Consumer Engagement and Experience in Unorganized Retail: Role of Modern Technology
Dr. Ritu Narang
Associate Professor
Department of Business Administration
University of Lucknow
Sonal Tiwari
Research Scholar
Department of Business Administration
University of Lucknow
Abstract
Improving customer experience and engagement has become a problem for organisations as customer expectations continue to rise. Faced with increased competition from organised retail, India's unorganised sector has sought to change its working practises in order to provide a better consumer experience. It is being believed that unorganised retail may benefit from the use of modern technology, which has enormous potential for enhancing consumer experience, customer engagement, and retail sales. Since technology for the purpose of customer experience entails usage by customers therefore, it becomes pertinent to understand their perceptions before investing resources in modern technology. The current study seeks to examine relationship between customer engagement, customer experience and smart retail technology in the context of unexplored unorganized retail sector. The results indicate a significant relationship between the three variables. This study has significant implications for unorganized retailers.
Keywords: Small business, Smart retail technology, Customer experience, Customer engagement, Retail, Technology
Introduction
India is not just the world's second most populous country, but also one of the world's most affluent and rapidly expanding economies (Sharma, 2016).Over the last decade, Indian retailing has transformed from a mainly unorganised and informal sector to a more corporatized business, at least in urban India(Kathuria & Jain, 2012).The rapid growth of internet, 4G, 5G, artificial intelligence, e-commerce has expanded the number of accessible shopping channels(Ailawadi & Farris, 2017) which include websites, mobile applications, physical stores, catalogues, call centres, and internet kiosks(Zhang, Ren, Wang, & He, 2018).Furthermore, retail technology has been enhanced due to the advancement ofAI, complex dataand various cutting-edge technologies. This has provided consumers with more product selections and information than before (André, et al., 2018).
Speedy expansion of online retailing is changing the rules of the game and forcing the merchants to come up with innovative concepts and goods to attract customers (Sengupta, 2008). This advancement has helped customers in finding and selecting the solutions that best meet their demands, allowing them to reduce their search expenses while increasing the value they get from their selections(Bakos, 1997; Lynch Jr & Ariely, 2000) .Offline retail, as a crucial practise of multi-channel marketing, is also an imperative touchpoint venue in customers' purchase journeys.Smart retail is being tested by retailers in attempt to deliver a smooth, integrated consumer experience(Fan, Ning, & Deng, 2020). As per a survey by McKinsey, smart technology is expected to yield a $6.2 trillion global economic effect by 2025, specifically in the retail business(Fan, Ning, & Deng, 2020). Studies point out that consumers are being pushed to use technology in their daily lives(such as the purchasing process) as their reliance on technology grows(Moriuchi, Landers, Colton, & Hair, 2021).Smart retail technology (SRT) advancements have the ability to improve consumer experience by improving firms' understanding of customers' buying habits and trends(Evans & Ghafourifar, 2019). Deploying smart/intelligent retail technology strategically at several critical consumer touch points may thus provide substantial benefits to businesses as well as an improvement in customer satisfaction(Ameen, Tarhini, Reppel, & Anand, 2021).
Enhancing customer experience and engagement has become a challenge for businesses as customer expectations continue to increase. Firms seeking a competitive advantage in customer service need to consider more than just delivering content at the appropriate moment through the right distribution channel. They have to develop innovative ways not only to minimise consumer pain points throughout the purchase process, but also to provide efficient customer service. Enhancing customer experience and engagement through technology could be one of the answers that will allow physical shops to not only attract, but also retain consumers (Sharma, 2016).
Subjected to increased competition from organized retail, India's unorganised sector has attempted to alter its working practises in order to deliver a better consumer experience, but it still has a long way to go. One probable explanation is that it has yet to completely accept contemporary technologies. Despite its greater control over resources and socioeconomic power, this sector remains larger in many crucial ways than the organised sector(Kabra, 2003). It is being believed that unorganised retail may profit from the use of contemporary technology, which has enormous potential for improving consumer experience, customer engagement, and retail sales. Since technology for the purpose of customer experience entail usage by customers so it is important to understand their perceptions before investing resources in modern technology. It may be pertinent to state that unorganised retail is characterized by limited stock with low pricing which attracts the masses.
As far as we know, till date no study has been conducted to evaluate the perceptions of consumers towards the use of smart retail technology (SRT) in enhancing customer experience and engagement in unorganised retail sector. To bridge this gap, the current study has been undertaken to find out consumers’ viewpoints towards role of SRT in increasing customer experience and engagement in unorganized apparel retailing. Research Objectives
The present study has the following objectives:
Literature Review
Retail Sector in India
The so-called "unorganised retail or traditional retail" in India is subjugated by a significant number of small retailers such as local general stores, clothing stores, owner-manned general stores, pharmacies, footwear store, and so on(Joseph, 2008). According to(Kathuria & Jain, 2012), traditional low-cost retailing forms, such as local ‘kirana' shops, owner-operated general stores, convenience stores, hand cart and pavement sellers, and so on, are referred to as unorganised retailing.
Kirana stores are similar to ‘mom and pop' shops in the West. A kirana store typically ranges in size from 25 to 400 square feet and offers a variety of product categories related to the everyday needs of the people. These categories include of labelled or unlabelled offerings such as coffee, tea, shampoos, edible oil, hair oils, grocery, rice and wheat, soaps, etc. Since the majority of the millions of kirana stores serve to the wide range of customers, they sell limited, popular, and low-cost store keeping units (SKUs) (Kumar & Vishvas, 2010).There are 11–12 million retail enterprises in India, yet only four percent of them are larger than 500 square feet(Guruswamy, Sharma, Mohanty, & Korah, 2005). Retail sales to Indian customers account for around 40% of the country's overall gross domestic product (GDP) of $1 trillion.
Since the Indian economy was liberalised in 1991, the retail business has seen substantial changes. Retail, which was once dominated by low-cost'mom and pop' stores, is now a multibillion-dollar industry. The establishment of an organised sector within the retail industry has resulted in a fundamental shift (Shabnam & Paul, 2008).Licensed retailers, i.e. those who are registered for sales tax, income tax, and other taxes, engage in organised retailing. Corporate-owned hypermarkets and retail chains, as well as privately held significant retail enterprises, are among them (Kathuria & Jain, 2012). Consumer tastes and preferences in India are rapidly changing, resulting in substantial changes in trends and spending patterns, which, in turn, are opening up new economic opportunities. In big cities, shopping malls have become increasingly popular. The rise of contemporary retail in India is attributable to more than simply greater consumer purchasing power; manufacturers and unorganised merchants also play an important part in its development. The trigger came from a variety of sources, comprising of the entrepreneurial desire to provide better service to customers, the social desire to offer relief to the public in the form of lower prices, the desire to capitalise on emerging business opportunities presented by the changing business environment, etc.(Sengupta, 2008). According to (Sinha & Kar, 2010), though there is excitement in the organised sector, the traditional format, which consists of tiny independent, largely mom and pop enterprises, is also rapidly expanding, with over 1.0 million outlets opening each year.
Smart Retail Technology (SRT)
The rapid spread of internet technology is radically changing the retail industry and the shopping experience of customers. One prominent reason behind this is the adoption of smart technology by many of the world's leading retailers(Inman & Nikolova, 2017). The notion of smart commerce arose from the larger phenomena of smart cities (Pantano & Timmermans, 2014). Essentially, the idea of "smartness" is associated with improved procedures and efficiency on the retailer's end, as well as higher pleasure and usefulness on the consumer's end(Roy, Balaji, Quazi, & Quaddus, 2018).
Smart retail technology is defined as an interactive program that offers clients retail services through a network of smart objects and devices. Integrated networked devices can sense their environment and collect data in real time, as well as communicate, interact, and offer feedback(Wünderlich, et al., 2015). It is a retail system which is offline that focuses on smart interaction as well as connection(Fan, Ning, & Deng, 2020).Traditional retailing (particularly e-commerce) focuses on retail channels and a dyadic interaction (between firm and consumers), whereas smart retailing relies on direct interaction with customers, smart objects, products, merchants, and retail channels.
In recent years, retail establishments have implemented a number of smart technology advances into their day-to-day operations. Self-service technologies (SSTs), touch screens, interactive displays, radio frequency identification systems (RFIDs), informational touchpoints, and self-check-out capabilities (Amazon Go), for example, have all been used to improve consumer experiences and engagement with retail establishments(Pantano & Timmermans, 2014; Roy, Balaji, Quazi, & Quaddus, 2018).
SRTs are being incorporated into the existing retail environment, with applications ranging from product displays to shopping lanes and even completely immersive retail shops. Rebecca Minkoff, for example, has launched a mirrored display that allows customers to visually try on apparel, build ensembles from the retailer's inventory, request matching products, buy beverages, and even connect to social media(Willems, Smolders, Brengman, Luyten, & Schöning, 2017).
Within the retail sector, SRT offers flexibility, customization, and lower transaction costs. The use of SRT also offers merchants with valuable information about consumer characteristics, transactions, requirements, preferences, and general behaviour(Liao & Chen, 2004).However, SRT, also raises particular problems, such as restricting organisations' dynamic capacities, the transfer of knowledge management methods, relationship management practises, service access controllability, and changes in consuming habits(Pantano & Timmermans, 2014). Nonetheless, the advantages of smart technology in the retail context exceed the disadvantages.
Customer Experience
Creating a distinct customer experience (CX) is critical in today's retailing. A pleasant client experience might provide a competitive edge (Bagdare & Jain, 2013). Customer experience, according to some research, is described as familiarity based on the number of visits to the store (Söderlund, 2002). Others have included the idea of emotional significance as a result of the user's exposure to specific cues (Carù & Cova, 2003; Holbrook & Hirschman, 1982).
Consumer experience is best defined as direct or indirect encounters with market actors that are impacted by cognitive, emotional, physical, sensory, and social factors(De Keyser,et al., 2015). “Consumer experience” refers to contacts between the consumer and the firm along the customer journey and includes various aspects, including emotional, cognitive, behavioural, sensory, and social (Lemon & Verhoef, 2016).
Numerous research on customer experience have focused on events that give remarkable experiences, such as entertainment, education, and adventure (Gilmore & Pine, 2002; Jones, Comfort, Clarke-Hill, & Hillier, 2010).
Many studies have concentrated on the relationship between customers and brands. The interaction between customers and all retail stimuli, such as store atmosphere, personnel, site, service experience, and loyalty points fosters a certain sort of experience while also initiating the process of value co-creation (Spena, Caridà, Colurcio, & Melia, 2012).
Customer Engagement
Customer engagement has been identified as a key objective for all organisations. Earlier studies define customer engagement as a consumer's concentrated attention (Chapman, Selvarajah, & Webster, 1999), interest (Jacques, 1995), and attraction(Jennings, 2000) to a specific item. It entails the notion of consumer dedication and commitment (Osei-Frimpong & McLean, 2018). It is an offline intelligent retail system with interaction and connection that accomplishes intelligent physical store transformation (Fan, Ning, & Deng, 2020). Thakur (2018) posits that customer engagement is a psychological condition characterised by emotional involvement in stores and brand throughout the customer journey, resulting in repeated encounters between consumers and retail stores. Van Doorn et al. (2010) defined customer engagement as a consumer's behavioural expressions toward products and services that continue beyond purchase and are prompted by motivational forces.
To conceptualise consumer involvement, studies encompass cognitive, emotional, and behavioural perspectives; nevertheless, there is still a lack of agreement on the dimensions employed. McEwen, (2004), for example, pride, confidence, passion and integrity; Patterson, Yu, & De Ruyter, (2006) identified vigour, commitment, interaction and absorption; Bennett, (2013) describe earnestness, passion, and enchantment; Cheung, Lee, & Jin, (2011) expound vigour, absorption, and dedication;Vivek, (2009) advance enthusiasm, socialisation and participation.
Conceptual Framework
SRT and Customer Experience
According to Cachero-Martı́nez & Vázquez-Casielles (2017), marketers are rebuilding retail shops which are completely based on technology. They are now facilitating online orders via websites, mobile applications and various modes of contactless deliveries. Front-end stores utilise the Internet of Things (IOT), smart application and interactive fitting studios to try to rethink the retail experience and design (Roy, Balaji, Quazi, & Quaddus, 2018). Smart technology in retail stores (social fitting rooms, virtual ledges, interactive exhibits, and in-store smartphone applications) integrates and increases interaction touchpoints between customers and retailers (Voropanova, 2015; Roy, Balaji, Quazi, & Quaddus, 2018).
Smart retail, enabled by intelligent technology, expands offline retail's sensing, communication, and processing capability, allowing it to connect the physical and digital dimensions.Customers may engage with businesses in real time, giving them the perceived independence that traditional purchasing cannot provide (Roy, Balaji, Quazi, & Quaddus, 2018). Smart retail gives retailers more tools for monitoring, managing, optimising, and offering autonomy. These abilities help retailers create customer value, define value propositions, and improve their consumers' purchasing experiences. (Adapa, Fazal-e-Hasan, Makam, Azeem, & Mortimer, 2020).
Pantano & Timmermans, (2014, p.102) state that “the emerging idea of smart retailing would reflect a particular idea of retailing, where firms and consumers use technology to reinvent and reinforce their role in the new service economy, by improving the quality of their shopping experiences”. Retailers may create seamless customer experiences by employing in-store iPads and interactive screens where customers can learn more about the items (for example, McDonald's fast food retail shops). Retailers may also use the in-store Wi-Fi to connect with, interact with, and track their consumers(Roy, Balaji, Quazi, & Quaddus, 2018).
According to BaeBrandtzaeg and AsbjrnFlstad (2017), consumers are interested in adopting chatbots because they are productive; in that they make it easier to get information, speed up procedures, and are available round the clock, 7 days per week. According to Legget (2017), numerous companies are increasingly using artificial intelligence (AI) to improve tailored consumer experiences. For example, 50% of all customers are already conversing with intelligent assistants such as Siri, Cortana, and Alexa.She claims that AI will please customers by making these dialogues more natural and productive, predicting requirements based on context, preferences, and past questions, offering advice, resolutions, warnings, and offers, and learning over time. Dahlhoff et al. (2018) employed drones as delivery methods as an example of utilising AI. The results were said to be encouraging, with over 40% of consumers responding that they would consider using a drone as a delivery method, elevating the customer experience to a new level. Hence, based on the review of literature, it is postulated that:
H1: Use of SRT will have a significant positive impact on customer experience in unorganized apparel stores.
SRT and Customer Engagement
Technology has altered the way businesses interact with their consumers. Automation is one of the technological developments that have significantly improved the way individuals engage with organisations (Pangriya & Singh, 2020). Because of technological developments, businesses can now provide customers with tools to interact with their brands via websites, social media platforms, and mobile applications (Osei-Frimpong & McLean, 2018).
In a study using Facebook applications byClaussen, Kretschmer, & Mayrhofer (2013) discovered that the instant updates, quick installations, push notifications, updates and cutting-edge technology based factors are significantly impact consumer engagement. Similarly, smart retail's physical environment influences customers' cognitive involvement. Customers mistrust the capabilities of the artificial intelligence-based retail systems and negatively impact their intention to use it as they expect delays in response, inadequate security and difficulty of access
Customers like to be dominant in artificial intelligence-based system. This suggests that they seek to govern the level of human interactions from a technology viewpoint (Zhao and Lu, 2012). The stronger the customers' self-efficacy and behavioural controllability over technology (Ajzen, 2002), the larger their cognitive participation in smart retail.
According to Kuo, Wu, & Deng (2009), subsequently, the contents of products impact the functional value required by the consumers and play an important role in making smart retail advantageous. As per Reitz (2012), the quality of content and information influences customer involvement. Service, in addition to content and information, has become a crucial component of smart retail accessibility. Customers will have a higher cognitive load while making a purchase if things are regularly out of stock or if they must spend an inordinate amount of time seeking for them. Smart retail self-service solutions enable customers to explore and pay more rapidly. Meanwhile, smart inventory systems refill things on time, allowing customers to shop more efficiently. Based on the literature review, it is hypothesised that:
H2: Use of SRT has a significant positive impact on customer engagement in unorganized retail stores.
Customer Experience and Customer Engagement
Customer experience, according to Bowden (2009), is a prelude to customer engagement. A meaningful customer-store experience, according to Hayes and MacLeod (2007), may develop a deeper link between customers and retailers, leading to increased customer engagement with the shop and a marketing advantage for the retailer (Hayes and MacLeod, 2007).It is defined as a method for customers to interact physically, intellectually, socially, and psychologically with goods and/or services, culminating in more interpersonal communication between businesses and consumers(Carù & Cova, 2003).According to Vivek (2009), there is a correlation between customer experience and engagement. He has stated that an interactive experience serves as a value driver, motivating consumers to interact with the retailer's offers.
Hayes and MacLeod (2007) studied approaches to promote customer engagement in the context of place marketing by providing the best possible experience.According to their research, in order to maximise consumer engagement, businesses should design their offerings with distinctive, relevant, and engaging experiences that result in higher customer participation and cooperation in the purchasing process.Customers who have a positive experience interacting with store attributes are more likely to engage with the store by being more enthused about the store, deliberately paying close attention to and interested in knowing anything attributed to the store, and evolving a desire to shop more as a result of social interaction(Vivek, 2009).The following hypothesis is proposed based on the preceding explanations:
H3: Customer experience has a significant impact on customer engagement in unorganized retail store.
H4: Customer experience partially mediates relationship between smart retail technology and customer engagement.
Figure 1 shows the conceptual model of the study.
Figure 1: Conceptual Model
Method
Materials, Procedure and Participants
Sampling was done in three stages-stage one included market selection, stage two included retailer selection, and stage three included sampling unit selection. The current study was conducted in two prominent cities of the state, Uttar Pradesh which is the India’s largest state, accounting for around 8% of the country's overall retail market. These two cities were chosen based on their high GDP (gross domestic product).Then four and three markets were selected respectively from each of these cities on the basis of concentration of unorganised apparel retail outlets. Total thirty-one retail outlets in these markets were chosen using a random sampling technique. Customers who shopped at these specified retail establishments were chosen randomly as the sampling unit. A total of 151 customers took part in the survey which was conducted from Jan-March 2021 during the prevailing COVID-19 conditions. Due to short footfall of customers in these retail outlets due to pandemic it was very difficult for the researchers to collect the data from large number of people. Additionally, out of the customers who were visiting the shops a lot were quite sceptical to interact with the researchers. Before administering the questions, an informal talk was done just to find out if the customers were familiar with smart retail technologies or not. Researchers were surprised to know that all the respondents were familiar with it in some form or the other. For statistical analysis, SPSS version 17 and AMOS version 16 were employed.
The research instrument comprised two sections. The first part dealt with statements for drawing the demographic profile of the respondents. The second part comprised 6-item scales on smart retail technology features, 5-item scales on customer experience and 5-item scales on customer engagement. These scales were adapted from the study conducted by Ullah, Zhang, & Ahmed (2021).Customer experience, customer engagement, and SRT features data were coded on a five - point Likert scale from "strongly disagree" to "strongly agree," with strongly disagree=1 and strongly agree=5.Since these scales had been developed in other cultural settings, it was believed appropriate to adjust these to the Indian context. For this purpose, the procedure indicated in research on scale adaptation (Borsa, Damásio, & Bandeira, 2012; Gjersing, Caplehorn, & Clausen, 2010) was followed. Following that, the instruments were pretested on 30 participants prior to data collection to ensure the scale's reliability and validity. The results indicate conceptual commonalities, albeit certain things needed to be adjusted in terms of question framing or removed from the constructs. Consequently, some wordings of the questionnaire items were modified. It was conveyed to the respondents beforehand that the participation in the study is optional and unnamed, and could be discontinued at any time at the respondents’ circumspection. Interviewees were requested to be as honest and accurate as possible.
Data Analysis and Results
Table 1 shows the demographic characteristics of the respondents. In total, 68.2 per cent of the respondents were male while 31.8 per cent were female. Majority of the respondents came were young (89.4%) belonging to the age group of below 21 years (37.1%) and 21-30 years (52.3%). Almost all the respondents were educated with about 86% being graduates or above and from urban areas (72.2%). Family income of 35.8% of respondents was below Rs. 2 lakhs ($ 2739.48) per annum. Students constituted 82.1% of the respondents.
Table 1: Demographic Characteristics of Respondents
|
Variables |
N (151) |
Percentage |
|
Gender Male Female |
103 48 |
68.2 31.8 |
|
Age <21 21-30 30-40 40-50 >50 |
56 79 10 2 4 |
37.1 52.3 6.6 1.3 2.6 |
|
Education Intermediate Graduate Post Graduate |
21 86 43 |
14 57.3 28.7 |
|
Place of Living Urban Rural |
109 32 |
77.3 21.2 |
|
Occupation Student Private Sector Government Self-employed Unemployed Retired House-wife |
124 12 5 1 4 1 2 |
83.2 8.1 3.4 .7 2.7 .7 1.3 |
|
Household Income <2Lakh 2-4Lakh 4-6Lakh 6-8Lakh >8Lakh |
54 24 25 20 10 |
40.6 18 18.8 15 7.5 |
A two-stage analytical technique was used to verify that the measurement model was validated before testing (Anderson & Gerbing, 1988). The first step examined scale reliability and internal consistency. The Cronbach's Alpha was 0.82, 0.84, and 0.90 for CN, SRT and CE respectively, indicating that all the constructs were reliable. The numerous constructs and their components are depicted in Annexure A. AMOS 16 was used to perform confirmatory factor analysis (CFA) on the confirmed measurement model using the maximum likelihood fitting procedure. When the CFA was performed, the model indicated a good fit with CMIN/DF =1.750(p=0.000), CFI=0.91, TLI=0.90, IFI=0.91, and RMSEA=0.08
The standardized estimate loadings of items on their respective factors were significant (p=0.000) and above 0.5. Construct reliability (CR) for the scales on customer experience, customer engagement and SRT features was 0.89, 0.84 and 0.86respectively.The value of construct reliability for all scales was higher than Nunnally’s (1978) suggested cut-off. The AVE values were in the range of 0.52 to 0.62 and above the recommended value of 0.50. Since the values of construct reliability for all of the constructs are higher than the suggested cut-off value, the model may be deemed to have convergent validity (Fornell & Larcker, 1981).
Table 2: Reliability and AVE scores of constructs
|
Constructs |
Construct reliability (CR) |
Average variance extracted (AVE) |
|
Customer Experience |
0.89 |
0.62 |
|
Customer Engagement |
0.84 |
0.52 |
|
Smart Retail Technology Features |
0.86 |
0.52 |
The parameter estimates for various variables are shown in Table 3. The results point out the acceptance of H1. The use of SRT has a significant impact on customer experience. Various studies back up this claim, stating that the use of smart/intelligent technology in retail outlets supports interactive touchpoints between customers and retailers and improves customer experience (Voropanova, 2015; Roy, Balaji, Quazi, & Quaddus, 2018; Chen, Chiang, & Storey, 2012). The outcome of the current study leads to the acceptance of H2 i.e., the use of SRT has a significant relationship with customer engagement. This finds support in a study conducted by Claussen, Kretschmer, & Mayrhofer, (2013) who found that the use of technology is a crucial driving factor in influencing customer engagement. The third hypothesis (H3) was also accepted i.e., customer experience has a significant impact on customer engagement. Research has consistently indicated that customers’ satisfactory experience leads to customer engagement in the form of recommendation behaviours, helping organisations, and positive word of mouth (Chen, Chiang, & Storey, 2012; Barnes, Mattsson, & Sørensen, 2014).
Table 3: Structural Equation Modelling Results
|
Variable |
Estimate |
SE |
CR |
P |
Significance |
|
Customer experience ß SRT |
1.409 |
.290 |
4.850 |
*** |
Significant |
|
Customer engagementß Customer experience |
.299 |
.141 |
2.123 |
.034 |
Significant |
|
Customer engagement ß SRT |
.630 |
.263 |
2.395 |
.017 |
Significant |
The results of five hundred bootstrap samples at bias corrected 95 percent confidence interval obtained through bootstrapping technique show the total, direct and indirect effect of SRT on CX (Table 4). The findings support H4 which states that customer experience partially mediates relationship between smart retail technology and customer. Hence, H4 is also accepted.
Table 4: Bootstrapping Results on Total, Direct and Indirect Effects at Two-tailed Significance
|
Relationship |
Total Effect |
Direct Effect |
Indirect Effect |
Type of Mediation |
|
SRT→CX (CE as mediator) |
.866 (significant) |
.850 (significant) |
.347 (significant) |
Partial |
Discussion
The present study aims to add to the existing literature on unorganized retail apparel industry by elucidating consumers’ attitude on the usage of SRT and its influence on customer engagement and experience. Previous studies have neither considered the use of SRT in unorganised retail sector nor examined customers’ perception for the same. The findings have made a significant contribution by giving some valuable insights and raising more interest in this sector.
The findings of the study may have a number of ramifications for current marketing scholars as well as practitioners in developing and developed countries. Understanding the perception of consumers towards the use of smart retail technology in unorganised retail sector and its relationship with customer experience and customer engagement can help the retailers to design their strategies accordingly. In 2019, the unorganised sector accounted for 88 percent of the Indian retail business. This is despite the fact that the organised and e-commerce industries have grown substantially in recent years. However, by 2021, this percentage is expected to fall to 75%, with organised retail accounting for a larger part and internet retail increasing. As a result, it is even more important for the unorganised retail industry to implement smart retail technologies in order to retain and expand their consumer base.
The result points out that in order to enhance customer shopping experience, unorganised retail sector can adopt smart retail technologies in their services. Several studies support this finding that the application of smart technology in retail outlets strengthens interactive connections between customers and retailers and improves the customer experience (Chen, Chiang, & Storey, 2012; Voropanova, 2015; Roy, Balaji, Quazi, & Quaddus, 2018). Therefore, the adoption of SRT will provide an opportunity to unorganized retailers to upscale themselves, remain more competitive and offer more services. This is further supported by a study (Steinfield, Adelaar, & Lai, 2002), which states that the use of technology in business not only provides opportunities to reach new consumers and deliver new services, but it may also have spill over effects, resulting in greater purchases and lower costs in other channels.
The use of SRT is found to have a significant relationship with customer engagement. This implies that the use of SRT will help in increasing customer engagement which in turn,might help in building customer loyalty. According to Pansari and Kumar (2017), more than 80percent of marketers aspire to gain the confidence and advocacy of engaged consumers.This has significant implication for unorganised retailers who are currently facing challenges from the rapid growth of organised as well as online retailing. In order to generate customer loyalty, they could employ smart retail technology in their stores which might help in engaging the customers and connecting them emotionally with the stores.
Customer experience is reported to have a significant impact on customer engagement. Research has consistently indicated that customers' pleasant experiences lead to consumer involvement in the form of recommended behaviours, supporting organisations, and positive word of mouth (e.g., Chen, Chiang, & Storey, 2012; Barnes, Mattsson, & Sørensen, 2014). Customers may view service quality as greater as a result of positive encounters, and they may provide more ideas and information to businesses and other customers (Bendapudi & Leone, 2003).These encounters may not only affect the behaviour and attitudes of other consumers, but they may also assist retailers in improving their own performance. Customers who have had positive social interactions with retailers or other customers are more eager to assist retailers and other customers. Buyers who have had a favourable experience with a retailer and its workers are motivated to create a long-term, mutually beneficial connection with the retailer (Groth, 2005).
It was indicated that consumers have a favourable attitude towards the usage of SRT in unorganised retail stores.This implies that they are receptive towards adoption and use of new and smart technology. It's possible that this is due to the fact that the majority of participants were between the ages of 21 and 30.The reason for this finding could also be that a lot of senior citizens stayed at home due to pandemic situation and their children went out for shopping. This could be a reason for a positive perception towards the use of SRT in unorganised retail sector as young generation adopts technology very quickly. Engel, Bell, Meier, Martin, & Rumpel, (2011) have stated that young consumers use multiplicity of interactive technologies more in comparison to older people.
It cannot be denied that there are several reasons for customers to shop from unorganised retail stores such as proximity, goodwill, credit facility, bargaining, convenience(Talreja & Jain, 2013). Moreover, the findings suggest that the advancement of technology is giving continual rise to customer expectations which might sway these customers and make them switch over to organised retail stores. Hence, it is the need of the hour for the unorganised sector to adopt smart retail technology if they seek to gain a competitive advantage in customer service.
However, no study is without limitations. The current study is limited to a State of the country. Findings in other parts of the country could vary. Therefore, it cannot be generalised for the entire country of India. In future, studies could be conducted to investigate the perception of consumers with different demographic profile (middle aged/old, rural, etc.) towards the usage of smart retail technology in unorganised retail sector. It would be interesting to do a comparative study on organised and unorganised retail sector in terms of technology usage. Additionally, it would be useful to understand the unorganized retailers’ perceptions towards integration of new technologies in their businesses and the associated challenges, if any. Similar studies could be conducted in other emerging markets as well.
Annexure A: Constructs and Their Items
Customer Experience
|
1. |
I will feel convenience in using intelligent retail technology (SRT) at the retail store. |
|
2. |
I will positive in using SRT at the retail store. |
|
3. |
I will feel excitement interacting with SRT at the retail store. |
|
4. |
I will enjoy using SRT. |
|
5. |
I will feel comfortable in interacting with SRT. |
SRT
|
1. |
SRT in this store will offer me personalized services |
|
2. |
SRT in this store will understand my specific needs |
|
3. |
SRT in this store will customize services to my needs. |
|
4. |
SRT in this store will be useful in having smoother shopping experience |
|
5. |
Using SRT will improve my ability to easily complete a shopping trip. |
|
6. |
SRT interaction will be very human like. |
Customer Engagement
|
1. |
I will provide feedback about my experience with SRT |
|
2. |
I will participate in discussions on SRT in retail stores in social media |
|
3. |
I will recommend this store with SRT to others |
|
4. |
I will speak about SRT in this store to others |
|
5. |
I will assist other customers with SRT if they need my help |
Acknowledgement
This is to acknowledge the support provided by the grant received under Centre of Excellence, Higher Education, Government of Uttar Pradesh vide Sanction No. 10/2021/281/Seventy-4-2021-04(2)/2021 dated 28.01.2021 to conduct this research.
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