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A new DSS based on situation awareness for smart commerce environments

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Abstract

Real time adaptation of marketing strategies and actions in smart commerce environments, such as shops and malls, is an open challenge with a tremendous impact for the survival of traditional retailers. A main issue of traditional retailers, in comparison with e-commerce shops, is that they usually rely on analysis of point-of-sales data after purchase and/or focus groups and self-reports where customers are asked about what they like or want. This techniques, even if solid grounded to marketing and consumer research, do not allow analysis of data and decision making in real time, i.e., when consumers are inside a shop. In this paper we present our results on the definition and validation of a decision support system for real time decision making on discount and promotion actions. The system makes decision on the basis of recognition and assessment of situations of interest for the consumers, modelled with heuristics related to behavioural economics results. We validated our solution in a virtual shop simulated with V-REP, demonstrating its capabilities to adapt with regards to the changes in the environments, in terms of sensors, people, products, and different situations.

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  1. http://www.coppeliarobotics.com/.

References

  • Abbate T, Bassano C, Coppola A, Miranda S, Rarita’ L (2014a) A knowledge-based decision support system for the service quality improvement in organizations. In: 7th International Workshop on Information Logistics and Knowledge Supply, ILOG 2014, Co-located with 13th International Conference on Perspectives in Business Informatics Research, BIR 2014, pp 49–60

  • Abbate T, D’Aniello G, Gaeta M, Orciuoli F, Perano M (2014b) Situation-aware dss framework for interactive marketing. Advances in business management towards systemic approach p 130

  • Aberer K, Hauswirth M, Salehi A (2006) The global sensor networks middleware for efficient and flexible deployment and interconnection of sensor networks. Tech rep LSIR-REPORT-2006-006, pp 1–21

  • Belk RW (1975) Situational variables and consumer behavior. J Consum Res 2(3):157–164

    Article  Google Scholar 

  • Benincasa G, D’Aniello G, De Maio C, Loia V, Orciuoli F (2015) Towards perception-oriented situation awareness systems. In: Angelov P, Atanassov K, Doukovska L, Hadjiski M, Jotsov V, Kacprzyk J, Kasabov N, Sotirov S, Szmidt E, Zadrony S (eds) Intelligent systems’2014, advances in intelligent systems and computing, vol 322. Springer International Publishing, pp 813–824

  • Blomqvist E (2014) The use of semantic web technologies for decision support a survey. Semant Web 5(3):177–201

    Google Scholar 

  • Capuano N, Gaeta M, Mangione G, Orciuoli F, Ritrovato P (2011) Integrating trust and competency management to improve learning. In: Proceedings of the 2011 11th IEEE International Conference on Advanced Learning Technologies, ICALT 2011, pp 326–330. doi:10.1109/ICALT.2011.102, cited By 11

  • Chen MC, Chiu AL, Chang HH (2005) Mining changes in customer behavior in retail marketing. Expert Syst Appl 28(4):773–781

    Article  Google Scholar 

  • Compton M et al (2012) The ssn ontology of the w3c semantic sensor network incubator group. Web Semant Sci Serv Agents World Wide Web 17:25–32

    Article  Google Scholar 

  • D’Aniello G, Gaeta M, Loia V, Orciuoli F, Tomasiello S (2014) A dialogue-based approach enhanced with situation awareness and reinforcement learning for ubiquitous access to linked data. In: Intelligent Networking and Collaborative Systems (INCoS), 2014 International Conference on, pp 249–256, doi:10.1109/INCoS.2014.73

  • D’Aniello G, Loia V, Orciuoli F (2015) A multi-agent fuzzy consensus model in a situation awareness framework. Applied Soft Computing 30(0):430–440. doi:10.1016/j.asoc.2015.01.061

  • Döring S, Preisinger T (2008) Personalisation and situation awareness of the search process in tourism. In: Information and Communication Technologies in Tourism, ENTER 2008, Proceedings of the International Conference in Innsbruck, Austria, 2008, pp 497–508

  • East R (2003) Comportamento del consumatore. PerCorsi aziendali, Apogeo

    Google Scholar 

  • Endsley MR (1995) Toward a theory of situation awareness in dynamic systems. Hum Factors 37(1):32–64. doi:10.1518/001872095779049543

    Article  Google Scholar 

  • Gigerenzer G, Gaissmaier W (2011) Heuristic decision making. Annu Rev Psychol 62:451–482

    Article  Google Scholar 

  • Gruska J, La Torre S, Parente M (2004) Optimal time and communication solutions of firing squad synchronization problems on square arrays, toruses and rings. In: Developments in Language Theory, 8th International Conference, DLT 2004, Auckland, New Zealand, December 13–17, 2004, Proceedings, pp 200–211

  • Gueguen N, Cavazza N (2010) Psicologia del consumatore. Universale paperbacks Il Mulino

  • Hepp M (2008) Goodrelations: An ontology for describing products and services offers on the web. In: Gangemi A, Euzenat J (eds) Knowledge Engineering: Practice and Patterns, 16th International Conference, EKAW 2008, Acitrezza, Italy, September 29 - October 2, 2008. Proceedings, Springer, Lecture Notes in Computer Science, vol 5268, pp 329–346, doi:10.1007/978-3-540-87696-0_29

  • Hubert M, Kenning P (2008) A current overview of consumer neuroscience. J Consum Behav 7(4–5):272–292

    Article  Google Scholar 

  • Jang JS (1993) Anfis: adaptive-network-based fuzzy inference system. Syst Man Cybern IEEE Trans 23(3):665–685

    Article  Google Scholar 

  • Johnson-Laird PN (1980) Mental models in cognitive science. Cognit Sci 4(1):71–115

    Article  Google Scholar 

  • Kahneman D, Tversky A (1979) Prospect theory: an analysis of decision under risk. Econom J Econom Soc 47(2): 263–291

    MATH  Google Scholar 

  • Kari J (2005) Theory of cellular automata: a survey. Theor Comp Sci 334(13):3–33, doi:10.1016/j.tcs.2004.11.021, http://www.sciencedirect.com/science/article/pii/S030439750500054X

  • Klein G (2008) Naturalistic decision making. Hum Factors 50(3):456–460. doi:10.1518/001872008X288385

    Article  Google Scholar 

  • Kosko B (1986) Fuzzy cognitive maps. Int J Mach Stud 24(1):65–75

    Article  MATH  Google Scholar 

  • Kröckel J, Bodendorf F (2012) Customer tracking and tracing data as a basis for service innovations at the point of sale. In: 2012 Annual SRII Global Conference, San Jose, CA, USA, July 24–27, 2012, pp 691–696

  • Kuan FY, Ho YP, Lu Z, Chen CW et al (2012) The consumers heuristics effects of e-commerce’s price promotion on perceived value. Adv Inf Sci Serv Sci AISS 4(20):353–361

    Google Scholar 

  • Lee MB, Suh KS, Whang J (2003) The impact of situation awareness information on consumer attitudes in the internet shopping mall. Electron Commer Res Appl 2(3):254–265

    Article  Google Scholar 

  • Lipovetsky S, Conklin M (2014) Finding items cannibalization and synergy by BWS data. J Choice Model 12(C):1–9, http://ideas.repec.org/a/eee/eejocm/v12y2014icp1-9.html

  • Matheus C, Kokar M, Baclawski K (2003) A core ontology for situation awareness. In: Information Fusion, 2003. Proceedings of the Sixth International Conference of, vol 1, pp 545–552, doi:10.1109/ICIF.2003.177494

  • Muller HA, Villegas NM, Tamura G, Ng J (2012) Situation-aware smarter commerce. In: Proceedings of the 2012 Conference of the Center for Advanced Studies on Collaborative Research, IBM Corp., Riverton, NJ, USA, CASCON ’12, pp 259–261, http://dl.acm.org/citation.cfm?id=2399776.2399813

  • Orciuoli F, Parente M, Vitiello A (2015) Solving the shopping plan problem through bio-inspired approaches. Soft Comput 1–13, doi:10.1007/s00500-015-1625-5

  • Poelmans J, Ignatov D, Kuznetsov S, Dedene G (2014) Fuzzy and rough formal concept analysis: a survey. Int J Gen Syst 43(2):105–134. doi:10.1080/03081079.2013.862377

    Article  MathSciNet  MATH  Google Scholar 

  • Power D (2002) Decision support systems: concepts and resources for managers. Quorum Books

  • Power DJ, Sharda R, Burstein F (2015) Decision support systems. John Wiley Sons Ltd. doi:10.1002/9781118785317.weom070211

  • Sánchez-Fernández R, Iniesta-Bonillo MÁ (2007) The concept of perceived value: a systematic review of the research. Market Theory 7(4):427–451

    Article  Google Scholar 

  • Stone JV (2013) Vision and brain: How we perceive the world. Color Res Appl 38(3):176–176. doi:10.1002/col.21807

    Article  Google Scholar 

  • Struss P (2011) A conceptualization and general architecture of intelligent decision support systems. In: Chan MD F, Anderssen R (eds) MODSIM2011, 19th International Congress on Modelling and Simulation. pp 2282–2288

  • Valery AA, Naranjo V, Mora I (2001) Real-time high density people counter using morphological tools. IEEE Trans Intell Transp Syst 2:2–1524

    Google Scholar 

  • Villegas NM, Müller HA, Muñoz JC, Lau A, Ng J, Brealey C (2011) A dynamic context management infrastructure for supporting user-driven web integration in the personal web. In: Proceedings of the 2011 Conference of the Center for Advanced Studies on Collaborative Research, IBM Corp., Riverton, NJ, USA, CASCON ’11, pp 200–214, http://dl.acm.org/citation.cfm?id=2093889.2093913

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Authors and Affiliations

  1. Dipartimento di Ingegneria dell’Informazione, Ingegneria Elettrica e Matematica Applicata, Univerisità degli Studi di Salerno, via Giovanni Paolo II, 132, 84084, Fisciano, Italy

    Giuseppe D′Aniello, Angelo Gaeta & Matteo Gaeta

  2. Co.Ri.Sa. (Consorzio di Ricerca Sistemi ad Agenti), Univerisità degli Studi di Salerno, via Giovanni Paolo II, 132, 84084, Fisciano, Italy

    Giuseppe D′Aniello & Mario Lepore

  3. Dipartimento di Informatica, Univerisità degli Studi di Salerno, via Giovanni Paolo II, 132, 84084, Fisciano, Italy

    Francesco Orciuoli

  4. Dipartimento di Studi e Ricerche Aziendali, Univerisità degli Studi di Salerno, via Giovanni Paolo II, 132, 84084, Fisciano, Italy

    Orlando Troisi

Authors
  1. Giuseppe D′Aniello
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  2. Angelo Gaeta
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  3. Matteo Gaeta
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  4. Mario Lepore
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  5. Francesco Orciuoli
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  6. Orlando Troisi
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Correspondence to Giuseppe D′Aniello.

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D′Aniello, G., Gaeta, A., Gaeta, M. et al. A new DSS based on situation awareness for smart commerce environments. J Ambient Intell Human Comput 7, 47–61 (2016). https://doi.org/10.1007/s12652-015-0300-0

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