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Indonesia is a developing country with a low-level e-waste management system based on a limited number of informal initiatives. E-waste requires proper management procedures, which involve the design of a reverse logistics management network. Consumers play a critical role in such a network, because the network runs when they willingly participate as suppliers of waste. This paper applies the Theory of Planned Behavior framework and extends it using Reverse Logistics drivers, the Value Belief Norm Theory, and facility accessibility to explain consumer intention to participate in e-waste collection programs. A survey was conducted on smartphone users in Indonesia, with a total of 324 valid questionnaires. The results showed that government drivers, facility accessibility, and personal attitudes significantly influence consumer intentions. Environmental concern has a positive influence on consumer intentions through the variables of the Theory of Planned Behavior and perceived behavioral control through government drivers. This study shows the need for integration, because the variables reinforce each other. However, neither economic drivers nor subjective norms significantly influence consumer intentions. This finding distinguishes Indonesia from other countries, especially developed countries, in that e-waste collection programs have not become part of the culture in Indonesia. For this reason, Indonesia needs regulations, as the most influential variable, to regulate the implementation of such a program.

This paper discusses good criteria for a supply chain performance measurement model and their level of importance. The criteria were obtained from results of previous research findings and recommendations from several researchers. The criteria are divided into two categories, namely efficient and effective. To examine which criteria can be used to assess a supply chain performance measurement model, a survey was conducted by distributing questionnaires to supply chain actors from different industry fields (both manufacturing and services) in Indonesia using random sampling techniques. Data analysis using pairwise comparisons with an analytical Hierarchy Process model showed that efficient criteria were more important than effective criteria. Efficient criteria consisted of three sub-criteria: the amount of data is not too much and low cost and output is presented in a simple form. Effective criteria consisted of the criteria in the order of importance as follows: clarity, validity, comprehensiveness, responsiveness and dynamics. Further research is needed for developing a model that meets these criteria

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