Sustainable digital marketing under big data: an AI random forest model approach

Digital marketing refers to the process of promoting, selling, and delivering products or services through online platforms and channels using the internet and electronic devices in a digital environment. Its aim is to attract and engage target audiences through various strategies and methods, driving brand promotion and sales growth. The primary objective of this scholarly study is to seamlessly integrate advanced big data analytics and artificial intelligence (AI) technology into the realm of digital marketing, thereby fostering the progression and optimization of sustainable digital marketing practices. First, the characteristics and applications of big data involving vast, diverse, and complex datasets are analyzed. Understanding their attributes and scope of application is essential. Subsequently, a comprehensive investigation into AI-driven learning mechanisms is conducted, culminating in the development of an AI random forest model (RFM) tailored for sustainable digital marketing. Subsequent to this, leveraging a real-world case study involving enterprise X, fundamental customer data is collected and subjected to meticulous analysis. The RFM model, ingeniously crafted in this study, is then deployed to prognosticate the anticipated count of prospective customers for said enterprise. The empirical findings spotlight a pronounced prevalence of university-affiliated individuals across diverse age cohorts. In terms of occupational distribution within the customer base, the categories of workers and educators emerge as dominant, constituting 41% and 31% of the demographic, respectively. Furthermore, the price distribution of patrons exhibits a skewed pattern, whereby the price bracket of 0–150 encompasses 17% of the population, whereas the range of 150–300 captures a notable 52%. These delineated price bands collectively constitute a substantial proportion, whereas the range exceeding 450 embodies a minority, accounting for less than 20%. Notably, the RFM model devised in this scholarly endeavor demonstrates a remarkable proficiency in accurately projecting forthcoming passenger volumes over a seven-day horizon, significantly surpassing the predictive capability of logistic regression. Evidently, the AI-driven RFM model proffered herein excels in the precise anticipation of target customer counts, thereby furnishing a pragmatic foundation for the intelligent evolution of sustainable digital marketing strategies

The Circular Economy Challenge: Towards a Sustainable Development

Many recent events, including the COVID-19 pandemic and climate change, have proven the necessity of a transformation of the current economic system based on a linear schema of: “take”, “make”, “use”, and “dispose”. This radical change should involve all of the actors involved in the economic system: institutions, industries, consumers, and scientific research. Only cooperation among these stakeholders can ensure an effective shift toward a circular model. However, which kinds of actions can be performed to implement an effective circular economy? The present Special Issue collects nine papers that prove the possibility of implementing the circular economy from different points of view. The authors analyze all of the spheres of sustainability (environmental, economic, and social) in a variety of contexts, evaluating the effect of the circular choices. The nine papers include several key product value chains, in agreement with the most recent European Circular Economy Action Plan (e.g., electronics and ICT, batteries, plastics, construction and buildings, and food). The present paper collection proves that the circular economy is not only a simple business model, but rather, it involves the integration of many strategies for the protection of the natural ecosystem and the maintenance of worldwide economic stability. The holistic approach is essential for a successful business model, and innovation has an indispensable role in the transition. In this context, the present Special Issue aims to be a multidisciplinary collection of innovations useful for all of the stakeholders involved in the circular economy

The Circular Economy Challenge: Towards a Sustainable Development

As it is now known, we have only one earth available for our life and it is our duty to preserve it [...

Energy Development for Sustainability

Recently, energy development has received significant attention through the promising results of technology development, experimentation, computational modeling, and validation. However, it remains a persistent challenge to produce the needed energy while significantly reducing the environmental effects, such as the emission of greenhouse gases, which lead to climate change. Moreover, technological and economic limitations may also hinder energy development for sustainability. This book entitled Energy Development for Sustainability covers technologies, products, equipment, and devices as well as energy services based on software and data protected by patents and/or trademarks. This book will serve as a collection of the latest scientific and technological approaches to various energy development initiatives for sustainability encompassing novel sonocatalytic application and integrated algal and sludge-based wastewater treatment system, energy storage, sustainable building, gas absorption, organosolv pretreatment, energy usage and CO2 emission in transportation, coal regulation for energy, solar photovoltaic system, torrefaction for fuel production, energy management system, clean energy incubator, biofuels from microalgae, and the influence of COVID-19 on climate change. Overall, this book addresses researchers, advanced students, technical consultants, as well as decision-makers in industries and politics. This book contains comprehensive overview and in-depth technical research papers addressing recent progress in the area of energy development for sustainability. We hope the readers will enjoy this book

THE IMPACT OF PERCEIVED BARRIERS TO EXPORT: AN ANALYSIS OF KENTUCKY AGRICULTURAL AND FOOD PROCESSING FIRMS

As intra-industry trade increases in U.S. agricultural and food processing industries, the historical agricultural trade surplus is tightening. In efforts to maintain the trade surplus a focus has shifted towards the promotion of agricultural and processed food exports among small and medium sized firms. This study intends to identify and evaluate the potential for exports among small to medium sized agricultural and food processing firms in Kentucky through a collection of survey data. The objectives of this thesis are to identify the state’s product marketing opportunities and product specifications for international exports while identifying transaction requirements for potential exports. An analysis of the constraints and challenges faced by firms in the decision to export reveals rational behavior Binary logistic regression analysis is used to identify the impact of firm characteristics, perceived marketing conditions and information constraints, and financial aspects on a firm’s decision to export. A second logit regression analyzes the impact on a non-exporting firm’s interest in international marketing opportunities. The lack of international market information, financial constraints, and risk are found to be significant factors in the decision to export and interest in foreign marketing

Economic Interrelationships and Impacts of the Aviation/Aerospace Industry in the State of Florida using Input-Output Analysis

The study provided a detailed description of the interrelatedness of the aviation and aerospace industry with principal industries in Florida and Volusia County (VC) using Input-Output (IO) analysis. Additionally, this research provided an economic impact analysis of the creation of a university research park in Daytona Beach (DB). The economic impact measures included not only direct economic output and industry employment descriptions but also described the multiplier effects in the form of indirect and induced impacts using data for 2012. This research concluded the average labor income of the aviation and aerospace industry was higher than average labor income in Florida and VC. A substantive difference between the Florida and VC average labor income for the aviation and aerospace industry existed because VC’s aerospace sector was only concentrated in the search, detection, and navigation instruments manufacturing sector. VC’s transport by air sector was one-fifth the size of Florida’s. Differences in the aviation and aerospace industry composition between Florida and VC are important because the economic impacts from a shock to the entire aviation and aerospace industry will be distributed differently. Since the aviation and aerospace average labor income is higher than the average labor income in Florida and VC, it would be a positive move for Florida’s economy to attract and grow the aviation and aerospace industry. It would be highly unlikely that the entirety of newly created jobs would be resourced from the local population. Nonetheless, growing the aviation and aerospace industry jobs would have a positive influence on the region’s economy and tax revenues. It would be a desirable course of action to spur the growth of this sector, as its direct effect would culminate with additional jobs in Florida that would bring higher wage jobs to the state. The interdependencies of the aviation and aerospace industry in Florida and VC with other industries had a positive indirect and induced effect in the economy providing almost a two-fold indirect and induced effect. However, the benefits were not equal. Florida’s average labor income of the most sensitive non-aviation and aerospace industry was 15% lower than the average Florida labor income. The average labor income in VC of the most sensitive non-aviation and aerospace industry was significantly higher than the average VC labor income. Industry interdependencies also presented risk. If the aviation and aerospace industry experiences a contraction, then through the interdependencies of the industries, the region would contract twice as much as the aviation and aerospace industry. The overall impact of a university research park would benefit Florida’s economy. Since the research park project is currently funded partially by public state money, 14 sectors of the economy experienced negative impacts. While the net result was an increase in additional labor income, the employment growth was characterized by gaining more lower-paying jobs while losing less higher-paying jobs. The most expected outcome, an expansion of the aviation and aerospace industry, was not evidenced by the model results