sustainability

Article

The Effects of Online Shopping Context Cues onConsumers’ Purchase Intention for Cross-BorderE-Commerce Sustainability

Liang Xiao 1,2, Feipeng Guo 1,2, Fumao Yu 1,2,* and Shengnan Liu 1

1 Modern Business Research Center, Zhejiang Gongshang University, Hangzhou 310018, China;xl@mail.zjgsu.edu.cn (L.X.); guofp@zjgsu.edu.cn (F.G.); liusn@rschn.com (S.L.)

2 School of Management and E-Business, Zhejiang Gongshang University, Hangzhou 310018, China* Correspondence: yufumao@zjgsu.edu.cn; Tel.: +86-571-2887-7399

Received: 17 April 2019; Accepted: 10 May 2019; Published: 15 May 2019�����������������

Abstract: China is currently the world’s largest cross-border e-commerce purchaser and destinationcountry. Therefore, how to promote consumer online shopping is the most important goal forcross-border e-commerce sustainability. Meanwhile, the previous research has not empiricallyverified the precise effect of online shopping context and perceived value on consumers’ cross-borderonline purchase intention. To address this gap, this study analyzes the online shopping contextthat determines consumers’ purchase intention and innovatively identifies four cues that promotethis consumption behavior in cross-border e-commerce, such as online promotion cues, contentmarketing cues, personalized recommendation cues, and social review cues. It proposes a theoreticalmodel based on cue utilization theory and stimulus-organism-response model, which introducesthis four cues and brand familiarity in analyzing the effects on consumers’ purchase intention incross-border online shopping (CBOS). In addition, the paper examines the mediating role of perceivedfunctional value and perceived emotional value. Survey data collected 372 cross-border onlineconsumers from China and the PLS-SEM method was used to empirically test the proposed model.The results show that these four cross-border online shopping context cues have a significantlypositive impact on consumers’ purchase intention. Brand familiarity has significantly negativemoderating effects between the four cues and the perceived functional value, while brand familiarityalso negatively moderates the relationship between online promotion cues, social review cues, andperceived emotional value, respectively.

Keywords: cross-border e-commerce; online shopping context cues; purchase intention; perceivedfunctional value; perceived emotional value; S-O-R theory

1. Introduction

With the continuous growth of global trade and the rapid advances of the digital society, consumersare increasingly shopping abroad. Cross-border e-commerce booms all around the world [1]. Whatis more, these trends have stimulated the upgrading of traditional foreign trade modes in multipledimensions of sustainability. It can offer attractive products to consumers with competitive prices andwide product assortments [2], and greatly shorten the time and space distance between consumersand suppliers [3–5]. According to a report published jointly by Accenture and Ali Research [6], theglobal Business to Customer (B2C) cross-border e-commerce market will balloon in size to $1 trillionin 2020, and more than 943 million people around the world will shop online internationally. China,with more than 200 million B2C cross-border e-commerce consumers, will become the world’s largestcross-border B2C e-commerce consumer market [6]. In view of the importance of the cross-border

Sustainability 2019, 11, 2777; doi:10.3390/su11102777 www.mdpi.com/journal/sustainability

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e-commerce, countries around the world have taken steps to promote sustainable development ofcross-border e-commerce. Given the importance of e-commerce in the Digital Single Market (DSM)strategy, the EU is committed to opening up digital opportunities for people and businesses, especiallythrough a wide range of initiatives to promote cross-border e-commerce [5]. The rapid development ofcross-border e-commerce in China is famous for its popular “one belt and one road” initiative, whichmay reshape our way of conceptualizing and managing manufacturing, logistics, and consumptionto achieve sustainable growth and development of cross-border e-commerce, especially in emergingcross-border markets [7].

Previous studies on cross-border e-commerce [8–10] pay more attention to the positive impactof cross-border e-commerce on economy and its potential growth and future development. There isnot much empirical research on the challenges and opportunities for both cross-border e-commercesuppliers and consumers, and less is conducted to address the increasingly intense price competitions,the efficiencies of the retail sector, positive impacts on other production sectors, the interests ofindividuals and household consumers, labor productivity, domestic production and total value growth,etc. [5]. While cross-border e-commerce is growing rapidly, especially in emerging market countries(such as China, India), there are still many factors that restrict consumers from purchase. Therefore,attracting more online consumers and recognizing factors that influence consumers’ purchase intention,have become an important goal for cross-border e-commerce sustainability [11]. In addition to factorssuch as Internet penetration and information technology facilities, Internet consumer experience,and perception are also important constraint factors [5]. The main constraints mentioned in theliterature are crossing language barriers, little familiarity and trust in the vendors, need of a secureway to pay, cost-efficiency of parcel delivery, etc. [11–13]. Many studies [5,14] have noted thatdemographic attributes, such as gender, age, income, and education, can make differences in theadoption of cross-border e-commerce. However, the impact of these factors is often context-dependent.According PayPal [2], global consumers’ attitude towards cross-border purchase varies from regionto region, and North Americans are most likely to be loyal to global or home websites and moresceptical of those from other countries, consumers in the Middle East are most likely to shopcross-border. Von Helversen et al. [14] found strong age differences in the influence of consumerreviews on purchasing decisions. Cross-border e-commerce platform can take a variety of measures toimprove online consumer satisfaction, such as providing personalized products [15,16] according tocustomers’ purchase history and personal information, providing the evaluation of products and theirsuppliers [17–19].

Cross-border online consumption is vastly expanding around the globe, but nowhere can oneobserve cross-border e-commerce developments like in China [20]. According to PayPal’s survey, theproportion of cross-border online consumers in China to the total number of online consumers hasincreased from 25% in 2014 to 43% in 2017 [2]. A number of relatively successful B2C cross-bordere-commerce platform companies have emerged in China, such as Yangmatou, Xiaohongshu (also knownas RED), Netease’s Koala, Tmall Global, AliExpress, etc. [2]. However, comparing to the domestice-commerce which has formed a relatively stable market competition pattern and enjoyed a leadingposition in the world, China’s cross-border e-commerce enterprises are still in the growth stage,and the marketing strategies of cross-border e-commerce retail enterprises is also mainly derivedfrom traditional import trade or domestic e-commerce model [7,13,20]. For consumers, cross-borderonline purchase and domestic online purchase are two significantly different online shopping contexts.In the traditional domestic online shopping context, even if consumers are not familiar with theproperties of online shopping products, they can avoid or fundamentally reduce potential lossesthrough seven days return/exchange policy, freight insurance, and other safeguard mechanisms [21].Under the cross-border online shopping context, it is often difficult for the seller to effectively providesuch a guarantee mechanism due to barriers such as international logistics costs, procedures, andtariffs. Therefore, consumers will be more cautious about the cross-border online purchase decision,

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and the influencing factors of cross-border online purchase intention may be quite different fromdomestic e-commerce.

The previous research has not empirically verified the precise effect of online shopping contextand perceived value on consumers’ cross-border online purchase intention. To address this gap, theaim of this paper is to identify the main categories of external cues that affect consumers’ cross-bordershopping, and discover the influence mechanism of the external cues affecting consumers’ willingnessto conduct cross-border shopping. The main research questions are: Are online promotion cues,content marketing cues, personalized recommendation cues and social review cues positively affectingconsumers’ purchase intention for cross-border commerce? Does consumer perception has a mediateeffect between external cues and cross-border purchase intention? Whether consumers’ familiaritywith online brand has a moderating effect on the influence of external cues? The innovative conclusionsto these questions provide insight in the behavior of online consumers, which can provide empiricalresearch support for B2C cross-border e-commerce enterprises to improve marketing strategies,enhance cross-border online purchase confidence of Chinese consumers, and promote the sustainabledevelopment of cross-border e-commerce.

The Section 2 of this paper reviews Cue Utilization theory and Stimulus-Organism-Responsetheory (SOR). The proposed research model and hypotheses are presented in Section 3. Section 4presents the methodology, including data description, measurement of variables and the econometricmodel. Then, Section 5 analyzes the results, and finally the paper is concluded with discussions on thefindings and their theoretical and practical implications.

2. Literature Review and Theoretical Background

2.1. Cue Utilization Theory

Cue utilization theory believes that products convey a series of cues that consumers can use tojudge their qualities [22,23]. Product cues categorize them as intrinsic cues and extrinsic cues [23].Intrinsic cues are related to the direct physical properties of the product, including product size, shape,taste, etc. If the physical characteristics of the product itself is not changed, intrinsic cues cannotbe changed or controlled by the test [24]. External cues are usually associated with indirect signalsand are “product-related attributes, but not part of physical attributes” [24,25]. The value of clues toconsumers can be divided into two categories: predictive values and confidence values. The former isthe degree to which consumers associate a clue with product quality. The latter is the degree to whichconsumers have confidence in their ability to correctly judge and use clues [26]. The importance ofcues in consumer perceived quality judgment is determined by the predictive value and confidencevalue of the cue. The cues of high predictive value and high confidence value will play an importantrole in value evaluation.

In most cases, consumers are more familiar with external cues than with intrinsic cues, so they relymore on external cues when evaluating products. For example, Wheatley et al. [27] found that changesin the physical quality of a product are less likely to be perceived by consumers than price changes.While physical quality cues have a great impact on perceived quality, when the level of physical qualitycues increases, its impact becomes smaller. Therefore, consumers are more inclined to use the externalcues of products to judge product quality. Zeithaml [28] argued that consumers are susceptible toadjustments in product factors when using internal leads, i.e., the same consumers may use differentinternal cues for different products. When using external cues, it is not affected by the adjustmentof product factors. For example, many products will use prices, brand names, advertisements etc.Because consumers cannot directly observe the intrinsic cues of products, they rely more on externalcues to assess product quality [29,30]. Therefore, under the cross-border online shopping context,external cues play a very important role in consumer decision-making.

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2.2. Stimulus-Organism-Response Theory

The SOR model [22] based on environmental psychology theory has been widely used to measurethe impact of product feature perception on consumer response [31]. According to SOR, environmentalstimuli (S) lead to emotional reactions (O), which in turn drive consumer behavioral responses (R).SOR theory indicates that environmental stimuli (S) lead to emotional responses (O), which then driveconsumers’ behavioral responses (R). In the study of marketing, emotion is considered to be the body’sresponse to external environmental stimuli and ends with some kind of action [32]. Similarly, Emotionplays a key role in consumers’ decision-making and buying behavior [33,34]. According to Wilkie [35],consumers deal with emotions when search for information, comparing alternatives, making purchasedecisions, and dealing with products that have already been purchased. Therefore, it can be seen thatconsumers are immersed in certain emotions throughout the purchase process.

Using the S-O-R model, many studies in the retail and service sectors have successfullyused environmental stimuli as predictors of emotional responses and consumer behaviors [36,37].Bagozzi et al. [38] validated the S-O relationship of the S-O-R model and found that consumption-relatedemotions were formed based on specific assessments made by consumers. A study by Baker et al. [39]found a link between the store environment and the emotional state of pleasure and awakening.Wakefield and Baker [40] argued that the overall architectural design and decoration of the mall is akey environmental factor that excites customers. Donovan and Rossiter [36] first applied the S-O-Rparadigm in a retail environment, and they argued that Mehrabian and Russell [22] did not explicitlyaddress the issue of stimulus classification. Meanwhile, in the marketing literature, there are manydifferent ways that people can use the S-O-R paradigm. Some scholars use consumer assessment ofexternal stimuli as part of the S-O-R model [41,42], while others use actual stimuli [43,44].

3. Conceptual Framework and Hypotheses

3.1. Conceptual Framework

According to the S-O-R model of Mehrabian and Russell [22], stimulus refers to attributes thatare located in the environment and affect the emotional and cognitive state of the individual, suchas product characteristics, promotion, brand reputation, music, price, layout, service, and so on.In the online shopping environment, consumers often face a large number of external leads. Previousstudies have suggested that the main cues to consumer purchasing decisions are visual appeal ofthe website [45], product price [46], third-party guarantee [47], online store reviews [48] and storereputation [49]. However, these previous studies have also found that when consumers face a largenumber of external cues, these cues play different roles. The information provided by differentcues cannot be simply added up. When one consumer receives the comment information of otherconsumers, the cues such as seals and store reputation are no longer important to the consumer. In thecross-border online shopping context, this study selects four cross-border online shopping contextcues as external stimuli to stimulate consumer emotional responses and cognitive processes, whichare online promotion cues, content marketing cues, personalized recommendation cues, and socialreview cues.

In the S-O-R model, the organism is a mediator of the relationship between environmental stimulusand response. It usually refers to an individual’s emotion or cognitive state. Emotion is a general termfor an individual’s series of subjective cognitive experiences. It is a psychological and physiologicalstate in which multiple feelings, thoughts, and behaviors are combined. Emotion is often intertwinedwith mood, temperament, personality, disposition, and motivation. Cognition is an important aspect ofemotion. Cognition is a psychological behavior or process that acquires knowledge and understandingthrough thoughts, experiences, and senses. Cognition includes attention, knowledge formation,memory and working memory, judgment and evaluation, reasoning and “calculation”, problemsolving and decision making, language understanding and production. Different analyzing methodsare used to analyze cognitive processes in different contexts and disciplines [50]. Hartman [51] first

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proposed a value model consisting of both emotion and cognition. Due to the constant changing ofconsumer’s needs, the dimensions of perceived value are gradually changing and advancing with thetimes. Sweeny & Soutar [52] use functional value as the basis of cognition and emotional or social valueas the basis of emotion. Among them, under the cross-border online shopping context, the perceivedfunction value mainly refers to the consumer’s usefulness perception of the various recommended cuesreceived, that is, customers’ completion of the cross-border shopping targets. Functional value andemotional value have been widely concerned in recent years’ research on consumers’ online purchaseintention, but few scholars have tested their relationship with other factors affecting e-commercesuccess [53,54]. In this study, the perceived value on cross-border online shopping context is used todescribe the organism variable, including the perceived functional value and perceived emotional value.

According to the S-O-R theory, consumer response refers to the approach or avoidance behaviorafter the emotional and cognitive processes. Approaching behavior includes positive responses such aspurchase intentions, patronage intentions, etc. Behavioral intentions are personal beliefs or feelings onwhich people base their actions. The consumer’s behavioral intention is a function of product cues suchas store image and price. It is a positive assessment of the store’s image, product price and packaging,and other cues that will enhance consumers’ purchase intention, patronage, or loyalty [55,56]. Basedon the theory of clue utilization and the SOR model, this study uses cross-border consumer’s purchaseintention as the final response of consumers to cross-border online shopping context cues.

In the context of cross-border online shopping, there are fewer internal cues but more externalcues consumers can directly have. Therefore, consumers have to rely on external cues to makepurchase decisions. When the impact of external cues on consumer perception and purchase intentionis discussed, the impact of other factors should be controlled or excluded. In the literature oninternational marketing, consumers’ previous shopping experience, education level, and foreignproduct knowledge are often considered to be important factors influencing consumers’ purchaseintention [57]. This study assumes that in the context of cross-border online shopping, Chineseconsumers’ brand familiarity (BF) may have an impact on the functional or emotional value of externalcues. Therefore, in addition to controlling the demographic attributes of Internet shoppers, this studyuses brand familiarity as a moderator between cues and perceived value.

The theoretical framework of this study is shown in Figure 1.

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cross-border online shopping context, the perceived function value mainly refers to the consumer’s usefulness perception of the various recommended cues received, that is, customers’ completion of the cross-border shopping targets. Functional value and emotional value have been widely concerned in recent years’ research on consumers’ online purchase intention, but few scholars have tested their relationship with other factors affecting e-commerce success [53,54]. In this study, the perceived value on cross-border online shopping context is used to describe the organism variable, including the perceived functional value and perceived emotional value.

According to the S-O-R theory, consumer response refers to the approach or avoidance behavior after the emotional and cognitive processes. Approaching behavior includes positive responses such as purchase intentions, patronage intentions, etc. Behavioral intentions are personal beliefs or feelings on which people base their actions. The consumer’s behavioral intention is a function of product cues such as store image and price. It is a positive assessment of the store’s image, product price and packaging, and other cues that will enhance consumers’ purchase intention, patronage, or loyalty [55,56]. Based on the theory of clue utilization and the SOR model, this study uses cross-border consumer’s purchase intention as the final response of consumers to cross-border online shopping context cues.

In the context of cross-border online shopping, there are fewer internal cues but more external cues consumers can directly have. Therefore, consumers have to rely on external cues to make purchase decisions. When the impact of external cues on consumer perception and purchase intention is discussed, the impact of other factors should be controlled or excluded. In the literature on international marketing, consumers’ previous shopping experience, education level, and foreign product knowledge are often considered to be important factors influencing consumers’ purchase intention [57]. This study assumes that in the context of cross-border online shopping, Chinese consumers’ brand familiarity (BF) may have an impact on the functional or emotional value of external cues. Therefore, in addition to controlling the demographic attributes of Internet shoppers, this study uses brand familiarity as a moderator between cues and perceived value.

The theoretical framework of this study is shown in Figure 1.

Figure 1. Conceptual framework.

online promotion

content marketing

personalized recommendation

social review

consumer-perceivedfunctional value

consumer-perceivedemotional value

cross-border onlinepurchase intention

brand familiarity ...gender age educ income

Figure 1. Conceptual framework.

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3.2. Research Hypothesis

3.2.1. Cross-Border Online Shopping Cues and Perceived Value

In the cross-border online shopping environment, Chinese consumers are faced with a largenumber of product recommendation information. According to the push body, push content, thepaper summarizes the main online shopping contexts that Chinese consumers face into four categories,namely online promotion cues, content marketing cues, personalized recommendation cues, and socialreview cues.

Online Promotion Cues and Consumer-Perceived Value

Unlike American consumers [58], most Chinese consumers are more sensitive to price concessions,which can be verified by the Double Eleven phenomenon. Initially 11.11 or Double Eleven was knownas ‘Singleton’s Day’ playing on the four ‘1′s that form the date and it aimed only at college students inChina. Starting in 2009, several major online retailers decided to offer significant discounts on 11.11.At the same time, they attempt to increase sales during National Day of China to Christmas Day.At present, Double Eleven has changed from self-mocking jokes of young people to national shoppingfestivals [21]. On 11 November 2018, the online shopping turnover reached 213.5 billion yuan [21].The main promotion of the Double Eleven is the various price-cutting activities.

Some studies suggest that price promotions have an important impact on consumer purchasedecisions [59,60]. Previous researches suggest that price promotions can create an economic incentivethat attracts consumers to purchase products [61]. Nagadeepa [62] pointed out that various promotionsare just like pleasant surprises for consumers, satisfying their desires for good but cheap products,thus increasing their purchase intention. In the online shopping context, if the products offered bythe two retailers are identical except for the price, then the consumers tend to think that the retaileroffering lower price has stronger corporate strength or enjoy a higher industry status. Therefore, pricepromotion is also conducive to the improvement of consumers’ perception of emotional value. Basedon the above mentioned, the hypothesis is proposed:

Hypothesis 1a (H1a). Online promotion cues have a positive impact on consumer-perceived functional valuein the cross-border online shopping context.

Hypothesis 1b (H1b). Online promotion cues have a positive impact on consumer-perceived emotional valuein the cross-border online shopping context.

Content Marketing Cues and Consumer-Perceived Value

Content marketing (also known as Advertorials in China [63]), as an advertisement, are articles ina newspaper, magazine, or a website which involves giving information about the product. Usually,brands pay publishers for such articles. Marketers use them to educate potential consumers aboutthe characteristics of content marketing of product. By choosing the right media, content marketingcan be used for a specific group of people. For example, content marketing in business newspaperswould involve educating a group of people who are more interested in economics, markets or financialproducts. For companies, storytelling is an effective medium to connect with consumers, which isunlike traditional print advertising in magazines, newspapers or on websites as a banner advertising.Content marketing is more detailed than advertising, which helps consumers to know more aboutproducts and is usually written by advertising agents or companies themselves.

In the Internet age, the forms and media of content marketing are more diversified. TikTok (alsoknown as Douyin in China, a media app for creating and sharing short videos), and WeChat (a Chinesemulti-purpose messaging, social media and mobile payment app) among Chinese netizens are allcontent marketing methods that online retail enterprises can choose. Online content marketing arealways educational and they are constantly presented on the Internet in an interesting way, thus greatly

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lowering the requirement for the cognitive ability of audience. Therefore, online content marketing areoften more effective than traditional advertisements [64,65].

The concealment of content marketing (which is often criticized) and the independence of thenews media have made people unwittingly pleasing and thus won over their trust. Some of the contentmarketing, such as those created by prominent bloggers and Internet celebrities, have even enhancedthe perceived value of their fans to the products. Wang and Yang [63] believe that customers can obtainuseful information about the goods from the content marketing posted on the e-commerce platformin a short span of time, so that they do not have to make great efforts for shopping. Sharifi Fard [66]pointed out that interesting, novel and unique content marketing enable consumers to focus on theonline shopping activities, to have a sense of pleasure and to meet their emotional needs. Based on theabove mentioned studies, the hypothesis is proposed:

Hypothesis 2a (H2a). Content marketing cues have a positive effect on consumer-perceived functional valueunder the cross-border online shopping context.

Hypothesis 2b (H2b). Content marketing have a positive effect on consumer-perceived emotional value underthe cross-border online shopping context.

Personalized Recommendation Cues and Consumer-Perceived Value

The personalized recommendation cues refer to the user preference data mined and processed bythe cross-border e-commerce platform. Hence the cross-border e-commerce platform can recommendproducts to target consumers. Using consumer demographics, shopping history, and preferenceinformation, the e-commerce recommendation platform can generate recommendations that meetusers’ needs [67]. Previous studies have shown that personalized recommendations have a significantrole in influencing consumer decision-making [68,69]. Personalized recommendations are more easilyaccepted by consumers than non-personalized re-suggestions (i.e., recommendations generated withoutregard to consumer preferences) [70], resulting in more clicks than random recommendations [71],and having higher user ratings than random recommendations [72]. In mobile commerce, theyalso bring a significant increase in pageviews/sales and total sales [73]. The personalization degreeof user perception can be used to explain the important role of personalized recommendation ininfluencing consumer decision-making. The personalization degree of user perception refers tothe extent to which consumers believe that the personalized system understands and representstheir personal preferences [74]. Komiak and Benbasat [74] found that consumers perceive thatthe platform’s personalized recommendations can better understand their preferences for productsand more personalized needs. The perceived consensus between consumers and recommendationsystems is enhanced. Customers are encouraged to accept recommendations. Xiao and Benbasat [75]believe that personalized recommendation is an e-commerce feature that consumers value highlyand helps online companies build brand loyalty. Aljukhadar and Senecal [76] pointed out thatpersonalized recommendations based on consumer needs can reduce consumers’ shopping time andmake consumers’ shopping process convenient and interesting. Based on the above mentioned, thehypothesis is proposed:

Hypothesis 3a (H3a). Personalized recommendation cues have a positive impact on consumer-perceivedfunctional value under the cross-border online shopping context.

Hypothesis 3b (H3b). Personalized recommendation cues have a positive impact on consumer-perceivedemotional value under the cross-border online shopping context.

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Social Review Cues and Consumer-Perceived Value

Social review, a blend of user-generated contents and social networks, is a virtual communityor online platform for people to share ideas, insights, experiences and perspectives with each other.As online media continues to evolve, users actively communicate and share ideas about productsand services through blogs, product reviews, wikis, and Twitter on a more regular basis [77]. Withthe increasing popularity of social review as an effective tool for socialization and informationsharing, social e-commerce has come into being [78]. In social e-commerce, consumers are exposed tovarious technologies or functions, such as user-provided shopping experience and comments, socialrecommendation and user preferences, etc., which arouse consumers’ enthusiasm to participate insocial e-commerce [79].

The technical characteristics of the social commerce platform reflect not only the objective attributesunrelated to the customer, but also the subjective attributes perceived by the customer. According toexisting research literature, online user reviews, product reviews, and other information in social reviewcues have important implications for consumer value perception and purchase decisions. For example,product ratings (or reviews) have a significant impact on perceived trust and can reflect whether asupplier is reliable [80]. Positive reviews often reflect the positive attributes of the product, such asgood quality and brand image, while negative reviews often reflect a lack of consumer confidencein the attributes of the product, such as quality and brand image. Cui et al. [81] found that negativereviews exerted a greater impact than the positive reviews did, since they confirmed negative biases.Consumers are not only inclined to read review ratings, but also tend to read the review text beforemaking a purchase decision [82]. The textual sentiment can be viewed as a unique type of cognitiveassessment from previous customers, and the assessment provides a useful set of information forpotential consumers’ cognitive processing [83,84]. Emotions inferred from the text of the seller’scomments can predict the consumer’s perceived usefulness. Therefore, social review cues such asproduct ratings and textual comments on online reviews are important factors influencing consumerperceived value and purchasing decisions. Based on the above mentioned, the hypothesis is proposed:

Hypothesis 4a (H4a). Social review cues have a positive impact on consumer-perceived functional value underthe cross-border online shopping context.

Hypothesis 4b (H4b). Social review cues have a positive impact on consumer-perceived emotional value underthe cross-border online shopping context.

3.2.2. Perceived Value and Cross-Border Online Purchase Intention

Consumers’ purchase intention depends on the extent to which the perceived value of the productreaches their expectations [85]. The direct impact of perceived value on consumer purchase intentionshas been widely supported by theoretical and empirical researches [86,87]. Perceived value is amultidimensional concept. Many scholars discuss the influence of consumer perceived functionalvalue and emotional value on purchase intention. In a recent study, Ghanbari et al. [88] found thatfunctional and emotional values have a significant impact on consumer’s purchase intention. It isconsistent with the views of Hines and Bruce [89], Rubera et al. [90], Asshidin et al. [91], Lim et al. [92],and Koo et al. [42]. This study proposes that the perceived value of consumers plays a mediatingrole between external cues and cross-border online purchase intention under the cross-border onlineshopping context. The assumptions is based on the SOR model and clue utilization theory:

Hypothesis 5a (H5a). The consumer-perceived functional value has a positive impact on their purchaseintention in cross-border online shopping.

Hypothesis 5b (H5b). The consumer-perceived emotional value has a positive impact on their purchaseintention in cross-border online shopping.

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3.2.3. Adjustment Effect of Brand Familiarity

The effects of brand-related factors on trust and consumer judgment are well known in themarketing literature. Brand familiarity is a continuous variable that reflects the extent of a consumer’sdirect and indirect experiences with a brand or product [93]. Since consumers have a differentunderstanding of different products, numerous studies have shown that familiar brands have majoradvantages over unfamiliar brands in terms of processing and attitudes. Information about familiarbrands requires less efforts made by consumers to process, the information is more easily retrievedand stored, and consumers usually prefer these brands [94–96]. In particular, research suggeststhat well-established brands act as a powerful heuristic cue that influences purchase decisions [97].Familiar brands include many positive associations that guide consumers to judge whether a productor company is trustworthy [98], thus serving as a quality signal when it is impossible to directly testthe product [99,100]. The empirical results can be seen from the structural equation model that thedegree of familiarity with the brand will affect consumers’ confidence in the brand, thus affecting theirintention to purchase the same brand. Türkel et al. [101] revealed that familiar and unfamiliar brandshad no difference in consumers’ attitudes toward news, but have different responses to brand andpurchase intention.

Previous literature has shown that familiar brands enjoy more cognitive and affective advantages,because they can be recognized and identified more easily. In addition, a consumer’s attitude toward aspecific brand is affected by his/her familiarity with the brand. Therefore, the impact of brand familiarityshould be controlled when studying the impact of external cues on consumer value perception. Thisstudy believes that under the cross-border online shopping context, the higher the Chinese consumers’familiarity with the brand of imported goods is, the less stimulating and influential the external leadssuch as online promotion, content marketing, personalized recommendation, and social review are.Based on this, the hypothesis is proposed:

Hypothesis 6a (H6a). Under the cross-border online shopping context, the higher the consumer’s brandfamiliarity, the smaller the influence of the online promotion cue on the consumer-perceived functional value/emotional value.

Hypothesis 6b (H6b). Under the cross-border online shopping context, the higher the consumer’s brandfamiliarity, the smaller the impact of content marketing on consumer-perceived functional value/ emotional value.

Hypothesis 6c (H6c). Under the cross-border online shopping context, the higher the consumer’s brandfamiliarity, the smaller the impact of personalized recommendation cues on consumer-perceived functional value/emotional value.

Hypothesis 6d (H6d). Under the cross-border online shopping context, the higher the consumer’s brandfamiliarity, the less the influence of social review cues on the consumer-perceived functional value/ emotional value.

3.2.4. Control of Demographic Variables

Online shopping (or purchasing) behaviors tend to differ demographically among individuals [102].Consumer demographic attributes are typically represented by differences in age, gender, education,income, and nationality [103]. The importance of this demographic data has led previous studies toinvestigate the manner in which consumer demographic traits (e.g., age and gender) influence onlineshopping and cross-border online shopping [5,14,104–106].

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At present, cross-border online shopping by Chinese consumers has become a very commonphenomenon. In view of the differences between cross-border online shopping and domestice-commerce in terms of tariffs, international logistics, and product uncertainty, the impact ofdemographic variables on consumer’s cross-border online purchase intension will be significantlydifferent from that of domestic e-commerce. In order to control the interference of demographicvariables on relevant research hypotheses, this study used demographic variables such as gender, age,education, income, and occupation as control variables.

4. Methodology

4.1. Measurement Development

Based on previous research into online purchase intention, Perceived Functional Value, PerceivedEmotional Value, Brand Familiarity, Online Promotion Cues, Content Marketing Cues, PersonalizedRecommendation Cues and Social Review Cues, survey items for the measurement of each constructwere selected and a questionnaire including those items was developed. All items were measured on afive-point Likert scale, from strongly disagree to strongly agree.

The items in the questionnaire were developed by adjusting measures validated by otherresearchers or by converting the definition of the constructs into a questionnaire format. The constructsin this model were adapted from previous studies and multi-item scales were used for these constructs.Measurements of each construct were modified to fit the research background, and the Chineseversion of origin measurements were translated from the original, back-translated and adjustedfor cultural adaptation. Measures of Online Promotion Cues with four items were adapted fromNagadeepa et al. [62]. Personalized Recommendation Cues with five items were modified from Leeand Johnson [107] and Zhang et al. [79]. Content Marketing Cues with five items were adaptedfrom [108], Reid et al. [109], and Wang and Yang [63]. Social Review Cues with five items were adaptedfrom Animesh et al. [110] and Zhang et al. [79]. Perceived Functional Value and Perceived EmotionalValue with four items respectively, were adapted from Sweeny and Soutar [52], and Wu et al. [111].Cross-border Online Purchase Intention with four items were adapted from Animesh et al. [110]and Wu et al. [111]. Brand Familiarity with four items were adapted from Kent and Allen [94],Laroche et al. [112], and Wang and Yang [63]. Backward translation (with the material translated fromEnglish into Chinese, and back into English; versions compared; discrepancies resolved) was used toensure consistency between the Chinese and the English version of the instrument.

Questionnaire development contains multiple stages, in order to improve and restructure surveyinstrument. Initial version of the survey instrument was finished by four professors at the University fortesting in advance, each professor has significant professional knowledge of cross-border e-commerce.After obtaining the specialists’ feedback, we modified the wording and structure of measuring items.Then, the revised version was further pilot-tested on 21 participants who had extensive experience incross-border online shopping. The pilot group represented various workforce demographics, includingscholars, professionals, public servants, self-employed, and undergraduate. Finally, the revised versionwas further tested through an extensive pre-test with 86 responses who had experience in cross-borderonline shopping, the internal consistency and discriminant validity of the instrument were assessed.Due to low item-to-total correlation (less than 0.50), one item from Personalized RecommendationCues and one item from Social review Cues were dropped. The refined instrument, in the form of aself-administered questionnaire, was then used to collect the sample data.

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4.2. Data Collection

The survey of this study is for Chinese consumers who have experience in cross-border onlineshopping. In order to maximize a response rate, both online and offline surveys were conductedto collect data. To maintain external validity, data is sampled from various groups such as schools,companies, railway stations, and supermarkets. Data were collected at different times of the day(morning and afternoon) and during different days of the week (Monday through Saturday) to ensurethat the samples were representative and unbiased. The data collection process lasted for 8 weeks.

A total of 984 surveys were distributed, of which a total of 661 were returned (a response rate of67.2%). After eliminating 289 responses due to insincerity or incompleteness through data filtering,a sample of 372 usable responses was ultimately employed in our empirical analysis. The descriptivestatistics of the sample are listed in Table 1. Among 372 participants, 42.2% are males, 57.8% females,and 75.5% are below 35 years old. Most of the respondents have a bachelor’s degree or highereducation level. Furthermore, nearly 70% of respondents’ households spend between 200–1500 ¥(26–198 €/29–222 $) on online purchase, and only 4.3% of households spend less than 200 ¥ (26 €/29 $)a month on online purchase. We compared the significant differences in the proportion of differentattributes of demographic variables, such as gender, age, and education between the two samples. Theresults showed that differences are not significant.

Table 1. Descriptive statistics of respondent characteristics (N = 372, 1 ¥ is approximately equal to0.1326 €/0.1485 $, the minimum average monthly income in China is approximately equal to 1753 ¥(231 €/259 $)).

Demographics Category Count Offline Sample Online Sample Difference Test

GenderFemale 215 82 133 z = 0.576Male 157 66 91 p value = 0.448

Age

18–25 86 28 58 z = −0.44826–35 195 87 108 p value = 0.65436–45 69 25 44

46 or older 22 8 14

EducationHigh school or below 48 19 29 z = −0.727

Bachelor’s degree 265 102 163 p value = 0.468Master’s degree or above 59 27 32

Occupation

Government/institution 84 26 58 χ2(5) = 7.344Listed company employees 93 35 58 p value = 0.197

Unlisted company employees 111 51 60self-employed 19 11 8

Student 55 21 34Others 10 4 6

Monthlyincome

≤5000 ¥ 101 45 56 z = −1.3595001–10,000 ¥ 158 63 95 p value = 0.174

10,001–20,000 ¥ 93 33 60≥20,001 ¥ 20 7 13

Monthlyexpenditure on

onlineshopping

≤200 ¥ 16 9 7 z = −0.460201–500 ¥ 88 35 53 p value = 0.645

501–1500 ¥ 164 62 1021501–2500 ¥ 79 33 46≥2501 ¥ 25 9 16

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4.3. Data Analysis Technique

To test the proposed research model, the partial least squares structural equation modeling(PLS-SEM) was used as it is more flexible in terms of data requirements, model complexity andrelationship specification to validate a model compared to covariance-based structural equationmodeling (CB-SEM) techniques. PLS-SEM is also considered to be an appropriate statistical toolfor theoretical exploration, and our research uses it. Path significance was assessed using bootstrapstatistics with a total of 5000 resamples and 372 samples. The moderating relationship was evaluatedusing the product indicator method first developed by Kenny and Judd (1984), and later implementedin PLS by Chin et al. [113]; that is, interaction terms were created by multiplying the indicators ofthe predictor and moderator constructs. Each moderator and predictor indicator was centered beforeperforming multiplication.

Smart PLS Version 3.26 is used in this analysis.

5. Analysis and Results

5.1. Measurement Model

Following the proposed two-stage analytical procedures, the confirmatory factor analysis wasfirst performed to evaluate the measurement model; then the structural relationships were examined.To validate our measurement model, we evaluated three types of validity, namely content validity,convergence validity, and discriminant validity. Content validity was determined by ensuringconsistency between the measurement items and existing literature. This was done by interviewingexperienced practitioners and pilot-testing the instrument.

Convergent validity was assessed by examining the internal consistency, composite reliabilityand average variance extracted from the measures. Cronbach’s alpha and factor loading were used tocalculate the internal consistency (reliability) of items used to measure each of the constructs featuredin the study. According to MacKenzie et al. [114], the Cronbach’s alpha value should be higher than0.7 and factor loadings should be greater than 0.7 for the scale to be considered reliable. As shown inTable 2, Cronbach’s alpha values of the constructs ranged from 0.722 to 0.821, all the loadings of themeasures in our research model are above 0.7, which indicates satisfactory internal consistency forconfirmation purposes. Although many studies employing PLS-SEM have used 0.5 as the thresholdreliability of the measures, 0.7 is a recommended value for a reliable construct. As shown in Table 2,the composite reliability values range from 0.827 to 0.882. For the average variance extracted (AVE) bya measure, a score of 0.5 indicates acceptability. Table 2 shows that the average variances extractedby measures range from 0.545 to 0.652, which are above the acceptability value. These test resultsdemonstrate good convergent validity.

The discriminant validity of the instrument was verified by observing the square root of theaverage variance. The results in Table 3 confirm the discriminant validity: The square root of theaverage variance extracted for each construct is greater than the levels of correlations involving theconstruct. Finally, all items are well loaded onto their own construct, but poorly on other constructs.All of these test results suggest good discriminant validity.

In addition to validity assessment, multicollinearity was also checked due to the relatively highcorrelations among some variables (e.g., a correlation of 0.687 between PR and PFV). The resultantvariance inflation factor (VIF) values for all of the constructs are acceptable (i.e., between 1.609and 1.982).

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Table 2. Construct reliability and validity.

Constructs Measure Items Factor Loading

Online PromotionCues

There are many forms of promotion on cross-bordere-commerce platforms 0.772

The promotion of merchandise on cross-border e-commerceplatforms is very strong 0.701

Promotion of imported goods on cross-border e-commerceplatforms is frequent 0.736

Cross-border e-commerce platform provides enoughmerchandising information 0.809

Content MarketingCues

content marketing on cross-border e-commerce platformsmake me feel more familiar with imported goods 0.749

content marketing on cross-border e-commerce platforms areuseful to me 0.709

I will pay special attention to content marketing oncross-border e-commerce platforms 0.730

content marketing on cross-border e-commerce platforms canimpress me 0.780

I will trust content marketing on the cross-bordere-commerce platform 0.765

PersonalizedRecommendation

Cues

CBOS platform knows what I want 0.798CBOS platform understands my needs 0.718

I like the products recommended by CBOS platforms 0.746does a pretty good job guessing what I want and

making suggestions 0.731

Social Review Cues

get a good impression of other residents/avatars in thevirtual world 0.742

develop good social relationships with othercommunity members 0.768

feel like part of the virtual world community 0.775willing to share my own shopping experiences with my friends 0.736

Perceived FunctionalValue

CBOS has good functions 0.748CBOS is reliable 0.756

CBOS fulfills my needs well 0.702CBOS is well provided 0.784

Perceived EmotionalValue

CBOS would help me to feel acceptable 0.784CBOS would make me want to use it 0.757CBOS is the one that I would enjoy 0.837

CBOS is the one that I would feel relaxed about using 0.848

Cross-border OnlinePurchase Intention

I will seriously consider purchasing imported goods fromcross-border e-commerce platforms 0.752

I am willing to buy imported goods on the cross-bordere-commerce platform 0.766

I will now buy imported goods on the cross-bordere-commerce platform. 0.796

I will buy imported goods on the cross-border e-commerceplatform within six months 0.775

Brand Familiarity

I often see ads for product brands recommended bycross-border e-commerce platforms 0.736

I often see the display and recommendation of commoditybrands recommended by cross-border e-commerce platforms 0.764

I often hear other people discuss the brand of goodsrecommended by cross-border e-commerce platforms 0.722

I often buy product brands recommended by cross-bordere-commerce platforms 0.730

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Table 3. Correlation between Constructs.

Cronbach’sAlpha

CompositeReliability OP CM PR SR PFV PEV CBOPI BF

Online Promotion (OP Cues) 0.750 0.841 0.756 a

Content Marketing (CM Cues) 0.802 0.863 0.545 0.747

Personalized Recommendation (PR Cues) 0.739 0.836 0.558 0.632 0.749

Social Review (SR Cues) 0.751 0.842 0.541 0.571 0.545 0.755

Perceived Functional Value (PFV) 0.737 0.836 0.589 0.644 0.687 0.620 0.748

Perceived Emotional Value (PEV) 0.821 0.882 0.495 0.528 0.614 0.557 0.630 0.807

Cross-border Online Purchase Intention(CBOPI) 0.775 0.855 0.474 0.632 0.670 0.532 0.733 0.646 0.772

Brand Familiarity (BF) 0.722 0.827 0.580 0.671 0.634 0.660 0.705 0.588 0.656 0.738

Note: a Diagonal elements represents square-root of AVE (average variance extracted).

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5.2. Structural Model

With an adequate measurement model and an acceptable level of multicollinearity, the proposedhypotheses are tested with PLS. The results of the analysis are depicted in Figure 2. The modelexplains 59.4 percent of the variance in cross-border online purchase intention, 60.5 percent of thevariance in perceived functional value, and 46.3 percent of the variance in perceived emotional value.Henseler et al. [115] introduced the SRMR (standardized root mean square residual) as a goodness offit measure for PLS-SEM that can be used to avoid model misspecification. A value less than 0.10 or of0.08 (in a more conservative version) are considered a good fit. The SRMR of final estimated model areequal to 0.070, which indicates that the model has a “good fit”.Sustainability 2019, 11, x FOR PEER REVIEW 14 of 23

Figure 2. Results of PLS Analysis. **p < 0.05; ***p < 0.01.

As shown in Figure 2, H1a, H2a, H3a and H4a which state that external cues such as online promotion, content marketing, personalized recommendation, and social review positively affect the perceived value of cross-border online consumers, are all supported (β = 0.160, 0.216, 0.337, and 0.226, t = 3.578, 3.987, 6.363, and 4.293).

H1b, H3b and H4b which state that external cues such as online promotion, personalized recommendation and social review positively affect the perceived emotional value of cross-border online consumers, are all supported (β = 0.127, 0.394 and 0.274, t = 2.484, 6.728 and 4.749). While, H2b which states that content marketing cues affect the perceived emotional value of cross-border online consumers is not supported.

H5a and H5b which state that perceived functional value and perceived emotional value positively affect consumers’ cross-border online purchase intention, are also supported (β = 0.541 and 0.306, t = 10.907 and 5.987).

H6a, H7a, H8a and H9a are supported. The results show that Brand Familiarity negatively moderate the relationship between Online Promotion Cues/Content Marketing Cues/Personalized Recommendation Cues/Social Review Cues and Perceived Functional Value. H6b and H9b were also supported. The results show that Brand Familiarity negatively moderate the relationship between Online Promotion Cues / Social Review Cues and Perceived Emotional Value.

To determine whether the significant moderating effects are substantive, R-square changes resulting from the interaction effects should be examined [116], specifically through the F-test. Table 4 and Table 5 provide the F-test and the effect size results by running nested (hierarchical) models. The results show that the interaction effects increased R² significantly, confirming the significance of the moderating effects hypothesized by H6a, H7a, H8a, H9a, H6b, and H9b.

online promotion

content marketing

personalized recommendation

social review

consumer-perceivedfunctional value

consumer-perceivedemotional value

cross-border onlinepurchase intention

gender

age education income

0.394***

R2 = 0.463

R2 = 0.605

R2 = 0.594

occupation expenditurebrand familiarity

Figure 2. Results of PLS Analysis. **p < 0.05; ***p < 0.01.

As shown in Figure 2, H1a, H2a, H3a and H4a which state that external cues such as onlinepromotion, content marketing, personalized recommendation, and social review positively affect theperceived value of cross-border online consumers, are all supported (β = 0.160, 0.216, 0.337, and 0.226,t = 3.578, 3.987, 6.363, and 4.293).

H1b, H3b and H4b which state that external cues such as online promotion, personalizedrecommendation and social review positively affect the perceived emotional value of cross-borderonline consumers, are all supported (β = 0.127, 0.394 and 0.274, t = 2.484, 6.728 and 4.749). While, H2bwhich states that content marketing cues affect the perceived emotional value of cross-border onlineconsumers is not supported.

H5a and H5b which state that perceived functional value and perceived emotional value positivelyaffect consumers’ cross-border online purchase intention, are also supported (β = 0.541 and 0.306,t = 10.907 and 5.987).

H6a is supported. The results show that Brand Familiarity negatively moderate the relationshipbetween Online Promotion Cues/Content Marketing Cues/Personalized Recommendation Cues/SocialReview Cues and Perceived Functional Value. H6b was also supported. The results show that BrandFamiliarity negatively moderate the relationship between Online Promotion Cues/Social Review Cuesand Perceived Emotional Value.

To determine whether the significant moderating effects are substantive, R-square changesresulting from the interaction effects should be examined [116], specifically through the F-test.Tables 4 and 5 provide the F-test and the effect size results by running nested (hierarchical) models.

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The results show that the interaction effects increased R2 significantly, confirming the significance ofthe moderating effects hypothesized by H6a and H6b.

Table 4. Hierarchical regression results.

Dependent Variable: Perceived Functional Value

Model 1 Model 2 Model 1 Model 2 Model 1 Model 2 Model 1 Model 2

OP Cues 0.271 *** 0.245 ***CM Cues 0.312 *** 0.279 ***PR Cues 0.401 *** 0.371 ***SV Cues 0.274 *** 0.265 ***

BF 0.548 *** 0.509 *** 0.497 *** 0.475 *** 0.451 *** 0.434 *** 0.525 *** 0.491 ***OP Cues*BF −0.143 ***CM Cues*BF −0.121 **PR Cues*BF −0.099 **SV Cues*BF −0.108 **

R2 0.546 0.563 0.551 0.563 0.594 0.602 0.540 0.550∆R2 0.017 *** 0.012 ** 0.008 ** 0.010 **

Note: * p < 0.05, ** p < 0.01, *** p < 0.001.

Table 5. Hierarchical regression results.

Dependent Variable: Perceived Emotional Value

Model 1 Model 2 Model 1 Model 2 Model 1 Model 2 Model 1 Model 2

OP Cues 0.234 *** 0.216 ***CM Cues 0.247 *** 0.230 ***PR Cues 0.327 *** 0.321 ***SV Cues 0.384 *** 0.296 ***

BF 0.448 *** 0.421 *** 0.419 *** 0.408 *** 0.407 *** 0.397 *** 0.304 *** 0.352 ***OP Cues*BF −0.102 *CM Cues*BF −0.063PR Cues*BF −0.033SV Cues*BF −0.100 *

R2 0.382 0.387 0.376 0.379 0.441 0.442 0.394 0.403∆R2 0.009 * 0.003 0.001 0.009 *

Note: * p < 0.05, ** p < 0.01, *** p < 0.001.

In addition, as shown in Figure 2, among the demographic variables, only age, education, andincome have a significant impact on Chinese consumers’ cross-border online purchase intention.Gender, occupation, and monthly online shopping spending have no significant impact on cross-borderonline purchase intention. For the elderly, the education level is graduate and above, and the monthlyincome exceeds 20,000. The intention of cross-border online shopping is not strong. Perhaps theseconsumers lack cross-border online shopping experience or skills, or have a better purchasing channelfor imported goods than online shopping.

The moderating effects of gender and income (the comparison of Under 10,000 ¥ (1317 €/1476 $)and Over 25,000 ¥ (3294 €/3690 $)) are conducted by comparing the path loadings across two groups.The multi-group analysis approach is used to assess the moderating effects. As shown in Table 6,gender and income have no significant effect on the model overall as a moderating variable. The resultsalso indicate robustness of the proposed model. Further, the cross-border online purchase intentiondoes not increase consistently with age, education, or income.

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Table 6. Results of multi-group analysis.

Gender: Group(M)—Group(F) Income: Group(high)—Group(low)

Difference t p Difference t p

PFV<—OP 0.239 2.525 0.012 0.068 0.629 0.530PEV<—OP 0.023 0.231 0.818 0.019 0.163 0.871PFV<—CM 0.043 0.416 0.678 0.111 0.925 0.356PFV<—PR 0.113 1.123 0.262 0.030 0.255 0.799PEV<—PR 0.033 0.295 0.768 0.004 0.027 0.979PFV<—SV 0.065 0.654 0.513 0.168 1.470 0.142PEV<—SV 0.033 0.295 0.768 0.004 0.027 0.979

CBOPI<—PFV 0.062 0.623 0.534 0.130 1.284 0.200CBOPI<—PEV 0.014 0.136 0.892 0.124 1.157 0.248

In order to compare and analyze the influence of four cross-border online shopping context cues onconsumers’ intention to purchase, the Bootstrap method (n = 5000) is used to estimate the impact of fouronline shopping context cues on consumers’ purchase intention and conduct significant test. It can befound from Table 7 that online promotion cues, content marketing cues, personalized recommendationcues, and social review cues have significant positive effects on consumers’ cross-border online purchaseintentions, but the degree of influence of different factors is significantly different. The influence ofpersonalized recommendation cues and social review cues on consumers’ cross-border online purchaseintension is significantly higher than that of online promotion cues and content marketing cues toconsumers’ cross-border online purchase intension. In addition, the impact of four online shoppingcontext cues on consumers’ cross-border online purchase intension needs to be transmitted throughmediation variables. Further comparing the mediating effect of the two mediator variables on the pathof online shopping context cues to consumers’ purchase intension. It can be seen from Figure 2 that themediating effects of perceived functional value and perceived emotional value are significantly different.The mediating effect of perceived functional value (normalized estimate of 0.510) is significantly higherthan the mediating effect of perceived emotional value (normalized estimate is 0.211).

Table 7. Mediation effect analysis.

Total Effects Direct Effects Indirect Effects t p Value

OP Cues—>CBOPI 0.120 - 0.120 3.526 0.000CM Cues—>CBOPI 0.147 - 0.147 3.682 0.000PR Cues—>CBOPI 0.291 - 0.291 6.879 0.000SV Cues—>CBOPI 0.198 - 0.198 5.106 0.000

6. Discussion, Implications, and Limitations

6.1. Conclusion and Enlightenment

In order to analyze the influence of external cues on consumers’ cross-border online purchaseintention, this paper constructs a conceptual model of extrinsic cues —> perceived value —>

cross-border online purchase intention based on clue utilization theory and SOR model. Basedon the effective questionnaire collected from 372 Chinese cross-border online shopping consumers, themodel proposed by this research is verified, and the following conclusions are further obtained:

(1) Through the intermediary transmission of perceived value, online shopping context cueshave a significant impact on consumers’ cross-border online purchase intension. In terms of theimpact of external cues on cross-border online purchase intension, the impact exerted by personalizedrecommendation cues ranks first, that by social review cues second, and that by content marketingcues and online promotion cues rank last. From the numerical estimation of the impact effect, the effect

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of personalized recommendation seems to be significantly higher than content marketing and onlinepromotion, and the difference effect between the latter two is not obvious.

(2) In terms of the mediating effect of perceived function value and perceived emotional value, themediating effect of perceived functional value and perceived emotional value is significantly differentin numerical value. The mediating effect of perceived functional value far exceeds the intermediaryof perceived emotional value effect. It shows that for online consumers, first, they hope the processof purchasing goods online is simple, and the second is to enjoy the pleasure of online shopping.Consumers who buy imported goods on cross-border e-commerce platforms not only obtain excellentquality, but also seek the satisfaction of emotional and social needs. The online shopping brings thempleasure and enjoyable emotional experience, to which some extent will also stimulate their purchaseintention. Similarly, because of the younger Internet consumers, they tend to pursue new things,curiosity but lack of patience. It is difficult to spend a long time to browse a website carefully, so thesimple and efficient shopping process will arouse their intention to purchase.

(3) Brand familiarity has a certain negative adjustment effect between external cues and cross-borderonline purchase intention. The higher the consumer’s familiarity with the brand, the less influential theexternal cues such as online promotion cues, content marketing cues, personalized recommendationcues, and social review cues on the perceived function value, and the influence of social review andonline promotion cues on perceived emotional value are.

The four external cues discussed in this paper that influence consumer cross-border onlinepurchase intention further complement Gefen [13], Gomez-Herrera et al. [11], Cardona et al. [9],Giuffrida et al. [15], and Valarezo et al. [5] and other consumers who study the constraints ofcross-border e-commerce. The conclusions about Chinese consumers’ cross-border online purchaseintention are consistent with the results of PayPal (2018) [2] and AliResearch (2015) [6] on cross-borderonline shopping consumers in China.

This study verifies the extrinsic cues —> perceived value —> cross-border online purchaseintention model based on perceived functional value and perceived emotional value. It has a positivereference value in helping cross-border online shopping providers improve marketing services andreduce psychological distance from customers [15,16]. As cross-border online shopping has a greateruncertainty than domestic online shopping, the primary purpose of Chinese consumers to cross-borderonline shopping is to buy high-quality overseas goods that meet their expectations, and secondlyto enjoy the fun of cross-border online shopping. In order to improve consumers’ perception of thevalue of various product recommendation information and further enhance consumers’ intentionto cross-border online shopping, cross-border e-commerce platforms and sales companies need todesign marketing plans that match the cross-border online shopping contexts. In other words, forthe cross-border online shopping characteristics and purchase intention of Chinese consumers, moreemphasis should be placed on the marketing method of personalized product recommendation, andthe content display of personalized recommendation information needs to be targeted accordingto cross-border online shopping contexts. Social e-commerce is gaining momentum, and Chineseconsumers are more likely to believe in other users’ shopping experiences and online reviews whenthey are engaged in cross-border online shopping. Therefore, cross-border online shopping platformsand sales companies should shape and maintain their good reputation among consumers. Consumersreading content marketing on cross-border e-commerce platforms are not just spending time for fun,but getting useful information about goods and make faster shopping decisions. Therefore, contentmarketing for cross-border online shopping should highlight the scientific popularity and knowledgeof content, rather than fun and entertainment. Cross-border online shopping consumers generallyhave relatively higher incomes, richer online shopping experience and skills, and most of them arenot price-sensitive consumers. Therefore, the traditional retail environment and the price promotionmethods commonly used in the domestic e-commerce environment are significantly less effective incross-border online shopping contexts. Many Chinese consumers do not have rich cross-border onlineshopping experience, and their skills in international logistics, cargo clearance, customs withholding,

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foreign language exchange are relatively weak. They are foreign products that are not familiar toChinese consumers. Promotions on cross-border e-commerce platforms, content marketing andrecommendations from friends will allow consumers to experience the value and fun of cross-borderonline shopping. Therefore, understanding and predicting consumer’s purchase intention has becomean important goal for cross-border e-commerce sustainability. This study has great enlightenment forthe sustainable development of cross-border e-commerce:

(1) Promotion is indispensable. The most important difference between online shopping andtraditional offline shopping is the price advantage, which needs to be firmly grasped by cross-bordere-commerce platforms. In order to enhance consumers’ intention to purchase, we can use somepromotional means, such as discounts, group-building, and so on. Continuous use of a variety ofinnovative promotional means to immerse consumers, satisfy personalized preferences, and thenenhance the intention to purchase.

(2) Scientific application of advertising strategies to enhance the effectiveness of content marketing.Content marketing is the most widely used way of communication in the world. Appropriate contentmarketing can enhance the brand image of enterprises and products. Content marketing, as the mostcommon advertisement on cross-border e-commerce platforms, should strictly control the quality of itscontent. Content marketing should combine the content of the article with the advertisement perfectly,and output more objective, comprehensive, and valuable commodity information as far as possible.

(3) Customized shopping experience. In the era of information explosion, personalized servicehas penetrated into all aspects of our lives. This is especially true for cross-border e-commerceplatforms, which provide consumers with tailor-made commodity information and services. Bigdata analysis technology is a powerful weapon to provide personalized services for consumers.Cross-border e-commerce platform grasps consumers’ personal information and behavior preferencedata. Cross-border e-commerce platform can use these data to build a proprietary model for eachconsumer’s shopping behavior, and provide recommendation services to meet their shopping needsand even potential shopping needs.

(4) The integration of social e-commerce. The process of communicating among consumerscan relax their mind and body and make shopping more pleasant. At the same time, youngeronline consumers are willing to keep up with the trend of fashion. When they see many consumersrecommending a product to themselves on cross-border e-commerce platform, “conformity psychology”and “social identity” will stimulate purchase intention, thus speeding up shopping decision-makingtime. Therefore, cross-border e-commerce platform needs to design such a function of social interactiveamong consumers.

(5) Consumer-perceived functional value has the greatest impact on their purchase intention,followed by consumer-perceived emotional value. Therefore, cross-border e-commerce platform shouldfirstly try to find effective online shopping context clues to improve consumer-perceived functionalvalue for stimulating the consumers’ purchase intention. This requires cross-border e-commerceplatforms to focus on improving the consumers’ purchasing efficiency when creating online shoppingcontext clues, so that they can obtain as much useful commodity information as possible in a short time.

6.2. Research Limitations

There are still some limitations and shortcomings in this paper that need to be improved in thefuture. First, as an exploratory study of structural equation modeling based on principal componentmethod, the advantage of PLS-SEM lies in its causality prediction. But as for the discussion of the fittingeffect of structural model, PLS-SEM is not as good as the traditional structural equation model whichis based on covariance. Therefore, more theoretical research is needed on the theoretical universality ofthe consumer purchase intention research framework for cross-border e-commerce platforms. Secondly,the interpretation effect of the “Online Context Cues —> Perceived Value —> Consumer PurchaseIntention” model established by this research, although reaching the proposed criteria, requiresfurther explorations for other explanations from the perspective of causality prediction. Third, the

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study validated the reliability and validity of measurement tools such as online promotions, contentmarketing, perceived functional value, and perceived emotional value based on sample data from86 pre-tested investigators and 372 formal investigators. In view of the large scale, wide distributionand many characteristics of individual social attributes in China, especially in the cross-border onlineshopping context, there are few tools presented to Chinese consumers for reference. Therefore,several important measurement questionnaires proposed in this study need to be further verified by alarger-scale, range-based random sample survey.

Author Contributions: Conceptualization, L.X. and F.Y.; Data curation, L.X. and F.Y.; Formal analysis, F.G. and F.Y.;Funding acquisition, L.X.; Investigation, S.L.; Methodology, L.X. and F.Y.; Project administration, L.X.; Resources,S.L.; Software, F.Y. and S.L.; Supervision, F.G. and F.Y.; Validation, F.G. and F.Y.; Visualization, F.Y. and S.L.;Writing—original draft, L.X., F.Y. and S.L.; Writing—review & editing, F.G. and F.Y.

Funding: This research was supported by the Major Project of Humanities and Social Sciences in University ofZhejiang Province, China, grant number No. 2016GH024.

Conflicts of Interest: The authors declare no conflict of interest.

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