measuring consumer perceptions of online shopping convenience

Measuring consumer perceptionsof online shopping convenience

Ling (Alice) JiangFaculty of Management and Administration,

Macau University of Science and Technology, Taipa,Macau, China

Zhilin YangDepartment of Marketing, City University of Hong Kong,

Hong Kong, China, and

Minjoon JunManagement Department, New Mexico State University,

Las Cruces, New Mexico, USA

Abstract

Purpose – The purpose of this paper is to identify the key convenience dimensions of onlineshopping, as convenience has been one of the principal motivations underlying customer inclinationsto adopt online shopping.

Design/methodology/approach – The authors first employ in-depth focus group interviews withonline consumers to identify the attributes of online shopping convenience and then develop andvalidate an instrument of five key dimensions to measure online shopping convenience by analyzingdata collected via a Web-based questionnaire survey.

Findings – The five dimensions of online shopping convenience are: access, search, evaluation,transaction, and possession/post-purchase convenience.

Practical implications – Online retailers can employ the five-factor measurement instrument toassess the degree of customer perceived online shopping convenience. This instrument can assistmanagers in identifying and overcoming key obstacles to the delivery of a highly convenient onlineshopping service to customers, and also helps them enlarge their loyal customer base.

Originality/value – This study focuses on uncovering the key dimensions of convenience and theirassociated sub-dimensions specific to the context of online shopping. Theoretically, the identifieddimensions and their related sub-items comprise a validated scale for measuring Web-based serviceconvenience and can serve as building blocks for further studies in e-commerce customer relationshipmanagement.

Keywords Consumer behaviour, Internet, Shopping, Electronic commerce, Perception, Convenience,Online shopping, Scale development, e-commerce

Paper type Research paper

Shopping convenience has been one of the principal motivations underlying customerinclinations to adopt online purchasing (Beauchamp and Ponder, 2010; Colwell et al.,2008; Degeratu et al., 2000; Easterbrook, 1995; Lohse and Spiller, 1998; Moeller et al.,2009; Morganosky and Cude, 2000; Reimers and Clulow, 2009; Tanskanen et al., 2002).As consumers allocate less time to shopping and more to other endeavors, their desire

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The authors thank Daniel Ding for his help in data collection. The second author gratefullyacknowledges a grant from City University of Hong Kong (CityU SRG Project No. 7008124).

Received 31 January 2012Revised 27 May 2012

24 August 20122 October 2012

Accepted 5 October 2012

Journal of Service ManagementVol. 24 No. 2, 2013

pp. 191-214q Emerald Group Publishing Limited

1757-5818DOI 10.1108/09564231311323962

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for convenience has mounted and their attention has been frequently diverted to virtualshopping as an alternative medium. A crucial point of departure for online retailerswho wish to take steps designed to maximize the speed and ease of shopping is todevelop an understanding of the salient dimensions of online shopping convenienceand the specific domain within each dimension.

As a context-based concept, consumers’ perceptions of convenience can vary from onesetting to another. Much of the existing convenience literature, however, has beenrestricted to a study of the development of the multidimensional service convenienceconstruct in a conventional, brick-and-mortar retailing environment (Clulow and Reimers,2009; Fitch, 2004; Reimers and Clulow, 2009). Although online shopping convenienceis one of the major factors that prompt consumers to access online retailers’ web sites(Ahmad, 2002; Jayawardhena et al., 2007), much of the prior research on e-commerce hastreated the convenience construct as one of the predictor variables, such as customerservice and trust, that affect outcome variables, such as customer satisfaction andbehavioral intentions (Colwell et al., 2008; Seiders et al., 2007), or as one of the facets ofonline service quality, such as accuracy and responsiveness (Hu et al., 2009; Kim and Park,2012; Prasad and Aryasri, 2009; Udo et al., 2010). Unfortunately, very few studies offer anin-depth, systematic investigation into online shopping convenience dimensions and thespecific items or components under each dimension (Colwell et al., 2008; Beauchamp andPonder, 2010). The study conducted by Beauchamp and Ponder (2010) is exceptional, buttheir study is limited to the convenience dimensions common to both online and offlineshopping settings and examines the relative importance of each dimension from theperspectives of online and offline shoppers, rather than exploring the dimensions and theirrelated items unique to online shopping. Thus, the unique aspects of the internet as ashopping platform, such as ease of use, interactivity, information search and contents, andsystem reliability (Jun et al., 2004; Kim and Park, 2012; Udo et al., 2010; Yang and Fang,2004) warrant further examination on online shopping convenience.

Our study, therefore, intends to address the following research questions:

RQ1. What dimensions of convenience do customers experience in the setting ofonline shopping?

RQ2. What distinct components under each dimension are unique to online shopping?

RQ3. What can be recommended to enhance the overall level of customer perceivedonline shopping convenience?

To answer these questions, we first attempt to identify the key convenience dimensionsof online shopping through conducting focus group interviews. We then develop andvalidate an instrument to measure online shopping convenience by analyzing datacollected via a web-based questionnaire survey from 550 online customers of a majorretail company in Hong Kong. Based on the findings, we summarize our theoreticalcontributions and provide managerial implications regarding how to enhance theoverall level of online shopping convenience.

Conceptual frameworkThe essence of convenienceWebster’s Dictionary defines convenience as “anything that adds to one’s comfort orsaves work; useful, handy or helpful device, article, service, etc.” In the marketing

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literature, the concept of convenience was introduced by Copeland (1923), whoreferred to convenience goods as those that the consumer purchases frequently andimmediately at easily accessible stores. Copeland (1923) and other researchers (Bucklin,1963) have used the convenience construct within the domain of the “convenience”classification of products, which relates to low risk or low involvement in purchasing(Brown, 1989). Subsequently, in an effort to accurately operationalize the construct,some researchers have shifted their attention from a product attributes-orientedapproach to a service attributes-oriented direction (Seiders et al., 2000, 2005, 2007).

Much of the literature on consumer convenience in a traditional retailingenvironment has revealed two factors of primary importance in delivering convenientservice to customers: time-saving and effort minimization efforts (Etgar, 1978; Kotlerand Zaltman, 1971; Seiders et al., 2000, 2005, 2007; Yale and Venkatesh, 1986).In particular, the marketing literature has emphasized the importance of desire forconvenience and the value of time. Berry et al. (2002) have concluded, based on theirliterature review, that the greater the time costs associated with a service, the lower thedegree of consumers’ perceived service convenience. They have further posited thatconsumer perceptions of convenience are negatively influenced by their perceptionsof the cognitive, physical, and emotional effort associated with the shopping effort.In the same vein, Seiders et al. (2000) have argued that the emphasis customers placeon convenience has prompted retailers to extend one-stop shopping, redesign storeoperating systems, and emphasize service sales. They also suggest some ways to offercustomers convenient shopping, including strategies to enhance the speed and easewith which consumers can reach a retailer, identify, select, and obtain products, andamend transactions.

Furthermore, Berry et al. (2002) and Seiders et al. (2007) have extensively reviewedthe literature on consumer convenience in a service economy and define “serviceconvenience” as consumers’ time and effort perceptions related to buying or using aservice. Although there are distinct differences between goods and service conveniencein some literature (Kelley, 1958), Berry et al. (2002) have noted that all businessesindeed offer service for their customers, so service convenience applies to both goodsproviders and service providers. As the definition implies, the level of perceived serviceconvenience is primarily influenced by non-monetary costs – those relating to timeand effort (or energy expenditure). Berry et al. (2002) further point out that the benefitsof service convenience constitute saving time and/or effort, whereas the burdens ofinconvenience entail wasting time and/or effort. In turn, researchers classify andsummarize major findings of prior research in terms of the identified two majorelements – time and effort (Berry et al., 2002; Seiders et al., 2007). The time-savingaspect of convenience has been intensively investigated in consumer waiting literature,particularly with respect to consumer reaction to waiting time (Gehrt and Yale, 1993).

The concept of effort-saving refers to the minimization of cognitive, physical,and emotional activities that consumers must bear to purchase goods and services(Berry et al., 2002). As noted by Berry et al. (2002), despite the abundant literatureaddressing the time-saving component of convenience, previous studies have devoted onlymoderate emphasis to the effort aspect (Brown, 1990; Hui et al., 1998; Seiders et al., 2000).While the cognitive effort is related to purchasing decisions, physical and emotionalefforts are associated with consumer participation in the production/operations process.Although there has been a lack of literature addressing physical and emotional efforts,


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many studies (Fennema and Kleinmuntz, 1995; Fiske and Taylor, 1984) have attempted toexamine the issue of cognitive (or mental) efforts and have consistently found that mostindividuals have quite limited cognitive resources and, acting as cognitive misers,conserve these resources during decision-making endeavors.

Dimensions of traditional service convenienceThe construct of service convenience is multidimensional in nature (Berry et al., 2002;Brown, 1989, 1990; Colwell et al., 2008; Seiders et al., 2007; Yale and Venkatesh, 1986).Service convenience in retailing mainly refers to the speed and ease of shopping.Yale and Venkatesh (1986) have developed six classes of convenience: time utilization,accessibility, portability, appropriateness, handiness, and avoidance of unpleasantness.Similarly, Brown (1990) has generated five dimensions of convenience: time, place,acquisition, use, and execution convenience. Further, he has noted that among these,the first four dimensions are closely related to the four utilities promulgated by economicutility theory.

In a subsequent effort, a content analysis conducted by Gehrt and Yale (1993)suggests that convenience consists of three distinct dimensions: time, place, andeffort. This classification possesses the advantages of simplicity and universality.Nevertheless, as argued by Berry et al. (2002), this scheme has two major weaknesses:First, the three dimensions are not mutually exclusive, as they are highly correlated;and, second, from a diagnostic or operational perspective, this scheme lacksmeaningful analytical functions. These disadvantages were partially addressed byBerry et al. (2002), in which they integrated time and effort dimensions into the processof consumer decision-making and categorized the convenience characteristics into fiveactivity-based dimensions, which mirror the activities consumers undergo to purchaseor use a service. These are: decision (consumers’ perceived time and effort expendituresto make service purchase or use decisions), access (to initiate service delivery),transaction (to effect a transaction), benefit (to experience the service’s core benefits,such as being transported in a taxi), and post-benefit convenience (when reinitiatingcontact with a firm for repairs or maintenance after the benefit stage of the service).

In the context of retailing, Seiders et al. (2000) suggest four avenues for providingconvenience:

(1) Access. Consumers may reach a retailer.

(2) Search. Consumers can identify and select products they wish to buy.

(3) Possession. Consumers can obtain desired products.

(4) Transaction. Consumers can effect or amend transactions.

Subsequently, Seiders et al. (2005, 2007) have developed and validated thefive-dimension instrument, the SERVCON scale, in the context of brick-and-mortarretailer chains that carry apparel and furnishings. The SERVCON scale with 17 items,measuring decision (easily determine prior to shopping whether it will offer what I need),access (able to get quickly and easily), transaction (makes it easy for me to conclude mytransaction), benefit (the merchandise I want can be located quickly), and post-benefitconvenience (easy to take care of returns and exchange), showed good reliability andvalidity for in-store shopping convenience. Furthermore, they have tested nomologicalvalidity to specify several antecedent and consequent factors related to service

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convenience (Seiders et al., 2007). Later, scholars identified such specific aspects ofconvenience as location convenience, parking convenience, and sales assistantservice convenience (Clulow and Reimers, 2009; Kwek et al., 2010; Reimers andClulow, 2009). A summary of convenience dimensions identified in the relevantliterature is presented in Table I.

Online shopping convenienceAs previously mentioned, convenience is a context-based concept. Seiders et al.’s (2007)SERVCON measurement developed in the context of traditional offline shopping doesnot embrace the unique facets of online shopping convenience since online retailersutilize the internet as a shopping platform. Prior literature on online service quality hasidentified several service convenience features unique to virtual shopping indicatingsome of the ingredients constituting online service quality, such as ease of use,interactivities, information search, the depth and richness of information, and security( Jun et al., 2004; Parasuraman et al., 2005; Wolfinbarger and Gilly, 2003; Yang andPeterson, 2004; Yang et al., 2005). However, despite the strategic importance of serviceconvenience to the success of online retailers, researchers have paid little attention toempirically examining the salient dimensions of online shopping convenience andtheir related features in an in-depth and systematic manner. Relatively few studieshave addressed the issue of consumer perceived convenience in e-commerce. In thesetting of internet services via wireless communications, Jih (2007) has extractedtwo dimensions, such as transaction convenience and operational convenience, andhas argued that the former dimension exerts a significant effect on the consumer’sonline shopping intentions. In the context of personal telephone and internetusage, Colwell et al. (2008) have developed, based on the work of Berry et al. (2002),a multiple-item scale measuring the five dimensions of service convenience.

Source Types of convenience Dimensions of convenience

Yale and Venkatesh (1986) Characteristics of conveniencegoods

Time utilization, accessibility,portability, appropriateness,handiness, and avoidance ofunpleasantness

Brown (1990) General Time, place, acquisition, use,and execution convenience

Gehrt and Yale (1993) General Time, place, and effortSeiders et al. (2000) Retail convenience Access, search, possession, and

transactionBerry et al. (2002), Seiders et al.(2005, 2007), Colwell et al. (2008)

Service convenience in aretailing context

Decision, access, transaction,benefits, and postbenefitconvenience

Jih (2007) Convenience in a mobilecommerce context

Transaction convenience andoperational convenience

Reimers and Clulow (2009),Clulow and Reimers (2009)

Retail centre convenience Time convenience, carconvenience, spatialconvenience, hedonic shopping,and effort convenience

Beauchamp and Ponder (2010) Retail convenience both for in-store and online shoppers

Access, search, transaction, andpossession convenience

Table I.Dimensions

of convenience


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They empirically find that service convenience has a significant impact on customers’overall satisfaction. Other researchers have also identified some key elements ofconvenience that are conducive to customer satisfaction, such as visual design,information quality, and delivery service (Koo et al., 2008; Yang et al., 2005). Later,Beauchamp and Ponder (2010) examine the key differences between in-store and onlinecustomers based on the following four types of retail convenience: access, search,transaction, and possession convenience. They find that, compared to conventionalin-store shopping, consumers perceive online shopping as being more convenient forpurposes of access and search convenience, but not in terms of transactionconvenience.

In sum, the importance of service convenience and the challenges facinginternet-based services necessitate insights on the part of managers insofar as whichattributes customers use in their evaluation of online shopping convenience. However,a rigorous measurement instrument of online shopping convenience has not yet beenmade available. In order to improve that condition, drawing on the work of Berry et al.(2002) and Seiders et al. (2005, 2007), we intend to identify salient online shoppingconvenience dimensions, confirm the identified major convenience dimensions and theirassociated features, and develop a parsimonious and valid online shopping conveniencemeasurement instrument.

MethodologyWe employed a two-stage approach in developing a reliable and valid instrument ofonline shopping convenience as perceived by online customers: in-depth focus groupinterviews and a web-based questionnaire survey.

Focus group interviewsWe employed focus group interviews as a means to collect detailed customers’feedback on their feelings, attitudes, and perceptions about online shoppingconvenience. The focus group interview method is similar to the in-depth interviewin that the group moderator has prepared guidelines that outline the topics to bediscussed. But instead of a one-on-one forum, questions are posed to the group, and agroup discussion of each topic ensues, where interaction among group membersproduces mutual stimulation of thoughts and recall of feelings and experiences(Ford et al., 1997). In this sense, focus group interviews are a robust method of gatheringinformation on how interviewees view online shopping convenience. Our study wascarried out in collaboration with one large company located in Hong Kong.

The selected firm is the largest supermarket retailer in the city, operating more than250 distribution outlets and employing over 5,000 employees. The company handlesover 13 million business transactions per month, providing a wide range of groceriesand household goods. The firm has been a leader among Hong Kong supermarketchains in the adoption of newly developed IT technologies to improve its internaloperating efficiency and create value for customers. In 1992, the company was the firstretailer to implement, in all of its distribution outlets, an electronic point-of-salessystem utilizing barcode-scanning techniques. This firm was also the first supermarketin Hong Kong to provide e-shopping service to the public in 1996. The company’s“Home Shopping on the Internet” service enables customers to order and receiveproducts at home through its web site. The supermarket retailer was chosen because:

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(1) it provides both traditional and online services, representing the emerging trendof the retailing industry;

(2) it has a large customer base; and

(3) its focus is on the convenience side of online shopping, instead of price.

Sample and instrumentWe conducted three separate focus group interviews with the customers of a majorsupermarket chain company located in Hong Kong. Each focus group interview lastedapproximately two hours. 15 customer participants were selected, as a conveniencesample, by the Marketing Director of the contact company from the list of its onlinecustomers living in Hong Kong. The selection of the interviewees was based upon thefollowing two criteria:

(1) diversity of interviewees in terms of demographic background and shoppingbehaviors; and

(2) willingness of interviewees to participate in the fairly lengthy group interviewin an active way.

Then, those selected were randomly assigned to each of the three interview groups sothat each group consisted of five participants. The sample size of the interviewees wasdeemed small, but still adequate for qualitative research methods, since the primaryfocus of this stage is placed on the elicitation of abundant textual data rather than onthe verification of certain research hypotheses (Cowles et al., 2002).

Semi-structured questionnaires were utilized for the focus groups interviews.These were conducted in a relaxing and pleasant atmosphere. Customer informantswere provided introductory questions and were further asked to describe criticalepisodes that occurred with online shopping, in general, and with the selected company,in particular. Most questions were concerned with the benefits of online shopping andthe issues related to online shopping convenience and inconvenience, e.g. productand information search, minimum purchase amount for obtaining free delivery service,and online security. The interviewees were also encouraged to make comparisonsbetween online and offline shopping convenience. The interview questions aresummarized in Appendix 1. All conversations were videotaped and recorded for furtheranalysis.

Results of focus group interviewsThe textual results of the focus group interviews were content analyzed by a trainedresearch assistant and the authors of this study. The two researchers coded the textindependently. All the differences were resolved through discussion. A total of30 coding words were developed after a general review of the entire content. Thesecoding words were created to capture critical facets of online shopping convenience orinconvenience based on elicited customer episodes. Meanwhile, the number of codingwords in each dimension was kept parsimonious by further regrouping similar wordsinto one generalized item. Table II sets forth the six major dimensions derived, such asaccess, search, evaluation, transaction, possession, post-purchase convenience, andtheir associated descriptions.


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Web-based questionnaire surveyTo verify the online-shopping convenience dimensions that emerged from analysis offocus group interview results, we follow the guidelines of scale development proceduresprovided by Churchill (1979) and Gerbing and Anderson (1988). We first drafted a surveyquestionnaire based on the six identified dimensions of online shopping convenience.A total of 31 measurement items were generated. These items were then assessedfor content validity by a panel of academics, consisting of five faculty members fromtwo universities located in Hong Kong and Macau. They were asked to review thedescriptions of six online shopping convenience dimensions, and match the 31 items withthe six dimensions, based on closeness in meanings. As a result, we removed three itemsthat were not clearly matched with any of the dimensions and created a revised surveyquestionnaire with 28 items. In addition, a pretest was conducted by sending thequestionnaire to 127 undergraduate marketing students. A total of 102 effectiveresponses were received. We performed a series of correlation analyses, reliability testsand exploratory factor analyses for each construct. As a result, six items with the lowestreliability or factor loading were deleted.

Dimension Description

Access convenience (1) Time flexibility(2) Space flexibility(3) Energy used(4) Accessibility of web sites(5) Availability of products and brands

Search convenience (1) Download speed(2) Web design(3) Search engine capacity(4) Search function(5) Product classification(6) Average number of items per product menu listing(7) Number of lists that have to be scrolled down

Evaluation convenience (1) Product information(2) Standardized and branded products(3) The presence of price information in product listings(4) Product categorization

Transaction convenience (1) Check-out process(2) Payment methods (e.g. check and cash)(3) Changes in purchase(4) Confirmative reply(5) Price inconsistency

Possession convenience (1) Delivery offered(2) On-time delivery(3) Delivery change notification(4) Product undamaged(5) Attitude and performance of deliverymen

Post-purchase convenience (1) Keep promises (e.g. product return and reward delivery)(2) Customer protection(3) Self-protection tips(4) Personal data security (e.g. e-mail address)

Table II.Descriptions ofonline shoppingconvenience dimensions

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The second revised survey questionnaire consisted of 22 items assessing onlineshopping convenience. In addition, three items assessing the “behavioral intentions”construct were adapted from Seiders et al. (2007). All items were measured on afive-point Likert scale anchored at strongly disagree (1) and strongly agree (5)(Appendix 2).

Data collectionWith assistance from the supermarket chain company, we posted a banner with anembedded link to the online survey questionnaire on the company’s official web site.We offered a supermarket cash coupon of HK$50 as an incentive to surveyparticipants. A total of 623 consumers responded within two weeks. After screeningthe questionnaires, we eliminated 73 incomplete and repeat questionnaires. As a result,a total of 550 usable responses were collected. A demographic profile of therespondents is presented in Table III. Non-response bias did not appear to be a problem

Variable Frequency Percentage

GenderMale 205 37.3Female 345 62.7Age in years16-24 81 14.725-34 159 28.935-44 161 29.345-54 110 20.055 and above 39 7.1EducationPrimary school 3 0.5High school 67 12.2Technical school/some college 130 23.6College graduation and above 350 63.6Annual household incomeLess than $10,000 23 4.2$10,000-$29,999 95 17.3$30,000-$49,999 129 23.5$50,000-$69,999 136 24.7$70,000-$99,999 86 15.6$100,000 and above 81 14.7Time of e-shoppingUnder six months 27 4.90.5-1 year 66 12.01-2 years 117 21.33-5 years 231 42.0Over 5 years 109 19.8Average hours spent online1-5 h per week 11 2.01-2 h per day 124 22.53-5 h per day 216 39.3Over 5 h per day 199 36.2

Note: n ¼ 550Table III.

Profile of respondents


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because a series of t-tests results indicated that there were no statistically significantdifferences between the early and late responses (Armstrong and Overton, 1977).

ResultsKey dimensions of online shopping convenienceWe conducted an exploratory factor analysis (EFA) using principal components factoranalysis with a Varimax rotation. To identify the major convenience dimensions ofonline shopping, we randomly selected 137 samples (i.e. one-fourth of the 550 samplescollected) for EFA. The rest were set aside for a confirmatory factor analysis (CFA).The initial EFA extracted six factors that had an eigenvalue greater than one. Basedon the EFA results, two items that did not load strongly on any factor or displayedsignificant cross-loadings were deleted. These two items were concerned with customerinformation protection and transaction data security, respectively. One plausibleexplanation for such removal of the two items lies in our respondents’ difficulty injudging the level of post-purchase convenience, as the surveyed retailer has maintaineda good record of ensuring information security. In addition, ensuring online informationsecurity and data integrity could be considered as an “order qualifier” allowing firmsmerely to remain in the market, rather than as an “order winner” allowing firms to gaincompetitive advantage in the market.

We reiterated EFA using the retained 20 items and, as a result, each itemloaded strongly on one and only one factor with an eigenvalue greater than one. Fivefactors were generated, explaining 64.318 percent of the total variance. They werelabeled as:

(1) access convenience;

(2) search convenience;

(3) evaluation convenience;

(4) transaction convenience; and

(5) possession/post-purchase convenience (Table IV).

Note that the EFA yielded a new factor, possession/post-purchase convenience, whichcombined four items pertaining to possession convenience with one item, “easy toreturn unwanted items”, assessing post-purchase convenience. As noted by Seiders et al.(2005, 2007), the construct of post-purchase convenience is mainly concerned withproduct returns.

Among the five factors, search convenience, accounting for the largest portion (30.967percent) of the total variance, centered on user-friendly web sites, variety of search options,and finding desired products quickly. The second factor, possession/post-purchaseconvenience, represented 13.383 percent of the variance. It measured timely productdelivery, whether or not prices are identical to those on the order form, and ease ofproduct returns. The third factor, evaluation convenience, made up 7.459 percent of thevariance. It consisted of three items referring primarily to the provision of detailed andwell-organized product information on the web site. The fourth factor, access convenience,explained 7.034 percent of the variance and addressed the accessibility to the web site. Thefifth and last factor, transaction convenience, accounted for 5.475 percent of the varianceand consisted of three items measuring the simplicity and flexibility of payment methods.The revised 20-item online shopping convenience scale is provided in Table IV.

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Confirmatory factors analysisAfter specifying the latent measurement model and employing the retained20 questionnaire items, we ran CFA on the remaining 413 cases to uncover theunderlying factor structure of the online shopping convenience construct. We firstundertook a first-order measurement model using AMOS7.0 (Figure 1).

The first-order measurement model exhibited a reasonable model fit (x 2/df ¼ 2.734;p , 0.001; RMR ¼ 0.035; GFI ¼ 0.903; IFI ¼ 0.914; CFI ¼ 0.913; RMSEA ¼ 0.065).However, the following two items were recommended to be discarded by the CFAresults because they had unacceptably weak loadings (below 0.5) on their designatedfactors: attractiveness of the web site and a variety of search options to find the sameproduct. From a practical standpoint, because 83.1 percent of the respondents have overone year online shopping experience with the retailer (Table III), the attractiveness ofthe web site has become less important in terms of convenience. In addition,our follow-up interviews with the respondents also reveal that they care more for thesearch function than for complex search options. Accordingly, after deleting these twoitems, we reiterated CFA and found that the revised first-order measurement modelshowed a good fit of model to the data (x 2/df ¼ 2.809; p , 0.001; RMR ¼ 0.032;GFI ¼ 0.910; IFI ¼ 0.924; CFI ¼ 0.923; RMSEA ¼ 0.066) (Hu and Bentler, 1999).

Factors1 2 3 4 5

Access convenienceCould shop anytime I wanted 0.806Could order products wherever I am 0.761The web site is always accessible 0.732Search convenienceEasy to understand and navigate web site 0.744Find desired products quickly 0.736Product classification is easy to follow 0.728Attractive web sitesa 0.727User-friendly web site for making purchases 0.678Variety of search options to find the same producta 0.536Evaluation convenienceProvides product specifics 0.803Uses both text and graphics of product information 0.705Sufficient information to identify different products 0.679Transaction convenienceSimple and convenient online payment 0.834Flexible payment methods 0.785Without difficulty to complete my purchases 0.629Possession/post-purchase convenienceUndamaged delivered goods 0.785Prices are identical to those on the order form 0.778Timely product delivery 0.720Easy to return unwanted items 0.684Receive all the items I ordered 0.648

Notes: aItems were deleted in the final scale; extraction method: principal component analysis;rotation method: Varimax with Kaiser normalization; n ¼ 137

Table IV.Exploratory factor

analysis


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As demonstrated in Table V, all of the 18 items loaded on their designated constructssignificantly, with loadings ranging from 0.589 to 0.848.

We assumed that there existed a second-order factor of customers’ perceivedoverall online shopping convenience that explained the five first-order factors.Therefore, a second-order factor measurement model was developed (Figure 2). All fivefirst-order factors strongly and significantly loaded on the second-order factor (.0.624).The fit indices confirmed a reasonable model fit (x 2(130) ¼ 414.957; x 2/df ¼ 3.192;

Factor and item Loading CR AVE

Access convenienceCould shop anytime I wanted 0.729 0.725 0.469The web site is always accessible 0.695Could order products wherever I am 0.627Search convenienceUser-friendly web site for making purchases 0.756 0.832 0.553Easy to understand and navigate web site 0.716Find desired products quickly 0.739Product classification is easy to follow 0.763Evaluation convenienceProvides product specifics 0.724 0.764 0.519Sufficient information to identify different products 0.742Uses both text and graphics of product information 0.694Transaction convenienceSimple and convenient online payment 0.848 0.784 0.551Flexible payment methods 0.663Without difficulty to complete my purchases 0.703Possession/post-purchase convenienceUndamaged delivered goods 0.680 0.841 0.518Receive all the items I ordered 0.668Timely product delivery 0.589Prices are identical to those on the order form 0.829Easy to return unwanted items 0.805

Notes: Model fit indices: x 2(125) ¼ 351.150; x 2/df ¼ 2.809; p , 0.001; RMR ¼ 0.032; GFI ¼ 0.910;IFI ¼ 0.924; CFI ¼ 0.923; RMSEA ¼ 0.066; CR – component reliability; AVE – average varianceextracted; n ¼ 413

Table V.Confirmatory factoranalysis

Figure 1.The first-ordermeasurement model

F1 F2 F3 F4 F5

Notes: Model fit: c2 (160) = 437.385, c2/df =2.734, p < 0.001, RMR = 0.035,GFI = 0.903, IFI = 0.914, CFI = 0.913, RMSEA = 0.065; F1 – access convenience,F2 – search convenience, F3 – evaluation convenience, F4 – transaction convenience,F5 – possession/post-purchase convenience; n = 413

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p , 0.001; RMR ¼ 0.043; GFI ¼ 0.893; IFI ¼ 0.904; CFI ¼ 0.903; RMSEA ¼ 0.073).This result indicates that there exists a second-order factor of customer perceivedoverall online shopping convenience.

To test the efficacy of the second-order model in comparison with the first-ordermodel, we employed the target coefficient (T-coefficient), which was developed by Marshand Hocevar (1985) and is commonly adopted by other studies on scale development(Segars and Grover, 1998; Smith et al., 2009). Following the formula proposed by Marshand Hocevar (1985), we computed the T-coefficient by dividing the adjusted x 2/df of thefirst-order model (2.809) by that of the second-order model (x 2/df ¼ 3.192). As a result,we obtained the T-coefficient of 0.857, which is in line with the values of T-coefficientreported in prior studies, ranging from 0.64 to 0.99 (Segars and Grover, 1998; Smith et al.,2009). Therefore, it can be interpreted that the second-order measurement modelrepresents the covariation among first-order factors in a more parsimonious way, thusleading support to the efficacy of the second-order measurement model.

Reliability and validity testsThe composite reliabilities of all the factors derived exceeded the 0.7 benchmark,ranging from 0.725 to 0.841 (Table V) and demonstrating adequate reliabilities (Fornelland Larcker, 1981). We then assessed convergent, discriminant, and nomologicalvalidity of the instrument. First, convergent validity is an indication of the extent towhich assessment measures correlate with other measures that it should be related to.We examined this validity by calculating the average variance extracted (AVE).As shown in Table V, the AVE of each measure in this study extracted more than50 percent of variance except that of the access convenience measure, which is 0.469,slightly lower than 0.5. Moreover, in the second-order measurement model, all fivefirst-order factors loaded significantly on the second-order factor, with thestandardized loadings equal to or larger than 0.624 (Figure 2). Thus, the convergentvalidity of the constructs was deemed acceptable.

Figure 2.The second-order

measurement model

F3

F2

F4

F1

F5

0.663***

0.814***

0.702***

0.637***

0.624***

OverallConvenience

Notes: Significant at: ***p < 0.001; model fit: c2 (130) = 414.957,c2/df =3.192, p < 0.001, RMR = 0.043, GFI = 0.893, IFI = 0.904,CFI = 0.903, RMSEA = 0.073; F1 – access convenience,F2 – search convenience, F3 – evaluation convenience,F4 – transaction convenience, F5 – possession/post-purchaseconvenience; n = 413


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Second, discriminant validity of the measures was assessed in two ways. First, allthe cross-construct correlation coefficients were significantly ( p , 0.001) less than1.0; second, the correlation coefficients of the constructs were less than the square rootof AVE (Fornell and Larcker, 1981). These results confirmed that the discriminantvalidity of the measures was evidenced. Table VI lists the means, standard deviation ofeach construct, correlations among the constructs, and the square root of AVE.

Finally, the nomological validity of the online shopping convenience scale wasassessed to verify that the online shopping convenience construct linked properly toother theoretical constructs as expected.

We investigated the relationship of online shopping convenience with behavioralintentions of online purchasing. Prior research has identified a positive link betweenservice convenience and behavioral intentions (Seiders et al., 2007). Behavioralintentions were measured by three items in this study:

(1) I will continue to shop online at this retailer.

(2) I encourage others to shop online at this retailer.

(3) I will use this retailer web site more often for online purchases.

Therefore, we tested a second-order nomological model that linked customers’ perceivedoverall online shopping convenience to their behavioral intentions. The structuralmodel demonstrated a good model fit (x 2(183) ¼ 527.330; x 2/df ¼ 2.882; p , 0.001;RMR ¼ 0.043; GFI ¼ 0.884; IFI ¼ 0.903; CFI ¼ 0.902; RMSEA ¼ 0.068). The testresults confirmed that customers’ perceived overall online shopping convenience hada significant and positive effect on their behavioral intentions (parameter estimate:0.670), providing support for the nomological validity of the scale. Furthermore,a five-factor nomological model was created as a rival model to test the relationshipbetween the five-factor model of online shopping convenience and behavioral intentions.The rival model shows that the standarlized coefficients of three out of five factorsare significant. Specifically, search, transaction, and possession/post-purchaseconvenience have positive relationships with behavioral intentions (Table VII).

DiscussionTheoretical implicationsCustomer perceived online shopping convenience is one of the crucial determinants ofsuccess of online businesses. Our extensive literature review revealed an important yetunanswered research gap that calls for an in-depth, systematic investigation of the key

Variable Mean SD 1 2 3 4 5 6

1. Access convenience 3.706 0.704 0.6852. Search convenience 3.617 0.683 0.492 0.7443. Evaluation convenience 3.525 0.729 0.509 0.421 0.7204. Transaction convenience 3.692 0.595 0.536 0.443 0.459 0.7415. Possession/post-purchase convenience 3.517 0.614 0.517 0.428 0.443 0.466 0.7216. Behavioral intentions 3.460 0.661 0.517 0.427 0.442 0.466 0.450 0.761

Notes: All the cross-construct correlation coefficients were statistically significant ( p , 0.001);SD – standard deviation; the square root of AVE is shown in the diagram; n ¼ 413

Table VI.Correlations forsecond-order onlineshopping conveniencefactor andbehavioral intentions

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dimensions of online shopping convenience as perceived by online customers. This studyempirically examined the construct of online shopping convenience in the contextof business-to-consumer e-commerce and focused on online service transformationprocesses through which online shoppers should undertake activities required topurchase products or services online, and, in turn, developed a rigorous measurementinstrument of online shopping convenience. The five salient dimensions derived are:access, search, evaluation, transaction, and possession/post-purchase convenience.Evidence indicates that each of the five identified dimensions has a significant andpositive effect on the overall levels of customers’ perceived online shopping convenience.

Theoretically, the five dimensions and their related items developed in this studycomprise a validated scale of web-based service convenience with only 18 scale items.These dimensions and items can serve as building blocks for further studies incustomer relationship management in e-commerce.

Unique online shopping convenience dimensions and related itemsComparing the traditional service convenience dimensions identified by Seiders et al.(2007) with this study, it is interesting to note that not only are those dimensionsdifferent, but the items differ as well. The scale developed by this study embodiesunique characteristics related to the e-commerce setting. Among Seiders et al. (2007)SERVCON’s five service convenience dimensions, namely decision, access,benefit, transaction, and post-benefit convenience, are considered important byoffline shoppers. For example, the traditional dimension of “decision convenience”,referring to the convenience of making a quick decision on where to visit and find desiredproducts, becomes the primary concern for offline shoppers, but this dimension can beregarded as almost inapplicable to the e-commerce setting (Beauchamp and Ponder,2010). Considering the substantial time and effort costs associated with visitingphysical stores prior to actual service exchange in comparison with browsing virtual

Standarlized coefficient t-value

Second-order factor modelOverall convenience ! behavioral intentions 0.670*** 8.031Overall convenience ! access convenience 0.771*** 7.847Overall convenience ! search convenience 0.638*** 7.202Overall convenience ! evaluation convenience 0.660*** 7.179Overall convenience ! transaction convenience 0.695*** 8.562Overall convenience ! possession/post-purchase convenience 0.671*** ax 2(183) ¼ 527.330; x 2/df ¼ 2.882; p , 0.001; RMR ¼ 0.043; GFI ¼ 0.884; IFI ¼ 0.903; CFI ¼ 0.902;RMSEA ¼ 0.068Rival model: five-factor modelAccess convenience ! behavioral intentions 0.113 1.252Search convenience ! behavioral intentions 0.161* 2.098Evaluation convenience ! behavioral intentions 0.065 0.769Transaction convenience ! behavioral intentions 0.262*** 3.307Possession/post-purchase convenience ! behavioral intentions 0.202** 2.669x 2(174) ¼ 454.815; x 2/df ¼ 2.614; p , 0.001; RMR ¼ 0.032; GFI ¼ 0.903; IFI ¼ 0.921; CFI ¼ 0.920;RMSEA ¼ 0.063

Notes: Significant at: *p , 0.05, **p , 0.01 and ***p , 0.001; a – denoted fixed parameterTable VII.

Structure models


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stores online, the availability and quality of information about the service provider andits competitors would greatly affect the level of customer perceived decision conveniencein offline shopping, but not in the case of online shopping. Even though twodimensions – access and transaction convenience – are considered important by bothoffline and online shoppers, the contents of the two dimensions are totally changed inthe two settings. Access convenience under traditional service relates to parking,location and opening hours, while online access convenience focuses on accessible website and unlimited access to shopping. Offline transaction convenience means thatthere is no need to wait for a long queue, and that, on the contrary, it is quick tocomplete purchasing and to pay, while online transaction convenience is associated withsimple and flexible payment methods. Moreover, our study identified three newconvenience dimensions, namely search, evaluation, and possession, unique to thee-commerce environment.

Access convenience. This dimension has turned out to be the foremost driver ofoverall online shopping convenience (Figure 2). Online consumers have the advantageof shopping at any time and are able to make multiple economies of time. They can alsopurchase products from such locations as home and office, rather than at physicalstores. These two types of flexibility – time and place – in turn provide psychologicalbenefits by avoiding crowds, reducing waiting time, and expending less effort intraveling to physical stores. Consumers enjoy the benefits of accessibility to products,brands, and stores that are not available in the location where they reside or work.

Search convenience. Theoretically, online customers can research products andcompare costs without physically visiting multiple locations to find their desiredproducts. Our study, however, revealed that consumers regard search inconvenience asa major obstacle to convenient and efficient online shopping. All the potential issuesassociated with product search over the internet can be grouped into four majorcategories:

(1) download speed;

(2) web site design;

(3) search function; and

(4) product classification.

Evaluation convenience. Evaluation convenience is associated with the availability ofdetailed yet easy-to-understand product descriptions by employing variouspresentation features, such as text, graphics, and video, on the web site. In recentyears, the overwhelming selection of products and detailed information that isaccessible, at just one click of the mouse, tend to make online shoppers more sensitivethan ever before to “evaluation convenience”. Thus, offering standardized onlineproducts and branded products, such as CDs, books, canned food, and pet food, wouldhelp consumers make easy evaluations because of “quality parity”. In addition, manyshopping sites have already established a customer review system, allowing newvisitors to read other customers’ comments/reviews about their product experiencebefore ordering. Such a peer evaluation system has proven to be very effective in savingconsumers’ evaluation time and efforts.

Transaction convenience. Although there is no queue in online shopping, the onlinecheck-out process is, by no means, simple and easy to follow. Simple and convenient

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online payment methods are essential. Complicated payment methods often preventonline shoppers from completing their purchasing process at the last minute.

Possession/post-purchase convenience. This dimension is concerned with consumers’perceptions of time and effort expenditures to possess what they wish and toexperience the benefits thereof. Shopping online releases shoppers’ burden of travelingto and from physical stores and thus customers prefer to purchase online heavy goodsand staples in large quantity to avoid dealing with the actual physical burden.

It should be also noted that our EFA and CFA yielded a composite construct ofpossession/post-purchase convenience consisting of four items measuring possessionconvenience and one item, “easy to return unwanted products”, assessing post-purchaseconvenience. This result implies that the item related to product returns, in terms of itsmeanings, might be more associated with the items of possession convenience, ratherthan with the other items under post-purchase convenience.

Managerial implicationsWith advancement of the internet, web, and mobile technologies, online customers cangain unlimited access to the information they require and enjoy a wider range ofchoices in selecting products and services with highly competitive prices. Therefore,sustaining a high level of online shopping convenience, in addition to offeringcompetitive prices, has increasingly become a key driving force for online retailers, withthe aim of enhancing customer loyalty. In this sense, the online shopping conveniencemeasurement instrument developed and validated in this study can be utilized as animportant diagnostic tool for online retailers to understand what conveniencedimensions and related features their customers value most, ascertain areas forimprovement, and implement effective solutions.

Our findings provide an important starting point to conduct effective onlineshopping convenience management. For example, as mentioned earlier, theaccessibility of web sites is considered as the most important factor in determiningconsumer perceived online shopping convenience. Accessing an online store from avariety of venues is essential with the rapid development of social media such asFacebook, MySpace, and Twitter, along with search engines.

Furthermore, our results suggest that online shopping convenience positivelycorrelates with behavioral intentions. Specifically, the more convenience that isperceived on searching, transaction and possession/post-purchase, the greater is thepossibility for repurchasing and recommendation by the customer. To expand a loyalcustomer base in rival-driven online retailing, online retailers need to consider how toimprove on those three aspects.

First, searching an appropriate product on a web site is often time-consuming evenwhen customers know specifically what they want. Customers demand user-friendlyweb sites to navigate since they often lack assistance from salespersons and are veryreluctant to call online help. A user-friendly web site design is essential for customers, ingeneral, and for those who have limited computer and internet knowledge, in particular.Some of our interviewees suggest that the layout of the web site should be the same as orsimilar to that of the physical store and that a visualized map of the store should beposted on the web site. It is also recommended that online retail managers exertconcerted efforts to enhance the overall level of online shopping convenience byadopting an intuitive sorting and classification scheme. Three interviewees complained


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that they were baffled by the difficulties they encountered in locating regular,commodity-type products because of unfamiliar or complicated sorting methods. In thissense, adopting an intuitive sorting and classification scheme can minimize consumers’search efforts.

Second, simple and flexible payment methods, provided by the online retailer candramatically improve consumer perceived online shopping convenience. Whileshoppers can benefit from online shopping by avoiding long customer queues topay, they may encounter another type of waiting, i.e. slow download speed of web sitesfor payment. Customers tend to feel frustrated and may even abandon the entirepurchasing process when they have to wait an inordinately long time for onlinepayment, even worse they never again return to the same online retailer. Paymentspeed is dramatically affected by transaction design and internet connection functions.While a pure online retailer can save costs in terms of rent and labor, being a hybridretailer employing both online and offline channels entails several significant benefitsfor consumer convenience. Hybrid retailers have the advantage of offering flexibilityof payment methods from which customers can select their preferred means, thusreducing consumers’ perceived expenditures of time and effort to complete atransaction. In addition, consumers can find product information from the retailers’web sites, but can actually buy from their physical stores after having viewed the realproducts there.

Third, online retailers should monitor their delivery process and return goodsservice. The delivery service to customers is inherently dynamic in nature as itembodies customers’ perceptions of online shopping convenience. However, it shouldbe noted that such benefits of possession/post-purchase convenience also create, asby-products, new types of inconvenience in obtaining ordered products, includingfailure of on-time delivery, uncertainty of waiting time for delivery, and immobilitycaused by staying home while waiting for the deliveryman to show up. Additionalinconvenience involves the risk of incomplete orders, damaged goods, unfriendlyattitudes of the delivery person, and difficulty in returning unwanted products.Moreover, the unavailability of ordered products has become an important issue thatgreatly affects customer perceived online shopping convenience, as online retailerstry to minimize storage costs. Five participants from our focus group intervieweesmentioned that they had encountered such inconvenience caused by out-of-stockproducts and suggested that this problem could be somewhat eased by providingcustomers with updated information regarding product inventory positions throughthe web site.

Online retailers should take steps to identify existing gaps between serviceperformance and customer expectations. Customer expectations of convenience haveincreased in accord with service innovations introduced by web managers andmarketers. Hence, constant monitoring of consumers’ perceptions and expectations is aprerequisite for achieving continuous improvement in rendering highly convenientonline service.

Limitations and future research directionsSeveral methodological issues can be further improved. First, the number ofparticipants in each focus group in this study is deemed relatively small. Increasing the

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number of interviewees might have resulted in generating more diversified perceptionsof and in-depth insights into online shopping convenience.

Next, although we divided our collected surveys into two sample datasets andutilized one of them for running EFA and the other for CFA, it would have been ideal toconduct CFA using a newly collected set of data to validate the measures previouslygenerated by EFA.

Finally, the construct of “access convenience” has an AVE of slightly lower than 0.5.Although we kept this dimension for theoretical reasons in our model, the scale itemspertaining to the dimension need to be further modified or changed to improveconvergence validation.

Two more caveats are worth mentioning for directing future research. First, ourstudy only selected one “brick-and-click” retailer, so further research may embracediversified company types and service industries to enhance the generality of ourresearch findings. Second, as internet, web, and mobile technologies have evolved, theirimpacts on customers’ experience and perceptions of online shopping conveniencehave also changed over time. Furthermore, increasingly popular social media havegreatly influenced consumers’ online shopping behavior. As such, it is recommendedthat future research investigate the evolutionary processes of changing customerperceptions of online shopping convenience by employing a longitudinal researchmethod.

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Appendix 1. Major issues addressed during focus group interviews

(1) In general, what drives you to make purchasing through the internet rather thanshopping in physical stores?

(2) What does “convenience services” derived from online shopping mean to you?

(3) What specific criteria do you use in assessing how convenient online shopping is?

(4) Consider the last few purchases you have made through the web. Were there anyinconvenient aspects that you found at those web sites in terms of the following areas?What are they?

(a) accessibility;

(b) product search;

(c) product availability and variety;

(d) delivery;

(e) after-sales services;

(f) technical issue (e.g. internet knowledge);

(g) web design (e.g. language, easy to flow); and

(h) customer services.

(5) What are major sources of inconvenience in purchasing from web sites? Can you providespecific examples?

(6) What are major obstacles that keep you from purchasing more frequently through theinternet than you currently do? What are the advantages and drawbacks of makingpurchases through the internet rather than shopping in physical stores?

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Appendix 2. Items in the survey questionnaireThe final survey questionnaire consists of 22 items measuring online shopping convenience andthree items measuring behavioral intentions. All items are measured on a five-point Likert scaleanchored at strongly disagree (1) and strongly agree (5).

Online shopping convenience

(1) Access convenience:. I could shop anytime I wanted.. The web site is always accessible.. I could order products wherever I am.

(2) Search convenience:. The web site is user-friendly for making purchases.. The web site is easy to understand and navigate.. The web site is very attractive *.. I am able to find desired products quickly.. The product classification is intuitive and easy to follow.. I am able to find the same product using a variety of online search options *.

(3) Evaluation convenience:. The web site provides product specifics, such as volume, weight, and size.. The web site provides sufficient information so that I can identify different products

within the same category.. The web site uses both text and graphics to provide in-depth product information.

(4) Transaction convenience:. Online payment is simple and convenient.. Payment methods are flexible.. I am able to complete my purchases without difficulty.

(5) Possession convenience:. Delivered goods are undamaged.. I received all the items I ordered.. Product delivery is timely.. The prices of delivered goods are identical to those on the order form.

(6) Post-purchase convenience:. It takes little effort to return some unwanted items.. The web site does not misuse my personal information *.. I feel safe in my transactions *.

Behavioral intentions. I will continue to shop online at this retailer.. I encourage others to shop online at this retailer.. I will use this retailer web site more often for online purchases.

Note: *Items were deleted from subsequent analyses.


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About the authorsLing (Alice) Jiang is an Assistant Professor in the Faculty of Management and Administration atMacau University of Science and Technology. She has published in the Journal of BusinessResearch and Industrial Marketing Management, among others.

Zhilin Yang is Professor of Marketing at the City University of Hong Kong. He has publishedin the Journal of Marketing, Journal of Marketing Research and Journal of International BusinessStudies, among others. Zhilin Yang is the corresponding author and can be contacted at:[email protected]

Minjoon Jun is Professor of Operation Management at New Mexico State University. He holdsa PhD in Operations Management from the Georgia State University. He has published in theJournal of Operations Management and Journal of Supply Chain Management, among others.

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