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The purpose of this paper is to investigate the adoption of Internet of Things (IoT) in the agriculture industry by the farmers' in India using the theoretical lens of the behavioral reasoning theory (BRT).

A survey on farmers was conducted to examine the adoption of IoT in agriculture industry (IoT-A) using BRT. The data analysis of the primary survey was done by applying the structural equation modelling (SEM) technique.

The ‘reasons for’ adoption of IoT-A were as follows: Relative advantage, social influence, perceived convenience, and perceived usefulness. The ‘reasons against’ adoption were as follows: Image barrier, technological anxiety, perceived price and perceived risk. The BRT theory provides the platform to discuss the psychological processing of acceptance of IoT in agriculture industry by the farmers.

This research has unique implications as it studies the rural consumers’ behavior of innovation adoption namely IoT in agriculture. It provides the specific reasons ‘for’ and ‘against’ IoT adoption in agriculture, which will give directions to the marketers of IoT technology to develop suitable marketing strategies to improve the adoption in rural areas.

This research takes the first step in the direction toward deliberation of the adoption of IoT-A by farmers in an emerging Indian economy using the BRT theory, which discusses the ‘reasons for’ and ‘reasons against’ adoption in a proposed model.

The main intention of this paper is to analyze various factors hindering the growth of the agricultural supply chain and several industry 4.0 technologies to eliminate the same. In addition to a detailed assessment on the implementation of these technologies in agriculture, this manuscript also presents a priority list providing a rank to them based on the relative efficiency of these advancements in addressing these obstacles.

This research proceeds with a two-step process. The particular barriers in the agriculture supply chain and industry 4.0 technologies are determined in the first step. Next, the proposed framework, a combination of data envelopment analysis (DEA) and analytic hierarchy process (AHP), i.e. DEA-AHP, is used to determine a hierarchical structure for the factors and the relative productive efficiencies of the alternatives. The DEA methodology gives a performance analysis of various decision-making units. At the same time, AHP helps in evaluating alternatives weights based on numerous criteria, allowing us to categorize their importance further.

This study reveals how the involvement of technological advancements in agriculture can help manage the supply chain more efficiently. It also justifies how the large quantities of data generated can handle these increasing challenges in the agricultural supply chain.

The results of this study provide a priority list of alternatives based on their final weights. This ranking system can help farmers and the government select the best-suited technology for bringing automation into the agricultural supply chain.

This research is unique as it analyes the general factors hindering the development of the agriculture supply chain while simultaneously providing a list of alternatives based on their relative efficiencies. The study enriches existing literature by providing an analytic approach to determine the weightage of various critical success factors that can help improvise and entrust the real and undeniable requirements of consumers, suppliers and producers.

Pakistan’s natural endowment of labour and land is suitable for labour-intensive agriculture and manufacturing sector. This study aims to investigate international trade competitiveness of Pakistan in 14 major industries of agriculture and manufacturing sector, accounting more than 85 per cent of total export receipts.

The competitiveness of Pakistan in selected industries of agriculture and manufacturing sectors from 2003 to 2014 is investigated using the revealed comparative advantage (RCA) index, introduced by Balassa (1965) on HS data collected from the United Nations Commodity Trade database. The obtained indices in this study are then subjected to panel regression analysis to investigate the effect of domestic productivity growth and real exchange rate on international trade competitiveness of major industries.

The results show that the agriculture sector of Pakistan has higher comparative advantage in raw cotton, cereals, raw leather and fruits. The raw cotton shows the highest competitiveness of 54.46 which is followed by cereals (17.13), leather (9.83) and fruits (1.97). The RCA of the manufacturing sector shows that textile (54.85), carpets (10.72), sports goods (2.18) and beverages (1.47) have higher competitiveness. The RCA, in relatively capital-intensive industries, shows a high disadvantage. The trend analysis shows distorted competitiveness in labour-intensive, textile, carpet and footwear industries. The results of panel regression analysis show that the domestic productivity growth and real exchange rate depreciation have a significant positive impact on the international competitiveness of selected industries. The study urges Pakistan to make its macroeconomic environment investment-friendly and encourage investment in deteriorating labour-intensive industries.

Globalisation has significantly increased international competition, and Pakistan is losing its competitiveness in labour-intensive industries owing to lack of domestic value addition and development efforts. The major problem with the productivity of these industries is the lack of proper infrastructure, acute energy crisis, lack of domestic and foreign investment and overvaluation of real exchange rate. The domestic investors are shifting their capital either to other domestic sectors and/or other investment-friendly countries. Policymakers in Pakistan should address the problems of these important labour-intensive industries. The government needs to understand macroeconomic uncertainties and make investment-friendly policies to encourage domestic and foreign investment. The future studies should perform in-depth research to identify both microeconomic and macroeconomic variables responsible for deterioration in competitiveness of major labour-intensive industries in the agriculture and manufacturing sectors of Pakistan.

This study is a comprehensive examination into the nature and pattern of international competitiveness of Pakistan in 14 important industries of the agriculture and manufacturing sector which has seldom been investigated empirically. The obtained indices in this study are also subjected to panel regression analysis to explore the effect of domestic productivity growth and real exchange rate depreciation on the international competitiveness of Pakistan.

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.

Studies concerning Soviet taxation demonstrate a diversity of opinions on the nature of turnover taxes. Four major views on the subject have emerged: (1) turnover taxes are simply a sales (excise) tax on articles' of consumption sold to the Soviet consumer; (2) not all turnover taxes are a sales tax, some of them are a substitute for rent on production of certain industrial materials; (3) in addition to being a sales (excise) tax on consumer goods and rent on some industrial materials, there exists a third type of turnover tax which is levied on agricultural production of the peasantry; (4) turnover taxes are a portion of the surplus product produced in industry and agriculture.

Karl Marx's social capital reproduction theory is his significant contribution to economics. The purpose of this paper is to review the contributions of the exploration of Chinese economists (especially Professor Liu Guoguang) in the concretization of Marx’s social capital reproduction theory combined with socialist construction since 1949.

During this process, Professor Liu Guoguang, a famous Chinese Marxist economist, has made an outstanding contribution by creating a Marxist social capital reproduction model with Chinese characteristics and a distinctive Marxist economic growth model. Professor Liu's exploration is still of crucial practical significance to building a socialist market economy today.

The process and achievements in the sinicization exploration of Marx's social capital reproduction theory were reviewed. With the reform and opening up, fundamental changes have occurred in China's economic system – the centralized planned economic system has been transformed into a socialist market economic system.

The planned management of the national economy is replaced by a macro-regulation system characterized by gross control gradually, and the concepts of agriculture, light industry, and heavy industry, and their intercorrelation are no longer applied in theory and policy. However, the sinicization exploration of Marx's social capital reproduction theory in the older generation of Marxist economists represented by Liu is not only of historical significance but also of important practical significance.

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 chapter proposes that efforts to improve our understanding of factors affecting migrant health and longevity in the United States must consider migrants’ labor market incorporation and the structural conditions under which they work. I use public-use death certificate data to examine whether there is a mortality penalty for foreign-born workers in the secondary sector industries of agriculture and construction. I focus on the decade of the 1990s for two contextual and empirical reasons: (1) the decade was characterized by economic restructuring, restrictive immigration policy, increased migration, and dispersion of migrants to new geographic destinations; and (2) the 1990s is an opportunistic decade because 19 states coded the industry and occupation of the decedent during this time. These numerator mortality data and Census denominator data are used to compare all-cause mortality rates between working-age (16–64 years) US-born and foreign-born agricultural and construction workers, the overall foreign-born population, and foreign-born workers in health care – an industry where the foreign-born tend to work in well-paid occupations that are well-regulated by the state. The results show a clear mortality penalty for foreign-born workers in agriculture and construction compared to the overall foreign-born population and foreign-born healthcare workers. The results also show the mortality penalty for foreign-born secondary sector workers varies by industry. These findings support the argument that bringing work into our analyses is critical to understanding the contextual and structural factors affecting migrant health and survival.

Nine causes for the occurrence of surplus agricultural labour with the modernisation of agriculture have been identified. Several solutions to this problem are presented. Urbanisation of the agricultural population in a way suited to China′s characteristics is necessary, important and possible.

Agriculture and cultivation firms are facing severe competition in the saturated market. Due to the characteristics of heavy assets, low investment return, long cycle and high price fluctuation, agri-food firms require innovations for capital support. The purpose of this paper is to provide valuable insights on how firms in the food/agricultural industry approach innovations and reinforce their advantages through functional and structural innovations by adopting supply chain finance (SCF).

This research adopts a single-case study methodology to investigate the innovations and mechanisms taking place at H Corp Agriculture Group (H Corp hereafter), a Chinese egg company.

The findings of this paper indicate that SCF could have a great impact on supply chain management through functional and structural innovations throughout the supply chain and solve the capital constraint problems in the agricultural development process, promoting the implementation of the integration strategy as well as innovation in the agricultural industry chain. The research also shows that supply chain structural and functional innovations could promote corporate social responsibility (CSR) and creating shared value (CSV).

The research contributes to the application of SCF mechanisms and the realization of CSV and CSR jointly – both in the literature and in firms’ practices. It also contributes to the extension of structural and functional innovations and vertical integration of the supply chain. However, generalizability and universality are insufficient for a single case study in the specified industry. Data collection and quantitative analysis could be extended for further research.

The study addresses the need for comprehensive research on SCF and its applications. It proposes effective and efficient strategies for agri-food firms applying SCF to overcome industry capital constraints and develop competitiveness. It also provides a balanced and positive circulation between economic value and social value, realizing CSR and CSV.