In the present study, the direct, indirect and total effects of job characteristics on organizational citizenship behavior are expressed in a structural equation model using job satisfaction as the parameter, and then quantitatively analyzed and verified based on the data from 832 individual responses. As the results support the hypothetical model, it was confirmed that designing a job, as shown in the study, to have specific job characteristics such as ‘task significance’, ‘feedback’ and ‘autonomy’, will raise job satisfaction and encourage organizational citizenship behavior. This is contrary to the conventional model of utilizing an indirect effect, in which a job is designed based on job characteristics that foster job satisfaction in order to raise job satisfaction, which in turn, is expected to promote organizational citizenship behavior.

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OpenStreetMap(OSM) artifacts and OSM community activities are a process of generating information using a variety of social activities that can contribute to society in disaster prevention, education, welfare, industry, tourism, and regional revitalization. OSM activities in Japan started in 2008. Many artifacts have been created by small contributors. It is necessary to continue to maintain the artifacts created in order to become a sustainable community. However, there are various problems. In this study, the authors aim to generalize an example of collective intelligence knowledge. They propose providing feedback to the community to enable the OSM community in Japan to become sustainable. In general, when the artifacts are increased rapidly by a small number of contributors, rough granularity of the artifacts can be expended. The number of OSM contributors in Japan is small. There is a possibility that a sufficient large amount of artifacts cannot be updated. The authors consider objects and rough artifacts. This paper examines a hypothesis, resulting in three findings verified through the analysis of real data. Compared to other regions, Japan's OSM has a very large number of artifacts with respect to the number of contributors and the small number of tag artifacts. If this is the case, while work has been done actively through this small group of contributors, this creates uncertainty for the future of sustainable community activities.

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In current society, new electronic equipment is developed and used according to the needs of consumers. As time passes, the products become obsolete as the result of competitive product development, and they are replaced by products with more or improved functions and offered at a cheaper price. The product life cycle is referred to as “PLC” and it consists of four stages: introduction, growth, maturity and decline. In the decline stage of the PLC, the manufacturer has to analyze the market behavior, and judge how long the current product will be sold and when the next-generation product will be introduced. This paper proposes a new model and methods to analyze the decline stage. On the background of the decline behavior in the PLC for electronic equipment, technological progress enables various functions to be incorporated into a single product according to a consumer's need. This paper focuses on the shift from single-function products to multifunction products, and analyzes the phenomena using a regression analysis for current products and determining the number of newly developed products to produce.

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Distance metric learning is the method of learning the relevant distance metric from a training dataset by considering statistical characteristics. In order to gain a desirable distance metric, the optimization problem under an arbitrary constraint is solved. However, the representative algorithms of distance metric learning need to perform eigendecomposition at each iteration. Therefore, if the dimensions of the input data become large, the computational cost will increase drastically and it is difficult to calculate the optimal solution in a realistic amount of time. In addition, those distance metric learning methods are formulated by assuming a global (unique) metric matrix for the total vector space. Therefore, the global metric matrix cannot take into account the difference in statistical characteristics between each category. To improve those problems, the authors introduce different metric matrices for each category and propose a way to estimate the plural matrices using category information that applies the method of Mochihashi et al. The estimated metric matrices reflect the statistical characteristics of each category. The formulation of classifications by template matching and the k-NN method making effective use of the metric matrices is proposed. To verify the effectiveness of the proposed method, a simulation experiment is conducted using the benchmark data of high-dimensional and low-dimensional input data.

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In this paper, the effect of constraints is shown in the case of solving a constraint satisfaction problem (CSP) using linear programming (LP). A timetabling problem (TP) is formulated as example CSP. Then, the authors try to solve the problem using a simplex method in order to get the exact solution by selectively varying the constraints. Using the results obtained, how constraints affect the solutions obtained are examined. The computation time and simplex pivot count are observed, excepting the constraints that do not affect the feasible TP solutions. Certain kinds of constraints are shown to make the problem difficult. As the result, it is found that constraints, such as giving two successive classes and limiting the number of times giving the same classes in a day, is a major factor for making the problem complicated. In addition, a method for importing ambiguous constraints is proposed.

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In Japan, many fresh agricultural products are distributed from farmers to consumers via agricultural cooperation, wholesalers and retailers. Farmers' markets have attracted considerable attention as a new distribution system for agricultural products. A key characteristic of farmers' markets is a distribution system without intermediate wholesalers and retailers between the farmers and consumers. Thus, consumers can buy fresh products at a relatively inexpensive price and farmers can sell their non-standard products at low price. Recently, it has become one of the major distribution channels for fresh agricultural products in suburban areas. However, farmers' markets have experienced problems with sales, cultivation, inventory and quality management. This paper proposes a vendor-managed inventory (VMI) system for fresh agricultural products. It is difficult to supply agricultural products adequately to meet demand because of the seasonality and other uncertainties. Therefore, inventory management systems in which vendors seize the leadership in decision-making, are suitable for fresh agricultural products in terms of flexibility in supply. This paper summarizes the introduction of a VMI system to a farmers' market by analyzing the use of a VMI support information system, sales/inventory data and an inquiry survey of farmers. These results can provide guidelines for utilizing the management system in farmers' markets.

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The Japanese forestry industry has been in decline due to major factors such as low productivity in the forestry, the increasing import of wood from overseas, declining wood prices and a decrease in wood demand. In order to revitalize the forestry economy, productivity in the forestry must be enhanced greatly. Accordingly, the author has been studying logging systems using forestry vehicles and machines for the purpose of increasing productivity. In this paper, the H-type operation system is researched. In the H-type operation system, two long wire ropes are strung in the forest and felled trees are conveyed to a workshop by hanging them on the wire ropes. The system is analyzed and is shown where the workshop should be placed in the forest for conveying felled trees to the workshop most efficiently. Moreover, a new H-type operation system for greatly improving worker productivity is proposed.

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Random numbers obeying beta distribution are utilized for simulation analyses of various stochastic models. However, the procedure for generating beta random numbers is limited depending on the values of the parameters. Therefore, in this paper, a unified procedure for generating beta random numbers independent of the values of the parameters is investigated using Wilson-Hilferty approximation and Stuart's proposition.

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