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An analysis of long-distance travel behavior of the elderly and the low-income


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An analysis of long-distance travel behavior of the elderly and the low-income
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vii, 136 leaves : ill. ; 29 cm.
Georggi, Nevine Labib
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Older people -- Transportation -- United States   ( lcsh )
Poor -- Transportation -- United States   ( lcsh )
Dissertations, Academic -- Civil Engineering -- Masters -- USF   ( lcsh )
bibliography   ( marcgt )
non-fiction   ( marcgt )


Thesis (M.S.C.E.)--University of South Florida, 2000.
Includes bibliographical references (leaves 110-112).
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by Nevine Labib Georggi.

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An Analysis of Long Distance Travel Behavior of the Elderly and the Lowincome Households in Florida Working Paper Prepared by Nevine Labib Georggi Center For Urban Transportation Research University of South Florida June 1999


Abstract This paper provides a detailed analysis of long distance travel behavior for two key socio-economic groups of the population in Florida the elderly and the low income. The analysis utilizes data from the 1995 American Travel Survey that provides a rich source of information on long distance travel {i.e., trips greater than 100 miles) undertaken over a period of 12 months. The analysis focuses on comparing the elderly and the low-incom e groups of the population against other groups with res pect to various demographic and trips characteristics. The travel behavior comparison includes an analysis by trip purpose, travel mode, travel distance, trip duration, and trip frequency. In addition, r egress ion models of long distance trip generation are estimated separately for different groups to examine differences in trip generation propensity across the groups. The result s show that both, the elderly and the low income, underta ke significanlly fewer long distance trips than other socio-economic groups. It was found that nearly one-half of the low income and elderly made no long distance trips in the one-year survey period. In addition, it was found that long distance trips made by these groups were more likely to be undertaken by bus and geared towards social and persona l business activities. The paper discusses the imp l ications of these findings in the context of transportation servic e provision and policy f o rmulat ion .. Acknowledgement This research was funded by the Center for Urban Transportation Research {CUTR) at the University of South Florida. The author is grateful to Ram Pendyala, Department of Civil and Environmental Engine ering, Un iver sity of South Florida, and Xuehao Chu CUTR, for providing valuable inputs during the course of this research.


1. Introduction The American Travel Survey (ATS) provides an extensive database on the long distance travel patterns of a sample of individuals in the United States. Long distance trave l constitutes a sizeable portion of total travel in the nation However, primarily due to a lack of disaggregate behavioral data, research in travel behavior and travel demand analysis has focused on trip making patterns within urban areas The availability of data from the recent 1995 ATS provides a key opportunity for examining various facets of long distance travel behavior Long distance travel has important social and economic consequences Long distance travel tends to be dominated by two primary trip purposes, namely, business and l eisure These trip purposes constitute economic and recreational opportunities that provide va lue both to the individual as well as to the geographic areas where the trips are made. In Florida the tourism industry rel i es heavily on the ability of individuals to undertake long distance trips for recreational purposes. In turn, the state depe n ds the vitality of the tourism industry for its revenues. Two spec i al market-segments merit consideration in the context of l ong distance travel behavior. They are the elderly and t h e low-income households. The e l derly include individuals who are aged 65 years or over while low i ncome households are those whose income is below $25,000 annually. These market segments tend to be of interest to researchers, planners, and policy makers because of their potential lack of access to opportunities. For example, quite often long distance travel entails the use of the automobile. However, individuals within these market segments may have disproportionately less access to an automobile when compared with the rest of the population. The elderly may not be able to drive long distances because of physical limitations, while low-income individua l s may not have access to an automobi l e even if they are abl e to drive. Sim il arly, long d i stance travel by air may not be comfortable for the elderly and may not be affordable for the low income. 1


This paper is aimed at performing a detailed analysis of long distance travel behavior for these two key market segments in Florida. Trip making patterns of these two market segments are compared with those of the rest of the population with respect to standard travel demand indicators such as overall trip rates, trip rates by purpose, mode choice, destination choice, trip length distribution, and travel time. Long distance trip generation models are estimated for these two market segments to determine the factors that affect their long distance travel. Coefficients i n the models of these two market segments are compared against coefficients obtained for the rest of the population to identify differences in trip making propensities for these market segments. The analysis in this paper provides key insights i nto the long distance travel needs, preferences, sensitivities, and opportunities (or lack thereof) for these market segments. Mobility issues associated with these market segments have been of interest to researchers and transportation planners in the recent past. ITE (1994), Rosenbloom (1995), and Benekohal (1994) describe trave l behavior characteristics of the elderly age groups in compar i son to other age groups. They find that average vehicle trip length declines steadily with age. The average daily vehicle miles of travel declines significantly after the age of 64 years. In addition it was found that transit usage declines with age. Other studies have looked at travel characteristics of the elderly from a safety and technology standpoint. For example, Chu (1994) and Abdei-Aty (1999) assess the transportation infrastructure needs of the elderly. They report that the elderly tend to avoid traveling at night, during rush hour conditions, and when icy snow conditions prevail. Interestingly, Chu (1994) notes that the elderly make as many trips as other age groups, but the total vehicle mil es of travel declines as they make trips of shorter length. There has a lso been considerable research in the area of travel behavior by income group. Recently, the focus has been on travel behavior characteristics of zero-vehicle households. For example, Crepeau and Lave (1994) find that zero-vehicle households make s ign ificantly fewer trips than the general population. Their analysis was based on the 1990 Nationwide Personal Transportation Survey (NPTS). If one considers car ?


ownership as a surrogate of income then these findings have important implications for transportation policy formulation. By no means does the above constitute a comprehensive l iterature review pertain ing to the travel behavior characteristics of the elderly and low income. It merely points to the widespread attention that these socio-economic segments have been receiving in the literature within the past decade. However, it should be noted that the l iterature has thus far focused on intra-urban trip making characteristics. This paper attempts to build on the knowledge accumulated in the literature by foc usi ng on the long distance travel behavior of these socio-economic groups using the recent 1995 American Travel Survey database. The remainder of thi s paper i s organized as follows. Following this intraductal)' section, the paper provides an overview of the ATS This is .followed by a description of the survey sample used in this study comparing Florida to the nation The fourth section of the paper provides a detailed analysis of long distance travel behavior of the elderly while the fifth section focuses on the l ow-income households Within these sections, statistical analyses o f the A TS sample in F lor ida are conducted to compare long distance travel patterns of the elderly and the low i ncome with those of the rest of the Florida population. Regression models of long distance trip generation models are estimated and comparisons of coefficients across population groups are performed. Finally, the paper ends with concluding remarks. 2. Description of the American Travel Survey The 1995 American T ravel Survey (ATS) collected detailed information about long distance travel behavior in the United States. The survey was conducted for the Bureau of Transportation Statistics of the U.S. Department of Transportat ion by the U S. Bureau of the Census as a component of the Census of Transportation (Bureau of Transportation Statistics, 1998). The previous survey that focused on long distance


travel was called tlie National Travel Survey and was conducted nearly 20 years earlier in 1977 As such, the 1995 ATS served as a timely resource for obtaining a clearer picture of long distance travel in the contemporary context. Approximately 80,000 households nationwide were randomly selected to participate i n the survey. The survey consisted of four detailed interviews conducted approximately every three months between April 1995 and March 1996. The interviews were conducted primarily by telephone, with in-person interviews for some respondents who could not be rea ched by telephone. The survey yielded a very respectable response rate of 85 percent for those households that were eligible for i nterview. The survey gathered detailed demographic characteristics of all household members regardless of age. Detailed travel information was collected for all one-way trips over 100 miles long that were undertaken between April 1995 and March 1996 Data collected in the survey was compiled int o four databases containing demographic and travel characteristics. The hou sehold and person demographic files contained information on household size, household and family income, household type, number of vehicles, employment status, age, type of residence, place of residence, race, marital status, and education level. The household and person trip fi les include origin and destination of the trip mode used, dista nce traveled, number of nights away from home, trip purpose, number of side trips, access and egress modes, number of members in the traveling party, type of lodging, and number of stops along the way to the main destination. Several reports published by the Bureau of the Transportation Statistics provide interesting facts and figures arising from the 1995 ATS (BTS, 1997 and 1998). The following points highlight some of the key facts and figures related to long distance travel in Florida and in the nation: 4


About 78 percent of the households in Fl orida took one or more long distance trips to a destination 100 or more miles away. Florida households travel less than the national average, which are about 80 percent of all h ouseholds. Travelers who liv e in Florida took 44.6 million person-trips, an average of 3 9 trips and 3, 972 miles per traveler. Visitors to F lorida took 59.1 million person trips, an average of 3.3 trips and 4,269 miles per traveler. The number of trips per visitor to Flor ida has increased 3 percent since 1977, and the number of miles per visitor has decreased 4 pe rce nt. On average in the United States, the number of trips per traveler has grown 20 percent and the numbe r of miles has increased 39 percent since 1977. The United States data show that 33 percent of-trips were un dertaken to visit friends or relatives, another 33 percent were undertaken for leisure, relaxation and vacation purposes, and about 23 percent were undertaken for business purposes. The remaining trips were undertaken for purposes of a personal nature such as school-related activities, weddings, funerals, or medical reasons. The corresponding percentages for Flo rid a were 31, 21, and 34 respectively. 47 percent of all air travel in Florida was undertaken for business purposes, compared with just 1 0 percent for personal business trips. The nationwide percent of all air travel undertaken for business purposes was 43 compared with just 8 for personal business. Nearly 67 percent of all vehicle trips in Florida were either for pleasure or personal business compared to 73 percent nationwide. The most popular destination states for trave lers who live in Florida are Georgia, Alabama, and New York. Georgia, New York and New Jersey are the most popular origin states for travelers to Florida 5


As the ATS focused on long distance trips more than 1 00 miles long, it did not capture long distance trips between 50 and 100 miles in length. Despite this limitation the ATS is a rich disaggregate source of behavioral data that permits the analysis and modeling of long distance travel in the United States. The paper Georggi and Pendyala (1999) utilizes the first release of the 1995 American Travel Survey databases to explore long distance travel characteristics of selected socio-economic segments of the population on a national level while the focus of this paper is the state of Florida. A more detailed description of the overall survey sample and that of Florida used for analysis are furnished In the next section. 3. A TS Sample Characteristics This section provides a brief overview of the 1995 ATS sample used in the analysis of this paper. As this paper is i ntended to analyze long distance travel behavior of two specific market segments, namely, the elderly and the low income, this section provides descriptive statistics for key socio-demographic and travel indicators of Florida's population and those of the nation. All of the statistics presented in the paper correspond to those obtained for the weighted sample. The weights used were those provided by the Bureau of Transportation Statistics within the A TS databases. These weights make the sample representative of the general population of the United States Various reports and publications of the Bureau of Transportation Statistics (e.g. BTS, 1997) provide further details on the survey methodology, sample composition, and terminology. One aspect that merits note here is that of the distinction between household and person trips If a household of three persons undertook a vacation trip together then that trip is counted as one household trip and three person trips. 6


The ATS household demographic database contained infonnation on 54,120 households that had responded to the survey; from which 1,353 households were from Florida. The ATS household trip file included only those households that made at least one long distance trip during the 12 month period covered by the survey. The total number of households in this database was 48,527 and the correspond ing number of household trips included iri the database was 337,520 nationwide. The households in Florida that made one or more long distance trips were 1,170 and they collectively made a total of 6,140 household trips. It should be noted that there are several households in the trip file that do not appear in the household demographic file. All of the sample sizes noted In this pa ragraph reflect unweighted samples. On the person side, the person demographic file included infonnation on 136,193 persons that resided in the households that responded to the survey of which 3,149 were Florida residents. The corresponding U.S. person trip file contained information on 556,026 records or person trips of 116,176 persons. The sub-file of Florida residents with one or more person trips were 9,993 persons reporting 122,502 person tr ips. All of the sample sizes noted in this paragraph reflect unwe ighted samples. 3.1 Socio-demographic Characteristics This section provides a brief overview of the socio-economic and demographic characteristics of both the weighted samples of households and persons in the demographic files of the United States and of Florida. Table 1 provides selected descriptive statistics pertaining to household characteristics. The average household size of the weighted sample was found to be about 2.5 persons per household. Flo rida had fewer single-parent households than the national average and 3 percent more households of married coup les with no children under 18 years old. About one-fifth of the househo ld s constituted families with child ren under 18 years of age in Florida compared to an average of one-quarter nationwide. Average vehicle ownership in Florida was about 1.5 vehicles per household with 17 percent of the households indicating a zero-car ownership status. About one-quarter of the sample had household 7


incomes less than $15, 000 while just about one-tenth of the sample had incomes ove r $60,000. Several characteristics of the househo ld are depict ed with reference to the hou seho l der. An examination of the householder revealed that one half of them have not had any college education experience. With respect to race about 27 percent of Florida households are either African-American or Hispanic compared to 20 percent of households in the United States. Nearly two-th i rds of the samp l e reside in sing lefam ily dwelling units. About 52 percent of the householders in Florida are employed full time compared to 59 percent nationwide, while nea rly 42 percent in F lo rida are not employed compare d to an average of 35 percent in the United States. The nationa l average age of the householder was found to be 48 years with about three-quarters falling in the age range of 25 years to 64 years In Florida the average age of the househo lder is 52 years with 10 percent more e l derly than the national average All of these d escript ive sta t istics are reasonable thus indicating that the household data set is suitable for travel behavior analysis Table 2 provides a similar description of personal characteristics for the weighted sample of persons in the 1995 ATS database. The average age of the total weighted sample was found to be 35 years with about 48 percent i n the midd l e age group of 25 years to 64 years I n t h e s u btotal samp l e of F l orida t h e average age was found to be 38 years with about 54 percent i n the middle age group of 25 years to 64 years. A little more than one-half of the persons in the United States are currently married compared to 42 percent in Florida. The rema inder have either been divorced, separat ed, or widowed. Almost one-half of the sample reported being employed full-time while about 44 percent indicated that t hey were not employed at all. The sample was nearly equally distributed with respect to gender Also, more than 50 percent of the sample d i d not have any college level educational experience. Once again it is noted that these descriptive statistics appear to be reasonable and plausible, thus indicating tha t the A TS databases are suitable for travel behavior analysis 8


Table 1. Key Household Characteristics (We i ghted Sample; N=5,580,456 for Florida and N=98,299,154 for U.S.) Characteristic F lorida u.s. Average Household Size 2 4 persons 2.5 persons % Single person 29% 27% Household Type Distribution % Married wilh chil d ren under 18 years o l d 21% 24% % Married with no children under 18 years old 32% 29% % Single with children under 18 years old 6.5% 8% Average Vehicle Ownership 1 5 vehicles 1. 7 vehicles % Zer o ca r households 17% 18% % One car househo l ds 41% 32% Average Household Income $34,517 $38,788 % L ess than $15,000 23 % 23% % $15,000$24,999 18% 14% %Greater than $60,000 9% 9% Education Level of Householder % High schoo l or less 52% 50% % co llege degree o r more 23% 25% Race and Ethnicify %White 82% 83% % African-American 14% 12% %Hispanic 1 3% 8% Type of Residence 65% % Single-family dwelling unit 68% % Mult i -family dwe lling unit 34% 34% Employment Status of Householder % Full-time employed 52% 59% % Part-time employed 5% 7% % Unem ployed 42% 35% Average Age of Householder 52 years 48 years % 15-24 years 5% 5% % 25-44 years 37% 43% % 45-64 years 26% 31% % 65 years and over 32% 22% 9


Tab l e 2. Key Person Characteristics (Weighted Sample; N = 264,207,543 for Florida and N=14396621 for U.S.) Characteristic F lo r i da u.s. Average Age 38 years 35 years % 15-24 years 14% 12% % 25-44 years 26% 30% % 45-64 years 29% 18% % 65 years and over 32% 11% Marital Status %Married 42% 54% %Divorced 8% 8% %Widowed 6% 6% Employment Status % Fulltime employed 48% 51% % Part-time employed 8% 10% % Unemployed 44% 40% Gender %Male 48% 49% Educ ation Level % High schoo l or less 55% 53% % 4-year college degree or m ore 25% 28% 3.2 Travel C h aracteristics This subsect ion focuses on the overall travel characterist i cs of the ATS sample that is included in the household demographic and tri p files As such, the statistics reported within this section pertain onl y to household trips and thei r associated characteristics. Detailed information on travel characteristics can be foun d in various publications of the Bureau of Transportation Statistics Therefore, only major trip characteristics are highligh ted in this section. Table 3 p r ovides an overview of major trave l indicators associated with F l orida household trips compared to the average U S. household trips The survey indicated that the overall average long distance trip frequency is equal to seven trips per household per year, while the average in Florida is onl y 5 tri ps per household per year. Nearly one-third ofthe households reported making no l ong distance trips of length 100 miles or more. In future studies of l ong distance trip making, it would be of interest to examine further the characteristics of househo l ds that report zero long distance trips. 10


The analysis conducted in this paper sheds some light on this topic. About 20 percent of the households made between five and ten long distance trips in the survey year. These trip frequency figures are derived from the household demographic file that includes the households that made zero trips. The remaining trip characteristics are derived from the household trip file. With respect to trip purpose in Florida, it was found that 37 percent of the trips are made for business, nearly 60 percent of trips are made for social visits and vacations and about 12 percent of the trips are made for persona l business. These figures are all consistent with the nation al average except where Flor idians make 8% more bus iness trips than the rest of the nation. More than three-quarters of all long distance trips are made by the personal automobile and about one in four trips in Florida is made by air while one in five trips are made by air nationwide. Conceivably, the trip mode choice distribution varies considerably by trip purpose and trip length. Interesting ly Floridians take much shorter trips on average than the rest of the nation with about 60% of these trips Is less than 300 miles compared to half that percentage nationwide. Cross tabulati ng these trip characteristics would provide a mechanism for capturing these variations. Interestingly a single adult with no children undertook 60 percent of all long distance trips reported. About one-quarter of the trips were day trips i nvolv ing no overnight stay while another one-half of the trips involved overnight stays of just one to three n i ghts. Table 3 gives a general description of travel characteristics comparing Florida to the rest of the nati on. In order to shed additional light on the relationships between mode purpose, and distance in Florida, an additional table has been included in this subsection. Table 4 shows how th e modal distribution, trip length distribution, travel duration, and travel party size changes across trip purpose. 11


Table 3. Key Household T rav el Characteristics (Weighted Sample; N =29,421, 599 trip_ s and N = 656,462,000 trips for U.S .) Characteri stic Florida u .s. Average Trip Frequ e n c y Strips 7 tnps %Zero trips 37% 32% % 1-4 trips 32% 29% % 5 -10 trips 20% 20% Trip Purpose Dlslrlbullon o/o Bus i ness 37% 29 % % Recreation and Vacation 22% 27 % %Social Visits 30% 30% % Personal B usiness 12% 14% Trip Mode Distribution o/o Pe rsonal Vehicle 70% 77% %Bus 2% 3% %Train 0% 1% %Air 26% 20% Averag e Round Trip Length Distributi on 566 miles 872 miles % 100-299 miles 57% 30% % 300-499 miles 9 % 2 7% % 500-999 miles 1 5 % 21% % 2000 m il es or more 5% 1 1 % Average Size of Travel /"arty 2 7 persons 1 6 p e rsons % One ad ult, no children under 18 y ears 58 % 59% % 2 or more adult s no children under 18 years 24% 24% % One adult one or more children under 18 yrs 5% 5% o/o 2 or more adults with c hildren under 18 years 10% 10% Average Travel Duration Distribution 5nights 4 5 nights % 0 n i ghts (day trip on l y) 23% 25% % 1-3 nights 43% 49% o/o 4-7 n i ghts 20% 19 % Table 4 reveals some interesting differences across various trip purposes For example, with respect to th e mode choice distribution, i t is found that the percent of business trips that are unde rtaken by air is nearly tw ice that for vacation and r ecreational trips. Similarly the percent of t rips that are undertaken by personal v ehicle is found to consistently increase as th e type of tri p purpose becomes increas ingly personal or social in nature The differences i n trip length d i stributions are qui te unexpected. Only one-half of the socia l visit and personal business trips made are of distances less than 300 miles while one-th[rd of the business and re creational trips are 300 miles or greater. But, across all tri p purposes, a bout 1 0 percent are over 300 miles and less than 500 miles. 12


With respect to travel party size, the difference between business trips and other trip purposes is marked. While about 80 percent of business trips were undertaken by one adult with no children, the corresponding percentage for other trip purposes is only about 45-50 percent. An examination of travel duration shows that recreation and social visit trips tend to be longer in du ration than business or personal business trips. While only 1120 percent of recreational and social trips involved no overnight stay, the corresponding percentage range for business and personal business trips was found to be 24-33%. Table 4. Mode, Length, Party Size, and Duration Variation by Purpose (Weighted Sample; N=29,421 ,599 trips for Florida) Characteristic Total In all of the cross-tabulations examined in Tables 4, the l statistic that tests the null hypothesis of inde pendence was found to be greater than the critical l value at the appropriate degrees of freedom. This indicates that, in all cases, the null hypothesis of i ndependence between trip purpose and the dimension examined may be rejected at 13


the 95 percent confidence level. It is clear from this analysis that business trips differ significantly from other trip purposes. However, the differences among the non business trip purposes (social v is it, recreation and vacation, and pe rsonal business) are less marked. This section has prov ide d an overall description of the A TS sample and their travel characteristics. The remainder of this paper is dedicated to analyzing long distance travel behavior for the two socio-economic market segments that constitute the focus of this paper, namely, the elderly and the low-incom e in the state of Florida. 4. Long Distance Travel by Elderly In the context of this paper the elderly age group corresponds to those individuals whose age is 65 years or over. As the analysis in this section is intended to be detailed in nature, the elderly age group is f u rther sub-divided into those betwee n 65 a nd 74 years of age and those 75 years or older. The analysis concentrates on the travel characteristics of these groups as compared to the other age groups in the sample. However, it was felt appropriate to also compare socio-demographic characteristics as such a comparison may shed light on the reasons behind the differences in travel characterist ics. 4.1 Socio-economic Characteristics of the Elderly Table 5 provides a summary comparison of key socio-economic and demographic characteristics across the various age groups. The comparison reveals several noticeable and statistically significant differences across the various age groups. More interestingly, it was fou nd that there are statistically significant differences even among the elderly with those between 65 and 7 4 years of age being quite different from those aged 75 years or over. 14


Table 5. Comparison of Demographic Characteristics across Age Groups (Florida Weigl)ted Sample) Characteristic Tot a l Average ho us ehold sizes are found to diminish with age of householder and correspon dingly the percent of si ng l e person households i ncreases d ramatically from about 23 percent in the lower age groups to about 50 percent in the high est age group With respect to car ownership also, it is found th a t car owne rship dec reases with Increasi ng age and t he percent of households not owning a car i n the age group of 75 years or more is 22 percent. While only about one-third of those in the age group of 65-74 years may be considered low incom e (i.e., i ncome less than $15 000 per year); the corresponding percentage for those in the age gro up of 75 years or more Is almost 50 percent. Similar significant differences are also seen when examining such cha racteristics as g e nd er, e mployment status, and marital status. An interesting note 15


here is that Florida's older elderly of ages 75 years or more has twice as much the percent of full time employment as the national average (Georggi and Pendyala, 1999.) Once again i t must be emphasized that the most important finding here is that even within the group that is traditionally categorized as "elderly", there are significant differences with respect to various demographic characteristics. It is to be noted that all of the comparisons shown in Table 5 are statistically significant a t the 95 percent confidence level. These differences are l ikely to play an important role in shaping the travel characteristics of people in different age groups The travel characteristics comparisons furnished in the subsequent sections should be interpr eted in light of the socio-economic comparisons reported in this subsection. 4.2 Trip Characteristics of the Elderly The discussion i n this section parallels the discussion furnished in Section 3.2 where overall travel characteristics for the entire ATS weighted sample were tabulated. I n this subsection, travel characteristics are tabulated by age group for the same trip attributes that were considered in Section 3.2. Table 6 provides a comparison of travel characteristics across various age groups consid ered in this paper. In general, it can be seen that the older age groups participate in fewer long distance travel activities and even within the older age groups, there are substantial differences between the age group of 65-74 years and the age group of 75 years or more. A l test conducted on each of the cross-classification tables shows that all of the differences across age groups are statistically significant at the 95 percent confidence level given the appropriate number of deg rees of freedom. The following points are especially noteworthy: On average, the 65-74 years age group makes about 4 trips per year, three times as many as those in the 75 years or more age group. The trip frequency distributions reveal that more than 10 pe r c ent of those in the 65-7 4 years age 16


group make 10 or more trips per y ear. The oorrespon d in g pe rc e ntage for the age g roup of 75 yea rs or more is only 1 percent. Table 6. Comparison of Trip Characteristics across Age Groups (Florida We ighted Sample) As expected the proportion of trips undertaken for busin ess d iminishes drastically after the onset of 65 years of age. On the other hand, in creas ing proportions of social visit trips occur with increasing age. A significant decrease in recreational trip generation occurs at age 75 years Whil e th e recre ational trip g e n eration rate 17


for the age group of 65-74 is greater than one trip per year, the corresponding average rate for those 75 years and above is only 0.25 trips per year. o The use of airplane, bus and personal automobile does not change significantly as age increases, although minor differences are again noted between the elderly and the older elderly groups. Whereas the age group of 65-7 4 years does not seem substantially different f ro m the 26-64 year age group, the older elderly 75 years or older are found to significantly differ from both of these age groups with respect to mode choice. For example, the mode sha re of bus triples when transitioning f ro m the 65-74 year age group to the 75 years or more age group. o It is i nteresting to note that average trip length increases with age. However, it is found that the trip length distributions only marginally differ across the age groups. For example, it is noted that about 15 percent of the trips are 500 miles or more for the three age groups of less than or equal to 25 years, 25-64 years, and 65-74 years while only 11perccent of the age group of 75 or more years make trips of that length. o With respect to travel duration, the average number of nights away from home increases significantly for the age group of 75 years or more. Interestingly, it is also found that the percentage of zero night trips is the highest for this particular age group. The i nc rease in average duration away from home is caused by the significant increase in trips that involve long stays of 8 nights or more away from home. This may be because people in this age group are undertaking larger percentages of social visit and personal business trips, which may typically be of longe r duration than busi ness trips. The analysis in this table reveals that older age groups, particularly those over the age of 74 years, are less mobile with respect to long distance travel. This is a result that one would expect; however, the dramatic drop of two-thirds in long distance trip (from 4.2 trips per year to 1.4 trips per year) seen between the age groups of 65-7 4 18


years and those 75 years or more raises important questions regarding the potential loss in mobility that occurs among the "older elderly". As seen above, Table 6 is quite informative regarding the travel characteristics of the elderly. However, it would be of Interest to see how the travel characteristics differ for different trip types. For example, are the older elderly (i.e those 75 years or more) more prone to undertake vacation trips of shorter length than the younger age groups that are potentially more mobile? Answers to these types of questions may shed light on the types of transportation opportunities that the older elderly may benefit from. Table 7 shows how the travel characteristics compare across various age groups for different trip purposes. As the elderly do not underta k e significant levels of business trips, only the three other trip purposes of social v isits, recreation/vacation, and pe r sonal business are analyzed The analysis in Table 7 reveals some interest i ng differences and trends by trip purpose. Once again, it is noteworthy that all of the/} statistics associated with the cross tabulations and the F-statistics associated with the multigroup comparison of means were statistically significant at the 95% confidence level. For the social visit trips that involve visiting friends and relatives it is found that the proportion of trips undertaken by personal vehicle significantly decreases while the proportion by air increases as age increases. There is virtually no difference in the proportions of trips undertaken by bus, train and other modes across the age groups. This drop in personal vehicle share is expected considering the driving impairment suffered by those in older age groups and the h i gher proportion of carless households. It is interesting to note that the average one-way trip length increases steadily across the age groups and a similar trend is found to exist for average trip duration as well (measured in terms of number of nights away from home). While the longer trip duration may be explained by the fact that those in the older age groups are not time constrained by work commitments, the longer trip length Is not as easily explained 19


Perhaps, h ere too, one could conjectu re that th e increased t ime availability allows those i n the older age groups to u ndertake longer trips both in length as well as in duration Table 7 Comparison of Characteristics of Different Trip Types across Age Groups (Weighted Sample) Trip Age Group Purpose Characteris tic 25 years 26 -64 65-74 75 years or l ess years vears or more Mode Choice Distribution % Personal Veh 84% 81% 79% 69% %Airpl ane 15% 18% 20% 29% Social %Bus 1% 1% 0% 0% Visits %Train 0% 0% 0% 0% %Other 0% 0% 1% 0% Avg. Trip Length (miles) 482 486 571 716 AvtJ.. Trip Durat ion (nights) 4.7 4.4 5 5 6.7 M o de Choice Distribution % Personal Veh 86% 79% 77% 60% %Airplane 9% 18% 14% 21% Recreation! %Bus 2% 0% 3% 10% Vacation %Train 0% 0% 0% 0% %Other 3% 3% 6% 9% Avg Trip Length (miles) 36 1 516 561 903 Avg TriP Duration (nights) 3.4 3 0 5 2 13.8 M ode Cho i ce Distribution % Personal Veh 82% 76% 78% 74% %Airpl ane 17% 19% 20% 22% Personal %Bus 0% 3% 0% 1% Business %Trai n 0% 2% 0% 3% %Other 0% 0% 2% 1% Avg. Tr ip Length (miles) 491 569 472 570 Avg Tri p Durati o n (nights) 1 4.4 4.7 5.2 8.8 To ta l 79% 20% 1% 0% 0% 549 5 2 78% 14% 3% 0% 5% 537 5.1 78% 19% 1% 1% 1% 526 5 5 For recreation/vacation trips, the most noticeable difference is that the drop in personal vehic l e share is significantly larger than that found for social v isit trips. The share of trips undertaken by air for this purpose is rather smaller than the share of air travel for social vis i t purposes. On the other hand, the percentage of re creational trips undertaken by bus is found to dramatically increase for the older elderly group of persons. Whereas the percentage of recreational trips undertaken by bus is between two and three percent for those 7 4 years or younger, the corresponding percentage for those over 7 4 years is 20


found to be 10 percent. This is pote ntially expla ined by the incr eased usage o f specia l cha rter and tour buses by those in the older elderly age groups Another s t riking difference between mod e choice across the different age groups is the sh a r e of "o ther mode which is the aggregated variab l e for all travel that involves cruise ship s c harter boats, and private yachts. Again, the Jack of binding time constraints imposed by rigid employ ment schedules appears to allow those i n the older age groups to undertake longer trip s both in length and duration. Th e most miles traveled a nd most nigh t s spent away fro m home is enjoyed by the o lder eldert y in the recreational/vacat io n tr i ps, almost twice as much the d istance and three times as much the duration as the age group of 65-74 years old. The personal business trip s include those undertaken for such purposes as family functions (wedding s fu nera l s, and grad u a tions) med ica l trea tm en t, and other personal matters. These trips are found to follow the same trends as the soc i a l visit trips However, the d ec rease in personal vehicle share is not as large as that found for socia l visit trips. In fact, th e shares associated with personal vehicle and airplan e are virtually s imilar across the diffe r ent age groups Even though the travel duration of p ers onal business trips is found to increase with age just as in the case of the other trip purposes examined, the trip lengt h is not found to follow that trend. The average trip l ength of personal busin ess trips appears to b e highest for those in the 25-64 year age group. The ana ly s is in this section shows that the e lderly are less mobile than other age group s with respect to long distance travel. However, th e drop in mobility appears to occur on a larger scale among the o lder elderly groups The trip generat i on rates of those 75 years and over for all trip purposes are found to be sig nificantly lower than those for all other age groups including tho se i n the 65-74 year grou p Similarly the dramatic increase in bus usa ge or conversely, the dramatic decrease in pe rsonal vehicle usage, especially in the context of recr eat ion a l trips, occurs again at the 75 year old mark as see n in Table 7 The decreased mobility expe r i enced by the older elderly may be explained by lower income levels, lower car ownership levels, and perhaps some physical limitations that make it difficult for them to e ngage in long distanc e trav el. This 21


find i ng is worthy of furthe r invest igation cons i dering that those in th is age group are the most vulnerable members of our society 4.3 Long Distance Trip Generation Models by Age Group The previou s two subsect i ons provided valuable insights i nto the differences in lo n g distance trip making behavior across various age groups However the analysis presented in those sec tio ns does not s hed light on th e pote nti al sensit ivity of different groups to various independent variables s uch as income and car ownership It is possible that there are differences among the age groups with respect to the cha nge in trip generation that would be brought about by a change In one of these independent variables. In order to exam ine these diffe ren ces linear regression models of trip generation were estimated for each age group In Table 8 estimat ion resu l ts from the linear r e gression models are presented for total tr ip generation A note is due here regarding the! statist ics that' are present ed in the regression results In order to obta in meaningful statistics that are not inflated (due to the huge size of the weighted sample), a s imple scale factor was applied to the sample for regression estimation The scale factor does not change the values of the model coeffic ients or descriptiv e statistics i n any way. It only changes the v a lues of the test sta tistics su ch as F s t atistic and !-stat istics so that they are not artificia lly i nflated by the mere presence of a huge samp le The regression models presented in Table 8 offer reaso n able indicat ions that are consistent with expectations A ll of the model coefficients have the expect ed values and signs and the goodness-of-frt statistics are as one would expect from a person based trip generation mode l I t is to be noted that the selection of explanatory variables to be i nc l uded in the model was not pu rel y driven by !-st at isti c valu es. If the model coefficient offered plausible indicati ons and the author considered the variable to be of value to the model (from an interpretive standpoint ), then even a variable that offered a sta tistically insignificant !-statis tic was retained In the model. It should also be noted 22


that all of the F-statistic values prese nt ed a t the bottom of each model we re statistically sig nificant at the 95 % confidence level and appropriat e deg r ees of freedom. Variable person Table 8 Linear Regression Model Estimation Results {Weighted Sample) or Total The table shows the result s of estimating models for total tri p generation. In g e n e ral it is found that car own ership and household inc ome positi vely and significantly Influence long distance trip generation Within ea ch group, i t is found that household size negatively impact s long di stan ce trip generation This may be attributable t o the fact that larger house hol ds may have mo r e constraints with res pect to disposable i ncome a nd time Among ho us ehold types, a married person is l ikel y to make more tr ips tha n othe r household types as ev idenced by the pos itive coeffici ent. Somewha t unexpected was the effect of the var iab l e single person, with no c hildren under 18 years o ld. This variable was not at all signif i cant in the older age group models possibly be cause those age groups do not have a sizea ble number of households that fall within th is house hold 23


type but in younger age groups seemed likely to make fewer trips. The B lack dummy variable exhibited negative coefficients among the older elderly group but was insignificant for all other age groups. The Hispanic dummy variable had a positive coefficient in all age groups except the older elderly when the coefficient was negative This may be unique to Florida since there is a higher percent of Hispanic population than the national average. Also, the geography of Florida may explain the positive coefficient of Hispanic trip making trends. The Female dummy has an expected overall negative coefficient for all age groups except the group of 65-74 years old. Higher education positively impacted long distance trip generation for various age groups. In summary, the analysis in th is section has shown that trip generat ion i ncreases in association with car ownership, education level, ma r ried status and Hispanic groups. On the other hand, it decreases in association with household size single parent household types, and Black groups. All of these trends were found to be consis tent with one's expectat ions. The income variable coefficient variations among age groups seem to imp ly that there are age-related lim itations besides automobile availability and disposable income that in hibit the pote n tial long-distance travel of the elderly. Once again, these findings point to the need to specially consider the physical and other capabilities/needs of the elderly in the provision of transportation services. 5. Long Distance Travel by Income Group Another market segment that has been the focus of much research attention over the past decade is that of the low income. The analysis in this section of the paper focuses on this group of hous eho lds and parallels the analysis presented in Section 4. A note is due here regard ing the method by which the "low income" group is defined in this paper. For the analysis the "household income" variable in the household demographic and trip files was used to categorize households by income level. However, it was considered desirable to control for household size effects in the definition of various 24


income levels. For example, a household income of $30,000 may be considered low for a family of four persons, but not so for a single person household. Therefore, a new variable was constructed for analyzing long distance travel by income group. The new variable is defined as "income per household member" and is calculated by dividing the household income variable by the household size. In order to do this, the ho usehold income categorical variable had to be converted into a variable with u nits of dollars For this, the midpoint of each incom e range was used to represent the dolla r value corresponding to each household i ncome category. This mid-value was then divided by household size to derive the household income on a per person basis Considering the newly created variable, income groups were defined as: Household income per person less than or equal to $7 4g9 Household income per person between $7500 and $12 ,499 Household income per person between $12,500 and $22,499 Household i ncome per person greater than or equal to $22,500 Comparisons across these income g roups are furnished in the next few subsections. 5.1 Socio-economic Characteristics of the Low Income Table 9 shows a comparison of demographic and socio-economic characteristics across various income groups. As expected the household size decreases as the income level increases. This is expected because of the way in which the income grouping was done. As the income grouping was done by dividing household income by household size, it is more likely that higher household sizes would fall into the lower income groups However, it is interesting to note that an examination of the average household income shows that higher household sizes are associated with lower household income levels. T he reasons behind this merit further investigation. 25


Table 9. Comparison of Demographic Characteristics across Income Groups (Weighted Sample) Characteristic Total Also, as expected, car ownership levels are slightly higher for those in the higher income groups. While only 8 percent of the households in the highest income group are carless, nearly three times as much are cartess in the lower income groups, twice as much in the lowest income group. The second income group shows the largest proportion of elderly. An examination of employment status indicates that there are substantial differences between the two lower income groups and the two higher income groups. This appears to correlate very well with education leve l of the householder. In the lowe r income groups, householders are predominantly high school 26


educated only. On the other hand, the higher income groups have higher percentages of householders who have had at least some college experience. With respect to household type, the trends observed are quite revealing. In general, the lower income groups have re latively h ighe r proportions of households that are married with children, single parent and single person when compared with households in the higher income group. The highest income group has a relatively high percentage of households that are married with no children Perhaps the absence of children under the age of 18 years allows both married partners to participate in the labor force; the higher income level resulting from dual-labor participation coupled with a small household size places this group in the highest income level. Finally, another revealing trend is seen in the aspect of race and ethnicity. The percentage of minorities is highest in the lower incor:ne groups and diminishes as income levels rise. This is quite important, as there appears to be a strong correlation between income and race and ethnicity If mobility is related to income, then it follows that mobility is also related to race and ethnicity. An analysis of the causal relations hips underlying the dynamics of race income, and mobility is beyond the scope of this study. 5.2 Trip Characteristics of the Low Income The previous section highlighted the important demographic trends that may affect the mobility patterns of individuals in different income groups. The analysis presented in this subsection will focus on trip characteristics of long distance travel, but should be interpreted in the context of the demographic trends presented in the last subsection. . Table 10 presents a comparison of trip chii"r"acteristics across income groups. It is to be . noted that this tab le compares household l evel travel characteristics. First and foremost, the table shows that mobility differs very significantly across the various income groups. Whereas the h ighest income group makes 9 long distance household 27


trips per year, the lower income groups make only about 3-4 trips. Nearly one-ha l f of the lower income groups make zero long distance trips in one-year time frame As expected, the higher income groups show the highest percentage of business trips, probably due to their higher emp l oyment and education levels Even though the pe r centage of recreation and vacation trips is r elatively simila r across the income groups, it should be noted that the highest income group makes about three times as many recr eational trips as do the lowest income group. L ower income groups show higher percentages of social visit and personal business trips, possibly because these trips are low cost (e. g do not involve lodging expenses) and relatively more obligatory. An examination of trip mode choice reveals that higher income levels are associated with increased usage of air transportation, twice as much as lower income. Nearly 40 percent of household trips are made by air In the highest income group compared wi t h just 18 percent in the lowest income group. The differences in mode usage should also be interpreted in conjunction with the differences in trip l engths. The trips of higher I ncome groups are, on average 70 percent longer than those of the lowest income group. In general, the mode and trip length distributions show that higher income groups have greater spatial access because of their ability to afford air transportation to a greater extent than the lower income groups. While significant differences were noted in mode and distance distributions the differences in travel duration (in terms of nights per trip) were not found to be significant across the income groups. However, one should note that the tota l time spent away from home on long d istance travel is much h igher for high-income households. Whereas the highest income group spent nearly 40 nights away from home in one year the corresponding duration for the lowest income group was only 18 nights. 28


Table 10. Comparison of Trip Characteristics across Income Groups (Weighted Sample) The analyses in Table 10 reveals that lower income groups have significantly lower mobility levels when compared with higher inco me groups. While this was an expected result. the amount of difference, especially between the lowest and highest income groups is striking. The highest income group makes about 300% more trips than the lowest income group and is about twice times more likely to utilize air transportation for their long distance trips. Clearly, the low income groups are significantly less mobile than other income groups, depend heavily on the automobile for their means of transportation, and have a substantially smaller action space within which they 29


undertake the i r long distance travel activities. Once again, these find ings are consistent with one's expectations but merit further consideration in the context of transportation equity. 5 3 Long D istance Trip Generation Model s by Income Group As in Section 4.3, this section focuses on the sensitiv i ty of long distance trip generation with respect to various i ndependent variables for different income groups T able 11 shows results of linear regression est i mation of long distance trip generation models for different income groups. As expected, vehicle ownership and household income positively influence household l ong distance trip generation in general. On the other hand, be ing a s i ngle parent B l ack, or H i spanic negat ivel y impacts household long distance trip generation and so does the larger household in general. Once again these trends are as expected and indicate that certain minority segments and ho u sehold types are less p rone to undertake long distance travel. A higher education level was found to positively influence long distance trip generation, possibly because households within these groups tend to have higher incomes. Looking closer at the variations among income groups, i t was found that household size has a positive coeffic ient imp l ying that there are other hindrances to long distance t r ip making othe r than that factor alone. Note that the coeff i cient for Retired person is positive in all but the highest income category where it is quite insignificantly negative. 30


Variable Table 11. Linear Regression Model Estimation Results (Weighted Sample) F = 112.6 or Total The finding that the age of householder variable has a negative coefficient in a ll income categories confirms the previous results that the mobility decl ines with age. In general, the results seem to indicate that, at the very high-income levels (i.e., the group with household income per person = $22,500 or more), the i nfluence of such variables as race and household type becomes quite marginal in nature. In summary, it may be concluded that substantial differences in trip generation behavior exist between the different income groups It appears that the higher income groups already indu lge In significant levels of long distance trip generation and are possibly more limited by time and other c onstraints than by car ownersh ip and income. 31


6 Conclusion s This paper analyzed long d istan c e travel behavior in F l orida fo r two key market segments that have been receiving co n siderable attention in the recent past, name l y the elderly and the low income Us ing the 1995 American Trave l Survey which collected deta i l ed informat i on about l ong d istance t r ips u ndertaken in a 12 month period, various aspects of long distance trave l behavior were analyzed for these market segments and compared against the general population The trip characteristics ana l yzed included t r ip freq u ency, tr i p purpose, tr i p mode trip distance, trip duration, and travel party size The analysis included the estimat i on of long distance trip generation models using l inear regress i on methods for d i ffe rent mar ket segments. Some of the main findings a n d unanswered quest i ons a r e highlighted here: Age-based Analysis There is a decl ine in trip generation w i th age with the greatest decrease occurring i n the 75 years o r over age group; this g r oup is a l so associated w i th t h e lowest h ousehold income and car owne r ship levels The elderly are sign i ficant l y more dependent on the bus mode t han the rest of the popu l ation. A l so, the auto mode share is found to diminish sign i ficant l y at the 75 years or over age group. Recr eation/vacation t rip generation decreases dramat i ca lly w i th the o n set o f the age of 75 years o r over. Whereas the other age groups made more tha n one recreational trip per year, this older elderly age group mad e just a little more t h an one-half of a trip per year (on average). Interestingly, both the average one-way trip distance and overall trip duration were found to increase with age; the o lder e l derly 75 years or over depicted the h ighest average va lues for these variables. 32


Income-based Analysis There is an increase in long distance trip generation with income; the trip generation rate almost triples when one transitions from the a very low-income group to a very high-income group. Whereas 48 percent of the lowest income group households made zero long distance trips, j us t 19 percent of the highest income group did so. The lower income groups were much more lik ely to travel by road (either auto or bus) when compared to other income groups; the share of air travel steadily increased with rising income levels. As expected, higher income levels were associated with higher percentages of business trip engagement possibly due to the employment status of the household members. The share of recreation/vacation trips was rather similar across the groups; however, the absolute number of recreation/vacation trips increased with Income Interestingly the shares of personal business and social visit trips decrease with increasing income level. Nearly 60 percent of all trips for the lowest income group were e i ther personal business or social visits; the corresponding percent for the highest income group was only 32 percent. Coupled with the increased usage of air transportation as income rises, the average one-way trip length was also found to increase significantly with income. On the other hand no substantial differences were noticeable with respect to overall trip duration. Overall, then, it can be seen that both the elderly and .the low income have significantly lower long distance mobility when compared to other segments of the population. The findings related to the elderly are very significant and important in the context of the aging of the U.S. population in general, and that of Florida in particular, over the next several decades. Similarly, the findings related to the lower Income groups are


significant in the context of providing access to opportunities outside their immediate vicinity. The 1995 American Travel Survey database is a very rich database that provides detailed personal and household demographic and long distance travel information. There are many aspects of the database that have not been analyzed within the scope of this paper. Future analyses utilizing this data set will undoubtedly reveal long distance travel trends valuable in a policy-making context. 34


7. References Abdei-Aty, M. and P. Jovanis. A Survey of the Elderly: An Assessment of Their Travel Characteristics. In Transportation Research Record (forthcoming), TRB, National Research Council, Washington, D C., 1999. Benekohal, R.H., R.M. Michaels, E Shim, and P.T.V. Resende. Effects of Aging on Older Drivers' Travel Characteristics. Presented at the 73rrJ Annual Meeting of the Transportation Research Board, TRB, National Research Council, Washington, D.C., 1994 Bureau of Transportat ion Statistics. 1995 American Travel Survey United States Profile. BTS Report No. BTSIATS95-US, U .S. Department of Transportation, 1997. Bureau of Transportation Statistics. 1995 American Travel Survey: Summary Travel CharacteristicsFlorida. BTS Report No. BTSIATS95-ESTC/Fl, U.S. Department of Transportation, 1997. Bureau of Transportat ion Statistics. Transportation Statistics Annual Report 1998 Long Distance Travel and Freight. BTS Report No. BTS98-S-01, U.S. Department of Transportation, 1998. Chu, X The Effects of Age on the Driving Habits of the Elderly: Evidence from 1990 National Personal Transportation Study. Research and Special Programs Administration Pub licat ion No. DOT-T-95-12, U.S. Department of Transportation, 1994. Crepeau, R. and C Lave. Travel by Househo ld without Vehicles. In Travel Mode Special Reports: 1990 Nationwide Personal Transportation Survey Report Series, Chapter 1, U.S. Department ofTransportation, Washington, D.C., 1994. Georggi, N. L. and R. Pendyala. An Analysis of Long Distance Travel Behavior of the Elderly and the Low Income. Paper prepared for presentation at the Transportatio n Research Board Conference on Personal Travel: the Long and short of It, Washington D.C. 1999. ITE Technical Council Committee 6F-50. Selected Travel Behavior Characteristics of the Elderly Institu te of Transportation Engineers, Washington D C ., 1994. Rosenbloom, S Travel by the Elderly. In 1990 Nationwide Personal Transportation Survey Demographic Special Reports, Chapter Ill. U.S Department of Transportation, Washington, D.C., 1995. 3'5

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An analysis of long-distance travel behavior of the elderly and the low-income /
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Thesis (M.S.C.E.)--University of South Florida, 2000.
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