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This study unravels an attempt to investigate the dynamic connectedness of agri-commodity (wheat) of Russia with 10 financial markets of wheat importing counties during the Russia–Ukraine invasion.

This study took the daily prices of Wheat FOB Black Sea Index (Russia) along with stock indices of 10 major wheat-importing nations of Russia and Ukraine. The time frame for this study ranges from February 24, 2022 to July 31, 2022. This time frame was selected since it fully examines all of the effects of the crisis. The conditional correlations and volatility spillovers of these indices are predicted using the DCC-GARCH model, Diebold and Yilmaz (2012) and Baruník and Křehlík (2018) models.

It is found that there is dynamic linkage of agri-commodity of with stock markets of Iraq, Pakistan and Tanzania in short run while stock markets of Egypt, Turkey, Bangladesh, Pakistan, Brazil and Iraq are spilled by agri-commodity in long run. In addition, it documents that there is large spillover in short run than medium and long run comparatively. This signifies that investors have more diversification opportunity in short run then long run contemplating to invest in these markets.

To the best of the authors’ understanding this is the first study to undertake the dynamic linkage of agri-commodity (wheat) of Russia with financial market of select importing counties during the Russia–Ukraine invasion.

The purpose of the study is to estimate the willingness to pay (WTP) for major chemical fertilizers and revisit the fertilizer subsidy policy in Nepal.

We surveyed 619 households from six districts and assessed farmers’ WTP for urea, diammonium phosphate (DAP) and muriate of potash (MOP) during the fertilizer crisis. Our study elicited the WTP for fertilizers when fertilizers were not available on the market. A modified payment card approach was used to elicit farmers’ WTP.

The study found that farmers who buy fertilizer from agrodealers, buy from gray markets, have bank accounts, are willing to take a risk, have strong or medium economic conditions and incur higher travel costs have a higher WTP for fertilizers. Farmers in sampled areas, on average, are willing to pay 31 percent more for urea, 13 percent more for DAP and 19 percent more for MOP than the government recommended fertilizer price.

The design of the payment card and the estimation techniques used to fit the valuation function are likely to influence WTP.

Overall, literature on households’ WTP for fertilizers in developing countries is scarce. Our study contributes to the knowledge of WTP for fertilizers.

Artificial intelligence (AI) offers many benefits to improve predictive marketing practice. It raises ethical concerns regarding customer prioritization, market share concentration and consumer manipulation. This paper explores these ethical concerns from a contemporary perspective, drawing on the experiences and perspectives of AI and predictive marketing professionals. This study aims to contribute to the field by providing a modern perspective on the ethical concerns of AI usage in predictive marketing, drawing on the experiences and perspectives of professionals in the area.

The study conducted semistructured interviews for 6 weeks with 14 participants experienced in AI-enabled systems for marketing, using purposive and snowball sampling techniques. Thematic analysis was used to explore themes emerging from the data.

Results reveal that using AI in marketing could lead to unintended consequences, such as perpetuating existing biases, violating customer privacy, limiting competition and manipulating consumer behavior.

The authors identify seven unique themes and benchmark them with Ashok’s model to provide a structured lens for interpreting the results. The framework presented by this research is unique and can be used to support ethical research spanning social, technological and economic aspects within the predictive marketing domain.

La Inteligencia Artificial (IA) ofrece muchos beneficios para mejorar la práctica del marketing predictivo. Sin embargo, plantea preocupaciones éticas relacionadas con la priorización de clientes, la concentración de cuota de mercado y la manipulación del consumidor. Este artículo explora estas preocupaciones éticas desde una perspectiva contemporánea, basándose en las experiencias y perspectivas de profesionales en IA y marketing predictivo. El estudio tiene como objetivo contribuir a la literatura de este ámbito al proporcionar una perspectiva moderna sobre las preocupaciones éticas del uso de la IA en el marketing predictivo, basándose en las experiencias y perspectivas de profesionales en el área.

Para realizar el estudio se realizaron entrevistas semiestructuradas durante seis semanas con 14 participantes con experiencia en sistemas habilitados para IA en marketing, utilizando técnicas de muestreo intencional y de bola de nieve. Se utilizó un análisis temático para explorar los temas que surgieron de los datos.

Los resultados revelan que el uso de la IA en marketing podría tener consecuencias no deseadas, como perpetuar sesgos existentes, violar la privacidad del cliente, limitar la competencia y manipular el comportamiento del consumidor.

El estudio identifica siete temas y los comparan con el modelo de Ashok para proporcionar una perspectiva estructurada para interpretar los resultados. El marco presentado por esta investigación es único y puede utilizarse para respaldar investigaciones éticas que abarquen aspectos sociales, tecnológicos y económicos dentro del ámbito del marketing predictivo.

人工智能（AI）为改进预测营销实践带来了诸多益处。然而, 这也引发了与客户优先级、市场份额集中和消费者操纵等伦理问题相关的观点。本文从当代角度深入探讨了这些伦理观点, 充分借鉴了人工智能和预测营销领域专业人士的经验和观点。旨在通过现代视角提供关于在预测营销中应用人工智能时所涉及的伦理观点, 为该领域做出有益贡献。

本研究采用了目的性和雪球抽样技术, 与14位在人工智能营销系统领域具有丰富经验的参与者进行为期六周的半结构化访谈。研究采用主题分析方法, 旨在深入挖掘数据中显现的主要主题。

研究结果表明, 在营销领域使用人工智能可能引发一系列意外后果, 包括但不限于加强现有偏见、侵犯客户隐私、限制竞争以及操纵消费者行为。

本研究通过明确定义七个独特的主题, 并采用阿肖克模型进行基准比较, 为读者提供了一个结构化的视角, 以解释研究结果。所提出的框架具有独特之处, 可有效支持在跨足社会、技术和经济领域的预测营销中展开的伦理研究。

This paper aims to analyse the factors influencing migration, the labour migration process and the status of migrant laborers in the informal sector, particularly those working in brick kiln factories. It will shed light on the precarious nature of their work, often characterized by informal and verbal contracts. The paper examines occupational and environmental health hazards affecting the labourers and their impact on their well-being, the vulnerability of women in the precarious work environment and the associated health risks in brick kiln factories in India.

The study relies primarily on primary data collection, supplemented by secondary literature and documents. Balangir district was chosen as the research region due to its historical deprivation, underdevelopment and the historical prevalence of environmental distress, leading to distress-driven migration. To gather primary data, 40 respondents were selected from five selected blocks in Balangir district, resulting in a total of 200 respondents. In addition, in-depth interviews were conducted with 35 individuals across the selected blocks, with approximately seven participants from each block. In addition, interviews of 10 kids were taken and around 10 key informants including the trade union leaders, intellectuals and civil society activists.

Migrant labourers, including men, women and children, face significant health issues and are exposed to similar occupational health hazards. Internal migrant women workers are more vulnerable as they face critical health risks during pregnancy in host areas due to unfavourable working conditions and limited access to health-care services. Factors such as strenuous work, long working hours, poor nutrition and inadequate maternal care contribute to adverse outcomes such as spontaneous abortion, premature delivery and abnormal postnatal development.

The brick kiln industry presents a distressing reality for men who are highly vulnerable to occupational accidents, and women workers are exposed to sexual abuse, exploitation and violence. The prevalence of physical harassment, ranging from leering to rape, is alarmingly high among women. These incidents not only inflict physical harm but also cause severe psychological trauma and increase the risk of sexually transmitted diseases. Despite the existence of laws aimed at protecting women’s rights and addressing sexual offences, the workers often remain unaware of their rights. This lack of awareness further compounds the vulnerability of women workers and perpetuates their exploitation in the workplace.

To address health issues comprehensively, interventions should encompass the entire migrant population, including men and children. Strategies should focus on improving access to health-care services, promoting occupational health and safety measures, ensuring proper immunization and nutrition for children and addressing the broader social determinants of health. Empowering women with knowledge about reproductive health and rights, raising awareness about available health-care services and strengthening health-care providers’ capacity to cater to migrant populations are crucial steps towards addressing health disparities.

Urgent interventions and policies are needed to address the health vulnerabilities of internal migrant workers and women workers. It is required to ensure health-care accessibility, improving working conditions, ensuring access to maternal care and essential supplements and providing health-care services for both pregnant women and their children, regardless of migration status.

The study focused on precarious health and occupational hazards and accidents faced by migrant workers. It highlights women migrant labourer’s and children’s vulnerability in the Brick Klin sector, which is a value addition to the existing knowledge in social science.

The purpose of this study is to examine the factors that drive superior social enterprise performance for women-led social enterprises. The authors examined the role of individual entrepreneur cognitive characteristics contributing to social enterprise performance and recommended a framework for women's social entrepreneur development.

The authors conducted an exploratory qualitative study of 22 women founders of social enterprises using a semi-structured questionnaire. In-depth interviews were conducted, and the transcripts were analyzed using thematic content analysis.

This study found a significant impact of self-efficacy on the performance of social enterprises among the studied subjects. Social support in the form of material, information and emotional support enhanced the ability of women social entrepreneurs to better achieve business sustenance and continuance of operations. The business skills of the women social entrepreneurs led them to move from just social impact generators to becoming thought leaders. The strong prosocial motivation of the founders contributed to building their resilience in the face of adversity.

This study extended the existing theories on social entrepreneurship by bringing the dimensions of entrepreneurial resilience in driving social enterprise performance along with business skills. Thus, it provided an enhanced explanation to the existing body of knowledge on contributors to superior social enterprise performance.

This study gathered insights into the role of entrepreneurship education focused on business skills, especially for women social entrepreneurs in achieving superior performance for their social ventures. This also reconfirmed the role of social support and how structurally this could be provided by educational systems to aspiring women social entrepreneurs.

The practice of social entrepreneurship by women social entrepreneurs has been growing. Its importance in developing economies because of its ability to make grassroots changes at the lower levels of society was substantive. Women have shown more inclination toward social business with an affinity for prosocial contribution. By focusing on nurturing these social enterprises, governments as well as global agencies like the United Nations and the World Economic Forum could accelerate social change. Furthermore, support for the current women social entrepreneurs as change-makers making a difference in society could be achieved.

To the best of the authors’ knowledge, this research study was one of the first studies on women social entrepreneurs focusing on the factors of self-efficacy, social support and entrepreneurial resilience contributing to social enterprise performance. This study combined the social entrepreneurship intention theory with entrepreneurial resilience and business skills to understand the factors leading to successful social enterprise performance for women social entrepreneurs.

This paper aims to examine the origins of value co-creation (VCC) knowledge streams, vis-a-vis their progression over the past 18 years. The study explores how knowledge of this discipline emerged across the tripartite strategic paradigms of business transformation.

Co-citation analysis (CCA) and co-word analysis (CWA) are used as bibliometric techniques, for which, a group of articles is retrieved using Scopus’s usual keyword-based search. The initial collection consists of 3,431 research articles published in business and management publications. By explaining the article clusters generated through CCA and keyword connections generated through CWA, the findings outline the origins and development of VCC research. A CWA-based chronological study adds further insights to the development of VCC research themes.

The results depict that VCC research has grown multifold in the past 18 years, whereby it has shifted its attention from a dyadic interaction approach to a multistakeholder ecosystem-based approach detailing the phenomenological instances of resource integration and institutional processes. Notably, extant research in this field has grown at a much faster rate since 2008. In fact, a stronger concentration of research emerged in the experience domain, particularly in terms of hedonic services. Development of engagement platforms has been driven by research into technologies such as IoT and artificial intelligence.

The theoretical framework of the VCC paradigm is used to describe the aggregation of co-creation research around the three strategic pillars. This framework is useful for business strategy and to track VCC research over time.

This work identifies the practices and strategies of VCC at three different levels: capacity, platform and experience. The study offers insights into a variety of co-creation practices at their respective levels, incorporating micro-level dyadic interactions and macro-level processes in a service ecosystem.

This study uses different bibliometric methodologies to investigate the development of this scientific field over time. “Document co-citation” analysis, a more preferred bibliometric technique under CCA, is used to construct the cluster of theoretical cores of this area. The results are classified under the strategic framework of the co-creation paradigm (Ramaswamy and Ozcan, 2014).

Face is the most intuitive and representative feature at the individual level. Many studies show that beautiful faces help individuals and enterprises obtain economic benefits and form a high economic premium, but the discussion of their potential social value is insufficient. This study aims to focus on the impact of the personal characteristics of executives. It mainly analyzes the impact mechanism of CEO facial attractiveness on corporate social responsibility (CSR) decision-making, clarifying the social value of beauty from the perspective of CSR.

The authors use the regression model to analyze the panel data set, which was conducted by a sample of Chinese publicly listed firms from 2016 to 2018.

The study found that CEOs with high facial attractiveness are more active in fulfilling CSR, which can usually bring higher social benefits. CEOs with beautiful faces are prone to overconfidence, are optimistic about their ability and the future development of the enterprise and are more willing to increase their investment in CSR. CEO duality can positively regulate the positive correlation between a CEO’s facial attractiveness and CSR.

Based on the perspective of upper echelons theory, this paper explores the mechanism of CEO facial attractiveness on CSR. This study enriches the perspective of the upper echelon’s theoretical research and has essential enlightenment for CEO selection and training practice.

This paper aims to explore the development of investment decision tools by understanding the rationality behind the disposition effect. We suspect that not all disposition decisions are irrational. The decisions should be evaluated based on the bounded rationality of the individuals’ target and tolerance level, which is not covered in previous literature. Adding the context of individual preference (target and tolerance) in their decision could improve the classic measurement of disposition effect.

The laboratory web experiment is prepared to collect the responses in holding and selling the stocks within 14 days. Two groups of Gen Z investors are observed. The control group makes a decision based on their judgment without any system recommendation. In contrast, the second group gets help inputting their target and tolerance. Furthermore, the framing effect is also applied as a reminder of their target and tolerance to induce more holding decisions on gain but selling on loss.

The framing effect is adequate to mitigate the disposition effect but only at the early day of observation. Bounded rationality explains the rationality of liquidating the gain because the participants have reached their goal. The framing effect is not moderated by days to affect the disposition effect; over time, the disposition effect tends to be higher. A new measurement of the disposition effect in the context of bounded rationality is better than the original disposition effect coefficient.

Gen Z investors need a system aid to help their investment decisions set their target and tolerance to mitigate the disposition effect. Investment firms can make a premium feature based on real-time market data for investors to manage their assets rationally in the long run. Bounded rationality theory offers more flexibility in understanding the gap between profit maximization and irrational decisions in behavioral finance. The government can use this finding to develop a suitable policy and ecosystem to help beginner investors understand investment risk and manage their assets based on subjective risk tolerance.

The classic Proportion Gain Realized (PGR) and Proportion Loss Realized (PLR) measurements cannot accommodate several contexts of users’ targets and tolerance in their choices, which we argue need to be re-evaluated with bounded rationality. Therefore, this article proposed new measurements that account for the users’ target and tolerance level to evaluate the rationality of their decision.

This study aims to explore the influence of risk preference and information acquisition on outdoor tourism safety decision-making.

Five hundred twenty outdoor tourists were surveyed, and data were analyzed using two-stage regression.

Risk preference positively affects tourists’ safety decisions for outdoor travel. The greater the risk preference is, the more likely the tourists are to make the risky decision of outdoor tourism. Information acquisition significantly negatively affects tourists’ safety decisions for outdoor tourism. Tourists who obtain information through social channels are more likely to make safer travel decisions than those who do not.

Risk preference and information acquisition are introduced into outdoor tourism safety research.

Nowadays, food problems are likely to arise because of the increasing global population and decreasing arable land. Therefore, it is necessary to increase the yield of agricultural products. Pesticides can be used to improve agricultural land products. This study aims to make the spraying of cherry trees more effective and efficient with the designed artificial intelligence (AI)-based agricultural unmanned aerial vehicle (UAV).

Two approaches have been adopted for the AI-based detection of cherry trees: In approach 1, YOLOv5, YOLOv7 and YOLOv8 models are trained with 70, 100 and 150 epochs. In Approach 2, a new method is proposed to improve the performance metrics obtained in Approach 1. Gaussian, wavelet transform (WT) and Histogram Equalization (HE) preprocessing techniques were applied to the generated data set in Approach 2. The best-performing models in Approach 1 and Approach 2 were used in the real-time test application with the developed agricultural UAV.

In Approach 1, the best F1 score was 98% in 100 epochs with the YOLOv5s model. In Approach 2, the best F1 score and mAP values were obtained as 98.6% and 98.9% in 150 epochs, with the YOLOv5m model with an improvement of 0.6% in the F1 score. In real-time tests, the AI-based spraying drone system detected and sprayed cherry trees with an accuracy of 66% in Approach 1 and 77% in Approach 2. It was revealed that the use of pesticides could be reduced by 53% and the energy consumption of the spraying system by 47%.

An original data set was created by designing an agricultural drone to detect and spray cherry trees using AI. YOLOv5, YOLOv7 and YOLOv8 models were used to detect and classify cherry trees. The results of the performance metrics of the models are compared. In Approach 2, a method including HE, Gaussian and WT is proposed, and the performance metrics are improved. The effect of the proposed method in a real-time experimental application is thoroughly analyzed.