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The purpose of this study is to identify and analyze the barriers associated with the adoption of Industry 4.0 technologies in agricultural supply chains.

The study initially identified thirteen barriers by conducting a literature review and semi-structured interviews with key stakeholders. Subsequently, these barriers were validated and modeled using an integrated Fuzzy Delphi-ISM approach. Finally, MICMAC analysis was employed to categorize the barriers into distinct clusters.

The results provide considerable insights into the hierarchical structure and complex interrelationships between the barriers as well the driving and dependence power of barriers. Lack of information about technologies and lack of compatibility with traditional methods emerged as the two main barriers which directly and indirectly influence the other ones.

The robust hybrid Fuzzy Delphi and ISM techniques used in this study can serve as a useful model and benchmark for similar studies probing the barriers to Industry 4.0 adoption. From a theoretical standpoint, this study expands the scope of institutional theory in explaining Industry 4.0 adoption barriers.

The study is timely for the post-COVID-19 recovery and growth of the agricultural sector. The findings are helpful for policymakers and agriculture supply chain stakeholders in devising new strategies and policy interventions to prioritize and address Industry 4.0 adoption barriers.

It is the first comprehensive, multi-country and multi-method empirical study to comprehensively identify and model barriers to Industry 4.0 adoption in agricultural supply chains in emerging economies.

This study aims to draw observations on the current status and potentials of the Philippines as a farm tourism destination and identify the underlying factors that inhibit farm tourism development. It intends to gauge the challenges that Filipino farmers face in diversifying farms and operating farm sites and uses these challenges in crafting strategies and policies for relevant stakeholders. It also provides Philippine farm tourism literature to address the limitations of references in the topic.

The study adopts an exploratory type of inquiry method and secondary data collection from various sources, such as published journal articles, news articles and reports, to gain insights and relevant information on farm tourism. The study also uses a threats, opportunities, weaknesses and strengths analysis approach to develop competitive farm tourism strategies.

The Philippines, with vast agricultural land, has the necessary base for farm tourism, and the enactment of the Farm Tourism Development Act of 2016 bridges this potential. With low agricultural outputs, the country draws relevance for farm tourism as a farm diversification strategy to supplement income in rural communities. While having these potentials, crucial initiatives in physical characteristics, product development, education and training, management and entrepreneurship, marketing and customer relations and government support must be implemented. Farmers' lack of skills, training and capital investment potential to convert their farms into farm tourism sites serves as the major drawback. Thus, developing entrepreneurial and hospitality skills is crucial.

This work presents a historical narrative of initiatives and measures of the Philippine farm tourism sector. It also provides a holistic discussion and in-depth analysis of the current state, potentials, strategies and forward insights for farm tourism development.

Considering that food security is a global responsibility, the purpose of this study is to examine the impact of agricultural industries on vulnerability to climate change and the moderating effects of gender-diverse parliaments, education expenditures, research and development (R&D) expenditures and foreign direct investment (FDI).

Using concepts in governance, innovation and knowledge theory, a large panel data set of 125 countries covering 1997–2018 (1,852 country-year observations) was analyzed. Data were sourced from the Notre Dame Global Adaptation Index, the World Bank, the Heritage Index and the International Monetary Fund. Moderated random effects regression was conducted in Stata.

The results reveal that agricultural industries are positively associated with vulnerability to climate change and provide support for our predictions that education expenditures and FDI both reduce the impact of agricultural industries on vulnerability to climate change. However, contrary to predictions, the percentage of women in parliament and R&D expenditures both increase this impact.

To the best of the authors’ knowledge, this is the first quantitative study that uses large, established data sets to explore the relationship between agricultural industries and country vulnerability to climate change. This study shows the significance of country-level factors that both decrease and increase the impact of agricultural industries on vulnerability to climate change.

This study aims to examine the impact and contribution of priority and non-priority sectors, as well as their sub-sectors, on the gross non-performing assets of public, private and foreign sector banks.

The Reserve Bank of India's database on the Indian economy is used to retrieve data over 13 years (2008–2021). Public sector (12), private sector (22) and foreign sector (44) banks are represented in the sample. Two-way ANOVA, multiple regression and panel regression statistical techniques are used in SPSS and EViews to examine the data. Further, the results are also validated by using robustness testing by applying the fully modified ordinary least square (FMOLS) and dynamic least square (DOLS) regression.

The results showed that, for private and foreign banks, the non-priority sector makes up the majority of the total gross non-performing assets, although both the priority and non-priority sectors are substantial for public sector banks. The largest contributors to the total gross non-performing assets in public, private and foreign banks are industries, agriculture and micro and small businesses. The FMOLS displays robustness results that are qualitatively similar to the baseline result.

Based on the study's findings about the patterns of non-performing assets originating from these specific industries, banks might improve the way in which these advanced loans are managed.

There has not been much research done on the subject of sub-sector-specific non-performing assets and how they affect total gross non-performing assets across the three sector banks. The study's primary focus will be on the issue of non-performing assets in the priority’s and non-priority’s sub-sectors, namely, agricultural, micro and small businesses, food credit, industries, services, retail loans and other priority and non-priority sectors.

Substantial pressure from civil society and investors has forced governments around the world to take climate neutrality initiatives. Several countries have pledged their nationally determined contributions towards net-zero. However, there exist various obstacles to achieving the same and the agriculture sector is one of them. Thus, this study identifies and models the critical barriers to achieving climate neutrality in the agriculture food supply chain (AFSC).

Sixteen barriers are identified through a literature survey and are validated by the questionnaire survey. Furthermore, the interactions amongst the barriers are estimated through the application of the “weighted influence non-linear gauge system (WINGS)” method which considers the both intensity of influence and the strength of the barrier. To mitigate these barriers, a framework based on green, resilient and inclusive development (GRID) is proposed.

The obtained results reveal that lack of collaboration amongst AFSC stakeholders, lack of information and education awareness, and lack of technical expertise obtained a higher rank (amongst the top five) in three indicators of the WINGS method and thus are the most significant barriers.

This paper is the first attempt in modelling the climate neutrality barriers for the Indian AFSC. Additionally, the mitigating strategies are prepared using the GRID framework.

Technological progress is a determining factor in the factors leading to economic and social well-being. Simultaneously, the development of a sustainable economy is based on the conservation of resources. In the energy sector, this fact can be corroborated with the reduction of energy consumption, thus increasing economic efficiency. On the one hand, improving energy efficiency contributes to increasing the quality of life, productivity, and, implicitly, the economy, but on the other hand, it leads to excess energy use – this behavioral change is known as rebound. The research estimates the rebound effect at the macroeconomic level for European countries in the period 2000–2019, referring the analysis to each country's gross domestic product (GDP) and energy consumption, as well as comparing the preaccession and postaccession periods of Romania in the EU space. The rebound effect is determined using multidimensional analysis methods, depending on the GDP of each country as well as the behavior of each in the use of energy resources in industry, agriculture, and services. Although the study results confirm the strong link between energy consumption and GDP at the level of each state, they did not show considerable changes between countries at the level of the two periods.

This study aims to analyse how the adoption of Industry 4.0 technologies can help different types of agri-food supply chains introduce and manage innovations in response to the challenges and opportunities that emerged following the COVID-19 pandemic.

A systematic literature review methodology was used to bring together the most relevant contributions from different disciplines and provide comprehensive results on the use of I4.0 technologies in the agri-food industry.

Four technological clusters are identified, which group together the I4.0 technologies based on the applications in the agri-food industry, the objectives and the advantages provided. In addition, three types of agri-food supply chains have been identified and their configuration and dynamics have been studied. Finally, the I4.0 technologies most suited for each type of supply chain have been identified, and suggestions on how to effectively introduce and manage innovations at different levels of the supply chain are provided.

The study highlights how the effective adoption of I4.0 technologies in the agri-food industry depends on the characteristics of the supply chains. Technologies can be used for different purposes and managers should carefully consider the objectives to be achieved and the synergies between technologies and supply chain dynamics.

The agriculture industry has a considerable impact on Malaysia’s economy, as seen by its contribution of roughly 8.2% of gross domestic product in 2018 and its potential to absorb 11.09% of Malaysian labor in the same year. This study aims to simulate rising output in a system model of sustainable and profitable crude palm oil (CPO) supply chain management (SCM) and to formulate policy solutions to build sustainable and profitable SCM of Malaysian CPO.

This research included both primary and secondary data. This study used the dynamic system model to simulate palm oil land expansion, replanting policies and environmentally friendly growing techniques.

This study’s findings suggest that the dynamic system model of Malaysia’s CPO’s sustainable and profitable SCM is valid when its structure and performance are tested. The fifth scenario provides the best results, with the most significant net benefit value compared to the other scenarios.

The ideal policy alternative is replanting sustainable agricultural practices without burning technologies during new land clearing to achieve the best net advantages.

The study attempts to estimate farm subsidies the governments can save by transitioning to a millet-based production system, replacing GHG emission-intensive crops.

It updates a 131 × 131 commodity input–output (IO) table of the year 2015–16 into 2021–22 using the RAS procedure and simulates the economy-wide impacts of replacing rice and wheat with pearl millet and sorghum using consumption and production approaches. It then quantifies fertilizer, electricity and credit subsidy expenses the government can save through this intervention. It also estimates the potential reduction in GHG emissions that the transition could bring about. India is taken as a case.

Results show pearl millet expansion brings greater benefits to the government. It is estimated that when households return to their pearl millet consumption rates that prevailed in the early-reform period, this could save the Indian government Rs. 622 crores (USD 75 m). The savings shall be reinvested in agriculture to finance climate adaptation/mitigation efforts, contributing to a sustainable food system. Net GHG emissions also decline by 3.3–3.6 MMT CO2e.

Indian government has been actively aiming to bring down paddy areas since 2013–14 through the Crop Diversification Program and promoting millets (and pulses and oilseeds) on these farms. The prime reason is to check rapidly declining groundwater irrigation in Green Revolution states. Regulations in the past in these states have not brought the intended results. Meanwhile, electricity and fertilizers are heavily subsidized for agriculture. A slight shift in the cropping system can help conserve these resources. Meanwhile, GHG emissions could also be brought down and subsidies could well be saved. The results of the study indicate the same.

A less warm society is what governments and nongovernment organizations across the world are aiming for at present. Financial implications affect actions against climate change to a greater extent, apart from technological innovations. The effects of policy strategies discussed in the study, taking a large country as a case, when implemented appropriately around the regions, could help move a step closer to action against climate change.

The paper addresses a key but rarely explored research issue – that how a climate-sensitive crop choice will help reduce the government’s fiscal burden to finance climate adaption/mitigation. It also offers a mechanism to estimate the benefits within an economy-wide framework.

The purpose of this research is to examine the impact of alterations in the path of monetary policy rates on inflation via the supply side of an emerging economy.

The study employed semi-annual data covering the period 2007S1 to 2020S2 on the inflation rate, the combined outputs of industry and agriculture, the lending rate, and the monetary policy rate. The vector autoregression model was estimated and counterfactual simulation exercises were conducted.

The study revealed that a move from a higher to a lower monetary policy rate regime resulted in a shift in inflation from a higher to a lower regime. In particular, a 200-basis point reduction in the monetary policy rate over the simulation horizon produces a 1.3% fall in the inflation rate over the same period.

The study has a limitation due to the unavailability of a long-span dataset on all relevant variables. As a result, it is important to exercise caution when interpreting the study's findings. A potential area for further research is to explore how changes in interest rates impact inflation in the real economy by utilising other multiple-variable time series techniques.

It is the opinion of the authors that for inflation in Ghana to move to a lower regime, conscious efforts should be made by the monetary authorities to gradually move from a regime of a high monetary policy rate to a lower one.

In particular, a 200-basis point reduction in the MPR over the simulation horizon produces a 1.3% fall in the inflation rate over the same period.

This study enhances the authors' knowledge of how monetary policy can affect inflation in developing countries through the supply-side channel.