Employee’s Market Orientation Behavior and Firm’s Internal Marketing Mechanism: A Multilevel Perspective of Job Performance Theory

Abstract

The competition in today’s market is increasingly intensive. Employees’ market orientation behavior (MOB) is crucial for a firm to respond to market changes and attain its business performance goal. Moreover, a firm must exercise the internal marketing mechanism (IMM) to prepare employees for providing superior service to satisfy internal and external customers’ needs. This study aims to examine how the IMM works with knowledge integration (KI), relationship quality (RQ), relational bond (RB), and organizational citizenship behavior (OCB) to influence MOB. A total of 471 valid responses from employees of 47 banks were collected. The Hierarchical Linear Model is used to analyze the IMM’s effects (as the organizational-level variable) on MOB (as the outcome variables) and the relationships between the other variables (as the individual-level variables) and MOB. The results show that all predictor variables have significant and direct effects on MOB. The IMM’s moderating effects are significant when it interacts with OCB and RB, but not RQ. The negative interaction effect of IMM and OCB offers a caveat to corporate management in balancing OCB activities among the employees.

1. Introduction

In the past few decades, marketers have employed market orientation as a significant source of competitive advantage [1]. Market orientation enables a firm to understand its customers, competitors, and environments better, thus increase its profitability [2] and sustainable competitive advantages [3], leading to long-term success [4]. Instead of customer acquisition, market orientation focuses on customer retention and has a more pronounced effect on a firm’s profit than sales. Market orientation is crucial for a firm in an intensively competitive environment to maintain its responsiveness to market changes and attain its business performance goal, especially in service-related industries [5,6]. Two seminal works in 1990 established market orientation as the cornerstone of marketing management. First, Kohli and Jaworski [7] define market orientation as the organization-wide information generation and dissemination and appropriate response to current and future customer needs and preferences. The formal is an internal component, while the latter is external. In the meantime, Second, Narver and Slater [2] describe market orientation with three behavioral components (i.e., customer orientation, competitor orientation, and inter-functional coordination) and two decision criteria (namely, long-term focus and profitability). A scrutiny of the three behavioral components reveals that the first two components are external and the last one is internal. As such, the success of market orientation relies on both external and internal behavioral strategies.

A successful organization depends primarily on employees’ effort, attitude, behavior, and interaction. All these factors are employee-related and play a critical role in accomplishing the organization’s strategy [8]. Scholars have confirmed that employees’ attitudes and behaviors positively influence a firm’s accounting measures and stock returns [9]. Therefore, it is crucial for a firm to entice employees to engage in market orientation behavior (MOB) to attain sustainable competitive advantages and excel at business performance.

In the marketing field, product, price, place, and promotion (known as the 4P’s) are the recognized external marketing mechanisms; However, very few have a concrete idea about the internal marketing mechanism (IMM) [10]. In the early 1970s, Kotler [11] introduced internal marketing and suggested that a firm should market to its employees before marketing to its customers. Soon after the emergence of this concept, firms began to view jobs as products [12] and employees as internal customers [13]. To be successful, a business must retain talented and competent employees; internal marketing can help businesses resolve this issue. Internal marketing is regarded as a model component of service marketing management [14] and a measurable scale for empirical research [15]. Researchers have examined the relationship between internal marketing and customer satisfaction [16]. Several studies have identified the direct and indirect effects of internal market orientation on internal team performance [17] and firm performance [18] of new service development, and organizational performance [10]. Others have studied internal marketing influences on employees’ customer promise and customer-oriented behavior [19]. Most empirical studies showed that it engenders employee’s customer-oriented behavior, leading to MOB [20]. However, no research has empirically verified the direct effect of internal marketing on MOB.

To promote employees’ MOB, both firm management and employees must work together. The former is responsible for rolling out the internal marketing program to prepare employees for engaging in MOB, while the latter must regard MOB as job performance. Based on job performance theory [21], three characteristics of individual employees must co-exist to some extent to complete a job successfully, including capacity, willingness, and opportunity. That is, given a chance to take on a job, an employee must be able and willing to do it right and well to excel at the performance. Based on the theory, this study aims to identify the antecedents of MOB and examine how the IMM works with these antecedents to influence MOB. Specific research questions are as follows

• RQ1: What the antecedents of MOB and how do they, directly and indirectly, affect MOB?
• RQ2: Does IMM affect MOB?
• RQ3: How does IMM interact with the antecedents to affect MOB?

To answer these questions, we conduct a multi-group survey and collect a total of 471 valid responses from employees of 47 banks. In the remaining sections, we first describe the theoretical background and review the literature related to the variables. Then, we postulate and justify hypotheses and develop a multilevel research model based on the theoretical framework. Next, empirical data from the usable subjects are analyzed to validate the research model. Finally, we test the hypotheses and discuss the study’s results and findings along with their theoretical and practical implications.

2. Theoretical Background

2.1. Job Performance Theory

In the early 1980s, Blumberg and Pringle [21] introduced an interactive model of job performance (JP). They theorized that the performance of a particular task is a function of capacity (C), willingness (W) and opportunity (O) and that they influence each other reciprocally. The underpinning theory can be expressed as JP = f(C × W × O). Capacity refers to ability, knowledge, skills, intelligence, education level, age, health, endurance, stamina, energy level, and motor skills. Willingness comprises motivation, job satisfaction, job status, anxiety, participation legitimacy, attitude, perceived task characteristics, job involvement, ego, self-image, personality, norms, values, perceived role expectations, and equity feelings. Opportunity includes tools, equipment, materials, supplies, working conditions, co-workers’ actions, leader behavior, mentorship, organizational policies, rules, procedures, information, time, and pay. Other researchers also argued that self-efficacy and adequate instruments, materials, and leaders’ guidance are significant determinants of job performance [22,23]. Based on the high-low strengths of the three elements (capacity, willingness, opportunity), Blumberg and Pringle [21] identified eight categories of potential performance outcomes. Employees with low capacity, low willingness, and less favorable opportunity have very poor performance. In contrast, those with high capacity, high willingness, and more favorable opportunity have very good performance. The other six categories in sequence are (1) poor performance, (2–3) poor to good performance, (4–5) good performance, and (6) better performance. Considering the degree of MOB as an employee’s job performance outcome, we applied these eight categories to MOB in this study.

2.2. The Antecedents of MOB

Nowadays, knowledgeable workers have dramatically increased, and many businesses had to create, manage, and keep up with new information in order to compete and attain vital competitive advantages [24,25]. Recently, research into knowledge management has become very popular. Knowledge is a critical factor in creating business advantages, yet related literature has shown that sharing knowledge among employees remains the most challenging issue for knowledge management in an organization [26]. There are many factors in an organization that hinder knowledge exchange activities. These include inappropriate organizational structure, knowledge-hoarding culture, and political factions [27]. Currently, very few studies have probed into the interaction between internal marketing mechanism and knowledge exchange [20,28]. Perhaps, the exchange itself is unable to maximize the utility of knowledge. Therefore, some scholars suggested that one must exchange and integrate knowledge to improve one’s knowledge and that one’s integration of knowledge relies heavily on one’s capability [29,30]. This study strives to close this gap and better understand the interplay of IMM and knowledge integration (KI) and their impacts on employees’ MOB.

From a relationship marketing perspective, Chaston [31] regards internal marketing as internal customer management. Even though internal and external customers are not identical in some aspects and conditions [32], businesses strive to build a good relationship with external and internal customers. Relationship marketing effectiveness relies heavily on trust and commitment [33]. Externally, the primary purpose is to build a strong bond with customers and maintain an excellent long-lasting relationship. It is also necessary to build a quality relationship and bond with internal employees by promoting IMM. Having internal relationship quality (RQ) and relational bond (RB), an employee may improve his/her MOB. This relation remains to be examined in this study.

Based on annual performance evaluation results, one should reward those employees who provide excellent service to customers. By doing so, employees would be more inclined to show motivation and offer more quality services to customers on all occasions [7]. To achieve high performance, an employee needs both the capacity and the willingness to complete required duties. The formal evaluation of individual performance mandates employees to comply with the job profiles but may not necessarily entice them to meet organizational goals consistently. Complying with job profiles refers to in-role activities while meeting organizational goals requires extra-role effort, known as organizational citizenship behavior (OCB) [34]. Those with high OCB provide, beyond their expectations, excellent service to customers. They demonstrate a high willingness to go the extra mile for the organizations. Hence, giving employees recognition and rewards based on a positive regular job performance evaluation is a great start. In return, they have a higher desire to perform well with their OCBs and more inclined to meet the organization’s market orientation goals [35]. Thus, we regard employee’s MOB as a surrogate of job performance in this study and examine the influence of OCB on MOB.

2.3. A Multilevel Model of Job Performance Theory

From the above discourse, we develop a multilevel research model in Figure 1 and postulate the individual employee’s KI as the capacity, OCB as the willingness, RQ and RB as the opportunity, while IMM is a firm-level opportunity. Prior research has confirmed that MOB engenders business performance [36,37] and environmental sustainability [38]. Therefore, we substitute job performance with MOB in this model.

3. Literature Review

3.1. Market Orientation Behavior

Market orientation is a firm’s direction toward creating excellent value for external customers; it plays an essential role in organizational management and strategy [2]. At the individual level, it refers to an organizational member’s practice of integrating customer needs, competitor intelligence, and product knowledge into the process of creating and delivering excellent value to customers [39]. It is the outside-in marketing to identify and satisfy customer needs more effectively than competitors [40]. Specifically, Narver and Slater [2] claim that market orientation encompasses three behaviors (customer orientation, competitor orientation, and inter-functional coordination) and two decision criteria (long-term focus and profitability). It can be conceptualized to involve all employees, customers, competitors, and internal processes [41]. Homburg and Pflesser [42] advocate that market orientation is a critical marketing construct with behavioral and cultural perspectives. The former behavioral perspective contains three relevant dimensions: (1) market intelligence generation about current and future customer needs, (2) market intelligence dissemination across departments, and (3) market intelligence responsiveness [7,40]. The latter is related to the organization’s culture “that most effectively and efficiently create the necessary behaviors for the creation of superior value for buyers and, thus, continuous superior performance for the business” [2] (p. 21). A company can be market-oriented only if it fully understands its markets and consumers [43]. It is a failure-prevention approach in service firms and a success-inducing approach in manufacturing firms [44]; it is more important than an entrepreneurial orientation [45].

Prior studies in the literature exhibit empirical evidence of a significant and positive relationship between market orientation and business performance [2,7,36,44,45]. Kohli and Jaworski [7] interview 62 managers of 42 organizations in four US cities and identify senior management factors, interdepartmental dynamics, and organizational systems as the three antecedents of market orientation, while customer responses, employee responses, and business performance as the consequences. To deliver consistently above-normal market performance, a firm must generate a sustainable value for its customers [2,39]. Specifically, market orientation has strong positive relationships with business performance such as profitability [37,45], customer retention [46], sales growth [39], job satisfaction [41] and employee commitment [47]. Moreover, established market orientation influences green supply chain practices and environmental performance [38]. It also influences salespeople’s selling behaviors and performance [39] that help to create firm performance and generate business success [37,41,46]. Looking beyond market share, profitability as a business goal is increasingly common in firms; a firm’s top management needs to understand how to meet customers’ wishes and needs and support the deployment of market orientation and proper behaviors to engender superior firm performance. This study focuses on the behavioral aspect of market orientation. It measures an individual employee’s MOB using the three behavioral components defined by [2]: customer orientation behaviors, competitor orientation behaviors, and inter-functional coordination.

3.2. Internal Marketing Machenism

A common view in marketing is that a firm must have satisfied employees before satisfying customers [48]. Internal marketing is a managerial philosophy with activities that tie the firm with employees [49]. It is a direct marketing strategy [50] that views employees as internal customers and job outcomes as internal products. In return, this strategy helps to offer internal products to satisfy their needs and wants while addressing the organization’s objectives [12,14]. IMM is commonly deployed through five practices: education and training, motivation and reward, career development, communications, and organization/management support. It engages employees in knowledge renewal of market and products/services while serving as a unique resource for competitive advantages [28]. It offers an organizational culture and a tool to achieve strategic alignment between front-line employees and the marketing unit. Such an alignment enhances IMM practices and increases employee satisfaction and organization performance [51].

Prior studies have considered internal marketing a superior service for satisfying internal and external customers’ needs [16,47]. It can help obtain better financial results and develop sustainable competitive advantages towards a successful firm [10,18]. Several studies have proven that internal marketing can improve employee job satisfaction [14,50,51], job retention [14], commitment to their firms [14,51], employee job attitudes [14], job behavior [14], work motivation [11,14,31,32,48,51] and organizational capabilities [12]. In summary, we define internal marketing as the philosophy of viewing employees as customers. This philosophy encompasses treating job outcomes as products that satisfy the internal customers and coordinating internal business functions through the five IMM practices.

3.3. Knowledge Integration

Knowledge is a fluid mix of framed experience, values, contextual information, and expert insights that provides a framework for evaluating and incorporating new experiences and information and fostering a firm’s sustainable competitive advantage [27]. Learning new things within and outside an organization helps generate new and better knowledge and experience, vertically and horizontally across organizational boundaries, and enhance inner and outer growth [52]. Scholars have identified that the greater the sales team’s customer knowledge creation, the higher the customer relationship performance in customer loyalty, customer retention, and customer satisfaction [53]. Some suggested that a firm could be recognized as a social community specializing in the speed and efficiency of generating and transferring knowledge [54]. It enables people to capitalize on the organizations’ existing knowledge bases, enhancing their capacities to develop creative solutions and introduce new products and services to the market [55]. Empirical evidence has shown that knowledge sharing among individuals and groups within an organization can make a firm do better in the markets [56]. Next to knowledge sharing is KI (exchange and combination) among employees. The success of KI depends on the organization’s social climate, trust, cooperation, and shared code and language [57], and the employee’s motivation and ability [29]. It increases a firm’s capability and establishes and sustains its competitive advantage [25]. In sum, knowledge and its associated processes are the critical foundations of organizational advantage [30]. Recent advances in ICT have significantly increased KI in a firm; technological trends and factors are driving a firm’s strategic change towards success [24].

Several studies have mentioned the knowledge within a firm, between customers, and from individuals. They noted how knowledge sharing [30,58], creation [30,53,54,56], transferring [52,54], exchanging [57] and combining [56,57] between employees and amongst organizations increase employee problem-solving capability and creative performance [58], team effectiveness [53], firm performance [53,56,57], innovation capability [56], as well as the competitive advantage [30]. By considering knowledge exchange and combination as one of the main focuses in the organizational annual operational plan, and through effective KI management, a firm can better improve its ability to perform and compete against the competitors and deliver excellent services to the customers.

The possibility of KI among employees depends on employee motivation and ability [29,30]. In this study, we define KI as a simple construct referring to workers’ knowledge exchange and combination that produce individual or organizational value (motivation) and the extent to which they believe that employees can exchange and combine information (ability).

3.4. Relationship Quality

RQ is a concept being used in relationship marketing to represent the strength or closeness of a relationship and its ability to persist. It is a critical feature of the group interaction process that reduces structural complexity [59]. It can be viewed as the degree of connectedness in a relationship to fulfill the customer requirements associated with that relationship [60]. Scholars often conceptualize RQ as a multifaceted global evaluation of the overall strength and solidarity of the relationship between exchange partners, the key contact person, and the firm [61]. It contains multiple dimensions, including trust in individuals and organizations [62], satisfaction [63], ethics [64], willingness to invest in the relationship with the expectation of continuity [65] and calculative and emotional commitments [66].

RQ plays a critical role in maintaining customer relationships and providing superior quality services in the service delivery industries. In support of this, previous researchers have identified that better RQ results in a lower level of conflict [65] as well as the greater trust of the salesperson [61,63,64,66], customer satisfaction [61,63,64,66], commitment [61,66], continuity [65], consistency [61], willingness to invest [61], employee performance [63], and organizational performance [59,61]. Therefore, many factors influence RQ (e.g., trust, commitment, and satisfaction) in different areas, such as similarity, expertise, relational selling behavior, ethical salesperson behavior, frequency of interaction, environmental uncertainty, attitudes, information sharing. When building a strong RQ between customer-salesperson, buyer-seller, and employee-leader, we should consider them to endure a long-term and healthy relationship. In summary, RQ is defined as how positively an employee perceives the relationship between the company and its employees. These include the degree of trust in their direct supervisor, their commitment toward the company, and the employee’s job satisfaction towards the company.

3.5. Relational Bond

Firms often initiate bonds to build relationships with their customers [67] and retain them [51]. Such bonds are created through economic or emotional marketing activities and may improve customers’ utilitarian or hedonic value perceptions [68]. RB can be of three types: social bond [51,69,70,71,72], structural bond [51,69,70,71,72] and financial bond [51,68,71,72]. Social bond refers to how organizational members bond together through individual and social relationships with their peers [70]. It is a personal bonding [73] with a reciprocal individual friendship that produces a positive interpersonal relationship and preference shared between partners (sellers and buyers) through the social exchange process [69,72]. It helps transform customers into patrons developed from personalized service delivery according to their individual preferences [51]. Next, the structural bond is a relationship associated with the structure, control, and institutionalization of a customer and a firm [71,73]. It indicates the extent to which certain connections keep a buyer and a seller together in a relationship due to mutual beneficiaries, technologies, organizational strategies, or objectives [70]. Such bonds are company efforts to stimulate employee’s work satisfaction using value-added programs [72] and enhance customer performance through value-added services provided by organizational systems [51]. Finally, a financial bond is the level of economic beneficiaries obtained from relationship exchange [71] in the forms of short-term purchase incentives (discounts) that entice customer patronage [51] or financial incentives (wages or salaries) that motivate employee financial satisfaction [72].

Long-term business with customers depends on the strength and quality of the relationship between firms and customers. Many pertinent variables influence the success or failure of a relationship. The variables comprise (personal, customer’s, or organizational) commitment [51,70,71,72], trust [51,70,71], value [51,68,70], cooperation [69,70,71], mutual goals [69], quality [71], Interdependence/power imbalance [69], customer loyalty [51,68,71], performance satisfaction [51,70,71], retention [51,72] and investments [71]. To sustain a firm’s success and business advantages, we need to develop and maintain this relationship by understanding customers’ needs and meeting their expectations. Firms need to keep focused, recognize the importance of the relationships between customers, employees, and organizations, provide a work environment of trust and support, and add value to the businesses and services to build a sustainable and long-lasting customer relationship. In summary, an RB is a measure of how close an employee is to his/her company. It is also a measure between an employee and his/her direct supervisor or colleagues associated with social, structural, and financial bonds.

3.6. Organizational Citizenship Behavior

OCB is discretionary and not directly or explicitly recognized by the formal reward system [34]. It includes helping behavior, civic virtue, and sportsmanship [74] that support the social and psychological environment in which task performance occurs [75]. The OCB is considered a flexible work behavior that improves an organization’s effective functioning [76]. It is a measure of individual extra-role behavior that maintains and enhances work context to support task performances, leading to contextual performance [77]. As time goes by, it may not stay as an optional extra-role if it is to be expected by supervisors and co-workers [35].

Since the OCB concept was introduced over 38 years ago (cf. [78]), relevant papers have grown dramatically, and many researchers have classified its dimensions and constructs into organizational and individual levels. They further identified its direct and indirect influences on organizational performance [79,80], service quality [81], customer satisfaction [80], and job satisfaction [82]. Researchers have examined and identified more than 30 dimensions of OCB [76,83], including helping behavior, sportsmanship, altruism, organizational loyalty, organizational compliance, individual initiative, civic virtue, self-development, courtesy, voice behavior, personal initiative-taking and conscientiousness, among others. This study follows [74] to define OCB as a single latent construct with three dimensions: altruism, civic virtue, and sportsmanship.

4. Hypotheses Development and Research Model

4.1. Direct Effect of Antecedents on MOB

Kohli and Jaworski [7] state that market orientation starts with information dissemination and exchange. Narver and Slater [2], on the other hand, argue that it is based on customer orientation, competitor orientation, and inter-functional coordination. In particular, inter-functional coordination integrates company resources to create superior value for target customers. In other words, KI can be considered as a part of inter-functional coordination. No matter what, businesses must keep a long-term promise to their customers and understand their expectations and how they change their purchase behaviors. To improve market orientation, market knowledge should be dispersed among employees across departments [7]. This action ensures that all employees can use the proper information to create responsiveness to face customers’ needs and their current competitive environment. We need to contact customers continuously after a sale is made to generate market intelligence, spread the necessary intelligence across departments, and gain high responsiveness for the whole organization [7]. In sum, KI in a firm indicates the active willingness of internal employees to exchange and combine knowledge with other employees across departments or businesses; it enables the firm to enhance inter-functional coordination and positively influence employee’s market orientation. Thus, we hypothesize:

Hypothesis 1 (H1).

Employee knowledge integration positively influences employee MOB.

RQ is an essential indicator of relationship marketing effectiveness. It indicates the commitment and trust between a focal firm and its partners and customers [33]. When a firm implements a relationship marketing mechanism internally, the RQ between the firm and its employees can be improved, leading to employees’ trust and commitment toward the firm and their direct supervisors [19,33,35]. Rafiq and Ahmed [84] also suggest that employees’ job satisfaction could engender external customers’ satisfaction. They note that a firm’s capability of satisfying external customers’ needs relies partly on how well it satisfies its employees. In sum, employee RQ could enhance employees’ job satisfaction and strengthen a firm’s capability to satisfy external customers. As external customers’ satisfaction and internal employees’ RQ are instrumental to customer orientation and inter-functional coordination (i.e., MOB’s objectives), hence we hypothesize:

Hypothesis 2 (H2).

Employee relationship quality positively influences employee MOB.

According to the social exchange theory [85], a structural bond that holds a buyer and a seller together in a relationship results from some mutually beneficial strategic, technological, and organizational objective [70]. Through emotional influences, social bonds can make internal customers (employees) voluntarily purchase their products (work) [67]. Financial bonds can offer additional economic and financial benefits to foster the satisfaction of internal customers, leading to a tighter bond with the firm and their willingness to implement its marketing plan. Employees usually participate in a series of activities to produce RBs; these activities gradually shape their behaviors. When a firm conveys market orientation messages to its employees in these activities, it can heighten the RBs and engender the employees’ willingness to display MOBs. Thus, we hypothesize:

Hypothesis 3 (H3).

Employee relational bond positively influences employee MOB.

Market orientation is considered the primary source of competitive advantage for a firm. It emphasizes the analysis of both the current and the potential competitors’ short-term strengths and weaknesses and long-term capabilities and strategies [86]. Internally, it ensures coordination across all functional areas to fully utilize company resources in creating superior value for target customers, which serves as the performance indicator of each employee. If we reward employees through their customer-service performance outcomes, employees may form an expectation of getting rewards and strive to deliver better quality services and enhance customer satisfaction [87]. In a firm, employees with high OCBs tend to proactively help each other (i.e., altruism), actively participate in political activities (civic virtue), and tolerate less-than-ideal conditions in the firm (sportsmanship). These behaviors improve the antecedents of market orientation and create superior value for target customers. In sum, the OCBs of employees can foster their MOBs. Thus, we formulate the following hypothesis:

Hypothesis 4 (H4).

Employee OCB positively influences employee MOB.

Internal marketing aims to ensure internal customer (employee) satisfaction, support the overall marketing strategy, and eventually satisfy the external customers and attain business goals [67]. Among the five IMM practices, motivation and reward, communications, and management support are relevant to several antecedents of market orientation, including communication-action gap, upward mobility, education, attitude toward change, ability to win top management’s trust, interdepartmental connectedness, and market-based reward systems. Hence, we hypothesize:

Hypothesis 5 (H5).

IMM of a firm positively influences employee MOB.

4.2. Cross-Level Moderation Effects of Internal Marketing Mechanisms

According to situational strength theory [88], the extent to which an employee displays MOB depends on the organizational context. IMM practices can create a strong situation at the organizational level to stimulate and entice employees to embrace a firm’s market orientation philosophy. Under such a situation, the outcome of internal marketing may moderate the effect of individual perceptions on MOB. Specifically, all IMMs, especially motivation and reward, communications [89] and management support [90] are the critical drivers for KI. Employees in a firm with these mechanisms should be more willing to support inter-functional coordination, competitor analysis, and customer-value creation, which are the essential objectives of MOBs. Therefore, we hypothesize:

Hypothesis 6a (H6a).

IMM of a firm positively moderates the relationship of employee knowledge integration and MOB.

Employee RQ enhances employees’ job satisfaction and strengthens a firm’s capability to satisfy external customers. These qualities are instrumental to MOB (especially customer orientation and inter-functional coordination). As some IMMs can improve the RQ through trust and commitment [91] and management support [92], they could moderate the relationship between RQ and MOB. Hence, we hypothesize:

Hypothesis 6b (H6b).

IMM of a firm positively moderates the effect of employee relationship quality on MOB.

RB is expected to shape an employee’s MOB through the structural bond, financial bond, and social bond, as explained previously in hypothesizing H3. As some IMMs can positively affect RB, such as organizational communications and management support [93], it is logical to postulate that these mechanisms can moderate the relationship between RB and MOB. We hereby hypothesize:

Hypothesis 6c (H6c).

IMM of a firm positively moderates the relationship of employee relational bond and MOB.

Studies have confirmed that IMM practices significantly affect employees’ OCBs. Specifically, communication [94], reward system [19,95], and organizational support [87] positively impact employees’ OCBs. These mechanisms further impact MOB [19], serving as a moderator and making the relationship between OCB and MOB stronger or weaker. Hence, we hypothesize:

Hypothesis 6d (H6d).

IMM of a firm positively moderates the relationship of employee OCB and MOB.

4.3. Moderated Multilevel Research Model

Based on the above discourse, we develop a research model that includes 6 constructs: IMM at the organizational level and OCB, KI, RQ, RB, and MOB at the individual level. The purpose is to explore whether OCB, KI, RQ, and RB could directly influence MOB at the individual level. In addition, we explore whether IMM may moderate these direct relationships at the organizational level. Employees’ RB and RQ are essential to customer relationship management that support the marketing orientation element of customer orientation. Employees’ KI and OCBs are instrumental to inter-functional coordination and positively influence MOB. Finally, IMM at the organizational level is hypothesized to influence MOB directly and moderate the effects of its antecedents. Based on the above discourse, we develop a moderated multilevel research model for this study in Figure 2.

5. Research Method

5.1. Measures

This research operationally defined each construct and developed a measurement questionnaire for each construct based on the extant literature. All sources, construct dimensions, and measurement items are shown in the Appendix A. In the first stage, content validity was ensured. A pretest was conducted after completing the questionnaire design to ensure the correctness and appropriateness of the items’ wording and contents. The pretest process included five professors, three doctoral students, and two banking business experts. We deleted vague, ambiguous, unmeasured, and duplicate items and checked each item’s wording and meaning in each construct. All items were measured on a 7-point Likert-type scale, ranging from 1 (strongly disagree) to 7 (strongly agree) or range from 1 (not at all) to 7 (great extent).

5.2. Data Collection

MOB is vital for a firm in an intensively competitive environment such as the service business. Moreover, scholars have suggested that internal marketing is crucial to the financial services businesses (e.g., banks, insurance firms, and financial securities companies); their employees must have sufficient knowledge and skills to provide investment services to the customers [16]. Therefore, this study uses the financial services business as the data source. We conducted a paper-based survey of commercial banks in Taiwan that provide investment services such as structured products, structured notes, super yield investments, mutual funds, and offshore bonds. The bank list was obtained from the September 2020 report of the Financial Supervisory Commission of Taiwan’s Executive Yuan [96]. A total of 60 branch offices of local banks and those foreign banks with branch offices in Taiwan were randomly selected. In order to conduct a multilevel analysis, we need 10 or more responses from each bank with at least 30 banks [97].

Fifteen questionnaires were sent to each bank’s manager, who was requested to distribute the questionnaires to employees who sell and support the aforementioned services. A total of 900 questionnaires (60 × 15) were distributed. The employees were given 4 weeks to complete and return the survey questionnaires. All participations were voluntary and anonymous. To increase the response rate, we offered each respondent a gift certificate worth ten US dollars for his or her time and effort. After 2 weeks, we contacted the bank managers to remind their employees to complete the survey. Four more weeks later, 488 completed questionnaires were received from 48 banks, giving a response rate of 54.2% (=488/900). A scrutiny of these questionnaires reveals that one bank has only 8 completed questionnaires while the other bank has 9 questionnaires that failed the reversed-coded item check. These 17 responses were excluded from the data analysis. The final sample for analysis contains 471 valid responses from 47 banks. After confirming the within-group agreement, we grouped the bank’s responses and aggregated the individuals’ composite scores for internal marketing construct within each bank into a common score, following the procedure in [98,99]. This score represents a bank’s overall internal marketing context shared by the bank’s employees.

Furthermore, to avoid the common method variance (CMV) problem, we adopted procedural, same-source-bias, and statistical remedies recommended by [100]. For the procedural remedy, we conducted a pretest to ensure content and face validities and inserted reversed-coded items in the questionnaire to reduce the potential effects of response pattern biases. For the same-source-bias remedy, we distributed groups of questionnaires to different banks and tested the banks’ differences. For the statistical remedy, we conducted Harman’s single-factor test [101]. All these remedies confirm the absence of common method biases.

5.3. Hierarchical Linear Model (HLM)

HLM is used to analyze the data that have been collected in this study. It is a multilevel statistical analysis method used to understand the relationship between multilevel independent variables and individual level dependable variables. Compared to traditional linear regression analysis methods, HLM is different in that it provides multilevel variance estimations. Before implementing the HLM analysis, we need to verify the respondents’ reliability, assess the intraclass agreement coefficients (r_wg) and the intraclass correlation coefficients, ICC₁ and ICC₂. While ICC₁ compares the between-organizations variance to the within-organization variance to indicate the portion of the variance in individual responses accounted for by the between-organizations difference, ICC₂ reveals the reliability of the mean of an organization-level variable [99]. The extent of the consensus to which employees perceive a concept (construct) in a firm is represented by r_wg. Therefore, before aggregating data from the individual level up to the organizational level for multilevel analyses, we must first examine a single firm’s homogeneity and the extent of consensus across its respondents toward the construct before aggregation. The formula r_wg is as follows:

$$r_{wg\left(J\right)}=\frac{J\left[1-\left(\overline{S_{xj}^2} ÷ {\sigma }_{EU}^2\right)\right]}{J\left[1-\left(\overline{S_{xj}^2} ÷ {\sigma }_{EU}^2\right)\right]+\left(\overline{S_{xj}^2} ÷ {\sigma }_{EU}^2\right)}$$

where J represents the number of questionnaire items for a construct; $\overline{S_{xj}^2}$ represents the average variance to jth questionnaire item of the construct perceived by employees in a firm; ${\sigma }_{EU}^2$ represents the variance generated by the random error in a continuous uniform distribution; where ${\sigma }_{EU}^2$ = (measurement scale² −1)/12. Since this study uses the Likert 7-point scale of measure for the questionnaire, therefore ${\sigma }_{EU}^2$ = (7² −1)/12 = 4

In addition to r_wg, we also need to calculate ICC₁ and ICC₂. The absolute value of ICC₁ and ICC₂ should be greater than 0.08 and 0.70, respectively [99,102]. The formulae of ICC₁ and ICC₂ are illustrated as follows:

$$IC{C}_1=\frac{MSB-MSW}{MSB+\left(K-1\right)\times MSW}$$

$$IC{C}_2=\frac{MSB-MSW}{MSB}$$

where K represents the truncated average firm size. For example, if the average sample size is 10 to 11 people for a firm, K would be 10. Furthermore, MSB and MSW are the mean square between groups and the mean square within groups obtained from ANOVA output. The test conditions and the sources for intraclass coefficients are: r_wg ≥ 0.70 [103]; |ICC₁| ≥ 0.08 [99,102]; |ICC₂| ≥ 0.70 [99,102]. If r_wg < 0.70, the within-firm variance is too high and the data from the firm are not suitable for the study and should be discarded. If ICC₁ < 0.08 or ICC₂ < 0.70, the between-firm variance is too low and multilevel data analysis is not suitable.

6. Analysis and Results

6.1. Demographics

According to the demographic profile listed in

Table 1. Demographic profile of respondents (N = 471).

Variable	Category	Frequency	%
Sex	Male	192	40.76
	Female	279	59.24
Age	<19	2	0.42
	20–30	106	22.51
	31–40	218	46.28
	41–50	127	26.96
	51–60	15	3.18
	61–70	3	0.64
	>71	2	0.42
Education	Junior high school	0	0
	High/vocational school	24	5.10
	College	385	81.74
	Graduate school	62	13.16
Working experience (year)	<1	12	2.55
	2–5	86	18.26
	6–10	120	25.48
	11~15	108	22.93
	16~20	74	15.71
	21~25	49	10.40
	26~30	15	3.18
	>30	7	1.49
Years at current job	<1	49	10.40
	2–5	162	34.39
	6–10	130	27.60
	11~15	57	12.10
	16~20	38	8.07
	21~25	25	5.31
	26~30	8	1.70
	>31	2	0.42

, 40.76% of the respondents are male, while 59.24% are female. The majority of respondents are between the ages of 31 to 40 (46.28%), are college graduates (81.74%) and have 6~15 years of working experience (48.41%). The majority (61.99%) of them have 2~10 years of experience at their current job position.

6.2. Factor Analysis

6.2.1. Exploratory Factor Analysis

We conducted the Kaiser-Mayer-Olkin (KMO) and Bartlett’s test of sphericity before performing the exploratory factor analysis. Using AMOS 20.0, we found the KMO value to be 0.955 (higher than the recommended level of 0.7) and the significance of Bartlett’s test to be p < 0.001. This finding confirms that the data set exhibits a multi-variant normal distribution and is adequate for exploratory factor analysis (EFA). Next, the exploratory factor analysis used the principal axis factoring method to extract the essential component items for each construct. Using the varimax with Kaiser normalization rotation [104,105], 6 factors were extracted, and the cumulative variance explained accounts for 63.50%.

Moreover, 20 items (as listed in the Appendix A) were deleted during the EFA process, leaving 42 items for further analysis. Based on Harman’s one-factor post-hoc analysis [101], we found that the 42 items did not fall on the same factor. The results showed that 6 key factors were extracted out of 42 items, and only a small amount of the variance (15.208%) was explained by the most prominent factor. This finding confirms that the questionnaire items did not fall on one factor; therefore, the CMV is not significant.

6.2.2. Confirmatory Factor Analysis

After the EFA above, we conducted a confirmatory factor analysis (CFA) to examine data reliability and validity. Based on the factor loading values, we removed 18 items (as listed in the Appendix A) from this study, leaving only 24 valid items to form the measurement model. The model’s goodness-of-fit indicators are all at the acceptable levels (χ² = 1248.358, df = 362, GFI = 0.84, AGFI = 0.808, CFI = 0.916, IFI = 0.916, RMSEA = 0.072). We then calculated the composite reliability to ensure the construct items’ internal consistency, convergent validity, and discriminant validities.

Table 2. Reliability, discriminate validity, and correlations of constructs (24 items).

Construct	No. of Items	Mean	Std. dev.	Composite Reliability	VIF	OL- IMM	IL- OCB	IL- KI	IL- RQ	IL- RB	IL- MOB
OL-IMM	4	4.124	1.061	0.854	2.084	0.771
IL-OCB	5	3.956	1.004	0.888	2.364	0.641	0.775
IL-KI	3	4.214	1.133	0.887	2.489	0.636	0.688	0.893
IL-RQ	5	4.338	1.109	0.904	2.097	0.608	0.618	0.626	0.805
IL-RB	3	4.661	1.020	0.905	1.878	0.526	0.576	0.619	0.586	0.874
IL-MOB	4	4.382	0.974	0.835	DV	0.544	0.584	0.582	0.526	0.512	0.744

Note: OL = Organizational Level; IL = Individual Level; IMM = Internal Marketing Mechanism; OCB = Organization Citizenship Behavior; KI = Knowledge Integration; RQ = Relationship Quality; RB = Relational Bond; MOB = Market Orientation Behavior. The bold value is the square root of AVE for the construct. These values should surpass the inter-construct correlations of that construct for adequate discriminant validity. Std. dev. = standard deviation; VIF = variance inflation factor; DV = dependent variable. All correlation values are significant at p < 0.001; N = 471.

lists the composite reliability (Cronbach’s α) value of each construct. The values range from 0.835 to 0.905, all exceeding 0.7 and indicating adequate internal consistency and reliability of the constructs [106]. Convergent validity is adequate since all values of average variance extracted (AVE) surpass the threshold of 0.5 [107]. Furthermore, for discriminant validity, the AVE value from a construct should be greater than the variance shared between the construct and the other constructs in the model [108]. According to the results in Table 2, each square root value of AVE exceeds correlations between the construct and any other construct; hence, the discriminant validity is confirmed.

6.2.3. Hierarchical Linear Model

We performed the Hierarchical Linear Model (HLM) analysis to examine the hypotheses. According to [100,101], we can calculate the organizational-level score of each company by aggregating the individual scores in a company if the within-group agreement index r_wg is sufficiently high. The aggregated score represents the shared perceptions toward a specific concept among all participants in the company. Following this procedure, we tested the r_wg of IMM in each company, and the values ranged from 0.700 to 0.945, all reached the recommended level of 0.70 [103]. Then, we examined the between-organizations variance and organization-mean reliability by estimating ICC₁ and ICC₂ intraclass coefficients. The absolute values of ICC₁ and ICC₂ in IMM were 0.08 (=|[110.96−417.90]/[110.96 + (10−1) × 417.90]| = |−306.94/3872.06|) and 2.77 (=|[110.96−417.90]/110.96|). Both of them exceeded the thresholds (ICC₁ ≥ 0.08 and ICC₂ ≥ 0.70) suggested by [99,102]. These results indicate that the within-firm variance is low and the between-firm variance is high, qualifying the use of the hierarchical linear model for multilevel data analysis. Finally, we conducted the ANOVA analysis for IMM using the individual employees’ scores. The results in

Table 3. ANOVA results for internal marketing mechanism.

	Sum of Square	df.	Mean Square	F	p
Between Groups	110.957	46	2.412	2.447	0.000
Within Group	417.902	424	0.986
Total	528.859	470

show that the variances between groups are larger than within groups (F = 2.447, p < 0.001), indicating the significant difference between banks and the use of HLM is appropriate.

To test the hypotheses, we examined three competing models with the null model as the baseline model. Model 1 shows the direct effects of individual-level variables (OCB, KI, RQ, and RB) on MOB. Model 2 adds the organizational-level construct of IMM. Finally, Model 3 adds the cross-level interactions between the variables at the two levels to verify the moderating effects postulated in H6a to H6d.

We regarded the group averages as the center to adjust prediction at the individual level. This method can decrease the collinearity of the organizational-level’s intercept and slope, providing higher accuracy of estimation for HLM analysis [98]. The results of the HLM analysis are shown in

Table 4. The results of HLM analysis.

	Dependent Variable: IL-MOB
	Null Model	Model 1	Model 2	Model 3
Individual Level (IL)
Intercept (γ00)	4.382 ***	4.382 ***	−0.004	4.381 ***
IL-OCB (γ10)		0.252 ***	0.405 **	0.228 ***
IL-KI (γ20)		0.225 ***	0.309 ***	0.179 ***
IL-RQ (γ30)		0.136 **	0.311 ***	0.158 **
IL-RB (γ40)		0.135 **	0.183 ***	0.160 **
Organizational Level (OL)
OL-IMM (γ01)			0.479 ***	0.673 ***
Cross-level
IL-OCB × OL-IMM (γ11)				−0.221 **
IL-KI × OL-IMM (γ21)				0.038
IL-RQ × OL-IMM (γ31)				0.039
IL-RB × OL-IMM (γ41)				0.271 **
Level-2 (OL) error term	0.11331	0.06408	0.05390	0.05901
Level-1 (IL) error term	0.83804	0.48306	0.48315	0.45048
Pseudo R2 between-group a		0.43447	0.15886	−0.09481 c
Pseudo R2 within-group b		0.42358	−0.00019 c	0.067619
Model deviance	1296.307	1051.257	1046.502	1041.317

Note: γ_ij represents the slope of the ith Level-1 predictor interacting with the jth Level-2 predictor. Pseudo R² = (unrestricted error term—restricted error term)/unrestricted error term. ^a Proportion of between-group variance explained by Level-2 predictors. ^b Proportion of within-group variance explained by Level-1 predictors. ^c Negative value indicates that the inclusion of an additional predictor increases the magnitude of the variance component. ** p < 0.01; *** p < 0.001.

.

According to Model 1, OCB (p < 0.001), KI (p < 0.001), RQ (p < 0.01), and RB (p < 0.01) significantly and directly affect MOB, respectively supporting H1, H2, H3, and H4. Meanwhile, IMM directly influences MOB as indicated by Model 2, supporting H₅. Furthermore, IMM’s moderation effects on the individual-level relationships of OCB and RB with MOB are both significant (p < 0.01). However, IMM’s moderation effects on MOB’s relationships with KI and RQ are insignificant and fail to support H6a and H6b. To test the validity of HLM, we randomly deleted two valid sample banks and test Model 3 again. The estimates and patterns did not change much, revealing that our model’s degree of validity was high. The results for Model 3 analysis are shown in Figure 3.

Table 4 indicates that all the direct effects from IMM (γ₀₁ = 0.673; p < 0.001), OCB (γ₁₀ = 0.228; p < 0.001), KI (γ₂₀ = 0.179; p < 0.001), RQ (γ₃₀ = 0.158; p < 0.01), and RB (γ₄₀ = 0.160; p < 0.01) to MOB are positive and significant. While the interaction effect of IL-RB × OL-IMM is positive and significant (γ₄₁ = 0.271; p < 0.01), the interaction effect of IL-OCB × OL-IMM is negative and significant (γ₁₁ = −0.221; p < 0.01). According to the interaction plots shown in Figure 4, when the IMM is higher, the relationship between RB and MOB is stronger. As the interaction effect of RB and IMM increases MOB, H6c is supported. However, Figure 5 shows that the relationship between OCB and MOB displays an opposite pattern (negative slope); it is weaker when the IMM is higher. That is, the OCB × IMM interaction effect reduced MOB regardless of the degree of IMM. Therefore, H6d is not supported.

7. Conclusions

The results confirm that all individual factors (KI, RQ, RB, and OCB) directly influence MOB. The finding of KI’s effect on MOB is consistent with that of [109], in which knowledge sharing among employees can improve competitive advantage and corporate performance. To improve MOB, market knowledge should be disseminated within the department and between departments to ensure all employees acquire adequate information to respond and create actions to deal with current customer needs and competitive environments [7].

Moreover, consistent with [19], RQ positively influences MOB. Viewing internal marketing from the relationship marketing perspective, implementing IMMs brings up an employee’s job satisfaction, commitment, trust in management, and excellent internal customer RQ, which in turn improves MOB. Likewise, RB affecting MOB is consistent with the finding of [67]. The activities to form structural, social, and financial bonds affect employees’ behaviors and promote customer orientation. Therefore, RB is a crucial factor that engenders internal customers’ willingness to display MOBs.

This study confirms the finding of [19] that OCB has a positive effect directly on MOB. It implies that rewarding employees for providing excellent customer service enhances desirable extra-role behaviors and entices employees to meet organizational performance requirements. Employees would expect rewards and strive to deliver better quality services and create more customer satisfaction. Therefore, OCB positively influences MOB.

In contrast to individual factors, a firm’s IMM directly and positively influences the MOB of individual employees. This finding is in line with the market orientation model of [7]. In their model, these antecedent factors of market orientation are affected by IMMs such as communications, motivation, reward, and support, positively affecting customer orientation and inter-functional coordination in the MOB.

Finally, a firm’s IMM can interfere positively with RB’s relationship with MOB but negatively with OCB’s relationship with MOB. Based on the path coefficients in Figure 3, IMM seems to overpower RB’s effect on the MOB because its direct and interaction effects are much higher than RB. Moreover, when IMM is high, its interaction effect on MOB with RB is much higher than that of low IMM, according to Figure 4.

Previous studies [19,87] reported that rewards, training, empowerment, trust, commitment, and organizational support enhance in-role performance, proactive behavior, customer satisfaction, and service quality. The negative moderation of IMM in this study is contrary to their findings. In particular, the interaction effect of OCB and IMM on MOB being negative offers a caveat to corporate management that IMM should be institutionalized, and OCB should not be overemphasized in a firm. According to Figure 5, when IMM is high, OCB should be low to maintain high MOB. To avoid any negative interaction effect, we highly recommend a firm to put employees’ OCB activities on hold when IMM practices are being deployed.

8. Contributions and Implications

8.1. Theoretical Contributions and Implications

This study is the first to adopt job performance theory and treat employee MOB as a surrogate of job performance. Based on the theory, the antecedents of MOB as job performance, i.e., opportunity, capacity, and willingness are identified and validated. The relationships of employee MOB and these antecedents are confirmed and interpreted. The research method and findings theoretically contribute to the human resource and marketing management literature. This study is the first to study the relationship between OCB and IMM and their interaction effect on MOB. It is the first to treat IMM as an organizational-level variable, and the research results show that employee MOB increases when either OCB or IMM is promoted. The OCB is very important to a certain extent, only when it is not overlapping with IMM activities. If a firm has too much OCB, it may consume its resources without increasing any performance. Since IMM is a firm’s formal program but OCB is not, it is much more important to focus on IMM rather than on OCB if it wants to increase MOB. Based on Figure 3, IMM shows a higher positive influence (γ₀₁ = 0.673; p < 0.001) on MOB than OCB does (γ₁₀ = 0.228; p < 0.001). However, the interactive influence of OCB and IMM on MOB is negative (γ₁₁ = −0.221; p < 0.01). This finding suggests that future researchers should avoid using both OCB and IMM in a research model. Figure 5 suggests that the value of OCB is opposite to that of MOB; when OCB increases, MOB decreases. Under high OCB, increasing IMM activities weakens MOB significantly. Therefore, OCB and IMM cannot be implemented together.

8.2. Practical Contributions and Implications

OCB is an extra-role behavior as well as a spontaneous behavior. According to Figure 3, all individual-level variables have significant and positive influences on the MOB, and OCB is the strongest. At the organizational level, IMM has a much stronger influence on MOB than OCB does. This finding implies that companies should institutionalize IMM and encourage OCB, KI, and, in sequence, increase RB and RQ. All these activities can lead to higher MOB and better competitive advantage.

Furthermore, the results in Figure 3 and Figure 4 support hypothesis H6c in that firm’s IMM moderates positively the effect of employee RB on employee MOB. The interaction plot in Figure 4 shows that the high IMM line slope is steeper than that of the Low IMM line. When implementing IMM in a firm with low RB, the MOB quickly increases (from 10.05 to 13.57). This improvement is much faster when a firm has a high RB (from 12.07 to 16.76). Therefore, when IMM is high, MOB increases faster, indicating the interaction is positive and supporting H6c. This result implies that managers should institutionalize IMM and promote RB at the same time to improve MOB in the firm.

In contrast, when IMM is deployed in a firm, it may thwart the spontaneous OCB among employees, as Figure 5 implies. One reason may be that internal marketing is a formal program with standard procedures and performance evaluation criteria. Usually, a firm has KPIs to evaluate general operational performance, coercing in-role behaviors over OCB. Executing IMM practices consumes much time and resources from a firm, leaving its employees little to no time to perform OCB activities. Under such a condition, anyone who insists on offering OCB to others is destined to suffer productivity loss and reduction in his/her MOB. According to the solid line in Figure 5, when a firm’s IMM is high, the smaller the number of OCB activities, the higher the employee MOB. Conversely, the more the OCB activities, the lower the employee MOB. In other words, too many OCB activities may interfere IMM activities and stifle its employees’ MOB. Therefore, when a firm is implementing IMM, all OCB activities should be temporarily discouraged or even prohibited, but no punitive action should be taken against the altruistic employees.

9. Limitations and Future Research

One limitation is that samples from this research are employees of the financial service industry who work at major banks in Taiwan. A future study could expand to financial holdings services that include life insurance, property insurance, securities (investment trust, investment consulting) and internet banking service. Without such a complete and abundant research sample, we could not generalize the conclusions. Moreover, this study used the procedural, same-source-bias, and statistical remedies to collect data from different firms [101] and avoid CMV. However, we should use different data sources (different respondents or measurement tools) for different variances and concurrently use both subjective and objective data in future research studies [100]. Finally, it is surprising that IMM generated a negative interfering effect on OCB in the cross-level analysis. We can further use personal interviews to interpret the statistical results carefully. The outcomes of such research can help us reflect on actual situations and gain accurate insights.