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Issues of diversity and inclusion increasingly influence the purchasing process and brand loyalty of new generations of customers. Additionally, scholars and policymakers are calling for a more inclusive society and advocating for the integration of people with disabilities. However, there is a lack of research investigating these issues from a marketing perspective. Using a strategy of inquiry regarding in-depth multiple case studies from different players of the toy industry, this paper highlights how to set marketing strategies that develop and communicate new offerings by promoting both Marketing and Social Value and fostering the social inclusion of children with a disability. The proposed model contributes to the emerging literature of Inclusive Marketing and will help marketers implement a socially inclusive approach. [ABSTRACT FROM AUTHOR]

We study the interplay between cyber failures and information technology (IT) capability reputation (ITCAPR). Cyber failures often reveal vulnerable information systems (IS) processes and IT assets at their root that point to firm IT capability weakness. For external stakeholders, firm IT capability is unobservable and therefore a matter of perception or reputation. We theorize about cyber failures' adverse impacts on firm market value and firm ITCAPR based on how external stakeholders reconcile their ex ante perception of firm IT capability strength, or established ITCAPR, and their perception of an ex post revelation of IT capability weakness by cyber failures. Our analysis of 264 cyber failures finds empirical support for our theory-based predictions. We find that ex post revelation of IT capability weakness leads external stakeholders to adjust downward their ex ante perceptions of firm IT capability proportional to the severity of IT capability weakness. Two ex post consequences are commensurate loss of firm market value and decline in firm ITCAPR. Based on our main finding, that external stakeholders perceive IT capability weakness as an endogenous contributory factor to cyber failures that leads to erosion of firm ITCAPR, we contribute to theory in significant ways. First, we theoretically complement a predominant research focus on IT capability strength as a value-relevant intangible asset by confirming that IT capability weakness is a value-relevant intangible liability as well as adding "vulnerability" or "weakness" as a distinctive process aspect absent from prior literature linking IS processes and IT capabilities. Second, we theoretically add to an almost exclusive focus of research on cyber failures' short-term adverse effect on firm market value by documenting for the first time a time-lagged eroding effect on firm ITCAPR. Last, we theoretically show IT controls and particularly ones embedded in IS processes as an essential aspect of IT capability strength as well as cybersecurity protection and prevention. [ABSTRACT FROM AUTHOR]

We propose a loglinear present-value identity in which investment ("scale"), profitability ("yield"), and discount rates determine a firm's market-to-book ratio. Our identity reconciles existing influential market-to-book decompositions and facilitates novel insights from three empirical applications: (1) Both investment and profitability are important contributors to the value spread and stock return news variance. (2) Any cross-sectional return predictability has a mirror image in cash-flow fundamentals, providing asset pricing theories with additional moments to match. (3) The investment spread significantly improves the predictability of time-series variation in the value premium and justifies the poor performance of value in recent years. [ABSTRACT FROM AUTHOR]

The large divergence in the returns of top-performing star firms and the rest of the economy is substantially reduced when we account for the mismeasurement of intangible capital. Star firms produce and invest more per dollar in invested capital, have more valuable innovations as measured by the market value of patents, and are as exposed to competitive shocks as nonstars. Star firms have higher markups that are predicted early in their life cycle at a time when they are small. Overall, after we correct for the mismeasurement of intangibles, the evidence points to the superior ability of star firms. [ABSTRACT FROM AUTHOR]

This paper considers how a manager decides to disclose or withhold segment information in a capital market setting. In particular, we develop a multi-period model in which a manager in each period decides how to allocate her effort between two businesses. The profit earned in each segment is determined by the manager's effort and ability as well as each segment's market profitability and inherent uncertainty. In this setting, in contrast to the expectation of segment disclosure being withheld due to conflicts of interest between managers and shareholders, we identify the conditions under which the manager rationally withholds segment information and achieves higher social welfare. In a setting where the manager is concerned about the current stock price, disclosing more disaggregated information to the stock market does not necessarily lead to more efficient monitoring. The capital market values various segment earnings differently, and in response to this valuation, a rational manager may greatly alter her behavior, leading to inefficient outcomes. [ABSTRACT FROM AUTHOR]

This article examines equity market perceptions of fair value reporting for tangible assets. We identify six events—four designated as increasing, two as decreasing—affecting the likelihood of U.S. adoption of fair value reporting for investment property (i.e., real estate) assets, one of the largest asset classes in the world. Fair value adoption in the United States would facilitate convergence of one of the widest remaining disparities between U.S. reporting and International Financial Reporting Standards (IFRS): accounting for tangible investment property assets, where the United States (IFRS) requires depreciated historical cost (recognized or disclosed fair values). Using a sample of U.S. investment property firms, we document an average positive market reaction for movement toward fair value reporting. We further find predictable cross-sectional variation, with the market reaction increasing for firms with greater commitment to high-quality reporting, greater investor demand for fair values, higher financial risk, and staler asset values. Overall, the results are consistent with U.S. equity markets perceiving net benefits to movement toward a fair value reporting approach for this asset class. [ABSTRACT FROM AUTHOR]

Cryptocurrencies and blockchain technology are disruptive innovations at the vanguard of a new wave of the digital revolution. The far-reaching appeal, global reach, unprecedented mobility of capital, and multitude of trading venues have created a marketplace like no other. The economic fundamentals underlying this market are yet to be fully comprehended, as evidenced by the often-contradicting guidelines recommended by accounting firms, government agencies, and standard setters. Many of the definitions and models used for classical markets cannot be applied directly to cryptocurrency. Basic concepts must be reinterpreted, and models must be modified to fit the mechanics of these markets. In this article, we focus on one such concept: that of fair value. We argue that in light of the fragmentation of cryptocurrency markets and the global dispersion of trading venues, a principal market may be difficult to identify. The primary objective of this article is to present a methodology to dynamically designate principal markets and derive fair value prices for financial reporting using this designation. [ABSTRACT FROM AUTHOR]

Purpose: The interplay between individual and collective creativity and its translation into innovation is a critical yet complex challenge in the ever-evolving innovation landscape. This study delves into the intricate relationship between managerial ability, intellectual property rights (IPRs) and research and development (R&D) investments contextualized within the dynamics of leverage, firm life stages and tangibility for pharmaceutical firms in the Asia-Pacific region. By exploring how micro-level factors influence macro-level innovation processes, this study aims to contribute to the broader understanding of creativity and innovation, a theme at the heart of addressing contemporary global challenges. Design/methodology/approach: Econometric methodologies were used to analyse a data set comprising 2,660 firm-year observations spanning the decade from 2011 to 2020. Findings: A key finding was that companies with lower managerial prowess strategically leverage R&D intensity to signal their value to the market and accrue reputational currency. The research unearths a significant positive relationship between managerial ability, IPRs and R&D investment. In environments characterized by strong managerial acumen and robust IPR safeguards, firms exhibit a heightened propensity to allocate resources to R&D endeavours. This underscores the role of intellectual leadership and legal protections in shaping R&D strategies within the pharmaceutical domain. Incorporating firm life stages as a moderating factor reveals that firm maturity fundamentally influences the interplay between managerial ability, IPRs and R&D expenditure. Originality/value: These findings' implications resonate profoundly within policy-making circles and pharmaceutical firms' day-to-day operational strategies, underscoring the pivotal role of intellectual capital and legal safeguards in shaping the future of innovation in the Asia-Pacific pharmaceutical sector. [ABSTRACT FROM AUTHOR]

Industrial organization economists and financial analysts often employ firm level Tobin's q, typically interpreted as the firm's market value divided by its book value. The measurements, applications, and interpretations vary considerably enough to warrant the questioning of its usefulness. This paper develops a conceptual framework for Tobin's q and, in doing so, offers some useful interpretations that hopefully clear up some of the past misunderstandings regarding this useful metric. [ABSTRACT FROM AUTHOR]

The occurrence of squad rotation in football and its effect on team performance in terms of points have not been comprehensively studied in football performance analysis literature. This study deploys a data-driven approach to examine the occurrence of squad rotation across English, French, Italian and Spanish leagues over multiple seasons. It aims to establish the relationship observed between average squad rotations in starting lineups and end-of-season points. A total of 16,720 matches dating from the 2010/11 to 2021/22 seasons were analysed for average rotations in each team involved and the respective team's end of season points, alongside contextual information such as injury and logarithmic market value. A linear mixed-effects model was used to study this relationship, with each variable as well as interaction of variables being analysed for fixed effects. The results show that a significant relationship exists between team success, average rotation of the team per match and market value of the team, while no significant effects are found for injuries. The results describe how universally deploying squad rotation may not yield higher points over a season, but also shows how the effect of rotations on team success keep increasing as the market value of teams increases. [ABSTRACT FROM AUTHOR]

Rice quality, which is intricately connected to market value and human nutrition, is sensitive to weather conditions. However, the relative importance of the different climatic factors is poorly understood, and the impact of climate change on rice quality has been little studied on a large scale. Here, using more than 35 years of rice quality data, we present the first effort to determine the key climate variables driving rice quality in China and Japan. Results show a significant decline in high quality rice rate (HRR, an indicator of rice quality), mainly driven by warm nighttime temperatures when they exceed a critical threshold estimated at 18°C and 12°C in China and Japan, respectively. Climate projections suggest a continuing decreasing trend in HRR under moderate and high emission scenarios by 2100. These findings emphasize the importance of breeding new heat tolerant cultivars to maintain stable rice quality in the future. Plain Language Summary: Food security is not only related to yield, but also to quality, which is closely related to human nutrition and market value. Although crop quality is generally controlled by breed genes, climate change also has an important impact. Unfortunately, existing studies on the impact of climate change on rice quality mostly performed at sites scale, the knowledge on a large scale such as the global or national scale is still limited. This is partly related to the incompleteness of relevant data, and also it is related to the current focus primarily on yield and neglect of quality. Our findings highlight that food security should consider both yield and quality aspects. Key Points: We find a significant decline in rice quality in both China and JapanNighttime temperature is the key driver of rice quality declineClimate projections suggest a continuing decreasing trend in rice quality in future [ABSTRACT FROM AUTHOR]

Browning reactions caused by oxidative stress occurring during postharvest procedures significantly compromise the quality of ready‐to‐eat (RTE) vegetables, negatively affecting their market value. Polyphenol oxidase (PPO) and peroxidase (POD) are two major enzymes involved in this phenomenon, as they oxidize phenolic compounds to quinones, which in turn polymerize to brown pigments. Recently, there has been an increasing interest in developing antibrowning treatments using food by‐products. Herein, the efficiency of a kiwi peel extract in reducing enzymatic browning of minimally processed lettuce (Lactuca sativa) has been investigated. PPO and POD activities showed an opposite spatial distribution within the leaf, with a higher POD activity in the midvein (MV) and in the inner lamina tissues, and a prevalence of PPO activity in the mesophyll. Considering that MV lignified tissues are those mainly affected by browning, the temporal trend of POD activity over a 20‐day storage period at 4°C was investigated. Data showed that treatment with a kiwi peel extract hinders both the increasing trend of POD activity and browning development compared to control leaves. These results could be potentially useful for the industry as they confirm that natural extracts, such as kiwi peel extract, can be valuable for extending the shelf‐life of RTE products. [ABSTRACT FROM AUTHOR]

Patient involvement is crucial in healthcare, a factor increasingly recognised by life sciences companies and research institutes. This article presents a case study on Servier, a life sciences company that founded a patient expert board, ahead of launching a new research and development (R&D) institute. The aim was to foster a patient-centric culture within the company. The case study explores key developments in patient and public involvement, emphasising a shift from paternalistic to patient-centred approaches, noting few available case studies on patient board collaborations in life sciences. It outlines the evolution of the board, its impact, and practical lessons learned, with related recommendations. The patient board resulted from a three-way collaboration between the company, Patvocates (a patient consultancy), and patient experts recruited. The patient consultancy played a crucial role in project management, governance, and facilitating relationships. The case study provides the context, timeframe, foundations laid, engagement of patient experts, and foundational values, including: co-creation, fair market value remuneration, voluntary participation, and patient-centric meeting protocol. Eighteen patient experts, representing ten disease areas and ten European countries, joined the board and helped prioritise and co-create projects. Ideas for activities were sourced from brainstorming sessions and an in-company challenge. The collaboration yielded five core ideas, each forming a working group. The study describes the groups and their outputs: a patient advisory council, an interactive gallery of patient experience in R&D, patient engagement and entrepreneurship in life sciences, creating patient-focused decentralised trials (DCTs), and staff training on patient engagement. The article emphasises how the organic evolution of the collaboration led to significant insights. Hurdles faced by the company included: upstream planning, cross-company buy-in, compliance, and internal resource allocation. Recommendations for the wider community included: identifying and contracting patient partners; clarifying roles; managing expectations; building trust; logistics; and sustainability. This case study presents a practical, positive example of patient engagement within a life sciences company, offering insights into the establishing, running, and the impact of collaborating with a patient expert board. Lessons learned and recommendations may serve as a model for other companies seeking to engage with patients and evolve towards a more patient-centric approach in their strategies. Plain English summary: Patient involvement in healthcare is crucial for developing patient-centred approaches, and life sciences companies and research institutes are increasingly recognising this. Servier, a life sciences company, established a patient expert board to support a patient-centric culture within the organisation, at the time of creating a new research and development (R&D) institute. This article presents a case study on the patient board and its impact. The patient board resulted from a three-way collaboration between the company, Patvocates (a patient consultancy), and patient experts recruited. The patient consultancy played a key role in guiding the project. The study provides the context, founding values, engagement of patient experts, and methodology used to establish the board. Eighteen patient experts, representing ten disease areas and ten European countries, joined and helped prioritise and co-create projects. From the collaboration, five core ideas emerged. The case study highlights that the organic evolution of the collaboration provided significant insights. Hurdles faced included cross-company buy-in, compliance, time, and resources. The study also offers a set of recommendations for the wider community, including identifying and contracting patient partners, clarifying roles, managing expectations, building trust, logistics, and sustainability. This case study presents a positive, constructive model of patient engagement within a life sciences company, offering insights into establishing and running a patient expert board and its impact on the company culture and R&D practices. The lessons learned and recommendations may serve as a model for other companies wanting to engage with patients and develop more patient-centric approach in their strategies. [ABSTRACT FROM AUTHOR]

This study proposes a novel distributed energy trading market model with a value distribution mechanism to optimize the allocation and transactions of distributed energy resources (DERs). The framework incorporates a direct load management approach via an electricity aggregator agent, simplifying market processes and reducing transaction costs. A Nash bargaining model is employed to design a fair and efficient value distribution mechanism, promoting equitable benefit allocation among participants. The model integrates stochastic programming to account for uncertainties in real-time load and DER output, enhancing its robustness and applicability in real-world scenarios. The proposed mechanism quantifies each DER's contribution using a market value contribution rate, serving as a foundation for the Nash bargaining model. This approach ensures individual rationality for both the aggregator and DERs while maximizing overall system benefits. Case studies validate the model's effectiveness, demonstrating improvements in resource utilization and fair benefit allocation. This research contributes to the advancement of distributed energy markets, offering valuable insights for designing efficient and equitable market structures, ultimately promoting grid stability, renewable energy adoption, and the development of more sustainable and flexible energy systems. [ABSTRACT FROM AUTHOR]

This research is aimed at addressing the significant challenges of detecting and classifying green coffee beans, with a particular focus on identifying defective coffee beans—an important task for improving coffee quality and market value. The main challenge is to accurately detect small and visually subtle defects in coffee beans in real‐world production environments with a large number of beans, varying lighting conditions, and complex backgrounds. To address these challenges, we propose a YOLOv8n‐based object detection model that employs several innovative strategies aimed at improving detection performance and robustness. Our research includes the introduction of WIoUv3 and the development of the Atn‐C3Ghost module, which integrates the ECA mechanism with the C3Ghost module to refine the feature extraction and improve the accuracy of the model. In order to validate the effectiveness of our proposed method, we conducted comprehensive comparison and ablation experiments. In addition, we compared the C3Ghost structure in combination with various attentional mechanisms to determine their impact on the model's detection ability. We also conducted ablation studies to evaluate the respective contributions of WIoUv3, ECA, and C3Ghost to overall model performance. The experimental results show that the YOLOv8n‐based model enhanced with WIoUv3, ECA, and C3Ghost achieves an accuracy of 99.0% in detecting green coffee beans, which is significantly better than other YOLO models. This study not only provides a practical solution for green coffee bean detection but also provides a valuable framework for addressing similar challenges in other small object detection tasks. [ABSTRACT FROM AUTHOR]

Patent strategies are an effective means of mitigating the negative effects of patent thickets on corporate market value. In reality, however, inappropriate patent strategies tend to exacerbate the negative effects of patent thickets. In this study, we used 2009–2019 panel data of 419 Chinese electronic equipment manufacturing companies, applied a panel threshold model, and analysed the influence mechanism. We empirically investigated the boundary dividing patent application, patent withdrawal, patent portfolio, and patent maintenance strategies from 'angel' to 'devil' and the influence mechanism of patent thickets on corporate market value. This study arrives at several conclusions. (i) Patent thickets exert a negative effect on corporate market value. (ii) Patent application and withdrawal strategies play a fully mediating role in the negative effect of patent thickets on corporate market value, while patent portfolio and maintenance strategies play a partially mediating role. (iii) Patent application, withdrawal, and maintenance strategies exhibit a double threshold effect, while patent portfolio plays a single threshold role. This study enriches the research on patent thickets. [ABSTRACT FROM AUTHOR]

This paper discusses the work of two twentieth‐century liberal economists, Friedrich Hayek and James Buchanan, who have made lasting contributions to our understanding of the role of the market in a free society. I argue that they offer significantly different but complementary visions of the value of the market as a system of individual freedom. Hayek's vision is of the price system as a marvel of spontaneous order which solves a fundamental economic problem – that of making efficient use of a totality of knowledge that is divided between individuals. Buchanan's vision is of the market as a space in which individuals are free to make voluntary exchanges. In his words, 'this is all that there is to it': the market is not a solution to any collective problem. These visions have a common blind spot. Both writers recognise the need for programmes of social insurance and consider how they should structured so as to be as compatible as possible with the workings of a market economy and a liberal democracy. But, I argue, neither sees the full importance of social insurance in a justification of the market system. [ABSTRACT FROM AUTHOR]

Purpose: This paper studies diversification and value in the investment portfolios of (non-listed) Real Estate Investment Funds (REIFs) exploring how the value of diversification is captured by the market and by investors (beyond reported valuations). Design/methodology/approach: We apply the Herfindahl-Hirschman Index (HHI) to study the level of concentration versus diversification in the investment portfolios of REIFs (both in terms of segment and geographical diversification). We use a dataset from INREV with data from 62 investment portfolios, with an average of 86 REIFs per portfolio for the period of 2008–2020 (to study segment diversification). We use a second dataset from INREV with data from 30 investment portfolios with an average of 79 REIFs per portfolio for the period of 2005–2020 (to study geographical diversification). We employ a cluster analysis approach to identify common features among the investment funds. Findings: We conclude that (segment diversified) portfolios with higher degrees of leverage exhibit higher income yields, albeit diversification is captured indirectly through asset choices – more diversified portfolios tend to exhibit a stronger risk and return relationship. Also, geographical diversification creates value (more significantly by for the correct combination of countries carefully choosing what different geographies to group in the diversified portfolio). Research limitations/implications: One limitation of our study is that our portfolios are funds of funds, since the available data could not reach the asset detail, but we believe this does not compromise our results. Practical implications: Diversification leads to higher risk-adjusted returns which suggests that properties may be undervalued (market value) in the framework of the Gordon Model, contrary to expectations (regarding investment value). Originality/value: Investors capture the value of diversification differently, suggesting a gap between market value and investment value that can be explored. [ABSTRACT FROM AUTHOR]

By considering market demand information, the objective of this study is to measure the bullwhip effect in a two-stage supply chain with one supplier and multiple retailers. First, a model is detailed for measuring the bullwhip effect in which multiple retailers exhibit AR(1) demand processes and the order-up-to inventory level is calculated using market demand information. We find results that the bullwhip effect increases with the market share and lead time and decreases with the contemporaneous correlation and the number of retailers. Second, by comparing the bullwhip effect with or without market information, our model can better control and reduce the bullwhip effect. Third, we calculate the value of market information with the newsvendor model and discover that the value of market information increases with the number of retailers and the contemporaneous correlation and decreases with the market share. In addition, numerical analyses are given to verify the previous results. Moreover, some suggestions are presented to help managers make decisions on the bullwhip effect. [ABSTRACT FROM AUTHOR]

Introduction: The marine microalga Isochrysis galbana is prolific producer of fucoxanthin, which is a xanthophyll carotenoid with substantial global market value boasting extensive applications in the food, nutraceutical, pharmaceutical, and cosmetic industries. This study presented a novel integrated experimental approach coupled with machine learning (ML) models to predict the fucoxanthin content in I. galbana by altering the type and concentration of phytohormone supplementation, thus overcoming the multiple methodological limitations of conventional fucoxanthin quantification. Methods: A novel integrated experimental approach was developed, analyzing the effect of varying phytohormone types and concentrations on fucoxanthin production in I. galbana. Morphological analysis was conducted to assess changes in microalgal structure, while growth rate and fucoxanthin yield correlations were explored using statistical analysis and machine learning models. Several ML models were employed to predict fucoxanthin content, with and without hormone descriptors as variables. Results: The findings revealed that the Random Forest (RF) model was highly significant with a high R² of 0.809 and RMSE of 0.776 when hormone descriptors were excluded, and the inclusion of hormone descriptors further improved prediction accuracy to R² of 0.839, making it a useful tool for predicting the fucoxanthin yield. The model that fitted the experimental data indicated methyl jasmonate (0.2 mg/L) as an effective phytohormone. The combined experimental and ML approach demonstrated rapid, reliable, and cost-efficient prediction of fucoxanthin yield. Discussion: This study highlights the potential of machine learning models, particularly Random Forest, to optimize parameters influencing microalgal growth and fucoxanthin production. This approach offers a more efficient alternative to conventional methods, providing valuable insights into improving fucoxanthin production in microalgal cultivation. The findings suggest that leveraging diverse ML models can enhance the predictability and efficiency of fucoxanthin production, making it a promising tool for industrial applications. [ABSTRACT FROM AUTHOR]

Recurring use of chemical fertilizers (CFs) in agriculture has resulted the remarkable improvement in crop productivity but their ruinous effects on environment have made a serious issue. Biological entities (e.g., several microorganisms) showing fertilizer‐like activities have gained attention in this regard. Several soil resident microorganisms interact strongly with neighboring plants and promote the growth and development of those plants through various means. In exchange of this, microbes utilize different compounds released from plant roots for their own nutrition. This mutualistic mode of interrelation predominantly relies on the transmission of signals from microbes to plants and vice versa. However, climatic factors (e.g., CO2 level, temperature, and water availability) are also important for this association. These bacterial strains are literally known as plant growth promoting rhizobacteria (PGPR) which facilitate plant growth through nitrogen fixation, mineral solubilization, phytostimulation, stress resistance, etc. Responding to the external environmental stimuli, they often modulate the expression of genes responsible for the transport of nutrients. Reduction of the use of CFs through the application of PGPR strains in the cultivation of some economically important plants has been reported by several authors. Significant yield improvement compared to the control groups was found in all experimental studies. Commercial development of the PGPR inoculants with remarkable biostimulating activities and their successive application should be expanded through collaborative association with different sectors after the removal of existing lacunae. Reading more than 100 articles on various aspects of rhizobacteria, the plan of writing this article has been executed. In this review, we have discussed about the colonization and potency of PGPR strains and how their well‐planned application in agriculture could evidently reinforce the global economy. The main structure of this text is designed as an outline from the development of interrelation between plants and PGPR to the commercialization of PGPR based on their potential role in the field of agriculture. [ABSTRACT FROM AUTHOR]

The relationship between a company's Environment, Social and Governance (ESG) scores and market value dynamics has been the focus of extensive research. Our study aimed to provide insights into this relationship and its implications for Chinese investors. We used a general Cross-lagged panel model to analyze data from 652 Chinese-listed companies from 2013 to 2019. Our findings indicate that ESG scores have a long-term impact on market value, with a consistently positive correlation between the two. We also discovered that Chinese investors consider ESG factors when evaluating a company's financial health. Companies that prioritize ESG factors are more likely to attract investment. Moreover, the diffusion of ESG information happens slowly, and past ESG performance influences future ESG performance. Thus, maintaining good ESG performance is crucial for long-term sustainability and success. In addition, our analysis reveals significant insights into the interplay between ESG metrics and mandatory disclosure regulations. Specifically, we find that the interaction between average ESG score and mandatory disclosure significantly impacts firm value, suggesting a nuanced relationship between ESG performance and market valuation in the context of regulatory requirements. Overall, our study highlights the importance of considering ESG factors when evaluating financial health and making investment decisions, providing valuable insights for firms and investors alike. [ABSTRACT FROM AUTHOR]

Stablecoins have gained prominence as an effective means to mitigate the inherent volatility in the cryptocurrency markets by providing a stable and reliable medium for value preservation and transfer. This research paper investigates the attributes that render stablecoins a preferable vehicle for value retention and transaction within these markets. By employing a quantitative methodology, this study collected data through surveys, with a sample size of 714 individuals chosen via purposive sampling techniques. To analyze the data, both descriptive and inferential statistical methods were applied. The demographic profiles of the sample were summarized using descriptive statistics such as frequencies and percentages. For examining the relationships between demographic factors (such as gender, age, education, income, and place of residence) and the perceived efficacy of stablecoins, inferential techniques including Chi-square tests and logistic regression were utilized. The logistic regression analysis specifically assessed how these variables influenced the likelihood of participants favoring stablecoins for financial transactions. The results indicate that the preference for stablecoins as a means of holding or transferring value within the cryptocurrency domain in Thailand varies significantly across different demographic groups, specifically influenced by factors such as gender, education, income, and place of residence. These outcomes provide insightful implications concerning the demographic influences on the adoption and utilization of stablecoins in financial activities. [ABSTRACT FROM AUTHOR]

The concept of fair value, defined by the valuation of assets and liabilities at their current market worth, remains central to the International Financial Reporting Standards (IFRS) and has persisted despite critiques intensified by the 2008 financial crisis. This valuation method continues to be prevalent under both IFRS and the US Generally Accepted Accounting Principles (GAAP). The adoption of IFRS has notably enhanced the role of accounting in information analysis, vital for owners who prioritize both secure accounting practices and reliable data for strategic management decisions. Real estate, a significant business asset, has long been a focal point in accounting discussions, prompting extensive research into the applicability and effectiveness of various accounting standards. These investigations assess the adaptability of standards based on property type, utility, and valuation techniques. However, the challenge of accurately determining the fair value of real estate remains unresolved, signifying its importance not only in the corporate manufacturing realm but also among development companies striving to manage property values efficiently. This study addresses the challenge of accurately determining the fair market value of real estate in Kazakhstan, leveraging a multi-methodological approach that encompasses statistical models, regression analysis, data visualization, neural networks, and particularly, an Adaptive Neuro-Fuzzy Inference System (ANFIS). The integration of these diverse methodologies not only enhances the robustness of real estate valuation but also introduces new insights into effective asset management. The findings suggest that ANFIS provides superior precision in real estate pricing, demonstrating its potential as a valuable tool for strategic management and investment decision-making. [ABSTRACT FROM AUTHOR]

The high global market value of fresh mushrooms implies high importance of spent mushroom substrate (SMS) as a by-product that poses environmental challenges, if not properly treated. Reported studies demonstrate the positive effects of SMS on earthworm growth and reproduction, particularly when combined with other substrates such as cow dung (CD). This study utilized SMS and CD as substrates in varying ratios. A total of 375 young non-clitellated Eisenia fetida were randomly assigned to plastic containers, ensuring similar average individual worm weight, and maintained at 50% to 60% moisture. Weekly observations were made on earthworm average weight, cocoon production, and hatchling count. The growth and reproduction of earthworms differed significantly among treatments, with Treatment 3 (T3) (50:50 SMS and CD) showing the highest growth and Treatment 5 (T5) (0:100 SMS and CD) the lowest. Changes in pH, EC, total Kjeldahl nitrogen (TKN), total organic carbon (TOC), C/N ratio, and total available phosphorus (TAP) were observed over the experimental period, indicating dynamic nutrient dynamics within the substrates. The exchangeable potassium decreased with increasing proportions of CD, while the exchangeable sodium content showed variation across treatments. The observed variations can be attributed to differences in initial substrate composition and microbial activity during vermicomposting. [ABSTRACT FROM AUTHOR]

Wuyi rock teas of different storage duration have different flavor, bioactivity, and market value, Shuixian is a main variety of Wuyi rock tea. In this study, metabolites composition of Shuixian with different storage years were analyzed using Ultrahigh Performance Liquid Chromatography‐Quadrupole‐Time of Flight‐Mass Spectrometry (UPLC‐Q‐TOF‐MS). A total of 1201 compounds were identified, and 104 differential compounds (VIP > 1.5) were determined. Furthermore, the results showed that five compounds exhibited a positive correlation with storage time, such as alpha‐terpineol formate, carnosol, 2‐phenethyl‐D‐glucopyranoside, Ellagic acid, and D‐ribosyl nicotinic acid, while 24 compounds showed a negative correlation, such as Ethyl linoleate, leucocyanidin, cis‐3‐hexenyl acetate. In total, 29 signature compounds significantly correlated with storage time. These findings shed light on the patterns and mechanisms of changes in the composition of Wuyi rock tea during storage and provide a theoretical foundation for distinguishing the storage years. [ABSTRACT FROM AUTHOR]

The post-harvest process is important to increasing the market value of limes and requires focus. During this process, limes are graded and categorized based on size, weight, and volume. Therefore, identifying efficient means of estimating these properties is very important and remains an open research area. This study applies the concept of computer vision based on traditional machine learning algorithms (partial least square regression (PLS), epsilon-support vector regression (ε-SVR), decision tree (DT), random forest (RF), adaptive boosting (AB), gradient boosting (GB), Bagging meta-estimator (BME), and extremely randomized trees (ERTs)) and pre-trained deep learning (InceptionV3, MoblieNetV2, ResNet50, and VGG-16) for estimating the weight and volume of limes. Our findings showed that the BME and ResNet50 could yield the highest performance for estimating the weight and volume of limes. The BME produced R test 2 values of 0.954 and 0.882 for weight and volume, respectively, while the R test 2 values of ResNet50 models were between 0.951 and 0.957 for weight and volume, respectively. This study concluded that computer vision based on both traditional machine learning and deep learning could be used to estimate the weight and volume of limes. The approach proposed in this study can be adopted for applications related to computer vision in the post-harvest process. [ABSTRACT FROM AUTHOR]

Demand and market value for pennywort largely depend on the quality of the leaves, which can be affected by various ambient environment or fertigation variables during cultivation. Although early detection of defects in pennywort leaves would enable growers to take quick action, conventional manual detection is laborious and time consuming as well as subjective. Therefore, the objective of this study was to develop an automatic leaf defect detection algorithm for pennywort plants grown under controlled environment conditions, using machine vision and deep learning techniques. Leaf images were captured from pennywort plants grown in an ebb-and-flow hydroponic system under fluorescent light conditions in a controlled plant factory environment. Physically or biologically damaged leaves (e.g., curled, creased, discolored, misshapen, or brown spotted) were classified as defective leaves. Images were annotated using an online tool, and Mask R-CNN models were implemented with the integrated attention mechanisms, convolutional block attention module (CBAM) and coordinate attention (CA) and compared for improved image feature extraction. Transfer learning was employed to train the model with a smaller dataset, effectively reducing processing time. The improved models demonstrated significant advancements in accuracy and precision, with the CA-augmented model achieving the highest metrics, including a mean average precision (mAP) of 0.931 and an accuracy of 0.937. These enhancements enabled more precise localization and classification of leaf defects, outperforming the baseline Mask R-CNN model in complex visual recognition tasks. The final model was robust, effectively distinguishing defective leaves in challenging scenarios, making it highly suitable for applications in precision agriculture. Future research can build on this modeling framework, exploring additional variables to identify specific leaf abnormalities at earlier growth stages, which is crucial for production quality assurance. [ABSTRACT FROM AUTHOR]

D-glucaric acid is an important organic acid with numerous applications in therapy, food, and materials, contributing significantly to its substantial market value. The biosynthesis of D-glucaric acid (GA) from renewable sources such as glucose has garnered significant attention due to its potential for sustainable and cost-effective production. This review summarizes the current understanding of the cell factories for GA production in different chassis strains, from static to dynamic control strategies for regulating their metabolic networks. We highlight recent advances in the optimization of D-glucaric acid biosynthesis, including metabolic dynamic control, alternative feedstocks, metabolic compartments, and so on. Additionally, we compare the differences between different chassis strains and discuss the challenges that each chassis strain must overcome to achieve highly efficient GA productions. In this review, the processes of engineering a desirable cell factory for highly efficient GA production are just like an epitome of metabolic engineering of strains for chemical biosynthesis, inferring general trends for industrial chassis strain developments. [ABSTRACT FROM AUTHOR]

Large multinational IT companies are always trying to produce competitive innovation at a faster pace. Even giant IT corporations, however, are unable to produce sustainable technological innovation alone. Literature offers many alternatives to obtain external technologies, but there are few studies about acquisition strategy to obtain technology innovation. A case study was carried out in a multinational IT company, EMC, which has applied mainly the acquisition strategy to develop innovations and increase its competitive position. The company has acquired many technology-based IT companies in the U.S. and abroad, and this strategy showed effectiveness in value creation, leading them to increase their income, value and market capitalisation during this period. An important finding here is that, by combining acquisitions with increasing investments in R&D, EMC was able to leverage innovations and strengthen its competitiveness and global market presence. The EMC experience has also allowed proposing a graphical tool, showing which are the key management processes that might be considered to get successful in using the acquisition strategy to create values for the business through innovation. Associated with this tool, this study also presents a step-by-step procedure to guide practitioners on how to manage the strategy of acquisition to access innovation. [ABSTRACT FROM AUTHOR]

We examine the short-term market impact of the beginning of the military conflict between Russia and Ukraine (24 February 2022) on the world's largest insurance firms. Using an event study for the 100 largest listed insurers globally, we observe that the unexpected loss effect seems to prevail over the long-term growth effect, leading to a decrease of insurance firm's equity market values. Furthermore, our results show a higher negative stock market reaction for foreign insurers with a high exposure to Russian/Ukrainian markets. These results also confirm the existence of a 'proximity penalty' for firms in the vicinity of the war zone. Finally, our results provide insight into which insurer-specific characteristics emerge as value drivers. Larger, well-capitalised, profitable and life or diversified insurance firms with less institutional ownership have superior stock market returns and are more able to handle the losses resulting from the war. [ABSTRACT FROM AUTHOR]

Purpose: Press reports have indicated that firms frequently underprice restricted stock and employee stock options. I test for underpricing of stock and options. Design/methodology/approach: I examined a sample of 5,333 private firm stock and option issuances between 1985 and 2017. I tested for underpricing using two approaches: assuming investors have no special market-timing ability and assuming instead they have perfect market-timing ability. Findings: I find evidence of widespread stock and option underpricing by private firms before they go public reflecting large discounts that exceed reasonable compensation for lack of marketability. Unreported underpricing is more frequent in the last pre-IPO private equity transactions that offer the last opportunity to give such discounts before the stock is publicly traded, but the discounts are greater in the earlier pre-IPO transactions where unreported discounts are presumably tougher for the SEC to detect. Underpricing is still detected even when the actual DLOMs are tested against a benchmark that assumes investors have perfect market-timing ability. Research limitations/implications: Firms frequently underprice restricted stock and employee stock options. Firms tend to underprice stock options more frequently than restricted stock, but restricted stock tends to be priced at deeper discounts when recipients are assumed not to have any special market-timing ability. Practical implications: Private firms issue restricted stock and options as incentive compensation. Lowballing the valuation transfers wealth from outside stockholders to employees/insiders. Wealth transfers take place through the issuance of equity claims to employees/insiders before firms go public. I found that more than a quarter of the DLOMs exceed the theoretical maximum by, on average, between 16% (median) and 20% (mean). This finding raises two questions worthy of investigation. First, to what extent do the frequency and magnitude of DLOMs above the theoretical maximum depend on whether a board of directors obtains an independent appraisal of a stock's fair market value? Second, if DLOMs above the theoretical maximum are observed even when the stock is independently appraised, how do appraisers justify such large DLOMs? Social implications: The wealth transfers that take place through the issuance of equity claims to employees/insiders before firms go public benefit employees/insiders at the expense of outside shareholders. Originality/value: My paper is the first to furnish evidence of widespread stock and option underpricing by private firms before they go public; demonstrate that the unreported underpricing is more frequent in the last pre-IPO private equity transactions that offer the last opportunity to give such discounts before the stock is publicly traded and show that the discounts are greater in the earlier pre-IPO transactions where unreported discounts are presumably tougher for the SEC to detect. [ABSTRACT FROM AUTHOR]

[Purpose] The purpose of this study is to discuss, based on international as well as national laws and practices, various issues and potential solutions surrounding the growing problem of money laundering practices using cryptocurrency transactions. [Methodology] A balanced combination of theoretical and empirical methods has been used in the course of research; in particular, the method of comparative legal research has been employed extensively throughout the text of article. The theoretical component of this research paper includes commentaries by Ukrainian, German, other European as well as American researchers in this field. Their works are cited appropriately. The subject scope of the paper covers modern phenomenon of money laundering based on cryptocurrency transactions. [Findings] This paper extensively discusses international and national legal frameworks for identifying and stopping as well as preventing various money laundering schemes and techniques based on cryptocurrency transactions and blockchain technology in general. It has been established that with the global cryptocurrency market valued at roughly $1 trillion, its attractiveness to money launderers endangers economies and financial systems of numerous world jurisdictions. Based on theoretical observations and relevant analyses of legal cases, authors' conclusions on how to fight this latent type of criminality have been presented. [Practical Implications] The research is deemed to be of value to national regulators, law enforcement agents and legal commentators, who think, write and act with the goal of fighting new money laundering patterns. It can serve as part of a broader international roadmap on how to identify suspicious money laundering schemes using various cryptocurrency transactions and also to impose effective sanctions on criminal actors behind those schemes. [Originality] The paper originality relies on its comprehensive and balanced combination of economic and legal analyses of the issues presented and potential solutions to them. It also incorporates both sound theoretical research and in-depth coverage of law enforcement actions, as well as legal cases against crypto money launderers. [ABSTRACT FROM AUTHOR]

The feed index is a weighted sum of the number of reactions (i.e. reading, comments, retweets, likes and dislikes, and so on.) that the content engine actively recommends and distributes to the users. It provides valuable information from big data on the Internet and high marketing value to Destination Marketing Organization as the content can be customized. A large-scale empirical study on the impact of the feed index on tourist arrival forecasting accuracy has been conducted, with a new approach proposed to incorporate the feed index into the tourist arrival forecasting model with higher forecasting accuracy. Firstly, the empirical results suggest that the feed index for different keywords reflects varying tourist preferences and has different impacts on tourist arrival movements, with variant lead-lag relationships. Secondly, the study shows that keywords need to be carefully selected based on theoretical analysis plus new methods such as entropy analysis. Therefore, it is proposed that entropy is employed to select the keywords and time lags, thus helping improve forecasting accuracy. [ABSTRACT FROM AUTHOR]

Copyright of Advances in New & Renewable Energy is the property of Editorial Office of Advances in New & Renewable Energy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We study how the misvaluation of banks affects their loan supply by considering proprietary data on 83 banks from 11 euro-area countries from 2010Q1 to 2019Q4. We measure bank market value by the Tobin's Q and identify the impact of nonfundamental changes in bank market value by saturating our specifications with observable bank fundamentals and analyst forecasts on future bank performance as well as several fixed effects. We show that nonfundamental rises in market value lead a bank to increase its loan supply to firms and households, even when the bank's capital structure constraint is not binding. Our findings are consistent with a mechanism in which bank managers cater to the misperceptions of stock market investors. [ABSTRACT FROM AUTHOR]

Our article seeks to investigate the impact of ESG disclosure in its three dimensions, both collectively and individually, on the market value of Jordanian-listed companies from 2012 to 2019. Using a sample of 173 companies listed in ASE, 1,384 observations were collected. The findings indicate that environmental and social disclosure maximize companies' market value, and the ESG disclosure collectively has positively affected the market value. At the same time, the results do not show any important role in governance. This indicates that companies pay close attention to various stakeholders, particularly external stakeholders, and wish to increase trust and transparency by disclosing their ESG performance. As a result, companies' confidence in the capital markets is reinforced, and improved disclosure practices positively affect market value. This study adds an empirical contribution to the literature by investigating the influence of sustainability reporting on companies' market value in the context of emerging economic countries. [ABSTRACT FROM AUTHOR]

This study examines the influence of risk disclosure (RD) in the annual reports on Firm Value (FV) in the UK context. Furthermore, it addresses the moderating role of the analyst information environment in shaping this relation. Our study distinguishes between favourable and unfavourable information and examines whether the different nature of risk information could affect the FV differently. Our study contributes to the existing literature by providing empirical evidence on the value relevance of the narrative risk information. In particular, using a sample of UK listed firms, we find a positive relation between risk information and FV. We also contribute to the dilemma of risk disclosure measurement by using four different RD proxies. Our study has important implications for academics, standard setters, investors and managers. [ABSTRACT FROM AUTHOR]

Traditional asset management strategy has emphasized building barriers to entry or closely guarding unique assets to maintain a firm's comparative advantage. A new "inverted firm" paradigm, however, has emerged. Under this strategy, firms share data seeking to become platforms by opening digital services to third parties and capturing part of their external surplus. This contrasts with a "pipeline" strategy where the firm itself creates value. This paper quantitatively estimates the effect of adopting an inverted firm strategy through the lens of application programming interfaces (APIs), a key enabling technology. Using both public data and those of a private API development firm, we document rapid growth of the API network and connecting apps since 2005. We then perform difference-in-difference and synthetic control analyses and find that public firms adopting public APIs grew an additional 38.7% over 16 years relative to similar nonadopters. We find no significant effect from the use of APIs purely for internal productivity: the pipeline strategy. Within the subset of firms that adopt public APIs, those that attract more third-party complementors and those that become more central to the network see faster growth. Using variation in network centrality caused by API degradation, an instrumental variables analysis confirms a causal role for APIs in firm market value. Finally, we document an important downside of public APIs: increased risk of data breach. Overall, these facts lead us to conclude that APIs have a large and positive impact on economic growth and do so primarily by enabling an inverted firm strategy. This paper was accepted by D. J. Wu, information systems. Funding: This work was partially supported by Mulesoft and Apigee Corporation. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4968. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Finance Letters / Maliye Finans Yazıları Dergisi is the property of Maliye Finans Yazilari Yayimcilik Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Following provincial quality awards announcements, this study explores whether winners' financial performance is significantly impacted by the quality award, using OLS and PSM-DID techniques. A placebo parallel trend model is adopted to re-estimate dynamic firms financial performance and test the robustness of the findings. The results show that the quality award significantly impacts manufacturing firms' financial performance. The regional quality award has significant positive benefits for first-time winners and winning firms located in the Delta region of China. There is a significant positive relationship between the firms' financial performance and the achievement of quality awards in the long run. The findings expand the research to the relationship between quality awards and firm market value in various institutional contexts. The positive association between a quality award and financial performance confirms the implication for policymakers and the government that a reasonable quality award reduces the quality problem, increases firm value, and supports the awards mechanism in China. [ABSTRACT FROM AUTHOR]

In the absence of comparative real estate data in the market segment of the property to be estimated, the appraiser may resort to income capitalization to estimate the market value. Often, however, the choice of which rate to apply is affected by subjective and arbitrary assessments. The estimation result can therefore be inaccurate and rather unclear. However, the Remote Segments Approach (RSA), through appropriate adjustments on the original values, prices, and incomes detected in the remote segments, makes it possible to arrive at an appraisal result consistent with estimative logic and real estate valuation standards. The proposed application illustrates the estimation of the market value of a specialized fruit orchard of avocado, which is to be considered new in relation to other fruit species already present in the reference area. The adjustments required by the RSA are solved with the General Appraisal System (GAS), defining the difference matrix based on relevant characters common to all segments considered. The application is carried out by comparing the segment in which the orchard being estimated falls (subject) with other remote market segments in which prices and incomes constituted by other tree crops are collected. The market value of the subject is derived by making adjustments to the prices and incomes observed in the remote segments of comparison with a comparison function constructed through relevant characters common to the segments considered. The comparison function makes it possible to arrive at the determination of the capitalization rate to be used in estimating the value of the fruit orchard by income approach. While it is based on the comparison of segments, the approach followed allows for a value judgment consistent with the estimation comparison and capable of providing a solution less conditioned by the appraiser's expertise in the presence of particularly pronounced limiting conditions. [ABSTRACT FROM AUTHOR]