Increasing online shop revenues with web scraping: a case study for the wine sector

Purpose – Wine has been produced for thousands of years and nowadays we have seen a spread in the wine culture. E-commerce sales of wine have increased considerably and online customer’s satisfaction is influenced by quality and price. This paper presents a case study of the company “QuieroVinos, S.L.”, an online wine shop founded in 2015 that sells Spanish wines in two main marketplaces. Design/methodology/approach – With the final target of increasing the company profits it has been designed and developed an application to track the prices of competitors for a set of products. This information will be used to set the product prices in order to offer the products both competitively and profitably in each Marketplace. This application must check, by tacking into account information such as the product cost or the minimum product margin, if it is possible to decrease the price in order to reach the top cheapest position and as a consequence, increase the sales. Findings – The application improved in a notorious way the company’s results in terms of sales and shipping costs. It must be said that without the use of the presented application, performing the price comparison process within each one of the marketplaces would have taken a long time. Moreover, as prices change very frequently, the obtained information has a very limited time value, and the competitors prices should be analyzed daily in order to take accurate decisions regarding the company’s price policy. Originality/value – Although the application has been designed for the wine sector and the two named marketplace, it could be exported to other sectors. For that, it should be implemented new modules to collect information regarding the competitor’s price of the products selling on each corresponding marketplaceThis work was supported by the Ministerio de Economía y Competitividad under contract TIN2017- 84553-C2-2-R. Also, the authors are members of the research group 2017-SGR363, funded by the Generalitat de Catalunya

Reliability framework for power network assessment

Reliability of power system in terms of investments in network maintenance and restructuring for power distribution network has gained importance due to increase in distributed generation. To determine the reliability of the power distribution network, the state of power apparatus, losses in the network and consumer satisfaction indices are key factors. Considering the aforementioned, this paper proposes a holistic reliability framework for power distribution networks. The framework lists the following factors: life cycle of power apparatus, environmental and sociological, node reliability, arc reliability. A case study for reliability evaluation is performed on a modified IEEE 14 bus network. Furthermore, multiple scenarios of generation fault or outage are studied and results are presented. The key contribution of this paper is to present a novel and holistic reliability framework to model distribution network

Smart contract formation enabling energy-as-a-service in a virtual power plant

Energy as a service (EaaS) is an emerging business model that enables the otherwise passive energy consumers to play an active role and participate in the energy utility services. This platform is formed through smart contracts registering peer-to-peer (P2P) transactions of energy through price and quantity. Many industries, including finance, have already leveraged smart contracts to introduce digital currencies. At this time, the utility industry is faced with the challenge of how to structure smart contract formation in a local energy market. Specifically, they are faced with the challenge of maintaining a balance between energy generation and demand while enabling traceability, security, and unbiased peer-to-peer energy transactions, especially within a virtual power plant. This article aims at addressing the aforementioned challenges. In particular, this article investigates how to structure the microgrids in a local energy market, and how to ensure balance and resiliency with incomplete information. Taking various generation asset dimensions and demand profiles into account, simulations are performed. A novel evolutionary computing strategy to structure the simulation is proposed. A comparison is made among random order, random selection, profit-based ranking, and evolutionary strategy for coordinating the contract formation. The discussions draw attention to each method's advantages and disadvantages in terms of their value as a strategy for forming smart contracts in a local energy market

A production planning model considering uncertain demand using two-stage stochastic programming in a fresh vegetable supply chain context

Production planning models are achieving more interest for being used in the primary sector of the economy. The proposed model relies on the formulation of a location model representing a set of farms susceptible of being selected by a grocery shop brand to supply local fresh products under seasonal contracts. The main aim is to minimize overall procurement costs and meet future demand. This kind of problem is rather common in fresh vegetable supply chains where producers are located in proximity either to processing plants or retailers. The proposed two-stage stochastic model determines which suppliers should be selected for production contracts to ensure high quality products and minimal time from farm-to-table. Moreover, Lagrangian relaxation and parallel computing algorithms are proposed to solve these instances efficiently in a reasonable computational time. The results obtained show computational gains from our algorithmic proposals in front of the usage of plain CPLEX solver. Furthermore, the results ensure the competitive advantages of using the proposed model by purchase managers in the fresh vegetables industry.This work was supported by the MEyC under contracts TIN2011-28689-C02-02, TRA2013-48180-C3-P and TIN2014- 53234-C2-2-R. The authors are members of the research group 2014-SGR163 and 2014-SGR151, funded by the Generali- tat de Catalunya

An Internet of Things Platform Based on Microservices and Cloud Paradigms for Livestock

With the growing adoption of the Internet of Things (IoT) technology in the agricultural sector, smart devices are becoming more prevalent. The availability of new, timely, and precise data offers a great opportunity to develop advanced analytical models. Therefore, the platform used to deliver new developments to the final user is a key enabler for adopting IoT technology. This work presents a generic design of a software platform based on the cloud and implemented using microservices to facilitate the use of predictive or prescriptive analytics under different IoT scenarios. Several technologies are combined to comply with the essential features¿scalability, portability, interoperability, and usability¿that the platform must consider to assist decision-making in agricultural 4.0 contexts. The platform is prepared to integrate new sensor devices, perform data operations, integrate several data sources, transfer complex statistical model developments seamlessly, and provide a user-friendly graphical interface. The proposed software architecture is implemented with open-source technologies and validated in a smart farming scenario. The growth of a batch of pigs at the fattening stage is estimated from the data provided by a level sensor installed in the silo that stores the feed from which the animals are fed. With this application, we demonstrate how farmers can monitor the weight distribution and receive alarms when high deviations happen.This research was partially supported by the Intelligent Energy Europe (IEE) program and the Ministerio de Economía y Competitividad under contract TIN2017-84553-C2-2-R, by the European Union FEDER (CAPAP-H6 network TIN2016-81840-REDT) and the demonstration activity financed by the Operation 01.02.01 of Technological Transfer from the Program of Rural Development in Catalunya 2014–2020 cofinanced by DARP and FEDER

Severity of COVID‑19 cases in the months of predominance of the Alpha and Delta variants

This work was supported by Contract 2019-DI-43 of the Industrial Doctorate Program of the Government of Catalonia, by the Spanish Ministry of Science and Innovation under Contract PID2020-113614RB-C22 and by the Lleida Biomedical Research Institute (IRB Lleida). Some authors are members of the 2014-SGR163 research group, funded by the Generalitat de Catalunya