India, currently, is the second largest smartphone market of the world where several national and international companies compete to acquire consumer preference, endowing the consumers with a large number of options to choose from. In such market environment, business organisations need to spend considerable amount of their resources to attract sales. However, performance of XIAOMI in its last four years of operations in Indian indicates towards the success of its marketing efforts in acquiring and retaining the attention and preference of Indian consumers (Singh, 2013). The flash sales played a major role in achieving this position. However, in recent years, limitations of flash sales, has been observed that need to be addressed for maintaining its applicability in the future promotional activities of XIAOMI (Mehta, 2016). This assignment aims to provide a guideline for a research on the impact of flash sales on consumer satisfaction.
For this, the assignment is segregated in five different parts. The first or the introductory part avails an insight into the research problem, aim, objectives, research questions, justification and potential outcome of the project. The second and third part of this assignment provides conceptual framework and research hypotheses respectively, while the fourth part outlines the research methodology. Finally, the fifth part includes outlining organisation of the research study, project activities, budget and schedule.
The flash sales activities are one of the key means of promotion and sales for XIAOMI in India. The strategy cost less compared to other means of sales and marketing that the brand and its competitors used, yet delivered better result by developing a sense of urgency and need among the customers, leveraging impulse buying (de Melo, Leone & Jose, 2015). Since its entry in the Indian market in 2014, the organisation has been able to acquire 23.5% market share by the end of 2017, while its competitors like Samsung, Oppo, Lenovo and Vivo either merely retained their market share or lost their share (Sushma, 2017). Moreover, by 2016, XIAOMI began to utilise additional sales measures along with flash sales. In a news report, Aulakh (2016) suggested that the days of flash sales are over and the consumers in Indian e-commerce environment have grown weary of the flash sales that companies arrange twice every week.
Therefore, this research study would investigate the impact of flash sales on the consumer buying behaviour and its applicability in future marketing and sales practices, with practical examples of performance of XIAOMI in Indian market. It is expected to compare the cost-effectiveness and applicability of flash sales with the promotional activities, undertaken XIAOMI and its other competitors in India. Result of this research is expected to reveal applicability of flash sales for different promotional, sales and operational purposes.
This research aims to investigate the effectiveness of flash sales as a means of influencing customer purchase behaviour towards impulse buying. For this, the research issue would be evaluated based on the practical examples of flash sale activities of XIAOMI in the Indian market and their result.
The research objectives are as follows:
The primary research question for this study is,
How do Flash sales of XIAOMI influence the Indian consumers?
The subordinate research questions are,
The project is expected to compare flash sales with other promotional, marketing and sales activities of XIAOMI and its competitors to understand its relevance in contemporary market. It is also expected to explain the manner in which the creation of urgency through marketing activities adds to the perceived value of a particular product hence, impulse buying, paving the path for future studies in this field (Amos, Holmes & Keneson, 2014). The literature linking social media presence of a company with success of their flash sales activities might be relevant here as it explains the vast accessibility of the organisation in the target market (Chen, Su & Widjaja, 2016). The available literature linking the variables is few and very rarely establishes a direct link between the flash sales and any aspect of consumer behaviour, other than impulse buying. This study, however, is expected to investigate the impact of such sales activities on consumer perception and identify different aspects of flash sales that might risk negative consumer perception.
Flash sales
Sahavashishta & Chadichal (2012) define flash sales as a channel for electronic distribution used for heavily discounted, time-limited purchase in advance. Though it might be true in some cases, this measure is used for both boosting sales and new product launch. While many identify flash sales as a mere means of promotion or a way for inventory clearance it is argued as an effective measure for increasing profitability of a product or service, acquiring new customers, faster and higher market growth, meeting the need for filling the occupancy and increasing exposure (Tu, Wu, Jean & Huang, 2017). Such sales activities also helps to reach new market segments as the flash sales often serve as the means of first customer trial (Shi & Chen, 2015). As such sales processes increase the market presence of the brand it also encourages the potential customers to acquire better knowledge regarding the brand leveraging better traffic to organisational website. However, Brown (2018) pointed out that the failure in achieving the product, due to the vast number of customers applying, often generates dissatisfaction. This might not be in favour of the organisational image.
Impulse buying
Impulse buying is a complex purchase behaviour where the hasty, hedonic decision of purchase leaves little scope for measuring options or assessing the consequence of such purchase behaviour in part of the consumer. Amos, Holmes and Keneson (2014) identified that around 60% of the retail purchases belong to this category. The stimulus-organism-response model explains that in case of online impulse buying the atmospheric cues of the e-commerce site such as the design, system of navigation and the content of the product and its description influence the behaviour variables like willingness to spend and the act of buying itself (Floh & Madlberger, 2013 and Chang & Tseng, 2014).
Social commerce, another branch of e-commerce, has also been at the forefront when it comes to encouraging consumers to impulse buy a product allowing companies like XIAOMI, with significant social media presence, succeed to attract impulsive buyers towards their flash sales events (Xiang, Zheng, Lee & Zhao, 2016 and Soo, 2018). Hence, it can be deduced that personal experience of social commerce like invitation to flash sales, positively influence the purchase decision.
The hunger driven market and flash sales
Identifying the need of the consumers and catering to those needs just enough to keep them wanting for more, instead of having surplus resources in the inventory that need otherwise allocation is considered the key to the success of XIAOMI. Rawal, Awasthi and Upadhayay (2017) identified that instead of manufacturing goods in bulk, at a time, XIAOMI kept its customers craving for its products by manufacturing goods in small amount and in regular intervals allowing it to incorporate innovative features in its models in frequent intervals. However, excessive use of this strategy in the Indian smartphone market has also reduced its appeal to consumers (Mehta, 2016).
Growing e-commerce industry in India
The e-commerce industry of India has exhibited rapid growth, which is expected to grow even larger in the following years. Gangeshwer (2013) marked that the market for e-commerce in India has been growing at an average rate of 70% per year. It has jumped from 3% in 2010 to 34% in 2014 (Mehta, 2017). Sujata, Menachem, Akshay and Viraj (2018) further suggested that this industry would grow larger and reach the worth around $20 billion by the year 2020. This escalated growth of the industry has been attributed to the changed attitude of the Indian consumers towards online shopping and increasing dependency of such customers upon e-commerce sites. With over 314 million internet users, Indian market the mobile commerce avails great prospect for flash sales and promotional activities in India (Agarwal & Dixit, 2017). This is one of the major reasons for vast acceptance of XIAOMI in the Indian market, despite it being from a different country.
Flash sales applicability
Flash sales, though primarily introduced by XIAOMI in the Indian market, by the end of 2014, had achieved the preference of its competitors in the Indian market such as Motorola, Asus and OnePlus. While not exactly through the flash sales, OnePlus succeeded to grab the fancies of Indian consumers through its innovative, innovative “invite only” model (Singh, 2013). Though both the models are regretted to trigger the fancies of customers, the limited availability of the products often limit the accessibility aspects of the product. In such circumstances, the in-store or regular online sales of the bigger brands like Samsung and Apple receive the upper hand, in terms of sales.
Yet, by the end of 2015, even these bigger brands to ensure rapid inventory clearance and faster market penetration of newly launched product, adopted similar sales and promotional strategies. However, by the second half of 2015 popularity of the flash sales declined considerably due to the overuse of the model in the e-commerce platforms (Mehta, 2016). Even the brands like XIAOMI that leveraged flash sales while entering Indian market began to establish and strengthen an offline presence to improve the aspect of availability of products. Yet, the organisation uses this model at regular intervals to retain the interest of its customers and maintain exhaustive sales of its new launches.
Figure 1: Conceptual framework
(Source: created by student)
Based on the review of literature the following hypotheses have been identified that validity of which would be investigated in due course of this research:
Hypothesis 1
Hypothesis 2
Hypothesis 3
Hypothesis 4
Survey Research
The primary data would be collected from 200 customers of XIAOMI in India, through an online survey. Respondents would be contacted by e-mail. Therefore, consumers of XIAOMI in India would be the source of primary quantitative data. Ten close-ended questions would be asked to the same customers of XIAOMI, India in two different periods, one before a flash sales event of XIAOMI in India and the other after it. Population of this survey could include consumers and marketing staffs of XIAOMI, India, and all the available secondary data on the sales marketing, promotional activities and consumer behaviour. However, due to the lack of time and resources the sample of this study has been limited to 200 customers of XIAOMI, India.
The convenience sampling technique of the non-probability sampling has been selected for the sample. While unlike the simple random sampling technique of probability sampling would allow the opportunity to careful selection of the respondents based on their association with the research issue it would also allow the selection of the respondents based on their convenient accessibility (Sekaran & Bougie, 2016). The total sample size for this survey would be 200 customers of XIAOMI in India.
Inclusion criteria:
Exclusion criteria:
Any other stakeholder of XIAOMI than customers
The survey questionnaire would contain 10 close-ended multiple-choice questions. The questions would be developed based on Likert scale, semantic differential scale and nominal scale. These questions would be sent to 200 customers of XIAOMI in India via e-mail in two different periods (Hill & Alexander, 2017). The followers of the official pages of XIAOMI India in social media sites would be contacted for participation in the survey and after acquisition of their approval would be sent the survey form through either message or e-mail. The questionnaire would contain questions exploring the aspects of sales of XIAOMI that attracted them to purchase their products and their opinion on its flash sales.
Longitudinal research design would be applied for investigating the change in the flash sales activities and their impacts on the Indian market (Bryman, 2016). The news and industry reports would be studies for successful achievement of this target along with the survey results. The longitudinal method has been undertaken as it would avail the opportunity to study the same subject in different periods. For this, the primary data collection would be conducted in two different stages. That is, the same survey questions would be asked to the customers of XIAOMI, India over two different stages, first time, before a flash sale the second, after it. This would help in recording the customer reaction to the flash sales over two different times, availing an insight to the change in customer behaviour or perception towards the flash sales activities of XIAOMI in India.
This research would be developed as a longitudinal study examining the effect of flash sales of XIAOMI in Indian market over period of its operation, in India until the present time and the organisation has been operating in the Indian market since 2014. Therefore, the secondary company-specific data would be acquired of that period to evaluate the changed approach of the customers towards the flash sales activities of XIAOMI.
As this research is targeted towards investigation of the usefulness of flash sales in enhancing performance of XIAOMI in the Indian market, its findings are expected to be context-specific. Therefore, deductive approach would be useful in this study to ensure the success of the longitudinal research design (Dolnicar & Ring, 2014).
For academic understanding of the research, issue and its variables like flash sales and customer behaviour theories and concepts on these topics would be studied from books, journals, news reports and websites. Information on the growth of Indian e-commerce and changing approach and preference of consumers regarding marketing strategies reflected through sales performance of companies operating in smartphone market of India would be gathered from news published online and industry and market analysis reports purchased from online or offline secondary sources. Moreover, news, company reports, industry data and market analysis reports would serve as the source of secondary market-specific data.
To evaluate the acquired quantitative data from the primary data collection process descriptive statistics would be merged with simple graphics analysis (Sekaran & Bougie, 2016). The acquired primary quantitative data would be transformed into tables and charts for systematic representation and understanding. Then through statistical analysis tools such as mean, median, mode and standard deviation such data would be evaluated. Along with the descriptive statistics analysis, hypothesis testing would be used for assessing the research hypotheses, listed in the earlier section (Sekaran & Bougie, 2016).
The primary statistical data would be compared with the secondary data acquired on the market and performance of XIAOMI in India compared to its competitors. It would also be evaluated based on the theoretical understanding developed through the study of academic theories, concepts and models of consumer behaviour and flash sales activities.
Organisation of the study
The project report would contain five chapters each of which would address the research issue and its variables in different ways.
Budget
The budget for the research is expected to be around $4500. Details of the budget allocation are available in the following table:
|
Area of expenses |
Probable amount required / to be spent |
|
Literature review |
$1000 |
|
Data acquisition |
$2000 |
|
Data analysis |
$500 |
|
Presentation and submission |
$500 |
|
Additional expenses (transportation, communication, stationary) |
$500 |
|
Total |
$4500 |
Table 2: Estimated budget for the project
(Source: created by student)
Project activities and task schedule
|
Task |
Start |
End |
Duration |
|
Initial Literature review |
17/09/2018 |
21/09/2018 |
5 |
|
Research problem and methods identification |
21/09/2018 |
22/09/2018 |
2 |
|
Research proposal |
23/09/2018 |
27/09/2018 |
5 |
|
Further literature review |
28/09/2018 |
02/10/2018 |
5 |
|
Market-specific secondary data collection |
03/10/2018 |
12/10/2018 |
10 |
|
Primary data collection |
06/10/2018 |
14/11/2018 |
40 |
|
Data analysis |
14/11/2018 |
02/12/2018 |
20 |
|
Report (1st draft) |
02/12/2018 |
09/12/2018 |
8 |
|
Review and improvement |
10/12/2018 |
12/12/2018 |
3 |
|
Report (final draft) |
10/12/2018 |
14/12/2018 |
5 |
|
Final submission |
15/12/2018 |
15/12/2018 |
1 |
|
Total days = 90 |
Table 3: Activities and schedule
(Source: Created by student)
(Source: Created by student)
References
Agarwal, H., & Dixit, S. (2017). The Encumbered Growth of E-commerce In India: Can We Help?. Aweshkar Research Journal, 23(2), 114-132.
Amos, C., Holmes, G. R., & Keneson, W. C. (2014). A meta-analysis of consumer impulse buying. Journal of Retailing and Consumer Services, 21(2), 86-97.
Aulakh, G. (2016). Flash sales for smartphones no longer the flashiest way of selling handsets. The Economic Times. Retrieved from https://economictimes.indiatimes.com/tech/hardware/flash-sales-for-smartphones-no-longer-the-flashiest-way-of-selling-handsets/articleshow/51465066.cms
Brown, S. (2018). Indian buyers angry that Xiaomi Redmi Note 5 Pro sold out in seconds. Android Authority. Huffpost. Retrieved from https://www.androidauthority.com/indian-buyers-angry-xiaomi-redmi-note-5-pro-sold-seconds-839743/
Bryman, A. (2016). Social research methods (5th ed). Oxford: Oxford university press.
Chang, C. C., & Tseng, A. H. (2014). The post-purchase communication strategies for supporting online impulse buying. Computers in Human Behavior, 39, 393-403.
Chen, J. V., Su, B. C., & Widjaja, A. E. (2016). Facebook C2C social commerce: A study of online impulse buying. Decision Support Systems, 83, 57-69.
de Melo, M. A., Leone, G., & Jose, R. (2015). Alignment between Competitive Strategies and Cost Management: a Study of Small Manufacturing Companies. Brazilian Business Review (English Edition), 12(5), 83-104.
Dolnicar, S., & Ring, A. (2014). Tourism marketing research: Past, present and future. Annals of Tourism Research, 47, 31-47.
Floh, A., & Madlberger, M. (2013). The role of atmospheric cues in online impulse-buying behavior. Electronic Commerce Research and Applications, 12(6), 425-439.
Gangeshwer, D. K. (2013). E-commerce or Internet Marketing: A business Review from Indian context. International Journal of u-and e-Service, Science and Technology, 6(6), 187-194.
Hill, N., & Alexander, J. (2017). The handbook of customer satisfaction and loyalty measurement (3rd ed). New York: Routledge.
Mehta, I. (2016). Flash Sales Are No Longer A Boost For Smartphone Brands. Huffpost. Retrieved from https://www.huffingtonpost.in/2016/06/09/flash-sale_n_10350992.html
Mehta, V. (2017). E-COMMERCE: A GAME CHANGER FOR THE INDIAN ECONOMY. Global Journal of Multidisciplinary Studies, 6(7), Retrieved, September, 24, 2018, from https://journal.edwin.co.in/index.php/GJMS/article/view/2748
Rawal, P., Awasthi, A., & Upadhayay, S. (2017). Creating a Hunger Driven Smartphone Market by Xiaomi. International Journal of Engineering Science, 7(5), 11250-11255.
Sahavashishta, D. & Chadichal, S. (2012), gone in 60 seconds-online flash sales: The next innovation in Indian e-commerce or just a flash in a pan?-A critical and empirical analysis with consumer perspective, Indian Journal of Management Science (IJMS), 2(1), 24-32.
Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill building approach (7th ed.). New Jersey: John Wiley & Sons.
Shi, S. W., & Chen, M. (2015). Would you Snap up the Deal?: A Study of Consumer Behaviour under Flash Sales. International Journal of Market Research, 57(6), 931-957.
Singh, R. (2013), How China’s handset maker Xiaomi came first in India. The Economic Times. Retrieved from https://economictimes.indiatimes.com/tech/hardware/how-chinas-handset-maker-xiaomi-came-first-in-india/articleshow/61798368.cms
Soo, Z. (2018), Flash sales, social media savvy helped Xiaomi topple Samsung as India’s No 1 smartphone supplier. South China Morning Post. Retrieved from https://www.scmp.com/tech/enterprises/article/2138503/flash-sales-social-media-savvy-helped-xiaomi-topple-samsung-indias
Sujata, J., Menachem, D., Akshay, P., & Viraj, T. (2018). Impact of Flash Sales on Consumers &E-Commerce Industry in India. GSTF Journal on Business Review (GBR), 5(3), 1-9.
Sushma, U. N. (2017). How Xiaomi is winning over India’s booming smartphone market. Quartz India. Retrieved from https://qz.com/india/1115071/samsung-beware-how-xiaomi-is-winning-over-indias-booming-smartphone-market/
Tu, C. K., Wu, K. W., Jean, C. H., & Huang, Y. (2017). The Impact of Online Promotions on Online Impulsive Buying Behavior: Mediating Effects of Perceived Value and Positive Emotion and Moderating Effect of Online Reviews. Economics & Management, 1(1), 280-282.
Xiang, L., Zheng, X., Lee, M. K., & Zhao, D. (2016). Exploring consumers’ impulse buying behavior on social commerce platform: The role of parasocial interaction. International Journal of Information Management, 36(3), 333-347.
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