Effective waste management in service industry: Fuzzy-based modelling approach for strategic decision-making

Abstract

Hospitals need to identify issues of greater importance on waste management because the implementation of many different strategies may lead to an unconscious increase in costs. Accordingly, the purpose of this study is to define the most effective waste management strategies in the service industry. For this purpose, a novel fuzzy decision-making model is proposed that has two different stages. In this context, six JCI-based indicators are weighted by using sine trigonometric fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) methodology. Additionally, a comparative evaluation has also been conducted with sine trigonometric fuzzy Criteria Importance Through Intercriteria Correlation (CRITIC) technique to check the reliability of the findings. On the other hand, five different strategy alternatives are selected by considering the principles of the integrated waste management hierarchy approach. These items are evaluated by considering sine trigonometric fuzzy Technique for Order Preference by Similarity (TOPSIS). On the other side, these factors are also ranked with the help of sine trigonometric fuzzy Additive Ratio Assessment (ARAS) to test the consistency of the results. The main contribution is that prior strategies can be presented to the hospitals to have appropriate waste management process by defining the most important factors. Criteria weighting and alternative ranking results are the same in all combinations. Therefore, it is seen that the proposed model creates coherent and consistent results. It is defined that efficient storage of waste is the key issue to have effective waste management process. Moreover, ‘reduce’ is found as the most critical stage of this process.

Introduction

Effective waste management is of great importance, especially for hospitals. Very high amounts of medical waste occur in hospitals (Baralla et al., 2023). Failure to properly dispose of these wastes may increase the risk of infection (Kurniawan et al., 2023). This situation threatens the health of both staff and patients. For waste management to be carried out effectively in hospitals, it is necessary to implement the right strategies (Fang et al., 2023). There are many different factors that affect the performance of this process. On the other hand, hospitals also have a budget constraint (Waqas et al., 2023). In other words, the implementation of many different strategies to increase the efficiency of waste management processes may lead to an unconscious increase in costs. Therefore, such an application is not very sustainable, as it will put hospitals in financial difficulties. Thus, hospitals need to identify issues of greater importance on waste management. In this way, they will be able to implement higher priority strategies, which will enable hospitals to implement effective waste management practices efficiently. In summary, there is a strong need for a new study to find the most essential items that have an important impact on effective waste management for the hospitals.

In this study, it is aimed to find the most effective waste management strategies in the service industry. Hence, the research question of this study is which factors play more critical role to overcome waste management process more effectively. For this purpose, six JCI-based indicators are defined for the hospitals. These factors are weighted by using ST-FDEMATEL methodology. Additionally, a comparative evaluation has also been conducted with ST-FCRITIC technique to check the reliability of the findings. Secondly, five different strategy alternatives are selected by considering the principles of the integrated waste management hierarchy approach. These items are evaluated by considering ST-FTOPSIS. On the other side, these factors are also ranked with the help of ST-FARAS to test the consistency of the results. The main motivation to make this study is that existing decision-making models in the literature are criticized because of some reasons. The main reason behind this situation is the uncertainty problem in the analysis process. Due to this condition, it is understood that there is a strong need for a novel decision-making model that can handle this problem more effective. Within this framework, in this study, a new decision-making methodology is proposed by integrating sine trigonometric fuzzy sets with four different multi-criteria decision-making techniques.

The main contributions of this study are indicated below.

1. The most critical strategies can be presented to the companies while defining the most important factors. Hospitals should take actions to increase the effectiveness of waste management by considering budget deficit (Sharma et al., 2023). In other words, making improvements related to the determinants of effective waste management can increase the costs at the same time. Because of this issue, making lots of improvements leads to high amount of costs for the hospitals. In this framework, there is a need to define the most crucial factors of this process (Bao and Lu, 2023). With the help of this issue, prior strategies can be presented to the hospitals to have appropriate waste management process.

2. Another important novelty is that integrated waste management hierarchy approach is considered to define the alternatives in the proposed model. This approach identifies the different stages of waste management (Bilgili and Çetinkaya, 2023). In this way, it is aimed that this process can be managed in the most effective way (Berenjkar et al., 2021). The integrated waste management hierarchy contributes significantly to minimizing the dependence of waste on resources. This allows businesses to save costs. This also helps to increase energy production from waste (Turkyilmaz et al., 2019). On the other hand, this approach enables more efficient use of natural resources.

3. Determining the criteria list in accordance with JCI standards is another issue that increases the quality of the study. JCI is an organization that evaluates the quality standards of healthcare providers (Van Wilder et al., 2021). JCI is based on quality standards aimed at improving patient safety. These criteria allow healthcare organizations to follow international best practices (Hammad et al., 2022). On the other hand, it encourages the continuous quality improvement efforts of health institutions. Compliance with these criteria both increases the safety of patients and helps to increase the quality of health services (Eskin Bacaksiz et al., 2020).

4. Using sine trigonometric structure provides many critical advantages. With the help of this structure, periodicity can be taken into consideration. Additionally, this structure is symmetrical regarding the origin (Riaz et al., 2022). Owing to these issues, better results can be reached with trigonometric operators. Another critical benefit of sine trigonometric structure is that defuzzification processes can be implemented more appropriately (Garg, 2021). Making evaluation regarding effective waste management is a very complex issue so that the analysis should not be done with the linear structure. In summary, sine trigonometric structure can minimize the uncertainties in this process. Thus, more appropriate solutions can be provided for this complex problem (Riaz et al., 2022).

Previous similar studies are analysed in the next section. The methods used in the proposed model are explained in the following part. The results are shared in the fourth part. The findings are discussed in the fifth part. The conclusions are given finally.

Important related previous research

For the waste management process to be successful, efficient storage of waste is an important issue. The storage of waste is the preliminary stage for the disposal, reuse or conversion of waste into energy without harming the environment and people (Gull et al., 2023). Therefore, the waste storage process is very important for the waste management process. Pradenas et al. (2020) pointed out a study on optimizing waste storage areas in health centres. They stated that the most important issue affecting the waste management process in terms of health centres is the packaging of waste. It is also emphasized that the storage of waste is also very important for this process. On the other hand, Bamakan et al. (2022) examined the blockchain-based hospital waste management system. Emphasizing the importance of waste separation, packaging and collection of waste, disposal and transportation of waste, the article also mentions the importance of storing waste. Motlatla and Maluleke (2021) conducted a study on waste management and risk assessment in a tertiary hospital in South Africa. This quantitative and cross-sectional study tried to measure the knowledge levels of physicians, nurses, pharmacists and laboratory technicians about waste management. Accordingly, it is identified that attention should be mainly given to the storage of waste to carry out the waste management process effectively in hospitals.

The process of separating waste is also very important for the efficiency of waste management. The process of separating the wastes refers to the classification of the resulting wastes according to their types (Hashemi-Amiri et al., 2023). In this context, the main purpose is to provide maximum benefit from the waste management process by separating the wastes according to their types, harmfulness and recycling status. Additionally, the waste management system had difficulties in this regard. According to Golbaz et al. (2019), they conducted a study to predict solid waste generation in hospitals using artificial intelligence and multiple linear regression. In the study, the hospital’s service, number of active and full beds, number of staff and inpatients, ownership type of the hospital and year of operation are defined as model inputs. It is established that the machine learning method is successful in estimating the amount of waste production, and it is defined that waste separation is important in terms of the waste management process. Osman et al. (2023) carried out a study to determine the amount of waste and evaluate general waste management models in a hospital in Uganda. The importance of waste separation was underlined in the study, which stated that waste mixing is one of the most important problems in hospitals.

Another important factor affecting the success of the waste management process is the competence of the personnel. Personnel who have received the necessary training will contribute to the process from collection of wastes to separation, storage and reuse (Tushar et al., 2023). Therefore, the contribution of trained personnel to this process is undeniably important. Cervantes et al. (2021) carried out a study to evaluate waste management systems in terms of governance. They planned to cover 66 municipalities in Mexico and 13 basic indicators were found to affect the process. Accordingly, one of the issues affecting the waste management process is the development of employees. Wu et al. (2020) actualized a study to promote the effective management of construction waste to promote sustainable development. In this study, successful practices in waste management were determined based on content analysis and focus group meetings in Hong Kong. Accordingly, employees and their qualifications are important for the waste management process. Adu-Gyamfi et al. (2023) made a study in Ghana to reduce the challenges of waste management. A structural equation model was used in this article, which reached 401 employees through a questionnaire. According to the results of the study, it is clearly understood that personnel have a direct impact on the waste management process.

Legal regulations and government incentives are very important in terms of participation in the waste management process. It is possible to ensure the success of the waste management process with the incentive or regulation policies to be carried out by the state (Bui et al., 2023). Therefore, necessary legal arrangements should be made in the decisions. In this way, since the number of people and businesses involved in the waste management process will increase, it will be easier to reach the target (Ranjbari et al., 2023). Shittu (2021) realized a study covering the waste management process of electrical and electronic equipment. It is stated that there are many factors affecting the waste management process, and these factors should be considered if this process is to be successful. Accordingly, it is definite that China, India and Latin American countries, regarding electronic products, have expanded their waste management legislation. Nukusheva et al. (2023) investigated regulatory practices to make waste management effective in Kazakhstan by comparing them with those in the European Union. Mentioning many factors for the success of the waste management process in their study, the authors stated that Kazakhstan has a significant lack of implementation of legal instruments. Kurniawan et al. (2022) carried out a study examining the transformation of solid waste management in China. Through digitalization, the waste industry also mentions the fulfilment of legal obligations so that the waste management process can be successful.

Occupational health and safety actions have a high impact on the success of the waste management process. These actions aim to protect both the employees and the institution from possible negative situations (Sundar et al., 2023). Therefore, occupational health and safety practices are necessary for the success of waste management. do Nascimento Beckert and Barros (2022) conducted a study examining the relationship between waste management and occupational health and safety practices during the COVID-19 pandemic period in Sao Paulo, Brazil. It has been emphasized that occupational health and safety practices, which are among the sustainable development goals, are also important in terms of the waste management process. Moloudi et al. (2022) concluded that occupational health and safety practices have a great importance. Apart from these, another issue affecting the waste management process is the creation of a complete list of waste used in the business. This is important for the planning phase of waste management. Accordingly, the creation of a list of wastes in the enterprise is important in terms of both effective execution and control of the process. Shareefdeen and Elkamel (2022) realized a compilation study on the management of hazardous waste. They focused on the examples of bad practices and related financial losses, and it is emphasized that the creation of a waste list is important for the process.

Apart from all these, the waste management hierarchy should also be taken into consideration for the success of the waste management process. The waste management hierarchy is an approach that aims to evaluate all waste management steps as a whole and ensure sustainability in both environmental and economic terms. The waste management hierarchy encompasses the reduction, reuse, conversion, energy and elimination of waste. Claassens et al. (2022) aimed to identify waste management measures, and they highlighted the significance of waste management hierarchy. Olatayo et al. (2022) examined plastic waste policies and determined that the waste management hierarchy should be taken into consideration to achieve the objectives.

Multi-criteria decision-making techniques were also taken into consideration in some studies for the subject of effective waste management. Demircan and Yetilmezsoy (2023), Musarat et al. (2022) and Raj and Samuel (2023) considered analytic hierarchy process (AHP) methodology regarding the implementation of sustainable waste management strategies for different industries, such as construction and healthcare. Similarly, Seikh and Mandal (2023) and Koska and Erdem (2023) used SWARA approach for the same purpose. In these studies, the weights of the significant criteria can be calculated. However, the main drawback of this study is that causal directions among these items cannot be considered. On the other side, Wang et al. (2023), Yadav et al. (2023) and Bin et al. (2022) created decision-making models with the help of DEMATEL methodology. Owing to this approach, they had an opportunity to identify the causal directions between these factors. In addition to these studies, Akram et al. (2023), Menekşe and Akdağ (2023) and Ali (2022) used fuzzy CRITIC approach so that criteria weights can be computed while considering the correlations among the indicators.

The main conclusions reached as a result of the literature review are given below:

1. The success of the waste management process is important for both the environment and human health.

2. Waste management in hospitals has become even more popular with the pandemic and technological developments.

3. In this context, it can be said that the issues affecting the waste management process are effective storage, separation of wastes, employing qualified personnel, legal regulations, occupational health and safety practices and the creation of a waste list.

4. However, hospitals and other buildings cannot respond to all of these criteria at the same time to improve the waste management process mainly because of budget constraints.

5. Therefore, the comparative significance of these factors should be computed so that the prior ones can be understood.

6. However, in previous studies, limited scholars have focused on this situation. Due to this issue, it is understood that a new study applying this subject is quite necessary.

By considering these conditions, in this study, a new analysis is conducted to identify the most significant determinants that affect efficiency of the waste management process in hospitals.

Methodology

In this study, an original decision-making model is generated by integrating different techniques (DEMATEL, CRITIC, TOPSIS and ARAS) with Sine trigonometric Pythagorean fuzzy sets (STPYFs). This section consists of the details of these approaches.

STPYFs

Sine trigonometric aggregation operators are considered with Pythagorean Fuzzy sets $(p=({\mu }_p,v_p))$ in this manuscript (Riaz et al., 2022). STPYFs are mainly described in Equation (1) (Ashraf et al., 2021).

$$\sin \tilde{p}=\left(\sin \left(\frac{\pi }{2}{\mu }_p\right),\sqrt{1-{\sin }^2\left(\frac{\pi }{2}\sqrt{1-v_p^2}\right)}\right)$$ (1)

When $\sin p_1$ and $\sin p_2$ are two different STPYFs, the operations are demonstrated in Equations (2)–(9) (Garg, 2021).

$$\begin{array}{l}\sin p_1\oplus \sin p_2\\ =\left(\begin{array}{l}\sqrt{1-\left(1-{\sin }^2\left(\frac{\pi }{2}{\mu }_1\right)\right)\left(1-{\sin }^2\left(\frac{\pi }{2}{\mu }_2\right)\right)},\\ \sqrt{1-{\sin }^2\left(\frac{\pi }{2}\sqrt{1-v_1^2}\right)}\sqrt{1-{\sin }^2\left(\frac{\pi }{2}\sqrt{1-v_2^2}\right)}\end{array}\right)\end{array}$$ (2)

$$\sin p_1\otimes \sin p_2=\left(\begin{array}{l}\sin \left(\frac{\pi }{2}{\mu }_1\right)\sin \left(\frac{\pi }{2}{\mu }_2\right),\\ \sqrt{\begin{array}{l}1-\left({\sin }^2\left(\frac{\pi }{2}\sqrt{1-v_1^2}\right)\right)\\ \left({\sin }^2\left(\frac{\pi }{2}\sqrt{1-v_2^2}\right)\right)\end{array}}\end{array}\right)$$ (3)

$$\lambda \sin p_1=\left(\begin{array}{l}\sqrt{1-{\left(1-{\sin }^2\left(\frac{\pi }{2}{\mu }_1\right)\right)}^{\lambda }},\\ {\left(\sqrt{1-{\sin }^2\left(\frac{\pi }{2}\sqrt{1-v_1^2}\right)}\right)}^{\lambda }\end{array}\right)$$ (4)

$${\left(\sin p_1\right)}^{\lambda }=\left(\begin{array}{l}{\left(\sin \left(\frac{\pi }{2}{\mu }_1\right)\right)}^{\lambda },\\ \sqrt{1-{\left({\sin }^2\left(\frac{\pi }{2}\sqrt{1-v_1^2}\right)\right)}^{\lambda }}\end{array}\right)$$ (5)

$$\begin{array}{l}S\left(\sin p\right)={\sin }^2\left(\frac{\pi }{2}{\mu }_p\right)-\\ {\left(\sqrt{1-{\sin }^2\left(\frac{\pi }{2}\sqrt{1-v_p^2}\right)}\right)}^2\end{array}$$ (6)

$$\begin{array}{l}D\left(\sin p_1,\sin p_2\right)=1-\frac{1}{n}{\displaystyle \sum }_{i=1}^n\sin \\ \left(\frac{\pi }{2}-\frac{\pi }{6}\left(\left|{\mu }_1^2-{\mu }_2^2\right|+\left|v_1^2-v_2^2\right|+\left|d_1^2-d_2^2\right|\right)\right)\end{array}$$ (7)

$$d=\sqrt{1-{\mu }^2-v^2}$$ (8)

$$\mathrm{STPFWA}=\left(\begin{array}{l}\sqrt{1-{\displaystyle \prod }_{i=1}^n{\left(1-{\sin }^2\left(\frac{\pi }{2}{\mu }_i\right)\right)}^{w_i}},\\ {\displaystyle \prod }_{i=1}^n{\left(\sqrt{1-{\sin }^2\left(\frac{\pi }{2}\sqrt{1-v_i^2}\right)}\right)}^{w_i}\end{array}\right)$$ (9)

The extension of DEMATEL

DEMATEL method is a multi-criteria decision-making technique that considers causality between criteria in determining the degree of importance of the criteria (Bhuiyan et al., 2022). This method is based on pairwise comparisons of criteria (Sun et al., 2022). Firstly expert opinions are obtained and converted into STPYFs using the values in Table 1.

Table 1.

Scales.

Linguistic term	Abb	Score	PFNs		STPYFs
			m	v	m	v
Very low	VL	1	0.15	0.85	0.2334	0.5136
Low	L	2	0.25	0.75	0.3827	0.3716
Moderately low	ML	3	0.35	0.65	0.5225	0.2651
Medium	M	4	0.5	0.45	0.7071	0.1187
Moderately high	MH	5	0.65	0.35	0.8526	0.0702
High	H	6	0.75	0.25	0.9239	0.0353
Very high	VH	7	0.85	0.15	0.9724	0.0126

In Table 1, by making necessary calculations stated in Equation (1) for PFNs, STPFYs are computed. By taking the average of the expert opinions, the fuzzy decision matrix (A) is formed as in Equation (10).

$$A=\left[\begin{array}{ccc}(0.0)& \cdots & \left(\sin \left(\frac{\pi }{2}{\mu }_{1n}\right),\sqrt{1-{\sin }^2\left(\frac{\pi }{2}\sqrt{1-v_{1n}^2}\right)}\right)\\ ⋮& \ddots & ⋮\\ \left(\sin \left(\frac{\pi }{2}{\mu }_{1n}\right),\sqrt{1-{\sin }^2\left(\frac{\pi }{2}\sqrt{1-v_{1n}^2}\right)}\right)& \cdots & \left(0.0\right)\end{array}\right]$$ (10)

Equation (6) is used to compute defuzzified values. Then, with the help of Equations (11) and (12), a normalized direct-relation matrix (X) is created.

$$X=s.A$$ (11)

$$s=\min \left(\frac{1}{{{\displaystyle \sum }}_{i=1}^n{a}_{ij}},\frac{1}{{{\displaystyle \sum }}_{j=1}^n{a}_{ij}}\right)$$ (12)

Total relation matrix is constructed by Equation (13).

$$T=X*{\left(I-X\right)}^{-1}$$ (13)

In the next step, the row (R) and column (D) sums of this matrix are obtained with Equations (14) and (15).

$$R_j={\displaystyle \sum }_{i=1}^n{t}_{ij}$$ (14)

$$D_i={\displaystyle \sum }_{j=1}^n{t}_{ij}$$ (15)

Using row and column totals, weights (w) are calculated using Equation (16).

$$w_i=\frac{\sqrt{{\left(C_i+D_i\right)}^2+{\left(C_i-D_i\right)}^2}}{{{\displaystyle \sum }}_{i=1}^n\sqrt{{\left(C_i+D_i\right)}^2+{\left(C_i-D_i\right)}^2}}$$ (16)

The extension of CRITIC

The CRITIC method is one of the criteria weighting methods. Using the ‘alternative x criteria’ matrix, it considers the relationship between the criteria and the standard deviations of the criteria (Mishra et al., 2022). The questions are prepared for these selected criteria. After that, expert team answer these questions. Then, these expert evaluations are converted into fuzzy sets with the values in Table 1. Next, Equation (17) is used to calculate the average values (Peng et al., 2020).

$$Z=\left[\begin{array}{ccc}\left(\sin \left(\frac{\pi }{2}{\mu }_{11}\right),\sqrt{1-{\sin }^2\left(\frac{\pi }{2}\sqrt{1-v_{11}^2}\right)}\right)& \cdots & \left(\sin \left(\frac{\pi }{2}{\mu }_{1n}\right),\sqrt{1-{\sin }^2\left(\frac{\pi }{2}\sqrt{1-v_{1n}^2}\right)}\right)\\ ⋮& \ddots & ⋮\\ \left(\sin \left(\frac{\pi }{2}{\mu }_{m1}\right),\sqrt{1-{\sin }^2\left(\frac{\pi }{2}\sqrt{1-v_{m1}^2}\right)}\right)& \cdots & \left(\sin \left(\frac{\pi }{2}{\mu }_{mn}\right),\sqrt{1-{\sin }^2\left(\frac{\pi }{2}\sqrt{1-v_{mn}^2}\right)}\right)\end{array}\right]$$ (17)

The values are defuzzified by Equation (18).

$$B=\begin{array}{c}\begin{array}{ccc}C1& \dots & Cn\end{array}\\ \begin{array}{cc}\begin{array}{c}A1\\ ⋮\\ Am\end{array}& \left[\begin{array}{ccc}{b}_{11}& \cdots & b_{1n}\\ ⋮& \ddots & ⋮\\ b_{m1}& \cdots & b_{mn}\end{array}\right]\end{array}\end{array}$$ (18)

The inter-criteria correlation matrix (ρ) is calculated by Equation (19).

$$\begin{array}{l}{\tilde{\rho }}_{jk}={\displaystyle \sum }_{i=1}^m\left({\tilde{b}}_{ij}-{\tilde{\overline{b}}}_j\right)\left({\tilde{b}}_{ik}-{\tilde{\overline{b}}}_k\right)/\\ \sqrt{{\displaystyle \sum }_{i=1}^m{\left({\tilde{b}}_{ij}-{\tilde{\overline{b}}}_j\right)}^2{\displaystyle \sum }_{i=1}^m{\left({\tilde{b}}_{ik}-{\tilde{\overline{b}}}_k\right)}^2}\end{array}$$ (19)

Equation (20) calculates the standard deviation (σ) of each criterion.

$${\tilde{\sigma }}_j=\sqrt{\frac{1}{n-1}{\displaystyle \sum }_{j=1}^n{\left({\tilde{b}}_{ij}-{\tilde{\overline{b}}}_j\right)}^2}i=1,2,\dots ,m$$ (20)

C index values are calculated with the help of Equation (21).

$${\tilde{C}}_j={\tilde{\sigma }}_j{\displaystyle \sum }_{k=1}^n(1-{\tilde{\rho }}_{jk})j=1,2,\dots ,n$$ (21)

The weights can be calculated by Equation (22).

$${\tilde{w}}_j=\frac{{\tilde{C}}_j}{{{\displaystyle \sum }}_{j=1}^n{\tilde{C}}_j}$$ (22)

The extension of TOPSIS

TOPSIS method is one of the methods used in ranking the alternatives (Erdebilli et al., 2023). In this process, ideal negative and positive values are calculated. After that, ranking of the alternatives is computed by considering the distance of each alternative from the optimal values (Silahtaroğlu et al., 2021). The average matrix calculated previously with the help of Equation (4) is multiplied by the weights and the weighted decision matrix is obtained. After that, ideal negative and ideal positive values are determined according to the score value calculated by Equation (6). The details are denoted in Equations (23) and (24).

$$V^{-}=\left\{v_i|\min \left(S\left(z_i\right)\right)\right\}$$ (23)

$$V^{+}=\left\{v_i|\max \left(S\left(z_i\right)\right)\right\}$$ (24)

Next, the distances to the alternative positive and negative values (S⁻ and S*) are calculated. Ranking score (C) is calculated with the help of Equation (25).

$$C=\frac{S^{-}}{S^{-}+S^{*}}$$ (25)

The extension of ARAS

The ARAS method is also a method of ranking different alternatives (Heidary Dahooie et al., 2022). Instead of distance, the ratio of each alternative is taken on the basis of criteria, and then the optimal summing ratio of the sum is calculated (Karagöz et al., 2021). Alternatives are ranked based on these total ratios. Optimal values are calculated using Equation (26) from expert opinions converted into fuzzy numbers.

$$\mathrm{optimal}=\left\{p_i|\max \left(S\left(z_i\right)\right)\right\}$$ (26)

Then, the optimal values are multiplied by the weights to obtain the weighted decision matrix (F). The values are defuzzified in the following process. Then the sum (S_j) of each alternative is calculated by Equation (27).

$$S_j={\displaystyle \sum }{k}_j$$ (27)

In the final step, the Q values are calculated by dividing the total values by the optimal sum as in Equation (28). The larger Q value is considered the most optimal value.

$$Q_i=\frac{S_i}{S_0}$$ (28)

Analysis results

The results of the evaluations are presented in the following subsections.

The definition of the problem

Waste management in enterprises means the effective disposal of waste arising from the production processes of an enterprise. This includes processes such as waste reduction, recycling and disposal. Waste management is an important factor for reducing environmental pollution and protecting natural resources. The right waste management strategies reduce the amount of waste of enterprises. In this way, businesses can achieve significant cost savings by reusing some materials. Moreover, thanks to a good waste management policy; it is understood that the enterprise is sensitive to the environment. This contributes to a significant increase in the reputation of the business. With the help of these issues, waste management process can be implemented effectively. This situation plays a critical role especially for the hospitals. To achieve this objective, it is necessary to implement the right strategies. Various indicators can have an influence on the performance of this process (Ismaeel and Kassim, 2023). Nevertheless, it is not possible for the hospitals to make improvements for all indicators due to the budget constraints. Therefore, hospitals need to identify issues of greater importance on waste management. In this way, they will be able to implement higher priority strategies, which will enable hospitals to implement effective waste management practices efficiently (Ghozatfar et al., 2023). Accordingly, this study aims to identify the most effective waste management strategies in the service industry. In this context, six JCI-based indicators are determined for the hospitals by using ST-FDEMATEL. In addition, a comparative evaluation has also been made with ST-FCRITIC to check the reliability of the findings. On the other side, five different strategy alternatives are selected by considering the principles of the integrated waste management hierarchy approach. These alternatives are ranked with the help of ST-FTOPSIS. Moreover, ST-FARAS is also taken into consideration for alternative ranking with the aim testing the consistency of the proposed model.

Identification of criteria and alternatives

The criteria that affect the performance of effective waste management in hospitals are defined based on JCI approach (Eskin Bacaksiz et al., 2020). JCI is an organization that evaluates the quality standards of healthcare providers worldwide (Van Wilder et al., 2021). The main purpose here is to increase the quality of health services. The quality of healthcare services provided by hospitals is a broad concept that includes a number of important criteria. Quality healthcare includes many factors such as patient safety, effectiveness, patient satisfaction and accessibility. Thus, it is possible to increase patient safety (Hammad et al., 2022). In this study, among the JCI criteria, those related to effective waste management were determined. As a result, six different indicators were determined. Details of these factors are shown in Table 2.

Table 2.

Selected JCI-based criteria.

JCI-based Criteria	Literature
Creation of the waste list (CWTL)	Cai et al. (2023)
Efficient storage of waste (FSGW)	Wu et al. (2020)
Increasing the competence of the staff (NMPS)	Ilyassova et al. (2021)
Separation of waste (SPOW)	Moloudi et al. (2022)
Ensuring occupational health and safety (OHST)	Bamakan et al. (2022)
Adequacy of legal regulations (DQGG)	Osman et al. (2023)

Separation of waste plays an important role for effective waste management. In this way, it may be possible to collect and recover materials with recycling potential. Efficient storage of waste is also very important in this process. Waste can cause significant damage to the environment due to improperly implemented storage methods. Increasing the competence of the personnel is necessary for effective waste management. This situation creates awareness and awareness about the correct management of waste. Another factor necessary for the effectiveness of waste management is the correct separation of waste. In this way, it can be easier to identify materials that can be recycled. On the other hand, ensuring occupational health and safety has a very important role in this process. Occupational health and safety measures enable these risks to be determined and managed correctly. Moreover, legal regulations must be sufficient in this process. Legal compliance is a factor that protects the reputation of organizations. On the other hand, the list of alternatives in this study was determined as five different parameters of the integrated waste management strategy technique. These issues are described in Table 3.

Table 3.

Integrated waste management hierarchy-based criteria.

Alternatives	Literature
Reduce	Pradenas et al. (2020)
Reuse	Adu-Gyamfi et al. (2023)
Recycling	Nukusheva et al. (2023)
Energy recovery	Shareefdeen and Elkamel (2022)
Landfill	Claassens et al. (2022)

Integrated waste management hierarchy is a process developed to make waste management more effective. It refers to a sequential approach that is recommended to be applied to increase the waste management performance of enterprises (Bilgili and Çetinkaya, 2023). In this context, five different stages are determined in the waste management process (Berenjkar et al., 2021). Reduction means minimizing waste generation. Reuse refers to the reintroduction of these wastes into the production process for a different purpose. Energy recovery involves the conversion of waste into energy. Landfill indicates that the waste is removed in an appropriate manner (Turkyilmaz et al., 2019).

Weighting the criteria with ST-FDEMATEL

Firstly, the evaluations of three different experts are considered. These people answer the questions related to the criteria by using the scales in Table 1. These evaluations are denoted in Appendix Table A1. Expert opinions are converted into fuzzy numbers and averaged. The normalized direct-relation matrix obtained by using Equation (11) is given in Appendix Table A2. Then, the total relationship matrix is obtained by Equation (12) (Appendix Table A3). Weights are obtained with Equations (13)–(15) and the results are given in Table 4.

Table 4.

Weights.

Criteria	D	R	R+D	R−D	Weights
CWTL	0.0744	0.6625	0.7369	0.5881	0.1313
FSGW	1.2989	0.1243	1.4233	−1.1746	0.2570
NMPS	0.0020	0.7382	0.7402	0.7363	0.1454
SPOW	1.1421	0.1524	1.2945	−0.9898	0.2270
OHST	0.1671	0.6322	0.7994	0.4651	0.1288
DQGG	0.1618	0.5366	0.6984	0.3748	0.1104

It is defined that efficient storage of waste is the key issue because of the highest weight (0.2570). Separation of waste is defined as the second most critical issue with the weight of (0.2270). Efficient storage of waste plays an important role for effective waste management. The uncontrolled execution of this work causes significant environmental pollution. As can be understood from this, the efficient storage of waste helps to conserve natural resources. On the other hand, thanks to the regular storage of waste; it is more possible to dispose of these wastes correctly. Separation of waste is also of critical importance for effective waste management. In this way, it will be easier to identify the materials to be recycled. This condition also significantly helps to increase energy efficiency.

Making comparative evaluation with ST-FCRITIC

A different evaluation has also been carried out by ST-FCRITIC approach. The comparative evaluation results are indicated in Figure 1.

Figure 1.

Comparative weighting results of criteria.

Figure 1 demonstrates that the weighting results of both ST-FDEMATEL and ST-FCRITIC are the same. This situation gives information about the coherency of the proposed model.

Ranking the alternatives with ST-FTOPSIS

Expert opinions are also provided for the alternatives. Appendix Table A4 gives information about these evaluations. These expert opinions are converted into fuzzy numbers by the scales in Table 1 and averaged with Equation (8). Then, by using DEMATEL weights, the weighted decision matrix is obtained by Equation (3) as in Appendix Table A5. Equations (21) and (22) calculate ideal positive and negative values over the weighted decision matrix. These values are indicated in Appendix Table A6. S* and S⁻ values are computed with Equation (6). By using them, C values are calculated by considering Equation (23). The ranking results of the alternatives are demonstrated in Table 5.

Table 5.

Ranking results of alternatives.

Alternatives	C values	Ranking results
Reduce	0.9995	1
Reuse	0.5902	3
Recycling	0.9521	2
Energy recovery	0.3199	4
Landfill	0.0425	5

Table 5 states that ‘reduce’ is the most significant stage of effective waste management. Recycling is another important alternative in this context. Therefore, necessary strategies should be developed to reduce the waste of the hospitals. Hospitals can implement a variety of strategies to reduce waste generation. In this context, less material consumption is required. To achieve this aim, effective stock control should be done in hospitals. In addition, hospitals should prefer products that are suitable for recycling. In this way, it is possible to reduce waste by reusing products.

Making a comparative ranking analysis with ST-FARAS

These alternatives are also ranked by using ST-FARAS. In this framework, both the weights of ST-FDEMATEL and ST-FCRITIC are taken into consideration. The comparative ranking results are illustrated in Figure 2.

Figure 2.

Comparative ranking results.

Figure 2 indicates that alternative ranking results are the same in all combinations. Therefore, it is seen that the proposed model creates coherent and consistent results.

Discussions

Efficient storage of waste plays an important role for effective waste management. To reduce environmental pollution, waste storage must be carried out correctly. If these processes are carried out in an uncontrolled manner, waste can damage soil and water resources. In summary, the correct construction of waste storage systems helps to protect natural resources. There are many different types of medical waste in hospitals. According to Brindhadevi et al. (2023), thanks to the efficient storage of these wastes; the safety of both patients and employees is ensured. The correct storage of these hazardous wastes helps to reduce the risk of infection. Rahmanifar et al. (2023) and Antasouras et al. (2023) mentioned that proper storage also helps the waste disposal process to be carried out more successfully. Thus, waste management processes of hospitals can be carried out without harming the environment and people (Cook et al., 2023).

It is necessary to take some measures for the efficient storage of waste in hospitals. Firstly, the waste must be properly separated. In this way, waste will be stored in the right place. Çelik et al. (2023), Kularatne (2023) and Negishi and Kawahara (2023) identified that the containers in which the waste is stored must also be chosen correctly. In this context, it is important that the containers selected for hazardous waste are robust. Otherwise, waste will leak from the containers, and this will cause environmental pollution. On the other hand, Altin et al. (2023) discussed that hospitals should organize their waste storage areas properly. In this context, waste should be stored according to their types. In this way, it is possible to determine the waste to be used in recycling more accurately. Moreover, importance should be given to the hygiene of the areas where the waste is stored. In this context, Antasouras et al. (2023) claimed that these areas should be subject to disinfection at certain periods. Additionally, safety precautions should be taken in the hospital waste storage area. In this context, a system should be developed where only authorized personnel can access these areas.

Necessary strategies must be applied to decrease waste amount in the hospitals. In this context, necessary training should be given to hospital personnel regarding this process. Thus, it is possible to increase the awareness of the personnel towards waste management processes. Moreover, Almubarak et al. (2023) concluded that hospitals should pay attention to the reusability of these materials when choosing the equipment, they will use. This helps hospitals to significantly reduce the amount of waste. Furthermore, Savitha and Joseph (2023) determined that hospitals should also develop strategies to reduce material consumption. In this context, identifying unnecessary materials allows to eliminate waste in this process. Barai and Bhanvase (2023) concluded that less material consumption also contributes significantly to reducing the amount of waste. In addition, ensuring energy efficiency in hospitals also helps to generate less waste. In this context, the use of materials that contribute to energy saving helps hospitals achieve these goals.

Creating an effective decision-making model is also a very difficult issue. This new model should represent the real problem appropriately. However, due to problems such as data not being able to represent reality and uncertainty not being reduced, most of the existing decision-making models in the literature are criticized (Başaran et al., 2023; Singh et al., 2023). For example, some scholars used AHP methodology in their model mainly because of the hierarchical evaluation advantage. However, they are also criticized mainly for not considering causal directions among the criteria (Sood et al., 2023; Tarife et al., 2023). Furthermore, DEMATEL methodology was also taken into consideration in some models for the advantage of creating impact relation map (Abdullah et al., 2023; Sathyan et al., 2023). Nevertheless, some studies also criticized this technique for providing incorrect results in case of symmetrical evaluation (Özdemirci et al., 2023). In some studies, this methodology is improved to minimize this problem (Eti et al., 2023; Oflaz et al., 2023). On the other side, TOPSIS and VIKOR methods were mainly considered in the decision-making models (Erdebilli et al., 2023; Sharaf, 2023). Nonetheless, considering Euclidian distance in the evaluation process is accepted as the main drawback of these approaches (Oflaz et al., 2023). In recent studies, some new ranking techniques are also proposed to overcome these problems (Dinçer et al., 2023a, 2023b).

Conclusions

The most crucial factors of the effective waste management process should be identified because making improvements related to the determinants can increase the costs at the same time. For this purpose, six JCI-based indicators for the hospitals are weighted by using ST-FDEMATEL methodology. It is defined that efficient storage of waste is the key issue because of the highest weight (0.2570). Separation of waste is found as the second most critical issue with the weight of (0.2270). A different evaluation has also been carried out by ST-FCRITIC approach. It is identified that both ST-FDEMATEL and ST-FCRITIC are the same. This situation gives information about the coherency of the proposed model. Hence, with the help of the correct construction of waste storage systems in hospital, the safety of both patients and employees is ensured. On the other side, in the second part of the analysis, five integrated waste management hierarchy-based criteria are ranked by using ST-FTOPSIS. On the other side, these factors are also ranked with the help of ST-FARAS to test the consistency of the results. These ranking results pave the way for both investors and managers to identify their strategic decisions in this issue. It is concluded that ‘reduce’ is the most significant stage of effective waste management because of the greatest C value (0.9995). Similarly, recycling is another important alternative in this context with the G value of 0.9521. The comparative analysis also demonstrates that alternative ranking results are the same in all combinations. Therefore, it is seen that the proposed model creates coherent and consistent results. Hospitals should mainly implement strategies to decrease waste amount in the hospitals. Thus, it is possible to increase the awareness of the personnel towards waste management processes.

The most critical strategies can be presented to the hospitals while defining the most important factors to have appropriate waste management process. Additionally, considering JCI standards to define criteria and integrated waste management hierarchy approach to select alternatives provides significant benefits, as well. With the help of this issue, energy efficiency and environmental protection can be provided more appropriately. Making evaluation for only hospitals can be accepted as the main limitation. By considering this issue, in future studies, different industries can be evaluated. For instance, waste management plays a critical role for automotive and textile industries. Thus, these industries can be examined with a different methodology in following manuscripts. The proposed model in this study has also some limitations. As an example, the evaluations of different experts are considered with equal weights. Nonetheless, these experts can have different qualifications mainly due to their experience and education levels. Thus, as a future research direction, a new fuzzy decision-making model can be generated that provides different weights for the experts based on their qualifications.

Appendix

Table A1.

Evaluations of criteria.

Criteria	CWTL	FSGW	NMPS	SPOW	OHST	DQGG
Expert 1
CWTL	0	2	2	2	3	2
FSGW	7	0	7	7	7	7
NMPS	3	1	0	2	3	3
SPOW	6	5	7	0	6	6
OHST	4	2	4	2	0	3
DQGG	3	1	4	2	4	0
Expert 2
CWTL	0	3	4	1	3	3
FSGW	6	0	7	6	7	6
NMPS	2	2	0	1	2	3
SPOW	7	5	5	0	6	5
OHST	3	3	3	2	0	1
DQGG	3	3	2	2	2	0
Expert 3
CWTL	0	1	2	1	3	2
FSGW	7	0	6	5	7	7
NMPS	2	1	0	2	2	3
SPOW	6	4	7	0	5	5
OHST	3	1	3	2	0	2
DQGG	3	1	3	2	3	0

Table A2.

Normalized direct-relation matrix.

Criteria	CWTL	FSGW	NMPS	SPOW	OHST	DQGG
CWTL	0.0000	0.0057	0.0482	−0.0276	0.0442	0.0176
FSGW	0.2014	0.0000	0.2014	0.1896	0.2061	0.2014
NMPS	0.0176	−0.0276	0.0000	−0.0119	0.0176	0.0442
SPOW	0.1949	0.1437	0.1976	0.0000	0.1783	0.1690
OHST	0.0692	0.0057	0.0692	0.0018	0.0000	0.0057
DQGG	0.0442	−0.0078	0.0592	0.0018	0.0592	0.0000

Table A3.

Total relation matrix.

Criteria	CWTL	FSGW	NMPS	SPOW	OHST	DQGG
CWTL	−0.0010	0.0005	0.0465	−0.0279	0.0410	0.0152
FSGW	0.2765	0.0195	0.2891	0.1832	0.2752	0.2555
NMPS	0.0102	−0.0301	−0.0063	−0.0177	0.0106	0.0351
SPOW	0.2573	0.1398	0.2710	0.0170	0.2392	0.2179
OHST	0.0721	0.0039	0.0744	−0.0003	0.0059	0.0110
DQGG	0.0473	−0.0093	0.0635	−0.0019	0.0603	0.0018

Table A4.

Evaluations of alternatives.

Alternatives	CWTL	FSGW	NMPS	SPOW	OHST	DQGG
Expert 1
Reduce	5	1	5	7	5	5
Reuse	4	3	7	6	4	5
Recycling	5	2	7	4	7	6
Energy recovery	3	1	7	5	6	4
Landfill	2	5	2	4	3	1
Expert 2
Reduce	6	6	5	6	7	6
Reuse	5	5	6	5	4	5
Recycling	6	5	5	4	7	6
Energy recovery	3	4	3	5	3	4
Landfill	2	2	3	3	3	3
Expert 3
Reduce	6	7	7	7	7	6
Reuse	3	3	4	3	4	3
Recycling	6	6	6	5	6	6
Energy recovery	3	4	2	3	4	5
Landfill	4	4	5	2	3	4

Table A5.

Weighted decision matrix.

Alternatives	CWTL		FSGW		NMPS		SPOW		OHST		DQGG
Reduce	0.99	0.02	0.97	0.03	0.99	0.02	0.99	0.01	0.99	0.01	0.99	0.01
Reuse	0.96	0.05	0.91	0.09	0.99	0.01	0.98	0.04	0.96	0.04	0.97	0.04
Recycling	0.99	0.02	0.95	0.05	0.99	0.01	0.97	0.05	0.99	0.01	0.99	0.01
Energy recovery	0.92	0.10	0.88	0.10	0.97	0.04	0.97	0.05	0.97	0.04	0.97	0.03
Landfill	0.92	0.09	0.92	0.07	0.94	0.07	0.93	0.11	0.92	0.10	0.93	0.09

Table A6.

Ideal positive and negative values.

Alternatives	CWTL		FSGW		NMPS		SPOW		OHST		DQGG
Ideal positive values	0.99	0.02	0.97	0.03	0.99	0.01	0.99	0.01	0.99	0.01	0.99	0.01
Ideal negative values	0.92	0.10	0.88	0.10	0.94	0.07	0.93	0.11	0.92	0.10	0.93	0.09