hotel customer perceptions of biometric door locks: convenience and security factors

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Hotel Customer Perceptionsof Biometric Door Locks:Convenience and SecurityFactorsJungsun (Sunny) Kim a , Pearl Brewer a & BoBernhard aa Hotel Management Department , University ofNevada , Las Vegas, NVPublished online: 11 Oct 2008.

To cite this article: Jungsun (Sunny) Kim , Pearl Brewer & Bo Bernhard (2008) HotelCustomer Perceptions of Biometric Door Locks: Convenience and Security Factors,Journal of Hospitality & Leisure Marketing, 17:1-2, 162-183

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Journal of Hospitality & Leisure Marketing, Vol. 17(1–2) 2008Available online at http://www.haworthpress.com© 2008 by The Haworth Press. All rights reserved.

162 doi:10.1080/10507050801978323

WHMM1050-70511541-0897Journal of Hospitality & Leisure Marketing, Vol. 17, No. 1-2, Jul 2008: pp. 0–0Journal of Hospitality & Leisure Marketing

Hotel Customer Perceptions of Biometric Door Locks: Convenience

and Security FactorsKim, Brewer, and BernhardJournal of Hospitality & Leisure Marketing Jungsun (Sunny) Kim

Pearl BrewerBo Bernhard

ABSTRACT. A biometric indicator is any human physiological feature(e.g. fingerprint) or behavioral feature (e.g. voice) that can be measuredand used for the purpose of automated identification (Nanavati, Thieme,& Nanavati, 2002). This technology has been used in many settingsbecause of its advantages in providing enhanced convenience and secu-rity to users. The purpose of this study is to examine one form of biomet-ric technology, a fingerprint door lock, and to provide an empirical studyof potential advocates and opponents of this application. Using the modi-fied TAM framework, 310 participants were sampled via an in-room TVsurvey system from an upscale hotel in Las Vegas. Findings suggest thatwhile convenience, physical security and data security are key determi-nants for an advocacy group, personal concerns (overall image of

Jungsun (Sunny) Kim is a Doctoral Student, Hotel Management Department,University of Nevada, Las Vegas, NV.

Pearl Brewer, PhD, is Professor, Director of Graduate Studies, HotelManagement Department, University of Nevada, Las Vegas, NV.

Bo Bernhard, PhD, is Assistant Professor, Director of Gambling Research,Hotel Management Department, University of Nevada, Las Vegas, NV.

Address correspondence to: Jungsun (Sunny) Kim, Doctoral Student, HotelManagement Department, University of Nevada, Las Vegas, Box 456013,4505 Maryland Parkway, Las Vegas, NV 89154-6013 (E-mail: [email protected]).

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Kim, Brewer, and Bernhard 163

technology) weigh more for opponents. The results will help operatorsunderstand customer perceptions and opinions of biometrics in a mannerthat can inform key decisions on the potential implementation of thesetechnologies.

KEYWORDS. Biometrics, security, consumer behavior, perceived risk,convenience, lodging

INTRODUCTION

A biometric indicator is any human physiological feature (e.g. finger-print, retina, face, or hand) or behavioral feature (e.g. voice or signature)that can be measured and used for the purpose of automated identification(Nanavati, Thieme, & Nanavati, 2002). This technology has potentiallysignificant convenience and security advantages: for instance, users offingerprint systems would not need to remember passwords or carry keys,and users must place a finger on a reader to be verified (International Bio-metric Group, 2005). Hospitality experts predict that biometrics will playan important role in the future due to reduced costs of the technology andincreased consumer acceptance (Rinehart, 2000). However, while thefuture appears promising for these technologies, from a user perspective,several critical issues still need to be addressed, such as personal privacyconcerns or the potential for physical harm (Most, 2004; Woodward,1997).

The purpose of this study is to examine uses of fingerprint technol-ogy in the hospitality industry and to identify consumer groups thatmight favor or reject these technologies. By using discriminant analy-sis, this study investigates the degree to which certain independentvariables (including convenience, physical security, data security, andpersonal concerns) help differentiate a dependent variable (opinionsabout using a fingerprint door lock). The results will help hotel manag-ers understand customers’ opinions on this new technology, and canultimately inform key decisions on these technologies’ potential imple-mentation.

Perhaps unsurprisingly, given the novelty of these technologies, nopublished research to date has empirically examined hotel customers’ per-ceptions of biometrics. This paper seeks to provide both a seminal currentunderstanding as well as an important foundation for future inquiries inthis new research field.

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164 JOURNAL OF HOSPITALITY & LEISURE MARKETING

OVERVIEW OF BIOMETRICS

Depending on the application context, biometric systems can serve aseither a verification system or an identification system. A verification sys-tem authenticates a person’s identity by comparing a captured biometriccharacteristic with a template pre-stored in a system database (one-to-onecomparison). Verifying financial transactions, assessing online securedata sources and employee entry/exit tracking are examples of this kind ofsystem. This system is generally faster and more accurate than an identifi-cation system, which recognizes an individual by searching the entire bio-metric template database for a match (one-to-many comparison).Importantly, these systems can determine whether a given person ispresent in a database more than once. For example, large-scale publicbenefit programs use these kinds of systems to prevent fraudulent enroll-ment for benefits (M2SYS, 2004; Nanavati, Thieme, & Nanavati, 2002).

Biometric technologies vary depending on which physical or behav-ioral characteristic is measured, such as a fingerprint, face, iris, retina,hand geometry, voice, or signature. Ultimately however, these diversetechnologies work in a similar fashion. A user initially enrolls in a bio-metric system by providing biometric data, such as fingerprints. Usingencryption technology, the raw image of this biometric data is convertedinto a template consisting of a numerical code, and this template is thenstored for the purpose of subsequent comparisons. Most templatesoccupy less than one kilobyte, which allows systems to perform rapidmatching processes. The templates’ small size also allows biometrics tobe stored on devices such as smart cards (Nanavati, Thieme, & Nanavati,2002).

From a privacy standpoint, it is important to note that because of theencryption technology and proprietary templates created by each vendor,biometric data cannot be reconstructed from a biometric template (Chirillo &Blaul, 2003; Maghiros et al., 2006; Most, 2004; Nanavati, Thieme, &Nanavati, 2002). These technologies are also remarkably dynamic: tem-plates are constantly updated each time the user is verified by the system,contributing to a “learning” capability. This capability takes into accountthe fact that biometric characteristics can change subtly over time (AiteGroup, 2006).

The most common biometric technology, and the one that will serve asthe focus of this study, can be found in fingerprint systems. It is estimatedthat 48% of biometric technologies incorporate fingerprints, according tothe International Biometric Group (2005). These systems acquire the

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fingerprint, process the image into a usable format, locate distinctivecharacteristics present in the fingerprint, and create templates for match-ing. Fingerprint ridges and valleys are characterized by discontinuitiesand irregularities known as minutiae – and it is these distinctive featuresupon which most finger scan technologies are based. Specifically, ven-dors utilize proprietary algorithms to map fingerprint minutiae, and thesealgorithms then process these templates to determine similarities betweenthe template of a person and the real fingerprint of the user (Maghiroset al., 2005; Nanavati, Thieme, & Nanavati, 2002; Ratha, Connell, &Bolle, 2001).

The popularity of this technology can be attributed to several factors:nearly every human being possesses fingerprints, fingerprints are distinc-tive, live-scan fingerprint sensors can capture high-quality images, theexisting systems have demonstrated strong performance, fingerprint read-ers have become small and affordable, and the stigma of criminality com-monly associated with fingerprints is shifting in the digitallyinterconnected world (Nanavati, Thieme, & Nanavati, 2002). Further-more, the use of multiple fingerprints, cryptographic techniques, and livedetection make fingerprint systems more challenging to circumvent(Maghiros et al., 2005). Current applications in the service industryinclude ATMs in hotels, electronic lockers in amusement parks, physicalaccess control in airports, and payment systems in school cafeterias orsupermarkets (International Biometric Group, 2005).

The biometric door lock system can conceivably benefit hotel opera-tions in a variety of settings. One potential procedure would involvehotels scanning each guest’s fingerprint at the front desk and then trans-ferring the data directly to the guest door. Hotels would save money onkeycard purchases (from 15 cents to two dollars per card), as well as onlabor costs associated with card dispensing and tracking (Whitford,1999; Pease, 2003). Alternatively, a second scenario might incorporateboth the use of both biometrics and current technology: the front deskencodes each guest’s fingerprint on a keycard or smartcard, and then thekeycard would be used in conjunction with a door scanner that providesa real-time finger read and confirms a match with the fingerprintencoded on the room key. This approach would result in an extra mea-sure of security, and could save processing time and memory because thescanner would not have to search through the entire database. This tech-nique could also provide hotel management with marketing and opera-tional opportunities by increasing the accuracy of the customer database(Whitford, 1999).

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Factors Influencing Customer Attitudes towards New Technology

Customers find themselves engaging a wide variety of new technolo-gies in hotels nowadays. Prominent examples of new technologies havebeen generated from self-service technologies (SSTs), which includeATMs and automated hotel check-outs, as well as more familiar servicesover the internet and television (Meuter, Ostrom, Roundtree, & Bitner,2000). While technology no doubt will continue to influence consumerbehavior in these settings, operators need to understand the nuances ofcustomer perceptions of and attitudes toward new technological options.

Information system research has precisely tackled these issues, propos-ing different models to help interpret these developments. The majority ofmodels are inspired by the Theory of Reasoned Action (TRA) (Fishbein& Ajzen, 1975). Grounded in social psychology, TRA was very importantto other models as it is one of the most fundamental theories of humanbehavior (Venkatesh, 2000). TRA stressed that both attitudes towards aspecific behavior as well as subjective norms pertaining to technologyhave an impact on behavioral intention – which in turn determine actualbehavior (Ajzen, 1991; Ajzen & Fishbein, 1980; Fishbein & Ajzen,1975). This study did not incorporate social norms as a potential attributebecause it was presumed that biometric technologies are too new to beassociated with specific usage norms.

In the technology acceptance model, or TAM (Davis, Bagozzi, &Warshaw, 1989), the model assumed that the perceived ease of use (theextent to which a person believes that using the system will be free ofeffort) and usefulness (the extent to which a person believes that using thesystem will enhance his or her job performance) of the new technologyare fundamental attributes in influencing the individual’s attitude towardusing that system. An individual’s attitude is assumed to influence theindividual’s behavioral intention to use a new technology, which is in turnrelated to the actual use of the technology. In the subsequent TAM2(Venkatesh & Davis, 2000) model, the attitude component was no longerincluded, and subjective norms were restored. Ultimately, because of ourassumptions about relevant norms and because the purpose of this studywas to find attributes that influence individuals’ attitudes toward a biomet-ric door-lock system, we chose to use TAM as the framework for our work.

To further specify our framework, we also applied other studies onself-service technologies. Previous research based on new SSTs revealedthat speed of delivery, ease of use, reliability, accuracy, and additionalbenefits serve as important attributes for potential customers (Dabholkar,

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1996; Meuter, Ostrom, Bitner & Roundtree, 2003). Other studies sug-gested that SST customers expect to receive a higher quality of service byutilizing them (Meuter et al., 2000; Meuter, et al., 2003). At the sametime, previous research also reveals that the perceived shortcomingsassociated with SSTs include process failure (Meuter et al., 2000) anda lack of consumer readiness and receptiveness (Meuter, Bitner, Ostrom, &Brown, 2005).

In sum, previous research has focused on a variety of positives andnegatives associated with the adoption of new technologies in businesssettings. In the next section, we explore research findings more specific tobiometric technologies.

FACTORS INFLUENCING PERCEPTION OF BIOMETRIC DOORLOCKS

Convenience

Biometric door lock systems have already been installed at a handful ofhotels, including the Hotel Palafitte near Lausanne, Switzerland and theNine Zero hotel in Boston, United States. In these settings, a biometricdoor lock can be combined with a hotel check-in system. To illustrate, acustomer could avoid checking-in at the hotel front desk and go directlyto his room once his fingerprint template has been saved in the hotel sys-tem, according to Raphael Henrich who invented the device and isresponsible for biometrics at the Siemens Building Security’s ProductCreation Center in Karlsruhe, Germany (Pease, 2003). Nine-Zero hotel, aluxury hotel in Boston which implemented the first biometric iris doorlock system in the U.S., reported that once customers used the system,they were not only enthusiastic about the technology but also surprised bythe ease of use. The hotel simply sends a room number for an enrolledcustomer’s reservation, hence allowing them to skip the traditional check-in process entirely (Feder, 2004; Grogan 2005).

In sum, TAM and studies of SSTs have found that convenience, ease ofuse, and speed of service are important attributes affecting positive opin-ions about a new technology. More relevant to our purposes, if customersexpect that service will be delivered conveniently by a fingerprint doorlock system, they are more likely to become advocates of this system.Hence, this leads us to our first hypothesis, which we will test later on inthis paper:

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H1: The perceived convenience of a biometric door lock will helpdifferentiate opponents and advocates of this system.

Physical Security

Many proponents expect biometric door lock systems to provideenhanced room security and hotel property security. In fact, motivatedsignificantly by these security enhancements, the general manager of theNine-Zero Hotel decided to install an iris door lock system on its CloudNine penthouse suite and its employee entrance. The general manager ofthe property has indicated that the biometric system proved a very strongsolution to security concerns (Feder, 2004; Findbiometrics.com, 2004). Forproperties that are especially concerned about security methods that areboth effective and convenient, these methods appear to hold substantialpromise. For instance, a biometric door lock can help to establish a detailedrecord of precisely who has had access to guest rooms or other facilities ofthe property at any given time (Creative Vision Electronics, 2004).

Again, because TAM and studies of SSTs suggest that perceived use-fulness and perceived benefits are important contributors to positive opin-ions about a new technology, we expect to be able to measure this todetermine whether this applies in this setting. If customers expect that afingerprint door lock will provide benefits of improved physical securitywithin guest rooms and the hotel property, we anticipate that they willmore likely to be advocates of this system. We have modified thisassumption into a second hypothesis:

H2: The perceived physical security benefit from a biometric doorlock will help differentiate opponents and advocates of this system.

Data Security

Perhaps the most contentious debate over biometrics revolves aroundprivacy and data security. Some critics envision a world in which biomet-ric information is integrated with massive centralized databases designedto track and monitor their every move (Nanavati et al., 2002). These con-cerns can lead to real-world hesitation on the part of hotel management toembrace the technology. For instance, a marketing supervisor ofVingCard, a hospitality door lock vendor, explained that customer distrustof biometric data retention is the most challenging obstacle to the marketingof biometric products (Personal communication, October 10, 2005).

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These are not mere speculations: when Caesars Palace in Las Vegasannounced that it would take advantage of the opening of its newest towerin 2005 to roll out new technologies, including biometric keys, the hotelultimately backed off due to these very concerns. Despite several substan-tial expansions in the property, Caesars eventually canceled the deploy-ment of biometric door locks, citing “Big Brother” fears (Miller, 2005).

In reality, despite these fears, the prospects for this technology may notprove so threatening. Biometrics can provide a key to lock information insuch a way that only the rightful owner has the ability to unlock it. In fact,this new technology may even be superior to older ones: biometrics canalso generate an audit trail that may prevent unauthorized access and usein a way not previously possible. Because of its massively integrateddatabases, it is important to recognize the potential to create a surveil-lance society that finds itself at odds with personal liberties. However, itis important to note that it is not biometric technology that makes thisdangerous – rather, it is the database linking itself. In sum, it appears pos-sible to apply this technology in such a way that the privacy of the indi-vidual who supplies the biometric data is actually greater than ifbiometrics were not used at all (Most, 2004).

Improvements in data security will presumably provide a unique bene-fit that customers can receive while using biometrics. If customers expectthat a fingerprint door lock system will function to protect them fromidentity theft and to keep their privacy safe, it follows that they will morelikely be advocates of this system. This leads us to our third hypothesis:

H3: The perceived data security benefit from a biometric door lockwill help differentiate opponents and advocates of this system.

Personal Concerns

Other critics express concerns that are more basic and personal whenencountering biometric technology. For some, there may be an inherentdiscomfort felt when interacting with biometric technology. These feel-ings of discomfort may stem from cultural, religious, or personal beliefs(Nanavati, Thieme, & Nanavati, 2002).

For instance, cultural objections might reflect concerns about stigmaand/or dignity. To cite a potentially glaring example, Simon Davies ofPrivacy International claims that it is no accident that biometric systemsare being tried out most aggressively with welfare recipients, arguing thatthe recipients are in no position to resist the State-mandated intrusion.

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Interestingly, in the 1995 GAO Report on the use of biometrics to deterfraud in the nationwide Electronic Benefit Transfer (EBT) program, theU.S. Department of the Treasury expressed concerns about how fingerimaging would affect the dignity of the recipients, calling for further test-ing and study. To be sure, these arguments against the use of biometricswith the less privileged classes have a strong rational and emotionalappeal (Woodward, Orlans, & Higgins, 2003).

In terms of religious objections, several religious groups criticize bio-metrics on the grounds that individuals are forced to sacrifice a part ofthem to the (godless) State. For example, in observing that “the Bible saysthe time is going to come when you cannot buy or sell except when amark is placed on your hand or forehead,” fundamentalist Christian PatRobertson places his doubts firmly in a foundation of sacred scripture.What is more, at least one religious group has complained that the handgeometry devices used by California were creating “the mark of thebeast” on enrollees’ hands (Woodward, 1997). Certainly, in jurisdictionswhere religious voices are expressed vociferously, even a small numberof people with religious objections can be difficult to ignore (Woodward,Orlans, & Higgins, 2003).

Biometrics also receive criticism on the grounds that a biometric identi-fier is nothing more than a biometric-based branding or a high-tech tattoo-ing. Certainly, there is an understandable stigma associated with the forcedbranding and tattooing of human beings. This concern is often based upon asophisticated knowledge of history: branding was used as a recognitionsystem to indicate property rights in human slaves in the eighteenth andnineteenth centuries, and tattooing was used by the Nazis to identify con-centration camp victims (Woodward, Orlans, & Higgins, 2003).

Once again, we recall that the literature suggests that a lack of con-sumer readiness can explain much of the failure to try new technologies,and that customers will be reluctant to try a technology if they perceive noclear benefit to using it (Meuter et al., 2005). On the other hand, if cus-tomers see personal detriments associated with new technologies, theypresumably would be less inclined to embrace them. This leads us to ourfourth hypothesis:

H4: The perceived personal concerns with a biometric door lockwill help differentiate opponents and advocates of this system.

To summarize, based upon our interviews with biometric vendors,hotel managers and scholars, upon previous studies of customer behavior

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toward new technologies, and upon other studies of biometrics, wepresent Figure 1 as a theoretical framework for the empirical research pre-sented in this paper.

MEASUREMENT AND ANALYSIS DATA AND MEASUREMENT

To subject this model to empirical inquiry, the research team con-ducted a survey of U.S. hotel customers – specifically, those staying at anupscale casino hotel located on the Las Vegas Strip. To examine the char-acteristics of the sample in this study, the profile of the sample was com-pared to that of 2005 Las Vegas visitors (see Appendix 2) (Las VegasConvention and Visitors Authority, 2006). The questionnaire consisted ofpresumed factors influencing customers’ perception toward a fingerprintdoor lock: convenience (speed of service and personal convenience),physical security (specifically room and hotel property security), datasecurity (protection from identity theft and protection of personal pri-vacy), and personal concerns (based upon cultural, religious, or physicalharm-based reasons).

First, we conducted an interactive pilot test with 50 graduate studentsat the University of Nevada, Las Vegas to refine the validity and readabilityof the questionnaire. The upscale hotel accepted the final survey proposal,

FIGURE 1. Theoretical framework: Perceptions of using fingerprintdoor locks.

Perceptionsof using

fingerprintdoor locks

Convenience- Speed of service- Personal convenience

Physical Security- Property security- Personal room security

Data Security- Protection from identity theft- Unconcern for privacy

Personal Concerns- Uncomfortable feeling- Concerns about physical harm

•TAM

•SST

•Biometrics Advocates

Opponents

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and suggested its implementation via the in-room TV survey system. Thesample ultimately consisted of customers who visited the hotel propertyfrom March 10, 2006 through March 31, 2006. When a customer turnedon the TV in a guest room, the screen showed eight options, including thefamiliar movie selections as well as ‘Guest Services.’ When the customerselected the ‘Guest Services’ menu, the next screen displayed threeoptions: (1) Show Bills, (2) Express Check Out; and (3) Guest Survey. Ifthe customer selected the ‘Guest Survey’ menu, the cover letter of thequestionnaire was shown on the screen and the customer had an option toproceed or to exit the survey. During the time period of the survey, a totalof 314 hotel guests opted to complete the questionnaire.

ANALYSIS

The data were entered and analyzed in SPSS (Statistical Package forthe Social Sciences) version 14.0. Editing was conducted for consistency(e.g. eliminating incorrect sampling unit) and for completeness (e.g. itemnonresponse). Data was then coded into SPSS: “strongly disagree” wascoded as number 1, “disagree” as number 2, “neither agree nor disagree”as number 3, “agree” as number 4, and “strongly agree” as number 5. Weshould note that in the questionnaire, question number 6 – “I have privacyconcerns about using biometric door-lock systems” – was a negative sen-tence. Thus, the order of the answers for this negative sentence wasreverse-coded so that the codes could reflect the same directions as thepositive statements’ codes. Demographic factors were coded in a numberformat: for example, male was coded as number 1, and female as number2. Finally, error checking was completed to make sure that all codes werelegitimate. When compared with the general profile of Las Vegas visitors,the profile of participants reveals a more male, younger, and highlyeducated sample (see Appendix 2).

First of all, an exploratory factor analysis was performed to see if thetested variables fall under any of the factors, or independent variables. Ifthe Kaiser-Mayer-Olkin (KMO) measure of sampling adequacy is closeto 1, it means that the variables are linearly related. The overall KMOmeasure was 0.718 (Table 1), indicating that it is reasonable to go aheadwith the factor analysis (Norušis, 2005).

With Principle Component Analysis, total variance explained by eachfactor was calculated in Table 2. For example, Factor 1 has a variance of3.4, which is 42.5% of the total variance of 8. The cumulative percentage

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column shows that about 83% of the total variance is explained by thefirst four factors. Some suggest that only factors that account for variance(Eigenvalue) greater that 1 should be included, but Norušis (2005)explained that this is not the best strategy when the Eigenvalue is close to 1.Thus, we kept Factor 4, which showed an Eigenvalue of 0.908.

To make factors easy to interpret and to achieve a simple structure, weapplied the Varimax rotation method. Table 3 shows a correlation matrixbetween the four factors and the eight variables. Each factor has largeloadings in absolute value for only some of the variables (Norušis, 2005).This table identifies the first factor as property security attributes: safetyof hotel property and safety of hotel room. The next set of variablesdefine a convenience factor: faster service and personal convenience. Thethird factor could be labeled as data security: protection from identifytheft and unconcern for privacy. The last set of variables defines a per-sonal concern factor: uncomfortable feeling and concern for physicalharm.

The reliability of component items for the four independent variableswas measured via a reliability analysis on SPSS 14.0, and the Cronbach

TABLE 1. KMO and Bartlett’s test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.718

Bartlett’s Test of Sphericity Approx. Chi-Square 938.010Df 28Sig. 0.000

TABLE 2. Total variance explained

Component (Factor) Initial Eigenvalues

Total % of Variance Cumulative %

1 3.400 42.501 42.5012 1.282 16.023 58.5243 1.067 13.338 71.8624 0.908 11.351 83.2145 0.438 5.478 88.6926 0.359 4.487 93.1797 0.315 3.938 97.1168 0.231 2.884 100.000

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alpha values ranged from 0.710 to 0.858 (see Table 4). This indicated thatall variables had acceptable alpha values, as values greater than 0.70 areacceptable (Nunnally, 1978, p. 245).

Discriminant analysis on SPSS 14.0 was employed to investigate thedegree to which the independent variables (convenience, physical secu-rity, data security, and personal concerns) could discriminate a dependentvariable (customer perception of using a biometric door-lock). To meetthe requirement of this technique, five numerical values for the dependentvariable (responses to the survey question: “I would like to use a biomet-ric door-lock in a hotel”) were recoded into two groups as indicatedbelow. The ungrouped cases were excluded from the analysis, whichreduced the sample size from 314 to 249.

• 1 = strongly disagree, 2 = disagree → “Group 1 = opponents”• 4 = agree, 5 = strongly agree → “Group 2 = advocates”• 3 = neither agree nor disagree → “Ungrouped” (excluded from

analysis)

TABLE 3. Rotated component matrix

Component (Factor)

1 2 3 4

Faster service 0.198 0.851 0.218 −0.104Personal convenience 0.192 0.886 0.097 −0.098Safety of hotel property 0.898 0.212 0.144 −0.094Safety of hotel room 0.897 0.186 0.116 −0.170Protection from Identity thefts 0.236 0.197 0.857 −0.041Unconcern for Privacy 0.033 0.113 0.866 −0.257Uncomfortable feeling −0.151 −0.189 −0.116 0.843Concern for Physical harm −0.093 −0.012 −0.151 0.872

TABLE 4. Reliability analysis

Variables Alpha value

Convenience items 0.810Property security items 0.858Data security items 0.726Personal concerns items 0.710

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For validation of the discriminant results, the sample was divided intotwo parts. To split the sample into approximately even groups, a randomsampling procedure was applied. This is the most general practice forsplitting samples in a discriminant analysis (Hair, Black, Babin, Anderson &Tatham, 2006). The first sub-sample, the analysis sample, was used inconstructing the discriminant functions (Opponent group = 34, Advocategroup = 87, and Total = 121). The second sub-sample, the holdout sample,was used to test the discriminant functions and to construct a classifica-tion matrix (Opponent group = 33, Advocate group = 95, Total = 128).The two group sizes of 34 and 87 in the estimation sample exceeded theminimum size of 20 observations per group. The purpose of utilizing aholdout sample is to see how well the discriminant function works on asample of observations not used to derive the discriminant function (Hairet al., 2006).

According to Norušis (2005), the assumptions necessary to check priorto performing discriminant analysis are: (1) equality variance, (2) multi-variate normality, (3) multicollinearity, and (4) outliers. Equality variancewas checked by Box’s M test of equality of covariance matrices. In spiteof a small significant value (sig. = 0.046 < 0.05), the violation was notconsiderable due to the large sample size. Stem-and-leaf plots were usedfor examining normality of independent variables. Although the data wasskewed, discriminant analysis is robust to violations of this assumption.Drawing a scatterplot matrix among independent variables checked multi-collinearity, and no linear relationship among the variables was found.Finally, boxplots helped check for outliers, and no such data were found.

In Table 5, the overall canonical discriminant function was significant,with Wilks’ Lambda = 0.544 and χ(4) = 71.295 (p = .000). This indi-cated that the null hypothesis – that an opponent group and an advocategroup of biometrics have the same average discriminant function score inthe population – could be rejected.

The values in the tables “Structure matrix” and “Functions at groupcentroids” (Tables 6 and 7) indicated that the “data security” factor was themost helpful to differentiate between an opponent group and an advocate

TABLE 5. Wilks’ Lambda

Test of Function(s) Wilks’ Lambda Chi-square df Sig.

1 0.544 71.295 4 0.000

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group, followed by the “Convenience”, “Physical security”, and “PersonalConcerns” factors respectively (Table 6). The negative value (−0.435)in “Personal Concerns” is the closest value to the Group 1 Centroid value(−1.453), indicating that this factor has an influence on negative views ofusing biometric door locks. The other factors showed positive values in the

TABLE 6. Structure matrix

Function

1

Data security factor 0.850Convenience factor 0.599Physical security factor 0.477Personal concerns factor −0.435

TABLE 7. Functions at group centroids

acceptance_recategorized1 Function

1

Group 1 (Opponents) −1.453Group 2 (Advocates) 0.568

TABLE 8. Classification results

acceptance_recategorized1

Predicted Group Membership

Total

1.00 2.00

Cases Selected Original Count Group 1 (Opponents) 28 6 34Group 2 (Advocates) 14 73 87

% Group 1 (Opponents) 82.4 17.6 100.0Group 2 (Advocates) 16.1 83.9 100.0

Cases Not Selected

Original Count Group 1 (Opponents) 31 2 33

Group 2 (Advocates) 15 80 95% Group 1 (Opponents) 93.9 6.1 100.0

Group 2 (Advocates) 15.8 84.2 100.0

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structure matrix, indicating that these factors have an impact on positiveperceptions of biometric door locks (Table 7).

Finally, the table of “Classification results” (Table 8) showed the “hitratio” for both the analysis and the holdout samples. The overall percent-age correctly classified (or hit ratios) for the analysis sample was 83.5%(Opponents = 82.4% and Advocates = 83.9%), and for the holdout samplethe percentage was 86.7% (Opponents = 93.9% and Advocates = 84.2%).This indicates that the classification was highly accurate. The precision ofcorrect classification was acceptable and the hypothesis that thoseindependent variables will classify opponents and advocates was henceconfirmed.

CONCLUSION

Our hypotheses were concerned with determining whether the four fac-tors examined (data security, convenience, physical security, and personalconcerns) classified customers into groups based upon their perceptionsof fingerprint door locks. The confirmation of this hypothesis implied thatcustomers who expected increased convenience, physical security, anddata security from biometrics would be advocates for a fingerprint doorlock. In addition, this implied that customers who did not expect thesebenefits and those who expected increased personal concerns would beopponents. Notably, not all factors were equally influential: the data secu-rity factor was the most helpful to classify these two groups, followed bythe convenience factor, the physical security factor, and the personal con-cerns factor.

The findings of this research study can assist hospitality managers in sev-eral practical ways. For instance, if one assumes that the business advan-tages of these technologies are significant, a variety of strategies might beimplemented. By focusing on the important and influential factors outlinedhere, hotel management can develop practical strategies to increase custom-ers’ positive perceptions toward a fingerprint door lock system.

To illustrate, data security turned out to be the most significant factor.Hence, hotel management might develop strategies to persuade customersto use biometric systems by emphasizing the benefits that these technolo-gies would provide in terms of increased data security. To achieve this, ahotel might advertise newly installed biometric door locks at the property– and highlight them as a component of their commitment to increaseddata security in an increasingly uncertain world of identify theft. Ads or

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brochures might educate consumers about the basic process of biometricsto demonstrate that this technique has a real advantage in protecting cus-tomers’ identities.

On the other hand, this study suggested that personal concerns, such asfear of physical harm, have a measurable negative effect on the hotel cus-tomers’ opinions about a fingerprint door lock. As a result, hotel operatorshave to be ready to answer customer concerns and to allay broader cus-tomer fears about the technology. Specifically, they should be able toexplain that there is no documented physical harm from biometrics, andthat feelings of discomfort are common (but often fleeting) with newtechnologies generally (Woodward, 1997). In a similar fashion, hotelemployees should be poised (and trained) to deal with religious or culturalobjections, as well as other personal concerns.

Limitations and Recommendations for Future Research

Since this is the first empirical study seeking to classify hotel customersbased on their perceptions of biometrics, replication studies should con-tribute to greater refinement of these findings. Conducting this study witha different sample would assist in establishing the applicability of theseresults in other settings. To be sure, Las Vegas is a unique tourist destina-tion, and the survey was limited to one upscale casino hotel on theLas Vegas Strip. This research model can also be applied in different hos-pitality sectors (e.g. restaurants or casinos) with different biometric tech-niques (e.g. an iris door lock) or with different applications (e.g. a biometrickiosk system). Finally, this study has all of the weaknesses of any surveyinstrument, including biases such as nonresponse error, response bias, orextremity bias. Other, more qualitative methodologies might well helpexplore nuances that are missed in this quantitative approach.

In conducting this research, one potential future research directionleapt to mind. Because the demographic factors of this sample are similarto the characteristics of “early adopters” of new technologies (Rogers,1983), further research might explore this group’s role as opinion leadersfor other potential adopters. While we used a discriminant analysis toreduce bias in prediction, bias might result from the homogeneity of thissample. As such, future research with broader samples might employ amultiple regression analysis to predict which factors contribute to differ-ent acceptance levels. Finally, as so often happens with new technologies,the dynamics of ongoing customer adaptation patterns should prove to bemost interesting to track in a longitudinal fashion.

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APPENDIX 1. COVER LETTER & QUESTIONNAIRE

This is a survey for a research project on biometric systems, conducted by agraduate student at University Nevada, Las Vegas (UNLV). A biometric systemis an automated technique of measuring a physical characteristic of an individualand comparing that characteristic to a database for purpose of recognizing thatindividual (e.g. fingerprint). Hotels have recently started using biometrics toenhance security and convenience for customers. The purpose of this survey isto measure customers’ intention to use a biometric fingerprint door lock in orderto deploy the system more effectively.

You are being asked to participate in the study because you are a hotelcustomer and at least 21 years of age. You will be given some questions onthe TV screen. It will take about 5 minutes to complete the questions. Theremay not be direct benefits to subjects as a participant in this study. However,when the hotel deploys biometrics based on the research results, participantswill receive benefits of the most appropriate biometric applications in thehotel.

This study includes only minimal risks. You may feel uncomfortable whenanswering some questions (e.g. demographic questions). Your participation isvoluntary. You may refuse to participate in this study or in any part of this study.The UNLV may not provide compensation or free medical care for an unantici-pated injury sustained as a result of participating in this research study. Youranswers will be kept confidential. No reference will be made in written or oralmaterials that could link you to this study. All records will be stored in a lockedfacility at UNLV for 3 years after completion of the study. After the storage time,the information gathered will be destroyed.

If you have any question or concerns about the study, you may contact studentinvestigator (Jungsun Kim) or principal investigator (Dr. Pearl Brewer). Forquestions regarding the rights of research subjects, any complaints or commentsregarding the manner in which the study is being conducted, you may contact theUNLV Office for the Protection of Research Subjects.

Thank you for your time and consideration. Your participation is greatlyappreciated.

* The following questions pertain to your opinions about a biometric fingerprintdoor lock. Please indicate the degree to which you agree or disagree with thefollowing statements.

Continue Exit

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1. A biometric fingerprint door lock will give me faster service (e.g.faster access to my room).Strongly disagree� Disagree�

Neither agree nor disagree� Agree� Strongly agree�

2. A biometric fingerprint door lock will provide me with more per-sonal convenience than a keycard lock (because there is no key tocarry or to lose).Strongly disagree� Disagree�


3. A biometric fingerprint door lock will keep the hotel propertymore secure.Strongly disagree� Disagree�


4. A biometric fingerprint door lock will keep my room more securethan a keycard lock.Strongly disagree� Disagree�


5. A biometric door lock system will protect me from identity thefts(because fingerprints are encrypted and stored in a safe way).Strongly disagree� Disagree�


6. I have privacy concerns about using a biometric door lock system.Strongly disagree� Disagree�


7. Using a biometric door lock would make me personally uncom-fortable.Strongly disagree� Disagree�


8. I worry that biometrics will cause me physical harm.Strongly disagree� Disagree�


9. I would use a biometric door lock in a hotel.Strongly disagree� Disagree�


*The following questions are asked for demographic purposes.

10. What is your gender? Male � Female �11. What is your age? Under 29 � 30–41 � 42–51�

52–60 � Over 60�

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12. What type of hotel do you usually stay in? Upscale� Mid-range� Economy�

13. What is the purpose of majority of your trips? Business � Leisure � Other �

14. What is the highest level of education you have completed?15. Some high school � High school graduate �

Some college� Collegegraduate �

APPENDIX 2. COMPARISON OF SAMPLE AND 2005 LAS VEGAS VISITORS

Sample % 2005 Las Vegas Visitors %

GenderMale 67 51Female 33 49

AgeUnder 29 28 1330–41 33 20 (30–39)*42–51 25 21 (40–49)*52–60 9 20 (50–59)*Over 60 5 26 (Over 59)*

Purpose of TripsBusiness 49 17Leisure 38 78Others 13 5

EducationSome high school 5 23High school graduate 11Some college 25 29College graduate 59 44

Type of HotelUpscale 42 34Mid-range 53 45Economy 5 17

Total 314 3600

*The Age category in the survey of Las Vegas Visitor was slightly differentfrom that of sample.

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hotel customer perceptions of biometric door locks: convenience and security factors

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