Understanding consumers’ paths to webrooming: A complexity approach

Journal of Retailing and Consumer Services 53 (2020) 101991

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Understanding consumers’ paths to webrooming: A complexity approach Eugene Cheng-Xi Aw Department of Management and Marketing, Universiti Putra Malaysia, Malaysia

A B S T R A C T

Webrooming (practice whereby products are researched online before making an offline purchase) has been recognized as a prevalent form of cross-channel shopping behavior. Grounded in complexity and configuration theories, this study examines how different causal conditions determine webrooming intention. Required data was obtained from a purposive sample through paper surveys, and was analyzed using fuzzy-set qualitative comparative analysis (fsQCA). The findings reveal three configurations in which different combinations of product, consumer, and channel factors may interact in different ways to explain high webrooming intention. Notably, product involvement was identified as the core condition in all configuration paths. This study enriches the theoretical foundations of webrooming behavior, and the findings yielded are expected to assist retailers in developing better-targeted strategies in dealing with this increasingly prevalent cross-channel behavior.

1. Introduction The ever-increasing retailing mix, together with more versatile consumer expectations, necessitates retailers to adopt the multi-channel business model (Verhoef et al., 2015). Just as traditional retailers have started to offer their products via online channels, pure play online re­ tailers, including the e-tailing giant Amazon, have started to embrace the click-to-brick strategy by opening more physical stores. Modern consumers increasingly leverage both online and offline channels in a complementary manner to achieve an optimal shopping experience. For instance, they can visit brick-and-mortar stores to search for information and make their final purchase online, thereby exhibiting behavior known as showrooming. Conversely, consumers can conduct information search online, but make the final purchase at brick-and-mortar stores, thus engaging in webrooming. Webrooming is rapidly becoming a prevalent cross-channel behavior across the globe. Not only do the majority of U.S. and European online users engage in webrooming behavior, Asian shoppers are increasingly resorting to this practice (eMarketer, 2014; Nielsen, 2016). Based on a Deloitte report, digital-influenced offline sales reached 56% in 2016 and a further upside was expected over the following years (Simpson et al., 2016), which thus presents a rather surprising finding, especially in the current environment where online commerce prevails. In fact, the rise of webrooming has resulted in the loss of customers and massive sales for online retail giants, such as AliExpress and Amazon (Ecommerce nation, 2019). Correspondingly, many online retailers are facing an undesirably low conversion rate from high online store traffic, suggesting that webrooming behavior has become a threat to pure play online retailer (Aw, 2019; Chew, 2018).

Although webroomers are potentially valuable to retailers, as they tend to purchase more products and spend more, webrooming is also �n et al., 2019; Van Baal and associated with free-riding behaviors (Flavia Dach, 2005). Cross-channel free-riding is the term used to refer to a phenomenon which consumers tend to switch retailers during the channel switching process (Heitz-Spahn, 2013). In this vein, multi­ channel retailers risk losing sales if they failed to lock in customers during the course of switching channel. Consequently, offline retailers have emerged as the sole beneficiary of webrooming, as the final pur­ chase is made in physical stores. However, offline retailers do need strategies to proactively capture webroomers and prevent them from heading to competitors’ physical stores. Thus, whether the aim is to cater, foster, or discourage webrooming behavior, it is vital to understand consumers and the factors that determine their channel choice. When introducing the notion of multi­ channel customer management, Neslin et al. (2006) stressed the un­ derstanding of consumers as the foundation for establishing successful multichannel marketing strategies. In a similar vein, Lemon and Verhoef (2016) stressed that future research efforts should be directed to building forward-looking models considering both consumer- and channel-related factors in understanding what drives webrooming. However, while ample body of research has been conducted on show­ rooming (Arora et al., 2017; Gensler et al. 2017; Rapp et al., 2015), webrooming remains insufficiently explored despite its importance to �n et al., 2016; Santos and Gonçalves, 2019). retailer performance (Flavia To address this gap in pertinent literature, the present study aims to elucidate the causal conditions motivating webrooming intention from the joint perspective of the consumer-, product-, and channel-related factors. To this end, complexity and configuration theory was adopted

E-mail address: [email protected]. https://doi.org/10.1016/j.jretconser.2019.101991 Received 6 August 2019; Received in revised form 25 October 2019; Accepted 1 November 2019 Available online 14 November 2019 0969-6989/© 2019 Elsevier Ltd. All rights reserved.

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Journal of Retailing and Consumer Services 53 (2020) 101991

€la € et al., 2018). channel preferences should never be overlooked (Yrjo Given that the authors of prior shopping—either webrooming or showrooming—literature have mostly overlooked the role of consumer traits despite their relevance, this presents an important gap to be �ndez et al., 2018). addressed (Arora and Sahney, 2019; Aw, 2019; Ferna It is also increasingly recognized that product characteristics repre­ sent an important determinant in the context of shopping channel se­ lection (Chocarro et al., 2013; Haridasan and Fernando, 2018; Schmid and Axhausen, 2019). For example, Schmid and Axhausen (2019) revealed that consumers prefer to purchase goods that may vary in quality (such as groceries) in physical stores, while resorting to the online channel for acquiring electronic appliances. Thus, Santos and Goncalves (2019) argued that product type could potentially explain the contradictory evidence regarding the “need for touch” effect on webrooming behavior. However, most authors of previous studies on this topic failed to account for product characteristics when examining cross-channel behaviors such as webrooming.

as the research framework and gathered data was subjected to fuzzy-set qualitative comparative analysis (fsQCA). Such an approach has rarely been used to investigate the webrooming phenomenon, despite its ability to offer a more nuanced and comprehensive view (Santos and Gonçalves, 2019). Unlike traditional regression-based approaches, fsQCA allows the assessment of causal asymmetry and equifinality, multifinality, and conjunctural causation (Woodside, 2018). Re­ searchers have contended that human behavior is unlikely to follow an antecedent outcome symmetry stance (Schmitt et al., 2017). Corre­ spondingly, as shown by Santos and Gonçalves (2019), webrooming behavior is driven by and better explained through multiple motiva­ tional configurations. The remainder of this paper is organized as follows. After providing a brief literature review, the conceptual development of predictors of webrooming intention is delineated. This is followed by the research methodology and the empirical results. After discussing the key findings, their theoretical and practical implications are outlined, before offering some suggestions for future research directions.

3. Conceptual development

2. Literature review

3.1. Information processing and uncertainty reduction theories

2.1. Webrooming

In order to determine the key factors influencing consumers’ �n et al.’s (2016) research approach was webrooming intentions, Flavia adopted as a theoretical foundation, focusing on the information pro­ cessing and uncertainty reduction theories. Prior research in which in­ formation processing theory was adopted substantiates the prevalent view that consumers perform comprehensive information searches in order to increase their confidence in the correctness of their purchasing decisions (Flavi� an et al., 2016; Tormala, Rucker, and Seger, 2008). Likewise, according to the uncertainty reduction theory postulates, as new relationships are characterized by high level of uncertainty, rela­ tionship partners seek to acquire more information as a means of un­ certainty reduction (Berger, 1987). In the shopping context, uncertainty reduction motivates consumers to use both online and offline channels with the aim of making right choices (Flavi� an et al., 2016). Webroomers spend extra efforts to seek product information online in before making their purchase decision (Fern� andez et al., 2018). For this purpose, both online and in-store consumers turn to online reviews, for they believe that they are more objective and thus more trustworthy than commercial advertising (Flavi� an et al., 2016; Lee and Jin Ma, 2012; Li, Li, Tayi, and Cheng (2019)). In particular, online reviews allow �n consumers to be more confident with their offline purchases (Flavia et al., 2016). Consequently, perceived usefulness of online reviews is hypothesized in the present study to contribute in explaining webrooming intention. Even though online channel offers significant informational benefits, its inherent characteristics contribute to uncertainty related to product quality (Santos and Goncalves, 2019). In particular, it is posited that consumers who value interactions with in-store salespeople and need to inspect products before making their purchases would be reluctant to shop online and are more likely to engage in webrooming as a means of increasing their confidence in their product choices (Arora and Sahney, �n et al., 2016; Keeling et al., 2007). Hence, the aforemen­ 2019; Flavia tioned consumer traits, namely need for touch and need for interaction are posited as causal conditions of webrooming intention. Grounded in the 3M model (Mowen, 2000), it is argued that con­ sumer traits (i.e., need for touch) are situational and their effects may vary depending on product characteristics (Gehrt & Yan, 2004). In a similar vein, Santos and Goncalves (2019) argued that both product category and consumer traits should be examined as factors contributing to webrooming. In an earlier study, Heitz-Spahn (2013) found that cross-channel behavior is closely linked to the type of product con­ sumers intend to purchase. These findings were subsequently confirmed by Kim, Libaque-;Saenz, and Park (2018). On top of that, the cognitive fit theory indicates that consumers seek information source that best fit

In the existing webrooming literature, researchers tended to explain webrooming in terms of channel-related benefits and costs (Arora and Sahney, 2018, 2019; Aw, 2019). For example, based on their research grounded in the theory of planned behavior and technology acceptance model, Arora and Sahney (2019) indicated that the key attributes of online channel, namely low search cost and high purchase risk, increase webrooming intention. Similarly, Reid et al. (2016) revealed that, as online channel does not permit full garment evaluation, the perceived risk encourages webrooming behavior. Conversely, offline channel al­ lows consumers to inspect the product physically and acquire it imme­ diately, which not only reduces uncertainty but also meets the need for instant gratification, thereby facilitating webrooming (Arora and Sah­ ney, 2019; Aw, 2019). In another research stream, antecedents of webrooming have been explored from the perspective of consumer motivations, such as price comparison and information seeking. Santos and Gonçalves (2019) found that consumers mainly utilize webrooming for information pro­ cessing (i.e., price comparison) and uncertainty reduction (i.e., choice confidence). These authors reported a rather surprising finding that need to physically inspect products is insignificant in explaining webrooming behavior. However, it is important to note that their research focused a single product category. Kang (2018), on the other hand, revealed that webrooming is motivated by social interaction, which is facilitated by the exchange of messages and comments with the virtual community, while subsequent purchase in a physical store meets the need for salient presence of others, such as salespeople and other customers. 2.2. Gaps in the extant literature In the extant literature on multi- and cross-channel shopping behavior, an economic perspective tends to predominate. Most re­ searchers assume that consumers rationally evaluate the channel-related benefits and costs during different phases of shopping, and choose the most optimal channel combination, i.e., the one that minimizes inputs (i. e., time and effort) and maximizes outputs (i.e. right purchase, shopping �n, Gurrea, and Orús, 2019). To further advance the un­ value) (Flavia derstanding of webrooming behavior, consumer-, product-, and channel-related factors are considered jointly in the present study. This approach was adopted, as empirical evidence indicates that individual differences like dispositional traits can influence consumers’ shopping channel preferences (Cho and Workman, 2015; Dholakia et al., 2010). Hence, the fact that consumers are heterogeneous in shopping 2

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Journal of Retailing and Consumer Services 53 (2020) 101991

3.5. Need for touch

with their purchasing task (i.e., purchase of different products) (Vessey & Galletta, 1991), implying that online reviews may be exceptionally useful in certain purchase situation. However, authors of extant studies tended to examine single product category, failing to account for moti­ vational differences. Hence, in-depth understanding of webrooming intention necessitates consideration of all aforementioned conditions and their non-linear relationships.

The importance of sense of touch has been extensively studied, and the available findings indicate that consumers rely on information ob­ tained through the sense of touch when making certain purchases (Dholakia et al., 2010; Peck and Childers, 2003). Preference for more complete information acquired through haptic system relates directly to the “need for touch” concept (Peck and Childers, 2003). As a result, need for touch has emerged as an important topic in cross-channel behavior �n et al., 2016). The important functionalities of touch research (Flavia and feel are absent from online channel, rendering product evaluation difficult. As a result, consumers need to resort to offline sources for further inspection (Dholakia et al., 2010). This has led to webrooming, as consumers with high need for touch can gain relevant information online, while visiting physical stores for a sense of reassurance, which also enhances their shopping enjoyment (Kim et al., 2018). Thus, high need for touch can be viewed as a vital condition of webrooming behavior (Arora and Sahney, 2018, 2019).

3.2. Product involvement According to Zaichkowsky (1985), product involvement refers to “the perceived relevance of the object based on inherent needs, values, and interests” (p. 342). In general, consumers tend to be more involved in the purchase process when the products are important, relevant, or expensive. Available evidence also indicates that consumers rely on different shopping channels when purchasing such so-called “high-­ involvement” products (Frasquet et al., 2015). In other words, when their informational needs are significant, consumers will try to obtain additional product information online to reduce purchase risk, and will �n et al., subsequently shift to physical channels for reassurance (Flavia 2016, 2019). Similarly, Voorveld et al. (2016) argued that online and offline channels offer complementary benefits for consumers seeking to purchase high-involvement products. For instance, in their conceptual study, Arora and Sahney (2019) proposed that consumers resort to on­ line channel for obtaining additional information before purchasing high-involvement products via offline channels.

3.6. Perceived usefulness of online reviews As previously noted, uncertainty reduction theory provides the �n foundation for examining the reasons behind webrooming (Flavia et al., 2016; Santos and Gonçalves, 2019). In the present study, this theoretical proposition was adopted to test whether perceived useful­ ness of online reviews is a potentially relevant motivation to webroom. Online reviews are perhaps the most relevant source of information in today’s retail environment, especially for the current generation of consumers. Online reviews allow consumers to understand products’ function and features, and compare them with those offered by available alternatives, which ultimately reduces uncertainty (Arora and Sahney, �n et al. (2016) also found that online 2018; Zhang et al., 2014). Flavia reviews can positively impact offline shopping encounters. In particular, �n et al. (2016) found that online reviews may exert a comple­ Flavia mentary influence when consumers’ motivation to touch is low. Thus, perceived usefulness of online reviews is hypothesized as a causal con­ dition of webrooming intention.

3.3. Product categories Nearly five decades ago, Nelson (1970) classified products into “search goods” and “experience goods”. The differentiation between the two is often made based on the extent to which consumers can research the product characteristics before purchasing. According to Frasquet et al. (2015), search goods are products that can be researched economically, whereas experience goods are those that require direct inspection. Clothing is an example of experience goods because most individuals would prefer to try on the items before buying them, while electronics represent search goods, as product features can be evaluated objectively via reviews and manufacturer’s specifications (Chocarro et al., 2013; Frasquet et al., 2015). Hence, consumers would be more likely to webroom when purchasing experience goods, as offline channel provides haptic information, and online channel allows them to conduct in-depth research (Huang et al., 2009).

3.7. Embracing the complexity and configuration theory The research model developed in the present study was grounded in the complexity and configuration theory, which has been extensively utilized in various disciplines, such as psychology and marketing (Woodside, 2014; Woodside et al., 2015). The rationale behind the adoption of complexity theory is that it acknowledges the fact that re­ ality is complex. Specifically, complexity theory rests on the tenet that, in reality, it is uncommon to observe highly symmetric relationships between two variables (Woodside et al., 2018), which would render assumptions of unidirectionality overly simplistic (Gigerenzer, 1991). Correspondingly, there is a need to move beyond traditional multiple regression analysis and structural equation modeling because such ap­ proaches often fail to deliver accurately predictive causal mechanisms for the occurrence of a specific outcome (Woodside et al., 2018). Authors of recent studies have advocated for the shift from null hy­ potheses statistical testing (NHST) toward the construction and testing of configuration statements (Woodside, 2017; Woodside et al., 2018). According to the perspective of complexity and configuration theory postulates, the “recipes” are more important than the “ingredients”. Single factors—the “ingredients”—rarely work in isolation and may yield different impacts in different contexts, and cannot therefore be meaningfully interpreted without considering proper config­ urations—the “recipes” (Ordanini et al., 2014). This analogy reflects the concept of “equifinality,” which indicates that different configurations of causal factors can yield the same outcome (Ragin, 2008). In addition, the principle of causal asymmetry embedded in configuration theory suggests that both absence and presence of a condition may lead to an

3.4. Need for interaction Social interaction has been found to exert significant influence on consumers’ shopping process (Kim et al., 2017). Besides family, friends, and online community, store employees represent one of the closest sources consumers interact with during their shopping process. In the context of online shopping, such direct interactions are lacking (Lee, 2017). As many consumers still prefer to interact with store employees (Bitner, 2001), their need for direct human interaction cannot be met in online channel. In the context of this study, need for interaction refers to the consumers’ tendency to emphasize personal contact with sales­ people during service encounters (Dabholkar, 1996). For such in­ dividuals, availability of salespeople is an advantage of physical stores, as their assistance with identifying product fit mitigates the uncertainty inherent in online purchases (Chiu et al., 2011; Kacen et al., 2013). Therefore, sales-staff assistance has been identified as one of the drivers of webrooming behavior (Arora and Sahney, 2019). In the present study, need for interaction is thus recognized as one of the causal conditions of webrooming intention, given that such trait heightens the importance of human sales staff in the shopping process, as well as elevates perceived �n, 2014). uncertainty of online transactions (Riquelme and Roma 3

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Journal of Retailing and Consumer Services 53 (2020) 101991

outcome, depending on its interaction with other conditions. The present study is guided by the premise that no single configu­ ration of antecedents proposed (i.e., need for touch, need for interaction, product involvement) can explain intention to webroom, but alternative configurations of these factors should be focused. For instance, con­ sumers who exhibit high need for touch are more likely to visit physical stores for making their purchases of experience goods, as they rely more on haptic information than on interpersonal sources (Flavi� an et al., 2016), making online reviews less relevant in explaining webrooming intention. On the other hand, most consumers would engage in webrooming when buying high-involvement products, even they possess low need for touch and low need for interaction. The high importance of the product they wish to acquire may prompt consumers to spend extra cognitive and/or physical effort to reduce uncertainty �n et al., 2016), making webrooming a (Arora and Sahney, 2019; Flavia perfect shopping behavior. Therefore, the research model adopted in the present study postulates that webrooming intention depends on a combination of consumer-related factors (need for interaction and need for touch), product-specific factors (product categories and product involvement), and channel factors (perceived usefulness of online re­ view) (see Fig. 1).

purchase to increase probability of recall and minimize selective mem­ ory effects. For the purpose of increasing response quality as well as response rate, respondents were guaranteed anonymity and confiden­ tiality. The study sample comprised of 210 students aged <24 years, 71.9% of whom were female. Their average age was 22 years (SD ¼ 1.31). Moreover, in the preceding 6-month period, 69% of re­ spondents purchased an apparel item, while 31% purchased an elec­ tronic product. 4.2. Measures The product involvement measure was adapted from Zaichkowsky (1985), need for interaction from Dabholkar (1996), need for touch from Peck and Childers (2003), perceived usefulness of online review from Park and Lee (2009), and that pertaining to webrooming intention from Arora and Sahney (2018). All items were measured on a five-point Likert scale, anchored at 1 ¼ “strongly disagree” and 5 ¼ “strongly agree.” 4.3. Fuzzy set qualitative comparative analysis As previously noted, fsQCA served as the analysis tool. Qualitative comparative analysis (QCA) is a set-theoretic analysis technique aimed at establishing causal relationships through systematic comparisons. FsQCA represents a variant of QCA that permits the scaling of mem­ bership scores and is thus capable of handling degree-vagueness (Ragin, 2008). FsQCA is deemed advantageous as it helps to identify multiple pathways explaining a particular outcome, in contrast to traditional multiple regression analysis that can only provide an estimate of a single path or “net effect” for all cases under examination (Woodside, 2013). Given the complex patterns of causal interrelationships among diverse consumer traits, product characteristics, and channel factors, fsQCA was adopted in the present study to better understand the underlying causes of webrooming intention.

4. Methodology 4.1. Data collection Young shoppers aged between 19 and 24 were selected as the target population for the present study, as they are digital natives and are thus expected to shop online (Boardman and McCormick, 2018). However, they have been shown to actively engage in webrooming, making them an interesting population to be studied (Aw, 2019). Purposive sampling was employed and data was collected from university students in Malaysia through paper surveys. Students were chosen for this study because (i) they represent the greatest current and future target market of most retail brands (Carpenter et al., 2005) and (ii) they tend to be a relatively homogeneous group, thus permitting theory testing (Carpen­ �n et al., 2016). Moreover, authors of prior ter et al., 2005; Flavia multichannel and cross-channel shopping studies have used student �n et al., sample (Burns et al., 2018; Cho and Workman, 2011; Flavia 2016, 2019). To meet the study inclusion criteria, target respondents had to have bought apparel or electronics products in the past six months using the webrooming approach. These two product categories were selected because they have been identified as typical experience and search goods (Frasquet et al., 2015). Following the approach adopted by Santos and Gonçalves (2019), individuals that had made more than one pur­ chase in the specified period were instructed to focus on the most recent

4.4. Data calibration The ground concept of set membership applied in fsQCA requires that original data be transformed into membership score sets that range from 0 (fully excluded from the set) to 1 (fully included in the set) (Ragin, 2008). Using direct method, three qualitative thresholds were determined based on the survey scale (five-point Likert scale), where full membership threshold was fixed at the value of 4, the full non-membership threshold was fixed at 2, and the cross-over point was set to 3. Subsequently, the values of all conditions were calibrated based on a logistic function to fit into these three thresholds. Similarly, search product was coded as 0, whereas experience product was coded as 1.

Fig. 1. Proposed configuration model. 4

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5. Data analysis

Table 2 Configurations for high webrooming intention.

5.1. Reliability and validity

Solution Configuration Product-related factors Product categories Product involvement

Confirmatory factor analysis (CFA) was conducted to check the reliability and validity of all adopted measures. For reliability testing, the value of composite reliability (CR) for each variable was greater than the recommended cut-off point of 0.7, suggesting sufficient internal consistency (Bagozzi and Yi, 1988). For validity testing, average vari­ ance extracted (AVE) for all variables exceeded the recommended threshold of 0.5, and the square root AVEs for all variables was higher than the corresponding correlations; thus, convergent and discriminant validity was established (Fornell and Larcker, 1981). Detailed results are provided in Table 1.

Consumer-related factors Need for touch Need for interaction Channel-related factor Perceived usefulness of online reviews Consistency Raw coverage Unique coverage Overall solution consistency: 0.937 Overall solution coverage:0.834

Necessity analysis for the presence of webrooming intention was performed first, whereby the threshold of 0.90 was adopted to establish a relevant necessary condition (Ragin, 2008). The findings revealed that perceived usefulness of online reviews is a necessary condition for webrooming intention (Consistency value: 0.957). With a high coverage value of 0.913, this necessary condition is deemed empirically relevant (Ragin, 2008). Next, analysis of sufficient conditions was performed, which involved construction, reduction in the number of rows, and the analysis of the truth table, as recommended by Ragin (2008). Hence, a truth table was developed by running fsQCA 3.0 software program (www.fsqca. com), entailing all possible configurations of conditions with respec­ tive cases. This was followed by the truth table reduction, based on the process adopted by Ragin (2008), whereby (i) at least 80% of cases in each sample were retained and (ii) minimum consistency threshold of 0.75 was adopted. Finally, the intermediate solution was analyzed, as this solution only includes simplifying assumptions (i.e., easy counter­ factuals) and is deemed more superior (Rihoux and Ragin, 2009). The results of fuzzy set analysis for webrooming intention are pre­ sented in Table 2. Adhering to the recommendations made by Pappas et al. (2017), analysis results are reported as core and peripheral con­ ditions, whereby the black circles (●) and crossed-out circles (�) denote the presence and absence of a condition, respectively. Moreover, large circles represent core conditions, while small circles represent periph­ eral conditions. Blank spaces indicate that the causal condition may be either present or absent. The consistency values for each configuration and the overall solu­ tion are also presented in Table 2. As all values exceed the recommended threshold of 0.75, no exclusion of configurations was needed (Ragin, 2008). Consistency examines indicates the extent to which a given configuration is a sufficient condition for the outcome. As coverage

1

2

3

4

1. Webrooming intention 2. Product involvement 3. Need for interaction 4. Need for touch 5. Perceived usefulness of online review

0.907

0.765

0.874

0.808

0.584

0.202

0.764

0.907

0.709

0.174

0.162

0.842

0.875

0.542

0.193

0.271

0.242

0.736

0.904

0.704

0.387

0.325

0.210

0.272

●

●

● 0.934 0.355 0.020

● 0.933 0.573 0.047

● 0.944 0.736 0.125

5.3. Predictive validity Following the recommendation for predictive validity testing in fsQCA (Pappas et al., 2017), the sample was segregated into a subsample and a holdout sample to examine the power of the developed model in predicting the outcome in additional samples. The findings obtained by conducting analyses on the subsample were tested against the holdout sample. Two configurations in Table 3 represents models to be plotted against the outcome variable (i.e., webrooming intention). As shown in Fig. 2, when Model 1 was applied to the data from the holdout sample, high consistency (0.892) and coverage (0.545) was obtained, suggesting high predictive validity with respect to webrooming intention. All re­ sults are available upon request.

Variables AVE

3

values for each configuration and the overall solution ranged from 0.355 to 0.834, the developed model was deemed informative (Woodside, 2013). Coverage index indicates the empirical relevance of a consistent subset, and is seen as analogous to R2 in conventional regression analysis (Rihoux and Ragin, 2009; Woodside, 2013). The results yielded by fsQCA suggest presence of three configuration paths that lead to high webrooming intention. Solution 1 indicates that consumers who have low need for interaction and perceive online re­ views to useful will have high intention to webroom when planning to purchase a high-involvement product, regardless of product categories and need for touch. Solution 3 is similar to Solution 1, positing that the presence of high need for touch, high perceived usefulness of online reviews, and high product involvement may lead to high webrooming intention, regardless of product categories and need for interaction. Finally, Solution 2 suggests that high webrooming intention may result from perceived online review usefulness when purchasing highinvolvement experience-type products, regardless of consumer-related factors. In the next phase, causal conditions that lead to the absence of webrooming intention were examined, as suggested by Schneider and Wagemann (2010). The truth table results indicate that the consistency values are below the recommended level of 0.75 for all configurations, implying causal asymmetry, as several configurations lead to the required outcome (webrooming intention) but none is consistently relevant to its absence.

Table 1 Result of measurement model testing. CR

2

Notes: Black circles (l) indicate presence of a condition. Circles with “x” (~) indicate its negation. Large circles indicate core conditions; small ones, pe­ ripheral conditions. Blank spaces indicate the condition may be either present or absent.

5.2. Fuzzy set qualitative comparative analysis

Variables

1

5

6. Discussion

0.839

The growing relevance of cross-channel behavior in contemporary omnichannel retail environment has attracted the attention of both re­ tailers and researchers. Notably, the increasing prevalence of

Notes: Diagonal elements (in italic) are the square root of the average variance extracted (AVE). Off-diagonal elements are the correlations among variables. 5

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longer have to rely on the product information provided by the retailers, as they can peruse online reviews to gain more objective product eval­ uations. Representing a form of electronic word of mouth (eWOM), online reviews have emerged as one of the most credible product in­ formation sources, and can thus be decisive in determining consumers’ attitudes towards products and retailers, thus driving their purchasing decisions (Hu and Krishen, 2019; Korfiatis et al., 2012). Arora and Sahney (2018, 2019) and Fern� andez et al. (2018) concur that online reviews can lead to webrooming behavior. The results reported here support these findings. The significance of perceived usefulness of online reviews is note­ worthy, as it was present in all three fsQCA solutions. However, as its presence is insufficient for explaining high webrooming intentions, and thus other factors should be examined jointly. The first of the three so­ lutions obtained in this study indicates that high-involvement product, high perceived usefulness of online reviews, and low need for interac­ tion explain high webrooming intention, while product categories and need for touch are irrelevant. In other words, product involvement is the core condition. This solution implies that, when purchasing a highinvolvement product which requires significantly more information, consumers who have low need for interaction with salespeople tend to see online reviews as a reliable information source, leading to webrooming intention. This finding seems to suggest that consumers who exhibit low need for interaction would be likely to webroom to take advantage of the online reviews, as this would allow them to avoid the time-consuming exchange of pleasantries with often persistent shop assistants in the physical stores (Keeling et al., 2007; Riquelme and �n, 2014). Similarly, Flavia �n et al. (2019) found that distrust in the Roma offline salesperson’s recommendation constitutes offline channel un­ certainty that motivates webrooming behavior, offering plausible

Table 3 Configurations indicating high webrooming intention for the subsample. Models from sub-sample 1

Raw coverage

Unique coverage

Consistency

EXP*PI*PUOR NFT*NFI*PI*PUOR Overall solution consistency: 0.943 Overall solution coverage: 0.748

0.597 0.532

0.216 0.151

0.968 0.984

Notes: EXP: Experience goods, PI: Product involvement, PUOR: Perceived use­ fulness of online reviews, NFT: Need for touch, NFI: Need for interaction.

webrooming presents both an opportunity and a threat to retailers. Multichannel consumers spend more than those who use a single channel for making their purchases (Venkatesan et al., 2007). As a result, webrooming may benefit offline and multichannel retailers that can implement effective multichannel marketing strategies. In contrast, webrooming reduces the number of online sales and potentially induce cross-channel free riding, and thus are harmful for pure play online and multichannel retailers, respectively. Hence, to deal with the aforemen­ tioned situations, it is valuable for all kind of retailers to pursue further understanding of webrooming. In the present study, the combined effect of product, consumer, and channel factors was examined using a model grounded in the complexity and configuration theory to explain the drivers behind young consumers’ webrooming intention. As expected, perceived usefulness of online reviews was shown to be a necessary causal condition for webrooming intention. The widespread accessibility of Internet has increased the range of options available to consumers, who can obtain abundance of information on retailers and products before making their purchasing decision. Consumers today no

Fig. 2. Result of predictive validity. 6

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(Arora and Sahney, 2018, 2019; Aw, 2019; Choi and Yang, 2016), thereby overlooking the role of consumer traits. In addition, authors of prior studies on this topic have largely considered a single product setting, such as electronics and clothes, thereby disregarding the po­ tential confounding effects of product characteristics. More importantly, extant studies heavily rely on structural equation modeling, and focus on the main effects of antecedents, while disregarding the in­ terdependencies and interconnected causal structures among variables (Woodside, 2014). These shortcomings are overcome in the present study by considering consumer behaviors as highly complex in nature. Thus, complexity and configuration theory was adopted as the research framework in order to contribute to the cross-channel behavior litera­ ture by offering a new perspective on how different internal and external factors combine to form configurations that influence webrooming intention. The findings reported in the preceding sections clearly indi­ cate that the interaction between conditions is a core tenet in explaining webrooming intention. Thus, retailers and researchers alike can better understand the causal conditions underpinning webrooming intention, whereby a combination of product-, consumer-, and channel-related factors could be the basis for new models in explaining cross-channel behavior. Furthermore, the use of young adult sample provides a unique perspective of when and why these digital natives switch to webrooming, paving the way for the idea that online channel is not al­ ways the primary shopping mode for young people, especially in the era of omnichannel.

explanation for the observed low need of interaction compels consumers to search information online before visiting physical stores. Hence, it is unsurprising that salespeople who have once served as the sole product information providers are starting to fear the Internet as the dominant product information source (Chiou et al., 2017). Consumers with low need for interaction are likely to visit physical stores when purchasing high level of product involvement to seek reassurance and minimize purchase risk. It is also likely that, due to the desire for immediate possession, even consumers that do not enjoy interaction with sales­ persons would visit physical stores. However, future studies are required to verify this supposition. Solution 3, while similar to Solution 1, requires presence of need for touch, rather than absence of the need for interaction. Although both solutions lead to webrooming intention, Solution 3 was associated with the highest consistency and coverage, suggesting that need for touch is probably more relevant for developing webrooming intention. Again, high product involvement emerges as a core condition in this solution. Thus, perceived usefulness of online reviews and consumers’ need for touch motivate webrooming intention, especially when purchasing high-involvement products. This finding is both intuitive and in good agreement with the results reported by other authors (Arora and Sahney, 2019). However, Santos and Gonçalves (2019) argued that need for touch does not influence webrooming behavior. Given these contradic­ tory findings, it is worth noting that product involvement may trigger higher level of need for touch as well as greater reliance on online re­ views, which thus jointly influence webrooming intention. On the other hand, Solution 2 implies that the combination of highinvolvement experience-type product and high perceived usefulness of online reviews would lead to high webrooming intention. Once again, high product involvement emerges as the core condition. Interestingly, in this solution, consumer-related factors are no longer relevant for webrooming intention when purchasing high-involvement products. Nonetheless, the personal first-hand experience offered in physical stores is still lacking. Consequently, high-involvement experience products will be seen to incur greater online purchase risk. In such cases, product experience shared by other customers becomes highly infor­ mative as this kind of products are hardly evaluated based on mere product description. The information obtained from other users is typically supplemented by visiting physical stores for product exami­ nation, which is particularly beneficial for products with high experi­ ential attributes. Thus, webrooming may emerge as the safest purchase method for goods of this kind. Finally, it is important to highlight the significant role of product involvement in relation to webrooming intention, given its presence as a core condition in all three solutions. This finding lends support to the �ndez et al. (2018), suggesting that webroomers results obtained by Ferna consider product attributes as important decision criteria, motivating them to spend more time and effort examining the product. On the other hand, Frasquet et al. (2015) found product involvement as a strong motivator of online channel usage for both search and purchase shop­ ping stages, contradicting the results obtained in the present study. However, this is not particularly surprising, given that cross-cultural differences between Europe and Asia, where these studies were con­ ducted, would likely affect consumer preferences. Thus, further studies on webrooming need to shed lights on this matter in detail.

6.2. Practical implications The findings yielded by this study can be of value to pure play online, offline, and multichannel retailers attempting to manage webrooming behavior, given the increasingly tightening tug-of-war between online and offline retailing. The results reported in this work show that it is important for retailers to distinguish between high- and lowinvolvement products, as this will determine how useful online re­ views will be to the consumers. This also implies that physical stores are seen as a suboptimal source of information as consumers cannot easily access opinions of other customers. For offline and multichannel re­ tailers wishing to encourage webrooming behavior, online reviews can be highly beneficial and should be strategically integrated into their online platforms to induce webrooming behavior and direct consumers to their physical stores (Li et al. 2019). Conversely, pure play online and multichannel retailers who wish to close deals online should strive to improve the usefulness of online reviews because this can transform experience goods into search goods, thereby reducing the need for physical product inspection (Park and Lee, 2009). Offline retailers could also psychologically heighten the perceived product importance by emphasizing the benefits of direct product experience (i.e., need for touch), which would implicitly increase the perceived online purchase risk, especially for experience goods, such as clothing and cosmetics. On the other hand, to induce online trans­ actions, pure play online and multichannel retailers should work on price, warranty, and return policy to mitigate the common risk concerns related to high-involvement and experience product categories. Upon successful execution, consumers are likely to disown a central route of information processing which characterizes elaborated shopping pro­ cess like cross-channel shopping (Fern� andez et al., 2018). It is also worth noting that certain consumers webroom as a means of avoiding pro­ tracted interactions with salespeople. In such cases, offline and multi­ channel retailers should instead utilize in-store technology strategically or equip salespeople with adaptive selling strategies, with the aim of offering consumers a personalized experience instead of creating un­ necessary pressure to purchase, commonly associated with physical stores.

6.1. Theoretical implications The findings obtained in this study add to the growing body of knowledge about webrooming, a popular cross-channel behavior in the current retail environment. Although there has been extensive research on shopping channel choice, very few authors have directly tapped into the webrooming phenomenon. Hence, the present study answers calls to identify the determinants of webrooming behavior at an individual level (Flavi� an et al., 2016). Extant research has mostly focused on channel-related attributes as an explanation of webrooming behavior 7

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Journal of Retailing and Consumer Services 53 (2020) 101991

6.3. Limitations and suggestions for further research

cross-channel behavior. Given that consumer shopping behaviors are inherently different across cultures, particularly in terms of attitudes towards online and offline channels, future studies in different cultural contexts are suggested. Lastly, although the use of student sample was deemed appropriate for meeting the objectives of the present study, the proposed model should be tested using data pertaining to different consumer segments. For instance, it would be interesting to examine the shopping preferences of older consumers and their propensity for webrooming, as well as underlying factors that drive this behavior in this age group.

As any study of this type, this research is also subject to some limi­ tations, one of which is inability to consider large number of causal conditions, due to which the proposed model would benefit from further refinement to fully capture the webrooming behavior. Thus, models discussed in this work can be used as the building blocks for a holistic understanding of webrooming behavior that can be expanded upon in future studies. For instance, other sub-factors can be incorporated in the interactive model of product-, consumer-, and channel-related factors. It would also be beneficial to examine if the webrooming behavior in­ volves crossing the channels of two different firms (competitive webrooming) or the same one. Moreover, as the models developed in this study were based on self-reported data, archival data from retailers could be used by other authors for a deeper insight into consumers’

Acknowledgements None.

Appendix. Measurement Instruments Webrooming intention (adapted from Arora and Sahney, 2018) I am likely to collect information online before buying offline when buying similar product. It is probable that I will collect information online before buying offline when buying similar product. I am certain that I will collect information online before I buy offline when buying similar product. Product involvement (adapted from Zaichkowsky, 1985) Product for which I have webroomed was important to me. Product for which I have webroomed was relevant for me. Product for which I have webroomed meant a lot to me. Need for touch (adapted from Peck and Childers, 2003) I place more trust in products that can be touched before purchase. I feel more comfortable purchasing a product after physically examining it. If I can’t touch a product in the store, I am reluctant to purchase it. I feel more confident making a purchase after touching a product. The only way to make sure a product is worth buying is to actually touch it. I would only buy this kind of products if I could handle it before purchase. Need for interaction (adapted from Dabholkar, 1996) Human contact in providing services makes the process enjoyable for the customer. I like interacting with the person who provides the service. Personal attention by the service employee is very important to me. It bothers me to use a machine when I could talk with a person instead. Perceived usefulness of online reviews (adapted from Park and Lee, 2009) Online consumer reviews are useful to me. Online consumer reviews make purchasing easier. Online consumer reviews make me a smarter shopper. Online consumer reviews are very beneficial to me.

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