JOURNAL OF ORGANIZATIONAL BEHAVIOR, VOL. 14,201 224 (1993)

The feedback environment: An exploratory study of cue use

SUSAN J. ASHFORD School of Business Administration, The University of Michigan. Ann Arbor, MI 48109-1234, liS..4.

Summary This paper examines individuals’ theories about cue use in organizations - theories about which of the many cues available in an organization’s feedback environment they should use to guide their behavior. It also investigates how these theories vary with increasing organizational experience. The research assesses individual’s implicit theories regarding cue use using both open- and closed-ended data collection methods. Results suggest that, regardless of experience, individuals place the most importance on cues from the company and their supervisors. Peer feedback and self-observations were seen as much less important. These results are interesting in light of previous studies showing that the self was the most available, and the organization the least available, source of feedback. With experience, managers appear to learn to emphasize negative over positive feedback, especially from superiors, and to emphasize theii peers’ actions over their words when a negative message is being conveyed.

Introduction Ashford and Cummings (1983) proposed that individuals seek feedback actively and use it to help them attain such goals as effective job performance and career advancement. Their argument raised a host of new questions about feedback processes in organizations. The current research adds to the literature on individuals’ active feedback-seeking (cf. Ashford, 1986; Herold and Parsons, 1985) by focusing on the feedback cues that employees believe they use to guide their work behavior. The first study provides a qualitative assessment of the cues individuals use to assess their performance. The second and third studies further examine respondents’ beliefs about cue use using close-ended survey methodologies. The literature on the feedback environment and feedback-seeking serve as the source of the research questions for this research. These are reviewed below.

Feedback seeking and the feedback environment Feedback researchers have labeled the set of information that tells individuals how well they are performing a goal the ‘feedback environment’ (Hanser and Muchinsky, 1978). Existing research on the feedback environment has focused primarily on identifying the amount of this information provided by various sources of feedback (Greller and Herold, 1975; Hanser and

The author would like to thank Don Fedor, Craig Pinder, Anne Tsui and Jim Walsh for their comments on earlier drafts of this paper. Special thanks to Greg Northcraft for his help with the data analysis and to the Tuck Associates Fund for supporting this research. This research was conducted while the author was on the faculty at the Amos Tuck School of Business Administration, Dartmouth College.

0894-3796/93/030201-24S17.00 0 1993 by John Wiley & Sons, Ltd.

Received 31 January 1991 Accepted 18 October 1992

202 S. 1. ASHFORD

Muchinsky, 1978; Herold and Greller, 1977). Of the five sources examined - formal organiza- tion, supervisor, co-workers, task, and self (Greller, 1980; Greller and Herold, 1975; Hanser and Muchinsky, 1978; Herold, Liden and Leatherwood, 1987) - sources psychologically close to the individual (e.g. self and task) were perceived as providing the most feedback, while more distant sources (e.g. superior and formal organization) were perceived as providing less feedback (Hanser and Muchinsky, 1978; Greller and Herold, 1975). Researchers have theorized that psychologically close sources are perceived as readily available and trustworthy; therefore, they are seen as providing the most information (Greller and Herold, 1975).

Only two studies have examined the utility of sources (i.e. how useful each is for finding out how well one has done one’s job). Greller (1980) found that supervisors and subordinates disagreed when assessing the relative utility of various sources of feedback. Supervisors empha- sized feedback under their control (e.g. formal rewards from the organization and informal assignments from the boss), while subordinates rated sources not under the supervisor’s control (e.g. co-workers and task feedback) as more useful. In addition, Greller (1980) (again, assessing the utility of feedback sources rather than the amount of feedback each source provided) found only equivocal support for the personal-to-more-distant-sources linear trend found by Greller and Herold (1975) and Hanser and Muchinsky (1978). A more recent study (Herold et al. 1987) combined employees’ perceptions of the amount, consistency, and utility of feedback into an overall measure of source quality. They found that perceived overall source quality was lower for feedback sources more distant from the individual. However, because the scale combined utility with amount and equality, the three dimensions were confounded, making it difficult to draw conclusions regarding source utility. In general, less is known about the perceived utility of feedback sources than about which sources are perceived to provide the most feedback.

Recently, research has moved away from an examination of feedback sources per se and toward the study of the specific cues that make up a feedback environment. Herold and Parsons (1985), for example, created a 63-item feedback environment scale that takes as its unit of analysis the cues available in an environment, not an abstract assessment of the sources them- selves. The move to a cue-specific analysis raises a set of questions that have not been answered as yet in the research on perceptions of feedback environments. These questions involve indivi- duals’ beliefs about how they would use this feedback information. That is, what feedback cues do individuals think they would actually use on a day-to-day basis in making judgments about the adequacy of their current behavior? A study of these questions is an important contri- bution to the feedback literature for several reasons.

First, if we accept the premise that underlies Herold and Parsons’ (1985) work - that indivi- duals actively seek, interpret, and use feedback (Ashford and Cummings, 1983) - then it is important to know not only what feedback is available to them in an organizational setting but what feedback they think they would actually use. In fact, Herold and Parsons (1985) justified the value of their feedback environment measure in part by arguing that now that a measure of the feedback available in a feedback environment exists, then questions can be asked about how people use the information available. While cue availability is important - it partially explains the effect that feedback may have on individuals-we need to understand what cues individuals believe they would actually attend to and use in guiding their subsequent behaviors if we are to understand the full effect of feedback.

Second, individuals’ observations of the feedback cues around them may be their primary means for deriving work-related feedback messages. Ashford and Cummings (1983) proposed that while individuals can seek feedback either by directly asking others (inquiry) or by observing cues around them (monitoring), inquiry is the more costly seeking strategy since it exposes

THE FEEDBACK ENVIRONMENT u)3

the individual’s need for feedback and this need may be seen as a sign of uncertainty or insecurity (Ashford and Northcraft, 1992; Northcraft and Ashford, 1990). Given the perceived social costs of inquiry, individuals may rely instead on feedback drawn privately from their own observations. However, reliance on observed cues is troublesome because the inferences drawn from these observations may be subject to a variety of biases resulting in erroneous self-assess- ments (Ashford, 1989). It is only by beginning to study what cues employees believe they would use, in addition to what cues are available to them, that we can assess the importance of this concern.

The current research represents an exploratory examination of employee cue use. Study 1 used an open-ended survey methodology to address a descriptive and general question: What cues provided by the feedback environment do individuals use - which do they see as most important and which do they de-emphasize? This study begins to answer the call for more empirical work on how individuals use cues by developing a qualitative description of cue use.

Studies 2 and 3 addressed two additional questions. First: How much do employees perceive they use the feedback cues provided by the various sources considered in previous research? While it has been shown that the self is the most, and the organization the least, available source of feedback (Greller and Herold, 1975), which source’s cues will be seen as the most useful guides for subsequent behavior? An answer to this question will contribute to the literature on the feedback environment.

The final research question concerned whether and how individuals’ perceptions of their use of the feedback environment varies with the amount of their work experience. Wagner and Sternberg (1985) argued that with experience beyond formal education (i.e. total work experience, across organizations, jobs, or work groups), managers develop a tacit knowledge about what they should be doing to manage their careers, themselves, and others successfully. Tacit knowledge is knowledge that is not openly expressed or stated; it is not taught directly to us, but is picked up as we gain experience in a domain (Wagner and Sternberg, 1985). Wagner and Sternberg found that experienced managers’ ideas about what they should be doing differed from those with less experience, and these differences were related to success within the experienced manager group (Wagner and Sternberg, 1985). Based on these results, they concluded that experienced managers developed a tacit knowledge regarding what they should be doing at work.

To regulate their behavior, however, managers need to know not only what they should be doing in order to attain their career goals, but also how well they have done it (i.e. feedback) (Ashford, 1989; Taylor, Fisher and Ilgen, 1984). Feedback allows them to correct errors should their behaviors get off track with respect to attaining valued goals. This paper proposed that, with experience, just as managers gain a sense of what they should be doing to manage themselves, their careers, and others, they should also become more sophisticated ‘readers’ of the feedback environment. Essentially, with experience in work organizations, managers should develop a tacit knowledge regarding what cues are important and which can be ignored. The nature of this tacit knowledge was examined in Studies 2 and 3. These studies differed in the goal for which feedback use-perceptions were assessed (performance versus career advancement) and in the manner in which experience was measured.

Study 1 Study 1 entailed an open-ended look at the cues individuals use in a feedback environment, and how their use might differ by level of work experience. Research on the feedback environment

204 S. .I. ASHFORD

to date has been decidedly quantitative. Though based on some initial open-ended queries, most of the empirical work has presented respondents with a set of cues and asked them to rate the cues according to their availability in their feedback environment (cf. Greller and Herold, 1975; Hanser and Muchinsky, 1978). Given that the current research addressed a differ- ent research question, an open-ended qualitative look at what cues individuals use seemed warranted.

Method Sample and procedure The sample for this study contained individuals from three groups varying in the extent of their work experience. The Experienced Manager group consisted of 108 managers randomly selected from the alumni body of a northeastern business school (with the constraint that they had at least 5 years of experience beyond graduate school). The Business Graduate Student group consisted of 90 graduate students attending the same northeastern business school. The Undergraduate group consisted of 95 randomly selected students attending the undergraduate college of the same northeastern institution.

All respondents were mailed questionnaires. A follow-up reminder postcard was mailed two weeks following the initial survey. The surveys were completed anonymously and confidentiality was assured. Three hundred undergraduates, 178 business graduate students and 255 managers were sent surveys. Return rates for the three samples were as follows: 32 per cent undergraduates; 51 per cent business graduate students; and 42 per cent business managers.

Open-ended measure of cue use Respondents were given a general description of the role of feedback (e.g. that managers often want to know how they are doing at work and that they use a variety of ways of getting feedback on their behavior). Respondents were then asked to list the various cues that they use as information about how well they are performing their jobs. Respondents were given ample space to respond and were told to use the back of the sheet if more space was needed.

The responses were coded into 12 categories created on the basis of previous research. These categories are as follows. First, following Herold and Parsons (1985), three source categories were used. These sources were: (1) Company/Supervisor, (2) Co-workers, and (3) Selfmask. A fourth, residual, source category, labeled Other/Unspecified, was also invoked. The Other! Unspecified category included cues not tied to a specific source (e.g. ‘people believe that what I tell them is true’) and cues provided by sources not considered by Herold and Parsons (1985) (e.g. subordinates, clients). Second, the content distinction that Herold and Parsons (1985) made between positive and negative feedback was also preserved. A third content dimension was also added for all sources representing cues that were neutral or for which the affective content could not be determined (e.g. ‘written or formal performance reviews’). Thus, a 12-cell coding scheme was created by crossing four sources (Company/Supervisor, Co-workers, Self/ Task, and OtherAJnspecified) with the three content possibilities (positive, negative and neutral).

Two research assistants were trained to code the open-ended responses using the classification scheme just described. Each assistant coded all of the cues on her own, and then the two met to resolve any differences and to reach an overall agreement for each cue.

The two raters agreed on 82 per cent of the cues without discussion. Agreement was reached easily on the remaining cues. Interpretation differences usually concerned whether the cue was positive or neutral (e.g. a raise - positive, or neutral because it depends on the level of the raise?), or on the (sometimes implied) source of the cue.

THE FEEDBACK ENVIRONMENT 205

Results The respondents had an average age of 19.5, 26.5 and 41.8 for the Undergraduate, Business Graduate Student and Manager samples, respectively. Similarly, the samples had average years of management experience of 0.97 (Undergraduate), 4.0 (Business Graduate Student) and 12.1 (Manager). A one-way ANOVA analysis indicates that the experience-level groups do differ in their age (F=588.70; p<O.OOl) and in length in organizational experience (F = 153.6; p<O.OOl). Specifically, the Manager sample had, on average, 8 years more of managerial exper- ience and were 15 years older than the Business Graduate Student sample. In turn, the Business Graduate Student sample had, on average, 3 years more managerial experience and were 7 years older than the Undergraduate sample.

The sample can be further described as follows. The three groups were predominantly white (99 per cent in the Practicing Manager group, 95 per cent in the Business Graduate Student group and 87 per cent in the Undergraduate group), and predominantly male (93 per cent, 80 per cent and 59 per cent in the Practicing Manager, Business Graduate Student, and Undergra- duate groups, respectively). The Undergraduates had work experience in: Politicdlaw (9 per cent), entry level jobs (e.g. clerk, cashier) (53 per cent), management (4 per cent), consulting/ engineering (1 per cent), saledmarketing (6 per cent), education (2 per cent), financial services (9 per cent), computing (10 per cent) and other (6 per cent). The Business Graduate Sample had work experience in: Financial services (4 per cent) entry level jobs (3 per cent), consulting/ engineering (26 per cent), saledmarketing (1 1 per cent), general management (9 per cent), politics/ law (3 per cent), computing (3 per cent) and other (4 per cent). The Manager group predominantly held Masters degrees (97 per cent) and represented the following functional areas: Marketing sales (40 per cent), production (7 per cent), research and development (2 per cent), human resource management (3 per cent), and other (48 per cent).

Respondents provided a total of 169 unique cues (many of these cues were provided by multiple respondents). The overall average number of cues listed by respondents was 5.59. The average number of categories presented was 3.40. The three experience-level groups did not differ in the average number of cues provided or in the average number of categories represented. To compare across the 12 categories and the three experience-level groups, the number of cues in each category were compared. These results are presented in Table 1. Simple visual inspection of Table 1 suggests a tendency to emphasize positive over negative cues and to list more cues from positive cues Company/Supervisor and Selfmask categories relative to cues from Co-workers and Others.

The analysis of the variance results presented in Table 1 show the differences in cue use across the three experience-level groups. These results suggest certain usage patterns. First, cues in three categories were listed more frequently on Business Graduate Students relative to both Managers and Undergraduates. These cues were positive cues from the Company/ Supervisor (F = 13.50, p < 0.001), positive cues in general (F = 7.52, p < 0.001), and cues from the Company6upervisor in general (F = 11.39, p < 0.001) In each of these cases the Business Graduate Student group listed the most cues, Managers the second most, and the Undergraduates the least. It appears that those with some, but not a lot, of work experience especially emphasize positive cues from the company and their superiors.

Second, respondents with more managerial experience listed fewer cues from the Selfmask category (F = 5.48, p ~ 0 . 0 1 ) and, specifically, listed fewer positive Selfflask cues (F = 5.27, p < 0.01) than did those with less managerial experience. In each of these cases (the number of positive Selfmask cues, the number of Selfmask cues in general, and the number of neutral Co-worker cues listed), the Business Graduate Students and the Managers did not significantly

206 S. J. ASHFORD

Table 1. Open-ended responses: Category percentages and analysis of variance results* Business graduate Practicing

Undergraduate students managers Ft aP Positive cues

CompanyISupervisor Co-workers Selfmas k 0 ther/Unspecified

Negative cues Company/Superviser Co-workers Selfmask OthedUnspecified

Neutral cues Compan y/Supervisor Co-workers Selfmask Other/Unspecified

Content distinctions Positive? Negative? Neutral?

Source distinctions Compan y/Supervisort Co-workers? Selfmaskt OtheriUnspecified?

1.59 0.13 1.16 0.44

0.08 0.04 0.02 0.09

0.90 0.24 0.16 0.35

3.33 0.23 1.66

2.57 0.41 1.35 0.89

3.00 0.15 0.81 0.51

0.06 0.00 0.01 0.04

0.94 0.16 0.06 0.47

4.48 0.11 1.63

4.00 0.32 0.87 1.03

2.14 0.15 0.71 0.63

0.12 0.01 0.02 0.02

0.80 0.14 0.12 0.49

3.63 0.17 1.54

3.05 0.29 0.85 1.15

13.50$ 0.11 5.168 1.57

0.83 1.97 0.17 2.31

0.50 1.35 1.52 1.06

7.52$ 1.48 1.56

I I .39$ 0.74 5.318 1.31

0.07 0.01 0.03 0.00

-0.00 0.01 0.01 0.01

0.00 0.00 0.00 0.00

0.04 0.00 0.00

0.06 -0.00

0.03 0.00

*The column entries are the mean number of cues provided by each group. t Summed from above. s p < 0.001. g p < 0.01.

differ from each other. These two groups, however, did significantly differ from the Undergra- duate group.

Discussion These results suggest several patterns in how respondents use the feedback environment. First, and not surprisingly, the ease with which the coding scheme was used suggests that the same source and content dimensions used to classify the availability of cues are also relevant for characterizing how individuals use those cues. The frequency with which cues from the ‘Other unspecified’ category were raised (primarily in reference to cues from subordinates and clients or customers) suggests that future research on cue use might want to include items referencing cues from these sources. Second, regardless of experience level, these results suggest that individuals emphasize positive

cues over negative cues and place most emphasis on cues from the company/supervisor and least emphasis on co-worker cues. These tendencies were most pronounced among those with some but not a lot of organizational experience (Business Graduate Students).

Third, the differences that did not emerge among the experience-level groups are also worth

THE FEEDBACK ENVIRONMENT 207

noting. Those with more experience did not list significantly more cues nor did they list cues from a significantly greater number of categories. These findings suggest that the cognitive maps that individuals hold of the feedback environment do not appear to become more complex or differentiated as a function of experience. This study is limited, however, in that it is unclear what a high frequency of reported use in a given category means. It may mean that respondents value this information a great deal or that so little information comes from this category sponta- neously so that respondents must explore every avenue within it just to derive a meaningful message.

Study 2 further examined individuals’ beliefs regarding how they would use the feedback environment. Study 2 used a much larger sample to respond to a series of closed-ended questions about the importance they would place on various cues.

Study 2

Study 2 addressed the question of which of the cues typically measured do individuals believe they use to guide their goal-related behavior. To maintain comparability with past research, the items developed by Herold and Parsons (1985) in their feedback environment measure were used as the stimulus set of cues. Given that these cues were all mentioned with some frequency in Study 1, this set of cues was deemed adequate for this sample. The goal of this study was to develop a quantitative portrait of individuals’ perceptions of their use of the feedback environment and to assess whether cue-use perceptions differed for individuals with varying levels of work experience.

Method Sample and procedure The sample used in this research was similar to that used in Study 1. It involved individuals from three experience-level groups, drawn from the same populations pools described in Study 1. The Manager group consisted of 97 managers randomly selected from the alumni body of a northeastern business school (with the constraint that they had at least 5 years of experience beyond graduate school). The Business Graduate Student group consisted of 105 graduate students attending the same northeastern business school. The Undergraduate group consisted of 103 randomly selected students attending the undergraduate college of the same northeastern institution. The procedure was identical to that employed in Study 1. Respondents completed mailed questionnaires, confidentiality was assured. Two hundred eighty-eight undergraduates, 254 business graduate students and 250 managers were sent surveys and response rates were 36 per cent, 41 per cent and a 39 per cent, respectively.

Closed-ended measure of cue use Respondents’ perceptions concerning their use of the feedback environment were measured with respect to a particular goal, that of career advancement within the organization. This goal was chosen due to its practical importance to a wide range of respondents. It is important to most people and is a goal to which they will likely devote some feedback-seeking energy. The career-advancement goal is also general enough so that cue importance ratings will more likely reflect respondents’ theories about the cue-importance rather than the peculiarities of

208 S. J . ASHFORD

any particular setting. Respondents were asked the extent to which they would attend to each of Herold and Parsons’ (1985) 634 cues if they held to goal of ‘rapidly advancing within the organization’.

Two issues about this measure deserve special mention. First, to give respondents some guid- ance regarding what it might mean to use a cue, they were told to rate a cue as important if they felt that they would attend to it and let it influence their subsequent behavior. While respondents can obviously attend to a cue and not allow it to influence their subsequent behavior, this would not constitute actual use of a cue. Thus, respondents were reminded at several points throughout the survey that if they rated a cue as important, they were indicating that they would attend to it and let it influence their subsequent behavior.

Second, respondents rated which cues they would use by rating the importance that they would attach to each cue. These ratings were made on a 7-point Likert scale ranging from not at all important to very important. The measure asked for importance ratings rather than ratings of actual cue use because any assessment of how much a cue is used (e.g. very frequently- very infrequently) would be determined in large part by the natural occurrence of that cue in the feedback environment. Thus, if one receives compliments from co-workers very infre- quently, one might report using this cue infrequently, when in fact, it may be a very powerful cue (in terms of affecting subsequent behavior) when it does occur. By having respondents rate a cue’s importance, the items attempted to tap respondents’ theories about what cues are important in the feedback environment rather than to develop an accurate portrait of actual cue use.

To examine experience-level differences in cue use, this study followed the methodology used by Wagner and Sternberg (1985). In their study, groups of novices (undergraduates), beginners (graduate students in psychology or business), and experts (psychology faculty or business managers) rated the importance of a variety of ways of achieving a particular goal. Differences found between the three groups were presumed to ‘measure knowledge acquired as a result of experience and formal training’ (Wagner and Sternberg, 1985; p. 443). Wagner and Sternberg (1985) compared ideas about what one should do at work provided by managers, graduate students with some work experience and undergraduates with little work experience. Given the nature of the likely work experiences of these three groups, the experience dimension thus captures both quantitative differences in the amount of experience and qualitative differences in the type of work performed.

Results The average age of the Undergraduate, Business Graduate Student and Manager samples was 20.2, 26.7 and 42.1, respectively. The groups had average years of management experience of 0.99 (Undergraduate), 3.5 (Business Graduate Student) and 12.69 (Practicing Manager). A one-way ANOVA suggests that the experience-level groups differ in age (F = 7 2 1 . 6 ; ~ < 0.001) and in their length of organizational experience (F = 232 .6 ;~ <0.001). Specifically, the Manager sample had, on average, 9.2 years more of managerial experience and were 15.4 years older than the Business Graduate Student sample. In turn, the Business Graduate Student sample had, on average, 2.5 years more managerial experience and were 6.5 years older than the Under- graduate sample.

The sample can be further characterized as follows. The three groups were predominantly white (98 per cent in the Manager group, 92 per cent in the Business Graduate Student group and 86 per cent in the Undergraduate group) and male (53 per cent in the Undergraduate group, 3 per cent in the Business Graduate Student group, and 94 per cent in the Manager

THE FEEDBACK ENVIRONMENI 209

group). The Undergraduates had work experience in: Politicsilaw (25 per cent), entry level jobs (e.g. clerk. cashier) (19 per cent), management (17 per cent), consulting/engineering and saledmarketing (7 per cent each), education (6 per cent), financial services, computing (3 per cent) and other (12 per cent). The Business Graduate Sample had work experience in: Financial services (55 per cent), consultinglengineering (15 per cent), saledmarketing (3 per cent), general management (6 per cent), politics/law (13 per cent each), computing (3 per cent) and other (5 per cent). The Manager group predominantly held Masters degrees (93 per cent) and repre- sented the following functional areas: Marketindsales (35 per cent), production (6 per cent), research and development (1 per cent), human resource management (5 per cent), and other (52 per cent).

Item classification A factor analysis of the 63 cues is presented in Appendix 1. Following Herold and Parsons’ ( 1985) methodology, principal factor analyses (with squared multiple correlations as communa- lity estimates) were performed on the importance ratings. A Scree test (Cattell, 1962) was per- formed to determine the number of factors to rotate to a varimax criterion. Again, following Herold and Parsons (1985), the positive and negative items for each of three source categories (Company/Supervisor, Co-workers, Selfmask) were analyzed separately, yielding six separate factor analyses. These factor analyses yielded 14 factors. Three factors represented positive cues from the company/superiors, tapping positive consequences (e.g. raises, etc.), expressions (e.g. verbal praise) and behaviors (e.g. job assignments), respectively. Two factors represented negative cues from company/superior, representing negative consequences (e.g. raise denied) and expressions (e.g. negative comments), respectively. Negative coworker cues loaded onto a direct and an indirect factor while comparable, positively worded, items all loaded on one factor. Positive selfhask items loaded on four factors: comparisons with others, comparisons with self (at a previous time), comparisons with internal standards and feelings of mastery. In contrast, negative self-task items loaded on just two factors - comparisons with others and negative task mastery (comparisons with self).

These data replicated Herold and Parsons’ (1985) factor analysis results for nine out of their 1 5 original categories. Exceptions occurred primarily with the positive cues from company/ supervisor and negative selfhask items. Given that these items assess a different issue (beliefs about cue use rather than reports of cue availability), some differences in findings are not surprising. Each of the factors obtained in this study is interpretable and conceptually mean- ingful. Scale characteristics for scales reflecting the factors found in this study are reported in Table 2 along with their intercorrelations. The reliability coefficients were generally of suffi- cient magnitude to allow interpretation.

Descriptive results - managers The importance that Managers placed on the various cues is indexed by the findings presented in column C in Table 3, The Managers reported that the most important cues (the cues that they would attend to and allow to influence their behaviors) were those representing Negative Consequences transmitted by their supervisors and companies (i.e. being denied a raise) (3 = 5.92) and Indirect Negative Cues from co-workers (x = 5.46). Of lesser importance were Positive Comparisons -- Others (4.87), Positive Comparisons - Self (4.60) and Negative Task Mastery (4.92). Of least importance were Positive Co-worker cues (z = 4.51), consisting of both direct comments and indirect indicators from this source and events representing Positive

210 S. J. ASHFORD

Expressions (direct comments) from supervisors and the company (x = 4.52) and Direct Negative comments from co-workers (x = 4.48).

The role of experience in feedback cue use

A MANOVA testing for mean differences for the three experience-level groups on the 14 factors that make up the feedback environment scale was conducted to gain an understanding of how the experience-level groups differed. These results are presented with the means in Table 3. The Wilks Lambda for the overall equation was significant (F = 5.69; p<O.OOl) and so the univariate effects were examined. Significant univariate Fs were found for nine of the 14 dimen- sions. Specifically, Managers saw Positive Expressions, positive things that their superiors and company directly expressed to them, as a less important set of cues than did their less experienced counterparts (F = 3.59, p ~ 0 . 0 5 ) . In contrast, Business Graduate Students and Managers placed more importance on Positive Consequences meted out by the company of their supervisors (F = 4.45, p c 0.005) than did less experienced Undergraduates. Managers and Business Gradu- ate Students also placed less importance on Direct Negative cues from co-workers (F= 3.71; p < 0.05) and on their own negative observations about their task mastery (F = 10.00, p < 0.01) than did their less experienced counterparts. In contrast to these results, more experienced managers (Managers and Business Graduate Students) rated Negative Consequences, Positive Internalized Standards and Indirect Negative Co-worker cues as significantly more important than did the less experienced groups (Fs - 3.42, (p < 0.01), 4.07 (p < 0.05) and 14.84 (p < 0.01)), respectively. Managers also saw indirect Positive Recognition from superiors and the company as more important than did Undergraduates, but at about equal level as did Business Graduate Students. Finally, it should be noted that while responses on several feedback dimensions differed by level of experience, the variance explained was modest (az statistic (cf. Winer, 1971) ranged from 0.02 to 0.14).

A final analysis was conducted to contrast the results of this study with previous research on feedback sources. This research has considered four sources rather than the three examined by Herold and Parsons (1985) (e.g. Hanser and Muchinsky, 1978; Greller and Herold, 1975). To contrast the current data with these studies, four source scales were created by summing the importance ratings on all items relating to the company (a = 0.76), supervisor (a = 0.76), co-workers (a = 0.85) and self/task (a = 0.91) sources, respectively. The means for these scales are presented in Table 4(a). Following the researchers just cited, a 3 (experience levels) x 4 (source) between-within analysis of variance design with source as the repeated factor was performed (Table 4(b)). Experience-level group was treated as a between-subject factor in order to assess whether the magnitude and pattern of cue use from the various sources differed as a function of experience.

Given that within-subjects designs are especially sensitive to quite small intercell variations, F statistics tend to be inflated. However, the source effect was highly statistically significant (Fs = 59.04, p < 0.001). Further, an analysis of the amount of rating variance accounted for by this effect suggested that the result is of practical significance as well (R2 - 0.17). This source main effect indicates simply that individuals attach different levels of importance to the cues provided by different sources. The nonsignificant Group effect (F= 0.06, n.8.) suggests that the magnitude of the ratings did not significantly differ across the three groups. Of particular interest is that across all samples the cues provided by the Supervisor were rated most important, Company cues second, Selfmask cues third, and Co-worker cues were rated least important. In fact. a test for linear trend for Source, based on the importance attached to cues from each, also proved to be highly significant (p ~ 0 . 0 0 0 ) and explained 6 per cent of the rating

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212 S. 1. ASHFORD

Table 3. Results of multiple analysis of variance reporting differences in group means on cue importance ratings

A B C Business

Undergraduate graduate Business Feedback dimension students students managers F* 0

Company /supervisor cues 1. Positive consequences 5.02 5.42 5.38 4.45t 0.02 2. Positive expressions 4.49 4.73 4.52 3.59t 0.02 3. Indirect positive recognition 5.31 5.26 5.36 0.25 -0.01 4. Negative consequences 4.93 5.65 5.92 23.42 0.14 5. Negative expressions 5.29 5.40 5.33 0.36 0.00

Co-workrr cues 6. Positive co-workers 4.86 4.46 4.51 4.331 0.02

3.71t 0.02 7. Direct negative co-workers 4.80 5.02 4.48 8. Indirect negative co-workers 4.49 5.08 5.46 14.84$ 0.09

9. Positive comparison -others 4.97 4.9 1 4.87 0.17 -0.01 Self/task cues

10. Positive comparison - self 4.69 4.29 4.60 3.19t 0.02 1 1. Positive internalized standards 4.36 4.5 1 4.98 4.07t 0.02 12. Positive task mastery 5.13 5.01 5.11 0.26 -0.00 13. Negative comparisons - others 5.25 5.23 5.08 0.78 -0.00 14. Negative task mastery 5.52 5.10 4.92 l0.OOf. 0.06

* F tests are based on degrees of freedom of 2,295. t p < 0.01 sp<o.o01.

Table 4. (a) Means of cue importance ratings from difference sources

Business graduate Source Total sample Undergraduates students Managers

Company 5.15 5.07 5.17 5.23 Supervisor 5.22 5.11 5.29 5.27 Co-workers 4.65 4.67 4.69 4.60 Selfhask 4.94 5.06 4.88 4.89

(b) Repeated measures analysis of variance results

ss df M S F P R2

Group 0.18 2 0.09 0.06 ns 0.00 Between subjects effects

Within subjects effects Source 54.92 3 18.31 59.04 0.000 0.17 Linear 20.32 1 20.32 65.26 0 * 000 0.06 Residual 34.60 2 17.30 55.81 0.000

Interaction effects

Error within 258.63 834 0.31 Source x group 5.39 6 0.90 2.90 0.008 0.02

THE FEEDBACK ENVIRONMENT 213

variance. This linear trend indicates that respondents place importance on cues from the firm and superior most, then their own observations and finally cues from peers. The source X group interaction suggests that the pattern of cue use did vary across the three experience level groups. The data presented in Figure 1 suggests that this interaction, while significant (F = 2.90; p <0.008), was small. It appears mostly attributable to the undergraduates’ slight underemphasis on company and superior cues and their overemphasis on self/task cues relative to the other two groups.

4.5 5.i A = Under- graduates

0 % MBA‘s 4 .O f * Managers

Company Supervisor CO-workers Selfmask Figure 1. Plot of mean cue importance ratings from different sources

Discussion The results suggest several descriptive observations regarding how managers use the feedback environment. These observations should be useful in shaping a continued research agenda in this area. The Manager sample placed the most importance on the cues contained in Herold and Parsons’ (1985) Negative Consequences factor, followed by Indirect Negative Co-worker cues. They placed the least importance on Direct Negative, and all Positive, Co-worker cues. The emphasis given to Negative Consequences, along with the overall source mean for Supervisor and company sources presented in Table 4a, attest to the importance of the supervisor and the company as sources of feedback. This finding was corroborated by the open-ended data collected in Study 1 in which cues from the superior and company were mentioned most fre- quently. The Negative Consequence finding also suggests the importance and impact of vivid cues (e.g. rewards). Each of the cues on the Negative Consequences factor refers to a reward withdrawn or not given. Apparently respondents believed that these cues are salient and impact- ful. It is also interesting to note that while managers report beliefs that they would use these cues to regulate their subsequent behavior, these are not examples of what researchers would call ‘effective’ feedback. They are not specific. Moreover, employees’ understanding of what causes the withdrawal of (or the failure to receive) a reward such as a raise is subject to a variety of potential attribution processes. As Ashford (1989) noted, in using an observation of an event as a feedback cue, the actor must decide an event is, in fact, feedback, whether

214 S. J. ASHFORD

the feedback contained in the event was meant for him or her, and then what the message means. As such, there can be much slippage between intended message and received message when people are interpreting events as feedback. The messages that employees take from the types of cues described above, and how they use these cues to guide their behavior, is a fruitful area for further research.

Positive cues from co-workers were among the cues seen as least important by the managers. This finding was again corroborated by the open-ended item .analysis presented in Study I. Positive co-worker cues were the least frequently mentioned positive cue. These cues differ from the Negative Consequences cues in both the source and the sign. It may be that positive cues, in particular from a source with less legitimate power, do not provide much information and, therefore, are not seen as particularly valuable guides to subsequent behavior. It should be kept in mind, however, that these cues may be valuable in terms of the role they play in maintaining the manager’s self-confidence and feelings of efficacy regarding future perform- ances (Ashford and Cummings, 1983). Individuals have multiple purposes in reading the feedback environment (Ashford and Cummings, 1983). The sometimes quite different goals of maximizing self-esteem and generating accurate performance information may trigger different feedback- utilization patterns. In studying respondents’ cue use, researchers will need to specify carefully which purpose they want respondents to consider.

Finally it is also interesting to note the contrasting attention that managers believed they would pay to negative cues from co-workers depending on whether they provided directly (X = 4.48) or indirectly (3 = 5.46). It appears that with co-workers, managers trust the feedback contained in what they do rather than what they say. This may reflect a level of competition with co-workers for organizational rewards. One outcome of this competition may be that managers feel that direct comments from co-workers are not to be trusted.

The source ratings presented in Table 4a also add to our understanding of feedback environ- ment perceptions. These data suggest that when the issue is perceptions of the importance of cues (as opposed to availability of cues, as measured in prior research) respondents rated their superiors and the company as the most important feedback sources and themselves and their co-workers as much less relevant. This finding conflicts with previous research that argues that psychologically close sources are seen as most available and useful (cf. Hanser and Muchinsky, 1978)). It may be that the difference in goals studied in this research and previous (career advancement versus performance) may account for this result. Respondents may see cues from supervisors as most important in assessing their advancement potential while psycholo- gically close sources as more relevant for performance feedback.

This research also examined the role that experience in business settings might play in shaping an individual’s understanding of how to use the feedback environment. These results suggest that more managers rate different cues as more important to attend to and use as guides for their subsequent behavior than do their less experienced colleagues. The results presented in Table 2 indicate that more managers believe that they would place increased emphasis on things that the supervisor and company do, rather than on the things that they say, particularly in the area of rewards. With more experience, respondents also report that they would emphasize both positive and negative reward-related cues from supervisors and the company, though this tendency is more pronounced for the negative cues. The open-ended data presented in Study 1 support this finding but only for Positive Consequence cues- those with some experience (i.e. Business Graduate Student sample) believe that they would place more rather than less emphasis on positive cues from Superiors/Company when compared both to those with no work experience and those with significant managerial experience.

The belief expressed in the manager group (that they would emphasize negative cues) may

THE FEEDBACK ENVIRONMENT 215

reflect the differential saliency of these cues due to these managers’ position on a theoretical learning curve for managerial behavior. That is, when new to the profession, negative feedback may be an expected and frequent occurrence. As managers move up the learning curve with experience, the frequency with which they receive negative feedback may decrease. At this point, any negative cues that experienced managers detect may be particularly salient. As such, they may be seen as particularly important guides to their subsequent behavior. The differences between the three experience-level groups in this research may reflect this underlying theoretical mechanism.

The data also suggest that those with more experience believe they would emphasize the negative feedback contained in the way that co-workers act toward them (Indirect Negative Co-workers), and de-emphasize Positive Co-worker cues, either those given directly to them or said to others. These differences may reflect a shift in how peers are viewed as one gains organizational experience, a shift from viewing peers as trustworthy classmates who are trying to help them succeed to semi-competitors with whom they must judge carefully any data directly given.

Finally, the experience-level groups differed in their perceived emphasis on things that they themselves might notice about their own performance relative to others. Managers believed they would emphasize comparisons that they make to their own internalized positive standards and de-emphasize observations regarding poor performance (e.g. failing to meet performance standards). These results may reflect a tendency, learned by those with more experience, to emphasize the positive. They may also suggest one source of the self-assessment biases typically found in the literature (cf. Mabe and West, 1982).

These findings reveal a portrait of the more experienced user of the feedback environment as one who believe that he/she would: (1) Attend to and use cues from sources with legitimate power rather than those without; (2) look for things that those in power do, over things that they might say and (3) emphasize negative over positive feedback from powerful others. and (4) distrust positive feedback from co-workers but find indirect negative feedback from co- workers to be important. These observations, if substantiated by future studies, give us a sense of the lessons that experience teaches managers regarding how to ‘read’ the feedback cues around them. They also suggest some ideas to feedback system designers about how they might set up feedback systems that capitalize on managers’ natural proclivities.

While Study 2 gives us more information regarding individuals’ cue-use beliefs, it suffers from two limitations. First, its compatibility to past research is questionable given that it assessed cue use regarding a career-advancement rather than a performance goal. Second, while the three subsamples did differ in terms of their experience levels, they may also differ in other attributes, such as the type of work experience that they have had. Thus, differences found between the three groups may not reflect differences due to increased experience. Study 3 over- came each of these limitations. It asked a sample of managers in a single firm with varying levels of work experience to report on the cues they would use to assess their job performance. The instrument, methodology and analyses were similar to those used in Study 2.

Study 3 Method Sample and procedure One hundred and six mid-level executives in a large paper company located in the Northeast provided data for this study. These executives represented the following functional areas: Market-

216 S . J. ASHFORD

ing (21 per cent), production (26 per cent), research and development (6 per cent), human resources (9 per cent), and administrative functions (38 per cent). On the average the focal managers were 43 years old and had been with the company for 15 years. The managers had held their current jobs for an average of 4 years. The managers had been with their current company an average of 14 years. All subsamples were predominantly male (96 per cent) and white (94 per cent).

Procedure Two hundred managers mailed a questionnaire containing the measures for this research (54 per cent response rate). The managers were asked to describe their use of various cues in the feedback environment using the identical items given in Study 2. In Study 3, however, the items’ stem asked respondents to assume that the various cues had happened to them in their current position and to rate the importance of each cue for assessing their performance effectiveness.

Measures Feedback dimension scales were created based on the results of Study 2. Coefficient alpha reliabilities were computed for each scale. These are reported in Table 5 . Company tenure was assessed by asking managers to report the number of years and months they had worked in their current company.

Results Table 5 presents the scale characteristics for the feedback dimensions and their correlations with two experience variables - length of tenure in the current company and length of full-time work experience. The alpha coefficients for the feedback dimensions were all acceptable, ranging from 0.67 to 0.89.

The means for cue types suggest that managers perceived the positive and negative conse- quences meted out by the organization and superiors to be the most important cues for assessing performance (I = 5.84 and 6.07, respectively). Of lesser perceived importance was indirect positive recognition from superiors (I = 5.47) and negative task mastery (I = 5.46). Of least perceived importance for assessing performance were cues derived from positive and negative comparisons made with others (x = 4.69 and 5.20, respectively) and with one’s self at a previous time (x = 5.14).

The relationship with company tenure suggests that the more experience one has in the firm, the more importance one places on positive and negative consequences from the company and supervisor (r =0.19, p < 0.05 and r = 0.27, p < 0.01, respectively) and on indirect negative cues from coworkers (r = 0.20, p < 0.05). The more full-time work experience respondents had, the greater was their emphasis on negative consequences from the company and superiors (r = 0.13, p < 0. lo), indirect negative cues from coworkers (p < 0.25, p < 0.01) and positive com- parisons that they make with others ( I = 0.16, p < 0.05).

A within-subjects analysis of variance was also conducted on these data to assess the ordering of sources. As in Study 2, four source scales were created by summing the importance ratings on all items relating to the company (a =0.77), supervisor (a = 0.74, coworkers (a = 0.84) and selfltask (a = 0.91) sources, respectively. The means for these scales are: 5.70 (company); 5.69 (supervisor), 5.40 (coworkers), 5.19 (selfkask). A within-subjects ANOVA with source as the repeated factor was performed. These results are presented in Table 6.

The source effect was again highly significant (F = 29.27, p ~0.001). The effect accounts

THE FEEDBACK ENVIRONMENT 217

Table 5. Scale characteristics and correlations of feedback dimensions with experience

Company Feedback dimensions R S. D. a tenure

Companyhpervisor cues 1. Positive consequences 5.84 1.20 0.75 0.19* 2. Positive expressions 5.26 1.02 0.69 0.08 3. Indirect positive recognition 5.41 0.91 0.67 -0.00

5. Negative expressions 5.82 0.90 0.68 0.10 4. Negative consequences 6.07 0.95 0.83 0.27t

Co-worker cues 6. Positive co-workers 5.24 0.93 0.83 0.06

8. Indirect negative co-workers 5.61 1.17 0.68 0.20* 7. Direct negative co-workers 5.27 0.94 0.78 -0.05

Selfltask cues 9. Positive comparisons -others 4.69 I .24 0.89 -0.02

10. Positive comparisons -self 5.14 1.02 0.86 -0.03 1 1. Positive internalized standards 5.79 0.94 0.70 0.04 12. Positive task mastery 5.36 1.25 0.76 0.05 13. Negative comparisons - others 5.20 1.05 0.85 0.02 14. Negative task mastery 5.46 0.85 0.77 -0.02

* p < 0.05. tp<0.01.

for 22 per cent of rating variance. This rating suggests that individuals attach different levels of importance to the cues provided by different sources. A linear trend for source, based on the importance attached to cues from each was, once again, highly significant (p <0.001) and explained 19 per cent of the source variance. This linear trend suggests that respondents place most importance on superior and company cues, than on cues from the coworkers and finally on cues from themselves and the task. This trend is the opposite of that found in research on the perceived availability of cues (Greller and Herold 1975; Hanser and Muchinsky 1978).

General discussion Herold and Parsons’ (1985) paper advanced the study of feedback in organizations by examining the availability of specific feedback cues. Their research suggested a new research direction - that of examining how individuals use the various cues available in their work lives. The current paper provides an initial look at the cue-use question. It adds to prior research on feedback environment perceptions by (1) using specific feedback cues as the level of analysis,

Table 6. Repeated measured analysis of variance results ss df MS F P R2

Source 19.78 3 6.59 29.21 O.Oo0 0.22 Linear 17.55 1 17.55 76.30 O.OO0 0.19 Residual 2.23 2 1.11 4.83 0.05

Error within 70.96 315 0.23

218 S. J. ASHFORD

(2) investigating how people perceive themselves using the feedback environment by asking them to report on which cues they attend to and allow to influence their subsequent behavior, (3) showing how cue use varies with differing levels of organizational experience, and (4) assessing perceptions of cue use regarding both a performance and a career advancement goal. Study 3 also helps overcome a weakness in Study 2 by assessing managerial experience within a single organizational context. The qualitative and quantitative analyses reported here suggest several conclusions.

First, the results suggest that we may need to complicate our theoretical picture of the feedback environment. In contrast to several previous studies that asked respondents to rate sources according to the amount of feedback that they provided or the utility of the source itself, this study did not find a linear trend for sources based on their ‘psychological closeness’ to the rater (Greller and Herold, 1975) for either the career-advancement or the performance goal. Past studies revealed that psychologically close sources such as self and task provided more feedback than more distant sources such as the firm. In contrast, this research examined self-reports of which cues individuals believed were important guides for their behavior as they pursued the goals of career-advancement or effective performance. When those cues were summed to form source scales, the results revealed a linear trend that was opposite to that found previously.

The trend captured in the current study might be described as one of ‘adaptive relevance’. That is, given the desire to survive and succeed in organizations, feedback from those with the power to influence the attainment of these goals is the most relevant for the individual’s adaptation. Thus, it is not surprising the respondents believed that they would give special attention to the things that the company or a superior did (such as withholding a raise or not sending an employee to a special meeting). Feedback from co-workers, and an individual’s own observations, while readily available, were rated as less important. It may be that respon- dents believed that co-workers have far less ability to ensure a person’s place in an organization, and while one might prize one’s own behavior, if it’s not prized by others, one might not last long in an organization. Thus, while Greller and Herold (1975) and Hanser and Muchinsky (1978) found that psychologically close sources of feedback (e.g. the performer’s own obser- vations) provided a great deal of information to an individual, the results here suggest that when focused on performance and career-advancement, respondents believed that they would attend to and use these cues less frequently to guide subsequent behavior. They believed they would rely instead on the more infrequently available, but perhaps more adaptively relevant, cues from psychologically distant sources (e.g. the supervisor and company). Cues from these sources were perceived as the most important guides to behavior.

It should be noted too, that the present results were found with a methodology that used more specific stimuli than those used in previous research. We asked respondents to rate their use of specific cues whereas previous research asked for ratings of the availability of feedback from various sources. This too may have contributed to the differences in finding, lending credence to Herold and Parsons’s (1985) claim that there are advantages to pursuing a more specific cue-level portrait of the feedback process.

Study 3’s results, describing the perceived importance of various cues, corroborates many of Study 2’s findings. Specifically, both studies suggest the importance of positive and negative consequences mediated by the organization as cues relevant to assessing both performance and career-advancement. It appears that people perceive themselves as attending more to actions from this important feedback source than they do to direct expressions from this source. The greater importance placed on actions versus expressions is also reflected in the findings in both Studies 2 and 3 for negative cues from co-workers. Respondents perceived the things that

THE FEEDBACK ENVIRONMENT 219

their co-workers did that conveyed a negative message about their performance or career-advan- cement as more important than the things their co-workers said.

Findings for the two studies differ in the relative importance placed on co-workers and selfltask cues. While co-worker cues were seen as the least important in Study 2 (career-advancement goal) selfhask cues were seen as least important in this study (performance goal). It may be that co-workers are a more relevant source of feedback for the performance goal, perhaps due to task interdependence, than they are for the career-advancement goal.

In addition to describing perceptions of use of the feedback environment, this research also attempted to show how these perceptions might change as individuals gain managerial exper- ience. The idea was that, with experience, individuals gain tacit knowledge regarding which cues, from which sources, should be attended to and which can be ignored. While the findings for Study 3 found fewer relationships between cue use and experience, the relationships it did find, however, corroborate findings from Studies 1 and 2. Specifically, there was a positive relationship between length of company tenure, perceived importance of positive and negative consequences mediated by superiors and the company. Also consistent with Study 2, those with longer company tenure placed less importance on indirect negative cues from co-workers. There was no relationship between company tenure and perceived use of direct negative co- worker cues. Study 3 found no relationships between longer company tenure and the perceived importance of cues from selfkask. These results are in contrast to two findings from Study 2. It appears that selfkask cues are seen as no more or less valuable by those with differing levels of company tenure when assessing job performance while two selfltask cues, positive comparisons with internal standards and with the self were seen as more important for assessing career advancement by more experienced managers. It may be that with experience one gains tacit knowledge about the value of one’s own appraisals of one’s success at reaching the more nebulous goals of career-advancement and success (i.e. it’s important to believe in oneself). Such learning may be less relevant for the performance goal where there are more objective referents for success and failure.

These findings need to be considered in the context of the studies’ weaknesses. First, the samples are limited to only a subset of all possible occupations. In particular, blue-collar employees’ feedback-seeking behavior is not represented in this research. The sample is also limited in that it represents volunteers. The study can’t rule out the possibility that these volun- teers were more conscientious, loyal and so forth, than those not participating in the study. Second, the data are all self-reports. It’s not clear that these reports reflect managers’ cue use accurately. While the methodology employed here is a useful first step, more objective measures of cue would also be desirable. It should be recognized, however, that this future research will encounter thorny measurement problems. Most importantly, given the nature of the phenomena to be measured, self-reports may be the only form of valid data. It may be impossible to get objective data regarding which cues individuals use. After all, many of these cues represent fleeting observations that the manager might make in an instant. The data collected in Studies 2 and 3 also do not incorporate cues from customers and subordinates feedback cues, even though these were mentioned in the open-ended responses in Study 1. finally, as do most previous studies on feedback source utility, this study aggregates across various task types to get source utility ratings. In doing so, the complexity of type of task-- feedback relationship may be obscured.

Future research In addition to addressing the limitations outlined above, future research should also consider the consequences of cue use. That is, do differences in self-reports of the cues attended and

220 S. J . ASHFORD

used as guides to subsequent behavior affect managers’ success in their jobs or in their organiza- tions? Having established what sources of feedback are available for use and which ones are actually used, we need to take the next step and consider which ones best serve the consumer of this information. Moreover, this research should consider the mediating processes through which cue-use patterns affect outcomes. Do they increase learning and accuracy of performance perceptions, or do they increase self-confidence (even if the performer does not have an accurate sense of how others view his or her behavior)?

Researchers might also begin to develop theoretical explanations for the different patterns of cue use among practicing managers and between individuals with varying levels of experience. For example, why is it that practicing managers view rewards from company and supervisor as important feedback while placing less importance on cues from co workers? One explanation might be the ‘adaptive relevance’ of the sources and cues, as mentioned. The explicit development and testing of a theoretical model that explains patterns of cue use (based on adaptive relevance or some other explanation) is desirable.

Finally, as mentioned, these findings begin to give feedback system designers some insights into more efficient and effective system design. That is, once we gain some systematic knowledge regarding the cues employees emphasize, we can focus our feedback system design efforts on ensuring that these cues are available in the environment and are conveying the intended mes- sages. In this way, research on cue usage should provide a basis for better managing the feedback environment, for perhaps tailoring it to the usage tendencies of particular employees by making certain types of cues more available, and for constructing and communicating intentional mes- sages in a form that most likely will be attended to by employees. While the findings presented here require corroboration, they represent an important first look at individuals’ theories about how to use the feedback environment.

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222 S. J. ASHFORD

Appendix 1 A . Factor analysis ofpositive organizationalhpervisory items

Item Factor

1 2 3 4 ~ ~~ ~

Positive consequences The company giving me a raise 0.15 0.04 The company giving me a promotion 0.07 0.11 My supervisor recommending me for a promotion or raise 0.28

The company expressing pleasure with my performance 0.69 -0.04 The company proving me with favorable date re my

performance 0.82 0.09 My supervisor complimenting me on something I have done 0.71 0.23 Receiving a formal report of good performance 0.63 -0.03

0.16 Positive expressions

Indirect positive recognition My supervisor giving me a more responsible or challenging

assignment -0.02 0.81 My supervisor increasing my responsibilities -0.09 0.61 My supervisor giving me a more desirable job or

assignment 0.05 0.65 Items not included

The company selecting me to attend special meetings or seminars 0.25 0.15

My supervisor assigning me to special jobs 0.19 0.38 Percentage of common variance 32% 16Yo

B. Fact or analysis of negative organizationalhpervisory items Negative consequences

The company denying me a raise My supervisor not recommending me for a promotion My supervisor passing me over for a promotion or raise

The company passing me over for a promotion The company denying me a promotion

My supervisor letting me know that he or she is unhappy

My supervisor expressing anger or annoyance towards me The company communicating with me concerning my poor

My supervisor telling me that I have just done something

Receiting negative comments from ‘higher ups’ in the

recommendation

Negative expressions

with my work

performance

wrong

organization Percentage of common variance

0.75 0.05 0.75 0.915

0.74 0.26 0.84 0.05 0.82 0.06

0.14 0.76 0.03 0.75

0.34 0.50

0.00 0.68

0.15 0.75 37% 19%

0.71 0.64 0.50

0.42

0.13 0.01 0.39

0.11 0.05

0.13

0.38 0.28 11%

THE FEEDBACK ENVIRONMENT 223

C. Factor analysis of positive co-worker items Positive co-workers

My co-workers coming to me for advice My co-workers expressing approval of my work My co-workers liking to work with me My co-workers telling me that I am doing a good job My co-workers commenting favorably on something I have

Receiving a compliment from my co-workers done

Percentage of common variance

D. Factor analysis of negative co-worker items Direct negative co-workers

My co-workers telling me that I am not doing a good job My co-workers talking about my poor performance My co-workers complaining about my work to others My co-workers speaking poorly of my work My co-workers complaining that I am not doing my fair

share Indirect negative co-workers

My co-workers trying to avoid working with me My co-workers keeping me out of things My co-workers not seeking my opinion or advice

No co-workers complaining to me about minor aspects of Items not included

my work Percentage of common variance

E. Factor analysis of positive serf/task items Positive comparisons with others

Knowing that the quality of my work is higher than that

Knowing that the way I go about my duties is superior

Finding that I need less time to complete my duties than

Finding that under pressure I can do better work than

Finding that I can take on more responsibility than others

Knowing that my present performance is better than it used

Finding that certain parts of my job are becoming easier Finding that I am getting more done than I used to

of others

to most others

others

others

Positive comparisons with self

to be

0.49 0.79 0.65 0.87

0.78 0.74 60%

0.68 0.77 0.69 0.84

0.61

0.36 0.19 0.13

0.42 47%

0.79

0.83

0.67

0.80 0.69

0.28 0.16 0.22

Feeling that I am accomplishing more now than I used to 0.33

0.22 0.19 0.19 0.14

0.33

0.61 0.65 0.81

0.26 1 5%

0.13 0.10

0.14 0.04

0.36 -0.05

0.10 0.04 0.22 0.06

0.61 0.17 0.83 0.12 0.68 0.25 0.63 0.21

0.18

0.21

0.09

0.21 0.16

0.20 0.13 0.08 0.34

224 S. J. ASHFORD

Knowing that I can now perform or do things which previously were difficult for me

Positive internalized standards Finding that I am satisfying my own standard for ‘good

Knowing that what I am doing ‘feels right’

Feeling confident of being able to handle all aspects of my

Feeling that I have mastered the difficult parts of my job

Being able to stay ahead of my work

work’

Positive task mastery

job

Items not included

Percentage of common variance

F. Factor analysis of negative self/task items Negative comparisons with others

Noticing that others are able to get ahead of their work

Noticing that I do not do the job as well as others Finding that I cannot take on as many assignments or

Noticing that I am able to do less work than others Finding that under pressure I do not do as well as others

Failing to meet my own performance standards Noticing that certain things on my job always gives me

trouble Noticing that something I have done has not turned out

the way I wanted it to Being behind in my work Finding that I cannot finish my duties in the allotted time

Finding that I do not know my job well enough to be of

while I cannot

responsibilities as others

Negative task mastery

Items not included

much help to others who need assistance Percentage of common variance

0.09

0.02 0.05

0.33 0.27

0.37 45%

0.72 0.82

0.82 0.68 0.69

0.14

0.31

0.1 1 0.31 0.37

0.43 46%

0.79

0.25 0.27

0.34 0.35

0.38 15%

0.23 0.31

0.19 0.22 0.24

0.49

0.57

0.66 0.69 0.7 1

0.31 13%)

0.25

0.71 0.82

0.23 0.23

0.08 8%

0.17

0.19 0.15

0.69 0.69

0.31 5%