices are equal could not be rejected. Consistent with this result, when multigroup LISREL analysis was again used to test the hypothesized model, all the measurement and structural parameters were specified to be invariant across the three procedures. Despite the rigor of the constraints, the LISREL results indicate a reasonable fit. The model produced a chi-square value of 139.01 with 115 df(p = .063), and, as shown in Table 2 (the three-group anal­ysis), all the estimated parameters were significant and in the direction hypothesized by Hui and Bateson (1991).

The three correlation matrices, when used separately to test the theoretical model, produced chi-square values of 35.86 (slide), 33.34 (videotape), and 32.98 (field), all

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PLEl PLE2 PREF Density Choice

1.000 .650 1.000 .637 .457 1.000

-.242 -.174 -.205 1.000 .371 .213 .272 .042 1.000

1.000 .698 1.000 .629 .622 1.000

-.378 -.328 -.358 1.000 .163 .236 .118 .042 1.000

1.000 .663 1.000 .611 .455 1.000

-.318 -.106 -.327 1.000 .122 .059 .105 -.097 1.000

of which had 25 df and indicated reasonable fit (p = .074, .123, and .131, respectively). The estimated values of the key measurement and structural param­eters are given in Table 2. The magnitudes and signs are largely consistent across the three procedures. The only exception is that two parameters ({j31 and 1'22) ob­tained with the field data, although in the expected di­rection, are not significantly different from 0 at the .05 level (t-value = -1.21 and 1.00, respectively). Relaxing the equality constraint on these two parameters in the multigroup analysis, however, did not significantly im­prove the fit of the model. When the two parameters were allowed to vary under the field-procedure condi­tion, the chi-square value was reduced by 3.55 but had 2 df less (chi-square difference test: X2 = 3.55, df = 2, NS).

DISCUSSION

Our findings suggested that the two environmental simulations, photographic slides and videotapes, that we used to simulate the service setting and to manip­ulate consumer density did evoke the same psycholog­ical and behavioral phenomena as the actual service setting did. The three different procedures supported the same theoretical model, and the hypothesis that they

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ECOLOGICAL VALIDITY 279

TABLE 2

ESTIMATES OBTAINED FROM SINGLE- AND MULTIGROUP LlSREL ANALYSIS

Parameters Slides Videotapes Field Three group

AYll 1.000 1.000 1.000 1.000 AY21 .967 (7.45) .919 (7.50) 1.059 (7.69) .977 (12.94) Ay32 1.000 1.000 1.000 1.000 AY42 .715 (5.91) .783 (7.24) .897 (5.00) .794 (9.74) Ay53 1.000 1.000 1.000 1.000 Ay63 .814 (6.92) .937 (7.96) .866 (8.55) .883 (13.57) Ay74 1.000 1.000 1.000 1.000 {312 -.584 (-5.25) -.657 (-5.80) -.862 (-3.95) -.689 (-8.20) {331 -.423 (-2.65) -.403 (-2.37) -.387 (-1.21)8 -.430 (-3.81) {332 .565 (3.63) .547 (3.36) .843 (1.97) .625 (4.97) {343 .725 (5.80) .825 (6.49) .716 (6.58) .750 (10.69) I'll .349 (3.99) .221 (2.40) .157 (1.79) .245 (4.68) 1'21 -.202 (-1.65) -.349 (-3.03) -.181 (-2.13) -.218 (-3.49) 1'22 .263 (2.15) .324 (2.82) .078 (1.00)8 .195 (3.20)

Goodness-of-fit index .882 .898 .929 .873 b

.860 e

.896d

Root mean square residual .059 .047 .047 .068 b

.088e

.082 d

x2 35.86 33.34 32.98 139.01 df 25 25 25 115 P .074 .123 .131 .063

NOTE.-Maximum likelihood estimates. For the sake of simplicity, only the estimated values of the Ay , f3, and "y parameters are presented. Numbers inside the parentheses are the t-values of the estimates. Estimates without a t-value are fixed parameters. A t-value beyond ±1.64 indicates that the parameter is significantly different from zero (one-tailed test).

a The t-value indicates that the parameter is not significantly different from zero (p > .10). b Value given is for slides. e Value given is for videotapes. d Value given is from field.

produced identical estimates for all the parameters could not be rejected. This finding is all the more pow­erful given the presence of some minor variations in the demographic characteristics (age, education, and income) between the three groups of respondents. Moreover, the nature of the questioning varied, with respondents being asked to project for another individ­ual in the laboratory experiment and answering for themselves in the quasi-experimental study. As a result, we can claim that the findings obtained from using slides or videotapes have both internal and external validity, at least in this study. The large number of benefits that come from laboratory studies can thus be gained with­out apparently jeopardizing external generalizability.

The value of experimental control is actually shown in our findings. In the field study, when consumer choice was operationalized by a self-report measure, the rela­tionship between consumer choice and perceived con­trol (1'22), although in the expected direction, became nonsignificant. This finding is not unexpected because, in addition to choice, many other situational factors, such as waiting time, may also influence perceived con­trol. Lack of experimental control also provides an al­ternative explanation to the insignificance of the rela­tionship between perceived crowding and pleasure ({131).

In the field setting, pleasure may be influenced by many factors other than perceived crowding and perceived control (e.g., the friendliness of the ticket seller).

Limitations and Future Research To the extent that the results of this study are gen­

eralizable to other settings and theories, the develop­ment and validation of environmental simulations can help to solve the often conflicting demands of internal and external validity in consumer research on services. A number oflimitations of this study do, however, need to be pointed out.

The variable manipulated in our study, consumer density, is one that readily lends itself to visual repre­sentation. Consumer density can be easily depicted by a static view of the service setting; hence, either the slides or videotapes, both of which were used largely as static-perceptual simulations in our study, are adequate to produce the expected effects of consumer density. A more rigorous test would depict true interactions be­tween the consumer and the service setting or personnel. Under such situations, the ability of videotapes to cap­ture movement from a number of angles might make it a more appropriate choice. Such an approach would,

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however, introduce an additional variable, in the form of the skill of the cameraman and/or editor. Replication of this type of study is clearly needed to test such prop­ositions.

Static-perceptual simulations are also expected to be less effective than dynamic-perceptual simulations in representing large, complex service settings. For ex­ample, it will be difficult, if not impossible, to represent even a regular-sized supermarket with one or a few pic­tures. A videotape tour is likely to give the viewer a better understanding of the design and layout of the supermarket.

The two kinds of environmental simulations exam­ined in this study convey only visual images and elim­inate all other human sensory modes (Belk 1984). Re­search findings have suggested that a number of nonvisual cues, such as sound level and smell, will also influence human reactions to density (Eroglu and Har­rell 1986). Nonvisual environmental simulations (e.g., sound could have been included in our videotapes) would be another logical direction for future research.

In short, slides and videotapes are appropriate and ecologically valid when (a) researchers want to manip­ulate one or a few visible dimensions of a simple service setting and (b) researchers are not interested in studying ongoing interactive behaviors between the consumer and the service setting. For example, the simulations can be used when one wants to study the consumer's psychological and behavioral reactions to a simple retail or service setting (e.g., Bitner 1990; Eroglu and Machleit 1990).

For interactive simulations, many advanced tech­niques, such as sequences of photomontages, videotapes produced from models, and computer-driven simula­tions, have been used in environmental psychology (McKechnie 1977). Any study that requires the presen­tation of actions and motions or requires that the de­cisions of the consumer be reflected in the subsequent images can benefit significantly from these kinds of simulations (see, e.g., Carpman et al. 1985; Winkel and Sasanoff 1976). In researching the service encounter, one can explore the possibility of simulating the inter­actions between the consumer and the contact person­nel using the techniques mentioned above. These tech­niques can also be useful when researchers want to examine the movement of the consumer in a complex service setting, for example, studying the effects of con­sumer density and signs (Wener and Kaminoff 1983) on the movement of the consumer in a supermarket. The development and validation of these alternative visual simulation approaches deserve future attention from consumer researchers studying services.

Testing New Services

Simulations may also be useful in the development of new service offerings that are primarily experiential in nature. For many service firms, building a test outlet

JOURNAL OF CONSUMER RESEARCH

is a common practice in the development of new ser­vices. In fact, until recent times, service firms had little choice: this was the only alternative available. The em­ployment of environmental simulations, such as pho­tographs of mock-ups or models, should enable the consumer aspects of the setting to be improved without engendering the cost of building an outlet. Even if it is necessary to build a test outlet to perfect the operating procedures, the use of environmental simulations can still be valuable. For example, instead of having to build a number of outlets, the firm could produce simulations from a single test unit and obtain the same effects. The firm will then be able to test a new service nationally or even overseas without needing to build multiple test outlets. More research effort is essential to further ex­plore the contribution that the various kinds of simu­lations can make to new services development. This may be a fruitful avenue to explore, because our findings suggest that these "pretests" could be generalizable to real settings.

[Received March 1991. Revised December 1991.]

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