Agent-based Big Data Analytics in retailing: A case study

Two Decades of Research on Consumer Behaviour and Analytics

“…Several studies were grounded based on the affecting factors, such as social media engagement, rewarding, point of sales data, and even cross-gaming behaviors. • Our study revealed a deficit of solid theoretical underpinnings in the current literature, as existing empirical literature mostly applied fewer theories and models, such as artificial intelligence theory (Ahmed et al, 2015); cross-gaming predictive models (Suh & Alhaery, 2014); Saaty scalebased model (Zhou et al, 2019); Bayes' theorem (Pantano et al, 2019); social media analytics framework (Ozturkcan et al, 2019); utility theory (Chiang & Yang, 2018); the social theory (Martens et al, 2016); parallel computing models (Guha & Kumar, 2018); duality theory (Gene et al, 2020); social representations theory (Pindado & Barrena, 2021); relationship marketing theory (Kitchens et al, 2018) and Bayesian approaches (Lin et al, 2020). • Concerning the context, authors identified that a large number of studies focused on the retailing and marketing sector, with fewer studies focusing on other industries, such as healthcare (Abraham et al, 2006); the apparel sector (Moisander et al, 2010); information technology (Lau, Li, & Liao, 2014); higher education (Duffy & Ney, 2015); the food industry (Fiore et al, 2017); finance (Lin et al, 2020); banking (Shirazi & Mohammadi, 2019) and the airline industry (Ma et al, 2019).…”

“…Our study revealed a deficit of solid theoretical underpinnings in the current literature as existing empirical literature mostly applied fewer theories and models, such as artificial intelligence theory (Ahmed et al, 2015); cross-gaming predictive models (Suh & Alhaery, 2014); Saaty scale-based model (Zhou et al, 2019); Bayes' theorem (Pantano et al, 2019); social media analytics framework (Ozturkcan et al, 2019); utility Theory (Chiang & Yang, 2018); the social theory (Martens et al, 2016); parallel computing models (Guha & Kumar, 2018); duality theory (Gene et al, 2020); social representations theory (Pindado & Barrena, 2021); relationship marketing theory (Kitchens et al, 2018) and Bayesian approaches (Lin et al, 2020). When considering the social media data analysis, it was identified that data gathering from different social media networks, including Facebook, Pinterest, or even Instagram, is needed for future research (Ozturkcan et al, 2019;Pantano et al, 2019).…”

“…This is primarily due to the easy availability of data in the retail industry. In the retail sector, big data technology applications can enable effective decision management and achieve further improvements (Ahmed et al, 2015). For instance, Pantano (2020) tested whether the facial expressions of customers can provide insight into the quality of retail service encounters.…”

“…Abraham et al (2006);Ahmed et al (2015); de Villiers (2015); Suh & Alhaery (2014); Moisander et al (2010); Pantano et al (2019); Boone et al (2019); Boone et al (2019); Chiang & Yang (2018); Birkin (2019); Martens et al (2016); Guajardo (2019); Kakatkar & Spann (2019); Guha & Kumar (2018); Hu & Winer (2017); Oh et al (2017); Lee et al (2020); Sturley et al (2018); Naraine et al (2019); Pindado & Barrena (2021); Fiore et al (2017); Ting & Kauffman (2012); Lin et al (2020); Ibrahim & Wang (2019); Li et al (2020); Aluri et al (2019); Luca et al (2020); Reutterer et al (2020); Huang & Mieghem (2013); Shirazi & Mohammadi (2019); Kitchens et al (2018); Ma et al (2019); Radha & Babu (2020); Wong & Wei (2018); Fuchs et al & Wu (2018); Hofacker et al (2016); Arda et al (2017); Lau et al (2014); Kakalejčík et al (2020); Marinelli et al (2020) Qualitative method 12 Pantano (2020); Giglio et al (2020); Belk (2017); Buzova et al (2020); Pantano & Dennis (2019); Tupikovskaja-Omovie & Tyler (2020); Arda et al (2017); Xiang et al (2015); Duffy & Ney (2015); Sheth (2019); Kumar et al (2016); Miles (2014) Mixed method 5 Belk (2017); de Villiers (2015); Lin et al (2020); Ibrahim & Wang (2019); Li et al (2020) Literature Review 7 Moisander et al (2010); Santiago & Robert (2020); Ozturkcan et al (2019); Zhang et al (2020); Pomirleanu et al (2013); Silva et al (2019); Maheshwari et al (2020)…”

An Approach to Data Reduction for Learning from Big Datasets: Integrating Stacking, Rotation, and Agent Population Learning Techniques

“…The implementation of the agent-based approach has been also a subject of the paper [35]. An agent-based paradigm and the example case study have been also discussed in the context of applying the big data analytics in retailing [36].…”