Mobile food ordering apps: An empirical study of the factors affecting customer e-satisfaction and continued intention to reuse

Abstract Mobile food ordering apps (MFOAs) have been widely considered in the restaurant sector as innovative channels to reach customers and provide them with high-quality services. However, there are important questions regarding the impact of implementing MFOAs on customer satisfaction and on customers’ intention to reuse such apps. Several studies have examined the outcomes of using MFOAs from the customer’s perspective. The fundamental purpose of this study is to identify and empirically examine the main factors predicting the e-satisfaction with MFOAs and customers’ intention to reuse such apps in Jordan. This research proposes an integrated model based on the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) and the features of MFOAs: online review, online rating, and online tracking. The data was collected from a convenience sample of Jordanian customers who have used MFOAs. The main results are based on structural equation modelling and support the role of online review, online rating, online tracking, performance expectancy, hedonic motivation, and price value on e-satisfaction and continued intention to reuse. This study provides a theoretical contribution and presents practical implications relevant to academics and practitioners working in areas related to MFOAs.

[1]  E. Anderson,et al.  The Antecedents and Consequences of Customer Satisfaction for Firms , 1993 .

[2]  Tao Zhou,et al.  An Empirical Examination of Initial Trust in Mobile Banking , 2011, Internet Res..

[3]  Manisha Sharma,et al.  Examining the role of trust and quality dimensions in the actual usage of mobile banking services: An empirical investigation , 2019, Int. J. Inf. Manag..

[4]  Yogesh Kumar Dwivedi,et al.  Finding and Ranking High-Quality Answers in Community Question Answering Sites , 2017, Global Journal of Flexible Systems Management.

[5]  Scott B. MacKenzie,et al.  Common method biases in behavioral research: a critical review of the literature and recommended remedies. , 2003, The Journal of applied psychology.

[6]  Faizan Ali,et al.  Psychological factors influencing customers’ acceptance of smartphone diet apps when ordering food at restaurants , 2018, International Journal of Hospitality Management.

[7]  A. Parasuraman,et al.  The Behavioral Consequences of Service Quality , 1996 .

[8]  J. Hair.  Multivariate data analysis : a global perspective , 2010 .

[9]  Barbara M. Byrne,et al.  Structural equation modeling with EQS : basic concepts, applications, and programming , 2000 .

[10]  Raffaele Filieri,et al.  E-WOM and Accommodation , 2014 .

[11]  Yogesh Kumar Dwivedi,et al.  Industrial Management & Data Systems Development of a survey instrument to examine consumer adoption of broadband , 2016 .

[12]  Yogesh Kumar Dwivedi,et al.  Using privacy calculus theory to explore entrepreneurial directions in mobile location-based advertising: Identifying intrusiveness as the critical risk factor , 2019, Comput. Hum. Behav..

[13]  Yogesh Kumar Dwivedi,et al.  Examining factors influencing Jordanian customers’ intentions and adoption of internet banking: Extending UTAUT2 with risk , 2018 .

[14]  Caroline Chan,et al.  Sharing Political Content in Online Social Media: A Planned and Unplanned Behaviour Approach , 2018, Inf. Syst. Frontiers.

[15]  Rolph E. Anderson,et al.  E‐satisfaction and e‐loyalty: A contingency framework , 2003 .

[16]  Steven M. Shugan.  The Impact of Advancing Technology on Marketing and Academic Research , 2004 .

[17]  Ing-Long Wu,et al.  Developing customer product loyalty through mobile advertising: Affective and cognitive perspectives , 2019, Int. J. Inf. Manag..

[18]  Yi-Shun Wang,et al.  Developing and validating a mobile catering app success model , 2019, International Journal of Hospitality Management.

[19]  Fred D. Davis,et al.  Toward preprototype user acceptance testing of new information systems: implications for software project management , 2004, IEEE Transactions on Engineering Management.

[20]  Karl G. Jöreskog,et al.  Lisrel 8: User's Reference Guide , 1997 .

[21]  Yogesh Kumar Dwivedi,et al.  SQ mGov: A Comprehensive Service-Quality Paradigm for Mobile Government , 2014, Inf. Syst. Manag..

[22]  Sajad Rezaei,et al.  Consumer experiences, attitude and behavioral intention toward online food delivery (OFD) services , 2017 .

[23]  B. Tabachnick,et al.  Using Multivariate Statistics , 1983 .

[24]  Christy M. K. Cheung,et al.  How Habit Limits the Predictive Power of Intentions: The Case of IS Continuance , 2007 .

[25]  Yogesh Kumar Dwivedi,et al.  Adoption of online public grievance redressal system in India: Toward developing a unified view , 2016, Comput. Hum. Behav..

[26]  E. Ofek,et al.  Case study second thoughts about a strategy shift , 2014 .

[27]  Adesegun Oyedele,et al.  Modeling satisfaction and repurchase intentions of mobile smart wristbands: the role of social mindfulness and perceived value , 2018, Young Consumers.

[28]  Anil Bilgihan,et al.  Proposing a model to test smartphone users' intention to use smart applications when ordering food in restaurants , 2014 .

[29]  Mark A. Bonn,et al.  Differences in perceptions about food delivery apps between single-person and multi-person households , 2019, International Journal of Hospitality Management.

[30]  Keng-Boon Ooi,et al.  Mobile social commerce: The booster for brand loyalty? , 2016, Comput. Hum. Behav..

[31]  Kieran Mathieson,et al.  Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior , 1991, Inf. Syst. Res..

[32]  Yogesh Kumar Dwivedi,et al.  Content design of advertisement for consumer exposure: Mobile marketing through short messaging service , 2017, Int. J. Inf. Manag..

[33]  Elena García Barriocanal,et al.  Evaluating content quality and helpfulness of online product reviews: The interplay of review helpfulness vs. review content , 2012, Electron. Commer. Res. Appl..

[34]  Fred D. Davis,et al.  Extrinsic and Intrinsic Motivation to Use Computers in the Workplace1 , 1992 .

[35]  Jill Mosteller,et al.  Online Reviewer Engagement , 2017 .

[36]  Victoria D. Bush,et al.  What We Know and Don't Know about Online Word-of-Mouth: A Review and Synthesis of the Literature , 2014 .

[37]  Shuai Yang,et al.  Brand engagement on social media: will firms’ social media efforts influence search engine advertising effectiveness? , 2016 .

[38]  H. Harman.  Modern factor analysis , 1961 .

[39]  Yogesh Kumar Dwivedi,et al.  Smart cities: Advances in research - An information systems perspective , 2019, Int. J. Inf. Manag..

[40]  I. Ajzen,et al.  The Influence of Attitudes on Behavior , 2005 .

[41]  Mojtaba Zare,et al.  The role of Security, Design and Content factors on customer trust in mobile commerce , 2015 .

[42]  June Lu,et al.  Are personal innovativeness and social influence critical to continue with mobile commerce? , 2014, Internet Res..

[43]  Donald Amoroso,et al.  The mediating effects of habit on continuance intention , 2017, Int. J. Inf. Manag..

[44]  Claude Sicotte,et al.  Modeling factors explaining the acceptance, actual use and satisfaction of nurses using an Electronic Patient Record in acute care settings: An extension of the UTAUT , 2015, Int. J. Medical Informatics.

[45]  Kent Eriksson,et al.  The adoption of commercial innovations in the former Central and Eastern European markets : The case of internet banking in Estonia , 2008 .

[46]  Yogesh Kumar Dwivedi,et al.  The battle of Brain vs. Heart: A literature review and meta-analysis of "hedonic motivation" use in UTAUT2 , 2019, Int. J. Inf. Manag..

[47]  Yujong Hwang,et al.  Mobile banking use: A comparative study with Brazilian and U.S. participants , 2019, Int. J. Inf. Manag..

[48]  Yogesh Kumar Dwivedi,et al.  Examining Adoption Behavior of Mobile Government , 2012, J. Comput. Inf. Syst..

[49]  Yogesh Kumar Dwivedi,et al.  Cronfa - Swansea University Open Access Repository , 2017 .

[50]  Yogesh Kumar Dwivedi,et al.  Service delivery through mobile-government (mGov): Driving factors and cultural impacts , 2014, Information Systems Frontiers.

[51]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[52]  Minna Pura.  Linking perceived value and loyalty in location‐based mobile services , 2005 .

[53]  Yogesh Kumar Dwivedi,et al.  Examining the impact of gamification on intention of engagement and brand attitude in the marketing context , 2017, Comput. Hum. Behav..

[54]  William B. Dodds,et al.  Effects of Price, Brand, and Store Information on Buyers’ Product Evaluations , 1991 .

[55]  J. Nunnally.  Psychometric Theory (2nd ed), New York: McGraw-Hill. , 1978 .

[56]  David Schuff,et al.  What Makes a Helpful Review? A Study of Customer Reviews on Amazon.com , 2010 .

[57]  Yogesh Kumar Dwivedi,et al.  The effect of telepresence, social presence and involvement on consumer brand engagement: An empirical study of non-profit organizations , 2018 .

[58]  Wenhua Liu,et al.  The effects of value co-creation practices on building harmonious brand community and achieving brand loyalty on social media in China , 2015, Comput. Hum. Behav..

[59]  Fabrizio Bert,et al.  Smartphones and Health Promotion: A Review of the Evidence , 2013, Journal of Medical Systems.

[60]  Silas Formunyuy Verkijika,et al.  Factors influencing the adoption of mobile commerce applications in Cameroon , 2018, Telematics Informatics.

[61]  Ali Abdallah Alalwan,et al.  Investigating the impact of social media advertising features on customer purchase intention , 2018, Int. J. Inf. Manag..

[62]  H. Yen,et al.  Internet retail customer loyalty: the mediating role of relational benefits , 2003 .

[63]  Yogesh Kumar Dwivedi,et al.  An empirical validation of a unified model of electronic government adoption (UMEGA) , 2017, Gov. Inf. Q..

[64]  Maged Ali,et al.  Perceived derived attributes of online customer reviews , 2016, Comput. Hum. Behav..

[65]  Ting Chi,et al.  Key factors influencing the adoption of apparel mobile commerce: an empirical study of Chinese consumers , 2018 .

[66]  B. Tabachnick,et al.  Using multivariate statistics, 5th ed. , 2007 .

[67]  Nina Michaelidou,et al.  Shopping motives as antecedents of e-satisfaction and e-loyalty , 2010 .

[68]  Hsi-Peng Lu,et al.  An examination of the celebrity endorsements and online customer reviews influence female consumers' shopping behavior , 2013, Comput. Hum. Behav..

[69]  Izak Benbasat,et al.  Virtual Product Experience: Effects of Visual and Functional Control of Products on Perceived Diagnosticity and Flow in Electronic Shopping , 2004, J. Manag. Inf. Syst..

[70]  Paul Jen-Hwa Hu,et al.  Modeling Citizen Satisfaction with Mandatory Adoption of an E-Government Technology , 2011, J. Assoc. Inf. Syst..

[71]  Yogesh Kumar Dwivedi,et al.  Homeworkers' usage of mobile phones; social isolation in the home-workplace , 2009, J. Enterp. Inf. Manag..

[72]  Karyn Rastrick,et al.  Impacts of website design on the adoption intention of mobile commerce: Gender as a moderator , 2014 .

[73]  Sue Newell,et al.  Communicational ambidexterity as a new capability to manage social media communication within organizations , 2015, J. Strateg. Inf. Syst..

[74]  Richard W. Brislin,et al.  Comparative Research Methodology: Cross-Cultural Studies , 1976 .

[75]  Martin Wetzels,et al.  More than Words: The Influence of Affective Content and Linguistic Style Matches in Online Reviews on Conversion Rates , 2013 .

[76]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[77]  Raffaele Filieri.  What makes online reviews helpful? A diagnosticity-adoption framework to explain informational and normative influences in e-WOM , 2015 .

[78]  Nicola Brace,et al.  SPSS for psychologists: a guide to data analysis using SPSS for Windows (versions 9, 10 and 11). 2nd edition , 2007 .

[79]  Viswanath Venkatesh,et al.  Model of Adoption and Technology in Households: A Baseline Model Test and Extension Incorporating Household Life Cycle , 2005, MIS Q..

[80]  Stuart J. Barnes,et al.  Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent dirichlet allocation , 2017 .

[81]  Serhat Murat Alagoz,et al.  A Study on Tam: Analysis of Customer Attitudes in Online Food Ordering System , 2012 .

[82]  Kevin K. W. Ho,et al.  Value co-creation and purchase intention in social network sites: The role of electronic Word-of-Mouth and trust - A theoretical analysis , 2014, Comput. Hum. Behav..

[83]  Yogesh Kumar Dwivedi,et al.  Investigating homeworkers' usage of mobile phones for overcoming feelings of professional isolation , 2008, Int. J. Mob. Commun..

[84]  Jamie Carlson,et al.  Feel the VIBE: Examining value-in-the-brand-page-experience and its impact on satisfaction and customer engagement behaviours in mobile social media , 2017, Journal of Retailing and Consumer Services.

[85]  Ingoo Han,et al.  The Effect of On-Line Consumer Reviews on Consumer Purchasing Intention: The Moderating Role of Involvement , 2007, Int. J. Electron. Commer..

[86]  Yogesh Kumar Dwivedi,et al.  An integrated model for m-banking adoption in Saudi Arabia , 2019, International Journal of Bank Marketing.

[87]  Angelika Dimoka,et al.  The Nature and Role of Feedback Text Comments in Online Marketplaces: Implications for Trust Building, Price Premiums, and Seller Differentiation , 2006, Inf. Syst. Res..

[88]  Kai H. Lim,et al.  Effects of conflicting aggregated rating on eWOM review credibility and diagnosticity: The moderating role of review valence , 2012, Decis. Support Syst..

[89]  Jalayer Khalilzadeh,et al.  Security-related factors in extended UTAUT model for NFC based mobile payment in the restaurant industry , 2017, Comput. Hum. Behav..

[90]  Yogesh Kumar Dwivedi,et al.  Reformation of public service to meet citizens' needs as customers: Evaluating SMS as an alternative service delivery channel , 2016, Comput. Hum. Behav..

[91]  Yogesh Kumar Dwivedi,et al.  Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a Revised Theoretical Model , 2017, Information Systems Frontiers.

[92]  Yogesh Kumar Dwivedi,et al.  A generalised adoption model for services: A cross-country comparison of mobile health (m-health) , 2016, Gov. Inf. Q..

[93]  Tahir M. Nisar,et al.  Brand interactions and social media: Enhancing user loyalty through social networking sites , 2016, Comput. Hum. Behav..

[94]  E. B. Andersen,et al.  Modern factor analysis , 1961 .

[95]  Agnes L. DeFranco,et al.  It's about time: Revisiting UTAUT2 to examine consumers’ intentions to use NFC mobile payments in hotels , 2016 .

[96]  Matthew K. O. Lee,et al.  The impact of electronic word-of-mouth: The adoption of online opinions in online customer communities , 2008, Internet Res..

[97]  Yogesh Kumar Dwivedi,et al.  Social media in marketing: A review and analysis of the existing literature , 2017, Telematics Informatics.

[98]  I. Simonson,et al.  What marketers misunderstand about online reviews , 2014 .

[99]  A. Kapoor,et al.  Technology at the dinner table: Ordering food online through mobile apps , 2018, Journal of Retailing and Consumer Services.

[100]  Nripendra P. Rana,et al.  Consumer use of mobile banking (M-Banking) in Saudi Arabia: Towards an integrated model , 2019, Int. J. Inf. Manag..

[101]  Sajad Rezaei,et al.  User satisfaction with mobile websites: the impact of perceived usefulness (PU), perceived ease of use (PEOU) and trust , 2014 .

[102]  Kun Chang Lee,et al.  Understanding factors affecting trust in and satisfaction with mobile banking in Korea: A modified DeLone and McLean's model perspective , 2009, Interact. Comput..

[103]  Kai-Yu Tang,et al.  Exploring the influential factors in continuance usage of mobile social Apps: Satisfaction, habit, and customer value perspectives , 2016, Telematics Informatics.

[104]  Rakhi Thakur,et al.  Understanding Customer Engagement and Loyalty: A Case of Mobile Devices for Shopping , 2016 .

[105]  Yogesh Kumar Dwivedi,et al.  Three dimensional product presentation quality antecedents and their consequences for online retailers: The moderating role of virtual product experience , 2017 .

[106]  Yogesh Kumar Dwivedi,et al.  Predicting the helpfulness score of online reviews using convolutional neural network , 2019, Soft Computing.

[107]  Gessuir Pigatto,et al.  Have you chosen your request? Analysis of online food delivery companies in Brazil , 2017 .

[108]  Amaradri Mukherjee,et al.  Investigating the effectiveness of retailers’ mobile applications in determining customer satisfaction and repatronage intentions? A congruency perspective , 2018, Journal of Retailing and Consumer Services.

[109]  Charlie C. Chen,et al.  Using social media to enrich information systems field trip experiences: Students' satisfaction and continuance intentions , 2016, Comput. Hum. Behav..

[110]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[111]  Michael R. Mullen,et al.  Structural equation modelling: guidelines for determining model fit , 2008 .

[112]  Yogesh Kumar Dwivedi,et al.  What do we know about consumer m-shopping behaviour? , 2017 .

[113]  Yogesh Kumar Dwivedi,et al.  Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust , 2017, Int. J. Inf. Manag..

[114]  Yogesh Kumar Dwivedi,et al.  Consumer adoption of mobile banking services: An empirical examination of factors according to adoption stages , 2018, Journal of Retailing and Consumer Services.

[115]  Moez Limayem,et al.  How Habit Limits the Predictive Power of Intention: The Case of Information Systems Continuance , 2007, MIS Q..

[116]  Yogesh Kumar Dwivedi,et al.  Advances in Social Media Research: Past, Present and Future , 2017, Information Systems Frontiers.

[117]  Viswanath Venkatesh,et al.  Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology , 2012, MIS Q..

[118]  Yogesh Kumar Dwivedi,et al.  Citizens’ adoption of an electronic government system: towards a unified view , 2015, Information Systems Frontiers.

[119]  I. G. Saura,et al.  Value dimensions, perceived value, satisfaction and loyalty: an investigation of university students’ travel behaviour , 2006 .

[120]  William B. Dodds,et al.  Effects of Price, Brand, and Store Information on Buyers’ Product Evaluations: , 1991 .

[121]  Hans van der Heijden,et al.  User Acceptance of Hedonic Information Systems , 2004, MIS Q..

[122]  Norman Shaw,et al.  The non-monetary benefits of mobile commerce: Extending UTAUT2 with perceived value , 2019, Int. J. Inf. Manag..

[123]  Wen-Yin Chen,et al.  The impact of inertia and user satisfaction on the continuance intentions to use mobile communication applications: A mobile service quality perspective , 2019, Int. J. Inf. Manag..