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This study aimed to examine organizational digitalization of farmers' associations (FAs) by conducting internal and external analyses of the contextual and geo-spatial attributes of the organizations, and further explored the role such associations play as key change agents in activating agricultural innovations and development in Taiwan.

Unlike previous digitalization studies, which employed user data such as attitudes and behaviors as the major determinants, the present study focused on the spatial and organizational characteristics of FAs. An exploratory spatial analysis was conducted using a geographic information system to discover whether the organizational characteristics, local agriculture development, and neighboring FAs affect the organizational decision and adaption on information services. Research data from three national surveys were analyzed with a spatial regression model.

Results showed that geographical neighborhood, in association with organizational characteristics, significantly affects the decision and level of organizational digitalization, while the development and characteristics of regional agriculture exert no significant influence.

In the development of information and communication technology (ICT) diffusion policies for promoting organizational digitalization, it is important to highlight regional initiatives and complementary public efforts to guarantee an equitable access to ICT in areas with variances in economic development. In neighborhood FAs, greater development of economic and labor scales and ICT human capital also contribute to higher levels of organizational digitalization.

Based on the study results, suggestions are provided for future research considering spatial forces in agricultural information studies and practical applications.

This paper aims to analyse the mainstream and emerging global challenges and trends in the global agriculture sector. The analysis leads to a discussion on the present state of the Russian agroindustry and possible future strategies for adaptation in the context of the rapidly changing global environment.

The design of this study is based on the application of the core methods of Foresight. First, a trend analysis is undertaken using reviews and expert methods. Trends identified are mapped using a social, technological, economic, environmental, political and value (STEEPV) framework to ensure that a broad range of trends are covered, which may be stemming from various factors affecting the agriculture sector. The analysis of the big picture of global trends and challenges, interacting with country-specific structural factors, translates are translated into the opportunities and threats, which will in turn help to develop possible strategies for adaptation.

This study develops two adaptive strategies for the development of the Russian agroindustry that are feasible in different short- and long–term time horizons. The first strategy is considered to be the most likely choice for the period before 2020. It includes radical imports’ substitution (of commodities as well as machinery and high-tech components) for ensuring national food security with inevitable temporary setbacks in efficiency and labour productivity. The second strategy, which becomes feasible after 2020, considers re-integrating Russia into global supply chains and expanding commodities exports (volumes and nomenclature) based on full-scale technological modernization with the use of international capital.

The study design is based on the assumption that Russia’s position as a country, which is highly self-sufficient on basic agricultural products and large exporter of crop commodities and fertilizers, will remain unchanged in the horizon of at least 20 years. However, long-term forecasts should also scrutinize the possibility of radical structural changes. Therefore, future research should concentrate on wild cards that can completely disrupt and transform the Russian agriculture industry and as well as the whole economy.

This paper suggests a number of recommendations on national science and technology policy for the three main industries of the Russian agricultural sector: crop husbandry, animal breeding and food processing (the fisheries sector is excluded from the scope of this paper). In addition, this paper proposes a number of measures towards alleviating the institutional barriers to raise the investment attractiveness of the sector.

The novelty of this paper lies in the originality of the research topic and methodology. The Russian agricultural sector has rarely been studied in the context of global agricultural challenges and threats taken on the highest level of aggregation beyond commodity market analysis or agro-climatic and logistics factors. There are few or no studies that lay out a map of possible long-term strategies of Russian agroindustry adaptive development. The Foresight methodology applied in this study is customized to better fit the practical purposes of the study.

China's population–land contradiction is a crucial issue, and by deeply analyzing causes of wasting arable land, this article recommends some policies to avoid waste.

Based on the current high-, middle- and low-class differentiation in the agricultural products' consumption structure against urban residents' rapid income growth, this article proposes that agricultural products with distinctive regional characteristics should be developed according to regional natural agricultural resources and market demand, so as to ensure that China's scarce arable land can be used effectively.

Choices in regional agricultural production relate to operational farmers' enthusiasm for profitability and production, residential farmers' ability to ensure their own food security, agriculture's sustainable development and arable land resources' optimal allocation. Therefore, the varietal structure of agricultural products and regional production layout should be compatibly decided according to consumer demand and resource endowment.

During the process of industrialization and urbanization, wasting of arable land has become a social development problem. On the basis of agriculture's regional resource endowment, this article reconstructs the functional positioning of various Chinese agricultural regions and solves the difficult problem of consumption structure transformation and homogeneous competition through the geographical division of labor, thereby optimizing allocation of arable land resources.

Purpose – Dairy has been the backbone of agriculture in regional Norway, and the processing of milk has been dominated by co-operatives owned by milk farmers. During the social democratic order (1945–1979), productivist agriculture thrived, while a more multifunctional agriculture was developed after 1980. As a measure against overproduction, a quota system was introduced in 1983. The purpose of this study is to see if there are signs of a neo-productivism revival after climate change and other global shocks, like the food crisis, featured prominently on the political agenda.

Design/methodology/approach – The chapter reviews the radical structural changes in Norwegian dairy production since the early 1960s, which reduced the number of milk farms radically from 148,000 in 1959 to almost 16,000 in 2009. According to the Agricultural Agreement between the Norwegian government and the farmers' organisations, the co-operatives are given an important semi-public role as market-price regulators and stock keepers. This Norwegian system may be described as a classical regulated dairy regime. The Norwegian dairy regime has been through several deregulations and re-regulations over the last 20 years, partly forced by internal pressures and partly inspired by liberalisation tendencies abroad.

Findings – After mid-1990s, there has been an increase in the number of joint dairy farms, where individual ownership of land is maintained while herds, buildings and machinery are merged. Three thousand six hundred thirty dairy farmers are now participating in 1,510 joint farming firms, producing 29 per cent of the milk in Norway. This rapid growth of joint farming is transforming the dairy sector in Norway. Analysis has shown that its evolution is closely tied to farmer socio-economic demands, including social benefits, such as increased leisure time, and security during illness. While there has been pressure to increase productivity, the food crisis changed attitudes, making the current policy of import tariffs and subsidies easier to defend.

Originality/value – This chapter shows that neo-liberalism in Norway was not pursued as far as in most other OECD countries, although some deregulation was taking place. Norwegian agricultural policies are still regulating the sector to a substantial degree, with the annual Agricultural Agreement negotiations serving as a centrepiece. Norway has ambitious climate goals, and by 2020 greenhouse gases emissions should be reduced to 30 per cent of the 1990 rate. A further goal is that Norway will be carbon neutral by 2030. As part of the implementation of its climate policy, a White Paper on agriculture and climate change was put forward in May 2009. For Norwegian food production as a whole, a change towards more grazing at the expense of crops would improve carbon storage and reduce the overall use of fertiliser. Such a shift in land use would benefit the dairy sector, in part because of easier access to domestically grown cow feed.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

This study aims to investigate the long-run relationship between financial inclusion and agricultural growth in Pakistan for the period of 1960–2018.

The autoregressive distributed lag (ARDL) approach, the Johansen co-integration test and the dynamic ordinary least squared (DOLS) method are used for the evaluation.

The results show that in both short- and long run, domestic credit has a significantly negative impact on the agricultural growth, while broad money and cropped area positively affected the agricultural growth in Pakistan in both cases.

The government and policymakers need to develop strategies that bring together agriculturalists on a single platform so that the government can clearly distinguish the interests of these farmers and can obtain precise information for allocating agricultural expenditure and easing access to credit for small-scale agriculturalists.

This is the first study to evaluate the impact of financial inclusion on the agricultural growth in Pakistan by using different econometric techniques, including the ARDL-bound approach, Johansen co-integration test and DOLS method.

The literature argues on ambiguous impacts of different types of the common agricultural policy (CAP) subsidies on farm technical efficiency (TE). The purpose of this paper is to estimate and analyse the TE and the impact of the CAP subsidies on the TE of wine farms in Hungary using the farm accountancy data network data set in the period 2013–2019.

The authors use stochastic frontiers analysis (SFA) models to estimate the TE scores for the Hungarian wine farms with four wine farm-level inputs in terms of agricultural land, labour, capital and intermediate consumption. The TE scores are explained by the CAP subsidies and economic wine farm size. The different SFA models were applied with robustness tests to investigate the drivers of the TE values of wineries.

Like for Hungarian farms in general, the distribution of the wine farm structure is a dual with a greater number of smaller wine farms and a smaller number of bigger wine farms. The agricultural land, capital and intermediate consumption are significantly positively associated with the wine farm TE. With higher capital intensity wine farm TE increase. The results imply that the CAP subsidies decrease the TE of the Hungarian wine farms, whereas economic farm size increase.

To the best of the authors’ knowledge, this is one of the first specific efficiency studies on the wine sector in the Central and Eastern European region and the first one for Hungary to evaluate the TE at wine farm level and to assess the impact of CAP subsidies and economic farm size on wine farm (in)efficiency to apply production technologies and use farm resources. This study is among the first that applied the fixed-effects stochastic frontier model at the wine farm level to measure the drivers of the TE scores.

This paper uses a method devised by Geary and Stark to estimate regional GDPs for 24 Swedish provinces 1855–2000. In empirical tests, we find that the Swedish estimations yield results of good precision, comparable to those reported in the international literature. From the literature, we generate six expectations concerning the development of regional GDPs in Sweden. Using the GDP estimations, we test these expectations empirically. We find that the historical regional GDPs show a high correlation over time, but that the early industrialization process coevolved with a dramatic redistribution of productive capacity. We show that the regional inequalities in GDP per capita were at their lowest point in modern history in the early 1980s. However, while efficiency in the regional system has never been as equal, absolute regional differences in scale of production has increased dramatically over our investigated period. This process has especially benefited the metropolitan provinces. We present detailed sources of our estimations and also sketch a research agenda from our results.

This chapter does three things. First, it estimates regional gross domestic product (GDP) for three different geographical levels in Switzerland (97 micro regions, 16 labor market basins, and 3 large regions). Second, it analyzes the evolution of regional inequality relying on a heuristic model inspired by Williamson (1965), which features an initial growth impulse in one or several core regions and subsequent diffusion. Third, it uses index number theory to decompose regional inequality into three different effects: sectoral structure, productivity, and comparative advantage.

The results can be summarized as follows: As a consequence of the existence of multiple core regions, Swiss regional inequality has been comparatively low at higher geographical levels. Spatial diffusion of economic growth occurred across different parts of the country and within different labor market regions. This resulted in a bell-shaped evolution of regional inequality at the micro regional level and convergence at higher geographical levels. In early and in late stages of the development process, productivity differentials were the main drivers of inequality, whereas economic structure was determinant between 1888 and 1941. The poorest regions suffered from comparative disadvantage, that is, they were specialized in the vary sector (agriculture), where their relative productivity was comparatively lowest.

This chapter highlights some features of the current structure of Italian agriculture by focusing on the regional patterns of agrarian change. These patterns are followed mainly by comparing the data of the 5th and 6th Census of Agriculture and the data of holdings registered to the Chambers of Commerce. The analysis confirms the Northern-Southern dichotomy of Italian agriculture as the physical and economic dimensions of Northern regions’ holdings are appreciably higher than those in the South. Other traits of farms, not usually included in most traditional analyses, help explain that Northern-Southern dichotomy: the farmers’ educational level and the ICT availability on farms. The agriculture of Southern regions has been affected less by the structural adjustment and has maintained some traits of more ‘traditional’ farming. However, important innovations, such as organic farming and direct selling to ‘consumers in house’, have been adopted more readily by Southern farms. The marked regional duality of Italian agriculture corresponds to the several ways in which farmers and their activities interconnect with territorial development models that have shown a deep regional differentiation.