1. Introduction

The story of the pandemic ‘‘COVID-19’’ began in 2019 when the first case were identified from Wuhan, China [1]. Since its first appearance, COVID-19 has been receiving an increasing attention by academic and executive specialists and many researches have been developed on it in order to provide a general definition of the virus. In the beginning, COVID-19 has created a global healthcare crisis, and then it disrupted other sectors: economic, environmental and social [2]. But perhaps the most significant pressure was for the healthcare organizations which strengthened their medical system [3] in order to enhance their responsiveness, adaptability, flexibility, which explains the importance of agility implementation in the healthcare sector through the outbreaks of COVID 19.

Agility concept was presented as the effective exploration of different competitive bases by including the suitable resources and practices in order to cope with the changing environment [4, 5]. Later, different proposals of agility definitions have been derived and which presented a general consensus [5]: It means the organization capacity to react quickly [5]–[11] to the varied changes in market demand [8]–[11] in terms of cost, specification, quality, quantity and delivery [11, 12] . Despite being defined in different ways and from different perspectives, agility has sometimes been used interchangeably to refer to concepts such as adaptability, flexibility, speed, intelligence or sharpness. In contrast to this point of view, several authors have expressed the difference between these concepts, which justifies our choice to use the word “Agility” many times in our paper.

In order to evaluate the agility of an organization [5], several approaches such as system approach [5, 13] , graph theory [5, 14], multi-grade fuzzy logic [15], regression analysis [5, 16]  and other artificial intelligence techniques, such as neural network [15], neuro-fuzzy [15], have been used [5, 13, 14, 16–19] . A main objective of this study is to help the healthcare organization to implement an easier and less complicated practical tool in order to evaluate their agility [11]. The above purpose suggests an assessment model in which we evaluated the enablers influencing the adoption of agility [15].

Our paper is organized as follows: In the next paragraph, we review previous researches related to agile enablers. By presenting the fuzzy logic approach, we presented the required steps to apply this methodology to a real case. Moreover, the results provided are discussed and the limits of the study and suggestions for future research are finally presented [11].

2. Literature review: Agile enablers

According to different conceptual models of agility presented in literature, companies can benefit from different enablers [11] in order to achieve agility. These enablers, also known as providers or levers [20], were introduced by Gunasekaran [21, 22]  in order to identify the required features of the agile organization [20]. In his study, he identified seven agile enablers: virtual corporation formation tools/metrics, physically distributed teams and manufacturing, quick partnership formation, concurrent engineering, integrated information system, quick prototyping tools and E-commerce [22]. In 1999, Yusuf et al. [4] presented different enablers under ten groups: the introduction of new products, the formation of partnerships, continuous improvement, short conception/production of deadlines, decentralized decision-making, response to market requirements …etc [20]. Later, Sharifi and his colleagues proposed four enablers from four different areas: organization, people, technology and innovation  [9, 23]. Based on their sample, Tolf et al. identified five essentials enablers for an agile organization: transparent and transient inter-organizational links at all levels, market sensitivity and customer focus, management by support for self-organizing employees, organic structures and flexible human and resource capacity for timely delivery [24]. In their paper [25], Lin and his colleagues suggested four agility enablers: collaborative relationships, process integration, information integration and customer sensitivity [26]. Other enablers were identified by Eshlaghy et al., as organizational structure, virtual organization, information technology, organizational culture, leadership, team working, empowerment and improvement, motivation system  and planning and evaluation performance [27].

From this literature review, we can notice that there is no single list of agility enablers [20] which is due to the varied requirements of each organization [28]. However, all the enablers should have some criteria and attributes that make them agile. For example, the criterion called “Organizational structure” should be flexible to accept changes, this means that the different attributes of the organizational structure should be easily adaptable [20], while promoting a fluid flow of information [15], communication [29] and knowledge [30], which makes it possible to accept the interchangeability of employees [15] and focus on teamwork [20, 27, 30, 31] . For the other criterion “Processes”, it should be flexible [20, 30], promote and concentrate on external environment developments [20, 30, 32]. According to Sherehiy et al. [30], human resource agility, as an enabler of the agile organization [20], should be flexible [33], multi-skilled [15, 33], adaptable, resilient [20, 30, 32], able to cooperate [15, 20, 30], take personal initiative and cope well with changes [20, 30, 32]. The technology enabler should also be flexible like other enablers, modular and easily scalable [20].

Summarizing the above literature, different enablers, as listed in Table 1, are chosen as necessary conditions for organizational agility [33]. Table 1 suggest an assessment model in which we defined, firstly, the agile enablers that should be implemented by organizations; secondly, for each enabler different agile criteria are listed and finally agile attributes are identified in order to achieve the required agile criteria [15].

Table 1: Organizational agility enablers (Adapted from [12, 15, 27, 29–34])

Agile enablers	Agile criteria	Agile attributes
Management responsibility agility (E1)	Organizational structure (E11)	Flattened, horizontal organizational structure that promotes innovation, training and having an open information, communication and knowledge policy (E111)
		Fluid information flow (E112)
		Staff interchangeability (E113)
		Collaborative and team work (E114)
	Devolution of authority (E12)	Clear definition of staff responsibility and authority (E121)
		Training to create self-managed and multi-functional teams (E122)
		Decentralized decision-making, knowledge and control (E123)
		Loyalty and commitment to a project or a group (E124)
		Authority change when tasks change (E125)
	Nature of management (E13)	Participative management style (E131)
		Clearly known management purpose (E132)
		Management participation and support (E133)
		Motivation of profit associated with a humanitarian approach (E134)
		Regular conduct of employer–employees meetings (E135)
		Quick evaluation and implementation of employee suggestions (E136)
		Less strict or few rules and procedures (E137)
Manufacturing management agility (E2)	Patient response adoption (E21)	Dominance of the culture of continuous improvement (E211)
		Communication media to collect responses (E212)
		Incorporating patient feedback into services (E213)
		Staff empowerment to resolve patient issues (E214)
		Efficient information system and technology (E215)
	Change in business and technical processes (E22)	Flexible business system (E221)
		Application of business process reengineering to reinvent and reorganize the organization (E222)
		Positive employee attitude towards change, new ideas and technology (E223)
		Risk management (E224)
	Outsourcing (E23)	Adopting supply chain management concepts to improve the efficiency of outsourcing (E231)
		Exploitation of information technology (IT) in supply chain management (E232)
		Involvement of suppliers and different agents in product/service development (E233)
		Working with fewer qualified suppliers (E234)
	Processes sensing (E24)	Promoting and concentrating on external environment developments (E241)
	Processes responding (E25)	Reconfigurable process (E251)
		Scalable process (E252)
		Simple process to implement (E253)
	Concurrent engineering (E26)	Process design (E261)
		Intelligent Engineering Design Support System (E262)
		Integrated multidisciplinary teams of customers and suppliers (E263)
		Continuous reengineering of the organization and business processes based on benchmarking (E264)
Human resource agility (E3)	Employee status (E31)	Flexible employees to accept the adoption of new technologies (E311)
		Multi-skilled and flexible staff (E312)
		Implementation of job rotation system (E313)
		Education and training for all the existing and new employees (E314)
	Employee involvement (E32)	Employee cooperation (E321)
		Employee empowerment (E322)
	Human resource management practices (E33)	Entrepreneurial organizational culture (E331)
		Reward programs to encourage innovation and based on financial and non-financial measures (E332)
		Multi-skill training improving organizational agility (E333)
		Multi-functional, developed and trained employees (E334)
		Development of differentiation and diversity (E335)
	Human resources capacities (E34)	Anticipation of problems linked to change and resolution of these problems (E341)
		Personal initiative (E342)
		Interpersonal and cultural adaptability (E343)
		Resiliency (E344)
	Coordination (E35)	Personal, informal, goal-oriented and spontaneous coordination (E351)
		Network communication (E352)
		Management-employee cohesion  (E353)
	Human knowledge and skills (E36)	Knowledge and skills management systems (E361)
		Protection of sensitive information (E362)
		Knowledge acquisition from internal and external sources (E363)
Technology agility (E4)	Manufacturing set-ups (E41)	Flexible manufacturing setups (E411)
		Less time to change machine settings (E412)
		Modernization of machines (E413)
		Usage of collapsible set-ups, Jigs and Fixtures (E414)
		Usage of automated tools (E415)
		Active policy to keep work areas clean and tidy (E416)
	Product life cycle (E42)	Specification of product life to the patient (E421)
		Company encourages patient to switch to new product (E422)
		Products superior field performance for a stipulated period with least maintenance cost (E423)
	Product service (E43)	Products designed for easy serviceability (E431)
		Products incorporated with a modular design (E432)
		Service centers well equipped with spares (E433)
		Minimum time required to execute the planning and to restore the defective product to its original performance (E434)
	Production methodology (E44)	Management’s interest towards investment on flexible manufacturing system (FMS) concepts (E441)
		Application of Lean manufacturing principles for waste elimination (E442)
		Development of products whose components are all outsourced and assembled in-house (E443)
		IT application for better supplier management (E444)
	Manufacturing planning (E45)	Execution of short range planning (E451)
		Organization’s procurement policy based on time schedule (E452)
		Strategic network in supply chain management to exercise zero inventory system (E453)
		Improved manufacturing technology (E454)
		Structured and flexible manufacturing processes (E455)
	IT integration (E46)	IT utilities incorporated with reengineered pattern of working  (E461)
		Electronic commerce [27] (E462)
	Customization (E47)	Rapid introduction of new products/services (E471)
		Responding to changing market requirements (E472)
		Products with high added value (E473)
		First-time correct design (E474)
Manufacturing strategy agility (E5)	Status of quality (E51)	Products/services exceeding patient expectations (E511)
		Carrying out surveys/studies to guarantee the quality status (E512)
		Usage of total quality management tools (E513)
	Status of productivity (E52)	Improved productivity in all functions (E521)
		Reduction of non value-adding costs (E522)
		Quality is not infused at the cost of productivity (E523)
	Cost management (E53)	Costing and product pricing system focused on value-added and non-value-added activities (E531)
		Costing system enabling the evaluation of future resource consumption (E532)
		Product cost fixed according to the pricing of the customer (E533)
	Time management (E54)	Scheduled activities (E541)
		IT based communication system  (E542)
		Adoption of time compression technologies (E543)

3. Fuzzy logic methodology to evaluate organizational agility

In order to enhance organizational agility in practice, the use of different methods and tools were recommended in literature [11, 23]. Focusing on methodological articles [11], the fuzzy logic approach has been used to assess the current agility level and identify the weaker attributes that need a particular attention to enhance the organizational agility. This approach is preferred over other methodologies because it can take the linguistic data as input, then convert linguistic expressions into corresponding fuzzy intervals and finally express the results back in linguistic terms with the help of Fuzzy Agility Index (FAI) [5].

Many studies in literature have used fuzzy logic to measure agility level of the healthcare organization (e.g. [5, 35]). Taking cues from these papers, this study uses this approach to evaluate the agility of a Moroccan healthcare organization.

4. Numerical illustration of fuzzy logic approach

4.1. About the healthcare organization

Our study has been done at a public hospital (referred as HealthOrg), located in Morocco and where patients can carry out the diagnosis of COVID-19. In order to cope with the new dynamic environment, HealthOrg aims to strengthen its agility level. However, it found it difficult to identify enablers that influence its agility, in particular the weaker ones which need to be improved [15]. In this context, we aimed to evaluate the agility of HealthOrg.

Table 2 provides an illustration of different steps to apply the fuzzy logic approach [11].

Table 2: Steps required applying the fuzzy logic methodology (Adapted from [5, 32])

Steps
Identify a list of agile enablers that influence the organizational agility.
Define the linguistic variables for evaluating performance rating and importance weights of agile attributes.
Approximate the linguistic terms by the corresponding fuzzy intervals.
Calculate the FAI of the organization.
Match the FAI with the appropriate linguistic level.
Calculate Fuzzy Performance Importance Index (FPII).

4.2. Fuzzy logic application

• Step1: Identification of agile enablers, criteria and attributes [32]: By identifying a list of five agile enablers from the literature [5], twenty-six criteria and ninety-eight attributes were identified (Table 1).
• Step 2: Definition of the linguistic variables for evaluating performance rating and importance weights of agile attributes [32]: Following this list, five experts (E1, E2,…, E5) from HealthOrg were asked to provide the weights in terms of linguistic variables ranging from “Very low (VL)” to “Very High (VH)” and ratings in terms of linguistic variables ranging from “Worst (W)” to “Excellent (E)” [5] (Table 3).

Table 3: Importance weight and performance rating of agile attributes

Agile attributes	Importance weight					Performance rating
	E1	E2	E3	E4	E5	E1	E2	E3	E4	E5
E111	H	FH	M	H	FH	E	VG	VG	G	F
E112	H	M	FH	FH	H	P	P	F	G	G
E113	FH	H	FH	H	FH	VP	W	G	F	F
E114	H	M	H	FH	FH	E	G	G	F	F
E121	H	M	FH	M	FH	F	F	G	VG	VG
E122	H	FH	M	H	FH	P	F	P	G	F
E123	FH	H	FH	M	FH	W	W	P	F	P
E124	H	H	M	FH	H	W	W	VP	F	F
E125	M	H	H	FH	H	G	VG	E	E	G
E131	VH	H	H	VH	H	G	F	G	G	VG
E132	H	FH	H	FH	FH	E	E	G	F	E
E133	H	FH	H	FH	H	G	G	G	VG	G
E134	FH	M	FH	M	FH	F	G	F	F	G
E135	H	M	M	M	H	G	G	G	VG	F
E136	VH	H	H	VH	VH	VP	F	P	P	G
E137	H	FH	M	FH	H	W	F	G	F	G
E211	H	H	H	FH	H	G	VG	G	F	F
E212	FH	M	FH	FH	M	W	W	F	G	VP
E213	FH	FH	FH	FH	FH	VP	P	P	F	P
E214	VH	H	H	VH	H	F	G	E	VG	E
E215	H	FH	H	FH	FH	VP	P	W	F	F
E221	FL	M	FL	FL	M	VG	F	E	F	G
E222	H	FH	H	M	FH	W	VP	G	E	G
E223	H	M	M	FH	H	VP	F	F	W	E
E224	FH	H	H	H	FH	F	G	E	VG	G
E231	VH	H	VH	H	H	F	F	G	F	VG
E232	H	M	FH	H	FH	VP	P	G	F	W
E233	H	H	H	H	H	F	W	VP	F	G
E234	FH	H	M	FH	FH	E	VG	F	G	G
E241	H	M	FH	FH	FH	VP	F	G	G	F
E251	H	FH	M	H	M	F	VG	VG	G	VG
E252	FH	FH	FH	FH	FH	VP	VG	F	G	F
E253	FH	M	FH	FH	M	W	W	VP	F	VP
E261	H	FH	H	FH	M	G	F	G	VG	E
E262	H	M	FH	H	H	W	W	G	F	G
E263	FH	M	H	FH	FH	VP	P	W	P	F
E264	H	FH	H	FH	M	G	F	P	VP	G
E311	FH	FH	H	FH	H	P	W	F	G	P
E312	H	H	H	H	H	W	W	F	F	P
E313	VH	H	VH	VH	H	F	G	P	P	P
E314	FH	H	FH	M	FH	E	VG	G	E	F
E321	H	H	H	H	H	E	E	VG	F	F
E322	FH	M	H	H	H	P	F	F	G	VG
E331	H	FH	H	H	M	E	VG	G	F	G
E332	H	H	H	H	H	E	F	G	F	F
E333	H	M	M	M	M	W	W	F	G	F
E334	FH	FH	H	H	FH	W	P	VP	G	F
E335	H	FH	FH	H	H	E	E	E	G	E
E341	H	M	FH	M	H	VP	P	F	G	F
E342	H	FH	FH	FH	M	F	G	P	F	G
E343	H	FH	H	FH	M	F	E	VG	G	F
E344	H	FH	FH	H	H	G	F	F	E	G
E351	H	H	FH	H	M	VP	F	F	F	F
E352	FH	M	M	FH	FH	E	G	G	F	F
E353	H	FH	H	FH	FH	G	E	F	F	VG
E361	M	M	M	FH	FH	W	W	W	F	P
E362	H	M	FH	FH	H	E	E	E	E	VG
E363	H	FH	H	H	H	E	VG	F	P	F
E411	M	H	M	M	FH	VG	G	F	E	E
E412	FH	FH	M	M	H	W	G	P	F	F
E413	H	M	M	M	FH	G	F	G	E	F
E414	FH	H	H	H	H	G	F	F	F	VG
E415	M	H	FH	H	H	E	G	F	P	VP
E416	FH	H	M	H	FH	W	VP	P	VP	F
E421	H	VH	H	H	H	E	F	G	E	VG
E422	FH	FH	FH	M	H	E	E	G	G	G
E423	H	FH	M	M	FH	E	VG	F	G	G
E431	H	H	FH	H	FH	G	G	VG	E	E
E432	FL	FL	L	VL	M	E	VG	G	VG	E
E433	FL	M	FH	H	FH	G	F	E	E	VG
E434	M	FH	FH	H	VH	VP	P	F	VG	VG
E441	FH	VH	M	FH	VH	E	VG	VG	VG	G
E442	H	M	H	FH	H	G	F	VG	E	VP
E443	FL	H	VH	H	FH	G	F	VP	G	F
E444	VH	H	H	FH	VH	G	E	F	VG	F
E451	VH	VH	H	H	FH	W	VP	F	G	F
E452	VH	VH	H	VH	H	W	W	G	F	F
E453	FH	VH	FH	VH	M	VP	P	G	VG	F
E454	VH	VH	H	FH	FH	G	F	F	VP	P
E455	M	H	VH	H	H	E	VG	G	VG	F
E461	FH	FL	FL	FH	FH	G	G	F	F	F
E462	FH	M	FH	FH	H	VG	E	E	F	G
E471	H	H	FH	H	H	F	F	G	VG	VG
E472	FL	FH	FH	L	FH	E	E	E	VG	G
E473	H	H	FH	FH	H	G	E	VG	F	F
E474	VH	M	VH	H	VH	W	VP	F	G	E
E511	FH	FL	FL	M	FH	F	F	G	F	F
E512	FH	FH	FH	FH	H	E	VP	E	F	G
E513	H	H	M	H	H	E	E	E	E	E
E521	H	FH	VH	H	H	VP	G	E	G	G
E522	VH	M	VH	H	VH	VP	P	P	W	G
E523	H	VH	FH	FL	FL	E	VG	G	E	E
E531	M	M	FH	H	FL	G	E	F	G	F
E532	H	FL	H	M	H	F	F	VG	F	G
E533	M	M	M	M	M	F	F	F	G	G
E541	M	H	FL	M	M	VG	E	F	G	G
E542	H	H	FH	FH	H	G	F	F	F	VG
E543	M	H	M	VL	VL	G	F	F	F	VP

• Step 3: Approximation of the linguistic terms by the corresponding fuzzy intervals [32]: These linguistic variables were approximated by fuzzy intervals [5] chosen from literature [5, 25]  and presented in Table 4.

Table 4: Linguistic variables and fuzzy numbers for weighting and rating of agility (Adapted from [25])

Importance Weight		Performance Rating
Linguistic variable	Fuzzy number	Linguistic variable	Fuzzy number
Very Low (VL)	(0, 0.05, 0.15)	Worst (W)	(0, 0.5, 1.5)
Low (L)	(0.1, 0.2, 0.3)	Very Poor (VP)	(1, 2, 3)
Fairly Low (FL)	(0.2, 0.35, 0.5)	Poor (P)	(2, 3.5, 5)
Medium (M)	(0.3, 0.5, 0.7)	Fair (F)	(3, 5, 7)
Fairly High (FH)	(0.5, 0.65, 0.8)	Good (G)	(5, 6.5, 8)
High (H)	(0.7, 0.8, 0.9)	Very Good (VG)	(7, 8, 9)
Very High (VH)	(0.85, 0.95, 1.0)	Excellent (E)	(8.5, 9.5, 10)

To calculate the average fuzzy weight and performance rating of each attribute [5], the literature recommended using average operation method [5, 27].

Example: Average fuzzy weight of the attribute E₁₁₁= [H+FH+M+H+FH]/5 = (0.7, 0.8, 0.9)/5, (0.5, 0.65, 0.8)/5, (0.3, 0.5, 0.7)/5, (0.7, 0.8, 0.9)/5, (0.5, 0.65, 0.8)/5 = (0.54, 0.68, 0.82)

Example: Average fuzzy performance rating of the attribute E₁₁₁= [E+VG+VG+G+F]/5 = (8.5, 9.5, 10)/5, (7, 8, 9)/5, (7, 8, 9)/5, (5, 6.5, 8)/5, (3, 5, 7)/5 = (6.1, 7.4, 8.6)

The following step consists of calculating the rating of each criterion [5]. An example of this calculation for the criterion E₁₁ is shown below.

Example: Rating of the criterion

E₁₁=

= [(6.1, 7.4, 8.6) Ä (0.54, 0.68, 0.82) Å (3.4, 5.0, 6.6) Ä (0.54, 0.68, 0.82) Å (2.4, 3.8, 5.3) Ä (0.58, 0.71, 0.84) Å (4.9, 6.5, 8.0) Ä (0.54, 0.68, 0.82)] / [(0.54, 0.68, 0.82) Å (0.54, 0.68, 0.82) Å (0.58, 0.71, 0.84) Å (0.54, 0.68, 0.82)] = (4.17, 5.65, 7.11)

By using R language, fuzzy calculations are presented in Table 5.

Table 5: Fuzzy index of agile criteria rating

Agile criteria	Agile attributes	Average fuzzy performance rating	Average fuzzy weight	Criteria rating
E11	E111	(6.1, 7.4, 8.6)	(0.54, 0.68, 0.82)	(4.17, 5.65, 7.11)
	E112	(3.4, 5.0, 6.6)	(0.54, 0.68, 0.82)
	E113	(2.4, 3.8, 5.3)	(0.58, 0.71, 0.84)
	E114	(4.9, 6.5, 8.0)	(0.54, 0.68, 0.82)
E12	E121	(5.0, 6.5, 8.0)	(0.46, 0.62, 0.78)	(3.52, 4.88, 6.28)
	E122	(3.0, 4.7, 6.4)	(0.54, 0.68, 0.82)
	E123	(1.4, 2.6, 4.0)	(0.50, 0.65, 0.80)
	E124	(1.4, 2.6, 4.0)	(0.58, 0.71, 0.84)
	E125	(6.8, 8.0, 9.0)	(0.58, 0.71, 0.84)
E13	E131	(5.0, 6.5, 8.0)	(0.76, 0.86, 0.94)	(4.49, 5.99, 7.47)
	E132	(6.7, 8.0, 9.0)	(0.58, 0.71, 0.84)
	E133	(5.4, 6.8, 8.2)	(0.62, 0.74, 0.86)
	E134	(3.8, 5.6, 7.4)	(0.42, 0.59, 0.76)
	E135	(5.0, 6.5, 8.0)	(0.46, 0.62, 0.78)
	E136	(2.6, 4.1, 5.6)	(0.79, 0.89, 0.96)
	E137	(3.2, 4.7, 6.3)	(0.54, 0.68, 0.82)
E21	E211	(4.6, 6.2, 7.8)	(0.66, 0.77, 0.88)	(3.66, 4.93, 6.23)
	E212	(1.8, 2.9, 4.2)	(0.42, 0.59, 0.76)
	E213	(2.0, 3.5, 5.0)	(0.50, 0.65, 0.80
	E214	(6.4, 7.7, 8.8)	(0.76, 0.86, 0.94)
	E215	(1.8, 3.2, 4.7)	(0.58, 0.71, 0.84)
E22	E221	(5.3, 6.8, 8.2)	(0.24, 0.41, 0.58)	(4.45, 5.77, 7.04)
	E222	(3.9, 5.0, 6.1)	(0.54, 0.68, 0.82)
	E223	(3.1, 4.4, 5.7)	(0.50, 0.65, 0.80)
	E224	(5.7, 7.1, 8.4)	(0.62, 0.74, 0.86)
E23	E231	(4.2, 5.9, 7.6)	(0.76, 0.86, 0.94)	(3.56, 5.05, 6.55)
	E232	(2.2, 3.5, 4.9)	(0.54, 0.68, 0.82)
	E233	(2.4, 3.8, 5.3)	(0.7, 0.8, 0.9)
	E234	(5.7, 7.1, 8.4)	(0.50, 0.65, 0.80)
E24	E241	(3.4, 5.0, 6.6)	(0.50, 0.65, 0.80)	(3.4, 5.0, 6.6)
E25	E251	(5.8, 7.1, 8.4)	(0.50, 0.65, 0.80)	(3.68, 4.89, 6.18)
	E252	(3.8, 5.3, 6.8)	(0.50, 0.65, 0.80)
	E253	(1.0, 2.0, 3.2)	(0.42, 0.59, 0.76)
E26	E261	(5.7, 7.1, 8.4)	(0.54, 0.68, 0.82)	(3.29, 4.63, 6.03)
	E262	(2.6, 3.8, 5.2)	(0.58, 0.71, 0.84)
	E263	(1.6, 2.9, 4.3)	(0.50, 0.65, 0.80)
	E264	(3.2, 4.7, 6.2)	(0.54, 0.68, 0.82)
E31	E311	(2.4, 3.8, 5.3)	(0.58, 0.71, 0.84)	(3.08, 4.57, 6.06)
	E312	(1.6, 2.9, 4.4)	(0.7, 0.8, 0.9)
	E313	(2.8, 4.4, 6.0)	(0.79, 0.89, 0.96)
	E314	(6.4, 7.7, 8.8)	(0.50, 0.65, 0.80)
E32	E321	(6.0, 7.4, 8.6)	(0.7, 0.8, 0.9)	(5.09, 6.55, 7.92)
	E322	(4.0, 5.6, 7.2)	(0.58, 0.71, 0.84)
E33	E331	(5.7, 7.1, 8.4)	(0.58, 0.71, 0.84)	(4.69, 5.97, 7.21)
	E332	(4.5, 6.2, 7.8)	(0.7, 0.8, 0.9)
	E333	(2.2, 3.5, 5.0)	(0.38, 0.56, 0.74)
	E334	(2.2, 3.5, 4.9)	(0.58, 0.71, 0.84)
	E335	(7.8, 8.9, 9.6)	(0.62, 0.74, 0.86)
E34	E341	(2.8, 4.4, 6.0)	(0.50, 0.65, 0.80)	(4.21, 5.79, 7.32)
	E342	(3.6, 5.3, 7.0)	(0.50, 0.65, 0.80)
	E343	(5.3, 6.8, 8.2)	(0.54, 0.68, 0.82)
	E344	(4.9, 6.5, 8.0)	(0.62, 0.74, 0.86)
E35	E351	(2.6, 4.4, 6.2)	(0.58, 0.71, 0.84)	(4.20, 5.86, 7.45)
	E352	(4.9, 6.5, 8.0)	(0.42, 0.59, 0.76)
	E353	(5.3, 6.8, 8.2)	(0.58, 0.71, 0.84)
E36	E361	(1.0, 2.0, 3.3)	(0.38, 0.56, 0.74)	(5.01, 6.04, 7.03)
	E362	(8.2, 9.2, 9.8)	(0.54, 0.68, 0.82)
	E363	(4.7, 6.2, 7.6)	(0.66, 0.77, 0.88)
E41	E411	(6.4, 7.7, 8.8)	(0.42, 0.59, 0.76)	(3.81, 5.30, 6.74)
	E412	(2.6, 4.1, 5.7)	(0.46, 0.62, 0.78)
	E413	(4.9, 6.5, 8.0)	(0.42, 0.59, 0.76)
	E414	(4.2, 5.9, 7.6)	(0.66, 0.77, 0.88)
	E415	(3.9, 5.3, 6.6)	(0.58, 0.71, 0.84)
	E416	(1.4, 2.6, 3.9)	(0.54, 0.68, 0.82)
E42	E421	(6.4, 7.7, 8.8)	(0.73, 0.83, 0.92)	(6.21, 7.52, 8.67)
	E422	(6.4, 7.7, 8.8)	(0.50, 0.65, 0.80)
	E423	(5.7, 7.1, 8.4)	(0.46, 0.62, 0.78)
E43	E431	(6.8, 8.0, 9.0)	(0.62, 0.74, 0.86)	(5.84, 7.14, 8.27)
	E432	(7.2, 8.3, 9.2)	(0.16, 0.29, 0.43)
	E433	(6.4, 7.7, 8.8)	(0.44, 0.59, 0.74)
	E434	(4.0, 5.3, 6.6)	(0.57, 0.71, 0.84)
E44	E441	(6.9, 8.0, 9.0)	(0.60, 0.74, 0.86)	(5.14, 6.53, 7.82)
	E442	(4.9, 6.2, 7.4)	(0.58, 0.71, 0.84)
	E443	(3.4, 5.0, 6.6)	(0.59, 0.71, 0.82)
	E444	(5.3, 6.8, 8.2)	(0.72, 0.83, 0.92)
E45	E451	(2.4, 3.8, 5.3)	(0.72, 0.83, 0.92)	(3.34, 4.76, 6.23)
	E452	(2.2, 3.5, 5.0)	(0.79, 0.89, 0.96)
	E453	(3.6, 5.0, 6.4)	(0.60, 0.74, 0.86)
	E454	(2.8, 4.4, 6.0)	(0.68, 0.80, 0.90)
	E455	(6.1, 7.4, 8.6)	(0.65, 0.77, 0.88)
E46	E461	(3.8, 5.6, 7.4)	(0.38, 0.53, 0.68)	(5.28, 6.76, 8.16)
	E462	(6.4, 7.7, 8.8)	(0.50, 0.65, 0.80)
E47	E471	(5.0, 6.5, 8.0)	(0.66, 0.77, 0.88)	(5.01, 6.42, 7.74)
	E472	(7.5, 8.6, 9.4)	(0.36, 0.50, 0.64)
	E473	(5.3, 6.8, 8.2)	(0.62, 0.74, 0.86)
	E474	(3.5, 4.7, 5.9)	(0.71, 0.83, 0.92)
E51	E511	(3.4, 5.3, 7.2)	(0.34, 0.50, 0.66)	(6.16, 7.34, 8.37)
	E512	(5.2, 6.5, 7.6)	(0.54, 0.68, 0.82)
	E513	(8.5,  9.5, 10.0)	(0.62, 0.74, 0.86)
E52	E521	(4.9, 6.2, 7.4)	(0.69, 0.80, 0.90)	(4.48 5.75 6.93)
	E522	(2.0, 3.2, 4.5)	(0.71, 0.83, 0.92)
	E523	(7.5, 8.6, 9.4)	(0.49, 0.62, 0.74)
E53	E531	(4.9, 6.5, 8.0)	(0.40, 0.56, 0.72)	(4.33, 6.01, 7.67)
	E532	(4.2, 5.9, 7.6)	(0.52, 0.65, 0.78)
	E533	(3.8, 5.6, 7.4)	(0.3, 0.5, 0.7)
E54	E541	(5.7, 7.1, 8.4)	(0.36, 0.53, 0.70)	(4.38, 6.01, 7.57)
	E542	(4.2, 5.9, 7.6)	(0.62, 0.74, 0.86)
	E543	(3.0, 4.7, 6.4)	(0.26, 0.38, 0.52)

In order to calculate the rating of each enabler, we firstly aggregate the five experts’ weights and ratings, by using median operation [25], and then we carry out the same calculation as that of the criteria rating (Table 6). An example of the rating of the enabler E₁ is shown below.

Example: Rating of the enabler

E₁=

= [(4.17, 5.65, 7.11) Ä (0.5, 0.65, 0.8) Å (3.52, 4.88, 6.28) Ä (0.5, 0.65, 0.8) Å (4.49, 5.99, 7.47) Ä (0.5, 0.65, 0.8)] / [(0.5, 0.65, 0.8) Å (0.5, 0.65, 0.8) Å (0.5, 0.65, 0.8)] = (5.14, 6.55, 7.86)

Table 6: Fuzzy index of agile enabler rating

Agile enablers	Agile criteria	Criteria rating	Fuzzy importance weight of the agile criteria	Enabler rating	Fuzzy importance weight of the agile enablers
E1	E11	(4.17, 5.65, 7.11)	(0.5, 0.65, 0.8)	(5.14, 6.55, 7.86)	(0.5, 0.65, 0.8)
	E12	(3.52, 4.88, 6.28)	(0.5, 0.65, 0.8)
	E13	(4.49, 5.99, 7.47)	(0.5, 0.65, 0.8)
E2	E21	(3.66, 4.93, 6.23)	(0.5, 0.65, 0.8)	(3.67, 5.04, 6.44)	(0.5, 0.65, 0.8)
	E22	(4.45, 5.77, 7.04)	(0.5, 0.65, 0.8)
	E23	(3.56, 5.05, 6.55)	(0.7, 0.8, 0.9)
	E24	(3.4, 5.0, 6.6)	(0.5, 0.65, 0.8)
	E25	(3.68, 4.89, 6.18)	(0.5, 0.65, 0.8)
	E26	(3.29, 4.63, 6.03)	(0.5, 0.65, 0.8)
E3	E31	(3.08, 4.57, 6.06)	(0.7, 0.8, 0.9)	(4.36, 5.79, 7.16)	(0.7, 0.8, 0.9)
	E32	(5.09, 6.55, 7.92)	(0.7, 0.8, 0.9)
	E33	(4.69, 5.97, 7.21)	(0.7, 0.8, 0.9)
	E34	(4.21, 5.79, 7.32)	(0.5, 0.65, 0.8)
	E35	(4.20, 5.86, 7.45)	(0.5, 0.65, 0.8)
	E36	(5.01, 6.04, 7.03)	(0.5, 0.65, 0.8)
E4	E41	(3.81, 5.30, 6.74)	(0.5, 0.65, 0.8)	(4.88, 6.31, 7.64)	(0.5, 0.65, 0.8)
	E42	(6.21, 7.52, 8.67)	(0.5, 0.65, 0.8)
	E43	(5.84, 7.14, 8.27)	(0.5, 0.65, 0.8)
	E44	(5.14, 6.53, 7.82)	(0.7, 0.8, 0.9)
	E45	(3.34, 4.76, 6.23)	(0.7, 0.8, 0.9)
	E46	(5.28, 6.76, 8.16)	(0.5, 0.65, 0.8)
	E47	(5.01, 6.42, 7.74)	(0.7, 0.8, 0.9)
E5	E51	(6.16, 7.34, 8.37)	(0.5, 0.65, 0.8)	(4.90, 6.28, 7.61)	(0.5, 0.65, 0.8)
	E52	(4.48, 5.75, 6.93)	(0.7 ,0.8, 0.9)
	E53	(4.33, 6.01, 7.67)	(0.3, 0.5, 0.7)
	E54	(4.38, 6.01, 7.57)	(0.3, 0.5, 0.7)

       Step 4: Calculation of the FAI of HealthOrg: We carry out the same calculation as that of the enabler rating [32].

FAI =

= [(5.14, 6.55, 7.86) Ä (0.5, 0.65, 0.8) Å (3.67, 5.04, 6.44) Ä (0.5, 0.65, 0.8) Å (4.36, 5.79, 7.16) Ä (0.7, 0.8, 0.9) Å (4.88, 6.31, 7.64) Ä (0.5, 0.65, 0.8) Å (4.90, 6.28, 7.61) Ä (0.5, 0.65, 0.8)] / [(0.5, 0.65, 0.8) Å (0.5, 0.65, 0.8) Å  (0.7, 0.8, 0.9) Å (0.5, 0.65, 0.8) Å (0.5, 0.65, 0.8)] = (4.57, 5.98, 7.34)

The overall agility of HealthOrg is (4.57, 5.98, 7.34).

·         Step 5: Matching the FAI with the appropriate linguistic level [32]: After determining the FAI of the organization, we converted it into linguistic terms. To do this, we used the Euclidean distance method in which we seek to obtain the minimum distance between FAI and the linguistic level (Table 8). Table 7 presents the linguistic terms of different agility levels and their fuzzy intervals [5].

Table 7: Fuzzy values of agility levels (Adapted from [25])

Level of agility	Fuzzy intervals
Slowly Agile	(0, 1.5, 3)
Fairly Agile	(1.5, 3, 4.5)
Agile	(3.5 5 6.5)
Very Agile	(5.5, 7, 8.5)
Extremely Agile	(7, 8.5, 10)

Table 8: Agility level of HealthOrg

FAI for HealthOrg	(4.57, 5.98, 7.34)
D (FAI, Slowly Agile)	{(4.57‐0)2 + (5.98‐1.5)2 + (7.34‐3)2}1/2 = 7.78
D (FAI, Fairly Agile)	{(4.57‐1.5)2 + (5.98‐3)2 + (7.34‐4.5)2}1/2 = 5.13
D (FAI, Agile)	{(4.57‐3.5)2 + (5.98‐5.0)2 + (7.34‐6.5)2}1/2 = 1.67
D (FAI, Very Agile)	{(4.57‐5.5)2 + (5.98‐7)2 + (7.34‐8.5)2}1/2 = 1.80
D (FAI, Extremely Agile)	{(4.57‐7)2 + (5.98‐8.5)2 + (7.34‐10)2}1/2 = 4.40

The minimum distance between FAI and the level of agility is that obtained with the “Agile” level. Then, HealthOrg is considered as an agile enterprise.

·         Step 6: Fuzzy performance importance index (FPII) calculation: Although HealthOrg is agile; some attributes weakened its agility during COVID-19 era. In order to identify them, we calculate FPII and the ranking score for each agile attribute (Table 9) [5]. An example of it for E111 is calculated as:

FPII₁₁₁ = [(1, 1, 1) – Average fuzzy weight of E₁₁₁] Ä Average fuzzy performance rating of

E₁₁₁= [(1, 1, 1) – (0.54 0.68 0.82)] Ä (6.1 7.4 8.6) = (2.81, 2.37, 1.55)

Ranking score of E₁₁₁ = (2.81 + 4 × 2.37 + 1.55) / 6 = 2.31

Table 9: FPII and ranking score of agile attributes

Agile Attributes	Average fuzzy weight	Fuzzy performance average rating	FPII	Ranking score
E111	(0.54, 0.68, 0.82)	(6.1, 7.4, 8.6)	(2.81, 2.37, 1.55)	2.31
E112	(0.54, 0.68, 0.82)	(3.4, 5.0, 6.6)	(1.56, 1.60, 1.19)	1.52
E113	(0.58, 0.71, 0.84)	(2.4, 3.8, 5.3)	(1.01 1.10, 0.85)	1.04
E114	(0.54, 0.68, 0.82)	(4.9, 6.5, 8.0)	(2.25, 2.08, 1.44)	2.00
E121	(0.46, 0.62, 0.78)	(5.0, 6.5, 8.0)	(2.70 2.47 1.76)	2.39
E122	(0.54, 0.68, 0.82)	(3.0, 4.7, 6.4)	(1.38, 1.50, 1.15)	1.42
E123	(0.50, 0.65, 0.80)	(1.4, 2.6, 4.0)	(0.70, 0.91, 0.80)	0.86
E124	(0.58, 0.71, 0.84)	(1.4, 2.6, 4.0)	(0.59, 0.75, 0.64)	0.70
E125	(0.58, 0.71, 0.84)	(6.8, 8.0, 9.0)	(2.86, 2.32, 1.44)	2.26
E131	(0.76, 0.86, 0.94)	(5.0, 6.5, 8.0)	(1.20, 0.91, 0.48)	0.89
E132	(0.58, 0.71, 0.84)	(6.7, 8.0, 9.0)	(2.81, 2.32, 1.44)	2.25
E133	(0.62, 0.74, 0.86)	(5.4, 6.8, 8.2)	(2.05, 1.77, 1.15)	1.71
E134	(0.42, 0.59, 0.76)	(3.8, 5.6, 7.4)	(2.20, 2.30, 1.78)	2.20
E135	(0.46, 0.62, 0.78)	(5.0, 6.5, 8.0)	(2.70, 2.47, 1.76)	2.39
E136	(0.79, 0.89, 0.96)	(2.6, 4.1, 5.6)	(0.55, 0.45, 0.22)	0.43
E137	(0.54, 0.68, 0.82)	(3.2, 4.7, 6.3)	(1.47, 1.50, 1.13)	1.43
E211	(0.66, 0.77, 0.88)	(4.6, 6.2, 7.8)	(1.56, 1.43, 0.94)	1.37
E212	(0.42, 0.59, 0.76)	(1.8, 2.9, 4.2)	(1.04, 1.19, 1.01)	1.13
E213	(0.50, 0.65, 0.80	(2.0, 3.5, 5.0)	(1.00, 1.22, 1.00)	1.15
E214	(0.76, 0.86, 0.94)	(6.4, 7.7, 8.8)	(1.54, 1.08, 0.53)	1.06
E215	(0.58, 0.71, 0.84)	(1.8, 3.2, 4.7)	(0.76, 0.93, 0.75)	0.87
E221	(0.24, 0.41, 0.58)	(5.3, 6.8, 8.2)	(4.03, 4.01, 3.44)	3.92
E222	(0.54, 0.68, 0.82)	(3.9, 5.0, 6.1)	(1.79, 1.60, 1.10)	1.55
E223	(0.50, 0.65, 0.80)	(3.1, 4.4, 5.7)	(1.55, 1.54, 1.14)	1.47
E224	(0.62, 0.74, 0.86)	(5.7, 7.1, 8.4)	(2.17, 1.85, 1.18)	1.79
E231	(0.76, 0.86, 0.94)	(4.2, 5.9, 7.6)	(1.01, 0.83, 0.46)	0.80
E232	(0.54, 0.68, 0.82)	(2.2, 3.5, 4.9)	(1.01, 1.12, 0.88)	1.06
E233	(0.7, 0.8, 0.9)	(2.4, 3.8, 5.3)	(0.72, 0.76, 0.53)	0.71
E234	(0.50, 0.65, 0.80)	(5.7, 7.1, 8.4)	(2.85, 2.48, 1.68)	2.41
E241	(0.50, 0.65, 0.80)	(3.4, 5.0, 6.6)	(1.70, 1.75, 1.32)	1.67
E251	(0.50, 0.65, 0.80)	(5.8, 7.1, 8.4)	(2.90, 2.48, 1.68)	2.42
E252	(0.50, 0.65, 0.80)	(3.8, 5.3, 6.8)	(1.90, 1.85, 1.36)	1.78
E253	(0.42, 0.59, 0.76)	(1.0, 2.0, 3.2)	(0.58, 0.82, 0.77)	0.77
E261	(0.54, 0.68, 0.82)	(5.7, 7.1, 8.4)	(2.62, 2.27, 1.51)	2.20
E262	(0.58, 0.71, 0.84)	(2.6, 3.8, 5.2)	(1.09, 1.10, 0.83)	1.05
E263	(0.50, 0.65, 0.80)	(1.6, 2.9, 4.3)	(0.80, 1.01, 0.86)	0.95
E264	(0.54, 0.68, 0.82)	(3.2, 4.7, 6.2)	(1.47, 1.50, 1.12)	1.43
E311	(0.58, 0.71, 0.84)	(2.4, 3.8, 5.3)	(1.01, 1.10, 0.85)	1.04
E312	(0.7, 0.8, 0.9)	(1.6, 2.9, 4.4)	(0.48, 0.58, 0.44)	0.54
E313	(0.79, 0.89, 0.96)	(2.8, 4.4, 6.0)	(0.59, 0.48, 0.24)	0.46
E314	(0.50, 0.65, 0.80)	(6.4, 7.7, 8.8)	(3.20, 2.69, 1.76)	2.62
E321	(0.7, 0.8, 0.9)	(6.0, 7.4, 8.6)	(1.80, 1.48, 0.86)	1.43
E322	(0.58, 0.71, 0.84)	(4.0, 5.6, 7.2)	(1.68, 1.62, 1.15)	1.55
E331	(0.58, 0.71, 0.84)	(5.7, 7.1, 8.4)	(2.39, 2.06, 1.34)	1.99
E332	(0.7, 0.8, 0.9)	(4.5, 6.2, 7.8)	(1.35, 1.24, 0.78)	1.18
E333	(0.38, 0.56, 0.74)	(2.2, 3.5, 5.0)	(1.36, 1.54, 1.30)	1.47
E334	(0.58, 0.71, 0.84)	(2.2, 3.5, 4.9)	(0.92, 1.01, 0.78)	0.96
E335	(0.62, 0.74, 0.86)	(7.8, 8.9, 9.6)	(2.96, 2.31, 1.34)	2.26
E341	(0.50, 0.65, 0.80)	(2.8, 4.4, 6.0)	(1.40, 1.54, 1.20)	1.46
E342	(0.50, 0.65, 0.80)	(3.6, 5.3, 7.0)	(1.80, 1.85, 1.40)	1.77
E343	(0.54, 0.68, 0.82)	(5.3, 6.8, 8.2)	(2.44, 2.18, 1.48	2.11
E344	(0.62, 0.74, 0.86)	(4.9, 6.5, 8.0)	(1.86, 1.69, 1.12)	1.62
E351	(0.58, 0.71, 0.84)	(2.6, 4.4, 6.2)	(1.09, 1.28, 0.99)	1.20
E352	(0.42, 0.59, 0.76)	(4.9, 6.5, 8.0)	(2.84, 2.66, 1.92)	2.57
E353	(0.58, 0.71, 0.84)	(5.3, 6.8, 8.2)	(2.23, 1.97, 1.31)	1.90
E361	(0.38, 0.56, 0.74)	(1.0, 2.0, 3.3)	(0.62, 0.88, 0.86)	0.83
E362	(0.54, 0.68, 0.82)	(8.2, 9.2, 9.8)	(3.77, 2.94, 1.76)	2.88
E363	(0.66, 0.77, 0.88)	(4.7, 6.2, 7.6)	(1.60, 1.43, 0.91)	1.37
E411	(0.42, 0.59, 0.76)	(6.4, 7.7, 8.8)	(3.71, 3.16, 2.11)	3.08
E412	(0.46, 0.62, 0.78)	(2.6, 4.1, 5.7)	(1.40, 1.56, 1.25)	1.48
E413	(0.42, 0.59, 0.76)	(4.9, 6.5, 8.0)	(2.84, 2.66, 1.92)	2.57
E414	(0.66, 0.77, 0.88)	(4.2, 5.9, 7.6)	(1.43, 1.36, 0.91)	1.30
E415	(0.58, 0.71, 0.84)	(3.9, 5.3, 6.6)	(1.64, 1.54, 1.06)	1.48
E416	(0.54, 0.68, 0.82)	(1.4, 2.6, 3.9)	(0.64, 0.83, 0.70)	0.78
E421	(0.73, 0.83, 0.92)	(6.4, 7.7, 8.8)	(1.73, 1.31, 0.70)	1.28
E422	(0.50, 0.65, 0.80)	(6.4, 7.7, 8.8)	(3.20, 2.69, 1.76)	2.62
E423	(0.46, 0.62, 0.78)	(5.7, 7.1, 8.4)	(3.08, 2.70, 1.85)	2.62
E431	(0.62, 0.74, 0.86)	(6.8, 8.0, 9.0)	(2.58, 2.08, 1.26)	2.03
E432	(0.16, 0.29, 0.43)	(7.2, 8.3, 9.2)	(6.05, 5.89, 5.24)	5.81
E433	(0.44, 0.59, 0.74)	(6.4, 7.7, 8.8)	(3.58, 3.16, 2.29)	3.08
E434	(0.57, 0.71, 0.84)	(4.0, 5.3, 6.6)	(1.72, 1.54, 1.06)	1.49
E441	(0.60, 0.74, 0.86)	(6.9, 8.0, 9.0)	(2.76, 2.08, 1.26)	2.06
E442	(0.58, 0.71, 0.84)	(4.9, 6.2, 7.4)	(2.06, 1.80, 1.18)	1.74
E443	(0.59, 0.71, 0.82)	(3.4, 5.0, 6.6)	(1.39, 1.45, 1.19)	1.40
E444	(0.72, 0.83, 0.92)	(5.3, 6.8, 8.2)	(1.48, 1.16, 0.66)	1.13
E451	(0.72, 0.83, 0.92)	(2.4, 3.8, 5.3)	(0.67, 0.65, 0.42)	0.61
E452	(0.79, 0.89, 0.96)	(2.2, 3.5, 5.0)	(0.46, 0.38, 0.20)	0.36
E453	(0.60, 0.74, 0.86)	(3.6, 5.0, 6.4)	(1.44, 1.30, 0.90)	1.26
E454	(0.68, 0.80, 0.90)	(2.8, 4.4, 6.0)	(0.90, 0.88, 0.60)	0.84
E455	(0.65, 0.77, 0.88)	(6.1, 7.4, 8.6)	(2.13, 1.70, 1.03)	1.66
E461	(0.38, 0.53, 0.68)	(3.8, 5.6, 7.4)	(2.36, 2.63, 2.37)	2.54
E462	(0.50, 0.65, 0.80)	(6.4, 7.7, 8.8)	(3.20, 2.69, 1.76)	2.62
E471	(0.66, 0.77, 0.88)	(5.0, 6.5, 8.0)	(1.70, 1.49, 0.96)	1.44
E472	(0.36, 0.50, 0.64)	(7.5, 8.6, 9.4)	(4.80, 4.30, 3.38)	4.23
E473	(0.62, 0.74, 0.86)	(5.3, 6.8, 8.2)	(2.01, 1.77, 1.15)	1.71
E474	(0.71, 0.83, 0.92)	(3.5, 4.7, 5.9)	(1.01, 0.80, 0.47)	0.78
E511	(0.34, 0.50, 0.66)	(3.4, 5.3, 7.2)	(2.24, 2.65, 2.45)	2.55
E512	(0.54, 0.68, 0.82)	(5.2, 6.5, 7.6)	(2.39, 2.08, 1.37)	2.01
E513	(0.62, 0.74, 0.86)	(8.5,  9.5, 10.0)	(3.23, 2.47, 1.40)	2.42
E521	(0.69, 0.80, 0.90)	(4.9, 6.2, 7.4)	(1.52, 1.24, 0.74)	1.20
E522	(0.71, 0.83, 0.92)	(2.0, 3.2, 4.5)	(0.58, 0.54, 0.36)	0.52
E523	(0.49, 0.62, 0.74)	(7.5, 8.6, 9.4)	(3.82, 3.27, 2.44)	3.22
E531	(0.40, 0.56, 0.72)	(4.9, 6.5, 8.0)	(2.94, 2.86, 2.24)	2.77
E532	(0.52, 0.65, 0.78)	(4.2, 5.9, 7.6)	(2.02, 2.06, 1.67)	1.99
E533	(0.3, 0.5, 0.7)	(3.8, 5.6, 7.4)	(2.66, 2.80, 2.22)	2.68
E541	(0.36, 0.53, 0.70)	(5.7, 7.1, 8.4)	(3.65, 3.34, 2.52)	3.25
E542	(0.62, 0.74, 0.86)	(4.2, 5.9, 7.6)	(1.60, 1.53, 1.06)	1.46
E543	(0.26, 0.38, 0.52)	(3.0, 4.7, 6.4)	(2.22, 2.91, 3.07)	2.82

Based on the five experts’ experience, scale 1.1 was considered as the threshold which distinguishes the weaker attributes than the other ones. Table 10 showed these attributes and some suggestions to improve them [5].

Table 10: Weaker agile attributes and improvement proposals

Weak agile attribute	References	Improvement proposals
·          Staff interchangeability ·          Multi-skilled and flexible staff ·          Implementation of job rotation system	[15, 33]	Prepare employees to participate in the implementation of job rotation system
·          Flexible employees to accept the adoption of new technologies ·          Multi-functional, developed and trained employees	[15, 29]	Develop a flexible working environment for employees
·          Decentralized decision-making, knowledge  and control ·          Knowledgeand skills management systems ·          Staff empowerment to resolve patient issues	[15, 29, 30, 31, 33]	Give authority to different level employees which contributes to improved their knowledge
·          Loyalty and commitment to a project or a group ·          Participative management style ·          Quick evaluation and implementation of employee suggestions ·          Involvement of suppliers and different agents in product/service development	[15, 29, 30]	Remove barriers to facilitate the participation of different employees and suppliers
·          Efficient information system and technology ·          Exploitation of information technology (IT) in supply chain management	[15, 27, 29, 30, 32, 33]	Link information systems to technology
·          Adopting supply chain management concepts to improve the efficiency of outsourcing ·          Simple process to implement ·          Intelligent Engineering Design Support System ·          Active policy to keep work areas clean and tidy ·          Execution of short range planning ·          Company’s procurement policy based on time schedule ·          Improved manufacturing technology ·          First-time correct design ·          Reduction of non value-adding costs		Use advanced technologies and production methods

5. Conclusion

This study evaluated organization agility of a public hospital in Morocco in times of COVID-19. The enablers influencing agility were studied, as were the agile criteria and attributes. After a literature review, an assessment model was presented and tested via the fuzzy logic approach. Empirical results showed that HealthOrg is agile. The COVID-19 outbreak has revealed how different enablers can influenced the hospital agility. It has also shown how some agile enablers need to be enhanced in order to increase the healthcare organization agility.

This article offers initial empirical exploration on how Moroccan healthcare organizations cope with the COVID-19 crisis. It allows identifying the required changes to improve the agility of the organization. There will be increasing improvement for hospitals in technology and human resources departments; COVID-19 has demonstrated their importance in making the healthcare organization extremely agile.

Despite the above benefits for using the assessment model, there is some limitation: this model does not take into account the different agile drivers and capacities which must be aligned with the agile enablers. Also, the organizational agility assessment has been done for a single healthcare organization; however future research should replicate the assessment model in others organizations, in public and private sector. Also, it is highly recommended to compare the results obtained in times of COVID-19 with those provided by previous studies. Moreover, further practical suggestions for healthcare sector through COVID 19 outbreaks should be provided.

Conflict of Interest

The authors declare no conflict of interest.

Acknowledgment

The authors acknowledge the financial support of the National Centre for Scientific and Technical Research (CNRST) under the Excellence Research Scholarships Program.

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