Coalitions in Organizational Purchasing: an Application of Network Analysis

ABSTRACT - Coalitions are a little understood organizational phenomenon yet they may significantly affect purchasing decisions. This paper suggests that a network perspective would aid their investigation and proposes a model hypothesizing that coalition members' social ties affect the coalition's stock of resources and thus its strength and its ability to influence organizational buying decisions. Some of the tools of network analysis are suggested as a means to identify and analyze coalitions.


Julia M. Bristor (1988) ,"Coalitions in Organizational Purchasing: an Application of Network Analysis", in NA - Advances in Consumer Research Volume 15, eds. Micheal J. Houston, Provo, UT : Association for Consumer Research, Pages: 563-568.

Advances in Consumer Research Volume 15, 1988      Pages 563-568


Julia M. Bristor, The University of Western Ontario


Coalitions are a little understood organizational phenomenon yet they may significantly affect purchasing decisions. This paper suggests that a network perspective would aid their investigation and proposes a model hypothesizing that coalition members' social ties affect the coalition's stock of resources and thus its strength and its ability to influence organizational buying decisions. Some of the tools of network analysis are suggested as a means to identify and analyze coalitions.


Coalitions occur when individuals work in concert in order to achieve an objective such as to influence a decision and/or reduce the power of another participant (Anderson and Chambers 1985). Because complex organizational buying decisions are often characterized by conflict arising from differing values and objectives of the various decision participants (Anderson and Chambers 1984; Sheth 1973), coalition formation is thought to be a very prevalent conflict resolution strategy (Morris and Feldman 1984). Conversations with individuals involved in purchasing decisions, and observations of organizational purchasing suggest that coalitional activity may have a significant positive or negative effect on the process. Yet, aside from acknowledging their existence, and their likely strong effects on organizational buying (e.g. Anderson and Chambers 1985; Bagozzi 1978; Morris and Feldman 1984), theoretical and empirical knowledge about organizational coalitions is virtually nonexistent (Pfeffer 1981; Stevenson, Pearce and Porter 1985).

In large part, this problem is viewed as being directly attributable to the use of the individual level of analysis, which has been criticized elsewhere (Bonoma, Bagozzi and Zaltman 1978; Bristor 1987; Johnston 1981; Wilson 1985). The individual level of analysis is inappropriate because of the interpersonal interdependencies found in buying coalitions. Members act, not in isolation, but within the context of the larger social milieu of interpersonal relationships (Calder 1977; Johnston 1981) and thus, knowledge of buying outcomes requires more than knowledge of the decision participants as individuals (Bonoma 1982). Therefore, investigations of buying coalitions, and other organizational buying processes, would be better served by the adoption of the network level of analysis and the exploitation of the concepts and methods of social network analysis.

Toward this end, this paper develops a network based model of buying coalitions that can provide insight into issues such as the conditions under which coalitions are likely to form, their operating tactics, their effects on decision outcomes and the organization, and how coalitions might be identified. The paper is organized as follows. First, coalition activities are framed as political activities. Second, after considering the applicability of experimentally-based coalition theories, recent efforts in the organizational behavior and organization buying literatures are drawn upon to form a network-based model of purchasing coalitions. Finally, some measurement and analysis issues are addressed.


Although political activities have long been recognized as an element of organizational behavior (Burns and Stalker 1961), it is only recently that researchers have advocated that a political perspective on organizational processes be adopted (Pfeffer 1981). One of the distinguishing features of a political perspective is that it explicitly recognizes the various informal structures through which organizational members attempt to exert influence and accomplish their personal and departmental goals (Bacharach and Lawler 1980; Burns and Stalker 1961). One of these informal structures, the coalition, is likely to form in competitive situations where the distribution of power (actual or perceived) is such that one or more parties views him/herself as disadvantaged with respect to obtaining an outcome individually, but not necessarily when joining forces with others to pursue that outcome (Rubin and Brown 1975). Since organizational buying behavior is organizational behavior (Anderson and Chambers 1985; Barclay 1986), and involves lateral relationships (Strauss 1962), and non-task, as well as task, factors (Webster and Wind 1972), a political perspective is viewed as an appropriate vantage point from which to investigate organizational buying, including coalitions.

Coalition research is traditionally associated with the political science and social psychology literatures. This research typically forces coalition formation in newly formed three-person groups in controlled laboratory experiments. Issues typically revolve around which two members form the coalition and the payoff division. It generally assumes perfect information, objective and rational decision making, zero-sum outcomes, and known, divisible winnings (Stevenson, Pearce and Porter 1985). In contrast, those researching actual organizational coalitions are concerned with issues such as when and why coalitions form, what activities they engage in and how they affect organizational processes. They assume imperfect information, non-zero-sum outcomes, historical and expected future relationships, and subjective and cognitive decision making. Because of these differences, the analysis of organizational coalitions must begin to develop its own theory and empirical base (Pfeffer 1981). Towards this end, the next section outlines a network-based model of buying coalitions.


As previously advocated, this model is based on the notion that purchasing participants are embedded nonindependently in an interpersonal network of relationships through which influence, opinions, information and liking/disliking, etc. are transmitted. Thus, to understand coalitions, and other purchasing processes, participants must be studied in the context of their social network of relationships. The relationships themselves are key to the investigation because it is through their manipulation that individuals recruit and mobilize coalition members, and accomplish other goals (Boissevain 1974; Bristor 1987; Kapferer 1969).



A network can be defined as "A specific set of linkages among a defined set of persons, with the additional property that the characteristics of these linkages as a whole may be used to interpret the social behavior of the persons involved," (Mitchell 1969, pg. 2). Networks are easily represented as graphs consisting of points (people, groups, organizations or other social entities3 and lines (relationships), (Harary, Norman and Cartwright 1965). Graphing a network can provide important information about the members and their relationships. For example, in contrast to the assumption of face-to-face interactions made by many buying center researchers, a graph may show that two members are not directly connected (Bristor and Ryan 1987).

The model, which is illustrated in Figure 1 and discussed below, consists of a conflict sub-model and a coalition sub-model. Part of the model is merely a synthesis of the various antecedents and consequences of coalition formation that appear in the literature. However, it makes two unique contributions. First, it describes coalitions in terms of network characteristics. Second, its core hypothesis is that a coalition's ability to accomplish its goals is a function of its strength, as defined by its stock of social relationships and other resources contributed by its members.


Antecedents to conflict and conflict resolution modes have been discussed by several authors and can be categoried into three groups: organizational variables, decision process variables and individual variables. Some of these are briefly described below.

The division of labor and task specialization results in task and resource interdependencies (Pfeffer 1981). The fact that some tasks are more important than others, tends to lead to perceived and real discrepancies in the distribution of resources and power (Morris and Feldman 1984; Pfeffer 1981; Stevenson, Pearce and Porter 1985). These discrepancies, plus discommonalities in the reward system (Anderson and Chambers 1985; Morris and Feldman 1984; Sheth 1973) often lead to decision conflict. Decision process characteristics such as the number of participants, decision complexity, and the attendant time pressures also lead to conflict (Morris and Feldman 1984). Finally, individual characteristics such as risk orientation, bargaining experience, and attitudes toward winning and competition also affect conflict (Morris and Feldman 1984).

The resolution of conflict can assume many forms such as problem solving, persuasion, bargaining and 'politicking" (Sheth 1983; Strauss 1962). Although these are typically thought of as individual strategies, they also have group level analogs. Given a tendency for political conflict resolution strategies, coalitions are likely to form when individual action is viewed as insufficient and/or when participants know that others hold similar outcome preferences. For example, in a purchasing situation where conflict centered on disparate purchasing goals, lower level engineering and plant maintenance coalesced and recruited higher level members to oppose a purchasing agent's vendor selection (Bristor 1987). Individually, these lower level employees had no chance of overruling the purchasing agent. Collectively however, they were able to use their personal connections to garner the resources needed to do so.


In contrast to the experimental coalition research, non-winning coalitions do form in organizations (Pfeffer 1981). Thus the fact that decision participants perceive coalition formation as a resolution strategy is a necessary, but insufficient condition for an effective coalition. Two factors contribute toward a strong coalition. First is the network of social ties of individual members. Social ties are critical because they provide information about positions on purchasing issues and the distribution of power and resources. They provide the opportunity for shared perceptions to emerge and they facilitate the process of searching for allies (Pfeffer 1981; Stevenson, Pearce and Porter 1985). Ties therefore both lead to coalition formation, and they determine with whom they are formed (Morris and Feldman 1984). Second is whether some or all of the members have a history of previous coalitional activity. When there is a history, knowledge about ties and member resources can minimize the need to search for allies and to develop and coordinate tactics (Stevenson, Pearce and Porter 1985).

A coalition can be defined as a temporary alliance among some subset of the involved parties and as: "an interacting group of individuals, deliberately constructed, independent of the formal structure, lacking its own internal formal structure, consisting of mutually perceived membership, issue oriented, focused on a goal or goals external to the coalition and requiring concerted member action," (Stevenson, Pearce and Porter 1985 pg. 261). From the network perspective, this means that a coalition, as a subset of the complete network of decision participants, is a network itself wherein members work towards common goals. Therefore, similar to other networks, coalitions can be characterized and compared along a number of structural and interactional dimensions, some of which are described below (Bristor 1987).

In a purchasing situation involving coalitional activity, the strongest coalition is likely to determine the outcome. The concept of strength is related to the coalition's possession of resources such as people, information, expertise, authority, veto power, etc. (See Figure 2.) Since resources are controlled by people, coalition members' social ties determine their access and thus are key to building coalitional strength. Access is accounted for by several coalitional characteristics. First is coalition size. While the political science and social psychology literatures theorize that coalitions will form with the minimum number of members needed to win, this does not appear to be the case in real organizational settings where winning is not a zero sum proposition and where the outcomes are not necessarily a fixed amount of a scare resource to be allocated among members (Pfeffer 1981). Therefore, coalitions intent on achieving their goals will tend to err on the conservative side (i.e., larger numbers) to preclude a potential member being recruited by another coalition and to maximize their chances of success. Size alone, however, is insufficient. It also matters who the coalition is composed of since each person brings a personal network of relationships to the coalition. People in similar structural roles are likely to have more similar resources than people in very different structural roles which suggests a need for diversity among coalition members. Thus resource accessibility, and coalition strength can be maximized by including a broad lateral range and vertical range.

Two other dimensions of coalition strength involve the linkage patterns rather than the members. First, density is the ratio of the actual number of relationships in the coalition, to the total possible number. This is an indication of the connectedness of the coalition. Coalitions are likely to be densely connected because, when people share homogeneous views and when the communication content is favorable, there is more communication on a given matter (Katz and Lazarsfeld 1955). Thus, while not inviolable, there is a tendency for small group processes such as face-to-face interactions to occur between coalition members to facilitate the transmission and coordination of information, coalition action plans, etc. Second, span refers to the ratio of the number of relationships in the coalition, to the number of total linkages in the entire network. Similar to the argument made about size, to the extent that a network member is involved in coalition relationships, s/he is less available for relationships outside the coalition.

Finally, a dimension of coalitions that describes the nature of the relationships themselves is degree of multiplexity. It is an indication of the complexity of the relationship. If a relationship contains only one type of relation such as information exchange, it is referred to as uniplex, if it contains more than one type, such as information exchange, friendship and advice, it is referred to as multiplex. In the coalitional context, a relationship composed of current and past coalition activity would be multiplex and as discussed previously, would make for a stronger coalition because members would already have knowledge about others regarding values, contacts and other resources. Thus, to the extent that there is a high degree of multiplexity in terms of past coalition activity, the coalition should be able to organize and mobilize more quickly than one without any Previous history of coalition activity.



Because coalitions operate outside the formal, legitimate organizational structure, precisely how they attempt to recruit members and accomplish their objectives is not well documented. It is generally agreed that members explicitly agree to join forces and are often active in their efforts to recruit other members (e.g. Stevenson, Pearce and Porter 1985). Coalition members may engage in advocacy activities and use information and appeals to rationality and reason to generate support. If this is insufficient, coalitions may also attempt to gather support or cooperation through the use of friendships, allies, past or future favors, and/or other forms of social indebtedness (Strauss 1962). Active gatekeeping and information manipulation and control are also coalitional tactics (Morris and Feldman 1984). For example, Thurman (1978/79) observed the use of rumor, criticism, withdrawal of support and denial of access to power by a levelling coalition (a coalition formed to destroy another person's power). In addition, Bristor (1987) observed a coalition that intentionally inflated financial estimates to support their preference and refused to meet with the vendor that the purchasing agent was advocating. Finally, Morris and Feldman (1984) also note that coalitions can set up "road blocks" that prolong the decision process.

Another coalition issue that has received little attention concerns the short and long term effects of coalitions. As previously suggested, coalitions may have a history and thus are dynamic over time. This implies that some coalitions may have very strong, but subtle effects on the organization, and in fact, may reduce organizational effectiveness (Bums and Stalker 1961). Thus, although the immediate goal is usually purchasing influence. coalitions can also effect the attitudes and behavior of organization members, spawn the formation of other coalitions, and can effect the organization itself by reallocating resources, imposing systems to control coalition behaviors, coopting coalition activities into the mainstream and legitimating coalitions into the formal organizational structure (Stevenson, Pearce and Porter 1985).


One of the most difficult challenges facing organizational buying researchers in general and coalition researchers in particular is data collection and analysis. The network level of analysis argues against the collection of data from one or two key informants as is typical in organizational buying research. This is .X&cause of the earlier mentioned fact that two network members may not be directly connected. This implies that if they are distant (i.e. separated by many other members), they would not be able, and should not be expected, to give reliable reports about the other, in terms of activity, influence, etc. since they cannot "see' what goes on in parts of the network in which they are not embedded. Therefore, a reliable picture of the buying network and its members and activities requires a census of buying participants and provides the first step necessary for coalition identification.

The buying network can be constructed by snowball sampling procedures (cf. Moriarty and Bateson 1982) whereby the researcher begins with one or more names of known decision participants. Each of the named participants is asked to list other decision participants. The process continues until there are no new names. Sociometric data describing who talked to whom, and/or tried to influence whom, and/or was influenced by whom, etc., and other attitudinal, preference and demographic data is then collected from each participant. Once the buying network members have been identified, numerous network analysis techniques are available to characterize and describe the buying network and individuals' personal networks along dimensions such as those in the buying coalition model or to investigate other issues (Bristor 1987). Network analysis is a loose grouping of techniques capable of analyzing relational data, the specifics of which are beyond the scope of this discussion. (The interested reader should refer to Knoke and Kuklinski (1982) and Rogers and Kincaid (1981) for excellent discussions.)

Of relevance to this discussion is the fact that there are numerous techniques capable of detecting cliques, or dense areas, in larger networks. Thus, they can be used to empirically detect the presence of coalitions in a manner that is less intrusive and less sensitive to respondent bias, than direct inquiry. One promising technique is Siedman and Foster's (1978a and 1978b) k-plex method of clique identification which is included in MacEvoy and Freeman's (1987) UCINET network analysis package. The method is based on the notion of a maximal complete subgraph, which is the largest possible set of points on a graph where each point is connected to every other (Harary, Norman and Cartwright 1965). (See Reingen et al (1984) for a recent application.) In other words, in a clique, everyone is connected to everyone else, whereas in the complete buying network, density, or connectedness, appears to be much lower (Bristor 1987). In some cases, this completeness requirement may be restrictive and thus it can be relaxed such that each of the n points need only be connected to n-k others (Reingen et al 1984). Thus, following the process outlined above, the k-plex method could be used to identify coalitions in the organizational buying context. Additional attitudinal and behavioral data can also be used to validate a coalition's existence and to learn more about its activities.

Network analysis is not a panacea and many issues are yet to be resolved, as illustrated by Rogers' (1987) recent comments. However, the application of network concepts and analytic techniques did provide important insight into influence processes in organizational buying decisions (Bristor 1987). Thus, it is felt that their judicious application would also benefit the investigation of organizational buying coalitions.


Coalitions are a little understood organizational phenomena. Their investigation presents a challenge because of the lack of theoretical and empirical results, and because of methodological problems such as the sensitive nature of coalition activities, the fact that they are difficult to identify, and the time and effort required for sociometric data collection. This paper suggests that the adoption of a network perspective and the tools of network analysis could lead to theoretical and methodological progress.


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Julia M. Bristor, The University of Western Ontario


NA - Advances in Consumer Research Volume 15 | 1988

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