1. Introduction

• Which KPIs of the performance measurement model are utilized in SHRL?
• How to assess SHRL KPIs under data uncertainty?
• How does the integration of the fuzzy Delphi-DEMATEL method enhance the accuracy and reliability of performance measurement in SHRL?

2. Literature Review

2.3. Proposed Key Performance Indicators

In this section, all the proposed KPIs are shortlisted with descriptions and sources for further study using MCDM techniques i.e. Fuzzy Delphi and Fuzzy DEMATEL methods.

Performance Measurement is a crucial management tool for assessing work impact, demonstrating value, managing resources, and directing efforts towards improvement. Lambert suggests aligning metrics with organizational goals for optimal performance measurement [80]. Metrics are essential for operational excellence success, providing objective performance measures for programs, activities, systems, and equipment. KPIs are metrics used to measure performance towards strategic and operational objectives of the organizations. They define effectiveness, monitor operational excellence, and show progress. Processes for actions in response to KPIs should be established, ensuring accurate performance and corrective action in case of discrepancies. Recent studies of performance indicators in humanitarian relief logistics pose challenges for humanitarian organizations due to complexity and information overload, necessitating a systematic guideline for prioritizing KPIs, as existing studies lack critical analysis and judgment biases.

Table 2. List of Key Performance Indicators with description and sources.

Table 2. List of Key Performance Indicators with description and sources.

Sr No	KPIs	Descriptions	Sources
1	Prompt Delivery	Prompt Delivery refers to the timely and efficient transportation of goods or services to their intended recipients within the agreed timeframe, with punctuality being a crucial factor, while promptness refers to the speed of delivery.	[9,12,81,82,83]
2	Delivery Accuracy	Delivery Accuracy refers to the quality or precision of goods and services, ensuring they accurately match specifications and requirements.	[30,74,81,83,84]
3	Trustworthiness of delivery	Trustworthiness of delivery measures consistency and dependability in terms of quantity, quality, and availability.	[14,85,86]
4	Responsive Delivery	Responsiveness measures flexibility and adaptability to changing needs.	[84,87]
5	Satisfied Delivery	satisfaction measures how satisfied beneficiaries, donors, and humanitarian organizations are with the goods and services provided.	[81,88]
6	Delivery Grievances	An Expression of dissatisfaction. A delivery grievance is a complaint that can be formal.	[89]
7	Delivery Errors	A failed delivery in logistics can occur when there's an error in the shipping address, a human error by the driver, or the driver doesn't meet the required time window	[90,91]
8	Delivery transparency	Delievry Transparency which assesses how accessible the information and communication about the goods and services are to stakeholders and the public.	[87,92]
9	Delivery Participation	Delievry Participation should be monitored to measure how inclusive and representative the involvement of affected populations and other stakeholders is in the planning, implementation, and evaluation of goods and services.	[81]
10	Delivery Feedback	Feedback should be assessed to determine how effective and responsive the mechanisms for receiving and addressing complaints, suggestions, and compliments are from beneficiaries.	[93,94]
11	Capacity Building and Training	CBT should be evaluated to ascertain how systematic and continuous the processes for collecting, analyzing, and applying lessons learned and best practices are from goods and services.	[95,96]
12	Delivery Compliance	Compliance should be surveyed to gauge how well goods and services adhere to relevant laws, regulations, policies, standards, and codes of conduct.	[97,98]
13	Stakeholder Engagement	Stakeholder engagement involves identifying, analyzing, planning, and implementing actions to influence stakeholders, ensuring inclusive and representative participation in planning, implementation, and evaluation of goods and services.	[99]
14	Resource Utilization	To evaluate resource utilization measures how optimal the use of resources is for goods and services.	[81,82,100]
15	Impact Assessment	Impact assessment measures how well goods and services achieve intended objectives.	[82,101]
16	Adaptive Capacity	Adaptative capacity measures how robust and adaptable goods and services are to cope with shocks.	[100,102]
17	Pollution Control	Pollution measures how to use a carbon footprint. A carbon footprint is a measure of the amount of carbon dioxide and other greenhouse gases emitted by an activity, service, or product.	[103,104,105]
18	Resource Conservation	Resource Conservation measures how waste and degradation of natural resources are from goods and services.	[106,107]
19	Local communities Empowerment	Community empowerment refers to the process of enabling communities to increase control over their lives	[108,109,110]
20	Labor Condition	How humanitarian organizations take care of the security and working condition and health of their workers in humanitarian relief activities	[111]
21	Political instability	Political instability refers to the probability of a government failing as a result of disagreements or competition among political parties.	[112]
22	logistics dispute and trade dispute	A logistics dispute involves supply chain disagreements, while a trade dispute involves workers and employers, or between countries over products traded.	[113]
23	legislation and regulatory amendments	Logistics legislation and regulatory amendments involves various regulations covering customs, transportation, safety, environmental concerns, and trade agreements, regulated by legislation or Acts of Parliament, and amendments.	[114]
24	Minimize total Cost	Economic impact measures positive effects on income, livelihoods, markets, and infrastructure, while cost minimization reduces unnecessary or inefficient expenditures.	[81,82,115]
25	Financial Efficiency	Financial efficiency refers to an organization's ability to efficiently convert expenses into revenue and achieve goals with minimal waste, effort, or energy.	[82,83,115]

Performance Measurement is a crucial management tool for assessing work impact, demonstrating value, managing resources, and directing efforts towards improvement. Lambert suggests aligning metrics with organizational goals for optimal performance measurement [80]. Metrics are essential for operational excellence success, providing objective performance measures for programs, activities, systems, and equipment. KPIs are metrics used to measure performance towards strategic and operational objectives of the organizations. They define effectiveness, monitor operational excellence, and show progress. Processes for actions in response to KPIs should be established, ensuring accurate performance and corrective action in case of discrepancies. Recent studies of performance indicators in humanitarian relief logistics pose challenges for humanitarian organizations due to complexity and information overload, necessitating a systematic guideline for prioritizing KPIs, as existing studies lack critical analysis and judgment biases.

In this study we identify the KPIs from literature review and expert opinion in this field, and grouped into four categories “Quality”, “Accountability”, “Operational Excellence”, and “Sustainability”. These pillars help to improve and monitor the performance of humanitarian organizations and enhance the generated knowledge in the field of relief operations, disaster management, and humanitarian logistics and supply chain. A total of 115 research papers pertaining to sustainable humanitarian logistics, performance measurement, relief operations, humanitarian supply chain were examined, resulting in the identification of 25 KPIs for SHRL.

3. Materials and Methods

3.1. Proposed Framework

Although attempts have been made to encourage varied performance evaluation in humanitarian organizations, there are still certain indicators impeding the progress towards efficient performance of HOs. Humanitarian Organizations still struggle to bridge the divide. Our goal is to gather these crucial indicators from a thorough perspective by conducting a literature review. It is essential to have a comprehensive classification of these indicators to gain a thorough grasp of performance measurement and identify the most crucial indicators. The framework integrates two methodologies and consists of three stages, as shown in Figure 3.

3.1.1. Fuzzy Delphi Method

The Delphi method, developed by Dalky and Helmer in 1963, is a widely used expert opinion communication technique for obtaining anonymous feedback and modifying previous comments. It has been applied in various domains, including industrial quality evaluation[116], investment decisions, production prediction, risk assessment and management, forecasting and trend analysis and disaster preparedness and response. However, the traditional method has deficiencies, such as low convergence ratings, distorted expert opinions, and high execution costs. To address these issues, the fuzzy Delphi method was introduced, allowing decision makers to express their comments through TFNs.

The fuzzy Delphi method is a method that combines subjective judgments with written communication to make final decisions. It is particularly useful in identifying significant KPIs. The process involves designing questionnaires to assess potential KPIs, assigning score intervals ranging from 0 to 4, representing their importance. The maximum score interval indicates positive (idealistic) cognition, while the minimum indicates negative (pragmatistic) cognition. This method offers advantages over conventional methods.

Let x, y, and z be the minimum, average, and maximum ways of representing opinions; they are considered as a TFN and can be written as:

$$E_m=(x_m,y_m,z_m)$$

(1)

Where $E_m$ represents the fuzzy number for the criteria m. $x_m$ , $y_m$ and $z_m$ can be represented as the minimum, average, and maximum number of experts’ opinions. The center-of-gravity method is used to de-fuzzified the obtained judgment opinions which can be computed with the assistance of equation mentioned below:

$$L_m=\left(x_m+y_m+z_m\right)/3$$

(2)

The principles for the final selection of the criteria are as follows:

(1)

If $L_m⩾ \beta$ accepts criterion m; and

(2)

If $L_m<\beta$ omit criterion m.

3.1.2. Fuzzy DEMATEL Method

The fuzzy DEMATEL technique is an effective instrument for addressing decision-making challenges and seeking comprehensive answers. It involves assigning a score of influence in the form of triangular fuzzy numbers (TFNs) to linguistic variables (qualitative data). There are five primary stages of the fuzzy DEMATEL algorithm. The TFNs Strongly agree

Table 3. Linguistic variables and their TFN.

Table 3. Linguistic variables and their TFN.

Linguistic variable	Score	TFNs
Strongly agree	4	(0.7, 0.9, 1)
Agree	3	(0.5, 0.7, 0.9)
Normal	2	(0.3, 0.5, 0.7)
Disagree	1	(0.1, 0.3, 0.5)
Strongly disagree	0	(0, 0.1, 0.3)

Step 1: Making a pairwise matrix of KPIs

Create a median direct relation matrix by assigning TFNs using a fuzzy linguistic scale. The relative importance of criteria i to j is shown by the element of the direct relation matrix $n\times n$ generated through pairwise comparison.

Converting fuzzy information to crisp scores (CFCS) facilitates the aggregation of fuzzy data. Crisp value is determined in CFCS's five main stages by averaging the weights of the fuzzy minimum and maximum values. Suppose $u_{ij}^k=\left(a_{ij}^k,b_{ij}^k,c_{ij}^k\right)$ indicates the three fuzzy judgments lower, medium and upper value denoted by a, b and c of evaluator k from criteria i to j; such that $k=1,2,\mathrm{3....}p$ . Where p denotes the number of respondents. Five stages algorithm for CFCS is given below

Stage 1: Normalization

$$x{a}_{ij}^k=(a_{ij}^k-\min a_{ij}^k)/{\Delta }_{\min }^{\max },$$

(3)

$$x{b}_{ij}^k=(b_{ij}^k-\min a_{ij}^k)/{\Delta }_{\min }^{\max },$$

(4)

$$x{c}_{ij}^k=(c_{ij}^k-\min a_{ij}^k)/{\Delta }_{\min }^{\max },$$

(5)

where

$${\Delta }_{\min }^{\max }=\max c_{ij}^k-\min b_{ij}^k,$$

(6)

Stage 2: Left and right normalized values

$$xl{s}_{ij}^k=x{b}_{ij}^k/(1+x{b}_{ij}^k-x{a}_{ij}^k),$$

(7)

$$xc{s}_{ij}^k=x{c}_{ij}^k/(1+x{c}_{ij}^k-x{b}_{ij}^k)$$

(8)

Stage 3: Total normalized crisp value

$$x_{ij}^k=\left[xl{s}_{ij}^k(1-xl{s}_{ij}^k)+x{c}_{ij}^k\times x{c}_{ij}^k\right]/\left[1-xl{s}_{ij}^k+xc{s}_{ij}^k\right]$$

(9)

Stage 4: Crisp value

$$u_{ij}^k=\min a_{ij}^k+x_{ij}^k{\Delta }_{\min }^{\max }.$$

(10)

Stage 5: Combine crisp value

$$u_{ij}^k=\frac{1}{p}(u_{ij}^1+u_{ij}^2+u_{ij}^3+\mathrm{...}+u_{ij}^l).$$

(11)

Step 2: Construction of normalized direct relation matrix

The normalizing$U$matrix calculates the normalized direct relation matrix, such that$M={\left[M_{ij}\right]}_{n\times n}$and $0\le M_{ij}\le 1$.

The matrix can be calculated by using the following formula:

$$M=\frac{U}{{\max }_{1\le i\le n}{\displaystyle \sum _{j=1}^n{u}_{ij}}},i,j=1,2,\mathrm{3...}n$$

(12)

Where ${\max }_{1\le i\le n}{\displaystyle \sum _{j=1}^n{u}_{ij}}$ denotes the driver having the most influence on other drivers.

Step 3: Finding the total relation matrix

The total relation matrix can be determined by using a normalized matrix.

$$T=M{(I-M)}^{-1}.$$

(13)

Where $I$denotes the identity matrix.

Step 4: Determining total row and total column values

The following formulas calculate the sum of the entire row (Q) and total column (S)

$$T={\left[t_{ij}\right]}_{n\times n}i,j=1,2,\mathrm{3...}n$$

(14)

$$Q={\left[{\displaystyle \sum _{j=1}^n{t}_{ij}}\right]}_{n\times 1}$$

(15)

$$S={\left[{\displaystyle \sum _{i=1}^n{t}_{ij}}\right]}_{1\times n}$$

(16)

Step 5: Formulation of a cause-and-effect diagram

The sum of Q and S denotes the prominence value, and the difference is the relaxation value. The positive relation value (Q+S) lies in the cause group, and the negative relation value (Q-S) lies in the effect side.

Step 6: The criteria weight calculation formula

$$T_i={\left[{\left(Q_i+S_i\right)}^2+{\left(Q_i-S_i\right)}^2\right]}^{1/2}$$

(17)

$$t_i=\frac{T_i}{{\displaystyle \sum _{i=1}^n{T}_i}}$$

(18)

4. Results

4.2. Fuzzy DEMATEL

After FDM and selecting critical KPIs by the expert opinions fuzzy DEMATEL method is applied to get the cause-and-effect relationship among KPIs and establish a structural model.

4.2.1. Making a Pairwise Matrix of KPIs

Participants evaluated each KPI using a five-point linguistic scale. Table 6 displays the outcome of an expert's assessment, illustrating the impact of one KPI on the others. According to the given table Expert argues that D1 has very strong impact (SA) on D2, D3, D4, D6, D10, D16, D17, and D18, medium impact on D5, D8, D9, D11, D12, and D19. He also elaborates that D1 has no impact on D13. Furthermore, D1 has high impact on remaining indicators D7, D14, and D15.

The respondents' reaction, represented as an influence score, is transformed into TFNs. As an illustration, the linguistic variable "Strongly Agree" (SA) with an influence score of 4 is converted into a fuzzy number (0.7, 0.9, 1). The process involves utilizing an excel sheet and implementing the CFCS defuzzification procedure, as described in equations (3) – (11), to transform fuzzy integers into a precise value. The results of the cause-and-effect diagram are calculated by equations 14 to 16 as shown in Figure 5. The results obtained from equation 14 to 16, the values of Q and S form the cause-and-effect diagram. By adding Q and S (Q + S) to obtain the horizontal values (x-axis) of the diagram, meanwhile subtracting Q and S (Q – S) to obtain the vertical values (y-axis) of the cause-and-effect diagram to describe the KPIs importance and interconnection with each other. From the results (Table 5) we conclude that the prompt delivery D1 is the main factor in the cause group with the highest vertical axis value. Prompt delivery is crucial in disaster management and humanitarian logistics, as it directly impacts various factors. It ensures the effectiveness of relief efforts, builds trust and confidence among stakeholders, and enables timely responses to evolving needs. It also contributes to beneficiary satisfaction by meeting their immediate needs, reducing frustration and disappointment. Prompt delivery also enhances operational efficiency by minimizing bottlenecks and optimizing logistics processes. It also promotes transparency and accountability in relief operations, providing stakeholders with clear visibility into their actions and decision-making processes. Therefore, prioritizing timeliness ensures aid reaches those in need promptly, maximizes the impact of relief interventions, and fosters trust and confidence among stakeholders involved in relief operations.

Sustainable humanitarian relief logistics are influenced by several indicators, which were categorized into four groups by experts and intensive literature review and proved by the study that these four groups are essential to measure the performance of HOs. The proposed model and findings reveal that these KPIs are essential to achieve the goals of HOs before, during, and after the disaster and cover all the phases of the disaster management cycle. SHRL's focus is to provide immediate relief to disaster victims to save the lives of people with vulnerabilities as it is its prime responsibility.

Table 6. Final weightage and Ranking for KPIs.

Table 6. Final weightage and Ranking for KPIs.

KPIs	Q	S	Q+S	Q-S	Group	Weights	Rank
D1	8.6448	7.2716	15.9164	1.3731	Cause	0.0553	1
D2	8.1965	7.5703	15.7668	0.6261	Cause	0.0546	2
D3	7.5424	8.0685	15.6109	-0.5261	Effect	0.0541	4
D4	7.7358	6.8506	14.5864	0.8852	Cause	0.0506	16
D5	7.7150	6.6829	14.3979	1.0321	Cause	0.0500	19
D6	7.8740	7.6831	15.5572	0.1909	Cause	0.0538	6
D7	7.5737	7.9353	15.5089	-0.3616	Effect	0.0537	7
D8	7.5101	7.8676	15.3778	-0.3575	Effect	0.0532	9
D9	7.7661	7.6369	15.4029	0.1292	Cause	0.0533	8
D10	7.0354	8.2786	15.3140	-1.2432	Effect	0.0532	10
D11	7.7218	7.4333	15.1550	0.2885	Cause	0.0525	11
D12	7.9556	7.0835	15.0391	0.8721	Cause	0.0521	13
D13	6.8688	8.1806	15.0493	-1.3118	Effect	0.0523	12
D14	7.3217	7.6536	14.9753	-0.3319	Effect	0.0518	14
D15	7.1318	7.4542	14.5860	-0.3224	Effect	0.0505	18
D16	7.2845	7.3141	14.5986	-0.0297	Effect	0.0505	17
D17	7.2280	7.3897	14.6177	-0.1617	Effect	0.0506	15
D18	7.5875	8.0297	15.6172	-0.4422	Effect	0.0541	3
D19	7.6420	7.9513	15.5934	-0.3093	Effect	0.0540	5

4. Discussion

5. Conclusions

6. Patents

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