(Chapter Title on Righthand Pages) 1

8th International Conference on Survey Methods in Transport Annecy, France - 25-31 May, 2008

Comparing GPS and Non-GPS Survey Methods for Collecting Urban Goods and Service Movements

Stephanie McCabe, University of Toronto, Toronto, Canada Matthew Roorda, University of Toronto, Toronto, Canada Helen Kwan, University of Toronto, Toronto, Canada

ABSTRACT

This paper describes results of the Region of Peel Commercial Vehicle Survey, a pilot data collection effort that collected commodity, mode choice, and commercial vehicle movement data from a sample of approximately 600 shippers and a sample of their drivers, in the Region of Peel, located just west of the City of Toronto, Canada. Two survey techniques are tested, including a mail-out/ mail-back survey and a mail-out/ mail-back survey with a GPS- supplement.

This paper describes the survey method, the results and the methodological lessons learned in the urban goods movement study. A comparison of survey implementation results for the two types of surveys are provided, including overall survey response rates and item non-response. Analysis of the quality of shipper, driver and GPS portions of the data are outlined with checks for consistency. Comparisons of commercial vehicle tour behaviour and stop location and time as reported in the paper survey forms and as recorded in the GPS units are made for an evaluation of the effectiveness of the GPS in identifying stops, and the potential of GPS as a passive replacement for more traditional paper and pencil survey methods. Specific and practical methodological lessons learned are also provided. INTRODUCTION

Canada has a well-developed transportation system for moving people and freight. Yet the use of that transportation system is not well understood, particularly in urban areas such as the Greater Golden Horseshoe (GGH) (which includes the Greater Toronto Area, and extends through Niagara Region to the US border). There is a need to build a balanced freight and personal transport analysis capability to assess “sustainability” impacts of urban land use and economic policies and to guide investment in transportation infrastructure such as highways, and intermodal facilities. Places to Grow, the growth plan for the GGH, emphasizes the need for strategic improvements in transportation infrastructure to facilitate goods movement, and the development of economic corridors designed to link to inter-modal transport infrastructure and to avoid impacts on natural systems (Ontario, 2006). The plan recognizes that: (a) a prosperous urban economy requires the efficient movement of goods and is sensitive to the time and energy costs associated with traffic congestion, and (b) within urban areas, freight transport must also be controlled to improve road safety, air quality, noise and other impacts on city residents. Currently, models available for urban freight transport are not sufficient to assess impacts of transport investments and land development toward meeting these goals. One of the key reasons for this is the lack of data describing urban freight movements and firm behaviour. Furthermore, there is insufficient literature describing how such data can be collected most effectively and with the highest quality results.

This paper describes results of the Region of Peel Commercial Vehicle Survey, a pilot data collection effort that collected commodity, mode choice, and commercial vehicle movement data from a sample of approximately 600 shippers and their drivers, in the Region of Peel, located just west of the City of Toronto, Canada. Two survey techniques are tested, including a mail-out/ mail-back survey and a mail-out/ mail-back survey with a GPS-supplement.

The Region of Peel Commercial Vehicle Survey was designed with the following objectives:  Provide shipment, trip, and tour generation data for Peel Region,  Provide information describing the behavioural and economic processes that lead to the shipment of goods and services, and the choice of mode, ultimately resulting in the movement of commercial vehicles.  Be of sufficient scale to provide enough observations for the preliminary estimation of a microsimulation model of the urban freight system for a study area within the GGH,  Allow for a formal statistical comparison of the response rate, respondent burden, cost, and data quality associated with mail-out/mail-back and GPS-supplemented surveys.  Act as the pilot for a large-scale shipper-based survey of commercial vehicle movements envisioned for the GGH.

The survey was conducted over the period from October 2006 to May 2007. The mail-out mail-back component of the Region of Peel Commercial Vehicle Survey was a successful undertaking, with an overall response rate of 25.3% for the shipper component of the survey. A total of 597 completed shipper surveys were obtained, providing detailed information on trip generation rates, firm characteristics, and inbound and outbound shipments. The driver component of the survey is smaller, with a total of 86 returned driver surveys. This lower number was expected because fewer companies were eligible for the driver portion of the survey, which was limited to commercial vehicle drivers that either worked for the shipper firm or regularly returned to the shipper firm.

A sub-sample of 42 GPS surveys were conducted by installing GPS units for 7 days in the vehicles of participating trucks. These units tracked the routes taken, identified stops, and collected engine information including idle time, engine load, rpm, fuel consumption, and the incidence of rapid decelerations.

This paper describes the survey method, the results and the methodological lessons learned in the urban goods movement study. The paper begins with a review of complementary data collection efforts in the GGH and shipper-based surveys in other jurisdictions. The study area is then described and is followed by a description of the survey design. A comparison of survey response for the two types of surveys are provided, including overall survey response rates, item and form non-response. Analysis of the quality of driver and GPS portions of the data are outlined by making comparisons of commercial vehicle tour behaviour and stop location and time as reported in the paper survey forms and as recorded in the GPS units. These comparisons allow for an evaluation of the effectiveness of the GPS in identifying stops, and the potential of GPS as a passive replacement for or supplement to more traditional paper and pencil survey methods. Finally, specific and practical methodological lessons learned are also provided.

REVIEW OF DATA COLLECTION EFFORTS

In the GGH, the best and most comprehensive sources of freight data are the Commercial Vehicle Survey (CVS) (MTO, 2001), and the Cordon Count program undertaken by the Data Management Group (DMG, 2002). These data sources are inadequate to model freight movement and firm behaviour in the GGH on municipal roads for a number of reasons. The CVS is a province-wide road-side vehicle survey, conducted at over 150 road-side directional sites in Ontario, 37 sites in the GGH, in which drivers are asked to report on truck activity characteristics related to the: trip, driver, carrier, commodity and vehicle. This survey is successful in the collection of long-haul intercity freight movements to/from and through Ontario, however, the lack of consistent detailed address-level trip information drastically reduces the accuracy of simulation on municipal facilities. It also only captures goods movements by the “truck/highway” mode, so no observations of the mode choice decision are made. Furthermore, in terms of “tour-making” behaviour, the CVS captures a maximum of 2 intermediate points and fails to capture the weight of goods picked up or dropped off at these points.

The Greater Toronto Area Cordon Count program provides counts of truck movements across a series of screenlines every 2-3 years. While geographically more comprehensive than the CVS, it only counts trucks in broad categories, with no observation of origin, destination, load characteristics or trip purpose and lacks 24 hour coverage plus is limited to one work day in one season. Thus it can act as a fair validation tool of an urban freight model, but cannot be used in the development of a behavioural / economic model of urban freight movement.

A shipper-based survey of goods movement is the preferred method to complement the data sources currently available in the GGH, for at least two reasons. First, most decisions that result in goods and service movements, including the number, timing and value of shipments, the destination location of shipments, and the choice of mode (or combination of modes, as in intermodal freight transport) are made, at least in part, by the provider (shipper) of those goods and services. To understand how those decisions are made, and how they are affected by economic, logistical, regulatory and transportation considerations it is necessary to survey the shipper, who is the player most closely associated with those decisions. The second reason is a practical one. Commodities that are consumed by a large population of households and firms are often produced in a small number of firms. To capture the flow of specific commodities, it is more efficient to survey the small number of producing firms than the large, diverse set of households and firms that consume the goods.

Shipper-based goods movement surveys have been conducted in a number of jurisdictions as shown in Table 1. The largest of these is the Commodity Flow Survey, undertaken in the US, in which commodity origins and destinations are obtained for approximately 50,000 domestic shippers across the United States. In Calgary (Stefan et al., 2005) and Edmonton (2003), business establishments were contacted to obtain the value and weight of goods shipped and the tour-based trip-diaries of commercial vehicles leaving those firms. Establishment surveys were conducted in Hamburg and in Dresden, Germany, each of which included two elements: a trip diary survey and a business survey that included information about the business, its employees and its vehicle fleet (Wermuth et al., 2004). Shipper-based surveys have also been conducted to obtain opinions from the freight community with regard to freight issues and the need for infrastructure improvements. Such studies have been completed in Baltimore (Louis Berger Group, 2001) and Oregon (Lawson and Strathman, 2002). Response rates of these shipper-based surveys have varied from 36% to over 60% depending on the nature and length of the survey, the method of contact with the respondent, and the quality of execution of the survey.

Yet it is recognized that shippers alone do not have information about all aspects of the movement of goods from their firm. To obtain a more complete picture of the nature of deliveries from a business establishment, it is useful to also obtain information from the drivers of delivery vehicles about the particulars of the truck tours that are undertaken, including stop sequence, stop location, reason for the stop and arrival/departure times. The commodity flow surveys recently undertaken in Calgary (Stefan et al., 2005) and Edmonton (2003) have successfully utilized the joint approach of surveying both the shipper and drivers of commercial vehicles leaving the establishment to obtain both commodity and vehicle movement information. The survey described in this paper builds upon the methods developed in Calgary and Edmonton, by capturing additional behavioural information and by assessing different methods for jointly obtaining information from both actors. Table 1 Recent Shipper-based Freight Surveys Survey Survey Res- Method: Survey type Response Name/location year(s) ponses rate Calgary – 2000 3,000 Mail-out mail-back: not given Commodity commodity flow/tour Flow Survey based trip diary Edmonton 2001 4,300 Mail-out mail-back: not given Commodity commodity flow/tour Flow Survey based trip diary Hamburg 2001 537 Mail-out mail-back: 36% mail-out mail- Establishment survey back and trip diary Hamburg 2001 220 Face-to-face: 40% face-to-face Establishment survey interview and trip diary Dresden 2001 856 Face-to-face: 42% Establishment survey and trip diary USA 1993, 50,000 Mail-out mail-back Census Commodity 1997, with commodity response Flow Survey 2002 flow required by law Baltimore 2001 14 Telephone with mail- 50% out/mail-back: Investigation of freight issues for specific industries Oregon DOT 2001 1,872 Telephone survey: 61% Infrastructure-related problems

STUDY AREA

The study area for the survey was the Region of Peel, a largely suburban region located just west of the City of Toronto. Peel Region has a large manufacturing/warehousing base with an estimated 240 sq. ft. of industrial floorspace per capita (more than double that of the Greater Toronto Area (GTA), Chicago, and other major industrial centres in North America). Peel is also a major Canadian transportation hub, which is served by three rail/truck intermodal terminals, Pearson International Airport and the densest expressway network in the GTA. Provincial highways in Peel region facilitate the movement of 45,000 trucks per day with trip ends or through travel carrying $1.4 billion worth of goods (MTO, 2001).

SURVEY METHOD

Mail-out Mail-back Survey

The Region of Peel Commercial Travel Survey was successfully conducted from October 2006 to May 2007. The mail-out/mail-back (paper-pencil) survey instrument has two main components; a shipper survey and a driver survey. The mail-out/mail-back questionnaire was the same for both the mail-out/mail-back and the GPS supplemented surveys. There are various advantages and disadvantages to the mail-out mail-back method. First, advantages include the relative low cost of mail-out surveys, compared to face-to-face interviews. While face-to-face interviews generally result in higher quality data, mail-out mail-back surveys may sometimes produce more valid responses to certain types of questions where the presence of an interviewer might be inhibiting (Sheatsley, 1983).

There are, however, significant disadvantages to mail surveys. Response rates are generally low, increasing the potential for bias. Less-educated persons may have trouble following the instructions. Similarly, it is not certain that the person to whom the questionnaire is addressed is the one who completes it. It has also been found that paper surveys may not have accurate results because travel is underreported or entire trips are omitted for ease of relaying information (Wolf and Guensler, 2002). Each of these disadvantages can be mitigated with careful survey design and persistent and persuasive recruiting. However, they cannot be eliminated.

Some precedence exists for this survey technique in Calgary (Stefan et al., 2005) and Edmonton (2003). However, response rates for this technique are generally expected to be lower than more resource intensive techniques such as in-person visits or telephone interviews as were applied in the Calgary and Edmonton surveys. Despite this, a self-administered survey was considered to be the best option given the time constraints and low cost of implementation.

The survey process is outline in Figure 1. The same process was used for the mail-out mail- back with and without the GPS unit. However, when a GPS unit was sent to the company, the survey team continued to follow up until the unit was received.

For the Region of Peel Commercial Travel Survey, a knowledgeable representative of the shipper establishment was identified, and was asked to fill out three forms:

 Form A- Establishment Information  Form B- Outbound Commodity Information  Form C- Inbound Commodity Information

The representative of the shipper firm was also asked to provide their driver(s) with a driver survey, which consisted of two forms:

 Form D- Stop Information  Form E- Tour Information Timeline

Recruitment Postcard

1 week after postcard is mailed Recruitment Call

Mail Survey ASAP

Day before Reminder Call Survey Day

on Survey Day Mail Thank-you Postcard

7 business days Follow up Call

12 business days after Survey Day Follow up Call 5 business days

Figure 1 Survey Process The information collected on each of the forms is discussed below.

Form A: Establishment Information (completed by the shipping firm representative) Form A includes establishment information such as number of employees, industry classification and square footage; number and values of annual shipments, trip generation information; and vehicle fleet information.

Forms B and C: Outbound and Inbound Shipments and Services (completed by the shipping firm representative) Forms B and C collected information about every shipment of goods or service provided by the business establishment on the survey day for outbound and inbound shipments, respectively. These Forms were presented in tabular format to the respondents to resemble a shipper manifest. A single row of the tables from Forms B and C are shown in Figures 2a and 2b, respectively.

Is Shipment Name of For Shipments ONLY Address of Destination Shipment or Mode(s) of Transportation or Service Destination for Shipment/Service Service? Please check all mode(s) used Time Commodity Weight Shipment/Service Value of Shipment Commodity Type Sensitive? Please specify Unit

Address/Closest Intersection Shipment Only Passenger Car Air Yes No Food Products Non-Metallic Products Pickup/Cube Van Marine Oil, Gas If Yes: kg Road Vehicles and Parts Service only Single Unit Truck Rail Earliest Arrival tonnes (metric) Wood, Pulp, Paper Manufactured Products Tractor and one Trailer tons (imperial) am ______Cdn $ Textiles Chemical Related : lb Tractor with two or more Trailers pm Metals and Products Mixed If services only, please describe Other Other Latest Arrival If other, please specify Other If other, please specify If other, please specify am : pm City : : : : : : : : : a) Form B – Outbound Commodity Information (one row of the table is shown) Is Shipment For Shipments ONLY Name of Destination Address of Destination Shipment or Mode(s) of Transportation or Service Shipment/Service for Shipment/Service Service? Please check all mode(s) used Time Commodity Weight Value of Shipment Commodity Type Sensitive? Please specify Unit

Address/Closest Intersection Shipment Only Passenger Car Air Yes No Food Products Non-Metallic Products Pickup/Cube Van Marine Oil, Gas If Yes: kg Road Vehicles and Parts Service only Single Unit Truck Rail Earliest Arrival tonnes (metric) Wood, Pulp, Paper Manufactured Products Tractor and one Trailer tons (imperial) am ______Cdn $ Textiles Chemical Related : lb Tractor and two or more Trailers pm Metals and Products Mixed If services only, please describe Other Other Latest Arrival If other, please specify Other If other, please specify If other, please specify am : pm City : : : : : : : : : b) Form C – Inbound Commodity Information (one row of the table is shown) Figure 2 Commodity / Shipment Information (shipper)

Form D: Stop Information (completed by the driver) Form D collects information from the driver describing the vehicle and the stops made on the survey day including stop descriptions, locations, purposes and arrival and departure times. The first page of Form D is shown in Figure 3. The form provided enough space for a total of 14 stops, although drivers were asked to record additional stops on a separate sheet of paper.

Form E: Tour Information (completed by the driver) Form E obtains from the driver of the vehicle more behavioural information describing the characteristics of the tour as a whole such as whether the tour is done routinely. Start Location Stop 1 Stop 2

This is the location where your work day begins. Arrival Time AM Arrival Time AM Time (hours, mins) : PM Time (hours, mins) : PM

Address at beginning of the day Address of Stop Address of Stop Address or nearest intersection Address or nearest intersection Address or nearest intersection

City City City

Vehicle Type Reason for Stop Reason for Stop Passenger Car What did you do at this stop? Please check all that apply. What did you do at this stop? Please check all that apply. Fuel Vehicle Fuel Vehicle Pickup or Cube Van Vehicle Repair Vehicle Repair Stop at Home Stop at Home Stop for Meal Stop for Meal Single Unit Truck Personal Personal Provide Services Provide Services Tractor Only Drop-off/Pickup Goods Drop-off/Pickup Goods Park Vehicle at Final Location Park Vehicle at Final Location Tractor and One Trailer Other Other Please Specify Please Specify Tractor and Two or More Trailers Did you pick up goods at this stop? Did you pick up goods at this stop? Yes Yes Vehicle Ownership No No Owned by Firm If yes, what commodity type has been picked up? If yes, what commodity type has been picked up? Owned by Driver Food Products Food Products For Hire: Owned by different transport company Road Vehicles and Parts Oil, Gas Road Vehicles and Parts Oil, Gas Wood, Pulp, Paper Chemical Related Wood, Pulp, Paper Chemical Related Fuel Type Manufactured Product Textiles Manufactured Product Textiles Gas Metals and Products Mixed Metals and Products Mixed Diesel Non-Metallic Products Unknown Non-Metallic Products Unknown Hybrid Other Other Propane Did you drop off goods at this stop? Did you drop off goods at this stop? Natural Gas Yes Yes Other No No Please describe If yes, what commodity type has been dropped off? If yes, what commodity type has been dropped off? Food Products Food Products Is this vehicle equipped with GPS? Road Vehicles and Parts Oil, Gas Road Vehicles and Parts Oil, Gas Yes Wood, Pulp, Paper Chemical Related Wood, Pulp, Paper Chemical Related No Manufactured Product Textiles Manufactured Product Textiles If Yes, what is the company name? Metals and Products Mixed Metals and Products Mixed Non-Metallic Products Unknown Non-Metallic Products Unknown Other Other When the vehicle departs is it: Empty Description of Stop Description of Stop 1% - 50% of capacity Please check all that DESCRIBE this stop. Please check all that DESCRIBE this stop. 51% - 75% of capacity Manufacturer / Industrial Location Manufacturer / Industrial Location 76% - 99% of capacity Intermodal Point Intermodal Point At capacity Warehouse/ Depot Warehouse/ Depot Does not apply Retail Retail Restaurant Restaurant What would capacity be constrained by? Residence Residence Weight Gas Station Gas Station Volume Other Other Please Specify Please Specify

Departure Time Departure Time Departure Time Figure 3 Form D: Stop Information (driver)

Mail-Out Mail-Back Survey with GPS Supplement

Approximately half of the firms that are served by a private fleet or a regularly returning driver were asked to participate in a GPS supplement to the mail-out mail-back component of the survey. This survey technique collects additional stop, route, dwell time and engine information to supplement the mail-out/mail-back survey

The GPS technology used in the survey is the Route Tracker, developed by Turnpike Global Technologies Inc. A Route Tracker is an electronic onboard recorder which records time- stamped locations and engine data for the vehicle every few seconds, and stores those data points every 500m, every 5 minutes, or when the vehicle stops for at least 5 minutes, whichever is less. The device is approximately 9.5cm8cm2.5cm, and is placed on the dashboard of the commercial vehicle. The Route Tracker connects to the J1708 engine port of the vehicle, which provides the power source and the source of engine data. The device collects information and transmits the information through Class 1 Bluetooth to a “base station” receiver, which was located in the survey office. The information is transmitted, via internet, from the base station to the Turnpike head office for post-processing, where invalid data points are removed and data are aggregated and summarized in web forms. The post- processed data were then made available to the research team through a web application. Route Trackers and the necessary cables were sent to the shipper firm representative by courier, along with instructions for self-installation, and a pre-paid return courier package.

Incentive

An optional lottery incentive was offered to both drivers and shippers upon survey completion to help persuade them to participate in the survey. The incentive was a 1 in 20 chance to win a $50 gift certificate to the respondent’s choice from a set of restaurants, bookstore, department stores, etc. It is uncertain whether this incentive had a major effect on the response rate. However, the lottery was made optional because of concern raised by at least one respondent in the pre-test that receiving some form of payment for information about their firm while working may be unethical, or may be perceived to be so.

SURVEY RESPONSE

A stratified random sample of 4178 telephone numbers was obtained for companies in the Region of Peel. The sample was stratified by primary industry classification and by ranges of number of employees. Of the total telephone numbers drawn, 15.3% were not legitimate numbers, the survey team could not communicate with a further 13.4%. Also, 14.8% of the businesses did not qualify for the study because they either had not shipped or received any goods in the past week, they were going out of business or they only generated commercial vehicle movements outside the study area. Of the remaining 2308 qualifying businesses, a total of 597 agreed to participate and returned usable information for at least Form A, representing an effective shipper form response rate of 25.3%. The main reasons for refusing the survey on the recruitment call for both survey methods were that the firm was too busy (20%) or that the firm was not interested (29%). These surveys cover a good representation of industry types and company sizes, with some over-sampling of manufacturing industries, and a somewhat heavier representation of mid-sized firms.

Shippers were asked to forward the driver survey (Forms D and E) to a driver working for the company or a driver that regularly visited the establishment. However, many shippers reported that they were unable to recruit a driver as the drivers were too busy, not interested or did not have proficient language skills to complete the survey. For the mail-out/mail-back survey, driver forms were sent out to 323 businesses. Of these 323 paper-pencil driver surveys, 86 (26.6%) were completed. 43 drivers also participated in the GPS supplement to the survey. The 43 GPS surveys were conducted by installing Route Tracker units for 7 days in the vehicles of participating trucks. It was expected that asking respondents to participate in the GPS supplement would have resulted in additional outright refusals because the GPS supplement is potentially considered more intrusive by the respondent. However, the effective shipper form response rate for those companies that were asked to participate in the GPS supplement was approximately the same as for those that were not asked (25.3%). When potential respondents refused to complete the survey, they were asked the reason. One of the possible responses was to cite confidentiality issues. The same proportion of refusals (1.7%) indicated reasons of confidentiality, regardless of whether a GPS supplement was requested. However, an additional 2.5% of potential respondents for GPS-supplemented surveys, refused to participate in any part of the survey because of the GPS supplement.

Another indicator of the effect of the GPS-supplement on survey response is the proportion of mailed driver surveys that are returned and completed. A total of 226 driver surveys were mailed to respondents without an accompanying GPS device, yielding 45 returned completed driver surveys (19.9%). The 97 driver surveys that were mailed with a GPS device yielded 42 returned completed paper-pencil surveys (43.3%) and 43 returned GPS devices with usable data (it is noted that all GPS devices were returned in the end). The completion rate of those paper-pencil surveys with a GPS supplement was markedly higher than those without, once they had indicated a willingness to conduct the survey.

Item Non-Response

Item non-response is another important factor that represents the quality of the survey data for each question. In the Region of Peel Commercial Travel Survey, item non-response occurred for three main reasons: respondent burden due to the question format, reluctance to divulge confidential shipment values and when the respondent just did not know the information. For Forms A to E, item non-response ranges from 1.6% to 83.1%; representing a very large range. Questions that required minimal effort, such as check boxes with likert scales had the lowest item non-response; however the open ended questions, such as “We invite you provide any other comments on how to improve the freight transportation system in Southern Ontario” that require substantial amount of effort from the respondent had higher levels of non- response (70% - 83.1%), which would be expected for a question with an “invited” response. Respondents were also reluctant to divulge shipment values and item non-response for all value questions ranged from 30% to 45%. In some cases, the high item non-response could be due to the respondent not knowing the required information. For example, the driver may have not known the commodity type being transported and the shipper may have not known the number of vehicles owned by the firm.

COMPARISON OF PAPER-PENCIL DRIVER SURVEY AND GPS DATA

Some pieces of information are commonly collected in both the mail-out mail-back questionnaire and by the GPS device. Other pieces of information are collected uniquely by each method. Information collected through paper-pencil driver surveys includes:  Beginning address of the tour  Vehicle and fuel type  Capacity of vehicle and whether it is constrained by weight, volume or both  Arrival and departure time of each stop  Address or nearest intersection of each stop  Stop activity and stop description for each stop  Commodity type that is being dropped off or picked up at each stop

Information that is available through GPS collected data includes:  Longitude and latitude of each stop that is > 5 minutes in duration or involves stopping the engine of the truck.  Longitude and latitude of commercial vehicle location every 500m or every 5 minutes  Stop duration  Time at which each GPS read was taken  Travel speed  Engine information including engine speed, rpm, engine load, instances of heavy deceleration, idle time and fuel consumption (for vehicles using J1708 cables)

The GPS devices were installed in commercial vehicles for 7 days or more, and drivers were requested to complete the single-day paper-pencil survey for the first day in which the GPS instrument was installed.

Out of the 43 drivers that installed the GPS unit in their truck, 5 did not return a paper survey. Analysis of the data also indicated that 11 of the 43 did not complete the paper survey for the first day of GPS tracking, as we had requested, despite clear instructions given to the drivers. Fortunately, the matching day between the two surveys could be identified by manually comparing travelled routes and stop arrival time collected from GPS unit and the stops identified on the paper survey forms.

Stop Comparison

Stops were collected in both the driver Form D from the mail-out mail-back survey and the GPS survey for the “survey day”. Yet significant discrepancies were discovered between the two sources of data. Some of these discrepancies were expected. For example, we expected that some stops recorded in the paper survey would be less that 5 minutes and therefore not identified by the GPS device. We also expected some level of stop non-response in the paper- pencil surveys. As shown in Table 2, 333 stops were identified by the GPS devices, and 435 stops were identified on the paper and pencil forms.

Locations and stop arrival time were compared between paper driver survey and GPS data in order to reconcile the stops identified in each of the two survey methods. A list of “matched” stops was compiled for companies which completed both paper-pencil and GPS components of survey. These common stops were determined by matching the location and time between stops reported by drivers and stops recorded from GPS units. A buffer around each GPS stop is set for both distance and time, and any paper-pencil reported stops that fell within both Table 2 Summary of Stops Recorded by Paper-Pencil Survey and GPS Device GPS Device1 Paper-Pencil Survey Combined Information Avg Avg Avg stops stops per stops per per driver/ Total driver/ Total driver/ Total vehicle % Stops vehicle % Stops vehicle % Survey day2 Total number of stops on survey day 333 9.00 100% 435 11.76 100% 602 16.27 100% Total number of matched stops on survey day 166 4.49 50% 166 4.49 38% 166 4.49 28% Total number of unmatched stops on survey day 167 4.51 50% 269 7.27 62% 436 11.78 72%

Total number of stops > 5 min 333 9.00 100% 334 9.03 100% 501 13.54 100% Total number of matched stops > 5 min 166 4.49 50% 166 4.49 50% 166 4.49 33% Total number of unmatched stops > 5 min 167 4.51 50% 168 4.54 50% 335 9.05 67%

Common time frame3 Total number of stops in common time frame 234 7.09 100% 241 7.30 100% 309 9.36 100% Total number of matched stops in common time frame 166 5.03 71% 166 5.03 69% 166 5.03 54% Number of unmatched stops in common time frame 68 2.06 29% 75 2.27 31% 143 4.33 46%

Total number of stops > 5 min 234 7.09 100% 195 5.91 100% 263 7.97 100% Total number of matched stops > 5 min 166 5.03 71% 166 5.03 85% 166 5.03 63% Total number of unmatched stops > 5 min 68 2.06 29% 29 0.88 15% 97 2.94 37% 1 – In the GPS survey, only stops > 5 minutes are recorded 2- The survey day analysis includes data from 37 drivers that completed both the paper-pencil survey and installed a GPS device, and have at least one identifiable address 3- The common time-frame analysis excluded 5 of the 37 drivers for which no common time frame was found between the GPS and paper pencil survey stops distance and time buffers were considered as “matched” stops. The time buffer used in this analysis is 30 minutes, and the distance buffer is 500m around the GPS recorded location. In addition to this automated matching procedure, manual matching was undertaken for some stops, including those with poor geo-coding precision (i.e. nearest main intersection was reported rather than street address). A total of 166 matched stops were found between the two survey methods, leaving 167 and 269 unmatched stops for the GPS and paper-pencil methods, respectively. This rate of matching was far worse than was expected and led us to further explore the reasons for a poor matching rate. Our detailed analysis revealed the following: First, 101 out of 435 total paper-pencil recorded stops were reported to be less than 5 minutes in duration, and therefore were not captured in GPS collected data. This clearly indicates that a threshold of 5 minutes for stop identification in an urban focused survey is too high. Second, 5 of the 37 drivers “truncated” their paper-pencil survey questionnaire, that is, they diligently filled out the survey for part of the survey day, but ceased to record stops after a certain time. Similarly, in some cases, the driver did not accurately report the first stop of the day in the paper-pencil survey form, (for example, starting from home and stopping at the business establishment), which was captured in the GPS survey. In total, 99 of the 333 stops recorded by the GPS devices were outside the period of travel reported in the paper-pencil survey.

Third, in some cases the GPS survey had been truncated. In other words, the paper pencil questionnaire indicated a continuing tour, but the GPS device was either unplugged or ceased to record information for some other unknown reason. At the outset of tours this was largely due to a “warm-up” period. At the end of the tours, this either indicates that the power to the GPS unit was interrupted, or that the stops reported in the paper-pencil survey were not carried out in the tracked commercial vehicle. A total of 194 stops reported on the paper- pencil survey fell outside of the period of travel captured in the GPS devices.

To facilitate a stop-by-stop comparison, a “common time frame” was analyzed in further depth. The common time frame is defined as the period of time within the survey day, for which information in available from both surveys, not included the truncated portions of either survey. Within the common time frame, 68 of the GPS recorded stops remained unmatched, and 75 paper-pencil reported stops remained unmatched.

Of the 75 unmatched paper-pencil reported stops in the common time frame, 46 had a stop duration of less than 5 minutes, explaining why they were not captured by the GPS devices. Of the remaining 29 unmatched stops, 8 were reported as stops, but no location was provided, 15 stops could not be geo-coded and 6 were reported with an incorrect location. Of perhaps greater concern were the 68 stops (> 5 min) within the common time frame that were recorded by the GPS device, but not reported by the driver at all. The only conclusion that can be made about these stops is that either the driver did not care to report these stops, they forgot about these stops or considered them redundant, or they did not want to report these stops on the basis of their own deliberate decision (these potential reasons are suggested by (Casas and Crce, 1999) in their assessment of passenger travel surveys).

Figures 4a and 4b show the distribution of number and proportion of unrecorded stops to total stops recorded by each survey method within the common time frame. The number of GPS unreported stops is calculated by subtracting the number of GPS stops recorded within the common time frame from the total number of stops in the common time frame that are identified using combined information from both survey instruments. Similarly, the number of paper-pencil unreported stops is the difference of the number of paper-pencil reported stops within the common time frame from the total number of stops in the common time frame that are identified using combined information from both survey instruments. The proportion of unreported stops is relative to all stops in the common time frame using combined information from both surveys.

12 Paper-Pencil recored stops Average=2.27 10 GPS Stops Average=2.06 s e l

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0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Number of Unreported Stops a) Distribution of the Number of Unrecorded Stops

12 Paper-Pencil Recorded Stops GPS Stops 10 s e l c

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0 % % % % % % % % % % % 0 0 0 0 0 0 0 0 0 0 0 1 2 3 4 5 6 7 8 9 0 ------1 1 1 1 1 1 1 1 1 1 - 1 2 3 4 5 6 7 8 1 9 % of unreported stops to total stops b) Distribution of the Proportion of Unrecorded Stops Figure 4 Stops Comparison Within the common time frame, 11 drivers reported the same stops identified by the GPS devices. 26 drivers have fewer than 4 unreported stops in the GPS recorded data, and in the paper-pencil survey. Figure 4b shows that unreported stops contribute to a high portion of total stops recorded in some cases but that for the majority, unreported stops represent less than 20% of all stops.

METHODOLOGICAL LESSONS LEARNED

Clearly there are many challenges associated with using a shipper based survey to successfully obtain high quality freight data. Many, but not all, of these challenges were successfully addressed or at least mitigated in the Region of Peel Commercial Travel Survey through careful survey design, extensive pre-testing, persistent and persuasive recruiting, and the use of GPS technology to supplement the paper-pencil portion of the survey.

The following subsections summarize the key practical methodological lessons learned in the study. We focus here on those lessons that are specific to freight surveys and GPS supplements, since many other sources exist to guide the implementation of travel surveys in general (e.g. Stopher et al., 2004).

Recruitment  One of the greatest challenges in recruitment is to make contact with an appropriate, knowledgeable person within the company. For large companies and manufacturing firms, we were most successful when we asked “Can I speak to a logistics manager, a shipping and receiving manager?” or in some cases “Can you please transfer me to the shipping/receiving department”. For office and services companies, it worked well to simply ask for “the manager”. When the call connected to an electronic directory, we selected the shipping department, the receptionist or a random name, in that order.  Asking the shipping manager in a company to recruit drivers to undertake the driver survey is difficult. This difficulty was a primary reason for the low number of driver survey completions. Many companies used different couriers each day and as a result were not able to designate a driver for the survey, since no driver was guaranteed to return to the firm.  Because of the diversity of firm types that were contacted, confusion could result even from seemingly simple questions at the recruiting stage. For example, the question “Do you ship goods?” could be interpreted to refer either to the delivery of goods or the manufacture of goods for delivery. For this example, since we were interested in both, it was better to ask “Do you produce or distribute goods that you ship?”  To avoid bias in the choice of survey day, we randomly chose a particular weekday and insisted that the respondents report their activities for that assigned day. However, many potential respondents had concerns with the assigned survey day because they did not ship on that day or were too busy that day. To avoid an overly-restrictive survey and the resulting higher response rate, we first encouraged the respondents to fill out the survey on the randomly chosen day and if that failed, we decided to allow such participants to self- select the week in which they were surveyed, but not the day of week.  When it had been determined that a company did not qualify for the study, then most (approximately 80%) did not mind answering two short questions regarding number of employees and industry classification. This information helped tremendously in characterizing the representativeness of the sample.  The main reason for refusal was that a company is too busy. Participants were concerned with the time of the survey would take, and some were reluctant to participate if it was a telephone survey.  Based on the judgment of the interviewers, the incentives did not seem to have an important effect on the recruitment. However, this judgment was not substantiated by any further analysis. We continued to offer an incentive. Similarly, most shipping managers did not recall the introductory postcards that were sent prior to the recruitment calls. Yet we continued to send a postcard.  The best time of the day for recruitment calls was found to be between 9:30am to 11:30am and between 2:30pm to 4:30pm.

Survey Questionnaire Design Many difficult decisions were made in the survey questionnaire design and the survey process design. To maximize the response rate, and the quality of the data, best practices for survey instrument and survey process design, as outlined by various authors (e.g. Dillman, 2000; Stopher et al., 2004; Lawson et al. 2002), were consulted. Our review of the literature and other successful surveys, and our pre-test led to our choice of a combination of a postcard, a recruitment telephone call, a mail-out mail-back survey, and follow-up calls.

We conducted a pre-test of 21 randomly chosen companies prior to the main implementation of the survey. Based on the pre-test survey results, and the follow up telephone interviews with 4 pre-test respondents, several changes were made to the survey instrument. In particular, the survey was too long and some of the questions were confusing for companies that are not directly involved in the trucking business. As a result, 11 questions were removed from the survey, and many wording changes were made. We were able, as a result of these changes to improve our pre-test response rate of 19% to 25.3%.

Even with careful attention to survey design, our comparative analysis showed that significant under-reporting of stops can be expected, both from the paper pencil survey and the GPS survey. This provides justification for the continued use and further development of GPS supplements to paper-pencil surveys for the freight sector.

Use of GPS Technology The introduction of a GPS component to the survey added significant technical, logistical and administrative complexity to the survey. The following key lessons were learned over the course of the GPS-supplemented survey.  Shipping coordinators in companies that qualify for the GPS component of the survey often require permission from owners or managers at a higher level. In such cases, it is important for the recruiter to obtain approval from a higher level in the company for the contact person. However, such persons are very difficult to contact and have little time to spend on recruitment phone calls. It is best to send a fax or email an introduction letter to the owners and managers through the initial contact person prior to the initial phone contact with them, to shorten the conversation time and reduce respondent burden.  Many companies hire third-party transportation companies to handle deliveries of their goods, and they typically refuse the GPS component of the survey initially. In some such cases, where specific drivers are assigned to specific companies, it is possible to obtain a response from the driver from the third-party logistics firm as well as from the shipper.  Some companies rent vehicles for making deliveries, and often the installation of a GPS device would require permission from the vehicle rental company. It is best to determine the reason for their refusal on the GPS component of the survey during the recruitment process and offer assistance to obtaining approval from their third-party companies or vehicle rental companies.  Some vehicles were not compatible with the Route Tracker cable connectors (J1708, J1850) that were originally provided from Turnpike Global Technologies. In response to this, port connectors to the cigarette lighter were obtained as an alternative power source. Reminder calls and follow-up calls are essential in these situations to ensure all technical difficulties are resolved.  Companies that agree to participate in the driver portion or the GPS portion of the survey were asked for driver’s contact information to prepare for future follow-up contacts. However, it was discovered that most shipping managers are reluctant to give out driver’s contact information. Therefore, in some cases, the driver portion and GPS equipment could only be sent to the contact person and to be transferred to the driver.  It is more difficult to recruit drivers to undertake a GPS-supplemented survey, because of privacy concerns, but this has a relatively small effect on response to other portions of the survey. However, drivers that do engage in a GPS supplement survey are more than twice as likely to return their survey completed, than those that do not.

ACKNOWLEDGEMENTS

Financial support for the data collection effort was provided by the Ministry of Transportation, Transportation Planning Section and the Region of Peel. Financial support for this work is gratefully acknowledged. Turnpike Global Technologies Inc. was the supplier of the Route Tracker units used in the survey. The technical support provided by the staff at Turnpike was essential. May Lynne Fong provided high quality assistance in the second half of the survey.

REFERENCES

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