Socio Cultural Approach To Learning About Customers Management Essay
Customer satisfaction can be defined in various ways. According to Kotler et al. (1996), satisfaction is “the level of a person’s felt state resulting from comparing a product’s perceived performance (or outcome) in relation to the person’s expectations.” In brief, satisfaction level simply is a function of the difference between perceived performance and expectation (Stahl, 1999).
In the contemporary global economy and highly competitive business environment, it is fatal for a business organization to be non-customer oriented (Dimitriades, 2006). In fact, only those customer-centred organizations that can deliver superior value to their customers will survive in the cut-throat business arena. To yield highly satisfied and loyal customers, organizations throughout the world are striving to produce products and services of superior quality. For decades, CS is considered to be the key success factors for every profit-oriented organization as it affects companies’ market share and customer retention. In addition, satisfied customers tend to be less influenced by competitors, less price sensitive, and stay loyal longer (Dimitriades, 2006).
Although a significant body of research has shown that learning about customers is crucially important to service firms, there has been little research into learning as a distinct process within service management. Most research has examined learning indirectly as either an antecedent variable or an outcome variable in the context of studying other phenomena. This is reflected in Table I, which lists the more important studies in this field.
Learning about customers has often been posited as a prerequisite to service quality. For example, of the ten service-quality determinants proposed by Parasuraman et al. (1985), the ninth was termed “understanding/knowing the customer,” which was said to involve “making the effort to understand the customer’s needs” (Parasuraman et al., 1985, p. 47). Similarly, Gro¨nroos (2000) and Norman (2000) both noted the importance of knowledge and skills in ensuring service quality.
Knowledge of customers has also been posited as an antecedent to service customisation – because frontline contact persons who know their customers have a greater opportunity to tailor the services that the firm offers (Bettencourt and Gwinner, 1996). In this regard, Gwinner et al. (2005) found that a frontline contact person’s level of knowledge influenced the employee’s propensity to adapt the service offering and the style of interaction.
Several studies on service development have implicitly adopted a learning perspective (Alam, 2002; Alamand Perry, 2002; Edvardsson and Olsson, 1996; Gustafsson et al., 1999). However, these authors, who adopted an organisation-wide view of learning, did not elaborate on how individual learners actually learnt. A more explicit focus on the relationship between service development and learning was adopted by Matthing et al. (2004), who established that such learning occurred in customer-employee interactions.
Similarly, Lundkvist and Yakhlef (2004), emphasised a “conversational perspective” of the learning process when they criticised the assumption that successful development of new services depends upon “drawing” information from customers; according to these authors, conversations should be understood as a knowledge-creating process, rather than merely being ameans of transferring information. In a similar vein, Lundkvist and Yakhlef (2004) contended that learning about customers involves more than cognitive processing of information; rather, such a learning process requires social interactions between customers and employees.
Learning about customers has also been seen as a prerequisite for value creation (Wikstro¨m, 1996; Na¨tti et al., 2006). However, Wikstro¨m et al. (1998, 1994), and Wikstro¨m (1996) do not explicitly elaborate on how learning about customers takes place; rather, they focus on why learning is important to value creation and what benefits it brings. In this regard, these authors were apparently influenced by the literature on organisational learning (Nonaka, 1994; Nonaka and Takeuchi, 1995; Senge, 1990).
A socio-cultural approach to learning about customers
According to Engestro¨m (2001), theories of learning have traditionally focused on the acquisition of clearly identifiable knowledge or skills that result in a change of behaviour; moreover, such theories have assumed that the acquired knowledge is stable and well defined. However, according to the same author, individuals in organisations do not learn in a stable and well-defined fashion; indeed, they might not even know when they are learning. Similar views have been advanced by Lave and Wenger (1991), who contended that individuals in organisations learn within the framework of practice, and by Contu and Willmott (2003), who argued that workplace learning should be understood as a part of everyday work practices. According to this socio-cultural approach, learning cannot be understood in isolation from its social, cultural, and historical context. As Sa¨ljo¨ (2000) has observed, knowledge is preserved in the socio-cultural context in which it is situated.
An important aspect of the socio-cultural approach is that learning is enabled (or limited) by the use of learning tools that individuals appropriate (or do not appropriate) fromthe socio-cultural context (Tsoukas andVladimirou, 2001). These tools, which can be intellectual or practical (Sa¨ljo¨, 2000), have been defined as “cultural and institutionalised entities that mediate meaning” (Vygotsky, 1978).Atool can thus be virtually any resource (Sa¨ljo¨, 2000) that contains meaning and enables an individual to make sense of phenomena. Although the vagueness of the notion of a “learning tool” makes it difficult to apply the concept in an empirical setting, it is the contention of the present study that it offers a new and useful way of conceptualising learning about customers.
The most important learning tool is communication (Salv, 2000; Wretch, 1991). Communication through language was described by Sa¨ljo¨ (2000) as a “discursive” tool, whereas non-language-based tools (such as elements of the physical environment) were referred to as “non-discursive” tools. In general, discursive and non-discursive tools are used simultaneously (Sa¨ljo¨, 2000).
The discursive tool of language is characterised by relatively stable forms of utterances that are used in specific situations (Igland and Dysthe, 2003). These types of utterances, which can be referred to as “speech genres” (Bakhtin, 1986), mediate meaning through accepted forms of everyday talk such as greetings, farewells, congratulations, table conversations, and intimate conversations among friends. According to Wertsch (1991, pp. 61-2), speech genres represent a “ready-made way of packaging speech” in forms that are typically routines, predictable, and bounded by framing devices. Linell (1998) suggested that such speech genres are first developed in interactions between individuals (as tools that mediate meaning), then become historically accepted and fixed in institutional settings, and are subsequently reconstructed and reiterated in various situations.
In summary, a socio-cultural approach to learning about customers perceives such learning as being more than a linear process of information transfer; rather, a socio-cultural approach to learning about customers conceptualises the process as a two-layered process (as shown in Figure 1). At the top of the diagram, the first layer is constituted by the interactions between the socio-cultural context and frontline contact persons. Below this, the second layer is constituted by the interactions between the customers and the frontline contact persons.
In the first layer, learning is of a general and comprehensive character; whereas, in the second layer, learning is specifically associated with particular customers. Certain tools are embedded in the first layer, and frontline contact persons appropriate these tools in learning how to learn about customers. This can be understood as a type of “meta-learning” (Engestro¨m, 1987; Illeris, 2001). In the second layer, the actual learning about customers takes place as discursive and non-discursive tools are appropriated for learning about specific customers in particular moments of interaction. The two layers complement each other; the first layer constitutes the basis of the second layer.
Overview of the framework
Our main thesis is that the smile of a service worker who interacts with a customer in a service encounter provides clues that set in motion a response process in which mediating variables are involved and that this process ultimately has an impact on customer satisfaction. These mediating variables are the customer’s appraisal of the service worker’s overall emotional state, the customer’s own positive emotions, and the customer’s attitude toward the service worker. Our model of this process contains seven links (Figure 1).
Comprising both emotional contagion and affect infusion, and we discuss these links in the sections below. These links, we argue, serve to produce a result in which the smiling service worker induces a higher level of customer satisfaction than the non-smiling service worker, and this outcome represents the main hypothesis in the present study.
Smiles as emotional display behaviour and the customer’s appraisals
While interacting with a customer in a service encounter, the service worker is likely to transmit clues – in terms of facial expressions, body language, and tone of voice – containing information about the service worker’s emotional state. These clues are sometimes referred to as emotional display behaviours (Sutton and Rafaeli, 1988). Given such clues, we assume that the customer (i.e. the receiver) uses them to assess the service worker’s (i.e. the sender’s) emotional state, because to facilitate social interaction, people are motivated to understand each other’s emotions (Ickes, 1993). This assessment can be viewed as an appraisal (Arnold and Landry, 1999; Lazarus, 1982; Nyer, 1997); that is, an immediate, well-nigh automatic response that serves to mediate the relationship between the individual and the environment. We believe that the receiver can make such appraisals in terms of many different, specific emotions (e.g. “the sender is irritated”, “the sender is angry”, “the sender is joyful”), yet we believe that one basic and universal valence dimension covers them all (Russell, 2003). This means that we expect that a general unhappy-happy continuum is a fundamental and irreducible aspect of the receiver’s perception of the sender’s emotional state. It appears as if facial expressions provide particularly important clues for such unhappy-happy appraisals, and individuals are very skilled at processing emotional information originating from faces (Niedenthal, 1990). Several empirical studies (Harker and Keltner, 2001; Neumann and Strack, 2000) also show that the receiver’s assessment of a person’s emotional state is highly correlated with the emotional state of the person who is displaying emotions. The display of smiles is a particularly important facial expression; it may be the earliest learned and most generally understood of the nonverbal cues of interpersonal relationships (Bayes, 1972). And several studies indicate that receivers use this variable for various attributions about the sender (Harker and Keltner, 2001; Lau, 1982; Reis et al., 1990). It should be noted that of all appearance-related characteristics of a person, smiling generates one of the highest levels of consensus among receivers (Borkenau and Liebler, 1992). Smiles have also received very high scores in studies of people’s beliefs about overt expressions of positive emotions (Shaver et al., 1987). Moreover, in terms of the expected correlation between the emotional states of a person who is displaying emotions and a receiver’s assessment of this person’s emotional state, it has been shown that the more extensive a person smiles, the more the receiver perceives this person to be in a positive emotional state (Otta et al., 1996). Given this, we assume that when the service worker is displaying a smile, she/he is judged to be in a more positive emotional state by a customer compared to when she/he is not displaying a smile. This assumption is represented by Link 1 in our proposed model (Figure 1).
Several authors have noted that emotions are contagious in social situations, in the sense that one person is easily “catching” the emotion displayed by another person with whom she/he interacts (Hatfield et al., 1992; Hess et al., 1998; Hsee et al., 1990; Neumann and Strack, 2000; Pugh, 2001). Given an emotion-charged view of service encounters, we therefore expect that the sender’s displayed emotions affect the receiver’s emotions.
The means, by which the receiver’s emotions are affected, however, are yet to be settled. Some authors view the link between the sender’s display behaviour and the receiver’s emotions in terms of a facial feedback hypothesis: exposure to the sender’s face results in mimicking muscular activity in the receiver’s face – and this muscular activity informs the receiver about his or her own emotional state (Hatfield et al., 1992; Hess et al., 1998). Barger and Grandey (2006) found support for this in a service setting; they found that the service worker’s smile strength was positively associated with the customer’s smile strength, and that customer smile strength was positively associated with the customer’s positive mood. Given this, we assume that when the service worker is displaying a smile, she/he produces more positive customer emotions compared to when she/he is not displaying a smile, which is represented by Link 2 in our proposed model in Figure 1.
We do not question the facial feedback hypothesis, but we are mindful of the modest variation in the receiver’s emotions that is explained by his/her own facial muscular movements (cf. the low-effect sizes in Barger and Grandey, 2006 and in Harris and Alvarado, 2005). Such empirical results invite the conjecture that one’s face muscles cannot be the only source of one’s emotions. Indeed, we believe that the receiver’s emotions are also predicated on cognitive activity in terms of the appraisal of the sender’s overall emotional state. This belief is consistent with Hsee et al.’s (1990) assumption that our conscious realization that one person is in one particular emotional state could make us end up in the same emotional state. An important assumption behind a causal link between:
-The receiver’s appraisal of the sender’s overall emotional state; and
- The receiver’s own emotion is that appraisals are antecedents to emotions; the link between a stimulus and an emotional reaction is thus seen as mediated by an appraisal (Ellsworth and Smith, 1988; Frijda et al., 1989; Lazarus, 1982; Nyer, 1997; Roseman, 1991; Smith and Ellsworth, 1985).
Empirical research on service customers, however, has only rarely considered the role of such appraisals for the individual’s own emotions. Yet in the light of a few appraisal-based empirical findings showing correlations between appraisals and emotions (So¨derlund and Rosengren, 2004; So¨derlund and Rosengren, 2007), we believe that such appraisals represent a potential for improving our understanding of why customers come to feel what they feel in social interactions. In a service encounter, then, we expect that the customer’s appraisal of the service worker’s overall emotional state serves as a point of reference for emotional mimicry and that the appraisal is related to the customer’s own emotions in a valence-congruent way. That is to say, we assume that the customer’s appraisal of the service worker’s emotional state is positively associated with the customer’s own positive emotions. This is Link 3 in our proposed model in Figure 1.
When one particular object is evoking emotions, such emotions often inform evaluations of this object in a valence-congruent way. This impact of emotions on evaluations has been referred to as affect infusion (Forgas, 1995; Forgas and George, 2001; Pham, 2004). Here, we expect that affect infusion serves to produce a positive association between the customer’s positive emotions and the attitude toward the service worker (that is, an overall evaluation of the service worker), which is represented by Link 4 in our proposed model (Figure 1).
Affect infusion, however, has been documented not only when the emotion-evoking object and the evaluation object are the same; affect infusion may also materialize when the two objects are relatively unrelated (Forgas, 1995; Pham, 2004). Presumably, the level of affect infusion is a function of the degree of relatedness between objects, in the sense that an evaluation of one particular object is likely to be more affected by emotions the more this particular object is responsible for the emotions. The level of relatedness between objects and its potentially moderating impact on affect infusion, however, has not received much attention in the literature (Pham, 1998). Here, we make an attempt to explore this issue by examining affect infusion in the mind of the service customer for which the emotion-evoking object is the service worker and the evaluation object is the firm in which the service worker is employed. Moreover, we examine this evaluation in terms of customer satisfaction – which we view as a global evaluation variable. In more specific terms, and thus in addition to the expected link between the customer’s own emotions and the attitude toward the service worker (i.e. Link 4 in Figure 1), we expect a positive association between the customer’s own positive emotions and customer satisfaction. This, then, is Link 5 in the proposed model in Figure 1. In empirical terms, Link 5 is suggested by the results in Barger and Grandey (2006) and So¨derlund and Rosengren (2004) and in several studies of emotional antecedents of customer satisfaction (Mano and Oliver, 1993; Mattila and Enz, 2002; Oliver, 1993; Wirtz and Bateson, 1999).
Additional and non-emotional links
We include two additional links in our model. First, we believe that there can be a direct link between the customer’s appraisal of the service worker’s overall emotional state and the customer’s attitude toward the service worker. This link should be seen in the light of research indicating that persons who are perceived to be in a positive emotional state are perceived to be more likeable (Clark and Taraban, 1991; Lau, 1982), pleasant (Harker and Keltner, 2001), friendly (Nelson et al., 1988), intelligent (Lau, 1982), sincere and sociable (Reis et al., 1990), and subject to more positive overall evaluations (Lau, 1982) than persons perceived to be in negative or neutral emotional states. A smile, then, and as one physical characteristic of a person, appears to work in a way which is similar to the more well-documented “what is beautiful is good” stereotype, in the sense that both the smile and good looks induce attributions of many positive aspects of a person. Yet the smile appears to have these effects independent of physical attractiveness, even though smiles serve to increase perceptions of physical attractiveness (Reis et al., 1990). Here, we assume that such smile effects are contingent on an appraisal of the person’s overall emotional state, and we therefore expect a positive association between the customer’s appraisal of the service worker’s overall emotional state and the customer’s attitude toward the service worker. This is represented by Link 6 in Figure 1.
Second, previous research shows that several specific characteristic of the service worker, such as friendliness (Grandey et al., 2005) and responsiveness to service delivery failures (Bitner et al., 1990, Bitner et al., 1994), are associated with customer satisfaction. The main reason appears to be that services in general are inseparable from the person who delivers the service; the service worker thus becomes a highly salient figure against a ground from the customer’s point of view. Moreover, the customer’s perceptions of the service worker’s characteristics can be viewed as beliefs about various service worker attributes; therefore, given attitude theories such at the theory of reasoned action (Ajzen and Fishbein, 1973), we assume that such attributes are subsumed under a general evaluation in terms of an attitude toward the service worker. We thus expect a positive association between the customer’s attitude toward the service worker and customer satisfaction; it is represented by Link 7 in Figure 1.
In sum, then, we expect that the service worker’s display of smile in a service encounter sets in motion a process involving the customer’s appraisal of the service worker’s emotional state, the customer’s own emotions and the attitude toward the service worker, and that these variables contribute to customer satisfaction. More specifically, this is what we hypothesize with regard to the outcome of the process:
H1. When the service worker smiles in the service encounter, she/he produces a higher level of customer satisfaction compared to when she/he does not smile.
We make an attempt to test this hypothesis by taking into account one additional aspect that may contribute to customer satisfaction when the customer is interacting with a smiling or non-smiling service worker in the service encounter: the sex of the service worker. Although theory is not well-developed in this area, it has been shown that women smile more than men (Deutsch, 1990). It has also been argued that women are more emotionally expressive than men (Mattila et al., 2003). This means that a smiling female service worker may be considered more prototypical than a male service worker. Given that a typical stimulus fosters information processing fluency (i.e. the ease with which information can be processed) to a larger extent than a non-typical stimulus, and given that a high level of processing fluency has a positively value and is likely to color an evaluation in a valence-congruent way (Schwarz, 2004), a smiling female service worker may contribute more to customer satisfaction than a smiling male service worker. Theory thus suggests an interaction between the service workers’s smiling behaviour and the service worker’s sex (rather than a main effect of the service worker’s sex), so we hypothesize the following:
H2. When the female service worker smiles in the service encounter, she produces a higher level of customer satisfaction compared to a smiling male service worker.
We turn now to an empirical assessment of these two hypotheses (and to an assessment of the assumed mediating links).
Review of Kano’s model
Kano’s model, proposed by the Japanese professor Noriaki Kano and his colleagues, is a useful tool to understand customer needs and their impact on customer satisfaction (Kano et al., 1984). It categorizes different CRs based on how well they are able to achieve customer satisfaction. In the following section, the literature on the traditional Kano’s model and its recent research is reviewed.
The Kano diagram and questionnaire
The Kano diagram depicts three types of relationships between the degree of customer satisfaction and the fulfilment level of CRs – namely must-be, one-dimensional and attractive (Kano et al., 1984) – as represented by three different relationship curves in the diagram, as shown in Figure 1. In the Kano diagram, the horizontal axis indicates the level of fulfilment of a specific CR, while the vertical axis denotes the level of customer satisfaction or dissatisfaction towards the fulfilment level of that CR.
Must-be Attributes. Customers take must-be attributes for granted when they are fulfilled. However, if the product does not meet these requirements sufficiently, customers will be dissatisfied.
One-dimensional attributes. Regarding one-dimensional attributes, their fulfilment is positively and linearly related to the level of customer satisfaction. The higher the level of fulfilment, the higher the degree of customer satisfaction, and vice versa.
Attractive attributes. Fulfilment of attractive attributes will lead to greater than proportional satisfaction. However, the absence of these requirements does not result in dissatisfaction because they are not expected by customers.
In addition to the three main categories of CRs, Kano and his colleagues also proposed three more categories of CRs:
(2) Reverse; and
If a CR is classified as indifferent, it means that customers are indifferent to that requirement and its fulfilment or lack of fulfilment will not cause any increase or decrease in customer satisfaction with the product. The other two categories indicate either a contradiction in the customer’s answers to the questions (questionable) or customers’ dislike towards the requirement (reverse).
The Kano questionnaire helps to categorize CRs into the six Kano categories. The questionnaire examines each CR with a pair of questions, functional and dysfunctional forms. There are five possible answers for each pair of questions: like, must-be, one-dimensional, neutral, live with and dislike. Based on the combination of customer responses to both questions, the CR is classified as one of six Kano categories for that customer by checking the Kano evaluation table (see Figure 2). Generally, the mode, or the most frequent observations of the sample set of responses, is considered as the final Kano category for that CR (Kano et al., 1984).
Existing research on Kano’s model
Kano’s model is widely recognised and used in the analysis of customer needs and satisfaction. It has been adopted by many researchers as a useful tool to study customer requirements and achieve better design in various industries, such as logistics services, website design, reliability studies and car design (Huiskonen and Pirttila¨, 1998; Tan et al., 1999; Shen et al., 2000; Zhang and Dran, 2001; Kuo, 2004; Shahin, 2004; Baki et al., 2009).
In addition to the research on the application of Kano’s model, a number of researchers have attempted to advance the theoretic analysis of Kano’s model. King (1995) proposed some general guidelines for the classification of CRs. He postulated that unsolicited complaints are most often must-be attributes, one-dimensional attributes are most-often identified by surveys, and attractive attributes are those developed by suppliers based on new insights and breakthroughs. Fong (1996) proposed using the self-stated importance questionnaire to complement the Kano questionnaire when customer responses are evenly distributed among two or more Kano categories. Matzler et al. (2004) compared Kano’s model with importance-performance analysis (IPA), another analytical technique for customer satisfaction. By using a regression analysis with dummy variables, Kano’s model, especially nonlinear relationships between attribute-level performance and customer satisfaction, is confirmed empirically. The above research focuses more on the categorization of CRs and classification method in Kano’s model, while the measurement on customer satisfaction was seldom discussed. Berger et al. (1993), however, introduced some quantitative analysis of customer satisfaction into Kano’s model by calculating two values (“better” and “worse”) to reflect the average impact of a CR on customer satisfaction or dissatisfaction of all customers. These two values, named by Matzler and Hinterhuber (1998) as extent of customer satisfaction (CS) and extent of customer dissatisfaction (DS) for each CR, respectively, indicate how strongly a CR may influence customer satisfaction with the existence of a CR (or its sufficiency), and in case of its unfulfillment, customer dissatisfaction. Tontini (2003) proposed some modifications of Kano’s model by introducing three customer satisfaction coefficients to have a more accurate measure of customer satisfaction or dissatisfaction. Both Berger et al.’s (1993) and Tontini’s (2003) analysis improved Kano’s model in understanding the impact of different CRs on customer satisfaction. However, simply calculating some index values cannot precisely reflect the diverse relationships between CR fulfilment and customer satisfaction, especially these non-linear relationships associated with must-be an attractive attributes which is a major contribution of Kano’s model (Xu et al., 2009). More quantitative research is in need to investigate the relationship curves in the Kano diagram.
Factor affects the customer satisfaction
LD can be defined as the process of influencing others towards achieving some kind of desired outcome (de Jong and den Hartog, 2007) and it is one of the essential elements (Fecˇikova´, 2004; Soltani et al., 2008). According to Gonza´lez and Guille´n (2002), the achievement of this principle depends much on the commitment of the top management to allocate resources and encourage actions (i.e. deployment of information-gathering devices, encourage the use of analytical tools that allow customer expectations to be transformed into product specifications and process standards, etc.). In an empirical study, Pannirselvam and Ferguson (2001) investigated the relationships between the Baldrige categories in relation to satisfaction philosophy. The results from this research signified that LD was significantly (either directly or indirectly) affected CS. Brookshaw and Terziovski (1997) further illuminated that effective LD in requirement to earn customer trust. Thus, the following hypothesis was proposed:
H1. LD has a significantly positive association with CS.
SP can be defined as the process managers use to formulate and implement strategies for providing the best value to the stakeholders and achieve the stipulated goals of the organization (Bounds et al., 1994). Ideally, it involves the mapping of long- and short-term organizational vision/mission (Tarı´, 2005). Particularly, there is lack of empirical studies that examines the effects of organization’s vision on CS. Indeed, a significant casual link is found between organization’s vision and CS, as well as employee satisfaction (Kantabutra, 2008; Kantabutra and Avery, 2007). Both Kantabutra (2008) and Kantabutra and Avery (2007) also studied the effects of vision on customer and staff satisfaction, but the former was focused on the Australian settings while the latter was applied in the context of Thai retail stores. Generally, the results of both studies revealed a significant association between overall customer and staff satisfaction, and stores with a vision. In the Thai settings, the vision attributes, communication, empowerment, motivation, and employee satisfaction were indirectly predicted enhanced CS. Ironically, the variables of vision attributes, communication and motivation rendered no significant effect in Australian retailers, only empowerment and staff personal factors were directly predicted enhanced CS. Thus, the following hypothesis was proposed:
H2. SP has a significantly positive association with CS.
CF is referred as the degree to which an organization continuously satisfies customer requirements and expectations (Zhang, 2000) and it is considered to be one of the basic building blocks of TQM (Bank, 2000). In the highly competitive business environment, one of the most vociferous pressures on management in all types of organization is to focus on customer needs (Piercy, 1995). The key to quality management is maintaining a close relationship with the customers, so that customers’ needs can be fully understood and those needs are being met can be received (Zhang, 2000; Li et al., 2006). In the efforts to pursuit CF, information about customers’ needs and wants, complaints, level of satisfaction, etc. are gathered and analyzed (Lagrosen, 2001; Zhang, 2000; Phusavat et al., 2009). According to the review results from Hackman and Wageman (1995), obtaining information about customer is one of the most frequently used TQM implementation practices.
In the contemporary global economy and turbulent market environment, it is vital for organizations to achieve high levels of CS. Only those firms who are able to satisfy customers’ needs and requirements are able to survive and compete effectively in the cutthroat business playing field. To be successful, firms should recognize the need to put customer first in every decision making or perhaps, adopt a customer-focus or customer-centred culture. Thus, the following hypothesis is formulated:
H3. CF has a significantly positive association with CS.
A process is a systematic approach for converting inputs into outputs; it is the way in which all the resources of an organization are used in an effective and efficient manner to achieve its goals (Zairi, 1997). A relatively new area of such improvements is “business process management (BPM)” (Elzinga et al., 1995, p. 119). Since business processes are considered to be the horizontal linkages between key activities that impact the customer (Zairi, 1997), managing these “end-to-end” processes should be a continuing effort if the companies are to meet customers’ specific needs and requirements. Process capabilities and implementation determine critical aspects of the customer encounter such as speed, accuracy, courtesy, and, etc. which in due course, determine CS (Maddern et al., 2007). In an empirical study, Kumar et al. (2008) systematically investigated the linkages between BPM and CS. The researchers also challenged the dominance of the customer contact perspectives on service processes and had proposed a more systemic focus on the totality of service design. The results revealed that the significance of BPM as a critical factor in driving CS.
Pritchard and Armistead (1999) have conducted a survey and case study research to understand the application of BPM in European companies. The study was drawn on a postal survey conducted with quality directors and business process managers in organizations which are the members of the European Foundation for Quality Management and case studies in a number of organizations regarded as being leaders in the adoption of BPM. It is not surprising that the findings endorsed BPM as a means to achieving business excellence (i.e. improved relationship with customers, better cross-functional working, and a change in organizational culture). Eventually, CS is established as well. The ultimate goal of such business excellences will undoubtedly, result in CS. Much research has shown that effective PM, especially BPM has a positive effect on CS. Thus, the following hypothesis was proposed:
H4. PM has a significantly positive association with CS.
Information and analysis
Concurrent competitive challenges induced by globalization, liberalization, and proliferation in information technology have forced companies to focus on managing customer relationships, and in particular CS (Stefanou et al., 2003). Thus, fulfilling customer needs and expectations are considered to be the baseline for any kind of businesses. When customers’ needs and expectations are met, satisfaction is established.
Benchmarking is the process of comparing performance information, both internally and externally and measuring an organization’s operations or its internal processes against those of a best-in-class performer from inside or outside its industry (Goetsch and Davis, 1997; Chang, 2006). The study of Min et al. (2002) highlighted the usefulness of dynamic benchmarking for continuous service improvements and establishment of CS, especially in the hospitality context (i.e. hotel industry). According to the researchers, CS is deemed to be the most important strategic weapons of best-practices hotel organizations. Nevertheless, without gaining the knowledge of a hotel’s competitive position in the changing marketplace and realizing the opportunity of continuous service improvements, hotel organizations cannot achieve total CS. Therefore, the following hypothesis was proposed:
H5. Information and analysis (IA) has a significantly positive association with CS.
Human resource focus
Human resource management (HRM) can be defined as “the policies and practices one needs to carry out the ‘people’ or human resource aspects of a management position including recruiting, screening, training, rewarding and appraisals” (Dessler, 2000, p. 678). Yang (2006) systematically studied the impact of HRM practices on the implementation of TQM within the high-technology firms and the empirical results of the study found that HRM practices can have significant effects on CS. For many years, CS has been the ultimate goal of every business organizations as it can lead to increased revenue and profit (Kotler et al., 1996). Thus, Yang (2006) justified that a company must design and implement systems of managing CS, and that company depends entirely on employees to implement and maintain such systems.
Ott and van Dijk (2005) investigated the effects of HRM on client satisfaction in the nursing and care industry. EightHRMactivities were developed and measured in the study, namely personal development plan, job-related training, annual performance review, employee involvement, protocol for labor-shortage, predictable work schedules, transparent management style, and supportive management style. Conversely, employee satisfaction was correlated primarily with the management style of the unit manager, and to a lesser degree affected by performance reviews and predictable work schedules. In the empirical study of the relationship between employee attitudes, CS, and departmental performance, Adsit et al. (1996) found that the dimensions of employee attitudes, namely team participation and attention to performance evaluation were positively related to CS. Based on the above comprehensive review of the association between HRM and CS, the following hypothesis was proposed:
H6. HR has a significantly positive association with CS.
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