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Agriculture in Ethiopia relies heavily on traditional farm power sources and is designated by the lowest farm machinery access, in contrast to other Sub-Sahara African (SSA) countries. The purpose of this research is to analyze the heterogeneity of mechanization service transactions and factors determining farmers' cooperation in mechanization clusters and willingness to accept land consolidation.

The authors conducted a cross-sectional survey of producer households in major crop production areas in the Oromia, SNNPR, Amhara and Tigray regions. The sampling design involved three stages: districts were selected using a stratified sampling approach accompanied by simple random samples of kebele units and producer households in the second and final stages, respectively.

This study’s results show that mechanization service costs, service relationships, clustering and land consolidation exhibit significant heterogeneity across the study areas. Cluster farming was found to be advantageous against diseconomies, rationalized by upgrading the mechanization scale. The probit model parameterization of the probability distributions reveals that household, land, crop, mechanization service, remoteness and location-related factors determine participation in mechanization clusters and willingness to accept land consolidation.

Fostering cooperation by focusing on constraints and demand of users is suggested to reduce transaction costs and expand hired mechanization services to unaddressed areas. The findings are relevant to most SSA countries where mechanization development is hampered by land fragmentation.

Limited information is available on agricultural mechanization development for smallholder farmers, particularly in Ethiopia, and this study adds empirical evidence about the synergy between cluster farming and mechanization, horizontal coordination and alternative supply models.

Facility maintenance is critical for the operation and management of petrochemical plants. Maintenance work completed with higher productivity eventually contributes to better plant performance. Mechanization reduces workforce demand and can increase the productivity of maintenance work. The purpose of this paper is to assess the current mechanization level of the maintenance activities and then identify applicable technology solutions for productivity improvement in petrochemical facility maintenance.

This paper utilizes a mechanization level assessment method for global maintenance data collection and analysis. Subject matter experts’ interviews and market scanning were used to identify corresponding technology solutions.

The study discovered numerous maintenance activities with lower mechanization levels and identified more than 50 technology solutions applicable for maintenance productivity improvement.

This paper provides a roadmap for petrochemical maintenance work participants to assess their mechanization level status quo and identify technology solutions for higher maintenance work productivity. The method adopted is replicable and customizable for further applications with different plant conditions in the petrochemical sector and other industrial contexts.

The purpose of this study is to investigate the interactive relationship between non-farm employment and mechanization service expenditure.

The study employs an innovative two-stage probit least squares (2SPLS) model to analyze the survey data collected from 1,148 rural households in China. This model not only simultaneously estimates the impact of non-farm employment on mechanization service expenditure and the impact of mechanization service expenditure on non-farm employment, but also addresses endogeneity issues associated with these two activities.

The empirical results show that non-farm employment and mechanization service expenditure are jointly determined. In particular, the study finds that non-farm employment significantly increases mechanization service expenditure, and vice versa. The results are confirmed by an estimation that captures a dichotomous decision of mechanization service usage. The interactive effects of non-farm employment on mechanization service expenditure are heterogeneous between male and female household heads and among households with different member sizes. Further analyses reveal that (1) mechanization service expenditure increases with increasing non-farm working time; (2) local non-farm employment, rather than provincial non-farm employment, has a larger impact on mechanization service expenditure; and (3) the number of household members employed in non-farm works does not affect mechanization service expenditure significantly.

Although mechanization service markets are rapidly growing in many developing and transition countries, little is known about how service purchasing interacts with farmers' decisions to work in the non-farm sector. This study makes the first attempt by investigating the interactive effects of non-farm employment on mechanization service expenditure in rural China. The findings provide significant evidence for policymakers in China and other countries in their efforts to generate non-farm work opportunities and promote agricultural mechanization, with the aim of boosting rural development and improving farm economic performance.

The purpose of this paper is to investigate the impact of mechanization services on farm productivity in Northern China from an empirical perspective, with the aim to identify the underlying market and institutional barriers.

The authors apply the regression method with the control of village fixed effects to examining the relationship between capital–labor ratio, mechanization service ratio and farm productivity, using the panel data collected in 2013 and 2015 by CCAP.

Mechanization services improve farm productivity through substituting labor, but it may generate a less positive impact on farms who do not have self-owned capital equipment.

It is the first study to investigate how mechanization services affect farm productivity for grain producers in Northern China.

This study examines the adoption drivers of scale-appropriate mechanization in Nepal's maize-based farming systems. The authors also assess the contribution of scale-appropriate mechanization to the United Nations Sustainable Development Goals (SDGs) of zero hunger (SDG2) and no poverty (SDG1).

Propensity score matching and doubly robust inverse probability-weighted regression adjusted methods were applied to estimate the effects of mini-tiller adoption. These methods control the biases that arise from observed heterogeneities between mini-tillers users and nonusers.

The study findings show that farm size, labor shortages, draft animal scarcity, market proximity, household assets and household heads' educational level influence the adoption of mechanization in Nepal. Mechanized farms exhibited enhanced maize productivity, profits and household food self-sufficiency. Reduced depth and severity of poverty were also observed. Nevertheless, these effects were not uniform; very small farms (≤0.41 ha) facing acute labor shortages benefited the most.

The study results suggest that policymakers in developing nations like Nepal may wish to expand their emphasis on scale-appropriate mechanization to improve farm productivity and household food security, reduce poverty and contribute to the SDGs.

This first-of-its-kind study establishes the causal effects between scale-appropriate farm mechanization and SDG1 (no poverty) and SDG2 (zero hunger) in a developing nation.

Changing climate has increasingly become a challenge for smallholder farmers. Identification of technical, institutional and policy interventions as coping and adaptation strategies and exploring risks of their adoption for smallholder farms are the important areas to consider. The aim of the present study was to carry out an in-depth analysis of adaptation strategies followed and the associated risk premium in technology adoption.

The study was carried out in the dryland systems of three Indian states – Andhra Pradesh, Karnataka and Rajasthan – and was based on a survey of 1,019 households in 2013. The flexible moment-based approach was used for estimating the stochastic production function, which allowed estimation of the relative risk premium that farmers are willing to pay while adopting the technologies to avoid crop production risks.

In all the three states, the risk premium (INR ha⁻¹) was higher for farm mechanization compared to supplemental irrigation, except in the case of Andhra Pradesh. The higher the level of technology adoption, the higher the risk premium that households have to pay. This can be estimated by the higher investment needed to build infrastructure for farm mechanization and supplemental irrigation in the regions. The key determinants of technology adoption in the context of smallholder farmers were climatic shocks, investment in farm infrastructure, location of the farm, farm size, household health status, level of education, married years, expected profit and livestock ownership.

Quantification of the risk premium in technology adoption and conducting associated awareness programs for farmers and decision-makers are important to strengthen evidence-based adoption decisions in the dryland systems of India.

Addresses the standardization of the measurements and the labels for concepts commonly used in the study of work organizations. As a reference handbook and research tool, seeks to improve measurement in the study of work organizations and to facilitate the teaching of introductory courses in this subject. Focuses solely on work organizations, that is, social systems in which members work for money. Defines measurement and distinguishes four levels: nominal, ordinal, interval and ratio. Selects specific measures on the basis of quality, diversity, simplicity and availability and evaluates each measure for its validity and reliability. Employs a set of 38 concepts ‐ ranging from “absenteeism” to “turnover” as the handbook’s frame of reference. Concludes by reviewing organizational measurement over the past 30 years and recommending future measurement reseach.

The study reported here sought to provide a type of analysis more detailed than aggregate investigations but more generalisable than case studies. The extent to which upgrading and downgrading characterised US manufacturing industries in the 1960s, and the extent to which downgrading exacerbated underutilisation among production workers are examined. Special attention is then paid to determining whether mechanisation has an effect on the skills requirements of jobs.

The purpose of this paper is to present an updated overview of printed circuit manufacturing equipment from the perspective of “mechanization strategies and systems” in order to enable printed circuit board (PCB) manufacturers to select the appropriate equipment.

Ten process mechanization strategies were studied and illustrated with emphasis on the new conveyorized vertical plating and traditional horizontal conveyors, with some highlights of reel‐to‐reel chip on flex conveyorized plating equipment.

Novel mechanization continues to be created to enhance the technology, quality, and productivity of printed circuit manufacturing.

Mechanized equipment has the most controlled conditions for research and another publication referenced will supply information on sensors and controllers for modern high‐speed PCB processes.

The paper describes various mechanization strategies for equipment used in printed circuit manufacturing, combined with process sensors, automatic control, statistical design of experiments, and automation strategies that will present the best scenario for optimal PCB production.

The European states, which started the industrial revolution by making use of mechanical power, provided their agricultural development by producing new technology tools that will increase the production in the agricultural sector. The Ottoman Empire made many attempts to increase agricultural sector in the nineteenth century and implemented policies to increase production. In this direction, primitive agricultural tools were changed, and many encouraging steps were taken to adopt and spread modern technology in the country. As a result of the policies made, since the second half of the nineteenth century, the use of modern technology has increased in the provinces such as İzmir, Edirne and Adana and then in Konya and Ankara, since the railways reached the interior. Increasing accessibility to international markets with the development of commercial agriculture and railway construction are also important factors that encourage the use of machinery. When the use of machinery increased in the twentieth century, many machine companies opened dealers in the country and attempted to reach the inner parts of the country. With the increase in the use of modern agricultural technology, agricultural production has increased and provided significant benefits to the labor problem, especially in regions where commercial agriculture has developed. The effect of modern technology on the increase in production can be seen in the agricultural numbers in 1909–1914. When the agricultural census is taken into consideration, although the production areas did not increase, the production amount increased. However, the contribution of modern agricultural technology to production was still somewhat limited. The reason for this is that due to the high prices of agricultural machinery, small farm owners cannot supply these machines.