CODING NATURALISTIC NEGOTIATION INTERACTION

Human Communication Research Vol. 10, No. 3, Spring 1984, 403-425

CODING NATURALISTIC NEGOTIATION I NTE RACTlO N

WILLIAM A. DONOHUE Michigan State University

MARY E. DIE2 Alverno College

MARK HAMILTON Michigan State University

While much rrcent btwk / i m ottrnipted to code nrgotiotiori interaction to identify h o ~ . individrrtils iisr cornmuniccrtion tactics in negotiation srttings. many coding schrmrs h u i v hren developed to unulyze simulotcd activities and mcry not be trppropriute for thr unulysis of formal, profrssioncrl negotio- tion rt'etits. Moreovrr, most codinfi rrsenrch has failed to focus on the rrla- tionships hetnven indiiidiru/ trrctics und Itrrgrr coinmrinicrrtiori strutegirs. This trrticle proposrs 11 coding mechanism .sensitiize to formul. nuturully occurring c~~mmuniccrtion in nrgotiution settings nnd cnpcrblr of identifying strntrgic iisr of individirul ttictics. The coding scheme is then npplied to .simrdtrtrd and nuturcrlistic negotirrtion interaction und the resrtlting dutu urr ussessed, using lug seqrrrntinl unalysis. Significtrnt dvferencrs are rrjlrcted hetllvrn the noturcilistic and simirlnted intrructions and strong puttrrns of communictition strotegy urr identified.

The negotiation process continues to attract attention across several disciplines, most of which has been focused on the factors impacting negotiation outcome (Bacharach & Lawler, 1981; Chertkoff & Esser, 1976; Druckman, 1977; Putnam & Jones, 1982a; Zartman, 1978). While explaining outcome has been accomplished under a number of

Willium A . Donohue (Ph. D. . Ohio State University) is an associate professor of communication at Michigan State University. M u ~ y E. Dirz (Ph. D. , Michigan State University) is an assistant professor of professional communication at Alverno College. Murk Humilfon is a Ph.D. candidate in the Department of Communication at Michigan State University.

0 1984 International Communication Assn

403

404 HUMAN COMMUNICATION RESEARCH / Spring 1984

approaches including personality traits, economics, game theory, and concessiodconvergence (Zartman, 1978) recent reseach has begun coding negotiation interaction to identify how individuals use communication tactics to create more cooperative or competitive negotiation contexts (Putnam & Jones, 1982b). However, these coding schemes were developed to analyze primarily simulated negotiation activities that may differ substantially from professionally organized, formal negotiation events. In addition, the research using coding schemes to analyze communication interaction has not generally focused on how individual tactics can be assessed as part of a larger communication strategy that each negotiator is attempting to imple- ment.

Given these gaps in the research, the purpose of this article is to build upon prior negotiation coding schemes to develop a coding mechanism that will be more sensitive to formal, naturally occuring bargaining communication behavior and be capable of locating the kinds of strategies and tactics that negotiators pursue most frequently. To accomplish this objective this articlewill begin by reviewing recent research in coding negotiation interaction to determine its viability in coding naturalistic communication in order to learn how strategies develop in negotiation interaction.

CODING NATURALISTIC NEGOTIATION INTERACTION

Currently, three systems for coding negotiation interaction continue to be refined in programmatic research efforts. Putman and Jones (1982a) provide an excellent review and critique of two of these category schemes, the Conference Process Analysis (CPA), used in Morley and Stevenson (1977), and the Bargaining Process Analysis I 1 (BPAII), which was developed by Hopmann and Walcott (1975) and used in Putnam and Jones (1982b). Putnam and Jones (1982a) indicate that these category systems appear capable of detecting differences in the ways in which bargainers develop more cooperative or more competitive negotiation environments. In addition, they seem to cover a broad range of behaviors that are likely to influence the outcome of the negotiation activity.

However, a more in-depth analysis of these two category schemes indicates that they have two primary conceptual limitations in providing insights about how communication functions in negotiation interaction The first problem is that these coding schemes are not conceptually sensitive to the way in which communication functions

Donohue et al. / NATURALISTIC NEGOTIATION 405

as a process. We know from the research dealing with relational control (e.g., Reusch & Bateson, 1951) that communication has not only a content dimension but a relational dimension that takes account of how messages are connected to one another. In addition, Ellis, Hamilton, and Aho’s (1983) research on conversational coherence indicates that accounts of communication processes must address the problem of how strings of utterances are heard in some coherent fashion as being connected to one another.

Neither the BPAII nor the CPA attempt to account for the “connectedness” of negotiation interaction. Neither provides any information about how each utterance attempts to deal simultaneously with the prior utterance and with the subsequent utterance. Such information is important. however, because any given utterance per- forms two functions: I t responds to the prior utterance, and structures the subsequent utterance. As indicated in Donohue’s (1981) research, being able to respond to the prior utterance and structure the opponent’s next utterance is an important negotiation skill. Thus, for a coding scheme to be most capable of detecting how communication works in negotiation it should be able to deal conceptually with the connectedness of utterances.

The second conceptual limitation of the BPAII and the CPA is that they are not particularly flexible in their ability to detect the manner in which the use of specific communication tactics reflects some larger communication strategy. To model how communication structures negotiation requires the ability of a coding mechanism to distinguish communication tactics and strategies. Schelling (1960) discusses strategy as a series of moves that a negotiator might pursue, identifying tactics as the specific moves themselves. Zartman (1978) makes a similar distinction between stategies and tactics.

Perhaps the best set ofdistinctions is offered by Putnam and Jones (1982a, 1982b). They argue that outcomes are structured by strategies that represent the program, or series of bargaining tactics intended to accomplish long-term objectives. Tactics are the individual com- municative behaviors intented to accomplish short-term objectives. The issue is to what extent the BPAII and the CPA can translate tactics into strategies by indentifying the specific long-term objective that can be used to organize the tactics into strategies.

The BPAII seems to have the most potential of translating tactics into strategies. This scheme (as reported in Putman &Jones, 1982b) organizes the 25 categories into six major groupings that appear to overlap a great deal. To resolve the overlap problem Putman and Jones factor-analyzed these tactics into three groups that they termed


“offensive,” and “integrative” strategies. Using the loadings to define the underlying conceptual organization proved tenuous for their study because several tactics loaded on two factors, making it difficult to identify the underlying strategic goal of the tactic. For example, “provides information” was the most frequently used category and it loaded on both the defensive and offensive strategy dimensions. While it is clearly reasonable that this tactic could have two kinds of strategic value, such overlap does make it difficult to define strategies retrospectively. It is probably more desirable to design a category scheme that conceptualizes each tactic a priori as having offensive, defensive, or integrative strategic value, and then test the extent to which each tactic works in the predicted manner.

A third category system developed by Donohue (1981) does appear prepared to address the two conceptual requirements of defining communication strategies a priori and of being sensitive to the communication process. To deal with the first requirment, the category scheme codes each utterance twice: as a response to the prior utterance, and as a cue or attempt to structure the subsequent utterance. In this way the coding scheme is able to manage the conceptual problem of how utterances are related to one another sequentially. This is a real advantage, particularly when “process” methodologies such as lag sequential analyses are used to make sense out of sequences of utterance exchanges (Putnam & Jones, 1982b).

The Donohue (1981) category scheme deals with the second problem of identifying communication strategies because the specific tactics are organized by strategies similar in nature to the ones dis- covered in the Putnam and Jones (1982b) research. The three strategies include attacking, defending, and regressing moves. The attacking tactics are intended to take the offensive by proposing descrediting modifications in the opponent’s position or proposing changes in the negotiator’s own position to undermine the opponent’s level of aspiration. The defensive tactics are used to stabilize the negotiator’s expected outcomes by either rejecting whatever modifications have been proposed by the opponent or bolstering one’s own position without specific reference to the opponent’s position. Regressing tactics accept the opponent’s modification of the negotiator’s position, and reveal weakness and/or lack of confidence in the negotiator’s own position.

These regressing tactics are similar to the integrative tactics proposed by Putnam and Jones (1982b). The labeling difference stems from the difference in focus of the two studies. Putnam and Jones made the argument that naturalistic negotiations are both distributive


and integrative in nature, and that the strategies coded by the re- searchers ought to reflect that orientation. The Donohue scheme, on the other hand, was intended to deal only with distributive bargaining situations. It is probably more appropriate to endorse the Putnam and Jones position, in light of Pruitt’s (1981) argument that integrative bargaining is common in various stages of bargaining, particularly in subsequent stages of negotiation when the bargainers need to encour- age more cooperation to settle.

While the Donohue (1981) coding scheme does fulfill important conceptual requirements, it is not as comprehensive as the BPAII. In particular, categories need to be upgraded to be more sensitive to behaviors that occur in naturalistic bargaining situations. A review of current negotiation research suggests that there are three dimensions of naturalistic bargaining behavior, not discussed in the previous Donohue research, that need to be integrated into an upgraded coding scheme. The first areas that seemed prevalent in the research related to the process of infornzrrtion mnnagament. Bargaining in natural settings requires extensive information management due to the complex features often present in the large numbers of proposals discussed among participants. For example, in Lieberman’s (1979) discussion of the interaction between teachers and the school board, he suggests that it is appropriate for the school board to get the union to explain the reason for each provision to pin down their meaning and assign priorities to their demands. Lieberman argues further that extending the topics through questioning may be the most important part of the negotiation because it pinpoints what the real issues are and helps set up the various trade-offs that will be necessary to reach agreement later on.

In addition to extending the interaction through questions it is often productive to structure the flow ofthe discussion toget the other team away from its initial proposal and focus the issues on the speaker’s counterproposal. This issue focusing and counterproposal promotion process can be particularly useful in the writing of the agreement so that the language that is ultimately accepted will be clear and acceptable to both parties. Thus, Lieberman places a great emphasis on structuring the negotiation so that the other side must choose one of the final alternatives by the side structuring the interaction.

The second dimension of behavior that seems relevant in naturalistic negotiation sessions is concessioning. While offer concessions were included in prior research, there appear to be other kinds of concessions, communicating different messages that might


influence the outcome of a negotiation. As indicated in Putnam and Jones (1982b) and in Pruitt (1981) certain kinds of concessions can communicate cooperativeness, such as proposing flexibility on issues. According to Lieberman (1979) it is often appropriate to show flexibility on minor items to get the ball rolling and present an air of reasonableness in the negotiations. I t should be made clear that the flexibility has its boundaries, particularly in the case of significant issues that are less open to concession. This concept is consistent with Barto's (1978) summary of research in bargaining, which demon- strated that a moderately tough strategy (one that avoids being un- cooperative) increases the chances for formulating a settlement. Bacharach and Lawler (1981) also agree that conciliatory gestures early in the negotiation will prevent a deadlock while inducing the greatest yield from the opponent.

However, giving concessions in response to excessive toughness is tantamount to accepting an inferior status and conveying a willing- ness to demean oneself, which could produce a loss of face (Bacharach & Lawler, 1981; Brown, 1977). One of the nonproposal ways of yielding to toughness is to respond to a request for a piece of information that should be provided, by not providing that information. This could result in a lack of face for a team, particularly if the information could support some important dimension of the team's position.

The third dimension along which bargaining strategies can be organized in natural settings is positioning. Positioning may be defined as the act of focusing the content of the issues on those aspects most advantageous to the negotiator. Fisher and Ury (1981) argue that various forms of blocking can be an effective means of positioning the issues in favor of the party using the blocking tactics. For example, one blocking means that can be used is denying the relevance of a particular utterance to the issue at hand, particularly if it is critical to the user's case. The net effect of this may be to move the discussion away from that point and position it on some potentially less damag- ing issue. Another blocking tactic these authors discuss is the act of denying fault or culpability, placed in the context of personal comment about the other. This tactic can be used as a means of taking the focus off the issue and placing it on a more personal level such as the integrity of the opponent or the amount of trust that the other is showing in the negotiation. I t may or may not be a high risk tactic depending upon the way in which the personal comment is directed.

The last positioning move is particularly relevant in contexts (like the teacher-school board negotiations) in which each group maintains


some formally defined set of bargaining rights. Terms must periodi- cally reaffirm their rights, particularly when moves presented from the other side might jeopardize those rights (Lieberman, 1979; Zartman, 1978). Making these assertions functionally limits the flexibility of the other and repositions the argument back in the direction desired by the side asserting the rights. At worst, the assertion of rights removes the discussion from the issue of substance to the issue of rights.

Given these dimensions it is possible to specify a coding scheme that builds upon the prior Donohue (1981) research while attempting to reach some of the breadth apparent in the BPAII coding system. The category system offered here uses the same organizing principles as the Donohue (1981) system except that the “regressing” tactics are reconceptualized as “integrative” tactics to be more consistent with the Putnam and Jones (1982b) findings and to be more consistent with the tendencies in naturalistic bargaining to use both distributive and integrative tactics at various points in the negotiation. The following set of categories should be useful in tapping communication strategies in negotiation interaction.

The question to be addresed is how the coding scheme can be validated using more naturalistic data. Two validation criteria seem relevant at this point. The first is that the category system ought to be able to detect patterns of strategy use among labor-management groups that are consistent with prior research. The works by Putnam and Jones (1982b) are particularly useful here. Putnam and Jones found that labor bargainers specialized in offensive affronts while management took the defensive. More specifically, when management initiated a defensive strategy, labor consistently responded with offensive maneuvers in an apparent attack-defend pattern. Or, alter- natively, interaction tended to follow more of an action-reaction cycle with offensive strategies being countered with more integrative strategies. The Morley and Stephenson research tends to support these patterns as well. The categories offered in this article ought to be able to detect similar patterns.

The second validation criterion that the category system should meet is that it ought to be able to discriminate between naturalistic negotiation interactions and simulated interactions. Interaction patterns in these two contexts ought to be different for several reasons. First, attacking tactics in the simulation sessions are likely to be used less frequently than in the naturalistic bargaining sessions as the participants in the simulations are not personally bound by the outcome. In addition, the simulation bargainers are not accountable to


TABLE 1

Cue-Response Negotiation Coding System

Number Category Name Category Definition

Responding Tactics: A t tac kina

1.1 Deny fault w i t h personal rejection

1.2 Topic change

1.3 Assert rightdneeds

1.4

1.5

1.6

1.7

1.8

1.9

2.0

-

Responding Tactics: Defending

Reject proposal

Reject rationale/ utterance

Extension

Responding Tactics: Integrating

Proposal other support

Rationale/utterance other support

Extension question

Et cetera

Challenging, disagreeing, o r rejecting the immediately preceding utterance accom- panied w i t h a rationale and personal affront.

In t roduct ion o f a new idea changing the direct ion o f the interaction.

Statement that addresses requirements/ expectations consistent with prior subject area, clearly arguing for compliance.

Challenging, disagreeing o r rejecting any part o f the other's proposal.

Challenging, disagreeing o r rejecting the immediately preceding utterance that i s n o t related t o the proposal per se.

Extending o r continuing the top ic in the immediately preceding utterance.

Giving agreement, assistance, acceptance o r approval t o any part o f the other's o f fer o r proposal.

Giving agreement, assistance, acceptance o r approval t o the immediately preceding utterance that is not related t o the proposal, per se.

A n extension o f the pr ior utterance's topic phrased in the interrogative form.

A n y response not conforming t o these category types.

(continued)

Donohue et al. / NATURALISTIC NEGOTIATION 41 1

TABLE 1 (Continued)

Number Category Name Ca tegory Definition

2.1

2.2

2.3

2.4

2.5

2.6

2.7

2.8

2.9

3.0

Cueing Tactics: Attacking

Assert proposal/offer

Change fault/responsibility

Decision

Cueing Tactics: Defending

Substantiation

Clarification request

Deny relevance

Cueing Tactics: Integrating

Offer concession

Information concession

Conciliation/flexibility

Etcetera

Asking the other to accept specific modifications in the proposal under discussion.

Attributing lack of good faith, incom- petence, negligence; derogating something about the other.

Positive structuring of the procedures for discussion.

Providing information or evidence supporting the speaker’s own position.

Asking for additional information.

Reject suggested structuring of the procedures suggested and/or assert the relevance of the issue/information raised by the other.

An offer that i s less than the speaker‘s immediately prior offer.

Offering less information than is requested.

Proposing flexibility in the speaker’s position.

Any cue not conforming to these category specifications.

constituents in the way in which the naturalistic bargainers are accountable. Second, most naturalistic labor-management negotiations are restricted by rather rigid conventions about who presents the proposals and how they are evaluated. In the naturalistic negotiation sessions the union is likely to make most of the demands while management responds to these demands. There is traditionally little flexibility in this pattern whereas in the simulation negotiations the bargainers can be more flexible with respect to seeking the opponent’s goals.


Given these validation criteria the following hypotheses will be used to test the ability of coding system to detect tactic and strategy differences in the two negotiation contexts.

H I : Both bargaining groups in the naturalistic context will use more attacking and fewer integrating cueing and responding tactics than will both bargaining groups in the simulated context.

H2: The union bargainers will use more attacking and fewer integrating cueing and responding tactics than will management bargainers in both negotiation contexts.

H3: The union bargainers will use a n attacking strategy in response to management’s attacking cues in both negotiation contexts.

H4: The management bargainers will use an integrative strategy in response to union attacking cues in both negotiation contexts.

METHODS

For this study two types of bargaining interactions will be compared. One type consists of 24 bargaining sessions of private-sector, labor-management negotiations, lasting on the average of two and one-half hours, ranging from ten minutes to four hours. The early sessions consisted of proposal presentation and evaluation, while the subsequent sections consisted largely of bargaining and concession making for these proposals. The bargaining sessions from the naturalistic interaction did not end with an agreement; they were terminated before the final agreements were negotiated to maintain the privacy of the bargaining activities. However, no more than 3 to 5 sessions beyond the 24 were necessary to reach an agreement. The bargaining content consisted of contract negotiations for a major communications company in the United States. Issues were focused largely on wages and working conditions. The bargaining agents for both sides had negotiated at least two or three prior agreements in one another’s presence, and they were professional bargaining agents for the union and the corporation with many years of experience. There were no sunshine laws in the state that mandated public bargaining sessions. Each of the sessions was held in private. Both sides were under some pressure to settle because the contract was due to expire several months after these bargaining sessions were initiated. How- ever, if no immediate settlement was achieved, a strike was not automatic because the union wanted to keep on working.

Two simulation interactions will be used as a comparison of the naturalistic interactions. These simulations were training sessions


conducted by the Michigan Education Association as an in-service, yearly training session for their regular, professional bargaining staff. Each session consisted of a two-day bargaining marathon to reach agreement on a contract dispute that was actually negotiated in a different state. As a result, the bargaining parameters were quite realistic. Both sides of the case (management and union) were negotiated by union people role playing their respective sides, five mem- bers on a side. These two negotiations produced I5 bargaining rounds of between two to four hours each. The first simulation produced 7 bargaining sessions and the dispute was settled. The second simulation produced 8 bargaining sessions. and the dispute was not settled before the deadline.

DATA

The combined simulation and naturalistic data sets produced 3016 utterances. An utterance was defined as an uninterrupted talking turn. As it is frequently the case that utterances in negotiation will be quite lengthy and that more than one response and cue tactic will be used at a time, these longer utterances were divided into separate units, with a unit being defined by a change in function. Technically, one utterance could have several different responses and cues. How- ever, what generally happened is that the nature of the cue changes and the response remained largely the same througout one utterance.

The problem of multiple-coded utterances also appeared in the Putnam and Jones (1982b) study. The issue is which coded behavior to focus upon in the analysis. They solved the problem by using the last function in a given negotiator’s talking turn. They slected the last behavior in a given turn because of Gottman’s (1979) view that the intent of an argument frequently emerges at the end of a contribution. For the data in this study, the problem had one more level of complex- ity because each talking turn was coded twice-once as a response to the prior utterance, and once as a cue to the subsequent utterance. To solve this problem we used the first response coded in a given talking turn, and the last cue in that same turn. Consistent with the Putnam and Jones research. it seems reasonable that the most intention- revealing response would be the first one given, and the most intention-revealing cue would be the last one given in a talking turn. This procedure reduced the data set from 3296 responses and 3456 cues to the 3016 responses and 3016 cues that were ultimately used in this analysis.

Using Guetzkow’s (1950) formula, unitizing reliability for the multiple-coded utterances was .05. which Guetzkow points out is an


acceptable score in the measurement of the disugreernenr among coders. Using his categorizing reliability formula, the four coders trained to work with the transcripts achieved reliabilities of .92 for the response codes and .82 for the cue codes. Both are acceptable levels.

DATA ANALYSIS

Several problems are generally encountered when analyzing frequency data of multiple interaction sessions in which participants are free to talk as long as they like. The first problem is the wide variation in session length (ten minutes to eight hours) and the corresponding differences in utterances per session. To compensate for this problem percentages for each of the 20 categories were computed by summing the frequency of each category across each session and then dividing this frequency by the total number of utterances in the session.

A total of 26 variables were used in the analysis. Of these. 20 variable were the “tactic” indicators (ten responses and ten cue categories) and 6 were the “strategy” indicators (three repsonses and three cue categories). The strategy variable were created by summing the percentages across the relevant tactic variables.

The second problem encountered in analyzing the data for this study was determining whether the two simulations could be col- lapsed into one data set and compared to the naturalistic sessions. To perform this test the mean percentage tactic use on all 26 variables was compared between the utterances generated by management and labor in both simulations. To address this question, 52 T-tests (13 df) were generated; only two were significant, indicating that the simulation data could be pooled and cornpared to the naturalistic data.

The third problem associated with data analysis was how to detect strategy use - that is, how to determine the sequence of tactics both labor and management groups used over time. To solve this problem lag sequential analysis was used (Sackett, 1977). (For a detailed analysis of the lag sequential technique applied to negotiation research, see Putnam, 1981, and Putnam and Jones, 1982b). The lags in this article were calculated by selecting a criterion event and then counting the sequential steps of behaviors following this event. Lag 1 is the immediately following behavior; lag 2 is the second behavior after the criterion; lag 3 is the third step following the criterion, and so on.

For this research calculating and interpreting the lags was somewhat problematic given the cue-response double coding of each utterance. This problem was solved by establishing cues given by

Oonohue et al. / NATURALISTIC NEGOTIATION 415

C r i t e r i o n B e h a v i o r Labor A t t a c k Cue 1 2 3 4 5 6

Manaq. Labor Manaq. Labor Manag. Lahor R C R C R C R C R C R C

Figure 1: Lag Sequential Analytical Procedure

either side as the criterion behavior. Next, the cues and responses were separated and lagged individually against the criterion cues. The separate analyses were then combined to present an accurate picture of how the cue and response behaviors worked in relation to one another. For example, management’s response (to the union’s cue) and management’s cue constituted the first lag. The analysis went out to six lags to present a fairly detailed view of the chain of events set off by the cueing behaviors. This arrangement produced the sample config- uration shown in Figure 1 .

The data for these analyses consisted of the six strategy variables (attack, defend, and integrate for both cue and response) to facilitate the detection of interpretation of patterns. A z score set at f. 1.96, p < .05 confidence interval was used to test the difference between observed and expected probabilities and to identify criterion-behavior lag sequences that would occur more than was predicted by chance alone.

The criterion behavior used to detect strategic patterns of tactical use was the attack cue. This behavior was selected because it was felt that the act of attacking would be most capable of “forcing” the other side to set some strategic behavior in motion to confront this threat. Thus, if strategies are apparent they ought to be most detectable in response to the attacking cue.

R ES U LTS

Tables 2 and 3 contain the cell means and F ratios for the cue and response tactics that will be useful for testing the first two hypotheses. The first two hypotheses predicted that the union bargainers would use more attacking tactics, particularly in the naturalistic settings, and the management bargainers would use more integrating tactics, particularly in the simulation context. The data for the attacking


tactics in Tables 2 and 3 appear to confirm these predictions for the most part.

In each of the cueing and responding tactics either labor used them more frequently than management or more attacks were used in the naturalistic as opposed to the simulation sessions. In two of the six attacking tactics (assert proposal and decision) there was a significant interaction that produced somewhat mixed results. In the “assert proposal” cue the union presented more proposals in the naturalistic setting. while management presented more in the simulation setting. For the decision cue tactic the union side in the simulation context seemed more eager to structure decision processes in the simulations than in the naturalistic setting, perhaps because of the more ambigu- ous procedural parameters in the simulation.

The patterns for the integrating tactics are less clear for two reasons. First, only three forms of integration (excluding the et cetera code) were used to any significant degree: the utterance-support and extension question responses, and the flexibility cue. The utterance- support cue data support the hypotheses as management used more extension-question cues than labor in the naturalistic setting; however, the union used more extension questions in the simulation setting. Finally, much more flexibility was displayed in the simulation settings than in the naturalistic context, providing further support for Hypothesis 1.

The defending behaviors, particularly with respect to how labor and management chose to respond to one another, revealed fewer group differences but rather extensive contextual differences. The more assertive means of responding (reject proposal, reject rationale) were more characteristic of naturalistic settings while the extension response was used more in the simulation sessions, which seems consistent with the use of integration tactics in the simulation settings.

The defending cues, on the other hand, revealed both group and contextual differences. Management used more clarification requests, particularly in the naturalistic setting, which may be expected since the uilion was making most of the proposals. However, the significant interaction in this category suggests that the context tended to mediate the extent to which these requests were forwarded. Finally, more substantiation was present in the naturalistic setting, regardless of group affiliation, perhaps because the proposals were more comprehensive requiring more support and because the proposals may have been under more attack in the naturalistic settings.


TABLE 2

Cell Means and F Ratios for Cueing Tactics

F Ratios (df = 1, 77)

Group Main Effects Interaction

Category Labor Manage Group eta Context eta eta

Cue attack

Assert proposal Naturalistic Simulation

Charge fault Naturalistic Simulation

Decision Naturalistic Simulation

Cue defend Substantiation Naturalistic Simulation

Clarification request Naturalistic Simulation

Deny relevance Naturalistic Simulation

Cue integrate Offer concession

Naturalistic Simulation

Info. concession Naturalistic Simulation

Flexibility Naturalistic Simulation

Etcetera Naturalistic Simulation

.15(.10)' .07(.10)

.05(.06) .09(.08)

.08(. 10) .08( .04)

.18(.11) .08(.06)

.35(.09) .36(.111

.25(.17) .26(.11)

.11(.07) .24(.13)

.24(.19) .22(.14i

.01(.02) .03(.04)

.01(.01) .01(.02)

.01(.03) .021.03)

.02(.05) .02(.06)

.00(.01) .01(.03)

.01(.02) .01(.02'

.01(.02) .03(.03)

.04(.06) .05(.05'

.04(.04) .02(.04)

.1 1(.09) .15(.07l

2.72 .17 3.74 .21 8.62' .31 power X .34 power =Z .45

3.95' .20 13.21' .37 3.05 .18 Dower .37

3.28 .19 6.55' .27 5.88' .25 power .40

,192 .05 12.82' .38 .032 .OO power .07 power % .OO

4.57' .23 3.09 .19 5.79' .25 power .40

4.40' .23 4.40' .23 .477 .OO power % .OO

.534 .OO 1.05 .10 .452 .OO power % .OO power % .14 power z .OO

2.05 .16 1.12 .12 ,668 .OO power =Z .31 power X .19 pswer .OO

1.82 .15 8.02' .13 .15 .OO power % .48 power .OO

.343 .05 49.52' .62 4.41' .24 power .07

*F=p< .05 . 1. Standard deviations in parentheses.


TABLE 3 Cell Means and F Ratios for Response Tactics

F' Ratios ldf= 7, 771



Resp attack Deny fault Naturalistic Simulation

Topic change Naturalistic Simulation

Assert rights Naturalistic Simulation

Reso. defend Reject proposal Naturalistic Simulation

Reject Rationale Naturalistic Simulation

Extension Naturalistic Simulation

Resp integrate Proposal support Naturalistic Simulation

Utterance suppofl Naturalistic Simulation

Extension question Naturalistic Simulation

Etcetera Naturalistic Simulation

.08( .0711 .09(.07)

.01 (.03) .051.07)

.15(.10) .07(.09)

.04( .05) .03 I .06)

.04(.05) .01(.02)

.02 (.05) .02 (.03)

.04(.07) .07 (.69)

.03(.07) .04( .05)

.20(.09) .19(.12)

.11(.07) .08!.07)

.30(.13) .25(.13)

.38(. 19) .39(. 1 81

.01(.02) .02(.04)

.01(.03) .02(.06)

.02(.04) .01 (.02)

.05(.08) .03(.03)

1.91 .15 12.23' .37 .37 .07 power z .43 power % .09

8.12" .29 13.08* .36 2.99 .17 power X .34

4.23' .23 .21 .05 1.13 .13 power % .07 power .22

1.24 .13 1.80 .15 .61 .08 power .22 power .28 power z .10

.55 .08 21.02' .47 .23 .04 power % .10 power % .05

.43 .07 9.32' .33 .64 .08 power % .08 power X .I0

,006 .14 1.38 .04 .l l .OO power % .25 power .01 power .oo

7.46" .27 20.49" .45 1.25 .10 power .14

1.97 .16 2.19 .16 7.06* .28 power % .28 power z .31

3.57 .23 4.29' .23 .50 .07 power .45 power X .08

~

*F = P < .05. 1 . Standard deviations in parentheses.


Table 4 tends to confirm the general frequency patterns discussed with respect to Tables 2 and 3. Specifically the significant interactions in both attack modes indicate that labor was doing most of the attacking, particularly in the naturalistic settings, with the cueing behavior carrying most of that burden. The significant interaction for the integration responses indicates that management was doing the integrating, particularly in the simulation sessions - a finding consistent with Putnam and Jones (1982b). The significant main effect for context in the integration cueing strategy supports the finding that simulations may contain more integration behavior than do naturalistic settings. The only significant finding for the defending behaviors occurred in the cueing form and supported the previous interpretation that labor-management tendencies to support their claims may be context dependent with more defending behavior apparent in the naturalistic sessions.

Tables 5 and 6 are intended to test hypotheses three and four, forwarding the prediction that the labor group would pursue an attacking strategy in response to management attacks, and that management would pursue a more integrating strategy in response to labor attacks.

Table 5 reveals that in the naturalistic negotiation setting the strategy hypotheses were confirmed. For example, management responds to labor attacks with integrating responses and defending cues, which are then answered by more attacking responses and cues by labor. This pattern is identical regardless of which group initiates an attack. Management chooses to select an integrate-defend, response-cue strategy to deal with the union attack-attack strategy. This finding is reasonably consistent with the Putman and Jones (1982b) finding with the exception that management was much more integrative in response to labor but defensive in the cueing behavior. Perhaps if Putman and Jones had coded responses and cues their findings would be consistent with those reported here.

Table 6 reports the simulation session lag results. When the criterion code is a labor attack cue the strategy pattern is similar to the naturalistic patterns with some important differences. As suggested by the frequency data, management is more integrative in response to labor, in these similations. Also, labor is a lot less attack-oriented and seems to pursue a defend-attack response cue strategy as opposed to a pure attack-attack strategy. When management attacks in the simulation, labor responds by integrating, moves back to attacking in the third lag, and then back to integration in the fifth lag. Management follows its cueing attack with more cueing and responding attacks


TABLE 4

Cell Means and F Ratios for Cueing and Responding Strategies

F Ratios (df = I , 77)



Cueing

Attack __

Naturalistic .46(.10l1 .29(.11) 20.21' .43 8.61' .28 4.55" .20 Simulation .32(.13) .27(.12J

Defend Naturalistic .48(.101 .63(.12) 7.65* .29 3.18 .19 4.99* .23 Simulation .21(.49) .14(.491 power .40

Naturalistic .06(.05) ,081.05) 1.85 .12 42.36* .60 .73 .07 Simulation .18(.14) .24(.11) power z.19 power z .08

Integrate

Responding

Attack Naturalistic .27(.12) .17(.101 4.13+ .20 25.41* .49 4.19" .I9 Simulation ,081.06 .10(.12)

Defend Naturalistic ,541.10) .52(. 13) .44 .08 .19 .05 .02 .OO Simulation ,521.15) . 5? ( . /9 ) power X.10 power z.06 power ".OO

Integrate Natrualistic .19(.09) .31(.12) 7.19" .25 25.29' .48 4.42+ .20 Simulation .39(.13) .39(.13)

'F = P < .05. 1. Standard deviations in Parentheses.

which is not consistent with strategy patterns set in motion by labor cueing attacks in the simulation. Thus, it seems that in the simulations, unlike the naturalistic settings, whichever group initiates the attacking strategy sets itself up to continue for some period.

DISCUSSION

The purpose of this article was to develop a means of coding negotiation interaction that would be more sensitive to formal, natu- raily occurring bargaining behavior and be capable of detecting strategic, in addition to tactical, use of communication. The data from this study indicate that the coding scheme does reasonably well in

TA

BL

E 5

Pro

babi

litie

s and

Ind

ices

for

Lag

Seq

uent

ials

: Nat

ural

istic

Neg

otia

tion

Cri

teri

on

: La

bor

LA

GS

Att

ack

Cue

IM

2

L

3M

4

L

5M

6L

Beh

avio

rs

Res

pons

e C

ue

Res

pons

e C

ue

Res

pons

e C

ue

Res

pons

e C

ue

Res

pons

e C

ue

Res

pons

e C

ue

Att

ac

k

.20

.31

.27

.47"

.1

6 .3

0 .3

0*

.37

.19

.37

.27"

.4

1 D

efen

d

.45

.61*

5

6

.48

.51

.63"

5

4

.56

.48

.56'

.5

6 .5

3 In

teg

rate

.3

5'

.08

.17

.06

.33

.07

.16

.07

.33*

.0

7 .1

6 .0

6 Z

ind

ex f

or

*beh

avio

r 4.

37

2.03

2.

82

3.88

3.

30

2.82

3.

89

3.96

3.

31

3.60

2.

69

Cri

teri

on

: M

anag

emen

t A

ttac

k C

ue

IL

2M

3L

4

M

5L

6

M

Beh

avio

rs

Res

pons

e C

ue

Res

pons

e C

ue

Res

pons

e C

ue

Res

pons

e C

ue

Res

pons

e C

ue

Res

pons

e C

ue

Att

ac

k

.44*

.5

1 .2

0 .3

3 .2

9*

.43

.2 1

.3

2 .2

2 .3

9 .1

7 .3

1 D

efen

d

.42

.42

.52

.58

.51

50

.50

.58

.57

.54

.54

.61

Inte

gra

te

.14

.07

.28

.09

.20

.07

.29

.10

.21

.07

.29

.08

2 in

dex

fo

r 'b

ehav

ior

8.52

4.

68

2.91

*Ob

se

rve

d p

rob

ab

ilit

y w

as s

ign

ific

an

tly

gre

ater

th

an

ex

pe

cte

d p

rob

ab

ilit

y.

Ex

pe

cte

d p

rob

ab

ilit

y f

or

cue

att

ac

k =

.37; d

efe

nd

= .56

; in

teg

rate

=

.07. E

xp

ec

ted

pro

ba

bil

ity

fo

r re

spo

nse

att

ac

k =

.21; d

efe

nd

= .53: i

nte

gra

te =

.2

6.

P

N

N

TABL

E 6

Pro

babi

litie

s an

d In

dice

s fo

r La

g S

eque

ntia

ls: S

imul

ated

Neg

otia

tions

Cri

teri

on:

Labo

r L

AG

S

Att

ack

Cue

iM

2

L

3M

4

L

5M

6

L

Beh

avio

rs

Res

pons

e C

ue

Res

pons

e C

ue

Res

pons

e C

ue

Res

pons

e C

ue

Res

pons

e C

ue

Res

pons

e C

ue

Att

ac

k

.ll

.24

.09

.32*

.08

.19

.11

.30

.07

.26

.12

.30

De

fen

d

.49

.46

.60

.46

.50

.54

.57

.5 1

.52

.52

.61

.53

Inte

gra

te

.40

.29*

.30

.22

.42

.27

.32

.I9

.4 1

.22

.26

.17

2 in

dex

fo

r 'b

ehav

ior

2.35

2.42

2.01

Cri

teri

on:

Man

agem

ent

Att

ack

Cue

1L

2M

3

L

4M

5

L

6M

Beh

avio

rs

Res

pons

e C

ue

Res

pons

e C

ue

Res

pons

e C

ue

Res

pons

e C

ue

Res

pons

e C

ue

Res

pons

e C

ue

Att

ac

k

.08

.25

.08

.32*

.10

.26

.11

.26

.10

.22

.10

.23

De

fen

d

.47

.53

.56

.40

.54

.55

.53

.45

.47

.55

.54

.55

Inte

gra

te

,450

.22

.36

.28

.36

.19

.36

.29*

.43

.22

.36

.31

2 in

de

x f

or

*be

ha

vio

r 2.05

2.41

2.25

*Ob

se

rve

d P

rob

ab

ilit

y w

as s

ign

ific

an

tly

gre

ate

r th

an

ex

pe

cte

d P

rob

ab

ilit

y.

Ex

pe

cte

d P

rob

ab

ilit

y f

or

cu

e a

tta

ck

= .23; d

efe

nd

= .

55

; in

teg

rate

=

.21. E

xp

ec

ted

Pro

ba

bil

ity

fo

r re

spo

nse

att

ac

k =

.08; de

fen

d =

56; in

teg

rate

= .37.


detecting differences between naturalistic and simulation bargaining sessions in the predicted directions, suggesting that the coding scheme may be sensitive to naturalistic negotiation interaction. In addition, the scheme detected significant differences in the ways in which labor and management used various tactics and strategies in both negotiation contexts. These capabilities support the view that this coding scheme can serve as a useful alternative to the coding mechanisms used in previous research.

The utility of the coding scheme in this article rests largely on two issues. The first issue is whether or not it is useful or necessary to code each utterance twice - once as a response to the prior utterance and once as a cue to the next utterance. The data presented here indicate that this distinction and subsequent dual coding is critical to capturing the essence of mixed-motive communication events. For example, the lag data reveal that bargainers often use more than one tactic in the same utterance. In the Putnam and Jones (1982b) data the dominant move for management was defensive. In the data reported here, management responded with integrative moves and cued with defensive moves in the naturalistic setting, and mixed moves also in the simulated setting. By not having the flexibility of detecting how each side is connecting their utterance to the prior utterance and making moves to structure the subsequent utterance, the BPAl I seems less capable of presenting an accurate picture of how communication works in bargaining situations. The essence of mixed motive interaction is that participants are required to be both cooperative and competitive in almost the same breath to reach an agreement. The BPAII is less sensitive to this need while the scheme used here attempts to explore it.

The second issue upon which the utility of this scheme rests relates to its ability to detect both tactical and strategic use of communication in bargaining. The data seem to support the conceptual organization of the tactics into attack, defend, and integrate strategies. One source of evidence for this support is that Putnam and Jones (1982b) found similar attack and defend patterns among labor and management groups to those that were found in this study. In addition, predicted differences in tactic and strategy use in both naturalistic and simulation contexts suggests that the tactics were generally organized into the appropriate set of general strategies. Thus, unlike the BPAII scheme the coding system presented in this article can be used more easily to detect the strategic use of tactics over time because the tactics are organized conceptually by their underlying potential strategic impact on the opponent’s position.


Beyond the util i ty of the coding scheme, this study seems to suggest some future directions for negotiation research that are worth noting. Perhaps the most interesting implication of the findings of this research is that naturalistic negotiations may differ from simulations with respect to the kind of communication tactics that negotiators are willing to use. The trends in the naturalistic interactions seemed much more consistent with seeing labor and management as having more complementary roles. In the simulation interactions the roles were not as consistently complementary over time. It is probably desirable in the future, given the differences observed in this article, to pursue naturalistic negotiation interaction as often as possible when trying to understand how actual bargaining communication tactics are used by negotiators.

REFERENCES

BACHARACH, S. B. & LAWLER,E.J. (1981). Powerundpoliticsinorgcrnhations. San Francisco: Jossey-Bass.

BARTOS, 0. J . (1978). Simple model of negotiation: A sociological point of view. In 1. W. Zartrnan (Ed.), The negotiation process: Theories and upplicutions. Bev- erly Hills: Sage.

BROWN, B.R. (1978). Face saving and face restoration in negotiations. ln D. Druckman (Ed.), Negotiations: Sociul psychologicul perspectives. Beverly Hills: Sage.

CHERTKOFF, J. M. & ESSER, J. K. (1976). A review of experiments in explicit bargaining. Joiirnul of Experimental Sociul Psycholgy, 12. 464-468.

DONOHUE, W.A. (1981). Development of a model of rule use in negotiation interaction. Communication monogruphs, 48,106-120.

DRUCKMAN, D. (1977). Negotiutions: Social psychologiccrlperspectives. Beverly Hills: Sage.

ELLIS, D. G. HAMILTON, M. & AHO, L. (1983). Some issues in conversational

FISHER, R. & URY, W. (1981). Getting to Yes. Boston: Houghton Mifflin. GOTTMAN, J. M. (1971). Marital interaction: Experimentul inwestigutions. New

York: Academic Press. GUETZKOW, H. (1950). Unitizing and categorizing problems in coding qualitative

data. Jorirnul of Clinicul Psychology. 6 , 47-58. HOPMANN, P.T. & WALCOTT, C . (1976). The impact of international conflict

and debate on bargaining in arms control negotiations: An experimental analysis. Internutionul Interaction. 2, 189-206.

coherence. Human Communicorion Research. 9, 267-282.

LIEBERMAN, M. (1979). Borguining. Chicago: Teach ‘Em. Inc. MORLEY, I . & STEPHENSON. G. (1977). The socinlpsycholoav ofhnrguining.

PRUITT, D. G. (1981). Negotiation Behnwior. New York: Academic Press. London: George Allen and Unwin.


PUTNAM. L. L. (1981) Pocedural messages and small group work climates: lag sequential analysis. In M . Burgoon (Ed.), Commrrnictifion Yetiuhook 5 . New Brunswick. NJ: Transaction Books.

PUTNAM, L. L. Rr JONES, T. S. (1982a). The role ofcommunication in bargaining. Humun Comniunirrrrion Reseirrch. 8. 262-280.

PUTNAM. L. L. &JONES. T. S. (1982b). Reciprocity in negotiations: A n analysis of bargaining interaction. Cornmunicufion Monogruphs, 49, 71-191.

REUSCH. J . & BATESON. C. (1951). Communicrrfion: Tl7e socirrl mrrfri.r of’ psyehirifry. New York: Norton.

SACKETT, G . P. (1977). The lag sequential analysis ofcontingency and cyclicity in behavioral interaction research. In J . Osofsky (Ed.). Hondbook of’infirnf ife- \?lopmenf. New York: John Wiley.

SCHELLINC, T. C. (1960). The .strrrfegy ofcon./7icf. Cambridge: Harvard Univ. Press.

ZARTMAN, I . W. (1978). Negotiation as a joint decision-making process. I n I . W. Zartman (Ed.), The negofitrrion proce.ss: Theories rind npplicrrfion.v. Beverly Hills: Sage.

CODING NATURALISTIC NEGOTIATION INTERACTION

Documents

Transcript of CODING NATURALISTIC NEGOTIATION INTERACTION