The Circular Economy and retail: using Deep Learning to predict business survival

Background The Circular Economy system can improve the product cycle and changes the system and mentality, both for production and the consumer and has become a significant alternative to the classic economic model. The retail sector has also started to advance along these lines. Following an analysis of the state of the art of the Circular Economy and retailing, using bibliometric techniques, our research focuses on understanding if the relationship between circularity and retailing can help us determine a business’ survivability and resilience. To this end, data pertaining to 658 commercial premises from four cities were studied over a period of 11 years. A Deep Learning technique is applied using Long Short-Term Memory to determine if there is a relationship between the resistance of the selected commercial premises, their status in previous periods of time, the type of business activity, and their classification in the Circular Economy plane. Results The system predicts, on the set of tests, with a 93.17% accuracy, the survival of a commercial premises based on the activity, and circularity information before 2012. The results of the training also show very significant precision values of the order of 94.15% with data from the post-depression period. Conclusions The results show that businesses with activities related to the Circular Economy are more likely to survive over extended periods of time.

Digital Transformation

The COVID-19 pandemic has intensified the digitization of traditional businesses. In the retail sector, e-commerce played a fundamental role and promoted major changes in the consumer pattern. This evolution and its impact can be studied through the digital transformation lens, which is a multidisciplinary and holistic concept that encompasses a new strategy and new ways of strategizing. The present study aims to describe the digital transformation strategy implementation path at a Brazilian pre-digital retail company and discusses the role the COVID-19 pandemic had played. Moreover, the case highlights important strategic issues and provides the opportunity to analyze whether it is a strategic process or a strategic practice. Thus, it can enlighten which theory best supports DTS studies. This study also increases the understanding of the strategic configuration of digital transformation embracing context, process, and outcomes. And it also sheds light on the dilemma between brick-and-mortar stores and digital ones.

Big Data, Green Growth, and Technology Disruption in Asian Companies and Societies

The rise of digitalization has inevitably impacted the growth of financial technology (FinTech) in Brunei Darussalam. The presence of e-wallet QR code-based payment system, as part of the Fintech development, deems to be the latest payment mode that hits the retail sector of the Sultanate in recent years. Thus, the chapter is aimed to understand the role and impact of e-wallet application in the retail sector. Despite the positive trending indicators for e-wallet growth amongst the population, the utilization of e-wallet in the retail sector is still quite low. Both driving factors and barriers towards e-wallet utilization in the retail sector are discussed by taking account of the views of both customers and retailers. Recommendation steps are also suggested especially on the roles played by both business and government in empowering this new payment system and to drive the population toward a cashless society and attain a smart nation aspiration.

Artificial Intelligence in Retail

This chapter gives an overview of how artificial intelligence is used by the retail sector to enhance customer experience and to improve profitability. It provides information about the role of the pandemic in stimulating AI adoption by retailers. It deliberates on how AI tools help retailers to engage customers online and in stores. Firms gain better understanding of customers, design immersive experiences, and enhance customer lifetime value using cost-effective technology solutions. It discusses popular AI algorithms like recommendation algorithm, association algorithm, classification algorithm, and predictive algorithm. Popular applications in retail include chatbots, visual search, voice search engine optimisation, in-store assistance, and virtual fitting rooms.

Impact of Artificial Intelligence on Customer Loyalty in the Indian Retail Industry

Artificial intelligence has led to the automation of traditional manufacturing and industrial processes and practices. The use of artificial intelligence improves customer experience and it's a proven fact that consumers who enjoy their shopping experience end up making more purchases. Retailing is one of the sectors that has seen drastic changes after the inception of artificial intelligence. This transformation can be seen in the supermarkets like Amazon Go store, Alibaba Hema store, IKEA, and many others. The objective of this chapter is to study the impact of artificial intelligence on Indian retail customers. Primary survey was conducted for the study and it was found that retail organizations emphasizing store design/layout and adoption of technological innovation to ease the consumer buying process were more successful in creating loyal customers for their stores. It can be concluded that India is still lacking in the adoption of IT systems in the retail sector and serious efforts are required in this direction.

Improving Operational and Sustainability Performance in a Retail Fresh Food Market Using Lean: A Portuguese Case Study

This paper presents a real application of a lean–green improvement initiative conducted at a large Portuguese hypermarket store. It explores how lean tools and techniques may be used to not only improve the operational performance, but also sustainability. A case study was carried out in one store of a multinational retail enterprise, with the aim of enhancing both the operational and sustainability performance in the cold meat section, one of the most relevant areas of the fresh food markets. The Gemba Kaizen event approach, which comprises three main stages, was adopted. During the workshop stage, the structured problem-solving methodology was followed, and was recorded in an A3 format. As a consequence of this project, food waste in the cold meat market was reduced by half, whereas the out-of-stock index decreased by a third. In addition, the pilot store hit top performance within all stores of the company in Portugal, ranking first in all key indicators for the cold meat market. The lean–green scope and performance improvement procedures developed and implemented in the pilot store were later deployed to other stores of the company. This is one of the first publications regarding the application of lean management in the food retail sector for improving both the operational and sustainability performance.

STUDI PENGEMBANGAN EKONOMI LOKAL KOTA BOGOR BERBASIS PRODUK UNGGULAN DAERAH DENGAN ANALISIS SWOT

The processing industry contributed 19% of GRDP in 2010 - 2017 the second largest after the trade and retail sector, this reflects the city of Bogor as a tourism area and residential area because it forms the largest GRDP of the four sectors. Thus, local economic development planning focuses on the processing industry. the processing industry, which is indeed mostly processed products typical of the city of Bogor, with commodities obtained from the FGD results, including typical culinary delights, processed food, fashion, footwear, and handicrafts. Local Economic Development is expected not only to solve economic problems, but also other aspects of development, namely improving the quality of development and improvement in local communities. Therefore, through a study of local economic development in Bagor City based on Regional Leading Products with the PUD assessment method based on twelve indicators and SWOT analysis with the aim of finding superior local economic products and determining the strategy for developing the Local Economy. This research approach is using a questionnaire, collecting primary and secondary data, through interviews, qualitative (but still measurable), document studies, and Focus Group Discussions (FGD). The city of Bogor has great local economic potential that is able to have a big impact on the regional economy. Some commodities in the city of Bogor, such as the rubber processing industry into footwear products that are able to open job vacancies for the surrounding community with an average workforce of 3-7 workers. There are five commodities that have the potential to be used as a foundation for the development of the local economy, namely commodities, culinary specialties, metal craft fashion, batik crafts, and footwear. through several development strategies of each commodity as a result of this study