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Microfinancing impacts on socio-economic development: an empirical study of Grameen Bank in Bangladesh.

INTRODUCTION

Deprivation is the main problem for sustainable human development [15]. Since the begging of civilization it is destroying human basic rights and depriving them through involving of multiple dimensions from limited income, vulnerability, lack of essential assets and opportunities in the face of shocks too few possibilities to participate in collective decision making for every human is entitled [11]. The economist and the policy makers have invented multiple numbers of poverty alleviation strategies and theories as well as clear relevant the conceptual issues over the time. But still there is no concert and perfect solution in the area [27].

In such situation, the existing conceptual frameworks are more important to know the rationality and the strength of any study. The participatory approaches of financing were coming in the front while the failure of the past macro-economic development strategies in eradicating poverty in a sustainable manner. In the last three decades participatory approach hasbeen launched as one of the prime strategies in the overall movement to end the poverty [18]. Participatory approach realized that poor as well as the lower income group are facing major problems is access to credit [8]. Their lack of assets for collateral, lack of financial records and limited credit history has made almost impossible for them to obtain credit from the formal financial institutions. Due to lack of capital, the poor are tied to low productivity, usually self-employed economic activities. Thus, providing the poor with credit will generally help to solve the problem of the poor. In this regards, microfinance program is generally perceived as one of the practical and attractive means for providing accessibility of the poor to credit, and hence reducing poverty and achieving development objectives.

In Bangladesh still poverty is considered prime threats where about more than 50% (formal counts and more are from informal counts) of population is under poverty. It was burning and questionable issues since the beginning of microcredit to how about it contributions on poor in the birth place. Many studies have done to get answer of many folds of issues but findings are still confused with different corner. In such situation, the present study aims to assess Grameen Bank contribution on the socioeconomics development in Bangladesh.

Literature Review:

Amin [2] has conducted an important study named "Does Micro Credit reaches the Poor and Vulnerable? Evidence from Northern Bangladesh," a study of the micro credit clients of Grameen Bank, BRAC and ASA. They observed that the micro-credit program was more successful to reach to the poor, but less successful to reach to the vulnerable poor. Moreover, Ashraf [3] examined the NGO activities in Bangladesh and analyzed the extension of their coverage and credit operations, socioeconomic impact, sustainability and effectiveness. The following findings were obtained: i) NGO interventions had minor impact on secondary occupations of their beneficiaries. ii) NGO interventions had a positive impact on health care, family planning and sanitation. iii) NGOs were almost entirely dependent on foreign donations to meet both program and non-program expenses. On the other hand, Bebczuk [6] focused on his study that micro credit changes the level of income and livelihood of households. He used household survey data on poor households from a number of Latin American Countries as part of his study. He found that credit increased the labor income statistically and the economic effect was also significant. He also found that the poor household income was increased with access to credit compared to the poor without access to credit by 4.8 times in Bolivia at the 10 % level of significance, 12.5 in Guatemala at the 1 % level of significance and 4.5 times in Haiti at the 5 % level of significance. The impact of credit was very sensitive in terms of size of the loan.

Bruntrup [9] conduced an empirical study on "Micro finance Programs of two Large NGOs, viz., Proshika and ASA". They found positive results of its programs in terms of increased income, savings and school enrollment rate, reduction in infant mortality and improvement in gender relations. Das [10] had an article on "Nature and Extent of Utilization of Credit in Irrigated Rice Farms". They showed that while 79 percent of the total credit is met by the institution agencies, only 21 percent of the total loan comes from non-institutional agencies. However, Husain [20] in a World Bank study, they produced evidence of wide-ranging impacts of micro finance on the condition of the borrowers. They examined programs of BRAC, Grameen Bank and Bangladesh Rural Development Board (BRDB), a public sector organization. The findings revealed that per capita expenditure increased due to micro finance among the borrowers of all these programs. Khandker [23] made a study named "Savings, Informal Borrowing and Microfinance," He assessed the impact of microcredit on saving and found that microcredit increased voluntary saving and the saving was more pronounced in case of women than men. The author further reported that the borrowing from informal sources had been reduced due to micro-lending.

Latif [24] made an empirical study on "Microcredit and Savings of Rural Households in Bangladesh". He measured the effects of microcredit on the household saving of Bangladeshi borrowers and found that saving income ratio was significantly higher for the participants than the non-participants. Mair [26] conducted a study on "Entrepreneurship in and around Institutional Voids: A Case Study from Bangladesh". In this study, they focused that Bangladesh Rural Advancement Committee (BRAC) has done well in the credit market because of modification of group based Grameen Bank model. While Grameen Bank thinks that the most immediate need of the poor is credit to create and expand self-employment opportunities by using their own previous experience, the Bangladesh Rural Advancement Committee (RAC) believes that the poor skill development needs as well as other organizational inputs.

Pitt and Khandaker [26] "Household and Intra household Impact of the Grameen Bank and Similar Targeted Credit Programs in Bangladesh" assessed the impact of microcredit borrowers of BRAC, BRDB and Grameen Bank and observed the positive impact of the program on women's employment, total per capita weekly expenditure and women's non-land assets. They also observed that credit programs could change the villagers' attitude and other behavior. Yunus [35] made an important study on "Expanding Micro-Credit Outreach to Reach the Millennium Development Goal- Some Issues for Attention." He says in his study, the micro-credit summit of 1997 set the goal to reach 100 million poorest families with micro credit, preferably through the women in those families by 2005. At the recently held micro credit summit, he reviewed the progress towards achieving the goals during the last five years. This study is based on different institutional data collected from over two thousand organizations that are working to implement the Summit goal of 2005. He made a guess that by the end of 2002 to have reached at least 35 million poorest families with micro credit. If this turns out to be closed to the real this would be significant progress. This would mean that we have crossed over a quarter of the path by 2001 and over a third of the path by 2002, and most likel y we'll cross the half-way mark or 50 million families, by 2003. Once we cross the half -way mark, we'll be better equipped psychologically and institutionally to cover the remaining half of the long journey. If this works out, it will mean that we have a good chance to make it to 100 million, or reasonably close to it, by 2005. The role of micro credit in disaster situations and post conflict areas has also been well documented, enabling families in those areas to rebuild economic activities and livelihoods when these services are flexible, convenient and easily accessible. Studies have also shown that micro credit programs improve the coping mechanisms of the poor. This was demonstrated very clearly during the time of disaster i.e. flood in Bangladesh in 1998. A large number of impact studies have been made on Grameen Bank from a different perspective. They all came up with findings showing significant impact on its members across wide range of economic and social indicators, including increased income, improved nutrition, better food intake, better consumption on clothing, lower child mortality, lower birth rate, higher adoption of family-planning practices, better health care, better access to education for the children, empowerment of women, participation in social and political activities, etc. Information technology supported by micro credit can be a very powerful force getting half the world's poor out of poverty by 2015. Issues raised in this paper needs to be seriously considered to get the world ready for successfully completing the most exciting task mankind ever embarked on. Let us not fail in this endeavor.

Microcredit has semultaneouse impact on Socio- Economic Development & Sustainable Livelihood for betterment of borrower household standard of living. For better or exact understanding of its impact this study has an overlook on the existing literature. In the same we found that Wodon in 1997 has been compared the performance of targeting indicators to identify the poor? If the ROC curve of one indicator lies above that of another, the first indicator dominates the second for all social welfare functions based on the two types of errors involved in targeting. The method is applied to Bangladesh. Fifteen indicators are used, including location, land ownership, education, occupation, demographics, age, family structure, and housing. The analysis is applied at the national, urban, and rural levels with two poverty lines. Education dominates land ownership in urban areas. The ranking is reversed in most cases in rural areas [33]. Further more, Schuler et.al have done good work to uses ethnographic and structured survey data from a study in rural Bangladesh to explore the relationship between domestic violence against women and their economic and social dependence. It describes some of the common situations in which violence against women occurs in Bangladeshi society, analyzes its larger context, and identifies factors that appear to lessen its incidence in this particular socio-economic setting. The study findings suggest that group-based credit programs can reduce men's violence against women by making women's lives more public. The problem of men's violence against women is deeply rooted, however, and the authors argue that much more extensive interventions will be needed to significantly undermine it [31].

More over, Morduch in 2000 has been mentioned in his study's that microfinance have put forward an enticing "win-win" proposition: microfinance institutions that follow the principles of good banking will also be those that alleviate the most poverty. This vision forms the core of widely-circulated "best practices," but as a general proposition the vision is fully supported neither by logic nor by the available empirical evidence. Recognizing the limits to the win-win proposition is an important step toward reaching a more constructive dialogue between microfinance advocates that privilege financial development and those that privilege social impacts [28]. How ever, Sen has been analyzed a panel dataset on 379 rural households in Bangladesh interviewed in 1987-88 and 2000. Using a "livelihoods" framework it contrasts the fortunes of ascending households (which escape poverty) and descending households (which fall into poverty). These two dynamics are not mirror images of each other. Escapees overcome structural obstacles by pursuing multiple strategies (crop intensification, agricultural diversification, off-farm activity, livelihood migration) that permitted them to relatively rapidly accumulate a mix of assets. Descents into poverty were associated with lifecycle changes and crises such as flooding and ill-health. The findings confirm that Bangladesh made considerable progress in reducing poverty in the 1980s and 1990s [32].

On the other hand, Hermes, Lensink, & Mehrteab in have been investigated the impact of monitoring and social ties on moral hazard behaviour within group lending programs based on data from an extensive questionnaire held in Eritrea among participants of 102 groups. They separately analyze the impact of group leaders and other group members. We show that the monitoring and the social ties of group leaders and not the other group members reduce the moral hazard behaviour within groups [17. In the same way, Dowla has also done to examine how Grameen Bank in Bangladesh - created social capital that has been a boon to the explosive growth of Microfinance in Bangladesh and elsewhere. Using Putnam's definition, he show how Grameen Bank created social capital by forming horizontal and vertical networks, establishing new norms and fostering a new level of social trust to solve the collective action problems of poor people's access to capital. The fact that a Microfinance Institution (MFI) can create social capital has strong policy implications. Since social capital is a public good - non-excludable and non-rivalrous - the market will under provide such good. This paper shows that Microfinance corrects another type of market failure--under provision of a public good, in addition to correcting the failure of the credit market. The social capital building aspects of an MFI need to be taken into account in the whole debate about the need for subsidy [14].

Ahmed, Adams et al. in 2000 examines the impact of membership in BRAC's integrated Rural Development Programme (RDP) on gender equity and health-seeking behaviour. Differences in health care seeking are explored by comparing a sample of households who are BRAC members with a sample of BRAC-eligible non-members. Individuals from the BRAC member group report significantly less morbidity (15-day recall) than those from the non-member group, although no gender differences in the prevalence of self-reported morbidity are apparent in either group. Sick individuals from BRAC member households tend to seek care less frequently than non-members. When treatment is sought, BRAC members rely to a greater extent on home remedies, traditional care, and unqualified allopaths than non-member households. While reported treatment seeking from qualified allopaths is more prevalent in the BRAC group, non-members use the para-professional services of community health care workers almost twice as frequently. In both BRAC member and non-member groups, women suffering illness report seeking care significantly less often than men. The policy and programmatic implications of between group and gender differences in care seeking are discussed with reference to the literature [1]. Wydick, Karp Hayes et al. 2011 in measured the extent to which social networks determine sources of credit from a survey of 465 households in western Guatemala. they estimate correlated, contextual, and endogenous effects of networks at the neighborhood, church, and village levels, finding that church networks display endogenous effects in credit access. they calculate an elasticity of social imitation (ESI) indicating if the percentage of people accessing microfinance in a church network doubles, the probability of an individual household accessing microfinance increases by 14.1%, a magnitude similar to our estimated ESIs for televisions and cell phones within church and neighbor networks [34].

Hartarska & Nadolnyak have examined whether microfinance rating agencies were able to impose market discipline on microfinance institutions (MFIs) during the period 1998-2002. The results indicate that not all rating agencies had the same impact. Rating by some rating agencies helped MFIs raise funds, while rating by other agencies did not. The evidence also suggests that subsidizing rating did not help MFIs raise more funds [16]. Sen has been analyzed a panel dataset on 379 rural households in Bangladesh interviewed in 1987-88 and 2000. Using a "livelihoods" framework it contrasts the fortunes of ascending households (which escape poverty) and descending households (which fall into poverty). These two dynamics are not mirror images of each other. Escapees overcome structural obstacles by pursuing multiple strategies (crop intensification, agricultural diversification, off-farm activity, livelihood migration) that permitted them to relatively rapidly accumulate a mix of assets. Descents into poverty were associated with lifecycle changes and crises such as flooding and ill-health. The findings confirm that Bangladesh made considerable progress in reducing poverty in the 1980s and 1990s [32].

Methodology of The Study:

The main purpose of the study is to analyze the impacts of microfinancing of Grameen Bank (GB) on socioeconomic development in Bangladesh. The study used quantitative approach of methodology on primary survey data from the Dhaka and Khulna division in Bangladesh. The study used primary survey data which has been used The Anderson's random sampling technique for selecting of sample size of the respondents (Anderson 1996, 820). So, up to December 31, 2009, 6272466 clients from GB have been considered the population of the present study (www.cdfbd.org accessed on 10.01.2010).

There are 100 of sample have been collected from the selected area where 50 samples are from Dhaka division (district of ManikgonjNaraingonjGopalgonj) and 50 samples from Khulna Division (district of Kushtia, Jessore and Khulna) respectively. Towards its objectives the present study used descriptive statistical techniques and paired samples t- test to analyze the survey data.

The present study has discussed how useful the difference of means test for comparing the means of two different independent groups to determine whether there is a difference between them or not. Two samples are said to be pared when each data point of the first sample is matched and related to the unique data point of the second sample. Since samples are paired, they must be equal size. The paired t-test is just a single sample t- test performed on the difference scores. That is, through this test for each matched pare, a different score may be computed. The null hypothesis for this is that the difference scores are a random sample from a population in which the mean difference has some value which the study specify.

In the equation for the paired t-test, X is often replaced with D, which for the mean difference. The formula of paired sample t-test is:

t = [[bar.D].sub.[mu]D]/[S.sub.[bar.D]]=[[bar.D].sub.[mu]D]/[S.sub.D]/[square root of n]

Where,

[bar.D] = The sample mean of the difference scores

[mu]D = The mean difference in the population, given a true

[S.sub.D]= The sample standard deviation of the indifference scores

[S.sub.[bar.D]] = The standard error of the mean difference

N = The number of matched pairs; the number of individuals =2n

Findings of The Study:

Annual Income before and after Receiving Loan:

After taking the loan from GB the income level up to 40000 reduced to 19%, Tk.40001-Tk.70000 increased to 77%, Tk.70001- Tk.100000 increased to 3%, Tk.100001- Tk.130000 remain unchanged, and above 130000 increased to 1%. Therefore, the above picture shows that the credit operations of GB have made a favorable impact on the income level of clients.

The rising income increases the purchasing power of clients and assists in improving their standard of living. Moreover, with the rising income the clients may involve in diversification of business and expansion of the existing production facility. So, it is seen that capability of annual income is improved by the respondents after joining GB.

Medical Treatment before and after Taking Loan:

The above table shows that the percentage of the respondents of taking medical treatment from an MBBS doctor was increased from 3% to 90%, and taking treatment from local or village doctor was decreased from 97% to 10% after receiving a loan from GB. It is reflected that nature of treatment has been improved by the respondents after joining GB.

No. of School Going Children before and after Taking Loan:

The above table indicates that the percentage of the respondents of having school going children were increased from 80% to 83%, and having school going no children was decreased from 20% to 17% after receiving loan from GB. It is observed that capability of sending school of their children is enlarged by the respondents after joining GB.

Enhancement of Social Leadership before and after Taking Loan:

The above table represents that only 20% of the respondents are taking part in various social activities and playing role as a leader after receiving a loan from GB. It is seen that social leadership capacity is enhanced by the respondents after joining IBBL and GB.

Employment Generation before and after Taking Loan:

The above table 07 reveals that in GB 10% of the respondents have generated employment only 36 persons and the rest did not generate any new employment. The above picture indicates that GB is contributing in employment generation.

6.1.6 Expansion of the Size of Investment from Savings after Taking Loan

Expansion of the Size of Investment from Savings after Taking Loan:

From the above table it is seen that 99% respondents of GB have expanded their investment from savings after receiving loan. In this situation, it is obvious that investment capacity has been expanded by the respondents after joining GB.

Results of Paired Samples t- Test:

This section finds out the result of the tested hypotheses that are formulated in the light of the objectives of the study. These hypotheses are tested through the paired samples t-test.

The study found that there is a highly significant difference between the annual income, employment generation, health care leadership development and investment from savings of the respondents before taking a loan and after taking loan from the bank at 1% level of significance. Finally, it can be said that for pared samples t-test in the case of GB, it is revealed that the all the independent variables influences positive role insocioeconomic development except one (i.e. Education has no positive impact on socioeconomic development). It can be concluded here that Grameen Bank is playing more important role insocioeconomic development in Bangladesh.

Concluding Remarks:

The main purpose of the study is to analyze the impacts of microfinancing of Grameen Bank (GB) on socioeconomic development in Bangladesh. The overall findings of the study revealed that the Grameen credit has influenced on the borrowers socioeconomic status through of increasing of annual income, number of school going children, employment generation, number of medical treatments, enhancement of social leadership as well as expansion of investment from savings after taking a loan in Bangladesh. Moreover, the study found that 77% of Grameen Bank borrower's household annual income has increased after involved with credit. Moreover, the increase of the respondents of taking medical treatment from an MBBS doctor was increased from 3% to 90% and treatment from local or village doctor was decreased from 97% to 10% after receiving a loan from GB. It is reflected that nature of treatment has been improved by the respondents after joining GB. The study also found that only 3% of the number of school going children has increased after receiving a loan from GB. It is also observed that capability of sending school of their children is enlarged by the respondents after joining with GB. However, the GB credit has radically about only 20% improved Social involvement after access of credit which helped the poor borrowers to empower themselves to develop society as well as nation.

The study also reveals that only 10% of the respondents have generated employment after access of Grameen Bank credit. The above picture indicates that GB is contributing to employment generation. Moreover, it is seen that 99% respondents of GB have expanded their investment from savings after receiving the loan. In this situation, it is obvious that investment capacity has been expanded by the respondents after joining GB. Finally the study found that there is a highly significant difference between the annual income, employment generation, health care leadership development and investment from savings of the respondents before taking a loan and after taking loan from the bank at 1% level of significance. It can be concluded here that Grameen Bank is playing most important role on socio economic development in Bangladesh.

ARTICLE INFO

Article history:

Received 25 January 2014

Received in revised form

2 June April 2014

Accepted 6 June 2014

Available online 15 June 2014

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(1) Md. Shaheb Ali, (2) Md. FerdausurRahman, (3) Abul Bashar Bhuiyan, (4) Md. Abu Sina

(1) Phd Fellow at School of Graduate Research, Royal Melbourne Institute of Technology University, Melbourne, Victoria, Australia (2) Assistant Professor at Dept. Business Administration Bangladesh Islami University, Maniknagar, Dhaka-1203, Senior Lecturer at the School of Business Innovation and Technoprenuership, University Malaysia Perlis (UniMAP), Perlis, Malaysia. (3) Research Fellow at Institute for Environment and Development (LESTARI), UniversitiKebangsaan Malaysia (UKM), Bangi- 43600, Selangor, & Accounting Research Institutes (ARI), University Technology Mara (UiTM), (4) Sha-Alam, Malaysia. Professor at Dept. of Accounting and Information Systems Islamic University, Kushtia, Bangladesh.

Corresponding Author: Md. Shaheb Ali, Phd Fellow at School of Graduate Research, Royal Melbourne Institute of Technology University, Melbourne, Victoria, Australia. E-mail: mdsali80@gmail.com
Table 01: Distribution of Sample Size of GB (Clients)

                                    Where
n = N.(p 1 - p)/N [[B.sup.2]/4]     N = Number of known
  + P(1 - P)                          population = 62,72,466
                                    P = Proportion belonging to
                                      specified category = .5
                                      (Assumed); (1-p) = Proportion
                                      not belonging to specified
n = 6272466 x 0.5 (1 - 0.5)/          category = .5(Assumed);
  6272466 [[(0.1).sup.2]/4] +       B = Level of significance = 10%
  0.5 (1 - 0.5)                       (i.e., level of significance)
n = 99.998                          n = Sample size

Sources: Survey Data

Table 02: Distribution of Sample Size by Division and Districts

Division    Districts     GB     Total    percent

            Manikgonj     30     50       50
Dhaka       Naraingonj    10
            Gopalgonj     10
            Kushtia       30     50       50
Khulna      Jessore       10
            Khulna        10
Total                     100    100      100

Sources: Survey Data

Table 03: Distribution of Annual Income of the Grameen
bank borrowers before and after Taking Loan

Annual income                         GB
(in Taka)
                         Before                  After

                 Frequency    Percent    Frequency    Percent

Up to 40000          79        79.00         19        19.00
40001-70000          20        20.00         77        77.00
70001-100000         1          1.00         3          3.00
100001-130000        0          0.00         0          0.00
Above 130000         0          0.00         1          1.00
Total               100        100.00       100        100.00

Source: Field Survey

Table 04: Distribution of Medical Treatment of the Grameen
bank borrowers before and after Taking Loan

Treatment       GB

                Before                  After

                Frequency    Percent    Frequency    Percent

MBBS doctor         3          3.0          90         90.0
Local doctor        97         97.0         10         10.0
Total              100        100.0        100        100.0

Source: Field Survey

Table 05: Distribution of No. of School Going Children of
the Grameen bank borrowers before and after Taking Loan

Going to                         GB
school
                   Before                    After

            Frequency    Percent    Frequency    Percent

Yes             80         80.0         83         83.0
No              20         20.0         17         17.0
Total          100        100.0        100        100.0

Source: Field Survey

Table 06: Distribution of Enhancement of Social Leadership
of the Grameen Bank borrowers before and after Taking Loan

Social Leadership                         GB

                             Before                  After

                     Frequency    Percent    Frequency    Percent

Involvement              0           0           20          20
Not Involvement         100         100          80          80
Total                   100        100.0        100        100.0

Source: Field Survey

Table 07: Distribution of Employment Generation of the
Grameen bank borrowers before and after Taking Loan

Employment        GB
Generation
                  Before                  After

                  Frequency    Percent    Frequency    Percent

Employment            0           0        10 (36)        10
Not Employment       100         100          90          90
Total                100        100.0        100        100.0

Source: Field Survey

Table 08: Distribution of Expansion of the Size of
Investment from Savings before and after Taking Loan

             Opinion    Frequency    Percent

Expansion      YES          99         99.0
of the          NO          1          1.0
Size          Total        100        100.0

Source: Field Survey

Table 09: Distribution of the Results of Paired
Samples t-Test

                                             Paired Differences

Variables                             Mean         Std.        Std.
                                                Deviation      Error
                                                               Mean

Annual income after taking loan      -9900        -17630       -1763

No. of school going children       -1.00E-02       0.17      1.74E-02
after taking loan

Employment generation after            1          0.124        0.14
taking loan

Medical treatment after               0.47         0.5       5.02E-02
taking loan

Enhancement of social                 1.91        0.287      2.88E+00
leadership after taking loan

Expansion of investment from           1          0.301      3.02E+00
savings after taking loan

                                   95% Confidence              t
                                   Interval of
                                   Difference

Variables                            Lower        Upper

Annual income after taking loan     -13398.2    -6401.82    -5.615

No. of school going children       -4.45E-02    2.45E-02    -0.575
after taking loan

Employment generation after          0.971        1.028      70.35
taking loan

Medical treatment after               0.37        0.57       9.37
taking loan

Enhancement of social                1.852        1.967      66.4
leadership after taking loan

Expansion of investment from        4.02E+00      0.159      3.31
savings after taking loan

                                    df       Sig.
                                          (2-tailed)

Variables

Annual income after taking loan    -99      0.00 *

No. of school going children        99       0.56
after taking loan

Employment generation after         99      0.00 *
taking loan

Medical treatment after             99      0.00 *
taking loan

Enhancement of social               99      0.00 *
leadership after taking loan

Expansion of investment from        9       0.00 *
savings after taking loan

Source: Field Survey.

 * indicates significant difference at 1% level
of significance
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Author:Ali, Shaheb; FerdausurRahman, Md.; Bhuiyan, Abul Bashar; Sina, Abu
Publication:Advances in Environmental Biology
Article Type:Report
Geographic Code:9BANG
Date:Jun 20, 2014
Words:5795
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