Big Data Analytics: The New Boundaries of Retail Location Decision Making

Aversa, Joseph; Doherty, Sean; Hernández, Tony

doi:10.1080/23754931.2018.1527720

Cited by 18 publications

(17 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The advancements in spatial big data and associated analytics have allowed for more granular level consumer behaviour data to be collected and analyzed. The retail, tourism, management, and health care industries have started to experience significant changes in their informatics and decision-making as a result of this data evolution [14,15,16,17,18,19,20,21,22,23]. Spatial big data are becoming a more prominent research area [24,25,26,27].…”

Section: Mobile Location Datamentioning

confidence: 99%

The effect of COVID-19 on customer traffic: A case study of Food and Beverage stores in Erie County, New York

Aversa¹,

Quach²,

Hernández³

et al. 2022

Proceedings of the Annual Hawaii International Conference on System Sciences

Self Cite

View full text Add to dashboard Cite

The declaration of the COVID-19 pandemic and the resulting lockdowns brought focus on the importance of the retail sector for community well-being. The restrictive government policies that were put into place to curb the spread of COVID-19 virus added pressure on retailers to adapt to the subsequent changes in consumption. This research, using a case study of Erie County in the State of New York (NY), investigates these changes in visitation patterns for a commercial service sector that was deemed 'essential' -food and beverage. This study uses mobile location data to identify variations in shopping patterns for independent and chain stores. The study finds that by comparing the pre-pandemic to pandemic, there were changes to visitation patterns over time and between retail types. While the study highlights the potential to use mobile data to study shifts in consumption behaviours, the paper also reveals several challenges in using such data. Research Context COVID-19 Timeline in Erie County

show abstract

Section: Mobile Location Datamentioning

confidence: 99%

The effect of COVID-19 on customer traffic: A case study of Food and Beverage stores in Erie County, New York

Aversa¹,

Quach²,

Hernández³

et al. 2022

Proceedings of the Annual Hawaii International Conference on System Sciences

Self Cite

View full text Add to dashboard Cite

show abstract

“…Third, the computational tool view overlooks the contextual organizational, environmental, and institutional features dynamically contributing to shaping algorithms across space and over time, including customs, culture, knowledge, or resources (e.g., Porter, 1996); global instruments such as regulatory frameworks, classifications, standards, policies, or the law (Mennicken & Espeland, 2019;Yeung, 2018); decision-making and problem-solving characteristics such as expertise, choice, and judgment (Aversa, Doherty, & Hernandez, 2018;Galliers, Newell, Shanks, & Topi, 2017); and material contingencies such as hardware, platforms, or languages (Nambisan, Wright, & Feldman, 2019). As created and enacted within a thick web of proximities and relationalities, algorithms thus stretch far beyond both the narrow conditions under which they are developed and deployed, and purely technical domains (Geiger, 2014).…”

Section: Limitations Of the Algorithms As Computational Tools Perspectivementioning

confidence: 99%

The Biography of an Algorithm: Performing algorithmic technologies in organizations

Glaser

Pollock

D’Adderio

2021

Organization Theory

View full text Add to dashboard Cite

Algorithms are ubiquitous in modern organizations. Typically, researchers have viewed algorithms as self-contained computational tools that either magnify organizational capabilities or generate unintended negative consequences. To overcome this limited understanding of algorithms as stable entities, we propose two moves. The first entails building on a performative perspective to theorize algorithms as entangled, relational, emergent, and nested assemblages that use theories—and the sociomaterial networks they invoke—to automate decisions, enact roles and expertise, and perform calculations. The second move entails building on our dynamic perspective on algorithms to theorize how algorithms evolve as they move across contexts and over time. To this end, we introduce a biographical perspective on algorithms which traces their evolution by focusing on key “biographical moments.” We conclude by discussing how our performativity-inspired biographical perspective on algorithms can help management and organization scholars better understand organizational decision-making, the spread of technologies and their logics, and the dynamics of practices and routines.

show abstract

“…Big data analysis in the e-commerce environment needs to properly integrate perceptual factors into business processes, technical optimization and data usage, which can greatly improve the company's analytical capability (Weill, 2012; Zuo et al , 2015). More and more retailers use big data analysis tools to support their decision-making behaviors in the operation process, which greatly influences the location decision of retailers (Aversa et al , 2018; Zuo et al ., 2017; Sun et al , 2021; Hu et al , 2019). Big data and predictive analytics affects the supply chain management and decision-making of enterprises, while the acceptance of big data technology by enterprises is affected by the management level and the industry environment (Gunasekaran et al , 2017; Zhu et al , 2018a; Xiong et al , 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

Understanding the role of big data analytics for coordination of electronic retail service supply chain

Wang¹,

Wu²,

Yu³

et al. 2021

JEIM

View full text Add to dashboard Cite

PurposeBased on the typical service supply chain (SSC) structure, the authors construct the model of e-tailing SSC to explore the coordination relationship in the supply chain, and big data analysis provides realistic possibilities for the creation of coordination mechanisms.Design/methodology/approachAt the present stage, the e-commerce companies have not yet established a mature SSC system and have not achieved good synergy with other members of the supply chain, the shortage of goods and the greater pressure of express logistics companies coexist. In the case of uncertain online shopping market demand, the authors employ newsboy model, applied in the operations research, to analyze the synergistic mechanism of SSC model.FindingsBy analyzing the e-tailing SSC coordination mechanism and adjusting relevant parameters, the authors find that the synergy mechanism can be implemented and optimized. Through numerical example analysis, the authors confirmed the feasibility of the above analysis.Originality/valueBig data analysis provides a kind of reality for the establishment of online SSC coordination mechanism. The establishment of an online supply chain coordination mechanism can effectively promote the efficient allocation of supplies and better meet consumers' needs.

show abstract

Big Data Analytics: The New Boundaries of Retail Location Decision Making

Cited by 18 publications

References 48 publications

The effect of COVID-19 on customer traffic: A case study of Food and Beverage stores in Erie County, New York

The effect of COVID-19 on customer traffic: A case study of Food and Beverage stores in Erie County, New York

The Biography of an Algorithm: Performing algorithmic technologies in organizations

Understanding the role of big data analytics for coordination of electronic retail service supply chain

Contact Info

Product

Resources

About