Subjective and objective grades for audio quality measurement.
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
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In multilevel steganography, at least two embedding methods are used in such a way that the second method may use the first method as a carrier. This approach has several potential benefits in hidden communication. It can be used to increase the level of security while transmitting the confidential information over public channels. It can also be used to provide two or more information hiding solutions simultaneously. Another important benefit is that the lower level embedding/extracting method and higher level embedding/extracting method are interrelated in terms of functionality and this makes the hidden communication harder to detect. If the cover object is interpreted by any adversary, only a decoy message or a partial message will be obtained.
\nThe main aim of steganography is to hide secret information in digital cover. The alteration of the cover caused by embedding secret information remains invisible to the third party opponents. This is possible by designing an appropriate embedding algorithm and choosing a suitable cover. Therefore, there will be no significant dissimilarity between original cover and embedded cover. So, secret information not only is hidden inside the cover, but the fact of the secret information communication is also hidden. Each steganographic method may be characterized by following requirements. First, undetectability which is defined as the inability of detecting secret information inside the embedded cover. Actually, the distortion of the embedded cover convinces the opponent to analyze the statistical properties of the cover and compare them to the distinguishing properties of that cover. Therefore, imperceptibility or inaudibility is directly relational to the undetectability. Second, embedding capacity is defined as an amount of secret information which can be transmitted using a particular algorithm per unit of time. Third, steganographic cost, which defines the amount of alteration of the cover caused due to the secret information embedding method. The steganographic cost depends on the cover used as a carrier and also depends on embedding algorithm used.
\nFor each steganographic method, there is always a trade-off between maximizing hiding capacity and remaining secret information undetected. Therefore, a certain level of tuning between embedding capacity and undetectability is required. If the embedding and extracting algorithm remains secret to the opponent, it can be used to transmit secret information freely. On the other hand, if the both algorithms are known to the opponent, anybody may be able to extract the secret information. This type of problem may be resolved by using the different encryption algorithms appropriate for a particular application. The encryption algorithm AES may be used to encrypt secret information before embedding it to the cover. Therefore, in this case, extracted information will not be readable by the opponent. There is a problem with this method, because the encryption key and the encrypted information are communicated using the same embedding technique. Thus, the encryption key and the secret information both will be revealed on successful detection. Alternatively, embedding capacity may be reduced due to embedding of the encryption key in cover object. The multilevel steganography was originally proposed by Al-Najjar for image steganography in [1]. The main idea in this paper was to hide a decoy image into LSB positions of the cover and the original secret information is embedded into the LSB positions of the decoy image.
\nEncryption and steganography are two general methods for hiding secret information [2, 3, 4]. Information is hidden using an encoding method that only authorized persons with the proper key can decode it in encryption. On the other hand, steganography hides secret information such a way that hidden information is imperceptible to the regular observer. The secret information can be embedded directly or some transformation can be applied to it before the embedding process. Generally, transformations include encryption, compression, transformation or a combination of digital transformation techniques. In [4], Vitaliev proposed two methods of information hiding. In the first method, plain text is hidden into an audio signal and in the second method; an audio file is hidden in an image object. In [5], Petitcolas et al. presented a method where a text object is hidden into another text object. In [6], Al-Najjar et al. proposed a method where an audio file is embedded in an image after performing encryption and compression. In [7], Marvel proposed a hidden communication method by hiding of an image into another image in his Ph.D. Dissertation. In [8], Solanki presented a multimedia data hiding technique to hide an image into a video file in his Ph.D. Dissertation.
\nIn [9], Lou et al. proposed an information hiding technique to protect a medical information. This paper suggests a multiple-layer data hiding technique in spatial domain. The reduced difference expansion method is utilized to embed the bit stream in the least significant bits (LSBs) of the expanded differences. A large amount of data is embedded in a medical image by using this method where quality of the image is also be maintained. Moreover, the original image can be restored after extracting the hidden data from the stego-image.
\nCocktail party effect is used in audio steganography system where blind key concept is applied to resist the attack in the system [10]. Private key on the domain of cosine discrete transform (CDT) is used in steganographic algorithm in [11]. A new quantization technique is used in a steganographic method and the algorithm is designed based on DCT in [12]. A DNA structural concept is utilized in audio steganography in [13]. A novel audio steganography is designed using ZDT in [14]. Here encryption is done using indexed based chaotic sequence.
\nIn this chapter, multilevel audio steganography is discussed to address the above stated problems. The proposed approach extends the concept of steganography to use it in more general purpose.
\nMultilevel steganography can be categorized as per the requirement of its application. Embedding capacity is the basic requirement in some of the applications where imperceptibility may be compromised in a certain level. On the other hand, imperceptibility is the main requirement in some of the applications where embedding capacity may be compromised in a certain level. So, the multilevel steganography may be classified as like below:
\n(i) Single message multiple covers—multilevel steganography denoted as
A message is embedded in multiple covers using several embedding functions to increase the level of security of the system. This approach provides better imperceptibility, but embedding capacity may be compromised in most of the cases.
\n(ii) Single cover multiple messages—multilevel steganography denoted as
Multiple messages are embedded in a single digital cover using several related embedding functions to increase the embedding capacity of the system. This approach provides better embedding capacity, but imperceptibility may be compromised in most of the cases.
\nIn this section, TYPE-I and TYPE-II types of multilevel steganography models are discussed [15].
\nSuppose, the Message is denoted as M, the Covers are denoted as \n
The message M is passed through the transformation \n
Message embedding and extracting operations are performed by the embedding and extracting function pairs embed() and extract() and denoted by \n
\n\n
The TYPE-I multilevel steganography model (for i = 3) is presented in Figures 1 and 2.
\nTYPE-I multilevel steganography model at the sender end for level = 3.
TYPE-I multilevel steganography model at the receiver end for level = 3.
At the sender end, in phase 1, secret message \n
At the receiver end, according to the above 2 level embedding process, in phase 1, stego-object \n
The cover is a grayscale image (\n
In this step, the cover is an audio signal (\n
The Intermediate Cover (\n
The Intermediate Cover (\n
Suppose, the Cover is denoted as \n
The messages \n
TYPE-II multilevel steganography model at the sender end for level = 3.
TYPE-II multilevel steganography model at the receiver end for level = 3.
At the receiver end, according to the above 2 level embedding process, in phase 1, message \n
The cover is an audio clip (\n
In this step, the cover is an Intermediate Cover or stego-cover (\n
The Intermediate Cover (\n
The Intermediate Cover (\n
Proposed algorithm has been tested on 10 audio sequences from different music styles (classic, jazz, country, pop, rock, etc.). All the Clips are 44.1 kHz sampled mono audio files, represented by 16 bits per sample, and length of the clips ranges from 10 to 20 seconds. An image and the all audio clips are used to test TYPE-I type of algorithm and all the audio clips are used to test TYPE-II algorithm.
\nBasic requirement is the imperceptibility in most of the applications, i.e., after hiding secret messages in audio signals; the quality of the embedded audio signals should remain same as original audio signals. Here, Subjective Difference Grade (SDG), Objective Difference Grade (ODG) and Signal-to-Noise Ratio (SNR) is used to measure the imperceptibility of the proposed method. The SDG and ODG listening tests use the 5-grade scale shown in Table 1.
\nAudio standard | \nSubjective difference grade (SDG) | \nObjective difference grade (ODG) | \n
---|---|---|
Indistinguishable | \n5 | \n0.0 | \n
Distinguishable, but not aggravating | \n4 | \n−1.0 | \n
Slightly aggravating | \n3 | \n−2.0 | \n
Aggravating | \n2 | \n−3.0 | \n
Very aggravating | \n1 | \n−4.0 | \n
Subjective and objective grades for audio quality measurement.
The ODG measurements of different audio clips are provided using the advanced ITU-R BS.1387 standard [16] and are calculated using the Opera software [17] which is implemented by maintaining ITU-R BS.1387 standard. ODG values for TYPE-I and TYPE-II approaches are reported in Tables 2 and 3 and respectively for different types of audio signals. The ODG values for TYPE-I model are −0.49 to −0.64 and the ODG values for TYPE-II model are −0.58 to −0.72.
\nAudio types | \nObjective difference grade (ODG) | \nSubjective difference grade (SDG) | \nSignal-to-noise ratio (SNR(dB)) | \n
---|---|---|---|
A1 | \n−0.51 | \n5.0 | \n92.25 | \n
A2 | \n−0.63 | \n4.9 | \n91.41 | \n
A3 | \n−0.61 | \n4.9 | \n91.63 | \n
A4 | \n−0.52 | \n5.0 | \n92.43 | \n
A5 | \n−0.49 | \n5.0 | \n92.54 | \n
A6 | \n−0.50 | \n5.0 | \n92.35 | \n
A7 | \n−0.64 | \n4.9 | \n91.55 | \n
A8 | \n−0.59 | \n4.9 | \n91.57 | \n
A9 | \n−0.49 | \n5.0 | \n92.36 | \n
A10 | \n−0.53 | \n4.9 | \n91.78 | \n
ODG, SDG & SNR values for different audio clips (TYPE-I, level = 2).
Audio types | \nObjective difference grade (ODG) | \nSubjective difference grade (SDG) | \nSignal-to-noise ratio (SNR(dB)) | \n
---|---|---|---|
A1 | \n−0.61 | \n4.9 | \n90.15 | \n
A2 | \n−0.72 | \n4.8 | \n89.31 | \n
A3 | \n−0.70 | \n4.8 | \n88.93 | \n
A4 | \n−0.61 | \n4.9 | \n90.41 | \n
A5 | \n−0.59 | \n4.9 | \n90.22 | \n
A6 | \n−0.60 | \n4.9 | \n90.16 | \n
A7 | \n−0.68 | \n4.8 | \n89.25 | \n
A8 | \n−0.69 | \n4.8 | \n89.36 | \n
A9 | \n−0.58 | \n4.9 | \n90.19 | \n
A10 | \n−0.63 | \n4.8 | \n89.14 | \n
ODG, SDG & SNR values for different audio clips (TYPE-II, level = 2).
Subjective quality measurements [18, 19] have been performed to evaluate the imperceptibility of our proposed data hiding scheme. The output of the subjective tests is an average of the quality ratings called a Mean Opinion Score (MOS). SDG values for TYPE-I and TYPE-II approaches are reported in Tables 2 and 3 respectively for different types of audio signals. The SDG values for TYPE-I model are 4.9–5.0 and the SDG values for TYPE-II model are 4.8–4.9.
\nThe signal-to-noise ratio (SNR) value is used to make the difference between the original and embedded audio signal [20]. Normally, if the SNR value is higher than 50 dB, then the secret data which are hidden in the audio signal are imperceptible to the human auditory system. The SNR values for TYPE-I and TYPE-II approaches are measured using equation no. (1) and are reported in Tables 2 and 3 respectively for different types of audio signals.
\nThe ODG, SDG, and SNR values are evaluated for different audio signals. Here, 2 level multilevel steganography is performed for TYPE-I and TYPE-II models. The results are presented in Tables 2 and 3 of TYPE-I and TYPE-II models respectively. For simplicity, 10 audio clips are denoted as A1, A2, A3, A4, A5, A6, A7, A8, A9 and A10.
\nOne of the basic requirements of the secret communication using steganography is increasing the embedding capacity by keeping the imperceptibility in a desired level. In the proposed system, if TYPE-I approach is followed, embedding capacity is not so much desired level, because imperceptibility given higher priority. But, if TYPE-II approach is followed, multiple messages may be embedded in a single cover object by designing appropriate transforms and embedding functions.
\nThe embedding capacity is measured by the number of bits that can be hidden into the audio signal per unit of time. Suppose, D is the duration of the original audio clip in seconds and B is the number of secret information bits. Now, the capacity is measured as:
\nIn this work, the frequency of the carrier signal is fixed, i.e., 44.1 Kz is considered. The sample rate 44.1 kHz means 44,100 samples per second in one channel.
\nSecurity is another very important requirement of hidden communication using steganography. A data hiding method is said to be secured if an adversary would not be able to detect or modify or remove the hidden information in the embedded object. To measure the security of the proposed technique, following scenarios may be considered:
The adversary has no information about the hidden information in the host object. So, the proposed method is secure.
The adversary has no idea about the embedding or extracting algorithm. Therefore, the proposed method is secure.
The adversary has information only about the embedding and extracting algorithm. In this case, the adversary cannot precede the extraction operation without knowing the actual location is used to hide information.
By minimizing the bit flipping during the embedding process is normally guaranteed that the algorithm designed to estimate the hidden data based on statistical analysis may be effectively disabled.
\nIn TYPE-I approach, a message is hidden in a cover object and that stego-cover object is hidden in another cover object, and so on. This approach increases the level of security of the system. Again, the number of levels is used during the embedding process in multilevel steganography is very important information at the receiving end. That means, security may be increased by varying the number of levels during embedding process. Along with this, any of the encryption algorithms may be used at a transformation phase of the system to increase the security of the system.
\nIn this section, a comparative study is performed with the very recent works on audio steganography as well as audio watermarking proposed by different authors. Actually, impartial comparison is very difficult, because every approach have its own characteristics and also designed to fulfill certain basic requirement. Anyway, most of the algorithm has some common characteristics like embedding capacity, imperceptibility etc. Here, comparisons are performed based on embedding capacity and imperceptibility (SNR & ODG) of the system and reported in Table 4.
\nAlgorithm | \nCapacity (bps) | \nSNR (dB) | \nODG | \n
---|---|---|---|
Xiang et al. [21] | \n2 | \n42.8–44.4 | \n−1.66 < ODG < −1.88 | \n
Mansour et al. [22] | \n4.3 | \n29.5 | \nNot reported | \n
Fallahpour et al. [23] | \n3 k | \n30.55 | \n−0.6 | \n
Fallahpour et al. [24] | \n2–6 k | \nNot reported | \n−0.6 < ODG < −1.7 | \n
Fallahpour et al. [25] | \n11 k | \n30 | \n−0.7 | \n
Kang et al. [26] | \n64 | \n30–45 | \n−1 < ODG | \n
Nishimura et al. [27] | \n8 | \nNot reported | \n−3 < ODG < −1 | \n
Proposed | \n44,100 | \n92.54 | \n−0.49 < ODG < −0.64 | \n
Comparative studies among different works.
The method in [21] provides a significant performance in the different properties of the data embedding technique. The method offers moderate data hiding capacity solutions for data hiding in audio file even though the imperceptibility in terms of SNR and ODG is below average in some of the issues. The important achievement of this scheme is robustness against different attacks such as echo, filtering, and noise added. The method in [23] achieves a low embedding capacity for the three audio files considered. The imperceptibility in terms of SNR is below average, but the imperceptibility (ODG) is moderate in this scheme. This scheme has a good performance against compression and the maximum of BER against this is about 1%. The algorithms in [24, 25] offer low embedding capacity, good transparency, and reasonably robustness against selected attacks. The scheme in [24] provides very a low data hiding rate, high distortion, and very robust scheme, while that in [25] provides very low embedding capacity, highly distorted signals (SNR is 30 dB), and moderate robustness against some attacks.
\nThe most important achievement of the proposed method is better imperceptibility in terms of SNR and ODG with higher embedding capacity. The comparison presented in Table 4 demonstrates the superiority in both capacity and imperceptibility of the proposed method with respect to the schemes discussed in the literature. The proposed method can hide much more information by introducing less distortion in the audio file. In brief, the proposed method achieves higher embedding capacity if we compare it to methods with similar imperceptibility.
\nThe data presented in Table 4 confirms that the proposed method have better performance in terms of embedding capacity and imperceptibility.
\nIn this chapter, two multilevel steganography models are proposed. Normally, the requirement of data hiding application varies from application to application. The proposed models are designed such a way that the customization may be done as per the requirement of a particular application. That means, number of embedding and extracting levels, number of messages to be hidden, and number of cover objects to be used etc. are customizable. The suggested model enhances the security level of the steganography technique in terms of imperceptibility as well as capacity. The stego-object, usually does not seem suspicious, since it looks similar to the original object to the general observer. An adversary may be satisfied with the decoy as the hidden message and may not use additional tools to look further. The authorized receivers have information about the hidden message, as well as the information required to extract the message. Hence, it can be concluded that the proposed models enhanced potentially more security to information hiding.
\nFirst and most of all, I thank God, the almighty for giving me this opportunity and granting me the ability to carry on the process successfully.
\nI take this opportunity to show my gratitude to all my teachers, starting from my school days to this day, who have guided me throughout my pursuit for knowledge, who have given me the opportunity to express my thoughts, who gave patient listening to my ideas even though many a time it was unreasonable. This book chapter looks like in its current form due to the guidance and support of several people. I am especially grateful to my supervisor Dr. Debasree Chanda (Sarkar), for her warm encouragement, critical comments, and thoughtful guidance. I also owe thanks to Dr. Partha Pratim Sarkar, Professor, for his insightful discussion, offering valuable advice, encouraging comments, and suggestions throughout this work. Despite his extremely busy schedule, he has gone through the thesis in depth.
\nLastly but not the least, I acknowledge the Academy of Technology, Hooghly, Kolkata, India.
\nReplace the entirety of this text with the ‘conflict of interest’ declaration.
Women consist of half of the world population and it is an open secret that an independent and educated woman leads an educated and self-reliant family, which is further translated into a liberal, independent and an educated society. As per census of 2011, in India, the female population was 586.4 million (48% of the total population). Out of these total female population, 405.1 million (69% of the total female population) were living in rural areas [1]. Without women contribution or support, it is not possible to develop the country as a whole because half of the nation’s human resources is women. Therefore, women are playing a very important role in the socioeconomic development of the country.
\nThe constitution of India honours both men and women with equal rights. But women are not treated as equals as men [2]. Certain barriers still exist between men and women. The literacy level of the rural women population is less than that of urban women population. During 2009–10, 46.7 % of rural women population was illiterate as reported by the National Sample Survey Office [3].
\nGenerally, the rural women face problems with regard to medical facilities, health care, malnutrition, environment, etc. Besides, finance is an essential part of their life. Hence, different financial inclusion programmes were launched by the Government for the rural population at different periods. Financial literacy is an integral part of the financial inclusion programme. It was introduced to rural women for the purpose of understanding the financial concept thoroughly and guiding them to take a decision on financial aspects [4]. This programme cultivates saving habits among the rural women. Also, it helps them to understand the financial affairs and motivate them to invest the savings in a profitable avenue.
\nNow-a-days, the financial institutions are offering a variety of schemes/products to the public. A careful selection of the product is important; otherwise, it leads to loss of their hard earned money. A large number of literature reports [5] that in India, financial literacy is not well developed particularly in rural areas and they are still waiting for revolutionary push. The purpose of the study is to investigate whether the learned knowledge on financial literacy by the Indian rural women population helps to invest their hard earned saving money in the profitable ventures or not?
\nA study on financial awareness among the salaried class people was carried out by Bhushan [6]; Umamaheswari and Kumar [7]. The studies reveal that certain demographic factors like general education level, gender, income level, employment etc. affect financial literacy. The financial literacy level between the salaried class persons is also varied. Vasagadekar [8] has informed that a working woman who has less knowledge in finance, finds difficulty in managing a portfolio. Hence, they should evaluate the available avenues before making investment [9].
\nSubha and Priya [10]; Agarwalla et al. [11] have reported that there are certain factors which affect financial literacy level viz. general literacy, income level, age, employment and place of work. Hence the government should take some sort of remedial measures to enhance financial attentiveness.
\nA variety of investment and saving products are available in the financial market, but people are still least aware. Therefore, a proper awareness about the products, among the public either through TV or radio is required as reported by Trivedi and Trivedi [12]; Goel [13]; Jappelli and Padula [14]; Kudva [15]. Awareness about the various investment avenues brings positive change in the lifestyle and investment pattern of people [16]. Only a few investors are aware about the industrial securities and most of the investors believe that such securities are insecure one [17].
\nA systematic analysis of the behaviour of rural and urban investors in terms of education, health care services, financial activities and priorities was carried out by Kumar and Mukhopadhyay [18]. The analysis reveals that both groups made an investment according to their requirements and rural investors’ especially rural women need certain help for making the financial decision.
\nThe awareness level of investors in a metro city is found to be higher than the investors in rural area [19]. The reason is that the metro investors are more concerned with financial gateways; news channels and finance or market related programs. In Pakistan, a study on impact of financial literacy on investment decisions was conducted. This study reveals that financial literacy has a positive trend on agreeableness, extraversion, openness and negative trend on neuroticism [20].
\nThe difference between the saver and investor was clearly mentioned by Thilakam [21]. The investment decision made by the investors is fully based upon risk bearing, yield amount and their future plan [22, 23]. If they are aware of the basic concepts of finance under present condition, it helps them to identify the best investment opportunities [24].
\nBhattacharya [25] has stressed that the financial literacy is an important requirement for resource planning. The investment behaviour of investors in India varies from time to time. Thulasipriya [26] has informed that in earlier stages, the investors invested in physical asset than financial assets. Later stage, their preference changed from physical assets to financial assets. Sharma and Pandey [27], Palanivelu and Chandrakumar [28] have expressed that Corporate bonds; post-office schemes; debentures; and bank deposits are the most promising investment avenues for the investors and more number of investors prefer these avenues. The rural people in India prefer to invest their savings in bank, insurance and post office only not in Public Provident Fund, Mutual Funds and Industrial Securities for the purpose of safety and security [29].
\nFinancial literacy is an energetic universal concern. Availability of large number of financial resources, different financial schemes and low level of financial awareness has led to financial literacy. Earlier studies have mainly concentrated on investment behaviour of women. Most of the studies concluded that investors are interested in investing their savings in banking, insurance and post office schemes. No in depth study has been carried out on impact of financial literacy on investment behaviour of rural women. Scope of this study is to develop a model for assessing the level of financial literacy and to apply the same among the rural women of Jalandhar district in the state of Punjab.
\nThe main objective of the present study is to assess the relationship between the financial literacy programme and the investment behaviour of rural women. The sub objectives of the present study are:
Identify the level of financial knowledge obtained by rural women through the financial literacy programme.
Analyse the awareness of rural women towards the available investment avenues.
Ascertain the push and pull factors for rural women with regard to savings and investment behaviour.
Develop financial literacy score.
Jalandhar district of Punjab has been selected as a sample district for this study. This district has five tehsils namely Jalandhar 1, Jalandhar 2, Nakodar, Phillour, and Sahakot. The present study attempts to evaluate the impact of financial literacy programme on investment behaviour of rural women. Hence, 2.5% of the potential rural women savers have been selected from each tehsil randomly. The total sample size is 335 rural women respondents.
\nIn respect of a wide diversity in socio-economic factors, the sample was drawn out of five tehsils in terms of rural women population across Jalandhar district. Data was collected through questionnaire. Age, occupation, education level, number of dependents, monthly income of family and the type of family were demographic traits on which data was collected. In addition to demographic attributes, the target group was required to respond on questions related to financial behaviour, financial planning and financial literacy. Details about the demographic variables of the respondents are shown in Table 1.
\nVariable | \nDetail | \nFrequency | \nPercentage | \n
---|---|---|---|
Age (in years) | \n20 and less | \n0 | \n0 | \n
21–30 | \n43 | \n12.8 | \n|
31–40 | \n126 | \n37.6 | \n|
41 and over | \n166 | \n49.6 | \n|
Education level | \nNo formal education | \n43 | \n12.8 | \n
Primary school | \n109 | \n32.5 | \n|
Matriculation | \n78 | \n23.3 | \n|
Diploma | \n52 | \n15.5 | \n|
Graduate/post-graduate | \n53 | \n15.8 | \n|
Marital status | \nUnmarried | \n28 | \n8.4 | \n
Married | \n230 | \n68.7 | \n|
Widowed | \n77 | \n23 | \n|
No. of dependents | \nTwo | \n3 | \n0.9 | \n
Three | \n17 | \n5.1 | \n|
Four | \n49 | \n14.6 | \n|
Five and more | \n266 | \n79.4 | \n|
Monthly income | \n1001–3000 | \n28 | \n8.4 | \n
3001–5000 | \n56 | \n16.7 | \n|
5001–10,000 | \n232 | \n69.3 | \n|
More than 10,000 | \n19 | \n5.7 | \n|
Family type | \nNuclear family | \n188 | \n56.1 | \n
Joint family | \n147 | \n43.9 | \n
Details of demographic variable.
Source: Primary data.
The largest numbers of investment avenues are available in financial markets to serve the desires of investors. Thousands of investment schemes are available in the market. The art of rational investment decision is maximum returns with minimum of risk. Investment pattern differs from one another in terms of invested amount, risk bearing capacity and expected returns. In recent times, awareness about financial products has become an issue of discussion in financial markets. Past studies have revealed that people prefer to invest in traditional safe investment avenues. Bank, insurance and post office investment schemes were the most preferred investment avenues. There is an information gap between financial markets and a financier and due to this a majority of investor does not use modern investment products. Data collected under this section confirms that there is imbalance in- between traditional and modern investment avenues. As we can figure out easily that awareness level of respondents is fairly high in banking avenues, post office schemes, insurance schemes and other traditional avenues like gold/silver and real estate opportunities. On the other hand as evidenced in Table 2, there is lack of awareness in Chit Fund Schemes, Bonds, Debentures, Public Provident Fund, National Savings Certificate, Government Securities and Forex Market and Commodity Market. It is also stated by Mohd and Verma [29].
\nFinancial product | \nFamiliar | \nNon-familiar | \n||
---|---|---|---|---|
Frequency | \nIn percentage | \nFrequency | \nIn percentage | \n|
Savings account | \n334 | \n99.7 | \n1 | \n0.3 | \n
Bank fixed deposit | \n333 | \n99.4 | \n2 | \n0.6 | \n
Public Provident Fund (PPF) | \n212 | \n63.3 | \n123 | \n36.7 | \n
National Saving Certificate (NSC) | \n210 | \n62.7 | \n125 | \n37.3 | \n
Kisan Vikas Patra (KVP) | \n259 | \n77.3 | \n76 | \n22.7 | \n
Post office savings | \n330 | \n98.5 | \n5 | \n1.5 | \n
Government securities | \n206 | \n61.5 | \n129 | \n38.5 | \n
Mutual funds | \n260 | \n77.6 | \n75 | \n22.4 | \n
Life insurance | \n329 | \n98.2 | \n6 | \n1.8 | \n
Debentures | \n195 | \n58.2 | \n140 | \n41.8 | \n
Bonds | \n194 | \n57.9 | \n141 | \n42.1 | \n
Equity share market | \n248 | \n74 | \n87 | \n26 | \n
Commodity market | \n96 | \n28.7 | \n239 | \n71.3 | \n
Forex market | \n135 | \n40.3 | \n200 | \n59.7 | \n
Real estate | \n315 | \n94 | \n20 | \n6 | \n
Gold/ Silver | \n308 | \n91.9 | \n27 | \n8.1 | \n
Chit fund | \n208 | \n62.1 | \n127 | \n37.9 | \n
Awareness about investment products.
Source: Primary data.
In terms of familiarity with financial products, data collected from the respondents revealed that rural female are most familiar with savings account (99.7%), followed by fixed deposit (99.4%), post office schemes (98.5%), life insurance (98.2%), real estate (94%) and gold/silver (91.9%) trading options. Furthermore, it is reported that rural females are most familiar with bank, post office, insurance and other traditional avenues of investment. Although, data do notreveal high familiarity of rural females with Debentures (58.2%), Bonds (57.9%), Forex Market (40.3%) and Commodity Market (28.7%) in moderate risk avenues. But marginal divergence is found among respondents about few investment avenues like Mutual Funds (77.6%), Equity Share Market (74%), Public Provident Fund (63.3%), National Savings Certificate (62.7%), Chit Fund (62.1%) and Government Securities (61.5%).
\nInvestment pattern refers to the outline of savings into various financial products with the objective of risk diversification or high expected profits. The very first step for voyage investment is savings. Investor can take the benefit of large chunk of financial products only if he/she is aware about the relevance of portfolio or diversified pattern of savings. The current investment pattern of selected rural women respondents are represented in Figure 1.
\nAttitude of rural women towards various avenues. Source: Primary data.
From Figure 1, it is revealed that most of the female respondents are investing in Savings Account (96.7%), followed by Bank Fixed Deposit (84.2%) and Life Insurance (81.5%). These three are found to be the most prominent investment avenues in pattern of rural females. Post Office Savings (56.4%), Mutual Funds (57.3%) and Gold/Silver (53.1%) are found less popular in the investment pattern of rural females. On the other hand, KisanVikasPatra (2.7%), Government Securities (10.1%), Debentures (6.3%), Bonds (4.2%), Commodity Market (2.1%), National Saving Certificates (0.9%), Chit Fund (0.6%) are preferred by very few persons to diversify their portfolio.
\nThe reason for the selection of the financial instrument by the rural women is presented in Figure 2.
\nReason behind financial selection. Source: Primary data.
From Figure 2, it can be concluded that familiarity with any financial institution influences most of the times investment decisions of investors. 34% of total females have selected a financial institution because of familiarity, followed by the reason of assured returns. 23% of respondents has selected only those financial products which assure return on their investment quantum. 22% of respondents have preferred to select a number of financial products. Here, portfolio diversification is the main aim of investment. Interestingly, safe and low risk factors have the lowest preferred reason for financial selection. Only 21% of people has invested in safe and low risk investment avenues.
\nFinancial and investment behaviour of a person is a vital component in a given financial environment. Investment pattern is affected by the awareness about the financial markets and the ability to make rational decisions. Hence, the variable behaviour prior to the selection of investment policy was investigated for this research. Data related to behaviour and rationality prior to financial selection is presented in Figure 3.
\nBehaviour of rural women with reference to product choice. Source: Primary data.
\nFigure 3, illustrates the behaviour-wise allocation of responses. Among 335 households’ surveyed 36.40% of respondents have preferred different financial or investment policies from one company only. It is clear that most of the respondents trust in the investment policies of only one company. 34.30% of responses belongs to those households who never compare different investment policies of one or more companies. They prefer to invest in pre-selected avenues. Consequently, 20.60% households compare various products from more than one company and 8.70% of sample population are found to be unaware of the availability of different financial avenues in the market.
\nFinancial literacy is the ability of a layman to understand the nature of finance and earning potential of his savings. In true sense, financial literacy allows a person to take a rational financial decision in specific areas like property or real estate matters, tax planning, banking and insurance and capital markets, etc. To achieve financial goals, basic knowledge about financial matters becomes the essential part of today’s world; not only for the investors of stock market; but also for the persons having saving habits. It can be defined as the tricks used by the finance player to manage their earnings in terms of savings, budgeting, investing and insuring etc. Definition of financial literacy also declares that financially knowledgeable people are well aware about money management concepts and know in which manner financial institutions work. The financial literacy score is a platform to identify trends of financial awareness among individuals. To depict awareness trends in basic financial matters, financial literacy index of rural women was calculated. The financial literacy index is prepared on the basis of following basic financial literacy indicators:
Simple interest rate
Compound interest rate
Affordability
Financial security
Portfolio diversification
Loan ideology
Financial awareness to life circumstances
Product choice
Credit card ideology
Basic taxation ideology
In order to determine the financial literacy level, a set of question was asked and based upon the response, a rank was assigned. The rank “0” is assigned to the respondent who does not have knowledge about financial literacy. The ranks “1” and “2” are assigned for those having average and thorough knowledge on financial activities, respectively.
\nAfter assigning rank for the all the parameters, the total financial literacy score for the individual respondent is calculated as follows:
\nwhere ‘actual value’ is the sum of ranks the individual respondent scored, ‘maximum value’ is the theoretical maximum, here it is = 20, (that is 10 × 2) and ‘minimum value’ is the theoretical minimum, here ‘0’ (i.e., 10 × 0).
\nIn order to get the net score, Total of the literacy score all the respondents is divided by the total number of the respondents.
\nIf the value is 0, it indicates that the financial literacy level is zero. Between 0.1 and 0.33 it specifies that level of financial literacy is at a minimum. Between 0.34 and 0.66 the level of financial literacy is of medium level. Between 0.67 and 0.99 the level of financial literacy is high and if the value is 1, it indicates that complete financial literacy level is achieved.
\nThe calculated value of financial literacy is 0.69552. This revealed that the overall level of financial literacy is encouraging in rural parts of Jalandhar district. This indicates that efforts of government and non-government organisations are leading to a positive change. The results of financial literacy index are given in Table 3 and Figure 4.
\nRespondent | \nValue for the respondent’s response for different parameters | \nActual score for individual respondent’s (maximum value 20) | \nFinancial Literacy score for individual respondent’s | \n|||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Simple interest rate | \nCompound interest rate | \nAffordability | \nFinancial security | \nPortfolio diversification | \nLoan ideology | \nFinancial awareness to life circumstances | \nProduct choice | \nCredit card ideology | \nBasic taxation ideology | \n|||
(A) | \n(B) | \n(C) | \n(D) | \n(E) | \n(F) | \n(G) | \n(H) | \n(I) | \n(J) | \n(H) | \n\n\n | \n|
Sum of (A to J) | \n||||||||||||
1 | \n0 | \n0 | \n1 | \n2 | \n2 | \n0 | \n0 | \n2 | \n0 | \n2 | \n9 | \n0.45 | \n
2 | \n1 | \n0 | \n2 | \n2 | \n2 | \n1 | \n1 | \n1 | \n0 | \n2 | \n12 | \n0.6 | \n
3 | \n2 | \n1 | \n2 | \n2 | \n2 | \n1 | \n1 | \n1 | \n0 | \n2 | \n14 | \n0.7 | \n
4 | \n2 | \n1 | \n1 | \n2 | \n0 | \n1 | \n1 | \n1 | \n0 | \n2 | \n11 | \n0.55 | \n
5 | \n2 | \n1 | \n2 | \n2 | \n2 | \n1 | \n1 | \n1 | \n1 | \n2 | \n15 | \n0.75 | \n
335 | \n2 | \n0 | \n1 | \n2 | \n2 | \n0 | \n2 | \n1 | \n1 | \n2 | \n13 | \n0.65 | \n
\n | 233.00 | \n|||||||||||
\n | 335 | \n|||||||||||
\n | 0.69552 | \n
Financial literacy index. Source: Primary data.
From the data collected from rural women of Jalandhar district, on the basis of combination of ten questions, it is revealed that the majority of respondents are falling in high level of financial literacy group followed by 38% of our total respondents who are coming under medium level of financial literacy.
\nSome differences concerned with investment pattern and financial selection include risk and portfolio choices. Choice of the portfolio, the level of risk bearing capacity is more concerned with the financial awareness of households. It is indicated that most of the rural females are aware of the ideology and framework of taxation (91%), Affordability and Financial security (73%). 72% of respondents confidently answer the calculation of simple interest rate. While portfolio diversification (64%), product choice (63%) and loan ideology (48%) are found lacking in this context. While in some typical financial matters financial knowledge of rural women is found lacking. Those financial concepts are Compound interest rate (24%), financial knowledge to life circumstances (22%) and Credit card ideology (10%). Table 4 is dictates the financial literacy score for selected financial concepts.
\nFinancial concepts | \nCorrect | \nIncorrect | \nDon’t know | \n
---|---|---|---|
Simple interest rate | \n240 (72%) | \n69 (20%) | \n26 (8%) | \n
Compound interest rate | \n79 (24%) | \n94 (28%) | \n162 (48%) | \n
Affordability | \n252 (75%) | \n83 (25%) | \nNIL (0%) | \n
Financial security | \n244 (73%) | \n47 (14%) | \n44 (13%) | \n
Portfolio diversification | \n213 (64%) | \n61 (18%) | \n61 (18%) | \n
Loan ideology | \n160 (48%) | \n128 (38%) | \n47 (14%) | \n
Financial knowledge to life circumstances | \n166 (22%) | \n122 (16%) | \n47 (62%) | \n
Product choice | \n211 (63%) | \n124 (37%) | \nNIL (0%) | \n
Credit card ideology | \n60 (10%) | \n62 (11%) | \n213 (79%) | \n
Taxation ideology | \n304 (91%) | \n18 (5%) | \n13 (4%) | \n
Financial literacy score.
Source: Primary data.
A financier, who is not financially literate, will not be able to select a suitable investment pattern. This behaviour is strongly evident in the rural society of India. Financial literacy is important not only for rural or uneducated one but even an urban educated can get him into financial suffering if he is not aware of financial concepts. The results highlight how important financial literacy is to make sound financial decisions. Financial control, Financial planning, Understanding of financial concepts and Selection of financial product are basic concepts to measure financial awareness of a person.
\nFor the purpose of finding out the relationship between financial literacy and pattern of investment, a correlation test is applied. Results obtained by correlation are given in Table 5.
\n\n | Financial literacy | \nInvestment pattern | \n|
---|---|---|---|
Financial Literacy | \nPearson correlation | \n1 | \n0.129*\n | \n
Sig. (2-tailed) | \n\n | 0.018 | \n|
N | \n335 | \n335 | \n|
Investment pattern | \nPearson correlation | \n.129*\n | \n1 | \n
Sig. (2-tailed) | \n.018 | \n\n | |
N | \n335 | \n335 | \n
Relationship analysis through correlation.
Source: Primary data.
From Table 5, it is observed that the value of correlation is 0.129. So it is evidenced that there is weak degree of positive correlation between financial literacy and investment pattern among rural females. The significance value revealed by correlation is 0.018 which is less than 0.05% level of significance. So it is strongly evidenced that correlation is statistically significant also.
\nFinancial Literacy is a vital element to predict households’ financial attitudes in developing nations. Indeed, in Indian heterogeneous household, levels of financial awareness vary greatly. From the empirical study it is revealed that most of the investors select financial institutions because of familiarity and their portfolio selection is largely based on comparison of number of financial products issued by the same familiar financial institution. So, guaranteed return, safety and diverse portfolio selection are contributing at large to describe the investment attitude of women.
\nThe study reveals that there is a relationship between financial literacy and investment behaviour of the rural female. Through financial literacy programme, majority of the respondents (62% of total) have acquired more knowledge on financial concepts such as taxation, financial security, calculation of interest rate etc.
\nThe awareness level of rural females in Investment Avenue is fairly high in banking avenues, post office schemes, insurance schemes and other traditional avenues like gold/silver and real estate opportunities. Their awareness level in investment avenue is very low in chit fund schemes, bonds, debentures, Public provident fund, National savings certificate, Government securities and Commodity market.
\nA website as a financial literacy guide was released by the Reserve Bank of India on 31st January 2013. This website was developed as a complete financial awareness guide and banks are advised to use this website as a fundamental curriculum to communicate basic financial knowledge. This financial literacy guide provides operational guidelines to organize financial awareness camps, as an initiative towards financial literacy.
\nBesides, various measures adopted by government and non-government institutions towards financial literacy, the results of the study reveal that still the investment pattern of rural women is followed by traditional avenues of investment. This, it is suggested to financial literacy program organizers to focusing on preferences and investment attitude of micro level segment investors. Hamza and Arif [20] have also suggested that policymakers and managers need to focus on profiling investors based on their status. It is strongly suggested to the program organizers to pass information on issue of budgeting, portfolio diversification, effective credit card management and loan ideology.
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\n\nRead more about Open Access in Horizon 2020 here.
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