Printer Friendly

Reaching the target: an investigation of salient channel attributes in consumer choice.


The question of how to reach target consumers is one of considerable importance for organizations. Substantial effort is often given to the design and choice of marketing channels which are able to satisfy demand for a product or service as well as to stimulate demand through the many intermediary functions that they perform. Economic value or welfare is created for the consumer through the performance of these functions (Lusch, 1979; Stern & El Ansary, 1988; Hanak, 1992).

When products are marketed through multiple channels the question of how consumers make channel choices becomes more important. How are the consumers in each channel different? What are the salient attributes manufacturers should offer?

The industry chosen to study these issues is the mutual fund industry. More specifically, the study focuses on the mutual fund industry outside of managed retirement and institutional accounts. Several reasons make this an appropriate choice. First, mutual funds have diffused extensively and become part of the American household. It has become one of the fastest growing categories of household financial assets for more than a decade commanding more than $9.3 trillion. More than half of all households own mutual funds compared to less than 6% in 1980. According to the Investment Company Institute, a trade organization for the United States fund industry, among investors who hold mutual funds outside work retirement plans, about 80% own mutual funds purchased through a channel intermediary, such as financial planners, full service brokers, banks, insurance agents or discount brokers. Over the last twenty five years, the distribution of mutual funds has undergone dramatic changes. Before 1980, most funds were sold through traditional channels such as full service brokers or directly to the consumers. Today, mutual funds can choose multiple channels to market their mutual funds. Apart from retirement plans and institutional accounts, 76% of mutual funds are sold through full service brokers, financial planners, banks and insurance agents, 17% are sold through the direct channel and 7% are sold through discount brokers (Reid and Rea, 2003).

Unquestionably, channels of distribution are an important consideration for funds marketing their shares. The two main reasons that contribute to how crucial distribution channels are in the marketing decision of fund managers relate to the nature of their customers and the remuneration system for fund sponsors. First, studies have shown that consumers after choosing a particular channel tend not to switch. These consumers often purchase other mutual funds through the same channel. Thus, each new customer is viewed as a stream of future cash flows into the fund. Secondly, fund managers are usually remunerated as a percentage of net asset value. The economics of fund manager compensation often results in a flat marginal revenue curve and a downward sloping marginal cost curve. Profit maximization in these situations usually necessitates attracting as many fresh purchases of fund shares as possible so as to increase the total net asset value of the fund net total redemption (Baumol et al., 1990).

Consumers in the mutual fund industry exhibit a diverse set of characteristics. It is important for mutual fund sponsors to choose the appropriate channel intermediary so as to effectively reach their target customers. As such, they need to have a clear understanding of what attributes consumers use when making their choice.

The aim of this study is to identify salient channel attributes deemed important to consumers in their choice process and investigate their relationship to consumer characteristics and search behavior. A theoretical model is first developed and tested with empirical data.


The Fishbein-Rosenberg theories of the expectancy-value model (Fishbein, 1967) and the theories of economic choice by Lancaster (1966) provide a theoretical rationale for the multiattribute modeling of consumer choice. Because of the importance of the income constraint and the trade off with the consumption of goods in other product categories, Rosen's (1974) utility framework is adopted.

The purchase process of mutual funds includes the search for information as well as the performance of necessary administrative tasks to procure and dispose of the mutual fund shares. Charles Schwab, a large discount brokerage firm has advertisements that claim that they do the "work" so that you don't. Individuals who desire to invest less of their own time to the purchase process would tend to delegate these tasks to be performed by channel intermediaries such as brokers or bankers. Others who prefer to perform these tasks would tend to bypass channel intermediaries and purchase directly from the mutual fund company itself. Consumers, in effect, trade off the cost of their own time and the cost of purchasing services, which are bundled with the explicit product (that is, mutual fund shares) from a channel. Therefore, a time constraint is added.

Assume that the representative consumer k invests [d.sub.i] proportion of total investment I on channel i. The total price or cost of a mutual fund purchase is defined as:

* The share price (for channel i, initial share price is denoted by Poi and final share price at the end of the period by []) plus

* The cost imposed by the channel in the form of annual fees ([f.sup.a.sub.i]), loads ([L.sub.i]) and fixed fees ([F.sub.i]). An example of annual fees are the rule 12b-1 fees and of the latter is the fixed fees paid to financial consultants for professional services rendered.

For a clearer exposition, the loads are amortized and combined with the annual fee to form a total variable annual fee of [f.sub.i] (amortization development is available from author), which will be used throughout the text. Initial share price Poi and the final share price [] of the mutual fund share are exogenous to the channel and are determined by the stock market.

The consumer has a selection of channels through which to purchase mutual funds. The choice of channel to use is based on his or her desire to invest personal time in the pre-purchase and purchase process. Given that the consumer chooses the channel i through which to purchase his mutual fund, let the initial share price of that mutual fund share be Poi. The consumer is able to obtain [X.sub.i] number of mutual fund shares. The channel i has characteristics [z.sub.1], [z.sub.2],........[z.sub.n]. Assume there is a discrete number of channels available, each described by some level of service and some channel cost ([f.sub.i], [F.sub.i], [L.sub.i]).

The open-end mutual fund is virtually in unlimited supply because a fund creates new shares for all new moneys entrusted. This feature makes the flow of money into the fund interpretable as a consumer's response to the attributes offered by the channel and fund. Mutual funds are able to select the attributes of their fund and channel. They do this with a knowledge of their costs and mindful of their rival's decisions and consumer response. Thus, let the characteristics or attributes of service in each channel be defined as [s.sub.1], [s.sub.2],...[s.sub.n].

The consumer allocates time, [t.sub.1], [t.sub.2],........[t.sub.i] to search for mutual fund investment products across the various channel. Variable [t.sub.i] is the time spent searching in channel i. The remainder of the consumer's time is devoted to work. Without loss of generality, leisure is ignored for simplicity of exposition.

Before going further, it is necessary to define the term service as used in this context. Service is a substitute for the own time input of the consumer. Some important services offered by channels are research, advice, guidance, assortment, convenience and diversification. Greater amounts of service ([S.sub.i]) given by the channel provide information and other time-saving functions that enable the consumer to reduce the time spent searching and purchasing mutual fund investments.

Since a consumer's own time is reduced by the presence of these services, they are thus willing to pay a higher fee (in the form of higher [f.sub.i], [L.sub.i] and [F.sub.i]) for channels that offer these service levels. In addition, since mutual fund companies cannot provide the service without incurring more operating expenses, they will need to be reimbursed by higher fees to provide these service levels. For the purpose of this exposition, the case of the back end load is considered and combined with the annual charges. Total variable fee is represented by [f.sub.i] which is expressed as a percentage of the total dollar value of shares. It is not included in the initial share price [P.sub.oi] or final share price [] which are determined exogenously by the stock market.

The purpose of amortizing all the relevant expenses and returns is to enable us to simplify the process into a one period problem. This is similar to the methodology used by Horsky and Nelson (1992) in which they amortized yearly installments for cars and provided the solution for a single period situation. Thus the following relationship is obtained:


[summation][t.sub.i]([s.sub.1]...[s.sub.n], [x.sub.i]) + [t.sub.w] = T [Time Constraint]

where AOG refers to all other goods, ti is the time spent searching and purchasing the mutual fund, [t.sub.w] is the time spent working, T is total time and Y is individual income. The fees [f.sub.i] are expressed as a percentage.

The only attributes that succinctly capture the nature of investment goods, such as mutual fund shares, are its risk and return. Therefore, let [R.sub.1], [R.sub.2].......[R.sub.n] refer to gross returns on investments in each channel. The measure of risk for a particular asset is simply taken as the standard deviation or variance of this return.

[P.sub.oi], is the initial share price. It is noteworthy that the initial price, [P.sub.oi] cannot be a function of services because it is determined exogenously by the stock market and is independent of the services performed by the mutual fund organization.

Specifying the form of the utility function

When the consumer is certain about the attribute levels, the utility function described in Equation (1.) measures the consumer's preference and is the objective function which consumers are normally assumed to maximize. However, in the consumer's channel choice decision, consumers make their decisions with some uncertainty about the true levels of attributes that they will obtain. Essentially, they are unable to know with any certainty the outcome of their choice. The overall value of investments in each channel however can be described by a distribution over its possible values. The uncertainty of the consumer's utility requires that the consumer maximize the expected utility of the overall value of the attributes instead. Assigning the notation [V.sub.k]as the overall value across channels, the consumer's utility can be described as a function of its overall value, [U.sub.i] = f([V.sub.k]), where V is a function of the returns and is fully defined subsequently.

The expected utility model is adopted to determine how consumers allocate their funds across different channels under conditions of uncertainty. Keeney and Raiffa (1976) showed that when the value function is measurable, if the consumer obeys the Von Neuman-Morgenstern axioms for lotteries and if the utility function exists, the value function [V.sub.k] should have constant risk aversion. Thus, the utility function may either be linear or negative exponential with respect to V.

Consistent with Horsky and Nelson (1992) and Currim and Sarin (1984), the negative exponential model is adopted. The utility function for the representative consumer k, therefore becomes:

(2) [U.sub.k] = c-bexp[-[a.sub.k]([V.sub.k])] for consumer k, where [a.sub.k] > 0 and [a.sub.k] =U"/U'.

In Equation (2.), [U.sub.k] is the utility that takes into consideration uncertainty in the value function [V.sub.k]. The consumer's risk aversion is represented by [a.sub.k] which is positive and constant. c and b are scaling constants where b (3) 0. Without loss of generality and at the same time preserving the utility difference orderings, we set c and b equal to 0 and 1 respectively. If V is normally distributed, the expected utility of the individual for channel i is as follows (Horsky & Nelson 1992):

(3) E([U.sub.k]) = -exp{-[a.sub.k] (E([V.sub.k])-0.5[a.sub.k] Var ([V.sub.k]))}

Given that the consumer derives utility from the channel, he will choose the channel for which the above equation is greatest. Looking at Equation (3.), we see that E(Uk) is monotonic in E([V.sub.k])-0.5[a.sub.k]Var([V.sub.k]). Therefore, maximizing Equation (3.) is equivalent to maximizing E([V.sub.k]) 0.5[a.sub.k]Var([V.sub.k]).

Defining the value function, V

Assuming back-end load, where the entire amount of investment is used to purchase shares, the relationship between initial share price and quantity of shares with the total dollar amount invested in a mutual fund product, can be stated as follows: (4) [X.sub.i] =([d.sub.i]I)/[P.sub.oi]

Equation (4.) simply states that the number of share obtained for the mutual fund product is equal to the amount of money invested in product one divided by the initial price of the shares at the time of purchase. Fees and loads are additional cost to the acquisition of mutual funds.

Defining gross returns on investments in the following manner:

(5) [R.sub.i]=([]-[P.sub.oi])/[P.sub.oi] final share price may be stated as, []=[P.sub.oi]([R.sub.i]+1).

Initial and final share prices are determined by the market and are exogenous variables. Thus, returns here are simply the pure returns from the stock market without taking into consideration other costs.

The choice decisions of individuals are made with some degree of uncertainty about the final outcome of investments. This is because a mutual fund product attribute namely returns on investment, [R.sub.i], is a random variable which makes it impossible for a consumer to know with certainty the outcome of the investment. Expected utilities therefore need to be taken into consideration. The value function [V.sub.k] is the final income from the investment in channel i and is the total value of the investment plus the value of all other goods, AOG:

(6) [V.sub.k] = [summation][][X.sub.i] + AOG

In equation (6.) the first term on the RHS represents the total end of period wealth from investment and the second term is the value of all other goods. Given equations (4.) and (5.) it is possible to rewrite equation (6.) in terms of total investment I and returns R.

(7) [V.sub.k] = [summation][[R.sub.i][d.sub.i][I.sub.k] + [d.sub.i][I.sub.k]] + AOG

From equation (1.), AOG and household income can be defined as follows:

(8) AOG = Y--([P.sub.oi][X.sub.i] + [f.sub.i][][X.sub.i] + [F.sub.i])

(9) Also, Y = wT--w[summation][t.sub.i]

Expected utility y needs to be maximized as follows:

(10) Maximize [Psi] = E([V.sub.k])-0.5akVar([V.sub.k])

Substituting the relationship found in equations (7.) and (8.) equation (10.) can be rewritten as follows:


Substituting equation (9.) and [] = [P.sub.oi](Ri+1) into equation (11.) yields the following equation:


Finally, because [P.sub.oi]Xi=diIk, equation (12.) becomes:


Differentiating equation (13.) with respect to d and setting to zero, the following equation is obtained:


Re-writing equation (14.):


The RHS represents the marginal revenues and the LHS is the marginal cost of investing. A corner solution comes about when the LHS lies above the RHS everywhere for all di. In this case, returns net of cost for one particular channel dominates for all channels. This may be written as:


In most situations, it is posited that an interior solution would prevail. Some insights are discussed in the empirical section.


Two focus groups were conducted in January 2005. Participants in the focus group were individuals who had purchased mutual funds in the last six months. Among other issues, the focus group investigated attributes respondents looked for in selecting their financial service provider, search efforts, information sources and satisfaction. The results of the focus groups were used to develop the questionnaire. The mail survey was conducted in June 2005. Five thousand questionnaires were distributed to individuals who had bought mutual funds over the last six months.

In this survey, respondents rated a list of service attributes according to their importance ("Please recall the reasons you selected your particular financial service provider. Could you specify how important the following factors are in your selection decision," "1" denotes "Not Important" and "7" denotes "Very Important.").

In order to uncover the underlying service dimensions demanded by consumers in each channel, these attribute ratings are subjected to factor analysis. This is the procedure for summarizing the information ratings on the twenty attributes into a smaller number of dimensions, which can then be identified as the dimensions underlying the respondents' ratings. The analysis determined that there are four factors.

The results of the factor analysis, after applying the varimax rotation procedure are summarized in table 1. Varimax rotation is used because of its assumption of orthogonality between the factors. The factors relate to the service requirements consumers desire.

The first factor relates to the personal service offered by the financial service provider, interpersonal interactions, familiarity as well as the reputation and reliability of the financial service provider. These relate in some way to a belief that a consumer's financial needs will be safely taken care of by the financial service provider. Thus, this dimension is termed security.

The second factor relates mainly to not requiring face to face dealings with or financial advice from the financial service provider. It also includes a requirement to have an economical means of communicating with the mutual fund organization. Since these attributes relate to performing financial transactions independently, this dimension is termed self-service.

The third factor relates mainly to being able to deal with the provider on a twenty-four hour basis and is labeled access.

Finally, the fourth factor relates to the performance of the mutual fund. Therefore, this dimension is termed performance.

These are the service characteristics discerned from the importance ratings of the respondents in each channel. In order to evaluate how these dimensions vary with consumer characteristics and search behavior, they are regressed against known consumer characteristics. The consumer characteristics used are:

1. Wage: From equation (15.), it is seen that M[R.sub.i]= w([delta][t.sub.i]/[delta][d.sub.i]), where MRi is the marginal revenues of investing. Across all channels, it is seen that:


When a channel provides a lot of services, [delta][t.sub.i]/[delta][d.sub.i] is small. With higher wages,

[delta][t.sub.i]/[[delta].sub.i] needs to be smaller. Thus individuals with higher wages tend to spend less time investing and would require more services. The higher the consumer's income, the greater the opportunity cost of time. This implies that the consumer would demand more services.

To operationalize this, the variable income is used here as an approximate measure of the opportunity cost of time. Consumers with higher incomes have higher opportunity costs of time and would tend to delegate functions to be performed by channel intermediaries. They would thus place higher importance on obtaining personal service and are less willing to expend their own time to perform tasks required for making investment decisions or transactions. Income is therefore hypothesized to vary negatively with the dimension of self-service and positively with that of security and access. At the same time, because they trade off the cost of time and effort on their part with the cost of obtaining time saving service from the provider, they are in essence willing to accept a lower return net of fees. Income is hypothesized to vary negatively with performance. Discretionary income is also used to capture purchase abilities. Respondents were asked to answer the following question:

"Discretionary income is the amount of money left over after taxes and all necessary expenses (e.g. food, housing, utilities, everyday clothing, basic transportation, and other recurring expenses) have been paid. Among the many uses of discretionary income are dining out, savings and investment, vacations, entertainment and audio and video equipment. What percentage of your annual household income would you estimate is discretionary?"

Consumers with large discretionary incomes would have more opportunities to purchase investments. It is hypothesized that consumers with larger discretionary incomes would place greater emphasis on self service and less on security.

2. Human

capital (HK): refers to human capital conducive to the use of service such as time spent using a particular channel or age, which requires more consumption of service (Patterson, 2007).

M[R.sub.i]/([delta][t.sub.i]/[delta][d.sub.i])= M[R.sub.j]/([delta][t.sub.j]/[delta][d.sub.j])

Older consumers will have smaller [delta][t.sub.i]/[delta][d.sub.i]. They would thus demand channels that offer more service. The presence of such human capital would make an otherwise expensive or inefficient investment optimal for the consumer. It can be said that an increase in human capital increases the productivity of using the channel. This implies that older consumer demand channels that provide them with more service.

This is operationalized as age which captures the notion of human capital. There is evidence that older consumers are more satisfied with their purchase (Furse, Punj & Stewart, 1984, Ratchford, Lee & Sambandam, 1994). The explanations put forward by Ratchford et al (1994) is that human capital built up through years of using a particular product results in the familiar product being perceived as more valuable. The probability of repeat purchase is therefore higher. This suggests that older consumers would tend to repeat using the service of the same financial service provider. Another explanation is that older consumers have lower information processing capacities (Cole & Balasubramaniam, 1993). This suggests that they would search less, since the returns to search would be less, and therefore would delegate some functions to be performed by financial intermediaries. It is hypothesized that age will vary positively with the dimension that captures the notion of service and familiarity namely the factor labeled security and negatively with the dimension that requires personal input namely self-service.

3. Search effort: This is a measure of how much time the consumer spends searching for information about the product class under investigation, in this case mutual funds. An individual who uses his or her own time to find an appropriate mutual fund to purchase, would demand a higher return and favor more time intensive channels. This implies that Individuals who engage in higher amounts of search would demand channel which are more time intensive.

This is operationalized as the time spent searching for information about a product class before purchase, larger amounts of time spent searching for the appropriate mutual funds to purchase would reduce the need to delegate this particular search function to the retailer. This is used as an independent variable. It is hypothesized that higher levels of search effort will result in the need for less personal service and guidance from the financial service provider. Search effort is hypothesized to be positively related to self-service and negatively to security.

4. Familiarity:

This captures the notion of human capital. Familiarity arising from the repeated use of a channel creates higher perceived value in that channel. In other words, it gives rise to human capital. Individuals who are more familiar with a channel that provides personal service would value that aspect while others familiar with channels that offer little personal service would be accustomed to serving themselves. Thus, this variable is hypothesized to vary positively with security and self service. It is measure in terms of the number of years the individual had been investing.

5. Knowledge:

This has been recognized in the marketing literature to be multidimensional and related to search (Huneke, 2004; Harrison, 2002; Brucks 1985; Alba and Hutchinson 1987). Two kinds of knowledge are identified. The first is knowledge of investing ([K.sub.m]) and that refers to the understanding that consumers have of the nature, process and possible outcomes of investing. The second refers to the knowledge that consumers have of the channels they use and this is captured in our human capital term (HK).

Knowledgeable consumers do not need to spend time to invest. Their [delta][t.sub.i]/[delta][d.sub.i] is small. They would tend to demand higher returns without having to pay a substantial amount of fees. More time intensive channels are favored. This implies that the greater a consumer's knowledge of investing, the less time spend investing and the higher the demand for time intensive channels.

This is operationalized as a ten-item scale (Sample items are "I understand how mutual funds work," "I understand what I read in the mutual fund prospecturs," Cronbach alpha = 0.90). More knowledge of the product class enables an individual to efficiently perform functions which would be delegated by a less informed consumer to intermediaries in the channel structure. Therefore, more knowledge is associated with the use of shorter channel structures, such as direct purchase from the mutual fund company, or with the absence of sales personnel, such as discount brokers. It is therefore hypothesized that knowledge is negatively related to the dimension security and positively related to the dimensions of self-service, access and performance.

6. Education: Education facilitates the individuals ability to collect, process and use external information (Newman & Staelin, 1972; Ratchford & Srinivasan, 1991). These abilities make it easier to understand the purchase process when acquiring mutual funds. More highly educated individuals have lower [delta][t.sub.i]/[delta][d.sub.i]. They would tend to demand higher returns without having to pay a substantial amount of fees. More time intensive channels are favored. This implies that more educated consumers demand channels that offer less service. It is hypothesized that education would be negatively related to security and positively to self service.

Two exploratory research issues involves the extent to which gender differences and marital status differences exist in terms of influences on the demand for services.

7. Gender: Eagly and Wood (1985) posit that the male role has an agentic focus which gives rise to the tendency to be assertive and controlling while the female role has a communal focus which leads to a caring attitude for the welfare of others. Research in social psychology has shown that males tend to be resistant to external influences while females being more communal tend to be more susceptible (Cooper 1979, Eagly and Carly1981, Becker 1986). Thus it is hypothesized that males would tend to demand less amounts of security and females would require less amounts of self service.

8. Marital Status: Gagliano and Hathcote (1994) showed that married individuals tended to require higher amounts of reliability from their service vendor. It is therefore hypothesized that married individuals would require more security, access and performance. They would also be negatively related to self service.


OLS regression analysis was performed to evaluate how the 4 service dimensions vary with consumer characteristics. The results are reported in Table 2.

The results show that knowledge is negatively related to security and positively related to self-service as hypothesized. Both are significant at the 0.05 level. Individuals who possess more knowledge are able to understand the purchase process better and require less personal service from the financial service provider. Being more knowledgeable, they are able to navigate the complex investment process by themselves and do not need the "security" of guidance from the financial service provider. Knowledgeable consumers are also found to be positively related to access at the 0.1 level. This underscores the importance knowledgeable consumers place on being able to monitor and perform transactions in a timely manner.

Education is found to be significantly and negatively related to security as hypothesized. Being more capable of collecting, processing and using information, these individuals find it easier to understand the purchase process. They therefore do not require the security that service and guidance from the financial provider gives.

Familiarity is found to be positively and significantly related to security and self service as hypothesized. Consumers who have gained more familiarity have in essence built up a bank of human capital in a particular activity or provider and would thus place a large emphasis on the benefits it provides. Thus individuals who have built up a store of human capital in a channel offering the benefit of security would value that benefit while others who have become familiar with channels that are characterized as being more self-service would value this quality that they have become accustomed to.

Discretionary income is found to be negatively related to security and postively related to self-service. Both are significant at the 0.05 and 0.1 level respectively. Discretionary income relates in essence to "excess" income individuals have after all the essential expenses have been paid. Individuals with higher discretionary incomes would tend to be frequent investors. They would probably be more savvy about the investment process and be more skilled at navigating the purchase process. Thus, it seems quite logical that they would tend to be less dependent on the comfort of "security" and be able to perform more "self-service" activities.

Search effort is found to be significant at the 0.1 level and positively related to access. Individuals who perform large quantities of search activities would tend to be extremely interested in investment activities and require that they be able to conveniently reach their financial service providers to monitor and perform financial investments.

Though not significant, it is seen that males require less security and married individuals more. These results are in the direction hypothesized and are quite logical depiction of consumer behavior.

In summary, individuals with greater perceived knowledge would tend to place less emphasis on the dimension of security and more on the factor labeled self service. Familiarity leads to repeated usage of a channel and varies positively with both security and self service. Access is important to individuals who perform extensive search while education enables an individual to rely less on the security of personal services rendered by the provider and more on self service.

Thus, consumers who tend to use channels that provide the service of financial transaction but no guidance and advice tend to be more knowledgeable and expand greater search efforts. They also tend to be familiar with their financial provider and the investment process. Ease of access is important to these consumers. If channels such as discount brokers and direct sales outlets want to increase their market share they need to educate the target consumers. They need to persuade the novice target consumers that investing is not complex and is a task that can be accomplished with ease.

Channels that are characterized as being strong in the dimension of security, such as financial planners and full service brokers, need to continue to improving their relationship with their consumers. Customers who use these channels form familiarity with them and tend to stay.


Alba, Joseph W. & Wesley J. Hutchinson (1987), "Dimensions of Consumer Expertise," Journal of Consumer Research, 13 (March), 411-454.

Baumol, William J., Steven M. Goldfeld, Lilli A. Gordon & Michael F. Koehn (1990), "The Economics of Mutual Fund Markets: Competition Versus Regulation," eds. Karl Brunner and Paul W. MacAvoy, New York: University of Rochester.

Becker, B.J. (1986), "Influence Again: Another look at Studies of Gender Differences in Social Influence," in The Psychology of Gender Advances Through Meta-Analysis, eds. J.S. Hyde and M.C. Linn, MD: Johns Hopkins University Press, 178-209.

Brucks, Merrie (1985), "The Effects of Product Class Knowledge on Information Search Behavior," Journal of Consumer Research, 12, (June), 1-16.

Cole, C. & S. Balasubramanian (1993), "Age Differences in Consumers' Search for Information: Public Policy Implications," Journal of Consumer Research, 20 (June), 157-169.

Cooper H.M. (1984), "The Integrative Reviewer: A Systematic Approach," CA: Sage.

Currim, I.S. & R.K. Sarin, (1984), "A Comparative Evaluation of Multiattribute Customer Preferences and Models," Management Science, 30 (May), 543-561.

Doyle, John M. (1993), "SEC Considers Set of Changes in Mutual Fund Regulations," The Buffalo News, (Thursday) December 16.

Eagly, Alice H. & L.L. Carlin (1981), "Sex of Researchers and Sex-Types Communications as Determinants of Sex Differences in Influenceability: A Meta-Analysis of Social Influence Studies," Psychological Bulletin 90, 1-20.

Eagly, Alice H. & W. Wood (1985), "Gender and Influenceability: Stereotypes vs. Behavior," in Women, Gender and Social Psychology, eds. V.E. O'Leary, R.K. Vager & B.S. Wallston, NJ: Lawrence Erlbaum Associates, 225-256.

Fishbein, M. (1967), "Attitude and Prediction of Behavior," in M. Fishbein (ed.) Readings in Attitude Theory and Measurement. New York: John Wiley and Sons.

Furse, David H., Girish N. Punj & David W. Stewart (1984), "A Typology of Individual Search Strategies Among Purchasers of New Automobiles," Journal of Consumer Research, 10 (March), 417-427.

Gagliano, Kathryn Bishop & Jan Hathcote (1994), "Customer Expectations and Perceptions of Service Quality in Retail Apparel Specialty Stores," Journal of Services Marketing, 8, 60-69.

Hanak, Ellen E. (1992), "A Service-Based Theory of Retail Banking," Managerial and Decision Economics, 13, 183-200.

Harrison, Tina, (2002), "Consumer Empowerment in Financial Services: Rhetoric or Reality?" Journal of Financial Services Marketing, Vol. 7, Is. 1, 6-10.

Horsky, Dan & Paul Nelson (1992), "New Brand Positioning and Pricing in an Oligopolistic Market," Marketing Science, 11 (Spring), 133-151.

Huneke, Mary E., Catherine Cole & Irwin P. Levin (1994), "How Varying Levels of Knowledge and Motivation Affect Search and Confidence During Consideration and Choice, Marketing Letters, Vol. 15, Is. 2/3, 67-79.

Keeney, R. & H. Raiffa (1979). Decision Making with Multiple Objective Preferences and Value Tradeoffs New York: John Wiley & Sons Inc.

Lancaster, K.J. (1966) A New Approach to Consumer Theory, Journal of Political Economy, 132-157.

Lusch, Robert F. (1979), "Erase Distribution Channel from your Vocabulary and Add Marketing Channels," Marketing News (July), 12.

Newman, Joseph W. & Richard Staelin (1972), "Prepurchase Information Seeking for New Cars and Major Household Appliances," Journal of Marketing Research, 9 (August), 249-257.

Patterson, Paul G. (2007), "Demoraphic Correlates of Loyalty in a Service Context," The Journal of Services Marketing, 21(2), 112.

Ratchford, Brian T. & Narasimhan Srinivasan (1993), "An Empirical Investigation of Returns to Search, Marketing Science, 12 (Winter), 73-87.

Rosen, Sherwin (1974), "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, 82 (January/February), 34-55.

Sirri, Erik R. & Peter Tufano (1998), "Costly Search and Mutual Fund Flows," The Journal of Finance, 53(5), 1589-1613.

Stern Louis W. & Adel I. El-Ansary (1988), Marketing Channels, New Jersey: Prentice Hall.

Peggy Choong, Niagara University
Table 1: Factor Analysis of Salient Attributes

Attributes Factor 1 Factor 2

Personal service given by provider 0.72 -0.28
Reputation of provider 0.69 -0.03
Reliability of provider 0.68 -0.01
Provision of full service 0.66 -0.11
Familiarity with the provider 0.66 -0.21
Better control over investment 0.65 0.24
Convenient transaction 0.64 0.16
Ability of provider to achieve 0.64 0.09
 better performance
Accurate execution of orders 0.63 0.27
Adequate variety of funds 0.61 0.30
Accurate monthly statements 0.58 0.28
Reputation of fund adviser 0.56 0.05
Availability of other services 0.53 -0.44
Easy transfer of funds 0.52 0.47
Location of provider 0.51 -0.49
Dealing face to face 0.51 -0.67
Telephone service 1-800 0.37 0.63
Quality of financial advice 0.55 -0.59
24 hours access to a representative 0.47 0.21
Performance of fund 0.42 0.40

Factor labels Security Self-service

Attributes Factor 3 Factor 4

Personal service given by provider 0.08 0.04
Reputation of provider -0.44 -0.02
Reliability of provider -0.43 -0.30
Provision of full service 0.02 -0.34
Familiarity with the provider -0.27 -0.04
Better control over investment 0.11 0.17
Convenient transaction 0.17 -0.39
Ability of provider to achieve -0.46 0.12
 better performance
Accurate execution of orders -0.21 -0.22
Adequate variety of funds 0.21 0.13
Accurate monthly statements 0.11 -0.28
Reputation of fund adviser -0.24 0.48
Availability of other services 0.34 0.04
Easy transfer of funds 0.36 0.14
Location of provider 0.28 -0.02
Dealing face to face 0.25 0.13
Telephone service 1-800 0.29 -0.06
Quality of financial advice 0.00 0.17
24 hours access to a representative 0.46 0.10
Performance of fund -0.18 0.47

Factor labels Access Performance

Table 2: Ordinary Least Squares Results

Dependent Variable is: Security Self-Service

Independent Variables Beta T-ratio Beta T-ratio

Knowledge -0.02 * -6.04 0.01 * 2.32
Income 0.08 0.97 0.00 0.01
Familiarity 0.02 * 2.56 0.01 ** 1.67
Discretionary Income -0.85 * -2.37 0.64 ** 1.78
Search Effort 0.00 0.17 0.00 0.00
Gender -0.05 -0.52 -0.07 -0.72
Marital 0.07 0.46 -0.04 -0.26
Age -0.06 -0.54 -0.05 -0.48
Education -0.14 * -3.77 -0.02 -0.45

Dependent Variable is: Access Performance

Independent Variables Beta T-ratio Beta T-ratio

Knowledge 0.01 ** 1.83 0.00 1.11
Income 0.11 1.13 -0.03 -0.34
Familiarity -0.01 -1.07 -0.01 -1.05
Discretionary Income -0.45 -1.13 -0.24 -0.61
Search Effort 0.00 ** 1.70 0.00 0.74
Gender 0.02 0.18 -0.07 -0.64
Marital 0.06 0.37 0.20 1.16
Age -0.02 -0.17 -0.45 -0.42
Education -0.07 ** -1.72 -0.03 -0.77

Note: * denotes significance at the .05 level
** denotes significance at the .1 level
COPYRIGHT 2008 The DreamCatchers Group, LLC
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2008 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Choong, Peggy
Publication:Academy of Marketing Studies Journal
Date:Jan 1, 2008
Previous Article:Letter from the editor.
Next Article:Regional influences upon the selection of imported versus domestic seafood.

Terms of use | Privacy policy | Copyright © 2020 Farlex, Inc. | Feedback | For webmasters