Eoghan Ciaran McHugh, Birmingham Business School, University of Birmingham
Rural brick-and-mortar retail accessibility in Wales is relatively limited. The adoption of online shopping broadens rural retailing accessibility to levels that are almost on a par with that in more densely populated areas. This article compares the online purchasing frequency of residents in selected Welsh rural and urban settlements, contributing to academic research examining rural online shopping. This study is important as use of the internet can aid residents of rural communities in overcoming time and distance constraints; rural online shoppers in the UK represent an important segment for retailers, and an equally important area of consumer behaviour for research.
Data collection was conducted through the use of quantitative questionnaires. A comparison of the results of both rural and urban respondents reveals that residents of rural settlements do not complete more purchases online than residents of urban settlements. Respondents in both rural and urban settlements shop equally online and through brick-and-mortar retailing. This study found that online shopping frequency is not affected by location; this furthers understanding of the impact the internet can have on rural consumer behaviour, contributing to the design of future marketing strategies.
Keywords: Brick-and-mortar retail, consumer behaviour, online shopping, rural settlements, urban settlements, Wales.
The availability of brick-and-mortar retailing is relatively limited in rural Wales. The proliferation of online shopping introduces a new purchasing channel which can reduce rural marginalisation stemming from accessibility limitations (Liu et al., 2011). There is a lack of research examining rural online shopping adoption in academic literature (Jensen, 2012; Lennon et al., 2009). Rural consumer history is steeped in both catalogue shopping and out-shopping due to limited local retailing accessibility (Ashley-Cotleur et al., 2009; Broekemier and Burkink, 2004), with some researchers (Lennon et al., 2009; Lokken et al., 2003) arguing that rural online shopping is an extension of these two substitutes.
A partnership between the Welsh government and British Telecom announced that by 2015 96% of Wales will have high-speed broadband (Superfast-Wales.com, 2013). With these improvements the Welsh government is aiming to position itself at the forefront of the global digital economy and is also promoting Wales as a great place to live, work, invest and visit (WelshGov, 2013). The Welsh government recognises that the internet can minimise rural marginalisation and improve rural quality of life (Broersma, 2013). Researchers (Lennon et al., 2009) have found that the internet can eliminate, or provide the potential to eliminate, rural marginalisation by reducing time or space constraints.
Only limited research examining online shopping in rural areas exists (Lui et al., 2011). Previous studies examining rural online shopping have found that rural Americans were the highest online shoppers of any segments (Hitwise, 2004), with Lennon et al. (2009) reporting that American rural consumers were 16% more likely to shop online than other consumers. Consumers in rural Wales are also more likely than their urban counterparts to shop online (Ping Wales, 2006). Understanding how the adoption of online shopping by rural consumers can contribute to their quality of life is an important topic to study (Lennon et al., 2007). This article addresses this largely ignored research problem, comparing residents of rural and urban settlements and examining how levels of consumer retail accessibility to brick-and-mortar retail influence consumer's choice regarding purchasing channels in Wales. This research will provide part of the basis for future research examining rural consumer retail accessibility and purchasing channel selection. Additionally, this research has marketing implications as approximately 19% of the UK's population lives rurally (Office of National Statistics, 2012). As this represents a significant amount of the population, marketers need to understand what barriers exist restricting rural consumers and what alternatives are available.
The article comprises four sections. Section one provides definitions, develops a literature review examining the key factors influencing rural settlements' adoption of the internet and online shopping, and setting research questions and hypothesis. Section two discusses the research methodology and methods. Section three presents the data analysis, comparing results from rural and urban settlements; finally, the article concludes with a discussion of these findings, research limitations, and suggestions for future research.
The UK's population in mid-2011 was approximately 56 million (Table 1); 46.3 million live in urban settlements while 9.8 million live rurally.
|Percent of population living rurally||18.9%||58%|
|Percent of population living in urban settlements||81.1%||42%|
The rural/urban definition used was developed by the Office of National Statistics (ONS). There are four settlement types:
- Urban: population exceeds 10,000;
- Town and fringe (Rural); population below 10,000;
- Village (Rural); smaller settlements with lower housing density than small towns;
- Hamlet (Rural); the very smallest settlements (Neil, 2008).
Additionally, accessibility is defined as 'the ability to get to, or be reached by, activities relevant to people seeking involvement in those activities' (Wayland et al., 2003: 41). In this article 'accessibility' refers to brick-and-mortar retail accessibility.
The literature review examines factors discouraging and encouraging the adoption of the internet in rural settlements. Lichy (2011) indicates that 'disparities in internet access may arise from a number of socio-demographic variables' (p. 470). These variables include limited employment/ lower wages, an older population, lack of IT familiarity/training, and limited broadband access.
Lack of well-paying or regular employment
Poor rural employment opportunities and lower-than-average wages have, historically, been regularly expressed themes amongst researchers (Gilbert et al., 2001; Cloke et al., 1997; Jones 1993). Employment in rural areas tends to be both low paid and seasonal or part-time.
The lack of rural employment opportunities results in employers paying staff lower-than-average wages (Jenkins et al., 1962), a point further validated by Gilbert and colleagues (2001) who note that rates of rural poverty in the UK are significant. Glyn-Jones (1979) reported that agriculture accounts for only 2% of rural employment with agricultural incomes declining in the UK by as much as 50% (Whatmore et al., 1991). Self-employment is very important in rural Wales, stemming from a persistent lack of employment opportunities (Cloke et al., 1997). Jones (2004) succinctly summarised the persistent rural/ wage dilemma: 'sectors associated with low pay are over-represented in rural areas' (p. 227).
Average older population in rural areas
The average age of rural populations tends to be older than the average age in urban settlements (Wayland, 2003). In 2001 40% of Wales's rural population was over 50 (Jones 2004). This is significant as studies examining technology adoption have determined that as people age they are less likely to accept new technology such as the internet and online shopping (Naseri and Elliot, 2011; Lokken et al., 2003).
Less IT training
Many rural firms are locally owned and/or managed, younger, and smaller with many enterprises less inclined to keep abreast of current business-training trends (Webber et al., 2009). Deakins and colleagues (2003) found that 86% of rural firms did not wish to grow. Rural workplaces in Wales have less continuous training or opportunities to update skills (Jones, 2004). This relates to online shopping as studies indicate that consumers possessing a lower level of computer skills are less likely to shop online (Chung et al., 2010).
Limited broadband access
The distribution of rural populations covers large areas affecting broadband efficiency. In 2010 average broadband speeds were slower rurally compared to urban areas with higher proportions of rural households reporting no broadband signal (Pateman 2011). Hill (2002) suggests that broadband access/speeds differ as the costs involved with installing and maintaining internet exchanges exceeds potential profits in areas where population densities are lower and have fewer end customers.
Limited access to rural shops and services
Rural public transport is scarce, if it exists at all (Jones, 2004). Rural authorities face transport challenges as operating costs increase and customer demand decreases (Liddle et al., 2012). Nutley (1983) revealed that 12% of the population is fully dependent on public transport, 33% of the population are partially dependent on public transport, and vehicle owners make more trips than non-owners. Research has found that distance from retail stores is positively related to online shopping (Lennon et al., 2009).
Rural businesses in 2001 totalled only one third of what had existed in 1985 (Hill, 2003), with approximately 75% of rural settlements in the UK lacking a general and/or village shop (Paddison and Calderwood, 2007). Rural residents report they face impoverished retail choice, higher prices, and poorer quality (Lee et al., 2009).
The likelihood of rural settlements adopting online shopping is quite high (Liu et al., 2011; Johnson et al., 2003), with research by Lennon and colleagues (2009) indicating that rural consumers have more positive attitudes toward online shopping than urban consumers. Additionally, as rural brick-and-mortar retail options decline some rural consumers may have less access to important goods in their communities (Lennon et al., 2007). The ability to connect and order products online may be beneficial, particularly for consumers who are far from stores, are ageing, or are housebound (Liu et al., 2011).
H1: When compared to residents of urban settlements the percentage of residents in rural Welsh settlements shopping online will be higher.
H2: Due to limited rural retailing accessibility, people in rural settlements shop online as a primary shopping channel for products not available through brick-and-mortar retailing.
In order to investigate the hypotheses, data was collected using quantitative research methods. Questionnaires were deemed to be the most expedient and efficient research instrument and were developed, with 20 questions divided into three sections examining three important dimensions positively associated with online shopping adoption:
- Participant demographics;
- Internet accessibility;
- Internet usage (Santana and Loureiro, 2010; Brashear et al., 2009).
There are several demographic factors linked with online shopping adoption: gender (Helsper, 2010), age (Chung et al., 2010), education (Liu et al., 2011), and employment (Brashear et al., 2009). Several studies indicate that men are more likely than women to shop online and that internet users are younger with higher incomes (Naseri and Elliot, 2011; Amanor-Boadu, 2009; Brashear et al., 2009).
Internet accessibility is critical to online shopping, as is familiarity with the internet (Helsper 2010). Familiarity is gained through general internet use, such as communication (social media, email), media (iPlayer, YouTube, news) and household functions (e-banking, paying bills online) (Lennon et al., 2009).
Finally, the questionnaire examines respondents' opinions towards online shopping and shopping within their communities. This section measures why consumers shop online; products not available locally (Ping Wales, 2006), greater selection (Teo, 2006), consumer accessibility to traditional-retailing (Brashear et al., 2009; Lennon et al., 2007), convenience (Gehrt et al., 2007), lower prices (McEachern and Warnaby, 2008), and greater information available (Jensen, 2012). Progressing from why consumers purchase online it is important to probe online shopping frequency, additionally questioning how many of the respondents' last five purchases were made online. What would dissuade consumers from shopping online is also an important area to understand; this may be because local product availability is satisfactory (Lokken et al., 2003), it is important to consumers to support local retail (Liu and Forsythe, 2010), they may distrust online shopping (Ramachandran et al., 2011), they have privacy concerns (Riemenschneider et al., 2009), or they prefer out-shopping (Rajamma and Neeley, 2005). The availability of transport, whether private or provided by the community, is linked to both brick-and-mortar accessibility and receptiveness towards online shopping. Lastly, it is important to understand why consumers prefer traditional retailing; they can see and touch products (Amanor-Boadu, 2009), and they can consult shop staff (Broekemier and Burkink, 2004).
Statements 2-5, 7, 11, and 12 had response ranges from four to six points. Statements 9, 10, 13-17, 19 and 20 had five-point responses. Regarding these latter statements, selecting '1' indicated participants did not agree while responding '5' demonstrated full agreement. Statements 1, 6, 8, and 18 had only two responses.
The research instrument was pre-tested, testing for question accuracy, respondents' ease comprehending the questionnaire, that the answers available were applicable to the questions asked, and researcher suggestiveness or bias. Pre-testing feedback indicated that the questionnaire was fit to use. As part of the process for completing the dissertation the research, research instrument and research methods were approved by an independent research board.
Three research sites were selected to capture data, providing evidence of distinct qualities when comparing rural and urban settlements and online shopping (see below). The researcher travelled to each site to collect data from residents of the selected settlements. Residents were approached in public places. The author introduced himself, where from, the research purpose, if the candidate lived in the settlement, and then asked if they would be willing to participate. That respondents lived within the settlement was critical to the analysis so results from each settlement could be accurately compared looking for particular patterns or beliefs proving or disproving the hypothesis. The researcher's supervisor advised that collecting twenty responses from each settlement was sufficient to compare rural and urban opinions regarding online shopping.
Community Profile and Context
The following section describes the specific research sites selected and why.
Site A: Llandeilo (Rural Settlement without Amenities/Services)
Distance from urban settlement:
15.1 miles from Carmarthen
23.8 miles from Swansea
62.1 miles from Cardiff
Public transport accessibility: bus and train (Llandeilo.gov.uk; Llandeilo.org)
Llandeilo does not offer post-secondary education or feature other major institutions which might attract outside solicitation and directly increase the influence any part-time residents could have on full-time residents regarding the adoption of online shopping. Over 75% of Llandeilo's residents live and work in the same rural authority (Jones, 2004).
Site B: Cardigan (With Services/Amenities)
Distance from urban settlement:
26.1 miles from Carmarthen
38.8 miles from Aberystwyth
94.5 miles from Cardiff
Public transport accessibility: Bus (tourism.ceredigion.gov.uk)
Cardigan is considered a rural settlement, but also has established infrastructure which draws people (i.e. a hospital, large supermarket, and college). Additionally, Cardigan is a popular tourist destination (visitcardigan.com). The demands from fluctuating and diverse numbers of visitors increases pressure on Cardigan to provide at least some of the brick-and-mortar retailing options found in larger settlements. Full-time citizens might also come to expect product accessibility due to the influence of visitors from other areas.
Site C: Cardiff (Urban Settlement)
Population 346,100 (Larger Urban Zone estimated 861,400)
Cardiff is Wales' largest city and its capital (Cardiff.gov.uk). In addition to a very diverse population Cardiff also caters to a healthy tourism industry, with over 18 million visitors in 2010 (Cardiff.gov.uk). Cardiff was chosen as the comparison urban site in determining whether location has any impact on consumers' choice of purchasing channel.
Table 2 reports the demographic breakdown for each category across all sixty participants.
|Questionnaire Statement||Highest Percentage from Respondents|
|Education||35% Degree Level Educated|
|Employment||43.3% Full Time Employment|
|Number of Jobs||53.3% One Job|
|Participate in Local Community Events||41.7% Sometimes Participate|
|Internet Access||96.7% Have Access|
|Shop Online||90% Yes|
Table 3 reports each site's results. Each site reported high internet accessibility rates. Internet use is a fairly regular aspect in each site, with respondents reporting that they spent several hours weekly using the internet for a number of functions. Respondents in each site revealed that a relatively high number had shopped online.
The majority of respondents from Site A and B shopped online because products were not available locally. Respondents from Site C said that products bought online were also available to purchase through traditional retailing. Both rural settlements felt there was a greater selection online. Respondents from Site C, however, disagreed with this statement. Regarding greater convenience, both rural settlements agreed it was more convenient to shop online while Site C reported 'somewhat agree' and 'agree' equally. Statement 9, which questioned why respondents shop online, showed that residents of both rural settlements shared similar reasons for shopping online compared with reasons why residents of the urban settlement shopped online.
Probing the frequency of online shopping among respondents (statement 11) indicated that residents of both rural settlements only shopped online monthly while Site C's respondents shopped online several times weekly. While Cardiff residents described traditional retailing accessibility being high with greater selection, they shopped online more frequently than those from Sites A and B. Additionally, the results of statement 12 showed that Site C, again, used the internet the most to complete purchases. Residents of Site A had not used the internet to make any of their last five purchases. Site A's data collection was on a Saturday during a Wales v England rugby match for the Six Nations tournament. Many respondents noted that they were making the most of the day with a pervasive, celebratory atmosphere in the settlement. As a result, responses from Site A may not be typical. The research undertaken in Site B, however, was conducted on a non-event day and the results showed that the majority of respondents from this site had made only one of their last five purchases online. Site C, the urban settlement, had the highest rate of online purchasing, with 20% of purchases being made online.
Respondents from each site reported that if everything they needed and wanted was available both locally and online, they would prefer to purchase locally. The site with the highest majority, Site B, reported only 35% of respondents felt they should shop locally to support their community. The majority of respondents from all sites revealed they somewhat disagreed with the statement that they did not trust online shopping. Internet security concerns have eased with more frequent use and greater security protection available (Gehrt et al., 2007). At each site, the majority of respondents agreed that maintaining their privacy was a concern for them conducting activities online.
|Questionnaire Statement||Site A: Llandeilo
(Rural Settlement): Highest Reported Percentage
|Site B: Cardigan
(Rural Settlement): Highest Reported Percentages
|Site C: Cardiff
(Urban Settlement): Highest Reported Percentage
|1. Gender||55% Female||55% Male||60% Male|
|2. Age Group||25% 36-45 Years old/ 25% 56-65 years old||30% 46-55 Years old||40% 26-35|
|3. Education||35% Degree educated||35% Degree educated||40% Degree educated|
|4. Employment||40% Full time employment||50% Full time employment||40% Full time employment|
|b. Number of Jobs||45% One job||65% One job||50% One job|
|5. Participate in Local Community Events||50% Sometimes||40% Sometimes||35% Sometimes|
|6. Internet Access||100% Have access||95% Have access||95% Have access|
|7. Weekly Internet Use:|
|a. Social Networking||45% Less than 5 hours||40% 11-15 hours||30% Less than 5 hours/ 30% 5-10 hours|
|b. Accessing Media||30% Less than 5 hours/ 30% 11-15 hours||30% 5-10 hours/ 30% 20+ hours||50% 5-10 hours|
|c. Household Related||75% 5-10 hours||70% 5-10 hours||75% Less than 5 hours|
|8. Shop Online||90% Have shopped online||95% Have shopped online||85% Have shopped online|
|9. Shop Online Because:|
|a. Products Not Available Locally||45% Somewhat agree||35% Agree||50% Somewhat disagree|
|b. Greater Online Selection||55% Agree||50% Agree||35% Somewhat agree|
|c. Shop Distance Too Great||25% Do not know/ 25% agree||40% Agree||30% Somewhat disagree|
|d. Convenience||75% Agree||60% Agree||35% Somewhat agree/ 35% agree|
|e. Cheaper Online||45% Agree||60% Agree||40% Somewhat agree|
|f. More Information Online||25% Agree||45% Agree||30% Do not know|
|10. Mainly Purchase:|
|a. Electronic Goods||30% Purchased electronic goods mostly||30% Purchased electronic goods mostly||25% Purchased electronic goods mostly|
|b. Clothing||35% Purchased clothing goods mostly||20% Purchased clothing goods mostly||30% Purchased clothing goods mostly|
|c. Household||40% Purchased household goods mostly||25% Purchased household goods mostly||25% Purchased household goods mostly|
|11. Online Shopping Frequency||30% Purchase monthly||30% Purchase monthly||30% Purchase a few times weekly|
|12. Amount of Previous Shop Online||25% None of last 5 purchases||30% One of last 5 purchases has been online||25% 2 of last 5 purchases made online|
|13. Online Purchase Satisfaction||45% Somewhat agree||55% Somewhat agree||55% Somewhat agree|
|14. Products Not Available Locally||35% Agree||40% Agree||50% Somewhat disagree|
|15. Can Find Products Locally, but:|
|a. More Enjoyable to Shop Online||25% Somewhat disagree||30% Somewhat disagree||30% Do not know|
|b. Wider Selection Online||35% Somewhat agree||45% Somewhat agree||40% Somewhat agree|
|c. Better Prices Online||50% Agree||45% Agree||30% Somewhat disagree/ 30% do not know/ 30% somewhat agree|
|16. Do Not Like Shopping Online Because:|
|a. Find Everything Locally||35% Disagree||35% Somewhat disagree||45% Somewhat disagree|
|b. Should Support Community||35% Somewhat agree||35% Somewhat agree||30% Somewhat agree|
|c. Distrust Online Shopping||25% Somewhat disagree||30% Somewhat disagree||40% Somewhat disagree|
|d. Privacy Concerns||35% Agree||45% Agree||45% Somewhat agree|
|e. Prefer Travelling to Bigger Districts||25% Disagree||35% Disagree||30% Somewhat disagree/ 30% somewhat agree|
|17. Municipal Transport||35% Do not know||30% Do not know||35% Somewhat agree|
|18. If Available, Purchase Channel Would Be||65% Locally||85% Locally||75% Locally|
|19. Local Shopping Satisfaction||45% Somewhat agree||35% Somewhat agree||35% Somewhat agree|
|20. Prefer Shopping In-store Because:|
|a. Physically See/ Touch Products||45% Agree||45% Somewhat agree||45% Somewhat agree|
|b. Consult Sales Staff||40% Agree||35% Agree||35% Somewhat disagree/ 35% somewhat agree|
Internet users are a complex audience; the internet informs users, it transforms users, and through the wealth of information online, it can also empower users (Segal, 2009). The proliferation of the internet has broadened new shopping opportunities (Thomas and Bromley, 2002), with online shopping transforming from an emerging channel into the shopping mainstream (Wan et al., 2012). Following is a discussion of the impact online shopping has had regarding residents online shopping in two Welsh rural settlements and comparing the results with an urban settlement to substantiate if a lack of brick-and-mortar accessibility influences consumers to rely more on online shopping.
Dillon and Reif (2004) discuss stereotypes that older generations do not shop online due to a lack of access and/or familiarity with technology. However, more recent studies are challenging these stereotypes (Gebauer et al., 2008). Anecdotally, while this research was being conducted many respondents discussed their use of the internet, demonstrating a firm grasp of the range of online activities available and many of the advantages and risks associated with internet use/shopping covered in this article. Those aged between 40 to 49 will benefit most from their online shopping experience (Liu et al., 2011) as this group has an optimal combination of traditional retailing and online shopping experiences (Gebauer et al., 2008). This age group is the first generation to be familiar with the internet and, also, to have the income to shop online (ibid).
McClosky (2006) reports that in the USA older generations are the fastest growing adaptors of the internet. Site A featured 25% of respondents between 56 and 65 years old, all of whom reported regular internet usage. This finding is consistent with Wan and colleagues (2012) who also reported greater numbers of older generations utilising the internet. Lam and Lee (2006) revealed that when older adults develop technological competencies and confidence the likelihood of them engaging with IT increases. Internet self-efficacy was a strong determinant of usage intention (Lam and Lee 2006). The sum of life experiences may also help older generations when purchasing online (Kelley and Charness 2009).
People who use the internet and are familiar with its functions would be more likely to use it for shopping (Xu and Paulins, 2005). Table 3 shows the majority of participants in this research have internet access and experience using the internet, and have purchased online. If consumers have positive attitudes towards the internet and online shopping it is likely they will purchase online more frequently (Wan et al., 2012; Lennon, 2009). Similar results have been reported by Ajzen (1985) and Ajzen and Fishbein (1980) who demonstrated that when someone holds a favourable or negative belief about an action or behaviour that belief can affect whether the person will choose to carry out that action or behaviour. Forsythe and colleagues (2006) concluded that 'heavy online shoppers perceived significantly greater benefits in terms of convenience and product selection' (p. 68).
Factors for Shopping Online
Rural consumers purchase products online which they cannot find, or do not like, in their local communities (Powe and Hart, 2009). This was reflected in both Site A and B where respondents stated they shopped online as products were not available locally (45% somewhat agree and 35% agree, respectively), there was greater selection online (55% of respondents in Site A agree and 50% of Site B's respondents agree), and brick-and-mortar retailing was too far to travel to (25% of Site A's respondents agree with 40% of Site B's agreeing). Comparing these answers with Site C, 50% of respondents disagreed that products were not available locally, only 35% somewhat agreed that there was more selection available online, and 30% somewhat disagreed that shops were too far away. The increased accessibility gained by residents of rural communities through the internet means while they recognise the limited brick-and-mortar retail accessibility they can use the internet to reduce the effects of rural marginalisation (Powe and Hart, 2009).
Forty-five percent of respondents in Site A, 55% in Site B, and 55% in Site C all somewhat agreed that they were satisfied with their online purchases. Only 65% of Site A's respondents reported that they would purchase locally were all their purchasing needs available locally, the lowest rate of all three sites. Could this despondency be related to a long-established acceptance that local product selection is limited?
Factors against Shopping Online
An intention to shop locally is positively associated with, and most strongly predicted by, consumer satisfaction regarding local brick-and-mortar retail (Lennon et al., 2009). Across all three sites the majority of respondents felt that they should shop locally to support their communities. While the research was being conducted many respondents expressed concern over what they felt were confused answers. Respondents said that supporting their community was important to them, but that it was not always possible as brick-and-mortar retailing satisfaction varied greatly product-to-product. It is likely that consumers enjoy both online and brick-and-mortar retailing (Lee et al., 2009).
Consumers have concerns when shopping online. Online fraud still represents a significant concern for internet users regardless of age (Wan et al., 2012). Regarding levels of trust and online shopping, residents of the rural settlement, Site A, had the highest levels of distrust and shopping online. The urban settlement, Site C, trusted online shopping the most. Security concerns are iterative as new technological developments result in new concerns/problems.
All three sites reported concerns about privacy and about having their personal information shared by companies online. However, those in Site A and B were more adamant in their demand for privacy. Even though some online shoppers perceive the internet as carrying high levels of risk, it does not mean they will stop shopping online (Liu and Forsythe, 2010). Further concern was expressed as products could not be directly inspected prior to purchasing and only limited communication with online retailers was possible (Wan et al., 2012).
The research results do not support the first hypothesis; online shopping does not occur more frequently in rural settlements when compared to an urban settlement. That the frequency of online shopping is not greater in rural settlements is similar to Xu and Paulins' (2005) findings. Additionally, people living in urban areas may still face brick-and-mortar retailing limitations depending on the availability of transport and other personal constraints such as time (Powe and Hart 2009).
Hypothesis two is supported; when compared with urban consumers, rural consumers shop online as a main purchasing channel due to relatively limited brick-and-mortar retailing in their local settlements. Site A and B indicated a limited amount of local shopping availability. Both sites agreed that there is greater selection online and that traditional retail shopping was too far to travel to. Respondents in Cardiff disagreed, indicating that products available online could also be purchased through brick-and-mortar retailers and consumer access to those retailers was not too difficult.
The internet has far exceeded its earlier role as just a new distribution channel (Siaw and Yu, 2004). The value of this research is through the contribution it makes to the small body of research examining online shopping amongst rural residents; the relationship between consumer location, retailing availability and accessibility, and the influence these two factors have on a consumer's choice of purchasing channel. Particularly, this research contributes further value in its comparison of rural and urban consumers. The internet's adoption in the UK is widespread. However, how consumers use the internet in either rural or urban settlements varies slightly. This study demonstrates that rural consumers use the internet to overcome any retailing limitations they feel present in their settlements. Rural consumers recognise the improved retail accessibility available online (Siaw and Yu, 2004). Understanding the influence these factors have on consumers and why particular consumer segments make the choices they do has significant strategic implications for marketing.
The internet makes the user and the user makes the internet (Segal, 2009). Rural consumers are able to utilise the internet to overcome an absence of traditional retailing. Residents of rural settlements do not shop online more frequently than consumers in urban settlements with greater traditional retail accessibility, but rural residents exhibit different motivations for shopping online than urban settlements.
While the research was being undertaken, concerns arose regarding the survey instrument's limited probing into participants' ability to access transport. Statement 17 queried the respondents' perception of municipal transport quality, failing to probe further about their access to privately owned transportation. Revisiting Cloke's (1984) research, car owners make more trips than non-owners. How well serviced a respondent's settlement is by municipal transport may be of no concern to them, as vehicle ownership can provide them with sufficient accessibility. This shortfall is now represented in the research.
The research and outcomes are limited by the depth of testing. Further analysis could have been conducted in the form of t-tests and correlation analysis providing a greater insight into whether the site-specific differences in respondents' answers were significant. This would have given the comparison between rural and urban settlements greater complexity. Another possible limitation is that research results may have been influenced by festivities occurring in one of the sites during data collection. Lastly, sample sizes used in this research may not accurately represent behaviour that is typical in these settlements.
Little is known about rural consumers' use of online shopping, whether satisfaction with local retailing affects rural consumers' online shopping preferences, or whether shopping outside the rural community is related to online shopping (Rajamma and Neeley, 2005; Broekemier and Burkink, 2004). Further research could continue examining the relationship between rural brick-and-mortar retailing and greater online accessibility. Specifically, research could delve further into rural motivation for online shopping and what types of items rural consumers are confident purchasing online (Santana and Loureiro, 2010).
Research for this study was conducted using only limited quantitative research methods; further research could be conducted using qualitative research to triangulate the study's findings. During data collection respondents shared anecdotes about their experiences with the internet which could not be captured, but with the limited body of research examining rural online shopping, exploratory research would be valuable to understand the various dimensions associated with technology engagement, such as age, education, technology uptake, and social influence.
Additional research could probe urban motivations for online shopping. Residents of urban settlements have greater accessibility to, and a wider selection of, brick-and-mortar retailing. Regarding the frequency that urban residents reported shopping online in this study more research could look at the factors driving urban online shopping.
This article has been re-invented from my undergraduate dissertation. I have received tremendous help from a number of people, including Kathryn James and Samuel Rule, in re-writing and re-formatting this piece to match the criteria of Reinvention. In addition, thank you to Reinvention and its editors for allowing undergraduates the opportunity to explore the academic process through publication.
Finally, I would like to dedicate this article to the memory of David Charles Parkinson.
List of tables
Table 1: Population figures
Table 2: Demographic responses of all respondents
Table 3: Questionnaire frequency responses
Part I- Participant Demographics
Please indicate the following details about yourself by selecting the information that best describes you:
- Age group:
A levels ☐
Degree educated ☐
Full time ☐
Part time ☐
- If you indicated that you are currently employed, how many jobs do you currently have?____
- I participate in local community events:
Almost Always ☐
Almost Never ☐
Part II- Internet Accessibility
- Internet access:
At home ☐
At work ☐
At school ☐
- Weekly internet use:
- Social networking (facebook, twitter, email, etc)
Less than 5 hours ☐
5-10 hours ☐
11-15 hours ☐
20+ hours ☐
- Access media (news reports, iplayer, etc)
Less than 5 hours ☐
5-10 hours ☐
11-15 hours ☐
20+ hours ☐
- Household related (online banking, bill payments, etc)
Less than 5 hours ☐
5-10 hours ☐
11-15 hours ☐
20+ hours ☐
- Social networking (facebook, twitter, email, etc)
- Do you, or have you, ever shopped online?
Part III- Internet Usage
Please read each of the following statements and indicate (by circling) the degree which this relates to you. Please provide an answer for each statement.
Disagree Somewhat Disagree Don't Know Somewhat Agree Agree
1 2 3 4 5
- I shop online because:
- Products are not available locally 1 2 3 4 5
- There is a greater selection online 1 2 3 4 5
- Shops are too far away 1 2 3 4 5
- Convenience 1 2 3 4 5
- Products are cheaper online 1 2 3 4 5
- More information available online 1 2 3 4 5
- I mainly purchase online:
- Electronic goods: 1 2 3 4 5
- Clothing: 1 2 3 4 5
- Household (not including food) 1 2 3 4 5
- I shop online:
A few times weekly ☐
Once a week ☐
Once a fortnight ☐
- Of my last five purchases (not including food), this many were online:
- I am satisfied with my online purchases: 1 2 3 4 5
- Products I buy online aren't available locally: 1 2 3 4 5
- I can find the products I want locally, but:
- More enjoyable to shop online 1 2 3 4 5
- Wider selection online 1 2 3 4 5
- Better prices online 1 2 3 4 5
- I don't like shopping online because:
- I can find everything locally 1 2 3 4 5
- I should shop locally to support my community 1 2 3 4 5
- I don't trust online shopping 1 2 3 4 5
- I don't want my details shared 1 2 3 4 5
- I prefer to travel to bigger shopping districts 1 2 3 4 5
- Municipal transport in my area is regular: 1 2 3 4 5
- If local selection of products was greater how would you purchase them?
a. Locally ☐
b. Online ☐
- I am satisfied with local shopping: 1 2 3 4 5
- I prefer shopping in store because:
- I can physically see and touch products 1 2 3 4 5
- I can ask questions and seek advice 1 2 3 4 5
 Eoghan McHugh graduated from the University of Wales, Trinity Saint David in 2013 with a First Class honours degree in Business Management. Currently, he is undertaking a masters in Strategic Marketing and Consultation at the University of Birmingham where his dissertation project will continue examining rural communities and accessibility provided through the internet.
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To cite this paper please use the following details: McHugh, E.C. (2014), 'Does Location Influence Consumer Behaviour?: Comparing Rural and Urban Use of Online Shopping in Wales', Reinvention: an International Journal of Undergraduate Research, Volume 7, Issue 1, http://www.warwick.ac.uk/reinventionjournal/archive/volume7issue1/mchugh/ Date accessed [insert date]. If you cite this article or use it in any teaching or other related activities please let us know by e-mailing us at Reinventionjournal at warwick dot ac dot uk.