How Is Mobile User Behavior Different? A Hidden Markov Model of Cross-Mobile Application Usage Dynamics

References

• Abhishek V, Fader PS, Hosanagar K (2013) Media exposure through the funnel: A model of multi-stage attribution. Working paper, Carnegie Mellon University, Pittsburgh.Google Scholar
• Babin BJ, Darden WR, Griffin M (1994) Work and/or fun: Measuring hedonic and utilitarian shopping value. J. Consumer Res. 20(4):644–656.Crossref, Google Scholar
• Bhat CR, Misra R (1999) Discretionary activity time allocation of individuals between in-home and out-of-home and between weekdays and weekends. Transportation 26(2):193–229.Crossref, Google Scholar
• Bitner MJ (1992) Servicescapes: The impact of physical surroundings on customers and employees. J. Marketing 56(2):57–71.Crossref, Google Scholar
• Botti S, McGill AL (2010) The locus of choice: Personal causality and satisfaction with hedonic and utilitarian decisions. J. Consumer Res. 37(6):1065–1078.Crossref, Google Scholar
• Brown SA, Venkatesh V (2005) Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. Management Inform. Systems Quart. 29(3):399–426.Crossref, Google Scholar
• Chaiken S, Liberman A, Eagly AH (1989) Heuristic and systematic information processing within and beyond the persuasion context. Uleman JS, Bargh JA, York N, eds. Unintended Thought Guilford), 212–252.Google Scholar
• Chaudhuri A, Aboulnasr K, Ligas M (2010) Emotional responses on initial exposure to hedonic or utilitarian description of a radical innovation. J. Marketing Theory Practice 18(4):339–359.Crossref, Google Scholar
• Chitturi R, Raghunathan R, Mahajan V (2008) Delight by design: The role of hedonic vs. utilitarian benefits. J. Marketing 72(3):48–63.Crossref, Google Scholar
• Collins K, Shiffman D, Rock J (2016) How are scientists using social media in the workplace? PLoS One 11(10):e0162680.Crossref, Google Scholar
• Danziger S, Levav J, Avnaim-Pesso L (2011) Extraneous factors in judicial decisions. Proc. National Acad. Sci. USA 108(17):6889–6892.Crossref, Google Scholar
• Ding AW, Li S, Chatterjee P (2015) Learning user real-time intent for optimal dynamic web page transformation. Inform. Systems Res. 26(2):339–359.Link, Google Scholar
• Donovan RJ, Rossiter JR (1982) Store atmosphere: An environmental psychology approach. J. Retailing 58(1):34–57.Google Scholar
• Fang Z, Gu B, Luo X, Xu Y (2015) Contemporaneous and delayed sales impact of location-based mobile promotions. Inform. Systems Res. 26(3):552–564.Link, Google Scholar
• Fong N, Fang Z, Luo X (2015) Geo-conquesting: Competitive locational targeting of mobile promotions. J. Marketing Res. 52(5):726–735.Crossref, Google Scholar
• Goldberg ME, Gorn GJ (1987) Happy and sad TV programs: How they affect reactions to commercials. J. Consumer Res. 14(3):387–403.Crossref, Google Scholar
• Griffin M, Babin BJ, Modianos D (2000) Shopping values of russian consumers: The impact of habituation in a developing economy. J. Retailing 76(1):33–52.Crossref, Google Scholar
• Hadlington LJ (2015) Cognitive failures in daily life: Exploring the link with Internet addiction and problematic mobile phone use. Comput. Human Behav. 51:75–81.Crossref, Google Scholar
• Hamilton JD (1989) A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 57(2):357–384.Crossref, Google Scholar
• Han SP, Park S, Oh W (2016) Mobile app analytics: A multiple discrete-continuous choice framework. Management Inform. Systems Quart. 40(4):983–1008.Crossref, Google Scholar
• Heckman J, Singer B (1984) A method for minimizing the impact of distributional assumptions in econometric models for duration data. Econometrica 52(2):271–320.Crossref, Google Scholar
• Hirschman EC (1984) Experience seeking: A subjectivist perspective of consumption. J. Bus. Res. 12(1):115–136.Crossref, Google Scholar
• Janiszewski C (1998) The influence of display characteristics on visual exploratory search behavior. J. Consumer Res. 25(3):290–301.Crossref, Google Scholar
• Jarboe GR, McDaniel CD (1987) A profile of browsers in regional shopping malls. J. Acad. Marketing Sci. 15(1):46–53.Crossref, Google Scholar
• Laurent G, Kapferer JN (1985) Measuring consumer involvement profiles. J. Marketing Res. 22(1):41–53.Crossref, Google Scholar
• Luo L, Ratchford BT, Yang B (2013) Why we do what we do: A model of activity consumption. J. Marketing Res. 50(1):24–43.Crossref, Google Scholar
• Luo X, Andrews M, Fang Z, Phang CW (2014) Mobile targeting. Management Sci. 60(7):1738–1756.Link, Google Scholar
• MacDonald IL, Zucchini W (1997) Hidden Markov and Other Models for Discrete-Valued Time Series (Chapman & Hall/CRC).Google Scholar
• Mattila AS, Wirtz J (2001) Congruency of scent and music as a driver of in-store evaluations and behaviour. J. Retailing 77(2):273–289.Crossref, Google Scholar
• Moe WW (2003) Buying, searching, or browsing: Differentiating between online shoppers using in-store navigational clickstream. J. Consumer Psych. 13(1-2):29–39.Crossref, Google Scholar
• Montgomery AL, Li S, Srinivasan K, Liechty JC (2004) Modeling online browsing and path analysis using clickstream data. Marketing Sci. 23(4):579–595.Link, Google Scholar
• Netzer O, Lattin JM, Srinivasan V (2008) A hidden Markov model of customer relationship dynamics. Marketing Sci. 27(2):185–204.Link, Google Scholar
• Park WC, Iyer ES, Smith DC (1989) The effects of situational factors on in-store grocery shopping behavior: The role of store environment and time available for shopping. J. Consumer Res. 15(4):422–433.Crossref, Google Scholar
• Park MH, Park EJ, Choi J, Chai S, Lee JH, Lee C, Kim DJ (2011) preliminary study of internet addiction and cognitive function in adolescents based on IQ tests. Psychiatry Res. 190(2-3):275–281.Crossref, Google Scholar
• Phang CW, Luo X, Fang Z (2019) Mobile time-based targeting: Matching product-value appeal to time of day. J. Management Inform. Systems 36(2):513–545.Crossref, Google Scholar
• Rabiner LR (1989) A tutorial on hidden Markov models and selected applications in speech recognition. Proc. IEEE 77:257–286.Crossref, Google Scholar
• Sedani A, Stover D, Coyle B, Wani RJ (2019) Assessing workplace health and safety strategies, trends, and barriers through a statewide worksite survey. Internat. J. Environ. Res. Public Health 16(4):2475.Crossref, Google Scholar
• Sherry JF, McGrath M, Levy SJ (1993) The dark side of the gift. J. Bus. Res. 28(3):225–245.Crossref, Google Scholar
• Shin C, Hong JH, Dey AK (2012). Understanding and prediction of mobile application use for smart phones. Proc. ACM Conf. on Ubiquitous Comput., 173–182.Google Scholar
• Singh PV, Sahoo N, Mukhopadhyay T (2014) How to attract and retain readers in enterprise blogging? Inform. Systems Res. 25(1):35–52.Link, Google Scholar
• Singh PV, Tan Y, Youn N (2011) A hidden Markov model of developer learning dynamics in open source software projects. Inform. Systems Res. 22(4):790–807.Link, Google Scholar
• Sledgianowski D, Kulviwat S (2009) Using social network sites: The effects of playfulness, critical mass and trust in a hedonic context. J. Comput. Inform. Systems 49(4):74–83.Crossref, Google Scholar
• Small GW, Moody TD, Siddarth P, Bookheimer SY (2009) Your brain on Google: Patterns of cerebral activation during internet searching. Amer. J. Geriatric Psychiatry 17(2):116–126.Crossref, Google Scholar
• Spangenberg ER, Grohmann B, Sprott DE (2005) It’s beginning to smell (and sound) a lot like Christmas: The interactive effects of ambient scent and music in a retail setting. J. Bus. Res. 58(11):1583–1589.Crossref, Google Scholar
• Suri R, Monroe KB (2003) The effects of time constraints on consumers’ judgments of prices and products. J. Consumer Res. 30(1):92–104.Crossref, Google Scholar
• Voss KE, Spangenberg ER, Grohmann B (2003) Measuring the hedonic and utilitarian dimensions of consumer attitude. J. Marketing Res. 40(3):310–320.Crossref, Google Scholar
• Wang YJ, Minor MS, Wei J (2011) Aesthetics and the online shopping environment: Understanding consumer responses. J. Retailing 87(1):46–58.Crossref, Google Scholar
• Xu J, Forman C, Kim JB, Van Ittersum K (2014) News media channels: Complements or substitutes? Evidence from mobile phone use. J. Marketing 78(4):97–112.Crossref, Google Scholar
• Yan L, Tan Y (2014) Feeling blue? Go online: An empirical study of social support among patients. Inform. Systems Res. 25(4):690–709.Link, Google Scholar
• Yang S, Allenby GM, Fennell G (2002) Modeling variation in brand preference: The roles of objective environment and motivating conditions. Marketing Sci. 21(1):14–31.Link, Google Scholar
• Yoon C, Lee MP, Danziger S (2007) The effects of optimal time of day on persuasion processes in older adults. Psych. Marketing 24(5):475–495.Crossref, Google Scholar
• Zaichkowsky JL (1985) Measuring the involvement construct. J. Consumer Res. 12(3):341–352.Crossref, Google Scholar
• Zhang Y, Li B, Luo X, Wang X (2019) Personalized mobile targeting with user engagement stages: Combining a structural hidden markov model and field experiment. Inform. Systems Res. 30(3):787–804.Link, Google Scholar
• Zheng J, Qi Z, Dou Y, Tan Y (2019) How mega is the mega? Exploring the spillover effects of WeChat using graphical model. Inform. Systems Res. 30(4):1343–1362.Link, Google Scholar
• Zheng Y, Zhang L, Xie X, Ma WY (2009). Mining interesting locations and travel sequences from GPS trajectories. Proc. 18th Internat. Conf. on World Wide Web, 791–800.Google Scholar