Managers are ever seeking for better ways of managing their constraints to improve their company’s value chain performance and competitiveness. Although previous literature explored constraint management, it was inconclusive as to how constraint management could affect the value chain performance in tea processing chains. The purpose of this study is to determine the relationship between constraint management and firm value chain performance of tea processing firms. This study undertook an empirical study using survey questionnaire design to collect data. The respondents were production managers who have experience in production activities. The study applied multiple correlation and regression models to test the hypothesis. The results indicate that constraints management had a significant positive impact on improvement in quality, time, flexibility, cost and resource utilization in tea firms. This study provides a broad analysis of how organizations can improve their value chain performance for sustainable development by managing various constraints in the internal value chain. To the best of the authors’ knowledge, this is the first empirical study of the relationship between constraints management and value chain performance using data from tea processing firms operating in Kenya.

The theory of constraints is an approach for production planning and control, which emphasizes on the constraints in the system to increase throughput. The theory of constraints is often referred to as Drum-Buffer-Rope developed originally by Goldratt. Drum-Buffer-Rope uses the drum or constraint to create a schedule based on the finite capacity of the first bottleneck. Because of complexity of the job shop environment, Drum-Buffer-Rope material flow management has very little attention to job shop environment. The objective of this paper is to apply the Drum-Buffer-Rope technique in the job shop environment using a Markov chain analysis to compare traditional method with Drum-Buffer-Rope. Four measurement parameters were considered and the result showed the advantage of Drum-Buffer-Rope approach compared with traditional one.

This study develops an effective method to measure value chain performance and rank them based on qualitative criteria and to determine the ranking order of the various forms of performance under study. This approach integrates the advantage of grey systems theory and TOPSIS to evaluate and rank value chain performance. Grey-TOPSIS approach has been applied to measure and rank the value chain performance of various firms. The results indicate that the proposed model is useful to facilitate multi-criteria decision-making (MCDM) problem under the environment of uncertainty and vagueness. The model also provides an appropriate ranking order based on the available alternatives. The Grey-TOPSIS approach that will be useful to the managers to use for solving the similar type of decision-making problems in their firms in the future has been discussed. Even though, the problem of choosing a suitable performance option is often addressed in practice and research, very few studies are available in the literature of Grey-TOPSIS decision models. Also, Grey-TOPSIS model application in the tea processing firms is non-existence hence this study is the very first to apply this model in evaluating value chain performance in the tea processing firms.

This study presents an empirical investigation to measure the relationship between traditional accounting performance measurement as well as theory of constraint-based figures with operating cash flow. Traditional accounting measurement includes net profit and return of investment and theory of constraint method includes net profit and return of investment based on theory of constraints. The study selects 69 firms list on Tehran Stock Exchange over the period 2000-2010. Using panel data and fixed effect, the study performs regression analysis and the results confirm that there was a positive relationship between net profit measured by theory of constraints and cash flow and it can be effectively used for performance measurement.

DOI: 10.5267/j.msl.2013.07.017
Keywords: Theory of constraints;; ;

Product mix problem is one of the most important decisions made in production systems. Several algorithms have been developed to determine the product mix. Most of the previous works assume that all resources can perform, simultaneously and independently, which may lead to infeasibility of the schedule. In this paper, product mix problem and scheduling are considered, simultaneously. A new mixed-integer programming (MIP) model is proposed to formulate this problem. The proposed model differentiates between process batch size and transfer batch size. Therefore, it is possible to have overlapped operations. The numerical example is used to demonstrate the implementation of the proposed model. In addition, the proposed model is examined using some instances previously cited in the literature. The preliminary computational results show that the proposed model can generate higher performance than conventional product mix model.

The theory of constraints (TOC) is a management tool, which considers any manageable system as being limited in reaching more of its objectives by some constraints. According to TOC, there is always, at least, one single constraint, and TOC implements a concentrating process to detect the constraint and restructure the remaining of the organization around it. This paper presents an overview of different perspectives of TOC and its implementation in different industries such as project management, quality management, outsourcing, product mix, make-to-buy, accounting, banking and health care, etc. The results indicate that the method has been extensively implemented in different areas of accounting.