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THESIS

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This is to certify that the

dissertation entitled

THE EFFECTS OF WEAK TIES ON PERCEIVED ORGANIZATIONAL
INNOVATIVENESS AND INNOVATION CHARACTERISTICS

presented by

Marcy Elisabeth Meyer

has been accepted towards fulfillment
of the requirements for

 

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7 , W

 

 

THE EFFECTS OF WEAK TIES ON PERCEIVED ORGANIZATIONAL
INNOVATIVENESS AND INNOVATION CHARACTERISTICS

By

Marcy Elisabeth Meyer

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Communication

1996

The Effects of Weak Ties on Perceived Organizational Innovativeness
and Innovation Characteristics

Marcy Elisabeth Meyer

DISSERTATION ABSTRACT
This longitudinal study examines the effects of weak ties on perceived organizational
innovativeness and innovation characteristics. Data were gathered at four points in time
from self-report questionnaires completed by organizational members (11 = 90) within the
Cancer Information Service (C18), 3 geographically-dispersed government health
information agency that is implementing innovative intervention strategies to disseminate
cancer information to traditionally underserved sectors of the public. Results indicate
that individual perceptions about innovation and innovativeness are diffused in
organizations through informal communication structure. However, the impact of weak
ties on perceptions of innovation characteristics and perceived organizational
innovativeness is not immediate; the most notable impact of weak ties is produced by
unexpected lag effects. These findings suggest that informal communication structure
has long term rather than short term effects on organizational innovativeness. Further,
functional role differences reveal the existence of groups who play key roles in the
innovation process. Results are discussed in terms of challenges that managers face in

orchestrating innovation-related communication.

ACKNOWLEDGEMENTS

I would like to first thank Adam and Gavin for their love and support. Without
them, this work would have not been possible.

Next, I would like to thank the members of my doctoral committee. In particular,
I would like to extend special gratitude to Dave Johnson for his support and guidance.
Without his direction, this dissertation would have lacked STRUCTURE. I remain
deeply indebted to Jim Dearing, Chuck Atkin, and Pennie Foster-Fishman for the
valuable contributions that they made to this work.

Thanks also go to the staff of the CIS/CISRC for participating in this study,
particularly the members of the Network Analysis Advisory Board who helped
throughout the many phases of the research process.

Finally, I would like to thank my fellow research team members, Betty La France,
Carolyn Ethington, Hui-Jung Chang, and Susan Pobocik, without whom this work would

not have been half as much fun.

iii

TABLE OF CONTENTS

LIST OF TABLES
LIST OF FIGURES

INTRODUCTION
The Nature of Organizational Innovation

Preview of the Study

CHAPTER 1
REVIEW OF THE LITERATURE
Fifty Years of Innovation Research
Innovation Outcomes
Predictors of Perceived Innovation Outcomes
Informal Communication Structure
Weak Ties
Range
Prominence
Key Roles in the Innovation Process
Perceived Organizational Innovativeness
Innovation Attributes
Reconceptualizing Innovation Attributes:
The Pros and Cons of Innovation
A Model of Effects of Weak Ties on Perceived Organizational
Innovativeness and Innovation Characteristics

CHAPTER 2
METHODS
Setting
The Cancer Information Service
Innovation in the Cancer Information Service
Sample Characteristics
Survey Procedure
Sampling Interval
Measurement
Network Variables
Psychometric Indicants
Perceived Organizational Innovativeness
Pros and Cons of Innovation

iv

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Analysis
STRUCTURE
Confirrnatory Factor Analysis
Weak Ties
Perceived Organizational Innovativeness
Pros and Cons of Innovation

CHAPTER 3

RESULTS
Descriptive Statistics
A Test of the Model “Short Term Effects of Weak Ties”
The Revised Model “Long Term Effects of Weak Ties”

CHAPTER 4
DISCUSSION
Summary
Functional Role Differences
The Political Context of Innovation
Resistance to Change
Limitations
Implications for Future Research
Implications for Practitioners

FOOTNOTE

APPENDICES
Appendix A - Tables
Appendix B - Figures
Appendix C - CISRC Chronology
Appendix D - February 1994 CISRC Communication Log
Appendix E - August 1995 CISRC Communication Log
Appendix F - CIS Innovation Survey
Appendix G - CISRC Innovation Characteristics Survey

REFERENCES

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LIST OF TABLES

Table 1 - Overview of the Major Goals and Objectives of the
Cancer Information Service

Table 2 - Demographics for the Cancer Information Service

Table 3 - Items, Factor Loadings, and Reliabilities for Weak Ties

Table 4 - Internal Consistency Error Matrix for Weak Ties

Table 5 - Items, Factor Loadings, and Reliabilities for Perceived Organizational
Innovativeness

Table 6 - Internal Consistency Error Matrices for Perceived Organizational
Innovativeness

Table 7 - Items, Factor Loadings, and Reliabilities for Pros

Table 8 - Internal Consistency Error Matrices for Pros

Table 9 - Items, Factor Loadings, and Reliabilities for Cons

Table 10 - Internal Consistency Error Matrices for Cons

Table 11 - Descriptive Statistics among Variables

Table 12 - Path Coefficients and Confidence Intervals for Model 1

“Short Term Effects of Weak Ties“

Table 13 - Error Matrix for Model 1 “Short Term Effects of Weak Ties”

Table 14 - Error Matrix for Model 2 “Long Term Effects of Weak Ties”

Table 15 - Path Coefficients and Confidence Intervals for Model 2

“Long Term Effects of Weak Ties“
Table 16 - Functional Role Differences in Weak Ties and Perceptions of

Innovation Characteristics

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LIST OF FIGURES

Figure 1 - The Effects of Weak Ties on Perceived Organizational
Innovativeness and Innovation Characteristics

Figure 2 - Project 2 Timeline

Figure 3 - Overview of the Cancer Information Service Network

Figure 4 - Model 1 “Short Term Effects of Weak Ties”

Figure 5 - Model 2 “Long Term Effects of Weak Ties”

vii

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INTRODUCTION

The CIS must remain sturdy yet flexible, stable yet progressive to meet the
challenges in the field of cancer communication in the 1990's and to have an
impact on that challenge. As the CIS W (emphasis added)
the new program concept, it will continue to be a template for national and
international health communications programs for the 1990s and beyond (Morra

etaL,l993,p.32)

The Nature of Organizational Innovation

Innovation has been defined as "an idea, practice, or object that is perceived as
new by an individual or other unit of adoption" (Rogers, 1983, p. l 1)1. Perhaps the most
compelling justification for studying organizational innovation is that organizations are
expected to innovate if they are to survive in today's rapidly changing environment
(Johnson, 1993). According to Deal & Kennedy, innovation enhances the corporate
image of modernity and vitality: “Change has become such a regular activity in the
business world that companies suddenly become suspect if they stay the same” (1982, p.
157). Government organizations, as well as private industry, are experiencing similar
pressures to reinvent themselves (e.g., Osborne & Gaebler, 1993). Increasingly,
innovation researchers have examined innovations developed as a means to make US
businesses or governmental agencies more competitive in an increasingly complex global
economy (Rakow & Navarro, 1993; Johnson, Donohue, Atkin, & Johnson, 1995). In

contrast, perhaps because of an over-emphasis on the desired outcomes associated with

successful innovation implementation, there is a lack of research that studies failed
innovations (Kanter, 1983; Weenig and Midden, 1991).

Currently, organizational scholars are placing emphasis on the need for
longitudinal studies of the process of organizational innovation (Huber & Van de Ven,
1995). It is by examining the antecedents and consequences of innovation, as well as the
ways in which innovation is generated, adopted, implemented, reinvented, or rejected that
we can begin to understand the nature of organizational innovation, along with its
subsequent successes and failures.

Preview of the Study

In this longitudinal study, weak ties, representing informal communication
structural indices, perceived organizational innovativeness, and perceptions of innovation
characteristics form a useful framework with which to examine perceived outcomes of
organizational innovation. Over four points in time, organizational members' weak ties
are examined with respect to: 3) their impact on the extent to which organizational
members consider their organization to be innovative in general, and b) the extent to
which they affect organizational members' perceptions of specific innovation
characteristics. In addition, this study examines the extent to which an innovative climate
is a predictor of the degree to which organizational members will be supportive of a
particular innovation. Longitudinally, this research explores the degree to which
organizational members form general perceptions about organizational innovativeness
based on their experience with a specific innovation. On the basis of our knowledge
about the relationship between organizational members' communication patterns and their
perceptions about innovation characteristics and organizational innovativeness, we can
begin to understand the process by which innovation is generated, adopted, implemented,

reinvented, and rejected through communication in an organizational setting.

The following section reviews relevant research on innovation, considers the
relationships between weak ties, perceived organizational innovativeness, and innovation

characteristics over time, and identifies key roles in the innovation process.

CHAPTER ONE
REVIEW OF THE LITERATURE
Fifiy years of innovation research

Much of the existing research on the phenomenon of innovation is summarized by
Rogers' review of the diffusion literature in which he constructs a theoretical framework
for the study of innovation (Rogers, 1983). Rogers defines innovation as "an idea,
practice, or object that is perceived as new by an individual or other unit of adoption"
(1983, p. 11)1. According to Rogers, early scholars in the field of rural sociology can
largely claim credit for laying the intellectual foundation used to guide research about the
diffusion of innovation. In particular, maverick researchers Ryan and Gross (1943)
investigated the spread of new agricultural techniques among midwestem farmers.

In these early diffusion studies, the diffusion of innovation was viewed as a
process by which new ideas spread among individuals in a larger social system. Many
early studies described innovations in terms of their characteristics and potential adopters
in terms of sociodemographic variables (Kivlin & Fliegel, 1967; Allan & Wolf, 1978).
At the outset, organizational innovativeness studies had their shortcomings: Research
methodologies copied from individual-level diffusion studies resulted in the outcome
variable, innovativeness, being measured as an organization's composite score aggregated
across innovations. This operationalization of innovation effectively removed the
process aspects of innovation adoption as well as the unique elements of individual
innovations (Rogers, 1983). Without intending to, these studies equated individual
adoption with organizational adoption, when they should have equated individual
adoption with organizational implementation. In addition, data were typically gathered
only from the top executive of the organization under analysis (Bach, 1989). This static,
top-down approach to data collection created at best an incomplete picture of

organizational innovation behavior.

According to Van de Ven and Rogers (1988), an important turning point for
innovation research was reached in the 1970's when innovation studies were initiated in
an organizational context. With this outgrth came three notable developments to
innovation studies: a focus on the organization, rather than the individual in a larger
social system, as the unit of adoption; a stress on innovation implementation over
innovation adoption; and an emphasis on process research rather than variance research, a
shift that drew attention to the temporal stages in the adoption process. Over the past two
decades, organizational studies have addressed innovation as it relates to issues such as
organizational climate, new technology, and structural properties of communication
networks (Weenig & Midden, 1991). Organizational communication researchers have
studied innovation as an outcome of the systemic functioning of communication networks
(Johnson, 1993). If we hope to understand innovation as a process that occurs over time,
through communication, within a social context (Rogers, 1983), there is a need to
examine causal processes related to innovation, specifically the ways in which individual
perceptions about innovations are diffused through communication in an organizational
setting over time to affect innovation adoption and implementation.

Innovation Outcomes

Innovation outcomes, or consequences of innovation, are the changes that occur in
an organization as a result of the adoption or implementation of an innovation. While
desired outcomes might include increased efficiency, effectiveness, productivity,
technical development, or increased ability to innovate, such consequences are
experienced subjectively by organizational members, so it is essential to differentiate
between actual and perceived outcomes. There is very limited research in the area of the
perceived effectiveness of an innovation compared with actual effectiveness (e. g.,
organizational performance outcomes). Damanpour (1988, 1990) is one scholar who has
conducted research in this area. In his research about the relation between an innovation's

rate of adoption, top management's perceived effectiveness of an innovation, and

objective organizational performance outcomes, Damanpour (1990) concluded that
organizational members' perceptions of innovation outcomes are not necessarily
congruent with actual innovation outcomes. In general, subjective perceptions of
performance exceeded objective performance levels in highly effective innovations, and
objective perceptions of performance exceeded subjective performance levels in highly
ineffective innovations. Jorde—Bloom (1988) also demonstrated how both objective and
subjective judgments are considered when evaluating innovation in decisions to adopt an
innovation.

In sum, organizational members' perceptions of innovation outcomes are formed
through subjective experience, so actual and perceived outcomes are not equivalent:
Most organizational members tend to either overestimate or underestimate innovation
performance. The discrepancy between actual and perceived outcomes will be discussed
in some depth at the end of this chapter. Meanwhile, as Van de Ven points out,
"objectively, of course, the usefulness of an idea can only be determined after the
innovation process is completed and implemented" (1986, p. 592). At the time of this
data collection, the innovation under scrutiny was in the implementation stage; hence, we
are concerned with perceptions of innovation outcomes rather than objective outcomes.

Predictors of Perceived Innovation Outcomes

In a recent meta-analysis of the organizational innovation literature, Damanpour
(1991) found the following determinants to be significantly associated with innovation:
Specialization, functional differentiation, professionalization, centralization, managerial
attitude toward change, technical knowledge resources, administrative intensity, slack
resources, and internal and external communication. Damanpour's results indicated that
specialization, functional differentiation, professionalization, managerial attitude,
technical knowledge resources, administrative intensity, slack resources, and internal and
external communication were positively correlated with innovation, while centralization,

formalization, and vertical differentiation had an inverse relationship with innovation.

While Damanpour's results indicate that a wide range of factors are associated
with innovation processes in organizations (e.g., Damanpour, 1991), his work reflects the
larger academic literature, in which the majority of the factors addressed have been
formal structural variables. Comparatively little work, until recently, has investigated the
impact of informal structure on organizational members perceptions about the degree to
which they work in an innovative organization (Johnson et al., 1996). Informal structure
is salient to innovation adoption and implementation because communication processes
can ultimately determine the extent to which an innovative idea is assimilated into the
constraints of an organization's existing structure (Johnson, 1993). Further,
communication processes are particularly relevant to generating informally-generated
innovations (Kanter, 1983). The next section will focus on the ways in which informal
communication structural variables contribute to organizational innovation in general and
individual perceptions of organizational innovativeness in particular.

WWW

Much is known about the relationship between formal organizational structure and
innovations, but comparatively little work has been done on the relationship between
innovation and the informal structure of organizations (Johnson, 1993). In the 1960 and
1970's researchers focused on formal approaches and the implementation of innovation
sanctioned by top-management (Rogers, 1983). More recently, network approaches to
informal communication have been tied to innovation adoption (Burkhardt & Brass,
1990). This focus on innovation adoption, rather than implementation, is characteristic of
the larger organizational innovation literature (Lewis & Seibold, 1993). Currently, there
is a growing focus on innovation implementation (Lewis & Seibold, 1993) as well as the
initiation of innovations by lower level organizational members (Johnson, 1993). The
initiation of innovations in organizations by non-administrative staff is more likely to
occur in an internal environment where such innovation is normative: people have easy

access to information, there are permeable boundaries between organizational units, there

are rewards for sharing, seeking and utilizing new information, there are rewards for risk
taking, accepting, and adapting to change, and the organization encourages its members
to be mobile and to develop interpersonal contacts (Goldhar, et al., 1976).

Rogers (1983) discussed the impact of social network characteristics on
innovation adoption behavior. He concluded that "in all cases it seems that social systems
whose members are more closely linked by communication networks have a stronger
diffusion effect and a faster rate of adoption of innovations" (1983, p. 235). However, in
order to understand the extent to which social networks impact an organization's ability to
innovate, one must be willing to assess critically the impact of communication on
perceptions of innovation characteristics. If organizational network members harbor
favorable perceptions about an innovation's characteristics, and the network is highly
interconnected, then that innovation is likely to be adopted rapidly. If, on the other hand,
an innovation is regarded by organizational members in an unfavorable light, and the
organization is highly interconnected, then that innovation is likely to be rejected rapidly.
Renn (1991) referred to this diffusion phenomenon, in a nutshell, as the "social
amplification effect". In a highly segmented, sparse communication network, perceptions
of innovation will still be subject to the social amplification effect, but to a lesser extent,
and at a much slower rate.

Weenig and Midden (1991) studied the effect of communication network
influences on environmental innovation diffusion in two Dutch neighborhoods. They
hypothesized that the process of information diffusion would be linked to the number of
social ties in an individual's social network, and the adoption decision would be linked to
advice received by strong communication ties. Similar energy conservation programs
were implemented in cohesive (highly interconnected) and non-cohesive (highly
segmented) neighborhoods. Interviewers collected communication network data as well
as information about program awareness, attention to program activities, and adoption

decisions. Their findings supported the hypothesis, reminiscent of Katz and

Larzarsfeld's (1955) two-step flow model, that innovation adoption is a two-stage process
of information diffusion and persuasion. Weenig and Midden’s research is relevant to the
diffusion of organizational innovations in two ways: 1) a large number of weak social
ties between potential adopters and influential organizational members who advocate
change can increase the rate of communication and information dissemination; and 2)
program participation of potential adopter's strong network ties can reduce the uncertainty
inherent in innovation.

We:

Intuitively, the strength of a social tie is a function of time, emotional intensity,
intimacy, and reciprocity (Granovetter, 1973). Weak ties refer to our less developed
relationships which are more limited in space, place, time, and depth of emotional bonds
(Adelman, Parks, & Albrecht, 1987; Weimann, 1983). The "strength of weak ties",
derived from the work of Granovetter (1973) on how people acquire information related
to potential jobs, is perhaps the most well-known concept related to network analysis
(Granovetter, 1982). It turns out that the most useful information comes from individuals
in a person's extended networks; casual acquaintances and friends of fiiends. This
information is the most useful precisely because it comes from infrequent or weak

contacts.

Most weak ties have been found in work-related networks rather than friendship
or kin networks (Granovetter, 1982), and single-content rather than multiplex networks
(Albrecht & Ropp, 1984). While weak ties have been conceptualized quite broadly in
terms of relationships that are limited along a number of dimensions (e.g.,
interdependency, intimacy, variety, physical and temporal contexts, density, social
distance, and range of information) (Adelman, Parks, & Albrecht, 1987), most
operationalizations have focused on the pattern of network linkages, which is perhaps the

most objective method of measuring the strength of a tie (Krackhardt, 1992). Although

10

some researchers argue that strong ties are important to organizations in general
(Krackhardt, 1992), and innovation generation in particular (Albrecht & Ropp, 1984),
they concede that weak ties play a key function in gaining access to information within
organizations (Adelman, Parks, & Albrecht, 1987). In fact, the weak ties concept has
been intimately tied to the flow of information within organizations (Weimann, 1983;
Burt, 1992). Individuals who have many weak ties have increased access to information,
due to the diverse nature of their sources of information as well as to the sheer number of
their contacts alone. In contrast, strong contacts are likely to be people with whom there
is a constant sharing of the same information. As a result, individuals who share strong
ties come to have the same information base. Information from outside this base gives
unique perspectives and, is, thus, often a source of innovative ideas.

Range and prominence measures are indicators of informal communication
network structure (Burt, 1991), specifically weak ties, which have important implications
for innovation. Individuals who are exposed to information about innovation from a
variety of sources are more likely to perceive that they work in an innovative
environment, and use that information to make evaluations about the pros and cons of
innovation. The present research will measure weak ties with the, range measures of
contacts and nonredundant contacts and the prominence measure of choice status. Since
these indices are characteristics of an organizational member's number of diverse
contacts, they are comparable to that individual's number of weak ties within the network
(Granovetter, 1973). Thus, high range and prominence scores indicate individuals who
have been exposed to information about innovation from a variety of sources. Since both
range and prominence are characteristics of an organizational member's strategic location
within the network, we expect that the two constructs will not necessarily be mutually
exclusive.

Range. Range is an estimate of an individual's access to valued social

information, or the extent to which he or she has bridge linkages to other groups in the

11

network. Range is one indication of an individual's weak ties in a network (Burt, 1991).
Individuals with high levels of contacts (direct communication linkages) and non-
redundant contacts (contacts independent of one another) are exposed to information
about innovation from a variety of sources. They are likely to perceive that they work in
an innovative environment and to be exposed to innovation-related knowledge.

Prominence. Prominence arises from being the object of relations from powerful
others in the network (Burt, 1991). In Burt's (1991) view, prominence is a reflection of
the extent to which an individual is in demand, as reflected by the strength of relations
focused on an individual. Thus, prominence tends to reflect an individual's formal status
within an organization (Burt, 1991). Individuals with high levels of choice status have a
large proportion of individuals contacting them out of the total people in the network who
could have done so. In this way, increased prominence may elevate an organizational
member's awareness of a myriad of activities in an organization, thus enhancing
perceived organizational innovativeness and providing an individual with knowledge
with which to evaluate specific innovations. Because of varying levels of prominence
within the innovation-related communication network, formal or informal groups of
organizational members may form distinctly different perceptions of the pros and cons of
innovation.

KW Earlier, it was stated that organizational
members' perceptions of innovation outcomes are formed through subjective experience,
so perceived outcomes are not equivalent to actual outcomes (Damanpour, 1990). There
are several factors which lead to such differences in perception of innovation outcomes.
Kossek (1989) found that differences in the acceptance of several human resource
program innovations were based upon respondents' level within the hierarchy, seniority,
experience, and organizational unit affiliation. Alternatively, distinct groups of
stakeholders are likely to have differing interests in the evaluation process (Weiss, 1983).

In an effort to evaluate innovation outcomes from their own perspective and situation,

12

different groups also will focus on different data in their assessment of outcomes (Brimm,
1988; Ashmos, McDaniel, & Duchon, 1990). For example, in examining the
perceptions of success for the same innovation, King (1990) found differing views
between groups based upon a group's stake and role in the innovation process as well as
the groups degree of identity with the organization. Hence, innovation outcomes are not
necessarily congruent with the perceived utility that organizational members ascribe to
the innovation. Because of varying experiences in the innovation process, indicated by
number of weak ties, formal or informal groups of organizational members may form
distinctly different perceptions of the pros and cons of innovation.

Organizational innovation requires the fulfillment of specific key roles that guide
a new idea through the innovation process. These roles are carried out by members of the
organization, and are commonly referred to as idea generators, sponsors, and
orchestrators (Galbraith, 1984), who are likely to be prominent individuals in innovation
networks. While critical to the innovation process, these roles are not formal positions,
but rather informal roles that can be assumed by individuals throughout the organization.
In organizations implementing a variety of innovations, however, there may be
potentially more innovation roles than there are adopters. This shortage of organizational
members to fill innovation roles may be exacerbated by the lack of slack resources in a
contractual network such as the CIS.

Idea generators are the creators of the innovative ideas that could be of potential
use to the organization. Idea generators initiate innovation by reformulating a particular
problem through a creative perspective that they are willing to promote within the
organization (Brimm, 1988). In organizations with informally-generated innovations
(Johnson, 1993) idea generators are usually low level staff who are close enough to the
problem to create an innovative solution. Because of their low status, idea generators
require sponsors to help promote the idea in the organization. In formally-generated

innovations, however, higher status idea generators may be their own chief advocates.

13

The sponsor, or idea champion, usually a management level person, is responsible
for recognizing the usefulness of the idea to the organization, and lending authority and
resources to the innovation throughout the development and implementation period
(Galbraith, 1984). The sponsor of an innovation plays a significant role in gaining
organizational acceptance of the innovation. Sponsors are committed to a particular
innovation, which is demonstrated through a personal identification with the innovation
and its outcomes (Brimm, 1988).

The third role needed in the innovation process is that of an orchestrator.
Innovations are rarely neutral. Instead they are often disruptive, and may be perceived as
impinging upon territorial rights and personal investments of others within the
organization. Therefore, orchestrators are needed to maneuver the innovation through
the organization's political process. The orchestrator must protect the innovation process
by supporting idea generators, finding sponsors for innovations, and promoting the trial
period and testing of innovative ideas. As the organization's political process is biased
toward those who have authority and control resources, orchestrators are the
organization's top managers. Orchestrators use their authority and resources to promote
the innovation process.

This research takes place in the CISRC, an organization that provides a
innovation-centered strategic alliance between researchers and practitioners within a
geographically-dispersed network (see Methods section for a complete description of the
context in which the study took place as well as the sample characteristics). In this case,
Program Project staff are simultaneously cast in dual roles: First, they are idea generators
who conduct research and evaluation related to new intervention strategies; second, they
play a key role as orchestrators in building support for innovation by developing and
maintaining an innovation-related communication structure across the network. Office of
Cancer Communication staff are officials at the policy level who are most involved in

centralized decision-making processes related to innovation adoption and

14

implementation. Project Directors are officials at the local level who have day-to-day
responsibility for managing the CIS. To this end, OCC and Project Directors would be
ideal sponsors or idea champions for the innovation. While people in other functional
roles (e. g., program officials at the local level, including Telephone Service Managers,
Outreach Coordinators, and Principal Investigators) do not hold key innovation roles,
they are nevertheless important stakeholders in the innovation process: They are
concerned about how innovation implementation will impact their organization's day-to-
day operation, especially the effectiveness with which they deliver the services that they
provide to the public.

Organizational members who play key roles in the innovation process are likely to
have more favorable attitudes toward innovations than other stakeholders. Key players
are active participants in innovation who “buy in” to the innovation process because they
have a great deal at stake. Since Program Project staff are idea generators and
orchestrators of innovation, and Office of Cancer Communication staff and Project
Directors would be ideal idea champions, one would expect that they would report higher
levels of pros and lower levels of cons associated with innovation than organizational
members in other functional roles. Further, since Program Project Staff are orchestrators
of innovation, it would seem reasonable to expect that they would report higher levels of
weak ties associated with innovation and be more prominent in innovation networks than
organizational members in other fianctional roles.

BerceixedflrganizationaLInncxat'meness

An organization's perceived innovativeness provides a viewpoint from those most
intimately aware and knowledgeable, its members, of the organization's overall approach
to innovation. Perceptions of innovativeness within an organization have been directly
linked to employee satisfaction and their willingness to participate in innovation

processes generally (Hurt & Teigen, 1977).

15

In the past, scholars have measured organizational innovativeness in two ways.
The first method is a behavioral variable in which innovativeness is measured as an
outcome variable, the rate of the adoption of innovations. Thus, the level of
innovativeness can be measured as the number, or percentage, of innovations adopted
within a given period of time. The second method has been adapted from self-report of
individual willingness to change (Hurt & Joseph, 1976) to measure employee perceptions
of organizational willingness to change, or Perceived Organizational Innovativeness
(PORGI) (Hurt & Teigen, 1977). PORGI is a 25-item scale generated from Rogers'
innovation attributes (Rogers, 1983) and Hurt and Joseph's Innovativeness Scale (1976).
Through exploratory factor analytic procedures, Hurt and Teigen (1977) have determined
that PORGI was a unidimensional construct (all factor loadings > .60) with a split-half
reliability coefficient of .96. It is interesting to note, at least at the level of face validity,
that PORGI seems to consist of a potpourri of items that tap several different constructs
related to organizational structure, communication quality, and innovation attributes.
These constructs may include formalization, decentralization, communication quality,
and perceived organizational innovativeness in terms of receptivity to new ideas. Hurt
and Teigen's (1977) blind multiple groups approach to factor analysis may have
precluded the identification of a multidimensional model. The present dissertation will
employ only those items adapted from PORGI that demonstrate content and face validity
with respect to the construct of perceived organizational innovativeness.

I . 5 '1

While there has been a wealth of research relating to innovation processes in
organizations (see Johnson, 1993, for a recent review), comparatively few studies have
examined innovations over time (Johnson et al., 1995). Historically, researchers have
described innovations in terms of their attributes. While attributes were initially
considered to be objective characteristics, they came to be seen as perceived

characteristics. In 1963, Katz saw the adoption of an innovation as being contingent upon

16

its compatibility, or the degree to which the attributes of an innovation matched the
attributes of potential adopters. Katz characterized compatibility as being composed of
communicability, pervasiveness, risk, and profitability.

Two decades later, Rogers (1983) developed perhaps the only commonly
recognized scheme available for examining differing properties of innovations. Much of
the existing research on the impact of perceptions of innovation attributes on innovation
adoption is summarized by Rogers in his review of the diffusion literature (Rogers, 1983,
1995). In this diffusion of innovations 'anthology,’ Rogers identified five perceived
attributes of an innovation: Lelatiye adyantag: (the degree to which an innovation is
perceived as being better than the idea it supersedes), bbmbatilu'lity (the degree to which
an innovation is perceived as consistent with the existing values, past experiences, and
needs of potential adopters), ttialability (the degree to which an innovation may be
experimented with on a limited basis), Emplbxity (the degree to which an innovation is
perceived as relatively difficult to understand and use), and Qbsetyability (the degree to
which the results of an innovation are visible to others).

In addition to Rogers' five innovation attributes, two additional characteristics
may be key factors in the innovation adoption process. Dearing, Meyer, & Kazmierczak
(1994) found that Leliability (the extent to which an innovation is communicated as being
consistent in its results) played a salient role in innovation-related communication.
Leonard-Barton & Sinha (1993), in their study of the dissemination of technological
innovations to operational subunits within an organization, found that mutual adaptation,
the degree to which users refine a system to fit their particular need, is a key factor in
successful technology transfer. Thus, innovations can be characterized in terms of their
adaptability, or the degree to which they can be adapted to fit the local needs of potential
adopters, and their lack of reliability, or tiskiness, the degree to which they present

uncertain outcomes for potential adopters.

17

While these attributes present an array of constructs with which to describe
innovations, there is a general lack of scale development in the literature about innovation
attributes (Meyer, Johnson, & Ethington, 1996). Rogers' five innovation attributes have
been operationalized in various, often conflicting ways in the literature. With respect to
relative advantage, Dearing et al. (1994) isolated three aspects of relative advantage:
economic advantage, effectiveness, and reliability. Effectiveness is the degree to which
an innovation is communicated as being relatively more capable in achieving an ideal
end-state. Reliability is the degree to which an innovation is communicated as being
consistent in its results. Dearing et al.'s (1994) study indicated that more than two-thirds
of comments related to relative advantage were non-economic.

Rogers distinguishes between two types of relative advantage: economic and
social advantage. Economic advantage can be equated with profitability, and Rogers
argues that an innovation perceived to be highly profitable is likely to be adopted.
Related to economic advantage is the award of incentives, payments that are given to an
individual or system in order to encourage overt behavioral change. Social aspects of
innovation involve the extent to which the innovation conveys social prestige or status to
the adopter. Rogers found that innovations with high levels of social prestige are likely
to be adopted because of the status that is gained by the adopter.

However, the effects of perceived social and economic aspects of advantage have
been inconsistent across studies. Kivlin and F liegel (1967) found that payoff, or
profitability, was significantly related to innovation adoption. Social approval, however,
was not significantly associated with innovation adoption, illustrating that the social and
economic attributes of relative advantage are distinct perceived characteristics of
innovation. Allan and Wolf (1978) examined the relationships between educators'
innovation adoption behavior and perceived innovation attributes. Their finding that
relative advantage was not significantly related to innovation adoption may be due to the

fact that two sub-attributes "money saved" and "popularity increased" were inversely

18

related to innovation adoption, the former negatively related and the latter positively
related.

Compatibility has also been operationalized in conflicting ways in the literature,
leading to inconsistent relationships with innovation adoption across studies. For
example, Kivlin and Fliegel (1967) viewed compatibility as the "similarity of an
innovation to older methods or ideas" (p. 88), or consistency with past experience. These
researchers found that compatibility was not of central importance in the innovation
adoption process. Alan and Wolf(1978) measured compatibility in terms of congruence
with past experience and existing values. While the former relationship was positively
correlated to adoption, the latter subscale was positively correlated with innovation
adoption. These inconsistent findings about the relationships between innovation
attributes and innovation adoption may be partially due to measurement limitations.

Besides the use of inconsistent, and often conflicting, operational definitions of
innovation attributes in early innovation studies, perhaps the most problematic issue is
the way in which innovation characteristics have been measured. In one study that is
representative of past research on innovation attributes (Fliegel & Kivlin, 1966),
dimensions of innovation characteristics such as relative advantage, risk, trialability, and
observability were measured by single-item measures. In light of the limitations inherent
in this type of measurement technique with respect to reliability and validity, one must
question whether past researchers were actually measuring the innovation characteristics
that they purported to measure.

Indeed, a review of exploratory factor analyses in innovation attributes indicates
that the distinction between innovation characteristics is not very clear-cut. Although
Rogers calls for working toward "a comprehensive set of characteristics of innovations
that are as mutually exclusive and as universally relevant as possible" (1983, p. 211),
there is little empirical support for the content validity of the classic innovation attributes.

This goal may be in part precluded by a dependence on the blind multiple groups (e. g.,

19

atheoretical) approach to factor analysis. For example, in Hahn's (1974) examination of
231 potential adopters' perceptions of social studies innovations, four factors emerged
from the data: Factor 1 "Observability of Valued Outcomes" consisted of relative
advantage items, compatibility items, and observability items. Factor 2 "Complexity"
was comprised of relative advantage items and observability items. Factor 3 "Feasibility"
consisted of relative advantage items, compatibility items, and trialability items. Hahn's
fourth and final factor, "Similarity" was composed of 2 compatibility items.

Similar "fuzzy construct" results were obtained by Haebegger's (1988) study of
260 internal audit directors' perceptions of three accounting innovations. In his study that
examined innovation in three different contexts, five factors emerged from the data:
Factor 1 consisted of complexity items. Factor 2 was comprised of relative advantage
items, compatibility items, and, in one context, the addition of an observability item.
Factor 3 consisted of a potpourri of relative advantage items, observability items,
trialability items, and, in one context, a single additional compatibility item. Haebegger's
fourth factor consisted of observability, and, in one context, two relative advantage items.
Haebegger's final factor, was composed of trialability items, with the addition of a
compatibility item in one context. Haebegger concedes that there is a "possibility that the
attributes are not unique" (p. 74).

Clinton's 1973 study of 338 teachers' perceptions of innovation characteristics
identified five factors across 16 educational innovations. Like Haebegger, Clinton's
factor structures varied between contexts, but he identified five factors that cropped up
consistently across innovations: Factor 1 "Relative Advantage" was comprised of
efficiency, advantage, pleasure, association with teaching, clarity of results. Factor 2
"Cost" encompassed initial and ongoing economic costs. Factor 3 "Compatibility"
consisted of reverse-scored novelty items and compatibility items. Factor 4
"Complexity" dealt with disadvantages, or repercussions and penalties. Finally, Factor 5

"Communicability" was composed of social relative advantage items. In examining

20

Clinton's 20 pages of factor loadings for five factors, one must ask whether there is
potentially a much simpler interpretation of the data.

Berman's (1994) study of 84 small manufacturing firms' executives' perceptions of
export innovations identified nine innovation characteristics. Relative advantage was
broken up into competitive advantage and profit. Compatibility was divided into
compatibility with objectives, compatibility with sales policies, and compatibility with
business policies. Berrnan also differentiated between three types of complexity: Factor
6, Factor 7, and Factor 8. Berman's final factors consisted of observability, and
trialability, which he rejected as a scale because of an unacceptably low alpha.

Finally, Karahanna (1993), examined differences in perceptions of information
technology innovations among 161 potential adopters and 107 users. Like Berman, she
identified eight factors: "Usefulness and compatibility", "trialability", "ease of use",

H H H H H H

"image , visibility , result demonstrability , compatibility", and "voluntariness".
i: H ‘01-...“ llOVqOIélIO-,' ' I‘ ’ 0 an n o no ._ H

In sum, past studies of innovation attributes have encountered measurement
problems. To address the general lack of scale development in the literature about
innovation attributes, a recent study employed confirmatory factor analytic techniques to
determine the extent to which these constructs are mutually exclusive (Meyer, 1996).
Results indicated that the innovation attributes of relative advantage, observability,
adaptability, and acceptance tap a manifest trait, pres, while complexity and risk
comprise 95m. The present dissertation will employ this alternate conceptual
framework, the pros and cons of innovation, because, unlike traditional innovation
attributes, the pros and cons of innovation demonstrate content, as well as face validity.

The pros of innovation are indicative of advantages that organizational members
associate with an innovation. Essentially akin to the extent to which organizational

members think that an innovation is a good idea, pros are linked closely to the traditional

innovation attribute of relative advantage. Pros may also encompass other attributes that

21

are positively related to innovation adoption, such as observability, adaptability,
compatibility, and trialability. Pros also gauge the level of acceptance for an innovation:
Organizational members who report high levels of pros associated with an intervention
are likely to support or "buy in" to that innovation. Research in health psychology has
identified pros as a factor positively related to adopting mammography screening
behaviors (Rakowski et al., 1992).

The cons of innovation can best be understood in contrast to the pros of
innovation. Cons are indicative of disadvantages that organizational members associate
with an innovation. Closely related to the innovation attributes of complexity and risk,
cons tap the extent to which organizational members perceive that there are drawbacks or
negative unintended consequences associated with an innovation. Cons may gauge the
level of resistance to change: Organizational members who report high levels of cons
associated with an intervention may fail to support, or even sabotage, the innovation.
Recent research in health psychology has identified cons as a factor that represents
perceived negative aspects of obtaining a mammogram (Rakowski et al., 1992).

a UH‘, 0. In: e o, 'e u "_ ‘ ‘0. 0 in .1030. Lu 1' 'I‘ .2- 0.

Based on the previous discussion, it seems likely that weak ties, perceived
organizational innovativeness, and the pros and cons of innovation are intimately
connected constructs. Individual perceptions about innovation and innovativeness are
diffused in organizations over time through communication, so informal structure at one
point in time should impact perceived organizational innovativeness and perceptions
about the pros and cons of innovation at later points in time. An innovative climate
should be a predictor of the degree to which organizational members will be supportive of
a particular innovation. Likewise, organizational members should form general
perceptions about the extent to which they work in an innovative climate through their

experience with a specific innovation in the organizational context. In order to present a

22

parsimonious model, it is hypothesized that predictor variables will have immediate,
direct effects on outcome variables from one data collection to the time period that
directly follows it. Hence, no lag effects are predicted. The conceptual model "The
Effects of Weak Ties on Perceived Organizational Innovativeness and Innovation
Characteristics" is presented in Figure 1.

Individuals with many weak ties are exposed to information about innovation
from a variety of sources. They are likely to perceive that they work in an innovative
environment and be exposed to innovation-related knowledge. Information from diverse
sources gives unique perspectives and, is, thus, often a source of innovative ideas. Thus,

it is hypothesized that:

H1: Weak ties at T2 will be positively correlated with perceived organizational

innovativeness at T3.

The "amplification effect" (Renn, 1991) suggests that weak ties should impact
future perceptions of innovation by amplifying existing attitudes about the pros and cons
of innovation. If people communicate with their weak ties about the favorable aspects of
the innovation, then this could have a positive effect on attitudes about innovation over
time. If, on the other hand, organizational members communicate with their weak ties
about the unfavorable aspects of the innovation, then this could have a negative effect on
attitudes about innovation over time. In contrast to the amplification effect, the "spiral of
silence" phenomenon (Noelle-Neumann, 1974) suggests that attitudes about innovation
may not necessarily get converted to talk among weak ties: Organizational members may
share dissimilar views about innovation, but the person with relatively less knowledge
about the topic may fail to express his or her opinions because he or she perceives that he
or she lacks expertise. In this case, opinion leaders' views about innovation would

eventually become paramount in the network. Since the extent to which organizational

23

members advocate innovation through innovation-related communication is not known,

the following research questions are generated:

RQl: How will weak ties at T1 influence attitudes about the pros of innovation at

T2?

RQla: How will weak ties at T1 influence attitudes about the cons of innovation

at T2?

RQ2: How will weak ties at T3 influence attitudes about the pros of innovation at

T4?

RQ2a: How will weak ties at T3 influence attitudes about the cons of innovation

at T4?

Since perceptions of innovativeness within an organization have been directly
linked to employee willingness to participate in innovation processes (Hurt & Teigen,
1977), it is expected that an innovative climate is a predictor of the degree to which
organizational members will be supportive of a particular innovation. At the beginning
of the first data collection period, the innovation (see Methods section for a detailed
description of the setting of this study and Figure 2 for a timeline of the innovation) was
in the early stages of implementation. At an early stage (T1), perceptions of
organizational innovativeness should have been especially salient to acceptance of the
innovation at T2, because organizational members would not yet have had much specific
information with which to evaluate the innovation. At the time of the third data
collection period, the innovation was in the later stage of implementation. At this later

stage (T3), perceptions of organizational innovativeness should have still been important,

24

although somewhat less salient, to acceptance of the innovation at T4, because
organizational members would have had more specific information with which to

evaluate the innovation. Thus, it is hypothesized that:

H2: Perceived organizational innovativeness at T1 will be positively correlated

with the pros of innovation at T2.

H23: Perceived organizational innovativeness at T1 will be negatively correlated

with the cons of innovation at T2.

H3: Perceived organizational innovativeness at T3 will be positively correlated

with the pros of innovation at T4.

H3a: Perceived organizational innovativeness at T3 will be negatively correlated

with the cons of innovation at T4.

Organizational members form perceptions about the extent to which they work in
an innovative climate through their hands-on or vicarious experience with a specific
innovation in the organizational context. By sampling organizational members'
perceptions about a particular innovation within an organization, we may be able to gauge
future levels of perceived organizational innovativeness across the entire organization.
Since data about the pros and cons of innovation were gathered as the innovation was in a
later stage of implementation, organizational members had specific information with
which to evaluate the innovation. So, organizational members' perceptions about the pros
and cons would have influenced their level of perceived organizational innovativeness at

T3. Thus, it is hypothesized that:

25

H4: Attitudes about the pros of innovation at T2 will be positively correlated with

levels of perceived organizational innovativeness at T3.

H4a: Attitudes about the cons of innovation at T2 will be negatively correlated

with levels of perceived organizational innovativeness at T3.

Often, in longitudinal studies, the clearest, strongest relationship between
variables are with themselves at different points in time (Blalock, 1982). According to
Finkel (1995), there may be substantive reasons for assuming that Y t _ 1 is a cause of
either Y t or AY, because prior orientations may exert some causal effect on either current

outlooks or changes in orientations over time. Thus, it is hypothesized that:

H5: Attitudes about the pros of innovation at T2 will predict levels of pros at T4.

H5a: Attitudes about the cons of innovation at T2 will predict levels of cons at

T4.

H6: Attitudes about perceived organizational innovativeness at T1 will predict

levels of perceived organizational innovativeness at T3.

Finally, since communication structures tend to be relatively stable over time
(Johnson, 1993), and it has been suggested that the best predictor of a variable at T2 is a

baseline measure of that variable at T1 , it is hypothesized that:

H7: Weak ties at T1 will predict levels of weak ties at T2, weak ties T2 will

predict weak ties T3, and weak ties T3 will predict weak ties T4.

26

 

Insert Figure 1 about here

 

The following section describes the setting in which this research took place and
the methods used in collecting the data. In addition, the next section details analytic
procedures used to test the measurement models, hypotheses, and research questions.

Finally, confirmatory factor analysis results are presented.

CHAPTER TWO
METHODS
Setting

This longitudinal study takes place in the Cancer Information Service (CIS), a
federal government health information agency that is implementing innovations to meet
strategic objectives, simultaneously striving to deliver services and to maximize its
innovative potential.

I] C I E . S .

The CIS was implemented in 1975 by the National Cancer Institute (N CI) to
disseminate accurate, up—to-date information about cancer to the American public (Morra,
Van Nevel, Mazan, & Thomsen, 1993). Over time, the CIS has become a community-
based laboratory for state-of-the-science communication research (Marcus, Woodworth,
& Strickland, 1993). The Cancer Information Service Research Consortium (CISRC) is
a research arm of the CIS that is currently involved in the process of generating,
implementing, and evaluating preventive health innovations to reach traditionally
underserved sectors of the American public (Johnson, Berkowitz, Ethington, & Meyer,
1994). In this endeavor, the CIS must be creative in its attempts to manage innovation in
order to generate organizational members' acceptance of change that at times may be
challenged by geographic and institutional barriers.

Perhaps the most unique characteristic of the CIS is its geographic dispersion
across 19 regional offices serving the entire U. S. (Marcus et al., 1993). What brings all
of the regional offices together is a fee for services contract, which in effect creates
partnerships between contractors for a five-year period, during which time they work
together toward the accomplishment of a common goal. These offices, however, still
retain their membership in their local organizations (e. g., cancer centers) and identify
with their regional concerns. Still, there is a strong normative thread that runs through

the activity of this network, a commitment to providing high quality information, free to

27

28

the public, concerning cancer (Marcus et al., 1993). A high degree of formalization,
evidenced by a well-developed policies and procedures manual, ensures uniformity of
service and adherence to a structured protocol across the CIS network.

The unique characteristics of the CIS become apparent when you contrast the CIS
with more conventional organizational forms, because, even though people in the
regional offices are formally members of other organizations, the CIS network itself has
many of the characteristics of unitary organizations; with centrally determined goals, a
formal bureaucratic structure of authority, a division of labor, formal plans for
coordination (e.g., sharing of calls), and a high normative commitment to providing
service to callers (See Table 1 for a description of the major goals and objectives of the
CIS and Figure 2 for an overview of the CIS network.) Performance standards for
telephone calls are set nationally and are monitored by an extensive formal evaluation
effort (Kessler et al., 1993). However, personnel issues such as salaries and fringe

benefits are locally determined.

 

Table l and Figure 2 about here

 

Many of the decisions that pertain to major national initiatives (e.g., prostate
cancer, breast cancer, affiliations with other organizations) related to innovation are made
in collaboration with organizations outside the immediate context of the CIS (e.g., the
NCI and the National Institutes of Health). This places CIS members in an interesting
position in terms of their relationship to the innovation adoption and implementation
process. Traditionally, innovation studies have focused on adopters or end-users,
individuals who actually make adoption decisions. In contrast, the majority of CIS
members are key stakeholders, rather than adopters or end-users. Exceptions to this

characterization would be the Office of Cancer Communication (OCC) staff at NCI and

29

Project Directors. Of all CIS members (see Sample Charaeterjsties for complete
descriptions of all functional roles), OCC staff and senior Project Directors are most like
adopters because they are most involved in centralized decision-making processes related
to innovation implementation.

I . . l C I E . S .

Over the past two years, the CISRC has been piloting three new intervention
strategies to facilitate the dissemination of cancer information to the public. In this study,
we will examine the second intervention, Project 2, Making Outcalls to Promote
Mammography, because it is the only project that was completed during the data
collection period (see Smyeyfltoeefinre for a detailed discussion of sampling intervals
and design issues). A chronology of key events that occurred in the CISRC during the
data collection period was compiled from archival documents (see Appendix C).

Project 2, Making Outcalls to Promote Mammography, is connected to the CIS 1-
800-4-CANCER telephone service, utilizing the toll—free number as a nexus from which
to disseminate cancer information to targeted populations who are traditionally
underserved sectors of the American public. Specifically, Project 2 is concerned with
encouraging women to receive regular mammograms. This new intervention strategy
reaches out to women by making cold calls frem the CIS tQ low income and minority
women in targeted communities in Colorado. This intervention strategy is unique in that
it focuses on making entealls from the CIS, an activity that is substantially different from
the traditional role of a telephone service that answers balls placed by people in the
community In a toll-free number. In February, 1994, at the time of the first data
collection, Project 2 was engaged in the pilot study for Making Outcalls. In July, 1994,
one month before the second data collection, Project 2 was just beginning the main pilot
study, and the CISRC was discussing various strategies to reach working women (e. g.,
making outcalls in the evening), and to create incentives for information specialists to

make outcalls (e.g., financial reimbursements or hiring a half-time information specialist

30

to make outcalls). By March, 1995, Project 2 reported reaching women with a lower
mammography adherence rate than women who were calling in to the CIS. The main
study was completed by the end of June, approximately two months before the third data
collection. In October, 1995, one month before the fourth data collection, Project 2
reported a 76% six-month follow-up response rate.

Currently, the CISRC is engaged in outcome evaluations associated with Project
2. First, the CISRC is conducting summative evaluation to determine the effectiveness of
Project 2 in promoting mammography screening in low income women. In addition, the
CISRC is conducting a study to determine the extent to which Project 2 is a cost effective
approach to delivering cancer information to the public. This study examines changes
over time in organizational members' perceptions of Project 2.

Sample Characteristics

The participants in this study (11 = 90) were highly educated. At baseline, 94
percent of respondents (n = 106) had earned college degrees, 62 percent of which were
graduate degrees. The majority of respondents were low in tenure: less than one-third of
respondents had worked for the CIS for five years or more, while nearly two-thirds had
worked for the CIS for under five years. This study focused on the key decision makers
within the CIS: the Office of Cancer Communication (OCC) staff at NCI, Principal
Investigators (PIS), Project Directors (PDs), Telephone Service Managers (TSMs), and
Outreach Coordinators (OCs) at the regional CIS offices. People in these functional roles
all play a different part in the adoption and implementation of innovations in the CIS:
OCC staff (13 percent of respondents) are most involved in centralized decision-making
processes related to innovation implementation; P13 (11 percent of respondents) provide
overall strategic direction for offices; PDs (15 percent of respondents) provide day-to-day
operational management for the projects, integrating national programs at the local and
regional level; TSMs (21 percent of respondents) are responsible for training and

managing the information specialists who actually operate the telephone service for

31

cancer information; and OCs (21 percent of respondents) form partnerships with local
organizations and the media in order to disseminate cancer information to the public. The
remaining 19 percent of respondents were CISRC Program Project staff (PP), who
conduct research and evaluation related to new intervention strategies. Table 2 reports
the baseline demographic characteristics of the participants in this overall research

project.

 

Table 2 about here

 

Survey Procedure

This research was part of a much larger project designed to evaluate the impact of
three planned innovations over a four year period (see Johnson et al., 1994 for a much
more complete discussion of methods and design issues). As part of the February 1994,
August 1995, August 1996, and November 1996 recurring quarterly data collections
associated with this larger project, a mailing was sent to respondents which included a
network questionnaire and a battery of questions relating to innovation. To ensure
completion, the self-report questionnaires were sent to the respondents approximately ten
days prior to the sample time period. A personalized letter was included to explain the
issues that would be examined and urge participation in the project. At the same time, an
e-mail was sent to all participants to notify them that they would be receiving the
questionnaire. A second e-mail was sent the day before the sample time period,
reminding participants that they should begin recording their communication contacts for
the next three days. A third e-mail was sent the day after the sample time period has
concluded, to remind participants to return their questionnaires in the stamped, self-
addressed envelope provided. Many follow-up steps (e. g., letters, faxes, e-mails)

recommended in the literature (e. g., Dillman, 1978, 1991) were taken in these recurring

32

data collections (see Johnson et al. 1994 for more details). Through these extensive
follow-up efforts, we achieved a very satisfactory response rate (95%, 96%, 91%, 85%).
Sampling Interval

Selection of a sampling interval is always a problematic issue, and one outcome
of this research will be a better feel for the most appropriate sampling interval for
studying changes in communication network structure, perceived organizational
innovativeness, and perceptions of innovation characteristics. With respect to
communication structure, extensive pretesting of the communication log in the summer
of 1993 and discussions with members of the network led to the decision to focus on a
three-day period every three months, rotating days of the weeks and weeks of the month
throughout the duration of the overall research project (a span of 40 months). It was felt
that this would be the best compromise for a number of reasons. First, this sampling
interval was frequent enough to detect major cycles of activities within the CIS network.
Second, sampling a three-day period was determined to be preferable to recording all
communication activities within a three-month period because of the limitations of
respondent memory, the desire to reduce respondent burden, and the vast volumes of data
that can be generated by more exhaustive measurement strategies.

With respect to the self-report questions that were distributed at the same time as
the communication log, collaboration with members of the network led to the decision to
focus on a few central issues over the course of the overall research project. Five key
issues were rotated over 14 data collection periods, with approximately equal intervals
between the distribution of a survey at three points in time. For example, Perceived
Organizational Innovativeness and Perceptions of Innovation Characteristics, the surveys
that pertain to this study, were disseminated at intervals of 18 months and 15 months,
respectively. Baseline measures of innovativeness were planned to coincide with the
initial piloting of the innovation, and baseline measures of perceptions of innovation

characteristics were gathered soon after the main study was implemented. F ollow-up

33

measures of innovativeness were collected soon after the main study was completed, and
follow-up measures of perceptions of innovation characteristics were gathered at the time
of the six-month follow-up to the main study.

Measurement

Two types of measurement approaches were used for the variables contained in
the model: classic self-report network analysis and self-report questionnaires focusing on
innovations. All survey instruments appear in their entirety in Appendices D - G.

Networkiatiables

Network analysis research is extremely vulnerable to low response rates and
missing data. It also differs from the sampling procedures and randomization approaches
more traditionally found in the social sciences. As a result several key issues, instrument
design, follow-up, boundary specification, and sampling interval, had to be explicitly
confronted in research decision about how network analysis research would be carried out
within the CIS (see Johnson et al., 1994 for more detail).

Perhaps the most well known, and at times most difficult, issue associated with
the context of networks is where to draw the boundaries around them. This is especially
problematic since boundaries imply some discontinuity in relationships; that relationships
across boundaries are in some sense qualitatively different than those within the
network's boundary (Monge & Eisenberg, 1987). In one of the more extended
discussions of this issue, Lauman, Marsden, & Prensky (1983) distinguish between
nominalist and realist views of this problem. In the realist approach, the researcher
adopts the vantage point of the actors in defining boundaries, while the nominalist
imposes a conceptual framework that serves his/her own analytical purposes. This study
used a combination of these approaches in determining the boundaries of the CIS.

The analytical power and breadth of any network analysis is determined by how
the relationships between nodes (i.e., members of the CISRC network), referred to as

links, are defined. Links are the basic datum of network analysis (Rogers & Kincaid,

34

1981). Essentially the measurement of linkages focuses on the classic question of who
speaks to whom about what using which communication modality. Although self-reports
of communication behavior have been questioned because of their effect on accuracy
(e.g., Bernard & Killworth, 1977), many still assert their validity on a conceptual level
(Corrnan & Scott, 1994). As Richards (1985) maintains, since self-report reveals a
person's perceptions of social reality, it often provides richer types of information than
mere reliance on observations and researchers who have reanalyzed the Bernard and
Killworth data have come to the opposite conclusion (Kashy & Kenny, 1990). Even
Bernard and Killworth have seen the utility of self-report for some problems (see
Killworth, Bernard, & McCarty, 1984). Indeed, while the accuracy of self-report network
data has been questioned on many grounds, for pragmatic reasons it has been the
predominant method used for network analysis (Marsden, 1990). Some have also argued,
from balance theory perspectives, that self-reports of behavior are mere meaningful than
actual behavior, since they more closely reflect the individual's perceptions and thus are
more closely linked to their attitudes about and reactions to a particular social system
(Kilduff & Krackhardt, 1994), a particularly important issue for perceived organizational
innovativeness.

Only interpersonal contacts, either face-to-face or by telephone, that were
initiated or received during the three day sampling interval, were recorded in the
communication log. In practice, because of geographic dispersion, interpersonal contacts
were primarily by telephone. The larger project examines links with two types of work-
related communication message content: intervention strategies and other work-related.
Intervention strategies, including, but not exclusive to, the efforts proposed in other
elements of the CISRC, focus on methods of reaching the target audiences of the CIS.
Other work-related issues focus on maintaining and/or enhancing the day-to-day
operation of the CIS (e.g., administrative chores such as budgeting). Respondents also

had the option of reporting that any one conversation contained both types of content.

35

Since this study's focus is on innovation, the analysis will concern only intervention
strategies contacts.

Separate predated forms were provided for each day of the data collection period.
Detailed examples were provided on how to fill out the log in the packet. In addition, as
part of the informed consent and follow-up procedures most members of the network
were contacted by telephone (or at conferences) and were given more detailed
instructions on how to fill out the logs. The CISRC network was defined for individuals
by their functional roles. In addition, a directory was provided of all members of the
network. This approach reduced respondent burden associated with paging through a
complete roster, while also providing a means for securing some of the advantages of
rosters. Often this is the only practicable means of recording data for larger social
systems (Marsden, 1990). Thus, individuals were asked to record the complete names of
individuals with whom they had contact. They also recorded their name, region, and
position on every page of the log.

Despite an extensive pretest, the communication log was modified twice during
the course of the research project, in response to issues raised by respondents (the
communication logs are included in Appendices D and E). In May 1995, nearly half-way
into the research project, the communication log was modified to capture only
communication at the national level. In August 1995, the communication log was
changed to include communication conducted by facsimile and electronic mail. The first
change may have reduced the level of communication reported across the network,
especially intraoffice and other work-related communication. The second change may
have led respondents to substitute one mode of communication for a variety of others.
Since this study is concerned with interpersonal innovation-related communication
contacts only, the impacts of the change in measurement instruments on communication

structure is minimal.

36

E l . I l.

The procedure by which self-report questionnaires were developed followed the
stages suggested by Devellis (1991). First, we identified the constructs to be measured
through a theory-driven process: We began by identifying nine factors based on a review
of the academic literature: relative advantage, compatibility, observability, complexity,
trialability, adaptability, riskiness, acceptance, and perceived organizational
innovativeness. Next, we generated a good-sized pool of items that could potentially be
included in the scales, wording questions carefully to avoid multicollinearity between
constructs. Data from initial, exploratory, qualitative interviews, and from formal
agency documents were used to adapt items to the organizational context of the CIS.
While we generated items, we carefully considered the format and the number of
response categories to be included in the questionnaire: All items were based on eleven
point semantic differential type scales. Once we generated a draft of the scales, we
determined face validity by having the draft reviewed by experts in the area of
organizational communication, health communication, and the diffusion of innovations.
In the pretest stage, we administered the revised scales to a sample of participants in the
target audience. In addition, we utilized participant feedback to fine-tune the
questionnaire and to improve the ease with which the directions could be understood and
followed.

E . I D . . l I .

In February 1994 and August 1995, six items tapping perceived organizational
innovativeness were adapted from PORGI (Hurt & Teigen, 1977). For example, one item
read "The CIS is receptive to new ideas". In some cases, items were tailored to the
context of innovation in the CIS. For example, one of Hurt and Teigen's items addressed
creativity in general, whereas in this study, creativity was more specific: "Most people
who work for the CIS are very creative in how they go about implementing innovations".

During the pretest phase, the word "innovations" was changed to "new intervention

37

strategies", reflecting the language of innovation in the CIS. Low factor loadings
associated with a confirmatory factor analysis of the scale indicated measurement
problems with the items "The CIS is receptive to new ideas" and "The CIS responds
quickly to necessary changes related to new intervention strategies". In the pretest of the
August 1995 revised Perceived Organizational Innovativeness survey, this item was
replaced with "Members of the CIS are innovative". Items that appear in the final
Perceived Organizational Innovativeness scale (see Appendix F) were collected at both
points in time.

Rmsandfinusnflnnmtion

In August 1994 and November 1995, items were generated to tap the classic
innovation attributes of relative advantage, compatibility, complexity, trialability, and
observability, as well as more recent attributes of riskiness, adaptability, and acceptance.
In the process of having the initial draft items reviewed by organizational communication
experts, concerns were raised about multicollinearity. It was noted that reliability (the
reverse of riskiness) and relative advantage are not mutually exclusive. In addition, it
became apparent that it was problematic to operationalize observability in a way that was
clear, yet value neutral.

Next, the revised draft was pretested with a sample of participants in the target
audience. We asked pretest participants to evaluate the three program projects with
respect to each item. Two pretest participants were worried about the quality of their
responses to projects other than the ones that was being piloted in their offices. In order
to address this concern, two additional response options were inserted: "DK" for "don't
know" and "NR" for "no response at this time". In the directions, respondents were given

a brief description of the projects under assessment as well as the following assurance:

We understand that you may not be completely familiar with each of the

components of the program projects: This is not meant to be a test, rather

38

we would like to find out peoples' current level of awareness about the
component parts of each program project. If you do not yet have enough
information to evaluate an item with respect to a particular program
project, write "DK" (for "don't know) in the space provided for item
evaluation. If you feel uncomfortable responding for another reason (e.g.,
the program project doesn't relate to your work or you have heard
conflicting things about the intervention strategy), write "NR" (for "no

response at this time").

As a result of the August 1994 pretest, several items were altered or omitted.
Many of the revisions had to do with observability. The observability item "This
intervention strategy places a number of demands on our office" was clarified by
specifying the nature of demands at the level of the telephone information specialist. The
observability item "This intervention strategy will be easy to evaluate" was omitted
because respondents felt it was too vague. Further, because pretest participants felt that
the effects of cancer information interventions on callers would not necessarily be
observable in the short run, additional observability items were revised to reflect more
short-term, observable effects. For example, "This intervention strategy will produce a
noticeable change in publics desire for cancer information" became "This intervention
strategy will change the way information is disseminated by the CIS", and "This
intervention strategy provides direct evidence that it has an effect on the target audience"
became "This intervention strategy will have an effect on the target audience".

With respect to trialability, the items "can be tried on a limited basis" and "can be
pre-tested before implementation" were rejected because of ambiguity. A new stem was
added for trialability items: “piloting this intervention strategy in a few offices...” which
tapped the extent to which respondents thought that piloting an intervention strategy was

a good idea.

39

With respect to riskiness, the (reversed) riskiness item "This intervention strategy
is a tried and true method for communicating cancer information to the public" was
omitted because respondents felt that innovation could not be "tried and true".
Additionally, the item "This intervention strategy has a high probability of succeeding "
was changed to "...is a reliable way to communicate cancer information to the public",
due to the apt perception of one participant that success can be measured in many ways.

In the revised November 1995 Innovation Characteristics scale, items with low
factor loadings were deleted if, when omitted, would raise the scale alpha (e.g., "This
intervention strategy has many different components" and "This intervention strategy is
something we can build on in the future"). As a result of the pretest of the revised survey,
in which it was acknowledged that the interventions were at different stages of
implementation than they had been at time one, a footnote was dropped to instruct
respondents to answer the questions as they pertained to current status of each project.

Perhaps foreshadowing future problems with respondent burden, one pretest
participant requested a reduction in the number of redundant questions (e.g., items that
tapped disadvantageous innovation characteristics such as complexity and risk). Since
this redundancy is a necessary evil for attaining acceptable levels of reliability and
validity of measurement, we did not reduce the number of items for each construct (five).

Again, a pretest participant responded that it was difficult to evaluate the program
projects because her office was not piloting an intervention strategy. Additionally, a new
organizational member had difficulty answering questions related to past initiatives about
which she know little or nothing. This difficulty was especially salient to relative
advantage and compatibility items. She added that outside of piloting an innovation in her
office, she felt that innovation outcomes were unpredictable. Items that appear in the
final Innovation Characteristics scale (see Appendix G) were collected at both points in

time.

40

Analysis

An investigation of the proposed hypothesized relationships required a four step
procedure. First, the informal communication structure data were analyzed by means of
STRUCTURE. The next step was the evaluation of the measurement model with the
confirmatory factor analysis subroutine of the PACKAGE computer program (Hunter &
Lim, 1987). The third step was generating descriptive statistics and testing hypotheses
of mean differences with ANOVA in SPSS for Windows. Finally, the path model was
analyzed with path analytic techniques of the PACKAGE computer program (Hunter &
Lim, 1987). The critical value was set at .05 for all analyses.

WEE

STRUCTURE is based on the work of the sociologist Ron Burt (1991), and, as
such, has explicit linkages to his theoretical work (e.g., Burt, 1982). STRUCTURE
calculates a large number of indices related to an individual's structural positioning within
the network. Structural Autonomy indices, revealed in part in range measures, relate to
the extent to which an individual's relationships may constrain his/her opportunities for
individual action within a network. Individuals high in structural autonomy have more
freedom of action within a network. Two measures of range, contacts and nonredundant
contacts, reflect the breadth of an individual's network ties. Contacts reflect counts of an
individual's direct and indirect contacts, while nonredundant contacts is a count of the
number of independent contacts (see Burt, 1991, pp. 180-183).

STRUCTURE also calculates a number of measures of the extent to which an
individual is prominent within a social network. Choice status measures the proportion
of an actor's contacts from others in the network to the total number of contacts possible.
While range focuses on the horizontal axis of the organization, prominence is typically
associated with the vertical axis, and tends to reflect an individual's formal status within

an organization (Burt, 1991).

41

CnnflnnaIQnLEaeteLAnalxsis

The measurement model for the first order scales was analyzed by means of the
confirmatory factor analysis subroutine of the PACKAGE computer program (Hunter &
Lim, 1987). Confirrnatory factor analysis is a superior technique when the a priori
specification of items expected to cluster together is possible (Fink & Monge, 1985;
Hunter & Gerbing, 1982). Three criteria proposed by Hunter (Hunter, 1980; Hunter &
Gerbing, 1982), homogeneity of item content (face validity), internal consistency (i.e.,
Spearman product rule), and parallelism (i.e., 'flat' correlation matrix), were used to
determine unidimensionality. Tests of unidimensionality are essential to scale
development since it has been demonstrated that alpha provides an unbiased estimate of
reliability only if scale items are unidimensional (Hunter, 1980; Hunter & Gerbing,
1982). In addition, because this study employed a longitudinal multiple indicator
measurement model, the data were examined for evidence of specific error (Hunter,
Coggin, & Gerbing, 1984). Since the inter-item correlations for scale items across time
were not inflated, specific error was not a problem in these data.
Wins

For the August 1995 prominence and range data, a two-factor solution failed tests
of internal consistency and parallelism, indicating that range and prominence are not
mutually exclusive. Further analyses revealed that the prominence and range data were
consistent with a unidimensional model in that final scale items met the following criteria
for internal consistency: face validity, primary factor loading of .7 or greater (see Table
3), and small residual errors between predicted and observed correlations (see Table 4).
Further, when compared against the Perceived Organizational Innovativeness scale, the
final scale demonstrated parallelism. A nonsignificant sum of squared errors did not
depart from the hypothesized measurement model ( x2 = 8.2, glf 9). Standardized alphas
for the final scale, Weak Ties, were .93, .96, .93, and .90, respectively, across the four

time periods.

42

13.13..” .v

Five Perceived Organizational Innovativeness items adapted from PORGI (Hurt
& Teigen, 1977) were analyzed with confirmatory factor analysis techniques. Three final
items met the following criteria for internal consistency: face validity, primary factor
loading of .7 or greater (see Table 5), and less than 6% of the discrepancies between
predicted and observed correlations were outside the bounds of the confidence interval at
T1 and T2, respectively (2.0%, 5.5%, p < .05) (see Table 6). Further, when compared
against formal structural variables and communication process variables, the final
Perceived Organizational Innovativeness scale demonstrated parallelism. At T1 and T3,
a nonsignificant sum of squared errors showed no departure from the hypothesized
measurement model (252 = 62.2, df 149, 32 = 128.8, df_l64). The standardized alphas for
perceived organizational innovativeness were .85 and .89 at T1 and T3, respectively.
Bmsandfinnuflnnmflcn

In August 1994 and November 1995, items were generated to tap the classic
innovation attributes of relative advantage, compatibility, complexity, trialability, and
observability, as well as more recent attributes of riskiness, adaptability, and acceptance.
Confirmatory factor analytic techniques indicated that the original subscales, with the
exception of trialability, were below acceptable parameters for internal consistency and
parallelism. Items not only failed to load highest on the factor to which they were
hypothesized to belong, but they also did not correlate highly with other items
hypothesized to load on that same factor. In fact, many items were highly correlated with
items hypothesized to load on other factors. Further, initial factor analyses of the
subscales across all three innovations revealed a relatively uniform pattern of high inter-
factor correlations between the innovation attributes of acceptance, relative advantage,
observability, adaptability. A similar pattern of multicollinearity was found with the
innovation attributes of complexity and risk (see Meyer, 1996 for details). Conversely,

both complexity and riskiness items had negative or small positive correlations with

43

relative advantage, observability, adaptability, and acceptance. Further analyses
regrouped innovation attributes into pros and cons of innovations. In the process, several
items dropped from the scales because they did not fit the criteria for parameters for
internal consistency and parallelism. The final set of items met the Spearman product
rule, since the predicted correlations were within sampling error of the observed
correlations. A nonsignificant sum of squared errors showed no departure from the
hypothesized model in August 1994 ( x2 = 74.5, glf 79) and November 1995 ( x2 = 78, df
79). At T2 and T4, standardized alphas were .96 and .95 for pros, and .88 and .77 for
cons, respectively.

With respect to the homogeneity of error for pros, eight items met the following
criteria for internal consistency: face validity, primary factor loading of .6 or greater (see
Table 7), and 3.6% of the discrepancies between predicted and observed correlations were
outside the bounds of the confidence interval (p < .05) during both data collections (see
Table 8). With respect to the homogeneity of error for cons items, three met the
following criteria for internal consistency: face validity, primary factor loading of .4 or
greater (see Table 9), and no significant discrepancies between predicted and observed
correlations (p < .05) during both data collections(see Table 10). In terms of
heterogeneity of error, 12.6% and 6.3% of the discrepancies between predicted and
observed correlations were outside the bounds of the confidence interval (p < .05) at T2
and T4 respectively. It is important to note that pros were composed primarily of
relative advantage and acceptance items, with two additional items from observability
and adaptability. Cons were comprised of complexity and negatively-valenced
observability items. Compatibility and riskiness items dropped out of the scale
altogether. Due in part to the fact that pros was derived from a greater number of
innovation attributes (and hence a larger initial pool of items) than were cons, there are

overall more final items tapping pros than cons.

44

 

Tables 3 - 10 about here

CHAPTER THREE
RESULTS
This chapter presents the results of longitudinal research investigating the
relationships between weak ties, perceived organizational innovativeness, and innovation
characteristics. This chapter can be divided into three sections. The first section presents
descriptive statistics. The next section sets forth the test of the causal model. A revised
model follows.
Descriptive Statistics
Preliminary analysis of the scales' mean, standard deviation, and Pearson
correlations are reported in Table 11. The factor with the lowest average item mean was
weak ties at T4 (.57), a sizable decrease from the baseline level of 4.85. Repeated
measures MANOVA indicated that, across all four time periods, the decline in weak ties
from 4.85 at baseline to .57 at T4 was significant (E = 11.19, df 3, p =.000). The scale
with the highest average item mean was perceived organizational innovativeness at T3
(6.77), a slight but nonsignificant increase from the baseline level of perceived
organizational innovativeness (6.22). Other nonsignificant changes included a slight
decrease in the pros associated with Making Outcalls from T2 (6.69) to T4 (6.01), and a
minor concurrent increase in cons (4.72) to (5.67). Over time, perceived organizational
innovativeness was strongly correlated with itself (r = .53), while pros and cons had

strong negative correlations with one another at T4 (r = -.42).

 

Insert Table 11 about here

 

A Test of the Model "Short Term Effects of Weak Ties"
The data were analyzed with path analytic techniques of the PACKAGE

computer program (Hunter & Lim, 1987). Path analysis evaluates the fit of a model

45

46

with both global and local tests. A global test of the fit of a model is obtained by
calculating chi square, or the sum of squared errors for each predicted correlation, with
degrees of freedom equal to the number of unconstrained residuals. If the obtained chi
square does not exceed the critical value at the .05 probability level, then the model
provides a good fit to the data. Local tests of each parameter are conducted by
drawing confidence intervals around the value of the predicted correlation. If a
predicted correlation falls between the upper and lower endpoints of a 95 percent
confidence interval, then that parameter is significant at the .05 level. As shown in
Figure 3, the results indicated that the model provided a less than satisfactory fit to the
data (x2: 38.9, df 27, p = .06). Most predicted links were nonsignificant (see Table
12 for path coefficients and confidence intervals); unexpected lag effects produced the
most notable unspecified paths.

Perceptions of innovation characteristics at T2 were predicted only weakly by
perceived organizational innovativeness at T1, failing to provide support for
Hypotheses 2 and 2a: The path coefficient between perceived organizational
innovativeness at T1 and pros T2 was .11, and the path coefficient between perceived
organizational innovativeness at T1 and cons at T2 was .20. With respect to Research
Questions 1 and 1a, the links between weak ties at T1 and pros and cons at T2 were
even weaker. The path coefficient between weak ties at T1 and pros T2 was .05, and
the path coefficient between weak ties at T1 and cons at T2 was -.07. The level of
perceived organizational innovativeness T3 was weakly predicted by pros at T2 with a
path coefficient of .13, and cons at T2 (path = -. 12), failing to support Hypotheses 4
and 4a. The path between weak ties at T2 and perceived organizational innovativeness
at T3 was practically nonexistent at -.O4, so Hypothesis 1 was not supported. Only
perceived organizational innovation T3 was significantly predicted by itself at T1 with

a path coefficient of .54, providing support for Hypothesis 6.

47

At T4, perceptions of innovation characteristics were predicted only weakly by
themselves at T2, failing to provide support for Hypotheses 5 and 5a: The path
coefficient between pros T2 and pros T4 was .04, and the path coefficient between cons
T2 and cons T4 was -.01. In addition, Hypotheses 3 and 3a were not supported,
because innovation characteristics at T4 were only weakly predicted by perceived
organizational innovativeness at T3: The path between perceived organizational
innovativeness T3 and pros T4 was = .03, and the path between perceived
organizational innovativeness T3 and cons T4 was -. 19. With respect to Research
Questions 2 and 2a, the links between weak ties at T3 and pros and cons at T4 were
virtually nonexistent: The path coefficient between weak ties at T3 and pros T4 was
.05, and the path coefficient between weak ties at T3 and cons at T4 was -.01. Weak
ties was only a significant predictor of itself from T3 to T4, with a path coefficient of
.21, providing partial support for Hypothesis 7.

With respect to the individual link analysis, errors, or the difference between
actual and reproduced correlations, are presented in Table 13. For predicted links,
errors were insignificant. However, it must be duly noted that two relationships were
in the opposite direction than expected: Perceived organizational innovativeness at T1
had a positive impact on the level of cons at T2 (path = .20), which in turn had a
slight negative effect on itself at T4 (path = -.01). Of the 27 unpredicted links, seven
significant errors were found when the Z values exceeded 1.645, suggesting these paths
should be added to the model. The errors, listed in terms of magnitude, affected the
following cross-lag correlations: pros and cons at T4 (-.44); cons at T2 and weak ties
at T3 (—.37); pros at T2 and cons at T4 (-.35); weak ties at T2 and pros at T4 (-.35);
weak ties at T1 and pros at T4 (-.32); perceived organizational innovativeness at T1

and pros at T4 (-.29); and cons at T2 and pros at T4 (.24).

48

 

Insert Figure 3 and Tables 12 - 13 about here

 

The Revised Model "Long Term Effects of Weak Ties"

A revised model that consisted of significant paths from the original model with
the addition of the seven missing links, which can be conceptually justified, was tested
with path analysis. The additional links produced the following strong path
coefficients: Pros and cons at T4 (path = -.40); cons at T2 predicting weak ties at T3
(path = -.37; pros at T2 predicting cons at T4 (path = -.36; weak ties at T2
predicting pros at T4 (path = -.26; weak ties at T1 predicting pros at T4 (path = -
.19); perceived organizational innovativeness at T1 predicting pros at T4 (path = -.22);
and cons at T2 predicting pros at T4 (path = .23. The revised model, shown in Figure
4, provided an excellent fit to the data (x2: 14.88, df 26, p .96), with no significant
errors between the original and reproduced correlations (see Table 14). All but two
paths were significant at the .05 level (see Table 15 for path coefficients and confidence
intervals).

While the x2 statistic offers an indication of the goodness of fit for a model, it is
more meaningful to use the x2 statistic to compare alternative models (Bartunek &
Franzak, 1988). By employing Bentler and Bonnett's (1980) method of comparing a
series of nested models, we can assess a significantly better fitting model with a high,
positive incremental fit index (above .9), calculated as p = (Q0 - Qf) / (Q0 - 1) when Q0 =
12 / df. Results indicated that Model 2 was a significantly better fit to the data (p = 1.98).

 

Insert Figure 4 and Tables 14 - 15 about here

 

CHAPTER FOUR
DISCUSSION

This chapter discusses the implications of the analyses presented in Chapter Three. The
chapter begins with a general consideration of the findings, specifically the short and long term
effects of weak ties on perceptions of organizational innovativeness and the pros and cons of
innovation. Second, functional role differences are discussed with respect to key roles in the
innovation process. Third, limitations of the study are presented. Finally, implications are
discussed for future research as well as for practitioners.

Summary

This research demonstrated that, over time, informal communication structure
(weak ties) affected perceptions of innovation characteristics and perceived
organizational innovativeness impacted perceptions of the pros of innovation. These
findings suggest that an innovative climate is a predictor of the degree to which
organizational members will be supportive of particular innovations.

Although informal communication structure (weak ties) affected perceptions of
’innovation characteristics, predicted links were surprisingly weak; the most notable effects
were produced by unexpected lag effects. This finding indicates that it takes time for
organizational members to process novel ideas. Although individuals with high levels of weak
ties may exposed to information about innovation from a variety of sources, this type of
communication does not have an immediate impact on the degree to which they perceive that
they work in an innovative environment, nor does it noticeably impact the degree to which they
are supportive of particular innovations in the short term. In the long run, however, informal
innovation-related communication can have more pronounced consequences for organizational
members' evaluations of the pros and cons of innovation.

Congruent with the "amplification effect" (Renn, 1991), the data suggest that weak ties
do indeed impact future perceptions of innovation, by amplifying existing attitudes about the

pros and cons of innovation. Two of the links added to Model 2 indicate that, at least in this case,

49

50

weak ties at T1 and T2 had relatively strong negative impacts on perceptions of the pros of
innovation at T4. The time lag between weak ties at T1 and T2 and pros of innovation at T4 may
be due in part to the sparseness of innovation-related communication in this organization. This
finding suggests that perceptions of innovation are influenced by the social amplification effect
in highly segmented networks, but to a lesser extent, and at a much slower rate than would be
expected in dense networks. This finding suggests the importance of studying the strength of
strong ties (Krackhardt, 1992) in securing support for innovation

In addition, the lag effects mirror Weenig and Midden's (1991) unexpected
finding that negative advice was obtained more frequently from weak than strong ties.
While we can only speculate about the reason for this finding, it may be that
organizational members are more likely to make negative evaluations of an innovation if
they do not have a vested interest in it. Since perceived organizational innovativeness at
T1 had a strong negative impact on pros at T4, organizational members may have been
unsupportive of this particular innovation because they did not perceive it to be a good
match with the current innovative climate of their organization. These unanticipated
findings accent the importance of evaluating the fit of an innovation within an
organization.

Additionally, the unexpected finding that cons at T2 had a strong negative effect
on weak ties at T3 points to a structurational account of innovation and communication
(Lewis & Seibold, 1993). Apparently, perceptions of negative outcomes associated
with innovation can put a damper on future levels of innovation-related innovation
communication among organizational members. This finding puts a new twist on the
old saying "If you don't have anything nice to say, don't say anything at all ".
Unfortunately, this spiral of silence can have negative consequences for the course of

particular innovations in organizations.

51

Functional Role Differences

The scales had high standard deviations, an indication of between-groups variance.
Analysis of variance was employed to determine if there were significant differences in
perceptions of organizational innovativeness and the pros and cons of innovation among
organizational members in different functional roles. While there were no significant between
groups differences in perceived organizational innovativeness, there were several significant
differences in how people in different functional roles perceived the innovation. When compared
to members of other functional roles, Program Project staff reported higher levels of pros at T2
and T4 and lower levels of cons at T4. In addition, there were significant group differences in
informal communication structure: Project Directors and Outreach Coordinators generally
reported more weak ties than Telephone Service Managers and Principal Investigators (see Table
16). The unexpected findings about functional role differences have interesting implications for
innovation in the CISRC. Functional role differences may be associated with prominence and

the fulfillment of particular innovation roles.

 

Insert Table 16 about here

 

As we have seen, functional roles may be associated with prominence and the
fulfillment of particular innovation roles. When compared to members of other
functional roles, Program Project staff reported higher levels of pros at T1 and T2 and
lower levels of cons at T2. This indicates that Program Project staff have bought in to the
innovation process, more so than other CISRC members. Counter-intuitively, Project
Directors and OCC staff did not report higher levels of pros and lower levels of cons
than members of other functional roles within the CIS. This pattern may reflect their role
as spokespersons for and disseminators of information to their regional offices. In fact, at

two points in time, they reported considerably different views about the pros and cons of

52

innovation than Program Project members. What reasons might contribute to the
discrepancy among idea champions' and orchestrators' perceptions of innovation?

Historical events may shed some light on the reasons behind Project Directors and
OCC staffs less favorable evaluations of the innovation (see Chronology in Appendix C).
Specifically, process evaluation data released in national meetings during the summer and
fall of 1995 cited evidence of low job satisfaction among Telephone Information
Specialists, measurement problems, and low cost effectiveness associated with Making
Outcalls. This evaluation information may have highlighted negative unintended
consequences of innovation for Project Directors, who may be concerned with the
negative impact of this innovation on staff and service delivery, and OCC staff, who may
have questioned the feasibility of demonstrating significant outcomes associated with the
intervention at a reasonable price.

Whatever the reason for the idea champions unfavorable response to this
innovation, the finding of the discrepancy among idea champions' and orchestrators'
perceptions of innovation is particularly disturbing: If Project Directors and OCC staff
have the power to champion innovation, they most likely also wield the power to subvert
it. Interestingly, a recent document released by leaders in the CISRC indicates that the

consortium leadership did not perceive that this attitudinal dissonance existed:

From the outset, the plan was to mobilize and recruit CIS Project Directors
to serve as "idea champions"...lf the Project Directors remained unenthusiastic,
the opportunity to establish the CISRC would suffer a serious if not irrevocable
set-back...Fortunately for the CISRC, the CIS Project Directors perceived this
challenge as an opportunity and became highly effective idea champions within

their organizations (Marcus et al., 1996, p. 14).

94‘"-

53

This finding, when coupled with the fact that Program Project staff did not report
more weak ties than other functional roles, may indicate that the orchestrators of
innovation have dropped the baton. The lack of communication initiated by the
orchestrators of innovation to other CISRC members suggests that they are out of the
loop, relatively unaware of how practitioners are appropriating their innovation.

Alternatively, this finding could indicate that Program Project staff are primarily idea
generators and not orchestrators.

Kanter (1988) discussed the subjective nature of perceptions of innovation outcomes by
exploring the phenomenon of pro-innovation bias (Rogers, 1983). She made the point that most
research about organizational innovation is characterized by an implicit assumption that
innovation is a good thing. According to Van de Ven, "innovation is often viewed as a good
thing because the new idea must be useful--profitable, constructive, or solve a problem. New
ideas that are not perceived as useful are not normally called innovations: they are usually called
mistakes" (1986, p. 592). Kanter found that it was extremely difficult to identify innovations that
fail (1983).

Kanter concluded that the organizational context has a major impact on the
conceptualization of innovation within an organization. According to Kanter's content analysis
of participant dialogue, the difficulty inherent in identifying the failure to innovate can be
attributed to one or more of the following reasons: the taboo nature of mentioning failure; the
threatening nature of failure that discourages risky ventures; the multiple goals of many projects
that prevent them almost by definition from being an outright failure; and the strategies by which
clever innovators convert potential "failures" into minor successes. In the case of the CISRC,
perhaps innovation orchestrators' failure to acknowledge the discrepancy among idea champions'
and orchestrators' perceptions of innovation indicates that the consortium leadership is reluctant
to identify an innovation as a mistake. Ultimately, however, when would-be idea champions call

an innovation a mistake, orchestrators need to listen. Stakeholders' valuable input can be utilized

54

by managers to modify innovations mid-stream or reconsider their communication strategies for
promoting innovation.
The Political Context of Innovation

According to Frost and Egri, "innovation is, at its core, a political and social process of
change" (1991 , p. 229). If, as Van de Ven (1986) argues, the extent to which new ideas are
“managed into good currency” is a key measure of innovation outcomes, then organizational
stakeholders’ perceptions about the advantages and disadvantages associated with innovations
may be an indicator of the extent to which managers are apt at manipulating innovation-related
communication. Deetz (1985) identifies naturalization, neutralization, legitirnation, and
socialization as political strategies that actors use to systematically distort reality for their own
benefit. Organizational innovation orchestrators manipulate information, control resources, set
agenda, acquire power bases, and frame decision premises to promote the political capital that
they have invested in a given innovation (Frost & Egri, 1991).

Poole, Gioia, and Gray (1989) consider the efficacy of various processes, or influence
modes, that managers use to produce changes in organizational schema in the interest of
promoting planned organizational change. The authors identified four modes for actively
managing organizational schema: enforcement (interpersonal communication about rewards or
sanctions associated with expected change), instruction (logical explanation of change in a group
forum), proclamation (written announcement about impending change), and manipulation
(resource reallocations where hidden intents are veiled by the rationale provided for the
announced change). Interestingly, the authors found the more coercive strategies of enforcement
and manipulation to be most successful in bringing about organizational transformation. These
findings are counter to previous research, which suggests that decentralization is positively
associated with involvement or active participation in innovation processes (Johnson et a1, 1995).
Decentralization is generally considered to be positively correlated with innovation because
participatory work environments facilitate innovation by increasing organizational members'

awareness, commitment, and involvement (Damanpour, 1991). Poole et al's counter-intuitive

55

findings could be explained in part because their research took place in a bank in the private
sector, an organization with a strong hierarchical structure. In an organization with a less
centralized power structure, enforcement and manipulation modes could easily boomerang and
result in resistance to change. As the CIS is a unique organizational form which brings together
previously autonomous regional organizations under a centralized bureaucratic structure, one can
only conjecture about which influence mode would be most likely to effect change.
Resistance to Change

Organizational members who “buy in” to the innovation implementation process become
more active, enthusiastic participants because they perceive that there are certain advantages to
doing so. Desired outcomes associated with innovation may include increased efficiency,
productivity, effectiveness, and technological development. In contrast, stakeholders who
perceive high levels of disadvantage associated with an innovation may be more resistant to
change, and thus more likely to engage in dysfunctional outcomes such as sabotaging the
innovation or leaving the organization.

Rokeach and Grube (1979) employ Cognitive Dissonance Theory to argue that we
can explain resistance to organizational change as a function of the degree to which
organizational members experience dissonance when an organization's original values are
supplanted by a new set of cultural values. Bartunek and Moch (1987) discuss the
importance of schemata, or cognitive frameworks, in understanding different types of
change that organizations experience. The authors posit the following typologies of
change: first-order or incremental change that takes place within organizational member’s
existing schemata; second order change that modifies existing schemata in a particular
direction; and third-order change that trains organizational members to be aware of their
present schemata and empowers them to change these schemata as they deem appropriate.
In the case of the CIS, Making Outcalls involves second-order change, since it involves a
procedure that departs significantly from previous methods of disseminating cancer

information to the public.

56

Bartunek and Moch (1987) present a preliminary model of the second order
change process, visualizing organizational change as the outcome in a situation where a
strong impetus (e. g. environmental constraint) leads organizational members to
experience a crisis or to perceive that their existing schema is inadequate. In this case, a
strong, clear presentation of alternative schema will lead to conflict between the two
schemata for each organizational member. Orchestrators of innovation act as negotiators
and facilitators to allow personnel to retain or revise their own schemata. Bartunek and
Moch found that two factors contributed to organizational members resistance to change:
First, conflicts that resulted from differences in schemata were perceived by
organizational member to be due to personality differences, and this led to unproductive
conflict. Second, organizational members use the conflict resolution strategies that they
are familiar with -- notably, patterns that tend to reinforce the existing schema. Because
of this tendency to engage in communication behaviors that reinforce the existing
schema, it is essential for orchestrators of innovation to be aware of communication
patterns that contribute to resistance to change.

Limitations

Overall, this study was characterized by disappointingly low levels of innovation-
related communication. The low levels of innovation-related communication reported in
this study is also reflected in previous research that has indicated that innovation-related
communication in organizations is relatively sparse (Albrecht & Ropp, 1984; Farace &
Johnson, 1974; Monge, Cozzens, & Contractor, 1992; Johnson, 1993). Still, the paucity
of informal communication about innovation in this study may have suppressed expected
effects, especially in the short term.

A second limitation related to the sparseness of innovation-related communication
is that the significant decline in weak ties may be in part due to changes in measurement
instruments: As discussed previously, the communication log was modified to capture

only communication at the national level in May 1995, and later changed to include

57

communication conducted by facsimile and electronic mail in August 1995. The first
change may have reduced the level of communication reported across the network,
especially intraoffice and other work-related communication. The second change may
have led respondents to substitute one mode of communication for a variety of others.
Thus, the significant decline in weak ties from T1 to T4 should be interpreted with
caution, as it may have resulted in part from changes in instrumentation.

It must be noted that the participants in this study were limited in number and in
scope, two common limitations of network analysis. First, the small sample size (N = 90)
limited not only the statistical power of the analysis, but also the generalizability of the
results. Second, the participants were restricted to six functional roles in the CIS. This
relatively small sample was chosen under the assmnption that individuals who hold
positions as OCC staff, Pls, PDs, TSMs, and OCs have the longest tenure and are
probably the most influential players in the adoption and implementation of preventive
health innovations at the CIS. While these individuals are key stakeholders in the
innovation process, they are not end-users of the innovation. It is possible that their
perceptions would differ significantly if they were actually using the new system. Since
information specialists are the individuals who actually operate the telephone service at
the CIS, it would probably be appropriate to determine, in future studies, information
specialists' perceptions of innovation attributes. Alternatively, it could be informative to
study organizational stakeholders’ perceptions about a different type of innovation, such
as a technological innovation. Thus, replicating this study in other contexts could
increase the generalizability of these initial findings about the ways in which
organizational members evaluate the pros and cons of innovation adoption and
implementation, as well as the ways in which they form perceptions of innovativeness
through communication in organizational settings.

This study was conducted within the larger political context of an evaluation of a

federal health services agency: One implicit understanding related to the research is that

58

the results will be utilized to demonstrate that the CI S can be used as a research arm of
NCI. For this reason, respondents may have been somewhat guarded in the extent to
which they felt free to give a critical assessment of innovation. If this were the case, then
one could expect that the between-groups differences in perceptions of innovation were
smaller than they may actually be.
Implications for Future Research

What are some implications of these findings for managers and scholars of
organizational innovation and of health communication? First, an earlier analysis of the
data found that a large percentage of participants chose not to respond to items evaluating
innovations based on their current level of knowledge (Meyer et al., 1995). This finding
suggests that there is also a need to examine, over time, the extent to which
organizational members feel inadequately informed to evaluate new innovations. When
coupled with the dramatic decrease in innovation-related communication during the
course of the study, such an increase in knowledge does not appear to be highly plausible.

The finding that many respondents chose not to answer items in this study based
on their current level of knowledge about innovation also suggests that stakeholders who
are not directly involved in the piloting of new intervention strategies may have limited
access to the information necessary for reducing their uncertainty about an innovation’s
expected consequences. Stakeholders' limited, often vicarious knowledge may create a
tendency for them to make general evaluations of the pros and cons of an innovation
rather than specific attributions about innovation characteristics. Thus, it appears that
reconceptualizing perceptions of innovation attributes in terms of pros and cons is a
highly appropriate framework for understanding stakeholders in the context of
organizational innovation in future research. This leads to the proposal that it would be
interesting to examine, in future research, the relationship between organizational
members' level of involvement with an innovation and the extent to which they feel

inadequately informed to evaluate it. Perhaps those individuals who have hands-on

59

experience with an innovation would be likely to make specific attributions about
innovation characteristics based on their current level of knowledge, while stakeholders
who are not direct users of the innovation would tend to make general evaluations of the
pros and cons of an innovation.

The significant functional role differences in perceptions of the pros and cons of
innovation and weak ties suggest that distinct groups play key roles in the innovation process,
and that these groups have varying perceptions of the utility of innovations. In his work on
rethinking technology transfer, Dearing (1993) stresses the importance of measuring
effectiveness of use by comparing source and receiver perceptions of utility. Future research
needs to explore more systematically the factors that contribute to the discrepancy in perceptions
of utility among key stakeholders in the process of innovation, paying special attention to the
features of the structural, cultural, and political environment in which innovation occurs over
time.

Finally, the most notable impact of informal communication (weak ties) on perceptions
of innovation were produced by unexpected lag effects. This finding has two implications:
First, it takes time for organizational members to process novel ideas; second, informal
innovation-related communication has pronounced long-term consequences for organizational
members' evaluations of the pros and cons of innovation. This finding raises the issue of the
match between the time lag between waves and the length of time in which the causal process
occurs (Williams & Podsakoff, 1989). Moreover, future research needs to consider the
importance of formulating dynamic theories and process hypotheses in longitudinal research
(Monge, 1990).

Implications for Practitioners

Organizational stakeholders’ perceptions about the advantages and disadvantages
associated with innovations may provide managers of preventive health innovations with
a diagnostic tool (Dearing & Meyer, 1994) that can determine the extent to which

individuals are supportive of new ways of doing things. Organizational members who

60

“buy in” to the innovation implementation process become more active, enthusiastic
participants because they perceive that there are certain advantages to doing so. In
contrast, stakeholders who perceive high levels of disadvantage associated with an
innovation may engage in dysfunctional outcomes such as resistance to change (Coch, &
French, 1948). Resistance to change can result in sabotage if organizational members do
not perceive that their voices are heard in the dialogue about innovation.

The CISRC provides a strategic alliance between researchers and practitioners
within a geographically-dispersed network. In this case, Program Project staff could
ideally play a key role as orchestrators in building support for innovation by developing
and maintaining an innovation-related communication structure across the network. In
this role as orchestrators of innovation, managers need to develop competent conflict
resolution skills in order to mediate conflicts that may arise as a result of competing
interests between groups of stakeholders. Since researchers and practitioners represent
distinct groups of stakeholders in the innovation process, they are likely to have differing
interests in the innovation process (Weiss, 1983). For example, practitioners may be
primarily concerned with the consequences of innovation that impact their organization’s
functioning, while researchers may be chiefly interested in the theoretical implications or
the generalizability of their findings. While involving multiple stakeholders in evaluating
innovations can lead to unproductive conflict that bogs stakeholders down in time-
consuming discussion and debates, it can also democratize access to innovation-related
information (Weiss, 1983). Thus, strategic innovation-related organizational
communication can facilitate the process by which stakeholders pool resources to
generate, adopt, or implement multiple innovations in the face of competitive pressures.

Managers need to be aware that contextual factors impact the ways in which
innovation attributes affect innovation outcomes (Downs & Mohr, 1976; Bigoness &
Perreault, 1981). For managers of preventive health innovations, a failure to consider

contextual factors could be costly in two ways: In the short term, innovations that are

61

perceived to be high in disadvantage run the risk of being rejected in less-than-innovative
innovative organizational climates. In the long run, the failure of a risky innovation can
have a dampening effect on the innovative climate of an organization, causing
organizational members to view future innovations as having increasingly uncertain
outcomes. On the other hand, members of a highly innovative organization could
perceive a conservative innovation as not radical enough to connote change.

Managers who assess organizational members’ perceptions of innovation
attributes can employ this information as a diagnostic tool to evaluate the fit of an
innovation with an organization, to anticipate problems arising as a result of innovation,
and to modify innovations to reflect the changes that stakeholders deem necessary. These
steps are ones which will enable managers to secure the successful implementation of an
innovation within their organization. In addition, the process of asking organizational
members about their perceptions of innovation creates a dialog about innovation within
the organization. This dialogue has the potential for generating creative solutions to
problems and reinventing an innovation to produce more effective interventions in the
future. Additionally, these outcomes of innovation-related communication may increase
the extent to which organizational members perceive that they work in an innovative
climate.

Three decades ago, Katz stated that "the capacity of interpersonal channels to
provide social support and enhanced confidence in the outcomes of the innovation can be
crucial in innovation implementation" (Katz, 1963). Pragmatically, managers should
carefully match their communication efforts to the nature of the innovations they are
implementing (Johnson et al., 1995). The attributes of innovations may entail more or
less challenging communication tasks (Fidler & Johnson, 1984), which in turn may make
more or less salient the role of communication in innovation processes, suggesting a

contingent impact of innovation attributes.

62

Managers of preventive health innovations need to be aware that knowledge about
the attributes of innovations may provide us with information about how best to manage
communication in the interest of innovation adoption and implementation. The use of
mediated communication, such as company newsletters, videos, magazines, etc., may
create an atmosphere of involvement and interest, producing a certain receptivity to
organization-wide innovations (Johnson et al., 1995). These channels are also more cost
efficient than interpersonally-driven participation or persuasion strategies (Fidler &
Johnson, 1984; Nutt, 1986). Especially in situations where there is a highly motivated set
of organizational members, the direct provision of information may be a highly effective
strategy (Katz & Kahn, 1978). Likewise, for innovations with high levels of perceived
relative advantage and acceptance, a mediated communication strategy is perhaps most
appropriate. Alternatively, in the case of certain complex and risky preventive health
innovations, direct interpersonal communication may be a necessary ingredient for
successful innovation implementation (Fidler & Johnson, 1984, Dearing, et al., 1994).

Finally, managers must not only be concerned with the successful adoption and
implementation of innovations to meet specific strategic objectives; they must also focus
on the generation of innovations, the process by which organizational members become
more innovative. The way in which managers respond to stakeholders’ perceptions of
innovation influences the organization’s ability to generate future innovations. For
example, managers who demonstrate the importance of organizational members’
perceptions of innovation by soliciting feedback and incorporating suggestions to
reinvent innovations are also cultivating the climate of innovation within their
organization. If organizational members, particularly idea champions, feel that their
voices are heard, then they will perceive that they have a higher level of participation in
innovation processes. In contrast, organizational members or idea champions who do not
perceive that management listens to their ideas will experience lower levels of

involvement in the innovation process. Since participation has been linked to

63

innovativeness in general (Albrecht & Ropp, 1984; F idler & Johnson, 1984; Johnson et
al., 1995; Johnson, et al., 1996), managers who are responsive to stakeholders’
participation in innovation processes have the potential to influence an organization's
level of innovativeness, hence its ability to generate future innovations. In organizations
such as the CISRC, where innovation is a central goal, understanding how to teach

organizational members to innovate is the key to the future.

FOOTNOTE

1In this study, innovation is defined as "an idea, practice, or object that is
perceived as new by an individual or other unit of adoption" (Rogers, 1983, p. 11). More
generally, innovation can be conceived of as "the adoption of an internally generated or
purchased device, system, policy, program, process, product, or service that is new to the
adopting organization" (Damanpour, 1991, p. 556). However, if one defines
organizational innovation broadly (a la Damanpour), one risks confusing it with
organizational change. While innovation and organizational change processes may
overlap, the terms are not interchangeable (although they are frequently treated as such in
the literature). How, then, does one distinguish organizational innovation from
organizational change?

According to West & Farr (1990), all innovation is change, but not all change is
innovation: Unintended change, undesired change, and routine change (e.g., work
stoppages and seasonal lay-offs) fall outside the rubric of innovation. For example,
organizational change encompasses the areas of administration, technology, and products
or services (Moberg & Caldwell, 1988), while innovation would most likely involve only
the latter three contexts. Thus, administrative changes, such as reorganizations,
personnel moves, downsizing, and changes in policies and procedures would be
considered organizational change efforts, but not necessarily innovations. On the other
hand, the development and introduction of a new technology, product, or services
could be conceived of as either organizational change or innovation. Note that, while
innovations may involve creative idea generation, not all innovations will be creative in
the absolute sense--they may just be perceived to be new by potential adopters.

It is important to make a distinction between organizational change and
innovation, because administrative changes entail outcomes that may be substantially
different from technological, product, and service innovations. While desired outcomes

of an administrative change might include increased efficiency, effectiveness, or

64

65

productivity, such consequences are not necessarily tied to innovations, where the goal
may be technical development or increased ability to innovate. In addition,
organizational change efforts and innovation may entail different sources of resistance.
For example, downsizing will, by definition, result in job loss for many organizational
members. This fear of personal loss may create an immediate source of resistance to
change. In contrast, sources of resistance associated with technological innovation,
such as the introduction of a new computerized communication system, may be rooted

in uncertainty, which can be reduced with information dissemination and training.

APPENDICES

APPENDIX A

66

Table 1

Overview of the Major Goals and Objectives of the Cancer Information Service

 

Goal;

. To use communication strategies to reduce cancer incidence, morbidity, and
mortality.

. To provide NCI-designated cancer centers and other major community cancer
organizations and intermediaries with a resource for developing outreach programs to
reach their various audiences.

c To establish a high-quality system that can serve as a resource and a database for
stimulating the development and implementation of new research projects in cancer

communications.

:1. .

. To support a network of regional CIS offices throughout the country that will serve as
local outlets for NCI to disseminate information on cancer to communities and serve
as catalysts for the adoption and adaptation of NCI/OCC education programs,
materials, and messages in the community.

. To operate a toll-free telephone service in the regional offices.

. To mobilize local media and community-based organizations to use and adopt OCC
programs, materials, and messages in support of NCI education initiatives.

. To establish reliable data collection strategies and dissemination techniques to
facilitate evaluation of the role of communication strategies in reducing morbidity and
mortality from cancer.

 

Nete. Abstracted from the Cancer Information Service Request for Contract Proposals,

January 3, 1992; National Cancer Institute, National Institutes of Health.

67

Table 2

Demographics for the Cancer Information Service

 

 

Demographic N Percentage
Education
High School Graduates / Some College 4 4
College Graduate 16 15
Some Post Graduate 22 21
Graduate Degree 62 58
Other 2 2
Lenthnffiemice
Less than 1 year 24 23
1-2 years 25 24
3-4 years 18 17
5-6 years 17 16
7-8 years 7 7
9+ years 12 11
missing 3 3
EunctionaLRQles
Office of Cancer Communication staff 14 13
Program Project staff 20 19
Project Directors 16 15
Telephone Service Managers 22 21
Outreach Coordinators 22 21
Principal Investigators 12 1 1

 

N=106

Note. Demographics calculated for participants who responded to the self-report

questionnaire or the communication log component of the baseline data collection in

November 1993.

68

Table 3

Items, Factor Loadings, and Reliablilities for Weak Ties

 

 

Item Factor Loading T1
1. Choice status .73
2. Contacts 1.01
3. Nonredundant contacts .96

 

Standard Score Alphas for Factor at T1, T2, T3, T4 = .93, .96, .93, .90

 

69

Table 4

Internal Consistency Error Matrix for Weak Ties

 

 

T1

Item Error
1 2

1 0

2 1 0

 

70

Table 5

Items, Factor Loadings, and Reliablilities for Perceived Organizational Innovativeness

 

 

 

 

Factor Loading

Item Time 1 Time 3
1. The CIS is creative in its method of operation. .72 .82
2. The CIS seeks out new ways to do things. .87 .94
3. The CIS frequently tries out new ideas. .84 .79

 

Standard Score Alphas for Factor at T1 and T3 = .85, .89

 

71

Table 6

Internal Consistency Error Matrices for Perceived Organizational Innovativeness

 

 

 

 

 

T1
Item Error

1 2 3
1 0
2 O 0
3 0 1 0
T3
Item Error

1 2 3
l 0
2 1 0

 

72

Table 7

Items, Factor Loadings, and Reliablilities for Pros

 

Factor Loading

 

Item

 

Time 2 Time 4

 

This intervention strategy...

1. is a good idea.

2. is a positive way to reach members of a target
audience.

3. is a sound policy option for reaching members
of a target audience.

4. is an acceptable method of outreach.

5. is something we can build on in the future.

6. is a more efficient means to reach targeted
populations than techniques we have used in
the past.

7. will result in greater behavioral change for
members of the target audience.

8. is a better way to provide targeted populations

with cancer information.

.74 .92
.78 .81
1.00 .97
.80 .83
.80 .88
.87 .84
.91 .66
.95 .86

 

Standard Score Alphas for Factor at T2 and T4 = .96, .95

 

Table 8

Internal Consistency Error Matrices for Pros

 

 

 

 

 

T2
Item Error
1 2 3 4 5 6 7
1 0
2 6 0
3 1 2 0
4 5 5 7 0
5 8 6 0 7 0
6 1 3 0 7 6 O
7 4 4 2 3 1 l 0
8 4 8 3 5 2 4 7
T4
Item Error
1 2 3 4 5 6 7
l 0
2 l 0
3 3 2 0
4 7 3 1 0
5 5 5 l l 0
6 6 1 4 1 O 4 O
7 2 l 4 3 3 1 7 0
8 1 0 2 1 6 7 3 1 8

 

Nete. Significant errors are in bold.

74

Table 9

Items, Factor Loadings, and Reliablilities for Cons

 

 

 

 

Factor Loading
Item Time 2 Time 4

This intervention strategy...
1. means that information specialists can't meet other

job responsibilities as well as they used to. .74 .94
2. will produce a visible change in our office's call

busy rate. .94 .88
3. will produce a visible change in our abandonment

rate. .87 .40

 

Standard Score Alphas for Factor at T2 and T4 = .88, .77

 

75

Table 10

Internal Consistency Error Matrces for Cons

 

 

 

 

 

T2

Item Error
1 2

1 0

2 1 0

3 1 1

T4

Item Error
1 2

1 0

2 1 0

 

76

 

 

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77

Table 12
Path Coefficients and Confidence Intervals for Model 1
“Short Term Effects of Weak Ties”

 

95 percent confidence interval

 

 

 

 

Parameter Path coefficient lower endpoint upper endpoint
PL2 .12 a10 .34
PL6 .05 219 .29
PL7 207 a32 .18
P16 .11 214 .36
P17 .20 205 .45
pig .54* .34 .74
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Weak ties (T3); 4 = Weak ties (T4); 5 = Innovativeness (T1); 6 = Pros (T2); 7 = Cons
(T2); 8 = Innovativeness (T3); 9 = Pros (T4); 10 = Cons (T4).

"‘ statistically significant, alpha = .05.

 

78

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Table 15
Path Coefficients and Confidence Intervals for Model 2

“Long Term Effects of Weak Ties”

 

95 percent confidence interval

 

 

 

 

 

 

 

 

 

 

 

 

Parameter Path coefficient lower endpoint upper endpoint
p13 -.19 -.43 .05
p23 -.26* -.46 -.06
P5,8 .53* .33 .73
p53 -.22 -.47 .03
136,10 -.36* -.58 -.14
p73 -.37* -.57 -.17
p79 23* -.01 .47
p3 .1 .21 * -.01 .43
139,10 --40* -.62 -.18

 

Nete. Parameters are numbered as follows: 1 = Weak ties (T1); 2 = Weak ties (T2); 3 =
Weak ties (T3); 4 = Weak ties (T4); 5 = Innovativeness (T1); 6 = Pros (T2); 7 = Cons
(T2); 8 = Innovativeness (T3); 9 = Pros (T4); 10 = Cons (T4).

* statistically significant, alpha = .05.

 

81

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APPENDIX B

82

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83

 

1994

February: Perceived Organizational Innovativeness (Tl)

Project 2 (Making Outcalls) pilot study begins

August: Innovation Characteristics (T2)

Project 2 (Making Outcalls) main study begins
1995 -—--—

August: Perceived Organizational Innovativeness (T3)

Project 2 (Making Outcalls) main study completed

November: Innovation Characteristics (T4)

Project 2 (Making Outcalls) conducts six-month follow-up

 

1996 ——

Eigmez. Project 2 Timeline

84

 

National Cancer Institute
Office of Cancer Communications

 

 

 

 

Cancer Information Service
1-800-4-CANCER

 

 

 

 

1 ' n I
- Telephone information specialists/individual
response to callers/mailouts to callers
- Physician Data Query
- Resource materials
- Subject-matter specialists/consultants
- Referral files (for local referrals)
- Booklets, pamphlets, flyers, etc., for mailouts
- Community outreach coordinators
- Mass-media campaigtns

 

 

 

 

IMajor strategies for reaching selected target populations l

Telephone service! Community outreach/
Information specialists/ Community intermediaries!
Publication distribution Mass-media campaigns

Figure}. Overview of the Cancer Information Service Network

85

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APPENDIX C

CISRC CHRONOLOGY

In June, 1993, the CISRC began the process of staffing, training, and piloting a
new intervention strategy to encourage women to receive regular mammograms. The
new intervention strategy, Project 2 (Making Outcalls to Promote Mammography)
utilizes the toll-free 1-800-4-CANCER number as a nexus from which to make cold calls
fmm the CIS tb low income and minority women in targeted communities in Colorado.
The following document gives a detailed summary of major developments in Project 2
over time, as well as a chronology of key events that affected the CISRC.

 

 

 

 

National Network Other Key

Date Project 2 Meetings Analysis Events

9/93 -1 1/93:
Project 2 staff In November, OCC The fust Network The final regional
conducted staff participated in Analysis data office was in place
formative research, a quality control collection took and the program
including focus meeting in place November 3- project grant was
groups and a Washington. The 5, during the same officially budgeted.
review of the Steering month there were Negotiations took
literature. The Committee numerous changes place for evening
findings were used Meeting took place in the e-mail hours on the
to formulate outcall in Denver on system. telephone service.
protocols. September 8-9.

mm -

2 I94: In January, training In December, The second In January, an
for the outcall 1993, the National Network Analysis OCC memo
protocol began at Conference was data collection took specified routing of
the Rocky held in Atlanta. place February 8- requests from
Mountain CIS. In 10, at which time regional offices to
February, 1994, baseline perceived other OCC staff
project staff began organizational through the Project
a two-month pilot innovativeness data Officer. In
of the outcall were gathered. February, Kate
protocols. Harsh winter Duffy Mazan
Debriefing surveys weather may have announces her
and follow-up contributed to the sabbatical, and
surveys were delayed receipt of Chris Thomsen
developed at this questionnaires for becomes head of
time. some offices. the CIS. At that

 

 

 

 

time, task forces
were in the process
of forming.
Individual e-mail
id's were in place
for people at the
National Office,
and a voice mail
system was added
across the network.

 

87

 

88

 

 

 

 

National Network Other Key

Date Project 2 Meetings Analysis Events
3/94 - 5/94:

Biostat core The third Network

collaborated with Analysis data

project staff to collection took

computerize outcall place during May

protocol. In May, CIS 16-18.

staff were trained to

implement protocol.

Debriefmg surveys and

follow-up surveys were

pretested. In addition,

TISs completed a

process evaluation

about making outcalls.
6/94 - 8/94:

In July, 1994, Project 2 The national CIS The fourth On June 9, the

was just beginning the meeting took place Network Analysis first issue of

main pilot study, and in Washington, DC data collection took CISRC NEWS

the CISRC was in June, 1994. The place during was distributed

discussing various CISRC Members August 24-26, at to the network

strategies to reach Council Meeting which time in the Weekly

working women (e.g., took place baseline innovation Package.

making outcalls in the simultaneously characteristics data

 

evening), and to create
incentives for
information specialists
to make outcalls (e.g.,
financial
reimbursements or
hiring a half-time
information specialist
to make outcalls).
Debriefing interviews
were conducted , and
by mid-August, Project
2 reported reaching
women with a lower
mammography
adherence rate than
women who were
calling in to the CIS.

 

with the meeting of
the newly-formed
Network Analysis
Advisory Board in
Washington from
June 21-24. The
CISRC
Investigators
Meeting took place
in Denver on
August 30-31.

 

were gathered.

 

 

 

89

 

 

 

 

 

National Network Other Key

Date Project 2 Meetings Analysis Events

9/94 -

11 I94: Initiated evening The Telephone The fifth Network Erroneous minutes
hours for making Services Managers Analysis data of the General
outcalls to reach Meeting took place collection took Session of the June
more working in Bethesda, MD, place during CISRC Members
women. 650 November 7-9. November 1-3. Council Meeting
subjects had been The were distributed by
accrued into Computerization the CISRC.
Project 2 at this Task Force met in Revised minutes
time. Denver in were sent out the

November. following week.

12/94 -

2 I95: Six-month follow The External The sixth Network
up interviews were Advisory Meeting Analysis data
conducted . Lori took place in collection took
Crane received a Denver on January place during
Department of 5-6. The February 6-8.
Defense grant to Evaluation Task
add a fourth arm to Force met in
the study, Washington on
contingent upon January 19-20.
receiving written
informed consent
from participants.

3/95 - 5/95:
Received 60 % of The CISRC The seventh
the needed sample Members Council Network Analysis
in the three arms of Meeting took place data collection took
Project 2. in Denver on place during May
Preliminary results March 30-31. 16-18.
reported at the May Communication
Steering log changed to
Committee indicate capture only
a statistically communication at
significant the national level.
difference in
mammography
adherence rates
between

 

intervention and
control groups.
Also, TISs reported
lower job
satisfaction
associated with
making outcalls.

 

 

 

 

 

90

 

 

 

 

 

 

 

 

 

National Network Other Key
Date Project 2 Meetings Analysis Events
6/95 - 8/95:
Project 2 exceeded On June 1, the In July, Dave
accrual goals, CISRC Steering Johnson, co-
completing the Committee director of the
project by the end Meeting convened Administrative
of June. in Chicago. Seven Core, went on
concepts were sabbatical. The
identified and eighth Network
targeted for Analysis data
development in the collection took
CISRC renewal place during
application, August 22-24, at
including: Project which follow-up
1 renewal, Project perceived
2 renewal, Project organizational
3 renewal, innovativeness data
Network Analysis were gathered.
renewal, Internet During this data
study, Outreach collection, the
Coordinator communication log
evaluation, was changed to
minority accrual to capture
clinical trials, and communication
pain control. conducted by
facsimile and
electronic mail.
9/95 - 11/95
76% six-month On October 16-17, The ninth Network In October,
follow-up response the CISRC Analysis data evening hour
rate. Discrepancies Member’s Council collection took telephone service
noted between met in Denver. place during was eliminated due
respondents self- Eight concepts November 6-8, at to budget cutbacks.
reports at baseline were discussed for which time follow- In November, the
and follow-up. development in the up innovation OCC staff was
CISRC renewal characteristics data furloughed due to
application. were gathered. the federal
government budget
impasse.
Sources

CISRC Investigators Meeting minutes, August 1994
CISRC Members Council Meeting minutes, June 1994, October 1995
CISRC POI Conference Call minutes, August 1993 - February 1996.

CISRC Steering Committee Meeting minutes, September 1993

 

 

APPENDIX D

FEBRUARY 1994 CISRC
COMMUNICATION LOG

This log asks you to record your work-related communication with individuals within the CISRC network
on the dates of February 8 through 10. We would like you to keep a diary of your work-related
interpersonal contacts with members of the CISRC Network. It may be easier for you to record each
communication event as it occurs. For your convenience, we have provided pro-dated pages for you to
record your communication contacts within the CISRC network from February 8 through 10. If you need
additional space, please copy the extra page provided, date it, and attach it to the beige log.

For purposes of this study, this network includes the Office of Cancer Communication staff, Principal
Investigators, Project Directors, Outreach Coordinators, and Telephone Service Managers at the CIS
regional offices, and members of the Cancer Information Service Research Consortium (the Program
Project Grant). A directory of individuals within the CISRC Network has been included for your
convenience (see enclosure).

The next two pages describe in more detail how to complete the log. Each page of the communication log
contains definitions for each of the categories for your convenience.

If you did not communicate with other members of the CISRC Network on a given day, please place a
check in the appropriate space on the page for that day.

Please write your name and job title in the space provided below:

Name:

 

Job Title:

 

If you did not have any communication with other members of the CISRC Network between
February 8 and February 10, please check this space , place this survey in the enclosed
envelope, and complete the questionnaires in the blue and green packet.

91

92

COMMUNICATION CONTACTS LOG
Key Term Summary

NAME: Please print your name in the space provided.

TITLE: Please place a check in the space preceding your title. If your title is not listed, please check
"Other", and record your title in the space provided.

REGION: Please record the number assigned to the CIS regional office in which you work. For
example, the staff in the Kentucky office would record a "9" in the space provided. If you work in the
National Office, please write the word "National" in the space provided. If you are a member of the
Program Project staff only, please write "Program Project" in the space provided.

CONTACTS: We are only interested in the work-related communication you initiate or receive with the
Office of Cancer Communication staff, Principal Investigators, Outreach Coordinators, Telephone Service
Managers, and Project Directors, and members of the Cancer Information Service Research Consortium
(the P01 grant). Please indicate the fill] name of the person with whom you communicated. (See enclosed
directory as needed.) Include as a contact phone calls where messages were left, even though you were not
able to speak with the person directly. Please also indicate if the contact was part of a conference call (see
details below).

TOPIC: We are primarily interested in national communication relating to CIS and Program Project
issues. Please indicate whether the communication addressed
1) intervention strategies, (initiatives that relate to the development or implementation of
programs which focus on reaching various target populations such as counseling protocols,
targeted outreach activities using the telephone, responses to calls associated with communication
campaigns, etc.), especially like the ones developed by this Program Project;
or dealt with
2) other work-related issues focusing on maintaining and/or enhancing the day-to-day operation
of the CIS (e.g., budgets, record keeping, ordering materials, or other administrative activities).
Please place an "X" in the space preceding the appropriate category. If both areas were discussed, place an
"X" in the space preceding "Both". We are interested in important communication contacts you have
which focus primarily on network-wide, national issues. Do NOT record conversations which are purely
of local interest (e.g., "Would you please put toner in the copier?").

MINUTES: Please record the length of the communication contact in minutes.

CONFERENCE CALLS ONLY: For conference calls, please estimate the number of individuals who
took part in the call, provide a general description of the topics discussed, and a description of the call
participants’ role within the CIS (e.g., Project Directors). For “Communication Contact,” pleade record the
name of the individual who led the conference call.

If you have any questions about these changes or how to complete any part of this log, Principal
Investigators and Outreach Coordinators contact Caroline Ethington at (517) 355-2170; Project Directors,
Telephone Service Managers, members of the Office of Cancer Communication and Program Project staff
may contact Marcy Meyer or Judy Berkowitz at (517) 355-5148.

93

 

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98

NOTES

Please provide any comments you have regarding communication within the CISRC network in the space
provided. If you need additional space, please continue on the back of this page or attach other pages as
necessary.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Thank you very much for your participation.

Please return this form by February 15, 1995
in the enclosed self-addressed stamped envelope to:

Dr. J. David Johnson
Department of Communication
4738 Communication Arts & Sciences Bldg.
Michigan State University
East Lansing, MI 48824
(517) 432-3311
FAX (517) 432-1 192

APPENDIX E

AUGUST 1995 CISRC COMMUNICATION CONTACTS LOG

This packet contains three parts. Please note that the gray communication log is
considered
Part A.

NOTE: there has been a change made to the communication log. We are now
asking you to indicate whether your work-related contact was made using one of

the following channels: 2 = telephone (including face-to-face communication), Q =
e-mail (including FTS-2000 and all other types), = fax.

Part B asks about your perceptions regarding your role within the CIS.
Part C asks for your opinions about innovations in general within the CIS.

Please feel free to write down any comments you have concerning communication within
the CISRC in Part D, the Notes section of this booklet.

This questionnaire may be completed at any time, but we do request that you return both
the pink questionnaire and the gray communication contact log to us in the enclosed self-

addressed, stamped envelope by August 30, 1995.

Please write your name and job title in the space provided below:

 

Name:

Job Title:

 

99

100

EXAMPLE

COMMUNICATION CONTACTS WITHIN THE CISRC NETWORK

 

Your Name: Title: _ Principal Investigator , . QLI
J9 /_ Project Director Region. —~-
£0141, M” ' _ Outreach Coordinator
__ Telephone Service Manager
Date: Tuesday, August 22, I995 _ Other (please specify): 9

 

Place a check in the space provided if you did not communicate within the
CISRC Network on this day.

NOTE: Please use the following to determine your mode of communication for each
contact (circle ONE): 3 = telephone, Q = e-mail (including FTS-2000 and all other

types), = fax

COMMUNICATION NUMBER

 

 

CONTACTS IN LENGTH TOPIC"r MODE
GROUP*
CW (72 Number; _ Intervention Strategies
/ Other work-related 3
Both
19 5O
PURPOSE: 0219 Call
1&6 (”Ia/ Number; L Intervention Strategies
Law _ Other work-related 2 Q
LI __ Both
PURPOSE:

 

Intervention Strategies
Other work-related i
Both

”QC? “8% Number:

PURPOSE: imam-5} g

\

lll‘

LN

 

 

 

 

 

 

AN EXAMPLE: On August 22, the following communication contacts occurred for the
r0j ect Director in Region 24. A conference call for all Project Directors with Chris
Omsen which lasted 50 minutes pertaining to other work-related matters. A four-page
ax was sent to A1 Marcus concerning staff training on the new 5 A Day counseling
protocol. Jay Doe sent a three-page, broadcast e-mail to eight people about training
prOcedures in relation to intervention strategies.

1Vote: The visit by the telephone service manager from Region 24 was omitted since it
Was not a national contact.

 

101

COMMUNICATION CONTACTS WITHIN THE CISRC NETWORK

Your Name: Title: _ Principal Investigator Region: .

_ Project Director

_ Outreach Coordinator

Date: Tuesday, August 22, I995 __ Telephone Service Manager
_ Other (please specify): -)

 

 

Place a check in the space provided if you did not communicate within the CISRC Network on
this day.

COMMUNICATION NUMBER IN

CONTACTS GROUP* LENGTH“ TOPIC MODE***
Number: Intervention Strategies i Q
Other work-related
PURPOSE: _ Both

 

 

Number: Intervention Strategies ' Q
Other work-related
PURPOSE: __ Both

 

Number: Intervention Strategies ' Q
Other work-related
PURPOSE: __ Both

 

Number: Intervention Strategies 3 Q
Other work-related

PURPOSE: Both

 

Number: Intervention Strategies i Q
Other work-related

PURPOSE: Both

 

Intervention Strategies ' Q
Other work-related
PURPOSE: _ Both

Number:

 

Number: Intervention Strategies i Q
Other work-related

PURPOSE: Both

\

 

 

 

 

 

 

 

:-
Topic: We are primarily interested in communication relating to CIS and Program Project issues. Please indicate
whether the communication addressed
I) intervention strategies, (initiatives that relate to the development or implementation of programs which
focus on reaching various target populations such as counseling protocols, targeted outreach activities using
the telephone, responses to calls associated with communication campaigns, etc.), especially like the ones
developed by this Program Project;

0’ dealt with

2) other work-related issues focusing on maintaining and/or enhancing the day-to-day operation of the CIS
(e.g., budgets, record keeping, ordering materials, or other administrative activities).

PleElse place an "X" in the space preceding the appropriate category. If both areas were discussed, place an "X" in the
SDace preceding "Both". We are interested in important communication contacts you have which focus primarily on
network-wide issues. Do NOT record conversations which are purely of local interest (e. g., "Would you please put

* *toner in the copier?").

Conference Calls: For conference calls only, please estimate the number of individuals who took part in the call, a
general description of the topic(s) discussed, and the roles within the CISRC Network (e.g., Project Directors) of
the individuals who participated. Record the name of the lead individual under "Communication Contacts."

Your Name:

102

COMMUNICATION CONTACTS WITHIN THE CISRC NETWORK

 

Date: Wednesday, August 23, 1995

Title:

Principal Investigator

_ Project Director
_ Outreach Coordinator

_ Telephone Service Manager

_ Other (please specify): -)

Region: ,

Place a check in the space provided if you did not communicate within the CISRC Network on

this day.

COMMUNICATION
CONTACTS

NUMBER IN
GROUP*

LENGTH“

TOPIC

MODE***

 

PURPOSE:

Number:

Intervention Strategies
Other work-related
Both

3 B

 

PURPOSE:

Number:

Intervention Strategies
Other work-related
Both

 

PURPOSE:

Number:

Intervention Strategies
Other work-related
Both

 

PURPOSE:

Number:

Intervention Strategies
Other work—related
Both

 

PURPOSE:

Number:

Intervention Strategies
Other work-related
Both

 

PURPOSE:

Number:

Intervention Strategies
Other work-related
Both

 

PURPOSE:

Number:

Intervention Strategies
Other work-related
Both

 

PURPOSE:

Number:

Intervention Strategies
Other work-related
Both

 

PURPOSE:

Number:

Intervention Strategies
Other work-related

Both

 

PURPOSE:

Number:

Intervention Strategies
Other work-related
Both

 

PURPOSE:

Number:

Intervention Strategies
Other work-related
Both

 

 

PURPOSE:

Number:

 

 

 

Intervention Strategies

Other work-related
Both

 

 

 

103

COMMUNICATION CONTACTS WITHIN THE CISRC NETWORK

Your Name: Title: __ Principal Investigator

_ Project Director

_ Outreach Coordinator

_ Telephone Service Manager

_ Other (please specify): 9

Region: ,

 

Date: Thursday, August 24, I995

 

Place a check in the space provided if you did not communicate within the CISRC Network on
this day.

COMMUNICATION
CONTACTS

NUMBER IN

GROUP* LENGTH“ TOPIC MODE“ *

 

PURPOSE:

Number:

Intervention Strategies
Other work-related
Both

3 Q

 

PURPOSE:

Number:

Intervention Strategies
Other work-related
Both

 

PURPOSE:

Number:

Intervention Strategies
Other work-related
Both

 

PURPOSE:

Number:

Intervention Strategies
Other work-related
Both

 

PURPOSE:

Number:

Intervention Strategies
Other work-related
Both

 

PURPOSE:

Number:

Intervention Strategies
Other work-related
Both

 

PURPOSE:

Number:

Intervention Strategies
Other work-related
Both

 

PURPOSE:

Number:

Intervention Strategies
Other work-related
Both

 

PURPOSE:

Number:

Intervention Strategies
Other work-related

Both

 

PURPOSE:

Number:

Intervention Strategies
Other work-related
Both

 

PURPOSE:

Number:

Intervention Strategies
Other work-related
Both

 

 

PURPOSE:

 

Number:

 

 

Intervention Strategies

Other work-related
Both

 

 

 

104

NOTES

Please provide any comments you have regarding communication within the CISRC in
the space provided. If you need additional space, please continue on the back of this page
or attach other pages as necessary.

 

 

 

 

 

 

 

 

 

 

 

 

 

Thank you very much for your participation.

Please return this form by August 30, 1995
in the enclosed self-addressed stamped envelope to:

Dr. J. David Johnson
Department of Communication
473B Communication Arts & Sciences Bldg.
Michigan State University
East Lansing, MI 48824
(517) 432-3311
FAX (517)432-1192

APPENDIX F

CIS INNOVATION SURVEY

Directions: The following statements deal with your opinions about new intervention strategies within
the CIS nationally. Intervention strategies are initiatives that relate to the development or implementation
of new methods for reaching target audiences such as counseling protocols for special target populations,
targeted outreach activities using the telephone, responses to calls associated with communication
campaigns, and other national initiatives like those developed by this program project.

We would like to respond by indicating how much you agree or disagree with each statement on a scale of
0 to 10 where 0 indicates "total disagreement" and 10 indicates "total agreement". Please answer these
questions for the CIS as a whole, rather than focusing on purely local concerns.

 

 

Scale:

Total Disagreement 0 l 2 3 4 5 6 7 8 9 10 Total Agreement

 

122811311911
1 have a reasonable amount of input into the creation of new intervention strategies at the CIS.
My job description accurately reflects the nature of my work.
There is a reliable source of funding for new intervention strategies at the national level.
I am satisfied with the quality of communication within the CIS.
Information is shared by members at all levels of the CIS.
I learn about new intervention strategies at CIS in the best possible way.
Most people who work for the CIS are very creative in how they go about implementing new
intervention strategies.
The policy and procedures manual for the CIS covers what happens in a typical day.
There are a number of people who have the skills necessary to implement new intervention
strategies.
The amount of information I receive related to new intervention strategies is adequate.
I am able to communicate important work-related problems to people at all levels of the CIS.
Decisions about new CIS intervention strategies are made by those who best understand the
work.
The CIS is creative in its method of operation.
When a decision is made regarding a new intervention strategy, those people most likely to be
affected are usually asked for their ideas.
Materials and supplies are available when needed for new intervention strategies.
CIS's formal communication system is efficient.
I am pleased with the quality of information that I receive from people at higher levels of the

CIS.

105

 

106

 

 

Scale:

 

Ix)
DJ
A
LII
O\
\I

Total Disagreement 0 I 8 9 10 Total Agreement

 

Exaluatism

The CIS provides me with a rationale as to how the new intervention strategies fit into its goals
and objectives.

The CIS is receptive to new ideas.

Policies and procedures are strictly enforced at CIS.

New intervention strategies can easily be added to what we are already doing.

The CIS maintains good communication between its members.

I have access to information from individuals at my same level in the CIS.

I am convinced by what I am told that new interventions are worthwhile projects.

The CIS responds quickly to necessary changes related to new intervention strategies.

I am usually consulted before the CIS adopts new intervention strategies.

I follow established procedures exactly.

I have the time to pursue new approaches to intervention strategies.

The CIS has reached a consensus about how to accomplish objectives at the local and national
level.

I fully understand the importance of new interventions at the CIS.

The CIS seeks out new ways to do things.

I feel I can initiate ideas for new intervention strategies

I feel free to change the way I do things at work.

CIS members communicate frequently about new intervention strategies.

The CIS frequently tries out new ideas.

When you were answering Part C dealing with innovations, which intervention strategy or strategies came to
mind?

 

 

 

APPENDIX G

CANCER INFORMATION SERVICE/PROGRAM PROJECT NETWORK
CISRC INNOVATION CHARACTERISTICS SURVEY

Part B asks for your opinions on several issues related to the separate projects contained in the
CISRC Program Project grant.

The questions in Part B of this packet could be interpreted in multiple ways. Please take each
question at its most general level and try to overlook specific instances that differ from your
overall impression. We would like you to respond to each question from your perspective in
your office, answering every item as it relates to each project.

We understand that you may not be completely familiar with each of the components of the
program projects: This is not meant to be a test, rather we would like to find out peoples' current
level of awareness about the component parts of each program project. If you do not yet have
enough information to evaluate an item with respect to a particular program project, write "DK"
(for "don't know) in the space provided for item evaluation. If you feel uncomfortable responding
for another reason (e.g., the program project doesn't relate to your work or you have heard
conflicting things about the intervention strategy), write "NR" (for "no response at this time").

This questionnaire may be completed at any time, but we do request that you return both the ivory
questionnaire and lavender communication contact log to us in the enclosed self-addressed,
stamped envelope by August 29, 1994.

Please write your name and job title in the space provided below:

Name:

 

Job Title:

 

107

108

CISRC INNOVATION CHARACTERISTICS SURVEY

Directions: The following items are statements regarding the three new intervention strategies
developed by the CISRC program project: Project 1 consists of the development and implementation of
proactive mammography screening counseling, Project 2 is geared toward making outcalls to low-
income women in underserved neighborhoods in order to promote mammography screening, and Project 3
implements a mass-media campaign that employs culturally sensitive videos to encourage African
American smokers to call the CIS for more information about smoking cessation.

We would like you to respond to the following items relating to these projects by indicating how much you
agree or disagree with each statement on a scale of O to 10 where 0 indicates "total disagreement" and 10
indicates "total agreement."

We would like you to respond to each question from the perspective of your office, answering
every item as it relates to each project. If you are not familiar enough with a particular
program project to answer an item, please write "DK" ("don't know") in the space provided
for item evaluation. If you feel uncomfortable responding for another reason, write "NR"
("no response at this time").

 

 

 

 

Scale:
Total Disagreement 0 l 2 3 4 5 6 7 8 9 10 Total Agreement
DK = "don't know" NR = "no response at this time"
Item Assessment
proactive making smoking
This intervention strategy... counseling outcalls cessation

 

will change the way that information is disseminated by the
CIS.

 

is similar to the techniques we have used in the past.

 

places a number of additional demands on information
specialists.

 

can be adapted to fit local needs.

 

presents risks to our office.

 

is more effective in communicating with targeted populations
than our previous efforts.

 

is a good idea.

 

is compatible with our office's customary method of
providing cancer information to the public.

 

will have outcomes that will be easy to measure.

 

is too complex.

 

can be modified for use in future campaigns

 

has a number of uncertain outcomes.

 

 

will have a greater impact on the target audience's cancer
awareness than previous national initiatives.

 

 

 

 

 

109

 

 

 

 

Scale:
Total Disagreement O l 2 3 4 5 6 8 9 10 Total Agreement
DK = "don't know" NR = "no response at this time"
Item Assessment
Project 1 m1 Ema
proactive making smoking
This intervention strategy... counseling outcalls cessation

 

should be supported by people at all levels of the CIS.

 

has required our office to change the ways we do
things.

 

will have clear outcomes.

 

has many different components.

 

can accommodate unique outreach efforts in our
regional CIS office.

 

is a risky method for communicating cancer
information to members of a target audience.

 

will result in greater behavioral change for members of
the target audience.

 

is a positive way to reach members of a target
audience.

 

will produce a visible change in our office's call busy
rate.

 

means that information specialists can't meet other job
responsibilities as well as they used to.

 

is something we can build on in the future.

 

is a reliable way to communicate cancer information to
members of a target audience.

 

is a more efficient means to reach targeted populations
than techniques we have used in the past.

 

is a sound policy option for reaching members of a
target audience.

 

is different from previous national initiatives.

 

will produce a visible change in our abandonment rate.

 

raises a number of issues for information specialists.

 

can be easily adapted to different situations that arise
at our office.

 

has predictable results.

 

is a better way to provide targeted populations with
cancer information.

 

is an acceptable method of outreach for the CIS.

 

 

will have a clear effect on the target audience.

 

 

 

 

 

110

 

 

 

 

Scale:
Total Disagreement 0 l 2 3 4 5 6 7 8 9 l0 Total Agreement
DK = "don't know" NR = "no response at this time"
Item Assessment
proactive making smoking
Piloting this intervention strategy in a few offices counseling outcalls cessation

 

informs people in other offices about its strengths and
weaknesses.

 

informs people in other offices about its effectiveness before
it is adopted by the entire network.

 

enables people in other offices to see how well the strategy
works in the target audience.

 

provides a valuable learning experience for other CIS offices.

 

helps people in other offices gain information about whether
the project will work across the entire network.

 

 

lets people in other offices learn about new procedures before
the entire network is asked to adopt them.

 

 

 

 

 

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