How perceived value drives the use of mobile financial services apps

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY-NC-ND 4.0 https://creativecommons.org/licenses/by-nc-nd/4.0/ How perceived value drives the use of mobile financial services apps © 2018 Elsevier Ltd. Accepted version (Final draft) Karjaluoto, Heikki; Shaikh, Aijaz A.; Saarijärvi, Hannu; Saraniemi, Saila Karjaluoto, H., Shaikh, A. A., Saarijärvi, H., & Saraniemi, S. (2019). How perceived value drives the use of mobile financial services apps. International Journal of Information Management, 47, 252-261. https://doi.org/10.1016/j.ijinfomgt.2018.08.014 2019 How perceived value drives the use of mobile financial services apps Abstract Mobile information services have revolutionized business models and service delivery methods by facilitating consumer access to information and order placement via mobile apps. In developed markets, mobile banking (m-banking) and mobile payment (m-payment) applications have replaced text-based mobile services. However, extant research has not addressed these mobile financial services apps (MFSAs) adequately from the perspective of consumer behavior. Thus, the present study developed and tested a series of hypotheses related to the antecedents of perceived value of MFSA use; it also examined how such use affects the development of customers’ overall relationships with banks. Our hypotheses were tested using two samples (N=992; N=524) comprising different types of MFSA endusers in one of the leading countries in digital banking, Finland. The results supported most of the hypotheses and revealed that self-congruence and new product novelty are the principal drivers of perceived MFSA value. In addition, the findings show that the perceived value of MFSAs yields strong positive effects on customers’ overall satisfaction and commitment to their bank. The present study’s key managerial implication is that banks’ investments in developing MFSAs result in improved relationships with customers and increased business. Keywords: Mobile financial services apps; Perceived value; Personal innovativeness; Self-congruence; New product novelty 1. Introduction M-banking and m-payment apps are recognized far and wide as highly critical components of mobile information services, providing a host of value-added and technology-based financial services to consumers. These services include, but are not limited to, funds transfers, balance inquiries, buying insurance, paying utility bills, receiving critical service alerts, messaging personal banking advisors, and saving beneficiary information. M-banking – which refers to the execution of financial and non-financial transactions using a mobile device, such as a cell phone or tablet (Shaikh & Karjaluoto, 2015) – has received greater attention from consumers recently, as it offers high usability, usefulness, and a personalized banking experience. On the other hand, m-wallet is an advanced m-application that includes several elements (e.g., m-payments) that contain information related to membership, including loyalty cards, and the ability to store both personal and sensitive information, including passports, credit card information, PIN codes, and encrypted online shopping accounts (Hepola, Karjaluoto, & Shaikh, 2016). Finland, the context of this study, reports a near 90% adoption rate for individual online banking service usage among consumers between 15 and 79 years old, and approximately three out of four (77%) adults in Finland own a smartphone that is not their primary device for accessing the Internet (Statistics Finland, 2018). Since 2016, the number of logins via m-banking apps has surpassed logins via desktop computers in Finland (Danske Bank, 2016). In addition, OP (2017), one of the largest financial groups in Finland, reports that in December 2017, m-banking received the distinction of being consumers’ primary service delivery channel for accessing banking services (with over 18 million logins), followed by online banking (with 9 million logins) and m-wallet logins (over 2.5 million). The present study’s purpose is multifold. First, a cursory analysis of consumer and information systems (IS) literature has suggested that individual acceptance of IS technology, such as m-banking services, occurs as both a central and recurrent theme in end-user research. Second, a great deal of extant research (e.g., Cruz, Barretto Filgueiras Neto, Munoz-Gallego, & Laukkanen, 2010; Laukkanen & Lauronen, 2005; Shaikh & Karjaluoto, 2015) has examined mobile financial services (MFS) and their many facets, such as m-banking and m-payment services. Third, a great deal of research on MFS (e.g., Glavee-Geo, Shaikh, & Karjaluoto, 2017; Shareef, Baabdullah, Dutta, Kumar, & Dwivedi, 2018) has chosen user pre-adoption and resistance (e.g., Laukkanen & Kiviniemi, 2010) perspectives, with a focus on users’ intent to access web- and text-based MFS. To date, little empirical evidence exists regarding the consequences of online banking use from the perspective of mobile app usage. Fourth, through a meta-analysis on m-banking-services adoption, Baptista and Oliveira (2016) have shown that many relevant studies in this field come from Asia or South Africa, and that only a few recent studies have been conducted in countries in which digital banking and payment adoption is more mature. They concluded that more research is needed on the antecedents and consequences of mapplications’ adoption and use. Thus, the present study intends to answer these calls for more research. Against this backdrop, the present study contributes to the ongoing debate concerning MFSA usage. In addition, this study advances our knowledge of the antecedents and consequences of perceived value (PV) in the MFSA context. This study develops a detailed series of hypotheses concerning the effects of personal innovativeness (PI), self-congruence (SC), perceived risk (PR), and new product novelty (NPN) on PV, as well as between PV and customer relationship metrics (measured as overall satisfaction and commitment). Relatively little research has considered how the PV of using m-applications affects the wider perspective of customer relationships. Specifically, extant literature has not considered the effects of m-application use on the relationship between m-application users and service providers. Thus, our study intends to fill this gap by discussing the effects of use on customers’ overall satisfaction and their commitment to their service providers. The remainder of this study proceeds as follows. Next, we present the theoretical background by discussing the principal study constructs and their application in the MFSA field. Subsequently, we present the research model and hypotheses. Thereafter, the research methodology is outlined, followed by a presentation of the results and finally a discussion of both the theoretical and managerial implications of the findings, as well as the study’s limitations. We conclude with recommendations for future research. 2. Theoretical background 2.1. Mobile financial services Due to the increasing importance and usage of MFS in developed, emerging, and developing countries, examining consumer responses in adopting and using MFS has become many scholars’ research priority (Yen & Wu, 2016; Lee, Park, Chung, & Blakeney, 2012; Peffers & Tuunanen, 2005). The present study considers MFS to consist of two major digital banking channels: m-banking and m-wallet (also referred to as m-payments). Financial and non-financial firms have developed and deployed various mechanisms to access and use MFS. For example, m-banking services – considered to be the most value-adding and important m-commerce applications (Singh & Srivastava, 2018) – can be accessed through texts or SMS, mobile Internet, and downloadable mobile applications. Although text/SMS banking provides limited service options, downloadable m-banking apps provide wider and more cost-effective service options, as well as greater protection. Consequently, MFSAs have become very popular in developed countries, such as Finland, which have advanced infrastructure and Internet connectivity. These MFSAs, because of their increasing ubiquity, convenience, and innovative options for banking and making payments virtually anytime, anywhere, have achieved vast market potential. 2.2. Perceived value (PV) PV offers a basis for understanding consumer behavior in the contexts of e-services (Li & Mao, 2015) and mobile IS (Shaikh & Karjaluoto, 2016). Zeithaml (1988, p.4) defined PV as “the global evaluation of the consumer regarding the utility of the product based on the perception of what is received in exchange for what is given.” The top priority for any business is to create value for customers while extracting value for the firm (Kumar & Reinartz, 2016). PV is the fundamental basis for many organizational activities, and it is considered essential to a firm’s success due to its significant impact on brand loyalty (García-Fernández, Gálvez-Ruíz, & Vélez- Colón, 2018). PV also represents the aggregation of benefits that the customer is seeking, expecting, or experiencing, as well as the possible undesired consequences resulting from them (Kumar & Reinartz, 2016). PV has been conceptualized as both a unidimensional and multidimensional construct (Yeh, Wang, & Yieh, 2016). Following Sweeney and Soutar’s (2001) scale-development study, PV often has been conceptualized through multiple dimensions, such as utilitarian, to include quality, price, and emotional and social value (Kim & Han, 2011; Li & Mao, 2015; Pihlström & Brush, 2008). Therefore, PV eventually can be approached through two broad dimensions: utilitarian and hedonic (Im, Bhat, & Lee, 2015). In the context of mobile data services, Kim & Han (2011) argue that utilitarian value is related closely to the effectiveness and efficiency resulting from the use of a particular service in accomplishing any everyday task and, therefore, widely is considered very instrumental in nature. On the other hand, hedonic value is considered non-instrumental, experiential, and effective, resulting from the pleasure and fun derived from use, rather than task completion (Kim & Han, 2011; Li & Mao, 2015). Together, these value dimensions provide a strong conceptual lens through which to view and understand consumer perceptions and behaviors. 2.3. Antecedents of perceived value 2.3.1 Personal innovativeness (PI) Personal innovativeness (PI) originally is derived from the Diffusion of Innovations Theory, one of the oldest social-science theories (Rogers, 1962). PI refers to the degree to which an individual is early in adopting new ideas compared with the average member of his or her social system (Leicht, Chtourou, & Youssef, 2018). Similarly, PI is considered a personal trait (Thakur, Angriawan, & Summey, 2016), normally associated with risk-taking consumers when they try new innovations and services, such as MFSAs. PI is a central factor that affects the adoption of IS, and research has examined it in relation to perceived ease of use and perceived usefulness (Thakur & Srivastava, 2014; Karjaluoto, Töllinen, Pirttiniemi, & Jayawardhena, 2014), and technological innovativeness and gadget lovers (Thakur et al., 2016). In a study conducted on business-to-business (B2B) sales managers’ willingness to use mobile CRM, Karjaluoto et al. (2014)) found that PI affects perceived ease of use, but not perceived usefulness, directly. Avlonitis and Panagopoulus (2005) said innovative consumers have more experience using different IS, which explains its positive effects on ease of use. 2.3.2 Self-congruence (SC) Until recently, research on SC with services and brands focused on offline aspects (Wallace, Buil, & de Chernatony, 2017). Scholarly research on IS has broadened exploration of SC to consider online services as well. The terms “self-congruence (SC),” “self-image congruence,” “self-congruity,” and “image congruence” are used interchangeably in IS literature (Hepola et al., 2016). The concept of SC widely is considered to be important for understanding the relationship between consumers, brands, and brand outcomes (Kressmann, Sirgy, Hermann, Huber, Huber, & Lee, 2006). According to Japutra, Ekinci, and Simkin (2017), SC reflects consumers’ perceptions of the fit between self-concept, which can be either actual or ideal, and brands’ or services’ personality or image. SC has multidimensionality, but for the sake of the present study, the perspective of “actual” SC is adopted because it represents “the real me” of the consumer. Thus, it has been found to yield a higher emotional attachment with the brand (Malär, Krohmer, Hoyer, & Nyffenegger, 2011). SC exists when the stereotype of the typical user of a brand (brand-user image or brand personality) matches with a consumer’s self-concept (Cowart, Fox, & Wilson, 2008; Kressman et al., 2006, Sirgy et al., 1997). This match implies that the use of the brand enhances a consumer’s self-esteem (Malhotra, 1988) and self-consistency (Ericksen & Sirgy, 1989). Self-concept is multi-dimensional, reflecting different perspectives of the self: actual self-image, ideal self-image, social self-image, and ideal social self-image (Sirgy, 1982). SC plays a critical role in many evaluations and brand outcomes, such as assessments of user satisfaction, PV, and brand loyalty (Loh, Ahmad, Kadir, & Alam, 2015; Shaikh & Karjaluoto, 2016). If a brand is closely connected with one’s sense of self, he or she, as a consumer, is more likely to trust it (Jahn, Gaus, & Kiessling, 2012). Zhang, Benyoucef, and Zhao (2015) found that consumers could develop a sense of SC by following a brand’s microblog. Furthermore, the importance of SC has been demonstrated in the adoption of mobile services (Hepola et al., 2016). However, SC’s effects have yet to be applied widely to explain consumer behavior in the mobile app context. 2.3.3. Perceived risk (PR) PR refers to a perceived negative consequence that arises from the purchase of a new product or service (Karjaluoto et al., 2014; Dholakia, 2001). In the technology acceptance context, risk affects consumers’ confidence in their intentions and behavior, and this uncertainty grows when the probabilities of outcomes are unknown (Im, Yongbeom, & Han, 2008). PR has been a major research topic in IS and marketing literature, and its effects on various aspects of consumer behavior, related to both technology adoption and usage, have been investigated in the mbanking (Glavee-Geo et al., 2017), m-wallet (Amoroso & Magnier-Watanabe, 2012), and electronic banking1 (Zhang, Weng, & Zhu, 2018) contexts. Thakur and Srivastava (2014) discussed the three dimensions of PR (security, privacy, and monetary risk) that affect m-payment adoption. Although research has shown that PR negatively affects attitude (Akturan & Tezcan, 2012) and intention toward technology adoption (Thakur & Srivastava, 2014), more information is needed on its effects on technology acceptance (see DelVecchio & Smith, 2005), especially in the MFSA context. 2.3.4. New product novelty (NPN) The novelty dimension of a new product refers to the degree to which a product is perceived differently from other products in terms of the product’s newness and uniqueness (Im et al., 2015). NPN and meaningfulness (or appropriateness) are conceptualized as two dimensions of creativity (Amabile, 1988) that should be studied separately (Im & Workman, 2004). Moreover, of these two, the novelty dimension provides easier and faster consumer assessment (Rubera, Ordanini, & Mazursky, 2010). Therefore, this study concentrates on this dimension of creativity. Im et al. (2015) stated that NPN effects have been studied thus far mostly from the perspective of managers. In addition, they noted that, although the effects from new product creativity remain rather unknown, the novelty might be related more to the evaluation of the hedonic value of the product, rather than the utilitarian value. 2.4. PV outcomes: Overall satisfaction and commitment Overall satisfaction aims to capture either cumulative or integrated satisfaction and, thus, refers to an overall assessment based on a consumer’s total experience with a product and/or service (Garbarino & Johnson, 1999). It not only addresses the functionalities of products and/or services, but also extends the perspective to all interactions between a customer and the company and its offerings over time. Like trust, commitment is another critical component of successful customer relationships (Shaikh, Karjaluoto, & Chinje, 2015; Dwyer, Schurr, & Oh, 1987; Morgan & Hunt, 1994), as it concerns the level of attachment between customers and the firm. Commitment can be defined as an “enduring desire to maintain a valued relationship” (Moorman, Zaltman, & Deshpande, 1992, p. 316). Based on 1 In Zhang, Weng, and Zhu’s (2018) study electronic banking referred to both online banking and mbanking. employee-commitment literature, Garbarino and Johnson (1999) suggested that personal identification, psychological attachment, concern for the future welfare of the organization, and loyalty are the key components of commitment. This idea aligns with affective commitment, which further emphasizes personal interaction, trust, and reciprocity (Gustafsson, Johnson, & Roos, 2005). 3. Research model and hypotheses development Building on the theories of PV, its antecedents and outcomes, and their application in the MFSA context (Baptista & Oliveira, 2016; Shaikh & Karjaluoto, 2016), the proposed conceptual model (Figure 1) suggests that four central antecedents to PV exist: PI, SC, NPN, and PR. Moreover, the research model suggests that PV is positively related to customers’ overall satisfaction with and commitment to their bank. We controlled the model for the effects of gender, age, and income, and the following subsections explain these linkages and propose hypotheses for testing these direct effects. [Insert Figure 1 about here] 3.1 Personal innovativeness on perceived value An understanding of the linkage between PI and PV is important because customers who are willing to explore the opportunities of a new IS also can perceive and expect more value from using innovative services, such as m-applications. As stated earlier, PI affects technology adoption via perceived ease of use and usefulness. Venkatesh, Morris, Davis, and Davis (2003) discussed how innovative users are more likely to form a favorable perception of the usability of a system, and Karjaluoto et al. (2014) proposed that PI might be more important in driving adoption of mobile CRM in its earlier stages. Although a direct relationship between PI and PV, to our knowledge, has not been addressed earlier, PV, as a construct, shares many similar aspects with perceived ease of use and perceived usefulness—two constructs affected by PI (Avlonitis & Panagopoulos 2005; Lu, Liu, Yu, & Wang, 2008). In line with this discussion, PI is likely to drive PV in the MFSA context. Thus, we propose the following hypothesis: H1: Personal innovativeness is related positively to the perceived value of MFSAs. 3.2 Self-congruence on perceived value To maintain the PV of the brand, as well as satisfy the customer, it is important to build a strong brand image and create both self- and brand-image congruity (Farhat & Khan, 2012) among present and potential customers. It is essential for service firms to compete through creativity, innovation, and assessment of consumers’ current and ever-changing values. When these values reflect consumers’ self-image congruently, firms are likely to create a sustainable market, as well as achieve sustainable growth and continued consumption of their products and services. Extant research (e.g., Shaikh & Karjaluoto, 2016) has found a direct and significant relationship between SC and PV in the MFSA context. Thus, we propose the following: H2: Self-congruence is related positively to the perceived value of MFSAs. 3.3 Perceived risk on perceived value The negative effect of PR on PV and purchase intention is well-established in literature (Chiu, Wang, Fang, & Huang, 2014). Snoj, Pisnik Korda, and Mumel (2004) argued that PR has a substantial, yet reverse, effect on PV in the mobilephone adoption context. In a survey of online store customers in Taiwan, Chiu et al. (2014) found that a higher level of risk weakens the effects of utilitarian value on repurchase intentions and strengthens the effects of hedonic value on repeat purchase intentions. Similar findings also were reported by Shaikh and Karjaluoto (2016), who found a significant negative relationship between PR and PV in the m-banking context. In addition, Karjaluoto et al. (2014) found that risk is an important driver of mobile CRM system adoption among sales managers. Therefore, we want to further test the relationship in the MFSA context and propose the following: H3: Perceived risk is related negatively to the perceived value of MFSAs. 3.4. New product novelty on perceived value The dimensions of creativity rarely have been studied and compared with other consumer evaluations such as PV (Im et al., 2015). Instead, utilitarian and hedonic value have been related to innovativeness. For example, in the IS field, Etemad- Sajadi and Ghachem (2015) found that, although innovativeness was influenced simultaneously by the hedonic and utilitarian value of webpage avatars, the effects from utilitarian value yielded greater importance. Im et al. (2015) said consumers’ creativity assessments are critical, particularly in how they relate to product or service evaluations. Thus, they tested the effects of NPN on PV in the context of retail, particularly on cell phone and athletic shoe purchases. Their results indicated that novelty does not affect hedonic value consistently. Furthermore, they said NPN affects hedonic value indirectly via coolness. Im et al. (2015) indicated a need for further research on the effects of novelty on PV. Accordingly, the present study examines these rather unknown effects from novelty on PV in MFSAs. Thus, we propose the following: H4: New product novelty is related positively to the perceived value of MFSAs. 3.5 Relational outcomes of perceived value: Overall satisfaction and commitment As stated previously, PV is a central predictor of customer loyalty (Sweeney & Soutar, 2001; Yeh et al., 2016). Oliveira, Faria, Thomas, and Popovič (2014) argued that m-information services foster customer relationships and provide holistic customer experiences. The positive relationships between PV and overall satisfaction (Chen & Chen, 2010) and commitment (Pura, 2005) also have been confirmed in literature. In the MFSA context, Amoroso and Magnier-Watanabe (2012) found that the PV offered by m-wallet apps in Japan contributed to positive attitudes toward using m-wallets, as well as reinforced behavioral intentions to use them. Pura (2005) analyzed the direct effects of PV on commitment regarding the use of location-based m-services. She found that both behavioral intentions and commitment are influenced significantly by the PV of m-services. In the broader context, marketing literature (e.g., Luarn & Lin, 2003; Parasuraman & Grewal, 2000) has discussed the positive effects from PV on various aspects of loyalty, such as commitment. Because research has not addressed adequately the link between the PV obtained from using MFSAs and bank-customer relationship development, this study aims to examine these rather unknown effects further. Therefore, we propose the following: H5: The perceived value of MFSAs is related positively to overall satisfaction toward the bank that employs them. H6: The perceived value of MFSAs is positively related to commitment to the bank that employs them. 4. Research methodology 4.1 Data collection We tested our hypotheses using two different samples that were drawn from mapplication users: One consisted of m-banking application users, and the other included users of a newly launched m-wallet application. The rationale for using the two samples is two-fold. First, these apps (m-banking and m-wallet) were chosen for this study because they are the apps that the banks offered. Second, two types of apps are expected to enhance our results’ validity. Data were collected using a survey instrument during a six-week period in the summer of 2015 via the participating financial organization’s website. The m-wallet application contained information related to personal banking accounts, payment cards, and a user’s favorite shops, based on the user’s location. A total of 1,516 valid responses were received, most of which were m-banking- application users (N=992), whereas the remainder were m-wallet application users (N=524). The sample (see Table 1) mirrored the Finnish population in terms of gender (the adult population in Finland is 51% female) and income (the average monthly income in Finland is 2,330 EUR), but was skewed toward younger consumers. Approximately 86% of our sample was between 18 and 49 years old, whereas that figure is approximately 50% of the entire population (Statistics Finland, 2018). The respondents were experienced users of MFSAs, with approximately 11% having less than three months of experience with the applications. [Insert Table 1 about here] In the m-banking application sample, approximately 65% had used the application for more than one year, whereas in the m-wallet-application sample, 75% had used the application for more than six months. To compare the results reliably between the two groups, we evaluated the measurement invariance (Rigdon, Ringle, & Sarstedt, 2010; Vandenberg & Lance, 2000), which considered that the measured constructs were comparable between the two groups (Steinmetz, Schmidt, Tina- Dwyer, F. R., Schurr, P. H., & Oh, S. (1987). Developing Buyer-seller Relationships. Journal of Marketing, 51, 11−27. Ericksen, M. K., & Sirgy, M. J. (1989). Achievement Motivation and Clothing Behavior of Working Women: A Self-Image Congruence Analysis. Journal of Social Behavior and Personality, 4(4), 307−326. Etemad-Sajadi, R., & Ghachem, L. (2015). The Impact of Hedonic and Utilitarian Value of Online Avatars on E-Service Quality. Computers in Human Behavior, 52, 81−86. Farhat, R., & Khan, B. M. (2012). Effect of Brand Image & Self Image Congruency on Brand Preference & Customer Satisfaction. International Journal of Marketing and Technology, 2, 92−102. Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18, 39−50. Garbarino, E,. & Johnson, M. S. (1999). The different Roles of Satisfaction, Trust, and Commitment in Customer Relationships. Journal of Marketing, 63, 70−87. Glavee-Geo, R., Shaikh, A. A., & Karjaluoto, H. (2017). Mobile Banking Services Adoption in Pakistan: Are There Gender Differences? International Journal of Bank Marketing, 35(7), 1090−1114. García-Fernández, J., Gálvez-Ruíz, P., Fernández-Gavira, J., Vélez-Colón, L., Pitts, B., & Bernal-García, A. (2018). The Effects of Service Convenience and Perceived Quality on Perceived Value, Satisfaction and Loyalty in Low-Cost Fitness Centers. Sport Management Review, 21(3), 250−262. Gustafsson, A., Johnson, M. D., & Roos, I. (2005). The Effects of Customer Satisfaction, Relationship Commitment Dimensions, and Triggers on Customer Retention. Journal of Marketing, 69, 210−218. Hair, J. F. Jr., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 2nd ed., Thousand Oaks, Sage. Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A New Criterion for Assessing Discriminant Validity in Variance-based Structural Equation Modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. Henseler, J., Ringle, C.M., & Sarstedt, M. (2016). Testing Measurement Invariance of Composites Using Partial Least Squares. International Marketing Review, 33, 405−431. Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The Use of Partial Least Squares Path Modeling in International Marketing, in Advances in International Marketing, R.R. Sinkovics & P.N. Ghauri (Eds.), Bingley, UK: Emerald Group, pp. 277-320. Hepola, J., Karjaluoto, H., & Shaikh, A. A. (2016). Consumer Engagement and Behavioral Intention towards Continuous Use of Innovative Mobile Banking Applications - Case Study of Finland. Proceedings of International Conference on Information Systems (ICIS-2016), Dublin, Ireland, December 11-14, 2016. Hong, J.W., &, Zinkhan, G. M. (1995). Self Concept and Advertising Effectiveness: The Influences of Congruency, Conspicuousness and Response Modes. Psychology & Marketing, 12(1), 53−77. Hosany, S., & Martin, D. (2012). Self-Image Congruence in Consumer Behavior. Journal of Business Research, 65(5), 685−691. Im, S., Bhat, S., & Lee, Y. (2015). Consumer Perceptions of Product Creativity, Coolness, Value and Attitude. Journal of Business Research, 68, 166−172. Im, S., & Workman, J.P., Jr. (2004). Market Orientation, Creativity, and New Product Performance in High-Technology Firms. Journal of Marketing, 68(2), 114−132. Im, I., Yongbeom, K., & Han, H-J. (2008). The Effects of Perceived Risk and Technology Type on Users’ Acceptance of Technologies. Information & Management, 45, 1−9. Jahn, S., Gaus, H., & Kiessling, T. (2012). Trust, Commitment, and Older Women: Exploring Brand Attachment Differences in The Elderly Segment. Psychology and Marketing, 29(6), 445−457. Japutra, A., Ekinci, Y., & Simkin, L. (2017). Self-Congruence, Brand Attachment and Compulsive Buying. Journal of Business Research (In press). DOI https://doi.org/10.1016/j.jbusres.2017.08.024 Karjaluoto, H., Töllinen, A., Pirttiniemi, J., & Jayawardhena, C. (2014). Intention to Use Mobile Customer Relationship Management Systems. Industrial Management & Data Systems, 114, 966−978. Kim, B., & Han, I. (2011). The Role of Utilitarian and Hedonic Values and Their Antecedents in a Mobile Data Service Environment. Expert Systems with Applications, 38(3), 2311−2318. Kressmann, F., Sirgy, M.J., Hermann, A., Huber, F., Huber, S., & Lee, D-J. (2006). Direct and Indirect Effects of Self-Image Congruence on Brand Loyalty. Journal of Business Research, 59(9), 955−964. Kumar, V., & Reinartz, W. (2016). Creating Enduring Customer Value. Journal of Marketing, 80(6), 36−68. Laukkanen, T., & Lauronen, J. (2005). Consumer Value Creation in Mobile Banking Services. International journal of mobile Communications, 3(4), 325−338. Laukkanen, T., & Kiviniemi, V. (2010). The Role of Information in Mobile Banking Resistance. International Journal of Bank Marketing, 28(5), 372−388. Li, M., & Mao, J. (2015), Hedonic or Utilitarian? Exploring the Impact of Communication Style Alignment on User’s Perception of Virtual Health Advisory Services. International Journal of Information Management, 35(2), 229−243. Liang, H., Saraf, N., Hu, Q., & Xue, Y. (2007). Assimilation of Enterprise Systems: The Effect of Institutional Pressures and the Mediating Role of Top Management. MIS Quarterly, 31, 59−87. Lee, Y. K., Park, J. H., Chung, N., & Blakeney, A. (2012). A Unified Perspective on the Factors Influencing Usage Intention toward Mobile Financial Services. Journal of Business Research, 65(11), 1590−1599. Leicht, T., Chtourou, A., & Youssef, K. B. (2018). Consumer Innovativeness and Intentioned Autonomous Car Adoption. The Journal of High Technology Management Research, 29 (1), 1−11. Loh, M., Ahmad, M., Kadir, S. A., & Alam, S. S. (2015). Influence of Customer Values And Self-Image Congruity On Customer Behavior-Based CRM Performance. Management and Marketing Journal, 13, 23−44. Luarn, P. & Lin, H. H. (2003). A Customer Loyalty Model for E-Service Context. Journal of Electronic Commerce Research, 4, 156−167. Lu, J., Yao, J.E., & Yu, C.S. (2005). Personal Innovativeness, Social Influences and Adoption of Wireless Internet Services via Mobile Technology. Journal of Strategic Information Systems, 14, 245−268. Lu, J., Liu, C., Yu, C.-S., & Wang, K. (2008). Determinants of Accepting Wireless Mobile Data Services in China. Information & Management, 45(1), 52−64. Malhotra, N. K. (1988). Self-Concept and Product Choice: An Integrated Perspective. Journal of Economic Psychology, 9(1), 1−28. Malär, L., Krohmer, H., Hoyer, W. D., & Nyffenegger, B. (2011). Emotional Brand Attachment and Brand Personality: The Relative Importance of the Actual and The Ideal Self. Journal of Marketing, 75(4), 35−52. Moorman, C., Zaltman, G., & Deshpande, R. (1992). Relationships Between Providers and Users of Market Research: The Dynamics of Trust Within and Between Organizations. Journal of Marketing Research, 29, 314−328. Morgan, R. M., & Hunt, S. D. (1994). The Commitment-Trust Theory of Relationship Marketing. Journal of Marketing, 58, 20−38. Oliveira, T., Faria, M., Thomas, M. A., & Popovič, A. (2014). Extending the Understanding of Mobile Banking Adoption: When UTAUT Meets TTF and ITM. International Journal of Information Management, 34, 689−703. OP (2017). OP Ryhma n toimintakertomus ja tilinpa a to s 2017, (OP Group’s Annual Report and Financial Statement 2017), https://uusi.op.fi/documents/209474/28185340/OP+Ryhmän+toimintakertomus+j a+tilinpäätös+2017/b559dcb9-86bc-425b-acc8-0396b01c2f22. Accessed 28.03.18. Parasuraman, A., & Grewal, D. (2000). The Impact of Technology on the Quality- Value-Loyalty Chain: A Research Agenda. Journal of the Academy of Marketing Science, 28, 168−174. Pihlström, M., & Brush, G.J. (2008). Comparing the Perceived Value of Information and Entertainment Mobile Services. Psychology & Marketing, 25(8), 732−755. Peffers, K., & Tuunanen, T. (2005). Planning for IS Applications: A Practical, Information Theoretical Method and Case Study in Mobile Financial Services. Information & Management, 42(3), 483−501. Podsakoff, P.M., MacKenzie, S.B., Lee, J.Y., & Podsakoff, N.P. (2003). Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies. Journal of Applied Psychology, 88, 879−903. Pura, M. (2005). Linking Perceived Value and Loyalty in Location-based Mobile Services. Managing Service Quality, 15, 509−538. Rigdon, E.E., Ringle, C.M., & Sarstedt, M. (2010). Structural Modeling of Heterogeneous Data with Partial Least Squares, in Review of Marketing Research, N.K. Malthora (ed.), Bingley, UK: Emerald Group, 255−296. Ringle, C.M., Wende, S., & Becker, J.-M. (2015). SmartPLS 3. Boenningstedt: SmartPLS GmbH, http://www.smartpls.com. Accessed 18.4.2018. Rogers, E. M. (1962). Diffusion of innovation. New York: Free Press. Rubera, G., Ordanini, A., & Mazursky, D. (2010). Toward a Contingency View of New Product Creativity: Assessing the Interactive Effects of Consumers. Marketing Letters, 21(2), 191–206. Shaikh, A.A., & Karjaluoto, H. (2015). Making the Most of Information Technology & Systems Usage: A Literature Review, Framework and Future Research Agenda. Computers in Human Behavior, 49, 541–566. Shaikh, A. A., & Karjaluoto, H. (2016). Mobile Banking Services Continuous Usage--Case Study of Finland. Proceedings of the 49th Hawaii International Conference on System Sciences (HICSS 2016), Tung X. Bui ja Ralph H. Sprague Jr. (eds.), IEEE Computer Society, (pp. 1497−1506). Shaikh, A. A., Karjaluoto, H., & Chinje, N. B. (2015). Continuous Mobile Banking Usage and Relationship Commitment–A Multi-Country Assessment. Journal of Financial Services Marketing, 20(3), 208−219. Shareef, M. A., Baabdullah, A., Dutta, S., Kumar, V., & Dwivedi, Y. K. (2018). Consumer Adoption of Mobile Banking Services: An Empirical Examination of Factors According to Adoption Stages. Journal of Retailing and Consumer Services, 43, 54−67. Singh, S., & Srivastava, R. K. (2018). Predicting the Intention to Use Mobile Banking in India. International Journal of Bank Marketing, 36(2), 357−378. Sirgy, M. J., Grewal, D., Mangleburg, T. F., Park, J. O., Chon, K. S., Claiborne, C. B., Johar, J. S., & Berkman, H. (1997). Assessing the Predictive Validity of Two Methods of Measuring Self-image Congruence. Journal of the Academy of Marketing Science, 25, 229−241. Sirgy, M. J. (1985). Using Self-congruity and Ideal Congruity to Predict Purchase Motivation. Journal of Business Research, 13, 195−206. Sirgy, M. J. (1982). Self-Concept in Consumer Behavior: A Critical Review. Journal of Consumer Research, 9(3), 287−300. Snoj, B., Pisnik Korda, A., & Mumel, D. (2004). The Relationships among Perceived Quality, Perceived Risk and Perceived Product Value. Journal of Product & Brand Management, 13, 156−167. Spiteri, J. M., & Dion, P. A. (2004). Customer Value, Overall Satisfaction, End-User Loyalty, and Market Performance in Detail Intensive Industries. Industrial Marketing Management, 33(8), 675−687. Statistics Finland. (2018). Official Statistics Finland (SVT): Väestön tieto- ja viestintätekniikan käyttö [online publication]. Helsinki: Statistics Finland. Accessed 20.4.2018. Steinmetz, H., Schmidt, P., Tina-Booh, A., Wieczorek, S., & Schwartz, S.H. (2009). Testing Measurement Invariance Using Multigroup CFA: Differences Between Educational Groups in Human Values Measurement. Quality & Quantity, 43, 599−616. Sweeney, J.G., & Soutar, G.N. (2001). Consumer Perceived Value: The Development of a Multiple Item Scale. Journal of Retailing, 77(2), 203−220. Thakur, R., & Srivastava, M.. (2014). Adoption Readiness, Personal Innovativeness, Perceived Risk and Usage Intention across Customer Groups for Mobile Payment Services in India. Internet Research, 24(3), 369−392. Thakur, R., Angriawan, A., & Summey, J. H. (2016). Technological Opinion Leadership: The Role of Personal Innovativeness, Gadget Love, and Technological Innovativeness. Journal of Business Research, 69(8), 2764−2773. Van der Heijden, H. (2004). User Acceptance of Hedonic Information Systems. MIS Quarterly, 28, 695−704. Vandenberg, R. J., & Lance, C. E. (2000). A Review and Synthesis of the Measurement Invariance Literature: Suggestions, Practices, and Recommendations for Organizational Research. Organizational Research Methods, 3, 4−70. Venkatesh, V., Morris, M.G., Davis, G.B., & Davis, F.D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425−478. Wallace, E., Buil, I., & de Chernatony, L. (2017). Consumers’ Self-Congruence with a “liked” Brand: Cognitive Network Influence and Brand Outcomes. European Journal of Marketing, 51(2), 367−390. Wu, J., & Lu, X. (2013). Effects of Extrinsic and Intrinsic Motivators on Using Utilitarian, Hedonic, and Dual-purposed Information Systems: A Meta-analysis. Journal of the Association for Information Systems, 14, 153−191. Yeh, C. H., Wang, Y. S., & Yieh, K. (2016). Predicting Smartphone Brand Loyalty: Consumer Value and Consumer-Brand Identification Perspectives. International Journal of Information Management, 36(3), 245−257. Yen, Y. S., & Wu, F. S. (2016). Predicting the Adoption of Mobile Financial Services: The Impacts of Perceived Mobility and Personal Habit. Computers in Human Behavior, 65, 31−42. Zhang, Y., Weng, Q., & Zhu, N. (2018). The Relationships Between Electronic Banking Adoption and Its Antecedents: a Meta-Analytic Study of the Role of National Culture. International Journal of Information Management, 40, 76−87. Zhang, K. Z. K., Benyoucef, M., & Zhao, S. J. (2015). Consumer Participation and Gender Differences on Companies’ Microblogs: A Brand Attachment Process Perspective. Computers in Human Behavior, 44, 357−368. Zeithaml, V. A. (1988). Consumer Perceptions of Price, Quality and Value: A Means-End Model and Synthesis of Evidence. Journal of Marketing, 52, 2–22.