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Attributional style 1

Running Head: ATTRIBUTIONAL STYLE

Applied Psychology: An International Review (in press)

Attributional Style and Engagement/Disengagement Responses

in the Chinese Workforce

C. Harry Hui1, S. Tess Pak1, Siu-On Kwan2, & AnAn Chao1

1The University of Hong Kong

2City University of Hong Kong

Keywords: attributional style, pessimism, Chinese, internality, disengagement

Corresponding author: C. Harry Hui, Department of Psychology, University of Hong

Kong, Pokfulam, Hong Kong. Email: [email protected]; Phone: (852) 2859 2291; Fax:

(852) 2858 3518.

Authors’ Note

Order of authorship is arbitrary. All coauthors made equal contributions to this

paper. This research was supported by a Hong Kong Research Grant Council grant

HKU744608H to the corresponding author. We have benefited greatly from discussion

with Samuel Ho and his research team. We gratefully acknowledge Hannah Tai’s

assistance in the pilot study that generated items for the CMAS described here, and the

two reviewers for useful suggestions.


Abstract

Internal attribution for bad events, along with stable and global attributions, has been

regarded as a component of pessimism, a precursor of negative work outcomes. Most

evidence in support of this conceptualization has come from research conducted in

individualist cultures. We questioned if internal attribution has the same pessimistic

implication in a collectivist culture. Findings from two studies conducted on Chinese

employees supported our expectations that the stability and globality dimensions (but

not the internality dimension) would predict disengagement responses (such as quitting

and being neglectful at work) and lack of engagement responses (such as voicing

suggestions and being loyal to the organization). A reconceptualization of pessimism in

the workplace is therefore necessary. A dimensional, rather than a composite, scoring

method is proposed for maintaining the predictive and construct validities of

attributional style as an indicator of pessimism.


Attributional Style and Engagement/Disengagement Responses in the Chinese Workforce

Attributional style (AS) was introduced in Abramson, Seligman, and Teasdale’s

reformulated model of learned helplessness (1978) to account for people’s individual

differences in helplessness upon perceiving noncontingency between behavior and

outcomes. According to the theory, people who habitually explain bad events in terms of

stable, global and internal reasons rather than unstable, specific and external ones are

more likely to experience depression. Studies conducted with North American samples

have found that this pessimistic AS is related to low performance at school, sports, and

workplace (e.g., Clarke & Singh, 2005; Seligman & Schulman, 1986; Tiggemann,

Winefield, Goldney, & Winefield, 1992). Research with Chinese samples supports the

importance of AS for mental health (Anderson, 1999; Guo, Yao, Yi, Peng, & Yang, 2003;

Wei, Zhao, & Wu, 1999; Yu, Su, & Li, 2005). The extent to which a pessimistic AS is

associated with organizational outcomes in the Chinese workforce is, however, less

understood. In this regard, this paper has three aims. First, we shall make a theoretical

proposition that explaining bad events in terms of personal factors is not necessarily

pessimistic or maladaptive in the non-Western world. Second, we shall propose removing

internality from the pessimism composite score, and use only the stability and globality

dimensions for operationalizing pessimism. Third, we shall introduce an internet-friendly

measure of AS for use in personnel selection of Chinese employees.

Pessimistic Attributional Style and Its Correlates

Whether a bad event would result in helplessness depends on the kind of

attributions people make for the event (Abramson et al., 1978). Employees who explain


the bad event with stable causes (e.g., “the job is a dead end”) rather than unstable causes

(e.g., “the boss happened to be in a bad mood”) see it as permanent. Employees who feel

that the causes are global (e.g., “all job assignments are unfair”) rather than specific (e.g.

“this job assignment is unfair”) expect bad events to pervade across situations. Moreover,

the bad event is particularly damaging if the person attributes it to internal causes (e.g., “I

am slow”) rather than external causes (e.g., “the job is too demanding”). Sweeney,

Anderson and Bailey’s meta-analysis (1986) showed that attributing negative events to

internal, stable and global causes was associated with depression (average sample-

weighted effect sizes were .21, .20, and .22 respectively).

Over the years, research has uncovered links of pessimistic AS to outcomes in

many life domains. Pessimists were reported to have poorer health (Peterson, Seligman &

Valliant, 1988), poorer academic performance (Peterson & Barrett, 1987), poorer sports

performance (Seligman, Nolen-Hoeksema, Thornton, & Thornton, 1990), lower income

and shorter tenure (Seligman & Schulman, 1986), lower job satisfaction (Welbourne,

Eggerth, Hartley, Andrew, & Sanchez, 2007), and more relocation-related stress (Martin,

Leach, Norman, & Silvester, 2000).

Attributional Style among the Chinese

The negative correlates of stable and global ASs found in Western studies appear

to replicate in Chinese samples. Stable and global attributions about bad events predict

depression, anxiety, obsession and compulsion (see, e.g., Li, Qiu, & Wang, 2001). They

were associated with low self-efficacy, low sales performance, and high turnover

intention among Taiwanese insurance salespeople in underselling and rejection

situations (Chung, 2002).


As for the internality attributional dimension, findings are mixed. In one camp, Yu

et al. (2005) found a relationship between internality and low subjective well-being in

Chinese college students. Sweeney et al. (1986) found a positive association between

internality and depressive outcomes. In another camp, however, making external

attribution for real-life misfortunes was positively related to impairments in emotional

well-being and physical health (Tennen & Affleck, 1990). Guo et al. (2003) and Wei et

al. (1999) found that internality could not differentiate between the depressives and the

non-depressives. Given the sparse findings, it is difficult to affirm internality

attributional dimension as a component of pessimism for Chinese people. In the

following paragraphs, we shall advance a theoretical position that internality should be

separated from the pessimistic AS, at least for the Chinese.

Chinese Organizational Culture and Internality

Chinese societies value modesty, personal sacrifice, and group harmony (Hui,

Triandis, & Yee, 1991; Markus & Kitayama, 1991). Maintaining relationship harmony is

critical to self-esteem and life satisfaction (Kwan, Bond, & Singelis, 1997) as well as job

satisfaction (Hui, Yee, & Eastman, 1995). Standing taller than one’s peers and blaming

others for one’s own mishaps are inconsistent with this set of values. As Hung (2004)

suggested, these values have become part of the Chinese organizational culture.

One desirable behavior in this culture is self-effacement, which includes accepting

responsibilities for failure and not claiming credit for success. For example, Asians who

make self-effacing attributions for their team’s success are more likeable than those who

self-enhance (Muramoto, Yamaguchi, & Kim, 2009). Along the same line, Chen, Chan,

Bond, and Stewart (2006) demonstrated that depression is correlated with low self-


efficacy more strongly among individualist American adolescents than among collectivist

Chinese adolescents. Whereas in other cultures like the U.S., where independence and

self-efficacy are central to a person’s identity (Anderson, 1999; Markus & Kitayama,

1991), making internal attribution for bad events hurts self-esteem (Abramson et al.,

1978).

Therefore, for the Chinese (Fernandez, Carlson, Stepina, & Nicholson, 1997;

Oyserman, Coon, & Kemmelmeier, 2002), acknowledging the self as the cause for bad

events might not be as self-defeating as some Western studies (Horney, 1937; Sweeney et

al., 1986) may suggest. Although Chinese people who self-efface their ability might be

seen as less competent, they are more likeable among their peers (Bond, Leung, & Wan,

1982). Likewise, a self-blaming group member could actually win colleagues’ acceptance

in Chinese societies, because this person contributes to the preservation of group

harmony (Sun, 2004). It is hence likely that Chinese employees high in internality

attributional dimension will put things back in their right order rather than withdrawing

from the scene.

Chinese Interdependence and Social Support

In our dealing with difficulties, people around us can help by reassuring us of our

worth despite temporary setbacks, providing us with aid and services needed, and

offering us insightful advice (Trivedi et al., 2009). Blaming others as the culprit of our

hardship, however, would turn them into enemies (Tennen & Afflect, 1990). People who

initially want to offer us help may withdraw support if we insist on making external

attribution for our failures, instead of working out the inadequacies. This other-blaming


is particularly disturbing among the Chinese, because they value interdependence over

independence (Markus & Kitayama, 1991),

A Psychometric Consideration

Apart from the unique Chinese organizational culture, there is a psychometric

reason for doubting if internality should be given the same weight alongside stability and

globality in the measurement of AS. For example, Zhang and Wang (1989) found that

among Chinese, internality for bad events correlated only weakly with stability and

globality (rs=.14 and .09, respectively). Internality in Guo et al.’s (2003) study was

correlated at r=.15 with stability and r=.16 with globality. In neither study was internality

correlated with depression.

Assessing the Role of Internality in Pessimism in the Workplace

To test the above proposition that internality is not a component in the construct

of pessimistic AS, we would examine the criterion-related validity of AS as measured

with two different scoring approaches. The first is to aggregate the stability and globality

dimensions, to contrast with the internality dimension. Another is the aggregation of all

three dimensions to form the conventional composite of pessimistic AS. The results

would inform us of the role of internality in pessimism among the Chinese.

Disengagement and Engagement Responses to Problems in the Workplace

There are various ways employees deal with difficulties and problems intrinsic to

their jobs (e.g., firefighters to extinguish a fire) and those which are contextual (e.g.,

office politics). Some of those ways can be called disengagement responses. They include

exit and neglect (Farrell, 1983). Exit signifies the determination and subsequent action to

separate from the employer. Examples include thinking about resigning, asking for a job


transfer, looking for alternative employment, and actually leaving the job. Neglect

represents the passive psychological withdrawal from the employment relationship.

Examples include absenteeism, increased error rates and other subjective withdrawal

behaviors. Others are engagement responses of voice and loyalty. Voice represents an

attempt to repair a deteriorating work context. This is often done through discussing the

problem with a supervisor or making suggestions to improve. Loyalty is showing

confidence and giving continual support such as extra-role behaviors to the employer. It

involves reframing the problems into a temporary challenge (Rusbult, Farrell, Rogers, &

Mainou, 1988).

Following Abramson et al.’s (1978) reasoning, we predicted disengagement

responses to be more common among Chinese employees who see difficulties in the

workplace as caused by stable and global factors, such as “the arrogant attitude is cast in

every level of our management”. In contrast, we expected a null or negative correlation

between internal attributions for bad events and disengagement responses among the

Chinese employees. Explaining bad events in terms of personal causes (e.g., “the

company’s failing the bid is due in part to my incompetence”) reduces the need for in-

group quarrels to assign blames. Social support from colleagues is hence likely and may

even encourage one’s volitional stay in the company. In addition, internal attribution is

positively related to the perception of personal responsibility for relationship problems

(Lussier, Sabourin & Wright, 1993). Hence, people who make internal attributions for

unpleasant events at work are unlikely to exhibit exit and neglectful behavior any more

than those who make external attributions. It may even be possible that those who make


internal attributions are less likely to give up, compared with those who make external

attributions. Therefore,

Hypothesis 1a: The stability and globality attributional dimensions for bad events

will be positively correlated with disengagement responses,

Hypothesis 1b: The internality attributional dimension for bad events will be

negatively or not correlated with disengagement responses.

Engagement responses are constructive. Voice behavior is intended to solve

problems by communicating with the management (Turnley & Feldman, 1999). The

primary purpose is to express discontent (Kowalski, 1996), and to restore the

relationship. Loyalty signifies an optimistic, albeit passive, hope and trust in the

employer (Hagedoorn, Van Yperen, Van de Vliert, & Buunk, 1999; Rusbult et al., 1988).

Conceivably, if the employee believes that problems in the workplace stem from causes

that are stable and global (therefore pessimistic), voice and loyalty would be minimal.

Conversely, the tendency to make internal attributions for bad events does not

have to depress engagement responses. Even when the difficulties are perceived to have

emerged from within the self, such admission would not hurt the self-esteem of Chinese

employees. This is because making such attributions is in line with the normative values

of modesty and group harmony. Given that internal attributions result in a sense of

personal responsibility (Lussier et al., 1993), the behavioral consequence could even be

more voice and requests for improving the work situation. Therefore,

Hypothesis 2a: The stability and globality attributional dimensions for bad events

will be negatively correlated with engagement responses.

Hypothesis 2b: The internality attributional dimension will be positively or not


correlated with the engagement responses.

Chinese Measure of Attributional Style (CMAS)

Hitherto, the most widely used instrument to measure AS is the Seligman

Attributional Style Questionnaire (SASQ; Peterson, Semmel, Baeyer, Abramson,

Metalsky, & Seligman, 1982). Respondents provide one important cause to each of 12

hypothetical events, of which six are bad and the other six are good. They then indicate

on a 7-point scale the extent to which the cause is internal (versus external) to the self,

stable (versus unstable) across time, and global (versus specific) in nature. The SASQ

yields a composite negative score and a composite positive score, from summing across

the three attributional dimensions. The composite positive score, derived from items

about the six good events, indicates a positive (optimistic) AS (i.e., attributing good

events to internal, stable and global factors). The composite negative score, which is

more widely used, is derived from items about the six bad events. It denotes a pessimistic

AS (i.e., attributing bad events to internal, stable and global factors).

There are variations of the SASQ. These include, for example, an ASQ for

General Use (Dykema, Bergbower, Doctora, & Peterson, 1996), an Academic ASQ

(Peterson & Barrett, 1987), a Sports ASQ (Le Foll, Rascle, & Higgins, 2006), an

Occupational ASQ (Furnham, Sadka, & Brewin, 1992), and a Financial Services ASQ

(Proudfoot, Corr, Guest, & Gray, 2001). These measures are similar to each other in their

inclusion of globality, stability and internality, but differ by the domain of interest. Guo et

al. (2003) developed a Chinese ASQ for the diagnosis of depressives.

To facilitate assessment of AS in the general Chinese population, we developed an

internet-friendly CMAS. This was to overcome a limitation of the original ASQ and ones


derived from it, namely requiring the respondents to answer open-ended questions. We

first described four bad events: having a serious argument with a family member

(Appendix A), being cheated in a purchase, failing a school test or some job assignment,

and having a conflict with a friend or colleague. These events were written after those in

previous, validated instruments. For example, the first event was taken from Dykema et

al. (1996), and the third from Dykema et al. as well as Furnham et al. (1992). The fourth

was very similar to an event in both Dykema et al. and Peterson et al. (1982). Considering

that the measure would be administered online and therefore has to be easy to respond to,

we elicited from six working adults in a pilot study during the instrument development

phase some explanations for those bad events. These explanations were then edited into

six to eight explanations (plus the generic “other reasons”) for each event. Such design

would relieve the respondents from the burden of typing on a keyboard.

Response to the CMAS consists of two steps. First, the participants chose from the

list what they perceived as the causes for each of the four hypothetical bad events.

Multiple responses were allowed. (The actual choices were not scored.) In the second

step, the participants rated, on a 7-point Likert scale, whether those selected causes were

internal (versus external), stable (versus unstable), and global (versus specific).

Summary

In this investigation, we will examine if internality differs from stability and

globality in the prediction of employees’ responses. Second, we will compare two scoring

methods of AS to determine if internality should be scored separately from stability and

internality. Finally, we will evaluate the psychometric properties of our AS measure.

Study 1


Method

Participants

We recruited adults with an email sent through the alumni affairs office of a

university in South China. The invitation described the purpose of a Chinese-language

online survey on work performance, included a URL link, and promised a free-of-charge

personality assessment in return for participation. Within a fortnight, 649 individuals

completed the survey. After excluding 102 individuals who described themselves as a

non-employee (i.e., “student”, “unemployed”, “self-employed” and “retired”), we had

547 Chinese employees in our sample. There were 179 men (32.72%), 364 women

(66.54%), and 4 (.70%) who did not report their gender. The modal age group was 26-30

years of age (42.60%), followed by the 21-25 years of age (35.20%).

Chinese Measure of Attributional Style

A confirmatory factor analysis (CFA), following Hewitt, Foxcroft, and

MacDonald’s (2004) multitrait-multimethod (MTMM) approach, supported a 3-factor

structure (Table 1). Given that ratings on the three attributional dimensions were elicited

by common bad events (i.e., the same “methods”), the MTMM approach was more

appropriate than the traits-only or the methods-only CFA model. The data-model fit met

various benchmarks (Diamantopoulos & Siguaw, 2000; MacCallum, Browne, &

Sugawara, 1996): the likelihood ratio of Chi-square (χ2 =59.84) to degree of freedom

(df=39) was 1.53; root mean square error of approximation (RMSEA) = .03; goodness of

fit (GFI) = .98 and adjusted GFI = .96. Items loaded on the respective dimensions as

expected.

To address the question regarding the uniqueness of internality, we examined the


internal consistency of AS scored in three different ways: (a) by individual dimensions

of internality, stability and globality; (b) by internality and an average of stability and

globality, which was to be called composite-2 for the sake of easy reference; and (c) by

the composite-3, which was an average of all three dimensions. Cronbach’s alphas of

internality, stability, globality, composite-2, and composite-3 were .38, .58, .69, .73

and .71 respectively. Replicating prior research, internality had the lowest reliability.

Whilst stability and globality were correlated at r=.46 (p<.001, two-tailed), internality

was correlated weakly with stability (r=.15, p<.001, two-tailed) and moderately with

globality (r=.29, p<.001, two-tailed). The correlation between internality and composite-

2 was r=.26 (p<.001, two-tailed), indicating not much of an overlap.

Disengagement and Engagement Responses

Disengagement responses were measured with six items written after similar

scales used in previous studies (e.g., Rusbult et al., 1988). The items tapped exit

intention (e.g., “I want to quit the job as soon as possible”) and neglect (e.g., “I now

work listlessly”). Engagement responses were measured with another six items, on voice

(e.g., “I would make suggestions to my supervisor to improve the current situation”) and

loyalty (e.g., “I still believe that my present employer is virtuous”.) The disengagement

and engagement responses were reliable (Cronbach’s alphas = .86 and .75 respectively)

and negatively correlated (r=-.68, p<.001, two-tailed).

Results and Discussion

Disengagement Responses

Disengagement responses correlated positively only with stability and globality,

but not with internality (Table 2). Regression analyses showed that AS as three separate


dimensions (i.e., scored using the dimensional scoring model) explained 2.40% (ΔR2,

p<.01, two-tailed) of the variance of disengagement responses, after controlling for

gender (n.s.) and age (β= -.15, p<.001, two-tailed). The effect came mainly from

globality (β= .11, p<.05, two-tailed). Internality and stability were unnecessary for the

prediction. Employees who explained bad events in terms of global causes were more

likely to disengage themselves from the organization. Therefore, H1a and H1b were

largely supported.

The internality and composite-2 scoring model explained 2.40% of the variance

(ΔR2, p<.001, two-tailed) after the demographic variables have been controlled for,

while the composite-3 scoring model (β=.14, p<.001, two-tailed) explained only 1.80%

of the variance (∆R2, p<.001, two-tailed). When compared with the other two scoring

models, the composite-3 (which treats internality as a component of pessimism) is the

least effective. It has the lowest criterion-related validity, and offers little information

about how AS would specifically impact on our disengagement responses. The

inferiority remained even when the number of predictors was considered by comparing

the adjusted variances across the models.

Engagement Responses

Consistent with H2a and H2b, stability and globality were correlated negatively

with engagement responses, while internality was not (Table 2). Regression analyses

(Table 3) showed that the dimensional model (i.e., consisting of three separate AS

dimensions) explained 2% (ΔR2, p<.05, two-tailed) of the variance of engagement

responses, after the effect of demographics (n.s.) had been controlled for. Closer

inspection shows that internality and globality did not predict. Only stability was


negatively related to engagement responses (β= -.11, p<.05, two-tailed). Employees who

explained bad events with stable causes were less likely to voice or stay loyal.

The internality and composite-2 model explained 1.90% variance (ΔR2, p<.001,

two-tailed) of engagement responses. This is comparable to that obtained in the

dimensional model. Internality was again redundant but there was a slightly increased

effect size of globality when joined with stability (β= -.14, p<.01, two-tailed). The

composite-3 (β=-.11, p<.01, two-tailed) explained only 1.20% variance (ΔR2, p<.01,

two-tailed) of engagement responses.

In sum, AS scored with these different scoring models did predict disengagement

and engagement responses (Table 3), with the predictive validity for the dimensional

model being slightly stronger. Consistent with prior research, attributing bad events to

stable and global causes was related to negative outcomes. Internality, however, did not

appear to be an integral component of pessimism. Furthermore, although not statistically

significant, the relationship of internality with the outcomes was in a direction opposite

to that found for stability and globality. As low reliability could be an alternative

explanation of why internality failed to be as predictive as the other two, we decided to

improve and retest the CMAS in another study, with a sample drawn from a different

working population.

Study 2

Method

Participants

Data were collected as part of a larger project. We emailed an invitation to

members of a Chinese professional society of insurance underwriters. The email stated


the purpose of developing a selection instrument for the insurance industry, and told

recipients that their participation would be voluntary and anonymous. A total of 497

individuals provided us with complete data on the internet. There were 179 men (36%),

258 women (51.90%), and 60 who did not disclose their gender (12.10%). Slightly over

half (55.70%) were sales agents, while the rest were sales managers. About 17.30% had

been with their companies for less than three years, 24.40% for 3 to 6 years, 19.80% for

7 to 10 years, and 38.40% for over 10 years. About 14.70% were aged 30 or below,

32.80% from 31 to 40, and 44.50% from 41 to 50. People above 50 accounted for 8% of

the sample.

Measures

To improve on the reliability of the CMAS dimensions, we added one scenario to

the measure: not being able to complete a job assignment on time. CFA of the five-

scenario CMAS by the MTMM approach can be found in Table 1. The likelihood ratio

of Chi-square (χ2 =221.72) to degree of freedom (df=72) was 3.08. This MTMM model

provides a good fit for the data: GFI = .94, AGFI = .90, RMSEA = .07. The three items

on the fifth scenario have significant loadings on their respective dimensions.

Cronbach’s alphas of internality, stability, globality, composite-2, and the

composite-3 were .58, .76, .80, .81 and .77 respectively (Table 4). Stability and globality

were correlated at r=.36 (p<.001, two-tailed), and internality was also correlated with

globality at r=.25 (p<.001, two-tailed). However, the correlation between internality and

stability was non-significant. The correlation between composite-2 and internality was

again relatively weak (r=.16, p<.001, two-tailed), despite lower measurement error this

time.


Cronbach’s alphas of disengagement and engagement responses were .79 and .76

respectively. The two scales were correlated negatively at r=-.58 (p<.001, two-tailed),

similar to what we found in the previous study.

Results and Discussion

Disengagement Responses

As shown in Table 4, stability and globality were positively correlated with

disengagement responses. There was a negative correlation (r = -.17, p < .001) between

internality and disengagement. Together, the three individual AS dimensions explained

5.20% (ΔR2, p<.001, two-tailed) of the variance in disengagement responses, after the

effects of gender (β=.11, p<.05, two-tailed), age (β=-.13, p<.05, two-tailed), rank (n.s.)

and tenure (n.s.) have been controlled for (Table 5). Internality negatively predicted

disengagement responses (β=-.19, p<.001, two-tailed). Globality positively predicted

disengagement responses (β=.15, p<.01, two-tailed) while stability showed no effect.

Insurance salespersons who explained bad events with external and global causes were

more likely to withdraw from their organization. In other words, internality and globality

exerted opposite effects. H1a and H1b were supported.

Engagement Responses

Stability and globality were negatively correlated with engagement responses

(Table 4). The dimensional model of AS explained 6.40% of the variance (ΔR2, p<.001,

two-tailed) of engagement responses, after the effects of gender (β=-.15, p<.001, two-

tailed), age (n.s.), rank (β=.11, p<.05, two-tailed) and tenure (n.s.) had been controlled

for (Table 5). Internality positively predicted engagement responses (β=.14, p<.05, two-

tailed) while stability negatively predicted the same (β=-.18, p<.001, two-tailed).


Insurance salespersons who explained bad events in terms of internal and unstable

causes would be more likely to voice their suggestions and stay loyal with the

organization. Internality was associated with engagement responses and not with

pessimism. Once again, H2a & H2b were supported.

Scoring Models

In the internality-composite-2 model, internality negatively predicted

disengagement responses (β=-.18, p<.001, two-tailed), while composite-2, as an

aggregate of stability and globality, predicted positively (β=.17, p<.001, two-tailed).

However, the composite-3 model did not predict disengagement responses at all. This

latter result can be attributed to the opposing effects of internality and composite-2, each

of comparable magnitude, cancelling out each other. Table 5 summarizes these results.

For engagement responses, AS measured with the internality-composite-2 model

explained 6.10% (ΔR2, p<.001, two-tailed) of the variance. Internality (β=.15, p<.001,

two-tailed) remained predictive of this outcome. Composite-2 performed better than

stability alone (β=.22, p<.001, two-tailed). However, composite-3 (β=-.12, p<.001, two-

tailed) could explain only 1.5% (ΔR2, p<.01, two-tailed) of the variance.

General Discussion

In our two studies, we found that among Chinese employees the internality

dimension of pessimistic AS, unlike the stability and globality dimensions, was neither

positively related to disengagement responses nor negatively related to engagement

responses in the workplace, as would have been expected on the basis of previous

findings in the West. Aggregating the internality, stability and globablity dimensions

into one incoherent construct of pessimistic AS would not only harm the predictive


validity but may also erroneously frame internality as an undesirable trait, at least among

Chinese employees. In short, the present investigation has three contributions.

First, we showed that making an internal attribution for bad events is not

necessarily maladaptive, and argued for the removal of internality from the pessimism

construct. Our proposition is consistent with a meta-analysis that showed an effect size

of .31 between externality and depression from 97 studies (Benassi, Sweeney, & Dufour,

1988). It is also consistent with findings that personal autonomy and self-determination

predict self-esteem (Deci & Ryan, 1985a, 1985b), adjustment (Koestner, Bernieri, &

Zuckerman, 1992; Philippe & Vallerand, 2008; Sheldon & Kasser, 1995), and

perseverance (e.g., Koestner, Otis, Powers, Pelletier, & Gagnon, 2008; Zhou, Ma, &

Deci, 2009).

Even within a North American culture, self-blame can be potentially beneficial.

Janoff-Bulman (1979) differentiated people into the characterological and behavioral

types. The former blames on one’s nonmodifiable character (“… for the kind of person

you are,” p.1803). This is a maladaptive mindset towards personal deservingness of

misfortune. The latter, behavioral type blames on the person’s own faulty but modifiable

behavior (“… for what you did,” p.1803). It implies controllability of the cause and

avoidability of recurrence. In other words, self-blame may be conducive to adaptation if

the attributor focuses on a personal, yet unstable and controllable cause. (Our measure,

however, did not include this subtle distinction.).

Furthermore, in a collectivist society like the Chinese, where modesty and group

harmony are valued, employees who make internal attribution for bad events preserve

harmonious working relationships and communicate humbleness. These individuals are


just as likely as coworkers with an external AS to voice and be loyal. At the same time,

they are not any more likely to show unproductive and disengagement responses such as

exit and neglect. This is not the pattern of correlation we had expected for pessimism.

Thus, for Chinese employees, pessimism is better conceptualized as viewing causes that

have led to failures as pervasive (global) and unchangeable (stable), rather than as

originating from oneself.

A second contribution of this investigation is methodological. Our findings

support the use of individual attributional dimensions over the conventional composite

scoring method. We showed that the three attributional dimensions when entered

separately into the regression model have higher predictive validity than the composite

AS score in predicting some work-related outcomes. We favor the dimensional scoring

approach, as it allows researchers to uncover any interactive relationships that may exist

among the attributional dimensions (Abramson, Dykman, & Needles, 1991; Janoff-

Bulman, 1979), and to appreciate the uniqueness of each dimension (Carver, 1989).

Third, an internet-friendly measure of AS is now available. The CMAS only

requires participants to choose from a list of common explanations, thus minimizing

cognitive demands on the respondents and eliminating the keyboard task. This procedure

would make the instrument easier for administration on a large scale and on the internet.

Apart from these contributions, some caveats and research implication have to be

mentioned. First, the AS measure in the present investigation includes only bad events.

Although some (e.g., Xenikou, Furnham, & McCarrey, 1997) have suggested that bad

events may be sufficient for tapping pessimism, future research could explore if

including good events in the measure may enhance the validity of the CMAS. Second,


there may be reasons to suspect common method variance between the predictor and the

criterion variables, as all data were collected at a single point in time (Podsakoff,

MacKenzie, Lee, & Poksakoff, 2003). Fortunately, because of the non-transparency of

the CMAS, the problem of demand characteristics can be partially avoided. Third, our

two samples may not be representative of the entire Chinese workforce, despite the

Study 1 sample was fairly heterogeneous in occupation. For better generalizability,

future research should target Chinese from other locations and occupations, and perhaps

even non-Chinese Asians.

The effect size of AS predictors in applied research is often small to medium by

Cohen’s (1988) standard. For instance, AS for negative events was correlated with

performance outcomes at r=-.11 in retail salespeople (Silvester, Patterson, & Ferguson,

2003) and r=-.18 in life insurance agents (Seligman & Schulman, 1986). Similarly, AS

for positive events correlated with performance ratings at r=.21 (Silvester, et al., 2003),

with problem-solving coping at r=.21 (Welbourne, Eggerth, Hartley, Andrew & Sanchez,

2007), and with intention to quit at r=.24, (Proudfoot et al., 2001). The present

investigation is no exception.

With regards to practical implications, we encourage organizations to take into

account Chinese job candidates’ AS when making a personnel decision. Given the large

size of the Chinese workforce in the global economy, even a small change in employee

turnover, apathy, or organizational commitment could have considerable financial

implications for the organizations.


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Appendix A

Instruction: Please imagine as vividly as possible that if the following events had

occurred to you, what would have been the major cause(s)? Please indicate by checking

on the given cause(s). Then please proceed to answer three follow-up questions

regarding your chosen explanatory options.

Event 1. …having a serious argument with a family member.

A. Please select from below the important reasons that caused the above event (you

may choose more than one).

i personality problems

ii emotional problems

iii influence of past experience or feelings

iv being treated unfairly

v communication problems

vi misunderstandings

vii discrepancies in mutual expectations

viii other reasons

B. Is/are your cause(s) you selected due to something about you or to something

about other people or circumstances?

C. In the future when facing a similar event, will this/these cause(s) again be present?

D. Is/are the cause(s) something that had influence(s) on only the above event or

does it/do they also influence other areas of your life?


Table 1 Measurement Model of Variables in Chinese Measure of Attributional Style

Study 1 (N=547) Study 2 (N=497)

Measure and Variable Factor

Loading

R2

Uniqueness

Factor Loading

R2

Uniqueness

Internality int_1 .41 .17 .83 .22 .05 .95 int_2 .16 .03 .97 .43 .19 .81 int_3 .37 .14 .86 .61 .37 .63 int_4 .50 .25 .75 .45 .20 .80 int_5 - - - .61 .37 .63 Stability stab_1 .38 .14 .86 .51 .26 .74 stab_2 .58 .34 .66 .58 .33 .67 stab_3 .69 .48 .52 .72 .51 .49 stab_4 .36 .13 .87 .63 .39 .61 stab_5 - - - .70 .49 .51 Globality glob_1 .52 .27 .73 .50 .25 .75


glob_2 .55 .30 .70 .60 .36 .64 glob_3 .72 .52 .48 .73 .53 .47 glob_4 .64 .41 .59 .69 .48 .52 glob_5 - - - .80 .64 .36 Fitness Index Chi-square (df, p) 59.83 (39, .02) 221.72 (72, .00) GFI; AGFI .98; .96 .94; .90 RMSEA (90% C. I.) .03 (.01; .05) .07 (.06; .08)

Note. Estimation by maximum likelihood, LISREL 8.52. Error covariance values among variables were freed following the multitrait-multimethod approach (Hewitt,

Foxcroft, and MacDonald, 2004).


Table 2 Means, Standard Deviations, Reliabilities and Correlations of Variables in Study 1 (n=540 after listwise deletion) Correlation with Chinese Attributional Style

Mean SDReliability

(Cronbach’s α) Internality Stability Globality Composite-2

Composite-3

Internality 4.19 .84 .38 - .15 *** .29 *** .26 *** .61 *** Stability 4.49 .88 .58 - - .46 *** .81 *** .72 *** Globality 3.91 1.14 .69 - - - .89 *** .85 *** Composite-2 4.20 .87 .73 - - - - .93 *** Composite-3 4.20 .70 .71 - - - - - Gendera 1.67 .47 N/A .12 ** .06 ns .07 ns .08 ns .11 ** Ageb 3.01 1.09 N/A -.09 * -.07 ns -.08 ns -.09 * -.11 * Dependent Variable Disengagement responses 2.55 .85 .86 .04 ns .13 ** .16 *** .17 *** .16 *** Engagement responses 3.47 .65 .75 -.02 ns -.14 ** -.11 ** -.15 ** -.13 ** Dependent Variable, Controlled for Age and Gender (df=538) Disengagement responses .02 ns .12 ** .14 *** .16 *** .14 ** Engagement responses .00 ns -.13 ** -.10 * -.13 ** -.11 **


Note. Composite-2 is an average of Stability and Globality. Composite-3 is an average of Internality, Stability and Globality. aGender: 1=male; 2=female. bAge: 20 or below=1; 21-

25=2; 26-30=3; 31-35=4; 36-40=5; 41-45=6; 46-50=7; 51 or above=8. ***p<.001, **p<.01,*p<.05, two-tailed. ns non-significant.


Table 3

Summary of Regression Results Predicting Disengagement and Engagement Responses in Study 1 (n=540 after listwise deletion)

Disengagement Responses Engagement Responses

B SE B β B SE B β

By Attributional Style Dimensions

Step 1 Gender .08 .08 .05 ns -.09 .06 -.07 ns

Age -.12 .03 -.15 *** .04 .03 .07 ns

Step 2 Internality -.02 .05 -.02 ns .02 .03 .03 ns

Stability .07 .05 .07 ns -.08 .04 -.11 *

Globality .09 .04 .11 * -.03 .03 -.06 ns

R2 for Step 1 .03 .01

△R2 for Step 2 .02 ** .02 *

Final R2 (η2) .06 .03

Adjusted R2 (η2) .05 .02

F(5, 536)=6.24*** F(5, 536)=3.60**

By Internality and Composite-2

Step 1 Gender .08 .08 .05 ns -.10 .06 -.07 ns

Age -.12 .03 -.15 *** .04 .03 .07 ns


Step 2 Internality -.02 .04 -.02 ns .02 .03 .03 ns

Composite-2 .16 .04 .16 *** -.11 .03 -.14 **

R2 for Step 1 .03 .01

△R2 for Step 2 .02 *** .02 **

Final R2 (η2) .06 .03


F(4, 537)=7.79*** F(4, 537)=4.33**

By Composite-3

Step 1 Gender .07 .08 .04 ns -.09 .06 -.06 ns

Age -.12 .03 -.15 *** .04 .03 .06 ns

Step 2 Composite-3 .16 .05 .14 ** -.10 .04 -.11 **

R2 for Step 1 .03 .01

△R2 for Step 2 .02 *** .01 **

Final R2 (η2) .05 .03


F(3, 538)=9.25*** F(3, 538)=4.61**

Note. Coefficients shown here are from the final model. Intercepts are omitted. Composite-2 is an average of Stability and Globality. Composite-3 is an average

of Internality, Stability and Globality. ***p<.001, **p<.01, *p<.01, two-tailed. ns=non-significant.


Table 4

Means, Standard Deviations, Reliabilities and Correlations of Study Variables in Study 2 (n=434 after listwise deletion)

Correlation with Chinese Attributional Style

Mean SD Reliability

(Cronbach’s α) Internality Stability Globality Composite-2 Composite-3

Internality 4.58 .90 .58 - .01 ns .25 *** .16 *** .55 ***

Stability 3.95 1.07 .76 - - .36 *** .80 *** .68 ***

Globality 3.70 1.21 .80 - - - .85 *** .82 ***

Composite-2 3.83 .94 .81 - - - - .92 ***

Composite-3 4.08 .74 .77 - - - - -

Gendera 1.59 .49 NA -.20 *** .01 ns -.03 ns -.01 ns -.09 ns

Ageb 5.32 1.63 NA -.04 ns -.06 ns -.12 * -.11 * -.11 *

Rankc 1.43 .50 NA .02 ns .01 ns -.04 ns -.02 ns -.01 ns

Tenured 4.82 2.10 NA .05 ns -.06 ns -.14 ** -.12 ** -.08 ns

Dependent Variable

Disengagement responses

1.73 .58 .79 -.17 *** .11 * .13 ** .15 ** .06 ns

Engagement responses

3.83 .53 .76 .15 ** -.22 *** -.14 *** -.21 *** -.12 *


Dependent Variable, Controlled for Gender, Age, Rank, and Tenure (df=428)

Disengagement responses

-.15 *** .11 * .12 * .14 *** .06 ns

Engagement responses

.12 * -.22 *** -.12 * -.20 *** -.13 *

Note. Composite-2 is an average of Stability and Globality. Composite-3 is an average of Internality, Stability and Globality. aGender: 1=male; 2=female. bAge: 20 or below=1;

21-25=2; 26-30=3; 31-35=4; 36-40=5; 41-45=6; 46-50=7; 51 or above=8. cRank: agent=1; manager=2. dTenure: below 1 year=1; 1-2 years=2; 3-4 years=3; 5-6 years=4; 7-8

years=5; 9-10 years=6; above 10 years=7. ***p<.001, **p<.01,*p<.05, two-tailed. ns non-significant.


Table 5 Summary of Regression Results Predicting Disengagement Response and Engagement Response in Study 2 (n=434 after listwise deletion)

Disengagement Responses Engagement Responses

B SE B β B SE B β By Attributional Style Dimensions Step 1 Gender .13 .06 .11 * -.16 .05 -.15 **

Age -.05 .02 -.13 * .01 .02 .05 ns

Rank -.10 .06 -.09 ns .12 .05 .11 *

Tenure .02 .02 .06 ns .01 .01 .06 ns

Step 2 Internality -.12 .03 -.19 *** .08 .03 .14 **

Stability .03 .03 .06 ns -.09 .02 -.18 ***

Globality .07 .03 .15 ** -.04 .02 -.09 ns

R2 for Step 1 .04 .07 △R2 for Step 2 .05 *** .06 *** Final R2 (η2) .10 .13 Adjusted R2 (η2) .08 .12 F(7, 426)=6.40*** F(7, 426)=9.19***

By Internality and Composite-2 Step 1 Gender .13 .06 .11 * -.16 .05 -.15 **

Age -.05 .02 -.13 * .01 .02 .05 ns


Rank -.10 .06 -.09 ns .12 .05 .11 *

Tenure .02 .02 .06 ns .01 .01 .05 ns

Step 2 Internality -.12 .03 -.18 *** .09 .03 .15 **

Composite-2 .10 .03 .17 *** -.13 .03 -.22 ***

R2 for Step 1 .04 .07 △R2 for Step 2 .05 *** .06 *** Final R2 (η2) .09 .13 Adjusted R2 (η2) .08 .12 F(6, 427)=7.31*** F(6, 427)=1.44***

By Composite-3 Step 1 Gender .18 .06 .15 ** -.20 .05 -.18 ***

Age -.04 .02 -.12 * .01 .02 .03 ns

Rank -.10 .06 -.08 ns .11 .05 .10 *

Tenure .01 .02 .03 ns .02 .01 .08 ns

Step 2 Composite-3 .05 .04 .06 ns -.09 .03 -.12 **

R2 for Step 1 .04 .07 △R2 for Step 2 .00 ns .02 ** Final R2 (η2) .04 .08 Adjusted R2 (η2) .03 .07 F(5, 428)=4.18*** F(5, 428)=7.66***


Note. Coefficients shown here are from the final model. Intercepts are omitted. Composite-2 is an average of Stability and Globality. Composite-3 is an average of Internality, Stability and Globality. ***p<.001, **p<.01, *p<.01, two-tailed. ns=non-significant.

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