Analyzing Relational Sources of Power at the Interorganizational Communication System

1

Analyzing Relational Sources of Power

at the Interorganizational Communication System1

Abstract

Based on the critical theory of communication, managing

stakeholder relations is significant to achieve more

democratic decisions that reconcile diverse interests of

various stakeholders. However, power inequalities among

stakeholders might inhibit to achieve finely balanced

decisions. More interestingly, these inequalities might

emerge from the nature of communication among

organizations. Conceptualizing interorganizational

relations (IORs) as the relations of an organization with

its stakeholders, the current study attempts to analyze the

relational sources of power. Following a graph theoretical

methodology, the frequency of interaction and trust were

analyzed as the relational sources of power on a sample of

76 logistics firms. The findings of the study reveal that

1 Cite: Turker, D. (2014). Analyzing Relational Sources of Power at the Interorganizational Communication System. European Management Journal. 32(3): 509–517

2

an organization’s frequency of interaction and level of

trustworthiness affect its power over other organizations.

Keywords: graph theory, interorganizational

communication, interorganizational relations, power

3

Introduction

Organizations are the key elements of our modern

societies through functioning in various fields of human

life. Perrow indicated (1991) that the organizations as we

know today have appeared since the beginning of the 20th

century and become the main phenomenon of our age.

According to the author, now in today’s world where the

organizations are principal actors, the politics, social

class, finance, technology, religion, family, and even the

social psychology become the dependent variables. From this

sociological perspective, an organization can be defined as

a social system, which focuses for the purpose of reaching

a relatively specific goal that contributes to a principal

function of an extensive system – usually society (Parsons,

1956, p. 63).

Based on the question of whether the organizational

theory should focus on inner dynamics of an organization or

its interactions with the environment, Jaffee (2001)

distinguishes two level of analysis. The first one,

intraorganizational level, includes all factors concerning

with the internal environment of an organization. At this

4

level, organization is conceptualized as a closed system.

However, today most managers recognize that an organization

can make sense and function for a long time, as far as it

maintains its relations with its external environment –

which is the second level of analysis,

theinterorganizational level (Jaffee, 2001). An

organization is an‘incomplete social system dependent on

interchanges with its environment’ and must simply obtain

all inputs from outside while providing all outputs again

to outside (Aldrich and Marsden, 1988).

The interest of scholars to interorganizational level

can be traced back to the 1960s. In their early study,

Litwak and Hylton (1962) clearly distinguish the

intraorganization and interorganizational levels and

develop an approach concerning the conditions on which the

interorganizational coordination depends. Henceforth,

organizations tend to be conceptualized as entities that

should align their goals consistent with environmental

changes so as to interrelate with their environment on a

desired level (Thompson & McEwen, 1958, p.23). This view of

organizations has been commonly accepted since the 1960s;

5

while the importance of other organizations in the external

environment become more apparent (Hall, Clark, Giordano,

Johnson, & Rockel, 1977, p.457; Laumann, Galaskiewicz, &

Marsden, 1978), organizations are usually conceptualized as

‘open’ systems (Thompson, 1967; Katz & Kahn, 1966).

The interaction of organizations with other

organizations has been frequently studied since the 1970s.

Today, interorganizational relations (IORs) become one of

the significant fields of organizational theory and

contribute a lot to our current understanding on

organizations. However, depending on the difficulties of

collecting data at this level, theoretical approaches in

this field of study are not sufficiently backed up with

empirical research and there is an increasing need for new

studies to provide managerial insights on IORs. The purpose

of current study is to analyze interorganizational

communication in terms of power inequalities among various

stakeholders. The study attempts to investigate the

relational sources of power in the nexus of an actor’s

overall frequency of interaction and trustworthiness within

an organization set with considering the power inequalities

6

among stakeholders as an obstacle to achieve Deetz’s “fully

developed stakeholder model”. In order to analyze the

propositions of study, data was collected on a sample of 76

companies, which are operating in logistics sector in

Turkey. The collected data was analyzed with using a

framework drawing from graph theory and centralities of

each organizational stakeholder was used to capture how

organizations relate with each other in the organization

set.

1. Interorganizational Relations in the Organization Set

According to Zeitz (1980), if possible, organizations

do not prefer to interact with other organizations since

these relations might restrict their operations in the

future. However, organizations need to contact with each

other in order to decrease the level of uncertainty and

minimize the impact of threats in their external

environment. From a network perspective on business

strategy, the context of an organization includes

continuous interaction with other parties and ‘endows the

organization with a meaning and a role’ (Hakansson &

7

Snehota, 2006, p.267). Therefore, IORs can be critical to

survive in a strictly competitive environment.

According to Bachmann and Van Witteloostuijn (2006,

p.4), IORs are “formal arrangements that bring together

assets (of whatever kind, tangible and intangible) of two

or more legally independent organizations with the aim to

produce joint value added (of whatever kind, tangible or

intangible)”. However, this definition narrows down the

concept of IORs and assumes that it consists of only the

collaborative relationships. An IOR can be also defined as

“the relatively enduring transactions, flows, and linkages

that occur among or between an organization and one or more

organizations in its environment” (Oliver, 1990, p.241). In

order to analyze this wide range of relations, IORs can be

classified into four groups as dyadic connections between

two organizations, organization sets, action sets, and

networks (Whetten, 1981). Following the study of Evan

(1966), the second type of IORs, organization sets, can be

defined as a set that includes all the interorganizational

connections of a focal organization in its environment

(Whetten, 1981). Drawing from the Merton’s concept of role-

8

set, this unit of analysis allows explaining various issues

in the organizational context, such as identifying the

internal environment of an organization, analyzing how an

organization coordinates and competes with others in the

external environment (Evan, 1965, p.220) or defining ‘the

salient context at work for a given organization’(Scott,

2004, p.8) etc.

The concept of organization set is closely overlapping

with Rowley’s (1997) stakeholder set, which tries to

capture all interactions of a focal organization with its

stakeholders. In a stakeholder set, a focal organization

can be “more than simply the central point of its own

stakeholders: it is also a stakeholder of many other focal

points in its relevant social system” (Rowley, 1997,

p.892). Considering the complexity of stakeholder

management problems in modern organizations, the current

study follows this useful conceptualization of Rowley

(1997) and assumes that all stakeholders in an organization

set are the focal organization of their own sets, but

eventually, they are embedded into an upper social system.

This twofold perspective, which takes into account the

9

centrality of each stakeholder in their own set and treat

them as part of a supra-system, can help to figure out the

complexity of interorganizational communication system.

2. Analyzing Interorganizational Relations as a

Communication System

As a rational and goal-directed human behavior,

communication can be defined as “the process by which

information is exchanged and understood by two or more

people” (Daft, 2003, p.581). In a broader sense, the term

means “the relational process of creating and interpreting

messages that elicit a response” (Griffin, 2009, p.6). At

the interorganizational level, the concept is treated as

‘variable’ that affects the nature of relationship

(Czepiel, 1975) and coordination among parties (Williamson,

1976) or helps to understand each actor’s considerations

(Van de Ven & Walker, 1984). Interorganizational

communication is a process through which an organization

sends a message across a channel to another organization in

a network (Kapucu, 2006, p.209). It usually covers “the

formal as well as informal sharing of meaningful and timely

10

information” (Anderson & Narus, 1984, p.66; 1990, p.44) and

might help organizations to learn and adopt strategic

advantages in their operations (Paulraj, Lado, and Chen,

2008).

Despite the increasing importance of communication

among organizations, communication theories mainly focus on

the concept at the interpersonal level (Griffin, 2009). The

approaches, which analyze communication at the

organizational level [such as cultural approach (Pacanowsky

& O-Donnell-Trujillo, 1982; 1983), information systems

approach (Bantza, 1989; Weick, 1989), or the approaches

derived from socio-psychological tradition (Hitt, Miller, &

Collela, 2009; Robbins, Judge, & Campbell, 2010)], are

usually interested in the inner dynamics of organizational

life, rather than interorganizational context. Despite all

these useful attempts to understand the various dimensions

of organizational communication; most communication

theories and approaches short fall when articulating the

interaction among organizations - with one exception.

Deetz’s critical theory of communication in organizations

partly fills this void by analyzing organizational

11

communication with considering the interaction of an

organization with its stakeholders.

According to Deetz (1992; 1995a), due to their

increasing power, the management and decision making

processes in business organizations should be carefully

examined2. Comparing his communication approach with

information approach (Griffin, 2009), Deetz (1995b)

proposes four ways of decision making in organizations –

strategy, consent, involvement, and participation. Among

these four ways, the author suggests the strength of

‘meaningful democratic participation’ to transform business

organizations and their communication. Participation can

allow all stakeholders to represent and negotiate their

conflicting interests in the corporate decision making

2 In parallel to the increasing power of business community during thelast decades, Deetz (1992, p.17) criticize how business organizationshave become “the primary institution in modern society, overshadowingthe state in controlling and directing of individual lives andinfluencing collective social development” and call this process ascolonizing activity – based on Habermas’s (1987) ‘colonization of thelife-world’. According to the author, “both economic and politicalchanges necessitate rethinking the practices of management anddecision making in major corporations” (Deetz, 1995a, 278). The authorhas tried to figure out how ‘linguistic turn’ is important tounderstand the organizations (Deetz, 1996) and explained hisontological stands with presenting a communication approach thatmainly views language as the medium in the construction of socialreality (Deetz, 1992, p.129).

12

process (Deetz, 1995b). Therefore, “in a fully developed

stakeholder model, management’s function would need to

become the coordination of the conflicting interests of

stakeholders rather than the managing or controlling of

them” (Deetz, 2006, p.273).

Despite its obvious benefits, “stakeholder

collaboration remains fairly underdeveloped and often

ineffective” in the real world (Deetz, 2006, p.267) due to

the limited stakeholder inclusion by management team and

the lack of serious attention to models of communication in

decision making (Deetz, 2006). However, the problem might

be more complex than it seems. Although Deetz’ perspective

shows the importance of democratic participation, fairness,

equality, diversity, and cooperation with “reserving a seat

at the decision-making table for every class of

stakeholder”, his approach neglects “the problematic nature

of stakeholder negotiations…and incredible difficulty of

getting all parties to sit at the table as equals”

(Griffin, 2009, p.273). In fact, while emphasizing

‘stakeholder collaboration’ as a significant alternative to

involve social values into the organizational decision

13

making process, the author himself also revolved around the

questions like “whose objectives should count?”, “how much

should they count?”, or “how will they be accounted for?”

(Deetz, 2006). All these questions are basically related

with the power inequalities among stakeholders sitting

around the same negotiation table. Therefore, in order to

increase the participation of stakeholders in the corporate

decision making process and achieve a ‘fully developed

stakeholder model’ in the whole society, we need to

understand the preconditions and nature of communication

among stakeholders.

3. Key Variables of Interorganizational Communication

3.1. Frequency of Interaction

Frequency of interaction can be seen as the basic

component of each communication system. At the

interorganizational level, the frequent interactions among

organizations might contribute to the development of long-

standing and valuable relations (Christopher, 1992),

increase the level of cooperation (Hall et al., 1977; Heide

& Miner, 1992) or conflict (Hall et al., 1977). In their

14

study, Schmidt and Kochan (1977) analyze the nature of

interaction in symmetric and asymmetrical relations from

the integrated perspective of exchange and power-dependency

approaches and suggest that IORs should be conceptualized

as “a mixed-motive situation in which each organization

behaves in accordance with its own self-interests”. As

self-oriented actors, organizations should maintain to keep

in contact with other organizations in order to survive in

a competitive environment.

3.2. Trust

As a multidimensional concept of literature, trust can

be viewed as another significant component of communication

among organizations. According to a well-known definition

of literature, trust is “the willingness of a party to be

vulnerable to the actions of another party based on the

expectation that the other will perform a particular action

important to the trustor, irrespective of the ability to

monitor or control that other party” (Mayer, Davis, &

Schoorman, 1995, p.712). In the literature, there is a

15

growing interest to the role of trust in the organizations

as an antecedent, consequence, or mediator of relationships

(Fulmer and Gelfand, 2012). The studies at the

interorganizational level support that trust affects the

level of knowledge spillovers (Bönte, 2008) and builds

successful relationship among organizations (Adobor, 2005).

Based on their elaborate review of literature in 1990-2003,

Seppanen, Blomqvist, and Sundqvist (2007) indicate that

mutual trust is a key factor of relationship quality and

performance with its impact on reducing perception of risk,

transaction costs, opportunistic behavior, and increasing

effectiveness and cooperation among actors. According to

Hardy, Phillips, and Lawrence (2002), there are two main

factors for ‘coordinating trans-organizational

relationships’ depending on the nature of institutional

environment. As the first factor, trust absorbs uncertainty

in relationship while producing risk of engaging an action

with limited available information (Luhmann, 1979) and

“grows out of a communication process in which shared

meanings develop to provide the necessary foundation for

non-opportunistic behavior” (Hardy et al., 2002, p.69). On

16

the other hand, the second factor that yields co-operation

among organizations is ‘power’ (Hardy et al., 2002).

3.3. Power

Similar to trust, power should be taken into account

to analyze social relations among firms. A review of

literature shows that power is important at the

interorganizational level as well (Hall et al., 1977;

Kochan, 1975; Pfeffer & Leong, 1977; Schmidt & Kochan,

1977). In their previously mentioned study of Schmidt and

Kochan (1977), power and power relations are among the

significant domains of explaining the interactions among

organizations.

Although most people attribute a negative meaning to the

concept of power, according to Granovetter (1985, p.501-

502), the ‘effective exercise of power’ can smooth the

social relationships and decrease the potential conflict

among actors. It can be defined as a potential ability to

affect other’s behaviors (Mintzberg, 1983) and usually seen

as a consequence of an actor’s inherent characteristics

like his or her knowledge, charisma or money. However,

17

following Emerson (1962), Hickson, Hinings, Lee, Schneck

and Pennings (1971, p.217) conceptualize power as a

‘property of social relationship, not of the actor’ in

order to analyze its nature at the upper social systems.

From this point of view, power might be derived from the

nature of communication among actors. According to Dahl

(1957, p.202-203), ‘A has power over B to the extent that

he can get B to do something that B would not otherwise

do’. In this case, A has something that B wants and the

more B depends on A, the more A has power on B (Pffefer &

Salancik, 2003). From this perspective of resource

dependency theory (Aldrich, 1976, 1979; Pffefer & Salancik,

2003), in IORs (1) the strong side is relatively the one

which controls a source that is depended on (2) and the one

which can reduce its dependency for the resources that

belong to someone else (Provan, Beyer & Kruytbosch, 1980,

p.200). Since “organizational choice is constrained by the

patterns of interdependence and influence emanating from

the social context”, organizations should take power

emerged from these patterns of resource exchange in their

18

relationships into consideration (Pffefer & Salacik, 2003,

p.138).

4. Relational Sources of Power at the Interorganizational

Level

Today, organizational resources can include everything

from capital to know-how, business network, strategic

partnerships or operating systems. Considering this variety

of resources, it might be difficult to understand what

makes an organization powerful and to articulate the nature

of power relationship among organizations. Based on the

classical typology of French and Raven (2001), A can

exercise power over B if (1) A has ‘the ability to mediate

rewards’ for B, (2) A has ‘the ability to mediate

punishments’ for B, (3) A has ‘a legitimate right to

prescribe behavior’ for B, (4) B has identification with A,

or (5) A has ‘some special knowledge or expertness’. These

sources of power can be used at the interorganizational

level as well; for instance, a government organization can

be more powerful over others, since it executes a fund-

19

raising system or, it has a legal right to punish other

organizations.

On the other hand, the nature of relationship can also

affect the power inequalities among organizations. The

‘relational’ sources of power are the determinants of power

that “derive from the structure of relationships among

actors, and groups of actors both intra- and

interorganizationally” (Thornton & Ocasio, 1999, p.804;

Thornton, 2004, p.70). For instance, let’s assume that

Company-C has a resource that is critical for Company-B,

and Company-A is the only actor that can bridge and bond B

and C. In this case, A becomes a structural hole between

two actors and obtains power over B. In the literature,

this resource-dependency relation is articulated as a

measure of power, in which an actor’s power basically

depends on the number of exchange partners who are

interested in the actor’s resource (Yamaguchi, 1996).

However, in the given example, it is assumed that B has

perfect information about which actor has this key resource

(C) and which actor knows the owner of this key resource

(A) in the organization set. In the real world,

20

organizations usually compete with imperfect and asymmetric

information and managers must make decisions under a high

degree of uncertainty. Therefore, if B has not sufficient

information about other actors in the organization set, it

might try to connect with the actor who interacts most in

the set to gather information about the owner of this

resource. As a result, the most frequently interacted actor

in the set can increase its power over others. This

discussion can lead the following proposition:

Proposition 1. There is a link between an organization’s overall frequency of

interaction in an organization set and its power in each dyadic relation within

this set.

Power might be related with trust as well. In his

study, Granovetter (1985) attributes a smoothing role to

both trust and power in social relationship. At the

interpersonal level, most people find referent or expert

power as a foundation of trust to other party. For

instance, the studies show that if a salesperson has an

expert power, he or she is perceived as more trustworthy

(Busch & Wilson, 1976; Crosby, Evans, & Cowles, 1990). On

the other hand, at the interorganizational level, “research

21

organizations or departments have achieved power because of

their specialized skills, trust is likely to follow as

users rely on those skills in the design and evaluation of

marketing strategies” (Moorman, Deshpande, and Zaltman,

1993, p.86).

Power and trust should be considered as the

“complementary and opposing components of social behavior”

(Ireland & Webb, 2007). In their study, Belaya, Török, and

Hanf (2008) indicate that “power coexists alongside with

trust” throughout the supply chain and managers should

scrutinize the cooperative and competitive structure of a

chain to manage it more effectively. However, power and

trust coexist in a relation depending on the type of power,

as coercive or non-coercive (Ireland & Webb, 2007). In

their study, Leonidou, Talias, and Leonidou (2008) find

that coercive power increases the level of conflict, which

affects trust among actors negatively. In their empirical

study, which is conducted on Chinese supply chains, Yeung,

Selen, Zhang, and Huo (2009) find that both trust and

coercive power contribute to the improvement of internal

and supplier integration, but if trust is low, coercive

22

power reduces internal integration. However, it is clear

that “an excessive use of either non-coercive or coercive

power may undermine trust in a relationship” (Ireland &

Webb, 2007). In sum, the literature indicates that trust

and power can coexist in IORs and based on this discussion,

the following proposition can be provided as:

Proposition 2. There is a link between an organization’s overall level of

trustworthiness in an organization set and its power in each dyadic relation

within this set.

5. Research Methodology

5.1. Population and Sample Selection

In the study, logistics sector was chosen to analyze

the proposed links empirically. Logistics can be defined as

“the planning and management of physical and information

flows though an organization” (Mangan and Christopher,

2005) and a logistics firm can take the role of mediator

between producers and consumers. Therefore, this sector is

characterized by intense web of relations among

organizations and a firm operating in this sector should

23

involve into the high degree of interorganizational

communication and coordination.

Population of study includes all logistics companies

operating in Turkey. In order to reach a generalizable data

set, a survey was conducted on the members of Association

of International Forwarding and Logistics Service Providers

(UTIKAD), which has been a leading logistics association in

Turkey since 1986. The questionnaire form was sent to 300

member companies. Although 81 completed questionnaire forms

were returned, only 76 of them were useable. Therefore, at

the end of the process, the response rate was approximately

25 percent.

5.2. Data Collection Method

The data was collected with using adjacency matrix. In

order to prepare matrices, first, organizational

stakeholders of a logistics company were determined with

conducting a group discussion with three practitioners,

working in this sector, and three academicians. Based on

the overall consensus of group, seven organizational

stakeholders of a logistics firm were identified and

24

represented as a vertex (v) on a graph. Thesymbols of each

organizational stakeholder can be seen in the following:

v1: focal organization; v2: customers; v3: competitors; v4: suppliers/subcontractors, v5:

banks & financial institutions, v6: public organizations, v7: chamber of commerce &

associations, and v8: non-governmental organizations (NGOs) & universities

In the questionnaire form, three 7x8 matrices were

used to measure 28 dyadic relations among these

stakeholders. Matrix structure (Knoke and Kuklinski, 1982:

43) can be used in many studies to collect data (Anderson,

1976; Bolland and Wilson, 1994; Galaskiewicz and Krohn,

1984; Galaskiewicz and Wasserman, 1989; Gulati and

Gargiulo, 1999; Oliver, 1988). Since all dyadic relations

in each matrix were assessed by focal organization, the

results reflect the perception of focal organization on the

interorganizational relationship in its own organization

set.

In the questionnaire form, three main variables of

study (frequency of interaction, trust, and power) were

provided in three matrices. Table 1 presents each item,

which was provided before each matrix and developed by

Turker (2010). In the literature, the interaction among

25

actors is usually measured through identifying the

existence/absence of interaction (Anderson, 1976) or its

frequency (Schmidt & Kochan, 1977). Following the latter,

frequency of interaction was measured on a five-point

Likert scale. Similarly, the level of trust in each dyad

was measured on a five-point Likert scale. In order to

measure power in 28 dyadic relations, the matrix was

separated into two main groups as A (representing the

organizations on the vertical axis) and B (representing the

organizations on the horizontal axis), and respondents

evaluated the balance of power in each dyad on a five point

Likert scale. Table 1 shows the alpha levels of three

matrices which were used to assess 28 dyadic relations in

organization set. It can be seen that all matrices have

Cronbach’s alpha values higher than suggested level of 0.70

(Hair, Black, Anderson, & Tatham, 2006).

-- Insert Table 1 here –

5.3. Analysis Method

In the analysis, some basic notions of graph theory

were used like directed graph or digraph (a graph each of

26

whose edges is directed) and weighted graph (a graph in

which each edge is assigned a number) (Gross & Yellen,

2006). The frequency of interaction and trust were analyzed

on the weighted digraph of power matrix with using the

concept of centrality. As a concept that is originally

derived from graph theory (Freeman, 1977) and frequently

used in the social network analysis (Borgatti, 2005, p.56),

centrality can be defined in many ways based on the nature

of research question. Therefore, today, the literature

provides different measures of centrality including degree,

closeness, betweenness, eigenvector, information, flow

betweenness, the rush index, influence centrality etc.

(Borgatti, 2005; Borgatti & Everett, 2006; Czepiel, 1974;

Estrada & Rodriguez-Velázquez, 2005; Everett & Borgatti,

2005; Freeman, 1977; Freeman, 1979; Freeman vd., 1991;

MacKenzie, 1966a, 1966b; Nieminen, 1973; Rogers, 1974;

Sabidussi, 1966). Despite this variety, ‘all measures of

centrality assess a node’s involvement in the walk

structure of a network’ based on four key dimensions as

type of nodal involvement assessed, type of walk

considered, property of walk assessed, and choice of

27

summary measure (Borgatti & Everett, 2006). In the current

study, degree centrality was computed with using UCINET 6

(Borgatti, Everett, & Freeman, 2002). In degree centrality,

the number of vertices adjacent to a given vertex in a

symmetric graph provides the degree of this vertex

(Borgatti et al., 2002). However, in the current study, the

data was collected with using a 5-point Likert scale for

each matrix and it is important to capture the information

from these weights of relationships. In UCINET, if the data

is valued then the degrees are calculated considering the

weights of relationships.

5.4. Results

The companies operate approximately for 19 years in

the sector. In terms of their employee numbers, 18.4

percent of them are micro (1-9 employees), 39.5 percent of

them are small (10-49 employees), 21.1 percent of them are

medium (50-249 employees), and 21.1 percent of them are

large scale companies. In terms of their ownership

structure, while 6 companies have a foreign partner, 11 of

them are foreign-owned companies. In order to determine

28

whether the respondents were knowledgeable about their

IORs, some questions were asked to them as well. The

results revealed that the mean value of respondents’ tenure

is approximately 7 years and most participants have

bachelor degree and currently work in a managerial position

in their companies. Following the study of Van Bruggen,

Lilien and Kacker (2002, p.476), a self-evaluation question

was asked to the respondents about their competency (Is your

current position in the organization sufficient to assess the relations of your

company with other organizations?) and all respondents said ‘yes’.

The overall condition of sector was evaluated with

using a four-item scale of Sharfman and Dean (1991) on a

five-point Likert scale. The results show that it is quite

difficult to be profitable in this sector (mean value is

3.48) and there are many legal regulations (mean value is

3.72). However, the sector provides relatively stable

conditions for firms (mean value is 2.81) and they can

follow and adapt the technological trends (mean value is

2.36).

29

Table 2 presents the descriptive statistics for the

frequency of interaction matrix. It can be seen that the

mean values range from 4.394 (the dyad between focal

organization and customers) to 1.492 (the dyad between

NGOs/Universities and Suppliers/Subcontractors). Table 3

shows the descriptive statistics for trust matrix and the

mean values range from 4.48 (the dyad between focal

organization and customers) to 3.28 (the dyad between

NGOs/Universities and Suppliers/Subcontractors).

-- Insert Table 2 here --


Table 4 presents the descriptive statistics for power

matrix. Following the formula of Newbold, Carlson, and

Thorne (2003), the dyadic relations were classified as

highly inequal, inequal or equal. While there is no equal

relations in the organization set, 11 of 28 dyadic

relations are characterized by high degree of inequality.

Based on this analysis, the weighted digraph of power

matrix was obtained showing the degree and direction of

power relations in each dyad (Figure 1).

30


-- Insert Figure 1 here --

In the next step, the centrality values for frequency

of interaction and trust were computed based on the data

given in Table 2 and Table 3. Table 5 shows that the focal

organization is the most central actor in both matrices.

Although the order of next three actors are different, the

analysis shows that customers (v2), banks & financial

institutions (v5), and public organizations (v6) are among

the most central actors of this organization set.

-- Insert Table 5 here --

In the last step, the propositions of study were

analyzed with inserting the vertex centrality values (Table

5) on the weighted digraph of power matrix (Figure 1). It

can be seen in Figure 2 that 21 of 28 dyadic relations

indicates that the more powerful actor has the higher

centrality value. This result can support the first

proposition regarding with the link between an

organization’s overall frequency of interaction and its

power in an organization set. On the other hand, the power

31

inequalities are high in 9 of these 21 relations, public

organizations are always the more powerful side of this

organization set.


The same procedure was followed in order to analyze

the second proposition on the link between trust and power.

Figure 3 shows that the more powerful actor has the higher

centrality value in 21 of 28 dyadic relations and this

result can also support the second proposition. Therefore,

an organization can gain power over other actors if it has

a trustworthy position in the organization set.


5.5. Limitation

The current study is subject to some limitations. The

empirical approach of study is exploratory in nature.

Although following a graph theoretical methodology fits

well to analyze relationships among actors, it does not

allow performing a hypothesis testing based on the

generally accepted threshold values. On the other hand,

grouping organizational stakeholders under a single actor

32

might limit to understand what actually happens among the

real actors in the organization set. However, this method

can partly overcome the most common problem of network

studies which is maintaining anonymity (Borgatti & Molina,

2003, p.338).

Since the data was collected from only one country and

one sector, the results can be generalized only in this

context. Turkey demonstrates significant convergence with

both Eastern and Western cultures. According to the well-

known study of Hofstede (1983, 2012), Turkey is

characterized by large power distance, low individualism,

strong uncertainty avoidance, and moderate femininity

together with some other Mediterranean and Middle Eastern

countries. In a more recent study, Turkey was taken as a

member of Arabic cluster (consisting of Egypt, Morocco,

Kuwait, and Qatar) depending on their common historical,

religious, and socio-cultural characteristics; these

countries are found as high group-oriented, hierarchical,

masculine, and low on future orientation (Kabasakal &

Bodur, 2002). In spite of these commonalities with Eastern

societies, Turkey has also adopted the Western culture and

33

values after the successful revolution of Atatürk. During

particularly the last decades, business community converges

to a similar way of business approach with Western

counterparts in parallel to globalization trends,

technological advancements and increasing relations with

Western countries. Therefore, the results obtained from

Turkey, which is geographically and culturally in between

East and West, can enlighten the various aspects of IORs in

different societies. On the other hand, logistics sector

might represent the case of similar sectors that builds on

the intense relationships among various actors.

Discussion

The current study attempts to investigate the

relational sources of power to figure out what might happen

when organizational stakeholders participate in a common

decision making process. Following a graph theoretical

approach, the proposed relations were analyzed, following

graph theoretical methodology and the results show that if

an actor was frequently interacting with other actors and

was found to be trustworthy in the set, its power in dyadic

34

relations can be much higher. Therefore, in addition to the

classical sources of power, the communication variables

like frequency of interaction and trust can become the

alternative sources of power. In order to achieve a

consensus among various stakeholders, managers should take

into account these relational sources of power. When

particularly making a decision, which affects various

organizational stakeholders simultaneously, a manager

should take into account the communication process as well.

The result of this survey indicates that managers might

gain power over other actors by interacting more frequently

and intensely in their organization set.

The study also gives some important clues about the

current role of actors in the organization set. For

instance, public organizations are found both powerful and

trustworthy and this result is in line with the current

theoretical debate on relations with state organizations in

Turkey (Bugra, 1994, p.5; Sozen and Shaw, 2003). In

accordance with the findings of Hofstede’s study (1983,

2012) on power distance, state institutions in Turkey act

like a ‘father’ (Sozen and Shaw, 2003) that both protects

35

his son and imposes discipline when needed. In fact, the

legal-base in a relationship can change all rules of a game

even in the Western societies. According to Hall et al.

(1977, p.470) “when the basis of interaction is a legal

mandate, the power issue is apparently resolved to the

extent that it does not become part of the pattern. This is

not to say that there are not power differences but that

these have apparently been accepted by the parties involved

and are no longer an issue”. Therefore, when a public

organization is involved into a decision making process,

managers of a focal organization should consider its power

over other actors and, if possible, try to balance this

power inequality by increasing their level of interaction

and building trustworthy relations with others.

In addition to public organizations, the study also

shows that customers are among the central actors of a

logistics firm’s organization set. Managing relations with

customers are critical not only for increasing

profitability or market share, but also these interactions

can enhance the innovation and knowledge accumulation in

the organizations (Ford, Gadde, & Hakansson, 2003;

36

Takeishi, 2001). In line with the previous studies,

customers are among the most valuable stakeholders of a

company and managers should build and maintain longstanding

relations by increasing the interaction and trustworthy

relations with this stakeholder.

On the other hand, NGOs & universities are the most

neglected actors in this organization set. This result is

partly related with the unfavorable political structure of

the country during the 1980s (Kongar, 1999, p.199).

However, today, there are serious attempts at the national

and international levels to strengthen the relations with

NGOs & universities. During the last decades, many techno-

parks have been established to encourage innovation and

increase the knowledge spillover between universities and

industry organizations (Aydogan-Duda, 2012). Despite all

these attempts, the current study reveals that the

relations with universities and business organizations are

not sufficient to create a knowledge accumulation to foster

innovation. Therefore business leaders should try to

increase the level of communication and cooperation with

these neglected groups of stakeholders. Involving these

37

stakeholders into decision making process will increase the

quality of decisions and foster the cooperation among these

organizations. Although this study attempted to understand

the nature of interorganizational communication system,

there is an increasing need for new studies to figure out

whether other dimensions of this system, like information

flows, specific resource exchanges, social networks, social

projects partnerships etc., can also affect the

communication among organizations.

References

Adobor, H. (2005). Trust as sensemaking: the microdynamics

of trust in interfirm alliances. Journal of Business

Research, 58, 330– 337.

Aldrich, H. (1976). Resource dependence and

interorganizational relations: Local employment

service offices and social services sector

organizations. Administration and Society, 7(4), 419-454.

Aldrich, H. (1979), Organization sets, action sets, and

networks: Making the most of simplicity. In P.C.

38

Nystrom & W.H. Starbuck (Ed.s), Handbook of Organization

Desing Vol.1 (pp.385-408). Amsterdam: Elsevier, s.385-408.

Aldrich, H.E. & Marsden, P. (1988). Environment and

organizations. In N.J. Smelser (Ed.), Handbook of

Sociology (pp.361-392). Beverly Hills (CA): Sage.

Anderson, R.C. (1976). A sociometric approach to the

analysis of interorganizational relationships.

W.M.Evan (Ed.), Inter-organizational Relations (pp.307-324).

Great Britain: Penguin Books Ltd.

Anderson, J.C. & Narus, J.A. (1984). A model of the

distributor's perspective of distributor-manufacturer

working relationships. Journal of Marketing, 48(4), 62-74.

Anderson, J.C. & Narus, J.A. (1990). A model of distributor

firm and manufacturer firm working partnerships.

Journal of Marketing, 54(1), 42-58.

Aydogan-Duda, N. (2012). Business Environment, Innovation

Culture, and Technology Clusters in Developing

Countries. In Making It to the Forefront (pp. 41-46).

Springer New York.

39

Bachmann, R. & Van Witteloostuijn, A. (2006), Analysing

inter-organizational relationships in the context of

their business systems – a conceptual framework for

comparative research. Institute for Advanced Studies, Sociological

Series (78). Retrieved from

http://www.ihs.ac.at/publications/soc/rs78.pdf

Bantza, C.R. (1989). Organizing and the social psychology

of organizing. Communication Studies, 40(4), 231-240

Belaya V., Török, T., & Hanf, J. (2008). Recognizing the

links between power and trust in managing supply chain

relationships. 12th Congress of the European Association of

Agricultural Economists. Retrieved from

http://195.0.30.90/EAAE/delegates/186.pdf

Blau, P.M. & Scott, W.R. (2003). Formal organizations: A

comparative approach. San Francisco: Stanford Univ. Press

Bolland, J.M. & Wilson, J.V. (1994). Three faces of

ıntegrative coordination: A model of

interorganizational relations in community-based

health and human services, Health Services Research, 29(3),

341-366.

40

Borgatti, S.P. (2005). Centrality and network flow. Social

Networks, 27: 55–71

Borgatti, S.P. & Everett, M.G. (2006). A graph-theoretic

perspective on centrality. Social Networks, 28(4): 466-

484.

Borgatti, S.P., Everett, M.G., & Freeman, L.C. (2002).

Ucinet for windows: Software for social network analysis. Harvard

(MA): Analytic Technologies.

Borgatti S.P. & Molina, J.L. (2003). Ethical and strategic

issues in organizational social network analysis. The

Journal of Applied Behavioral Science, 39(3), 337-349.

Bönte, W. (2008). Inter-firm trust in buyer–supplier

relations: Are knowledge spillovers and geographical

proximity relevant? Journal of Economic Behavior &

Organization, 67, 855–870.

Buğra, A. (1994). State and business in modern turkey: A comparative

study. USA: Sate University of New York Press.

Busch, P. & Wilson, D.T. (1976). An experimental analysis

of a salesman’s expert and referent bases of social

power in the buyer-seller dyad. Journal of Marketing

Research, 13, 3-11.

41

Christopher, M., (1992). Logistics and supply chain management.

London: Pitman.

Cook, K.S. (1977). Exchange and power in networks of

interorganizational relations. The Sociological Quarterly

(Special Issue Organizational Analysis: Critique and Innovation), 18

(1), 62-82.

Crosby, L.A., Kenneth, R. E., & Cowles, D. (1990).

Relationship quality in services selling: An

interpersonal influence perspective. Journal of Marketing,

54, 68-81.

Czepiel, J. A. (1974). Word of mouth processes in the

diffusion of a major technological innovation. Journal

of Marketing Research, 11, 172-180.

Czepiel, J.A. (1975). Patterns of interorganizational

communications and the diffusion of a major

technological innovation in a competitive industrial

community. The Academy of Management Journal, 18(1), 6-24.

Daft, R.L. (2003). Management. USA: Thomson South-Western.

Dahl, R.A. (1957). The concept of power. Behavioral Science,

2(3), 201-218.

42

Deetz, S.A. (1992). Democracy in an age of corporate colonization:

Developments in communication and the politics of everyday life.

Albany: State University of New York Press.

Deetz, S. (1995a). Transforming communication, transforming

business: Stimulating value negotiation for more

responsive and responsible workplaces. International

Journal of Value-Based Management, 8: 255-278.

Deetz, S. (1995b). Transforming communication, transforming business:

Building responsive and responsible workplaces, Hampton,

Cresskill, NJ.

Deetz, S. (1996). Describing differences in approaches to

organization science: Rethinking Burrell and Morgan

and their legacy. Organization Science, 7(2), 191-207.

Deetz, S. (2006). Corporate governance, corporate social

responsibility, and communication. In S.K. May, G.

Cheney, & J. Roper (Ed.s), The debate over corporate social

responsibility (pp.267-278). Oxford: Oxford University

Press.

Emerson, R.E. (1962). Power-dependence relations. American

Sociological Review, 27, 31-41.

43

Estrada, E., & Rodriguez-Velázquez, A. (2005). Subgraph

centrality in complex networks. Physical Review E., 71(5),

056103/9.

Evan, W.M. (1965). Toward a theory of inter-organizational

relations. Management Science, 11(10), 217-230.

Evan, W. (1966). The organization set. In J. Thompson

(Ed.), Approaches to organizational design. Pittsburgh:

University of Pittsburgh Press [Cited in Whetten

(1981)].

Everett, M. & Borgatti, S.P. (2005). Ego network

betweenness. Social Networks, 27, 31-38.

Ford, D.G., Hakansson, L.E., & Snehota, H.I. (2003).

Managing business relationships. England: Wiley.

Freeman, L.C. (1977). A set of measures of centrality based

on betweenness. Sociometry, 40 (1), 35-41.

Freeman, L.C. (1979). Centrality in social networks:

Conceptual clarification. Social Networks, 1, 215-239.

Freeman, L.C., Borgatti, S.P. & White, D.R. (1991).

Centrality in valued graphs: A measure of betweenness

based on network flow. Social Networks, 13: 141-154.

44

French, J.R.P., & Raven, B. (2001). The bases of social

power. In I.G. Asherman & S.V. Asherman (Ed.s). The

negotiation sourcebook (61-73). USA: HRD Press.

Fulmer, C. A., & Gelfand, M. J. (2012). At what level (and

in whom) we trust trust across multiple organizational

levels. Journal of Management, 38(4), 1167-1230.

Galaskiewicz, J. & Krohn, K.R. (1984). Positions, roles,

and dependencies in a community ınterorganization

system. The Sociological Review, 25(4), 527-550.

Galaskiewicz, J. & Wasserman, S. (1989), Mimetic processes

within an ınterorganizational field: An empirical

test, Administrative Science Quarterly, 34(3), 454-479.

Granovetter, M. (1985). Economic action and social

structure: The problem of embeddedness. American Journal

of Sociology, 91(3), 481-510.

Griffin, E. (2009). A First Look at Communication Theory.

Singapore: McGraw-Hill.

Gross, J.L. & Yellen, J. (2006). Graph Theory and Its

Applications. USA: Taylor & Francis Group.

45

Gulati, R. & Gargiulo, M. (1999). Where do

interorganizational networks come from? The American

Journal of Sociology. 104(5),1439-1493.

Habermas, J. (1987) The Theory of Communicative Action Volume II:

System and Lifeworld. Cambridge: Polity.

Hair, J.F., Black, W.C., Anderson, R.E., & Tatham, R.L.

(2006). Multivariate Data Analysis, New Jersey: Pearson-

Prentice Hall.

Hakansson, H. & Snehota, I. (1989). No business is an

island: The network concept of business strategy.

Scandinavian Journal of Management, 5(3), 187-200.

Hall, R.H., Clark, J.P., Giordano, P.C., Johnson, P.V., &

Rockel, MV. (1977). Patterns of interorganizational

relationships. Administrative Science Quarterly, 22(3), 457-

474.

Hardy, C., Phillips, N., & Lawrence, T. (2002).

Distinguishing trust and power in interoranizational

relations: Forms and façades of trust. In C. Lane & R.

Bachmann (Ed.s), Trust within and between organizations: conceptual

46

issues and empirical applications (pp.64-87). Oxford: Oxford

University Press.

Heide, J.B. & Miner, A.S. (1992). The shadow of the future:

Effects of anticipated interaction and frequency of

contact on buyer-seller cooperation. The Academy of

Management Journal, 35(2), 265-291

Hickson, D. J., Hinings, C. R., Lee, C. A., Schneck, R.

E., & Pennings, J. M. (1971). A strategic

contingencies’ theory of intraorganizational power.

Administrative Science Quarterly , 16(2), 216-229.

Hitt, M.A., Miller, C.C., & Colella, A. (2009).

Organizational Behavior: A Strategic Approach. USA: John Wiley &

Sons.

Hofstede, G. (1983). The cultural relativity of

organizational practices and theories. Journal of

International Business Studies. 14(2), 75-89.

Hofstede, G. (2012). Countries. Retrieved from

http://geert-hofstede.com/turkey.html

Jaffee, D. (2001). Organization Theory: Tension and Change.

Singapore: McGraw Hill.

http://geert-hofstede.com/turkey.html

47

Kabasakal, H. & Bodur, M. (2002). Arabic cluster: A bridge

between East and West. Journal of World Business, 37, 40-54.

Kapucu, N. (2006). Coordination interagency communication

networks during emergencies: Boundary spanners in

multiagency. The American Review of Public Administration, 36,

207-225.

Katz, D. & Kahn, R.L. (1966). The Social Psychology of

Organizations. New York: John Wiley.

Kochan, T.A. (1975). Determinants of the power of boundary

units in an interorganizational bargaining relation.

Administrative Science Quarterly, 20(3), 434-452.

Kongar, E. (1999). 21.yüzyılda Türkiye: 2000’li yıllarda

Türkiye’nin toplumsal yapısı İstanbul: Remzi Kitabevi.

Laumann, E.O., Galaskiewicz, J., & Marsden, P.V. (1978).

Community structure as interorganizational linkages.

Annual Review of Sociology, 4, 445-84.

Leonidou, L.C., Talias, M.A., & Leonidou, C.N. (2008).

Exercised power as a driver of trust and commitment in

cross-border industrial buyer–seller relationships.

Industrial Marketing Management, 37, 92–103.

48

Litwak, E. & Hylton, L.F. (1962). Interorganizational

analysis: A hypothesis on coordinating agencies.


Luhmann, N. (1979), Trust and Power, Chichester: Wiley.

[Cited in Bachmann & van Witteloostuijn (2006); Hardy,

Phillips, & Lawrence (2002)].

Ireland, R.D. & Webb, J.V. (2007). A multi-theoretic

perspective on trust and power in strategic supply

chains. Journal of Operations Management, 25, 482–497

Mackenzie, K. D. (1966a). Structural centrality in

communications networks. Psychometrica, 31, 17-25.

Mackenzie, K. D. (1966b). The information theoretic entropy

function as a total expected participation index for

communication network experiments. Psychometrika, 31,

249-254.

Mangan, J., & Christopher, M. (2005). Management

development and the supply chain manager of the

future. International Journal of Logistics Management, The, 16(2),

178-191.

49

Mayer, R.C., Davis, J.H., & Schoorman, F.D. (1995). An

integrative model of organizational trust, The Academy

of Management Review, 20(3), 709-734.

Mintzberg, H. (1983). Power in and around Organizations,

Englewood Cliffs (N.J.): Prentice-Hall. [Cited in Daft

(2003)]

Moorman, C., Deshpandé, R., & Zaltman, G. (1993). Factors

affecting trust in market research relationships.

Journal of Marketing, 57(1), 81-101.

Newbold, P., Carlson, W.L., & Thorne, B. (2003). Statistics for

Business and Economics. New Jersey: Pearson Education.

Nieminen, U.J. (1973). On the centrality in a directed

graph. Social Science Research, 2, 371-378.

Oliver, C. (1988), The collective strategy framework: An

application to competing predictions of isomorphism.


Oliver, C. (1990). Determinants of interorganizational

relationships: Integration and future directions.

Academy of Management Review, 15(2), 241-265.

50

Pacanowsky, M., O’Donnell-Trujillo, N. (1982).

Communication and Organizational Cultures. Western

Journal of Speech Communication, 46, 115-130.

Pacanowsky, M., O’Donnell-Trujillo, N. (1983).

Organizational Communication as Cultural Performance.

Communication Monographs, 50, 127-147.

Parsons, T. (1956). Suggestions for a sociological approach

to the theory of organizations. Administrative Science

Quarterly, 1, 63-85.

Paulraj, A., Lado, A.A., & Chen, I.J. (2008). Inter-

organizational communication as a relational

competency: Antecedents and performance outcomes in

collaborative buyer–supplier relationships. Journal of

Operations Management, 26(1), 45-64,

Perrow, C. (1991), A society of organizations. Theory and

Society, 20(6), 725-762.

Pfeffer, J. & Leong, A. (1977). Resource allocations in

United Funds: Examination of power and dependence.

Social Forces, 55(3), 775-790.

51

Pfeffer, J. & Salancik, G.R. (2003). The external control of

organizations: A resource dependence perspective. New York:

Harper & Row.

Provan, K.G., Beyer, J.M., & Kruytbosch, C. (1980).

Environmental linkages and power in resource-

dependence relations between organizations.


Robbins, S.P., Judge, T.A., & Campbell, T.T. (2010).

Organizational Behavior. Italy: Pearson.

Rogers, D. L. (1974). Sociometric analysis of

interorganizational relations: Application of theory

and measurement. Rural Sociology, 39, 487-503.

Rowley, T.J. (1997). Moving beyond dyadic ties: A network

theory of stakeholder influences. The Academy of

Management Review, 22(4), 887-910

Sabidussi, G. (1966). The centrality index of a graph.

Psychometrika, 31(4), 581-603.

Scott, W.R. (2004). Reflections on a half-century of

organizational sociology. Annual Review of Sociology, 30, 1-

21.

52

Seppanen R, Blomqvist K., & Sundqvist, S. (2007). Measuring

inter-organizational trust: A critical review of the

empirical research in 1990-2003. Industrial Marketing

Management, 36(2), 249-265

Sharfman, M.P. & Dean, J.W. (1991). Conceptualizing and

measuring the organizational environment: A

multidimensional approach. Journal of Management, 17(4),

681-700.

Sozen, S. & Shaw, I. (2003). Turkey and the European Union:

Modernizing a traditional state? Social Policy &

Administration, 37(2), 108–120.

Schmidt, S.M. & Kochan, T.A. (1977). Interorganizational

relationships: Patterns and motivations. Administrative

Science Quarterly, 22(2), 220-234.

Takeishi, A. (2001). Bridging inter- and intra-firm

boundaries: Management of supplier involvement in

automobile product development. Strategic Management

Journal, 22, 403–433

Thompson, J.D. & McEwen, W.J. (1958). Organizational goals

and environment: Goal-setting as an interaction

process. American Sociological Review, 23(1), 23-31.

http://apps.isiknowledge.com/DaisyOneClickSearch.do?product=WOS&search_mode=DaisyOneClickSearch&db_id=&SID=Q116eG58LmAmEjGlb1n&name=Sundqvist%20S&ut=000244729900012&pos=3

53

Thompson, J.D. (1967). Organizations in action, New York:

McGraw-Hill. [Cited in Cook (1977)]

Thornton, P. H. 2004. Markets from culture: Institutional

logics and organizational decisions in higher

education publishing. Stanford: Stanford University

Press.

Thornton, P.H. & Ocasio, W. (1999). Institutional logics

and the historical contingency of power in

organizations: Executive succession in the higher

education publishing industry, 1958-1990. American

Journal of Sociology,105(3),801-843.

Turker, D. (2010). Örgütlerarası İlişkiler Analizi:

Lojistik Sektöründe Bir Alan Araştırması. Unpublished

PhD Dissertation. Dokuz Eylul Universitesi, Izmir.

Whetten, D.A. (1981). Interorganizational relations: A

review of the field. The Journal of Higher Education, 52(1),

1-28.

Van de Ven, A.H. & Walker, G. (1984). The dynamics of

interorganizational coordination. Administrative Science

Quarterly, 29(4), 598-621.

54

Van Bruggen, G.H., Lilien, G.L., & Kacker, M. (2002).

Informants in organizational marketing research: Why

use multiple informants and how to aggregate

responses. Journal of Marketing Research, 39(4), 469-478.

Yamaguchi, K. (1996). Power in networks of substitutable

and complementary exchange relations: A rational-

choice model and an analysis of power centralization.

American Sociological Review, 61(2), 308-332

Yeung, J.H.Y., Selen, W., Zhang, M., & Huo, B. (2009). The

effects of trust and coercive power on supplier

integration.Int. J. Production Economics, 120, 66-78

Weick, K.E. (1989). Organized improvisation: 20 years of

organizing. Communication Studies, 40(4), 241-248.

Williamson, O.E. (1976). A dynamic theory of interfirm

behavior. In W.M. Evan (Ed.), Inter-organizational Relation

(pp.27-43), Great Britain: Penguin Books Ltd.

Zeitz, G., (1980). Interorganizational dialectics.


55

Tables

Table 1

Three Matrices of StudyNo Matrix Item* Scale Cronbach

’s Alpha1 Frequency of

interactionWhat is the frequency of interaction between the following dyadic relations?

1=Almost never5=Very frequent

.859

2 Trust What is the degree of trust between following two organizations?

1=Very low5=Very high

.946

3 Power Which organization is more powerful in the dyadic relation?

1=Always A5=Always B

.879

56

Table 2Descriptive Statistics for Frequency of Interaction Matrix

Note. v1:focal

organization; v2: customers; v3: competitors; v4:suppliers/subcontractors, v5: banks & financial institutions, v6:public organizations, v7: chamber of commerce & associations, and v8:non-governmental organizations (NGOs) & universities

v1 v2 v3 v4 v5 v6 v7

v2Mean 4.394SD .7317

v3 Mean2.394

3.515

SD1.222

1.192

v4 Mean3.986

2.846

3.403

SD.9308

1.371

1.286

v5 Mean3.934

3.876

3.650

3.550

SD.8844

.9922

1.080

1.048

v6 Mean3.592

3.531

3.587

3.269

3.433

SD1.190

1.140

1.101

1.272

1.240

v7 Mean3.223

2.815

3.111

2.590

2.583

2.816

SD1.114

1.059

1.017

1.116

1.168

1.255

v8 Mean1.666

1.615

1.666

1.492

1.766

2.186

2.275

SD1.255

1.056

1.121

1.176

1.212

1.332

1.348

57

Table 3Descriptive Statistics for Trust Matrix

Note. v1:focal organization; v2: customers; v3: competitors; v4:suppliers/subcontractors, v5: banks & financial institutions, v6:public organizations, v7: chamber of commerce & associations, and v8:non-governmental organizations (NGOs) & universities

v1 v2 v3 v4 v5 v6 v7

v2Mean 4.48SD .702

v3 Mean 3.04 3.50SD 1.20 1.01

v4 Mean 4.02 3.75 3.68SD .937 .854 .911

v5 Mean 4.24 4.06 3.80 3.77SD .694 .765 .789 .756

v6 Mean 4.20 4.03 3.96 3.82 4.15SD .859 .836 .836 .993 .833

v7 Mean 4.00 3.72 3.67 3.50 3.81 3.77SD .810 .819 .824 .959 .887 .879

v8 Mean 3.73 3.60 3.55 3.28 3.67 3.75 3.75

SD 1.05 1.02 .976 1.13 .998 .978 .931

58

Table 4Descriptive Statistics for Power Matrix

A → B↓

v1 v2 v3 v4 v5 v6 v7

v2 Mean 3.054b

SD 1.259v3 Mean 2.794b 2.65

5b

SD .9712 1.163

v4 Mean 2.232a 2.101a

2.245a

SD 1.136 1.077

1.106

v5 Mean 2.739b 2.847b

2.898b

3.052b

SD 1.302 1.156

1.241

1.259

v6 Mean 3.902a 3.966a

3.915a

4.034a

3.796a

SD 1.268 1.206

1.249

1.184

1.270

v7 Mean 2.944b 2.916b

3.016b

3.189b

2.762b

2.491a

SD 1.033 .9964

1.008

.9992

1.022

1.194

v8 Mean 2.550a 2.694b

2.678b

2.706b

2.694b

2.288a

2.551b

SD 1.064 1.021

.9903

1.092

1.021

1.099

.9398

Note 1. v1: focal organization; v2: customers; v3: competitors; v4:suppliers/subcontractors, v5: banks & financial institutions, v6:public organizations, v7: chamber of commerce & associations, and v8:non-governmental organizations (NGOs) & universitiesNote 2. The data obtained from matrix is divided into threesubgroups based on the formula developed by Newbold etal.’s formula (2003, p.15) and then dyads under eachsubgroup are represented within three separate groups (a,b, and c). After finding width values (g), this value wasadded for each subgroup as seen in the following:

60

Table 5Degree Centrality Values for Frequency of Interaction and Trust Matrices

Frequency ofInteraction

Trust

Degree

NmrDegree

Share

Degree

NmrDegree

Share

v123,189

65,968

0,140

v1 27.727

77.260

0.130

v522,792

64,838

0,138

v6 27.714

77.224

0.130

v2 22,592

64,269

0,136

v5 27.519

76.680

0.129

v6 22,414

63,763

0,135

v2 27.167

75.699

0.128

v3 21,326

60,668

0,129

v7 26.232

73.094

0.123

v4 21,136

60,127

0,128

v4 25.837

71.993

0.121

v7 19,413

55,226

0,117

v8 25.353

70.645

0.119

v8 12,666

36,032

0,077

v3 25.227

70.294

0.119

Network Centralization = 10,83%

Network Centralization = 4.80%

Blau Heterogeneity = 12,81%Normalized (IQV) = 0,35%

Blau Heterogeneity = 12.52%Normalized (IQV) = 0.02%

Note 1. v1: focal organization; v2: customers; v3: competitors; v4:suppliers/subcontractors, v5: banks & financial institutions, v6:public organizations, v7: chamber of commerce & associations, and v8:non-governmental organizations (NGOs) & universitiesNote 2. For valued data, the normalized centrality may be larger than 100. The centralization statistic is divided by the maximum value in the input dataset.

61

Figures

Figure 1. The Weighted Digraph of Power Matrix

Note 1. v1: focal organization; v2: customers; v3: competitors; v4:suppliers/subcontractors, v5: banks & financial institutions, v6:public organizations, v7: chamber of commerce & associations, and v8:non-governmental organizations (NGOs) & universitiesNote 2. The direction of arrows shows the powerful side of each dyadic relation. Bold edges: w ≤ 2.55 and w ≥ 3.51 (highly inequal dyadic relations) / Thin edges: 2.55 < w < 3.00 and 4 = 3.00 < w < 3.51 (inequal relations)

v8

v2v1

v4 v6

v3

v7

v5

62

Figure 2. Centralities of Frequency of Interactions on Weighted Digraph of Power


21,13

22,59

21,32

22,44

22,79

23,18

19,41

12,66

v8

v2v1

v4 v6

v3

v7

v5

63

Figure 3. Centralities of Frequency of Interactions on Weighted Digraph of Power


25,83

27,16

25,22

27,71

27,51

27,72

26,23

25,35

v8

v2v1

v4 v6

v3

v7

v5

Analyzing Relational Sources of Power at the Interorganizational Communication System

Documents

Transcript of Analyzing Relational Sources of Power at the Interorganizational Communication System