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A Scientific Meta-Analysis, of kiosk integration within the hospitality industry

By David J. Paster

David J. Paster, PrincipalYarborough Planning, LLC

19 Brentmoor ParkClayton, MO 63105

United States of Americadavid.paster@yarboroughplanningllc.com

(702) 813-5062

Introduction

Why should a restaurant and its respective prospective or established guests adopt Self Service Technology (SST) in the form of a kiosk-based system? The simple answer is for the field of food and beverage-based hospitality not merely to tolerate an evolutionary progress in an environment such as quick serve or (informal) table dining restaurants, but actually embrace this transactional transformation and its identifiable advantages to not just streamline but also overall improve the patron within a restaurant experience.

The ability to promote behavioral alteration of consumers is only possible if the change-agents understand the drivers of patron choice to accept, find satisfaction and utilize (or, contrarily, reject and abandon) a self-service, computer and human interacting technology.

A half century ago, pulling money from an Automated Teller Machine (ATM), paying for gas with a credit card or a RFID fob (e.g., Mobil® Speed Pass™) and, due to lack of options, being forced to perform shadow labor (e.g., filling with air one’s own deflated car tires or wiping off a smattered windshield) are two simple examples of contemporary consumer practices in the majority of the United States that have become de rigueur.

Thus, the technological leaps, as alluded within this “thought piece,” from dropping nickels in a slot to obtain a piece of pie or bowl of soup from a human stocked holding cabinet at a Horn & Hardart Automat’s at the turn of the 20th century to ordering by phone app and having food brought curbside (by no-less-than effectively equivalent “car hops” at McDonald’s™) during this post-industrial era is less revolutionary than evolutionary.

The general phenomenon of progress made in expedience and accuracy in the food and beverage transactional process was and continues to be driven by advances with human and computer interactive technology. This piece is intended to serve as a product agnostic, conceptual introduction that deals directly with how a customer is convinced (i.e., systemically manipulated) via classical conditioning into making transactional changes; from “live” cashiers and waitstaff to electronic intermediaries. This behavioral transition might best be understood within the context of the body of knowledge surrounding consumer choice theory and practice.

While the scale and scope of the comprehensive issues that arise is far too broad to consolidate into a short topical revue, those who find interest with the approached constructs shall find modules of subject consistent citations (i.e., sources from the proverbial horse’s mouth) to reference for further exploration. For example, in reference to the Automat phenomenon noted…

The Automat; References 1:

A) Bromell, N. (2000). The Automat: Preparing the Way for Fast Food. New York History, 81(3), 300-312.

B) Hardart, M., & Diehl, L. B. (2002). Automat: The History, Recipes, and Allure of Horn & Hardart’s Masterpiece: Clarkson N Potter Publishers.

C) Shapiro, L., & Federman, R. (2014). ‘Let’s all go eat at the Automat’: Machines and Miracles in New York City. Paper presented at the Food & Material Culture: Proceedings of the Oxford Symposium on Food and Cookery 2013.

Primary Text

The manner by which one might best understand the likelihood of consumer behavioral transference from the status quo of ordering and being served by wait staff or even “live” cashier to the relative novelty of utilizing self-service technology is via an understanding the applicability of some hospitality choice models; namely, the Theory of Planned Behavior (TPB), the (modified hedonic) Technology Acceptance Model (mhTAM), and the Technology Readiness Index (TRI). While TPB and mhTAM will be recognized, the reader shall find that TRI maintains the “best fit”.

General Background; References 2:

A) Bitner, M. J., Ostrom, A. L., & Meuter, M. L. (2002). Implementing successful self-service technologies. Academy of management perspectives, 16(4), 96-108.

B) Buchanan, N. (2011). An examination of electronic tablet-based menus for the restaurant industry. University of Delaware.

C) Huber, M. M., Hancer, M., & George, R. T. (2010). A comparative examination of information technology usage in the restaurant industry. Journal of Foodservice Business Research, 13(3), 268-281.

D) Kimes, S. E. (2008). The role of technology in restaurant revenue management. Cornell Hospitality Quarterly, 49(3), 297-309. .

E) Law, R., Leung, R., & Buhalis, D. (2009). Information technology applications in hospitality and tourism: a review of publications from 2005 to 2007. Journal of travel & tourism marketing, 26(5-6), 599-623.

F) Oronsky, C. R., & Chathoth, P. K. (2007). An exploratory study examining information technology adoption and implementation in full-service restaurant firms. International Journal of Hospitality Management, 26(4), 941-956

G) Wang, H.-Y., & Wu, S.-Y. (2014). Factors influencing behavioural intention to patronise restaurants using iPad as a menu card. Behaviour & Information Technology, 33(4), 395-409.

H) Zhu, Z., Nakata, C., Sivakumar, K., & Grewal, D. (2007). Self-service technology effectiveness: the role of design features and individual traits. Journal of the academy of marketing science, 35(4), 492-506.

The espouse of intention or planning and observable behavior within an environment (i.e. servicescape) might seem to be almost dichotomous species. Again, not a unique observation of the human condition. Ella Fitzgerald belted out the lyrics in the now song standard, Undecided:

First you say you do

And then you don’t

And then you say you will

And then you won’t

You’re undecided now

So what are you gonna do?

The theory of planned behavior suggests that individuals that plan on or intend for an activity will more-than-likely follow through with a directly correlated responsive behavior; in this case, the adoption of the usage of self-service technologies (e.g., kiosks) to order in a restaurant servicescape.

When all other elements are reduced, the simple concept of consumer convenience is paramount. The question to be posed is whether using a kiosk to order everything from a soda or snack to a full meal, desserts of various sizes included, might be found to be more convenient in terms of allocation of resources than effecting the same results through traditional interactions (e.g. ordering through a cashier or waiter)? The attitude toward transitioning to self-service technology, whether it be perceived ease of use, utility garnered or some other advantage is figuratively how the score is kept on whether kiosks are an admissible technology for adoption by the food and beverage consumer patron base.

Servicescape; References 3:

A) Kim, W. G., & Moon, Y. J. (2009). Customers’ cognitive, emotional, and actionable response to the servicescape: A test of the moderating effect of the restaurant type. International Journal of Hospitality Management, 28(1), 144-156.

B) Wakefield, K. L., & Blodgett, J. G. (1994). The importance of servicescapes in leisure service settings. Journal of services marketing, 8(3), 66-76.

C) Wakefield, K. L., & Blodgett, J. G. (1996). The effect of the servicescape on customers’ behavioral intentions in leisure service settings. Journal of services marketing, 10(6), 45-61.

According to Buchanan, a master’s student completing research on the topic of electronic tablet usage, despite the wide availability of new technologies, Meuter et al. (2003) argue that very little is known about the factors influencing customer usage of technology-based options. Still, for the purpose of this examination into patron behavior, the primary tool of self-service technology is the kiosk.

The implementation of self -service technologies, such as a kiosk, have allowed customers to (euphemistically) “co-produce” or deliver a service for themselves (engage in Ivan Illich’s “Shadow Work”) without assistance from others (Meuter, Bitner, Ostrom and Brown, 2005). With the emergence of fast casual dining (i.e., quick serve), restaurateurs have realized the need to meet customers demand for quality and quick service, as these factors are seemingly important in the retention and loyalty of their customers. The introduction of restaurant kiosks have assisted restaurant operators in facilitating these needs, as customers are given an opportunity to be “co-producers” in the service which may be more convenient to some customers.

Meuter et al., (2000) defines a kiosk as a self-service technology which allows the customer to consume services electronically without direct personal contact. Co-production can be defined as customers‘ participation in the creation and delivery process and it requires meaningful and cooperative contribution to the service process (Auh, Bell, McLeod and Shih, 2007). Co-production gives the customer some level (or at least perception) of control over the outcome of the service experience, and as a result of this; customers may perceive more value from the experience (e.g., utilizing interactive menues).

Yet, innovations are not universally embraced and are accepted or rejected by different groupings with a myriad of timing. This staggered adoption is the whole rasion d’etre grounding the “Bass Diffusion Model” (referring to production) and Roger’s Diffusion of Innovation model (referencing patron adoption).

Figures 1 & 2: Bass Diffusion Model and Roger’s Diffusion of Innovation Curve:

Product Diffusion and Improvement; References 4:

Mahajan, V., Muller, E., & Bass, F. M. (1990). New product diffusion models in marketing: A review and directions for research. The Journal of Marketing, 1-26.

Manos, A. (2007). The benefits of Kaizen and Kaizen events. Quality Progress, 40(2), 47.

Mendoza, E. G. (1991). Real business cycles in a small open economy. The American Economic Review, 797-818.

Rogers, E. M. (2010). Diffusion of innovations: Simon and Schuster.

Time

InnovatorNum

ber

of n

ew a

dop

ters

New Adopters Roger’s Diffusion of Innovation Curve

ImitatorsTipping Point

0

25

50

75

100

Innovators 2.5%

Early Adopters 13.5%

Early Majority 34%

Late Majority 34%

Laggards 16%

Market S

hare %

Technology Adoption Life Cycle must be minded. Before the implementation of various technologies within a restaurant, restaurant operators need to consider the fact that some technology will become obsolete at a rapid rate due to continuous upgrade of technological tools. The lifecycle of technology is similar to that of a product; it experiences the four stages of the product lifecycle that entails the introduction, growth, maturity and declination and of such should be considered before implementation (Beldona, Nusair and DeMicco, 2009).

Individuals will accept technology at different stages of its lifecycle based on individual‘s acceptance and attitudes towards the use of technology. Five segments , known by differing collectivisms, have been identified to group consumers based on the technological acceptance, these segments include —explorers, pioneers, skeptics, paranoids and laggards|| (Parasuraman and Colby 2001).

Customers that are categorized as explorer are expected to enter the market first, once they have entered, the pioneers will follow and accept a technology, it is then that the technology will move to the next phase to be more widely accepted by others. Once restaurateurs understand the concerns of consumers towards technology from these different segments it will be easier for them to implement technology, so it can be accepted by the different market segments (Yen, 2005).

While the introduction of self-service kiosks may assist in meeting the needs (i.e., creating satisfaction and subsequent terms from loyalty) of customers, some customer may experience some level of frustration with the use of kiosks. It is important to identify the sources of satisfaction and dissatisfaction with the use kiosks as customer‘s satisfaction or dissatisfaction is a factor in determining their retention and loyalty to the organization (Markovic, Raspor, & Šegaric, 2010).

In a study conducted by Mueter, Ostrom, Roundtree and Britner (2000), the authors sought to find the sources of satisfaction and dissatisfaction from the use of self-service technologies. Robert Johnston’s Critical Incident Technique (CIT) was used in a study to identify some of the sources associated with the dissatisfaction or satisfaction from the use of self-services technologies.

The authors identified some of the sources of satisfaction were ease of use, saving time, convenience and the avoidance of service personnel. From the study, it was also revealed that some people experienced dissatisfaction from the use of these self-service technologies as a result of technology failure, poor design, service design or customer driven failure. It was also suggested that research be done to find out what motivates an individual to use self –service technologies and how individuals learn their roles to use these technologies.

As noted, according to Pocius (1991) human computer interaction can be defined as a process in which a user and a computer engage in a communication dialogue in order to accomplish a task. Human computer interaction may differ among individuals, as users‘ possess different characteristics. Pocius (1991) and Kumar, Smith and Bannerjee (2004) highlighted that such knowledge may help individuals when designing computer systems to be utilized by individuals from a wide market.

Being characterized as a “service industry,” technology introduced within the restaurant industry is expected to perform the same roles which are normally executed by humans to ensure the service experience matches or exceeds the customers‘ expectations. According to Brown (1988) having knowledge such as this, “systems should be designed in such a manner that they do not require the user to dedicate extensive mental processing to utilize these systems or lead to an increase in service time”. This is so as it may affect customers‘ acceptance and avoidance of technological tool, some customers have openly welcomed and accepted computer technology while others avoid the use of the technology whenever possible (Pocius, 1991). Sharma (1987) identified personality as a vital role in human computer interaction as it not only affects human computer interaction on a task level, but it also helps to determine whether or not humans will use a computer to execute a task. Satisfaction is the antecedent and the catalyst to the continuance of self-service technology utilization.

Not only technology acceptance but a form of Technology Readiness is paramount.To facilitate the adoption of technology within restaurants, it is important for restaurateurs to focus on customers‘ reaction and level of comfort with the technological tool (Dixon, Kimes and Verma, 2009). Restaurateurs have realized properly implemented self-service technology can lead to increased revenue and profit. It also contributes to an increase in speed, improved service and the quality of food provided by the organization (Berry, Seiders, and Grewal, 2002).

The implementation of technology also has potential benefits for customers as it helps in the improvement of customer convenience, increased control (perceived and actual) and improves transactional quality (Kimes, 2009). The customer who is now aware (i.e., “plugged in”) can make an estimation of both the seating and service process (Kimes, 2008). Customers also have a level of control over the dining experience with the involvement of technology such as kiosks and virtual menus as they are able to determine specification of their dishes with the elimination of server errors. Kimes (2008) study also highlighted that technology helps to increase reliability as customers perform the same procedure each time the technology is used, thus a high level of consistency in service is necessary.

While studies have highlighted the potential benefits for the restaurant and the customers from the use of technology, the fact that individual‘s personality affects their technological readiness should be at the forefront of the minds of restaurateurs (Parasuraman, 2000). This is important as the quality of service of a technological tool depends on how the technology is accepted and employed by users. According to Parasuraman (2000) technology readiness is an individual‘s ability to embrace and use a new technology in home and work life (Verma, Victorino, Karniouchina and Feickert, 2007).

Technology readiness focuses on individuals feelings to accept and utilize technologies based on four traits which include; innovativeness, optimism, insecurity and discomfort. Individuals who display traits of optimism in their personality are often seen as positive drivers of technological readiness and they willingly encourage the use and acceptance of new technologies. Optimism trait focuses on the belief that there is increased control, flexibility and efficiency in life as a result of the introduction of technology because they perceive technology as being more useful and easier to use. Persons who display traits of innovativeness has the tendencies to be the first to use the technology or thought of as a technology pioneer (Walczuch, Lemmink, and Streukens, 2007; Verma, Victorino, Karniouchina and Feickert, 2007).

However, traits of discomfort and insecurity can be seen as negative forces as they discourage consumers from even trying out a new technology in order to achieve potential benefits. Individuals with traits of insecurity will distrust technology for security and privacy reasons and also its ability to work properly. While traits of discomfort normally tend to have a need for control and perceive the use of technology as reducing their control level. Furthermore, they may feel a sense of being overwhelmed from the use of technology (Walczuch, Lemmink, and Streukens, 2007). According to Liddle (2005), the restaurant industry has become modernized by the use of information technology. The author stated that it is with this change in the industry, restaurateurs have to constantly measure their overall customer satisfaction to ensure they are meet customers‘ needs. Oliver (1997) posits customer satisfaction can be defined as the customer‘s response based on fulfillment and may also been seen as a judgment that a product or service feature provides the customer with pleasurable level of consumption related fulfillment . Analeeb and Conway (2006) provided another definition for customer satisfaction; they defined customer satisfaction as the overall level of contentment that a customer receives from a service or product feature.

Preece (1993) stated that the goals of Human Computer Interaction (HCI) is to develop and improve systems that include computers so that users are able to execute their tasks in a safe, efficient and effective manner while enjoying the experience. The author also stated that these aspects are communally referred to as usability. In Bedi and Banati (2006) study it was determined that usability can also be referred to as the ease by which a product can be used and learned by a user while providing the user with satisfaction.

Based on the factors which have been identified in several studies, it is evident that the usability of a technology is very important for human computer interaction and may impact the reuse of the technology. Several studies have identified that poor usability can lead to dissatisfaction from the use technology as a result of the inconvenience it presents for users and may also reduce customers intention of reusing the technology (Wotton 2003; Souza, Manning , Goldman and Tong2000; Law and Ngai 2005).

If customers believe that self-service technologies are easy to use, it is expected that they will have a higher level of satisfaction. Thus, the usability of an electronic menu paradigm is an important factor, as it can affect the ordering experience for the guest. Self Service Technology; References 5:

A) Dabholkar, P. A. (1996). Consumer evaluations of new technology-based self-service options: an investigation of alternative models of service quality. International Journal of research in Marketing, 13(1), 29-51.

B) Dabholkar, P. A., & Bagozzi, R. P. (2002). An attitudinal model of technology-based self-service: moderating effects of consumer traits and situational factors. Journal of the academy of marketing science, 30(3), 184-201.

C) Meuter, M. L., Bitner, M. J., Ostrom, A. L., & Brown, S. W. (2005). Choosing among alternative service delivery modes: An investigation of customer trial of self-service technologies. Journal of marketing, 69(2), 61-83.

D) Meuter, M. L., Ostrom, A. L., Bitner, M. J., & Roundtree, R. (2003). The influence of technology anxiety on consumer use and experiences with self-service technologies. Journal of Business Research, 56(11), 899-906.

E) Meuter, M. L., Ostrom, A. L., Roundtree, R. I., & Bitner, M. J. (2000). Self-service technologies: understanding customer satisfaction with technology-based service encounters. Journal of marketing, 64(3), 50-64.

Service Convenience; References 6:

Berry, L. L., Seiders, K., & Grewal, D. (2002). Understanding service convenience. Journal of marketing, 66(3), 1-17. Collier, J. E., & Kimes, S. E. (2013). Only if it is convenient: Understanding how convenience influences self-service technology evaluation. Journal of service research, 16(1), 39-51.

Several theoretical models have been proposed to gain more knowledge on how innovation influences consumer intentions and behavior. Those that appear to have attracted the most attention from researchers include the theory of reasoned action (TRA) (Ajzen and Fishbein, 1980); the theory of planned behavior (TPB) (Ajzen and Madden, 1986); the technology acceptance model (TAM), which is rooted in the TRA (Davis, 1989); and more recently the TRI (Parasuraman, 2000). While the first two of these models are generic, the latter two are specific to technology adoption and use.

The TAM was developed to predict employees’ acceptance of a new technology at work (Davis, 1989) and posits that this is influenced by their beliefs about its usefulness and ease-of-use.

This initial model for TAM was work-related, for example, did computers make a DMV agent’s life more convenient, effective and efficient (as perceived by the DMV worker). The modified hedonic (i.e., personal pleasure seeking) TAM that this paper reviews is based on a leisure (i.e., not-work) perspective of an individual utilizing a technology to enable a better experience than without the employment of said technology.

One might argue that for the consumer who enjoys listening to music, an MP3 player (e.g., Ipad™ or a streaming tool / phone application (e.g., Y(ou)T(ube) Music™), the sonic experience is superior (or at least more convenient) to the prior technological innovations for listening to recorded music (e.g., the portable CD player, the audio cassette deck based “boom box” / Walkman™, or even portable phonograph). Albeit, some stalwart diehards will argue to their death that phonographic Vinyl records remain a superior means of audio-hedonism in terms of maintaining performer intended fidelity. Still, it is pretty difficult to carry a vinyl playing turntable in one’s pocket.

Hui & Bateson, (1991) have indicated in their study that perceived control has had significant positive impact on an individual‘s well-being, both physical and psychological. Yen (2005) also found in a study that an individual‘s perceived control affected the level of confidence they had in a technological tool. It was found that persons reported higher level of confidence benefits from the relationship with a firm when they perceived a better control over self-service technologies than those who felt they had little control.

Customer perception of control over a technology should lead to an increase in their confidence with using the technology. According to Yen and Gwinner (2003), having control leads users to have a greater predictability over the likely outcome of the service experience. The study further highlighted that customers may be more satisfied with the quality of service as they perceive more control over the technology they have to utilize. Yen‘s study (2005) also found that perceived control is critical

and was a determinant for pioneer‘s satisfaction when using self-service technologies. Shamdasani, Mukherjee and Malhotra (2008) have highlighted the importance of perceived control to consumers and have stated that high levels of perceived control will affect the overall adoption of a technology. In Namasivayam and Hinkin (2003) study, the authors have highlighted that when customers feel like they have lost control in a service encounter it may lead to dissatisfaction in the service experience and may also create a variety of negative responses from the customer.

A later extension, the TAM2 (Venkatesh and Davis, 2000), augmented the original model but is subject to some of the same constraints as its predecessor, including, that it also focuses on employee behavior at work as opposed to consumers in the leisure market, of which hospitality is a form. Venkatesh and Bala (2008) developed and tested the TAM3, which is an integrated model of the determinants of individual-level (IT) adoption and use; however, this newer model has also been focused on employees and not consumers and is not directly like mhTAM (Paster, 2016). The superior customer usage evaluation model is the technology readiness index where modifying variables include static demographics (age, gender, race), dynamic variables such as education level attainment, and perspectives / attitudes. By contrast, the TRI (Parasuraman, 2000) is an attitudinal scale that is “individual specific” (Lin et al., 2007). It has been developed to measure “people’s propensity to embrace and use new technologies for accomplishing goals at home and at work” (Parasuraman, 2000, p. 308). The index is a multi-dimensional construct, consisting of four distinct dimensions:

1. optimism: a positive view of technology and a belief that it offers people increased control, flexibility, and efficiency in their lives;

2. innovativeness: a tendency to be a technology pioneer and thought leader;3. discomfort: a perceived lack of control over technology and a feeling of being overwhelmed by

it; and4. insecurity: distrust of technology and skepticism about its ability to work properly.

The first two dimensions are “contributors” to Technology Readiness (TR), while the last two are “inhibitors.” In other words, high levels of the former will boost a person’s overall TRI score whereas high levels of the latter will suppress it. As a result, each individual can be located on a technology beliefs continuum ranging from resistant to receptive on technology.

Lin et al. (2007) incorporated the TRI into the TAM model to propose an integrated technology readiness and acceptance model (TRAM) in the context of adoption of e-service systems. They argue that by integrating individual factors (the TRI approach) with system characteristics of usefulness and ease-of-use (TAM) it may be possible to broaden the applicability of the two models by helping to explain, for example, why the higher the TRI and the lower the TAM score is, the more likely it may be that consumers would adopt new technologies – and vice versa.

Theory of Planned Behavior References 7:

A) Ajzen, I. (1985). From intentions to actions: A theory of planned behavior: Springer.B) Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision

processes, 50(2), 179-211. C) Ajzen, I. (2001). Nature and operation of attitudes. Annu Rev Psychol, 52(1), 27-58. doi:10.1146/

annurev.psych.52.1.27D) Ajzen, I., & Driver, B. L. (1991). Prediction of leisure participation from behavioral, normative, and

control beliefs: An application of the theory of planned behavior. Leisure Sciences, 13(3), 185-204. E) Ajzen, I., & Driver, B. L. (1992). Application of the theory of planned behavior to leisure choice.

Journal of leisure research. F) Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour. G) Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory

and research.

Attitude Toward The Behavior (Ab)

Purchase Behavior (B)

Subjective Norm (SN)

Situational Factors

Figures 3 and 4: Theory of Reasoned Action and Theory of Planned Behavior (TPB)

Theory of Planned Behavior

Attitude

Subjective Norm

Intention Behavior

Perceived Behavioral

Control

Technology Acceptance Model (TAM); References 8:Figure 5: TAM

A) Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.

B) Davis, F. D. (1993). User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International journal of man-machine studies, 38(3), 475-487.

C) King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information & management, 43(6), 740-755.

D) Koivisto, K., Makkonen, M., Frank, L., & Riekkinen, J. (2016). Extending the technology acceptance model with personal innovativeness and technology readiness: a comparison of three models. BLED 2016: Proceedings of the 29th Bled eConference” Digital Economy”, ISBN 978-961-232-287-8.

E) Paster, D. J. (2016). An Application of the Hedonic Technology Acceptance Model (TAM): A Case Study of Online Gaming Adoption in New Jersey.

F) Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision sciences, 39(2), 273-315.

G) Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.

H) Venkatesh, V., Speier, C., & Morris, M. G. (2002). User acceptance enablers in individual decision making about technology: Toward an integrated model. Decision sciences, 33(2), 297-316.

I) Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 157-178.

External Variables

Attitude Towards Using

(A)

Behavior Intention to Use

(BI)

Actual System Use

Perceived Usefulness

(U)

Perceived Ease of Use

(E)

Figure 6: Technology Readiness Index:

Technology Readiness Index References 9:

A) Lam, S. Y., Chiang, J., & Parasuraman, A. (2008). The effects of the dimensions of technology readiness on technology acceptance: An empirical analysis. Journal of interactive marketing, 22(4), 19-39.

B) Liljander, V., Gillberg, F., Gummerus, J., & Van Riel, A. (2006). Technology readiness and the evaluation and adoption of self-service technologies. Journal of Retailing and Consumer Services, 13(3), 177-191.

C) Lin, C. H., Shih, H. Y., & Sher, P. J. (2007). Integrating technology readiness into technology acceptance: The TRAM model. Psychology & Marketing, 24(7), 641-657.

D) Lin, J.-S. C., & Chang, H.-C. (2011). The role of technology readiness in self-service technology acceptance. Managing Service Quality: An International Journal, 21(4), 424-444.

E) Lin, J.-S. C., & Hsieh, P.-l. (2006). The role of technology readiness in customers’ perception and adoption of self-service technologies. International Journal of Service Industry Management, 17(5), 497-517.

F) Lin, J.-S. C., & Hsieh, P.-L. (2007). The influence of technology readiness on satisfaction and behavioral intentions toward self-service technologies. Computers in Human Behavior, 23(3), 1597-1615.

G) Parasuraman, A. (2000). Technology Readiness Index (TRI) a multiple-item scale to measure readiness to embrace new technologies. Journal of service research, 2(4), 307-320.

H) Parasuraman, A., & Colby, C. L. (2007). Techno-ready marketing: How and why your customers adopt technology: The Free Press.

I) Parasuraman, A., & Colby, C. L. (2015). An updated and streamlined technology readiness index: TRI 2.0. Journal of service research, 18(1), 59-74.

J) Rojas-Méndez, J. I., Parasuraman, A., & Papadopoulos, N. (2017). Demographics, attitudes, and technology readiness: A cross-cultural analysis and model validation. Marketing Intelligence & Planning, 35(1), 18-39.

K) Zulkifly, M., Zahari, M. S., Hanafiah, M., Hemdi, M., & Ismail, M. N. (2016). Customers’ technology readiness and customer information satisfaction on tablet-based menu ordering experience. Paper presented at the 3rd International Hospitality and Tourism Conference, IHTC 2016 and 2nd International Seminar on Tourism, ISOT 2016.

Conclusion

Gradual transition is the adaptation / technology adoption process when working with the introduction of kiosks into any commercial, transactional environment. Even with the introduction of kiosk-based mechanisms, the role of the service agent as facilitator remains.

For example, one of the largest roll-outs of customer facing kiosk in a food service environment has been with McDonalds. Yet, the traditional cashier is still needed to complete some transactions such as paying with currency (in lieu of a credit card) and expediting the food to the ordering party. Plus, there are bound to be the technology laggards who will summarily refuse to use kiosks and rather interact, no-matter-how perfunctory, with a human cashier. Thus, kiosks are not necessarily complete replacements for traditional labor but should be understood as supplementing and expanding the defined roles of the present labor force.

The draw of human interaction will simply not be alleviated by kiosks. In the hospitality service industries there are too many opportunities for “moments of truth” or “warm touches” in the service cycle to take the place of patron and server familiarity. One look no further than the nearest neighborhood of business community Starbuck’s™ where standing orders might be assisted by technology, the recognition of the customer and their request for “the regular” will not be completely lost in the immediate future. There has simply been too much conditioning of the barista patron relationship, to borrow a technology term, KYC (Knowing Your Customer). Joe customer could walk into a Starbuck’s™ and enter his exotic order a café au lait, using the dark roast brew, prepared with skim milk and served “kid” temperature, but the reality is that as long as the habitual Joe customer comes in with enough frequency for the barista to recognize him, part of the “reward” for his consistency and loyalty is being assured of being served his favorite drink customized to his specifications without having to interact at all.

Thus, kiosks are best used where there are transactional and not relationship based commercial interactions (i.e., the customer is not a known or “regular”). A source of the resistance to the kiosk technology is the break in human interaction, as perfunctory and purely functional as ordering a preferred coffee concoction might be. On the other hand, the great move to a standardized ordering and subsequent dining experience, beginning with the waiter-less automats, is the patron prerogative via situational options to have minimal interaction with the serving parties (e.g., host, servers, expediters, managers, et cetera). This scenario is where the kiosk option maintains a competitive advantage over traditional ordering means.

Contemporary Case Studies; References 10:

Fredette, S. (2016). How Restaurant Kiosks are Empowering Guests for the First Time. Restaurant Technology.

Johnson, H. (2018). We Ordered from McDonald’s new Kiosks to see if they’re better than real cashiers - and the winner is a surprise. Business Insider.

Olen Kiok. (2017). Why Restaurants Kiosks Work for Customers and Owners.

Morris, C. (2017). How to Cash In on Self-Ordering Kiosks. QSR.

Nichols, G. (2018). Automated kiosks are the future of retail, restaurants, even roach coaches. Robotics.

PYMNTS. (2017). Taking a Bite Out of Smart Self-Serve Kiosk Trend.

PYMNTS. (2018). What the $1B Kiosk Industry Can Do For Hotels and Restaurants.

Westbrooks, A. (2017). 4 Growing Pains of Kiosks in Restaurants. Restaurant Business.

Note

NOTE: Future research on the integration of self-service technology will focus on the choice processes (as per the optics) of behavioral economics and the importance of maintaining authenticity with the interactive computer-human experience.

Behavioral Economics:

FINDING AUTHENTIC EXPERIENCE AND PREFERRED UTILITY

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Oliver, R. L. (2014). Satisfaction: A Behavioral Perspective on the Consumer: A Behavioral Perspective on the Consumer: Routledge..

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Tversky, A., & Kahneman, D. (1989). Rational choice and the framing of decisions: Springer.

Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5(4), 297-323. doi:10.1007/bf00122574

Note

Experiential Authenticity and Forces for Substitution:

Cloud, J. (2008). Synthetic authenticity. Time Web site.(Accessed:).

Curran, J. M., & Meuter, M. L. (2007). Encouraging existing customers to switch to self-service technologies: put a little fun in their lives. Journal of Marketing Theory and Practice, 15(4), 283-298.

Curran, J. M., & Meuter, M. L. (2007). Encouraging existing customers to switch to self-service technologies: put a little fun in their lives. Journal of Marketing Theory and Practice, 15(4), 283-298.

Dean, D. H. (2008). Shopper age and the use of self-service technologies. Managing Service Quality: An International Journal, 18(3), 225-238.

Dixon, M., & Verma Ph D, R. (2009). Customer preferences for restaurant technology innovations.

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Godoe, P., & Johansen, T. (2012). Understanding adoption of new technologies: Technology readiness and technology acceptance as an integrated concept. Journal of European Psychology Students, 3(1).

Kim, J., Christodoulidou, N., & Choo, Y. (2013). Factors influencing customer acceptance of kiosks at quick service restaurants. Journal of Hospitality and Tourism Technology, 4(1), 40-63.

Meuter, M. L., Bitner, M. J., Ostrom, A. L., & Brown, S. W. (2005). Choosing among alternative service delivery modes: An investigation of customer trial of self-service technologies. Journal of marketing, 69(2), 61-83.

Meuter, M. L., Ostrom, A. L., Bitner, M. J., & Roundtree, R. (2003). The influence of technology anxiety on consumer use and experiences with self-service technologies. Journal of Business Research, 56(11), 899-906.

Meuter, M. L., Ostrom, A. L., Roundtree, R. I., & Bitner, M. J. (2000). Self-service technologies: understanding customer satisfaction with technology-based service encounters. Journal of marketing, 64(3), 50-64.

Oliver, R. L. (2014). Satisfaction: A Behavioral Perspective on the Consumer: A Behavioral Perspective on the Consumer: Routledge.

Oronsky, C. R., & Chathoth, P. K. (2007). An exploratory study examining information technology adoption and implementation in full-service restaurant firms. International Journal of Hospitality Management, 26(4), 941-956.

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Pine, B. J., 2nd, & Gilmore, J. H. (1998). Welcome to the experience economy. Harv Bus Rev, 76(4), 97-105.