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Entrepreneurship is of utmost importance in a country's economic development. Starting one's own business is not easy and it is even more difficult to sustain in this highly competitive environment. This research helps understand the relative importance of challenging factors that hinders the growth of an enterprise resulting in an entrepreneur deciding whether to continue the business or exit it in the early phase itself. The analytic hierarchy process (AHP) is the technique used here to determine the relative position of these factors in persuading an entrepreneur's decision to continue or exit the business. A thorough literature review identified the key challenging factors in early-stage entrepreneurship related to, Finance, Administration, Personal, Product & Market, Environment, and Human Resources. Pairwise comparison is done by collecting the opinions of eight specialists from the industry and from academia, for formulating the reciprocal matrix and analysis using AHP. The finding of this study helps entrepreneurs identify the major hurdles and their impact on the successful launch or growth of their enterprise. On the other side, this research can also be useful for the Government and other support agencies in framing policies, to wipe out hurdles that pave way for a conducive entrepreneurial environment. [ABSTRACT FROM AUTHOR]

Foreign Direct Investments (FDI) and Foreign Institutional Investors (FII) provide capital for the growing Indian economy, to develop her infrastructure, such as sea ports, railways, roadways, airports, telecommunication, and other services. The present pace of industrialisation in India has also accelerated the need for foreign capital in the Indian context. The Indian stock market is continually responding to the changes in the foreign investment policies from time to time. This research analyses the impact of foreign capital investment inflow on the Indian stock market, with special reference to BSE Sensex and CNX Nifty. Statistical techniques such as correlation and multi-regression are used. The regression method used is Ordinary Least Squares (OLS) method or Auto-Regressive Distributed Lag (ARDL) Cointegration method, depending on whether the data is stationary, at level or not, with further analysis on long-run and short-run relationship among the variables studied. The research finds that there exists a weak negative correlation between FDI and Sensex, whereas a strong positive correlation exists between FDI and Nifty, as well as between FII and Sensex and FII and Nifty. Further, the variable FII shows a significant relationship with Sensex, whereas the relationship between FDI and Sensex is insignificant. FII also showed a significant positive relationship with Nifty, but the relationship between FDI and Nifty is insignificant. In summary, FII only showed a positive relation to stock movements, whereas with FDI, it was insignificant. Based on the empirical findings, FDI shows only long-run relationship towards the Indian Stock markets. It is recommended that the government must attract more FDI for economic growth, through industrial growth, infrastructural developments, technological upgradations, competitive advantages, and more. On the other hand, FII are directly connected to the stock market movements and also help in the growth and development of the country, in short-run as well as the long-run. This indicates that the government must adopt appropriate measures to attract more foreign institutional investors, in order to strengthen the economic development. This research contributes to the decision-making by the government regarding the promotion of FII or FDI in short-run or long-run, for accelerating growth in the economy. This finding is highly relevant in the contemporary context, as this relationship is derived for India based on recent data. [ABSTRACT FROM AUTHOR]

Byline: Suresh Subramoniam, Mohamed Tounsi, K.V. Krishnankutty This paper introduces the development aspects of an intelligent agent for mutual fund investment decisions. The success of next-generation Enterprise Resource Planning (ERP) systems mainly depends on making intelligent systems more useful for automated planning and strategic-level decisions, rather than using them merely for transaction processing at the operational level. The required knowledge for the development of the rule base has been adapted from the literature and the working of the intelligent agent prototype has been demonstrated using suitable examples. The developed system, based on fuzzy logic, takes a wide range of values as input and comes out with a unique decision, whereas an ordinary expert system would have given multiple decisions as output. Vagueness handling is possible on the internet and this helps the evolution of ERP, for which internet enabled strategic decision-making is of paramount importance.

According to Reserve Bank of India (RBI) Governor, public sector banks are having stressed accounts equivalent to over Rs.7 lakh Crores including non-performing assets (NPA) and restructured loans (News Asia, 2016). RBI has also pointed out that gross NPA of public sector banks has risen to 6.03% during June 2015 from 5.20% during March 2015. As banks have growing huge bad debts, steps are being laid down by the RBI and the government to help lending banksclean up their balance sheet by 2017. NPAs impact bank growth/stability and deteriorate profits, increase provisions, reduce reserves, affect capital adequacy, increase market borrowings, drop share values, build negative image about the economy and high interest rates. In order to compensate for the money lost in the form of interest in NPAs, banks have to charge high interest rate from other borrowers. This will have indirect impact on inflation and results in negative impact on development. Overall development of the country will also get affected due to NPA by way of unemployment, business exit due to inability to meet its loan repayment obligations, instability of the banking system, and liquidity crisis. A detailed analysis on the factors which cause NPA has become a high priority research agenda in the present day context. A questionnaire is developed for the purpose to acquire and analyse data to identify factors which cause NPA. Also, an exploratory factor analysis has been carried out to identify factors which contribute to growing NPA in financial institutions. Purpose: The purpose of this paper is to identify factors which cause non-performing assets in non-banking financial institutions. Design/methodology/approach: A questionnaire has been developed to gather data from 120 professionals who are involved in the process of granting or recovering loans in non-banking financial institutions in India and appropriate statistical techniques have been used to test for statistical significance. Findings: As a result of exploratory factor analysis, three components with corresponding factors are identified for the cause of non-performing assets in non-banking financial institutions. These are component 1 which is professional incapability of the borrower in running the firm leading to NPA, component 2 related to borrower nature in wilful default and his/her influential nature on financial institution and government resulting in NPA and, component 3 due to weak internal policy of the firm or external environment which aid non-repayment of loan. Component 1, component 2, and component 3 have nine factors, seven factors, and six factors associated with them, respectively, as explained in the paper. Research limitations/implications: The study identified the factors which are to be critically analysed prior to granting loan so that chance of the loan becoming NPA can be minimised. The success of this finding depends on suitably designed electronic credit worthiness evaluation system that evaluate the borrower. Originality/value: The identification of various factors which contribute to non-performing assets and to take suitable measures to control them is a high priority agenda for any financial institution and this research is directly oriented towards that direction. [ABSTRACT FROM AUTHOR]

According to statistica.com, the internet users at 2015 were 45% which is projected to increase by 51.5% in the year 2019 globally. With 80% users connected to social network being below 30 years and increasing every year with the rate of 55%, it becomes easy for the stakeholders to get more amounts of data. New advancements in technology and the development of Information and Communication Technologies (ICT) in the present world have had an immense impact on the business practices, strategies as well as industry structures. Tourism is a very complex industry, and managing tourist destinations is even more challenging as it involves several factors such as culture, branding and communication. Today, tourism industry is using ICT to obtain information on nearly all tourism transactions, market structure, customer needs etc in one single electronic platform. Today, concepts like Internet of Things (IoT), Business Analytic tools and the like could extract complex information from all such sources, thus helping stakeholders to make effective decisions. Very less research has been done in this direction, hence making it mandatory to unfold its full potential in tourism domain. There is also a tendency amongst stakeholders to collect and exploit huge data that are available from various systems or exchanged through web in order to help decision makers, make decisions in a very complex environment. Moreover fierce global competition within tourism industry has forced stakeholders to take innovative steps towards enhancing their competitive advantage over equally efficient rivals. The Internet of Things (IoT) is another technology embedded in organizations or destinations that utilizes ubiquitous computing, has emerged as one of the global internet based information architecture in order to enhance and enrich tourist expenditure. It has recently been accepted by all organizations ranging from telecommunications to engineering among many others. The use of Business Analytics in tourism industry starting from raw materials, till supply and distribution will not only help in measuring customer satisfaction but will also increase revenue management by coordinating inventories amongst suppliers and retailers in the industry. Tourism companies have invested heavily on technology during internet escalation as it opened up immense opportunities to improve their business strategies as well increase sale. Along with this, tremendous growth of social media and consumer generated content has altogether changed the approach of various stakeholders towards customers. It has helped to redefine the segmentation strategies and forced stakeholders to move towards disintermediation. Several studies since decades have been towards understanding the customer's needs. The process has been made easy by the social media and consumer generated content which has been very successful in getting attention of public and the community alike. This could be considered as a new form of Business Process Re-Engineering (BPR) where organizations could redesign and re engineer the process, to be able to fit into the new generation of customer centric era thus giving competitive advantage over rivals. The concept is one form of Business Analytics where in with a modified technical and organizational infrastructure the company is able to predict the potential demand of its products well in advance. This paper tries to introduce the concept of IoT, Business Analytics to tourism which can have better application value and broad development process. [ABSTRACT FROM AUTHOR]

The aim of this study is to rank branches under different zones of a Non-Banking Financial Institution based on probability of advances becoming Non Performing Asset (NPA) using Markov Chain analysis and to correlate the same with the rank based on amount of loan disbursed for each sector in a zone using Spearman's Rank Correlation Test. This is to identify the problem sectors coming under each zone which will help exercise more caution in granting advances for certain sectors that are concluded as problem sectors. [ABSTRACT FROM AUTHOR]

Most of the tour operators and travel information offices around the world find it difficult to collect relevant information from the sea of data to rate an ecotourism destination. A knowledge base created based on the opinion of domain experts can only address this problem. An attempt has been made to design and develop a sample expert system to rate the ecotourism destinations under consideration to help make the decision whether to select best destination or not. Though the literature gives the evidence of the existence of expert systems in the tourism industry in the areas of accommodation, transportation, development, wholesaling, retailing, financing and government, not much of concrete work has been found done in the development of expert systems for rating ecotourism destinations. Beaches, waterfalls, mangroves, backwaters, hill stations and rivers are to name a few such ecotourism destinations which can be rated using the developed expert system. The user friendly system accepts inputs for various ecotourism parameters, for the destination at hand, to come out with rating for the same after consulting the rule base. A sample interactive session, in the form of screen shots, is also included in this paper to gain better clarity in demonstrating the theme. Hence, the paper initially starts with a brief introduction regarding ecotourism and its role within the current scenario. It then continues with the review of literature which deals with the importance of expert systems and its influence on tourism. Section 3 explains the working of the expert system developed by the authors and its utilization for the benefit of rating eco destinations. The paper then concludes in section 4 by giving the importance of such expert systems for the development of best destinations within state or country. [ABSTRACT FROM AUTHOR]

This study helps evaluate the in-house information system implemented at a hospital from the usability point of view so that problems with users can be identified and can be corrected in the future versions of the software. Analysis is carried out to find out whether there is significant difference existing between the in-house software and other similar software based on the usability point of view. This can be used as measurement scale in comparison to other software for improvement. [ABSTRACT FROM AUTHOR]