International Journal of Sustainable Agricultural Management and Informatics (31 papers in press)

Regular Issues

• Seeding sustainable practices: a value-attitude-behaviour analysis of farmers green innovation adoption  
  by Geetha Krishnan, Naga Venkata Raghuram Jeedigunta 
  Abstract: This study intends to investigate the impact of egoistic and altruistic values, farmers’ attitudes, and green innovation adoption behaviour using the value-attitude-behaviour framework. Altruistic value was represented by environmental concern, while egoistic value was represented by health concern. The researchers utilised purposive sampling to collect data from 211 farmers through a self-administered questionnaire survey. Structural equation modelling (SEM) was utilised to test the conceptual model. The results show that altruistic and egoistic values influence farmers’ green innovation adoption behaviour. Further research revealed that the association between both types of values and farmers’ green innovation adoption behaviour was mediated by attitude. These research findings have important implications for promoting sustainable agricultural practices and contribute to advancing environmental psychology and sustainable development theories. This study is one of the early attempts made in India to comprehend the significance of egoistic and altruistic values in relation to farmers’ green innovation adoption behaviour.
  Keywords: green innovation; altruistic value; egoistic value; health concern; environmental concern.
  DOI: 10.1504/IJSAMI.2024.10063014
   
  
• Promoting the concept of viability in agri-food supply chains  
  by Maria Kontopanou, Giannis T. Tsoulfas 
  Abstract: The rapid adaptation, and the reconfiguration of processes and structures, is necessary in response to unpredictable disruptions of supply chains. Sustainability and resilience are seen as the most promising approaches for dealing with the occurring disruptions. Both concepts focus on the ways in which supply chains should modify their functions to sufficiently respond to external or internal disturbances. Supply chains also need to reconfigure their long-term strategies to support their place in the market and preserve competitive advantage. The recently proposed concept of viability comes to reset the goals of the supply chain systems, aiming to ensure the long-term effectiveness of the measures taken while dealing with a crisis. This paper aims to define the concept of viability in the context of agri-food supply chains and propose interventions and ways of adoption for the existing supply chain systems.
  Keywords: viability; agri-food; supply chain; sustainability; resilience.
  DOI: 10.1504/IJSAMI.2024.10063191
   
  
• Blockchain-based application for grain production and trade: a case study of Huzhou storehouse tender mode, China  
  by Feiyu Hu, Taige Qin 
  Abstract: Grain security is vital for achieving Sustainable Development Goals and is a top national priority in China. To address natural disasters and emergencies, China has maintained a grain reserve system for decades. However, the current system faces issues in reservation efficiency and grain quality, risking waste in the grain industry. In order to solve these problems, in 2018, Huzhou City initiated an experiment named storehouse tender mode (STM) to improve the grain reserve system in production and trade. This paper provides an overview of STM, explores efficiency and security issues within the grain reserve system, and introduces a blockchain-based prototype system designed to bolster STM implementation. The system simulation highlights blockchain’s potential to establish a transparent, traceable, and trustworthy trade environment for STM. Findings confirm the feasibility and optimisation capacity of the proposed solution, signalling a transformative potential for the traditional grain reserve system.
  Keywords: blockchain; smart contract; storehouse tender mode; STM; information system; China.
  DOI: 10.1504/IJSAMI.2024.10063471
   
  
• Deep learning and machine learning approaches for data-driven risk management and decision support in precision agriculture  
  by Mounia Mikram, Chouaib Moujahdi, Maryem Rhanoui 
  Abstract: Modern agriculture grapples with challenges such as unpredictable weather, biosecurity threats, market volatility, evolving regulations, and farmer health concerns. Effectively addressing these issues while maintaining sustainability demands informed decision-making. Data-driven technologies, especially deep learning (DL), emerge as crucial solutions. This study introduces a sustainable multivariate risk management system for precision agriculture, encompassing plant disease detection, weed detection, fire and smoke detection, and crop recommendation modules. Empowering farmers with tools to navigate risks and enhance operational efficiency, the system leverages DL techniques to uncover correlations among diverse risk factors. Enabling well-informed decisions on risk mitigation, this innovative system has the potential to revolutionise precision agriculture, fostering sustainability and profitability. Insights from the study set a benchmark for adopting data-driven, sustainable practices in smart agriculture. Farmers can utilise the system to conduct informed assessments, proactively mitigate crop damage, and redefine their approach to modern agriculture, ensuring improved yields and enhanced monitoring.
  Keywords: deep learning; precision agriculture; risk management; farming; risk mitigation strategies; smart agriculture.
  DOI: 10.1504/IJSAMI.2024.10063472
   
  
• Farmers profile and their entrepreneurial orientation in Greece  
  by Athanasios Falaras, Odysseas Moschidis, Katerina Gotzamani, Demetres Subeniotis 
  Abstract: The research aim was to create the human geographic map of farmers in Greece. So a survey was conducted, where 735 answers were collected. The study employed MCA to extract critical data insights, AHC to form clusters of farmers, and tests to identify statistically significant categories within each cluster. Three clusters emerged: The innovative group of farmers is consisted of farmers in Epirus, Western Greece and Crete and they are young, well-educated and wealthy farmers featuring strong entrepreneurial orientation characteristics. The inefficient cluster consists of farmers in Central and Western Macedonia, earning 20.001-30.000 per year, who demonstrate weak entrepreneurial orientation characteristics. The old guard cluster consists of farmers in Eastern Macedonia and Thrace, Thessaly and Central Greece, who possess low educational level, income and arable land size. The innovative cluster along with the suitable soil and climate of Greece propose a hopeful future for agriculture in Greece.
  Keywords: entrepreneurship; innovation; agriculture; Greece.
  DOI: 10.1504/IJSAMI.2024.10063574
   
  
• A review on the relation between European protected areas, farming systems and labelled agri-food products with a protected area logo  
  by Athina Koutsouki, Stefanos Nastis, Dimitrios Zikos 
  Abstract: Agricultural practices exert significant influence on the conservation and sustainable management of European protected areas (PAs). Traditional low-intensity farming systems have become unprofitable leading to either abandonment or intensification of farming practices. These changes have contributed to the environmental degradation of biodiversity-rich agricultural landscapes and the loss of valuable cultural knowledge. The development of certification and labelling schemes of high quality agri-food products with a PA logo could generate environmental improvements and positive socio-economic changes. This paper review presents the findings of existing studies focusing on the relationship between the European PAs, farming systems and certification/labelling schemes of agri-food products with a PA logo. Academic research on the subject is limited but provides valuable insights. The findings can serve as a starting point for discussions and reveal opportunities for further research to better understand the interrelations and additional effects emerging from the labelling/certification of high quality agri-food products within PAs.
  Keywords: European protected areas; farming systems; low-intensity farming; agri-food products; labelling schemes; sustainable rural development.
  DOI: 10.1504/IJSAMI.2024.10063674
   
  
• Exploring the role of consumers’ intention in sustainable agriculture through organic foods  
  by Shrish Singh, Vijay Kumar Jain, Hemraj Verma 
  Abstract: The study focuses on identifying determinants of purchase intention for organic foods using decomposed TPB. Consumers attitude, subjective norms, and perceived behavioural control have been extended, and finally mutual relationship of all the variables with behavioural intention was discovered in the presence of desire as a mediator. An empirical investigation of 350 responses was carried out by applying CFA and SEM using Smart-PLS 4. After confirming the surveys reliability, the items were finalised and the surveys instruments were validated through pilot testing. The result shows that perceived usefulness and perceived satisfaction leads to attitude. It is also proven that interpersonal influence like family and friends have less impact on subjective norms than external ones like the media. The finding shows that desire partially mediates attitude to behavioural intention and fully mediates subjective norms to behavioural intention but does not mediate perceived behavioural control to behavioural intention.
  Keywords: extended TPB; organic food; behavioural intention; structural equation modelling; SmartPLS.
  DOI: 10.1504/IJSAMI.2024.10063754
   
  
• Export motivation and clustering of Greek yogurt firms  
  by Zacharias Papanikolaou, Christos D. Karelakis, Konstantinos Polymeros, Apostolos Goulas, George Theodossiou 
  Abstract: In a turbulent economic environment, the exports of dairy products and mainly Greek yogurt to Greece are essential for Greek firms economic growth and empowerment. The study aims to cluster Greek yogurt production firms according to the antecedents of their internationalisation motives. Data were collected through a survey (structured questionnaire) in a sample of 137 yogurt firms, of which 21 have export activities and an overall response rate of 75.91%. The clustering of firms was achieved via the hierarchical cluster analysis method performed with the Ward method to minimise the differences within the clusters. Regarding selecting the number of clusters to be created, the choice was made based on the number of sample firms within a range of two to five clusters. The results show that Greek yogurt firms are divided into two distinct clusters: large-sized exporting firms with experience in the field and small-sized non-exporting firms of the local market.
  Keywords: cluster analysis; competitive advantage; internationalisation; Greek yogurt.
  DOI: 10.1504/IJSAMI.2024.10063800
   
  
• Millet Marvels: unravelling the nexus between social media influence, expectation confirmation, and customer purchase intentions for millet products in the digital age  
  by K. Geetha, R. Manigandan, J. Naga Venkata Raghuram, Pulidindi Venugopal 
  Abstract: In the dynamically evolving landscape of consumer behaviour, this study explores the intricate relationships among social media interaction, confirmation, satisfaction, and repurchase intention of millet products. The study employs a quantitative research design, utilising survey data collected from a sample of 269 millet product consumers. The findings show that social media interactions and confirmations significantly contribute to customer satisfaction, ultimately fostering a higher likelihood of repurchase intention for millet products. The mediating effect of satisfaction underscores its pivotal role as a key determinant in shaping the repurchase intention of millet products. The study contributes to understanding consumer behaviour in the digital age and offers insights for marketers aiming to improve engagement and loyalty in India's millet product market.
  Keywords: millet products; social media interaction; confirmation; customer repurchase intention; satisfaction.
  DOI: 10.1504/IJSAMI.2024.10064123
   
  
• An overall indicator for assessing the innovation level in the dairy industry sector. The case of Greek dairy cooperatives  
  by Athina Charalampidou, Panagiota Sergaki, Anastasios Michailidis 
  Abstract: This paper attempts to empirically investigate the degree of innovation in dairy industries using an overall innovation indicator. Innovations were identified through the literature review. A questionnaire was distributed to industry experts who held senior positions in or were academically relevant to dairy industries, for evaluation. The innovations identified were grouped into six sections: production, marketing, dairy organisation, quality control, storage/distribution and milk zone. The integrated questionnaire was used to collect information on the adopted innovations from two cooperative dairy industries in Greece. An overall innovation indicator was applied to the six departments of each dairy industry and a degree of innovation was derived for each of them. The innovation indicator revealed that the marketing and quality control departments were more innovative. Besides, none of the cooperative dairies approached the maximum degree of innovation adoption in all six departments.
  Keywords: overall innovation indicator; innovation measurement; dairy industries; cooperatives; evaluation innovation in dairy industry; Greece.
  DOI: 10.1504/IJSAMI.2024.10064445
   
  
• Innovations and green development: are a way out for the small and medium enterprises of the Western Macedonia Region  
  by Georgios Maggiridis, Fotios Chatzitheodoridis, Efstratios Loizou 
  Abstract: The study aims to assess the difficulties faced by SMEs in the region of Western Macedonia during the previous five years and to highlight their possible way out through innovations and green development. For this purpose, a questionnaire was used, which was drawn up for data collection by the SMEs of the region. According to the results of the survey, the shock of the energy transition, the economic crisis and the COVID-19 virus dramatically limited and stopped the development of SMEs in Western Macedonia. the investments in innovation and green development that significantly increasing the last few years in the area are related mainly to multinational enterprises and less to the SMEs. The role of the SMEs could be mainly supporting these large energy companies through trading activities and more significantly in the primary sector to the fields of bio and new cultivations, and bio and traditional products.
  Keywords: small and medium enterprises; innovation; green development; Western Macedonia Region; renewable energy.
  DOI: 10.1504/IJSAMI.2024.10064455
   
  
• Drivers and barriers to the adoption of digital farming technology: evidence from Nigeria  
  by Andrew A. Achille, Vivek K. Velamuri 
  Abstract: Rising concerns about food security, labour shortages, consumer preferences, and climate change have increased interest in how to efficiently use farm resources and promote sustainable agriculture. The introduction of digital technologies and data applications in agriculture offers a potential solution to these problems, but their adoption among farmers is remarkably low, and uncertainties exist about their use. This research seeks to identify the most practical and logical explanation of the factors influencing the adoption of digital farming technologies in Nigeria by using qualitative data from semi-structured interviews and focus group discussions. Our study shows that farmers are optimistic about the technology. The main drivers of the adoption of digital farming technology are the perceived value of the technology and the farmer’s social influences. The barriers to adoption are identified as human factors, technical hurdles, cost and infrastructure hurdles, and the limited provision of training and support.
  Keywords: digital farming technology; technology adoption; agricultural efficiency; drivers and barriers; sustainable agriculture; farmers; Nigeria.
  DOI: 10.1504/IJSAMI.2024.10064884
   
  
• Evaluating dimensionality reduction strategies on mixed-type datasets: a comparative analysis using Python, R and SPSS  
  by Zacharenia Kyrana, Emmanouil D. Pratsinakis, Nikolaos Papafilippou, Angelos Markos, Christos Dordas, George C. Menexes 
  Abstract: Multidimensional and multivariate datasets encompassing diverse data types provide researchers a platform to apply a range of dimensionality reduction methods. This study assessed principal components analysis, factor analysis, multiple correspondence analysis, categorical principal components analysis and factor analysis for mixed data. We examined different strategies based on input variable measurement scale selection and variable value coding. The objectives were to highlight the importance of applying different analysis strategies, ascertain the applicability of these methods to multidimensional mixed-type data, compare outcomes, and evaluate execution times from three different statistical software to identify notable computational and interpretive drawbacks. drawbacks. Significant issues included the curse of dimensionality concerning the determination of crucial dimensions, the need for increased computing power, the absence of software code for some methods and criteria, discrepancies in results calculations across software packages, and the inability of some software packages to handle numerous variables or binary-coded variables and perform parallel analysis.
  Keywords: multivariate data; principal components analysis; factor analysis; multiple correspondence analysis; categorical principal components analysis; factor analysis for mixed data; dimensionality reduction.
  DOI: 10.1504/IJSAMI.2024.10065202
   
  
• Organisation and management of beekeeping parks and the contribution of their infrastructure  
  by Georgios Kolkos, Apostolos Kantartzis, Symeon Marnasidis, Christos Charizanis, Christina Moulogianni, Garyfallos Arabatzis 
  Abstract: Honey bees play a crucial role in both natural and agricultural ecosystems worldwide by pollinating various crops. In Greece, beekeeping is predominantly nomadic and serves as a significant source of supplementary income for many. However, there’s a need for tailored land management policies to support and promote the apiculture sector, including adaptations in the National Forest Policy to facilitate beekeeping activities. While Greek legislation offers some flexibility regarding apiary placement on public lands, there’s a lack of regulations regarding designated placement sites. To address these issues, the establishment of especially demarcated beekeeping parks is proposed. These parks would not only provide beekeepers with designated spaces to increase production and lower costs but also contribute to organising beekeeping activities more effectively both nationally and internationally. Such measures are crucial for ensuring the sustainability and prosperity of beekeeping ventures in Greece and beyond.
  Keywords: beekeeping parks; forest roads; infrastructures; organisation; management; land use planning.
  
  
• Agricultural finance dynamics in Bangladesh: exploring factors influencing rice yield and farmers access to credit  
  by Rozina Yeasmin, Babor Ahmad, Shuktara Khanom, Md. Shakiul Hossain, Mohammad Main Uddin, Shahiduzzaman Selim, Anowar Hossain, Ashrafuzzaman Sohag 
  Abstract: This study examines factors influencing Bangladeshi farmers acceptance of agricultural financing and the impact of credit on rice output. Through a comprehensive survey involving 255 rice producers and utilising logistic regression and the Cobb-Douglas production function, the study identifies key determinants affecting rice yield among farmers utilising formal and informal credit, as well as those without credit. Factors such as household characteristics, land ownership, inputs (e.g., seeds and irrigation), and proximity to markets significantly influence rice productivity. Additionally, the study underscores the importance of unauthorised lending sources in facilitating higher-than-average rice yields and emphasises critical determinants - like age, education, experience, household size, and landholding - for farmers access to financing. The result also reveals that credit amount significantly influences rice production, with an average incremental positive effect of 12.60%. For formal credit holders, this effect is estimated at 14.4%, while for informal credit access, it is predicted to be 20.10%. These findings offer insights into enhancing agricultural credit accessibility and emphasise the role of informal credit sources in driving agricultural productivity.
  Keywords: agricultural credit; rice producer; productivity; formal credit; informal credit; Bangladesh.
  DOI: 10.1504/IJSAMI.2024.10065697
   
  
• Cultural and landscape elements in the integrated local development strategies  
  by Maria Paschalidou, Fotios Chatzitheodoridis, Achilleas Kontogeorgos, Athanasia Mavrommati 
  Abstract: The purpose of our research it is a first approach to identify how cultural landscapes are promoted, included, and developed in common agricultural policies. The major role of cultural landscape policy should be to bring social cohesion, to enhance prosperity and succeed integrated local development. The cultural policies of the rural landscape are a demanding and complex task, because of a mixture of globalisation, local history and tradition, and the current local political context. The findings show that, in terms of both output and income, the regional economy has not yet benefited from the adoption of the Pillar II policy initiatives about culture of rural landscape.
  Keywords: rural landscape; cultural heritage; regional development; culture; values; cultural landscape; rural space; Pillar II; policy impacts.
  
  
• A spatial data image processing model using unmanned aerial vehicles and RGB imagery for crop farming on small-scale subsistence farms  
  by Basuti Gerty Bolo, Irina Zlotnikova, Dimane Mpoeleng 
  Abstract: This paper presents a spatial data image processing model using unmanned aerial vehicles (UAVs) equipped with RGB cameras for enhancing agricultural productivity on small-scale subsistence farms in semi-arid regions of Botswana. The model leverages high-resolution UAV imagery (0.19 cm/pixel) to transform raw, non-spatial complex data into actionable geospatial information. It integrates machine learning algorithms, including unsupervised ISODATA and supervised support vector machine (SVM) classifiers, with proposed new RGB-based vegetation indices, to extract detailed information on crop types, land use, and coverage. The research addresses the challenges faced by smallholder farmers, such as limited access to advanced technologies and fluctuating environmental conditions. This model facilitates improved agricultural decisions and productivity by providing a cost-effective and accurate method for monitoring and managing crops through localised data capture and advanced data processing techniques. Results demonstrate an overall classification accuracy of 82.5% with the ISODATA algorithm, proving its utility in precision agriculture tailored for resource-limited settings. The study underscores the potential of integrating UAV technology with machine learning to support sustainable agriculture in developing regions.
  Keywords: unmanned aerial vehicles; UAVs; RGB imagery; small-scale subsistence farming; spatial data processing; crop monitoring; machine learning; vegetation indices; ISODATA; support vector machine; SVM; accuracy assessment; precision agriculture.
  
  
• Hyperledger Fabric blockchain-based secured framework for agricultural IoT data  
  by Neenu Johnson, M.B. Santosh Kumar, T. Dhannia 
  Abstract: Agricultural internet of things (IoT) data is a significant digital asset and requires to be securely shared and effectively analysed to enhance productivity, optimise resource usage, achieve sustainability, and support the economic development of the nation. Agricultural IoT data gathered from various connected devices and sensors deployed in agricultural environments primarily involves data related to crop monitoring, soil health, weather patterns, and other relevant factors. The successful adoption of IoT revolutionises agrarian society and enhances the livelihood of farmers. Agricultural IoT data has an inherent sensitivity that emphasises the requirement of a secured IoT data sharing platform. A secured data sharing and storage platform for agricultural IoT data that leverages the benefits of blockchain, and Node-Red is proposed. The proposed framework facilitates the secured storage and exchange of agricultural IoT data among various agricultural stakeholders.
  Keywords: internet of things; IoT; Hyperledger Fabric; sensors; Raspberry Pi 4; Node-Red; agriculture; blockchain; smart contract.
  
  
• Integrating UTAUT3 and DM ISS 2016 theory: a proposed framework for identifying determinants and successful factors in agricultural information systems  
  by Hafni Amalia Juniarti, Alia Bihrajihant Raya, Subejo, Rahima Kaliky, Siti Andarwati 
  Abstract: The usage of agricultural information systems must be determined based on a literature review of characteristics that depend on user behaviour and the success of information systems. The methodology applied in this paper is a narrative review. The review used the search, appraisal, synthesis, and analysis (SALSA) methodology to integrate or synthesise data relevant to the review topics. Twenty-two adoption innovation theories contribute to theoretical research and are appropriately utilised. The simplest model that presumably evolves to determine behavioural intention in the adoption information system in agriculture is the Unified Theory of Acceptance and Use of Technology (UTAUT). Examining successful information systems is DeLone and McLeans as pioneers for the information system (DM ISS). The UTAUT and DM ISS research in the 2017-2023 agricultural adoption innovation period is described in related studies. The merger of UTAUT3 and DM ISS 2016 could be presented as complementary theories focusing on intention variables and successful agricultural information system usage behaviour.
  Keywords: adoption; UTAUT; DM ISS; agricultural information systems; SALSA methodology; adoption innovation; complementary theories.
  
  
• From consumerism to contentment! The role of minimalism in promoting well-being: a moderated mediation approach  
  by Varghese Joy, Vijay Kumar Jain, Ashwin H. Parwani, Vijay Prakash Anand, Preeti Sharma 
  Abstract: Current consumption behaviours have resulted in environmental deterioration, which endangers the underlying processes that underpin our future development and existence. There is a need to adopt new consumption habit is that are environmentally friendly and have a positive impact on consumers. As a result, the current study has proposed a framework to examine the impact of minimalism on consumer well-being using survey data from a representative Indian population. It also tests the mediating role of satisfaction and happiness and mediated moderated role of environmental knowledge. The SMARTPLS results show a favourable association between minimalism and well-being. The study supports the mediation of satisfaction and happiness in the aforementioned relationship. Marketers can capitalise on the growing trend of minimalism and it is link to well-being to attract new segments of consumers wanting a more balanced and intentional existence. This expanding customer demographic is increasingly drawn to brands that value quality over quantity, sustainability, and transparency.
  Keywords: mindfulness and self-care; holistic well-being; sustainability; sparse aesthetics; voluntary simplicity; pro-environmental consumption.
  
  
• Utilising the potential of circularity: novel strategies for minimising food loss and waste in the circular economy  
  by ShivamKrishn Agrawal, Shrish Singh, Akhilesh Shukla, Bipin Kandpal 
  Abstract: This study examines novel strategies to tackle food loss and waste in the food industry, with a focus on resource efficiency and sustainability. It aims to promote sustainability in the food sector by applying circular economy principles. The research prioritises agri-food industry circular practice drivers using literature review and expert opinions. The methodology uses interpretive structural modelling and analytic hierarchy process to rank fourteen key drivers from a comprehensive literature survey. The findings suggest that policy factors, such as favourable legislation and accurate demand forecasting, are of paramount significance. Additional notable factors contributing to the overall progress are water recycling, the integration of renewable energy, and the use of sustainable packaging. The study emphasises the crucial importance of systemic methodologies and cooperation among stakeholders in circular food supply chains. The framework contributes by offering an organised plan for drivers, policy recommendations, and future research directions to advance circularity in agri-food systems.
  Keywords: circular economy; sustainable food packaging; food waste; water recycling; carbon footprint reduction.
  
  
• M-Velanmai: fuzzy artificial immune network model-based mobile application for plant protection in rice and its users evaluation  
  by C. Karthikeyan, S. Pazhanivelan, S. Aravindh Kumar, Smitha S. Kumar 
  Abstract: The fuzzy artificial immune network (FAINet) model was developed for rice pest and disease identification, utilising deep learning techniques and trained on a dataset of 19,642 images collected directly from rice fields. These images were pre-processed, and transfer learning was employed to optimise model performance. The FAINet model showed a strong negative correlation between training steps and both training and validation loss (0.86 and 0.94), while a positive correlation (0.92) was observed with training accuracy. The confusion matrix confirmed the models strong performance in accurately identifying all major rice pests. FAINet achieved an overall prediction accuracy of 99.10% and a test accuracy of 98.50%, surpassing other models. Integrated into the M-Velanmai mobile app, FAINet automates the identification of rice pests, disorders, and diseases. Feedback from 510 M-Velanmai app users indicated a predominantly positive perception regarding the effectiveness of pest management advisories, highlighting FAINets ability to deliver timely and reliable solutions.
  Keywords: ‘M-Velanmai’ app; fuzzy artificial immune network; FAINet; convolutional neural network; CNN; neural network; automated pest identification; training loss; model performance; feedback; advisories; rice and evaluation.
  
  
• Sustainability benchmarking in HEIs: best practices and future trends  
  by Dimitra B. Manou, Odysseas Christou, Anastasia Blouchoutzi, Eduardo Franco, Stefano Armenia, Juan Uribe Toril, Jose Luis Ruiz Real 
  Abstract: The UN 2030 Agenda sets an ambitious framework for all countries and actors, state and non-state, and calls for them to align their development perspectives with the sustainable development goals (SDGs). Higher education institutions (HEIs) have an important role to play in fulfilling SDG 4 Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all. Target 4.7 requires mainstreaming of sustainable development in national policies, curricula, and assessment tools. This paper analyses the development and implementation of appropriate mechanisms and tools in HEIs sustainability benchmarking and identifies best practices for institutional sustainability self-assessment tools under the lens of the whole institution approach. It presents most prominent self-assessment tools for sustainability benchmarking applied by HEIs, which could lead to sustainable and energy-efficient universities. Finally, it explores future trends in higher education sustainability benchmarking. The analysis and results may offer a new perspective to academic research in this field.
  Keywords: sustainability; higher education; assessment tools; higher education institutes; HEIs; sustainability benchmarking; whole-institution approach; sustainable education; sustainable development goals; SDGs; energy-efficient universities; green universities.
  
  
• Does responsible consumption lead to consumer well-being? An empirical study exploring generation Z perspective using sustainable consumption theory  
  by Aditi, Akhilesh Shukla, Shivendra Singh, Shriram S. Dawkhar, Shipra Agarwal 
  Abstract: The astonishing consumption levels have a significant impact on the ecosystem and biodiversity. The rapidly diminishing resources and a deteriorating environment are forcing new consumption patterns and casting doubt on the notion that consumers are making logical choices. Therefore, the goal of the current research is to identify the factors that contribute to responsible consumption. It further examines the impact of responsible consumption on consumer well-being. The current study has taken four exogenous variables, namely: sustainable living, redefining consuming mind-set, perception of fair trade and circular consumption. The model was investigated and validated using data from 500 respondents via structural equation modelling. The most significant antecedent to responsible consumption, after redefining consumption attitude, is circular consumption. The findings of the study will help marketers to develop strategies to encourage responsible purchasing among consumers, thereby, improving their well-being and creating positive impact on society. From an environmental perspective, encouraging responsible consumption will result in less resource depletion, smaller carbon footprints, and improved sustainability practices across businesses.
  Keywords: responsible consumption; decarbonisation; circular consumption; linear economy; carbon-footprint; sustainable purchasing.
  
  
• Optimised polyculture vertical farming: harnessing IoT and machine learning for enhanced crop rotation strategies  
  by Nissi Grace A. Coronel, John Eric L. Espion, Daryll C. Maldicas, John Joshua F. Montañez 
  Abstract: This study developed a polyculture vertical system with crop rotation recommendations. The crop monitoring system was implemented using sensors to monitor soil pH, soil moisture, NPK levels, temperature, and humidity. Z-test was utilised as a statistical method to assess and evaluate the performance and effectiveness of the sensors. The developed system involved training and testing of three machine learning models that gave recommendations on the best crops to be grown. They included K-nearest neighbours (KNN), random forest, and extreme gradient boosting (XGBoost). Performance was measured on the basis of four metrics namely, Precision, Recall, F1-Score, and Accuracy with respect to the three machine learning models. In terms of the crop recommendation system, the XGBoost algorithm emerged as the top-performing model, delivering a maximum mean accuracy of 91.26%, compared to 88% and 91.16% of KNN and random forest, respectively.
  Keywords: algorithm selection; extreme gradient boosting; XGBoost; infinite agriculture; internet-of-things; K-nearest neighbours; KNN; machine learning algorithms; plant polyculture; random forest.
  DOI: 10.1504/IJSAMI.2024.10068121
   
  
• Evaluation and enhancement of accessibility of forest areas through the road network for conducting firefighting operations via GIS and fire susceptibility analysis  
  by Georgios Kolkos, Anastasia Stergiadou, Apostolos Kantartzis, Stergios Tampekis, Garyfallos Arabatzis 
  Abstract: Managing wildfires relies on comprehensive prevention studies and decision-making plans, with the forest road network serving as the primary means for ground firefighting forces. This research establishes a multi-criteria assessment and improvement system for forest areas accessibility, enhancing firefighting operations. Criteria like hiking time, distance from the road network, and terrain topography determine accessibility. Using the analytical hierarchy process (AHP) and spatial analysis considering slope, aspect, fuel type, and distances from human infrastructure, high fire risk areas are identified. This insight led to designing new roads in critical zones to enhance firefighting effectiveness. Re-evaluating accessibility post-road design demonstrates the percentage improvement achieved. Applied in mountainous, mid-altitude, and suburban Mediterranean forest ecosystems, this methodology offers guidelines for real-world forest management, enhancing the sustainability and resilience of forest ecosystems.
  Keywords: forest firefighting; wildfire prevention; forest roads planning; decision support system; analytical hierarchy process; AHP; multicriteria analysis.
  DOI: 10.1504/IJSAMI.2024.10062068
   
  
• Enhancing crop yield prediction through machine learning regression analysis  
  by Seema Sharma, Anupriya Jain, Sachin Sharma, Pawan Whig 
  Abstract: The economic prosperity of any nation hinges significantly on its agricultural output, a cornerstone of sustained growth. The integration of advanced technology plays a pivotal role in enhancing agricultural productivity. Farmers today are leveraging breakthroughs in data mining, the internet of things (IoT), artificial intelligence (AI), and machine learning to optimise their practices. This paper is dedicated to the exploration of this transformative field, offering insights into its multifaceted applications. It delves into the assessment of diverse parameters to facilitate the cultivation of specific crops in a given region. Moreover, it collaborates closely with farmers, tailoring these parameters to maximise crop yields and diversify agricultural produce. The study also incorporates the deployment of AI algorithms, such as logistic regression and multiple regressions, to bolster decision-making processes in agriculture.
  Keywords: agriculture; artificial intelligence; logistic regression; machine learning; data mining.
  DOI: 10.1504/IJSAMI.2025.10067961
   
  
• Water quality index prediction using artificial neural network: a case study of Selangor River, Malaysia  
  by Jia Jun Tan, Senthil Kumar Arumugasamy, Fang Yenn Teo 
  Abstract: Rapid urban development often leads to deterioration of river water quality, and water quality index (WQI) is a number that represents the water quality of a water body. According to Department of Environment, Malaysia parameters used to calculate WQI are dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), potential of hydrogen (pH), suspended solids (SS) and ammoniacal nitrogen (AN). Data was collected from the ASEAN Working Group on Water Resources Management website in Sungai-Selangor section. Two ANN models were developed; a prediction model to predict the current WQI, and a forecasting model to predict the future WQI. The prediction model gave good results with very low overall root mean squared error (1.15), an excellent overall regression value (0.97874), and a high correlation with the actual WQI (99.94%). The forecasting model did not provide good result with the overall RMSE of 4.80 and overall regression value of 0.752.
  Keywords: artificial neural networks; ANNs; water quality index; WQI; dissolved oxygen; DO; biochemical oxygen demand; BOD; chemical oxygen demand; COD; potential of hydrogen; pH; suspended solids; SS; ammoniacal nitrogen; AN; Malaysia.
  DOI: 10.1504/IJSAMI.2025.10067962
   
  
• Circular economy! Sustainable growth and achieving zero net emissions - a way ahead for building sustainable tomorrow by optimising consumption  
  by ShivamKrishn Agrawal, Vijay Kumar Jain, Hemraj Verma 
  Abstract: The concept of a circular economy has received an increasing amount of focus in recent years due to its potential as a means to achieve long-term economic sustainability. The current study applies the interpretive structural modelling (ISM) methodology to investigate the complex relationships between a total of 16 key variables from the literature that affect circular economy efforts. The findings imply that initiatives to advance technological know-how, awareness, resource sharing, recycling and reuse, and reverse logistics may have a substantial influence on the circular economy. As organisations seek to enhance their sustainability efforts, these insights can guide decision-makers in formulating effective strategies that harness technological advancements, optimise logistics operations, and raise awareness to foster a circular economy that benefits both the environment and society. This research based on ISM theory adds clarity on what helps spread the concept of a circular economy. It offers significant fresh insights for marketers and policy-makers.
  Keywords: circular economy; circular infrastructure; zero carbon emission; product utility; resources optimisation; frugal innovation.
  DOI: 10.1504/IJSAMI.2024.10062874
   
  
• How digitalisation affects agricultural progress in Azerbaijan: evidence from panel data approach  
  by Mirvari Kh. Gazanfarli 
  Abstract: This study focuses on measuring the impacts of digital transformation on agricultural productivity in Azerbaijan. To realise the set goal, ICT characteristic indicators, including the infrastructural and human provision of ICT in agricultural enterprises, were identified, and 14 economic regions were investigated based on these factors in Azerbaijan within 2019-2021. Due to data structure, three static panel data models (POLS, REM, and FEM) were built for designing this process. Diagnostic tests analysis proved that the random effect model characterises these effects much more than others. The estimations and simulations concluded that the number of employees who used the internet in agricultural enterprises is associated negatively with the general product of agriculture in Azerbaijan. However, web page usage, software development, and the expenses of ICT infrastructure in the enterprises help to increase the productivity of the agricultural field of Azerbaijan's economy.
  Keywords: agricultural enterprises; digital agriculture; economic regions; measurement indicators; diagnostic analysis; panel data analysis.
  DOI: 10.1504/IJSAMI.2024.10063983
   
  
• Integrating sustainable coastal tourism and aquaculture principles into higher education curricula: a comprehensive literature review  
  by Sofia K. Gkarane, Dimitra B. Manou 
  Abstract: Education can play a key role in achieving Goal 14 of the Sustainable Development Goals (SDGs) by raising awareness of the importance of sustainable aquaculture and coastal tourism practices. Despite the global recognition of the importance of the SDGs and their significance in promoting the sustainable development of oceans, seas, and marine resources as well as the role of education in achieving these goals, only a few studies have focused on aquaculture and coastal tourism in higher education. The aim of this paper is to provide a comprehensive literature review that examines the current status of education in higher education institutions (HEIs) with regard to aquaculture and coastal tourism. Through an analysis of papers published between 2000 and 2023, this study offers a starting point for more discussion and also offers a conceptual framework, thus providing a basis for further research on the integration of sustainable coastal tourism and aquaculture principles into higher education curricula. Opportunities, implications and future research directions to enhance the role of HEIs in fostering a more sustainable coastal tourism and aquaculture sector are also discussed.
  Keywords: higher education; coastal tourism; aquaculture; Sustainable Development Goals; SDGs; oceans; higher education institutions; HEIs.
  DOI: 10.1504/IJSAMI.2024.10062873