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This study focuses on Aaker's Brand Equity Model, to check the effect of brand equity determinants on booking intention (BI) for ridesharing in India. The study also explores the moderation of ecologically conscious consumer behavior (ECCB) on the multiplicative effect of brand awareness (BAw), brand association (BA) and perceived quality (PQ) in influencing the BI.

Responses from 393 Indian ridesharing users were collected using judgmental sampling and were analyzed using Hayes Process macro.

The study found a direct relationship between BAw and BI, BAw and BA, BAw and PQ, BA and PQ, PQ and BI, and BA and BI. Findings revealed mediation of BA in BAw and BI relationship and PQ in BAw and BI relationship. Results revealed that BA and PQ serially mediate BAw and BI relationship. ECCB moderates PQ and BI relationship but not BAw and BI relationship.

Serial mediation and moderated-mediation results draw various theoretical implications for determinants of Aaker's Brand Equity model and ECCB.

The research has several implications for managers in view of brand equity determinants and ECCB. The study also contributes to policy implications.

Study's novel contributions are mediation, serial mediation between brand equity determinants, and moderation of ECCB between BAw and BI for ridesharing.

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。

According to Global Healthcare Security Index 2021, India ranked 66 out of 195 countries, indicating the need and scope for improvement. The Cooperative healthcare system which has been rendering exemplary services is yet to gain visible recognition in India. Given the need for upgrading the health infrastructure in India and providing more affordable health services to the country’s growing population, it would help appreciate the large role that cooperative healthcare can play along with others. This study explores the structure, conduct, and performance of healthcare co-operatives in India, the factors contributing to their success and failure, and the challenges they face. The Health Cooperatives have a strong presence in Kerala and Karnataka and are also coming up in other parts of the country. However, a detailed database of them for public awareness is very limited. The cooperative hospitals can meet the basic requirements of curative treatment in rural and poorly-endowed urban areas. The democratic way in which they function makes them a destination for a financially weaker section. They must retain this feature. The study covers two successful cases which reveal that India needs a more dense healthcare cooperative network. Since cooperative hospitals in tune with the spirit of service run on the principle of being ‘Not-for-Profit’ they need to be supported by the governments more liberally, without however interfering with their governance and administration.

Although Asia's rise in the global economy is increasingly recognized, international business (IB) interactions between Japan and India remain under-commented. These interactions are especially salient due to the United Nations Sustainable Development Goal 17 (UN SDG 17), which focuses on partnerships. This study updates and analyzes the strategic orientation of Japanese multinational enterprises (MNEs) in India.

Following a subjectivist approach, this study employs a constructivist epistemology. Utilizing mixed methods, it obtains primary data from interviews and informal conversations with senior personnel from Japan and India and secondary data from archives. These data then undergo manual organic thematic analysis.

The study reveals instances of Japanese MNEs diverging from traditional ethnocentric orientations, such as senior management's growing commitment to India. The findings also indicate that the transformation to a polycentric orientation remains incomplete.

The study uncovers themes impeding a polycentric transformation, offering insights for strengthening international partnerships and emphasizing the necessity of prioritizing local demands and cultural expectations.

Clues to strengthening IB contribute to attain UN SDG 17, especially given the advanced-emerging characteristics of the Japan–India dyad.

This study’s research makes a novel contribution to the literature on international strategic orientations by providing insights into a rare dyad – namely, Japanese MNE expansion in India. It is also a valuable and timely addition consistent with current beyond-China business diversification trends.

This study aims to assess the knowledge-sharing risks and controls in the government sector from the knowledge workers’ perspective.

This qualitative study combines two techniques. First, the study uses the Delphi technique to identify the risks and rank them. Second, the study used a follow-up interview approach to identify the needed controls to mitigate these identified risks.

The Delphi study revealed the top knowledge-sharing risks are related to organizational and individual risks. Furthermore, the study identified the top controls that needed to mitigate these identified risks from technology, process and people dimensions. The study findings suggested that implementing controls on people and processes is the most important, and the focus must be on them, especially in the government sector.

The study offers several practical implications for the government sector to establish a knowledge-sharing risks management strategy. Such study has been given little attention in previous research, especially in developing countries.

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.

Innovation is a process that enables organizations to sustain and prosper in a competitive business environment. This study aims to understand the key drivers of innovation within organizations from the lens of employees.

This study uses a grounded theory approach based on semi-structured in-depth interviews of 20 professionals working in information technology (IT) firms. Judgmental sampling was adopted to select the respondents. Open coding, inductive analysis was conducted on the interview transcripts to generate relevant themes.

Emerging themes indicate that innovation within organizations can be triggered as a response to client requirements or the employees’ inherent urge to innovate. Certain factors such as user engagement, formal organizational processes and practices, informal collaborative practices, the role played by experts and leaders and upskilling were seen to enable innovative outcomes within organizations.

Findings from this study will allow leaders to activate the identified drivers by designing suitable organizational processes and strategies to nurture a successful innovation culture within their teams.

This grounded theory-based study looks at drivers of innovation within IT organizations from the perspective of employees.

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 the research is to recognize and rank the barriers preventing Industry 4.0 (I4.0) adoption in Bangladesh’s food and beverage industries. It aims to highlight the major difficulties the sector is currently facing and offer a hierarchical framework for evaluating these barriers.

An exhaustive literature review was conducted along with expert interviews with academics and industry professionals to identify and assess the barriers. The interpretive structural modeling and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement (ISM-MICMAC) approach was used to classify the identified barriers based on driving and dependent power and understand the interrelationships among them.

A total of 20 barriers to I4.0 adoption in the food and beverage sector of Bangladesh were identified. The top tier of significant barriers includes “Financial constraints,” “Lack of management support,” “Lack of research and development team,” “Lack of adequate skills in the workforce,” “Lack of digital strategy alongside resource scarcity” and “Employee resistance to change.”.

The created hierarchical framework offers a useful tool for dealing with the noted barriers and assisting with the successful adoption of I4.0 in the food and beverage sector. Businesses can overcome financial constraints by allocating enough resources and obtaining management support. By creating a focused research and development team and giving the workforce the necessary training, the lack of knowledge and skills can be overcome. By developing a thorough digital strategy and making sure that the necessary resources are available, resource scarcity can be overcome. Furthermore, effective change management methods can support the adoption of I4.0 technologies by overcoming employee resistance to change.

By concentrating specifically on the difficulties encountered by the food and beverage industries in Bangladesh as it attempts to adopt I4.0, this study contributes to the body of existing literature. The study’s originality lies in its thorough analysis of barriers and the use of the ISM-MICMAC approach to comprehend how these barriers interact with one another.