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K. Selvarajah T. Krishnan, Leong Kuok How
Business & Law, International University of Malaya-Wales, Kuala Lumpur, Malaysia
Correspondence to: K. Selvarajah T. Krishnan, Business & Law, International University of Malaya-Wales, Kuala Lumpur, Malaysia.Email: |
Copyright © 2016 Scientific & Academic Publishing. All Rights Reserved.
This work is licensed under the Creative Commons Attribution International License (CC BY).
http://creativecommons.org/licenses/by/4.0/
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Abstract
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Mobile apps is becoming more popular than desktop application usage nowadays. The designs of mobile apps needs to produce the most desired amount of downloads. This paper explore the attractiveness of mobile apps on Gen Z’s intention to download the apps. Lack of study in literature review on mobile apps’ download, therefore the findings provide an exploration on effective marketing mix to increase mobile apps downloads. Theory of Reason Action (TRA) will be able to analyze the attractiveness of mobile apps designs on the Gen Z’s intention to download the mobile apps.Simple random sampling techniques was used and self-administered questionnaire was distributed by mail to students. The research findings provide the information academically and practically for industry regarding the designs of mobile apps and the intention to download by Gen Z.
Keywords: Mobile Apps, Gen Z, Marketing Mix and Malaysia
Cite this paper: K. Selvarajah T. Krishnan, Leong Kuok How, The Effect of Mobile Apps on Gen Z’s Intention to Download Apps in Malaysia, International Journal of Advanced and Multidisciplinary Social Science, Vol. 2 No. 3, 2016, pp. 51-60. doi: 10.5923/j.jamss.20160203.01.
Article Outline
- 1. Introduction
- 2. Literature Review
- 3. Methodology
- 4. Finding and Conclusions
1. Introduction
- In recent years, the increasing number of smartphone subscribers has driven the usage of mobile application software for mobile devices, commonly referred to as mobile ‘‘apps’’. Originally, ‘‘app’’ referred to software for general productivity and information retrieval purposes, including email, calendar and contact management, and stock market quote and weather information lookup. However, a huge surge in user demand and the widespread availability of developer tools has driven a rapid expansion to include other categories of apps including games, e-books, utilities, social networking platforms and others providing access to information on business, finance, lifestyle and entertainment.The global mobile app market is expected to reach US$25 billion by 2015 (Markets and markets, 2010). In-Stat (2011) also projects 48 billion mobile application downloads annually by 2015. Despite the explosive growth of mobile application downloads, free apps accounted for up to 89% of global downloads in 2012 (Gartner, 2012), indicating that the market for paid apps is still in its infancy.According to Gupta (2013), the average smartphone user spends 82% of his mobile minutes using apps, with the remainder split between calling, e-mailing, and texting. Each of the leading smartphone operating system providers (Android, iOS, Windows Mobile etc.) also hosts an app marketplace from which users can download apps (Google Play, App Store and Windows Phone Store). To attract more users, many app publishers offer a basic/trial version of their apps for free and then charge a fixed monthly subscription fee for premium services. Others offer the full version for free and derive their revenue from advertising or in-app purchases that unlock additional functionality such as advertisement removal or value-added content. Therefore, to reduce risk and uncertainty in buying a paid app, users generally start by using a trial or free version of a paid app first to become familiar with its content and functionality. Based on this initial experience with the trial or free version, they then determine whether or not to purchase the paid version (Whitfield, 2013). This is a typical digital business strategy for content providers (Singer-Oestreicher and Zalmanson, 2013). Consequently, the factors that contribute to user intention to purchase paid apps are an important consideration for app publishers and marketers.The purpose of this study is to examine apps users’ purchasing intention by modifying and extending the Theory of Reasoned model (TORA). Technology use research often focuses on the antecedents associated with intention to use a specific technology, or the actual use of such technology. Theories developed to explain this phenomenon include the technology acceptance model (Davis, 1989), the theory of reasoned of action (Ajzen and Fishbein, 1980; Fishbein and Ajzen, 1975), the theory of planned behaviour (Ajzen, 1991). More recent efforts reflect an attempt to apply these theories in an m-commerce setting. For example, Rao and Troshani (2007) develop a model of adoption intentions based on perceived usefulness and perceived ease of use, along with user predisposition and social influence. Maity (2010) extracts TAM-related factors, i.e. perceived usefulness and ease of use, as well as subjective norms, behavioural controls, self-efficacy and the role of alternate channels, from qualitative data on m-commerce usage. Khalifa and Shen (2008) apply the theory of planned behaviour – an extension of the theory of reasoned action – to develop an m-commerce framework, with adoption as the behavioural outcome predicted by perceived consequences of adoption, attitude and subjective norms. These studies, though, examine the antecedents of technology use without considering how respondents expect the technology to perform specifically.In addition, previous studies have verified that the determining factors of IT/IS adoption differ between potential users and experienced users (Dwivedi and Irani, 2009; Teo, 2006; Teo et al., 2009; Hsu and Lu, 2007). Hence, this study also aims to identify factors that influence purchasing intention for experienced users (i.e., users who have purchased apps before) and potential users (users who have not made prior purchases). Since different groups may exhibit different app preferences and purchasing behavior, the results can provide further insights for the design of app marketing strategies.
2. Literature Review
- E-commerce concerns electronic transactions of either financial or informational data between the company and any third party (Sila and Dobni, 2012) using the Internet (Li and Xie, 2012). Therefore, e-commerce does not only relate to the buying, sales and exchange of goods online (Grandona and Pearson, 2004), but also includes any transaction of information from consumers to the business or from the business to the consumer; including outbound emails or consumer enquiries (Chaffey et al., 2009). There are two main types of e-commerce: B2B (business to business) and B2C (business to consumer), whereby a business or an individual consumer transacts with another business via the ‘global networked environment;’ the Internet (Turban et al., 2002).M-commerce is the sub-set and extension of e-commerce (Turban et al., 2002), where product purchases have now moved onto mobile devices over a wireless network (Yeh and Li, 2009). It enables consumers to participate in e-commerce activities in an entirely new and innovative manner compared with existing shopping channels (Yang, 2010). Multimedia technology and innovations have turned mobile phones into portable computers, allowing consumers to access the Internet and information, equivalent to the experience of a laptop computer (Aldás -Manzano et al., 2009). Smartphone devices and web enabled portable devices such as the Apple iPad have allowed consumers another channel to access the Internet and retail stores (Zhou, 2013). Johnson et al., (2010) found that smart-phones are the fastest growing sales segment, offering Internet access to more and more mobile consumers. In fact, research figures from 2013 suggested that 30% of the world population (2.1 billion people) have a mobile broadband subscription (International Telecommunication Union, 2013). Mobile commerce sales regardless of category now equate to 33% of all online sales (IMRG, 2014), rising from 23% in 2013 (Capgemini, 2013) and 13.3% in 2012 (Tode, 2012); figures that indicate that the popularity of mobile purchasing is annually increasing (IMRG, 2014).App Design: The researcher agrees with the inclusion of the colour, typography, symbols and other graphic designstimuli as creating the visual identity of a brand (Abratt and Kleyn, 2012; Jun and Lee, 2007; Melewar and Saunders, 1998). It is therefore classified that the brand typeface, colour and symbols are sub-elements within the category of brand design; and consistent with other studies which regarded them as brand design stimuli (e.g. Rowley, 2009, Eroglu et al., 2003). Layout and presentation style have been added as additional sub-elements. This is due to their importance to the brand’s visual identity in an online or mobile environment, their inclusion as brand design stimuli within the literature (Rowley, 2004; Okonkwo, 2007; Harridge-March, 2006) and their connection with graphic design and delivering the brand identity (Abratt and Kleyn, 2012).Typeface: Practitioners and academics alike have noted the importance of typeface as a visual tool for communicatingthe brand’s objectives (Childers and Jass, 2002; Jun and Lee, 2007). The font can affect the consumer’s perception of the brand, memorability and influence its legibility (Childers and Jass, 2002). It is agreed by academics that typefaces affect consumer responses (Henderson et al., 2004) and is therefore important to the branding strategy of any company. Layout: The layout is the organisation of all of the images, text, headers and graphics and their arrangement on theonline page (Rowley, 2004; Harris and Goode, 2010). It relates to the placing of elements as well as the functionality and usage of navigation buttons to move around the site (Harris and Goode, 2010).Colour: Website colours, including fonts and background colours (Ha and Im, 2012) can have a significant effect onlevels of pleasure and arousal (Wu et al., 2008). The unique and representative colours of a brand are used online within text, backgrounds, menus and images (Rowley, 2009) in order to create an identifiable entity (Okonkwo, 2007). Colour palettes are ‘brand norm’ (Harridge-March, 2006) that help to epitomize brand values in a consistent manner across channels (Rowley, 2009). They are designed to deliver associated messages (Rowley, 2004) such as ‘fun’, ‘modern’, ‘warm’ and ‘friendly’; epitomizing the brand’s personality and identifying the brand’s character (De Chernatony and McDonald, 2003).Shapes/Icons: Shapes and icons work alongside the colours, typeface and overall presentation to increase theuser’spositivity towards a brand (Ha and Im, 2012). Shapes may include graphical buttons, the shapes of pictures, menu boxes (Rowley, 2004) or even the overall shape of the layout. Each will have been designed to communicate the brand’s visual identity and deliver an exciting experience (Wu et al., 2008). Rowley (2004) mentions that even by rounding the corners of a rectangular box, the brand can communicate an alternative message and style. ‘Symbol’ is utilized within the literature to refer to the logo attached to the brand name (Van Riel and Van den Ban, 2001). Yet, it could also relate to graphical symbols on a webpage or mobile app. Again, the symbols will have been designed to match the brand’s visual identity and personality. However, practitioners and developers in web design refer to such symbols as icons (Ha and Im, 2012).Imagery: Whereas imagery can be utilised for marketing and promotional purposes, the objective of brand imageryis to promote the brand’s values, image, lifestyle and personality (White et al., 2013; Eroglu et al., 2003). Imagery can include graphics, pictures, headers and background images, designed to visually represent such brand values (Rowley, 2004). They create an enjoyable, attractive (Chen and Dibb, 2010) and interactive web experience and can act as part of the functionality of a website through page links (Heeter, 2000; Page and Lepkowska-White, 2002). They additionally act as a web atmospheric, facilitating the overall feel of a site and offering information about the brand (Eroglu et al., 2003; Chen and Dibb, 2010). Website imagery has been found to heighten the user’s perception of the online store in terms of safety, convenience and enjoyability (Oh et al., 2008).Copy: Rowley (2004) refers to copy as the words written by the retailer to communicate with the consumer. It willhave been written with a tone of voice that defines the brand’s values and is consistent with the brand’s personality and message (Chaffey and Smith, 2008; Rowley, 2004).Sound/Video: Sound often forms an essential part of the traditional shopping experience for many consumers (Fioreand Kelly, 2007) as audio helps to represent the brand’s personality and lifestyle. It has been deemed as a form of verbal communication due to its purpose of communicating the brand message (Fiore and Kelly, 2007). Yet, research has found that many online consumers perceive website audio as unsatisfying and opt to mute automatic sound (Abdinnour-Helm et al., 2005). If sound is to be used in mobiles, similar issues will come into play, yet due to the more personal and public nature of mobile phone usage (Yang, 2010; Lee et al., 2011).Apps Promotion: Traditional marketing communications tools have been utilised by retail marketers for many years(Kitchen, 1996) and are still in current employment (Kotler and Keller, 2009), albeit in a modernised format. Yet there are a number of newer communications methods, such as interactive marketing and social media networking that have evolved due to the growth of digital media technologies (Smith, 2012). The following literature will discuss the tools of the Marketing Communications Mix (Kotler and Keller, 2009) and review the development of the newer, value-creating and conversational (Burton and Soboleva, 2011) tools for online and m-commerce marketing.Advertising: Advertisements can be distributed throughout a variety of media including radio, television (Kapoor,2003; Naik and Peters, 2009), newspapers and the Internet for example and are a non-personal presentation of goods and ideas (Kotler and Keller, 2009). They have the ability to reach a wide and dispersed audience (Cadden and Leuder, 2013) yet are often the most expensive form of promotion due to the use of models or celebrity endorsements (Lear et al., 2009).Direct Marketing: Direct marketing was traditionally executed via catalogues and mailing, sending messages directlyto the relevant consumer. Yet, modern direct messages are regularly sent via social media networks and push marketing techniques including emails, mobile app pop-ups and text messages (Lascu and Clow, 2007). The advantages of such media lies in their ability to reach the intended recipient of the message directly and form the connection needed to build brand loyalty (Lascu and Clow, 2007).Word of Mouth (WoM): Word of mouth promotion involves the transmission of marketing messages from peer topeer (Woerndl et al., 2008), whereby one consumer will recall their experience to another consumer, to spread the message. Due to the explosion of social media and blogging communities, word of mouth promotion is now much faster and more effective (Woerndl et al., 2008). It is therefore important that retailers utilise social media to announce promotions and information (Lin and Lekhawipat, 2014), to encourage sharing and increase the power of their messages.Sales Promotion: Sales promotions are intended to draw in a larger audience of consumers via the incentive of pricereductions and special offers (Álvarez and Casielles, 2005). The discounts, traditionally during the festive time or the change of season, ensure stock clearance, increase profits, attract new consumers and create excitement within the store (Fam, 2003; Tong et al., 2012). They also benefit the consumer via monetary savings, convenience, entertainment, exploration and an increase of quality perception (Weng and Cyril de Run, 2013).PR and Publicity: The role of the Public Relations (PR) team is to manage relationships and communications,encompassing public affairs, internal and corporate communications, media relations, community relations and managing issues related to the public view of the company (Gregory, 2011). In the UK, the term public relations is used interchangeably with corporate communications, as UK companies tend to employ staff to manage both internal and external communications, that aim to influence the positive perception of stakeholders, such as the press or affiliated businesses (Van Riel and Fombrum, 2007; Gregory, 2011). Due to the increase in the blogging community (Hsu et al., 2013).Personal Selling: Personal selling traditionally related to the one-to-one communication found within the retail storebetween consumer and sales staff (Hammann, 1979). For many years, academics and practitioners have been interested in how the performance of sales staff can affect retail sales (Churchill et al., 1985; Plouffe et al., 2010; Verbeke et al., 2011), and it has been found that supervisory coaching is essential for staff development (Shannahan et al., 2013). Yet, the online services cape lacks the physical presence of a sales person, and therefore retailers have attempted to recreate the experience of personal selling via personalised search results and recommendation systems (Lepkowska-White, 2013).Interactive Marketing: Marketing has shifted from a transaction-based activity to a conversational effort (Burtonand Soboleva, 2011). Yet, there is still confusion as to how to define and interpret interactivity (Koolstra and Bos, 2009). In one definition, interactivity is said to involve interpersonal communication between individuals and/or organisations via reactive communications (when messages respond to previous messages) and fully interactive communications (Burton and Soboleva, 2011) (whereby a conversation has a preceding thread) (Sundar et al., 2003). Such a definition could imply that the consumer has a platform on which to form an interaction with the company, such as the physical store, a chat forum or a social network, i.e. Twitter (Burton and Soboleva, 2011).
3. Methodology
- The paper focuses on males Gen Z, which are from one of the public higher education provider were subjected to analysis under the theory of reasoned action to determine whether the theory could provide direction for marketing strategy. A four-page TORA based questionnaire was designed and were administered to 310 male students from age range from 20-24. The target population was defined by experience (Hennink et al., 2011), gender, country of residence and age range, due to the objectives of the research and the mobile applications that were chosen as test subjects. The research aimed to understand the mobile device consumer, and therefore the sample population included only mobile device users. Any person who had had an experience with mobile or online retailing (due to the technological similarities of the mobile and online channels) was viable as a participant. Online and mobile retailing experience was a criterion within the sample frame for the research (Malhotra and Birks, 2007) and therefore the population was defined due to an experiential criterion (Hennink et al., 2011). Participants were selected purposefully depending on their suitability and knowledge of the interview subject. The researcher is able to choose participants and settings that would reveal the richest and most relevant information (Russell and Gregory, 2003).Interest in the potential mobile application was measure initially as a give point modified Likert, sixteen possible contributing variables to understand the effectiveness of each will leads to the intention to download. Further, all respondents were coded based on their mobile device operating system for future research purpose. The measure of Mobile Apps Design (nine variables) and Mobile Apps Promotion (seven variables) were measured during this research. Regression analysis was used to analyses the data.Given that the purpose of this study was to simultaneously test multiple theorized causal relationships among the constructs, the data were analysed using partial least squares regression (Diamantopoulos and Winklhofer, 2001; Levin et al., 2012) using SmartPLS software (Ringle et al., 2005) for a number of reasons. Partial least squares regression is preferable to estimate a path dependent model when the following conditions exist: the hypothesized model includes formative constructs; assumptions about normality do not hold (Chin and Newsted, 1999). Partial least squares regression also requires a sample size with at least ten times the number of predictor variables that influence a criterion variable (Wixom and Watson, 2001).
4. Finding and Conclusions
- This study provides a theoretical understanding of the factors contributing to intention to download mobile apps by using Theory of Reasoned Action (TORA) as a base model. First we studies on the effectiveness of mobile apps design in which will improves the chances of downloads. Then, TORA also stresses out the importance of mobile apps promotion are one of the determinant of user intention to download.The studies provides some information for mobile apps publishers and marketers. The finding underscore the important of apps design and promotion. Most of the apps are free and thus providers must understand the contributing factors which suggest that developers and marketers should consider enhancing and emphasizing the designs and promotion of the apps to increase the intention to download.As from the study provides interesting and actionable insights for both academics and practioners into the attitude and subjective norms of the mobile app users. First the study finds string correlations between the design in the mobile app and the intention to download. This finding is particularly important to app designer and advertising manager, who are facing intense budgeting and competition in the market. The study also provides support to the potential return on investment on the development of mobile apps it finds a significant relationship between the mobile apps and the desired mobile apps download behavior. Managers will benefit from the knowledge on the investment in the mobile apps and further to understand the measurable financial benefit. From the theoretical perspective, the study lends a further support to the extant literature on the correlation between the design and promotion to the intention to download by using Theory of Reasoned Action as a base model.Secondly, the model presented in this paper provides insights into what users expects a mobile publisher needs to do. That is the user’s desires from the mobile apps that pushes the users in completing downloads.In the same way that Rowley (2004) published her perception of the elements of design, this paper pieces together a marketing literature to deliver a framework of mobile apps design and promotion elements. (Bredahl et al., 1998) further added that the model of TORA statiscally significant and this study results demonstrates, it helps to understand and explain mobile apps intention to download. Other studies have also successfully used the similar theoretical framework from which to examine the purchase intention.As with any study, there are several limitations. First, the survey data were collected in Malaysia, the results might not be applicable to other nation due to the demographically, social and cultural background. Secondly, the measure are all self-administered, and no actual behavior are measured. Finally, the respondent may be limited. Nevertheless, it provides valuable theoretical and managerial insights that may be expanded upon in future research.The paper suggests a number of opportunity for research. First and foremost, the TORA model should be expanded to include more marketing mix component, mobile app price and mobile app place. In addition, the study was only limited to understand the effectiveness of mobile apps design and the relationship to the intention to download, however, additional study on the after download service can be an area of research or the mobile apps shopping experience.The growth of mobile apps adoption among consumers suggests that research in this area will be increasingly important. Smartphones now account for approximately ten percent of web site traffic (Montate, 2012). A recent study indicated that 69 percent of retailers intended to increase their expenditures on mobile commerce (Brohan, 2012), so any research that assists retailers in allocating these dollars should be considered valuable. Furthermore, the emergence of an “apps culture” provides a rich new context in which to study consumers, their preference and behaviors. This study provides some interesting directions for mobile app research.
References
[1] | Ajzen, I. (1991). The theory of planned behavior, Organizational Behavior and Human Decision Processes, Vol. 50 No. 2, pp. 179-211. |
[2] | Aldas-Manzano, J., Ruiz-Mafe, C. and Sanz-Blas, S. (2009). Exploring individual personality factors as drivers of M-shopping acceptance, Industrial Management & Data Systems. Vol. 109 No. 6, pp. 739-57. |
[3] | Arbitron (2013), iPhones trump Androids for mobile commerce app usage. PR Newswire, April 15. Available at: http://online.wsj.com/article/PR-CO-20130415-907188.html |
[4] | Aubrey, C. and Judge, D. (2012). Re-imagine retail: why store innovation is key to a brand’s growth in the “new normal”, digitally connected and transparent world, Journal of Brand Strategy, Vol. 1 No. 1, pp. 31-39. |
[5] | Bagozzi, R.P., Baumgartner, H. and Youjae, Y. (1992). State versus action orientation and the theory of reasoned action: an application to coupon usage, Journal of Consumer Research, Vol. 18 No. 4, pp. 505-518. |
[6] | Baker, M.J. (2003). The Marketing Book, 5th ed., Butterworth-Heinemann, Oxford. |
[7] | Barkhi, R., Belanger, F. and Hicks, J. (2008). A model of the determinants of purchasing from virtual stores. Journal of Organizational Computing & Electronic Commerce, Vol. 18 No. 3, pp. 177-196. |
[8] | Bauer, H., Barnes, S., Reinhardt, T. and Neumann, M. (2005). Driving consumer acceptance of mobile marketing: a theoretical framework and empirical study. Journal of Electronic Commerce and Research, Vol. 6 No. 3, pp. 181-92. |
[9] | Bennett, R. and Savani, S. (2011). Retailers’ preparedness for the introduction of third wave (ubiquitous) computing applications. International Journal of Retail & Distribution Management, Vol. 39 No. 5, pp. 306-325. |
[10] | Bigne, E., Ruiz, C. and Sanz, S. (2007). Key drivers of mobile commerce adoption. An exploratory study of Spanish mobile users. Journal of Theoretical and Applied Electronic Commerce Research, Vol. 2 No. 2, pp. 48-60. |
[11] | Boone, L.E. and Kurtz, D.L. (2011). Contemporary Marketing. South-Western Cengage Learning, Stamford, CT. |
[12] | Broekhuizen, T. and Huizingh, E.K.R.E. (2009). Online purchase determinants: is their effect moderated by direct experiences? Management Research News, Vol. 32 No. 3, pp. 440-57. |
[13] | Brohan, M. (2012). The internet retailer survey: mobile commerce. Internet Retailer, October. Available at: www.internetretailer.com/2012/10/01/internet-retailer-survey-mobile-commerce |
[14] | Brown, J., Broderick, A.J. and Lee, N. (2007). Word of mouth communication within online communities: conceptualizing the only social network. Journal of Interactive Marketing, Vol. 21 No. 3, pp. 2-20. |
[15] | Chaffey, D. and Smith, P.R. (2008). eMarketing eXcellence: Planning and Optimising your Digital Marketing. Butterworth-Heinemann, Oxford. |
[16] | Chaffey, D., Ellis-Chadwick, F., Mayer, R. and Johnston, K. (2009). Internet Marketing, 4th ed., Pearson Education Limited, Essex. |
[17] | Chang, H.-H. and Wang, H.-W. (2011). The moderating effect of customer perceived value on online shopping behavior. Online Information Review, Vol. 35 No. 3, pp. 333-59. |
[18] | Charland, A. and Leroux, B. (2011). Mobile application development: web vs. native. Communications of the ACM, Vol. 54 No. 5, pp. 49-53. |
[19] | Chiang, W.-Y. (2012). To establish online shoppers’ markets and rules for dynamic CRM systems: an empirical case study in Taiwan. Internet Research, Vol. 22 No. 5, pp. 613-25. |
[20] | Chiang, W.K. and Li, Z. (2010). An analytic hierarchy process approach to assessing consumers’ distribution channel preference. International Journal of Retail & Distribution Management, Vol. 38 No. 2, pp. 78-96. |
[21] | Chin, W.W., Marcolin, B.L. and Newsted, P.R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research, Vol. 14 No. 2, pp. 189-217. |
[22] | Chin, W.W. (1998). Issues and opinions on structural equation modeling. MIS Quarterly, Vol. 22 No. 1, pp. 7-16. |
[23] | Chin, W.W. and Newsted, P.R. (1999). Structural equation modeling analysis with small samples using partial least squares, in Hoyle, R. (Ed.). Statistical Strategies for Small Sample Research, Sage, Thousand Oaks, CA, pp. 295-336. |
[24] | Chiu, Y., Fang, S. and Tseng, C. (2010). Early versus potential adopters: exploring the antecedents of use intention in the context of retail service innovations. International Journal of Retail & Distribution Management, Vol. 38 No. 3, pp. 443-459. |
[25] | Cisco (2008). Multimodal learning through media: what the research says. Cisco Systems Inc, San Jose, CA. Available at: www.cisco.com/web/strategy/docs/education/Multimodal-Learning-Through-Media.pdf |
[26] | Cyr, D. and Trevor-Smith, H. (2004). Localisation of web design: an empirical comparison of German, Japanese and US website characteristics. Journal of American Society for Information Science and Technology, Vol. 55 No. 13, pp. 1-10. |
[27] | Cyr, D., Kindra, G.S. and Dash, S. (2008). Web site design, trust, satisfaction and e-loyalty: the Indian experience. Online Information Review, Vol. 32 No. 6, pp. 773-90. |
[28] | Da Silva, R.V. and Alwi, S.F.S. (2008). Online brand attributes and online corporate brand images. European Journal of Marketing, Vol. 42 Nos 9/10, pp. 1039-58. |
[29] | Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, Vol. 13 No. 3, pp. 318-340. |
[30] | Dawson, S. and Kim, M. (2010). Cues on apparel web sites that trigger impulse purchases. Journal of Fashion Marketing and Management, Vol. 14 No. 2, pp. 230-46. |
[31] | De Cannie `re, M.H., De Pelsmacker, P. and Geuens, M. (2009). Relationship quality and the theory |
[32] | Dholakia, R.R. and Zhao, M. (2009). Retail web site interactivity: how does it influence customer satisfaction and behavioral intentions?. International Journal of Retail & Distribution Management, Vol. 37 No. 10, pp. 821-38. |
[33] | Diamantopoulos, A. and Winklhofer, H.M. (2001). Index construction with formative indicators: an alternative to scale development. Journal of Marketing Research, Vol. 38 No. 2, pp. 269-277. |
[34] | Doherty, N.F. and Ellis-Chadwick, F. (2010). Internet retailing: the past, the present and the future. International Journal of Retail & Distribution Management, Vol. 38 Nos 11/12, pp. 943-965. |
[35] | Eroglu, S.A., Machleit, K.A. and Davis, L.M. (2001). Atmospheric qualities of online retailing: a conceptual model and implications. Journal of Business Research, Vol. 54 No. 2, pp. 177-84. |
[36] | Evans, M., Wedande, G., Ralston, L. and Hul, S.v. (2001). Consumer interaction in the virtual era: some qualitative insights. Qualitative Market Research: An International Journal, Vol. 4 No. 3, pp. 150-9. |
[37] | Feinberg, R. and Kadam, R. (2002). E-CRM web service attributes as determinants of customer satisfaction with retail web sites. International Journal of Service Management, Vol. 13 No. 5, pp. 432-51. |
[38] | Fiore, A.M. (2002). Effects of experiential pleasure from a catalogue environment on approach responses toward fashion apparel. Journal of Fashion Marketing and Management, Vol. 6 No. 2, pp. 122-33. |
[39] | Fiore, A.M. and Jin, H. (2003). Influence of image interactivity on approach responses towards an online retailer. Internet Research, Vol. 13 No. 1, pp. 38-48. |
[40] | Fiore, A.M., Jin, H.-J. and Kim, J. (2005), “For fun and profit: hedonic value from image interactivity and responses toward an online store”, Psychology& Marketing, Vol. 22 No. 8, pp. 669-94. |
[41] | Fishbein, M. and Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research, Addison-Wesley, Reading, MA. |
[42] | Gartner, Inc. (2011). Gartner says sales of mobile devices in second quarter of 2011 grew 16.5 percent year-on-year; smartphone sales grew 74 percent. Gartner research. Available at: www.gartner.com/it/page.jsp?id¼1764714 |
[43] | Goldman, D. (2010). Transformers. Journal of Consumer Marketing, Vol. 27 No. 5, pp. 469-73. |
[44] | Google (2012). Our mobile planet. Available at: www.thinkwithgoogle.com/mobileplanet/en |
[45] | Grandon, E. and Ranganathan, C. (2001). The impact of content and design of web sites on online sales. Proceedings of the 7th Americas Conference on Information Systems, pp. 920-6. |
[46] | Grotnes, E. (2009). Standardization as open innovation: two cases from the mobile industry. Information Technology & People, Vol. 22 No. 4, pp. 367-81. |
[47] | Gulliver, S.R. and Ghinea, G. (2010). Cognitive style and personality: impact on multimedia perception. Online Information Review, Vol. 34 No. 1, pp. 39-58. |
[48] | Ha, Y. and Lennon, S.J. (2010). Online visual merchandising (VMD) cues and consumer pleasure and arousal: purchasing versus browsing situation. Psychology and Marketing, Vol. 27 No. 2, pp. 141-65. |
[49] | Ha, Y., Kwon, W.-S. and Lennon, S.J. (2007). Online visual merchandising (VMD) of apparel web sites. Journal of Fashion Marketing and Management, Vol. 11 No. 4, pp. 477-93. |
[50] | Hair, J.F., Ringle, C.M. and Sarstedt, M. (2011). PLS-SEM: indeed a silver bullet. Journal of Marketing Theory and Practice, Vol. 19 No. 2, pp. 139-151. |
[51] | Harris, L.C. and Goode, M. (2010). Online services capes, trust, and purchase intentions. Journal of Services Marketing, Vol. 24 No. 3, pp. 230-43. |
[52] | Henseler, J., Ringle, C.M. and Sinkovics, R.R. (2009). The use of partial least squares path modeling in international marketing. in Sinkovics, R.R. and Ghauri, P.N. (Eds), Advances in International Marketing, Emerald, Bingley, pp. 277-320. |
[53] | Ho, J.Y.C. and Dempsey, M. (2010). Viral marketing: motivations to forward online content. Journal of Business Research, Vol. 63 Nos 9-10, pp. 1000-6. |
[54] | Hsiao, K., Lin, J.C., Wang, X., Lu, H. and Yu, H. (2010). Antecedents and consequences of trust in online product recommendations: an empirical study in social shopping. Online Information Review, Vol. 34 No. 6, pp. 935-53. |
[55] | Hu, J., Liu, X., Wang, S. and Yang, Z. (2012). The role of brand image congruity in Chinese consumers’ brand preference. Journal of Product and Brand Management, Vol. 21 No. 1, pp. 26-34. |
[56] | Huizingh, E. (2000). The content and design of web sites: an empirical study. Information and Management, Vol. 37 No. 3, pp. 123-34. |
[57] | ITU World Telecommunication (2011). The world in 2011: ICT facts and figures. Available at: www.itu.int/ITU-D/ict/facts/2011/index.html. |
[58] | Jacobs, R. (2012). The case for HTML5 over mobile apps. Available at: www.mobilemarketer.com/cms/opinion/columns/12630.html. |
[59] | Jayawardhena, C. and Wright, L.T. (2009). An empirical investigation into e-shopping excitement: antecedents and effects. European Journal of Marketing, Vol. 4No. 9, pp. 1171-87. |
[60] | Jin, C.H. and Villegas, J. (2008). Mobile phone users’ behaviors: the motivation factors of the mobile phone user. International Journal of Mobile Marketing, Vol. 3 No. 2, pp. 4-14. |
[61] | Johnson, R. (2010). Apps culture reinventing mobile internet. Electronic Engineering Times, No. 1588, pp. 24-30. |
[62] | Kalyanaramanm, S. and Sundar, S.S. (2006). The psychological appeal of personalized content in web portals: does customization affect attitudes and behavior? Journal of Communication, Vol. 56 No. 1, pp. 110-32. |
[63] | Kaplan, A.M. and Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, Vol. 53 No. 1, pp. 59-68. |
[64] | Keng, C.J. and Ting, H.Y. (2009). The acceptance of blogs: using a customer experiential value perspective Internet Research, Vol. 19 No. 5, pp. 479-95. |
[65] | Khalifa, M. and Shen, K.N. (2008). Drivers for transactional B2C m-commerce adoption: extended theory of planned behavior. Journal of Computer Information Systems, Vol. 48 No. 3, pp. 111-117. |
[66] | Kim, E.Y. and Kim, Y.K. (2004). Predicting online purchase intentions for clothing products. European Journal of Marketing, Vol. 8 No. 7, pp. 883-97. |
[67] | Kim, H. and Lennon, S. (2010a). E-atmosphere, emotional, cognitive, and behavioral responses. Journal of Fashion Marketing and Management, Vol. 14 No. 3, pp. 412-38. |
[68] | Kim, J. and Forsythe, S. (2007). Hedonic usage of product virtualization technologies in online apparel shopping. International Journal of Retail & Distribution Management, Vol. 35 No. 6, pp. 502-14. |
[69] | Kim, J. and Forsythe, S. (2008). Sensory enabling technology acceptance model (SE-TAM): a multiple-group structural model comparison. Psychology & Marketing, Vol. 25 No. 9, pp. 901-22. |
[70] | Kim, J. and Forsythe, S. (2010). Factors affecting adoption of product virtualization technology for online consumer electronics shopping. International Journal of Retail & Distribution Management, Vol. 38 No. 3, pp. 190-204. |
[71] | Kim, J. and Lennon, S. (2010b). Information available on a web site: effects on consumers’ shopping outcomes”, Journal of Fashion Marketing and Management, Vol.14 No.2, pp.247-62. |
[72] | Kim, J., Fiore, A.M. and Lee, H. (2007). Influences of online store perception, shopping enjoyment and shopping involvement on consumer patronage behaviour towards an online retailer. Journal of Retailing and Consumer Services, Vol. 14 No. 2, pp. 95-107. |
[73] | Kim, M. and Lennon, S. (2008). The effects of visual and verbal information on attitudes and purchase intentions in internet shopping. Psychology and Marketing, Vol. 25 No. 2, pp. 149-81. |
[74] | Kim, M., Kim, J.-H. and Lennon, S.J. (2011). E-service attributes available on men’s and women’s apparel web sites. |
[75] | Managing Service Quality, Vol. 21 No. 1, pp. 25-45. |
[76] | Kim, M.J., Kim, J.-H. and Lennon, S.J. (2006). Online service available on apparel retail websites: an E-S-QUAL approach. Managing Service Quality, Vol. 16 No. 1, pp. 51-77. |
[77] | Klein, L.R. (2003). Creating virtual product experiences: the role of telepresence. Journal of Interactive Marketing, Vol. 17 No. 1, pp. 41-55. |
[78] | Korzaan, M.L. (2003). Going with the flow: predicting online purchase intentions. Journal of Computer Information Systems, Vol. 43 No. 4, pp. 25-31. |
[79] | Ktoridou, D., Epaminonda, E. and Kaufmann, H.R. (2008). Technological challenges and consumer perceptions of the use of mobile marketing: evidence from Cyprus. International Journal of Mobile Marketing, Vol. 3 No. 2, pp. 34-43. |
[80] | Kukar-Kinney, M., Ridgway, N.M. and Monroe, K.B. (2009). The relationship between consumers’ tendencies to buy compulsively and their motivations to shop and buy on the internet. Journal of Retailing, Vol. 85 No. 3, pp. 298-307. |
[81] | Lee, D., Park, J.Y., Kim, J., Kim, J. and Moon, J. (2011). Understanding music sharing behaviour on social network services. Online Information Review, Vol. 35 No. 5, pp. 716-33. |
[82] | Lee, H. and Lee, S. (2010). Internet vs mobile services: comparisons of gender and ethnicity. Journal of Research in Interactive Marketing, Vol. 4 No. 4, pp. 346-374. |
[83] | Lee, Y.E. and Benbasat, I. (2003). Interface design for mobile commerce. Communications of the ACM, Vol. 46 No. 12, pp. 49-52. |
[84] | Levin, M.A., Hansen, J.M. and Laverie, D.A. (2012). Toward understanding new sales employees’ participation in marketing-related technology: motivation, voluntariness, and past performance. Journal of Personal Selling & Sales Management, Vol. 32 No. 3, pp. 379-393. |
[85] | Li, H., Daugherty, T. and Biocca, F. (2001). Characteristics of virtual experience in electronic commerce: a protocol analysis. Journal of Interactive Marketing, Vol. 15 No. 3, pp. 13-30. |
[86] | Lohmoller, J.-B. (1989). Latent Variable Path Modeling With Partial Least Squares, Physica, Heidelberg. |
[87] | Lohse, G.L. and Spiller, P. (1999). Internet retail store design: how the user interface influences traffic and sales. Journal of Computer-Mediated Communication, Vol. 5 No. 2. |
[88] | Lookout_Mobile_Security (2011). App genome report. Lookout Mobile Security. Available at: www.lookout.com:resources/reports/appgenome#platform-wars. |
[89] | Lowe, B. (2010). Consumer perceptions of extra free product promotions and discounts: the moderating role of perceived performance risk. Journal of Product and Brand Management, Vol. 19 No. 7, pp. 496-503. |
[90] | Lu, H.-P. and Su, P.Y.-J. (2009). Factors affecting purchase intention on mobile shopping web sites. Internet Research, Vol. 19 No. 4, pp. 442-58. |
[91] | Lu, Y. and Smith, S. (2008). Augmented reality e-commerce: how the technology benefits people’s lives. in Pavlidis, J. (Ed.), Human-Computer Interaction, InTech, Rijeka, Croatia. |
[92] | Macmillan, K., Money, K., Money, A. and Downing, S. (2005). Relationship marketing in the not- for-profit sector: an extension and application of the commitment-trust theory. Journal of Business Research, Vol. 58 No. 6, pp. 806-818. |
[93] | Maity, M. (2010). Critical factors of consumer decision-making on m-commerce: a qualitative study in the United States. International Journal of Mobile Marketing, Vol.5 No. 2, pp. 87-101 |
[94] | Manganari, E.E., Siomkos, G.J., Rigopoulou, I.D. and Vrechopoulos, A.P. (2011). Virtual store layout effects on consumer behaviour: applying an environmental psychology approach in the online travel industry. Internet Research, Vol. 21 No. 3, pp. 326-46. |
[95] | Mangold, W.G. and Faulds, D.J. (2009). Social media: the new hybrid element of the promotion mix. Business Horizons, Vol. 52 No. 4, pp. 357-65. |
[96] | McCormick, H. and Livett, C. (2012). Analysing the influence of the presentation of fashion garments on young consumers’ online behavior. Journal of Fashion Marketing and Management, Vol. 16 No. 1, pp. 21-41. |
[97] | McKechnie, S., Winklhofer, H. and Ennew, C. (2006). Applying the technology acceptance model to the online retailing of financial services. International Journal of Retail & Distribution Management, Vol. 34 Nos 4/5, pp. 388-410. |
[98] | McMullan, R. and Gilmore, A. (2008). Customer loyalty: an empirical study. European Journal of Marketing, Vol. 42 Nos 9/10, pp. 1084-94. |
[99] | Mehrabian, A. and Russell, J.A. (1974). An Approach to Environmental Psychology, MIT Press, Cambridge, MA. |
[100] | Meyer-Waarden, L. (2008). The influence of loyalty programme membership on customer purchase behavior. European Journal of Marketing, Vol. 42 Nos 1-2, pp. 87-114. |
[101] | Mikhailitchenko, A., Javalgi, R.G., Mikhailitchenko, G. and Laroche, M. (2009). Cross-cultural advertising communication: visual imagery, brand familiarity, and brand recall. Journal of Business Research, Vol. 62 No. 10, pp. 931-8. |
[102] | Mild, A. and Reutterer, T. (2003). An improved collaborative filtering approach for predicting cross-category purchases based on binary market basket data. Journal of Retailing and Consumer Services, Vol. 10 No. 3, pp. 123-33. |
[103] | Mintel (2010a). E-commerce – UK – February 2010. Available at: http://0x9.me/R1MDp. |
[104] | Mintel (2010b). E-commerce – UK – February 2010. Available at: http://academic.mintel.com/sinatra/oxygen_academic/search_results/showand/display/id¼479843. |
[105] | Monetate (2012). Ecommerce quarterly (EQ3). Available at: http://resources.monetate.com/ios/images/profile/real_images/47646231book47646231.pdf. |
[106] | Mort, G.S. and Drennan, J. (2007). Mobile communications: a study of factors influencing consumer use of m-services. Journal of Advertising Research, Vol. 47 No. 3, pp. 302-312. |
[107] | Muller, B. (2008). Consistency between brand image and website image: does it matter? International Journal of Internet Marketing and Advertising, Vol. 4 No. 4, pp. 350-61. |
[108] | Nguyen, B. and Mutum, D.S. (2012). A review of customer relationship management: successes, advances, pitfalls and futures. Business Process Management Journal, Vol. 18 No. 3, pp. 400-19. |
[109] | Nielsenwire (2011a). Generation App: 62% of Mobile Users 25-34 Own Smartphones, Nielsenwire, New York, NY. Available at: http://blog.nielsen.com/nielsenwire/online_mobile/generation-app-62-of-mobile-users-25-34-own-smartphones/. |
[110] | Nielsenwire (2011b). Consumers and Mobile Apps in the US: All about Android and Apple iOS, Nielsenwire, New York, NY. Available at: http://blog.nielsen.com/nielsenwire/online_mobile/consumers-and-mobile-apps-in-the-u-s-all-about-android-and-apple-ios/. |
[111] | Njite, D. and Parsa, H.G. (2005). Structural equation modeling of factors that influence consumer internet purchase intentions of services. Journal of Services Research, Vol.5 No.1, pp. 43-59. |
[112] | Park, J. and Stoel, L. (2002). Apparel shopping on the internet: information availability on US apparel merchant web sites. Journal of Fashion Marketing and Management, Vol. 6 No. 2, pp. 158-76. |
[113] | Park, M. and Lennon, S.J. (2009). Brand name and promotion in online shopping contexts. Journal of Fashion Marketing and Management, Vol. 13 No. 2, pp. 149-60. |
[114] | PayPal (2011). The UK mobile retail opportunity: why consumer will spend 2.5 billion in 2016 by shopping on their mobiles. white paper, PayPal, San Jose, CA. Available at: http://thefinanser.co.uk/files/paypal-uk-mobile-retail-forecast.pdf. |
[115] | Phau, I. and Teah, M. (2009). Young consumers’ motives for using SMS and perceptions towards SMS advertising. Direct Marketing: An International Journal, Vol. 3 No. 2, pp. 99-108. |
[116] | Pitta, D.A. (2011). Location-based social networking and marketing. Journal of Consumer Marketing, Vol. 28 No. 2. |
[117] | Rafiq, M. and Fulford, H. (2005). Loyalty transfer from offline to online stores in the UK grocery industry. International Journal of Retail & Distribution Management, Vol. 33 No. 6, pp. 444-60. |
[118] | Ranganathan, C. and Ganapathy, S. (2002). Key dimensions of business-to-consumer web sites. Information and Management, Vol. 39 No. 6, pp. 457-65. |
[119] | Rao, S. and Troshani, I. (2007). A conceptual framework and propositions for the acceptance of mobile services. Journal of Theoretical and Applied Electronic Commerce Research, Vol. 2 No. 2, pp. 61-73. |
[120] | Rigby, D. (2011). The future of shopping. Harvard Business Review, Vol. 89, No. 12, pp. 64-75. |
[121] | Ringle, C.M., Wende, S. and Will, A. (2005). SmartPLS, 2.0 (beta) ed. SmartPLS.de, Hamburg. |
[122] | Roach, G. (2009). Consumer perceptions of mobile phone marketing: a direct marketing innovation. Direct Marketing, Vol. 3 No. 2, pp. 124-138. |
[123] | Rowley, J. (1996). Retailing and shopping on the internet. Internet Research: Electronic Networking Applications and Policy, Vol. 6 No. 1, pp. 81-91. |
[124] | Rowley, J. (2004). Online branding. Online Information Review, Vol. 28 No. 2, pp. 131-8. |
[125] | Rowley, J. (2009). Online branding strategies of UK fashion retailers. Internet Research, Vol. 19 No. 3, pp. 348-69. |
[126] | Ruparelia, N., White, L. and Hughes, K. (2010). Drivers of brand trust in internet retailing. Journal of Product & Brand Management, Vol. 19 No. 4, pp. 250-60. |
[127] | Santos, J. (2003). E-service quality: a model of virtual service quality dimensions. Managing Service Quality, Vol. 13 No. 3, pp. 233-46. |
[128] | Sarker, S. and Wells, J.P. (2003). Understanding mobile handheld device use and adoption. Communications of the ACM, Vol. 46 No. 12, pp. 35-40. |
[129] | Scott, D.M. (2010). The New Rules of Marketing and PR: How to Use Social Media, Blogs, News Releases, Online Video, and Viral Marketing to Reach Buyers Directly. John Wiley & Sons, Hoboken, NJ. |
[130] | Sheppard, B.H., Hartwick, J. and Warshaw, P.R. (1988). The theory of reasoned action: a meta-analysis of past research with recommendations for modifications and future research. Journal of Consumer Research, Vol. 15 No. 3, pp. 325-343. |
[131] | Shim, S.I. and Lee, Y. (2011). Consumer’s perceived risk reduction by 3D virtual model. International Journal of Retail & Distribution Management, Vol. 39 No. 12, pp. 945-59. |
[132] | Shimp, T.A. and Kavas, A. (1984). The theory of reasoned action applied to coupon usage. Journal of Consumer Research, Vol. 11 No. 3, pp. 795-809. |
[133] | Shin, D.H. (2010). Analysis of online social networks: a cross-national study. Online Information Review, Vol. 34 No. 3, pp. 473-95. |
[134] | Shukla, P. (2009). Impact of contextual factors, brand loyalty and brand switching on purchase decisions. Journal of Consumer Marketing, Vol. 26 No. 5, pp. 348-57. |
[135] | Siddiqui, N., O’Malley, A., McColl, J.C. and Birtwistle, G. (2003). Retailer and consumer perceptions of online fashion retailers: web site design issues. Journal of Fashion Marketing and Management, Vol. 7 No. 4, pp. 345-55. |
[136] | Simmons, G. (2007). i-Branding: developing the internet as a branding tool. Market Intelligence and Planning, Vol. 25 No. 6, pp. 544-62. |
[137] | Simmons, G., Thomas, B. and Truong, Y. (2010). Managing i-branding to create brand equity. European Journal of Marketing, Vol. 44 No. 9, pp. 1260-85. |
[138] | Singh, T., Veron-Jackson, L. and Cullinane, J. (2008). Blogging: a new play in your marketing game plan. Business Horizons, Vol. 51 No. 4, pp. 281-92. |
[139] | Solomon, M.R., Marshall, G.W. and Stuart, E.W. (2008), Marketing: Real People, Real Choices, 5th ed., Pearson, Prentice Hall, Upper Saddle River, NJ. |
[140] | Srinivasan, S.S., Anderson, R. and Ponnavolu, K. (2002). Customer loyalty in e-commerce: an exploration of its antecedents and consequence. Journal of Retailing, Vol. 78 No. 1, pp. 41-50. |
[141] | StatCounter (2012). Statcounter global stats. Available at: http://gs.statcounter.com/ |
[142] | Szymanski, D.M. and Hise, R.T. (2000). E-satisfaction: an initial examination. Journal of Retailing, Vol. 76 No. 3, pp. 309-22. |
[143] | Ting-Peng, L. and Chih-Ping, W. (2004). Introduction to the special issue: mobile commerce applications. International Journal of Electronic Commerce, Vol. 8 No. 3, pp. 7-17. |
[144] | Tong, D.Y.K., Lai, K.P. and Tong, X.F. (2012). Ladies’ purchase intention during retail shoes sales promotions. International Journal of Retail & Distribution Management, Vol. 40 No. 2, pp. 90-108. |
[145] | Varadarajan, P.R. and Yadav, M.S. (2002). Marketing strategy and the internet: an organizing framework. Journal of Academy of Marketing Science, Vol. 30 No. 4, pp. 296-312. |
[146] | Venkatesh, V., Ramesh, V. and Massey, A.P. (2003). Understanding usability in mobile commerce. Communications of the ACM, Vol. 46 No. 12, pp. 53-6. |
[147] | Vesanen, J. (2007). What is personalization? A conceptual framework. European Journal of Marketing, Vol. 41 Nos 5/6, pp. 409-18. |
[148] | Weathers, D., Sharma, S. and Wood, S.L. (2007). Effects of online communication practices on consumer perceptions of performance uncertainty for search and experience goods. Journal of Retailing, Vol. 83 No. 4, pp. 393-401. |
[149] | Whiteaker, J. (2012). More than 5% of all online sales made via mobiles. Available at: www.retailgazette.co.uk/articles/21331-more-than-5-of-all-online-sales-made-via-mobiles. |
[150] | Wirtz, B.W., Schilke, O. and Ullrich, S. (2010). Strategic development of business models: implications of the Web 2.0 for creating value on the internet. Long Range Planning, Vol. 43 Nos 2/3, pp. 272-90. |
[151] | Wisniewski, J. (2011). Mobile that works for your library. Online, Vol. 35 No. 1, pp. 54-7. |
[152] | Wixom, B.H. and Watson, H.J. (2001). An empirical investigation of the factors affecting data warehousing success. MIS Quarterly, Vol. 25 No. 1, pp. 17-41. |
[153] | Wong, S.H.R. (2012). Which platform do our users prefer: website or mobile app? Reference Services Review, Vol. 40 No. 1, pp. 103-15. |
[154] | Wu, C., Jang, L. and Chen, C. (2011). Assessing the role of involvement as a mediator of allocentrist responses to advertising and normative influence. Journal of Consumer Behaviour, Vol. 10 No. 5, pp. 255-266. |
[155] | Yang, S. (2012). Mobile applications and 4G wireless networks: a framework for analysis. Campus-Wide Information Systems, Vol. 29 No. 5, pp. 344-57. |
[156] | Yeh, Y.-S. and Li, Y.-M. (2009). Building trust in m-commerce: contributions from quality and satisfaction. Online Information Review, Vol. 33 No. 6, pp. 1066-86. |
[157] | Yoh, E., Damhorst, M.L., Sapp, S. and Laczniak, R. (2003). Consumer adoption of the internet: the case of apparel shopping. Psychology & Marketing, Vol. 20 No. 12, pp. 1095-1118. |
[158] | Yoo, W., Lee, Y. and Park, J. (2010). The role of interactivity in e-tailing: creating value and increasing satisfaction. Journal of Retailing and Consumer Services, Vol. 17 No. 2, pp. 89-96. |
[159] | Yoon, D., Choi, S.M. and Sohn, D. (2008). Building customer relationships in an electronic age: the role of interactivity of e-commerce web sites. Psychology and Marketing, Vol. 25 No. 7, pp. 602-18. |