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Co-production: A Fair-Weather syndrome?

Tor W. Andreassen Anders Gustafsson Heiko Gebauer Tor W. Andreassen is chair and professor of marketing at BI Norwegian School of Management and Karlstad University, Center for Service Research* Anders Gustafsson is a professor of marketing at Karlstad University, Center for Service Research and at BI Norwegian School of Management Heiko Gebauer is an associate professor for service management at the Institute of Technology Management at University of St.Gallen. * Corresponding author BI Norwegian School of Management Nydalsveien 37 N-0442 Oslo Norway Email: tor.w.andreassen@bi.no UNDER REVIEW AT JOURNAL OF THE ACADEMY OF MARKETING SCIENCE. PLEASE DO NOT QUOTE OR CITE WITHOUT THE CONCENT OF THE AUTHORS Acknowledgement The authors recognize the valuable help from Mads Erik Erikson and Jim Fossheim in collecting data for this research. All authors have contributed equally to the paper.

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Abstract

An emerging perspective in marketing considers customers as being actively

involved in the production, delivery, and consumption of services. The terms used to

describe this involvement include co-production, servuction, co-creation, and

prosumption. This paper investigates the assumed positive associations between

Prahalad’s (2004) five co-production elements (customer engagement, self-service,

customer involvement, problem solving, and co-designing), and value co-production,

as well as the positive association between value co-production and behavioral

intension. Contrary to conventional thinking, the study found that those customers

who have an option would like to co-produce in all elements except problem solving.

This finding is robust across highly and slightly experienced users. Consequently, this

paper concludes that co-production reflects the ‘fair-weather syndrome’; that is,

customers are only willing to co-produce when the service functions as expected.

This paper offers three theoretical and managerial contributions. We document that

although co-production is a multifaceted construct, not all elements contribute equally

to value co-production. Self-service and co-designing contribute more strongly, while

customer engagement and customer involvement contribute incrementally.

Furthermore, willingness to co-produce is asymmetric in that it takes place only when

customers experience a positive value creation. Finally, the paper provides a valid

measurement scale for co-production.

Key words: co-production, co-creation, self-service, problem solving

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Value Co-production: A Fair-Weather Syndrome?

1 Introduction

Value co-production frameworks are increasingly relevant to understanding

management and organizational practices for the creation of new business

opportunities (Ramirez 1999). Such frameworks arose from the changing view of

consumers as creative actors in a value-creating process rather than as passive

responders. Four terms have been used to capture the changing role of consumers:

prosumption, servuction, co-production, and co-creation (Toffler 1980, Vargo and

Lusch 2004; Prahalad and Ramaswamy 2004; Ramirez 1999). Some researchers

have argued that customers co-create for their own consumption (Xie et al. 2007).

In the service-dominant logic (Vargo and Lusch 2004), co-production and co-creation

are defined as phenomena that are connected to the production and delivery of

service; that is, how firms deal with their customers by involving customer

participation in the joint creation of service value (Vargo and Lusch 2008, Etgar

2008). The sixth fundamental premise of service dominant logic argues that,

regardless of the service offer’s degree of tangibility, “The customer is always a co-

creator of value” (Vargo and Lusch 2008, p. 2). The growing interest in the role of

customers as co-producers has arisen from the emergence of standardized,

inexpensive technology and communication networks such as the Internet (Yadav

and Varadarajan 2005). The Internet has enabled companies to communicate

directly with all their customers, which, in turn, enables customization and co-

production to a larger extent. Today, value co-production takes many forms, and

companies are continuously introducing new means for including their customers in

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the value production process. Embedded in the co-production logic is an assumption

that co-production occurs during all steps of the production, delivery, and

consumption processes, even in service recovery. In order to cover co-production

comprehensively across production, delivery, consumption, and recovery processes,

Prahalad (2004) introduced the five following elements of value co-production:

customer engagement, self-service, customer involvement, problem solving, and co-

design.

While a growing body of research has focused on co-production, surprisingly

few researchers, if any, have challenged the embedded logic of co-production, which

states that the customer is always willing and able to co-produce value. A noteworthy

exception is Bendapudi and Leone’s (2003) investigation of the psychological

implications of customer participation in co-production and Grönroos’s (2011

fortcoming) discussion of value-co-creation in service logic. By challenging the

assumed positive association between self-service technologies and value co-

production, these authors argued that customers who participate in value co-

production tend to have a self-serving bias, but also that such a tendency is reduced

when customers have the choice to participate. In order for self-service technologies

to contribute positively to value co-production, companies should generally provide

customers with the option to use a self-service alternative or a staffed counter.

The present study challenges the basic assumption that customers are always

willing to co-create value, including service recovery. We test the positive association

between Prahalad’s (2004) five elements of value co-production, as well as the

positive association between value co-production and behavioral intension. The

study makes several contributions to the literature. Firstly, it documents whether

customers wish to co-produce in all elements of an interaction, which provides a

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framework to help organizations manage the co-creation process (Payne et al. 2008).

Secondly, customers are willing to co-produce in all but problem solving for

recovering services. This finding follows Dong, Evans and Zou’s (2008)

recommendation to deepen the understanding of how service recovery can be

embedded in the value co-production literature. Thirdly, by conceptualizing and

operationalizing the constructs and items related to value co-production, we develop

valid measurement scales that can guide future research on scale development.

Finally, the findings of the study substantiate Prahalad’s (2004) assumption that

value co-production is a multi-faceted construct.

The next section elaborates on our conceptual model, which forms the basis

for the hypotheses and empirical testing. The paper concludes by discussing the

findings, their managerial implications, and recommendations for future research.

2 The Conceptual Model 2.1 Terminology and nature of value co-production

In the literature on value co-production, it is possible to discern the four

following similar terms: (i) ‘pro-sumption’, (ii) servuction, (iii) co-production, and (iv)

co-creation.

The term ‘pro-sumption’ or ‘prosumer’ has been used in three different ways.

Toffler (1980) introduced it as an abbreviated form of “producer and consumer.”

Toffler argued that the role of consumers was changing towards that of prosumers;

that is, they were becoming active parties in producing value. For example, beyond

the image value a car provides, its value to the owner only emerges when the owner

drives the car. Consequently, the owner becomes a producer and consumer of value

(Toffler 1980; Kotler 1986; Tapscott and Williams 2006). The term pro-sumption

indicates a more active role for the consumer, as a participant in the value-production

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process. Unlike Toffler, Humphreys and Grayson (2008) used the term to combine

the meanings of ‘professional’ and ‘consumer.’ In this sense, prosumer refers to an

expert-user who demands advanced and/or high-performance features. As Troye

(1999) explained, the success of the consumers’ role as a prosumer depends on their

qualifications and interests. Finally, the customers’ role in the production process has

been discussed in postmodernism, where customers act as customizers and

producers who look for more active roles in the production and delivery processes

(Firat and Venkatesh 1993; Firat et al. 1995).

The term ‘servuction’ (short for service production; Langeard and Eiglier 1987)

reflects a high degree of involvement by clients in the service production process.

The servuction system accounts for the relations between the elements of an eco-

system that consists of the client, the physical medium, the contact personnel, the

service, the system of internal organization, and other clients. One of the underlying

assumptions in a servuction system is that customers form a relationship with a

service provider. On one hand, this service relationship comprises operational

relations or interactions (co-production); on the other hand, it comprises the social

relations that control and regulate (by contract or convention) the action in question

(Gallouj 2002).

Co-production was developed in the early 1930s, when supermarkets

implemented models of customer co-production by allowing customers to select

items from shelves, load them in carts, and transport their carts to the check-out

(Bendapudi and Leone 2003). According to Brudney and England (1983), co-

production describes the degree of overlap between the sphere of a conventional

producer and the sphere of a conventional consumer. In the context of public service,

Whitaker (1980) and Levine and Fisher (1984) both used the term ‘co-production’ to

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describe the participation of citizens in the delivery of public services. Similarly, Sharp

(1980) referred to the co-production of urban services and the involvement of citizens

in co-producing safety and security in the community.

As the concept evolved, customers came to be viewed as free-of-charge part-

time employees in co-production. As such, customers may become a potential

source of competitive advantage (Ramirez 1993). Further contributions to the

evolution of the concept include those by Lovelock and Young (1979) and Mills,

Chase, and Marguiles (1983), who began to consider customers as potential sources

of productivity gains. More recently, co-production has been seen as part of the

changing customer’s role, from being passive to being active co-creators of

experience. Companies can achieve a competitive advantage by leveraging and

including customers’ competence (Prahalad and Ramaswamy 2000) through a

process of resource integration (Vargo and Lusch 2006). The argument that

customers take part in the production process as co-producers was used in the

conceptualization of service-dominant logic (Vargo and Lusch, 2004).

The term ‘value co-creation’ started with the transition from a product-centric

and firm-centric view to a more personalized, consumer-experienced view. Pine and

Gilmore (1999) described value co-creation as the process of informed, networked,

empowered, and active consumers increasingly co-creating value in conjunction with

the firm. In Pine and Gilmore’s world view, the interaction between the firm and the

consumer has become the locus of value creation and value extraction. Prahalad and

Ramaswamy (2004) elaborated on the changing role of the consumer, which they

saw as moving from passive to active, from isolated to connected, and from unaware

to informed. The fundamental insight behind the co-creation concept is that the

customer is involved, together with the producer, in creating value. However, we

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have not found a conceptual definition of co-creation that is clear and distinct, or

distinguishes the term from co-production. Because co-production seems to have a

longer history in the literature and captures the meaning that this paper wishes to

communicate, this term is used henceforth.

2.2 Main elements of co-production

Co-production occurs throughout a product or service’s lifetime, from the

customers’ initial information search (e.g., reading adverts), to active usage (e.g.,

driving a car), and finally to value destruction. As such, co-production depends on the

customer and the company jointly defining and solving the problem. Co-production is

also related to the experience environment, wherein consumers can have active

dialogue and co-construct personalized experiences (Prahalad 2004; Bendapudi and

Leone 2003; Payne et al. 2009). Reflecting the various aspects of value co-

production, our point of departure is Prahalad’s (2004) five elements of co-production

(customer engagement, self-service, customer involvement, problem solving, and co-

designing). The conceptual model in the following section elaborates on Prahalad’s

(2004) five elements. Each element is defined conceptually and substantiated

theoretically. In addition, simple examples are used to illustrate the elements and

their practical importance.

2.2.1 Customer Engagement

Prahalad (2004, p. 23) defined customer engagement as “when firms try to

persuade customers through advertising and promotions.” This definition is

somewhat narrower than that offered by van Doorn et al. (2010): “A customer’s

behavioral manifestations that have a brand or firm focus, beyond purchase, resulting

from motivational drivers” (p 254). Manifestation beyond purchase could involve, for

example, customers writing recommendations about a firm (e.g., Yelp.com),

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reviewing a book (e.g., Amazon.com), registering as visitors with a firm (e.g.,

Foursquare.com), or engaging in Interent-based discussion forums for specific

products or services. Because the present study is framed within Prahalad’s

framework, his narrow definition of customer engagement is used herein.

Specifically, firms try to engage customers cognitively and emotionally, if not

physically, in the act of co-production. An example of engaging customers is when

service providers use advertising and marketing activities to try to involve and

activate the receiver of the message. The Elaborate Learning Model (see Petty and

Wegener (1999) for a review) suggests that beliefs about an object are integrated in

the attitude formation process through two distinct processes: the central route or the

peripheral route. Via the central route, attitudes are shaped by a rational process that

involves critical thinking regarding beliefs. Via the peripheral route, attitudes are

shaped with little (or no) conscious thought about beliefs; instead, they are primarily

shaped by the application of so-called heuristics as a means to reduce effort in

decision making. Therefore, firms that wish to impact their customers’ attitudes must

involve them cognitively in their advertising, through something that will trigger the

central route of cognition. The brand Absolut Vodka cognitively involved readers of

their advertising by having them find the hidden bottle or bottle shape in

advertisements. Other ways of engaging customers include using coupons that must

be cut out and sent to the supplier to be honored, or requiring that customers submit

answers to participate in a contest. The underlying motive for engaging consumers is

to make them more cognitively involved, and thereby more favorably disposed toward

relationships with service providers (Celsi and Olson 1988; Park and Hastak 1994).

2.2.2 Self-Service

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The past decade has witnessed rapid growth in self-service that allows

consumers to take on the traditional role of a service worker in the provision of a

service. Among the best known self-service technologies are ATM banking, Internet

shopping, pay-at-the-pump gas terminals, and various automated telephone services

(Meuter et al. 2000). Rapidly evolving technology has made it more likely that self-

service will become part of value co-production (Peppard and Rylander 2006). Self-

service often involves technologies that enable customers to order, buy, and

exchange companies’ products or services without any direct interaction with

company employees (Meuter et al. 2000). There are three pillars to the rationale for

implementing self-service: reduced costs (Normann and Ramirez 1993), increased

customer satisfaction, and increased customer loyalty (Selnes and Hansen 2001).

While self-check-in and electronic tickets are typical illustrations of reducing service

costs, increased access to an online helpdesk or self-diagnosis features on copying

machines and printers are associated with increased service, customer satisfaction,

and loyalty. Self-service technologies that help customers use products or services

are also considered useful ways to attract new customer segments with less

advanced technical skills (Bitner et al. 2002).

2.2.3 Customer involvement

Prahalad (2004) defined the customer involvement element of co-production

as “the staging of an experience wherein the firm constructs the context and the

consumer plays an active role.” In this way, services are used as the stage for

creating experiences and memorable events for the customer. This idea is close to

Pine and Gilmore’s (1998) experience economy and Vargo and Lusch’s (2004) value-

in-use. In a recent article, Verhoef et al. (2009) proposed that “the customer

experience is holistic in nature and involves the customes cognitive, affective,

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emotional, social and physical responses to the retailer” and that it “encompasses the

total experience.” Following that model, Prahalad’s view of customer involvement fits

best under the label of “retail atmosphere” (design, scents, temperature, music, etc.)

(Verhoef et al. 2009, p. 32).

Experiences are important because they can encourage customers to

participate more in the value creation process. Normal day-to-day service

experiences (Edvardsson et al. 2005; Korkman 2006) and peak experiences (Pine

and Gilmore 1999) lead to customer learning, which involves numerous experiential

encounters throughout the consumer-supplier relationship. Therefore, it is in

companies’ interests to identify the experiences embedded in the value co-production

process (Payne et al. 2008). Creating pleasurable customer experiences could be a

new means of competing, which should make it an area of interest for companies.

Customers’ experiences affect their satisfaction, loyalty, and expectations, instill

confidence, and create emotional bonds (Johnston and Kong 2011). There are many

business examples of orchestrating experiences, a well-known example of which is

the Disney experience in the amusement parks of California, Florida, Japan, and

France. Even McDonald’s speaks in terms of offering a hamburger and an

experience. In a Starbucks’s Hear Music Coffeehouse, customers can use individual

music listening stations with CD-burning capabilities. Consequently, customers can

enjoy a Starbucks drink while listening to and burning CDs of their favorite music.

2.2.4 Problem solving

Prahalad (2004) defined problem solving as the service provider allowing

customers to navigate their way through the firm’s IT system in order to solve a

problem caused by a service failure. This option is not new in business. For example,

Federal Express has for years allowed customers to track their lost or delayed

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packages via FedEx’s computer system. The websites of many firms contain

answers to frequently asked questions (FAQs). Hewlet Packard offers Internet-based

diagnostic tools that allow customers to solve problems themselves. Some firms offer

on-line complaint systems that enable dissatisfied customers to complain efficiently

and effectively. Other firms simply refer customers to user communities for further

assistance. If such online help does not solve the problem, customers can often

make a problem follow-up request, which gives them access to a web page where

they can check the status of their request. The success of this problem-solving

method, working together with the customer, depends completely on the customer’s

skills. In this element of co-production, the customer becomes an operant resource;

that is, a resource that produces effects (Constantin and Lusch 1994). According to a

recent study by Dong et al., “when customers participate in the service recovery

process in self-service technology contexts, they are more likely to report higher

levels of role clarity, perceived value of future co-creation, satisfaction with the

service recovery, and intention to co-create value in the future” (Dong et al. 2008).

This conclusion draws on the assumptions that customers are using self-service

technologies to solve the problem; that is, there is no option not to. The present study

differs from Dong et al. (2008) in that it focuses on the willingness to co-produce

using self-service technologies when something goes wrong.

2.2.5 Co-designing

In the co-design element, customers can participate in the co-creation process

through their own innovative product design efforts (Füller et al. 2007). Hoyer et al.

(2010) provided two good examples of co-designing. The first, Threadless.com, is a

T-shirt company where community members and visitors to their website vote on

customer-submitted designs, the most popular of which are sent into production and

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sale (Beer 2007). The second, a UK-based company called Walkers, launched a

campaign they called “Do us a flavour,” in which they invited customers to suggest

new flavors of potato chips that Walkers could produce and sell. Other business

examples are Dell Computers, which allows customers to configure their hardware

(e.g., video card, storage, etc.) when they order online. Some wine makers let

customers design labels for their own wine bottles, while airline companies allow

customers to reserve a specific seat or add fast-track services – all at a price.

At the heart of co-designing is the unbundling of the product or service based

on unique components that can be-assembled as customers like. In so doing,

providers allow customers to create their own unique service. Co-designing not only

transfers creative work from the firm to the customer, it also transfers risk. As

mentioned above, the outcome greatly depends on the customer’s skills and

knowledge, which means that the firm is not alone in being responsible for the

outcome. Consequently, it is important to guide and educate the customer through

the co-designing process (Payne et al. 2008). Michel et al. (2008) noted that co-

designing opportunities facilitate customers’ value-in-context and help customers use

or reconfigure their value-creating resources.

In summary, there are a number of reasons why customers are willing and

able to engage productively in the various elements of the co-production process:

financial (to save money or time), social (recognition), technical (gain new insight and

knowledge), and altruism (Fûller 2008). In some other situations, consumers do not

have an option (for example, Amazon.com e-tailing) and are forced to adopt and use

self-service technologies in order to use their services.

2.3 Hypotheses development

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Companies are increasingly trying to engage their customers and build

relationships with current and potential customers. They do this through various

means – such as advertising, discussion forums, newsletters, competitions, coupons,

rebate forms, and the Internet – that require cognitive, emotional, or physical

engagement. These methods require a certain degree of cognitive involvement,

which triggers a central route rather than a peripheral – heuristic – route to

persuasion. This paper argues that customers become engaged because they

perceive value in doing so. As a result, they are more likely to engage in co-

production. Therefore, we propose the following hypothesis for empirical testing:

Hypothesis 1 (H1): Customer engagement is positively associated with value co-

production.

There is debate as to whether customers are willing to participate in self-

service. Bendapudi and Leone (2003) demonstrated that customers participate in

value co-production when they have the choice to do so. With regard to self-service

technologies, it is assumed here that companies provide customers options and

incentives to use self-service alternatives or staffed counters. Incentives to go on-lline

can include increased convenience (Berry et al. 2002), the ability to shop at any time

and at the customer’s own pace, lower prices, and the absence of lines; in short,

increased convenience through reduced time, effort, or money. Therefore, we

propose the following hypothesis for empirical testing:

Hypothesis 2 (H2): Self-service is positively associated with value co-production.

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Through their carefully crafted and designed services, firms stage a service

experience. Based on an axiom of maximizing return on time through unique

experiences, customers may be interested in creating an experience that has greater

utility for them by combining a degree of involvement and content. Their incentive for

doing this is to transform the service experience into something that is unique, fun,

and exciting with a view to increasing the derived value. In summary, customers are

willing to help create an individualized experience if given the opportunity. Therefore,

we propose the following hypothesis for empirical testing:

Hypothesis 3 (H3): Customer experience is positively associated with value co-

production.

As mentioned, the underlying assumption in the value co-production literature

is that customers are always willing and able to co-produce. Their willingness should

lead to a positive association between willingness to engage in problem solving and

co-production (Prahalad 2004) if they experience a problem or service failure and

they are offered the option to participate in problem solving. Therefore, we propose

the following hypothesis for empirical testing:

Hypothesis 4 (H4): Problem solving is positively associated with value co-production.

Co-designing allows customers to buy a service that they have tailored to their

own preferences, needs, and desires. For example, air travel customers can choose

a seat, meal, in-flight entertainment, and purchase fast-track services to avoid long

lines and waiting time. In Europe, several theaters allow customers ordering tickets

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online to also pre-book a table, or order beverages that will be waiting for them during

the intermission. Special customer needs are easier to fulfill when customers partake

in service design. Such tailor-made customer participation leads to higher levels of

customer satisfaction (Fornell 1992). Therefore, customers’ interest in co-designing a

service experience should positively affect their value co-production. This leads to the

following hypothesis for empirical testing:

Hypothesis 5 (H5): Co-designing is positively associated with value co-production.

Finally, we argue that co-production is positively associated with future

behavioral intension; that is, customer willingness to buy the service again, buy more

of it, or recommend it to others. The sixth hypothesis concerns the relationship

between co-production and behavioral intent. Essentially, we argue that customers

who partake in co-production with the service provider are likely to reflect a high

behavioral intent because they can achieve several benefits when co-producing,

such as saving time and reducing expenses (Meuter et al. 2000).

Hypothesis 6 (H6): Value co-production is positively associated with behavioral

intension.

Figure 1 summarizes the six hypotheses and illustrates the corresponding

structural equation model. The hypotheses on the positive association between the

five elements of value co-production (customer engagement, self-service, customer

involvement, problem solving, and co-designing) and value co-production should be

robust across different degrees of user experiences.

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Place Figure 1 about here

Figure 1: The conceptual model and hypothesized causal relationships.

3 Research methodology 3.1 Data sample and research process

The respondents were selected at random on randomly selected days and

times while traveling to the airport or waiting for the airport express train at one of

three stations. A total of 400 travelers were approached. Some declined and others

left with non-completed questionnaires, leaving 300 usable responses – an overall

response rate of 75 percent, which is within the range reported for related research

(e.g., Baruch, 1999, indicating a mean of 48.4 percent with a standard deviation of

22.5 percent). Most respondents were between the ages of 22 and 49, and 48

percent were women.

The questionnaire contained statements and questions that were designed to

test the research hypotheses. A scenario technique was used to portray the various

situations in which co-production could occur when booking or taking a flight. One

such scenario was as follows: “After the layover, you are now on board the newest

Airbus airplane, a large airplane on which you have access to, among other things, a

small restaurant and bar, limited duty-free shopping, and a small casino plus simple

training facilities.”

We asked the recipients to read the scenarios carefully and then answer the

questions. Using familiar scenarios is known to be very useful because respondents

can imagine themselves in a familiar role or situation (Eroglu 1987). A total of five

scenarios were developed, each representing one of Prahalad’s five elements of co-

production. The same five statements were given for each of the five scenarios.

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Among other things, respondents were asked how interesting, likely, willing, and

unnecessary their participation in each of these elements would be, as well as how

they perceived the utility of participation. The same five statements were given for

each scenario (see the appendix entitled “Measures” for more details).

Although there is a general understanding that value co-production occurs in various

stages (Prahalad and Ramaswamy 2004), this understanding has rarely been

formalized in terms of theoretical conceptualization and operationalization of

constructs. In order to operationalize the five constructs – customer engagement,

self-service, customer involvement, problem solving, and co-design – the study

followed Churchill’s (1979) recommendations for developing reliable and valid

measurement scales. A confirmatory factor analysis was conducted to measure

validation (Anderson and Gerbing 1988). The hypothesized path model was

estimated by structural equation modeling techniques using the AMOS 7.0 program.

Because value co-production is conceptualized as mediating the impact of the five

elements on behavioral intension, a χ²-difference test was conducted in order to

establish the mediating effect (Homburg and Giering 2001).

The robustness of the hypotheses was tested with two opposing sub-groups

formed by classifying the user experience into high and low. The first subgroup (“high

user experience”) refers to respondents holding a platinum, gold, or silver loyalty

card. Twenty-seven percent of the respondents belonged to this subgroup. The

second subgroup, which accounts for 40 percent of the respondents, included those

with low user experience (i.e., no loyalty card). The third group (medium experience)

referred to travelers holding basic loyalty cards and accounted for 33 percent of the

respondents. However, this group was not used in the analysis. Hypotheses H1 to H5

were analyzed for only high and low experienced customers; two-group structural

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equation analyses were applied in order to examine whether parameter estimates y1,

y2, y3, y4, or y5 were supported in size and significance for each of these two group.

3.2 Measure development and validation

Measure development and validation was guided by the procedure suggested

by Churchill (1979). In addition, we first considered whether the measurement scales

should be conceptualized through reflective or formative indicators. Reflective

indicators suggest that the latent variables cause the observed variables (Bollen,

1989), while formative indicators can be viewed “as causing rather than being caused

by the latent variable measured by the indicators” (MacCallum and Browne 1993, p.

533). Formative measures involve the construction of an index rather than a scale

(Bollen and Lennox 1991). The majority of marketing scales are conceptualized

through reflective indicators, because formative scales still present challenges in

terms of assessing the validation and reliability of the scales (Diamantopoulos and

Winklhofer 2001). Because of this, we used reflective scales.

Specifying the domain of each construct by analyzing the existing literature led

to a preliminary version of the questionnaire and items. This version was pre-tested

by randomly distributing the questionnaire to 50 students at a North-European

business school. The intention was to evaluate whether the results would appear to

be satisfactory when the SPSS analysis program was used; in other words, whether

the questions used in the survey were valid in relation to the model we wanted to

test. Different tests conducted with SPSS revealed results that were satisfactory for

testing the theoretical model. This was the final confirmation we needed to begin

distribution to our target recipients.

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As a guideline for how to formulate the five statements, a scale handbook was

used (Yoo et al. 2000), which made it possible to formulate scales that were similar to

each other and, therefore, to check the respondents’ answers for consistency. The

operationalization of customer engagement uses five items, including statements

about customers’ willingness to be engaged in marketing and sales activities, and

about their perceptions of the benefits they will receive from such engagement. For

example, customers were asked whether they would say yes to receiving a

newsletter or if a newsletter would be unnecessary for them. The five items including

the likelihood, usefulness, and interest of customers regarding partaking in self-

service activities operationalized self-service. The same was done with regard to

customer experience and for problem solving. The items capture the likelihood,

necessity, and interest of customers to participate in problem solving on their own.

Co-design was operationalized using five items, which include various aspects

concerning customer benefits associated with the customer’s participation in co-

designing services and products.

Co-production was measured using five items that reflect aspects of

customers’ active participation in the value co-production process. These aspects

include the customer’s preferences and willingness to co-produce, as well as

customer benefits associated with their participation in co-production. Behavioral

intension was operationalized using scales developed by Crosby and Stephens

(1987) and Yoo et al. (2000). The five items capture various facets of the likelihood

that customers would advise other customers to co-produce their travel experience

with the airline, and of the probability that they would travel again with an airline. All

items were measured on a seven-point LIKERT scale anchored by ‘strongly disagree’

and ‘strongly agree.’

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In order to measure user experience, respondents were asked if they had a

frequent flyer loyalty card and, if so, their level of membership status. Experienced

travellers were divided from inexperienced travellers according to their card’s status

level. This method has two weaknesses that we are aware of: (1) some customers do

not have a loyalty card, or do not use their loyalty card even though they are frequent

flyers, and (2) some customers who fly with numerous airlines or airline alliances

would have had higher card status if they used only one airline/alliance and the

respective loyalty card. Overall, however, loyalty card membership and membership

status seemed to be a good proxy for customers’ experience level.

In order to validate the newly described measurement scale, we followed

Anderson and Gerbing’s (1988) recommendation. All reflective multi-item constructs

were subjected to a confirmatory factor analysis. The overall measures indicate a

good fit with the hypothesized measurement model (χ²/df=1.747 (p<0.001)); TLI

(Tucker-Lewis-Index) = 0.96; NFI (Normed-Fit-Index) = 0.92; CFI (Comparative Fit

Index) = 0.96; RMSEA (Root Mean Square Error of Approximation) = 0.049). As

Table 1 illustrates, the reliabilities of the individual scales provide further evidence of

the measure’s sound psychometric properties, ranging from 0.44 to 0.96 for indicator

reliability, from 0.85 to 0.95 for Cronbach’s Alpha, and from 0.84 to 0.96 for construct

reliability. The discriminant validity is examined by means of the Fornell-Larcker

criterion, which suggests that the average variance extracted should be greater than

0.5 (Fornell and Larcker 1981). All constructs meet the criterion; in other words, the

degree of discriminate validity was sufficient for the study. Together, the results

proved that the measures have the sound psychometric properties necessary for

hypothesis testing (Bagozzi and Yi 1988).

22  

Place Table 1 about here

Table 1: Psychometric properties.

4 Results of the structural equation modeling

The overall fit measures suggest that the hypothesized path model provides a

good data fit. The χ²-degrees of freedom ratio yielded strong results (χ²/df=1.669,

p<0.001), and the other overall measures (NFI=0.92; TLI=0.96; CFI=0.97;

RMSEA=0.047) met the requirements suggested in the relevant literature (Bagozzi

and Yi, 1988). As depicted in Figure 2, the four hypotheses related to the

relationships among co-production, customer engagement, self-service, customer

involvement, and co-design (H1: γ1=0.09, p<0.1; H2: γ2=0.24, p<0.01; H3: γ3=0.09,

p<0.1; H5: γ5=0.53; p<0.1) are supported in terms of significance and size of effect.

The direct impacts of customer engagement and customer involvement (as single

constructs) on value co-production are significant, but low compared with the similar

direct impacts of self-service and co-design.

Our results do not show a positive association between problem solving and

value co-production (H4: γ4=0.05, p>0.1) and, therefore, do not support Hypothesis 4.

Finally, the hypothesized positive association among co-production and behavioral

intension is supported (H6: γ6=0.72, p<0.01). All of the hypotheses, except

Hypothesis 4, are consistent with the literature and our thinking.

Place Figure 2 about here

===================================================================

Figure 2: Results of path model using structural equation modeling.

23  

The support in terms of size and significance for H1, H2, H3 and H5 was

robust across different degrees of user experience (Table 2). Customer engagement

had a small but significant impact on co-production when user experience was high

(y1H=0.095, p<0.1). There was also support in significance and size for a positive

association between customer engagement and co-production when user experience

was low (y1L=0.151; p<0.1). The positive association between self-service and co-

production was significant for both high- and low-experience users (y2L=0.550,

p<0.01; y2H=0.159, p<0.05). The positive association (y3H=0.212, p<0.05) between

customer involvement and co-production was supported in size and significance for

both high- and low-experience customers (y3H=0.048, p<0.1; y3L=0.094, p<0.1).

Contrary to what we expected, the hypothesized positive association between

problem solving and co-production (H4) was not supported in size and significance

for either high- or low-experience customers (y4H=-0.080, p>0.1 and y4L=-0.012,

p>0.1). The positive association between co-design and co-production was

supported in size and significance across both sub-groups (y5H 0.317, p<0.01;

y5L=0.430, p<0.01).

Place Table 2 about here

================================================================

Table 2: Results of the path analysis (structural equation modeling) for different

degrees of user experience.

We can conclude that the underlying assumption – that co-production takes

place regardless of what happens during the consumption process – is rejected

24  

based on empirical testing. In summary, we propose that when things go wrong (for

example, if firms break contracts through service failures), customers will no longer

cooperate, which will require the firm to solve the problem alone.

5 Discussion 5.1 Theoretical implications

The conceptualization and operationalization of value co-production through

the five elements of customer engagement, self-service technologies, customer

involvement, problem solving, and co-designing lead to a valid scale that can be

used for further research. Future scale development could draw on the

comprehensive conceptualization and operationalization of value co-production

presented here. Instead of co-production being a uni-dimensional construct, our

findings indicate that it compromises four elements: customer engagement, self-

service technologies, customer involvement, and co-designing. All four elements are

integral parts of value co-production and reveal a positive association with it.

Interestingly, the four elements do not contribute to value co-production

equally; the impacts of customer engagement and customer involvement are

relatively low. While significant, the parameter estimates for customer engagement

and involvement are only 0.09 for both relationships, compared with the γ2=0.24 and

γ5=0.53 for self-service technologies and co-design. Value co-production is mainly

predicted by the provision of self-service and co-designing opportunities. This finding

empirically extends Prahalad’s (2004) argument that customer engagement and

involvement are two common features in all five elements. However, our findings

suggest that customer engagement and involvement are two common features that

25  

are even more strongly related to self-service and co-designing opportunities than the

other elements.

Most interestingly, problem solving was suggested as a ‘fair-weather

syndrome,’ which is contrary to the basic assumption that the customer is always a

co-creator of value. Considering problem solving as a fair-weather syndrome

contributes to the literature in three ways. Firstly, there is a difference between

customers wanting to co-produce in creating value and customers wanting to co-

produce in service recovery. Co-creating and co-repairing value (that is, service

recovery) are not only different in their nature, but also emotionally. While co-creating

value can be described in emotional terms as joy, recovering from a failure has been

found to include negative effects (Andreassen 1999, 2000). Therefore, the incentives

to co-produce are fundamentally different. Arguably, the incentive to co-produce is

high in terms of creating value, but low in repairing value. Future contributions to

value co-production literature could elaborate the role of different emotions and

incentives.

Secondly, given the lower incentives to repairing value and the tendency to

externalize the fault to the supplier (Heider 1958), customers are not willing to

participate in problem solving. The unwillingness is captured by the term “cognitive

miser” (Fisk and Taylor 1984), developed from psychology. This term refers to a

mental characteristic whereby the least amount of attention and mental effort needed

to process information is used. The existence of a cognitive miser would explain why,

when things go wrong, customers are not willing to participate in solving something

they feel the firm has created and is therefore responsible for solving.

Thirdly, following the logic of the Prisoner’s Dilemma and the tit-for-tat strategy

(Axelrod 1984), from game theory we propose that when things go wrong (that is,

26  

when firms do not cooperate with the customer), the customer will not co-operate and

will require or expect that the firm solves the problem alone. This behavior is in line

with the tit-for-tat strategy.

From a theoretical perspective, the study made some surprising findings. In

their fundamental proposition # 6, Vargo and Lusch (2004) stated that “the customer

is always a co-producer” of value. Contrary to this, the present study documents

empirically that co-production and co-creation of value are primarily fair-weather

syndromes. If the service is co-produced to the customer’s dissatisfaction, the

customer will no longer be a cooperative co-producer of value.

The findings are robust across different degrees of user experience. The

positive correlations between customer engagement, self-service, customer

involvement, and co-design on value co-production are consistent for both high- and

low-experience customers. When things go wrong, high- and low-experience

customers are both unwilling to participate in co-producing. Our results reject H4 for

both high- and low-experience users.

Interestingly, testing the robustness of H1 to H5 revealed that H1, H2, H3, and

H4 are not only robust across high- and low-experience users. User experience

functions as a moderator in the causal relationship. By applying a moderator

analysis, as suggested by Homburg and Giering (2001), we found evidence that user

experience moderates the causal relation. The effect is negative. Increasing user

experience weakens the positive associations between customer engagement, self-

service, customer experience, co-design, and value co-production. Highly

experienced users seem to be less engaged in marketing activities, self-service,

customer involvement, and co-designing; in other words, their willingness to

participate in value co-production is reduced. This finding challenges the traditional

27  

lead-user concepts, which suggest that the effects would be relatively strong for

extreme users. The findings of this study show the opposite effect; specifically, co-

designing with less experienced customers affects co-production positively. A similar

argumentation applies for self-service: highly experienced users are less willing to

participate in self-service activities than less experienced users. This finding

potentially enriches the self-service technology literature that argues that users must

possess some initial knowledge in order to make successful use of self-service

opportunities.

The observed moderating effects seem to be another promising research

opportunity. Instead of arguing that customers are always co-creators of value, future

research should elaborate the interaction effects arising from value co-production and

user experience and contexts (for example, fast moving standardized consumer

services relative to tailor-made competence-based services).

5.2 Managerial implications

Managers can learn from the dominance of self-service and co-design in co-

producing value. The findings of this study indicate that customer engagement and

involvement only have an incremental influence on value co-production. From a

service productivity perspective, it seems more promising to invite customers to co-

produce using self-service technology and co-designing than to invite them to co-

produce in the other elements of value co-production. From a service innovation

perspective, allocating resources to find new ways of self-serivce and co-designing

will improve added customer value, and thus the adoption and diffusion of the new

innovation.

Most importantly, managers must reconsider customer unwillingness to

participate in problem solving. At the initial stage of customers’ encounters, it is

28  

essential to provide service quality, so things must go right in order to persuade

customers to keep co-producing. Whenever things go wrong, managers should

design service recovery with minimal customer participation. It is beneficial if

customers require neither training nor commitment in order to participate in problem

solving.

5.3 Limitations This study has certain limitations. Firstly, only five elements that contribute to

value co-production were included. Additional elements might exist, of course, but we

assumed that the five included elements capture the main opportunities for value co-

production. Potential interrelationships between the five value co-production

elements were also neglected as they were considered to be beyond the scope of

this study. Further research could elaborate these potential interrelationships.

29  

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Figures and Tables

Figure 1: The conceptual model and hypothesized causal relationships

34  

Figure 2: Results of path model using structural equation modeling

35  

Table 1: Psycometric qualities

Mean (Std.

Deviation)

Cronbach’s

Alpha

Indicator

reliability

Construct

reliability

Average

variance

extracted

Behavioral

intension

bi1

5.02 (1.27) 0.85

0.70

0.88

0.82

0.58

0.58

0.84 0.52

bi2

bi3

bi4

bi5

Co-production

cp1

4.97 (1.39) 0.86

0.70

0.87

0.73

0.76

0.78

0.88 0.59

cp2

cp3

cp4

cp5

Customer

engagement

cen1

3.64 (2.17)

0.95

0.95

0.98

0.84

0.85

0.90

0.96

0.78

cen2

cen3

cen4

cen5

Customer

experience

cex1

5.31 (1.34)

0.90

0.96

0.91

0.74

0.64

0.90

0.64

cex2

cex3

36  

cex4 0.72

cex5

Self-service

ss1

5.68 (1.25)

0.91

0.92

0.91

0.72

0.71

0.79

0.91

0.66

ss2

ss3

ss4

ss5

Problem solving

ps1

3.08 (1.79)

0.94

0.97

0.96

0.84

0.84

0.79

0.95

0.79

ps2

ps3

ps4

ps5

Co-design

cd1

5.08 (1.51)

0.94

0.92

0.94

0.82

0.86

0.87

0.94

0.78

cd2

cd3

cd4

cd5

37  

Table 2: Results of the path analysis (structural equation modeling) for different degrees of user experience

Level of user experience

High Low

H1: Customer

engagement’s effect on co-

production

y1H=0.095 p<0.1 y1L=0.151 p<0.1

H2: Self-service’s effect on

co-production

y2H=0.159 p<0.05 y2L=0.550 p<0.01

H3: Customer experience’s

effect on co-production

y3H=0.048 p<0.1 y3L=0.094, p<0.1

H4: Problem solving’s effect

on co-production

y4H=-0.080, n.s. y4L=-0.012 n.s.

H5: Co-design’s effect on

co-production

y5H =0.317 p<0.01 y5L=0.430 p<0.01

38  

Appendix: Measures

Customer engagement

Imagine the following:

In two weeks you will travel from Oslo to New York, with a layover in Copenhagen. You are currently searching the Internet for potential airlines. One company’s website offers to send you an electronic newsletter every two weeks. The newsletter will contain offers from the company, destinations, games/competitions, and campaigns. The following are some statements, anchored by ‘completely disagree’ and ‘completely agree.’

cen1 It is likely that I will say yes to receiving a newsletter as described above.

cen2 I would be interested in receiving such a newsletter or e-mail.

cen3 I feel it would be unnecessary for me to receive such a newsletter.

cen4 I would not be willing to receive such a newsletter.

cen5 It would be useful for me to receive this kind of newsletter.

Customer experience

After the layover, you are now on board the newest Airbus airplane, a large airplane on which you have access to, among other things, a small restaurant and bar, limited duty-free shopping, and a small casino plus simple training facilities.

cex1 It is highly likely that I would take part in the activities described above.

cex2 It would be interesting for me to take part in activities such as those described above.

cex3 I think it would be unnecessary for me to take part in activities such as those described

above.

cex4 It would be useful for me to take part in activities such as those described above.

cex5 I am somewhat reluctant to take part in activities such as those described above.

Self-service

Related to your travel, the airline wants you to perform certain operations. In addition to buying the ticket on the Internet, the airline gives you the option to check in your luggage using a kiosk at the airport and scan the ticket at the gate.

ss1 It is likely that I would take part in such activities on my own.

ss2 It would be interesting for me to take part in such activities on my own.

ss3 I think it is necessary for me to take part in such activities on my own.

ss4 I am somewhat reluctant to take part in such activities on my own.

39  

ss5 It is useful for me to take part in such activities on my own.

Problem solving

You arrive in New York, but your luggage is missing. You report your missing luggage at the airline’s service desk. They offer you the option of solving the problem yourself by using the company’s web page to report missing luggage and to check where the luggage is and when it will arrive.

ps1 It is likely that I would take part in this kind of problem solving on my own.

ps2 It would be interesting for me to participate in this kind of problem solving on my own.

ps3 I think it would be somewhat unnecessary for me to take part in this kind of problem

solving on my own.

ps4 I am somewhat reluctant to take part in this kind of problem solving on my own.

ps5 It would be useful for me to engage in this kind of problem solving on my own.

Co-designing

At the same time as you purchase an air ticket on the Internet, you receive an offer to adapt your travel to your unique requirements. For example, you can choose between different departure times, meals, in-flight movies, onboard newspapers, and access to a comfort room with a shower and a bed during the layover.

cd1 It is likely that I, together with the airline company, would take part in designing the travel

to fit my personal preferences.

cd2 It would be interesting for me to take part in designing the travel so that it would meet my

personal needs.

cd3 I think it would be unnecessary for me to take part in designing the travel together with the

airline company in order to meet my personal preferences.

cd4 I am somewhat reluctant to participate in the designing of the flight together with the

airline company in order to meet my personal wishes and needs.

cd5 It would be useful for me to take part in designing my travel together with the airline

company in order to meet my personal preferences.

40  

Co-production

The air travel described above requires that you co-produce the travel together with the airline.

Thinking about the air travel as described, to what extent do you agree or disagree with the following

statements?

Cp1 If I were given the opportunity to produce the travel together with the airline, I would

always prefer to do so.

cp2 If I were given the opportunity to produce the travel together with the airline, I would wish

to avoid doing so.

cp3 If I were given the opportunity to produce the travel together with the airline, I would wish

not to take part.

cp4 I find it beneficial to produce the travel together with my airline company under most

circumstances.

cp5 If I were offered the chance to co-produce the travel on my own, I would always

participate in such activities.

Behavioral Intent

bi1 It is likely that I would recommend others to produce the travel together with the airline

company if this opportunity is offered to them.

bi2 I will probably travel more with an airline that offers me the opportunity to produce my

travel together with them.

bi3 It would be likely for me to travel with an airline that offers me the opportunity to produce

the travel together with them.

bi4 It is highly unlikely that I would ever take part in a travel experience if I had to produce it

together with Company X.

bi5 I would not produce a trip together with my airline if the opportunity was offered to me.