Impact of electronic word-of-mouth metrics on service provider choice moderated by organizational image: Insights from Zimbabwean polytechnics

Prospective Polytechnic marketing management students experience challenges as they make decisions on which institution to enrol with. While making a decision, impact of consistent use of electronic word-of-mouth from institutions become evident in their ability to determine Polytechnic image, choice and subsequently, levels of enrolment. This article depicts the impact of electronic word-of-mouth metrics on training service provider choice, moderated by insights in organisational image from eight Polytechnics in Zimbabwe. Quantitative data were gathered from a sample of 217 respondents using a structured questionnaire in Likert format. The same data were analysed using WarpPLS software in Structural Equation Modelling. A sample of 12 was used to collect qualitative data which were analysed through Thematic Analysis in Nvivo 11. Findings were that volume of electronic word-of-mouth had insignificant positive influence on Polytechnic image while positive electronic word-of-mouth (eWOM) valence enhanced positive Polytechnic image. eWOM variability had a positive correlation with the transformation of old organisational images to new ones. Finally, positive organizational image positively impacted enrolment. Conclusively, the number of eWOM posts had an insignificant impact on Polytechnic image development; which did not concur with the theory of eWOM volume. Positive valence and variability enhanced positive Polytechnic image which ultimately improved enrolment.


Introduction
With the current developments in information and communication technology, electronic word-of-mouth (eWOM) has become a not-to-ignore marketing communication strategy in developing and maintaining organisational image and influence service provider choice.Traditional word-of-mouth gave birth to electronic word-of-mouth which was, and is still being driven by digital technologies today.Ismagilova et al. (2017, p. 29), argue that, "Enhancement of the Internet, popularity of e-commerce, and widespread diffusion of social media applications led to the emergence of electronic word-of-mouth".Jalilvand et al. (2011) contend in the same vein, that, online communication technologies have spread information power to Business to Consumer from Consumer to Consumer through sharing of life changing information and opinions.eWOM is therefore, a social influence which is supplier-generated or consumer-generated and is a powerful force in the contemporary marketing of goods and services either for profit or civil service (Liu et al. 2024;Montazemi & Saremi, 2014).With the new developments in communications technologies, eWOM is inevitable.Some organisations initiate it while others do not and seem not to value it any much.There are organisations, especially in developing economies, which seem not to understand and value the impact of eWOM metrics on organisational image and consumer purchase behaviour.Institutions such as Polytechnics do not treat their stakeholders with enough care yet they are the ambassadors of the institution.eWOM in general strongly influence purchase behaviour (service provider choice) (Ghouri et al., 2020;Filieri et al., 2018).This may be an indication of a serious communication challenge since the organisation seems not to be aware of what works best for it in terms of eWOM.Volume, valence, and variability are some of the metrics that are used to measure the performance of eWOM in marketing communications management.Few published studies on these metrics focused on valence (Park & Lee, 2009), message volume and valence (Park & Kim, 2008), volume (Park & Lee, 2008) but, in the goods industry.Therefore, there is a notable paucity of studies on electronic word-of-mouth metrics in the services industry.The purpose of this study was to analyse the impact of volume, valence, and variability of electronic word-of-mouth on Polytechnic image and the ultimate choice of Polytechnics for training by prospective students.The contribution of this study is evident and obvious since the outcomes on eWOM metrics will act as valuable guidelines for Polytechnics management teams in their endeavour to improve their electronic word-of-mouth approaches, organisational images and ultimately improve enrolment levels.

Electronic Word-of-mouth
Electronic word-of-mouth is, "…the dynamic and ongoing information exchange process between potential, actual, or former consumers regarding a product, service, brand, or company, which is available to a multitude of people and institutions via the Internet" (Ismagilova, et al. 2017, p. 18).Another definition of eWOM is given by Kietzmann and Canhoto (2013, p. 39) as, "…any statement based on positive, neutral, or negative experiences made by potential, actual, or former consumers about a product, service, brand, or company, which is made available to a multitude of people and institutions via the Internet (through websites, social networks, instant messengers, news feeds, etc.)".Both definitions emphasize on the consumption qualifications of the eWOM participants, that is, potential, actual, and former consumers.The two studies also focus on the size of the group of people reached through electronic word-of-mouth via the internet.Ismagilova et al. (2017) and Kumar (2023) noted that this process of online sharing product or service information is dynamic and continuous, while Kietzmann and Canhoto (2013) are silent about that but pointing on the nature of consumer experiences (whether positive, neutral, or negative).Consumers can share electronically whatever product/service or organisational information they have and that can guide their organisational images and choice of organisations to engage with for service provision (Liu et al., 2024).

Electronic Word-of-Mouth Volume
As an organization provides its services, consumers share information, opinions, and observations about the organization and the services quality through digital media.The number of the posted messages is the eWOM volume (Abd-Elaziz et al., 2015).This has an impact on the image of the organization and consumer choice of service providers.The number of eWOM messages in circulation or going viral is an indication of the popularity of the service or organization providing the service (Ismagilova et al., 2020).Previous studies found out that eWOM volume positively influences organizational image in the context of sales (Rosario, 2018) and intention to buy (Ismagilova et al., 2020).Adjei et al. (2010, p. 639) define valence as "…the extent to which the information exchanged reflects positively or negatively on the product in question".Hence, valence exposes a consumer's feelings and perceptions (Majeed et al., 2023) about a Polytechnic's services which may in turn influence choice of a Polytechnic to train with.Whether, the shared consumer opinions are positive or negative is also influenced by the nature of the source of the eWOM, that is, whether it is from an interested or a neutral source (Rosario et al., 2016;Adjei et al., 2010).Neutral eWOM platforms are usually preferred by consumers since they seem not to be biased.In this instance, all Polytechnic websites in Zimbabwe are non-commercial and controlled by the government, therefore, to consumers they may sound biased since they may not be able to say it as it is where they cannot offer the best service.Additionally, the Polytechnics compete for students among themselves, so, positive communication is essential for the Polytechnics.Abd-Elaziz et al. (2015) found out that positive valence strongly encouraged online consumers to make more internet purchases.Similarly, in the hotel industry Mauri and Minazzi (2013) discovered that positive eWOM reviews had a notable incremental influence on the number of bookings.However, negative valence was found to be more influential when the product or service is expensive.

Electronic Word-of-Mouth Variability
Even though variability in electronic word-of-mouth was not studied by many researchers, Rosario et al. (2016) views the concept as consumer disagreements about the quality of a product.The disagreements enhance consumer understanding of the product as they share their experiences and feelings.Hence, in the same study Rosario et al. (2016) argued that variability reduces sales; which are viewed as enrolment levels in this study.Polytechnic prospects are rational beings, so the positive and negative consumer reviews might have the potential to both enhance and suppress enrolment figures.

Organisational Image
Lievens (2017) views organizational image as people's overall impressions of an organization, that is, people's knowledge, beliefs, and perceptions about an organization.Similarly, Putro (2016) contends that organisational image is a general impression of the customer's mind created as a sum total of the interaction of ideas, feelings, and attitudes as the customer experience the use of the purchased product/service or enjoys after sale services.However, some people can have an organisational image through electronic word of mouth, without purchasing a service from the organisation.Frandsen (2017) refer to organizational image as the impression of an organization that exists among both external stakeholders and organizational staff members as construed external images and desired images.That is, an organisation creates an image in the minds of its publics which it expects the publics to adopt.This is done through marketing communications techniques and customer care.The organisation's stakeholders may be viewing the organisation from the same perspective or may be holding a different image depending on their expectations.Organizational image gives the final picture of the customers, investors, applicants and employees' cognitive reactions and associations to an organization's name (Lievens, 2017).Lievens (2017) further argues that organizational image serves as a guide for the classification of the institution and remembrance of organisation related information leading to final consumer choice of the supplier.Viewing it from the angle of an individual, organizational image helps to explain how individuals: (1) want to be associated with the organizations, (2) identify with organizations, (3) try to understand and compare organizations, (4) align their decisions and behaviour with others serving the same organizational cause, and (5) want to position themselves in relation to the organisations (Carroll, 2008).
Taking it from an organisational view, organisational image positions the institution in the minds of customers, employees, investors and many other stakeholders (Carroll, 2008).Hamidizadeh et al. (2016) studied the effect of electronic word of-mouth on destination image of tourists and tourist intention and found out that word-of-mouth from friends and family members is an essential factor in image formation.Additionally, Beerli and Martin (2004a) contend that electronic word-of-mouth is the most credulous and worth-trusting means of communication that has a considerably high influence on cognitive image.In light of Polytechnic image, the formed image significantly influences the choice (Maru & Vijay, 2024) of a Polytechnic to train with in the tertiary education in Zimbabwe.

Conceptual Model
Figure 1 shows the conceptual framework of the study.Electronic word-of-mouth volume and electronic word-of-mouth valence are eWOM dimensions which carry ideas, beliefs, and opinions which influence consumer perceptions and organizational image."Perception is a mental process, whereby an individual selects data or information from the environment, organizes it, and then draws significance or meaning from it" (Brosekhan & Velayutham,n.d:9).The number of people sharing eWOM through various digital channels and platforms determines the numbers of people who hold either positive or negative images about a Polytechnic.eWOM valence relates to the band wagon effect whereby positive or negative organizational information goes viral affecting perceptions of stakeholders and their organizational images.Ultimately, the positive or negative organizational image held by the potential consumer seems to influence the consumer's choice of a Polytechnic for training.

Electronic Word-of-Mouth Volume and Polytechnic Image
Liu ( 2006) views electronic word-of-mouth volume as the total amount of eWOM interaction about an object.Similarly, Flanagin et al. (2014) suggest that eWOM volume is the total number of reviews posted online.Electronic word-of-mouth volume, therefore, gives a clue on the number of people who experienced the service before and how reputable the service provider is in the market.No matter the messages are negative or positive, eWOM volume swells as more people share opinions about a service or its provider (Yubo et al., 2011).Rosario et al. ( 2016) studied the influence of eWOM volume on sales and found out that negative eWOM volume does not always damage sales since the buzz can increase consumer awareness of the service and reduce uncertainty about the service and the service provider (Vermeulen & Seegers, 2009).More positive perceptions and images about the service quality and service provider can emerge from the user generated analyses and information thereof.On the basis of the above discussion, the following hypothesis was proposed: H1: eWom volume improves the number of people possessing images about an organization.

Electronic Word-of-Mouth Valence and Polytechnic Image
Electronic word-of-mouth is positive, negative or neutral (Liu, 2006;Amblee & Bui, 2011), therefore, consumers adopt new ideas, values, beliefs, attitudes and purchase intentions from the eWOM reviews (Vermeulen & Seegers, 2009;Roy et al., 2021).As consumers share the favourable or unfavourable information about Polytechnics, they form some preferences for particular Polytechnics, raising or reducing consumer expectations in terms of service quality provision.Hence, dimensions of valence increase consumer behaviour (Roy et al., 2021) even in the non-profit making service industry.Following this discussion, the following hypothesis was proposed: H2: Positive eWOM valence enhances positive impressions about a Polytechnic in the market.

Electronic Word-of-Mouth Variability and Polytechnic Image
Electronic word of-mouth variability emerges from online consumer reviews which are made up of analyses and commentaries that are crafted as consumers share service opinions and critiques (Almana & Mirza, 2013).Through these online sharing of service experiences and evaluations between students and potential students' Polytechnic images are formed and reformed bringing better understanding of the service and the service provider.Comprehension comes from the conflicts that arise from the discussions between students themselves and potential students before taking positions on which Polytechnic performs better than the other.On the basis of the discussion above, the following hypothesis was proposed.
H3: eWOM variability enhances the transformation of old organizational images to new ones.

Polytechnic Image and Consumer Service Provider Choice
Generally, consumers have a habit of sharing their experiences, opinions, and beliefs with other consumers which builds institutional images and influences service provider choices.Since education is not a leisure product, consumers are very serious when they influence others either positively or negatively in making choices.Negative reviews are believed to have more impact than positive comments (Sen & Lerman, 2007).However, some of the negative reviews may be having remote associations with the service quality since some of the analyses are done by students already in the Polytechnic system.Conversely, Vermeulen and Seegers (2009) argue that one post of negative eWOM may not have significant damage on the market, while a positive one can have much influence.
H4: A positive organizational image increases the number of people who choose to train with the Polytechnic.

Target Population
This study involved Polytechnic marketing management students from National Certificate (NC) level to Higher National Diploma (HND) level, staff involved in student affairs, and the institution promotional communication staff.The study targeted Marketing Management students only since including the whole lot of students meant an estimated population of more than thirty thousand subjects; a figure more expensive to study.Together the target population for this study was 508 students (excluding students on attachment) and staff members.Current students were the central source of primary data in the study since they are the consumers who chose to train with the Polytechnics basing on their Polytechnic images.They know how much eWOM volume and the conflicting messages they have experienced about the Polytechnic.Students seem to have some experiential knowledge to offer since they know what brought them to Polytechnics of their choice.Staff from the student affairs section participated since they seem to have reliable knowledge about students' Polytechnics images.They also understand why they chose to study with the Polytechnics.They gain this knowledge from their regular interaction with the students.

Sampling Design
Sample elements were randomly selected from class lists using random numbers.The only qualifying characteristic for participation of students was valid studentship identification card.From the population (508 units) a sample of 217 was selected to provide primary data, as suggested in Krejcie and Morgan's (1970)  A sample of twelve (12) participants was selected from 217 using the purposive sampling method since a few knowledgeable participants were required to provide qualitative data in the second phase of the study.The sample of twelve was adequate since it reduced chances of repetition of ideas without value addition (Guest et al., 2006).

Data Collection Techniques
The structured questionnaire was administered through drop-off technique which allowed respondents adequate time to complete the questionnaire.Qualitative data were gathered using an interview guide which enabled participants to orally express their views and feelings concerning Polytechnics images and service provider choices.

Data Analysis Approaches
Quantitative data analysis was done using WarpPLS software in Structural Equation Modelling.Qualitative data were analysed through Thematic Analysis in Nvivo 11 in order to explain the relationships discovered during quantitative data analysis and other explanations that were found important in the study.

Reliability and Results Analysis
Reliability analysis was conducted on all the construct variables using WarpPLS software.The calculated statistics include the Composite Reliability (CR), Cronbach's alpha (CA), Average Extracted Variance (AVE) and Variance Inflation Factors (VIFs).Table 2 presents the reliability results.  2 are below 5 implying the absence of multicollinearity among the variables.To investigate the existence of convergent validity, the cross-loadings were calculated and are presented in Table 3.All the cross-loadings shown in Table 3 are above 0.6.This suggests convergent validity on the measurement constructs, hence model fitting can be done.The variables with low factor loadings that were below 0.6 were removed from the model.
To confirm discriminant validity of the measurement items, correlations among latent variables with square root of AVEs were calculated.The results are displayed in Table 4.

Source: Survey data
It can be noted from the results displayed in Table 4 that discriminant validity is confirmed on all the latent variables since the square root of the AVE values (diagonal values) for the latent variables exceeded the corresponding correlation coefficient values.
A Structural Equation Model (SEM) was designed for the selected measurement items.PLS software was used in the calculation of the model's path coefficients and the results are summarized in Table 5. 0.601, p < 0.001).However, VOL had a positive and little effect on OI (β = 0.053, p >0.05).These research results imply that the hypothesis H2, H3 and H4 are supported and statistically significant at 1% while the hypothesis H1 is statistically insignificant.Figure 3 displays the SEM with model parameters.It can be noted from Figure 3 that 77% (R²=0.77) of the total variation in OI was being explained in the model by the independent variables (VOL, VAL and VAR) and 36% (R²=0.36) of the total variation in SPC.The R square (R²) for OI suggests a good model (Hair et al., 2011) and that of SPC suggest a moderate model.From the SEM, the following hypotheses were developed.

H1: eWom volume improves the number of people possessing images about an organization.
The volume of eWOM posts had a positive and little effect on Polytechnic image (β = 0.053, p >0.05).Thus, the impact of electronic word of mouth on Polytechnic image was found to be positive, very minimal, and insignificant leading to the rejection of hypothesis 1 at 90% significant level.The results do not uphold the theory of electronic word of mouth which holds that the volume of eWOM posts mass educates consumers there by increasing the number of consumers who hold impressions about the institution culminating in improved enrolment.High eWOM volume or feedback on a product signifies the popularity of a product or service (De Maeyer, 2012) which would imply that many consumers have experienced, learned and formed images about the innovation.The notion is also supported by Anastasiei and Dospinescu (2019, p. 4) who argue that, "Positive eWOM leads to a better product image, which positively influences buying intention".Similarly, Kumar (2023) share the same view about service or organisational image.Figure 4 shows qualitative results on electronic wordof-mouth volume Polytechnic images.

Figure 4: Qualitative Results on Electronic Word-of-Mouth Volume and Polytechnic Images
Source: Survey data While quantitative results pointed out that volume of electronic word-of-mouth had positive but insignificant impact on Polytechnic image and choice of service provider as shown in Table 5, qualitative results suggest that large volumes of electronic word-of-mouth result in more Polytechnic images (positive and negative).Figure 4 shows that, more Polytechnic images indicate that the service consumers and potential consumers now understand the organisation better than before.Interviewees reported that, the Polytechnic awareness enables potential students to select a Polytechnic for their training.However, it emerged from interview participants that eWOM posts are limited to potential students in urban areas with resources such as smartphones to access social media platforms and cash to purchase data to go online.

H2: Positive eWOM valence enhances positive impressions about a Polytechnic in the market.
The results in Table 5 suggest that electronic word of mouth valence had a positive effect on organisational image (β = 0.54, p = 0.001< 0.10).The results were positive and significant, for that reason, hypothesis 2 was not rejected at 90% significant level.Thus, as service consumers share positive ideas and beliefs about a Polytechnic, more consumers, and potential consumers become positive about the institution (Mauri & Minazzi, 2013).The results are in congruent with electronic word of mouth literature which argue that positive eWOM valence enhances positive organisational images.Figure 5 illustrates the outcomes of the qualitative survey on positive eWOM valence and impressions about an organisation in the market.5, are in synch with the qualitative results in Figure 5. Qualitative survey interviewees revealed that positive consumer reviews are the bricks that build up a positive organisational image.Quality service provision by a Polytechnic builds on to its organisational image and popularity.Hence, it was discovered that positive eWOM valence develops positive perceptions which lead to good Polytechnic image (Mauri & Minazzi, 2013) and more choices of a particular Polytechnic by potential students.In short, Figure 5 shows that, positive electronic word-of-mouth, therefore, boosts sales (enrolment) (Hyrynsalmi et al., 2015) and Polytechnic image.Unbelievable sources of eWOM were, however, found to be a challenge since they can exaggerate how well or bad a Polytechnic might be in terms of service provision.That alone, more often than not, was reported to be misleading consumers as they made their decisions on Polytechnic choices.

Results for Electronic Word-of-Mouth Variability and Polytechnic Images
H3: eWOM variability enhances the transformation of old organizational images to new ones.Electronic word of mouth variability had a positive effect on organisational image (β = 0.381, p = 0.001 < 0.10) as illustrated in Table 5. Basing on this empirical evidence, hypothesis 3 was not rejected at 90% significance level.That is, the more consumers share the varied positive and negative eWOM, about the organisation, the more they learn new ideas, beliefs, and attitudes and adopt new Polytechnic images.Figure 6 shows the qualitative reflections on the theme 'electronic word-of-mouth variability'.5. Electronic word-of-mouth variability entails acquisition of favourable and unfavourable eWOM ideas, which is consumer learning about the Polytechnic.Figure 6 illustrates that electronic word-of-mouth variability enhances assimilation of ideas and learning by consumers, which results in informed transformation of Polytechnic images (from positive to negative or vice versa).In brief, it was found out that, as consumers share varied eWOM opinions and facts about an organisation, the gained knowledge enhances their propensity to modify their organisational images, which in turn influence their choices (Maru & Vijay, 2024) of Polytechnics to train with.

Results for Polytechnic Image and Service Provider Choice
H4: A positive organizational image increases the number of people who choose to train with the Polytechnic.
The results in Table 5 suggest that organisational image had a positive effect on service provider choice (β = 0.601, p = 0.001<0.1).The results were positive and significant.Thus, a positive Polytechnic image proved that it can increase enrolment.Hypothesis 4 was therefore not rejected at 90% significant level.Figure 7 illustrates the impact of positive organisational image on Polytechnic enrolment in Zimbabwe.7 shows that a positive organisational image is closely and positively associated with a good reputation, high institutional status and student statuses which are highly sought by the student themselves.Lievens (2017) argues that organisational image can be viewed as a signal of product quality and a sturdy pillar to gain competitive advantage.Such organisational characteristics improve Polytechnic enrolment since potential students seek to be identified with the high personalities which in a way explain theirs in the industry of work.

Model Fit Results
Model diagnostics was done whereby various measures were looked at to see if they met the acceptable cut-off points.The model fit indices that were calculated are displayed in Table 6.It can be concluded that the data fitted well to the model as suggest by the results displayed in Table 6.All the recommended cut-off points were met.The model can be used for prediction purposes.

Theoretical Implications
The volume of eWOM posts proved that a minimal positive increase was insignificant to cause a notable increase in the number of potential students possessing images about the Polytechnic.Therefore, the use of integrated marketing communications strategies would enable stronger marketing communications techniques to cover up for the weaker ones.Positive eWOM valence was positively correlated to positive organisational images.Positive eWOM valence enhances Polytechnic image and hence improves enrolment (service provider choice).Electronic word of mouth variability enhances the transformation of old images to new ones.The sharing of positive and negative information about a Polytechnic service enhances consumer understanding of the institution which culminates in purchase of the services (enrolment).A positive organizational image increases the number of people who choose to train with the Polytechnic.A good Polytechnic image attracts potential students for high enrolment (actual purchase).

Managerial Implications
When using electronic word-of-mouth marketing strategy, marketing managers should make sure that high volumes of eWOM reach more relevant market segments.Polytechnic marketing managers could apply other marketing communication methods such as digital public relations, electronic direct mail (EDM) marketing and email automation campaigns as economical and effective outbound marketing.The marketing section for a Polytechnic or the Public Relations office should focus on improving commercial eWOM for the institution in order to encourage positive eWOM among stakeholders, current students, and potential students to improve enrolment.The marketing arm for a Polytechnic or the Public Relations office should monitor and moderate eWOM variability so that it enhances adoption of positive institutional images.
Polytechnics should invest more on corporate image building in order to attract more students for enrolment.

Limitations and Future Research
The study did not include publics of the Polytechnics who might be holding different positive and negative views about the Polytechnics since they may not have been influenced by the Polytechnics administrations.Maybe these parents, guardians, and youths could have provided data on why they chose other different Polytechnics or why they had to take their children to Polytechnics of their choice.Future research could focus on involvement of such stakeholders as parents/guardians and future students for the Polytechnics who are in the local areas in order to get balanced data.
Figure 1: The research model Source: Survey data Figure 2: The Structural Equation Model (SEM) Source: Survey data From the SEM, the following hypotheses were developed.

Figure 3 :
Figure 3: SEM with parameters Source: Survey data

Figure 5 :
Figure 5: Electronic Word-of-Mouth Valence Source: Survey data Quantitative results, in Table5, are in synch with the qualitative results in Figure5.Qualitative survey interviewees revealed that positive consumer reviews are the bricks that build up a positive organisational image.Quality service provision by a Polytechnic builds on to its organisational image and popularity.Hence, it was discovered that positive eWOM valence develops positive perceptions which lead to good Polytechnic image(Mauri & Minazzi, 2013) and more choices of a particular Polytechnic by potential students.In short, Figure5shows that, positive electronic word-of-mouth, therefore, boosts sales (enrolment)(Hyrynsalmi et al., 2015) and Polytechnic image.Unbelievable sources of eWOM were, however, found to be a challenge since they can exaggerate how well or bad a Polytechnic might be in terms of service provision.That alone, more often than not, was reported to be misleading consumers as they made their decisions on Polytechnic choices.

Figure 6 :
Figure 6: Electronic Word-of-Mouth Variability Source: Survey data Qualitative results were found to be in congruency with the quantitative results on eWOM variability shown in Table5.Electronic word-of-mouth variability entails acquisition of favourable and unfavourable eWOM ideas, which is consumer learning about the Polytechnic.Figure6illustrates that electronic word-of-mouth variability enhances assimilation of ideas and learning by consumers, which results in informed transformation of Polytechnic images (from positive to negative or vice versa).In brief, it was found out that, as consumers share varied eWOM opinions and facts about an organisation, the gained knowledge enhances their propensity to modify their organisational images, which in turn influence their choices(Maru & Vijay, 2024) of Polytechnics to train with.

Figure 7 :
Figure 7: Positive Organisational Image and Service Provider Choices Source: Survey data

Figure
Figure7shows that a positive organisational image is closely and positively associated with a good reputation, high institutional status and student statuses which are highly sought by the student themselves.Lievens (2017) argues that organisational image can be viewed as a signal of product quality and a sturdy pillar to gain competitive advantage.Such organisational characteristics improve Polytechnic enrolment since potential students seek to be identified with the high personalities which in a way explain theirs in the industry of work.
table.Table1shows the sampling frame from which the respondents were chosen.

Table 2 : Reliability Statistics
Hair et al. (2009)yed in Table2show that all the CA values are exceeding the recommended threshold value of 0.7 indicating presence of internal consistency of the variables.Hair et al. (2014)recommended a CR value that is above 0.7 and an AVE value that exceed 0.5.It can be noted from the CR and AVE values displayed in Table2that they are meeting the recommended thresholds.The results imply that the measurement constructs are reliable.According toHair et al. (2009), the VIFs values which are below 5 suggest the absence of multicollinearity.All the VIFs values shown in Table

Table 4 : Correlations among Latent Variables With Square Root of Aves
Note.The bolded diagonal values are the Square roots of the AVE values.

Table 5 : Structural Model Path Coefficients
Source: Survey dataThe results in Table5suggest that VAL had a positive effect on OI (β = 0.54, p < 0.001), VAR had a positive effect on OI (β = 0.381, p < 0.001) and OI had a positive effect on SPC (β =