Introduction

AJA

Arab J. Admin.

1110-5453 2663-4473

The Arab Journal of Administration

Arab Administrative Development Organization, League of Arab States

Cairo, Egypt

10.21608/aja.2023.208530.1435

875

Research Article

Evaluation of E-service Quality and its Impact on Customer Satisfactions for Mobile Commerce Applications in Egypt

Morsi

Shereen

shereen_morsi@aast.edu

Business Information Systems Department College of Management & Technology Arab Academy for Science, Technology & Maritime Transport

Egypt

07 2023

02 2026

05 2023 06 2023 26 01 2026 46 1 311 328

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).

Since the COVID-19 pandemic, mobile commerce (m-commerce) is increasing as a global phenomenon, and Egypt is no exception. The implementation of quality management practices in m-commerce applications is crucial for enhancing user satisfaction and increasing customer loyalty. However, little work introduced for evaluating the quality of e-service for m-commerce provided to consumers. In addition, the adoption of such practices is a new and emerging area that requires further research and investigation, where finding and determining the factors that should be considered for implementing quality management practices in m-commerce applications is necessary. Therefore, in this study, a proposed model to e-service quality (e-SERVQ) in m-commerce applications by using the modified SERVQUAL model has been introduced. The proposed model included six dimensions, and was empirically evaluated using online survey data collected from 421 online consumers responding about their perceptions of e-service quality provided through m-commerce applications, and the data tested by using structural equation modelling (PLS). The analytical results showed that the six dimensions namely, information quality, responsiveness, reliability, personalization, usability, and security were found to have significant influence on e-SERVQ, leading to significant influence on customer satisfaction. These findings contribute to the current insights of the existing literature on e-service quality in the m-commerce field. Besides, the results can be used by online businesses in Egypt to develop their strategies for improving e-SERVQ that meet customer expectations across multiple dimensions and enhance the satisfaction and loyalty of customers.

E-service Quality SERVQUAL Model Mobile Commerce Applications E-satisfaction E-loyalty

Introduction

M-commerce businesses worldwide, including those in Egypt, have been significantly affected by the COVID-19 pandemic. Social distancing and restrictions increased demand for online shopping and m-commerce applications. Consumers have shifted from physical stores to mobile applications, with smartphones becoming the primary internet device. M-commerce applications let retailers present their brand and create shopping experiences even when users are not in physical stores. The rapid adoption of mobile shopping has transformed markets, supplanting traditional online shopping. Smartphones now include many apps and mobile internet features, simplifying online shopping; wearable devices (e.g., smartwatches) also enable m-commerce.

M-commerce refers to buying, selling, advertising, and conducting business while on the move. In Egypt, common m-commerce apps include Amazon, OLX, noon, Mazadat, Almowafir, B.TECH, Raneen, RayaShop, Sharwa, among others. Convenience in search, evaluation, purchase, and post-purchase makes mobile devices efficient shopping platforms. Users are migrating from electronic to mobile channels for more satisfying experiences; merchants integrate mobile shopping with physical stores to compete in multichannel retail.

Rising customer use of m-commerce apps intensifies competition, challenging firms to attract and retain customers. Both offline and online businesses must deliver value and excellent experiences. Many retailers moved online during the pandemic, facing global e-competitors; strong value propositions and personalization are critical. M-commerce apps identify users and deliver solutions to improve satisfaction and loyalty, with features for accessibility and user-friendliness. Yet virtual channels pose risks: security, responsiveness, transparency, and information protection are key concerns. Retailers must clearly communicate policies and ensure data protection. Strategic, well-documented plans are needed to deliver high e-service quality.

Few studies examined how e-SERVQ factors relate to overall e-SERVQ, satisfaction, and loyalty in m-commerce. Not all e-SERVQ scales suit m-commerce; inappropriate scales add complexity and mis-evaluation. A comprehensive framework for e-SERVQ in m-commerce is lacking, and research on e-SERVQ evaluation, especially in Egypt, is scarce. This study addresses these gaps.

Literature Review Service Quality

Service quality is the customer’s evaluation of the overall excellence of received service. Improving service quality yields competitive advantage and affects satisfaction and behavior. In IS adoption, service quality is critical to success and has been extended to e-services. The SERVQUAL model (Parasuraman et al., 1988) measures service quality via gaps between expectations and perceptions; originally ten dimensions, reduced to five, widely applied to identify improvement areas.

E-Service Quality (e-SERVQ)

E-SERVQ adapts traditional service quality to online contexts, defined as how well a website enables effective browsing, buying, and receiving goods/services while enhancing consumer trust and commitment. It is key to IS success in e-service channels. Early work (Dabholkar et al., 1996) identified six dimensions; later models adapted SERVQUAL to e-services (e.g., Zeithaml et al., 2002; E-S-QUAL/E-RecS-QUAL). Critics note e-services differ: less physicality and human interaction, self-service, two-way digital interaction, and virtual marketplaces. Thus, measuring e-SERVQ differs from physical service quality, and generic SERVQUAL may be unsuitable without adaptation.

Significance of e-SERVQ to Customer Satisfaction and Loyalty

Customer satisfaction is a post-use evaluation of fulfillment and enjoyment. Most studies find perceived e-SERVQ significantly affects satisfaction; some find no effect. Better e-SERVQ increases satisfaction and fosters loyalty. Loyalty is the desire to revisit and recommend; satisfaction–loyalty links are well-established. Frameworks show overall e-SERVQ drives satisfaction and repurchase intentions; satisfaction also drives repurchase. In m-commerce, loyalty is vital due to intense competition and acquisition cost. Loyalty comprises behavioral (repeat purchase) and attitudinal (emotional commitment, recommendation) aspects. Measures include repurchase intention and willingness to recommend.

Research Questions and Hypotheses

Given differences between m-commerce and traditional e-commerce, e-SERVQ measurement requires context-specific factors. Prior work links e-SERVQ to satisfaction and loyalty in e-commerce; m-commerce needs further examination. This study aims to develop an e-SERVQ framework for m-commerce apps and test effects on satisfaction and loyalty.

Research questions: Q1: What is the impact of m-commerce apps’ e-SERVQ dimensions on users’ satisfaction? Q2: What impact does users’ satisfaction have on customer loyalty?

The proposed model (adapted from SERVQUAL) includes six dimensions: information quality, usability, reliability, responsiveness, security, personalization. Hypotheses:

H1: Information quality positively impacts e-SERVQ.

H2: Usability significantly impacts e-SERVQ.

H3: Responsiveness significantly impacts e-SERVQ.

H4: Reliability positively associates with e-SERVQ.

H5: Personalization significantly impacts e-SERVQ.

H6: Security positively impacts e-SERVQ.

H7: e-SERVQ significantly impacts customer satisfaction.

H8: Customer satisfaction positively impacts customer loyalty.

Figure 1. Structural model

Table 1. Attributes of e-SERVQ

Construct	Definition	References
Information Quality	Extent to which m-commerce apps provide excellent quality content	Blut et al. (2015); Holloway & Beatty (2008)
Usability	How well-organized and effortless navigation is in m-commerce apps	Thakur (2018)
Responsiveness	Efficient management of issues and returns via m-commerce apps	Zemblyte (2015)
Reliability	Degree to which m-commerce apps deliver services as pledged and operate accurately	Zhang et al. (2021)
Personalization	Degree to which the app can be customized to individual preferences and histories	Zhang et al. (2021); Blut et al. (2015)
Security	Customer confidence that the app safeguards personal information and prevents unauthorized access	Blut et al. (2015); Holloway & Beatty (2008)
Customer Satisfaction	User sentiment/perception toward a good or service after use	Fornell (1992)
Customer Loyalty	Connection and dedication motivating repeat purchase and reduced switching	Oliver (1997); Ahmad et al. (2017)

Methodology Data Collection

Target population: Egyptian internet users (male/female, age >17) with experience using mobile apps and having purchased products/services via mobile apps. An online questionnaire (Google Forms) was distributed via Facebook and WhatsApp from 15 Sep 2022 to 22 Oct 2022. Respondents answered based on their most recent m-commerce app experience. Total responses: 451; 30 without relevant experience removed; final sample: 421.

Power analysis (G*Power; effect size 0.15, α=0.05, power 0.95, 8 variables) indicated minimum N=170; the obtained N=421 exceeds this.

Measurement

Eight constructs measured with 5-point Likert (1=strongly disagree, 5=strongly agree). Items adapted from prior validated scales:

Information quality (3 items; Blut et al., 2015; Holloway & Beatty, 2008)

Usability (4 items; Thakur, 2018)

Responsiveness (3 items; Zemblyte, 2015)

Reliability (5 items; Zhang et al., 2021)

Personalization (3 items; Zhang et al., 2021; Blut et al., 2015)

Security (3 items; Blut et al., 2015; Holloway & Beatty, 2008)

Customer satisfaction (3 items; Fornell, 1997)

Customer loyalty (3 items; Hsu & Lin, 2010; Oliver, 1997)

Data Analysis

SPSS used for data cleaning, descriptives, normality. PLS-SEM (SmartPLS) used to assess measurement and structural models, chosen for prediction focus, handling complex models, and modest sample size requirements.

Results Sample Characteristics

Gender: 68.1% female, 31.8% male. Age: 18–25 (11.8%), 26–35 (36.3%), 36–45 (31.1%), >45 (20.6%). Education: High school (22.5%), Bachelor’s (68.8%), Post-graduate (8.5%). Preferred m-commerce app: OLX Egypt (52.9%), Amazon (21.6%), Noon (8.7%), Alibaba (6.4%), Defacto (5.4%), Others (4.7%).

Table 2. Sample Demographics Analysis (N = 421)

Characteristics	Categories	Frequency	Percent (%)
Gender	Male	134	31.8
Gender	Female	287	68.1
Age	18–25	50	11.8
Age	26–35	153	36.3
Age	36–45	131	31.1
Age	>45	87	20.6
Education	High school	95	22.5
Education	Bachelor’s degree	290	68.8
Education	Post-graduate	36	8.5
Preferred mobile app	OLX Egypt	223	52.9
Preferred mobile app	Amazon	91	21.6
Preferred mobile app	Noon	37	8.7
Preferred mobile app	Alibaba	27	6.4
Preferred mobile app	Defacto	23	5.4
Preferred mobile app	Others	20	4.7

Measurement Model

Convergent validity: factor loadings 0.729–0.928 (>0.70), CR 0.770–0.896 (>0.70), AVE 0.517–0.751 (>0.50). VIF 1.436–2.935 (<10) indicates no multicollinearity. Discriminant validity: HTMT values <0.90.

Table 3. Measurement Model Validity (N = 421)

Construct	Item	Factor loading	VIF	Cronbach alpha	CR	AVE
Information Quality	INFQ1	0.888	2.179	0.829	0.830	0.618
Information Quality	INFQ2	0.858	1.951
Information Quality	INFQ3	0.844	1.723
Usability	USB1	0.863	2.206	0.856	0.860	0.600
Usability	USB2	0.840	2.002
Usability	USB3	0.851	2.195
Usability	USB4	0.787	1.664
Responsiveness	RES1	0.830	1.596	0.758	0.770	0.517
Responsiveness	RES2	0.780	1.436
Responsiveness	RES3	0.851	1.599
Reliability	RLB1	0.844	2.336	0.893	0.896	0.628
Reliability	RLB2	0.791	1.982
Reliability	RLB3	0.869	2.730
Reliability	RLB4	0.888	2.935
Reliability	RLB5	0.797	1.918
Personalization	PER1	0.861	1.925	0.866	0.867	0.684
Personalization	PER2	0.901	2.553
Personalization	PER3	0.902	2.562
Security	SEC1	0.909	2.289	0.857	0.861	0.751
Security	SEC2	0.928	2.176
Security	SEC3	0.729	1.942
Customer Satisfaction	CSF1	0.753	1.984	0.856	0.861	0.668
Customer Satisfaction	CSF2	0.836	2.167
Customer Satisfaction	CSF3	0.859	2.345
Customer Loyalty	LOY1	0.839	2.242	0.860	0.863	0.673
Customer Loyalty	LOY2	0.850	2.146
Customer Loyalty	LOY3	0.770	2.154

Table 4. Fornell–Larcker Criterion and Heterotrait–Monotrait (HTMT)

	Cust_Loy	Cust_Sat	E_Serv_Q	Info_Qual	PER	REL	RES	SEC	USB
Cust_Loy	—	0.891	0.766	0.658	0.650	0.684	0.775	0.675	0.575
Cust_Sat	0.891	—	0.834	0.723	0.711	0.781	0.801	0.730	0.605
E_Serv_Q	0.766	0.834	—	0.843	0.887	0.841	0.803	0.794	0.895
Info_Qual	0.658	0.723	0.843	—	0.650	0.713	0.827	0.583	0.887
PER	0.650	0.711	0.887	0.650	—	0.823	0.781	0.617	0.590
REL	0.684	0.781	0.841	0.713	0.823	—	0.854	0.588	0.642
RES	0.775	0.801	0.803	0.827	0.781	0.854	—	0.705	0.879
SEC	0.675	0.730	0.794	0.583	0.617	0.588	0.705	—	0.526
USB	0.575	0.605	0.895	0.887	0.590	0.642	0.879	0.526	—

Notes: Info_Qual = Information Quality; PER = Personalization; REL = Reliability; RES = Responsiveness; SEC = Security; USB = Usability; Cust_Sat = Customer Satisfaction; Cust_Loy = Customer Loyalty.

Structural Model

Bootstrapping (5,000 subsamples) shows all hypothesized paths significant (p<0.05). e-SERVQ predicts customer satisfaction (β=0.750, p<0.001); satisfaction predicts loyalty (β=0.790, p<0.001). R²: Satisfaction 0.562; Loyalty 0.624.

Figure 2. Total model (PLS results)

Table 5. Hypothesis testing

Hypothesis	Relationship	Beta	STDEV	t	Supported
H1	Info_Qual → e-SERVQ	0.181	0.006	29.529	Yes
H2	USB → e-SERVQ	0.210	0.008	26.323	Yes
H3	RES → e-SERVQ	0.173	0.006	28.892	Yes
H4	REL → e-SERVQ	0.306	0.010	30.339	Yes
H5	PER → e-SERVQ	0.189	0.008	23.632	Yes
H6	Security → e-SERVQ	0.151	0.008	19.677	Yes
H7	e-SERVQ → Cust_Sat	0.750	0.029	26.157	Yes
H8	Cust_Sat → Cust_Loy	0.790	0.026	30.488	Yes

Dependent variable	R-square	R-square adjusted
Customer_Loyalty	0.624	0.623
Customer_Satisfaction	0.562	0.561

Discussion

Reliability is the strongest predictor of e-SERVQ and satisfaction, aligning with prior online settings research. Usability, personalization, information quality, responsiveness, and security also positively affect satisfaction. Information quality significantly shapes e-SERVQ, supporting the need for rich product/service descriptions. Satisfaction positively affects loyalty; satisfied users intend to repurchase and recommend, consistent with prior studies.

Implications

Theoretical: Extends m-commerce and service research by evidencing predictive power of e-SERVQ dimensions (reliability, usability, responsiveness, personalization, security, information quality) on satisfaction and loyalty, and by showing satisfaction mediates effects on loyalty.

Practical: M-commerce providers should enhance information quality, responsiveness, and personalization; ensure reliability, usability, and security; and design value-added services (e.g., sign-up discounts, birthday coupons, free shipping, exclusive pricing) to boost satisfaction and loyalty.

Conclusion

This study develops and tests an e-SERVQ framework for m-commerce apps in Egypt. All six e-SERVQ dimensions significantly influence e-SERVQ, which drives satisfaction, which in turn drives loyalty. Findings guide app providers and online retailers to prioritize reliability, usability, security, responsiveness, personalization, and information quality, and to craft value-added offerings to sustain loyalty and long-term success.

References

Ahmad

Rahman

Khan

M. N.

2017

Exploring the role of website quality and hedonism in the formation of e-satisfaction and e-loyalty: Evidence from internet users in India

Journal of Research in Interactive Marketing 11 3 246 267

Alarif

A. A.

Husain

K. S.

2021

The influence of Internet banking services quality on e-customers’ satisfaction of Saudi banks: Comparison study before and during COVID-19

International Journal of Quality & Reliability Management 38 4 595 604

Aldholay

Isaac

Abdullah

Abdulsalam

Al-Shibami

A. H.

2018

An extension of Delone and McLean IS success model with self-efficacy: Online learning usage in Yemen

International Journal of Information and Learning Technology 35 4 285 304

10.1108/IJILT-11-2017-0116

Aksoy

Buoye

Aksoy

Larivière

Keiningham

T. L.

2013

A cross-national investigation of the satisfaction and loyalty linkage for mobile telecommunications services across eight countries

Journal of Interactive Marketing 27 1 74 82

Amin

2016

Internet banking service quality and its implication on e-customer satisfaction and e-customer loyalty

International Journal of Bank Marketing 34 3 280 306

Blut

Chowdhry

Mittal

Brock

2015

E-service quality: A meta-analytic review

Journal of Retailing 91 4 679 700

Blut

2016

E-service quality: Development of a hierarchical model

Journal of Retailing 92 4 500 517

Brent

2013

Antecedents to website satisfaction, loyalty and word-of-mouth

Journal of Information Systems & Technology Management 10 2 209 219

Carlson

O’Cass

2010

Exploring the relationships between e-service quality, satisfaction, attitudes and behaviours in content-driven e-service web sites

Journal of Services Marketing 24 2 112 130

Carlson

O’Cass

2011

Developing a framework for understanding e-service quality, its antecedents, consequences, and mediators

Managing Service Quality 21 3 264 286

Chang

H. H.

Chen

S. W.

2009

Consumer perception of interface quality, security, and loyalty in electronic commerce

Information and Management 46 7 411 417

Choi

J. H.

Seol

Lee

Cho

Park

2008

Customer satisfaction factors of mobile commerce in Korea

Internet Research 18 3 313 335

Choi

Kwon

Shin

2017

Location-based system: Comparative effects of personalization vs ease of use

Telematics and Informatics 34 91 102

Chen

Wang

2016

Customer participation, value co-creation and customer loyalty: A case of airline online check-in system

Computers in Human Behavior 62 346 352

Dabholkar

P. A.

Thorpe

D. I.

Rentz

J. O.

1996

A measure of service quality for retail stores: Scale development and validation

Journal of the Academy of Marketing Science 24 1 3 14

Dattalo

2008 Determining sample size: Balancing power, precision and practicality Oxford University Press

New York

Desmal

A. J.

Othman

M. K. B.

Hamid

S. B.

Zolait

A. H.

Kassim

N. B. A.

2019

Proposing a service quality framework for mobile commerce

International Conference for Emerging Technologies in Computing

Dumanska

Hrytsyna

Kharun

Matviiets

2021

E-commerce and M-commerce as global trends of international trade caused by the Covid-19 pandemic

WSEAS Transactions on Environment and Development 17 386 396

Egala

S. B.

Boateng

Mensah

S. A.

2021

To leave or retain? An interplay between quality digital banking services and customer satisfaction

International Journal of Bank Marketing 39 7 1420 1445

Felix

2017

Service quality and customer satisfaction in selected banks in Rwanda

Journal of Business & Financial Affairs 6 1 246 256

Fornell

1992

A national customer satisfaction barometer: The Swedish experience

Journal of Marketing 56 1 6 21

Faul

Erdfelder

Lang

A. G.

Buchner

2007

G* Power 3: A flexible statistical power analysis program for the social, behavioural, and biomedical sciences

Behavior Research Methods 39 2 175 191

Gounaris

Dimitriadis

Stathakopoulos

2010

An examination of the effects of service quality and satisfaction on customers’ behavioural intentions in e-shopping

Journal of Services Marketing 24 2 142 156

Hair

J. F.

Anderson

R. E.

Tatham

R. L.

Black

W. C.

1995 Multivariate data analysis 3rd

Macmillan Publishing Company

New York

Hair

J. F.

Ringle

C. M.

Sarstedt

2011

PLS-SEM: indeed, a silver bullet

Journal of Marketing Theory and Practice 19 2 139 152

Hair

J. F.

Hult

G. T. M.

Ringle

Sarstedt

2021 A primer on partial least squares structural equation modelling (PLS-SEM) 2nd

Sage Publications

Thousand Oaks, CA

Hair

J. F.

Hult

G. T. M.

Ringle

Sarstedt

2017 A primer on partial least squares structural equation modelling (PLS-SEM) Sage

Thousand Oaks

Hasanat

M. W.

Hoque

Shikha

F. A.

Anwar

Hamid

A. B. A.

Tat

H. H.

2020

The impact of coronavirus (Covid-19) on e-business in Malaysia

Asian Journal of Multidisciplinary Studies 3 1 85 90

Henseler

Ringle

Sarstedt

2015

A new criterion for assessing discriminant validity in variance-based structural equation modelling

Journal of the Academy of Marketing Science 43 1 115 135

Herington

Weaven

2009

E-retailing by banks: E-service quality and its importance to customer satisfaction

European Journal of Marketing 43 9/10 1220 1231

Hew

J. J.

Lee

V. H.

Ooi

K. B.

Lin

2016

Mobile social commerce: the booster for brand loyalty?

Computers in Human Behavior 59 142 154

Holloway

B. B.

Beatty

S. E.

2008

Satisfiers and dissatisfiers in the online environment: A critical incident assessment

Journal of Service Research 10 4 347 364

Hsin Chang

Wang

2011

The moderating effect of customer perceived value on online shopping behaviour

Online Information Review 35 3 333 359

Hsu

C. L.

Lin

J. C. C.

2010

A study of the adoption behaviour for in-car GPS navigation systems

International Journal of Mobile Communications 8 6 603 624

Huang

E. Y.

Lin

S. W.

Ya-Chu

2015

Mobile service quality measurement

Electronic Commerce Research and Applications 14 2 126 142

Kadry

El Hami

2017 Innovations in E-systems for Business and Commerce Apple Academic Press

Kalia

Paul

2021

E-service quality and e-retailers: attribute-based multidimensional scaling

Computers in Human Behavior 115

106608

Khan

M. A.

Zubair

S. S.

Malik

2019

An assessment of e-service quality, e-satisfaction and e-loyalty: Case of online shopping in Pakistan

South Asian Journal of Business Studies 8 3 283 302

Kao

T. W. D.

Lin

W. T.

2016

The relationship between perceived e-service quality and brand equity: A simultaneous equations system approach

Computers in Human Behavior 57 208 219

Kansra

Jha

A. K.

2016

Measuring service quality in Indian hospitals: an analysis of SERVQUAL model

International Journal of Services and Operations Management 24 1 1 17

Kim

Wang

Roh

2021

Do information and service quality affect perceived privacy protection, satisfaction, and loyalty? Evidence from a Chinese O2O based mobile shopping application

Telematics and Informatics 56

101483

Kitapci

Akdogan

Dortyol

I. T.

2014

The impact of service quality dimensions on patient satisfaction, repurchase intentions and word-of-mouth communication in the public healthcare industry

Procedia - Social and Behavioral Sciences 148 161 169

Kock

Hadaya

2018

Minimum sample size estimation in PLS-SEM: The inverse square root and gamma-exponential methods

Information Systems Journal 28 1 227 261

Knezevic

Delic

2017

Young customers’ perception of problems and usefulness of mobile shopping applications

Young Consumers 5 1 43 58

Jalil

Kaur

Jogia

A. V.

2021

The impact of e-service quality on customer loyalty in United Kingdom

International Journal of Applied Business and Management Studies 6 1 69 90

Jeyaraj

2020

DeLone & McLean models of information system success: critical meta-review and research directions

International Journal of Information Management 54

102139

Lee

W. O.

Wong

L. S.

2015

Determinants of mobile commerce customer loyalty in Malaysia

6th International Research Symposium in Service Management

64 60 67

Laudon

K. C.

Traver

C. G.

2021 E-commerce 2020-2021: Business, technology and society 16th

Pearson Education

Lee

S. M.

Kim

H. K.

2022

A study on the effect of service quality on satisfaction and corporate image in enterprise exhibition hall: Focusing on Korean coffee

Journal of Logistics, Informatics and Service Science 9 2 82 99

Reima

2009

A proposed scale for measuring e-service quality

Science and Technology 2 1 11

Mahapatra

2017

Mobile shopping among young consumers: An empirical study in an emerging market

International Journal of Retail & Distribution Management 45 9 930 949

Nandankar

Sachan

Mukherjee

Adhikari

2021

Electronic service quality (e-SQ) measurement: A cross-functional review

International Journal of Quality & Reliability Management

Nilashi

Ibrahim

Mirabi

V. R.

Ebrahimi

Zare

2015

The role of security, design and content factors on customer trust in mobile commerce

Journal of Retailing and Consumer Services 26 57 69

F. Z. X.

Yap

H. Y.

Tan

G. W. H.

P. S.

Ooi

K. B.

2022

Fashion shopping on the go: A dual-stage predictive-analytics SEM-ANN analysis on usage behaviour, experience response and cross-category usage

Journal of Retailing and Consumer Services 65

102851

Oliver

R. L.

1997 Satisfaction: A behavioural perspective on the consumer Irwin/McGraw-Hill

New York

Omar

Mohsen

Tsimonis

OoZeerally

Hsu

J.-H.

2021

M-commerce: The nexus between mobile shopping service quality and loyalty

Journal of Retailing and Consumer Services 60

102468

Parasuraman

Zeithaml

V. A.

Berry

L. L.

1988

SERVQUAL: A multiple item scale for measuring consumer perceptions of service quality

Journal of Retailing 64 1 12 40

Parasuraman

Zeithaml

V. A.

Malhotra

2005

ES-QUAL: A multiple-item scale for assessing electronic service quality

Journal of Service Research 7 3 213 233

Pantano

Priporas

C. V.

2016

The effect of mobile retailing on consumers’ purchasing experiences: A dynamic perspective

Computers in Human Behavior 61 548 555

Rita

Oliveira

Farisa

2019

The impact of e-service quality and customer satisfaction on customer behaviour in online shopping

Heliyon 5 10

e02690

Raza

S. A.

Umer

Qureshi

M. A.

Dahri

A. S.

2020

Internet banking service quality, e-customer satisfaction and loyalty: The modified e-SERVQUAL model

The TQM Journal 32 6 1443 1466

Reichheld

F. F.

Schefter

2000

E-loyalty: Your secret weapon on the web

Harvard Business Review 78 4 105 113

Rizan

Warokka

Listyawati

2014

Relationship marketing and customer loyalty: Do customer satisfaction and customer trust really serve as intervening variables?

Journal of Marketing Research and Case Studies 1 12

Sardjono

Selviyanti

Mukhlis

Tohir

2021

Global issues: Utilization of e-commerce and increased use of mobile commerce application as a result of the covid-19 pandemic

Journal of Physics 1832 12 24

Sauro

2015 Customer analytics for dummies Wiley

Newark, NJ

Santos

2003

E-service quality: A model of virtual service quality dimensions

Managing Service Quality 13 3 233 246

Seung-Wan

2022

A study on the effect of service quality on satisfaction and corporate image in enterprise exhibition hall

Journal of System and Management Sciences 12 2 443 461

Shafee

M. M.

Bazargan

N. A.

2018

Behavioural customer loyalty in online shopping: The role of e-service quality and e-recovery

Journal of Theoretical and Applied Electronic Commerce Research 13 1 26 38

Sørum

Andersen

K. N.

Vatrapu

2012

Public websites and human-computer interaction: An empirical study of measurement of website quality and user satisfaction

Behaviour & Information Technology 31 7 697 707

Swanson

S. R.

Chen

2016

The effects of perceived service quality on repurchase intentions and subjective well-being of Chinese tourists: The mediating role of relationship quality

Tourism Management 52 82 95

Swid

A. A.

El-Melegy

A. R.

2012

Management of e-services adoption in the telecommunications sector in Bahrain

Journal of Global Business & Technology 8 2 1 15

Thakur

2018

The role of self-efficacy and customer satisfaction in driving loyalty to the mobile shopping application

International Journal of Retail & Distribution Management 46 3 283 303

Peak

Prybutok

2015

A customer value, satisfaction, and loyalty perspective of mobile application recommendations

Decision Support Systems 79 171 183

Yan

L. Y.

Tan

G. W. H.

Loh

X. M.

Hew

J. J.

Ooi

K. B.

2021

QR code and mobile payment: the disruptive forces in retail

Journal of Retailing and Consumer Services 58

102300

Zemblyte

2015

The instrument for evaluating E-service quality

Procedia - Social and Behavioral Sciences 213 801 806

Zhang

Huang

Wang

A. G.

2015

E-service quality perceptions: An empirical analysis of the Chinese e-retailing industry

Total Quality Management & Business Excellence 26 11 1357 1373

Zeithaml

V. A.

1988

Consumer perceptions of price, quality and value: a means-end model and synthesis of evidence

Journal of Marketing 52 3 2 22

Zeithaml

V. A.

Parasuraman

Malhotra

2002

Service quality delivery through web sites: A critical review of extant knowledge

Journal of the Academy of Marketing Science 30 4 362 375

Zhang

Jun

Palacios

2021

M-shopping service quality dimensions and their effects on customer trust and loyalty: An empirical study

International Journal of Quality & Reliability Management

Safeddine

2017

Mobile commerce: Definition and scope