Customer Centricity: Antecedents and Consequences

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ustomer Centricity:

Antecedents and consequences

. GEERTS

January 2015

Customer Centricity:

Antecedents and Consequences

T. GEERTS

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Customer Centricity:

Antecedents and Consequences

by

TOMAS GEERTS

University of Groningen

Faculty of Economics and Business

MSc Marketing

January, 12, 2015

Supervisor: dr. J.C. Hoekstra External supervisor: drs. J. Berger

Oosterkade 9d14 9711 RS Groningen

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PREFACE

After a student life of six and a half years, the completion of this master thesis, marks the end of my life as a student. I can say without doubt, that I got the most out of it. Highlights were my time in the executive board of student association Dizkartes, and the IBR research project in South Africa. But I also enjoyed the courses I followed in the Bachelor Business Administration, and the program of the Master Marketing Management even more. I really liked the fact that my master thesis project was commissioned by the PvKO (Platform van Klantgericht Ondernemen). The fact that the outcomes of this study would be of practical relevance motivated me. Besides, the cooperation with the PvKO and my fellow students made the writing of my master thesis more vivid.

All in all, I can look back at a successful and inspiring period. First of all, I would like to thank my parents Freddie and Marjolein, my sister Renée, and my girlfriend Rixt, for the support they gave me the last couple of months, but also in the years before. Second, I would like to thank Sicco Hempenius and Lisette Klaver, for the great cooperation and joyful time working together. Third, I would like to thank Janny Hoekstra, for the supportive and pleasant guidance during the whole project. Lastly, I would like to thank the members of the Platform voor Klantgericht Ondernemen (PvKO), for giving me and my fellow students the opportunity to write our master thesis on a challenging and exciting topic. Their contribution, especially in the field of data collection was of great help.

Tomas Geerts

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MANAGEMENT SUMMARY

This study examines customer centricity, its antecedents, and consequences. As a starting point, the model of Shah et al. (2006) is used. We expect that eight factors in the field of organizational structure, processes, organizational culture and customer metrics positively influence the customer centricity in organizations. Furthermore, we expect that customer centricity, and its antecedents, positively influences the customer performance and organizational performance of an organization. Lastly, customer performance is expected to increase the organizational performance of an organization. To assess these relationships, an online survey is conducted among 162 Dutch marketing and customer managers, incorporating questions regarding all the variables in the study. Several questions regarding control variables are added to the survey as well. These control variables are firm size, industry, B2B/B2C, competitive intensity and environmental dynamism. When possible, measurement scales from literature were altered or adopted, in other occasions own measurement scales were developed.

The collected data was analyzed using regression analysis. The result show that only an aligned organization structure, and a customer integrated organization structure, increase customer centricity and customer performance. The other antecedents were not found to have a significant influence on customer centricity or customer performance. There is also no proof for the influence of customer centricity on customer performance. Organizational performance is only significantly influenced by the collection of customer information, the measurement of customer metrics, and customer performance. The other antecedents of customer centricity, and customer centricity itself, do not influence organizational performance. We found however, that a customer integrated organizational structure has an indirect positive influence on organizational performance. This effect is mediated by customer performance. Lastly, the control variables in our study do not significantly influence customer centricity, customer performance and organizational performance.

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5 The managerial implications of this study are small in number. Managers should focus on shaping an organizational structure that enables and promotes close cooperation of departments throughout the organization, and the integration of customers’ needs and wants in the development of products and services. In that way they can improve the customer centricity and customer performance of their organization. Besides, managers should concentrate on the collection of customer information, the measurement of customer metrics, and the introduction of a customer integrated organizational structure to improve organizational performance. Lastly, managers should focus on the customer performance of their organization, to increase their organizational performance. This study proves that customer performance functions as a great predictor of organizational performance.

Keywords:

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1 INTRODUCTION

The earliest work in the field of customer centricity dates back half a century. Drucker (1954) and Levitt (1960) proposed that the customer determines what an organization produces and sells, and that the focus of organizations should be on fulfilling customer needs instead on just selling products and services. Over the past decades, customer centricity received increased attention of academics and marketing practitioners. The traditional product-centric approach of organizations gradually converted into a marketing-centric, and eventually a customer-centric approach (Sheth et al., 2000). This shift entailed a change in marketing thought and practice. Whereas the focus of product-centric organizations was on serving the needs of the mass market, the focus of a market-centric and customer-centric organizations is serving, respectively, market segments and the individual customer (Sheth et al., 2000).

Although the concept of customer centricity did not emerge recently, it is very relevant at the moment. Research indicates that marketers who spend 50% or more of their time on customer-centric marketing processes and activities perform at least 30% better at marketing ROI than their competitors (Marcus & Collins, 2003). Furthermore, a growing number of companies consider customer centricity as the most important part of their competitive advantage (Lamberti et al., 2013). It is clear that customer centricity has been on the agenda of organizations for a long time; however, to this day a lot of organizations lack behind on terms of being customer-centric (Shah et al., 2006; Lamberti, 2013). The results of CRM implementation are not exclusively positive (Reinartz et al., 2004); approximately 29%-70% of CRM projects fail (Iriana et al., 2013). Furthermore, the quality of customer information that is compiled by organizations strongly differs among firms (Krasnikov et al., 2009). Problems arise through internal conflicts about information ownerships, the failure of information sharing across business units, and the lack of organization-wide strategy in regards to managing customer information (Peltier, 2013).

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8 centricity literature has not succeeded in identifying factors that foster customer centricity, nor its outcomes. As a result, guidelines to accomplish customer centricity, as well as an incentive to implement customer centricity, are missing. This paper addresses this gap in customer centricity literature by empirically assessing the antecedents and consequences of customer centricity, and developing an instrument to measure the degree of customer centricity in an organization.

Prior work on customer centricity did not take customer centricity as the main construct of analysis. Jayachandran et al. (2005), found that implementing a customer-centric management system, has an indirect influence on customer relationship performance. Besides, Peelen et al. (2009) found that a customer-centric strategy positively contributes to performance of CRM processes, however they found no positive relation between customer-centric strategy and customer experience. Other studies examined antecedents and consequences of related marketing concepts, like customer orientation and customer relationship management (e.g. Narver & Slater, 1990; Reinartz et al., 2004; Zhu & Nakata, 2007; Reimann et al., 2010). However, discrepancy between these concepts and customer centricity hinders guidance in this matter: CRM is a collection of processes to manage customers, whereas customer centricity is a business philosophy, and the focus of customer orientation is not necessarily on the individual customer, whereas the focus on the individual customer is an essential part of the customer centricity concept.

In conceptual work on customer centricity, Lamberti (2013) identifies four elements that represent building blocks for customer centricity. Related to this Shah et al. (2006) presented a model that describes antecedents of customer centricity. These antecedents are organizational elements in the field of organizational culture, organizational structure, processes and financial metrics and represent challenges that retain firms from being customer centric. Furthermore, Shah et al. (2006) state that customer centricity leads to superior customer and organizational performance, because customer-centric organizations are enabled to gain a sustainable competitive advantage. The model of Shah et al. (2006) is used as a starting point in this study1, and leads us to the following research question: ‘What are the antecedents and consequences of customer centricity?’.

1_{This study is executed in close cooperation with the Platform voor Klantgericht Ondernemen, and is divided in}

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9 To examine customer centricity, measurement scales are developed for every construct of the model of Shah et al. (2006), and combined in a survey. The survey is sent to a database of approximately 4000 Dutch marketing managers to gain insights in the antecedents and consequences of customer centricity.

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2 THEORETICAL FRAMEWORK

In this chapter the theoretical framework of this paper will be assessed. The conceptual model that is used as the starting point of this paper is represented in section 2.1, followed by the theoretical background of all the constructs and hypothesized relationships in the model. In section 2.2 customer centricity will be defined, also by exploring neighboring marketing concepts. In section 2.3 customer performance and organizational performance are defined. Subsequently, in section 2.4, prior work on antecedents of customer centricity will be reviewed. Lastly, in section 2.5 customer and organizational performance as consequences of customer centricity are explained.

2.1 Conceptual model

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11 Control variables: - Firm size - Industry - B2B/B2C - Environmental dynamism - Competitive intensity H26 2 H1,4,7,10, 11,16,19,20 H6,9,14,15,18,23,24 H25 H27 Org. Structure Processes Customer metrics H3 2 2.2 Customer centricity

To define customer centricity, prior work in the field of customer centricity is discussed. Prior work in the field of customer orientation and CRM, concepts closely related to customer centricity, are discussed as well. This is done to explore the boundaries of the customer centricity concept, and subsequently arrive at an accurate definition of customer centricity. It is remarkable that while the customer centricity concept was introduced during the early 2000´s already, a shared definition is missing to this day. Customer centricity is commonly seen as the opposite of product centricity (Galbraith, 2002; Shah et al., 2006; Lamberti, 2013). Whereas the main philosophy of product centricity is that the products and services are the core value proposition of an organization (Galbraith, 2002), customer centricity has the underlying assumption that an organization should employ its resources and competences to

Figure 1: Conceptual model, based on Shah et al. (2006).

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12 meet customers’ needs and wants, to retain them for a long period of time (Day, 2003). In short a product-centric organization, tries to identify as many customers as possible for its products or services, whereas a customer-centric organization tends to detect as many products as possible for its customers (Galbraith, 2002).

More concrete, customer centricity is seen as a marketing practice that emphasizes the understanding and satisfaction of individual customers’ needs and wants (Sheth et al., 2000). In a customer-centric organization, the individual customers are the main object of analysis for introducing or improving products and services and other organizational actions, instead of internal concerns of business units (Jayachandran et al., 2005; Wagner & Majchrzak, 2007). Furthermore customer centricity is identified as a strategy that places the customer at the center of its activities, to optimize the value creation for customers (Peelen et al., 2009). Lamberti (2013) states that a customer-centric organization manifests itself in four different ways: (1) the gathering of customer intelligence to understand customers’ explicit and hidden needs, (2) the involvement of customers in decision making, (3) the alignment of organizational structures to manage customers along all customer touch-points (also supported by Wagner & Majchrzak, 2007) , and (4) the existence of supply-chain that is capable of producing customized products and/or services. What stands out in these definitions is that the individual customer is considered to be the focal point of analysis, when developing products and/or services. Besides, customers’ interest should be considered when making decisions, regardless of which part of the organization is involved.

Customer orientation

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13 ‘’The degree to which the organization obtains and uses information from customers, develops a strategy which will meet customer needs, and implements that strategy by being responsive to customers’ needs and wants’’. Summarizing, customer orientation encompasses a strategic approach that puts the customer’s interest first (Deshpandé et al., 1993) and is focused at creating and maintaining value for customers (Olson et al., 2005). To accomplish this, information about customers’ needs and preferences is obtained, which is then used to identify possible segments, develop products and/or services for these segments, and base a marketing mix on (Ruekert, 1992; Balakrishnan. 1996; Gatignon & Xuereb, 1997). When we compare the customer orientation concept with the customer centricity concept they seem to be similar, since they both focus on fulfilling the needs and wants of customers. However, there is a clear distinction to make. Customer centricity applies the principles of customer orientation in a more personalized way (Lamberti, 2013): customer centricity is clearly focused on the individual customer, whereas customer orientation, as an element of market orientation, looks at the needs and wants of customer segments, not the individual customer.

Customer Relationship Management

Previous literature also focused on Customer Relationship Management (CRM). CRM is an organizational process that combines marketing strategies and information technology to establish, maintain and enhance long-term relationships with customers (Srivastava et al., 1999, Peelen et al., 2009), to maximize the value of the customers for the organization (Reimann et al., 2010). CRM consists of processes that manage customers through different phases of the customer life cycle. This for example can be cross or upsell, but relationship termination as well (Reinartz et al., 2004). We state that CRM differs from customer centricity in terms of scope. Whereas customer centricity is an organization wide philosophy that beliefs that organizations should focus on maximizing value for individual customers, CRM is more a collection of processes that enables long-lasting profitable relationships with customers. Customer centricity can be the strategy an organization follows, in which CRM is a collection of processes that embodies this strategy.

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2.3 Customer performance & organizational performance

Following prior work (i.e. Homburg & Pflesser, 2000; Zhu & Nakata, 2007; Ramani & Kumar, 2008; and Peltier et al., 2013) we make a distinction between customer performance and organizational performance. Customer performance can be identified as the extent to which an organization successfully uses its marketing capabilities to satisfy its customers, and is reflected in the performance on customer metrics like: customer satisfaction, customer lifetime value (CLV), and net promoter score (NPS). Organizational performance on the other hand, reflects the organization’s capability to convert its activities in financial outcomes, and is indicated by metrics as sales, net profit margin and return on investments (Zhu & Nakata, 2007). In short, customer performance is an estimate of the relationship strength between customers and the firm, whereas organizational performance assesses the financial performance of the firm (Peltier et al., 2013).

2.4 Antecedents of customer centricity2

In this section the antecedents of customer centricity in the field of organizational structure, processes, organizational culture and customer metrics are described, alongside with associated hypotheses.

Organizational structure

Regarding organizational structure, centralization, alignment and customer integration are identified as antecedents of customer centricity. A centralized organization structure, is a structure in which decision-making is delegated to higher management levels. Employees at lower levels within the organization are less empowered to take part in decision making (Mintzberg, 1979; Thalmann & Brettel, 2012). In a decentralized organization on the other hand, the decision-making authority is transferred to lower organization levels, making the organization more adaptive and responsive to the environment, enhancing customer-interactions (Lin and Germain, 2003). Interaction with customers increases the knowledge concerning customer's needs and wants, and leads to profitable customer relationships, accompanied with high levels of customer loyalty and profitability (Sheth et al., 2000; Srinivasan et al., 2002; Ramani & Kumar, 2008; Kasim & Minai, 2009). On the other hand, centralization functions as a barrier for organizations that try to interact with customers, since

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15 centralizing the decision-making authority at the top rather than empowering employees in lower levels obstructs the organization from responding to customers’ needs and wants (Jaworski & Kohli, 1993; Lin and Germain, 2003; Auh & Menguc, 2007; Thalmann & Brettel, 2012). Following these arguments, we expect that a centralized organizational structure negatively influences customer centricity in an organization. Therefore, we hypothesize:

H1: A centralized organizational structure decreases customer centricity

Centralization is found to have a negative influence on the interaction orientation of an organization (Thalmann and Brettel, 2012). Responsiveness, compliance with the customer concept and low levels of bureaucracy are important determinants of an interaction orientation, which are lacking in a centralized organization (Ramani and Kumar, 2008; Thalmann and Brettel, 2012). Interaction orientation increases an organization’s customer-based relational performance, indicating higher customer satisfaction levels (Ramani and Kumar, 2008). Subsequently, high customer satisfaction levels have a positive influence on the creation of superior customer performance (Hooley et al., 2005). These findings show that centralization hinders customer performance by disabling the organizations ability to interact with customers in order to satisfy customers. Furthermore, Boles et al. (2001) state that centralization obstructs the ability and willingness of employees to satisfy customers’ needs and wants, which negatively influences customer performance (Hooley et al., 2005). Based on prior literature we expect a negative influence of centralization on customer performance. Therefore we hypothesize the following:

H2: A centralized organizational structure decreases customer performance

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16 H3: A centralized organizational structure negatively moderates the relationship

between customer centricity and firm performance.

Alignment can be defined as the shared understanding of organizational goals and objectives throughout all levels and departments of the organization (Kathuria et al., 2007). Aligned organizations are better able to share information throughout the organization, because functional silos obstructing the sharing of information are absent (Eng et al., 2006; Peltier et al., 2013). Alignment is also expected to have a positive influence on the organization's ability to respond to the needs and wants of customers and develop relationships with customers (Johnson et al., 2012; Reinartz et al., 2004). Besides, the cooperation and information sharing among departments is expected to improve customer information systems (Johnson et al., 2012; Zahay & Peltier, 2008). Moreover, the integration of customer related activities by aligning all organizational activities around customer value-adding activities, positively influences customer centricity in organizations (Sheth et al, 2000). Based on the literature discussed above, we expect a positive relationship between alignment and customer centricity. Therefore, we hypothesize the following:

H4: An aligned organizational structure positively influences customer centricity.

Kathuria et al. (2007) found a positive influence of alignment on organizational performance. Besides, Eng (2006) investigated the relationship between cross-functional coordination and supply chain performance and found a positive relationship. Furthermore, the sharing of knowledge within an organization improves the learning orientation, and the performance of information systems in organizations, and in that way positively influences an organization’s performance (Calantone et al., 2002; Eng et al., 2006; Zahay and Peltier, 2008). Based on the literature described above, a positive relationship between alignment and both customer performance and organizational performance is expected. Therefore we hypothesize the following:

H5: An aligned organizational structure positively influences customer performance

H6: An aligned organizational structure positively influences organizational

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17 Customer integration can be defined as the coordination and collaboration with customers in product/service development, in order to successfully meet customers’ needs and wants (Flynn et al., 2010; Lamberti, 2013). A customer integrated organization structure is a structure that enables this dialogue between the organization and the customer. Customer integration leads to a better fulfilling of customers’ needs and wants, and therefore it is expected to lead to customer centricity in organizations (Lamberti, 2013). Besides, Fuchs and Schreier (2011) provide an insight in how customers perceive an organization that empowers its customers. In this, customer empowerment is concerned with keeping the customer’s interest in mind, monitoring customer’s preferences, and matching this preferences with the right product or service. Findings show that organizations are significantly perceived as better satisfying customer needs when they are empowering customers. Besides, customers might be incorrectly valuated when the organization does not engage them (Verhoef et al., 2010). In line with the literature described above, we hypothesize the following:

H7: A customer integrated organizational structure positively influences customer

centricity

Looking at prior work assessing the relationship between customer integration and performance, Swink et al. (2007) and Frohlich & Westbrook (2001) found that customer integration has a positive effect on both customer performance, and organizational performance. Using information regarding customer needs and wants to improve products and services is costly for organizations, but eventually increases performance through customer engagement value (Kumar et al., 2010; Fuchs & Schreier, 2011). This customer empowerment leads to strong behavioral intentions, which has a positive impact on purchase intentions and customer loyalty (Fuchs & Schreier, 2011). Following prior work on the relation between customer integration and customer and organizational performance we hypothesize the following:

H8: A customer integrated organizational structure positively influences customer

performance

H9: A customer integrated organizational structure positively influences

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18 Processes

Building on work in the field of CRM (Reinartz et al., 2004; Jayachandran et al., 2005; Payne & Frow, 2005; Peelen et al., 2009), we define customer-centric processes as the collection and use of customer information along all touch points, to create a single and comprehensive view of the customer, in order to build a profitable long-term relationship. In this study we make a distinction between the collection of customer information and the use of customer information. Through the collection of customer information along all touch points, an organization gains insights in the needs and wants of its individual customers, which enables an organization to act upon this (Lamberti, 2013). Besides, Chang et al. (2014) found that a CRM capability positively influences the interaction orientation of an organization. They state that in order to make customer related decisions, organizations should collect customer information. This is supported by Jayachandran et al. (2004). Organizations with a high level of customer knowledge generation are more successful in responding to the needs and wants of customers. Based on these findings described above, we hypothesize the following:

H10: The collection of customer information positively influences customer centricity

The use of customer information enables an organization to really act upon the collected customer information, in order to increase the interaction orientation of the organization, and build long-term relationships with customers (Peelen et al., 2009). Ramani and Kumar (2008) state that an interaction orientation can enhances customer relationships, by using stored customer information when interacting with customers. Besides, stored customer information can be used to effectively identify customers and provide a great customer experience (Peelen et al., 2009). Furthermore, Jayachandran et al. (2005) found a positive relationship between relational information processes and a customer-centric management system. In this relational information processes can be identified as the use of customer information in order to meet customers’’ needs and preferences. Based on the above, we hypothesize the following:

H11: The use of customer information positively influences customer centricity

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19 The study of Chang et al. (2014), provided similar results. They examined the influence of CRM relational information processes on both customer-based relational performance, and profit performance. They found support for the positive effect of CRM relational information processes on customer-based relational performance, evidence for a significant influence on customer-based profit performance is missing however. Based on the studies described above we expect that the collection of customer information, and the use of customer information positively influence both customer performance and organizational performance. Therefore we hypothesize the following:

H12: The collection of customer information positively influences customer

performance

H13: The use of customer information positively influences customer performance

H14: The collection of customer information positively influences organizational

performance

H15: The use of customer information positively influences organizational performance

Culture

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20 Furthermore, Peelen et al. (2009) found that the formulation of CRM in an organizations vision, together with the commitment of top management increases CRM success, which in turn increases customer centricity in organizations. Based on the research discussed above we expect a positive relationship between customer-centric organizational culture and customer centricity. Therefore, we hypothesize:

H16: A Customer-centric organizational culture positively influences customer

centricity.

Jayachandran et al. (2005) found that customer relationship orientation, which is entrenched in an organization’s culture, has a positive influence on relational information processes. Besides, Homburg and Pflesser (2000) found a positive relationship between customer oriented organizational culture and long term performance of organizations. Customer oriented cultures are more likely to achieve higher levels of customer satisfaction and customer loyalty. This proves that the right cultural foundations in organizations can influence the customer performance in organizations. Based on this we hypothesize:

H17: A Customer-centric organizational culture positively influences customer

performance.

Several studies proved a positive influence of organizational culture on organizational performance (e.g. Pinho et al., 2013; Rashid et al., 2003 and Flamholtz, 2001). Homburg and Pflesser (2000) found that firms with strong customer oriented organizational cultures have higher long term performances, which results in higher organizational performance. Besides, Iriana et al. (2013) found proof for a positive relationship between organizational culture and CRM financial outcomes. Furthermore, Peltier et al. (2013) found a positive relationship between organizational culture and organizational performance. Data quality functions as a mediator in this relationship. Following this literature, we hypothesize the following:

H18: A Customer-centric organizational culture positively influences organizational

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21 Customer Metrics

Traditional financial metrics are inadequate in relating marketing to performance outcomes, the use of customer metrics enabled this, and in that way increased the accountability of marketing (Rust et al., 2004). Customer performance metrics assess the strength of the relationships between an organization and its customers (Peltier et al., 2013). It include satisfaction and retention, cross-selling, share-of-wallet, CLV, and customer equity (Peltier et al., 2013). A focus on customer metrics motivates employees to act more customer-centric (Jaworski and Kohli, 1993; Srivastava et al., 1998). With the help of CRM processes, organizations can measure customer metrics and act on them, and in that way transform from a product centric, to a customer-centric organization (Verhoef et al., 2010 and Shah et al., 2006). The measurement of the customer metric Customer Lifetime Value (CLV), proved to increase customer centricity in organizations, since it helps organizations to select profitable customers (Gupta and Zeithaml, 2006) and effectively allocate the marketing budget of the organization (Berger et al. 2002). Furthermore, Ramani and Kumar (2008) found that focusing on customer metrics increases the interaction orientation of an organization. Locke et al. (1981) examined the relationship between goal setting and task performance, and found that 90% of tasks are executed better, when specific goals or objectives are in place. Therefore, regarding customer metrics, we make a distinction between the measurement of customer metrics and having objectives in terms of customer metrics. Based on the literature discussed above, we expect that both the measurement and having objectives in terms of customer metrics, increases customer centricity in organizations

H19: Measurement of customer metrics positively influences customer centricity.

H20: Organizational objectives in terms of customer metrics positively influences

customer centricity

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22 H21: Measurement of customer metrics positively influences customer performance.

customer performance

Focusing on customer metrics, increases the effective spending of an organizations’ marketing budget, and in that way enables organizations to cut costs (Gupta and Zeithaml, 2006). Furthermore, research shows that effective implementation of CRM processes (which generates information regarding customer metrics), positively influence organizational performance (Reinartz et al., 2004; Homburg et al., 2008; Ramani & Kumar 2008; Krasnikov, et al., 2009). Besides, Seddon et al. (2010) and Peltier et al. (2013) found that the gathering and use of data that correctly reflects the behavior and sentiments of customers, has a positive influence on organizational performance. Based on prior work discussed above we expect a positive relationship between both the measurement and having objective in terms of customer metrics and organizational performance. Therefore, we hypothesize the following:

H23: Measurement of customer metrics positively influences organizational

performance.

organizational performance

2.5 Consequences of customer centricity

As follows from the conceptual model in figure 1, we expect that customer centricity has a positive influence on both the customer performance and organizational performance of an organization. Customer centricity is expected to have a positive influence on customer performance, because customer-centric organizations have a better understanding of customers’ needs and wants, which leads to loyal customers (Shah et al., 2006). More extensively, customer-centric organizations are better capable in responding to explicit and hidden needs of customers, by generating and sharing customer information throughout the organization, translating this information into customized offers, and in that way improving the customer performance (Lamberti, 2013).

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23 Jayachandran et al. (2005), found that implementing a customer-centric management system, has an indirect positive influence on customer relationship performance, through relational information processes. Besides, Peelen et al. (2009) infer that a customer-centric strategy positively contributes to performance of CRM processes, however they found no positive relation between a customer-centric strategy and customer experience. Furthermore, Ramani & Kumar (2008), found that an interaction orientation, which is the organization’s ability to take advantage of interacting with and obtaining information from customers, has a positive influence on customer-based relational performance.

Prior work also found positive relationships between customer orientation and customer performance. Zhu & Nakata (2007) found that customer orientation (as one of the components of a market orientation) positively influences market performance (customer performance with the addition of market share). In line with this Brady & Cronin (2001) and Singh & Ranchhod (2004) ascertained a positive relation between customer orientation and respectively customer perceptions and customer retention. Prior work also focused on the relationship between CRM and customer performance. Mithas et al. (2005) and Reimann et al. (2010), found that CRM as a whole has a positive influence on customer satisfaction. Customer information processes are linked to customer performance as well. Zahay & Griffin (2004) and Chang et al. (2014) conclude that CRM information processes leads to a higher customer-based performance. Besides, several studies found positive relationships between CRM information processes and customer performance metrics like CLV and share of wallet (Berger & Nasr, 1998; Reinartz & Kumar, 2003). Based on prior literature on customer centricity and related concepts, we expect a positive relationship between customer centricity and customer performance. Therefore we hypothesize:

H25: Customer centricity positively influences customer performance.

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24 business performance. Besides, a relation is ascertained between CRM processes and business performance (Reinartz et al., 2004; Reimann et al., 2010). The underlying logic in this relationship is that organizations that successfully practice CRM processes, are better capable in selecting and investing in highly profitable customers, while neglecting unprofitable customers, and in that way improving business performance (Reinartz et al., 2004). Although the implications of CRM on organizational performance are not directly translatable to the implications of customer centricity on organizational performance, we expect a direct relationship between the two concepts. Therefore we hypothesize:

H26: Customer centricity positively influences organizational performance.

Regarding consequences of customer centricity we lastly expect that customer performance leads to a higher organizational performance. Numerous papers examined the effect of customer or market performance on organizational performance, and found a positive relationship between the two (e.g. Homburg & Pflesser, 2000; Zhu & Nakata, 2007; Ramani & Kumar, 2008; Peltier et al., 2013). Two underlying factors play a role in this relationship. Firstly, research shows that customer satisfaction is a good predictor of financial performance, because satisfied customers spend more and stay longer with a firm (e.g. Anderson & Sullivan, 1993; Behn & Riley, 1999; Banker et al., 2000). Besides, customer performance leads to a higher profitability, through declining acquisition costs and higher price tolerance of customers (Reichheld, 1996; Chang et al., 2014). Building on these studies, we hypothesize the following:

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3 METHODOLOGY

In this chapter, the methodology of this study will be discussed. First, the process of data collection is described in section 3.1. Subsequently, the development of the measurements of this research are explained in section 3.2. Finally, the processing and analysis of the data is described in section 3.3.

3.1 Data collection

This quantitative study uses an online survey to examine customer centricity, its antecedents, and consequences. The survey consists of a range of questions regarding: the extent to which organizations operate customer centrically, organizational structure, processes, culture, and metrics, and the customer performance and organizational performance of organizations. Besides, a range of questions were added to assess the control variables in our conceptual model. Together with the responsible committee of the PvKO (Platform van Klantgericht Ondernemen), the first version of the survey was critically assessed in multiple meetings. Based on the outcomes of these meetings the survey was improved. Then the survey was pre-tested by three contacts of the PvKO to assess the length of the survey and the phrasing of the questions, after which the survey was finalized. The survey is shown in appendix 1.

Contacts of the PvKO were used to compile a database of approximately 4000 marketing- and customer managers of Dutch organizations, with above 30 employees. The contacts in the database received an e-mail with an invitation to the survey. Alongside with the invitation a short introduction about the research and its importance was presented. To seduce contacts to fill in the survey, a compensation was offered. Respondents receive a management survey of the research, a benchmark in which their organization’s score on customer centricity is compared with other participating organizations, and an invitation to a PvKO seminar in which customer centricity and the results of the research will be presented.

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26 both. Lastly, the majority of respondents (71%) work at a location with less than 200 employees. Only 6,5 % of the respondents work at a location with a number of employees that exceeds 1000. When shifting the view from the number of employees on the location to the number of employees country wide, we ascertain that 16,8% of the respondents works for a large organization with a number of employees exceeding 1000 in the Netherlands. In contrast with this, approximately 50% of the respondents work for a company with a number of employees between 50 and 199 in the Netherlands.

3.2 Measurement of constructs

Where possible existing measurement scales were used, or adapted to fit our study. In some occasions own scales were composed, based on literature. After the collection of the data, factor analysis was used to develop our measurement scales. The factor analysis procedure is described below, followed by the development of the measurement scale per variable. The measurement scales of customer centricity, customer performance, organizational performance, environmental dynamism and competitive intensity, are shown in table 1, accompanied with factor loadings and Cronbach´s alpha values. The measurement scales of centralization, alignment, customer integration, collection of customer information, use of customer information, organizational culture, measurement of customer metrics and customer metrics objectives are adopted from Hempenius (2015) and Klaver (2015), and are presented in appendix 3. Besides, variables’ means, standard deviations and correlations are shown in appendix 4. This table demonstrates that the variables in our research are very coherent with each other, since exclusively significant correlations are found.

Factor analysis procedure

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27 of each factor should exceed 1, each factor individually should explain at least 5% of the total variance, all the factors together should account for minimal 60% of the total variance, and lastly, the items’ cross loadings in the rotated component matrix may not exceed 0.3. The item factor loadings are rotated with Varimax rotation with Kaiser Normalization, which makes the factor analysis solution easier to interpret (Malhotra, 2009). When all these requirements are met, and the factor analysis solution makes logical sense, Cronbach’s alpha analysis is done to test the reliability of the scale. A scale can be considered as reliable, when the score on Cronbach’s alpha analysis is, equal to, or exceeds 0.6 (Malhotra, 2009).

Customer Centricity

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28 Factor analysis customer centricity

The factor analysis of customer centricity resulted in a KMO of 0.5 and a significant Bartlett’s test of Sphericity. Subsequently, both items have a communality of 0.726, which is sufficient. The analysis resulted in a 1 factor solution explaining 72,6% of the variance in the data. The loadings of the items on the factor are shown in table 1. A Cronbach’s alpha analysis is conducted on this two item scale, to test whether the scale is reliable. This resulted in a value of 0.609, which is sufficient since it is above 0.6.

Customer performance

The customer performance measurement scale is largely based on the market performance scale of Homburg & Pflesser (2000). The market share item of this scale was removed (since this item indicates organizational performance instead of customer performance), and cross- and upsell (Peltier et al., 2013) and net promoter score (Reichheld, 2003) were added to this scale. Customer performance is assessed in comparison to the main competitor, in comparison to last year, and in comparison to the organization’s ambitions. This is done to be able to compare the firms’ evaluations of customer performance and to see which variant delivers the best model fit in regression analysis, which is further discussed in chapter 4.

Factor analysis customer performance in comparison to the main competitor

To develop the three measurement scales for customer performance, we directed the factor analysis to compute a factor analysis solution of one factor, because we expect that the items in the analysis have only one underlying dimension. The factor analysis for customer performance in comparison to the main competitor, resulted in a KMO measure of 0,800 and a significant Bartlett’s Test of Sphericity, demonstrating that factor analysis is appropriate for these items. Based on a communality value of 0,350 (<0.5) we eliminated ‘customer acquisition’ and ran factor analysis again. This time ‘cross and upsell’ had a communality value of 0,429, and was therefore removed. The third factor analysis incorporated 4 items, which all had a communality value above 0.5. The analysis resulted in a one factor solution explaining 73,3 % of the variance, the loadings of the items are shown in table 1. Cronbach’s alpha analysis on the items in this factor resulted in a sufficient value of 0,873.

Factor analysis customer performance in comparison to last year

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29 appropriate, since the KMO measure was 0,812 and Bartlett’s Test of Sphericity was significant. Based on the communalities none of the items had to be removed, since the communality of each item was above 0,5. The factor analysis resulted in a one factor solution, explaining a sufficient 61,2% of the variance. The loadings of the items on this factor are represented in table 1, alongside with the result of Cronbach’s alpha analysis, which was 0,871.

Factor analysis customer performance in comparison to the ambitions

We ran a factor analysis searching for one factor, incorporating the six items of customer performance in comparison to the ambitions. A KMO measure of 0,842 and a significant Bartlett’s test of Sphericity proved that factor analysis was appropriate. All the communalities were above 0,5 so none of the items had to be removed from the factor analysis. The one factor solution accounted for 69,1% of the variance in the model, with factor loadings shown in table 1. The outcome of Cronbach’s alpha analysis was 0,909, which proves that the scale is reliable.

Organizational performance

The organizational performance scale is adopted from Brockman et al. (2012). The items ‘sales growth’ and ‘market share growth’ in this scale, were revised to ‘sales’ and ‘market share’. For the same reason as the customer performance scales, organizational performance is assessed in comparison to the firms’ main competitor, in comparison to last year, and in comparison to the firms’ ambitions.

Factor analysis organizational performance in comparison to the main competitor

In line with the factor analysis of the customer performance scales, we directed the analysis to search for a one factor solution. Factor analysis for the items of organizational performance in comparison to the main competitor resulted in a KMO measure of 0,827 and a significant Bartlett’s test of Sphericity. All the communalities complied to the requirement of >0,5. The factor analysis resulted in a 1 factor solution explaining 72% of the variance. The items’ loadings on this factor are represented in table 1. Cronbach’s alpha analysis resulted in a score of 0,920.

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30 The factor analysis for this variant of organizational performance resulted in a KMO measure of 0,820 and a Bartlett’s Test of Sphericity, proving the appropriateness of the factor analysis. All the communalities were above 0,5, so none of the items had to be removed from factor analysis. The 1 factor solution explained 81% of the variance in the items. The loadings of the items on the factor are shown in table 1. Cronbach’s alpha analysis resulted in a score of 0,952.

Factor analysis organizational performance in comparison to the ambitions

Factor analysis for the last variant of organizational performance resulted in a KMO measure of 0,821 and a significant Bartlett’s Test of Sphericity. The communalities were all above 0,5, and the 1 factor solution accounted for 77,9% of the variance. The items’ loading on the factor are represented in table 1. Cronbach’s alpha analysis resulted in a score of 0,942.

Control variables

Questions regarding five control variables were added to the survey. These were firm size, industry, B2B/B2C, environmental dynamism and competitive intensity. The measurement scales of firm size, industry and B2B/B2C are provided by the Dutch company and PvKO member MarketResponse and are shown in appendix 1. The reflective measurement scale for environmental dynamism is adopted from Jayachandran et al. (2005), two items were added to this scale. The measurement scale for competitive intensity is adopted from Jayachandran et al. (2005) as well.

Factor analysis environmental dynamism

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31 revealed that one of the factors had only one item loading on that factor, namely: ‘In our industry, governmental regulation has a big influence on how we can shape our offerings’. A factor with only one item is too weak to be considered a factor, and therefore the only item loading on that factor was removed and factor analysis was ran again. This factor analysis resulted in item communalities above 0,5, and a one factor solution explaining 69,5% of the variance. The loadings of the items on this factor are shown in table 1, alongside with the result of Cronbach’s alpha analysis, which was 0,853.

Factor analysis competitive intensity

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32

Table 1: Measurement of constructs

Construct Item Reference Cronbach’s

α

Loading

Customer centricity

We use information of individual customers to serve the needs and wants of customers.

Sheth et al., 2000

0.609

0.852

Information of individual customers is used as a starting point in decision making throughout the organization.

Wagner & Majchrzak,

2007 0.852 Customer performance (in comparison to main competitor) Customer satisfaction

Homburg & Pflesser, 2000 0.873 0.889 Customer retention 0.872 Customer acquisition* - Customer equity 0.726

Net promoter score (NPS) Based on Reichheld

(2003). 0.923

Cross- and upsell* Peltier et al., 2013 -

Organizational performance (in comparison to main

competitor)

Return on investments (ROI)

Brockman et al., 2012 0.920

0.861

Return on equity (ROE) 0.893

Net profit margin 0.840

Return on assets (ROA) 0.915

Turnover 0.829 Market share 0.743 Customer performance (in comparison to last year) Customer satisfaction

Homburg & Pflesser, 2000 0.871 0.782 Customer retention 0.780 Customer acquisition 0.763 Customer equity 0.778

Net promotor score (NPS) Based on Reichheld

(2003). 0.873

Cross- and upsell Peltier et al., 2013 0.710

Organizational performance (in comparison

to last year)

Brockman et al., 2012 0.952

0.928

Return on equity (ROE) 0.939

Turnover 0.877 Market share 0.816 Customer performance (in comparison to ambitions) Customer satisfaction

Homburg & Pflesser, 2000 0.909 0.809 Customer retention 0.803 Customer acquisition 0.800 Customer equity 0.839

Net promoter score (NPS) Based on Reichheld

(2003). 0.862

Cross- and upsell Peltier et al., 2013 0.846

Organizational performance

Brockman et al., 2012 0.942 0.892

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33

(in comparison to ambitions)

Turnover 0.821

Market share 0.843

Environmental dynamism

In our business, customers’ preferences change rapidly.

Jayachandran et al., 2005

0.853

0.771 The composition of the target

group in our industry is changing rapidly.*

Based on

- We are witnessing demand

for our products and services from customer groups who never bought them before.*

Jayachandran et al.,

2005 -

The technology in our industry is changing rapidly.

0.893 Technological changes

provide big opportunities in our industry.

0.817 In our industry, governmental

regulation has a big influence on how we can shape our offerings.*

Based on Wells et al.,

2013 -

A large number of new product ideas have been made possible through technological breakthroughs in our industry. Jayachandran et al., 2005 0.849 Competitive intensity

Competition in our business is cut throat.

Jayachandran et al.,

2005 0.900

0.929 We are in a business with

very aggressive competitors. 0.904

Price competition in this

business is severe. 0.907

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34

3.3 Data preparation and data analysis

All the analyses are performed with IBM SPSS. Before running analyses, the dataset was checked for outliers, straight liners and other errors. This resulted in the removal of 7 cases, resulting in a dataset of 155 respondents. After that, dummy variables for the control variables were coded, to enable regression analysis with these control variables. Subsequently, as described above, factor analysis and Cronbach’s alpha analysis was conducted to arrive at reliable measurement scales for the variables in the conceptual model. After that the significance of the control variables was tested, to assess which control variables should be included in the regression analyses. This is discussed below. Subsequently, the econometric models that are assessed to test our hypotheses are described.

Estimating the significance of control variables

To judge which control variables should be included in the regression analysis that test our hypotheses, we assessed the relationship between the control variables and the dependent variables (i.e. customer centricity, customer performance and organizational performance), excluding the other variables in our conceptual model. To accomplish this, we created dummy variables for the control variables, and ran multiple regression analysis afterwards. The results are shown in appendix 5. Based on the result we conclude that when assessing organizational performance in comparison to the main competitor, construction industry should be included in the regression, and when assessing organizational performance in comparison to the ambitions, construction industry, health and welfare industry, and sport culture and tourism industry should be included in the regression.

Econometric models

After the completion of the measurement scales for the constructs in our conceptual model, and verifying which control variables have a significant influence on our dependent variables, the relationship between the variables in our conceptual model can be assessed with multiple regression analysis. Based on the model fit (R2_{) of the regression results we decide which}

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35

Model 1 - H1,4,7,10,11,16,19,20:

CCi = ∝ + β1SCi + β2SAi + β3SIi + β4PCi + β5PUi + β6Ci + β7MRi + β8MOi + ε

Model 2 - H2,5,8,12,13,17,21,22,25:

CPcomi = ∝ + β1SCi + β2SAi + β3SIi + β4PCi + β5PUi + β6Ci + β7MRi + β8MOi + β9CCi + ε

Model 3 - H2,5,8,12,13,17,21,22,25:

CPyri = ∝ + β1SCi + β2SAi + β3SIi + β4PCi + β5PUi + β6Ci + β7MRi + β8MOi + β9CCi + ε

Model 4 - H2,5,8,12,13,17,21,22,25:

CPambi = ∝ + β1SCi + β2SAi + β3SIi + β4PCi + β5PUi + β6Ci + β7MRi + β8MOi + β9CCi +

ε

Model 5 – H3,6,9,14,15,18,23,24,26,27:

OPcomi = ∝ + β1SCi + β2SAi + β3SIi + β4PCi + β5PUi + β6Ci + β7MRi + β8MOi + β9CCi +

β10CC*SCi + β11CPcomi + β12CIi + ε

Model 6 – H3,6,9,14,15,18,23,24,26,27:

OPyri = ∝ + β1SCi + β2SAi + β3SIi + β4PCi + β5PUi + β6Ci + β7MRi + β8MOi + β9CCi +

β10CC*SCi + β11CPyri + ε

Model 7 – H3,6,9,14,15,18,23,24,26,27:

OPambi = ∝ + β1SCi + β2SAi + β3SIi + β4PCi + β5PUi + β6Ci + β7MRi + β8MOi + β9CCi +

β10CC*SCi + β11CPambi + β12CIi + β13HWIi + β14SCTIi + ε

The meaning of the abbreviations is given below:

SC: Structure - Centralization SA: Structure - Alignment

SI: Structure – Customer integration

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36 MR: Measurement of customer metrics

MO: Objectives in terms of customer metrics CC: Customer centricity

CPcom: Customer performance in comparison to the most important competitor CPyr: Customer performance in comparison to last year

CPamb: Customer performance in comparison to the ambitions

OPcom: Organizational performance in comparison to the most important competitor OPyr: Organizational performance in comparison to last year

OPamb: Organizational performance in comparison to the ambitions CI: Construction industry

HWI: Health/welfare industry

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37

4 RESULTS

In this chapter the results of this study are presented. First, in section 4.1, the difference in model fit among the three variants of customer and organizational performance are discussed. Then, in section 4.2, we present the multiple regression results regarding customer centricity. In section 4.3 the multiple regression results regarding customer performance are shown, followed by the multiple regression results regarding organizational performance in section 4.4. Lastly, the mediating role of customer centricity and customer performance is discussed in section 4.5.

4.1 Model fit

As mentioned earlier, respondents rated their customer performance and organizational performance in comparison to their main competitor, in comparison to last year, and in comparison to their ambitions. In table 2 the regression model fit for the three variants of customer performance and organizational performance are presented (model 2-7). Based on the R2 and adjusted R2 values we can conclude that the variant that measures customer performance and organizational performance in comparison to the ambitions (model 4 and 7) provides the strongest regression models to base our results on. Therefore, the results of this study are bases on this variant of customer and organizational performance. From here, we consider ‘customer performance in comparison to the ambitions’ and ‘organizational performance in comparison to the ambitions’ as ‘customer performance’ and ‘organizational performance’.

Table 2: Model fit

In comparison to main competitor In comparison to last year In comparison to the ambitions

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38

4.2 Customer centricity

Main effects

The regression results for Model 1, 4 and 7 are shown in table 3. Model 1 assessed the relationships between customer centricity and its antecedents. H1 hypothesizes a negative

relation between a centralized organizational structure and customer centricity, and is not supported (p < .10). A centralized organizational structure does not decrease customer centricity. H4 hypothesizes a positive relationship between an aligned organizational structure

and customer centricity, and is supported (β = .173; p < .10). This means that alignment increases customer centricity. H7is supported as well (β = .303; p < .01), confirming that a

customer integrated organizational structure increases customer centricity. H10 and H11

hypothesize a positive association between both the collection of customer information and the use of customer information and customer centricity, but are not supported (p > .10).

Table 3: Regression results (standardized coefficients)

Model 1 (CC) Model 4 (CP) Model 7 (OP)

Main variables Hyp. S.C. Hyp. S.C. Hyp. S.C

Centralization 1(-) .055 2(-) .068 -.059

Alignment 4(+) .173c 5(+) .181c 6(+) -.074

Customer integration 7(+) .303a ₈₍₊₎ _.321b ₉₍₊₎ _.024

Collection of customer information 10(+) -.046 12(+) .019 14(+) .158b

Use of customer information 11(+) .095 13(+) .103 15(+) .028 Organizational culture 16(+) .131 17(+) .027 18(+) -.020 Measurement of customer metrics 19(+) .019 21(+) .048 23(+) .144c Objectives in terms of customer metrics 20(+) .120 22(+) .073 24(+) -.095

Customer centricity 25(+) -.043 26(+) -.32

Customer performance 27(+) .693a

Moderators

Customer centricity * Centralization 3(-) -.036

Control variables Construction industry -.087 Health/welfare industry -.020 Sports/culture/tourism industry .021 R2 (Adjusted R2) .379 (.344) .331 (.290) .551 (.506) F-value (Sig.) 11.116 (.000) 7.988 (.000) 12.276 (.000)

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39 The collection and the use of customer information do not improve customer centricity. H16

hypothesizes a positive relationship between customer-centric organizational culture and customer centricity, this hypothesis is not supported (p > .10). This means that a customer-centric organizational culture does not improve customer customer-centricity. Lastly, H19 and H20

hypothesize that the measurement of customer metrics and objectives in terms of customer metrics increases customer centricity. Both hypotheses are rejected (p > .10), which means that measuring and having objectives in terms of customer metrics do not improve customer centricity in an organization. An overview of the supported and rejected hypothesis in regards to model 1 are shown in table 4.

Table 4: Hypotheses customer centricity

Hypothesis Result

H1: A centralized organizational structure negatively influences customer centricity Not supported

H4: An aligned organizational structure positively influences customer centricity Supported

H7: A customer integrated organizational structure positively influences customer

centricity

Supported

H10: The collection of customer information positively influences customer

centricity

Not supported

H11: The use of customer information positively influences customer centricity Not supported

H16: A customer-centric organizational culture positively influences customer

centricity

Not supported

H19: The measurement of customer metrics positively influences customer

centricity

Not supported

H20: Objectives in terms of customer metrics positively influences customer

centricity

Not supported

4.3 Customer performance

Main effects

Table 3 shows the regression results for model 4. Model 4 assessed the relationships between customer centricity, its antecedents, and customer performance. H2 hypothesizes a negative

relationship between centralization and customer performance, but is not supported (p > .10). This means that a centralized organizational structure does not decrease customer performance. H5 hypothesizes a positive relationship between alignment and customer

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40 structure does increase customer performance. There is also support for H8 (β = .321; p < .05),

confirming that a customer integrated organizational structure increases customer performance. H12 and H13 hypothesizes a positive association between respectively the

collection of customer information and the use of customer information, and customer performance. Both hypotheses are not supported (p > .10). The collection and use of customer information does not increase customer performance. Furthermore, there is no support for H17

(p > .10), hypothesizing that customer-centric organizational culture has a positive influence on customer performance. Besides, H21 and H22 are not supported. Both the measurement and

objectives in terms customer metrics, do not positively influence customer performance. Lastly, H25 hypothesizes that customer centricity increases customer performance. This

hypothesis is not supported (p > .10). Customer centricity does not lead to higher customer performance. Table 5 gives an overview of the supported and rejected hypotheses of model 4.

Table 5: Hypotheses customer performance

Hypothesis Result

H2: A centralized organizational structure negatively influences customer

performance.

Not supported

H5: An aligned organizational structure positively influences customer

performance.

Supported

H8: A customer integrated organizational structure positively influences customer

performance.

Supported

H12: The collection of customer information positively influences customer

performance

Not supported

H13: The use of customer information positively influences customer performance. Not supported

H17: A customer-centric organizational structure positively influences customer

performance.

Not supported

H21: The measurement of customer metrics positively influences customer

performance.

Not supported

H22: Organizational objectives in terms of customer metrics positively influences

customer performance.

Not supported

Customer Centricity: Antecedents and Consequences

ustomer Centricity:

Antecedents and consequences

. GEERTS

January 2015

Customer Centricity:

Antecedents and Consequences

T. GEERTS

Customer Centricity:

Antecedents and Consequences

by

TOMAS GEERTS

University of Groningen

Faculty of Economics and Business

MSc Marketing

January, 12, 2015

PREFACE

MANAGEMENT SUMMARY

TABLE OF CONTENTS

1

INTRODUCTION

2

THEORETICAL FRAMEWORK

3

METHODOLOGY

4

RESULTS