Integrated Farming Systems (IFS) have gained prominence as a sustainable and resource-efficient approach to enhance farm productivity, income stability, and livelihood security among small and marginal farmers. By integrating multiple enterprises, IFS improves resource use efficiency and strengthens resilience against climatic and market uncertainties. The study was conducted in the Morena district of Madhya Pradesh to identify the major constraints faced by farmers practicing Integrated Farming System (IFS) under the Farmer FIRST Programme (FFP). A total of 60 beneficiary farmers were selected, and data were collected using a structured interview schedule. Constraints were categorized into production, marketing, financial, and management constraints, and ranked using Garrett’s Ranking Method. Results revealed that shortage of labour (mean score = 56.33) and uncertain weather conditions (mean score = 50.00) were the most critical production constraints. Among marketing constraints, high transportation costs (mean score = 59.50) and price fluctuations (mean score = 54.75) ranked highest. Increasing rate of labour wages (mean score = 64.25) and inadequate subsidies (mean score = 45.25) were the top financial constraints. In terms of management, difficulty in labour management (mean score = 59.50) and pest and disease management (mean score = 54.75) were the key barriers. The findings indicates that financial and management constraints dominate the challenges faced by IFS farmers. Policy and extension interventions, including farm mechanization, affordable credit, improved storage facilities, strengthened market linkages, and capacity building, are essential to mitigate these constraints effectively.

The automotive component industry faces significant challenges in improving operational efficiency and production quality, particularly due to reliance on manual processes. A key issue identified is the company's Overall Equipment Effectiveness (OEE) performance, which has not met the established target, with an average achievement of only 72%, indicating considerable process inefficiencies and productivity losses. External pressures such as global market dynamics, economic uncertainty, and increasing Regional Minimum Wage (UMP) rates have further exacerbated the need for digital transformation to enhance operational efficiency and organizational competitiveness. This study aims to design a digitalization system to address operational inefficiencies and low production quality in the automotive component industry, focusing on improving OEE performance, reducing operational costs, and supporting data-driven decision-making. This research proposes an integrated digitalization system developed through the combination of the selective QC 7 Tools and Design Thinking approaches, with the selective QC 7 Tools applied to systematically identify and analyze the root causes of operational inefficiencies. The implementation resulted in significant improvements, including the complete elimination of 195 minutes per shift of non-value-added activities, the reduction of reporting lead time from 2–3 days to near real-time (0.5 days for analysis), and a 10% increase in OEE performance. The system also enabled the reallocation of 13 administrative personnel to more value-added roles, reduced operational costs, and minimized paper waste and CO₂ emissions. This study confirms that the selective QC 7 Tools prove effective in supporting digital transformation, and that data-driven digitalization can significantly improve competitiveness and business sustainability.

Nigeria continues to have chronically high youth unemployment despite continued foreign direct investment (FDI) inflows, contradicting traditional development theory's assertion that FDI inflows boost employment through investment expansion and knowledge transfer. This study uses annual time-series data spanning 25 years (2000–2024) to reexamine the relationship between youth unemployment in Nigeria and foreign direct investment (FDI). The Autoregressive Distributed Lag (ARDL) method was used for analysis in this study. Results indicated that all the explanatory factors (exchange rate, government spending, inflation rate, minimum wage rate, population growth rate, and foreign direct investment) in Nigeria have a long-run relationship with the dependent variable (youth unemployment rate). In the short run, the a priori assumption is met by government spending, FDI, and the minimum wage rate, but not by the rate of inflation, population growth, or currency rate. The findings suggest that the weak employment response to FDI reflects structural and absorptive capacity constraints rather than the ineffectiveness of foreign investment per se. The study recommends that policymakers should formulate and implement programs to boost foreign direct investment within the domestic economy. Additionally, the government should implement labor-absorbing FDI policies and make sure that FDI is directed toward labor-intensive industries like manufacturing, agriculture, and information, communication, and technology (ICT) that have a high ability to absorb labor.

ABSTRACT It is widely recognized that Japan successfully imported advanced technologies from Europe in the prewar period, particularly in the modern cotton‐spinning and silk‐reeling industries. However, the traditional silk‐ and cotton‐weaving industries also flourished using imported technologies. This study explores key factors contributing to the successful development of the textile industries in prewar Japan by examining long‐term statistical evidence and synthesizing the accumulated insights from the existing studies. We found that while many of these industries initially failed to develop through the direct importation of modern capital‐intensive technologies, the unique and common feature of the successful industrial development in prewar Japan was the selective choice of appropriate foreign technologies, combined with the adaptations of these technologies to domestic factor endowments, including skilled and unskilled workers and capital. As a result, labor‐intensive industrialization preceded World War I, when the real wage rate began increasing sharply, and was later followed by capital‐intensive industrialization.

ABSTRACT This article combines the price system and the quantity system in duality through the system transformer and formulates the dual equation, facilitated by adopting the minimum subsistence basket of consumer goods and services as the numéraire. The resulting simple ‘nutshell economy’ unveils two findings. First, it reveals symmetry breaking in the duality, signifying that G < R and w < c , in which G, R, w, and c denote 1 + growth rate g , 1 + profit rate r , the real wage rate, and the consumption rate, respectively. Symmetry breaking is shown to be equivalent to Marxian exploitation of workers. This leads to the theorem of discrepancy between income distribution Rw and resource allocation Gc, namely Rw < Gc . Second, it establishes the theorem of parallel traverse of R and G, and w and c with their widening symmetry breaking as R and G increase, and vice versa. The theorem suggests the burden of growth and profit, namely that an increase in g and r disproportionately sacrifices c and w. Finally, it is attempted to construct a unified classical approach since Adam Smith in contrast with the post-Keynesians.

Farm mechanization has become a critical intervention in sugarcane cultivation in India in response to persistent labour shortages, rising wage rates, and the need to enhance productivity and operational efficiency. Adoption of mechanized technologies in sugarcane farming, however, remains uneven and influenced by a complex interaction of socio-economic, psychological, and institutional factors. This review synthesizes empirical evidence from studies conducted across major sugarcane-growing regions of India to examine the determinants shaping farmers’ awareness, knowledge, and utilization of farm machinery. The findings reveal that education, farm size, income, farming experience, and access to information significantly influence mechanization adoption, while psychological attributes such as innovativeness, risk orientation, scientific orientation, and economic motivation play a crucial role in farmers’ decision-making behaviour. Institutional factors, including availability of machinery, custom hiring services, training exposure, extension support, and credit access, further condition the extent and intensity of mechanization. Although mechanization has improved timeliness of operations and reduced labour drudgery, its adoption remains largely confined to selected operations, with limited penetration in planting, harvesting, and ratoon management. The review underscores the need for a holistic mechanization strategy that integrates appropriate technology, capacity building, and institutional support to promote inclusive and sustainable mechanization in sugarcane cultivation. Addressing these determinants is essential for improving productivity, reducing production costs, and ensuring the long-term viability of the sugarcane sector in India.

ABSTRACTAimTo quantify the time- and cost-savings to US oncology practices from using a single bispecific antibody (bsAb) for both relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL) compared with using two separate single-indication therapies.Materials & methodsThe study conducted a national survey of clinicians (oncologists, pharmacists, nurses/physician assistants) treating non-Hodgkin lymphoma (NHL) patients in the US to quantify the impact of operational efficiencies identified through formative qualitative interviews with oncology staff. Quantitative analysis estimated time-savings based on survey data, assuming one new prescription per patient per year and 12 (DLBCL) and 15 (FL) administration visits per patient per year. Time-savings were combined with staff wage rates to estimate cost-savings.ResultsAmong n = 105 respondents, drivers of operational efficiencies included onboarding, coordinating insurance and financial aid, and medication preparation. For a hypothetical community practice treating 100 bsAb-eligible patients (61% DLBCL, 39% FL), total time-savings were 3110 h in the first year of adoption, resulting in total monetized time-savings of $278,013. For a hypothetical academic practice, monetized time-savings were $963,074 in the first year of adoption.ConclusionsUsing a single bsAb to treat R/R DLBCL and FL is predicted to lead to considerable time- and cost-savings for oncology practices.

This article describes and analyzes the economic growth and stagnation of postwar Japan, focusing in particular on its manufacturing industry during the post-Cold-War period, when it faced intense global competition and explosive digitalization. Both semi-macro statistics and field survey results are used for historical analysis. In addition, the combination of a classical economics (Ricardian) industry study and modern design theories is adopted. Our empirical research shows that Japan’s manufacturing industry continued to grow slowly between the1990s and the 2010s. The number of its employees shrank to about two thirds, while value-added productivity doubled during the same period. After China’s entry into the world market with extremely low wages, Japan’s average wage rate almost stopped growing in the 1990s–2010s, but it started to increase again in the 2020s. Many Japanese manufacturing firms disappeared during the wave of global competition and digitalization, but many survived thanks to significant improvements in physical labor productivities, achieved by introducing advanced production systems/technologies, such as the Toyota-style production system. The Japanese manufacturing industry tended to accumulate coordinative manufacturing capability in the Cold War period of rapid economic growth (economy of scarcity), and it later retained its design-based comparative advantage in coordination-intensive or integral-architecture products, e.g., highly-functional automobiles, as predicted by the CAP (capability-architecture-performance) approach to industry studies. Overall, for Japan’s manufacturing industries, firms, and factories, the post-Cold-War period was characterized not simply by stagnation and decline, but by multifaceted interactions among stagnation, struggles, and resilience.

Clubs and investors need to have full knowledge of the economic conditions within the football game, because the movement of the market value provides a strong force on the transfer strategy as well as the wage structure and financial regulations of fair play. A bibliometric analysis has been conducted to evaluate the market valuation of professional football players and investigate the extent to which the idea of performance metrics and the institutional factors have influenced the valuation practices of clubs in the transfer market. A sample of 357 publications, which are listed in the Scopus database between the year 2000 and 2025, was collected and utilized to determine the current trends and research gaps. VOSviewer was used to analyze the corpus and produced networks of co-authorship, co-citation, co-occurrence, and bibliographic coupling. The study reveals that recent research in the field of sports economics and finance is majorly written in Europe, published in journals dedicated to football business and economics, and uses more sophisticated tools, including machine learning, player-tracking data, and network analysis to determine player value in the transfer market. Network visualisations indicate three major areas like what drives transfer fees and wage rates received by clubs, how financial controls in leagues and revenue systems affect player values, and new valuation systems that combine on-field performance metrics with financial information. Since 2018, the trends have highlighted the high volatility of player values in an instant, the impacts of COVID-19 pandemic on salaries and market values, and the talent concentration required in order to create competitive balance. The research offers an extensive summary of the discipline, descriptions of under-researched field topics, including women football and lower leagues, and outlines the practical solutions on managing the club and future research directions.

This study aims to analyze the interactions among the minimum wage, unemployment rate, economic growth, and financial development in relation to inflation, as well as to identify causal relationship patterns among these variables. The research employs a quantitative approach using Vector Error Correction Model (VECM) analysis based on time-series data. Stationarity tests, optimal lag determination, stability tests, Granger causality tests, cointegration tests, and VECM estimation are conducted to examine the direction of relationships among variables and to estimate long-run effects in measuring the impact of each variable on inflation. The data utilized are secondary data obtained from official publications of relevant institutions and are analyzed using the E-Views statistical software. The results indicate that not all variables exhibit causal relationships. Inflation shows a one-way causal relationship with the unemployment rate, while financial development exhibits a one-way causal relationship with inflation. In addition, bidirectional causality is found between financial development and the minimum wage, as well as between financial development and economic growth. Long-run estimation results reveal that the minimum wage and unemployment rate have a positive and significant effect on inflation, whereas economic growth has a negative and significant effect on inflation. Financial development is also shown to have a positive effect on inflation. The findings underscore that inflation is influenced by a combination of labor market factors, macroeconomic conditions, and financial sector development; therefore, effective inflation control requires integrated and sustainable economic policies.

Nurses are crucial for high-quality healthcare, but there's a growing shortage. Wage inequality is a significant problem among nurses, affecting both nurses and patient care. This study investigates the wage gap among nurses in Iran. This study examined wage inequality among 595 nurses using wage quartiles, Lorenz curves, and a Gini coefficient (GC) decomposition. The decomposition method was used to analyze the contributions of within, between, and overlap subgroups to the overall wage inequality, along with the population share, wage share, and GC for each subgroup of nurses. The findings revealed that nurses in the top quartile earn 2.03 times more than nurses in the bottom quartile, with respective wage rates of $9.31 and $4.58. The total GC for nurses' wages was 0.16, indicating a moderate wage gap. Among nurses, those in specialized roles had the highest wage at $9.10 based on Purchasing Power Parity (PPP). This was followed by nurses aged over 40years ($8.30), nurses with over 15years of work experience ($8.15), and those working in psychiatric centers ($8.08). Conversely, the lowest wage rates among nurses were observed in those working in non-provincial hospitals ($5.51), followed by nurses in the private sector ($5.73), and nurses working in general hospitals ($5.76). The GC analysis revealed that the highest wage inequality was among nurses working in hospitals specializing in Ophthalmology and ENT (GC = 0.23), the private sector (GC = 0.18), and emergency departments (GC = 0.18). Conversely, the lowest wage inequality was observed in nurses working at the surgery department (GC = 0.10) and cardiology hospitals (GC = 0.11). The wage gap among Iranian nursing staff was moderate. Work experience, employment type, age, number of children, hospital specialty, workplace sector, and department significantly affected wage inequality among nurses, while gender and academic qualifications had no significant impact on the wage gap. Considering the importance of the wage gap for nurses' motivation and function, policymakers should consider these key determinants and develop targeted strategies to mitigate the wage gap among nurses.

I study the effect of viable technical change on the equilibrium profit rate in Classical-Marxian models of economic growth with alternative labor market closures. Capitalists adopt a new technique of production only if it is expected to increase the profit rate at the existing real wage rate. I consider three alternative closures: (a) constant real wage rate (labor surplus economy), (b) constant wage share (advanced capitalist economy with strong labor), and (c) constant unemployment rate (advanced capitalist economy with weak labor). I show that the equilibrium profit rate can unambiguously fall after viable capital-using, labor-saving (CU-LS) technical for an advanced economy with strong labor. JEL Classification : B51, C02

The present study was undertaken to analyse integration among wages of farm men, farm women, and non-farm labour in Godavari Delta Zone of Andhra Pradesh. Time series data on monthly average wages of farm and non-farm labour over a period of twenty years were used. The growth rate of farm men, farm women, and non-farm wages showed an increasing trend. The unit root test indicated that, the wage series became stationary after first differencing, and Johansen co-integration test confirmed the presence of a long-run relationship among the variables. The Vector error correction model revealed that, both men and women farm labour wages adjust to restore long-run equilibrium when short-run deviations occur. Whereas, non-farm wages showed divergence from equilibrium. Pairwise Granger causality results revealed a bidirectional causal relationship between farm men and farm women wages, while non-farm wages exhibit unidirectional causality toward both categories of farm wages. The findings of the study provide valuable insights for wage policy formulation, particularly in the context of agriculture and rural employment.

Floriculture plays a vital role in the horticulture sector of Karnataka, particularly in districts like Chikkaballapur where commercial flower cultivation is widely practiced. The present study was conducted in Chikkaballapur and Shidlaghatta taluks with a total sample of 120 flower growers, comprising 60 chrysanthemum growers and 60 gladiolus growers selected through random sampling. Data were collected using a structured interview schedule and analysed using frequency, percentage and rank-based methods. The findings revealed that high cost of inputs and planting materials, non-availability of labour, high wage rates, and inadequate irrigation were the major production constraints. Financial problems such as untimely credit, inadequate subsidies and complicated loan procedures further limited smooth cultivation. Marketing-related constraints including price fluctuation, high transportation cost, lack of transport facilities, perishability of flowers and middlemen exploitation also affected farmer profitability. Growers suggested timely supply of quality inputs, increased subsidies, effective marketing systems, formation of co-operatives, adoption of mechanization, provision of cold storage facilities and establishment of nearby markets to overcome these challenges. The study highlights the need for strengthened institutional support and improved infrastructure to enhance the sustainability and profitability of flower cultivation in the region.

This study investigates Cameroon and the Democratic Republic of Congo, both contending with significant technological disparities—defined as variations in capital-augmenting technological capacity across sectors that influence productivity and growth potential. Using data from the year 2015, the analysis employs a dynamic computable general equilibrium (CGE) model combined with a microsimulation approach. The study examines how capital-augmenting technological innovation (TI)-that is, improvements in the efficiency of capital use-affects key macroeconomic variables such as GDP growth, wage rates, consumption patterns, and household welfare. Results from the CGE simulations reveal that increased TI positively influences GDP growth through contributions from agriculture, industry, and transport sectors. Welfare and income effects benefit households engaged in innovative sectors, while investment and consumption responses differ across activities. At the micro level, higher TI reduces poverty rates in both countries, especially within agriculture, industry, and transport. The findings highlight the importance of targeted investments in technology-intensive sectors to maximise TI’s benefits for growth, income distribution, and poverty reduction. Policymakers are encouraged to foster innovation-friendly environments, support entrepreneurship, and promote inclusive growth strategies that enhance labour market outcomes and long-term welfare.

Many employers link wages at establishments outside of the home region to the level at headquarters. We show this using new data on 1,200 multinationals’ establishments across the world and linked employee-level data on their establishments in Brazil. Headquarters wage changes arising from minimum wage and exchange rate shocks are partially transmitted to workers employed in the same position abroad. Wage change transmission appears to be direct and results from firm-wide wage-setting procedures rather than associated technology or employment changes. “Anchored” wage setting is somewhat associated with particular characteristics of the job × employer × headquarters-establishment country-pair. (JEL F23, F31, J24, J31, J38, M16, O15)

An 'Austrian' Model of International Specialization

The article is devoted to improving methods for assessing the degree of compliance with the principles of social responsibility in the field of labor remuneration of Ukrainian enterprises. The authors propose methods for calculating indicators suitable for evaluating both the dynamics of the spread of the principles of business social responsibility and for comparing the results observed in different types of economic activity. In particular, it is proposed to supplement the assessment based on the ratio of labor productivity growth rates to the growth rates of wages with the use of the index of inequality of factor income distribution, which will reflect the ratio of per capita personnel costs to per capita incomes from profit per recipient of such type of incomes. That ensures an advantage compared with common indicators, which are not suitable for comparing the extent of implementation of social responsibility principles in different branches of the economy.It is substantiated that the period since the beginning of the full-scale Russian military invasion is characterized by an increase in the susceptibility of Ukrainian businesses to the principles of social responsibility, which is manifested in the equalization of the distribution of factor income. Despite the processes of forced militarization of the economy, the growing share of capital-intensive economic activities, and the intensification of production concentration, since the beginning of the full-scale war, Ukrainian businesses have mostly maintained the share of wages in the value added, which indicates the importance of institutional prerequisites for strengthening the social responsibility of business, in particular regarding wages. The factor inequality of income distribution has also decreased, as evidenced by the dynamics of the index calculated according to the author's methodology. The use of the proposed tools allows for improving the analytical support for the development of state policy on the regulation of incomes and wages, more accurately determining the current “margin of safety” that enterprises have to improve the conditions of remuneration.

Since the 1990s, there have been rapid increases in concentration ratios in many industries in the U.S., Australia and, we suspect, in other countries. Despite this, applications of GTAP continue to be based on pure competition or Melitz-style Large-Group Monopolistic Competition (LGMC). In either case, all firms are small, there is free entry, and industries make zero pure profits. Markusen challenges modellers to move to Small-Group Monopolistic Competition (SGMC) in which industries have high levels of concentration and firms are aware of the likely behaviour of their rivals. By making two generalizations of Melitz-LGMC specifications, we create a version of GTAP in which some industries are modelled as SGMC. First, we treat the demand elasticities perceived by firms for their products as variables. In our SGMC specification, markups over marginal costs, which depend on perceived elasticities, rise when these elasticities are reduced (in absolute terms) by anti-competitive practices. Second, we allow for sticky adjustment of the number of firms in an industry and simulate situations in which entry is blocked or partially blocked, allowing incumbent firms to make positive pure profits. As illustrated in our simulations, the emergence of pure profits has the potential to suppress real wage rates.

BackgroundMany persons living with dementia receive care from adult children. Providing care is mentally and physically demanding, and time intensive and may reduce caregivers’ lifetime earnings and wealth. Population estimates of the financial impact of dementia caregiving has been limited by lack of nationally representative, longitudinal data on changes over time of middle‐age adults’ work and time spent caregiving and their parents’ health, and of estimates using rigorous panel data methods.MethodWe used nationally‐representative data from 2012‐2018 waves of the Health and Retirement Study on the demographic, economic and health characteristics of respondents ages 50 to 64 and of their parents/parents‐in‐law (hereafter “parents”). Primary outcomes were caregiving for a parent with dementia and labor force status. We first used fixed effect models to estimate the probability of providing care to a parent with dementia and quantify the association of dementia caregiving and labor supply independent of unobserved differences. We then employed the United States Cost of Dementia Model (USCDM), a validated dynamic microsimulation model, to quantify the impact of dementia caregiving on lifetime earnings and wealth accumulation for a cohort of middle age adults.ResultWe used data from 7,522 respondents and their 12,010 living parents. Fifty four percent of respondents were female and mean age was 58. Sixty seven percent of respondents’ parents were female and mean age was 82.7. About one‐fifth (20.4%) of respondents had a least one parent with dementia. Among respondents who had a parent with dementia, 19.4% were providing care for an average 17.9 hours per week. Among dementia caregivers, 57.5% were in the labor force. A 10% increase in wage rate was associated with a 0.08% decline in the probability of being a dementia caregiver. The likelihood of working was reduced by 3.4% for dementia caregivers relative to non‐caregivers.ConclusionDementia caregiving is common among middle age adult children and reduces their labor supply. For most workers, earnings levels peak at middle age and labor market exits are permanent. Ongoing work employs dynamic microsimulation to quantify the impact of dementia caregiving on lifetime earnings and household wealth accumulation and differences by sex, race, and education.