PurposeThe aim of the present study is to overcome some of the limitations of the FMEA method by presenting a theoretical base for considering risk evaluation into its assessment methodology and proposing an approach for its implementation.Design/methodology/approachFuzzy AHP is used to calculate the weights of the likelihood of occurrence (O), severity (S) and difficulty of detection (D). Additionally, the prospect-theory-based TODIM method was integrated with fuzzy logic. Thus, fuzzy TODIM was employed to calculate the ranking of potential failure modes according to their risk priority numbers (RPNs). In order to verify the results of the study, in-depth interviews were conducted with the participation of industry experts.FindingsThe results are very much in line with prospect theory. Therefore, practitioners may apply the proposed method to FMEA. The most crucial failure mode for a firm's attention is furnace failure followed by generator failure, crane failure, tank failure, kettle failure, dryer failure and operator failure, respectively.Originality/valueThe originality of this paper consists in integrating prospect theory with the FMEA method in order to overcome the limitations naturally inherent in the calculation of the FMEA's RPNs.

PurposeThis study aims to propose an electronic waste collection and classification system to enhance social, environmental and economic sustainability by integrating data-driven technologies in emerging economies.Design/methodology/approachGM (1, 1) model under grey prediction is used in this study in order to estimate the trend of the amount of collected electronic waste in emerging economies.FindingsIt is revealed that the amount of collected electronic waste is increasing day by day, and within the framework of sustainability in the process of collecting and classification of electronic waste, digital technologies were found to be lacking. It has been determined that this deficiency, together with the increasing amount of electronic waste, has caused environmental, social and economic damage to emerging economies.Originality/valueThe main originality of this study is integrating electronic waste collection and classification processes with data-driven technologies and sustainability, which is a relatively new subject.

The growing need for solving the problem of food waste for tackling the survival of the planet and humankind is encouraging researchers to seek sustainable operations that alter the conventional methods that are currently in use in the food industry. Lean thinking has been used in this study to propose sustainable operations that incorporate social, economic, and environmental aspects and to handle the multidisciplinary and complex nature of reducing food waste. The value stream mapping methodology has been employed to explain food waste and generate drivers and to observe the end-to-end system flow. Since most of the waste is observed in upstream operations in emerging economies, one of the biggest meat-processing companies in Turkey is studied for illustrating the proposed methodology. As a result of the model, lean and sustainable food operations are suggested considering social, economic and environmental aspects.

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