Agriculture is essential to any country’s economy. Agriculture is crucial not only for feeding a country’s population but also for its impact on other businesses. The paradox of agri-food companies generating substantial profits despite seemingly high product prices is explored in this article, focusing on the role of digital marketing within the agri-food industry. Enhanced digital marketing performance leads to efficient advertising campaigns, through reduced advertising costs and increased resource efficiency. To do so, the authors collected web analytical data from five established agri-food firms with the highest market capitalization. Then, linear regression and correlation analyses were used, followed by the utilization of fuzzy cognitive mapping (FCM) modeling. The analysis revealed that increased traffic through search sources is associated with reduced advertising costs. Additionally, enhanced website engagement contributes to lower advertising expenses, emphasizing the optimization of the user experience. However, it has been discovered that allocating funds for social media advertising eventually results in higher expenses with higher website-abandoning rate. Ultimately, successful management of the balance between product costs and profitability in the agri-food sector lies on the increased use of search sources and greatly reducing the use of social media sources.

Crises are always challenging for banking systems. In the case of COVID-19, centralized payment networks and FinTech companies’ websites have been affected by user behavior globally. As a result, there is ample opportunity for marketing managers and professionals to focus on big data from FinTech websites. This can contribute to a better understanding of the variables impacting their brand name and how to manage risk during crisis periods. This research is divided into three stages. The first stage presents the web analytics and the data retrieved from the FinTech platforms. The second stage illustrates the statistical analysis and the fuzzy cognitive mapping (FCM) performed. In the final stage, an agent-based model is outlined in order to simulate and forecast a company’s brand name visibility and user behavior. The results of this study suggest that, during crises, centralized payment networks (CPNs) and FinTech companies with high organic traffic tend to convert new visitors to actual “customers”.

From the outset of the war in Ukraine, extensive crises in many sectors of the world economy have occurred, with firms offering services and products both online and through physical stores facing serious problems. These problems are mainly related to higher operational costs and the lack of website visibility. For this research study, centralized payment network organizations (CPNs), firms providing online payment services through their networks, were selected and analytical data from their websites were collected for a period of 6 months. The main focus of this research study is to evaluate benefits and the role of social media strategies for CPNs’ digital marketing performance during crisis events and to also assess their utility as a risk-management tool. Following data collection, the authors performed statistical processes (regression and correlation analysis) and stationary modeling with Fuzzy Cognitive Mapping (FCM) tools; finally, dynamic simulations were performed by utilizing Agent-Based Models (ABM). The authors suggest that various variables of CPNs’ social media platforms can aid in improving their digital marketing performance and, using proper analysis, can lead to higher user social engagement, thus rendering social media strategy a useful risk-management tool.

Agriculture firms face an array of struggles, most of which are financial; thus, the role of decision making is discerned as highly important. The agroeconomic indexes (AEIs) of Agriculture Employment Rate (AER), Chemical Product Price Index (CPPI), Farm Product Price Index (FPPI), and Machinery Equipment Price Index (MEPI) were selected as the basis of this study. This research aims to examine the connection between digital marketing analytics and the selected agroeconomic indexes while providing valuable insights into their decision-making process, with the utilization of AI (artificial intelligence) models. Thus, a dataset of website analytics was collected from five well-established agriculture firms, apart from the values of the referred indexes. By performing regression and correlation analyses, the index relationships with the agriculture firms’ digital marketing analytics were extracted and used for the deployment of the fuzzy cognitive mapping (FCM) and hybrid modeling (HM) processes, assisted by using artificial neural network (ANN) models. Through the above process, there is a strong connection between the agroeconomic indexes of AER, CPPI, FPPR, and MEPI and the metrics of branded traffic, social and search traffic sources, and paid and organic costs of agriculture firms. It is highlighted that agriculture firms, to better understand their sector’s employment rate and the volatility of farming, chemicals, and machine equipment prices for future investment strategies and better decision-making processes, should try to increase their investment in the preferred digital marketing analytics and AI applications.

Today, more than ever, the popularity of decentralized payment systems has risen, creating an outbreak of new cryptocurrencies hitting the market. Unique websites have been staged for each cryptocurrency, where information and means for mining cryptocurrencies are available daily. People visit those cryptocurrency websites either from desktop or mobile devices. Thus, the impulsion for appropriate promotion of cryptocurrency websites and customer factors affecting it rises. The above process increases cryptocurrency organizations’ website visibility, raising the need for customer relationships and satisfaction optimization concerning organizations’ supply chain strategy. Research data were collected from 10 well-known cryptocurrency websites, regarding mobile and desktop devices, in 180 days, regarding on-site web analytics. Therefore, a model consisting of three stages was applied. Starting phase of the model pertains to statistical and regression analysis of cryptocurrency web analytics, followed by Fuzzy Cognitive Mapping and Agent-Based Model deployment. Throughout this study, methods for promoting cryptocurrency websites can be deduced from assessing specific website metrics and device preferences. Research results indicate that web analytics give a clearer image of customer behavior in cryptocurrency websites and, therefore, provide opportunities for further website optimization through increased web traffic and digital reputation.

Emerging technologies in the digital context can favor industrial sector firms in their aim to improve their performance. Digitalization is mainly expressed through the utilization of big data that originate from various sources. Blockchain technology has led to the extended adoption of capitalization of Decentralized Finance (DeFi) services, such as cryptocurrency trade platforms. Supply chain firms, in their quest to exploit any means and collaborations available to promote their services, could place advertisements on DeFi’s social media profiles to boost their financial performance. Social media analytics, as a part of the big data family, are an emerging tool for promoting a firm’s digital transformation, based on the plethora of customer behavioral data they provide. This study aims to examine whether the social media analytics of DeFi platforms are capable of affecting their website visibility, as well as the financial performance of supply chain firms. To do so, the authors collected data from the social media profiles of the most-known DeFi platforms and web analytics from the most significant supply chain firms’ websites. For this purpose, proper statistical analysis, Fuzzy Cognitive Mapping, Hybrid Modeling, and Cognitive Neuromarketing models were adopted. Throughout the present research, it has been discerned that from an increase in the social media analytics of DeFi platforms, their website visibility increases, while the organic and paid traffic costs of supply chain firms decrease. Supply chain firms’ website customers tend to increase at the same time.