Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Showrooming vs. Webrooming: The Effect of Multichannel Information Search on Purchase Behavior

1,068 views

Published on

Although there has been a steady growth in multichannel retailing, few studies examine how different channels of information search affect customers’ purchase behavior. As the retailing industry evolves toward multichannel or omnichannel retailing, customers may use one channel to search for information and purchase in another channel. For example, customers can get product information in a brick-and-mortar retail store and then purchase a product online, referred to as “showrooming.” Alternatively, customers may go online to search product information but then go to a brick-and-mortar retail store to complete their purchase, referred to as “webrooming.” Besides, customers can evaluate product attributes by touch and feel the product in the store and they can simultaneously get additional information using an online search at the brick-and-mortar retail store, and then make a purchase decision in the brick-and-mortar retail store or in the online channel.

In this study, we compare the effect of offline information sources (e.g., advertising/direct marketing, conversation with friend or family) and online information sources (e.g., online advertising, email marketing) on customers’ purchase behavior in both online and offline channels. In addition, we also examine the influence of in-store online information search on in-store and online purchase behavior. We test our conjectures by using data from more than 700 respondents of the 2014 National Technology Readiness Survey (NTRS), who have made personal purchase for a various types of products where the total amount of the transaction was at least $50 in the past 3 months.

We find that offline information source is positively and strongly associated with the likelihood of purchasing in a brick-and-mortar retail store, but we see a significant negative association between use of an online information source and probability of purchase in a brick-and-mortar retail store. These results elucidate the importance of channel consistency between information search and purchase. Interestingly, we find counterintuitive evidence of showrooming and webrooming behavior: while in-store online search has significant and positive correlation with in-store purchase behavior, in-store online search decreases the probability of purchasing online. These results provide new insights for customer behavior in multi-channel settings and provide implications for designing marketing interventions.

Published in: Retail
  • Login to see the comments

Showrooming vs. Webrooming: The Effect of Multichannel Information Search on Purchase Behavior

  1. 1. 1 Dongwon LeeFrontiers 2016 Dongwon Lee Robert H. Smith School of Business University of Maryland Showrooming vs. Webrooming: The Effect of Multichannel Information Search on Purchase Behavior 25 June 2016, 1030-1055 am (This version 22 June 2016) Frontiers 2016 Sunil Mithas Robert H. Smith School of Business University of Maryland Gina Woodall Rockbridge Associates, Inc
  2. 2. 2 Dongwon LeeFrontiers 2016 INTRODUCTION Shift in Shopping For the first time, online shoppers bought more of their purchases online rather than in stores.
  3. 3. 3 Dongwon LeeFrontiers 2016 SHOWROOMING VS. WEBROOMING Showrooming vs. Webrooming
  4. 4. 4 Dongwon LeeFrontiers 2016 RESEARCH QUESTION Research Question 1: How do offline/online information sources influence online/brick-and-mortar store purchase? Research Question 2: How does in-store online information search influence online/brick-and-mortar store purchase? Information sources online offline Purchase online store offline store In-store online information search
  5. 5. 5 Dongwon LeeFrontiers 2016 ACADEMIC BACKGROUND Multi-Channel Customer Management Implementation of buy-online,pick up in store (BOPS) is associated with a reduction in online sales and an increase in store sales and traffic (Gallino and Moreno 2014). When a store opens locally, people substitute away from online purchasing (Forman et al. 2009). The introduction of an offline channel increases demand overall and through the online channel as well (Bell et al. 2013).  E.g., Warby Parker and Amazon offline store  Despite the growing importance of showrooming and webrooming in practice, comparison between showrooming and webrooming has not been studied
  6. 6. 6 Dongwon LeeFrontiers 2016 METHODS AND DATA National Technology Readiness Survey 2014 Authored by Parasuraman and Rockbridge, Co-sponsored by the Center for Excellence in Service TRI Scale licensed to over 120 scholars in 30 countries, including Germany, Turkey, China, UK, Brazil, India, Malaysia, Philippines, Canada, South Africa Nationally representative survey of U.S. adults Frame: online panel from 2 reputable providers Weighted to match U.S. Census Margin of Error: +/- 3% Final sample in this analysis: 705 respondents Source: Rockbridge Associates (2015)
  7. 7. 7 Dongwon LeeFrontiers 2016 METHODS AND DATA Empirical Model 𝐿𝑜𝑔𝑖𝑡 (𝑂𝑓𝑓𝑙𝑖𝑛𝑒 𝑃𝑢𝑟𝑐ℎ𝑎𝑠𝑒𝑖) = 𝛽0 + 𝛽1 𝑂𝑓𝑓𝑙𝑖𝑛𝑒𝐼𝑛𝑓𝑜𝑖 + 𝛽2 𝑂𝑛𝑙𝑖𝑛𝑒𝐼𝑛𝑓𝑜𝑖 + 𝛽3 𝐼𝑛𝑆𝑡𝑜𝑟𝑒𝑂𝑛𝑙𝑖𝑛𝑒𝑆𝑒𝑎𝑟𝑐ℎ𝑖 + γ𝑃𝑖 + δ𝐶𝑖 + 𝜀𝑖 Dependent Variable  Offline Purchase: dummy variable for purchase channel (1=offline, 0=online) Independent Variables  Offline Information: use any offline information sources (1=yes, 0=no)  Online Information: use any online information sources (1=yes, 0=no)  In-Store Online Search: use any online information sources at an offline store (1=yes, 0=no) Product Controls (P)  Product Price, Product Categories (16 dummy variables) Customer Controls (C)  Age, Gender, Marital Status, Living Area (1=city or suburb, 0=rural or small town), Technology Related Job, Race, Born in US
  8. 8. 8 Dongwon LeeFrontiers 2016 METHODS AND DATA Descriptive Statistics and Correlations (n=705) Mean SD 1 2 3 4 5 6 7 8 9 10 11 1 Offline Purchase 0.63 0.48 1.00 2 Offline Information 0.84 0.36 0.17* 1.00 3 Online Information 0.71 0.46 -0.36* 0.13* 1.00 4 In-store Online Search 0.14 0.34 0.05 0.14* 0.25* 1.00 5 Product Price (log) 5.21 1.11 0.02 0.12* 0.15* 0.13* 1.00 6 Age 41.61 12.47 0.09* -0.06 -0.22* -0.17* -0.03 1.00 7 Male 0.49 0.50 -0.03 -0.04 0.00 0.04 0.01 0.04 1.00 8 Marry 0.55 0.50 0.04 0.00 0.00 0.02 0.07* 0.15* 0.00 1.00 9 City 0.74 0.44 0.02 0.05 -0.02 0.00 -0.05 -0.06* -0.01 -0.06* 1.00 10 Tech Job 0.13 0.34 -0.06 -0.02 0.07 0.13* 0.05 -0.07* 0.19* 0.11* -0.04 1.00 11 White 0.69 0.46 0.02 -0.03 -0.05 -0.04 0.00 0.16* 0.07* 0.10* -0.15* 0.03 1.00 12 Born US 0.89 0.31 0.05 -0.01 -0.07* -0.01 0.02 0.03 0.00 0.03 -0.06 -0.05 0.28* *significant at p<0.05
  9. 9. 9 Dongwon LeeFrontiers 2016 RESULTS (1) (2) (3) (4) Dependent Variables Offline Purchase Offline Purchase Offline Purchase Offline Purchase Offline Information 1.703*** 1.691*** 1.722*** 1.693*** (0.278) (0.286) (0.282) (0.288) Online Information -2.766*** -2.726*** -2.825*** -2.804*** (0.296) (0.298) (0.305) (0.307) In-Store Online Search 0.695*** 0.776*** 0.570** 0.619** (0.253) (0.257) (0.263) (0.268) ln(price) 0.094 0.082 (0.085) (0.086) Age 0.009 0.006 (0.007) (0.008) Male -0.250 -0.243 (0.177) (0.194) Marry -0.022 -0.183 (0.180) (0.194) City 0.031 0.059 (0.201) (0.214) Tech Job -0.246 -0.234 (0.269) (0.277) White -0.074 -0.119 (0.195) (0.204) Born US 0.502* 0.479* (0.278) (0.284) Constant 1.181*** 0.548 0.410 0.110 (0.274) (0.512) (0.545) (0.675) Product Category X X O O Observations 705 705 705 705 Wald χ2 98.66*** 99.80*** 118.46*** 121.56*** Log pseudolikelihood -383.646 -379.167 -375.646 -372.226 Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1
  10. 10. 10 Dongwon LeeFrontiers 2016 RESULTS Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1 (1) City/Suburb (2) Rural/Small town (3) Total Dependent Variables Offline Purchase Offline Purchase Offline Purchase Offline Information 1.531*** 2.506*** 1.717*** (0.343) (0.599) (0.289) Online Information -2.849*** -3.043*** -2.817*** (0.345) (0.641) (0.310) In-Store Online Search 1.022*** -0.211 -0.228 (0.333) (0.587) (0.460) In-Store Online Search 1.203** x City (0.552) City -0.152 (0.234) Constant -0.692 2.787* 0.279 (0.797) (1.437) (0.683) Product Controls O O O Customer Controls O O O Observations 522 183 705 Wald χ2 106.83*** 49.18*** 122.58*** Log pseudolikelihood -268.006 -88.691 -359.742 Location (City/Suburb vs. Rural/Small town) and In-Store Online Search In-store online search affects offline purchase only in city/suburb but not in rural/small town areas. Is this result because of better availability of SKUs in cities/suburbs than in rural/small town areas?
  11. 11. 11 Dongwon LeeFrontiers 2016 RESULTS Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1 (1) (2) (3) (4) Dependent Variables Offline Purchase Offline Purchase Offline Purchase Offline Purchase Offline Information 1.892*** 1.888*** 1.903*** 1.881*** (0.296) (0.304) (0.304) (0.310) Online Information -2.855*** -2.817*** -2.898*** -2.880*** (0.316) (0.320) (0.324) (0.327) In-Store Online Search 15.833*** 16.086*** 15.060*** 15.300*** (0.646) (0.732) (0.700) (0.790) In-Store Online Search -15.258*** -15.434*** -14.612*** -14.808*** X Offline Information (0.685) (0.760) (0.737) (0.819) Constant 1.096*** 0.435 0.341 0.032 (0.272) (0.511) (0.546) (0.676) Product Controls X X O O Customer Controls X O X O Observations 705 705 705 705 Wald χ2 644.94*** 535.70*** 597.90*** 504.14*** Log pseudolikelihood -379.635 --375.316 -372.033 -368.258 Interaction Effect of Offline Information Source and In-Store Online Search Results indicate that in-store online search acts as a substitute of offline information.
  12. 12. 12 Dongwon LeeFrontiers 2016 Information Search Purchase channel OnlineOffline Offline Online Traditional Brick-and-Mortar Increase in probability of in- store purchase Showrooming Decrease in probability of online purchase Webrooming Decrease in probability of in- store purchase Instore online search increases offline purchases, more effective in city/suburb, negatively moderates the effect of offline sources Traditional ecommerce Increase in probability of online purchase SUMMARY OF MAIN RESULTS
  13. 13. 13 Dongwon LeeFrontiers 2016 • Among offline sources, employees, packaging information and store display play an important positive role in offline purchase • Among online sources, retailers’ website, app, consumer reviews, and online employees play an important negative role in offline purchase • The positive role of offline employees dominates that of online employees • Robustness check: Models with continuous count measures of online and offline sources yield broadly similar results ADDITIONAL FINDINGS
  14. 14. 14 Dongwon LeeFrontiers 2016 ADDITIONAL FINDINGS .2.4.6.8 1 0 1 2 3 4 5 6 7 # of Offline Sources w/o In-store Online Search w/ In-store Online Search
  15. 15. 15 Dongwon LeeFrontiers 2016 IMPLICATIONS FOR RESEARCH Extends the growing literature on multi-channel retailing by documenting new findings for information search and purchase behavior across channels Showrooming vs. Webrooming: Offline information search decreases online purchase probability; Online information search decreases offline purchase probability In-store online information search  In-store online information search increases offline purchase probability  In-store online information search can be a substitute of offline information search for offline purchase  Positive effect of in-store information search on offline purchase probability applies only for customers in city/suburb rather than in rural/small town area
  16. 16. 16 Dongwon LeeFrontiers 2016 MANAGERIAL IMPLICATIONS Strategies for managing information sources and information search for omni- channel management for brick-and-mortar and online retailers  Importance of channel consistency between information search and purchase  Developing consistent and optimal customer experience across channels  Move toward becoming dual-channel retailers For brick-and-mortar retailers  Integrate in-store and online channels  Focus on providing information and services consistently For online retailers  Provide competitive prices and neatly curated contents  Enable customers to use physical channel as showroom and pickup points
  17. 17. 17 Dongwon LeeFrontiers 2016 THANK YOU

×