Informatica

Due to the increasing importance of evaluating the quality of health care services using the patient-centred approach, this study aimed to propose a novel framework by combining the SERVQUAL model and multi-attribute decision-making (MADM) methods using interval-valued triangular fuzzy numbers (IVTFN). In this study, after an initial overview of related work and expert opinions, a list of the most important dimensions and indicators for measuring the quality of health care services was extracted and localized. Then, to determine the importance of each of the identified factors, one of MADM’s acceptable methods called step-wise weight assessment ratio analysis (SWARA) was used. Then, in order to use the developed framework for comparing different health centres and ranking them, after collecting evaluation data in the form of linguistic variables, another practical method in the field of MADM has been used, namely, Additive Ratio Assessment (ARAS) method. The dimensions and sub-dimensions identified are, on the one hand, appropriate to the conditions of the case study and, on the other hand, the findings from the implementation show that among the dimensions of health service quality, responsiveness and then reliability has the highest rank in this case. Also, the use of IVTFN, on the one hand, eliminates the problems related to the use of Likert scale in other quality assessment methods and, on the other hand, reduces the possibility of facing imperfect knowledge of data which is a common problem in the field of qualitative evaluations. Utilizing the results of this study can significantly help decision makers in their choice of strategies to improve service quality. Furthermore, improving the quality of services can play an important role in promoting the competitiveness and performance of health care providers by increasing patient satisfaction with the services received. Also, as a side effect, the developed framework can be used to compare the performance of different hospitals and health centres, as well as their ranking.

Policy-makers are often hesitant to invest in unproven solutions because of a lack of the decision-making framework for managing innovations as a portfolio of investments that balances risk and return, especially in the field of developing new technologies. This study provides a new portfolio matrix for decision making of policy-makers to identify IoT applications in the agriculture sector for future investment based on two dimensions of sustainable development as a return and IoT challenge as a risk using a novel MADM approach. To this end, the identified applications of IoT in the agriculture sector fall into eight areas using the meta-synthesis method. The authors extracted a set of criteria from the literature. Later, the fuzzy Delphi method helped finalise it. The authors extended the SWARA method with interval-valued triangular fuzzy numbers (IVTFN SWARA) and used it to the weighting of the characteristics. Then, the alternatives were rated using the Additive Ratio Assessment (ARAS) method based on interval-valued triangular fuzzy numbers (IVTFN ARAS). Finally, decision-makers evaluated the results of ratings based on two dimensions of sustainability and IoT challenge by developing a framework for decision-making. Results of this paper show that policy-makers can manage IOT innovations in a disciplined way that balances risk and return by a portfolio approach, simultaneously the proposed framework can be used to determine and prioritise the areas of IoT application in the agriculture sector.