Business Spectrum (ISSN: 2249-4804) Volume IX No. 2 July-December, 2019 An Open Access Fully Referred Peer Reviewed Bi-annual Journal of IAA South Bengal Branch (Available online at: www.iaasouthbengalbranch.org) IMPACT OF DEMONETIZATION-AN EMPIRICAL STUDY IN THE SOUTHERN PART OF WEST BENGAL Mahasweta Roy (Dutta) Assistant Professor, Department of Economics, Burdwan Raj College, Burdwan, West Bengal E-mail: [email protected] Arindam Das Professor, Department of Commerce, The University of Burdwan, Burdwan, West Bengal E-mail: [email protected] Abstract The strategic decision taken by the Government of India on November 8th, 2016, had a tremendous impact on all the sectors in India. The primary purposes of demonetization are to addressthe resolve against corruption, black money, and counterfeit notes. Not only that, this policy has created a compulsion to perform online/cashless financial transactions and to adopt digital banking services. In this paper,we have studied the effects of demonetization on different, said issues (black money, economic growth, change in perception on Banking Services of the customer, etc.) with the help of the Fuzzy Logistic method. We have identified 20 experts among 200 respondents, who have a minimum post-graduation degree.At first, Triangular Fuzzy Numbers (TFN) for each of the linguistic variables have been determined based on expert opinion. Then, Shannon’s entropy method is used in determining the weights of the said issues of demonetization. After that, theLogistic regression is applied to identify the different impact of demonetization. It has been observed that the impact of demonetization on black money and corruption is negligible. Key words: Impact of Demonetization; Fuzzy Linguistic Variable; Shannon Entropy; Logistic Regression. Introduction Demonetization is the process of stripping a currency unit of its status as legal tender. Demonetization takes place whenever there is a change in national currency. On 8th November 2016, Hon’ble Prime Minister of India, Narendra Modi, announced “demonetization,” third time in Indian history, which was a withdrawal of legal tender of Rs. 500 and Rs. 1000 from the next day, which was about 86% of the total value of the currency in circulation. In January 1946, the first demonetization was reported when Rs. 1,000, Rs. 5,000, and Rs.10,000 notes were taken out of circulation, which was reintroduced after independence in 1954. Again on January 16, 1978, the same currencies were banned, which has been marked as the second demonetization in India. Initially, it has been claimed that this action is a masterstroke to curtail the shadow economy by eradicating black money, which includes 10% to 40% of GDPand reduces the use of illicit and counterfeit cash to fund illegal 11 Business Spectrum (ISSN: 2249-4804) Volume IX No. 2 July-December, 2019 An Open Access Fully Referred Peer Reviewed Bi-annual Journal of IAA South Bengal Branch (Available online at: www.iaasouthbengalbranch.org) activity and terrorism. However, many critiques argued that demonetization is not a proper solution to grasp black money. Some of the researchers argued that the objective of demonetization was not just to confiscate black money, but the main objectives are to create more taxpayers, a bigger tax base, more digitization, and lesser cash in the system, integration of the formal and informal economy. This strategic decision taken by the Government of India created a tremendous impact on all the sectors. The banking sector was one of the major affected sectors. This policy made a compulsion to perform online/cashless financial transactions and to adopt digital banking services [Roy and Das]. In the last few years, a colossal number of papers on demonetization pointed to its positive and negative impact. Some researchers [Deodhar (2016); Shettigar et al. (2016); Veerakumar, K. (2017), etc.] visualized the impact of demonetization on removing black money and corruption. Several researchers (Kumar 2017; Gupta 2016; Ali et al. 2017) have focused on the effects of demonetization on digital banking and e-payment. Besides these, many other researchers [Gayathiri et al. (2017), Pandey and Chaudhary (2017), Dareker and Peshave (2017), Ravi (2017), Reshma et al.(2017), Kakkad (2017) etc.] claimed a significant positive relationship between demonetization and e-commerce or cashless payment for different sectors. They also tried to give thescenario of the present and future of online businesstaking into consideration the demonetizationin India. Some of the researchers [Kalyani (2016), Tiwari and Singh (2017), Mehta et al. (2016),Shendge and Shelar (2017)] have also concluded that demonetization supported cashless society in India. Some researchers [Banerjee &Chatterjee (2016); Singh (2016) etc.] have analyzed the impact of demonetization on the different industrial sectors of India (Automobile Industry etc.) Logistic regression is a multi‐purpose statistical tool. When the dependent variable in an attrition study is dichotomous (i.e., degree earned vs. not earned), logistic regression, as opposed to either multiple regression or discriminant analysis, is particularly appropriate (Hosmer &Lemeshow, 1989; SPSS, 1989). Customs logistics services generally include unloading, warehousing, and loading of goods that employs services inside and outside the organization. [Esmaeili et al. (2015)]. Ladhari (2009) has identified service quality dimensions in the logistics industry to broaden the SERVQUAL scale. Multi-Criteria Decision Making (MCDM) approach has been used for integrating the results of different dimensions to make an overall judgment. Secme et al. (2009), Wu et al. (2009), and Hu and Liao (2011) have considered the multiple criteria decision making (MCDM) models for the performance evaluation of the bank branches. Fuzzy logic is a mathematical term, whose use is observed by many researchers in differentfields during different time periods. A significant change has been occurred by the use of fuzzy logic. Due to the use of fuzzy logic, many things have become more comfortable and this has helped to savetime, money and energy. LottiZadeh first proposed fuzzy logic in 1965. Before Zadeh, many efforts were made in this field by many researchers like Plato, Hegel, Marx, Lukasiewicz, etc. Fuzzy logic has been used in different sectors by several researchers [Davidson and Haywar, 2003;Ganesa, 2015, etc.]. Hung and Chen (2009) have proposed a new fuzzy TOPSIS 12 Business Spectrum (ISSN: 2249-4804) Volume IX No. 2 July-December, 2019 An Open Access Fully Referred Peer Reviewed Bi-annual Journal of IAA South Bengal Branch (Available online at: www.iaasouthbengalbranch.org) decision-making model using entropy weight for dealing with multiple criteria decision- making problems.The primary purpose of this study is to examine the overall impact of demonetization on said issues based onthe expert opinion of the southern part of West Bengal and also to find out the overall impact of demonetization from the viewpoint of the short and long run. Objectives The main objective of our study is to evaluate the overall impact (short and long term) of demonetization. Besides this, other objectives are - (i) To find out the overall impact of demonetization on said issues based onthe expert opinion (Fuzzy Methods) of the southern part of West Bengal. (ii) to develop a logistic regression for the impact of demonetization to identify respondents' satisfaction after three years of this policy adoption by the government, (iii)to identify the different implications of demonetization of selected issues (Black money and corruption, terrorism, digitization, economy, social life) Database and Methodology According to the objectives of our study, as mentioned earlier, firstly, we have collected the data by using a stratified random sampling method from 200 respondents (who have minimum post-graduation degree). Next, we have identified 20 individuals as an expert from 50 respondents belonging to the group of academicians, lawyers, doctors, senior Government officials, etc. Cronbach’s alpha (α) test has been measured to test the reliability of each dimension (black money and corruption, terrorism, digitization, economy, and social life), which are selected for observing the impact of demonetization.To find out the impact of demonetization for different selected dimensions (black money and corruption, terrorism, digitization, economy, and social life), we have developed a logistic regression equation. Step 1: To determine the fuzzy number for the linguistic variable, experts’ opinions have been used, and they have been asked to assessthe spectrum of a linguistic variable from 0 to 10. Triangular fuzzy numbers (TFN) for each of the linguistic variables have been determined. In this study, five spectrums namely, Strongly Agree (STA), Agree (AE), Neutral (NL), Disagree (DE) and Strongly Disagree(STD) have been used to measure the impact of demonetization on the view of the respondents of the respondents against each selected criteria (24) about demonetization.After obtaining the opinion on five spectrums from 20 experts, the next step is to find out the triangular membership function which is calculated by using the following formula: 13 Business Spectrum (ISSN: 2249-4804) Volume IX No. 2 July-December, 2019 An Open Access Fully Referred Peer Reviewed Bi-annual Journal of IAA South Bengal Branch (Available online at: www.iaasouthbengalbranch.org) Where, a= lower bound, b= middle bound, and c = upper bound. A