The path to digital maturity: A cluster analysis of the retail industry in an emerging economy

Pinto, Marcelo Rezende; Salume, Paula Karina; Barbosa, Marcelo Werneck; Sousa, Paulo Renato de

doi:10.1016/j.techsoc.2022.102191

Cited by 16 publications

(10 citation statements)

References 79 publications

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“…The appropriation of the system by researchers in these areas favors the understanding and elaboration of public policies that allow for reductions in social vulnerabilities [84], the equitable distribution of public infrastructure in cities [85], improvements in public healthcare services [86], making better decisions in custody hearings [87], promoting the digital maturation of companies, achieving opportunities and avoiding market threats [88], and improving accessibility to healthcare facilities [89], among others.…”

Section: Discussionmentioning

confidence: 99%

Fuzzy-Set-Based Multi-Attribute Decision-Making, Its Computing Implementation, and Applications

Ferreira,

Ribeiro,

Schuffner

et al. 2024

Axioms

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This paper reflects the results of research analyzing models of multi-attribute decision-making based on fuzzy preference relations. Questions of constructing the corresponding multi-attribute models to deal with quantitative information concomitantly with qualitative information based on experts’ knowledge are considered. Human preferences may be represented within the fuzzy preference relations and by applying diverse other preference formats. Considering this, so-called transformation functions reduce any preference format to fuzzy preference relations. This paper’s results can be applied independently or as part of a general approach to solving a wide class of problems with fuzzy coefficients, as well as within the framework of a general scheme of multi-criteria decision-making under conditions of uncertainty. The considered techniques for fuzzy preference modeling are directed at assessing, comparing, choosing, prioritizing, and/or ordering alternatives. These techniques have served to develop a computing system for multi-attribute decision-making. It has been implemented in the C# programming language, utilizing the “.NET” framework. The computing system allows one to represent decision-makers’ preferences in one of five preference formats. These formats and quantitative estimates are reduced to nonreciprocal fuzzy preference relations, providing homogeneous preference information for decision procedures. This paper’s results have a general character and were applied to analyze power engineering problems.

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Section: Discussionmentioning

confidence: 99%

Fuzzy-Set-Based Multi-Attribute Decision-Making, Its Computing Implementation, and Applications

Ferreira,

Ribeiro,

Schuffner

et al. 2024

Axioms

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“…Particularly, the role of customer insights in driving digital strategy and informing digital design and development seems to be undervalued. This could indicate a potential gap in understanding the importance of customer-centric approaches in digital transformation, which is a key aspect of digital maturity (Pinto et al, 2023).…”

Section: Discussionmentioning

confidence: 99%

“…A study by Pinto et al (2023) employed a five-dimension model focusing on strategy, market, operations, culture, and technology to gauge the digital maturity of the retail industry in an emerging economy. The authors found that most of the companies evaluated demonstrated a low level of digital maturity.…”

Section: Introductionmentioning

confidence: 99%

Measurement of digital maturity in medium-sized companies in the municipality of Tecomán, Colima, Mexico

Preciado Álvarez,

Ojeda Pérez

2023

rgn

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The present study aims to analyze the digital maturity of medium-sized companies in the municipality of Tecoman, Colima, Mexico, and the relation it as with the gender or level of study of the leader of the organization, by applying the Forrester four-dimension model. For this purpose, a mixed approach is used, selecting a sample of 40 economic units out of a total of 47 in the municipality, all medium-sized companies with between 51 and 250 employees. As a result, it was observed that the gender and level of education of the person in charge has no influence on the digital maturity of medium scale business.

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“…Using cutting-edge information technologies enables retailers to identify potential customers and gather relevant information to make decisions [20]. The retail industry has undergone significant changes in recent years, with the evolution towards Retail 4.0 involving the inclusion of various technologies such as AI, cloud computing, internet of things (IoT), augmented reality (AR), and big data analytical (BDA) [21].…”

Section: Retail Businessmentioning

confidence: 99%

“…This allowed us to easily configure and run experiments with the YOLOX network. For this project, a copy of the Exp file named "yolox_base.py" was made and then configured with specific data, as follows: depth = 0.33; width = 0.25; input size = (640, 640); mosaic scale = (0.5, 1.5); random size = (10,20); test size = (640, 640); exp name = os.path.split(os.path.realpath(file)).split(". "); enable mixup = False; data dir = "datasets/STEREN COCO format 9k"; train ann = "instances train2017.json"; val ann = "instances val2017.json"; num classes =1.…”

Section: Model Size (Pixels) Params (Milions) Flopsmentioning

confidence: 99%

Analyzing computer vision models for detecting customers: a practical experience in a mexican retail

Fernández Del Carpio

2024

Int. J. Adv. Intell. Informatics

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Computer vision has become an important technology for obtaining meaningful data from visual content and providing valuable information for enhancing security controls, marketing, and logistic strategies in diverse industrial and business sectors. The retail sector constitutes an important part of the worldwide economy. Analyzing customer data and shopping behaviors has become essential to deliver the right products to customers, maximize profits, and increase competitiveness. In-person shopping is still a predominant form of retail despite the appearance of online retail outlets. As such, in-person retail is adopting computer vision models to monitor store products and customers. This research paper presents the development of a computer vision solution by Lytica Company to detect customers in Steren’s physical retail stores in Mexico. Current computer vision models such as SSD Mobilenet V2, YOLO-FastestV2, YOLOv5, and YOLOXn were analyzed to find the most accurate system according to the conditions and characteristics of the available devices. Some of the challenges addressed during the analysis of videos were obstruction and proximity of the customers, lighting conditions, position and distance of the camera concerning the customer when entering the store, image quality, and scalability of the process. Models were evaluated with the F1-score metric: 0.64 with YOLO FastestV2, 0.74 with SSD Mobilenetv2, 0.86 with YOLOv5n, 0.86 with YOLOv5xs, and 0.74 with YOLOXn. Although YOLOv5 achieved the best performance, YOLOXn presented the best balance between performance and FPS (frames per second) rate, considering the limited hardware and computing power conditions.

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The path to digital maturity: A cluster analysis of the retail industry in an emerging economy

Cited by 16 publications

References 79 publications

Fuzzy-Set-Based Multi-Attribute Decision-Making, Its Computing Implementation, and Applications

Fuzzy-Set-Based Multi-Attribute Decision-Making, Its Computing Implementation, and Applications

Measurement of digital maturity in medium-sized companies in the municipality of Tecomán, Colima, Mexico

Analyzing computer vision models for detecting customers: a practical experience in a mexican retail

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