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The quantitative understanding of the safe input management practices of vegetable producers is essential for both food safety and environmental protection. The purpose of this study is to investigate the current status of safe production in vegetable enterprises and examine the key risk factors affecting the safe production of vegetables from the perspective of agricultural inputs.

Based on the theory of risk analysis, a framework of safe vegetable production risk analysis is constructed from the perspective of production input behaviour. Based on 202 valid questionnaires in Beijing, China, this paper identifies direct risks in input management through statistical descriptive analysis; determines weights through an expert elicitation process and calculates weighted safety values accordingly; and finally uses a categorical regression model to explore the indirect risks affecting corporate safety production.

The results show that direct risk factors include seed treatment risk, pesticide and fertilizer use criteria risk, pesticide and fertilizer operation risk, and pesticide application object risk. The production safety value of Beijing's enterprises is found to be high in the north and south regions, and low in the central region. Finally, some indirect risk factors, namely the cognition of agricultural product safety laws, the cognition of pesticide safety intervals, the cognition of prohibited pesticides and the possession of brands, are found to have positive and significant impacts on the safe production behaviour of enterprises.

These findings provide entry points for interventions aimed at reducing dependence on pesticides and fertilizers and promoting input management for safe vegetable production in enterprises, thus avoiding vegetable safety incidents due to improper practices in the production chain.

This paper aims to conceptualise and measure the technical aspects of the division of labour (DoL) with a new survey indicator of technical complexity (ITC) at work.

Two technical criteria skills and functions are used to distinguish positions in the DoL and to cluster and rank them into a 28‐category ordinal survey ITC. The indicator's construct‐validity is tested by assessing the correlation between these criteria and occupational activities' levels of substantive and organizational complexity, as uncovered by categorical principal component analysis. Criterion‐validity is assessed by testing the indicator's ability to predict occupational prestige, absolutely and relatively to other indicators.

The indicator shows high levels of construct and criterion‐validity.

The paper contributes to a better understanding and measurement of technical constraints in the DoL, facilitating a future evaluation of their impact on class inequalities.

Previous research shows a positive effect of job satisfaction and retention on both workers’ and organizations’ welfare, it is important to understand whether the characteristics of a job and workers’ perceptions of certain job traits can predict job satisfaction and retention in an organization. This paper explores the effect of 18 job characteristics on the likelihood that a worker is satisfied with his or her job, the chance that he or she looks for an alternative employer in the following year and the number of years employed by the same organization.

The author adds to the current state of the literature on the importance of job characteristics in several ways. First, the author utilizes a list of 18 job characteristics or perceptions, which to the best of our knowledge is one of the most extensive sets of characteristics that has been considered. This allows us to examine lots of aspects of the job, and their connection to the outcomes of interest. Second, the author uses not only basic regression methods but also ordered Logit specifications to obtain more precise estimates of the effect of job characteristics on job satisfaction and workers’ propensity to look for a new job. Third, the author considers the possibility that a combination of job characteristics, rather than a single factor, influences the level of satisfaction with the job and retention, measured by the likelihood that a worker plans to look for an alternative job in the following year and the years at the current job. The author explores the latter through principal component analysis. Fourth, the author explores gender differences in the effect of job characteristics on job satisfaction and retention. Finally, the author discusses the implications of this research to policy decision-making and managerial decisions.

The author finds that personal development opportunities and job security are positively related to job satisfaction, and negatively related to the likelihood of looking for a new job. Opportunities for personal development have a stronger effect on job satisfaction of men than women. Male workers’ job satisfaction also depends on whether they are given enough time to complete assigned tasks. The perception of security in the current job, having reliable coworkers and receiving sufficient help in a job make it less likely for women to perform a job search. Fringe benefits encourage workers of both genders to stay in an organization longer. Job security also has a positive relationship with the years in a given job for women, but not for men.

The findings have implications for managers and policy decision-makers. For managers, it is important to be aware of the value male and female workers place on different job characteristics, because a number of studies show the importance of job satisfaction on the success of companies (Porter et al. 1977; Mobley et al., 1979; Tett et al. 1993; Posner et al. 1993), and the author shows that job satisfaction depends on different characteristics for men and women. In addition, managers’ awareness of the findings related to the factors that are likely to retain workers in a company is important because of the costs of recruiting new workers, including hiring, training and opportunity costs. For policy considerations, programs that help in matching employers with potential workers are likely to find good fits for both sides of the labor market if they direct women to jobs that provide more security, opportunities for personal development, and help at work. Jobs that offer more time to complete tasks would retain and increase the chance of keeping male workers satisfied with their job.

The purpose of the study is to analyse social and demographic factors that affect tax stamp compliance in Upper Denkyira East Municipal and Upper Denkyira West District in Ghana.

The study adopted a cross-sectional survey design to sample 783 micro-taxpayers through the use of multi-stage sampling technique. Primary data were collected from micro-taxpayers by using a structured interview. Ordered logit regression model was used to regress the extent of tax stamp compliance on socio-demographic factors in relation to tax stamp cases in the study area.

The study found that occupational association status, location, gender, type of business operated, age, level of education and household size are significant predictors of tax stamp compliance in the study area.

The originality of the study is in twofold. First, the study dwells on extant literature on social and demographic factors of tax compliance in general and specifically applies them to a special kind of presumptive tax, tax stamp, in Ghana. The study is also considered as the first of its kind to perform rigorous statistical analysis of social and demographic factors in relation to tax compliance.

Small-scale farmers in developing countries are undersupplied with capital. Although microfinance institutions (MFIs) have become well established in developing countries, they have not significantly extended their services to farmers. It is generally believed that this is partly due to the riskiness of lending to farmers. The purpose of this paper is to combine original data from a Madagascan MFI with weather data to estimate the effect of rainfall on the repayment performance of loans granted to farmers.

The basis of the empirical analysis is a unique data set of a commercial MFI in Madagascar and weather data provided by the German Meteorological Service. The repayment performance of loans granted to small-scale farmers is estimated using a two-step estimation approach based on linear probability models (LPMs) and a sequential logit model (SLM).

The results reveal that an excessive amount of rain in the harvest period of rice increases the credit risk of loans granted to small-scale farmers in Madagascar. Furthermore, the results confirm that credit features affect the repayment performance of loans.

Since the returns from weather index-based insurance (at least as a future contract) are perfectly correlated with weather events, the authors can set the effect of weather events on the repayment performance of loans equal to the effect of the returns of weather index-based insurance on the repayment performance of loans. Thus, the results imply that weather index-based insurance might have the potential to mitigate a certain part of the risk in agricultural lending.

The focus and results of the present study are very relevant for MFIs, potential providers of weather index-based insurances as well as for farmers. The results confirm that weather events are a primary reason for the risk perception of lenders in developing countries toward small-scale farmers. Future research should, hence, concentrate on the development of index-based insurances in agricultural lending and consider interventions on different levels, e.g., insurance on the farm and the bank level.

To the knowledge, this is the first study that combines original loan repayment data from a Madagascan MFI with weather data in order to estimate the effect of weather events on the repayment performance of loans granted to farmers. Furthermore, to the knowledge, this is the first study that uses a two-step estimation approach based on LPMs and a SLM to investigate the repayment performance in agricultural lending.

Constructing and evaluating behavioral science models is a complex process. Decisions must be made about which variables to include, which variables are related to each other, the functional forms of the relationships, and so on. The last 10 years have seen a substantial extension of the range of statistical tools available for use in the construction process. The progress in tool development has been accompanied by the publication of handbooks that introduce the methods in general terms (Arminger et al., 1995; Tinsley & Brown, 2000a). Each chapter in these handbooks cites a wide range of books and articles on specific analysis topics.

The purpose of this paper is to investigate the effects and relative influence of: surface floor area; number of trowelling machines used in the operation; machine floating ring diameter size; and operative employment mode, on power‐trowelling productivity of concrete surface floors.

To achieve this objective, a sufficiently large volume of productivity data was collected and analyzed using the categorical‐regression method. As a result, the effects and relative influence of the factors investigated on trowelling productivity were determined and quantified.

The findings show significant influence of the factors explored on the trowelling productivity of concrete surface floors, which substantiate the importance of the “economy of scale” concept, and confirm the negative effect of “overcrowding”. On the other hand, contrary to many previous productivity research findings, and anecdotal perceptions of industry practitioners, the results obtained provide little evidence to the positive impact of the subcontracting employment mode on the trowelling operation.

Further research into the influence of other factors which could not be determined by this study, i.e. quantifying the difference in trowelling productivity between the “walk‐behind” and “ride‐on” machine types, and the average change in the operation efficiency as a result of utilizing the 0.60 m “walk‐behind” floating ring diameter size, in comparison with the 0.80, 1.00, and 1.20 m explored ring‐size, is recommended. On the other hand, the results obtained suggest that for a specific surface floor area, there may be an optimum number of trowelling machines, which leads to optimum trowelling productivity. It is, therefore, recommended to determine this number in order to rationalize the use of such devices and optimize the efficiency of the operation.

The findings of this research can provide estimators, planners and construction managers guidance for reasonable estimates, effective planning and efficient operative utilization. The results obtained may be further used to “benchmark” the efficiency of the operation, and “formalize” the specific productivity knowledge acquired.

The outcomes of this study fill a gap in productivity knowledge of primary factors influencing an important surface floor finish technique, which is frequently encountered on concrete construction sites, especially parking structures, storages and industrial facilities.

The purpose of this paper is to specify the treatment options of manufacturing companies with the specific emphasis on recyclable wastes. The options are focused mainly on recycling instead of taking recycling issue as a sub‐function of environmental policies or reverse logistics disposition strategies. This paper also aims to find out if there are some relationships between those options and some characteristics of manufacturing companies.

A survey methodology is structured in order to collect pure categorical data. Pearson chi‐square and categorical regression analyses were carried out on a sample of 255 Turkish manufacturers mostly operating in the textile, furniture, automotive and machinery industries.

The results indicate that some characteristics that were expected to have relationships with the treatment options, are supported by the two analyses while others are not. For example, “employing at least an engineer” is in double‐supported and “collaboration with other companies for returns” is in the non‐supported characteristic.

The results can be used as a guideline for manufacturers when they try to find out what obstacles are making their companies less desirous of recycling. The companies will be able to eliminate those obstacles and gain some competitive advantages by recycling materials.

The approach to treatment options on recyclable wastes, from manufacturing companies’ point of view, links together the behavioural issues and institutional levels of those companies. This study is unique not only in handling those issues in this perspective by intensely focusing on recycling, but also by being the first large sample survey of those issues in Turkey.

The aim of the study is to propose certain agricultural policy measures for the financing and development of Greek farms, established by young farmers, based on the results of a clustering method suitable for handling socio‐economic categorical data.

The clustering method was applied to categorical data collected from 110 randomly selected investment plans of Greek agricultural farms. The investment plans were submitted to the “Region of Central Macedonia” administrative office, in the framework of the Operational Programme “Agricultural Development – Reform of the Countryside 2000‐2006” and refer to agricultural investments by “Young Farmers”, according to the terms and conditions of Priority Axis III: “Improvement of the Age Composition of the Agricultural Population”. The input variables for the analyses were the farmers' gender, age class, education level and permanent place of residence, the farms' agricultural activity, Human Labour Units (HLU) and farms' viability level. All these variables were measured on nominal or ordinal scales. The available data were analyzed by means of a hierarchical cluster analysis method applied on the rows of an appropriate matrix of a complete disjunctive form with a dummy coding 0 or 1. The similarities were measured through the Benzécri'sχ²distance (metric), while the Ward's method was used as a criterion for cluster formation.

Five clusters of farms emerged, with statistically significant diverse socio‐economic profiles. The most important impact on the formation of the groups of farms was found to be related to the number of HLU, the farmers' level of education and gender. This derived typology allows for the determination of a flexible development and funding policy for the agricultural farms, based on the socio‐economic profile of the formulated clusters.

One of the limitations of the current study derives from the fact that the clustering method used is suitable only for categorical, non‐metric data. Another limitation comes from the fact that a relative small number of investment plans were used in the analysis. A larger sample covering and other geographical regions is needed in order to confirm the current results and make nation‐wide comparisons and “tailor‐made” proposals for financing and development. Finally, it is interesting to contact longitudinal surveys in order to evaluate the effectiveness of the funding policy of the corresponding programme.

The study's results could be useful to practitioners and academics because certain agricultural policy measures for the financing and development of Greek farms established by young farmers are proposed. Additionally, the data analysis method used in this study offers an alternative way for clustering categorical data.