Research Article: 2022 Vol: 26 Issue: 4
Malay Bhattacharjee, Vellore Institute of Technology
Gautam Bandyopadhyay, National Institute of Technology
Sudheer Muhammed, Vellore Institute of Technology
Citation Information: Bhattacharjee, M., Bandyopadhyay, G., & Muhammed, S. (2022). Determination of effectivity of significant information sources in the decision making process of select durable commodities: A multivariate statistical approach for low literate consumers. Academy of Marketing Studies Journal, 26(4),1-12.
Consumer behavior.
Investigations also reveal that and had proposed a model relating to the stages involved in the consumption behaviour having five steps ear-marked as awareness, interest, evaluation, trial and adoption. In the same context suggested that the principle aim of marketing activities in the introductory stage of a hospitality product is to create product awareness. So, it is hereby evident that all the models indicate that for repeat purchase behaviour, first and foremost there must be a prior purchase, which can be ear-marked as ‘trial purchase’, and consequently, it needs no mention that ‘trial purchase’ can only be possible when awareness about the product is there with the consumer (Milman & Pizam 1995). Here, literatures suggest that ‘awareness’ depends on ‘information’ and its various sources as consumers rely a given information source, for instance the consumers reliance on websites (Chatterjee 2001; Dholakia & Soltyinski 2001) this is to some extent because, prior knowledge about a product significantly helps a consumer in acquiring or looking for new and updated information in his search endeavor. Bhattacharjee & Bandyopadhyay (2017) suggest that, relevant information and its processing hold the very first step towards the consumption of a product, as it is suggested that people (consumers) engage themselves in purposeful and meaningful information processing before choosing, deciding to buy, or buying Petty, Cacioppo & Schumann 1983). It must be noted here that the sources of information for the consumers are segmented into two broad categories, a) internal and b) external source, and that both these sources are extensively used by the consumers to effectively deal with perceived risk of purchase (Murray 1991), as well as Lynch & Srull (1982) suggests that ‘internal’ informational search is fundamentally linked to ‘memory scan’, while on the other hand ‘external’ information search depicts a well directed and purposeful intention of the consumer to look for information from the existing environment which is not known to him (Moore & Lehman 1980).
This study pertains to a typical class of people termed as ‘Low-Literate’, that is, individuals who have acquired a functional literacy of standard six or below of formal education (Adkins & Ozanne 2005), of Kolkata. It’s worth mentioning that information about how these people meet their needs in their daily lives is practically not there (Adkins & Ozanne 2005) including their consumption of durable commodities (Bhattacharjee & Bandyopadhyay 2017). This study aims to further extend the earlier study which came up with understanding, that, out of the eight sources of information considered by Price & Lawrence (2001), three were found to be of potential importance to this category of people (Bhattacharjee & Bandyopadhyay 2017) when they look for information, especially, for select durable products like: Televisions, Refrigerators, DVD’s, Washing Machines, Air Conditioners, Water Filters, Mobile Phones for self use, and Mobile Phones for family use. The three potential sources as identified are: ‘Word-of-mouth’, ‘Sales People’, and finally ‘Imitation Behavior’ (Bhattacharjee & Bandyopadhyay 2017). This study aims to identify the effectiveness of the said sources of information pertaining to the select durable commodities considered for the purpose of the study. In simple words, the study would come by with the clear understanding as to which source of information happens to be the most effective for each of the products considered for the purpose of the study in relation to the ‘Low-Literate’ consumers of Kolkata.
Objective(s) of the Study
1. Identify if all the information sources, that is, word-of-mouth, sales people, and imitation behavior are equally important for the consumers of this category (Low-Literate) for all the given durable products under study.
2. Identify which source of information among word-of-mouth, sales people, and imitation behavior does have the highest relevance and acceptance among the ‘Low-Literate’ consumers for each of the products under contention.
Evidence shows that very few studies have been done till date on the ‘Low-Literate’ consumers. But within the very few resources available, it becomes evident that the ‘Low-Literate’ consumers are faced with a host of impediments, for example, difficulty in interpreting written communication because of their constrained literacy skills while evaluating various products of tangible and intangible nature (Kirsch et al. 1993). It is understood that ‘product information’ in the real life practice educates the consumers about the given product or brand. In this respect one cannot deny the fact that consumer education becomes pivotal with the growing complexity of the marketplace. The principle reason for which a firm engaged in making high quality products increases sales over time is primarily to utilize the benefits of the communication that originates from the consumers in the fullest way, as this consumer driven communications result in educating the prospective consumers about the given product. To quote Adkins & Ozanne (2005): “Consumer education programs assume that consumers have the right to full product information, and well-informed consumers will be able to get their needs met in the marketplace”. Wallendorf (2001) supports this view and suggests that ‘Low-Literate’ consumers are faced with a vulnerable and unfavourable situation in the marketplace.
It is true that in the age of consumerism the consumer stands as the king (McGuire 2000) but only partially, as unless the consumer is armed with relevant product information, very high chance exists whereby the consumer would be the victims of lower quality product choices as in the case of ‘Low-Literate’ people (Jea & DelVecchio 2004). Interpersonal sources of information are extensively used in the consumer decision making process (Price & Lawrence 2001) of which ‘Word-of-Mouth’, ‘Sales People’, and ‘Imitation Behaviour’ are three different types. All of these three sources are found to be very much potential and relevant to this category of people when it comes to the consumption of the durable commodities in contention. As already discussed ‘Low-Literate’ consumers often face limitations of interpreting written communications because of their educational inadequacy. As a result, consumers are often found to be restricting themselves to a single source of information or considering a single alternative (Newman & Staelin 1972; Newman 1977; Olshavsky & Granbois 1979).
Word-of-Mouth (WOM) as a Potential Source of Information and Consumers Reliance on It
Information sources which tend to ultimately take the shape of references or recommendation sources in the consumer decision making process, are in a way, not exclusively, considered as personal sources of information (Stewart et al., 1985) and but incidentally all are being studied under the nomenclature of ‘word-of-mouth’ communication suggest that there lies a high possibility of consumers getting influenced by their reference groups. Here, it is understood that the prospective consumer always seeks information about the product that he or she is interested to arrive at a favourable decision. Evidences prove that word-of-mouth is widely accepted as a much more credible source over other sources of information which are typically generated by the selling firm. In the process these probable consumers being uncertain about the characteristics of a given product learns a lot about the product or product brand from the existing consumers who have a prior experience of the product or product brand. In a recent study it appears that, online word-of-mouth in the form of consumer opinions, users experiences, and product reviews have emerged as a significant source of information in the decision making process of consumers (Gu et al. 2012). In this field Mishra & Satish (2016) corroborates that “online reviews are one type of electronic word-of-mouth communication”.
Sales People (SP) As a Potential Source of Information and Consumers Reliance on it
It is assumed that a product (of any nature, class, or category) is being sought by consumers to solve a problem physical or psychological in their daily life. Thereby, a given product, tangible or intangible, serves as a solution to the consumer for then. Previous literatures suggest that 63 percent of the ‘Fortune 100’ firms presently offer ‘solutions’ and not products of tangible or intangible nature to their customers (Tuli et al., 2007). Sales people play a very important role in providing a customer with a solution that their firms have developed (Panagopoulos et al., 2017). Contemporary studies concerning the role of sales people, states that the sales people play a critical role in the customer interaction interface (La Rocca et al., 2016; Murtha et al., 2014). Modern day firms have understood the all important role of the sales people and this becomes evident when it is seen that majority of the Fortune 100 firms have prioritized their efforts in building an efficient sales force who are focused on rendering solutions to customers or consumers (Guido 2012; Koivuniemi, 2016). A study taken up in Seattle, Washington and, Anchorage, Alaska to determine the most effective source of information to consumers of kitchen cabinets while these consumers were subject to buying. It was found that the in-store sales people were the most sought after source of product information to the consumers (Donovan et al., 2004). There seems to be a very high possibility that sales people are often being considered as ‘opinion leaders’ by the consumers because opinion leadership is often regarded as being product class specific.
Imitation Behaviour (IB) as a Potential Source of Information and Consumers Reliance on it
Imitation Behaviour which can be defined as information gathered by the consumers through talks, observation, mere copying, and, or more than one of these or all of these, happens to be a major source of human learning (Morales 2002). The great Italian philosopher and statesman Niccolo Machiavelli stated that “Men nearly always follow the tracks made by others and proceed in their affairs by imitation” (https://www.goodreads.com). Bonabeau (2004) in his study quotes the great Greek philosopher Aristotle’s famous words “One of man’s advantages over the lower animals is that he is the most imitative creature in the world”. Since long ago social scientists or researchers are found to have recognized imitation in human society as a very important phenomenon. All of these justify the fact that ‘imitation behaviour’ in human being is a natural trait and is very common. In the same likelihood it can well be assumed that imitating others happens to be a very common phenomenon in consumer purchases also. In fact it has been identified that a major chunk of the researchers assume that, in the real life practice, imitation behaviour has a significant contribution in the generation of demand of commodities (Bass et al. 1969; Griffin, 2006). Bonabeau (2004) suggests that people imitate others as they believe that the other person knows better than him. At the same time literature suggests that when a consumer is faced with too much information needing to be processed, imitation becomes an easy way out (Bonaneau, 2004) as it is perceived to be fast and economical too (Gigerenzer & Goldstein 1996). The whole thing sums up to the understanding that lack of information or lack of abilities in understanding the available information creates uncertainty in the mind of a given consumer, in turn under the prevailing uncertainty imitation is deemed to be quite advantageous for a variety of rationale (Briscoe & Safford 2008).
Research Idea
Investigations in the field of ‘Low-Literate’ consumers reveal that only a very few studies have been made so far involving these people throughout the world and nothing in India so far. In other words this study is the first of its kind in this country. As this country (India) does have a large population who are deemed to be ‘Low-Literate’, and constitute a substantial share of the market, it becomes imperative to know them and their consumption process. Earlier study made by the same authors identified word-of-mouth, sales people, and imitation behaviour as the most accepted sources of information to this population among several sources. This study aims to find out which source of information, out the three (already mentioned) sources has the highest impact on the ‘Low-Literate’ consumers in relation to all the products considered. This would somehow give a direction, by which the producers or brands would be able to understand which route they should take to inform these people pertaining to their product or products.
Research Gap
It is already discussed that work with this set of people (Low-Literate) has been very few. Furthermore, nothing worth mentioning could be identified about the consumption of durable commodities of these people. Nothing in this area has been done in this country. In an earlier study the same authors have identified the most effective sources of information which have a considerable impact on the consumption of select durable commodities of these people. But, as the present study has considered eight consumer durables of varying nature, it can well be assumed that the effectivity of all of the three sources of information would not be the same with all the commodities considered. Given this as pretext, the following is understood to be the gap which this study would address in due course:
Identify which source of information has the highest acceptance for which product, and is mostly sought by these consumers, whenever, they decide buying any of the eight durables considered for purpose of the study.
Research Methodology
The basic purpose of going into the quantitative approach is to find out the relevance of the said sources of information in contention to the ‘Low-Literate’ consumers decision making process. In this regards the questionnaire has used a ‘Likert’ scale where “1 = completely disagree; 2 = disagree; 3 = neutral; 4 = agree; and 5 = completely agree.”
WoM, SP, and IB have been found to be the most entrusted and effective sources of information, to this set of people (Bhattacharjee & Bandyopadhyay 2017). This study has been taken up to identify the products which require the aid of these sources one or more, in somewhat influencing the consumers in their decision making process. The Mean ( ) value of all the eight products considered for WoM, SP, and IB has been calculated initially to derive the Grand Mean (GM) of the respective category. Where GM = Σ (of all X where, X = respondents answers for each product in a scale of five) / n where, n=8 (number of products considered).
The need for ‘criteria’ selection necessitated in the development of a computation method.
As already discussed the questionnaire itself made it evident that scores of 1, 2, and 3 reflect ‘Negative or Neutral outcome’, while 4, and 5 reflect ‘Positive outcome’.
Let, p = Probability of two ‘Positive responses’ And, q = Probability of three ‘Negative response’. Let ‘Y’ here be the random variable of taking the responses from the various households with positive responses (4 or 5) and complement of positive responses (1 or 2 or 3).
Y: 2 3
PY: 2/5 3/5
Therefore E (Y) = 2 * 2/5 + 3 * 3/5 = 13/5 = 2.6
Therefore, 2.6 can be considered as the mean of Y.
Again, Variance of Y = E (Y2) – {E (Y)}2
That is, S. D (Y) = √V (Y)
E (Y2) = 22 * 2/5 + 32 * 3/5 = 8/5 + 27/5 = 7
V (Y) = 7 – (2.6)2 = 7 – 6.76 = 0.24
Again, SD (Y) = √0.24 = 0.49
Using E (Y) and SD (Y) we get the range of criteria of acceptance of the respondents’ responses which are enumerated below:
That is, equation: (6.1) 2.6 – 0.49 = 2.11 (lower limit of the criteria)
(6.2) 2.6 + 0.49 = 3.09 (upper limit of the criteria)
Therefore, the range of the criteria value selected exists between 2.11 and 3.09 in our proposed model for selecting the dichotomous values of the dependent variable.
Now, the product wise positive responses of the individuals (400 in number) have been considered. For eight products an individual would be giving (400*8) that is 3200 responses, out of them some would be ‘Positive’ in nature while some would be ‘Complement of Positive’. The study has considered only the ‘Positive’ responses of the respondents for a given query. The reason behind this approach happens to be the simple logic that of categorically finding out the consumer reliance pertaining to the three sources of information. So, the number of ‘positive’ responses in each case has been divided by total responses and then the outcome is multiplied by 5, (since there are five options used in the questionnaire in accordance with the Likert scale). Taking the arithmetic mean of the desired output (AM of Lower limit and Upper limit [6.1 and 6.2]) and the Grand mean has enabled us to fix the criteria for running the Logistic Regression model. The main reason behind this was to arrive at a point where the arithmetic mean (AM)>sample mean SM, (sample mean (SM) has been calculated by the average of respondent answers for eight products for each factor) would be considered as 1 otherwise 0, that is, the AM values for WoM 3.0825, SP 2.755625, and IB 2.8946875 if > than their respective SM values for 400 respondents then, it would be considered as 1 otherwise 0. This was called for to enable the application of Logistic Regression Approach to analyze the ‘goodness of fit’ of the derived models on WoM, SP, and IB. Logistic Regression is frequently applied to determine the association of dichotomous responses which generally culminates in providing odd ratios (Dwivedi et al., 2014).
As the AM values of WoM was calculated as 3.0825; SP as 2.755625; and IB as 2.8946874, it clearly signifies that all the AMs of these three factors lies within the criteria range of 2.11 and 3.09 indicating that the approach thus taken is reliable and robust enough to come through with a desired outcome.
Hypothesis Testing
H01: Word-of-Mouth is an effective source of information for more than one durable commodity considered.
H02: Sales People are an effective source of information for more than one durable commodity considered.
H03: Imitation Behaviour is an effective source of information for more than one durable commodity considered.
The Hosmer and Leme shows Test of goodness-of-fit in this case have been considered at 1 percent level of significance. The test does indicate that WoM does have a role as a source of information to these people but it is also true that the function of WoM is quite restricted in order Table 1.
Table 1 Hosmer and Lemeshow Test for Wom | |||
Step | Chi-square | df | Sig. |
1 | 12.432 | 5 | 0.029 |
Table 2 shows that the model created with the help of logistic regression in relation to WoM as a source of product information within the select band of durable commodities considered for the purpose of the study is capable of predicting 77 percent overall. While if we look at the performance of the model in relation to the observed response categories with that of the predicted response categories, then we find that those who rely on WoM can be predicted to the extent of 85.1 percent while those who do not can be predicted to the extent of 59.2 percent.
Table 2 Showing the Predictability of the Model in Relation to Wom | |||||
Observed | Predicted | ||||
Trial | Percentage Correct | ||||
0 | 1 | ||||
Step 1 | Trial | 0 | 74 | 51 | 59.2 |
1 | 41 | 234 | 85.1 | ||
Overall Percentage | 77.0 |
Variable(s) entered on step 1: WoM_TV, WoM_REF, WoM_DVD, WoM_WM, WoM_AC, WoM_WF, WoM_Mob_S, WoM_Mob_F. The Wald test is used to determine statistical significance for each of the independent variables. From the test results of Table 1.3, we can find that WoM_TV (p=.003), WoM_Mob_F (p=0.000), WoM_WF (0.002), WoM_AC (0.005), WoM_WM (0.188) added significantly towards the prediction of the model. Therefore, in other words it can be said that WoM as a source of information is 11.678 times more effective than it is with WoM for Mobile phones for family use. Therefore, it is understood that WoM as a source of information has a significant contribution in the decision making process for products like Mobile phones for family use, Water filter, TV, and AC in particular Tables 3 and 4.
Table 3 Showing Theproduct wise Effectiveness of Wom | |||||||
B | S.E. | Wald | df | Sig. | Exp(B) | ||
Step 1a | WoM_TV | 2.458 | 0.823 | 8.926 | 1 | 0.003 | 11.678 |
WoM_REF | -17.672 | 40197.541 | 0.000 | 1 | 1.000 | 0.000 | |
WoM_DVD | 23.156 | 40197.541 | 0.000 | 1 | 1.000 | 11390658770.734 | |
WoM_WM | 1.370 | 1.040 | 1.736 | 1 | 0.188 | 3.935 | |
WoM_AC | 1.859 | 0.662 | 7.878 | 1 | 0.005 | 6.414 | |
WoM_WF | 1.827 | 0.596 | 9.413 | 1 | 0.002 | 6.218 | |
WoM_Mob_S | 0.315 | 0.579 | .296 | 1 | 0.586 | 1.371 | |
WoM_Mob_F | -11.462 | 3.202 | 12.817 | 1 | 0.000 | 0.000 | |
Constant | -4.899 | 0.840 | 34.030 | 1 | 0.000 | 0.007 |
Table 4 Hosmer and Lemeshow Test for SP | |||
Step | Chi-square | df | Sig. |
1 | 11.628 | 7 | 0.113 |
The Hosmer and Lemeshow Test of goodness-of-fit in this case have been considered at 7 percent level of significance. The test does indicate that SP (Sales People) does have a role as a source of information to these people in their decision making process Table 5.
Table 5 Showing the Predictability of the Model in Relation to SP | |||||
Observed | Predicted | ||||
Source_Credibility | Percentage Correct | ||||
0 | 1 | ||||
Step 1 | Source_Credibility | 0 | 0 | 25 | 0.0 |
1 | 0 | 375 | 100.0 | ||
Overall Percentage | 93.8 | ||||
a. The cut value is 0.500 |
Table 5 shows that the model created with the help of logistic regression in relation to SP as a source of product information within the select band of durable commodities considered for the purpose of the study is capable of predicting 93.8 percent overall. While if we look at the performance of the model in relation to the observed response categories with that of the predicted response categories, then we find that those who rely on SP can be predicted to the extent of 100 percent while those who do not cannot be predicted giving the overall prediction at 93.8 percent Table 6.
Table 6 Showing Theproduct wise Effectiveness of SP | |||||||
B | S.E. | Wald | df | Sig. | Exp(B) | ||
Step 1a | SP_TV_LR | -0.439 | 0.405 | 1.179 | 1 | 0.278 | .644 |
SP_REF_LR | 0.720 | 0.426 | 2.852 | 1 | 0.091 | 2.054 | |
SP_DVD_LR | 0.241 | 0.635 | 0.144 | 1 | 0.704 | 1.273 | |
SP_WM_LR | 0.146 | 1.092 | 0.018 | 1 | 0.893 | 1.157 | |
SP_AC_LR | 0.768 | 1.054 | 0.532 | 1 | 0.466 | 2.156 | |
SP_WF_LR | 0.030 | 0.585 | 0.003 | 1 | 0.959 | 1.030 | |
SP_Mob_S_LR | -0.276 | 0.465 | 0.352 | 1 | 0.553 | 0.759 | |
SP_M0b_F_LR | 0.294 | 0.516 | 0.325 | 1 | 0.569 | 1.342 | |
Constant | -1.866 | 1.548 | 1.453 | 1 | 0.228 | 0.155 | |
a. Variable(s) entered on step 1: SP_TV_LR, SP_REF_LR, SP_DVD_LR, SP_WM_LR, SP_AC_LR, SP_WF_LR, SP_Mob_S_LR, SP_M0b_F_LR. |
From the test results of Table 7, we can find that the Wald statics indicate SP_WF =0.003, and SP_WF=0.018, added significantly towards the prediction of the model. Therefore, it is understood that SP as a source of information has a significant contribution in the decision making process for products like Water Filter and washing Machines in particular.
Table 7 Hosmer and Lemeshow Test for IB | |||
Step | Chi-square | df | Sig. |
1 | 11.880 | 7 | .105 |
The Hosmer and Lemeshow Test of goodness-of-fit in this case have been considered at 7 percent level of significance. The test does indicate that IB (Imitation Behaviour) does have a role as a source of information to these people in their decision making process.
Table 8 shows that the model created with the help of logistic regression in relation to IB as a source of product information within the select band of durable commodities considered for the purpose of the study is capable of predicting 93 percent overall. While if we look at the performance of the model in relation to the observed response categories with that of the predicted response categories, then we find that those who rely on IB can be predicted to the extent of 100 percent while those who do not can be predicted to the extent of 6.7 percent.
Table 8 The Predictability of the Model in Relation to IB | |||||
Observed | Predicted | ||||
SC_SCORE_IB | Percentage Correct | ||||
0 | 1 | ||||
Step 1 | SC_SCORE_IB | 0 | 2 | 28 | 6.7 |
1 | 0 | 370 | 100.0 | ||
Overall Percentage | 93.0 | ||||
a. The cut value is 0.500 |
From the test results of Table 9, we can find that WF_IB (p=0.009), DVD_IB (p=0.046), have added significantly towards the prediction of the model. Therefore, in other words it can be said that IB as a source of information is approximately 11.106 times more effective in WF (Water Filters) than it is with for Mobile phones for family use. Therefore, it is understood that IB as a source of information has a significant contribution in the decision making process for products like WF, and DVD players in particular.
Table 9 TheProduct wise Effectiveness of IB | |||||||
B | S.E. | Wald | df | Sig. | Exp(B) | ||
Step 1a | TV_IB | 0.538 | 0.508 | 1.122 | 1 | 0.290 | 1.712 |
REF_IB | -0.996 | 0.614 | 2.627 | 1 | 0.105 | 0.370 | |
DVD_IB | -2.748 | 1.377 | 3.984 | 1 | 0.046 | 0.064 | |
WM_IB | 1.355 | 1.615 | 0.704 | 1 | 0.401 | 3.877 | |
AC_IB | 1.383 | 1.174 | 1.388 | 1 | 0.239 | 3.988 | |
WF_IB | 2.407 | 0.928 | 6.736 | 1 | 0.009 | 11.106 | |
Mob_S | .236 | 0.516 | 0.209 | 1 | 0.647 | 1.266 | |
Mob_F | -.114 | 0.542 | 0.044 | 1 | 0.834 | 0.893 | |
Constant | -3.933 | 1.473 | 7.125 | 1 | 0.008 | 0.020 | |
a. Variable(s) entered on step 1: TV_IB, REF_IB, DVD_IB, WM_IB, AC_IB, WF_IB, Mob_S, Mob_F. |
This paper has tried to categorically identify the role of the three potential sources of information, which were a result of our last endeavor, namely Word-of-Mouth (WoM), Sales People (SP), and Imitation Behaviour (IB). This work has tried to predict the products within the selected list of durable commodities considered for the purpose of the study which when considered for purchase actually gets triggered by one source or more sources of information as the sources of information are deemed as ‘credible’ to the concerned consumer. Knowing this it is assumed that, a given brand of these commodities can try out to reach these people at the shortest possible time involving the least cost but can reap the benefit of being taken as ‘credible’ as a result of the calculated approach. The study is limited by the size of its sample. The study has confined itself to the city of Kolkata only which can also be a limitation.
Adkins, N.R., & Ozanne, J.L. (2005). The low literate consumer. Journal of Consumer Research, 32(1), 93-105.
Indexed at, Google Scholar, Cross Ref
Adkins, N.R., & Ozanne, J.L. (2005). Critical consumer education: Empowering the low-literate consumer. Journal of Macromarketing, 25(2), 153-162.
Indexed at, Google Scholar, Cross Ref
Bhattacharjee, M., & Bandyopadhyay, G. (2017). Effectivity wise ranking of interpersonal sources of information in the consumer decision making process of select consumer durables: evidence from the “low-literate” consumers of Kolkata. Asian Journal of Multidimensional Research (AJMR), 6(9), 133-142.
Bonabeau, E. (2004). The perils of the imitation age. Harvard business review, 82(6), 45-54.
Briscoe, F., & Safford, S. (2008). The Nixon-in-China effect: Activism, imitation, and the institutionalization of contentious practices. Administrative science quarterly, 53(3), 460-491.
Indexed at, Google Scholar, Cross Ref
Chatterjee, P. (2001). Online reviews: do consumers use them?.
Dholakia, U.M., & Soltysinski, K. (2001). Coveted or overlooked? The psychology of bidding for comparable listings in digital auctions. Marketing Letters, 12(3), 225-237.
Indexed at, Google Scholar, Cross Ref
Donovan, G.H., Nicholls, D.L., & Roos, J. (2004). Sources of product information used by consumers when purchasing kitchen cabinets. Forest Products Journal. 54 (12): 77-79.
Dwivedi, A.K., Mallawaarachchi, I., Lee, S., & Tarwater, P. (2014). Methods for estimating relative risk in studies of common binary outcomes. Journal of applied statistics, 41(3), 484-500.
Indexed at, Google Scholar, Cross Ref
Gigerenzer, G., & Goldstein, D.G. (1996). Reasoning the fast and frugal way: models of bounded rationality. Psychological review, 103(4), 650.
Indexed at, Google Scholar, Cross Ref
Gu, B., Park, J., & Konana, P. (2012). Research note—the impact of external word-of-mouth sources on retailer sales of high-involvement products. Information Systems Research, 23(1), 182-196.
Hauser, J., Tellis, G.J., & Griffin, A. (2006). Research on innovation: A review and agenda for marketing science. Marketing science, 25(6), 687-717.
Indexed at, Google Scholar, Cross Ref
La Rocca, A., Moscatelli, P., Perna, A., & Snehota, I. (2016). Customer involvement in new product development in B2B: The role of sales. Industrial Marketing Management, 58, 45-57.
Indexed at, Google Scholar, Cross Ref
Lynch Jr, J.G., & Srull, T.K. (1982). Memory and attentional factors in consumer choice: Concepts and research methods. Journal of consumer research, 9(1), 18-37.
Indexed at, Google Scholar, Cross Ref
McGuire, W.J. (2000). Standing on the shoulders of ancients: Consumer research, persuasion, and figurative language. Journal of consumer research, 27(1), 109-114.
Indexed at, Google Scholar, Cross Ref
Milman, A., & Pizam, A. (1995). The role of awareness and familiarity with a destination: The central Florida case. Journal of travel research, 33(3), 21-27.
Indexed at, Google Scholar, Cross Ref
Mishra, A., & Satish, S.M. (2016). eWOM: Extant research review and future research avenues. Vikalpa, 41(3), 222-233.
Indexed at, Google Scholar, Cross Ref
Morales, A.J. (2003). Absolutely expedient imitative behavior. International Journal of Game Theory, 31(4), 475-492.
Moore, W.L., & Lehmann, D.R. (1980). Individual differences in search behavior for a nondurable. Journal of consumer research, 7(3), 296-307.
Indexed at, Google Scholar, Cross Ref
Murray, K.B. (1991). A test of services marketing theory: consumer information acquisition activities. Journal of marketing, 55(1), 10-25.
Indexed at, Google Scholar, Cross Ref
Murtha, B.R., Bharadwaj, S.G., & Van den Bulte, C. (2014). Interlocking Networks: How and When Do Connections Between Buying and Selling Teams Affect Customer Solutions?. MSI Report, 14.
Newman, J.W., & Staelin, R. (1972). Prepurchase information seeking for new cars and major household appliances. Journal of Marketing Research, 9(3), 249-257.
Indexed at, Google Scholar, Cross Ref
Newman, J.W. (1977). Consumer external search: Amount and determinants. Consumer and industrial buying behavior, 79-94.
Olshavsky, R.W., & Granbois, D.H. (1979). Consumer decision making—fact or fiction?. Journal of consumer research, 6(2), 93-100.
Indexed at, Google Scholar, Cross Ref
Panagopoulos, N.G., Rapp, A.A., & Ogilvie, J.L. (2017). Salesperson solution involvement and sales performance: The contingent role of supplier firm and customer–supplier relationship characteristics. Journal of Marketing, 81(4), 144-164.
Indexed at, Google Scholar, Cross Ref
Petty, R.E., Cacioppo, J.T., & Schumann, D. (1983). Central and peripheral routes to advertising effectiveness: The moderating role of involvement. Journal of consumer research, 10(2), 135-146.
Indexed at, Google Scholar, Cross Ref
Price, L.L., & Feick, L.F. (1984). The role of interpersonal sources in external search: An informational perspective. ACR North American Advances.
Swartz, T.A., & Stephens, N. (1983). Marketing professional services: the case of the physician. In Proceedings of the 1983 Convention of the American Academy of Advertising (pp. 78-82). Lawrence, KS: American Academy of Advertising.
Tuli, K.R., Kohli, A.K., & Bharadwaj, S. G. (2007). Rethinking customer solutions: From product bundles to relational processes. Journal of marketing, 71(3), 1-17.
Indexed at, Google Scholar, Cross Ref
sWallendorf, M. (2001). Literally literacy. Journal of Consumer Research, 27(4), 505-511.,