PRODUCTIVITY MANAGEMENT (BEYOND MANAGEMENT)
Year:2019 | Volume:13 | Issue:50 |Papers Count:8

Promoting productivity is an essential prerequisite for organizational survival in today's highly competitive and dynamic contexts. Hence, a vital managerial task concerns the efficient use of resources that can guarantee achievement of goals and attainment of predicted outcomes. A necessary condition for improving sustainable productivity is identification and optimizing challenges and issues that are closely associated with organizational productivity. Therefore, the current exploratory, applied and mixed-method study presents a model of the main problems in improving productivity among employees in Tehran Municipality. Initially, the data obtained from structured interviews with 10 human resource management experts in the field were analyzed via Theme Analysis and Structural Equation Modeling and the effective factors were coded and categorized as a model. Further, the model was operationally tested quantitatively using the views of 384 managers and experts in the Department of Urban and Environmental Services of Tehran Municipality. To this end, the three-layer confirmatory factor analysis was undertaken using the PLS software. The results of the data analysis showed five main categories of factors effecting employee productivity including individual, managerial, organizational, cultural and technological factors. Any improvement in the productivity of human resources in this organization relies on prerequisite enhancement of status quo of these factors.

Owing to the key role small and medium enterprises play in achieving social and economic goals, it has become gradually more vital to scrutinize their performance. Human resource development via expanding organizational and employees’ capabilities guarantee survival and functional improvement of such companies. This descriptive mixed-method research was thus undertaken to identify the dimensions, components and indicators of human resources development in SMEs and explicate the factors affecting it based on the threedimensional management model. The research sample in the qualitative phase comprised a panel of 25 professors and experts from different universities and industries selected via snowball sampling procedure. In the quantitative phase, the research population comprised all manufacturing organizations and companies with 10-99 employees and operating under the name of SMEs. Using a two-step purposeful cluster sampling based on geographical distribution and the company’ s orientation, nine provinces and two randomly selected cities in each province were chosen to form the cluster sample of 384 workshops. The research data were collected via interviews with experts that were analyzed using the Delphi technique to form the 50-item questionnaire which was employed in the quantitative phase. The research data were further analyzed using Mic Mac Software to locate the identified variables and exploratory analysis was conducted to define the components that were effective on human resources.

Knowledge Management discipline is still in its infancy in Iran, and thus, includes numerous unknown and unexplored issues. Although organizations, especially the University of Mazandaran which is the case study of this research, have gradually acknowledged the importance of Knowledge Management in their different units, it is still far from operationalization. Various units of Mazandaran University must consciously concern themselves with this issue and take preventive actions to take maximum advantage of this opportunity. The current study aimed to design and implement an optimal Knowledge Management plan. To this end, the researcher applied a mixed-method approach using metasynthesis and Interpretive Structural Modeling techniques to assess the maturity of Knowledge Management and to design a model for optimizing its implementation at University of Mazandaran. Meta-synthesis results led to the identification of 98 sub-criteria (code), 14 criteria and three main dimensions in implementing Knowledge Management which were screened and localized by the researchers using Delphi technique and based on expert views and further employed to assess the maturity of knowledge management at Mazandaran University. The results of the analysis revealed that Knowledge Management was at an undesirable maturity level. The study offers a number of implications and suggestions to promote the maturity level of knowledge management at this university.

Oil, gas and petrochemical industry managers are nowadays preoccupied with finding ways of punctually completing projects while maintaining the highest implementational standards and minimizing financial costs and environmental threats. Reaching a balance among time, cost, quality and environmental effects is a paramount goal for these managers since these goals are contradictory and focus on any of them can lead to changes in the others. The purpose of this applied mathematical research was hence to design an authentic simulated multi-purpose mathematical model that can review and resolve the issue of project scheduling and balancing time, cost, quality and environmental effects in multi-mode projects. Using the GAMS software and CPLEX solver, the Model was validated through Expanded Epsilon Limitation Method and the analytical results of various sensitivities are reported.

The study of the relationship between wage and macro variables of productivity and unemployment, as the link in employment economy, is of particular importance in the economy of Iran. The present study was conducted with the aim of offering a dynamic pattern for examining the effects of productivity, unemployment, training, and inflation on wage rate between 1971 and 2016. To this end, the ARDL Dynamic Model, along with short-term and long-term methods and error correction model, was employed. The results of estimating the research model indicated both short-term and long-term relationships among the research variables. Moreover, inflation rate, productivity and training were found to be positively and significantly correlated in such a way that an increase in training and productivity was found to promote a parallel raise the work force rage. However, unemployment was found to have a negative effect on the rate of workforce wage. Besides, the obtained results of the error correction model used to analyze short-term and long-term relationship indicated an error correction coefficient of-0. 30. In addition, the current difference of wage rate in the short run was found to be significantly affected by the current difference between productivity of the workforce and the inflation rate but not by the current difference of training. Finally, the current difference of wage rate was found to be negatively and significantly affected in the short run by the current difference of unemployment rate.

This study aimed to analyze the relationship among Humanized Flexible Manufacturing System (HFMS) enablers in auto-manufacturing Industries using the Fuzzy Cognitive Map (FCM) approach. The theoretical foundation of the study was set and consolidated through a comprehensive literature review and based on views from 10 experts in Iran auto-manufacturing companies. The research population comprised 20 auto-manufacturing industry experts familiar with the HFMS system and 320 employees at car manufacturing companies including Iran Khodro, Pars, and Zagros, Saipa, Kerman, Bahman and Modiran Khodro companies. A sample of 10 from the experts and 174 from the employees were randomly selected using Cochran Formula. The relationship among the HFMS system enablers was investigated by analyzing verbal tags in the form of FCM. The findings revealed that the most important flexible HFMS system enablers comprised employees’ commitment, availability of trained personnel, top management involvement and commitment, effective long-term planning, sound favourable financial condition, reduced maintenance cost, organizational work culture, employees’ satisfaction, provision of incentives and rewards and operational and control techniques. The findings underscore the key role of human factor in the FMS and signify the need for developing a road map in carmanufacturing companies that can be employed to prevent the loss of resources including human resources and updat the company’ s objectives and perspectives in the strategic planning process.

An important issue in the supply chain concerns minimizing response time for the delivery of goods to the final destination, which can be achieved through selecting the correct route. The optimal path connecting the origin and destination nodes through the least intermediate nodes is called the shortest path. The shortest path in supply chain networks considered in this paper concerns the problem of sending an order from an original node to a destination node on a network which lacks a perfect and permanent fixed structure. The queuing theory measures were employed in the present enquiry to find out the shortest path. Initially, the supply chain and queuing network were concisely introduced and then, the two-input and three-stage supply chain of Balan Sanaat Company was displayed. Each input order to the supply chain is represented by two stochastic variables including the occurrence time and the number of commodities to be delivered. Further, the measures of the performance and productivity measures were extracted via the queuing network approach to serve the purpose of the study which was to compute the minimum response time for the delivery of items to the final destination along the three-stage network. The average number of items that can be delivered during this minimum response time constitutes the optimum capacity of the queuing network. At each stage of the queuing network, decisions regarding the most appropriate delivery route to the next node in the shortest possible time is made right at the preceding delivery node.

Human participation and involvement have long been of concern in human social life and has now become a fundamental issue in bureaucracy. Accordingly, the current applied mixed-method research aimed to identify effective variables in implementing municipal public policy, and thereby, to find out an employee participatory pattern that can be implemented to promote cooperation among municipal employees and enhance productivity. To serve the purpose, a researcher-made questionnaire was designed. Initially, a profound literature review was undertaken to delineate employee participation variables. Further, the public policy making was delineated based on views obtained from 18 experts in the field of public administration and using the snow ball method. To collect the research data, a researcher-made employee’ s participation questionnaire including 10 factors and 58 prominent components was designed based on Delphi Method. The research population comprised all the mayors and municipality managers from the Northwest of the country out of which a cluster sample of 223 was selected. The data were analyzed descriptively and statistically via PLS Structural Equation Modelling and t-test. The results revealed that the executives’ behavioural, expertise, structural, management and executive skills, cultural, group, economic, environmental and participatory components play significant roles in affecting employees’ participation in implementing public policy. Based on the expert views and the findings, a practical model was proposed to enhance employee participation in implementing public policy.