1
SERVICE QUALITY IN SOCIAL NETWORKING
SMARTPHONE APPLICATIONS
A study on how context-aware social networking applications should be
designed to improve service quality for customers
By
Mohammad Kambiz Ehsan
Faculty of Economics and Business, University of Groningen, Nettelbosje 2, 9747 AE Groningen, THE NETHERLANDS (s2202905@student.rug.nl)
This thesis is submitted in fulfillment of the requirements for the thesis for the MSc Business Administration - specialization Strategic Innovation Management
Student number: S2202905
Supervisors:
Dr. C.W. Tan (University of Groningen) & Dr. E.T.K. Lim (University of Groningen)
Word count: 42884
Groningen, the Netherlands
26 July, 2013
2 ABSTRACT
The purpose of this paper is to study the effect of electronic service quality towards customer’s satisfaction on context-aware social networking smartphone applications. The effects are tested with the help of the eight dimensions (consisting of 47 measure items) which are derived from literature. By comparing the dimensions of the proposed framework (derived from the ESQUAL model and other related theories and models) on the most downloaded social networking applications a relationship is ought to be found between user satisfaction and the various measure items. Furthermore, by comparing specific smartphone applications from certain countries with each other, an attempt is made to examine service quality on smartphone applications from the perspective of cultural differences and demographic differences between the United States, France, Spain, United Kingdom, Germany, Italy, China, and India.
Findings show that items from the efficiency dimension and the systems’ technical functioning dimension are strongly present on the 31 (unique) examined smartphone application, while items from the contact dimension and the emotional appeal dimension show poor presence statistics. However the results do suggest that the presence of efficiency items, systems’ technical functioning items, socialability items, and emotional appeal items have a positive effect on the average user ratings. Furthermore the cultural and age differences among the eight countries do not show the expected results, with the exception of hypothesis four which states that relatively younger users value the presence of emotional appeal items higher than the relatively older users.
Although the findings from this study can be useful for professionals in the IT sector, more scholars are urged to study this phenomenon.
3 ACKNOWLEDGEMENTS
During the writing of this paper, I initially perceived this master thesis to be the last obstacle in my academic career and my graduation. At the completion of this master thesis, I can say that using the term obstacle does no justice for this master thesis. By saying this, I want to emphasize that I have learned tremendously from doing this research and that I can really be proud of the work I have produced. In finalizing this master thesis, I will end a chapter in my life (which I will probably miss a lot in the future). My career as a student has had its tough times, but it has always been interesting. I have experienced wonderful times, which I will never forget during the rest of my life. These wonderful times and the knowledge I have gained so far are made possible by my amazing study mates, colleagues, and university professors. Thank you for being part of my life. Furthermore I would like to take this opportunity to thank some people in particular.
First of all, I would like to express my gratitude to my thesis supervisors. Dr. Chee-Wee Tan and Dr. Eric Lim have spent a considerable amount of time in reviewing my work and making sure I remained on track. Every time I needed advice, you guys were there to help me out. I highly appreciate the sacrifices you have made in my graduation process. I have learned a lot from your expertise in doing research, and all this would be impossible without your efforts, so thank you very much for everything!
4 TABLE OF CONTENTS
1. INTRODUCTION ... 8
1.1. Background information ... 8
1.2. Satisfying the online customer: electronic service quality ... 9
1.3. Social networking ... 10
1.4. Purpose of the study ... 10
1.5. Application area: social networking applications ... 11
1.6. Outline of the current research ... 12
2. LITERATURE REVIEW ... 13
2.1. Literature review procedure ... 13
2.2. Service Quality ... 15
2.3. Electronic service quality ... 16
2.4. From e-commerce to m-commerce ... 18
2.5. Context awareness ... 19
2.6. Online social networks ... 19
2.6.1. Cultural differences in online social networking ... 21
2.6.2. Age differences in social networking ... 22
2.7. Proposed dimensions for current study ... 24
3. METHODOLOGY ... 26
3.1. Operationalization ... 26
3.2. The final model ... 27
3.3. Discussing the measures ... 33
3.3.1. Efficiency measures ... 33
3.3.2. System’s technical functioning measures ... 34
3.3.3. Privacy measures ... 36
3.3.4. Responsiveness measure ... 37
3.3.5. Contact measure ... 37
3.3.6. Customization/Personalization measure ... 38
3.3.7. Socialability/content contribution measure ... 38
3.3.8. Emotional appeal measure ... 39
3.4. Tested sample: most downloaded social networking applications ... 40
3.4.1. Criteria for selecting applications ... 40
3.5. Actual application selection procedure ... 41
3.6. Analyzing the data ... 43
5
4. FINDINGS ... 45
4.1. Dimension level ... 46
4.1.1. Best rated apps versus worst rated apps ... 46
4.1.2. Top 3 rated apps versus bottom 4 rated apps ... 47
4.2. Measure item level ... 48
4.2.1. Efficiency dimension analysis ... 48
4.2.2. Systems’ technical functioning dimension analysis ... 50
4.2.3. Privacy dimension analysis ... 52
4.2.4. Responsiveness dimension analysis ... 54
4.2.5. Contact dimensions analysis ... 56
4.2.6. Personalization / Customization dimension analysis ... 58
4.2.7. Socialability / Content contribution dimension analysis ... 60
4.2.8. Emotional appeal dimension analysis ... 62
4.3. Cross-country findings ... 64
4.3.1. Dimension level findings ... 64
5. DISCUSSION ... 67
5.1. Dimension level ... 67
5.2. Measure item level ... 69
5.3. Cross-country level ... 71
5.4. Theoretical implications ... 72
5.5. Practical implications ... 73
5.6. Limitations ... 74
5.7. Direction for future researches ... 75
6. CONCLUSION ... 76
REFERENCES ... 77
APPENDICES... 87
Appendix A: Summary of Extant Literature on E-Service Quality ... 87
Appendix B: Screenshot of measure items ... 113
6 TABLE OF TABLES
Table 1: Proposed dimensions for current study ... 25
Table 2: Complete framework (dimensions + measure items) ... 27
Table 3: Efficiency dimension measure items ... 33
Table 4: Systems' technical functioning dimension measure items ... 34
Table 5: Privacy dimension measure items ... 36
Table 6: Responsiveness dimension measure items ... 37
Table 7: Contact dimension measure items ... 37
Table 8: Cusomization/Personalization dimension measure items ... 38
Table 9: Socialability/Content contribution dimension measure items ... 38
Table 10: Emotional appeal dimension measure items ... 39
Table 11: Selected smartphone applications per country ... 42
Table 12: Most unique applications per country (from the top 10 most downloaded) ... 43
Table 13: Dimension level analysis (best rated apps versus worst rated apps) ... 46
Table 14: Dimension level analysis (top 3 rated apps versus bottom 4 rated apps) ... 47
Table 15: Efficiency dimension items (best rated apps versus worst rated apps) ... 48
Table 16: Efficiency dimension items (top 3 rated apps versus bottom 4 rated apps) ... 49
Table 17: Systems' technical functioning dimension items (best rated apps versus worst rated apps) ... 50
Table 18: Systems' technical functioning dimension items (top 3 rated apps versus bottom 4 rated apps) ... 51
Table 19: Privacy dimension items (best rated apps versus worst rated apps) ... 52
Table 20: Privacy dimension items (top 3 rated apps versus bottom 4 rated apps) ... 53
Table 21: Responsiveness dimension items (best rated apps versus worst rated apps) ... 54
Table 22: Responsiveness dimension items (top 3 rated apps versus bottom 4 rated apps) ... 55
Table 23: Contact dimension items (best rated apps versus worst rated apps) ... 56
Table 24: Contact dimension items (top 3 rated apps versus bottom 4 rated apps) ... 57
Table 25: Personalization dimension items (best rated apps versus worst rated apps) ... 58
Table 26: Personalization dimension items (top 3 rated apps versus bottom 4 rated apps) ... 59
Table 27: Socialability dimension items (best rated apps versus worst rated apps) ... 60
Table 28: Socialability dimension items (top 3 rated apps versus bottom 4 rated apps) ... 61
Table 29: Emotional appeal dimension items (best rated apps versus worst rated apps) ... 62
Table 30: Emotional appeal dimension items (top 3 rated apps versus bottom 4 rated apps) ... 63
7 TABLE OF FIGURES
Figure 1: Age distrubution in Europe ... 22
Figure 2: Dimension level analysis (best rated apps versus worst rated apps) ... 46
Figure 3: Dimension level analysis (top 3 rated apps versus bottom 4 rated apps) ... 47
Figure 4: Efficiency dimension items (best rated apps versus worst rated apps) ... 48
Figure 5: Efficiency dimension items (top 3 rated apps versus bottom 4 rated apps) ... 49
Figure 6: Systems' technical functioning dimension items (best rated apps versus worst rated apps) 50 Figure 7: Systems' technical functioning dimension items (top 3 rated apps versus bottom 4 rated apps) ... 51
Figure 8: Privacy dimension items (best rated apps versus worst rated apps) ... 52
Figure 9: Privacy dimension items (top 3 rated apps versus bottom 4 rated apps) ... 53
Figure 10: Responsiveness dimension items (best rated apps versus worst rated apps) ... 54
Figure 11: Responsiveness dimension items (top 3 rated apps versus bottom 4 rated apps) ... 55
Figure 12: Contact dimension items (best rated apps versus worst rated apps) ... 56
Figure 13: Contact dimension items (top 3 rated apps versus bottom 4 rated apps) ... 57
Figure 14: Personalization dimension items (best rated apps versus worst rated apps) ... 58
Figure 15: Personalization dimension items (top 3 rated apps versus bottom 4 rated apps) ... 59
Figure 16: Socialability dimension items (best rated apps versus worst rated apps) ... 60
Figure 17: Socialability dimension items (top 3 rated apps versus bottom 4 rated apps) ... 61
Figure 18: Emotional appeal dimension items (best rated apps versus worst rated apps) ... 62
Figure 19: Emotional appeal dimension items (top 3 rated apps versus bottom 4 rated apps) ... 63
8 1. INTRODUCTION
1.1. Background information
In the eighties and nineties the internet changed the way people live. Suddenly new communication channels were introduced which were better and more convenient than the incumbent channels. Nowadays, with the introduction of smartphones a same pattern can be witnessed. Smartphones have replaced the phones which could only be used to call and text. Smartphones are multifunctional since it provides the users with all kinds of functionalities. Functionalities which were first only available on the desktop and via web browsers. Some purposes for which smartphones can be used include entertainment, lifestyle, travel, business, education, communication and many more purposes. The most popular internet activities among European smartphone users are using email, acquire information about the weather, and accessing social networking sites or blogs (ComScore, 2013).
The introduction of smartphones also altered the way of doing business in many industries and have added mobile commerce (m-commerce) as a way of delivering electronic commerce capabilities directly to the customer via smartphones. Barnes acknowledged that this new trend was very promising for the proliferation of e-commerce and defined m-commerce as “any transaction with a monetary value – either direct or indirect – that is conducted over a wireless telecommunication network” (Barnes, 2002: 92). In order to service their customers in a better way, businesses and retailers have developed smartphone applications. With these applications, businesses can extend their reach and accessibility, collect detailed information about their customers and deliver better service quality in the end. Although smartphone applications are relatively new, this trend has already had an impact on the economy in general. The relation between m-commerce and social networking applications is interesting, because more often businesses and retailers utilize social networking sites and applications to reach out to their potential customers. Figures on the money spent on advertisements in social networking applications emphasize this relation and show great advertisement growth potentials for these applications in the future (Business Insider, June 2013).
The importance of smartphone applications in the economy can be evaluated when looking at the statistics of m-commerce and mobile advertising. Analysts of Strategy Analytics have studied this phenomenon and published an article about this in 2012. According to them, consumers have spent $138 billion in 2012 and advertisers have almost doubled their expenditures on mobile ads to a total of $11.6 billion in 2012 (Strategy Analytics, 2012). Relevant to this study, Strategy Analytics mentioned that “revenue from display ads on the mobile web ($934.5 million) has been overtaken by in-app advertising ($1.7 billion)” across the US and major Western European countries (Strategy Analytics, 2012). Furthermore Deloitte revealed that the impact of smartphones on retail purchases will increase from the current level of $159 billion (5.1% of total retail sales) to $689 billion (19% of total retail sales) by 2016 (Deloitte, 2012). When analyzing their findings, Deloitte recommended retailers to develop a smartphone application in order to stay competitive (Deloitte, 2012).
9 11 billion, and it is predicted that 20 % of this amount ($ 2.2 billion) will be generated from social networking applications (Business Insider, June 2013). The study of MoPub (August, 2012) confirmed this explosion in ad revenue in social networking applications, by showing that the increase of sales figures of ads on social networking applications already show a huge growth (31% increase in June 2012). Taking all these findings together, it can be justly be said that there is much potential in developing social networking applications for smartphones.
1.2. Satisfying the online customer: electronic service quality
Considering the increased importance of smartphone application, businesses and retailers should do their upmost best in order to serve their customers and beat the competition. Since offering smartphone applications to consumers is a service, these businesses and retailers should attempt to offer superior electronic service quality. The importance of (electronic) service quality for firm performance is discussed by many scholars (Grönroos, 1982; Lehtinen & Lehtinen, 1982; Lewis & Booms, 1983; Parasuraman, Zeithaml & Berry 1985). Traditional service quality referred to all offline customer interactions and experiences with service providers. Early scholars considered service quality as a “comparison of what customers feel a company should offer (i.e., their expectations) with the company’s actual service performance” (Parasuraman, Zeithaml & Malhotra, 2005: 2). A difference between traditional service quality with electronic service quality, is that electronic service quality is not dominated by people-delivered services, but mainly dominated by the human interaction with electronic devices and interfaces (e.g., smartphone applications). Superior service quality can result in better sales figures and more loyal customers, and thus is crucial for the long-term survival of the organization (Parasuraman et al. 2005). The same can be said about electronic service quality. But in order to offer superior electronic service quality, companies must have sufficient knowledge on the different components of electronic service quality. Electronic service quality is a term which is studied rather extensively in literature. Past studies on service quality have covered many areas in marketing and business. But literature is lagging behind on studies about service quality in context-aware social network applications. This has partly to do with the specified area of the topic and the recent increasing popularity of this type of smartphone applications. Past studies on service quality may not be applicable since it concerns a new type of business model here. Thus the scarceness of scientific publications on the topic of service quality in mobile applications and the increasing popularity of social network application in today’s world calls for more studies in this field.
10 applications. More about this can be read in the literature review. Since literature on this topic is scarce, it is expected that by creating such a tailor-made scale for measuring service quality on social networking smartphone applications will be highly valued. Furthermore it is expected that the findings from this study may enable practitioners to understand factors for increasing service quality of users.
1.3. Social networking
Social and psychological scholars have studied the phenomenon of social networking for decades now. It is generally accepted that social capital plays a major role in the diffusion of information among users in the social network (Gainous, Marlowe & Wagner, 2013). The importance of social capital is not only evident in offline social networks, but also in online social networks. Scholars have found that cultural and demographic differences may affect the social capital generation (Correa, Hinsley & Gil de Zuniga, 2010; Jackson & Wang, 2013). Knowing that social capital generation is dependent on user characteristics and behavior, it is worth studying these effects in social networking applications (Gainous et al., 2013). In explaining why user characteristics and user behavior have an effect on social capital generation, one can consider the example of introvert and extravert type of people and the effect on social capital given by Robbins, Francis & Powell (2012). It is said that extrovert people like to be among other individuals and enjoy interaction with others. The introvert type of people are less fond of interacting with others, and thus will also create less social capital (Robbins et al., 2012). In the current study, the differences between users on culture and age are the subject of study. By reviewing studies of prominent scholars on cultural issues (such as Hofstede (1980)), it is decided that a separation should be applied in terms of individualistic and collectivistic cultures. Furthermore the differences in service quality of young and old users are topic of study. It is expected that applications selected from individualistic cultures will be less concerned about privacy issues, and will value items which stimulate contribution to the social network higher than individuals from collectivistic cultures.
1.4. Purpose of the study
11 The problem statement for this study therefore is as follows:
“How can context-aware social networking applications be designed to improve service quality for customers”
The sub-questions in this research are the following:
- What design items in social networking applications on smartphones do users value high in respect of user ratings?
- What role does culture play in service quality of users in social networking applications among the selected countries?
- What role does the age of users play in service quality of users in social networking applications among the selected countries?
1.5. Application area: social networking applications
The application area for this study is focused merely on social networking applications for smartphones. Due to the high number of social network application users (International Telecommunication Union, 2010), it is especially relevant to study this category. Smartphone applications may also differ in the nature of the mobile application, they can be context-aware or context-unaware. Although data is collected from both context-aware and context-unaware applications, the study merely recommends design features for context-aware social networking applications. Context-aware applications are those applications that are aware of the environment of the user (location). Context-aware applications typically collect data on the computing environment, user environment, physical environment, and on time contexts (Schilit, Adams & Want, 1994).
12 1.6. Outline of the current research
13 2. LITERATURE REVIEW
To derive at a framework for the purpose to evaluate design features on social networking smartphone applications, it is required to consider current literature on the topic of service quality. Literature from the four most related academic journals to electronic service quality is collected and studied. The journals in question are respectively MIS Quarterly, Information Systems Research, Journal of the Association for Information, and Journal of Management Systems. These journals are especially relevant since the majority of the articles in these journals are on the subject of information systems, e-commerce, electronic service quality, and mobile devices.
The actual procedure for selecting literature will be described in the next section. Then the theories and models which are perceived to be relevant will be reviewed. The review and discussion of current theories and models is crucial, since the framework for examining design features of social networking applications will be mainly based on these theories and models. The proposed framework will be provided once all related literature is reviewed and discussed.
2.1. Literature review procedure
The four related academic journals are accessed online through the interface of EBSCO from the account of the University of Groningen. Other literature is accessed from the Business Source Premier database. Due to the short product-life-cycle of smartphones and applications (Gibert, April 2013)and the increased technological advances in the last decade in the mobile industry, initially only literature is selected that is published between 2008 and 2013. If found necessary, literature is retrieved from years before 2008.
Once all published articles from the four journals (from 2008-2013) were reviewed, all conceptualizations on the topic of electronic service quality, social networks, and context-awareness were listed along with the context and scope of application, the theoretical frame of reference, and its corresponding dimensions. This summary of extant literature can be viewed in appendix A.
Furthermore, this table with extant literature contains constructs and theories which are related to satisfaction, trust, contribution behaviors, technology adoption, website quality, online product reviews, online communities, m-commerce, information quality, and online customer loyalty. It is likely that literature referring to these key words will supplement the theoretical framework with additional dimensions and provide different perspectives to electronic service quality theories. A brief explanation of these key words is included below.
14 Trust: Although trust can be seen as a factor which has an effect in many research areas, for the sake of this research the definition of informational trust is applied of Choudhury and Karahanna (2008). They define informational trust as “a user’s belief about the reliability, credibility, and accuracy of information gathered through the web” (Choudhury & Karahanna, 2008: 184). In other studies, the effect of trust on users’ intention to use certain technologies is discussed (Vance, Elie-Dit-Cosaque & Straub, 2008). It is said that trust plays a great role in the adoption and use of new technologies. Also it can be assumed that more trust will be beneficial for information sharing in social networks.
Contribution behaviors: in order to reveal the reasons why people contribute in (online) social networks it is required to know more about the behaviors of online users. Especially literature from social and psychological studies can provide valuable insights on this topic. An example of this can be found in the study of Robbins, Francis, & Powell (2012) who investigated the psychological user type of individuals on the social bonding and the creation of social capital. Especially the characteristics of introvert and extravert type of users were studied in that paper. Insights from such studies can be utilized in understanding contribution behaviors of individuals in online communities. Thus it speaks for itself that literature should be searched for on the subject of contribution behavior and online communities.
Technology adoption: articles on technology adoption have been searched for to find out how users adopt new technologies and what factors play a role in this. By reviewing these, it is expected that determinants on why some technologies attract more participants than other, can be found. Fortunately there are many papers published on the subject of technology adoption. These studies resulted in various models for technology adoption motives. The technology acceptance model (TAM) is such a construct that clarifies the reasons for accepting a new technology by users (Devaraj, Easley & Crant, 2008). The ease of use and usefulness of the new technology, together with the intention to use and subjective norms of users form the core constructs of the TAM model (Devaraj et al., 2008; Sykes, Venkatesh & Gosain, 2009). The unified theory of acceptance and use of technology (UTAUT) and the theory of reasoned action (TRA) are other models that explain the motives of users to use and accept new technologies (Cenfetelli, Benbasat & Al-Natour, 2008; Venkatesh, Thon & Xu, 2012). The factors that are discussed in these models are necessary to be evaluated in order to grasp why users should participate in social networking applications.
Website quality: there is much literature published on the topic of website quality. Although websites are not the same as smartphone application, theories that are constructed for the purpose to examine website quality can be evaluated and re-applied for smartphone applications. Measure scales or certain dimensions for example can be considered to be included in the framework for examining service quality of smartphone applications. The most explicit scale developed for measuring website quality is from Parasuraman et al. (2005). By understanding what the determinants are of service quality of websites, a better perspective can be applied in creating a scale for measuring service quality for smartphone applications.
15 motivator of mobile data services usage, while system quality (measured by access, usability, and navigation) can be regarded as the de-motivator for mobile data services usage (Lee et al., 2009). By understanding these motivators and de-motivators, perhaps new dimensions or items can be formulated which can improve the information quality of mobile applications, which in turn can improve the service quality of mobile applications.
Online customer loyalty: customer loyalty is an important construct in business (Xu, Benbasat & Cenfetelli, 2011). In examining online customer loyalty, scholars have found that trust and satisfaction are important antecedents of creating online customer loyalty (Cyr, 2008). Online customer loyalty (also called e-loyalty) is defined as the intention to revisit a website (Cyr, 2008) and thus insights gained from these papers will improve the understanding on how to assure that users return to the social networking application and contribute more often to the social network.
2.2. Service Quality
Although it was rather complicated and difficult to delimit and measure the construct initially, many scholars have researched the determinants and effects of service quality on customer satisfaction, behavioral intention, and firm performance in many research fields over the years. Academic papers on the topic of service quality can thus be found in large numbers. As one of the first researchers on this topic, Grönroos (1982) defined service quality as the difference between expected service and perceived service. In line with this thinking, Lewis and Booms (1983) stated that successfully delivering quality service to customers means meeting the requirements of customer expectations on a regular basis. The main challenge these researchers were facing was the lack of established evaluation criteria in order to measure services. Even if there were evaluation criteria suggested, these were not commonly recognized among all scholars. The reason for a lack of full understanding of service quality had to do with the characteristics of services, and fortunately these were widely acknowledged by scholars (Parasuraman, Zeithaml & Berry, 1985). The four well-documented characteristics of services are intangibility, heterogeneity, inseparability, and perishability (Vargo & Lusch, 2004). Intangibility refers to the fact that services lack the tactile quality of goods, although services often have tangible results (Vargo & Lusch, 2004). The heterogeneity characteristic can be explained since services (unlike goods) cannot be standardized, and thus is dependable on both the customer and the supplier (Vargo & Lusch, 2004). Another key difference in comparison to goods, is that services are simultaneously produced and consumed, referring to the inseparability characteristic (Vargo & Lusch, 2004). The perishability nature of services elucidates that services cannot be produced ahead of time and inventoried (Vargo & Lusch, 2004).
In their pursuit to create a service quality model, Parasuraman et al. (1985) identified the nature and determinants of service quality as perceived by consumers. The ten determinants of service quality according to the study of Parasuraman et al. (1985) are:
1. Reliability: involves consistency of performance and dependability.
2. Responsiveness: concerns the willingness or readiness of employees to provide the service. 3. Competence: means possession of the required skills and knowledge to perform the service. 4. Access: involves approachability and ease of contact.
16 6. Communication: means keeping customers informed in language they can understand and
listening to them.
7. Credibility: involves trustworthiness, believability, honesty. It involves having the customer's best interests at heart.
8. Security: is the freedom from danger, risk, or doubt.
9. Understanding/knowing the customer: involves making the effort to understand the customer's needs.
10. Tangibles: include the physical evidence of the service (e.g. Physical facilities, appearance of personnel, tools or equipment used to provide the service, etc.).
The identification of such determinants stimulated the search for models for the purpose of increasing service quality for consumers. Especially the ground breaking work of Parasuraman, Zeithaml & Berry (1988) has made a significant contribution to service quality research. More specifically they managed to develop a 22-item measure scale (SERVQUAL) to assess customer perceptions of service quality in service and retailing organizations (Parasuraman et al., 1988). These 22 items are spread among five dimensions, which are the following (Parasuraman et al., 1988):
1. Tangibles: Physical facilities, equipment, and appearance of personnel.
2. Reliability: Ability to perform the promised service dependably and accurately. 3. Responsiveness: Willingness to help customers and provide prompt service.
4. Assurance: Knowledge and courtesy of employees and their ability to inspire trust and confidence.
5. Empathy: Caring, individualized attention the firm provides its customers.
Despite the widespread use of the SERVQUAL model among scholars and professionals, a number of critics have been raised against the scale (Ladhari, 2008). A major weakness of the original SERVQUAL model can be found in the generalization of the scale to other industries (Babakus & Boller, 1992). Due to this weakness, scholars have been suggesting that there is a need to develop industry-specific measures of service quality in order to measure the service quality performance of a specific industry.
Other developed models for the purpose of assessing customer perceptions of service quality are less ground breaking than the SERVQUAL model, but perhaps more effective for the designated industry. A proper example of this can be found in the IT industry, where numerous scales are developed and available for measuring electronic service quality. More about this can be found in the next section.
2.3. Electronic service quality
17 Continuing their understandings of service quality, Parasuraman et al. (2005) conceptualized another multi-item scale, but this time for the purpose of measuring the service quality delivered by web sites. During the conceptualization of this scale, it was considered that the customers’ assessment of a web site’s quality included both, experiences during the interactions and post interactions with the web site, resulting in a scale to “encompass all phases of a customer’s interaction with a website” (Parasuraman et al., 2005: 5). Furthermore they defined electronic service quality as “the extent to which a web site facilitates efficient and effective shopping, purchasing, and delivery“ (Parasuraman et al., 2005: 5). By comprehensively looking at the meaning of service and effectively encompassing all phases of a customer’s interaction with a website, the E-S-QUAL scale of Parasuraman et al. (2005) is justly the most applied scale in measuring online service quality among scholars. For this reason, the framework developed in this study is built on the foundation of the E-S-QUAL. Nevertheless, dimensions advocated in other studies are also considered and included in the framework, if found necessary. The author refers to the study of Kim et al. (2006) for the consideration of alternative scales and dimensions for measuring online service quality. The dimensions of the E-S-QUAL scale (consisting of 22 items) and a description of the dimensions are retrieved from the original article of Parasuraman et al. (2005) and provided below:
Efficiency: the ease and speed of accessing and using the site.
Fulfillment: the extent to which the site’s promises about order delivery and item availability are fulfilled.
System availability: the correct technical functioning of the site.
Privacy: the degree to which the site is safe and protects customer information.
To have a more complete understanding of service quality determinants as a basis for this study, the three e-recovery dimensions of service quality (E-RecS-Qual) are retrieved and included in this study. According to Parasuraman et al. (2005) E-RecS-Qual consists of 11 items on the following three dimensions:
Responsiveness: effective handling of problems and returns through the site.
Compensation: the degree to which the site compensates customers for problems.
Contact: the availability of assistance through telephone or online representatives.
18 2.4. From e-commerce to m-commerce
Although literature on the topic of m-commerce is found in small numbers (in comparison to e-commerce), the impact of this new form of commercialization is significant. It is predicted that 15% of the total online retail sales in the US will be done via mobile devices, which will constitute nearly $ 39 billion (eMarketer, April 2013). By 2017, it is estimated that this will rise to nearly $ 109 billion, constituting 25% of the online retail sales in the US (eMarketer, April 2013). The major difference between e-commerce and m-commerce can be found in the way of transaction and access of information (Stafford & Gillenson, 2003). Especially the increase of accessibility to information (not being bound to a certain physical location) can be seen as a great advantage for buying and selling information, products and services. Considering this, it must be concluded that a broader perspective must be applied and other theories and models related to the adoption and usage of new technologies must be reviewed in order to come up with a tailor-made framework for measuring service quality of smartphone applications. The following theories are perceived to be valuable in extracting dimensions or items for the proposed framework:
Technology Acceptance Model (TAM); this theory deals with the degree of user acceptance on new technologies. So it may explain why some new technologies will be accepted by users and why some others not. It consists of the following four dimensions: ease of use, usefulness, intention to use, and subjective norms (Devaraj, Easley & Crant, 2008).
Unified Theory of Acceptance and Use of Technology (UTAUT); this theory is built to explain the factors of accepting and using new technologies by users. It consists of the following four constructs: performance expectancy, effort expectancy, social influence, and facilitating conditions (Venkatesh, Thon & Xu, 2012). The frequently used moderators for this model are age, gender, and experience.
Social Capital Theory; this model describes “the sum of the actual and potential resources embedded within, available through, and derived from the network of relationships possessed by an individual or social unit” (Chai, Das, and Rao, 2012: 312). It represents embedded values, such as social ties, trusting relations, and value systems that facilitate actions of individuals. In the process of creating social networks, social capital plays a role in enforcing behavioral norms among the various members of the network as well as promotes a diffusion of information.
Social Network Analysis (SNA); this theory captures the interactions and connections between different social entities (e.g., individuals, groups) and enables the researcher to study individuals’ actions and behaviors “within the context of larger structural configurations” (Sarker, Ahuja, Sarker & Kirkeby, 2011: 281). Especially trust centrality and communication centrality are important constructs in this model.
19 against initial expectations” (Lankton & McKnight, 2012: 89). Thus the main variables examined in this model are expectation, performance, satisfaction, and disconfirmation.
2.5. Context awareness
Context-aware applications are those applications that are aware of the environment of the user (location). Schilit et al. (1994) define context to be the constantly changing execution environment. The following pieces of the environment are included in their definition:
Computing environment available processors, devices accessible for user input and display, network capacity, connectivity, and costs of computing
User environment location, collection of nearby people, and social situation
Physical environment lighting and noise level
Dey & Abowd (1999) did research on the topic of context and defined context-awareness as a system which provides relevant information and/or services to the user, where relevancy depends on the user’s task. Chen & Kotz (2000) studied the context-awareness of mobile computing and added another piece of the environment to the traditional theory of Schilit et al. This new piece of environment was the time context, such as time of a day, week, month, and season of the year (Chen & Kotz, 2000). Also they related the context-aware theory in mobile computing and stated that context-aware mobile computing is a paradigm in which applications can discover and take advantage of contextual information (such as user location, time of day, nearby people and devices, and user activity) (Chen & Kotz, 2000). In practice this information can be very useful for commercial organizations; especially firms in the field of advertising would appreciate this customer information, because it makes it easier for them to select the right consumers to advertise to. Since the aim of this study is to provide answers on how service quality on context-aware smartphone applications can be improved, and not so much on how businesses can increase their returns with the help of context-aware elements, there are no hypotheses articulated on the matter of context-context-awareness.
2.6. Online social networks
20 for investigating the attitudes and factors of users. The results indicated that based on the motivation theory, users participate in social networks due to extrinsic motivations (for usefulness purposes) and intrinsic motivations (for enjoyment purposes) (Lin & Lu, 2011; Davis, Bagozzi & Warshaw, 1992). From the network externalities viewpoint, it is said that the number of peers and perceived complementarity (e.g., users with similar ideas, behaviors, and likings) effectively reinforces the usefulness and enjoyment of social networking sites (Lin & Lu, 2011). This can be explained by referring to the fact that an increase in the number of available peers and perceived complementarity may lead to an opportunity to meet new friends and increase the range of their social network (Li & Bernoff, 2008; Powell, 2009; Sledgianowski & Kulviwat, 2009; Tapscott, 2008). Another study on the purposes of using social networking sites found that the main five reasons for participating are: (1) to build new relations, (2) to stay in contact with close friends and acquaintances, (3) for socializing reasons (e.g., share experiences, report activities, and small-talk), (4) to be informed about events, fashion, music, publications, and people’s opinions, and (5) for debating purposes (Brandtzæg & Heim, 2009).
Others scholars have emphasized the importance of social capital in social networks. In offline social networks, scholars have generally agreed upon the fact that social capital is of crucial importance for a healthy social network (Gainous et al., 2013). This importance can be explained when considering that social capital results from the interconnectedness between people (Bourdieu, 1986; Gainous et al., 2013; Putnam, 1995). In fact, social capital refers to the “resources available to people through their social interactions” (Valenzuela, Park & Kee, 2009: 877). People with more connections and resources in their network will have more social capital than those with small, and less diverse resources in their network (Valenzuela et al., 2009). Investments in social capital can be done by participating in online social networks (Resnick, 2002). Valenzuela et al. (2009) suggest four mechanisms by which the use of social networking sites may generate social capital.
1- Social networking sites help with personal identity construction by providing channels for feedback and peer acceptance generating life satisfaction.
2- Social networking sites can fulfill the informational need necessary for political/collective action.
3- Social networking sites could be used purely for entertainment, which could be negatively related to the generation of social capital and distract users from meaningful politically relevant content.
4- Social networking sites provide opportunity for people to gain a sense of belonging by connecting with family, friends, and society-building reciprocity and trust.
21 2.6.1. Cultural differences in online social networking
In literature it is evidently mentioned that cultural differences have an impact on the behavior of users in online social networks. Hofstede (1980: 260) defined culture as ‘‘the collective programming of the mind which distinguishes the members of one human group from another.” Hofstede also identified four cultural values, which are individualism/collectivism, power distance, uncertainty avoidance, and masculinity/femininity (Hofstede, 1980). Lewis & George (2008) included the four cultural values in a model in which the deceptive behavior of users was measured. Their cross-cultural findings suggested that there are differences observed between national cultures, which may influence deception in social networking sites. Importance for this research is the finding that the majority of these differences were found to be originating from the four cultural values. In cross-cultural psychology literature these cultural values are extensively studied, and it is concluded that especially the individualism-collectivism cleavage is most important for cultural differences (Gorodnichenko & Roland, 2012). The reason for only studying this cultural value is thus because it is expected that significant results will arise from analyzing this cultural factor.
The significance of cultural values in the use of social networking sites is emphasized by Jackson & Wang (2013), who did a comparative study of China and the United States. Especially the separation of collectivistic and individualistic cultures and its results on the use of social networking sites are essential in this research. It is said that “in collectivistic cultures the importance of the family, friends and one’s groups may be partly responsible for Chinese participants’ lesser use of social networking sites, whereas in individualistic cultures the importance of self and having more but less close and enduring friendships may be partly responsible for US participants’ greater use of social networking sites” (Jackson & Wang, 2013: 910). This understanding leads to first hypothesis for this study:
Hypothesis 1: Individuals from individualistic cultures tend to be more willing to contribute in the
network than individuals from collectivistic cultures. Thus they will rate apps with socialability items higher than individuals from collectivism cultures.
Another cultural difference among users of social networking sites and applications can be found by looking at the privacy concerns and issues of users around the globe. An empirical multinational study on online privacy showed that privacy concerns of internet users may be influenced by individual differences, nationality, and national cultures (Cho, Rivera-Sánchez & Lim, 2009). More specifically, the results indicated that “individuals from an individualistic culture are more likely to be concerned about online privacy” (Cho et al., 2009: 407). Considering this insight, the following can be hypothesized:
Hypothesis 2: Individuals from collectivistic cultures tend to be more concerned about privacy issues in
22 2.6.2. Age differences in social networking
Another factor which influences user behavior in online social networks is the age of participants. Correa, Hinsley & Gil de Zuniga (2010) examined personality factors and demographic characteristics of US adults in their study. It was revealed that age and gender are moderating variables to extraversion, openness, and emotional instability (Correa, Hinsley & Gil de Zuniga, 2010). Younger adults are said to be more extravert on social media, while older adults are being more open to experience in social media. These findings are shared by Pfeil, Arjan & Zaphiris (2009) who compared the older age groups (60+ years) with teenagers (between 13 and 19 years) on MySpace. Besides the finding that teenage users’ friends are approximately of the same age, whilst this is not the case with older age groups, it was found that teenagers make more use of different media which stimulate the emotional appeal (e.g. video, music) (Pfeil, Arjan & Zaphiris, 2009). Furthermore in the study of Cho et al. (2009) it was revealed that relatively older internet users were more concerned about their online privacy, than relatively younger counterparts.
Practitioners could use the findings that come out from the analysis to understand what interests the different types of users and age groups of social networking applications, and how this information can be applied to increase user ratings. Since each country has a different user age average, differences among countries can be expected. For example, 62% of the mobile internet users in China are below 30 years (China Internet Network Information Centre, 2012). In 2010, in India 75% of the mobile users were between 20 and 30 years, while only 5% was above the age of 35 (Trak.in, 2011). The average ages in Europe are more equally distributed, as can be seen in figure 1. Although the national cultures in Europe are relatively comparable, there are some large differences when comparing it to India and China. In Italy for example 50% of the mobile users are over 45 years of age (ComScore, 2013).
Figure 1: Age distrubution in Europe
23 When viewing the findings and suggestions from prior literature in the light of age differences in social networking for social networking applications, the following hypotheses can be formulated:
Hypothesis 3: Countries with relative younger users on average will be more likely to contribute more
often and intense in the social network than countries with relative older users on average. Thus countries with relative younger users will value more sociability items on the application higher than countries with older users on average.
Hypothesis 4: Countries with relative younger users on average will perceive items that stimulate the
emotional appeal of users more valuable than countries with relative older users on average. Thus countries with relative younger users will rate the emotional appeal items on the application higher than countries with older users on average.
Hypothesis 5: Countries with relative older users on average tend to be more concerned about privacy
24 2.7. Proposed dimensions for current study
In the previous sections all the theories and models that were perceived to be useful for the purpose of this study are reviewed. These useful theories and models were collected after an extensive literature review (of which the result can be found in appendix A).
Although the seven dimensions (four dimensions of E-S-QUAL and three dimensions of E-RecS-QUAL) are designed to measure the electronic service quality (e-commerce), thus mainly purposed to measure the service quality of websites, the seven dimensions can also be used to examine the service quality of smartphone applications (m-commerce). To make the dimensions more suitable some adjustments are required to make though.
First of all, efficiency in smartphone applications refers to the ease and speed of accessing and using the mobile application (Parasuraman et al., 2005). The rationale for this dimension is that the application must be easy to use and it shouldn’t be difficult for the users to learn how to use the application.
Fulfilment and system availability are two dimensions which are joined together to form one well-fitted dimension, namely system’s technical functioning. This new dimension is designed to examine the correct technical functioning of the mobile application and the availability of functions to the users. The reason why this dimension is included is to measure the technical functioning of the mobile application and to what extent the functions promised about are available to the users.
The third dimension is about the privacy of the users. This dimension refers to the degree to which the mobile application is safe and protects user information (Parasuraman et al., 2005). The original E-S-QUAL model describes this dimension adequately and it thus can be simply taken over to examine the service quality of smartphone applications.
The fourth dimension concerns the responsiveness of the firm behind the application. This responsiveness can be described as the effective handling of problems and errors through the mobile application (Parasuraman et al., 2005) and is usable for this study in the sense to examine the degree that users of social network applications should be replied/helped in an effective way by the application.
Contact is another dimension which is taken over from the original E-S-QUAL model. This dimension is defined as the availability of assistance through telephone or online representatives of the mobile application. This dimension is perceived to be relevant for this study, since it is important for users to be able to contact the firm behind the application in case of troubles or other issues.
25 Socialability/Content contribution is a dimension which is merely added to examine the extent of how easy users find it to interact and share information with each other through the smartphone application. The dimension is derived from the study of Phang, Kankanhalli & Sabherwal (2009). This dimension is especially relevant to social network application, because the content contribution possibilities are crucial for information sharing in the social network.
The eight dimension is emotional appeal and the reason for including this dimension to the scale is due to the importance of hedonic factors on service quality (Kohler, Fueller, Matzler, & Stieger, 2011; Nambisan & Nambisan, 2008). It is said that nurturing playfulness, providing challenging tasks, and making the user feel good or happy can increase the enjoyment of users, which will most likely increase service quality (Kamis, Koufaris & Stern, 2008; Kohler et al., 2006; Xiao & Benbasat, 2011).
Table 1 lists all the dimensions that are selected to examine the service quality of context-aware social network smartphone application.
Table 1: Proposed dimensions for current study Dimension Definition
Efficiency (A) The ease and speed of accessing and using the mobile application (Parasuraman, Zeithaml & Malhotra, 2005)
System's technical functioning (B)
The correct technical functioning of the mobile application and the availability of functions to the users (Parasuraman, Zeithaml & Malhotra, 2005)
Privacy (C) The degree to which the mobile application is safe and protects user information (Parasuraman, Zeithaml & Malhotra, 2005)
Responsiveness (D) Effective handling of problems and errors through the mobile application (Parasuraman, Zeithaml & Malhotra, 2005)
Contact (E) The availability of assistance through telephone or online representatives of the mobile application (Parasuraman, Zeithaml & Malhotra, 2005)
Customization/ Personalization (F)
How much and how easily the application can be tailored to individual customers’ preferences (Parasuraman, Zeithaml & Malhotra, 2005), (Sheng, Nah & Siau, 2008)
Socialability/Content contribution (G)
The extent of how easy users find it pleasant to interact with each other in attaining community-shared purposes through the mobile application (Phang, Kankanhalli & Sabherwal, 2009)
Emotional appeal (H)
26 3. METHODOLOGY
3.1. Operationalization
27 3.2. The final model
Table 2: Complete framework (dimensions + measure items)
Dimension Definition Measurement item + description Source How to measure the item
Efficiency (A) The ease and speed
of accessing and using the mobile application (Parasuraman, Zeithaml & Malhotra, 2005)
1. Accessibility
Refers to the degree of effort needed to access the information system
Au, Ngai & Cheng (2008)
The application offers the possibility to stay logged on once signed up, even when switching to other application on the smartphone.
2. Load time The time needed to load the
application on the smartphone
Hoxmeier & DiCesare (2000), Parasuraman, Zeithaml & Malhotra, (2005)
The application loads the user interface under 9.5 seconds.
3. Response time/promptness
The elapsed time for execution of a program submitted or requested by a user and the return of the output to that user.
Au, Ngai & Cheng (2008)
The application loads the other pages/slides (like user profiles) on the user interface under 9.5 seconds. Refers to the speed and quickness
on the use of an information system.
Au, Ngai & Cheng (2008)
4. Navigability function
The organization and hierarchical layout of the content and pages in a website and involves the relative effort required for a user to traverse an IT artifact user interface.
Vance, Elie-Dit-Cosaque &
Straub (2008) Is there a navigation bar present that
offers the possibility to return to the home screen and other screens of the application?
The effectiveness in navigating between screens of mobile data services
Lee, Shin & Lee (2009), Lim, Cyr & Tan (2012)
5. Search function Refers to the presence of a search
function in the application Luo, Ba & Zhang, (2012)
There is a search function present in the application
6. Filler interface
Refers to the presence of a filler item, which shows whether a page is loading or not
Lee, Chen & Illie (2012) There is a filler item available in the
28
7. User
friendliness/ease of use/convenience
Refers to the ease of use or learn to use a certain information system.
Au, Ngai & Cheng (2008)
A guide/help document is available for users to get acquainted with the application.
1. be easy to get to do what I want it to do, 2. be easy for me to learn to use, 3. be easy for me to become skillful at, 4. be easy to use.
Davis (1993), Lankton & McKnight (2012)
Time and effort required to interact through a channel
Choudhury & Karahanna (2008)
8. Instruction video
Refers to the presence of a brief instruction video on how to use the application
An instruction video is available for the
users. Systems' technical functioning (B) The correct technical functioning of the mobile application and the availability of functions to the users (Parasuraman, Zeithaml & Malhotra, 2005) 1. System availability
Refers to the percentage of time an information system is available for use.
Au, Ngai & Cheng (2008), Parasuraman, Zeithaml & Malhotra (2005), Lee, Shin & Lee (2009)
The application is always available for use.
2. Functionality Refers to the quality or state of
being functional Au, Ngai & Cheng (2008)
The application functions as promised by the application developer, so there are no errors encountered by the users
3. Usefulness
1. Increase productivity, 2. improve performance, 3. enhance effectiveness, 4. be useful.
Bhattacherjee & Premkumar (2004), Lankton & McKnight (2012)
The application offers the same (or even more) features as the web version of the application (if applicable) once
downloaded Person’s perception on how useful
the technology might be to him/her once acquired
Devaraj, Easley & Crant (2008)
4. Timeliness
The availability of the output of information at a time suitable for its use
Au, Ngai & Cheng (2008) All user updates are directly uploaded
and viewable to other users 5.
Presentation/visual representation
Refers to the visual representation of the information system that is viewable to the users of the information system.
Au, Ngai & Cheng (2008) All information needed is provided on
29
6. Graphic quality
Refers to the correct visual representation of pictures, videos and other graphics in the
application
Fassnacht & Koese (2006), Cyr (2008)
The pictures and videos are correctly displayed on the screen of the mobile application (graphics adjust automatically to the resolution of the screen)
7. Application-system fit
Refers to the technical competency of how well the application fits to the operating system (it must not hinder other active applications or systems on the device).
The application can be operational simultaneously with other applications on the smartphone (the music on the device won't stop for example)
8. GPS location identification
Refers to the presence of a GPS location identifier on the application.
The application is able to collect the
geographical location of the user.
9. Failure report system
Application collects information about errors and system failures and reports this to the application developer.
There is a button or page on the application that offers the possibility to check past failure reports.
Privacy (C) The degree to
which the mobile application is safe and protects user information (Parasuraman, Zeithaml & Malhotra, 2005)
1. Privacy policy
The availability of a privacy policy for user information on the smartphone application
Kim et al. (2006) Is there a privacy policy document
available which is readable by the users? 2. Password
encryption
The availability of a password
encryption on the application Douglas (2003)
Are user passwords encrypted on the application?
3. Personal information protection
The possibility for the users to protect their personal information from other users.
Janda et al. (2002)
Is it possible for users to protect their disclosed information from seeing by other users?
4. User post-control
An affective perception by individuals of their level of control over the environment and their actions
Kamis, Koufaris & Stern (2008)
Can users customize/delete their actions once submitted and made publically? 5. Third-party
validation on security measures
The availability of a third-party validation on the security of the application
Tan, Benbasat & Confetelli (2013)
30
Responsiveness (D)
The effective handling of
problems and errors through the mobile application (Parasuraman, Zeithaml & Malhotra, 2005)
1. FAQ availability
The availability of a FAQ section on the application to help users when having questions/troubles
Palmer (2002), Singh (2002) Is there a FAQ present on the application
to help users?
2. Feedback system
Refers to the availability of a feedback feature on the application, in which users can post their
ideas/suggestions/improvements for the application
Palmer (2002), Tan (2009)
Is there a possibility to feedback/contact the application developer on
ideas/suggestions/improvements for the application?
3. Report misuse by other users
Refers to the possibility to report misuse or other inappropriate online actions by other users on the application
Is there a possibility to report misuse or other inappropriate online actions by other users on the application? 4. System update
notification
Refers to the information provided
after a system update.
There is a button or function on the application to check or update the current application version.
Contact (E) The extent in which
the users can contact the application developer on the mobile application (Parasuraman, Zeithaml & Malhotra, 2005) 1. Phone helpdesk
Refers to the possibility to contact the application developer by phone.
Parasuraman, Zeithaml & Malhotra, 2005)
Is it possible to contact the application developer by phone (is the phone number visible on the application)?
2. Live help technology
The availability of a technology which enables users to interact with human customer service representatives using an online medium.
Xu, Benbasat & Confetelli (2011)
Is there a live help technology on the smartphone application which can be used by the users?
3. Contact information
Refers to the presence of a page or slide on which contact details of the application developer are visible.
Is there a page/slide present on the application with contact details of the application developer?
Customization/ Personalization (F)
How much and how easily the
application can be tailored to
1. Adaptability
Extent to which the application reflects revised service content and accommodates fluctuations in users’ usage patterns
Tan, Benbasat & Confetelli (2013)
31 individual customers’ preferences (Parasuraman, Zeithaml & Malhotra, 2005), (Sheng, Nah & Siau, 2008)
2. Personalized system
recommendation
The extent to which the application provides
recommendations to the user that matches individual user
preferences (recommendations on people the user might know)
Zhang, Agarwal & Luca (2011).
The application provides
recommendation to the user on which other users or pages the user might like or be interested in.
3. Arousal
Subjective feeling state in which a person feels excited, stimulated, alert, or active about the target product(s)
Xiao & Benbasat (2011)
The application provides the users with event notifications in which users are alerted on updates or activities of other member and interested pages.
Socialability/ Content contribution (G)
The extent of how easy users find it to interact with each other in attaining community-shared purposes through the mobile application (Phang, Kankanhalli & Sabherwal, 2009) 1. Number of active users
Number of users that have interacted with the application
Claussen, Kretschmer & Mayrhofer (2013)
The number of active users in the network is visible on the application
2. Exposure Refers to the appearance of the
users in social media Tang, Gu & Whinston (2012)
The possibility to view other users profiles.
3. Reputation Refers to the possibility to build an
online reputation Tang, Gu & Whinston (2012)
Is it possible to build an online reputation?
4. Anonymous viewer
Refers to the possibility to check other users profiles without them knowing about it
Users can act anonymously
5. Social ties
All social
relationships/interactions users have with social networks, personal contacts, memberships, and social classes.
Chai, Das & Rao (2012) Are user's social ties visible to other users
6. Subjective norm
Defined as a person’s perception that most people who are important to him think he should or should not perform the behavior in question
Devaraj, Easley & Crant (2008)
The actions (excluding status updates) of friends in the network is visible in the application (e.g. new friend connections).
7. Interactivity
The extent to which users can participate in modifying the form or content of a website in real-time
Jian, Chan, Tan & Chua (2010)
32
8.
Recommendation option
Refers to the possibility to recommend the appliction to other people via email.
Sarker, Ahuja, Sarker & Kirkeby (2011)
The application offers a possibility to recommend the application to other people via email on the interface of the mobile application.
Emotional Appeal (H)
Subjective feeling state in which a person feels good, joyful, or happy about the target product(s) (Xiao & Benbasat, 2011. Kamis, Koufaris & Stern, 2008). Can also be defined as the fun or pleasure derived from using a technology (Venkatesh, Thon & Xu, 2012)
1. Picture uploader functionality
The application offers the possibility to upload and share pictures on the application
Venkatesh, Thong & Xu (2012), Al-Natour & Benbasat (2009)
It is possible to upload and share pictures on the user profile via the smartphone application?
2. Picture viewer functionality
The application offers the possibility to view the pictures within the application.
Venkatesh, Thong & Xu (2012), Al-Natour & Benbasat (2009)
Is it possible to open pictures on the application and view them within the application?
3. Video uploader functionality
The application offers the possibility to upload and share videos on the application
Kamis, Koufaris & Stern (2008), Venkatesh, Thong & Xu (2012), Al-Natour & Benbasat (2009)
It is possible to upload and share videos on the user profile via the smartphone application?
4. Video player functionality
The application offers the possibility to play videos within the application.
Kamis, Koufaris & Stern (2008), Venkatesh, Thong & Xu (2012), Al-Natour & Benbasat (2009)
Is it possible to play videos within the application?
5. Music uploader functionality
The application offers the possibility to upload and share music on the application
Kamis, Koufaris & Stern (2008), Venkatesh, Thong & Xu (2012)
It is possible to upload and share music on the user profiles via the smartphone application?
6. Music play functionality
The application offers the possibility to play music on the application.
Kamis, Koufaris & Stern (2008), Venkatesh, Thong & Xu (2012)
Is it possible to play music within the application?
7. Game play functionality
The application offers the possibility for the users to play games on the application
Kamis, Koufaris & Stern (2008), Venkatesh, Thong & Xu (2012)
It is possible to play games on the smartphone application?
