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Despite the steady rise of electric vehicles (EVs) in other countries, the Philippines has yet to capitalize on its proliferation due to several mixed concerns. Status, socio-demographic characteristics, and availability have been the main concerns with purchasing EVs in the country. Consumer segmentation and analysis for EV acceptance and utility in the Philippines were determined in this study due to the need for understanding consumer preferences and market segmentation towards EVs in the Philippines. A total of 311 valid responses coming from EV owners were collected through purposive and snowball sampling approaches. The data were collected via face-to-face distribution and online distribution of a questionnaire covering demographic characteristics for market segmentation. Demographic data such as gender, age, residence type, car ownership, and income were used to identify consumer segments using the K-means clustering approach. Jupyter Notebook v7.1.3 was used for the overall analysis, and the number of clusters was optimized, ensuring precise segmentation. The results indicated a strong correlation between car ownership and the ability to purchase EVs, where K-means clustering effectively identified consumer groups. The groupings also included "Not Capable at All" to "Highly Capable" individuals based on their likelihood to purchase EVs. Based on the results, the core-value customers of EVs are male, older than 55 years old, live in urban areas, own a vehicle and car insurance, and have a monthly income of more than PHP 130,000. Following those are high-value customers, considered target users expected to use EVs frequently. It could be posited that customers are frequent purchasers of products and services. Based on the results, high-value customers are male, aged 36–45 years old, live in urban areas, own a car, have car insurance, and have a monthly income of PHP 100,001–130,000. Both of these should be highly considered by EV industries, as these characteristics would be the driving market of EVs in the Philippines. The constructed segmentation provided valuable insights for the EV industry, academic institutions, and policymakers, offering a foundation for targeted marketing strategies and promoting EV adoption in the Philippines. Moreover, the sustainable marketing strategies developed could be adopted and extended among other developing countries wanting to adopt EVs for utility. Future works are also suggested based on the study limitations for researchers to consider as study extensions, such as a holistic approach to EV adoption that considers environmental, social, and economic factors, as well as policies and promotion development. [ABSTRACT FROM AUTHOR]

Bamboo breeding strategies are essential in realizing "Bamboo as a Substitute for Plastic (BASP)". This review article aims to explore the crucial role of breeding strategies in achieving the substitution of plastic products with bamboo as outlined under the BASP Initiative. Firstly, we address the issue of plastic pollution, along with the background of reducing the market share and demand for plastic products. It categorizes the types of bamboo products that can fully or partially replace plastic products in various categories, such as daily necessities, building materials, and industrial products. Then, we investigate which bamboo species can replace which plastic products and propose the need for bamboo improvement. Furthermore, it presents data from positioning observation research stations for bamboo forest ecosystems in China and outlines the essential traits necessary for bamboo substitution, including characteristics like long internode length, extended fiber length, thick culm wall, and optimal cellulose-to-lignin content ratio, among others. Finally, we discuss breeding methods and genetic improvement as key strategies to achieve bamboo substitution and suggest the potential of enhancing bamboo traits to serve as a viable replacement source for plastics. This comprehensive approach aims to enhance bamboo's growth features and physical properties to meet the criteria for substituting bamboo for plastics effectively. [ABSTRACT FROM AUTHOR]

For several stakeholders, including market players, customers, grid operators, policy-makers, investors, and energy efficiency initiatives, having a precise estimate of power pricing is crucial. It is easier for traders to plan, purchase, and sell power transactions with access to accurate electricity price forecasting (EPF). Although energy production and consumption topics are widely discussed in the literature, EPF and renewable energy trading studies receive less attention, especially for intraday market modeling and forecasting. Considering the rapid development of renewable energy sources, the article highlights the significance of integrating the deep learning model, long short-term memory (LSTM), with the proper trading strategy for short-term hourly renewable energy trading by utilizing two different spot markets. Day-ahead and intraday markets are taken into account for the West Denmark grid region (DK1). The time series analysis indicates that LSTM yields superior results compared to other benchmark machine learning algorithms. Using the predictions obtained by LSTM and the recommended trading strategy, promising profit values are achieved for the DK1 wind and solar energy use case, which ensures future motivation to develop a general and flexible model for global data. [ABSTRACT FROM AUTHOR]

This systematic review meticulously explores the transformative impact of digital technologies on the grid planning, grid operations, and energy market dynamics of power distribution grids. Utilizing a robust methodological framework, over 54,000 scholarly articles were analyzed to investigate the integration and effects of artificial intelligence, machine learning, optimization, the Internet of Things, and advanced metering infrastructure within these key subsections. The literature was categorized to show how these technologies contribute specifically to grid planning, operation, and market mechanisms. It was found that digitalization significantly enhances grid planning through improved forecasting accuracy and robust infrastructure design. In operations, these technologies enable real-time management and advanced fault detection, thereby enhancing reliability and operational efficiency. Moreover, in the market domain, they support more efficient energy trading and help in achieving regulatory compliance, thus fostering transparent and competitive markets. However, challenges such as data complexity and system integration are identified as critical hurdles that must be overcome to fully harness the potential of smart grid technologies. This review not only highlights the comprehensive benefits but also maps out the interdependencies among the planning, operation, and market strategies, underlining the critical role of digital technologies in advancing sustainable and resilient energy systems. [ABSTRACT FROM AUTHOR]

Stance information has a significant influence on market strategy, government policy, and public opinion. Users differ not only in their polarity but also in the degree to which they take a stand. The traditional classification of stances is quite simple and cannot fully depict the diversity of stances. At the same time, traditional approaches ignore user sentiment features when expressing their stances. As a result, this paper develops a multi-stance detection model by fusing sentiment features. First, a five-category stance indicator system is built based on the LDA model, then sentiment features are extracted from the reviews using the sentiment lexicon, and finally, stance detection is implemented using a hybrid neural network model. The experiment shows that the proposed method can classify stances into five categories and perform stance detection more accurately. [ABSTRACT FROM AUTHOR]

This paper delves into the concept of socially responsible marketing and its significance in fostering diversity, equity, and inclusion within organizational environments. It elucidates the connection between marketing and corporate social responsibility (CSR), showcasing methods of integrating social responsibility into marketing activities. Ethical principles inherent in socially responsible marketing are delineated, along with examples of CSR programs and projects within marketing initiatives. Furthermore, the paper explores the context and nature of diversity management policies and practices in organizations, highlighting the need for aligning marketing efforts with inclusive practices. It delves into the perception of various antecedents and consequences of diversity, equity, and inclusion at individual, group, and organizational levels, emphasizing the role of marketing in shaping perceptions and fostering inclusivity. Additionally, the paper addresses systemic, structural, organizational, institutional, cultural, and societal obstacles related to diversity, equity, and inclusion, underscoring the importance of socially responsible marketing in overcoming these challenges. It provides insights into how marketing initiatives can contribute to dismantling barriers and promoting diversity and inclusion within diverse organizational settings and workplaces. In conclusion, the paper underscores the pivotal role of socially responsible marketing in advancing diversity, equity, and inclusion agendas within organizational settings. It emphasizes the need for ethical and inclusive marketing practices and offers recommendations for incorporating social responsibility into marketing strategies to foster a more inclusive and equitable business environment. [ABSTRACT FROM AUTHOR]

We propose a general approximation method for the determination of optimal trading strategies in markets with proportional transaction costs, with a polynomial approximation of the residual value function. The method is exemplified by several problems, from optimally tracking benchmarks and hedging the log contract to maximizing utility from terminal wealth. Strategies are also approximated by practically executable, discrete trades. We identify the necessary trade-off between the trading frequency and trade size to ensure satisfactory agreement with the theoretically optimal, continuous strategies of infinite activity. [ABSTRACT FROM AUTHOR]

In the dynamic world of finance, the application of Artificial Intelligence (AI) in pair trading strategies is gaining significant interest among scholars. Current AI research largely concentrates on regression analyses of prices or spreads between paired assets for formulating trading strategies. However, AI models typically exhibit less precision in regression tasks compared to classification tasks, presenting a challenge in refining the accuracy of pair trading strategies. In pursuit of high-performance labels to elevate the precision of classification models, this study advanced the Triple Barrier Labeling Method for enhanced compatibility with pair trading strategies. This refinement enables the creation of diverse label sets, each tailored to distinct barrier configurations. Focusing on achieving maximal profit or minimizing the Maximum Drawdown (MDD), Genetic Algorithms (GAs) were employed for the optimization of these labels. After optimization, the labels were classified into two distinct types: High Risk and High Profit (HRHP) and Low Risk and Low Profit (LRLP). These labels then serve as the foundation for training machine learning models, which are designed to predict future trading activities in the cryptocurrency market. Our approach, employing cryptocurrency price data from 9 November 2017 to 31 August 2022 for training and 1 September 2022 to 1 December 2023 for testing, demonstrates a substantial improvement over traditional pair trading strategies. In particular, models trained with HRHP signals realized a 51.42% surge in profitability, while those trained with LRLP signals significantly mitigated risk, marked by a 73.24% reduction in the MDD. This innovative method marks a significant advancement in cryptocurrency pair trading strategies, offering traders a powerful and refined tool for optimizing their trading decisions. [ABSTRACT FROM AUTHOR]

Investment decision-makers increasingly rely on modern digital technologies to enhance their strategies in today's rapidly changing and complex market environment. This paper examines the impact of incorporating Long Short-term Memory (LSTM) models into traditional trading strategies. The core investigation revolves around whether strategies enhanced with LSTM technology perform better than traditional methods alone. Traditional trading strategies typically depend on analyzing current closing prices and various technical indicators to take trading action. However, by applying LSTM models, this study aims to forecast closing prices with greater accuracy, thereby improving trading performance. Our findings indicate that trading strategies that utilize LSTM models outperform traditional strategies. This improvement suggests a significant advantage in using LSTM models for market prediction and trading decision making. Acknowledging that no one-size-fits-all strategy works for every market condition or stock is crucial. As such, traders are encouraged to select and tailor their strategies based on thorough testing and analysis to best suit their needs and market conditions. This study contributes to a better understanding of how integrating LSTM models can enhance traditional trading strategies, offering a path toward more effective decision making in the unpredictable stock market. [ABSTRACT FROM AUTHOR]

Online reviews are an important part of product information and have important effects on consumers' purchasing decisions. Some sellers try to manipulate the market by inducing online reviews. In this study, a signal game model based on Bayesian conditional probability is constructed to analyze the preconditions, decision-making process, and effect on market demand and profit of this behavior. The results show that first, when consumer sensitivity to rebates reaches a certain threshold, low-quality sellers will adopt a conditional rebate strategy to induce consumers to give positive reviews. Second, the optimal rebate cost ( β * ) is obtained, where β * increases with the product price (p), but it is not necessarily monotonic in consumers' sensitivity to rebates (ρ) or the proportion of high-quality products (α). Third, the conditional rebate strategy can only work in a market dominated by low-quality goods. Using the conditional rebate strategy in a market dominated by high-quality goods will not bring benefits to low-quality sellers but will harm their profits. This study proposes that some developing online markets have collusive behaviors owing to a lack of regulations and laws, as well as consumers' concern for small interests. Ensuring the orderly development of online markets will require joint efforts by platform enterprises, government agencies, and consumers. [ABSTRACT FROM AUTHOR]

Using stochastics in stock market analysis is widely accepted for index estimation and ultra-high-frequency trading. However, previous studies linking index estimation to actual trading without applying low-frequency trading are limited. This study applied William%R to the existing research and used fixed parameters to remove noise from stochastics. We propose contributing to stock market stakeholders by finding an easy-to-apply algorithmic trading methodology for individual and pension fund investors. The algorithm constructed two oscillators with fixed parameters to identify when to enter and exit the index and achieved good results against the benchmark. We tested two ETFs, SPY (S&P 500) and EWY (MSCI Korea), from 2010 to 2022. Over the 12-year study period, our model showed it can outperform the benchmark index, having a high hit ratio of over 80%, a maximum drawdown in the low single digits, and a trading frequency of 1.5 trades per year. The results of our empirical research show that this methodology simplifies the process for investors to effectively implement market timing strategies in their investment decisions. [ABSTRACT FROM AUTHOR]

The ultimate goal of innovation is to improve performance. But if people's needs and uses are ignored, innovation will only be a formality. In the past, research on innovation mostly focused on technology, processes, business models, services, and organizations. The measurement of innovation focuses on capabilities, processes, results, and methods, but there has always been a lack of pre-innovation measurements and tools. This study is the first to use the innovation use theory proposed by Christensen et al. combined with innovation types, and it uses the measurement focus on the early stage of innovation as a post-innovation performance prediction. This study collected 590 valid samples and used SPSS and the four-step BK method to conduct regression analysis and mediation tests. The empirical results obtained the following: (1) a confirmed model and scale of the innovation use theory; (2) that three constructs of innovation use theory have an impact on market performance; and (3) that innovation types acting as mediators will improve market performance. This study establishes an academic model of the innovation use theory to provide a clear scale tool for subsequent research. In practice, it can first measure the direction of innovation and performance prediction, providing managers with a reference when developing new products and applying market strategies. [ABSTRACT FROM AUTHOR]

The wide-scale integration of electric vehicles (EVs) in developed countries represents a significant technological innovation and a step toward reducing carbon emissions from transportation. Conversely, in developing nations like the Philippines, the adoption and availability of EVs have not been as rapid or widespread compared to other countries. In identifying this gap, this study delved into the preferences and factors influencing Filipino consumers' willingness to purchase EVs. The study gathered 311 valid responses utilizing conjoint analysis with an orthogonal approach to assess the attributes influencing customers' purchase decisions. Conjoint analysis tools such as IBM SPSS v25 statistics were utilized to infer consumer preference. The results determined that cost is the primary concern for consumers by a considerable margin; followed by battery type and charging method; along with the type of EV, driving range, and charging speed; and most minor concern is regenerative brakes. Therefore, there is an apparent sensitivity to price and technology. This study is the first to apply conjoint analysis to the Philippine market, delivering in-depth consumer preference insights that can help manufacturers and policymakers customize their approach to making EVs more attractive and more viable in less developed markets. The results suggest that a targeted effort to overcome cost barriers and improve technological literacy among prospective buyers should be productive for speeding up EV adoption in the Philippines. The results could be extended in future research to a broader assessment of socioeconomic and environmental benefits, laying out a broader plan for promoting sustainable solutions in transportation. [ABSTRACT FROM AUTHOR]

Shadow prices simplify the derivation of optimal trading strategies in markets with transaction costs by transferring optimization into a more tractable, frictionless market. This paper establishes that a naïve shadow price ansatz for maximizing long-term returns, given average volatility yields a strategy that is, for small bid–ask spreads, asymptotically optimal at the third order. Considering the second-order impact of transaction costs, such a strategy is essentially optimal. However, for risk aversion different from one, we devise alternative strategies that outperform the shadow market at the fourth order. Finally, it is shown that the risk-neutral objective rules out the existence of shadow prices. [ABSTRACT FROM AUTHOR]

An efficient and effective portfolio provides maximum return potential with minimum risk by choosing an optimal balance among assets. Therefore, the objective of this study is to analyze the performance of optimized portfolios in minimizing risk and achieving maximum returns in the dynamics of Timor-Leste's equity portfolio in the international capital market for the period from January 2006 to December 2019. The empirical findings of this study indicate that the correlation matrix showed that JPM has a very strong positive correlation with one of the twenty assets, namely BAC (0.80). Moreover, the optimal portfolio of the twenty stocks exceeding 10% consists of four consecutive stocks, namely DGE.L (10.69%), NSRGY (10.37%), JPM (10.04%), and T (10.03%). In addition, the minimum portfolio consists of two stocks with a minimum variance of more than 10%, namely SAP.DE (11.20%) and DGE.L (10.39%). The evaluation of the optimal portfolio using Markowitz parameters also showed that the highest expected return and the lowest risk were 1.22% and 3.12%, respectively. [ABSTRACT FROM AUTHOR]

The focus of this paper is the revitalization of a heritage city center and the significance of retail trade and cruise ship tourism within this context. Fundamental concepts are presented in the literature review and the factors contributing to the decline of old city centers explored. The empirical section of the paper comprises a case study that highlights a specific municipality's efforts to revive its heritage city center. The main attraction in Koper is its well-preserved medieval city center with five-centuries-old Venetian architecture. An analysis of the municipality's initiatives is performed and a qualitative study that investigates the perceptions and experiences of stakeholders regarding the situation and the municipality's actions to preserve commercial activity in the city center. The results of the semi-structured interviews conducted with three distinct stakeholder groups are analyzed using the qualitative content analysis method. The findings reveal that the chosen municipality has achieved relative success in revitalizing its heritage city center. Concurrently, stakeholders' perspectives are utilized to identify potential drawbacks and explore opportunities for mitigating them. This paper concludes by presenting its theoretical and methodological contributions to the field of heritage city center revitalization, not only in the selected municipality but also beyond. These insights can inform the appropriate sustainable policy development and marketing strategy. [ABSTRACT FROM AUTHOR]

In the context of energy transformation and power market system reform, it is crucial to address the network risks associated with enhancing the integration of the "Energy–Information–Market" paradigm. This necessitates research on multi-energy market trading modes and the corresponding offensive and defensive technologies. This paper proposes a novel approach centered around a node-local Energy Hub (EH) that represents large industrial users with diverse energy demands. To facilitate multi-energy two-way trading, a price-oriented Transactive Energy (TE) market clearing strategy is developed. Building upon this transaction network framework, a data-driven attack strategy targeting the state estimator of the Transmission System Operator (TSO) is introduced and implemented in two stages, encompassing real-time topology estimation and False Data Injection attacks. By leveraging Matrix Transfer Entropy (MTE), the optimal attack target is identified to disrupt the economic stability of the system and the profit of the attacker increases significantly. The proposed attack strategy is validated through simulations conducted on a 30-node system, yielding conclusive evidence of its effectiveness while offering vital insights for system defense. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has rapidly emerged as a transformative force in multiple sectors, with digital marketing being a prominent beneficiary. As AI technologies continue to advance, their potential to reshape the digital marketing landscape becomes ever more apparent, leading to profound implications for businesses and their digital outreach strategies. This research seeks to answer the pivotal question: "How could AI applications be leveraged to optimize digital marketing strategies"? Drawing from a systematic literature review guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework, this study has identified 211 pertinent articles. Through a comprehensive bibliometric analysis, the findings were categorized into distinct clusters, namely: AI/ML (Machine Learning) Algorithms, Social Media, Consumer Behavior, E-Commerce, Digital Advertising, Budget Optimization, and Competitive Strategies. Each cluster offers insights into how AI applications can be harnessed to augment digital marketing efforts. The conclusion synthesizes key findings and suggests avenues for future exploration in this dynamic intersection of AI and digital marketing. This research contributes to the field by providing a comprehensive bibliometric analysis of AI in digital marketing, identifying key trends, challenges, and future directions. Our systematic approach offers valuable insights for businesses and researchers alike, enhancing the understanding of AI's evolving role in digital marketing strategies. [ABSTRACT FROM AUTHOR]

The overseas market expansion strategy is important for achieving competitive advantage and sustainable growth of global electronic component companies. Although the global electronic component market has grown rapidly recently, research focusing on the innovation strategy of global electronic component companies' expansion into overseas markets is scarce. This paper defines the key factors that influence the success of a global electronic component company's overseas market expansion strategy based on the Technology, Organization, and Environment (TOE) framework and quantitatively identifies the relative importance of factors at the technology, organization, and environmental levels through Analytic Hierarchy Process (AHP) analysis. As a case study, we analyze Samsung Electro-Mechanics, which has grown as a global electronic components company through an overseas market expansion strategy in recent decades. As a result of the analysis, among the three top factors defined as key factors, the technology factor was evaluated as the most important factor, and among the subfactors of the technology factor, "R&D Availability", and "Production Availability" were analyzed as the most important influencing factors. These analysis results suggest that global electronic component companies can achieve successful results when they pursue overseas market expansion strategies by prioritizing technology development and focusing on growth strategies suited to the market environment. This study is meaningful as an academic study focusing on the overseas market expansion strategies of global electronic component companies and makes a practical contribution by providing management implications that can be taken by electronic component companies seeking to expand overseas markets. [ABSTRACT FROM AUTHOR]

In this technological era, businesses tend to place advertisements via the medium of Wi-Fi advertising to expose their brands and products to the public. Wi-Fi advertising offers a platform for businesses to leverage their marketing strategies to achieve desired goals, provided they have a thorough understanding of their audience's behaviors. This paper aims to formulate a new RFI (recency, frequency, and interest) model that is able to analyze the behavior of the audience towards the advertisement. The audience's interest is measured based on the relationship between their total view duration on an advertisement and its corresponding overall click received. With the help of a clustering algorithm to perform the dynamic segmentation, the patterns of the audience behaviors are then being interpreted by segmenting the audience based on their engagement behaviors. In the experiments, two different Wi-Fi advertising attributes are tested to prove the new RFI model is applicable to effectively interpret the audience engagement behaviors with the proposed dynamic characteristics range table. The weak and strongly engaged behavioral characteristics of the segmented behavioral patterns of the audience, such as in a one-time audience, are interpreted successfully with the dynamic-characteristics range table. [ABSTRACT FROM AUTHOR]

Participation in the electricity market requires making commitments without knowing the real generation or electricity prices. This is problematic for renewable generators due to their fluctuating output. Battery energy storage systems (BESSs) integrated with renewable sources in a hybrid farm (HF) can alleviate imbalances and increase power system flexibility. However, the impact of battery degradation on long-term profitability must be taken into account when choosing the correct market participation strategy. This study evaluates the state-of-the-art on energy management systems (EMS) for HFs participating in day-ahead and intraday markets, incorporating both BESSs' calendar and cycling degradation. Results suggest that efforts to attain additional profits in intraday markets can be detrimental, especially when the degradation effect is considered in the analysis. A new market participation strategy is proposed that aims to address the limitations of market overlapping and forecasting errors. The results demonstrate that the proposed method can enhance long-term benefits while also reducing battery degradation. [ABSTRACT FROM AUTHOR]

Featured Application: This study applies to object capture of traditional live streaming scene frames to help the live e-commerce field to obtain more data to provide more marketing strategies. Nowadays, the commercial potential of live e-commerce is being continuously explored, and machine vision algorithms are gradually attracting the attention of marketers and researchers. During live streaming, the visuals can be effectively captured by algorithms, thereby providing additional data support. This paper aims to consider the diversity of live streaming devices and proposes an extremely lightweight and high-precision model to meet different requirements in live streaming scenarios. Building upon yolov5s, we incorporate the MobileNetV3 module and the CA attention mechanism to optimize the model. Furthermore, we construct a multi-object dataset specific to live streaming scenarios, including anchor facial expressions and commodities. A series of experiments have demonstrated that our model realized a 0.4% improvement in accuracy compared to the original model, while reducing its weight to 10.52%. [ABSTRACT FROM AUTHOR]

This study, based on the AISAS model, explores the impact of the interaction effect between visual and auditory signals on consumer purchase behavior. Using experimental methods, 120 participants were randomly assigned to four different visual and auditory signal combinations, and their purchase intentions and actual purchase behavior were measured. The results show that the interaction effect between visual and auditory signals has a significant impact on both purchase intentions and actual purchase behavior, and there is a significant positive relationship. Specifically, when visual and auditory signals are mutually consistent, consumers have the highest purchase intentions and actual purchase behavior; when both visual and auditory signals are absent, consumers have the lowest purchase intentions and actual purchase behavior; when either the visual or auditory signal is missing, consumers' purchase intentions and actual purchase behavior are between the two extremes. This study provides a new perspective for understanding consumers' decision-making processes in multi-sensory environments and offers valuable insights for the development of marketing strategies. [ABSTRACT FROM AUTHOR]

Featured Application: Human resources, security, customer service, and intelligent recommendations can benefit from deploying and applying systems such as the one proposed in this paper. Market segmentation is a crucial marketing strategy that involves identifying and defining distinct groups of buyers to target a company's marketing efforts effectively. To achieve this, the use of data to estimate consumer preferences and behavior is both appropriate and adequate. Visual elements, such as color and shape, in advertising can effectively communicate the product or service being promoted and influence consumer perceptions of its quality. Similarly, a person's outward appearance plays a pivotal role in nonverbal communication, significantly impacting human social interactions and providing insights into individuals' emotional states. In this study, we introduce an innovative deep learning model capable of predicting one of the styles in the seven universal styles model. By employing various advanced deep learning techniques, our models automatically extract features from full-body images, enabling the identification of style-defining traits in clothing subjects. Among the models proposed, the XCEPTION-based approach achieved an impressive top accuracy of 98.27%, highlighting its efficacy in accurately predicting styles. Furthermore, we developed a personalized ad generator that enjoyed a high acceptance rate of 80.56% among surveyed users, demonstrating the power of data-driven approaches in generating engaging and relevant content. Overall, the utilization of data to estimate consumer preferences and style traits is appropriate and effective in enhancing marketing strategies, as evidenced by the success of our deep learning models and personalized ad generator. By leveraging data-driven insights, businesses can create targeted and compelling marketing campaigns, thereby increasing their overall success in reaching and resonating with their desired audience. [ABSTRACT FROM AUTHOR]

Fuzzy marketing considers the degree to which a customer belongs to specific segments and subsequently allows them to be targeted with messages that engage them emotionally. To better understand the application and importance of fuzzy logic in marketing strategy, we developed a systematic literature review with bibliometric analysis to examine a sample of 96 studies from the SCOPUS database to identify research activity on this topic until December 2022. It was possible to create a connection between these concepts, marketing and fuzzy logic, to increase the efforts of marketing professionals. For instance, the results show that adopting approaches such as fuzzy marketing or the fuzzy marketing mix model enhances the company's capability to build stronger customer relationships, enhance profitability, and improve marketing performance. [ABSTRACT FROM AUTHOR]

The social influencer integrated marketing strategy, which builds social influencers through potential users, has gained widespread attention in the industry. Traditional Scoring Link Prediction Algorithms (SLPA) mainly rely on homogeneous network indicators to predict friend relationships, which cannot provide accurate link prediction results in cold-start situations. To overcome these limitations, the Closeness Heterogeneous Link Prediction Algorithm (CHLPA) is proposed, which uses node closeness centrality to describe the social intimacy of nodes and provides a heterogeneous measure of a network based on this. Three types of heterogeneous indicators of social intimacy were proposed based on the principle of three-degree influence. Due to scarce overlapping node sample data, CHLPA uses gradient boosting trees to select the most suitable index, the second most suitable index, and the third most suitable index from Social Intimacy Heterogeneous Indexes (SIHIs) and SLPAs. Then, these indicators are weighted and combined to predict the likelihood of other node users in the two product circles in an online brand community becoming friends with overlapping node users. Finally, a hill-climbing algorithm is designed based on this to build integrated marketing social influencers, and the effectiveness and robustness of the algorithm are validated. [ABSTRACT FROM AUTHOR]

Innovation has always been the driving force behind social progress. Enterprises will adopt different types of technological innovations according to their goals, resources, and market strategies. The industry generally pays attention to the development and application of electric vehicle technology innovation, but a single method may not be able to fully explain the innovation of electric vehicle technology. Furthermore, the results of technological innovation must be presented in terms of market benefits. Otherwise, insufficient cash flow will lead to innovation interruption. Therefore, this study uses the innovation matrix proposed by Rothaermel to classify the matrix formed by the market and technology. This study collects 43 periodicals and special publications published in 2010–2022 and 40 related electric vehicle literature that can be downloaded, summarizes the literature content according to the innovation matrix using literature bibliometric perspective and analysis, and obtains (1) most of the innovative technologies of electric vehicles originated from the extension of previous technologies and (2) batteries and power supplements that are the key items of electric vehicles. The proportion of radical technological innovation is relatively high, and they are also the main factors of market sales. Theoretically, this study can provide a basis for studying the combination of Rothaermel's "innovation matrix" and Ansoff's "expansion matrix". In practice, this is the first time the electric vehicle industry is taken as an example, combining the two models, aiming at technology/production/market/performance for electric vehicle industry managers, the technological innovation direction, and the formulation of market strategy operations and advanced deployment. [ABSTRACT FROM AUTHOR]

The Web has provided an increasing proportion of use as a medium for e-commerce in addition to various recommender systems. It can be used for analyzing recommendation system-based feedback (e.g., a form in which a user inputs their preferences for various items as numerical values into a specific evaluation system) to estimate customer interest; in addition, analyzing multi-modal types of feedback (e.g., product purchase traces, inquiry lists, inquiry times, and comments) with deep learning can also be used to estimate user interest. As many companies around the world promote their products through micro-influencers on the Web, related research has continued to predict the purchase conversion rate of the influencer through a variety of technologies. In this work, we present a multi-modal micro-influencer analysis scheme for a marketing maximization strategy. Our scheme uses the multi-modal data stored in Mecha Solution's own shopping mall of Korea, as well as famous Korean Internet platforms, and Coupang, Naver, and Oliveyoung's data such as article posting comments and statistics information. By extracting the main characteristics of the real article postings from real users as opposed to those from factitious influencers posting articles and comments and identifying articles other than advertisements, influencer scores are obtained, assuming that articles other than advertisements can further increase the purchase conversion rate. Based on influencer score, we propose a multi-modal micro-influencer analysis scheme that recommends influencers use content-based collaborative filtering and user-based collaborative filtering for items that the influencer has not yet reviewed. The experiment was implemented to prove that the proposed scheme successfully achieves this goal. [ABSTRACT FROM AUTHOR]

This paper aims to explore Youth's attitudes towards digital marketing utility perception and its effect on behavioral patterns in a cross-cultural perspective. The unified theory of acceptance and use of technology (UTAUT 2) model was adopted together with three new variables from the reasoned action theory and the 5S Internet marketing model to propose a theoretical model on Youth's digital marketing adoption. A survey was conducted in Italy (N = 165) and Lebanon (N = 150), and PLS analysis was implemented for the empirical testing of the proposed research model. In the Italian sample, Hedonic motivation, social influence, facilitating conditions, and efficiency significantly predicted the behavioral intention of digital marketing which, in turn, was significantly related to use behavior. Subsequently, in the Lebanese sample, the subjective norms of hedonic motivation, social influence, experience and habit predicted behavioral intention, which was positively related with use behavior. The results led to the conclusion that national cultures still play an important role in affecting digital marketing adoption among younger generations, especially in less industrialized and technologically developed countries. Therefore, companies should keep this aspect in mind when innovating and developing digital marketing strategies targeting this generation. [ABSTRACT FROM AUTHOR]

For the tourism industry, the COVID-19 pandemic has acted as an accelerator towards the 4th industrial revolution by creating new and innovative solutions, which have transformed management, finance, planning and opened new avenues for the introduction of innovative sales and marketing technologies. As the tourism industry in Greece faces significant challenges and opportunities posed by the COVID-19 pandemic, additional needs have arisen for tourism businesses, as confirmed in this research, to adapt faster to digital operations and strengthen digital marketing through multi-channel distribution and use of digital assistants. This study aims to investigate the use of digital marketing tools by tourism companies as well as the overall satisfaction of the companies with its use and the areas of impact of digital marketing from the COVID-19 pandemic, and then to highlight all those features that stand out from those of their competitors, as well as the creation of an appropriate marketing strategy that will ensure the flow of new customers and increased revenue. To meet this purpose, an empirical survey was conducted in tourism companies in order to provide answers to research questions. As tourism businesses have not yet made sufficient use of digital media as a strategic marketing tool, this research is the basis for further research into the use of technology and digital tools to reach customers and create a more personalized experience for them. [ABSTRACT FROM AUTHOR]

This bibliometric review explores the role of social media in small- and medium-sized enterprises (SMEs) by examining the current literature and identifying research gaps. A comprehensive analysis of 293 Scopus-indexed journal articles published between 2007 and 2022 was conducted using VOSviewer software. The study's objective is to understand the impact of social media on SMEs' growth and development, with a focus on customer engagement, return on investment (ROI) metrics, and marketing strategies. The analysis uncovers three primary research clusters: (i) social media customer engagement, (ii) social media ROI metrics, and (iii) social media marketing strategies. These findings offer valuable insights for researchers and practitioners aiming to comprehend the existing knowledge landscape and inform future studies regarding the practical implementation of social media in SMEs. [ABSTRACT FROM AUTHOR]

In the current post-COVID-19 era, online marketing is a supporting tool in marketing. The potential visitors to tourism destinations, such as geoparks, are increasingly guided and oriented by the rules of online marketing as the online space represents the main source of information. Geoparks should take this as a key fact. The research concentrates on the issue of geopark marketing from the view of the available information that geoparks present in the online space. The fundamental is to point out the information that is available on geopark websites. The method used in the research is based on an evaluation matrix that served as a basis for searching for information on websites. Based on the results of the analysis, geoparks in the EGN network present information of a general nature to a sufficient extent on their websites; they lack a better offer of product packages, online sales and orientation to new social networks that are used by the young generation. The clear answer is the professionalization of marketing, which would undoubtedly represent an effective step in the management of geoparks as well as the promotion of the country that the geopark represents. [ABSTRACT FROM AUTHOR]

This study aims to determine the importance of factors affecting supplier selection in the pesticide distribution sector as a global emerging market and present a decision-making model for the corporate marketing strategy. Specifically, a comparative study between suppliers and retail distribution experts was conducted to compare differences in the perception of supplier selection factors according to organizational characteristics. Based on previous studies, a decision-making model based on the AHP methodology was constructed with a total of 20 factors in five areas: product quality, price, flexibility, promotion support, and brand. Then, 42 Korean experts were surveyed to measure the importance of these factors. The results showed that product quality is the most critical factor in supplier selection, followed by price, brand, promotional support, and flexibility, in that order. Manufacturers consider product quality as the most important factor, while retailers consider price as the most important factor. Among the 20 factors, 'quality excellence', 'expected return', and 'technological competitiveness' were found to be the most important factors. In addition, while manufacturers considered factors such as 'corporate reputation' and 'corporate trust' as more important, retailers considered factors related to product characteristics, such as 'product awareness' and 'brand reputation' as more important. [ABSTRACT FROM AUTHOR]

This study aims to estimate the market value, or implicit prices, associated with the main craft beer attributes (e.g., beer style, organic, gluten-free, and package-related features) and support producers in detecting the more profitable marketing strategies. For this purpose, we conducted an empirical analysis employing sales data of craft beers from the Italian online market, and we estimated a hedonic price model via ordinary least squares. Results show that the type of package and cup only has moderate effects on price. Furthermore, a moderate premium price is found for gluten-free craft beers, while craft beers with organic labels and Italian origin do not benefit from the higher price. Instead, the beer style adopted strongly affected the product price: the highest premium prices were detected for Barleywine (+49.9%) and Italian Grape Ale (+39.6%) beer styles. Furthermore, relevant premium prices, higher than +25%, were estimated for other beer styles such as Sour, Fruit Beer, and Stout. Results suggest that artisanal breweries can effectively differentiate their product according to the beer style. To the best of our knowledge, the current study offers the first empirical evidence on how beer styles as well as other product characteristics affect the market price of craft beer by using secondary data. [ABSTRACT FROM AUTHOR]

Due to the rising worldwide demand for green chemicals, the bio-based polymer market is anticipated to expand substantially in the future. The synthesis of functional polymers has been a burgeoning area of research for decades. The primary driving force behind the development of bio-based polymers has been their compostability and biodegradability, which are critical given the public concern about waste. Significant advancements in the method for refining biomass raw materials towards the creation of bio-based construction materials and products are driving this rise. Bio-based polymers with this chemical structure are more flexible and adaptive, which allows them to attain their intended characteristics and functionalities. In commercial applications and healthcare and biotechnology, where completely manufactured, naturally occurring biomolecules are utilized and such polymers have the greatest impact. At the same time, limitations in polymer architectural control, biostability, and structural dynamics hinder the creation of biocompatible and functionally varied polymers. From this standpoint, the importance of functional biosynthetic polymers in the future years is highlighted, as well as new methods for addressing the aforementioned challenges. The article comprehensively highlighted the current strategies, market dynamics, and research trends of emerging Bio-Based Polymers. In addition, the most recent scientific breakthroughs in bio-based polymers are discussed. [ABSTRACT FROM AUTHOR]

Innovative technology significantly transforms numerous activities and operations in the logistics sector across various industries, including the aviation sphere. This primary quantitative research aimed to explore the evolution of logistics and supply chain management in the digital age for aviation companies in Saudi Arabia. The research involved conducting a survey among 104 supply chain and technology personnel from Saudi Cargo and its affiliate firms in Saudi Arabia. Partial least squares (PLS–SEM) was used for data analysis to determine the relationships between three independent variables: market intelligence quality (MIQ), manufacturing–marketing coordination (MMC), and supply chain intelligence quality (SCIQ), with product innovation performance (PIP) as the dependent variable. The results indicated that SCIQ and MIQ have a positive and significant statistical relationship with PIP. Nonetheless, the findings disproved that the MMC gives insights into consumer needs directly affecting PIP. From this study, it can be concluded that aviation companies should improve their supply chain systems, marketing domain, and manufacturing marketing coordination to realize the improved performance of their product innovations in the contemporary digital era. [ABSTRACT FROM AUTHOR]

Leading to the enhancement of smart grid implementation, the peer-to-peer (P2P) energy transaction concept has grown dramatically in recent years allowing the end-users to successfully exchange their excess generation and demand in a more profitable way. This paper presents local energy market (LEM) architecture with various market strategies for P2P energy trading among a set of end-users (consumers and prosumers) in a smart residential locality. In a P2P fashion, prosumers/consumers can export/import the available generation/demand in the LEM at a profit relative to utility prices. A common portal known as the transactive energy market operator (TEMO) is introduced to manage the trading in the LEM. The goal of the TEMO is to develop a transaction agreement among P2P players by establishing a price for each transaction based on the price and trading demand provided by the participants. A few case studies on a location with ten residential P2P participants validate the performance of the proposed TEMO. [ABSTRACT FROM AUTHOR]

Integrating green approaches and digital marketing strategies for Information and Communication Technologies (ICTs), which reduce environmental risks to desired levels by eliminating emissions and pollution, is considered one of the most promising solutions for logistics companies. The study strives to bring a practical and applicable solution to the decision problem involving the selection of indicators for green approaches and digital marketing strategies for ICTs in the logistics sector. An integrated Fermatean Fuzzy Step-wise Weight Assessment Ratio Analysis (FF–SWARA) and Fermatean Fuzzy Complex Proportional Assessment (FF–COPRAS) methodology is applied to evaluate green approaches and digital marketing strategies. Concerning the findings, the foremost criterion is "data management," whereas the best strategy is "programmatic advertising." To the best of the authors' knowledge, there is no other study that both offers a strategy selection for the logistics industry and considers environmental protection, sustainability, digital transformation, energy costs, and social and economic factors. The study is a part of ongoing research on productivity, sustainability, the environment, digitization, recycling and estimating levels of waste reduction, as well as business practices, competitiveness and ensuring employee satisfaction and resource efficiency. Also, it investigates the similarities and dissimilarities in the green approach practices of business in logistics and determines the extent to which these practices could be reflected. It is expected to ensure a roadmap for green approach practices and to support sustainable and ecological awareness efforts for ICTs in the logistics sector. Logistics companies can select an integrated digital strategy based on green informatics that suits them using the decision model employed in this study, which can handle uncertainties effectively. In this regard, the study's findings, which focus on reaching customers and the most precise target audience in digital applications for businesses, are critical for developing strategy, plan and process. [ABSTRACT FROM AUTHOR]

Cities operate in a competitive social environment requiring local authorities to adopt marketing strategies with significant economic ratings. City marketing that is related to the meaning of a city's name encourages activities in the city or region. The present study adopted a quantitative survey on a sample of 152 employees in companies to explore how important marketing is perceived for a city's development. The research was done in Trikala, a city in Greece. The key conclusion was that the more critical the participants consider the interventions in the city's natural environment, the more they believe that the city can benefit from corporate sponsorships. Subsequently, it appeared that the more they support the interventions in the structured environment of the city, the less they consider that corporate sponsorships can benefit it. It was explained that structured interventions usually involve very high investments that require funding from the central government, as sponsorships are not enough. The most substantial positive relationship was found between the importance of interventions in employment, entrepreneurship and tourism, and the importance of business sponsorships. [ABSTRACT FROM AUTHOR]

(1) Background: Marketing and advertising strategies for food products are very diverse and have a differential effect on consumers' behaviours and attitudes towards products. (2) Objectives: To examine the influence of point-of-purchase (PoP) marketing and advertising strategies and the promotion of products employing opinion leaders (celebrities) on the healthy perception of pre-packaged food and buying behaviour of young consumers. (3) Methods: Online survey (N = 130) of 18–31 years old participants. (4) Results: "Price" was the most influential factor when purchasing a snack (66.2%), although "salt and macronutrient content" had a major influence on females (x2(1,N=129) = 14.02, p < 0.001). Participants with low or no weight satisfaction were more prone to consider "low fat" (x2(1,N=130) = 5.02, p = 0.025) and chose "green" as the most suitable colour for healthy snack packaging. Male celebrities were more picked by males than female participants (x2(1,N=129) = 6.41, p = 0.011). (4) Conclusion: Using green packaging, nutritional claims related to low-calorie intakes or accentuating salt and macronutrient content, and using opinion leaders with whom consumers can relate to, were the most influential factors in fostering a healthy perception of pre-packaged food products. These results highlight the need for policies to limit marketing strategies to avoid misleading consumers' opinion of a product as healthy when it is not. [ABSTRACT FROM AUTHOR]

This paper attempts to situate the notion of shumi as a rhetorical device used by modern Japanese department stores as part of their marketing strategies. Although often equated with the concept of 'taste', I demonstrate how shumi both overlaps with and differs from the concept of taste, as it is often discussed in critical theory in the context of consumerism. I do this by examining how shumi was used in the PR-magazines of various department stores and other related forms of print media. Special attention is paid to the PR-magazine of Mitsukoshi, which is perhaps the most innovative department store in modern Japanese history. Subsequently, I analyze three short stories by Mori Ōgai (1862–1922) published in Mitsukoshi's PR-magazine between 1911 and 1912. Mitsukoshi printed short stories by acclaimed authors in their magazines, mostly as a form of lighthearted entertainment and branding. Yet, when read closely, Ōgai's three stories also form a profound observation of the skewed moral reality of a market-driven economy. Each of the narratives under scrutiny in this paper shows the human cost of a system in which social relations are dictated by consumer objects. The cultivation of the urge to consume was carefully framed around the rhetoric of shumi and was thus not merely a marketing tool to increase profit margins but also a mechanism to manipulate the desires and anxieties of consumers. A reading of Ōgai's three short narratives reveals the ambivalent morality produced by the rhetoric of shumi, which in turn engendered and validated the identities of an emerging middle class through the consumable object-as-sign. [ABSTRACT FROM AUTHOR]

This review is devoted to an overview of the prospects for the development of the global hydrogen market and the strategies of individual countries aimed at transforming energy systems in favor of decarbonization and greening through the use of hydrogen. Special attention is paid to the prospects for the development of the Russian hydrogen market. The authors of the review used the method of comparative analysis and analytical generalization of publications, programs and regulatory documents from different countries. The results of the comparative analysis led to the conclusion that most of the publications currently focus on the technical and technological aspects of hydrogen energy, solving the problem of increasing the efficiency of methods for the production, transportation, distribution and storage of hydrogen fuel. The results of the analytical generalization led to the conclusion that in all countries of the world, the technology for the production of highly environmentally friendly "green" hydrogen is at an early stage, which makes it highly dependent on government initiatives to develop hydrogen projects and government funding of both scientific research in this area and realizable projects. In addition, the peaks of interest in the field of hydrogen energy are associated with market changes in the fossil energy markets, which makes the development of this technology unstable and dependent on market conditions. Moreover, the focus of attention of a number of authors is the prospects for the development of the hydrogen market. It is concluded that many countries are ready to invest in the development of hydrogen energy and, given the growth in demand for hydrogen, are ready to export it at an affordable price. That is, in the future, the international hydrogen market, as technical, technological, and economic problems are solved, will grow. The results of the study also indicate the fundamental co-direction of the trends in the development of hydrogen energy in Russia with global trends. At the same time, it should be emphasized that the high resource and scientific and technological potential allows Russia to fully focus its strategy on its implementation, not only developing the domestic market but also acting as an exporter of hydrogen and expanding international cooperation in this area. [ABSTRACT FROM AUTHOR]

To reduce food waste, it is essential to motivate consumers to purchase and consume products that deviate from optimality on the basis of only cosmetic specifications (also called suboptimal products). Previous research has shown it to be challenging to motivate consumers to buy such suboptimal products. Sustainability or authenticity positioning of suboptimal products may be a promising avenue, but no research to date has examined their effects on consumer behaviour. The current research examines whether sustainability and/or authenticity positioning increase the sales of suboptimal products and whether these strategies increase suboptimal product perceptions up to the level of optimal products. Two field experiments examined whether sustainability and authenticity positioning could increase the sales of suboptimal products in two settings: a daily market and a supermarket. They reveal that both types of positioning can increase the sales of suboptimal products. Moreover, in an online experiment, consumers were presented with suboptimal and optimal products with sustainability, authenticity, information, or no positioning, and consumers indicated their perceptions of and purchase intentions for suboptimal and optimal products. It demonstrates that the strategies motivate consumers to perceive suboptimal products as more similar to optimal products and can increase purchase intentions for suboptimal products. Together, these findings suggest that sustainability and authenticity positioning of suboptimal products can support the fight against food waste. [ABSTRACT FROM AUTHOR]

The aim of this paper is to study the quantum-like approach to the description of the market in the context of the principle of minimum Fisher information. We wish to investigate the validity of using squeezed coherent states as market strategies. For this purpose, we focus on the representation of any squeezed coherent state with respect to the basis of the eigenvectors of the observable of market risk. We derive a formula for the probability of being the squeezed coherent state in one of these states. The distribution that we call generalized Poisson establishes the relation between the squeezed coherent states and their description in the language of risk in quantum terms. We provide a formula specifying the total risk of squeezed coherent strategy. Then, we propose a risk of risk concept that is in fact the second central moment of the generalized Poisson distribution. This is an important numerical characterization of squeezed coherent strategies. We provide its interpretations on the basis of the uncertainty relation for time and energy. [ABSTRACT FROM AUTHOR]

The practice of unsolicited advertisements on social media has grown prevalent. This data article presents 837 US-based social media users' consumer perceptions of such advertisements. Understanding how consumers perceive unsolicited advertising is vital to developing effective digital marketing strategies. Data collection was via an online survey adopting multi-measurement items from extant studies for reliability and validity. The data showed high internal consistency with Cronbach's alpha testing, and confirmatory factor analysis (CFA) found the measurement model valid. Goodness-of-fit indices showed a good fit with the data. Finally, convergent and discriminant validity was confirmed using the composite reliability, average variance extracted (AVE), and correlations among constructs. Further research may utilise the data using inferential analysis techniques to add to our understanding of consumer perceptions of unsolicited advertising on social media. Dataset: 10.17632/zcp5httw5c.1. Dataset License: CC BY 4.0 [ABSTRACT FROM AUTHOR]

In this paper, a study was completed investigating the financial viability of a 5 MW solar power plant in Montenegro with direct access to the market, rather than a long-term power purchase agreement. The empirical research included an econometric analysis and forecast of the prices on the exchange market, using two methods, autoregressive integrated moving average (ARIMA) and neural network auto regression (NNAR), which are compared to the forecast electricity prices. The former was used in order to obtain the electricity prices forecast, since it showed significantly better predictive performances. Consequently, the financial analysis results indicated this business strategy is a financially more viable option, even though it implies increased risks. All investigated metrics and sensitivity analysis pointed in favor of this option, which has significantly higher profitability with a shorter payback period, compared to the usual market strategy. The main conclusion and recommendation drawn from the analysis are that taking into account the entire environment and prospects for the following years, a riskier business strategy of entering the market directly, or a so-called structured PPA, is put forward to improve project returns and speed up energy-transformation processes in a developing country. [ABSTRACT FROM AUTHOR]

Saudi Arabia has proposed a new project, NEOM city, planned on the coast of the Red Sea with various unique and challenging features as a part of its vision 2030 to transform itself from an oil-dependent economy to knowledge-based economy. However, there are various risks and challenges associated with the project, the study of which is essential to effectively design and implement marketing and promotional strategies. Considering the large scale and scope of the project, the purpose of this study is to identify and evaluate the major contexts and associated risks in accordance with the planned city's objectives. An online questionnaire-based survey was used to collecting data related to the severity of the risks identified and classified in a literature review. A purposive sampling approach was adopted to select experts from various governmental institutions to participate in the study. A final sample of 417 expert participants was achieved from various ministries and departments in Saudi Arabia. Eleven risk factors and challenges were identified, including design challenges, as well as legal, contractual, operational, force majeure, human resources, financial, technological, political, environmental, and sociocultural risks. Risks related to human resources (mean impact = 4) and technology factors (mean impact = 4), as well as contractual risks (mean impact = 3.9), were identified to be very high, whereas environmental (mean impact = 2.7), legal (mean impact = 2.5), and force majeure (mean impact = 2.2) risks were identified to be of low severity. Managing mega projects requires effective planning and implementation, along with risk identification and mitigation mechanisms. In addition, it is essential to manage various influencing factors (especially government decisions) in the process of implementation to achieve success. [ABSTRACT FROM AUTHOR]

Environmentally intense and negative consequences relateing to conventional meat production systems have induced some actors to suggest alternative meat sources. Diseases carried by animals, human perception of cruelty to animals, and public health concerns about cardiovascular diseases have provided the basis for the development of cultured meat. The current market is influenced by many factors, including regulators, affordability, religion, and media perception. The existing cultured meat market is also regulated by legislatures, affordability, consumer religion, and the media. Consumer perception is distributed across various aspects, including ethical priorities, nutritional profile of the meat consumed, age-based acceptance, gender differentiation, political orientation, land-based attitude, education status, socioeconomic factors, and familiarity factor with the existing product in the market. Inhibiting barriers reported among consumers—including low naturalness, safety, nutritional concerns, trust, neophobia, economic, and ethical approaches—should be employed as marketing tactics directly to address their respective concerns. Tissue culture, starter cells, printing, and 3D printing are some of the methods currently being used for the production of cultured meat. Similarly, many hybrid technologies are also being used to produce meat-like products to increase consumer familiarity along and market presence. Existing research frameworks have improved the previous mindset of consumers with media coverage, educational frameworks, and the textural attributes of cultured meat. Additional benefits of CUME may include being environmentally friendly with less production of greenhouse gases. However, consumer trust, affordability, improving nutritional status, and widescale adoption are just a few of the parameters that need to be addressed to enhance consumer acceptability of these products. The aim of this article was to analyze the current state of cultured meat and the marketing content challenges and strategies used to advance public acceptance of cultured meat. [ABSTRACT FROM AUTHOR]

This paper focuses on strategic corporate financial decisions related to capital structure to increased firm value, moderated by the COVID-19 pandemic under MM theory, trade-off theory, and pecking order theory. The analytical method used is panel data analysis, with observations of 1828 non-financial companies on the Indonesia Stock Exchange from the years 2019 to 2021. The results show that there is an effect of capital structure on firm value in a positive direction, and the moderating role of the COVID-19 pandemic weakens the effect of capital structure on firm value. The findings show that capital structure only has a significant effect on firm value for the debt-dominant group, but not for the equity-dominant group. The moderating effect of the COVID-19 pandemic affects firm value for the debt-dominant group, but not for the equity-dominant group. [ABSTRACT FROM AUTHOR]

Continual scrutiny of and attacks on the palm oil industry in Indonesia have been ongoing for decades. The constant arguments against the palm oil industry have always touched on the issues of environmental sustainability, including deforestation and biodiversity loss, human rights issues, and various unsustainable practices. Even though many major palm oil players have voluntarily joined the RSPO, as well as the mandatory ISPO, with both certification bodies covering the environmental sustainability contexts of community development and human rights, constant attacks from stakeholders are mounting. This paper argues that besides fulfilling all of these requirements, there is a need for the industry as a whole to apply the right approach to green marketing or sustainable marketing as a means of strategy and business sustainability. Without a proper green marketing strategy and platform, the message of sustainability will not be delivered efficiently to the intended targets. There needs to be an understanding in regard to the market and also collaborative action between various stakeholders—including competitors and NGOs—to create and execute a fruitful green marketing strategy that can cross boundaries and be well received by the intended market. [ABSTRACT FROM AUTHOR]