Relationship Marketing Team Design: A Powerful Predictor for Relationship Effectiveness
Gabi Helfert Hans Georg Gemunden, University of Karlsruhe
ISBM Report 6-1998
Institute for the Study of Business Markets The Pennsylvania State University 402 Business Administration Building University Park, PA 16802-3004 (814) 863-2782 or (814) 863-0413 Fax
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Paper submitted to the ISBM Report Series Institute for the Study of Business Markets The Pennsylvania State University March 1998
Relationship Marketing Team Design: A Powerful Predictor for Relationship Effectiveness
Gabi Helfert and Hans Georg Gemuden*
University of Karlsruhe Institute for Applied Management Science and Corporate Strategy PO Box 6980 76 128 Karlsruhe Germany
Tel. +49-72 l-608-4758
Tel. +49-72 l-608-343 1
Fax. +49-72 l-608-6046
Fax. +49-72 l-608-6046
email:
[email protected]
email:
[email protected]
* The authors wish to thank Dr. Achim Walter for valuable support on earlier drafts of this work.
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Relationship Marketing Team Design: A Powerful Predictor of Relationship Effectiveness
ABSTRACT The paper deals with the empirical test of a theoretical framework concerning the design of effective relationship marketing (RM) teams. The authors draw upon major fmdings of team effectiveness research and suggest team composition, group processes, and the
organizational context of RM teams to account for a good team task performance regarding three crucial RM tasks: exchange, coordination, and adaptation. RM team task performance, in turn, is proposed to explain both relationship atmosphere, in terms of customer trust and customer commitment, and relationship effectiveness regarding sales, product/service development, and market access through an existing customer relationship. The model is tested empirically on a sample of 233 German and French software companies and advertising agencies that use teams for managing their relationships with industrial customers. LISREL analysis reveals a strong support for the proposed model. Finally, implications for research and managerial practice are discussed.
INTRODUCTION An increasing number of companies which have established long-term relationships with their customers use more than one person to manage such a customer relationship. This doesn’t come as a surprise, as the management of a business relationship with a customer encompasses a multiplicity of different tasks which require a broad range of knowledge, skills, and abilities on part of a supplier firm. Following theoretical approaches in
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relationship marketing literature as well as summarizing our
ow n
observations from
previous qualitative interviews, we have identified three main RM task bundles that have to be performed by the supplier company: Exchange, coordination, and adaptation. Exchange activities (cf. Anderson and Narus 1984 and 1990, Bagozzi 1975, Dwyer, Schurr, and Oh 1987, Homans 1958, Thibaut and Kelley 1959) serve to settle needs and requirements of the partners in a relationship. We can distinguish between product/servicerelated exchange activities which include transfer of goods or money, information exchange regarding specifications of goods, logistics, delivery or payment matters, special offers or orders as well as middle-range forecast of opportunities, needs and requirements of both parties; problem-related exchange activities that are important if a customer has difficulties with the use, the functionality or the quality of products or services provided by the supplier, or if a customer needs long-term support regarding specific solutions for his problems; and person-related exchange activities that serve to build up personal relationships between members of each partner company in order to get to know each other better and to establish social bonds. Coordination refers to the synchronization of the relationship partners’ actions (Mohr and Nevin 1990). It is always necessary when more than one party is involved in organizational processes. Coordination comprises the establishment, use, and control of formal rules and procedures, the exertion of informal influence, and the utilization of constructive conflict resolution mechanisms (cf. Ruekert and Walker 1987). Adaptation often becomes necessary in customer relationships in order to meet the special needs or capabilities of a partner. These adaptation acitivities can refer to a multitude of different areas such as products/services, manufacturing processes, logistics, delivery or
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payment modes, employee qualification, or conditions for the use of a product or service (cf. Hallen, Johanson, and Seyed-Mohamed 1991). As one can easily see, the supplier company has to work in many quite different areas. This requires a multitude of qualifications from the supplier’s employees who deal with the customer. Moreover, it isn’t always possible to carry out these different task-related activities sequentially. More frequently, several of them have to be performed simultaneously. Thus, there is substantial reason for the use of relationship marketing (RM) teams in terms of both quality and quantity of work to be done. Nevertheless, not all customer relationships which are managed by an RM team can be termed successful for a supplier firm. Empirical studies have shown that there are huge differences in the level of effectiveness a supplier company can achieve in a specific customer relationship. Gemiinden. Walter and Helfert (1996) examined 578 European business relationships between small and medium-sized manufacturing enterprises and their industrial customers. On the supplier side, between 3 and 4 employees had been directly and constantly involved in the customer relationship (p. 179 f.). The authors identified three major dimensions of relationship success: The amount of sales to the customer, the extent to which a customer helps the supplier to gain market access, and the extent to which a customer relationship is useful for the supplier’s technological development. A cluster analysis of the 578 relationships revealed four different success patterns regarding these three dimensions (cf. Gemunden, Walter and Helfert 1996, p. 30 ff.): While only 15.22% of the suppliers exploit all three success potentials of their customer relationship above average, 32.70% are high performers regarding two of the three dimensions, 29.41% make an above-average use of their customers only with respect to the sales dimension, and
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22.67% are poor performers concerning all three dimensions in question. The four clusters and their exploitation of the relationship potential on the three success dimensions are shown in Figure 1. The grey triangle symbolizes the sample means on these three dimensions. FIGURE 1 Success patterns in 578 European business relationships 1
Cluster 1 (n=88)
sales volume in relationship
Cluster 2 (n=189)
sales volume in relationship
market access through technology development market access through technology development existing relationship through existing relationship existing relationship through existing relationship Cluster 3 (n=170)
sales volume in relationship
Cluster 4 (n=131)
sales volume in relationship
market access through technology development market access through technology development existing relationship through existing relationship existing relationship through existing relationship from: Gemunden, Walter, and Helfert (1996, p. 31)
The empirical fact that multipersonality on part of the supplier firm is quite common in RM, together with the observation of different success patterns in supplier-customer relationships, served as a motivator for the study which shall be documented in this paper. The basic-question of this research is: How can the design of an RM team contribute to
achieve relationship effectiveness? To answer this question, Helfert (1997) has put up a theoretical model that draws upon conceptual approaches of research on supplier-customer relationships as well as theoretical and empirical team effectiveness research. In this paper,
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we will present the findings of an empirical test of this model. The following section will therefore describe the team design constructs examined in this study, their effects on RM task performance and the contingency relationships among them. Furthermore, the relationship outcomes in question are presented. This section is followed by a brief description of the data collection process and the sample included in this analysis. Construct measurement, data analysis procedures and the empirical results are presented in the next three sections. The last section of the paper deals with the discussion of the results and their implications for RM research and practice.
RELA TIONSHP MARKETING TEAM DESIGN, TASK PERFORMANCE, AND RELATIONSHIP OUTCOMES For more than one century, behavioral, social, engineering, and management scientists have been dealing with the question of what makes team work effective. In this context, a huge and almost countless number of variables have been suggested to account for a team’s performance. Empirical studies, however, have mostly been restricted to the examination of one or a few of these variables. Moreover, they have almost exclusively been carried out in laboratory settings, frequently observing student samples. In the context of RM, there is no empirical study known to the authors where a comprehensive model of team effectiveness has ever been tested in a field setting up to now (for first conceptual or exploratory approaches cf. Deeter-Schmelz and Ramsey 1995, Moon and Armstrong 1994, Narus and Anderson 1995, and Smith and Barclay 1993). During the past two decades, several attempts have been made to summarize the proposed predicting variables by naming a sensible number of constructs and setting up hypotheses
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regarding their contingency relationships and their impact on effectiveness (cf. the theoretical models of Campion, Medsker, and Higgs 1993, Cannon-Bowers, Oser, and Flanagan 1992, Cohen 1994, Cohen and Bailey 1997, Cohen, Ledford, and Spreitzer 1996, Cummings 198 1, Gist, Locke, and Taylor 1987, Gladstein 1984, Goodman, Ravlin, and Argote 1986, Guzzo and Shea 1992, Hackman 1987, Sundstrom, DeMeuse, and Futrell 1990, Tannenbaum, Beard, and Salas 1992 and Vinokur-Kaplan 1995). In short, three major second-order constructs can be identified to account for team effectiveness: Team composition, group processes, and the organizational context in which a team operates. We define these constructs, their dimensions, and their probable effect on task performance in the RM context as follows:
Team Composition Team composition refers to the individuals a team is built of. First, it can be seen in terms of quantity, i.e., the number of persons involved. Empirical studies have revealed that a team should be just large enough to do the work it is required to do (“principle of least group size”, cf. Thelen 1949), as a smaller number isn’t technically able to perform its tasks (Campion, Medsger, and Higgs 1993, p. 828), and a larger number is bound to produce process losses due to increasing coordination requirements (Ziller 1957, p. 171) and a reduced effort of the individual team members, termed “social loafing” (Harkins and Petty 1982, Karau and Williams 1993, Latane and Nida 1980, Moede 1927, Williams, Nida, Baca and Latane 1987). Thus, regarding sub-optimal RM team size, we assume the following:
H1a: The greater the gap between actual team size and minimum team size the lower the R M team performance will be.
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Team composition can also be defined in terms of quality, i.e., team member qualification regarding specialist skills and social competence. For successful RM, we assume the following specialist skills to be of importance: Technical skills are required to inform or train a customer concerning technical product specifications, to understand the customer’s technical requirements or to initiate technical adaptation of products to the specific needs of a customer (Johanson and Mattsson 1988, p. 289). Knowledge about legal matters is mainly important for setting up contracts (Helfert 1998, p. 78). Boundary-spanning competence (cf. Ancona 1990, Ancona and Caldwell 1988, Bristor 1993, and Gladstein 1984) can be of value whenever relationships to third parties may be used for the benefit of the customer relationship in question (cf. the role model “relationship promoter” in Gemunden and Walter, 1994). Third parties can be members of organizational departments not represented by any team member, or important persons in different companies (such as other customers of the supplier, other suppliers of the customer, suppliers of the supplier, customers of the customer, research institutions, or consultants) who can be of help if special problems occur. Finally, experiential knowledge from different customer relationships facilitates the management of ‘the relationship in question, as many of the experiences with other customers can directly be used to anticipate and evaluate critical situations and to select appropriate action (Helfert 1998, p. 29).
Social competence is the extent to which a person is able to exhibit autonomous, prudent and useful behavior in a social setting (Helfert 1998, p. 29). It contains communication ability, extraversion, conflict management skills, empathy, emotional stability, selfreflectiveness, sense of justice, and cooperativity. Social competence is extremely important for RM task performance, as working on RM tasks can be understood as a series
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of social situations with members of the customer company that can only be met successfully when the RM team members in the supplier company possess these social qualifications. Thus, regarding team member qualification, we propose the following:
H1 b: The higher the specialist and social skills of the RM team members, the better it will perform its RM tasks.
Group Processes These are phenomena which occur due to the interaction of team members (Douglas 1983, p. 56 f.). They encompass the establishment of group norms, setting up group goals, building group cohesiveness as well as exhibiting a certain level of communication quality.
Group norms are “the group’s shared beliefs about appropriate behavior, attitudes, and perceptions concerning matters that are important to the group” (Kolb, Osland, and Rubin 1995, p. 227). They affect team performance especially if norms for effort and output of the group are set lower than theoretically possible (Hackman 1976). We assume two dimensions of an effort/output norm to be of importance regarding team performance: Its absolute level and the level of conformity of the team members regarding the norm (Helfert 1998, p. 47 f.).
Goals can be defined as “normative statements which describe a desirable future state of reality” (cf. Hauschildt 1977, p. 9). The existence of a common, clear, challenging and specific group goal which the team members are equally committed to has a motivating, complexity-reducing, coordinating and conflict-reducing function (Gemunden 1995, p. 254)
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for the team members and thus enables them to perform their tasks better (Weldon and Weingart 1993). Group cohesiveness is “the resultant of all the forces acting on the members to remain in the group” (Festinger, Schachter, and Back 1950, p. 164), also referred to as “the commitment of the members to the group and its task” (Smith and Barclay 1993, p. 23). Empirical studies have shown that especially the attachment of the group members to their common task has a positive influence on task performance (George and Bettenhausen 1990, Prapavessis and Carron 1997), whereas interpersonal cohesiveness was sometimes found to have this effect, and sometimes not (cf. the studies of Greene 1989, Klein and Mulvey 1995, and Zaccaro and McCoy 1988, as well as the meta-analyses by Evans and Dion 199 1, Gully, Devine, and Whitney 1995, and Mullen and Copper 1994). We assume taskbased cohesiveness to be a potential predictor for RM team performance, as a high attractiveness of the group task will directly effect the motivation to tackle with taskrelated problems, exhibit task-related behavior and thus increase the probability of a high task performance. The communication within an RM team, i.e.; the information exchange between the team members, is an essential condition for the team’s task performance. Whenever more than one person is working on a given task, information has to be exchanged in many different areas, such as allocation of responsibilities, transfer of information that is relevant for working on a task, coordination of several sub-tasks that are worked on by different team members, giving feedback or making decisions about joint action (Helfert 1998). Thus, communication intensity, i.e., the overall amount of communication within the RM team, is the first indicator of communication quality (cf. the empirical study of Katz 1982 in R&D
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project teams). With complex tasks, such as RM tasks, it is moreover necessary that the communication pattern within the team is rather decentralized than centralized, i.e., every team member should communicate with any other team member directly and not via one or more central persons (Bavelas 1968, Cavalier, Klein, and Cavalier 1995, Leavitt 1951, and Shaw 1954). To summarize the reflections on group processes made above, we assume the following: H2: The higher the quality of the group processes in the RM team in terms of (a) the
strength of and conformity
regarding
performance and output norms, (b) the clarity,
commonness, challenge and specificity of the group goals, (c) the intensity of taskbased cohesiveness within the team, and (d) the communication quality, in terms of intensity and decentrality of communication in the team, the better the RM team will perform its tasks.
The Organizational Context The organizational context contains the team’s access to resources necessary for task performance, the degree of decision autonomy granted to the team by the organization, and the availability of team training and development interventions. An RM team has to have access to many different resources, such as information on the own company, the customer or the market; communication media and other technical equipment such as telephone, fax or e-mail in order to contact the customer and to be contacted by the customer whenever necessary; financial resources, e.g. for visiting the customer; or sufficient space in the company, e.g. to conduct team meetings. Access to critical resources has a positive impact on task performance, because without it, the RM
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team isn’t technically able to perform its tasks appropriately. Furthermore, resource shortage may result in competition as well as political maneuvering among the team members (Friedlander 1987, p. 309) which certainly is contra-productive, as energies that may be used for task performance have to be wasted for political quarrels within the team. A high decision autonomy granted to the RM team by the organization has a lot of advantages with respect to task performance: Basic know-how of the team members, who certainly can be seen as experts in their field, can be used when decisions have to be made regarding relationship goals, division of the common task into sub-tasks, use of resources or the allocation of responsibilities. Furthermore, the identification of the team members with the decision and their motivation to follow the decision can be enhanced when they themselves have been involved, as cognitive dissonance (Festinger 1957) and reactance (Brehm 1966) are less likely to occur (cf. also Brickner, Harkins, and Ostrom 1986). Thus, we assume decision autonomy to have a positive impact on task performance (cf. the studies by Campion, Medsker, and Higgs 1993, Cohen, Chang, and Ledford 1997, Gist, Locke, and Taylor 1987, Uhl-Bien and Graen 1992). Finally, task-based team training and development interventions serve to enhance the task performance of the team. By participating, team members acquire a better understanding of the task, they are enabled to use their tools more efficiently, and they learn about effective performance strategies (Buller 1986, p. 157; cf. also the meta-analysis by DeMeuse and Liebowitz 198 1). Thus, if a company provides task-based team training and development interventions for the RM team members, this is likely to have a positive effect on its task performance. In summary, with respect to the organizational context, we propose as follows:
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H3: The quality of the organizational context in terms of (a) the availability of necessary resources, (b) the degreee to which an RM team is enabled to make its decisions autonomously, and (c) the availability of task-based team training and development for the team members has a direct positive impact on the team’s task performance. Finally, causal relationships between the three team design aspects can be assumed to exist. We propose the quality of group processes t o be enhanced by a favorable team
composition as well as by the quality of the organizational context: If an RM team is too large, it will have difficulties to find common norms, although they are especially important in large teams. Social loafing is more likely to occur in larger teams (Moede 1927) so that norms regarding effort and output wil l be lower. Group cohesiveness
is
weaker in larger teams (Carron and Spink 1995, Porter and Lawler 1965).
Communication intensity, viewed as number and length of individual contributions, decreases with team size (Bray, Kerr, and Atkin 1978, Carter 195 1, Hare 1952). Communication gets more centralized with growing team size as it is not possible to maintain decentralized communication structures: Sub-groups and cliques are likely to emerge. On the other hand, if the RM team is too small, its members will be so consumed with performing their operative tasks that common goal setting and norm building, communicating and becoming cohesive have to be neglected. A real team can’t develop.
H4a: The quality of group processes will be negatively affected to the amount of which the R M team is smaller or larger than it should be. For the emergence of favorable group processes, the qualification of the team members is of importance as well: If the team members are better able to perform their tasks by disposing
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of the necessary specialist skills, high output norms and challenging goals lose their threatening potential to them. The task is more attractive if the members feel they can put up with it: Task-based cohesiveness will be higher. Social skills enhance the quality of group processes as well, as interaction quality within the team will increase when team members are socially competent.
H4b: The higher the specialist and social skills within the RM team, the better the quality of group processes will be. The quality of the organizational context will also affect the group processes within the RM team. Only when a team has access to the necessary resources for working on its tasks will it be able to build up common output norms or common goals. If these resources are short, team members will compete for them in order to achieve individual goals rather than those of the group. Not the mutual task is attractive for them; instead, securing one’s own status and resource supply becomes focal: Task-based cohesiveness can’t develop. Communication frequency is likely to decrease, as information will be withheld from others in order to secure the own advantage. Centralized communication patterns will emerge, as everyone is bound to build centralized sub-teams and coalitions against other sub-teams. Task-based cohesiveness will increase with the degree of decision autonomy, as the team can decide on its own how to work on a task. If the team members have the opportunity to decide about their goals autonomously, the acceptance of and commitment to these goals will also be higher, as well as norms regarding output and effort. By providing a high degree of decision autonomy, the team is forced to communicate more frequently and less centralized, as finding a decision within the team requires intensive communication between all of its members. Finally, the participation in task-oriented team training and
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development interventions can also positively affect group processes. Goal setting workshops, e.g., enhance the team’s ability to formulate realistic and challenging goals. Unfavorable norms within the team can be made conscious to the members so that they are able to change them. And the task is more appealing if the team members are better able to manage it: Task-based cohesiveness will increase. Communication and conflict management trainings enable the team members to recognize and tackle communication problems within the team more quickly, so that communication frequency will increase if there is less conflict and less misunderstanding between the team members.
H5: By increasing the quality of the organizational context, the quality of the group processes will be positively affected.
Relationship Outcomes Companies establish relationships with external partners in order to achieve goals they could otherwise not achieve or not as efficiently. These goals can take different forms such as improving the amount or continuity of sales volumes, making use of relationships to gain access to new markets or integrating external partners in the development of new products or processes (Gemunden, Schaettgen, and Walter 1992, Gemiinden, Walter, and Helfert 1996, p. 21 f.). Relationship effectiveness for a supplier firm thus equals the extent of goal attainment the company is able to reach due to the relationship. A good task performance of the RM team regarding exchange, coordination, and adaptation in the customer relationship is a necessary precondition for relationship effectiveness. This can be explained as follows:
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First, relationship effectiveness is affected directly by the RM team’s task performance: If the RM team is able to manage the exchange of goods, technology, information, attitudes etc. with the customer in the right way, to coordinate the actions of the own company with those of the customer and to recognize, initiate, and perform adaptation activities and processes, it is more likely that the goals of the relationship can be attained.
H6: The performance of the R M team regarding exchange, coordination, and adaptation tasks in the relationship has a positive direct influence on relationship effectiveness for the supplier firm. Second, an indirect effect of RM team task performance can be assumed, namely through the mediating construct of relationship atmosphere. Relationship atmosphere is relevant for the supplier in terms of customer trust and customer commitment: Trust refers to the expectation that the relationship partner is willing and able to act in the best interest of the relationship (Helfert 1997, p. 6). The most effective way for a supplier to make the actors in a customer firm trust in his competence and benevolence is to provide them with positive experience: If the actors in the customer firm feel that the supplier is able and willing to fulfill their needs and demands and to be a reliable and predictable partner, they will be likely to develop trust in the supplier. A good task performance of the RM team can thus produce such positive experience and is likely to enhance trust within the customer company. The commitment of a customer can be described as the “enduring desire to maintain a valued relationship” (Morgan and Hunt 1994, p. 23). Commitment for the relationship with the supplier can best be achieved by establishing strong bonds on a structural and social level (Wilson and Mummalaneni 1986). The establishment of such
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bonds through exchange, coordination, and adaptation activities of the supplier thus serves to strengthen customer commitment.
H7: The level of task performance of the R M team has a positive impact on relationship atmosphere in terms of the customer’s trust and commitment. Although there have been numerous publications on the role of trust and commitment in business relationships, hardly any quantitative empirical studies have been conducted to examine their impact on relationship effectiveness for a supplier. Nevertheless, it is likely that the goals of the relationship, especially those that are of a more long-term nature, can better be achieved if the customer is committed to the relationship and trusts the actors of the supplier. If we think, e.g., of information the customer makes available in order to help the focal firm gain access to new markets or develop their products - which both are frequent objectives of business relationships (cf. Gemunden, Walter, and Helfert, 1996) - it will be more likely that these efforts will be higher and produce better results when the customer can trust the supplier company’s actors that they handle this information carefully and without producing disadvantages for the customer. And if there is only little commitment to the relationship, the customer won’t even think about taking the risk of passing on critical information to the supplier.
H8. The better the relationship atmosphere in terms of customer trust and commitment is, the better the relationship effectiveness for the supplier company will be. To summarize, Figure 2 gives an overview of the complete theoretical model, its constructs, their dimensions, and the proposed relationships between them.
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FIGURE 2 The theoretical framework of the study
I
Customer
Team Membe
DATA COLLECTION AND SAMPLE Data were collected between December 1996 and September 1997 in standardized personal interviews with 233 RM team leaders in German (n=l77) and French (n=56) software companies (n=126) and advertising agencies (n=107). Each interview took between 60 and 90 minutes. The response rate compared to the 600 companies we asked for an interview was 43.6%. In addition, we asked every team leader to pass on a short standardized questionnaire to every team member in order to obtain measures for group cohesiveness and a validation of the effectiveness measures. Of the 994 questionnaires distributed that way, 589 (59.6%) were returned by mail to the authors.
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MEASUREMENT Communication within the team was measured by a matrix where communication frequency had to be assessed on a person-to-person level with a 5-point rating scale (0 = never, . . . . 4 = very often). The mean of all of these dyadic measures in one team was used as an indicator of average communication frequency within the team. Communication
decentrality was computed by first calculating the communication frequency of each person. The coefflcicient of variation between these scores of each team member was used for centrality. This value was further subtracted from 1, so that decentrality of communication could be expressed. The value was transformed to a 5-point-scale so that a measure for communication quality could be calculated by computing the mean of the values for communication frequency and communication decentrality. Regarding team size, subjects were asked to report the actual number of team members and the number of team members they think would be appropriate for performing the tasks in this customer relationship. The absolute deviation between the two values was taken as an expression for sub-optimal team size. All otherjrst-order constructs were measured by 5- or 7-point multi-item rating scales that may be obtained in full length from the first author. Items were summarized by building the scale mean of each first-order construct. Reliability of the first- and second-order constructs as named above was checked by computing Cronbach’s Alpha coefficients and item-to-total correlations. Items with item-to-total correlations below .30 were eliminated. Convergent validity was conventionally checked by performing exploratory factor analyses with the first-level constructs as input variables. In all cases, only one factor was extracted by the Kaiser criterium (eigenvalue above 1).
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Table 1 gives an overview of the Cronbach’s Alphas for any first- and second-order construct and of the explained variance of the exploratory factor analyses on second-order construct level. The results are very good on first-order construct level, showing twelve Cronbach’s Alphas above .80, four above .70, and only one slightly below .70. On a second-order construct level, results are still satisfactory, with three Cronbach’s Alphas above or equal .70 and three still above .60, and, in all cases, an explained variance of more than 50% by one extracted factor. Therefore, sufficient reliability and convergent validity of the measures, as checked by conventional statistics, are given. TABLE 1 Reliability and validity of measurement
First-order construct (n of items/dimensions) Specialist skills (7) Social skills (13) Group norms (7) Group goals (5) Group cohesiveness (9) Communication quality (2) Resource availability (8) Decision autonomy (7) Team training and develoument (6) Exchange activities (6) Coordination activities (8) Adaptation activities (4) Customer trust (12) Customer commitment (9) Sales effectiveness (5) Product/service development effectiveness (4) Market access effectiveness (4)
Cronbach’s Alpha .68 .89 .87
Second-order construct (n of first-order constructs)
Explained Cronbach’s variance Alpha by 1 factor
Team member qualification (2)
.67
75.3%
Quality of group processes (4)
.700
59.1%
.87 .83 .71 .80 .71
Quality of organizational context (3)
.70
62.9%
RM team task performance (3)
.74
66.5% %
.85 .83
Relationship atmosphere (2)
.66
74.5%
Relationship effectiveness (3)
.64
58.5%
.88 .84 .76
.74
.83 .811
The validation of the effectiveness measures obtained from the team leader with the responses from the team members was made by performing a correlation analysis between the mean item score on each of the three first-order effectiveness constructs with the mean team member score of the overall estimations regarding each of the three effectiveness
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dimensions in the team member questionnaire. Correlations ranged between .32 and .47 and were all significant on a p variance (pv) > .40, and construct reliability (pJ 1 .60 (cf. Anderson and Gerbing 1988, Backhaus, Erichson, Plinke, and Weiber 1994, Bagozzi and Baumgartner 1994, Bagozzi, Yi, and Philipps 199 1, Homburg and Baumgartner 1995, and Homburg and Giering 1996).
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RESULTS Both the measurement model and the structural model showed a good fit to the data (cf. Table 2). TABLE 2 Fit measures from LISREL analysis
Measurement model
Structural model
Goodness-of-fit index (GFI)
.973
.967
Adjusted goodness-of-fit index (AGFI)
.960
Root mean square residual (RMR)
.056
.062
XL
126.21
153.26
df
115
123
X’ldf
1.10
1.25
Fit measures
R
2
64)
1 .ooo
R2 (Y/l?>
-
Total Coefficient of Determination (TCD)
-
I
t
I
.954
.990 1 .ooo .611
Reliability of the items (p,), explained construct variance (pJ, and construct reliability (pc> were satisfactory, between 78% and 100% of the estimated parameters met or exceeded the prescribed limits for both measurement model and structural model estimations.
Convergent validity was assessed by comparing the average explained variance of a secondorder construct (pV) with its reliability (pC). In each case, pC was greater or equal than pV, indicating a sufficient convergent validity. The Fornell/Larcker criterium (Fomell and Larcker 1981, p. 46), an indicator of discriminant validity, was met in all cases with the measurement model and in all but one case (which equals 98% fulfillment) with the structural model. An adequate level of fit in both the measurement model and the structural model can be assumed.
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Figure 3 shows the test results regarding the structural model, indicating the structural equations coefficients, the t-values, and the explained variance of the endogenous constructs ql to q4. FIGURE 3 Results of the structural model
.28 (3.28) &QiiLj
x.xX: standardized path coefficient 132: explained construct variance
All hypotheses but one can be confirmed significantly, so that the theoretical model may be accepted due to the data. Hypothesis la, proposing a negative effect of sub-optimal team size on RM team task performance, only shows tendencies towards being confirmed, as the t-value doesn’t indicate significance. Still, the proposed negative relationship can be found. An elimination of the suggested path from the model estimation, however, didn’t show any significant improvement of the model, so that we suggest to still keep this hypothesis. Table 3 gives an overview of the direct, mediated and total effects of the antecedent constructs on relationship effectiveness.
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TABLE 3 Relationship Effectiveness: Direct, mediated, and total effects
I
Impact on Relationship Effectiveness Antecedent Constructs
Direct Effects
Mediated Effects I1
Team Member Qualifications
-
I
Total Effects 1
16
.16 I
Sub-optimal Team Size
- .12
Quality of Group Processes
.15
Quality of Organizational Context
.21
.21
Task Performance of RM Team
.42
.19
.61
Relationship Atmosphere
.32
-
.32
Overall, the findings indicate that team composition, group processes, and the organizational context all have a significant influence on the way the RM team performs its exchange, coordination, and adaptation tasks, which, in turn, is essential for a good relationship atmosphere and a high relationship effectiveness. RM team design is a
powerful predictor for a supplier’s relationship effectiveness. This effect is mediated by RM team task performance and, partially, by relationship atmosphere.
DISCUSSION AND OUTLOOK Despite the powerful support of the hypothesized relationships between the constructs, there are several limitations to this study: First, most of the data were obtained from a single informant in the supplier company. This is a common practice in marketing research (cf. Philipps 198 1, John and Reve 1982). We have invested a considerable amount of time to identify a person that is equally wellinformed about the RM team, the supplier company in general, and the customer relationship in question. Results from pretest interviews didn’t indicate large differences
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between the key informants’ view of the relationship and the view of the customer’s employees. And, validation of effectiveness measures by the team members showed satisfactory results. However, differences between measurement and “reality” can still not be excluded entirely. Moreover, we have restricted data collection only to two industries that have been working with team approaches in RM for a long time. Whether the findings can be generalized to different industries, especially those that have just begun to establish team work in RM, must remain unanswered, although we can’t think of any sensible hypotheses on industry effects in the context of this study. Moreover, we only had the opportunity to look at the RM team in the supplier company. Previous studies, however, have shown that also on the customer’s side of the dyad, more than one person is usually involved in a long-term business relationship. In this context, one can think of several interesting research questions: Are these multi-person structures permanent, like the observed RM team in the supplier company, or are they more of a transitory or dynamic nature, like e.g. a buying center which mostly interacts only when a specific buying decision is to be made and disintegrates afterwards (cf. Dowling 1995)? Do the persons in the customer company who are in contact with the supplier’s RM team also have intensive interaction and relationships with each other and can thus be termed “team” as well? Does this have any explanatory or moderating effect with regard to the proposed model and- the explanation of relationship effectiveneness? These are questions that may be interesting to answer in follow-up studies. Finally, the focus of observation in this study was a single customer relationship. In entrepreneurial practice, especially in small companies, employees are usually involved in a
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multiplicity of relationships with different customers. Considering this, phenomena like role conflict, resource allocation problems or work overload are likely to occur under certain circumstances. An extension of the study to a network perspective might be quite interesting with regard to these questions. Nevertheless, there are a couple of useful practical recommendations that can be derived from this study:
Team composition should include quantitative as well as qualitative considerations. All respondents were able to name the “right” number of team members with respect to a given task very quickly. Nevertheless, almost 50% of the observed RM teams included either too many or too few persons. A comprehensive analysis of quantitative personnel requirements for the management of a specific customer relationship could prevent from selecting a wrong number of team members. By a sensible personnel selection and continuous personnel development, the necessary specialist and social skills could be identified and their development supported. The organizational context has also been identified to be a very important way to improve RM team task performance, and, by this, relationship effectiveness. Companies should do their best in providing their RM teams with the necessary resources, because otherwise, task performance will be poorer than theoretically possible, and performance-enhancing group processes can’t emerge. Companies should as well leave task-related decisions to the RM team,-as this will also result in a better quality of the group processes and a higher probability for a good task performance. Team training and development interventions also serve to enhance the group processes and the task performance of the team, so that opportunities for team members’ participation should be created by the company.
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Group processes, finally, can be influenced purposefully only to a very limited extent by persons external to the team. If the supplier company, however, will be careful in designing team composition and the organizational context, favorable group processes are likely to emerge, as the findings of this study suggest, and they will also contribute to a good task performance and a high relationship effectiveness for the supplier.
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