Abstract
Keywords
Introduction
Results
Conclusions
References

Cultivating high quality relationships with customers is of paramount importance in the banking sector. However, there has been little effort to examine relationship quality (RQ) in financial services, and though the evaluation of RQ should depend on the experience provided, empirical evidence on how customer experience may contribute to RQ is scant. Therefore, based on data collected from 227 retail banking clients, analysed using PLS-SEM, the purpose of this study is to understand the role played by customer experience on RQ in retail banking, and its impact on relational outcomes, comparing customers with and without a dedicated account manager.

Introduction

Owing to the intangibility, long-term delivery and complexity of financial services (FS), also characterized by considerable uncertainty (Ponsignon et al., 2015), cultivating high quality relationships with customers is of paramount importance (Ndubisi, 2007; O’Loughlin et al., 2004), particularly in an age of increased depersonalization, homogenization and automation in the industry (Barari and Furrer, 2018; Rajaobelina and Bergeron, 2009). A strong relationship is an intangible asset not easily duplicated by competitors (Wong et al., 2007) that reflects the psychological connection that customers have with a service provider (e.g. Crosby et al., 1990; DeWulf et al., 2001). Relationship Quality (RQ) has been defined as “the degree of appropriateness of a relationship to fulfil the needs of the customer” (HennigThurau and Klee, 1997, p.751), and it means that the customer is able to trust and rely on providers integrity because the level of past performance has consistently been satisfactory (So et al., 2016). Numerous authors (e.g. Roberts et al., 2003; Grégoire and Fisher, 2006; Wu and Li, 2011) have acknowledged that maintaining high quality relationships fosters loyalty-related outcomes, such as customers’ willingness to provide referrals and to pay a price premium. Therefore, according to Hennig-Thurau et al. (2002), the RQ approach is among the most expressive ones in modelling the determinants of relationship marketing outcomes. Because of the lack of concreteness of service outcomes high in credence qualities, functional attributes associated with customer experience (i.e. how the service is delivered), such as accessibility, professionalism, and empathy of FS providers, are likely to heavily contribute to consumer’s evaluation of their relationship with the bank (Eisingerich and Bell, 2007; Roy, 2018). In fact, although the banking industry is identified as “weak experiential” and goal oriented, “process” factors are pivotal to the service experience provided by a bank (O’Loughlin et al., 2004), and may play a more dominant role than technical, outcome-based factors, intrinsically difficult for customers to evaluate (Bell and Eisingerich, 2007).

1- Introduction

2- Conceptual background

3- Research model and hypotheses development

4- Methods

5- Data analysis and findings

6- Discussion

7- Implications to research and practice

8- Conclusions, limitations and future directions

References

Abstract

Increased use of smart technologies by customers is leading to recognition of their influence on the shopping experiences of customers by practitioners. However, the academic literature fails to acknowledge the influence of smart technology usage, combined with behavioural intention of the customer, on the dynamics and experience of customers. This research utilises explanatory research at the preliminary stage to examine this phenomenon in a retail setting. A conceptual framework was created, based on the scholarly knowledge available in extant literature, and was tested using a survey of a convenience sample of 330 consumers shopping in a high-end retail store in London, United Kingdom. Structural Equation Modelling (SEM) via AMOS was employed to test the proposed model. This study contributes to technology adoption based consumer behaviour literature, by explaining the ability of learning commitment to drive the participation of an individual, but its inability to influence their behavioural intention. Findings of this research also reflect on the role of customer dynamics and customer experience in embracing innovative application of smart technologies in a retail setting. The results and implications included in our study also contribute to the understanding of the determinants that affect customer dynamics and customer experience when making use of smart technologies.

Introduction

The rapid proliferation and use of smart technologies (e.g. smart mobile phones, tablets, wearables etc.), which was once predominantly a trend amongst the younger generation, is becoming widely accepted by all parts of society (Grewal et al., 2017). In this context, a technology is referred to as ‘smart’ when it is an electronic device or system that can be connected to the internet and used interactively. With society having turned more tech- and internet-savvy (Immonen and Sintonen, 2015), people now have the chance to experience efficient services provided by organisations. This trend has resulted in consumers expecting targeted, more responsive, and equally efficient services from retailers and other businesses. Retailers have embraced the concept of customer experience management, with many incorporating the notion into their business mission statements. Equally, retailers around the globe, including Europe, are aware of the new possibilities that smart technologies have to offer in their retail environment (e.g. Smart Labels and Unique Identifiers, NFC payments) and have started exploring them (Pantano, 2014). According to Barthel et al. (2015), one of the key drivers in retail is an increasing demand for a seamless experience between online, mobile and in-store shopping. The creation of a superior customer experience is asserted to be one of the pivotal objectives in retailing environments whether it be offline (Verhoef et al., 2009) or online (Chang et al., 2016). According to a report by McKinsey, these disruptive technologies are forecast to have a $6.2 trillion effect on the world economy by 2025 and one of the key industries that this will impact will be retail (Manyika et al., 2013). However, the possibilities are far more than simply introducing or making use of new technologies, as this phenomenon in the retail environment has opened up challenges and opportunities at the same time for the retailers (Grewal et al., 2017). Therefore, it is important that the retailers assess the real value and the changes that the use of smart technologies can have on consumer dynamics and creating a new customer shopping experience, based on all the interactions and thoughts about the business (Verhoef et al., 2009; Oh et al., 2007).

This paper presents an investigation on the current market conditions in sales based in the automotive industry and a new approache triggered by the digitization in this industry. Various studies prove that the behavior of the customers has changed drastically. By this customer experience, management becomes a central strategy in the digital age to reach long-term customer loyalty and enterprise growth. It is therefore necessary to adapt the function of the car dealers and, in general, innovative sales formats and technologies for communication with the customer. This paper describes how Daimler AG is reacting to these market changes with the concept of “Mercedes Me”.

Introduction

In the past few years, digitalization has changed our everyday lives enormously. It affects the way we communicate, our leisure time, our buying habits, the way we acquire information and many other issues. Various industries are also being revolutionized by this current trend. Dr. Dieter Zetsche, Chairman of the Board of Management of Daimler AG and Head of Mercedes‑Benz Cars states: “We are transitioning from car manufacturer to networked mobility provider, whereby the focus is always on the individual – as customer and employee.” (Daimler AG 2016) The sales department plays a significant role in this turnaround as this area is closely linked to the customer. It is no longer sufficient to stand out from the competition through innovative technologies, the product quality, the price or the quality of the service. The attention is more and more paid on the customer. The aim of the present work is to investigate the current market conditions in sales based on the digitalization and, in the next step, to examine whether and how these aspects are practically applied at one of the world’s largest automobile manufacturers, Daimler AG. In the following chapter, the current management approach ‘customer experience management’ is picked up and the present changes in customer behaviour triggered by the digitalization are revealed. Chapter three then analyses the practical application at Daimler AG. The elaboration is concluded with a summary and an outlook.

Drawing on social exchange theory (SET), this research explores customer engagement (CE) as a firm-initiated resource. Based on interviews with 41 managers from 34 companies, a five-facet, strategic customer engagement marketing (CEM) decision making framework emerges. CE Conceptualization differentiates between behavioral and psychological engagement. CE Target refers to who is engaged with the firm through CE (end-users or intermediaries such as retailers or distributors). CE Domain distinguishes between online and offline contexts. CE Experiential Routes differentiates absorption (controlled by the firm) from appropriation (controlled or transformed by the customer). Finally, CE Value demarcates customer interactional value from customer multiplier value. The decision options identified for each facet are interrelated and firms are advised to follow an integrative approach to CEM. However, acknowledging SET’s emphasis on cost-benefit ratios and opportunity costs, suggestions for potential moderators to the CEM framework are provided.

Introduction

Engagement has been recognized as an important and meaningful concept in organizational behavior, marketing, social psychology, and education. For example, Kahn (1990) investigates the effects of engaged employees, and Fredricks, Blumenfeld, and Paris (2004) describe how students engage with schools. Academic and managerial interest in customer engagement (CE) is considerable (Hollebeek, Srivastava, & Chen, 2017), increasing (Roy, Balaji, Soutar, Lassar, & Roy, 2018), and expected to persist (Beckers, van Doorn, & Verhoef, 2018). Marketing practitioners expect increased brand equity, sales, and profits from truly engaged customers. For example, a recent study from Rosetta Consulting (2014) shows that highly engaged consumers spend 60% more in each transaction, make 90% more frequent purchases, and are four times more likely to advocate for the brand. Marketing academics emphasize CE’s potential to develop relationships with customers beyond monetary transactions (Venkatesan, 2017) and achieve sustainable competitive advantage (Kumar & Pansari, 2016). Extant research has made important contributions through defining CE (e.g., Brodie, Hollebeek, Jurić, & Ilić, 2011; Hollebeek, 2011a; Mollen & Wilson, 2010; van Doorn et al., 2010; Vivek, Beatty, & Morgan, 2012) and investigating its valence and dimensions (e.g., Dessart, Veloutsou, & Morgan-Thomas, 2016; Hollebeek, Glynn, & Brodie, 2014; van Doorn et al., 2010; Vivek, Beatty, Dalela, & Morgan, 2014). However, two issues have not been addressed sufficiently by the extant literature. First, while prior research examines the psychological mechanisms that drive CE (compare, e.g., Harmeling, Moffett, Arnold, & Carlson, 2017; Pansari & Kumar, 2017), CE as a strategic company resource remains unexplored. Second, existing interpretative research investigating CE from a managerial perspective that incorporates the “voice of the firm” is rare (for exceptions, see Hollebeek, 2016; Hollebeek et al., 2017; Vivek et al., 2012), and managerial implications are predominantly deduced from consumer-based research. Viewing CE as a firm-initiated resource is important because organizations typically take the initiative to engage the customer (Vivek et al., 2012), and firms should proactively manage the CE experience (Calder, Hollebeek, & Malthouse, 2018; Lemon & Verhoef, 2016; van Doorn et al., 2010).

Postmodernism stresses the importance of experience in the theory foundation (Addis & Podestà, 2005). The interaction between the consumer and the product is at the heart of the real experience of consumption. This interaction seems to be under-estimated by researchers. By and large, the experiential view aimed at revising the models and the tools in order to improve adherence to reality. It is, in fact, through studying the consumption behavior of hedonistic products (though not strictly “rational”) that the concept of experience is defined (Carù & Cova, 2003a, 2003b). In postmodernity, marketing has to involve the consumer by considering him/her as the producer of experiences (Cova, 1996). In this case, the excerpt from Cova (1996) aptly exposes the fundamental ideas: “It was a fundamental shift in the role and purpose of marketing: from manipulation of the consumer to genuine customer involvement, from telling and selling to experiencing and sharing knowledge and emotions. This approach will help customers gain the status of being in control of constructing their world” (p. 2). Therefore, the individual does not wish to be different any more by what he buys but by what he lives (Cinotti, 2007). For the consumer, consumption is an act of production of experiences, identities or images of itself and not a fact of destruction (Cinotti, 2007; Filser, 2002). From the experiential perspective, the people are involved in building up and reinforcing their identities (Badot & Cova, 2003; Carù & Cova, 2007; Cova & Cova, 2001; Cova & Cova, 2009). This approach is phenomenological in the spirit and it considers the consumption as a subjective state of consciousness with different layers of symbolic meanings, hedonic answers and an esthetic criterion. Hence, Addis and Holbrook (2001) presented the experiential consumption as a result of the explosion (disintegration) of subjectivity. “THE LIVED” becomes the most important element to integrate an emotional consumer, in search of sensitive experiences resulting from the interaction with products or services of the system of consumption (Maffesoli, 1990). Consequently, Carù and Cova (2006) stressed that: “there is an ‘incorporation’ of meanings under the shape of experiences, in other words individual staging where the accent is put on the sensualist and the importance of the lived” (p. 100). This incorporation of meaning constitutes a rich source of experiential knowledge as it is innovative and enriching. It tends to recognize the knowledge-based innovation or innovation as knowledge based focusing on the knowledge content of an innovation while clarifying the role of knowledge in the process of innovation (Quintane, Casselman, Reiche, & Nylund, 2011). According to literature review, knowledge is a pre-requisite for the innovation to occur (Murovec & Prodan, 2009; Quintane et al., 2011). In the light of the present paper, the innovation results from the knowledge exchange (Nonaka & Takeuchi, 1995). Therefore, this research adopts the view of innovation as an outcome while integrating the knowledge perspective (Quintane et al., 2011).

From past some years ,the biggest challenge companies are facing in this area with massive data is translation of business to models. Since it is just an evolving area, it is difficult even to define a problem thoroughly for example non technical staff can’t communicate the problem definition to the technical data scientists 1 . A large amount of data is produced from structured, semi structured and unstructured sources which makes it very difficult to manage information about customers usage. Mainly it’s the need of big Shopping giants like Amazon and Flipkart to process huge amount of data so as to process massive datasets to find hidden patterns. These data have to be extracted ,transformed and loaded to study patterns related to customer behavior and their interactions. Companies can improve the overall performance by using the customer feedbacks .Survey results from big data show them where they stand today in the competitive market. Crowd sourcing is an idea which is different from Big Data, crowdsourcing projects have shown the potential of using a wide group of real people to collect useful and accurate data 2 . To begin with, there cannot be reliable data management without some human involvement to check for errors and the administrators can easily make their own mistakes and put their own subjective slant on the filing of information 2 . Big data companies need crowdsourcing in their operations to ensure objectivity and diversity, prevent against errors more effectively and let social trends play a part in data examination. This combination of big data and crowdsourcing provides a way to modern data collection for customer experiences to make information more valuable, authentic and manageable. Big benefits can be reaped by pairing up crowdsourcing with big data.

مقاله سال 2016

In late 2013, Amazon introduced Mayday, a singleclick video chat solution that allows customers to interact with a remote tech support representative to solve problems with their tablets 24/7. The service allows customers to see the tech support person in a small window while the support person can watch what the customer is doing online and can interact with the device. According to Amazon CEO Jeff Bezos, it is ‘‘actually very similar to having someone next to you’’ offering tech support (Biggs, 2013). Solutions such as Mayday–—which provide the customer with real-time, personalized support through a remote expert–—have the potential to significantly shape how customer service is delivered going forward. With Mayday, Amazon has been able to beat its response time goal of 15 seconds or less with an average response time of 9.75 seconds (Shaul, 2014).

The Mayday example illustrates the potential for today’s immersive digital technologies to transform the customer experience by delivering real-time, context-specific expertise when and where the customer needs it. We define the crisis of immediacy as the need for consumers to receive content, expertise, and personalized solutions in real time during their shopping experience. We are living in the age of the informed consumer; because consumers are comfortable with using self-service technologies, they are much better informed today about the products and services they intend to purchase. According to HubSpot (2011), 89% of U.S. Internet users search online before making a purchase, even when the actual purchase processitself is conducted at a local business. Therefore, consumers are expecting higher levels of service from the retailer throughout their purchase journey. Roughly 50% of U.S. online consumers will abandon their purchase if they cannot get quick answers to their questions (Leggett, Schoeller, Band, & Bookstein, 2013).

Customers are increasingly becoming omnichannelshoppers, using multiple channels–—such as physical stores, websites, social platforms, and mobile apps–—to conduct a single transaction. It is estimated that 86% of global shoppers and 65% of U.S.-based shoppers currently shop across at least two channels (McPartlin & Dugal, 2012). Furthermore, online shoppers are spending more (Maxwell, 2013) and are more profitable (Graeber, 2013) when they use multiple channels.

مقاله سال 2016

 مجله تحقیقات بازاریابی – Journal of Business Research

Some studies present innovation and marketing as the two aspects central to the organizations’ ability to gain capital in a competitive market (Ngo & O’Cass, 2013; Nguyen, Yu, Melewar, & Gupta, 2016). Incidentally, retailers around the globe, including Europe, are aware of the new possibilities that innovation (e.g., Smart Labels and Unique Identifiers, and NFC payments) can offer in a retail environment. However, the change goes beyond simply introducing or making use of innovation, as this phenomenon creates both challenges and marketing opportunities for corporations. Marketers get favorable reputations to allow stakeholders to form positive perceptions about the corporation and thus, to retain customer loyalty (Chun, 2005). In this sense, the academic literature reports the capability of innovation to drive company reputation and customer loyalty (Gupta & Malhotra, 2013) and reflects on reputation as collective judgments that observers make according to their evaluation of the corporation’s ability to be innovative (Foroudi, Melewar, & Gupta, 2014). Balmer, Powell, and Greyser (2011) add that corporate reputation is the result of beliefs, images, facts, and experiences that an individual may encounter over time. Consumers perceive a company as trustworthy and respectful because of their experience with the company, its products and services, and their corporate reputation (Bhattacharya & Sen, 2003). These behaviors can affect the likelihood of customers’ identification with different demographic features and with the organization.

Socio-technical system theory classifies the innovation capability of companies into two categories: (1) technical innovation capability (development of new services, service operations, and technology) and (2) non-technical innovation capability (managerial, market, and marketing) (Ngo & O’Cass, 2013). According to Ngo and O’Cass (2013), the literature pays much attention to technical innovation whereas nontechnical innovation, such as management, sales, and marketing, has received little attention to date. Few studies focus on the specific experiences that favorably affect consumers’ affective and cognitive reactions (Dennis, Brakus, Gupta, & Alamanos, 2014). To fill this gap and using theory of complexity, this study pushes the existing boundaries of the link between innovation capability as a management concept, connecting innovation capability with customer experience, reputation, and loyalty as marketing concepts. The arguments defend that the ability of a company offering a product or a service to create a strong position in a highpotential market depends upon the level to which the company is able to influence the experiences of its consumers, according to their demographic features and with or without using technology.

The theory of complexity provides a clear reflection of non-linearity between the links under investigation in a competitive market and under a situation of uncertainty. In addition, the study also investigates the influence of the consumers’ demographics (age, gender, occupation,  and education) on the linearity of such links. Therefore, the main aim of this study is to identify configurations that can describe customer experience for retailers operating in retail settings. The key findings enable managers to understand how the deployment of the technical innovation capability (developing new services, service operations, and technology) and the non-technical innovation capability (managerial, market, and marketing) in the retail environment can link consumer’s shopping experience with reputation of the firm and customers’ loyalty. This research achieves its objective using confirmatory factor analysis (CFA) and fuzzy set qualitative comparative analysis (fsQCA) (Ragin, 2006, 2008). Both analyses provide a deeper and richer perspective on the data when they work together with complexity theory (Mikalef, Pateli, Batenburg, & Wetering, 2015; Ordanini, Parasuraman, & Rubera, 2013; Woodside, 2014; Wu, Yeh & Woodside, 2014).