Organizational Forms and Social Network Types –

A Framework for Analysis

Navneet Bhushan, Karthikeyan Iyer

navneet.bhushan@crafitti.com, karthikeyan.iyer@crafitti.com

Crafitti Consulting Private Limited, Bangalore, India

http://www.crafitti.com

(This paper was communicated to the Social Network Analysis Conference 2008 hosted by Tata

Institute of Social Sciences, Mumbai on Dec 26-27, 2008)

Abstract

Recent developments in society and business have triggered the emergence of new

forms of organizations, beyond the traditional hierarchical form. A study of

contemporary literature and industry practices reveals the following distinct forms:

hierarchical, ambidextrous, collaborative, learning and emergent. Simultaneously,

embedded within organizations are different types of social networks. Our research

indicates classifications of social networks along three key dimensions - the type of

response generated by these networks (customized response, modular response and

routine response), the centrality of the networks (ego-centric, socio-centric and

open networks) and the network architecture (centralized networks, request-based

networks, hub-swarms and swarms).This paper examines the relevance of social

network types to organizational forms. We have designed a survey instrument based

on the Analytic Hierarchy Process to solicit opinions of experts in the above areas.

Preliminary results of this initial survey clearly indicate that specific combinations

of social network types are found in particular organization forms. Potential

applications of this study towards organizational design and transformation are also

explored in the paper.

Introduction

The changing shape and form of organizations is a topic of considerable interest in recent times.

The reasons for the changes are multi-fold. Some argue that these changes have been

necessitated by the phenomenon of hyper-competition [1] that characterizes the nature of

disorder, stress and unpredictability that is confronting modern organizations. This phenomenon

is seen to arisen from the shift in economic growth cycles from the post-war economy to the new

economy based on technological drivers of information, communication and technology [2].

Along similar lines, others have pointed out that modern organizations are driven by

discontinuity rather than continuation and stabilization [3].

Along with competitive drivers, changes to organization form and shape have also been

influenced by social factors – primarily the organizational culture and climate, with its emphasis

on attitudes, values, feelings and social processes [5]. Organizational culture and climate are

greatly influenced by the leadership of the organization. At the same time they also get impacted

by prevalent cultures and climate in other organizations as well as by overall trends in social

culture.

Irrespective of the specific factors driving organizational change, it is clear that in the recent

past, new organizational forms have emerged. These new forms offer insights for organizational

design and change and are being seen as key drivers for innovation and growth.

Recent renewed interest in social network theory is a result of the new evidence that the way

large group of people behave collectively is not in a hierarchical structured manner as desired by

the proponents of hierarchical organization designers. In fact, the natural way we behave is more

close to a messy world of networks of complex connections. The new studies have shown variety

of social structures and processes that govern overall behavior of a group of population. These

social processes lead to different type of emergent properties that cannot be easily established by

studying only local individual interactions. This is in fact the hallmark of complex systems [26]

These two interesting trends of emerging new organization forms and various social network

structures – intuitively seem to be linked in some form. To study these relationships we have

used a framework based on the methodology of Analytic Hierarchy Process (AHP) [24, 25]. This

paper describes the framework and the initial results obtained so far. The paper is organized in

following sections – Section 2 gives a brief overview of emerging new organization forms and

also gives our understanding and for the purpose of this study our classification of the new

organization forms. In Section 3, an overview of various social network types and basis of these

different types are described. It also describes our understanding and classification of social

network types. Section 4, describes the methodology based on the AHP. Section 5 describes the

framework derived from the analysis of results obtained in the previous section. The paper ends

with Section 6 where potential applications of the framework are discussed and future steps are

identified.

2 New Forms of Organizations

Several new organizations forms have been proposed and discussed in literature [2]; while these

forms (clubbed together) offer a stark contrast to the regular hierarchical organizational form,

there are a few distinct types of new organizational forms that have been the subject of much

interest and study. Broadly, these may be classified as:

a) Ambidextrous Organization

b) Collaborative Organization

c) Learning Organization

d) Emergent Organization

2.1 Ambidextrous Organization

Ambidextrous organizations look at simultaneous exploration and exploitation as a means to

sustained performance and growth.

In order to successfully compete, they pursue a portfolio of innovations including:

a) Incremental Innovations: Small improvements in existing products or operations

b) Architectural innovations: Technology or process changes to fundamentally change a

component or element of business

c) Discontinuous innovations: Radical advances that may significantly alter the basis for

competition in an industry

For ambidexterity, the creation of project teams that are structurally independent units, each

having its own processes, structures and cultures, but integrated into the existing management

hierarchy i.e. connected at the top, has been recommended [8].

2.2 Collaborative Organization

These organizations look at collaboration as the means to achieve organizational goals. There is

great emphasis on team-based structures. Information pathways and flows between teams

(horizontally, vertically, internal, external) are widened and the boundaries and intersections are

exploited for value creation and innovation.

Three levels of collaborative work systems have been defined [7], each level increasing the

organization‟s capacity to serve its customers, employees and owners with an increase in

investment and results moving from left to right:

a) Traditional Teams

b) Team-based organizations

c) Collaborative Organizations

2.3 Learning Organization

These organizations focus on experimentation and learning as the key goals to be pursued. There

is a clear orientation towards the pursuit of perfection at all levels [14]. Knowledge (and thereby

change) is expected to be continuously created. “To create new knowledge means quite literally

to re-create the company and everyone in it in a nonstop process of personal and organizational

self-renewal. In the knowledge-creating company, inventing new knowledge is not a specialized

activity – the province of the R&D department or marketing or strategic planning. It is a way of

behaving, indeed a way of being, in which everyone is a knowledge worker – that is to say, an

entrepreneur.”[11]

Learning organizations use the following building blocks [13] to institutionalize learning:

a) A supportive learning environment

b) Concrete learning processes and practices

c) Leadership behavior that reinforces learning

Learning organizations tend to focus on systemic problem-solving as the means to competitive

excellence [10]. Learning and knowledge are transparently shared with the environment as a

long-term strategy for sustained growth and innovation [12].

2.4 Emergent Organization

Emergent organizations follow living system principles with focus on evolution. Boundaries are

ephemeral and created and destroyed as relevant. The organization is extremely receptive to

change and thrives on adapting to and creating change.

Emergent organizations are characterized by extra-ordinary decentralization [15]. They have also

therefore been described as open or boundary-less organizations or structures. The behavior of

emergent organizations is seen to bear similarities with swarm behavior seen in the natural

world, e.g. the intelligence embedded in the behavior of swarms of ants [16].

Much of recent evolution of social networks as a consequence of the growth in size, utility and

connectivity of the internet is being studied from the perspective of learning and application to

organizations. For instance, the development of user communities or information communities

has opened up multiple avenues for new businesses and business models (EBay, Google Ads).

Organizations have looked at emergent strategies to identify new products or services through

lead user innovations [17]. There are also interesting explorations of how a relatively small

number of key opinion influencers in social networks can determine the overall outcome or

direction of change for that network [18].

Table 1 summarizes the key differences between the five organization forms.

Table 1: Key Differences between Organizational Forms

Organization

Form

Hierarchical Ambidextrous Collaborative Learning Emergent

Key function Efficient

allocation of

resources

Balance growth

and efficiency

Information

flow, 1+1 > 2

Continuous

improvement

Evolution

Flow Uni-

directional,

top-down

Conditional Multi-

directional,

peer-to-peer

Cyclic, Directed

towards ideality

Natural, not

consciously

directed

Evolution Standard Tree The banyan tree Cross- Continuous Living system

hierarchy model Pollination

improvement,

pursuit of

perfection

principles

Knowledge Assumed to be

codified,

known

Some

knowledge

codified, some

to be obtained

Potential to be

maximized

through sharing

Knowledge to be

improved and

increased

continuously

Created as

needed

Interdependence Clear, closed

boundaries

Modular

architecture,

Clear, closed

boundaries

Fuzzy

boundaries

Clear but open

boundaries

Boundary-less

Detection of and

Response to

change

Central

detection and

intelligence,

command-

control, crisp

response,

detection and

response slow

for large org.,

fast for small

organizations

Multiple

antennae ready

for feedback,

multiple

intelligence

centres, crisp

response

Fuzzy,

democratic

response, some

change

absorbed, some

adapted,

detection and

response slow

but holistic

Clear yet

decentralized

detection and

response,

response strategic

Decentralized,

adaptive

response

3 Types of Social Networks

The informal connections formed in a large population leads to emergent structures that

sociologists term the formation of social networks. The social network theory has remained more

of a curiosity rather than a serious field to pursue, despite the work of Milgram [28], Granovetter

[27] and tipping point framework offered by Gladwell [18]. Recently, however, the work by

Duncan Watts [26] has brought the social network theory to the forefront. The need was also felt

as the world has become more connected and hence more networked. The organization structures

of the past are transforming naturally into different forms or structures that resemble more of the

networked form rather the hierarchical one.

Since then various researchers have studied the social networks and tried to distinguish between

various types of social networks based on desired response, centrality of the network and the

architecture of the network. In [23], networks in 60 different industries have been studied and

classified into three archetypes according to the response delivered by the Network. We

summarize these three types of social networks in Table 2 along three main parameters – the

types of problems and solutions encountered by the networks, the value delivered and illustrative

industries where these are likely to be found.

Table 2: Social Network Archetypes

Type --> Customized Response Modular Response Routine Response

Problems and Solutions Ambiguous Known components – but

combination or sequence

not known

Well-defined and

predictable

Value Quickly framing and

solving a problem in an

innovative way

Delivering a unique

response depending upon

the constellation of

expertise required by the

problem

Efficient and consistent

response to a set of

established problems

Examples New product dev,

investment banks, Strategy

consulting

Surgical teams, Law firms,

B2B sales

Call centers, insurance

claims processes

According to [21], social scientists have studied three types of networks – the ego centric, socio-

centric and open networks. The characteristics of the three types are shown in Table 3.

Table 3: Social Scientists Classification of Social Networks

Ego-Centric Networks Socio-Centric Networks Open-System Networks

Networks that are connected with a

single node or individual

Boundaries of the network are clear;

Networks in a Box

Boundaries are not necessarily clear

Example, My good friends, All

companies doing business with ABC

Example, students in a class,

employees of an organization

Example, network of elite class,

connections between corporations

Lists alone are insufficient – info

about connections also is required

Most studied in terms of fine points

of network structure

Most interesting and most difficult

to study

The shift to network form of organizations has become so prevalent that even the historically

most hierarchical form of human organization, i.e., military structures, are now beginning to

explore the network form of organizations to take care of increasingly complex situations and

foes that these forces are asked to tackle. The Network Centric Warfare as the field is now called

is a new form of military strategy, technologies, organization and doctrines that requires more

holistic explorations and understanding. The trend towards network form is clearly evident. In

[22], authors describe different forms of network centric warfare architectures that are possible.

Table 4 list down these architectures – which varies from centralized, where a central hub

controls the network, to a loosely coupled network structure where the elements or nodes come

together to solve a problem and then go back or move to next problem – through the process of

swarming.

Table 4: Taxonomy of Network Centric Warfare Architectures

Architecture Characteristics

A. Centralized One central high value Hub – other low value nodes networked and controlled

by Hub

B. Hub-Request “Type E” Request based plus one or more central high value hubs

C. Hub-Swarm “Type G” Swarming plus one of more central high value hubs

D. Joint Mixture of other six types (Type A, Type B, Type C, Type E, Type F and Type

G)

E. Request-Based Nodes of same value, but with different specialized capabilities. Request for

service between nodes of different kinds

F. Mixed Mixture of “Request-Based” and “Swarming”

F1: Limited Types Small number of node types (includes the case of separate sensor, engagement,

and C2 grids”

F2: Commonality Nodes are different, but have significant commonality

G. Swarming Nodes identical or nearly so

G1: Emergent Swarming Nodes follow simple rules, like insects

G2: Situationally Aware

Swarming

Nodes share information to build up Situational Awareness picture

G2(a): Orchestrated One node is a temporary “leader”

G2(b): Hierarchical Nodes are arranged in a Hierarchy

G2(c): Distributed No Leader or Hierarchy

The above discussion points to three key dimensions in which social networks have been studied

or classified in the literature. The three key dimensions are - (1) The type of response that these

networks generate i.e., what kind of output the networks can generate (three different type of

responses are Customised Response, Modular Response and Routine Response, (2) Second

dimension is the centrality of the networks - in this dimension also there are three types - Ego-

centric (individuals at the center with their network), Socio-Centric Networks where boundaries

of the network are clear and finally Open Networks where boundaries are not necessarily clear,

(3) Third dimension is the network architecture - where we have four options Centralized

networks, Request based networks, Hub swarms and Swarms. Combining these three dimensions

one can in principle get 3x3x4 = 36 different Network types. However we have selected finally 5

different types of Social Networks as described below.

Customized Response Open Swarms (CROSs): These types of social networks usually do not

have any clear boundaries (they are open). They have nearly identical nodes in terms of their

capabilities and authority. These nodes come together to respond to problems through a process

of creating shared awareness, quickly formulating the problems and solving problems by

leveraging each other's capabilities collectively. After problems are responded to they go to next

problems or keep on building their capabilities. These networks typically create customized

responses to unstructured problems.

Modular Response Socio-Centric Request-Based (MRSR): These types of social networks

have clear boundaries and typically generate solutions through a combination or re-sequencing of

components of the over-all solutions. They work in an environment when components of the

problems and solutions are known but constructing the solution requires combination of

components in a non-trivial way. Further the nodes of these networks have same value but

different capabilities and they respond to the problems by requesting each other to provide their

unique capabilities to solve problems through modularized responses.

Routine Response Ego-Centric Centralized (RECC): These types of social networks create

routine responses to structured problems. There is typically a centralized hub of high value

which has low value nodes connected. The centralized hubs of different sub-nets have their own

ego-centric networks based on the network of the leader of the hub. However the low value

nodes of a subnet do not connect to low-value nodes of other subnets.

Customized Response Socio-Centric Hub-Swarm (CuSHuS): These types of social networks

have one or more high value hubs besides large number of nearly equal value nodes. These

nearly equal value nodes swarm together for solving an unstructured problem with the high value

hubs. Each subnet may have its own high value hub and many equal value nodes that can create

shared picture of the problems which gets picked and responded to through swarming in a

slightly controlled manner.

Customized Response Open Request-Based (CROR): These types of social networks do not

have clear boundaries. However, customized response is created through a request based

mechanism.

The question we are exploring here is – which of these social network types are most likely to be

found in which type of organization forms as defined in Section 2. This mapping is of interest for

variety of purposes, and a framework to study this mapping may be useful. We describe the

methodology of developing such a framework using the technique of Analytic Hierarchy Process

(AHP) in Section 4.

4 Methodology

Let us formulate the problem. The question we need to answer is the following,

In each of the organization forms that we have defined in Section 2 – Hierarchical,

Ambidextrous, Collaborative, Learning and Emergent, what are the relative chances of finding

each of the social network types that we have defined in Section 3 – Customized Response Open

Swarms (CROSs), Modular Response Socio-Centric Request-Based (MRSR), Routine Response

Ego-Centric Centralized (RECC), Customized Response Socio-Centric Hub-Swarm (CuSHuS),

and Customized Response Open Request-Based (CROR).

Possible ways in which this question can be answered is – (a) to have direct measurement in real

life organization forms, (b) to make a mathematical model and solve it (c) to simulate the

organization forms and let the social networks emerge (d) to ask the experts and to use the

consensus of experts to reach to a high level mapping of social network types to organization

forms. The first three methods as of now have found to be infeasible hence we chose the opinion

of experts as a surrogate for actual measurement. For this purpose we have used the methodology

of Analytic Hierarchy Process (AHP). Before we define the methodology and results, in Section

4.1 we give a brief overview of AHP.

4.1 Analytic Hierarchy Process (AHP) – An Overview

AHP [24, 25] provides a means of decomposing the problem into a hierarchy of sub-problems

which can more easily be comprehended and subjectively evaluated. The subjective evaluations

are converted into numerical values and processed to evaluate each alternative on a numerical

scale. The detailed methodology of AHP can be explained in following steps:

Problem is decomposed into a hierarchy of categories and parameters.

Opinion is collected from experts corresponding to the hierarchic structure, in pair wise

comparison of alternatives on a qualitative scale. Expert can rate the comparison as equal,

marginally strong, strong, very strong, and extremely strong. The comparisons are made

for each criterion and converted into quantitative numbers on a 9 point scale.

The pair wise comparisons of various criteria generated at step 2 are organized into a

square matrix. The diagonal elements of the matrix are 1. The criteria in the ith

row is

better than criteria in the jth

column if the value of element (i,j) is more than 1; otherwise

criteria in jth

column is better than criteria in ith

row. The (j,i) element of the matrix is

reciprocal of (i,j) element.

The principal eigen value and the corresponding right eigen vector of the comparison

matrix gives the relative importance of various criteria being compared. The elements of

the normalized eigen vector are termed weights with respect to the criteria or sub criteria.

The consistency of the matrix is then evaluated. Comparisons made by this method are

subjective and AHP tolerates inconsistency through the amount of redundancy in the

approach. If this consistency index fails to reach a required level then answers to

comparisons may be re-examined. The consistency index, CI is calculated as

CI = (max – n)/ (n-1) (1)

Where, max is the maximum eigen value of the judgment matrix and n is the order of the

matrix. This CI is compared to that of a random matrix, RI. The ratio derived, (CI /RI) is

termed the consistency ratio (CR). It is suggested that the value of CR should be less that

0.1 [24, 25].

The ratings of each alternative is multiplied by the weights of the sub-criteria and aggregated to

get local ratings with respect to each criterion. The local ratings are then multiplied by weights of

the criteria and aggregated to get global ratings.

4.2 Derivation of Ratings from Expert Opinions

The social network ratings are derived from a process of consensus creation in inputs from

multiple experts. These experts have been involved in studying various organization forms and

also experienced in multiple social networks. However, there are variations in their views on

relative probability of the social network types. We present below the process of creating

consensus.

In the initial setting, 5 experts were chosen. These experts were given the background of the

model and information on organization forms and social network types. The experts were asked

to fill in the relative importance of each social network type for every organization form in pair

wise qualitative comparisons as shown in Fig. 1.

Fig 1. Pair wise comparisons from experts

Consistency Ratio of each matrix by each expert is checked and in kept below 0.1 as

recommended by the methodology. The final output using the AHP process from each of the

experts is given in the figures below.

As one can see from the above table, the experts differ from each other and there is no

consensus. The methodology calls for taking the normalized geometric mean as a basis for

consensus of experts. The Table below gives the geometric mean of the inputs from experts

using AHP.

The geometric means are normalized to get the final consensus rating of all the five experts. The

final consensus ratings are given below. The green marks are the top ranking social network

types that the experts feel will be found in specific organization forms. The orange marks are the

second ranked social network type that the experts feel will be found in the specific organization

forms. And finally the blue marks are the third ranked social network type that the experts

believe will be found in the specific organization forms.

4.3 The Results

The results obtained as shown in the Table above are represented as radar plots where each spoke

of the radar indicates one of the five social network types. The mapping of social network types

to each of the organization forms is explained below:

a) Hierarchical organization

forms are likely to have Routine

Response Ego-Centric

Centralized type (47.5%). as

well as Modular Response

Socio-Centric Request Based

type (30.9%) of social

networks.

b) In Ambidextrous organization

form, experts believe the Modular

Response Socio-centric Request-

based social network will be most

prevalent form (43.5%). It is

interesting to note that Customized

Response Socio-Centric Hub-

Swarm comes out to be distant second (21.4%) closely followed by Routine-response

Ego-centric Centralized (16.5%).

c) In the case of Collaborative

organization form, the Customized

Response Socio-centric Hub-

Swarm social network type wins

with 42.5%, distantly followed by

Customized response open swarms

(18.7%) and Customized response

open request based (18.5%) social

network types.

d) In the Learning organization form,

Customized Response Socio-Centric

Hub-Swarm wins with 43.7%

followed by Customized Response

Open Request-based with 24.9%

and Customized Response Open

Swarms with 17.2%.

e) In the Emergent organization form

Customized Response Open Swarms

with 45.4% wins followed by

Customized Response Open Request-

based with 24.9% and Customized

Response Socio-Centric Hub-Swarm

with 16.9%.

The consolidated picture that emerges when we combine all the five charts is shown in the figure

below.

While experts have differed with each other on several counts, it is interesting to note that the top

three social networks identified as most likely to be found in a particular form of organization are

consistent. This implies that the experts are differing in the degree to which a social network type

is likely to be found in a particular form of organization but are fairly in agreement on the types

of social networks that are likely to be found. Furthermore, the top 3 social network types for any

particular organizational form cover more than 75% of the relative weights. In combination,

these two results signify that there are clear associations or mapping between organizational

forms and social network types. As we move from hierarchical to emergent forms, there is

unambiguous change in the mappings to social network types.

5 The Framework for Analysis

5.1 Patterns in most likely combinations

Using the topmost relevant social network types in combination, it is possible to find the aspects

of social networks that are potentially critical to a particular organizational form.

a) Hierarchical form

This form is characterized by the absence of customized response and open type of social

networks. However, within the other forms there seems to be scope for freedom and

movement (routine and modular response, ego-centric and socio-centric, centralized and

request-based).

b) Ambidextrous form

This form is characterized by socio-centric and ego-centric social networks to some

extent (open type of social networks may make ambidexterity difficult). There is

considerable freedom with respect to all the other types of social networks. All types of

responses are valid, but there is movement away from routine responses and towards

customized responses. Similarly, all architectures are possible but there seems to be

movement away from centralized and towards hub-swarm type of architecture.

c) Learning form and Collaborative form

At the outset, experts seem to be associating the same combinations of social networks to

both these forms. Therefore, both of them are essentially characterized by customized-

response type of social networks. A deeper look however, reveals some interesting

differences. Learning organizations seem to have a preference towards request-based

architectures, while collaborative organizations are equally likely to involve swarm as

well as request-based architectures. In both learning as well as collaborative forms, there

seems to be a movement towards open social networks.

d) Emergent form

This form is characterized by customized-response open swarm types of social

networks. Request-based architecture may exist in some cases.

5.2 The existence of evolution paths

If one were to look at gradual change in the compositions of social network types in an

organization (this may happen by design or by accident in the real world) i.e. the second most

likely social network type gradually becomes more prevalent, and some previously non-existent

type of social network structure gets introduced), there seem to be clear evolution paths as

showed in the following figure:

a) Hierarchical organizations are most likely to evolve into ambidextrous organizations, if a

hub-swarm architecture gets introduced, as is necessary for exploratory capability.

b) Ambidextrous organizations may evolve into either learning or collaborative

organizations, if the social network is opened up beyond socio-centric networks. What

would trigger a specific movement towards learning or collaboration as the primary form

is difficult to assess. It seems that, if there is movement away from the swarm

architecture towards request-based architectures, learning-based approach may form the

primary focus, with collaboration as one of the means to achieve learning. On the other

hand, if swarm-based architectures continue to remain, it is likely that collaboration

becomes the primary driver, and learning is one of the many things achieved through

collaboration.

c) Collaborative organizations are more likely to morph into emergent forms, once the

transition from socio-centric hub-swarms to open swarms is complete. By the same

token, emergent organizations may revert to more controlled collaborative behavior if

there is a need for socio-centric networks to assume greater importance.

d) Learning organizations can gradually move towards more emergent forms once the

transition from socio-centric to open social networks is complete and request-based

architecture are supplemented with swarm-based architectures. In essence, this implies

the addition of the capability to learn from external, random, decentralized events in

addition to process driven learning.

6 Applications and future steps

There are several potential applications of this framework from an organizational design

perspective.

Firstly, this framework can help organizations start thinking about what is their current

form or type of organization and what do they want to be in the future. Simultaneously,

organizations can start observing the types of social networks that are prevalent.

Sometimes it may be difficult for organizations to determine their exact form; there may

be evidence to suggest that more than one form fits the bill. In such cases, the prevalent

types of social networks can offer a clue towards the essential form of the organization.

Once organizations are clear about “which form seems to fit best” and “what types of

social networks are prevalent”, they can use the framework to figure the path of evolution

they would like to take and correspondingly the changes to the organizational social

networks that they need to make. The framework gives clear guidelines to the types of

capabilities that need to be added and movements that need to be made in order to move

towards organizational forms more suitable to growth and innovation, based on the

organizational context.

Often, organizations struggle to extract the best out of their people because organizational

processes are not in sync with the way people work and interact on the ground. This

framework can be used by organizational leadership to redefine their understanding of the

form of their organization to synchronize with the nature of social networks prevalent.

The framework lends itself well to incremental application as well as part-application

(application to parts of the organization without affecting other parts); it does not require

whole-sale changes to the organizational design.

Most importantly, the framework is sufficiently flexible and open to fine-tuning and

modification by incorporating opinions of further more experts in the field. It is an

evolving framework and can be continually (or periodically) updated and used as a

strategic tool for organizational design feeding into organizational growth and

innovation.

While this is a preliminary framework that incorporates the opinions of a fairly small number of

experts (5 in number), the results are sufficiently interesting for us to pursue this research in

greater detail. The next steps are to broaden this research by getting opinions from a larger

community of experts and then (or simultaneously) apply the framework in live organizational

contexts. We also anticipate the need for mechanisms to objectively detect the types of social

networks prevalent in organizations as well as to identify portions of organizations most

receptive to the types of changes articulated in this paper.

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