3.1 Discussion
Looking at the overall results of the literature review we argue that this paper found more evidence that smartphones rather increase than decrease sales in brick-and-mortar stores, as far more positive (38) than negative statements (9) could be identified. However, no prediction can be made about how strongly each individual factor affects sales in brick-and-mortar stores. The research conducted on the various sales influencers is discussed below.
Extensively Researched Sales Influencer.
Looking at the sales influencers in detail, only “Information Search” and “Mobile Payment” have been researchedextensively. “Information Search” was mostly analyzed from a utilitarian driver perspective (see Table 4). Additionally, the highest number of positive (5) but also negative statements (3) was found for this sales influencer. Grewal et al. [30] argues that “Information Search” can lead to distraction which makes customers divert from their normal shopping path and increases purchases (this effect gets stronger with increasing customer age). Paul et al. [31] indicate that “Information Search” leads to a more locked in shopping experience which drives sales rate. Rippé et al. [32] reasons that “Information Search” leads to a perceived increase in control which fosters purchase intention. In contrast, Bellini and Aiolfi [27] and Sciandra and Inman [28] claim, that the use of smartphones in a shopping related way leads to fewer planned and unplanned purchases because mobile device use consumes attentional resources and makes in-store communication strategies less effective. Fuentes and Svingstedt [15] argue that young adults who use their smartphone to obtain information become more knowledgeable and competent to the point where they can effectively challenge the “sales pitch” of shop assistants which leads to a reduction in revenue. Although “Information Search” is seen as positive, retailers should regard it as an ambivalent sales influencer. On the one hand, information search creates an informed and distracted customer who is locked into a perceived superior purchase experience and therefore buys more. Alternatively, it can lead to an over informed customer who has an increased bargaining power and does not rely on in-store stimuli. According to the reviewed literature, factors like gender, age or product categories are moderators [16]. For example, “Information Search” by younger customers is more likely to have a negative effect on sales whereas information search by older customers leads to an increase in sales. Therefore, it can be concluded, that the sales influencer “Information Search” can be viewed as having a sale enhancing effect on older customers and a sales decreasing effect on younger ones. Papers about “Mobile Payment” focused on a hedonic driver perspective. Six positive statements and one neutral statement could be identified, describing that “Mobile Payments” can enhance shopping experience [18, 31, 37, 38], lead to higher positive price image judgement and therefore store loyalty [37], increase the willingness to pay compared to cash payments [37] and do not inherit greater privacy concerns compared to fixed payment[21]. Therefore, mobile payments seem to have a strong influence on brick-and-mortar store sales rate. Although the sales influencers “Information Search” and “Mobile Payment” were researched by the highest number of papers in the conducted literature review this research focused mainly on one sales driver (“Information Search”/UD; “Mobile Payment”/HD). Therefore, we argue that even for these highly researched sales influencers more research, analyzing the sales drivers not yet covered, is needed to give a more comprehensive overview of their influence on sales.
Moderately Researched Sales Influencers.
Moderate research has been carried out for the sales influencers “Showrooming”, “Distraction”, “Scan and Pay” and “Personalized mobile Coupons”. Research about “Showrooming” was mainly conducted from a cost and time reduction perspective. According to literature “Showrooming” has a negative influence on sales as it is generally seen as a technique which decreases profit for retailers by enhancing price competition [13, 15, 27, 28]. However, it can be sale enhancing if it is avoided or mitigated by retailers. To counter “Showrooming” Mehra et al. [5] suggest price matching as a short term solution and an exclusivebrand strategy as a long term solution. Another way would be to cut internet access for in-store customers but this would also have an unforeseeable impact on other sales influencers, which rely on an internet connection, wherefore it is not recommended. The sales influencer “Distraction” was analyzed from a hedonic driver perspective only. “Distraction” seems to have a mixed influence on sales. Grewal et al. [30] argue that distraction caused by non-shopping related phone use leads to extra time spent and distance walked in brick-and-mortar stores which ultimately leads to an increase in purchases (this effect gets stronger with increasing customer age). Sciandra and Inman [28] add that these distractions lead to more unplanned purchases and customer’s reliance on in-store signage and promotion signals significantly improves. In sharp contrast, Bellini and Aiolfi [27] point out that non shopping related use of mobile technology negatively influences the ability of customers to recall in-store stimuli. Taking into account that according to Fuentes and Svingstedt [15] young adults use smartphones to ask for advice and feedback concerning their planed in-store purchases using their social media channels, we argue that young adults are more likely to miss or disregard in-store stimuli as they get distracted by checking their phones for new advice from their peers. Summing it up, the sales influencer “Distraction” is sale enhancing for older customers or customers who do not rely on social advice and feedback and sales diminishing for younger customers or customers who do rely on social advice and feedback. The sales influencer “Scan and Pay” was analyzed mainly from a cost and time reduction perspective. However, one paper also analyzed this aspect from a hedonic driver perspective. As all statements about “Scan and Pay” were positive, and therefore it seems to have a sale enhancing effect. According to literature, this works by enabling retailers to reduce the number of cashiers and customer waiting time, thus enabling retailers to cut costs and improve customer experience. Perceived ease of use, usefulness and adoption likelihood are regarded highly by customers [17]. Additionally, “Scan and Pay” does increase both customer service levels (in terms of speeding up the process) as well as retailer internal performance [36], while also making the shopping experience hyper relevant [18]. “Personalized Mobile Coupons” was mainly researched from a utilitarian driver and cost and time reduction driver perspective, though one paper analyzed it from a hedonic driver perspective. According to literature it positively influences sales in a hedonic way as shoppers prefer shopping in brick-and-mortar stores that provide personalized coupons[7], as well as in utilitarian and cost and time saving ways by offering discounts, based on previous shopping behavior, which require shoppers to travel farther through the retail store [22, 23]. Moderate research about the mentioned sales influencers was published and that research focused mainly on analyzing one type of sales driver. Therefore, we argue that more research needs to carried out to cover the non-addressed sales drivers to obtain a deeper understanding of how these factors can influence sales in brick-and-mortar stores.
Partially Researched Sales Influencers.
For all not yet mentioned sales influencers only limited research was found, and therefore it is too early to draw conclusions regarding their impact on brick-and-mortar store sales rate. However, for all sales influencers in this category, with the exception of “Coupons Locational Targeting Own Retail Store and “Location Based Promotions”, only positive statements about the influence of smartphones on sales in brick-and-mortar stores could be identified. This substantiates the conclusion that smartphones influence sales rather in a positive than a negative way.
Additional Findings.
As 20 of the 26 papers analyzed utilitarian drivers and made 31 of the 56 identified statements (6 negative, 6 neutral 19 positive), we observe an imbalance if compared to cost and time reduction (14 papers/25 statements/5 negative, 1 neutral, 19 positive) and hedonic drivers (12 papers/23 statements/2 negative, 3 neutral, 18 positive). In the years 2007 to 2013 only little research was carried out, whereas after 2014 the quantity of research increased significantly peaking in 2017 with 7 published papers. This is correlated with the rising importance of smartphones in retail in general [3, 40] and the constant growth of e-commerce [2].
3.2 Call for Future Research
Future Research Implications.
Summarizing the literature review, we conclude that additional research is needed for all identified sales influencers and sales drivers. Even the extensively researched sales influencers “Information Search” and “Mobile Payment” have only been examined from either a utilitarian driver or a hedonic driver perspective, whereas even for these sales influencers additional research is needed to better understand their influence on sales in brick-and-mortar stores. Future researchers can use our overview created in Table 4 to identify possible research opportunities for each individual sales influencer. Additionally, we propose that some kind of unifying research is needed which makes it possible to predict the influence of each individual sales influencer on sales in brick-and-mortar stores.
Limitations.
Although an extensive literature review with forward and backward search has been conducted, it cannot be guaranteed that all relevant literature has been found. Therefore, while we consider our review as comprehensive, it may not be necessarily exhaustive. In addition, in the present paper we did not take into account all specific store settings, product types, gender implications or other very specific variables. Therefore, one has to be careful when applying results of the extracted statements in different settings.