Toward a measure of service convenience: multiple‐item scale development and empirical test

Toward a measure of service convenience:multiple-item scale development and

empirical testScott R. Colwell, May Aung, Vinay Kanetkar and Alison L. Holden

Department of Marketing and Consumer Studies, University of Guelph, Guelph, Canada

AbstractPurpose – The purpose of this paper is to report on the development and nomological testing of a 17-item scale measuring the five dimensions ofservice convenience (decision, access, transaction, benefit, and post-benefit) as proposed by Berry, Seiders, and Grewal.Design/methodology/approach – A cross-sectional survey methodology was used to collect the data.Findings – Reliability and validity assessments provided evidence of the scale’s psychometric validity. Service convenience was found to be asignificant predictor of overall satisfaction in the context of personal cellular telephone and internet usage.Research limitations/implications – This study uses a student sample which may limit its generalizability to other respondents. Also, thecross-sectional survey methodology does not allow for the investigation of causation. Future research should investigate other contexts outside of thecellular and internet services examined in this study and across a broader sample. Furthermore, the ability to retrospectively rate service convenience,the trade-off between price and convenience, and the continuum of convenience need to be investigated further.Originality/value – This study provides psychometrically valid scales to measure service convenience as conceptualized by Berry et al..

Keywords Consumers, Telecommunications, Internet

Paper type Research paper

An executive summary for managers and executive

readers can be found at the end of this article.

In dynamic competitive service environments, providingsatisfactory value to the consumer is imperative. Failure todo so can lead to lost customers and future revenue streamsthat are costly to replace (Reichheld and Teal, 1996).Research suggests that organizations have traditionallyincreased value to consumers by either:. lowering the price of the product or service;. increasing the quality of the product or service; or. decreasing non-monetary costs such as the time and effort

required to acquire and consume the product or service(Zeithaml and Bitner, 2000).

Consumer desire for more convenient methods of conductingbusiness has increased in conjunction with technologicaladvances and migrating socioeconomic standings (Berry,1979; Gross, 1987; Seiders et al., 2000). To meet theincreasing convenience demands of consumers (Lovelock,2001; Dabholkar et al., 2003) and to minimize potentialcustomer loss (Keaveney, 1995), service providers haveemployed methods such as internet commerce, live technicalonline chat capabilities, and mobile telecommunicationservices. Given the pressure to provide increasedconvenience, it is not surprising that organizations have

made significant investments in enhancing the convenience

aspect of their product and service offering. As such, service

convenience is of significant interest to management and

scholars.The notion of service convenience has generated a

significant amount of scholarly research. Copeland (1923),

for example, initiated the classification of convenience goods

as one of the schemas of consumer products. Morganosky

(1986, p. 37) suggested that convenience is the ability to

“accomplish a task in the shortest time with the least

expenditure of human energy.” Similarly, Brown (1990)

suggested that convenience consists of the time and effort

consumers expend on product and service acquisition and

consumption. More recently, researchers have investigated

how technology (specifically self-service technology) may

enhance convenience and increase consumer satisfaction with

service encounters (Dabholkar et al., 2003; Meuter et al.,

2000). However, Berry et al. (2002) posited that the literature

still lacks a solid understanding of the conceptualization and

measurement of service convenience, and they proposed a

conceptualization of five different forms of service

convenience.To date, little research has been conducted to measure and

verify this conceptual framework (for two unpublished

graduate theses exceptions see Holden, 2005 and Chou,

2003). Thus, the development and empirical testing of

measurement scales for the Berry et al. (2002) framework isThe current issue and full text archive of this journal is available at

www.emeraldinsight.com/0887-6045.htm

Journal of Services Marketing

22/2 (2008) 160–169

q Emerald Group Publishing Limited [ISSN 0887-6045]

[DOI 10.1108/08876040810862895]

The exploratory research for this study was presented (June 18, 2005) atthe INFORMS Marketing Science Conference in abstract form.

Received: September 2005Revised: March 2006Accepted: June 2006

160

the primary focus of our research. In conducting this research

we provide two contributions to the literature. First, weprovide psychometrically valid scales for measuring theservice convenience dimensions as originally conceptualized

by Berry and coworkers. Second, we provide a nomologicaltest of these measures as antecedents to satisfaction in thecontext of consumer cellular telephone and internet serviceusage. We begin by reviewing the Berry et al. (2002) service

convenience framework. We then provide an overview of thescale development process and an empirical test of thesemeasurements. We conclude with theoretical and managerialimplications and directions for future research.

Conceptual framework

Service convenience: a multidimensional

conceptualization

Service convenience, as conceptualized by Berry et al. (2002,p. 4), is defined as the “consumers’ time and effortperceptions related to buying or using a service.”Consumers experience an increase in time deficiency whenconducting tasks related to the acquisition and consumption

of a service (Zeithaml and Bitner, 2000). Thus, serviceconvenience can be thought of as a means of adding value toconsumers, by decreasing the amount of time and effort aconsumer must expend on the service. Berry et al. (2002)

argue, however, that service convenience is amultidimensional construct, and that convenience, vis-a-visconsumer time and effort, must be understood within the

context of the activities that consumers undergo in the processof purchasing and using a service. Given the basic acceptancethat consumer buying processes might include problemrecognition, information search, alternative evaluation,

purchase and post-purchase stages (Engel and Blackwell,1982), they conceptualize five dimensions of serviceconvenience that reflect the potential for convenience ateach stage of the consumer buying process. These five

dimensions include:1 decision convenience;2 access convenience;3 transaction convenience;4 benefit convenience; and5 post-benefit convenience.

Decision convenienceConsumers who have recognized the need for a product orservice are immediately faced with the decision of which

supplier and offering to choose. For example, a consumerrecognizes the need to have a personal cellular phone service.Faced with a plethora of cellular service providers and serviceplan configurations to choose from, the consumer must

expend time and effort in making the decision. Decisionconvenience is therefore defined as the “consumers’ perceivedtime and effort expenditure to make service purchase or use

decisions” (Berry et al., 2002, p. 6).

Access convenienceAccess convenience is defined as the “consumers’ perceived

time and effort expenditures to initiate service delivery”(Berry et al., 2002, p. 7). To carry on with our previousexample, once the consumer has decided on a service providerand service package, initiating access to that service requires

personal or technological interaction. For example, aconsumer may choose to use the service provider’s

automated telephone service to have the service “initiated”(Berry et al., 2002; Bitner et al., 2000). This type ofinteraction is often seen in services such as credit cards sentby mail and cellular telephones or internet services purchasedthrough retail suppliers.

Transaction convenienceTo complete the purchase transaction of the service, aconsumer must again invest time and energy. As such,transaction convenience is defined as “consumers’ perceivedexpenditures of time and effort to effect a transaction” (Berryet al., 2002, p. 7). In essence, providing convenience duringthe transaction stage enables the consumer to efficientlyassume possession of the acquired service.

Benefit convenienceOnce a consumer has accessed and purchased a service,consumption of the service begins (Peter and Olson, 1999).Along with consumption comes the confirmation (ordisconfirmation) of the benefits of the service (Churchilland Surprenant, 1982). Thus, benefit convenience is definedas “consumers’ perceived time and effort expenditures toexperience the service’s core benefits” (Berry et al., 2002,p. 7). Using our example, the cellular telephone servicecustomer now obtains benefits in relation to the time andeffort to receive them, such as the benefit of security affordedto them to now more easily call their service agent after theirautomobile fails to start.

Post-benefit conveniencePost-benefit convenience is defined as “consumers’ perceivedtime and effort expenditures when reinitiating contact with afirm after the benefit stage of the service” (Berry et al., 2002,p. 7). This effort might involve the need to contact theprovider after the sale is complete to initiate servicecomplaints or failures, request maintenance or upgrades, orfor general service support (Gwinner et al., 1998; Zeithamland Bitner, 2000).The notion of service convenience,therefore, provides a mechanism by which to involuntarilyreduce a consumer’s perceived time and effort expended onservice acquisition and consumption (Berry et al., 2002). Bycreating additional convenience to the consumer, the non-monetary value of the service offer is increased.

Satisfaction an outcome of service convenience

Consumers develop perceptions of service encounters basedon monetary and non-monetary components of a service. Assuch, outcomes of a service encounter might include increasesin perceived quality, reliability, fairness, and overallsatisfaction (Olsen and Johnson, 2003). The satisfactionliterature often incorporates responses such as reliability andfairness as evaluations of satisfaction (Johnson et al., 1995). Aconsiderable amount of literature exists on consumersatisfaction, with its conceptualization falling into twogeneral categories: transaction specific satisfaction andcumulative satisfaction (Johnson et al., 1995). A transactionspecific conceptualization attempts to understand aconsumer’s satisfaction evaluation of a specific product orservice encounter (Olsen and Johnson, 2003), whereas acumulative conceptualization is more concerned with overallsatisfaction evaluations of a product or service (Johnson et al.,1995; Olsen and Johnson, 2003).For the purpose of testing the multidimensional service

convenience scale, we have chosen to focus on overallsatisfaction for two reasons.

Toward a measure of service convenience

Scott R. Colwell et al.


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First, expectation-disconfirmation theory suggests that

when consumers’ expectations are met, they are more likely

to evaluate the service as being satisfactory.Second, a significant amount of research has found that, in

general, satisfaction is positively related to perception of

service quality and to monetary and non-monetary cost

considerations (Keaveney, 1995; Zeithaml and Bitner, 2000).Drawing on Johnson et al. (1995), we define satisfaction as

a cumulative evaluation of a consumer’s total experience with

a product or service. A cumulative view encapsulates both

recent experience through consumers’ performance

expectations and past experience through consumers’

expectations, providing a more holistic service evaluation

(Crosby and Stephens, 1987; Winsted, 1997). Consistent

with previous empirical studies (Crosby and Stephens, 1987),

it is suggested that service convenience provides the means for

decreasing time and effort costs in the acquisition and

employment of a service, which in turn enhances satisfaction

evaluation. Therefore, we expect the following:

H1. Service convenience is related positively to satisfaction.

A graphical representation of our conceptual model is shown

in Figure 1.

Research method

Scale development and measures

In developing the scale items for each of the five domains of

service convenience, we followed the guidelines provided by

Churchill (1979), Gerbing and Anderson (1988), and

DeVellis (1991). We first conducted 25 exploratory

interviews with consumers regarding their personal

experiences with their cellular telephone service provider.

During the interviews, we asked participants to describe how

convenient it was to deal with their service provider in relation

to the decision to purchase, access to the service, transaction

with the provider, benefits provided by the service, and post-

benefits. Our aim at this stage was to generate a list of key

words and attributes associated with the five dimensions of

service convenience as outlined by Berry et al. (2002).We analyzed the interview transcripts, comparing these

qualitative data to the 15 service convenience items proposedby Berry et al. (2002) and the 40 service convenience items

tested by Chou (2003). This process resulted in 30

measurement items, including 11 revised items from Berryet al. (2002) and ten revised items from Chou (2003). A

number of the items from Chou (2003) were based on Berryet al. (2002), but in the context of the airline industry, and

thus did have some overlap. These 30 items were thensubmitted for face validity testing to a panel of experts,

consisting of six faculty members from a large university incentral Canada, who were each asked to match the construct

definition to the item they felt reflected that particularconstruct. As a result of this process, four items were

removed; leaving 26 items measuring the five dimensions ofservice convenience. To further test and refine the

measurement items, two separate pilot studies wereconducted. The first consisted of a convenience sample of

30 respondents who were asked to complete the survey withone of the researchers present. The second pilot study utilized

a mall intercept method consisting of 152 participants. Theresults of this pre-test allowed for further refinement of

measurement items, the measurement scale, and the surveydesign.Our final scales for service convenience consisted of five

items each for decision convenience, access convenience,

transaction convenience and benefit convenience, and sixitems for post-benefit convenience. All items were measured

using a five-point Likert scale anchored at strongly disagree tostrongly agree. Overall satisfaction was measured on a six-

point semantic differential scale using Winsted’s (1997)overall satisfaction measure.

Sample and data collection

Our main study was conducted in the context of consumers’

use of personal cellular telephone services and personalinternet services. These two industries were thought to be

appropriate since 52 percent of Canadian households have aleast one personal cellular telephone and a personal internet

connection (Statistics Canada, 2003). Furthermore, ourexploratory interviews and pilot results provided evidence

that consumers of these products experience each stage of thedecision making process, such as that modeled by Engel and

Blackwell (1982), indicating the potential need forconvenience at each stage.We invited 667 undergraduate students to participate in the

main study, which consisted of an online survey for cellularservice or internet service users, and was conducted using the

university’s course and survey delivery software. This systemallowed us to control for the potential of multiple responses

by a single respondent. Respondents were made aware of thesurvey through in-class announcements and electronic course

messages. Participants were asked which of the two servicesthey owned and were then directed toward the appropriate

survey. Where respondents indicated ownership of bothservices, they were randomly assigned to one of the two

surveys; respondents were automatically restricted fromcompleting both surveys. After three weeks, a response rate

of 30 percent was achieved, consisting of 203 completes and201 useable surveys. A descriptive profile of the respondents

is shown in Table I.

Figure 1 Conceptual model of service convenience and satisfaction




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We assessed the potential for nonresponse bias by comparing

early versus late respondents (Armstrong and Overton, 1977).

We found no significant differences between the early and late

respondents, ruling out the potential for nonresponse bias. We

conducted Harman’s single factor test (Podsakoff and Organ,

1986) to assess the potential for common method bias in the

data. Results showed that the first factor only accounted for

38 percent of the variance in the data, indicating that

common method variance was not a significant issue. Prior to

analyzing the measurement model we conducted an

exploratory factor analysis (EFA) on the service convenience

measures using a Promax rotation. Based on the EFA results,

we removed nine items that either did not load significantly

onto their primary factor or displayed significant cross-

loading. The final 17-item service convenience scale and five-

item satisfaction scale are provided in the Appendix.

Measurement model assessment

We assessed the measurement model for unidimensionality,

internal consistency, convergent validity, and discriminant

validity by conducting confirmatory factor analysis (CFA)

using Mplus 3.13 software (Muthen and Muthen, 2004). The

five-factor measurement model results (x2 ¼ 265:79ð190Þ(p , 0:00), CFI ¼ 0:96, TLI ¼ 0:96, RMSEA ¼ 0:05 (0.03,

0.05), SRMR ¼ 0:05) suggested a good fit of the model to the

data (Hu and Bentler, 1999), indicating that

unidimensionality of the scales was achieved. A subsequent

CFA of the second-order factor model of service convenience

provided similar results (x2 ¼ 301:54ð199Þ (p , 0:00),CFI ¼ 0:95, TLI ¼ 0:94, RMSEA ¼ 0:05 (0.04, 0.06),

SRMR ¼ 0:05). The complete measurement model results

and construct correlations are provided in Tables II and III.Cronbach alpha values, which ranged from 0.66 to 0.92,

exceeded the acceptable threshold of 0.65 recommended by

Nunnally and Bernstein (1994), indicating that internal

consistency was obtained. Convergent validity was assessed

using the guidelines provided by Anderson and Gerbing

(1988) and Steenkamp and van Trijp (1991). Item number

one from decision convenience and item number two from

benefit convenience exhibited slightly lower item to total

correlation coefficients (0.34 and 0.36, respectively) than the

suggested threshold of 0.40 to 0.60 (Steenkamp and van

Trijp, 1991). However, these two items were not removed

because they loaded on to their respective constructs

significantly (0.50 and 0.58), and removal did not increase

Table II Measurement model results

Item —a Loadingb T-value

Decision convenience (a5 0:66)

1. Information received made it easy

to choose

3.37 0.50 6.89

2. Making up my mind about what to

buy was easy

3.59 0.59 8.28

3. Information was very clear and

easy to read

3.69 0.62 8.84

4. Service provider let me know

exact cost or special offers

3.51 0.61 8.58

Access convenience (a5 0:75)

1. Provider was available when I

needed them

3.59 0.79 12.21

2. Service provider is accessible

through various ways

4.13 0.50 6.90

3. Hours of operation were

convenient

3.73 0.57 8.08

4. Easy to contact an employee of the

provider

3.68 0.78 11.89

Transaction convenience (a5 0:67)

1. Easy to complete my purchase 3.82 0.68 9.57

2. Able to complete the purchase

quickly.

3.82 0.59 8.17

3. No problems that added to the

purchase time

3.61 0.63 8.82

Benefit convenience (a5 0:67)

1. Obtain benefits with little effort 3.58 0.71 10.51

2. Service provider solved needs 3.61 0.58 8.31

3. The time required to receive the

benefits was reasonable

3.64 0.66 9.67

Post-benefit convenience (a5 0:79)

1. Provider quickly resolved any

problems I had

3.26 0.78 12.32

2. Easy to obtain follow up service 3.47 0.73 11.19

3. Service provider is able to resolve

my problems

3.64 0.74 11.35

Satisfaction (a5 0:92)

1. Overall, I am satisfied with my

provider

4.41 0.78 12.82

2. Feelings about being served by

provider again would be . . .

4.33 0.76 12.37

3. Encounter with the provider

was . . .

4.02 0.84 14.20

4. Impression of the interaction with

provider was . . .

4.15 0.83 14.06

5. As a result of my interaction I

was . . .

4.34 0.86 14.76

Note: afull item description is available in the Appendix; bLoadings arestandardized beta coefficients

Table I Profile of online survey respondents

Percentage of users

Variable Internet Cellular

GenderMale 53 39

Female 47 61

Age in years18-20 59 60

21-25 37 38

36-35 4 2

Year in university programFirst year 38 22

Second year 25 41

Third year 25 19

Fourth year 12 18

Note: n ¼ 201




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the internal consistency of the scales. As other items were

within the recommended item to total correlation threshold

(ranging from 0.44 to 0.82), and the regression coefficients of

all measurement items loaded significantly at the p , 0:01level (ranging from 0.50 to 0.86), we determined that

convergent validity had been obtained. Furthermore, the

factor determinacy scores for the six constructs were 0.91 for

decision convenience, 0.91 for access convenience, 0.89 for

transaction convenience, 0.92 for benefit convenience, 0.93

for post benefit convenience, and 0.96 for satisfaction.To assess discriminant validity we constrained the

correlations between constructs to unity in the measurement

model, one at a time as described by Bagozzi (1981) and

Anderson and Gerbing (1988), and then repeated the

confirmatory factor analysis. Performing a chi-square

difference test revealed that in each case the constrained

model indicated a significant increase in chi-square (at the

p , 0:001 level) versus the unconstrained model (smallest

difference was Dx2 ¼ 4:78, df ¼ 1, p ¼ 0:028), suggesting

that discriminant validity was achieved.

Analysis and results

We assessed our hypothesis regarding service convenience and

overall satisfaction via structural equation modeling (SEM)

using Mplus 3.13 software (Muthen and Muthen, 2004). We

estimated one structural equation model to test the

relationship between the second-order factor model of

service convenience and satisfaction, and one structural

equation model to test the relationship between the five-factor

model of service convenience and satisfaction. The structural

model results are provided in Table IV. As was hypothesized,

service convenience was positively related to satisfaction

(g11 ¼ 0:98, t-value ¼ 5:23). Overall, service convenience

accounted for 98 percent of the variance in satisfaction.

Furthermore, as indicated in Table IV, the second-order

factor model of service convenience explained a significant

amount of the variance in the five first-order latent variables

reflecting the construct.These results indicate that the proposed second-order

factor is suitable, but they do not suggest that the

second-order model is better than a five-factor first-order

model of service convenience. Thus, we created and assessed

two rival models. Rival model no. 1 is based on the premise

that service convenience is not a second-order construct, but

rather five separate constructs of convenience with each of the

five constructs correlated to one another. Rival model no. 2

suggests that service convenience is a single-factor construct

rather than a second-order factor with five underlying

Table III Correlations for second-order service convenience factor and satisfaction

Construct/variable 1 2 3 4 5 6 7

1. Decision convenience –

2. Access convenience 0.64 –

3. Transaction convenience 0.69 0.55 –

4. Benefit convenience 0.80 0.65 0.70 –

5. Post-benefit convenience 0.74 0.59 0.64 0.75 –

6. Service convenience (second order) 0.89 0.72 0.77 0.90 0.83 –

7. Satisfaction 0.88 0.71 0.76 0.89 0.82 0.99 –

Average variance extracted 0.34 0.45 0.41 0.42 0.56 – 0.66

Scale mean 14.20 15.16 11.28 10.85 10.39 21.23

Standard deviation 2.73 2.66 2.03 2.16 2.83 4.94

No. of items 4 4 3 3 3 5

Note: All correlations are significant at the p , 0:01 level

Table IV Structural model results

Standardized

coefficient t-value

Second-order factor model:b

Service convenience ! Satisfaction 0.98 5.23

Service convenience ! Decision convenience 0.89 a

Service convenience ! Access convenience 0.72 5.41

Service convenience ! Transaction

convenience

0.77 3.94

Service convenience ! Benefit convenience 0.90 4.87

Service convenience ! Post-benefit

convenience

Explained variance in

satisfaction 5 97%

decision convenience 5 79%

access convenience 5 51%

transaction convenience 5 60%

benefit convenience 5 81%

post-benefit convenience 5 69%

0.83 4.69

Rival model no. 1: Five-factor model:c

Decision convenience ! Satisfaction 0.35 2.12

Access convenience ! Satisfaction 20.08 0.82

Transaction convenience ! Satisfaction 20.12 0.55

Benefit convenience ! Satisfaction 0.46 1.78

Post-benefit convenience ! Satisfaction

(Explained variance in satisfaction 5 94%)

0.44 4.00

Rival model no. 2: One-factor model:d

Convenience ! Satisfaction

(Explained variance in satisfaction 5 90%)

0.95 6.62

Notes: adenotes fixed parameter; bx2 ¼ 301:54ð199Þ p , 0:00, CFI ¼ 0:95,TLI ¼ 0:94, RMSEA ¼ 0:05 (0.04, 0.06), SRMR ¼ 0:05; cx2 ¼ 265:79ð190Þ

p , 0:00, CFI ¼ 0:96, TLI ¼ 0:96, RMSEA ¼ 0:05 (0.03, 0.06),SRMR ¼ 0:05; dx2 ¼ 442:93ð204Þ p , 0:00, CFI ¼ 0:88, TLI ¼ 0:87,RMSEA ¼ 0:08 (0.07, 0.08), SRMR ¼ 0:06




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dimensions. Results of the rival model comparison, providedin Table V, indicate that the five-factor model provides abetter fit to the data then both the second-order serviceconvenience model and the one-factor service conveniencemodel.The standardized regression coefficients for the five-factor

model (shown in Table IV), indicate that decision, benefit,and post-benefit convenience are positively associated withoverall satisfaction, albeit benefit convenience is onlysignificant at the p , 0:05 level. However, the relationshipsbetween overall satisfaction and both access and transactionconvenience are very small (negatively) and not statisticallysignificant. We discuss the implications of these results in thenext section.

Discussion

Service convenience is considered to be a significant part ofthe non-monetary value of a consumer service offering. Priorresearch has investigated convenience within a situationalsetting, but little has been done to develop measures for itsconceptualization within the context of the consumer buyingprocess. Berry et al. (2002) proposed a five-dimensionalconceptualization of service convenience that reflects theactivities consumers engage in during the acquisition andconsumption of services. To date, psychometrically validscales measuring this concept have not been published in theliterature. Our objective in this research was to develop andtest valid scales for measuring service convenience asconceptualized by Berry et al. (2002).

Theoretical contribution

At a theoretical level, our research contributes to the literaturein three ways. First, we have extended the services domain bydeveloping psychometrically valid scales for measuring serviceconvenience as a multidimensional construct includingdecision convenience, access convenience, transactionconvenience, benefit convenience, and post-benefitconvenience. This represents the “crucial early step”described by Berry et al. (2002, p. 11) that is required tofurther investigate future propositions regarding consumer,organization, and environmental factors that may moderatethe relationship between convenience and consumer serviceevaluation.Our second contribution to the service convenience domain

is the nomological testing of the service convenience measuresagainst satisfaction. Our results indicate the nomological

validity of the second-order model, and the model

comparison results and subsequent post hoc analysis

indicated that service convenience is positively associated

with satisfaction. However, the five components of

convenience may influence satisfaction in entirely different

ways. For example, the five-factor model found that access

and transaction convenience were not related to overall

satisfaction. These findings may indicate that in the

evaluation of satisfaction, consumers view convenience in

decision making and convenience of experiencing the benefits

they receive as the most important aspects of satisfaction with

the service provider and their offering. We discuss this further

in our directions for future research.Our third contribution is the assessment of service

convenience as a second-order factor. Our measurement

model fit results indicate that it is feasible to consider service

convenience as second-order construct given: first, the

acceptable model fit results, and second, the high positive

correlation between the five first-order factors. However,

given the rival model comparison results, it would appear that

although highly correlated, the dimensions of the service

convenience may be best modeled as five separate first-order

factors. Again, we discuss this in our directions for future

research.

Managerial implications

Managers are well aware of the positive implications of

convenience to consumer value and loyalty (Berry et al., 2002;

Keaveney, 1995). While the purpose of this paper was

primarily to begin the process of service convenience scale

development, and thus potentially of more interest to

researchers than managers, our results would suggest three

specific actions that managers could implement to increase

the convenience of their offer to customers.First, our results suggest that consumers positively related

overall service convenience to satisfaction. It may be prudent,

therefore, for managers to consider how they can improve

customer satisfaction through increasing the convenience of

their service. In homogeneous markets, where service

offerings are similar and therefore not key competitive

differentiators, providing greater convenience may enable a

competitive advantage. This may be particularly true for

technological services, such as cellular and internet, where the

consumer often initiates the service outside of the service

provider’s presence (e.g. at home).

Table V Rival model comparison

Rival model no. 1: Five-factor model Second-order factor model Rival model no. 2: One-factor model

x2 (df) 265.79(190) 301.54(199) 442.93(204)

CFI 0.96 0.95 0.88

TLI 0.96 0.94 0.87

RMSEA 0.05 (0.03, 0.06) 0.05 (0.04, 0.06) 0.08 (0.07, 0.08)

SRMR 0.05 0.05 0.06

AICa 10,290.472 10,308.218 10,439.607

BICb 10,498.580 10,486.597 10,601.469

S.A. BICc 10,298.987 10,315.516 10,446.230

Dx2 (df) 35.75(9) p , 0:001 177.14(14) p , 0:001

Notes: aAkaike Information Criterion; bBayesian Information Criterion; cSample-Size Adjusted Bayesian Information Criterion




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Second, our results suggest that consumers’ satisfactionincreases when providers make decision making moreconvenient and ensure that the customer can easily takeadvantage of the benefits of the service they seek. As such,ensuring that personal and non-personal support (e.g.salespeople and catalogues) is clear and understandable fromthe consumers’ perspective is an important part of makingdecisions easier for consumers. Furthermore, when developingspecific attributes for new or existing service offerings (e.g.adding voice messaging to cellular packages), managers shouldconsiderhoweasily theseattributes canbeusedby thecustomer.In short, when customers can conveniently make decisionsabout a service purchase and then conveniently experience thebenefits of the service, they are more likely to be satisfied.Third, our results suggest that providing convenient post-

purchase support to consumers is vital to enhancing theirsatisfaction with the service. Berry et al. (2002) suggest thatmaking post-purchase contact convenient for consumersincreases their satisfaction by providing more satisfyingmethods of resolving any issues they may have. Furthermore,unresolved or unreported complaints generally result indecreased repurchase behavior (Zeithaml and Bitner, 2000).Therefore, managers should ensure that customer supportfunctions are easily accessible to consumers should they need tocontact their service provider for post-purchase activities.Finally, this research provides firms with a relatively

simple tool that can be used to measure different aspects ofthe convenience of their offering. This tool enablesmanagers to further investigate their own customers’ needsand wants in relation to the acquisition and consumption oftheir service.

Limitations and directions for future researchAs with all studies, this study has several limitations andfuture directions that need to be considered. First, we used astudent sample to test the model and hypotheses. Theexploratory research we conducted in the generation ofservice convenience measurement items was drawn from aconvenience sampling outside of the student population.Although students are consumers of cellular and internetservices, it is possible that they are a homogenous group,which may affect the generalizability of the results. Futureresearch should consider the use of a random sampling of amuch wider base of consumers.Second, our data collection has twoprimary limitations.One,

we used an online survey method, which may have precludedthose who did not have access to the internet, although themethod did allow us to control for duplicate responses. Also, wecannot know for sure that the intended respondent was indeedthe one who completed the survey. Two, the survey askedrespondents to report on both the service convenience andoutcomes of service convenience (satisfaction) within the samesurvey. As such, it is possible that the results may be subject tocommon method bias. Future research might considerreplicating these results using multi-method approachescombining experimental and staged surveys in both online andoffline environments. Similarly, researchers should investigatethe process by which consumers retrospectively evaluate andmake sense of service convenience (Weick, 1995). Our findingthat access and transaction convenience are not related tosatisfaction may indicate that consumers are not able toretrospectively separate out these dimensions accurately byway of a self-administered questionnaire.

Furthermore, our research investigated service convenience

within the cellular telephone and internet services context,

within one city, and within one country. Thus, there are risks

associated with generalizing these results to other industries in

other cities and countries. Future research should consider

replicating and extending this research across cultures and

industries to provide for a more solid understanding of how

service convenience influences consumers’ evaluation of their

services. Replication and extension is also important in order

to further develop the scale items. It is possible that in

different contexts the factors may not be invariant as they

were in this research.Further research is also needed to explicate the role that

variables such as price and quality play in the service

convenience to satisfaction relationship. For example, it is

known that consumers explicitly or implicitly consider the

price and quality of a product or service when evaluating its

overall value (Zeithaml, 1988). Thus, varying degrees of

perceived value influence the convenience to satisfaction

relationship. Furthermore, given the potential that certain

products or services may, by their nature, require varying

degrees of consumer tolerance with regards to wait times

(Durrande-Moreau and Usunier, 1999), the effect of this

inconvenience cost (Zeithaml and Bitner, 2000) may not be

captured in the service convenience construct.Finally, future research should consider expanding the

service convenience domain by further exploring the

propositions set out by Berry et al. (2002). This research

represents the first step in providing valid scales for measuring

service convenience, but as Berry et al. (2002, p. 14) suggest,

“service convenience is uncharted territory and requires

further investigation in order to increase our understanding of

this phenomenon.”

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Appendix. Survey items

Decision convenience

1 The information I received from the —a service providermade it easy for me to choose what to buy.

2 Making up my mind about what —a service I wanted tobuy was easy.

3 The information that I received from the service providerwas very clear and easy to read.

4 The service provider let me know the exact cost or specialoffers before I bought the —a service.

Access convenience

1 The service provider was available when I needed to talkto them.

2 The service provider is accessible through various ways(online, telephone, and in person).

3 The hours of operation of the service provider wereconvenient.

4 It is easy for me to contact an employee of the —a serviceprovider if necessary.




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Transaction convenience

1 I found it easy to complete my —a service purchase withmy provider.

2 I was able to complete the purchase of my service quickly.3 There were no problems to deal with during the purchase

that added to the purchase time.

Benefit convenience

1 I was able to get the benefits of the —a service with littleeffort.

2 The service provider solved my —a needs without creatingother problems.

3 The time required to receive the benefits of the —a servicewas reasonable.

Post-benefit convenience

1 My —a service provider quickly resolved any problems Ihad with the service.

2 It was easy for me to obtain follow up service from theprovider after my purchase.

3 When I have questions about my service, my —a serviceprovider is able to resolve my problem.

Satisfaction

1 Overall, I am satisfied with my —a service provider(Strongly disagree . . . Strongly agree).

2 My feelings about being served by this —a service provideragain would be . . . (Very Unhappy . . . Very Happy).

3 My encounter with the —a service provider was . . . (Worse

than expected . . . Better than expected).4 My impression of the interaction of the service provider

with me was . . . (Unfavorable . . . Favorable).5 As a result of my interaction with the service provider I

was . . . (Dissatisfied . . . Satisfied).

Note: —a was either internet or cellular.

Corresponding author

Scott R. Colwell can be contacted at: [email protected]

Executive summary and implications formanagers

This summary has been provided to allow managers and executivesa rapid appreciation of the content of the article. Those with aparticular interest in the topic covered may then read the article intoto to take advantage of the more comprehensive description of theresearch undertaken and its results to get the full benefit of thematerial present.

“Help yourself” is one of those courteous, small-talk phrasespeople often use. Whether it’s “help yourself” to a cup ofcoffee or a piece of cake in someone’s home your are visiting,

or “help yourself” to some of the newly-dug potatoes orcarrots from their allotment, or “help yourself” to a novelfrom their bookshelf which you’ve expressed an interest in

reading, it’s a kind, unselfish sort of sentence which denotesfriendliness, generosity, welcome and sharing.

In business, however, far from referring to something you

give away gladly, “help yourself” is an invitation to customersto share in the service delivery – more convenient for them,

and less costly for the supplier. Whether it’s a mighty internetshop, such as Amazon, with customers “helping themselves”

by browsing and ordering books online, or a farmer’s roadside“pick your own strawberries” venture, getting the customer to

do a chunk of the work themselves can’t be a bad idea.Especially in the face of an increasing consumer desire for

more convenient methods of conducting business.To meet these desires, and to minimize potential loss of

customer, service providers have employed methods such asinternet commerce, live technical online chat capabilities, and

mobile telecommunication services. Given the pressure toprovide increased convenience, it is not surprising that

organizations have made significant investments in enhancingthe convenience aspect of their product and service offering

and, as such, service convenience is of significant interest tomanagement and scholars.As a solid understanding of the conceptualization and

measurement of service convenience appeared to be lacking,

previous researchers proposed a conceptualization of fivedifferent forms of service convenience that reflects the

activities consumers engage in during the acquisition andconsumption of services – decision, access, transaction,

benefit, and post-benefit.In the context of cellular phones and internet service usage,

Scott R. Colwell et al.’s study provides psychometrically-validscales for measuring these conceptualized dimensions.While their purpose was primarily to begin the process of

service convenience scale development, and consequently the

results are potentially of more interest to researchers thanmanagers, they do suggest three specific actions that

managers (who are no doubt well aware of the positiveimplications of convenience to consumer value and loyalty)

could implement to increase the convenience of their offer tocustomers.First, consumers appear to positively relate overall service

convenience to satisfaction. It may be prudent, therefore, for

managers to consider how they can improve customersatisfaction through increasing the convenience of their

service. In homogeneous markets, where service offeringsare similar and therefore not key competitive differentiators,

providing greater convenience may enable a competitiveadvantage. This may be particularly true for technological

services, such as cellular and internet, where the consumeroften initiates the service outside of the service provider’s

presence (e.g. at home).Second, results suggest that consumers’ satisfaction

increases when providers make decision-making moreconvenient and ensure that the customer can easily take

advantage of the benefits of the service they seek. As such,ensuring that personal and non-personal support (e.g.

salespeople and catalogs) is clear and understandable fromthe consumers’ perspective is an important part of making

decisions easier for consumers. Furthermore, whendeveloping specific attributes for new or existing service

offerings (e.g. adding voice messaging to cellular packages),managers should consider how easily these attributes can beused by the customer. In short, when customers can

conveniently make decisions about a service purchase andthen conveniently experience the benefits of the service, they

are more likely to be satisfied.




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Third, the results suggest that providing convenientpost-purchase support to consumers is vital to enhancingtheir satisfaction with the service. Making post-purchasecontact convenient for consumers increases their satisfactionby providing more satisfying methods of resolving any issuesthey may have. Unresolved or unreported complaintsgenerally result in decreased repurchase behavior.Therefore, managers should ensure that customer supportfunctions are easily accessible to consumers should they needto contact their service provider for post-purchase activities.Finally, this research provides firms with a relatively simple

tool that can be used to measure different aspects of theconvenience of their offering. It enables managers to furtherinvestigate their own customers’ needs and wants in relationto the acquisition and consumption of their service.

Organizations have traditionally increased value to

consumers by either:. lowering the price of the product or service;. increasing the quality of the product or service; or. decreasing non-monetary costs such as the time and effort

required to acquire and consume the product.

In dynamic competitive service environments, providing

satisfactory value to the consumer is imperative. Failure to

do so can lead to lost customers and future revenue streams

that are costly to replace.

(A precis of the article “Toward a measure of service convenience:

multiple-item scale development and empirical test”. Supplied by

Marketing Consultants for Emerald.)




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Toward a measure of service convenience: multiple‐item scale development and empirical test