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This paper seeks to identify the prevailing streams in the research of climate-smart agriculture in order to help to conceptualize this new scientific notion and assist in drawing clear borders between climate-smart agriculture, agricultural sustainability and resilience.

In order to conceptualize the climate-smart agriculture (CSA), the current research provides an in-depth bibliometric analysis indicating the prospective research directions in CSA. The findings of this paper are important in guiding the research on creation of climate-smart agriculture across different regions.

The notion of the CSA covers three main objectives: increased productivity, enhanced resilience and reduced environmental footprint of agriculture. It is found that due to its novelty, the climate-smart notion does not always have its defined research agenda and is considered to be both a constituent part of some other scientific framework (e.g. sustainability) and an independent research avenue.

This paper presents an in-depth analysis of the literature on the CSA. The linkages among the concepts, research centers and research strands are identified via the citation-based analysis.

The paper embarks on the development of theory and methodology for managing the sustainable development of machine-building enterprises through the use of quantitative modeling tools. The article proposes an algorithm for estimating the position of an enterprise in its competitive space for sustainable development.

The three dimensions of sustainability (social, economic, environmental) are represented by the equations based on the multiple criteria of sustainability. The three-dimensional space is constructed and the effects of managerial decisions can be quantified in terms of the latter space.

The proposed model is applied in the case of Ukrainian machinery construction company. The effects of introduction of the environmentally friendly business strategy are assessed in the three-dimensional sustainability space. The changes in the level of sustainability can be estimated based on the projected changes in the criteria of sustainability.

The proposed methodology combines expert knowledge, empirical data and quantitative methods in order to quantify the level of sustainability of enterprises. The model can be extended to include additional dimensions and applied to different empirical cases.

The new programming period of 2021–2027 of the European Union (EU) Common Agricultural Policy requires reconsidering the policy measures. In the new period, the European Commission is to allow each member state (MS) developing eco-schemes to support and/or incentivise farmers to observe agricultural practices beneficial for the climate and the environment beyond their mandatory requirements. The purpose of this paper is to compare the performance of organic and conventional family farms.

Organic farming under the organic farming measure of the Rural Development Programme is one of the most widely applied sustainable farming practices in the EU as well as in Lithuania. By assessing the ex post economic impact of the organic farming measure on farm performance indicators, the authors seek to reveal possibilities and obstacles for the implementation of sustainable farming practices. A counterfactual ex post impact assessment method – propensity score matching (PSM) analysis – was used to evaluate ex post economic impact of the organic farming measure on the performance of farming indicators.

The application of the PSM allowed assessing both the effectiveness of the implemented measure and possibilities for applying this measure in the future. The research has revealed that organic farming is less profitable and the gap between farm income in organic and conventional farms has increased during the period of 2007–2013.

The most comprehensive economic information about the farm activities from the Farm Accountancy Data Network (FADN) was used for the ex post economic impact evaluation of the organic farming measure in Lithuania. The matched groups of Lithuanian family farms (organic and conventional) were compared. The results of the research provide a new knowledge about the effectiveness of the organic farming measure in Lithuania and suggest the ways of their improvement in the future. The results can also be generalised to other countries with similar agricultural structure.

The Green Deal strategy of the European Union (EU) as well as the increasing concerns over resource scarcity worldwide has put forward such concepts as the circular economy. This paper seeks to compare the progress of the development of the circular economy across the EU Member States. Such analysis is helpful in guiding the circular economy support policies.

This paper develops a quantitative framework for analysis of the implementation of the circular economy objectives in the EU Member States. The framework proposed includes three multi-criteria decision making methods representing reference point and outranking approaches. The use of multiple methods allows exploiting the differences in the underlying aggregation principles.

Germany, Sweden and the Netherlands appear as the most advanced in the sense of circular economy development. The results indicate that the water-locked small countries and the new EU Member States are among the lowest performing ones. The flows of the waste need to be monitored more tightly in order to increase the circularity. The development of recycling facilities can also increase circularity irrespectively of the economic development level (e.g. the case of Bulgaria).

The paper contributes to the discussion regarding the circular economy by proposing an indicator system and the multi-criteria analysis framework. The proposed indicator system covers input use (circularity), trade flows and recycling processes. The proposed framework can be applied to track the progress of different countries in implementing the targets of the circular economy.

The proposed DHHFLOWLAD is used to design a recommendation system, which aims to provide the most appropriate treatment to the patient under a double hierarchy hesitant fuzzy linguistic environment.

Based on the ordered weighted distance measure and logarithmic aggregation, we first propose a double hierarchy hesitant fuzzy linguistic ordered weighted logarithmic averaging distance (DHHFLOWLAD) measure in this paper.

A case study is presented to illustrate the practicability and efficiency of the proposed approach. The results show that the recommendation system can prioritize TCM treatment plans effectively. Moreover, it can cope with pattern recognition problems efficiently under uncertain information environments.

An expert system is proposed to combat COVID-19 that is an emerging infectious disease causing disruptions globally. Traditional Chinese medicine (TCM) has been proved to relieve symptoms, improve the cure rate, and reduce the death rate in clinical cases of COVID-19.

The purpose of this paper is to identify the effects of recent demographic transition and rising labor costs on agricultural production structure and pattern in China during 1998-2012.

The authors, first, theoretically discuss the effects of changing relative input prices due to rising labor cost on producers’ decisions regarding input mix (substitution effect), output level, and product quality (output effect). A logarithmic mean Divisia index decomposition method is then applied to empirically identify these effects at aggregated levels, followed by an analysis based on the visualization of land use indicators on changing cropping patterns across Chinese provinces.

The authors find that tightened effective agricultural labor supply and rises in rural labor costs are associated with divergent changes in input mixes and output choices across products. Producers of land-intensive products focusing more on input mix adjustment, while those of labor-intensive products seem to more likely to adjust output choices. Producers’ adaption strategies also varied across Chinese provinces due to natural conditions, leading to shifts and concentrations in the regional distribution of agricultural products, with lower-value bulk products concentrating in the plain areas, whereas higher-value horticulture products increasingly prevailing in sloped areas.

This paper illustrates how adjustments in input mixes and output choice in Chinese agriculture counteracted disadvantages caused by rising labor costs and how such adjustments are product and region specific. Based on these observations, implications regarding further innovations in production technology and institutional arrangements needed within China’s agricultural sector are highlighted in the paper.

The purpose of this paper is to assess the efficiency of agricultural production in South Africa from 1970 to 2014, using an integrated two-stage fuzzy approach.

Fuzzy technique for order preference by similarity to ideal solution is used to assess the relative efficiency of agriculture in South Africa over the course of the years in the first stage. In the second stage, fuzzy regressions based on different rule-based systems are used to predict the impact of socio-economic and demographic variables on agricultural efficiency. They are compared with the bootstrapped truncated regressions with conditional α levels proposed in Wanke et al. (2016a).

The results show that the fuzzy efficiency estimates ranged from 0.40 to 0.68 implying inefficiency in South African agriculture. The results further reveal that research and development, land quality, health expenditure–population growth ratio have a significant, positive impact on efficiency levels, besides the GINI index. In terms of accuracy, fuzzy regressions outperformed the bootstrapped truncated regressions with conditional α levels proposed in Wanke et al. (2015).

Policies to increase social expenditure especially in terms of health and hence productivity should be prioritized. Also policies aimed at conserving the environment and hence the quality of land is needed.

The paper is original and has not been previously published elsewhere.

China's economy has transformed from a high-speed growth phase to a high-quality development phase. The agriculture sector has grown substantially since the economic reform in 1978. Considering the five-year plan (FYP) as a collection of policies, this study explores the relationship between the FYP and agricultural total factor productivity (TFP).

This study uses 31 provincial-level panel data of the five FYPs from 1996 to 2020. The data envelopment analysis (DEA) is used to compute Malmquist productivity indexes. The authors analyze the temporal and spatial changes and convergences of China's agricultural TFP, and investigate the impact of economic planning on China's agricultural TFP and its regional difference.

There is a slow but upward growth trend in China's agricultural TFP. The technical change has played a leading role in the growth of China's agricultural TFP. The agricultural TFP of all provinces has shown a “catch-up” effect and is developing toward their respective steady-state levels. The regional difference in productivity growth among the eastern, central and western regions exists. Test results show that the FYP has a positive effect on the agricultural TFP, and the effect has obvious regional heterogeneity. The FYP also plays a positive role in the gross value of agricultural output, and the impact effect is greater than that on the improvement of agricultural productivity.

There are many forms of industrial policy in China, among which the FYP is the guiding document of industrial policy, which makes a systematic plan for industrial development in the subsequent five years. The development objectives, guidelines and overall deployment for agriculture in the FYP not only describe the general context of China's agricultural development but also show the key ideas of agricultural development. Therefore, this study explores its impact on agricultural quality development from the perspective of FYP. The results provide evidence for examining the governance performance of the government and the objective evaluation and restraint of the FYP. As agriculture moves toward the stage of high-quality development, the Chinese government should strengthen the critical guiding role of the FYP and pay attention to quality indicators such as technical progress, efficiency improvement and regional coordination in the formulation of the FYP.

Drawing on the technology-organization-environment (TOE) framework, this study aims to investigate determinants of performance of artificial intelligence (AI) adoption in hospitality industry during COVID-19 and identifies the relative importance of each determinant.

A two-stage approach that integrates partial least squares structural equation modeling (PLS-SEM) with artificial neural network (ANN) is used to analyze survey data from 290 managers in the hospitality industry.

The empirical results reveal that perceived AI risk, management support, innovativeness, competitive pressure and regulatory support significantly influence the performance of AI adoption. Additionally, the ANN results show that competitive pressure and management support are two of the strongest determinants.

This research offers guidelines for hospitality managers to enhance the performance of AI adoption and presents policy-making insights to promote and support organizations to benefit from the adoption of AI technology.

This study conceptualizes the performance of AI adoption from both process and firm levels and examines its determinants based on the TOE framework. By adopting an innovative approach combining PLS-SEM and ANN, the authors not only identify the essential performance determinants of AI adoption but also determine their relative importance.