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8190161 car-buying-behavior

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8190161 car-buying-behavior

  1. 1. On the partial fulfillment of 3rd Tri-semester of POST GRADUATE DIPLOMA IN BUSINESS MANAGEMENT AT INSTITUTE OF MANAGEMENT STUDIES, Ghaziabad We the following students submit our report entitled :: FACTORS AFFECTING CAR BUYING BEHAVIOUR OF CUSTOMERS:: Under the esteemed guidance of Prof. Manish Agarwal ACADEMIC SESSION 2007-2009:: Submitted To :: :: Submitted By ::Dr. Manish Agarwal SHELLY DIXIT (138) TAMONASH ADITYA (160) TARUN KUMAR (165) VIGYAN (178)
  2. 2. INSTITUTE OF MANAGEMENT STUDIES, GHAZIABAD CERTIFICATEThis is to certify that this report contains bonafide work of SHELLY DIXIT, TAMONASHADITYA, TARUN KUMAR, VIGYAN during Term III, session 2007-2009 for the subjectResearch Method in BusinessDATE: Signature of Faculty 40
  3. 3. ACKNOWLEDGEMENTThis report bears the imprint of many people and without their support it wouldnot have existed. First of all we would like to express our sincere indebt ness andprofound sense of gratitude to our parents whose support in all manners had madeus capable to complete this project. We acknowledge our deepest thanks to Prof. Manish Agarwal for allher care and encouraging words and giving suggestion at different point of times.At the outset we would like to put on record our sincere gratitude to all of ourfriends for giving us valuable ideas throughout of our project. Shelly Dixit(138) Tamonash Aditya (151) Tarun Kumar (153) Vigyan (178) 40
  4. 4. IntroductionAccording to the ninth annual Capgemini automotive study – Cars Online 07/08. Each yearthey extend the scope and depth of their survey to explore new and evolving trends within theretail side of the automotive industry, with a particular focus on consumer buying habits. CarsOnline 07/08 continues the detailed analysis of the changing patterns of consumer demand,shopping trends, web usage and customer loyalty that we have uncovered over the past eightyears. This year, however, we have broadened the scope to explore in greater detailenvironmental issues, including fuel-efficient and alternative-fuel vehicles, as well as consumeruse of new online tools, such as web logs, discussion forums and search engines. Theseadditional areas of focus reflect changes in today’s automotive landscape. The industry isclearly in transition, with static sales in almost all developed markets; growing pressure fromAsian manufacturers; eroding customer loyalty; and increased emphasis on environmental andregulatory compliance. Consumer behaviour will be a primary force in determining how thistransition will evolve. Getting closer to the customer in today’s highly competitive landscape isessential for the entire industry and is no longer just a retail issue. It requires all organisationsacross the supply chain to work as a single enterprise, sensing and responding rapidly toconsumer demand in a co-ordinated manner.Capgemini’s annual Cars Online study is designed to give automotive companies informationthat can help them get a better grasp on changing consumer trends, shopping patterns anddemands. This year’s research involved almost 2,600 consumers in five countries: China,France, Germany, the United Kingdom and the United States. Interestingly, we foundsignificant commonalities among responses across the more mature markets, with differencesstill quite apparent in the emerging Chinese automotive market. This report highlights theseresults, as well as country-specific differences. The executive summary provides an overview ofkey findings from the study, and the sections that follow offer more in-depth data and analysison consumer behaviour, environmental issues, web usage, lead management and customerloyalty. The automotive world today is changing; consumers are changing. And the speed ofchange is continuing to accelerate. 40
  5. 5. Executive SummaryCompetitive pressures and increasing complexity have led automotive companies to look for anedge wherever they can find it. Improved consumer insight into vehicle shopping and buyingbehaviour can provide that valuable advantage. Capgemini’s Cars Online report contains insightthat can help vehicle manufacturers and dealers develop and execute more effective strategies inareas such as sales, marketing and advertising, after sales service, Customer RelationshipManagement (CRM) and manufacturer/dealer collaboration. AUTOMOBILE INDUSTRY IN INDIAIn India there are 100 people per vehicle, while this figure is 82 in China. It is expected thatIndian automobile industry will achieve mass motorization status by 2014.Industry OverviewSince the first car rolled out on the streets of Mumbai (then Bombay) in 1898, the AutomobileIndustry of India has come a long way. During its early stages the auto industry was overlookedby the then Government and the policies were also not favorable. The liberalization policy andvarious tax reliefs by the Govt. of India in recent years has made remarkable impacts on IndianAutomobile Industry. Indian auto industry, which is currently growing at the pace of around 18% per annum, has become a hot destination for global auto players like Volvo, General Motorsand Ford.A well developed transportation system plays a key role in the development of an economy, andIndia is no exception to it. With the growth of transportation system the Automotive Industry ofIndia is also growing at rapid speed, occupying an important place on the canvas of Indianeconomy.Today Indian automotive industry is fully capable of producing various kinds of vehicles andcan be divided into 03 broad categories: Cars, two-wheelers and heavy vehicles.Snippets • The first automobile in India rolled in 1897 in Bombay. • India is being recognized as potential emerging auto market. • Foreign players are adding to their investments in Indian auto industry. • Within two-wheelers, motorcycles contribute 80% of the segment size. • Unlike the USA, the Indian passenger vehicle market is dominated by cars (79%). 40
  6. 6. • Tata Motors dominates over 60% of the Indian commercial vehicle market. • 2/3rd of auto component production is consumed directly by OEMs. • India is the largest three-wheeler market in the world. • India is the largest two-wheeler manufacturer in the world. • India is the second largest tractor manufacturer in the world. • India is the fifth largest commercial vehicle manufacturer in the world. • The number one global motorcycle manufacturer is in India. • India is the fourth largest car market in Asia - recently crossed the 1 million mark.Segment Know howAmong the two-wheeler segment, motorcycles have major share in the market. Hero Hondacontributes 50% motorcycles to the market. In it Honda holds 46% share in scooter and TVSmakes 82% of the mopeds in the country.40% of the three-wheelers are used as goods transport purpose. Piaggio holds 40% of themarket share. Among the passenger transport, Bajaj is the leader by making 68% of the three-wheelers.Cars dominate the passenger vehicle market by 79%. Maruti Suzuki has 52% share in passengercars and is a complete monopoly in multi purpose vehicles. In utility vehicles Mahindra holds42% share.In commercial vehicle, Tata Motors dominates the market with more than 60% share. TataMotors is also the worlds fifth largest medium & heavy commercial vehicle manufacturer.MiscellaneousHyderabad, the Hi-Tech City, is going to come up with the first automobile mall of the countryby the second half of 2008. It would be set up by city-based Prajay Engineers Syndicate in areaof more than 35 acres. This Autopolis would have facilities for automobile financinginstitutions and insurance services to create a complete range of services required for both autocompanies and customers. It will also have a multi-purpose convention centre for auto fairs andproduct launches.Cars by Price RangeUnder Rs. 3 Lakhs • Maruti 800, Alto, Omni 40
  7. 7. • Reva • Ambassador • Fiat Palio • Hyundai Santro, Getz • Chevrolet Opel CorsaRs. 3-5 Lakhs • Maruti Zen, Wagon R, Versa, Esteem, Gypsy • Ford Icon & Fiesta • Tata Indica, Indigo XL, Indigo Marina • Chevrolet Swing, Optra Magnum, Tavera • Hyundai Accent, Elantra • Mahindra Scorpio • Maruti Baleno • Toyota InnovaRs. 5-10 Lakhs • Tata Safari • Mitsubishi Lancer, Mitsubishi Cedia • Honda City ZX • Mahindra Bolero • Hyundai Sonata Embera • Toyota Corolla • Ford Mondeo & Endeavour • Chevrolet ForesterRs. 10-15 Lakhs • Skoda Octavia & Combi • Honda Civic • Honda CR-V • Maruti Suzuki Grand Vitara • Terracan & Tucson • Mitsubishi Pajero • Audi A4Rs. 15-30 Lakh • Opel Vectra • Honda Accord • Mercedes C Class • Toyota Camry • Audi A6, A8 & Audi TT • BMW X5, 5 Series & 7 Series • Mercedes E Class, S Class, SLK, SL & CLS-ClassRs. 30-90 Lakhs • Porsche Boxster, Cayenne, 911 Carrera & Cayman S • Toyota PradoAbove Rs. 1 Crore • Bentley Arnage, Bentley Continental GT & Flying Spur 40
  8. 8. • Rolls Royce Phantom • MaybachThe following links gives the complete picture of Indian Auto Industry: The first auto vehicle rolled out in India at the end of 19th century. Today, India is the the 2nd largest tractor and 5th largest commercialAutomobile History vehicle manufacturer in the world. Hero Honda with 1.7M motorcycles a year is now the largest motorcycle manufacturer in the world. On the cost front, OEMs eyeing India in a big way to source products and components at significant discounts to home market. On the revenueIndustry Investment side, OEMs are active in the booming passenger car market in India. The passenger car and motorcycle segment in Indian auto market is growing by 8-9 per cent. The two-wheeler segment will clock 11.5%Industry Growth rise by 2007. Commercial vehicle to grow by 5.2 per cent. India is the 11th largest Passenger Cars producing countries in the world and 4th largest in Heavy Trucks. Maruti Udyog Ltd. is the leading 4-Vehicle Production wheelers manufacturer. Hero Honda is the leading 2-wheelers manufacturer. Passenger vehicle exports have grown over five times and two-wheeler exports have reached more than double. Exports of auto components,Auto Export whose manufacturing costs are 30-40 per cent lower than in the West, have grown at 25% a year between 2000 to 2005. Hero Honda is the largest manufacturer of motorcycles. Hyundai Motors India is the second largest player in passenger car market. Tata MotorsAuto Companies is the fifth largest medium & heavy commercial vehicle manufacturer in the world. Know about the number of vehicles registered as Transport or Non-Vehicle Distribution Transport in the Indian states and Union Territories. Get all the contact details of Automobile Association of Upper India (AAUI), Automotive Research Association of India (ARAI),Associations Automobile Association of Southern India (AASI), Automotive Component Manufacturers Association of India (ACMA) and moreMajor Manufacturers in Automobile Industry 40
  9. 9. • Maruti Udyog Ltd. • General Motors India • Ford India Ltd. • Eicher Motors • Bajaj Auto • Daewoo Motors India • Hero Motors • Hindustan Motors • Hyundai Motor India Ltd. • Royal Enfield Motors • Telco • TVS Motors • DC Designs • Swaraj Mazda LtdGovernment has liberalized the norms for foreign investment and import of technology and thatappears to have benefited the automobile sector. The production of total vehicles increased from4.2 million in 1998- 99 to 7.3 million in 2003-04. It is likely that the production of such vehicleswill exceed 10 million in the next couple of years.The industry has adopted the global standards and this was manifested in the increasing exportsof the sector. After a temporary slump during 1998- 99 and 1999-00, such exports registeredrobust growth rates of well over 50 per cent in 2002-03 and 2003-04 each to exceed two and- a-half times the export figure for 2001-02. 40
  10. 10. Anticipating Consumer ChangesWhat do these findings tell us? They make it clear that consumer behaviour is evolving and thatautomotive companies need to anticipate this evolution in order to be part of, or even influence,the changes. Is your company ready? What changes will you need to make? Companies willneed to take a look at their multi-channel approach as they consider the potential market foronline sales. Effective web strategies will be vitally important, as the online landscape evolvesrapidly with the emergence of powerful consumer-to-consumer tools like blogs, discussionforums, social networking sites and virtual worlds. Automotive companies will need to stayfocussed on environmental developments and evolving consumer attitudes about fuel-efficientand alternative-fuel vehicles. As with the web, green issues are dynamic and it’s still too earlyto determine their ultimate impact on the automotive industry. Manufacturer/dealercollaboration in the form of effective retail integration and integrated lead management willbecome more important than ever to satisfy increasingly sophisticated and demandingconsumers and to retain loyalty. And companies will need to establish and maintain a true two-way dialogue with individual customers through personalised communication. While thistopline review provides a summary of key findings from this year’s Cars Online study, thesections that follow offer more in-depth data and analysis of consumer behaviour,environmental issues, web usage, lead management and customer loyalty.Consumer Behaviour: Turning to the Web and New C2C ToolsConsumers today have a multitude of sources from which to gather information during thevehicle buying process, but the Internet tops the list. The web has become a standard resource inthe shopping process for eight out of 10 consumers when researching car purchases. However,the way they use it is changing. As the web matures, vehicle buyers are visiting fewer sites andfocussing more on manufacturer and C2C websites and less on third-party information sites andindependent e-tailer sties.Manufacturer Sites a Key Information SourceJust two years ago, information websites were identified as the number one information sourceby web users responding to the Cars Online survey (tied with family and friends andmanufacturer specific dealer), named by 55% of consumers. This year, they dropped to thenumber four source, named by 41% of web users. In comparison, manufacturer sites are nowthe top source for consumers who use the web when researching vehicles, named by 70% ofrespondents. Two years ago manufacturer sites held the number three position, named by 43% 40
  11. 11. of web users. The use of dealer websites has remained steady, with about half of web usersturning to these sites. 40
  12. 12. At the same time, the use of new online consumer-to-consumer tools such as blogs, RSS (ReallySimple Syndication) feeds, user-generated content, social networking sites and web forums is 40
  13. 13. growing. In this year’s study, 29% of web users indicated that they use these kinds of toolswhen researching during the vehicle shopping process, up from 21% a year ago. (For a moredetailed analysis of the use of these new online tools see separate section on “Web Usage.”)Interestingly, it is not just the young generation who use the web to research vehicles. Almosthalf of consumers 50 and older visit manufacturer sites, nearly the same number as those in the18 to 34 age group. The numbers do fall off, however, when it comes to blogs and web forums.About 30% of the youngest consumers rely on these new tools, compared with just 12% ofthose 50 and older. As web usage rises, consumer reliance on other more traditional informationsources is on the decline. Take print advertising, for example, which has shown a steadydownward trend particularly among consumers who rely on the web during the vehicleshopping process. This year, just 20% of web users said they useprint ads when researching vehicles, compared with 32% in 2005. The message for automotivecompanies is clear: Consumers trust the information they receive from manufacturer and C2Csites. Vehicle manufacturers and dealers need to be aware of how fast online changes areoccurring and continually adjust their marketing mix and resources accordingly to anticipatetomorrow’s mix. Marketing funds directed toward more traditional media such as printadvertising should be regularly re-examined for ROI.Key Factors in Vehicle ChoiceWhen it comes to making their final decision about which vehicle to buy, consumers focus onfactors such as reliability, safety, price and fuel economy. At the bottom of the list are cash-backincentives, named by fewer than half of consumers. The importance of incentives as a decidingfactor has declined for the past several years, indicating that consumers today seem lessinterested in gimmicks when it comes to their car purchases. Where consumers are in the buyingcycle can make a difference in how they rank the factors that influence their vehicle choice. Forexample, additional warranty coverage is important to consumers who are furthest away fromthe point of purchase; it was named by 69% of respondents who were 13 to 18 months frompurchase. However, the number declines as consumers get closer to actually buying the car:55% of respondents who were within three months of purchase said extra warranty coveragewas important. This reflects the fact that consumers will narrow down the factors that reallymatter to them as they get closer to the point of purchase. Demographic factors such as age andgender accounted for some variances. For example, older consumers tend to put more emphasis 40
  14. 14. on reliability and safety than do younger respondents. Those in the 50-plus age group were alsomore concerned with environmental issues and fuel economy. The youngest respondents weremost likely to rate the ability to research information on the Internet as an important factor intheir vehicle decision. Women tend to rate most of the factors as more important than do men.The difference was most pronounced for cash-back incentives, low financing, safety,environmental issues, fuel economy and additional warranty coverage. 40
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  16. 16. Going ‘Green’: Fuel Efficiency Takes Centre StageFuel efficiency and environmental issues have moved to the forefront in consumers’ minds andin automotive industry forums thanks to factors including global warming, fluctuating gasolineprices, and proposed legislation to increase fuel efficiency and reduce CO2 emissions. Thisgrowing interest in so-called green vehicles was evident in this year’s Cars Online research.More than one-quarter of respondents said they currently own or lease a fuel-efficient vehiclewhile almost half said they are planning to buy or thinking seriously about buying a fuel-efficient vehicle. Not surprisingly, the numbers for alternative-fuel vehicles were lower. Just 2%of respondents currently own an alternative-fuel vehicle and 11% are planning to buy orthinking seriously about buying one. The most common type of alternative-fuel vehiclerepresented in the survey were gas/ electric hybrids, named by about half of current alternative-fuel car owners.Biodiesel vehicles were the second most common, named by 15%. The alternative-fuel marketremains in transition and it’s still too early to tell how it will ultimately shake out, althoughsales are expected to continue to grow. For example, J.D. Power and Associates predicts thatU.S. sales of hybrid vehicles will increase by 35% in 2007, compared with 2006.Current ownership of fuel-efficient and alternative-fuel vehicles tended to be quite consistentacross gender and age groups, although the oldest consumers were somewhat more likely to beseriously thinking about buying an alternative-fuel car. 40
  17. 17. Why Buy a Green Vehicle?Fuel economy is the number one factor driving consumer decisions about green vehicles(named by 57% of respondents), followed by the impact on the environment (23%). Tax creditsand cost factors were less important. Some consumers pointed to less tangible reasons such as“it makes me feel better.” This is in line with research conducted by CNW Marketing Research.When asked why they bought a Toyota Prius, 57% of Prius owners said because it “makes astatement about me.” However, the Cars Online research uncovered some differences in thereasons behind consumer decisions about green vehicles. For example, European consumerswere more likely to cite environmental impact as a primary factor, while more respondents inChina and the U.S. pointed to fuel economy. Older consumers were somewhat more likely toidentify fuel economy as a primary factor, compared with the youngest respondents (18-34).Men put more emphasis than did women on fuel economy, while a higher proportion of womenidentified environmental impact as the primary reason driving their decisions about greenvehicles. 40
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  19. 19. PERSONAL SELLING: CONSUMER BUYING BEHAVIOR CONSUMER BUYING vs. ORGANIZATIONAL BUYINGFinal (or ultimate) consumers purchase for: • personal, • family, or • household useOrganizational consumers purchase for: • further production, • usage in operating the organization, and/or • resale to other consumersConsumer Buying BehaviorThe decision processes and acts of final household consumers associated with evaluating,buying, consuming, and discarding products for personal consumptionConsider the purchase an automobile. You generally will not consider different options untilsome event triggers a need, such as a problem needing potentially expensive repair. Once thisneed has put you "on the market", you begin to ask your friends for recommendations regardingdealerships and car models. After visiting several dealerships, you test drive several models andfinally decide on a particular model. After picking up your new car, you have doubts on the wayhome, wondering if you can afford the monthly payments, but then begin to wonder if insteadyou should have purchased a more expensive but potentially more reliable model. Over the nextfive years, the car has several unexpected breakdowns that lead you to want to purchase adifferent brand, but you have been very happy with the services of the local dealership anddecide to again purchase your next car there. 40
  20. 20. In this particular case, the following generic model of consumer decision making appears tohold:=====>need recognition =====>information search =====>evaluation of alternatives =====>purchase decision =====>postpurchase behaviorNow consider the purchase of a quart of orange juice. You purchase this product when you doyour grocery shopping once per week. You have a favorite brand of orange juice and usually doyour grocery shopping at the same store. When you buy orange juice, you always go to thesame place in the store to pick it up, and never notice what other brands are on the shelf or whatare the prices of other brands. How is it that the generic model above works differently in thissecond scenario? Why does it work differently? Why would we generally need the ministrationsof a sales person in the sale of a car, but we generally do not need the help of a salesperson inthe purchase of orange juice?How can the marketer of orange juice get a consumer like you to exert more effort intoinformation search or to consider alternative products? How is it that the marketer of your brandgot you to ignore alternative competing brands? What is the involvement of salespeople in salespromotions that might be associated with products such as orange juice?Consumer behavior researchers are not so interested in studying the validity of the abovegeneric model, but are more interested in various factors that influence how such a model mightwork.INFLUENCES ON THE GENERIC MODEL • external o group -e.g., cultural, family, reference group influences 40
  21. 21. o environmental/situational -e.g., time of day, temperature and humidity, etc. • inernal o lifestyle, personality, decision making process, motivation, etc.GROUP INFLUENCES ON CONSUMER BEHAVIORCulturethe set of basic values, beliefs, norms, and associated behaviors that are learned by a member ofsocietyNote that culture is something that is learned and that it has a relatively long lasting effect onthe behaviors of an individual. As an example of cultural influences, consider how thesalesperson in an appliance store in the U.S. must react to different couples who are consideringthe purchase of a refrigerator. In some subcultures, the husband will play a dominant role in thepurchase decision; in others, the wife will play a more dominant role.Social ClassA group of individuals with similar social rank, based on such factors as occupation, education,and wealthReference GroupsGroups, often temporary, that affect a persons values, attitude, or behaviors • E.g., your behaviors around colleagues at work or friends at school are probably different from your behaviors around your parents, no matter your age or stage in the family life cycle. If you were a used car salesperson, how might you respond differently to a nineteen year old prospect accompanied by her boyfriend from one accompanied by two girlfriends? • Opinion leader A person within a reference group who exerts influence on others because of special skills, knowledge, personality, etc. 40
  22. 22. o You might ask the webmaster at work for an opinion about a particular software application. Software manufacturers often give away free beta copies of software to potential opinion leaders with the hope that they will in turn influence many others to purchase the product. • Family A group of people related by blood, marriage, or other socially approved relationshipENVIRONMENTAL / SITUATIONAL INFLUENCES ON CONSUMERBEHAVIORCircumstances, time, location, etc.Do you like grapes? Do you like peas?You might like grapes as a snack after lunch, but probably not as a dessert after a fancy meal ina restaurant. You might like peas, but probably not as a topping on your pancakes. Everydaysituations cause an interaction between various factors which influence our behaviors. If youwork for tips (a form of incentive related to commission) as a waiter or waitress, you mustcertainly be aware of such interactions which can increase or decrease your sales.If you are doing your Saturday grocery shopping and are looking for orange juice, you areprobably much more sensitive to price than if you stop at the quick store late at night, when youare tired and cranky, after a late meeting at the office. A prospect shopping for a newautomobile while debating the wisdom of a necessary expensive repair to his car might be moreinterested in what cars are on the lot than in shopping for the best deal that might involve aspecial order.INTERNAL INFLUENCES ON CONSUMER BEHAVIORPersonalityA persons distinguishing psychological characteristics that lead to relatively consistent andlasting responses to stimuli in the environment 40
  23. 23. We are each unique as individuals, and we each respond differently as consumers. For example,some people are "optimizers" who will keep shopping until they are certain that they have foundthe best price for a particular item, while other people are "satisficers" who will stop shoppingwhen they believe that they have found something that is "good enough." If you are asalesperson in a retail shoe store, how might you work differently with these two personalities?Lifestyle and Psychographics • lifestyle is a pattern of living expressed through a persons activities, interests, and opinions • psychographics is a technique for measuring personality and lifestyles to developing lifestyle classificationsMotivation: Multiple motivesConsumers usually have multiple motives for particular behaviors. These can be a combinationof: • manifest known to the person and freely admitted • latent unknown to the person or the person is very reluctant to admitNote: different motives can lead to the same behavior; observing behavior is not sufficient todetermine motives. 40
  24. 24. What are the thoughts of Johns friend?What is Johns manifest motive?What might be his latent motive?How might a salesperson discover these motives? What features should a salespersonemphasize?InvolvementHas to do with an individuals • intensity of interest in a product and the • importance of the product for that personThe purchase of a car is much more risky than the purchase of a quart of orange juice, andtherefore presents a higher involvement situation. This modifies the way that the generic modelworks.As involvement increases, consumers have greater motivation to comprehend and elaborate oninformation salient to the purchase. A life insurance agent, for example, would typically bemore interested in contacting a young couple who just had a baby than an eighteen year oldcollege student - even though the new parents might be struggling to make ends meet while thestudent is living more comfortably. Although the annual investment into a policy is much lowerif started at a younger age, most young college students are not open to thinking about long term 40
  25. 25. estate planning. A young couple with a new child, however, is much more open to thinkingabout issues associated with planning for the childs future education, saving to buy a house, oreven saving to take an extended vacation upon retirement.TYPES OF CONSUMER PROBLEM-SOLVING PROCESSESRoutinized • used when buying frequently purchased, low cost items • used when little search/decision effort is needed • e.g., buying a quart of orange juice once per weekLimited Problem Solving • used when products are occasionally purchased • used when information is needed about an unfamiliar product in a familiar product categoryExtended problem solving • used when product is unfamiliar, expensive, or infrequently purchased • e.g., buying a new car once every five yearsUnder what sorts of conditions would the assistance of a salesperson be needed? Not needed?POST-PURCHASE CONSUMER BEHAVIORSatisfactionAfter the sale, the buyer will likely feel either satisfied or dissatisfied. If the buyer beleives thats/he received more in the exchange than what was paid, s/he might feel satisfied. If s/he believesthat s/he received less in the exchange than what was paid, then s/he might feel dissatisfied.Dissatisfied buyers are not likely to return as customers and are not likely to send friends,relatives, and acquaintences. They are also more likely to be unhappy or even abusive when theproduct requires post-sale servicing, as when an automobile needs warranty maintenance.The above idea can be modeled as Homans basic exchange equation: 40
  26. 26. Profit = Rewards - CostsUnfortunately, even a buyer who "got a good deal" with respect to price and other terms of thesale might feel dissatisfied under the perception that the salesperson made out even better.This idea is called equity theory, where we are concerned with: Outcomes of A Inputs of A vs. Outcomes of B Inputs of BConsider, for example, that you have purchased a used car for $14,000 after finding that the"e;blue book" value is listed at $16,000. You are probably delighted with the purchase until youaccidentally meet the prior owner who had received a trade-in of $10,000 on the car just a fewdays before. That the dealer appears to have received substantially greater benefit than youcould lead to extreme dissatisfaction, even though you received good value for the money spent.(Note that the selling dealer might actually have paid $12,000 for the car at a statewide dealersauction, and then might have incurred another $1,000 in expenses associated with transportingthe car and preparing it for sale. Management of buyer perceptions is very important!)An issue related to this is attribution theory. According to attribution theory, people tend toassign cause to the behavior of others. Marys life insurance agent advises her to purchase awhole life policy, while her accountant advises her, "buy term insurance and invest thedifference.". The reason, explains the accountant, "is that insurance agents receive substantiallyhigher commission payments on sales of whole life policies."If Mary believes that the insurance agent is recommending a product merely because hereceives a higher commission, she will likely be displeased with the relationship and will nottake his recommendation. If the agent is able to show Mary that the recommended product is thebest solution for her situation, then she will likely attribute his recommendation to having her 40
  27. 27. best interests in mind and will not be concerned about how it is that he is compensated for hisservices.Cognitive dissonanceIt has to do with the doubt that a person has about the wisdom of a recent purchaseIt is very common for people to experience some anxiety after the purchase of a product that isvery expensive or that will require a long term commitment. Jane and Fred, for example, signeda one year lease on an apartment, committing themselves to payments of $1500 per month. Aweek later, they are wondering if they should have instead leased a smaller $900 apartment in amore rough part of town; they are not sure if they really can afford this much of a monthlyobligation. Dick and Sally, on the other hand, ultimately rented the $900 apartment, and noware wondering if the savings in rent will be offset by noisy and sometimes unsafe conditions inthis neighborhood.Perhaps neither couple would be experiencing this anxiety if their landlords had given them justthe smallest of assurances that they had made a good decision. After a close on products that areexpensive or that require a long term commitment, the salesperson should provide the prospectwith some reasons to be happy with the decision. Allow the car buyer to reinforce her ownpositive feelings by calling her a week after the purchase to ask how things are going. Call thenew life insurance policy holder after two months to see if there are any questions; a lack ofquestions can only help the buyer to convince himself that he did the right thing.MethodologyThe study is based on primary data collection with a sample size of 100 respondents residing inNational Capital Region of New Delhi, India. The questionnaire used for the sample survey is astructured and non-disguised questionnaire and consisted of two major sections. The firstsection intended to collect the various demographic factors; the second section intended tocollect the various opinions containing questions about the various factors affecting the carpurchasing decision. A five point Likert scale was used to capture the consumers responsesranging from strongly agree to strongly disagree. The different statements regarding the variousfactors affecting the car buying behavior of customers were generated based on literature review 40
  28. 28. as well as expert opinion in an iterative manner. It could be therefore said that the itemized scalein this case actually asks the respondents to rank their opinions in a decreasing order ofimportance. Data analysis was done using SPSS software. The statistical analysis methodsemployed was factor analysis. To study the impact most frequently indulged in weightedaverage method was used.Data collectionThe study entailed data collection with the help of a questionnaire from the residents ofNational Capital Region of New Delhi, India. Data was collected by personally contacting therespondents and explaining in detail about the survey. A total of 120 customers from differentareas were contacted and 100 correctly completed questionnaires were obtained from all thecustomers, the break-up of which is given in Figure 1,2 and 3Descriptive profile of respondents (n=100)Gender Percentage Female Male 0 20 40 60 80 100 Fig 1 Fig 2 Age 40
  29. 29. 60 40 20 0 Percentage Below 18 18-25 26-35 36-50 Above 51 Occupation 60 40 20 Percentage 0 Service Business Student House-Wife Fig 3Findings and AnalysisFactor Analysis for factors affecting car purchasing decision 40
  30. 30. Factor analysis was performed to identify the key dimensions affecting purchase of carsprovided by different car manufacturing companies. The respondent ratings were subject toprincipal axis factoring with varimax rotation to reduce potential multicollinearity among theitems and to improve reliability on the data (see Table 6: Rotated Factor Matrix). Varimaxrotation (with Kaiser Normalization was converged in thirty-one iterations. Thirty items werereduced to nine orthogonal factor dimensions which explained 73.555% of the overall variance(Table 4) indicating that the variance of original values was well captured by these nine factors.The nine factors and their components is given in table 7. Reliability of Data Table 1: KMO and Bartletts Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .769 Bartletts Test of Approx. Chi-Square 1650.000 Sphericity df 435 Sig. .000 Kaiser-Meyer-Olkin [Index for comparing the magnitudes of the observed co-relation coefficient to themagnitude of the partial correlation coefficients] From the above table, we can interpret that there is no error in 76.9% of the sample and inthe remaining 23.1%, there may occur some sort of error. “Bartlett’s Test of Sphericity” [Strength of relationship among variables is strong. It presents good idea to proceed tofactor analysis for the data.] Ho : There is significant indifference of all the factors affecting car purchase decision H1 : There is significant difference of all the factors affecting car purchase decision The observe significance level is 0.0000 which is less than .05, which is small enough toreject the hypothesis. It means there is a significant difference between the factors affectingcar purchasing decisions.Communality”- Common Factor Variance Communality of each statement refers to the variance being shared or commonby other statements. With reference to the first statement, the extraction is .833 which indicatesthat 83.3% of the variance is being shared or common to other statements. Refer Table 2. 40
  31. 31. “Eigen Value”: Indicates the amount of variance in the original variables accounted or by eachcomponent. The total initial variance in the new components will be 30. Table 2: Communalities Initial Extraction S1 1.000 .833 S2 1.000 .692 S3 1.000 .760 S4 1.000 .800 S5 1.000 .695 S6 1.000 .795 S7 1.000 .746 S8 1.000 .731 S9 1.000 .783 S10 1.000 .875 S11 1.000 .851 S12 1.000 .782 S13 1.000 .642 S14 1.000 .628 S15 1.000 .674 S16 1.000 .715 S17 1.000 .662 S18 1.000 .707 S19 1.000 .653 S20 1.000 .728 S21 1.000 .762 S22 1.000 .710 S23 1.000 .642 S24 1.000 .687 S25 1.000 .835 S26 1.000 .684 S27 1.000 .803 S28 1.000 .683 S29 1.000 .857 S30 1.000 .650Extraction Method: Principal Component Analysis. 40
  32. 32. Table 3: Total Variance Explained Extraction Sums of SquaredComponent Initial Eigenvalues Loadings Rotation Sums of Squared Loadings % of Cumulative % of Cumulative % of Cumulative Total Variance % Total Variance % Total Variance % 1 7.102 23.672 23.672 7.102 23.672 23.672 3.398 11.327 11.327 2 3.539 11.798 35.470 3.539 11.798 35.470 3.227 10.756 22.083 3 2.543 8.477 43.947 2.543 8.477 43.947 3.080 10.268 32.350 4 2.188 7.292 51.239 2.188 7.292 51.239 2.556 8.520 40.870 5 1.716 5.721 56.960 1.716 5.721 56.960 2.543 8.476 49.345 6 1.631 5.435 62.396 1.631 5.435 62.396 2.356 7.855 57.200 7 1.218 4.059 66.455 1.218 4.059 66.455 1.909 6.364 63.564 8 1.112 3.706 70.161 1.112 3.706 70.161 1.718 5.725 69.289 9 1.018 3.394 73.555 1.018 3.394 73.555 1.280 4.266 73.555 10 .948 3.160 76.715 11 .815 2.717 79.432 12 .683 2.278 81.710 13 .634 2.113 83.823 14 .567 1.889 85.712 15 .500 1.667 87.379 16 .489 1.631 89.010 17 .439 1.464 90.475 18 .421 1.403 91.878 19 .330 1.099 92.976 20 .297 .991 93.967 21 .277 .924 94.891 22 .271 .905 95.796 23 .226 .752 96.547 24 .209 .697 97.245 25 .194 .647 97.892 26 .183 .608 98.501 27 .161 .537 99.038 28 .129 .431 99.468 29 .089 .297 99.766 30 .070 .234 100.000 Extraction Method: Principal Component Analysis. 40
  33. 33. Table 4: Cumulative Frequency Component 1 Explain a variance of 3.398, which 11.327% is 11.327 % of the total variance of 30 Component 2 Explain a variance of 3.327, which 22.083% is 10.756 % of the total variance of 30 Component 3 Explain a variance of 3.080, which 32.350% is 10.268 % of the total variance of 30 Component 4 Explain a variance of 2.556, which 40.870% is 8.520 % of the total variance of 30 Component 5 Explain a variance of 2.543, which 49.345% is 8.476 % of the total variance of 30 Component 6 Explain a variance of 2.356, which 57.200% is 7.855 % of the total variance of 30 Component 7 Explain a variance of 1.909, which 63.564% is 6.364 % of the total variance of 30 Component 8 Explain a variance of 1.718, which 69.289% is 5.725 % of the total variance of 30 Component 9 Explain a variance of 1.280, which 73.555% is 4.266 % of the total variance of 30 40
  34. 34. Scree Plot 8 7.1 6 Eigenvalue 4 3.54 2.54 2.19 2 1.63 1.72 1.11 0.95 1.22 0.68 0.57 0.49 1.02 0.44 0.3 0.82 0.28 0.23 0.63 0.19 0.16 0.13 0.5 0.07 0.42 0 0.33 0.27 0.21 0.18 0.09 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Component Number Fig 4With the help of table 3 and 4, we can interpret that 30 statements are now reduced to 9components contributing 73.555% of the total variance. With the help of Fig1. Scree plot, wecan just visualize that nine factors are reduced with eigen value greater than 1.0000Table 5. Component Matrix:This table reports the factor loadings for each variable on the unrotated components or factors. Component Matrix 40
  35. 35. Component 1 2 3 4 5 6 7 8 9S1 .377 .267 .541 -.333 .217 .171 -.327 .176S2 -.166 -.163 -.228 .665 -.119 .180 .303S3 .649 -.382 .347 .119 .188 .121S4 -.551 -.191 .503 .338 -.271 -.106S5 .599 -.244 .388 .141 .102 .115 .108 -.166 .210S6 .751 -.265 -.164 -.156 .291 .131S7 .223 .232 -.138 .223 -.344 .390 -.237 .498S8 .430 .124 .128 .249 .581 .125 .306S9 -.104 -.267 .229 .699 -.224 -.271 -.147S10 -.170 .698 -.418 .363 .129 .178S11 .232 .808 -.272 .132 -.161 .157S12 -.542 -.211 .628 .144 .135S13 .177 .528 .462 -.216 -.103 .205 -.100S14 .627 -.139 -.171 -.220 .279 -.227S15 .689 .337 .100 -.197S16 .569 .357 .170 .273 -.119 -.346 -.154S17 -.312 .398 .592 .161 -.109S18 .481 .343 .427 .117 -.343 -.183S19 .718 -.106 -.196 -.273S20 -.395 -.122 .254 .107 .667 .163S21 .730 -.205 -.139 .116 -.367 .114S22 .537 -.294 .154 -.108 .245 .470S23 .484 -.354 .115 .311 .395S24 .368 .168 .226 -.252 .527 .104 -.341S25 -.499 .207 .617 -.288 -.106 -.145 .191S26 .621 .112 .187 .256 .323 .186 -.195S27 -.503 .430 .516 .251 -.138S28 .652 .247 .227 -.278 -.236S29 -.535 .186 .663 .112 .158 -.225S30 .459 .422 .117 -.300 -.123 -.153 .335 Extraction Method: Principal Component Analysis. a 9 components extracted. Each number represents the correlation between the item and the unrotated factor. This correlation helps to formulate an interpretation of the factors or components. This is done by looking for a common thread among the variables that have large loadings for a particular factor or component. It is possible to see items with large loadings on several of the unrotated factors, which makes interpretation difficult. In these cases, it can be helpful to examine a rotated solution. Table 6: Rotated Component Matrix 40
  36. 36. Component 1 2 3 4 5 6 7 8 9S1 .447 .753 .205S2 .191 -.765 -.115 .201S3 -.122 -.414 .591 .282 .153 .194 .284S4 .189 -.123 -.799 -.232 -.134 -.175S5 -.374 .570 .295 .158 .158 .120 .256S6 .755 -.192 .102 .304 .114 .265S7 .219 .191 .111 .799S8 .150 .821 .131S9 .308 -.308 .193 .388 -.466 -.213 -.344 .135S10 .826 -.152 -.253 -.293S11 .872 .134 .117 .225S12 .210 -.138 -.329 .177 -.570 -.208 -.404 .108 .190S13 .319 .221 .122 .109 .224 .643S14 -.337 .481 .152 -.114 .371 .272 .180S15 -.174 .271 .385 .215 .156 .379 .302 .332S16 -.213 .438 .566 .235 -.267 .172S17 .113 .429 .161 -.165 -.591 -.139 -.195S18 .311 .513 .233 .426 .136 -.238 -.190S19 -.499 .225 .152 .482 .269 .124S20 -.182 -.821S21 -.422 .323 .280 .148 -.112 .543 .217 -.140S22 -.151 -.205 .226 .413 .263 -.129 .551 -.178S23 -.187 .212 .178 .187 .670 .175S24 .809 .143S25 .885 -.160 -.120S26 -.179 .105 .537 .391 .167 .246 -.135 .207 -.222S27 .851 .195 -.103 -.151S28 -.289 .250 .636 .215 .121 .148 -.157 .152S29 .860 -.290 -.107S30 .141 .413 .107 .274 .461 .276 .281 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a Rotation converged in 31 iterations. With the help of table 6, we can categorize each statements depending upon the factor loadings and shown in table7. Table 7: Factors Factor 1: • S19 : Information Provided By Salesperson • S25 :Safety • S27 : Easy Availability Of Spare Parts • S29 : Technology 40
  37. 37. Factor 2:• S10 : Government Policies And Regulations• S11 : Import Duties Imposed By Government Factor 3:• S3 : Family Needs• S5 : Brand Image• S6 : Income Level• S8 : Special Family Programs/Events Like Anniversary, Birthday• S15 : Insurance Facility• S18 : Credit Card Acceptance• S26 : Car Accessories Factor 4:• S14 : Installment Payment Facility• S16 : Location Of The Car Dealer Shop• S24 : Looks• S28 : Availability Of Service Station Factor 5:• S4 : Status Symbol• S12 : Advertisements And Promotions• S17 : Home Delivery Facility• S30 : Overall, I Am Satisfied With My Car I Own Factor 6:• S1 : Price Of The Car• S2 : You Take Suggestions Of Your Family Members• S9 : Family Members & Friend Circle• S13 : After Sales Service Factor 7:• S20 : Availability Of Variety Of Cars Under One Roof• S21 : Information Provided By Various Car Related Magazines Factor 8: 40
  38. 38. • S22 : Mileage • S23 : Power Factor 9: • S7 : Festival Season/Offers Table 8: Component Score Coefficient Matrix Component 1 2 3 4 5 6 7 8 9S1 .019 -.096 .179 -.106 -.051 .347 -.042 -.094 .209S2 .062 .064 .164 -.069 -.018 -.386 -.001 .100 .174S3 .051 -.113 .193 .009 -.025 -.058 .034 .119 -.033S4 .026 -.010 .082 .079 -.386 -.084 .132 -.020 -.120S5 .022 -.144 .202 -.001 -.010 .062 -.054 -.017 .226S6 -.031 .226 -.105 .060 -.035 .102 -.080 .101 .149S7 .010 .031 .009 -.035 .016 -.053 .008 .035 .627S8 .011 .064 .400 -.185 -.120 -.091 -.054 .111 .065S9 .119 -.112 .105 .005 .244 -.177 -.097 -.193 .122S10 -.055 .261 .081 -.028 .029 -.074 -.163 -.101 .035S11 .040 .282 .025 -.007 .003 -.087 .116 .059 -.023S12 .030 -.011 -.075 .212 -.240 -.050 -.187 .164 .124S13 .099 .022 .000 .047 .097 .282 -.100 -.043 -.010S14 -.022 .010 -.099 .169 -.035 -.110 .175 .103 .078S15 .007 .080 .084 -.017 -.037 .084 .068 .150 .041S16 -.048 -.037 .092 .240 -.129 .031 .099 -.311 .084S17 -.013 .149 .148 -.012 -.305 .020 .046 -.028 -.147S18 .048 .087 .145 .057 .150 -.049 .019 -.200 -.191S19 -.111 -.007 -.011 -.033 .164 -.004 .054 -.026 -.087S20 -.080 .034 .081 .039 .056 -.001 -.563 .075 -.067S21 -.040 .001 .028 .042 -.054 -.130 .289 .050 -.139S22 .037 -.002 .006 .158 .071 -.077 -.219 .358 -.196S23 .021 .001 .076 -.179 -.028 -.022 .021 .444 .171S24 .073 .026 -.146 .470 -.076 .010 -.068 .035 -.079S25 .329 -.023 -.029 -.008 .116 -.040 .076 .130 -.021S26 -.027 .055 .148 .147 -.006 .085 -.248 .079 -.225S27 .291 .047 .067 .001 .027 -.041 .061 .013 .003S28 -.071 -.018 -.032 .289 .000 .079 -.004 -.250 .039S29 .295 -.042 .018 .112 -.102 .018 .125 .001 -.044S30 .150 .153 -.061 .078 .170 -.117 .109 .201 -.132 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. 40
  39. 39. From the table 8 of component score coefficient matrix, we can obtain the quantifiable data of eachfactor. The coefficients between the statements and the factors are taken according to the statementaffecting the factor ( on the basis of Table 7)Conclusions and RecommendationsSince Indian Automobile market is continuously in the prowl of surging as a major carmanufacturer, people are purchasing car as there is increase of income of common people aswell as change in tastes and preferences of consumers. It is important for the car manufacturersand car dealers to be able to understand the different factors affecting the extent in carpurchasing behaviour. The factor analysis results indicate that factor 1 (table 7) which consistsof Information provided by salesperson; safety; easy availability of spare parts; technology areaffecting the car purchasing behavior. People are more conscious about the on spot informationprovided about various cars who serves according to the needs and wants of the customer. Thetype of technology used and the wider reach of the service stations also affect the most on carpurchasing decision. While government obligations and various policies like import duties,custom exemptions is seen as second most affecting driver (factor 2, table 7) of purchase ofcars. Factor 3 includes family needs; brand image; income level; special family programs/eventslike Anniversary, Birthday; insurance facility; credit card acceptance; car accessories affectscustomers car purchase decision causing a variance of 3.080.This shows that importance offamily decisions, special occasions in family and the various services provided by car dealers.Factor 4, Table 7 includes installment payment facility; location of the car dealer shop; looks;availability of service station showing customers accessibility to the service provided. Factor 5shows the impact of various promotional activities and extra care taken by car dealers. Factors 6shows the impact of suggestion provided by family members and peers as well as price and aftersales service provided. Factor 7 includes the infrastructural benefits of the shop and the varietyof cars it stores .The last but not the least ones shows the impact of factors of technicalspecifications of the car and the festive season offersOverall, various internal and external factors like extra care facilities, location of the shops,various information provided by car dealers, advertisement and print media promotions,features of the car in all are contributing in making car purchasing behaviour of customers. 40
  40. 40. ANNEXURE Opinion SurveySection IDemographic FactorsName……………………………………………………………Gender…………..Age Below18 18-25 26-35 36-50 51 and aboveOccupation Service Business Student HousewifeSection IIAccording to you which of these Factors are Affecting Car Purchasing Decision in India.Please fill according to instruction in bracket given below 40
  41. 41. (SA-Strongly Agree; A-Agree; N-Neutral; DA-Disagree; SDA-Strongly Disagree)Sl.No Statements Strongly Agree Neutral Disagree Strongly Agree Disagree1. Price Of The Car2. You Take Suggestions From Your Family Members3. Family Needs4. Status Symbol5. Brand Name6. Income Level7. Festival Season/Offers8. Special Family Programs/Events Like Anniversary, Birthday9. Family Members & Friend Circle10. Government Policies And Regulations11. Import Duties Imposed By Government12. Advertisements And Promotions13. After Sales Service14. Installment Payment Facility15. Insurance Facility16. Location Of The Car Dealer Shop17. Home Delivery Facility18. Credit Card Acceptance19. Information Provided By Salesperson20. Availability Of Variety Of Cars Under One Roof21. Information Provided By Various Car Related Magazines22. Mileage23. Power24. Looks25. Safety26. Car Accessories27. Easy Availability Of Spare Parts 40
  42. 42. 28. Availability Of Service Station29. Technology30. Overall, I Am Satisfied With My Car I Own 40

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