a Study on Acceptability of Sbi Point of Sale Machine in Hospitals and Medical Stores in Mehsana City Essay

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a Study on Acceptability of Sbi Point of Sale Machine in Hospitals and Medical Stores in Mehsana City

1.1 Introduction of Banking

A bank is a financial institution that provides banking and other financial services to their customers. A bank is generally understood as an institution which provides fundamental banking services such as accepting deposits and providing loans.

There are also nonbanking institutions that provide certain banking services without meeting the legal definition of a bank. Banks are a subset of the financial services industry.
A banking system also referred as a system provided by the bank which offers cash management services for customers, reporting the transactions of their accounts and portfolios, throughout the day.

1.2 Need of the Banks

Before the establishment of banks, the financial activities were handled by money lenders and individuals. At that time the interest rates were very high. Again there were no security of public savings and no uniformity regarding loans. So as to overcome such problems the organized banking sector was established, which was fully regulated by the government. The organized banking sector works within the financial system to provide loans, accept deposits and provide other services to their customers.

The following functions of the bank explain the need of the bank and its importance:
• To provide the security to the savings of customers.
• To control the supply of money and credit
• To encourage public confidence in the working of the financial system, increase savings speedily and efficiently.
• To avoid focus of financial powers in the hands of a few individuals and institutions.
• To set equal norms and conditions (i.e. rate of interest, period of lending etc) to all types of customers

1.3 Function of bank

Source: (Akranj, 2011)

Chart No.1.1

1) Accepting Deposits
a) Saving Deposits
b) Fixed Deposits
c) Current Deposits
d) Recurring Deposits
2) Granting Advances
a) Over draft
b) Cash Credits
c) Loans
d) Discounting of Bill of Exchange
3) Agency Functions
a) Transfer of Funds
b) Collection of Cheques
c) Periodic Payments
d) Portfolio Management
e) Periodic Collection
f) Other Agency Functions

4) Utility Functions
a) Issue of Drafts, Letters of Credits, etc.
b) Locker Facility
c) Underwriting of Shares
d) Dealing in Foreign Exchange
e) Project Reports
f) Social Welfare Programmes
g) Other Utility Functions
1.4 Innovations in banking sector

Trends such as increasingly demanding customers, banking realization, and the evolution and revolution of retail banking have rendered current bank service models unsustainable. To position for success in the future, banks require new and innovative business models.

Over the years, the Reserve Bank has laid special emphasis on technology infusion in the day o day operations of banks. Technology, apart from increasing the efficiency of banking services, is expected to boost the ongoing process of financial inclusion emphasized by the Reserve Bank.

Computerization has changed the face of the Indian banking sector. Although private banks and foreign banks have an edge in this regard, Public Sector Banks have been upgrading their operations. In recent years, increase in the number of ATMs in various locations as well as use of mobile and online banking technology further facilitated banking outreach in remote areas. Changing consumer preferences for multichannel banking are driving IT investments into online and mobile channels.

Sustained increase in total number of ATMs indicating move towards door-step banking. Total numbers of ATMs installed in India by various banks as on end June 2012 is 99,218. Mobile banking is a method of using one’s mobile phone to conduct banking transactions. Online Banking is a term used for performing multiple transactions, payments etc. over the Internet.

Mobile banking is expected to become the second largest channel for banking after ATMs. Mobile banking used to offer banking services will drive the growth of banking industry exponentially in the future by increasing productivity and acquiring new customers. One major innovation in banking industry was Payment cards; increase the methods of payment processing available to the general public and business clients. These products include debit cards, prepaid cards, smart cards and credit cards. They make it easier for consumers to conveniently make transactions and smooth their consumption over time. Payment cards are considered as the main drivers of the shift from paper-based towards electronic-based payment instruments, which is commonly viewed as a significant socio-economic and welfare improvement. E-Banking

Enables people to carry out most of their banking transactions using a safe website which is operated by the respected bank. Data Management

Both to increase efficiency and ensure regulatory compliance, banks need better methods of gathering and reporting data. Data integration will help banks obtain a more accurate view of their customers. Messaging: New Tool of Communication

Communication through message centers, dedicated web portals designed for secure communication between a bank and its customers. Tablet Banking

Tablet banking is still a young channel, but it is rife with potential. As with initial mobile forays, it may take banks some period of trial and error to determine how to build the best banking experience for the tablet environment. (September-December 2012) Electronic Funds Transfer (EFT) system, with the BANKNET communications network is another new technology based service provided by the banking industry. Another major innovation in banking services was the use of Point of Sale Machine. Point of Sale or Swipe Machine as it is popularly known is a technological instrument provided to a Merchant Establishment (ME) to carry out the sale of goods or services to customers in a cashless environment.

1.5 Use of Technology in Banking Sector

Today technology plays a very important role in driving banking business. With the advent of the process of liberalization in the early ’nineties, the demands on banks’ resources and capabilities increased as banks had to match the challenges of being financial service providers in a globalised, competitive environment. This posed a dual challenge for the banking industry.

The first challenge was to manage the growing needs of their existing customer segments and business locations for better and more efficient services, and the second was, how to expand the reach of their services and business beyond the traditional services and locations, which had large socio-economic implications because large parts of the population did not have access to even basic banking services.

At this juncture, banks in India were looking at huge potential in business growth as well as several constraints, such as inadequacy of infrastructure and human resources, geographical, topographical and distance limitations, communication inefficiencies, cost implications and delivery, as well as the processing capability to manage more business information and larger accounts.

Increased use of information technology emerged as the key to meeting these challenges. Several measures were taken at the level of the Government, the Reserve Bank and industry, which provided an impetus to adoption of technology in the banking sector.

Core Banking Solutions (CBS) implementation has made customer account maintenance seamless and enhanced data storage and retrieval capabilities tremendously. It has also enhanced the banks’ capacity to develop and market new products, as technology has increased information availability and the capacity for analysis and communication manifold.

Economic theory supported by empirical evidence suggests that, in general, increases in technology investment will raise productivity, lower costs, and allow firms to operate more efficiently. Information technologies and innovations reduce the costs of financial transactions, improve the allocation of financial resources and increase the competitiveness and efficiency of financial institutions.

Globally, the effect of IT on the banking industry has been positive. In general, studies have concluded two positive effects regarding the relation between IT and banks’ performance. First, IT can reduce banks’ operational costs (the cost advantage). Second, IT can facilitate transactions among customers within the same network (the network effect). Technology is of key importance in improving efficiencies, enhancing the customer experience, and achieving regulatory compliance. Information technology has facilitated transformation of transactions and analytical processes of the banking business. IT has helped in increasing the speed and efficiency of banking operations by facilitating introduction of innovative products and new delivery channels.

Various new products and services have emerged in payment and settlement systems including Negotiated Dealing System (NDS) for Government Securities, the Real Time Gross Settlement (RTGS), National Electronic Funds Transfer (NEFT) and the Centralized Funds Management System (CFMS), apart from the Structured Financial Messaging System (SFMS). As announced in the Annual Monetary Policy Statement 2012-13, adoption of well structured IT governance models will assist banks in enabling better alignment between IT and business, create efficiencies, enhance conformity to internationally accepted best practices and improve overall IT performance, as also enable better control and security. In order to achieve these objectives, banks need to move towards adoption of well-structured IT governance models. Further, banks are increasingly relying on various IT based channels to operate their businesses and market interactions. Ability of banks to take advantage of new opportunities is largely contingent upon their capability to provide accessible and secure IT service channels.

1.6 Global Banking Industry Overview

The United States banking industry is one of the most heavily regulated in the world, with multiple specialized and focused regulators. The United States has the most banks in the world in terms of institutions of 7,085 at the end of 2008 and possibly branches of 82,000. As of Nov 2009, China’s top 4 banks have in excess of 67,000 branches with an additional 140 smaller banks with an undetermined number of branches. Japan had 129 banks and 12,000 branches. Germany, France, and Italy each had more than 30,000 branches- more than double the 15,000 branches in the UK. 1.7 Globalization in the Banking Industry

In modern time there have been huge reductions to the barriers of global competition in the banking industry. Increases in telecommunications and other financial technologies have allowed banks to extend their reach all over the world. The growth in cross-border activities has also increased the demand for banks that can provide various services across borders to different nationalities. During the 20th century, developments in telecommunications and computing caused major changes to banks’ operations and let banks dramatically increase in size and geographic spread. The financial crisis of 2007-2008 caused many bank failures, including some of the world’s largest banks. The Late -2000s financial crisis caused significant stress on banks around the world. The failure of a large number of major banks resulted in government bail-outs.

The collapse and fire sale of Bear Stearns to JP Morgan Chase in March 2008 and the collapse of Lehman Brothers in September that same year led to a credit crunch and global banking crises. The ongoing crisis in the euro zone region, coupled with new regulations aimed at enhancing liquidity and risk management, is expected to impact the cost and profitability of banks globally in the near term. The financial crisis of 2008-09 severely impacted the asset and profitability growth of the global banking sector, which started to recover during 2009 and 2010. The growth rate of assets for the top 1000 banks grew by 6.4% in 2010 reaching well above the pre-crisis level. However, during 2010-11 the growth moderated to 5.5% due to the ongoing euro zone crisis, but was compensated by the growth of assets in the Asia-Pacific and Latin American regions. Profits before tax (PBT) of the banking sector also witnessed strong growth during 2009-10. The PBT of the top 1,000 banks increased by $566 billion between 2008 and 2010 but declined by 2.4% during 2010-11 primarily due to the ongoing sovereign debt crisis in euro zone countries, leading to a decline in profits of the European banks. Banks in emerging markets (China, India, and Brazil) have grown at extraordinary rates in recent years due to financial inclusion of the “bankable” income segment and more resilient economies.

Trend 1: Increasing adoption of social media

With growing demand for mobile and social media, banks have an opportunity to improve their interaction with customers. Social media can help banks enhance their brand image and value, reduce service and marketing costs, grow their revenue, and support the design and development of innovative products.

Trend 2: Convergence of mobile and online banking technology Changing consumer preferences for multichannel banking are driving IT investments into online and mobile channels. The rapid rise in internet services and the increasing propensity of young consumers to use internet and mobile applications for day-to-day transactions has challenged banks to develop the next generation of online and mobile banking platforms.

Trend 3: Big data and customer data analysis
Adoption of big data is expected to affect how banks collect, organize, manage, and analyze their data. Banks today are realizing the huge potential big data provides in delivering customer value, improving profitability, and managing risks better.

Banks and financial services firms have been handling and interpreting internal and market data for decades but big data provides a game changing opportunity for banks. The large piles of unstructured data that banks have today provide significant potential in analyzing customer spending patterns, supporting revenue growth and reducing risks.

1.8 BANKING SYSTEM IN INDIA

1.8.1 Introduction
The banking system in India should not only be hassle free but it should be able to meet the new challenges posed by the technology and any other external and internal factors. For the past three decades, India’s banking system has several outstanding achievements to its credit.

The Banks are the main participants of the financial system in India. The Banking sector offers several facilities and opportunities to their customers. All the banks safeguards the money and valuables and provide loans, credit, and payment services, such as checking accounts, money orders, and cashier’s cheques. The banks also offer investment and insurance products.

1.8.2 Historical Background of Banking in India
Although banking is said to have originated in the affluent cities of Italy in the 14th century, it was introduced in India in the late 18th century.
Bank of Hindustan was set up in 1870; it was the earliest Indian Bank. Later, three presidency banks under Presidency Bank’s act 1876 i.e. Bank of Calcutta, Bank of Bombay and Bank of Madras were set up, which laid foundation for modern banking in India.

In 1921, all presidency banks were amalgamated to form the Imperial Bank of India. Imperial bank carried out limited number of central banking functions prior to establishment of RBI. It engaged in all types of commercial banking business except dealing in foreign exchange.

Reserve Bank of India Act was passed in 1934 & Reserve Bank of India (RBI) was constituted as an apex body without major government ownership.

Banking Regulations Act was passed in 1949. This regulation brought RBI under government control. Under the act, RBI got wide ranging powers for supervision & control of banks. The Act also vested licensing powers & the authority to conduct inspections in RBI.

In 1955, RBI acquired control of the Imperial Bank of India, which was renamed as State Bank of India. In 1959, SBI took over control of eight private banks floated in the erstwhile princely states, making them as its 100% subsidiaries.

It was 1960, when RBI was empowered to force compulsory merger of weak banks with the strong ones. It significantly reduced the total number of banks from 566 in 1951 to 85 in 1969.

1.8.3 Nationalisation
In July 1969, government nationalized 14 banks having deposits of Rs. 50 crores & above. In 1980, government acquired 6 more banks with deposits of more than Rs.200 crores. Nationalisation of banks was to make them play the role of catalytic agents for economic growth.

1.8.4 Liberalisation
The Narasimha Committee report suggested wide ranging reforms for the banking sector in 1992 to introduce internationally accepted banking practices. The amendment of Banking Regulation Act in 1993 saw the entry of new private sector banks (Joshi, 2012).During Liberalisation, relaxation in the norms for Foreign Direct Investment was take place.

1.8.5 Structure of Indian Banking Industry
Indian banking industry has been divided into two parts, organized and unorganized sectors. The organized sector consists of Reserve Bank of India, Commercial Banks and Co-operative Banks, and Specialized Financial Institutions (IDBI, ICICI, IFC etc). The unorganized sector, which is not homogeneous, is largely made up of money lenders and indigenous bankers.

Banking Industry in India functions under the sunshade of Reserve Bank of India – the regulatory, central bank. Banking Industry mainly consists of:
Banks in India can be classified into:
1) Commercial Banks
i) Public Sector Banks
ii) Private Sector Banks
iii) Foreign Banks
iv) Regional Rural Banks
2) Cooperative Banks
i) Urban Cooperative Banks
ii) State Cooperative Banks

Chart No.1.2

1.8.6 Regulatory Authority

Currently in most jurisdictions commercial banks are regulated by government entities and require a special bank license to operate.
Reserve Bank of India (RBI)
The central bank of the country is the Reserve Bank of India (RBI). It was established in April 1935, under the Reserve Bank of India Act, 1934.The
Bank was constituted to meet the following requirements: * Regulate the issue of currency notes

* Maintain reserves with a view to securing monetary stability * Operate the credit and currency system of the country to its advantage

Indian Banks’ Association (IBA)
The Indian Banks’ Association (IBA) was formed on September 26, 1946, with 22 members. Today, IBA has more than 156 members, such as public sector banks, private sector banks, foreign banks having offices in India, urban co-operative banks, developmental financial institutions, federations, merchant banks, mutual funds, housing finance corporations, etc.

The IBA has the following functions:
* Promote sound and progressive banking principles and practices. * Render assistance and to provide common services to members. * Organize co-ordination and co-operation on procedural, legal, technical, administrative, and professional matters. * Collect, classify, and circulate statistical and other information.

NABARD
NABARD is an apex development bank with an authorization for facilitating credit flow for promotion and development of agriculture, small-scale industries, cottage and village industries, handicrafts and other rural crafts. It also has the mandate to support all other allied economic activities in rural areas, promote integrated and sustainable rural development and secure prosperity of rural areas

1.8.7 Market shares of leading players (based on total credit)

Table No 1.1

Banks | Market Share|
State Bank of India| 18%|
Punjab National Bank| 6%|
Bank of Baroda| 5%|
ICICI Bank| 5%|
Bank of India| 5%|
Canara Bank| 5%|
HDFC Bank| 4%|
IDBI Bank| 4%|
Axis Bank| 3%|
Central Bank of India| 3%|
Others| 42%|
Source: ICRA (White)

1.8.8 Indian Banking Sector: Trend Analysis
The Indian banking sector has recorded an impressive improvement in productivity over the last 15 years; many of the productivity/ efficiency indicators have moved closer to the global levels. There has been a particularly discernible improvement in banks’ operating efficiency in recent years owing to technology up-gradation and staff restructuring. However, to sustain high and inclusive growth, there is a need to raise the level of domestic savings.

TREND-1. The financial crisis has caused banks to re-assess their business fundamentals like profitability and client relationship management to improve client retention and cross selling capabilities.

TREND- 2. Banks are renewing their focus on the fundamental assets of customer, staff and capital rather than product innovation for long-term growth to become well managed.

TREND-3. Banks are focusing on staff efficiency to make them more aligned with the bank’s risk and profit strategy by enhancing their IT solutions.

TREND-4. Banks are moving from a product-centric approach to a client-centric approach with a 360-degree understanding of their clients to better manage and maintain client relationships.

TREND-5. Customer Relationship Management in which Relation Manager, mostly for private banking or business banking, often visiting customers at their homes or businesses.

TREND-6. Green Banking: Many banks are promoting online banking services, which involve less paperwork, less number of customers’ visiting branches and lower costs for banks arising from paper overload and bulk mailing fees.

Current period
The banking system has witnessed a huge growth and the competition amongst various banks has increased these days. The boom in e-commerce industry, globalization, and increased popularity of internet has made it vital for the banks keep up with the latest technology trends.

With the entry of the private and global banks in the market, the competition amongst the banks has increased in the country. They provide a wide variety of services other than borrowing and lending money to people. By 2010, banking in India was generally fairly mature in terms of supply, product range and reach-even though reach in rural India still remains a challenge for the private sector and foreign banks. With the growth in the Indian economy expected to be strong for quite some time-especially in its services sector-the demand for banking services, especially retail banking, mortgages and investment services are expected to be strong

The RBI, deviating from its traditional policy of granting licenses to only a few private institutions, is now issuing new bank licenses to all entities that satisfy the eligibility criteria. This move is expected to encourage healthy competition and promote financial inclusion in the banking industry.

The RBI is encouraging foreign players entering the Indian banking industry to conduct business through wholly owned subsidiaries. Further, it is promoting existing important foreign players to incorporate themselves as wholly owned subsidiaries of foreign parent companies. This move is expected to benefit foreign players by allowing them to expand their consumer base to semi urban areas.

Expansion into rural markets:
Expanding operations to rural markets has been a concern for private and foreign banks. Some larger players have managed to establish their presence in rural markets either through mergers and acquisitions, or acquiring associates. For instance, ICICI Bank merged with Bank of Rajasthan to expand its consumer base in rural markets. (Indian Banking Industry, April 2012) 1.8.9 Challenges Before Indian Banking Industry

There are many challenges before Indian Banks such as improving capital adequacy requirement, managing non-performing assets, enhancing branch sales & services, improving organization design; using innovative technology through new channels and working on lean operations. Apart from this, frequent changes in policy rates to maintain economic stability, various regulatory requirements, etc. are additional key concerns. Some of the key trends expected to emerge in the near future are as economic slowdown likely to impact the demand for credit, high interest rates and domestic consumption impacted the growth of the Indian economy which slowed down from 8.4% in FY11 to 6.5% during FY12. 1.8.10 Future Outlook for Banking Industry

High population base of India, mobile banking – offering banking operations through mobile phones, financial inclusion, rising disposable income, etc. will drive the growth Indian banking industry in the long-term. The Indian economy will require additional banks and expansion of existing banks to meet its credit needs. According to an IBA-FICCI-BCG report titled ‘Being five star in productivity – road map for excellence in Indian banking’, India’s gross domestic product (GDP) growth will make the Indian banking industry the third largest in the world by 2025.

According to the report, the domestic banking industry is set for an exponential growth in coming years with its assets size poised to touch USD 28,500 billion by the turn of the 2025 from the current asset size of USD 1,350 billion (2010)”. Country’s financial services sector, including banking, has got tremendous growth potential for the next few years. “The banking sector should grow at least 2.5 to 3 times the GDP growth rate, and the improvement in the GDP growth rate will drive growth in the banking sector. India’s growing global linkages, whether in terms of international companies investing in India or Indian companies going overseas, will provide a growth opportunity for Indian banks. (ICICI Bank MD and CEO Chanda Kochhar, 2013) 1.9 Porter’s 5 Forces Model for the Indian Banking Industry

Chart No 1.3

Power of Buyers: Customer’s bargaining power is high because bank provides homogeneous kind of services and customer can get all information very easily. So, the switching cost is Low for customer.

Power of Suppliers: In the banking industry, suppliers bargaining power is Low because banks have to meet many regulatory criteria, made by RBI.

Competitive Rivalry: Competition in banking industry is Very High because large number of Public, Private, Foreign, and Co-operative banks.

Availability of Substitute: There is a High Threat from substitute such as Mutual funds, T-bills, Government securities, NBFC’s.

Threat of New Entrants: Banking regulations requires the approval from the regulator RBI before setting up a new bank. So, the threat of new entrants is Low in the banking sector.
1.10 Profile of Gujarat State

: Source: (2013)

The Banking Profile of the State (exhibited in Table No 1.2) Bank| No. of Banks| No. of Branches|
Public Sector Banks| 20| 344|
Private Sector Banks| 4| 483|
Regional Rural Banks | 2| 289|
Cooperative Banks| 8| 241|
Total| 34| 1357|

Table No 1.3
Branch Area | No. of Branches|
Rural| 736|
Semi Urban| 277|
Urban| 344|
Total| 1357|
Table No 1.4
Banking Parameters| Amount in Rs. Crores|
Total Deposits| 48,394.49|
Total Advances| 17,280.51|
Advances to Priority Sector| 10,825.35|
Percentage of Priority Sector advances to total advances| 62.64%|

1.11 Point Of Sale (Pos) Machine

1.11.1 Definition|
|
POS or Swipe Machine as it is popularly known is a technological instrument provided to a Merchant Establishment (ME) to carry out the sale of goods or services to customers in a cashless environment. All the customer has to do is swipe his/her Debit, Credit or Prepaid Card.1.11.2 Types of Point of Sales (POS) Machines1. PSTN: Available over Landline phone. The telephone charges for swiping the card are local land line charges in case of PSTN line. 2. GPRS: Working with Sim card. Sim card will be provided by the bank. Minimum charges are applied for monthly rental and one time security deposit. I) Desktop GPRS: Requires electric connection. ii) Portable GPRS: Require battery backup. |

1.11.3 Advantages Of Installing Pos Machine * Zero cost for machine. * Free installation & Maintanance. * No annual maintenance charge. * Free of cost training will be provided to merchant. * No requirement of minimum business volume. * No hidden charges. * Prompt service to customer.Advantage To Merchant * Cash handling is avoided. * Avoid robberies and thefts. * Additional revenue stream from value added services. * Customer have tendency to higher purchase while using the card than cash thus more sales and higher profits. * For Desktop & Portable GPRS,SBI provide new simcard without any cost. Advantage To Customers * Not need to carry cash, which is risky. * Maintains higher balances in the account resulting in higher interest on deposits. * Save time in visiting bank branch/ATM to withdraw money. * Increase customer loyalty.| |

|
Advantage To Bank |
Merchant acquisition generates cash deposits in the form of merchant accounts, it brings in fee income on every card transaction and it also increases demand for cards among customers. 1.11.4 Challenges for POS * The growth of ATMs is found to negatively affect POS adoption. * Skimming: One of fastest growing debit card fraud activities is through an illegal process called skimming. This is the act of stealing debit or credit card data by reading information on the magnetic stripe of the card. Criminals attach portable electronic devices to ATM or Point of Sale (POS) machines, just over the slot where the card slides through. When a card holder slides their card through the ATM/POS they are actually sliding it through the skimming device.1.12 Global Trend in POS

Growth in IT spending by the banking sector is predicted to reach $184.7 billion by 2014, a healthy growth of around 4.0% during 2010-2014. The majority of this growth is expected to come from Asia-Pacific banks, where spending by banks is expected to grow by 6.0% in 2012 to reach $59.4 billion. IT spending by banks in North America and Europe is expected to remain subdued primarily due to the uncertain economic and sociopolitical climate.In the long run, there is still enormous potential demand for POS machines to be developed in China.Automated Teller Machine (ATM), Point of Sale (POS), Mobile Banking (MB) and Internet Banking (IB) are new term in Bangladesh. Most of the people in Bangladesh live in rural areas and the services of banks are being increased through ATM, POS, IB and MB day by day. Almost all banks are trying to provide financial service to maximum customers through these delivery channels and some of them are becoming popular.

Due to the cash-less policy introduced by the Central Bank of Nigeria (CBN), over 150,000 Point of Sale (PoS) terminals have so far being deployed in Lagos State. As a result of the cashless policy, cheques, PoS and Automated Teller Machines (ATM) usage have continued to record huge volume and value. As a result of the significant success recorded in Lagos, the apex bank recently said it planned to extend the Cash-less policy to other states of the Nigeria.New habits in shopping increased the use of plastic cards. Now there are 313140 POS installed in Turkey.POS Market Facts * 28 billion transactions are made using dial-up POS systems in North America. * In the United States, there are 10 million payment terminals; over 60% currently dial-up terminals. Point of sale systems involves hardware and software used by retailers to accept payment transactions from their customers. The global point of sale (POS) software industry is expected to reach $3.2 billion in 2014, according to TechNavio. The market is driven by retailers upgrading their point of sale systems. The world POS hardware industry is expected to reach almost $31.5 billion in 2014, reports TechNavio. .1.13 Indian Trend in POS Machine

| Private sector Axis Bank is the market leader in the merchant acquisition business with nearly 1, 87,000 PoS terminals deployed and HDFC Bank, which has 1, 25,000 POS machines, plans to add another two lakhs terminals. State Bank of India currently 18,500 PoS terminals deployed and plan to deploy 50000 PoS terminals in near future. The usage of credit cards has exploded with the growth of retail chains such as Big Bazaar which accounts for a large chunk of credit card transaction in India. Changing Trend of the Payment Systems from Cash to Cashless. In India, cash continues to be the pre-dominant mode of payment. The policy initiatives and the regulatory stance of the Reserve Bank has continued to focus on increasing the acceptance and penetration of safe, secure and efficient non-cash payment modes comprising cheques, credit/debit cards over the years. Payment Cards in India is a guide to one of Asia’s key growth payment card markets.

Payment card transactions in India for the year 2010 totaled €191bn.Forecasts put the growth of the total value through payment cards at a compound annual growth rate of 25.7% over 2011–15. ICICI Bank and HDFC Bank are the two largest players and jointly hold 55% of the credit card market. The three biggest privately owned banks hold 21.1% of the market share, whereas foreign-owned banks have the smallest share of the debit card market. Prepaid cards are a new concept in India and as such do not have a very large share in the payment card market. In India credit cards account for the largest share of online transactions, in line with global trends. The value of online payments made with debit cards in India is below the global average.

ATM transactions are far more common than POS transactions. Frequency of use at ATMs is much higher than at the POS, and is increasing. The value of ATM transactions was more than nine times the value of transactions at the POS in 2010.

The average value of transactions in India is higher at ATMs than at the POS. India has the second lowest average value of pay now transactions at the POS.

Asian countries exhibit a huge disparity in the average transaction value of pay later cards at the POS. Citibank has the highest value of transactions in the charge card domain.

2.1 Vision, Mission and Values

Vision
My SBI.
My Customer First.
My SBI: First in customer satisfaction.

Mission
* We will be prompt, polite and proactive with our customers. * We will speak the language of young India.
* We will create products and services that help our customers achieve their goals. * We will go beyond the call of duty to make our customers feel valued. * We will be of service even in the remotest part of our country. * We will offer excellence in services to those abroad as much as we do to those in India. * We will imbibe state of art technology to drive excellence. Values

* We will always be honest, transparent and ethical.
* We will respect our customers and fellow associates.
* We will be knowledge driven. We will learn and we will share our learning. * We will never take the easy way out.
* We will do everything, we can, to contribute to the community, we work in. We will nurture pride in India.

2.2 Logo and slogan

The logo of the State Bank of India is a blue circle with a small cut in the bottom that depicts perfection and the small man the common man – being the center of the bank’s business.

Slogans: “PURE BANKING, NOTHING ELSE”, “WITH YOU – ALL THE WAY”, “A BANK OF THE COMMON MAN”, “THE BANKER TO EVERY INDIAN”, “THE NATION BANKS ON US”.

2.3 History of SBI

The largest bank, and the oldest still in existence, is the State Bank of India, which originated as the Bank of Calcutta in June 1806, which almost immediately became the Bank of Bengal. This was one of the three presidency banks, the other two being the Bank of Bombay and the Bank of Madras, all three of which were established under charters from the British East India Company. The three banks merged in 1921 to form the Imperial Bank of India, which, upon India’s independence, became the State Bank of India in 1955. 2.4 Profile of SBI

State Bank of India (SBI) is a multinational banking and financial services company based in India. It is a government-owned corporation with its headquarters in Mumbai, Maharashtra. As of December 2012, it had assets of US$501 billion and 15,003 branches, including 157 foreign offices, making it the largest banking and financial services company in India by assets. SBI provides a range of banking products through its network of branches in India and overseas, including products aimed at non-resident Indians (NRIs). SBI has 14 regional hubs and 57 Zonal Offices that are located at important cities throughout the country. SBI is a regional banking behemoth and has 20% market share in deposits and loans among Indian commercial banks. SBI was ranked 285th in the Fortune Global 500 rankings of the world’s biggest corporations for the year 2012. The State Bank of India was named the 29th most reputed company in the world according to Forbes 2009 rankings and was the only bank featured in the “top 10 brands of India” list in an annual survey conducted by Brand Finance and The Economic Times in 2010. Table No 2.1

Particulars| Amt US $.(in billion-2012)|
Revenue| 36.950|
Profit| 3.202|
Total Assets| 359.237|
Total Equity| 20.854|
Source: (1)

SBI ATM services
SBI has 27,000+ and SBI group (including associate banks) has about 45,000 ATMs. SBI has become the first bank to install an ATM at Drass in the Jammu & Kashmir Kargil region. Branches SBI is India’s largest bank with a network of over 13,000 branches and 5 associate banks located even in the remotest parts of India. Foreign Offices

As of 28 June 2013, the bank had 180 overseas offices spread over 34 countries. It has branches of the parent in Moscow, Colombo, Dhaka, Frankfurt, Hong Kong, Tehran, Johannesburg, London, Los Angeles, and Male in the Maldives, Muscat, Dubai, New York, Osaka, Sydney, and Tokyo. It has offshore banking units in the Bahamas, Bahrain, and Singapore, and representative offices in Bhutan and Cape Town. It also has an ADB in Boston, USA.

2.5 The State Bank of India Group

Associate banks
Main Branch of SBI in Mumbai.SBI has five associate banks; all use the State Bank of India logo, which is a blue circle, and all use the “State Bank of” name, followed by the regional headquarters’ name: 1) State Bank of Bikaner & Jaipur

2) State Bank of Hyderabad
3) State Bank of Mysore
4) State Bank of Patiala
5) State Bank of Travancore

Non-banking subsidiaries
Apart from its five associate banks, SBI also has the following non-banking subsidiaries: 1) SBI Capital Markets Ltd
2) SBI Funds Management Pvt Ltd
3) SBI Factors & Commercial Services Pvt Ltd
4) SBI Cards & Payments Services Pvt. Ltd. (SBICPSL)
5) SBI DFHI Ltd
6) SBI Life Insurance Company Limited
7) SBI General Insurance
2.6 Products & Services

1) Personal Banking
SBI offers a wide range of services in the Personal Banking Segment which are indexed in Table No 2.2. SBI Term Deposits| SBI Loan For Pensioners|
SBI Recurring Deposits| Loan Against Mortgage Of Property| SBI Housing Loan| Loan Against Shares & Debentures|
SBI Car Loan| Rent Plus Scheme|
SBI Educational Loan| Medi-Plus Scheme|
SBI Personal Loan| Rates Of Interest|

2) Agriculture / Rural
3) NRI Services
4) International Banking
5) Corporate Banking
6) Working Capital Financing
7) Term Loans
8) Deferred Payment Guarantees
9) Corporate Loans
10) Export Credit

SERVICES
1) DOMESTIC TREASURY

2) BROKING SERVICES

3) REVISED SERVICE CHARGES

4) ATM SERVICES

5) INTERNET BANKING

6) STATE BANK MOBICASH

7) E-PAY

8) E-RAIL

9) RBIEFT

10) SAFE DEPOSIT LOCKER

11) MICR CODES

12) FOREIGN INWARD REMITTANCES

Value Added Services
* SBI e-File (E-filing of IT Returns)
* Online Shopping
* SSC & UPSC Online Fee Collection
* Utility Bill Payments
* E-tickets
* Mutual Funds Investments
* SBI e-Tax: Online Tax Payment
* Credit Card (Visa) Bill Pay
* Tax Payment using ATM cum Debit Card

2.7 BOARD OF DIRECTORS

Sr. No.| Name| Designation|
1| Shri Pratip Chaudhuri| Chairman|
2| Shri Hemant G. Contractor| Managing Director |
3| Shri Diwakar Gupta| Managing Director|
4| Shri A. Krishna Kumar| Managing Director|
5| Shri S.Vishvanathan| Managing Director|
6| Shri S. Venkatachalam| Director|
7| Shri D. Sundaram| Director|
8| Shri Parthasarathy Iyengar| Director|
9| Shri Thomas Mathew| Director|
10| Shri Jyoti Bhushan Mohapatra| Workmen Employee Director| 11| Shri S.K. Mukherjee| Officer Employee Director|
12| Dr. Rajiv Kumar| Director|
13| Shri Deepak Amin| Director|
14| Shri Harichandra Bahadur Singh| Director|
15| Shri Rajiv Takru| Director|
16| Dr. Urjit R. Patel| Director|

2.8 Awards and Recognitions

1) Best Online Banking Award, Best Customer Initiative Award & Best Risk Management Award (Runner Up) by IBA Banking Technology Awards 2010 2) The Bank of the year 2009, India (won the second year in a row) by The Banker Magazine 3) Best Bank – Large and Most Socially Responsible Bank by the Business Bank Awards 2009 4) Best Bank 2009 by Business India

5) The Most Trusted Brand 2009 by The Economic Times
6) Most Preferred Bank & Most preferred Home loan provider by CNBC 7) Visionaries of Financial Inclusion By FINO
8) Technology Bank of the Year by IBA Banking Technology Awards 9) SKOCH Award 2010 for Virtual corporation Category for its e-payment solution 10) The Brand Trust Report: 11th most trusted brand in Hindustan. 2.9 Major competitors

Some of the major competitors for SBI in the banking sector are ICICI Bank, HDFC Bank, Axis Bank, Bank of India, Punjab National Bank and Bank of Baroda. However in terms of average market share, SBI is by far the largest player in the market. 2.10 SBI future POS plan

|
State Bank of India group plans to acquire 50,000 Point-of-Sale (PoS) machines for deployment over the next 18 months. These are being done as part of its plans to upgrade its technological infrastructure and improve the speed of customer handling at its branches as well as merchant locations. SBI has over 14,100 branches while its five associate banks have over 4,500 branches. The group has about 28,000 ATMs. At present, the bank and its associates have a Single Window Operator counter called Green Channel at their branches. Under this facility, it is possible to withdraw, deposit or remit amount up to Rs 40,000.The SBI group plans to enlarge the type of transactions at these Green Channel counters through deploying these terminals. Currently about 35 per cent of the transactions done by SBI’s 200 million customers is through alternate channels (non-branch) such as internet, mobile, ATMs, etc. (4) (BUSSINESS LINE , 2012)

Literature Review

The term innovation means “to make something new”. Banks no longer restricted themselves to traditional banking activities but explored newer avenues to increase business and capture new market.

Impact of Innovation on Banks in terms of Products and Services

Banking sector got success because of their innovation, now a day banks are providing very innovative services, even they are seeking the technologies which can help more to the customer.

Eyadat and Kozak examined the impact of the progress in IT on the profit and cost efficiencies of the US banking sector during the period 1992-2003. The research showed a positive correlation between the levels of implemented IT and both profitability and cost savings. (S., 2005)

There is an improvement in bank performance and consolidation of the banking industry in the US during the deployment of new technologies (Berger, 2003).

In the Indian context, technological innovation and investment in IT during the period 2005-06 to 2009-10 led to efficiency gains for the scheduled commercial banks (M, 2011)

Technological innovation not only enables a broader reach for consumer banking and financial services, but also enhances its capacity for continued and inclusive growth .(Subbarao, 2009). Rogers describes the adoption of innovations over time. Rogers Diffusion of Innovations (DOI) theory indicates how an individual or organization (i.e. any decision-making unit) decides to adopt (or not) an innovation. (Rogers, 2003)

Several threats affect the survival of small, independent retail companies. Adoption and use of Point-of-Sale (POS) systems may offer important benefits to counter these threats. A survey has been held among 37 Dutch small, independent retailers, to answer the question what the most important determinants for POS system adoption are. This survey also study on IT adoption, specifically for small organizations (A Survey among Small Retailers in the Netherland). Julien and Raymond‘s technology adoption model for the retail sector proposes eight organizational aspects as determinants of technology adoption: centralization, complexity, size, status (i.e. independent/affiliated), sector, and assertiveness, rationality, and interaction of the organisational strategy. In the study 79 firms in food, hardware and clothing were assessed through questionnaires and semi-structured interviews.

Clothing firms and large firms were less apt to use POS systems, while firms that had a longer organisational planning horizon used POS systems more often. (Raymond, 1994) Thong and Yap developed a model based on the notion that the adoption process of small businesses differs from that of large firms. One of their main assumptions is that characteristics of the CEO are critical for IT adoption decisions. CEOs play a major role in small firms as they are the primary decisions makers. In their research, the authors developed a causal model, which assumes that the following factors are positively correlated with the likeliness of IT adoption for small firms: business size, competitiveness of the business environment, information intensity, innovativeness, and attitude towards adoption of IT and IT knowledge.

A survey among 166 Singaporean small organizations in the manufacturing, commerce and service industry was used to validate these assumptions. Results showed that firm size, the CEO’s innovativeness, attitude towards IT adoption and IT knowledge were indeed positively correlated with IT adoption. Although competitiveness and information intensity were both not correlated with IT adoption, they were positively correlated with the CEO’s attitude towards IT adoption. (Yap, 1995)

Venkatesh found that men and younger people have a higher performance expectancy of IT systems than women or older people. This performance expectancy in turn positively influences the attitude towards adoption. (Venkatesh, 2003) Thong and Yap who found that CEOs of organizations that adopt IT are generally more innovative and more computer literate than CEOs of organizations that do not adopt IT. (Yap, 1995) Lacovou, Thong and Yap, who found that larger organizations (measured by respectively turnover and employees) are more likely to adopt IT.

Based on the positive relationship between organisational size and innovation Iacovou, Thong and Yap, found that larger retail organizations are more likely to have a POS system than their smaller counterparts (Lacovou, 1995). On the contrary, Julien and Raymond found that retail organizations with a POS system were generally smaller. (Raymond, 1994). Personal variables of the owner (like age and gender) as key determinants of POS adoption by retailers. In addition, organisational characteristics (like size and competition) can be considered as additional determinants of the IT adoption decision. Application of innovation in State Bank of India

State bank of India, the largest public sector bank in India, being a public sector bank it has a good reputation in the market, offers the innovative services like SMS Unhappy, Crorepati Only Branch and One Rupee Bank. Other innovative services of SBI include, Online Education, Online Home, Online SME, Online Demat, Online Car Loans, e-Invest Cyber Plus and Swarojgar Credit Card etc.

Conclusion

The boom in e-commerce industry, globalization, and increased popularity of internet has made it vital for the banks keep up with the latest technology trends. With the entry of the private and global banks in the market, the competition amongst the banks has increased in the country. They provide a wide variety of services other than borrowing and lending money to people.

Banks need to augment their innovation capabilities in terms of new products, services and strategies which would enable them to maximize their efficiency gains. Need to further leverage technology in the banking sector.

Literature Gap

There is lot of scope for further research in this area of service operations in banks. The models and theory discussed can further be applied for conducting a survey to check the possibility of innovative products and services of banks.

RESEARCH METHODOLOGY

Organization

State Bank of India
4.1 Research Title

A Study on Acceptability of SBI Point of Sale Machine in Mehsana City.

4.2 Research Objective

Primary Objective:
* To check the possibilities of SBI POS in Mehsana City
* To know the factors that encourages customers to accept SBI POS.

Secondary Objective
To know the customers interest area for bank in purchasing the POS Machine. To know the potential growth of SBI POS in Mehsana city.
To know share of card payment offering by patients in Mehsana city. To check awareness about SBI POS Machine.
To find out that if people don’t purchase POS Machine what is the reason behind that.

4.3 Research Design

* Exploratory research provides the information to conduct the descriptive research, review of literature explores the necessity for the further research. So to study the acceptability of SBI POS Machine, Descriptive Research Design has been applied. * In that Cross Sectional study has been applied, as units are measured from a sample of the population at one point in time. * So, for the study I used Conclusive Research Design, Descriptive Research Design and Single Cross Sectional Design. 4.4 Research Type

* Applied Research

4.5 Research Approach

* The research approach to be followed here will be the survey method of collecting the data. Survey is conducted through Personal Interview.

4.6 Research Period

Duration of the Research Period is 8 Weeks.

4.7 Data Source

1) Primary Data:-
Primary data are organized by researcher for the specific purpose of addressing the problem at hand.
Here the Doctors, Owner of the Medical Stores and Admin. Officers at Hospital will be surveyed to collect the primary data.

2) Secondary Data:-
Secondary data are data that have already been collected for purposes other than the problem at hand.
Tools used for collection of data:-
a) Website
b) Magazine
c) Information provided by SBI Bank
4.8 Data Collection Method

a) Personal Interview

4.9 Sampling Plan

Population Definition
* A person having engaged in different sector like Hospital, Nursing Home, Dental Clinic, Medical Stores, Pathological laboratory.

Sample Unit:
* A person having engaged in different sector like Hospital, Nursing Home, Dental Clinic, Medical Stores, Pathological laboratory in Mehsana City.

Sample area:

* Mehsana City

4.10 Sampling Method

* I have used non- probability sampling method because it is relied on the personal judgments of the researcher. In that Convenience sampling is used in Project study. * Convenience Sampling

A non probability sampling technique that attempts to obtain a sample of convenient elements. The selection of sampling units is left primarily to the interviewer.

4.11 Sample Size

* 196 (95 % Level of Significance and 7 % Probable Error)

= Z2PQ
E 2
= (1.96) 2(0.5) (0.5)
(0.7) 2

= 196
4.12 Data Collection Instrument

a) Questionnaire

4.13 Analytical Techniques applied

1) Chi-Square Test
2) One way ANNOVA Test
3) Friedman Test
4) KMO and Bartlett’s Test

4.14 Limitations of Research

* Time Period of the survey.
* Reluctance on the part of the respondent to provide exact and correct details.

4.15 HYPOTHESIS

Chi – Square Hypothesis

No.| Hypothesis|
HO.1| Percentage share of Credit & Debit Card payment offering by Patients and Age of the Respondent are independent to each other.| HO.2| Percentage share of Credit & Debit Card payment offering by Patients and Computer Literacy of Respondent are independent to each other.| HO.3| Percentage share of Credit & Debit Card payment offering by Patients and Size of Hospital Respondent are independent to each other.| HO.4| Awareness of SBI POS Machine and Age of the Respondent are independent to each other.| HO.5| Awareness of SBI POS Machine and Gender of Respondent are independent to each other.| HO.6| Awareness about monthly rent of SBI POS Machine with landline connection and Age of the Respondent are independent to each other| HO.7| Awareness about monthly rent of SBI POS Machine with landline connection and Gender of Respondent are independent to each other| HO.8| Awareness about SBI POS special discount scheme for Hospital and Gender of Respondent are independent to each other| HO.9| Awareness about SBI POS special discount scheme for Hospital and Type of Respondent are independent to each other| HO.10| Awareness about SBI POS special discount scheme for Hospital and Age of Respondent are independent to each other|

One Way ANNOVA Hypothesis

No.| Hypothesis|
HO.1| There is a significance difference between Perception towards Training on Usage of POS and Type of the Hospital.| HO.2| There is a significance difference between Perception towards Training on Usage and Age group of the Respondent.| HO.3| There is a significance difference between Perception towards Training on Usage and Gender of the Respondent.| HO.4| There is a significance difference between Perception towards Training on Usage and Computer Literacy of the Respondent.| HO.5| There is a significance difference between Perception towards Transaction Time and Size of Hospital.| HO.6| There is a significance difference between Perception towards Transaction Time and Types of Hospital.| HO.7| There is a significance difference between Perception towards Technical Problem and Computer Literacy.| HO.8| There is a significance difference between Perception towards Technical Problem and Age group of the Respondent.|

HO.9| There is a significance difference between Perception towards Transaction Charges and Type of the Hospital.| HO.10| There is a significance difference between Perception towards Transaction Charges and Size of the Hospital.| HO.11| There is a significance difference between Perception towards Transaction Charges and Age group of the Respondent.| HO.12| There is a significance difference between Perception towards Installation Cost and Type of the Hospital.| HO.13| There is a significance difference between Perception towards Installation Cost and Size of the Hospital.| HO.14| There is a significance difference between Perception towards Delay in Access to Fund and Age of the Respondent.| HO.15| There is a significance difference between Perception towards Delay in Access to Fund and Gender of the Respondent.| HO.16| There is a significance difference between Perception towards Fear of fraud and Age of Respondent.| HO.17| There is a significance difference between Perception towards Fear of fraud and Gender of Respondent.| HO.18| There is a significance difference between Perception towards Fear of not being able to operate POS terminal and Age of Respondent.| HO.19| There is a significance difference between Perception towards Fear of not being able to operate POS terminal and
Computer literacy of Respondent.|

Questionnaire Analysis

Q 1
Q1.

By which mode do you accept payment (Fees) from patients? (Please Tick Mark in the Blanks) Table No 5.1
Mode of Payment| Frequency| Percentage|
Cash| 196| 100|
Cheque| 31| 15.8|
Debit card| 1| 0.5|
Credit card| 1| 0.5|
Others| 1| 0.5|

Chart No.5.1

Interpretation
From the above chart it can be interpreted that from the sample size taken for survey all the Patients are using cash as a mode of payment. Portion of cheque is 15.8%, 0.5% patient use debit card, credit card and other mode of payment because of customers insistence to use cash as a mode of payment.

Q2.

By comparing Cash and Card payment, what is percentage share of Card payment Offering by patients?
Table No 5.2
Share of card payment| Frequency| Percentage|
0| 195| 99.5|
1 to 19| 1| 0.5|
20 to 39 | 0| 0|
40 to 59| 0| 0|
60 to 80| 0| 0|
>80| 0| 0|
Total| 196| 100%|

Chart No.5.2

Interpretation
From the above chart it can be interpreted that percentage share of card payment offered by patients is very low and only 0.5% share of card payment is there. 99.5% patient prefers cash as a mode of payment. The reason behind this is customer’s insistence to use cash as a mode of payment.

.

Q3.

Which bank account do you have?
Table No 5.3
Bank Name| Frequency| Percentage|
S.B.I| 88| 44.9|
HDFC| 61| 31.1|
ICICI| 24| 12.2|
AXIS| 14| 7.1|
OTHER| 18| 9.2|

Chart No.5.3

Interpretation
From the above chart it can be interpreted that out of 196 sample 44.9% respondent have a bank account with SBI. Other banks like HDFC, ICICI, and AXIS have a market share in bank account of 31.1%, 12.2%, 7.1% respectively. So, SBI bank is a market leader in bank account in Mehsana city.

Q4.
Do you have SBI current account?
Table No 5.4
SBI CURRENT A/C| Frequency| Percentage|
YES| 06| 3.1|
NO| 190| 96.9|
Total| 196| 100%|

Chart No.5.4

Interpretation
From the above chart it can be interpreted that from the sample size taken for survey 96.9% does not have current account with SBI and only3.15 respondent have SBI current account. The reason is that the Doctors and owners of medical stores do not require daily cash deposit and withdrawal transaction with bank.

Q5.

Do you have SBI POS machine?
Table No 5.5
SBI POS Machine| Frequency| Percentage|
YES| 01| 0.5|
NO| 195| 99.5|
Total| 196| 100%|

Chart No.5.5

Interpretation
From the above chart it can be interpreted that from the 196 sample size taken for survey 99.5% respondent do not SBI POS machine and only 0.5% respondent have SBIPOS machine . out of So all the Patients are using cash as a mode of payment. Portion of cheque is 15.8%, 0.5% patient use debit card, credit card and other mode of payment. In Hospitals most of the patients are rural people and they o not use card for payment of fees.

Q6.
How long have you had your current SBI POS?
Table No 5.6

Particulars| Frequency| Percentage|
Less than 6 month| 1| 100|
Between 6 to 12 month| 0| 0|
More than 1 year| 0| 0|
Total| 1| 100|

Chart No.5.6

Interpretation
From the above table it can be interpreted that there is only one user of SBI POS machine and the user using the POS machine less than 6 month.

Q7.
How did you come to know about this SBI POS machine?
Table No 5.7
Particulars| Frequency| Percentage|
Internet| 0| 0|
Advertisement| 0| 0|
Bank representative| 0| 0|
Other| 1| 100|
total| 1| 100|

Chart No.5.7

Interpretation
From the above table it can be interpreted that only one use of SBI POS machine knows through other sources. Current user knows SBI POS machine because user have already have POS machine of other bank.

Q8.
Which of the following factors are motivating you to adopt SBI POS system? [Rank the factors according to your priority. Where 6 being the highest & 1 is the lowest priority]

Table No 5.8
Factors| Rank|
Additional payment method| 6|
Simplicity of usage| 2|
Easiness of cash handling| 5|
To avoid robberies and thefts| 4|
No duplicate currency| 1|
Faster payment processing| 3|

Interpretation
From the above table it can be interpreted that respondent give highest rank to the additional payment method for using SBI POS machine and lowest rank to know duplicate currency for using POS machine.

Q9.

Which bank’s POS machine are you using?

Table No 5.9
Bank Name| Frequency| Percentage|
HDFC| 1| 0.5|
ICICI| 1| 0.5|
AXIS| 0| 0|
Not using| 195| 99|

Chart No.5.8

Interpretation
From the above chart it can be interpreted that from the sample size taken for survey 99% respondent does not using POS machine in hospital and medical stores. Market share of POS of HDFC and ICICI bank is 0.5% out of sample taken for the survey.

Q10.

Are you aware about of this SBI POS machine?

Table No 5.10
Awareness about POS| Frequency| Percentage|
YES| 168| 85.7|
NO| 28| 14.3|
Total| 196| 100%|

Chart No.5.9

Interpretation
From the above chart it can be interpreted that from the 196 sample size taken for survey 85.7% Doctors and owner of the medical store are aware about SBI POS machine. and 14.3% respondents are not aware about SBI POS machine.

Q11.

Are you aware about Monthly Rent free SBI POS machine with landline Connection? Table No 5.11

Awareness about Monthly rent| Frequency| Percentage|
YES| 26| 12.8|
NO| 170| 87.2|
Total| 196| 100%|

Chart No.5.10

Interpretation

From the above chart it can be interpreted that from the sample size taken for survey only 12.8% respondents are aware about monthly rent fee of SBI POS machine with land line connection and 87.2% are not aware about monthly rent fee of SBI POS machine with land line connection. A local call rate charge is rent for SBI POS machine with landline connections.

Q12.

Are you aware about SBI POS special discount scheme for Hospitals?

Table No 5.12
Awareness about Discount scheme| Frequency| Percentage|
YES| 21| 10.3|
NO| 175| 89.7|
Total| 196| 100%|

Chart No.5.11

Interpretation
From the above chart it can be interpreted that from the sample size taken for survey 89.7% respondent are not aware about SBI POS special discount scheme for hospitals and only 10.3% respondent aware about SBI POS special discount scheme for hospitals. There is a discount of 0.15% in MDR for hospitals.

Q13.

Please allocate points from 10 to bellow mention six reasons for not accepting PoS machine in your hospital /medical store. More point you will assign will indicate that the particular reason is more responsible /barrier for not accepting PoS in your hospital/medical store. If you feel that an attribute is not at all important, then please assign 0 for that attribute. The total of all the points should be equal to 10. Table No 5.13

Reasons| 0| 1| 2| 3| 4| 5| 6| 7| 8| 9| 10|
Fear of fraud| 105| 35| 36| 4| 11| 0| 2| 1| 0| 0| 1| Difficulty in accessing cash | 126| 28| 23| 5| 10| 3| 0| 0| 0| 0| 0| Transaction Cost | 101| 28| 45| 6|
12| 1| 2| 0| 0| 0| 0| Customer’s insistence to use cash | 2| 2| 20| 17| 73| 27| 21| 7| 18| 3| 5| Fear of not being able to operate PoS terminal. | 123| 17| 30| 9| 10| 5| 0| 1| 0| 0| 0| Other| 99| 11| 24| 19| 20| 10| 10| 1| 1| 0| 0|

Interpretation
From the above table it can be interpreted that from the sample size taken for survey customer insistence to use cash as a mode of payment is the main reason for not accepting POS machine in Hospital/Medical stores. Difficulty in accessing in cash and fear of fraud are not important factor to accept POS machine in Hospital and medical stores.

Q14.
What are the factors are encourage you to accept SBI POS? [Rank the factors according to your priority Where 6 being the highest & 1 is the lowest priority]

Table No 5.14
RANK| 6| 5| 4| 3| 2| 1|
Particulars| F| %| F| %| F| %| F| %| F| %| F| %| State Bank’s brand name| 76| 38.78| 16| 8.16| 41| 20.92| 22| 11.22| 36| 18.37| 05| 2.55| State Bank’s marketing| 4| 2.04| 9| 4.59| 36| 18.37| 25| 12.76| 66| 33.68| 56| 28.58| State Bank’s transparency| 5| 2.55| 12| 6.12| 16| 8.16| 42| 21.43| 43| 21.94| 78| 39.80| Lowest MDR| 76| 38.78| 72| 36.73| 22| 11.22| 10| 5.10| 7| 3.57| 09| 4.59| Account can be opened at zero balance| 19| 9.69| 67| 34.18| 49| 25| 27| 13.78| 21| 10.72| 13| 6.63| Special discount rate for Hospital | 16| 8.16| 20| 10.20| 35| 17.86| 67| 34.18| 24| 12.24| 34| 17.35|

Interpretation
From the above table 38.78% respondent give 1st rank to the SBI brand name and only 2.55% respondent give last rank to the SBI brand name to accept SBI POS. Most important factor which encourages to accept SBI POS is lowest MDR because total 75.51% respondent gives 1st and 2nd rank to that factor. State bank transparency and State bank marketing that the last two rank respectively.

Q15.

Do you feel that POS becomes essential service nowadays? Table No 5.15
Particulars| Definitely not| Probably not| Not sure| Probably| Definitely| Total respondent| | F| %| F| %| F| %| F| %| F| %| |
Hospitals| 46| 35.11| 48| 36.64| 14| 10.69| 23| 17.56| 0| 0| 131| Medicals Stores| 34| 52.31| 29| 44.61| 1| 1.54| 1| 1.54| 0| 0| 65|

Chart No.5.12

Interpretation
From the above chart it can be interpreted that from the sample size taken for survey 46respondent feel that POS definitely not becomes essential services now a day in hospital.48respondent feel that POS probably not becomes essential services now a day in hospital. 14 respondents are not sure about POS as an essential service now a day in hospital. 23 respondent feel that POS becomes probably essential services now a day in hospital and no respondent feel that POS definitely becomes essential services now a day in hospital.

Chart No.5.13

Interpretation
From the above chart it can be interpreted that from the sample size taken for survey 34respondent feel that POS definitely not becomes essential services now a day in medical stores.29 respondent feel that POS probably not becomes essential services now a day in medical stores.. 1 respondent is not sure about POS as essential services now a day in medical stores. 1 respondent feel that POS becomes probably essential services now a day in medical stores and no respondent feel that POS definitely becomes essential services now a day in medical stores.

Q16.

Give your preference for the following factors to accept the POS machine. Table No 5.16
PARTICULARS| VERY IMPORTANT| IMPORTANT| NEUTRAL| NOT IMPORTANT| NOT AT ALL IMPORTANT| | F| %| F| %| F| %| F| %| F| %|
Installation Cost| 52| 26.53| 111| 56.63| 02| 1.02| 31| 15.82| 0| 0| Training on usage | 08| 4.08| 132| 67.35| 09| 4.59| 47| 23.98| 0| 0| Transaction time | 22| 11.22| 123| 62.76| 13| 6.63| 38| 19.39| 0| 0| Connectivity/network | 23| 11.73| 129| 65.82| 19| 9.69| 25| 12.76| 0| 0| Technical problems| 19| 9.69| 115| 58.7| 31| 15.82| 30| 15.31| 0| 0| Transaction charges | 144| 73.47| 52| 26.53| 0| 0| 0| 0| 0| 0| Delay in access to funds | 64| 32.65| 101| 51.53| 16| 8.16| 15| 7.65| 0| 0|

Table No 5.17
Particulars| IMPORTANT| NOT IMPORTANT|
Cost| 83.16| 15.82|
Training on usage | 71.43| 23.98|
Transaction time | 73.98| 19.39|
Connectivity/network | 77.55| 12.76|
Technical problems| 68.39| 15.31|
Transaction charges | 100| 0|
Delay in access to funds | 84.18| 7.65|

Chart No.5.14

Interpretation
From above chart and Table 9.1 it is to be interpreted that, according to the view of the Doctors and owner of medical store transaction charges are most important factor to accept the POS machine. Delay in access to fund is another important factor to accept POS machine installation cost is the third important factor to accept Pos machine. Whereas training on usage and transaction time is the least important factor to accept POS machine.

Q17.

Please indicate which of the following bank’s PoS machine you prefer from the pair of PoS machines presented as bellow.(‘+’ indicate that coloum bank is preferred over row bank and ‘-‘ indicate that row bank is preferred over column bank.) Table No 5.18

Bank Name| Frequency| Percentage|
SBI| 112| 57.14|
HDFC| 84| 42.86|
Total| 196| 100%|

Chart No.5.15

Interpretation
From the above chart it can be interpreted that out of 196 respondent 57.14% respondent prefer SBI for POS over HDFC with 42.86%.Preference for SBI POS is more than HDFC POS machine.

Table No 5.19

Bank Name| Frequency| Percentage|
SBI| 142| 72.40|
AXIS| 54| 27.60|
Total| 196| 100%|

Chart No.5.16

Interpretation
From the above chart it can be interpreted that out of 196 respondent 72.4% respondent prefer SBI for POS over AXIS with 27.6%.Preference for SBI POS is
more than AXIS POS machine.

Table No 5.20

Bank Name| Frequency| Percentage|
SBI| 167| 85.20|
ICICI| 29| 14.80|
Total| 196| 100%|

Chart No.5.17

Interpretation
From the above chart it can be interpreted that out of 196 respondent 85.20% respondent prefer SBI for POS over ICICI with 14.8%.Preference for SBI POS is more than ICICI POS machine.

Table No 5.21
Bank Name| Frequency| Percentage|
SBI| 176| 89.80|
OTHER| 20| 10.20|
Total| 196| 100%|

Chart No.5.18

Interpretation
From the above chart it can be interpreted that out of 196 respondent 89.8% respondent prefer SBI for POS over other bank with 10.20%.Preference for SBI POS is more than other bank POS machine.

DEMOGRAPHIC DETAILS
RELATION
Table No 5.22
Relation| Frequency| Percentage|
Owner| 189| 96.4|
Jobber| 07| 3.6|
Total| 196| 100|

Chart No.5.19

Interpretation
From the above chart it can be interpreted that 96.4% respondent are owner of hospitals and medical stores and only 3.6% respondent are jobber at hospital and medical stores.

LANDLINE CONNECTION
Table No 5.23
Landline No.| Frequency| Percentage|
YES| 133| 67.9|
NO| 63| 32.1|

Chart No.5.20

Interpretation
From the above chart it can be interpreted that 67.9 percent hospitals and medical store have a landline connection and 32.1 percent does not have a landline connection.

GENDER
Table No 5.24
Gender| Frequency| Percentage|
Male| 177| 90.3|
Female| 19| 9.7|

Chart No.5.21

Interpretation
From the above chart it can be interpreted that 90.3% respondent are male and 9.7% respondent are female.

AGE
Table No 5.25
Age| Frequency| Percentage|
<30| 04| 2.0|
31 TO 40| 58| 29.6|
41 TO 50| 102| 52.0|
>50| 32| 16.3|

Chart No.5.22

Interpretation
From the above chart it can be interpreted that more than half of the populations are come in 41 to 50 age group.2% population are in below 30 age group. In 31 to 40 and >50 age group 29.6% and 16.3% are come in population respectively.

COMPUTER LITERACY

Table No 5.26
Computer Literacy| Frequency| Percentage|
YES| 180| 91.8|
NO| 16| 8.2|

Chart No.5.23

Interpretation
From the above chart it can be interpreted that 91.8% respondent have computer knowledge and only 8.2% respondent does not have computer knowledge.

TYPES OF HOSPITAL
Table No 5.27
Types of Hospitals| Frequency| Percentage|
Specialty| 67| 52.3|
Multispecialty| 07| 5.5|
Other| 54| 42.2|

Chart No.5.24

Interpretation
From the above chart it can be interpreted that 52.3% hospitals are specialty hospitals, 5.5% hospitals are multy specialty hospitals and 42.2% hospitals fall in other category like dental clinic and pathology laboratory.

SIZE OF HOSPITAL
Table No 5.28

Size of Hospitals/Medical Store| Frequency| Percentage|
Small| 88| 44.9|
Medium| 99| 50.5|
Large| 09| 4.6|

Chart No.5.23

Interpretation
From the above chart it can be interpreted that 44.9% hospitals/medical stores are small in size, 50.5% are medium in size and only 4.6% are large in size.

Hypothesis Test Analysis
6.1 Chi – Square Hypothesis

No.| Hypothesis| Significance Value| Result |
HO.1| Percentage share of Credit & Debit Card payment offering by Patients and Age of the Respondent are independent to each other.| 0.819| ACCEPT| HO.2| Percentage share of Credit & Debit Card payment offering by Patients and Computer Literacy of Respondent are independent to each other.| 0.765| ACCEPT| HO.3| Percentage share of Credit & Debit Card payment offering by Patients and Size of Hospital Respondent are independent to each other.| 0.000| REJECT| HO.4| Awareness of SBI POS Machine and Age of the Respondent are independent to each other.| 0.219| ACCEPT| HO.5| Awareness of SBI POS Machine and Gender of Respondent are independent to each other.| 0.844| ACCEPT| HO.6| Awareness about monthly rent of SBI POS Machine with landline connection and Age of the Respondent are independent to each other| 0.783| ACCEPT|

HO.7| Awareness about monthly rent of SBI POS Machine with landline connection and Gender of Respondent are independent to each other| 0.300| ACCEPT| HO.8| Awareness about SBI POS special discount scheme for Hospital and Gender of Respondent are independent to each other| 0.967| ACCEPT| HO.9| Awareness about SBI POS special discount scheme for Hospital and Type of Respondent are independent to each other| 0.362| ACCEPT| HO.10| Awareness about SBI POS special discount scheme for Hospital and Age of Respondent are independent to each other| 0.239| ACCEPT|

HO.1| Percentage share of Credit & Debit Card payment offering by Patients and Age of the Respondent are independent to each other.|

Interpretation: Here the significance value is .819 which more than 0.05 so alternative hypotheses is accepted it means that the Percentage share of Credit & Debit Card payment offering by Patients and Age of the Respondent are dependent to each other.

HO.2| Percentage share of Credit & Debit Card payment offering by Patients and Computer Literacy of Respondent are independent to each other.|

Interpretation: Here the significance value is .765 which more than 0.05 so alternative hypotheses is accepted it means that the Percentage share of Credit & Debit Card payment offering by Patients and Computer Literacy of the Respondent are dependent to each other.

HO.3| Percentage share of Credit & Debit Card payment offering by Patients and Size of Hospital Respondent are independent to each other.|

Interpretation : Here the significance value is .000 which less than 0.05 so alternative hypotheses is rejected it means that the Percentage share of Credit & Debit Card payment offering by Patients and Size of Hospital
Respondent are independent to each other.

HO.4| Awareness of SBI POS Machine and Age of the Respondent are independent to each other.|

Interpretation: Here the significance value is .219 which more than 0.05 so alternative hypotheses is accepted it means that the Awareness of SBI POS Machine and Age of the Respondent are dependent to each other.

HO.5| Awareness of SBI POS Machine and Gender of Respondent are independent to each other.|

Interpretation: Here the significance value is .844 which more than 0.05 so alternative hypotheses is accepted it means that the awareness of SBI POS Machine and Gender of Respondent are dependent to each other.

HO.6| Awareness about monthly rent of SBI POS Machine with landline connection and Age of the Respondent are independent to each other|

Interpretation: Here the significance value is .783 which more than 0.05 so alternative hypotheses is accepted it means that the Awareness about monthly rent of SBI POS Machine with landline connection and Age of the Respondent are dependent to each other.

HO.7| Awareness about monthly rent of SBI POS Machine with landline connection and Gender of Respondent are independent to each other|

Interpretation: Here the significance value is .300 which more than 0.05 so alternative hypotheses is accepted it means that the Awareness about monthly rent of SBI POS Machine with landline connection and Gender of Respondent are dependent to each other.

HO.8| Awareness about SBI POS special discount scheme for Hospital and Gender of Respondent are independent to each other|

Interpretation: Here the significance value is .967 which more than 0.05 so alternative hypotheses is accepted it means that the Awareness about SBI POS special discount scheme for Hospital and Gender of Respondent are dependent to each other.

HO.9| Awareness about SBI POS special discount scheme for Hospital and Type of Respondent are independent to each other|

Interpretation: Here the significance value is .362 which more than 0.05 so alternative hypotheses is accepted it means that the Awareness about SBI POS special discount scheme for Hospital and Type of Respondent are dependent to each other.

HO.10| Awareness about SBI POS special discount scheme for Hospital and Age of Respondent are independent to each other|

Interpretation: Here the significance value is .239which more than 0.05 so alternative hypotheses is accepted it means that the Awareness about SBI POS special discount scheme for Hospital and Age of Respondent are dependent to each other.

6.2 One Way ANNOVA Hypothesis

No.| Hypothesis| Significance Value | Result |
HO.1| There is a significance difference between Perception towards Training on Usage of POS and Type of the Hospital.| 0.069| ACCEPT| HO.2| There is a significance difference between Perception towards Training on Usage and Age group of the Respondent.| 0.074| ACCEPT| HO.3| There is a significance difference between Perception towards Training on Usage and Gender of the Respondent.| 0.037| REJECT| HO.4| There is a significance difference between Perception towards Training on Usage and Computer Literacy of the Respondent.| 0.828| ACCEPT| HO.5| There is a significance difference between Perception towards Transaction Time and Size of Hospital.| 0.030| REJECT| HO.6| There is a significance difference between Perception towards Transaction Time and Types of Hospital.| 0.473| ACCEPT| HO.7| There is a significance difference between Perception towards Technical Problem and Computer Literacy.| 0.123| ACCEPT|

HO.8| There is a significance difference between Perception towards Technical Problem and Age group of the Respondent.| 0.531| ACCEPT| HO.9| There is a significance difference between Perception towards Transaction Charges and Type of the Hospital.| 0.351| ACCEPT| HO.10| There is a significance difference between Perception towards Transaction Charges and Size of the Hospital.| 0.008| REJECT| HO.11| There is a significance difference between Perception towards Transaction Charges and Age group of the Respondent.| 0.988| ACCEPT| HO.12| There is a significance difference between Perception towards Installation Cost and Type of the Hospital.| 0.307| ACCEPT| HO.13| There is a significance difference between Perception towards Installation Cost and Size of the Hospital.| 0.062| ACCEPT| HO.14| There is a significance difference between Perception towards Delay in Access to Fund and Age of the Respondent.| 0.035| REJECT| HO.15| There is a significance difference between Perception towards Delay in Access to Fund and Gender of the Respondent.| 0.053| ACCEPT| HO.16| There is a significance difference between Perception towards Fear of fraud and Age of Respondent.| 0.062| ACCEPT| HO.17| There is a significance difference between Perception towards Fear of fraud and Gender of Respondent.| 0.113| ACCEPT| HO.18| There is a significance difference between Perception towards Fear of not being able to operate POS terminal and Age of Respondent.| 0.719| ACCEPT| HO.19| There is a significance difference between Perception towards Fear of not being able to operate POS terminal and Computer literacy of Respondent.| 0.230| ACCEPT|

HO.1| There is a significance difference between Perception towards Training on Usage of POS and Type of the Hospital.|

Interpretation: A one-way was conducted to compare the significance difference between Perception towards Training on Usage and Type of the Hospital. There was significant difference between Perception towards Training on Usage and Type of the Hospital at the p>0.05 level.

[F=2.726, p=0.069]

HO.2| There is a significance difference between Perception towards Training on Usage and Age group of the Respondent.|

Interpretation: A one-way was conducted to compare the significance difference between Perception towards Training on Usage and Age group of the Respondent. There was significant difference between Perception towards Training on Usage and Age group of the Respondent. at the p>0.05 level.

[F=2.350, p=0.074]

HO.3| There is a significance difference between Perception towards Training on Usage and Gender of the Respondent.|

Interpretation: A one-way was conducted to compare the significance difference between Perception towards Training on Usage and Gender of the Respondent. There was no significant difference between Perception towards Training on Usage and Gender of the Respondent at the p<0.05 level [F=4.416, p=0.037].

HO.4| There is a significance difference between Perception towards Training on Usage and Computer Literacy of the Respondent.|

Interpretation: A one-way was conducted to compare the significance difference between Perception towards Training on Usage and Computer Literacy of the Respondent. There was significant difference between Perception towards Training on Usage and Computer Literacy of the Respondent. at the p>0.05 level. [F=0.047, p=0.828]

HO.5| There is a significance difference between Perception towards Transaction Time and Size of Hospital.|

Interpretation: A one-way was conducted to compare the significance difference between Perception towards Transaction Time and Size of Hospital. There was no significant difference between Perception towards Transaction Time and Size of Hospital at the p<0.05 level [F=3.558, p=0.030]

HO.6| There is a significance difference between Perception towards Transaction Time and Types of Hospital.|

Interpretation: A one-way was conducted to compare the significance difference between Perception towards Transaction Time and Types of Hospital. There was significant difference between Perception towards Transaction Time and Types of Hospital .at the p>0.05 level. [F=0.753, p=0.473]

HO.7| There is a significance difference between Perception towards Technical Problem and Computer Literacy.|

Interpretation: A one-way was conducted to compare the significance difference between Perception towards Technical Problem and Computer Literacy. There was significant difference between Perception towards Technical Problem and Computer Literacy at the p>0.05 level. [F=2.406, p=0.123]

HO.8| There is a significance difference between Perception towards Technical Problem and Age group of the Respondent.|

Interpretation: A one-way was conducted to compare the significance difference between Perception towards Technical Problem and Age group of the Respondent. There was significant difference between Perception towards Technical Problem and Age group of the Respondent at the p>0.05 level. [F=0.738, p=0.531]

HO.9| There is a significance difference between Perception towards Transaction Charges and Type of the Hospital.|

Interpretation: A one-way was conducted to compare the significance
difference between Perception towards Transaction Charges and Type of the Hospital. There was significant difference between Perception towards Transaction Charges and Type of the Hospital at the p>0.05 level. [F=0.012, p=0.351]

HO.10| There is a significance difference between Perception towards Transaction Charges and Size of the Hospital.|

Interpretation: A one-way was conducted to compare the significance difference between Perception towards Transaction Charges and Size of the Hospital. There was no significant difference between Perception towards Transaction Charges and Size of the Hospital at the p<0.05 level for three conditions [F=4.944, p=0.008]

HO.11| There is a significance difference between Perception towards Transaction Charges and Age group of the Respondent.|

Interpretation : A one-way was conducted to compare the significance difference between Perception towards Transaction Charges and Age group of the Respondent There was significant difference between Perception towards Transaction Charges and Age group of the Respondent at the p>0.05 level. [F=1.099, p=0.988]

HO.12| There is a significance difference between Perception towards Installation Cost and Type of the Hospital.|

Interpretation: A one-way was conducted to compare the significance difference between Perception towards Installation Cost and Type of the Hospital. There was significant difference between Perception towards Installation Cost and Type of the Hospital at the p>0.05 level. [F=1.191, p=0.307]

HO.13| There is a significance difference between Perception towards Installation Cost and Size of the Hospital.|

Interpretation: A one-way was conducted to compare the significance difference between Perception towards Installation Cost and Size of the Hospital. There was significant difference between Perception towards Installation Cost and Size of the Hospital at the p>0.05 level. [F=2.826, p=0.062]

HO.14| There is a significance difference between Perception towards Delay in Access to Fund and Age of the Respondent.|

Interpretation: A one-way was conducted to compare the significance difference between Perception towards Delay in Access to Fund and Age of the Respondent. There was no significant difference between Perception towards Delay in Access to Fund and Age of the Respondent at the p<0.05 [F=2.921, p=0.035]

HO.15| There is a significance difference between Perception towards Delay in Access to Fund and Gender of the Respondent.|

Interpretation: A one-way was conducted to compare the significance difference between Perception towards Delay in Access to Fund and Gender of the Respondent. There was significant difference between Perception towards Delay in Access to Fund and Gender of the Respondent at the p>0.05 level. [F=3.791, p=0.053]

HO.16| There is a significance difference between Perception towards Fear of fraud and Age of Respondent.|

Interpretation: A one-way was conducted to compare the significance difference between Perception towards Fear of fraud and Age of Respondent. There was significant difference between Perception towards Fear of fraud and Age of Respondent .at the p>0.05 level. [F=2.490, p=0.062]

HO.17| There is a significance difference between Perception towards Fear of fraud and Gender of Respondent.|

Interpretation: A one-way was conducted to compare the significance difference between Perception towards Fear of fraud and Gender of Respondent. There was significant difference between Perception towards Fear of fraud and Gender of Respondent at the p>0.05 level. [F=2.541, p=0.113]

HO.18| There is a significance difference between Perception towards Fear of not being able to operate POS terminal and Age of Respondent.|

Interpretation: A one-way was conducted to compare the significance difference between Perception towards Fear of not being able to operate POS terminal and Age of Respondent. There was significant difference between Perception towards Fear of not being able to operate POS terminal and Age of Respondent at the p>0.05 level. [F=0.448, p=0.719]

HO.19| There is a significance difference between Perception towards Fear of not being able to operate POS terminal and Computer literacy of Respondent.|

Interpretation: A one-way was conducted to compare the significance difference between Perception towards Fear of not being able to operate POS terminal and Computer literacy of Respondent. There was significant difference between Perception towards Fear of not being able to operate POS terminal and Computer literacy of Respondent at the p>0.05 level. [F=1.449, p=0.230]

6.3 Friedman Test
|

H0: There is no significant difference among the factors to accept the POS machine. H1: There is significant difference among the factors to accept the POS machine.

RanksTable No 6.|
Factors to accept the POS machine.| Mean Rank|
Installation Cost| 3.87|
Training on usage | 4.80|
Transaction time | 4.59|
Connectivity/network | 4.39|
Technical problems| 4.65|
Transaction charges | 2.09|
Delay in access to funds | 3.61|

Test Statistics aTable No 6.2|
N| 195|
Chi-square| 336.100|
df| 6|
Asymp. Sig.| .000|
a. Friedman Test|
Interpretation
Here Friedman test P value is 0.000<0.05. So here we Reject H0, Accept H1, there is significant difference among the factors to accept the POS machine. So, doctors and owner of medical store believed in differently for different factors to accept POS machine.

Rank on different criteria as below
Table No 6.3
Criteria| Rank|
Transaction charges | 1|
Delay in access to funds | 2|
Installation Cost| 3|
Connectivity/network | 4|
Transaction time | 5|
Technical problems| 6|
Training on usage | 7|

6.4 KMO and Bartlett’s Test

Table No 6.4

KMO and Bartlett’s Test|
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.| .581|
Bartlett’s Test of Sphericity| Approx. Chi-Square| 198.519| | df| 21|
| Sig.| .000|

Table No. 6.4 show, the KMO measure of sampling adequacy for the various attributes categories measured 0.581, which indicates the scale is appropriates and help in extracting the factor. The ideal measure for this test (KMO>0.40) and here in this case KMO is 0.581 indicates the variable are measuring a common factor.

Table No. 6.4 show the Bartlett’s test for Sphericity for judging the appropriateness of a factor model. The existence of the identity matrix puts the correctness of the factor analysis under suspicion. Table shows that chi-square static is 198.51 with 21 degree of freedom. This value is significant at 0.01 levels.

FINDINGS

* Percentage share of card payment offering by patient in Hospitals & medical stores is very low. * Most of hospital & medical stores does not use POS machine of any bank. * Majority of Doctors & owners of medical stores are aware about SBI POS machine. * Majority of doctors & owners of medical stores are not aware about monthly rent of SBI POS with land line connection & special discount scheme for hospital. * Lowest MDR & state bank’s brand name are important factors which encourage accepting of SBI POS. * Main reason for not accepting POS machine is customer’s insistence to use cash as a payment method. * Majority of Doctors & owners of medical stores does not feel that POS becomes essential services now a day. * Transaction charges and delay in access to fund are priority factors to accept the POS machine. * Training on usage and Technical problem are less important factors to accept the POS machine. * Potential POS market share of SBI is more comparing to other bank.

SUGGESTIONS

* Rural people less use debit & credit card. So bank have to first remove this barrier. * Bank need to use promotional tools and proper advertisement for clearing misperception like fear of fraud about POS machine. * Bank need to do advertisement to aware about monthly rent of SBI POS with landline connection & special discount Scheme for hospital * Bank continues to offer POS machine as a free of cost. * Lowest MDR is important factor for choosing POS of SBI. So, continues to offer POS at lowest rate.

BIBLIOGRAPHY

BOOKS:
1. (Bajpai, 2011)Business Research Methods, Naval Bajpai, Page no. 309-319,364,430-435, Publication House: Pearson 2. (BLACK, 2011)Business Statistics, Ken BLACK, Page no. 479, Publication House: WILEY INDIA WEB SITES:

1. www.sbi.co.in
2. https://www.sbi.co.in/user.htm.
3. www.wikipedia.com
4. http://www.studymode.com

ANNEXURE

Questionnaire
Dear Respondent,
I am a student of S.V. Institute of Management, Kadi pursuing M.B.A. As a part of curriculum, I required to undergo Summer Internship Programme. As a part of this Summer Internship Programme, I am doing research on “A Study on Acceptability of SBI Point of Sale Machine in Hospitals and Medical Stores in Mehsana City ”The information provided by you would be used for academic purpose only and will be kept confidential.

1. By which mode do you accept payment (Fees) from patients? (Please Tick
Mark in the Blanks) By cash
By cheque
By debit card
By credit card
Others___________________ (Please specify)
2. By comparing Cash and Card payment, what is percentage share of Card payment Offering by patients?
0 1 to 19 20 to 39 40 to 59 60 to 80 >80 3. Which bank account do you have?
SBI HDFC ICICI AXIS OTHER (Please specify) _____________ 4. Do you have SBI current account?
Yes No
5. Do you have SBI POS machine?
Yes No

IF YES, then
6. How long have you had your current SBI POS?
Less than 6 months Between 6 to 12 months More than 1 year 7. How did you come to know about this SBI POS machine?
Internet Advertisement
Bank Representative other _________________ (Please specify) 8. Which of the following factors are motivating you to adopt SBI POS system? [Rank the factors according to your priority. Where 6 being the highest & 1 is the lowest priority] Additional payment method ________

Simplicity of usage ________
Easiness of cash handling ________
To avoid robberies and thefts ________
No Duplicate currency ________
Faster payment processing time ________

IF NOT, then
9. Which bank’s POS machine are you using?
HDFC ICICI AXIS NOT USING 10. Are you aware about of this SBI POS
machine?
Yes No
11. Are you aware about Monthly Rent free SBI POS machine with landline Connection? Yes No

12. Are you aware about SBI POS special discount scheme for Hospitals? Yes No
13. Please allocate points from 10 to bellow mention six reasons for not accepting PoS machine in your hospital /medical store. More point you will assign will indicate that the particular reason is more responsible /barrier for not accepting PoS in your hospital/medical store. If you feel that an attribute is not at all important, then please assign 0 for that attribute. The total of all the points should be equal to 10. Reasons Points Fear of fraud _____ Difficulty in accessing cash _____ Transaction Cost _____ Customer’s insistence to use cash _____ Fear of not being able to operate PoS terminal. _____ Other _____ Total 10

14. What are the factors are encourage you to accept SBI POS? [Rank the factors according to your priority Where 6 being the highest & 1 is the lowest priority]

State Bank’s brand name_____
State Bank’s marketing_____
State Bank’s transparency_____
Lowest MDR_____
Account can be opened at zero balance_____
Special discount rate for Hospital _____

15. Do you feel that POS becomes essential service nowadays? Particulars| Definitely not| Probably not| Not sure| Probably| Definitely|
Hospitals| | | | | |
Medicals Stores| | | | | |

16. Give your preference for the following factors to accept the POS machine.

PARTICULARS| VERY IMPORTANT| IMPORTANT| NEUTRAL| NOT IMPORTANT| NOT AT ALL IMPORTANT| Installation Cost| | | | | |
Training on usage | | | | | |
Transaction time | | | | | |
Connectivity/network | | | | | |
Technical problems| | | | | |
Transaction charges | | | | | |
Delay in access to funds | | | | | |

17. Please indicate which of the following bank’s PoS machine you prefer from the pair of PoS machines presented as bellow.(‘+’ indicate that column bank is preferred over row bank and ‘-‘ indicate that row bank is preferred over column bank.)

Bank Name| SBI| HDFC| AXIS| ICICI| Other |
SBI| | | | | |
HDFC| | | | | |
AXIS| | | | | |
ICICI| | | | | |
Other| | | | | |

————————————————-
18. Any other feedback you want to give?

————————————————-

DEMOGRAPHIC PROFILE
Name of Hospital/Medicals Store: ______________________________________________ Address: ___________________________________________________________________ Name of
Respondent: ________________________________Relation: _________________ Mobile No.:_______________________ Landline No.: ______________________________ Gender:______ Age:_______ computer Literacy:_______ Size of Hospital/Medical store: Small Medium Large

OPD : __________ NO. OF BED: __________ Types of Hospital
Specialty Multispecialty Other

Chi – Square Hypothesis

H0:1 Chi-Square Tests
|
| Value| df| Asymp. Sig. (2-sided)|
Pearson Chi-Square| .926a| 3| .819|
Likelihood Ratio| 1.311| 3| .727|
Linear-by-Linear Association| .059| 1| .808|
N of Valid Cases| 196| | |
a. 5 cells (62.5%) have expected count less than 5. The minimum expected count is .02.|

H0:2 Chi-Square Tests
|
| Value| df| Asymp. Sig. (2-sided)| Exact Sig. (2-sided)| Exact Sig. (1-sided)| Pearson Chi-Square| .089a| 1| .765| | |
Continuity Correctionb| .000| 1| 1.000| | |
Likelihood Ratio| .171| 1| .679| | |
Fisher’s Exact Test| | | | 1.000| .918|
Linear-by-Linear Association| .089| 1| .766| | |
N of Valid Cases| 196| | | | |
a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is .08.| b. Computed only for a 2×2 table|

H0:3 Chi-Square Tests|
| Value| df| Asymp. Sig. (2-sided)|
Pearson Chi-Square| 20.884a| 2| .000|
Likelihood Ratio| 6.272| 2| .043|
Linear-by-Linear Association| 5.922| 1| .015|
N of Valid Cases| 196| | |
a. 3 cells (50.0%) have expected count less than 5. The minimum expected count is .05.|

H0:4 Chi-Square Tests|
| Value| df| Asymp. Sig. (2-sided)|
Pearson Chi-Square| 4.423a| 3| .219|
Likelihood Ratio| 3.116| 3| .374|
Linear-by-Linear Association| .373| 1| .542|
N of Valid Cases| 196| | |
a. 3 cells (37.5%) have expected count less than 5. The minimum expected count is .57.|

H0:5 Chi-Square Tests|
| Value| df| Asymp. Sig. (2-sided)| Exact Sig. (2-sided)| Exact Sig. (1-sided)| Pearson Chi-Square| .039a| 1| .844| | |
Continuity Correctionb| .000| 1| 1.000| | |
Likelihood Ratio| .038| 1| .846| | |
Fisher’s Exact Test| | | | .739| .531|
Linear-by-Linear Association| .039| 1| .844| | |
N of Valid Cases| 196| | | | |
a 1 cell (25.0%) have expected count less than 5. The minimum expected count is 2.71.| b. Computed only for a 2×2 table|

H0:6 Chi-Square Tests|
| Value| df| Asymp. Sig. (2-sided)|
Pearson Chi-Square| 1.074a| 3| .783|
Likelihood Ratio| .983| 3| .805|
Linear-by-Linear Association| .164| 1| .685|
N of Valid Cases| 195| | |
a. 3 cells (37.5%) have expected count less than 5. The minimum expected
count is .51.|

H0:7 Chi-Square Tests|
| Value| df| Asymp. Sig. (2-sided)| Exact Sig. (2-sided)| Exact Sig. (1-sided)| Pearson Chi-Square| 1.076a| 1| .300| | |
Continuity Correctionb| .457| 1| .499| | |
Likelihood Ratio| 1.315| 1| .251| | |
Fisher’s Exact Test| | | | .477| .265|
Linear-by-Linear Association| 1.070| 1| .301| | |
N of Valid Cases| 195| | | | |
a. 1 cells (25.0%) have expected count less than 5. The minimum expected count is 2.44.| b. Computed only for a 2×2 table|

H0:8Chi-Square Tests|
| Value| df| Asymp. Sig. (2-sided)| Exact Sig. (2-sided)| Exact Sig. (1-sided)| Pearson Chi-Square| .002a| 1| .967| | |
Continuity Correctionb| .000| 1| 1.000| | |
Likelihood Ratio| .002| 1| .968| | |
Fisher’s Exact Test| | | | 1.000| .607|
Linear-by-Linear Association| .002| 1| .968| | |
N of Valid Cases| 195| | | | |
a. 1 cell (25.0%) has expected count less than 5. The minimum expected count is 1.95.| b. Computed only for a 2×2 table|

H0:9Chi-Square Tests|
| Value| df| Asymp. Sig. (2-sided)| Exact Sig. (2-sided)| Exact Sig. (1-sided)| Pearson Chi-Square| .830a| 1| .362| | |
Continuity Correctionb| .076| 1| .782| | |
Likelihood Ratio| 1.544| 1| .214| | |
Fisher’s Exact Test| | | | 1.000| .463|
Linear-by-Linear Association| .826| 1| .364| | |
N of Valid Cases| 195| | | | |
a. 1 cells (25.0%) have expected count less than 5. The minimum expected count is .72.| b. Computed only for a 2×2 table|

H0:10Chi-Square Tests|
| Value| df| Asymp. Sig. (2-sided)|
Pearson Chi-Square| 4.220a| 3| .239|
Likelihood Ratio| 3.596| 3| .309|
Linear-by-Linear Association| .668| 1| .414|
N of Valid Cases| 195| | |
a. 3 cells (37.5%) have expected count less than 5. The minimum expected count is .41.|

One Way ANNOVA Hypothesis

|

H0:1 ANOVA|
Training on usage |
| Sum of Squares| df| Mean Square| F| Sig.|
Between Groups| 4.063| 2| 2.032| 2.726| .069|
Within Groups| 93.156| 125| .745| | |
Total| 97.219| 127| | | |

H0: 2 ANOVA|
Training on usage |
| Sum of Squares| df| Mean Square| F| Sig.|
Between Groups| 5.630| 3| 1.877| 2.350| .074|
Within Groups| 153.324| 192| .799| | |
Total| 158.954| 195| | | |

H0: 3 ANOVA|
Training on usage |
| Sum of Squares| df| Mean Square| F| Sig.|
Between Groups| 3.537| 1| 3.537| 4.416| .037|
Within Groups| 155.417| 194| .801| | |
Total| 158.954| 195| | | |

H0:4 ANOVA|
Training on usage |
| Sum of Squares| df| Mean Square| F| Sig.|
Between Groups| .039| 1| .039| .047| .828|
Within Groups| 158.915| 194| .819| | |
Total| 158.954| 195| | | |

H0:5 ANOVA|
Transaction time |
| Sum of Squares| df| Mean Square| F| Sig.|
Between Groups| 5.836| 2| 2.918| 3.558| .030|
Within Groups| 158.261| 193| .820| | |
Total| 164.097| 195| | | |

H0:6 ANOVA|
Transaction time |
| Sum of Squares| df| Mean Square| F| Sig.|
Between Groups| 1.135| 2| .568| .753| .473|
Within Groups| 94.169| 125| .753| | |
Total| 95.305| 127| | | |

H0:7 ANOVA|
Technical problems|
| Sum of Squares| df| Mean Square| F| Sig.|
Between Groups| 1.766| 1| 1.766| 2.406| .123|
Within Groups| 141.650| 193| .734| | |
Total| 143.415| 194| | | |

H0:8 ANOVA|
Technical problems|
| Sum of Squares| df| Mean Square| F| Sig.|
Between Groups| 1.644| 3| .548| .738| .531|
Within Groups| 141.772| 191| .742| | |
Total| 143.415| 194| | | |

|
|

H0:9 ANOVA|
Transaction charges |
| Sum of Squares| df| Mean Square| F| Sig.|
Between Groups| .005| 2| .002| .012| .988|
Within Groups| 26.300| 125| .210| | |
Total| 26.305| 127| | | |

H0:10 ANOVA|
Transaction charges |
| Sum of Squares| df| Mean Square| F| Sig.|
Between Groups| 1.862| 2| .931| 4.944| .008|
Within Groups| 36.342| 193| .188| | |
Total| 38.204| 195| | | |

H0:11 ANOVA|
Transaction charges |
| Sum of Squares| df| Mean Square| F| Sig.|
Between Groups| .645| 3| .215| 1.099| .351|
Within Groups| 37.559| 192| .196| | |
Total| 38.204| 195| | | |

H0:12 ANOVA|
Installation Cost|
| Sum of Squares| df| Mean Square| F| Sig.|
Between Groups| 2.559| 2| 1.280| 1.191| .307|
Within Groups| 134.308| 125| 1.074| | |
Total| 136.867| 127| | | |

H0:13 ANOVA|
Installation Cost|
| Sum of Squares| df| Mean Square| F| Sig.|
Between Groups| 5.043| 2| 2.522| 2.826| .062|
Within Groups| 172.222| 193| .892| | |
Total| 177.265| 195| | | |

H0:14 ANOVA|
Delay in access to funds |
| Sum of Squares| df| Mean Square| F| Sig.|
Between Groups| 6.039| 3| 2.013| 2.921| .035|
Within Groups| 132.308| 192| .689| | |
Total| 138.347| 195| | | |

H0:15 ANOVA|
Delay in access to funds |
| Sum of Squares| df| Mean Square| F| Sig.|
Between Groups| 2.651| 1| 2.651| 3.791| .053|
Within Groups| 135.696| 194| .699| | |
Total| 138.347| 195| | | |

H0:16 ANOVA|
fear of fraud|
| Sum of Squares| df| Mean Square| F| Sig.|
Between Groups| 15.921| 3| 5.307| 2.490| .062|
Within Groups| 407.033| 191| 2.131| | |
Total| 422.954| 194| | | |

H0:17 ANOVA|
fear of fraud|
| Sum of Squares| df| Mean Square| F| Sig.|
Between Groups| 5.495| 1| 5.495| 2.541| .113|
Within Groups| 417.458| 193| 2.163| | |
Total| 422.954| 194| | | |

H0:18 ANOVA|
fear of not able to operate pos|
| Sum of Squares| df| Mean Square| F| Sig.|
Between Groups| 2.744| 3| .915| .448| .719|
Within Groups| 390.404| 191| 2.044| | |
Total| 393.149| 194| | | |

H0:19 ANOVA|
fear of not able to operate pos|
| Sum of Squares| df| Mean Square| F| Sig.|
Between Groups| 2.929| 1| 2.929| 1.449| .230|
Within Groups| 390.220| 193| 2.022| | |
Total| 393.149| 194| | | |

——————————————–
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[ 8 ]. http://en.m.wikipedia.org/wiki/Banking_in_India#cite
[ 9 ]. http://www.vitt.in/banks.html#sthash.HDJ9mrxd.dpuf
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[ 18 ]. http://www.reportlinker.com/p0463538-summary/Global-POS-Software-Market.html [ 19 ]. http://economictimes.indiatimes.com/hdfc-bank-ltd/stocks/companyid-9195.cms http://timesofindia.indiatimes.com/topic/Big-Bazaar

[ 20 ]. www.datamonitor.com/store
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[ 27 ]. https://www.onlinesbi.com/personal
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