Big Data Analytics in Retail

Lekhwar, Shubham; Yadav, Shweta; Singh, Archana

doi:10.1007/978-981-13-1747-7_45

Cited by 18 publications

(5 citation statements)

References 4 publications

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“…The integration in OCR has been categorized from three perspectives i) OCR stages ii) OCR types iii) OCR agents (Saghiri et al, 2017). The core enablers of integration and consistency in OCR strategy (Melero et al, 2016;Shen et al, 2018;Mirzabeiki & Saghiri, 2020).The Omnichannel need enablers, including broadband internet accessibility (Ye et al 2018); well located and welldesigned distribution centers (Melacini et al, 2018;Mkansi et al, 2018); efficient & extensive logistics (Kembro et al, 2018;Murfield et al, 2017;Saghiri et al, 2017;Daugherty et al, 2018;Hazen & Ellinger, 2019); customer analytics (Lekhwar et al, 2019;Vakhutinsky et al, 2019;Zaki & Neely, 2019); Visibility to customers (Ewerhard et al, 2019;Gawor & Hoberg, 2018); information system (Kembro et al, 2018;Kembro & Norrman, 2019) and product digitization (Cortiñas, et al, 2010;Ainsworth & Ballantine, 2017). Few researchers have underlined integration and Visibility as essential enablers for OCR (Ewerhard et al, 2019;Verhoef et al, 2015).…”

Section: Literature Reviewmentioning

confidence: 99%

Omni-Channel retailing enhancing unified experience amidst pandemic: An emerging market perspective

Joshi

Sharma

Chatterjee³

2023

Decis. Mak. Appl. Manag. Eng.

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The research aims to explore the strength of enablers, and adoption barriers present in omnichannel retailing (OCR), and discuss how organizations may focus to redesign their business models in emerging markets to manage the disruptive environment. The prominent enablers may enhance the omnichannel’ performance to deliver a unified experience across all channels during the pandemic time. The paper has used hybrid Multi-Criteria Decision-Making (MCDM) Methods. These methods are widely used by organizations for the exploration of the interrelationship among barriers and enablers affecting their performance. In the current study, 18 experts from different domains have examined and evaluated the 10 barriers and 7 enablers. The study reveals that integration, visibility, internet accessibility, and advanced distribution centers are the prominent enablers and driving the customer analytics enabler to strengthen their customer engagement and providing a unified experience to the. During the pandemic time the usage of the online channels have increased and thus retail channels may consider these enablers to enhance the unified experience level of the customers. The study also shows that inconsistency in price is the main adoption barrier followed by inconsistency in product discounts that should be minimized to engage customers effectively. The retail organizations need to understand the roadblocks in the adoption of OCR and should take relevant actions to minimize them. The retail organization or marketers may redesign their existing strategies based on price consistency, integration, visibility, information systems, and coordination to develop a unified experience across channels during the pandemic situation.

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Section: Literature Reviewmentioning

confidence: 99%

Omni-Channel retailing enhancing unified experience amidst pandemic: An emerging market perspective

Joshi

Sharma

Chatterjee³

2023

Decis. Mak. Appl. Manag. Eng.

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“…Bradlow et al (2017) identified five "typical" sources of Big Data use in retail, namely Customers (to track new customers), Products (to obtain product information, particularly for storage), Time (to replace the manufactured product or modify the flow of customers in the store), Location (to be able to use the spatial location of the customer at a given location) and Channel (to collect data from different channels). Lekhwar et al (2019) also identified five challenges and opportunities in retail such as understanding customer needs by identifying multiple sources of information, improving the accuracy of product data to better manage price management, improving the reliability of information to better manage supplier relationships, manage historical data sales to improve forecasting and improve management of customer data privacy and security. Therefore, the use of BDA in retail provides several benefits such as in-store customer behavior analysis, location and price optimization, improved labor, optimization of inventory management operations and online price comparison (Dekimpe, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

Logistics 4.0 for supply chain performance: perspectives from a retailing case study

Hrouga,

Sbihi

2023

BPMJ

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PurposeThis study considers the potential of logistics 4.0 for supply chain (SC) optimization in French retail. The authors investigate the implementation of Industry 4.0 technologies to optimize SC performance in the retail sector and SC's role in the digital transformation in supply chain management (SCM).Design/methodology/approach The authors first carry out a comprehensive bibliographic taxonomy to highlight the different existing digital tools. Based on this, the authors posed three research questions (RQs) and hypotheses to examine the contribution of logistics 4.0 in improving the performance of retail logistics. Then, the authors considered a case study of retail in France based on qualitative and quantitative analysis to answer all the RQs and examine the hypotheses.FindingsThe results showed that digital tools such as Cyber Security Systems (CSS), Big Data Analytics (BDA) and Blockchain (BC) technology are the most effective and appropriate tools to optimize the SC performance in retail.Practical implicationsThis research work showed that the implementation of these tools in retail can offer several benefits such as improved productivity, optimized delivery times, improved inventory management and secure real-time communication, which leads to improved profitability of the SC.Originality/valueThe study opens a door to develop practical roadmaps for companies that enable smart deliveries based on logistics 4.0.

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“…The researchers explore the primary areas of information amalgamation methods that could influence the reliability and stability of information beneficial for smart transport methods, congestion handling, and remote sensing uses, etc. (Lekhwar et al, 2019).…”

Section: Big Data Managementmentioning

confidence: 99%

High Efficiency Public Transportation System: Role of Big Data in Making Recommendations

Sazu

Jahan

2022

Jour Proc Manag New Tech

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Big data has a huge impact on urban planning and cities morphology. Big data is utilized to appraise the requirements of the shared transport structure, by focusing on funding and portability plans inside the key cities. The research provides a recommendation-making system (RMS) focused on suggesting transport methods to automobile consumption by detailing a huge volume of transport methods information originating from various products. The research focuses on the utilization of big data to come down with shared transport, and presents a structural understanding for gathering, combining, aggregating, incorporating, disseminating, and controlling information from numerous origins. Information extraction methods are utilized, allowing the evaluation of both organized big data, that follows developed benchmarks like CRISP-DM, and disorganized, readily offered big data. Investigational information has been gathered from a representative of phones and automatic vehicle location devices in the region. The suggested RMS allowed to examine the temporal and spatial scope of shared transport facilities, and suggested plans to enhance the transportation.

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Big Data Analytics in Retail

Cited by 18 publications

References 4 publications

Omni-Channel retailing enhancing unified experience amidst pandemic: An emerging market perspective

Omni-Channel retailing enhancing unified experience amidst pandemic: An emerging market perspective

Logistics 4.0 for supply chain performance: perspectives from a retailing case study

High Efficiency Public Transportation System: Role of Big Data in Making Recommendations

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