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Everywhere and at All Times: Mobility, Consumer Decision-Making, and Choice

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Abstract

Advancements in mobile technologies mean that consumers can engage the digital world wherever they are and whenever they want. This intersection between the digital and the physical has important implications for consumer decision-making. We propose that mobile ecosystems vary in their capabilities and pervasivity (i.e., the degree to which a mobile ecosystem is accessible everywhere and at all times). Further, we propose that accounting for distinguishing aspects of mobile ecosystems, the context in which mobile ecosystems are used, and interactions between mobile ecosystems and mobile contexts are critical in advancing theoretical and substantive understanding of the role of mobile technologies in the marketplace. Based on this perspective, we identify important research topics as well as opportunities and challenges for modeling mobile consumer decision-making.

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References

  1. Aguirregabiria V, Mira P (2010) Dynamic discrete choice structural models: a survey. J Econ 156(1):38–67

    Article  Google Scholar 

  2. Andrews M, Goehring J, Hui S, Pancras J, Thornswood L (2016) Mobile promotions: a framework and research priorities. J Int Mark 34(May):15–24

    Article  Google Scholar 

  3. Barnard L, Yi JS, Jacko JA, Sears A (2007) Capturing the effects of context on human performance in mobile computing systems. Pers Ubiquit Comput 11(2):81–96

    Article  Google Scholar 

  4. Bart Y, Stephen AT, Sarvary M (2014) Which products are best suited to mobile advertising? A field study of mobile display advertising effects on consumer attitudes and intentions. J Mark Res 51(3):270–285

    Article  Google Scholar 

  5. Belk RW (2013) Extended self in a digital world. J Consum Res 40(3):477–500

    Article  Google Scholar 

  6. Berger J, Heath C (2007) Where consumers diverge from others: identity signaling and product domains. J Consum Res 34(2):121–134

    Article  Google Scholar 

  7. Biswas D, Biswas A, Das N (2006) The differential effects of celebrity and expert endorsements on consumer risk perceptions. The role of consumer knowledge, perceived congruency, and product technology orientation. J Advert 35(2):17–31

    Article  Google Scholar 

  8. Brasel SA, Gips J (2014) Tablets, touchscreens, and touchpads: how varying touch interfaces trigger psychological ownership and endowment. J Consum Psychol 24(2):226–233

    Article  Google Scholar 

  9. Casasanto D, Boroditsky L (2008) Time in the mind: using space to think about time. Cognition 106(2):579–593

    Article  Google Scholar 

  10. Ching AT, Erdem T, Keane MP (2013) Learning models: an assessment of progress, challenges, and new developments. Mark Sci 32(6):913–938

  11. Danaher PJ, Dagger TS (2013) Comparing the relative effectiveness of advertising channels: a case study of a multimedia blitz campaign. J Mark Res 50(4):517–534

    Article  Google Scholar 

  12. Diehl K, Zauberman G, Barasch A (2016) How taking photos increases enjoyment of experiences. JPSP 111(2):119–140

    Google Scholar 

  13. Escalas JE (2004) Imagine yourself in the product. J Advert 33(2):37–48

    Article  Google Scholar 

  14. Feldman JM, Lynch JGJ (1988) Self-generated validity and other effects of measurement on belief, attitude, intention, and behavior. J Appl Psychol 73(3):421–435

    Article  Google Scholar 

  15. Fisher M, Goddu MK, Keil FC (2015) Searching for explanations: how the internet inflates estimates of internal knowledge. J Exp Psychol Gen 144(3):674–687

    Article  Google Scholar 

  16. Fong NM, Fang Z, Luo X (2015) Geo-conquesting: competitive locational targeting of mobile promotions. J Mark Res 52(5):726–735

    Article  Google Scholar 

  17. Friedman SA (2013) Phones, friends, and flu shots: how phone attachment can affect pain perceptions (Honors thesis). Cornell University, Ithaca

  18. Ghose A, Goldfarb A, Han SP (2013) How is the mobile internet different? Search costs and local activities. Inf Syst Res 24(3):613–631

    Article  Google Scholar 

  19. Grewal D, Bart Y, Spann M, Zubcsek PP (2016) Mobile advertising: a framework and research agenda. J Int Mark 34:3–14

    Article  Google Scholar 

  20. Inman JJ (2012) The elephant not in the room: the need for useful, actionable insights in behavioral research. In: Gürhan-Canli Z, Otnes C, Zhu RJ (eds) NA—advances in consumer research, vol 40. Association for Consumer Research, Duluth, pp 1–4

    Google Scholar 

  21. Iyengar SS, Lepper MR (2000) When choice is demotivating: can one desire too much of a good thing? JPSP 79(6):995–1006

    Google Scholar 

  22. Kahneman D (2011) Thinking, fast and slow. Farrar, Straus, and Giroux, New York

  23. Kardes FR, Kalyanaram G, Chandrashekaran M, Dornoff RJ (1993) Brand retrieval, consideration set composition, consumer choice, and the pioneering advantage. J Consum Res 20(1):62–75

    Article  Google Scholar 

  24. Kardes FR, Cronley ML, Kellaris JJ, Posavac SS (2004) The role of selective information processing in price-quality inference. J Consum Res 31(2):368–374

    Article  Google Scholar 

  25. Koufaris M (2002) Applying the technology acceptance model and flow theory to online consumer behavior. Inf Syst Res 13(2):205–223

    Article  Google Scholar 

  26. Lamberton C, Stephen AT (2016) A thematic exploration of digital, social media, and mobile marketing: research evolution from 2000 to 2015 and an agenda for future inquiry. J Mark 80(6):146–172

    Article  Google Scholar 

  27. Leonardi PM (2011) When flexible routines meet flexible technologies: affordance, constraint, and the imbrication of human and material agencies. MIS Q 35(1):147–167

    Article  Google Scholar 

  28. Luan YJ, Sudhir K (2010) Forecasting marketing-mix responsiveness for new products. J Mark Res 47(3):444–457

    Article  Google Scholar 

  29. Luo X, Andrews M, Fang Z, Phang CW (2013) Mobile targeting. Manag Sci 60(7):1738–1756

    Article  Google Scholar 

  30. Lurie NH (2004) Decision making in information-rich environments: the role of information structure. J Consum Res 30:473–486

    Article  Google Scholar 

  31. Lurie NH, Ransbotham S, Liu H (2014) The characteristics and perceived value of mobile word of mouth. Marketing Science Institute Working Paper Series. Report No. 14–109

  32. Manchanda P, Rossi PE, Chintagunta PK (2004) Response modeling with nonrandom marketing-mix variables. J Mark Res 41(4):467–478

    Article  Google Scholar 

  33. Maniar N, Bennett E, Hand S, Allan G (2008) The effect of mobile phone screen size on video based learning. J Softw 3(4):51–61

    Article  Google Scholar 

  34. Novak TP, Hoffman DL (2016) Visualizing emergent identity of assemblages in the consumer internet of things: a topological data analysis approach. doi:10.2139/ssrn.2840962

  35. Petty RE, Cacioppo JT (1986) The elaboration likelihood model of persuasion. In: Berkowitz L (ed) Advances in experimental social psychology, vol 19. Academic Press, San Diego

    Google Scholar 

  36. Pornpitakpan C (2004) The persuasiveness of source credibility: a critical review of five decades’ evidence. J Appl Soc Psychol 34(2):243–281

    Article  Google Scholar 

  37. Sarnato V (2013) New survey finds Americans treat mobile devices like their best friends. Brighthand. February 24. Retrieved from http://www.brighthand.com/news/new-survey-finds-americans-treat-mobile-devices-like-their-best-friends/.

  38. Schlosser AE, Barnett White T, Lloyd SM (2006) Converting web site visitors into buyers: how web site investment increases consumer trusting beliefs and online purchase intentions. J Mark 70(April):133–148

    Article  Google Scholar 

  39. Shankar V, Inman JJ, Mantrala M, Kelley E, Rizley R (2011) Innovations in shopper marketing: current insights and future research issues. J Retail 87(1):S29–S42

    Article  Google Scholar 

  40. Shiv B, Fedorikhin A (1999) Heart and mind in conflict: the interplay of affect and cognition in consumer decision making. J Consum Res 26(3):278–292

    Article  Google Scholar 

  41. Simonson I (2015) Mission (largely) accomplished: what’s next for consumer BDT-JDM researchers? J Mark Behav 1(1):9–35

    Article  Google Scholar 

  42. Soman D, Ainslie G, Frederick S, Li X, Lynch J, Moreau P, Mitchell A, Read D, Sawyer A, Trope Y (2005) The psychology of intertemporal discounting: why are distant events valued differently from proximal ones? Mark Lett 16(3–4):347–360

    Article  Google Scholar 

  43. Suh K-S, Lee YE (2005) The effects of virtual reality on consumer learning: an empirical investigation. MIS Q:673–697

  44. Sultan F, Rohm A (2005) The coming era of “brand in the hand” marketing. MIT Sloan Manag Rev 47(1):83–90

  45. Turkle S (2008) Always-on/always-on-you: the tethered self. In: Katz JE (ed) Handbook of mobile communication studies. MIT Press, Cambridge, pp 121–137

    Chapter  Google Scholar 

  46. Turkle S (2012) Alone together: why we expect more from technology and less from each other. Basic Books, New York

    Google Scholar 

  47. Wang RJ-H, Malthouse EC, Krishnamurthi L (2015) On the go: how mobile shopping affects customer purchase behavior. J Retail 91(2):217–234

    Article  Google Scholar 

  48. Ward AF, Duke K, Gneezy A, Bos MW (2017) Brain drain: the mere presence of one’s own smartphone reduces available cognitive capacity. J Assoc Consum Res 2(2):140–154

    Article  Google Scholar 

  49. Yadav MS, Pavlou PA (2014) Marketing in computer-mediated environments: research synthesis and new directions. J Mark 78(1):20–40

    Article  Google Scholar 

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Correspondence to Nicholas H. Lurie.

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Contribution Statement

We add to empirical research on mobile marketing by developing a conceptual framework that identifies how characteristics of mobile ecosystems and mobile contexts are likely to affect consumer behavior. Drawing on research in psychology, marketing, and information systems, we identify theoretical antecedents and psychological mechanisms that should affect mobile consumer information search, consideration set formation, and choice. Based on this perspective, we identify important research topics as well as opportunities and challenges for modeling mobile consumer decision-making.

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This paper is based on a workshop at the 2016 Invitational Choice Symposium, Lake Louise, Alberta.

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Lurie, N.H., Berger, J., Chen, Z. et al. Everywhere and at All Times: Mobility, Consumer Decision-Making, and Choice. Cust. Need. and Solut. 5, 15–27 (2018). https://doi.org/10.1007/s40547-017-0076-9

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