Search results

Many scholars and practitioners in the fields of business and management have recently published theoretical and empirical studies on the subject of business culture and its impact on its growth and effectiveness; yet, there has been a dearth of research on the topic of how organizational culture affects productivity. Moreover, there are hardly any theoretical or empirical research that examines these two concepts within the context of a micro-enterprise. This chapter uses a sample of 279 Ancash Region microenterprises to investigate the effect of local entrepreneurial culture on businesses’ overall performance. Among the four types of entrepreneurial cultures studied, only the Hierarchical culture was shown to have no effect on the degree of performance of the microenterprises. There is evidence of a significant causal relationship between the variables studied, the coefficient of determination was; business performance (r² = 0.796), with an SRMR of 0.037, the confirmatory model is relevant within its range of accuracy, while market culture has the greatest impact on business performance.

The development of information technologies has led to a considerable transformation in human resource management from conventional or commonly known as personnel management to modern one. Data mining technology, which has been widely used in several applications, including those that function on the web, includes clustering algorithms as a key component. Web intelligence is a recent academic field that calls for sophisticated analytics and machine learning techniques to facilitate information discovery, particularly on the web. Human resource data gathered from the web are typically enormous, highly complex, dynamic, and unstructured. Traditional clustering methods need to be upgraded because they are ineffective. Standard clustering algorithms are enhanced and expanded with optimization capabilities to address this difficulty by swarm intelligence, a subset of nature-inspired computing. We collect the initial raw human resource data and preprocess the data wherein data cleaning, data normalization, and data integration takes place. The proposed K-C-means-data driven cuckoo bat optimization algorithm (KCM-DCBOA) is used for clustering of the human resource data. The feature extraction is done using principal component analysis (PCA) and the classification of human resource data is done using support vector machine (SVM). Other approaches from the literature were contrasted with the suggested approach. According to the experimental findings, the suggested technique has extremely promising features in terms of the quality of clustering and execution time.

The market for insuring insect damage is far from complete. This study introduces a new type of derivative instrument‐insect derivatives‐that provide growers a market‐based means of transferring insect risk to speculators or others who may profit from higher insect populations. A risk‐neutral valuation model is developed and applied to Bemisia tabaci population data. Economic simulation models show how insect derivatives can improve risk‐return results for a representative cotton farm in the Imperial Valley of California. The results suggest that insect derivatives may become important risk management tools for a wide range of growers.

The textile sector struggles with cotton stickiness from honeydew contamination. It hurts agriculture and marketability. This study aims to examine how bacterial enzymes could reduce honeydew-contaminated cotton adherence in textile businesses sustainably.

Enzyme was extracted from bacteria isolated from the fermented bamboo shoots “Lung siej”. The enzyme was tested for α-glucosidase using p-nitrophenyl-α-D-glucopyranoside as a substrate. Design of experiments determined enzyme activity temperature and reaction time. Laboratory-prepared artificial honeydew was added to ginning mill cotton to show honeydew contamination. After enzyme treatment, sticky cotton was tested for microscopic examination, ultraviolet (UV), Benedict’s, Elsner colorimetric, high volume instrument (HVI) and viscosity tests.

The bacterial isolate is characterized as Lysinibacillus sp. as confirmed by 16S rRNA gene sequencing. The enzyme extracted was identified as α-glucosidase. The ideal temperature and reaction time for enzymatic activity were 32 °C and 35 min, respectively, using central composite design. The microscopic examination, UV test, Benedict’s test, Elsner colorimetric test, HVI test and viscosity test showed that bacterial enzyme treatment reduced cotton fiber adherence.

Although few patents have examined the effect of yeast enzymes, to the best of the authors’ knowledge, a bacterial enzyme is investigated for the first time to reduce the adhesion of honeydew-contaminated cotton.

The purpose of this paper is to review the life of the famous mathematician Kiyosi Itô and discuss his influence on the study of agricultural finance and agricultural economics.

This paper is a qualitative historical review.

The paper provides a biographical stretch of Itô's life. It is shown that his influence started to infiltrate the agricultural economics profession at around 1985 and is currently a major influence of a range of economic issues from farm policy to agricultural investments.

The biography is limited to a review of Itô's academic life and influence.

The paper offers a historical perspective on how probability emerged as a critical piece of the economic puzzle. For scholars and practitioners of agricultural finance, the paper provides an in depth review of how Itô processes have, and can, be used.

This paper provides a historical perspective on Itô that is of use to students and scholars of rural credit. This is the first “biography” of Itô to discuss his influence on agricultural finance and agricultural economics.

The widespread introduction of genetically modified (GM) crops may change the effect of agriculture on the environment. The magnitude and direction of expected effects are still being hotly debated, and the interests served in this discussion arena are often far from those of science and social welfare maximization. This chapter proposes that GM crops have net positive environmental effects, while regulatory responses focus mainly on environmental concerns, giving an unbalanced picture of the regulatory context. This unbalance supports the hypothesis that environmental concerns about GM crops have been politically instrumentalized and that more attention should be paid to regulatory responses considering the environmental benefits of this technology. It is also argued that a number of environmental effects have not yet been quantified and more research is needed in this direction.

The purpose of this paper is to provide a general discussion of how techniques from financial engineering can be used to investigate the economic costs of farm programs and to aid in the design of new financial products to implement margin protection for dairy farmers. Specifically the paper investigates the Milk Income Loss Contract (MILC) and the Dairy Margin Protection (DMP) program. In addition the paper introduces the concept of the Milk to Corn Price ratio to protect margins.

The paper introduces and reviews the tools of financial engineering. These include the stochastic calculus and Itô's Lemma. The empirical tool is Monte Carlo simulations. The approach is part pedagogy and part practice.

In this paper the authors illustrate how financial engineering can be used to price complex price stabilization formula in the USA and to illustrate its use in the design of new products.

In this paper the authors illustrate how financial engineering can be used to price complex price stabilization formula in the USA and to illustrate its use in the design of new products.

Farm programs designed to protect dairy farmers margins are designed in a seemingly ad hoc fashion. Assessments of programs such as MILC or DMP are conducted on an ex-post basis using historical data. The financial engineering approach presented in this paper provides the means to add significant depth to the assessment of such programs which can be used in conjunction with Monte Carlo simulation to identify alternative model structures before they are written into law.

This paper builds upon an existing literature. Its originality is in the application of financial engineering techniques to farm dairy policy.

This paper aims to provide a “biography” of sorts on Agricultural Finance Review. The paper tracks the evolution of Agricultural Finance Review from its introduction in 1938 to its current status.

The paper is based on a complete review of every paper and every issue. Not all papers were read by the author, but key papers of interest that in one way or another made significant contributions to the study of agricultural finance were reviewed.

The paper shows the evolution of agricultural finance from the early days of reporting financial data in the 1930s and 1940s, to its emergence as a major and significant sub discipline of the general field of agricultural economics.

As indicated, not all papers were fully reviewed or read. It is possible that papers identified as “firsts” may have been preceded by other papers. Nonetheless the paper identifies the basic evolutionary path of the journal and defines key points in time when a paradigm shift emerged to change the direction of this discipline.

As Agricultural Finance Review transitions from the Department of Applied Economics and Management at Cornell University to Emerald Group Publishing Limited, this “biography” provides readers with a general overview of the journal's and the discipline's historical development.

This paper is simply a review of the existing literature found in Agricultural Finance Review.

The purpose of this paper is to investigate weather risks facing Chinese farmers, and to determine whether farmers would have a preference for weather insurance over other types of agricultural insurance.

The data are based on 1,564 farm households surveyed in Shaanxi, Henan, and Gansu provinces in Central China between October 2007 and 2008.

Results suggest that the greater risk for farmers is drought followed by excessive rain. Heat is less critical as a risk but more significant than cool weather. Results suggest a strong interest in precipitation insurance with 50 and 44 percent of respondents indicating strong interest in the product. Supplementary results indicate that interest is equal between planting, cultivating, and harvesting. Furthermore, results suggest that farmers are willing to adopt new ideas, and where possible action has already been taken to self‐insure through diversification and other means.

This research is based on primary data gathered in China. However, the authors are limited in the access to Chinese weather station data to illustrate how weather insurance operates. Instead, the authors use weather data from the weather station in Ashland, Kansas which has similarities to the wheat growing regions of China. While the example is for illustrative purposes only, the authors cannot claim that it actually represents premiums that might actually be found in China.

The Chinese Government has within the past year authorized an investigation into agricultural insurance. The burst of research and applications of weather insurance in both developed and developing countries suggest that a wide array of applications could be feasible in China. The results are encouraging because they suggest that farmers in China would have an interest in purchasing weather insurance.

The authors believe that this is the first study conducted on weather insurance in China. The survey instrument is designed to specifically determine what weather risks are important to Chinese farmers and the interest that farmers would have in using such a product.

Bales of cotton run through the gins and textile mill instruments, stick to them and make it cumbersome for the ginning mill workers. This is so because more time and money have to be invested in cleaning these instruments. The stickiness of cotton causes health hazards to the workers, decreases the yarn quality and economic loss to the textile industry. The effect of cotton stickiness on textile ginning, various methods for cotton stickiness detection and the steps for reduction are discussed.

The different methods that are available for detecting and measuring cotton stickiness are described. The sugars that cause stickiness are either of plant origin (physiological sugars) or from the feeding insects (entomological origin). The methods for stickiness detection and reduction are discussed under physical, chemical and biological categories.

This review suggests possible ways to mitigate cotton stickiness.

One of the major issues of the textile industry is honeydew-contaminated cotton stickiness. However, there are few papers on detection methods for analyzing honeydew cotton stickiness along with the approaches to reduce stickiness. This paper summarizes different methods along with a study for detection as well as reduction of cotton stickiness.