1

Taking a Regulatory Fit Perspective for Understanding Employees in their Work

Context

Griet VAN DER VURST Bart LARIVIERE

Abstract This study investigates employee attitudes and behaviors from a regulatory fit perspective, in particular organizational commitment, job performance and helping behaviors. Regulatory focus reflects goal orientations, with promotion focus concentrating on advancement and ideals and prevention focus emphasizing security and oughts. Goal orientations can be chronic (i.e., personality trait) and context-dependent (e.g., work context). In a service context, regulatory fit is experienced when employees’ chronic goal orientations are congruent with the strategies employed at work. Drawing on various literature streams, this study proposes a framework of employee - work context fit and yields three important insights. First, regulatory fit has a strong positive impact on employees’ commitment and behavior, except for continuance commitment based on few job alternatives. Second, for job performance, both goal orientations are found to be effective in which avoiding a misfit in prevention has the strongest impact. Third, frontline employees and back-office workers experience different commitment levels. Key words: Employees, Regulatory Focus, Regulatory Fit, Organizational Commitment, Job Performance, Helping Behaviors Griet VAN DER VURST PhD Candidate, Center for Service Intelligence, Ghent University Tweekerkenstraat 2, 9000 Ghent, BELGIUM E-mail: Griet.Vandervurst@UGent.be Bart LARIVIERE Associate Professor of Service Management, Center for Service Intelligence, Ghent University, Tweekerkenstraat 2, 9000 Ghent, BELGIUM E-mail: Bart.Lariviere@UGent.be

2

INTRODUCTION Service employees provide and/or co-create services (Coulter and Coulter 2002; Ostrom et al. 2010). As a consequence, employee behaviors and attitudes affect service quality perceived and experienced by customers, customer satisfaction and subsequent firm success (Bowen and Schneider 2013; Heskett et al. 1994). As such, organizational commitment is a crucial employee attitude contributing to the customer’s service experience, because of its determining role for service quality (e.g. Gazzolli et al. 2013; Malhotra and Mukherjee 2004). Organizational commitment reflects an employee’s attitude towards the organization, suggesting a strong bond and a low likelihood of leaving (Allen and Meyer 1996). Employees that remain with an organization become better at delivering service and provide continuity in customer relationships. Next to this attitude, employees’ behaviors also determine the customer’s service experience (De Keyser et al. 2015; Meyer and Schwager 2007). Employees exhibit both in-role and extra-role behaviors. While in-role behaviors are the actions described in their job description, extra-role behaviors are discretionary efforts, not formally written in the job description, that are beneficial for the company. In-role behavior thus determines job performance. Helping co-workers (e.g. with a heavy work load, after an absence, etc.) is a form of extra-role behaviors that contributes positively to firm success and is selected as an appealing employee engagement behavior in service encounters, as customers also need to be served when colleagues are absent because of illness, when colleagues are insecure, inefficient or ineffective caused by a lack of expertise or when colleagues experience a work-overload. In all these situations, a ‘giving hand’ engagement behavior by a colleague may have an impact on serving customers. In response to Bowen’s (2015) call for renewed interest in employees as a key research topic in service, the present research focuses on improving service outcomes by investigating these employee attitudes and behaviors from a regulatory focus perspective. What employees do depends on the goals they are pursuing. Regulatory Focus (RF) Theory (Higgins 1997) proposes that there are two goal-striving orientations: promotion focus and prevention focus. Promotion-focused individuals are motivated to work toward achieving their ideals using eagerness strategies, while prevention-focused individuals are motivated to fulfill their obligations using vigilant strategies. This study investigates both chronic regulatory focus and work-based regulatory focus. The former represents someone’s dispositional goal orientation(s) in everyday life (RFP, i.e. a personality trait) and the latter reflects strategies employed specifically at work (RFW, i.e. context-specific). Whereas employees can have a dominant personally-preferred regulatory focus in general, they are exposed to leadership behavior, organizational climate and work rules affecting the strategies used for reaching goals at work. This dual approach is taken to be able to examine how fit between these goal orientations (RFP and RFW) affects service employee behaviors and attitudes. Previous research established that regulatory fit is beneficial for motivation, persistence and well-being (e.g. Higgins 2000; Aaker and Lee 2006). Current knowledge on regulatory fit in the work context is limited. Table 1 (available on request) provides a literature review of previous studies that linked RFP and/or RFW to organizational commitment, in-role (i.e., job performance) and extra-role (i.e., citizenship behaviors) behaviors. Table 1 reveals that most studies have focused on either RFP or RFW in isolation. Regulatory fit, however, has not been studied in relation to these outcomes, although fit results in

3

employees feeling better and arguably in stronger patterns for these outcomes. Therefore, this research aims to provide insight into the effects of regulatory focus on employee outcomes and to enhance our understanding of aligning individuals’ goal-striving personalities (RFP) with a well-fitting work context (RFW). More precisely, the authors study how fit between one’s chronic regulatory orientation and one’s work-specific regulatory strategies affect employee performance, extra-role helping behaviors and commitment. In doing so, this research uses the ‘response surface analysis’ technique that is proposed by Shanock et al. (2010) to model congruence (fit) and discrepancies (misfit) between RFP and RFW and its impact on the outcome variables. In the next section, we present the theoretical background and hypotheses of our study. Thereafter, the methodology is explained, the results are provided and finally, the conclusions, theoretical and managerial implications and suggestions for future research are discussed.

THEORETICAL BACKGROUND & HYPOTHESES The aim of this study is examining the effect of regulatory fit on work attitudes and behaviors for service employees, as shown in Figure 1. Below, we introduce the theoretical framework by explaining the constructs. Next, the hypotheses are developed for each of the employee outcome variables separately.

FIGURE 1: Conceptual Framework 1. Regulatory Focus Theory

Higgins (1997) distinguishes two regulatory focus (RF) orientations: (a) a promotion focus, which is concerned with needs for advancement, growth and accomplishments, and (b) a prevention focus, which concerned with needs for security, safety and responsibilities. The regulatory focus theory postulates that a promotion focus emphasizes the ‘ideal’ self, as reflected in the person’s hopes and aspirations, whereas a prevention focus emphasizes the ‘ought’ self, as reflected in the person’s duties and obligations. People strive to align themselves with these goals or standards. Promotion-focused individuals are motivated to approach their

4

ideal selves (desired end-states), for which they employ eagerness means (Förster et al. 1998; Higgins et al. 1994, 2001). They focus on the presence of positive outcomes as they perceive their environment in terms of gains and nongains (Brendl et al. 1995; Shah et al. 1998). As a consequence, they want to ensure hits and minimize errors of omission (e.g. missing an opportunity to make progress) (Crowe and Higgins 1997; Higgins et al. 2001). Prevention-focused individuals are motivated to avoid mismatches to their ought selves (desired end-states), by employing vigilance means (Förster et al. 1998; Higgins et al. 1994, 2001). They focus on the absence of negative outcomes as they perceive their environment in terms of losses and nonlosses (Brendl et al. 1995; Shah et al. 1998). Thus, they want to minimize errors of commission (e.g. doing something that turns out to be a mistake) (Crowe and Higgins 1997; Higgins et al. 2001). These foci also have different implications for the emotional experience of success or failure, along the cheerfulness/dejection continuum for promotion-focused individuals and along the quiescence/agitation continuum for prevention-focused individuals (Higgins 1987; 1997). Promotion focus and prevention focus are both goal-striving orientations that coexist independently (Higgins 1997; Higgins et al. 2001; Wallace and Chen 2006). As such, a person can have high levels on both promotion and prevention foci.

a) Personal Regulatory Focus (RFP)

Previous research found that some people are chronically more promotion-oriented and others more prevention-oriented (Higgins 1997; Higgins et al. 1994; Higgins et al. 1997). Indeed, chronic RF pertains to a general tendency in everyday life, which has been shown to be a reliable individual difference variable (Higgins et al. 2001). RFP has been used in service research to study individual’s goal striving orientations (e.g. Wirtz and Lwin 2009; Smith et al. 2014; Wang et al. 2013) in which the individual as a unit of analysis is studied from a customer perspective. In this study, an individual’s RFP is considered from an employee perspective. The term RFP will be used in the remainder of this study for RF as chronic personal orientation. Higgins (1987) argued that childhood socialization experiences contribute to its development by communicating what matters. When parents are protective and use the threat of punishment (negative outcomes), strong oughts are created and a prevention focus is fostered; when parents are encouraging and use rewards (such as praise) and the withdrawal thereof (absence & presence of positive outcomes) as a discipline, strong ideals are created and a promotion focus is fostered (e.g. Higgins 1987, 1997; Crowe and Higgins 1997). Although RF can also be situationally primed (e.g. Shah et al. 1998), this study will focus on chronic RFP.

b) Work-Specific Regulatory Orientations (RFW)

Next to RFP, which is often used in social psychology and marketing, work-specific RF is used as a more context-specific variable in organizational behavior. Brockner and Higgins (2001) were the first to introduce RF at work and later scales were developed for measuring this domain-specific RF (e.g. Wallace et al. 2005). We will use the term RFW for RF as work disposition. Although RFP and RFW focus on another context (everyday life vs. work life), they have similar underlying fundamentals. Wallace (Wallace and Chen 2006; Wallace et al. 2008, p 97) defined and operationalized a work promotion focus as “a moderately stable engagement strategy with a focus on accomplishing more tasks, more quickly” and a work prevention focus as “a moderately stable engagement strategy with a focus on

5

performing tasks accurately and in accordance with one’s duties”. Thus, promotion is concerned with progress, achievement, speed and eagerness strategies, while prevention is concerned with attention for detail, following rules, fulfilling responsibilities and vigilance strategies. Similar to personal regulatory focus, work promotion and work prevention are independent of one another (Wallace and Chen 2006; Wallace et al. 2009).

RFW consists of “both stable personal attributes and malleable situational stimuli” (e.g. Wallace et al. 2009, p.807). Thus, there are situational stimuli in a work setting that drive the development of work-specific regulatory orientations. Similar to childhood socialization, employees experience a socialization process when entering and staying in an organization that informs them of the expected attitudes and behaviors. Brockner and Higgins (2001) argued that employees’ prevention and promotion foci can be manipulated through everyday behaviors of supervisors. They do this by communicating which behaviors are hoped for and/or which behaviors should be performed, by stressing ideals and/or responsibilities, by serving as role model and by the way they give feedback (Brockner and Higgins 2001). Indeed, previous research has shown that certain leadership styles (e.g. Kark and Van Dijk 2007; Neubert et al. 2008, 2013) foster promotion focus and others prevention focus in followers or that certain styles are more appropriate for promotion subordinates and other for prevention subordinates (Hamstra et al. 2011; Moss et al. 2006). Moreover, congruent feedback (Van Dijk and Kluger 2004) is more beneficial, such that negative feedback increases motivation for prevention-focused individuals and positive feedback for promotion-focused individuals. Brockner and Higgins (2001) also asserted that the contextual aspects such as reward system, organizational culture and procedures influence employees’ RF. These contextual factors are expected to remain relatively stable over time, as long as there are no critical changes in the environment (Brockner and Higgins 2001). As such, it is clear that RFW is moderately stable, unless an employee experiences changes in these stimuli. 2. Employee Attitudes: Organizational Commitment

Organizational commitment is defined as “a psychological link between the employee and his or her organization that makes it less likely that the employee will voluntarily leave the organization”(Allen and Meyer 1996, p.252) and is therefore considered as a crucial employee attitude (Klein et al. 2009) contributing to the customer’s service experience, because of its determining role for service quality (e.g. Gazzolli et al. 2013; Malhotra and Mukherjee 2004). Meyer and Allen’s (1991) well-established model has conceived organizational commitment as consisting of three components: affective commitment (AC), normative commitment (NC) and continuance commitment (CC). These components reflect different psychological states or mindsets of the employee vis-à-vis the organization: a desire, an obligation and a need to remain with the organization, respectively (Allen and Meyer 1990). Affective commitment reflects employees' emotional attachment to, identification with and involvement in the organization. Normative commitment is about a feeling of (moral) obligation to remain with the organization and to reciprocate the benefits received from the organization (e.g. training). Continuance commitment has two distinct dimensions, one dimension involves the personal sacrifices (e.g. time and effort invested in acquiring an organization-specific skill) associated with leaving the organization (CC-HiSac) and the other an awareness of a lack of job alternatives

6

(CC-FewAlt) (e.g. Hackett et al. 1994; Jaros 1997; Meyer et al. 1990, 2002; Vandenberghe et al. 2007; Taing et al. 2011). There are several conceptual suggestions on the relationship between RF and the commitment components (Johnson et al. 2010; Kark and Van Dijk 2007; Meyer et al. 2004; Van Dijk and Kluger 2004). These conceptual papers make allusions to RF in general or RFP, except for Kark and Van Dijk (2007) who include both chronic RFP and situational RF (RF induced by the work context). Despite its importance and conceptual suggestions to distinguish between four aforementioned types of commitment (e.g. Hackett et al., 1994; Jaros et al., 1997; Meyer et al., 2002; Vandenberghe et al., 2007; Taing et al., 2011), especially in their relationship with RF (e.g., Johnson et al. 2010), the empirical papers related to this topic took a fragmented perspective when studying RF and commitment (Markovits et al. 2008; Moss et al. 2006; Neubert et al. 2013; Tseng and Kang 2008). Regarding the commitment components, Markovits et al. (2008), Lanaj et al.’s (2012) and Gorman et al.’s (2012) meta-analyses only incorporate three components of commitment (AC, NC and CC), Moss et al. (2006) and Neubert et al. (2013) only include AC and NC and Tseng and Kang (2008) include a higher-order construct of organizational commitment. Further, Markovits et al. (2008), Moss et al. (2006) and Tseng and Kang (2008) only measured RFP, Neubert et al. (2013) only incorporated RFW. Although the meta-analysis by Lanaj et al. (2012) tests both RFP and RFW correlations with commitment separately, they do not test how RFP and RFW together drive commitment. This paper thus contributes to existing knowledge by investigating the four commitment components, taking into account the two dimensions of CC, and by including both RFP and RFW to examine the effect of regulatory fit on employee outcomes.

3. Employee Behaviors

Table 1 shows some performance metrics that have been studied in an employee setting. Most studies focused on job performance and fewer studies examined the influence of RF on extra-role behaviors. a) Job Performance

Since regulatory orientations reflect motivational goal-oriented constructs, it is logical that both RFP and RFW have been found to be important for predicting performance. Many studies investigate how regulatory focus affects performance on specific laboratory tasks (e.g. anagram task). Although much work on RF investigates performance for small laboratory or hypothetical tasks, Lanaj et al. (2012) find RF a valuable predictor of work behavior, and especially of work performance. Prevention-focused individuals are vigilant against mistakes, focus on accuracy (Förster et al. 2003; Wallace et al. 2008), and adhere to rules and regulations which contributes to (safety) performance (Förster et al. 2003; Wallace and Chen 2006; Wallace et al. 2008, 2009). Promotion-focused individuals are eager to make progress, aim to do a lot of work in a short time and focus on speed (Förster et al. 2003; Wallace et al. 2008), which contributes to (productivity) performance (Förster et al. 2003; Wallace and Chen 2006; Wallace et al. 2008, 2009). Moreover, promotion focus has also been associated with innovative performance (Wallace et al. 2013), as promotion-focused individuals show more creative behavior (Crowe and Higgins 1997; Dong et al. 2015; Friedman and Forster 2001; Neubert et al. 2008), are more daring to take risks (e.g. Crowe and Higgins 1997) and their positive emotions facilitate creative

7

thinking (Lanaj et al. 2012). While promotion-focused individuals aim for maximum performance (Förster et al. 2003; Brendl and Higgins 1996), prevention-focused individuals try to satisfy minimum requirements (Brendl and Higgins 1996).

b) Colleague Helping Behavior

Our research looks into a particular form of extra-role behavior: helping behavior. This is in line with Lanaj et al. (2012)’s recommendation to look into the facets of OCB separately. From a managerial point of view, it is crucial that a service delivery is always guaranteed, also in these situations when some employees are absent (because of illness), are overworked or need support (e.g., less experienced employees). A “giving hand” engagement behavior by a colleague might therefore be beneficial for a firm’s success. Although literature proposed items and constructs that encompass this helping behavior (e.g., Williams and Anderson 1991; Neubert et al. 2008), the RF literature has typically ignored this specific type of engagement behavior. Therefore, this study includes colleague helping behavior as an important employee outcome and tests its relationship with both RFP and RFW. 4. Regulatory Fit Theory & Hypotheses Development

Regulatory fit reflects the compatibility between someone’s regulatory orientation and the strategies he/she used for goal pursuit (Higgins 2000). Experiencing regulatory fit results in enhanced motivation and greater persistence (Higgins 2000; Shah et al. 1998; Spiegel et al. 2004), higher performance (Freitas et al. 2002; Keller and Bless 2006; Shah et al. 1998), more task enjoyment (Freitas et al. 2002), higher subjective well-being (Aaker and Lee 2006) and goal pursuit feeling right (Higgins 2000; Camacho et al. 2003). Overall, regulatory fit thus has beneficial effects on performance (motivation). The phenomenon of regulatory fit has typically been studied in the consumer behavior (CB) marketing literature, and has mainly been operationalized using two approaches (Aaker and Lee 2006; Higgins 2000; Motyka et al. 2014). In the first approach, respondents/consumers pursue a goal using eager or vigilant means matching one’s regulatory orientation (e.g. Freitas et al. 2002; Spiegel et al. 2004). In the second approach, respondents/consumers are asked to complete a task for a reward compatible with their regulatory orientation (gain or nonloss) (e.g. Lee and Aaker 2004; Shah et al. 1998). As a result, most studies on regulatory fit focused on individuals in their role and context of being consumers (as opposed to employees as subjects of investigation) and took place in a laboratory, including some sort of manipulation to create ‘fit conditions’. Although the vast majority of research on regulatory fit has been in an experimental CB setting, there exist exceptions that study regulatory fit for employees. Some of these studies used an actual work context (e.g. Neubert et al. 2008; Hamstra et al. 2014, study 1 and 2), whereas others used hypothetical situations (e.g. Sassenberg and Scholl 2013, study 1 and 3). These studies investigate regulatory fit in an employee setting and how certain leadership styles (Hamstra et al. 2014; Kark and Van Dijk 2007; Moss et al. 2006), work values (Kark and Van Dijk 2007; Sassenberg and Scholl 2013) and a leader’s promotion- or prevention-oriented communicated vision (Stam et al. 2010) are more congruent with an employee’s regulatory focus than others. For example, it is suggested and found that transformational leadership fits with promotion focus (Hamstra et al. 2014; Kark and Van Dijk 2007).

8

Hence, existing studies used only one view of RF (chronic or work-specific) and a particular work variable (e.g. leadership style; Hamstra et al. 2014) or investigated fit in a hypothetical context. To our knowledge, there exist only three studies in the work context that examined the fit between trait and state regulatory focus, but they incorporated other outcome variables. These studies examine how fit influences perceived leader effectiveness (Hamstra et al. 2014), job crafting behavior (Petrou and Demerouti 2015) and adaptation to change (Petrou et al. 2015). Moreover, these studies use interaction terms to assess fit, but not the recommended methodology to analyze fit (Shanock et al. 2010). Hamstra et al. (2014) also assessed regulatory fit directly through items (reflecting the fit between an employee and his supervisor, rather than actual regulatory fit). This study investigates the fit between an employee’s chronic regulatory orientation and the regulatory work strategies he/she employs at work for actual employees in their work environment. In the work context, work-specific regulatory focus reflects an employee’s situational RF or the regulatory strategies required by the work (situation), whereas someone’s chronic RF reflects that person’s general disposition for regulation. Thus, an employee experiences regulatory fit at work when his/her chronic regulatory focus is congruent with the goal pursuit strategies adopted at work (or the expected consequences of behavior). In line with Higgins’ (2000) theorizing about regulatory fit, we expect that experiencing fit between RFP and RFW will affect both employee attitudes and behaviors. Moreover, we use the recommended methodology to analyze fit (Shanock et al. 2010). RF – Affective Commitment There seems to be considerable agreement on the promotion focus – AC relationship in literature (Gorman et al. 2012; Johnson et al. 2010; Kark and Van Dijk 2007; Lanaj, et al. 2012; Markovits et al. 2008; Meyer et al. 2004; Neubert, et al. 2013; Van Dijk and Kluger 2004). The mindset associated with promotion focus is one of accomplishments and intrinsic motivation. Promotion-focused individuals are driven by their ideals and value advancement, for which the organization might be an enabler. Reaching aspirations and making progress is something that promotion-focused individuals want to do (Brockner and Higgins 2001, p.54), this mindset of desire is associated with AC. Thus, promotion-focused individuals are expected to be committed to the organization in an autonomous form (AC) (Meyer et al. 2004; Kark and Van Dijk 2007). Employees with a personal promotion focus that are able to demonstrate work-specific promotion strategies at work will experience fit. As a consequence, their promotion mindset is much stronger, and thus the expected relationship between promotion and AC will also be stronger when there is promotion fit. Therefore, we hypothesize the following:

H1: There is a positive relationship between promot ion focus and AC, in such a way that promotion fit strengthens AC.

RF – Normative Commitment Previous theorizing suggests that prevention focus should map onto NC (Gorman et al. 2012; Johnson et al. 2010; Kark and Van Dijk 2007; Lanaj et al. 2012; Meyer et al. 2004). The mindset associated with prevention focus is one of responsibilities and obligations. Fulfilling duties is something that prevention-focused individuals believe

9

they have to do (Brockner and Higgins 2001, p.54), they see it as an obligation. These feelings of obligation toward the organization might cause those individuals to become normatively committed to the organization (Kark and Van Dijk 2007). As a result, remaining with the organization is the right and moral thing to do and will be perceived as just another duty by prevention-focused employees. Employees with a personal prevention focus that are able to demonstrate a work-specific prevention focus at work, will experience fit. As a consequence, their feeling of obligation toward the organization and their NC might be strengthened. In accordance to these theoretical suggestions we hypothesize:

H2: There is a positive relationship between preven tion focus and NC; in such a way that prevention fit strengthens NC.

RF – Continuance Commitment So far, the relationship between RF and continuance commitment has always been approached with CC as one-dimensional construct, either in positive association with prevention (Gorman et al. 2012; Kark and Van Dijk 2007; Markovits et al. 2008; Meyer et al. 2004; Van Dijk and Kluger 2004) or both promotion and prevention (Lanaj et al. 2012). Johnson et al.’s propositions (2010) suggest that the two dimensions of CC are differently related to RF. Therefore, we include both dimensions separately in our investigation. RF – Continuance Commitment: Few Alternatives (CC-F ewAlt) Johnson et al. (2010) proposed a link between promotion focus and CC-Few alternatives reasoning that the search for more desirable job opportunities elsewhere represents a gain and that interpreting the environment in terms of gains and non-gains reflects a promotion focus. Additionally, promotion-focused individuals are more open to change (Liberman et al. 1999). Therefore, promotion-focused individuals are less likely to develop CC-FewAlt. We again argue that fit will strengthen this relationship.

H3: Promotion focus relates negatively to CC-FewAlt , in such a way that promotion fit reduces CC-FewAlt.

RF – Continuance Commitment: High Sacrifice (CC-HiS ac) Johnson et al. (2010) also proposed a link between prevention focus and CC- HiSac, arguing that employees who think about what would be sacrificed when they quit the organization interpret the environment in terms of potential losses, which reflects a prevention focus. Indeed, a necessity to stay with the organization and fulfill minimum requirements in order to avoid losses corresponds with both the continuance commitment and prevention focus mindset. Thus, prevention-focused individuals are likely to be committed to the organization in calculative way, reluctant to set made investments and job security at stake (Liberman et al. 1999). We again argue that fit will strengthen this relationship according to the premises of the Regulatory Fit Theory.

H4: Prevention focus relates positively CC-HiSac, i n such a way that prevention fit strengthens CC-HiSac.

10

RF- Job Performance / In-Role Behavior Extant research indicates a positive association between promotion focus and performance (Gorman et al. 2012; Johnson and Chang 2008; Wallace et al. 2009; Lanaj et al. 2012). Individuals with a promotion focus set challenging goals, aim for maximal performance, do their work eagerly and fast, show greater persistence, are more creative and innovative than individuals with a prevention focus (e.g. Kark and Van Dijk 2007). The ideal goals that they set for themselves stipulate the way to success. All together, these promotion-focused task behaviors contribute to effective performance. Moreover, van Beek et al. (2013) find a link between promotion focus and work engagement. Stam et al. (2010) find that regulatory fit in leadership style and an employee’s RFP contributes to better performance compared to nonfit. As a consequence, we hypothesize:

H5a: Promotion focus is positively related to job p erformance, as such performance will be better when employees experienc e promotion fit.

Regarding the relationship between prevention focus and performance, some researchers expect a negative relationship (Gorman et al. 2012; Johnson and Chang 2008) and others a positive relationship (Lanaj et al. 2012; Neubert et al. 2008; Wallace et al. 2009). Findings are inconsistent, going from a positive association (Neubert et al. 2008; Wallace et al. 2009) to unrelated (Gorman et al. 2012; Lanaj et al. 2012) to negative association (Johnson and Chang 2008). van Beek et al. (2013) find a link between prevention focus and workaholism. Individuals with a prevention focus aim to do the minimally required task behaviors, to fulfill responsibilities and to be vigilant and accurate (in order to avoid negative consequences). Although some authors (e.g. Johnson and Chang 2008) suggest that prevention focus might be less effective in directing behavior than promotion focus, we expect prevention focus to facilitate in-role behavior, i.e. fulfilling the prescribed job tasks.

H5b: Prevention focus is positively related to job performance, as such performance will be better when employees experienc e prevention fit.

RF – Helping Colleagues / Extra- Role Behavior Based on previous studies, a promotion focus is expected to be associated with extra-role behaviors (Gorman et al. 2012; Johnson and Chang 2008; Lanaj et al. 2012; Neubert et al. 2008; Wallace et al. 2009). We thus expect a positive association of promotion focus with helping behavior, in line with Neubert et al.’s (2008) finding. Promotion-focused individuals aim for maximum performance, which might include performance of colleagues, thus helping them contributes to fulfilling this ideal. As van Beek et al. (2013, p.48) argue “a promotion-focused employee who considers good performance as an accomplishment is likely to approach matches to this desired goal by performing extra-role behavior”. They are also more likely to see the gains of performing helping behavior. One possible reward is getting opportunities for advancement and polishing their image (Bolino 1999; Lanaj et al. 2012). We hypothesize:

H6: Promotion focus is positively related to helpin g behaviors, as such promotion fit strengthens helping behaviors.

11

METHODOLOGY

Data Collection & Sample Following Neubert et al. (2008) and Hamstra et al. (2014), an actual work context is chosen to study RF and employee outcomes. As suggested by Klein et al. (2009, p. 407), we approached individuals from several organizations such that the data better reflect the general employee population. Surveys were completed by 238 adults working in services in Belgium. Ten respondents were excluded from the data analyses because they failed to fill out the majority of questions related to the relevant concepts of this study. Employee demographics were as follows: 40 % were male; their average age was 43 years (SD=11.1); their average tenure in their current organization was 16 years (SD=11.3) and 71% of the respondents in the sample had frequent customer contact, and can be referred to as frontline employees (or front office workers) as opposed to back office workers. In order to address the potential impact of sample characteristics on our tested model (Figure 1), these demographic variables are accounted for in the remainder of this paper. Measures All measures were adapted from the literature. Performance and helping behavior: Scale items of Williams and Anderson (1991) were adapted to measure job performance and helping behavior, using a 5-point Likert scale (1= strongly disagree, 5= strongly agree). Commitment: The four components of commitment were assessed using the organizational commitment scale of Vandenberghe et al. (2007; Bentein et al. 2005), which consists of 18 items and which was previously employed and validated in a Belgian context. Responses were measured on a 5-point Likert scale (1= strongly disagree, 5= strongly agree). Work-Based Regulatory Focus: Items from the Regulatory Focus at Work scale of Wallace, Chen, and Kanfer (2005; Wallace, Johnson, and Frazier 2009) assessed RFW. Respondents indicated how often they focused on certain thoughts or activities when they are working (1= never, 5=constantly). Personality-Based Regulatory Focus: RFP was measured using the composite scale of Haws, Dholakia, and Bearden (2010). These authors recently reviewed several RFP measures and developed a composite scale which they recommended for measuring RFP. Employees responded to all items using a 5-point Likert scale (1= strongly disagree, 5= strongly agree). Controls: The control variables included gender, age (in years), organizational tenure (in years), and a dummy variable for direct customer contact which denotes whether the employee is a frontline employee versus back office worker. DATA ANALYSIS

First, the quality of the measurement model was investigated by means of CFA. Next, the relationship between RF and employee outcomes as depicted in the conceptual framework (Figure 1) was examined. For this, we compared a base model including RFP (as prior studies in the marketing, organizational behavior, and social psychology literature just focused on this particular RF type) and a second model that explicitly tested for the impact of regulatory fit using the methodology of response surface analysis. RSA is a statistical approach that allows researchers to examine the extent to which combinations of two predictor variables relate to an outcome variable, particularly in the case when fit (agreement) between the two

12

predictor variables is a central consideration (Shanock et al. 2010). That way, we examined how congruence and discrepancies in work-based and person-based regulatory foci related to our outcome variables. In order to test our hypotheses, we ran polynomial regressions in MPlus using Bayesian estimation. Given our small sample, we chose for a Bayesian method (following the approach of Yuan and MacKinnon (2009) and Zhao et al. (2010)). FINDINGS

All descriptive data, reliability measures and zero-order correlations are presented in Table 2. Except for RFP, scales demonstrated strong reliability immediately. We had to delete some items due to low factor loadings (lower than 0.6) and due to low AVE (lower than 0.5). Using the combined thresholds for fit indices proposed by Hu and Bentler (1999) (CFI>0.95; RMSEA<0.06; SRMR<0.08), our final measurement model had acceptable fit: CFA=0.95, RMSEA=0.042; and SRMR=0.053. The final measurement model also showed discriminant validity, since all AVEs were higher than the squared standardized correlations. TABLE 2: Descriptives, Internal Consistency Reliabi lity, and Correlation Matrix

Variables M SD CR 1 2 3 4 5 6 7 8 9 1. Pprom 3.26 .84 .74 2. Pprev 3.05 .98 .75 .30** 3. Wprom 3.60 .66 .81 .31** .35** 4. Wprev 4.19 .63 .92 .10 .17** .49** 5. AC 3.78 .78 .90 .09 -.06 .24** .21** 6. NC 2.77 1.05 .92 .19** .16* .30** .15* .51** 7.CC- FewAlt

2.41 1.11 .88 -.10 .20** .03 .12 -.23**

-.11

8. CC-HiSac

3.13 .92 .85 -.10 .16* .04 .12 .01 .12 .30**

9. JP 4.42 .52 .89 .11 -.14* .07 .24** .15* -.06 .03 .18** 10 HB 3.99 .64 .80 .05 -.12 .11 .23** .20** .14* -.09 .04 .25** Note: M=mean construct score (unweighted); SD=standard deviation; CR=composite reliability; the off-diagonal numbers represent the correlations among constructs; *p<.05, **p<.01 Table 3 shows the results of our analysis. Overall, our findings indicate an additive model for regulatory focus. Affective commitment is enhanced by personal and work-specific promotion focus in combination. Thus, high personal promotion and work promotion (i.e. promotion fit) result in higher affective commitment (indicated by a1=0.217), as predicted by H1. Interestingly, there is a negative effect of nonfit (a3= -0.236). The bigger the discrepancy between personal and work promotion is, the lower AC. Similarly, prevention fit enhances normative commitment, which supports H2. The positive additive effect of fit diminishes with increasing prevention values (indicated by a negative value for a2). Thus, the effect of increasing from 3-3 to 4-4 on NC is stronger than the effect from 4-4 to 5-5 on NC. Prevention fit also enhances continuance commitment based on high sacrifices related to leaving the organization, as predicted by H3. H4 is not supported, since only the control variables have a significant relationship with continuance commitment based on few perceived alternatives. If we run the model without controls, we do find that personal promotion has a significant negative effect on CCFA (p-values 0.06 for model 1 and 0.03 for model 2). Promotion fit is found to have a positive effect on performance, supporting H5a. Promotion misfit also increases job performance, this is, when personal promotion is low and work promotion is high or vice versa. Thus, it seems that high performance

13

AC NC CCHiSac CCFewAlt JP

HB

Model 1

age -0.193* -0.291* 0.073 0.107 0.081

-0.019

gender 0.015 0.074 -0.032 -0.184* -0.202* -0.031

organizational tenure 0.224* 0.196* 0.188* 0.289* 0.110 0.065

d_customer contact 0.041 0.164* -0.005 -0.106* 0.053 -0.089

personal promotion 0.073 - - -0.014 0.218* 0.055

personal prevention - 0.174* 0.180* - -0.192* -

R2 5% 9.9% 10.2% 18.5% 13.9% 3.2%

Model 2

age -0.218* -0.273* 0.072 0.108 0.081 -0.009

gender 0.049 0.081 -0.045 -0.178* -0.210* -0.030

organizational tenure 0.230* 0.171* 0.182* 0.290* 0.051 0.053

d_customer contact 0.077 0.172* -0.011 -0.103(p=0.057) 0.044 -0.085

personal promotion -0.009 - - -0.027 0.232* 0.032

personal prevention - 0.126* 0.195* - -0.185* -

work promotion 0.226* - - 0.018 -0.037 0.116

work prevention - 0.141* 0.033 - 0.272* -

personal promotion

squared 0.045 - - -0.002 0.065

0.029

work prom sq 0.011 - - -0.024 0.018

-0.017

wpprom -0.099 - - 0.001 0.021 0.089

pprev sq - -0.112* 0.048 - 0.053 -

wprev sq - 0.016 0.026 - 0.093* -

wpprev - -0.067 -0.093 - 0.037 -

R2 11.8% 14.7% 12.6% 19.6% 24.1% 6.5%

Response surface analysis Prom fit Prev fit Prev fit Prom fit Prev fit Prom fit Prom fit

a1 (fit linear) 0.217* 0.266* 0.228* -0.008 0.087 0.195* 0.148*

a2 (fit nonlinear) -0.043 -0.163* -0.019 -0.026 0.183* 0.104 0.102

a3 (nonfit linear) -0.236* -0.015 0.162 -0.045 -0.457* 0.269* -0.084

Tableau mis en forme

Commentaire [BL1]:

Commentaire [BL2]:

14

a4 (nonfit nonlinear) 0.155 -0.029 0.167 -0.027 0.109 0.062 -0.077

TABLE 3: Results for surface response analysis through polyn omial regression in Mplus with Bayesian estimation Model 1 AC NC CCHiSac CCFewAlt JP

HB

Age -0.193* -0.291* 0.073 0.107 0.081 -0.019

Gender 0.015 0.074 -0.032 -0.184* -0.202* -0.031

Organizational tenure 0.224* 0.196* 0.188* 0.289* 0.110 0.065

D_customer contact 0.041 0.164* -0.005 -0.106* 0.053 -0.089

Personal promotion 0.073 - - -0.014 0.218* 0.055

Personal prevention - 0.174* 0.180* - -0.192* -

R2 5% 9.9% 10.2% 18.5% 13.9% 3.2%

Model 2

Age -0.218* -0.273* 0.072 0.108 0.081 -0.009

Gender 0.049 0.081 -0.045 -0.178* -0.210* -0.030

Organizational tenure 0.230* 0.171* 0.182* 0.290* 0.051 0.053

D_customer contact 0.077 0.172* -0.011 -0.103(p=0.057) 0.044 -0.085

Personal promotion -0.009 - - -0.027 0.232* 0.032

Personal prevention - 0.126* 0.195* - -0.185* -

Work promotion 0.226* - - 0.018 -0.037 0.116

Work prevention - 0.141* 0.033 - 0.272* -

Personal promotion squared 0.045 - - -0.002 0.065 0.029

Work promotion squared 0.011 - - -0.024 0.018 -0.017

Work promotion x personal

promotion -0.099 - - 0.001 0.021 0.089

Personal prevention squared - -0.112* 0.048 - 0.053 -

Work prevention squared - 0.016 0.026 - 0.093* -

Work prevention x personal

prevention - -0.067 -0.093 - 0.037 -

R2 11.8% 14.7% 12.6% 19.6% 24.1% 6.5%

Response surface analysis Prom fit Prev fit Prev fit Prom fit Prev fit Prom fit Prom fit

a1 (fit linear) 0.217* 0.266* 0.228* -0.008 0.087 0.195* 0.148*

a2 (fit nonlinear) -0.043 -0.163* -0.019 -0.026 0.183* 0.104 0.102

a3 (nonfit linear) -0.236* -0.015 0.162 -0.045 -0.457* 0.269* -0.084

a4 (nonfit nonlinear) 0.155 -0.029 0.167 -0.027 0.109 0.062 -0.077

Note: AC= affective commitment; NC= normative commitment; CCHiSac= Continuance Commitment based on High Sacrifices for leaving; CCFewAlt= Continuance Commitment based on few perceived job alternatives; JP= job performance; HB= helping behavior; * significant at 0.05 (Bayesian p-values)

15

Hypotheses

Findings R2

improvement (when accounting for regulatory fit)

H1 There is a positive relationship between promotion focus and AC, and promotion fit strengthens this positive relationship.

supported 6,8%*

H2 There is a positive relationship between prevention focus and NC; and experiencing prevention fit will strengthen this relationship.

supported 4,8%*

H3 Promotion focus relates negatively to CC-FewAlt , but promotion fit has a positive influence on CC-FewAlt.and promotion fit strengthens this relationship

not supported

1,1%n.a.

H4 Prevention focus relates positively CC-HiSac , and prevention fit strengthens this relationship.

supported 2,4%*

H5 (a) Promotion focus is positively related to job performance , its effect will be stronger when employees experience regulatory fit. (b) Prevention focus is positively related to job performance , its effect will be stronger when employees experience regulatory fit.

supported 10,2%*

H6 H6: Yes 10,2% H6 Promotion focus is positively related to helping

behaviors , and promotion fit strengthens this relationship.

supported 3,3%*

results from being high on both personal promotion and work promotion but being high on one of the two promotion foci is also beneficial for performance. Prevention fit has a positive effect on performance, supporting H5b, and this effect is stronger for higher prevention scores (a2 is positive). We find a very strong negative effect for prevention misfit on job performance. Thus, performance of individuals scoring high on personal prevention working in an environment that doesn’t support their prevention orientation suffers from this misfit. Similarly, individuals working in a highly prevention-focused work environment that doesn’t fit their own low prevention mindset won’t perform well. Next, we find support for the additive effect of promotion fit (a1 is significant) on helping behavior, and thus H6. For every model, the variance explained increases significantly by including both personal and work-specific regulatory foci. Several of the control variables have a significant effect as well. For example, organizational tenure increases all forms of commitment, which is in line with previous research (e.g. Meyer et al. 2002). We find that men are significantly less likely to have CC-FA. Interestingly, customer contact increases NC, but lowers CCFA. For NC, it is possible that the felt obligation to reciprocate extends from the company to the customers that one serves. For CCFA, being is contact with customers and having the skills to do this properly might make job alternatives more salient and within reach.

DISCUSSION

Tableau mis en forme

16

Drawing on literature from organizational behavior, social psychology, and marketing, this paper proposes and tests regulatory fit as an important predictor of employee commitment and behavior. Regulatory focus is approached taking a dual perspective, with regulatory fit reflecting the congruence between an employee’s chronic regulatory focus (RFP) and the regulatory strategies used in the service context (RFW). As such, it offers an alternative view for understanding service employees in their work context. Our results indicate that regulatory fit has significant relationships to different components of organizational commitment, job performance and helping behavior. Promotion fit is experienced when employees who focus on advancement and growth and try to be their ideal self in general, are able to employ strategies at work focused on doing a lot of work eagerly and fast. It contributes positively to affective commitment, job performance and helping colleagues. Prevention fit is experienced when employees who focus on security and responsibilities and try to be their ought self in general, are able to employ work strategies focused on performing tasks accurately and in accordance to duties. Prevention fit contributes to normative commitment, continuance commitment based on high sacrifices to be lost and job performance. Prevention fit has a positive, but diminishing effect on normative commitment, while it has a positive, and further increasing effect on in-role behavior. Overall, regulatory fit predicts all 5 out of the 6 investigated work variables. It is worth noting that misfit also had a significant impact for some variables. More precisely, we found that promotion misfit reduces affective commitment, whereas prevention misfit has a negative impact on in-role performance. In fact, the largest effect size in our model was the effect of prevention misfit on job performance. It also appears that promotion misfit was not a considerable problem for job performance: promotion focus as a personality trait or as a work orientation together and separately are found to positively impact job performance. One finding that did not support our hypothesis (H4) was that prevention fit did not influence employees’ CC-FewAlt, although the parameter estimates had the anticipated sign (negative, but insignificant). The final model shows that goal-striving orientations are not strongly correlated to perceptions of employment alternatives, but employee demographics are, with job tenure having the largest impact. These variables have a more direct relationship with CC-FewAlt. For example, employees working with their employer for a longer time, might be so used to its procedures that they do not see themselves fit in other environments, resulting in higher CC-FewAlt. It is important to note, however, that in case the controls were not included in the model, we did find a negative (and significant) impact of promotion fit on perceiving job alternatives elsewhere. In addition, both promotion fit and prevention fit increase job performance, though in a nonlinear way for prevention fit, whereas helping behaviors were found to benefit from promotion fit. We conclude that it is important for companies that service employees experience fit between their chronic regulatory focus and the regulatory strategies they employ at work. Five out of six hypotheses were fully supported and we found evidence of significant R2 improvements, meaning that the prediction power of the model significantly enhanced by introducing fit (between RFP and RFW) to our understanding of employee outcomes. Not all employees are equal, but every form of fit is found to beneficial for at least one type of commitment or employee behaviors. In sum, it is not just about having the right people (with the ‘right’ RFP), but rather about aligning the work context with these employees (through RFW) since

17

regulatory fit strongly impacts a company’s firm success through three types of commitment (AC, NC and CC-HiSac), job performance and employees’ helping behaviors. Theoretical Implications While prior service research has investigated how service context variables (e.g., service climate) impact employees, this study emphasizes the importance of considering the service employee as a person within this context. We argue that it is not only about the employee fitting in the service context, but also about the service employee himself experiencing fit in doing his/her work. Previous research has mainly investigated the link between RF and commitment, by using RFP metrics as focal RF variables. In contrast, this study reveals that both personality trait variables (like RFP) and contextual factors (like RFW) should be considered to better understand employee outcomes. Our results demonstrate that regulatory fit, reflecting the congruence between RFP and RFW, has a significant impact on the employee outcomes. The predictive power of our models increased significantly by accounting for regulatory fit by conducting surface response analysis (Shanock et al. 2010). For future RF studies performed in actual organizational settings, it is therefore recommended to measure both RFP and RFW and to additionally test for regulatory fit. In addition, our study reveals the importance of accounting for employee demographics to better understand the true link between RF and CC based on few alternatives (CC-FewAlt), and to unveil the importance of different types of employees (in casu: back office versus frontline employees) and their specific impact on employee attitudes. Finally, this study provides support for the two-dimensional nature of CC. Although the vast majority of previous research did not discriminate between these 2 forms of CC, we strongly recommend researchers to do so, since nomological validity (Netemeyer 2003) was found for the two-dimensional construct. Managerial Implications For managers that try to optimize employee attitudes and behaviors, it is important to realize that companies can benefit from employees experiencing regulatory fit. Employees who experience “this just feels like the right working context for me” are more likely to be committed, to perform better in their job tasks and will be more inclined to help colleagues in serving customers. Hence, it is strongly recommended to align the working conditions with an employee’s regulatory focus as personality trait. This study offers insight into selecting the right employees (e.g., RFP) and creating optimal working conditions (e.g., RFW), and as a result, stimulate regulatory fit. First, since RFP is a personality trait, it is important to pay attention to this stable goal orientation when hiring people. We reconcile with Bateson et al. (2014) who underline the importance of a good selection procedure when hiring service employees. In this regard, we argue that RF might be a viable criterion to take into consideration since employees’ goal-striving motivations are important drivers of a firm’s success. Overall, promotion focus seems to be the most beneficial goal orientation. However, prevention focus is also likely to drive beneficial forms of organizational commitment and also contributes to performance. Depending on the type or mix of commitment or performance behaviors that a manager wants to achieve for his employee base, he can consider the personal regulatory focus (RFP) of the job candidate. Next, a manager can strive for optimal working conditions by trying to instill fit with the personal regulatory orientation. If managers are aware of the chronic goal orientations of their personnel, they can stimulate positive employee

18

attitudes and behaviors by choosing matching work strategies. More precisely, managers could use the way they give feedback, their work rules and/or the organizational culture (Brockner and Higgins 2001) to influence promotion or prevention regulatory orientations at work or both. For instance, congruent feedback is recommended, such that negative feedback will motivate prevention-focused individuals, whereas positive feedback will motivate promotion-focused individuals (Van Dijk and Kluger 2004). In addition and as hypothesized, in order to optimize an employee’s job performance, both promotion fit and prevention fit are found to be effective in which avoiding a misfit in prevention is having the strongest impact. For promotion focus as a goal-striving motivation, only a low RFP in combination with a low RFW is harmful for achieving job performance. In this regard, it is also important to acknowledge the significant increase in variance explained when these fit effects are accounted for (i.e., an increase from 13.9% to 24.1%, see Table 3). Hence, for managers it is important to realize that both prevention and promotion-oriented persons (RFP) are likely to do their job well, as long as the optimal and well-fitting working contexts (RFW) are present. Our findings also demonstrate that demographics, like tenure, age, gender and type of employee (frontline versus back office worker) have a significant impact on all types of commitment and job performance. Interestingly, customer contact has a contradictory impact on commitment. While it increases NC, it lowers CCFA. We postulate that frontline employees (who have direct customer contact) are more likely to feel obliged to stay with their employer (i.e., normative commitment) because of the relationships built with “their” customers. In the meanwhile, meeting customers and people makes them more aware of what is happing outside the company, including attractive job alternatives. Finally, as manager, one should also be aware that there exist two forms of continuance commitment, and that these two dimensions have different drivers. While CC-HiSac can be influenced by managers through effective hiring and managing the work environment, managers cannot manipulate CC-FewAlt through RFW, nor can they avoid it by selecting employees based on their RFP. CC-FewAlt is the least beneficial commitment component and this study shows that only employee demographics drive this component of commitment. It is plausible to assume that alternatives are more likely to be influenced by factors outside and out of control of the company (such as job contents, conditions, and climate within other companies). Limitations and future research directions Although this research delivers a contribution to the service literature by showing the importance of regulatory fit, there are some limitations. First, this study was conducted in one country. We believe that investigating different countries and cultures in a cross-sectional design might be valuable given the potential influence of cultural differences (Hofstede 1980; Lee et al. 2000; Randall 1993). Second, another limitation is the use of cross-sectional data, meaning that all relations were examined at one point in time. This hampers the investigation of causality. Third, although we employed self-reported measures for commitment and job performance like prior studies (e.g., Markovits et al. 2008; Neubert et al. 2008; Wallace et al. 2009), it offers a viable opportunity to include supervisor-rated metrics in future regulatory fit studies. Finally, future research might examine other foci than the organization (e.g.,

19

supervisor commitment in addition to organizational commitment) in testing its relationship with RF and regulatory fit (Johnson et al. 2010).

REFERENCES Aaker, J. L., and Lee, A. Y. (2006), “Understanding regulatory fit”, Journal of Marketing Research, Vol.

43, No. 1, pp. 15-19. Allen, N. J. and Meyer, J. P. (1996), “Affective, continuance and normative commitment to the

organization: An examination of construct validity”, Journal of Vocational Behavior, Vol. 49, No.3, pp. 252-276.

Allen, N. J. and Meyer, J. P. (1990), “The measurement and antecedents of affective, continuance, and normative commitment to the organization”, Journal of Occupational Psychology, Vol. 63, No.1, pp. 1-18.

Bateson, J.E.G., Wirtz, J., Burke, E. and Vaughan C., (2014), “Psychometric sifting to efficiently select the right service employees”, Managing Service Quality, Vol. 24, No. 5, pp 418-433.

Becker, T. E. and Billings, R.S. (1993), “Profiles of Commitment: An Empirical Test”, Journal of Organizational Behavior, Vol. 14, No. 2, pp. 177-190.

Bentein K., Vandenberg R. J., Vandenberghe C. and Stinglhamber F. (2005), “The role of change in the relationship between commitment and turnover: A latent growth modeling approach”, Journal of Applied Psychology, Vol. 90, No.3, pp. 468–482.

Bolino, M. C. (1999). “Citizenship and impression management: Good soldiers or good actors?”, Academy of Management Review, Vol. 24, No.1, pp. 82-98.

Bowen, D.E., “The changing role of employees in service theory and practice: An interdisciplinary view”, Human resource management review (2015), http://dx.doi.org/10.1016/j.hrmr.2015.09.002

Bowen, D. E., and Schneider, B. (2014). “A service climate synthesis and future research agenda”, Journal of Service Research, Vol. 17, No.1, pp. 5-22.

Brendl, C.M., Higgins, E.T. and Lemm K.M. (1995), “Sensitivity to varying gains and losses: The role of self-discrepancies and event framing”, Journal of Personality and Social Psychology, Vol. 69, No.6, pp. 1028-1051.

Brendl, C. M., and Higgins, E. T. (1996), “Principles of judging valence: what makes events positive or negative?”, Advances in experimental social psychology, Vol. 28, pp. 95-160.

Brockner, J. and Higgins E. T., (2001), “Regulatory Focus Theory: Implications for the Study of Emotions at Work”,Organizational Behavior and Human Decision Processes,Vol. 86,No.1,p.35-66

Camacho, C. J., Higgins, E. T., and Luger, L. (2003). “Moral value transfer from regulatory fit: what feels right is right and what feels wrong is wrong”, Journal of personality and social psychology, Vol. 84, No. 3, pp. 498-510.

Coulter, K. S. and Coulter, R. A. (2002). “Determinants of trust in a service provider: the moderating role of length of relationship”, Journal of services marketing, Vol. 16 No.1, pp. 35-50.

Crowe, E. and Higgins, E. T. (1997), “Regulatory Focus and Strategic Inclinations: Promotion and Prevention in Decision-Making”, Organizational Behavior and Human Decision Processes, Vol.69, No.2, pp. 117-132.

De Keyser, A., Lemon K.N., Klaus P., and Keiningham T.L. (2015), “A Framework for Understanding and Managing the Customer Experience,” Marketing Science Institute, Working Paper Series Report No. 15-121, Boston, MA.

Dong, Y., Liao, H., Chuang, A., Zhou, J., and Campbell, E. M. (2015). “Fostering Employee Service Creativity: Joint Effects of Customer Empowering Behaviors and Supervisory Empowering Leadership”, Journal of Applied Psychology, Vol. 100, No. 5, pp. 1364-1380.

Edwards, J. R. (2007), “Polynomial Regression and Response Surface Methodology. In C. Ostroff & T. A. Judge (Eds.), Perspectives on organizational fit (pp. 361-372). San Francisco: Jossey-Bass.

Förster, J., Higgins, E.T. and Bianco, A. T. (2003), “Speed/accuracy decisions in task performance: Built-in trade-off or separate strategic concerns?”, Organizational Behavior and Human Decision Processes, Vol. 90, No.1, pp. 148-164.

Förster, J., Higgins, E.T. and Idson, L. (1998), “Approach and avoidance strength as a function of regulatory focus: Revisiting the ‘goal looms larger’ effect”, Journal of Personality and Social Psychology, Vol. 75, No. 5, pp. 1115-1131.

Friedman, R. S., and Förster, J. (2001). “The effects of promotion and prevention cues on creativity”, Journal of personality and social psychology, Vol. 81, No. 6, pp 1001-

Freitas, A. L., Liberman, N., and Higgins, E. T. (2002). “Regulatory fit and resisting temptation during goal pursuit”, Journal of Experimental Social Psychology, Vol. 38 No.3, pp. 291-298.

20

Gazzoli, G., Hancer, M., and Kim, B. (2013). “Explaining why employee-customer orientation influences customers' perceptions of the service encounter”, Journal of Service Management, Vol. 24, No.4, pp. 382-400.

Gorman, C. A., Meriac, J. P., Overstreet, B. L., Apodaca, S., McIntyre, A. L., Park, P., and Godbey, J. N. (2012). “A meta-analysis of the regulatory focus nomological network: Work-related antecedents and consequences”, Journal of Vocational Behavior, Vol. 80, No.1, pp. 160-172.

Hackett, R. D., Bycio, P. and Hausdorf, P. A. (1994), “Further Assessment of Meyer and Allen’s (1991) Three-Component Model of Organizational Commitment”, Journal of Applied Psychology, Vol. 79, No.1, pp.15-23.

Hamstra, M.R.W., Van Yperen, N.W., Wisse, B. and Sassenberg, K. (2011),”Transformational-Transactional Leadership Styles and Followers’ Regulatory Focus: Fit Reduces Followers Turnover Intentions”, Journal of Personnel Psychology, Vol. 10, No.4, pp. 182-186.

Hamstra, M. R., Sassenberg, K., Van Yperen, N. W., and Wisse, B. (2014). “Followers feel valued—When leaders' regulatory focus makes leaders exhibit behavior that fits followers' regulatory focus”, Journal of Experimental Social Psychology, Vol. 51, pp. 34-40.

Haws, K. L., Dholakia, U. M. and Bearden, W. O. (2010), “An Assessment of Chronic Regulatory Focus Measures”, Journal of Marketing Research, Vol. 47, pp. 967-982.

Heskett, J. L., and Schlesinger, L. A. (1994). “Putting the service-profit chain to work”, Harvard Business Review, Vol. 72, No. 2, pp. 164-174.

Higgins, E.T. (1987), “Self-discrepancy theory: A theory relating self and affect”, Psychological Review, Vol. 94, No. 3, pp. 319-340.

Higgins, E.T. (1997), “Beyond pleasure and pain”,American Psychologist, Vol.52,No.12,pp.1280-1300. Higgins, E.T. (2000), “Making a good decision: Value from fit”, American Psychologist, Vol. 55, No. 11,

pp. 1217-1230. Higgins, E.T., Friedman, R.S., Harlow, R.E., Idson, L.C., Ayduk, O.N. and Taylor, A. (2001),

“Achievement orientations from subjective histories of success: promotion pride versus prevention pride”, European Journal of Social Psychology, Vol. 31, No. 1, pp. 3-32.

Higgins, E.T., Roney, C., Crowe, E. and Hymes, C. (1994), “Ideal versus ought predilections for approach and avoidance: Distinct self-regulatory systems”, Journal of Personality and Social Psychology, Vol. 66, No. 2, pp. 276-286.

Higgins, E.T., Shah, J.Y. and Friedman, R. (1997), “Emotional responses to goal attainment: Strength of regulatory focus as moderator”, Journal of Personality and Social Psychology, Vol. 74, No. 2, pp. 515-525.

Hofstede, G. (1980), “Culture’s consequences: International differences in work-related values”, Sage, Newbury Park, CA.

Jaros, S. J. (1997), “An Assessment of Meyer and Allen’s (1991) Three-Component Model of Organizational Commitment and Turnover Intentions”, Journal Of Vocational Behavior, Vol. 51, No.3, pp. 319–337.

Johnson, R. E. and Chang C.-H. (2008) “Development and Validation of a Work-based Regulatory Focus Scale” Paper presented at the 23rd Annual Society for Industrial and Organizational Psychology Conference, San Francisco.

Johnson, R.E., Chang, C.H. and Yang, L.Q. (2010), “Commitment and Motivation at Work : the Relevance of Employee Identity and Regulatory Focus”, Academy of Management Review, Vol. 35, No.2, pp. 226-245.

Kark, R. and Van-Dijk, D. (2007), “Motivation to lead, motivation to follow: The role of the self-regulatory focus in leadership processes”, Academy of Management Review, Vol. 32, No.2, pp. 500–528.

Klein, H.J., Becker T.E. and Meyer, J.P. (2009), Commitment in Organizations, Accumulated Wisdom and New Directions, SIOP Organizational Frontiers Series, Routledge, New York, NY.

Lanaj, K., Chang, C.-H. D. and Johnson, R.E. (2012), “Regulatory Focus and Work-related Outcomes: A Review and Meta-Analysis”, Psychological Bulletin, Vol.138, No. 5, pp. 998-1034.

Lee, A. Y., and Aaker, J. L. (2004). “Bringing the frame into focus: the influence of regulatory fit on processing fluency and persuasion”, Journal of personality and social psychology, Vol. 86, No.2, pp 205-218.

Lee, Y.L., Aaker, J.L. and Gardner, W.L. (2000), “The Pleasures and Pains of Distinct Self-Construals: The Role of Interdependence in Regulatory Focus”, Journal of Personality and Social Psychology, Vol. 78, No. 6, pp. 1122-1134.

Liberman, N., Idson, L.C., Camacho, C.J. and Higgins, E.T. (1999), “Promotion and Prevention Choices Between Stability and Change”, Journal of Personality and Social Psychology, Vol. 77, No. 6, pp. 1135-1145.

21

Malhotra, N. and Mukherjee, A. (2004), “The relative influence of organizational commitment and job satisfaction on service quality of customer-contact employees in banking call centers”, Journal of Services Marketing, Vol. 18, No. 3, pp. 162-174.

Markovits, Y., Ullrich, J., van Dick, R., and Davis, A. J. (2008), “Regulatory foci and organizational commitment”, Journal of Vocational Behavior, Vol. 73, No.3, pp. 485–489.

Meyer, C. and Schwager A. (2007), "Understanding Customer Experience," Harvard Business Review, Vol. 85, No.2, pp. 117-126.

Meyer, J. P. and Allen, N. J. (1991), “A three-component conceptualization of organizational commitment”, Human Resource Management Review, Vol. 1, No. 1, pp. 61-89.

Meyer, J.P., Stanley, D. J., Herscovitch, L. and Topolnytsky, L. (2002), “Affective, Continuance, and Normative Commitment to the Organization: A Meta-analysis of Antecedents, Correlates, and Consequences”, Journal of Vocational Behavior, Vol. 61 No.1, pp. 20-52.

Meyer, J. P., Becker, T. E. and Vandenberghe, C. (2004),“Employee Commitment and Motivation: A conceptual Analysis and Integrative Model”, Journal of applied Psychology, Vol.89 No.6, pp.991-1007.

Moss, S., Ritossa, D. and Ngu, S. (2006), “The Effect of Follower Regulatory Focus and Extraversion on Leadership Behavior: The Role of Emotional Intelligence”, Journal of Individual Differences, Vol. 27, No. 2, pp. 93-107.

Motyka, S., Grewal, D., Puccinelli, N. M., Roggeveen, A. L., Avnet, T., Daryanto, A., and Wetzels, M. (2014). “Regulatory fit: A meta-analytic synthesis”, Journal of Consumer Psychology, Vol. 24, No. 3, pp. 394-410.

Netemeyer, Richard G., William O. Bearden and Subhash Sharma (2003), Scaling Procedures. Issues and Applications. Thousand Oaks: Sage Publications.

Neubert, M.J., Kacmar, K.M., Carlson, D.S., Chonko, L.B. and Roberts, J.A. (2008), “Regulatory Focus as a Mediator of the Influence of Initiating Structure and Servant Leadership on Employee Behavior”, Journal of Applied Psychology, Vol. 93, No. 6, pp. 1220-1233.

Neubert, M.J., Wu, C. and Roberts, J.A. (2013), “The Influence of Ethical Leadership and Regulatory Focus on Employee Outcomes”, Business Ethics Quarterly, Vol. 23, No. 2, pp. 269-296.

Ostrom, A. L., Bitner, M. J., Brown, S. W., Burkhard, K. A., Goul, M., Smith-Daniels, V., Demirkan H. and Rabinovich, E. (2010). Moving forward and making a difference: research priorities for the science of service. Journal of Service Research., pp. 1-33

Petrou, P., and Demerouti, E. (2015). “Trait-level and week-level regulatory focus as a motivation to craft a job”, Career Development International, Vol. 20, No. 2, pp. 102-118.

Petrou, P., Demerouti, E., and Häfner, M. (2015). “When fit matters more: The effect of regulatory fit on adaptation to change”, European Journal of Work and Organizational Psychology, Vol. 24, No.1, pp. 126-142.

Randall, D. M. (1993), “Cross-Cultural Research on Organizational Commitment: A Review and Application of Hofstede’s Value Survey Module”,Journal of Business Research,Vol. 26, p. 91-110.

Sassenberg, K., and Scholl, A. (2013). “If I can do it my way… The influence of regulatory focus on job-related values and job attraction”, Journal of Economic Psychology, Vol. 38, pp. 58-70.

Shah, J. E., Higgins E. T. and Friedman, R. S. (1998), “Performance Incentives and Means: How Regulatory Focus Influences Goal Attainment”, Journal of Personality and Social Psychology, Vol. 74, No.2, pp. 285-293.

Shanock, L. R., Baran, B. E., Gentry, W. A., Pattison, S. C., and Heggestad, E. D. (2010). “Polynomial regression with response surface analysis: A powerful approach for examining moderation and overcoming limitations of difference scores”, Journal of Business and Psychology, Vol. 25, No. 4, pp. 543-554.

Smith, J. S., Gleim, M. R., Robinson, S. G., and Kettinger, W. J. (2014). “Using an Old Dog for New Tricks A Regulatory Focus Perspective on Consumer Acceptance of RFID Applications”, Journal of Service Research, Vol. 17, No. 1, pp. 85-101.

Spiegel, S., Grant-Pillow, H., and Higgins, E. T. (2004). “How regulatory fit enhances motivational strength during goal pursuit”, European Journal of Social Psychology, Vol. 34 No.1, pp. 39-54.

Stam, D., van Knippenberg, D., and Wisse, B. (2010). “Focusing on followers: The role of regulatory focus and possible selves in visionary leadership”, The Leadership Quarterly, Vol. 21, No.3, pp. 457-468.

Taing, M.U., Granger, B.P., Groff, K.W., Jackson, E.M. and Johnson, R.E. (2011), “The multidimensional nature of continuance commitment: commitment owing to economic exchanges versus lack of employment alternatives”, Journal of Business and Psychology, Vol 26, No.3, pp. 269-284.

Tseng, H.-C. and Kang, L.-M. (2008), “How does regulatory focus affect uncertainty towards

22

organizational change?”, Leadership and Organizational Development Journal, Vol.29, No.8, pp. 713-731.

van Beek, I., W. Taris, T., B. Schaufeli, W., and Brenninkmeijer, V. (2013). “Heavy work investment: its motivational make-up and outcomes”, Journal of Managerial Psychology,Vol. 29, No.1, pp. 46-62.

Van-Dijk, D., and Kluger, A. N. (2004), “Feedback sign effect on motivation: Is it moderated by regulatory focus?”, Applied Psychology: An International Review, Vol. 53, pp. 113–135.

Vandenberghe, C., Bentein, K., Michon, R., Chebat, J., Tremblay, M. and Fils, J. (2007), “An examination of the role of perceived support and employee commitment in employee-customer encounters”, Journal of Applied Psychology, Vol. 92, No.4, pp. 1177–1187.

Wallace, J.C., Chen, G. and Kanfer, R. (2005, April), “Development and validation of a work-specific measure of regulatory focus”, Paper presented at the 20th Annual Conference of the Society for Industrial/Organizational Psychology, Los Angeles, CA.

Wallace, C. and Chen, G. (2006), “A Multilevel Integration Of Personality, Climate, Self-Regulation, And Performance”, Personnel Psychology, Vol. 59, No.3, pp. 529-557.

Wallace, J. C., Johnson, P. D. and Frazier, M. L. (2009), “An examination of the factorial, construct, and predictive validity and utility of the regulatory focus at work scale”, Journal of Organizational Behavior, Vol. 30, No. 6, pp. 805-831.

Wallace, J.C., Little, L.M. and Shull, A. (2008), “The Moderating Effects of Task Complexity on the Relationship Between regulatory Foci and Safety and Production Performance”, Journal of Occupational Health Psychology, Vol. 13, No. 2, pp. 95-104.

Wallace, J. C., Butts, M. M., Johnson, P. D., Stevens, F. G., and Smith, M. B. (2013). “A Multilevel Model of Employee Innovation Understanding the Effects of Regulatory Focus, Thriving, and Employee Involvement Climate”, Journal of Management, pp. 1-23

Wirtz, J., and Lwin, M. O. (2009). “Regulatory focus theory, trust, and privacy concern”, Journal of Service Research, Vol. 12, No. 2, pp. 190-207

Wang, Y., Kandampully, J., & Jia, H. (2013). “Tailoring” customization services: Effects of customization mode and consumer regulatory focus”. Journal of Service Management, Vol. 24, No. 1, pp. 82-104.

Williams, L. J., and Anderson, S. E. (1991). “Job satisfaction and organizational commitment as predictors of organizational citizenship and in-role behaviors”, Journal of management, Vol. 17, No. 3, pp. 601-617.

Yuan, Y. and MacKinnon, D.P. (2009), “Bayesian Mediation Analysis”, Psychological Methods, Vol. 14, No.4, pp. 301-322.

Zhao, X., Lynch, J.G. and Chen, Q. (2010), “Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis”, Journal of Consumer Research, Vol. 37, No. 2, pp. 197-206.