Contemporary Research in E-Marketing_2 pot

We show these results in Table 3B and make the following observations: i rediff.com high information and high entertainment: The individual specific information seeking tendency appears

Data Collection

In the first survey, we collect data for classifying Web sites, and in the secondsurvey, we collect data for measurement of involvement In the third survey, wecollect data for measure of involvement after some fixed duration of time.Initially, before the first survey, we follow judges-based procedure to select theWeb sites for conducting the three surveys

Selection of Web Sites

We classified Web sites in a 2×2 (Information properties × Entertainmentproperties) matrix on the basis of the level (high or low) of their information andentertainment properties To initiate the selection of the Web sites, we usewww.bestindiansites.com’s “Top 50 Web Sites” appraisal, which uses param-eters such as traffic ratings by various traffic ranking tools, cross-links withsearch engines/other sites, ratings on various quality parameters (e.g., load time,browser compatibility), HTML validity, content, site design, and listings in majorsearch engines The following steps were taken for primary selection of Websites:

Step 1: We used “Top 50 Web Sites” data by www.bestindiansites.com for six

months prior to the study We give one point if the Web site appears in theTop 50 list in a week, and zero otherwise We then sum to get the totalnumber of times a Web site appeared in the list during the six months.9

Step 2: Using a cutoff value of 70%, we discarded the Web sites that appeared

in the list less than 70% of time.10 A reduced pool of 46 Web sites wasobtained after this step

Step 3: The above short-listed Web sites were classified on the basis of

information and entertainment properties of Web sites The classification

was done by three independent judges, who were postgraduate students

and used the Web (for surfing, literature search, paper downloads, etc.) forthe previous two years on average of over 30 hours per week The judgeswere asked to check the general criteria that the Web sites are easy tounderstand by the 18 to 25-year-old student respondents, and the Web sitesare of general interest (i.e., without any cultural or regional biases) In eachquadrant of the 2×2 matrix, we retained only those Web sites for whichthere were no differences among judges This resulted in a set of 20 Web

sites as shown in Table 1 To validate the classification by the judges, wethen contacted a larger group of respondents as discussed below.

Survey 1: Classification of Web Sites

Survey 1 is used for classifying, in terms of numerical values, the Web sites onthe basis of their information and entertainment properties This survey wasconducted with a sample of 31 respondents Each respondent examined threerandomly assigned sites out of the 20 Web sites11 listed in Table 1 Afterdiscarding some incomplete forms, there were 89 responses, which were usedfor the classification of Web sites The average of information and entertainmentproperties (on a scale of 1 to 5) of each Web site is presented in Table 2, and theirrelative positions are shown in Figure 2

We then compared the positions of the sites in Table 1 and Figure 2 and selectedthe sites, which were common to both for a particular quadrant Therefore, weselected www.rediff.com, www.indiainfoline.com, www.allindia.com, andwww.nazara.com for further analysis We selected two additional Web sites(www.mapsofindia.com and www.indiafm.com) closer to the mean for betteranalysis of the differences between the sites’ evaluations The brief overviewsand screenshots of some short-listed sites are shown in Appendix 2

Table 1 Web sites classified by the judges on the basis of information and entertainment properties

Entertainment Properties

High www.rediff.com www.123india.com www.indiainfo.com www.indiatimes.com www.indya.com www.webindia.com

www.mapsofindia.com www.timesofindia.com www.naukri.com www.indiainfoline.com

www.allindia.com www.dgreetings.com www.theholidays.com www.indiaserver.com www.ciol.com

Table 2 Site scores on information and entertainment properties

S No Name of Web Sites Information

Average Entertainment Average

Survey 2: Measurement of Involvement

Survey 2 is used for measuring the involvement and positive affect of therespondents toward a Web site This survey was conducted on a sample of 37respondents The sample included all the respondents who had participated inSurvey 1 and six additional respondents Most respondents (33 out of 37) in thesample were assigned two Web sites to examine, while a few (4 out of 37) wereassigned four Web sites Thus, this survey resulted in 82 responses The siteswere assigned randomly to respondents This survey was conducted in thefollowing manner

First, an in-class survey was conducted which was concerned with the individualcharacteristics pertaining to information (e.g., information-seeking tendency)and entertainment (e.g., sensation-seeking tendency) profiles of the respon-dents Then the respondents were told the names of the Web sites randomlyassigned to them 1 week before filling out the questionnaires related to utilitarianand hedonic evaluations of involvement and positive affect They were in-structed to visit the assigned sites as many times as they could over that period.One week later, they were asked to fill out the questionnaires in the computersystems laboratory

Survey 3: Effect of Time on Involvement

In Survey 3, we investigate the effect of time on the involvement of Web users

at a one-week interval for three weeks We appointed a panel of 14 respondentsfor this study Half of the respondents were new respondents, while the rest hadparticipated in the earlier two surveys Based on the possible levels of anindividual’s profiles (high × low, information × entertainment), which he/she filled

in the first session, we analyzed four types of respondents in this study For theentire period of this analysis, the respondents were assigned a specific Web siteout of the four possible Web sites classified in the above fashion

Results and Analysis

We performed statistical analyses using STATISTICA software on the lected data from various surveys

col-Reliability of the Constructs

The following Cronbach alpha values were found for the various constructs:

With the exception of sensation-seeking tendency scale, the other scales showreasonable values of Cronbach’s alpha In case of sensation-seeking tendencyscale, it is possible that some respondents were not able to relate well with somescale items such as “I sometimes like to do things that are a little frightening” or

“I would not like to be hypnotized.” This could be attributed to the language orcultural barriers hindering the correct interpretation of terms “hypnotized” or

“frightening.”

Analyses and Interpretation of Results

Results Related to Main Effects

Overall Results

For hypotheses testing, we use multiple regression technique The results ofindividual specific main effects are shown in Table 3(A) and the results of

moderator effects are shown in Table 3(B) All hypotheses, except Hypothesis

2(A), were supported at 95% level Hypothesis 2(A) on the relationship between

Scale Cronbach alpha

Utilitarian evaluation of involvement

hedonic evaluation of involvement and sensation-seeking tendency could not besupported, possibly due to the measurement-related problems mentioned earlier

in connection with the sensation-seeking tendency variable

The overall results, shown in Table 3(A), suggest that utilitarian evaluation ofinvolvement is significantly affected by the two factors, individual information-seeking tendency (α1 =0.65, t = 4.94) and individual specific focused attention

(α2 =0.33, t =2.52) Hence Hypotheses 1(A) and 1(B) are supported Similarly,

the hedonic evaluation of involvement is affected by the two factors, individualspecific sensation-seeking tendency and individual specific mood variability.Both factors are positive but only one factor (mood variability) is significant(β1 = 0.82, t = 10.31) Hence, it supports Hypothesis 2(B) but does not

provide enough support for Hypothesis 2(A)

Table 3(A) Overall results of main effects

Table 3(B) Site-specific results of main effects

Seeking Tendency

Sensation-Mood Variability Utilitarian Evaluation of

Involvement

Hedonic Evaluation of Involvement

Tendency

Mood Variability Utilitarian Evaluation

of Involvement

Hedonic Evaluation of Involvement Name of

Web Site (t-statistic) α1 (t-statistic) α2 (t-statistic) β1 (t-statistic) β2 (t-statistic) γ1 (t-statistic) γ2

The last result of Table 3A suggests that positive affect is also affected by twofactors, utilitarian (γ1 = 0.42, t = 4.6) and hedonic (γ 2 =0.58, t = 6.4) evaluation

of involvement Since both the independent variables are positive and significant,the results support Hypotheses 3(A) and 3(B)

on entertainment profile variables Moreover, the coefficient of regression ofaffect on utilitarian evaluation would be more significant than on hedonicevaluation of involvement for such a site Similar results for other sites wouldprovide greater support to our hypotheses testing results We show these results

in Table 3(B) and make the following observations:

(i) rediff.com (high information and high entertainment): The individual

specific information seeking tendency appears to affect utilitarian

evalua-tion of involvement (a 1 =0.79, t = 3.60), and individual specific mood variability appears to affect hedonic evaluation of involvement (b 2 = 0.95,

t = 7.43) For positive affect, only utilitarian evaluation of involvement is significant (g 1 = 0.66, t = 3.34) Thus, even though this site was classified

as high on both information and entertainment aspects, the respondentsrelied mainly on the utilitarian aspects while evaluating this site

(ii) mapsofindia.com (high information and low entertainment): Both vidual specific information-seeking tendency (a 1 =0.66, t = 4.25) and individual specific focused attention (a 2 =0.34, t = 2.15) affect utilitarian

indi-evaluation of involvement Again, individual specific mood variability

affects hedonic evaluation of involvement (b 2 = 0.75, t = 4.97), and as

expected, only utilitarian evaluation of involvement affects positive affect

(g 1 = 0.71, t = 4.33).

(iii) indiainfoline.com (high information and low entertainment): Individual

specific information-seeking tendency seems to affect utilitarian evaluation

of involvement (a 1 =0.87, t = 2.35) Individual specific mood variability seems to affect hedonic evaluation of involvement (b 2 = 0.95, t = 7.43) As

expected, only utilitarian evaluation of involvement affects positive affect

(g 1 = 0.63, t = 2.73).

(iv) allindia.com (low information and low entertainment): Both individual

specific information-seeking tendency and focused attention are not cant for utilitarian evaluation of involvement The effect of mood variability

signifi-is significant (b 2 = 2.6, t = 2.67) for hedonic evaluation of involvement For

positive affect, both utilitarian and hedonic evaluations of involvement arenot significant

(v) indiafm.com (low information and high entertainment): Individual specific

information-seeking tendency affects utilitarian evaluation of involvement

(a 1 =0.81, t = 2.26) even for this high entertainment site, which seems to

suggest that some respondents might have been interpreting some tainment-specific details (e.g., results from box office, movie review, cineawards, and interview of celebrities) as “relevant information.” Again, forhedonic evaluation of involvement, individual specific mood variability is

enter-significant (b 2 = 0.89, t =7.16), and as expected, only hedonic evaluation of

involvement affects positive affect (g 2 = 0.71, t = 3.36).

(vi) nazara.com (low information and high entertainment): Individual specific focused attention affects utilitarian evaluation of involvement (a 2 =0.66, t

= 1.96), which can be expected as even a high entertainment site maycontain some amount of information, which requires focused attention forentertainment-prone individuals For hedonic evaluation of involvement,

only individual specific mood variability is significant (b 2 = 0.72, t = 3.28).

As expected, only hedonic evaluation of involvement is significant for

positive affect (g 2 = 0.6, t = 2.27).

Results Related to Moderator Relationship

Hypotheses 4(A) to 6(B) are related to moderator relationship For analysisregarding Hypotheses 4 and 6A (i.e., information profile of a Web site), we poolthe observations of high and low information sites (HI vs LI) separately TheChow test for comparing the regressions of HI and LI sites of utilitarianevaluation of involvement on information-seeking tendency and focused atten-

tion results in the value of statistic = 6.31, which is greater than the critical

F-value of 3.13 at 5% confidence level and degrees of freedom 2 and 78 Thus,Hypothesis 4 is supported In other words, the positive impact of an individual’sinformation profile on utilitarian evaluation of involvement appears to be greaterwhen the information profile of the site assigned is better Similarly, the Chowtest for comparing the regression of positive affect on utilitarian evaluation of

involvement results in the value of F-statistic = 12.66, which is greater than the critical F-value of 3.98 at 5% confidence level and degrees of freedom 1 and 80.

Thus, the utilitarian evaluation appears to lead to more positive affect for betterinformation sites

For analysis regarding Hypotheses 5 and 6B (i.e., entertainment profile of a Website), we pool the observations of high and low entertainment sites (HE vs LE)separately The Chow test for comparing the regressions of HE and LE sites ofhedonic evaluation of involvement on sensations-seeking tendency and moodvariability, and positive affect on hedonic evaluation of involvement, result in the

values of F-statistic lower than the critical F-value at 5% confidence level Thus,

Hypotheses 5 and 6B are not supported This could be due to small sample size

in the case of individual sites or lower reliabilities of entertainment profilemeasures.12

Summary of Results

All the hypotheses, except hypothesis 2(A) on the relationship between hedonicevaluation of involvement and sensation-seeking tendency, are supported Ingeneral, the site-specific results are in the direction that makes intuitive sense.For example, an individual’s information profile factors, information-seekingtendency, and focused attention appear to affect significantly the utilitarianevaluations of high information sites (e.g., rediff.com, indiainfoline.com, ormapsofindia.com) Similarly, an individual’s entertainment profile factor, moodvariability, is important for hedonic evaluation of high entertainment sites (e.g.,allindia.com, indiafm.com, or nazara.com) Further, in general, utilitarian evalu-ation is more significant in generating positive affect in high information sites,whereas hedonic evaluation is more significant in generating positive affect inhigh entertainment sites

An interesting result obtained is that for some high entertainment sites (e.g.,indiafm.com), the individual information profile factors, such as information-seeking tendency, are also significant for utilitarian evaluation of involvement.This could be attributed to the nature of information available at these sites.Moreover, for all of the high information sites, the individual entertainment profilefactor, mood variability, was found highly significant in explaining hedonicevaluation It is also possible that some of the short-listed Web sites wereinterpreted as both informative and entertaining This could particularly be thecase with the sites that provide relevant “information” about “entertaining”Indian movie industry

Results of Effect of Time on Involvement

Since the concept of involvement has long-term implications, it is useful to studythe effect of time on involvement (Richins & Bloch, 1991) Previous researchers

have also differentiated between situational involvement (primarily dealt with inthis paper) and enduring involvement (a long-term measure of involvement,which has time-based implications) (Bearden & Netemeyer, 1992) It is ex-pected that the involvement of a visitor would increase in the case of a matchbetween the site profile and the user profile, and vice versa We present somerepresentative results of this site-user analysis in Figure 3.

When a high information and high entertainment profile respondent is “matched”with a site of high information and high entertainment profile (e.g., rediff.com),the utilitarian as well as hedonic evaluation of a person (high on information aswell as entertainment profile) increases as time passes (see Figure 3(A)) Incase of a match of a high information and low entertainment profile respondentwith a high information but low entertainment profile site (e.g., indiainfoline.com),the utilitarian evaluation of the respondent increases, but hedonic evaluation ofinvolvement does not show any trend with the passage of time (see Figure 3(B))

In case of a mismatch of a low information and high entertainment profilerespondent with a high information but low entertainment profile site (e.g.,indiainfoline.com), as expected, both utilitarian and hedonic evaluations showgenerally decreasing trend (see Figure 3(C)) Interestingly, in case of a match

Figure 3 Time-based measurement of involvement

5.2 5.3 5.4 5.5 5.6 5.7

of a low-low respondent with a low-low site, the evaluations do not show anytrend as time passes (see Figure 3(D)) The result is interesting as it indicatesthat the sites that provide low levels of information or entertainment may not beable to involve a person who is low in seeking information or entertainment.These results are encouraging, and future research should examine such time-based evaluations of involvement in greater detail.

Conclusions, Limitations, and

Directions for Future Reseach

The importance of Internet-based commerce to the global economy has longbeen recognized (Henry et al., 1999) However, as the competition in thisenvironment intensifies, Web marketers increasingly need to understand factorsthat engage consumers in order to fulfill their marketing objectives in terms ofvisit durations, repeat visits, and online purchase We propose the currentframework as an important early step in developing the understanding and use

of factors affecting consumer involvement toward Web sites

Figure 3 Time-based measurement of involvement

At a broad level, the major contribution of this line of research is to conceptualizethe factors that lead a consumer to visit a Web site more frequently and toillustrate how the individual difference in Web site involvement can be explainedand measured in terms of the different constructs Our results show that thecomponents of consumer’s information (e.g., information-seeking tendency,focused attention) and entertainment (e.g., mood variability) profiles signifi-cantly affect utilitarian (need, value) and hedonic (interest, appeal) evaluations

of involvement, respectively, to generate positive affect toward the Web site.Web site factors such as informativeness and organization further enhance theserelationships

Our findings imply that a good Web site is one that delivers relevant and organized information in an engaging manner At a basic level, the majormanagerial implications of our work are that if a site has high informationproviding elements, then it must target high information-seeking visitors Con-versely, for a given segment profile, our methodology can help in editing anddesign decisions by studying the impact of modifying the site’s content according

well-to the involvement level of the target segment

Since the proposed framework involves stable individual difference factors (e.g.,information- or sensation-seeking tendencies), the approach can be used tocompare the online consumer behavior from diverse backgrounds, nationalities,and cultures for the benefit of global sites such as amazon.com or yahoo.com.The consumer behavior differences can also be compared for traditional versuselectronic media Further, understanding differences in people’s behavior couldalso aid the development, design, and evaluation of commercial Web sites, onlineretail stores, search engines, and other information products and services Theculmination of the proposed framework in a quantitative model of onlineconsumer behavior will help generate a priori predictions about the effectiveness

of different Web site designs and promotional strategies There might also be ahigher dimension to the concept of involvement in online environments Forexample, there might be a greater possibility of involvement of online consumerswho are more techno-ready (see Parasuraman, 2000, and Parasuraman &Colby, 2001, for the concept of techno-readiness)

Our study has some limitations, which could be addressed by future research.The survey involved student respondents who tended to be younger, bettereducated, and more informed than the general Internet population It is possiblethat these individuals have greater ability to use and develop affect toward a Website; thus, their responses would overstate the true evaluation of Web site for allconsumers On the other hand, it is plausible that these individuals would alsohave higher expectations regarding information and the market strategies ofWeb sites, and thus might be more critical of Web sites Further, it is possible thatsome subjects who viewed more than one Web site may have carried their

evaluations from one Web site to another Future researchers should examine alarger sample without repeated measures Another refinement could be anexperiment that also examines interactions Such an experiment could be2×2×2×2 type, in which the first two combinations refer to the individual’s andthe last two combinations refer to the site’s information and entertainmentproperties.

In the present framework, we have included only information and entertainmentprofiles of an individual Some other personality or demographic characteristics,such as skill, Web usage, and playfulness, should also be included in futureresearch Further research on the Web site involvement model could also includeadditional variables, which we may have omitted in the interest of parsimony andtractability For example, the investigation of the role of prior expectation toenjoyment, based on advertising and word of mouth, could play a role indetermining actual enjoyment Another variable that could be included in thisframework is that of techno-readiness of a consumer (Parasuraman, 2000) Ahypothesis worth examining in this context could be that more techno-readyconsumers of the Web show greater levels of involvement than those by novices.Our model is essentially a static model in which we took individual constructs asstable over time, although some construct may change during the consumptionexperience Therefore, another research direction would be to extend thisframework to take into account the dynamic nature of different constructs.Another attractive future research direction would be to extend the model formeasuring the customer’s involvement for those consumers who purchasedfrom Web sites

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