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Agriculture is a vital sector for every country, especially for a country like India, where the majority of the population is dependent on agriculture as their earning source. Technological improvements in agriculture will increase output with proper forecasting of input resources. In this study, the author tries to investigate the attitude of end users (farmers) about the use of Industry 4.0 (I4.0) technologies.

The unified theory of acceptance and use of technology (UTAUT) model is used to assess the behavioral aspects. The significance of socioeconomic and technological factors is highlighted, providing the study with a thorough understanding of farmers' decision-making processes. A research questionnaire was developed for data collection, and descriptive and inferential statistics were used to analyse the results using AMOS and SPSS software.

A total of 371 survey responses were collected. The results demonstrate that the hypothesis regarding UTAUT model components is validated, while several mediating hypotheses are not supported, indicating that they are not significant in farmers' decision-making.

In this study, socioeconomic and technological factors are considered to be mediating and moderating elements between the constructs of the UTAUT model. Increasing the accuracy and reliability of our study by integrating mediating and moderating variables. This study assists industry specialists in understanding the elements that farmers consider while switching toward new technologies.

This study aims to conduct a bibliometric analysis to provide a comprehensive picture and identify future research directions to enrich the existing literature on behavioral biases.

The data set comprises 518 articles from the Web of Science database. Performance analysis is used to highlight the significant contributors (authors, institutions, countries and journals) and contributions (highly influential articles) in the field of behavioral biases. In addition, network analysis is used to delve into the conceptual and social structure of the research domain.

The current review has identified four major themes: “Influence of behavioral biases on investment decisions,” “Determinants of home bias,” “Impact of biases on stock market variables” and “Investors’ decision-making under uncertainty.” These themes reveal that a majority of studies have focused on equity markets, and research on other asset classes remains underexplored.

This study extracted data from a single database (Web of Science) to ensure standardization of results. Consequently, future research could broaden the scope of the bibliometric review by incorporating multiple databases.

The novelty of this research is to provide valuable guidance by evaluating the existing literature and advancing the knowledge base on the conceptual and social structure of behavioral biases.

This paper aims to explore the determinants of intention towards the use of agro-advisory mobile applications by extending the technology acceptance model (TAM) with addition of the following constructs: result demonstrability (RD), trust, self-efficacy (SE) and mobile usage proficiency (MUP).

The study employed a survey on farmers (n = 446), which was analysed through structural equation modelling using Analysis of Moment Structures (AMOS).

The results show that RD and farmer's trust on agro-advisory mobile apps (AAMA) positively impact their perceptions of usefulness. Also, farmer's SE and MUP positively affect their perceptions of ease of using AAMA. Further, interestingly, farmer's attitude towards the AAMA fully mediates the relationship between perceived usefulness and perceived ease of use on intention to use them.

Understanding the antecedents of agro-advisory mobile application offers a unique contribution to policymakers, private firms, and non-government organizations by proving key insights on the acceptance of agriculture based mobile technologies in context of developing nations.

To the best of author's knowledge, this is one of the first research enquiries on the adoption of agro-advisory mobile applications. The new theoretical framework adds to the original TAM and offers novel insights that are helpful in augmenting the current understanding on AAMA and their acceptance by the beneficiaries.

Implementing big data analytics and client customization programs is causing a significant revolution in the insurance sector. This study examines how big data analytics may revolutionize the insurance industry, emphasizing how consumer customization can improve customer experiences, maximize risk assessment, and spur company expansion.

An empirical study with statistical analysis using tools like correlation and regression was carried out to ascertain the relationships between the various sets of variables—personalized customer experiences and customer satisfaction and customer profiling leads to more effective targeting of marketing efforts. We explore essential ideas like client segmentation, profiling, and retention via a thorough analysis of the literature and case studies, showcasing best practices and inspirational tales from top insurers.

The empirical study found that there is a very high correlation between transparency in data and stakeholders' trust. The study found that insurers may preserve their innovation-driven culture, strengthen customer relationships, and achieve sustainable development in a competitive market by embracing future technological innovations and resolving current challenges.

Insurance companies may seize new chances for individualized client experiences and long-term success in a market that is becoming increasingly competitive by utilizing cutting-edge technology like artificial intelligence and the Internet of Things. To effectively manage the changing terrain of consumer customization in the digital age, insurance professionals, academics, and legislators will find this study highly insightful.

The study is an original contribution based on literature and case studies analysis, showcasing best practices and inspirational tales from top insurers.

Consumers and businesses are becoming increasingly conscious of sustainable business practices and are often willing to pay a premium for responsibly sourced and manufactured products. Many countries and organizations have implemented regulations and standards for sustainability and companies face penalties or are barred from exporting for not meeting the requirements. Rooted in the resource-based view theory, this study aims to test a moderated mediation model to improve the sustainability performance of exporting firms.

Textile firms generating more than 25% of export revenues were targeted for this research. The data collected from 245 middle management-level employees were tested for reliability and validity. The structural equation modelling in AMOS 26 was used to test hypotheses.

Organizational readiness for green innovation (ORGI) has a direct positive effect on sustainability performance. The mediation analysis implies that ORGI translates into sustainability performance through improvement in green innovation performance. The moderating effect of knowledge integration highlights the importance of being prepared internally and actively seeking and incorporating external knowledge to improve green innovation performance.

The findings offer a solid foundation for informed decision-making, policy development and strategies to improve sustainability performance while aligning with the global nature of the textile industry and its inherent challenges. The proposed model and practical implications guide policymakers and managers of exporting firms to foster a culture of green innovation to leverage the effect of their readiness for green innovation on sustainability performance.

Green innovation, particularly in manufacturing firms, is one of the most advocated methods to curb the effects of climate change. This study aims to investigate the impact of the integration of green customers and suppliers on the green innovation performance of food manufacturing firms in Pakistan. The institutional and resource-based view theories determine the moderating role of regulatory pressure and the mediating role of green knowledge integration capability (GKIC).

Data was collected from 511 middle management-level employees of food manufacturing firms in Pakistan. The questionnaire was tested for reliability and validity. Hierarchical regression is used to test the proposed hypothesis.

A marginal improvement in integration with green customers can increase the green innovation performance (GIP) of a firm by 23.6%. Green supplier integration can improve the GIP by 14.2%, whereas the GKIC mediates the relationship between Green Customers Integration (GCI) and GIP but not for green suppliers integration (GSI). The moderating effect of regulatory pressure was significant for the relationship between GCI and GIP but insignificant for GSI.

Food manufacturing accounts for approximately 16% of global green house gases (GHG) emissions. Sustainable development goals (SDGs) cannot be achieved without a significant decrease in GHG emissions by food manufacturing companies. Therefore, it is crucial to investigate firms' green innovation performance in this sector. The findings of this study can help policymakers develop policies for achieving SDGs.

This study aims to explore the relationship between brand image and buying intentions, which is crucial in understanding consumer buying behaviour. This study aims to review the literature, identify research trends and further suggests research directions for future study.

A bibliometric analysis was conducted on 402 research articles extracted from the Scopus database, following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework. The study includes performance analysis, science mapping and network visualization, with VOSviewer and Biblioshiny software for the analysis. It examines publication trends, prolific countries, institutions, authors, highly cited papers, keyword co-occurrence and thematic evolution for a comprehensive analysis.

The study reveals the increasing scholarly interest of researchers in brand image and purchase intention over time and identified various research themes. Results state that Brand image and purchase intention themes remained central throughout both time zones (1995–2012 and 2013–2024). Emerging themes of the field include green marketing, corporate social responsibility, influencer marketing and entrepreneurial marketing.

This research study makes an addition to the body of literature by identifying the research hotspots and areas that need further investigation. Further, the thematic evolution of the brand image and purchase intentions illustrates how perception at various consumer levels and decision-making process has shifted over time in response to changing market dynamics. This study is of quite paramount importance for a vast group of stakeholders including researchers, businesses, brand managers, policy makers, marketing professionals and future research scholars.

This study aims to examine the influence of condominium attributes on resident satisfaction and word of mouth from the perspectives of the elderly in Thailand.

Data were collected from 338 elderly residents through a questionnaire survey and analysed by using descriptive statistics and structural equation modelling procedures.

The results showed that the strongest predictor of resident satisfaction was design functionality, followed by social environment, safety and security and service quality. In addition, the strongest predictor of word of mouth was safety and security, followed by design functionality, proximity, service quality and social environment.

The data were drawn at the level of the overall characteristics of elderly residents. People may be different in terms of their demographic characters such as gender, age, and user experience.

The study suggests that condominium developers and designers should pay attention to design functionality both physically and mentally such as suitable materials, lighting and common areas. Moreover, the developers should focus on the proximity of the nearest hospitals, safety and security measures, well-trained security personnel and social activity arrangement.

Elderly condominium markets are increasingly growing as a result of the ageing society in Thailand. However, very few empirical studies investigate condominium attributes that affect resident satisfaction and word of mouth provided by real estate developers. The paper aims to determine driving factors that enhance the better well-being of elderly residents.

E-retailers face challenges in adding, engaging and retaining customers. Voice interface is a new and more inclusive modality that provides customers with a hands-free, convenient e-shopping option and is relevant for e-retailers. However, the voice interface is significantly different from the text interface that consumers are accustomed to. This study investigates customer experiences with voice interface for search and selection of products on e-commerce platforms and its subsequent impact on customer engagement and enhanced usage.

We conducted 34 in-depth interviews with executive management students. For analysis and findings, we used a grounded theory paradigm and thematic analysis.

Based on in-depth probing and analysis consumers' experiences with voice interfaces in e-commerce platforms, we identified two enablers: customer satisfaction and awe-experience that positively impacted and two inhibitors: risk perceptions and inertia that negatively impacted customer engagement and enhanced usage of voice interface.

Voice interface is transforming the customer journey in the online shopping domain. How customers experience voice interfaces when searching and selecting products on e-commerce platforms impacts their engagement with the platform and their intentions to use voice modality to interact with the e-retailer in the future. The findings substantiate tenets of dual-process theory and found that enabling and inhibiting factors are independent and can coexist. The study identifies the most salient factors that positively and negatively affect customer engagement and enhanced usage of voice interfaces.