1. INTRODUCTION:

The 2025 Prayag Maha Kumbh Mela, held in Prayagraj, Uttar Pradesh, stands as a monumental testament to the scale of religious gatherings and the complex planning required to ensure their success. The event, rooted in centuries of Hindu tradition, occurs every 12 years and is considered the largest human congregation on Earth. This year's Kumbh Mela not only surpassed expectations in terms of attendance but also set new records in terms of infrastructure, security, international participation, and logistical coordination.

According to official estimates, by mid-February 2025, more than 500 million devotees had visited the holy site at Triveni Sangam, where the Ganga, Yamuna, and the mythical Saraswati rivers meet. This turnout marks the highest attendance in Kumbh Mela history, with February 14, 2025, alone witnessing a staggering 9.2 million people taking the sacred dip. These figures reflect the deep spiritual significance of the festival and its capacity to draw both national and international pilgrims in unparalleled numbers.

To manage such an influx, the Uttar Pradesh government executed an extensive preparation plan that included the deployment of 50,000 police personnel and 14,000 home guards across the Mela grounds. The use of technology played a critical role, with 2,750 AI-powered CCTV cameras strategically installed to monitor crowd movement, detect emergencies, and prevent untoward incidents. These measures underscore a shift towards more tech-enabled crowd control systems in India’s religious and public events.

A massive tent city was erected along the banks of the Sangam to house millions of visitors. This temporary settlement included approximately 150,000 tents and 145,000 restrooms, offering basic sanitation and shelter to the pilgrims. Additionally, 11 temporary hospitals staffed with doctors and nurses were established to provide emergency medical care, thereby ensuring a comprehensive health response mechanism in place.

The international dimension of the Maha Kumbh Mela has also expanded. Pilgrims from countries including the United States, United Kingdom, Australia, Canada, France, Germany, Russia, China, and Japan participated in the event. On February 1, 2025, a high-level diplomatic delegation comprising 118 diplomats from 77 countries, along with their spouses, visited the site. This diplomatic visit not only amplified India’s soft power globally but also underscored the spiritual and cultural importance of the Kumbh Mela on a world stage.

Despite all the efforts, the event was not without challenges. On January 29, 2025, a tragic stampede resulted in the loss of at least 30 lives and left 60 injured, prompting concerns over crowd management during peak hours. Later, on February 2, 2025, a fire caused by a gas cylinder explosion damaged 18 tents, although, fortunately, no casualties were reported. These incidents highlight the importance of emergency response preparedness and the need for constant vigilance during high-density events.

In the face of such challenges, the overall execution of the 2025 Maha Kumbh Mela is considered a success. From an event management perspective, the seamless integration of traditional practices with modern planning tools offers a template for organizing other mega-events in India and globally. The festival's planning and execution provide critical insights into the logistical, infrastructural, and human resource challenges associated with mass gatherings.

Furthermore, the event presents a valuable case study for researchers exploring the intersection of spirituality, tourism, public policy, urban planning, and emergency management. It reveals the socio-cultural depth and economic potential of spiritual tourism in India, reinforcing the country's identity as a global spiritual hub.

In the 2025 Prayag Maha Kumbh Mela was more than a spiritual congregation; it was a massive demonstration of India's capability to manage mega-events while preserving the essence of its religious traditions. The records broken, the infrastructure developed, and the lessons learned from this edition of the Kumbh Mela will serve as a guiding framework for future editions and other mass events around the world.

1.1 PROBLEM STATEMENT:

The Maha Kumbh is the world’s largest religious gathering, attracting millions of pilgrims. Despite substantial investments in infrastructure and management, limited empirical research evaluates how key factors like religious experience, infrastructure, and event organization influence pilgrim satisfaction and future intentions. Most existing studies are descriptive, lacking robust statistical validation. This study addresses the gap by using Structural Equation Modeling (SEM) to examine relationships among these variables. It aims to offer actionable insights for policymakers and organizers to improve pilgrim experiences and ensure efficient planning for future events. The research provides a data-driven framework for enhancing satisfaction and sustaining event success.

1.2 SIGNIFICANCE OF STUDY:

The significance of this study lies in its empirical assessment of factors influencing pilgrim satisfaction and behavioral intentions during the Maha Kumbh, a globally recognized religious event. By applying Structural Equation Modeling (SEM), the study offers a robust analysis of the impact of religious experience, infrastructure, and event management. The findings will guide policymakers, administrators, and event planners in designing better facilities, enhancing spiritual experiences, and improving overall management. This research also contributes to academic literature by filling the gap in evidence-based evaluation of large-scale religious events, ultimately supporting sustainable and satisfying pilgrimage experiences for future gatherings.

2. LITERATURE REVIEW:

Religious tourism has emerged as a prominent area of academic interest due to its cultural, spiritual, and economic significance. The Maha Kumbh Mela, considered one of the largest religious congregations in the world, attracts millions of pilgrims from India and abroad. Researchers have studied various aspects of such events, particularly focusing on factors contributing to pilgrim satisfaction and behavioral intentions. Several constructs such as religious experience, infrastructure, and event management have been consistently found to influence pilgrim perceptions and experiences.

Religious experience plays a central role in shaping the satisfaction levels of pilgrims. According to Sharma and Chowdhary (2015), spiritual enrichment and emotional fulfillment at religious sites directly influence visitor contentment. Similarly, Raj and Morpeth (2007) highlighted that the authenticity of religious rituals, spiritual atmosphere, and personal devotion significantly enhance satisfaction during religious pilgrimages. In the context of Maha Kumbh, Singh and Pandey (2020) found that factors like sacred bathing, spiritual discourses, and interaction with holy saints contribute to a deeply fulfilling religious experience, which positively impacts overall satisfaction.

Adequate infrastructure and facilities are essential for managing large gatherings such as the Maha Kumbh. According to Choi and Chu (2001), cleanliness, safety, transport, accommodation, and public amenities are core determinants of visitor satisfaction in mass religious tourism. Pyo, Uysal, and Chang (2002) emphasized that availability of clean drinking water, sanitation, medical services, and emergency management systems are vital in determining the quality of the pilgrim experience. In their study on the 2013 Maha Kumbh, Tiwari et al. (2015) noted that well-planned infrastructure led to better crowd control, health outcomes, and an enhanced sense of security, thus contributing significantly to pilgrim satisfaction.

Effective event management has been highlighted as a major predictor of satisfaction in large-scale religious events. Getz (2008) stressed that strategic planning, clear communication, crowd regulation, and volunteer coordination play a crucial role in event success. In the Indian context, Singh and Mishra (2017) argued that timely dissemination of information, real-time updates through mobile apps, and effective coordination with various stakeholders are essential for successful event execution. Their study further noted that during the Maha Kumbh, administrative transparency and responsiveness of the staff positively affected the perception of management quality, thereby increasing overall satisfaction.

Numerous studies have established a strong link between satisfaction and behavioral intentions in tourism. Zeithaml, Berry, and Parasuraman (1996) proposed that higher satisfaction results in positive word-of-mouth, repeat visits, and recommendations. Similarly, Yoon and Uysal (2005) found that satisfied visitors are more likely to revisit and encourage others to attend. In the specific case of the Maha Kumbh, Rai and Yadav (2021) showed that pilgrims with higher satisfaction levels expressed strong intentions to return in future melas and recommend the event to others. This suggests that maintaining high satisfaction levels is not only beneficial for pilgrim welfare but also for sustaining the event’s popularity and credibility.

Structural Equation Modeling (SEM) has increasingly been used to assess complex relationships between variables in religious tourism studies. According to Hair et al. (2010), SEM allows for simultaneous analysis of multiple relationships and provides robust insights into direct and indirect effects. In their SEM-based study of the Kumbh Mela, Sharma and Kumar (2019) identified religious experience, infrastructure, and event management as significant predictors of satisfaction, which in turn influenced behavioral intentions. Their model confirmed the mediating role of satisfaction between independent variables and future behavioral responses.

2.1 Gaps in Literature

While existing literature has examined various individual components of religious tourism, there is a lack of comprehensive SEM-based studies that integrate all key factors—religious experience, infrastructure, and event management—within a unified framework specific to the Maha Kumbh. Most past studies are either descriptive or limited to qualitative observations. Additionally, fewer studies consider behavioral intentions as an outcome variable linked to satisfaction through quantitative techniques.

The reviewed literature indicates strong theoretical support for analyzing the Maha Kumbh experience using constructs such as religious experience, infrastructure, event management, satisfaction, and behavioral intentions. The application of SEM provides a robust methodological foundation for testing the interrelationships between these variables. This study builds on the existing research and contributes a contextualized, data-driven analysis of pilgrim behavior and satisfaction during the Maha Kumbh.

2.2 RESEARCH OBJECTIVES

1. To examine the impact of religious experience on visitor satisfaction during the Mahakumbh Mela.

2. To analyze how infrastructure and facilities influence visitor satisfaction at large-scale religious events.

3. To evaluate the role of event management in shaping visitor satisfaction during the Mahakumbh.

4. To investigate the effect of visitor satisfaction on behavioral intentions, such as revisiting and recommending the event to others.

2.3 Hypotheses:

H₀₁: Religious experience positively impacts satisfaction.

H₀₂: Infrastructure and facilities positively impact satisfaction.

H₀₃: Event management positively impacts satisfaction.

H₀₄: Satisfaction positively impacts behavioral intentions.

3. RESEARCH METHODOLOGY:

3.1 Research Design:

This study employs a quantitative research design using the Structural Equation Modeling (SEM) approach to analyze the causal relationships among various latent constructs, namely Religious Experience, Infrastructure, Event Management, Satisfaction, and Behavioral Intentions. The research is descriptive and causal in nature, aiming to explain the impact of experiential and service-related factors on participants' satisfaction and behavioral intentions during the Mahakumbh event.

3.2 Population and Sample:

The target population includes individuals who attended the Mahakumbh religious festival in Prayagraj, Uttar Pradesh, India. A probability sampling method was adopted to ensure that only actual participants were included. A total of 100 valid responses were collected, which is considered appropriate for SEM analysis.

3.3 Data Collection Method:

Primary data was collected using a structured questionnaire developed based a five-point Likert scale. The survey consisted of two sections:

· Demographic information (e.g., age, gender, frequency of visit).

· Measurement items related to the five latent variables:

· Religious Experience (RE1–RE3),

· Infrastructure (IF1–IF3),

· Event Management (EM1–EM3),

· Satisfaction (SAT1–SAT3), and

· Behavioral Intentions (BI1–BI3).

All items were measured using a five-point Likert scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree).

3.4 Data Analysis Tools and Techniques:

Data were analyzed using SmartPLS 4 and SPSS software. The analysis involved:

· Descriptive statistics for demographic profiling.

· Measurement Model Evaluation to assess reliability (Cronbach’s Alpha, Composite Reliability) and validity (Average Variance Extracted – AVE, Factor Loadings).

· Structural Model Evaluation for hypothesis testing through path coefficients (β), t-values, and p-values.

· Model fit indices such as SRMR (Standardized Root Mean Square Residual) were examined to assess the overall model adequacy.

3.5 Reliability and Validity:

The construct reliability was ensured with all Cronbach’s Alpha and Composite Reliability values exceeding the recommended threshold of 0.70. Convergent validity was confirmed through factor loadings ≥ 0.70 and AVE ≥ 0.50. Discriminant validity was also assessed using the Fornell-Larcker criterion.

4. DATA ANALYSIS:

Table-1 Demographic Profile

Variable	Category	Frequency	Percentage (%)
Gender	Male	58	58%
Gender	Female	42	42%
Age Group	Below 25 years	15	15%
	25–34 years	28	28%
	35–44 years	30	30%
	45–54 years	17	17%
	Above 55 years	10	10%
Frequency of Visit	First Time	87	87%
	Occasionally (2–3 times)	9	9%
	Regular (Every event)	4	4%

Gender

Age group

Frequency of visit

The demographic profile of the respondents (N = 100) reveals that 58% were male and 42% were female. In terms of age distribution, 15% were below 25 years, 28% were between 25–34 years, and 30% were in the 35–44 years range. Respondents aged 45–54 accounted for 17%, while those above 55 made up 10% of the sample. A significant majority of participants (87%) reported attending the Mahakumbh for the first time. Occasional visitors (2–3 times) represented 9%, and only 4% were regular attendees. These figures, converted into decimals, reflect proportions of 0.58 (male), 0.42 (female), and 0.87 (first-time visitors). The data supports that Mahakumbh draws a large number of first-time participants. This trend highlights the event’s broad appeal and growing interest among new attendees. The demographic diversity ensures a comprehensive understanding of visitor behavior and satisfaction.

Table-2 Loading Values

Loading values ≥ 0.70 are considered strong.
Latent Variable	Indicator	Factor Loading
Religious Experience	RE1	0.81
	RE2	0.77
	RE3	0.74
Infrastructure	IF1	0.79
	IF2	0.83
	IF3	0.75
Event Management	EM1	0.82
	EM2	0.78
	EM3	0.8
Satisfaction	SAT1	0.85
	SAT2	0.81
	SAT3	0.77
Behavioral Intentions	BI1	0.84
	BI2	0.8
	BI3	0.79

In Structural Equation Modeling (SEM), factor loadings represent the strength of the relationship between observed variables (indicators) and their underlying latent constructs. A factor loading value of 0.70 or higher is generally considered strong, indicating that the observed variable reliably measures the latent construct. In this study, all the factor loadings for the five latent variables—Religious Experience, Infrastructure, Event Management, Satisfaction, and Behavioral Intentions—exceeded the 0.70 benchmark, demonstrating robust construct reliability and convergent validity.

The construct Religious Experience was well-represented by its indicators RE1 (0.81), RE2 (0.77), and RE3 (0.74). Similarly, Infrastructure showed strong loadings with IF1 (0.79), IF2 (0.83), and IF3 (0.75), confirming the indicators’ reliability. The indicators for Event Management, namely EM1 (0.82), EM2 (0.78), and EM3 (0.80), also loaded highly on the construct. Satisfaction was strongly indicated by SAT1 (0.85), SAT2 (0.81), and SAT3 (0.77), while Behavioral Intentions had equally strong representation through BI1 (0.84), BI2 (0.80), and BI3 (0.79).

These consistently high factor loadings support the unidimensionality of each construct and confirm that the indicators effectively measure their respective latent variables. The strength and consistency of these loadings enhance the model's overall reliability, validity, and fit, providing a solid foundation for further path analysis and hypothesis testing.

The Structural Equation Model (SEM) path analysis demonstrates significant relationships among key constructs affecting satisfaction and behavioral intentions in the context of a religious or cultural event like Mahakumbh. The findings reveal that Religious Experience has a moderate positive effect on Satisfaction (β = 0.40, t = 4.21, p = 0.000), indicating that meaningful spiritual experiences contribute significantly to visitors’ overall satisfaction. Similarly, Infrastructure shows a positive and significant impact on satisfaction (β = 0.35, t = 3.74, p = 0.000), emphasizing the role of physical facilities, accessibility, and amenities in enhancing the experience. Event Management also plays a crucial role (β = 0.38, t = 3.89, p = 0.001), suggesting that efficient coordination, safety, and logistical arrangements are vital for ensuring visitor satisfaction.

Fig. 1 Structural Equation Model (SEM) – Path Analysis Diagram

Table-3 Structural Equation Model (SEM) – Path Analysis

Path	Path Coefficient (β)	t-Value	p-Value	Significance (α = 0.05)
Religious Experience → Satisfaction	0.4	4.21	0.000	Significant
Infrastructure → Satisfaction	0.35	3.74	0.000	Significant
Event Management → Satisfaction	0.38	3.89	0.001	Significant
Satisfaction → Behavioral Intentions	0.57	5.60	0.000	Significant

Furthermore, the most substantial relationship is observed between Satisfaction and Behavioral Intentions (β = 0.57, t = 5.60, p = 0.000), implying that higher satisfaction significantly increases the likelihood of future participation and positive word-of-mouth recommendations. All relationships are statistically significant at the 0.05 level, thus supporting the hypothesized model. This analysis underscores the importance of enhancing religious engagement, infrastructure quality, and event planning to boost satisfaction, which in turn drives favorable behavioral outcomes among attendees.

To evaluate the adequacy and reliability of the proposed Structural Equation Model (SEM), several widely accepted model fit indices were assessed. The Chi-square to degrees of freedom ratio (χ²/df) was found to be 2.13, which is well below the threshold of 3, indicating an overall good model fit.

Table-4 Model Summary

Fit Index	Threshold Criteria	Obtained Value	Model Fit Status
Chi-square (χ²/df)	≤ 3	2.13	Good Fit
CFI (Comparative Fit Index)	≥ 0.90	0.96	Good Fit
TLI (Tucker-Lewis Index)	≥ 0.90	0.95	Good Fit
RMSEA (Root Mean Square Error of Approximation)	≤ 0.08	0.055	Acceptable Fit
SRMR (Standardized Root Mean Square Residual)	≤ 0.08	0.047	Good Fit
AVE (Average Variance Extracted)	≥ 0.50 per construct	> 0.60	Good Convergent Validity

The Comparative Fit Index (CFI) achieved a value of 0.96, and the Tucker-Lewis Index (TLI) was 0.95—both exceeding the minimum criterion of 0.90. These values suggest that the model explains the observed data substantially better than a null model.

Furthermore, the Root Mean Square Error of Approximation (RMSEA) stood at 0.055, which is within the acceptable range (≤ 0.08), indicating an acceptable approximation error. Similarly, the Standardized Root Mean Square Residual (SRMR) value of 0.047 confirms a good residual fit, as it is well below the 0.08 benchmark. Lastly, the Average Variance Extracted (AVE) for all constructs was greater than 0.60, surpassing the 0.50 threshold, thereby confirming good convergent validity. Collectively, these indices demonstrate that the model is statistically robust and well-fitted, making it suitable for interpretation and further discussion.

5. DISCUSSION:

The findings of the study indicate that all hypothesized relationships in the structural model are statistically significant, suggesting a strong and positive connection between the observed constructs. The results reveal that Religious Experience has a significant positive impact on Satisfaction (β = 0.40, p < 0.001), aligning with the findings of Raj & Griffin (2015), who emphasized the role of spiritual engagement and rituals in enhancing visitor satisfaction at religious tourism destinations. When pilgrims experience a deeper spiritual connection, it enriches their overall journey, creating lasting impressions and emotional fulfillment.

The positive relationship between Infrastructure and Satisfaction (β = 0.35, p < 0.001) supports previous research by Prayag et al. (2017), which found that cleanliness, transportation, sanitation, and safety facilities are essential in determining the satisfaction level of tourists, especially during large-scale events like Kumbh Melas. Poor infrastructure can not only reduce comfort but also result in stress and dissatisfaction. Hence, well-planned physical facilities play a pivotal role in shaping visitor perceptions.

Event Management was also found to significantly influence Satisfaction (β = 0.38, p = 0.001). This finding resonates with the work of Lee, Lee & Wicks (2004), who concluded that efficient coordination, security arrangements, and crowd control during large religious or cultural festivals are directly linked to the satisfaction of attendees. In contexts like Mahakumbh, where managing millions of people is a challenge, seamless event execution builds trust and confidence among participants.

The strongest relationship in the model was between Satisfaction and Behavioral Intentions (β = 0.57, p < 0.001), indicating that a highly satisfied attendee is more likely to revisit and recommend the event to others. This result is consistent with Yoon & Uysal (2005), who highlighted that satisfaction is a key predictor of tourist loyalty and intention to revisit. In religious tourism, positive word-of-mouth plays a critical role in attracting future participants.

Overall, this model confirms that improving religious experience, infrastructure, and event management directly boosts visitor satisfaction, which in turn leads to stronger behavioral intentions. These findings offer practical implications for event organizers, government authorities, and religious tourism planners to focus on holistic service delivery for sustainable and repeat attendance.

6. CONCLUSION:

This study provides valuable insights into the factors influencing visitor satisfaction and behavioral intentions during large-scale religious events such as the Mahakumbh. The Structural Equation Model (SEM) analysis confirms that religious experience, infrastructure, and event management significantly contribute to overall satisfaction, which in turn has a strong positive impact on behavioral intentions like willingness to revisit or recommend the event to others.

The strongest predictor of behavioral outcomes was satisfaction, highlighting the central role it plays in shaping attendees' future decisions. Religious engagement, supported by well-planned infrastructure and efficient event management, collectively enhances the experience, making it memorable and spiritually fulfilling.

These findings not only validate the proposed hypotheses but also offer practical implications for stakeholders involved in planning and executing religious tourism events. Emphasizing emotional, spiritual, and logistical aspects can lead to improved visitor experiences and foster long-term loyalty. Future research can expand on this model by including variables such as cultural identity, safety perception, and environmental sustainability to offer a broader understanding of religious tourism dynamics.

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Received on 21.05.2025 Revised on 25.06.2025

Accepted on 26.07.2025 Published on 07.11.2025

Available online from November 17, 2025

Asian Journal of Management. 2025;16(4):299-305.

DOI: 10.52711/2321-5763.2025.00045

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Creative Commons License.