ARTICLES

 

Determinants of the purchase influence of online consumer-generated reviews amongst Generation Y students in South Africa: Application of the information adoption theory

 

 

Ayesha Lian Bevan-Dye

School of Management Sciences, North-West University, South Africa. Email: aveshabevandve@gmail.com; ORCID: https://orcid.org/0000-0003-2146-4763

 

 

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ABSTRACT

PURPOSE OF THE STUDY: Online consumer reviews have significantly enhanced consumer decision-making and are a particularly popular purchasing decision-making aid amongst the young adult consumer segment, currently classified as members of Generation Y. Despite the significance of such reviews in Generation Y consumer behaviour, there is a dearth of studies on the purchase influence of online consumer reviews amongst this segment, especially in the context of emerging economies such as South Africa. In addressing this limitation in the literature, this study applied an adapted version of the information adoption model to test the influence of perceived information quality, trustworthiness and usefulness on the purchase influence of such reviews amongst Generation Y university students in South Africa
DESIGN/METHODOLOGY/APPROACH: Following a single cross-sectional descriptive research design, data were collected from a sample of 538 university students from the campuses of three South African public universities. Data analysis included structural equation modelling
FINDINGS: The results infer that Generation Y students in South Africa perceive online consumer-generated reviews and the information contained therein as being trustworthy, of a high quality, as useful and they have adopted such reviews into their consumption-related decision-making in that those reviews influence their purchase decisions. Furthermore, information trustworthiness and quality explain 51 percent of the variance in their perceived usefulness of online consumer reviews and perceived usefulness, together with its predictors, explain 32 percent of the variance in their adoption of such reviews into their purchase decision-making processes
RECOMMENDATIONS/VALUE: These findings augment managerial understanding of the role of online consumer reviews in South African Generation Y consumers' purchasing decision-making
MANAGERIAL IMPLICATIONS: These findings highlight the degree to which Generation Y consumers have integrated consumer-generated online reviews into their consumption-related decision-making and the extent to which those reviews exert an influence their purchase behaviour, thereby highlighting the necessity of incorporating such reviews into managerial strategies targeting Generation Y consumers in South Africa
JEL CLASSIFICATION: M31

Keywords: Information adoption model, online consumer reviews, Generation Y consumers, model validation, path analysis, South Africa

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1. INTRODUCTION

Online consumer reviews are a digital form of word-of-mouth communication using text, images, texts and images or videos, whereby user-generated product and/or service evaluations are digitally uploaded to an organisation or third-party review website (Diwanji & Cortese, 2021). Members of the young adult consumer market, currently called Generation Y (individuals born between 1986 and 2005) (Markert, 2004), are both leading users of and contributors to these online review sites (Hall, 2018; Kats 2018). Generation Y consumers represents an attractive market segment across a range of retail sectors, making up the largest portion of the global population (Neufeld, 2021) and are forecasted to have a spending power outpacing that of any previous generational segment (Tilford, 2018). Similarly, in South Africa individuals delineated as being part of Generation Y account for a sizable portion of the population, making up an estimated 34 percent of the country's population in 2022 (Statistics South Africa, 2022).

The sociology-based field of generational studies proposes that shared life experiences, dominating social trends and historical occurrences experienced during a person's formative years synthesise into a collective generational consciousness that differentiates members of one generation's perceptions, attitudes, values and behaviour (Howe & Strauss, 2007), including consumer behaviour (Schewe & Meredith, 2004) from that of other generations. From a business management perspective, the single most important shared life experience to have shaped the persona of Generation Y individuals is their digital astuteness stemming from growing up in the digital age (Deloitte Global, 2021), which they harness to enhance their consumption-related decision-making (Ordun, 2015; Jain & Pant, 2016; Indahingwati et al., 2019; Fairlie, 2022).

Digital technologies enable consumers to enhance each stage of the typical consumer decision-making process, from the initial search for consumption-related information, to evaluating alternative product and service features and prices, using the product or service on a trial basis in the case of certain product categories, to purchasing and paying online, right through to providing them with a platform to express their post-purchase sentiments (Faulds et al., 2018). Online consumer-generated reviews are an important contributor to the enhancement of the consumer decision-making process in that they allow consumers to share first-hand product/service experiences with a wide range of fellow consumers, thereby facilitating each other's decision-making processes (Kaemingk, 2020; Guo et al., 2022; Perez et al., 2022). More so than members of previous generations, Generation Y individuals are keenly aware the consumer power that digital technologies afford them and typically research potential purchases online, even when purchasing in-store (Drenik, 2019) and rarely make a purchase decision without first perusing online consumer reviews (KPMG, 2017; Hall, 2018; Kats, 2018; Fairlie, 2022).

Although it is widely accepted that Generation Y consumers frequently consult consumer-generated online product reviews prior to making a purchase decision (KPMG, 2017; Hall, 2018; Kats, 2018; Fairlie, 2022), there is only limited empirical research on the purchase influence of these reviews; that is, the extent to which they adopt online consumer reviews into their consumption-related decision-making process (Abedi et al., 2020). This dearth of literature on the topic is particularly notable in the South African market where despite ecommerce growing by 66 percent from 2020 to 2021 (Kibuacha, 2021) and projected to reach US$8.46 billion in 2022 (Statista, 2022), still only accounts for 2 percent of the country's total retail spend, compared to the global average of 16 percent (Daniel, 2020). Furthermore, while one study found that South African consumers are as willing and likely, sometimes even more likely to share their positive online shopping experiences as their negative experiences with others, online retail managers in the country are failing to monitor online consumer reviews adequately and still seem to be grappling with integrating such reviews into their business strategy (Ahlfeldt, 2020). Understanding the purchase influence of online reviews amongst Generation Y consumers, together with the antecedents of that influence will contribute to online retail managers' ability to leverage such reviews to their advantage when targeting this consumer segment.

In order to address this limitation in the management literature and shortfall in South African online retail management practices, the primary purpose of this article is to outline the findings of a study that sought to evaluate an adapted version of the information adoption model proposed by Sussman and Siegal (2003) as a measure of the purchase influence of online consumer reviews, and to ascertain the influence of perceived information quality, trustworthiness and usefulness on the purchase influence of such reviews amongst Generation Y university students in South Africa. The focus on a university target population was intentional, based on the notion that, generally, a graduate qualification is associated with a higher earning potential and social standing within a society, making university students exemplars amongst their peers (Bevan-Dye & Akpojivi, 2016). Target populations involving tertiary undergraduate students are typically delineated as including registered students from 18 to 24 years old (Meyer et al., 2020; Dalziel & De Klerk, 2021; van Deventer, 2021), which currently also makes university bachelor degree/diploma students an ideal microcosm for studying the consumption-related behaviour of adult Generation Y individuals (Kim & Hahn, 2012).

 

2. LITERATURE REVIEW

Sussman and Siegal (2003) developed the information adoption model in an effort to explain individuals' adoption of advice in digitally-mediated contexts. Given that in essence consumer-generated online reviews involve providing consumption-related advice in the digitally-mediated environment of the Web, the information adoption model manifests as an ideal theory for understanding the adoption of such reviews into recipients' consumption-related behaviour (Salehi-Esfahani et al., 2016). Sussman and Siegal's (2003) conceptualisation of the information adoption model was based on two theories, namely the elaboration likelihood model developed by Petty and Cacioppo (1986) and the technology acceptance model developed by Davis (1986) and adapted by Davis et al. (1989).

According to Petty and Cacioppo's (1986) elaboration likelihood model, information recipients may be influenced by a message via two routes, namely the central route or the peripheral route, where the central route relates to the core of the message, while the peripheral route relates to the issues that are indirectly related to core of the message. In terms of the technology acceptance model, people's intentions to use a particular technological system is influenced by their overall feelings or attitude towards that system, which, in turn, is influenced by their subjective perceptions that using the system will enhance their performance in carrying out tasks (Davis et al., 1989).

Published studies have applied versions of the information adoption model to explain information recipients' behaviour in a range of contexts and across a range of digital platforms, including the persuasiveness of social media travel influencers (Nadlifatin et al., 2022), travel destination selection and YouTube (Arora & Lata, 2020), electronic word-of-mouth and consumer-to-consumer ecommerce platforms (Bueno & Gallego, 2021), restaurant selection and information websites (Salehi-Esfahani et al., 2016) and electronic word-of-mouth and social media websites (Erkan & Evans, 2016a).

The information adoption model includes the four dimensions of source credibility, information usefulness, argument/information quality and information adoption, where attitude towards the information in the form of an assessment of its usefulness mediates the influence of argument quality and source trustworthiness on information adoption (Sussman & Siegal, 2003).

2.1 Information trustworthiness

Source credibility relates to the peripheral route of persuasion (Sussman & Siegal, 2003; Abedi et al., 2020) and, in the case of online consumer reviews, is associated with the trustworthiness of the information contained in the review (Cheung et al., 2012; Tien et al., 2019; Hsu, 2022). Information trustworthiness refers to the credibility of the content in the review and, therefore, indirectly relates to the core of the message (Petty & Cacioppo, 1986; Sussman & Siegal, 2003) but is, nonetheless, crucial to the persuasion process (Tien et al., 2019; Hsu, 2022). The trustworthiness of consumer-generated product reviews differs substantially between traditional word-of-mouth and electronic word-of-mouth communication (Moran & Muzellec, 2017). Traditional word-of-mouth communication occurs between acquainted individuals, which contributes to its inherent credibility and makes it the most persuasive form of consumption-related advice (Cheung et al., 2009; Abedi et al., 2020). However, online consumer reviews are often posted anonymously (Erkan & Evans, 2016a; Abedi et al., 2020), which may lead to a lack of personal accountability, as well as identity deception issues (Song et al., 2021). Online review site administrators are advised to only allow reviews from authenticated purchasers and/or to develop and employ software tools using machine learning approaches based on content- and behaviour-based spam filtering to identify and route out fraudulent reviews (Zelenka et al., 2021).

2.2 Information usefulness

Information usefulness, which Sussman and Siegal (2003) explain in terms of the value, usefulness and helpfulness of information, is in essence an attitudinal dimension in that it seeks to capture individuals' overall evaluative feelings towards the information (Fishbein & Ajzen, 1975). It relates to the perceived usefulness dimension of Davis' (1986) technology acceptance model in that it too considers how, in this case, information can enhance task-related performance; that is, the subjective assessment of its value. For information in online consumer reviews to be deemed as being helpful, of value and useful, receivers need to believe that it will enhance their ability to make a satisfactory consumption-related purchase decision and mitigate potential post-purchase cognitive dissonance (Liu et al., 2021). It is the extent to which the review recipients perceive the content of the review as facilitating their purchase decision by making them smarter shoppers (Park & Lee, 2009). According to the information adoption model, the perceived usefulness of information forecasts the likelihood of that information being adopted by the message recipient, which, in turn, depends on the perceived quality of the information and the extent to which it is perceived as being trustworthy (Sussman & Siegal, 2003).

2.3 Information quality

Information quality refers to the core of the message or the task-related advice and, hence, relates to the central route of persuasion in terms of the elaboration likelihood model (Petty & Cacioppo, 1986; Sussman & Siegal, 2003). The information quality is the effectiveness of the meaning embedded in a message (Erkan & Evans, 2016b) and predicts the extent of the message's informational influence (Petty & Cacioppo, 1986). In relation to e-mail messages, Sussman and Siegal (2003) conceptualise information quality as the completeness, accuracy and consistency of the message's information. In terms of online reviews, Zhang et al. (2014) and Tien et al. (2019) operationalise information quality as the extent to which the reviews provide relevant, complete and timely product information. Another salient facet of information quality is its currency, where up-to-date product information is likely to be an essential contributor to the perceived quality of the information contained in the review (Khwaja et al., 2020; Lata & Rana, 2021). The required currency of the information provided emphasises the significance of encouraging a constant stream of up-to-date reviews (Rose, 2017) using mechanisms such as automated emails sent out requesting a review immediately following a purchase, running competitions where prizes are offered to customers that post a review or incentivising reviews with a badge system, where a greater number of reviews by an individual earns a higher badge status (Millwood, 2018). While online retailers clearly cannot control the information quality of consumer-generated online reviews, they are advised to supply a review template with sections covering usage situation, functionality, performance, aesthetics, positive assessments and negative assessments in order to encourage review content that is more relevant and complete (Cheung et al., 2009). Furthermore, ensuring that online consumer-generated reviews can be conveniently and easily located and accessed, whether from a computer or a mobile device, will serve to improve the timeliness of the information (Erkan & Evans, 2016b).

2.4 Information adoption

Information adoption pertains to the recipients' inclination to act on the information received (Erkan & Evans, 2016a), which in the case of online consumer reviews may be viewed as the extent to which individuals internalise such information into their consumption-related decision making; that is, the purchase influence of online consumer reviews (Park & Lee, 2009). Sussman and Siegal (2003) indicate that information adoption is largely dependent on the receivers' perceived usefulness of that information, which is their affective attitude towards that information. They add that the quality of the information received, together with its trustworthiness act as precursors of recipients' attitude towards that information. These findings are confirmed by several empirical studies, including Erkan and Evans (2016a), Erkan and Evans (2016b), Tien et al. (2019), Arora and Lata (2020), Lata and Rana (2021) and Song et al. (2021).

 

3. METHODOLOGY

The study adhered to the descriptive research design and employed a single cross-sectional sampling approach.

3.1 Sampling and questionnaire administration

The population targeted for data collection in this study was defined as Generation Y university students registered at South African public universities, aged between 18 and 24 years. The sampling frame included public university campuses situated in South Africa's Gauteng province, whereby judgement sampling was used to ensure that the sample included students from a campus from a traditional university, a campus from a university of technology and a campus from a comprehensive university. Fieldworkers distributed 600 self-administered questionnaires equally to a convenience sample of students at each of these three campuses who, when approached, volunteered to participate in the study.

3.2 Research instrument

The survey questionnaire utilised in the study included a cover letter, a section requesting respondents' demographic information and a section comprising the scaled-response items, which were adapted from published studies. The perceived trustworthiness of online reviews was measured using a scale developed by Ohanian (1990) and comprised five items, namely online consumer reviews are "dependable", "honest", "reliable", "sincere" and "trustworthy". Perceived usefulness of online reviews was measured using the three items of online consumer reviews are "useful", "valuable" and "important" that were adapted from a scale developed by Ducoffe (1996). The information quality dimension was operationalised using three items from the scale developed by Zhang et al. (2014), namely online consumer reviews "supply relevant product information", "provide timely information" and "supply complete information", plus a fourth item from the Ducoffe (1996) scale, namely online consumer reviews "are a good source of up-to-date product information". The purchase influence dimension representing information adoption was measured using the three items from the Park and Lee (2009) study, which included "I am influenced by online consumer reviews when I choose a product", "I rely on online consumer reviews when I purchase a product" and "Online reviews crucially affect my choice of product". A six-point Likert-type scale, ranging from strongly disagree (1) to strongly agree (6) was used to measure responses to these 15 scaled items.

3.3 Data analysis

The survey data were captured and analysed using Versions 27 of IBM's Statistical Package for Social Sciences (SPSS) and Analysis of Moment Structures (AMOS) for the structural equation modelling. Statistical analysis included descriptive statistics, a one-sample t-test, Pearson's product-moment correlation for nomological validity analysis, collinearity diagnostics, confirmatory factor analysis using the maximum likelihood method, internal-consistency and composite reliability analysis, together with convergent and discriminant validity analysis, and model fit assessment, and path analysis, again using the maximum likelihood method.

Descriptive statistics analysis encompassed the computation of the means and standard deviations. For the one-sample t-test, the expected mean was set at 3.5, as what is applicable for responses recorded on a six-point scale. The nomological validity of a measurement model requires statistically significant correlation coefficients in the direction that corresponds with the underlying theory between each of the pairs of latent factors planned for inclusion in a model (Hair et al., 2018). An absence of serious multi-collinearity issues in a proposed measurement model requires tolerance values above 0.10 and an average variance inflation factors (VIF) below 10 (Pallant, 2020).

For confirmatory factor analysis of the measurement model, four-factor model was specified, whereby the first loading on each of the four latent factors was fixed at 1.0. This resulted in an over-identified model with 135 distinct sample moments and 51 distinct parameters to be estimated, which equates to 84 degrees of freedom (df) based on a chi-square value of 195.466, with a probability level equal to 0.000. Given the chi-square value's known vulnerable to large sample sizes (Byrne, 2016), other model fit induces were applied to assess fit, which included the normed fit index (NFI), the incremental-fit index (IFI), the Tucker-Lewis index (TLI), the comparative-fit index (CFI), the standardised root mean square residual (SRMR) and the root mean square error of approximation (RMSEA). In terms of the fit indices, NFI, IFI, TLI and CFI values above 0.90, and SRMR and RMSEA values below 0.08 suggest acceptable model fit (Malhotra, 2020).

Internal-consistency reliability and composite reliability (CR) require a Cronbach's alpha (a) and CR value of 0.70 and above (Malhotra, 2020; Hair et al., 2018), convergent validity requires latent factor loading estimates and average variance extracted (AVE) values of 0.50 or above and discriminant validity requires the square root of those AVE values (VAVE) to exceed the correlation coefficient estimates between the relevant factors (Fornell & Larcker, 1981). As advised by Franke and Sarstedt (2019), discriminant validity was also tested by applying the relatively recent measure proposed by Henseler et al. (2015), namely the heterotrait-monotrait (HTMT) ratio of correlations parameter. With this measure, HTMT value below 0.85 between each of the pairs of latent factors in a measurement model is recommended to conclude discriminant validity (Voorhees et al., 2016). The level of statistical significance was set at p < 0.01 throughout.

 

4. FINDINGS

Fieldwork at the three campuses yielded 538 complete questionnaires, representing a 90 percent response rate. The sample description is outlined in Table 1. Sample descriptors included gender, age, province of origin, language and institution, which included students from a campus of a traditional university (A), a university of technology (B) and a comprehensive university (C).

The demographic information provided in Table 1 indicates that the sample respondents fit with the target population definition. The sample comprised male (52%) and female (47%) participants from each of the seven age categories specified, with the majority of participants falling into the 18- and 19-year old age category (49%). There was a relatively even spread of respondents between the three main types of public universities, with 181 from the traditional university (A) (34%), 170 from the university of technology (B) (32%) and 187 from the comprehensive university (C) (35%) campuses. Furthermore, each of South Africa's nine provinces and 11 official language groups were representative in the sample.

In order to determine the extent to which Generation Y students perceive the information in consumer-generated online reviews as being trustworthy, of a high quality and as useful, and whether they adopt such information into their consumption-related decision making, descriptive statistics, namely the means and standard deviations, together with a one-sample t-test were computed. The means, standard deviations, t-values and p-values for the four latent factors are reported on in Table 2.

As shown in Table 2, the means of the responses recorded on the six-point Likert-type scale were all statistically significant (p < 0.01). These results suggest that Generation Y students in South Africa are influenced by online consumer reviews in that they have adopted them into their consumer behaviour. The highest means were returned for information usefulness (mean = 4.47), information quality (mean = 4.19) and online review adoption (mean = 3.82). While still significantly (p < 0.01) in the agreement area of the scale, a lower mean was recorded for perceived information trustworthiness (mean = 3.60). This is somewhat concerning given the importance of trustworthiness in the information adoption theory.

The measurement model specified for confirmatory factor testing in this study was that Generation Y students' online consumer review adoption is a four-factor model that includes the latent factors of online consumer reviews' perceived trustworthiness, usefulness, quality and adoption. Confirmatory factor analysis was preceded by the construction of a matrix of Pearson's Product-Moment correlation coefficients to test for nomological validity, together with collinearity diagnostics to check for any concerning multi-collinearity issues. The computed correlation coefficients, tolerance values and VIF values are reported in Table 3.

The correlation coefficients reported in Table 3 indicate statistically significant (p < 0.01) positive associations between each of the pairs of latent factors planned for inclusion in the online consumer review adoption measurement model, thus inferring the model's nomological validity. The computed tolerance values, which ranged from 0.610 to 0.743 and the average VIF of 1.50 indicate that there are no serious multi-collinearity issues.

A confirmatory factor analysis of the measurement model was then undertaken using AMOS. Table 4 outlines the computed estimates for the measurement model, including the standardised loading estimates, squared multiple correlation estimates (R²), Cronbach alphas (a), CR, AVE and VAVE values.

The estimates for the measurement model set out in Table 4 indicate that all Cronbach alpha and CR values are above 0.70, thus indicating internal-consistency and composite reliability. In terms of the convergent validity, while the CR values were all above 0.7 and the standardised factor loading estimates all above 0.50, AVE values equal to or greater than 0.50 were only computed for three of the four latent factors. An undesirably low AVE value of 0.375 was computed for the information quality latent factor. Given the salience of this factor to the information adoption theory and the fact that the AVE is known to be a particularly stringent measure of convergent validity (Malhotra, 2020), alternative measures of convergent validity were undertaken in the form of assessing the factor's average inter-item correlation value and the corrected item-total correlation values of its items. All of the corrected item-total correlation values exceeded the recommended level of 0.30 (Pallant, 2020), ranging from 0.462 to 0.527 and the computed average inter-item correlation value of 0.376 falls well within the recommended range of 0.20 to 0.40 (Briggs & Cheek, 1986). Furthermore, deletion of any of the items would have resulted in a decrease rather than increase in the factor's Cronbach alpha value. As such, following the advice of Malhotra (2020) and in light of the CR value, standardised factor loading estimates, corrected item-total correlation values and average inter-item value all suggesting sufficient correlation between the items representing the factor, the information quality latent factor was retained, and its convergent validity cautiously concluded.

With the VAVE values of each of the factors exceeding their relevant correlation coefficients there was evidence of discriminant validity according to the Fornell and Larcker (1981) measure. The additional assessment of the discriminant validity of the measurement model based on the HTMT ratio values is reported in Table 5.

The HTMT ratio values reported in Table 5 are all below 0.85, with the highest value of 0.647 being between perceived information trustworthiness and perceived information quality, which, according to Voorhees et al. (2016), provides additional evidence of discriminant validity.

Having established the reliability and construct validity of the model, the model fit indices computed by AMOS were then assessed. The computed model fit indices all suggested good model fit with a NFI of 0.942, an IFI of 0.966, a TLI of 0.957, a CFI of 0.966, a SRMR of 0.046 and a RMSEA of 0.050. Based on the above findings, this study asserts that consumer-generated online review adoption by Generation Y students is a four-factor measurement model that exhibits the psychometric properties of construct validity, reliability and good model fit.

Based on the literature reviewed pertaining to the information adoption theory, a structural model was specified to test the theorised paths that Generation Y students' perception of the trustworthiness and quality of information in online consumer reviews predicts their perceived usefulness of such reviews, and that the perceived usefulness of those reviews predicts their adoption of such reviews into their consumption-related decision making. The specified structural model is illustrated in Figure 1.

In terms of the model fit indices, a SRMRl (0.055) and the RMSEA (0.053) below 0.08, and a NFI (0.936), an IFI (0.960), a TLI (0.951) and a CFI (0.960) above 0.90, the structural model in Figure 1 exhibited good model fit (Malhotra, 2020). Table 6 outlines the un-standardised and standardised regression coefficients, standard error estimates and p-values estimated by AMOS for the structural model.

The estimates in Table 6 indicate that all of the regression paths tested were positive and statistically significant (p < 0.01). The standardised regression estimates indicate that perceived information trustworthiness (β = 0.44, p < 0.01) and perceived information quality (P = 0.35, p < 0.01) are statistically significant predictors of Generation Y students' perceived usefulness of consumer-generated online reviews, and with a squared multiple correlation coefficient (SMC) of 0.505 explain 51 percent of the variance in Generation Y students' perceived usefulness of online consumer reviews. Perceived usefulness (β = 0.56, p < 0.01), in turn, is a statistically significant predictor of Generation Y students' adoption of online consumer reviews and, together with its predictors, explain 32 percent of the variance in the purchase influence of those reviews on their consumption-related decisions.

 

5. DISCUSSION AND CONCLUSION

This study sought to determine the extent to which Generation Y university students in South Africa view online consumer-generated reviews to be trustworthy, as offering quality information, as being useful and as influencing their purchase decisions, as well as the extent to which that trustworthiness, information quality and usefulness influence their adoption of those reviews into their consumption-related decision-making.

The means and one sample t-test results computed indicate that Generation Y students in South Africa perceive the information contained in consumer-generated online reviews as being trustworthy, of a high quality and as useful, and that they adopt such information into their consumption-related decision making in that these reviews exert an influence on their decision to purchase or not, and their choice of product. These findings suggest that it is essential that online retailers actively encourage customers to post reviews on their site or on a third-party review site when targeting Generation Y consumers. While all mean values were statistically significant (p < 0.01), a slightly lower value was recorded on the information trustworthiness dimension, suggesting that online retailers should preferably only allow verified product/service purchasers to post reviews on their site. They should also monitor relevant reviews on third-party sites and report any suspected fraudulent reviews to the site administrators.

The CFA conducted on the 15 scaled-response items of the measurement model concluded that online consumer product review information adoption amongst Generation Y university students in South Africa is a four-factor model. This model exhibited internal-consistency and composite reliability, good model fit, nomological and discriminant validity. Despite an undesirably low AVE computed on the information quality factor, following further investigation it was deemed tenable to conclude convergent validly each of the four latent factors.

The results of the path analysis infer that the perceived trustworthiness and the quality of information contained in online consumer-generated reviews are statistically significant positive predictors of Generation Y students' affective evaluation of the usefulness of such reviews. Their perceived usefulness of such reviews, in turn, predicts the purchase influence of those reviews on their consumption-related decisions.

Theoretically, this study augments the literature on Generation Y consumers' consumption-related behaviour in the digital age by applying the information adoption model to explain the role that online consumer-generated product reviews play in their consumption decision-making. Furthermore, it theoretically contributes to comprehension of this generation's use of online consumer-generated product reviews in the emerging economy of South Africa, where the strategic use of such reviews is still in its infancy.

Practically, the study's findings highlight the need for South African online retailers to grasp the opportunity of actively encouraging such reviews when targeting Generation Y consumers. This is particularly true for smaller-sized online retailers who may need to rely on the testament of previous customers to build trust in their site amongst potential consumers. In South Africa, ecommerce spending as a percentage of total retail spend still lags behind that experienced globally. Employing a strategy to energise satisfied customers to post informative and trustworthy product reviews is key to stimulating the growth of ecommerce in the both South Africa and other emerging economies. Applying the lens of the information adoption theory employed in the study, it is essential to not only encourage the posting of online reviews but also to ensure that such reviews are trustworthy and informative in order to foster positive attitudes towards them and, ultimately, encourage product purchase. Strategic tactics may include actively asking customers to post reviews using post-purchase automated emails or incentivising reviewers with competitions or a badge system, providing a review template and only allowing verified purchasers to post reviews, as well as monitoring third-party review sites.

 

6. LIMITATIONS AND FUTURE RESEARCH PROSPECTS

When interpreting the findings reported in this article, there are certain caveats that should be observed. The first being the sampling technique used to collect the required data from the target population. Advancements in the regulations governing personal data protection both internationally and in South Africa have hampered the collection of marketing research data (Martin & Murphy, 2017) and have made access to complete sampling frames of potential sample participants progressively more difficult, meaning that the opportunity of employing probability sampling techniques is increasingly rare. Given this difficulty, it was necessary to utilise the non-probability sampling technique of convenience sampling for this study, which has the limitation of decreasing the generalisability of the sample evidence to the target population. A second caveat is that the study was cross-sectional in design, providing only a snapshot in time. Given the dynamic nature of digital platforms, ongoing research into the extent to which online consumer reviews exert an influence on the purchasing behaviour of Generation Y students in South Africa is advisable. Another potential caveat to the study is that it did not delve into the specific aspects of online consumer reviews that increase their information quality and trustworthiness amongst Generation Y consumers in South Africa. Research into specific facets of online consumer reviews that Generation Y consumer' perceive as being credible and informative offers an interesting and valuable future avenue for investigation. A last potential caveat is that the study did not consider the negative online review scenario. Future research into the perceived trustworthiness and information quality of negative online consumer-generated reviews, together with the influence thereof on Generation Y consumers' perceived usefulness and adoption of such reviews will, without a doubt, be valuable as it will contribute to developing relevant strategies to mitigate the harmful effects of negative reviews to South African online retailers.

 

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