Factors affecting Buyer Behavior: A Study on the Consumers of Two-Wheelers (Motorcycles) of Dhaka City

 

Dr. Partha Prasad Chowdhury

Chartered Marketer (UK)

Associate Professor, School of Business, American International University-Bangladesh (AIUB), Dhaka.

 

ABSTRACT:

Consumer behavior has always been an important and interesting area for research. This research study investigates the importance of different attributes/evaluation criteria and the impact of demographic variables on importance of attributes to select a two-wheeler (motorcycle). This study is based upon the empirical findings of a quantitative research where primary data is collected by surveying a structured questionnaire to the male consumers of different age groups in the Dhaka city. Statistical method, multivariate analysis of variance (MANOVA) is used for data analysis. The study reveals that fuel consumption, design, and brand image are the three most important factors/ criteria to select a motor cycle.  Promotion comes out as least important attribute to evaluate a motorcycle brand.  This study further reveals that there exist not statistically significant differences in terms of ranking different attributes between different age and marital status categories but occupation plays significant role to rank different attributes. The study extends a direction for new researchers and concludes with suggestions for further research in other settings with different purchase categories, degrees of purchase involvement, and sample populations in order to verify and generalise the findings of this study and to determine other factors if any and suggests marketers in the two-wheeler sub-sector of automobile industry to focus on developing attributes that play significant role to influence consumers’ buying decision process.

 

 

1. INTRODUCTION:

Consumption behavior is an important and exciting subject for marketers to explore (Mehta, 1978). A number of factors or attributes guide buyers to shape their buying decision process towards any product and consumers buy a brand out of available brands in the market based on the attributes that can more effectively satisfy their needs and requirements (Jha and Singh, 1988). The economic environment is changing rapidly and this is heavily driven by consumers. For a customer-driven organization, in depth knowledge and understanding of consumer behavior and the factors that influence the consumers’ buying decision process has become a valuable source of competitive advantage (Kaze, 2010). Marketers have high interests in the evaluation criteria buyers’ use and in the importance that the consumers put in each attributes relative to their products with a view to develop product offerings that excel on these attributes (Hawkins and Mothersbaugh, 2010). Consumers’ buying decision processes for any product(s) are always influenced by some factors which lead them to select a particular product. Marketing practices of a firm in any product market should be very much focused on the consumer behavior of the target audience so that firm can posit the right product offering (s) in the target market segment.

 

2. RATIONALE AND OBJECTIVES:

In order to shape consumer decisions, marketers need to formulate strategy by determining three things. These are: which evaluative criteria are used by the consumers; how the consumer perceives the various alternatives on each criterion; and the relative importance of each criterion. (Hawkins et al., 1989). Consumer attitudes and behaviors are fundamental, long-lasting and likely to continue to be disruptive (Currie and Rowley, 2010). In order to satisfy the needs of the target market, marketers need to understand its buying behavior and then devise appropriate marketing actions to influence buyers during the buying. To do this, marketers need to develop their marketing mix to match the needs of each market segment. Each attribute carries a utility function for the consumer and the consumer’s product satisfaction varies with different levels of each attribute (Kotler 1996). Customer perception is continuously changing (Vishwanathan and Childers, 1999). All product attributes are not equally important for all consumers and importance varies within the same individual over time (e.g. Kotler 1996; Hawkins and Mothersbaugh, 2010) and evaluation of alternatives on each criterion depends on evaluation criteria, importance of criteria and alternatives considered (Hawkins et al., 1989; Hawkins and Mothersbaugh, 2010). By identifying the product attributes and measuring their relative importance in the target market, firms can determine the most suitable offering for a given market (Hawes and Baker, 1994). When buyers are offered with the products that meet their needs, desires of buyers then they are in general believed to be satisfied (Helgesen, 2006). Despite the critical role of different attributes on consumers’ buying behavior, in the context of two-wheeler sub-sector of automobile industry of Bangladesh, to the best of my knowledge no study has been made recently to identify the importance of different attributes to select a two-wheeler (motorcycle) and to examine the role of different demographic variables on these evaluation criteria. Hence the purpose of this study is to address this gap and the specific objectives of this study are:

·        To identify the key factors/attributes influencing consumers buying decisions to buy a two- wheeler (motorcycle).

·        To examine whether age, marital status, occupation have any impact on the importance of evaluation criteria to buy a two-wheeler (motorcycle).

3. LITERATURE REVIEW:

Individual consumer in the marketplace plays the roles as a buyer, payer and user. During consumption, consumers pass through different stages in the consumer’s purchasing decision-making process (Belch and Belch, 2003). The consumer buying decision process consists of five stages. These are need recognition, information search, evaluation of alternatives, purchase decision and post-purchase behavior (e.g. Mullins and Walker, 2013; Kotler et al., 2011) and these five phases of buying decision process are used by the marketers to gain better understanding about their buyers and their behaviors (Commgys et al., 2006). Understanding the buyer behavior is fundamental to the development of effective marketing strategies. Three questions are important to this understanding:

·        Which customer needs must be satisfied in order to achieve defined objective (for each segment or niche or other specific target audience)?

·        What motivates each segment to purchase?

·        How, when and where can marketers successfully influence their buying decision-making process?

 

There are different types of decision making processes. These are habitual decision making, limited decision making and extended decision making. As the consumer moves from a low level of involvement to high level of involvement decision making becomes increasingly complex and for high involvement products (e.g. homes, personal computers, and complex recreational items) buyers use complex evaluation of multiple alternatives (Hawkins et al., 1989). High involvement products are those that carry some risks and are expensive. In the context of developing country like Bangladesh, motorcycle is a high involvement product. During high involvement consumer behavior, consumers are information seekers, information processors and they evaluate brands before buying (Mullins and Walker, 2013).

 

During evaluation of alternatives consumers use two types of information: list of brands/models from which they plan to buy and the criteria they will use to evaluate brand (Schiffman and Kanuk, 2007). In their purchasing decision-making process, consumers are often influenced by both internal and external influences (Belch and Belch, 2003). Overall orientation toward object depends on emotions or feelings (affective component); beliefs (cognitive Component) about specific attributes or overall object and behavioral intention (behavioral component) with respect to specific attributes or overall object attitudes (Hawkins et al., 1989). As per attitude-toward-object model of consumer attitudes, attitudes of consumers toward a product depend on the presence or absence and evaluation of certain product-specific beliefs and/or attributes/features and buyers usually possess positive attitudes toward the product that they believe that it carries attributes with adequate level and they possess negative attitudes towards the product if it does not carry adequate level of attributes (Schiffman and Kanuk, 2007).

 

In the evaluation stage of the buying decision process, potential customers compare the characteristics, features and benefits that are important to them of various products to see what might best meet their needs and what their preference is. Each criterion is assigned (usually unconsciously) a salience (a level of important) that ultimately may decide what is bought and from whom. Whenever buyers make a final judgement of value they do not follow simple and single evaluation process and an individual customer follows different evaluation process at different situations where buyers’ evaluation processes are cognitively oriented and form product judgements largely on conscious and rational basis (Kotler, 1996). The study (e.g. Mullins and Walker, 2013; Kotler, 1996; Kotler and Keller, 2009; Kotler et al., 2011; Kotler et al., 2009) suggested that the marketing mix is a set of controllable marketing variables that the organization blends in order to produce the response it wants in the target market and to build customer relationship and it consists of everything that the firm can do to influence the demand for its product. Marketing mix consists of a firm’s product offerings to customers and the methods and tools it selects to accomplish the exchange (Schiffman and Kanuk, 2007).

 

Consumer buys any product to receive some benefits and consumer sees each product as bundle of attributes with varying capabilities of desired benefits and satisfying the needs (Kotler, 1996). Characteristics of the product through which products can be identified and differentiated are known as product attributes. These are the features or specific descriptive aspects of a marketing strategy that represent consumer’s evaluation criteria of particular product. The study (e.g. Deming, 1986; cited by Chen, 2009) have pointed out that a customer evaluates the quality of a product on the basis of certain important quality attributes, where an attribute is defined as a descriptive feature of a product which is involved with its purchase or consumption (Keller, 1999). The study on consumer behaviour pointed out that consumers use different attributes to evaluate a product. These are availability (Fotheringham, 1988); packaging (Prendergast and Pitt, 1996); fit, durability, ease of care, favourable price, comfort, quality, colour, attractiveness, fashionableness, brand name, appropriateness for occasion, choice of styles (Beaudoin et. al., 2000); brand reputation (Temporal and Lee, 2001); quality price, availability, variety, assortment, value of products (Gwin and Gwin, 2003). The study suggested that during buying a motorcycle consumer evaluates different attributes which are brand image, spare parts, less fuel consumption, low price, easy driving, design, color, durability, after-sales service, speed, resale value, guarantee, sound, promotion (Kamal and Kamal, 1994)

 

Consumers give the most priority to that attribute which deliver desired benefits. The study (e.g. Hawkins et al., 1989; Hawkins and Mothersbaugh, 2010) suggested that the several features, attributes or dimensions which consumers use in response to specific problem is known as evaluation criteria and customers use several features to make any purchase decision and the attributes or evaluation criteria that a consumer uses in a decision making process may vary from tangible (e.g. cost, performance) to intangible (e.g. style, taste, prestige etc.). The study (e.g. Kotler, 1996; Kotler and Keller, 2009; Kotler et al., 2009; Kotler et al., 2011; Kotler and Keller, 2012) suggested that consumer buying behaviour is influenced by four major types of factors. These are cultural (culture, sub-culture and social class); social (reference groups, family and roles and statuses); personal (age, life style, occupation, economic circumstances, personality, self-concept); and psychological (motivation, perception, learning, beliefs and attitudes) and gender, age, occupation and marital status are considered to be key factors that influence consumer’s buying behavior.

 

There are several variables which can influence the brand choice behavior. Berkman and Gilson (1978) outlined that choice process is influenced by two broad objective-sociocultural and individual. Mullins and Walker (2013) mentioned that the factors that are likely to increase prepurchase search are product factors (long interpurchase time, frequent changes in product styling, frequent price changes, high price, many alternative brands, much variation in features); situational factors (experience-first time purchase, social acceptability-gift item or visible item, value related consideration (discretionary purchase or necessary purchase); personal factors (demographic characteristics-education, income, occupation, age and personality). They also classified attributes that, consumers use to evaluate a product/brand into four categories. These are- cost attributes (e.g. purchase price, operating costs, repair costs, cost of installation, costs of extra option); performance attributes (e.g. durability, quality of materials, construction, dependability, functional performance, efficiency, safety); social attributes (e.g. reputation of brand, brand personality, status image, popularity with friends and family members, design style, fashion); availability attributes (carried by local stores, credit terms, quality of service, delivery time). The nature of consumers’ needs and requirements, their ability to buy products to satisfy those needs, the perceived importance of different attributes or evaluation criteria and buyers’ attitudes toward and preferences for different products all are influenced by demographic variables (Mullins and Walker, 2013). The number of evaluative criteria used depends on the product, consumer and situation as characteristics of the individual (e.g. age) and characteristics of the purchase situation (time pressure) also influence the number of evaluation criteria and during buying any high involvement product (e.g. automobile, stereo system, house) buyers use more criteria for the evaluation process (Hawkins et al., 1989). Decision making process of a buyer also depends on personal characteristics like age, occupation, lifestyle, life-cycle stage, economic circumstances, personality and self-concept (Kotler, 1996). I considered demographic variables age, marital status and occupation by assuming that there exist some differences among the users regarding buying behaviors. Hence our hypothesis is as follows:

 

H1: There is an impact of age, marital status, occupation on the importance of attributes of marketing mix during decision making process of a motorcycle.

 

4. METHODOLOGY:

The quantitative approach has been used to know the degree of importance of different attributes and to verify the impact of demographic variables on different attributes to select a two-wheeler/ motorcycle. The study is empirical in nature where research approach is deductive, research style is descriptive and the objectives are to identify the key attributes that are used to evaluate motorcycle brands and to measure the impact of demographic variables (e.g. age, marital status and occupation) on attributes/evaluation criteria.

 

The literature review points out that importance of evaluation criteria/service attributes depends on demographic variables. The hypothesis of this study is formulated for empirically testing of the impact of demographic variables (e.g. age, marital status and occupation) on attributes/evaluation criteria. The research question and hypothesis of this study were as follows:

·        Is there any impact of demographic variable (age, marital status, occupation) on the importance of attributes to select a motorcycle/two-wheeler?

 

H1₀: There is no impact of demographic variable (age, marital status, occupation) on the importance of attributes to select a motorcycle/two-wheeler?

H1_a: There is an impact of demographic variable (age, marital status, occupation) on the importance of attributes to select a motorcycle/two-wheeler?

To determine which criteria are used by the users/consumers to buy a motorcycle and to rank attributes direct method of measurement is used by asking buyers questions with the help of survey method. Convenience type of non-probability sampling technique was used to select the respondents as it is relatively inexpensive and less time consuming (Wilson, 2011; Malhotra and Das, 2011). Non-probability sampling is used as required sampling frame was not accurate and easily accessible. A self-completion questionnaire was used to obtain opinion of the respondents which was pretested before the field work. To find out how consumers give emphasis to each of the attributes/factors in the selection of a two-wheeler (motor cycle) product five-point Likert-style rating scale anchored by ‘Most unimportant’ (i.e., value 1) and ‘Most important’ (i.e., value 5). Personal interview technique was applied while administering the questionnaire on respondents in order to collect necessary information. Respondents were given necessary explanation during the course of interview and encouraged them to answer accurately to increase validity of the information. Sample size should be at least ten times the number of variables (Roscoe, 1975; cited by Lin and Chen, 2006) and larger samples are necessary for conclusive research such as descriptive surveys, and to use sophisticated data analysis (Malhotra and Dash, 2011). Data for the study were gathered from 200 respondents hence the sample size is 200. Sample respondents were chosen from different areas of Dhaka city. Data was analysed by using SPSS to measure the importance of factors/attributes. Descriptive analysis and multivariate analysis of variance (MANOVA) are used to calculate the mean values of different attributes.

 

5. RESULTS AND DISCUSSIONS:

To examine the importance of different attributes to select a two-wheeler (motorcycle) product, the respondents were asked to indicate on five point scale, the degree of importance attached to the attributes. To determine the degree of importance of different attributes/evaluation criteria, the mean values are considered.

 

Table-1 provides the mean values of different evaluation criteria/attributes consumers use during buying a motorcycle. It appears from table-1 that fuel consumption (mean 4.03), design (mean 3.98), brand image (mean 3.94) are the three most important factors/ criteria to select a motor cycle.

 

 

Table-1: Mean Values of Different Attributes

	N	Minimum	Maximum	Mean	Std. Deviation
Brand Image	200	2	5	3.94	.741
Spare parts	200	2	5	3.90	.683
Less fuel consumption	200	2	5	4.03	.756
Low price	200	1	5	3.88	.814
Easy Driving	200	2	5	3.80	.881
Design	200	2	5	3.98	.871
Color	200	2	5	3.84	.863
Durability	200	2	5	3.92	.763
After Sales Service	200	2	5	3.91	.809
Speed	200	1	5	3.77	.908
Resale value	200	1	5	3.84	.876
Guarantee	200	1	5	3.71	.955
Sound	200	1	5	3.61	.855
Promotion	200	1	5	3.00	1.025
Valid N (listwise)	200

 

Age-wise mean values for different attributes are shown in Table-2. It reveals from the study that young adult users are more concerned about the attributes. They are more concerned about design (µ= 4.17), less fuel consumption (µ= 4.16), brand image (µ= 4.12) and after sales service (µ= 4.10). Adult users rank less fuel consumption (µ= 3.97), design (µ= 3.97), and durability (µ= 3.93) as important criteria to evaluate brands whereas middle aged (40-60 yrs.) users rank less fuel consumption (µ= 4.00), after sales service (µ= 3.97), and resale value (µ= 3.94) as three important attributes for the selection of a motorcycle. The table-2 also reflects that irrespective of the age, promotion plays least important role to influence buying behaviour. If we look at the Multivariate Tests of MANOVA (see: Table-3), value of WILKs’ Lambda 0.838 and its associated significance level is 0.214. This is greater than 0.05; therefore, there is not statistically significant differences between different age groups in terms of importance of different attributes/evaluation criteria (Pallant, 2007).

 

Table-2: Age-wise Mean Values of Different Attributes

Age		Brand Image	Spareparts	Less fuel consumption	Low price	Easy Driving	Design	Color	Durability
Young Adult (19-25)	Mean	4.12	3.98	4.16	3.83	3.88	4.17	3.88	3.91
	N	58	58	58	58	58	58	58	58
	Std. Deviation	.595	.662	.790	.752	.860	.901	.900	.801
Adult (26-39)	Mean	3.85	3.92	3.97	3.93	3.82	3.97	3.88	3.96
	N	108	108	108	108	108	108	108	108
	Std. Deviation	.807	.685	.755	.817	.874	.837	.851	.748
Middle aged (40-60)	Mean	3.91	3.68	4.00	3.79	3.56	3.71	3.68	3.82
	N	34	34	34	34	34	34	34	34
	Std. Deviation	.712	.684	.696	.914	.927	.871	.843	.758
Total	Mean	3.94	3.90	4.03	3.88	3.80	3.98	3.84	3.92
	N	200	200	200	200	200	200	200	200
	Std. Deviation	.741	.683	.756	.814	.881	.871	.863	.763

 

Conti….

Age		After Sales Service	Speed	Resale value	Guarantee	Sound	Promotion
Young Adult (19-25)	Mean	4.10	3.83	3.98	3.95	3.57	3.09
	N	58	58	58	58	58	58
	Std. Deviation	.810	.976	.827	.926	.861	1.159
Adult (26-39)	Mean	3.79	3.71	3.73	3.58	3.62	2.98
	N	108	108	108	108	108	108
	Std. Deviation	.786	.843	.838	.968	.862	.957
Middle aged (40-60)	Mean	3.97	3.82	3.94	3.68	3.68	2.88
	N	34	34	34	34	34	34
	Std. Deviation	.834	.999	1.043	.912	.843	1.008
Total	Mean	3.91	3.77	3.84	3.71	3.61	3.00
	N	200	200	200	200	200	200
	Std. Deviation	.809	.908	.876	.955	.855	1.025

 

 

 

 

 

Table-3: Multivariate Tests (Using Age)

Effect		Value	F	Hypothesis df	Error df	Sig.	Partial Eta Squared
Intercept	Pillai's Trace	.992	1667.470a	14.000	184.000	.000	.992
	Wilks' Lambda	.008	1667.470a	14.000	184.000	.000	.992
	Hotelling's Trace	126.873	1667.470a	14.000	184.000	.000	.992
	Roy's Largest Root	126.873	1667.470a	14.000	184.000	.000	.992
Age	Pillai's Trace	.168	1.213	28.000	370.000	.214	.084
	Wilks' Lambda	.838	1.213a	28.000	368.000	.214	.084
	Hotelling's Trace	.186	1.213	28.000	366.000	.214	.085
	Roy's Largest Root	.125	1.653b	14.000	185.000	.069	.111

a. Exact statistic

b. The statistic is an upper bound on F that yields a lower bound on the significance level.

c. Design: Intercept + Age

 

 

Marital status-wise mean values for different attributes are shown in Table-4. It appears that unmarried users are more concerned about the attributes. They are more concerned about design (µ= 4.17), less fuel consumption (µ= 4.07), and brand image (µ= 4.00) whereas married users rank less fuel consumption (µ= 4.00), durability (µ= 3.94), and brand image (µ= 3.89) as important criteria to evaluate brands. Irrespective of marital status, users have responded that promotion plays less important role in the buying decision process of motorcycle. If we look at the Multivariate Tests of MANOVA (see: Table-5), value of WILKs’ Lambda 0.908 and its associated significance level is 0.192. This is greater than 0.05; therefore, there is not statistically significant differences between married and unmarried users in terms of importance of different attributes/evaluation criteria to select a two-wheeler/motorcycle (Pallant, 2007).

 

Table-4: Marital Status-wise Mean Values of Different Attributes

Marital Status		Brand Image	Spare parts	Less fuel consumption	Low price	Easy Driving	Design	Color	Durability
Un married	Mean	4.00	3.98	4.07	3.81	3.83	4.17	3.90	3.91
	N	90	90	90	90	90	90	90	90
	Std. Deviation	.687	.653	.804	.833	.915	.851	.937	.729
Married	Mean	3.89	3.83	4.00	3.93	3.76	3.84	3.80	3.94
	N	110	110	110	110	110	110	110	110
	Std. Deviation	.782	.702	.717	.798	.856	.862	.799	.793
Total	Mean	3.94	3.90	4.03	3.88	3.80	3.98	3.84	3.92
	N	200	200	200	200	200	200	200	200
	Std. Deviation	.741	.683	.756	.814	.881	.871	.863	.763

 

Conti….

Marital Status		After Sales Service	Speed	Resale value	Guarantee	Sound	Promotion
Un married	Mean	3.94	3.74	3.84	3.71	3.70	2.87
	N	90	90	90	90	90	90
	Std. Deviation	.853	.881	.847	.951	.841	1.030
Married	Mean	3.88	3.78	3.84	3.70	3.55	3.10
	N	110	110	110	110	110	110
	Std. Deviation	.775	.932	.904	.963	.863	.1.013
Total	Mean	3.91	3.77	3.84	3.71	3.61	3.00
	N	200	200	200	200	200	200
	Std. Deviation	.809	.908	.876	.955	.855	1.025

 

 

Table-5: Multivariate Tests (Using Marital Status)

Effect		Value	F	Hypothesis df	Error df	Sig.	Partial Eta Squared
Intercept	Pillai's Trace	.994	2040.854a	14.000	185.000	.000	.994
	Wilks' Lambda	.006	2040.854a	14.000	185.000	.000	.994
	Hotelling's Trace	154.443	2040.854a	14.000	185.000	.000	.994
	Roy's Largest Root	154.443	2040.854a	14.000	185.000	.000	.994
MStatus	Pillai's Trace	.092	1.333a	14.000	185.000	.192	.092
	Wilks' Lambda	.908	1.333a	14.000	185.000	.192	.092
	Hotelling's Trace	.101	1.333a	14.000	185.000	.192	.092
	Roy's Largest Root	.101	1.333a	14.000	185.000	.192	.092

a. Exact statistic

b. Design: Intercept + MStatus

 

 

 

Table-6: Occupation-wise Mean Values of Different Attributes

Occupation		Brand Image	Spareparts	Less fuel consumption	Low price	Easy Driving	Design	Color	Durability
Student	Mean	4.18	3.86	4.30	3.91	3.73	4.14	4.05	3.91
	N	44	44	44	44	44	44	44	44
	Std. Deviation	.446	.632	.765	.772	.872	.878	.914	.802
Job Holder	Mean	3.91	3.92	3.91	3.93	3.84	3.97	3.88	3.88
	N	113	113	113	113	113	113	113	113
	Std. Deviation	.762	.629	.676	.741	.862	.850	.847	.765
Business Person	Mean	3.77	3.86	4.07	3.70	3.74	3.86	3.56	4.05
	N	43	43	43	43	43	43	43	43
	Std. Deviation	.868	.861	.884	.1.013	.954	.915	.796	.722
Total	Mean	3.94	3.90	4.03	3.88	3.80	3.98	3.84	3.92
	N	200	200	200	200	200	200	200	200
	Std. Deviation	.741	.683	.756	.814	.881	.871	.863	.763

 

Conti….

Occupation		After Sales Service	Speed	Resale value	Guarantee	Sound	Promotion
Student	Mean	4.16	3.70	3.91	3.84	3.73	3.23
	N	44	44	44	44	44	44
	Std. Deviation	.834	.978	.858	.939	.899	1.217
Job Holder	Mean	3.81	3.79	3.73	3.61	3.56	2.84
	N	113	113	113	113	113	113
	Std. Deviation	.766	.829	.845	.940	.778	.862
Business Person	Mean	3.93	3.77	4.05	3.81	3.65	3.16
	N	43	43	43	43	43	43
	Std. Deviation	.856	1.043	.950	1.006	.997	1.153
Total	Mean	3.91	3.77	3.84	3.71	3.61	3.00
	N	200	200	200	200	200	200
	Std. Deviation	.809	.908	.876	.955	.855	1.025

 

Table-6 shows the mean values of different attributes/evaluation criteria according to occupation which highlights that students put more emphasis on evaluation criteria. The study reveals that students are more concerned about fuel consumption (µ= 4.30), brand image (µ= 4.18) and after sales service (µ= 4.16), and design (µ= 4.14). Jobholders rank design (µ= 3.97), price (µ= 3.93), and availability of spare parts (µ= 3.92), as three important attributes whereas business persons rank less fuel consumption (µ= 4.07), design (µ= 4.05), and resale value (µ= 4.05) as three important attributes for the selection of a motorcycle. The table-6 also reflects that irrespective of the occupation, promotion plays least important role to influence buying behaviour. If we look at the Multivariate Tests of MANOVA (see: Table-7), value of WILKs’ Lambda 0.755 and its associated significance level is 0.003. This is lower than 0.05; therefore, there is statistically significant differences between different occupation groups in terms of importance of different attributes/evaluation criteria for the selection of two-wheeler/motorcycle (Pallant, 2007).

 

Table-7: Multivariate Tests (Using Occupation)

Effect		Value	F	Hypothesis df	Error df	Sig.	Partial Eta Squared
Intercept	Pillai's Trace	.992	1730.946a	14.000	184.000	.000	.992
	Wilks' Lambda	.008	1730.946a	14.000	184.000	.000	.992
	Hotelling's Trace	131.702	1730.946a	14.000	184.000	.000	.992
	Roy's Largest Root	131.702	1730.946a	14.000	184.000	.000	.992
OCPN	Pillai's Trace	.262	1.992	28.000	370.000	.002	.131
	Wilks' Lambda	.755	1.982a	28.000	368.000	.003	.131
	Hotelling's Trace	.302	1.973	28.000	366.000	.003	.131
	Roy's Largest Root	.167	2.211b	14.000	185.000	.009	.143

a. Exact statistic

b. The statistic is an upper bound on F that yields a lower bound on the significance level.

c. Design: Intercept + OCPN

 

 

6. CONCLUSION, MANAGERIAL IMPLICATIONS AND FURTHER RESEARCH:

 

6.1 Conclusions:

The primary contribution of this study was to identify the key attributes that affect the consumer buying decision process to select a motorcycle; to examine whether age, marital status, occupation have any impact on the importance of attributes/evaluation criteria or not. The major findings of the study are as follows:

 

·        Degree of importance of all chosen attributes is moderate but the study suggests that fuel consumption (mean 4.03), design (mean 3.98), brand image (mean 3.94) are the three most important factors/ criteria to select a two-wheeler (motor cycle).

·        The study suggests that in order to evaluate alternatives, young adult users are more concerned about the attributes but there exist not statistically significant differences between different age groups in terms of importance of different attributes/evaluation criteria.

·        The study suggests that during evaluation of alternatives, unmarried users are more concerned about the attributes but there exist not statistically significant differences between married and unmarried users in terms of importance of different attributes/evaluation criteria to select o motorcycle.

·        The study highlights that students put more emphasis on evaluation criteria. The study also points out that there exist statistically significant differences between different occupation groups in terms of importance of different attributes/evaluation criteria for the selection of motorcycle.

 

The study of Kamal and Kamal (1994) pointed out that availability of spare parts, brand image and durability are three important criteria whereas this study suggests that fuel consumption, design, brand image are the three most important factors/ criteria to select a motor cycle. The study of Kamal and Kamal (1994) further pointed out that users belonging different age, marital status, and occupation categories have more or less similar pattern in ranking different attributes during buying of a motorcycle. This study reveals that there exist not statistically significant differences in terms of ranking different attributes between different age and marital status categories but occupation plays significant role to rank different attributes which is in line with the study of Hawkins et al., (1989) in which they mentioned that occupation is associated with education and income and reflects the lifestyle of a people and is widely used cue to evaluate and define individuals.

 

6.2 Managerial Implications and Further Research:

Marketers need to identify the preferential rankings of consumers towards different features/evaluation criteria and by combining the right combination of attributes that provide benefits to fulfill a need or solve a problem; marketers of two-wheeler sub-sector can create more value for their consumers. This study also reveals that irrespective of age, marital status and occupation promotion is least important attribute to evaluate a motorcycle brand. In order to be successful in the long run, price does not play important role and marketers of high involvement products need to formulate their product offerings in a way so that it carries one or more product benefits (Mullins and Walker, 2013). A key implication of this study is that marketers in the two-wheeler sub-sector of automobile industry of Bangladesh may drive competitive advantage from others imbued with desired level of attributes. This could be used as a guideline for the marketers for developing marketing strategies to influence buying decision processes of the consumers which will in turn develop customer satisfaction.

 

The findings of this study might not be directly generalised to entire two-wheeler sub-sector of automobile industry as the limited number of respondents (sample size is 200) were selected from different areas of Dhaka city only and for convenience type non-probability sampling is used hence this study might suffer from some respondent bias caused by self selection and or construction of the sampling frame. At present, there are no studies investigating the preferential ranking towards different attributes during selection of a two-wheeler (motorcycle) and to examine the impact of demographic variables (e.g. age, marital status, and occupation) on different evaluation criteria on consumer buying decision process. Therefore more comprehensive research is required in other settings is suggested in order to verify and establish the findings of this study.

 

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Accepted on 31.12.2018            © A&V Publications All right reserved