The marketing consumer behavior is relatively a new field of study and it emerged after the Second World War. The focus of the sellers suddenly shifted from the product to the consumer behavior and their buying patterns (Solomon, Russell-Bennett & Previte, 2013). Consumer behavior is the study of decision making of a buyer; it may be an individual or an organization. The process includes searching, selecting, purchasing and dumping of goods. This is a report, which shows how the consumer behavior varies depending upon the demographics and personality and how the compensatory decision rule can be used to calculate which property option each respondent is likely to choose.
According to the Compensatory decision rule, a consumer evaluating a service or a product will trade one characteristic for the other so that good characteristic will compensate for the bad one (Lima, Osiro & Carpinetti, 2013). A survey was conducted and compensatory decision rule will be used to determine the choices of three respondents, and how the results vary from the actual data (Chai , Liu & Ngai, 2013).
Total weighted score for option 1:
Option1 = (60*1) + (5 *4) + (10 *5) + (5 *5) + (5*5) + (15*4)
= 240
Total weighted score for option 2:
Option2 = (60*3) + (5 *3) + (10 *3) + (5 *5) + (5*4) + (15*5)
= 345
Total weighted score for option 3:
Option3 = (60*3) + (5 *3) + (10 *1) + (5 *3) + (5*4) + (15*4)
= 300
Total weighted score for option 4:
Option4 = (60*1) + (5 *4) + (10 *4) + (5 *5) + ( 5*2)+( 15*5)
= 230
Total weighted score for option 5:
Option5 = (60*4) + (5 *4) + (10 *3) + (5 *4) + ( 5*2)+( 15*1)
= 335
Total weighted score for option 6:
Option6 = (60*3) + (5 *4) + (10 *3) + (5 *5) + ( 5*3)+( 15*2)
= 180+20+30+25+15+30
= 300
The respondent should choose the option 2, as is it the ideal rental property but the result from the compensatory decision rule varies from the actual choice made by the respondent.
Total weighted score for option 1:
Option1 = (10*3) + (15 *5) + (20 *5) + (15 *5) + (15*5) + (25*5)
= 470
Total weighted score for option 2:
Option2 = (10*4) + (15 *1) + (20 *2) + (15 *3) + (15*3) + (25*5)
= 310
Total weighted score for option 3:
Option3 = (10*5) + (15 *1) + (20 *2) + (15 *2) + (15*3) + (25*5)
= 305
Total weighted score for option 4:
Option4 = (10*3) + (15 *4) + (20 *4) + (15 *4) + (15*4) + (25*5)
= 415
Total weighted score for option 5:
Option5 = (10*5) + (15 *3) + (20 *3) + (15 *3) + (15*3) + (25*2)
= 295
Total weighted score for option 6:
Option6 = (10*5) + (15 *4) + (20 *3) + (15 *5) + (15*3) + (25*3)
= 305
The optimal solution according to the compensatory decision analysis is option 1 but it varies from the actual decision made by the respondent.
Total weighted score for option 3:
Option1 = (40*1) + (10 *5) + (10 *5) + (10 *5) + (5*5) + (25*2)
= 265
Total weighted score for option 2:
Option2 = (40*2) + (10 *2) + (10 *2) + (10 *3) + (5*3) + (25*1)
= 190
Total weighted score for option 3:
Option3 = (40*4) + (10 *2) + (10 *1) + (10 *1) + (5*2) + (25*3)
= 285
Total weighted score for option 4:
Option4 = (40*1) + (10 *4) + (10 *4) + (10 *4) + (5*4) + (25*1)
=205
Total weighted score for option 5:
Option5 = (40*5) + (10 *3) + (10 *3) + (10 *3) + (5*3) + (25*5)
= 430
Total weighted score for option 6:
Option6 = (40*3) + (10 *4) + (10 *3) + (10 *5) + (5*3) + (25*4)
= 120+40+30+50+15+100
= 355
The compensatory decision analysis shows that the optimal choice is the option 5 and it does not vary from the actual decision of the respondent.
There are certain decisions, which cannot be simplified using the simple trade off, as one of the attributes is considered much more superior. This is exactly what has happened in the case of respondent 1 and respondent 2. The respondents used the lexicographic decision rule in this scenario (Shin & Ferguson, 2015). The respondents ranked all the attributes according to their preferences and then they compared the most important attribute. The scores of the other attributes do not matter even if their ranking is higher when other attributes are considered (Bruch & Feinberg, 2017). The second respondent considers the distance from the city centre as the most important attribute and so even if the option 1 had a higher ranking he chose option 4 as the distance from the city centre is less than the previous option. Similarly, in case of the respondent 1 the rent is the most important factor and so she chose the option with the lowest price.
The respondent 1 is a female foreign exchange student who is currently working part time at a grocery store. The annual pretax income of the student is $27000, which is quite less, and so for her the rent expense is an important factor. Thus, she chose the rental property, which is the cheapest and farthest from the city centre. The respondent 2 is an old man who is aged 54 and he is divorced. The pretax income of the man is $198000 and he is senior manager at a bank. This shows that the man has enough earnings to live a luxurious life and so the weekly rent is not an important attribute compared to the distance from the city centre. The respondent 5 is an old married man who works as an accountant. The main priorities for this man are rent and the distance from the city centre so the option he chose shows that the one attribute compensated for the other. The rent for the apartment is less but the distance from the city centre is relatively high so the tendency of this man is to save more than he is spends (Zeugner-Roth, Žabkar & Diamantopoulos, 2015).
The personality assessment of respondent 1 shows that she is not extrovert and she is quite flexible. She is willing to try new things and so staying with two other roommates will not be a problem (Thompson & Prendergast, 2015). Moreover, she is compassionate so she will not face any problems in adjusting with others. The respondent is also very careful and so staying with two others ensures her safety. The personality assessment of respondent 2 shows that the man is emotionally neutral and does not care about others and so safety is the only factor that is important to him and so living close to the city centre ensures it. The respondent 5 is introvert so socializing with others is not his strong suit, being a family man he is compassionate and open to new changes so living in the outskirts could be ideal for him (Claiborne & Sirgy, 2015).
The consumers follow the law of marginal utility and that means that they are rational and aware of the various economic calculations. There are certain characteristics of the consumers based on economic factors and they are family income and size, income expenditure, liquidity of funds, tendency to save or spend and consumer credit (Dasgupta et al2016). The size of a family determines the amount of expenditure for a family; a larger family will spend more. The higher the income the higher will be the expenditure. There are people who like to spend more and vice versa. The amount of cash in hand also affects the liquidity of the fund. Some buyers prefer credit and so if they are offered credit they will readily accept it (Foxall, 2014).
The consumer behavior is based on Stimulation-Response theory; they develop buying habits by recalling their memory (Byrne et al. 2014). The theory of learning is a process of motivation, relationship, conditioning and repetition. THE S-R theory shows the steps involved in learning and they are Drive, response and cues (Crowder, 2014).
Conclusion
Thus, this report shows that a trade off cannot simplify not all consumer-buying decisions. There are few hybrid decisions that are non-compensatory in nature and the various non-compensatory rules like the Lexicographic decision rule will be implemented. The respondent 1 and 2 are the perfect example of a Lexicographic decision where one attribute has the top most priority. The respondent 5 is an example of compensatory decision rule, which shows a simple tradeoff between the attributes. This shows how the consumer buyer behavior varies depending upon their learning and memory.
Reference
Bruch, E. E., & Feinberg, F. (2017). Decision making processes in social contexts. Annual Review of Sociology, 43(1).
Byrne, J. H., LaBar, K. S., LeDoux, J. E., Schafe, G. E., & Thompson, R. F. (2014). Learning and memory. In From Molecules to Networks. Elsevier Inc..
Chai, J., Liu, J. N., & Ngai, E. W. (2013). Application of decision-making techniques in supplier selection: A systematic review of literature. Expert Systems with Applications, 40(10), 3872-3885.
Claiborne, C. B., & Sirgy, M. J. (2015). Self-image congruence as a model of consumer attitude formation and behavior: A conceptual review and guide for future research. In Proceedings of the 1990 Academy of Marketing Science (AMS) Annual Conference (pp. 1-7). Springer International Publishing.
Crowder, R. G. (2014). Principles of Learning and Memory: Classic Edition. Psychology Press.
Dasgupta, P., Southerton, D., Ulph, A., & Ulph, D. (2016). Consumer behaviour with environmental and social externalities: implications for analysis and policy. Environmental and Resource Economics, 65(1), 191-226.
Foxall, G. R. (2014). Consumer Behaviour (RLE Consumer Behaviour): A Practical Guide (Vol. 3). Routledge.
Lima, F. R., Osiro, L., & Carpinetti, L. C. R. (2013). A fuzzy inference and categorization approach for supplier selection using compensatory and non-compensatory decision rules. Applied Soft Computing, 13(10), 4133-4147.
Shin, J., & Ferguson, S. (2015, August). Modeling Noncompensatory Choices With a Compensatory Model for a Product Design Search. In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (pp. V02AT03A036-V02AT03A036). American Society of Mechanical Engineers.
Solomon, M. R., Russell-Bennett, R., & Previte, J. (2013). Consumer behaviour: Buying, having, being. Pearson Australia.
Thompson, E. R., & Prendergast, G. P. (2015). The influence of trait affect and the five-factor personality model on impulse buying. Personality and Individual Differences, 76, 216-221.
Zeugner-Roth, K. P., Žabkar, V., & Diamantopoulos, A. (2015). Consumer ethnocentrism, national identity, and consumer cosmopolitanism as drivers of consumer behavior: A social identity theory perspective. Journal of international marketing, 23(2), 25-54.
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