TIME-SPACE DIARIES: MERGING TRADITIONS by
Andrew S. Harvey
Director, Time-use Research Program Saint Mary’s University Halifax, NS, Canada
[email protected] 902-420-5676
prepared for International Conference on Transport Survey Quality and Innovation
The author wishes to thank SSHRC for project support, which made this paper possible. He also wishes to thank Jamie Spinney, Heather Thompson and Danuta Pietkiewicz for their assistance.
ABSTRACT Activities occur in time and space. Traditionally the study of these two dimensions has been bifurcated. Time-diary researchers have focused on activities and the context of activities occupying time. They have tended to treat space generically. Travel behaviour/demand researchers have focused mainly on travel, the overcoming of space, paying little attention to activities. This paper identifies basic instruments used by each approach, and given this authors experience with activity/time/space studies, examines data captured by time-dairy studies in light of the data needs for understanding travel, emphasizing the value added by time-space diaries. It also supports the view, based on existing work, that the activity approach increases the capture of daily trips. Time-use studies date from the second decade of the last century. From the mid 1960’s to mid 1970’s some time-use researchers explored time and space but the work did not make it into the travel literature. Researchers then continued looking only at time. About 1990 a call was made for the examination and integration to time-use and travel behaviour research, and at the same time travel researchers started to explore the integration of activities in diary collection. This paper argues that while the typical organizing principle of travel diaries was trips it is important that it be time. This would ensure that all activities are captured. Additionally it is important that activities be freely recorded without broad catchall categories like “at home”. Additionally, it is observed that an attempt must be made to capture all significant dimensions of an activity. These include, minimally, what is being done, what else is being done, where- generically and geographically--, with whom and for whom. This information can be best captured using time-space diaries, which will show all activities at each location and all locations for each activity.
TIME-SPACE DIARIES: MERGING TRADITIONS Andrew S. Harvey
1. INTRODUCTION Activities occur in time and space. Traditionally, the study of these two dimensions has been bifurcated. Time-diary researchers have focused on activities and the context of activities occupying time. They have tended to treat space generically. Travel behaviour/demand researchers have focused mainly on travel-the overcoming of space-paying little attention to activities. In practice, travel modellers venturing into activity modelling, as well as time-use researchers, whose stock in trade is activities, have been working in a surprisingly “aspatial” world (Miller, 1996). Over the past 30 years, travel and time-use researchers have made intermittent forays into each other’s traditional territory and have flirted with the integration of space. In addition, during the past decade, there has been a slow but sustained movement of the approaches toward each other with the explicit goal of developing improved activity- and trip-measuring instruments. This paper identifies basic instruments used by each approach, and given this author’s experience with activity/time/space studies, examines data captured by time-diary studies in light of the value added by time-space diaries. It argues for the adoption of the use of the time-space diary as a crucial input to travel and activity behaviour modelling.
2. TIME-USE AND TRAVEL DEMAND RESEARCH Time-use studies date from the second decade of the last century. However, starting in the mid1960s, through the mid-1970s, a few time-use researchers recognized the importance of space in shaping behaviour and the need for better data to explore related issues. Consequently, studies were undertaken that collected activity data with specific spatial coordinates for all activities (von Rosenbladt 1972, Chapin, 1974; Elliott, Harvey, Procos, 1976). The time-space data was exploited by planners and geographers but never made its way into the travel literature. Following those studies, time diaries reverted to collecting generic location only, if they collected location at all. Concurrent with the waning time-use foray into time-space studies, travel researchers undertook to develop an activity-based approach and expanded travel studies to capture activity data more in line with typical time-diary studies (Jones, 1979; Jones et al., 1983). As in the case of time-diary data collection, following initial work, on the activity approach there was a hiatus in the collection of expanded activity data. In a paper presented in 1991 at the International Association for Time Use Research conference in Quebec, Eric Pas and this author started to explore the relationship between time-use and travel behaviour research (Pas and Harvey, 1997). In that paper, we briefly addressed the history of the development of travel demand modelling which, at least until the mid 1970s, viewed daily travel in terms of a set of separate trips. We argued that this approach failed to deal adequately with the derived-demand nature of daily travel and with the interdependencies, inherent in travel choices, 3
among trips and among people. We further argued that neither the development of disaggregate travel-choice models beginning in the late 1960s nor the introduction of psychometric scaling techniques to explore preferences really changed the paradigm by which travel was analyzed. Further, we argued for closer ties between time-use and travel researchers. Fortunately, our plea coincided with increasing interest among travel researchers in examining travel in light of activities. In 1992, Stopher introduced an activity diary that was implemented in the Boston area. Its introduction was fostered by the conviction that most travel is a derived demand, and hence, it is necessary to identify and understand the activities that give rise to travel. A little later in the 1990s time-use researchers started to explore in greater depth the travel data captured in time-diary studies (Harvey et al., 1997; Harvey et al., 1999; Vilhelmson, 1997)
2.1
Needs and Directions
With or without appropriate data, the activity approach to travel behaviour research appears to have gradually taken a secure place on stage. Growing questioning of, and dissatisfaction with, the fourstep method of travel analysis over the past two decades and the recognition that travel is typically not an end in itself but a derived demand have given rise to a number of events and writings examining and promoting the activity approach (Stopher, Meyburg & Brog, 1981; Jones, Koppleman & Orfeuil, 1990; Ettema & Timmermans, 1997; Engelke L.J. (1997). The sessions that resulted in the foregoing works strongly present the need to move foreward with activity analysis.
3. TRAVEL AND ACTIVITY MEASUREMENT: THE INSTRUMENTS What is the current state of the measurement of trips and activities? I am going to avoid chronicling the myriad measurement techniques that can be used and their strengths and weaknesses. These have been dealt with at some length elsewhere (Harvey, 1993; Goulias, 1997). This paper focuses on two measurement approaches: trip diaries and activity diaries. The organizing structure of traditional travel diaries is trips. Respondents are led through an instrument that asks them to record all trips being sought and some contextual information on each trip in the order in which the trips are undertaken. Figure 1 presents a trip diary which, according to Axhausen, has been very influential since its inclusion in the U.S. Bureau of Public Road’s manual for home interview studies (Axhausen, 1995). It captures origin and destination, limited modes of travel, start and arrival times, limited purposes, number of vehicle occupants, and parking detail. Trips are dealt with out of context amidst daily activities, and the diaries provide no inherent check that all daily trips are accounted for. In contrast, time diaries capture trips in the context of all daily activities. Respondents report all activities in a day from midnight to midnight, or some comparable 24-hour period, and trips are captured as just another activity (Harvey, 1993). Much of the trip detail, such as OD, timing, purpose and travel mode, explicitly captured in the trip diary, is inherent in the activity diary structure and can be derived. However, activity diaries typically provide only for generic OD
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coding. In contrast, trip diaries can provide for somewhat precise spatial coding but seldom use the spatial detail. An examination of travel diaries presented by Axhausen (1995) suggests that an activity diary study was first used in a regular travel study in Belgium in 1986-87. It was not until Stopher developed an activity diary for a 1991 Boston study that activity-based travel diaries began to be more regularly used to collect travel data, (see Figure 2). Stopher’s diary required capturing all activities over the day, thus exhausting the 24 hours (Stopher, 1992). This is one of the main defining features of time diaries. However, capture of activity detail was limited to out-of-home activities. The diary provided for limited activities mostly focused on travel. In-home activities were undifferentiated. The diary captured considerable travel detail, including mixed travel mode. Time allocated to each mode was not distinguished, and a total travel time between activities was captured. Non-home, non-travel activities were specified for later coding. The diary captured activity and travel time both as start time and end time and also as a respondent estimated total travel time. It also captured some parking detail and costs and public transit cost. Location was captured by address and nearest intersection.
Figure 1 - Diary form: US Bureau of Public Roads 1954.
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Source: Axhausen (1995)
Figure 2 - Diary form: Stopher, Boston 1991 The organizing principal for time diaries has always been a time frame, as noted above, typically a 24-hour period. Respondents are asked to account for all time from the beginning of the diary to the end, be it a one-day, two-day, or seven-day diary. By its nature, the diary provides an immediate check that the 24 hours or other time units have been fully accounted for. Over the day, the time diary elicits information on several daily flow dimensions, (to be discussed below), and thus it aids recall and promotes comprehensiveness. The principle of capturing all activity was addressed in the Boston diary (Figure 2). The major shortcomings of the Boston diary are its failure to more fully account for activities and their context and its bulkiness. Regardless, it represented a significant advance in travel data collection in the U.S. Time diaries may present the respondent with closed or open intervals. Closed interval diaries present the day in time blocks of five or more minutes and allow for the respondent to note desired activity details for each period. Open-activity diaries present no explicit time structure but allow respondents to report their behaviour in terms of distinct activities that they deem reportable. Hence the temporal grain of an open diary is generated by the respondent, and activities and not dictated by the instrument. However, respondents are typically given a guideline for activities such as “ten minutes or longer except for travel, which should be reported for all trips no matter how short.” Additionally, they are advised that the new activity be deemed to have commenced when any contextual dimension changes. The Boston diary was an open interval diary with the respondent reporting their sequence of activities with start and end times. 6
With further research including use of a focus group a day planner format was developed (Stopher & Wilmot 2000). As Figure 3 shows the format is very innovative. It has an implicit 12-minute closed interval based on the shading. However, it really allows for open intervals. This is, potentially, a very important improvement. Conventional wisdom and experience have indicated that open intervals work well when there is an interviewer while closed intervals work best for selfcompletion studies since the respondents need more structure. The diary in Figure 3 provides for both. In addition, the Stopher diary could eliminate a column by capturing mode with location.
Figure 3 - Diary form: Stopher, 2000. In contrast, the prototype self-completion activity diary for the European Harmonized Time-use Study, the EUROSTAT diary adopts a ten-minute closed interval approach. (see Figure 4). W h a t w e r e y o u d o in g ?
W h a t e ls e w e r e y o u d o in g ?
R e c o r d y o u r m a in a c t iv it y f o r e a c h 1 0 - m i n u t e
R e c o r d t h e m o s t im p o r t a n t p a r a ll e l a c t i v i t y .
W e re y o u a l o n e o r t o g e t h e r w ith s om ebody y ou know ?
p e r i o d fr o m 0 7 .0 0 to 1 0 .0 0 a m ! M a r k " y e s " b y c r o s s in g C h i ld r e n
O th e r
O th e r
O n ly o n e m a i n a c t i v it y o n e a c h li n e !
u p to 9
h o u s e h o ld
p e rso n s
D is t in g u i s h b e t w e e n t r a v e l a n d t h e a c t i v it y t h a t is t h e r e a s o n f o r t r a v e ll in g .
A lo n e
li v in g i n y o u r m e m b e r s
th a t y o u
D o n o t f o r g e t t h e m o d e o f t r a n s p o r t a t io n .
h o u s e h o ld
k now
T im e , a m
D is t in g u i s h b e t w e e n f ir s t a n d s e c o n d jo b , if a n y .
0 7 .0 0 -0 7 .1 0
W oke up the children
0 7 .1 0 -0 7 .2 0
H ad breakfast
0 7 .2 0 -0 7 .3 0
T alked w ith m y fam ily
- -" - -
- -" - -
0 7 .3 0 -0 7 .4 0
C leared the table
Listened to the radio
0 7 .4 0 -0 7 .5 0
H elped the children dressing
T alked w ith m y children
0 7 .5 0 -0 8 .0 0
W ent to the day care centre, by foot
0 8 .0 0 -0 8 .1 0
B y bus to job
0 8 .1 0 -0 8 .2 0
B y bus to job
0 8 .2 0 -0 8 .3 0
R egular w ork (first job)
- -" - -
R ead the new spaper - -" - -
0 8 .3 0 -0 8 .4 0 0 8 .4 0 -0 8 .5 0 0 8 .5 0 -0 9 .0 0 0 9 .0 0 -0 9 .1 0 0 9 .1 0 -0 9 .2 0 0 9 .2 0 -0 9 .3 0
U s e a n a r ro w , c it a t io n m a r k s o r t h e li k e t o m a rk t h a t a n a c t i v it y la s t s lo n g e r t h a n 1 0 m in u te s .
0 9 .3 0 -0 9 .4 0 0 9 .4 0 -0 9 .5 0
Figure 4 – Prototype EUROSTAT diary for the European Harmonized Diary Study 0 9 .5 0 -1 0 .0 0
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Respondents complete the diary by writing in next to the appropriate time each activity as they start it. They then complete the additional contextual information. The only additional information sought by the EUROSTAT diary is a secondary activity and a very abbreviated “with whom.” Hence, in the EUROSTAT diary, a new activity episode starts if any one of what is being done, what else is being done, or with whom it is being done changes. From the travel perspective, a notable feature of this diary is that it does not directly provide for the capture of location. Instead, respondents are asked where they were when they first began recording the diary, and location is then imputed from travel episodes. When travel occurs, it is assumed that location changes. Researchers at Statistics Finland have promoted this approach. While the approach has some surface value, there has been no solid analysis of its efficacy. This approach is considered further below in the discussion of location. In contrast to the closed interval approach taken by the EUROSTAT diary an open activity diary was used to collect the time-space data in the Dimensions of Metropolitan Activity (DOMA) study, In Halifax, Canada. (see Figure 5). Such a form is much less busy and captures all the information gained in a closed interval diary except that relating to parking and costs. The activity detail is, of course, far greater in the DOMA diary. Respondents filled in what they were doing (e.g., eating breakfast, driving to work), the precise minute they started doing it, what else they were doing (e.g., listening to radio), where they were or in transit (e.g., home, car), whom they were with (e.g., spouse, co-worker), and any remarks useful in interpreting the episode recorded for that time. Remarks were prompted for certain activities, type of reading, type of shopping, etc. In some cases, respondents volunteered random information, indicating most often subjective feelings. Information about specific locations was requested in terms of civic address; name of store, school or other place; and in their absence, nearest intersection, in a fashion very similar to that used in the Boston survey, (see Figure 2). Each stage or segment of travel was reported as a new activity allowing all contextual information to be captured for each. If an activity was omitted respondents could add it anywhere simply by identifying its start time and all collateral information. What you did from midnight until 9 in the morning What did you do?
Time Began
What else were you doing?
Where?
With Whom?
Remarks
Figure 5 – Dimensions of Metropolitan Activity Survey (DOMA), Halifax 1971-72. The main spatial interest in the DOMA study was the geographic location and sequencing of activities, rather than travel. A central issue of concern was the possibility of eliminating travel by means of mixed land use design. However, travel was of considerable interest, and extensive travel-related information was captured in the questionnaire.
8
In contrast, a study undertaken by Jones and colleagues had as its central purpose the understanding of travel behaviour (Jones et al., 1983). The report on their study, Understanding Travel Behaviour, outlines a very serious attempt to construct an approach and instruments to achieve their goal. With a multi-method approach that is very well documented, they developed a main activity survey, which they conducted in Banbury. Central to that study was an activity diary (see Figure 6). The instrument paralleled closely the DOMA instrument in that it was an open diary allowing for the sequencing of activities in natural language and for the reporting of location. It did not provide for secondary activities or company.
Figure 6 – Banbury Activity Travel Study, Jones et al. (1983) The authors provide considerable insight into the strengths and weakness of their diary. They found a major strength was that activity recall contrasted strongly and favourably with trip recall. Respondents had little trouble recalling activities, changes of place, and hence, travel. In contrast to recall trips out of context was more demanding and less intuitive (Jones et al., 1983). The authors also identified problems with completion of their diary. First, they found technical problems in recording activities. With respect to location recording, they found that location was often too general. Also, respondents often include travel in the activity, e.g., “went shopping.” Second they found problems in activity definition, particularly in the way the respondents had recorded overlapping and co-occurring activities. Most importantly, they noted that activities are distinguished by several dimensions, including behaviour, situation, psycho-physiological state, social orientation, and psychological orientation (Jones et. al., 1983). They concluded that understanding activities requires the capture of all dimensions of an activity. This is a tenet of any good diary. They also concluded that activity representation was sensitive to type of survey instrument and respondent instructions. Further they noted that strong interrelationships among household members with respect to travel argued for collecting household diaries (Jones et. al., 1983).
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3.1 Time-Diary Surveys Aside from ongoing research in travel behaviour, there is a rich tradition in time-budget/diary studies. Beginning early in the past century, the research approach gained considerable momentum following the Multinational Time-use Study in the mid 1960s (Szalai, 1972). Commencing in 1970, statistical bureaus in a number of countries started collecting official time-use data. Since the Beijing Women’s Conference, there has been a rapid escalation in activity aimed at promoting standardized collection of time-use data. The EUROSTAT harmonized time-use project and efforts by the UN Statistical Office to develop a standard activity classification are evidence of this push. The motivation, however, for this interest is the need for data for valuing non-market production. While interest in travel behaviour may not be absent, it plays no role in the overall development of studies. This is unfortunate. Travel researchers need to make their interests known and to participate in the design of such studies to ensure that they are able to optimize the usefulness of time-use data for travel behaviour research. A sampling of time-use studies suggests that travel accounts for nearly one-fifth (18.9%) of all activities reported. (see Table 1). It also shows that over all the studies identified, reporting individuals averaged 4.3 trips per day. Table 1 -- Basic Dimensions of Selected Time-use Surveys
Halifax (DOMA) 1971
2,141
2,141
1
Diary Events 60,607
Canada Pilot 1981
2,682
2,682
1
72,987
13,145
18.1
4.9
Persons
Diaries
Days
Trips as % Trips per of Events Person 11,614 19.2 5.4
Trips
Canada 1992
8,996
8,996
1
190,327
38,563
20.3
4.3
Canada 1998
10,479
10,479
1
221.105
40.910
18.5
3.9
Netherlands 1990
3,415
23,905
7
493,553
101,807
20.6
4.3
Netherlands 1995
3,227
22,589
7
560,258
102,349
18.3
4.5
Netherlands 1997
1,328
2,693
2
49,780
10,338
20.9
3.8
Norway 1990
3,088
6,174
2
176,191
28,616
16.2
4.6
Austria 1991
25,233
25,233
1
513,152
98,073
19.1
3.9
Sweden 1991
3,630
7,187
2
219,165
36,684
16.7
5.3
58,438
107,256
2,423,531
457,340
18.9
4.3
Total
Source: Derived from Harvey et al. (1999).
Behavioural analysis requires a considerable amount of collateral data. Diary data provide a clear insight into all daily behaviour, but if the appropriate data is not available, many desirable analyses will be weak or impossible to perform. It is possible to examine the nature of collateral data in travel and activity studies building on the work of Axhausen (1995). His work outlines a number of domains for which information needs to be gathered. (see Table 2). The data presented in Table 2 is not exhaustive by any means. However, it does show many of the variables deemed to be significant by many of the data collection efforts. In particular, it shows the importance to travel researchers of collecting vehicle-and preferences-related data and information on alternative possibilities. Typically, time-use researchers have not captured such information. However, in the questionnaire, the DOMA study did collect considerable detail relating to travel possibilities, costs, and perceptions.
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Table 2 -- Study Contents Selected Study Types Domain Household
Travel-Diary* Public transport accessibility Telecommunications links/information sources Allocation/kind of residence Household income Number of vehicles Number of household residents Location of household
Time-Diary** Spouse’s employment (50) Household type (100) Type of dwelling (60) Household Equipment (60) Other household facilities (40) Location of household (90) Income (60) Local facilities (30)
Personal
Sex Year of birth Position in Household Education/training Work details Mixed occupation/class Transport access Usual travel arrangements
Vehicle
Technological detail of cars Information technology in car Ownership and funding of car Access and use Time (start/end times) Space (addresses or proxy) Modal detail Information availability/use Situational handicaps (weight/child) Company in vehicle Parallel activity Type of parking Costs Sources of funding Walking distance/time to Legality of the parking space Of trip
Sex (100) Age (100) Civic status (100) Position in household (60) Education/training (90) Employment status (90) Occupation (60) Class/status (50) Industry/branch (40) n/a n/a n/a Use shown only for respondent Diary – continuous chronological Captured with generic location Captured in location Information not typically captured Company captured by with whom Captured as secondary activity
Movement
Parking
Time Other
No Detail
Halifax DOMA (Time-Space) Public transport acccessibility Spouses employment Household type Type of dwelling Household equipment Other household facilities Location of household Income Local facilities Number of vehicles Sex Age Civic status Position in household Education/training Employment status Occupation Class/status Industry/branch n/a n/a Number of Household cars Access and use Diary– continuous chronological Addresses or proxy Coded to 1/10th km Captured in location Company captured by with whom Captured as secondary activity Availability/use of travel alternatives No Detail
Day of the week (60) Week/month/season/date (60) Preferences/beliefs (40) Background data (30) Health/well-being (10)
Sources: *Axhausen (1995) **Harvey (1993) (50) Percent of examined time use studies incorporated this measure
3.2 Events/Episodes Activities and Trips The basic unit in a time-diary study is the event or episode. It is, in fact, a line in a diary with a start time and values for all other dimensions being collected. Whenever any single dimension changes, a new episode starts with a new start time and new values for any changed dimensions. Hence, in the DOMA diary in Figure 5 above, a new episode starts with a change in any one of “What were you doing?; What else?; Where?; With whom?” Activity refers to the content of the block of time (What were you doing?; What else were you doing?) as defined by a coding scheme. It may be characterized as primary or secondary. Primary activities are defined as the main content being undertaken at the recorded time. Secondary activities are concurrent content occurring in the sametime slot as the primary activity. In fact, individuals may not be limited to only two concurrent activities at a time. Some time use researchers claim they cannot capture secondary activities while others have captured more than two activities at time (Kinsley & O’Donnell, 1984). Typically, the respondent is left to indicate which activities are primary and which are secondary. Gathering and coding activity data requires an understanding of what activities should be captured and how they should be structured. An economic model requires that the data permit the identification of market and non-market activities. A social perspective requires the ability to 11
separate individual and social activities or work and leisure activities. The travel perspective requires the distinction between travel and non-travel related activities. There are many activity coding schemes, a few of which are noted in Tables 3 and 4. Typically activity oriented surveys use more elaborate coding schemes than those used by trip studies. This is evidenced in Tables 3 and 4. Salt Lake City in Table 3 was a purely trip based study. In contrast Boston and Dallas were activity surveys, as were Jones and Lawton in Table 4. All the activity surveys except Boston have a more elaborate activity scheme. The multinational Time Use Study (MTUS) recodes existing time diary studies into a 23 and a 40-code scheme. These have been designed to maximize consistency across data sets. The Salai data while captured at a 96-code level is also presented using a 27 category coding. (see Table 4). Time diary activity codes do not need to distinguish home and out-of-home orientation since that is derived from location data. Table 3 – Trip Purposes Available from Selected Surveys Boston (Activity)
DOMA 1971 (Time/space Diary)
Canada 1992 (Time Diary)
Salt Lake City
Portland
Dallas 0 Sleep at home 1 Work at home 2 Other at home
At Home Only
All activities at Home
All activities at home
1 At home
51 Amusements (at home) Developed “At Home” from Location
Pick-Up/Drop Off
Can be derived
Can be derived
2 Pick-Up/ Drop Off
22 Pick-Up/ Drop-Off Passengers
5 Pick-Up/Get Picked U 6 Drop Off/Get Dropped \\Off
Work
Work
3 Work and Work Related
12 Work
7 Work
Work-Related
Work-Related Classes Homework Waiting
Work Second job Work-Related Classes Homework Waiting By type groceries, durables, bank, services. etc.
13 Work-Related
8 Work-Related
4 School
41 School
9 Preschool, school, college
5 Shopping
14 Shopping (general) 15 Shopping (major)
21 Shop - Groceries, Housewares, Meds 22 Shop - Furniture, Clothes, App.
5 School
6 Shopping
By type groceries, durables, bank, services. Etc.
7 Social
Can be derived
8 Recreational
Can be derived
9 Eat Out
10 Banking Personal Business
11 Other
Can be derived
In shopping
Separate for each of 10 major groups
6 SocialRecreational, and Eat Out
31 Visiting 32 Casual entertaining 33 Formal entertaining 42 Culture 44 Civic 52 Amusements (out-ofhome) 53 Hobbies 54 Exercise/Athletics 55 Rest/Relaxation 56 Spectator athletic events
15 Entertainment 16 Visit Friends/Relatives 17 Community Meeting
13 Gym/Health club 14 Exercise/Recreation
Can be derived
11 Meals
11 Eat Out
In shopping
7 Personal Business Banking
16 Personal services 18 Professional services 19 Household or personal business 20 Household maintenance 21 Household obligations 43 Religion/Civil services
19 Church, Temple 20 Buy Gas 23 Banking, Post Office, Utilities 24 Other Personal Business
8 Childcare 9 Other
17 Medical care 45 Volunteer work 90 Incidental trip 91 Tag along trip
10 Childcare, Daycare 12 Medical 18 Occasional volunteer Work 25 Accompany another 26 Other
Can be calculated
Source: Expansion based on Stopher (2000)
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Table 4 -- Activity Classifications Relevant t o Activity and Travel Analysis Jones (1983) Work Education Homework Extra-mural educ. Household Chores Food preparation Odd jobs Gardening Child and Adult care Eating and drinking Main sleep Personal care Resting Shopping Services In-home social Out-of-home social Group social Read/TV/radio Outings Spectating Children’s play Active leisure Individual hobbies Travel Waiting
Lawton (1996) Meals Work Work-related Shopping (General) Shopping (Major) Personal services Medical care Professional services Household or pers. business Household maintenance Household obligations Pick-Up-/Drop-Off others Visiting Casual entertaining Formal Entertaining School Culture Religion/Civil Services Civic Amusements (at home) Amusements (Out of home) Hobbies Exercise/Athletics Rest and Relaxation Spectator Athletic Events Out of area travel Incidental travel Tag along travel
MTUS- 23 Code Paid work etc Routine housework Food preparation & cooking Meals and snacks Child Care Shopping (All Sorts) Domestic-related travel Other non-work travel Personal care activities Eating Out At Pubs, Clubs Spectator Active Sporting Walking Visiting Or Entertaining Television, Radio, Etc. Reading Talking, Relaxing Non-Routine Domestic Work Hobbies Medical-Related Pers. Care Education
MTUS-40 Code Paid work Paid work at home Second job School/classes Travel To/From Work Cooking, washing up Housework Odd jobs Gardening, pets Shopping Child Care Domestic Travel Dressing/Toilet Personal Services Meals, Snacks Sleep Leisure Travel Excursions Active Sport Passive Sport Walks Religious Activities Civic Duties Cinema, Theatre Dances, Parties Social Club Pub Restaurant Visiting Friends Listening To Radio Television, Video Listening To Tapes Study Reading Relaxing Conversation Entertaining Friends Knitting Sewing Etc Other Hobbies
Szalai – 27 code Regular work Non-work activities Work related Cleaning house Laundry, mending Other house upkeep Housework Child care Shopping Non-Work Trips Family Tasks Personal Care Eating Physiological Needs Education Organizations Reading Social Life Conversation Walking Sports Spectacles Various Leisure Resting Free Time
Another concept that can be elicited from a diary is a project. A project consists of a combination of activities and contexts related to the achievement of a particular end. Hence, meal provision consists of shopping, cooking, setting the table, and cleaning up. Similarly going to the movies may consist of getting changed to go, picking up the baby sitter, driving to the theatre, watching the movie, driving home from the theatre, and taking the baby sitter home. Thus, while watching a movie at the theatre taken alone may only require one setting and two hours, the project involves several settings and may take up to twice as long. Neither time-use researchers nor travel researchers have come to grips with the concept of project, and yet it may well be more meaningful than the concepts with which both have been working. Considerable work needs to be done to operationalize the concept of project. In a sense, the concept of project is an activity equivalent of the concepts of tour or journey used by travel researchers. Understanding the concept of projects and their constituent parts could help to develop new technologies and regimens that can facilitate their achievement. Such changes may have important
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impacts on travel behaviour. It can be expected that the rapid growth in information technology may well play a significant role in the more efficient achievement of projects. Indeed much of technological change with respect to daily living has significantly altered standard projects of daily life. The growth of services offered through such technology as the internet increases opportunities for a wide range of activities. Therefore, an understanding of the substitutes for and complements of human behaviour is necessary for any simulation or forecasting endeavours. For example, banking which used to have to be carried out at a specific place during specific hours, and therefore, in a well-defined activity setting, has now become a less restricted activity for many, most banking activities and some mailing activities can now be undertaken in a virtually unlimited spatial-temporal terrain. In work valuing non-market production, this author and a colleague found that the value typically assigned to providing a home meal including the value of labour amounted to nearly twice the value of the same meal purchased commercially. This fact has not gone unnoticed by businesses and consumers as meals are increasingly purchased outside the home. Such change represents a massive behavioural shift, possibly increasing person trips. However, there may be no shift at all as trips to the bank or post office are simply replaced by trips to fast food venues. The trip not taken may become a different trip. Time-use researchers have constantly grappled with the definition and treatment of travel. There has been little uniformity in the way trips have been defined and treated. As primarily a time-use researcher, I thought the ambiguity stemmed from our lack of experience with travel surveys. However, examining the travel literature, I realized that time-use researchers had no monopoly in definitional ambiguity which also exists in the travel literature. Axhausen (1995) defined travel in terms of, Stage a continuous movement with one travel mode including any waiting times before the start of or during the movement; trip, a sequence of one or more stages between two activities; tour, a sequence of trips starting and ending at the same location; and, finally, a journey, a tour starting and ending at home. This appears to be in accordance with the 1995 NPTS where a travel day trip is defined as any time the respondent goes from one address to another by any travel mode. While these definitions are commonly held they are not always adopted in travel studies. From the traditional time-diary perspective, a trip typically corresponds to a stage as defined by Axhausen (1995). It is a change of place or a change in one of the characteristics of the movement episode, for example, a change of travel mode. Hence, walking to a bus, taking the bus to a stop near work, and walking from there to work would be three trips, not one trip with three stages since in reality, they were three different episodes and two different activities (walking, taking a bus). This approach needs careful examination by time-use researchers. Time-diary researchers have two methods for determining trip purpose. Using the traditional method, all trips are defined in terms of their destination purpose except those ending at home. The purpose of trips ending at home is determined by purpose at the origin. However, determination of the origin has not always been constant across studies. Where trips are bounded on each side by non-travel activities, determination of purpose is fairly straightforward. Time-diary researchers define a trip starting at work and ending at home as a work trip. If, however, that trip includes a stop at a store its purpose
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is a little less certain. In some cases, it is counted as a work trip with a stop; in other cases, it is counted as a work trip between work and the store and a shopping trip between the store, and home. Trip-purpose has also been defined in Sweden and Finland using a different method involving the concept of turning point. The turning point may either be designated by the respondent or be determined as the longest activity or site duration in the chain. Accordingly, on trips away from home, the trips purpose is assigned at the destination. However, on trips following the turning point, the trips purpose is assigned to the origin. Time diaries permit a full analysis of trips in terms of timing, travel mode, purpose, and OD orientation or type (see Table 5). Travel, in a series of diary studies, shows that non-peak trips, auto trips, other trips (not for work, shop, or leisure), and primarily home-out of home account for the largest shares in their respective classifications. Timediary researchers have not recognized returning home as a trip purpose. Further, non-home, workbased trips have not been explicitly studied by time-use researchers. However, the diary format and data easily support such analysis. Table 5 -- Trip Characteristics, Selected Time-use Surveys
Number of Daily Trips Total Travel Time (Daily) Travel reported Total travel
Canada Netherlands Netherlands Netherlands 1992 1990 1995 1997 Mean Mean Mean Mean 4.28 4.26 4.53 3.82
Norway 1990 Mean 4.64
Austria 1991 Mean 3.88
Sweden 1991 Mean 5.31
64.89 69.28
71.13 98.04
82.06 98.75
57.5 88.9
67.91 92.38
47.71 75.97
80.66 88.22
Travel Timings (Daily Trips) Morning peak Afternoon peak Non peak
0.18 0.33 3.76
0.16 0.38 3.72
0.21 0.41 3.91
.28 .70 2.92
0.13 0.29 4.21
0.28 0.44 3.16
0.19 0.43 4.68
Modal Split (Daily Trips) Car trips Walking trips Other mode trips
2.88 0.57 0.2
1.25 0.37 1.01
1.43 0.38 1.11
2.13 0.58 1.52
2.22 0.62 0.1
0.82 0.31 0.78
2.38 0.96 0.69
Trip Purpose (Daily Trips) Work travel Shopping travel Leisure trips Other trips
1.1 0.94 1.1 1.15
0.68 0.99 1.21 1.46
0.86 0.99 1.31 1.47
.52 .63 .88 1.52
1.23 0.26 1.17 2.03
0.83 0.73 1.05 1.3
1.44 1.18 1.2 1.51
Trip Type (Daily Trips) Home-to-Out Home-to-Home Out-to-Out Out-to-Home
1.39 0.24 1.33 1.31
1.57 0.62 0.85 1.19
1.62 0.58 1.04 1.29
0.93 0.03 1.63 1.07
1.59 0.21 1.34 1.49
1.56 0.62 0.63 1.08
1.72 0.48 1.65 1.44
For purposes of this paper, the author generally accepts the travel definitions used by Axhausen in his examination of travel surveys. Axhausen suggests that “an activity is the main business carried out in one spatial setting while interacting with the same group of relevant people or being alone. It 15
includes any waiting time before the start of the activity proper” (Axhausen, 1995, p. 5). What Axhausen defines as an activity is, from the time-use perspective, an event or episode, which is the basic building block of the flow of behaviour and hence of the time diary (Chapin & Hightower, 1966). It is a row in a diary. The detail of the event/episode captures much of the information deemed necessary to understand what activity is being performed and what its immediate context is. In contrast, an activity, as indicated above, is a unit of behaviour—what is being done-defined in terms of content by a coding scheme. Typically, activities are examined in terms of total time allocated to them, which is determined by the aggregation of all identically denominated episodes in a diary. Therefore, the activity of eating may consist of three episodes-breakfast, lunch, dinnersummed to get the daily time allocation for the activity. Breakfast would be an episode aggregated into the activity eating.
3.3 Contextual Trip/Activity Coding The value of context in understanding human behaviour cannot be overestimated. On one hand, context plays an important part in activity coding (Harvey & Spinney, 2000). On the other, it can be important for understanding behaviour (Harvey & Royal, 2000). An activity-based approach provides the opportunity to bring context into travel analysis and modeling. While trip analysis has not been totally oblivious to the value of context, its contextual focus has been much narrower than is required. Peak vs. non-peak travel, travel mode, origin-destination, parallel activities, and travelling companions have all played more or less important roles in the trip paradigm. However, these all fail to capture what is the essence of the activity approach, which is the focus on the tapestry of activities and relationships that generate activities and the demand for travel. While many of the contextual elements have been examined as concomitants of trips there has been little analysis of their contributory effect on travel. Both trip and activity studies contain contextual elements that should be merged into a more integrated approach to travel analysis. Contextual variables take two forms. They may be situationally determined or activity determined (Harvey & Royal, 2000). Situationally determined variables are those that apply to all activities. Activities are performed alone or possibly in conjunction with other activities such as eating and watching TV. Also, every activity occurs at a location and every activity occurs with some degree of social contact, albeit zero if done alone (see Figure 7). In contrast, activity-determined context is unique to given activities. Hence, travel has at minimum a purpose and a mode. It may also have other contextual dimensions. Indeed, trip diaries collect a number of additional activity-determined dimensions such as cost, route, and parking details. Therefore, travel activities present no special problem for activity surveys.
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Situationally Determined Context Location Home Elsewhere
Secondary Activity Conversation Read
Travel
Purpose : Work Shop Leisure Other
Type: Professional Text
Car Other
Alone With Others
TV
Read Book
Mode Walk
With whom
Sports/music
Drama Sports News Other
Activity Determined Context Sub-context
Source: Derived from Harvey and Royal (2000).
Figure 7 – Classification of Contextual Variables
3.4 Time Episodes take place in time, and time has many dimensions. They include, among many others, temporal location (timing), sequence, and duration. Subject to economic, social, and political forces, time both impels and constrains human behaviour. Time-diary analysis recognizes this by capturing behaviour as a flow of episodes that generates a continuing stream of human behaviour with timing, duration, and sequencing characteristics. Populations and sub-populations are subsumed in time and space and must constantly function within them (see Figure 8). One should be able to enter the cycle depicted at any point and determine the behaviour of the population in relation to the existing temporal-spatial structure. All the players are on the stage. What needs to be determined is the mix between script and improve that is between what is determined and what is by choice. In contrast, most travel analysis that has been carried has generated either a discontinuous flow of episodes that focus only on certain aspects of behaviour, e.g., travel or out-of-home activities, or a continuous but aggregated flow lacking sufficient detail to understand the juxtaposition of travel and non-travel activities. As noted in an earlier study, “A major difference between the activitybased approach to travel demand analysis and that of the original, trip-based paradigm of travel demand is the way in which time is conceptualized and treated” (Pas & Harvey, 1997, p. 318). In the trip paradigm, time is considered primarily as duration or as timing with respect to peak vs. non17
peak travel. While trip studies primarily focus on time as duration, activity studies recognize the greater complexity of time in terms of both sequencing and scheduling; hence, behaviour is recorded as a continuing flow.
Source: Procos and Harvey, 1977
Figure 8 – Multi-directionality of Behaviour
There are, however, other ways in which time is important. Time can either impede or promote travel from the point of view of timing, sequencing, and scheduling rather than simply being a cost of travel. From the supply side, the timing/scheduling of work/shopping/service hours have a profound affect on the level and nature of travel. Additionally, activity and travel sequencing may also play an important role in travel demand. Activity scheduling contributes to maximizing utility. As such, it must encompass not only dynamics within the day, but also day-to-day, weekly, and longer-term dynamics. While past behaviour may provide clues to, or help shape, current behaviour there is little doubt that future behaviour, at times, also plays a significant role in determining current behaviour. While there are other explanations, the time-space prism of Hagestrand clearly illustrates this point. In the face of a given obligatory event, the action space of an individual is constrained by location and travel resources to engage in activities within a time-space prism that allows for those activities. If facilities for a desired activity are beyond reach from the individual’s location, another activity will supplant that which was unattainable. If the unattained activity is sufficiently important that it must be within an achievable range, an action will be forthcoming to make it so. The individual may move or obtain transport that makes it possible. Based on the foregoing the important dimensions of activity context are secondary activities, location, social contact (with whom), for whom, and time. The following sections explore these dimensions in relation to travel.
3.4.1 SECONDARY ACTIVITIES Understanding any activity means knowing whether or not it excludes or includes other activities. By performing a given activity, is an individual, due to activity requirements or context, prevented from carrying out any or all other activities? Or does the given activity provide an opportunity or 18
impetus to engage in other activities? Different activities give rise to differing combinations of activities. This can be seen in Table 6, which shows activities co-occurring with different modes of travel. First, it is clear that people who are walking are the least likely to be doing something else at the same time. Over half, (56 percent), of Nova Scotia teachers reporting two days of activities reported no secondary activity while walking. People driving or riding in cars as passengers were more likely to be combining the trip with another activity. Only 38.6 and 31.3 percent respectively reported no secondary activity. In fact, automobile passengers were more likely to be engaged in some form of communication than to be doing nothing else. Will the increased ability to communicate while travelling engender more travel? How will legislation prohibiting the use of cell phones in automobiles affect travel? Table 6 -- Trips by Mode and Secondary Activity, Nova Scotia Teachers, 1999 Number of Trips
Percent of Trips
Cumulative Percent of Trips
Walking No Secondary Activity Reported Talking, Conversation, Telephone Listening to the Radio Relaxing, Thinking, Resting, Smoking Gardening and Pet Care Listening to CD's, Cassette Tapes, or Records Pleasure Drives/Sightseeing/Other Sport or Active Leisure Groceries and Other Regular Shopping Help/Teach/Reprimand/Reading/Play with Children Socializing with Friends / Relatives
244 50 28 20 17 15 14 13 11 7
56.0% 11.5% 6.4% 4.6% 3.9% 3.4% 3.2% 3.0% 2.5% 1.6%
56.0% 67.4% 73.9% 78.4% 82.3% 85.8% 89.0% 92.0% 94.5% 96.1%
Car Driver No Secondary Activity Reported Listening to the Radio Talking, Conversation, Telephone Listening to CDs, Cassette Tapes, or Records Help/Teach/Reprimand/Reading/Play with Children Relaxing, Thinking, Resting, Smoking Meals / Snacks / Coffee
2357 2263 576 306 172 69 54
38.6% 37.1% 9.4% 5.0% 2.8% 1.1% 0.9%
38.6% 75.7% 85.2% 90.2% 93.0% 94.1% 95.0%
Car Passenger Talking, Conversation, Telephone No Secondary Activity Reported Listening to the Radio Help/Teach/Reprimand/Reading/Play with Children Socializing with Friends / Relatives Listening to CD's, Cassette Tapes, or Records Marking, Grading Relaxing, Thinking, Resting, Smoking
530 393 168 30 27 21 21 15
42.2% 31.3% 13.4% 2.4% 2.1% 1.7% 1.7% 1.2%
42.2% 73.5% 86.9% 89.3% 91.4% 93.1% 94.7% 95.9%
Source: NS Teachers Time-Use Study, Saint Mary’s University Time-use Research Program
3.4.2 LOCATION OF ACTIVITIES Most activity diary surveys capture some form of activity location or attempt to derive it from the reported data. Almost without exception, it is captured generically in some form, shown in Table 7.
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Table 7 - Location of Activity, Halifax 1971-72, 1981; Canada 1981, 1992 and Finland 1986-87 Location of Activity
Halifax 1971* (%) 60.6
Halifax 1981** (%) 57.0
Canada 1981** (%) 58.7
Canada Canada Finland 1992** 1998** 1986/87*** (%) (%) (%) 61.5 61.2 65.8 1.6 7.6 7.4 5.8
At home At summer cottage Workplace 10.3 7.1 7.5 Own garden, in front of the door 0.5 In somebody else's dwelling 2.7 4.2 4.1 2.7 5.2 Outdoors, streets/squares/public gardens 0.9 In building for goods and services 4.9 6.0 5.9 Establishment for leisure - indoors 0.7 0.8 0.9 Establishment for leisure - outdoors 0.1 0.3 0.3 Eating and drinking locals 0.8 1.4 1.3 Other and no answer 1.1 0.8 0.6 13.2 10.0 9.1 Travel by walk 6.1 6.2 5.0 2.7 2.8 2.9 Travel by bus, trolley ,bus ,tram 0.6 0.9 0.7 1.2 Travel by car 10.3 13.5 13.2 13.9 14.8 6.4 Travel by ship, ferry-boat 0.1 * Travel by other means 0.3 0.7 0.9 1.1 1.0 1.1 Waiting in transit 1.1 0.9 Total 100.0 100.0 100.0 100.0 100.0 100.0 Source: Derived from DOMA Study 1971 , Canadian Time Use Pilot Study 1981, Statistics Finland Time Use Survey 1986/87 and Statistics Canada General Social Survey, 1992. * location captured generically and on a UTM grid, ** generic location captured, *** location derived from activities
Table 7 shows locations captured by three different approaches. The only survey to provide actual spatial coordinates was the 1971 DOMA study. It also captured generic descriptions and/or business names and derived the coordinates using lookup table of land uses and businesses. With generic coding, as used in the other Canadian studies, and, in fact, in most time-use surveys, respondents report the nature of the location visited, and, when travelling, the mode of travel used. Location in the Finnish study is not captured in the diary. Instead, respondents are asked where they are when the diary begins, and travel and activities are used to derive location. In general, the values for Finland are not wildly different from those for Canada. However, their very low proportion of car travel seems out of line with the other sites, particularly since they have above-average km of car traffic per head (7000km in comparison with 18 other countries, including the U.S. and European countries, which average 6000km). (National Road Traffic Forecasts, 1997). Axhausen (1995) indicates that while detailed addresses are asked in local surveys, at the national/regional scale a crude location indicator in conjunction with a travel distance or odometer reading, is usually obtained. It is argued that while street address is normally used to capture location, it may be better to try to capture the highest level of precision the respondent can reliably provide. This information can then be used to determine location (Axhausen, 1995). The approach used in the DOMA time-space study complies with that recommended by Axhausen. Respondents in that study were asked to report their location by name of building, business, street address, or nearest intersection. These were then coded onto a UTM grid on a 1/10th of a kilometre grid. The UTM considerably enhanced analysis opportunities in relation to the opportunities 20
provided by generic location coding. In addition to travel duration, it is also possible to gain a rough estimate of distance, speed, and direction of travel. In addition, travel may be examined in relation to both actual and potential destinations that can be generically coded and related to activities actually undertaken. Overlaying a mapping of home and work locations with a map of other activity locations provides insight into the spatial organization of activities. Travel researchers are interested in the extent to which activities occur in or out, (away from) home. Typically, travel instruments pre-categorize those activities expected to occur away from home, and, even more frequently, ignore altogether activities occurring at home. Time-diaries, even with only generic spatial coding, provide insight into the in/out of home orientation of activities. At an aggregate level, all types of activities are carried out both at home and away from home. The least likely activities to be undertaken at home are paid work and shopping (see Table 8). However, they are also the activities currently thought to be subject to the greatest change in spatial orientation. Media engagement, housework, and personal care predominantly, but not exclusively, occur at home. Hence, one can consider paid work, shopping/services, media, housework, and personal care locationally anchored. On the other hand, activities such as organizational/volunteer engagement, social/entertainment and games/crafts/hobbies are likely to occur in a broad range of locations and are therefore hard to categorize. It is little wonder that travel studies have focused on work and shopping/services. They tend to present the fewest measurement problems, partially because of the fairly well defined and constant motivation for engaging in them. In contrast, engagement in more discretionary, footloose, activities is harder to understand and explain, and yet constitute the request proportion of trips. Table 8 -- Where are Activities Carried Out? Canada 1998
Paid work Housework Childcare Shopping/Services Personal Education Organizations/Volunteer Social/Attendance Games/Crafts/Hobbies Media Group Total
Percentage Distribution of Activities over Locations Work Other Other Home Car Walk place home place 5.4 56.8 0.5 4.0 27.0 3.5 95.4 0.1 1.6 2.3 0.5 0.1 62.1 0.1 1.1 4.7 28.0 3.5 1.2 0.1 0.4 39.1 48.2 9.0 89.7 0.2 1.4 4.6 3.2 0.8 17.5 0.8 1.5 52.9 10.6 9.1 13.2 1.1 7.1 22.0 48.5 6.7 22.1 0.2 20.3 12.5 34.7 8.3 32.4 0.3 1.6 34.4 25.5 4.0 96.9 0.1 1.7 0.8 0.4 0.1 61.2 7.4 2.7 10.0 14.8 2.8
Other travel 2.8 0 0.5 2.0 0.1 7.6 1.4 1.9 1.9 0 1.0
Group Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Source: Derived from Canada General Social Survey 1998
Another way of looking at the relationship between activities and location is to explore the range of activities occurring at a given location. The most restrictive location with respect to activity involvement appears to be the workplace (see Table 9). However, that may be because in traditional time-use studies, respondents are asked only to indicate when they start work and when they end work: they are not asked for detail. This may have the effect of obscuring other activities, such as socializing, conversing, and viewing or listening to media during the work time. Others’ homes appear to provide a richer range of activity than does one’s own home. The top three activities in
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one’s own home, the dominant of which is personal care (46.1%), account for 88% of all activities performed there. In contrast, in others’ homes where social/entertainment dominates (52.6%), the top three activities account for only 77.9% of all activities (Table 9). Table 9 - What Activities are performed at which Locations? Canada 1998 Percentage Distribution of Activities by Location Home Paid work Housework Childcare Shopping/Services Personal Education Organizations/Volunteer Social/Attendance Games/Crafts/Hobbies Media Group Total
1.1 23.7 4.8 0.2 46.1 0.7 0.5 2.6 2.1 18.2 100.0
Work place 98.0 0.1 0 0.1 0.7 0.3 0.3 0.2 0.2 0.1 100.0
Other home 2.2 8.8 2.0 1.3 16.5 1.3 5.6 52.6 2.4 7.2 100.0
Other Car place 5.1 23.4 3.6 0.5 2.2 8.9 33.4 27.7 14.4 6.9 13.0 1.7 4.7 7.0 8.9 16.7 13.7 6.8 0.9 0.3 100.0 100.0
Walk 16.3 0.7 5.9 27.6 9.2 8.0 5.2 21.2 5.6 0.4 100.0
Other travel 35.2 0.5 2.2 16.9 3.4 18.2 2.9 13.4 7.3 0.1 100.0
Group Total 12.9 15.2 4.7 8.5 31.5 2.4 2.2 7.1 4.0 11.5 100.0
Source: Derived from Canada General Social Survey 1998
In many cases, spatial location also has an impact on the time allocated to specific activities. Hence, the duration of time allocated to social/attendance activities is much lower at home (65 mins.) than in another’s home (112 mins.) or in another place (126 mins.). This is also true for organization/volunteer activities (see Table 10). In contrast, episodes of paid work or education are essentially the same in all locations. Table 10 - How Long is Spent Performing Activities in Different Location? Home Paid work Housework Childcare Shopping/Services Personal Education Organizations/Volunteer Social/Attendance Games/Crafts/Hobbies Media Group Total
113 39 37 50 101 112 65 67 82 76 77
Work place 117 41 22 76 59 115 90 64 72 41 116
Minutes Spent by Activity and Location Other Other Other Car Walk home place travel 119 109 24 11 46 48 40 24 13 35 31 49 17 12 29 42 45 15 11 33 139 77 17 10 31 112 78 21 14 38 109 97 20 9 48 112 126 22 11 38 111 91 38 15 108 85 62 24 23 231 106 73 21 11 45
Group Total 86 39 31 27 97 70 50 63 72 76 70
Source: Derived from Canada General Social Survey 1998
3.4.3 WITH WHOM Social contact is another important element of activity context and, together with social space, can provide insight into travel behaviour, (see Table 11). Virtually all time-use studies collect information on whom activities are done with. Activities undertaken alone, with family, or with colleagues or non-family individuals take on differing meanings and usually involve differing locations. Hence, the most time spent with others is spent with work colleagues (Harvey & Taylor, 22
2000). From a modelling or policy perspective, this reality must be factored into any discussion about alteration of work patterns, such as telecommuting. One recent study identified 30 different classifications of with whom, including some which are overlapping or repetitive, among six timeuse studies (Harvey & Royal, 2000).
Sweden 1991 Norway 1990 Canada 1992 Canada 1986 Canada 1981
Table 11 -- The Dimensions of the Social Environment (Percentage allocation of total time) Social Circle Alone Family Others & Multiple Total Canada 1981 Alone Family Others & Multiple Total Canada 1986 Alone Family Others & Multiple Total Canada 1992 Alone Family Others & Multiple Total Norway 1990 Alone Family Others & Multiple Total Sweden 1990
Home 22.9 28.1 1.1
Workplace 3.6 0.6 14.8
Social Space Community 2.4 12.1 4.2
52.1
19.1
18.7
10.2
100.0
28.1 22.9 3.5
1.7 0.3 12.6
2.7 4.7 11.5
5.7 3.4 2.9
38.3 31.3 30.5
54.5
14.7
18.9
11.9
100.0
31.2 19.9 3.8
3.1 0.4 14.5
3.4 5.2 11.1
3.5 2.5 1.4
41.2 27.9 30.9
54.8
18.1
19.7
7.4
100.0
21.9 26.1 4.1
7.4 0.6 13.4
3.3 6.2 9.4
3.2 2.6 1.8
35.8 35.6 28.6
52.2
21.4
18.9
7.5
100.0
21.2 26.5 5.8
5.2 0.4 18.7
2.7 2.2 9.4
3.7 1.9 2.3
32.7 31.0 36.3
53.5
24.3
14.3
7.9
100.0
Transit 4.4 4.8 0.9
Total 33.4 45.6 21.0
Source: Harvey and Taylor (2000).
Clearly, such a broad range is untenable. Travel researchers need to identify the categories of social contact that are meaningful for travel measurement and analysis. One simple classification in terms of self, family, and others, as incorporated in Table 11, has proven useful (Harvey & Taylor, 2000). Undoubtedly, other less aggregated possibilities exist.
3.4.4 FOR WHOM For whom an activity is done has surfaced recently in time-diary studies as a significant contextual variable (Harvey & Spinney, 2000). Its role in travel behaviour can be seen in Table 12. As travel mode changes from walking, to car driver, to car passenger, the extent to which the trip is for oneself diminishes from 73 to 66 to 58 percent respectively, and the extent to which it is for one’s family increases. Six to seven percent of car trips are for people other than self and family. Clearly, these findings illustrate the need to explore interpersonal/family behaviour if attempts are to be made to model it as suggested by Jones et al (1985). It would appear that some travel decisions maybe imposed by others. If so, such behaviour needs to be understood and built into any modeling process.
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Table 12 -- Table Trips by Mode and Motivation, Nova Scotia Teachers, 1999 Walking Number Percent
For Whom
Car Driver Number Percent
Car Passenger Number Percent
Self 319 73.2 4013 65.8 731 58.2 Students/Administrators 5 1.1 176 2.9 41 3.3 Family 33 7.6 1116 18.3 258 20.5 Others 1 .2 215 3.5 226 3.8 Not reported 78 17.9 581 9.5 179 14.3 Total 436 100.0 6101 100.0 1256 100.0 Source: NS Teachers Time-Use Study, Saint Mary’s University Time-use Research Program
4. TECHNOLOGY Technology brings about both spatial and temporal reorganization (Harvey, 1982). Transport technology, walkmans, VCRs, ATMs, internet, laptops, web banking and shopping, remote access software, PDAs, cell phones, wireless internet and many more technologies have altered the way many people work and live. For example as shown in Figure 9, certain technologies like e-mail set people free in both time and space. In contrast, phone conservations or teleconferences require at least temporal coincidence. Technology helps remove constraints on behaviour and communication but also imposes limits. We have yet to fully understand the actual effects of these technologies on daily behaviour, and yet, until we do, it will be difficult- if not impossible-to realistically model or simulate travel behaviour. To date, little attention has been paid to the capture of technology in time-diary studies except in the case of travel, where mode has typically been captured. In view of the impact technology can have, it is essential that the effect of technology be considered more extensively in diary studies than it has been in the past. Spatial coincidence of communicating parties Required YES Face-to-face meeting A Temporal coincidence
YES
of communicating Refrigerator notes C Hospital charts
parties NO required
NO Picture phone B Phone(wire/cell/satellite) Teleconference (audio or audio-visual) Radio - CB/HAM/VHF Net phone Instant messaging Cuseeme Answering and recording machines Mail/E-mail Telegrams, telex, fax Printed publications Computer conferencing Source: Harvey and McNutt (2000).
Figure 9 – Spatial and Temporal Constraints on Communications
5. TIME-SPACE STUDIES The development of time-diary methodology has made possible the capture of time-use information by means of a broad array of instruments. National statistical offices are moving to collect more and 24
more time-use data. In the past, however, virtually all time-use studies have failed to adequately capture spatial detail. In contrast, travel studies have typically captured good spatial data, which has then been extensively underutilized. At the same time, travel studies have not captured sufficient activity detail to allow for adequate analysis of the relationships among activities, times, and locations. Experience indicates grave shortcomings in our ability to model and simulate behaviour. I would argue that these shortcomings are not owing to the unpredictable nature of human behaviour or even to a lack of knowledge about decision processes. Rather, I believe they result from our failure to capture simultaneously the essential elements shaping behaviour. There is clear evidence of the relationships among time, space, and activities based on the analysis of time-space data collected to date. DOMA study data showed that among household tasks, caring activities took place closer to home than any of the other tasks (Elliott & Clark, 1975). Religion was very much a neighbourhood activity, registering the shortest average distance from home at 1.97 km. Activities requiring specialized facilities tended to occur somewhat further from home, with medical care registering the longest distance at 5.75 km (Elliott & Clark, 1975). Beyond such findings, the analysis showed a complex relationship between distance travelled, duration, and particular activities. Therefore, there is much to explore. Other DOMA based research has also shown that space-time data can be used to describe diurnal changes in the urban social structure (Goodchild & Janelle, 1984). The research illustrated the need to “reevaluate current theoretical views about urban-structure and to consider how refinements in this type of analysis might be directly applicable in both private and public decision making” (Goodchild & Janelle, 1984, p. 818). Further research showed the strongest space-time differentiation between home and work-oriented activities and identified entertainment and shopping as strong space-time dimensions (Goodchild, Klinkenberg & Janelle, 1993). Several findings based on the DOMA space-time data are more directly relevant to travel behaviour. For example, measures of space-time autonomy relating to fragmentation of the day (block-time) and transport capability (trip-speed) showed inequalities between men and women (Janelle & Goodchild, 1983). However, life-cycle classifications suggested that the inequalities were related to societal roles. In measures developed in analysis, trip speed and length of trips combined to represent transport capability, while physical accessibility and duration of discretionary time appeared as separate dimensions ((Janelle & Goodchild, 1983). Statements gleaned from the work of Goodchild, Janelle and Klinkenberg provide strong support for the efficacy of space-time data. "An inescapable conclusion … is that the urban socioeconomic systems are more complex than most of the urban-social-ecological literature would suggest (Janelle & Goodchild, 1983, p. 424). They argue that "The availability of large-scale space-time diary data sets … represents an opportunity for closing an important gap in our understanding of the human geography of cities (Janelle & Goodchild, 1983, p.424). Using the Halifax data they observed that even given the complexity of individual travel behaviour "the flexibility of space-time diary data may allow for a systematic search for behavioural constants (Janelle, Goodchild & Klinkenberg, 1988, p.905). In their most recent work they concluded that "The methods developed [using space-time 25
data]…hold promise for useful inputs into decisions about urban transport systems and about individual transportation behaviour (Janelle, Klinkenberg & Goodchild, 1998, p.136). Time-space diaries incorporating cardinal measures of both time and space offer travel researchers great flexibility and almost limitless analysis opportunities. Given technological advances in spatial measurement (e.g., GPS) and improved opportunities for the real-time capture of activities using PDAs, cell phones, or other respondent-friendly technologies, collection and machine capture of time-space data can become convenient, affordable, and reliable.
6. MORE TRIPS from TIME DIARIES? Even without an explicit spatial dimension time-diaries appear to better capture trips. The c wisdom is that time diaries generate more trips per person than are generated by the traditional trip diary. Indeed, one of the major reasons for turning to the time-diary is to capture more trips on the assumption that the higher number is more accurate. This argument has support. Jones et al. (1983) found that their activity survey identified 4.37 trips per person compared to 3.86 for their trip diary, a difference of .51 trips. They further noted that the difference came in discretionary trips. Additionally, Vilhelmson (1997) compared trip generation in Sweden for the population aged 20-54 using the both travel and time-use survey data. He found an average of 4.3 tips per person using the time diary data (TUS) and 4.0 using the travel survey data (NTS). Additionally, he found an average of 91 minutes of travel time with TUS and 79 minutes with the NTS. He argues that the NTS survey excludes a number of short but time-consuming trips. (Vilhelmson, 1997). More recently, Stopher and Wilmot (2000) report an average of 4.17 trips per person using the diary shown in Figure 3. This is in line with typical time-diary results. Examining trips rates from a meta-analysis of trip and time diaries provides further insight. Based on Purvis (1994) it was calculated that average person trips measured by utilizing trip diaries, averaged over a variety of 22 US cities ranging from 1960 to 1991, was 2.8 trips per person per day. The similar figure averaged over 10 national time-use surveys was 4.3 person trips per day. At the .05 level of significance, there is a significant difference between the two averages. The highest average number of trips for a trip diary reported by Purvis was 4.04. Admittedly, given the variety methods and populations used across the studies, such a comparison is questionable. The fact that the trip diaries are urban-based while the time-diaries are nationally based lends additional support to the expectation that time-diaries do, in fact, capture more trips. A recent experiment testing alternative diary formats, a stage based diary, a time based diary and a combination of the two produced somewhat different results (Arentze, 2001). It found mean trips per person day highest for a stage-based diary and equal for time based and combination diaries. The study concluded that the combination diary had clear theoretical advantages (Arentze, 2001).. However, the registered gains may simply be the result of accurate reports of location changes generated by trip stages. This should be explored.
7. Alternate Diary Advantages
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The foregoing, as promised in the introduction, concentrated on the time use and time-space approaches to the collection of activity and trip data. Each promises to provide more accurate and useful data than is determined by traditional trip diaries. Some of the advantages of each follow.
7.1 Advantages of the Time-diary Approach Time diary studies provide for a more accurate measure of trips: As shown above, it appears that time-diaries capture more trips. Additionally, they appear to capture a different kind of trip, specifically shorter, and non-work/shop trips. Beyond these benefits the time-diary approach also provides for. 1. Study of the significance of parallel activities: The ability to carry out parallel activities undoubtedly affects behavior. We need to know how this impacts on travel. 2. Study of substitution of activities among generic locations: Since all activities are captured in a time diary, it is possible to explore the extent to which activities are locationally fixed or unrestricted. If activities are pre-allocated to locations (e.g., work to a workplace), considerable information is lost and results are distorted. One needs to know the division of episodes of a given activity among generic locations in order to explore activity and location substitutions. 3. Study of time allocation related to generic locations: Time allocation to particular activities varies depending on where they are carried out. 4. Study of time allocation related to social contact: With whom activities are carried out impacts on individual behavior.
7.2 Advantages of Time-space Approach In addition to the above, time-space diaries provide for the following. 1. Study of key destinations: In the Halifax study, as a check on the results, work arrivals at Dalhousie University were estimated. This figure was then compared with a staff total given by the university. The two estimates appeared reasonably close. Similarly, it was possible to study shopping centre arrivals. Being able to identify who uses shopping centres made possible a subsequent study of the variety of characteristics of the users, for example, demographic characteristics, speed and direction of travel, time spent on daily activities and with media. 2. Calculation of distance, speed and direction of travel: With all activities spatially coded, in the time-space diary, it is possible to estimate travel distance and determine the direction of travel. With the travel time given, it is also possible to estimate speed.
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3. Study substitution of activities among geographic locations: As in the case of generic locations, it is important to know the division of time allocated to a given activity among alternative geographical locations. 4. Identification of the diurnal cycle of spaces: The significance of the diurnal cycle of spaces is highlighted in Lynch’s delightful treatise What Time is This Place? (Lynch, 1972). The character of neighbourhoods and public spaces changes constantly throughout the day. Timespace diaries show what is happening at each location at any time in the day. Goodchild & Janelle (1984) vividly describe such changes using Halifax DOMA time-space data. In addition to identifying the changes occurring in the CBD, they identified particular spatial-temporal patterns by hospitals, military establishments, and universities. As the day progresses, some areas maintain their levels of activity while others wax and wane. The nature of these changes is well identified by time-space data. 5. Identification of the spatial dimension of activities: The rich activity data captured in timespace studies, along with the spatial detail, facilitates identification of the time-space “structure” of activities. For example, in Halifax, religious participation occurred, on average, closer to home (1.97 miles) than any other of 15 activities examined (Elliott & Clark, 1975). Using variance measures as well as central tendency measures it is possible to explore, also, the dispersion of activities.
8. FUTURE DIRECTIONS Travel research has come a long way. It has developed instruments fully capable of capturing much of the information required for meaningful spatial and transportation analysis. Unfortunately, the expertise and the adoption of state of the art capture are severely limited on two fronts. First, the collection of appropriate activity detail over the day has not yet sufficiently infiltrated travel data collection. Second, spatial data captured is greatly underutilized. If spatial locations were captured and coded on a UTM or comparable grid system, the transport data collected would be far more useful. Finally time cannot be considered independent of location nor location independent of time. Hence, travel researchers, at the very least, must move to a time-based data collection approach. The questions facing travel research are threefold. Does it maintain its traditional collection approach? Does it attempt to fine tune the traditional approach toward a better treatment of activities, a task pretty well accomplished? Or does it move to combine travel and activity researchers skills, building on the strengths of each in collecting meaningful data that facilitates interrelated and/or integrated analysis of behaviour? In short does it seek to capture and fully use time-space diary information. I argue for the latter approach.
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8. REFERENCES Axhausen, K.W. (1995). Travel diaries: an annotated catalog (2nd ed.) Innsbruck: Institut fur StraBenbau and Verkehrsplanung, Leopold-Franzens-Universitat. Elliott, D.H. & Clark, S. (1975). The spatial context of urban activities: Some theoretical, methodological and policy considerations. In Michelson, W. (Ed.), Public Policy in Temporal Perspective. The Hague: Mouton, 1979. Engelke L.J. (Ed.) (1997). Travel model improvement program, Activity-Based Travel Forecasting Conference June 2-5, 1996. Proceedings Summary, Recommendations and Compendium of Papers. . Ettema D., Timmermans H. & Leo van Veghel (1996). Effects of data collection methods in travel and activity research. Rotterdam: European Institute of Retailing and Services Studies. Goodchild, M. F., Klinkenberg, B., & Janelle, D. G. (1993). A factorial model of aggregate spatiotemporal behaviour: Application to the diurnal cycle. Geographical Analysis, 25(4 }, 277294. Goodchild, M.F. & Janelle, D.G. (1984). The city around the clock: space-time patterns of urban ecological structure. Environment and planning A, 16, 807-820. Goodchild, M.F., Klinkenberg B., & Janelle, D.G. (1983). Geographical Analysis 25(4), 277-294. Goulias K.G. (1996) Activity-based travel forecasting: What are some issues? Activity-Based Travel Forecasting Conference Proceedings Goulias, K. G. (1997). Syrveys using multiple approaches. Presented at the International Conference on Transport Survey Quality and innovation, Grainau, Germany, May 24-30, 1997 Gronmo S. & Harvey, A.S. (1982). Time-diaries and trip-diaries A comparison. Paper presented at the 10th World Congress of Sociology, Mexico City, August 16-21, 1982. Harvey, A.S. & Taylor, M. (2000). Activity settings and travel behavior: A social contact perspective. Transportation, Vol. No. 27:1. Harvey, A.S. & Royal, M. (2000). Use of context in time-use research. Paper prepared for Time-use Workshop, United Nations Statistical Office, New York. Harvey, A.S. & Spinney, J.E.L. (2000). Activity and contextual codes: Implications for time-use coding schemes. Paper presented to International Association for Time-use Research, Belo Horizonte, Brazil, June 7-9. Harvey, A.S., Holler, B., Spinney, J. & Arsenault, E. (1999). Flexibility and mobility. A report prepared for The Netherlands Ministry of Transport, Public Works an Water Management, Flexibility and Mobility. Halifax: Time-use Research Program, Saint Mary’s University. Harvey, A.S. (1997). From Activities to Activity Settings. In Dick Ettema & Harry Timmermans. Activity-based approaches to travel analysis. Tarrytown, New York: Pergamon, (1997). pp. 209228. 29
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Pas, E.I. (1996). Recent advances in activity-based travel demand modeling. Activity-based travel forecasting conference proceedings. http://www.bts.gov/trnip/Papers/trnip/abtUpas.htm Pendyala, R.M. and Pas, E.I. (1996). Activity-based travel forecasting conference proceedings, summary of workshop 2: Models of activity engagement and behavior. http://www.bts.gov/tniip/papers/tmip/abtf/pendyala.htm Purvis, C.L. (1994). Changes in regional travel characteristics and travel time expenditures in the San Francisco Bay Area: 1960-1990. Paper submitted to the Transportation Research Board for Presentation at the 73rd Annual Meeting January 9-13, 1994 Washington, D.C. Rydenstam, K. (1993). Notes on Swedish time-use Survey 1990/91. Stopher, P.R. (1992). Use of an activity-based diary to collect household travel data. Transportation, 19 (2) 159-176. Stopher P.R. (2000). Allocation of time to activities and household members: Results from four urban areas. Paper presented to the 9th International Association for Travel Behaviour Research Conference, Gold Coast, Queensland, Australia. Stopher, P.R. and Wilmot, C.G. (2000). Prototype time-use diary and application in Baton Rouge, Louisiana. Paper presented to the 9th International Association for Travel Behaviour Research Conference, Gold Coast, Queensland, Australia. Szalai, A. (1972). The use of time. The Hague: Mouton. van der Hoorn, A.I.J.M. (1983). An empirical model of travel and activity choice:A case study for the Netherlands. Ph.D. thesis presented to the University of Amsterdam. Vilhelmson, B. (1997). On travel in time use surveys: A comparison with other approaches. Draft paper tabled at the XIX Conference of the International Association for Time-Use Research (IATUR). Stockholm Sweden, October 8-10, 1997. Von Rosenbladt (1972). The outdoor activity system in an Urban Environment. In Szalai, A. The use of time. pp. 335-355. The Hague: Mouton.
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