The Effect of Reciprocity on Mobile Wallet Intention

The authors build on the literature on reciprocity by exploring a prevalent social and economic phenomenon in the Philippines where individuals with positive mobile phone balances can SMS loads to acquaintances. This practice is known as “pasaload”—an abbreviation of Pass-A-Load. The research was designed based on the literature review that in turn resulted in a research model that focused on six constructs: reciprocity, loyalty, habit, switching costs, trust, and future repurchase. Hypotheses were developed as the basis for a scaled survey of 1050 Philippine smartphone users, with the questions adapted from but adhering closely to the original questions from appropriate articles in the literature review. Overall the mediating effects from the two models are consistent with the expectations from the literature and analysis. In the Philippine context, habit might be a strong mediator even if the true financial and convenience costs to switch is low.


INTRodUCTIoN
This paper focuses on three questions. First, to what extent do the social constructs of reciprocity and trust affect Philippine telecommunication product continuance? While reciprocity has been studied extensively in the context of electronic communities and social media, it has not figured in technology use or acceptance, or in purchase intention. If the TAM (Davis et al. 1989) and UTAUT (Venkatesh et al. 2003) models explain intention from a usefulness perspective, we attempt to build on earlier literature on habit and product loyalty. Second, how do Philippine cultural values of bayanihan, or kinship, and utang na loob, or "debt of gratitude" reinforce the use of a popular Telecommunication mobile wallet application called "pasaload?" Third, can reciprocity and trust enhance the effects of customer switching costs, loyalty, and habit on their intent to repurchase?

Background
In 2014 the Philippines' population of 100 Million people had 1.16 SIM cards per capita: many Filipinos used multiple SIM cards or had more than one mobile phone. Moreover, 96% of the country's SIM cards were prepaid (Waring 2014). The Philippine telecommunications industry is effectively a duopoly, comprising two main players: SMART and Globe, and a few minor other telecommunications trust, behavioral trust, propensity to trust, and trustworthiness. Trust is difficult to define and is multidimensional (Rousseau et al. 1998). In the IT literature trust is present in IT and individual, groups, markets, and virtual collaboration (Chiu et al. 2006;Sidorova et al. 2008). In the e-commerce market literature in particular, trust is a belief in an attribute of a trustee, in most cases, web or e-commerce commercial site (McKnight et al. 2002).
Trust exists between buyer (truster) and seller (trustee) e.g. McKnight et al. (2002) research on initial trust for web vendors. Trust can be measured by the trustee's levels of ability, benevolence, and integrity. Ability can mean the trustee's reputation (Josang et al. 2007) Integrity itself is the trustee's ability to meet obligations, fulfill agreements, and maintain reliability (Bhattacherjee, 2002). Beyond initial trust, subsequent interactions may reinforce or diminish the strength of trust. Continued social interaction leads to enhanced ties, or trust (Granovetter 1973). Eventually after such repetition and social capital build up, trust for each other remains (Bigley & Pierce 1998). It is defined as the expectation or belief that persons will keep their promises and fulfill obligations with honesty, goodwill, and non-opportunistic motives (Tian et al. 2011).

Switching Costs
Consumers incur switching costs when they transition between products. To own a smartphone includes not only new product and breaking contract fees, time, and effort, but also psychological costs such as learning curve and uncertainty when switching to a new provider. Switching may occur when consumers are dissatisfied with their current choice and are aware of potential replacements (Battacherjee et al. 2001). Maintaining high switching costs has thus been a critical management strategy to keep consumers loyal. In the technology context the more effective information systems can increase switching costs of users, thus deterring churn and defection (Shapiro & Varian 1998). This is reflected in the lock-in contracts companies give in exchange of free handsets in most countries. To increase consumer loyalty, telecommunication firms might also push consumer loyalty programs. If a consumer switches, losing those loyalty benefits adds extra switching costs. Lam et al. (2004) argued part of switching cost may involve loyalty benefits consumers give up when their relationship with the service provider ends (Lam et al. 2004). Past research found a strong relationship between switching costs and loyalty (Amoroso & Chen 2017). For instance, given the fierce competition among mobile financial apps in China, financial mobile apps, especially leading ones, commonly use the same strategy of giving coupons, discounts, points to their loyal consumers. Such programs increase consumers' switching costs.

Loyalty
Loyalty is defined by Lin et al. (2015) as consumer dependence and goodwill toward a product or service, as a result of culminating in consumer satisfaction. Loyalty is a strong commitment behavior toward a vendor or brand; and a loyal consumer not only continuously comes back to the same vendor or brand but also helps the vendor/brand sustain long-term growth through advocacy. Furthermore, a vendor/brand can also gain from cross-/up-selling opportunities, forecast accuracy, receive constructive feedback, leading to marketing and service costs reduction and brand image improvement. Hence, establishing consumer loyalty and retention is an important business activity, as it often leads to more consumer purchases, increasing in both sales and profits (Chi 2005).
Loyalty is a commitment behavior and develops as the vendor earns the trust of the consumer. Prior research found that consumers trusting an online vendor are more likely to have the intention to share personal information with the vendor and to allow the vendor to personalize products and services for them. A loyal consumer not only continuously comes back to the vendor but helps the vendor win fierce competition and sustains long-term growth through word-of-mouth (Reichheld & Schefter 2000). Lin, et al. (2015) defined loyalty as the consumer generating dependence and goodwill to a product or service, culminating in repurchase intention behavior.

Habit
Habit is the extent to which people automatically perform specific behaviors because of prior learning. The use of a mobile phone, an everyday common appliance, is susceptible to automatic behavior (Oulette & Wood 1998;Aarts et al. 1998). De Guinea & Markus's meta-study (2009 defines habit as learned behaviors that evolve into repeated behavior without conscious intention. An analog to habit is inertia, a construct of Status Quo Bias (SQB). SQB posits that people will maintain an existing action in the face of a superior action (Samuelson & Zeckhauser 1988). In the IS field Kim & Kankanhalli (2009) use SQB to describe user resistance to a new system. On the one hand, habit and inertia are simultaneously cognitive and affective (Polites & Karahanna 2012). Habit is a learned response automatically triggered by stimulus cues; inertia is a conscious choice to stay with the status quo (De Guinea & Markus 2009). The choice of status quo may also be driven by other constructs such as cognitive misperceptions, loss aversion, uncertainty, and psychological commitment (Lee & Joshi 2016). On the other hand, habit may be unconscious. De Guinea & Markus (2009) state, "behavioral inertia implies that use of a system continues simply because it is what the individual users have always done, and therefore without giving it much, if any, thought." Habit therefore seems frequently interchanged with Inertia. Cognitive inertia implies that an individual consciously continues to use the (incumbent) system even if he or she is aware that it might not be the best system. Affective inertia reflects how users continue to use a system because it is stressful to change.

Future Repurchase Intention
Future repurchase intention is the strength of consumers' intention to perform a specified behavior. In the IT context intention predicts actual usage of a technology (Bhattacherjee 2001). It was proposed that continuance intention is a post-initial adoption behavior (Limayem et al. 2007). Continuance intention does well in predicting actual usage of a technology or application. Any factors that influence behavior act as indirect influences through continuance intention. Previous literature has established that continuing IT use, like continuance intention, is fundamentally intentional and rational; users make rational decisions based on perceptions such as ease of use and usefulness, expectations from experience, beliefs. But users also use affective, emotional responses, including satisfaction and cognitive absorption; for example, emotion, not just cognition, may be an input to the continuing use decision or intention formation (De Guinea & Markus (2009). The IS literature has proposed various general models of IT usage intention: Bhattacherjee (2001) and Limayem et al. (2007) complement the theories of TAM (Davis et al. 1989) and UTAUT (Venkatesh et al. 2003). However, this paper tests the relationships of three extant drivers of continuance intention-loyalty, switching costs, and habit.

Reciprocity and Trust
In the field of entrepreneurship, where networking and partnering appear critical to success, reciprocal behavior creates a willingness to trust others when starting a business, but the added component of negative reciprocity may influence exit decisions. (Caliendo et al. 2006). Wu et al. (2008) directly examine consumer reciprocity as a mediator in the relationship between brand trust and loyalty, product familiarity and future purchase intentions both theoretically and through an empirical study of printer users. Reciprocity is present in the Perceived Organizational Support, (POS) literature. If employees perceive that they receive support from their organization so-called POS -that supports employees, the employees will in turn respond in a trusting way with care, affective commitment, and reciprocity. (Eisenberger et al. 2001;Aselage & Eisenberger 2003). Several studies (Berg et al. 1995;Wu et al. 2008;Caliendo et al. 2010;Sanchez-Franco & Roldan 2015) have established the correlation between trust and reciprocity. Trust increases the ability of people to work together and promotes reciprocity (Villares et al. 2011). Reciprocity as a form of social interaction may be the antecedent, and continuing mutual byproduct with trust (Schoorman et al. 2007). In game theory trust and reciprocity may even be simultaneous (Villares et al. 2011). A variation of trust is trustworthiness, the qualitative level of trust perceived by others in a person. (Wilson & Eckel 2010;Amoroso & Mukahi 2013;Fleming et al. 2014). In the IS literature, reciprocity and trust are forms of relational social capital; trust covaries with reciprocity to lead to higher volume and quality of knowledge sharing in virtual communities (Chiu et al. 2006). We therefore hypothesize: H1a: Reciprocity is positively correlated with Trust.

Reciprocity and Habit
Reciprocity is a key driver of user motivation to contribute habitually to knowledge communities (Wasko & Faraj 2005;Kankanhalli & Tan 2005;Chen et al. 2017). In the social media context, Social Q & A Communities become communities of practice and that may generate habitual exchanges and the expectation of reciprocal information exchange (Wu & Korfiatis 2013). In game theory, reciprocity acts as an input variable in understanding repeated, cooperative behaviors (Goldstein et al. 2011). The feeling of obligation, or indebtedness, occurs commonly in social, family, and organizational situations. Among peers in a formed social network there was a tendency for members to share knowledge and contribute. There was also a perceived social pressure to continue this contribution (Chow & Chan 2008). When the member is structurally embedded, he or she contributes even more (Wasko & Faraj 2005). Families are another type of social group. There are moral obligations and indebtedness between young adults and their parents. (Freeberg & Stein 1996) This is particularly felt for collective societies such as in Asian cultures, where youths retain strong traditions of duty, respect, and support to and for family members (Fulgini et al. 1999). Such a tradition may extend to Asian peer groups such as those in the Philippines. We therefore posit: H1b: Reciprocity is positively correlated with Habit.

Trust and Loyalty
In marketing, multi-dimensional trust drives perceptions of value and ultimately loyalty (Sirdeshmukh et al. 2002). Trust also builds commitment and then positive behaviors such as lower propensity to leave, aka loyalty (Morgan & Hunt 1994). As mentioned earlier Wu et al. (2008) examine how trust affects loyalty with printer consumers. One possible context for trust and loyalty may be in the pasaload process; it is not just a financial mechanism but is also an interaction of social and economic exchanges. In the pasaload context trust is an important antecedent of reciprocity: before exchanges can occur, there must be a modicum of trust between senders and receivers of prepaid loads. Amoroso & Mukahi (2013) found that a consumer's propensity to trust leads to increased loyalty among persons trusting and being trusted. Therefore, we hypothesize that: H2a: Trust is positively correlated with Loyalty.

Trust and Future Purchase Intention
Trust can be "a social lubricant that reduces the cost exchange…in daily market exchange." In the IT and marketing literature, the construct of trust is normally used to describe a consumer's trust for a product, a website, or a company reputation (Chen et al. 2002;Bauer et al. 2002;Pornpratang et al. 2013) in our study we use trust in the social context, i.e. trust in a community (Gilbert & Karahalios 2009). We propose that trust leads to a greater degree of repurchase intention: trust, trustworthiness and loyalty positively simultaneously interact. Trust reinforces repurchase intention (and vice versa). The process starts when someone asks another for his or her surplus cash from the mobile phone's prepaid card primarily via the much cheaper SMS or text messaging. It does not involve a transaction among strangers, since a probable relationship already exists via mobile phone communications-among classmates, fellow employees, relatives and friends, and so on. Trust is therefore the precondition for pasaload repurchase, especially since the process involves multiple two-party relationships. Therefore, we posit: H2b: Trust is positively correlated with Future Repurchase Intention.

Switching Costs, Future Repurchase Intention, and Habit
Switching costs were found to have a positive impact on continuance intention because switching costs make switching to alternatives difficult for consumers (Kim, et al. 2014;Zhou & Lu 2011). Switching costs also were found to increase consumers' propensity to continue use a service (Liaw and Liang 2013). Switching costs rise when consumers are satisfied with their current choices, despite potential replacements (Battacherjee et al. 2001). Status Quo Bias (SQB) describes how people, given satisfaction with the status quo, maintain an existing action, i.e. develop a habit, even in the face of a superior action or products (Samuelson & Zeckhauser 1988). We therefore hypothesize: H3a: Switching Costs are positively correlated with Future Repurchase Intention. H3b: Switching Costs are positively correlated with Habit. Cyr et al. (2006) found that loyalty is an indicator of continuance intention and an important construct in the context of online financial transactions. Holland & Baker (2001) developed an e-business marketing model and found that creating brand site loyalty leads to both behavioral and attitudinal outcomes from consumers, such as repeat visits of, strong support of, and favorable attitude toward the website. Shih (2011) and Amoroso & Ogawa (2013) found relationships between attitude and loyalty and between repurchase intention and loyalty and concluded that the both the behavioral loyalty model and the attitudinal loyalty model were predictors of repurchase intention. Loyalty was also found to be a key to online retailers to enhance satisfaction and increase repeated use intention for online consumers (Amoroso & Ogawa 2013), and for mobile app repurchase (Amoroso & Lim 2015). Therefore, we hypothesize that: H4: Loyalty is positively correlated with Future Repurchase Intention.

Habit and Future Purchase Intention
The habit construct, in the IS field, is a learned, and then an automatic-unconscious behavior, that impacts intention and usage. Information systems studies link habit to continuance intention (Kim & Malhotra 2005;Cheung & Limayem 2005;Liao et al. 2006;Lankton, et al. 2010;Venkatesh, et al. 2012). Habit limits the predictive power of intention on usage behavior; past online behaviors have a significant effect on continued usage, and initial use can significantly impact future repeated use (Cheung & Limayem 2005). Liao et al. (2006) tested habit, perceived usefulness, and trust to strongly determine online purchase behavior. Kim et al. (2012) found strong relationships between habit, perceived switching costs, and continuance intention. Hsu et al. (2015) found that habit moderated the relationships between purchase intention and perceived value, trust, and satisfaction.
In the marketing literature the constructs of habit and inertia are used to predict a consumers' continuance intention, and brand loyalty (Polites & Karahanna 2012;Bawa 1990;Greenfield 2005;McMullan 2005). There might be a "tug-of-war" between conscious (self-regulating) and unconscious (habitual) behavior in mobile phone use (Soror et al. 2015). Habit appears to be a "push" variable for loyalty and repeat consumer purchases and, by association, higher levels of satisfaction (Amoroso & Ogawa 2013). Consumers may be creatures of habit and prefer repetition as the path of least effort. Once consumers consciously attach themselves to a brand that meets rational or emotional needs, habit may trump satisfaction and loyalty in predicting continuance intention (Lafley & Martin 2017). Habit might also make users blind to novelty (Berinato 2017). Habit can therefore represent a kind of switching cost. Therefore, we propose: H5: Habit is positively correlated with Future Repurchase Intention.

Research Model
Our research model comprises six constructs: loyalty (Bajaj & Nidomulu 1998;Karahanna et al. 1999); habit (Polites & Karahanna 2012); switching costs (Bhattacherjee et al. 2001); reciprocity (Belk 2009); trust (Gilbert & Karahalios 2009.); and future repurchase intention (Bhattacherjee 2001;Limayem et al. 2007). The framework in Figure 1 shows how we address these research gaps. Appendices A and B summarize the literature used to support the theory for the reciprocity and trust constructs in the model.

Measures
We operationalized constructs for mobile technologies by using validated items from prior research (see Table 1). From  and , we used scales for loyalty, and habit from that research. For reciprocity and switching costs, we examined the future repurchase intention to use mobile technologies as a combination of actual and planned reciprocity ). All items identified in existing instruments were categorized according to literature. To limit survey length, we selected two to five scales for the measurement of each of the constructs, wording them similarly to the original studies (See Table 1). We eliminated redundant or ambiguous items, which might load on more than one factor in subsequent analysis.

data Collection
We used the snowball sampling approach per Kosinski et al. (2015) to achieve a rapid increase sample size. Social media samples provide an inexpensive and relatively high-quality alternative for collecting data (Balter & Brunet 2012). Given enough participants, the representativeness of the population can be improved, coming close to true randomization (Kosinski et al. 2015). Benefits from snowball sampling include increasing the sample size and determining respondents yet unknown. Atkinson & Flint (2001) found that snowball sampling may be applied as a more formal methodology for making inferences about a population which might be difficult to locate. The initial sample for the survey was 1,113 Filipino consumer respondents. After scrubbing the data and deleting incomplete answers we generated a final sample of 1,050 respondents, for a response rate of 94.3%.
The gender breakdown was very close to half with 48% male and 52% female. Although most of the sample covers persons in the 18-20 age group (46.4%), there was strong participation of 26-30-year-olds (20.2%). Because we used the snowball approach to collecting data, we got respondents through age 50 (9.2%) and even at the younger age, less than 18 (5.8%). We feel that the sample shows diversity in the population. Most of the living budget for the Filipino respondents was between 250-500 pesos per week (29.8%) with a larger group having a budget over 500 pesos (37.7%). (USD 1 = 50 pesos) Respondents with less than 50 pesos allocated for load per week were predominantly post-paid consumers (21.9%) or both pre-paid and post-paid. The majority of respondents claimed having a load budget of between 50-100 pesos per week (32.6%), followed by 100-250 pesos (16.6%).
The majority of respondents passed or received load only one time per week (50.5%). Very few respondents passed or received load every day (3.5%) or even as much as 4-5 days per week (16.2%). We asked respondents: if they ran out of load, did they borrow load (55.7%), get a loan for load (27.0%), or get a gift for the load (21.9%)? We defined loans as giving back the load plus additional interest agreed upon in the future; whereas borrowing load is an agreement to pay back the exact amount in the future; and receiving a gift of load that does not require any pay back in the future. We also asked respondents if they purchased load, did they do so at a retail outlet (66.9%) or from another source (33.1%). The consumer purchase behavior for the mobile phone plan was predominantly prepaid (78.1%), followed by postpaid (15.1%). Respondents were also asked if they took advantage of promo plans by the carriers, such as 50 pesos for unlimited texts for a week. We found that the majority of respondents (70.9%) did take advantage of promos while 29.1% did not purchase promos from the carriers.

Measurement Model Assessment
The research constructs are based on prior research where scales fit the construct's conceptual meaning, to ensure reliability and construct validity. Construct validity and reliability was established by Cronbach alpha, AVE, and factor analysis. All measurement scales showed high Cronbach alphas (see Table 1) at α 3 0.70 for most of the measures (Moore & Benbasat, 1991). Although continuance intention (α=.683) and loyalty (α=.692) are slightly under 0.70 we observe reasonable scale reliability, consistent with prior research dealing with similar constructs.
Discriminant validity analysis refers to testing statistically whether two constructs differ; convergent validity tests through measuring the internal consistency within one construct. Indicators for different constructs should not be so highly correlated as to lead one to conclude that they measure the same thing. This would happen if there were definitional overlaps between constructs. The average variance extracted (AVE) estimate, which measures the amount of variance captured by a construct in relation to the variance due to random measurement error, ranged from 0.688 to 0.812. Discriminant validity requires that the square roots of the AVE should be greater than correlation between two constructs. We calculated the square roots of the AVE and compared with each correlation scores and we found that with all constructs the AVE was greater than the correlations between the constructs, indicating that all the constructs share more variances with their indicators than with other constructs. Thus, our measures exhibited sufficient discriminant validity.
We conducted exploratory factor analyses (EFA) and confirmatory factor analysis (CFA) using Amos 25. EFAs were used to examine the basic structure of the measurement items. Using a principle components extraction method, all of the measures were analyzed through the Varimax rotation. The EFA factors loadings are reported on Table 1 where each of the measurement items loaded cleanly on one and only one factor, without any cross-loadings. Next, a CFA with maximum likelihood was conducted on the 12 indicators of the 4 latent variables to further ensure the reliability and validity of the measurement items. The structural model fit was estimated to test the proposed research model and hypotheses. The final factor analysis accounted for 72.4% of the total variance. While all EFA loadings ranged from 0.522 to 0.751, the CFA loadings ranged from 0.571 to 0.814. The excellent fit indices and lack of cross-loadings lend support to the construct validity of each measurement in the model as indicated by the earlier EFA and CFA results. These coefficients also provided evidence for the convergent validity, suggesting that each construct is well represented by its own indicators.

Assessing the Predictive Model
Figures 2 and 3 present the final SEM models for the impact of consumer trust and habit as intermediary constructs on repurchase intention in the Philippines without the reciprocity and trust constructs, and with reciprocity and trust. The path diagrams were produced with AMOS 25. The first model shows the effects using trust and habit as independent variables mediated through loyalty and switching costs, respectively, and without reciprocity and trust variables. on future repurchase intention (see Figure   Table 1

. Construct Reliability and Validity
2). To determine whether the sample data are consistent with this studied hypothesized distribution, we developed a structural equation model (SEM) and conducted a chi-square goodness of fit test. From the goodness of fit tests, we found that the χ 2 is at 638.2 with 127 degrees of freedom; where NFI (.967), RFI (.951), IFI (.977), TLI (.965), and CFI (.977) are reasonable with most indicators greater than 0.90, with the accepted value of RMSEA at 0.048. These imply a good fit of the model, which the proposed three constructs could generally well explain trust and of consumers toward future repurchase decisions in the Philippines.
The constructs in Model #1 showed strong R 2 values for future repurchase intention (67%). Loyalty showed a highly statistically significant path coefficient with future repurchase intention (b=.97), while switching costs showed a significant path with habit (b=.95) and with future repurchase intention (b=.88). Habit was a strong predictor of future repurchase intention (b=.81), and had a strong relationship to loyalty (b=.81), similar to the findings of Amoroso & Chen (2017) where switching costs showed a weak relationship with continuous intention, but habit showed a stronger path coefficient with continuous intention. This model shows the strong impact of switching costs on trust, habit, and future purchase intention behavior.
Model #2 shows the effects of reciprocity and trust, and reciprocity as an antecedent of trust and habit (see Figure 3). With the SEM goodness of fit tests (see Table 6), Χ 2 is at 676.7 with 127 degrees of freedom; where NFI (.885), RFI (.910), IFI (.905), TLI (.885), and CFI (.905) are reasonable greater than 0.90, with the accepted value of RMSEA at 0.054, implying a good fit of the model. The constructs in Model #2 showed strong R 2 , strong explanation of variance with future repurchase intention (83%). Adding reciprocity as an antecedent variable shows a 16% increase in variance explained from Model #1 to Model #2. Again, loyalty shows a strong path coefficient with future repurchase intention (b=.96) like Model #1 (b=.97). Trust shows a strong path coefficient with loyalty (b=.84). Switching costs showed a markedly weaker path coefficient with future repurchase intention (b=.26) in this model with the addition of reciprocity than in Model #1 (b=.88). Switching

Figure 2. Structural Equation Model #1 without Reciprocity and Trust
costs has a strong relationship with habit (b=.92) like Model #1 (b=.96), however the path between habit and future repurchase intention was slightly weaker (b=.65) than Model #1 at b=.81) showing the relative impact of reciprocity. Reciprocity, being added as an antecedent construct, shows strong relationships with both trust (b=.66) and habit (b=.60) -showing its importance in boosting the levels of the mediator variables on future repurchase intention.

Mediation Analysis
We tested mediation, using bootstrapping in Amos 25, as recommended by MacKinnon (2008). Bootstrapping is a resampling method to estimate standard errors and create confidence intervals. Mediation analysis confirms the mediation effects of satisfaction and habit on continuous intention and consumer satisfaction in our research model. Bootstrapping is also useful in assuming a more normal distribution, required as an assumption of SEM, reducing type 1 errors (Changya & Wang 2010). Bootstrapping can be used if the variables have measurement errors that then cause the mediation effect to be potentially underestimated. We ran the predictive SEM model to get indirect, direct and total effects. Cheung & Lau (2008) recommended the generation of 1,000 bootstrap samples in order to determine type 1 error rate. The results of the bootstrapping procedure estimate the standard error and potential biases of each path. We examined standardized indirect and two-tailed significance. The criterion for mediation was the identification of a significant indirect effect of the predictor on the outcome, rather than a significant decrease in the direct effect (Rucker et al. 2011). Both loyalty and habit showed mediator effects. Trust to future repurchase intention was found to be mediated by loyalty (p=.002), where the direct effect without the mediator is b=.32 and the direct effect with the mediator is b=.21. Similarly, switching costs to future repurchase intention was found to be mediated by habit (p=.001) where the direct effect without the mediator is b=.26 and with the mediator is b=.11.

Theoretical Contributions
The paper demonstrates the potential explanatory power of social mediation on technology use. While past IS literature delved on physical, i.e. instrumental, functional, ease of use, habit, loyalty, satisfaction attributes, in models such as TAM (Davis et al. 1989) and UTAUT (Venkatesh et al. 2003), we might now account for the shifts in the availability, ubiquity, and interconnectivity of current IS technologies, and how they generate social interaction, which might enhance physical drivers of tech use. This is not only reflected on use of tech as communication devices; computers have become social capital building and social capital maintenance devices as well (Gilbert & Karahalios 2009;de Zuniga et al. 2012). Table 2 shows the maximum likelihood estimates and resultant hypotheses support. SEM model #1 shows the confirmatory support for earlier, "seminal" IT models on repurchase intention. For instance, Limayem et al. (2007) discuss habit; Kim et al. (2014) cover switching costs;and Cyr et al. (2005) assess loyalty. The contexts for such studies varied from intention to repurchase from e-commerce sites, to intention to reuse applications, but common to these contexts was that all constructs in the base model ultimately derive from the users' direct interaction with the product, sans social factors: Were they loyal to the product? Did they form habitual use of a product that was hard to break? Did their switching costs about the product lock them in to continued use, despite their desire to break away? SEM model #1 alone provides support for factors to consider in creating a "sticky" IT product, such as an app or an e-commerce site.
SEM model #2 introduces a new set of factors: the role of a social or socially-mediated feature in the product-in this case, reciprocity and trust. The factors add significant variance explained in the repurchase intention of the product. We measured not so much the social play, interactivity, and aesthetic qualities of social tech games such as "League of Legends," but pasaload, a relatively benign transaction with no sophisticated user interfaces other than a basic text screen. In other words, pasaload does not fundamentally change the physical way users interact with the mobile phone. However, in subtle ways, pasaload reciprocity makes the mobile phone more than just a communication appliance; it becomes a mechanism of exchange, and therefore trust and social capital building (Chiu et al. 2006;Gilbert & Karahalios 2009).
The IT literature notes that a product is "sticky," given loyal, habitual customers, and customers who believe their switching costs are too high to change products. Base model #2 illustrates how the same loyalty, habit and switching costs can be dramatically enhanced with a simple load-sharing mechanism. More deeply, the act of load sharing opens a pathway to understanding how such a feature alters standard user behavior about the product. As indicated earlier, reciprocity might straddle between pure exchange and pure sharing. The debt of gratitude strongly influences the pasaload phenomenon in Philippine mobile users. Though unquantifiable, the exchange may still be considered as a social capital transaction more than an economic one. If reciprocity is withheld or delayed, there may be social penalties, at least in the Philippine context. In effect, a pasaload network could have the same behaviors as a social community, such as shirking, response, mutual monitoring, and altruism (Bowles & Gintis 2001;Uyen & Prociuncula 2010). In the context of virtual knowledge communities, trust and reciprocity are merely one aspect of relational social capital. Chiu et al. (2006) have modeled three different aspects social capital" relational, structural and cognitive dimensions (e.g. social ties, identification, shared language, shared vision) to knowledge sharing quantity and quality. Any positive social capital seems to make not only products more "sticky" but also non-consumer activities such as virtual communities sustainable and empowering.
Sharing as a socio-cultural phenomenon not only builds the social network and the community of users, but also reduces friction, such as the cost of search-well documented in electronic marketplace literature, and once initiated, lowers price sensitivity to products--effectively easing the burden of the decision to repurchase (Alba et al. 1997;Bakos 1998;Lynch & Ariely 2000). The pasaload reciprocity model of behavior provides an accessible and immediate "supply" of funds, and given reciprocal expectations, both the strength of the network and mobile usage should increase. Finally, as suggested in model #2, the implied economic and social factors are more deeply embedded in reciprocity than in the other constructs of trust, loyalty, and habit, and thereby reinforce the construct as an antecedent variable that influences other variables. The Philippine telecommunications model of reciprocity may be generalizable to any system of exchange and/or sharing: as reciprocity builds, so do trust, loyalty, and habit, thus resulting in ultimate stickiness and reuse of a product or system or service.

Practical Contributions
The findings in SEM model #1 suggest that habit might be a strong mediator even if the true financial and convenience costs to switch is low: throughout the Philippines, the many company stores of Globe and SMART are complemented by many thousands of neighborhood stores, street vendors, and mall kiosks who have ready-to-sell SIM cards. Note however that pasaload only functions within the same telecommunications firm, raising the practical inconvenience of having an entire network of users switch.
The marketing and product specialists are familiar with switching cost, loyalty and habit as "tools" to influence consumers. Given the inconvenience for users to switch, the marketing strategist might shift priorities in the marketing budget from raising switching costs to building on social connection initiatives that increase usage (and company profits) while at the same time reinforce the other mediators -such as habit and loyalty. One obvious tactic would be to increase reminders of pasaload as a gift to target specific network users during key events such as Christmas or Valentine's days among friends. Companies already promote "events" from birthday reminders to "specials" such as Father's Day. Some events may be "extended"-preparations for weddings, for example, are a source of continuous social exchange and an opportunity for offering products to the different groups. Brand building via pasaload need not be completely commercial, even as marketing executives suggest opportunities for socialization via pasaload. For example, one socially responsible initiative occurs in the Philippines during emergencies such as typhoons where land lines temporarily cease to function.
SEM model #2 suggests that reciprocity augments switching costs as a mediator. Pasaload itself might be tacked on to switching costs as a new fee. Pasaload shows the hidden power of social mediation in a product, without players actually socializing. It effectively becomes a social exchange tool, thus adding a strategic dimension to marketing. A socially mediated product therefore opens a new dimension for product design and marketing. For example, "feel good" and "do good" products and services help build social esteem among members of the network. Moreover, a telecommunications company might consider adding the accumulation of social capital as a more sustainable competitive edge against other competing products, over and above the traditional factors of the 4Ps of price, brand, Table 2. Hypotheses Support features, and delivery. Such effects are easily executable in the digital space such as in social media products like Facebook, Instagram, and Pinterest (de Zuniga et al. 2012), and the popular literature already recognizes the power of socially mediated streaming sites as YouTube and the streaming platform such as Twitch (Clark 2017) that has created careers for individuals with their own growing networks and is a ready vehicle for building consumer awareness and capturing them.
In the digital space reciprocity is even more convenient: with a click, users may reciprocate, or send an SMS to give a load to a friend. Such convenience may be more difficult to reproduce in the physical, rather than digital world. But technology can be so ubiquitous with the growth of the internet of everything devices which make reciprocity possible. Today, retailers, like Wal-Mart or Target, can provide barcode readers to shoppers for bridal registries. Might such strategies also extend to reciprocal gift-giving to family and friends? Anecdotal experience from one of the Philippine telecommunications firms suggests the following social interaction: Even if the giver of pasaload may continue to have positive social capital with the recipient, if the former perceives that his or her gifts are one-sided, the prospective recipient may not get another load but instead a chiding message, usually in the vernacular saying in essence: "That's enough for now." While the translation does not capture the nuances of the original, the implications are in essence: "We're still friends (Bayanihan or kinship) but you owe me (utang na loob) and it's your turn (to give me something)." Reciprocity, however, is not necessarily a monetary equivalent. For example, the passage of time without an actual transmission of a pasaload may be sufficient to satisfy the original giver. More likely, a token amount and not a repayment of the accumulated pasaload will be sufficient. As stated earlier, reciprocity involves some implicit contract to return favors, even if the returned favors are economically unequal (Belk 2009). Marketing strategists know that not all consumers are equal-not only in terms of income but also in persuasive ability. The social exchange of pasaload can reinforce this phenomenon and develop individuals within their network who in effect become informal enhancers of a brand or product.
In the Philippines, the duopoly between SMART and Globe generates intense competition for customers. The thrust of efforts to reduce churn and capture market seems to be through competitive pricing or physical product enhancements. As such, telecommunication product managers might consider reciprocity-based options. If at present, individual plans predominate, there might be opportunities instead for reciprocating micro-community plans, where users join as cliques or "barkadas," in the local vernacular. Already one competitor has considered giving SIM cards to groups of friends to effectively lock them into one system. Likewise, group plans for nuclear families, where reciprocating is almost obligatory (i.e. head of family purchases a large load, then passes smaller loads to children) and thus might lock customers in and increase convenience, loyalty, and raise switching costs. To encourage heavier use or product, telecommunication firms might also discount pasaloads if sent to cliques or friends (Bowles & Gintis 2001).
The two telecommunications firms are riding the trend towards data science with big data analysis. Telecommunication product managers already possess substantial big user data for analytics. The two competitors are aggressively expanding their resource pool of data analysts. By tracking customer usage, they can identify pasaload peaks and valleys and send out occasional prompts to the effect that: "Isn't it time to pasaload?" By now SMART and Globe must be able to track the millions of pasaloads to and from, to who and when. The analysts can be directed to assess inter-friend and inter-family pasaload and correlate it with usage as well as repayment security. Such analytics may reveal seasonal, cyclical, occasional patters on social consumption/reciprocity, which leads to more efficient plans to make pasaloads last longer and to buy more than normal loads.
Reciprocity may be extended beyond pasaload and into e-money. Currently Japanese consumers make most retail purchases via their mobile NFCs (Near-Field Chips). In the Philippines, a telecommunications firm might allow pasaload to pass through third parties like retail and financial companies. An arrangement can take place whereby a retailer that is not normally part of the reciprocal network can, through the telecommunication firms, participate in pasaload transactions for gift-giving, holiday presents, and special occasions. These options for telecommunication firms in the Philippines are currently limited by banking, anti-trust, and anti-competitive regulations that act as barriers to telecommunication firms selling of financial products. However, globalization and the need to attract foreign direct investment from multinational corporations are gradually wearing down these barriers.
Beyond pasaload, reciprocity as an antecedent may work well in strategic marketing communications. Reciprocity can be enhanced beyond the exchange of goods or services for cash as a transaction to a sharing that connects the company to the product-based network or community of consumers. It can reinforce existing practices. For example, various loyalty programs offer points and other incentives. The communications message may be adjusted from "we want your loyalty" to "we are doing something for you." Corporate social responsibility initiatives are indirectly a key part of marketing communications. Reciprocity could call attention to these initiatives as part of sharing, or participation by multiple stakeholders as socially responsible. Marketing communications in a social network almost by definition requires a social or sharing component and a message or advertisement involving reciprocity could result-for example, in viewers not clicking the "Skip Ad" button, a process that can explored.
Finally, reciprocity and trust are only two forms of social capital building. Chiu et al. (2006) identify other social building behaviors such as identification, or the recognition of a person as an in-member of a group (e.g. Facebook groups), or having a shared language, (e.g. Instagram will have features that teenagers easily and uniquely identify with versus their parents), even a shared vision (e.g. special interest groups, members-only blogs) (Chiu et al. 2006). Philippine telecommunication firms have actively complemented their services with popular external apps like Facebook, in order to make their phone products stickier. SMART and Globe, for example, give free data to Philippine Facebook users, (though without messaging or image downloading) knowing that Facebook is almost a necessary appliance for Filipinos (Castro 2018). However, the telecommunication firm itself might investigate how to simulate these other social capital building activities beyond complementary apps and into their in-house native products.

Limitations and Future Research
As in many survey-based methods papers we based our findings on static, variance theory (Markus & Robey 1988). However, a more interesting extension is to take a process view, as in study smartphone users' reciprocity over time-how do the same factors affect the journey of reciprocity of users? How so social interactions grease or hinder reciprocity? How do such interactions degrade or increase trust with respect to reciprocity? This article did not assess other omnipresent social factors, such as network externalities, where the sheer lack of alternatives makes users more inertial, harder to switch, or render loyalty and trust moot. For this article, we considered these network effects as a common factor affecting all users, a recognized limitation but also an area for future research.
Within the Philippine cultural context of "debt of gratitude," deeper research can be undertaken on pasaload within the nuclear and extended family network where a dichotomy can be explored between family as insiders and friends and others as outsiders-with the obvious presumption that load sharing would be significantly stronger with the former, which is not yet demonstrated by research. This exploration might also create a dichotomy on "reasons why" that in turn would offer practical suggestions on reciprocity and repurchase intent. We can likewise investigate how other forms of social capital like identification, shared language, and shared vision relate to product stickiness.
Given the Philippine context, one comparative area of research is to explore the impact of debt of gratitude in other Asian countries with a common cultural context. For example, Japan has a similar concept of obligation -"giri"-that could be explored. Moreover, the research can be expanded to other non-Asian countries where the cultural contexts may differ, and more transaction-based economics may be more prevalent. Finally, the original research by Goulding (1960) that demonstrated the universality of the reciprocity concept might be juxtaposed against the research that implies the differentiating impact of culture.

CoNCLUSIoN
The strong cultural sense of kinship (bayanihan) and its corollary of reciprocity (utang na loob) among Filipinos extends beyond the immediate family with telecommunications and mobile phone technology as a driver for Filipinos to build and expand social networks with via social media as the key vehicle. With respect to the research objectives, pasaload exchange reinforces reciprocity, and it appears embedded within the Philippine cultural value system, such that practitioners are already applying it in their strategies. Pasaload acts as a "stickiness" tool to sustain the process of reciprocity. At the same time, pasaload has both intrinsic value and social worth as it is exchanged among friends and other members of the social network.
Our paper allows for the convergence of theoretical and practical considerations. While bearing in mind ethical and privacy issues, software already exists to track and identify "persons of influence" in social networks. Quite apart from tracking "hits "and scoring "likes", pasaload represents a quantifiable measure of exchanges among network members as a means to analyze individual impact on particular networks or clusters of communities. The data, once analyzed and structured, may result in further identifying characteristics and patterns of behavior and action. Research on pasaload data might successfully measure degrees of influence among members, for example, and further enrich the study of reciprocity.
The practical implications show even more promise. Once again keeping in mind ethics and privacy, practitioners can engage in targeted marketing to identified persons of influence, as opposed to simply blanketing a network or cluster. Since pasaload appears to be a form of currency, companies through the telecommunication firms, can offer "bonus" pasaload to reward key individuals in a group and to provide quasi-monetary pasaload incentives that allow these targeted persons to expand their influence. The combination of pasaload with specific products might generate increased revenues and build brand reputations.
Beyond telecommunication products, this paper illustrates how social capital lubricates and enhances trust and loyalty. Social capital raises switching costs and habitual behaviors. All these converge to raise continued use of products. Habitual use of smartphones is well-documented and may have actually reached epidemic rates (see literature on FOMO, or "Fear of Missing Out" in Rosen et al. 2013;Elhai et al. 2016). However social capital may be the extra "glue" that makes general products, not just phones, stickier. For example, while a streaming product like Netflix may have a wide selection and quality content, as well as a crowd-sourced recommending system, Netflix does not inherently have direct social elements such as friends and "likes" in Facebook. Netflix may be therefore more susceptible to customer churn, compared to, a counter example of socially mediated services in Spotify, the Swedish-based music service. One of Spotify's features is for users to collaboratively build and share and/or look at other people's playlists, to augment their listening variety (Gilmour 2018). There is also Israel-based iTero, a relatively new product that uses social trading, "wisdom of crowds" brokerage service, where one can copy stock trades of strangers and acquaintances. While quality content and user interfaces are still paramount for consumer loyalty, we submit that "extra" social capital building elements can help raise switching costs and lock-in users just about any product.