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Purpose: This article harmonizes the causal diagram with the objective tree to evaluate service quality and to identify action strategies that improve the quality of service in the hotel industry. Design/methodology/approach: In stage I, we obtained the quality perception records of 127 historical costumers, and 384 questionnaires. Subsequently, a causal diagram was generated in stage II. And finally, the above-mentioned strategies were created. The Causal Diagram clarifies the relationship between customer complaints and company weaknesses. Findings: The goal tree makes it possible to categorize these strategies according to target levels. Research limitations/implications: Costumers' opinions could generate biases in their responses. Future studies must consider other methods, such as Fuzzy Logic to reduce this bias. Practical and social implications: This study approach can be replicated in other industrial sectors and is particularly useful for defining improvement plans related to service quality. Originality/value: The integration of these tools will allow managers to better understand the experiences reported by guests because it allows understanding of the behaviors between the variables that influence the quality of service and the variables under the tangible elements of the service. [ABSTRACT FROM AUTHOR]

This article presents a study that identifies the variables with greatest impact on the biogas and methane production over a process with thermal pretreatment, to accelerate anaerobic digestion process in sewage sludge in a water treatment plant, for a poultry processing factory, by using fuzzy logic. The designed fuzzy logic model includes 688 inference rules, with a correlation of 99.3% between prediction data against experimental data, for the biogas variable; and 97% for the methane variable. The predictions of the fuzzy logic model were analyzed with response surface models, and it is concluded that the temperature and operating time variables are mutually determining in the biogas and methane production. Likewise, this research provides a methodology for the design of an expert decision support system that allows to evaluate and optimize a mesophilic anaerobic digestion process through a previous thermal treatment in order to improve the yields of biogas and methane in the treatment of effluent sludge from agroindustry. These results propose to diffuse logic as a reliable tool to make comparisons, and predictions for operation variables management on the treatment of residual sludge with thermal pretreatment on anaerobic digestion. [ABSTRACT FROM AUTHOR]

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