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Farmer producer organisations (FPOs) are considered as a strategy to improve the livelihoods of small farmers through economies of scale by providing collective strength to farmers for improved access to production technology, value-addition services, high-quality inputs and marketing services for improving their incomes. This study investigates the impact of FPO membership on organic farming household's income in Northeast India.

This study uses field survey data collected from all four districts of Sikkim. Primary data were obtained from a survey of 560 organic farming households, 280 of which are FPO members and the rest 280 are non-members. Propensity score matching (PSM) is used to estimate the impact of FPO membership on net returns, return on investment (ROI) and profit margin.

Results show that the FPO members had, on average, Rs. 7,254–8,133 higher annual net returns, 4.6–4.8% higher ROI and 8–8.4% higher profit margin than the non-members. The findings confirm that FPO membership has a positive and significant impact on net returns, return on investment and profit margin. Also, heterogeneity analysis indicates that FPO membership has larger positive impact on relatively bigger farmers and female-headed households.

As the study was based on a cross-sectional survey, the findings may be subjected to some limitations.

This study is based on a novel data set, collected specifically to examine the economic impact of FPO membership on organic farming in India.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2023-0451

This study aimed to understand the agri-entrepreneurial traits of undergraduate university students using machine learning (ML) algorithms.

This study used a conceptual framework of individual-level determinants of entrepreneurship and ML. The Google Survey instrument was prepared on a 5-point scale and administered to 656 students in different sections of the same class during regular virtual classrooms in 2021. The datasets were analyzed and compared using ML.

Entrepreneurial traits existed among students before attending undergraduate entrepreneurship courses. Establishing strong partnerships (0.359), learning (0.347) and people-organizing ability (0.341) were promising correlated entrepreneurial traits. Female students exhibited fewer entrepreneurial traits than male students. The random forest model exhibited 60% accuracy in trait prediction against gradient boosting (58.4%), linear regression (56.8%), ridge (56.7%) and lasso regression (56.0%). Thus, the ML model appeared to be unsuitable to predict entrepreneurial traits. Quality data are important for accurate trait predictions.

Further studies can validate K-nearest neighbors (KNN) and support vector machine (SVM) models against random forest to support the statement that the ML model cannot be used for entrepreneurial trait prediction.

This research is unique because ML models, such as random forest, gradient boosting and lasso regression, are used for entrepreneurial trait prediction by agricultural domain students.

The success of the organization depends on its sustainability and growth in the competitive market. Retention and attraction of talent in the organization are strongly associated with organizational performance. Employer branding is an outcome activity that helps organizations show their strength to attract and retain talent. Talent management practices are mostly essential in the current context for retaining talent. This study aims to explore and identify the contributing factors in efficient talent management and to examine whether the factors contributing to employer branding differ concerning different demographic profiles of the employees for information technology organizations.

Data were collected from 617 adult participants using an 85-item questionnaire on talent management comprising 25 domains, developed for the present study.

Principal component analysis of the data indicated that 20 different factors make an impact in developing strong talent management practices. Three broad areas were identified, namely, personal benefits and growth, transparent organizational culture and social commitment of the organizations.

Present research has not taken care of few other factors associated with the organization where employees’ retention gets adversely effected such as evaluation of performance and compensation management, training and development, etc. So, future research can be conducted these areas. These aspects are also required to be incorporated in future research.

Several implications of the present research can be presented in the following areas. It is found in the present research that the effectiveness of the talent management system mostly depends on personal benefits and growth, organizational culture and climate and the organizational out. Apart from the academic implications of the present research, practical implications of the present study cannot be ignored. The components and elements of the talent management in the perspectives employer branding can also appropriately applied by the organizations.

The contribution of the study lies in exploring and identifying three important aspects of the organization in talent management. Findings will have implications for different organizations in understanding, developing and implementing policies related to employer branding and talent management.

This study attempts to conduct a post-occupancy assessment of the primary technical, functional and behavioral features in a student housing facility at the Visvesvaraya National Institute of Technology campus in Nagpur, India to see if the students are satisfied with the residential hostel's environs and facilities.

The study reviews knowledge areas pertinent to the technical, functional and behavioral performance of student housing facilities by looking at the body of accessible literature. Even though the literature review gave a thorough overview of the broad issues, it was essential to learn about the situation as it is and addresses the specific issues brought up to undertake a thorough evaluation, just as every in-depth study depends on a reliable methodology. Therefore, a methodology appropriate for the research was developed, which helped in identifying relevant attributes for the questionnaire to be used for the survey. This aided in analyzing the building's performance evaluation through the sole users of the hostel which are the students. The survey data is analyzed by statical methods using SPSS software to identify the key determinants of satisfaction in students' residential hostels and if these are affected by the gender of the students.

The survey results were examined to determine the level of satisfaction with the selected performance aspects, and the major determinants governing it. The findings concluded that most of the technical and functional determinants of satisfaction in hostels are identified the same by both genders, except for some of the attributes in behavioral elements. The research looked at how well key success elements in the student housing facility had been implemented.

Research is carried out in CFTI only wherein architecture is one of the branches.

Planning professionals, architects, housing managers and facility managers involved in the design, construction and management of student housing facilities might benefit from feedback from a post-occupancy evaluation. The post-occupancy study can therefore aid in continually enhancing the standard and effectiveness of the facilities for planning, constructing, managing and maintaining student residential housing.

Digital supply chains require nascent technologies like blockchain and Internet of Things (IoT). There is a need to develop a roadmap for the implementation of these technologies, as they require a huge amount of resources and infrastructure. The purpose of this paper is to analyze the challenges of implementing blockchain-IoT integrated architecture in the green supply chain and develop strategies for the same.

After a thorough literature survey of Scopus-indexed journals and books, 37 barriers were identified, which were then brought down to 15 barriers after confirming with industry and academic experts using the Delphi method. Using the total interpretive structural modeling (TISM) method and cross-impact matrix multiplication applied to classification (MICMAC) analysis, the barriers were modeled, and finally, strategies were formulated using a concept map to handle the barriers in the blockchain-IoT integrated architecture for a green supply chain.

This paper presents the research on barriers that can be considered for incorporating blockchain and IoT in the green supply chain. It was found from the TISM model that environmental concerns are Level-1 barriers and need to be addressed by developing appropriate technology and allocating funds for the same. An integrated ecosystem with blockchain and IoT is developed.

The focus of this study was on the challenges of blockchain and IoT; hence, it is required to extend the research and find challenges for different industries and also analyze the criteria using other multi-criteria decision-making (MCDM) methods. Further research is required for the integration of blockchain-IoT with supply chain functions.

The transformation of a traditional supply chain into a green supply chain is possible with the integration of technologies. This research work and the strategies developed are useful to managers and practitioners working on technology implementation. Planning resources and addressing key barriers is possible with the concept maps and architecture developed.

Green supply chain management (SCM) is gaining importance in industry as well as the academic sector due to government Policies and norms worldwide for reducing emissions and encouraging environment-friendly production systems. Incorporating blockchain and IoT in a green supply chain will further digitize and increase transparency in supply chains.

We have done a categorization of all barriers based on the expert survey by academicians and industry experts from industries in India. The concept map helps in identifying possible solutions for the challenges and initiatives to be taken for the smooth integration of technologies in the green supply chain.

Selecting and using the same health monitoring devices for a particular problem is a tedious task. This paper aims to provide a comprehensive review of 40 research papers giving the Smart health monitoring system using Internet of things (IoT) and Deep learning.

Health Monitoring Systems play a significant role in the healthcare sector. The development and testing of health monitoring devices using IoT and deep learning dominate the healthcare sector.

In addition, the detailed conversation and investigation are finished by techniques and development framework. Authors have identified the research gap and presented future research directions in IoT, edge computing and deep learning.

The gathered research articles are examined, and the gaps and issues that the current research papers confront are discussed. In addition, based on various research gaps, this assessment proposes the primary future scope for deep learning and IoT health monitoring model.

The host–guest molecules are often used in various fields and applications. This paper aims to discuss the role of host–guest complexes in the textile industry, focusing on calixarenes as a potential adsorbent for hazardous dyes. The paper begins with an introduction to nanotechnology and its many uses, including textiles.

The risks associated with the utilisation of dyes and its adverse effects on the environment are then also highlighted. This paper also discusses the structure and characteristics of calixarenes and their potential use as an adsorbent to extract toxic metals from aqueous solutions. The paper also explains the molecular structure of calixarenes, especially the ability of its upper and lower rims, which can be altered to yield derivatives with various selectivities for diverse guest ions and small molecules. In addition, the application of various host–guest molecules in the textiles industry to extract dyes also had been discussed.

In conclusion, the paper highlights the essential in establishing a systematic review on the significance of selective adsorbents, such as calixarenes, to isolate particular targets from diverse matrices in the textile industry.

Only discussing several applications for several host–guest molecules.

The paper concisely describes various host–guest molecule applications in the textile industry, with each molecule being elaborated upon in detail.