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Perturbations have a negative influence on the operation of the business system, which may weaken business performance. However, in the field of the product–service system (PSS), perturbation is still a rarely discussed concept. Researchers and managers have a limited understanding of perturbations in the context of PSS. This hinders PSS designers and managers to prepare for mitigation due to a lack of knowledge and information. Thus, this paper aims to build a taxonomy of PSS perturbation through a systematic literature review. To achieve this target, the authors have reviewed 171 papers and found 18 effective papers. Twenty-five items are considered effective ones that are directly related to PSS perturbation. The result of the review shows that PSS perturbations could be classified into six categories, namely, behavioral, social, environmental, competence, resource, and organizational perturbations. The proposed terminology and taxonomy appear to be effective, which could enable researchers to understand the scope of PSS perturbations on a conceptual level. This finding is also expected to provide useful knowledge and information for researchers who are interested in vulnerability analysis and the robust design of PSS.

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The high demand of meat causes the seller mix the fresh and not-fresh meat. Electronic nose was used to detect the quality of the meat quickly and accurately. This research is proposed to test and analyze the sensitivity of MOS sensor in the electronic nose and simulate it using Matlab to identify meat classification using neural network. Test parameters based on Indonesian National Standard (SNI 3932-2008) requirement on the quality of carcass and meat. In this simulation, the number of neurons in the hidden layer was varied to find the most accurate identification. The sensitivity analysis of the MOS sensor was conducted by testing the meat sample aroma, calculate the sensitivity, identify the formation of input, hidden layer, outputs, and simulate the result of the varied formation. Then, found the number of the most optimal neurons. The result of the data training will be applied to the real instrument.

SARS-CoV-2 has become a global pandemic, causing many disruptions in multiple sectors. The World Health Organization has urged the public to wear face masks as part of the countermeasure. As the demand for face masks increased, research on the environmental sustainability of face masks production started to emerge. However, the scope of the prior studies is limited to environmental impacts during the manufacturing process. Broadening the research scope is critical to acquire a comprehensive environmental impact analysis. Therefore, this study investigates the life cycle impact assessment of disposable face mask production, from raw material extraction to the point of sale, by adopting the life cycle assessment method. Disposable face masks are assessed for a single person, over one functional unit (FU) of 30 12-h days. The ReCiPe approach was used with a Hierarchist perspective. The results reveal that disposable face mask manufacture contributes significantly to enormous environmental impact categories. As a solution, this study proposes a reconfiguration of the manufacturing process, by altering the design and material proportion of the earloop to minimise the environmental impact. The investigation indicates that the proposed design might decrease the global warming contribution, from 1.82593 kg CO2 eq. to 1.69948 kg CO2 eq.

Lean supply chain management (LSCM) is a research theme that is currently developing. This research objective is to offer LSCM frameworks of the palm oil industry in Indonesia. LSCM frameworks from Jasti and Kodali [6] were adopted, where seven of the eight pillars were chosen because they were in accordance with the palm oil industry. The seven pillars are including information technology management, supplier management, elimination of waste, customer relationship management, logistics management, top management commitment, continuous improvement. The simple additive weighting method (SAW) is used to measure and rank 39 LSCM frameworks subelements that are breakdown from 7 selected pillars. Three of the most important subelement is the long-term supplier partnership, seven waste throughout the supply chain, and value stream mapping.

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