The Indian land division has made a ton of progress and is today one of the quickest developing markets on the planet. It involves four sub-divisions – lodging, retail, neighborliness, and business. While lodging helps five–six percent of India's horrible household item (GDP), the staying three sub-divisions are additionally expanding at a quick pace. Land in India is continuously perceived as a base administration that is driving the monetary development motor of the nation. Developing foundation prerequisite in assorted parts, for example, tourism, instruction, human services, and so forth., are putting forth a few financings open doors for both household and additionally remote speculators. The part of the Government of India has been instrumental in the improvement of the area. With the administration attempting to present engineer and purchaser neighborly approaches, the viewpoint for the land division does look encouraging.

Once widely prominent as magnificent Jamnagar has always been a multicultural and glamorous city renowned for its urbane manners, beautiful gardens, and gracious lifestyles. Real estate factors play a pivotal part in expansion, growth, and opulence of any city, with Jamnagar being no exception. The real estate sector of Jamnagar is one of the fastest flourishing industries of Jamnagar.

The literature establishes a clear nexus between quality management, customer satisfaction, and project success in the construction industry. Customer satisfaction is widely regarded as both a primary goal and a critical metric for evaluating construction quality and company performance (Kärnä et al.). Empirical research in the Finnish context by Kärnä et al. identifies key determinants of client satisfaction, categorizing them into five critical factors: quality assurance and handover, environmental and safety performance, co-operation, personnel competence, and the effectiveness of site supervision and subcontracting.

This focus on meeting customer requirements is positioned as a core business strategy for maintaining competitiveness. As Shanmugapriya and Subramanian argue, quality is a critical success factor defined by conformance to predetermined specifications. Their study of Indian construction firms, utilizing a Relative Importance Index (RII) analysis, ranks the top influencing factors as: conformance to codes and standards, robust quality documentation, the ability to satisfy customer needs, organizational knowledge sharing, and effective human resource planning. This underscores the necessity for implementing formalized Quality Management Systems (QMS) to survive in a demanding market.

The imperative for customer-centricity is particularly acute in residential real estate. Rathod et al. emphasize that understanding resident needs is essential for continuous improvement, especially in challenging market conditions. Their research in Western India reveals significant resident dissatisfaction with facilities, highlighting a gap between developer offerings and homeowner expectations. Ultimately, the successful execution of projects that achieve this satisfaction hinges on efficient implementation. Henckel and McKibbin caution that infrastructure projects frequently suffer from significant cost and time overruns (20-25%). They advocate for a rigorous assessment of project viability, particularly for Public-Private Partnerships (PPPs), to ensure accurate cost estimation and appropriate risk transfer to the private sector, thereby securing project profitability and successful delivery.

Rationale for the Study

Customer satisfaction is a critical determinant of success and longevity in the competitive real estate sector. For infrastructure developers, systematically understanding this satisfaction provides a strategic tool for quality improvement and business development. This study is motivated by the necessity to empirically evaluate the customer satisfaction levels of Divyam Infra Private Limited's clientele. The rationale extends beyond mere measurement to garner insights into the company's quality control management practices and the perceived effectiveness of its management and administrative staff. Furthermore, this research seeks to analyze market demand patterns and gather critical data on customer needs and requirements. The findings are intended to furnish the company with actionable guidance for the strategic planning and execution of its future residential projects, thereby enhancing its competitive positioning and service delivery.

Research Objectives

This study is designed to achieve the following specific objectives:

1. To quantitatively measure the current level of customer satisfaction among residents of Divyam Infra Private Limited's projects.
2. To identify and analyze the relationship between the occupational profile of customers and their primary purpose for purchasing an apartment (e.g., investment, self-use, rental income).
3. To investigate and establish the correlation between the size of a customer's family and their preference for a specific type or size of apartment.

Scope of the Study

The scope of this research is delineated to ensure a focused and comprehensive analysis. The study encompasses:

• The Company: Divyam Infra Private Limited, including its operational practices, project portfolio, and quality management systems.
• The Customers: Existing residents and property owners within the company's completed residential projects.
• Management and Administration Staff: Employees responsible for customer interaction, project delivery, and post-sales service.
• Regulatory Bodies: The relevant Government and Municipal Corporation regulations and policies that influence project development and customer satisfaction.
• Financial Advisors: The role of financial intermediaries in influencing customer decisions and satisfaction.

Hypotheses of the Study

Based on the research objectives, the following hypotheses are proposed for testing:

1. There is a significant relationship between a specific residential project developed by Divyam Infra Private Limited and the customers' primary reason for moving into that community.
2. A significant relationship exists between the occupation of a customer and their purpose for buying the apartment (e.g., self-use, investment, rental).
3. The size of a customer's family significantly influences the type of apartment they require.
4. There is a significant relationship between a specific residential project and its overall customer satisfaction rating.

Research Design

This study employs a mixed-methods research design, integrating both qualitative and quantitative approaches. The quantitative component will be used to numerically measure customer satisfaction levels and test the stated hypotheses through statistical analysis. The qualitative component will provide deeper insights into the reasons behind the satisfaction scores, capturing nuanced opinions on quality management, staff effectiveness, and customer needs.

Data Sources

Data will be gathered from the following primary and secondary sources:

• Primary Data: Collected directly from first-hand sources.
  • Structured Interviews: Conducted with the Directors of Divyam Infra Private Limited to gain insights into company policies, quality control management, and strategic vision.
  • Survey Data: Gathered from customers through a structured questionnaire.
• Secondary Data: Obtained from existing internal sources.
• Customer Databases: Existing records of customers from Divyam Infra Private Limited will be used for sampling and contextual analysis.

Data Collection Instrument

The primary instrument for data collection from customers is a structured questionnaire. This questionnaire will be designed to include:

• Section A: Demographic Profile (to capture data on occupation, family size, etc.)
• Section B: Quantitative Metrics (utilizing Likert scales to measure satisfaction levels across various attributes: construction quality, amenities, management staff, etc.)
• Section C: Qualitative Open-ended Questions (to gather detailed opinions, suggestions, and reasons behind the ratings).

SAMPLING DESGIN:

Sampling Frame: The study population consists of customers (flat owners) from three specific residential projects developed by Divyam Infra Private Limited: SHREEJI, BHAGYALAKSHMI, and DIVYAMVILLA.

Sampling Unit: The primary sampling unit is an individual residential flat within the specified projects. The respondent for each unit will be the primary decision-maker or head of the household residing in the flat.

Sample Size: A total of 150 customers were selected for this study. This sample is distributed across the three aforementioned projects.

Sampling Technique: A non-probability convenience sampling technique was employed for this study. Participants were selected based on their willingness and availability to participate during the data collection period. While this method is efficient for exploratory research and provides initial insights, it is acknowledged that the findings may have limitations regarding generalizability to the entire customer base.

LIMITATIONS OF THE STUDY

While this study provides valuable insights, its findings must be interpreted in light of the following methodological limitations:

1. Participant Accessibility and Non-Response Bias: The primary limitation involved significant challenges in securing participant engagement. Difficulties in accessing customers and obtaining their time to complete the survey may have introduced non-response bias, as the final sample may not be fully representative of the entire customer population. Those who chose to participate may hold systematically more positive or negative views than those who did not.
2. Constraints of the Survey Instrument: The structured nature of the questionnaire, while excellent for collecting quantitative data, is inherently inadequate for capturing the full depth of qualitative information, such as nuanced emotions, underlying feelings, or detailed personal experiences that influence customer satisfaction.
3. Reliance on Self-Reported Data: The study relies on respondents' self-reported perceptions and opinions. As such, the accuracy of the data is contingent upon their honesty and self-awareness. There was no feasible method to verify the truthfulness of their responses, which may be subject to social desirability bias (the tendency to respond in a manner deemed socially acceptable).
4. Potential for Response and Researcher Bias: The use of a non-probability convenience sampling method increases the potential for selection bias. Furthermore, despite efforts to maintain objectivity, the interpretation of open-ended responses could be unconsciously influenced by the researchers' own perspectives, introducing a potential for researcher bias.

DATA ANALYSIS AND INTERPRETATION

1. Distribution of Customers by Investment Capacity

Data: The data shows the number of customers in different investment brackets:

• 5,000: 0 customers
• 10,000: 46 customers
• 10,000 or more: 102 customers

Interpretation:

The vast majority of the customer base (102 out of 148 respondents, or ~69%) has a high investment capacity, willing to invest Rs. 10,000 or more. A significant portion (46 customers, ~31%) is clustered at the Rs. 10,000 level. This indicates a financially capable clientele, which is typical for the real estate sector. This finding is crucial for the company's pricing strategy and for designing payment plans for future projects.

2. Distribution of Customers by Age

Data: The age distribution of customers is as follows:

• 25-35 Years: 27 customers
• 35-45 Years: 31 customers
• 45-60 Years: 66 customers
• 60 above: 0 customers

Interpretation:

The data reveals that the primary customer demographic is middle-aged individuals, with the largest segment (66 customers, ~53%) being between 45-60 years old. This is followed by the 35-45 age group (31 customers, ~25%). This suggests that customers in this market are typically established in their careers and have accumulated sufficient capital for real estate investment, which aligns with the data on high investment capacity. The absence of customers above 60 may indicate a lack of targeted marketing towards retirees or a preference for this demographic to invest in other financial instruments.

3. Distribution of Customers by Gender

Data: The gender distribution is perfectly balanced:

• Male: 68 customers
• Female: 68 customers

Interpretation:

The customer base is split evenly between male and female respondents (68 each). This suggests that the decision to purchase residential real estate is equally shared among genders in this market. For the company, this implies that marketing messages and customer engagement strategies should be inclusive and appeal to a gender-neutral audience.

4. Distribution of Customers by Occupation

Data: The occupational background of customers is:

• Tech & Trade Professional: 41 customers
• Clerical & ...: 13 customers
• Others: 199 customers

Interpretation:

The occupational data is heavily skewed towards the "Others" category (199 customers), which limits detailed analysis. This category likely encompasses business owners, self-employed individuals, and other professions not specified. The second largest group is "Tech & Trade Professionals" (41 customers). To gain more actionable insights, future research should break down the "Others" category into more specific occupational fields.

5. Distribution of Customers by Purchase Purpose

Data: The primary reasons for purchasing a property are:

• Investment: 199 customers
• Retiring to the property: 0 customers
• Living with family: 41 customers
• Others: 0 customers

Interpretation:

This is a highly significant finding. An overwhelming majority of customers (199, or ~83%) purchased the property as an investment. Only 41 customers (~17%) purchased it for the purpose of "Living with family." This clearly indicates that the company's projects are primarily perceived as financial assets rather than immediate homes. This has major strategic implications: marketing should be tailored to investors highlighting rental yield and capital appreciation, and project features should cater to tenant needs rather than just owner-occupiers.

HYPOTHESIS AND TESTING – ANOVA

1. The relationship between selection of projects and reason for its selection.

H0: There is no significant difference among selection of Project and reason for its selection.

H1: There is significant difference among selection of Project and reason for its selection.

Based on the results of the one-way ANOVA test, we fail to reject the null hypothesis (H0).

The analysis provides no statistically significant evidence to suggest that the reason for selecting a property differs based on which project (SHREEJI, BHAGYALAKSHMI, or DIVYAMVILLA) a customer chose. The perceived reasons for selection (e.g., investment, location, amenities) are consistent across the company's different projects.

In practical terms, this means that the factors driving customer choice are likely universal to the company's brand and overall offering, rather than being specific to the unique features of any single project. Marketing and sales strategies can therefore be developed cohesively across the project portfolio.

2. The relationship between Occupation of owners and Purpose for buying the apartment.

H0: There is no significant difference between occupation of owners and purpose for buying the apartment.

H1: There is significant difference between occupation of owners and purpose for buying the apartment.

Based on the results of the one-way ANOVA test, we fail to reject the null hypothesis (H₀). The analysis provides no statistically significant evidence to suggest that the purpose for buying an apartment (e.g., investment, self-use, retirement planning) differs based on the occupation of the property owners.

In practical terms, this implies that factors driving the purchase decision are consistent across different occupational groups. Whether buyers are professionals, business owners, or employed in other sectors, their reasons for investing in residential property appear to be similar. This finding suggests that marketing strategies and project positioning do not need to be tailored specifically to different occupational segments, as purchase motivation appears to be universal across these groups.

3. The relationship between number of people in the family and type of apartment.

H0: There is no significant difference between number of people and type of Apartment.

 H1: There is significant difference between number of people and type of Apartment.

Based on the results of the one-way ANOVA test, we fail to reject the null hypothesis (H₀).The analysis provides no statistically significant evidence to suggest that the type of apartment preferred (e.g., 1BHK, 2BHK, 3BHK) differs based on the number of people in the family.

In practical terms, this implies that factors beyond just family size may be influencing apartment type selection. While conventional wisdom suggests larger families would prefer larger apartments, this statistical analysis does not support that relationship in your sample. Other factors such as budget constraints, investment goals, or availability of apartment types might be playing a more significant role in the decision-making process.

FINDINGS OF THE STUDY

The analysis of data collected from 150 customers of Divyam Infra Private Limited yielded the following key findings:

1. Customer Demographic Profile:

• The typical customer is middle-aged, with the largest segment (53%) belonging to the 45-60 years age group, followed by those aged 35-45 (25%). No customers were above the age of 60.
• The customer base is perfectly balanced in terms of gender, with an equal split between male and female respondents.
• The majority of the clientele (69%) exhibits a high investment capacity, indicating strong financial capability.

2. Customer Occupational Profile and Purchase Purpose:

• The occupational data was dominated by an unspecified "Others" category, limiting detailed analysis. Among specified professions, "Tech & Trade Professionals" formed the largest group.
• A overwhelming majority (83%) of customers purchased properties primarily as an investment, with only 17% buying for the purpose of "Living with family."

3. Hypothesis Testing:

• Project Selection and Reason: The ANOVA test revealed no significant difference in the reasons for selection (e.g., investment potential, amenities) across the different projects (SHREEJI, BHAGYALAKSHMI, DIVYAMVILLA). The driving factors for customer choice are consistent across the company's portfolio.
• Occupation and Purchase Purpose: The ANOVA test found no significant relationship between the occupation of buyers and their purpose for purchasing an apartment. Purchase motivation (investment vs. self-use) is consistent across all occupational groups.
• Family Size and Apartment Type: Contrary to conventional expectation, the ANOVA test showed no significant relationship between the number of people in a family and the type of apartment they prefer. Factors other than family size are more influential in this decision.

CONCLUSIONS

Based on the findings of this study, the following conclusions can be drawn:

1. Divyam Infra's Market Position: The company successfully attracts a demographically diverse and financially robust customer base. However, its product is predominantly perceived as a financial investment vehicle rather than a primary residence. This defines the company's core market position as a provider of investment-grade real estate.
2. Universal Value Proposition: The consistent reasons for project selection across all three properties indicate that customers value the company's overall brand promise—likely rooted in trust, timely delivery, and perceived return on investment—over the unique attributes of any single project.
3. Marketing and Strategic Implications:
   • Target Audience: Marketing and communication strategies should be tailored to target middle-aged, high-capacity investors rather than first-time homebuyers seeking a primary residence.
   • Messaging: The promotional focus should emphasize investment-centric benefits such as rental yield, capital appreciation, and property management services, rather than just lifestyle and familial amenities.
   • Product Development: For future projects, the company should consider features that appeal to tenants (e.g., low maintenance, rental-friendly layouts) since the end-user will likely be a renter, not the owner-occupier.

1. Henckel, T., & McKibbin, W. (Year). Title of the specific article or report. Centre for Applied Macroeconomic Analysis, Australian National University.
2. Kärnä, S., Junnonen, J., & Kankainen, J. (Year). Title of the article. Journal Name, Volume(Issue), page range.
3. Rathod, P., Bhat, R., & Pitroda, J. (Year). Analysis of satisfaction factors of customers of residential flats. Journal Name, Volume(Issue), page range.
4. Shanmugapriya, S., & Subramanian, K. (Year). Ranking of key quality factors in Indian construction projects. Journal Name, Volume(Issue), page range.
5. Hussain, S., & Zhu FangWei, & Ali, Z. (2019). Examining Influence of Construction Projects’ Quality Factors on Client Satisfaction Using Partial Least Squares Structural Equation Modeling. Journal of Construction Engineering and Management, 145(5).
6. Jraisat, L., Jreisat, L., & Hattar, C. (2016). Quality in construction management: an exploratory study. International Journal of Quality & Reliability Management, 33(7), 920-941.
7. Forsythe, P. J. (2016). Construction service quality and satisfaction for a targeted housing customer. Engineering, Construction and Architectural Management, 23(3), 323-348.
8. Milion, R. N., Alves, T. d. C. L., & Paliari, J. C. (2017). Impacts of residential construction defects on customer satisfaction. International Journal of Building Pathology and Adaptation, 35(3), 218-232.
9. El Sakka, K. J., Hadidi, L. A., & Islam, M. S. (2024). Developing customer satisfaction index for the construction industry: a case study for Saudi Arabia. International Journal of Productivity and Quality Management,
10. Othman, A. A. E. (2015). An international index for customer satisfaction in the construction industry. International Journal of Construction Management, 15(1), 33-58.
11. Improving clients’ satisfaction in construction projects: the case of Saudi Arabia. (Year). Benchmarking: An International Journal, (Vol/Issue). — This qualitative study identifies key satisfaction drivers such as effective financial management, skilled labour, technology use, customer relations, and time management.
12. Suhada, D., & Syairuddin, B. (Year). Analysis of Customer Satisfaction in Construction Companies Using QFD Method. (IPTEK Journal of Proceedings Series). The study uses Quality Function Deployment to find priorities among service quality features.
13. Literature Study on Satisfaction Factors of Customers in Construction Industry. (2017). IJERT, 06(11). Shruthi Sivaprakasam, R. Shanmuga Priyan, J. Jayashree. Analyses factors affecting customer satisfaction like cost, time, quality, etc