Luiz Cláudio Oliveira Impacts Observed on Private Label

LUIZ CLÁUDIO OLIVEIRA

IMPACTS OBSERVED ON PRIVATE LABEL CARDHOLDERS OF A LOCAL COMPANY WHEN PURCHASED BY A MULTINATIONAL COMPANY

SÃO PAULO - LISBON

2017

LUIZ CLÁUDIO OLIVEIRA

IMPACTS OBSERVED ON PRIVATE LABEL CARDHOLDERS OF A LOCAL COMPANY WHEN PURCHASED BY A MULTINATIONAL COMPANY

A Work Project, presented as a part of the requirement for the award of a Master Degree in Management from the NOVA - School of Business and Economics and INSPER - Instituto de Ensino e Pesquisa.

A project carried out on the Master in Management Program, under the supervision of Professor Carlos Santos from NOVA – School of Business and Economics and Professor Sérgio Lazzarini from INSPER – Instituto de Ensino e Pesquisa.

SÃO PAULO - LISBON

2017

ABSTRACT

Some countries still have private label credit card companies which worldwide leading companies see as an opportunity of acquirement to conquer new markets and to increase profits. This study analyzes the evolution of a private label cardholder base, which has had its instrument changed to a worldwide brand of acceptance. Therefore, the monthly consumption base of the card users for equivalent periods before and after the brand change was analyzed, using multilinear regression and panel data. The results show an unexpected behavior of fast increase of the use of the card and a change in the mix of the basket of products.

Keywords: Consumer Behavior, Private Label, Credit Card, Strategy

TABLE OF CONTENTS

1. INTRODUCTION ...... 4

2. PRIVATE LABEL AND BUSINESS MODEL “CARTÃO BENEFÍCIO” ...... 6

3. LITERATURE REVIEW ...... 8

3.1 Payment Mode Effects ...... 8 3.2 Credit Card Logo Effect ...... 8 3.3 Oligopolistic network ...... 9 3.4 The Nature and Evolution of the Credit Card Market ...... 9 3.4.1 Credit card network ...... 10 4. HYPOTHESIS ...... 12

5. METHODOLOGY ...... 13

5.1 Data Collection, Data Organization and Regression Model chosen ...... 13 5.2 Regressions ...... 15 6. ANALYSIS OF RESULTS ...... 18

6.1 Multinational Company – Regional Management...... 19 6.2 What they did not know...... 19 7. LIMITATIONS AND FUTURE RESEARCH FIELDS ...... 21

8. REFERENCES ...... 25

1. INTRODUCTION

The credit card was created in the middle of the 20th century and with the advent of online technology, it was possible to evolve the concept of credit for debit card, prepaid card, food voucher, fleet card among so many other forms. In this way, the credit card that was created inside banks evolved and reached other economic sectors, yet maintaining its main purpose of guaranteeing the financial settlement for those who receive it. Since credit card brands were created, they reached a global scale in a short period of time and, despite the initiative of some countries, the current brands are still almost an American oligopoly (MasterCard, Visa and Amex). In emerging markets, like Brazil, banks were the first to adopt these companies and comply with the international rules offering national and international products to their clients.

Starting out in the 70s and advancing the early years of the twenty-first century, incentive products and social benefits have been created, such as food, meal, pharmacy, fuel and cultural vouchers. Brazilian companies that did not belong to the financial system, regional card companies, benefit companies, prepaid card companies, have become so large and so promising that the ultimate regulatory authority has decided to regulate and discipline this market, creating a specific legislation for the issuance of electronic money (especially private labels companies) in 2013 with practical effects from 2015 until 2022.

Nowadays, in Brazil, it has been estimated more than 100 companies (Policard, ValeCard, Unik, CooperCard, MinasCred, ExtraCard, Brasil Cartões, Vale Presente, Acesso Card and others). These companies have not been studied yet despite their regional importance. In this study, we observed a multinational company, one of the largest companies in the world issuing world brand cards, to acquire, in 2012, a Brazilian regional private label credit card company (regional brand), with its own brand, its own issuance, its own acquiring with the establishments.

The purpose of this paper is to evaluate the effect of changing the brand in the use of the card and in the diversification of the use of the card. Thus, it is necessary to observe what happens to users of the regional brand credit card, with direct payment from their salary (“Cartão Benefício”), when cards change to an international and world branded card with a larger network of establishments, a greater range of benefits and a greater exposure to marketing. It is important to highlight that this change from Regional brand to World brand did not occur at the 5

same time for all clients. An implementation schedule was created to roll out for almost two years thus avoiding a negative impact from this change.

It should also be noted that the literature on the impacts of consumer behavior when a private label regional company is acquired by a multinational company has not been clearly explored so far, as this phenomenon is still underway. The main issue is that some of the actual data need to be well structured and assembled for better analysis and a better prediction of future behavior, which is often not easily accessible for studies. For this reason, this study intends to fill a new gap in the literature that could help future studies.

2. PRIVATE LABEL AND BUSINESS MODEL “CARTÃO BENEFÍCIO”

The “Cartão Benefício” (a kind of payroll card), from this Multinational Company is an example of versatility and therefore was chosen to carry out this study. Multinational company bought the entirety of regional brand in 2012. Regional brand is a card company. It is neither bank nor financial institution, but for many years it was the only non-financial company associated with Banco24Horas, an automated teller machine (ATM) network (like Multibanco in Portugal/Europe).

This card, does not have the nomenclature "credit", neither in the plastic, nor in its sales and operational approach. Also, it does not have any financial charge for its users since all purchases made within the established credit limit are deducted directly from each user's payroll by the employer and contractor of this card. Indeed, this card is not acquired by the user but through an agreement between regional brand and the contracting companies which, in turn, are the employers of the users.In addition to being a shopping card, the regional brand card allows the payment of bills online and cash withdrawals in the Banco 24Horas, in which case, the services are performed through the payment of service charges and charges that are informed at the time of the transaction. Therefore, this card has a very large acceptance in low income social classes, where, the arrival of a card sponsored by the employer, is generally a reason for joy, since the employee has a sense of social inclusion with the new tool. Many employees will use it even if they do not understand the card either for reasons of technology aversion or for reasons like not being able to keep track of the ratio of spending to salary.

In this type of card, there is always a concern that the employee will not receive his or her salary at the end of the month because the card "will have eaten everything", although insistently the contractor company's Human Resources (HRs) provide explanatory training about the use of the card with its operation and its established limits. Many HRs consider this card as a salary- in-advance card, meaning that the employees do not have to feel embarrassed every month by asking for the "voucher". The card functions are an antecipation of up to thirty percent (30%) of theemployee total gross salary.

The first perception of regional brand by users is a service to help the HRs of the contracting companies to monitor their employees, therefore it is seen asa benefit card. Indeed, the “Cartão Beneficio” regional brand has a "controlled" acceptance network. The cardholders cannot spend money shopping at any trade but only in supermarkets, pharmacies, fuel stations and other merchants that HRs requests and approves to be part of the payment system of the regional

brand. The main advantage of this card is that the card user does not pay fees or financial charges. The payment is fully deducted from the employee’s salary in the month following use. The card obeys the cycle from the 20th day of the previous month to the 19th day of the current month, and the corresponding payment is deducted on the next month’s 5th day.

Through the acquirement by Multinational company, the regional brand business model was rearranged and its network increased. Firstly, the new regional brand / world brand (“Cartão Benefício”) has now a network of 1.8 million establishments in Brazil and this card can be purchased at any e-commerce. In this way, HRs cannot any longer "manage" the consumption of its collaborator. Indeed, the card remained a shopping card, keeping the flow and routine up cycles, but had now a monthly fee of R$ 2,50 (almost US$ 1,00) every month the “Cartão Benefício” is used, which could turn into a major inhibitor in card usage, since regardless of the number of transactions in the month, there would be a charge imposed. Regarding the rules for collection of events, withdrawal and payment of bills (fees and rates), no changes occurred. Also, the previous credit offer remained the same, with no changes in the setting of loan rates.

Being the focus of the “Cartão Benefício” to grant benefits to the company’s employees, its use and its activation are concentrated in the base of the salary structure. Employees who have low salaries are the largest and regular clients, once they find this product as a practical and useful way to get wage advance without payment of fees or interest. Many of the users are simple people that have never had the opportunity to have a bank account, and this card is their first chance to have one and to access the financial system, with all the facilities it offers. With the arrival of the Multinational Company and the World brand, the product got a new and more interesting packaging for this population that has now not only a regional card but also an international brand card, a known one with extensive media exposure. These characteristics make the card more attractive by combining social inclusion with low cost to the company and/or employee and making the product more valuable (features and brand).

3. LITERATURE REVIEW

Considering the object of investigation of this study, the theoretical foundations based on the pertinent literature which will guide its whole discussion will be approached in this topic. In this way, the following theories will be explored: factors that interfere in the behavior of the consumer credit card and the nature and evolution of credit cards.

3.1 Payment Mode Effects Early findings about the payment mode effects have been done in the studies of Thaler (1980) who introduced the mental accounting theory to the literature, which he divided up in his second study (Thaler, 1999). The mental accounting theory entitles the cognitive processes required by individuals to manage their financial operations and has three main components: the price paid and the benefit sought, the payment for specific purposes (ex: bills) and the awareness of the money they currently have on their account. As he explains in his studies, the more people do these financial operations, the more shortcuts they use and therefore, they reduce the process. Therefore, by using credit card people lose the sense of transparency. They lose the perception of the value (money) that is being transferred during the payments as they do not see it physically. More recently, Soman (2001) reinforced the importance of loss in transparency during memory recall. As people use their past experience in order to make new payments and these payments are not being memorized, they usually ignore if they are over spending money or not. Kahn (2011) explained that cash gives a different experience to consumers as it is a physical value, an aspect electronic payment do not have. In fact, the study will bring evidences the withdrawal cash has a significant role in the overall consumption of the “Cartão Benefício”. In addition, Prelec and Semester (2001) conducted two studies to evaluate the willingness of people to make payments using their credit card instead of cash. In the first study, the results reported that people are more likely to bid with credit cards than with cash and in the second study in the same context, these persons are more likely to place higher bids than others who pay in cash. The relationship between the payment mode effects and the consumer behavior can also be explained by studies regarding the credit card logo effect. This brand effect (logo) should also have its relevance in this study.

3.2 Credit Card Logo Effect

A study conducted by Feinberg (1986) explores the responsibility level of American consumers whenever they pay with credit cards, that is to be, if they over use it or not. During this study, the behavior of consumers was observed in a restaurant. According to the first part of the

literature, it was proved that consumers who pay in credit card gives a higher tip to waiters than those who pay in cash. However, Feinberg also discussed the presence of the credit card logo as being a facilitator of spending and stimuli to spending behavior. Indeed, consumers will tip even more when they see the credit card logo, with a faster time decision making. On the other hand, a more recent study conducted in New Zealand shows the opposite effect. Over there, the number of credit cards is increasing, at the same time, that the credit card debts increase. Therefore, this could be explained by Feinberg. However, in this study, when consumers were exposed to credit card logo, they would have limited stimuli and would spend less than people who would see the credit card logo. Consequently, this implies that there are other factors responsible to the positive effect of credit cards (Lie, Hunt and Peters, 2010).

3.3 Oligopolistic network

There are four main players controlling the global market share with an open loop network: Visa (44.1%), MasterCard (29%), UnionPay (15%), and American Express (7.1%) (Source: Nilson Report 2017). This distribution is very similar when applied to the Latin American market. In Brazil, both Visa and MasterCard combined represented a value share of 89% in 2015 (Euromonitor International, 2016). As there is a small number of leaders in the credit card industry, it makes the entry to the market very difficult for small players. Therefore, it creates an oligopolistic structure in which only few big players invest money in R&D and set either low prices to attract new customers or high prices to exploit old customers. Consequently, the entries barriers are very restricted for any small company.

As the competition is important among these few players, companies may come to collusive agreements and reduce even more the competition. Therefore, a tendency towards a monopolistic market structure occurs. This latest market structure is the least competitive and closes even more the barriers to new entrants. (Wang, 2007). However, as Baxter (1983) demonstrated, these collusions often lead to a decrease in bargaining costs between issuers and acquirers.

3.4 The Nature and Evolution of the Credit Card Market

Evan and Schmalensee (1999) argue that credit is as old as human society, however, the concept of a general-purpose credit card came to existence in 1949 with Frank McNamara. Later, he founded and named Diners Club, which would issue cards to consumers and sign merchants to accept those cards.

Abdelrahman (2011) shows that in 1958, the first widely accepted plastic charge card was introduced by American Express having the marketing tagline as “Do not Leave Home without It.” Bank Americard introduced the first revolving general-purpose credit card in 1959, which became Visa in 1977. In 1966, the Interbank Card Association introduced “Master Charge” which became MasterCard in 1979.

Garman and Forgue (2000) stands out that credit in general is of two types: collateralized (secured) and non-collateralized (non-secured). Credit cards are a non–collateralized means of credit with an interest- free grace period. Moreover, credit cards are non-installment consumer debt or open-ended credit in which consumers do not have to reapply each time a credit transaction is made. The amount owed can be repaid monthly in equal or unequal payments. Because of the uncertainty problem in this industry, the interest rates on the credit cards are higher than for regular credit.

The participants in the card industry are: brands, issuing banks, acquiring companies, merchants and users. Credit card issuers are usually banks, which provide the credit line, stipulate fees, rates and develop relationship with the carriers. The credit card issuer pays for the transactions, but the cardholders have to repay the money plus any interest accrued. Interest is the cost of borrowing money and is calculated as a fixed fraction of the total outstanding balances. Still, the card industry includes two customer platforms: cardholders (carriers) and merchants (establishments).

In terms of consumer risk, industry researchers distinguish four types of cards users: (1) low- risk convenience users who use cards for convenience purpose only with no intention to revolve balances; (2) low-risk users who revolve balances; (3) high-risk users who carry balances and (4) high-risk users who do not carry balances (Kim, Dunn and Mumy, 2005).

Users usually relate to a bank. The bank manages customer needs for banking services, including credit. The shopping facilities accept credit card for the payment of goods and services. Finally, stands out the largest credit card brands in Brazil and worldwide are MasterCard, Visa and American Express. The brands establish use rules, flows and homologation processes, supports and creates global strategies (Rocha, 2007).

3.4.1 Credit card network

The credit card market is considered as a two-sided network: a platform satisfying two different end-users by setting the price for each of them (Chakravorti & Roson, 2006). In this context,

both consumers’ and merchants’ benefits result from two independent demands that need to be satisfied at the same time. From the merchants’ perspective, they will accept credit cards only if there are enough active cardholders while, from the cardholder’s perspective, they will use a card only if there are enough merchants accepting the card (Chakravorti, 2003). In more recent studies, Hagiu (2014) called Visa a multisided platform which put in direct contact several participants. Rochet & Tirole (2002) and Wright (2002) explain through their studies that merchants started to accept credit cards for two main reasons: to attract more customers and to increase their profit. As not every merchant was accepting credit cards, merchants who accepted cards had a competitive advantage on others. Indeed, they could attract a larger number of customers including those who pay in cash or with credit. For the financial perspective, Chakravorti & To (2007) stated an additional important point about the discount fees for merchants. These fees are established according to the number of customers who use a credit card. Furthermore, even if these interchange fees for merchants are quite high, they often counteract this issue by increasing the price of their products or services to keep their margin regardless if the consumer pays with cash or credit card. From the consumers’ perspective, there is a trade off as using credit cards as they would pay the same price than someone who pays in cash anyway.

By using credit cards consumers can benefit from a reward card program. (Schuh, Shy, Stavins, 2010). Thus, the interactions between both consumers and merchants create a “positive network effect” (Rochet and Tirole, 2003).

4. HYPOTHESIS

These previous studies highlight the relationship between the consumer’s behavior and the credit cards usage in specific context. It has been proved that consumers spend more money when they use credit cards as a mean of payment as the transparency previously established during cash transactions is disappearing. Also, if these people are reminded to use credit card, it will stimulate their spending behavior (Lie, Hunt & Peters 2010) proposed in a contradictory study. In this study, it was analyzed a change in behavior of consumers who were previously exposed to a smaller network in which they could use their card and who are now exposed to a bigger network. As they were already using credit cards, this study will try to fill in the gap in the literature by exploring if these effects and stimuli will increase as the network becomes bigger and if the spending of each consumer will also diversify. However, it is not only a change in the size of the network that affects the cardholder. The regional card has a global brand with a lot of institutional exposure of such brand. And, it may be that this set of changes, positively or negatively, affects the total amount spent on the card.

So, we have a set of leads or issues in actual literature. Thaler (1999) talks about the behavior of the user and tries to explain (1) the relation of price paid against benefits received, (2) payments for specific purposes and (3) consumption influenced by the rewards that total spending can bring. Feinberg (1986) showed that the change of brand brought simultaneous increases and decreases in the observed consumption of a different population. In the same situation (logo change) was found evidence of increase and decrease in consumption (USA x New Zealand). Also, there is another features the facility of multi-sided platforms attracts more consumers and get higher revenue and profit (Wang, 2007). Based on this, the first hypothesis of this work emerges:

Hypothesis 1: The change in the brand of credit cards positively affects the behavior of consumers, leading to a higher consumption.

Feinberg (1986) has proven that using the credit card brand makes the purchase decision quicker and more spending. In this study, the network of establishments of the new brand is 1.8 million establishment compared to 40 thousand in the previous brand. Based on these two topics, the following hypothesis is proposed:

Hypothesis 2: The change in the brand of credit cards positively affects the diversification of product baskets

5. METHODOLOGY

5.1 Data Collection, Data Organization and Regression Model chosen

In order to accomplish the empirical hypothesis test, Regional brand was asked a random sample from its base that has more than 2 million active clients (Februrary 2017). The first base had more than 500 thousand registrations, but the majority was excluded because they did not have any relevant information or they showed inconsistencies not easy to identify and resolve. Most clients do not have a complete register data with relevant information like hiring date of employee, date of birth, education, position or function, wage or salary range. Some transactions did not have information about the limit of the card at the time of purchase due to particularities established by the agreement or even due to timely requests of the company. For not presenting a large sample of 12 observations from Regional brand and World brand, this study looks into 8 monthly consecutive observations, before and after the change of the brand of the “Cartão Benefício”. It was not possible to determine if the existing gap in monthly movement came from an error in the data extraction, from generating or storing data, or even from exogenous factors. And for this reason, they were not used. So, the random base was reduced to 5.376 observations corresponding to 336 users identified by a registration number (CPF - Social Security Number). Thus, there are two brands that appeared during the period of study, Regional brand (0), in the first eight months, and World brand (1). Next, the data collected was grouped into four categories: online shopping, automatic debt, ATM withdrawals (loan) and establishments (store purchase). The total amount of expenses corresponds to the sum of the four values presented. The sample is organized in a panel format. But we shall highlight that in this collected data, the amounts spent with the debts and online shopping present many zeros. When carrying out a regression of the data in a panel with four independent variable elements and the total value of use as dependent variable element, the result shown in the regression is that there is a collinearity for the values related to automatic debts and online shopping, therefore there is no need to use this data. When carrying out a regression with the variable elements total value, establishment and withdrawal using or not a variable dummy, the variable coefficients of establishment and withdrawal equal one, and the value of the constant and the variable coefficient of dummy corresponds to 10-12, and the value of R² equals one. Thus, this regression will not be used in this work. So, this above mentioned elements will be used as variable elements, together with the value of total cost of the card, the value of

purchasing and the value of withdrawal. As a matter of facilitating the identification of the independent variable elements we will call them X, being t instant of time and i the specific variable element.

Table 1: Descriptions of the variable elements

Variable element Representation Independent Variable element description or Dependent

Total Value Vtotal Dependent. It corresponds to the total value of the card in a determined month

Establishment Merchant Independent or It corresponds to a value used in shopping in a dependent. determined month

Withdrawal Withdrawal Independent It corresponds to a value used in withdrawal in or dependent a determined month

l_vtotal l_vtotal Dependent or Natural logarithm of the variable of the sum Independent between total value and one.

l_establishment l_merchants Dependent or Natural logarithm of the sum of the variable independent establishment with 1.

l_withdrawal l_saque Independ or Natural logarithm of the sum of the variable withdrawal dependent withdrawal with 1.

Withdrawal and total Sdt Dependent It’s the relation between withdrawal and total value relation value variables

Purchasing and total Cdt Dependent It’s the relation between purchasing value and value relation total value. For the same period

Brand Brand Independent Variable dummy indicates the brand card, equals1for World brand and equals zero for Regional brand.

mi mi Independent Variable dummy evaluate the effect of the use of the card over time, the indexes i vary from 1 to 16, for i from 1 to 8 correspond to the months with the Regional brand, with 1 being the oldest month in relation to the change of the brand and 8 the nearest month in relation to the change of

brand. For i ranging from 9 to 16 corresponds the World brand with 9 the month closest to the change of brand and 16 the most distant month. This variable may show behavior change over time.

(*) for this effect, values of m until m = 15 were applied to the calculations (Source: personal collection).

For analyzing data, a multiple regression analysis was necessary and the statistical software Stata, version 13.1 was used.

5.2 Regressions

The main regression was:

n Y     D  u it 0 j1 j ji it D is the dummy variable used for each regression.

The regressions that will be done are described as following: Regression 1: dependent variable total value and variable dummy mi as independent variable elements. The objective will be the analysis of the use of the card throughout each month taking into account the brand change. Regression 2: dependent variable withdrawal value and variable dummy mi as independent variable elements. The objective will be the analysis of the use of the withdrawal service throughout each month taking into account the brand change. Regression 3: dependent variable establishment and variable dummy mi as independent variable elements. The objective will be the analysis of the use of the card for shopping throughout each month taking into account the brand change. Regression 4: dependent variable total value and variable dummy as independent variable element. The objective is the analysis of the use of the card before and after the brand change. Regression 5: dependent variable withdrawal value and variable dummy as independent variable element. The objective is the analysis of use of monthly withdrawal taking into account the brand change Regression 6: dependent variable establishment and variable dummy as independent variable element. The objective is the analysis of the use of the card for shopping before and after the brand change.

Regression 7: dependent variable sdt and variable dummy mi as independent variable elements. The objective is the analysis of the use of the card for withdrawal throughout each month taking into account the brand change, considering the withdrawal proportion. Regression 8: dependent variable cdt and variable dummy mi as independent variable elements. The objective is the analysis of the use of the card for shopping throughout each month taking into account the brand change, considering the purchasing proportion. Regression 9: dependent variable cdt and variable dummy as independent variable element. The objective is the analysis of the purchasing proportion in the use of the card before and after the brand change. Regression 10: dependent variable sdt and variable dummy as independent variable element. The objective is the analysis of the proportion related to the total use of the withdrawal service throughout each month taking into account the brand change. Regression 11: dependent variable the natural logarithm of the total value and variable dummy as independent variable element. The objective will be the analysis of the use of the card before and after the brand change. Regression 12: dependent variable the natural logarithm of the withdrawal value and variable dummy as independent variable element. The objective will be the analysis of the use of the withdrawal in each month taking into account the brand change. Regression 13: dependent variable the natural logarithm of the value of the establishment variable and a variable dummy as variable independent element. The objective will be the analysis of the use of the card for shopping before and after the brand change. Regression 14: dependent variable natural logarithm of the total value variable, the independent variable elements are the natural logarithm of the establishment variable, the natural logarithm of the withdrawal variable and the dummy variable.

The regressions of numbers 7, 8, 9 and 10 are used to verify the hypothesis number 2, while the other regressions are used to verify the hypothesis number 1.

Table 2: Results of the multiple regressions

Fixed Effect Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8

Withdrawal and Purchasing and total Total Value Withdrawal Establishment Total Value Withdrawal Establishment total value relation value relation Constant 989,2691 875,1363 114,1328*** 226,076* 129,4208* 96,6559* 0,2455431* 0,754457* (149,8507) (147,1845) (28,63578) (54,17666) (53,21971) (10,344) (0,0220588) (0,0220588)

Brand 317,8029* 287,3881* 30,3148* (76,617765) (75,26403) (14,62862)

R-squared 0,0068 0,0065 0,0027 0,0032 0,0027 0,0008 0,0075 0,0075 Númber of observations 5376 5376 5376 5376 5376 5376 5376 5376 Number of Individuals 336 336 336 336 336 336 336 336 Time Dummy 3 significant 2 significant 2 significant NO NO NO 6 significant 6 significant

Fixed Effect Random Effect Model 9 Model 10 Model 11 Model 12 Model 13 Model 14 Model 15

Purchasing and Withdrawal and total value total value log_ Total relation relation Value log_Withdrawal log_Establishment log_ Total Value log_ Total Value Hypothesis Constant 0,698399* 0,301601* 4,733271* 1,786868* 3,5554595 2,258836* 2,119916 (0,0079917) (0,0079917) (0,0229966) (0,0509863) (0,0317372) (0,0289097) (0,035288) H1 and H2, Brand 0,068692* -0,068692* 0,177986* -0,170427* 0,5089898 0,0067977* 0,00500129 Supported (0,0112862) (0,0112862) (0,0325221) (0,0721055) (0,0448832) (0,017781) (0,0150799) log_Withdrawal 0,4882329** 0,471885** H1, Supported (0,003845) (0,0044342) log_Establishment 0,4977874** 0,4897639** H1, Supported (0,006177 (0,0069105)

R-squared 0,0069 0,0069 0,0055 0,001 0,234 0,7106 0,7407 Númber of observations 5376 5376 5376 5376 5376 5376 5376 Number of Individuals 336 336 336 336 336 336 336 Time Dummy NO NO NO NO NO NO NO Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1

6. ANALYSIS OF RESULTS

Analyzing the coefficients obtained in the regression represented by 4, the coefficient of the dummy variable referring to the total consumption of the World brand corresponds to the value of 543, that the result of the sum of the brands and constant coefficients of table 2 for model 4, and the corresponding value to consumption with the regional brand corresponds to 226, which corresponds to the value of the constant. Thus, these data show that the average consumption with the World brand was higher than the average consumption with the regional brand, that is, with the brand change there was an increase of the total consumption or the use of the card in a general way. The regression represented by model 5 shows the average value of the draw performed with the World brand and the regional brand. The average value of the service with the World brand was 416 and with the regional brand was 129. These results show that with the brand change there was an increase in the use of the service. The regression represented by model 6 shows the average values of purchases in establishment and with the brands World brand and the regional brand. The average value of purchase in establishments with the World brand was 127 and the average value of purchases in establishments of purchases with the regional brand was of 96. These results show that with the change of Regional brand for World brand there was an increase in the use of the Card for purchases in establishments. The regression by model 9 shows the average draw ratio in relation to the total use of the card for the regional brand and World brand banners. The average proportion for looting with the regional brand was 69%, while for the World brandit was 77%, so it shows that with the change of brand there was an increase in the proportion of looting. The regression represented by model 10 shows the average proportion of purchases in establishments in relation to the total use of the card for the regional brand and World brand banners. The average proportion for the World brand was 23% and for the regional brand was 30%. These values show that the proportion of use for purchases decreases with the change of brand. However, it is worth mentioning, as we have already discussed, that the absolute amount of purchases increased with the change of brand. Thus, it can be said that the increase in use of the card was greater than the increase of use for purchases with the brands changes.

Thus, we can conclude that the two hypotheses could be supported with the following assertions: there is statistical evidence that there is an increase in the average spend of card users when there is the exchange of the Regional brand for the World brand. There is also statistical evidence that there is a change in the consumption of the baskets of products: the withdrawal starts to have a greater weight in the total consumption. Curiously, the withdrawal network (Banco 24Horas) has not increased. This network remained the same. The network of establishments has increased considerably (from sixty thousand to 1 million and eight hundred thousand establishments). And what was verified was an increase in the spending of establishments but mainly a much greater expense in the service. We already know that consumption of establishments has increased, but the increase in withdrawal has had a greater impact on total spending, contradicting up to now the existing literature on consumer behavior regarding network growth and exposure to a global brand. We should not forget, that the new card has a higher cost to the card user, because it brings a monthly fee that the Regional brand card did not have.

6.1 Multinational Company – Regional Management

The preliminary results were informally discussed with the C-Level of regional team. From the beginning of this work, an observation has been carefully and sensibly established regarding the confidentiality of the register data of the clients as well as every single information classified as confidential by Regional team. In general terms, Regional team operates its results using management systems that report the behavior of its clients almost online. In addition to that, it uses its own methodology to segment its clients and users and to observe several KPI (Key Performance Indicator).

6.2 What they did not know

They thought that physically changing a card, a set of factors (logistic, time delivery for HR to the employees, time an employee takes to activate it) would be responsible for determining a less use of the card from the observed so far creating a slope of the consumption curve. The new element is that the evidences show there is no significant delay that can affect the use of the new card. What happens is a rapid adjustment to use the new card and an increase in purchasing (establishment), an absolute increase of withdrawals and a new mix of revenue

20 to Regional brand. It is also important to highlight that despite the fact the new business model of Multinational Company, World brand charges a fee that did not exist in “Cartão de Benefícios regional brand”, this did not affect the increase of the amounts used in the sample.

7. LIMITATIONS AND FUTURE RESEARCH FIELDS

This study is restricted to some relevant factors. First, the extraction of data to accomplish the research was a new event for the Multinational Company. This leaded to a need for adaptation of the internal processes, as well as the utilization of unexpected resources to accomplish the extraction. Second, even after meetings with the technology teams, the first available data for this study had many inconsistencies, and some were clearly a problem from the registration data and not from the extraction nor from its manipulation. As discussed in the study, regional brand provides services to Human Resource that does not required the employees to give any personal details (salary, date of emission, address, function, position, civil status) that could allow a credit analysis. Thus, the data required is minimal which fits with the willingness of the companies to protect their employees registered data. Therefore, the few data collected from the user register of the company could not allow a solid analysis or an analysis with mores independent variable elements. After setting some points, the quality of the extraction was improved but it would take time and some investment from Multinational Company to solve the relevant gaps. However, even identifying specific issues with understandings that were solved during the organization of the data, the data used for the study was finally available at the end of May 2017, which limited even more the period of time to accomplish this study. As mentioned, in spite of the company's efforts to extract the best data quality, a database with 52,104 observations of customers with a limit of 10 to 100 reais was made available. However, for the conclusion of this work it had to be subsequently manipulated, generating a final sample of 5.376.

This study shows that in the future it will be possible to get a base with a great number of balanced observations in both events (0 - Regional brand) and (1 - World brand) to (re)confirm these results. We can also have a more qualified analysis, when the users will be enrolled in the relisting process. In addition, we can continue the study to understand which variable elements could affect the relationship and the behavior of the users with this card.This emphasizes the importance of maintaining an effective and updated database of consumers and merchants to understand the cause and effects of each change in their behaviour and to conduct further studies. Despite the significant increase in the network of establishments, it was not possible to determine if the increase in consumption occurred in the same establishments of the old network or if it occurred due to the increase in the size of the network, since there is no data available to show the second hypothesis.

Furthermore, this study will help future studies in the understanding of themes such as: 1. Cardholders loyalty 2. Consumption of product bases by cardholder (volume or mix) 3. The Business Model for the company and for the companies-customers 4. The acceptance network of merchants 5. Evaluation of the results of the Corporate Strategy of a multinational company in the acquisition of a payment company in another country 6. Evaluation of cardholders decision-making process 7. Evaluation (or not) about the Corporate Social Responsibility policies.

Appendix 1 – Variable Elements Summary Variable Mean Std. Dev. Min Max Observations total overall 3.849.774 2.813.081 0 124503.8 N = 5376 value between 8.115.687 6.494.586 8.459.649 n = 336 within 2.693.811 -8.037.821 116429.1 T = 16

overall 2.731.149 2.762.708 0 124263.4 N = 5376 withdrawal between 8.011.691 0 8.333.102 n = 336 within 2.644.329 -8.059.988 116203.4 T = 16

establishment overall 1.118.626 536.46 0 30354.82 N = 5376 between 1.461.731 .15625 1910.39 n = 336 within 5.162.193 -1.798.527 28556.29 T = 16

overall .5 .5000465 0 1 N = 5376 brand between 0 .5 .5 n = 336 within .5000465 0 1 T = 16

l_total value overall 4.822.264 1.195.486 0 117.321 N = 5376 between .7138035 154.829 6.703.176 n = 336 within .9597357 -1.070.555 1.115.312 T = 16

l_ overall 1.701.655 2.644.558 0 1.173.017 N = 5376 withdrawal between 2.123.419 0 6.253.754 n = 336 within 1.580.304 -4.552.099 1.079.978 T = 16

l_ establishment overall 380.999 1.664.863 0 1.032.074 N = 5376 between 1.288.231 .0782977 6.262.165 n = 336 within 1.056.816 -.8120259 1.244.535 T = 16

sdt overall .2671589 .4142575 0 1 N = 5353 between .3382581 0 .9991032 n = 336 within .2395489 -.6671553 1.204.659 T-bar = 15.9315

cdt overall .7328411 .4142575 0 1 N = 5353 between .3382581 .0008968 1 n = 336 within .2395489 -.2046589 1.667.155 T-bar = 15.9315

Variable Obs Mean Std. Dev. Min Max

total value 5376 3.849.774 2.813.081 0 124503.8 withdrawal 5376 2.731.149 2.762.708 0 124263.4 Establishment 5376 1.118.626 536.46 0 30354.82 Brand 5376 .5 .5000465 0 1 l_total value 5376 4.822.264 1.195.486 0 117.321

l_withdrawal 5376 1.701.655 2.644.558 0 1.173.017 l_establishment 5376 380.999 1.664.863 0 1.032.074 sdt 5353 .2671589 .4142575 0 1 cdt 5353 .7328411 .4142575 0 1 Source: personal collection.

Appendix 2: elaborated with the data provided by the company throughout this work

Brand Establishment Withdrawal Vtotal

Regional 43% 57% 100% Multinational 23% 77% 100% Increase 31% 222% 141%

Source: personal collection.

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