Journal of Hospitality & Tourism Research - Sage Publications

Journal of Hospitality & Tourism Research EXECUTIVE EDITOR K. S. (Kaye) Chon The Hong Kong Polytechnic University

EDITORIAL REVIEW BOARD Francis Adu-Kwansa, University of Delaware Robert Bosselman, Florida State University Carl P. Borchgrevink, Michigan State University John T. Bowen, University of Nevada, Las Vegas Fred J. DeMicco, University of Delaware Tim H. Dodd, Texas Tech University George G. Fenich, University of New Orleans Zheng Gu, University of Nevada, Las Vegas J. S. Perry Hobson, Southern Cross University Cathy H. C. Hsu, The Hong Kong Polytechnic University Yang H. Huo, Roosevelt University David Kirk, Queen Margaret University College Ken W. McCleary, Virginia Polytechnic Institute and State University Ady Milman, University of Central Florida Alastair M. Morrison, Purdue University Daniel Mount, The Pennsylvania State University H. G. Parsa, The Ohio State University Angela Roper, Oxford Brookes University Raymond Schmidgall, Michigan State University Carol Shanklin, Kansas State University Jeannie Sneed, Iowa State University Beverley Sparks, Griffith University Larry Stalcup, Georgia Southern University Hubert B. Van Hoof, Northern Arizona University

For Sage Publications: Amy Landru, Jim Kelly, Joe Cribben, Scott F. Locklear, and Elena Nikitina

Journal of Hospitality & Tourism Research VOLUME 25

n NUMBER 4

n

NOVEMBER 2001

CONTENTS ARTICLES A Comparison of the Views of Involved Versus Noninvolved Citizens on Quality of Life and Tourism Development Issues Claudia Jurowski and Desmond Omotayo Brown

355

Environmental Accounting of Municipal Solid Waste Originating From Rooms and Restaurants in the Hong Kong Hotel Industry Wilco W. Chan and Joseph Lam

371

Environmental Uncertainty Within the Hospitality Industry: Exploring the Measure of Dynamism and Complexity Between Restaurant Segments Robert Harrington

386

Tourism Forecasting and Its Relationship With Leading Economic Indicators Vincent Cho

399

An Assessment of the Effectiveness of Simulation as an Instructional System in Foodservice Andrew Hale Feinstein

421

The Dimensions of Organizational Climate in Four- and Five-Star Australian Hotels Michael Davidson, Mark Manning, Nils Timo, and Paul Ryder

444

PUBLICATION IN REVIEW Human Resources Management for the Hospitality Industry (2nd ed.) By Mary L. Tanke Reviewed by Terry Lam

462

Research Conferences

465

Conference Announcements and Calls for Papers

467

Reviewers

474

Index to Volume 25

476

JOURNALBrown Jurowski, OF HOSPITALITY / CITIZENS & ON TOURISM QUALITYRESEARCH OF LIFE

A COMPARISON OF THE VIEWS OF INVOLVED VERSUS NONINVOLVED CITIZENS ON QUALITY OF LIFE AND TOURISM DEVELOPMENT ISSUES Claudia Jurowski Northern Arizona University Desmond Omotayo Brown University of Kentucky Rural communities seeking to improve the quality of life for their residents often turn to tourism as a means to improve their economic position. The sustainability of any economic development plan is dependent on community organizations that are actively trying to control and shape their quality of life within their community. This study reveals that involved residents evaluate their quality of life higher than do the noninvolved residents. Even though the results indicated that there are no statistically significant differences in how involved versus noninvolved citizens evaluate the potential impacts of tourism, differences in the support each group indicated for the development of cultural tourism infrastructure were identified. The views of the involved citizens are important to decision makers because the involved citizens are the ones most likely to influence public policy. KEYWORDS: tourism; community organizations; empowerment; involvement; quality of life; Kentucky.

Rural communities seeking to improve the quality of life for their residents often turn to tourism as a means to improve their economic position and create jobs to maintain the existence of their community (Andereck & Vogt, 2000; Jurowski, 1998). At the same time, rural residents who value their clean environment and social structure resist efforts that would result in a deterioration of their lifestyle. For development strategies to be sustainable, they must be socially equitable, provide economic security, and maintain the integrity of the environment (Flint, 1999). Faced with such a challenge, many community organizations have become proactive and are attempting to control and shape their own destiny through both collective organization and social action (Heskin, 1991; Logan & Rabrenovic, 1990). Such involvement provides individuals with a direct link to the larger social and political structure and empowers individuals to effect changes (Miner & Tolnay, 1998). Journal of Hospitality & Tourism Research, Vol. 25, No. 4, November 2001, 355-370 © 2001 International Council on Hotel, Restaurant and Institutional Education

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JOURNAL OF HOSPITALITY & TOURISM RESEARCH

Scope of Community Organizations

In estimating the scope of community organizations in the United States, two main issues tend to make the discussion somewhat obscure. First, the total number of community organizations or the memberships they reach are virtually impossible to estimate. However, some estimates by the Alliance for Volunteerism estimate more than 6 million voluntary associations, and a study by ACTION indicates greater than 40 million volunteers, or one fourth of all Americans older than age 13. Second, the range in the scope of grassroots community groups complicates such estimates considerably. For example, in a field study of grassroots groups conducted by Langton (1978), at least three multistate organizations, a dozen citywide alliances, and thousands of neighborhood associations were identified. However, given that there are some 10,000 block clubs in New York City alone, the national estimates would be astronomical. In addition, these groups are expanding at an overwhelming rate. Problem Area

An understanding of the views of citizens who are involved in community organizations is critical to any development effort that seeks their cooperation and assistance. Community planners need to know how these residents view their quality of life and how they might react to proposed strategies. To date, little is known about community organization members’perceptions of tourism in a community. Hence, this study sought to better understand community involvement through community organizations by comparing the similarities and differences among citizen groups based on various levels of their community involvement and perceptions of their community’s tourism-related quality-of-life indicators. It expanded knowledge about how a specific subset of the population, that is, those who are members of community organizations, might respond to tourism development. Community organization membership was operationalized in this study as self-reported membership in one or more of the following types of organizations: school related, religious, civic, service, hobby oriented, organized sports for children, organized sports for adults, and neighborhood. The specific research question this study sought to answer is whether highly involved residents differed from those who are not at all involved or less involved on three specific aspects. The research question was as follows: Are there differences in the way each group (a) viewed its quality of life in relation to its community, (b) evaluated the impacts of tourism, and (c) expressed support for different types of tourism infrastructure development? The null hypotheses tested in this study were as follows: Hypothesis 1: There is no relationship between the viewpoints of residents on the quality of life in their community and membership in community organizations. Hypothesis 2: There is no relationship between the viewpoints of residents on the impacts of tourism on their community and membership in community organizations. Hypothesis 3: There is no relationship between residents’ support for different types of tourism and membership in community organizations.

Jurowski, Brown / CITIZENS ON QUALITY OF LIFE

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LITERATURE REVIEW The Role of Community Organizations

The literature on community organizations has become a focal theme in urban research in recent years. Most of the research in this area has centered on defining the role of such organizations and their meaning to society. For example, Logan and Rabrenovic (1990) described them as civic associations whose goals are to maintain and improve neighborhood quality of life and to protect common economic and social interests. Some posited that they are place specific, volunteer driven, shaped by the direct involvement of members, and defined by problem solving as their principal reason for existence (Berry, Portney, & Thompson, 1993; Florin & Wandersman, 1990; Haberle, 1989; Sampson, 1991). They defined the role of community organization as a means by which residents acting collectively with little or no professional help take control of their neighborhoods. Their objectives are often to obtain better city services, to fight crime, to engage local youths in prosocial activities, to protest and clean up environmental problems, or merely to organize a block party. Other researchers have concluded that participants’ economic resources or investments (e.g., home ownership) and the material benefit of protecting those investments were important reasons for their existence (Hyman & Wright, 1971; Prestby, Wandersman, Florin, Rich, & Chavis, 1990). From this perspective, it can be concluded that community involvement seeks to foster self-efficacy as residents work collectively to solve community problems (Perkins, Brown, & Taylor, 1996). Others have researched their changing status during recent years. For example, Hogan (1986) and Graham and Hogan (1990) have concluded that community organizations have recently assumed the roles of visible local organizations that confront public and private agents that pose threats to the social and physical well-being of the neighborhood. Schwirian and Mesh (1993) concluded that neighborhood residents have learned that there are limited prospects for outside political or economic help in their struggle against large-scale agents of change—city hall, the “growth machine” (a powerful coalition of government officials and local businesses that are united in the pursuit of economic development), and big development interests. Perkins (1995) contended that the concepts of empowerment are more apparent in small community-based organizations than in larger, more complex organizations. Reasons for Involvement

Membership in community organizations at the individual level has been identified as an intrapersonal component of psychological empowerment that defines how people think about their capacity to influence social and political systems (Rappaport, 1984; Zimmerman, 1994). It describes a self-perception that includes control, self-efficacy, motivation to exert control, and perceived competence (Berger & Neuhaus, 1977; Cornell Empowerment Group, 1989; Kieffer, 1984; Paulhus, 1983; Rappaport, 1984, 1987; Schulz & Israel, 1990; Swift & Levin, 1987; Zimmerman, 1990). Citizen involvement in grassroots community organi-

358


zations can be viewed as either an integral component of self-empowerment or as both a cause and effect of such empowerment (Perkins, 1995; Zimmerman, 1990). Thus, it is essential to understand why some individuals in communities are motivated to be more actively involved than others are. To date, there have been two major studies in the social psychology literature that have addressed community-focused predictors of citizen involvement in block associations. Unger and Wandersman (1983) examined neighboring behavior (such as loaning a tool or looking after each other’s house) on residential blocks in Nashville, Tennessee. They found that informal assistance facilitated block organizing. They also found that once a block is organized, association members engaged in more social interaction, which may lead to more neighborhood collaboration. From the same study, Florin and Wandersman (1990) derived personcommunity predictors of involvement based on cognitive social learning variables (CSLVs). Their version of the CSLV expectancies includes self- and collective efficacy, which are similar to the concept of psychological empowerment. They found encoding strategies (residents’ perceptions of satisfaction and dissatisfaction with community problems) to be a better predictor of involvement. One problem with this finding is that community satisfaction and perceptions may be related to involvement in different ways (Perkins, Florin, Rich, Wandersman, & Chavis, 1990). Residents may be satisfied with their community as a place to live and, at the same time, be critical of community problems. Thus, satisfaction alone may encourage involvement by enhancing other social cognitions and behaviors. Being satisfied with one’s community may give residents a greater sense of community and collective efficacy and may result in more favorable interaction among neighbors, all of which are predicted to lead to greater collective involvement. A psychological sense of community is also important to community involvement (Ahlbrandt, 1984). Chavis and Wandersman (1990) have clarified this process at the individual level by showing that, over time, a sense of community can lead, through greater self-efficacy, to collective involvement. Their results also suggest that involvement itself further enhances an individual’s sense of community. A major study of block associations was conducted in New York City. It systematically examined both the physical and social context of crime, fear, and citizen involvement in community organizations at the block level. No significant relationship was found between involvement and reported crime, perceived crime problems, victimization, fear, and informal social controls, despite considerable block variability. The built environment (as opposed to the natural environment), territoriality, neighboring (e.g., loaning a tool or looking after each other’s house), block satisfaction, and organizational efficacy, however, were significantly related to block association involvement, even after controlling for income, length of residency, and race. This latter finding suggests that perceived and actual problems or deficiencies in the physical environment may serve as catalysts for involvement and that community social cohesion may be an even more effective enabler of involvement.


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Involvement and Tourism

Several studies on resident attitudes toward tourism have determined that variability in support for tourism development differs by population segments (Allen, Long, Perdue, & Kieselbach, 1988; Ap, 1992; Jurowski, 1998; Murphy, 1983; Sheldon & Var, 1984; Tyrell & Spaulding, 1984; Um & Crompton, 1987). There is evidence to suggest that positive attitudes toward tourism may be related to how residents feel about life in their community. An expressed positive attitude toward tourism was positively correlated with a concern about the economic future of their community in the Perdue, Long, and Allen (1990) study. Another relationship was found by Johnson, Snepenger, and Akis (1994), who suggested that attitudes toward tourism might be a result of self-image and group-identity feelings rather than a belief that tourism will result in personal benefits. A few studies have focused on the relationship between attachment to a community and attitudes toward tourism (Brougham & Butler, 1981; Davis, Allen, & Cosenza, 1988; Jurowski, Uysal, & Williams, 1997; Lankford & Howard, 1994; Liu & Var, 1986; McCool & Martin, 1994; Pizam, 1978; Um & Crompton, 1987; Williams, McDonald, Riden, & Uysal, 1996). In some of these studies, the more the resident was attached to the community, the less support that resident expressed for tourism development. The findings of other studies were either inconclusive or contradictory. As suggested by Pearce, Moscardo, and Ross (1996), the contradictory findings may be attributable to differences in the way the community sentiment was measured. Three basic concepts were used to measure what was called attachment in the cited studies: (a) birthplace or length of residency, (b) sentiments about the community, and (c) involvement in the community. A more recent study demonstrated that the concept of attachment is composed of two elements, sentiment and involvement (Jurowski, 1998). The results of this study indicate that those who were willing to commit time and energy to improving their community were less optimistic about the impacts of tourism and somewhat less supportive of tourism development than those who evaluated their quality of life and emotional attachment to the community as being higher. METHOD Sample

The study took place in Lexington, Kentucky, internationally known as the home of the thoroughbred, which each year brings thousands of race fans and buyers to the city. Located about 81 miles south of Cincinnati and 74 miles east of Louisville, the area is generally known as the Bluegrass area and is located at the center of a 31-state distribution area and is within a 500-mile radius of nearly three fourths of the manufacturing employment, retail sales, and population of the United States. Planners have emphasized controlled growth as the key to the future of Lexington, because thoroughbred horse farms surround the city. The questions were designed to summarize public perceptions of the impact of tourism on the local economy and the level of public support expressed toward a variety of development options.

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The sample was composed of individuals eligible to vote in households with telephones in the Lexington/Fayette area. Using the Walsbery random-digit dialing method, a procedure that gives every residential telephone an equal probability of being called, the researchers attempted 760 calls in June 1998. Of those numbers called, contact was made with 497 individuals, 17 of whom were from households with no eligible respondent and 80 of whom refused to participate. Among the refusals, many were hang-ups in which it was impossible to determine whether there was an eligible person in the household. One refusal conversion attempt was made, and households who asked us to call back were called back up to seven times before the abandoning the number. The 163 remaining were not contacted because of one of the following conditions: disconnected phone, computer tone, business/government, perpetual no answers or busy signals, and abandonment after 15 attempts. Overall, 400 completed interviews were obtained, yielding a response rate of 52.6% for the study. Variables

Organization membership was measured by a question that asked respondents to indicate the number of organizations to which they currently belong or are involved in one of six categories. The categories were developed based on Babchuk and Booth’s (1969) typology. They included school-related organizations, such as a parent-teacher association or site-based council; religious organizations; civic organizations, such as Rotary, Kiwanis, or Lions organizations; service organizations, such as Red Cross, God’s Pantry, or Newcomers; hobbyoriented organizations, such as music, crafts, and so forth; organized sports for children; organized sports for adults; and neighborhood associations. Respondents were asked to mention any other organizations to which they belonged that were not mentioned. Residents’ evaluations of their quality of life were measured by questions that asked them to rate the quality of specific aspects of their community. The aspects selected included those defined in the literature as factors that are affected by tourism (Jurowski, 1998). Added to the list were education, quality of air transportation, and quality of public transportation. The impact scale was taken from the work of Jurowski (1994), who tested the scale for reliability and validity. Measures of support for the type of tourism residents prefer were based on Jurowski’s (1994, 1998; Jurowski et al., 1997) work. Additions to the type of tourism included in the instrument were made to adjust the instrument to local conditions. Research Method

Respondents were asked to list all of the organizations to which they belonged. The total number of organizations to which each respondent belonged was calculated. Respondents were placed in one of four categories: no group membership, member of one organization, member of two or three organizations, member of four or more organizations. Frequencies and percentages were calculated. A one-way analysis of variance (ANOVA) was used to determine whether any of the


361

observed differences in the level of involvement groups were significant with respect to their evaluation of their quality of life and the impacts of tourism and their support of various types of tourism infrastructure development. ANOVA allows for the comparison of mean scores from multiple samples to determine whether the differences in the means of the populations from which the samples were drawn are statistically significant. The null hypotheses assumed that the four levels of involvement means were equal for all variables. The analysis used an alpha level of 0.05. Tests for homogeneity of variance provided evidence of equality of variance. LIMITATIONS

In a telephone survey, there is always the potential of sample bias because all eligible respondents may not have telephones or may not be willing to participate. However, this threat is now considered to be minimal (Babbie, 1986). The study is limited by the measurement of community involvement because it was based on the number of organizations to which individuals belong. No attempt was made to classify the types of organizations or to segment the population on the role respondents played in the organization or their level of commitment to the organization. RESULTS Demographics

Approximately one half of the respondents were male (49.8%). The sample included a relatively balanced number of people in each age category. The vast majority of the respondents were White (90.5%), with a few other races being represented. A small number had been in the community less than 1 year (5.2%). The largest portions of the sample had incomes of between $20,000 and $40,000 or between $40,000 and $60,000. Table 1 provides details on the gender, age, race, length of residence, and income of the sample. Involvement

On the average, respondents belonged to 1.67 organizations within their communities. More than one fifth (20.3%) of the respondents belonged to one organization. Another 16.8% belonged to no organizations. A significant segment (42.5%) belonged to two or three organizations, and about one fifth (20.5%) belonged to four or more organizations (see Table 2). Quality of Life

The respondents indicated that they evaluated their overall quality of life as generally good. Especially good were the quality of the environment, recreational, shopping, and employment opportunities. The quality of education was also rated fairly high. Only a few items were rated fair: driving flow and traffic flow, the quality of public transportation, and the cost of land and housing. The

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Table 1 Demographics of Respondents Characteristic

%

Gender Male Female Age 18-34 35-44 45-54 55-64 Older than 65 Race White African American Hispanic Other Length of time in current neighborhood (in years) Less than 1 1-2 3-5 6-10 11-15 16-20 More than 20 Annual income (in dollars) Less than 20,000 20-39,999 40-59,999 60-79,999 80-99,999 More than 100,000

49.8 50.2 27.5 18.0 23.3 13.2 18.0 90.5 5.8 0.2 1.3 5.2 13.0 23.0 17.7 10.0 8.5 22.5 10.0 24.3 24.3 12.3 9.5 6.8

Note: Percentages may not equal 100 due to rounding error.

Table 2 Level of Involvement Level of Involvement No group membership Member of one organization Member of two or three organizations Member of four or more organizations Total

Frequency

Valid %

Cumulative %

67 81 170 82 400

16.8 20.3 42.5 20.5 100.0

16.8 37.0 79.5 100.05

analysis found statistically significant differences in mean scores in several of the quality-of-life variables. Significant differences were found between the groups in their evaluation of the quality of the environment, recreation opportunities, cultural opportunities, and overall quality of life. In this case, the first null hypothesis


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Table 3 Comparison of the Evaluation of Quality-of-Life Variables by Group Organization Membership/ Variable

Overall Mean = 0 Mean = 1 Mean = 2-3 Mean (n = 66) (n = 82) (n = 170)

Overall quality of life The environment Shopping opportunities Employment opportunities Recreation opportunities Education Cultural opportunities Costs of goods and services Quality of air transportation Crime rate Cost of land and housing Quality of public transportation Driving flow and traffic flow

Mean = 4 or more (n = 82)

F

Significance

3.12 3.06

2.99 2.93

3.04 2.93

3.18 3.10

3.20 3.23

3.08 4.11

.027* .007*

3.05

2.84

3.09

3.07

3.12

2.06

.106

2.97

2.86

2.92

3.03

3.11

1.53

.206

2.84 2.77 2.66

2.62 2.70 2.39

2.72 2.79 2.68

2.82 2.74 2.68

3.17 2.88 2.82

6.59 0.84 3.29

.000* .471 .021*

2.58

2.48

2.53

2.56

2.72

1.72

.161

2.58 2.47

2.57 2.27

2.48 2.48

2.54 2.50

2.74 2.59

1.87 2.08

.135 .103

2.26

2.10

2.33

2.24

2.37

1.54

.204

2.24

2.35

2.35

2.14

2.27

1.65

.178

1.97

1.97

1.91

1.94

2.06

0.456

.713

Note: Respondents were asked to indicate how they would rate the quality of the variables listed in their community on a scale in which 4 = excellent, 3 = good, 2 = fair, and 1 = poor. *Significant at the .05 level.

(Hypothesis 1) was rejected because a Tukey b multiple comparison test verified that individuals who belonged to four or more organizations were more likely to evaluate the quality of the environment, recreation opportunities, cultural opportunities, and overall quality of life significantly higher than those of other groups. An observation of the means indicates that those who belonged to no community organizations evaluated the quality of most aspects of their lives lower than those that were the most involved. Differences in the mean scores of the four groups along with ANOVA statistics are displayed in Table 3. Impacts of Tourism

The second null hypothesis (Hypothesis 2) was not rejected. No significant differences were found among the groups in reference to their evaluation of the impacts of tourism. However, those who belonged to no organizations appeared to be more optimistic than the average about the impact of tourism on employment opportunities, opportunities for shopping and recreation, the price of goods and services, the cost of land and housing, improvements in local services, relationships between residents and tourists, and the ability of tourism to preserve the local culture. This group appeared to be the most optimistic in more categories than other groups. Those who belonged to four or more organizations were also more optimistic than the average on three of the same items (recreation opportu-

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nities, the cost of land and housing, and preservation of the local culture). However, the latter group was more pessimistic about employment opportunities, opportunities for shopping, the price of goods and services, and the relationship between residents and tourists. Members of this group were, on the other hand, the most optimistic about the potential for improving traffic congestion and the crime rate. The mean scores and ANOVA statistics are displayed in Table 4. Types of Tourism Infrastructure Development

Overall, there was considerable support for the development of tourism infrastructure. In fact, the groups differed little on the type of tourism infrastructure they would support or oppose. The highest level of support was found for preserving rural land and horse farms. Nearly equally strong support was indicated for improvements in transportation, the development of cultural and folk events, and cultural or historic-based attractions. The types of tourism infrastructure development the Lexington residents were likely to oppose are theme parks, a new convention and civic center, and new facilities for sporting events. The third hypothesis (Hypothesis 3) can only be rejected for two of the types of tourism infrastructure the citizens would oppose or support. Significant differences were found in cultural or historic-based attractions and cultural and folk events. Support for these types of cultural tourism increased as the level of involvement increased. Details concerning the variations in support or opposition for various types of tourism infrastructure along with ANOVA statistics are delineated in Table 5. DISCUSSION

This study found evidence to confirm earlier research that noted a positive relationship between membership in community organizations and residents’ satisfaction with their quality of life (Florin & Wandersman, 1990). In addition, the relationship between group membership and concern about the built environment identified by Perkins et al. (1990) was confirmed. Residents who were members of a greater number of organizations evaluated their quality of life as higher than those who were not involved in community organizations did. They appeared to be slightly more supportive of specific types of tourism infrastructure development, especially those types of tourism infrastructure that will preserve the culture and history of their community. On the whole, the residents opposed large-scale infrastructure development such as a new convention center, theme parks, or a sporting events arena. It is interesting to note that there were no differences in the way the subsegments of the population viewed the impacts of tourism. It seemed as though residents, whether or not they were involved in community organization, were aware of how tourism would affect their lives. They realized that an increase in the number of visitors might provide increased revenues for government and better opportunities for employment, recreation, and shopping. It was clear that the respondents understood the economic benefits and costs. They appeared to be


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Table 4 Comparison of the Evaluation of Impact of Tourism Variables by Group Organization Membership/ Variable Revenues for local government Employment opportunities Opportunities for recreation Opportunities for shopping Preservation of local culture Relationship between residents and tourists Price of goods and services Local services (police, fire, etc.) Cost of land and housing Crime rate Traffic congestion



F

Significance

4.25

4.15

4.11

4.35

4.26

1.95

.121

3.89

3.91

3.95

3.89

3.82

0.92

.411

3.69

3.82

3.48

3.72

3.73

2.52

.058

3.65

3.87

3.56

3.66

3.52

2.59

.052

3.21

3.34

3.05

3.18

3.32

1.68

.170

3.21

3.40

3.19

3.17

3.14

2.20

.088

3.02

3.16

3.07

2.97

2.95

0.96

.412

2.88

2.73

2.98

2.89

2.88

1.04

.376

2.78 2.46 1.78

2.90 2.44 1.71

2.78 2.35 1.72

2.72 2.49 1.80

2.82 2.51 1.88

0.590 0.79 0.82

.622 .499 .483

Note: Respondents were asked to indicate how each item would be for them and other residents of their county if the number of tourists were to increase. Their responses were coded on a scale in which 5 = much better, 4 = somewhat better, 3 = about the same, 2 = somewhat worse, and 1 = much worse.

most concerned about traffic congestion and the crime rate. Residents in this community apparently evaluated the impacts of tourism similarly to those of other communities (Allen et al., 1988; Ap, 1992; Jurowski et al., 1997; Perdue et al., 1990). The lack of differences within population segments is important to tourism planners and developers because the viewpoints of the citizens that are most likely to influence public policy are not likely to be different from those of the general population. Similarly, the type of tourism supported or opposed by the various segments were alike. Even through significant differences were found in the intensity of support or opposition, in general all four groups supported cultural tourism infrastructure development and opposed tourism that required building on a large scale. Because the results indicate that there was little difference based on level of involvement in the support for specific types of tourism infrastructure, planners should develop relationships with community organizations for several reasons. First, the involved citizens appear to reflect the viewpoints of the general populace. Second, the involved citizens are those who are proactive and want to affect the future of their community (Heskin, 1991; Logan & Rabrenovic, 1990).

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Table 5 Comparison of the Type of Tourism Supported or Opposed by Group Organization Membership/ Variable Preserving rural land and horse farms Improved Transportation, facilities, and roads Cultural and folk events Cultural or historicbased attractions Nature programs Outdoor recreation programs and activities Horse shows and competitions Dinner playhouse, outdoor dramas, or amphitheaters Amateur sports competitions Renovated convention & civic center Promotion Professional sports development New facilities for sporting events New convention and civic center Theme parks



F

Significance

3.70

3.58

3.65

3.73

3.79

1.81

.146

3.64

3.64

3.71

3.61

3.63

0.59

.621

3.58

3.46

3.49

3.60

3.72

3.43

.017*

3.54 3.52

3.42 3.48

3.45 3.53

3.58 3.47

3.64 3.65

2.71 1.63

.045* .181

3.48

3.49

3.52

3.42

3.55

0.87

.456

3.43

3.29

3.49

3.40

3.56

2.32

.075

3.43

3.28

3.47

3.45

3.49

1.48

.220

3.29

3.28

3.29

3.49

2.85

1.30

.276

3.08 2.85

3.05 3.15

2.89 3.17

3.12 3.23

3.21 3.40

1.90 1.78

.129 .151

2.83

2.95

2.74

2.80

2.89

0.67

.573

2.62

2.76

2.66

2.56

2.62

0.59

.620

2.43 2.39

2.58 2.54

2.36 2.23

2.38 2.38

2.49 2.46

0.74 1.33

.531 .263

Note: Respondents were asked to indicate how much they would support or oppose each type of tourism development for the Lexington and Bluegrass, Kentucky, areas on a scale in which 4 = strongly support, 3 = somewhat support, 2 = somewhat oppose, and 1 = strongly oppose. *Significant at the .05 level.

Finally, the organizations provide planners with a direct link to those who are most likely to support or oppose their actions (Miner & Tolnay, 1998). The findings of this research indicate that planners and developers could use their limited resources most efficiently by working with the most active members of the community. The involved citizens can be an especially valuable asset to the planner because their views are similar to those of the general population and because they are somewhat more optimistic about their quality of life and less pessimistic about the impacts of tourism. In addition, actively involved citizens are


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likely to perceive that they can affect the outcome of a proposed development and may be more likely to volunteer their time and resources, especially for the development of cultural or historic events and attractions. FUTURE RESEARCH

More research is needed to determine if the involved citizens identified in this study are willing to participate in the tourism development process and to verify the hypothesis that suggested that tourism planners can use their resources better by focusing attention on the involved citizen. Knowledge is needed that will uncover which groups are most likely to become involved and to identify what role the individual groups would like to play in community planning and tourism development. More research is needed to determine how the tourism planner can best use those individuals who choose to become involved in their community. In addition, a better understanding of individuals who participate in tourism-related community development projects is needed to understand why they participate and how the tourism planner and/or developer can take advantage of their interest and support. An earlier study by Jurowski (1998) indicated that the involved citizen was somewhat less supportive of tourism development than were those citizens who were emotionally attached to their community. This study suggested that the involved citizen more strongly supports certain types of tourism than the noninvolved citizen. Future research focused on the involved citizens is needed to determine why these two studies provide conflicting information. Specifically, information is needed that will clarify whether weaker support for tourism infrastructure is based on a belief that other types of development may provide more benefits for the same cost or if weaker support can be equated to opposition to tourism development. REFERENCES Ahlbrandt, R. S., Jr. (1984). Neighborhoods, people and community. New York: Plenum. Allen, L. R., Long, P. T., Perdue, R. R., & Kieselbach, S. (1988). The impact of tourism development on residents’ perceptions of community life. Journal of Travel Research, 27(1), 16-21. Andereck, K. L., & Vogt, C. A. (2000). The relationship between resident’s attitudes toward tourism and tourism development options. Journal of Travel Research, 39(1), 27-36. Ap, J. (1992). Residents’ perceptions research on the social impacts of tourism. Annals of Tourism Research, 17(4), 610-616. Babbie, E. (1986). The practice of social research. Belmont, CA: Wadsworth. Babchuk, N., & Booth, A. (1969). Voluntary association memberships: A longitudinal analysis. American Sociological Review, 27, 647-655. Berger, P. J., & Neuhaus, R. J. (1977). To empower people: The role of mediating structures in public policy. Washington, DC: American Enterprise Institute for Public Policy Research.

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Berry, J., Portney, K., & Thompson, K. (1993). The rebirth of urban democracy. Washington, DC: Brookings Institution. Brougham, J. E., & Butler, R. W. (1981). A segmentation analysis of resident attitudes to the social impact of tourism. Annals of Tourism Research, 8, 569-590. Chavis, D. M., & Wandersman, A. (1990). Sense of community in the urban environment: A catalyst for participation and community development. American Journal of Community Psychology, 18, 55-82. Cornell Empowerment Group. (1989). Empowerment and family support. Networking Bulletin, 1, 1-23. Davis, D., Allen, J., & Cosenza, R. M. (1988). Segmenting local residents by their attitudes, interests, and opinions toward tourism. Journal of Travel Research, 31(4), 2-8. Flint, W. (1999). Sustainable development [Online]. Available: http://205.157.137.10/ ~sustainrwf/ee00002.htm Florin, P., & Wandersman, A. (Eds.). (1990). Citizen participation, voluntary organizations, and community development: Insights for empowerment through research. [Special section]. American Journal of Community Psychology, 18, 41-177. Graham, L., & Hogan, R. (1990). Social class and tactics: Neighborhood opposition to group homes. Sociological Quarterly, 31, 513-529. Haberle, S. (1989). Planting the grassroots: Structuring citizen participation. New York: Praeger. Heskin, A. D. (1991). The struggle for community. Boulder, CO: Westview. Hogan, R. (1986). Community opposition to group homes. Social Science Quarterly, 67, 442-449. Hyman, H., & Wright, C. (1971). Trends in voluntary association memberships in American adults: Replication based on secondary analysis of national sample surveys. American Sociological Review, 36, 191-206. Johnson, J., Snepenger, D. J., & Akis, S. (1994). Residents’ perceptions of tourism development. Annals of Tourism Research, 21, 629-642. Jurowski, C. (1994). The interplay of elements impacting resident perceptions of tourism: A path analytic approach. Unpublished dissertation, Virginia Polytechnic Institute and State University. Jurowski, C. (1998). A study of community sentiments in relation to attitudes toward tourism development. Tourism Analysis, 3(1), 17-24. Jurowski, C., Uysal, M., & Williams, D. R. (1997). An analysis of host community resident reactions to tourism. Journal of Travel Research, 36(1), 1-11. Kieffer, C. H. (1984). Citizen empowerment: A developmental perspective. Prevention in Human Services, 3, 9-36. Langton, S. (1978). Citizen participation in America. Lexington, MA: Lexington Books. Lankford, S. K., & Howard, D. R. (1994). Developing a Tourism Impact Attitude Scale. Annals of Tourism Research, 21, 121-139. Liu, J., & Var, T. (1986). Resident attitudes toward tourism impacts in Hawaii. Annals of Tourism Research, 13, 193-214. Logan, J., & Rabrenovic, G. (1990). Neighborhood associations, their issues, their allies and their opponents. Urban Affairs Quarterly, 26, 68-94. McCool, S. F., & Martin, S. R. (1994). Community attachment and attitudes toward tourism development. Journal of Travel Research, 32(3), 29-34.


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Miner, S., & Tolnay, S. (1998). Barriers to voluntary organization membership: An examination of race and cohort differences. Journal of Gerontology, 53B, S241-248. Murphy, P. E. (1983). Community attitudes to tourism. Tourism Management, 2(3), 189-195. Paulhus, D. (1983). Sphere-specific measures of perceived control. Journal of Personality and Social Psychology, 44, 1253-1265. Pearce, P. L., Moscardo, G., & Ross, G. F. (1996). Tourism community relationships. Oxford, UK: Elsevier Science Ltd. Perdue, R. R., Long, P. T., & Allen, L. (1990). Resident support for tourism development. Annals of Tourism Research, 17, 586-599. Perkins, D. D. (1995). Speaking truth to power: Empowerment ideology as social intervention and policy. American Journal of Community Psychology, 23, 765-794. Perkins, D. D., Brown, B. B., & Taylor, R. B. (1996). The ecology of empowerment: Predicting participation in community organizations. Journal of Social Issue, 52(1), 85. Perkins, D. D., Florin, P., Rich, R. C., Wandersman, A., & Chavis, D. M. (1990). Participation and the social and physical environment of residential blocks: Crime and community context. American Journal of Community Psychology, 17, 83-115. Pizam, A. (1978). Tourism’s impacts: The social costs to the destination community as perceived by its residents. Journal of Travel Research, 16(4), 8-12. Prestby, J. E., Wandersman, A., Florin, P., Rich, R. C., & Chavis, D. M. (1990). Benefits, costs, incentive management and participation in voluntary organizations: A means to understanding and promoting empowerment. American Journal of Community Psychology, 18, 117-149. Rappaport, J. (1984). Studies in empowerment: Introduction to the issue. Prevention in Human Services, 3, 1-7. Rappaport, J. (1987). Terms of empowerment/exemplars of prevention: Toward a theory for community psychology. American Journal of Community Psychology, 15, 121-148. Sampson, R. (1991). Linking the micro and macro dimensions of community social organization. Social Forces, 70, 43-64. Schulz, A. J., & Israel, B. I. (1990). Empowerment and empowering processes: A theory development seminar series, academic year 1988-1989. Unpublished manuscript, University of Michigan, Center for Research on Social Organization, Program on Conflict Management Alternatives, Ann Arbor. Schwirian, K. P., & Mesh, G. (1993). Embattled neighborhoods: The political ecology of neighborhood change. In R. Hutchison (Ed.), Research in urban sociology (Vol. 3, pp. 83-110). Greenwich, CT: JAI. Sheldon, P. J., & Var, T. (1984). Resident attitudes to tourism in North Wales. Tourism Management, 5(1), 40-47. Swift, C., & Levin, G. (1987). Empowerment: An emerging mental health technology. Journal of Primary Prevention, 8, 71-94. Tyrell, T. J., & Spaulding, I. A. (1984). A survey of attitudes toward growth in Rhode Island. Hospitality Education and Research Journal, 8, 22-23. Um, S., & Crompton, J. L. (1987). Measuring residents’ attachment levels in a host community. Journal of Travel Research, 26(2), 27-29. Unger, D. G., & Wandersman, A. (1983). Neighboring and its role in block organizations. American Journal of Community Psychology, 11, 291-300.

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Williams, D. R., McDonald, C. D., Riden, C., & Uysal, M. (1996). Community attachment, regional identity and resident attitudes toward tourism. In 26th Annual T TRA Conference Proceedings, Acapulco, Mexico, pp. 424-431. Zimmerman, M. A. (1990). Taking aim on empowerment research: On the distinction between psychological and individual conceptions. American Journal of Community Psychology, 18, 169-177. Zimmerman, M. A. (1994). Empowerment theory: Psychological, organizational and community levels of analysis. In J. Rappaport & E. Seidman (Eds.), The handbook of community psychology. New York: Plenum.

Submitted October 28, 1999 First Revision Submitted June 25, 2000 Second Revision Submitted December 1, 2000 Accepted December 20, 2000 Refereed Anonymously Claudia Jurowski, Ph.D., is an associate professor in the School of Hotel and Restaurant Management at Northern Arizona University (Flagstaff, Arizona), and Desmond Omotayo Brown, Ph.D. (e-mail: [email protected]), is an associate professor in the division of Hospitality and Tourism Management at the University of Kentucky (Lexington, KY 40506-0050).

JOURNAL Chan, LamOF / MUNICIPAL HOSPITALITY SOLID & TOURISM WASTE RESEARCH

ENVIRONMENTAL ACCOUNTING OF MUNICIPAL SOLID WASTE ORIGINATING FROM ROOMS AND RESTAURANTS IN THE HONG KONG HOTEL INDUSTRY Wilco W. Chan The Hong Kong Polytechnic University Joseph Lam City University of Hong Kong This article focuses on the estimation and the environmental accounting of municipal solid waste (MSW) produced by the hotel industry in Hong Kong. Five models to estimate the amount of the hotel industry’s MSW were developed. It was revealed that plastic toiletries in the industry ranked highest, and newspapers ranked second. Also, the research found that the minimum amount of MSW produced for each occupied room was 1.978 kg, and the quantity of MSW created by the Hong Kong hotel industry reached at least 53,070 tons in 1996, with an estimated environmental cost of 3.02 million Hong Kong dollars. The model predicted that local hotels would produce 53,607 tons of MSW by the year 2000. On average, the hotel industry’s share in the overall MSW was 1.5% in the 1986 to 2000 period. Based on the methodologies and findings, suggestions concerning green accounting at three levels are made. KEYWORDS: municipal solid waste; landfill; hotel; plastic toiletries; environmental costs.

Since the Rio Earth Summit in 1992, the green movement has gained momentum in the hotel industry worldwide through the efforts of various associations and activities. Notably, when the Prince of Wales launched the International Hotels Environment Initiative (IHEI) in 1993, 11 international hotel chains agreed to work together and initiated the development of a manual to embrace a comprehensive campaign to advance environmental performance in the hotel industry (IHEI, 1993). In the following year, another 16 hotel groups in the Asia Pacific Rim echoed this campaign and formed the first regional chapter—the Asia Pacific Hotels Environment Initiative (Mackie, 1994). In the same year, the Hotel & Catering Institute Management Association participated in Green Globe, an environmental management awareness program initiated by the World Travel Tourism Council (Anonymous, 1994). Journal of Hospitality & Tourism Research, Vol. 25, No. 4, November 2001, 371-385 © 2001 International Council on Hotel, Restaurant and Institutional Education

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In Hong Kong, a survey conducted in 1992 found that about 30% of hotels had launched environmental programs, with varying degrees of success (Barlett, 1992). The thrust of the green campaign in the local hospitality sector focused mainly on energy savings. Municipal waste management received very little attention until the mid-1990s. It is generally believed that the unenthusiastic response to reduce solid waste in hotels was due mainly to the anticipated high capital cost associated with the purchase of recycling equipment and the increased labor involvement. Furthermore, there was difficulty in converting the environmental impact of municipal solid waste (MSW) produced by hotels into a corresponding environmental cost. In the 1980s, the green issue in the hospitality literature in the United States centered on energy efficiency. Concerns about solid waste grew significantly in the early 1990s. In 1990 and 1991, trade journals raised the alarm about the “garbage crisis” (Crosby, 1990; Foss, 1990; Hasek, 1991; King, 1991; Townsend, 1990). Trade associations began to develop resource packages about solid waste management and published monthly articles on this topic (Crosby, 1990). The articles in this period highlighted different approaches taken by hotel properties and foodservice operations to address the solid waste problem. Scholars also echoed these developments (Shanklin, Petrillose, & Pettay, 1991). Coupled with the decrease in landfill space, commentaries and articles in research journals demanded that the U.S. government and the private sector take a proactive stance to deal with this issue (Cummings & Cummings, 1991; Environmental Protection Agency, 1989; Schwartz & Miller, 1991). Following these publications was a study of the composition and the amount of waste generated by hotels (Pettay, 1992). In 1993, some suggested future research directions in greening hotels were proposed (Nicholls & Nystuen, 1993; Shanklin, 1993), and a case study about solid waste minimization practices was subsequently undertaken in a megaresort (Cummings, 1997). Research work, however, has largely focused on individual waste measurement and reduction practices. There has been little coverage on green accounting for pollutants such as MSW in lodging industry. In the nonhospitality field, accounting for the environment has received much more attention. Contemporary environmental accounting research can be traced back to 1971 (Mathews, 1997). In his study, Mathews reviewed the previous 25 years of social and environmental accounting literature and grouped the work into seven classifications: empirical studies, normative statements, philosophical discussion, the nonaccounting literature, teaching programs, textbooks, and other reviews. The hospitality industry’s share of this green accounting initiation, however, is very small. The action plan for sustainable development, Agenda 21, adopted at the Rio Earth Summit 1992, has been a key factor in driving industry and business to recognize environmental management. Its chapter 30 has further encouraged business and industry to report annually on their environmental records as well as on their use of energy and natural resources. The first survey of green reports from 100 companies operating worldwide did not include a single hotel company (United Nation Environmental Program Industry and Environment Office, 1994). This suggests that the hotel industry in general has been slow to introduce green reporting.

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In Australia, an opinion survey about the perception of the materiality of environmental information in company reports was conducted in 1997. The study found that the importance of environmental performance information ranked 4th (mean = 3.62), environmental policies information ranked 6th (mean = 3.51), cost of environmental programs ranked 8th (mean = 3.41), and the cost of environmental compliance ranked 11th (mean = 3.37) (Deegan & Rankin, 1997). Based on a 5-point scale, this research revealed that the general public had a slightly above average interest in seeking environmental performance information about a particular company. In 1998, the International Federation of Accountants released an International Auditing Practice Statement about the consideration of environmental matters in the audit of financial statements. It reported that accountants around the world expressed a great deal of interest in and a positive reaction to the topic. Further documents on this topic are being planned. In the light of these developments, this study investigates the MSW issue in the hotel sector. The objectives are (a) to estimate the minimum amount of MSW generated in guest rooms and restaurants in the hotel industry, (b) to estimate the amount of MSW produced in the period from 1986 to 2000, and (c) to cost the external effect exerted by MSW in the hotel industry. A new conceptual framework for predicting the minimum amount of MSW in the hotel industry and its environmental cost was developed. It is hoped that the information and benchmark built up in this study will be used to construct green indicators for future reports of hotel operations and statistics in the hotel industry. It is envisaged that the established norms will provide a foundation for further analysis on the environmental costs incurred by an individual hotel and by the hotel industry generally. METHOD

Because most hotels do not employ individuals trained in statistical analysis, the use of robust statistical techniques is inappropriate (Redlin & deRoos, 1980). Instead, all MSW ratios described in the study are based on the industry practice of analyzing performance on a per room and per check-in guest basis. Sample and Measurement

For the room department of hotels, there are four major identifiable categories of waste. The first type of waste is plastic toiletries, such as shampoo bottles, bath foam bottles, combs, shower caps, toothbrushes, and toothpaste tubes. The second category is unused portions of soap. The third type is slippers, and the fourth is newspapers. Midscale hotels account for 70% of the market share in Hong Kong. Therefore, samples of plastic toiletries, soap, slippers, and newspapers were collected from 20 midscale hotels in 1996. Electronic scales were used to measure the weight of these four types of solid waste. For the solid waste originating from hotels’ restaurants, 14 samples from two midscale hotels were considered. The sampled solid waste included all items that were disposed of in plastic garbage containers, including paper napkins, paper place mats, straw, organic

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food remains, and so on. This solid waste was collected and weighed for 7 days in both hotels. All together, there were 14 samples. The number of meal covers was also recorded. Model Specification

The theoretical framework of environmental accounting for the hotel industry’s MSW considers the green costs of five independent variables, namely, in-room plastic waste, unused soaps, disposed slippers, discarded newspapers, and MSW originating from the hotel restaurants. The main equation for predicting the green cost originating from the minimum amount of MSW in the hotel industry can be expressed as follows: ECmsw = (E1)κ + (E2)κ + (E3)κ + (E4)κ + (E5)κ,

(1)

where ECmsw is the environmental cost of municipal waste created by the rooms and restaurants in the hotel industry, E1 is the estimated amount of plastic waste produced in the room, E2 is the estimated amount of unused soaps, E3 is the estimated amount of discarded slippers, E4 is the amount of newspapers, E5 is the predicted amount of solid waste originating from the hotel restaurants, and κ is a constant parameter associated with the cost environmental conversion. Figure 1 shows the steps taken in constructing this model for predicting the green cost attributable to solid waste produced by the hotel industry. To predict the minimum amount of each type of solid waste, that is, E1, E2, E3, E4, and E5, a further five subequations were developed. The first four subequations are based on the assumption that the amount of weight of waste per check-in guest, multiplied by the actual number of check-in guests, is equal to the amount of waste produced by all check-in guests. The remaining subequation is related to solid waste produced in hotel restaurants and is based on the product of the weight of waste per meal cover and the number of meal covers. Fifteen housekeepers and 10 restaurants managers were asked to determine the magnitude of the discount factors or adjustment ratios set in the subequations, as follows: E1(plastic waste) = (AnDn)(W1Cβ1),

(2)

where An is the number of occupied rooms in year n, Dn is the double occupancy ratio in year n, W1 is the average weight of total plastic waste per room in the sampling year, C is a constant (assumed to be 0.5), and β1 is the discounting factor based on the actual consumption of plastic toiletries. Because not all rooms (An) were occupied by two guests, the estimated number of customers actually staying in hotel rooms could be obtained by multiplying the number of occupied rooms by the double occupancy ratio (Dn). The average weight (W1) of plastic toiletries per room was obtained in the sampling measurement and was then divided by two (i.e., C = 0.5) to reflect the weight of plastic waste per check-in guest. Discounting for the amount of disposed toiletries was considered because some bath kit items might have been used for more than 1 day. A discount factor of 20% was used for the period from 1986 to 1996.


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Figure 1 Steps in Building a Model That Predicts the Environmental Costs Attributable to Municipal Solid Waste (MSW) Generated in the Hotel Industry

Similarly, E2(soaps’ remains) = (AnDn) (W2Cβ2).

(3)

W2 is the average weight of soaps collected per room basis in the sampling year, and β2 is the discounting factor based on the actual consumption of soaps. The estimation of actual number of check-in guests followed the same principle used in equation E1. Discounting was applied to the average weight of soap obtained in the sample analysis because the unused portions of soap were discarded. The discarded amount was estimated to be 50% of the original. Slippers are another major source of waste in many midscale hotels in Hong Kong. The equation to estimate the number of discarded slippers is as follows:

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E3(discarded slippers) = (AnDn) (W3Cβ3),

(4)

where W3 is the averaged weight of paired slippers on a per room basis in the sampling year, and β3 is the discounting factor on the actual consumption of slippers. The number of users of slippers was assumed to be equal to the number of check-in customers. The average weight of the slippers was discounted because some slippers may be used for more than 1 day. After considering the reuse practice for guests staying for 2 days or more, a 20% discount factor was adopted. Newspapers are another category of waste produced in hotel rooms. The estimation of this sort of waste was also based on the multiplication of the number of occupied rooms and the adjusted average weight of newspapers, as follows: E4(newspapers) = (An)(W4β4),

(5)

where W4 is the average weight of newspapers, and β4 is the discount factor based on the weight of newspapers. The weight of the local newspapers increased in the past decade. First of all, the increase in the selling price of newspapers in the past provided the publisher a larger profit margin, allowing the press to enhance the content, ranging from overseas financial news to international sports news. Second, the economic boom in the past years also encouraged business and other entities to advertise more. To reflect the weight of the pre-1996 newspaper, the average weight of the sample newspaper was discounted by 10% for every 3-year period, working backward. The 10% discount was based on the average number of pages and can only be regarded as a rough estimate. To enhance the accuracy of this measurement, it would be useful if any environmental center could record the actual weight of each newspaper in future. Only one set of newspapers for each room was assumed in the calculation. Solid waste such as paper napkins, paper place mats, carton boxes, plastic film, and organic matter is generated in hotel restaurants. An equation that comprises the product of the number of meal covers in the industry and the average weight of waste per cover was applied to estimate the amount of waste produced. Thus, E5(restaurants’ waste) = (NnRn ÷ Sn)(Mn)(W5),

(6)

where Nn is the average number of available rooms in a day in period n, Rn is the restaurant food revenue per available room in period n, Sn is the revenue per seat in period n, and Mn is the estimated number of meal covers served per seat (i.e., turnover ratio) in period n given in the annual survey (Hong Kong Tourist Association, 1977-1997). Mn is used to multiply the derived number of seats (i.e., NnRn ÷ Sn) available in the industry, and W5 is the average weight of measured solid waste per meal cover. Due to resource restrictions, only 14 samples collected in two hotels were used as an indicative reference for estimating the average waste per cover. Thus, it would be useful to do a larger scale study of the weight of different types of restaurant waste in future.


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Environmental Cost Conversion

From the early 1970s to the late 1980s, Hong Kong did not have any long-term planning system for dealing with solid waste. Since the publication of its statutory Waste Disposal Plan in 1989, the local government has been following this blueprint to establish an infrastructure to handle and dispose of a variety of waste. The infrastructure includes three large modern landfills and a network of nine refuse transfer stations (RTSs). Waste collected in the urban area is delivered to the RTSs, where it is compacted in purpose-built containers for onward transportation to the remote landfills. Waste collection from individual hotel premises is largely undertaken by cleaning companies contracted by the hotel management. The role of these cleaning companies is to take waste to designated refuse collection points at street level, where it becomes the responsibility of the municipal councils and private contractors to transport the refuse to the refuse transfer stations. The cost conversion exercise was based on four indicative environmental costs (κ) (Chung & Poon, 1994): the cost of vehicular refuse collection, the operational costs (including depreciation) of RTSs, the cost of landfill site construction, and the subsequent operational costs (including discharging untapped methane gas, which may give rise to the greenhouse effect). The environmental cost data established by Chung and Poon were based on 1994 market prices. To reflect the actual price levels in different years, the cost analysis was therefore adjusted according to the inflation rates in the respective years. RESULTS AND DISCUSSION Quantity of MSW

Table 1 shows the mean weight of sample waste per room with a confidence interval of 95% for a 15-year period from 1986 to 2000. The mean weight was based on the measurement made in 1996, and the discounting factors were estimated based on information from 15 experienced housekeeping staff. Because of hygiene and convenience, the reuse potential of plastic toiletries is low. This makes plastic toiletries the heaviest MSW at 0.594 kg per room. It is therefore suggested that more attention should be paid to the recycling of these plastic materials. For instance, the installation of lotion dispensers could be an alternative. Also, the selling of newspapers to waste collectors for recycling should be promoted, and the return of soap remains to special collectors should be considered. The amount of MSW generated from the hotel restaurants was estimated to be 0.751 kg per meal cover. This is slightly higher than the average of 0.665 kg reported in the United States (Pettay, 1992). This could be due to the inclusion of Chinese restaurants in the present study. Chinese restaurants tend to offer more menu items and more fresh items than their Western counterparts. This implies that more organic waste and more packaging materials are generated.

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Table 1 The Weight of Municipal Solid Waste Generated in Rooms and Restaurants Per Room Basis

Per Cover Basis

Plastic Laundry Paired Original Room Restaurant Toiletries Bag Slippers Soap Newspapers Waste Waste Mean Standard deviation Confidence intervals at 95% Discount factor (in percentages) 1986-1996 1997-1998 1999-2000 Discounted mean 1986-1996 1997-1998 1999-2000

0.742 0.078 0.705 to 0.778

80 70 65 0.594 0.519 0.482

0.181 0.011

0.833 0.055

0.554 0.081

0.176 0.420 0.575 to 0.185 to 0.481 to 1.091

0.174 to 0.934

30 20 20 0.054 0.036 0.036

0.451 0.065

80 70 70 0.361 0.316 0.316

50 40 40 0.417 0.333 0.333

2.761 0.119

2.204 0.693 to 3.315 to 0.808

10a 10 10 0.554 0.499 0.499

0.751 0.100

NA NA NA b

1.980 1.704 1.666

NA NA NA c

NA NA NA

Note: All values are in kilograms (except for discount factor percentages). a. A 10% discount factor was applied for the periods 1994-1996, 1991-1993, 1988-1990, and 1986-1987 based on the successive period’s weight. b. Discounted mean weight of each newspaper was 0.554 kg for the years 1994-1996, 0.499 kg for the years 1991-1993, 0.449 kg for the years 1988-1990, and 0.404 kg for the years 1986-1987. c. Daily discounted mean weight of total room waste was 1.98 kg for the years 1994-1996, 1.925 kg for the years 1991-1993, 1.875 kg for the years 1988-1990, and 1.83 kg for the years 1986-1987.

Based on the estimated weight of the MSW, the number of guests, and the total number of guest rooms in Hong Kong, the amount of MSW generated by the local hotel industry was determined for the 15-year period. The results are shown in Table 2. It can be seen that the total room waste rose steadily from 15,953 tons in 1986 to 31,605 tons in 1996. The sudden drop in 1997 was due mainly to the sharp downturn in the tourist industry (as a result of the Asian financial crisis) and the public’s growing awareness of the issue of environmental protection (as a result of green campaigns). Environmental Cost

Table 3 shows the summary of the breakdown of environmental costs for the 15-year-period from 1986 to 2000. Using 1994 as the basis for comparison, it was found that vehicular refuse collection (HK$252) was the most significant among the four green costs studied. To reduce this pollution cost, hotel environmentalists should not only minimize MSW but should also put more pressure on the municipal council’s vehicles and the light oil companies.

Table 2 Estimation of Room Waste and Restaurant Waste, 1986-2000 Plastic Toiletries

Year

Estimated Number of Guests

1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

9,414,536 10,358,591 12,370,879 12,081,303 12,172,849 12,796,307 16,058,762 17,188,969 15,585,409 16,407,013 17,988,845 13,908,143 15,303,731 16,487,021 18,343,495

Annual Discount Discard Factor (kg) 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.7 0.7 0.65 0.65

5,588,469 6,148,860 7,343,354 7,171,461 7,225,803 7,595,888 9,532,481 10,203,372 9,251,499 9,739,203 10,678,178 7,223,889 7,948,758 7,951,690 8,847,068

Laundry Bag

Slippers

Soap

Annual Discount Discard Factor (kg)



0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.2 0.2 0.2 0.2

511,209 562,471 671,739 656,015 660,986 694,839 871,991 933,361 846,288 890,901 976,794 503,475 553,995 596,830 664,035

0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.7 0.7 0.7 0.7

3,396,765 3,737,380 4,463,413 4,358,934 4,391,964 4,616,908 5,794,001 6,201,780 5,623,216 5,919,650 6,490,375 4,390,801 4,831,388 5,204,953 5,791,041

0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.4 0.4 0.4 0.4

3,921,154 4,314,353 5,152,471 5,031,863 5,069,992 5,329,662 6,688,474 7,159,206 6,491,323 6,833,521 7,492,354 4,634,193 5,099,203 5,493,475 6,112,053

Occupied Room

Discount Factor

Total Annual Discard (kg)

6,276,358 6,905,727 7,683,776 7,794,389 8,115,899 8,530,871 10,036,726 10,810,672 10,390,273 10,254,383 10,771,763 9,272,095 10,202,487 10,991,347 12,228,997

0.404 0.404 0.449 0.449 0.449 0.499 0.499 0.499 0.554 0.554 0.554 0.499 0.499 0.499 0.499

2,535,649 2,789,914 3,450,015 3,499,681 3,644,039 4,256,905 5,008,326 5,394,525 5,756,211 5,680,928 5,967,557 4,626,775 5,091,041 5,484,682 6,102,269

Newspapers

Restaurant Waste Room Waste (tons)

Estimated Number of Cover

Annual Disposal (tons)

15,953 17,553 21,081 20,718 20,993 22,494 27,895 29,892 27,969 29,064 31,605 21,379 23,524 24,732 27,516

25,111,749 29,397,425 31,982,673 30,100,882 27,406,969 27,724,076 31,114,877 32,211,848 28,405,570 30,819,735 28,582,141 30,011,249 31,511,811 33,087,401 34,741,772

18,859 22,077 24,019 22,606 20,583 20,821 23,367 24,191 21,333 23,146 21,465 22,538 23,665 24,849 26,091

Note: The drop of discount factor on or after 1997 was due mainly to the growing awareness of environmental protection thanks to green campaigns and the increasing cost-consciousness due to the recent tourist slump. A 10% discount factor on the weight of newspapers was applied for the periods 1994-1996, 1991-1993, 1988-1990, and 1986-1987 based on the successive period’s weight.

379

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Table 3 Breakdown of Environmental Costs (cost in Hong Kong dollars per ton)

Year

Vehicular Refuse Collectiona

Use of Refuse Transfer Stationsb

Landfill Site Construction and Operationc

Air Pollutiond

Total

1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

131 147 147 151 190 195 229 240 252 271 295 317 333 349 367

66 68 68 72 76 78 82 85 88 89 95 101 106 111 117

24 28 32 39 49 59 69 80 75 85 94 103 108 114 119

48 50 51 54 59 66 75 83 90 99 105 111 116 122 128

269 292 298 316 374 398 455 488 505 544 590 632 663 696 730

a. Vehicular refuse collection cost was based on Chung and Poon’s (1994) study and adjusted according to the rate of annual change in the average price of light diesel for motor vehicles. A 5% rate of increase was assumed for 1998 to 2000. b. The variable costs of refuse transfer stations in base year 1996 included the amortized capital costs, recurrent cost, assumed 15 years of life, and the amount of municipal solid waste published in Environment Hong Kong (Environmental Protection Department, 1996). Adjustment was then made for other years according to annual increase/decrease in the consumer price indexed electricity prices. A 5% rate of increase in electricity price was assumed for 1998 to 2000. c. Landfill cost before 1993 and after 1993 was available from Environmental Protection Department (1993) yearbook. The costs in other years were adjusted with the rate of change of de-indexed salaries. d. The air pollution cost was estimated by Chung (1996). Adjustment in remaining years was based on inflation rates in respective years.

Table 4 shows the estimates of MSW generated in hotel restaurants. The lowest amount, 18,859 tons, was recorded in 1986, and the highest was 24,191 tons recorded in 1993. These figures excluded the waste generated in room service. The total amount of MSW originating from hotels grew steadily from 34,811 tons in 1986 to 53,070 tons in 1996. The growth rate in this 11-year period was 52.4%. On average, the hotel industry’s share of the total amount of the city’s MSW was 1.5% in this period. Table 4 also shows the environmental costs, at the current price, of solid waste incurred by the local hotel industry. The total environmental cost attributable to MSW rose from HK$9.36 million in 1986 to HK$31.31 million in 1996. The rate of increase in these 11 years was 235%. For the Rooms Division, the environmental costs of MSW per occupied room night in 1986 and 1996 were HK$0.68 and HK$1.73, respectively. The latter was equivalent to 3.5% of the departmental

Table 4 Estimation of Environmental Costs Attributable to Municipal Solid Waste Generated in the Hotel Industry

Year

Estimated Number of Covers

Average Weight per Cover (kg)

Estimated Amount of Restaurant Waste (tons)

1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

25,111,749 29,397,425 31,982,673 30,100,882 27,406,969 27,724,076 31,114,877 32,211,848 28,405,570 30,819,735 28,582,141 30,011,249 31,511,811 33,087,401 34,741,772

0.751 0.751 0.751 0.751 0.751 0.751 0.751 0.751 0.751 0.751 0.751 0.751 0.751 0.751 0.751

18,859 22,077 24,019 22,606 20,583 20,821 23,367 24,191 21,333 23,146 21,465 22,538 23,665 24,849 26,091

Estimated Estimated Environmental Environmental Costs (restaurant) Costs in Hong Kong a Dollars (millions) per Ton 269 292 298 316 374 398 455 488 505 544 590 632 663 696 730

Estimated Environmental Costs per Cover

Estimated Number of Occupied Rooms

0.20 0.22 0.22 0.24 0.28 0.30 0.34 0.37 0.38 0.41 0.44 0.47 0.50 0.52 0.55

6,276,358 6,905,727 7,683,776 7,794,389 8,115,899 8,503,871 10,036,726 10,810,672 10,390,273 10,254,383 10,771,763 9,272,095 10,202,487 10,991,347 12,228,997

5.07 6.45 7.16 7.14 7.70 8.29 10.63 11.81 10.77 12.59 12.66 14.24 15.69 17.29 19.05

a. Estimated environmental costs per ton originate from the computed result in Table 3.

Estimated Estimated Estimated Amount Environmental Estimated Environmental on Room Costs (room) Environmental Costs (total) Waste in Hong Kong Costs per in Hong Kong (tons) Dollars (millions) Room Dollars (millions) 15,952 17,552 21,079 20,716 20,991 22,491 27,891 29,888 27,969 29,064 31,605 21,379 23,524 24,732 27,516

4.29 5.13 6.28 6.55 7.85 8.95 12.69 14.59 14.12 15.81 18.65 13.51 15.60 17.21 20.09

0.68 0.74 0.82 0.84 0.97 1.05 1.26 1.35 1.36 1.54 1.73 1.46 1.53 1.57 1.64

9.36 11.57 13.44 13.69 15.55 17.24 23.32 26.39 24.90 28.40 31.31 27.76 31.29 34.51 39.13

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profit in 1996 (Hong Kong Tourist Association, 1997). This study also revealed that the environmental cost per cover in the Food Division was HK$0.2 per cover in 1986, increasing to HK$0.44 per meal cover in 1996. CONCLUSIONS

A set of environmental costs relating to solid waste in the hotel industry was produced, and some benchmarks for converting local hotels’ MSW into environmental costs were established. This study has developed a simple method that allows practitioners to estimate the environmental cost of solid waste and has shown that the inclusion of environmental costs is not difficult. As Hamilton and Lutz (1996) said, “While the published work (for green accounts) reflects a wide variety of approaches to constructing accounts, this sort of experimentation is healthy in any developing field.” Thus, it is expected that similar approaches and standard environmental costs can be developed for other pollutants and can be incorporated into management reports and statistical publications. In the long run, it is hoped that the established yardstick of green cost could serve as a useful tool in reducing the solid waste of hotel operations. In general, there are three accounting models. The first approach recognizes the actual and potential costs of waste management to a company and adjusts the policy accordingly. The second approach employs nonfinancial data and sets up an information system that records the physical quantities of waste. The third approach, close to conventional accounting, charges all waste management costs back to the line management, who are more aware of the external impacts of its activities on the rest of the company (Gray, Bebbington, & Walters, 1993). It is obvious that the first and the second approaches entail a large amount of research. The third approach is considered more feasible for the environmental accounting of MSW produced by the hotel industry. Based on these research methodologies and findings, we make the following suggestions. The executives of individual hotels could consider inserting green indicators in their master profit and loss statements. The green indicators could appear in the notes section of the financial statements. The suggested green indicator is an estimate of the amount of solid waste consumed in terms of weight and environmental costs. To pass the green message down to operating departments, a more supportive practice would be to add such a green indicator, showing the green cost of MSW incurred, to individual departmental profit and loss statements. The same approach could also be considered to apply in environmental costing of MSW produced by the overall hotel industry. In fact, the majority of current tourism-related statistical reports emphasize financial and marketing information. Environmental performance indicators are rarely included in these reports. Therefore, we suggest that travel-related organizations such as industry associations, government bodies, and global hotel or tourism authorities could construct some green reminders or performance indicators in their statistical reports. For instance, certain annual publications, such as the Hong Kong Hotel Industry, the


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Statistical Review of Tourism in Hong Kong, and Trends in the Hotel Industry, would be good testing areas for such pilot schemes. In addition, the results and models of this study suggest possible further developments in the hospitality-related area of tourism satellite accounts (TSAs) (Mei & Lapierre, 1995; Nordstrom, 1996; Smith & Wilton, 1997). The traditional economic indicator of GNP, as codified in the United Nations System of National Accounts, masks the depletion of natural resources and hides the pollution costs of economic activities (Hamilton & Lutz, 1996). There is therefore a growing body of published work on green accounts. In 1993, the United Nations published interim guidelines on an integrated System of Environmental and Economic Accounts (SEEA) and provided a common framework for green national accounting. In countries such as Canada and Sweden, the hotel industry’s contribution to the GNP is reflected in the TSAs. The development of the TSAs has been on the economic side, and the revised TSAs were forwarded to the United Nations for comment in early 1998 (World Tourism Organization, 1998). It is envisaged that the next evolutionary phase in the development of the TSAs will involve this environmental element, in line with the United Nations’ SEEA. This study has demonstrated a method for costing some of the environmental pollutants produced by the hotel industry and can thus serve as a reference for the development of green TSAs. REFERENCES Anonymous. (1994). HCIMA backs new environmental initiative. Hospitality, 145, 16-17. Barlett, F. (1992). How green are Hong Kong hotels? One Earth, 16, 22-23. Chung, S. (1996). Policy and economic considerations on waste minimization and recycling in Hong Kong. Doctoral thesis, Hong Kong Polytechnic University, Hong Kong. Chung, S., & Poon, C. (1994). Waste recovery, How is it compared to other waste management tools? In Proceedings in POLMET Conference (pp.779-784). Hong Kong: The Hong Kong Institute of Engineers. Crosby, M. (1990, September). A hotel chain with an environmental vision. Restaurant USA, p. 10. Cummings, L. (1997). Waste minimisation supporting urban tourism sustainability: A mega-resort case study. Journal of Sustainable Tourism, 5(2), 93-108. Cummings, L., & Cummings, W. (1991). Foodservice and solid waste policies: A view in three dimensions. Hospitality Research Journal, 14(2), 163-71. Deegan, C., & Rankin, M. (1997). The materiality of environmental information to users of annual reports, Accounting Auditing & Accountability Journal, 10(4), 570-579. Environmental Protection Agency. (1989). The solid waste dilemma: An agenda for action (EPA/530-SW-89-019). Washington, DC: U.S. Government Printing Office. Environmental Protection Department. (1993). Environment Hong Kong. Hong Kong: Author. Environmental Protection Department. (1996). Capital investment on waste management programmes. In Environment Hong Kong. Hong Kong: Author. Foss, K. (1990). Green power. Foodservice and Hospitality, 22(8), 23-32.

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Gray, R., Bebbington, J., & Walters, D. (1993). Accounting for the environment. London: Paul Chapman Publishers Ltd. Hamilton, K., & Lutz, E. (1996). Green national accounts: Policy uses and empirical experience (Environment Department Paper 39). Washington DC: World Bank. Hasek, G. (1991). Hotels keeping watch on waste. Resource Recycling, 10(1), 56-60. Hong Kong Tourist Association. (1977-1997). A statistical review of tourism. Hong Kong: Author. Hong Kong Tourist Association, Hong Kong Hotel Association and Horwath Asia Pacific. (1987-1997). Hong Kong hotel industry. Hong Kong: Author. International Federation of Accountants. (1998, July). IFAC Quarterly, New York: International Federation of Accountants. International Hotels Environmental Initiative. (1993). Environmental management for hotels. Oxford, UK: Butterworth-Heinemann. King, P. (1991). Garbage war ’91 report from the front. Food Management, 26(2), 40. Mackie, A. (1994). Hotels turning green. Asian Hotel and Catering Times, 16(7), 19-22. Mathews, M. (1997). Twenty-five years of social and environmental accounting research—Is there a silver jubilee to celebrate? Accounting Auditing & Accountability Journal, 10(4), 481-511. Mei, S., & Lapierre, J. (1995). Occasional studies: Measuring tourism’s economic importance—A Canadian case study. EIU Travel and Tourism Analyst, 2, 78-91. Nicholls, L., & Nystuen, C. (1993). Future foodservice waste management. Hospitality Research Journal, 17(1), 234-238. Nordstorm, J. (1996). Tourism satellite account for Sweden 1992-93. Tourism Economics: The Business and Finance of Tourism and Recreation, 2(1), 13-41. Pettay, A. (1992). An analysis of the type and volume of waste generated in food and beverage operations in two selected hotel properties. Master’s thesis, Kansas State University, Manhattan. Redlin, M., & deRoos, J. (1980). Gauging energy savings: Further applications of multiple- regression analysis. The Cornell Hotel and Restaurant Administration Quarterly, 20(4), 48-52. Schwartz, J., & Miller, T. (1991). The earth’s best friends. American Demographics, 10(2), 26-35. Shanklin, C. (1993). Ecology age: Implications for the hospitality and tourism industry. Hospitality Research Journal, 17(1), 221-222. Shanklin, C., Petrillose, J., & Pettay, A. (1991). Solid waste management practices in selected hotel chains and individual operations. Hospitality Research Journal, 15(1), 59-74. Smith, S., & Wilton, D. (1997). TSAs and the WTTC/WEFA methodology: Different satellites or different planets? Tourism Economics: The Business and Finance of Tourism and Recreation, 3(3), 249-262. Townsend, R. (1990). Dealing with full problems. Restaurants and Institutions, 101(18), 40-54. United Nations Environmental Program Industry and Environment Office. (1994). Company environmental reporting: A measure of the progress of business & industry towards sustainable development (Technical Report No. 24). London: Sustainability Ltd.


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World Tourism Organization. (1998, January-February). In WTO news. Madrid, Spain: Author.

Submitted August 15, 1999 First Revision Submitted March 13, 2000 Second Revision Submitted July 26, 2000 Accepted December 15, 2000 Refereed Anonymously Wilco W. Chan (e-mail: [email protected]) is an assistant professor in the Department of Hotel and Tourism Management, The Hong Kong Polytechnic University (Hung Hom, Kowloon, Hong Kong), and Joseph C. Lam, Ph.D. (e-mail: [email protected]), is an associate professor in the Department of Building and Construction, City University of Hong Kong (Tat Chee Avenue, Kowloon, Hong Kong).

ENVIRONMENTAL UNCERTAINTY WITHIN THE HOSPITALITY INDUSTRY: EXPLORING THE MEASURE OF DYNAMISM AND COMPLEXITY BETWEEN RESTAURANT SEGMENTS Robert Harrington Washington State University The use of aggregated macro-level data is underrepresented in hospitality research, and it is suggested here that traditional measures of environmental uncertainty are insufficient when measuring differences within a hospitality sector. This article reviews the traditional measures of environmental uncertainty using secondary data and proposes a measure of heterogeneity as an alternative method grounded in previous theory. Aggregated segments of the restaurant industry are used to illustrate the usefulness of heterogeneity in resources as a measure of environmental uncertainty. Using this exploratory measure, significant differences are shown to exist between limited service and full service restaurant segments. KEYWORDS: environmental uncertainty; heterogeneity; dynamism; complexity; restaurants.

The concept of environmental uncertainty is encountered frequently in the literature on organizations. When assessing the level of environmental uncertainty between industries, strategy and organizational theory research has considered two main dimensions: complexity and dynamism. These dimensions were derived from Dess and Beard’s (1984) exploratory work that synthesized previous theoretical models. These variables work reasonably well when comparing differences between industries but seem problematic in determining differences in environmental uncertainty between segments of the same industry. For example, these measures could be used to measure differences between the lodging and restaurant industries but may not provide sufficient insight into differences between restaurant segments (i.e., limited service vs. full service). JOURNAL OF Harrington / ENVIRONMENTAL HOSPITALITY & TOURISM UNCERTAINTY RESEARCH

Author’s Note: I would like to thank K. W. Kendall, David Lemak, and Richard Reed at Washington State University for their feedback and encouragement on earlier versions of this article. Earlier versions of this article were presented at the Fourth and Fifth Annual Graduate Education and Graduate Students Research Conferences in Hospitality & Tourism (January 1999 and 2000). Journal of Hospitality & Tourism Research, Vol. 25, No. 4, November 2001, 386-398 © 2001 International Council on Hotel, Restaurant and Institutional Education

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Harrington / ENVIRONMENTAL UNCERTAINTY

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The importance of contingency variables in macro-level research has been noted, and environmental uncertainty has generally shown a relationship with required levels of flexibility or rigidity in processes of the firm (Homburg, Krohmer, & Workman, 1999). Dynamism, in particular, has been shown to be an important moderator of the link between organizational decisions and performance (Li & Simerly, 1998). Although the contingency approach is generally accepted in strategy and organizational theory research, it seems to be underrepresented in macro-level hospitality research (Baloglu & Assante, 1999; Okumus & Roper, 1999). It is suggested here that one reason for this is that generally accepted methods of measuring environmental uncertainty are too coarse grained to detect differences within a hospitality industry sector. Although Dess and Beard (1984) used multiple indicators to measure dynamism and complexity, most empirical work has assessed them using one indicator of volatility and one indicator for dispersion of firms (e.g., Keats & Hitt, 1988). Baloglu and Assante (1999) encouraged hospitality researchers to use more sophisticated methods to provide richer information and a better understanding of the topics studied. In addition, they pointed out that a greater use of aggregated macro-level data would be helpful to “generate information and knowledge generalizable to the [hospitality] industry segments and, therefore, identify common behaviors and practices” (p. 63). Following these suggestions, this article provides a discussion of alternate measures of dynamism and complexity that provide a more fine-grained assessment of these two constructs. The proposed method is exploratory in nature and is intended to encourage further discussion in this area. The proposed method has theoretical grounding in Schumpeterian economics, resource-based theory, and contingency theory. To test this method, aggregated macro-level data is analyzed for restaurant segments as defined by the National Restaurant Association (NRA) (1995, 1996, 1997, 1998). First, this discussion focuses on commonly used measures of complexity and dynamism. Second, the underlying theory of the uncertainty construct is evaluated. Next, exploratory methods are suggested and evaluated. And finally, future research for the development of valid and reliable measures of environmental uncertainty is discussed. CURRENT MEASURES

As mentioned above, both environmental complexity and environmental dynamism are related to environmental uncertainty. Thus, for this discussion, environmental uncertainty is viewed as a higher order latent construct that is caused by both complexity and dynamism. Environmental dynamism is defined as unexpected change that is hard to predict. Firms that operate in this type of environment face increased risk. Because change is hard to predict, members have a higher level of perceived uncertainty. As Aldrich (1979) suggested, this environmental volatility “leads to externally induced changes . . . that are obscure to administrators and difficult to plan for” (p. 69). Typical measures of dynamism using secondary or objective data include the volatility of net sales in an industry

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and the volatility of operating income (Keats & Hitt, 1988). In a study of the lodging and restaurant industries, Crawford-Welch (1990) found that firms in a highly dynamic environment “experience high levels of volatility in prices charged by suppliers, in customer demand, and in availability of credit” (p. 371). In addition, 41.1% of the firms responding to the study operated in this type of environment (Crawford-Welch, 1990). This suggests that a significant proportion of firms in various segments of the hospitality industry operate with high dynamism in their environment. Environmental complexity has been defined using two different dimensions: the variety and range of an organization’s activities and the concentrationdispersion level of firms within an industry or segment (Dess & Beard, 1984; Duncan, 1972). A wider range of activities tends to increase information-processing requirements. The greater information-processing requirements are due to managers’ perceived uncertainty when facing a more complex environment (Dess & Beard, 1984). The primary influence of the greater information-processing requirements is on organizational structure. This leads to divisionalization and decentralized decision-making authority. In addition, complex environments require high internal differentiation; resources must be used for extensive human resource training and to manage interdependencies. Environments low in complexity have more resources available to invest in assets and market promotion (i.e., external differentiation) (Keats & Hitt, 1988). The second dimension of a complex environment is concerned with the number, size, and distribution of firms within an industry or segment. Typically, members of a hospitality segment in a complex environment have low monopoly power and are “infused with entrepreneurial newcomers” (Keats & Hitt, 1988, p. 579). Measures of complexity in the operations dimension include amount of diversification, breadth of product or service line, and geographical dispersion. Measures of complexity in the concentration-dispersion dimension include movement to or from higher levels of concentration of firms within an industry segment, the number of firms within a segment, the diversity of firms within a segment, and their distribution (Keats & Hitt, 1988). Although these traditional measures may be useful in assessing differences between industries, they appear too coarse grained to provide meaningful information in assessing differences between segments of a particular industry. For example, the currently accepted dynamism measures using secondary data rely on a number of implicit assumptions. The level of dynamism is measured by the volatility in industry performance, so this assumes that volatility is a proxy for unexpected change and (generally) that past levels of volatility will continue at the same relative levels for each industry in the study. Thus, if we are suggesting that a particular industry has a higher level of dynamism based on past levels of volatility, then by definition it is not unexpected change that is being measured but rather expected change (granted, we may not know where this change will happen). Because the level of dynamism can manifest itself in many ways other than financial measures of volatility, this analysis suggests that a richer measure of dynamism (and, hence, environmental uncertainty) can be achieved.


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A second method of assessing the level of environmental uncertainty is to use subjective reporting or self-reporting by key informants of an organization (e.g., Homburg et al., 1999). Although executive interpretations of the environment influence decisions and perceptions, it has been well documented that key informants’ beliefs and expectations are biased toward confirmation (Fiske & Taylor, 1991; Simons & Namasivayam, 1999). Because of these problems in measuring environmental uncertainty, it begs a number of questions for hospitality industry researchers. First, is the generally accepted approach to the measurement of environmental uncertainty fine grained enough to determine differences between hospitality industry segments? Second, besides using subjective data or traditional objective measures of environmental uncertainty, how else might this be assessed? THEORETICAL DEVELOPMENT

A number of researchers have provided theoretical discussions of unanticipated change and uncertainty. One of the more influential theorists in this area has been Schumpeter (1950). Schumpeter is considered part of the Austrian school, which embraces the dynamic nature of the competitive environment (Conner, 1991). In Schumpeterian terms, the economic environment is viewed as less predictable than other approaches (i.e., Porter, 1980), and capitalism is described as a process of “creative destruction.” Sometimes referred to as “Schumpeterian shocks,” this process creates a continuous decay of competitive advantages of a firm. This is proposed to occur through innovations of entrepreneurs. Hence, Schumpeterian shocks can be described as continuous evolutionary innovations in products, markets, or technology (Barney, 1986). And, unexpected changes or shocks are more likely in an environment with entrepreneurial entry and innovation potential. Furthermore, Rumelt’s (1984) discussion of sources of potential rents or unexpected events (along with isolating mechanisms) provides additional support in suggesting elements likely to increase the level of dynamism. An assessment of his overall ideas is that unique resources allow firms to receive rent through unexpected change (i.e., technology, consumer tastes, and discoveries). Building on previous work of Schumpeter (1950) and Rumelt (1984), the resource-based view (RBV) of the firm embraces Schumpeterian shocks within its framework (Conner, 1991). This view has received considerable attention over the past decade, with significant empirical testing appearing in all major journals of hospitality, management, and strategy (e.g., Brush & Artz, 1999; Combs & Ketchen, 1999). An important notion that appears consistently throughout the RBV is that of heterogeneity in firm resources. Firm resources “include all assets, capabilities, organizational processes, firm attributes, knowledge, etc. controlled by a firm that enable the firm to conceive and implement strategies that improve its efficiency and effectiveness” (Barney, 1991, p. 101). These resources may be tangible or intangible and can be classified as physical, human, and organizational.

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The concept of homogeneous versus heterogeneous resource distribution is discussed explicitly in previous research comparing the market model of competitive advantage (i.e., Porter, 1980) and the RBV of the firm (e.g., Barney, 1991; Peteraf, 1993). In a seminal paper by Barney (1991) on the RBV of the firm, he developed a theoretical basis for the relationship between firm resources and sustained competitive advantage. This discussion is particularly relevant to our discussion of environmental uncertainty in which Barney (1991) explicitly discussed implications of homogeneity-heterogeneity of resources between firms. Although it seems reasonable to expect that all segments of the hospitality industry will be characterized with at least some level of heterogeneity in firm resources, let us assume complete homogeneity in firm resources within a hospitality segment along with perfect mobility of resources. Mobility is defined as resources that “can be bought and sold in factor markets” (Barney, 1991, p. 100). Hospitality Segments With Homogeneous and Perfectly Mobile Resources

In this hypothetical condition, firms of this hospitality segment will have the same amount and kinds of strategically relevant physical, human, and organizational capital. Because of this, firms in this segment could not conceive of or implement strategies that could not be conceived of or implemented by any other firms within this segment. Hence, the conception and implementation of strategies requires that firms have unique resources that are not perfectly mobile (Barney, 1986, 1991). Because a segment populated by identical firms cannot create strategies or tactics that are unexpected by other firms, homogeneity in hospitality resources suggests less environmental uncertainty with no unanticipated change. In other words, any change in firm strategies can be conceived of and anticipated by all other firms within this segment. If firms in a hospitality segment with homogeneous resources and perfect mobility have less uncertainty, it seems logical that firms in a hospitality segment with heterogeneous resources and imperfect mobility will have greater uncertainty in the form of both complexity and dynamism. In addition to the theoretical relationship between heterogeneity in resources and unanticipated change (dynamism) suggested by Barney (1991), Rumelt (1984), and Schumpeter (1950), Aldrich (1979) suggested six dimensions of the environment and predicted that the level of homogeneity-heterogeneity in the environment had an impact on environmental complexity. Dess and Beard (1984) tested measures of both the homogeneity-heterogeneity dimension and the concentration-dispersion dimension of environmental complexity. Using exploratory factor analysis, they found the concentration-dispersion dimension to be a fairly discrete construct, whereas the homogeneity-heterogeneity dimension appeared to be multidimensional. Measures to operationalize the homogeneityheterogeneity dimension included diversity of industry products, a specialization ratio indicating the proportion of shipments accounted for by a primary product, and concentration of industry inputs. Their factor analysis suggested that two of the variables used to operationalize homogeneity-heterogeneity (concentration of industry inputs and outputs) showed high loadings (.82029 and .64739, respec-


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tively) on what they termed as another dimension of the complexity construct. In addition, concentration of industry outputs had a significant factor loading (.35291) with a dimension defined as turbulence. A third variable, the specialization ratio (indicating the proportion of shipments accounted for by a primary product), had high loadings on both the complexity (–.30621) and dynamism (–.53626) factors. Finally, a measure of concentration-dispersion in an industry (the number of establishments) had high loadings on both their complexity dimension (.3006) and a “technological dynamism” dimension (.83243) (Dess & Beard, 1984). An assessment of both the underlying theory (Aldrich, 1979; Barney, 1991; Rumelt, 1984; Schumpeter, 1950) and exploratory analysis (Dess & Beard, 1984) suggests two main points. First, the level of environmental uncertainty is a function of both the complexity of the environment (how many things are going on) and unexpected change or dynamism (which is a function of entrepreneurial entry and innovation). Second, a more fine-grained secondary measure of environmental uncertainty is the level of heterogeneity in resources that are imperfectly mobile for firms in a particular segment of an industry. An Exploratory Test of Differences in Levels of Environmental Uncertainty

To provide an initial test of differences in heterogeneity of resources between restaurant segments, aggregated macro-level data were used. Before describing the test procedures, it is necessary to discuss some underlying assumptions of this research project. First, it is proposed (grounded in previous theory) that a higher level of heterogeneity in types of resources suggests higher levels of environmental uncertainty. For this to hold, the resources must be imperfectly mobile (which is an assumption of the variables chosen). Second, this study uses secondary data from the NRA’s (1995, 1996, 1997, 1998) Restaurant Industry Operations Report. This assumes that the preparers of the data at the NRA are knowledgeable informants of the restaurant industry who have separated the industry into meaningful segments and resource categories. This assumption is common in research using other categorization systems (i.e., standard industrial classification codes) and other restaurant industry research (e.g., Combs & Ketchen, 1999). Four years of data were collected and analyzed for this study (1995 through 1998). During this time period, the NRA report divided the commercial restaurant industry into three main segments: limited-service restaurants (fast food restaurants), full-service restaurants (average check per person less than $10), and full-service restaurants (average check per person $10 and greater). The data for this analysis are based on the aggregated segment. In other words, the unit of analysis is the restaurant segment as defined by the NRA rather than individual restaurants within each segment. Thus, any findings do not generalize to individual restaurants but to their aggregated segment. The hypotheses for this study were developed using previous empirical findings, a visual inspection of the data, and anecdotal evidence. Given the exploratory nature of this study, all of these methods seemed appropriate. Tse and Olsen

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(1988) found that the majority of executives in the limited-service restaurant segment perceived their strategies as primarily low-cost producers. In contrast, the majority of executives in the full-service segment viewed their strategies as primarily differentiation. This suggested a greater reliance on idiosyncratic resources (i.e., heterogeneity) for firms in the full-service segments. A visual assessment of the NRA data and anecdotal evidence suggested that the limitedservice segment had relatively higher homogeneity for a couple of reasons. First, marketing costs as a percentage of total sales are consistently higher than the full-service segments. This suggests national branding or marketing efforts that imply more of a focus on the industry as a level of analysis and less internal differentiation. An industry level of analysis and external differentiation are characteristic of the market model of competition, which assumes resource homogeneity (Peteraf, 1993). Second, the limited-service segment appears to lend itself more readily to standardization, suggesting more homogeneity in resources. And finally, the higher employee turnover rate in the limited-service segment suggests that any unique abilities will be more quickly dispersed to other firms in the segment (e.g., Decarolis & Deeds, 1999). Thus, the limited-service segment has relatively higher homogeneity in resource distribution than the full-service segments. This hypothesis is formally stated below: Hypothesis 1: The aggregated limited-service segment has a higher level of homogeneous resource distribution than the aggregated full-service restaurant segments (average check less than $10 as well as greater than $10).

In addition, it is predicted that the full-service restaurant segments have significantly different levels of heterogeneity. If the average customer is willing to pay a higher check average, then it suggests that the full-service segment with an average check of $10 and greater is providing unique and valuable services to the customer. In other words, it is presumed that restaurants are able to achieve a higher check average by using unique or idiosyncratic resources and capabilities of the firm. Specifically, it is hypothesized that the full-service restaurant segment (average check per person $10 and greater) will have the highest level of heterogeneity in resources of all the restaurant segments and, thus, a higher level of environmental uncertainty. This hypothesis is formally stated below: Hypothesis 2: The aggregated full-service restaurant segment (average check per person less than $10) has a higher level of homogeneous resource distribution than the aggregated full-service restaurant segment (average check per person $10 and greater). METHOD

According to the NRA’s annual Restaurant Industry Operations Report, respondents were mailed questionnaires and included members of the NRA and members of state restaurant associations. The sample size for each of the following years were 1,917 (1995), 1,695 (1996), 1,335 (1997), and 1,630 (1998).


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Because the research design involves classification factors (restaurant segments), it is generally the case that a nonorthogonal design will occur. In other words, there is no reason to believe that the number of restaurants that are placed in each segment will be equal. Hence, the unequal cell counts are not a result of experimental factors and should not reduce the robustness or power of the analysis (Maxwell & Delaney, 1990). MEASURES

Blau’s (1977) index of heterogeneity was used to calculate the distribution of resources within each segment. The level of heterogeneity is calculated as D = 1 – Σ(Pi2), where Pi is the proportion of firms in a segment within a particular survey category. This is basically an application of the Herfindal index, and the value is subtracted from 1 to produce an index that increases with increasing heterogeneity. For example, if all firms within a segment were placed into one category of an item on the survey, D would equal zero. If the proportional responses were spread evenly across all survey categories for an item, D would equal 1 – 1/n (where n is the number of categories for that item on the survey) (Haveman, 1992). Hence, the higher the D value, the more heterogeneity that exists within a segment. An exception to this conception of heterogeneity level is for the affiliation type measure. Because single unit is the largest proportional category across all restaurant segments, the heterogeneity score is reversed (i.e., a higher proportion of single units within a segment suggests more heterogeneity but a lower D value). Eight variables measuring heterogeneity were used to test for differences between restaurant segments. VARIABLES

Variables included in this exploratory analysis included those that reflect theoretical measures of complexity and dynamism as well as being likely to be imperfectly mobile. Age. Heterogeneity in firm age for this segment was chosen because it reflects the entrepreneurial entry dimension. If a significant difference exists between segments for this variable, additional interpretation of the results will need to be done to assess its impact (i.e., the proportion of young firms). Affiliation type. This variable measures the proportion of firms in a segment that are single units, multiple units, chains, and so forth. It reflects the complexity dimension and entrepreneurial entry. As mentioned above, this variable was interpreted in a fashion opposite of the other variables, with a lower D value indicating greater heterogeneity (i.e., more single-unit firms). Meal periods. This variable measured the variety of meal periods served in the restaurant segment. A greater variety of meal periods reflects a wider variety of activities and tacit knowledge within the segment. Tacit knowledge is defined as

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“the implicit and non-codifiable accumulation of skills that results from learning by doing . . . that is accumulated through experience and refined by practice” (Reed & DeFillippi, 1990, pp. 89-91). Menu themes. The variety in menu themes was used as a measure of heterogeneity because it represents a level of idiosyncratic abilities between firms, specific know-how, and tacitness, which are not perfectly mobile. Sales volume. This variable measures the proportion of firms within a segment that fall within a particular sales range category. A higher D value in the variable measures heterogeneity in volume for restaurant segments. Location types. The variety in location type suggests a higher level of heterogeneity in firms and a wider variety of target markets within a segment. Types of locations include freestanding, hotels, clubs, shopping malls, and so forth. Number of seats. The number of seats represents heterogeneity in size but also assesses differences in takeout capabilities and drive-through capacity and varies by meal period of the firm. Size: Square feet. This variable is correlated to number of seats and sales volume but was included because it represents heterogeneity in amount of on-premise food preparation, service levels, partitioning of the facility, and so forth. RESULTS

Multiple t tests were conducted to determine if significant differences existed in heterogeneity between restaurant segments. In general, Hypothesis 1 was supported; the tests indicated that both full-service segments were significantly more heterogeneous than the limited-service segment. Specifically, there were significant differences between the limited-service segment and the full-service segment (average check less than $10) for five of the heterogeneity measures. Seven of the heterogeneity measures were significantly different for the full-service segment (average check $10 and greater) compared to the limited-service segment. In contrast, Hypothesis 2 was only marginally supported. The tests for differences in heterogeneity between the full-service segment (average check less than $10) and the full-service segment (average check $10 and greater) resulted in mixed findings. Five of the eight variables (age, affiliation type, menu themes, location types, and size) indicated statistically significant differences in the expected direction. But two of the eight variables (menu periods, number of seats) were significant but in the opposite direction. Table 1 indicates the level of significance and the findings of these tests. DISCUSSION

This research has been undertaken with the aim of exploring the development of a more valid and fine-grained measure of differences in environmental uncertainty between restaurant segments. The goal has been to further discussion in


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Table 1 Level of Heterogeneity Between Segments Variable

Limited Service

Full Service (