Intelligent parking technology adoption

Bilodeau, Victor P. (2010) Intelligent parking technology adoption. [Thesis (PhD/Research)]

[img] Text (Introductory Pages)

Download (3MB)
[img] Text (Whole Thesis)

Download (3MB)


Inefficient parking practices have costs associated with them that extend well beyond lost profits and frustrated customers. This dissertation focuses on why parking providers appear hesitant in adopting Intelligent Parking
Technology (IPT) that could help benefit all stakeholders. More specifically, this dissertation analyses the following question:

Why do parking providers appear reluctant to adopt intelligent parking technologies?

Intelligent Parking Technology (IPT) potentially offers drivers many benefits including faster parking times, more convenient payment options and safer parking lots. For parking providers, benefits of IPT implementation might include higher profits realized through increased
business process efficiencies such as automated payment collection. Society could potentially benefit from IPT through primary effects such as reduced traffic congestion, greenhouse gas emissions and driver frustration levels. It may also benefit through secondary effects where, for example, a government uses profits realized through increased efficiencies and spends it on things that will benefit the community such as better roads and more
green spaces.

We define Intelligent Parking Technology (IPT) as technologies that are managed by a parking service provider and add value by adapting themselves to whatever a parking situation may be. Intelligent Parking Technology (IPT) includes those technologies that offer a unique
functionality such as giving customers the ability to pay for parking using their cellular telephone (m-commerce), automatically directs them to empty parking spaces or automates payment via smart cards.

The parking providers investigated include businesses, schools, and governments. We consider technologies currently available to them as well market willingness to adopt them.

The Delphi technique is used and consists of interviewing independent content experts such as parking services managers within various organizations. We also interview one senior level manager working for a company that licenses or sells Intelligent Parking Technology (IPT).
Questions formulated from these interviews are then brought forward and used in surveying drivers. Data is collected from the surveys and then analysed and interpreted through discussion with the independent content experts initially interviewed so that they may corroborate or disapprove the
findings. Their interpretations of the data are also considered in the study, as this research is primarily qualitative in nature.

The driver survey included questions that explored the perceived value drivers might get from different parking technologies currently available to parking providers. Findings from the driver surveys clearly show that
drivers are more than willing to adopt Intelligent Parking Technology (IPT).

In every case, the majority of drivers indicated that they would get at least some value from the specific parking technologies presented. This varied from a low of 60.9 percent of respondents indicating they would get value
from a robotic parking system to a high of 94.7 percent indicating they would receive value from a system that would direct them to empty parking spaces.

Over 66 percent of drivers also stated that they would be willing to pay more for a parking space if Intelligent Parking Technology (IPT) added value for them.

The senior manager from the parking technology company was not at all surprised by the driver survey results. Parking providers, on the other hand, seemed somewhat surprised by the survey findings and the follow-up interviews where these findings were discussed seemed to initiate a state of
reflection for them.

Statistics for USQ ePrint 19466
Statistics for this ePrint Item
Item Type: Thesis (PhD/Research)
Item Status: Live Archive
Additional Information: Doctor of Business Administration (DBA) (Research) thesis.
Faculty/School / Institute/Centre: Historic - Faculty of Business - School of Information Systems (1 Apr 2007 - 31 Dec 2010)
Faculty/School / Institute/Centre: Historic - Faculty of Business - School of Information Systems (1 Apr 2007 - 31 Dec 2010)
Supervisors: Soar, Jeffrey; Cater-Steel, Aileen
Date Deposited: 09 Aug 2011 05:37
Last Modified: 25 Sep 2019 05:44
Uncontrolled Keywords: intelligent; parking; technology; adoption; intelligent parking technology
Fields of Research (2008): 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080199 Artificial Intelligence and Image Processing not elsewhere classified
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4699 Other information and computing sciences > 469999 Other information and computing sciences not elsewhere classified

Actions (login required)

View Item Archive Repository Staff Only