Towards Friction-Free Work:
A Multi-method Pilot Study of the Use of Information Technology
In the Real-Estate Industry
Final Report
NSF Grant # IIS-9732799
Submitted by:
Rolf T. Wigand, Ph. D. (rwigand@syr.edu) and
Kevin Crowston, Ph. D. (crowston@syr.edu)
School of Information Studies
Syracuse University
and
Steve Sawyer, DBA. (sawyer@psu.edu)
School of Information Sciences and Technology
The Pennsylvania State University
March, 2001
Towards Friction-Free Work:
A Multi-method Pilot Study of the Use of Information Technology
In the Real-Estate Industry
Final Report
To explore the relationships between individual information and
communication technologies (ICT) use and changes to organization and
industry structures, we examined the residential real estate industry. While
ICTs are often associated with organizations (and industries), their use
occurs at the individual level. In other words, in such industries, changes to
individual work due to the use of ICTs reshape both organization and
industry structures, and vice versa. This final report is structured as follows:
We provide a brief overview of the real estate process and highlight why it is
an appropriate domain for this study. In this overview we also outline the
role of agents in the real estate process and address what roles (ICT) play in
that process. We then discuss our research methodology and highlight the
principal findings. Lastly, we characterize today’s real estate industry
especially with regard to the role of ICT and the Internet. Various descriptive
statistics are presented in the Appendix.
The Real Estate Process, the Role of Agents and ICT
Real estate was chosen because it is large, both in people employed and
contribution to the economy. The work of a realtor is information-intensive
and information-driven and occurs in an intermediated market (agents and
brokers connect buyers and sellers). It is transaction-based, with high value
and asset specificity; and currently experiencing ICT-induced changes,
leading to predictions of disintermediation.
Residential real estate agents are affected by the presence and use of
information and communication technologies (ICT) that can change the cost
of collecting and distributing information. However, they also control other
resources (e.g., relationships, access to the house key) that are harder to
duplicate and not directly affected by the presence and/or uses of ICT.
Therefore, analyses that focus only on the effects of the ICT tell only a
partial story.
A real estate transaction (buying/selling a house or “closing”) has four
defining characteristics:
1
1. There is a set of steps that must be done and these steps are not
easily sequenced. Instead, they form a complex process of common
pieces for each closing.
2. The entire set of steps that make this process are embedded in a
network of other transactions. Changes in one part of this network
are constrained by and have implications for the rest of the network.
For example, electronic forms can be used in the purchase and sales
stage. But, most particular jurisdiction’s law allows only paper copies
to be filed.
3. Agents contribute different values to different parts of the process.
For example, agents may be less valued for listing information, but still
provide guidance to the closing process.
4. Many parts of this process are structured by federal, state and
local regulations, professional norms, and particular idiosyncrasies of
the participants. The structures that constrain and enable the closing
process are both being reinforced and changed by the presence and
use of ICT.
Analyses of ICT in use have to consider individual and organizational
practices as well as the presence and capabilities of the technology. A
specific example is a realtor's multiple listing service (MLS). The MLS is
often considered as merely a database of listings. In practice though, the
MLS includes the practices of agents to enter and search the MLS and a set
of agreements among agents to compensate one agent for selling a listing
obtained by another.
The role of ICT depends on the perspective of the user. For example, both
agents and their agencies view listings as advertising, and so are willing to
pay to have their listings available on a web site. From the perspective of
web site developers, listings are content, and they would be willing to pay to
have them on their web site. From the perspective of the real estate
industry organization, the National Association of Realtors (NAR), listings are
intellectual property, and the NAR is lobbying for changes to copyright laws
to protect this property.
Similarly, individual uses of ICT are shaped by organizational and even
industrial practices, while simultaneously, new use of ICT have the potential
to reshape these practices. For example, the Web provides a way to
distribute listings, but without a new set of agreements, it cannot directly
replace the MLS. On the other hand, as sellers become aware of the Web,
they increasingly demand that their listing be distributed this way. By
contrast, in countries such as England or New Zealand, where there are no
MLS agreements, the Web seems to pose a much more direct threat.
2
However, there is no evidence in the US that the number of closing down by
owner (FSBO) has changed in the last five years.
As a second example, the increased use of ICT demands a more pervasive
and complex computing infrastructure than most agents can afford (or
understand). This raises the profile and importance of the agencies and
shifts some power away from the individual agents (who are employed as
contractors) towards agencies. In turn, this is leading to a consolidation of
agencies and an increasingly full-time professional (as opposed to part- time)
pool of agents.
In a survey of 150 real estate agents in one mid-sized city, we found that
agents are nearly all heavy users of basic communications technologies, such
as the phone, fax, cell phone, voice mail and pagers. But, only a few use
more advanced technologies such as PCs or the Web.
Research Methodology
Data were collected using a self-administered mail questionnaire of
residential real estate agents. Items for the questionnaire were based in some
cases on survey items in the literature or were developed based on the
interviews with real estate agents. Most questions are closed-ended (e.g., 7point Likert scales), although a select number of opened-end questions were
offered to elicit additional concerns. The questionnaire was pre-tested with a
focus group of real estate agents to refine the questions prior to
administration.
The questionnaire was administered to 868 licensed real estate agents in a
single metropolitan area in the Northeast United States. The local real estate
agent association assisted us in data collection by providing access to the
association’s mailing list. Several of the larger agencies further assisted data
collection by providing time in agency meetings. The association also helped
to publicize the survey.
To encourage response, we sent announcement and follow up letters,
following Dillman’s (1978) total design method. Some local real estate
agencies provided time during regular meetings of their real estate agents for
us to administer the questionnaire, which also promoted responses. For
privacy reasons, we elected not to identify survey respondents, which made
it impossible to target follow-up requests or thoroughly investigate nonrespondent bias.
3
A total of 153 surveys were received, for a total 18% response rate. After
coding, 150 responses were usable. Given their specific assistance, the
response rate for agents associated with the four large agencies was
substantially higher, 24% (121 out of 512); for other agents, the response
rate was 9% (32 out of 356).
Findings
Below are the main points summarizing the research we have conducted.
Various descriptive statistics are presented in appendix A. These findings are
grouped by the following rubrics: Use of Information and Communication
Technologies (ICT), Changes in Individual Work, Changes in Organization
Structure, as well as Changes in Industry Structure.
Use of ICT
1. The type of IT used varies dependent upon different steps in the real
estate process.
2. ICT changes the abilities of actors to access information, an essential
resource in real estate.
3. A critical aspect of the agents work is the extension and maintenance of
their social capital.
4. Analyzing an agent’s social capital - the set of social resources embedded
in relationships - provides insight into how the work of real estate agents
is affected by ICT.
5. Increased use of ICT provide for the potential for people to extend their
social networks and increase their social capital.
6. Mobile communications technologies were heavily used.
7. Internet and computing technologies were used less intensively than
mobile communication technologies.
8. ICT use varies depending upon the stage in the real estate process.
9. The MLS takes multiple forms and is distributed and accessed through
the use of different technologies.
10. Individual-level uses of ICT may be associated in turn with changes in
the organizations in which the work is done. These effects manifest
themselves, in part, as changes to organizational processes and
4
eventually to change in organizational and industry structures and value
chains.
Changes in Individual Work
1. Real estate agents seem to play an increasing role in process support.
Process support can also be described as transaction knowledge.
2. There are distinct stages or steps in the real estate process: (1) listing a
house, (2) marketing the listing, (3) finding a house for a buyer, (4)
helping a buyer select a house, (5) negotiating a contract, (6) removing
contract contingencies, and (7) closing the sale of a house.
3. Analyzing an agent’s social capital - the set of social resources embedded
in relationships - provides insight into how real estate agents work and
how that work is affected by ICT.
4. Real estate agents actively manage weak ties and social capital.
5. Agents use social capital to establish their stake in the value chain.
6. Different kinds of information are needed at each stage in the real estate
process.
7. Agents classify social contacts and develop them differently.
8. There are two main ways that agents provide value. (1) Agents can
provide resources from their social network. (2) Agents can provide a
value adding service for both buyers and sellers - guiding them through
the series of steps that are required to complete a transaction.
9. Agents are process or transaction consultants.
10. Professionals in the real estate process factored into the following
three groupings: (1) professional contacts, (2) customers, and (3)
attorneys and other real estate agents.
Changes in Organization Structure
1. A socially thin functional perspective using transaction costs and a
socially rich interpretive perspective using social capital provide for a
more complete explanation of the behaviors of residential real estate
agents and their use of ICT.
5
2. The traditional role of real estate agents as an information intermediary is
being contested.
3. Transactions are socially embedded.
4. It is the core networks the agent maintains and the interconnections
among them that function as coordination mechanisms.
5. Agents draw on large informal social networks to provide value-adding
services to prospective buyers (and sellers).
6. The network of the real estate agent is critical and is comprised of both
loose and strong ties.
7. The agent-controlled access to MLS provides for domination of agents
over buyers and sellers.
8. Agents are information intermediaries between buyers and sellers. Control
of listing information helps maintain this position.
9. Stages in the real estate process factored into the following two stages:
(1) support stages, and (2) legal stages.
10. The real estate agent is an exemplar of an information and information
technology intensive industry that is a “organization of one”.
11. The real estate process can be broken down into several stages: (1)
listing, (2) searching, (3) evaluation, (4) negotiation, (5) execution
(closing).
Changes in Industry Structure
1. Real estate is an intermediated market connecting buyers and sellers
through the use of the multiple listing service, MLS.
2. Other value added players are disaggregating the value chain.
3. A package of services through coalitions can provide for some degree of
market lock.
4. Structural reconfiguration of the industry is taking place due to ICT.
6
5. Real estate is more complex than other volatile industries changed by
ITC. Real estate is not a perfect market.
6. Disintermediation is less of a threat than reintermediation.
7. The real estate industry is indicative of other industries experiencing
disintermediation and reintermediation such as the travel, insurance,
automobile, and financial industries.
8. The social network and knowledge of the transaction process serve, to
some degree, to safeguard the agent from being circumvented as a
segment in the supply chain.
9. The structure of the industry has evolved toward small, clearly identified,
specialized firms and large market-share brokerages.
10. Due to the pervasiveness of the Internet, we anticipate an eroding of
the power position of real estate professionals, as they adapt to the loss
of exclusive access to the MLS.
11. The real estate process is distinctively different depending upon the
state in which the transaction takes place.
12. Real estate is practiced in distinctively different ways in other
countries.
13. Different contexts (countries, states, markets) have distinctively
different real estate process and use of ICT in those processes.
14. Given that residential agents and real estate firms are pure marketintermediaries (connecting buyers and sellers but rarely buying and selling
themselves), their positions are potentially threatened when ICT provide
new ways for buyers and sellers to find one another.
15. Our research provides insight into how value is provided in the real
estate industry and into the potential for disintermediation, the possible
outcomes of re-intermediation and the identification of emerging
intermediaries in the market.
16. Web-based commerce is eroding the long enjoyed information
monopoly of real estate agents and electronic commerce applications
have the potential to drastically change current practices in the real estate
industry.
7
Emerging Trends within Today’s Real Estate Industry: The Online Struggle
In spite of the hard times that have fallen on many dot-coms, several major
firms such as Goldman Sachs Group Inc. and FrontLine Capital Group have
announced spin-offs as dot-com firms in the real estate business and
strategic alliances with consortia of landlords and real-estate brokers. One
such company, Zethus, is developing a Web-based platform to streamline the
paper-intense, as well as information-intense process of transaction leases
and building sales.
Efforts to streamline such typical transaction processes should be welcome
news to nearly everyone involved in the buying and selling of property.
Processes that would simplify many of the cumbersome, slow, timeconsuming tasks associated with buying a house are indeed highly desirable.
The resulting benefits of such streamlining and standardization are obvious:
In a typical transaction, a piece of paper is required to float through 128
different checkpoints before a house is actually sold (Hickey, 2000).
Bankers, brokers, lawyers, mortgage specialists and many others often
operating behind the scenes in a very fragmented real-estate value chain
would welcome tools enabling them to cooperate, collaborate and conduct
business over portals. There are over 40 disparate parties in a real estate
transaction and the consumer has to deal with all of them (Krafchow, 2000).
The potential to streamline many of these processes is attractive to all
involved.
Home buyers have already moved in sizable numbers from traditional sources
of information (friend/neighbor, open house, magazine, yard sign, newspaper
ad and agent) to the Internet. A National Association of Realtors (2000)
study reports that in 1997 18 percent of respondents in a nationwide study
used the Internet as an information source whereas in 1999 37 percent
reported using that source. In 1995 merely two percent used the Internet. It
seems that the Internet is penetrating the buy-side of this industry at an
increasingly strong pace. These developments seem to be analogous to car
buyers increasingly using the Internet as the starting point when purchasing
a new car. Some studies report that about 60 percent of all new car buyers
start the purchase process with the Internet.
On the other hand, as in the case with online lenders, paper documents must
still be sent in to the lender, papers must be signed by hand, etc. Forrester
Research reports U.S. households with an Internet connection that had
obtained a mortgage in 1999, one-third of the borrowers had used the Web
8
to research mortgages. Even though approximately 50 percent of all
households do have an Internet connection today, yet only one percent of
those mentioned borrowers closed loans on line (McAllister, 2000). These
individuals tend to find the best rates from the best lender and they in turn
get a mortgage broker to give them personal advice and handle all the
paperwork at nearly the same cost as online.
This apparent dilemma is observable in other industries as well (e.g.,
automobile purchasing, travel bookings). This seems to suggest that buyers
probably will not switch from this method until a future point in time when
the process is much more automated than it is now, when digital signatures
and electronic document delivery have been substantially streamlined the
process of closing a mortgage or house purchase online. For mortgage firms
specifically, this situation means that having branch offices is still relatively
important, as long as people are not willing to make the mortgage purchase
online. This implies that mortgage must for now pursue a dual or hybrid
channel strategy, i.e. offer brick and click features to their customers. It
appears that this segment of the Internet, just like many others, is going
through a shake-out period in which the fittest, not the strongest, seems to
survive. It seems that opportunities may exist for these and other firms by
focusing on the potential of future realtor relationships and various affinity
groups.
For many years little change was observable in how people bought and sold
a house, Buyers and sellers hired agents to represent their interests. When a
deal closed, the seller typically paid six or seven percent commission and this
was split among the contributing agents following a pre-determined
allocation. Agents were part dealmakers and part counselors. They
researched recent sales (market analysis) in the area to help determine what
price a buyer could reasonably expect to pay, to arranging a visit by the
house inspector and exterminator. This role has not changed for traditional
brokers, but the situation has changed if using an online broker.
If a customer chooses an online broker, he/she is likely not to see the agent
very often and the online broker is likely to stress this fact. They are likely to
argue that much of the work an agent does can be automated and
streamlines or accomplished via e-mail and phone calls. As a result, many
online brokers charge sellers a 4.5 percent commission instead of the six or
seven percent commission and they may even offer buyers a one percent
rebate. In the case of a $300,000 house, the seller would save $4,500 and
the buyer would get a $3,000 rebate. Many agents working for online
brokerages are salaried thus taking away the added incentive of receiving a
commission based on the sale as traditional brokers would. In that sense
online brokers do not need to be as worried as traditional agents in securing
9
the next deal. Typically, a separate marketing department focuses on
soliciting new listings. It should not be surprising in that traditional agents
would criticize these developments, as they tend to argue that customers
will not get adequate and appropriate service. Moreover, they argue that
online buyers and sellers are likely to be treated like commodities and that no
one will be around when problems arise. On the other hand, if this is true
then online brokers simply will not survive over time. .
For now online brokers represent indeed a tiny fraction of the residential real
estate market. Each year, about five million homes are bought and sold
nationwide according to the National Association of Realtors. Gomez
Advisors (2001) reports that fewer than one percent of those deals occur
online. Consumers make a trade-off when choosing an online broker. Several
segments of the buying or selling process that used to be carried out in
person now occurs electronically. This becomes quickly evident when
examining the process of buying a home, specifically the search process:
The online broker expects buyers to engage in most of the house-hunting on
their own. Instead of the traditional agent poring over thousands of listings
to sort and find a few strong possibilities, buyers go online to review the
listings themselves and they even may physically drive past homes that
seem most promising. Only after a shortlist has been compiled the agent is
being contacted to arrange physical inspections and tours of the interiors of
those houses. At the point in time when negotiations start, buyers most
likely will communicate directly with their agent over the phone or e-mail
until the process closes.
10
References
Crowston, K. (2000). Processes as theory in information systems
research. Paper presented at the IFIP TC8 WG8.2 International Working
Conference on the Social and Organizational Perspective on Research
and Practice in Information Technology, Arlborg, Denmark.
Crowston, K., Sawyer, S., & Wigand, R. (1999). Investigating the interplay
between structure and technology in the real estate industry. Paper presented at
the Academy of Management Conference, Chicago, IL.
Crowston, K., Sawyer, S., & Wigand, R. (in press). Investigating the
interplay between structure and information and communications technology in
the real estate industry. Information, Technology, and People.
Crowston, K., & Wigand, R. (1998). Use of the Web for electronic
commerce in the real estate. Paper presented at the Association for Information
Systems Americas Conference, Baltimore, MD.
Crowston, K., & Wigand, R. (1999). Real-estate war in cyberspace: An
emerging electronic market? Electronic Markets, 9(1-2), pp. 1-8.
Dillman, D. (1978). Mail and Telephone Surveys: The Total Design
Method. New York: Wiley.
Gomez Advisors (2000). Cited in Hieger, Jennifer. Digital House Hunting.
Syracuse Herald American, February 18, 2000, p. BB-2.
Hickey, Kevin (2000). Cited in Chuck Moozakis, Portals Automate Real
Estate Deals. Internet Week, May 29, 2000, pp. 1, 57.
Krafchow, Ed (2000). Cited in Chuck Moozakis, Portals Automate Real
Estate Deals. Internet Week, May 29, 2000, pp. 1, 57.
McAllister, Sue. Homebuyers use Web to shop –not secure-mortgages.
Syracuse Herald American, December 24, 2000, p. BB-3.
National Association of Realtors (2000). Cited in Chuck Moozakis, Portals
Automate Real Estate Deals. Internet Week, May 29, 2000, pp. 1, 57.
Sawyer, S., Crowston, K., & Wigand, R. (1999). ICT in the real estate
industry: Agents and social capital. Paper presented at the Association for
Information Systems America Conference, Milwaukee, WI.
0
Appendix:
Descriptive Statistics as Results of the Real Estate Survey.
Degree of formal education completed.
Valid
less than high school
high school
some college
college
graduate
Total
Missing
9
System
Total
Total
Frequency
2
16
Percent
1.3
10.7
Valid Percent
1.4
11.0
38
53
37
146
3
25.3
35.3
24.7
97.3
2.0
26.0
36.3
25.3
100.0
1
4
150
.7
2.7
100.0
Degree of formal education completed
60
50
40
30
Frequency
20
10
0
less than high schoo
some college
high school
graduate
college
Degree of formal education completed
Real estate certifications received
Valid
Missing
Total
CBR
CRS
GRI
Frequency
9
3
16
Percent
6.0
2.0
10.7
Valid Percent
10.3
3.4
18.4
RMM
other
N
Total
1
15
43
87
.7
10.0
28.7
58.0
1.1
17.2
49.4
100.0
62
1
63
150
41.3
.7
42.0
100.0
9
System
Total
1
Cumulative
Percent
10.3
13.8
32.2
33.3
50.6
100.0
Cumulative
Percent
1.4
12.3
38.4
74.7
100.0
Real estate certifications received
50
40
30
Frequency
20
10
0
CBR
CRS
GRI
RMM
other
N
Real estate certifications received
Age
Valid
Missing
20-29
30-39
Frequency
5
17
Percent
3.3
11.3
Valid Percent
3.4
11.7
40-49
50 Total
9
47
76
145
4
31.3
50.7
96.7
2.7
32.4
52.4
100.0
System
Total
1
5
150
.7
3.3
100.0
Total
Cumulative
Percent
3.4
15.2
47.6
100.0
Age
100
80
60
Frequency
40
20
0
20-29
30-39
40-49
50 -
Age
Sex
Valid
female
male
Total
Missing
9
System
Total
Total
Frequency
89
49
138
Percent
59.3
32.7
92.0
11
1
12
150
7.3
.7
8.0
100.0
Valid Percent
64.5
35.5
100.0
2
Cumulative
Percent
64.5
100.0
Sex
100
80
60
Frequency
40
20
0
female
male
Sex
Years in industry and in Syracuse area.
N
Statistic
Years worked in
real estate industry
Years lived in
Syracuse Area
Valid N (listwise)
Std.
Deviation
Statistic
Mean
Statistic
Std. Error
Variance
Statistic
137
13.01
.85
9.96
99.235
133
35.01
1.38
15.88
252.083
125
Years worked in real estate industry.
14
12
10
8
6
Frequency
4
2
0
0
2
4
6
10
12 14
16
18 20
22 24
26
33 36
40
Group you primarily represent
Valid
Missing
Total
exclusively buyers
mostly buyers
Frequency
1
13
Percent
.7
8.7
Valid Percent
.8
9.8
buyers and sellers
mostly sellers
exclusively sellers
Total
9
104
13
2
133
16
69.3
8.7
1.3
88.7
10.7
78.2
9.8
1.5
100.0
System
Total
1
17
150
.7
11.3
100.0
3
Cumulative
Percent
.8
10.5
88.7
98.5
100.0
Group you primarily represent.
120
100
80
60
Frequency
40
20
0
exclusively buyers
buyers and sellers
mostly buyers
exclusively sellers
mostly sellers
Average days to sell a listing.
N
Statistic
Average days to
sell a listing
Valid N (listwise)
Mean
Statistic
Std. Error
103
84.42
Std.
Deviation
Statistic
4.82
48.87
Variance
Statistic
2388.187
103
Listings closed and hours worked.
N
Statistic
Number of listings
closed last year
Hours worked per
week last year
Valid N (listwise)
Mean
Statistic
Std. Error
Std.
Deviation
Statistic
70
19.61
2.62
21.94
481.429
89
44.85
1.47
13.87
192.444
66
Descriptives for listings.
N
Average
days to sell
a listing
103
47
Valid
Missing
Number
of listings
last year
74
76
Number
of listings
closed
last year
70
80
Average days to sell a listing.
30
20
Frequency
10
0
18
38
30
50
42
65
60
80
75
100
85
121
110
Variance
Statistic
230
180
4
Hours worked
per week last
year
89
61
Number of listings last year.
8
6
Frequency
4
2
0
0
4
2
10
6
15
12
20
17
25
22
32
27
50
36
66
60
168
69
Number of listings closed last year.
10
8
6
Frequency
4
2
0
0
2
4
6
11
14
18
20 22
25
28 34
39
49 125
Hours worked per week last year.
20
Frequency
10
0
0
20
28
33
37
42
45
50
55
65
72
Descriptives for aggrgated variables.
N
Statistic
Internet technology use
q1
Mobile commnication
use q1
Internet technologies q18
RCPROFME
RCCUSME
RCAAAME
Valid N (listwise)
Mean
Statistic
Std. Error
Std.
Deviation
Statistic
Variance
Statistic
144
3.8899
.1341
1.6093
2.590
129
5.2907
.1779
2.0211
4.085
137
140
3.1460
3.3558
.1554
.1217
1.8184
1.4402
3.307
2.074
142
143
120
5.7130
5.6247
.1011
9.528E-02
1.2043
1.1394
1.450
1.298
5
How often do you use these technologies in a typical week (question 1)?
never
Count
%
monthly
Count
%
weekly
Count
%
2-5x a week
Count
Telephone
use in a
wk
3
Cell
phone use
in a wk
12
8.6%
4
2.9%
7
5.0%
Int. cell
phone,
beeper,
and voice
use in a
wk
19 16.1%
1
.8%
4
3.4%
3
4
2.9%
2
Voice
mail use
in a wk
3
2.1%
Fax use in
a wk
1
.7%
13
9.0%
6
5.7%
%
134 91.2%
3.4%
24 20.3%
63 53.4%
1.4%
6
4.3%
36 25.7%
89 63.6%
20 13.8%
38 26.2%
43 29.7%
8.6%
25 23.8%
37 35.2%
17 13.3%
15 11.7%
18 14.1%
30 20.7%
11
8.6%
21 16.4%
30 23.4%
E-mail
with
attached
file use in
a wk
50 46.7%
13 12.1%
17 15.9%
13 12.1%
WWW
resources
use in a
wk
23 18.5%
14 11.3%
23 18.5%
20 16.1%
WWW
posted
page use
in a wk
30 24.2%
19 15.3%
22 17.7%
PDA use
in a wk
67 77.0%
PC access
use in a
wk
19 14.6%
6
6.8%
4
16 12.5%
3.1%
%
2.5%
E-mail use
in a wk
4
Count
62 44.6%
1.9%
4.6%
10
%
33 23.7%
2
6
Count
6+x a day
5.0%
24 22.9%
2.3%
%
2-5x a day
7
Beeper
use in a
wk
2
Count
2.0%
14 10.1%
2
once a day
1.9%
9
8
7.5%
3
2.8%
18 14.5%
12
9.7%
14 11.3%
27 21.8%
5
4.0%
12
9.7%
9
7.3%
4
4.6%
3
3.4%
5
5.7%
13 10.0%
10
7.7%
21 16.2%
3
6
2.8%
6.9%
57 43.8%
How often do you use these technologies in a typical week (question 1)?
N
Mean
Std. Deviation Variance
Statistic Statistic Std. Error
Telephone use in a wk
147
6.87 4.01E-02
Cell phone use in a wk
139
5.50
Int. cell phone, beeper, and voice use in a wk
118
Voice mail use in a wk
Statistic
Statistic
.49
.237
.16
1.94
3.745
5.51
.20
2.22
4.936
140
6.37
.10
1.18
1.401
Fax use in a wk
145
5.45
.11
1.37
1.888
Beeper use in a wk
105
4.84
.23
2.40
5.752
E-mail use in a wk
128
4.08
.17
1.88
3.521
E-mail with attached file use in a wk
107
2.41
.16
1.67
2.792
WWW resources use in a wk
124
3.71
.18
1.95
3.801
WWW posted page use in a wk
124
3.69
.21
2.29
5.258
87
2.02
.21
1.99
3.976
130
5.15
.19
2.22
4.906
PDA use in a wk
PC access use in a wk
Valid N (listwise)
57
7
To what extent do you access these technologies on the road (question 3)?
not at all
Count
%
2
Count
3
%
Count
some extent
%
Count
%
5
Count
%
Telephone
on the
road
27 22.0%
5 4.1%
6 4.9%
30 24.4%
10
Cell
phone on
the road
10
1
1
22 15.9%
14 10.1%
Int cell
phone,
beeper,
and voice
on the
road
25 23.4%
Voice
mail on
the road
14 10.6%
Fax on
the road
56 50.5%
Beeper on
the road
7.2%
.7%
2 1.9%
.7%
4 3.7%
8.1%
Count
6
%
Count
%
4.9%
39 31.7%
17 12.3%
73 52.9%
7.5%
11 10.3%
.8%
21 15.9%
14 10.6%
11 9.9%
4 3.6%
20 18.0%
4
3.6%
28 25.9%
4 3.7%
6 5.6%
11 10.2%
9
8.3%
E-mail on
the road
62 59.6%
8 7.7%
5 4.8%
16 15.4%
3
2.9%
3
2.9%
7
6.7%
E-mail w/
attached
files on
the road
72 76.6%
7 7.4%
1 1.1%
6
6.4%
2
2.1%
3
3.2%
3
3.2%
WWW
resources
on the
road
68 64.8%
10 9.5%
7 6.7%
9
8.6%
4
3.8%
3
2.9%
4
3.8%
WWW
posted
page on
the road
70 66.7%
7 6.7%
6 5.7%
11 10.5%
4
3.8%
2
1.9%
5
4.8%
PDA on
the road
69 77.5%
4 4.5%
2 2.2%
5.6%
1
1.1%
3
3.4%
5
5.6%
PC access
on the
road
60 56.6%
3 2.8%
6 5.7%
11 10.4%
4
3.8%
6
5.7%
1
8
a very great
extent
6
5
8
9
8.4%
48 44.9%
20 15.2%
62 47.0%
3
2.7%
13 11.7%
12 11.1%
38 35.2%
16 15.1%
To what extent do you access these technologies on the road (question 3)?
N
Mean
Std. Deviation Variance
Statistic Statistic Std. Error
Statistic
Statistic
Telephone on the road.
123
4.34
.21
2.29
5.243
Cell phone on the road.
138
5.70
.15
1.79
3.191
Int cell phone, beeper, and voice on the road.
107
4.84
.24
2.46
6.041
Voice mail on the road.
132
5.49
.17
1.92
3.702
Fax on the road.
111
2.69
.20
2.12
4.505
Beeper on the road.
108
4.45
.24
2.47
6.082
E-mail on the road.
104
2.30
.19
1.90
3.609
94
1.72
.16
1.58
2.482
WWW resources on the road.
105
2.01
.16
1.68
2.836
WWW posted page on the road.
105
2.03
.17
1.73
3.009
89
1.81
.19
1.75
3.065
106
2.79
.23
2.34
5.480
E-mail w/ attached files on the road.
PDA on the road.
PC access on the road.
Valid N (listwise)
62
9
To what degree does your working relationships help you to be more effective (question 9)?
not very
helpful
Count
%
2
Count
helpful to
some degree
3
%
Count
%
Count
%
5
Count
6
%
Count
very helpful
%
Count
%
Relationship
w/ attorneys
helps to be
more
effective
3
2.2%
4
2.9%
2
1.5%
28 20.4%
14 10.2%
34 24.8%
52 38.0%
Relationship
w/ outside
agents helps
to be more
effective
4
2.9%
5
3.6%
8
5.8%
25 18.2%
14 10.2%
40 29.2%
41 29.9%
Relationship
w/ inside
agents helps
to be more
effective
3
2.2%
2
1.5%
3
2.2%
20 14.7%
18 13.2%
35 25.7%
55 40.4%
Relationship
w/ mortgage
officers helps
to be more
effective
4
3.0%
3
2.3%
8
6.0%
20 15.0%
15 11.3%
31 23.3%
52 39.1%
13 11.8%
9
8.2%
21 19.1%
Relationship
w/ title
companies
helps to be
more
effective
Relationship
w/ home
inspectors
helps to be
more
effective
40 36.4%
7
9
8.2%
6
5.5%
12 10.9%
5.2%
8
5.9%
8
5.9%
26 19.3%
24 17.8%
26 19.3%
36 26.7%
Relationship
w/ appraisers
helps to be
more
effective
17 13.1%
12
9.2%
8
6.2%
30 23.1%
19 14.6%
18 13.8%
26 20.0%
Relationship
w/
newspapers
helps to be
more
effective
26 20.8%
13 10.4%
14 11.2%
18 14.4%
17 13.6%
15 12.0%
22 17.6%
Relationship
26 21.3%
22 18.0%
25 20.5%
16 13.1%
12
10
9.8%
8
6.6%
13 10.7%
w/
community
development
organizations
helps to be
more
effective
Relationship
w/ GSAR
helps to be
more
effective
15 11.8%
Relationship
w/ National
realtors
association
(Realtor.com)
helps to be
more
effective
24 19.7%
5
3.9%
17 13.4%
14 11.0%
20 15.7%
23 18.1%
33 26.0%
15 12.3%
17 13.9%
22 18.0%
13 10.7%
10
8.2%
21 17.2%
Relationship
w/ Past
customers
helps to be
more
effective
3
2.2%
1
.7%
6
4.4%
35 25.9%
15 11.1%
30 22.2%
45 33.3%
Relationship
w/ buyers
help to be
more
effective
4
2.9%
2
1.5%
3
2.2%
26 19.1%
14 10.3%
30 22.1%
57 41.9%
Relationship
w/ sellers
help to be
more
effective
3
2.2%
2
1.5%
3
2.2%
27 20.1%
13
28 20.9%
58 43.3%
9.7%
To what degree does your working relationships help you to be more effective (question 9)?
N
Mean
Statistic Statistic
Std.
Error
Std.
Deviation
Variance
Statistic
Statistic
Relationship w/ attorneys helps to be more
effective
137
5.60
.13
1.52
2.301
Relationship w/ outside agents helps to be more
effective
137
5.36
.14
1.61
2.586
Relationship w/ inside agents helps to be more
effective
136
5.74
.12
1.43
2.059
Relationship w/ mortgage officers helps to be
133
5.56
.14
1.61
2.582
11
more effective
Relationship w/ title companies helps to be more
effective
110
3.11
.20
2.09
4.355
Relationship w/ home inspectors helps to be more
effective
135
5.03
.15
1.75
3.074
Relationship w/ appraisers helps to be more
effective
130
4.38
.18
2.00
3.990
Relationship w/ newspapers helps to be more
effective
125
3.96
.19
2.15
4.635
Relationship w/ community development
organizations helps to be more effective
122
3.34
.18
1.94
3.765
Relationship w/ GSAR helps to be more effective
127
4.73
.18
2.02
4.071
Relationship w/ National realtors association
(Realtor.com) helps to be more effective
122
3.81
.19
2.09
4.386
Relationship w/ Past customers helps to be more
effective
135
5.43
.13
1.50
2.247
Relationship w/ buyers help to be more effective
136
5.66
.13
1.54
2.359
Relationship w/ sellers help to be more effective
134
5.69
.13
1.50
2.259
Valid N (listwise)
95
12
In a typical home sale, how important is the participation of: (question 13)?
not at all
Count
%
2
Count
3
%
Count
some extent
%
Count
Participation
of attorneys
1
.7%
1
.7%
4
2.8%
Participation
of outside
agents
4
2.8%
1
.7%
5
3.5%
Participation
of inside
agents
6
4.3%
3
2.2%
4
2.9%
1
.7%
2
1.4%
Participation
of mortgage
officers
9
%
Count
%
Count
%
Count
%
32 22.5%
87 61.3%
20 14.2%
18 12.8%
39 27.7%
54 38.3%
20 14.4%
19 13.7%
32 23.0%
55 39.6%
4.3%
37 26.4%
88 62.9%
4.3%
8
a very great
extent
6
5.6%
6
6.3%
5
6
Participation
of title
companies
10
8.2%
10
8.2%
10
8.2%
16 13.1%
14 11.5%
20 16.4%
42 34.4%
Participation
of home
inspectors
1
.7%
2
1.4%
4
2.8%
10
7.1%
23 16.3%
36 25.5%
65 46.1%
Participation
of appraisers
2
1.4%
3
2.1%
4
2.9%
7
5.0%
27 19.3%
33 23.6%
64 45.7%
14 11.1%
11
8.7%
25 19.8%
17 13.5%
6
4.8%
13 10.3%
8
6.0%
19 14.2%
11
8.2%
78 58.2%
Participation
of
newspapers
Participation
of MLS
40 31.7%
6
4.5%
3
2.2%
9
6.7%
Participation
of
community
develepment
organizations
52 43.3%
20 16.7%
21 17.5%
15 12.5%
Participation
of GSAR
25 19.4%
18 14.0%
11
8.5%
10
7.8%
21 16.3%
12
9.3%
32 24.8%
Participation
of national
realtors
association
(Realtor.com)
37 31.1%
21 17.6%
20 16.8%
11
9.2%
13 10.9%
6
5.0%
11
Participation
of past
customers
18 14.3%
14 11.1%
20 15.9%
16 12.7%
18 14.3%
15 11.9%
25 19.8%
10
24 17.4%
94 68.1%
Participation
of buyers
2
1.4%
2
1.4%
6
13
4.3%
7
5.8%
7.2%
5
4.2%
9.2%
Participation
of sellers
2
1.5%
2
1.5%
1
.7%
14
6
4.4%
10
7.3%
23 16.8%
93 67.9%
In a typical home sale, how important is the participation of: (question 13)?
N
Mean
Statistic Statistic
Std.
Error
Std.
Deviation
Variance
Statistic
Statistic
Participation of attorneys
142
6.28
9.91E02
1.18
1.395
Participation of outside agents
141
5.70
.12
1.46
2.142
Participation of inside agents
139
5.58
.14
1.62
2.636
Participation of mortgage officers
140
6.43
8.06E02
.95
.909
Participation of title companies
122
4.98
.18
2.02
4.082
Participation of home inspectors
141
5.98
.11
1.26
1.578
Participation of appraisers
140
5.92
.11
1.35
1.814
Participation of newspapers
126
3.28
.18
2.04
4.154
Participation of MLS
134
5.81
.15
1.73
2.995
Participation of community develepment
organizations
120
2.38
.15
1.60
2.556
Participation of GSAR
129
4.15
.20
2.27
5.173
Participation of national realtors association
(Realtor.com)
119
3.03
.18
1.98
3.914
Participation of past customers
126
4.17
.18
2.07
4.300
Participation of buyers
138
6.39
9.99E02
1.17
1.379
Participation of sellers
137
6.36
.10
1.21
1.469
Valid N (listwise)
97
15
To what extent do you use each of the technologies in marketing the listing of home (question 17)?
not at all
Count
%
2
Count
3
%
Count
some extent
%
Count
%
5
Count
a very great
extent
6
%
Count
%
Count
%
Use of email in
marketing
the listing
33 25.2%
18 13.7%
8
6.1%
19 14.5%
23 17.6%
11
8.4%
19 14.5%
Use of
WWW in
marketing
the listing
20 15.2%
10
7.6%
9
6.8%
25 18.9%
14 10.6%
20 15.2%
34 25.8%
Use of
WWW
site in
marketing
the listing
43 35.8%
8
6.7%
11
9.2%
13 10.8%
10
8.3%
10
8.3%
25 20.8%
Use of
virtual
walk
throughs
in
marketing
the listing
62 53.9%
9
7.8%
11
9.6%
5
4.3%
7
6.1%
4
3.5%
17 14.8%
Use of email w/
attached
files in
marketing
the listing
64 52.9%
12
9.9%
15 12.4%
10
8.3%
6
5.0%
6
5.0%
1
.7%
4
2.9%
6
4.4%
12
8.8%
Use of
MLS in
marketing
the listing
3
2.2%
16
8
6.6%
111 81.0%
To what extent do you use each of the technologies in marketing the listing of a home (question 17)?
N
Mean
Statistic Statistic
Std.
Error
Std.
Deviation
Variance
Statistic
Statistic
Use of e-mail in marketing the listing
131
3.69
.19
2.15
4.632
Use of WWW in marketing the listing
132
4.51
.19
2.13
4.542
Use of WWW site in marketing the listing
120
3.58
.22
2.40
5.742
Use of virtual walk throughs in marketing the
listing
115
2.70
.21
2.27
5.157
Use of e-mail w/ attached files in marketing
the listing
121
2.44
.18
1.93
3.715
Use of MLS in marketing the listing
137
6.57
9.82E02
1.15
1.321
Internet technology use q1
144 3.8899
.1341
1.6093
2.590
Mobile commnication use q1
129 5.2907
.1779
2.0211
4.085
Internet technologies q18
137 3.1460
.1554
1.8184
3.307
Valid N (listwise)
95
17
To what extent do you use each of the technologies in closing a home (question 17)?
not at all
Count
%
2
Count
3
%
Count
Use email in
closing
71 55.9%
17 13.4%
Use
WWW
in
closing
99 78.6%
11
8.7%
9
Use
hosting
WWW
site in
closing
99 83.2%
9
7.6%
Use
virtual
walk
throughs
in
closing
85 71.4%
10
Use email w/
attached
files in
closing
93 78.8%
Use
MLS in
closing
51 44.0%
some extent
%
Count
14 11.0%
%
5
Count
a very great
extent
6
%
Count
%
Count
%
9 7.1%
9 7.1%
4 3.1%
3
2.4%
7.1%
3 2.4%
2 1.6%
1
.8%
1
.8%
8
6.7%
2 1.7%
1
.8%
8.4%
6
5.0%
1
.8%
2 1.7%
3 2.5%
10
8.5%
11
9.3%
1
.8%
1
1
9
7.8%
8
6.9%
11 9.5%
18
.8%
7 6.0%
.8%
6 5.2%
12 10.1%
1
.8%
24 20.7%
To what extent do you use each of the technologies in closing a home (question 17)?
N
Mean
Statistic Statistic
Std.
Error
Std.
Deviation
Variance
Statistic
Statistic
Use of e-mail in marketing the listing
131
3.69
.19
2.15
4.632
Use of WWW in marketing the listing
132
4.51
.19
2.13
4.542
Use of WWW site in marketing the listing
120
3.58
.22
2.40
5.742
Use of virtual walk throughs in marketing the
listing
115
2.70
.21
2.27
5.157
Use of e-mail w/ attached files in marketing
the listing
121
2.44
.18
1.93
3.715
Use of MLS in marketing the listing
137
6.57
9.82E02
1.15
1.321
Use e-mail in closing
127
2.15
.15
1.64
2.684
Use WWW in closing
126
1.45
9.47E02
1.06
1.130
Use hosting WWW site in closing
119
1.30
7.22E02
.79
.620
Use virtual walk throughs in closing
119
2.01
.18
1.98
3.907
Use e-mail w/ attached files in closing
118
1.42
9.28E02
1.01
1.016
Use MLS in closing
116
3.24
.23
2.44
5.941
Internet technology use q1
144 3.8899
.1341
1.6093
2.590
Mobile commnication use q1
129 5.2907
.1779
2.0211
4.085
Internet technologies q18
137 3.1460
.1554
1.8184
3.307
Valid N (listwise)
79
19
To what extent are your interactions with those listed determined by formal contractual agreements (question 27)?
not at all
Count
%
2
Count
3
%
Count
Use e-mail
in closing
71 55.9%
17 13.4%
Use WWW
in closing
99 78.6%
11
8.7%
9
Use
hosting
WWW site
in closing
99 83.2%
9
7.6%
Use virtual
walk
throughs in
closing
85 71.4%
10
Use e-mail
w/
attached
files in
closing
93 78.8%
Use MLS in
closing
51 44.0%
some extent
%
Count
Count
a very great
extent
6
%
Count
%
Count
%
9
7.1%
9
7.1%
4
3.1%
3
2.4%
7.1%
3
2.4%
2
1.6%
1
.8%
1
.8%
8
6.7%
2
1.7%
1
.8%
8.4%
6
5.0%
1
.8%
2
1.7%
3
2.5%
10
8.5%
11
9.3%
1
.8%
1
.8%
1
.8%
9
7.8%
8
6.9%
11
9.5%
7
6.0%
6
5.2%
24 20.7%
3.8%
4
3.0%
8
6.0%
19 14.3%
12
9.0%
21 15.8%
64 48.1%
Interactions
with
agents in
your
agency
determined
by formal
contractual
agreements
34 25.6%
4
3.0%
19 14.3%
21 15.8%
14 10.5%
Interactions
with other
agents
determined
by formal
contractual
agreements
31 23.5%
3
2.3%
10
7.6%
23 17.4%
4
3.0%
4
3.0%
13
Interactions
with broker
determined
by formal
contractual
agreements
Interactions
with buyer
client
5
3
2.2%
14 11.0%
%
5
20
9.7%
9
12 10.1%
1
.8%
6.8%
32 24.1%
17 12.9%
15 11.4%
33 25.0%
14 10.4%
29 21.6%
67 50.0%
determined
by formal
contractual
agreements
Interactions
with seller
client
determined
by formal
contractual
agreements
1
.7%
6
4.5%
11
8.2%
22 16.4%
94 70.1%
8.3%
12
9.0%
14 10.5%
84 63.2%
Interactions
with seller
determined
by formal
contractual
agreements
5
3.8%
2
1.5%
5
3.8%
11
Interactions
with buyer
determined
by formal
contractual
agreements
9
6.8%
4
3.0%
7
5.3%
16 12.0%
19 14.3%
17 12.8%
61 45.9%
20 19.2%
7
6.7%
11 10.6%
14 13.5%
12 11.5%
17 16.3%
23 22.1%
Interactions
with other
brokers
determined
by formal
contractual
agreements
To what extent are your interactions with those listed determined by formal contractual agreements
(question 27)?
N
Mean
Std.
Error
Std.
Deviation
Variance
Statistic
Statistic
Statistic
Statistic
Use of e-mail in marketing the listing
131
3.69
.19
2.15
4.632
Use of WWW in marketing the listing
132
4.51
.19
2.13
4.542
Use of WWW site in marketing the listing
120
3.58
.22
2.40
5.742
Use of virtual walk throughs in marketing the
listing
115
2.70
.21
2.27
5.157
Use of e-mail w/ attached files in marketing
the listing
121
2.44
.18
1.93
3.715
Use of MLS in marketing the listing
137
6.57
9.82E02
1.15
1.321
Use e-mail in closing
127
2.15
.15
1.64
2.684
21
Use WWW in closing
126
1.45
9.47E02
1.06
1.130
Use hosting WWW site in closing
119
1.30
7.22E02
.79
.620
Use virtual walk throughs in closing
119
2.01
.18
1.98
3.907
Use e-mail w/ attached files in closing
118
1.42
9.28E02
1.01
1.016
Use MLS in closing
116
3.24
.23
2.44
5.941
Internet technology use q1
144
3.8899
.1341
1.6093
2.590
Mobile commnication use q1
129
5.2907
.1779
2.0211
4.085
Internet technologies q18
137
3.1460
.1554
1.8184
3.307
Valid N (listwise)
79
22
Indicate the extent to which you outsource or subcontract: (question 33).
not at all
Count
%
2
Count
3
%
Count
some extent
%
Count
%
5
Count
a very great
extent
6
%
Count
%
Count
%
Outsource
listing the
house
98 77.8%
12
9.5%
4 3.2%
6 4.8%
1
.8%
3 2.4%
2 1.6%
Outsource
marketing of
the listing
93 73.8%
14 11.1%
7 5.6%
4 3.2%
1
.8%
3 2.4%
4 3.2%
Outsource
finding
houses for a
buyer
94 74.6%
14 11.1%
3 2.4%
7 5.6%
3 2.4%
2 1.6%
3 2.4%
Outsource
helping a
buyer select
a house
96 76.2%
14 11.1%
3 2.4%
7 5.6%
2 1.6%
1
3 2.4%
100 79.4%
14 11.1%
4 3.2%
4 3.2%
1
.8%
3 2.4%
Outsource
removing
contract
contingencies
96 76.2%
13 10.3%
7 5.6%
3 2.4%
4 3.2%
3 2.4%
Outsource
closing the
sale of a
house
94 75.8%
13 10.5%
2 1.6%
7 5.6%
1
Outsource
negotiating a
contract
23
.8%
.8%
3 2.4%
4 3.2%
Indicate the extent to which you outsource or subcontract: (question 33).
N
Mean
Std. Deviation Variance
Statistic Statistic Std. Error
Statistic
Statistic
Outsource listing the house
126
1.55
.11
1.29
1.658
Outsource marketing of the listing
126
1.66
.13
1.44
2.067
Outsource finding houses for a buyer
126
1.64
.12
1.39
1.943
Outsource helping a buyer select a house
126
1.57
.12
1.30
1.703
Outsource negotiating a contract
126
1.44
.10
1.15
1.321
Outsource removing contract contingencies
126
1.56
.11
1.27
1.609
Outsource closing the sale of a house
124
1.65
.13
1.47
2.163
Valid N (listwise)
124
24