1 
 
Unifying Services Marketing and Operations  
With Service Experience Management 
 
 
 
Robert J. Kwortnik, Jr.* 
and 
Gary M. Thompson, 
 
Published in the Journal of Service Research (2009), 11 (4), pp. 389-406.   
 
 
*Robert J. Kwortnik, Jr. is Assistant Professor of Services Marketing, School of Hotel 
Administration, Cornell University, 545 Statler Hall, Ithaca, NY 14853, phone: 607-254-6543, 
fax: 607-255-1355, email: rjk34@cornell.edu., Gary M. Thompson is Professor of Operations 
Management, School of Hotel Administration, Cornell University, 352 Statler Hall, Ithaca NY 
14853, phone: 607-255-8214, fax: 607-254-8839, email: gmt1@cornell.edu. The authors would 
like to thank Erica Wagner and Rohit Verma for their valuable comments on drafts of this 
manuscript. 
 
  2 
Unifying Service Marketing and Operations 
with Service Experience Management 
 
 
ABSTRACT 
One of the pioneer firms in the leisure cruise industry embarked on a bold idea in 2000 to offer 
an unregimented experience unlike most cruises. Despite the appeal of the concept from a 
marketing perspective, the service innovation posed operational challenges, many of which 
continue to undermine the firm’s competitive position. Using a multi-method empirical approach 
and interdisciplinary views that draw on research from marketing and operations management, 
the authors analyze this business case to identify challenges that service firms face when services 
are developed and managed from siloed functional perspectives. Based on their research findings 
and guided by the literature, the authors derive a service-systems model to aid service planning 
and management. The authors further highlight a new organizational form and function for 
services under the domain of service experience management that is positioned as a means to 
unify service operations and marketing for delivering on service promises. The authors offer 
direction for further research on service operations systems and service experience management.  
  3 
INTRODUCTION TO THE RESEARCH CONTEXT 
The advertisement for Liberty Cruise Line read, “Dinner is served promptly … whenever. 
On an LCL cruise, you can do whatever. With no set dining times and 12 restaurants, you’re free 
1
to dine where you want, when you want. It’s called Choice Cruising.”  LCL featured this ad as 
part of a $100-million marketing campaign conducted in 2006-07, the most expensive in the 
company’s history, to reintroduce Choice Cruising to consumers and travel retailers. The success 
of the campaign and the fate of LCL in the competitive cruise industry depended on the firm’s 
ability to flawlessly deliver on the service promise that cruisers can escape life’s stresses through 
the freedom of a flexible, relaxed experience unlike traditional cruising. The linchpin of this 
promise was a redesigned dining process that removed the set meal times that anchored the daily 
cruise itinerary. However, providing such freedom and choice to 2,500 passengers in a capacity-
constrained environment put enormous pressure on operations. In fact, LCL customers at times 
faced long waits during peak dining hours and frustration with the process of making restaurant 
reservations, which yielded a range of negative outcomes for customers and service personnel, 
problems that persist to this day (mid 2008)—eight years after the concept was introduced. 
The present study was conducted to identify the determinants of customer dissatisfaction 
with the LCL cruise experience. By applying interdisciplinary views to the analysis of service 
processes associated with Choice Cruising, unexpected findings emerged related to disconnects 
between marketing and operations. These findings underscore the need for a cross-functional, 
systems-based approach to service design and management. We develop a model of this 
approach that we call Service Operations Systems (SOS). We ground this model by calling for a 
new organizational function, service experience management, which melds service management 
(process/operations) and customer management (experience/marketing).  
As deeds, processes, and performances, services result from cross-functional production 
efforts of marketing and operations management, including human resources and information 
systems (Zeithaml, Bitner, and Gremler 2008). Empirical studies of this integration are scarce 
(for exceptions, see Evangelist et al. 2002; Verma et al. 2001), despite the repeated call for 
multidisciplinary research on service design and delivery systems (Metters and Marucheck 2007; 
Rust 2004; Parasuraman 2007). For example, the Journal of Operations Management devoted 
two special issues, published in 1991 and 2002, to the integration of marketing and operations, 
but only two of twelve papers in these issues examined a service context. The editors of the latter 
special issue stated that “…the study of the marketing-operations interface still has not evolved 
as much over the past decade as was expected or needed” (Malhotra and Sharma 2002). We have 
found little in the service literature since 2002 to suggest that the situation has improved. 
Based on a reading of the respective literatures and interaction with academics and 
practitioners across the disciplines, we identify four main issues that continue to stymie efforts to 
better integrate service marketing and operations. First, the siloed nature of the fields, both in 
academe and in practice, limits communication and knowledge transfer. Second, scholars and 
practitioners foray rarely, if ever, beyond their areas of expertise, even when a particular problem 
(e.g., service design) could benefit from diverse perspectives. Third, different research methods 
commonly used within disciplines (e.g., qualitative or experimental techniques used in marketing 
versus modeling techniques used in operations) can lead to biases for or against certain 
approaches for testing theories. Fourth, the complexity of services encourages empirical 
investigation in a piecemeal fashion (e.g., of a specific production process) rather than as holistic 
                                                 
1
 Data for this study are based on an actual firm that operates in the global cruise industry. To protect the anonymity 
of key informants and the firm, identities have been masked. All original sources are available from the authors. 
  4 
systems that include customer co-production as inputs/outcomes in addition to the endogenous 
service processes, rules, and procedures that comprise the service operation. We return to a 
discussion of these issues following the presentation of our empirical context and analysis. 
Because of the nascent state of research on the service marketing-operations gap, we take 
an exploratory approach to develop an understanding of this divide, and follow the guidance of 
Malhotra and Sharma (2002), who noted: “Given the complexity and inter-functional nature of 
conducting research that jointly looks at marketing and operations issues, in-depth case analyses 
… [are] desirable in meaningfully tackling the interface-related issues.” We first detail our path 
to discovery using the LCL Choice Cruising context and a multi-method research design that 
involved participant observation and analysis of more than 5,500 online customer reviews. We 
then integrate emergent thought from the literature to inform our analysis of the marketing-
operations dilemma at LCL and to derive our SOS model and conclusions. Finally, we propose 
an approach to managing the service marketing-operations interface, which we explore with data 
collected from executives across 16 different cruise brands. Our main contributions are threefold: 
1) a grounded, data-driven analysis of a service redesign that has gone adrift; 2) the derivation of 
a model to aid the study and management of service marketing and operations; and 3) the call for 
a new cross-functional organizational approach to service experience management. 
 
THE LIBERTY CRUISE LINES CASE—RESEARCH METHODS 
In 2006, Liberty Cruise Lines sought academic researchers with discipline- and industry-
relevant expertise to examine service problems that were difficult to study internally due to 
potential inter-departmental tension. To accommodate the initial request, we observed the service 
delivery in person, as described below. To triangulate on the phenomena of interest and to obtain 
a perspective of LCL’s competitive position in the cruise industry, we supplemented the 
observational record with publicly-available industry data and online consumer ratings of service 
delivery for LCL and the firm’s two main competitors. In addition, we surveyed cruise industry 
executives to obtain a view of the marketing-operations interface within their firms.  
Participant Observation Data 
We negotiated the scope of the research with LCL’s corporate hotel operations division 
and gained access to data that is often beyond the reach of academic studies of management 
practice. We chose participant observation of the LCL service environment as one means for 
developing an understanding of the relationship between marketing and operations. Participant 
observation is an empirical, inductive method of data collection appropriate for exploratory 
studies that address research problems for which theoretical frameworks and prescriptive models 
are lacking (Gummesson 2000). The level of researcher participation versus observation varies, 
though the researcher’s role is usually known to the people being studied (Gummesson 2000).  
LCL had the research team study two voyages in different cruising regions in the fall of 
2006. This permitted data comparison across contexts for differences in service delivery and 
customer experience. The first site visit was conducted by four MBA students studying with one 
of the primary investigators. Two of the students performed covert participant observation; the 
other two were identified to onboard management as student researchers studying the firm’s 
dining system. These latter investigators gained access to managers for interviews and 
demonstrations of service processes and technology. Data analysis suggested that a richer view 
of the service system was attained by non-covert interactions and observation. Hence, the second 
team entered the field identified to onboard management as academic researchers. This team had 
two investigators, one a novice cruiser and the other a veteran of 12 voyages who also had 
conducted prior studies in the cruise context, thus possessing preunderstanding (Gummesson 
  5 
2000). The use of two field sites and multiple investigators with differing levels of contextual 
knowledge and direct participation was expected to reduce researcher bias during data collection. 
This phase of the study was completed in January 2007, lasting nine months, and involving 11 
days of on-site field research.  
Data collection involved observation and recording of dining reservation processes, 
waiting lines, occupancies, table utilization, and service encounters. Data were also collected 
through interaction with ship officers and crew, including unstructured interviews with such key 
crew members as the hotel director, food and beverage director, and head maitre d’, as well as 
participation in officer meetings and back-of-the-house tours. Prior to the site visits, we also 
participated in a Web demo of the restaurant-management application used by LCL, “InfoDine” 
(a pseudonym). The participant-observation data record contains more than 200 pictures and 80 
pages of field notes and memos. Although data collection was unstructured and fluid to permit 
the capture of naturally-occurring data, the analytic process was systematic, with interpretations 
of the data recorded as memos and distributed iteratively within the team for further analysis to 
arrive at a grounded, consensual understanding of the research issues (Gummesson 2000). To 
help reduce bias, drafts of this paper were provided to key informants for review and comment.  
 
Customer Comment Data 
To attain a customer-based perspective of the Choice Cruising experience, we gathered 
publicly available data from the cruise-community Web site: www.cruisesonly.com. The site, 
which is promoted as “America’s Largest Cruise Agency,” features customer feedback that is 
authenticated to ensure that cruisers sailed on the ships they reviewed. The CruisesOnly data 
contains cruisers’ written reviews and quantitative ratings across five dimensions (ship quality, 
dining/food, stateroom quality, ship staff quality, entertainment & activities), an overall cruise 
rating, and demographics (age, number of cruises taken, type of traveling party).  
From this site we downloaded data in two waves. First we collected 1,090 customer 
reviews of LCL cruises posted from November 2005 to May 2007 across the line’s fleet of 12 
ships. To provide a comparison dataset, we randomly collected 1,000 customer reviews of LCL’s 
two main competitors: Festival Cruise Lines and Regal Cruise Lines (both pseudonyms). The 
focus of this dataset was the qualitative comments, which were content analyzed by two 
independent coders to identify customer references to Choice Cruising or Dining (or to general 
dining processes for the competitor brands), the valence of these references (positive, negative, 
or ambivalent), and perceptions of the positive or negative aspects of the experience. For the 
second wave, we collected 1,123 customer reviews of LCL cruises posted from November 2005 
to February 2008 across 10 ships (reviews were no longer available for two ships that had left the 
fleet since the first wave of data collection). The focus of the second dataset was quantitative 
ratings, which were analyzed with multiple regression to examine the effects of the rated 
dimensions of the cruise product on the evaluation of the overall cruise experience. Ratings were 
also downloaded for Festival (2,432 ratings across 21 ships) and Regal (1,995 ratings across 19 
ships) cruise lines. Although this dataset has limitations typical of secondary sources (e.g., it is a 
convenience sample of self-selected cruisers, which creates the potential for response bias; the 
single-item ratings could not be assessed for reliability or validity), there is no a priori reason to 
suspect that sample or measurement biases would align in such a way across more than 5,500 
cases to produce the score distributions found in this dataset both within and across cruise lines. 
 
Survey Data from Executives across Cruise Lines 
  6 
To investigate the service marketing-operations integration across the cruise industry, we 
contacted executives from 20 cruise lines that serve the North American market. Sixteen cruise 
executives from sales, marketing, revenue management, public relations, and hotel operations 
responded to our inquiry, for a response rate of 80%. The executives were first contacted by 
email and asked several open-ended questions, such as whether a department (or person) was 
responsible for monitoring and managing the customer experience, where this function existed in 
the organizational chart, and how the function was performed. Responses were collected either 
by email or phone. The text data was content analyzed to assess frequencies and commonalities, 
as well as unique instances in organizational forms, functions, and relationships. These findings 
were also compared to the demographics of the cruise lines (e.g., firm size, number of ships, 
average passenger loads per ship, target market) to identify potential moderating factors. 
Findings from the cruise executive survey data are reported separate from the LCL analysis in a 
call for service experience management to better connect service marketing and operations.  
 
THE SERVICE MARKETING-OPERATIONS GAP 
The Case of LCL’s Choice Cruising: Backstory 
The leisure cruise industry changed dramatically during the past few decades. LCL’s 
rivals in the mass-market segment grew quickly by focusing on new ships with increasingly 
more impressive designs and facilities (Kwortnik 2006). In the 1980s-90s, LCL lacked the 
finances to innovate through ship building and instead strived to keep pace through creative 
marketing, a course of action yielding no sustainable competitive advantage (Dickinson and 
Vladimir 1997). By the end of the 1990s, LCL was a distant third in market share and needed a 
more radical strategy. With limited resources for innovation, LCL looked to service redesign. 
In 1999, LCL executives debated an open-seating dining model that was well outside the 
knowledge and operational norm of the mainstream cruise lines whose ships are floating service 
factories that carry thousands of guests and crew. The cruise industry was rooted in naval 
tradition, which was evident in a structured itinerary: meals had set dining times, typically a 
main seating (e.g., dinner at 6 pm) and a late seating (e.g., dinner at 8 pm), and guests dined at 
the same table for the duration of the cruise. Preset dining processes were deemed necessary for 
control of the service system. Restaurants were not designed to seat all guests at the same time; 
ships that sailed full might have capacity for 50 to 60% of guests at one seating. Scheduled 
dining was used to optimize restaurant occupancies and the flow of guests through the ship’s 
bars, lounges, spa, casino, and theaters, as well boarding/debarking the ship when at port, and to 
optimize the concomitant staffing decisions required by these customer flows. Structured dining 
also enabled the kitchen and dining-room crew to develop an efficient production model for 
delivering high-quality meals and service several times per day, seven days per week.  
On the surface, open-seating dining seemed to be an incremental change; however, it was 
actually a radical redesign that required alterations to the ship-wide service architecture and 
processes. Except perhaps for the sailing schedule (cruise ships typically keep to a firm sailing 
schedule to catch tides, ensure docking space at ports, and make efficient use of fuel), dining 
defines the service rhythm of a cruise itinerary. For example, theaters and lounges offered two 
show times to accommodate the staggered movement of guests through early and late-seating 
dining. Many other activities, from wine tastings to dance lessons, followed a similar pattern. 
The dining schedule even affected the ebb and flow of sunbathers and their pursuit of often-
scarce pool-side lounge chairs.  
  7 
The greater predictability of service production afforded by set dining times also enabled 
efficient use of kitchen and dining staff. In contrast, open-seating dining required more staff and 
longer dining hours to buffer uncertain demand. Permitting guests to dine where, when, and with 
whom they wanted also meant guests were less likely to receive service from the same staff 
(waiter and busboys), which altered the guest-server relationship. This change demanded a more 
flexible team-based service delivery structure, as well as a different compensation system, since 
the traditional end-of-cruise tipping of servers would no longer be viable. Finally, open-seating 
dining was likely to require tactics for demand management similar to those used by land-based 
restaurants, such as waitlists, reservations, or incentives for dining at off-peak hours. 
Given the expected—and unknown—changes required of the service system, the idea of 
an unstructured-dining model was resisted by some LCL executives and operations management, 
and the concept was shelved. However, in light of the brand’s competitive weaknesses, LCL 
became a takeover target, and in mid-2000, a new LCL owner and leadership unveiled Choice 
Cruising as a “revolution” in cruise dining. Advertisements touted the concept as “innovative” 
and “the future of cruising.” As an indication of the impact of Choice Cruising, later the same 
year a rival cruise line modified its dining system by adding two seating times to the early- and 
main-seating schedule. Another competitor followed with a hybrid model whereby guests could 
choose at the beginning of their cruise either traditional scheduled dining or open-seating. A 
third rival, though, opted to leave the traditional approach to cruise dining unchanged. Perhaps 
most tellingly, no other major cruise lines adopted a completely unstructured dining process. 
In 2001, LCL launched the first of eight new ships that were purpose-built for Choice 
Cruising, most notably with up to 12 restaurants (see Table 1). LCL’s management promised to 
liberate guests from the traditional cruise experience—and leveraged the brand on the Choice 
Cruising service concept. However, reliably delivering on the service promise proved difficult. 
 
[Insert Table 1 about Here] 
 
The Choice Cruising Service Experience 
Marketing for Choice Cruising set high customer expectations. Advertisements stated, 
“the point of a vacation is to get away from work, regimen, and schedules—right? With Choice 
Cruising—only from Liberty Cruise Line—you get endless activities and fun on your schedule.” 
Similarly, a description of the Choice concept on the LCL website told visitors that from the 
moment they boarded the ship, they were “off the clock,” with “no rules to follow or schedules 
to keep.” Reality often revealed otherwise. Guests wishing to dine in the specialty restaurants 
could not expect to simply walk in and be seated. Reservations were highly recommended and 
often required. Guests typically had to make a reservation early in the day or even at the start of a 
cruise—though this was not clearly communicated in LCL marketing materials.  
The research teams experienced an inconsistent restaurant-reservations process. In most 
cases, reservations were accommodated, but not necessarily for the time or day requested. If a 
reservation could not be accommodated, reservation agents surprisingly did not suggest other 
venues. The teams’ experience with walk-up dining was also mixed. Some walk-up requests 
were accommodated—typically if restaurants were less than half full (LCL reserves a fixed 20% 
of its tables for walk-up guests). In other cases, hosts provided a wait estimate and offered a 
pager for table notification. In yet other cases (one in which a restaurant was only half full), hosts 
stated that the restaurants were booked, a reservation was required, and guests could return later. 
In none of these instances did the hosts use the available table management system to explore 
dining options at other restaurants or make recommendations to guests. 
  8 
Guests generally liked Choice Cruising, especially dining at the specialty restaurants, 
though the execution of the concept could make the dining process chaotic and uncertain. Some 
guests were unaware that reservations were required at certain restaurants and found making 
reservations unpleasant, as it limited promised freedom. One incident witnessed by a member of 
the research team illustrates these issues. The encounter occurred at 5:30 pm on the fourth day of 
a seven-day cruise. A queue of more than 50 guests was waiting for a restaurant to open. The 
host informed a guest near the front of the queue that his party could not be seated immediately 
without a reservation. Peering into the empty restaurant, the guest barked his disbelief that not 
one table was available. The host asked if he wished to return in 15 minutes to see if she could 
seat him. Saying he would not wait to eat when on vacation, he stormed off, vowing (profanely) 
never to sail with LCL again. When the host was asked what would make her job easier in light 
such guest behavior, she replied, “no reservations.” The implication of this statement: the 
reservations process limited her ability to accommodate walk-up customers who expect greater 
freedom of choice. The queue already in existence when the restaurant opened also suggested 
that operating hours were still too short to meet customers’ expectations of dining freedom. 
Operations managers reported that customer comment cards often showed frustration 
with dining processes. For some voyages, mean scores for a question measuring the ease of 
making a reservation failed to earn a passing grade, whereas scores on non-dining dimensions 
were very good to excellent. Clearly, the service structure and processes designed to support the 
Choice Cruising service experience were inadequate; less clear, though, was why. 
 
Choice Cruising: Service—Technology Processes  
More than six years after LCL introduced Choice Cruising, the dining system remained 
problematic: some restaurants had long waits, especially during peak dining hours, whereas other 
restaurants had low occupancies depending upon the time of day and day of the week. This led to 
poor utilization of perishable seat inventory and staffing, customer complaints, and employee 
frustration. To smooth demand, LCL created a reservation call center and desk, and invested in a 
computerized restaurant reservations and table management application by InfoDine that was 
originally designed for stand-alone restaurants, but that supposedly could be adapted to manage 
multiple restaurants. LCL also implemented a number of fixes for the evident issues, such as a 
pager system to notify guests when their tables were ready and discounted cover charges for the 
specialty restaurants to entice guests to visit during non-peak hours (before 6 pm or after 9 pm). 
LCL’s corporate (shore-side) operations team was unsure why the guest dining 
experience was evaluated poorly, especially the restaurant-reservation process. One hypothesis 
was that reservations agents were inconsistent in suggesting dining choices to guests whose first 
requests could not be accommodated. Operations managers also believed that onboard restaurant 
managers were not effectively controlling the dining experience. Anecdotal evidence suggested 
that the InfoDine reservation-management application was under-used and even misused by 
onboard restaurant personnel, for example, that managers were placing dummy reservations in 
the application for later dining periods so the restaurants could close earlier.  
The InfoDine program was promoted as an integrated solution for controlling restaurant 
bookings and making these available to managers, maitre d’s, and hosts. The table management 
module had graphical images of restaurant layouts, with tables color-coded by status (reserved, 
occupied, or available). A customer-profile function could link reservations with guest data (e.g., 
identification of VIPs in higher-priced cabins and suites, who received priority reservations). 
InfoDine was linked to onboard electronic restaurant seating guides located in public areas; these 
flat-screen monitors showed restaurant occupancies using color-coded status bars: green = 
  9 
empty; yellow = filling up; red = full/wait. Based on presumed capabilities of InfoDine, shore-
side management hoped to reduce problems with guest queuing. Cruisers were expected to use 
the electronic seating guides to make dining choices and to avoid busy restaurants. Hosts were 
expected to switch views to see waitlists and occupancies at other restaurants, which would 
permit hosts at busy restaurants to recommend other dining options to guests seeking a table. 
Thus, it was unclear to shore-side operations managers whether recurring problems represented a 
people/training issue, a technology issue, a management issue, or some combination of issues. 
 
Choice Cruising: Technology—Employee Processes 
The general conclusion derived from analysis of the field-studies data is that Choice 
Cruising worked well on the sampled itineraries. The research teams noted few queues at various 
dining locations and times. However, both cruises sailed with low occupancies; cruise lines 
commonly sail “full” because ship occupancy is calculated as basis-2 (two occupants per cabin), 
though some cabins have additional berths, which increases maximum ship capacity. One of the 
sampled LCL voyages sailed with 1,700 guests, or 86.5% basis-2 occupancy (68.7% maximum 
capacity); the second voyage sailed with 2,198 guests, or 89.1% basis-2 occupancy (78% 
maximum capacity). Fuller ships could be expected to put more pressure on service systems. 
Observation of LCL’s dining facilities revealed impressive operations, in particular food-
preparation, cleanliness, order, and inventory control. Interviews with the food & beverage and 
hotel management teams highlighted experienced professionals who were determined to make 
Choice Cruising work. Yet, restaurants did not run efficiently. We observed that the specialty 
restaurants operated below capacity in the first few days of the cruise; guests wanted to eat at the 
specialty restaurants, but were often unaware that doing so was more difficult later in the voyage. 
We were surprised, too, to find that managers were not evaluated on customer throughput—a key 
metric for a capacity-constrained system. Aiming for high utilization would have mitigated, at 
least to some extent, the increased cost of service delivery that Choice Cruising requires. 
Given the purported functionalities of InfoDine, problems with pre-dining processes are 
evidence that the technology was not providing the vendor’s promised “solution.” Observation of 
staff as they used InfoDine suggests that it failed to meet the needs of a multi-restaurant, open-
seating service model. Dining reservations were taken by phone or at the reservations desk from 
8 am to 5 pm. Managers then assigned reservations in the table-management system, either at the 
beginning of the meal period (locking the guest to a table) or when the guest arrived. After 5 pm, 
reservations could be made only by walking up to individual restaurants. If guests could not be 
accommodated, the host should have used InfoDine to view other restaurants and recommend 
options, but the interface for doing this required clicking through multiple screens. We observed 
no hosts go to the trouble. Hosts also could not make reservations at other restaurants for guests. 
Thus, what appeared to be a lack of service may actually have been the result of IT constraints; 
staff found it hard to manipulate the software to act on needed information. Because host stations 
could not easily toggle between restaurants in InfoDine, the technology fell short of being a 
decision-support tool that facilitated employees’ efforts to enhance the guest experience.   
The research team also found that some restaurant managers and hosts worked around 
InfoDine by blocking tables as reserved even when no reservation existed. This had the effect of 
showing the restaurant as filling up or full on the electronic seating guides, which some guests 
used for making dining decisions. Inspection of actual occupancies suggested that this practice 
was not unusual; the electronic seating guides often showed waits while visual inspections 
showed no lines and empty tables. This finding is in keeping with studies showing that 
technology is adapted in unintended ways to meet operational needs (Wagner and Newell 2006). 
  10 
 
Choice Cruising: Customer Processes 
The Choice Cruising service promise shifts perceived control to the customer, who must 
be ready, willing, and able to co-produce the experience, much more so than on a traditional 
cruise. Given capacity constraints, customers cannot expect to dine wherever and whenever they 
wish without some planning. Choice Cruising does have rules to be followed for reservations at 
some restaurants and dining attire, though these rules are informal and variously communicated. 
LCL attracts a diverse market and appeals to first-time cruisers who are unlikely to 
possess the script knowledge needed to co-produce in a way that maximizes the efficiency of the 
service system (Bateson 2002). We found evidence to support this in the confusion some cruisers 
expressed about required reservations and cover charges at the specialty restaurants, as well as 
low occupancies of these restaurants early in the sampled cruises. Additional evidence can be 
found in online queries about how Choice Cruising works and in tips from past cruisers for how 
to take advantage of Choice Cruising (e.g., to make reservations for specialty restaurants on the 
first day of the cruise). It is clear that many LCL cruisers embarked ill-prepared to perform 
important customer processes—a finding echoed in LCL-management interviews.  
LCL’s marketing efforts to drive demand for Choice Cruising exacerbated the customer-
knowledge gap. The new marketing campaign set expectations for choice, freedom, and access 
that were not consistently met. While the “free to whatever” brand message is a powerful 
statement about how Choice Cruising differed from other cruises, it also may have confused 
customers. Finding information on the LCL Web site about restaurant reservations and cover 
charges was a daunting task: it took a research assistant 23 minutes and 21 Web page views 
before locating a Welcome Aboard document and the pertinent information. Onboard messaging 
was not sufficient to close the knowledge gap. Although customers need training to co-produce 
and enjoy the service experience, marketing communications produced by LCL were inadequate 
and counter to the promise of freedom and flexibility that is the foundation of the Choice 
Cruising service concept. In summary, LCL’s evident issues reveal service-operations problems 
that were more accurately attributable to a gap between service marketing and operations. 
 
Choice Cruising: Ongoing Effects on the Customer Experience 
LCL has continued to struggle with Choice Cruising since our participant-observation 
study. Content analysis of 1,090 reviews collected from CruisesOnly.com in 2007 show that the 
Choice concept is highly salient for the firm’s cruisers relative to dining processes of competitive 
lines, but evaluations are mixed: of the 52.5% of cruisers who referred to the Choice concept, 
46.7% evaluated the experience positively, 21% were ambivalent, and 32.3% were negative. By 
comparison, only 17.8% of 500 randomly-selected reviews of rival Festival Cruise Lines, which 
uses a semi-structured dining model, referred to dining processes (51.7 of these references were 
positive, 19.1% were ambivalent, and 29.2% were negative), and only 15% of 500 randomly-
selected reviews of Regal Cruise Lines, which uses a structured dining model, referred to dining 
processes (38.7% of these references were positive, 17.3% were ambivalent, and 44% were 
negative). Although the proportion of negative evaluations of the dining experience aboard LCL 
cruises is not significantly different than for rival firms, the relative frequency of negative 
perceptions is greater for LCL given that dining processes are three times more likely to be 
mentioned by cruisers in their evaluations of the LCL experience. A closer look at the online 
comments reveals that LCL cruisers were particularly frustrated by service from restaurant staff, 
food quality, the restaurant-reservation process, and long lines/waits to dine (Table 2).  
  11 
 
[Insert Table 2 about Here] 
 
To further examine the import of customer perceptions of Choice Cruising on their 
evaluation of the LCL cruise experience, in 2008 we collected ratings posted on the CruisesOnly 
site from 1,123 LCL cruisers, as well as ratings from more than 4,400 Festival and Regal 
cruisers. As reported in Table 3, ratings for LCL cruises are the lowest of the three competitive 
firms on all measured dimensions, and the evaluation of food/dining has the weakest score. 
 
[Insert Table 3 about Here] 
 
Separate regression analyses for the three cruise lines using the cruise attribute measures 
and covariates available on the CruisesOnly site told a similar story. A regression of the overall 
cruise rating on evaluations of ship quality, dining/food, stateroom quality, ship staff quality, and 
entertainment/activities produced significant positive coefficients across cruise lines. Of the 24 
variables included in the three regression models to control for traveler type, stateroom, and 
cruise experience, only two were significant, which suggests that these individual difference 
factors had minimal influence on cruise evaluations. Similarly, of the 52 indicator variables used 
to control for differences in cruiser evaluations attributable to the ship they sailed on, only four 
were significant (two for LCL and one each for other cruise lines), which suggests effective 
implementation of brand standards within cruise lines. Age was negatively associated with cruise 
rating for the Festival (B = -.03, p < .01) and Regal brands (B = -.03, p < .01); these cruise lines 
target younger vacationers, so this finding supports the external validity of the analysis. Sailing 
date was also negatively associated with cruise rating for LCL (B = -.03, p < .05) and Regal (B = 
-.06, p < .001), revealing that cruise evaluations have declined over time for these brands.  
The most notable finding, however, is the relatively large coefficient for LCL’s 
dining/food rating (B = .36, p <.001) when compared to the rival firms (B = .26, p <.001, for 
both Festival and Regal). For LCL, the dining/food evaluation has the largest effect on overall 
cruise rating after controlling for other factors in the model (partial r = .49). In contrast, ship 
quality (partial r = .42) and ship staff quality (partial r = .39) have a larger effect on overall 
cruise rating than dining/food (partial r = .37) for Festival Cruise Lines. For Regal Cruise Lines, 
ship quality and dining/food (partial r = .37 for both) had a more balanced effect. Moreover, the 
size of the standardized beta and partial r for the LCL’s dining/food factor is the largest across 
the three models. These comparative findings highlight the ongoing importance of the Choice 
Cruising dining experience to customers, and the deleterious effects on the overall cruise 
experience of a dining system that falls short of customer expectations. 
 
Choice Cruising Epilogue 
During the period that LCL was the focus of our empirical investigation (fall 2006 to 
spring 2008), the firm announced a spate of bad operational and financial news. In early 2007, 
LCL reduced ship capacity by two-thirds in a key cruising market due to weak yields. For the 
year, LCL lost more than $200 million—while rival cruise lines were profitable. In early 2008, a 
private equity firm bought half of LCL with a $1 billion stake, which some industry observers 
saw as a move to gain strategic control of a struggling brand. Also in 2008, the travel media 
reported on a lawsuit filed by a customer seeking class-action status for millions of fellow LCL 
cruisers who were unable to make reservations at specialty restaurants because priority was 
given to customers who paid for more expensive cabins. The suit claimed that LCL marketed 
  12 
cruises based on the Choice Cruising concept of having many restaurants to choose from, but 
that customers not in the highest cabin categories were “disenfranchised from effectively 
participating in the [Choice Cruising] program” (Jainchill 2008).  
Despite the consistent and compelling evidence from multiple data sources—anecdotal, 
participant-observation, qualitative customer comments, and quantitative ratings—that calls for 
an overhaul of the service system, LCL deepened its commitment to Choice Cruising in 2008. 
The firm launched new television commercials that compared Choice Cruising to the structured 
itineraries of competitors. Management also began a fleet-wide rollout of product enhancements, 
from new menus and dishes in all restaurants to upgraded bedding and amenities in all cabins. 
Most significant was a new ship-building initiative designed for Choice Cruising. The ships 
would be the largest to date for the cruise line and would do away with main dining rooms and 
pool-deck buffet restaurants, which further upped the ante for the Choice Cruising service model.  
 
THE LCL MARKETING-OPERATIONS GAP: INSIGHTS FROM THE LITERATURE 
The Choice Cruising case presents puzzles that continue to play out in practice and that 
warrant examination with respect to the service marketing-operations interface: How did LCL 
arrive at the service quandary that is the core of the firm’s service promise? What determined the 
service marketing-operations gap that undermines Choice Cruising? Why does LCL continue to 
support the concept despite this gap? How can LCL reduce the service marketing-operations gap 
without sacrificing the billion-dollar investment in the brand’s identity? To address these 
questions, we mine the service literature for insights. 
 
Insights from Research on New Service Development 
LCL’s Choice Cruising is a service innovation—an idea under-examined and only 
loosely defined discussed in the literature (Johnson et al. 2000). Unlike goods production, which 
is typically divorced from the customer, the customer is a supplier to service production 
(Sampson and Froehle 2006). This implies that service development should involve the customer 
in a real or simulated manner, otherwise a new or modified service may not capture the variance 
in customer inputs to and outcomes from co-production (Tsai, Verma, and Schmidt 2007).  
Service outcomes—experiences, deeds, and performances—are produced by a complex 
system of people and physical elements connected by processes through which information and 
goods flow. Predicting the interactions between elements and processes in the service system is 
difficult, especially for high-contact, customizable, extended services such as leisure cruises. The 
use of service blueprints can aid service design by mapping anticipated customer touchpoints and 
service processes to visually depict the service structure (Shostack 1984). However, few firms 
use service blueprints in this manner or understand the interrelationships of core service-delivery 
processes (Metters and Marucheck 2007). Research suggests instead that service development is 
typically an unsystematic, trial-and-error process fraught with under-designed, untested, and 
unpredictable service concepts (Froehl et al. 2000; Griffin 1997; Sundbo and Gallouj 2000).  
As revealed by the LCL context, when pressed into action by competitive exigencies, 
service firms are apt to skip deliberate planning and analysis, especially for aspects of the service 
system that are perceived to be outside of the realm of operational control and expertise, such as 
customer co-production and the interaction of customer inputs with new or untested service 
processes. As a result, new services are tested in real-time with paying customers. Such was the 
case with LCL, where the hasty rollout of Choice Cruising, backed by a new branding campaign, 
became a multi-year service experiment with customers as unwitting participants.  
  13 
 
Insights from Marketing: Customer Experience Design 
An emerging view of service highlights the psychological experience of consumption 
(Ariely and Carmon 2000; Pullman and Gross 2004). A service-dominant logic grounds this 
view and focuses on value co-creation from the customer’s perspective (Vargo and Lusch 2004).  
Customer-centricity demands a deep understanding of the needs and self-relevant goals that 
influence consumer behavior, which should form the basis of the organization’s service promise: 
the articulation of how the service delivers desired benefits. LCL’s management had a vision for 
the Choice Cruising service promise as satisfying customers’ needs for freedom and choice on a 
cruise. Whether this vision was induced by an understanding of the customer or the search for a 
competitive advantage is unclear; however, it is clear that LCL’s customers are attracted to the 
promise of Choice Cruising, at least as the concept is promoted by the firm’s brand messaging. 
Our research reveals that LCL’s customers often enter the service factory uncertain of 
their role. Edvardsson (1997) proposed that services should be designed to make it easy for 
customers to contribute to production via customer processes: activities that when transferred to 
the customer and managed well can enhance flexibility and service quality. Customers can 
improve service production if they are appropriately informed, trained, socialized, and motivated 
(Bateson 2002; Kelley, Donnelly, and Skinner 1990). Bateson (2002) argued that rather than 
trying to buffer a service’s technical core from customer disturbance, firms should find ways to 
develop customer co-production performance. LCL’s marketing and operations teams have not 
adequately trained the customer to participate in the service system. As a result LCL customers 
do not possess appropriate production knowledge, which impairs their efforts to co-create value. 
Evidence across our data sets shows customer displeasure as they try to reconcile their 
expectations for Choice Cruising with their resulting experiences. Research finds that people do 
not evaluate an experience by summing the emotional responses to transient events that comprise 
the experience; rather, gestalt characteristics, such as intense states (delight or anger), salient 
hedonic trends (intensifying pain or pleasure) and the final state (e.g., ending on a high note) 
affect summary evaluations (Ariely and Carmon 2000). From a managerial view, this means that 
service design must account for both service outcomes and emotional responses to specific 
processes and the experience sequence (Chase and Dasu 2001). As illustrated by the strong effect 
of (poor) ratings of LCL dining on the overall cruise evaluation, as well as negative comments 
(and lawsuits) about dining processes, customer reactions to Choice Cruising failures are gestalt 
characteristics that exert a disproportionate negative influence on their impressions of LCL. In 
short, fixing the dining experience clearly matters to customers—and to LCL’s future.   
  
Insights from Service Operations Management 
The Operations Management (OM) discipline, by definition, is concerned with the 
management of operations; however, Armistead (1990, p. 6) observed that “many service 
organizations have failed to realize the fundamental factors which determine the ability of 
operations management to produce and deliver a service package which matches the expectation 
of customers.” He described four key issues for service operations: identifying the organization’s 
operational focus, the task to be done, the choices for performing the task, and performance 
metrics. Similarly, Johnston (1999) suggested that OM researchers studying services should 
focus on performance quality, design, and operational improvement. We likewise believe the 
core OM concepts of designing and measuring processes offer insight into challenges with 
Choice Cruising, as well as what contribute to the service marketing-operations divide. 
  14 
From an OM perspective, systematic process design is vital to successful implementation 
of new or redesigned services. However, the question of how to go about service process design 
is relatively unexplored in OM. Whereas marketing scholars point to service blueprinting as one 
approach (Shostack 1984), operations scholars advocate such methods as prototyping and skunk 
works, though little empirical research examines the use or effectiveness of these approaches 
(c.f. Single and Spurgeon 1996). A growing body of research also shows that simulation can 
enable evaluation of service designs. Researchers have used simulation models to assess service 
capacity planning decisions in appointment systems (Vanden Bosch and Dietz 2001), customer 
waiting lines (Evangelist et al. 2002), and service networks (Pullman and Thompson 2003). Two 
simulation-based studies are particularly relevant to the Choice Cruising case. Kimes and 
Thompson (2004) examined how matching a restaurant’s table capacity with its customer mix 
can increase effective capacity, allowing it to serve more patrons in the same time. Thompson 
and Kwortnik (2008) showed how pooling reservations by table size is more efficient than 
matching each reservation to a specific table (as was being done by LCL). LCL would have 
benefited from using one or more of these design tools to work out service-delivery problems 
before commercializing the Choice Cruising system. 
Another main issue for service delivery and a core OM concept is the need to assess how 
well the service operation is doing through performance metrics that focus on key processes and 
outcomes. Spitzer (2007) identified such metrics as customer engagement, customer loyalty, 
collaboration, productivity, and waste. He called these metrics “transformational” because they 
require that performance be measured holistically, rather than the more common task-specific 
(silo-based) measures of performance. Holistic measures highlight interdependencies between 
functional areas (Morgan and Rao 2002). To the best of our knowledge, however, LCL used 
standard operational metrics (e.g., total meals served per restaurant) and customer-satisfaction 
scores that, though insightful in suggesting problems with service delivery, are limited. Perhaps 
more effective would be a holistic, transformational metric such as a customer-productivity 
metric that measures both co-production knowledge customers bring to the consumption setting 
(capturing marketing’s effectiveness in educating customers) as well as customer-process action 
(capturing the degree to which customers perform activities designed for their co-production).  
 
Insights from Work Integrating Marketing and Operations 
Research that examines service marketing-operations integration is sparse, though a few 
studies highlight the benefits of taking a holistic, systems view of service development and 
management. Using pizza delivery as a context, Verma, Thompson and Louviere (1999) showed 
how marketing tactics (e.g., discount on a second pizza) and operations decisions (e.g., delivery 
times) can affect customers’ choices and subsequent market share, and how managers can use 
this information to guide integrated marketing and operations decisions. Evangelist et al. (2002) 
developed a process model for Blockbuster, Inc., that linked marketing and operations. Using a 
simulation approach, the researchers showed the system of effects that occur when marketing 
programs cause unexpected changes in operations. Similarly, Pullman and Thompson (2003) 
constructed an integrated model for a ski resort to evaluate operations efforts (e.g., capacity 
additions) and marketing efforts (e.g., moving demand from weekend to weekday). They found 
that an initiative advocated by marketing—changing the customer mix—significantly degraded 
service levels experienced by customers as measured as the waiting time for ski lifts.  
 
Literature Summary 
  15 
As our review of the relevant services, marketing, and operations-management literatures 
reveals, there is useful conceptual and empirical counsel available to managers who seek it out. 
Indeed, Malhotra and Sharma (2002) noted: “the importance of better managing the interface 
between marketing and operations…has been well understood by academics and practitioners for 
a long time.” Scholars have identified challenges for service development (e.g., customer co-
production) and methods for addressing these challenges (e.g., service blueprints). Research on 
customer experience design underscores the importance of translating customer needs into a core 
service promise and specific customer processes for enhancing the service experience. OM 
research and studies of the marketing-operations interface illustrate how firms can better manage 
service delivery by using holistic models and measures, as well as simulation methods to test 
interactive service systems. In sum, knowledge exists in the literature to prevent service failures; 
we next apply this knowledge to the LCL case to draw conclusions and ideas for improved 
management of the service marketing-operation integrated function.  
 
DISCUSSION 
LCL ventured into uncharted waters with Choice Cruising—a bold idea, especially given 
the industry’s traditional operating model. In theory, the concept offered customers the ability to 
design a cruise experience to suit their personal preferences. LCL has invested billions of dollars 
into purpose-built ships, brand-building marketing, information technology, employee training, 
and other initiatives designed to support the concept. However, the findings presented in this 
paper suggest that Choice Cruising is a classic case of marketing/operations discontinuity. 
Simply put, marketing is selling customers a service promise that operations has been unable to 
deliver effectively. We envision two solutions to this problem, which we describe below. 
 
Service Operations Systems (SOS): An Analytic Model  
The Choice Cruising challenge shows that the reality of the context—changing market 
preferences, competitive pressures, the need for speed, and extant organizational structures and 
decision processes—can preclude the cross-functional coordination advocated by academics to 
better ensure service innovation success (Evangelist et al. 2002; Griffin 1997). Prescriptive 
approaches to service design such as quality function deployment (Dube, Johnson, and Renaghan 
1999), customer choice modeling (Verma et al. 2001), and the service planning cycle (Tax and 
Stuart 1997) are complex and arguably cumbersome methods that require an understanding of 
scientific management approaches that are uncommon competencies in most service firms 
(Gummesson 2000; Metters and Marucheck 2007). As a result, service development becomes a 
trial-and-error process of major changes and incremental fixes—as illustrated by LCL’s ongoing 
efforts to patch Choice Cruising. Scheuing and Johnson (1989, p. 28) aptly depict this problem: 
“Driven by a sense of urgency and a perceived need for the ‘quick fix,’ many service firms jump 
right into idea generation. Doing this is akin to lifting anchor without first determining the 
desired destination. The course of the ship then becomes the result of whim and happenstance.”  
The potential risks and rewards of service innovation require a methodical and holistic 
approach to service design that is fathomable for non-management-scientists charged with 
conceiving and implementing the process. We advocate the Service Operations Systems (SOS) 
model (Figure 2) as a starting point. This inductively-derived conceptual model depicts the 
process relationships revealed in our data-driven analysis of the LCL case and augmented by the 
literature. The SOS model accounts for interconnectedness of the service promise, operational 
processes, and management systems across functional areas, as well as the importance of co-
  16 
opting customer knowledge and skills as inputs to the system (Prahalad and Ramaswamy 2000; 
Vargo and Lusch 2004). The key components of the SOS model include: 
 
[Insert Figure 2 about Here] 
 
 Service Promise and Concept. An organization’s service promise states how the service 
fundamentally delivers value to customers, such as LCL’s promise to give cruisers time 
and activity freedom. Whereas the service promise may be abstract, the service concept is 
a more concrete articulation of how key elements of the promise map onto core customer 
needs (Edvardsson 1997), such as how LCL’s unstructured dining model corresponds to 
cruisers’ purported need for freedom of choice and lack of structure when vacationing. 
The service promise and concept should, therefore, guide development and management 
of the service system. Processes that do not align with the service promise and concept 
require redesign. In the Choice Cruising context, service system elements such as the 
restaurant reservation process and table management application are not well aligned 
with service concept elements of freedom, choice, and flexibility. This view reflects 
several findings, most notably that guest frustration with Choice Dining is a function of a 
marketing-operations disconnect and not just flawed operational processes. 
 Customer Inputs. Because customers are inputs to the service system, uncontrolled 
variability in the customer input reduces the firm’s ability to effectively and efficiently 
deliver the service product. In communicating the service promise, marketing not only 
sets expectations for the experience, but also begins the process of customer shaping 
through education and socialization. Much like new employees, new customers in 
particular may need additional education and training to learn how best to co-produce to 
yield experiences that match their expectations, especially for an innovative service. In 
LCL’s case, customer expectations and co-production knowledge are highly variable, but 
marketing communications and customer-process information (pre-board and on-board) 
are insufficient for standardizing the customer input—and setting more realistic 
expectations for the Choice Cruise experience. 
 Customer Processes. A unique aspect of the SOS model is the explicit role for 
customers as productive resources. Managing customers as inputs to the service system 
requires guidance from operations about marketing programs that affect customer 
knowledge and co-production processes (Evangelist et al. 2002). Such an adjustment to 
service management is consistent with a coordinated approach to service delivery, as 
opposed to independent management of marketing and operations (Verma et al. 2001). 
LCL’s customers are expected to co-produce by performing such processes as making 
reservations and attending to the electronic restaurant seating guides to avoid waits. 
Customers are not equally prepared to do this; however, LCL has no mechanism for 
identifying and training customers who require service socialization. Customers are also 
not provided with consistently useful and accurate information (e.g., correct restaurant 
occupancy) to facilitate customer processes critical to co-producing the service. 
 Employee Processes. Employees can help customers co-produce by educating customers 
about the experience, suggesting choices to aid customers’ decisions, and performing 
service recovery when service fails. This requires employee training, as well as IT that 
facilitates employee processes without workarounds that undermine the system. LCL 
employees should be trained to offer suggestions to customers when dining choices 
cannot be accommodated. Training would also ensure that employees do not undermine 
  17 
the system by, for example, blocking tables in the table management application that 
result in the electronic seating guides misrepresenting restaurant occupancies. 
 Technology Processes. Given the trend of buying standard software products off-the-
shelf, firms must be ready to adapt the IT product—or employ external expertise to 
customize a solution. For LCL, having applications that are purpose-built to facilitate 
Choice Cruising (e.g., that permit quick views of restaurants and the ability to reserve 
tables at any restaurant) would have been far preferable to ad-hoc attempts to modify the 
InfoDine application far outside its original design scope.  
 Service Processes. Service processes must align with a firm’s service promise. Dining is 
a main appeal of cruising (Dickinson and Vladimir 1997). Displeasure with the dining 
experience is a gestalt factor that strongly affects overall satisfaction, as our regression 
results for LCL demonstrated. Choice Dining is undermined by pre-dining processes 
(e.g., reservations and queues) that create uncertainty for guests. Not all guests are aware 
that reservations are required or even possible. Guests do not expect to wait or be turned 
away, and this leads to frustration when they see empty tables. These problems are not 
mitigated by reservations agents or hosts through assistance with the process, so many 
guests are disappointed, in search of a place to eat, but unsure of where to turn next. Such 
negative experiential outcomes violate the service promise. 
 Customer Outcomes. Service systems require metrics that reflect whether a service is 
being delivered consistent with its design, and that intended experiences are resonating 
with customers. In addition to standard measures of overall and process-level customer 
satisfaction and operational performance, firms should measure emotions associated with 
salient experiences, such as delight produced by pleasant surprises. When customers play 
a co-production role, measures of customer knowledge development and sourcing are 
also important for identifying shortcomings in customer-process performance. Finally, 
tracking customer loyalty and linking this behavior with operational measures is also 
critical. A drop in rebooking numbers could signal that the service promise is not being 
met in terms of some specific service process. 
 Information Systems: For many services, information systems are vital for capturing, 
transforming, and transmitting data to develop knowledge-based competencies (Vargo 
and Lusch 2004). Knowledge gaps and organizational silos hinder learning and system 
improvement. Information gleaned from customers and service-performance metrics 
should be cycled back into the system to close knowledge gaps, as well as to shape future 
customer education and socialization. For example, Choice Cruising requires real-time 
data about restaurant occupancies and reservations, as well as measures that track process 
performance, such as the percentage of reservations accepted, average waits for walk-up 
customers, and the percentage of guests who are redirected to alternative venues when 
first choices are unavailable. The concept also demands data to better illustrate 
customers’ expectations, the knowledge they possess for co-production, and the 
effectiveness of their training (Bateson 2002). Analysis of this information might suggest 
changes to customer processes, for instance the need for an information session for new 
cruisers to learn how to co-produce. IT also should enable monitoring of guest behavior 
(e.g., reservation requests) to determine if successful co-production is occurring.  
 
SOS Summary 
  18 
While the Service Operations Systems model and associated ideas for service design and 
analysis have promise for service management, on its own, the model could fall into the category 
of academic literature that “sound good in theory,” but receive little application in practice (to 
wit, see the literature already cited). The simple reason for this is, we believe, that the model 
advocates a holistic view of the service product, whereas most managers apply a myopic view of 
their own functional area. Perpetuating this problem are siloed organizational structures that do 
little to enable cross-functional knowledge creation and exchange. Only by having an integrated 
approach to service design, marketing, and delivery can organizations hope to avoid service-
system challenges like Choice Cruising. For this to occur, we propose a new organizational form 
and function to reduce the marketing-operations divide.  
 
Unifying Service Marketing-Operations with Service Experience Management 
The Choice Cruising case shows that coordination is critical between marketing and 
operations not only during service development, but also during ongoing service management. 
Marketing and operations must be able to jointly determine the design of the service system, how 
to adapt a service that is not working as planned, or when to pull the plug on a service that is 
beyond recovery. Such coordinated action is difficult in contexts where marketing and operations 
are separate departments with distinctly different purposes and tasks. We observed this problem 
at LCL, where managers talked about the “hand off” of the guest from marketing to operations, 
instead of cross-functional management of the service experience throughout the consumption 
cycle. A look at LCL’s organizational structure revealed that no one person or department was 
responsible for ensuring that operations was able to keep the promises that marketing made to 
customers. What was needed, then, was an integrating function, which we call service experience 
management (SEM), which unifies service management (process/operations) and customer 
management (experience/marketing).  
We envision SEM as a new functional area sufficiently high in the organizational 
hierarchy such that marketing and operations are its reports. We argue for the elevation of SEM 
in the organization because this department, group, or person would advocate for the customer 
and the operations team to ensure that customers get what they want given realistic operational 
capabilities. In other words, SEM would use the Service Operations Systems model as a guiding 
framework for aligning the organization under the firm’s service promise and concept. 
To explore potential forms and functions of SEM, we examined qualitative data collected 
via survey from executives of 16 cruise lines. All of the firms claim to perform customer-
satisfaction monitoring and quality assurance, though responsibility for these tasks is variously 
located in marketing, operations, and customer service. More often the firms use a standing 
committee that meets regularly (from weekly to monthly) to review new product and marketing 
initiatives, as well as feedback from customer comments and satisfaction measures. In fact, 9 of 
the 16 cruise lines used some form of high-level (i.e., VP or higher) inter-departmental team (an 
“executive committee” or “marketing committee,” though labeled the “guest experience team” at 
one firm) for SEM. Four of the firms had no such integrating function and instead relied upon 
informal coordination across marketing and operations areas. Size of the firm did not matter: the 
committee approach to managing the operations-marketing interface was as likely to be used by 
small, two-ship companies that carried a few thousand cruisers per year, to large, multi-ship 
firms that carried millions of customers.  
Perhaps the most important finding from the cruise-executive data is a trend toward 
formalizing SEM along the lines we advocate in this paper. Only one cruise line has an SEM 
function—a four-person team called the Operations Integration Group that reports to the SVP of 
  19 
Operations, and that sits on planning, marketing, and operations meetings to “ensure that 
operations is aligned with marketing.” However, three cruise lines announced in 2008 new 
positions that are consistent with the SEM concept. For example, one small cruise line 
established a Director of Product Marketing who is tasked with “the product vision for 
reservations, messaging, the onboard experience, etc.” A large cruise line is in the process of 
hiring a VP of Guest Experience who “understands what the product needs to deliver,” and who 
will report to the newly created position, EVP of Marketing and Guest Experience. Finally, and 
most notably, LCL, announced a new position, EVP and Chief Product Officer, and promoted a 
marketing executive into the role, described as overseeing a “multidisciplinary project team” and 
taking broad responsibility for the Choice Cruising product to ensure that it is aligned with the 
marketing and brand positioning of the company.  
The cruise industry—and the hospitality industry more broadly—is a fertile context for 
service experience management to emerge as an interdisciplinary approach for better integrating 
service marketing and operations because of the focus on experience as core product. A service-
dominant-logic view of co-production, process and knowledge management, and experiential 
outcomes of service products (Vargo and Lusch 2004), argues for SEM as a key function for 
many other services as well. For example, in 2006 a legacy U.S. airline sought candidates for 
VP-Customer Experience (“airline experience is not required, but hospitality experience is 
definitely required”). The ideal candidate had to understand customer service, but also airline 
and airport operations (e.g., onboard, gate, security, online experience, baggage, call center, 
reservations, etc.). To highlight the importance of the position, compensation was pegged at 
2
“mid 200s + 45% target bonus + equity.”  In another example, a retail bank created a Chief 
Customer Officer position with the defined role of “articulating the service experience (value 
proposition), ensuring that human and operational resources were aligned to deliver it, and then 
3
measuring gaps and making process improvements.”  
Other services for which value is largely determined by operations-enabled customer 
experiences include financial, healthcare, information systems, and retailing. Except for retailing, 
though, experience management (customer, guest, service, or otherwise) is relatively rare. An 
examination of position announcements in October 2008 on the popular employment website, 
Monster.com for service experience management revealed no listings, and of the 50 listings that 
included the search terms “service” and “experience,” nearly all were for customer-service 
representative jobs or some variant thereof. A search using the terms “customer” and 
“experience” yielded 73 postings—only 5 of which were for management positions that linked 
marketing and operations through activities such as monitoring customer satisfaction and 
experience, customer advocacy within the firm, and customer-defined process improvement and 
quality initiatives. Three of these positions were for healthcare-related services; the other two 
positions were located in the information technology sector. Another five postings were for 
traditional marketing research or quality assurance positions—but not for cross-functional roles. 
The remaining 86% of the listings were for customer service representative, retail/sales, or 
customer relationship management. These findings echo the concern advanced by Palmer (2008) 
that customer experience management is merely an extension of customer relationship 
management, despite the shortcomings of the latter as an effort to better integrate the firm around 
the relationship with the customer. 
SEM is fundamentally different than customer experience management because of SEM’s 
focus on management of the service operations system (as opposed to management of the firm-
                                                 
2
 This example is from a private email correspondence between one of the authors and an executive recruiter.  
3
 This example is from an academic colleague who served in this Chief Customer Officer role. 
  20 
customer relationship). As such, we see an opportunity for SEM to break free from the customer 
experience management (and customer relationship management) to become a new a functional 
area in the service firm that targets the systematic management of service experiences through 
the integration of service management and customer management. 
 
A Call for Research on Service Experience Management 
Given the paucity of research on the intersection of service marketing and operations, 
SEM is ripe for examination. A first step in such a research program would be to verify that 
organizations with SEM perform better than those that without such a function. Again, one of the 
most puzzling aspects of Choice Cruising is that we observed service problems more than eight 
years after the concept’s launch. While we generalize from a single case study in this paper, we 
propose that SEM will reduce the likelihood of problematic service concepts being implemented, 
and will offer a quicker resolution when SOS crises arise. Nevertheless, this is an empirical 
question. It would be difficult to test SEM efficacy in controlled experiments, though quasi-
experimental field studies could permit comparison of firms within an industry to examine the 
effects of SEM (and/or the application of the SOS model to guide SEM) on such outcome factors 
as service innovation success, service quality, and customer and employee satisfaction. 
Another area of investigation is identification of type of organizational structure that is 
appropriate for integrating the marketing and operations functions given the service context. 
SEM need not be one-size-fits all and may vary in form and scope. For example, although we 
envision SEM as a new department alongside more traditional functional areas, SEM could be 
coordinated under a single person in the organization, perhaps an EVP of SEM. Another way of 
delivering SEM is via a high-level committee comprised of VPs of marketing, operations, 
information systems, and other areas with broad, but related, responsibilities. SEM scope might 
range from a strong unifying function with the authority to bring marketing and operations into 
alignment, to a linking function that merely facilitates cross-functional knowledge sharing and 
decision making. Research that draws on organizational theory could examine which form of 
SEM would be most effective for new service development and/or SOS management depending 
upon such contextual factors as industry characteristics and dynamics, competition, service-
system complexity, firm size, and level of customer co-production. A starting point for such 
research might be the development of a typology of SEM forms crossed by SEM scope. By 
exploring such a typology in light of contextual factors, scholars might develop a contingency 
framework to guide research on SEM and application of the SEM function in practice. 
Finally, SEM offers opportunities for a new research paradigm and movement away from 
narrowly-focused, single-discipline-oriented investigations. Papers taking a holistic approach to 
the customer and service-provider experience could become more prevalent. In the short term, 
this argues for more cross-disciplinary research teams. We propose that, in addition to marketing 
and operations management, SEM is a discipline that should interest scholars studying human 
resources, organizational behavior, strategy, and information systems. Academic journals also 
need to foster multidisciplinary research; without that happening, paradigm-shifting integrative 
research will never take off. The Journal of Service Research, by its very name and mission, is 
positioned to be a key player in the integration, as reflected in the editor’s recent call for research 
that is methodologically diverse and cross-disciplinary in focus (Parasuraman 2007). 
 
Conclusion 
  21 
The LCL Choice Cruising case provides a compelling example of the difficulties firms 
face when designing and managing service systems, especially when marketing and operations 
functions are not well-integrated. Improving service management demands a holistic picture of 
the system and cross-functional analysis of interactive effects and process linkages—a 
perspective presented in our Service Operations Systems model and conceptualization of the 
service experience management function. We hope these contributions will guide researchers in 
the further development of service-centered theoretical and/or product opportunities—and will 
help managers to avoid “save our service” distress calls.  
 
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  24 
TABLE 1 
Choice Cruising Dining Options 
    
Restaurant Description Cover Charge Seating Capacity 
    
Grand Dining Room Main restaurant No Cover 552 
Sea View Dining Room Main restaurant No Cover 310 
Lido Café Indoor Buffet No Cover 430 
Pool-side Grill Outdoor Buffet No Cover 225 
American Grill Specialty: American No Cover 100 
Italian Trattoria Specialty: Italian No Cover 120 (estimated) 
Tapas Restaurant Specialty: Latin No Cover 94 
Asian Garden Specialty: Pan Asian Cover 32 
Sushi & Sashimi Bar Specialty: Asian Cover 10 
The Steakhouse Specialty: American Cover 168 
The Orient Room Specialty: Asian Cover 108 
Le Bistro a Manger Specialty: French Cover 129 
   1623/2278* 
    
*
Total dining capacity is 2,278 seats; however, the Pool-side Grill is not open for dinner and the Lido 
Café does not offer table service; a more realistic estimate of dining capacity at sit-down, table-service 
restaurants is 1,623 seats. The ship’s passenger capacity is 2,466, two passengers per cabin, with a 
maximum capacity of 2,816 passengers including upper and sofa berths; therefore, the dining rooms can 
handle approximately 57.5% of guests when the ship sails full. 
 
 
TABLE 2 
Choice Cruising: Negative and Positive Attributes Derived from Customer Comments 
     
Negative Attributes* Count  Positive Attributes Count 
     
Poor service from restaurant staff 171  Good food quality 194 
Poor food quality 165  Flexibility of experience 189 
Need for or problems with reservations 140  Choice of restaurants 155 
Long lines and waits to dine 121  Good service from restaurant staff 88 
Cover charges for specialty restaurants 96  Relaxing experience 36 
Poor food selection or variety 56    
Could not get into specialty restaurants 48    
Automatic service charges 23    
Inflexible: could not eat when one wants  14    
Meals took too long 11    
Atmosphere was too casual 11    
Could not meet other cruisers 10    
     
*Attribute categories were derived from content analysis of 1,090 customer reviews on 
www.cruisesonly.com. Customer comments were evaluated and assigned to attribute categories such that 
multiple comments by one customer about an attribute were counted only once for that attribute.  
  25 
 
TABLE 3 
Descriptive Statistics for Key CruisesOnly Cruise Reviews 
    
 LCL: Festival:  Regal: 
unstructured semi-structured structured 
dining dining \dining 
 Mean (SD) Mean (SD) Mean (SD) 
    
Overall Rating 3.98 (1.55) 4.57 (1.30) 4.74 (1.20) 
Ship Quality 4.43 (1.36) 4.70 (1.21) 4.92 (1.13) 
Dining/Food 3.91 (1.52) 4.64 (1.32) 4.68 (1.25) 
Stateroom Quality 4.28 (1.39) 4.93 (1.09) 4.66 (1.24) 
Ship Staff Quality 4.48 (1.57) 5.03 (1.22) 5.15 (1.13) 
Entertainment & Activities 4.06 (1.39) 4.51 (1.29) 4.68 (1.19) 
    
Notes: Ratings are on a 6-point “smiley-face scale,” with higher numbers indicating better scores. LCL, N 
= 1,123; Festival, N = 2,432; Regal, N = 1,995. 
 
 
 
TABLE 4 
Regression of Customer Cruise Rating on Key Cruise Attributes and Covariates 
         
 LCL  Festival  Regal 
         
 Beta Partial r  Beta Partial r  Beta Partial r 
         
Ship Quality .21*** .27  .36*** .42  .32*** .37 
Dining/Food .36*** .49  .26*** .37  .26*** .37 
Stateroom Quality .13*** .19  .08*** .12  .14*** .19 
Ship Staff Quality .25*** .34  .21*** .39  .22*** .30 
Entertainment/Activities .12*** .20  .17*** .26  .12*** .19 
Sailing Date -.03* -.07  -.01 -.02  -.06*** -.12 
Age -.00 -.01  -.03** -.05  -.03** -.06 
Cruise Experience -.00 -.01  .01 .02  -.00 -.00 
         
F statistic 206.54   227.29   192.41  
2
R  0.83   0.77   0.77  
         
Notes: Additional categorical covariates included traveler type (family with older children, family with 
younger children, single/friends, group), stateroom type (inside cabin, ocean view cabin, suite), and ship; 
however, with only a few exceptions, these control variables were not significant and are not reported here. 
*** p < .001; ** p  < .01; * p < .05 
  
  26 
 
FIGURE 1
Service Operations Systems Model
Customer Socialization Organizational Learning
Service Promise and Concept
Services Operations Systems
Customer Customer 
Inputs Outcomes
Expectations Satisfaction
Experiences Customer Employee Technology Service Experiences
Knowledge Processes Processes Processes Processes Knowledge
Skills Loyalty
Information Systems
Customer Profiling Experience Measurement
Adapted from Edvardsson (1997)