4th National Business and Management Conference
Ateneo de Davao University
July 22-23, 2016
IMPULSIVE BUYING BEHAVIOR OF MILLENNIALS ON ONLINE SHOPPING
Jose Luis Legaspi, Ireene Leoncio Oliver Galgana, Clare Hormachuelos
De La Salle University – Manila
This study presents findings on consumer behavior among millennials in the Philippines
regarding online impulse purchase behaviors. The rapid growth in information technology has evidently influenced the landscape of consumer behavior in the Philippines despite infrastructure constraints. Filipino consumers’ buying patterns had diversified through an increased accessibility to products and services with online options. The research presented Filipino Millennials as online impulse buyers in four scales: Consumer Impulsiveness Scale, Optimum Stimulation Level Scale, Self-monitoring Scale, and Level of Impulsiveness in Purchase Decision Scale in the local setting. Participants were millennials aged 19 to 35 years old; student, employed or unemployed; single or married. These Millennials are social media users (i.e Instagram, Facebook); they subscribe and receive promotional emails from different brands and individuals. They have tried buying online using credit card, debit card or cash-on-delivery basis.
The result showed that Filipino Millennials are not impulsive buyers when it comes to shopping online. There are key barriers identified to encourage more incidence of online impulse purchase such as perception on security vulnerabilities and the abundance of options through other traditional retail channels.
Online shopping; Millennials; Online retailing
The increasing amount of spending in today’s society has created a new lifestyle that has
been integrated and accepted among consumers. Owning items has become an expression of selfidentity for a lot of consumers which has helped to increase shopping as a lifestyle (Dittamar, Beattie &Friese, 1996). A change in society is also shown in the decreasing amount of free time outside of work. Consumers spend less time planning before shopping but with the attitude of a lifestyle shopper and an increased income by which consumers are encouraged to buy more, impulse buying increases (Williams et al, 1972).
According to Beatty & Ferrell (1998), impulse buying is defined as the sudden and
immediate purchase with no pre-shopping intentions either to buy the specific product category or to fulfill a specific buying task, and with little or no deliberation or consideration of available alternatives. Impulse buying has become a more regular occurrence in today’s society because of how shopping is more blended with regular life (Dittamar et al. 1996).
Over the years, Internet has become an integral part in the daily lives of people both in the workplace and at home. The rapid growth in information technology has evidently influenced the landscape of consumer behavior. The online retailing that is available 24/7 has brought about an increase in impulse buying. Impulse buying is now considered as s phenomenon.
With the Internet, consumers’ buying opportunities have expanded through an increased accessibility to products and services and the increased ease to make purchases. Moreover, this new mode of shopping promotes convenience than traditional in-store buying (Eroglu, Machleit, Davis, 2001). Its potential to compete with traditional retailing is hard to ignore.
With online retail sales steadily increasing, and projected to continue doing so, companies are trying to capitalize on the convenience of online shopping by incorporating strategies to encourage impulse purchases. With the continual evolution of technology and increased experience in online marketing, websites have become very innovative in encouraging impulse buying.
According to Crafts (2012), technology does not create impulse buyers; rather, it gives
impulsive consumers more resources to shop and the easier access to complete transactions in a short amount of time, making purchases truly a reaction to an impulse.
However, online impulse purchase behaviors have been seldom investigated here in the
Philippines. This topic has interested foreign researchers as well as retailers but only a few local studies have tapped on this. Therefore, this study will greatly enrich our knowledge of this essential element on consumer behavior among millennials.
This research introduces a conceptual framework by researchers Sharma, Sivakumaran& Marshall in their first study about “Impulse buying and variety seeking: A trait-correlates perspective” last 2010 which was updated during their second study last 2014 “Exploring impulse buying in services: toward an integrative framework“. The framework consists of several individual and situational variables influencing impulse buying and variety seeking to have deeper understanding of these behaviors by the help of these three relevant consumer traits: Consumer Impulsiveness (CI), Self-monitoring (SM) and Optimum Stimulation Level (OSL).
Statement of the Problem
The research seeks to know and understand if Filipino Millennials are online impulse
buyers and if the four scales: Consumer Impulsiveness Scale (CIS), Optimum Stimulation Level Scale (OSLS), Self-monitoring Scale (SMS), and Level of Impulsiveness in Purchase Decision Scale (IBS) are reliable in the local setting.
1. CI has a negative effect on the level of impulsiveness in purchase decision.
2. OSL has a negative effect on the level of impulsiveness in purchase decision.
3. SM has a positive effect on the level of impulsiveness in purchase decision.
Assumption of the Study
One of the largest generations in history is about to move into its prime spending years.
Millenials are poised to reshape the economy; their unique experiences will change the ways we buy and sell, forcing companies to examine how they do business for decades to come.
This study is conducted based on the following assumptions:
1) That the Filipino Millennials are online impulse buyers.
2) That the respondents can understand the questions.
3) That the scales are reliable in the local setting.
Scope and Limitation of the Study
Participants were millennials aged 19 to 35 years old; student, employed or unemployed;
single or married.
These Millennials are social media users (i.e Instagram, Facebook). Subscribes and
receives promotional emails from different brands, and individuals who have tried buying online using credit card, debit card or cash-on-delivery basis.
Sample of Target Respondents:
Definition of Terms
Impulsivity is often defined as an irresistible urge that coincides with a lack of concern for objective reasoning (Bellman, 2012). It is a fundamental part of human nature.
According to Rook, Impulsive buying behavior, which means a consumer experiences a
sudden, often powerful, and persistent urge to buy something immediately, is the main focus of research on consumer behavior and marketing activities, In the succeeding paragraph Li and Jing (2014), have said that Scholars first paid attention to consumer impulse buying 60 years ago when they focused on the definition of impulsive buying behavior (Li, 2015).
According to Inman & Winer (1998), 59% of purchases are influenced by impulse buying.
This increasing unplanned chase sale is a significant topic to look into by marketing researchers and retailers. Additionally, extreme impulse buying, sometimes referred to as compulsive buying, can result in severe financial consequences for some individuals. However, extreme impulsive buying can cause extreme consequences that can be seen throughout the media.(Bellman, 2012).
Since the 1990s, researchers have begun to study the factors influencing consumer impulse buying and classified them into the following three categories: external environmental stimulation, personality traits, and situational factors (e.g., time pressure) (Dholakia, 2000).
In Lehtonen & Maenpaa 1997, shopping is a satisfying activity. It does not necessarily
purchasing at all but when consumers encounter something interesting they act impulsively. This contrasts from the usual view that shopping is an essential, a rational, task-oriented activity which is directed towards satisfying a functional need – making planned purchases. To date, shopping related activities are considered as leisure and purchasing which is not necessarily the main focus (e.g. Lehtonen&Mäenpää, 1997; Mäenpää, 2005, 209 231). As a result, the more time the consumers are exposed in shopping environments, the more likely they make more impulsive purchases (Mesiranta, 2009).
It has even been argued that discretionary unplanned buying, a form of impulsive buying behavior, has become part of the core meaning of consumer society today (Wood, 2005). If people goes to stores to get only what they need, there will a great deflation in the economy (Paco Underhill, 1999). Impulsive purchasing is, indeed, also an important source of revenue for retailing. As retailers in traditional brick-and-mortar stores have realized the importance of the phenomenon, they have developed strategies to encourage their customers to make more impulsive purchases, for example through in-store promotions, store packaging, and store layouts (Dholakia, 2000).
As mentioned in Kacen & Lee (2002), previous research conducted in the United States
and Great Britain (individualist cultures) has shown that many factors influence impulsive buying behavior: the consumer’s mood or emotional state (Donovan, Rossiter, Marcoolyn, & Nesdale, 1994; Rook, 1987; Rook & Gardner, 1993: Wein- berg &Gottwald, 1982), trait buying impulsiveness (Puri, 1996; Rook & Fisher, 1995; Weun, Jones, & Beatty, 1998), normative evaluation of the appropriateness of engaging in impulse buying (Rook & Fisher, 1995), selfidentity (Dittmar et al., 1995), and demographic factors, such as age (e.g., Bellenger, Robertson, & Hirschman, 1978; Wood, 1998).
Optimum Stimulation Level
According to researchers Hebb & Leuba in (1955), the concept of Optimum Stimulation
Level was introduced simultaneously in psychology literature. They argued in their studies that every organism whether animal or human being prefers certain stimulation which is known as its Optimum Stimulation level. While for McReynolds in 1971 individual behaviour is influenced by the intrinsically motivated desire to accomplish a specific level of stimulation, termed the ‘optimum stimulation level.’ OSL is a personality trait referring to the amount of stimulation individuals prefer in life (Sapra & Mor, 2012)
Optimum stimulation level is a property that characterizes individuals in terms of their
general response to environmental stimuli (Raju 1980). Specifically, all human beings prefer an optimum level of stimulation, so as to try to increase stimulation when the environmental stimulation is below the optimum level and reduce it when it is above the optimum level. Hence, compared to individuals with low OSL, those with higher OSL are chronically lower in their arousal level, and this makes them indulge in sensation-seeking activities to achieve their desired (optimum) stimulation level (Steenkamp and Baumgartner 1992). Prior research associates OSL with risk taking and exploratory behaviors (Baumgartner and Steenkamp 1996), brand switching (Van Trijp et al. 1996), new product adoption (Mittelstaedt et al. 1976), and even impulse buying behavior (Sharma et al. 2010b), which are all inherently risky behaviors because of the uncertainty surrounding a new product or brand or an unplanned purchase. However, consumers with high OSL levels do not mind taking this risk; rather, they feed on this risk and hence may be more likely to indulge in such behaviors.
Self-monitoring can be defined as a fundamental behavioural self-control skill related to
monitoring positively valued behaviours that one is encouraged to increase, and negatively valued behaviours that one is encouraged to decrease (Piwek, Joinson, & Morvan, 2015).
Self-monitoring is defined as the tendency to modify or adapt one’s behavior in response
to others’ presence or behavior (Snyder 1987). High self-monitors are willing to adapt their behavior to enact clearly defined roles appropriate to different situations; low self-monitors are less willing to put on a show to please those around them, preferring instead to be true to their own attitudes and values across different situations (Snyder 1987). These different orientations lead low and high self-monitors to exhibit different behaviors. For example, high self-monitors seek more variety in public (vs. private), in order to depict themselves as interesting and creative people (Ratner & Kahn 2002). High self-monitors also have a greater desire to appear rational when they
feel that their decisions may come under scrutiny by others because they consider themselves as more accountable for their decisions under such circumstances (Lerner &Tetlock 1999). High selfmonitors may also exercise greater control on their impulsive urges and indulge in less impulse buying, compared to low self-monitors (Luo 2005; Sharma et al. 2010b).
According to Aruna&Santhi (2015) impulse buying is relatively extraordinary and
exciting, emotional rather than rational, and likes to be perceived as bad rather than good. It might also be assumed that no pre-purchase stages would be relevant with this (Bayley&Nancarrow, 1998) and impulse buying is an irrational process in which the urge to gratify an impulse triumphs over the rational parts of the mind (Rook, 1987).
Impulse purchase or an unplanned decision to buy a product or service made just before a purchase or on the spot purchase is triggered by stimulus. Marketers and retailers tend to exploit these impulses which are tied to the basic want for instant gratification (Aruna&Santhi, 2015).
Based on the research of Li (2015) Scholars first paid attention to consumer impulse buying 60 years ago when they focused on the definition of impulsive buying behavior (Li & Jing, 2014). Since the 1990s, researchers have begun to study the factors influencing consumer impulse buying and classified them into the following three categories: external environmental stimulation, personality traits, and situational factors (e.g., time pressure; Dholakia, 2000).
As reported by Philippine Daily Inquirer’s Pedroso (July 2015), MasterCard’s study found
that Filipinos turn to the Internet to purchase the following: Airline tickets (38.4 percent), home appliances and electronic products (35.1 percent), clothing and accessories (31 percent), hotels (29.9 percent) and computer software (29.4 percent).
Meanwhile, sites of apps stores (50.1 percent), music downloads (42.6 percent) and home
appliances/electronic products (38.2 percent) draw the most web traffic, the study also showed. Why do Filipinos go online to shop? Ease and convenience are the most cited reasons. “Most of the Filipino respondents are satisfied with online shopping, describing it as easy (73.3 percent), convenient (71.9 percent), or fun (64.4 percent), and expressing greater likelihood to purchase in the next six months (79.2 percent).
The study also found more Filipinos using their mobile phones to purchase items— from
21.4 percent in 2012 to 34 percent in 2014, with 94.2 percent of participants able to access the Internet via smart phones, MasterCard noted, adding that those who purchased via mobile phones did so because they were able to do it “on the go.”(Mastercard, 2014)
Also in accordance with the study of Euromonitor (2016) During 2015, m-commerce
gained a strong following because of the increasing usage and dependency of Filipinos on their smartphones. Popular online shopping conglomerates such as Zalora and Lazada launched their respective mobile applications earlier in the review period and are now being highly used by their customers when they browse their catalogues and purchase products. Aside from money transfer service payment options that internet retailers accept via Globe G-Cash and Smart Money, Smart e-Money Inc partnered with Citi Philippines and Visa to offer Charge2Phone. This service is said to be the first sticker-based contactless payment product in the country, which allows mobile
phones to be transformed into a credit card or wallet. This innovation is expected to further encourage cashless purchase via the internet.
Significant growth of internet retailing in the Philippines was credited to retailers’
continued efforts to develop their businesses by way of providing more product options to their customers, widening their reach to serve other areas apart from Metro Manila and carrying out recurrent promotions such as giving away discounts or markdowns.
Since Filipinos now live more hectic and fast-paced lifestyles, they look for ways to make
things easier and more convenient in order to save time and effort. As a result, some just do their shopping online instead of personally going to store-based outlets to avoid heavy traffic and overly populated shopping centers. Their exposure to various retail channels also made them smart buyers as it gave them the capacity to differentiate between channels and identify those that can give them the best deals, which internet retailers do.
Internet retailing will continue to experience strong growth over the forecast period as more Filipinos are expected to be drawn to the channel due to the convenience, wide selection of products and attractive promotions that retailers will continue to provide.Over the forecast period, internet retailers are also expected to further expand their reach and focus on catering to the needs of other key cities in the country outside of Metro Manila, as the potential seems promising due to the limited shopping centres and retail channels available in the provinces. (“Internet Retailing”, 2016)
Customers’ increasing interest in Internet shopping has led companies to open web-based outlets. Customers can visit and purchase from a 188 International Journal of Electronic Commerce Studies web-based store at a time of their choosing. Customers find the ability to purchase products at any time and from any place particularly appealing aspects of web-based stores (Chen & Hung, 2015)
Shopping online is generally defined as the idea of buying and selling of products over the internet. The sellers’ viewpoint is to convince and catch the attention of the prospective consumers’ to purchase products, and make sure that he / she is satisfied. The buyers’ outlook towards online shopping is the extent to which he / she can access, browse, purchase, transact and repeat the same behaviour. In this digital age consumers are driven by the technology. They are searching for the product on the internet and eventually buying it (Raman, 2014).
Based on the study of Euromonitor, Internet retailing has become one of the most popular ways for consumers to shop in the US. Hence, in 2015, the channel recorded current value growth of 13%. Over the review period most store-based retailers had to add online platforms so as to be able to better compete. As a result, strong store-based players now also command important positions in this channel. Another factor which has favoured internet retailing is the influence of millennial consumers. These consumers are accustomed to using the internet and like shopping online. Moreover, internet retailers continue to drive sales by offering discounts which can only
be used with consumers’ mobile phone applications or via codes which can be used online. Therefore, continuous growth of this channel is a result of a very wide choice of products, an increasing consumer base and retailers’ own efforts. (“Internet Retailing”, 2016).
At 77 million, the millennial generation is one-and-one-half times as large as Generation
X and almost equal in size to the baby boomer generation. Hailed as digital natives, millennials are also described as creative, solution-focused, socially conscious, and team-oriented. (DeVaney, 2015).
From the study of our own DLSU Alumna Pineda &Swedish Researcher Bernhardsson,
The millennials are born after 1985, the millennials have great degree of exposure to media starting at age 0. Most of them grew up with exposure to different forms of traditional and technology enhanced media. At age 8, most of them would have possessed a mobile phone, a music player or tronic game pad. (Deterle, Dede and Schrier, 2008) Many of them grew up with constant access to computers and eventually the web, have constantly visited Wikipedia for their daily homeworks. Millennial learners possess a self-service learning skill, the habitual ability to get fast, relevant and immediate knowledge and information, views technology engagement as second nature together with learning (Pineda, 2009). Millennial learners and technology are coupled together (Pineda &Bernhardsson, 2011).
Correlation of Impulsive Behavioral Studies and Online Shopping
The Reader’s Digest Trusted Brand 2013 Survey showed that only 17 percent of the 1,000
Filipino respondents have significantly changed their shopping habits despite the rising number of online stores in the last two years. “Filipinos might be among the most active netizens on social media, but when it comes to shopping it seems tradition remains a hard habit to break,” it said (Desiderio, 2013).
“The love for shopping is alive among Filipinos. They find joy in going up and down the
aisles to check out grocery items. Retailers can further intensify the in-store shopping experience by offering a pleasant store environment,” said Lou-Ann Navalta, Nielsen’s Shopper Insights leader in the Philippines. Despite the rise of online shopping, Filipinos still prefer making a purchase in a store and seeing, if not touching the goods for themselves.
According to Nielsen’s Shopper Trends Report, at least 9 out of 10 Filipinos enjoy doing
their grocery shopping in-store, with 8 out of 10 wanting to take their time and go through the aisles. (InterAksyon.com)
As said by Raman (2014) online retail market in India has been emerging at an
extraordinary rate. With the growing internet diffusion and broadband availability, and increasing usage of Smart phones and tablets, Indian population have started buying products online. According to a report by Gartner more than 30% of the traffic on online shopping portals is coming from smart phones and tablets. E-commerce industry has picked up pace and has been striding leaps and bounds over the past few years. This scenario is estimated to carry on as the market is expected to reach $14.5 billion by 2018. Forrester Research projections for Asia-Pacific also portray the rapid growth of e-commerce market in India. The prediction depicts e-commerce’s growth in India, where sales are expected to grow by 57% yearly till 2016. It will reach $8.8 billion by 2016. This demand is backed by increase in consumers’ online buying behavior and growing penetration of technology.
According to Nguyen & Nham (2014), online customer loyalty has been the dominating
behavioral issue in researches of customer service. The reason is that customer loyalty nowadays is critical to many aspects of the society, including the e-commerce field. The central thrust of the marketing activities of a firm is often considered to be development, maintenance, or enhancement of customers’ loyalty towards its products/services.
Traditional theories on consumer purchase decisions purport that consumers possess
sufficient information to select and implement the best option. However, such a concept is limited in consideration of actual conditions. Prior to 1982, the definitions of impulse buying focused on the product rather than the consumer as the motivator of impulse purchases (Chen &Zhang, 2015). In the succeeding paragraph Chen & Zhang said that a definite concept of impulse buying remains lacking because it involves complex mental processes and emotional states. However, relevant studies imply that impulse buying involves two principles. First, it lacks a clear, detailed purchase
target, so it is an unplanned action. Second, it is a complex emotional reaction to an external stimulus. Therefore, online impulse buying is defined as an action without consideration or purchase intention and is a result of a mental reaction to an external stimulus from the online environment.
Loopholes and Criticisms
The study made by Sharma, Sivakumaran& Marshall develops a conceptual framework
with several individual and situational variables but focuses on three relevant consumer traits for parsimony and greater control in the empirical study with the retail shoppers only. We tested it for Online Shopping and in the local scene to test its significance and if it will work here in the Philippines. Future research may include different variables that could contribute to the variation of results.
Based on the study made by Sharma, Sivakumaran& Marshall (2010), recent research
shows significant cross-cultural differences in consumer impatience (Chen Haipeng et al., 2005), assumptions about choice and uniqueness (Kim and Drolet, 2003), and level of impulsiveness (Kacen and Lee, 2002). Hence, future research on impulse buying and variety seeking behaviors may benefit by including cultural orientation as an important variable.
This study tested the reliability and correlation of five scales which aims to determine
whether the variables consumer impulsiveness, self-monitoring, and optimum stimulation level predicts level of impulsiveness in purchase decision. Millennials were chosen to answer five scales: Consumer Impulsiveness Scale (CIS), Optimum Stimulation Level Scale (OSLS), Selfmonitoring Scale (SMS), and Level of Impulsiveness in Purchase Decision Scale (IBS).
The study followed the quantitative research design of the existing study. This design is in numerical form so that statistical calculations can be made and conclusions can be drawn. In addition, this will allow the study answer the possible relationships between the variables being tested.
The participants were Millennials, aged 19 to 35 years old. A total of 200 participants
composed of 96 women and 104 men participated in the survey. They were mixed of De La Salle University and Miriam College students and members of the workforce.
They answered a structured questionnaire which consists of close-ended questions. Each
question is systematically constructed in the same words through all the respondents. The surveys are made in paper-and-pencil and online forms for convenience.
The pretest was necessary to find out if the scales were understandable. The participants
for the pre-test were qualified based the inclusion criteria of the study.
We conducted a pretest among 20 participants. Most questionnaires were distributed
among De La Salle University students and a few to working participants. They completed the Consumer Impulsiveness Scale (CIS), Optimum Stimulation Level
Scale (OSLS), Self-monitoring Scale (SMS), and Level of Impulsiveness in Purchase Decision Scale (IBS).
We asked the participants to feel free to approach the researchers for clarifications if they have difficulty understanding the questions. After answering, we asked them on what questions they think should be simplified. This is to help us revise the questionnaire for the actual test.
The researchers distributed paper-and-pencil forms in schools and offices. On the other
hand, we sent the link online to qualified respondents.
We ensured that the instructions were clear. The scales were revised for better
understanding and to guarantee that no questions will be left unfilled.
The participants completed the Consumer Impulsiveness Scale (CIS), Optimum
Stimulation Level Scale (OSLS), Self-monitoring Scale (SMS), and Level of Impulsiveness in Purchase Decision Scale (IBS).
The trait survey included a six-item reduced scale adapted from Sharma et al. (2011) for
CIS, a four-item reduced scale adapted from Steenkamp and Baumgartner (1995) for OSLS, and a five-item scale adapted from Lennox and Wolfe (1984) for SMS; all with seven-point Likert scales (1=strongly disagree and 7=strongly agree). IBS is with a five-item scale adapted from Rook and Fisher (1995) (as shown in Appendix B).
In addition, we asked for the top three situations when do they impulse buy the most and
top three motivator of their impulse buying. We also requested them to mention one online store they transacted with (as shown in Appendix B).
Finally, demographics (age, gender, education, occupation, monthly, and household
income) were recorded (see Appendix A).
A non-probability sampling procedure, namely, convenience sampling method was used
for selecting the sample respondents comprised of the individuals aged between 19 years and 35 years.
Statistical Treatment of Data
The study’s respondents are the millennial people aged 19-35 years old, who are online
shoppers or have tried using the internet to shop. The respondents numbered to two hundred (200). The table below summarizes the gender of the respondents. The table shows that majority of the respondents are male.
Table 2 and 3 summarizes that most of the respondents (139) are employed while 69 out
of the 200 respondents are earning P20,000 – P30,000.
The purpose of this study was to identify if Filipino Millennials are online impulse buyers, to know the reliability of the scales and to understand and analyze the impulse purchase behavior.
The study’s respondents are the millennial people aged 19-35 years old, who are online
shoppers or have tried using the internet to shop. The respondents numbered to two hundred (200). The table below summarizes the gender of the respondents. The table shows that majority of the respondents are male.
Table 4.Summary of Respondent’s preferred time in doing impulse purchase
The table presented the top threetimes by the Filipino Millennial when doing impulsive
purchase decision. 48% says that they do it when they are by themselves, while 45% when they are hungry and 41% when they have time to spare.
Table 5.Summary of what motivates the respondents in doing impulse purchase
The table presents the top three reason what motivates the Filipino Millennialsin doing
impulsive purchases decision. 38.5% said it is just their desire that motivates them in purchasing online, while 37% said when the items are in bargain mode and 35.5% because the goods are trendy.
Table 6. Top 3 Online Store by the Respondents
Table 6 shows the top three online store chosen by Filipino Millennials. 23% said Instagram (a social networking application, using pictures) while Lazada (online goods store) and Zalora(online clothes store) have 14%.
Table 7.Cross tabulation in thinking about choosing the online store
Table 7 cross tabulation strongly shows that the respondents thought about where to online shop before making a purchase while others are neutral about thinking the online store they want.
Table 8.Summary of considering the consequences in choosing an online store
Table 8 shows that most of the respondents thought about what could be the consequences in buying in an online store or thru the internet. Concludes that most of the millennial respondents are thinking and reviewing the online store before purchasing.
Table 9.Summary of how tempting it is to shop online
Table 9 shows that Female respondents shows that 43 of them agreed it is tempting to shop online while there are 37 respondents for male agreed about temptation in shopping online.
Table 10.Summary of Likelihood to do Impulse Buying
Table 10 summarizes that millennial respondents are neutral about doing an impulse purchase online. Question 10 with the average of 4.62% says they are neutral on feeling tempted about buying goods online.
Table 11.Summary of being an Impulsive Consumer
Table 11 presents that the respondents are not impulsive consumers, getting a neutral average of 4.61% as total while Question #17 clearly states that they sometimes plan in advance before making a purchase.
Table 12.Summary of Respondent’s Optimum Stimulation Level.
Table 12 shows that millennial’s behavior are seeking new experience, likes to try different things and continually changing their common activities with an average of 5.035.
Table 13.Summary of Respondent’s Self-Monitoring.
Table 13 shows that the respondents are consistent in a neutral manner towards changing their behavior if the situation calls in for a changing of behavior.
Table 14.Summary of Respondent’s Level of Impulse Buying
Table 14 concludes that the respondents are not showing impulsive behavior towards buying goods online with an average of 3.501.
Table 15. Correlation of Consumer Impulsiveness to Level of Impulse Buying
Consumer Impulsiveness Ave. Level of Impulse Buying Ave.
Table 15 shows the correlation between consumer impulsiveness and level of impulse
buying is weak with an average of 0.37.
Table 16. Correlation of Optimum Stimulation Level to Level of Impulse Buying Optimum Stimulation Level Ave. Level of Impulse Buying Ave.
Table 16 shows that the optimum stimulation level of the respondents has a weak
correlation with the level of their impulse buying with an average of 0.33.
Table 17. Correlation of Self-Monitoring to Level of Impulse Buying
Table 17 shows a weak correlation between the respondents self-monitoring behavior and their level of impulse buying.
Summary, Conclusions, and Recommendations
This study aims to find out the reliability of the existing scales and the correlation of the three variables – consumer impulsiveness, self-monitoring, and optimum stimulation level to level of impulse among Millennials. Convenient sampling was used to gather 200 participants, aged 19-35 years, from private offices and schools. The participants were asked to answer three standardized scales: Consumer Impulsiveness Scale, Self-Monitoring Scale, Optimum Stimulation Level Scale and Level of Impulse Buying Scale.
Correlation results revealed that the three variables – consumer impulsiveness, selfmonitoring, and optimum stimulation level to level of impulse has weak correlation to level of impulse buying.
Consumer impulsiveness is a weak predictor of level of impulse buying. Consumer
impulsive buying behavior is a relatively complex concept and other factors aside from mood, such as budget and price, should be considered (Kwak,Zinkhan, DeLorme, & Larsen, 2006). Therefore, future researchers could utilize field investigations combined with the real impulse buying decision-making process to obtain a more comprehensive research conclusion. (Li, 2015).
Self-monitoring is a weak predictor of level of impulse buying. According to Li (2015)
regardless of whether or not consumers’ impulsive buying behavior occurs, there will be a conflict between consumers’ personal desires to acquire products and their willpower to save money (MacInnis& Patrick, 2006; Mukhopadhyay&Johar, 2007). If willpower is weaker than the desire to buy, impulse buying will occur; otherwise, when willpower is strong, it will not occur.
Optimum stimulation level is a weak predictor of level of impulse buying. High OSL
consumers buy services more impulsively to satisfy their need for stimulation; hence services marketers may enhance the sensations associated with their services to trigger impulse buying for their services.For example, service providers such as fitness clubs and adventure sports companies could arrange free trials for their potential customers in order to attract those with high need for stimulation(Sharma, Sivakumaran, & Marshall, 2014). Results showed that the three variables are weak predictors of level of impulse buying.
The result shows that Filipino Millennials are not impulsive buyers when it comes to
shopping online. Millennials are highly likely to be very critical about the consequences that could happen when they buy online. There is low readiness for online shopping infrastructure as perceived by the respondents which served as barrier for adaptation. If online stores could strengthen the sense of security perception to its target online shoppers and solidify means for a differentiated, value-adding experience of online shopping there might be a change in behavior for the coming years. There are various reasons that could have affected their decisions however it was not tested during the survey. We could suggest that some reasons would be because millennials still prefer brick-and-mortar stores or online stores are not well marketed online.
We recommend that more research with consumers from different age groups to test the
generalizability of our results. Future research may also look beyond the three consumer traits used (i.e., CI, OSL, and SM) and examine the role of other individual and situational factors to develop a more comprehensive conceptual framework for impulse buying in both goods and services.
With this study, online sellers can have a guide how to engage the millennials more on
online shopping. As the study shown, Instagram is the most popular shop among Millennials. This can help Instagram sellers engage more the buyers by having different promotions.
On the other hand, brick-and-mortal stores can foresight on how to improve their strategy how to influence more their customers on buying impulsively buy making the store more unique and interesting. Also, they can add differentiated product offering, enticing price points and specific promotions and advertisements to drive shopper habit preferences in via channel.
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