The Service Industries Journal ISSN: 0264-2069 (Print) 1743-9507 (Online) Journal homepage: http://www.tandfonline.com/loi/fsij20 How transformational leadership fuels employees’ service innovation behavior Ping-Jen Kao, Peiyu Pai, Tingling Lin & Jun-Yu Zhong To cite this article: Ping-Jen Kao, Peiyu Pai, Tingling Lin & Jun-Yu Zhong (2015) How transformational leadership fuels employees’ service innovation behavior, The Service Industries Journal, 35:7-8, 448-466, DOI: 10.1080/02642069.2015.1015519 To link to this article: https://doi.org/10.1080/02642069.2015.1015519 Published online: 26 Feb 2015. Submit your article to this journal Article views: 959 View Crossmark data Citing articles: 9 View citing articles Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=fsij20 The Service Industries Journal, 2015 Vol. 35, Nos. 7–8, 448–466, http://dx.doi.org/10.1080/02642069.2015.1015519 How transformational leadership fuels employees’ service innovation behavior Ping-Jen Kaoa*, Peiyu Paib, Tingling Lina and Jun-Yu Zhonga a Department of Business Administration, National Taipei University, 151, University Rd., San Shia, New Taipei City 237, Taiwan; bDepartment of Business Administration, National Chengchi University, No. 64, Sec. 2, Zhi-Nan Rd., Taipei, Taiwan (Received 1 April 2014; accepted 1 February 2015) Although there is a consensus that transformational leadership (TFL) is critical to successful service innovation behavior, the relationship between the two remains inconclusive. This study adopts a dual perspective approach that considers both motivational and social-political perspectives to further elicit the inﬂuence of TFL on the service innovation behavior of frontline employees. Using multiphase and multisource data from 269 employees and 1396 customers of hair salons, the results show that the perceived organizational climate for innovation, creative self-efﬁcacy, and expected image gains fully mediate the relationship between TFL and employees’ service innovation behavior. TFL positively inﬂuences employees’ perceived organizational climate for innovation, which in turn enhances the service innovation behavior of employees through both motivational (i.e. creative self-efﬁcacy) and socialpolitical (i.e. expected image gains) mediating mechanisms. Surprisingly, expected image risks are found to have a non-signiﬁcant relationship with service innovation behavior. We discuss implications of these ﬁndings with respect to innovation literature and management practice, as well as offer suggestions for further research. Keywords: transformational leadership; psychological climate; motivational mechanism; social-political mechanism; service innovation Introduction Frontline employees are essential to achieving innovation success in service industries because of their pivotal role in delivering innovative service offerings to customers (Lin, 2013). Scholars in various disciplines have investigated the wide variety of factors that potentially affect innovation behavior in employees (e.g. Scott & Bruce, 1994; Yuan & Woodman, 2010; Zhang & Bartol, 2010). Transformational leadership (TFL) is one factor widely acknowledged as being of particular importance (Bass, 1985; Gong, Huang, & Farh, 2009; Gumusluoglu & Ilsev, 2009; Shin & Zhou, 2003; Sun, Zhang, Qi, & Chen, 2011). However, the underlying inﬂuence processes for TFL remain vague and lack systematic investigation (Yukl, 1999, p. 287). This study attempts to address three research gaps in the extant research. The ﬁrst gap pertains to the relationship between TFL and the service innovation behavior of employees. *Corresponding author. Email: email@example.com This article was originally published with errors. This version has been amended. Please see Corrigendum (DOI: http://dx.doi.org/10.1080/02642069.2015.1026203). © 2015 Taylor & Francis The Service Industries Journal 449 Although studies have examined the direct and indirect effects of TFL on the innovation performance of employees, empirical ﬁndings have been inconclusive (e.g. Gong et al., 2009; Jaussi & Dionne, 2003; Jung, Chow, & Wu, 2003; Shin & Zhou, 2003). Avolio, Walumbwa, and Weber (2009, p. 429) stated that ‘despite signiﬁcant progress in understanding how and when charismatic and transformational leadership behaviors are more effective, further research is needed that explores the process and boundary conditions for charismatic and transformational leadership with beneﬁcial work behaviors’. The second gap involves the limitations that are inherent to the single theoretical perspective that is most commonly used in the innovation literature (Wolfe, 1994). These limitations preclude considerations of combinations of multiple theoretical perspectives, which hold the potential to further elucidate the relationship between TFL and innovation behavior. Many studies have adopted a motivational perspective in their explorations of the inﬂuence of TFL on innovation behavior (e.g. Gong et al., 2009; Shin & Zhou, 2003; Sun et al., 2011) while overlooking the pivotal role of the social-political (i.e. expected image outcomes) mediating mechanism (Farr & Ford, 1990; Yuan & Woodman, 2010). Considering both motivational and social-political mediating mechanisms facilitates the assessment of how these dual mediating processes simultaneously affect the relationship between TFL and employees’ service innovation behavior. The third gap addresses the vital role of organizational climate for innovation in the TFL–dual mediating processes linkage. This climate has been shown to have a signiﬁcant mediating inﬂuence on the relationship between TFL and innovation behavior (Eisenbeiss, van Knippenberg, & Boerner, 2008; Wang, Rode, Shi, Luo, & Chen, 2013), acting as a psychological mechanism that directs employees’ attention toward innovation and shapes their behavior in the workplace (Scott & Bruce, 1994). However, despite its importance, the effect of organizational climate for innovation has not been previously linked to these mediating processes. Anderson, Potočnik, and Zhou (2014) suggested that future research should investigate the effects of leadership on climate for innovation, which stimulates innovation behavior. Therefore, this study includes an in-depth examination of the mediating processes between TFL and service innovation behavior by combining the perceived organizational climate for innovation with motivational and social-political perspectives. To address these research gaps, the current study builds and tests a theoretical model linking TFL and service innovation behavior via perceived organizational climate for innovation, creative self-efﬁcacy, and expected image outcomes. This study contributes to scholarly knowledge in the ﬁeld of service innovation in three important ways. First, we advance prior research by resolving the controversy regarding the relationship between TFL and service innovation behavior (Avolio et al., 2009). Speciﬁcally, this study develops a comprehensive framework to explain how the sequentially dual mediating processes inﬂuence the relationship between TFL and service innovation behavior by employing a multiphase research design and collecting data from multiple data sources. This research design reduces the risk of observed correlations reﬂecting same-source or common method biases (Rindﬂeisch, Malter, Ganesan, & Moorman, 2008). Second, this study extends and deepens extant research by elucidating the simultaneous inﬂuences of motivational and social-political variables on the relationship between TFL and service innovation behavior (Gong et al., 2009; Yuan & Woodman, 2010). Integrating motivational and social-political perspectives into one research design facilitates investigation of how these dual mediating mechanisms affect frontline employees’ service innovation behavior. Third, this study extends extant research by investigating whether the perceived organizational climate for innovation fully channels the effects of TFL onto both motivational and social-political mediating mechanisms. By exploring the sequentially mediating 450 P.-J. Kao et al. mechanisms, we can more deeply investigate the service innovation processes and better understand the relationship between TFL and service innovation behavior. Theoretical background and research hypotheses development This section introduces service innovation behavior and develops hypotheses pertaining to the effects of motivational and social-political mediating mechanisms on this behavior. This is followed by explanations of the mechanisms by which TFL inﬂuences service innovation behavior. Figure 1 depicts the research framework. Service innovation behavior Marketing research and practice reﬂect a strong consensus that innovation helps organizations succeed in a dynamic environment (Aas & Pedersen, 2011; Ordanini & Parasuraman, 2011). Research has traditionally classiﬁed innovation into two categories: manufacturing innovation and service innovation (Carlborg, Kindström, & Kowalkowski, 2014). Innovation in manufacturing refers to product-centric orientation activities. This type of innovation requires R&D departments to invest substantial money and efforts into developing new products (Sood & Tellis, 2005). In contrast, innovation in services does not require new, quantiﬁable investments, but rather is ‘a process, a sequence of operations, a formula, a protocol, a problem solution’ (Gallouj & Savona, 2009, p. 154). Although some service innovation creation such as combined ﬁnancial products might be created by service providers themselves, most service innovations represent the cooperative effort of service providers and customers, particularly in situations in which customer feedback is used to continuously improve the innovation. Therefore, customers are in general an integral part of service innovation because they are active coproducers in the innovation creation process (Ordanini & Parasuraman, 2011). According to Carlborg et al. (2014, p. 373), ‘Service innovation introduces something new into the way of life, organization, timing and placement of what can generally be described as the individual and collective processes that relate to consumers.’ A service innovation depends on the presence and cocreation of the customer, which means that the value of service innovation is always uniquely and phenomenologically determined by the customers (Vargo & Lusch, 2008). Drawing on these concepts, this paper deﬁnes Figure 1. Conceptual framework. The Service Industries Journal 451 ‘service innovation behavior’ as a frontline employee’s introduction or application of new ideas, skills, technologies, processes, and procedures to his/her customers. As previously stated, this behavior is an outcome of value cocreation contributed by the efforts of frontline employees and their respective customers (Jaakkola & Alexander, 2014). Examples of such behavior include developing new ideas to improve service performance, adopting new technologies, and using new processes to serve customers (Gallouj & Savona, 2009). Creative self-efﬁcacy → service innovation behavior Creative self-efﬁcacy refers to the belief that one has the ability to produce creative outcomes (Tierney & Farmer, 2002, 2011). In their work on self-efﬁcacy theory, Bandura and Locke (2003, p. 97) noted that ‘a resilient sense of efﬁcacy provides the necessary staying power in the arduous pursuit of innovation and excellence’. Empirical evidence shows that this motivational variable is a preeminent factor stimulating creativity. For example, Tierney and Farmer (2011) suggested that a creativity-focused sense of efﬁcacy facilitates creativity by offsetting obstacles inherent to creative engagement. Gong et al. (2009) also show that employees with high levels of creative self-efﬁcacy set higher creativity goals, which relates positively to actual creative performance. For these reasons, it is important to understand the relationship between creative self-efﬁcacy and innovation behavior in the context of service. Creative self-efﬁcacy is conducive to service innovation behavior in at least three ways. First, creative self-efﬁcacy facilitates the adoption of a mastery goal orientation, which contributes to more trial-and-error experimentation and a greater willingness to learn from these efforts (Richter, Hirst, van Knippenberg, & Baer, 2012). Thus, frontline employees with higher creative self-efﬁcacy are more likely to engage in service innovation behavior. Second, in the context of service, frontline employees face uncertain and unfamiliar situations and must come up with the best ideas to address customer needs. Employees with highly creative self-efﬁcacy behave in a self-starting manner rather than ‘do[ing] things by the book’ (Raub & Liao, 2012, p. 654). They are more proactive in terms of implementing creative ideas and trying new methods (Chen, Farh, Campbell-Bush, Wu, & Wu, 2013; Raub & Liao, 2012). Finally, Ryan and Deci (2000) indicated that employees engage intrinsically in activities when they feel efﬁcacious with respect to those activities. Employees with higher creative self-efﬁcacy are more likely to set their own challenging goals, focus on solving problems, and commit to those goals, due to higher task motivation. Therefore, this study hypothesizes: H1: Creative self-efﬁcacy is positively related to service innovation behavior. Expected image gains/risks → service innovation behavior In addition to the motivational mechanism, we propose a social-political mechanism, identiﬁed as a pivotal proximal antecedent to individual innovation behavior (Farr & Ford, 1990; Yuan & Woodman, 2010), as another important source stimulating frontline employees to engage in service innovation behavior. Individuals’ behaviors are often limited to speciﬁc situations and determined by impression management tactics (Ashford & Cummings, 1983; Ashford, Rothbard, Piderit, & Dutton, 1998). These tactics help them create various desired social images and elicit beneﬁts from social interaction partners (Liu, Wang, & Wayne, 2014). A previous study has clearly distinguished between two approaches to impression management: assertive and defensive (Schlenker, 1980). Assertive impression management (i.e. expected image gains) helps employees improve their social image, whereas defensive 452 P.-J. Kao et al. impression management (i.e. expected image risks) helps employees protect an established social image (Tetlock & Manstead, 1985; Yuan & Woodman, 2010). Both tactics are critical factors that affect service innovation behavior for two reasons. First, from a social-political perspective, expected image gains push frontline employees to apply new ideas in their daily tasks, which can assist them to earn a positive social image (e.g. competence and conscientiousness) from supervisors and coworkers (Raghuram, 2013). Conversely, expected image risks deter employees from service innovation behavior because doing so may cause others to think unfavorably of them (e.g. incompetence and show-off) (McDonnell & King, 2013). They choose to play it safe to prevent negative social evaluations from other employees (Yuan & Woodman, 2010). Second, from a feedback-seeking perspective, individuals search proactively for evaluative information about their performance due to the potential image gains and costs associated with their behavior (Wood & Hoefﬂer, 2013). If employees expect innovation behavior to enhance their social image, they become more likely to seek feedback. Conversely, employees who believe that the risks associated with feedback-seeking may harm their social image will be less likely to engage in this type of behavior (Ashford & Cummings, 1983). In their study on work team performance, De Stobbeleir, Ashford, and Buyens (2011) demonstrated that direct verbal feedback from leaders and coworkers enhances employees’ understanding regarding how others perceive their work and ideas, and thus facilitates subsequent adjustments and improvements. In addition, employees examine their environment for indirect feedback cues to diversify their thinking and enrich their innovation performance. Therefore, this study hypothesizes: H2a: Expected image gains are positively related to service innovation behavior. H2b: Expected image risks are negatively related to service innovation behavior. Transformational leadership → perceived organizational climate for innovation Bass and Avolio (1995) characterize TFL as comprising four unique but interrelated behavioral components. These components include (1) idealized inﬂuence (including idealized attribution and idealized behavior), in which a leader inﬂuences followers by inspiring strong admiration, respect, and loyalty and by fostering a collective sense of mission; (2) inspirational motivation, in which a leader communicates high expectations, articulates a compelling vision for the future, shows followers how to achieve stated goals, and expresses conﬁdence in their ability to accomplish these goals; (3) intellectual stimulation, in which a leader heightens the attention of followers to problems and encourages them to view old problems from new perspectives; and (4) individualized consideration, in which a leader supports, mentors, and develops followers. Service research has shown that transformational leaders are central to the creation and maintenance of a climate in service contexts (Bowen & Schneider, 2014; Liao & Chuang, 2007). Leaders who utilize TFL inﬂuence employees’ perceptions of the organizational climate for innovation, which refers to the degree of support and encouragement an organization provides to employees to increase their willingness to take initiative and explore innovative approaches (Sarros, Cooper, & Santora, 2008; Scott & Bruce, 1994). This climate comprises two important signals during the service innovation process at the individual level: the organizational expectations with regard to innovation behavior and the potential outcomes of that behavior (Amabile, 1988; Scott & Bruce, 1994). These signals inﬂuence employees’ psychological mechanisms, which in turn enhance their individual innovation behavior. Previous studies have demonstrated that leaders who possess TFL behaviors inﬂuence the climate for innovation at the organizational level (e.g. The Service Industries Journal 453 Eisenbeiss et al., 2008; Jung et al., 2003). Following Sarros et al.’s (2008) suggestion to directly measure innovation behavior at the individual level, we posit that TFL has a positive impact on frontline employees’ perceived organizational climate for innovation. Several TFL behaviors inﬂuence the perceptions of frontline employees with regard to the organizational climate for innovation. As idealized inﬂuencers and inspirational motivators, transformational leaders serve as inﬂuential models that articulate a compelling vision throughout the organization. These leaders establish an organizational culture that underscores the central role of service innovation in business success (Wang, Oh, Courtright, & Colbert, 2011). As intellectual stimulators, transformational leaders help foster an organizational climate that challenges and motivates employees to seek innovative approaches at work (Sarros et al., 2008). As mentors, transformational leaders provide individualized support and personalized development guidance to help employees understand the importance of service innovation (Chen et al., 2013). Given these arguments, this study hypothesizes: H3: TFL is positively related to perceived organizational climate for innovation. Perceived organizational climate for innovation → creative self-efﬁcacy Previous research has conceptualized psychological climate as a construct comprising an individual’s psychologically meaningful representations of proximal organizational structures, processes, and events (James, Hater, Gent, & Bruni, 1978). Scott and Bruce (1994) suggested that this climate represents the signals that individuals receive regarding organizational expectations for behavior and potential outcomes of behavior. In the service innovation context, the process whereby frontline employees interpret the meaning of environmental cues is critical to the innovation process (Tierney & Farmer, 2004). Bandura (1982) proposed four main sources for the formation of self-efﬁcacy beliefs: (1) social persuasion, (2) vicarious experience, (3) mastery experience, and (4) psychological state. We expect that employees who perceive the existence of an organizational climate for innovation will elevate their creative self-efﬁcacy through these four mechanisms. First, employees who strongly perceive that an organizational climate for innovation exists tend to focus on information that conﬁrms their capabilities for innovation, and ignore contradictory information (Tierney & Farmer, 2011), thereby enhancing the positive inﬂuence of social persuasion. Second, these employees will actively exchange information and hence learn vicariously from their coworkers (Richter et al., 2012). Third, these employees tend to interpret this climate as being connected to the expectations of their supervisors, and engage in the innovation process. They feel free to propose new ideas without fear of being criticized (Anderson et al., 2014), making them more likely to accumulate mastery experience over time (Gong et al., 2009). Fourth, these employees tend to believe that they will receive support when implementing innovation (Chen et al., 2013). Therefore, they are more likely to focus on the positive side of innovation, which helps reduce aversive states of psychological arousal related to fear, anxiety, and stress. In summary, the perceived organizational climate for innovation is an important precursor to enhancing creative self-efﬁcacy. H4: Perceived organizational climate for innovation is positively related to creative selfefﬁcacy. Perceived organizational climate for innovation → expected image outcomes The perceived organizational climate for innovation not only inﬂuences how employees see themselves in terms of creative self-efﬁcaciousness, but also inﬂuences their expectations of 454 P.-J. Kao et al. potential image outcomes. According to Jones and James (1979), psychological climate perceptions affect how an individual interprets events, predicts possible outcomes, and ascertains the appropriateness of subsequent actions. In the context of service innovation, employees use these signals regarding perceived organizational climate for innovation to predict potential image gains and risks. Speciﬁcally, employees with a higher perception of organizational climate for innovation are more likely to experience a sense of psychological safety due to the belief that their supervisors favor innovation behavior in their employees. These employees are also more likely to believe that engaging in service innovation behavior is valuable (Chen et al., 2013), which enhances expected image gains and reduces expected image risks (Ashford et al., 1998). Likewise, employees who perceive the existence of an organizational climate for innovation are more inclined to interact with their colleagues and perceive a greater sense of context favorability, which legitimates their desire for innovation behavior (Tse, Ashkanasy, & Dasborough, 2012). In other words, this type of climate indicates that with respect to organizational norms and values, the organization favors innovation rather than tradition; therefore, frontline employees will be more likely to consider innovativeness as a desirable image, which strengthens expected image gains and reduces expected image risks. H5a: Perceived organizational climate for innovation is positively related to expected image gains. H5b: Perceived organizational climate for innovation is negatively related to expected image risks. Methodology Research context This study was conducted in hair salons in urban areas of northern and central Taiwan. A hair salon is a setting in which services are marked by a high level of interaction between frontline employees and customers, and in which the participation of customers is critical to successful service innovation (Liao & Chuang, 2007). Therefore, hair salons offer a good setting for researching service innovation issues and achieving our study objectives. This study uses the standard term ‘hairstylist’ to refer to the frontline service providers working at hair salons. Hairstylists offer innovative services such as hair design, hair cutting, and hair coloring to satisfy customer expectations. Examples of service innovation behavior in this industry include implementing new hair service concepts, developing new hair design methods, and using new technologies in providing hair services. Because customers are codevelopers in the service process (Jaakkola & Alexander, 2014), their opinions provide a strong and valid measure of hairstylists’ service innovation behaviors. Therefore, this study collected dyadic data (i.e. a combination of information offered by hairstylists and their respective customers) in three phases (see Table 1). This temporal separation (i.e. multiphase) design is recognized as a key marker of causality by assessing the inﬂuence of a predictor at a time subsequent to its cause (Rindﬂeisch et al., 2008). Moreover, this design enables the investigation of individual service innovation behavior over time and reduces common method bias (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). The questionnaire used in this study was translated from English into Chinese by a Taiwanese marketing professor. Two doctoral students then independently translated the questionnaire back into English to conﬁrm equivalency of meaning. The Service Industries Journal 455 Table 1. Measurement design. Variable Transformational Leadership Perceived Organizational Climate for Innovation Creative Self-Efﬁcacy Expected Image Outcomes Customer Participation Service Innovation Behavior Time 1 Time 2 Time 3 X X X X X X Data source Service Service Service Service Service Service providers providers providers providers receivers receivers Notes: We collected data at three time periods: Time 1 (initial), Time 2 (one month after Time 1), and Time 3 (one month after Time 2). Data collection In the ﬁrst phase (Time 1), eight trained graduate-level research assistants administered the hairstylist surveys at each of the targeted salons. The hairstylist participants were asked to evaluate the TFL behaviors of the store manager and their perceptions of the organizational climate for innovation. Hairstylist surveys and the corresponding envelopes were coded using random identiﬁcation numbers interpretable only by the researchers to facilitate later matching of the data from the hairstylist participants to the data from the second survey. A central collection box was set up in the staff room for participants to submit their completed surveys in conﬁdence. Additionally, participants were informed that they could mail their surveys directly to the researchers using a prepaid return envelope if they preferred. We administered a second survey to the same hairstylist participants one month after the ﬁrst survey (Time 2) to assess their creative self-efﬁcacy and expected image outcomes. To motivate participation, those who completed both surveys were offered a shopping voucher worth NTD 200 (approximately US$7). In the next phase (Time 3), research assistants approached customers randomly to ﬁll out a brief survey after these customers had received their hair service. This random approach avoided any potential selection bias. Customers answered questions about the service innovation performance of their hairstylist. All respondents were guaranteed conﬁdentiality for their responses. Sample characteristics A total of 331 hairstylist participants completed the ﬁrst wave of the survey, while 309 completed both waves. We deleted 40 incomplete surveys, leaving 269 valid survey responses available for analysis (valid response: 81.2%). The average number of employees in each salon was approximately seven. The average age of the participants was 27 years. Most (221; 82%) were women, and the average tenure was seven years. In terms of education, 10 (4%) held a junior high school degree, 213 (79%) held a senior high (or vocational) school degree, 26 (10%) held a two-year college degree, and 20 (7%) held a university or higher degree. In addition, 1630 customers were asked to participate in the third wave, and 1396 (85%) completed and returned the study questionnaire. On average, ﬁve customers for each participant completed the questionnaire. These returned surveys enabled us to identify 269 usable matched data from hairstylists and customers. Measures Table 2 provides a detailed summary of the multiple-item scales, composite reliabilities (CRs), and average variances extracted (AVEs). As in the original English-language versions, the questionnaires used seven-point Likert scales to record responses. 456 P.-J. Kao et al. Table 2. Summary of measures. Construct TFL (CR = .89, AVE = .67) Perceived Organizational Climate for Innovation (CR = .85, AVE = .66) Creative Self-Efﬁcacy (CR = .82, AVE = .61) Expected Image Gains (CR = .87, AVE = .62) Expected Image Risks (CR = .95, AVE = .85) Service Innovation Behavior (CR = .84, AVE = .63) Conceptual deﬁnition/measuresa Standardized factor loadingb TFL is deﬁned as four unique but interrelated behaviors enacted by a leader (Bass & Avolio, 1995) (1) Idealized inﬂuence (Attributes) .70 (2) Inspirational motivation .86 (3) Intellectual stimulation .89 (4) Individual consideration .82 Organizational climate for innovation refers to the degree of support and encouragement an organization provides employees to take initiative and explore innovative approaches (Sarros, Cooper, & Santora, 2008; Scott & Bruce, 1994). (1) I perceive that people in this store are always searching for .85 new ways of looking at problems (2) I perceive that we take time to develop ideas in this store .81 (3) I perceive that people in this store cooperate in order to .77 develop and apply ideas Creative self-efﬁcacy refers to the belief that one has the ability to produce creative outcomes (Tierney & Farmer, 2002, 2011) (1) I have conﬁdence in my ability to solve problems creatively .80 (2) I feel that I am good at generating novel ideas .73 (3) I have a knack for further developing the ideas of others .81 Expected image gains help improve an individual’s social image (Tetlock & Manstead, 1985; Yuan & Woodman, 2010) (1) If I were to do something innovative, my image in the hair .80 salon would be enhanced (2) Searching out new technologies or techniques for my .86 company will make me look good (3) Participating in the implementation of new ideas will .81 improve my images in the hair salon (4) Suggesting new ways to achieve goals will improve my .67 supervisor’s evaluation of me Expected image risks helps protect an individual’s established social image (Tetlock & Manstead, 1985; Yuan & Woodman, 2010) (1) My coworkers will think I am showing off if I come up with .93 new approaches in my work (2) People will think I am crazy if I come up with new ways of .95 doing my job (3) Other people will think worse of me if I try to change the way .89 things operate within the hair salon Service innovation has been deﬁned as introducing something new into the way of life, organization, timing, and placement of what can generally be described as the individual and collective processes that relate to consumers (Carlborg et al., 2014) (1) I think this hairstylist often comes up with new and practical .78 ideas to improve hair service performance (2) I think this hairstylist often develops new methods for hair .79 design (3) I think this hairstylist often uses new technologies, processes, .82 and techniques in hair services Notes: CR = composite reliability and AVE = average variance extracted. a All items were assessed on seven-point scales, anchored at 1 = Strongly disagree, 4 = Neutral, and 7 = Strongly agree. b All factor loadings are signiﬁcant at p < .001. The Service Industries Journal 457 Service innovation behavior. Drawing on the work of Gong et al. (2009) and Zhang and Bartol (2010), this study used a three-item service innovation measure. Customers provided information about service innovation behavior by answering the three items. These items are as follows: ‘I think this hairstylist often comes up with new and practical ideas to improve hair service performance’; ‘I think this hairstylist often develops new methods for hair design’; and ‘I think this hairstylist often uses new technologies, processes, and techniques in hair services’. These items are consistent with Ordanini and Parasuraman’s (2011) conceptualization of service innovation. This adaptation approach is also consistent with Farh, Canella, and Lee’s (2006) recommendation for developing valid research instruments in a Chinese context. This study further aggregated evaluations of the same stylist from multiple customers at the stylist level to measure the hairstylists’ overall service innovation performance (Liao & Chuang, 2007). TFL. This study adopted the multifactor leadership questionnaire form 5X-Short to scale TFL (Bass & Avolio, 1995). Respondents were asked to respond to each item based on how appropriately it described their manager. Sample items included ‘My manager displays self-conﬁdence and authority in dealing with matters’ (idealized inﬂuence category); ‘My manager often expresses his/her conﬁdence that we will achieve our goals’ (inspiration motivation category); ‘My manager often encourages us to face problems with diverse perspectives’ (intellectual stimulation category); and ‘My manager spends time teaching and coaching me’ (individualized consideration category). Perceived organizational climate for innovation. This study measured perceived organizational climate for innovation with three items that were adapted from the support for innovation scale in the Team Climate Inventory developed by Kivimaki and Elovainio (1999). A sample item is: ‘I perceive that people in this store are always searching for new ways of looking at problems.’ Participants indicated the degree to which they perceived an organizational climate for innovation. Creative self-efﬁcacy. This study used the three-item Creative Self-Efﬁcacy Instrument (Tierney & Farmer, 2002) to assess this measure. Participants responded to items such as ‘I have conﬁdence in my ability to solve problems creatively’ to evaluate their creative ability. Expected image gains. This study measured expected image gains using four items adapted from Ashford et al.’s (1998) measures of image outcomes associated with issue selling (e.g. ‘If I were to do something innovative, my image in the hair salon would be enhanced’). The participants indicated their anticipated degree of image gain. Expected image risks. This study asked participants to indicate their anticipated degree of image risk using three items adapted from Ashford’s (1986) measure of image risk (e.g. ‘My coworkers will think I am showing off if I come up with new approaches in my work’). Results Measurement model evaluation Item reliability. The standard used to measure items reﬂects research suggestions by Bagozzi and Yi (1988) that factor loadings for each observed item of every latent construct should exceed 0.50. All results obtained in the model were signiﬁcantly higher than 0.70 (p < .001). 458 P.-J. Kao et al. Internal consistency. We used the CR coefﬁcient (Bagozzi & Yi, 1988; Fornell & Larcker, 1981) and AVE (Fornell & Larcker, 1981) to assess the internal consistency of the construct measures. Though identical to Cronbach’s alpha, the CR coefﬁcient uses the corresponding estimated factor loading to weigh each measure. CR coefﬁcient and AVE estimates above 0.60 and 0.50, respectively, are deemed to demonstrate adequate internal consistency. CR and AVE values for all constructs in the model were signiﬁcantly higher (0.82∼0.95 and 0.61∼0.85, respectively) than the stipulated criteria, indicating good internal consistency. Discriminant validity. Three different approaches were used to evaluate the discriminant validity of model constructs. The results of a conﬁrmatory factor analysis model, built with 6 latent constructs and a total of 20 measures, showed good ﬁt with the data. The goodness-of-ﬁt statistics for the model were as follows: χ2(169) = 319.09, non-normed ﬁt index (NNFI) = 0.96, conﬁrmatory ﬁt index (CFI) = 0.97, and root mean squared error of approximation (RMSEA) = 0.056. As a ﬁrst test of discriminant validity, we checked whether correlations among latent constructs were signiﬁcantly less than one. Lack of the value of 1 appearing in any of the conﬁdence intervals for the φ values (φ values ± two standard errors) suggests good discriminant√validity (Bagozzi & Yi, 1988). Next, Fornell and Larcker (1981) suggested that the AVE value of each latent construct should exceed its vertical and horizontal correlation values (i.e. the correlation value between the latent construct and other constructs). √ All correlation values for each latent construct in this study were less than the AVE value (see Table 3). Finally, for each pair of factors, the chi-square value obtained using a measurement model that constrained their correlation to one was compared against a baseline measurement model without this constraint. We Table 3. Correlation matrix and summary statistics. Correlationa Variable 1. Service Innovation Behavior 2. Creative Self-Efﬁcacy 3. Expected Image Gains 4. Expected Image Risks 5. Perceived Organizational Climate for Innovation 6. Transformational Leadership 7. Customer Participation Response range of multiple-item scales Mean Standard Deviation a 1 2 3 4 5 6 7 b 0.80 0.27 (0.06)c 0.27 (0.06) −0.01 (0.06) 0.13 (0.06) 0.09 (0.05) 0.67 (0.07) 2–7 0.72 (0.06) −0.10 (0.05) 0.46 (0.06) 0.19 (0.04) 0.14 (0.05) 1–7 −0.15 (0.05) 0.39 (0.06) 0.26 (0.04) 0.13 (0.05) 2–7 −0.11 (0.06) −0.08 (0.05) 0.02 (0.05) 1–7 0.54 (0.05) 0.06 (0.05) 3–7 0.02 (0.04) 1–7 0.76 5.83 0.55 5.75 1.01 5.78 1.01 2.75 1.62 4.24 0.67 5.67 1.06 5.35 0.90 0.78 0.79 0.92 0.81 0.82 1–7 All correlations are signiﬁcantly less than 1.00. The ﬁgures on the diagonal are the square roots of the average variance extracted score for each construct. c Standard errors appear in parentheses. b The Service Industries Journal 459 then performed a chi-square difference test on each (see Appendix). When, for example, we tested whether construct 1 (Service Innovation Behavior) and construct 2 (Creative SelfEfﬁcacy) were distinct, the measurement model with the correlation constrained to one yielded a chi-square value of 386.78 (df = 70), and the difference between the baseline model and the constrained model was x2d (1) = 67.69 (p < 0.001). This result identiﬁed the two factors as distinct. These tests revealed factor pairs as distinct in all cases, again offering evidence of discriminant validity for all construct measures. Structural model estimation Structural equation models were built separately for the full sample to test H1–H5. Mediation tests were then conducted on the full sample to determine robustness. The ﬁt statistics for the full sample model (χ2(181) = 421.08, p ≅ 0.00; NNFI = 0.94; CFI = 0.95; RMSEA = 0.066) demonstrate the signiﬁcance of chi-square (p < .001), likely a reﬂection of the large sample size. All other statistics were also within acceptable ranges, indicating a good ﬁt to the data. We found signiﬁcant support for the paths from creative self-efﬁcacy and from expected image gains to service innovation behavior (see Figure 2), with beta coefﬁcients of 0.12 (p < .05) and 0.13 (p < .01), respectively, providing support for H1 and H2a. We found that expected image risks (β = 0.01) was not a signiﬁcant predictor of service innovation behavior; thus, H2b was not supported. These antecedents explained nearly half (46%) of all service innovation behaviors. In terms of the perceived organizational climate for innovation, we found that TFL (γ = 0.53) was a signiﬁcant predictor of perceived organizational climate for innovation, which supported H3. In terms of creative self-efﬁcacy, we found that the path from perceived organizational climate for innovation to creative self-efﬁcacy was signiﬁcant (β = 0.49), supporting H4. Finally, for the path from perceived organizational climate for innovation to expected image outcomes, we found that the expected image gain was positive and signiﬁcant (β = 0.45) and that the expected image risk was negative but not signiﬁcant (β = –0.12), which supported H5a but not H5b. Test of mediation To obtain further support for the model’s validity, rather than using a saturated model in which ‘everything is related to everything else’ as the baseline, we performed formal Figure 2. Standardized path coefﬁcients for the model. Note: *p < .05, **p < .01. 460 P.-J. Kao et al. tests of mediation for all possible paths in the model. We did this to check for the potential signiﬁcance of additional direct paths not speciﬁed in the model. Four of these tests were conducted. To check the signiﬁcance of the direct path from the perceived organizational climate for innovation to service innovation behavior, M1 (see Table 4) was compared with a model in which an additional path from perceived organizational climate for innovation to service innovation behavior was added. We used the difference in chi-square values between the two models (M0 and M1) (x2d (1) = 0.02) with a single degree of freedom to test the signiﬁcance of the added path. We found a lack of signiﬁcance (p > .88), which indicates the non-signiﬁcance of this direct path and that creative self-efﬁcacy and expected image outcomes mediate all the effects of the perceived innovation climate on innovation behavior, as hypothesized. Furthermore, we tested the direct paths from TFL to, respectively, creative self-efﬁcacy, expected image gains, and risks (M2, M3, and M4), with chi-square differences from the baseline model (M0) calculated as x2d (1) = 2.19, x2d (1) = 0.19, and x2d (1) = 0.10, respectively, indicating clear non-signiﬁcance. Therefore, the hypotheses stating that perceived organizational climate for innovation mediates the effects of TFL on creative self-efﬁcacy, expected image gains, and expected image risks were supported. Discussion and conclusions This study developed a comprehensive framework for investigating the effect of dual mediating processes on the relationship between TFL and the service innovation behavior of frontline employees. Using a multiphase design and multiple measurement sources, we found that the perceived organizational climate for innovation, creative self-efﬁcacy, and expected image gains fully mediated the relationship between TFL and service innovation behavior. We also found that the perceived organizational climate for innovation channeled the entire effect of TFL onto creative self-efﬁcacy and expected image gains. Motivational mechanisms and social-political mechanisms each uniquely affect service innovation behavior when considered simultaneously. Theoretical implications We extend and deepen the existing research in this area by resolving the controversy over the relationship between TFL and service innovation behavior (Avolio et al., 2009). Jaussi and Dionne (2003) found that TFL had no inﬂuence on individual creativity, whereas Shin and Zhou (2003) found a positive relationship between these two constructs. Early innovation research relied predominantly on the motivational perspective to investigate the association between TFL and service innovation behavior (e.g. Gong et al., 2009; Gumusluoglu & Ilsev, 2009; Jaussi & Dionne, 2003; Shin & Zhou, 2003), which neglected the potential effects of other mediating mechanisms. The present study combined motivational and social-political perspectives to build a framework that effectively captures a more comprehensive picture of the relationship between TFL and service innovation behavior. The ﬁndings reveal that three factors fully mediate this relationship: perceived organizational climate for innovation, creative self-efﬁcacy, and expected image gains. TFL is an integral part of successful service innovation. Supervisors may use four TFL behaviors (i.e. idealized inﬂuence, inspirational motivation, intellectual stimulation, and individualized consideration) when seeking to establish an organizational climate that enhances the pivotal role of innovation in corporate success and creates a favorable working environment that encourages employees to seek innovative solutions, which should lead to increased The Service Industries Journal 461 Table 4. Mediation tests. Model Added Path M0 Baseline model: hypothesized paths M1 Perceived organizational climate for innovation →Service innovation behavior Transformational leadership →Creative self-efﬁcacy Transformational leadership →Expected image gains Transformational leadership →Expected image risks M2 M3 M4 Goodness of Fit x2 (181) = 421.08, p .00, RMSEA = 0.066, NNFI = 0.94, CFI = 0.95. x2 (180) = 421.06 x2 (180) = 418.89 x2 (180) = 420.89 x2 (180) = 420.98 Tests of Hypotheses – M0−M1:x2d (1) = .02, p > .88 M0−M2:x2d (1) = 2.19, p > .13 M0−M3:x2d (1) = 0.19, p > .66 M0−M4:x2d (1) = 0.10, p > .75 Notes: RMSEA = root mean squared error of approximation; NNFI = non-normed ﬁt index; and CFI = conﬁrmatory ﬁt index. levels of service innovation behavior due to strengthened creative self-efﬁcacy and expected image gains. Furthermore, the present study empirically incorporates both motivational and socialpolitical mediating mechanisms into one research design, which improves on Gong et al.’s work (2009). Our results reveal that the dual mediating processes simultaneously shape the way TFL inﬂuences service innovation behavior. Although extant research has focused on creative self-efﬁcacy as the important antecedent of innovation behavior, our results highlight that, in addition to creative self-efﬁcacy, the desire to enhance one’s own image serves as another important psychological mechanism that underpins service innovation behavior. Speciﬁcally, our results indicate that creative self-efﬁcacy and expected image gains are positively related to service innovation behavior when considered simultaneously. In addition, the present study extends the work of previous studies by demonstrating that the perceived organizational climate for innovation fully channels the effects of TFL onto both motivational and social-political mediating mechanisms. Somech and DrachZahavy (2013) found that team creativity enhances innovation implementation only when the climate for innovation is high. In this study, we use perceived organizational climate for innovation to connect TFL and dual mediating mechanisms. That is, our ﬁnding extends Somech and Drach-Zahavy’s work (2013) by considering this critical variable as an important precursor of both motivational and social-political mediating processes. We demonstrate that this type of climate indirectly inﬂuences service innovation behavior through creative self-efﬁcacy and expected image gains. This ﬁnding is important because prior innovation research has directly linked this climate to innovation behavior. The current results suggest that the perceived organizational climate for innovation may also have an indirect association with service innovation behavior through both motivational and social-political mechanisms. Finally, this study extends prior research by addressing the call to examine the impact of expected image outcomes on innovation behavior in different cultures. Yuan and Woodman (2010) found that in a Western cultural context, expected image gains had a signiﬁcant and negative effect on innovative behavior (β = –0.22) and expected image risks had a negative effect on innovative behavior (β = –0.19). In contrast with their ﬁndings, the results of the 462 P.-J. Kao et al. present study suggest a positive association between service innovation behavior and expected image gains (β = 0.13) and no signiﬁcant association between service innovation behavior and expected image risks (β = 0.01). Differences in the cultural settings of these studies may explain these contradictory ﬁndings. This study used data obtained in Taiwan, a country with different cultural values from Western countries (Hofstede & Hofstede, 2005). Chinese culture emphasizes the importance of the social ‘face’ (i.e. mianzi) and the moral ‘face’ (i.e. lian) (Hwang, 1987). ‘Mianzi represents the social reputation of a person … that has been deliberately accumulated through effort and achievement and with pride over the course of life’ (Hwang, 2012, p. 267). ‘Lian is the social respect offered by a group to an individual with high morality. A person with lian would do what is proper no matter what difﬁculties were encountered and behave honestly in every situation’ (Hwang, 2012, p. 268). Speciﬁcally, the effect of expected image gains is stronger in Chinese culture because Chinese emphasize mianzi more than Westerners, while the effect of expected image risks on service innovation behavior is weaker in Chinese culture because Chinese also emphasize lian more than Westerners. For these reasons, it is worth considering the extent to which our ﬁndings are culturally speciﬁc. Managerial implications The results of the present study suggest that service ﬁrms should focus greater effort on building training programs that enhance their managers’ TFL style. In addition, ﬁrms should hire and promote employees who have personalities marked by extraversion and emotional stability, as these individuals are more likely to become transformational leaders (Wang et al., 2011). In terms of recommendations to managers of service businesses, the present study highlights the importance of TFL in developing the service innovation behavior of frontline employees. The results show the potential beneﬁt of using several TFL behaviors to strengthen the service innovation behavior of frontline employees. First, managers can serve as inﬂuential models and use verbal persuasion to encourage employees to be innovative (Wang et al., 2011). Second, to stimulate creative thinking, transformational leaders can create hands-on opportunities for subordinates to apply new skills to resolve difﬁcult problems (Sarros et al., 2008). Third, transformational managers can provide individualized support and personalized development guidance to help alleviate potential feelings of anxiety or fear that might arise in employees due to the inherent uncertainties of innovative endeavors (Chen et al., 2013). These behaviors may facilitate service innovation behavior by creating an organizational climate that favors service innovation. For frontline employees, the results of the present study show a positive relationship between creative self-efﬁcacy and service innovation behavior. Employees with highly creative self-efﬁcacy behave in a self-starting manner and are more proactive in tackling unclear/unfamiliar situations. Furthermore, our ﬁndings reveal that expected image gains affect service innovation behavior positively. This image-enhancing motive may encourage frontline employees to use service innovation behavior to create a favorable impression on their managers and coworkers. The ﬁnding is consistent with Baer’s (2012) research that creative ideas are realized when employees expect positive outcomes to be associated with their creative implementation efforts. In conclusion, our results suggest that service ﬁrms should include effective TFL training in their regular managerial training programs. In addition, ﬁrms should create an environment that encourages service innovation behavior. Having managers with a TFL style and an organizational climate that is favorable toward innovation will enhance the The Service Industries Journal 463 creative self-efﬁcacy of frontline employees and help them achieve desired image gains – two factors that have been shown to foster service innovation behavior. Research limitations and further research This study has several limitations that suggest potential avenues for additional research. First, the focus of this study on one service-sector business area limits the observed variability, and thus decreases the external validity of results. However, the single-industry focus facilitated the control of potential industry-level confounding variables. Future research may selectively widen the scope of consideration to other service businesses of a similar nature (e.g. medical and ﬁnancial) as well as to other professional settings in order to increase the generalizability of the ﬁndings. Second, this study examined two psychological mechanisms that mediated the relationship between the perceived organizational climate for innovation and service innovation behavior. Other variables such as intrinsic motivation, prosocial motivation, and mood may be examined to further expand our knowledge of service innovation processes. Third, the present study was conducted in Taiwan. Further research may replicate this study in other cultural contexts and compare ﬁndings. Fourth, participants in the present study had a relatively low level of formal education. Further research may examine the effect of education by comparing the results of respondents in groups segmented by education level. Fifth, because business size and number of employees per salon are largely similar across the hair salon sector in Taiwan, the present study included customer participation as the only control variable. Future research may add other variables as controls. Moreover, it may be fruitful to collect data from service managers in order to analyze data from three sources, rather than two. Finally, the methodology of future studies may be supplemented with qualitative case studies. The present investigation provides a clear direction and purpose for additional research and adds meaningfully to the current knowledge in this area. 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Linking empowering leadership and employee creativity: The inﬂuence of psychological empowerment, intrinsic motivation, and creative process engagement. Academy of Management Journal, 53(1), 107–128. Appendix 1. χ2 Statistics regarding discriminant validity of factor pairs Construct 1. Service Innovation Behavior 2. Creative Self-Efﬁcacy 3. Expected Image Gains 4. Expected Image Risks 5. Perceived Organizational Climate for Service Innovation 6. Transformational Leadership 7. Customer Participation a 1a 2 3 4 x2d (1) = 67.69 x2d (1) = 68.51 x2d (1) = 261.11 x2d (1) = 86.66 x2d (1) = 31.29 x2d (1) = 138.78 x2d (1) = 51.52 x2d (1) = 157.09 x2d (1) = 61.68 x2d (1) = 137.76 x2d (1) = 112.39 x2d (1) = 19.19 x2d (1) = 106.98 x2d (1) = 99.79 x2d (1) = 95.97 x2d (1) = 102.22 x2d (1) = 153.75 x2d (1) = 113.28 5 6 x2d (1) = 55.05 x2d (1) = 110.01 x2d (1) = 135.16 7 The difference in the chi-square values of the two models (i.e. the baseline and the constrained model), with one degree of freedom.