A systematic review of consumer information search in online and offline environments

Haridasan, Anu C.; Fernando, Angeline Gautami; Saju, B.

doi:10.1108/RAUSP-08-2019-0174

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Sumário

Consumer information search • RAUSP 56 (2) • Apr-Jun 2021 • https://doi.org/10.1108/RAUSP-08-2019-0174 copy

A systematic review of consumer information search in online and offline environments

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

Purpose

The purpose of this study is to identify major themes and potential research opportunities in online and offline consumer search.

Design/methodology/approach

A systematic review was conducted based on 118 articles identified from prevalent journal databases. Keywords frequency analysis was carried out to identify the major themes. An inductive thematic analysis was carried out to verify the generated themes.

Findings

Results show that uncertainty, knowledge, perceived risk, price, experience and involvement are the major themes associated with consumer information search. Uncertainty, one of the major themes of offline search, has not been studied in the online search context. Similarly, the previous experience needs to be explored in the context of the offline search. Finally, potential research opportunities for future research has been summarized based on the retrieved themes.

Research limitations/implications

The systematic review provides an in-depth understanding on the current research on information search literature with future research directions.

Practical implications

This study helps retailers to understand the key elements that motivate consumers to perform external information searches from online and offline sources and to curate targeted information provision strategies to influence purchase decisions.

Social implications

Consumers with limited internet availability may access channels prior to decision-making. The themes identified in this study can aid policymakers to design affordable access to these channels.

Originality/value

This study adds to the sparse literature on systematic reviews on consumer search for online and offline channels.

Keywords
Uncertainty; Knowledge; Experience; Online/offline search

Keywords	Frequency
	Offline	Online
Knowledge	1,406	788
Price	1,157	995
Perceived risk	1,096	618
Experience	–	731
Involvement	816	500
Uncertainty	675	–

Themes	Findings	Major gaps identified
Uncertainty	• Knowledge uncertainty decreases the amount of offline information search because of the higher costs of search. Choice uncertainty increases the number of brands considered (*Urbany et al., 1989Urbany, J. E., Dickson, P. R., & Wilkie, W. L. (1989). Buyer uncertainty and information search. Journal of Consumer Research, 16(2), 208–215. doi: 10.1086/209209. https://doi.org/10.1086/209209... ). Knowledge and evaluation uncertainty decrease search intention whereas choice uncertainty increases search intention (Shiu et al., 2011Shiu, E. M., Walsh, G., Hassan, L. M., & Shaw, D. (2011). Consumer uncertainty, revisited. Psychology & Marketing, 28(6), 584–607. doi: 10.1002/mar.20402. https://doi.org/10.1002/mar.20402... ) • Higher level of categorization uncertainty limits the breadth of search (Ozanne et al., 1992Ozanne, J. L., Brucks, M., & Grewal, D. (1992). A study of information search behavior during the categorization of new products. Journal of Consumer Research, 18(4), 452–463. doi: 10.1086/209273. https://doi.org/10.1086/209273... ) • Amount of search increases with individual brand uncertainty. Consumers try to gather brand information from various sources including TV/radio/newspaper advertisements, magazine reports, salespersons and dealers. The total amount of search increases with relative brand uncertainty. Consumers rank the brands in the consideration set and gather information in a particular order and not in a random order (Moorthy et al., 1997Moorthy, S., Ratchford, B. T., & Talukdar, D. (1997). Consumer information search revisited: Theory and empirical analysis. Journal of Consumer Research, 23(4), 263–277. doi: 10.1086/209482. https://doi.org/10.1086/209482... ) • P1:* Uncertainty is positively related to offline information search	• The impact of uncertainty on online information search has not been explored • Scant attention has been given to this theme even in an offline context • Lack of empirical studies in comparison of the effect of uncertainty in online and offline information search
Perceived risk	• Higher the socioeconomic risk involved in the purchase decision, greater the importance and usage of information sources (Perry & Hamm, 1969Perry, M., & Hamm, B. C. (1969). Canonical analysis of relations between socioeconomic risk and personal influence in purchase decisions. Journal of Marketing Research, 6(3), 351–354. doi: 10.1177/002224376900600311. https://doi.org/10.1177/0022243769006003... ) • Products prone to social risk (e.g. men’s clothing) may require greater external information search mainly from personal sources including peer referents (Midgley, 1983Midgley, D. F. (1983). Patterns of interpersonal information seeking for the purchase of a symbolic product. Journal of Marketing Research, 20(1), 74–83. doi: 10.1177/002224378302000109. https://doi.org/10.1177/0022243783020001... ) • Results show the linkage between perceived risk and search through intervening variables of benefits and evoked-set size. Perceived risks have smaller effects on search effort (Srinivasan & Ratchford, 1991Srinivasan, N., & Ratchford, B. T. (1991). An empirical test of a model of external search for automobiles. Journal of Consumer Research, 18(2), 233–242. doi: 10.1086/209255. https://doi.org/10.1086/209255... ) • Consumers with higher product-category risk try to reduce the riskiness of a set of purchase tasks by gathering information from various sources (retailer, media, interpersonal and introspection). Consumers gather information regarding product price, quality rating in a product class and the product-specific risk increases information search. Consumers with higher acceptable risk seek more product information when compared to others (Dowling and Staelin, 1994Dowling, G. R., & Staelin, R. (1994). A model of perceived risk and intended risk-handling activity. Journal of Consumer Research, 21(1), 119–134. doi: 10.1086/209386. https://doi.org/10.1086/209386... ) • Perceived risk is positively related to the level of search conducted for different product categories (Chaudhuri, 1998Chaudhuri, A. (1998). Product class effects on perceived risk: The role of emotion. International Journal of Research in Marketing, 15(2), 157–168. doi: 10.1016/S0167-8116(97)00039-6. https://doi.org/10.1016/S0167-8116(97)00... ) • Functional risk influences consumers’ propensity to seek product-related information prior to purchases. Social risk does not influence consumers’ information seeking for product purchases (Dholakia, 2001Dholakia, U. M. (2001). A motivational process model of product involvement and consumer risk perception. European Journal of Marketing, 35(11/12), 1340–1362. doi: 10.1108/EUM0000000006479. https://doi.org/10.1108/EUM0000000006479... ) • Financial risk is not related to consumers preference for interpersonal sources. Even though consumers perceive performance risk, they will not necessarily favour personal sources (*Mourali et al., 2005Mourali, M., Laroche, M., & Pons, F. (2005). Antecedents of consumer relative preference for interpersonal information sources in pre‐purchase search. Journal of Consumer Behaviour, 4(5), 307–318. doi: 10.1002/cb.16. https://doi.org/10.1002/cb.16... ) • Functional risk affects on-going search negatively and does not have an impact on pre-purchase search. Emotional risk positively affects on-going and pre-purchase information search (Zhang & Hou, 2017*Zhang, Z., & Hou, Y. (2017). The effect of perceived risk on information search for innovative products and services: The moderating role of innate consumer innovativeness. Journal of Consumer Marketing, 34(3), 241–254. doi: 10.1108/JCM-04-2016-1768. https://doi.org/10.1108/JCM-04-2016-1768... ) • P2: Perceived risk is positively related to offline information search and online information search	• Very few studies exist on the relationship between perceived risk and online information search • Formation of antecedents of information search contexts in a combined fashion (online and offline) is understudied
Involvement	• Product involvement is positively related to an ongoing search. Enduring involvement in a product class is strongly and positively related to the propensity to engage in ongoing search (*Bloch et al., 1986Bloch, P. H., Sherrell, D. L., & Ridgway, N. M. (1986). Consumer search: An extended framework. Journal of Consumer Research, 13(1), 119–126. doi: 10.1086/209052. https://doi.org/10.1086/209052... ) • Purchase involvement is positively associated with external search efforts. Ego involvement is not associated with total search effort (Beatty & Smith, 1987Beatty, S. E., & Smith, S. M. (1987). External search effort: An investigation across several product categories. Journal of Consumer Research, 14(1), 83–95. doi: 10.1086/209095. https://doi.org/10.1086/209095... ) • Purchase involvement is a multidimensional construct. To avoid low construct reliability, it was deemed appropriate to use the purchase risk facet of purchase involvement and eliminate other measures. Results show that consumers with higher purchase risk engaged in greater external search (Smith & Bristor, 1994Smith, J. B., & Bristor, J. M. (1994). Uncertainty orientation: Explaining differences in purchase involvement and external search. Psychology and Marketing, 11(6), 587–607. doi: 10.1002/mar.4220110606. https://doi.org/10.1002/mar.4220110606... ) • Hedonic aspect of involvement is directly related to information search. The impact of the importance dimension on information search is not direct and is mediated by perceived risk (Chaudhuri, 2000Chaudhuri, A. (2000). A macro analysis of the relationship of product involvement and information search: The role of risk. Journal of Marketing Theory and Practice, 8(1), 1–15. doi: 10.1080/10696679.2000.11501856. https://doi.org/10.1080/10696679.2000.11... ) • The extent of use of information sources is higher for consumers with high/low involvement and with weak brand commitment and high involvement with strong brand commitment. However, low involvement consumers with strong band commitment are less likely to be influenced by sources of brand information (Warrington & Shim, 2000Warrington, P., & Shim, S. (2000). An empirical investigation of the relationship between product involvement and brand commitment. Psychology and Marketing, 17(9), 761–782. doi: 10.1002/1520-6793(200009)17:9<761::AID-MAR2>3.0.CO;2-9. https://doi.org/10.1002/1520-6793(200009... ) • Perception of play will be higher in high product involvement information search contexts when compared to low involvement conditions (Mathwick & Rigdon, 2004Mathwick, C., & Rigdon, E. (2004). Play, flow, and the online search experience. Journal of Consumer Research, 31(2), 324–332. doi: 10.1086/422111. https://doi.org/10.1086/422111... ) • Enduring product involvement is positively related to the use of online and offline information sources (van Rijnsoever et al., 2012van Rijnsoever, F. J., Castaldi, C., & Dijst, M. J. (2012). In what sequence are information sources consulted by involved consumers? The case of automobile pre-purchase search. Journal of Retailing and Consumer Services, 19(3), 343–352. doi: 10.1016/j.jretconser.2012.03.008. https://doi.org/10.1016/j.jretconser.201... ) • P3:* Involvement is positively related to offline information search, online information search, offline and online information search	• Extant research has made little attempt to investigate the role of involvement as an influencing factor, which triggers the online and offline search • Only a few studies exist on the determination of its impact on online information search
Knowledge	• Prior stored knowledge is positively related to external information search (Moore & Lehmann, 1980Moore, W. L., & Lehmann, D. R. (1980). Individual differences in search behavior for a nondurable. Journal of Consumer Research, 7(3), 296–307. doi: 10.1086/208817. https://doi.org/10.1086/208817... ) • There are two components of prior knowledge: specific product knowledge and general product-class knowledge. Specific product knowledge causes lesser external search whereas general product-class knowledge results in more external search (Punj & Staelin, 1983Punj, G. N., & Staelin, R. (1983). A model of consumer information search behavior for new automobiles. Journal of Consumer Research, 9(4), 366–380. doi: 10.1086/208931. https://doi.org/10.1086/208931... ) • Subjective knowledge is positively related to search variability and negatively related to search for retailer evaluations. The inappropriateness of search is less strongly related to consumers’ subjective knowledge. Search variability increases for consumers with higher objective knowledge (Brucks, 1985Brucks, M. (1985). The effects of product class knowledge on information search behavior. Journal of Consumer Research, 12(1), 1–16. doi: 10.1086/209031. https://doi.org/10.1086/209031... ) • Positive relationship is found between objective knowledge/expertise and total search time. An inverted U relation exists between subjective knowledge/expertise and total search time (Klein & Ford, 2003Klein, L. R., & Ford, G. T. (2003). Consumer search for information in the digital age: An empirical study of prepurchase search for automobiles. Journal of Interactive Marketing, 17(3), 29–49. doi: 10.1002/dir.10058. https://doi.org/10.1002/dir.10058... ) • Men with lower subjective knowledge gather information from the retail clerk for assistance compared to other sources while buying wine offline (*Barber et al., 2009Barber, N., Dodd, T., & Kolyesnikova, N. (2009). Gender differences in information search: Implications for retailing. Journal of Consumer Marketing, 26(6), 415–426. doi: 10.1108/07363760910988238. https://doi.org/10.1108/0736376091098823... ) • Amount of online consumer information search decreases with an increase in consumers’ prior knowledge (Rose & Samouel, 2009Rose, S., & Samouel, P. (2009). Internal psychological versus external market-driven determinants of the amount of consumer information search amongst online shoppers. Journal of Marketing Management, 25(1/2), 171–190. doi: 10.1362/026725709X410089. https://doi.org/10.1362/026725709X410089... ). • Product knowledge has a significant effect on duration, cycles and alternatives. There exists a negative relationship between knowledge and intensity of the decision-making process (Karimi, Papamichail, and Holland, 2015Karimi, S., Papamichail, K. N., & Holland, C. P. (2015). The effect of prior knowledge and decision-making style on the online purchase decision-making process: A typology of consumer shopping behaviour. Decision Support Systems, 77, 137–147. doi: 10.1016/j.dss.2015.06.004. https://doi.org/10.1016/j.dss.2015.06.00... ) • Subjective knowledge has a positive impact on the proportion of time spent online conducting information searches using personal information sources (Gallant & Arcand, 2017Gallant, I., & Arcand, M. (2017). Consumer characteristics as drivers of online information searches. Journal of Research in Interactive Marketing, 11(1), 56–74. doi: 10.1108/JRIM-11-2014-0071. https://doi.org/10.1108/JRIM-11-2014-007... ) • P4:* Knowledge is positively related to offline information search, online information search, offline and online information search	• The effect of knowledge on online and offline channels require further attention as not much studies exist on this relationship
Price	• More search helps consumers to acquire products at lower prices, thereby increasing the purchased quantity (Carlson & Gieseke, 1983Carlson, J. A., & Gieseke, R. J. (1983). Price search in a product market. Journal of Consumer Research, 9(4), 357–365. doi: 10.1086/208930. https://doi.org/10.1086/208930... ) • Amount of search is higher for greater perceived price dispersion (Putrevu & Ratchford, 1997Putrevu, S., & Ratchford, B. T. (1997). A model of search behavior with an application to grocery shopping. Journal of Retailing, 73(4), 463–486. doi: 10.1016/S0022-4359(97)90030-0. https://doi.org/10.1016/S0022-4359(97)90... ) • Price has a smaller impact on consumer choices and online information search when compared to traditional supermarkets (*Degeratu et al., 2000Degeratu, A. M., Rangaswamy, A., & Wu, J. (2000). Consumer choice behavior in online and traditional supermarkets: The effects of brand name, price, and other search attributes. International Journal of Research in Marketing, 17(1), 55–78. doi: 10.1016/S0167-8116(00)00005-7. https://doi.org/10.1016/S0167-8116(00)00... ) • High search segment engages in greater price comparisons of products when compared to others (Putrevu & Lord, 2001Putrevu, S., & Lord, K. R. (2001). Search dimensions, patterns and segment profiles of grocery shoppers. Journal of Retailing and Consumer Services, 8(3), 127–137. doi: 10.1016/S0969-6989(00)00013-8. https://doi.org/10.1016/S0969-6989(00)00... ) • Consumers with higher price sensitivity actively search across brands to find lower prices (Mehta et al., 2003Mehta, N., Rajiv, S., & Srinivasan, K. (2003). Price uncertainty and consumer search: A structural model of consideration set formation. Marketing Science, 22(1), 58–84. doi: 10.1287/mksc.22.1.58.12849. https://doi.org/10.1287/mksc.22.1.58.128... ) • Consumers spend significant time gathering price information from online sources (Ratchford et al., 2003Ratchford, B. T., Lee, M. S., & Talukdar, D. (2003). The impact of the internet on information search for automobiles. Journal of Marketing Research, 40(2), 193–209. doi: 10.1509/jmkr.40.2.193.19221. https://doi.org/10.1509/jmkr.40.2.193.19... ) • Search increases with sticker price and internet substitute the time spent in price negotiation with the dealer (Ratchford, Talukdar, and Lee, 2007Ratchford, B. T., Talukdar, D., & Lee, M. S. (2007). The impact of the internet on consumers' use of information sources for automobiles: A re-inquiry. Journal of Consumer Research, 34(1), 111–119. doi: 10.1086/513052. https://doi.org/10.1086/513052... ) • Price consciousness will significantly increase online information search (Seock & Bailey, 2008Seock, Y. K., & Bailey, L. R. (2008). The influence of college students' shopping orientations and gender differences on online information searches and purchase behaviours. International Journal of Consumer Studies, 32(2), 113–121. doi: 10.1111/j.1470-6431.2007.00647.x. https://doi.org/10.1111/j.1470-6431.2007... ) • Price is negatively related to the use of online and offline information sources (Kulkarni et al., 2012Kulkarni, G., Ratchford, B. T., & Kannan, P. K. (2012). The impact of online and offline information sources on automobile choice behavior. Journal of Interactive Marketing, 26(3), 167–175. doi: 10.1016/j.intmar.2012.02.001. https://doi.org/10.1016/j.intmar.2012.02... ) • Consumers rely on online price comparison sites to gain price information and later evaluate prices and shop at offline stores (Bodur, Klein, and Arora, 2015Bodur, H. O., Klein, N. M., & Arora, N. (2015). Online price search: Impact of price comparison sites on offline price evaluations. Journal of Retailing, 91(1), 125–139. doi: 10.1016/j.jretai.2014.09.003. https://doi.org/10.1016/j.jretai.2014.09... ) • Price consciousness results in more WOM communication online than offline (Scarpi et al., 2014Scarpi, D., Pizzi, G., & Visentin, M. (2014). Shopping for fun or shopping to buy: Is it different online and offline?. Journal of Retailing and Consumer Services, 21(3), 258–267. doi: 10.1016/j.jretconser.2014.02.007. https://doi.org/10.1016/j.jretconser.201... ) • Price has a positive impact on online review intentions (Moriuchi & Takahashi, 2018Moriuchi, E., & Takahashi, I. (2018). An empirical investigation of the factors motivating Japanese repeat consumers to review their shopping experiences. Journal of Business Research, 82, 381–390. doi: 10.1016/j.jbusres.2017.07.024. https://doi.org/10.1016/j.jbusres.2017.0... ) • P5:* Price is positively related to offline information search, online information search, offline and online information search	• The effect of price on consumers’ online and offline information search has not been captured much by the researchers
Experience	• Market experience is positively related to consumer’s propensity to search for lower prices (Goldman & Johansson, 1978Goldman, A., & Johansson, J. K. (1978). Determinants of search for lower prices: An empirical assessment of the economics of information theory. Journal of Consumer Research, 5(3), 176–186. doi: 10.1086/208729. https://doi.org/10.1086/208729... ) • Purchase experience through the internet has a positive impact on the usage of the internet for product information search (Shim, Eastlick, Lotz, and Warrington, 2001Shim, S., Eastlick, M. A., Lotz, S. L., & Warrington, P. (2001). An online prepurchase intentions model: The role of intention to search. Journal of Retailing, 77(3), 397–416. doi: 10.1016/S0022-4359(01)00051-3. https://doi.org/10.1016/S0022-4359(01)00... ) • Consumers with higher previous internet experience will use online sources for information search and purchase when compared to others (Park & Stoel, 2005Park, J., & Stoel, L. (2005). Effect of Brand familiarity, experience and information on online apparel purchase. International Journal of Retail & Distribution Management, 33(2), 148–160. doi: 10.1108/09590550510581476. https://doi.org/10.1108/0959055051058147... ) • Presence of experience simulation and prior experiences increases the time spent on a website (*Huang et al., 2009Huang, P., Lurie, N. H., & Mitra, S. (2009). Searching for experience on the web: An empirical examination of consumer behavior for search and experience goods. Journal of Marketing, 73(2), 55–69. doi: 10.1509/jmkg.73.2.55. https://doi.org/10.1509/jmkg.73.2.55... ) • Internet experience will decrease the relative importance of information sources (online and offline) for internet purchases (Cheema and Papatla, 2010Cheema, A., & Papatla, P. (2010). Relative importance of online versus offline information for internet purchases: Product category and internet experience effects. Journal of Business Research, 63(9/10), 979–985. doi: 10.1016/j.jbusres.2009.01.021. https://doi.org/10.1016/j.jbusres.2009.0... ) • Experienced internet users do a larger proportion of total search on the internet when compared to others (Dutta & Das, 2017Dutta, C. B., & Das, D. K. (2017). What drives consumers' online information search behavior? Evidence from England. Journal of Retailing and Consumer Services, 35, 36–45. doi: 10.1016/j.jretconser.2016.10.015. https://doi.org/10.1016/j.jretconser.201... ) • P6:* Experience is positively related to offline information search, online information search, offline and online information search	• Researchers have not captured the effect of experience on offline information search • Studies on the relationship between experience and online and offline information search are sparse

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E-mail: rausp@usp.br

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[1] *Corresponding author Anu C. Haridasan can be contacted at: anudas4@gmail.com