Abstract
The internet of things has changed the way we interact with information system. With the pervasive information system facing various complexities of end clients, the development mode based on semantic association and context-awareness made it possible to provide personalized service for each client. In this paper, the context-awareness-based ambient intelligence predicts users’ intention to use depending on the contexts they provide. By applying the prediction to logistics services, it can provide customized service to keep clients satisfied. A key issue in user-centered services is how to detect each user specific situation and choose a certain service that meets users’ requirements the best, and then to provide support for real-time decision making. We believe that the complishment of ambient intelligence cannot be separated from technology support when it comes to intelligent behavior.


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Albadarneh A, Qusef A (2017) Personalization in mobile commerce. In: International conference on information technology, pp 889–894
Azimi I, Rahmani AM, Liljeberg P, Tenhunen H (2017) Internet of things for remote elderly monitoring: a study from user-centered perspective. J Ambient Intell Hum Comput 8(2):1–17
Bienstock CC, Mentzer JT, Bird MM (1997) Measuring physical distribution service quality. J Acad Mark Sci 25(1):31–44
Chellappa RK, Sin RG (2005) Personalization versus privacy: an empirical examination of the online consumer’s dilemma. Inf Technol Manag 6:181–202
Corno F, Russis LD (2017) Training engineers for the ambient intelligence challenge. IEEE Trans Educ 60(1):41–49
Dholakia RR, Miao Z, Dholakia N, Fortin DR (2000) Interactivity and revisits to websites: a theoretical framework. RITIM Working Paper, 2000. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.108.1748&rep=rep1&type=pdf. Accessed 29 Aug 2018
Ghiani G, Polet J, Antila V, Mäntyjärvi J (2013) Evaluating context-aware user interface migration in multi-device environments. J Ambient Intell Hum Comput 6(2):1–19
Goldsmith J, Junker U (2009) Preference handling for artificial intelligence. AI Mag 29(4):9
Hennington A, Janz B, Poston R (2011) I’m just burned out: understanding information system compatibility with personal values and role-based stress in a nursing context. Comput Hum Behav 27(3):1238–1248
Homola M, Patkos T, Flouris G, Šefránek J, Šimko A, Frtús J, Zografistou D, Baláž M (2015) Resolving conflicts in knowledge for ambient intelligence. Knowl Eng Rev 30(05):455–513
Hsu SL, Chu FY (2014) A user study on the adoption of context-aware destination mobile applications. World Acad Sci 8(7):2296–2300
Ilham NF, Handayani PW, Azzahro F (2017) The effects of pictures, review credibility and personalization on users satisfaction of using restaurant recommender apps: case study: Zomato dan qraved. In: International conference on informatics and computing, pp 1–6
Jaroucheh Z, Liu X, Smith S (2012) An approach to domain-based scalable context management architecture in pervasive environments. Pers Ubiquitous Comput 16(6):741–755
Kim S, Yoon YI (2017) Ambient intelligence middleware architecture based on awareness-cognition framework. J Ambient Intell Hum Comput. https://doi.org/10.1007/s12652-017-0647-5
Lee C, Ke CH, Siau KA (2017a) Prediction-based query processing strategy in mobile commerce systems. J Database Manag 12(3):14–26
Lee J, Chang HL, Kim DW, Kang BY (2017b) Smartphone-assisted pronunciation learning technique for ambient intelligence. IEEE Access 5(99):312–325
McMillan SJ, Hwang JS (2002) Measures of perceived interactivity: an exploration of the role of direction of communication, user control, and time in shaping perceptions of interactivity. J Advert 31(3):29–42
Mentzer JT, Flint DJ, Kent JL (1999) Developing a logistics service quality scale. J Bus Logist 20(1):9–32
Mentzer JT, Flint DJ, Hult GTM (2001) Logistics service quality as a segment-customized process. J Mark 65(4):82–104
Najar S, Pinheiro MK, Souveyet C (2015) Service discovery and prediction on pervasive information system. J Ambient Intell Hum Comput 6(4):407–423
Oguego CL, Augusto JC, Muñoz A, Springett M (2018a) A survey on managing users’ preferences in ambient intelligence. Universal Access in the Information Society, vol 2, pp 1–18
Oguego CL, Augusto JC, Muñoz A, Springett M (2018b) Using argumentation to manage users’ preferences. Future Gener Comput Syst 81:235–243
Orsini G, Bade D, Lamersdorf W (2016) Generic context adaptation for mobile cloud computing environments. Procedia Comput Sci 94:17–24
Otebolaku AM, Andrade MT (2015) Context-aware media recommendations for smart devices. J Ambient Intell Hum Comput 6(1):13–36
Parasuraman A, Zeithaml VA, Berry LL (1985) A conceptual model of service quality and its implications for future research. J Mark 49:41–50
Parasuraman A, Zeithaml VA, Berry LL (1988) Communication and control processes in the delivery of service quality. J Mark 52(4):35–48
Rafaeli S, Sudweeks F (1997) Networked interactivity. J Comput Mediat Commun 2(4). https://academic.oup.com/jcmc/article/2/4/JCMC243/4584410. Accessed 29 Aug 2018
Ramos C, Augusto JC, Shapiro D (2008) Special issue on ambient intelligence. IEEE Intell Syst 23(2):15–57
Ricci A, Piunti M, Tummolini L, Castelfranchi C (2015) The mirror world: preparing for mixed-reality living. IEEE Pervasive Comput 14(2):60–63
Robb JM, McCarthy JC, Sheridan HD III (1997) Intelligent interactivity. Forrester Rep 1(12):18
Salber D, Dey AK, Orr RJ, Abowd GD (1999) Designing for ubiquitous computing: a case study in context sensing. Technical Report GIT-GVU-99-29. Georgia Institute of Technology, BVU Center, Atlanta
Talebifard P, Leung VCM (2014) Context-aware dissemination of information and services in heterogeneous network environments. J Ambient Intell Hum Comput 5(6):775–787
Tham JCK (2018) Interactivity in an age of immersive media: Seven dimensions for wearable technology, internet of things, and technical communication. Tech Commun 65(1):46–65
Thirumalai S, Sinha KK (2013) To personalize or not to personalize online purchase interactions: implications of self-selection by retailers. Inf Syst Res 24(3):683–708
Toudji D, Hilia M, Djouani K, Chibani A (2017) A knowledge oriented approach for composing ambient intelligence services. Procedia Comput Sci 109:584–591
Vallée T, Sedki K, Tabia K, Ugon A (2016) On personalization in IoT. In: International conference on computational science and computational intelligence, IEEE, pp 186–191
Wu JJ, Chang YS (2005) Towards understanding members’ interactivity, trust, and flow in online travel community. Ind Manag Data Syst 105(7):937–954
Yachir A, Amirat Y, Chibani A, Badache N (2016) Event-aware framework for dynamic services discovery and selection in the context of ambient intelligence and internet of things. IEEE Trans Autom Sci Eng 13(1):85–102
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Liu, C., Park, EM. & Jiang, F. Examining effects of context-awareness on ambient intelligence of logistics service quality: user awareness compatibility as a moderator. J Ambient Intell Human Comput 11, 1413–1420 (2020). https://doi.org/10.1007/s12652-018-1004-z
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DOI: https://doi.org/10.1007/s12652-018-1004-z