The effects of transformational leadership on the distinct aspects development of social identity

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The online version of this article can be found at: DOI: 10.1177/1368430212454926

2013 16: 87

Group Processes Intergroup Relations

Jyun-Wei Huang

social identity

The effects of transformational leadership on the distinct aspects development of

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Group Processes & Intergroup Relations 16(1) 87 –104 © The Author(s) 2013 Reprints and permission: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/1368430212454926 gpir.sagepub.com Article G P I R

Group Processes &

Intergroup Relations

Over the past two decades, organizational researchers have paid considerable attention to the construction of transformational leadership (TFL) (Bass, 1999), which is defined as the extent to which a leader employs idealized influence, inspirational motivation, intellectual stimulation, and individual consideration in order to direct followers into a higher level of thinking (Bass, 1990). The positive association between TFL and follower behaviors is well documented (e.g., Bono

& Judge, 2003; Shamir, House, & Arthur, 1993); however, the mechanism and process by which TFL exerts its influence on followers’ social identification via its work organization have not

Article

1National Chiao Tung University, Taiwan

Corresponding author:

Jyun-Wei Huang, 4F, 118, Sec. 1, Jhongsiao W. Rd., Taipei, 10044, Taiwan.

Email: ulwwulww@gmail.com

The effects of transformational

leadership on the distinct aspects

development of social identity

Jyun-Wei Huang

1

Abstract

Although transformational leadership (TFL) has been extensively investigated, the mechanism and process by which perceived TFL exerts its influence on followers’ social identification development behaviors is relatively unexplored. Accordingly, this study proposes a latent growth model based on social identity theory to address these influences. To test the proposed model, data were collected by surveying 1,501 employees of R&D departments at Taiwanese IT firms at multiple points in time over a 10-month period. Therein, we found that as employees perceived more TFL at Time 1, they were more likely to show increases in social identification development behaviors over time. Further, increases in social identification development behaviors demonstrate their positive relationship with task performance and organizational citizenship development behaviors over time. My empirical model confirms all of my proposed hypotheses, and these findings highlight that the potential dynamic consequences of organization behaviors can lead to employee career development.

Keywords

latent growth model, organizational citizenship behavior, social identity, task performance, transformational leadership

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been adequately addressed in the literature (Avolio, Zhu, Koh, & Bhatia, 2004; Bono & Judge, 2003; Pittinsky, & Welle, 2008). Therefore, I propose a different mechanism to explain the effects of TFL: One that is rooted not in the per-ceptions of the leader or self, but, instead, is rooted in how TFL elicits employees’ social iden-tification development behaviors over time. One of the powerful influences a leader can have on followers is the “management of meaning” (Smircich & Morgan, 1982), wherein leaders define and shape the “reality” in which followers work. Although previous studies have proposed that leadership may be treated as a factor in the promotion of social identification (e.g., Hogg, Otten & Hinkle, 2004; van Knippenberg & Hogg, 2003), relatively little attention has been devoted to the question of how perceived TFL influences social identification. The first goal of this study is to address how the effects of perceived TFL may influence the development behaviors (change) of social identification among employees at work group, and how these development behaviors subsequently influence task performance (TP) and organizational citizenship behavior (OCB) development behaviors of employees over time.

The emphasis on “development behaviors” in the previous statement denotes a serious short-coming in the organizational behaviors literature (Bentein, Vandenberg, Vandenberghe, & Stinglhambe, 2005). That is, with rare exceptions (Lance, Vandenberg, & Self, 2000), and even in the case of previous carefully conducted longitu-dinal studies, the emotional component of social identity (i.e., affective commitment) has been treated as a static variable (i.e., one point in time) in the majority of studies (e.g., Beck & Wilson, 2000; Ray & Mackie, 2009; Rink & Ellemers, 2006, 2010). For example, they employed cross-section data with repeated measures through analysis of variance to test relationships between variables rather than a change perspective of con-struct. We examine this concern in the present study to yield a wealth of knowledge regarding social identification constructs with their ante-cedents and consequences from a change per-spective over time. Until now, the fundamental

premise that employees may adjust their level of identification (e.g., emotional component of social identity) as a function of the way they interpret and make sense of their work context (Vandenberg & Self, 1993) has remained rela-tively unexamined. The change in social identifi-cation that underlies this question is not trivial because the notion of individual changes in iden-tification is also fundamental to other prominent theories, such as socialization (e.g., Feldman, 1976) and attraction-selection-attrition (e.g., Schneider, 1975). The implication is that change in identification is relevant for these models (the-ories) of long-term individual productivity. However, the change in social identification is also crucial for practices because practitioners have long been concerned with employees’ iden-tification to the organization in light of economic events, such as mergers, acquisitions, or layoffs, all of which change the nature of the relationship between employees and the organization (Brockner, Tyler, & Cooper-Schneider, 1992; Mottola, Bachman, Gaertner, & Dovidio, 1997). The practical implication is that perhaps some inspiration or stimulus (e.g., TFL) may be imple-mented to enhance the positive changes in identi-fication to increase organization effectiveness.

The social identity theory that Tajfel (1978, p. 63) originally described is a unique and important motivation: “Part of an individual’s self-concept which derives from his knowledge of his mem-bership of a social group (or groups) together with the value and emotional significance attached to that membership”. Although social identifica-tion plays a key role in social identity theory, rela-tively little attention has been devoted to the question of how exactly this concept should be defined theoretically, or how it can be measured empirically (Ellemers, Kortekaas, & Ouwerkerk, 1999). A significant contribution to the social identity theory is an examination of the multidi-mensional aspects of social identification in the context of past arguments (e.g., Ashmore, Deaux, & McLaughlin-Volpe, 2004; Ellemers, et al., 1999; Luhtanen & Crocker, 1992). The second limita-tion of the social identity theory is its content. Brubaker and Cooper (2000) argued that social

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identity is too ambiguous and torn between “hard” and “soft” meanings to be capable of adequately serving the demands of social analy-sis. I suggest that this concern with the concep-tual confusion needs to be better articulated. Recognizing that social identification is a multidi-mensional concept is key to this articulation (Ashmore, Deaux, McLaughlin-Volpe, 2004; Ellemers et al., 1999; Luhtanen & Crocker, 1992). I consider social identification to consist of a cognition aspect (cognitive social identification), affective aspect (emotional social identification), and evaluation aspect (evaluative social identifica-tion), and I employ these three dimensions as my social identification concept. Although a previous study has examined the different subfactors of identification (e.g., Ellemers et al., 1999), an investigation of social identification in a work organization not only show the generalizability of the dimensionality of social identification, but also provides insight into the role of social iden-tification in work organization, thereby contribut-ing to the ecological validity of measures of social identification. The second goal of this study is to articulate the content of social identity theory and the means by which it is shaped by TFL effects on dynamic changes in organization.

Taken together, this study employed a latent growth model to examine the effects of per-ceived TFL on social identification develop-ment behaviors. Most previous TFL research has been cross-sectional in nature (e.g., Avolio et al., 2004; Piccolo & Colquitt, 2006) rather than an examination of employee development behaviors as a result of TFL over time. Even longitudinal studies in this area of research have seldom examined how TFL influences changes in organizational development behav-iors over time (e.g., Liao & Chuang, 2007). Consequently, I do not have much empirical evidence on whether the consequences of TFL strengthen, weaken, or remain stable over time. By collecting data from 1,501 employees of R&D departments at multiple points in time over a 10-month period, I were able to address these gaps in the literature.

Theory and development of

the hypotheses

Social identity theory

The current research is intended to improve the understanding about the content of social identi-fication rather than to utilize the narrow consid-eration of the unidimensional context of social identification. According to the definition of social identity theory that was originally proposed by Tajfel (1978, p. 63), social identity is “… that part of an individuals’ self-concept which derives from his knowledge of his membership of a social group (or groups) together with the value and emotional significance attached to that mem-bership”. This conceptualization not only sug-gests a linkage between social identification and group attachment but also represents an inclusive view of the individual’s identification, which is identified to consist of cognition (awareness of one’s membership in a social group), evaluation (a positive or negative value connotation applied to the group), and emotion (a sense of emotional involvement with the group).

The three distinct aspects of social

identification

Self-categorization Self-categorization refers

to the notion that in many situations, people organ-ize social information by categorizing individuals into groups. This enables individuals to focus on collective properties that are relevant to the situa-tion at hand (e.g., employees vs. supervisors) and neglect the “noise” of other variations (e.g., differ-ences in age) that occurs among individuals within the same group. This process occurs through cog-nitive processes of categorization, wherein one forms self-categories of organizational member-ship and one’s similarities with others in the organ-ization (Bergami & Bagozzi, 2000), as well as dissimilarities with others in different organiza-tions (Turner, 1985). Thus, Dutton, Duckerich, and Harquail (1994, p. 242) consider identity to be “the cognitive connection between the definition

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of an organization and the definition a person applied to him- or herself ”. Indeed, as a member increasingly identifies with an organization, his individual self-perception tends to become deper-sonalized such that the member views himself as an interchangeable representative of the organiza-tion, which is otherwise referred to as a socia1 cat-egory. These perspectives have interpreted cognitive social identification as the awareness of one’s membership in the organization, such as assimilating organization goals as a member’s own goals or common attributes so as to form the basis for cognitive social identification. This process makes group behavior possible because it trans-forms self-conception so that individuals think of themselves in terms of the group prototype; there-fore, I adopt the term “self-categorization” as a cognition component of social identification.

Affective commitment Allen and Meyer

(1996, p. 253) proposed affective commitment to be “identification with, involvement in, and emo-tional attachment to the organization”. Given that we want to draw the concept of “a sense of emotional involvement with the group”, “we adopt the term ‘affective commitment’ to outline the emotional component of social identifica-tion” (Bergami & Bagozzi, 2000).

Group self-esteem Based on the evaluative

component of social identification, we suggest that group esteem is an evaluation of self-worth that derives from one’s membership in the organization (Bergami & Bagozzi, 2000). In other words, positive or negative value connotations that are attached to the group represent how peo-ple think about self-worth in the context of attending a group. Luhtanen and Crocker (1992) have proposed that group self-esteem refers to evaluations of the worthiness or value of the social group; thus, we employ this construct as my evaluative component of identification.

Social identification is usually treated as a uni-dimensional construct. However, a notable exception is a study by Hinkle, Taylor, Fox-Cardamone, and Crook (1989), who distinguish

three factors in the group identification scale. Although Hinkle et al. (1989) argue a multi-com-ponent conceptualization of group identification, the components they distinguish show substan-tial intercorrelations (between .43 and .58), which seems to have been taken as an indication that a common treatment as one factor would be acceptable for practical purposes. More impor-tantly, this imprecision at the operational level is often reflected in conceptual treatments of social identification, and has resulted in a considerable amount of theoretical confusion (Ellemers et al., 1999). For example, people who acknowledge that they belong to a particular social category (the cognitive component of social identification) do not necessarily feel committed to that group (the emotional component of social identifica-tion), or emphasize the positive characteristics of their group (the evaluative component of social identification). Instead, they might prefer to belong to another group, or simply be indifferent to this particular categorization. The key proposal of social identity theory, however, is that it is the extent to which people identify with a particular social group that determines their inclination to behave in terms of their group membership. In this sense, social identification is used to refer to a feeling of affective commitment to the group (the emotional component of social identifica-tion), rather than the possibility to distinguish between members of different social categories (the cognitive component of social identifica-tion). Therefore, this study proposes that it is important to distinguish cognitive awareness of one's group membership per se (self-categoriza-tion) from the extent to which one feels emotion-ally involved with the group in question (affective commitment). Indeed, previous empirical evi-dence shows that people who belong to the same social group may show differential responses, depending on the extent to which they feel affec-tively committed to that group (Ellemers, Van Rijswijk, Roefs, & Simons, 1997). Accordingly, it has also been demonstrated that self-categoriza-tion (denoting a cognitive awareness of one’s group membership) can be distinguished from

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affective commitment to the group (Spears, Doosje, & Ellemers, 1997). On the other hand, this study also distinguishes extent to which peo-ple feel emotionally involved with their group (affective commitment) from the value connota-tion of that particular group membership (group self-esteem). Previous studies have repeatedly argued and demonstrated that the affective com-mitment and group self-esteem often covary (Ellemers, 1993). In other words, affective com-mitment tends to be stronger in more positively evaluated groups (because these groups may con-tribute more to a positive social identification) while people are inclined to distance themselves from less attractive groups. Indeed, previous empirical evidence reveals that, provided their identification as members of a distinct social group is sufficiently important, people may show signs of strong emotional involvement (affective commitment) while simultaneously acknowledg-ing or even emphasizacknowledg-ing the negative characteris-tics of their group (low group self-esteem) (see Mlicki & Ellemers, 1996).

Change in the intra-individual

Past researchers who have investigated the emo-tional component of social identification have used longitudinal data (repeated measures within groups) and interpreted change through a com-parison of group means over time through anal-yses of variance (ANOVAs), correlations, and regression procedures (e.g., Beck & Wilson, 2000; Farkas & Tetrick, 1989). Beck and Wilson (2000) have attempted to operationalize change in emotional component of social identification by combining cross-sectional and longitudinal data collections, which they defined as a cross-sequential design approach (for technical details, see Beck & Wilson, 2001). However, as under-scored by Chan and Schmitt (2000, p. 190), important questions concerning intra-individual change (e.g., change in social identification devel-opment behaviors over time) cannot be ade-quately conceptualized and empirically examined with any of these traditional approaches. These

questions concern (a) the form of the intra-indi-vidual change trajectories (i.e., whether linear or nonlinear, positive, or negative), (b) the system-atic individual differences at initial status and in the rate of intraindividual change, (c) the conse-quences and antecedents of both an individual’s initial status on the construct of interest and his or her rate of change on that construct across time, (d) whether there is a relationship between an individual’s initial status and rate of change on the construct of interest, and (e) whether the change in one variable is related to the change in another.

Latent growth modeling (LGM) has recently gained widespread acceptance as a powerful approach to the description, measurement, and analysis of longitudinal change and, therefore, as a means to address the above questions (Lance et al., 2000, p. 108). Its acceptance is due in large part to the fact that LGM overcomes many of the prob-lems characterizing other approaches (e.g., repeated measures, regression, difference scores) encoun-tered in attempting to operationalize longitudinal change (for comparative reviews, see Chan, 1998; Duncan, Duncan, & Strycker, 2006; Lance et al., 2000). To capture intra-individual change, LGM develops a trajectory of change along each of the focal constructs for each individual across time, aside from the individual’s initial status on the con-structs (Willett & Sayer 1994). The LGM approach requires that the constructs be measured at several occasions (at least 3) in order to define second-order or higher second-order latent constructs, initial sta-tus, and change (i.e., slope) of the variable(s) of interest. More precisely, the first-order latent con-structs representing the variable of interest (e.g., latent affective commitment constructs at Times 1, 2, and 3), display a separate loading on second-order latent factors, one defining initial status and the other defining the rate of change along the first-order constructs (i.e., the affective commit-ment construct). This is referred to as second-order factor LGM. By applying LGM into my proposed model, not only can I detect how intra-individual change trajectories in social identifica-tion development behaviors are affected by the

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perception of TFL at Time 1––as underscored by Chan and Schmitt (2000)––but also determine how these change trajectories in social identifica-tion subsequently affect change trajectories in job performance (i.e., OCB and TP); this will permit us to test the hypothesized associations among changes in those constructs. As mentioned above, I can accurately represent the true conceptual premises regarding the evolution of change in social identification and the impact of those changes in the job performance process.

Research framework and hypotheses

development

I draw on extant literature to propose that the perception of TFL at Time 1 may positively relate to social identification development behaviors and then use these development behaviors to positively predict OCB and TP development behaviors (see Fig. 1).

Antecedents of social identification

Researchers have proposed that TFL behaviors consist of four components (Bass, 1985). Idealized influence is the first dimension, which refers to the degree to which leaders behave in charismatic ways that cause followers to identity with them. Inspirational motivation is the second dimension, which refers to the degree to which leaders articulate visions that are appealing to fol-lowers. Individualized consideration is the third dimension, which refers to the degree to which leaders attend to followers’ needs, act as mentors or coaches, and listen to followers’ concerns. Intellectual stimulation is the fourth dimension, which refers to the degree to which leaders encourage followers to challenge assumptions, take risks, and solicit followers’ ideas.

Conceptual work has drawn attention to the link between leadership processes and followers psychologically belonging to a group (e.g., van Knippenberg, van Knippenberg, De Cremer, &

H9 H6 H8 H5 H7 H4 H3 H1 Transformational leadership at Time 1 Affective commitment development behavior Self-categorization development behavior Group self-esteem development behavior Task performance development behavior Organizational citizenship development behavior H2

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Hogg, 2004). Regarding the role of TFL for organizational self-categorization, Shamir et al. (1993) have suggested that transformational lead-ers transform the self-concepts of the followlead-ers, build personal identification among followers with the mission and goals of the organization, and further enhance followers’ feelings of involvement, cohesiveness, commitment, potency, and performance. Furthermore, Lord, Brown, and Freiberg (1999) have also suggested that the effectiveness of specific leadership behaviors will depend on followers’ self-con-cepts, and TFL behaviors via collective goals and inspiring a common vision make subordinates’ collective identification more salient. However, no empirical study has investigated the role of TFL as a predictor in the self-categorization of behavior development perspectives over time. Therefore, I propose the hypothesis as follows:

Hypothesis 1 Greater perceptions of

transfor-mational leadership at Time 1 result in more self-categorization development behaviors over time. Prior research suggests that work experiences, in addition to personal and organizational factors, serve as antecedents to affective commitment (e.g., Allen & Meyer, 1990, 1996). One such per-sonal and organizational factor that is considered a key determinant of affective commitment is leadership (Mowday, Porter, & Steers, 1982). In particular, there is considerable research that sug-gests that TFL is positively associated with affec-tive commitment in a variety of organizational settings and cultures (e.g., Avolio et al., 2004; Bono & Judge, 2003; Walumbwa & Lawler, 2003). Research by Shamir, Zakay, Breinin, and Popper (1998) suggests that TFL are able to influence followers’ affective commitments by promoting higher levels of goal accomplishment-associated intrinsic value, emphasizing the links between fol-lower effort and goal achievement, and creating higher levels of personal commitment between the leader and followers to common visions, mis-sions, and organizational goals. By encouraging followers to seek new ways to approach problems and challenges and identifying with followers’ needs, transformational leaders are able to

motivate their followers to become more involved in their work, resulting in higher levels of affec-tive commitment (Walumbwa & Lawler, 2003). However, no empirical research has focused on the processes by which TFL predicts affective commitment from the perspective of develop-ment behaviors over time. Therefore, I propose the hypothesis as follows:

Hypothesis 2 Greater perceptions of

trans-formational leadership at Time 1 result in more affective commitment development behaviors over time.

The third component of social identification is group self-esteem, which is defined as individu-als’ appraisals of their own worthiness and confi-dence specific to the organizational setting (Bergami & Bagozzi, 2000). Transformational leaders can build team spirit through their enthu-siasm, high moral standards, integrity, and opti-mism, and they provide meaning and challenge to their followers’ work by enhancing followers’ lev-els of self-confidence and meaning (Avolio et al., 2004). In addition, Shamir et al. (1993) have pro-posed that transformational leaders produce a high level of esteem and a great sense of self-worth in their followers. However, no empirical study has examined the role of TFL as a predic-tor of followers’ development behaviors in the context of group self-esteem over time. Therefore, I propose the hypothesis as follows:

Hypothesis 3 Greater perceptions of

trans-formational leadership at Time 1 result in more group self-esteem development behaviors over time.

Consequences of social identification

Individuals’ job performances consist of distinct sets of activities that contribute to an organiza-tion in different ways (Campbell 1990). The first narrow aspect of job performance is task perfor-mance, which is defined as activities that are directly involved in the accomplishment of core job tasks or activities that directly support the accomplishment of tasks involved in an

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organization’s technical core (Borman & Motowidlo, 1993). Based on the perspective of social identification, individuals with more identi-fication will engage their cognitive, emotional, and evaluative identifications into their work groups and should exhibit enhanced perfor-mance because they have excellent coherence with their fellows for their tasks. They are more attentive and more focused on coherence and, therefore, may be more cognitively, emotionally, and evaluatively connected to the tasks. For example, an employee with high categoriza-tion, affective commitment, and group self-esteem may see the goal of organization as his own goal, put more effort into their work and have confidence to perform their tasks to achieve good TP. Previous studies have also argued that self-categorization, affective commitment, and group self-esteem are connected to performance (e.g., Judge & Bono, 2001; Van Knippenberg et al., 2004); however, no empirical research has focused on that increases in social identification fosters increases in followers’ TP development behaviors. Therefore, I propose the hypotheses as follows:

Hypothesis 4 The greater the increases in

self-categorization development behaviors, the greater the increases in task performance devel-opment behaviors will be over time.

Hypothesis 5 The greater the increases in

affective commitment development behaviors, the greater the increases in task performance development behaviors will be over time.

Hypothesis 6 The greater the increases in

group self-esteem development behaviors, the greater the increases in task performance devel-opment behaviors will be over time.

Job performance includes not only direct task performance but also less-formal “emergent” behaviors that contribute to organizations in a less direct capacity (Motowidlo, Borman, & Schmit, 1997). The label for these less-formal emergent behaviors is organizational citizenship

behavior (OCB) (Organ 1988), which do not directly contribute to an organization’s technical core, but rather, they contribute to the organiza-tion by fostering a social and psychological envi-ronment that is conducive to the accomplishment of work that is involved in the organization’s technical core (Motowidlo et al., 1997). To the extent that individuals with more identity engage themselves more fully with their work groups while at work than those who have less identity, they should be more willing to step outside of the bounds of their formally defined jobs and engage in acts that constitute organizational citizenship behavior. Previous studies have argued that employees with high social identity have greater attachment or affect toward their organization (e.g., Bergami & Bagozzi, 2000; Ellemers et al., 1999); however, no empirical research has focused on that increases in social identification fosters increases in followers’ organizational citizenship behavior. Therefore, I propose the hypotheses as follow:

Hypothesis 7 The greater the increases in

self-categorization development behaviors, the greater the increases in organizational citizenship behavior development behaviors will be over time.

Hypothesis 8 The greater the increases in

affective commitment development behaviors, the greater the increases in organizational citizen-ship behavior development will be over time.

Hypothesis 9 The greater the increases in

group self-esteem development behaviors, the greater the increases in organizational citizenship behavior development will be over time.

Methodology

My conceptual model (Fig. 1) starts from TFL to job performance based social identity theory. The model then illustrates a series of mechanisms that I propose to explain the effects of perceived TFL on its consequences.

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Measures

The constructs in this study are measured using 7-point Likert scales drawn from existing litera-ture. Two doctoral and 5 EMBA students special-izing in organizational behavior were invited to help refine the questionnaire items to ensure con-tent validity of scale. Finally, backward translation was applied to compare an English version ques-tionnaire to a Chinese version (Reynolds, Diamantopoulos, & Schlegelmilch, 1993). A high degree of consistency between the 2 question-naires assures that the translation process of this study did not introduce serious translation biases in the Chinese version of the questionnaire.

Transformational leadership The 4

dimen-sions of transformational leadership were meas-ured with items from the Multifactor Leadership Questionnaire (MLQ Form 5X, Bass & Avolio, 1995). Four items were used to measure intellec-tual stimulation (e.g., “My supervisor … seeks differing perspectives when solving problems”), inspirational motivation (e.g., “ … articulates a compelling vision of the future”), and individual-ized consideration (e.g., “ … treats me as an indi-vidual rather than just a member of a group”). Eight items were used to measure idealized influ-ence (e.g., “ … instills pride in me for being asso-ciated with him/her”).

Self-categorization The 3 Likert items

devel-oped and validated by Ellemers et al. (1999) were used. Participants indicated the agreement of statements, such as, “I identify with other fellows of my work group”, “I am like other fellows of work group”, and “My work group is an import reflection of who I am”

Affective commitment The 7 items validated

by Bergami and Bagozzi (2000), based on the ear-lier work of Allen and Mayer’s (1990) Affective commitment scale were used. Items for “joy” were, “I will be very happy … ” , “I enjoy … ”, “I really feel someone’s problems are my own within my group”, and “Someone has great deal of

personal meaning for me … ”. Items for “love” or attachment affect factors were, “I feel like part of the family at someone within my group” , “I feel emotionally attached to my group”, and “I feel a strong sense of belonging to my group”.

Group self-esteem The six items validated by

Bergami and Bagozzi (2000), based on the earlier work of Heatherton and Polivy’s state self-esteem, were used. Items are, “I feel confident about my abilities around here” , “I feel that others respect and admire me around here” , “I feel as smart as others around here”, “I feel good about myself around here” , “I feel confident that I understand things around here” , and “I feel aware of or am conscious of myself around here”.

Task performance Supervisors were also

asked to complete the 7-item scale developed by Williams and Anderson (1991). Supervisors indi-cated the extent to which they agreed with state-ments about their subordinates’ performance, such as, “This employee … adequately completes assigned duties” and “ … fulfills responsibilities specified in his/her job description”.

Organizational citizenship behavior

Super-visors were also asked to complete the 16-item measure of OCB published by Lee and Allen (2002), indicating the extent to which they agreed with statements about their subordinates’ behav-ior. Items included, “This employee … helps oth-ers who have been absent”, “ … assists othoth-ers with their duties”, and “ … offers ideas to improve the functioning of the organization”.

Subjects and procedures

I tested the proposed theoretical framework using data that were collected in 3 phases (e.g., 3 points in time over a 10-month period) from R&D departments in the information technology (IT) industry in Taiwan. The IT industry was selected to represent my sample because the Taiwanese IT industry is highly developed in the world. I used a commercial directory as my

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sample list, which involved cooperation between industry and a prominent private university in Taiwan. I corresponded with supervisors of R&D departments in order to recruit voluntary participants to the survey. As an incentive, survey respondents were provided with gifts when they completed my questionnaires.

After I received the initial responses of the employees regarding their assessments of trans-formational leadership (TFL), self-categorization (SC), affective commitment (AC), and group self-esteem (GSE) as well as the initial responses of the supervisors regarding their assessments of organizational citizenship behavior (OCB) and task performance (TP) at the first measurement point in time, I surveyed the employees and supervisors again in reference to these attributes 5 months later. Ten months after the responses of the first survey were collected, I performed a third survey to investigate the same aforemen-tioned respective data among employees and supervisors. This 3-wave survey method was also adopted for a longitudinal research investigation of organization development behaviors (e.g., Ng & Feldman, 2010). Each wave of the survey was completed within a 1-week span. I adopted a 5-month lag between survey collections over a 10-month period because (a) changes in organi-zational development behaviors should be visible over 4 months (Ng & Feldman, 2010), and (b) previous studies that have used latent growth model analyses to study employee behaviors have adopted similar time frames (Chan & Schmitt, 2000, Jokisaari & Nurmi, 2009; Lance et al., 2000). In previous studies, time intervals that were as short as 1 month and as long as 6 months have been used (e.g., Hobman & Bordia, 2006), and these studies suggest that employees do change their behaviors within the 4-month time frame (Ng & Feldman, 2010). Therefore, the 5-month time frame that was used in this study should be appropriate for testing the latent growth model. In addition, the use of informa-tion that has been obtained from multiple sources and multiple times in a longitudinal design allows us to reduce common-method bias (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003).

Phase 1 At Time 1, the 211 supervisors of the

R&D departments were asked to participate in this academic study and recruit employees from their R&D departments. Of these 211 supervi-sors, 155 agreed to provide a list of employees who would voluntarily participate in the survey. The sample list included 1,700 employees of R&D departments in Taiwan. The employees were asked to assess their supervisors’ TFL and their SC, AC, and GSE for their groups. The supervisors were asked to assess their employee’s TP and OCB. To ensure confidentiality, I adopted a questionnaire marking code such that the respondents would not be readily identifiable and notified the employee participants that their supervisors would not receive their responses. With the supervisors’ support, I obtained 1,652 responses at a high response rate of 97.1%, and the final usable sample included 1,650 responses.

Phase 2 The Time 2 survey was sent to the

1,650 employees and their supervisors who had participated in the Time 1 survey, and I retrieved 1,606 usable samples, which constituted a response rate of 94.4%. The second employee survey, which assessed SC, AC, and GSE for their work groups, and the second supervisor survey, which assessed TP and OCB for their employees, were administered 5 months after the initial data were collected.

Phase 3 Ten months later, at Time 3, I again

collected employee and supervisor assessments. Ten supervisors were dropped because these supervisors were not available when I attempted to correspond with them or they had left the R&D department; hence, I also dropped 50 employees who were associated with these super-visors because they did not receive TP and OCB supervisor assessments. We obtained usable eval-uations from 1,501 employees who participated in Time 1 and Time 2 of the study. The final usable sample represents an 88.3% retention rate of employee responses and a 94.3% response rate of supervisors from the initial sample list in Phase 1, which is a rate that is comparable to what has been reported in other longitudinal

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studies (e.g., Cable and DeRue, 2002; Liao and Chuang, 2007; Ng & Feldman, 2010). Non-response bias was tested using the t-test, which

indicated no significant difference.

The effective sample size for the current study was 1,501. The average age of the participants in the study was 35 years. A total of 51% of the respondents were female, and 50% of the respondents were married. The average job ten-ure was 3.8 years. Finally, 59% of the sample had at least some college education.

Data analysis

Confirmatory factor analysis CFA analysis

was performed on all of the items that corre-sponded to the six constructs that were measured using Likert-type scales. These variables include perception of TFL (Time 1), SC (Time 1, 2, and 3), AC (Time 1, 2, and 3), GSE (Time 1, 2, and 3), TP (Time 1, 2, and 3), and OCB (Time 1, 2, and 3). The Cronbach’s alpha, composite reliability (CR), and average variance extracted (AVE) for these variables were all greater than the modest criteria (e.g., α > .7, CR > .6, AVE > .5, Fornell & Larcker, 1981). The overall goodness-of-fit of models (e.g., the model in Time 1, 2, and 3) all fit the criteria that were originally established by Fornell and Larcker (1981) (e.g., The RMR for the three models were all less than .05, the RMSE were all less than .08, and the CFI, GFI, and NFI were all greater than .09). For example, the RMR, RMSE, CFI, GFI, and NFI of the CFA model at Time 1, including the construct of TFL, SC, AC, GSE, TP, and OCB measured at Time 1, are respectively 0.048, 0.078, 0.92, 0.93, and 0.91. The RMR, RMSE, CFI, GFI, and NFI of the CFA model at Time 2, including the construct of SC, AC, GSE, TP, and OCB measured at Time 2, are respectively 0.045, 0.075, 0.93, 0.94, and 0.93. The RMR, RMSE, CFI, GFI, and NFI of the CFA model at Time 3, including the construct of SC, AC, GSE, TP, and OCB measured at Time 3, are respectively 0.044, 0.076, 0.92, 0.91, and 0.94. Finally, all factor loadings for the indicators that measured the same construct were all statistically significant. The discriminant validity of my

collected data was confirmed via the chi-square difference test. Finally, I tested whether these scales longitudinally demonstrated measurement invariance (Chan, 1998; Vandenberg & Lance, 2000). Based on chi-square difference tests, none of the items had significantly different factor loadings at the 3 points in time (e.g., Time 1, 2, and 3); hence, my measured factor structures, both theoretically and methodologically speaking, are invariant and stable (Lance et al., 2000).

Latent growth model Latent growth model

(LGM) is an extension of structural equation modeling, and it can be used to assess changes in the levels of variables over time and how these changes are related to other constructs. For example, there are 3 measurement waves in my survey (e.g., 3 points in time over a 10-month period in my study), LGM allows for the assess-ment of linear change on social identity and job performance development behaviors over time. The latent growth model that include covariates that may affect the trajectory of change has been able to examine the strengths of the relation-ships of the covariates with the latent intercept factor (e.g., representing the average initial status of individuals via measurement) and the latent slope factor (representing the rate of change over time) using these models (Ng & Feldman, 2010). In addition, the latent growth model has been applied in organizational studies to assess changes in the levels of individual behaviors (e.g., Bentein et al., 2005; Lance et al., 2000; Ng & Feldman, 2010).

To identify the intercept factor (latent inter-cept factor), the loadings from the interinter-cept fac-tor to each of the 3 repeated measures are fixed to 1.0; hence, the intercept factor equally influ-ences all repeated measures. As prescribed by Duncan et al. (2006) and suggested by Ng and Feldman (2010), the loadings from the slope fac-tor (latent slope facfac-tor) to each of the 3 repeated measures are fixed to values of 0, 1, or 2 for posi-tive linear changes. The first loading is specified to be 0 such that the intercept factor will reflect the mean values of measures at Time 1 (Bollen & Curran, 2006). To test the significance among

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constructs (or variables) for my model, a second-order-factor LGM approach was employed. The perceptions of TFL that are measured at Time 1 were specified to be associated with both the ini-tial status factor and the slope factor (the trajec-tory of change) of SC, AC, and GSE development behaviors. In addition, the initial status and the slope factor of SC, AC, and GSE development behaviors were specified to be related to the ini-tial status and slope factors of TP and OCB. Each first-order latent factor was represented by its respective measurement items (e.g., affective commitment at Time 1 and its 7 measurement items, such as Y1 to Y7), and the error variances of those measurement items that were repeatedly used across time points were allowed to be cor-related (Singer, 1998). For example, the percep-tions of TFL that are measured at Time 1 were specified to be associated with both the initial status factor and the slope factor (the trajectory of changes) of WE behavior development; and further, the initial status and the slope factor of WE behavior development were specified to be related to the initial status and slope factors of SP and WFC behavior development. Each first-order latent factor was represented by its respec-tive measurement items, and the error variances of those measurement items that were repeatedly used across time points were allowed to be cor-related (Singer, 1998). To understand the opera-tion of parameters in LGM, I suggest readers to refer to several paradigmatic studies for more technical details of LGM use, including Bentein et al. (2005); Chan (1998); Chan, Ramey, Ramey, and Schmitt (2000); Duncan et al. (2006); Lance et al. (2000); and Singer (1998).

Finally, it is important to note that I have included age, gender, and job tenure as control variables in my model testing, due to they may differently affect the perceptions of TFL and social identity development behaviors (Bass, 1999; Mael & Ashforth, 1992).

The results of analysis

My results of analysis are based on the assumptions

that the perception of TFL at Time 1 will affect

the trajectory of change (increase) in social iden-tity and that the trajectory of change (increase) in social identity may also elicit subsequent trajec-tory of changes (increase) in TP and OCB (please see Fig. 2).

The analysis results of my proposed model suggest that the fit of my proposed model is acceptable (e.g., SRMR: .07, RMSEA: .05, CFI: .92) (Fornell & Larcker, 1981). Based on the acceptable fit of my proposed model, I examined the param-eter estimates that were contained in the model in order to test my hypotheses. Hypotheses 1, 2, and 3 predict that perceptions of higher TFL at Time 1 would be associated with greater increases in SC, AC, and GSE development behaviors over time. These hypotheses are supported, as shown in Table 1. The perceptions of TFL at Time 1 were associated with increases in SC development behaviors (0.23, p < .01), AC development

behav-iors (0.36, p < .01), and GSE development

behav-iors (0.13, p < .01). The hypotheses that state that

individuals who perceived themselves as highly TFL at Time 1 are more likely to demonstrate greater increases in social identity development behaviors over time were supported. These find-ings make sense because transformation is a core component of TFL perceptions (Bass 1985), and employees who considered themselves to be highly TFL at Time 1 were more likely to have already developed social identity behaviors via the associ-ated transformational effects.

Hypotheses 4, 5, 6, 7, 8, and 9 predict that increases in SC, AC, and GSE development behav-iors positively relate to increases in TP develop-ment behaviors and OCB developdevelop-ment behaviors. That is, when social identity development behav-iors increase over time, TP development behavbehav-iors and OCB development behaviors should also increase. Based on Table 1, I found that increases in SC, AC, and GSE development behaviors sig-nificantly related to increases in TP (SC: 0.33, p <

.01; AC: 0.34, p < .01; GSE: 0.1, p < .01) and

OCB development behaviors (SC: 0.34, p < .01;

AC: 0.42, p < .01; GSE: 0.23, p < .01). Therefore,

Hypotheses 4, 5, 6, 7, 8, and 9 are supported, which state that increases in social identity devel-opment behaviors would positively relate to

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increases in TP and OCB development behav-iors. Furthermore, the initial status of SC, AC, and GSE development behaviors also positively related to the initial status of TP and OCB devel-opment behaviors. In other words, respondents who reported high levels of SC, AC, and GSE development behaviors at Time 1 also reported

high levels of TP and OCB development behav-iors at Time 1.

Discussion

An important result of my analysis is that beyond a certain point, there is an emphasis on how TFL

.23** .13** .10* .42** .34** .33** .34** 0.01* .02* .05* .04* .04* .03* .02* .36** .23** .09* 2 2 2 2 2 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Increase ACDB Initial status ACDB Initial status TPDB Increase TPDB Initial status OCBDB Increase OCBDB TP Time1 TP Time2 TP Time3 AC Time2 AC Time1 AC Time3 TFL Time 1 OCB Time1 OCB Time2 OCB Time3 Initial status SCDB Increase SCDB SC Time1 SC Time2 SC Time3 … Y1 Y7 … Y1 Y7 … Y1 Y7 … Y1 Y16 … Y1 Y16 … Y1 Y16 … Y1 Y3 Y1 … Y3 Y1 … Y3 … Y1 Y6 … Y1 Y6 … Y1 Y6 … Y1 Y20 Increase GSEDB Initial status GSEDB GSE Time3 GSE Time2 GSE Time1 … Y1 Y6 Y1 … Y6 Y1 … Y6 .07*

Figure 2. Latent growth model for this study.

Note: AC = Affective commitment; ACDB = Affective commitment development behavior; GSE = Group self-esteem; GSEDB = Group self-esteem development behavior; OCB= Organizational citizenship behavior; OCBDB= Organizational citizenship behavior development behavior; SC = Self-categorization; SCDB = Self-categorization development behavior; TFL = Transformational leadership; TP = Task performance; TPDB = Task performance development behavior; Yn = Measurement items. *p < .05; **p < .01.

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influences individuals’ social identity develop-ment behaviors via the latent growth model.

Implications of the theory and

methodology

Within social psychology, Tajfel’s (1978) social identity has become central to the discipline, as well as in conceptual and empirical work in anthropology and cultural studies (e.g., Eriksen, 2001; Holland, 1997), wherein it has pushed the concept of identity to the forefront of contem-porary academic discussions. However, subse-quent research has primarily utilized the limited unidimension perspective of social identity to explain its antecedents and consequences (e.g., Oldmeadow & Fiske, 2010; Trötschel, Hüffmeier, & Loschelder, 2010). We have therefore attempted to rectify this by investigating the multidimension of social identity (e.g., Bergami & Bagozzi, 2000; Ellemers et al., 1999) with due consideration of the underlying nature by including the three dis-tinct aspects of social identity from the changes

in organization development behaviors. Moreover, I are the first to draw social identity into the perspective of development behaviors in order to explain how individuals’ behaviors are sculpted. That is, individuals’ social identity devel-opment behaviors could indeed be influenced by the perception of TFL at Time 1, and this impact subsequently could foster job performance devel-opment behaviors.

Regarding variable growths and how these elicit subsequence variable growths, my study opens a new direction for the literature; that is, this study not only contributes to the TFL and social identity literature in the context of applying distinct aspects of social identity to the explana-tion of job performance, but also proposes a growth perspective of variables and shows how these variable growths (e.g., social identity) shape the growths of their consequence variables (e.g., job performance). Thus, my study provides important first evidence of the value of the latent growth modeling approach in understanding and identifying individuals’ development behaviors,

Table 1. Test results of latent growth model

ISSCDB ISCDB ISACDB IACDB ISGSEDB IGSEDB ISTPDB ITPDB ISOCBDB IOCBDB

β β β β β β β β β β Control variables Gender .02 .08 .01 .02 .01 .04 .02 .05 .03 .04 Age .08 .11 .08 .02 .06 .02 .05 .06 .03 .01 Job tenure −.04 −.11 −.09 −.03 −.06 −.08 −.05 −.04 −.05 −.08 Antecedent variables TFL .09* .23** .07* .36** .02* .13** ISSCDB .03* .04* ISCDB .33** .34** ISACDB .04* .05* IACDB .34** .42** ISGSEDB .02* .01* IGSEDB .10* .23**

Note: IACDB = Increase on affective commitment development behavior; IGSEDB = Increase on group self-esteem devel-opment behavior; IOCBDB= Increase on organizational citizenship behavior develdevel-opment behavior; ISACDB = Initial status on affective commitment development behavior; ISCDB = Increase on self-categorization development behavior; ISGSEDB = Initial status on group self-esteem development behavior; ISOCBDB= Initial status on organizational citizenship behavior development behavior; ISSCDB = Initial status on self-categorization development behavior; ISTPDB = Initial status on task performance development behavior; ITPDB = Increase on task performance development behavior; TFL = Transforma-tional leadership. *p < 0.05; **p < 0.01.

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which opens a new and important avenue of future organization behavior research in develop-ment behaviors studies.

The implications of management

The results of this study suggest that through a leader’s TFL behaviors, internal organizational management may transform followers into iden-tification outcomes. First, my results suggest that social identification can enhance job performance and that these improvements in job performance are likely to take the form of both task perfor-mance and OCB. This finding suggests that, rather than spreading resources over various practices aimed at assessing and improving a vari-ety of attitudes and motivational states, it may be worthwhile focusing resources on practices that enhance employee social identity through TFL. In other words, employees’ social identification toward their work groups plays a dominant role in their job performance. Second, my results also suggest that a good job performance by an employee may be achieved when TFL behaviors are accompanied by the enforcement of social identification development behaviors. Social identification development behaviors also pro-vide a strategic focus for TFL behaviors and ena-ble transformational leaders to be more effective in directing employee behaviors toward achieving high job performance development behaviors. Finally, I suggest that transformational behaviors can be incorporated into training courses to improve follower outcomes and yield better results in comparison to those achieved via eclec-tic leadership training (e.g., managerial skills sur-veys, 360-degree feedback instruments).

Limitations and further research

The results of this study suggest that the three different aspects of social identification serve as meaningful constructs that have several different avenues of unexplored content. Future research could test a broader range of predictors that are linked to particular aspects of social identification and might consider individual difference variables

that might predict employee identity with work groups, such as hardiness and locus of control (Maslach, Schaufelli, & Leiter, 2001).

Second, even though I collected three waves of data over a 10-month period, my research design did not allow for strong causal inferences. Longitudinal designs with more measurement waves and lengthier time frames are needed to provide stronger causal evidence. Nevertheless, objective or archival measures of such participa-tion would be especially useful for further research.

Third, as social identity theory is a collective-level (group-collective-level) conceptualization (e.g., aware-ness of one’s membership in a social group, a positive or negative value connotation applied to the group, and a sense of emotional involvement with the group), further research should consider employing hierarchical linear modeling (HLM) (Raudenbush & Bryk, 2002) to explore cross-level inference in more detail.

Finally, the sample for this study is limited to IT firms in Taiwan. Although this may be a valid concern, the factor structure of the construct scale with employees of this study may be similar to that for employees in other firms. Moreover, this study was more interested in the commonal-ity of the factors, rather than in loadings of the first-order factors. A previous study also argued that the use of specific subjects is justifiable when the goal is not to generalize results but to test a theory (Calder, Phillips, & Tybout, 1981). Nevertheless, the generalization of findings may be specific to salespeople brought up in the Chinese culture of Taiwan, where the society accepts an unequal distribution of power and preference for strong ties among people. Future research may extend this model to other cultural and geographical settings and examine whether these findings can be generalized to organiza-tional contexts across different countries.

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數據

Figure 1.  Research model for this study.

Figure 1.

Research model for this study. p.7
Figure 2.  Latent growth model for this study.

Figure 2.

Latent growth model for this study. p.14
Table 1.  Test results of latent growth model

Table 1.

Test results of latent growth model p.15