2025 年 13 巻 4 号 p. 100-127
In India, 40% of the population is under 25. Therefore, the demand for higher education is growing. This results in the migration of the young population, creating a high demand for housing. Higher Education Institutes (HEI) often cannot cater to this demand. Rental housing options in neighbourhoods around the HEI cater to a large portion of this demand. Such an influx of students in neighbourhoods often creates chaos and leads to gentrification. It affects the neighbourhood’s liveability, resulting in the growth of poor and low-quality housing conditions. Students’ preferences are very significant to assess to provide planning interventions in systematic allocation and creation of standard housing in a typical city. The paper analyses students’ preferences for a rental housing unit in a neighbourhood in Dehradun, one of India’s educational hubs. It focuses on ten locational and twenty-seven housing attributes identified. Importance-performance analysis (IPA) was conducted using primary data collected from 425 respondents. The research findings show that the neighbourhood’s safety, environment, and location are essential, while affordable locality is crucial and needs focus. Regarding housing, cost, amenities, and privacy are crucial for choice-making by the students, while focus needs to be given to security. Finally, we focus on housing options that can be considered, i.e. Purpose-Built Student Accommodation (PBSA). The study shall help the developers and HEIs develop the housing options and preferences for students migrating to cities for education and jobs. Moreover, the findings will also enrich the literature related to housing satisfaction in a contextual manner.
Higher education institutions often struggle to meet their student’s housing needs. Over time as institutions expand, a shortage of accommodations arises. Students end up exploring a variety of rental accommodations per their affordability. This is a general and worldwide phenomenon. Researchers have attempted to study these conditions wherein students become agents of change in urban areas, introducing the concept of University Towns (Choyimanikandiyil, 2019), student cities (Chatterton, 2010), urban dormitories (Revington, Moos et al., 2020), town and gown (Hubbard, 2008; Revington and August, 2020). At the same time, some public-funded education does take responsibility for providing decent housing and food during their study. A typical city accommodates a balanced amount of university-provided and market-supplied student housing. However, with the increase in population, there is increasing demand for student housing. That can be due to the sudden increase of institutions or the substandard quality of existing students' housing, such a sudden influx of demand in student housing leads to a situation where a typical residential neighbourhood gradually transforms into a mix of rental accommodation. This phenomenon can be understood as gentrification around HEIs (Buchori, Zaki et al., 2023). Such a condition may be attractive initially but chaotic in the long run and is termed as ‘studentification’ (Smith, D. P., 2004).
The student accommodation issue is widely discussed because of its current market size and multidimensional impact on urban neighbourhoods and its intra-urban dynamics (Zasina and Antczak, 2023).Such studentification phenomenon is quite different in various countries and was reported in the literature in a limited way. However, studentification in the countries of the global south could be unique and more challenging considering the high density and lower controls on rental markets. For example, India, the most populous country in the world, shows a diverse canvas for studentification, which is concentrated in a few cities where many HEIs were developed in the near past. Secondly, studentification in Indian cities is also characterised by the influx of job aspirants who prepare for competitive examinations where the number of students could be a few million to billions. The nature of such migrating students on a grand scale has largely not been reported and studied. This has resulted in the formation of student ghettos in the pockets of various Indian cities. The recent increase in HEIs has led to a focus on investment in student housing. Housing, being a physical entity, is greatly associated with the quality of life and is responsible for psychological well-being (Baiden, Arku et al., 2011; Shaw, 2004; Sultana, Suhi et al., 2022; Zou, Ma et al., 2022). There is a gap in the literature which does not investigate the preferences of the students enrolled in these HEIs regarding housing.
From 2006 to 2018, a survey of 55 countries highlighted the increase in the number of HEI’s by 52%. During this time, India reported more than 22,000 new HEI’s (UNESCO., 2022). This, therefore, influenced the student population in the country. A significant student population in the vicinity of universities, colleges, and prominent coaching centres in various cities in India like Kota and Delhi profoundly affects the local economy and the surrounding area's physical, social, economic, and cultural aspects. In India, nearly 40% of the population falls below the age of 25, representing the world’s largest 5-24 age group (Bansal, 2021). Consequently, the demand for higher education continues to rise. Therefore, like many other countries, India is also experiencing a surge in the education industry. With increased enrolment in higher education, it becomes crucial to understand the transformations brought about by students in the urban fabric. Statistics reveal that there are 37.8 million students enrolled in higher education in India, with 75% being outstation candidates (Shah, Sharma et al., 2020). The demand for student rental housing was analysed when the gross enrolment ratio was 26.8 in 2018. However, with the new National Education Policy (NEP), which aims to increase the gross enrolment Ratio (GER) to 50% by 2035, the need for student housing is expected to escalate. As of 2019, there were 148000 student housing and co-living beds operated by 30-35 operators in the market (JLL., 2019). This sector is estimated with a potential market worth of 50 billion Dollars (Knight, 2019), with the projections indicating further growth in the industry. With such massive projections of student enrolment and consequent increase in housing needs, there is a need to study the exact nature of the student’s preferred housing and strategy to create such housing. Unfortunately, the earlier housing policies only focussed on the family-based housing and owner-based housing typology till the National Rental Housing Policy,2015, which indicated the need for student housing even though there are a lot of unanswered questions. This study focuses on Dehradun, which is an emerging educational hub experiencing rapid growth in higher education institutions (HEIs).
This study contributes to the literature by applying the IPA technique in the context of student housing preferences in Dehradun, India. It identifies the critical importance and satisfaction dimensions of housing and the neighbourhood preferences of students and determines the improvement needed in the student housing industry. Specifically, the research addresses the following research question
How do students perceive the priorities of importance and performance levels of the neighbourhood and housing factors using the IPA framework?
The study is systematically organised into five distinct sections. The following section offers a thorough analysis of the relevant literature, precisely identifying the gaps in the present pool of knowledge. This is followed by a thorough explanation of the methodology adopted for the study. The analysis's conclusions are then given, followed by a discussion section. A comprehensive conclusion that summarises the research findings and their consequences completes the study.
The term “student” refers to an individual engaged in formal education at a school, university, or any educational institution, as the Cambridge Dictionary defines. In India, students often migrate at a young age, typically around the eighth grade, driven by the need to prepare for competitive examinations in fields such as engineering and medicine and pursue higher education at colleges. Consequently, students can be categorised as those enrolled in traditional education like schools and colleges (formal) and those attending coaching institutes or similar informal institutions (informal). The concentration of the student population in a city is generally observed around HEIs. This phenomenon transforms urban landscapes, generating interest in studying these changes. The urban transformation where students become the agent of change can be associated with the concept of studentification (Smith, D. P. and Holt, 2007). Smith, D. P. (2004) described studentification as the inflow of students in a neighbourhood, which then experiences physical, economic, social, and cultural changes. This phenomenon is experienced and researched worldwide and comprehended as follows:
| Countries | Observations | Study |
|---|---|---|
| U.K. | Student-dominated are, developed near universities with the growth of private accommodations | Hubbard (2008); Kinton, Smith et al. (2016); Kinton, Smith et al. (2018); Sage, Smith et al. (2012a); Smith, D. (2008); Smith, D. P. and Hubbard (2014) |
| South Africa | Overpopulated student neighbourhoods were documented | Ackermann and Visser (2016); Gregory and Rogerson (2019) |
| European | Student-dominated neighbourhoods transform residential areas | Atkinson (2004); Miessner (2021); Verhetsel, Kessels et al. (2017); Winston (2017) |
| America | Phenomena affect spatial urbanism and housing facilities become crucial towards housing satisfaction, | Revington and August (2020); Revington, Moos et al. (2020) |
| Australia | Phenomena studied when it goes vertical and infuses change in neighbourhood and housing market | Holton and Mouat (2021) |
| Asia | The dominance of the student population on rental housing thereby changing Social, economic, cultural and physical aspects in the area | Dewi, Ristianti et al. (2019); Gu and Smith (2020); Situmorang, Antariksa et al. (2020) |
Although relevantly studied worldwide, literature focusing on Indian aspects remains scarce. Considering the widespread prevalence, dynamic characteristics, and diverse effects of studentification, it is crucial to understand the factors that influence its intra-urban geographies.
The key feature of this phenomenon is the prevalence of privately rented accommodation in a neighbourhood (Smith, D. P., 2004) and student demand for housing in the knowledge-based economy, which becomes even more prominent with the mobility of international students (Malet Calvo, 2018) as more and more countries aim to make education in Western countries more global. This student-led gentrification stresses the neighbourhood due to the over-concentration of students near HEIs, even leading to the downgrading of the otherwise better neighbourhood area. Often marked by recommodification of housing with a change in tenure, a shift of family-based or non-student housing to single-person housing (Sage, Smith et al., 2012b; Smith, D., 2008; Zasina and Antczak, 2023). Subsequently, it increases the rent of housing in the area. Concerns over the deterioration of the natural environment, the relocation of families, and the resulting decline of community schools are also included. The parking demand is also a result of the development of Housing for Multiple Occupation (HMO), which excludes other tenants due to increased expenses. (Munro and Livingston, 2012; Smith, D. P., 2004; Smith, D. P. and Holt, 2007; Smith, D. P. and Hubbard, 2014).Socially and culturally, the main criticisms focus on how students might disrupt a neighbourhood by being less mindful of noise with late-night parties or being inconsiderate of various social norms. Such that the neighbourhood becomes unfit for a family living and they rather move out from such areas (Munro and Livingston, 2012).It encompasses various unique aspects not typically found in traditional gentrification (Nakazawa, 2017).
However, tension and conflict may arise in these regions. Traditionally students typically hail from upper or middle-class families, thus they tend to build exclusive geographies rather than being seen as celebratory examples of a consumption-oriented postmodern metropolis that acts as a platform for lifestyle (Chatterton, 1999, 2010).
The market response to this urban phenomenon of studentification, mostly observed is the supply of purpose-built student housing (PBSA). Ironically, though, this strategy may further isolate students from society at large (Smith, D. P. and Hubbard, 2014). This might somewhat reduce the concentration and spread of students in traditional neighbourhoods (Hubbard, 2009). Therefore, it becomes crucial to understand the factors responsible for housing satisfaction for the students. Hence, the next sections highlight the literature on student housing and satisfaction.
Student housing options can be divided into two broad categories.
i) On-campus, which is the housing provided by the HEI’s, and
ii) Off Campus, which is the market response to the demand of students for housing outside the campus of HEIs. Students have a tendency to settle in neighbourhoods adjacent to HEI campuses seeking private housing, living in whatever the market offer (Garmendia, Coronado et al., 2012). In general, as well, residential satisfaction has a direct and inherent connection with neighbourhood factors (Buchori, Zaki et al., 2023).Moreover, several studies also pointed out that students prefer amenities neighbourhoods which need not necessarily be near HEI, which can be observed in city centres (Allinson, 2006) or in periphery (Sage, Smith et al., 2012a) wherever it's cheap and affordable for them. Therefore, the cost of amenities becomes an integral factor in these cases. To date, most researchers have focused on exploring student housing preferences and the inter-urban geographies of student accommodations. Numerous studies have been conducted on student accommodations focused on On-campus housing (Najib, Nurul Ulyani Mohd, Yusof et al., 2011; Najib, Nurul‘Ulyani Mohd, Yusof et al., 2015) and others on Off-campus housing (Adebowale and Simpeh, 2023; Gbadegesin, J. T., Komolafe et al., 2021; Gu and Smith, 2020; Hubbard, 2009; Johari, Mohd et al., 2017; Muslim, Karim et al., 2012; Muslim, Karim et al., 2013; Revington, Moos et al., 2020), looking back on aspects such as student perception of housing, overall satisfaction, and decision-making leading to academic property development (Revington, Moos et al., 2020) relationships between town and HEI’s (Zasina and Antczak, 2023).Such that this relationship has developed a potential market for Purpose Built Student Accommodations (PBSA) (Holton and Mouat, 2021; Kenna and Murphy, 2021; Revington and August, 2020; Wilkinson and Greenhalgh, 2024).While some researchers point out that distance from the university and room furnishing is ranked lower in priority among other attributes like housing type, rent, and size, demanding privacy is a prime important (Verhetsel, Kessels et al., 2017) other points out various neighbourhood attributes which also become crucial deciding factors for students (Zasina and Antczak, 2023).
Therefore, we explore the student perception of different attributes at the Neighbourhood level and the housing level while making a housing choice and the performance of these attributes towards their overall Satisfaction towards the Neighbourhood and the housing they are living in.Giving us the demand side expectation and the available supply of housing in the market. Hence, we focus on how to improve the quality of life suited to the student's preferences.
In this section, the methodology adopted for the study is discussed. The methodology adopted for the study is qualitative in nature. The conceptual methodology is shown in Figure 1.
The methodology adopted had the following steps:
Step 1: Identification of attributes to analyse student housing preferences. This was done using a literature review and focused group discussion with a group of students. These attributes were then evaluated based on students' perceived importance and satisfaction.
Step 2: Data Collection was done using a paper-based questionnaire using a rating of each attribute by the students of HEIs and coaching in Dehradun. Thus, collecting importance-satisfaction for neighbourhood and housing on a Likert scale format. Hence, the database was developed.
Step 3: Data Analysis was done using IPA to classify the attributes in four clusters based on the perceived degree of importance and performance considered through the satisfaction rating by the students. IPA method is used to analyse customer (student here) satisfaction. IPA is a graphic method which is shown in a two-dimensional coordinate system, the average values of importance and performance of different elements, which are calculated to one another, mainly in the area divided into four quadrants. ‘Performance'' represents the user's perception of the quality of services delivered, while ''importance'' refers to the assessment of the importance of those services by users—this method to determine the most important areas that need improvement or attention. This will enable housing providers to focus on improving rental housing services. Hence, it is a crucial analysis, especially for the service industry.
Data collectionThe study focused on students’ housing; hence, the data was collected from the students as the respondents. The data was collected in or near the prominent universities, colleges, and coaching centres of Dehradun city. The survey was done from October to December 2023. The questionnaire was divided into 3 sections. Section 1 collected the basic demographic profile and information on HEI housing. Section 2 recorded respondents’ perception of the importance and satisfaction of Neighbourhood attributes. While in section 3, respondents' assessments of the importance and satisfaction of neighbourhood qualities were recorded. A 5-point Likert scale was used for sections 2 and 3, which ranged from 1” least important” to 5 “most important”. Similarly, 1 was “least satisfied”, and 5 was “most satisfied”. For the sample collection at a 95% confidence level with a Z-score value of 1.96 and using formula n = (Z^2 * p * q) / E^2 (Deming, 1940), 380 samples were targeted. Data was collected in and around HEI’s and coaching institutes of Dehradun. The main transepts were the food joints and the libraries.424 samples were collected from different parts of the city Data Filtering and checking for reliability of data through Cronbach alpha test: The use of Cronbach's alpha in this study provides evidence of the validity and reliability of the scale used to measure Student housing choice. This helps to ensure that the results obtained from the study are accurate and can be used to inform decision-making and policy development related to rental housing for students in an Indian context. Cronbach's alpha is a measure of the internal consistency of a scale or questionnaire. The value of Cronbach's alpha ranges from 0 to 1, where a higher value indicates greater internal consistency or reliability of the scale. Generally, a Cronbach's alpha value of 0.7 or higher is considered acceptable for a scale to be reliable. A total of 434 survey forms were given out to participants for the research project, and 424 of those forms were correctly and totally filled out. During the data entry phase, two forms were excluded from analysis due to a standard deviation of 0, suggesting a lack of meaningful response or engagement from the respondents in those cases.
Internal consistency or reliability of 422 valid samples was checked, and a high value of Cronbach alpha, i.e. 0.9, was obtained, which indicated high internal consistency for the scale used and samples collected.
The relevancy, importance, and satisfaction scores for the neighbourhood, housing attribute and overall had Cronbach's alpha coefficients of 0.80, 0.794, 0.892, 0.920, and 0.926, respectively. These results demonstrate the scale's good reliability and internal consistency.
The study considered thirty-seven attributes for the research. The following section gives the details on the identification of the attributes:
Identification of attributesThe attributes were identified from the literature, and a focused group discussion on the instrument design was done, which involved 12 university students. These students were selected based on their experience in house hunting, and each had lived for more than 5 years in rental accommodations. The students were to list the attributes they considered while choosing housing, and at the end of the discussion, we were able to list down the most significant attributes of rental housing from the student perspective. In literature, studentification is studied in four broad aspects, which are Physical, social, cultural and economic aspects (Smith, D., 2008; Smith, D. P. and Holt, 2007).The findings revealed nine broad indicators from the discussion and 26 factors with 205 sub-variables from the literature (‘Ulyani Mohd Najib, Aini Yusof et al., 2011; Gbadegesin, J., Marais et al., 2022; Simpeh and Akinlolu, 2021). The common and distinct attributes derived from both discussion and the literature were compiled for the study. These attributes were divided into two categories, one at the neighbourhood level with 10 variables and another at the housing level with 27 variables. The neighbourhood attributes included the following in Table 2:
| Code | Attribute Name | Description | Literature |
| N1 | Safe locality | It means a sense of overall safety and security in the neighbourhood | Ackermann and Visser (2016); Allinson (2006) |
| N2 | Environment, surroundings & Good Parks | It refers to the overall environment of the neighbourhood in terms of green spaces. | Muslim, Karim et al. (2012); Muslim, Karim et al. (2013) |
| N3 | Affordable locality | It refers to the perception of students towards overall affordability in the locality | Ackermann and Visser (2016); Dewi, Ristianti et al. (2019); Gbadegesin, J., Marais et al. (2022) |
| N4 | Friends in the same locality | It refers to the social indicator of having friends living in the same locality | Ackermann and Visser (2016); Allinson (2006) |
| N5 | Bus /Auto stand | It refers to the connectivity of the locality with public transit for the students | Allinson (2006); Baron and Kaplan (2010); Dewi, Ristianti et al. (2019) |
| N6 | College/Institute/Coaching | It refers to the perception towards having HEI in the same locality where they live | Ackermann and Visser (2016); Allinson (2006); Baron and Kaplan (2010); Dewi, Ristianti et al. (2019) |
| N7 | Photocopy, Library stationery, Convenience Shops | It refers to the perception of having Student friendly amenities in the same locality | Allinson (2006) |
| N8 | Restaurants, cafes, and food outlets | It refers to the relevance of Student oriented commercial facilities such as café etc, in the same locality of their housing | Allinson (2006); Baron and Kaplan (2010); Dewi, Ristianti et al. (2019); Gu and Smith (2020) |
| N9 | Vegetable/fruit Shops | It refers to the availability of food facilities in the locality | Gu and Smith (2020) |
| N10 | Barber, Taylor, Parlor, cobbler etc. | It refers to the miscellaneous student-oriented amenities in the locality |
On the other hand, the housing level attributes are encompassed in the following Table 3:
| Code | Attribute Name | Description |
|---|---|---|
| H1 | Cost of Room | Economical aspect covering the cost of the room |
| H2 | Single occupancy in room | It is the Physical aspect of Housing |
| H3 | Attached washroom | Physical aspect of Housing |
| H4 | Attached balcony | Physical aspect of Housing |
| H5 | Kitchen for cooking | Physical aspect of Housing |
| H6 | Good ventilation | Physical aspect of Housing |
| H7 | HI speed Wi-Fi/LAN | Physical aspect of Housing |
| H8 | 24 hr Water supply | Physical aspect of Housing |
| H9 | Hot water availability | Physical aspect of Housing |
| H10 | 24hrs Electricity with backup | Physical aspect of Housing |
| H11 | AC (Air Conditioner) / Cooler | Physical aspect of Housing |
| H12 | food facility/ mess food availability | Physical aspect of Housing |
| H13 | Living with friends | Social aspect in Housing |
| H14 | Living with same stream people | Social aspect in Housing |
| H15 | Privacy from Landlord | Cultural aspect in Housing indicative towards privacy |
| H16 | Privacy from Neighbours | Cultural aspect in Housing indicative towards privacy |
| H17 | Presence of security guard | Safety and Security at housing level |
| H18 | Presence of CCTV | Safety and Security at housing level |
| H19 | Secured building | Safety and Security at housing level |
| H20 | NO restriction on IN-OUT timing | Cultural aspect in Housing indicative towards freedom in living |
| H21 | Common Study Area | Physical aspect of Housing |
| H22 | Indoor games room | Physical aspect of Housing |
| H23 | Laundry Room | Physical aspect of Housing |
| H24 | Gym facility | Physical aspect of Housing |
| H25 | Common TV room | Physical aspect of Housing |
| H26 | Common area for Guests | Physical aspect of Housing |
| H27 | Recommendation by friend/known person | Social aspect of Housing |
(‘Ulyani Mohd Najib, Aini Yusof et al., 2011; Ackermann and Visser, 2016; Allinson, 2006; Dewi, Ristianti et al., 2019; Foote, 2017; Gregory and Rogerson, 2019; Gu and Smith, 2020; Muslim, Karim et al., 2012; Sage, Smith et al., 2012b; Situmorang, Antariksa et al., 2020)
The attributes were assessed by the importance-performance analysis (IPA). It is used to prioritise attributes in two dimensions: importance and satisfaction level (Hansen and Bush, 1999). It was initially introduced by (Martilla and James, 1977) to achieve customer satisfaction. In the IPA graph, the X-axis depicts the attributes' importance, and the Y-axis depicts the attributes' performance (satisfaction). The means of importance and satisfaction divide the graph into four quadrants as shown in Figure 2.
Each quadrant had the following meanings:
First Quadrant ("keep up the good work"): This quadrant signifies the combination of high performance and high importance. If an attribute is placed here on a company's diagram, it indicates that the company is sufficiently emphasizing this attribute to gain a competitive edge and should continue to do so.
Second Quadrant ("possible overkill"): This quadrant represents the combination of high performance and low importance. If an attribute falls into this area, developers should conserve resources and avoid overinvesting in that attribute.
Third Quadrant ("low priority"): This quadrant indicates the intersection of low performance and low importance. Attributes in this quadrant are of low priority, and the quality of service concerning these attributes is less critical.
Fourth Quadrant ("concentrate here"): This quadrant signifies the intersection of low performance and high importance. If an attribute falls into this quadrant, the company needs to focus on improving that attribute.
IPA has been previously used for various research to evaluate customer satisfaction in various areas of small business (Levenburg and Magal, 2004), banking, information technologies (Skok, Kophamel et al., 2001), education (Alberty and Mihalik, 1989), healthcare (Abalo, Varela et al., 2007), and hospitality and tourism (Evans and Chon, 1989; Morley, 1997) urban design (Insch, 2010)and elderly home (Afacan, 2019). However, it was examined that there is a significant gap in the use of the analysis for rental housing demand and expectation gap, especially in the context of students. Therefore, the study proposes an effective use of IPA in bridging the gaps in students' wants and desires in terms of housing and its environment.
This study investigates students' housing preferences in Dehradun, an emerging educational hub experiencing rapid growth in HEIs
Descriptive statisticsA total of 422 eligible responses were analysed, with following demographic profile:
| Socioeconomic attribute | Classification | % of Respondents (Total 422) |
|---|---|---|
|
Gender |
Male | (228) 54% |
| Female | (193) 46% | |
| Prefer not to say | (1)0% | |
|
Age |
15 - 18 | (154) 36% |
| 19 -21 | (220) 52% | |
| Above 21 | (48) 11% | |
| Educational Level | Undergraduate | (363) 86% |
| Postgraduate | (30) 7% | |
| Job aspirants | (24) 5% | |
| Other (Ph.D. Etc.) | (5) 1% | |
| Distance between HEI and House | Less than 500 mt | (126) 30% |
| 500 mt to 1 km | (55) 13% | |
| 1 km to 1.5 km | (22) 5% | |
| 1.5 km to 2 km | (21) 5% | |
| More than 2km | (198) 47% | |
| Type of Residence | Traditional PG (TPG) | (102) 24.3% |
| Operator Paying Guest (OMPG) | (97) 22.9% | |
| Shared Flat (SF) | (73) 17.3% | |
| Fully serviced co-living (FSCl) | (59) 13.9% | |
| Hostel | (91) 21.6% |
Among the respondents, 24.3% lived in Traditional PG, the share of operator-managed paying guests was 22.9%, a fully serviced co-living respondents share was 21.6%, and 17.3% lived in shared flats
Assessment of Student Housing options, services offered and rent corresponding rent adjustmentThe housing typologies for rental properties were documented on six websites: Magic Bricks, Stanza Living, 99 Acres, OLX AND Square Yards.500 properties were listed and subsequently, 96 telephonic inquiries were conducted to gather information on rents and facilities offered by the housing providers.20 properties were finally surveyed to categorise the available housing options for students in Dehradun, detailed in Table 5.
Neighbourhood-Level Facilities:
At the neighbourhood level, prominent attributes advertised were the location of the housing, its proximity to HEI or coaching, transit hubs, and the availability of student-friendly amenities. These findings align with market research reports (Wakefield, 2020).
Housing-Level Facilities:
Facilities were categorised into standard and value-added among different housing typologies directly related to rental pricing as shown in Figure 5:
| Housing typology | Essential | Value-Added | Rental Range | ||
|---|---|---|---|---|---|
| Physical | Non-Physical | Physical | Non-Physical | ||
| TPG | Bed, study table and cupboard water facility | Owner's vigilance, | Private, Twin sharing RO purification, refrigerator kitchenette Electricity backup | Wi-Fi | 4,000-8,000 |
| OMPG | Bed, study table and cupboard Electricity backup, water facilities | Caretaker vigilance, | Services like a refrigerator in the kitchen, geyser, Laundry service departmental store | Non-interference from landlord | 8,000-15,000 |
| SF | Unfurnished flat | Non-interference from landlord | Furnished flat with amenities like bed, sofa RO purification, refrigerator kitchenette Electricity backup Availability of security guard, CCTV coverage | No restrictions on entry and exit | 15,000-30,000 |
| FSCl | private, sharing rooms | Non-interference from landlord No restrictions on entry and exit app-based services (paying rent, complaint filing, feedback) | RO purification, refrigerator kitchenette Electricity backup Mess for dining, kitchen for private cooking Food Cafeteria for paid services | 24x7 medical facility (on-call doctor), housekeeping services, | 12,000-18,000 |
| Hostels | Bed, study table and cupboard Sharing rooms | Double Sharing room Availability of security guard, CCTV coverage | Pick or drop services | 12,000-20,000 | |
Students from higher-income families often pay more for value-added services, especially those enrolled in high-end HEIs (such as DIT and UPES) in affluent city areas. These students, typically pursuing degrees in MBA, law, and engineering, prefer rental accommodations that offer both luxury and convenience, enabling them to share flats with peers while enjoying freedom from restrictive rules. Gender-wise, female students prioritise privacy and security, opting for accommodations with better safety measures and pick-and-drop services, and are willing to pay a premium for these features. They also show a keen interest in facilities such as gyms and cafeterias. On the other hand, male students tend to prioritise recreational amenities like game rooms and gym facilities in their housing choices. Additionally, exam aspirants are willing to pay more for accommodations conveniently located near coaching centres and libraries or that offer dedicated study areas, underscoring the importance of location and study-friendly environments in their decision-making process.
Importance-performance analysis- NeighbourhoodTo investigate how students perceive the priorities of importance and performance levels of the neighbourhood and housing factors, using the IPA framework. the importance and performance rating of each attribute were calculated at the neighbourhood level and at the housing level. Figure 3 shows the gap between the most important level and the most satisfactory level of the attributes by the respondents at the neighbourhood level. Based on c responses and their analysis,
Table 6 gives the responses on a scale based on perceived importance and satisfaction. The table enables the respondents to understand each attribute. N1 (Safety in Neighbourhood), which indicates the safety factor of the neighbourhood, was marked as most important by 70.9% of the respondents. In comparison, only 45.3% were mostly satisfied with the safety in the locality they were living in. Similarly, it can be read for other attributes. Among the other nine attributes, N7 Facilities in a locality, like libraries, photocopy shops, and stationery and convenience shops, have a gap of 20.4% between the most important and most satisfied. Meanwhile, other attributes also had this gap of more than 10% except the N4, which took the perception of having friends in the society for their social needs.
| S.No | Code | Perceived Importance | Perceived Satisfaction | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 5 | 4 | 3 | 2 | 1 | 5 | 4 | 3 | 2 | 1 | |||
| 1 | N1 | N | 299 | 73 | 36 | 6 | 8 | 191 | 126 | 67 | 22 | 16 |
| % | 70.9 | 17.3 | 8.5 | 1.4 | 1.9 | 45.3 | 29.9 | 15.9 | 5.2 | 3.8 | ||
| 2 | N2 | N | 205 | 126 | 58 | 22 | 11 | 157 | 108 | 81 | 50 | 26 |
| % | 48.6 | 29.9 | 13.7 | 5.2 | 2.6 | 37.2 | 25.6 | 19.2 | 11.8 | 6.2 | ||
| 3 | N3 | N | 177 | 148 | 71 | 14 | 12 | 100 | 122 | 118 | 56 | 26 |
| % | 41.9 | 35.1 | 16.8 | 3.3 | 2.8 | 23.7 | 28.9 | 28.0 | 13.3 | 6.2 | ||
| 4 | N4 | N | 166 | 100 | 93 | 40 | 23 | 134 | 93 | 79 | 58 | 58 |
| % | 39.3 | 23.7 | 22 | 9.5 | 5.5 | 31.8 | 22.0 | 18.7 | 13.7 | 13.7 | ||
| 5 | N5 | N | 162 | 137 | 61 | 34 | 28 | 105 | 103 | 105 | 60 | 49 |
| % | 38.4 | 32.5 | 14.5 | 8.1 | 6.6 | 24.9 | 24.4 | 24.9 | 14.2 | 11.6 | ||
| 6 | N6 | N | 210 | 111 | 60 | 16 | 25 | 133 | 106 | 113 | 35 | 35 |
| % | 49.8 | 26.3 | 14.2 | 3.8 | 5.9 | 31.5 | 25.1 | 26.8 | 8.3 | 8.3 | ||
| 7 | N7 | N | 227 | 102 | 68 | 16 | 9 | 141 | 118 | 106 | 39 | 18 |
| % | 53.8 | 24.2 | 16.1 | 3.8 | 2.1 | 33.4 | 28.0 | 25.1 | 9.2 | 4.3 | ||
| 8 | N8 | N | 172 | 109 | 99.0 | 27 | 15 | 126 | 117 | 105 | 40 | 34 |
| % | 40.8 | 25.8 | 23.5 | 6.4 | 3.6 | 29.9 | 27.7 | 24.9 | 9.5 | 8.1 | ||
| 9 | N9 | N | 193 | 131 | 66 | 19 | 13 | 128 | 123 | 97 | 45 | 29 |
| % | 45.7 | 31.0 | 15.6 | 4.5 | 3.1 | 30.3 | 29.1 | 23.0 | 10.7 | 6.9 | ||
| 10 | N10 | N | 159 | 121 | 95 | 28 | 19 | 113 | 99 | 129 | 54 | 27 |
| % | 37.7 | 28.7 | 22.5 | 6.6 | 4.5 | 26.8 | 23.5 | 30.6 | 12.8 | 6.4 | ||
A deeper insight into Table 6’s data reveals that N2, N3, N4, N5, and N9 had more than a 10% difference between importance and satisfaction, indicating a significant gap. This gap was based on responses scoring 5 and 3 on the importance and satisfaction scale, highlighting a clear mismatch between expectations and supply in the student housing market. IPA literature suggests evaluating ratings for importance and satisfaction. Table 7 shows the standardized means and standard deviation (S.D.) for importance and satisfaction, indicating which quadrant the attributes fall into in the IPA graph, as illustrated in Figure 4.
| S.No | Attributes | Perceived Importance | Perceived Satisfaction | Quadrant | |||
|---|---|---|---|---|---|---|---|
| Mean | S.D. | Mean | S.D. | No. | |||
| 1 | N1 | 4.54 | 0.86 | 4.11 | 1.05 | I | |
| 2 | N2 | 4.17 | 1.02 | 3.78 | 1.23 | I | |
| 3 | N3 | 4.11 | 0.98 | 3.54 | 1.16 | IV | |
| 4 | N4 | 3.83 | 1.21 | 3.48 | 1.39 | III | |
| 5 | N5 | 3.89 | 1.19 | 3.41 | 1.3 | III | |
| 6 | N6 | 4.12 | 1.14 | 3.67 | 1.21 | I | |
| 7 | N7 | 4.24 | 0.99 | 3.79 | 1.13 | I | |
| 8 | N8 | 3.95 | 1.09 | 3.64 | 1.23 | III | |
| 9 | N9 | 4.13 | 1.02 | 3.69 | 1.19 | I | |
| 10 | N10 | 3.9 | 1.11 | 3.54 | 1.2 | III | |
IPA sets priorities on two dimensions: importance and performance. The cutoff points between IPA quadrants were the means of importance and performance (Chen, Murphy et al., 2016). The values were later plotted on the two-dimensional matrix, the result of which was shown in Figure 4. The overall means of importance calculated was 4.09, and that for performance was 3.66.
Quadrant-wise interpretation suggests that the first quadrant, with both positive importance and positive student satisfaction responses, includes attributes such as safety in the locality, the neighbourhood environment, proximity to HEIs, and the availability of commercial facilities like photocopy shops, convenience stores, and markets for vegetables and fruits. These attributes perform relatively well and are tagged under “Keep up the good work.” The second quadrant, indicating low importance and high performance, scored no attributes in this range, meaning there was no overkill in Dehradun. Four attributes—having friends in the same area (N4), public transport facilities (N5), eateries within walking distance (N8), and grooming facilities nearby (N10)—scored as “low priority” on the IPA graph. To enhance student neighbourhood satisfaction in Dehradun, facility providers must focus on developing housing in affordable neighbourhoods.
Importance-performance analysis- HousingSimilarly, The gap in the demand and supply in terms of housing attributes is highlighted in Graph 5. Table 8 gives the percentage of responses on the scale for perceived importance and satisfaction. It can be observed here that the attributes have a relatively higher percentage of importance ranking than their satisfaction. This shows the need to improve the services by working on the listed attributes accordingly. At premises level, the study focused on 27 attributes. The performance of each attribute through the IPA graph can be summed up as follows:
Table 8 shows the standardised means for the importance and satisfaction for which the IPA was conducted for housing attributes and analysed on the two-dimensional matrix, the result of which was as shown in Figure 4
| S.No | Attributes | Perceived Importance | Perceived Satisfaction | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 5 | 4 | 3 | 2 | 1 | 5 | 4 | 3 | 2 | 1 | |||
| 1 | H1 | N | 236 | 107 | 56 | 9 | 14 | 146 | 113 | 94 | 38 | 31 |
| % | 55.9 | 25.4 | 13.3 | 2.1 | 3.3 | 34.6 | 26.8 | 22.3 | 9.0 | 7.3 | ||
| 2 | H2 | N | 135 | 133 | 98 | 33 | 23 | 123 | 114 | 90 | 50 | 45 |
| % | 32.0 | 31.5 | 23.2 | 7.8 | 5.5 | 29.1 | 27.0 | 21.3 | 11.8 | 10.7 | ||
| 3 | H3 | N | 269 | 83 | 42 | 7 | 21 | 184 | 83 | 61 | 36 | 58 |
| % | 63.7 | 19.7 | 10.0 | 1.7 | 5.0 | 43.6 | 19.7 | 14.5 | 8.5 | 13.7 | ||
| 4 | H4 | N | 215 | 97 | 68 | 22 | 20 | 150 | 79 | 78 | 40 | 75 |
| % | 50.9 | 23.0 | 16.1 | 5.2 | 4.7 | 35.5 | 18.7 | 18.5 | 9.5 | 17.8 | ||
| 5 | H5 | N | 217 | 94 | 64 | 20 | 27 | 164 | 76 | 76 | 42 | 64 |
| % | 51.4 | 22.3 | 15.2 | 4.7 | 6.4 | 38.9 | 18.0 | 18.0 | 10.0 | 15.2 | ||
| 6 | H6 | N | 262 | 106 | 38 | 8 | 8 | 162 | 110 | 71 | 44 | 35 |
| % | 62.1 | 25.1 | 9.0 | 1.9 | 1.9 | 38.4 | 26.1 | 16.8 | 10.4 | 8.3 | ||
| 7 | H7 | N | 258 | 85 | 43 | 19 | 17 | 143 | 79 | 73 | 57 | 70 |
| % | 61.1 | 20.1 | 10.2 | 4.5 | 4.0 | 33.9 | 18.7 | 17.3 | 13.5 | 16.6 | ||
| 8 | H8 | N | 306 | 75 | 28 | 7 | 6 | 201 | 100 | 67 | 35 | 19 |
| % | 72.5 | 17.8 | 6.6 | 1.7 | 1.4 | 47.6 | 23.7 | 15.9 | 8.3 | 4.5 | ||
| 9 | H9 | N | 231 | 109 | 57 | 11 | 14 | 156 | 94 | 81 | 47 | 44 |
| % | 54.7 | 25.8 | 13.5 | 2.6 | 3.3 | 37.0 | 22.3 | 19.2 | 11.1 | 10.4 | ||
| 10 | H10 | N | 279 | 91 | 34 | 9 | 9 | 194 | 97 | 76 | 25 | 30 |
| % | 66.1 | 21.6 | 8.1 | 2.1 | 2.1 | 46.0 | 23.0 | 18.0 | 5.9 | 7.1 | ||
| 11 | H11 | N | 95 | 97 | 124 | 61 | 45 | 79 | 73 | 103 | 67 | 100 |
| % | 22.5 | 23.0 | 29.4 | 14.5 | 10.7 | 18.7 | 17.3 | 24.4 | 15.9 | 23.7 | ||
| 12 | H12 | N | 230 | 107 | 61 | 20 | 4 | 120 | 108 | 92 | 46 | 56 |
| % | 54.5 | 25.4 | 14.5 | 4.7 | 0.9 | 28.4 | 25.6 | 21.8 | 10.9 | 13.3 | ||
| 13 | H13 | N | 165 | 104 | 98 | 29 | 26 | 114 | 107 | 101 | 44 | 56 |
| % | 39.1 | 24.6 | 23.2 | 6.9 | 6.2 | 27.0 | 25.4 | 23.9 | 10.4 | 13.3 | ||
| 14 | H14 | N | 152 | 121 | 93 | 33 | 23 | 106 | 105 | 96 | 50 | 65 |
| % | 36.0 | 28.7 | 22.0 | 7.8 | 5.5 | 25.1 | 24.9 | 22.7 | 11.8 | 15.4 | ||
| 15 | H15 | N | 255 | 97 | 48 | 11 | 11 | 140 | 96 | 78 | 53 | 55 |
| % | 60.4 | 23.0 | 11.4 | 2.6 | 2.6 | 33.2 | 22.7 | 18.5 | 12.6 | 13.0 | ||
| 16 | H16 | N | 250 | 114 | 40 | 9 | 9 | 143 | 92 | 87 | 50 | 50 |
| % | 59.2 | 27.0 | 9.5 | 2.1 | 2.1 | 33.9 | 21.8 | 20.6 | 11.8 | 11.8 | ||
| 17 | H17 | N | 223 | 94 | 69 | 19 | 17 | 138 | 78 | 75 | 50 | 81 |
| % | 52.8 | 22.3 | 16.4 | 4.5 | 4.0 | 32.7 | 18.5 | 17.8 | 11.8 | 19.2 | ||
| 18 | H18 | N | 234 | 88 | 53 | 23 | 24 | 128 | 91 | 80 | 58 | 65 |
| % | 55.5 | 20.9 | 12.6 | 5.5 | 5.7 | 30.3 | 21.6 | 19.0 | 13.7 | 15.4 | ||
| 19 | H19 | N | 271 | 95 | 35 | 12 | 9 | 170 | 108 | 76 | 35 | 33 |
| % | 64.2 | 22.5 | 8.3 | 2.8 | 2.1 | 40.3 | 25.6 | 18.0 | 8.3 | 7.8 | ||
| 20 | H20 | N | 229 | 99 | 55 | 25 | 14 | 136 | 91 | 82 | 48 | 65 |
| % | 54.3 | 23.5 | 13.0 | 5.9 | 3.3 | 32.2 | 21.6 | 19.4 | 11.4 | 15.4 | ||
| 21 | H21 | N | 144 | 115 | 99 | 28 | 36 | 93 | 102 | 95 | 63 | 69 |
| % | 34.1 | 27.3 | 23.5 | 6.6 | 8.5 | 22.0 | 24.2 | 22.5 | 14.9 | 16.4 | ||
| 22 | H22 | N | 123 | 115 | 119 | 31 | 34 | 71 | 78 | 88 | 71 | 114 |
| % | 29.1 | 27.3 | 28.2 | 7.3 | 8.1 | 16.8 | 18.5 | 20.9 | 16.8 | 27.0 | ||
| 23 | H23 | N | 146 | 140 | 82 | 33 | 21 | 89 | 87 | 98 | 59 | 89 |
| % | 34.6 | 33.2 | 19.4 | 7.8 | 5.0 | 21.1 | 20.6 | 23.2 | 14.0 | 21.1 | ||
| 24 | H24 | N | 173 | 110 | 85 | 28 | 26 | 87 | 83 | 82 | 58 | 112 |
| % | 41.0 | 26.1 | 20.1 | 6.6 | 6.2 | 20.6 | 19.7 | 19.4 | 13.7 | 26.5 | ||
| 25 | H25 | N | 101 | 102 | 108 | 58 | 53 | 75 | 68 | 100 | 64 | 115 |
| % | 23.9 | 24.2 | 25.6 | 13.7 | 12.6 | 17.8 | 16.1 | 23.7 | 15.2 | 27.3 | ||
| 26 | H26 | N | 114 | 106 | 104 | 51 | 47 | 92 | 88 | 82 | 68 | 92 |
| % | 27.0 | 25.1 | 24.6 | 12.1 | 11.1 | 21.8 | 20.9 | 19.4 | 16.1 | 21.8 | ||
| 27 | H27 | N | 139 | 141 | 95 | 30 | 17 | 95 | 113 | 97 | 59 | 58 |
| % | 32.9 | 33.4 | 22.5 | 7.1 | 4.0 | 22.5 | 26.8 | 23.0 | 14.0 | 13.7 | ||
| S.No | Attributes | Importance | Satisfaction | Quadrant | ||
|---|---|---|---|---|---|---|
| Mean | S.D. | Mean | S.D. | No | ||
| 1 | H1 | 4.29 | 1 | 3.75 | 1.21 | I |
| 2 | H2 | 3.78 | 1.14 | 3.55 | 1.29 | II |
| 3 | H3 | 4.36 | 1.06 | 3.74 | 1.42 | I |
| 4 | H4 | 4.11 | 1.14 | 3.47 | 1.48 | I |
| 5 | H5 | 4.08 | 1.19 | 3.59 | 1.46 | I |
| 6 | H6 | 4.44 | 0.88 | 3.79 | 1.27 | I |
| 7 | H7 | 4.3 | 1.08 | 3.43 | 1.46 | II |
| 8 | H8 | 4.59 | 0.08 | 4.04 | 1.17 | I |
| 9 | H9 | 4.27 | 1.01 | 3.67 | 1.34 | I |
| 10 | H10 | 4.48 | 0.89 | 3.98 | 1.21 | I |
| 11 | H11 | 3.33 | 1.27 | 2.96 | 1.42 | III |
| 12 | H12 | 4.28 | 0.94 | 3.49 | 1.34 | I |
| 13 | H13 | 3.84 | 1.2 | 3.44 | 1.34 | II |
| 14 | H14 | 3.84 | 1.16 | 3.34 | 1.38 | III |
| 15 | H15 | 4.36 | 0.97 | 3.52 | 1.39 | I |
| 16 | H16 | 4.4 | 0.9 | 3.55 | 1.37 | I |
| 17 | H17 | 4.16 | 1.1 | 3.35 | 1.51 | IV |
| 18 | H18 | 4.16 | 1.18 | 3.39 | 1.44 | IV |
| 19 | H19 | 4.44 | 1.91 | 3.85 | 1.25 | I |
| 20 | H20 | 4.2 | 1.08 | 3.46 | 1.42 | I |
| 21 | H21 | 3.73 | 1.24 | 3.24 | 1.36 | III |
| 22 | H22 | 3.64 | 1.2 | 2.83 | 1.45 | III |
| 23 | H23 | 3.85 | 1.13 | 3.08 | 1.43 | III |
| 24 | H24 | 3.9 | 1.19 | 2.95 | 1.49 | III |
| 25 | H25 | 3.35 | 1.31 | 2.84 | 1.46 | III |
| 26 | H26 | 3.46 | 1.3 | 3.08 | 1.46 | III |
| 27 | H27 | 3.86 | 1.07 | 3.33 | 1.32 | III |
In Dehradun, the "Keep up the good work" quadrant featured a relatively higher number of attributes essential to student satisfaction. These include the cost of the room (H1), room facilities such as attached washrooms (H3), attached balconies (H4), and kitchens for cooking (H5). Other crucial features are good room ventilation (H6), high-speed Wi-Fi/LAN (H7), 24-hour water supply (H8), availability of hot water (H9), and electricity with backup (H10). Additionally, having food or mess facilities on the premises (H12), privacy from landlords (H15) and neighbors (H16), secure buildings (H19), and unrestricted entry and exit timings (H20) are vital. Continued investment in these areas is essential to maintaining student satisfaction.
The second quadrant, indicating potential overkill, included single occupancy or private rooms (H2) and living with friends in the same building (H13). These are of low importance, and students are relatively satisfied, suggesting that further investment or promotion may be unnecessary.
Attributes of low priority include air conditioning (H11), living with peers from the same academic stream (H14), common study areas (H21), indoor games rooms (H22), laundry facilities (H23), gyms (H24), common TV rooms (H25), guest common areas (H26), and housing recommendations (H27). Investment in these areas is currently a waste of resources.
For Dehradun students, security is a critical factor. Attributes needing more focus are the presence of a security guard (H17) and CCTV in common areas (H18), falling into the "concentrate here" quadrant.
This study is a premier contribution to the literature by applying Importance-Performance Analysis to Student Rental Housing (SRH). It is observed that the young tenants also give priority to overall wellbeing. The IPA results at both neighbourhood and housing level, gives valuable insights into the preferences and priorities of students.
Neighbourhood level:
The analysis identified several key attributes in the high-performing 1st quadrant, including the locality's safety, the neighbourhood environment, proximity to HEI, and the availability of commercial facilities such as photocopy shops, convenience stores, and markets for fresh produce. These attributes are performing well and should continue to be prioritised to maintain student satisfaction. For the neighbourhood, there were no high-performance attributes of low importance, and thus, no over-investment happened at the neighbourhood level.
The four low-priority quadrant attributes are critical for students and do not require immediate investment. These attributes include friends in the same locality and the availability of public transport or grooming facilities nearby. These results are significant because HEIs provide opportunities for students to socialise on campus, and modern technologies like social media maintain social connections. Since the survey was conducted in the Studentified zones, the students were living within walking distance of HEI and cities of the scale of Dehradun, which have compact urban layouts where walking and cycling are more convenient options for students. Facilities like eateries were also available on campus or just outside campus, and app services making these services convenient have made these factors a low priority for young tenants. In contrast, grooming facilities are not a daily need, while these facilities are also mostly available in university hubs in many cases.
However, to enhance overall student satisfaction at the neighbourhood level, it is crucial to focus on developing affordable housing options since it emerged as a significant concern (CITE)
Housing level:
The Importance-Satisfaction Analysis for SRH reveals critical insights for developing purpose-built student accommodations in India. High-priority attributes, such as the cost of the room, essential room facilities (attached washroom, balcony, kitchen), good ventilation, high-speed internet, and reliable utilities (24-hour water supply, hot water, electricity with backup), are essential for student satisfaction.
Additionally, the presence of food or mess facilities and ensuring privacy from landlords and neighbours are crucial for a positive living experience. Security emerged as a prime concern, with the presence of security guards and CCTV surveillance in common areas needing urgent enhancement. Conversely, attributes such as single occupancy, living with friends, air conditioning, and various social and recreational amenities (common study area, indoor games room, gym, common TV room, and guest areas) were deemed less critical by students, suggesting that resources allocated to these facilities at premises level may be better invested elsewhere. These findings underscore the importance of prioritising cost-effective, secure, and well-equipped living environments that cater to the primary needs of students, ensuring their comfort and safety while avoiding unnecessary expenditures on less effective features for student satisfaction. This focused approach can significantly improve the quality and appeal of student accommodations across India.
It also highlights how Purpose-Built Student Accommodation (PBSA) requirements can be strategised in the service industry. Developers and investors must, therefore, be more sensitive to the complex demands and preferences of the youth’s demand for student housing. A more comprehensive approach is currently being used in PBSA projects, giving equal weight to facilities that promote physical and mental well-being, privacy and security. Attached balconies enable much natural light, and communal living areas with amenities like kitchens and attached bathrooms are standard.
To further assist students in their academic pursuits, the supply of high-speed internet connectivity is required. Along with installing security features like CCTV surveillance and onsite guards, it creates a secure living.
The master plans must consider incorporating PBSA, which does not incorporate non-family residential zones. Therefore, there is a need to develop Special Residential Zones (SRZ) to cater to need-based housing.
Given the findings, the PBSA industry must focus on several key areas to meet student needs effectively:
The findings of this study have several policy implications for urban planners, HEIs, and housing developers. Policy initiatives should focus on creating affordable housing options near educational institutions, emphasising safety and a conducive living environment. Inclusivity in urban planning involves considering the findings from all four quadrants to formulate balanced policies that address immediate needs while avoiding overinvestment in less critical areas. Policymakers should adopt a holistic approach that strengthens infrastructure and services across all quadrants, setting priorities based on the importance and satisfaction level identified:
This study sheds light on students' housing preferences in Dehradun, India, providing valuable insights for urban planning and housing development. The young house hunters prioritise safety, affordability, and locational considerations. Hence, policymakers and developers should address the growing demand for student housing considering various attributes at the neighbourhood and housing levels. Various thoughtful approaches, such as PBSA, can be adopted to balance studentification and neighbourhood preservation, allowing cities to accommodate the rising student population while ensuring sustainable and vibrant urban environments.
A possible approach is to identify SRZs in the city master plan, placing them near HEIs with the necessary infrastructural needs of the student population. These areas would be designed with students' requirements in mind, providing a variety of PBSA developments along with auxiliary infrastructure, including eateries, recreational facilities, and public transit. While it is crucial simultaneously, it is difficult to identify the required densities of such areas in the neighbourhood and housing level to ensure a better quality of living. By concentrating student housing in designated areas, urban planners can foster a vibrant and cohesive student-centric environment with improved quality of living.
Defining suitable densities for PBSA developments and designated zones is a major difficulty for urban planners. Density criteria need to be reevaluated because, unlike conventional residential buildings, PBSA units usually permit higher occupancy rates per unit. Achieving sustainable and fair development requires striking a balance between providing sufficient living space for students and the effective use of urban land. Density planning is further complicated by differences in student demographics, preferences, and housing market dynamics, necessitating flexible and adaptive strategies.
For developers and investors, the PBSA offers a large market opportunity as the demand for student housing increases. PBSA developers must, therefore, investigate the aspects such as privacy, security, and amenities that promote both physical and mental well-being. In addition to improving the quality of life for students, innovation in the housing sector is needed. In addition, creating PBSA projects diversifies the housing market by providing other avenues for investment and preventing oversaturation in the conventional residential sectors. It offers the housing industry a transformative opportunity with its standardisation as in the hospitality industry, like Airbnb models, developers need to set standards for quality while making sure they are inclusive and financially sustainable for short-term rentals, which extend from six months to one year as in the case of student tenants. PBSA is a rising industry that influences market dynamics, investment strategies, and housing development trends.
While this study provides valuable insights into student housing preferences in Dehradun, it has some limitations. The sample size and the study's focus on a specific city may limit the generalizability of the findings. Future research can expand the scope to include a broader geographical area and a more diverse student population to enhance the study's applicability.
Future research can build on these findings to address the evolving needs of student populations in other educational hubs, contributing to the development of inclusive and student-friendly University towns. Where not just the HEI but also the private housing accommodations are positively developed to upgrade the quality of life.
Conceptualization: methodology, software, investigation.; resources; data curation.; writing—original draft preparation, DT.; writing—review and editing, DT and UKR supervision, UKR. All authors have read and agreed to the published version of the manuscript.
The authors declare that they have no conflicts of interest regarding the publication of the paper.
I sincerely wish to express my deep sense of gratitude to my supervisor Dr. Uttam Kumar Roy, Associate Professor, Department of Architecture and Planning, Indian Institute of Technology, Roorkee for his able guidance, wholehearted cooperation, critical comments, and motivation in carrying out my comprehensive proposal and presentation. I express my indebtedness to the journal for
