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The pressing issues of climate change and environmental degradation call for a reevaluation of how we approach economic activities. Both leaders and corporations are now shifting their focus, toward adopting practices and embracing the concept of circular economy (CE). Within this context, the Food and Beverage (F&B) sector, which significantly contributes to greenhouse gas (GHG) emissions, holds the potential for undergoing transformations. This study aims to explore the role that Artificial Intelligence (AI) can play in facilitating the adoption of CE principles, within the F&B sector.

This research employs the Best Worst Method, a technique in multi-criteria decision-making. It focuses on identifying and ranking the challenges in implementing AI-driven CE in the F&B sector, with expert insights enhancing the ranking’s credibility and precision.

The study reveals and prioritizes barriers to AI-supported CE in the F&B sector and offers actionable insights. It also outlines strategies to overcome these barriers, providing a targeted roadmap for businesses seeking sustainable practices.

This research is socially significant as it supports the F&B industry’s shift to sustainable practices. It identifies key barriers and solutions, contributing to global climate change mitigation and sustainable development.

The research addresses a gap in literature at the intersection of AI and CE in the F&B sector. It introduces a system to rank challenges and strategies, offering distinct insights for academia and industry stakeholders.

The objective of this study is to examine the various factors that exert an influence on the green economy. This study also investigates the impact of foreign direct investment (FDI) on the Malaysian economy, specifically focusing on its position as a mediator. This research also examines the correlation between FDI and its influence on the contemporary green economy.

The authors employed quantitative methodologies and a self-administered survey to evaluate data and derive a definitive conclusion. The result was constructed using SPSS and SEM-PLS as the analytical software.

The study reveals that technological advancement, investment country and government policy significantly and positively affect the green economy, catalyse SDG goals and restructure the economy in better shape.

The current empirical research bridges the research gap in the context of technology advancement in government policy from emerging economies by exploring important factors, proposing their impact on the performance of the green economy, and empirically testing those hypothesized relationships. This study deciphers that FDI influences the green economy, where the investment country plays a significant role. Also, for a graphical presentation of this abstract, see the online appendix.

This study aims to examine the effects of climate change and agricultural technologies on crop production in Vietnam for the period 1990–2018.

Several econometric techniques – such as the augmented Dickey–Fuller, Phillips–Perron, the autoregressive distributed lag (ARDL) bounds test, variance decomposition method (VDM) and impulse response function (IRF) are used for the empirical analysis.

The results of the ARDL bounds test confirm the significant dynamic relationship among the variables under consideration, with a significance level of 1%. The primary findings indicate that the average annual temperature exerts a negative influence on crop yield, both in the short term and in the long term. The utilization of fertilizer has been found to augment crop productivity, whereas the application of pesticides has demonstrated the potential to raise crop production in the short term. Moreover, both the expansion of cultivated land and the utilization of energy resources have played significant roles in enhancing agricultural output across both in the short term and in the long term. Furthermore, the robustness outcomes also validate the statistical importance of the factors examined in the context of Vietnam.

This study provides persuasive evidence for policymakers to emphasize advancements in intensive agriculture as a means to mitigate the impacts of climate change. In the research, the authors use average annual temperature as a surrogate measure for climate change, while using fertilizer and pesticide usage as surrogate indicators for agricultural technologies. Future research can concentrate on the impact of ICT, climate change (specifically pertaining to maximum temperature, minimum temperature and precipitation), and agricultural technological improvements that have an impact on cereal production.

To the best of the authors’ knowledge, this study is the first to examine how climate change and technology effect crop output in Vietnam from 1990 to 2018. Various econometrics tools, such as ARDL modeling, VDM and IRF, are used for estimation.

This study aims to explore the smallholder farmers’ perceptions of climate change and its adaptation options (changing crop variety; improved crop and livestock; soil and water conservation [SWC]; and irrigation practices) and drought indices in the Dire Dawa Administration Zone, Eastern Ethiopia.

A cross-sectional household survey was used. A structured interview schedule for respondent households for key informants and focus group discussions were used. This study used both descriptive statistics and an econometric model. The model was used to compute the determinants of climate adaptation options in the study area. Drought characterization was carried out by DrinC software.

The results revealed households adapted to selected adaptation options. The model results confirmed that education level, farm size, tropical livestock units (TLUs) and access to agricultural extension services have positive and significant impacts on changing crop variety by 0.0014%, 0.045%, 0.032% and 0.035%, respectively. The likelihood of farmers’ decisions to use adaptation strategies (family size, TLU, agricultural extension service and distance from the market) has positive and significant impacts on SWC. The reconnaissance drought index (RDI6) of ONDJFM and AMJJAS showed extreme and severe drought index values of −2.88 and −1.96, respectively.

This study used a locally adopted climate change adaptation intervention for smallholder farmers, revealing the importance of drought characterization indices both seasonally and annually.

Despite the vast potential of mobile phone use, grape smallholder farmers’ satisfaction with mobile phone use has attracted insufficient attention among scholars in Tanzania. The study examined factors influencing satisfaction with mobile phone use for accessing agricultural marketing information.

The study used a cross-sectional research design and a mixed research method. Structured questionnaire and focus group discussions were used to collect primary data from 400 sampled grape smallholder farmers. Data were analysed inferentially involving two-way analysis of variance, ordinal logistic regression and thematic analysis.

The findings indicate a statistically significant disparity in grape smallholder farmers’ satisfaction across different types of agricultural marketing information. Grape smallholder farmers exhibited higher satisfaction levels concerning information on selling time compared to all other types of agricultural marketing information (price, buyers, quality and quantity). Factors influencing grape smallholder farmers’ satisfaction with mobile phone use were related to perceived usefulness, ease of use, experience and cost.

This study contributes to scientific knowledge by providing actionable insights for formulating unique strategies for smallholder farmers’ satisfaction with agricultural marketing information.

Time of flight (ToF) imaging is a promising emerging technology for the purposes of crop identification. This paper aim to presents localization system for identifying and localizing asparagus in the field based on point clouds from ToF imaging. Since the semantics are not included in the point cloud, it contains the geometric information of other objects such as stones and weeds other than asparagus spears. An approach is required for extracting the spear information so that a robotic system can be used for harvesting.

A real-time convolutional neural network (CNN)-based method is used for filtering the point cloud generated by a ToF camera, allowing subsequent processing methods to operate over smaller and more information-dense data sets, resulting in reduced processing time. The segmented point cloud can then be split into clusters of points representing each individual spear. Geometric filters are developed to eliminate the non-asparagus points in each cluster so that each spear can be modelled and localized. The spear information can then be used for harvesting decisions.

The localization system is integrated into a robotic harvesting prototype system. Several field trials have been conducted with satisfactory performance. The identification of a spear from the point cloud is the key to successful localization. Segmentation and clustering points into individual spears are two major failures for future improvements.

Most crop localizations in agricultural robotic applications using ToF imaging technology are implemented in a very controlled environment, such as a greenhouse. The target crop and the robotic system are stationary during the localization process. The novel proposed method for asparagus localization has been tested in outdoor farms and integrated with a robotic harvesting platform. Asparagus detection and localization are achieved in real time on a continuously moving robotic platform in a cluttered and unstructured environment.

This study aims to evaluate how the criteria of sustainability standards (SS) ensure the social dimension of corporate sustainability (CS) in rural entrepreneurships using the case of banana agribusinesses in Magdalena (Colombia).

The methodological design was quantitative, explanatory and cross-sectional, where a sample of banana producers from Magdalena (Colombia) was selected. A structural equation model (SEM) was developed to evaluate the hypotheses. The SEM goodness-of-fit and fit indices were all acceptable.

There is a strong and statistically significant correlation between SS criteria and the social dimension of CS. In particular, local development is the most influential factor in shaping CS in the context of banana agribusinesses in Magdalena, Colombia, operating as rural entrepreneurship. Meanwhile, working conditions and human rights show moderate effects, while labor rights do not have a perceptible impact.

Only the SS criteria that ensure the social dimension of CS in the banana agribusinesses of Magdalena (Colombia) were considered. It is important to note that other variables may be involved in ensuring CS. Future research to identify these possible variables is recommended.

This investigation explores an understudied issue within the CS sphere, explicitly focusing on rural entrepreneurship in developing countries, notably Colombia. The study scrutinizes the impact of SS on the social dimension of CS in rural environments, using banana cooperatives as a case study and highlighting the value of developing strategies to help improve the CS performance of this type of organization.

El objetivo de esta investigación es evaluar cómo los criterios de los Estándares de Sostenibilidad (SS) aseguran la dimensión social de la Sostenibilidad Corporativa (CS) en los emprendimientos rurales utilizando el caso de los agronegocios bananeros en Magdalena (Colombia).

El diseño metodológico fue cuantitativo, explicativo y transversal, donde se seleccionó una muestra de productores bananeros del Magdalena (Colombia). Se desarrolló un modelo de ecuaciones estructurales (SEM) para evaluar las hipótesis. Los índices de bondad de ajuste y ajuste del SEM fueron aceptables.

existe una correlación fuerte y estadísticamente significativa entre los criterios de SS y la dimensión social de la SC. En particular, el desarrollo local aparece como el factor más influyente en la conformación de la SC en el contexto de las agroempresas bananeras de Magdalena, Colombia, que operan como empresas rurales. Mientras tanto, las condiciones de trabajo y los derechos humanos muestran efectos moderados, mientras que los derechos laborales no parecen tener un impacto perceptible.

sólo se consideraron los criterios de SS que aseguran la dimensión social de la SC en los agronegocios bananeros de Magdalena (Colombia). Es importante señalar que otras variables pueden estar involucradas en el aseguramiento de la CS. Se recomiendan futuras investigaciones para identificar estas posibles variables.

Esta investigación explora un tema poco estudiado dentro de la esfera de la Sostenibilidad Corporativa (SC), centrándose explícitamente en el empresariado rural en los países en desarrollo, en particular Colombia. El estudio analiza el impacto de los Estándares de Sostenibilidad (SS) en la dimensión social de la SC en entornos rurales, utilizando las cooperativas bananeras como caso de estudio y resaltando el valor de desarrollar estrategias que ayuden a mejorar el desempeño en SC de este tipo de organizaciones.

O objetivo desta pesquisa é avaliar como os critérios dos Padrões de Sustentabilidade (SS) garantem a dimensão social da Sustentabilidade Corporativa (SC) em empreendimentos rurais usando o caso das agroindústrias de banana em Magdalena (Colômbia).

O desenho metodológico foi quantitativo, explicativo e transversal, onde foi selecionada uma amostra de produtores de banana de Magdalena (Colômbia). Foi desenvolvido um modelo de equação estrutural (SEM) para avaliar as hipóteses. Os índices de adequação e de ajuste do SEM foram todos aceitáveis.

existe uma correlação forte e estatisticamente significativa entre os critérios de SS e a dimensão social da SC. Em particular, o desenvolvimento local aparece como o fator mais influente na formação da SC no contexto dos agronegócios da banana em Magdalena, Colômbia, que operam como empresas rurais. Entretanto, as condições de trabalho e os direitos humanos apresentam efeitos moderados, enquanto os direitos laborais não parecem ter um impacto percetível.

apenas foram considerados os critérios de SS que garantem a dimensão social da SC nas agroindústrias da banana de Magdalena (Colômbia). É importante notar que outras variáveis podem estar envolvidas na garantia da SC. Recomenda-se a realização de investigação futura para identificar estas possíveis variáveis.

Esta investigação explora uma questão pouco estudada no âmbito da Sustentabilidade Empresarial (SC), focando explicitamente o empreendedorismo rural nos países em desenvolvimento, nomeadamente na Colômbia. O estudo examina o impacto dos Padrões de Sustentabilidade (SS) na dimensão social da SC em ambientes rurais, utilizando cooperativas de banana como estudo de caso e destacando o valor do desenvolvimento de estratégias para ajudar a melhorar o desempenho da SC deste tipo de organização.

Jubail Industrial City is one of the largest industrial centers in the Middle East, offering potential opportunities for renewable energy generation. This research paper presents a comprehensive analysis of the wind resources in Jubail Industrial City and proposes the design of a smart grid-connected wind farm for this strategic location.

The study used wind data collected at three different heights above ground level – 10, 50 and 90 m – over four years from 2017 to 2020. Key parameters, such as average wind speeds (WS), predominant wind direction, Weibull shape, scale parameters and wind power density (WPD), were analyzed. The study used Windographer, an exclusive software program designed to evaluate wind resources.

The average WS at the respective heights were 3.07, 4.29 and 4.58 m/s. The predominant wind direction was from the north-west. The Weibull shape parameter (k) at the three heights was 1.77, 2.15 and 2.01, while the scale parameter (c) was 3.36, 4.88 and 5.33 m/s. The WPD values at different heights were 17.9, 48.8 and 59.3 W/m², respectively.

The findings suggest that Jubail Industrial City possesses favorable wind resources for wind energy generation. The proposed smart grid-connected wind farm design demonstrates the feasibility of harnessing wind power in the region, contributing to sustainable energy production and economic benefits.

This study aims to examine the value orientations of New Zealand agribusiness investors and how these orientations influence their reactions to the environmental and social implications of agribusinesses.

In the context of the New Zealand agricultural sector, the views of investors as published in print and broadcast media between 2018 and 2022 are gathered. The study uses qualitative content analysis to analyse the data. The study is based on the value-belief-norm theory.

The study reveals that New Zealand agribusiness investors express concern about the environmental (biospheric) and social (altruistic) impacts of the agribusiness sector, prompting calls for greater transparency, climate adaptation and ethical investment options. Additionally, they actively support local businesses to benefit their communities and preserve cultural heritage. Despite these biospheric and altruistic tendencies, investors also prioritise financial and non-financial interests (egoistic). This highlights a nuanced perspective guiding their investment choices – a balance between self-interest and contributing to the greater good. This signals a shift towards socially and environmentally responsible investment practices driven by multifaceted values.

The findings of this study highlight the role of non-pecuniary motives, like values, in determining the relevance of environmental and social information.

The study’s findings offer insight to agribusinesses on how investors’ value orientations shape their investment decisions. This understanding can guide businesses in framing a reporting strategy that enhances the likelihood of investors perceiving reporting as relevant and persuasive, thereby attracting more investments. In turn, this tailored reporting approach assists investors in making well-informed decisions in assessing the environmental and societal risks of agribusinesses.

The study offers a framework explaining how agribusinesses can increase the likelihood of investors finding firms reporting relevant and persuasive, leading to increased investments in environmentally and socially sustainable practices.

This study aims to explore how sustainable business models (SBM) can be developed within agri-innovation systems (AIS) and emphasize an integration of the two with a systemic understanding for reducing food loss and value loss in postharvest agri-food supply chain.

This study conducted longitudinal qualitative research in a developing country with food loss challenges in the postharvest supply chain. This study collected data through multiple rounds of fieldwork, interviews and focus groups over four years. Thematic analysis and “sensemaking” were used for inductive data analysis to generate rich contextual knowledge by drawing upon the lived realities of the agri-food supply chain actors.

First, this study finds that the value losses are varied in the supply chain, encompassing production value, intrinsic value, extrinsic value, market value, institutional value and future food value. This happens through two cumulative effects including multiplier losses, where losses in one model cascade into others, amplifying their impact and stacking losses, where the absence of data stacks or infrastructure pools hampers the realisation of food value. Thereafter, this study proposes four strategies for moving from the loss-incurring current business model to a networked SBM for mitigating losses. This emphasises the need to redefine ownership as stewardship, enable formal and informal beneficiary identification, strengthen value addition and build capacities for empowering communities to benefit from networked SBM with AIS initiatives. Finally, this study puts forth ten propositions for future research in aligning AIS with networked SBM.

This study contributes to understanding the interplay between AIS and SBM; emphasising the integration of the two to effectively address food loss challenges in the early stages of agri-food supply chains. The identified strategies and research propositions provide implications for researchers and practitioners seeking to accelerate sustainable practices for reducing food loss and waste in agri-food supply chains.