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Price volatility and scarcity have become a great problem in the distribution system of seasonal staple foods produced by the agricultural industry. There is a salient supply disparity during the harvest and planting seasons. This condition could cause disadvantages to stakeholders such as producers, wholesalers, consumers, and government. This paper proposes a buffer stock model under free-trade considerations to substitute quantitative restrictions and tariffs with an indirect market intervention instrument. This instrument was developed using a buffer stock scheme in accordance with a warehouse receipt system (WRS) and a collateral management system. A public service institution for staple food buffer stock (BLUPP) is proposed as the wholesaler's competitor, with as main responsibility to ensure price stabilization and availability of staple food. Multi-criteria decision-making is formulated as a single objective mixed integer non-linear programming (MINLP) model. The results shows that the proposed model can be applied to solve the distribution problem and can give more promising outcomes than its counterpart, direct market intervention.

Purpose: To develop LIRP (location-inventory-routing problem) model with considering multiple links and solve it using method of heuristic based on algorithm of simulated annealing. Method of heuristic for the LIRP model is applied in city of Jakarta to improve effectiveness and efficiency of the food supply chain. Design/methodology/approach: The LIRP model is developed using main references. To solve the model, this paper develops two methods, namely method of optimal and method of heuristic. Computational experiments are performed to obtain the efficiency of the method of heuristic. New design of food supply chain is resulted from the application of the method of heuristic in city of Jakarta. Findings: The new design of food supply chain resulted from the application of LIRP model in city of Jakarta reduces total cost by 18%, increases availability from 76% to 95%, and reduces the number of vehicles by 73%. This paper also shows that distance is not the only consideration to decide the traversed links in cities. Research limitations/implications: Average gap between method of heuristic and method of optimal in terms of total cost is 3.1%. Practical implications: Government of city of Jakarta can improve effectiveness and efficiency of the food supply chain by implementing the LIRP model. Social implications: Citizens of Jakarta are well provided with their needs of vegetables and fruits. Originality/value: The first LIRP model that considers multiple links to represent road networks in cities. The LIRP model developed in this paper consists of probabilistic demands, multi products, and multi echelons. Traditional markets, UCCs (urban consolidation centers) and province of suppliers are the places where decisions of inventory made ; Peer Reviewed

Indonesian Palm Oil Industry has the largest market share in the world, but still faces problems in order to strengthen the level of competitiveness. Those problems are in the industry chains, government regulation and policy as meso environment, and macro economic condition. Therefore these three elements should be considered when analyzing the improvement of competitiveness. Here, the governmental element is hoped to create a conducive environment. This paper presents the industry competitiveness conceptual model, using hierarchical multilevel system approach. The Hierarchical multilevel system approach is used to accommodate the complexity of the industrial relation and the government position as the meso environment. The step to develop the model firstly is to define the relevant system. Secondly, is to formulate the output of the model that is competitiveness in the form of indicator. Then, the relevant system with competitiveness as the output is built into a conceptual model using hierarchical multilevel system. The conceptual model is then discussed to see if it can explain the relevant system, and the potential of it to be developed into mathematical model.

Purpose: The purpose of this research is to develop an assessment model to identify phase of industrial cluster life cycle which comprises definition of the cycle phases, identification of assessment components, and characterization of each phase of cluster life cycle. Design/methodology/approach: This research uses the Delphi method to develop the conceptual model i.e. define phases of cluster life cycle and identify assessment components, and design typology of cluster life cycle. Findings: The proposed indicators used to assess industrial cluster phases are (i) concentration of industry, (ii) market accessibility, (iii) completeness of actors, and (iv) collaboration of stakeholders. Research limitations/implications: This study developed a conceptual model based on expert opinion in Indonesia. Given the limitations of experts in this field in Indonesia, it is necessary to develop advanced research involving more experts and if possible, to involve experts outside Indonesia. Practical implications: This paper provides an assessment conceptual model to identify phase of industrial cluster life cycle. The objective of assessing industrial cluster phases is to evaluate and improve the condition of industrial clusters and as basis for formulation policy interventions in accordance with each phase of cluster life cycle. The final results of this study are the position of each cluster on their life cycle, which reflects the condition of each industrial cluster. On a practical level, the assessment result could be used to improve the competitiveness of industrial sectors and help local and central government to formulate appropriate policy interventions. Originality/value: The paper provides an assessment conceptual model to identify phases of industrial cluster life cycle, which include definition phases, assessment components and typology of each phase of cluster life cycle based on assessment criteria. Research in this field was rarely done by the other researchers. ; Peer Reviewed

Purpose: The purpose of this research is to develop an assessment model to identify phase of industrial cluster life cycle which comprises definition of the cycle phases, identification of assessment components, and characterization of each phase of cluster life cycle. Design/methodology/approach: This research uses the Delphi method to develop the conceptual model i.e. define phases of cluster life cycle and identify assessment components, and design typology of cluster life cycle. Findings: The proposed indicators used to assess industrial cluster phases are (i) concentration of industry, (ii) market accessibility, (iii) completeness of actors, and (iv) collaboration of stakeholders. Research limitations/implications: This study developed a conceptual model based on expert opinion in Indonesia. Given the limitations of experts in this field in Indonesia, it is necessary to develop advanced research involving more experts and if possible, to involve experts outside Indonesia. Practical implications: This paper provides an assessment conceptual model to identify phase of industrial cluster life cycle. The objective of assessing industrial cluster phases is to evaluate and improve the condition of industrial clusters and as basis for formulation policy interventions in accordance with each phase of cluster life cycle. The final results of this study are the position of each cluster on their life cycle, which reflects the condition of each industrial cluster. On a practical level, the assessment result could be used to improve the competitiveness of industrial sectors and help local and central government to formulate appropriate policy interventions. Originality/value: The paper provides an assessment conceptual model to identify phases of industrial cluster life cycle, which include definition phases, assessment components and typology of each phase of cluster life cycle based on assessment criteria. Research in this field was rarely done by the other researchers. ; Peer Reviewed

Purpose: The purpose of this research is to develop an assessment model to identify phase of industrial cluster life cycle which comprises definition of the cycle phases, identification of assessment components, and characterization of each phase of cluster life cycle.Design/methodology/approach: This research uses the Delphi method to develop the conceptual model i.e. define phases of cluster life cycle and identify assessment components, and design typology of cluster life cycle. Findings: The proposed indicators used to assess industrial cluster phases are (i) concentration of industry, (ii) market accessibility, (iii) completeness of actors, and (iv) collaboration of stakeholders. Research limitations/implications: This study developed a conceptual model based on expert opinion in Indonesia. Given the limitations of experts in this field in Indonesia, it is necessary to develop advanced research involving more experts and if possible, to involve experts outside Indonesia. Practical implications: This paper provides an assessment conceptual model to identify phase of industrial cluster life cycle. The objective of assessing industrial cluster phases is to evaluate and improve the condition of industrial clusters and as basis for formulation policy interventions in accordance with each phase of cluster life cycle. The final results of this study are the position of each cluster on their life cycle, which reflects the condition of each industrial cluster. On a practical level, the assessment result could be used to improve the competitiveness of industrial sectors and help local and central government to formulate appropriate policy interventions. Originality/value: The paper provides an assessment conceptual model to identify phases of industrial cluster life cycle, which include definition phases, assessment components and typology of each phase of cluster life cycle based on assessment criteria. Research in this field was rarely done by the other researchers.

Purpose: The purpose of this research is to develop a model that will explain the impact of government policies to the competitiveness of palm oil industry. The model involves two commodities in this industry, namely crude palm oil (CPO) and refined palm oil (RPO), each has different added value. Design/methodology/approach: The model built will define the behavior of government in controlling palm oil industry, and their interactions with macro-environment, in order to improve the competitiveness of the industry. Therefore the first step was to map the main activities in this industry using value chain analysis. After that a conceptual model was built, where the output of the model is competitiveness of the industry based on market share. The third step was model formulation. The model is then utilized to simulate the policy mix given by government in improving the competitiveness of Palm Oil Industry. Findings: The model can accommodate government's policy mix which is then optimized. The model has been built structurally based on hierarchical multi-level system approach, while in the process element, the subprocesses are built using VCA approach. The model can simulate industry performance, and show that such government policy mix can improve the competitiveness of Indonesian palm Oil Industry. Research limitations/implications: The model was developed using only some policies which give direct impact to the competitiveness of the industry. For macro environment input, only price is considered in this model. Practical implications: The model can simulate the output of the industry for various government policies mix given to the industry. The techno-economic aspect is also discussed. Originality/value: This research develops a model that can represent the structure and relationship between industry, government and macro environment, using value chain analysis and hierarchical multilevel system approach. ; Peer Reviewed

Purpose: The purpose of this research is to develop a model that will explain the impact of government policies to the competitiveness of palm oil industry. The model involves two commodities in this industry, namely crude palm oil (CPO) and refined palm oil (RPO), each has different added value. Design/methodology/approach: The model built will define the behavior of government in controlling palm oil industry, and their interactions with macro-environment, in order to improve the competitiveness of the industry. Therefore the first step was to map the main activities in this industry using value chain analysis. After that a conceptual model was built, where the output of the model is competitiveness of the industry based on market share. The third step was model formulation. The model is then utilized to simulate the policy mix given by government in improving the competitiveness of Palm Oil Industry. Research limitations/implications: The model was developed using only some policies which give direct impact to the competitiveness of the industry. For macro environment input, only price is considered in this model. Practical implications: The model can simulate the output of the industry for various government policies mix given to the industry. Originality/value: This research develops a model that can represent the structure and relationship between industry, government and macro environment, using value chain analysis and hierarchical multilevel system approach.

Purpose: The purpose of this research is to develop a model that will explain the impact of government policies to the competitiveness of palm oil industry. The model involves two commodities in this industry, namely crude palm oil (CPO) and refined palm oil (RPO), each has different added value. Design/methodology/approach: The model built will define the behavior of government in controlling palm oil industry, and their interactions with macro-environment, in order to improve the competitiveness of the industry. Therefore the first step was to map the main activities in this industry using value chain analysis. After that a conceptual model was built, where the output of the model is competitiveness of the industry based on market share. The third step was model formulation. The model is then utilized to simulate the policy mix given by government in improving the competitiveness of Palm Oil Industry. Findings: The model can accommodate government's policy mix which is then optimized. The model has been built structurally based on hierarchical multi-level system approach, while in the process element, the subprocesses are built using VCA approach. The model can simulate industry performance, and show that such government policy mix can improve the competitiveness of Indonesian palm Oil Industry. Research limitations/implications: The model was developed using only some policies which give direct impact to the competitiveness of the industry. For macro environment input, only price is considered in this model. Practical implications: The model can simulate the output of the industry for various government policies mix given to the industry. The techno-economic aspect is also discussed. Originality/value: This research develops a model that can represent the structure and relationship between industry, government and macro environment, using value chain analysis and hierarchical multilevel system approach. ; Peer Reviewed