The retail sector in India has witnessed significant transformations with the emergence of organized shopping malls, offering consumers a blend of shopping, entertainment, and leisure under one roof. In tier-II cities like Nashik, the rapid growth of shopping malls has led to changes in consumer behavior and shopping patterns. With the rising disposable incomes, exposure to global retail formats, and evolving lifestyles, consumer preferences have shifted from traditional marketplaces to modern retail spaces. Understanding these behavioral patterns becomes crucial for mall developers, retailers, and marketers to strategize their offerings effectively.

This study aims to analyze the factors influencing consumer behavior in shopping malls across the Nashik region. The focus is to explore consumer motivations, preferences, and satisfaction levels by assessing key factors such as product variety, ambience, accessibility, convenience, and family-oriented experiences. Additionally, the study investigates how promotional offers and discounts shape consumer buying decisions, thereby helping retailers frame effective promotional strategies.

In today's digital age, technological advancements such as digital payments, self-service kiosks, and app-based engagement have revolutionized the shopping experience. To capture this aspect, the Technology Adoption Model (TAM) is applied to evaluate the impact of technology and digital payment systems on consumer behavior. Further, the study employs Parasuraman's Service Quality Dimensions (SERVQUAL) to examine the influence of service quality on consumer satisfaction and behavior.

By measuring consumer satisfaction, the research seeks to offer insights into the effectiveness of mall management practices in Nashik. The outcomes of this study will contribute valuable inputs for mall developers, retail managers, and marketers to enhance customer engagement, improve service delivery, and design customer-centric strategies. Overall, this research bridges the gap in understanding consumer behavior within the context of organized retail spaces in emerging urban regions like Nashik.

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RESEARCH OBJECTIVES:

1. To analyze the key factors influencing consumer preferences and motivations for shopping in malls across the Nashik region.
2. To examine the influence of service quality of shopping malls on consumer behavior by applying Parshuraman's Service Quality Dimensions.
3. To measure the overall consumer satisfaction with shopping malls across the Nashik Region.

RESEARCH HYPOTHESIS:

H1: Key factors such as product variety, ambience, convenience, and accessibility significantly influence consumer preferences and motivations for shopping in malls across the Nashik region.

H2: Service quality dimensions (Tangibility, Reliability, Responsiveness, Assurance, and Empathy) have a significant influence on consumer behavior in shopping malls across the Nashik region.

H3: Consumers are significantly satisfied with shopping malls across the Nashik region. 

• Type of Research: Descriptive Research.
• Sample size: 415 Customers from 55 Shopping Malls Across the Nasik Region (Shopping Malls at Nashik, Ahilya Nagar, Dhule, Jalgaon, Nandurbar
• Sampling Technique: Stratified Random Sampling
• Methodology: Primary data is collected through a structured questionnaire for Shopping Mall Customers across the Nasik Region. Secondary data is also collected through government circulars, policies, reports, news articles, Research Articles, theses, working Papers, etc.
• Statistical Test: ANOVA, Factor Analysis, Chi Square, Correlation, Linear Regression Regression applied through SPSS 25 software

DATA ANALYSIS AND INTERPRETATION:

DEMOGRAPHIC ANALYSIS:

TABLE 1: AGE OF RESPONDENTS

(Source: Researcher’s Analysis on SPSS 25)

TABLE 2: GENDER OF RESPONDENTS

(Source: Researcher’s Analysis on SPSS 25)

TABLE 3: EDUCATION LEVEL OF RESPONDENTS

(Source: Researcher’s Analysis on SPSS 25)

TABLE 4: EMPLOYMENT STATUS OF RESPONDENTS

(Source: Researcher’s Analysis on SPSS 25)

TABLE 5: MONTHLY HOUSEHOLD INCOME

(Source: Researcher’s Analysis on SPSS 25)

TABLE 6: MONTHLY SPENDING ON GLOSSARIES AND OTHER ITEMS AVAILABLE IN SHOPPING MALLS

(Source: Researcher’s Analysis on SPSS 25)

TABLE 7: PRIMARY REASON FOR VISITING SHOPPING MALLS

(Source: Researcher’s Analysis on SPSS 25)

TABLE 8: USUALLY VISIT THE MALL WITH

(Source: Researcher’s Analysis on SPSS 25)

TABLE 9: USUALLY TRAVEL TO SHOPPING MALLS

(Source: Researcher’s Analysis on SPSS 25)

HYPOTHESIS TESTING:

H1: THERE IS A SIGNIFICANT RELATIONSHIP BETWEEN KEY FACTORS INFLUENCING CONSUMER PREFERENCES AND MOTIVATIONS FOR SHOPPING IN MALLS ACROSS THE NASHIK REGION.

TABLE 10: DATA SUMMARY TO ANALYZE THE KEY FACTORS INFLUENCING CONSUMER PREFERENCES AND MOTIVATIONS FOR SHOPPING IN MALLS ACROSS THE NASHIK REGION.

(Source: Researcher’s Analysis on SPSS 25)

FACTOR ANALYSIS: TEST STATISTICS

TABLE 11 FACTOR ANALYSIS RESULTS

(Source: Researcher’s Analysis on SPSS 25)

TABLE 12 ROTATED COMPONENT MATRIX (VARIMAX)

(Source: Researcher’s Analysis on SPSS 25)

TABLE 13 TOTAL VARIANCE EXPLAINED

(Source: Researcher’s Analysis on SPSS 25)

TABLE 14 COMMUNALITIES

INTERPRETATION

• Interpretation: All extracted communalities > 0.60, indicating each variable is well-explained by the extracted factors.
• The KMO value of 0.731 and significant Bartlett’s test (p < 0.001) confirm the data is suitable for factor analysis. The communalities show all 7 items are well-explained by the factor solution (>0.60).
• Two principal components explain approximately 71% of the total variance, indicating a strong factor structure. The rotated component matrix reveals two clear groupings: one focused on experiential and brand-related preferences, and the other on convenience and affordability.

CONCLUSION

• All seven factors significantly contribute to consumer preferences and motivations for shopping in malls. key factors (convenience, ambiance, variety, affordability, brand presence, and socializing) significantly influence consumer preferences for shopping in malls in the Nashik region.
• This supports the hypothesis H1; hence, there is a significant relationship between key factors influencing consumer preferences and motivations for shopping in malls across the Nashik region.

H2: SERVICE QUALITY OF SHOPPING MALLS HAS A SIGNIFICANT IMPACT ON CONSUMER BEHAVIOR.

TABLE 15: DATA SUMMARY TO EXAMINE THE INFLUENCE OF SERVICE QUALITY OF SHOPPING MALLS ON CONSUMER BEHAVIOR BY APPLYING PARSHURAMAN'S SERVICE QUALITY DIMENSIONS.

MULTIPLE LINEAR REGRESSION: TEST STATISTICS

TABLE 16: H2 MODEL SUMMARY

TABLE 17 H2 ANOVA TEST STATISTICS

TABLE 18: INTERPRETATION OF REGRESSION ANALYSIS

Conclusion: The model explains a very high proportion of consumer behavior variance using SERVQUAL dimensions, indicating a strong model fit

ANOVA Interpretation:

• The F-value = 23.281 is statistically significant with p = 0.012 < 0.001, indicating the overall regression model is highly significant.
• This means that the combined SERVQUAL factors meaningfully explain the variance in consumer behavior.

INTERPRETATION AND CONCLUSION FOR H2:

Independent Variables (SERVQUAL Dimensions)

The model includes five key dimensions:

1. E1 – Physical appearance and cleanliness (Tangibles)
2. E2 – Reliable services (Reliability)
3. E3 – Quick response from mall staff (Responsiveness)
4. E4 – Assurance of product quality (Assurance)
5. E5 – Empathy and helpfulness of staff (Empathy)

These are the five standard SERVQUAL dimensions, and their inclusion validates the model's alignment with established service quality theory.

Conclusion for H4

• The regression results support Hypothesis H4. With an R² of 0.806 and a highly significant ANOVA result (p = 0.000), it is evident that:
• Service quality, as measured by the SERVQUAL dimensions, significantly and substantially impacts consumer behavior in shopping malls in the Nashik region.
• Specifically, tangibility, reliability, responsiveness, assurance, and empathy are crucial in shaping how consumers perceive and engage with shopping malls.

H3: CONSUMER SATISFACTION LEVELS SIGNIFICANTLY VARY ACROSS NASHIK REGION.

TABLE 19: DATA SUMMARY TO MEASURE THE OVERALL CONSUMER SATISFACTION WITH SHOPPING MALLS ACROSS NASHIK REGION.

TABLE 19: ANOVA TEST STATISTICS BASED ON DISTRICT-WISE CONSUMER SATISFACTION ANALYSIS ACROSS NASHIK REGION (DISTRICTS: NASHIK, AHILYA NAGAR, JALGAON, DHULE, NANDURBAR)

TABLE 20: SUMMARY OF ANOVA TEST STATISTICS BASED ON DIFFERENT INCOME GROUPS

INTERPRETATION:

Across all seven consumer satisfaction indicators (G1 to G7), the F-values range from approximately 2.8 to 4.6, and p-values are all below 0.05. This means:

• There is a statistically significant difference in consumer satisfaction levels across different districts in the Nashik Region.
• Particularly strong differences are seen in:
• Overall shopping satisfaction (F = 4.59, p = 0.003)
• Customer service expectations (F = 5.59, p = 0.001)
• Comfort level in malls (F = 4.78, p = 0.004)

ANOVA Based on Income Levels

Interpretation:

• The F-values across satisfaction items (G1–G7) are all above 3.1, with all p-values < 0.05, indicating:
• Consumer satisfaction varies significantly across income levels.
• Key differences are observed in:
• Overall satisfaction (F = 3.29, p = 0.005)
• Customer service (F = 3.66, p = 0.002)
• Navigation ease (F = 3.52, p = 0.012)

Final Conclusion for H3

Both ANOVA analyses demonstrate that, Consumer satisfaction is not uniform across the Nashik region. There are statistically significant differences based on both geographic location (district) and income level. This supports Hypothesis H3 and highlights the need for customized strategies in mall operations and marketing to cater to local demographics and economic segments.

SUMMARY OF HYPOTHESIS TESTING:

TABLE 21:  HYPOTHESIS TESTING SUMMARY

STATISTICAL FINDINGS:

H1: There is a significant relationship between key factors influencing consumer preferences and motivations for shopping in malls across the Nashik region.

To test this hypothesis, Factor Analysis (EFA) was conducted. The KMO value of 0.731 and Bartlett’s test (p < 0.001) confirmed the dataset’s suitability for factor analysis. The communalities for all seven variables exceeded 0.60, indicating strong shared variance. The Total Variance Explained was 71%, and the Rotated Component Matrix revealed two dominant factors: one capturing experiential and brand-driven preferences, and another representing convenience and affordability. These results support H1, confirming that consumer motivations are significantly shaped by multiple underlying dimensions in the shopping mall context.

H2: The Service quality of shopping malls has a significant impact on consumer behavior.

The hypothesis was tested using Multiple Linear Regression based on the five SERVQUAL dimensions. The regression model reported a very high R² value of 0.806 and an Adjusted R² of 0.771, with a statistically significant ANOVA result (p = 0.000). This suggests that 80.6% of the variation in consumer behavior can be attributed to service quality factors such as tangibles, reliability, responsiveness, assurance, and empathy. These findings strongly support H2, indicating that well-delivered service experiences significantly enhance mall-goers’ engagement and satisfaction.

H6: Consumer satisfaction levels significantly vary across the Nashik Region.

ANOVA was conducted across five districts: Nashik, Ahilya Nagar, Jalgaon, Dhule, and Nandurbar. The F-values across all seven satisfaction indicators ranged from approximately 2.8 to 4.6, with p-values consistently below 0.05. Specific variation was observed in overall satisfaction (G1), customer service (G4), and comfort (G6), affirming geographic variation in satisfaction levels.

These findings support H3, proving that consumer satisfaction in malls differs significantly by location within the Nashik region

MAJOR FINDING:

Consumers in the Nashik region exhibit multifaceted motivations for shopping in malls that go beyond simple purchase intentions. Factor analysis revealed that experiential elements like brand variety, ambience, and social interaction, along with practical considerations such as convenience, parking, and affordability, significantly influence their preferences. Two principal factors emerged: one centered on emotional and lifestyle-driven shopping behavior, and the other on utility-based drivers. This finding confirms that mall developers and marketers need to provide a comprehensive shopping experience that addresses both hedonic and utilitarian consumer motivations.

Service quality has a strong and measurable impact on consumer behavior in shopping malls. Using the SERVQUAL model, dimensions such as tangibles (cleanliness and appearance), reliability, responsiveness, assurance, and empathy were all found to be highly significant in shaping consumer perceptions. The regression model demonstrated that over 80% of consumer behavior variation could be attributed to service quality variables. This finding underscores the importance of training staff, maintaining hygiene standards, and delivering consistent service to influence mall goers’ shopping decisions positively.

Consumer satisfaction levels significantly differ across districts within the Nashik region. ANOVA analysis across Nashik, Ahilya Nagar, Jalgaon, Dhule, and Nandurbar revealed significant variation in key satisfaction indicators like overall shopping experience, customer service quality, and comfort levels. These geographic differences suggest that mall management practices and customer expectations may not be uniformly met across districts. Thus, mall operators must localize their offerings and service strategies according to regional consumer expectations and infrastructure capabilities.

RECOMMENDATIONS:

The research underscores that convenience, atmosphere, product diversity, and cost-effectiveness substantially affect consumer choices in shopping malls. Mall developers and managers should prioritise the creation of user-centric layouts that facilitate effortless navigation and accessibility. An appealing atmosphere featuring aesthetically pleasing decor, suitable lighting, and comfortable seating can elevate the overall shopping experience. Moreover, assembling a broad yet economical range of products across several categories is crucial to address the unique requirements of clients while ensuring value for money. These initiatives can together enhance patronage and promote return visits.

The characteristics of service quality, including reliability, staff empathy, responsiveness, & cleanliness, were identified as significant determinants of consumer satisfaction. Mall management should implement SERVQUAL-based training programs for workers to enhance customer-centric service behaviour and improve service quality. Upholding stringent cleanliness standards, particularly in communal spaces like food courts, is essential for improving the perception of quality and safety. Implementing real-time support for consumer systems such as information kiosks, mobile assistance applications, and feedback collection platforms will facilitate prompt resolution of client issues and enhance the shopping experience.

The present research indicated substantial disparities in consumer satisfaction among several districts of the Nashik region, underscoring the necessity of localised strategies. Mall operators ought to perform regular district-specific satisfaction audits to ascertain regional expectations and service deficiencies. Marketing campaigns, promotional methods, and service offerings should be tailored to align with local preferences and purchasing capacity. This focused strategy will foster enhanced customer interaction, boost regional competitiveness, and improve overall mall performance in the Nashik region.

This study comprehensively explored the multifaceted dimensions of consumer behavior in shopping malls across the Nashik region, focusing on preferences, promotional impacts, digital experiences, service quality, elderly consumer perceptions, regional satisfaction variations, and retention dynamics. The findings confirmed that key elements such as convenience, ambiance, affordability, and variety significantly shape consumer motivations. Promotional strategies—especially loyalty programs, discounts, and seasonal offers—have a pronounced effect, though their impact varies by gender and income levels. Furthermore, technological advancements and the ease of digital payments emerged as significant drivers of consumer behavior, emphasizing the growing importance of tech-enabled retail experiences. Service quality, based on SERVQUAL dimensions, strongly influenced satisfaction, while elderly shoppers expressed distinct and positive perceptions based on accessibility and staff support.

Despite achieving satisfactory levels of service and experience, the study found that, crucial insight malls need to go beyond transactional relationships and build emotional connections, trust, and personalized value to retain customers. Differences in satisfaction levels across Nashik's districts further highlighted the importance of region-specific marketing and operational strategies.

In light of these findings, the study recommends a series of targeted interventions, including digital integration, personalized marketing, district-wise service adaptations, and inclusive infrastructure enhancements. These measures not only align with the needs of different consumer segments but also future-proof shopping malls by cultivating stronger emotional loyalty and tech-responsiveness. Future research may explore the role of AI in personalization, sustainability practices in mall management, or the influence of post-pandemic consumer psychology on mall culture in Tier-II cities like Nashik. By implementing these strategies, mall operators and marketers can transform consumer behavior and position malls as vibrant, responsive, and emotionally connected spaces in India's evolving retail landscape.

1. Abdullah, P., and T. Sipos. Exploring Factors Influencing Consumer Preferences for Automated Driving Vehicles. 2024. Elsevier. <https://api.elsevier.com/content/article/PIIS2666691X24000083>.
2. Asmithaa, G., M. Chandrakumar, D. Murugananthi, G. Vanitha, and E. Parameswari. Consumer Awareness and Adoption of Multi‑Source Edible Oils: Key Influencing Factors and Barriers. 2025. Horizone Publishing. <https://horizonepublishing.com/journals/index.php/PST/article/download/6042/5511>.
3. Barchi, G., D. Moser, and R. Lollini. Renewable Malls: Transforming Shopping Centres into Flexible, Decarbonized Urban Energy Assets. 2018. Elsevier. <https://api.elsevier.com/content/article/PIIB9780081020746000334>.
4. Calvo‑Porral, C., and J.-P. Lévy‑Mangín. Pull Factors of the Shopping Malls: An Empirical Study. 2018. Emerald Insight. <https://www.emerald.com/insight/content/doi/10.1108/IJRDM-02-2017-0027/full/html>.
5. Chaudhary, P., and R. Thiebaut. Digital Transformation Strategies in Indian Supermarkets in Germany. 2025. IGI Global. <https://www.igi‑global.com/view.aspx?Id=371778>.
6. Chebat, J.-C., N. Haj‑Salem, and S. Oliveira. Why Shopping Pals Make Malls Different? Elsevier. <https://api.elsevier.com/content/article/PIIS0969698913001112>.
7. Chotipanich, S., and S. Issarasak. A Study of Facility Management Operation Strategy in Shopping Malls. 2017. Emerald Insight. <https://www.emerald.com/insight/content/doi/10.1108/PM-07-2015-0029/full/html>.
8. Demirkan, H., and J. Spohrer. Developing a Framework to Improve Virtual Shopping in Digital Malls with Intelligent Self‑Service Systems. 2014. Elsevier. <https://api.elsevier.com/content/article/PIIS0969698914000253>.
9. Dubihlela, D. Attributes of Shopping Mall Image, Customer Satisfaction, and Mall Patronage for Selected Shopping Malls in Southern Gauteng, South Africa. 2014. AMH International. <https://ojs.amhinternational.com/index.php/jebs/article/download/528/528>.
10. Eduful, A. K., and M. Eduful. Malls, Modernity, and Consumption: Shopping Malls as New Projectors of Modernity in Accra, Ghana. 2021. SAGE Journals. <https://journals.sagepub.com/doi/pdf/10.1177/14695405211033666>.
11. El‑Adly, M. I., and R. Eid. An Empirical Study of the Relationship Between Shopping Environment, Customer Perceived Value, Satisfaction, and Loyalty in the UAE Malls Context. 2016. Elsevier. <https://api.elsevier.com/content/article/PIIS0969698916300017>.
12. ELSamen, A. A., and R. I. Hiyasat. Beyond the Random Location of Shopping Malls: A GIS Perspective in Amman, Jordan. 2017. Elsevier. <https://api.elsevier.com/content/article/PIIS0969698915300631>.
13. Ferreira, D., and D. Paiva. The Death and Life of Shopping Malls: An Empirical Investigation on the Dead Malls in Greater Lisbon. 2017. Taylor & Francis Online. <https://www.tandfonline.com/doi/pdf/10.1080/09593969.2017.1309564>.
14. Han, H., N. Sahito, T. V. Nguyen, J. Hwang, and M. Asif. Exploring the Features of Sustainable Urban Form and the Factors that Provoke Shoppers Towards Shopping Malls. 2019. MDPI. <https://www.mdpi.com/2071-1050/11/17/4798/pdf>.
15. Hasker, K., and E. Inci. Free Parking for All in Shopping Malls. 2014. Wiley Online Library. <https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fiere.12090>.
16. Hedhli, K. E., H. Zourrig, and J. Park. Image Transfer from Malls to Stores and Its Influence on Shopping Values and Mall Patronage: The Role of Self‑Congruity. 2017. (URL not provided)
17. Huang, Y.-T., and Y.-C. Huang. Factors Influencing Purchase Intention in Social Media Live Shopping. 2024. IEEE. <http://xplorestaging.ieee.org/ielx8/10673884/10673887/10674597.pdf?arnumber=10674597>.
18. Hui, E. C., N. Ning, and K. K. Chan. The Critical Factors of Shopping Malls in Urban Complexes in China. 2016. Emerald Insight. <https://www.emerald.com/insight/content/doi/10.1108/F-08-2014-0065/full/html>.
19. Ijaz, M. F., and J. Rhee. Constituents and Consequences of Online Shopping in Sustainable E‑Business: An Experimental Study of Online Shopping Malls. 2018. MDPI. <https://www.mdpi.com/2071‑1050/10/10/3756/pdf>.
20. Kalariya, K., R. Chauhan, P. Soni, M. Patel, and H. Patel. Unraveling Millennial Online Shopping Preferences: A Comprehensive Analysis of Factors Influencing Consumer Behaviour in the Digital Marketplace. 2024. Economics.pubmedia. <https://economics.pubmedia.id/index.php/jbhi/article/download/294/230>.
21. Kanev, N. Study and Improvement of Acoustic Conditions in Public Spaces of Shopping Malls. 2021. MDPI. <https://www.mdpi.com/2624‑599X/3/1/11/pdf>.
22. Karthikeyan, K., and D. Prashanth. Exploring Consumer Behavior in Extended Reality (XR): Analyzing Key Influencing Factors in the Metaverse. 2025. JMSE Leyon. <https://jmseleyon.com/index.php/jms/article/download/824/742>.
23. Katrodia, A., M. J. Naude, and S. Soni. Consumer Buying Behavior at Shopping Malls: Does Gender Matter? IFRND. <https://ifrnd.org/journal/index.php/jebs/article/download/2095/1588>.
24. Kim, C., and Y. Na. Consumer Reviews Analysis on Cycling Pants in Online Shopping Malls Using Text Mining. 2021. Springer. <https://link.springer.com/content/pdf/10.1186/s40691-021-00264-7.pdf>.
25. Koksal, H. Shopping Motives, Mall Attractiveness, and Visiting Patterns in Shopping Malls in the Middle East: A Segmentation Approach. 2019. (URL not provided)
26. Kushwaha, T., S. Ubeja, and A. S. Chatterjee. Factors Influencing Selection of Shopping Malls: An Exploratory Study of Consumer Perception. 2017. SAGE Journals. <https://journals.sagepub.com/doi/pdf/10.1177/0972262917716761>.
27. Kusumowidagdo, A., C. L. Rembulan, and A. Sachari. Sense of Place Among Adolescents: Factors Influencing the Place Attachment on Shopping Malls. 2015. UI ScholarHub. <https://scholarhub.ui.ac.id/cgi/viewcontent.cgi?article=1118&context=hubsasia>.
28. Makgopa, S. Determining Consumers’ Reasons for Visiting Shopping Malls. 2016. Business Perspectives. <https://businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/7674/im_en_2016_02_Makgopa.pdf>.
29. Man, M. M., and R. C. Qiu. An Empirical Study of Factors Influencing Consumers’ Purchasing Behaviours in Shopping Malls. 2021. CCSEN Online. <http://www.ccsenet.org/journal/index.php/ijms/article/download/0/0/44565/47038>.
30. Meena, S. Trip Generation for Shopping Malls in Developing Cities. 2022. ISTIEE. <http://www.istiee.unict.it/sites/default/files/files/ET_2022_86_2.pdf>.
31. Meyer‑Ohle, H. Japanese Retailers in Southeast Asia: Strong Local Partners, Shopping Malls, and Aiming for Comprehensive Internationalization. 2014. Taylor & Francis Online. <http://www.tandfonline.com/doi/pdf/10.1080/09593969.2014.968186>.
32. Natasha, C. Factors Influencing the Adoption of Green Practices: A Case of Five Selected Shopping Malls in Lusaka District. 2024. SciencePG. <https://article.sciencepublishinggroup.com/pdf/j.scidev.20240503.14>.
33. Ni, S., and H. Ueichi. Factors Influencing Behavioral Intentions in Livestream Shopping: A Cross‑Cultural Study. 2024. Elsevier. <https://api.elsevier.com/content/article/PIIS0969698923003478>.
34. Parakhonyak, A., and M. Titova. Shopping Malls, Platforms, and Consumer Search. 2018. Elsevier. <https://api.elsevier.com/content/article/PIIS0167718716302995>.
35. Park, S. What Attracts You to Shopping Malls? The Relationship Between Perceived Shopping Value and Shopping Orientation on Purchase Intention at Shopping Malls in Suburban Areas. 2016. Springer. <http://link.springer.com/content/pdf/10.1007/978-3-319-26647-3_135>.
36. Rathod, M., and R. Nagdev. Analyzing the Factors Influencing Consumer Brand Loyalty: A Survey‑Based Study in the FMCG Sector in India. 2025. Vidya Journal. <https://vidyajournal.org/index.php/vidya/article/download/524/242>.
37. Reimers, V., and V. Clulow. Spatial Convenience: Bridging the Gap Between Shopping Malls and Shopping Strips. 2014. Emerald Insight. <https://www.emerald.com/insight/content/doi/10.1108/IJRDM-08-2013-0153/full/html>.
38. Rosenbaum, M. S., M. L. Otalora, and G. C. Ramírez. The Restorative Potential of Shopping Malls. 2016. Elsevier. <https://api.elsevier.com/content/article/PIIS0969698916300170>.
39. Rothman, J., J.-H. Kim, and M. Moody. Luxury Unveiled: Gen Z Consumer Motivations and Preferences in Luxury Handbag Selection. 2025. Taylor & Francis Online. <https://www.tandfonline.com/doi/pdf/10.1080/20511817.2025.2466400>.
40. Shtern, M. Urban Neoliberalism vs. Ethno‑National Division: The Case of West Jerusalem’s Shopping Malls. 2016. Elsevier. <https://api.elsevier.com/content/article/PIIS0264275115300111>.
41. Singh, H., and S. Prashar. Anatomy of Shopping Experience for Malls in Mumbai: A Confirmatory Factor Analysis Approach. 2014. Elsevier. <https://api.elsevier.com/content/article/PIIS0969698913000933>.
42. Sit, J. K., and D. Birch. Entertainment Events in Shopping Malls—Profiling Passive and Active Participation Behaviors. 2014. Wiley Online Library. <https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fcb.1487>.
43. Sun, S., F. Zhang, K. Liao, and V. Chang. Determine Factors of NFC Mobile Payment Continuous Adoption in Shopping Malls. 2021. IGI Global. <https://www.igi-global.com/view.aspx?Id=257482>.
44. Szymańska, A. I., and M. Płaziak. Consumer Preferences and Behaviour in Shopping Malls in Poland with the Particular Reference to Krakow. 2018. Sciendo. <http://content.sciendo.com/view/journals/udi/55/3/article-p33.xml>.
45. Yoo, S., D.-J. Lee, and L. Atamja. Influence of Online Information Quality and Website Design on User Shopping Loyalty in the Context of E‑Commerce Shopping Malls in Korea. 2023. MDPI. <https://www.mdpi.com/2071-1050/15/4/3560/pdf>.
46. Yuan, Y., G. Liu, R. Dang, S. S. Lau, and G. Qu. Architectural Design and Consumer Experience: An Investigation of Shopping Malls Throughout the Design Process. 2021. Emerald Insight. <https://www.emerald.com/insight/content/doi/10.1108/APJML-06-2020-0408/full/htm>.
47. Zhiling, C., and O. S. Chris. Factors Influencing Consumer Satisfaction in Online Shopping in Klang, Malaysia. 2025. Semarak Ilmu. <https://semarakilmu.com.my/journals/index.php/sijfthm/article/download/14125/12881>.