Service Innovation and Customer Choices in the Hospitality Industry 
Liana Victorino, University of Utah 
Rohit Verma, University of Utah 
Gerhard Plaschka, DePaul University 
Chekitan Dev, Cornell University 
Purpose: The purpose of this paper is to understand the impact service innovation has 
on customers’ choices within the hotel and leisure industry. The paper also discusses the 
influence of the creation of new services on both service development and operational strategy. 
Design/methodology/approach: The analysis is based on a national survey of 
approximately 1,000 travelers in the United States, using a web-based data acquisition 
approach. The travelers are segmented by reason of travel (business or leisure), and discrete 
choice analysis is applied to model customer preferences for various hotel service innovations. 
Findings: Overall, the study finds that service innovation does matter when guests are 
selecting a hotel, with type of lodging having the largest impact on a customer’s hotel choice. In 
addition, service innovation is found to have a larger influence on choices when guests are 
staying at economy hotels rather than mid-range to up-scale hotels. Also, leisure travelers were 
found to be more influenced by innovative amenities such as childcare programs and in-room 
kitchenettes than business travelers. 
Practical implications: The understanding of customers’ choices allows managers to 
better design their service offerings and formulate corresponding operational strategies around 
customer needs. 
Originality/value: This paper examines the addition of innovation to the hotel service 
concept and is an excellent tool for managers deciding on which innovations to implement. 
Keywords: Innovation, Service industries, Hospitality services, United States of America, 
Customization  
Paper type: Research paper 
Introduction 
Customers, in a number of industries, are constantly bombarded with run-of-the-mill product 
and service offerings. As a result, customers both desire and more often demand innovative 
alternatives. In response, many service-oriented firms are striving to integrate novel features into their 
product-service offerings. Even product-oriented firms have noted the benefits of adding service 
innovation to their business strategies. For example, during recent years, IBM, a predominantly product-
oriented firm, generated over half of its total revenue from services. Yet, only 15 percent of IBM’s 
research and development budget was being allocated to services (Fitzgerald, 2005). Realizing this 
discrepancy, IBM recently realigned its strategy and business plan emphasizing service-based 
innovations. The new strategy was a resounding success. With one of IBM’s innovative service programs 
adding over $300 million to last year’s total revenue (Fitzgerald, 2005). 
The benefits of service innovation are apparent. What is not as clear is how managers should 
decide on which innovations to implement. In some cases, innovative service offerings are necessary 
just to maintain a firm’s current market share. This phenomenon suggests “. . . that some innovations 
may merely raise the cost of doing business without a significant economic benefit, other than to 
preserve current business and without providing a competitive edge . . . ” (Reid and Sandler, 1992). 
However, other innovations may enhance service differentiation and induce financial gains. Thus, it is 
important for managers to implement innovations which are not only desired by customers but also are 
economically beneficial to the firm (Reid and Sandler, 1992). 
Hospitality firms, such as hotels, are an ideal example of a market which could benefit from the 
implementation of service innovation. First, from a customer’s perspective, the hospitality market is 
perpetually inundated by many similar, often easily substitutable service offerings. This can cause 
difficulties for hotel managers as they attempt to differentiate an individual hotel from its competitors 
(Reid and Sandler, 1992). One solution to this challenge may be to offer new and innovative features to 
customers. Secondly, the hospitality industry is rapidly changing due to accelerations in information 
technology (Olsen and Connolly, 2000). Managers will need to make proactive changes which focus even 
more intensely on customer preferences, quality, and technological interfaces in order to stay 
competitive in such a dynamic environment (Karmarkar, 2004). Thirdly, travelers today do not exhibit, as 
in past decades, a truly brand loyal behavior. Travelers instead are choosing to patronize hotels that 
offer the best value proposition under existing budgetary constraints. (Olsen and Connolly, 2000). In 
order to add value to the guests’ experience, hotel managers and marketers must meet the challenge of 
determining which services are preferred by hotel guests (Olsen and Connolly, 2000). Once a manager 
understands customers’ preferences, the challenge then becomes prioritizing those preferences which 
add the greatest value to the hotel’s existing service offering. 
The purpose of this study is to explore customer tradeoffs for service innovation. The paper will 
examine the addition of innovative offerings and its relation to the hotel’s core service concept. The 
service concept encompasses both the “how”, in other words, the operations content, and the “what”, 
the marketing content, of service design as well as the integration of the two (Goldstein et al., 2002). In 
other words, we will examine the innovative service preferences of hotel guests, while also exploring 
how these preferences align with the strategic intent of the firm. Aligning customer preferences with 
operational strategy is important because operational constraints make it impossible to implement all 
options of innovative service offerings. Instead, hotel managers need to develop an understanding of 
market preferences prior to the addition of new services. This type of knowledge will enable managers 
to select innovative offerings that are most beneficial to the firm and that will truly have an impact on 
customer’s choices. 
The importance of studying innovation’s role in services seems obvious. Yet, analysis in service 
innovation research is lacking in comparison to product innovation research (Chesbrough, 2004). 
Research which examines the opportunities and risks specific to service innovation as well as the choice 
sets for system design is needed to further the knowledge in service innovation research (Chesbrough, 
2004). In this paper, we provide insight into service innovation by exploring the hotel preferences of 
both business and leisure travelers. We specifically aim to: 
(1) Understand the trade-offs made for business and leisure travelers when choosing a hotel, in 
terms of innovative hotel market drivers or attributes. 
(2) Explore the influence the addition of innovative services has on the design of the core 
service concept. 
(3) Examine the impact of innovative service preferences on operational strategy formulation. 
We believe that achieving these objectives will be beneficial to academics and practitioners 
when considering the impact service innovation has on a given firm’s core concept. The structure of the 
paper is organized in the following manner: first, we give a general overview of the previous research 
regarding the service concept and innovation value. Next we discuss the current hotel innovations that 
pertain to our study. We then describe our research methods and the application of discrete choice 
modeling. In addition, we discuss the tradeoffs made by business and leisure travelers when selecting a 
hotel. We conclude by providing insights into service concept development as well as operational 
strategy formulation. 
Background 
The Service Concept 
The wide array of research related to service innovation has primarily focused on the definition 
of the “service concept” (Goldstein et al., 2002). Edvardsson and Olsson (1996, p. 149) defined the 
service concept as a “prototype for service, covering the needs of the customer and the design of the 
service”. Previous research has discussed the critical role of the service concept in service design and 
development (Edvardsson and Olsson, 1996). Furthermore, Goldstein et al. (2002) propose that the 
service concept is the missing key element in service design research. They suggest that the service 
concept integrates the “how” and “what” of service design while keeping both the customers’ needs 
and strategic intent of the firm in mind. In other words, the service concept gives a detailed description 
of what the customer needs and how the organization will deliver the service (Figure 1). 
The conceptual background of the “service concept” in operations management literature is 
similar to “marketing concept”. The marketing concept is the key to achieving organizational goals and 
involves “. . . determining the needs and wants of target markets and delivering the desired (customer) 
satisfactions more effectively than competitors . . . ” (Agarwal et al., 2003, p. 68). Firms that are 
considered to be market-oriented are presumed to have the capability of understanding their customers 
better than their competitors. Innovation plays an important role in the marketing concept because it 
gives the service firm the ability to stay ahead of its competitors through new market offerings. The 
association between innovation and the market-orientation of a firm was determined to be both 
positive and significant (Agarwal et al., 2003). In other words, a more market-oriented firm is more likely 
to consider innovation, which ultimately leads to superior firm performance (Agarwal et al., 2003; Han 
et al., 1998). The relationship found between innovation and market orientation emphasizes the 
importance of identifying customers’ needs. By understanding customer tradeoffs, service firms will 
have a better market orientation with a resulting improvement in firm performance. 
 
Figure 1. Service concept (Source: Goldstein, Johnston, Duffy, and Rao 2002) 
Innovative Value Strategy 
Managers when reexamining their existing service offering also need to decide which 
innovations will create value. For example, managers must ask themselves, which innovations not only 
deliver additional value to their customers but also are economically viable to the firm. Customer value 
can be defined as, “the customer’s perception of what they want to have happen in a specific-use 
situation, with the help of a product and service offering in order to accomplish a desired purpose or 
goal”. (Stahl et al., 1999, p. 53). The hospitality industry has an abundance of options which to choose 
from, when determining which products and services will add value for their customers. For example, a 
hotel operator can offer various combinations of traditional value drivers such as price, location, and 
typical hotel amenities, such as pool or work-out facilities. On the other hand, new and innovative value 
drivers could be offered which include features such as online reservations, in-room high-speed internet 
access, customization of room décor, and flexible check in/out policies. Before introducing a new service 
innovation, hotel managers need to assess the value that it will bring to their customers. 
A good understanding of value can be gained through empirical research methods, such as 
customer surveys. Survey research relies heavily on a customer’s perception of the functionality, 
performance, and worth of a supplier’s offerings (Anderson and Narus, 1998). By acquiring the vital 
information of why guests choose to stay at particular hotels, hotel managers are better able to 
understand the attributes which drive guest’s purchasing decisions. Furthermore, understanding the 
guest’s needs and desires is invaluable when determining methods for improving company image. A lack 
of customer preference understanding leads to problems in both product and service design (Schall, 
2003). Research shows that the most successful companies are the ones which are fully aware of 
customer preferences and develop their services in line with targeted market needs (Karmarkar, 2004). 
As a competing service firm, it is essential to not only consider the types of innovative attributes 
to offer but also which operational strategy must be implemented to achieve the firm’s goals. Kim and 
Mauborgne (2000) coined the term “value innovative logic” which differs from a more conventional 
approach. The conventional objective is to maximize the value of industrial bound offerings while the 
value innovative goal is to aid the innovative aspect of the service offering (Kim and Mauborgne, 2000). 
Our research focuses on the value innovation logic for product and service offerings. Therefore, rather 
than taking a more traditional approach in determining which product and services to offer, an 
innovative logic approach presents options, “. . . in terms of the total solution customers seek, even if 
that takes the company beyond its industry’s traditional offerings” (Kim and Mauborgne, 2000, p. 106). 
Innovations in Hospitality Firms 
Hotel Type 
The emergence of “boutique” hotels during recent years is an excellent example of an 
innovative offering in an otherwise standardized industry. The boutique hotel typically features a 
contemporary or minimalist décor while also offering many additional lifestyle amenities. Hotel guests 
tend to perceive boutique hotels as a stylish location for which they are willing to pay premium room 
rates for (Binkley, 1999). Recently, the boutique hotel trend has crossed over into the mid-priced hotel 
market (Chittium, 2004). Rather than focusing exclusively on the functionality of the hotel product 
offering, mid-price hotels are beginning to consider the aesthetic appearance of the building’s structure 
and décor (Chittium, 2004). Hotels’ guest rooms as well as lobbies are being redesigned in order to 
stand out amongst the basic hotel offerings. For example, Choice Hotels are planning a new chain of 
hotels, tentatively named the Diplomat that will feature flat-screen TVs and stylish shelving in its guest-
rooms (Chittium, 2004). Another higher-priced hotel chain has adopted amenities that are typically 
associated with boutique hotels while pricing its rooms to be competitive with the mid-priced market. 
These innovative changes are expected to boost their occupancy rates beyond their rivals (Binkley, 
2003). Amenities being offered will include platform beds with no box springs, wire storage racks rather 
than dressers, plasma television screens, and complimentary wireless DSL access (Binkley, 2003). The 
trendy boutique hotel is an innovation to the traditional hotel experience and an attractive option to 
consider when designing a hotel service concept, especially when it crosses the traditional industry 
boundaries into co-branded fashion and jewelry concepts (e.g. the Bulgari-Marriott alliance). 
Use of Information Technology 
Another example of innovation in hotel services is the use of information technology. One study 
determined which of the recent technological innovations were most beneficial, least beneficial, and 
had future benefits for hotels (Reid and Sandler, 1992). The technological innovations that were found 
to be most beneficial included: a wake up system, electronic door locks, in-room pay-per-view, video 
cassette players, multiple phone lines, video library, personal computers, voice mail, computer modem 
connections, video check out, electronic in-room safes, and a software library (Reid and Sandler, 1992). 
However, it may be impractical for a specific hotel or chain to adopt all available technological amenities 
due to a lack of operational capabilities or limited resources. Instead, hotels must determine which 
technological innovations will most benefit their organization. 
Aside from customer preferences for technology, the addition of new technological features to a 
hotel’s service concept has distinct phases of adoption (Namasivayam et al., 2000). The technology 
adoption process includes: 
 customer signaling, such as internet booking and in-room modems; 
 enabling management, such as management email; 
 enabling employees, such as voice mail; 
 customer service revenue add-ons, such as ATM and interactive TVs; 
 customer service value add-ons, such as internet access and in-room fax machines; and 
 wireless technology, such as curbside check-in, voice recognition, and smart cards 
(Namasivayam et al., 2000). 
With the intricacies of implementing technological advances to the service concept, hotel managers 
need to also take into consideration the adoption process of implementing technology on top of 
understanding the operational capabilities of the hotel. 
Customization of Service 
Customizing the service experience for hotel guests is another means of service innovation. 
Some examples of service customization include: allowing guests to have flexible check in/out times, 
personalizing room décor, or having child care options available. Customized options adapt the hotel’s 
service offering to each individual guest’s preferences. However, customization is not easy to implement 
due to the operational capabilities of the firm. For example, a flexible check in/out policy could lead to 
labor scheduling problems. Adding such a policy successfully requires the alignment of hotel’s marketing 
and operational activities. Skinner (1974) provides a product-oriented example of the importance of 
balancing marketing and operational activities. He suggests that while it may seem profitable to add 
more products/features to the product mix, it may be too difficult operationally to implement (Skinner, 
1974). This dilemma is equally applicable to a service setting, in which adding more services may not 
operationally be possible. 
As we discussed earlier, service innovation is a crucial aspect of a firm’s ability to differentiate 
itself from its competitors and can contribute more to a firm’s revenues. Yet, service innovation 
research is lacking in comparison to product innovation. In this paper, we address this discrepancy by 
presenting an analysis of hotel travelers’ preferences for innovative service offerings and the role 
innovation plays in service development. The next section describes our research methodology in 
exploring the innovative choice drivers for business and leisure hotel travelers. 
Research Methodology 
Analysis Approach 
An effective method for determining the market-based relative value of various features of a 
service (e.g. hotels) involves modeling customer preferences in response to experimentally designed 
service profiles. This approach, commonly known as probabilistic discrete choice analysis (DCA) has been 
used to model choice processes of decision-makers in a variety of academic disciplines, including 
marketing, operations management, transportation, urban planning, hospitality, and natural resource 
economics (Louviere and Timmermans, 1990; Pullman and Moore, 1999; Verma et al., 1999; Verma et 
al., 2001; Verma et al., 2004). 
Statistical models (e.g. Multinomial logit (MNL) models, nested logit models), developed from a 
DCA study, link service attributes to customer preferences. Therefore by describing a service in terms of 
appropriate attributes, DCA can be used to predict relative market impact of various service offerings 
(Danaher, 1997). Recent papers by Verma et al. (1999) and Verma et al. (2002) review DCA literature 
and provide guidelines for designing and conducting DCA studies of services. Rather than repeating here 
what has already been detailed in various publications, we only briefly describe the DCA method. 
Discrete choice experiments involve careful design of service profiles, in this case, a specific 
hotel and choice sets (a number of service alternatives) in which two or more service alternatives are 
offered to decision-makers and they are asked to evaluate the options and choose one (or none). Each 
subject in a DCA experiment typically receives several choice sets to evaluate (e.g. 8-32 sets) with two or 
more hypothetical services to choose from in each set. The design of the experiment is under the 
control of the researcher, and consequently, the decision-makers’ choices (dependent variable) are a 
function of the attributes of each alternative, personal characteristics of the respondents, and 
unobserved effects captured by the random component (e.g. unobserved heterogeneity or omitted 
factors). For a detailed theoretical and statistical background of DCA please refer to Ben-Akiva and 
Lerman (1991), Louviere et al. (2001) and McFadden (1986). 
DCA applications based on choice experiments typically involve the following steps: 
 identification of attributes; 
 specification of attribute levels; 
 experimental design; 
 presentation of alternatives to respondents; and 
 estimation of the choice model. 
Past studies have shown that in general, the market share predictions generated from the statistical 
models (e.g. MNL) based on DCA are extremely accurate (Ben-Akiva and Lerman, 1991; Louviere et al., 
2001). Subsequently we describe our implementation of DCA within the context of business and leisure 
hotel travelers in the US. 
Hotel Attributes and Experimental Design 
Prior to finalizing the experimental attributes and levels with the discrete choice customer 
survey, we conducted extensive qualitative research (Verma et al., 1999). We interviewed managers 
from economy, mid-range and upscale hotels and several business and leisure hotel customers. Based 
on qualitative data and a review of academic and practitioner’s literature on the topic, we identified five 
broad constructs of hotel attributes to be varied in discrete choice experiments. They are – hotel type; 
price; loyalty/frequent user programs; eating options; office facilities and technology options; 
customization options; and hotel amenities. Each of these constructs was further expanded into 
attributes (each with two or more levels). However, in this paper we will only focus on the innovative 
constructs: hotel type, technology, and customization for ease of understanding and clarity. Each of 
these constructs is considered to be innovative because each involves offering services which are not 
traditional to the industry. 
The “hotel type” construct consisted of three attributes: economy, midrange, and upscale. Each 
attribute was represented by four of the six experimental levels: motel, bed and breakfast inn, 
independent boutique hotel, standardized hotel affiliated/operated by recognized chain, boutique hotel 
operated by a recognized chain, and convention style hotel. The “technology” construct was described 
by three attributes: internet access in room (none, free, $5 or 10/day), business center (not available; 
full-service and centrally located; multiple business kiosks, in-room printer, fax, etc.), and availability of 
internet reservations (yes, no). The last construct, customization, includes different alternatives which 
match a person’s life-style. Customization was described by five attributes: ability to bring small pets to 
room (yes, no), availability of flexible check-in/check-out times (yes, no), ability to personalize in-room 
décor (yes, no), childcare (not available, fee-based nanny and/or kids club for infants and up to 12 years 
old kids), and in-room kitchen facilities (none, coffeemaker, microwave, refrigerator, and full-
kitchenette). Table I describes the innovative attributes and their corresponding experimental levels. 
After finalizing the list of attributes and their experimental levels, we designed 64 orthogonal 
profiles that allowed us to reliably estimate the main effects of all the hotel attributes described above 
(Verma et al., 1999). To enhance the realism of the task, a full-profile approach was used in presenting 
the choice sets (Green and Srinivasan, 1990), i.e. each profile shown to the respondents simultaneously 
described some combination of all the attributes. Within the actual survey three hotel profiles (one 
economy, one mid-range and one upscale) were shown to respondents at the same time and they were 
asked to choose one hotel (or neither) which varied from each other on numerous attributes 
simultaneously. Each respondent evaluated eight hotel choice-sets. In addition to the hotel choice task, 
the survey instrument included several questions about respondents’ past hotel visits as well as 
demographics. 
We pre-tested the survey with 25 randomly-selected hotel customers to ensure ease and 
comprehension of the task, as well as to ensure reliable data collection methods. Average time for 
completing the entire survey was approximately 20 minutes and respondents did not indicate difficulty 
in comprehension. 
Sampling Frame and Data Collection 
The population of interest consisted of business and leisure travelers who stayed in economy, 
mid-range or upscale hotels. To obtain a representative sample (or as close to it as possible) we acquired 
from a third party vendor a reliable electronic mailing list of 4,000 potential respondents with residences 
scattered across the United States from a well-reputed marketing research company. The mailing list 
contained a sample of respondents balanced according to US census data validated by various 
demographics criteria. Each of the potential respondents received an email invitation to participate in 
the survey from the lead researcher. By participating in the survey, a respondent had the ability to 
participate in a raffle to win one of the ten gift certificates for $100. From the initial list of potential 
respondents, approximately 2,500 chose to participate in the survey. Approximately 40 percent of the 
respondents answered negatively to the screening question (have you taken a business or leisure trip 
during the last one year which required a hotel stay?) and were not allowed to continue with the survey. 
At the conclusion of a three-week data collection period, a total of 930 respondents completed and 
returned the survey (each received a second email reminder). Since there was no indication of any 
response bias, the analysis presented in this paper is based on survey data collected from all the 
respondents. 
Analysis and Results 
Sample Characteristics 
General sample characteristics and demographics are presented in Table II which shows that the 
respondent pool is very diverse in terms of age, gender, annual household income, and education level. 
Table III shows a snapshot of travel frequency, the type of hotel room stayed in, and nightly 
room rate for the sample. A majority of the respondents had traveled in the last three months, taken 1-3 
trips during the last 12 months, and paid nightly room rates between $40 and 100. 
The sample was divided into two segments based on the following classification scheme. 
Respondents who report that that more than 50 percent of their trips requiring hotel stays are business 
related are considered to be business travelers. A total of 169 respondents were classified as business 
travelers. Respondents who report that more than 50 percent of their trips requiring hotel stays are 
leisure related are considered to be leisure travelers. A total of 691 respondents were classified as 
leisure travelers. Those respondents who were split equally, 50 percent business and 50 percent leisure 
were categorized as business travelers. This resulted in a total of 239 business travelers and 691 leisure 
travelers. Next, we explain the results of the innovative hotel choice experiment. 
Table 1. Experimental constructs, attributes, and levels 
 
Innovative Hotel Choice Modeling Results 
The primary analysis approach associated with DCA is the estimation of the MNL models based 
on a maximum likelihood estimation technique (Ben-Akiva and Lerman, 1991). Recall that each 
respondent had to evaluate eight choice sets, each containing two descriptions of hotels along with the 
option of not choosing either. Statistical details about MNL model estimation is described in extensive 
detail by Ben-Akiva and Lerman (1991) and Louviere et al. (2001).Amore applied description of DCA and 
MNL model estimation is provided in Verma et al. (2002) and Verma and Plaschka (2003). Louviere et al. 
(2001) and Ben-Akiva and Lerman (1991) recommend that when estimating MNL models, experimental 
variables can be “effects-coded” to accurately estimate the relative impact on respondents’ choices. The 
estimated MNL model for this study was statistically significant at the 5 percent level. 
Table IV shows the relative impact of each experimental attribute on hotel choice decisions. 
Recall that we are only focusing on the innovative attributes that were included in the original broader 
dataset. Therefore, all results presented ignore the non-innovative attributes that were also included in 
the study. The estimated β weights for the innovative attributes are standardized to be between “zero” 
and “one” based on the highest and lowest part worth utility of an attribute. By transforming the data 
linearly, it is easy to compare and contrast the impacts of each attribute to one another. We estimated 
the relative main effect by subtracting the highest and lowest β weights for a given attribute (Louviere 
et al., 2001). The main effects allow us to compare the overall impact of changing the levels of 
innovative attributes in hotel choice against each other. 
Table 2. Demographic characteristics 
 
Table 3 Traveling Characteristics 
 
The numerical results presented in Table IV are shown in Figures 2-5 to depict graphically the 
hotel choice patterns. It is important to reemphasize that the results provided are determined from the 
innovative constructs only; all other options were not included in the calculation of the estimated 
standardized b weights. Figure 2 shows the relative main effects of all experimental attributes and the 
relative impact of each of the levels. Among these three constructs, “hotel type” accounts for 61 percent 
of the relative weight, followed by “customization” with a relative weight of 27 and 12 percent from 
“technology”. The main effect for each attribute was determined to give a more detailed insight into 
hotel choice criteria. For example, within the “customization” construct, the attributes with the smallest 
main effects are the option to customize room décor and the option of flexible check in/out. In addition, 
the availability of internet reservations has a small overall effect in comparison to the other 
technological attributes. A larger main effect for type of hotel became apparent when respondents were 
selecting a midrange to upscale hotel in comparison to an economy hotel. 
Table 4. Relative impact and relative main effects 
 
 
Figure 3 shows the relative impact of each level of the “hotel type” attributes. For business 
travelers choosing an economy hotel, motels were the most preferred type of hotel. While those who 
were selecting a midrange to upscale hotel preferred standardized hotel chains with independently 
operated boutique hotels following close behind. In comparison, the most popular hotel type for leisure 
travelers selecting economy hotels were boutique hotels. In addition, leisure travelers choosing among 
upscale hotels most prefer boutique hotels operated by a recognized chain. Overall, boutique hotels 
were a strongly preferred option across both customer segments. 
 
Figure 2. Relative main effects on constructs and determinant attributes 
The relative main effects for the “technology” attributes are shown in Figure 4. For business 
travelers, providing internet access has the largest impact on hotel choice while for the leisure traveler it 
is the availability of a business center. While it may appear counterintuitive that leisure travelers’ hotel 
choice is being influenced by a technological offering such as a business center, possible reasons for this 
perceived anomaly are described below: first, recall that these reported main effects are relative 
comparisons to one another. A business center may be the most preferred technological option, but 
when compared to other innovations such as childcare and in-room kitchen amenities it no longer has 
the largest impact. Second, leisure travelers may want a business center available to them because it 
provides benefits such as email checking, copying, package delivery, and other facilities which a leisure 
traveler might also value. Both segments ranked the option of booking hotel reservations via the 
internet as a low priority probably because internet reservations are no longer “order winners” but a 
necessary requirement. Furthermore, those respondents selecting amongst economy hotels, 
consistently weighted the availability of technological innovations more heavily than when selecting a 
midrange or upscale hotel. This would suggest that the hotel choice of travelers staying at economy 
hotels is swayed more from offerings of technological service innovations than travelers staying at 
midrange or upscale hotels. 
 
Figure 3. Relative impact of hotel attributes on hotel choice 
Figure 5 shows the main effects for the “customization” attributes. Across all hotel and traveler 
types, available childcare facilities, in-room kitchen facilities, and pet policies have the largest impact on 
hotel choice. Respondents deciding on economy hotels placed a greater emphasis on all the customized 
service options in comparison to the other types of hotels. Once again, implying that travelers choosing 
among economy hotels make their choices based on the innovative offerings the hotels provide. 
The results shown in Figures 2-5 and Table IV have both academic and managerial implications. 
First, the results present the tradeoffs made by hotel guests. Secondly, by examining the tradeoffs made 
by hotel guests, in terms of innovative service offerings, we are able to enhance the design and 
development of a service concept. Lastly, by pinpointing which innovative attributes have an impact on 
hotel choice; managers will be able to judge how, operationally, they should deliver such innovative 
services. 
 
Figure 4. Main effects of technology attributes on hotel choice 
 
Figure 5. Main effects of customization attributes on hotel choice 
Discussion and Conclusions 
Past research and anecdotal evidence suggest that service innovation, in general, has a positive 
impact on customers’ choice and can result in increased revenues for a firm. IBM’s innovative service 
program is just one example of the financial benefits that can be realized from implementing service 
innovation. Our study, demonstrates the impact of including innovation within a hotel’s service concept. 
The type of hotel has the largest impact for both business and leisure travelers’ hotel choices. We also 
find service innovation to have a larger impact on guests who are selecting economy hotels in 
comparison to midrange or upscale hotels. Furthermore, innovative service amenities, such as 
technological improvements and customization features, have a stronger impact on leisure travelers’ 
hotel choices in comparison to business travelers; while hotel type has a larger effect for business 
travelers’ choices. Overall, we found across both customer segments that innovation does matter when 
selecting a hotel. 
Recalling the three broad categories of hotel innovation presented in our study – hotel type, 
technology, and customization we can infer the following results. First, hotel type contributed to the 
majority of hotel choice. In particular, business travelers’ decisions were found to be guided more by 
hotel type when compared to leisure travelers; and midrange to upscale hotel selection were influenced 
more by hotel type than economy hotel selection. Second, the technology option, specifically the 
booking of hotel reservations via the internet, has the smallest impact on both business and leisure 
travelers’ hotel choice. Third, the customization construct’s greatest impacts came from available child 
care, pet accommodation, and the inclusion of in-room kitchen facilities. 
Within each construct, tradeoffs were apparent for both business and leisure travelers. First, 
hotel type contributed to a significant portion of hotel guests’ choices. The boutique hotel, the 
innovative option, stood out as a preferred choice among other more traditional alternatives. 
Independent boutique hotels were the second most popular hotel type for business travelers staying at 
midrange and upscale hotels and it is the most popular type for leisure travelers staying at economy 
hotels. Also, leisure travelers selecting from upscale hotels prefer boutique hotels operated by a 
recognized chain more than the other hotel options. A recognized chain boutique hotel was a secondary 
preference for leisure travelers selecting from mid-range hotels. Second, business travelers, across all 
hotel types, are more greatly influenced by the technological offering of in-room internet access. The 
availability of a business center was next in priority, followed by internet booking reservations. In 
contrast, leisure travelers, across all hotel types, are more greatly guided by the presence of a business 
center, followed by in-room internet access. Once again the smallest impact emanated from the 
internet reservation bookings option. Lastly, the preferred customization options included service 
offerings such as on-site child care, pet friendly policies, and in-room kitchen facilities rather than 
flexible check in/out and customized room décor. By examining the tradeoffs made by hotel guests, we 
are able to gain a better understanding of what types of innovative service offerings determine a 
traveler’s hotel choice. 
The customer tradeoffs we have identified play an important role in the design and 
development of a hotel’s service concept. We have to remember that a service concept acts always as a 
mediator between the “what”, customer needs, and the “how”, operational capabilities of service 
design must be aligned. Additionally the study emphasizes the “what” for the service concept but does 
not specifically test the “how”. However, a thorough understanding of customers’ desires will allow 
experienced managers to more easily infer which operational capabilities are necessary to implement 
such innovations. For example, the popular hotel type option of a boutique hotel conjures up such 
operational questions as: what layout and facility changes would be necessary? What staff training 
would need to be conducted? What service amenities would be needed to constitute a boutique hotel 
to would be guests? Another example, in-room internet access, brings forth operational issues such as: 
what infrastructure costs are incurred from adding technological services? What price level would the 
hotel need to charge for the access or can it be complimentary? Would managers need to hire 
information technology staff for dealing with internet-related problems? Or would managers need to 
train the current staff to handle such problems? Similarly a flexible checking option might require 
implementation of a more complex hotel reservation and labor scheduling system. Therefore, while we 
have not statistically tested the influence of innovative service offerings on operational strategy 
formulation, we are still able to make inferences regarding operational issues which might arise from 
implementing various service innovations. 
Numerous managerial implications can be drawn from our study. First and foremost, our study 
assists hotel managers in understanding what service innovations might have the greatest impact on 
potential guests’ choices. This understanding will enhance the design and development of hotel service. 
In addition, it will focus manager’s efforts around the innovations which are most important to guests. 
Through the provision of customer choice patterns, managers will be more adept at improving their 
operational planning and decision-making. Ultimately, the end result will be a better-devised 
operational strategy formulation that is sensitive to the preferences of customers. Furthermore, the 
results presented in this paper can be used to develop a decision-support model which can assist in 
conducting “what-if” type of analyses. The managers can evaluate the relative values and willingness to 
pay for each proposed service innovations prior to making huge investment of money and effort (Verma 
et al., 1999). 
While our study provides a detailed outlook of the tradeoffs made by hotel travelers and the 
design and development of a hotel’s service concept, there are limitations in our conclusions. For 
example, as in most studies, our data represents only one snapshot in time. This limits our ability to 
draw conclusions on the long-term impact of service innovations. In order to address this issue, a 
longitudinal study would be required to track and compare the impact of guests’ choices over time. Also, 
our data are limited to the hotel industry and one geographic market, the US, which presents issues 
concerning the generalizability of the results. Studying hotels in a variety of countries, for example, 
would undoubtedly yield different service preference results. Thus, cross-cultural, horizontal and vertical 
industry sector studies would enhance the generalizability of the results. Despite the inherent 
limitations of our study, we have presented a solid first examination of the impact service innovation 
has on customer’s choices and the operational issues which arise from implementing such service 
innovations. 
In summary this paper offers both academic and managerial contributions through the 
examination of innovative service tradeoffs made by hotel guests. Our goal was to contribute to the 
service management literature by presenting an innovative-specific industry sector perspective when it 
comes to adding new services into the core service concept. We also presented a managerial tool for 
hotel managers to utilize when deciding which service innovations to implement. Finally the results can 
be used in formulating an operational strategy which aligns with hotel guests’ values and preferences. 
By understanding the service innovation tradeoffs made by customers, a service concept can be 
designed more effectively yielding into a firm’s much more profitable and sustainable operational 
strategy. 
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