Rise of the machines? : the effects of self-service-technologies interactions in hospitality on brand and service evaluation : a study of self-service technologies and motive commnications as moderators for brand and se

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Rise of the Machines?

The effects of Self-Service-Technologies

interactions in hospitality on brand and

service evaluation

A study of Self-Service Technologies and Motive Commnications as moderators

for Brand and Service Evaluations in Hotels

Chaiyakit Limsuval

10435689

Master’s Thesis

MSc in Business Administartion: Marketing Faculty of Economics and Business

Supervisor:

Dr. Andrea Weihrauch

June 23th, 2017

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Statement of Originality

This document is written by Student Chaiyakit Limsuval who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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Abstract

“With increasing technological maturity, Self-Service-Technologies (SSTs) have become sophisticated enough to replace traditional employees in service interactions. Despite having the potential to change the nature of customer-company interactions of tomorrow, research analyzing the effects that SSTs have on brands is unprecedented. Giving this gap in literature, the objective of this thesis was to determine whether SST-supported check-ins would influence service quality and brand perceptions of consumers in the hospitality sector. Whereas quality evaluation remained unaffected, the results indicated that customer-SST interaction yields lower brand evaluation. However no effect is observed when an assisting employee is present nearby. This research thesis contributes to the sparse literature in the field of SST, and may facilitate managers and marketers to effectively leverage SSTs in their businesses.”

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Introduction

In the past years various forms of Self-Service Technologies (“SSTs”) have been implemented in the delivery of many services (Bitner, Brown, & Meuter, 2000; Meuter, Ostrom, Bitner, & Roundtree, 2000; 2003). One of the oldest SST system currently in use are automated teller machines (bank “ATMs”) where consumers can conveniently conduct banking businesses without any assistance of employees. Examples for SSTs in use today range from self-check-in machines at airports, to self-checkout counters in some supermarkets, or various self-service options online.

With decreasing “technological anxiety” of consumers, and increasing maturity of technology, also known as “technology readiness” (Mankins, 1995), SSTs have become a feasible channel for companies to deliver services (Meuter et al., 2003; Curran & Meuter, 2005). Since customers seem to be increasingly willing to perform services themselves, companies have strong incentives to expand a SST option (for delivery), which would (standardize service delivery and) greatly reduce labor costs. This development can also be seen in the emergence of modern SSTs in businesses and industries which are usually characterized by high customer-orientation and service contacts, such as hospitality and hotels (Meuter et al., 2000).

Although this evolution has potentially great implications on how businesses may be conducted in the future, literature and research in the field of SST is sparse. Past research has mainly focused on the functionality of SSTs and tangible impacts for the company:

Several studies have analyzed what SST-characteristics contribute to customer usage-intention and customer satisfaction (Dabholkar, 1996; Dabholkar & Bagozzi, 2002; Meuter et al., 2000; 2003; Beatson, Coote, & Rudd, 2006), and how implementing SSTs influence financial performance (Chen, Tsou, & Huang, 2009; Hung, Yen, & Ou, 2012; Orel & Kara; 2014).

However, past researches have not directly addressed potential effects that SSTs may have on intangible factors, such as customers’ mindsets or companies’s brand images. Various researches have established the important role of brand image and its management on a firm’s performance (Roth, 1995; Chaudhuri & Holbrook, 2001; Aaker, 2004; 2009), but the potential effects of SSTs on these branding issues have been overlooked by past researchers.

SST implementations can pose a great opportunity if brand image can be enhanced, for instance to reflect an image of innovation, which is shown to positively affect a company’s performance (Chen, Tsou, & Huang, 2009; Hung, Yen, & Ou, 2012). On the other hand, if

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consumers perceive that the firm’s reason for introducing SSTs is to replace human jobs to purely gain more profit, it could backfire and harm the brand image (Einwiller, Fedorikhin, Johnson, & Kamins, 2006; Ellen, Webb, & Moor, 2006). This is especially true for service heavy industries, such as hotels, where brand image and reputation are crucial. SST-customer interactions could be beneficial or detrimental, depending on how the SST influences the brand. Thus it is imperative to understand how the brand perception changes when SSTs are implemented, which is currently not addressed in academia.

Furthermore, past research did not address the notion that SST implementation can vary in different degrees. Depending on the SST, some service-interaction revolve exclusively around automated kiosks, while other SSTs are accompanied by a nearby employee for assistance. This difference in SST-centrality may affect the brand image and customer mindset differently. If a company implements more SST elements in daily business interactions, or even replaces all personal touch points completely, the company needs to thoroughly understand the effects that varying degrees of SST implementation have on their brand.

In conclusion, the full effects of SSTs and their variations on consumers’ evaluative mindsets are not fully explored yet. Furthermore, the potential moderating influences of a firm’s marketing communication and motifs are unaddressed by current literature. To address these gaps in the current literature the following research question is synthesized:

“How does the level of SST implementation and interaction influence service and brand evaluation in the hospitality sector?”

This research on self-service technologies within the contexts of branding and marketing communications is unprecedented and may shed light on the sparse and scattered research in the field of SSTs. The insights from this research paper could help managers and marketers utilize SSTs to their highest potential. As previously-mentioned, the firm needs to understand the effect that SSTs have on their firm’s image, especially in industries where brand image and reputation are crucial. Companies that can gather strong insights and figure out the best way to make use of this emerging SST phenomena, may have a headstart in the market of tomorrow, giving the accelerating user acceptance, technological development, and possibilities for implementation.

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The following literature review chapter will present current findings in the field of SST, marketing, branding, and marketing communications in detail and highlight how these variables relate to one another. From these theoretical constructs the research hypotheses will be deducted, which will be additionally summarized in a conceptual framework.

Next, the methods section will outline how the research variables are defined, gathered, manipulated, and measured. Additionally, the experiment setup as well as the sample will be presented in detail.

The outcome of the experiment will be presented in the results section, and its implications will be analyzed in the subsequent discussion. This Master’s thesis will then conclude with contributions and ramifications for academia and management.

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Literature Review

The purpose of this Master’s thesis is to examine the effect of self-service technologies (“SSTs”) on the mindset of consumers and their perception of a company. This section will outline the current findings and insights in the field of self-service technologies in conjunction with literature on service and brand evaluation. This extensive literature review will be identify current gaps in research from which the research hypotheses will be synthesized.

Self-Service Technologies

Self-service technologies (SSTs) are technological interfaces which allow customers to independently produce a service, free from direct involvement of employees (Meuter et al., 2000). Typical examples of SSTs include automated teller machines (ATMs), self-checkouts at supermarkets and gas stations, and various online self-services. According to multiple academic researchers, this technology is recognized as critical for delivering services in customer-firm interactions of today and the future (Bitner et al., 2000; Dabholkar, 1994; 1996; Parasuraman 1996).

There are several reasons for companies to implement SSTs within their businesses; the most prominent example is the great potential for cost savings. This applies especially for services where technology and automated solutions can substitute active tasks of traditional employees, therefore reducing labour costs (Bitner, Ostrom, & Meuter, 2002). In other cases, introducing SSTs creates additional channels to potentially reach previously inaccessible customers, such as customers that are bound to regular business-times or entire new customer segments (Bitner et al., 2002). Yet another reason for introducing SSTs come from customer demand, where the new technology solution increases customer satisfaction. The bank “Wells Fargo” is an example or this, which was the first bank to introduce online banking in the US, giving the company a competitive advantage over its competitors (Bitner et al., 2002).

This change in service interaction enabled by new technology is transforming the current marketplace, which is also reflected in the various types of SST currently in use by many companies. Whereas SSTs emerged as interactive voice responses via telephone (e.g. telephone banking) for instance, advancing computer technology and innovation allows SSTs to perform more complex tasks and services, such as online banking or parcel tracking (Meuter et al., 2000).

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Considering that automated-teller machines (ATMs) were the most prominent example of extensive self-service kiosks usage, today these self-service kiosks are emerging in businesses and industries, which were usually known for high intensity of service interactions. Examples for this phenomenon include self-check-in terminals at airports, self-checkout terminals at supermarkets, and self-order terminals at fast-food restaurants. In all these cases, the self-service kiosks perform the same (or very similar) tasks as traditional service employees.

In summary, SSTs allow customers to take an active role in service encounters, performing more and more of their own service without direct assistance from employees. According to Parasuraman (1996) and Meuter et al. (2000), these technological advances will take an increasingly critical role in customer-firm interactions, and become a key factor for establishing long-term business success. This growing importance of SST initiates a shift in the nature of services (Parasuraman, 1996).

Although previous researchers have studied the influence and effects of SSTs in businesses, none have made distinctions between the various degrees of SST implementation. More precisely, how much the service-interaction revolves around the automated kiosk varies from service to service. Although there is not an absolute scale to quantify the centrality of SSTs in a service interaction, this research distinguishes two types of SST implementation, based on common practices how many businesses have implemented SSTs.

The first type entails a pure SST interaction, where the kiosk fully replaces the task that a traditional service employee would perform. Traditional ATMs fall under this category, where customers can produce the service without any employee-interaction. The second type can be described as a “hybrid implementation”, where the customer performs the service with the SST but is additionally assisted or accompanied by a nearby employee. This form can often be seen at automated check-out booths in some supermarkets, or check-in terminals at airports.

Due to the different degree of SST centrality, these two types of SST implementation may have different effects on the consumer, compared to interactions with traditional service employees. To fill this gap in the current literature on SST, this research will analyze the effects of varying degrees of SST implementation.

Since the implementation of SSTs changes the nature of how the service is conducted, it is necessary to look at potential effects on the service evaluation of consumers. These implication will be discussed in the following section.

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Service Evaluation

Businesses in every field strive for excellence in service, since it is usually vital for a firm’s survival. Long-standing theoretical and empirical evidence shows that companies which provide greater levels of customer service yield higher profits than those that do not (Oliva, Oliver, & MacMillan, 1992).

However, other research also suggests that this is not always the case: Attempts to improve service quality can end up being inefficient, because costly service features were added that do not generate profitable gains (Zeithaml, Parasuraman, & Berry, 1990; Oliva et al., 1992). This may be because features were implemented, that do not improve the quality of the service, or which seem to be irrelevant for consumers to creating customer satisfaction.

Due to this it is important to analyze whether this case applies to the implementation of SSTs. Its implementation can either improve traditional service channels and lower overhead costs, or remain an unsuccessful attempt to improve service quality and ultimately wasting funds. To shed light on this question, this section will turn to current findings in the field of SSTs.

Previous research has been conducted to identify the sources of customer satisfaction and dissatisfaction where SSTs are involved (Meuter et al., 2000). Further, the research compares these SST sources of customer satisfaction to traditional interpersonal encounters, and how these sources are similar or different from each other. The results yielded that the main contributor for satisfaction with SST usage lay in the criteria: “Solved intensified needs”, “Did its job”, and “Better than alternative”, which all highlight the functional benefit of SSTs (Meuter et al., 2000). This research was confirmed in a similar context through an empirical research conducted by Orel and Kara (2014). The results are in line with Meuter et al. (2000), and show the positive influence of self-checkout systems in supermarkets on customer satisfaction.

A different research by Beatson, Coote and Rudd (2006) expands this even further, by analyzing the overall satisfaction from SST attributes and personal service attributes in the context of the very service-focused hospitality industry. The authors analyzed a hotel self-check-in and checkout option, and compared the effects of the SST usage and hotel personnel interaction on customers’ overall satisfaction. The results of Beatson, Coote and Rudd (2006) show that both personal services and SSTs can equally achieve overall satisfaction. This may come as a surprise, since intuitively highly trained service employees should outperform automated service machines.

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These above-mentioned researches have looked into the effects of SSTs. However those focused only on the implementation of SST, but did not draw comparison between the levels of integration: Full vs. hybrid SST could have different implications for service quality perception. The SST services accompanied by employees could boost service quality by giving extra assistance, or harm because of confusion, or no difference at all. Because of these implications, this thesis will attempt to close this research gap by analyzing the effect on service evaluation of varying degrees of SST implementation. As mentioned in the previous section, the varying degrees of SST implementation will be analyzed in this research through an automated check-in kiosk in a hotel. The conditions that will be analyzed are full SST condition, a hybrid condition, and a traditional check-in with an employee as a baseline.

Based on the arguments put forward in the research by of Meuter et al. (2000) on SST satisfaction, and Beatson, Coote and Rudd (2006) that showed the effectiveness of SSTs in hotels, it can be predicted that both SST conditions will spawn similar evaluation ratings to the traditional check-in. Based on this line of reasoning the following hypothesis can be deducted: H1: The implementation of SST yields equal service evaluation as traditional employee service In conclusion, this section has presented arguments based on existing literature that the implementation of SST can provide service satisfaction for the consumer. However, these previous studies have mainly focused only on tangible measurements and functional benefits of the SST interaction. Meuter et al. (2000) for instance, analyzed satisfaction criteria such as ‘the SST fulfilled its purpose’, which mainly revolve around functional need satisfaction.

Although it is a prerequisite for positive evaluation, only looking at functional and tangible measurement does not capture the full picture how a consumer thinks about the company and brand. The consumer mindset entails also intangible and symbolic aspects, such as brand associations and brand image (Keller, 1993; Aaker, 1996; Keller & Lehmann, 2003).

Why it is crucial for businesses to have favorable brand evaluation, and how the implementation and varying degrees of SST have an effect on the consumer mindset, will be discussed in the following section.

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Brand Evaluation

The strategic importance of managing a brand’s perception in the eyes of consumers is well established in business practices. Various researchers have established the important role of brand image, and its management, on a firm’s performance (Roth, 1995; Chaudhuri & Holbrook, 2001; Aaker, 2004; 2009). An example of how poor brand management has a detrimental effect on the company in the recent years is the fashion brand Abercrombie & Fitch. After multiple scandals, most notably from an interview of CEO Mike Jeffries ‘fat-shaming’ clients, A&F received massive backlashes, causing public outcry and resulting the stock price to plummet. The tainted brand image dramatically changed customer mindsets, and the negative brand image persistent until today (Carter, 2013). This example show that liking and perception of a brand is crucial for its success.

One theoretical explanation for this development, and the underlying scientific foundation, is how brand value is created in consumers’ minds: Brand performance, which ultimately influences the financial performance of a company, depends on the favorability of the so-called ‘customer mindset’ (Keller & Lehmann, 2003). Any action or change in a marketing program affects this mindset (Keller & Lehmann, 2003). These marketing programs can be directly linked to the product or service, or can manifest in the form of a firm’s marketing communications. This 'customer mindset’, which shape the consumers thinking and behavior, consist of five dimensions and are all affected by a company’s marketing program: ‘awareness’, ‘associations’, ‘attitudes’, ‘attachment’, and ‘activity’ (Keller & Lehmann, 2003).

Awareness is the consumer's ability to recall and recognize the brand’s product or service. The key source of the brand value are its associations, which are measured on the dimensions ‘strength’, ‘favorability’, and ‘uniqueness’ (Keller & Lehmann, 2003). Associations are highly intertwined with customers’ attitudes (or “liking”), which adds to the consumer’s overall evaluation of the brand. These two factors, associations and attitude, are forming the heart of the ‘consumer mindset’. Together they also influence ‘attachment’ and ‘activity’, which translates to the loyalty towards the brand and how much they engage with, or talk about the brand. All these five dimensions are part of the ‘consumer mindset’, which heavily influences the brand performance, and ultimately translates to the financial performance of the company (Keller & Lehmann, 2003).

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program investment’ (such as SST implementation) is dependent on the ‘clarity’, ‘relevance’, ‘distinctiveness’, and ‘consistency’ of the program quality. Having a marketing message, marketing program, or a product/service that is clear and in line with the overall brand persona, reduces confusion among consumers, which increases favorability and support for the brand (Park, Milberg, & Lawson, 1991).

In summary, the more favorable and synergetic the associations of the brand and its marketing program, the better the overall brand evaluation. Managers are therefore inclined to establish a positive mindset and have high brand concept consistency, and should therefore conduct marketing programs with care. This especially applies, when companies will adapt SSTs in their businesses which consumers will be encountering.

The implementation of SST is a significant and highly visible change of how customers conduct businesses and services. Depending on the brand and industry nature, the implementation of SST can potentially be beneficial in terms of favorable associations and brand concept consistency. For instance, SST usage with tech companies or brands that focus on innovation and speed can easily establish concept consistency. However, this research will shed light on SST usage in a service heavy industry, where the associative compatibility is intuitively low.

In the mind of consumers the associative network of hotels will likely revolve around other associations than the ones for self-service technologies (Till, Braak, & Waterman, 2011). For instance, hotels will likely trigger associations such as ‘luxury service’ and ‘highly customer-oriented’, whereas SSTs may trigger technology-based associations, which may be perceived as not being fully compatible.

Also undesirable associations and attitudes of SSTs could be added, which would harm the parent company (Aaker, 1990).Although some typical SST associations such as ‘speed’ and ‘convenience’ may be beneficial and compatible with hotel associations, the connection is less obvious and these characteristics usually have not the highest priority during the evaluation of hotel services. Hotel association often center highly around human-to-human interaction, whereas SSTs has a lack thereof, often yielding associations such as “cold” and “impersonal”. Apart from this, being unfavorable associations, “cold” and “impersonal” are in sharp contrast to hotel association revolving around “customer-orientation”, which leads to low brand concept consistency that potentially lowers brand evaluation even further. In summary, the

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implementation of SSTs in a hotel context will likely generate lower favorability.

However, as outlined in the previous sections, two types and degrees of SST implementation may cause different influences when these associations are formed. The degree of mechanical-related associations that would likely yield negative evaluation, might be dependent on the centrality of SST implementation and interaction focus. A SST service accompanied by an employee could either add positive associations to the overall associative network, or harm the overall evaluation, because the customer could perceive a lower concept consistency; or there might not be difference between the two condition at all.

Nevertheless, based on the earlier presented arguments regarding how associations are formed in the consumer mindset, it is likely that negative associations will be dominant: The longer/higher the interaction with SSTs, the higher the exposure to stimuli associated with the mechanical SST. Therefore, these associations will likely be more prominent in consumers mind (Keller & Lehmann, 2003; Till et al., 2011).

In line with this argumentation on centrality, the effect strength of the varying SST implementation degrees can be deduced: Full automated SST interaction will likely generate the lowest brand evaluation due to the high centrality in the interaction.The hybrid setting might be more favorable because of human interaction, but also due to the high centrality of the interaction the customer mindset will likely be predominantly occupied with robotic SST associations. In addition, pairing human associations with robotic associations may dilute overall brand concept consistency and therefore also negatively impact brand evaluation, in contrast to traditional employee-only service interactions. Based on this line of reasoning the following hypothesis can be derived:

H2: The implementation of SSTs will yield lower brand evaluation in contrast to traditional employee service

In conclusion one can establish that any form of marketing program and communication, such as the implementation of SST, will add further associations and nodes into the mind of consumers, which influence consumers’ attitudes and evaluation of the brand as a whole. However, the way customers perceive and react to SST implementation is strongly influenced by various other

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factors. These moderating influences will be discussed in the following section.

Motive Communication

The extent to which SSTs may influence service and brand evaluation does not purely depend on the mere implementation alone, but also on various other factors and conditions. As established earlier, corporate associations play an important role in brand performance. Any aspect of a company’s marketing program will create associations and attitudes, which can strengthen or weaken brand attitude (Keller, 1993; Aaker, 1996; Ellen et al., 2006). However, these associations are not only built and triggered by the company’s actions, for instance adding new features of the product and service, but also by what and how the brand communicates its marketing programs to the consumer.

This is where consumer perception is involved: The behavior and communication of companies have an influence on consumers’ perceptions, and their attitude towards the company (Kelley & Michela, 1980; Ellen et al., 2006).

According to ‘attribution theory’, individuals evaluate the motives of companies and these perceived motives influence subsequent attitudes and behavior towards the brand (Kelly & Michela, 1980; Foreh & Grier, 2003; Ellen et al., 2006). Consumers try to understand the firm’s Motives embedded within the marketing strategy or communications by elaborating their messages. In other words, consumers may care less about ‘what’ firms are doing than about ‘why’ they are doing it.

Further, research has found that individuals attribute mainly two primary types of motives to a company’s behavior: “firm-serving” motives that focus on the potential benefit to the firm itself, and “public-serving” motives that focus on the potential benefit to others, outside the firm (Foreh & Grier, 2003). Ellen et al. (2006) expanded on these “self-centered” and “other-centered” motives by dividing these into further sections. Self-centered motives will be regarded negatively, if they merely serve egoistic purposes, such as enriching oneself. However self-centered motives can also be regarded positively, if they serve a strategic purpose, because it presents the company as being a competent expert. Similarly, other-centered motives are regarded positively, when they are value-driven, such as helping communities and the environment. On the other hand, other-centered motives can also be seen negatively if they are

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stakeholders-driven, or focus on pleasing stockholders (Ellen et al., 2006).

Companies therefore have an incentive to manage the perception of their Motives (in the eyes of the owner), which commonly is shaped via PR and communication efforts. From this line of reasoning the main effects of Motive communication can be described in the following hypotheses:

H3a: Egoistic-Self-serving motives will yield low brand evaluation H3b: Altruistic-Value-driven motives will yield high brand evaluation

With ‘attribution theory’ about consumer perceptions in mind, this research will look at its relevance in the context of SSTs. The implementation of SSTs poses a highly visible change for consumers, of how a company conducts its service interactions. Due to this and in line with attribution theory, it is highly likely that consumers will question the motives behind the business decision. The consumers’ attitudes towards the brand will therefore be influenced by their perceived motives of the company for implementing SSTs.

As mentioned before, consumers interpret the reasons for various business decisions. The implementation of SSTs can be interpreted as an attempt to increase profits for the firm. This reason falls under egoistic self-serving motives which would likely cause negative brand evaluation (Ellen et al., 2006). However, this negative perception and effect could potentially be reduced, if the company presents a more noble reason for implementing SST than cost-saving. For instance, being innovation seeking and actively communicating these values would display altruistic motives to consumers, consequently benefiting brand evaluation. In addition, actively presenting the motives clearly would also reduce brand concept consistency. From this reasoning, the following hypotheses for the moderating effects of motive communications are derived:

H4a: Egoistic-self-serving motive communication enhances the negative influence of SST implementation therefore yielding lower brand evaluation.

H4b: Strategic-value-driven motive communication weakens the negative influence of SST implementation therefore yielding higher brand evaluation.

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Conceptual Framework

SST Interaction

Service Evaluation Brand Evaluation

Motive

Communication

H1 H2 H3a/b H4a/b

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Methodology

Independent Variable: SST Conditions

Self-service technology, in comparison to personal service, is a relatively novel method for service delivery, with rather sparse research. Even though previous researchers looked at the effect of SSTs, they did not draw comparison on the level of implementation, or how much SSTs replaced a traditional service interaction. Because of this research gap there is no pre-existing scale for measuring the level of implementations and centrality of SSTs. Although defining this ‘degree of SST implementation’ into absolute quantitative values may seem problematic, one can indeed observe varying levels of centrality during the SST interaction.

To examine the different levels of SST implementation, this research measured how central the role of SSTs are during service interactions. Participants watched a video of a model performing a hotel check-in. Although having participants interact with an actual SST would yield higher internal validity, it would have exceeded the scope of this Master’s thesis. Nevertheless, using a video setup provided sufficient internal validity: Due to ‘vicarious learning’, observing an interaction can work as a proxy for actual experience (Singh, Balasubramanian, & Chakraborty, 2000). To ensure a high-level of realism, the check-in process was filmed in the foyer of an actual business hotel in Amsterdam which have SST check-in kiosks implemented. In addition, the videos were shot with a Point-of-View angle which may enhance the experiential effect (Singh et al, 2000). To improve unbiasedness towards the actual brand, the hotel was given a fictional name for the experiment, referred to as the “M-Hotel”. Participants are assigned to different conditions, where one of the following three check-in versions were presented.

Pure SST interaction: The first condition featured a video of a fully automated check-in process through a SST terminal. The model solely interacted with the SST in the hotel lobby with no other persons and employees present. This condition simulated a case, where the SST has fully replaced the traditional service employee, eliminating personal interaction with the staff.

SST with employee assistance: The second condition featured a hybrid condition where the model performed the check-in with a hotel staff member accompanying the process. This has

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the advantage that consumers can use the SST freely, but still have personal assistance if help or additional services are required. In this research, the assisting employee was present near the SST but only took a passive role: He greeted the customer and offered assistance if needed, however he remains uninvolved during the actual check-in process. This SST setup in combination with an employee is currently a popular method of SST implementations, which adds external validity.

Traditional employee service: The third condition showed the check-in process via the traditional means. Interaction of the service was solely between the customer and the front-desk staff. The check-in terminal remained out of reach from the customer. This condition acts as a baseline to compare the other two conditions.

Although these levels of SST implementation can be further divided into smaller segments, this outline covers the basic dynamics of the SST-customer-employee relationship. Further, these divisions of SST implementation are the most common types currently found in the market, which ensures external validity.

Dependent Variables: Customer Evaluations

As discussed in the literature review, the brand image entails the set of brand associations, which is rooted deeply in the consumer's mindset (Keller, 1993; 2003; Aaker, 1996; Keller & Lehmann, 2003). These associations can be functional or symbolic, and have varying levels of favorability, strength, and uniqueness. For instance, Hyatt hotels are likely to be associated with luxury and comfort, and Apple with high-quality and high-cost technology. The degree of favorability, strength, and uniqueness of these brand associations contribute to the overall evaluation of the service and the brand (Keller, 1993; Faircloth, Capella, & Alford, 2001). The means to measure these factors will be outlined in the following section.

Service Evaluation

As mentioned in the literature review the majority of existing research on SST focus on the evaluation of SSTs, and antecedents such as SST characteristics (Meuter et al., 2000; 2003). Scales like the ‘SSTQUAL’ scale were introduced to measure the functional aspects of SSTs and how they affect customer evaluation and customer satisfaction (Lin & Hsieh, 2011).

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these factors may pose as antecedents for the evaluation of the brand (Dodds et al., 1991; in Yoo & Donthu, 2011). There is an abundance of scales to measure service quality from the perspective of customers, which can be applied to the context of SSTs (Dabholkar, 1996; Dabholkar & Bagozzi, 2002; Meuter et al., 2000; 2003). Therefore, this research used these well-established scales to measure the participant’s perceived service quality during the check-in process.

The perceived service quality is measured on the dimensions of ‘functionality’, ‘enjoyment’, ‘customizability’, which all contribute to service quality, as well as as the ‘recommendation likelihood’ (Dodds et al., 1991; in Yoo & Donthu, 2011)

These items were rated by the participants on a 7-point Likert-scale, and included statements such as: “The check-in process is simple and easy to understand” or “The check-in process could adjust to my specific needs”.

Brand Evaluation

The implementation of SST will add further nodes to the associative network of a company and brand. These can include the attributes of the SST, the functional benefits, symbolic values and many more. Given this extension of the associative network, the brand image and brand evaluation will be shaped further as well.

This influence, the consumer’s attitude towards the brand, is measured by questions which asked participants to rate various statements concerning the brand on a 7-point Likert-scale. These questions and scales were used to determine the favorability and strength of a brand and included statements such as “I find the brand… [...] unpleasant/pleasant, unlikable/likable, not irritating/irritating, and not interesting/interesting” (Park & Young, 1986; Zhang & Zinkhan, 2006).

Moderating Variables: Motive Communication

Brand and company associations play an important role in corporate outcomes, including reputation, product and brand evaluations, purchase intention , and customer identification with a company (Keller, 1993; Aaker, 1996; Ellen et al., 2006). These associations are built and triggered by what the company does but also by what it communicates.

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company’s actions (Kelley & Michela, 1980; Ellen et al., 2006). The two primary types of motives for a company’s behavior are “self-centered / firm-serving” motives, which focus on benefitting the firm itself, and “other-centered / public-serving” motives that focus on the benefit to others external to the firm (Foreh & Grier, 2003; Ellen et al. 2006). As argued in the literature review, the consumer’s motive interpretation may be influenced by what the company communicates to the public.

To test this moderating effect, the company’s motive was established through the means of priming. Two conditions were primed by stating the company’s motive before showing the service-interaction video:

Egoistic-Stakeholder-driven: Experiment participants were presented with the message “The strategy of M-Hotel is to increase its profits and reducing its expenses (e.g. cutting personnel cost)”. Expense reduction will satisfy the company’s ‘egoistic’ criteria and increasing profits will represent stockholder interests.

Strategic-Value-driven: Participants in this second condition saw a message that stated, “The strategy of M-Hotel is to attract customers and facilitate technology innovation for society”. Attraction of new customers acts as the strategic means, and the facility of technology and innovation is rooted in values.

This research utilizes the means of direct priming to negate possible interfering effects of company communications. These relate to believability of the message and skepticism of consumers, or in other words, whether the consumer feels that the company is telling the truth about their real motives (Foreh & Grier, 2003). Being a truthful third party, having the researcher stating the company motive, instead of the company itself, may overcome this influence.

Control Variables

Typical variables that may become relevant during analyses are demographics such as age, gender, and education. In the case of SSTs, additional consumer traits that affect the interaction with technology, are potential influences which need to be accounted for (Dabholkar, 1996; Dabholkar & Bagozzi, 2002). These may include ‘sensation seeking’ traits or ‘technology anxiety’ (Dabholkar, 1996; Dabholkar & Bagozzi, 2002).

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influence the relationships were controlled for by randomly assigning participants to the different group conditions. So the confounding effects of irrelevant variables, which are not being studied, are being reduced (Field, 2013).

Nevertheless, the data on several of these potential control variables were gathered additionally, by including the corresponding questions to the survey. These traits were measured in the dimensions of ‘technological anxiety’,’venturesomeness’, and ‘confidence’.

Furthermore, the frequency of past and current usage of other SSTs were measured, since experience with SST interaction may influence the evaluations. These other forms of SSTs included ATMs (automated ticket machines), Internet shopping, and self check-out SSTs at supermarkets.

Data collection

This research used a survey design to carry out the experiment. Data gathering for the analysis was achieved through the online survey software Qualtrics. As mentioned before, showing the SST conditions through a video attached to the survey offers sufficiently similar stimuli to recreate the condition as if the respondent is taking part in the SST interaction in real-life (Singh et al., 2000).

Doing a survey research has the advantage that the motives, feelings and attitudes of respondents can be asked directly instead of inferring them from their behavior (Martin, 2007). Secondly, collecting large amounts of data can be done in a fast and cost-efficient manner (Martin, 2007). Additional advantages are that respondents can participate at their own speed and from any location, which provides comfort so that answers are less restrained.

This online study was conducted by sending out links to the survey to a panel of respondents. These participants were reached mainly through announcements on social media networks and word-of-mouth, representing convenience sampling.

In this experimental between-subject research design every participant was randomly assigned to the different groups. Randomization of the convenience sample ensured that every participant had equal chances to be in any of the six experiment conditions (see table below) and therefore reduced sample biases (Saunders & Lewis, 2012; p.135). This randomization has been achieved by programming the survey tool Qualtrics to assign each participant randomly to any condition

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group. An additional layer of randomization is included, which presents either brand evaluation questions or service evaluation questions first. Presenting these question blocks in different orders may further reduce biases from spillover effects, where the evaluation of one might affect the other.

The order of questions and pages that participants saw is: 1. Introduction

2. Video of the interaction (three conditions) 3. Priming (two conditions)

4. Brand evaluation or service evaluation 5. Brand evaluation or service evaluation 6. Traits questions

7. Demographics questions

Experiment Conditions: 3x2 between-subject design

Egoistic-driven motives Value-driven motives SST “SST for Cost-saving” “SST for Innovation”

SST + Employee “SST + Employee for Cost-saving”

“SST + Employee for Innovation”

Employee “Employee

+ Cost-saving message”

“Employee

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Method

This research framework entails a continuous outcome variable with multiple categorical predictors. Therefore, the effects of varying degrees of SST implementation on brand evaluation will be tested using an independent factorial analysis of variance (ANOVA) with multiple regressions. In the following chapter the data and analyses will be discussed in detail.

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Analysis & Results

In the following section, the main variables used for this research are summarized and discussed. Furthermore, the descriptive and frequency statistics will be presented in detail. Data analysis and hypothesis testing was performed via SPSS.

Descriptive Statistics & Reliability

In total, 185 respondents participated in the online experiment, ranging between the age of 19 and 61 (M=25.75, SD = 6.923). The around half of participants obtained a bachelor's degree (52%) and more than 66% of the sample respondents were female (123=female and 62=male).

62 participants were exposed to the pure SST condition (28 egoistic / 34 altruistic), 61 respondents watched the hybrid SST condition (29 egoistic / 32 altruistic), and 62 participants were assigned to the baseline condition of traditional employee interaction (33 egoistic / 29 altruistic). Each condition has sufficiently large sample size (n 30), which in line with central limit theorem will roughy yield a normal distribution. This will provide valid results since the ANOVA is also robust against minor deviations from normality (Hogg & Tanis, 1977).

Counter-indicative items were recoded accordingly; for instance the items for trait variable ‘technological anxiety’ (TraitTechAnx) were recorded (rTraitTechAnx) to match the other traits variables ‘confidence’ and ‘venturesomeness’.

The two dependent variables, were both formed from question items regarding the evaluation of the brand or service. Question blocks measuring the research relevant variables were grouped and Cronbach’s Alpha (α) was used to measure the internal consistency of these scales. Both perceived service quality and brand attitude showed high consistency with Cronbach’s Alpha above 0.7 (MeanServiceEvaluation α=.807 & MeanBrandEvaluation α=.879), which also applied to the recoded ‘Tech Traits’ items (α=.774) After the exclusion of one frequency item (‘rQ26Freq’) a Crombach’s Alpha above 0.7 was also reached for “UseFrequency” (α=.734). The scale reliability is very high, and deleting more items would have not yielded a relevantly higher Cronbach’s Alpha. Therefore these scale means for the variables were computed and used for further analysis.

Overall, only a slight negative skewness can be observed for both service scores (Skew= -.307) and brand scores (Skew= -.579), suggesting that the assumption of a normal distributed sample is

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fulfilled. Further, the mean score given for service quality is M=4.841 (SD=.6901), and for brand evaluation is M=4.804 (SD=1.031). Per condition mean service scores range between M=4.731 (SST), M=4.865 (Hybrid), to M=4.931 (Employee); and mean brand scores range between M=4.395 (SST), M=4.931 (Hybrid), to M=5.088 (Employee). These means with the skewness might indicate that participant’s evaluations are overall slightly lower than with traditional employee service.

From these variables a correlation test was run, and the results can be seen in the following correlation table, which includes means, standard deviations, and again the Cronbach’s Alphas on the diagonals. The Pearson correlation indicate a negative correlation between brand attitude and SST implementation conditions.

Table 1: Means, Standard Deviations, Correlations, Reliability

Measure Mean SD 1 2 3 4 5 6 7 8

1. Service Evaluation 4.841 0.691 (.807)

2. Brand Evaluation 4.804 1.031 .729** (.879) 3. Check-in Condition 2.00 0.821 .119 .276**

4. Motive Priming 1.51 0.501 .026 .047 -.066

5. Trait Tech Score (Control) 2.662 0.853 -.090 .015 .189* -.104 (.774)

6. Usage Frequency (Control) 3.786 1.316 -.277** -.163* .057 -.082 .238** (.734) 7. Age (Control) 25.75 6.932 -.075 .002 .059 .053 .209** .041

8. Gender (Control) 1.66 0.473 .007 .051 -.028 -.027 .090 -.124 -.112

9. Education level (Control) 3.786 0.928 -.049 -.147* -.007 -.021 -.069 -.191** .216** -.116 ** Correlation is significant at the 0.01 level (2-tailed)

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Hypotheses Testing

This experimental setup manipulated three conditions with two moderating variations, totalling six respondent groups, who were subjected to six different categorical conditions. In order to test whether the ratio of the between group variance and the within group variance was statistically different (in a 95% confidence interval), a one-way mANOVA between the dependent and independent variable was conducted.

Independent variables are the Conditions and Priming of the groups. Dependent variables consist of the evaluation of service and brand quality. The control variables age, gender, education level, individual traits, and usage frequency were used as covariates.

As shown in table 2 The mANOVA table reveals the main effect of the check-in type is significant on brand evaluation (F=8.814, p<.001), but the effect on service evaluation is insignificant (p=.155). The both main effects of the motive priming process show insignificant results on service (p=.931) and brand evaluation (p=.550). Lastly, also the interaction effects of the check-in types and priming resulted in insignificant results for service (p=.234) and brand evaluation (p=.604). Furthermore, the Levene’s test shows that variances are equal across group. This homogeneity, as well as the normal distribution of data, satisfy the conditions necessary for a valid ANOVA.

Table 2: Significant Bivariate Effects for Check-In & Priming Conditions

Dependent Variable df F Conditions (IVs) Mean Sq. p-value

2 1.883 Check-in Type 0.837 0.155

Service Evaluation 1 0.008 Motive Priming 0.003 0.931

2 0.505 Interaction 0.225 0.604

2 8.814 Check-in Type 8.227 <.001 Brand Evaluation 1 0.359 Motive Priming 0.335 0.550

2 1.464 Interaction 1.366 0.234

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This significant ANOVA is followed up with a Tukey post-hoc test, to show the effects per SST condition. As shown in the multiple comparison table below, mean brand-liking scores for the pure SST condition were statistically significantly different from the hybrid-SST condition (p=.009), and from the base employee condition (p<.001). However, no statistically significant difference was found between the hybrid-SST condition and base employee condition (p=.649). These differences are visualized by the generated plots below (Plot 1). Finally, no statistically significant difference in the means for service evaluation was found between all conditions.

Table 3: Multiple Comparissons

Dependent Variable (I) (J) Mean Difference (I-J)

Std. Error p-value

Service Evaluation SST Hybrid -0.1344 0.1246 0.529

Employee 0.1993 0.1241 0.861

Brand Evaluation SST Hybrid -0.5352 0.1785 0.009

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Discussion

The objective of this thesis was to determine whether SST-supported check-ins would influence service quality and brand perceptions of consumers in the hospitality sector. More precisely, this research compared evaluations of varying implementation types: full SST interaction, SST with employee support, and traditional employee service. In addition, the thesis aimed reveal whether company communication has a moderating effect on the brand and service evaluation, by communicating egoistic or altruistic motives.

The results indicate strong support for hypothesis H2, which stated that SST implementation yields lower brand evaluation. Lower scores on brand evaluation point out that the favorability of the brand has decreased. However the effect varies between the two different degrees of SST implementation:

Compared to the traditional service interaction, statistically significant lower brand evaluation solely occurs at the pure SST interaction. In other words, consumers who exclusively interact with the SST gave statistically significant lower brand evaluation scores, in contrast to traditional employees. As predicted in the literature review, brand evaluation seem to be affected by the SST service, causing negative evaluation. Three arguments support this view:

Firstly, this lower score may have occurred additionally due to unfavorable SST associations being connected to the associative network of the hotel brand (Aaker, 1990; Keller & Lehmann, 2003). Hotel brands will likely trigger associations linked to the hospitality sector, such as ‘luxury services’, which often center strongly around human-to-human interaction such as ‘high customer orientation’. SSTs on the other hand likely entail associations from the tech industry and robotics, where the lack of human-to-human interaction may yield associations such as “cold” and “impersonal”; both of which are unfavorable in the hospitality sectors.

Secondly, the implementation of SST in the hotel section may succumb to brand concept inconsistencies (Park, Milberg, and Lawson; 1991). Although some typical SST associations such as ‘speed’ and ‘convenience’ may be compatible with hotel associations these links between may not be clearly visible to the consumer, as outlined in the literature review. Due to this, low brand concept consistency may be a cause for the lower brand evaluation (Park, Milberg, and Lawson; 1991).

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diagnosticity’ (Meyvis & Janiszewski, 2004), which describes how easily associations come to the mind of the consumer and how relevant these are for the evaluation: Unfavorable associations of the SST (such as ‘cold & impersonal’) may come to the consumer’s mind faster than its benefits associations, causing lower favorability.

However, the lower scores on brand evaluation varies between the two different degrees of SST implementation. In contrast to the pure SST condition, the effects on brand evaluation for the hybrid condition remain insignificant: Customers who were accompanied by an employee when checking-in with the SST did not give lower brand evaluation scores, compared to the traditional check-in method.

Contrary to the initial prediction in the literature review, the mere presence of an employee may have weakened the effect that the SST would have had on its own. This may be due to the fact that an accompanying employee would add favorable service associations to the previously ‘impersonal SST’, yielding positive brand evaluation (Aaker, 1990; Keller & Lehmann, 2003). Also, in line with ‘accessibility & diagnosticity’ of associations as described by Meyvis and Janiszewski (2004), the associations brought by the employee may interfere with some SST associations, preventing negative SST associations to come up in the consumer’s mind. Lastly, the presence of an employee at the SST interaction may have also facilitated the customer to perceive the brand concept to be consistent, resulting in higher brand evaluation (Park, Milberg, and Lawson; 1991).

To sum up the effects of SSTs on brand evaluation, the overall results indicate that the implementation of SST has a negative effect on the evaluation of brands. This is true for the full SST implementation. However, there was no statistical evidence that the hybrid condition yields lower brand evaluation scores than the traditional employee condition - indicating that SST with employee assistance yield similar brand liking compared to traditional employee-only service interaction. Therefore, this indicates that the hybrid SST interaction is more favorable perceived than the full SST implementation.

In terms of service evaluation, no statistically significant effect of SST implementation could be found (H1). As predicted, the evaluation of service quality remains unaffected in all conditions. Based on the results it can be deducted, that the implementation and use of SST yields similar service-satisfaction outcome to a human counterpart.

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This is in line with Meuter et al. (2000) and Orel and Kara (2014), which highlight the source of customer satisfaction being the functional benefit of the SST. In addition, this study has analyzed the influence of SST implementation in a hotel, which is similar to the research of Beatson, Coote and Rudd (2006), also confirming these findings. This means, checking-in at a computerized terminal gives the similar functional value as with a regular front-desk hotel employee.

The remaining hypotheses (H3a/b and H4a/b) have focused on the effect of company motives. The results show no statistical proof to infer any influence on service and brand evaluation (H3a/b). Contrary to the initial prediction, there seems to be no effect of how the brand or service is perceived, regardless of what kind of motivation is communicated. This outcome may be due to credibility reasons (from the priming process) of the company, where the customers may doubt the intentions and honesty of the communicated messages. For instance, behaving altruistic in a for-profit company seems to be contracting, causing customers to ignore the communication message in their evaluation process (Ellen, Webb & Mohr, 2006).

In line with the lack of the main effect of motive communication (tested in H3a/b), there was no statistically significant interaction effect observed (H4). This means, the communication efforts of the company does not magnify or weaken the effect from SST implementation on brand evaluation. Because of these reasons it can be argued, that in the eyes of the general consumer the implementation of SST is likely to always be attached to some negative sentiments or egoistic motives to a certain degree.

It is worth mentioning that the control variable ‘SST usage frequency’ stands out with strong significant results. When treated as a moderator the Johnson-Neyman Technique revealed that its influence on brand attitude are in effect at low to medium usage frequency. People who were not frequently exposed to SST give particularly negative scores in brand evaluations when interacting with the check-in SST. This indicates that the higher the contact of consumers with SST in the past, the less its effect is taken into consideration during the evaluation processes. In other words, being generally used to self-service technologies weakens the negative sentiment of SST.

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Theoretical and Managerial Implications

In terms of theory, this study contributes to the currently sparse research field of Self-Service Technologies by adding the dimensions of branding, marketing and communication efforts of companies. Further, this research analyzed the effects of SST in the service-heavy industry of hotels, which expands the scope and area where SST kiosks were usually found in the past. Previous research has primarily looked at the satisfaction that SSTs provide in the service (Dabholkar, 1996; Meuter et al., 2000; Orel & Kara, 2014), or the financial bottom-line of SSTs (Hung et al., 2012). The findings of this research, which imply that SST implementation affects the brand perception, may further be expanded upon with additional relevant moderating and mediating factors. Furthermore, this research analyzed a possible interaction effect of communication, and future research may look at the perception of consumers directly, for instance in terms of message credibility.

The results of this research has practical implications for managers and marketers, as well as theoretical implications for researchers. The findings imply overall that great attention should be paid when implementing self-service technologies, since it effects extend beyond mere customer satisfaction. Although SST provides a cost-efficient way of delivering basic service, which even yield good service satisfaction (Meuter et al., 2000; Orel & Kara, 2014), managers and marketers should also take effects on the brand into consideration. The cost-saving benefit of SSTs can be deteriorated by suffering brand perception, especially with customers who are inexperienced with technology. Managers and marketers should therefore be very selective about the context and situation in which SST implementation is strategically wise for positive customer response and branding. This especially holds true in the hospitality and hotel business where brand reputation is essential.

Lastly the results on motive communication for using SSTs, indicate that these efforts may be obsolete. This may be due to low message credibility, since implementing SSTs may always convey some egoistic and strategic motives. Instead of focusing on communication and attempting to reach all customers and convince consumers of altruistic motives, it is more effective to focus on identifying the ‘right’ customers for the company. As seen in the results, consumers who are often exposed to SST and are used to this type of services are less affected by

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negative sentiments of SSTs. Translating this branding insight into a focused marketing strategy may also be a way to turn SST implementation into a “blue ocean strategy” (Kim & Mauborgne, 2004): meaning SSTs could be exactly targeted and tailored to the needs of a specific technophile customer segment, resulting in competitive advantage for the firm. In this case of hospitality sectors, SSTs could be implemented in hotels specifically targeted for tech-savvy business travellers.

Limitations

As mentioned earlier, this research attempted to observe an interaction effect of company communication with the implementation of SSTs. The reasoning that an interaction was predicted is based in ‘attribution theory’ (Ellen et al., 2006), where the perceived motive and message credibility affect the evaluation of the brand. However, this research only indirectly stimulated this factor through the means of priming, and no interaction effect was found. This priming procedure could be seen as a limitation since the priming procedure takes place after an initial impression has already been formed in the minds of the consumer. The specific priming has to work against the already established salient beliefs that are hard to replace (Keller, 2001). Future researchers could overcome by directly measuring the perception of credibility from consumers. This also in line with the limitation of the experiment setup, where future researchers should analyze actual customer behavior and attitude with real brands and real SST usage. Apart from increased validity, this would then also reduce the limiting effects of the convenience sampling.

In addition, the sample may be adapted to a specific target group, instead of hotel visitors in general, since the needs and preferences may vary dramatically and influence the brand evaluation. This type of SST hotel check-in is well-tailored to the needs of non-commercial hotel visitors, such as business people who travel frequently and may value the SST more favorably. Managerial relevance would be increased since normally only a market segment is targeted and not the whole spectrum of different type of hotel visitor. The significant control variable ‘frequency’ could be an additional indication that the initial negative response may be diminished throughout multiple exposure to self-service technologies. Therefore, generalization of SST effect on brand evaluation should be made with caution, since further research is still

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needed in different settings and contexts, such as other industries.

Conclusion

This research has provided statistical evidence that the implementation of self-service technologies in hospitality yield lower brand evaluation and liking. Also this research confirms previous findings that SSTs provide equal satisfactory services as human counterparts, which also apply in hospitality. Communication of company motives does not influence brand liking, as SST implementation seem to always imply egoistic motives to a certain extent. Managers and marketers should therefore be aware and cautious about the context and situation in which SST implementation is strategically feasible for creating positive customer response.

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