why“re-usable smart application for Hotel“ is the factor that plays an important role in the success of a product?

Journal of Services Marketing Enhancing customers’ continued mobile app use in the service industry Seonjeong (Ally) Lee,

Article information: To cite this document: Seonjeong (Ally) Lee, (2018) "Enhancing customers’ continued mobile app use in the service industry", Journal of Services Marketing, https://doi.org/10.1108/JSM-01-2017-0015 Permanent link to this document: https://doi.org/10.1108/JSM-01-2017-0015

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Enhancing customers’ continued mobile app use in the service industry

Seonjeong (Ally) Lee Kent State University, Kent, Ohio, USA

Abstract Purpose – This study aims to empirically investigate ways to enhance customers’ continued mobile app use intention on the basis of information adoption model. Design/methodology/approach – This study conducted an online, cross-sectional, self-administered survey, recruiting mobile app users in the USA. Findings – Results identified both argument quality and source credibility positively influenced usefulness of branded apps and parasocial interactions. Results also confirmed a positive influence on usefulness of the branded app and parasocial interaction relating to continued branded app use intentions. Originality/value – This study enriched the understanding of mobile app use behaviors, extending information adoption model in the service industry.

Keywords Usefulness, Argument quality, Mobile marketing, Parasocial interaction, Information adoption model, Source credibility, Continued mobile app use intention

Paper type Research paper

Introduction

The rapid growth of mobile technologies results in the proliferation of various types of mobile applications (hereafter, apps; Kim et al., 2015). Over 25 billion iOS apps and 50 billion Android apps were downloaded in 2015 (Dogtiev, 2015). Responding to customers’ needs, different segments of the service industry, including financial services (Ravuri, 2016), retailing (CRR, 2015), the tourism industry (Oh, 2014) and the hotel industry (Davidson, 2017), shifted to the mobile era. For example, an eMarketer’s (2015) report noted 51.8 per cent of travelers who booked trips via digital channels used mobile devices and 0.75 billion airline boarding passes were delivered via a mobile phone, increasing to 1.5 billion passes by 2019 (Statistia, 2017). Mobile marketing explains how customers access

information through personal, mobile devices, which enable them to receive personalized messages (Chou et al., 2015). It refers to “the two-way or multi-way communication and promotion of an offer between a firm and its customers using a mobile medium, device, or technology” (Shankar and Balasubramanian, 2009, p. 118). Mobile marketing started with the ShortMessage Service (SMS) for advertising purposes (Amirkhanpour et al., 2014). Potential customers received text messages related to deals and promotions through SMS (Pantano and Priporas, 2016). Mobile marketing expanded to mobile apps for smart phones, Quick Response (QR) codes and

Near Field Communication (NFC). NFC is a technology that provides mobile devices with wireless, two-way and short-range connectivity. QR codes enable customers to pay in a contactless way (Zhao et al., 2015). Development of mobile technology fosters interactive brand–

customer relationships (Shankar and Malthouse, 2007). The exponential growth of mobile technology leads to a mobile marketing platform known as “brand in the hand” (Sultan and Rohm, 2005). On the basis of customers’ increased level of engagement with mobile devices in their daily activities, service organizations develop branded apps as an essential marketing communication channel to attract new customers and enhance customers’ brand loyalty (Wang et al., 2016). Branded apps refer to “software downloadable to a mobile device which prominently displays a brand identity, often via the name of the app and appearance of a brand logo or icon, throughout the user experience” (Bellman et al., 2011, p. 191). Despite the increased role of the branded apps and their

potential impacts in the service industry, there is a dearth of research on continued branded apps use as a persuasive communication channel (Kim et al., 2015). Given managerial needs and prevalence of mobile technology, scholars (Hsiao et al., 2016; Ozturk et al., 2016a) call for more research investigating how mobile technology is used in the service industry, and the role of the branded app on customer behavior (Bellman et al., 2011; Kim et al., 2015). Previous research on mobile marketing focuses on adoption intentions toward mobile technology (Muk and Chung, 2015; Park and Kim, 2014; Slade et al., 2015). However, understanding customers’ continued mobile app use behavior is a complex process that

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Journal of Services Marketing © Emerald Publishing Limited [ISSN 0887-6045] [DOI 10.1108/JSM-01-2017-0015]

Received 17 January 2017 Revised 25 August 2017 15 January 2018 Accepted 19 April 2018

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requires sophisticated investigation beyond the technology adoption process (Ozturk et al., 2016b). While adoption models, such as technology acceptance

mode (TAM), theory of reasoned action (TRA) or theory of planned behavior (TPB), are useful in understanding how customers’ behavioral intentions toward a technology are formed, these models do not examine the persuasive process of the technology. Even though initial acceptance of technology is important, acceptance does not guarantee continued use (Hsieh et al., 2008). Customers do not automatically use branded app activities because it is in a “pull” format; meaning customers only engage with an app when they actually want to use it (Bellman et al., 2011). For instance, most mobile app users download travel apps; however, almost half of those apps are deleted later (Linton andKwortnik, 2015). This study takes the information adoption model (IAM) as a theoretical lens to examine the dual-routes of communication for continued use behaviors of a branded app in the context of the hotel industry. IAM explains the dual-process of persuasion on customers’ attitudes and behaviors (Sussman and Siegal, 2003), proposing both central cue (argument quality) and peripheral cue (source credibility) of technology. In particular, this study investigates relationships among argument quality, source credibility, usefulness, parasocial interaction and continued branded app use intentions. This study enriches IAM by incorporating a relation-related factor and applying IAM to branded app situations in the service industry. Results also provide suggestions tomanagers in the service industry, showing how to encourage customers’ continuedmobile app use behavior.

Literature review

Customer relationshipmanagement via branded apps Sustaining and creating customer loyalty helps organizations develop long-term relationships with customers (Pan et al., 2012). Mobile marketing promotes relationships between customers and service providers, enhancing customer relationship management (CRM). CRM is derived from relationship marketing, serving as the key area of services marketing (Sheth and Parvatiyar, 2002). CRM is a comprehensive strategy, integrating the marketing, sales and customer service of an organization to create and deliver value to customers (Navimipour and Soltani, 2016). Owing to severe competition, hotels attempt to improve the quality of their services to gain new customers (Wu and Lu, 2012). CRM in the hotel industry not only focuses on identifying and retaining loyal customers, but also improves the profitability of less loyal customers (Rahimi andGunlu, 2016). Mobile apps provide innovative CRM practices because they

develop new consumption habits in customers’ daily lives. A branded app builds strong relationships with customers (Watson et al., 2013). Bellman et al. (2011) support persuasive effects of branded apps, which influence the favorability of brand attitude and purchase intention. By logging in with a branded app, customers engage in multiple touch points with the brand. It allows customers to share information, engage various contents and make purchases (Wang et al., 2016). For instance, Ritz-Carlton’s mobile app provides special digital experiences related to the particular hotel location through a built-in QR code reader (Weissman, 2013). The Mandarin

Oriental Hotel’s app enables customers to use an interactive 3- D global view and local city guide (Weissman, 2013). With these various technology options, a branded app in the hotel industry provides mobile concierge (e.g. local restaurant reservations, attraction information, etc.) and service request functions to customers (e.g. housekeeping service, late check- out request, etc.; Law et al., 2015). The prevalence of mobile devices fundamentally

transformed operational practices and customers’ experiences in the hotel industry (Ozturk et al., 2016b). Hotels use mobile devices to provide personalized services to customers (Ozturk et al., 2016a) and enhance customer loyalty (Berman, 2017). For instance, customers’ preferences are stored via branded apps to sustain their relationships. However, mobile marketing requires a customer’s agreement before delivering any marketing activities (Im andHa, 2013). Thus, it is important to understand what factors influence customers’ continued mobile app use behaviors.

Information adoptionmodel Theoretical underpinnings on mobile technology research include TAM (Park and Kim, 2014), TPB (Khalifa et al., 2012), innovation diffusion theory (L�opez-Nicolás et al., 2008) and unified theory of acceptance and use of technology (Slade et al., 2015). The adoption models, such as TRA and TAM, assume customers’ adoption intentions are based on what customers expect after they adopt the technology (Filieri and McLeay, 2013). Wang and Wang (2010) argue existing technology adoption models are not enough to comprehend customers’ behavioral intentions toward mobile apps. Leisure and business travelers may consider additional factors before they decide to use the mobile hotel app (Wang and Wang, 2010). Therefore, this study applies IAM, which investigates the persuasiveness of the branded app extending beyond the formation of behavioral intentions (Sussman and Siegal, 2003). The original IAM explains argument quality and source

credibility influence information usefulness, which further influences information adoption behavior. The IAM is developed based on the TAM (Davis, 1989), TRA (Fishbein and Ajzen, 1975) and dual-process models of informational influence (Petty and Cacioppo, 1986). When customers are motivated to cognitively process information, they engage in central route processing. On the other hand, when customers have low motivation and little knowledge to process information, they engage in the peripheral route of processing (Bhattacherjee and Sanford, 2006). According to IAM, argument quality serves as an important central cue in the persuasive process (Bhattacherjee and Sanford, 2006; Li, 2013). In addition, source credibility is a peripheral cue in the persuasive process (Bhattacherjee and Sanford, 2006; Li, 2013). The dual-process of persuasion leads to users’ information adoption behaviors (Sussman and Siegal, 2003) and continued use behaviors (Hur et al., 2017). Owing to the high abandonment rates of mobile apps,

understanding factors that influence customers’ continued mobile app use behavior is critical for the success of mobile marketing (Shankar and Balasubramanian, 2009). Researchers advocate the importance of information system continuance as continued information system use is central to the survival of organizations (Bhattacherjee and Sanford, 2006; Hur et al.,

Customers’ continued mobile app use

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2017; Kim et al., 2016). Scholars (Kim et al., 2015) call for more research on factors that influence continued app use intention. Increasing app recency, the duration (e.g. the number of days) a customer has not accessed the app, indicates a sign of negative effects to the company (Kim et al., 2015). Kim et al. (2015) identifies discontinued use of a brand’s app hurts brand sales. Therefore, this study focuses on the continued branded app use intentions, which refer to the likelihood of customers’ continued use of a branded app. The IAM explains general motivations for users’ intention to

use technology, based on the dual-routes of persuasion process (Jin et al., 2009). IAM applies to different technological applications to explain how people process and adopt information, such as the information system (Li, 2015), social media (Teng et al., 2014), travel websites (Tseng and Wang, 2016) and online reviews (Zhang et al., 2014). Depending on the research context, different variables are incorporated in IAM to better understand the persuasiveness of technology. Previous research includes playfulness (Li, 2015), site attachment (Kim et al., 2016) and preference (Chang et al., 2015) into the IAM model. For instance, Jin et al. (2009) incorporates disconfirmation of information quality, disconfirmation of source credibility and satisfaction into IAM to examine continued intention to use a computer-supported social network. As this study focuses on branded apps in the service industry,

a relationship-relevant variable is included in the model to better understand IAM in such contexts. One unique characteristic of the service industry is intangibility, where inherent risks are high and relationship building is important owing to the person-based business (Weathers et al., 2007). Therefore, this study includes parasocial interaction (PSI) because developing an interaction is important owing to competitive markets in the service industry. PSI refers to media-enabled connections between users and media personalities (Rubin and Step, 2000). Such interactions allow users to enjoy interpersonal relationships with their media, enhancing the relationship between customers and brand.

Hypotheses development Argument quality The argument quality of the branded app serves as a central cue. Argument quality refers to “the persuasive strength of the arguments embedded in an information message” (Bhattacherjee and Sanford, 2006, p. 811). Argument quality is based on customers’ rational and cognitive judgment (Bhattacherjee and Sanford, 2006) and is validated through comprehensiveness, accuracy and relevance of the information (Delone andMcLean, 2003). People are involved in thoughtful processing for persuasive arguments to generate their own thoughts (Hur et al., 2017). Such argument quality is associated with task-related or functional information, serving as an important central cue for customers’ purchase decisions (Zhu et al., 2016). Argument quality plays an important role in information technology (Kim et al., 2016), since it influences customers’ trust (Filieri et al., 2015), persuasive messages (Teng et al., 2014) and usefulness (Cheng and Ho, 2015). If a mobile app is perceived as effective, users develop a positive attitude toward the mobile app and vice versa (Cheung et al., 2009).

When a branded app is valuable to use, it was observed that customers had better evaluations toward the app. Bellman et al. (2011) confirmed informational style encouraged generation of personal connections with the brand and showed more advertising effectiveness. Kim et al. (2013) also identified informational message strategies were used more in service branded apps than in product branded apps. In addition, it was assumed when a mobile app provided quality service customers were more likely to have enhanced feelings of PSI. Motivation was central to PSI, as different motivations led to various communication choices and behaviors (Rubin and Step, 2000). Previous studies identified social media users’ motivations for using media positively influenced PSI (Joinson, 2008; Yuan et al., 2016). In the context of mobile technology, Hur et al. (2017) identified argument quality positively influenced relationship maintenance motives, along with information seeking motives and entertainment motives. In line with IAM and previous research, this study proposed positive effects of argument quality on usefulness and customers’ relationships with the brand.

H1. Argument quality has positive effects on usefulness of the branded app.

H2. Argument quality has positive effects on customers’ feelings of PSI.

Source credibility The source credibility of the branded app is an important peripheral cue. Source credibility refers to “the perceived ability and motivation of the message source to produce accurate and truth information” (Teng et al., 2014, p. 748). Source credibility explains whether users perceive an information source as believable, competent and trustworthy (Gunawan and Huarng, 2015) through expertise, trustworthiness and attractiveness (Teng et al., 2014). Source credibility is more influential for weak arguments and/or customers’ low involvement conditions; however, argument quality is more persuasive for object-relevant arguments, such as product-relevant attributes when customers are highly involved (Li, 2013). In mass communication contexts, source credibility

determines audiences’ attitudes toward mass media sources (Hovland et al., 1953). Previous studies identify source credibility influences customers’ attitudes (Ayeh, 2015), persuasive messages (Teng et al., 2014) and perceived usefulness (Ayeh, 2015). In addition, source credibility influences feelings of interaction, such as PSI (Yuan et al., 2016). Celebrity source credibility (Ohanian, 1990), media features and customer characteristics (Kim and Rubin, 1997) influence PSI. Yuan et al. (2016) identified source credibility also influenced PSI, which further influenced attitude and customer equity drivers in a social media context. Hur et al. (2017) identified source credibility positively influenced different customers’ motives, such as information seeking motives, entertainment motives and relationship maintenance motives in the context of travel-related social media. Therefore, positive customer evaluations are predicted when the branded app includes source credibility. Applying the role of source

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credibility in a branded app context, the following hypotheses are proposed:

H3. Source credibility has positive effects on usefulness of the branded app.

H4. Source credibility has positive effects on customers’ feelings of PSI.

Usefulness of the branded app Perceived usefulness is an important determinant in information system use (Adams et al., 1992). Usefulness refers to whether potential users expect benefits when using an information technology system for their task performance (Davis et al., 1989). According to the IAM, usefulness plays an important role between central and peripheral cues of persuasive information and information adoption behavior (Zhu et al., 2016). In a mobile app context, characteristics of the branded app help customers evaluate the usefulness of a mobile app, such as whether the mobile app is worth using in the service delivery process. For instance, Kim et al. (2016) identified the positive relationship between usefulness and continuing usage of mobile tourism shopping. Since the branded app is expected to include useful features in making customers’ use behaviors, this study predicts a positive effect of usefulness on continued mobile app use intentions. Based on IAM and previous research, the following hypothesis is proposed in the context of a branded app in the service industry.

H5. Usefulness positively influences customers’ continued mobile app use intentions.

Parasocial interaction Horton and Wohl (1956) proposed the idea of PSI, which explains a face-to-face interaction that occurs between media characters and their audience (Ballantine and Martin, 2005). PSI is a social interaction rather than personal, owing to proximity, similarity and attraction characteristics (Wohlfeil and Whelan, 2012). PSI refers to an imaginary social relationship (Cohen, 2004), an illusion of a face-to-face relationship (Horton and Wohl, 1956) and an interpersonal interaction between media user and the consumed media (Schramm andWirth, 2010). Branded apps provide a “pull” marketing opportunity

delivered via a mobile platform where customers develop

strong emotional attachments toward the brand. Many brands aim to emphasize the interactive experience between customers and mobile apps (Bellman et al., 2011). For instance, Zhu et al. (2016) identified the role of relationship type on customers’ product usefulness evaluation. They investigated tie strength as a form of relationship type. Previous research identified the positive role of PSI on customers’ responses. For instance, PSI positively influences customers’ loyalty intentions (Labrecque, 2014) and customer equity drivers (Yuan et al., 2016). Thus, this study predicts PSI plays a positive role in the context of branded apps, proposing the following hypotheses:

H6. Customers’ feelings of PSI positively influence usefulness of the branded app.

H7. Customers’ feelings of PSI have positive effects on their continuedmobile app use intentions.

Continued mobile app use intentions On the basis of attitude theory (Ajzen, 2002), continuedmobile app use intentions explain the likelihood of using a mobile app over service staff during the service delivery process. Owing to the predictive power of behavioral intentions, use intentions are one of the important concepts in information systems and marketing literature (Davis, 1989; Hur et al., 2017). Behavioral intention refers to a person’s subjective probability to carry out a specific action (Ajzen and Fishbein, 1980). Previous research (Venkatesh and Davis, 2000) identified that intention serves as a major determinant on actual behavior. Even though mobile phones are ubiquitous, not many customers experience a branded app in the service industry because they are considered in infancy stage. Thus, investigating customers’ continued mobile app use intention is a desirable approach, allowing a timely investigation of customers’ perceptions toward mobile app use. On the basis of the above discussions, Figure 1 describes the

hypothesized relationships. The proposed conceptual model is useful in understanding and predicting customers’ continued branded app use behavior.

Methodology

Study context The hotel industry serves as the study context. Mobile technology is “new buzz” in the hotel industry as more customers attempt to use mobile apps for their service delivery

Figure 1 Proposed framework

Source credibility

Argument quality

Parasocial interaction

Usefulness

Continued use intentions

H1

H4

H3 H6

H2

H7

H5

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process (Rudra, 2016). With mobile technology emerging as a major distribution channel, understanding factors that influence customers’ continued mobile app use intentions in the hotel industry becomes vital (Ozturk et al., 2016a). Features of a hotel app offer hotel information and services (e.g. location, amenities and facilities), enabling customers to customize their service and update their preferences (Ozturk et al., 2016b). Accordingly, it is expected that hotel apps will play a key role, not only in distribution of rooms, but also in strengthening customer relationships and brand loyalty (Anuar et al., 2014). The nature of the service industry involves interactive

processes between customers and service providers, which require customers to coproduce services (Verleye, 2015). During the service delivery process, customers decide to use mobile apps or interact with service staff for a similar service outcome. For example, hotel customers are encouraged to coproduce their service delivery process for check in/out on behalf of service representatives by using their app. In addition, the hotel industry is in an early stage of implementing mobile apps into the operational process; therefore, they need to understand how to promote customers’ continued mobile app use behavior to garner a better return on investment.

Survey development The online survey included five parts: screening questions, previous mobile app experience, argument quality and source credibility, usefulness, PSI and continued mobile app use intention and respondents’ background questions. The survey beganwith two screening questions asking whether: 1 respondents stayed at a hotel within the previous 12

months; and 2 they used a hotel app during their hotel stays within the

previous 12 months.

Once these two qualification questions were met, respondents were asked to provide the hotel app they used to recall their memories. To control the quality of responses, five validation questions were included throughout the survey. Validation questions, such as “click strongly agree to proceed with the survey”, were included to ensure respondents carefully read survey questions before answering. Respondents who answered the qualification and validation questions correctly were included in the data analysis. A seven-point, Likert-type scale (1= strongly disagree to 7=

strongly agree) was used in the survey. Measurement items were adapted from previous studies to ensure validity and reliability issues. Measurement items of argument quality were measured with three items, adopted from Chang et al. (2015) and measurement items of source credibility were measured with three items adopted from Li (2013). Items of usefulness, PSI and continued mobile app use intentions were from Gao et al. (2013), Labrecque (2014) and Ayeh (2015), respectively. Items of usefulness included three items, PSI included six items and continuedmobile app use intentions included three items.

Data collection A pilot test was conducted with 60 students enrolled in a mid- western university. Minor adjustments were made to the survey to improve flow and clarity based on results from the pilot test. After the pilot, a Web-based, self-administered survey was used

for data collection. The professional online research company, Qualtrics, was hired to collect data. On the basis of the convenience sampling method, an invitation email was sent to consumer panel members of the online research company, who were over 18 years old and represented the general population of the USA. Among those members, those who had stayed at a hotel in the previous 12 months and used a hotel mobile app in the past 12months were qualified to participate in the survey. A total of 350 surveys were collected within a week; however,

15 surveys were excluded from analysis owing to incomplete or invalid responses. This study aimed to collect 300 responses based on the rule of thumb for the sample size requirement of structural equation modeling (SEM). The required sample size was based on 10 responses per one variable or 5 to 10 observations per estimated parameter to apply SEM for the data analysis (Bentler and Chou, 1987). A total of 335 surveys were used for data analysis, which was enough to apply the SEM.

Data analysis Data were analyzed using the LISREL 8.80 structural equation analysis package (Jöreskog and Sörbom, 1989) based on Anderson and Gerbing’s (1988) two-step approach – confirmatory factor analysis (CFA) and SEM. Before conducting the two-step approach, initial data analysis was conducted. Non-response bias analysis was conducted since this study used a self-reported online survey. Early responses were compared with later responses (Ary et al., 1996) and no significant differences were identified; thus, non-response bias was not an issue in this study. Normality was also checked based on the results of skewness and kurtosis values. Values of skewness and kurtosis were between -2 and12, representing an acceptable range (Hair et al., 2010). In addition, the Kaiser– Meyer–Olkin (KMO) test and the Bartlett’s Test of Sphericity were used to measure sampling adequacy. The value of the KMO value was 0.958 and the significance of the Bartlett’s Test of Sphericity was 0.00, indicating the suitability of factor analysis (Hair et al., 2010). An exploratory factor analysis was conducted to examine the

underlying factor structure of the construct as measurement items were modified based on the study context (e.g. the hotel industry). Three measurement items from PSI were eliminated owing to cross-loadings and ambiguity. Moreover, a CFA of all items loading on a single latent factor was performed to rule out common method bias (Podsakoff et al., 2003). Results of the CFA with a single factor indicated a poor fit compared with the multi-factor models; thus, common method bias was not an issue in this study.

Results

Sample characteristics Almost half of the respondents were female (50.7 per cent). A majority of respondents were between 25 and 34 years of age (37.9 per cent), followed by 35 and 44 years (25.1 per cent) and 19 and 24 years (14.3 per cent; see Table I). Respondents had hotel app experiences with different brands, includingMarriott (n = 120), Hilton (n = 60), Hyatt (n = 28), Intercontinental (n = 54), MGM Resorts (n = 5), Omni (n = 7), Choice Hotels

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(n = 19), Drury Hotels (n = 2), Red Roof Inn (n = 4), Wyndham (n = 20) and BestWestern (n = 16).

Measurementmodel According to the results from the CFA, the goodness of fit indices were x2 (80) = 158.31, p = 0.00; x2/df = 1.97; normed fix index (NFI) = 0.98; non-normed fit index (NNFI)= 0.99; incremental fit index (IFI)= 0.99; comparative fit index (CFI) = 0.99; goodness of fit index (GFI)=0.94; standardized root mean square residual (SRMR)= 0.034; and root mean square error of approximation (RMSEA) = 0.054. Results indicated an acceptable value for each model fit index based on Bagozzi and Yi’s (1988) recommendation. Therefore, it was concluded themeasurementmodel fit well with the data. Results of CFA were used to evaluate construct reliability

and validity. Convergent validity was investigated through factor loadings, average variance extracted (AVE), Cronbach’s alpha and composite reliability (CR; see Table II). Factor loadings exceeded the recommended level of 0.60; values of AVE were greater than 0.50; and values of reliabilities were close to 0.90 (Hair et al., 2010). In addition, discriminant validity was investigated by comparing the squared correlations between constructs and variance extracted from a construct. All AVE estimates were larger than the corresponding squared inter-construct correlation estimates, showing discriminant validity (see Table III; Fornell and Larcker, 1981).

Structural model and hypothesis testing SEM results confirmed an acceptable value for each model fit index (Bagozzi and Yi, 1988). The goodness-of-fit statistics for

the structural model were x2 (82) = 158.92; p = 0.00; x2/df = 1.93; NFI = 0.98; NNFI= 0.99; IFI= 0.99; CFI = 0.99; GFI = 0.94; SRMR= 0.035; andRMSEA= 0.053. The proposed hypotheses were investigated based on the

results of the SEM (see Table IV). Argument quality positively influenced usefulness of the branded app (b = 0.43, p < 0.00) and feelings of PSI (b = 0.20, p < 0.05), supporting Hypotheses 1 and 2. The effects of argument quality on customers’ responses were consistent with previous research (Cheng and Ho, 2015; Teng et al., 2014). Source credibility also positively influenced usefulness of the branded app (b = 0.20, p < 0.05) and feelings of PSI (b = 0.75, p < 0.00), supporting Hypotheses 3 and 4. Consistent with previous research (Ayeh, 2015; Teng et al., 2014), results indicated a positive influence of source credibility on customers’ responses. These findings confirmed that when customers perceived high levels of argument quality and source credibility from a branded app, they developed positive evaluations toward the branded app. Moreover, usefulness of the branded app influenced

customers’ continuedmobile app use intentions (b = 0.37, p< 0.00), supporting Hypothesis 5. Customers’ feelings of PSI positively influenced usefulness of the branded app (b = 0.24, p < 0.00) and customers’ continued mobile app use intentions (b = 0.54, p < 0.00); thus, Hypotheses 6 and 7 were supported. The impact of PSI on customers’ continued mobile app use intentions showed a stronger path coefficient than the path from usefulness of the branded app. This result supported the importance of PSI on the branded apps, in addition to usefulness in the service industry. PSI promoted customers’ continued app use intentions in the service industry where relationship building played a vital role in enhancing customers’mobile experiences.

Discussion

Mobile marketing strategies were based on how customers accessed information through mobile devices and interacted with a company (Chou et al., 2015). Previous studies investigated mobile marketing by examining risk avoidance (Gao et al., 2013), personal traits (such as innovativeness) (Rohm et al., 2012), value co-creation (Morosan and DeFranco, 2016), perceived value (Turel et al., 2007) and social influence (such as subjective norm; Ozturk et al., 2016b). With the increased role of mobile marketing, little attention was paid to factors that promoted customers’ continuedmobile app use behavior and examined the persuasiveness of a branded app. Therefore, this study investigated important factors that promoted customers’ continued mobile app use intention in the service industry. As central and heuristic cues of the persuasion process, both

argument quality and source credibility of a branded app positively influenced usefulness and feelings of PSI. Among those relationships, the strongest was between source credibility and PSI, followed by the relationships between argument quality and usefulness, argument quality and PSI and source credibility and usefulness. The effects of argument quality and source credibility were consistent with previous research. Jin et al. (2009) identified positive effects of argument quality on information usefulness and positive effects of source

Table I Respondents’ background (N = 335)

Characteristic Frequency (%)

Gender Female 170 50.7 Male 165 49.3

Age 18-24 years old 48 14.3 25-34 years old 127 37.9 35-44 years old 84 25.1 45-54 years old 45 13.4 55-64 years old 22 6.6 65 years and older 9 2.7

Education High school 75 22.4 Associate degree 85 25.4 Bachelor degree 125 37.3 Master’s degree 42 12.5 Doctoral degree 8 2.4

Annual household income Under $50,000 84 25.1 $50,000-$74,999 108 32.2 $75,000-$99,999 72 21.5 $100,000-$124,999 31 9.3 $125,000-$149,999 22 6.6 $150,000 and above 18 5.4

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credibility on customer satisfaction in the context of a computer-supported social network. Interestingly, effects of argument quality on usefulness of the

branded app were stronger than those of source credibility. Effects of source credibility on PSI were stronger than those of argument quality. These results were owing to dual-routes of the persuasion process (Sussman and Siegal, 2003). Argument quality was based on cognitive evaluation, whereas source credibility was based on affective evaluation (Sussman and Siegal, 2003). Thus, the effects of each process were different. Results not only made comparisons between the systematic and heuristic persuasion process toward the branded app, but also contributed to mobile marketing research by examining the dual-route of persuasive communications in enhancing customers’ continuedmobile app use intentions. Moreover, usefulness of the branded app had significant

effects on customers’ continued mobile app use intention, supported in the IAM and previous literature (Bhattacherjee and Sanford, 2006; Zhu et al., 2016). Consistent with previous

research (Lee and Lee, 2017; Yuan et al., 2016), results supported a positive influence of PSI on usefulness and customers’ continued mobile app use intention. Mobile technologies transformed the mobile device into an innovative, powerful platform that engaged customers (Gao et al., 2013). As more customers adopted mobile technology, it became an indispensable distribution channel in the service industry. It was imperative to understand key determinants of customers’ continued mobile app use intentions. Success of information systems depended on customers’ continued use of technology, rather than initial acceptance (Bhattacherjee, 2001). Thus, encouraging customers’ continued mobile app use intention was a desirable marketing approach because the brand grew by increasing return on investment and attracting more customers to the business.

Conclusions

Theoretical contributions This research developed and empirically examined a theoretical model that investigated antecedents of customers’ continued mobile app use intentions. Results demonstrated the IAM was highly predictive of customers’ continued mobile app use intentions, examining the formation of customers’ continued mobile app use intentions. Results of this research provided theoretical contributions to the mobile marketing in a general context and to branded apps in a service industry context. This study contributed to previous mobile marketing

research by providing a conceptual model that predicted customers’ continued app use intention in the service industry. While the importance of adoption and use behaviors is recognized in mobile marketing (Muk and Chung, 2015;

Table II Measurement model results (N = 335)

Measurement items Mean (SD) SFL CR a

Argument quality 0.91 0.91 Using the branded mobile app is informative 5.80 (0.90) 0.89 Using the branded mobile app is valuable 5.80 (0.89) 0.88 Using the branded mobile app is helpful 5.56 (0.92) 0.72

Source credibility 0.90 0.90 Using the branded mobile app is trustworthy 5.57 (1.01) 0.81 Using the branded mobile app is credible 5.76 (1.00) 0.88 Using the branded mobile app appears to be an expert 5.68 (0.98) 0.91

Usefulness 0.90 0.90 Using the branded mobile app would be useful in requesting my service 6.12 (0.97) 0.85 Using the branded mobile app would make my hotel stay easier 5.90 (1.05) 0.92 Using the branded mobile app would be useful in meeting my needs 5.78 (1.06) 0.85

Parasocial interaction 0.89 0.89 Using the branded mobile app makes me comfortable, as if I am with a friend 5.39 (1.43) 0.84 When I interact with the branded mobile app, I feel included 5.76 (1.19) 0.85 I can relate to the branded mobile app 5.74 (1.14) 0.88

Continued use intention 0.94 0.94 I intend to use the branded mobile app for the next time 4.55 (1.62) 0.92 I expect to use the branded mobile app in the future 4.72 (1.62) 0.97 I plan to use the branded mobile app in the future 4.67 (1.66) 0.89 SFL refers to standard factor loadings, and CR refers to composite reliability

Table III Discriminant validity (N = 335)

Constructs 1 2 3 4 5

1. AQ 0.85 2. SC 0.46 0.88 3. USE 0.35 0.35 0.84 4. PSI 0.35 0.49 0.32 0.84 5. UI 0.14 0.18 0.18 0.20 0.80 Note: The values in italic represent the average variance extracted and the values below represent the squared inter-construct correlations

Customers’ continued mobile app use

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Journal of Services Marketing

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Slade et al., 2015), the conceptualization and empirical validation of continued mobile app use behavior derived from the dual-persuasion process in a branded app has not been addressed. Simply investigating customers’ intentions to adopt technology does not guarantee long-term success of the branded app (Wang and Wang, 2010). Investigating and validating customers’ continued mobile app use intentions provided a theoretical contribution by determining a role of persuasive process in the development of customers’ continued use behavior. In addition, this study investigated the persuasion process

of the branded app, derived from IAM research (Sussman and Siegal, 2003). Applying IAM to a mobile app context of the service industry extended the applicability of IAM theory to other contexts. By using the IAM to gain insights into branded apps in the service industry, this study revealed central and peripheral routes were not mutually exclusive in branded app contexts, as customers relied on both information processes to evaluate branded apps. Building upon previous research on the dual-routes of persuasion, this study revealed both dimensions were critical determinants that significantly influenced customers’ continued mobile app use intentions. Moreover, results provided insights on the role of PSI in a

branded app context. Reflecting on unique characteristics of the service industry, an additional construct was incorporated into the IAM model to better understand factors influencing customers’ continued mobile app use intention. Investigating the formation of usefulness perceptions and PSI helped researchers understand the dynamics of branded apps at the micro-level. Results of this research were supported in the behavioral decision theory (Edwards, 1961). Behavioral decision theory explained customers’ decision-making processes were based on their values and beliefs (Einhorn and Hogarth, 1981; Khan et al., 2005). When customers were confronted with options, they weighed available options before making decisions. Customers needed to use their time and skills when requesting service via mobile apps, compared to when they received service via a standardized method or a person-to-person interaction. Therefore, findings contributed to the emerging mobile marketing literature on PSI, proposing how positive relationship marketing was achieved via mobile apps.

Industry implications Results suggest ways to gain competitive advantages for branded app use in the service industry. As the mobile app is a popular communication channel, understanding how and why customers engage provides useful implications for service businesses to gain competitive advantages (Tsiotsou, 2015). More companies are adopting branded apps given the potential advantages of adopting this technology (Jan and Contreras, 2011). For instance, Marriott implements a mobile request function in its app, enabling customers to request service before, during or after their hotel stay (Wolf, 2017). If the customer’s requested room is ready before check-in, the app provides an automatic notification to the customer. Conard Hotels’ app from Hilton serves as a full-service concierge. The Conard Hotel app enables customers to customize and arrange their room service options, bath amenities and airport transportation (Weissman, 2013). Even though apps are powerful advertising tools, their positive impact on customer relationship building occurs only when customers are willing to continuously use the mobile app (Kim et al., 2015). Thus, branded apps should include features that enhance customers’ continued use intentions. The results identified both central and peripheral processing

persuaded customers. Service organizations should convey strong arguments in their mobile app strategies. Argument quality had a significant impact on perceived usefulness and PSI; thus, the service industry should contribute high-quality content given that accuracy of information is a vital factor influencing customers’ continuous branded app use behavior. For instance, a branded app can convey updated and relevant information and include detailed and in-depth information to enhance central processing. In addition, service organizations should enhance source

credibility of branded apps. Branded apps need to incorporate trustworthy perceptions and integrity as a way of source credibility. Mobile apps use different types of peripheral cues, such as pictures and virtual tours, to formulate source credibility. For instance, branded apps can include vivid pictures and live videos to enhance trustworthy perceptions and believability of the branded apps. Moreover, mobile apps enhance usefulness and PSI to promote customers’ continued use intentions. Branded apps can be integrated with other communication channels, such as websites and social media, to promote usefulness and PSI features of branded apps. When customers feel PSI and usefulness, they are more likely to use the mobile app in their daily life. With easily incorporated and user-friendly technologies, service organizations can foster a favorable relationship with customers via branded apps.

Limitations and suggestions for future research This study had limitations, suggesting the need for future research. Respondents were previous hotel customers in the USA. Many service organizations pursue globalization to serve customers worldwide. Thus, cultural differences might play a significant role in responses. For instance, investigating different cultural backgrounds could provide different perceptions of mobile app persuasiveness. In addition, there were technological issues for customers to adopt branded apps. Mobile apps often required updates, and installing updates burdened customers. Therefore, future research should

Table IV Structural model results (N = 335)

Structural paths Standardized

path coefficients t-statistic

Results of hypotheses testing

H1: AQ! Usefulness 0.43*** 4.50 Supported H2: AQ! PSI 0.20** 2.21 Supported H3: SQ! Usefulness 0.20** 1.80 Supported H4: SQ! PSI 0.75*** 8.68 Supported H5: Usefulness! Use intention

0.37*** 3.29 Supported

H6: PSI! Usefulness 0.24*** 2.85 Supported H7: PSI! Use intention

0.54*** 4.88 Supported

Notes: ***p < 0.01; **p < 0.05; NFI = 0.98; IFI = 0.99; CFI = 0.99; RMSEA = 0.048

Customers’ continued mobile app use

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investigate the role of technological issues, such as technology compatibility, to better understand customers’ mobile app use behavior. In addition, this study focused on argument quality and

source credibility as mobile app features based on the IAM. Different styles influence customers’ attitudes and behaviors in the branded app (Bellman et al., 2011). Therefore, future research should investigate how to design mobile app interfaces, and what content create real-world app practices that encourage customers’ engagement. Moreover, individual differences and situational characteristics should be explored. For instance, the role of customers’ involvement (Jung et al., 2016) should be investigated in the proposed model investigate persuasive branded app use in the service industry.

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Further reading

Oh, H., Jeong, M. and Baloglu, S. (2013), “Tourists’ adoption of self-service technologies at resort hotels”, Journal of Business Research, Vol. 66No. 6, pp. 692-699.

Corresponding author Seonjeong (Ally) Lee can be contacted at: [email protected]

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Customers’ continued mobile app use

Seonjeong (Ally) Lee

Journal of Services Marketing

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