PRODUCTIVITY MANAGEMENT (BEYOND MANAGEMENT)
Year:2015 | Volume:9 | Issue:33|Papers Count:9

The purpose of this research is to measure and analyse the total factor productivity (TFP). The case under study is the industrial sector of Kordestan Province in Iran. In order to achieve this goal, based on the International classification of the commodities, (ISIC Riv, 2) and applying panel data for the period 2005-2011, the industrial sector is categorized into 23 groups and the productivity is measured. Since the data for the capital stock is not available for the Kordestan Province, it is calculated in this study first. Using various production functions, and selecting the most suitable functions, the elastisities, are then estimated. In the next step, the TFP is measured by applying the Divisia Index, for the period under consideration. The findings of this research show that TFP for the Industrial sector of Kordestan Province has reduced annually by 2 percent on average. However, the TFP in the industrial sector as a whole was 0.06 during the period under study.

Nowadays competition in the business has made attention to productivity, customer satisfaction and compliance with his requirements more important. In this regard, the effort of organization in order to meet this requirement is based on improving the existing processes in organizations and several improvement philosophies have been introduced. In this paper, mapping knowledge management as a tool to improve the process according to productivity concepts is discussed. It examines the relationship between components (culture, process of practice, policy and technology) and productivity. For data collection, the demographic information, knowledge management and human resources productivity questionnaires were used. To examine the relationship between the variables and their interaction, structural equation modeling was used through Excel and LISREL softwares. The results indicate the relationship between the two structures, or how to change the conceptual model of research. The significant relationship between the dimensions of knowledge of management is confirmed. Based on the results, the component of culture with 0.38 effect rates has the highest effect on human resource productivity, and the other dimensions, i.e. technology, policy, and process of practice are ranked next in priority, respectively.

Research and development (R&D) is a suitable strategy for increasing agricultural production and supply and alleviating poverty and food shortages. Research and development affects agricultural productivity and production in several ways. Spillovers of research and development from other sectors and foreign countries has an important role in increasing agricultural productivity. In this study, by using OLS and Almon distribution lag model, agricultural research and development policy and spillovers for the years 1959-2012 are evaluated .The results indicate that agricultural research and development elasticity is 0.311, other sectors research and development elasticity is 0.109, capital input import elasticity is 0.057 and intermediate input import is 0.046. So, supply of agricultural research and development parameter is 0.193, supply of other sectors research and development parameter is 0.068, supply of imported research and development (capital input) parameter is 0.035 and supply of imported (intermediate input) research and development parameter is 0.029.Therefore, agricultural research has more impact than other sectors research (spillovers) on agricultural productivity.

Despite the growth of labor organizations, little empirical research on the effects of fun at work has been done. In addition, measuring fun at work has not been done extensively. The direct relation of employee happiness to the productivity of organizations has encouraged organizations to achieve greater efficiency by training their employees to have fun at work. In this study, we have attempted to provide a definition of joy and happiness and to enumerate their benefits for organizations and managers in order to encourage them to create a happy environment for their staff. The statistical population includes the academic staff members of Tabriz Islamic Azad University, 120 of who were selected as research sample through the use of Cochran’s formula. Structural equation modeling has been used for data analysis. The results showed that fun at work has a positive impact on the productivity (job performance)of the individuals.

This paper seeks to investigate the effects of emotional intelligence on social-mental factors of human resource productivity with emphasis on mediator role of emotional creativity. The statistical population includes employees of Region 2 Mellat Bank in Tehran Province, 248 of who were selected for data analysis. A questionnaire is used for data collection. Dimensions of emotional intelligence come from bar-on model(1980), emotional creativity come from Averill (1999), and social-mental factors of human resource productivity comes from Tavari et al (2008). Variance-based SEM is used for analysing data. Results at 99 percent confidence interval show that emotional intelligence has positive and meaningful effects on social-mental factors of human resource productivity through emotional creativity.

Customer satisfaction in today's business environment has gained importance. Many companies to increase profits and customer satisfaction are focused on customer value. Customer relationship Management (CRM) is tools to enhance customer relationships has emerged as the principal competing companies. Successful customer relationship management in companies start from identifying customer value beacuse Customer value provides important information for the development and management. Techniques such as data mining has led to the development of customer relationship management in new competition areas so that companies can be profitable in business competition. Through data mining -the discovery of hidden knowledge database- organizations can identify valuable customer and predict their future behavior and take useful and knowledge-based decisions. The purpose of this research is to gain the effective features to select valuable customer that can classify customers based on population characteristics and other variables relating to transactions in classes very low profit, low profit, high profit and very high profit. In this study the influence of demographic characteristics including age, education and job level also affect the degree of branch, bank branch location and number of transactions on customer value will be checked. Dependent variable in this research is customer value that is classified into four categories. Statistical population is the all customers have an active checking account with Bank Saderat Iran in Tabriz city. To review the case, the CHAID decision tree data mining algorithms were used.Results showed that the variables age, education level of customer and bank branches have no significant effect on customer value and the number of customer transactions with bank has most effective in identifying the class of customer.

This study with the evaluation direction and with aim of four basic factors and elements of technology includes Techno ware; Human ware; Organization ware; and Info ware as THIO of technology main and basic factors in official organizations, recognized main hypothesis that mentioned factors are not balance at these official organizations. In relation of study goal, data collected from five available official organizations as sample through questionnaire, interview and science challenge. Statistical analysis and another results showed that four basic factors and elements of technology are not balance at official organizations and quantity of TCC as Technology Content Coefficient is different. The abstracts of results are as follows: Four technology factors of official organization with welfare and health activity from maximum to minimum gap with priority are Organization ware; Human ware; Info ware and Techno ware that this organization must notify to improvement of them for technology balancing, Four technology factors of official organization with touristy activity from maximum to minimum gap with priority are Human ware; Organization ware; Info ware and Techno ware that this organization must notify to improvement of them for technology balancing, Four technology factors of official organization with housing activity from maximum to minimum gap with priority are Human ware; Organization ware; Info ware and Techno ware that this organization must notify to improvement of them for technology balancing. Four technology factors of official organization with cultural activity from maximum to minimum gap with priority are Info ware; Human ware; Organization ware; and Techno ware that this organization must notify to improvement of them for technology balancing, Four technology factors of official organization with food activity from maximum to minimum gap with priority are Organization ware; Human ware; Info ware and Techno ware that this organization must notify to improvement of them for technology balancing, Four technology factors of official organization with banking activity from maximum to minimum gap with priority are Organization ware; Human ware; Info ware and Techno ware that this organization must notify to improvement of them for technology balancing.

Today consideration of knowledge management as a strategic need makes lack of enough knowledge the most significant issue. As a result, knowledge management is one of critical success factors in modern organizations and it is more important for project-based organizations. This article is the result of the survey done with thematic scope of the Knowledge Management basis in project-based companies, and the matter is studied among mid-level managers. By using Hadi Darami’s “success factors of Knowledge management in project-based companies”, a researcher-made questionnaire was devised. The Face and content Validity of the instrument was approved, the reliability of the instrument was approved by the reliability coefficient (Chronbach’s Alpha) of 0.916. In this article descriptive statistics, the kolmogroph-Smirnoph test, Spearman correlation coefficient, Binomial test, Friedman’s test and TOPSIS method have been used. The results show that the status of the organization infrastructure, Staff Motivation, and Human Resource Management factors are at a medium level and the status of the Strategy and Goal, Leadership and Management Support, Training, IT, and Culture factors are at a high level. Also, the priorities of the factors are: Strategy and Goal, IT, Organization infrastructure, Leadership and Management Support, Training, Culture, Human Resource Management, and Staff Motivation.

The aim of this research was to make study of the components of the learning organization and its compliance whit entrepreneurial strategies of the technical and professional organizations in Uromiyeh. The Statistical population consisted of technical and professional staff of uromiyeh. The sample of the study included 120 technical and professional staff who were randomly selected using stratified sampling. To collect the data, the researcher used the learning organization and entrepreneurial strategies questionnaires. To check the reliability of the questionnaires, cronbach's alpha coefficient was calculated which was 0.82 and 0.90 for entrepreneurial strategies and learning organization questionnaires respectively. The obtained data was analyzed by conducting descriptive and inferential statistics, T test, Friedman and Structural Equation Modeling analyses using SPSS and PLC software. The results revealed that the components of learning organization were above the mean at an optimal level. Moreover, the components of learning organization matched some of the strategies.