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Many thanks to those who responded to the request for discussion of the
questions posed last week about the data collection via ICTs on networks
and innovation diffusion to be gathered in GM, Ford, and DaimlerChyrsler.

Most of the responses were off-list, so I requested permission to post
them here in this summary.  Hope you can attend the Organizations and
Innovation session at INSA at 2pm on Wednesday next week to continue the
discussion.

We are grateful to the following colleagues for their expressions of
support in this effort:

Charles Kadushin <[log in to unmask]>
Ken Frank <[log in to unmask]>
Ronald E. Rice <[log in to unmask]>


Here are comments that addressed the questions in some detail:


Tom Valente <[log in to unmask]>:

This is a fantastic development.  Some ideas off the top of my head:

1) it would be helpful to track both ideas and behaviors, that is
knowledge about the innovations and their actual adoption.

2) collect data on innovations expected to spread rapidly and those
expected to diffuse slowly or not at all during the time frame.

3) will you supplement the online data collection with survey data? if
so you'll want the usual demographics as well as media use, both general
and technology specific.

4) you will also want an innovativeness scale and a leadership scale (I
can send both)

5) clearly organizational structures and physical locations will also be
important so the data should be supplemented with HR data on job
position, reporting responsibilities, etc.


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Siyuan Huang <[log in to unmask]>:

This sounds like a very interesting project!  I happen to be building a
computer simulation model on social network structure and diffusion of
innovation.  I'd be interested in several kinds of innovations,
innovations in communication technology, management procedures and
production procedures.

As for the network side, I think the strength of relationship
would be interesting to know, although measuring it may be challenging.
Also at the individual level, it would be great to know the personal
threshold in terms of adopting innovation.  By the way, will the data be
made available to researchers in general?  I will not attend the INSA
meeting this year, but would very much like to track the discussion.

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Emanuela Todeva <[log in to unmask]>


Colleagues,

Your project sounds very interesting. Regarding the questions, I have been
working on these for quite some time, and have offered a synthesis of
theories that map indicators of actors, relationships and structural
configurations in my book on Business Networks:

http://search.tandf.co.uk/ - and then search for <Todeva>.

This should give a very long list of categories that you may consider for
your database.

Looking forward to hear about the developments on the project.

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Mary Lang <[log in to unmask]>:

This sounds like a tremendous discovery opportunity.  We will be at
SUNBELT, and I will attend your session.  In the meantime, here are some
thoughts:


1.  What types of innovations would you most like to see tracked?

A)  Innovations in how technology is applied to enterprise challenges
(i.e.: moving from an applications-based approach to a service-based
approach; aka: service-based architectures "SOA").

B)  Innovations involving both emerging organizational ICT's along with
mature ICT's specifically [emerging] enterprise portals, wikis and blogs,
along with [established] email and collaboration platforms such as
LotusNotes; how do these ICT's impact innovations in the development of
"C" below?

C)  Innovations around new Product &/or Service Development as well as the
(accompanying) innovations in organizational design/structure to
support/sustain the new products and/or services.

2.  What parameters and attributes for data collection will be most
useful to you?

Would need to know more about your environment realities and constraints
to early answer this, but generally speaking, we value these attributes:


A)  Durability of results (i.e.: all the usual suspects to achieve high
confidence levels, i.e.: longitudinal vs. a series of anecdotal; large
diverse populations, etc.)

B)  Richness of results (i.e.:  again, the usual suspects for richness:
Multiple variable capture around each data point [like full spectrum node
descriptors of age, sex, culture, education, tenure {both organizational
and positional} and Clear and consistent descriptors of the innovations
being examined and their multiple dimensions)

C)  Reality of results (i.e.: when you say "IT log record" will that
include telephone logs?  Are the results going to be restricted to ONLY
those drawn from IT logs - will there be other overlays?  I.e.: how are
you avoiding the danger of achieving results that register high on the
"interesting" scale, yet low on the "reality" scale).


3.  How can the most comprehensive, valuable, and available database
possible be built?

A)  DISCOVER & DESIGN:   Ask (and re-ask), "what do the people who could
benefit most from the knowledge this research is building want to discover
in this space?", and "are we capturing the right data to make those
discoveries?"  Let those answers inform your design. Spend significant
time in the dataset design phase before moving into any actual collection.
Common sense, but we see researchers go at it reversed, collect and then
try to design around what they've collected and also forget that what is
"valuable" to an internal research team is not always seen in the same
light once results are released.

B)  VALIDATE: Your PI Team composition looks great, but you may want to
also consider throughout your work (and significantly in the design and
discovery phases) enhancing your team with practicing organizational
innovation and effectiveness professionals.


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Eric Quintane <[log in to unmask]>:

I am a PhD student in the management department at the University of
Melbourne, Australia.

Your research agenda looks great! Also, it is quite similar to what I am
currently investigating for my PhD, as I am looking email communication
patterns in a large organisation, and relating them to organizational
structure and innovativeness. I have already collected approximately
300,000 emails from a MNC in Europe and started to analyse the patterns of
communication.

There are many questions that I would like to ask you but first, I will
try to answer yours:

    1) Types of innovations: my favourite would be internally created
innovations, but in a diffusion analysis this may be difficult, therefore
I think most interesting would be knowledge intensive innovations, in
order to be able to track the flows of knowledge linked to their
diffusion.

    2) Parameters and attributes for data collection: I would really be
interested to have a picture of communication flows at three points in
time, before the introduction of an innovation, during the adoption of the
innovation and after the adoption. In this way it is possible to
understand:

1) the disruption of the communication created by the introduction of an
innovation,

2) the changes in the communication patterns occurring because of the
introduction of an innovation.

As such, email communication patterns, meeting logs, phone logs would be
very useful, with time, date, subject, sender name, recipient name,
existence and size of attachments. This should be linked to the date/time
at which each individual a) was first informed about the existence of the
innovation, b) adopted it.

    3) Database: in terms of format, I think that the Enron database is a
good example of a comprehensive and easy to use database
http://bailando.sims.berkeley.edu/enron_email.html
They use mysql and different tables for recipient, message, and sender. In
this case, if the data comes from different logs, different tables could
be created for the different logs in order to be able to compare the
communication patterns depending on the communication medium.

I would really be interested in seeing also organisational charts of the
departments that you will be including in your study, in order to be able
to relate the communication patterns to the formal position of employees
in the organisation. Additional employee information such as tenure,
education level, previous positions occupied, and gender would also be
useful.

My questions are around the type of tools that you will be using to
extract the IT log records. I have been using Emailnet to access email
communication patterns.

Which software package are you planning you use?

Do you plan to extract different types of logs?

Do you plan to have a longitudinal analysis of the email patterns?

If the information is made public I suppose that identification elements
will be removed from the dataset, how do you plan to achieve this, and at
the same time link the information that you are collecting to innovation
adoption measures and demographics?

How do you plan to resolve some of the technical difficulties linked to
the use of aliases, archiving procedures, viruses, spam and mailing lists?

Will you do the study in specific departments of each organisations?
If yes, how do you plan to select the departments?

What do you expect you total sample size to be?

How will you (and your team) inform the academic community of the
progresses of the project, and of the availability of the final
results/database?

Will you make the software that will be developed available to the
academic community?

I suppose that this may be an obvious question, but the technical solution
took me quite some time to workout: Will the identifier enable you to
pinpoint the individual on the formal structure? If you are interested in
that I can send you the procedure that I developed to create the
identifier in a way that keeps the formal structure information.

Thanks again for your answers and it is great that you are undertaking
this project.


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