A contextual perspective on consumers' perceived usefulness: The case of mobile online shopping

Journal of Retailing and Consumer Services 38 (2017) 22–33

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Journal of Retailing and Consumer Services journal homepage: www.elsevier.com/locate/jretconser

A contextual perspective on consumers' perceived usefulness: The case of mobile online shopping

MARK

Stefanie Sohn University of Technology Braunschweig, Abt-Jerusalem-Straße 4, D-38106 Braunschweig, Germany

A R T I C L E I N F O

A B S T R A C T

Keywords: Mobile commerce Mobile online shopping touchpoints Perceived usefulness

This research aims to study the origins of consumers' usefulness perceptions through the example of mobile online shopping adoption in Europe. The results of an empirical study, which is grounded in technology acceptance theory, reveal the pivotal role of consumers' beliefs about the quality of mobile online stores in the formation of usefulness perceptions prior to adoption. While this study identifies that consumers form their usefulness evaluations depending on the respective shopping tasks, the results of a moderation analysis yield usefulness predictors that differ in relevance across product categories and shopping touchpoints. This contextual perspective has implications for both adoption and (online) channel research. It also helps managers to identify starting points on how to promote (mobile) online shopping adoption.

1. Introduction 1.1. The purpose of this research This research aims to study the origins of consumers’ usefulness perceptions by examining mobile online shopping adoption processes in Europe. In harmony with technology acceptance theory (e.g., Davis, 1989), extant research illustrates the relevance of usefulness perceptions (i.e., the extent to which one believes that using a technology will enhance his/her job performance) in predicting consumers’ adoption behavior of technologies (Venkatesh and Davis, 2000). However, empirical knowledge regarding the antecedents of perceived usefulness is limited and inconsistent (Benbasat and Barki, 2007), especially in the context of mobile online shopping (Groß, 2015). Moreover, the heterogeneity underlying the formation of usefulness perceptions requires in-depth research (Venkatesh et al., 2012). The primary research objective is to develop a model of the antecedents to consumers' usefulness perceptions. These origins are examined in a pre-adoption stage, and usefulness evaluations for different online shopping tasks are distinguished. A secondary research objective is to test the developed model on the antecedents of perceived usefulness across varying contexts. This research studies these objectives at the example of mobile online shopping in Europe. The justification of this study is possible from current market developments and academic findings. First, consumers' perceived usefulness plays a pivotal role in the formation of consumers' usage intentions towards, and usage of, mobile online shopping (e.g., Groß, 2014). Second, during the second quarter of 2016,

E-mail address: [email protected]. http://dx.doi.org/10.1016/j.jretconser.2017.05.002 Received 29 January 2017; Received in revised form 20 April 2017; Accepted 10 May 2017 0969-6989/ © 2017 Elsevier Ltd. All rights reserved.

48% of worldwide electronic commerce (e-commerce) transactions have been realized through mobile devices. In some countries (e.g., Japan) the mobile share of e-commerce transactions already exceeds the desktop share (Criteo, 2016). In spite of tremendous growth in the European smartphone-based Internet use (comScore, 2015), the mobile share of e-commerce transactions here remains below the global average (Criteo, 2015)—requiring that the crucial regional antecedents of mobile online shopping adoption be elucidated. Third, current research emphasizes that mobile device-based online purchases could increase consumers’ overall online purchases (Huang et al., 2016; Wang et al., 2015); however, little knowledge exists on mobile online shopping in general (Hew, 2017), and more specifically on consumer adoption thereof. 1.2. The contribution of this research This research yields theoretical and managerial contributions. The theoretical contribution relates to the understanding of consumer adoption determinants and the origins of usefulness perceptions in and beyond the field of mobile online shopping research. Current research increasingly considers extending the core assumptions of the technology acceptance model (TAM) (Davis, 1989) by including external factors explaining behavioral beliefs such as perceived usefulness (Table 1). However, existing knowledge on the determinants of perceived usefulness suffers from several shortcomings. On the one hand, scholars largely neglect to consider the potential heterogeneity underlying the formation of these behavioral beliefs. Consumer characteristics are often integrated to elucidate the origins of usefulness

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Table 1 Current research insights on perceived usefulness (2015–2017). Context of research

Data collection

Antecedents to perceived usefulness

Nature of usefulness perceptions

Moderators

Hubert et al. (2017) Mobile commerce Post-adoption perspective

United Kingdom, N=410 quota sample with prior experiences

Instant connectivity (+), contextual value (+), hedonic motivation (ns), habit (+), financial risk (ns), performance risk (+), security risk (ns)

Smartphone-based online shopping for different shopping tasks

Mobile shopping application type

Khalilzadeh et al. (2017) Mobile services Pre-adoption perspective

USA, N=412 convenience sample with prior experiences

Social influence (+) Trust in service provider (+) Perceived effort expectancy (+) Perceived risk (-)

Using mobile payment service in restaurants

Gender, age, previous, experience

Natarajan et al. (2017) Mobile commerce Post-adoption perspective

India, N=675 quota sample with prior experiences

Perceived enjoyment (+) Perceived ease of use (+)

Using mobile shopping applications

–

Yu et al. (2017) Mobile technology Post-adoption perspective

Korea, N=450 quota sample with prior experiences

Functionality (+) Content (+) Brand name (+) Price (ns)

Using mobile tablets

–

N=262 convenience sample

Perceived ease of use (+) Perceived ubiquity (+)

Using mobile cloud storage services

–

J.-J. Hew et al. (2016) Mobile commerce Post-adoption perspective

Malaysia, N=208 convenience sample with prior experiences

Confirmation on expectations (+) Concern for social media information privacy (+)

Using mobile social commerce

–

T.-S. Hew et al. (2016) Mobile services Pre-adoption perspective

Malaysia, N=463 convenience sample with prior experiences

Trust in mobile transactions (+) perceived financial cost (-)

Using mobile entertainment

–

Korea, N=357 convenience sample

Argument quality (+) Source credibility (+)

Using mobile shopping website for purchasing

Involvement

Koç et al. (2016) Mobile technology Post-adoption perspective

Turkey, N=227 convenience sample with prior experiences

Context (+) Perceived ease of use (+)

Using education management information system

–

Matute et al. (2016) Online commerce Post-adoption perspective

Spain, N=252 convenience sample with prior experiences

Quantity of customer reviews (+) Credibility of customer reviews (+) Quality of customer reviews (+)

Using website for information search and for purchasing

–

Wang (2016) Online commerce Post-adoption perspective

Taiwan, N=658 convenience sample with prior experiences

Information quality (+) System quality (+)

Using online shopping website

Utilitarian orientation, gender

Yen and Wu (2016) Mobile services Post-adoption perspective

Taiwan, N=368 convenience sample with prior experiences

Perceived mobility (+) Personal habit (+) Perceived ease of use (+)

Using mobile financial services in performing certain financial activities

Gender

Interaction quality (nr) Environment quality (nr) Outcome quality (nr)

–

–

Perceived enjoyment (+)

Using mobile commerce during the purchase of tickets

Mobile commerce experience

Subjective norm (ns), image (+) output quality (+) result demonstrability (+)

Using mobile commerce

Experience

Personal innovativeness (+)

–

–

Arpaci (2016) Mobile services Pre-adoption perspective

Kim et al. (2016) Mobile commerce Post-adoption perspective

Abbas and Hamdy (2015) Kuwait, N=512 Mobile services random sample with Post-adoption prior experiences perspective Agrebi and Jallais (2015) Mobile commerce Post-adoption perspective

France, N=300 convenience sample

Faqih and Jaradat (2015) Mobile commerce Jordan, N=425 Pre-adoption convenience sample perspective Kitchen et al. (2015) Mobile services Pre-adoption perspective

Malaysia, N=530 convenience sample

(continued on next page)

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Table 1 (continued) Context of research

Data collection

Antecedents to perceived usefulness

Nature of usefulness perceptions

Moderators

Rivera et al. (2015) Mobile services Post-adoption perspective

USA, N=914 convenience sample with prior experiences

Technology experience (+)

Using mobile apps during travelling

–

Zhou et al. (2015) Mobile services Post-adoption perspective

China, N=223 convenience sample with prior experiences

Referent network size (+) Perceived complementarity (+)

Using a mobile IM

–

Notes: (+) positive influence, (-) negative influence, (ns) non-significant, (nr) non-reported.

The results of this study suggest that usefulness perceptions have their origin in consumers’ beliefs about the quality of mobile online stores. The role of individual quality dimensions in the formation of usefulness perceptions depends upon the product category of interest and upon the respective mobile online shopping touchpoints. Moreover, this study provides insights into the relative importance of quality beliefs in the formation of usefulness perceptions across different shopping tasks.

perceptions (e.g., Khalilzadeh et al., 2017); however, contextual characteristics and their interplay with the determinants of usefulness perceptions have been widely ignored. Hubert et al. (2017) were the first to specify this role by considering the types of mobile shopping applications, but found limited empirical support for the relevance of their selection of contextual characteristics. On the other hand, heterogeneity in the formation of usefulness perceptions might also depend on the nature of specific tasks to which the usefulness evaluations refer. Prior research either captures usefulness perceptions across shopping tasks (e.g., Hubert et al., 2017) or neglects to consider specific shopping tasks (e.g., Faqih and Jaradat, 2015). This study is the first to explicitly distinguish between the shopping tasks to which these evaluations refer. As such, it provides an in-depth understanding of the formation of these behavioral beliefs. This research broadens the nuanced understanding of consumers’ usage of electronic shopping channels. While empirical evidence indicates that device-specific qualities impact how humans behave and form evaluative judgments (e.g., Ghose et al., 2013), these device particularities are largely neglected when online shopping behavior is researched (e.g., Matute et al., 2016). While mobile commerce—and mobile online shopping, in particular—exhibit several sub-forms that differ in the drivers of consumer evaluations (Sohn et al., 2017), extant research largely neglects to address this underlying fragmentation (Faqih and Jaradat, 2015; Natarajan et al., 2017; Gupta and Arora, 2017). In addition, this study extends existing knowledge on mobile shopping channels. Despite the pivotal role of usefulness perceptions regarding the prediction of behavioral intentions or behavior in the context of mobile shopping (Hubert et al., 2017), current research either neglects to consider this construct (San-Martín et al., 2015) or replicates existing knowledge (Agrebi and Jallais, 2015). Research on the antecedents to usefulness perceptions is scarce in this area. The works of Kim et al. (2016) and Hubert et al. (2017) represent two exceptions. However, their contributions neglect on the one hand to the pre-usage perspective on mobile shopping and fail on the other hand to specify usefulness perceptions with regard to shopping tasks. For managers, an understanding of the factors that affect consumer adoption of novel retail channels permit active management of consumer channel choices. In particular, the understanding of the drivers of use intentions can aid the design of appropriate and context-dependent interventions. Proactively shaping the origins of behavioral beliefs can help promote the adoption of mobile online shopping and ultimately the sales of retailers.

2. Conceptual framework and hypotheses development 2.1. Perceived usefulness Perceived usefulness is a core construct of the TAM (Davis, 1989). The latter provides insights into the causal interplay between behavioral beliefs (i.e., perceived usefulness and perceived ease of use), attitudes, intentions, and behavior, and posits that human behavior can be explained by those two beliefs. Empirical studies across various technological applications demonstrate the predictive power of behavioral beliefs, and specifically of usefulness perceptions (Blut et al., 2016; Ovčjak et al., 2015). Research indicates that usefulness perceptions—also called perceptions of performance expectancy (Ovčjak et al., 2015)—refer to “the extent to which a person believes that using particular technology will enhance his/her job performance” (Davis, 1989, p. 320). Here, usefulness perceptions describe the degree to which consumers believe that using mobile online stores enhances their shopping task performance. Existing research related to perceived usefulness either refer to single shopping acts (e.g., Kim et al., 2016), mix different shopping acts (e.g., Matute et al., 2016), or fail to specify the nature of the shopping task (e.g., Natarajan et al., 2017; Table 1). Mobile online stores theoretically support multiple shopping acts (e.g., information search, buying). Since humans connect their behavioral beliefs with specific behavior (Fishbein and Ajzen, 1975), this study considers different shopping acts when specifying usefulness perceptions. In particular, it elucidates information gathering about an offering and performing a purchase. The goal-directed nature of information search and purchasing correlates with the typically short interactive use sessions of smartphones (Cliquet et al., 2014). The perceived usefulness of mobile online stores for these purposes indicates the degree of an individual’s belief that a mobile online store would enhance information search/purchasing performance. Individual shopping acts are related to one another (Darden and Dorsch, 1990); each act comprises specific goals and interrelated steps. However, shopping acts are subject to hierarchical processes to achieve one superior goal (e.g., shopping) (Lichtenstein and Brewer, 1980). Naturally, consumers progress through a pre-purchase, a purchase, and a post-purchase stage (Frambach et al., 2007). For instance, the typical pre-purchase information gathering precedes the act of purchasing. To avoid mental inconsistencies, humans attempt to cognitively balance elements that are part of a superior system (Heider, 1958). Gensler et al. (2012) apply this idea to channel choices and argue that

1.3. An overview of this research paper The remainder of this research paper is organized as follows. Section 2 contains the conceptual framework as well as theoretical explanation of the hypotheses considering current research findings. The employed methods are explained in Section 3, and the results of the study are presented and discussed in Section 4. Section 5 concludes the document. 24

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stimulus from related stimuli (Lynch et al., 1991). Hence, in evaluating mobile online store quality, consumers may bundle prior computeraccessible online store experiences and/or non-commercial mobile websites. As mobile online stores are required for mobile online shopping, humans may associate their behavioral beliefs (e.g., perceived usefulness of mobile online store for purchasing) with cognitive beliefs of an object (e.g., beliefs about the quality of a mobile online store) as substantial in performing the behavior in question. Humans strive to achieve consistency of their beliefs (O'Keefe, 2002). Empirical evidence indicates that beliefs about the quality of a technology contribute to consistent behavioral beliefs—perceived quality has been found to positively affect perceived usefulness (Shih, 2004). Hence, expected quality informs the decision of whether to accept or avoid usage of a technology (Shneiderman and Plaisant, 2010). Beliefs about a mobile online store’s quality refer to perceptions about specific store elements (Al-Qeisi et al., 2014). In harmony with the NetQual scale (Bressolles, 2006), perceived security, perceived information, perceived aesthetic quality, and perceived technical quality play a pivotal role in perceptions of e-service quality. Similar dimensions have been identified with regard to perceptions of mobile interface quality (Gao et al., 2015; Hoehle and Venkatesh, 2015). Hence, this study focuses on individuals’ beliefs about the quality dimensions outlined above. While aesthetic quality refers to how organized and attractive a mobile online store is expected to be (Cai and Xu, 2011), perceived technical quality captures the ease of navigation, speed of loading information, and the undisturbed functionality of mobile online stores (Al-Qeisi et al., 2014). Information quality reflects individuals beliefs about the informativeness of mobile online stores, including the relevance, sufficiency, and timeliness of the presented content (Gao et al., 2015). Security quality reflects how individuals’ overall security is associated with mobile online stores and the use and protection of personal information (Parasuraman et al., 2005). To sum up, one might hypothesize:

spillover effects explain why consumers use one channel across different stages of the buying process. Accordingly, they argue “considering a channel in one stage of the stage for a particular product affects that channel’s utility and the likelihood of choosing that channel in another stage of the buying process” (Gensler et al., 2012, p. 992). To sum up, one might assume that behavioral beliefs about the information search significantly influence those about purchasing an offering: H1. An increase in the perceived usefulness of mobile online stores for information search will lead to an increase in the perceptions of usefulness of mobile online stores for purchasing. 2.2. Antecedents to perceived usefulness 2.2.1. Existing knowledge on the antecedents to perceived usefulness Due to the TAM’s parsimonious nature and its limited managerial guidance (e.g., Benbasat and Barki, 2007), scholars have attempted to broaden their view, predominantly by focusing on variables that explain behavioral beliefs. The extensions, TAM 2 (Venkatesh and Davis, 2000) and TAM 3 (Venkatesh and Bala, 2008), shed light on such variables. Venkatesh and Davis (2000) offer considerable insights into the potential origins of usefulness perceptions; two distinct theoretical processes—social influence and cognitive instrumental—are proposed to uncover these antecedents. They theorize that usefulness perceptions result on the one hand from subjective norms and image (i.e., the extent to which using a technology enhances one’s social status) through processes of internalization and identification. On the other hand, in light of the cognitive instrumental process perspective, usefulness perceptions have their origin in cognitive beliefs of job relevance (i.e., the extent to which an individual believes that the technology relates to the task), output quality (i.e., the degree to which an individual thinks that the technology performs the specific task well), and result demonstrability (i.e., the degree to which results of using a system are observable). Faqih and Jaradat (2015) recently analyzed the extensions of the TAM in the context of mobile commerce and found no empirical support for the effect of the social influence processes. Instead, other contributions attempt to extend the spectrum of repeatedly confirmed determinants of usefulness perceptions (Table 1). Kitchen et al. (2015) and Rivera et al. (2015), for instance, examine the role of consumer characteristics to predict usefulness perceptions but fail to provide insights into variables moderating the origins of usefulness perceptions. Some of the current publications address the role of quality perceptions in the formation of usefulness perceptions (Table 1). While prior research predominantly refers to output quality as the quality of the accomplished shopping task (e.g., quality of products/services) (Faqih and Jaradat, 2015), current contributions increasingly consider the output quality of the environment in which a shopping task is accomplished (e.g., online store) (Yu et al., 2017; Wang, 2016; Abbas and Hamdy, 2015). Research on mobile commerce has acknowledged the relevance of these output quality perceptions as predictors of usefulness perceptions (Kim et al., 2016). However, the focus is on single quality dimensions, resulting in incomplete insights (e.g., Wang, 2016). Moreover, prior studies present mixed results (Wang, 2016) or the findings have been insufficiently reported (Abbas and Hamdy, 2015).

H2. Perceived (a) technical quality, (b) information quality, (c) aesthetic quality, and (d) security quality of mobile online stores positively affect the perceived usefulness of mobile online stores for purchasing. H3. Perceived (a) technical quality, (b) information quality, (c) aesthetic quality, and (d) security quality of mobile online stores positively affect the perceived usefulness of mobile online stores for information search. 2.3. Variables moderating the antecedents to perceived usefulness Consumers’ usage and usage-related judgment development relies on individual and contextual variables. Technology acceptance theory demonstrates that technology experiences moderate the interrelationships between computer anxiety and perceived ease of use (Venkatesh and Bala, 2008). Examination of moderators in the context of mobile commerce predominantly focus on the role of consumer characteristics (e.g., Agrebi and Jallais, 2015; Kim et al., 2016). Hubert et al. (2017) are the first to consider the differing relevance of usefulness predictors across contexts. This research extends their view by emphasizing the role of the mobile touchpoint and product of interest (Fig. 1).

2.2.2. Analyzed antecedents to perceived usefulness in this research To broaden prior findings, this study analyzes the role of mobile online store quality in the formation of usefulness perceptions acknowledging a multi-dimensional perspective of quality perceptions. Cognitive beliefs (e.g., beliefs about the quality of mobile online stores) are naturally acquired through experiences (Duncan and Olshavsky, 1982). Information integration theory informs about this process of combining available information with beliefs about unknown objects (Anderson, 1991). Humans make inferences about an unknown

2.3.1. The role of the product category Wang et al. (2015) recently concluded that an online store’s product offering substantially determines mobile online shopping usage. Market analysts underline the fragmented adoption levels of mobile online shopping depending on the specific product category (Centre for Retail Research, 2016). Mechanisms behind the effect of product characteristics on mobile online shopping adoption remain unexplored; this research therefore addresses the role of the product category in the 25

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2.3.2. The role of the mobile online shopping touchpoint Mobile online stores are accessible through different touchpoints—most prominently mobile apps and browser-accessible mobile websites. Mobile apps, that are utilized via mobile interfaces, differ from fixed websites with respect to layout, content, and usability (Wagner, 2015). Mobile websites adapt and format the principal visual and content features of the fixed website for mobile use (Magrath and McCormick, 2013). Mobile websites are accessible through pre-installed browser on mobile devices, while mobile app use is associated with an initial investment of download and install time. Given the higher degree of adaptation of mobile apps to the physical constraints of mobile devices, one might conclude that mobile online shopping through apps is perceived as less effortful than through browsers (even when websites are optimized for mobile access) (Song et al., 2014). For a specific task, mobile shopping apps instead of optimized mobile shopping websites may be less time-consuming. Higher engagement in online store interaction requires high quality surroundings that compensate for effortful tasks (Cho, 2015); one can therefore assume that the relationship between the perceived quality of mobile online stores and usefulness perceptions vary for different touchpoints. A mobile browser, compared to app-based access, will strengthen this effect independent of the shopping task. To sum up:

Fig. 1. Conceptual model.

formation of usefulness perceptions. Prior online shopping research demonstrates that the determinants of consumer adoption vary for different product categories (Lian and Lin, 2008). Specifically, individuals form usefulness perceptions by comparing what an online store’s capabilities to what an online store needs to do to fulfill the respective shopping acts (Venkatesh and Davis, 2000). The product category determines the scope of shopping acts (Huang et al., 2009), which explains why the formation of usefulness perceptions might differ for different product categories in a specific shopping situation. Extant research classifies products into different categories to assess consumers’ responses according to category-specific characteristics. One widely accepted classification scheme distinguishes between search and experience products (Girard and Dion, 2010). While attributes of experience products are generally difficult to obtain and judge without direct experience and use before purchase, qualities of search goods are accessible without direct product contact. Especially with regard to online purchases, the quality of experience goods is more difficult to judge than the quality of search goods (Gupta et al., 2004). The level of perceived uncertainty and perceived costs/difficulty consumers encounter in pre-purchase product attribute assessment is therefore more pronounced when purchasing experience (e.g., wine) instead of search goods (e.g., books). High degrees of uncertainty lead to an extended in-depth search for information (Luo et al., 2012). Hence, Huang et al. (2009) provide empirical evidence that experience goods lead to a deeper online search than search goods. They further notice that the time spent per website augments when product uncertainty increases. Cho (2015) explains this behavior by the degree of product identifiability, which describes the extent to which product characteristics are identifiable online. Accordingly, the lower the identifiability, the more web interaction is required. The location of online information is mainly determined by the quality of retailers’ online stores; websites of high quality facilitate the search for information (Luo et al., 2012) and the identifiability of product characteristics (Cho, 2015). Given the differing nature of experience and search goods, and the associated need for pre-purchase information, one might assume that perceived quality impacts usefulness perceptions of mobile online stores more when shopping for experience than for search goods. Thus:

H5. The relationship between perceived mobile online store quality and perceived usefulness of mobile online stores: H5a. will be stronger for browser-based mobile online store access than for app-based mobile online store access for information search, and H5b. will be stronger for browser-based mobile online store access than for app-based mobile online store access for purchasing. 3. Methods 3.1. Sampling strategy and administration of survey Data was collected through a self-administered online questionnaire among smartphone users and online shoppers. The dominant role of smartphones for online shopping justifies the focus on this device category (Criteo, 2016). Smartphones create unique opportunities for online shopping through on-the-go online store access (Cliquet et al., 2014). A professional market research firm that follows branch-specific quality standards to overcome recruitment and conditioning bias (ESOMAR, 2016) collected the data using an online access panel during the summer of 2016. Quota sampling was used to reflect the distribution of smartphone users in Germany according to age, gender, education, and occupation. Despite the widespread use of mobile technologies across different social classes, few findings rely on representative samples (Table 1). Hence, the present study extends prior perspectives through varying sampling approaches. Germany was selected for data collection due to its well-progressed adoption of mobile online shopping. However, the mobile share in electronic transactions is still below the global average despite the large portion of German smartphone users (Criteo, 2016). The survey yielded 901 responses. Due to missing data and implausible answers, 789 of these responses were included in the final data analysis. Attendees were informed about the anonymity of the data collection process, and it was emphasized that there were neither right nor wrong answers. Screening questions were asked to identify the study population users with Internet access via smartphone, known mobile apps, and mobile websites. Quota sampling required that socio-demographic information be collected at the outset. Respondents next informed about their experiences and habits (e.g., smartphone use). One out of four mobile online shopping scenarios was assigned randomly at the outset, inspired by the scenario-based approach of Dabholkar and Bagozzi (2002). This ensured that all questions and

H4. The relationship between perceived mobile online store quality and perceived usefulness of mobile online stores: H4a. will be stronger for experience goods than for search goods for information search, and H4b. will be stronger for experience goods than for search goods for purchasing. 26

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quality dimensions and of usefulness. Questionnaire development and refinement involved several pre-tests. Potential respondents (N=10) and marketing experts (N=3), who are experienced mobile Internet users, evaluated the survey for readability, clarity, and applicability to the topic; the initial questionnaire items were modified accordingly (e.g., eliminating the ambiguity of some items). One common issue was the differentiation of the two usefulness measures; this was resolved by highlighting the respective shopping tasks (i.e., purchasing versus information search) to which the items refer. Afterwards, a convenience sample (N=259) was used to conduct an online pre-study, which yielded satisfactory reliability and validity measures.

items referred to a specific context. The four scenarios rely on a variation of products (i.e., clothes versus event tickets) and mobile shopping touchpoints (i.e., mobile app versus mobile-optimized website). Respondents were asked to imagine and then evaluate a situation in which a friend uses a smartphone-accessible online store through either a mobile app or a mobile-optimized website to purchase clothes or event tickets. While prior academic research emphasizes the relevance of these product categories in the context of mobile online shopping (Ko et al., 2009; Agrebi and Jallais, 2015), recent market developments confirm their pivotal role in mobile online shopping (comScore, 2016). Clothes differ from tickets regarding the need for physical inspection and the experience requirements (Girard and Dion, 2010), allowing for the testing of Hypothesis H4. Clothes represent an experience good and tickets a search good, according to the extensive product classification research of Girard and Dion (2010). Subsequent questions were on the correct understanding of the scenarios. Then, multi-item scales were used to assess the perceived usefulness of mobile online stores for information search, and respondents’ perceptions about the usefulness of mobile online stores for purchasing were clarified. Subsequent items captured individuals’ beliefs about the various quality dimensions.

4. Results and discussion 4.1. Respondents' characteristics The sample (Table 3) represents the distribution in terms of age, gender, education, and occupation of smartphone-based Internet users in Germany (Statistisches Bundesamt, 2014). Male respondents comprised 52.1%, and more than 74% were between 25 and 64 years old. The majority use Android-based smartphones, followed by Apple iOS-based smartphones. Mobile Internet access is used several times a day by 39.7% of respondents. Online smartphone purchasing has been done by 56.5% of respondents.

3.2. Measures and pre-studies The questionnaire to test the hypotheses was based on measures taken from extant literature adapted for this research context (Table 2). This study employed five-point Likert scales (1=strongly disagree, 5=strongly agree) to understand individuals’ perceptions of the various

4.2. Measurement assessment Models were validated through a covariance-based approach, based

Table 2 Questionnaire items. Constructs and sources/Employed items for data analysis

Aesthetic Quality (AQ) (Cai and Xu, 2011) Mobile online stores are visually appealing. The visual design of mobile online stores is attractive. The layout of mobile online stores is intuitive. The design of mobile online stores is harmonious.

Overall (N=789)

Group Clothes (N=395)

Group Tickets (N=394)

Group Apps (N=396)

Group Websites (N=393)

M=3.67 SD=.69

M=3.69 SD=.69

M=3.68 SD=.70

M=3.72 SD=.68

M=3.67 SD=.71

M=3.59 SD=1.10

M=3.99 SD=.70

M=3.97 SD=.73

M=3.93 SD=.69

M=3.19 SD=.98

M=3.19 SD=.97

M=3.19 SD=.99

M=3.19 SD=.98

M=3.20 SD=.99

M=3.74 SD=.76

M=3.71 SD=.75

M=3.76 SD=.78

M=3.75 SD=.74

M=3.73 SD=.79

M=3.57 SD=1.04

M=3.65 SD=1.05

M=3.54 SD=1.06

M=3.61 SD=1.07

M=3.65 SD=1.12

M=3.54 SD=1.08

Technical and Functional Quality (TQ) (Al-Qeisi et al., 2014; Fassnacht and Koese, 2006) Mobile online stores are easy to navigate. M=3.95 Mobile online stores are easy to use. SD=.71 Mobile online stores are always up and running. Security Quality (SQ) (Parasuraman et al., 2005) Mobile online stores protect information about my shopping behavior. Mobile online stores do not share my personal information with other sites. Mobile online stores are secure. Information Quality (IQ) (Gao et al., 2015) Mobile online stores provide me with information that is relevant to my needs. Mobile online stores provide me with sufficient information. Mobile online stores provide me with up-to-date information.

Perceived usefulness of mobile online stores for information search (PUINF) (Porter and Donthu, 2006) Using mobile online stores can make an information search on M=3.59 M=3.62 clothes/tickets easier. SD=1.06 SD=1.07 Using mobile online stores can make an information search on clothes/tickets more productive. Overall, using mobile online stores for information search on clothes/tickets is useful. Perceived usefulness of mobile online store for purchasing (PUPUR) (Porter and Donthu, 2006) Using mobile online stores can make purchasing clothes/tickets M=3.59 M=3.56 easier. SD=1.10 SD=1.13 Using mobile online stores can make purchasing clothes/ tickets more productive. Overall, using my smartphone for purchasing clothes/tickets is useful.

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Table 3 Demographics of respondents. Demographics

Overall (N=789)

Group Clothes (N=395)

Group Tickets (N=394)

Group Apps (N=396)

Group Websites (N=393)

Gender Male Female

437 (52.1%) 402 (47.9%)

202 (51.1%) 193 (48.9%)

204 (51.8%) 190 (48.2%)

204 (51.5%) 192 (48.5%)

202 (51.4%) 191 (48.6%)

Age 16–24 years 25–44 years 45–64 years 65 years and older

158 368 264 49

(18.8%) (43.9%) (31.5%) (5.8%)

72 (18.2%) 175 (44.3%) 121 (30.6%) 27 (6.8%)

70 (17.8%) 167 (42.4%) 134 (34.0%) 23 (5.8%)

76 (19.2%) 174 (43.9%) 125 (31.6%) 21 (5.3%)

66 (16.8%) 168 (42.7%) 130 (33.1%) 29 (7.4%)

Education Middle school or below High school, college Postgraduate

160 (19.1%) 479 (57.1%) 200 (23.8%)

75 (19.0%) 227 (57.5%) 93 (23.5%)

77 (19.5%) 228 (57.9%) 89 (22.6%)

77 (19.4%) 225 (56.8%) 94 (23.7%)

75 (19.1%) 230 (58.5%) 88 (22.4%)

Occupation Student Employee, official, freelancer Unemployed Pensioner, housewife/-husband

78 (9.3%) 633 (75.4%) 32 (3.8%) 96 (11.4%)

41 (10.4%) 289 (73.2%) 16 (4.1%) 49 (12.4%)

30 (7.6%) 299 (75.9%) 14 (3.6%) 51 (12.9%)

37 (9.3%) 295 (74.5%) 13 (3.3%) 51 (12.9%)

34 (8.7%) 293 (74.6%) 17 (4.3%) 49 (12.5%)

Smartphone type Android iOS Windows RIM OS Symbian others

600 (71.5%) 176 (21.0%) 45 (5.4%) 8 (1.0%) 3 (.4%) 7 (.8%)

289 (73.2%) 79 (20.0%) 21 (5.3%) 3 (.8%) 1 (.3%) 2 (.5%)

282 (71.6%) 78 (19.8%) 22 (5.6%) 5 (1.3%) 1 (.3%) 6 (1.5%)

272 (68.7%) 89 (22.5%) 23 (5.8%) 6 (1.5%) 2 (.5%) 4 (1.0%)

299 (76.1%) 68 (17.3%) 20 (5.1%) 2 (.5%) 0 (.0%) 4 (1.0%)

Frequency of use of the mobile Internet Several times an hour Once an hour Several times a day Once a day Scarcer

236 (28.1%) 134 (16.0%) 333 (39.7%) 85 (10.1%) 51 (6.1%)

111 (28.1%) 64 (16.2%) 158 (40.0%) 41 (10.4%) 21 (5.3%)

102 (25.9%) 54 (13.7%) 163 (41.4%) 44 (11.2%) 31 (7.9%)

110 (25.9%) 66 (13.7%) 159 (41.4%) 36 (11.2%) 25 (7.9%)

103 (26.3%) 52 (13.2%) 162 (41.2%) 49 (12.5%) 27 (6.9%)

216 (54.7%) 179 (45.3%)

230 (58.4%) 164 (41.6%)

239 (60.4%) 157 (39.6%)

207 (52.7%) 186 (47.3%)

Purchasing via mobile (i.e., smartphone-based) online stores At least once 446 (56.5%) Never 343 (43.5%)

the perceived usefulness for purchasing. In addition, perceived usefulness for information search positively influences the perceived usefulness for purchasing. The hypotheses describing the relationships between perceived technical quality (H2a), information quality (H2b), aesthetic quality (H2c), and perceived usefulness of mobile online stores for purchasing, as well as Hypothesis H3d, cannot be accepted. Hence, the formation of usefulness perceptions during information search is independent of the perceived security quality. Hypothesis H3a can be marginally supported (p < .10), suggesting that the perceived usefulness of mobile online stores for information search depends on the beliefs about the technical quality. Individuals’ usefulness perceptions of mobile online stores for information search fully mediate the relationship between aesthetic quality and information quality, and perceived usefulness for purchasing. Although technical quality neither directly nor indirectly influences usefulness perceptions of mobile online stores for purchasing, a significant total effect can be observed. Thus, all of the considered belief dimensions about the quality of mobile online stores exert some influence on the perceived usefulness for purchasing. The findings support the results of Wang’s (2016) reported positive effect of perceived information and system quality on usefulness perceptions in a post-adoption situation. The findings are also in line with those of Li and Yeh (2010), who emphasize the role of design aesthetics for the formation of usefulness perceptions. For systemrelated issues (i.e., technical quality), Davis et al. (1989) argue that the associated beliefs become obsolete as the user becomes accustomed with the system. Smartphone owners typically use apps and the Internet browser several times a day, using skills required by mobile online

on confirmatory factor analysis (CFA) involving the use of Mplus 7.31 (Muthén and Muthén, 2012) and the MLR estimator with robust standard errors (Satorra and Bentler, 2001). The CFA results indicated acceptable reliability and validity for all measurement models. Factor loadings exceeded the recommended level of .70 (Bagozzi and Yi, 2012) for all items, and were statistically significant, indicating convergent validity. The composite reliability (CR) and average variance extracted (AVE) exceeded the recommended thresholds (Table 4). Discriminant validity was evaluated by the Fornell-Larcker-criterion (Fornell and Larcker, 1981). Employed measures discriminate one from another. Accordingly, the lowest AVE value exceeded the highest squared inter-construct-correlation. Except for the significant χ2 value (Table 4), the remaining fit indices occurred within acceptable ranges, suggesting that the measurement models fit well with the data. An additional CFA, in which all items loaded onto one factor, indicated that common method variance was unlikely to present an obstacle (overall: χ2(152)=5054.622, CFI=.495, TLI=.432, RMSEA=.202, SRMR=.132). 4.3. Hypotheses testing 4.3.1. Hypotheses on the main effects Structural equation modeling (SEM) with Mplus showed an acceptable fit with regard to the overall sample (N=798); however, the χ2 values were statistically significant (Table 5). Hypotheses tests indicated that the significance of the standardized path coefficients support Hypotheses H1, H2d, H3b, and H3c. Perceived aesthetic and information quality positively affect perceived usefulness of mobile online stores for information search, and perceived security quality enhances 28

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paths were constrained to being equal across samples. The χ2-difference-test reveals a statistically non-significant result when comparing clothes with tickets, suggesting that the overall structural model is invariant across samples (Δχ2(9)=10.97, n.s.). However, the post-hoc analysis of single structural paths demonstrates several statistically significant differences between clothes and tickets (Table 5). In particular, the effect of information quality (aesthetic quality) on perceived usefulness of mobile online stores for information search is more (less) pronounced for tickets than for clothes. Thus, H4 can partially not be supported. The effect of information quality on usefulness perceptions regarding information search is stronger for tickets than for clothes. This counterintuitive finding might refer to the fact that consumers can theoretically evaluate the quality characteristics of search goods in their entirety prior to purchase (Ekelund et al., 1995). Therefore, a high level of information quality is required to ensure good search good choices. Moreover, in case of experience good purchases, consumers typically extend the online assessment of these goods to the offline environment (i.e., in-store or at home). This offline assessment of product information is rather atypical for search goods which explains the pivotal role of online information quality. This research additionally analyzed the moderating effect of the respective mobile shopping touchpoints on the relationships between quality and usefulness perceptions (Table 5). Following the procedure described above, the overall structural model and single paths do not differ between the groups' mobile apps and mobile websites, contradicting H5. Hence, consumers seem to form their usefulness perceptions through mobile online store quality, independent of the respective touchpoints to the mobile online store. This supports Wagner et al.’s (2017) conclusion of no differences in the determinants of perceived usefulness between apps and browser-accessible websites. Instead, individuals seem to develop an overall mobile channel image. Potentially, the enhanced quality of the browser-accessible mobile websites further justifies this finding.

Table 4 Reliability and validity of multi-dimensional measures. Group Clothes (N=395)

Group Tickets (N=394)

Group Apps (N=396)

Group Websites (N=393)

Aesthetic Quality (AQ) FL .832 CR .917 AVE .735

.816 .915 .729

.837 .920 .743

.829 .914 .727

.818 .920 .742

Technical Quality (TQ) FL .852 CR .900 AVE .751

.850 .906 .763

.853 .893 .736

.847 .901 .753

.839 .901 .752

Security Quality (SQ) FL .896 CR .939 AVE .837

.899 .933 .823

.896 .945 .852

.902 .936 .829

.890 .943 .848

Information Quality (IQ) FL .844 CR .834 AVE .716

.843 .833 .714

.844 .835 .717

.831 .829 .708

.841 .838 .722

Overall (N=789)

Usefulness of mobile online stores for information search (PUINF) FL .821 .834 .808 .826 CR .952 .960 .943 .952 AVE .832 .857 .806 .833

.811 .951 .829

Usefulness of mobile online stores for purchasing (PUPUR) FL .919 .911 .926 .918 CR .960 .957 .963 .961 AVE .890 .882 .896 .891

.919 .959 .885

Highest squared inter-construct-correlation ϕ2 .653 .650 .656

.697

.616

Model Fit Indices χ2(df) 258.967(137) RMSEA CFI TLI SRMR

.034 .987 .984 .024

186.746(137)

218.732(137)

195.772(137)

188.293(137)

.042 .983 .979 .034

.039 .983 .979 .026

.033 .988 .985 .026

.031 .990 .987 .028

4.4. Post-hoc analyses

Notes: FL - lowest standardized factor loading, CR - Composite Reliability, AVE - Average Variance Extracted. RMSEA - Root Mean Square Error of Approximation, CFI - Comparative Fit Index. TLI - Tucker Lewis Index, SRMR - Standardized Root Mean Square Residual.

Given the observed between-product differences, further analyses of these variances were conducted, considering the potential interaction effects between the moderating variables (Table 6 and Table 7). In the group clothes, the structural model differs between the subgroups mobile apps and mobile websites (Δχ2(9)=20.99, p < .05). Specifically, the mobile touchpoint moderates the effect of aesthetic quality on perceived usefulness of mobile online stores for information search; the effect is stronger when accessing an online store with an app than through a mobile-optimized website. Clothes shopping is often associated with an intense web interaction, requiring a shopping experience similar to the physical one (Kim and Forsythe, 2008). Hence, virtual shopping touchpoints might be particularly important when evaluating the purchase of, or information search for, clothes. Apps offer an environment that supports intense interactions, by providing a high degree of usability and attractiveness. The outstanding relevance of the aesthetic quality might be justified thereby that aesthetics are associated with an ease of processing of environmental information (Reber et al., 2004). Fluent processing might be particularly valuable during the intense interactions associated with app-based clothes shopping. In the group tickets, the effect of perceived information quality on perceived usefulness of mobile online stores for purchasing is stronger when using an app instead of a mobile-optimized website. Using an online store app might be associated with the desire to use the respective online store frequently and intensively on mobile devices, due to the pre-usage costs (i.e., download and installation). This might explain the stronger effect of information quality on usefulness perceptions when referring evaluations to apps instead of mobile websites. The effect of aesthetic quality on perceived usefulness of a mobile

shopping; one can therefore assume transfer of these experiences to the ease of use of mobile online stores. Overall, the findings confirm the importance of information-related aspects (i.e., information and aesthetic quality) when evaluating the usefulness of mobile online stores for information search. According to Carlson et al. (2008), consumers pursue a learning goal during this stage, thus explaining the relevance of these aspects. 4.3.2. Hypotheses on the moderating effects Product and touchpoint differences in the relationship between perceived quality and usefulness perceptions were analyzed using multi-group analysis implemented in Mplus. First, it was ensured that the measurement models were invariant across samples; their fit for the single samples exhibits acceptable values (Table 4). In addition, models with freely estimated and those with constrained factor loadings were compared across products and touchpoints. The constraints increased the χ2 from 432.27 to 453.75 on 19 degrees of freedom, based on the Satorra-Bentler scaling correction—a statistically insignificant difference, indicating metric invariance for the sub-sample clothes. Similarly, measurement variance across the two touchpoints yields no concern with regard to metric invariance (Δχ2(19)=13.20, n.s.). Second, tests for structural coefficient differences between samples followed, by comparing a model that enabled each path to be estimated freely across the compared samples with a nested model in which all 29

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Table 5 Hypothesis testing. Overall (N=789)

Group Clothes (N=395)

Group Tickets (N=394)

.641** .069ns .090ns −.007ns .136** .111† .262** .195** .025ns .296 .633 258.967(137) .034 .987 .984 .024

.658** .141* .055ns −.062ns .169** .175† .212* .248* .033ns .373 .688 213.476(137) .038 .986 .982 .029

.622** −.009ns .104ns .064ns .113† .050ns .311** .129ns .025ns .229 .582 218.732(137) .039 .983 .979 .026

Indirect Effectsa TQ → PUPUR IQ → PUPUR AQ → PUPUR SQ → PUPUR

.071ns .168* .125* .016ns

.115* .139* .163* .022ns

Total Effectsa TQ → PUPUR IQ → PUPUR AQ → PUPUR SQ → PUPUR

.140* .258* .118* .152*

.257* .195ns .101ns .191*

H1: PUINF → PUPUR H2a: TQ → PUPUR H2b: IQ → PUPUR H2c: AQ → PUPUR H2d: SQ → PUPUR H3a: TQ → PUINF H3b: IQ → PUINF H3c: AQ → PUINF H3d: SQ → PUINF R2 PUINF R2 PUPUR χ2(df) RMSEA CFI TLI SRMR

H4:Δχ2

Group Apps (N=396)

Group Websites (N=393)

.671** .070ns .158† −.080ns .129* .049ns .189ns .377** −.023ns .325 .671 195.772(137) .033 .988 .985 .026

.609** .067ns .053† .036ns .144* .181* .321** .009ns .085ns .285 .595 188.293(137) .031 .990 .987 .028

.031ns .193* .080ns .016ns

.033ns .127ns .253* −.015ns

.110* .195* .005ns .052ns

.022ns .297* .144ns .128*

.103ns .285* .173ns .114ns

.177* .249* .042ns .196*

(1)

.81ns 2.76† 1.02ns .47ns 1.14ns 2.65† 4.62* 6.86** 2.60†

H5:Δχ2

(1)

2.26 ns .83ns 1.5ns .38ns .28ns .03ns .09ns 1.95ns .11ns

Notes: nsNot significant. RMSEA - Root Mean Square Error of Approximation, CFI - Comparative Fit Index, TLI - Tucker Lewis Index, SRMR - Standardized Root Mean Square Residual. * Significant at .05. ** Significant at .01. † Significant at .10. a Values between brackets indicate confidence intervals (CI) at 95% level, bootstrapping with N=1000.

websites, where the formation of usefulness perceptions seems to be independent of product category (Table 7). To sum up, the findings demonstrate that consumers form product-specific usefulness evaluations of mobile online shopping through beliefs about the mobile online

online store for information search is significantly stronger for clothes than for tickets when holding the touchpoint constant for mobile apps. In contrast, the effect of information quality is weaker for clothes than for tickets. These effects do not occur when focusing on mobile

Table 6 Post-hoc analysis I. Group Clothes (N=395)

Group H1: PUINF → PUPUR H2a: TQ → PUPUR H2b: IQ → PUPUR H2c: AQ → PUPUR H2d: SQ → PUPUR H3a: TQ → PUINF H3b: IQ → PUINF H3c: AQ → PUINF H3d: SQ → PUINF R2 PUINF R2 PUPUR χ2(df) RMSEA CFI TLI SRMR

Group Tickets (N=394)

Group Apps (N=204) [Cl_A]

Group Websites (N=191) [Cl_W]

Group Apps (N=192) [Ti_A]

Group Websites (N=202) [Ti_W]

.731** .149ns .067ns −.078ns .248** .195ns .143ns .490** −.110ns .514 .727 186.746(137) .042 .983 .979 .034

.611** .150† .142ns −.074ns .118ns .164ns .250* .032ns .170† .285 .652 168.848(137) .035 .988 .985 .035

.646** .030ns .308* −.094ns .033ns −.095ns .178ns .300* .081ns .195 .631 172.692(137) .037 .985 .982 .032

.626** −.052ns −.067ns .186ns .176† .206* .415** −.036ns −.005ns .295 .559 187.929(137) .043 .981 .977 .031

Notes: ns not significant, RMSEA - Root Mean Square Error of Approximation, CFI - Comparative Fit Index, TLI - Tucker Lewis Index, SRMR - Standardized Root Mean Square Residual. * Significant at .05. ** Significant at .01. † Significant at .10

30

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Table 7 Post-hoc analysis II.

Metric Invariance Δ 2 χ (19) Structural Invariance Δ 2 χ (9) Path Invariance (Δχ2 (1)) H1: PUINF → PUPUR H2a: TQ → PUPUR H2b: IQ → PUPUR H2c: AQ → PUPUR H2d: SQ → PUPUR H3a: TQ → PUINF H3b: IQ → PUINF H3c: AQ → PUINF H3d: SQ → PUINF Notes:

ns

not significant;

†

[Cl_A] vs. [Cl_W]

[Ti_A] vs. [Ti_W]

[Cl_A] vs. [Ti_A]

[Cl_W] vs. [Ti_W]

[Cl_A] vs. [Ti_W]

[Cl_W] vs. [Ti_A]

16.21ns

13.64ns

18.72ns

16.95ns

20.90ns

20.99ns

20.99*

9.25ns

27.63**

5.97ns

20.41*

4.33ns

1.14ns .05ns .03ns .02ns .55ns 5.01* 2.76† 9.40** .17ns

1.16ns 1.74ns 3.77* .02ns .07ns 1.85ns .44ns .07ns .02ns

.20ns .03ns .18ns .03ns 1.83ns 17.81** 5.51* 8.32** .85ns

.65ns 2.92† 2.32ns .41ns 1.83ns .22ns .07ns .15ns 1.36ns

4.16* 4.51* 2.89† 1.03ns 1.17ns 3.81* 2.79† 14.52** 1.26ns

.22ns .16ns .05ns .00ns .17ns 2.47ns 1.32ns .51ns 1.52ns

significant at .10;

*

significant at .05;

**

significant at .01.

mobile commerce, and multi-channel-retailing. For consumer adoption processes, this research broadens the understanding on the psychological mechanisms underlying the formation of usefulness perceptions as a solid predictor of consumer adoption. This work outlines the so far largely neglected heterogeneity underlying the formation of usefulness perceptions. For consumer channel choice, this work emphasizes the need to distinguish between shopping tasks to determine the predictors of channel choice appropriately. Furthermore, it provides current insights into online shopping as it highlights a specific channel of online shopping and consumers’ associated use determinants. As the findings suggest that the mobile online shopping touchpoint induces differing predictors of usefulness perceptions, this work contributes to the knowledge on other forms of online shopping (Wagner et al., 2017), multi-channel-retailing, and more specifically on the multi-channel electronic commerce (Wagner, 2015). Finally, in contrast to the mobile commerce research (e.g., Ko et al., 2009), this study offers a crossproduct perspective on mobile online shopping and thus helps to uncover the cited role of the product category during mobile online shopping adoption (Wang et al., 2015).

store quality, depending on the respective mobile online shopping format. 5. Conclusion 5.1. Summary of the findings and theoretical implications This research suggests that consumers form usefulness perceptions of mobile retail websites through their beliefs about website quality. In particular, consumers’ aesthetic, information, security, and technical quality perceptions influence usefulness perceptions in a pre-adoption stage. Although quality perceptions have been predominantly considered in studies that evaluate consumers’ post-usage impressions (e.g., after a website interaction) (e.g., Kim et al., 2016), they also seem to enable adoption processes, presumably by integrating experiences from related activities (Anderson, 1991). The results further highlight the importance of defining the nature of usefulness perceptions by underlining consumers’ clear differentiation between usefulness evaluations for shopping tasks. While the beliefs associated with security quality directly influence the perceived usefulness of using mobile online stores for purchasing, beliefs about the information, aesthetic, and technical quality are indirectly related through usefulness perceptions of the use of mobile online stores for information search. Single shopping activities are typically associated with particular requirements, which, in turn, determine the way in which consumers develop behavioral beliefs. This research underlines this so far unexplored assumption, as such extending the study of de Kerviler et al. (2016) who found that the effects of perceived benefits on use intentions differ across shopping tasks. Moreover, this study’s findings substantiate the assumption that a clear distinction is required to identify determinants of consumer evaluations in a channel choice context (Verhoef et al., 2007). Additionally, the findings highlight the relevance of contextual variables, which moderate the relationships between the quality beliefs and the usefulness perceptions. For instance, when consumers evaluate mobile retail stores offering clothes, the relationship between aesthetic quality and perceived usefulness for information search is stronger than for websites selling event tickets. Hence, consumers base their usefulness perceptions of channel-related shopping tasks on the product category. Moreover, this study yields support for the importance of the mobile online shopping touchpoint when consumers form usefulness perceptions, as is indicated by the differing relevance of the predictors of perceived usefulness. Although the developed model has been tested for mobile online shopping, it also provides insights for research in related fields. In particular, this work has implications for consumer adoption processes and consumer channel choice, as well as for online shopping/retailing,

5.2. Managerial implications The findings provide (aspiring) mobile e-channel retailers (e.g., online retailers) with information on how to shape consumer adoption. In particular, they provide insights into perceived usefulness as a substantial predictor of mobile online shopping adoption. This could be enhanced in a pre-usage stage by focusing on shaping consumers’ beliefs about mobile online store quality. As marketing communications are relevant to forming consumer beliefs (Pitt et al., 1995), managers should focus on designing targeted communication campaigns that provide consumers’ with appropriate information about newly created mobile online stores. The campaigns should inform about the aesthetic, technical, security, and information quality of mobile online stores, as these perceptions shape the perceived usefulness for purchasing. When planning communication strategies, managers should consider the contextual use scenarios of mobile online stores to address the needs of potential users. Table 8 provides orientation on the quality dimensions that are relevant to address, depending on the access touchpoint and product category. For instance, advertising mobile online stores offering clothes should emphasize all of the considered quality dimensions, while communications for mobile online stores offering event tickets should highlight information quality. Communicating these quality aspects requires creating mobile online stores with the respective quality levels. Prior research yields, for instance, additional insights into how to influence consumers’ perceived aesthetic quality of online stores. Jiang et al. (2016) illustrate that high degrees of the unity, intensity, novelty, and interactivity of the design elements in the 31

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Table 8 Managerial implications for the creation and redesign of mobile online store. Product category Experience Goods

Search Goods

Aesthetic quality ↑ Security quality ↑ Technical quality ↑ Information quality ↑

Information quality ↑

App

Security quality ↑ Aesthetic quality ↑

Security quality ↑ Aesthetic quality ↑

Information quality ↑ Aesthetic quality ↑

Browser-accessible Website

Security quality ↑ Technical quality ↑ Information quality ↑

Information quality ↑

Information quality ↑ Technical quality ↑

Touchpoint

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store enhance perceived aesthetics. 5.3. Limitations and future research avenues On the one hand, this study considers extrinsic motivations (i.e., perceived usefulness) while neglecting intrinsic motivations (e.g., perceived enjoyment) when specifying behavioral beliefs. Since extant research highlights the relevance of intrinsic and hedonic parameters in related contexts (e.g., Agrebi and Jallais, 2015), future research might consider this perspective to explain behavior. On the other hand, the focus on the antecedents to usefulness perceptions might represent another weakness of the model. To further advance the knowledge on usefulness perceptions, scholars should consider analyzing the effects of these shopping task-related usefulness perceptions on, for instance, behavioral intentions. Furthermore, this study specifies perceptions of usefulness by considering goal-directed tasks that people can accomplish by using their smartphone (e.g., information search). Since consumers also shop online for experiential reasons (Wolfinbarger and Gilly, 2001), clarifying the psychological origins and their predictive power could represent a valuable future research avenue. Finally, this study focuses its findings on selected product categories with several particularities. Within the groups of search and experience goods, product category differences might emerge that could broaden the presented findings (Cho, 2015). Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. References Abbas, H.A., Hamdy, H.I., 2015. Determinants of continuance intention factor in Kuwait communication market: case study of Zain-Kuwait. Comput. Human. Behav. 49, 648–657. Agrebi, S., Jallais, J., 2015. Explain the intention to use smartphones for mobile shopping. J. Retail. Consum. Serv. 22, 16–23. Al-Qeisi, K., Dennis, C., Alamanos, E., Jayawardhena, C., 2014. Website design quality and usage behavior: unified theory of acceptance and use of technology. J. Bus. Res. 67 (11), 2282–2290. Anderson, N.H., 1991. Contributions to Information Integration Theory: Cognition. Erlbaum Associates, Hillsdale, NJ, USA. Arpaci, I., 2016. Understanding and predicting students' intention to use mobile cloud storage services. Comput. Hum. Behav. 58, 150–157. Bagozzi, R.P., Yi, Y., 2012. Specification, evaluation, and interpretation of structural equation models. J. Acad. Mark. Sci. 40 (1), 8–34. Benbasat, I., Barki, H., 2007. Quo vadis TAM? J. Assoc. Inf. Syst. 8 (4), 211–218. Blut, M., Wang, C., Schoefer, K., 2016. Factors influencing the acceptance of self-service technologies. J. Serv. Res. 19 (4), 396–416. Bressolles, G., 2006. La Qualité de Service Electronique. NetQu@l Proposition d'une Echelle de Mesure Appliquée aux Sites Marchands et Effets Modérateurs. Recherche

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