Human Resources

AD 320
HUMAN RESOURCES MANAGEMENT
TERM PROJECT

BY:
Serdar Çalışkan
Fulya Yüksel Ersoy
Doruk Küçüksaraç
Sevnur Malik
Gülin Serpel

09.06.2009

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TABLE OF CONTENTS
I. LITERATURE REVIEW
A. What is Organizational Learning? ……………………………………3
a. Individual Learning and Organizational Learning…………………...4
b. Learning Organizations………………………………………………5
c. Why do firms learn?.............................................................................5
d. Levels of Learning……………………………………………………6
e. Factors Facilitating Organizational Learning………………………...7
f. Four Contrasting Models of Organizational Learning………………..9
B. What is innovativeness in organizations?...............................................13
a. Why some organizations are more innovative than others?.................14
b. Types of Innovation…………………………………………………..17
c. Innovation Process in Organizations…………………………………18
d. How manageable is the innovation process?........................................20
C. Comparison of Organizational Learning & Organizational
Innovativeness……………………………………………………………21
II. STATISTICAL ANALYSIS
A. Analysis of General Characteristics of Our Companies........................25
B. Hypothesis about Sector’s Differences and Organizational
Learning&Innovation...............................................................................27
C. Hypothesis I………………………………………………………………28
D. Hypothesis II……………………………………………………………...31
E. Hypothesis III……………………………………………………………..34
F. Hypothesis IV……………………………………………………………..37
III.CONCLUSIONS…………………………………………………………………42
IV. APPENDIX……………………………………………………………………….43
V. REFERENCES…………………………………………………………………..44

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I. LITERATURE REVIEW

What is Organizational Learning?

The idea of organizational learning has been present in the management studies
literature for decades but as it is said by Mark Easterby-Smith it has only become widely
recognized in the past twenty years. It is argued in the book Organizational Learning and the
Learning Organization that “Two developments have been highly significant in the growth of
the field. First it has attracted the attention of scholars from disparate disciplines who had
hitherto shown little interest in learning processes. For example, business strategies have
realized that the ability of the organization to learn faster, or “better”, than its competitors
may indeed be the key to long term business success (Collis, 1994; Grant, 1996). Some
economists have taken a similar path, arguing that firms learn by doing, as well as through
formal learning processes. Second development is that many consultants and companies have
caught onto the commercial significance of organizational learning. Consultants and
practicing managers have added to the theoretical literature on the learning organization with
accounts of how their own interventions have worked out in practice.” Organizational
learning approach is a very critical success factor for the companies today so they should give
attention to this issue. Definitions of organizational learning found in the literature include:
encoding and modifying routines, acquiring knowledge useful to the organization, increasing
the organizational capacity to take productive action, interpretation and sense-making,
developing knowledge about action-outcome relationships, and detection and correction of
error.

The important points to note about these definitions are that learning organizations:

Are adaptive to their external environment
Continually enhance their capability to change/adapt
Develop collective as well as individual learning
Use the results of learning to achieve better results

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Individual Learning and Organizational Learning

Some researchers contend that human capital by itself is of little value. For example,
Edvinsson (1996) argued that without the supporting resources of a firm, people do not have
the ability to do anything with their ideas. Nonaka & Takeuchi (1995) suggested that human
capital alone may not benefit the organization if there are no mechanisms in place for
employees to share knowledge with one another. Although learning is essentially based on
individuals in the workforce, a firm can learn as well. Evolutionary economic theorists have
suggested that firms effective at 'learning' develop routines that allow them to effectively
develop, store and apply new knowledge on a systematic basis (Nelson & Winter, 1982).
Organizational socialists suggest that a firm can be understood as a social community
specializing in speed and efficiency in the creation and transfer of knowledge (Kogut &
Zander, 1996). Thus, organizational learning is not simply an aggregation of the knowledge
held by a set of individuals (Brown & Duguid, 1991). It emphasizes the interaction patterns of
employees through which people acting together to achieve a meaningful purpose. According
to the knowledge-based view of the firm, knowledge starts with the individual and firms are
superior to markets in their ability to integrate knowledge across individuals (Kogut &
Zander, 1996).

An organization must try to encourage and provide various learning mechanisms so
that knowledge can be easily shared and enhanced. Because researchers comment that no
systematic effort has been devoted to developing valid measures for learning-related
constructs (e.g. Sinkula, 1994; Slater & Narver, 1995), we explored the construct of learning
orientation drawn from knowledge management theories. The learning orientation refers to an
organization-wide commitment to promote knowledge creation and sharing so as to increase
the firm's capability. Six components of organizational learning orientation were identified
(ICT, culture, organizational structure, measurement system, resource and leadership support)
by reviewing the major knowledge management literature. An organization that emphasizes
these six factors is considered a learning-committed organization.

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Learning Organizations

Regarding learning, Mark Dodgson wrote in his article “It can be described as the
ways firms build, supplement and organize knowledge and routines around their activities and
within their cultures, and adapt and develop organizational efficiency by improving the use of
the broad skills of their workforces. This broad definition incorporates a number of
assumptions:
-learning generally has positive consequences even though the outcomes of learning may be
negative, i.e. firms learn by making mistakes.
-although learning is based on individuals in the workforce, firms can learn in total. While
emphasizing the role of human agency in learning, corporate and group culture is influenced
by individual learning and can assist the direction and use that learning.
-learning occurs throughout all the activities of the firm, and, as will be argued later it occurs
at different speeds and levels. Encouraging and coordinating the variety of interactions in
learning is a key organizational task.”

Mark Dogson continues with the definition of learning organizations. “Firms that
purposefully construct structures and strategies so as to enhance and maximize organizational
learning have been designated „learning organizations‟. The characteristics of the learning
company are described by Pedler et al. (1989) who define it as „an organization which
facilitates the learning of all its members and continually transforms itself‟, and argue that it:
-has a climate in which individual members are encouraged to learn and to develop their full
potential.
-extends this learning culture to include customers, suppliers and other significant
stakeholders.
-makes human resource development strategy central to business policy.
-continually undergoes a process of organizational transformation.”

Why do firms learn?

Common explanations of the need to learn are the requirement for adaptation and
improved efficiency in times of change. Learning is seen as a purposive quest to retain and
improve competitiveness, productivity, and innovativeness in uncertain technological and
market circumstances. The greater the uncertainties are, the greater the need for learning is.
Learning is a key feature in the process by which firms accumulate technology in order to
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compete. This is seen particularly in Japanese firms, whose industrial organization is
increasingly observed as a model to be replicated (Marceau 1992). Japanese firms place
particular emphasis on learning (Pucik 1988b).
Bertrand Moingeon defines learning why as organizational members inquiring into
causality using diagnostic skills. The objective is to develop these processes as a strategic
capability, such that individual members develop the capacity to diagnose and identify
underlying causes in a variety of new situations, including potentially difficult interpersonal
situations.
According to Dodgson, by building the metaphor of individual learning, conflict, and
hence learning, can be seen as inevitable in organizations as it is in individuals. It is a natural
state. Organizational learning is as natural as learning in individuals as they attempt to adjust
and survive in an uncertain and competitive world. We simply agree with the idea that firms
should continuously learn in not to lose their competitive advantage and better deal with the
new situations. Learning improves the competitive advantages we say “core competence” of
the companies.

Levels of Learning

John Farago and David J. Skyrme had stated that a learning organization is not about
'more training'. While training does help develop certain types of skill, a learning organization
involves the development of higher levels of knowledge and skill. They have developed a 4-
level model that we found the most useful:

Level 1: Learning facts, knowledge, processes and procedures. Applies to known situations
where changes are minor. We think that this is the easiest one and most of companies are
involved in that level of learning.

Level 2: Learning new job skills that are transferable to other situations. Applies to new
situations where existing responses need to be changed. Bringing in outside expertise is a
useful tool here. This is more difficult to achieve for many companies in Turkey. However, it
is very important for today‟s business environment to survive.

Level 3: Learning to adapt. Applies to more dynamic situations where the solutions need to
be developed. Experimentation and deriving lessons from success and failure is the mode of
learning here. Unfortunately very few companies can apply this level of learning in their
organizations, but the ones who achieve are competitively advantageous to others.

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Level 4: Learning to learn. It is about innovation and creativity; designing the future rather
than merely adapting to it. This is where assumptions are challenged and knowledge is
reframed. This is the highest level of learning. It is about being the leader of the market,
leading the change. The innovative companies such as Apple, Google are the ones who make
this successfully. They have the products that design the future. They create the trends and the
future and others follow them.

Factors Facilitating Organizational Learning

Ricardo Chiva-Gómez comprehensively reviews the literature and represents his
findings in the paper called “The facilitating factors for organizational learning: bringing
ideas from complex adaptive systems”. According to Chiva-Gómez organizational learning
literature was divided into two categories by Argyris and Schön (1996, p. 180). One is “more
practically orientated and prescriptive” and the other is “more critical and descriptive”
literature of organizational learning. The first one is focused on the development of normative
models for the creation of a learning organization which has several facilitating factors. The
latter is mostly related with nature and process of learning. Hence according to author two
main categories of organizational learning arise (Easterby-Smith et al., 1998; Easterby-Smith
and Araujo, 1999): cognitive perspective (based on individual learning) and social perspective
(based on relational orientation).
Both studies from cognitive approach and social approach suggest factors that are
facilitating organizational learning. Chiva-Gómez includes in this article a great deal of
important names and their findings (Table 1 summarizing review of Chiva-Gómez is included
in the appendix). Here, we would like to mention findings of Hedberg and Ulrich as 2 brief
examples.
Chiva-Gómez indicates that Hedberg identifies 4 key factors as main facilitators of
organizational learning. These are: “(1) promoting experimentation; (2) encouraging
awareness in the organization, i.e. through discovering more about the organization; (3)
redesigning and improving inner environments (rewards and punishments); (4) achieving
dynamic balances, through diversity and heterogeneity. According the Hedberg, employees
should be free to experiment and make failures. Cost of these failures should be shared
through organization and employee selection should be based on applicants‟ ability to
effectively structure problems.
Chiva-Gómez indicates that Ulrich, in the learning organization literature, describes
some important factors regarding learning ability. These are “(1) building a commitment to
learning capability by making learning a visible and central element of the strategic intent, by

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investing in learning and training, by measuring learning, etc.; (2) working to generate ideas
with impact by experimenting, continuous improvement, competence acquisition and
observing what others do; (3) working to generalize ideas with impact by a shared mind-set,
capacity for change, or leadership.”
We understand that researchers have a different understanding of organizational
learning and factors smoothing the progress of organizational learning. However, from these
examples and information given in the appendix we can conclude that despite these
differences researchers identify similar points as factors facilitating organizational learning.
After these analyses the author of the article proposes that the second perspective
namely social approach has similarities with Complex Adaptive Systems (CAS). Before going
into the details of this issue, we will have a look on what CAS is and what are its key
characteristics.
Sherman and Schultz (1998, p. 17) define CAS as a system:
“. . . composed of interacting „agents‟ following rules, exchanging influence with their
local and global environments and altering the very environment they are responding to by
virtue of their simple actions.”
According to Chiva-Gómez “CASs are the combination of three concepts: they have
many autonomous parts, they are able to respond to external changes, and form self-
maintaining systems with internal feedback paths. Their essential essence is that they self-
organize.”
Chiva-Gómez develops key factors by the help of CAS and its similarities with social
approach of organizational learning. He proposes that when the characteristics presented in
the table below exist in an organization, then organizational learning will take place.

Figure 1 The facilitating factors for organizational learning according to CAS

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Four Contrasting Models of Organizational Learning

After analyzing the factors which help an organization through organizational learning
process, we will continue with models of organizational learning. Alice Lam in “Tacit
Knowledge, Organisational Learning and Innovation: A Societal Perspective” article
identifies four contrasting models of organizational learning based on knowledge types.
Before intensively exploring these four models of organizational learning, we would
like to inform you about the viewpoint of authors of this article on knowledge type-
organizational learning and innovation triangle:
“What organisations can do, in particular, their capacity for learning and innovation
are closely related to how their knowledge is constituted, utilised and generated. All
organisations will potentially have a mixture of different knowledge types. However, their
relative importance can differ. Organisations can be dominated by one knowledge type rather
than another. There is a close correspondence between the dominant knowledge type and the
structural configuration of the organisation, resulting in different dynamics of learning and
innovation.”
Article suggests 4 categories of knowledge, which are first suggested by Collins
(1993) and then are adapted by Blacker (1995). These four categories are a. „Embrained
Knowledge‟ (depends on conceptual skills and cognitive abilities of the individual); b.
„Embodied Knowledge‟(action-oriented tacit knowledge ); „Encoded Knowledge‟(based on
sign and signals) and „Embedded Knowledge‟ (based on organization routines, practices and
shared norms).
Given the information above, we will comprehend these four models precisely. The
article, based on Mintzberg‟s (1979) classic typology of organizational forms and the work of
Aoki (1988) and Nonaka and Takeuchi (1995) on the „Japanese model‟, identifies four ideal
typical organizational forms in terms of organizational learning and its effects on innovation.
According to the article, each organizational form is related with a dominant knowledge type.
These models can be analyzed in terms of “the mechanisms for the coordination of operating
tasks” and “the knowledge agents”.
a. ‘Professional Bureaucracy’ :

Definition: According to the article “an organisation which derives its capability from the
formal „embrained knowledge‟ of its highly trained individual experts can be defined as a
„professional bureaucracy‟”. In this type, coordination is achieved by the standardization of
knowledge and skills. The formal knowledge creates a significant base for internal work rules,
standards, job boundaries and job status, states Lam.
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Approach to problem solving: Logical and consistent application of existing knowledge
into problems. This approach results in deficiencies when dealing with uncertainties.
Key agents: The individual professionals.
Learning perspective: The learning focus is narrow and constrained within the boundary
of formal specialist knowledge.
Innovation Capacity: Model inhibits innovation.
Classic examples: Universities, hospitals and craft production firms are the classic
examples of professional bureaucracy according to article. Municipalities in Turkey can be
classified in this model.

b. ‘Machine Bureaucracy’ :

Definition: As stated in the article “an organisation which depends heavily on „encoded
knowledge‟ can be defined as a machine bureaucracy”. The most important factors of a
machine bureaucracy are “specialization, standardization and control”. Machine bureaucracy
is utilized to achieve efficiency and stability in the organizations. Work is divided to small
routine tasks which require the minimal formal knowledge of workers.
Key agents: Not the employees who directly engaged in operations, but the formal
managerial hierarchy whose responsibility is to formulate rules, procedures and performance
standards.
Learning perspective: According to Lam machine bureaucracy learns by „correction‟
through performance monitoring. Accumulation of new knowledge is very slow.
Innovation Capacity: Unable to deal with “novelty or change” due to the fact that the
model is designed to deal with routine problems. (Little capacity to innovate)
Classic examples: Lam states that mass production firms operating on the principles of
Scientific Management are classic examples. Production processes of automotive firms in
Turkey can be classified in this category.

c. ‘Operating Adhocracy’ :

Definition: “An organisation which relies not only on the formal knowledge of its
members, but draws its capability from the diverse know-how competencies and practical
problem solving skills embodied in the individual experts, can be described as an 'operating
adhocracy'” based on the definition of article. In this organic model, standardization of
knowledge and work are minimized.
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Approach to problem solving: Experience and capacity to adapt to new situations is vital
in this model according to author. Formal professional knowledge and standardized expertise
has little effect on problem solving. The knowledge structure is individualistic but
collaborative.
Learning perspective: Learning is broad and rooted in different experiences and know-
how of different experts (Not restricted with specialization). According the authors, learning
occurs on multiple levels and employees have a strong incentive to engage in 'extended
occupational learning',
Innovation Capacity: Model activates innovation. We would like cite an important point
from the article:
“…learning and innovative capabilities [of operating adhocracy ] stem from: 1)the way its
collaborative approach to problem-solving facilitates the distribution and dissemination of
knowledge; 2) the high degree of autonomy given to individuals and entrepreneurial project
teams leads to a diverse and varied knowledge base; and 3) its strong market-discipline exerts
pressures on individuals to accumulate their knowledge and expertise in line with shifting
market opportunities.”
“The operating adhocracy is the most innovative and yet least stable form of
organisation.”

Classic examples: Organizations providing non-standard, creative and problem-solving
services directly to the clients, such as professional partnerships, advertising agencies,
software engineering firms and management consultancies can be typical examples as stated
article. Mobilera, Alametifarika, Marka which are advertising companies founded in Turkey,
are perfect examples of this model.

d. ‘J-form’ Organization :

Definition: According to article in consideration “An organisation which derives its
capability from knowledge that is 'embedded' in its operating routines, team relationships and
shared culture can be described as a 'J-form' organisation.” This model is a combination of
bureaucracy model (stability and efficiency) and operating adhocracy model (flexibility and
importance of teams).
Key agents: Lam indicates that the semi-autonomous project team (members from
different functions) has the utmost importance in this model. Both the autonomous individual
expert and the controlling managerial hierarchy lose its vital role over the project team.

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Learning perspective: In J-form organizations learning generally takes place through
“shared work experiences and joint problem-solving in project teams” like in operating
adhocracy according to the article. The difference is that in J-form organization learning
perspective is broader due the cross-functional nature of teams. These cross-functional teams
create a culture which encompasses diversity of knowledge.
Innovation Capacity: Innovative and adaptive. Lam states:
“It is marked by a tremendous capacity to generate, diffuse and accumulate tacit
knowledge continuously through „learning-by-doing‟ and interaction. It has a unique
capability to generate innovation continuously and incrementally. However, learning in the J-
form organization is also potentially conservative. Its stable social structure and shared
knowledge base can reduce the capabilities of the organization to learn from individual
deviance and the discovery of contrary experience (Levinthal and March 1993: 108; Dodgson
1993: 383).”
However, these characteristics of J-form organization can make radical innovation
difficult.
Classic examples: Japanese type of organization, knowledge creating factories. Turkish
telecommunication companies eg. AVEA and Turkcell are the examples for this model.
To conclude the article argues that “there are dominant societal patterns of learning and
innovation. Two out of four models can be accepted as alternatives for innovational learning.
These are operating adhocracy and the J-form organization. These two have a great deal of
similarities: being organic, decentralized problem-solving, importance of cross functional
teams, non-hierarchical structure. They both argue that learning and innovation cannot be
thought apart social interaction and practical experience. The most important difference
between two is their approach to learning: the former utilizes an external approach but the
latter an internal and firm-centered one.

What is innovativeness in organizations?

If we take the narrower concept of innovation first, the main definitional issue which
has occupied academic writers is how to distinguish it from the organizational change.
Probably the most widely cited formulation of this distinction is developed by Michael West
and colleagues (West and Farr,1990;King and West,1987). They characterize organizational
innovation as follows:
-“An innovation is a tangible product, process or procedure within an organization. A new
idea may be the starting point for an innovation but cannot be called an innovation.
-An innovation must be new to the social setting within which it is introduced.
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-An innovation must be intentional rather than accidental.
-An innovation must not be a routine change. The creation of an entirely new post would.
-An innovation must be aimed to produce benefit to the organization. Intentionally destructive
actions such as sabotage or purely whimsical changes are excluded from the definition.
-An innovation must be public in its effects. If an individual introduces a change to his or her
work which has no effect on other people in the organization, it wouldn‟t be considered an
innovation.”
There are some criticisms about the definition of organizational innovation which is
done by Michael West and his colleagues. Nigel Nicholson(1990) has argued that they had the
difficulty of defining what is meant by terms such as intentional, accidental, new or
beneficial. Another criticism to West‟s definition is that it doesn‟t take into account the scale
or scope of the products, processes or procedures to which it is applied. Writers such as
Kimberly(1981)have argued that it only makes sense to define as innovations those changes
which has a substantial impact on the organization.
As a conceptual basis for theorizing innovation, definition of West has limitations but
as a pragmatic point of view his definition remains valuable.

Why some organizations are more innovative than others?

Researchers have identified some factors that help them in their attempts to describe
the characteristics of high or low innovative organizations. A vast number of different factors
have been examined as possible facilitators or inhibitors of innovation. The major ones are
listed below:

1) People
2) Structure
3) Climate and Culture
4) Environment

People:

When trying to explain why some organizations are more innovative than others, one
of the first factors at which researchers looked at were the characteristics of people in the
organization. Leaders and other top decision makers were the principal focus of early studies.
Recent research has broadened its scope to consider other influential individuals, such as
internal change agents and informal ideas champions.
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Early research into the influence of leaders on organizational innovation has been
based on individual characteristics: personality traits, values and beliefs, experience and
knowledge. There has been some research about these issues however the biggest problem is
that researchers have not been able to identify characteristics which predict innovation in all
types of leaders. In many studies, leader characteristics are found to be associated with
organizational innovation. Recent studies are based on the style required for innovative
leadership. Drawing heavily on the work of organizational gurus like Tom Peters and Robert
Waterman and Rosabeth Moss Kanter, writers in Europe and North America stressed the need
for a participative, democratic style of leadership which encourages subordinates to be
involved in innovation decisions and to feel able to suggest novel ideas without fear of
censure. According to these writers, the second aspect of innovative leadership is the ability
of the leader to provide a vision of where the organization is going to which organizational
members can commit themselves. More recently, academic and managerial authors have
argued that transformational leadership is facilitator of innovation. This concept was
developed by Bass to refer to leaders who inspire followers to act together towards shared
goals. It comprises components of charisma, inspiration, intellectual stimulation and
individual consideration. Many critics argue for a contingency approach, whereby the type of
the leadership depends on the nature of external demands on the organization and the attitudes
of organizational members towards change (Dunny and Stace,1988). Where an organization
faces a threatening, turbulent environment, leaders may need to be directive rather than
participative in order to implement innovations.
Research on the influence of individuals other than leaders on organizational
innovativeness has concentrated on formal change agents and informal idea champions. A
change agent may be defined as a person who has been given explicit responsibility for
overseeing the introduction of a specific change within an organization. He or she may be a
member of the organization or an outside consultant. However, the individuals responsible for
the introduction of an innovation often are not appointed as change agents but idea
champions. Idea champions feel a strong commitment to the idea and are able to transform it
to others in the organization. According to a research done by Frost and Egri (1990a,1990b),
two critical factors determine whether idea champions are successful or not. These are
personal power in the organization and ability to access and utilize wide communication
networks. According to Dougherty and Hardy; senior, long serving members of staff were
often able to succeed in championing through their credibility and extensive personal
networks where less experienced staff found their efforts frustrated.

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Organizational Structure:

John Child defines the organizational structure as follows: “The formal allocation of
work roles and the administrative mechanisms to control and integrate work activities
including those which cross organizational boundaries.”
Burns and Stalker state that organizational structure should be related to the
environment in which the organization operates. Where the organization is very stable and
predictable, a mechanistic structure is suitable. People know what is expected of them and can
concentrate on performing their tasks efficiently. Where the organizational environment is
unpredictable and subject to change, mechanistic organizations lack the flexibility to cope
with changes and an organic structure is required. This enables the organization to change
direction rapidly in response to market demand and to take advantage of new technologies.
The American researchers Lawrence and Lorsch took Burns and Stalker‟s approach a stage
further. As well as saying that different types of overall structure were required according to
environmental conditions, they claimed that in turbulent environments a greater degree of
structural differentiation between departments is required than in predictable environments.
Thus in a firm facing an unstable market, the production department would have a more
mechanistic structure than the sales department, which needs to respond quickly to changing
demand.
According to Hill and Amabile, the psychological rationale for the effectiveness of
such structures is in terms of job discretion and idea ownership through participation. High
discretion is consistently found to predict innovation and creativity at work through the
motivating effects of a sense of control over one‟s work and by removing hierarchical barriers
to try new ideas. Idea ownership stems from the participation in idea generation and decision
making in the context of team working, ownership associated with autonomy and participative
leadership may encourage the development of an innovative group identity.

Organizational Climate and Culture:

The 1980s and 1990s saw a shift in emphasis in the search for antecedents of
successful innovation away from characteristics of people and structures toward less tangible
features of organizations in particular their climate and cultures. According to Nystorm,
organizational culture is the values, norms, beliefs and assumptions embraced by participants
and climate is the feelings, attitudes and behavioral tendencies, which characterize
organizational life. According to a study done by Nystrom, Ekvall and West common

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recommendations for climates supporting innovation emerging from such work include
openness to change, risk taking, tolerance of debate and disagreement and playfulness.
Approaches to culture may be categorized as either structural or interpretative. The
structural focus is on the link between culture and organizational structure. One well known
structural typology is proposed by Charles Handy, who identifies 4 types of culture. Role
cultures are typical of the classic bureaucratic model of organization, where the structure is
one of multiple layers of hierarchy, each reporting to the one above. Key values are
adherence to and expertise within clearly defined roles. Ambiguity of any kind is highly
threatening and as a result formal rules, regulations and procedures around. Role cultures are
not effective innovators. They generally work in stable, predictable environments. Power
cultures are often found in organizations which have grown up around one strong,
authoritative individual. Status, obedience and control are highly valued but in contrast to role
cultures the central authority functions through ad hoc decisions. This enables such cultures to
respond and initiate change rapidly. If the organization is small and staff members largely
share their vision, power cultures can be effective. Task cultures are associated with matrix
structures. They stress flexibility, adaptability and egalitarianism within project teams, lateral
rather than vertical communications. Person cultures emphasize individual autonomy and
interpersonal relationships. They are associated with highly decentralized and informal
structures, where control is exercised through mutual accountability.

Environment:

In seeking to identify factors which help or hinder innovation, it is not enough to look
at features of the organization itself; its people, structure, climate and culture. It is also
necessary to look at the environment within which the organization exists, and the way it
interacts with that environment. In an economic analysis of organizational innovation, a wide
range of factors in both the physical and commercial environment would need to be
considered. Studies have shown innovativeness to be associated with the existence of
boundary spanning roles within the organization and with the professionalization of
organization members.
According to Miles and Snow, the extent to which an organization engages in an
active search of the environment for new ideas to adopt (environmental scanning) depends on
its perceptions of its own relationship with its environment. Such perceptions have been used
as the basis for classifying organizations into strategic types. There are four types: defenders,
prospectors, analyzers and reactors. Defenders are the organizations which see their
environment as essentially stable and concerned with the efficiency of existing operations in
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order to dominate their market niche. Prospectors see their environment as uncertain and
turbulent, therefore place high value on innovation.

Types of Innovation

Fariborz Damanpour and William Evan distinguished between technical innovation,
which occurs within the primary work activity of the organization and administrative
innovation, which occurs within the social system and is concerned with the organization of
work and the relationships between organizational members. In a study of American public
libraries, it is found that the adaption of administrative innovation triggered technical
innovation. Damanpour has since added a third category, ancillary innovations. These are the
innovations which span organizational-environmental boundaries and go beyond the primary
work functions of the organization.
In 2001, Damanpour and Gopalakrishnan distinguished the innovation into two
groups; product and process innovation. They define the product innovation as new products
or services introduced to meet an external user or market need and process innovation as new
elements introduced into an organization‟s production or service operations.

The characteristics of an innovation are classified under 3 terms according to Zaltman,
Duncan and Holbek. These are programmed-non programmed, instrumental-ultimate and
radicalness. Whether an innovation is scheduled in advance is related to programmed-non
programmed. Non-programmed can also be divided into two as distress or slack. Whether an
innovation is introduced to facilitate a further innovation or as an end in itself is related to
instrumental and ultimate side. The extent to which the change is both novel and risky is
related to radicalness.

Innovation Process in Organizations

Managing the introduction of innovations in an organization does not only consist of
implementing the change and taking a single decision to adopt. It involves a range of
activities prior to and following the adoption such as fact finding, political maneuvering,
formal and informal discussion and so on.
Writers have been proposing models describing the sequence of events in the
innovation process since the field first emerged in the 1960s. All of these models have three
common features. First, they are based largely and solely on theoretical speculation rather
than observation. Secondly, they are normative; they seek to describe how innovation
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“normally” occurs. Thirdly, they describe a process as a sequence of developmental stages,
each of which must be passed through in turn.
A model to study innovation processes is to approach retrospectively; in other words
by constructing innovation histories. In this case, past events will be taken into account.
However, there is a problematic side of this model. People usually tend to reconstruct events
in their memories in a way which appears them more logical and orderly than it usually was.
In order to prevent this and increase the reliability and validity, innovation histories can be
enhanced by triangulation of methods – that is by using a combination of interviews,
questionnaires and analysis of documents. The information should be collected from as many
groups as possible. The concern in these circumstances is to have a sufficiently deep
understanding of the case and its context to enable a credible interpretation to be produce

Stage based Models:

In this part a typical stage based model which has been developed by Zaltman et
al.(1973) will be introduced. This model describes the process in two main stages. First one is
initiation and second one is implementation.
In this model (Zaltman et al.‟s) the division between two main stages is at the point of
adoption of the innovation; that is, the point at which the organization makes a firm decision
to implement the innovation.
Initiation process consists of three sub-stages. First one is knowledge awareness which
implies that the organization becomes aware of the existence of an innovation which it has the
opportunity to utilize. Second sub-stage is formation of attitudes which means that the
members of the organization form and exhibit their attitudes to the proposed innovation. Last
sub-stage is called decision where the potential innovation is evaluated and the decision to
proceed with it or abandon the idea is made.
The following implementation process has two sub-stages. Firstly, initial
implementation occurs in which first attempts to utilize the innovation are made, often on
some sort of trial basis. Continued-sustained implementation is the second sub-stage where
the innovation becomes routinized as part of organizational life.
The start of the innovation process is ascribed conventionally to the detection of a
“performance gap” which is defined as a mismatch between actual and potential performance.
According to Zaltman, this may occur in two ways: either the organization realized that the
performance is unsatisfactory and looks for new innovative solutions or it becomes aware of
the potential innovation in its environment. It would be incorrect to state that all the

18

innovation process stems from “performance gap”. Some innovations are to be forced by law
to the organizations. For example, the parental leave for 6 months is such an innovation.
After the implementation process of innovation it becomes routinized. At the end,
innovation becomes absorbed into the daily life of the organization. So, it will be accepted as
a part of status quo. For the organization to accept the innovation successfully, any initial
problem has to be clarified. Then, routinization occurs without any problem.
The last process is called “exnovation” where the organization decides to get rid of the
fully realized innovation when it becomes obsolete, allowing the life cycle to start again and
continue this way. This process is also essential for organizations to keep up with the
changing world.

Criticisms of stage-based models:

In the literature, conventional innovation models have been criticized a lot. Schroeder
et al. put forward an alternative model based on longitudinal data from Minnesota Innovation
Research Program which describes a series of innovations but does not place them into stages.
The applicability of this model as a general approach was tested. However, some of the
observations showed that the model could not be completely applicable. Schroeder et al.‟s
model was compared with a conventional stage-based model and found out that the broadly
defined model could not be applied by the raters independently and it was also shown that the
stages did not progress in the order Zaltman et al. suggested. Other studies have also found
limited support for developmental stages in innovation processes. Pelz (1983), found in a
study of urban innovations in United States that there were some signs of progressing through
stages but in a relatively simple, non-radical innovations but no evidence in more complex
innovations.
Another observed weakness was that people neglect the different perspectives and
approaches within the organization towards an innovation. Top management could think that
the innovation was implemented and routinized successfully whereas people on the ground
are more likely to avoid implementing the innovation. Another possibility is that the
innovation develops differently in different parts of the organization. It is the patterns of
interaction between individuals and groups within the organization which determine how
innovation progresses.

19

How manageable is the innovation process?

We saw that we may distinguish broad phases in innovation development, however at
a more detailed level of innovation, the progress is rarely in a clear and predictable sequence.
It is found that innovations frequently show a lack of “fidelity”. In other words, a mismatch
occurs between the outcome intended by those who initiated and the actual consequences
once implemented. Nevertheless, in the literature innovation is presented as a controllable
phase. Popular texts try to encourage managers about the positive outcomes of the innovation.
When managers follow the given advice, they will reach the desired successful outcomes.
More precisely, it is assumed that change can be directed from above and that, as its outcomes
are more or less predictable, the final outcome of the process is largely due to the competence
and skill of those directing the change.
It is found that this general illusion of manageability is composed of three sets of
second-order illusory beliefs. First one is the illusion of linearity. It implies that organization
change proceeds through a neat set of stages and that change always proceeds through this
order of stages. Second one is the illusion of predictability due to which change processes are
predictable. This predictability provides an unerring template for action. It also underscores
and therefore facilitates management of change. Third component is illusion of control. First
and second believes lead managers to exert extensive control over change. There are some
exceptional uncontrollable events in the change process. “Failed” change processes must be
due to something beyond managerial control.
To summarize, the illusion of manageability has remained unchallenged in the
literature for too long. It is important for managers to recognize their own limits in change
management. Realizing these restrictions early on during a major change will facilitate
appropriate and balanced action later in the change process. In managing the innovation and
change processes two characteristics have significant importance. First one is vigilance in
detecting the unforeseen as early as possible, second one is flexibility in reacting to it.

Comparison of Organizational Learning & Organizational Innovativeness

After organizational learning and innovation are explained separately, it is required to
compare them in order to make their difference clear and to determine their effects on each
other. Their difference can begin with their definition. Although a review of the literature
gives us diverse definitions of organizational learning, from each definition of them we can
understand the difference of these concepts. By definition, organizational learning has a

20

cognitively driven orientation while organizational innovation has a practically driven
orientation.
According to Nitza Schwabsky‟s paper, a review of the literature on organizational
learning emphasizes that its core concept is the collective access, acquisition, transfer,
development and the memory collection of knowledge and insight that effect organizational
behavior. Learning, by means of accumulating and storing collective knowledge and insight
can be theoretical or experiential. While learning improves organizational capacity to
transform its future in cognitive and theoretical means, the practical implementation of the
idea or the new knowledge is not central to learning. Based on the explanation above, it is
right to say that organizational learning has a cognitively-driven organizational orientation.
Also, according to Nitza Schwabsky‟s paper, “innovativeness refers to the
organization's openness to new ideas, as well as to its capacity to innovate, to implement and
to adopt the new idea, process or product successfully. Innovativeness encompasses both the
tendency to change as well as the practical capacity to innovate. While openness to new ideas
and learning is part of innovativeness, the practical aspect of the organizational capacity to
innovate is central. An organization that does not implement innovations cannot be perceived
as innovative.‟‟ At that point from the preceding explanation, the definition of innovativeness
can be drawn as an organizational tendency to support new and creative ideas towards their
implementation, as a result innovativeness is perceived as a practically-driven organizational
orientation.
Although organizational learning and innovativeness are different terms, their effect
on an organization should not be evaluated independently from each other. However it is also
important to say that learning and innovativeness are not perceived as overlapping terms
(Hurley and Hult, 1998). They are perceived as overlapping because their relationship with
each other is very strong. Organizational innovation can take place while learning and
learning can take place while innovating. If it is required to speak theoretically, there have
been many studies and theories suggesting that learning is an antecedent of innovativeness
(e.g. Cohen and Levinthal 1990, Hurley and Hult 1998), and of internal efficiency and
organizational competitiveness. According to that view , innovativeness requires a firm to be
able to turn their knowledge to their different kinds of development processes. The point is
that innovations need knowledge and knowledge can be gained by organizational learning,
however while translating knowledge into developments via innovations, these organizational
innovations feed back organization with new learning processes. In short, although
organizational innovativeness and learning are not same concepts, they are not evaluated
seperately because their sustained effect on each other and organizations increase the
efficiency of organization‟s value added processes.
21

Resource based view (RBV) of the firm can help us to explain the relationship of
learning and innovativeness by providing some examples. The RBV defines strategic assets as
rare, valuable, inimitable, and non-substitutable resources. Trafalgar War which contains
lessons from resource based view is one of the most suitable example to clear the
organizational learning and innovativeness.
According to the article of Andy C. L. Yeung*, Kee-Hung Lai and Rachel W. Y. Yee ,
learning-oriented organizations consistently improve their existing abilities through
experience. An RBV of strategic management involves examining the resources and
capabilities of firms, as a result they gain above-normal rates of return and a sustainable
competitive advantage. Learning-oriented organizations generate collective tacit knowledge
that is difficult for competitors to imitate (Osterloh and Frey 2000). This knowledge thus
becomes a strategic asset that is the source for creating sustainable competitive advantages. In
Trafalgar also we can see that organizational learning as a navy is created a great knowledge
which becomes a competitive advantage later. At the heart of the Royal Navy‟s competitive
advantage lay the inescapable fact that Great Britain was an island. This natural setting,
unique among European states, gave rise to a nation of seafarers through experience which
resulted from organizational learning.
As we have already explained that organizational learning results in experience and
tacit knowledge which give the power of translating knowledge and experience into the
innovativeness. Trafalgar is also one of the examples which shows the relationship how an
organization that has a great learning capacity turns its knowledge into innovation. The Royal
Navy implemented an innovative strategy that resulted from high experience provided by high
organizational learning. Lord Nelson was effective because he was willing to depart from
convention and employ innovative strategies to catch his opponents off guard.
To sum up, we can compare organization learning and innovation with each other,
innovativeness is perceived as a practically-driven organizational orientation, while
organizational learning has a cognitively-driven organizational orientation. But also we
should not forget that these two processes result in and affect each other very deeply. RBV
can give us very suitable examples which show the difference of them and their strong
relationship.

22

II. STATISTICAL ANALYSIS OF GROUP DATA AND INTERPRETATIONS

1. Analysis of general characteristics of our companies:

1. Our companies are service companies and they have exteremly internal financing in
order to make new investment. Because the average of the their B4 variables are 98%.

Mean 0,98
Standard Error 0,02
Standard Deviation 0,044721
Sample Variance 0,002
Confidence
Level(95,0%) 0,055529
From the data above, it is obivious that the confidence level is very high. As a result, we can
conclude that external financing is not preferred by our companies.
2. Our companies don‟t have much R&D investment. Their average R&D investment is
15,8% of their total sales but you can see that standartd deviation is very high because
only two of our companies have a good R&D expenditure compare to others.

Mean 0,158
Standard Error 0,097283
Standard Deviation 0,217532
Sample Variance 0,04732
Confidence
Level(95,0%) 0,270101

3.
A. In comparison with our competitors, our company has introduced more innovative
products and services in during the past five years.
B. The technology of our main machinery in use is very up-to-date.
C. Our company changes production methods at a great speed in comparison with our
competitors.
D. We encourage people to think and behave in original and novel ways.
E. When we cannot solve a problem using conventional methods, we improvise on
new methods.
F. New product development

23

SUMMARY TABLE
frequency as percentage A B C D E F
str.disagree 1 0 0 0 0 0 0
disagree 2 20% 0 0 0 0 20%
indifferent 3 20% 40% 0 0 20% 20%
agree 4 0 40% 80% 60% 40% 20%
str. Agree 5 60% 20% 20% 40% 40% 40%

The above listed factors as A,B,C,D,E,F are the indicators of the organizational
innovativeness other than the R&D expenditures. Moreover the summary table shows
that the frequencies are very high at above average rates of 4 and 5. Our companies
deal with organizational innovativeness at the product development level especially
because our indicators are selected to analyse the product development process. They
agree or highly agree with the indicators.

4.
A. We use networks and links to acquire knowledge.
B. We jointly work with other organizations to acquire knowledge.
C. We share information with employees.
D. We continuously improve our personnel.
E. We learn from market changes that enable us to successfully compete.
F. We evaluate the cost of failures not as a loss but as an opportunity to learn.

SUMMARY TABLE
frequency as percentage A B C D E F
str.disagree 1 0% 0% 0% 0% 0% 0%
disagree 2 0% 0% 0% 0% 0% 0%
indifferent 3 0% 0% 0% 20% 0% 20%
agree 4 60% 60% 80% 40% 20% 60%
str. Agree 5 40% 40% 20% 40% 80% 20%

The above listed factors as A,B,C,D,E,F are the indicators of the organizational
learning selected from the questionnaire. In the summary table, you see that about all
of the companies agree or strangly agree with organizational learning indicators.
Based on that summary table and accepting that these indicators are the most suitable
for organizational learning, our companies have high degree organizational learning.
As a conclusion, because there is a strong relationship between organizational
learning and innovativeness, it is possible to say also our companies prove that strong
relationship. According to our above short analysis, our companies have
organizational learning and innovativeness .
24

HYPOTHESIS ABOUT SECTOR’S DIFFERENCES AND
ORGANIZATIONAL LEARNING& INNOVATION:

After we try to find general characteristics of our companies related to the
literature review and our topic, now we want to continue our statictical analysis with
finding some relationships between variables and organizational learning and
innovation and making some differences deal with our reserch clearer between service
and manufacturing companies. Below , we generate some hypothesis, now we try to
evaluate these hypothesis statistically on our questionnaire.
The processed data set is used to analyze hypotheses which have been either
derived from the relevant literature review or been developed according to our
considerations. In addition to that, some hypothesis will be established with aim of
data mining in order to find a unknown pattern between variables. Four topics we
developed are given as follows:

1. The higher organizational innovativeness applied or organizational learning
generalized by the company, the greater total sales growth achieved in the
company (positive correlation is expected).
generalized by the company, the more market share obtained by the company
(positive correlation is expected).
3. If a company has a target to decrease cost as much as possible or if a company
engages in cost leadership strategy, that company provides it organizational
learning or innovativeness.
4. If a company engages in differentiation strategy, that company take care of
organizational learning or organizational innovativeness.

Because there is no single indicator which asks respondents directly about
organizational learning , organizational innovation and cost leadership strategy, we
wanted some other subindicators listed below which represent highly the
organizational learning , innovation and cost leadership and the points given by
respondents to these subindicators are averaged and round the nearest intiger
because Likert scale used in the questionnaire contains only integers as values.

25

For Organizational Learning: C30, C37, C44, C46, C50, D68 are the
main subindicators of organizational learning in the questionnaire
according to the literature review and we take average of the scores of these
subindicators then round the mean to the nearest integer and then we get a
score for the organizational learning for each company.

For Organizational Innovation: A5, A11, A17, A27, A29, E12 are the
main subindicators of organizational innovation in the questionnaire
according to the literature review and we take average of the scores of these
subindicators then round the mean of scores to the nearest integer and then
we get a score for the organizational innovation for each company.

For Cost Leadership Strategy: D53, D54, D59, D60, D61, D69 are the
main subindicators of cost leadership strategy in the questionnaire
according to the course AD320 that we take from Prof. Dr. Güven Alpay
and we take average of the scores of these subindicators then round the
mean of scores to the nearest integer and then we get a score for the cost
leadership strategy for each company.

For Differentiation Strategy: A6, A9, A18, D56, D57, D63, D74, are the
main subindicators of differentiation strategy in the questionnaire
according to the course AD320 that we take from Prof. Dr. Güven Alpay
and we take average of the scores of these subindicators then round the
mean of scores to the nearest integer and then we get a score for the
differentiation strategy for each company.

There are variables directly for market share (E2) , total sales growth
(E1) in the questionnaire, that‟s why we use the scores of these variables
directly as an indicator for market share and total sales growth.
The chi-square test is used to determine whether there is a
significant difference between the expected frequencies and the observed
frequencies in one or more categories.
Chi-Square Test Requirements
1. Quantitative data.
2. One or more categories.
3. Independent observations.

26

4. Adequate sample size (at least 10).
5. Simple random sample.
6. Data in frequency form.
7. All observations must be used.
If your chi-square value is equal to or greater than the table value,
reject the nullhypothesis, it means that differences in your data are not due
to chance or the Chi-square tests table will show the value of Pearson Chi-
Square value, associated with the significance value. From the two-tailed
significance value, we can make a statistical decision and accept or reject the
null hypothesis. If the value of significance is less than the predetermined
level of significance, we will reject the null hypothesis and conclude that
relationship is significant.

generalized by the company, the greater total sales growth achieved in the
company.
HYPOTHESIS 1A:
Ho: Organizational learning is independent of total sales growth.
Ha: Organizational learning is associated with total sales growth.
ORGANIZATIONAL LEARNING* TOTAL SALES GROWTH
CROSSTABULATION

Q3

1 2 3 4 5 Total

Q1 1 Count 1 0 0 0 0 1

% of Total ,8% ,0% ,0% ,0% ,0% ,8%

3 Count 0 1 2 5 1 9

% of Total ,0% ,8% 1,6% 4,1% ,8% 7,3%

4 Count 1 3 18 47 13 82

% of Total ,8% 2,4% 14,6% 38,2% 10,6% 66,7%

5 Count 0 0 9 11 11 31

% of Total ,0% ,0% 7,3% 8,9% 8,9% 25,2%

Total Count 2 4 29 63 25 123

27

ORGANIZATIONAL LEARNING* TOTAL SALES GROWTH
CROSSTABULATION

Q3

1 2 3 4 5 Total

Q1 1 Count 1 0 0 0 0 1

% of Total ,8% ,0% ,0% ,0% ,0% ,8%

3 Count 0 1 2 5 1 9

% of Total ,0% ,8% 1,6% 4,1% ,8% 7,3%

4 Count 1 3 18 47 13 82

% of Total ,8% 2,4% 14,6% 38,2% 10,6% 66,7%

5 Count 0 0 9 11 11 31

% of Total ,0% ,0% 7,3% 8,9% 8,9% 25,2%

Total Count 2 4 29 63 25 123

% of Total 1,6% 3,3% 23,6% 51,2% 20,3% 100,0%

About all the firms, you will see exact percentage as bold in the table, have a high total
sales while their organizational learning scores are also high, in other words there is no firm
which has a high total sales while their organizational learning score is very low. According
to cross tabulation table, we can draw the conclusion that there is a positive relationship
between organizational learning and total sales. But, it is also important to see a statistically
significant result in the chi square table. From the chi square table below, we can reach a
statistically significant result. As a result, we reject the null hypothesis in chi square test and
we prove that organizational learning is associated with total sales growth, and cross
tabulation also supports that relationship between variables.

28

Chi-Square Tests

Asymp. Sig.
Value df (2-sided)

Pearson Chi-Square 71,297a 12 ,000
Likelihood Ratio 19,665 12 ,074
Linear-by-Linear
13,254 1 ,000
Association
N of Valid Cases 123

a. 14 cells (70,0%) have expected count less than 5. The
minimum expected count is ,02.

HYPOTHESIS 1B:
Ho: Organizational innovation is independent of total sales growth.
Ha: Organizational innovation of is associated with total sales growth.

ORGANIZATIONAL INNOVATION* TOTAL SALES GROWTH
CROSSTABULATION

Q3

1 2 3 4 5 Total

Q2 2 Count 1 0 0 0 1 2

% of Total ,8% ,0% ,0% ,0% ,8% 1,6%

3 Count 0 2 7 17 2 28

% of Total ,0% 1,6% 5,7% 13,8% 1,6% 22,8%

4 Count 1 2 16 39 13 71

% of Total ,8% 1,6% 13,0% 31,7% 10,6% 57,7%

5 Count 0 0 6 7 9 22

% of Total ,0% ,0% 4,9% 5,7% 7,3% 17,9%

Total Count 2 4 29 63 25 123

29

ORGANIZATIONAL INNOVATION* TOTAL SALES GROWTH
CROSSTABULATION

Q3

1 2 3 4 5 Total

Q2 2 Count 1 0 0 0 1 2

% of Total ,8% ,0% ,0% ,0% ,8% 1,6%

3 Count 0 2 7 17 2 28

% of Total ,0% 1,6% 5,7% 13,8% 1,6% 22,8%

4 Count 1 2 16 39 13 71

% of Total ,8% 1,6% 13,0% 31,7% 10,6% 57,7%

5 Count 0 0 6 7 9 22

% of Total ,0% ,0% 4,9% 5,7% 7,3% 17,9%

Total Count 2 4 29 63 25 123

% of Total 1,6% 3,3% 23,6% 51,2% 20,3% 100,0%

About all the firms, you will see exact percentage as bold in the table, have a total
sales growth, while their organizational innovation scores are also high, but for the
organizational innovation, it is very easy to say that there are some firms which have lower
total sales growth while their organizational learning score is very high, moreover also there
are some firms which have very low innovation scores although their total sales growth scores
are very high. According to cross tabulation table, we can draw the conclusion that there is no
strong relationship between organizational innovation and total sales compared to
organizational learning, although it is important to see a statistical result in the chi square
table. In the chi square table below, we see that there is statistically important relationship
between variables. We can conclude that organizational learning is much more related with
the total sales growth than the organizational innovation but it can not be concluded that
organizational innovation is not associated with the total sales growth.

30

Chi-Square Tests

Asymp. Sig.
Value df (2-sided)

Linear-by-Linear
5,792 1 ,016
Association


generalized by the company, the more market share obtained by the company.

HYPOTHESIS 2A:
Ho: Organizational learning is independent of market share.
Ha: Organizational learning of is associated with market share.

ORGANIZATIONAL LEARNING*MARKET SHARE CROSSTABULATION

Q4

1 2 3 4 5 Total

Q1 1 Count 1 0 0 0 0 1

% of Total ,8% ,0% ,0% ,0% ,0% ,8%

3 Count 0 0 7 2 0 9

% of Total ,0% ,0% 5,7% 1,6% ,0% 7,3%

4 Count 2 7 17 38 18 82

% of Total 1,6% 5,7% 13,8% 30,9% 14,6% 66,7%

5 Count 0 3 4 11 13 31

% of Total ,0% 2,4% 3,3% 8,9% 10,6% 25,2%

Total Count 3 10 28 51 31 123

31

ORGANIZATIONAL LEARNING*MARKET SHARE CROSSTABULATION

Q4

1 2 3 4 5 Total

Q1 1 Count 1 0 0 0 0 1

% of Total ,8% ,0% ,0% ,0% ,0% ,8%

3 Count 0 0 7 2 0 9

% of Total ,0% ,0% 5,7% 1,6% ,0% 7,3%

4 Count 2 7 17 38 18 82

% of Total 1,6% 5,7% 13,8% 30,9% 14,6% 66,7%

5 Count 0 3 4 11 13 31

% of Total ,0% 2,4% 3,3% 8,9% 10,6% 25,2%

Total Count 3 10 28 51 31 123

% of Total
2,4% 8,1% 22,8% 41,5% 25,2% 100,0%

About all the firms, you can see exact percentage as bold in the table, have a high
market share while their organizational learning scores are also high, in other words there is
nearly no firm which has a high market share while their organizational learning score is very
low, it is also required that there is one exception. According to cross tabulation table, we can
draw the conclusion that there is a positive relationship between organizational learning and
market share. But also it is important to see a statistically significant result in the chi square
table. In the chi square table below we can reach a statistically significant result. Because if
the value of significance is less than the predetermined level of significance, we will reject the
null hypothesis and conclude that relationship is significant. As a result, we reject the null
hypothesis in chi square test and we prove that organizational learning of is associated with
market share, and cross tabulation also supports that relationship between variables.

32

Chi-Square Tests

Asymp. Sig.
Value df (2-sided)

Linear-by-Linear
15,498 1 ,000
Association


HYPOTHESIS 2B:
Ho: Organizational innovation is independent of market share.
Ha: Organizational innovation of is associated with market share.

ORGANIZATIONAL INNOVATION*MARKET SHARE Crosstab

Q4

1 2 3 4 5 Total

Q2 2 Count 1 0 1 0 0 2

% of Total ,8% ,0% ,8% ,0% ,0% 1,6%

3 Count 1 4 9 9 5 28

% of Total ,8% 3,3% 7,3% 7,3% 4,1% 22,8%

4 Count 1 4 14 34 18 71

% of Total ,8% 3,3% 11,4% 27,6% 14,6% 57,7%

5 Count 0 2 4 8 8 22

% of Total ,0% 1,6% 3,3% 6,5% 6,5% 17,9%

Total Count 3 10 28 51 31 123

% of Total 2,4% 8,1% 22,8% 41,5% 25,2% 100,0%

33

About all the firms, we may see exact percentage as bold in the table, they have a high
market share, while their organizational innovation scores are also high, but for the
organizational innovation, it is very easy to say that there are some firms which have a low
market share score while their organizational innovation score is very high, moreover also
there are some firms which have very low innovation scores although their total market share
scores are very high. According to cross tabulation table, we can draw the conclusion that
there is no strong relationship between organizational and total sales compared to the
relationship between organizational learning and total market share, although it is important to
see a statistical result in the chi square table. In the chi square table below, we see that there is
statistically important relationship between variables because we reject the null hypothesis.
We can conclude that organizational learning is much more related with market share than the
organizational innovation but it can not be concluded that organizational innovation is not
associated with the market share.

Chi-Square Tests

Asymp. Sig.
Value df (2-sided)

Linear-by-Linear
8,244 1 ,004
Association


3. If a company has a target to decrease cost as much as possible or if a company
engages in cost leadership strategy, that company provides it with organizational
learning or innovativeness.

HYPOTHESIS 3A:
Ho: Organizational learning is independent of cost leadership strategy.
Ha: Organizational learning of is associated with cost leadership strategy..

34

ORGANIZATIONAL LEARNING*COST LEADERSHIP
CROSSTABULATION

Q5

1 2 3 4 5 Total

Q1 1 Count 1 0 0 0 0 1

% of Total ,8% ,0% ,0% ,0% ,0% ,8%

3 Count 0 0 5 4 0 9

% of Total ,0% ,0% 4,1% 3,3% ,0% 7,3%

4 Count 0 1 26 48 7 82

% of Total ,0% ,8% 21,1% 39,0% 5,7% 66,7%

5 Count 0 1 8 16 6 31

% of Total ,0% ,8% 6,5% 13,0% 4,9% 25,2%

Total Count 1 2 39 68 13 123

% of Total ,8% 1,6% 31,7% 55,3% 10,6% 100,0%

Taking all the companies into the account, the chi square test draws a conclusion that
there is an association between organizational learning and cost leadership because we reject
the null hypothesis. In addition to that, it is more important to emphasize that according to
cross tabulation there is a positive relationship between organizational learning and cost
leadership because companies have high organizational learning scores while paying attention
on the cost leadership strategy. That conclusion is significant because cutting costs does not
mean cutting learning, in literature review we have already reached that organizational
learning has a great support to that strategy.

35

Chi-Square Tests:

Asymp. Sig.
Value Df (2-sided)

Pearson Chi-Square 1,296E2a 12 ,000
Linear-by-Linear
16,577 1 ,000
Association


HYPOTHESIS 3B:
Ho: Organizational innovation is independent of cost leadership strategy.
Ha: Organizational innovation of is associated with cost leadership strategy.

ORGANIZATIONAL INNOVATION*COST LEADERSHIP CROSS
TABULATION

Q5

1 2 3 4 5 Total

Q2 2 Count 1 0 0 1 0 2

% of Total ,8% ,0% ,0% ,8% ,0% 1,6%

3 Count 0 0 13 14 1 28

% of Total ,0% ,0% 10,6% 11,4% ,8% 22,8%

4 Count 0 2 22 40 7 71

% of Total ,0% 1,6% 17,9% 32,5% 5,7% 57,7%

5 Count 0 0 4 13 5 22

% of Total ,0% ,0% 3,3% 10,6% 4,1% 17,9%

Total Count 1 2 39 68 13 123

% of Total ,8% 1,6% 31,7% 55,3% 10,6% 100,0%

36

Taking all the companies into the account, the chi square test draws a conclusion that
there is an association between organizational innovation and cost leadership because we
reject the null hypothesis in which the value of significance is less than the predetermined
level of significance that is equal to 0,005. In addition to that, it is more important to
emphasize at that point, that according to cross tabulation there is a positive relationship
between organizational innovation and cost leadership because companies have high
organizational innovation scores at the same time they pay attention on the cost leadership
strategy. That conclusion is very important because cutting cost does not mean decreasing
innovations because in literature review we see that organizational innovation has a great
support to that strategy by process innovation. Organizational innovation is as important as
organizational learning for cost leadership strategy. It is a different conclusion compared to
first two assumptions because the importance degree of organizational innovation increases
and becomes equal to organizational learning when we begin to talk about strategies unlike in
first two cases in which the main issues were total sales and market shares respectively.

Chi-Square Tests

Asymp. Sig.
Value Df (2-sided)

Linear-by-Linear
10,652 1 ,001
Association


4. If a company engages in differentiation strategy, that company takes care of
organizational learning or innovativeness.
HYPOTHESIS 4A:
Ho: Organizational innovation is independent of differentiation strategy.
Ha: Organizational innovation is associated with differentiation strategy.

37

ORGANIZATIONAL INNOVATION* DIFFERENTIATION Crosstab

V7

2 3 4 5 Total

Q2 2 Count 2 0 0 0 2

% of Total 1,6% ,0% ,0% ,0% 1,6%

3 Count 2 20 6 0 28

% of Total 1,6% 16,3% 4,9% ,0% 22,8%

4 Count 0 15 53 3 71

% of Total ,0% 12,2% 43,1% 2,4% 57,7%

5 Count 0 0 12 10 22

% of Total ,0% ,0% 9,8% 8,1% 17,9%

Total Count 4 35 71 13 123

% of Total 3,3% 28,5% 57,7% 10,6% 100,0%

Taking all the companies into the account, the chi square test draw a conclusion again
that there is an association between organizational innovation and differentiation strategy
because we reject the null hypothesis. In addition to that, it is more important to attract your
attention to the point that cross tabulation says that a positive relationship between
organizational innovation and differentiation strategy, has a high diversity mainly at the
center of the table because it reflects that companies don‟t pay attention on the
organizational innovation and differentiation strategy together at a high degree. Maybe it is a
major characteristic of our samples because they are operated mostly in domestic market, in
Turkey the differentiation strategy is not as significant as cost leadership because Turkey is a
developing country. That conclusion is very important because our data has a power to reflect
some differences and to give some indicators about domestic characteristic.

38

Chi-Square Tests

Asymp. Sig.
Value df (2-sided)

Pearson Chi-Square 1,305E2a 9 ,000
Linear-by-Linear
58,904 1 ,000
Association


HYPOTHESIS 4B:
Ho: Organizational learning is independent of differentiation strategy.
Ha: Organizational learning of is associated with differentiation strategy.

ORGANIZATIONAL LEARNING * DIFFERENTIATION
CROSSTABULATION

V7

2 3 4 5 Total

Q1 1 Count 1 0 0 0 1

% of Total ,8% ,0% ,0% ,0% ,8%

3 Count 1 6 2 0 9

% of Total ,8% 4,9% 1,6% ,0% 7,3%

4 Count 2 26 51 3 82

% of Total 1,6% 21,1% 41,5% 2,4% 66,7%

5 Count 0 3 18 10 31

% of Total ,0% 2,4% 14,6% 8,1% 25,2%

Total Count 4 35 71 13 123

39

ORGANIZATIONAL LEARNING * DIFFERENTIATION
CROSSTABULATION

V7

2 3 4 5 Total

Q1 1 Count 1 0 0 0 1

% of Total ,8% ,0% ,0% ,0% ,8%

3 Count 1 6 2 0 9

% of Total ,8% 4,9% 1,6% ,0% 7,3%

4 Count 2 26 51 3 82

% of Total 1,6% 21,1% 41,5% 2,4% 66,7%

5 Count 0 3 18 10 31

% of Total ,0% 2,4% 14,6% 8,1% 25,2%

Total Count 4 35 71 13 123

% of Total 3,3% 28,5% 57,7% 10,6% 100,0%

Taking all the companies into the account, the chi square test draws a
conclusion that there is an association between organizational learning and
differentiation strategy because we reject the null hypothesis in which the value of
significance is less than the predetermined level of significance that is equal to 0,005.
In addition to that, it is more important to emphasize at that point, cross tabulation
says that the positive relationship between organizational learning and differentiation
has a high diversity mainly at the center of the table because it reflects that companies
don‟t pay attention on the organizational learning and differentiation strategy together
at a high degree. Again, it can be a characteristic of our samples because they are
operated mostly in domestic market in Turkey, the differentiation strategy is not as
significant as cost leadership because Turkey is a developing country. That conclusion
is very important because our data has a power to reflect some differences and to give
some indicators about domestic characteristic. It is a different conclusion compared to
first two topics because the importance degree of organizational innovation increases
and becomes equal to organizational learning when we begin to talk about strategies
like in third case in which we talked about cost leadership strategy and unlike in first
two cases in which the main issues were total sales and market shares respectively anD

40

the organizational learning had stronger effect on variables than organizational
innovation.
Chi-Square Tests

Value Df Asymp. Sig. (2-sided)

Pearson Chi- 62,102
Square a
9 ,000

Likelihood 37,486 9 ,000
Ratio
Linear-by-
Linear 30,258 1 ,000
Association
N of Valid 123
Cases

41

CONCLUSIONS:

After we concluded to analyse the data, we want to draw some conclusions about our work.
First of all, we reached to the solution that organizational learning is associated with total sales
growth and cross tabulation. We have also seen that cross tabulation supports that relationship
between variables.
Another conclusion was that organizational learning is much more related with the total
sales growth than organizational innovation. However, we have not concluded that
organizational innovation is not associated with total sales growth.
Organizational learning is found to be associated with market share. According to our
analysis, organizational learning is much more related with market share compared to
organizational innovativeness however, we can not conclude that organizational innovation is
not related to market share.
We also found that a positive relationship between organizational learning and cost
leadership because companies had high organizational learning scores while they were paying
attention on the cost leadership strategy.
According to the data analysis, cutting costs did not mean decreasing innovations in the
company because in literature review we saw that organizational innovation was as important
as organizational learning for cost leadership strategy. This was a distinct conclusion compared
to our first two assumptions because the degree of organizational innovation increases and
becomes equal to the organizational learning when we begin to talk about strategies unlike in
first two cases in which the main issues are total sales and market shares respectively.
We have reached to the positive relationship between organizational innovation and
differentiation strategy, which had a high diversity mainly at the center of the table because it
reflected that companies didn‟t pay attention on the organizational innovation and
differentiation strategy together at a high degree.
Finally we concluded our analysis by stating, that this was a different conclusion again
compared to first two topics because the degree of importance in organizational innovation
increases and becomes equal to organizational learning when we begin to talk about strategies
like in third case in which we talked about cost leadership strategy and unlike in first two cases
in which the main issues were total sales and market shares respectively and the organizational
learning had stronger effect on variables than organizational innovations.

42

REFERENCES

Arayjo, Luis, John Burgoyne, and Mark Easterby-Smith. Organizational Learning and
the Learning Organization. London: SAGE Publications, 1999
Chiva-Gómez, Ricardo. “The facilitating factors for organizational learning: bringing
ideas from complex adaptive systems”. Knowledge and Process
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<http://www3.interscience.wiley.com/cgibin/fulltext/104526106/PDFSTART>
Dodgson, Mark. “Organizational Learning: A Review of Some Literatures”
Edmondson, Amy, and Bertrand Moingeon. Organizational Learning and Competitive
Advantage. London: SAGE Publications, 1996
Farago, John, and David J.Skyrme. “The Learning Organization” 1995
Lam, Alice. “Tacit Knowledge, Organisational Learning and Innovation: A Societal
Perspective”. Danish Research Unit For Industrial Dynamics Working Paper No. 98-
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Sheng-Hsun, Hsu. “Human Capital, Organizational Learning, Network Resources and
Organizational Innovativeness” Total Quality Management & Business Excellence;
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King, Nigel and Neil Anderson. “Managing Innovation and Change” Edition 2002 by
Thomson
Schwabsky Nitza, Eran Vigoda-Gadot, Aviv Shoham and Ayalla Ruvio “Towards a
Performance Orientation Measurement Grid”: „The Impact of Innovativeness and
Organizational Learning on Organizational Performance in Public Sector‟ Paper
submitted to the 2004 European Group of Public Administration (EGPA) meeting
Andy C. Yeung, Kee- Hung Lai and Rachel W.Y. Yee, “Organizational Learning,
Innovativeness, and Organizational Performance: A qualitative investigation”
International Journal Production Research, Vol.45, No.11, 1 June 2007, 2459-2477
Gregory E. Kersten, International Institute for Applied Systems Analysis, Austria and
Concordia University, Montreal, Canada Learning Organizations in the 5th Long
Wave: Management, Innovation, Knowledge, and IT 11/18/99

44

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