Alizar Hasan

A structural equation model for evaluating the relationship between total quality management and employees’ productivity

Purpose The purpose of this paper is to analyze the influences of TQM implementation on employees’ productivity in crumb rubber industry (case study conducted in the XYZ firm), and analyze the predominant factors affecting employees’ productivity in order to establish the success of TQM implementation. Design/methodology/approach Data used in the research was primary data obtained from interview and questionnaire, and secondary data obtained from the study of literatures, internet, and company’s documents. The number of respondents in this research was 191. The analysis was done through structural equation modeling (SEM) using the smart partial least square software. Findings The findings of this study showed that TQM implementation had positive influences on employees’ productivity in XYZ. Tool is the most predominant factor in order to achieve a successful TQM implementation in XYZ. Therefore, the XYZ company will need to work on improving the development and management of the tool which has been available to sustain the effectiveness of TQM practices. Research limitations/implications Using a large sample size in the SEM method could improve the results. The implications of this study can be demonstrated through how top managers in this rubber company can improve their employees’ productivity through total quality management practices. Practical implications This research is useful for manufacturing companies in Indonesia, especially in the crumb rubber industry. Originality/value This research used the variable based on the empirical research. TQM was measured using six indicators: human resources, standard, tools, organization, internal audit, and training and education. On the other hand, the work productivity of employees is measured by four indicators: work willingness, work ability, work environment, and work relations.

Assessing the Impact of IT Competency on Organizational Learning Capability of Indonesian Manufacturing Firms

This paper investigates a development of single machine batch scheduling for multi items with dependent processing time. The batch scheduling problem is to determine simultaneously number of batch ( ), which item and its size allocated for each batch, and processing sequences of resulting batches. We use total actual flow time as the objective of schedule performance. The multi item batch scheduling problem could be formulated into a biner-integer nonlinear programming model because the number of batch should be in integer value, the allocation of items to resulting batch need binary values, and also there are some nonlinearity on objective function and constraint due to the dependent processing time. By applying relaxation on the decision variable of number of batch ( ) as parameter, a heuristic procedure could be applied to find solution of the single machine batch scheduling problem for multi items.