4.1. Research Model and Its Hypotheses
According to the findings obtained from the exploratory study, the research model (see Figure 1
) has been proposed. In this model, the seven factors acknowledged earlier are expected to directly influence consumers’ intention to purchase paid mobile Apps. The following sections discuss and justify all the hypotheses relating to the research model.
Davis et al. [30
] point out that perceived enjoyment represents “…the extent to which the activity of using the computer is perceived to be enjoyable in it’s own right, apart from any performance consequences that may be anticipated
” (p. 1113). Thus, App enjoyment in this study refers to the sensation of joy, entertainment or pleasure derived from the use of a mobile App. In fact, enjoyment reflects the hedonic (intrinsic) value of a product or service, where the utility stems from affective or feeling states that the product or service generates [31
]. Consumers are more likely to purchase products/services depending on feelings of joy and pleasure, mainly in the case of hedonic products (e.g., a mobile game) [33
]. Therefore, hedonic value has been recognized as one of the key antecedents that significantly influences how consumers make their purchasing decisions [34
]. It has been argued by Tang et al. [11
] that “App consumers focus more on satisfying their own inner spiritual needs rather than targeting practical purpose
” (p. 1632). Further, enjoyment positively influences mobile App usage intentions because, when consumers’ entertainment requirements are met, the pleasurable feelings about the App are realized. Hence, consumers may intend to assess a mobile App before purchasing it in anticipation of the level of fun generated from using the App, and its ability to provide pleasure. Thus, the intention to purchase a mobile App is more likely to be increased directly by the mobile App’s perceived enjoyment.
Hypothesis 1 (H1).
Intention to purchase a mobile App is positively influenced by App enjoyment.
Xu et al. [35
] define price as “…the financial cost required to obtain and use a product
”. With regard to mobile Apps, price value has been described by Venkatesh et al. [36
] as that price value that serves as “…consumers’ cognitive trade-offs between the perceived benefits and cost of using various applications”
(p. 181). Price value is perceived by consumers on the basis of their beliefs of what is received in return for what is given (monetary investment). Hence, the increase in consumer returns as compared to consumer investment will therefore lead to a perception of increased monetary value. It has been found that price value is among the core factors that determines mobile App purchase [32
], especially in light of the fact that the current market for mobile Apps is dominated by free Apps. In mobile App stores, there are several different Apps with comparable functions, and the majority of these Apps are free, which subsequently minimizes consumers’ motivation to purchase paid mobile Apps with the same functions [11
]. This assumption holds true even if paid mobile Apps provide an improved functional quality in comparison with other Apps. Consumers are inclined to assess the overall expected price against the overall expected gain of the paid mobile Apps. When an App’s performance surpasses its price, the most likely result is for it to be purchased. Otherwise, it will suffer from poor adoption rates. Consumers who consider purchasing a mobile App are more likely to evaluate its value for its price and purchase it if its value is high. Therefore, price value of paid mobile Apps is assumed to have direct role in increasing consumers’ intention to purchase such Apps.
Hypothesis 2 (H2).
Intention to purchase a mobile App is positively influenced by App price value.
] states that word of mouth (WOM) is referred to as “communication between consumers about a product, service, or company in which the sources are considered independent of commercial influence
” (p. 1). Such interpersonal and informal exchanges offer access to vital information regarding the consumption of products/services in addition to formal advertising. In other words, WOM adds a layer to the messages offered by sellers, and influences the decision making of consumers. WOM is broadly viewed as one of the most critical factors driving consumer behavior [40
]. As a result, WOM is recognized by various researchers [41
] as the most significant source of information in terms of consumer buying decisions. Abubakar and Ilkan [43
] point out that the emergence of online platforms has resulted in extending WOM to electronic WOM (eWOM), which is now regarded as one of the most significant information sources on the Web. In the case of eWOM, information is offered by consumers through the Internet about products/services [44
]. Specifically, consumers post and share their recommendations, comments, reviews and suggestions about products/services on the internet through various tools such as e-bulletin systems, review sites, social networking sites, discussion platforms and forums. WOM communication can have both positive (PWOM) and negative impacts (NWOM). Al-Adwan and Kokash [45
] point out that PWOM “…is triggered when there are social cues that deliver positive signs such as significant number of customers who have purchased or intended to purchase a product or service
” (p. 20). PWOM is recognized by marketing experts as an effective marketing tool as it generates positive opinions and feedback that can affect consumers’ decisions to purchase the brand in question [46
]. On the other hand, opposite effects can be generated by NWOM. The conceptualization of WOM with regard to mobile Apps in this study is described as the electronic or traditional communication of positive assessment provided by other consumers about the App in question. The content of most eWOM is generated by genuine customers who are independent of the market [39
]. Therefore, this independency makes eWOM about an App a more credible and reliable medium by decreasing risk and uncertainty about the App with respect to purchasing and using it. As a consequence, this practice of reassurance and guarantee could result in the development of consumers’ trust in the App under consideration [2
]. Accordingly, eWOM about an App can significantly influence its reference price in and raise the value of the deal. Based on such a perception of value, consumers are inclined to purchase the App in question. Hence, positive eWOM about an App is expected to improve consumers’ intention to purchase that paid mobile App.
Hypothesis 3 (H3).
Intention to purchase a mobile App is positively influenced by positive eWOM about an App.
Performance is recognized as a critical aspect in measuring mobile Apps’ service quality [47
]. The theory of expectancy-confirmation [48
] has been developed to explain consumer satisfaction. It is suggested that consumers develop expectations with regard to the performance of products/services before purchasing and will make their mind up about perceived performance after obtaining the products/services [49
]. Consumers will then compare their expectations and perceived performance. They will be satisfied if the perceived performance exceeds their expectations. On the other hand, if expectations are less than the perceived performance, a negative disconfirmation will be generated, and therefore consumers will be less satisfied. Similar to [32
], this study considers App performance in terms of the extent to which a mobile App is believed to have functional value depending on performance expectation and perceived quality. A high perception of performance is achieved when the performance of a mobile App surpasses its expected performance. Furthermore, mobile Apps are expected to operate smoothly without dropout or malfunction. Wulfert [47
] states that the performance of mobile Apps is weighted by the functional quality (the processing speed) of the App, and its resource requirements. In terms of resource requirements, two main aspects are identified: mobile network usage and device storage. The processing speed of mobile Apps relates to the processing performance of any operation or function with regard to mobile Apps, including instant page loading and transitions, smooth scrolling and quick responses to the customer’s inputs [50
]. Moreover, Madu and Madu [51
] point out that processing speed is related to the ability to download information. It also relates to the quality of data processing and transfer [52
]. Device storage usage is concerned with the use of disk space on the mobile device resulting from the downloading of mobile Apps. High memory usage is recognized as a key issue when deciding whether or not to download a particular mobile App [53
]. Given that the storage capacity of mobile devices is limited [54
], and most devices cannot be extended in terms of extra memory capacity, mobile Apps should have an appropriate size. Such a size indicates that mobile Apps should take up as little disk space as possible when it comes to providing their mobile services (m-services) to consumers [47
]. The usage of mobile network data relates to the traffic that mobile Apps cause [55
]. It measures the network traffic it causes for the mobile cellular network, and the consumers’ volume of purchased data. It is critical that mobile Apps cause as little mobile network traffic as possible, as well as the traffic required to provide their information and features. Therefore, App performance is expected to increase consumers’ intention to purchase paid mobile Apps.
Hypothesis 4 (H4).
Intention to purchase a mobile App is positively influenced by App performance.
Recent research indicates that perceived usefulness has an essential role on users’ intention to adopt mobile Apps. Based on previous research [56
], App usefulness refers to what extent the use of a mobile App improves performance in accomplishing what she/he wishes to do. Kim et al. [2
] define perceived usefulness as “…the functional value of a good, which is the utility derived from the perceived quality and expected performance of the good
”. Functional value reflects the level to which a product’s features satisfy the utilitarian needs of consumers [57
]. It has been reported that functional value is recognized as a major decisive factor regarding consumers’ purchasing decisions [37
]. When considering the purchase of a mobile App, individuals are inclined to evaluate whether or not the App is beneficial and useful in terms of what they want to achieve. Consequently, consumers’ intentions to purchase a mobile App are expected to be directly increased by the App’s perceived usefulness.
Hypothesis 5 (H5).
Intention to purchase a mobile App is positively influenced by App usefulness.
Technical reliability represents the technical features of the reliability of mobile Apps [47
]. It focuses on ensuring the consistency and accuracy of mobile Apps’ operations and services. Mobile Apps are expected to operate on mobile devices without any failure or dropout. According to the Institute of Electrical and Electronics Engineers (IEEE) [60
], reliability is described as “…the ability of a system or component to perform its required functions under stated conditions for a specific period of time
”. However, technical reliability is referred to by Parasuraman et al. [61
] as “system availability”. Al-Kuwaiti et al. [62
] point out that reliability refers “…to failure-free operation during an interval, availability refers to failure-free operation at a given instant time
” (p. 113). Accordingly, one can argue that availability can be considered as an evaluation of reliability at a particular point in time. Wulfert [47
] points out that technical reliability can be broken down into two key sub-dimensions: the m-service availability and the feature reliability of mobile Apps. Feature reliability is concerned with measuring the promised performance and adequacy of operation of a mobile App. It particularly highlights the mobile App’s reliability in terms of constant operation without any malfunctions, and the appropriate start of the mobile App. Availability refers to the percentage of time during which the system is fully operational and available. It is important that the m-services offered through the mobile App must be available at any time consumers need to use and access them. Furthermore, since there are no spatial and temporal constraints in terms of accessing m-services, such services have to be available. As m-services can be accessed without any temporal and spatial constraints, the availability of such service is deemed to be necessary any time. It has been suggested that the unavailability of m-services adversely impacts consumers’ perceptions with regard to mobile Apps’ technical reliability.
Hypothesis 6 (H6).
Intention to purchase a mobile App is positively influenced by App technical reliability.
According to the theory of innovation diffusion [63
], trialability indicates that individuals need to personally experience and try out an innovation in such a way as to entirely test that innovation before adopting it. Having the opportunity to try an innovation enables users to endorse expectations and develop beliefs as to the extent to which the innovation can meet their personal needs [64
]. Thus, it allows users to proactively avoid any potential costs and commitment by trying innovations prior to adopting them. This study describes mobile App trialability as the extent to which potential consumers believes that they can sufficiently test and try mobile Apps prior to purchase [2
]. A free trial of a new technology or system (such as mobile Apps) is effective in diminishing uncertainty and ambiguity, allowing potential users to arrive at a purchasing decision [65
]. Trial versions allow users to test and examine products and resolve any uncertainty about the products’ real value, such as ease of use and usefulness [1
]. Furthermore, trialability can act as an indication of product quality; knowing that products are available in free trial versions may act as a guarantee to consumers. Since consumers place higher weight on certain outcomes rather than merely probable ones, trialability increases the outcome certainty, and subsequently influences consumers’ intention to purchase paid mobile Apps.
Hypothesis 7 (H7).
Intention to purchase a mobile App is positively influenced by App trialability.