The role of digital learning towardstudents’ satisfaction anduniversity brand image at

educational institutes of Pakistan:a post-effect of COVID-19

Sidra ShehzadiSchool of Multimedia Technology and Communication, Universiti Utara Malaysia,

Sintok, Malaysia

Qasim Ali NisarDepartment of Business Administration and Management Sciences,

Superior University Lahore, Lahore, Pakistan

Muhammad Sajjad HussainUniversity of Management and Technology, Lahore, Pakistan

Muhammad Farhan BasheerSchool of Economics, Finance and Banking, Universiti Utara Malaysia,

Sintok, Malaysia

Waseem Ul HameedDepartment of Management Sciences,

The Islamia University of Bahawalpur Pakistan, Bahawalpur, Pakistan, and

Naveed Iqbal ChaudhryDepartment of Business Administration, University of the Punjab,

Lahore, Pakistan

Abstract

Purpose – This study is undertaken to examine the role of information and communication technology (ICT),e-service quality and e-information quality towards brand image of universities by concentrating on students’e-learning, e-word of mouth and satisfaction.

Design/methodology/approach –The target populationwas the students of public and private universitiesin Pakistan. Data collected using an e-questionnaire by 408 students were subjected to PLS-SEM for analysis.Findings – Findings revealed that ICT, e-service quality and e-information quality are positively contributedtoward students’ e-learning which ultimately leads to create positive e-word of mouth and students’satisfaction. Meanwhile, results also identified that e-word of mouth and students’ satisfaction lead to generatea positive brand image of universities.

Practical implications – This study has unique implications for universities to develop an e-learningplatform to facilitate their students in this situation of COVID-19. It provides guidelines for educationalinstitutions to implement the learning management system effectively with a view to facilitate the studentswith education.

Originality/value – This study has novel contribution in literature in the domain of digital learning. It isunique in a way to integrate the usage of technology with students’ e-learning and satisfaction that ultimatelycreate brand image of universities.

Keywords Coronavirus, Information and communication technology, E-Service quality, E-Information

quality, E-Learning, E-Word of mouth, Student satisfaction, University brand image

Paper type Research paper

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The current issue and full text archive of this journal is available on Emerald Insight at:

https://www.emerald.com/insight/2046-3162.htm

Received 25 April 2020Revised 13 July 2020Accepted 27 July 2020

Asian Education and DevelopmentStudiesVol. 10 No. 2, 2021pp. 276-294© Emerald Publishing Limited2046-3162DOI 10.1108/AEDS-04-2020-0063

1. IntroductionThe world has a long history of deadliest pandemics. Pandemic is a wide-reaching outbreakof a transferable infectious disease, which not only increase the morbidity and mortality butalso cause significant economic, social and political disruption. Evidence suggests thatincreasing globalization, urbanization and excessive exploitation of natural andenvironmental resources has increased the likelihood of pandemics (Grønseth, 2018;Cunningham et al., 2017). The coronavirus pandemic (COVID-19: one of the deadliestpandemics of the current century) is an ongoing disease and spreading rapidly across theglobe. The COVID-19 caused by an acute respiratory syndrome coronavirus 2 (SARS-CoV-2).The first case of COVID-19 was identified in Wuhan, Hubei, China in December 2019, andlater on 11th March 2020, the World Health Organization (WHO) declared COVID-19 apandemic. As of 7thApril 2020, is affecting in 209 countries and one international conveyance(the Diamond Princess cruise ship harbored in Yokohama, Japan) resulting in more than1,415,000 cases, 82,000 deaths and more than 301,000 recoveries.

On the 26th February 2020, the Special assistant of Prime Minister of Pakistan on Healthconfirmed the first two cases of COVID-19. A student at the University of Karachi Pakistanand a person from the federal territory of the country are the first two patients of COVID-19 inPakistan. A week later Pakistan confirmed three more cases, and as of 26th March 2020, atotal of 1,179 cases of COVID-19 are reported (see Figure 1).

The shutdown of educational institutes aiming at the public health emergency is acontagion effect of the novel coronavirus. In response to tackle the educational institution’sclosure situation caused by COVID-19, the UNESCO has recommended the educationalinstitutes to equip them with online learning tools (Crawford et al., 2020). Therefore, just afterthe closure of the universities in Pakistan, the higher education commission advised theuniversities to be equipped with and advance e-learning management system. However, atlarge the higher education system in Pakistan is still relying on the classical method ofteaching and training and the Universities in Pakistan and their corresponding programs areaccredited by the Higher education commission of Pakistan enhancement.

In the age of information, the technology and in particular the information technology inthe shape of e-learning has landscaped the education industry. The latently impending shiftfrom the classical design of teaching and training is a source of both the challenges andopportunities for higher education institutions. One of the distinguishing factors is theadvancement in information and communication technology (ICT), which like otherindustries has landscaped the education industry. ICT coupled with the e-service quality

050

100150200250300350400450500

Number of COVID-19 Cases in Pakistan

Source(s): National Institute of Health

Figure 1.Source: National

institute of health

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and e-informational quality offers many new benefits to students, which numerousundergraduate and postgraduate programs have begun to explore. The available literature(Reily, 2017) on the relationship between service quality and student e-learning explains theservice quality as one of the key determinants of the e-learning. Student satisfaction is at theheart of any method of teachings. Students’ satisfaction is the judgment that the informationand knowledge quality or the information and knowledge themselves is copingwith students’expectations. In this context, e-learning can improve the learning efficacy of students thusincreasing the efficiency of students. According to Oduma et al. (2019), the highest quality ofeducation associated with e-learning can help the universities in increasing the satisfaction ofstudents.

The electronic word of mouth (e-WOM) focuses on the explicit interpersonal contacts thathappen on the Internet. e-WOM is a kind of buzz marketing where a message instantly canbecome viral. Though the concept itself is not new, however, the speed in which a messagecan be viral makes it important. The brand image can be defined as a unique bundle ofassociationswithin themind of the target customer (Uppal et al., 2018). It is basically an imagein the eyes of customers, which develops over time. Universities in developing countries havenot always paid much attention to their brands (Jayakumar and Ali, 2016), and many of thehigher education institutions are considering the reputation and grade averages as a viabletool to attract the students. However, the recent shift to online learning as a result of the crisisfromCOVID-19 has increased the likelihood of their exposure to e-WOM.Thus, the purpose ofthis study is to examine the role of digital learning toward students’ satisfaction anduniversity brand image at educational institutes of Pakistan in this pandemic situation ofCOVID-19.

2. Literature reviewThis section shows the critical literature on understudy variables along with associationamong them in the following subsections.

2.1 Information and communication technology in E-learning of studentsThe provision of information is one of the most significant aspects of e-services as theexchange of information between two particular parties has prior significance. The majorityof scholars view that it is a common conception about the facility of the Internet that it’smostly used to quench the thirst for knowledge and to satisfy the necessity of information inthe education sector (Talebian, et al., 2014). It’s quite evident that the acquisition ofknowledge and information is one of the considerable online practices. The constantimprovement in ICT contributes to students’ academic achievements. The current situationaround the globe has increased the requirement of ICT in terms of student learning due to thecoronavirus breakdown. The ICT usage in Pakistan also quite considerable before theCOVID-19 but after coronavirus lockdown almost all of the education institutions adoptedICT and provided e-learning to the students during a lockdown situation. In addition,educational and non-educational institutions of Pakistan have adopted ICT in the lockdownsituation while communicating to the students and other business stakeholders throughonline business meetings. Thus, ICT usage in Pakistan during COVID-19 has become anessential part of every institution in the country. This breakdown cut out the physicalcontacts between the educational institutions and students that enhance the demand of ICTin the learning of the students around the globe. Thus, the current study developed thefollowing hypothesis:

H1. Information and communication technology has positive nexuswith the e-learning ofthe students.

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2.2 E-services quality and E-learning of studentsThe e-learning quality is the most significant perspective of e-learning of students, which isfollowed by e-learning tutor and the quality of material in course, and the quality ofE-learning administration and service support (Pham et al., 2019). Despite the limited qualityof the website, a few studies focus on the association between the quality of the website andstudents’ academic achievements. The qualitative literature on web-based educationprocedures highlights that the quality of the website is linked to students’ learningrequirements, availability of better education and web-based education system is linked withstudents’ satisfaction of teaching (Alkhattabi et al., 2011). In addition, the use of web-basededucation has to gain the focus all over the world due to the coronavirus threat due to whichseveral education institutions move toward online education that may affect the learning ofthe students. This situation motivates the researcher to conduct this type of study thatexamines the e-learning of the students and institutional reputation in this lockdown sessiondue to coronavirus threat. Therefore, the examination of e-services quality is necessary forthe e-learning of the students and this study developed the following hypothesis:

H2. E-services quality has a positive association with the e-learning of the students.

2.3 E-information quality on E-learning of studentsThe empirical studies have proved that the higher the quality of e-information provided, thebetter is the e-learning of students. The comparison between typical services and web-basedservices has given a base for the perception that all the features of service quality do notinfluence the whole service quality given to the students to the same degree (Alkhalaf et al.,2013). In this tough situation of coronavirus, there is an extensive level of need about the highquality of e-information that enhances the e-learning of the students. In the online servicecontext of education, several studies have highlighted that the service quality features havedifferent significance in forming overall service quality. Thus, e-information quality is theessential part of the e-learning session that enhance the e-learning of the students that isthe essential requirement for all over the world in coronavirus lockdown situation and gainthe attention of the researchers and this study also proposed the hypothesis that:

H3. E-information quality has a positive association with the e-learning of the students.

2.4 E-learning of students and E-words of mouthThe termWOMcan be defined as casual communication by customers regarding acquisition,usage or features of services and service renders. But recently, the World Wide Web hasconsiderably changed the way of communication converting the termWOM into a new terme-WOM (Wu et al., 2010). The significant difference between the two terms is that e-words ofthe mouth are communicated through an innovation-based web. While taking into accountother features, e-WOM is similar to offline WOM (Litvin et al., 2018). Furthermore,information creditability is as much essential for e-WOM as it is significant for offline WOM.In the education sector, e-WOM plays a significant role. The permanent web-connectedstudents are sufficiently being affected by online education procedures and sources ofinformation. Thus, coronavirus lockdownmay affect the e-WOM reputation of the institutiondue to extensive use of e-learning source of education andmotivates the researcher to explorethis aspect and this study proposed the hypothesis that:

H4. E-learning of the students has a positive association with the e-WOM.

2.5 E-learning of students and student satisfactionStudent satisfaction is used as a prominent benchmark to measure the success of educationalwebsites of universities. Student satisfaction is a crucial element for all educational

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institutions to maximize their profitability by creating as well as maintaining students’behavioral attitudes and intentions. Satisfaction is of two types such as cognitive satisfactionand effective satisfaction according to Yilmaz (2017). Effective satisfaction of students ariseswhen the information and knowledge received to have the same quality as was expected bystudents and it positively influences the mentality of students (Dominici and Palumbo, 2013).This effective satisfactionmay reduce in the case of e-learning and affect the reputation of theinstitution like in the case of coronavirus lockdown, many institutions go for the onlinelearning that may affect the student’s satisfaction along with institutions’ reputation.However, effective e-learning has positive impact on the satisfaction level of the student andthis study proposed the hypothesis that:

H5. E-learning of the students has a positive association with the satisfaction of thestudents.

2.6 E-words of mouth and university brand imageThe quality of e-WOM put strong influences on universities’ image. E-WOM is not limited tosome particular technology or particular population (Gupta and Harris, 2010). It has beendiscovered by analysts who not only highly experienced but young persons are also animportant source of e-WOM. Universities use specific sources of information for theachievement of brand image (Yoo et al., 2013). This type of information not only motivatesstudents to get education from the same websites but also makes them develop relevantuniversity’s brand name. By managing brand expectations, management minimizes the gapbetween the university’s predicted image and students’ perception of brand image. Currently,the situation of coronavirus also boosts up the use of technology, as most of the universitieshave started an online session that creates the positive and negative e-WOM that influencesthe brand image of the universities. This situation also boosts up the researchers toinvestigate this aspect and this study has developed the following hypothesis:

H6. E-WOM of the students has positive nexus with the university brand image.

2.7 Student satisfaction and university brand imageThe image of the university plays an important role in forming students’ decision making. Theadvanced marketing instrument, university branding, is utilized to get students involved,interested and put the institution in competition. Azoury et al. (2014) argue that there is anecessity of branding of university image in this highly competitive age for applying strategiesregarding the branding of image. Thus, the brand indicates the ability of the university to fulfillthe requirements of students, the building of trust in the university’s competency to renderbetter services to students (Chen and Chen, 2014). However, the satisfaction level of thestudents may be affected due to online sessions instead of physical classes due to coronaviruslockdown. The universities now started online classes for the students that not only can affectthe learning of the students but also can affect their satisfaction level regarding the brandimage of the university. Thus, the present study developed the hypothesis that:

H7. Satisfaction of the students has positive nexus with university brand image.

H8. E-learning of students mediates the relationship between information andcommunication technology and e-word of mouth

H9. E-learning of students mediates the relationship between e-service quality ande-word of mouth

H10. E-learning of students mediates the relationship between e-information quality ande-word of mouth

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H11. E-learning of students mediates the relationship between information andcommunication technology and students’ satisfaction

H12. E-learning of students mediates the relationship between e-service quality andstudents’ satisfaction

H13. E-learning of students mediates the relationship between e-information quality andstudents’ satisfaction

H14. E-word of mouth mediates the relationship between e-learning of students anduniversity brand image

H15. Students’ satisfaction mediates the relationship between e-learning of students anduniversity brand image.

3. Methods3.1 Sample and data collectionThe target population of this study was students of public and private universities. Based onranking issued in 2019 by the Higher Education Commission of Pakistan, the top 10universities (Public and Private) were selected for data collection. These selected universitieswere representative of all other institutions because most of these selected universities arealso secured a good position in QSWorld Ranking 2020. An online questionnaire was used tocollect data from the education sector of Pakistan included private and public sectoruniversities that started to use an online learning system for educational continuity in thecurrent situation of COVID-19. The unit of analysis was individuals, and the respondentswere university students who are involved in e-learning by taking their online classes. Datawere collected via an online questionnaire survey.We shared an online link via Facebook andWhatsApp groups to reachmost of the University students to fill up the online questionnaire.We received a total of 408 questionnaire responses and useable responses were 374 that weused for data analysis (see Figure 2).

3.2 Questionnaire and measuresThe questionnaire consisted of 71 items. Based on a study by Bhat and Bashir (2018),information technology and communication was measured by 15 items from whichadvantage contained four items, compatibility had three items, ease of use consisting of five

H7

H6

H5

H4

H3

H2

H1

Informa�on &Communica�on

Technology� Advantage� Compa�bility� Ease of Use� Percep�on

E-Learning of Students

University Brand Image

Student Sa�sfac�on

E-Service Quality� Efficiency� Fulfillment� System

Availability� Privacy

E-Word of Mouth

E- Informa�on Quality

Figure 2.Theoretical framework

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items and perception had three items. The e-service quality scale consisted of four dimensionswith 22 items was adapted by Parasuraman et al. (2005) with eight items for efficiency, fouritems for system availability, seven items for the fulfillment and three items for privacy.Furthermore, online information quality was measured by nine items that were developed byZhou et al. (2014). Moreover, based on a study by Udo et al. (2011), a four-item scale wasadapted for e-learning. Moreover, based on a study by Lee et al. (2019), four-item scale wasused to measure e-WOM. Student satisfaction was measured by nine items that weredeveloped by Headar et al. (2013). Lastly, the university brand image was measured by eightitems and we adapted this scale from a study proposed by Sultan and Wong (2019).

3.3 FindingsPLS-SEMwas employed for data analysis by using Smart PLS 3 as it is deemed as a popularand advanced estimation technique in the hospitality and tourism domain (Ali et al., 2018).Moreover, the PLS algorithm followed by the bootstrapping technique was used to assess themeasurement as well as the structural model.

3.4 Measurement Model AssessmentThe measurement model was evaluated and convergent validity was assessed by usingloadings, average variance extract and competitive reliability. Refer to Table 1 except for afew values, factor loadings exceeded the recommended value of 0.60 for both countries.Similarly, all values of composite reliability (CR) also exceeded the recommended value of0.70. All the values of average variance extract (AVE) for all under-study constructs exceededthe recommended values of 0.50 (Hair et al., 2016). Items were deleted with the lowest factorloadings (<0.50) (see Figure 3).

4. Discriminant validityHenseler et al. (2015) proposed a new and advanced criterion (HTMT ratio) to assess thediscriminant validity and they agreed that the Fornell–Larcker criterion was one of theeffective methods to evaluate discriminant validity but this approach had not detectedthe lack of discriminant validity in various research situations. Therefore, the HTMT ratiowas used to assess the discriminant validity of constructs. As shown in Table 2, all the valuesof the HTMT ratio were given in the Malaysian and Pakistani context. All the values are lessthan 0.90 as recommended by Dayan et al. (2017), hence discriminant validity had also beenestablished for all constructs.

5. Structural Model Assessment (SEM)The structural model was also assessed after the evaluation of the measurement model. Forthis purpose, the significance of the model assessed on the basis of path coefficients, t-valuesand standard errors. The hypotheses were tested for themain and indirect effects through thebootstrapping procedure in Smart PLS 3 (Ringle et al., 2005). Refer to Tables 3 and 4, andFigure 4, direct and indirect hypotheses were empirically tested. Hypotheses were supportedon the basis of critical ratio (t > 1.645; p < 0.05). It was found that all the hypotheses aresupported except few relationships.

6. Discussion and conclusionThe objective of the current studywas to examine the impact of the ICT, e-service quality ande-information quality on the e-learning of the students in the higher education institutes ofPakistan. To address the objective of this study, 15 hypotheses were proposed based on the

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First-orderconstructs Second-order constructs Items Loadings CR AVE

Advantage Adv1 0.858 0.935 0.781Adv2 0.918Adv3 0.889Adv4 0.869

Compatibility Comp1 0.941 0.947 0.899Comp3 0.956

Ease of Use EOU1 0.808 0.901 0.646EOU2 0.876EOU3 0.745EOU4 0.725EOU5 0.854

Perception Perc1 0.863 0.931 0.819Perc2 0.928Perc3 0.921

Information and CommunicationTechnology

Advantage 0.888 0.829 0.553

Compatibility 0.618Ease of Use 0.782Perception 0.655

Efficiency E1 0.906 0.934 0.739E2 0.866E3 0.833E4 0.805E5 0.885

Fulfillment F1 0.844 0.869 0.689F2 0.861F3 0.783

Privacy P1 0.766 0.799 0.57P2 0.727P3 0.771

System Availability SA1 0.886 0.911 0.774SA2 0.871SA3 0.883

E-Service Quality Efficiency 0.384 0.797 0.515Fulfillment 0.843SystemAvailability

0.888

Privacy 0.643E-InformationQuality

EIQ1 0.839 0.897 0.685EIQ2 0.775EIQ3 0.822EIQ4 0.872

E-Learning ofStudents

ELS1 0.924 0.891 0.733ELS2 0.87ELS3 0.768

E-Word of Mouth EWOM1 0.887 0.788 0.49EWOM2 0.565EWOM3 0.62EWOM4 0.685

(continued )Table 1.

Convergent validity

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previous studies and post-effects of COVID-19 in relation to the Pakistani universities.Among these 15 hypotheses, seven hypotheseswere based on the direct hypotheses and eighthypotheses were based on the indirect hypotheses. A survey was carried out and data werecollected from universities. Finally, data were analyzed by using the statistical tool to achievethe objective of the current study. The results of the current study partially fulfilled theobjective and provided valuable insights for universities toward digital online learning as aconsequence of COVID-19. The outcomes of the study and applications of this study modelare a paradigm shift in the universities because this model assists the university to apply acompletely new model which facilitates online learning.

The current study provided evidence that students’ e-learning is one of the vital elementsto provide online education in an emergency situation like COVID-19. However, students’e-learning enquires three major components; ICT, e-service quality and e-information quality.The results of the study highlighted that ICT has a positive role to enhance studentse-learning. Better ICT can enhance students’ e-learning. These results are also supported byprevious studies. According to Shaw and Marlow (1999), ICT has a major role to promotestudent e-learning. Further studies are also proved a significant positive influence of ICT onstudent e-learning (Supriadi and Sa’ud, 2017; Terry, 2016; Wilkinson et al., 2010).Furthermore, the results of the study also proved that e-service quality is a positivecontribution to promote student e-learning. Therefore, e-service quality is themain element ofthe paradigm shift. Better e-service quality has the potential to help the paradigm shift inuniversities. Better quality of e-service can encourage students for learning through an onlinesystem. Consistentwith the current studyNsamba (2019) elaborated that the e-service qualityaffects directly to the loyalty of e-learning students. In line with the current study, variousprior studies also highlighted that e-service quality has a positive effect on student e-learning(Khodadad Hoseiny et al., 2013; Mart�ınez-Arg€uelles et al., 2009; Zeglat et al., 2016).Furthermore, the current study proved that to promote student e-learning, e-service qualitymust have tangibility, reliability, responsiveness and assurance. Additionally, to ensure abetter student e-learning system, better e-information quality must be provided.E-information quality is vital to develop a student e-learning system and to motivate thestudents to avail of the online learning facility. Previous literature is also consistent with thecurrent study and provides evidence that e-information quality has a positive role to enhancestudents e-learning. As previous studies investigated a significant positive effect ofe-information on student learning (Alkhalaf et al., 2013; Mammo and gulube, 2019).Nevertheless, WOM also have a major role in universities during COVID-19. This study alsoproved that the e-learning of students has considerable influence on e-WOM and studentsatisfaction. Both e-WOM and student satisfaction are vital to carry on e-learning amonguniversities in response to COVID-19. Better students’ e-learning system has the ability to

First-orderconstructs Second-order constructs Items Loadings CR AVE

Student Satisfaction SS1 0.827 0.895 0.634SS2 0.744SS3 0.862SS4 0.875SS5 0.651

University BrandImage

UBI1 0.691 0.865 0.619UBI2 0.704UBI4 0.873UBI5 0.86

Note(s): AVE-Average Variance Extract; CR-Composite ReliabilityTable 1.

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P1P2

P3SA

1SA

2SA

3

Adv10.

741

0.77

60.

765

0.88

5

0.24

3

0.88

80.

941

0.95

60.

618

0.80

80.

876

0.74

50.

725

0.85

4

0.78

2

0.65

5

0.11

6

0.92

80.

863

0.77

50.

839

0.87

20.

822

0.92

1

Adva

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Com

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Ease

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70.

869

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Fulfi

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0.91

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872

0.82

90.

796

0.89

0

Effic

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84

0.87

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884

Priv

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0.85

80.

918

0.88

90.

869

Adv2

Adv3

Adv4

EOU

1

EOU

2

EOU

3

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4

EIQ

1EI

Q2

EIQ

3EI

Q4

EWO

M1

EWO

M2

EWO

M3

EWO

M4

ELS1

ELS2

ELS3

EOU

5

Com

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Com

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Perc

1

Perc

2

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F1F2

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0.81

30.

754

0.85

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863

0.67

4

0.47

50.

712

0.62

00.

887

0.56

50.

685

0.92

4-0

.084

0.73

3

0.41

80.

446

0.76

90.

869

0.69

30.

706

0.87

20.

859

Stud

ents

’Sa

tisfa

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Uni

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SS1

SS2

SS3

SS4

SS5

UBI

1

UBI

2

UBI

4

UBI

5

Figure 3.Measurement model

assessment

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ADV

COMP

EIQ

ELS

EWOM

EOU

Eff

Full

PER

Privacy

SS

SA

UBI

ADV

COMP

0.533

EIQ

0.614

0.432

ELS

0.899

0.56

0.584

EWOM

0.571

0.511

0.545

0.561

EOU

0.595

0.433

0.618

0.525

0.592

Eff

0.552

0.471

0.38

0.854

0.462

0.262

Full

0.589

0.415

0.654

0.543

0.497

0.626

0.335

PER

0.553

0.235

0.659

0.578

0.298

0.355

0.308

0.409

Privacy

0.258

0.163

0.296

0.237

0.389

0.397

0.101

0.438

0.191

SS

0.799

0.687

0.644

0.823

0.678

0.775

0.473

0.681

0.428

0.411

SA

0.617

0.42

0.866

0.644

0.47

0.489

0.426

0.615

0.723

0.152

0.668

UBI

0.757

0.539

0.756

0.641

0.878

0.68

0.34

0.884

0.511

0.327

0.866

0.744

Table 2.Discriminant Validityfor First-OrderConstructs(HTMT ratio)

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foster e-WOM and student satisfaction. Consistent with the current study, Le Hoanh et al.(2014) highlighted a significant relationship between students e-learning and e-WOM. Alongwith the positive effect of e-WOM, it also has positive effect on student satisfaction. Betterstudents’ e-learning system has the ability to satisfy the students. An increase in the studentsatisfaction level will show positive outcomes for the universities. Consistent with the currentstudy,Wu et al. (2010) also proved that e-learning has a positive effect on student satisfaction.These results are also in line with other studies (Cole et al., 2014; Dominici and Palumbo, 2013;Nortvig et al., 2018).

Finally, the results of the study highlighted that both e-WOM and student satisfactionhave a significant contribution to develop the university brand image. Positive e-WOMgenerate impressive university brand image and lead the universities to fight with COVID-19.

H Relationships Beta SEt-

value LL UL Decision

H1 Information and CommunicationTechnology → E-Learning of Students

0.733 0.051 14.44 0.642 0.81 Supported

H2 E-Service Quality → E-Learning ofStudents

0.116 0.062 1.872 0.017 0.22 Supported

H3 E-Information Quality → E-Learning ofStudents

�0.084 0.054 1.567 �0.174 0.001 NotSupported

H4 E-Learning of Students → E-Word ofMouth

0.418 0.041 10.202 0.345 0.482 Supported

H5 E-Learning of Students → Students’Satisfaction

0.712 0.024 29.19 0.667 0.748 Supported

H6 E-Word of Mouth → University BrandImage

0.446 0.052 8.521 0.356 0.529 Supported

H7 Students’ Satisfaction → UniversityBrand Image

0.475 0.06 7.933 0.377 0.573 Supported

Beta SEt-

value LL UL Decision

H8 Information and CommunicationTechnology → E-Learning ofStudents → E-Word of Mouth

0.306 0.039 7.873 0.241 0.369 Supported

H9 E-Service Quality → E-Learning ofStudents → E-Word of Mouth

0.049 0.026 1.855 0.007 0.094 Supported

H10 E-Information Quality → E-Learning ofStudents → E-Word of Mouth

�0.035 0.023 1.556 �0.074 0.001 NotSupported

Information and CommunicationTechnology → E-Learning ofStudents → Students’

Supported

H11 Satisfaction 0.522 0.041 12.743 0.451 0.587 SupportedH12 E-Service Quality → E-Learning of

Students → Students’ Satisfaction0.083 0.045 1.851 0.012 0.159

H13 E-Information Quality → E-Learning ofStudents → Students’ Satisfaction

�0.06 0.038 1.568 �0.123 0.001 NotSupported

H14 E-Learning of Students → E-Word ofMouth → University Brand Image

0.187 0.03 6.269 0.14 0.237 Supported

H15 E-Learning of Students → Students’Satisfaction → University Brand Image

0.338 0.048 7.088 0.263 0.421 Supported

Table 3.Path analysis

Table 4.Indirect effects

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P1P2

P3SA

1SA

2SA

3

Adv18.

217

11.9

7511

.075

55.5

33

4.94

7

66.1

4083

.649

143.

002

18.2

36

39.1

1441

.770

26.0

0923

.572

37.5

65

28.5

97

15.0

91

1.87

2

83.8

3836

.560

31.7

3137

.568

42.1

5432

.687

98.8

41

Adva

ntag

e

Com

pata

bilit

y

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of U

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79.0

35Sy

stem

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46.1

5751

.786

28.5

12

Fulfi

llmen

t

77.5

6660

.527

35.1

0932

.429

63.5

75

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ienc

y36

.227

6.14

4

43.8

0858

.965

Priv

acy

48.0

7293

.336

62.9

9030

.726

Adv2

Adv3

Adv4

EOU

1

EOU

2

EOU

3

EOU

4

EIQ

1EI

Q2

EIQ

3EI

Q4

EWO

M1

EWO

M2

EWO

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EWO

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ELS1

ELS2

ELS3

EOU

5

Com

p1

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1

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2

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3

F1F2

F3E1

E2E3

E4E5

33.1

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50.6

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329

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10.3

4871

.349

9.10

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132.

057

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869

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58.8

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SS1

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1

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2

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4

UBI

5

Figure 4.Structural modelassessment

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According to the results of the current study, the quality of e-WOM put strong influences onuniversities’ image in the sight of the general public. These results are also consistentwith theresults of previous studies. Previous studies also highlighted a significant relationshipbetween e-WOM and brand image (Jalilvand and Samiei, 2012; Kim et al., 2014; Vahdati andMousavi Nejad, 2016). Additionally, the current study also proved a significant relationshipbetween student e-learning and student satisfaction. These results are in line with previousstudies as previous studies proved that student online learning has a positive effect onstudent satisfaction (Eom and Arbaugh, 2011; Nortvig et al., 2018; Peng and Samah, 2006;Vate-U-Lan, 2020). Finally, this study proved that to develop a better student e-learningsystem, ICT, e-service quality and e-information quality is required which further promotee-WOM and student satisfaction. This whole mechanism causes to increase university brandimage in the tense condition of COVID-19 and allow the universities to start their normaloperations. Consequently, the relationship between ICT, e-service quality and e-informationquality toward brand image of universities by concentrating on students’ e-learning, e-WOMand satisfaction is one of the steps further toward a paradigm shift in the South Asianuniversities.

7. Implications of the study7.1 Theoretical implicationsThe current study has significant implications for literature. Because the current studyprovided a comprehensive framework including important insights into facilitate a paradigmshift in universities. Theoretically, this is one of the first studies which provided acomprehensive framework to start the student e-learning system as post-effect of COVID-19.Various studies are available in the literature addressing student’s e-learning; however, this isthe first study which considered the post-effect of COVID-19. Second, the study is among thepioneering study that proposed a framework to develop a good online learning systemwhichcan promote university brand image. Therefore, this study contributed to the literature bydeveloping a framework in response to the COVID-19. Third, the current study fills the gap byexploring the post-effect of COVID-19 in the context of a South Asia country and targetedmost affected countries from COVID-19. Fourth, this is the unique study that investigatedthat in the worse condition of COVID-19, ICT, e-service quality and e-information quality arethe major weapons of students’ e-learning. Along with this contribution, the current studyalso contributed that to launch e-learning effectively, universities require a good brand imagewhich is possible by promoting e-WOM and student satisfaction.

7.2 Practical implicationsAlong with the theoretical implications, the current study also has significant practicalimplications. Particularly, the current study is most important for universities to start thee-learning system in the current COVID-19 situation which is leading to the paradigm shift inthe education system. This study is helpful because the current situation of COVID-19required a paradigm shift in the education industry. This study is important because theframework of the study can be implemented in universities to develop an online learningsystem to facilitate a paradigm shift in universities. Due to the COVID-19, universities areunable to continue the normal procedure, in this direction, the current study proposed aframework to develop a good online learning system which can promote university brandimage. Currently, universities are facing various issues while developing an online learningsystem. In this situation, the current study highlighted that proper implementation of ICT canresolve these issues. Therefore, this study has unique implications for universities todevelop an e-learning platform to continue university operations in such a unique situation

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of COVID-19. The current study also suggested to the universitymanagement that to developa good online learning system, universities should promote ICT, e-service quality ande-information quality. The results of this study provided the implications to enhance brandimage through e-WOM and student satisfaction. Hence, along with other implications, themajor practical implication of this study is that this study providing the solution to resolvevarious issues related to the online learning system as a post-effect of COVID-19. Hence, acritical contemporary issue for governments, higher education commissions and universitiesto understand the antecedents to the online learning system and their relationship withuniversities brand image, the current study has unique insights that are helping universitiesto fight with COVID-19.

These results are significant for the universities while starting students’ e-learning due tothe effect of COVID-19 which a paradigm shift in the education industry, particularly inuniversities. To assist the paradigm shift, ICT must include important elements: advantage,compatibility, ease to use and perception. Universities should implement e-services andimprove the e-service quality which is quite helpful to develop e-learning among universities inthe current lockdown situation due to COVID-19 to support paradigm shift. Therefore, duringthe paradigm shift process and while adopting online learning, universities must focus on ICTalong with tangibility, reliability, responsiveness and assurance. Moreover, while startingstudents’ e-learning, universities will also benefit through e-WOM. Therefore, with the help of aparadigm shift, universities can continue their operations through online learning by applyingthe aforementioned elements in the situation of COVID-19. Majorly, this study has vitalimplications for the government of Pakistan, as in the critical situation of COVID-19,universities are unable to carry on the education system. Therefore, this study suggested acomprehensive framework for online learning in universities. Furthermore, this study is alsohelpful for the teachers to deliver lectures online byusing the online learningplatform. Studentscan also continue their normal activities to learn with the help of the online education system.Therefore, this study provided a solution for universities to continue their normal activities.

8. Limitations and future directionsAlthough the current study has a significant contribution to the literature and practice,however, this study also has few limitations which could be the future directions. First, theresults of this study are majorly applicable to the developing countries where the onlineeducation system is at the initial stage. However, the online learning system is wellestablished in most of the developed countries. Future research should be carried out indeveloped countries by extending the current research framework. Second, this study onlyprovided the framework for the online learning system; however, universities are facingseveral problems to implement online learning system. Therefore, future studies shouldaddress the problems facing by the universities in online learning along with the possiblesolution. Third, this study is based on questionnaire survey, however, to get a clear picture ofonline learning, future studies should also include interviews of higher authorities inuniversities.

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About the authorsSidra Shehzadi is a Ph.D candidate of Communication studies from school of Multimedia Technologyand Communication, UUM. Her research areas are marketing communication, corporatecommunication, public relations and advertising. She has 3 years working experience as a lecturerand visiting lecturer in various public and private sector colleges and universities. She has taught Newmedia and communication, PR & advertising, Introduction to mass communication, Risk management,Communication theories, training and development and these all combine to support her hybridprofession linking with communication and management. Sidra Shehzadi is the corresponding authorand can be contacted at: shehzadisidra3@gmail.com

Dr Qasim Ali Nisar is working as Assistant Professor at faculty of Business Administration andManagement Sciences, Superior University Lahore. He has more than 5 years of teaching experience indifferent public and private universities and has number of research publications in international wellreputed (SSCI, ESCI, Scopus, ABDC, and HEC indexed) journals. His research areas includes emotionsmanagement, big data management, organizational behaviors and human resource management. He isthe director of Research Solutions Consultancy and organized more than 50 training workshops ondifferent statistical tools (Smart PLS, AMOS, SPSS, and NVivo) in Malaysia, Indonesia and Pakistan.

Dr Muhammad Sajjad Hussain is working as visiting faculty of University of Management andTechnology. He has more than 7 years of teaching experience in different private universities andcolleges and has number of research publications in international well reputed journals. He is theassistant director of Research Solutions Consultancy, and organized training workshops on differentstatistical tools.

Muhammad Farhan Basheer currently works at the School of Economics, Finance and Banking(SEFB), University Utara Malaysia. Muhammad does research in Business Economics, Operationalmanagement and Financial Economics. His current projects are ‘Pyramidal ownership and firmperformance’, Agency Theory, and Entrepreneurial Finance.

Waseem Ul Hameed is an Assistant Professor at Department of Management Sciences (DMS), TheIslamia University of Bahawalpur (IUB), Pakistan. He is a former bank employee. He receives his PhD in

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Finance and Banking from Universiti Utara Malaysia (UUM), Malaysia and has published his works inreputed journals including Sustainability, Asian Women, International Journal of Finance andEconomics, European Journal of International Management, Uncertain Supply Chain Management,Management Sciences letters, Calitatea, Pakistan Journal of Humanities and Social Sciences, Journal ofGlobal Entrepreneurship Research, Social Sciences, and Journal of Applied Economics and BusinessResearch, among others. His research areas include microfinance, women-empowerment, open-innovation, entrepreneurship, hospitality management, banking and finance.

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