Category Archives: IRDP – Innovative Research Developers and Publishers

A Study on Consumer Inertia towards E-Wallet usage at Patan City

Author
Anand Patel, Dr. Khuman L. Rathod
Keywords
Consumer; E-wallet; Inertia; Concern; Adoption.
Abstract
Demonetization effect, Government promotion, Merchant acceptance, Effect of COVID-19, availability of internet and smart phones etc. are in favour of adoption of E-wallet in market as payment alternative but still Consumer inertia towards use of E-wallet prevails in India. In spite of many advantages to use E-wallet over traditional payment system, Consumers having hesitation due to concerned factors associated with it. Perceived Risk associated with E-wallet usages are safety, privacy, digital literacy, language, cost, fraud etc. makes impact on intention to use and consumer adoption behaviour. Research aims to examine the major factors concern for consumer’s inertia to use of E-wallet. It is an attempt to find out reasons of adoption and impact of demographic variable on concern factors with statistical analysis using SPSS.
References
[1] Swapnil Undale, Ashish Kulkarni and Harshali Patil;“E-Wallet security: impact of COVID- 19 pandemic”; July 2020. Retrieved from https://www.emerald.com / insight / 0973- 1954. htm on 12.03.2021.
[2] Abhipsa Pal, Sai Dattathrani, Dr. Rahul Dé (march 2017) “ Security in Mobile Payments: A Report on User Issues”, IIM banglore; retrieve from https:// www.iimb.ac.in/ sites/default/files/inline-files/ iimb -csitm- security- issues- in- mobile- payment. pdf on 10.03.2021.
[3] Rathore, H. S. (2016, April) Adoption of Digital Wallet by Consumers. BVIMSR’s Journal of Management Research, VIII (1), 69-76.
[4] Chauhan, P. (2013) E-wallet: The trusted partner in our pocket. International journal for research in management and pharmacy, Vol 2, issue 4, 12-19.
[5] Sushil Punwatkar, Dr. Manoj Verghese (march 2018) “Adaptation of e-Wallet Payment: An Empirical Study on Consumers’ Adoption Behavior in Central India” International Journal of Advanced in Management, Technology and Engineering Sciences, Volume 8, Issue III, MARCH/2018.
[6] https:// www.e- wallet.ae/en/faq/ faq-about- wallet.jsp retrieve on 10.03.2021.
[7] https:// www.livemint.com/ money/ personal- finance /should-you-be-held-responsible-for-preventing-an-e-wallet-fraud-11575268929129.html retrieve on 11.03.2021.
[8] https://www.varindia.com/news/freecharge – launches-india- first- ewallet- protection-plan retrieve on 12.03.2021.
[9] https://www.thehindubusinessline.com/specials/technophile / how-safe- is – your – favourite- ewallet / article9 402284. ece retrieve on 14.03.2021.

Received : 30 April 2021
Accepted : 25 September 2021
Published : 30 September 2021
DOI: 10.30726/ijmrss/v8.i3.2021.83023

An Association of Education and Income with Convenient Payment Mode in the E-tail Industry during the COVID Pandemic

Author
Gurumoorthy. K, Dr. V. Sasirekha
Keywords
COVID Pandemic; Education; E-tailing; Income; Payment Mode.
Abstract
E-tailing is the process of selling the goods and services to the large number of customers in the smaller quantity through the internet platform. Indian e-tailing sector is showing a burgeoning growth during the COVID Pandemic. The main purpose of the study is to test the association of the demographic variables Education and Income with the customer’s preference towards the mode of payment. The scope of the study is confined with both the tangibles and the intangibles in horizontal e-tailers. The sampling frame of the study is the respondents those who have a previous experience in buying goods from the horizontal e-tailers. The purposive sampling technique was adapted to choose the respondents. The sample size was 620 respondents. The data was collected during COVID pandemic in India. The data analysis tool was the Chi-square test. The result from the data analysis indicates that both the education and income of the customers are related to the customer’s preference towards the convenient mode of payment during the online shopping. The suggestions and conclusions are discussed further in detail.
References
[1] Abu-Shamaa. R., Abu-Shamab.E. andKhasawneh.R., (2016), Payment Methods and Purchase Intention in Online Stores: An Empirical Study in Jordan, International Journal of E-Business Research,12(2), 31-44.
[2] Antinoja.R. and Scherling.D. (2019). The effect of e-payment methods on Online Purchasing Cancellation, Jonkoping University.
[3] Bandi.C.,Moreno.A., Ngwe.D. andXu.Z. (2019). The Effect of Payment Choice on Online Retail: Evidence from the 2016 Indian Demonetization, Harward Business School.
[4] Business Today(2021, July)., The e-tailing in India, Business today.
[5] Khan.S. and Jain.S. (2018). A study on Usage of e-Payments for sustainable growth of online business, IOSR Journal of Business and Management, 74-81.
[6] Mallesha.C. (2020). A Case study on Perception Towards Online Payment Systems Among Urban and Rural Customers, International Journal of Advanced Research in Commerce, Management and Social Science, 3(1), 196-204.
[7] Mchugh.M.L(2013)., The Chi-Squae Test of Independence, BiochemiaMedica, 23(2),143-149.
[8] Siby.R.M. (2021). A study on consumer perception of digital Payment Methods in times of Covid Pandemic, Munich Personal Repec Archive.

Received  :21 July 2021
Accepted  :23 September 2021
Published :29 September 2021
DOI: 10.30726/ijmrss/v8.i3.2021.83021

Employee Transfer, Work Motivation and Employee Performance

Author
Muhammad AlkiromWildan
Keywords
Employee Transfer; Motivation; Performance.
Abstract
This study was pointed to decide: employees’ transfer, work inspiration, performance, the impact of representatives transfer on the performance; work inspiration towards the performance; workers transfer and work inspiration towards the employees’ performance of BPK Representative of JawaTimur Province. This investigate employments quantitative approach with clear affiliated inquire about. The information examination method utilized in this considers is path analysis. The comes about of this ponder demonstrate that: recognition of workers transfers in BPK Representative of JawaTimur province is moo, the work inspiration of representatives is exceptionally sufficient, the performance is sufficient, workers transfer isn’t noteworthy to workers performance. The conclusion from this study is that employees’ exchange doesn’t have noteworthy impact on employees’ performance somewhat. Work inspiration has positive and noteworthy impact on employees’ performance. Workers exchange and work inspiration together have a critical commitment on representatives performance.
References
[1] Astuti. (2017). Analysis of EmployeeWorkActivityM InAn Effort toImproveEmployeeWorkProductivityCaseStudy Of Metal Button Company Assembling Parts. Bandung: Pasundan University Bandung.
[2] Budiman, Arif (2018). Employee Transfer: a Review of Recent Literature.Journal of Public Administration Studies. JPAS Vol. 3 No. 1, pp 33-36, 2018. ISSN: 2548-902X.
[3] Dewi, J.P. (2017). Effect ofTransferand Motivation on EmployeePerformance ofPT.BuanaSamudra Lestari. Bekasi: PelitaBangsa College of Economics.
[4] Dimyati, A. (2018). Effect ofTransferonEmployee Motivationin Housing Office ofResidentialArea and Water ResourceManagement of Lampung Province(Research). Downloaded April 19, 2019 from World Wide Web: http://docplayer.info
[5] Hasibuan, M.S.P. (2016) Human ResourceManagement. Revised Edition. Jakarta: BumiAksara. Mangkunegara, A.P. (2017). Corporate HumanResourceManagement.Fourteenth Printing. Bandung: PT. Teen Rosda Works.
[6] Panggabean, M. S. (2016). Human ResourceManagement. Issue 2. Third Printing. Tangerang: Open University.
[7] Prasetya,Arik (2018). Analysis of Factors that Influence Employee Performance (Study on Permanent Employees in OperationelSection of PT WIMCycleIndonesia-Surabaya). Journal of Profit Volume 12 No. 1. 2018.
[8] Princess, G.F. (2016). Effect ofWorkTransferonOperationalEmployeePerformance at VioCihampelasHotel Bandung. Bandung: Bandung College of Tourism. September 3, 2019
[9] Purwanto, Agus J., Elu, Wilfridus B. (2017). Innovationand OrganizationalChange. Second Edition. First Printing. South Tangerang:Unversitas Open.
[10] Republic Indonesia. Government Regulation No. 11 of 2017 concerning Civil Servant Management.
[11] Sari, D. (2015). The Influence of Job Satisfaction and Organizational Commitment to Employee Performance at PT. PUSKOPKAR Riau Pekanbaru. JOM FEKON Vol. No. February 101-1055.
[12] Sayd. G.A., etal. (2016). Journal of Factors Affecting the Quality of Performance of Rote Ndao Land Office. Journal of Socialand PoliticalSciences 19(3), March 2016 (264-274). ISSN 1410-4946.
[13] Sutrisno,Edy. (2016). Human ResourceManagement. Eighth Printing. Jakarta: KencanaPrenada Media Group.
[14] Wildan, M.A. (2021). Macroeconomic Factors Affecting Natural Gas Export Management. International Journal of Energy Economics and Policy, 2021, 11(1), 639-644.
[15] Wildan, M.A. (2021). Work Motivation and Supervisor Performance in Indonesia. International Journal of Management Research and Social Science (IJMRSS), 8(2), April – June 2021.
[16] Wutsqo, W. U. (2017). Effect ofTransferand IncentiveonEmployeePerformance (CaseStudy at The Office of ForeignInvestmentTaxServiceLima Jakarta). Yogyakarta: State University of Yogyakarta. Retrieved July 3, 2021 from World Wide Web: https://eprints.uny.ac.id

Received :17 June 2021
Accepted :22 September 2021
Published :29 September 2021
DOI: 10.30726/ijmrss/v8.i3.2021.83020

अरुणकमल की कविताओं में अंतरराष्ट्रीय चेतना

Author
Guhanandan
Keywords
आयाम;चेतना;विश्वप्रजापतित्व;अपमिश्रण;भौगोलीकरण;अवगमन;संवेदनशीलता ।
Abstract
अरुणकमल सत्तरोत्तर कवियों में प्रमुख और विशष्ट हैं । अंग्रेजी के प्राध्यापक होते हुए भी हिन्दी कविता में उनकी विशेष रुचि व आसक्ति बनी रही । समसामयिक मुद्दों को केंद्रित करके उन्होंने अपनी कविताओं का सृजन किया है । साम्यवादी विचारधारा परिपूर्ण प्रगतिवादी काव्य की विशेषताओं से अपने काव्य को समलंकृत करते हुए समसामयिक तत्वों को अपने काव्य का विषय बनाकर अपनी केवल धार से लेकर योगफल तक काव्य संग्रहों का प्रकाशन करवाया । उनका एक अनूदित काव्यसंग्रह ‘जब पुकारती है कोयल’है जोकि वियतनामी कवि ‘तो हू’ की प्रगतिवादी उद्गार व भावाभिव्यंजना थी । कवि की चेतना स्थानीय समसामयिक मुद्दों को विचार प्रदान करने से एक कदम आगे अंतरराष्ट्रीय मुद्दों को अपनी वाणी देना चाहती है । यह उनके अंतरराष्ट्रीय नागरिकता का परिचायक है । कवि अरुणकमल ने प्रगतिवादी कविता व समसामयिक कविता से अंतरराष्ट्रीय विचारधारा को निरूपित किया है । इस शोध-लेख का उद्देश्य है कि अरुणकमल की कविताओं में होनेवाली अंतरराष्ट्रीय चेतना प्रतिपादित हो ।
References
[1] आचार्यरामचंद्रवर्मा, मानकहिन्दीकोश, प्रयाग
[2] अरुणकमल, अपनीकेवलधार, पृ.11, वाणीप्रकाशन, नईदिल्ली
[3] अरुणकमल, अपनीकेवलधार, पृ.19, वाणीप्रकाशन, नईदिल्ली
[4] अरुणकमल, अपनीकेवलधार, पृ.19, वाणीप्रकाशन, नईदिल्ली
[5] अरुणकमल, अपनीकेवलधार, पृ.26, वाणीप्रकाशन, नईदिल्ली
[6] अरुणकमल, अपनीकेवलधार, पृ.52, वाणीप्रकाशन, नईदिल्ली
[7] अरुणकमल, नएइलाकेमें, पृ.81, वाणीप्रकाशन, नईदिल्ली
[8] अरुणकमल, मैंवोशंखमहाशंख, पृ.56, वाणीप्रकाशन, नईदिल्ली
[9] अरुणकमल, मैंवोशंखमहाशंख, पृ.57, अरुणकमल, मैंवोशंखमहाशंख, पृ.78, वाणीप्रकाशन, नईदिल्ली
[10] अरुणकमल, मैंवोशंखमहाशंख, पृ.78,
वाणीप्रकाशन, नईदिल्लीअंतरजाल–चेतनाकेपाँचआयाम-
[11] अंतरजाल-https://hi.wikipedia.org/wiki/चेतना
[12] अंतरजाल–चेतनाकेपाँचआयाम-
[13] http://literature.awgp.org/book/Gayatree_kee_panchakoshee_sadhana/v7.13
[14] अंतरजाल–CWLG Definition – Global Consciousness –
https://www.surveymonkey.com/r/ZYJ7CW3
[15] अंतरजाल–https://libguides.westsounda
cademy.org/wsee/global-consciousness
[16] अंतरजाल- https://hi.wikipedia.org/wiki/मिलावट

Received : 05 July 2021
Accepted :23 September 2021
Published :27 September 2021
DOI: 10.30726/ijlca/v8.i3.2021.83006

குறளும் தொகையும்

Author
ஜெ. தேவி
Keywords
குறள்வெண்பாதொகைநிலைத்தொடர்; வினைத்தொகைபண்புத்தொகை; உம்மைத்தொகை; உவமைத்தொகை; அன்மொழித்தொகை; வேற்றுமைத்தொகை.
Abstract
திருக்குறள்சமயச்சார்பற்றபொதுமையானகருத்துகளைஎல்லாகாலத்திற்கும்ஏற்கும்வகையிலும்எளிமையாகப்பின்பற்றக்கூடியநீதிக்கருத்துகளையும்கொண்டுபல்வேறுசிறப்புகளைப்பெற்றுத்திகழ்கின்றது. இவ்வாறுதிருக்குறள்பெற்றுள்ளசிறப்புகளுள்குறள்வெண்பாதொகைநிலைத்தொடர், வினைத்தொகைபண்புத்தொகை, உம்மைத்தொகை, உவமைத்தொகை, அன்மொழித்தொகை, வேற்றுமைத்தொகைஆகியஇலக்கணஅமைப்புகளின்ஊடாகநிகழ்ந்தஆய்வின்வழிக்குறளின்முக்கியத்துவத்தைஎடுத்துரைக்கும்நோக்கில்இவ்வாய்வுக்கட்டுரைஅமைந்துள்ளது.
References
[1] சுந்தரமூர்த்தி, இ.,பரிமேலழகர்உரைத்திறன், ஐந்திணைப்பதிப்பகம், சென்னை, முதற்பதிப்பு, 2006.
[2] திருக்குறள், பரிமேலழகர்உரை, பழனியப்பாபிரதர்ஸ், சென்னை, முதற்பதிப்பு, 1962, எட்டாம்பதிப்பு, 2010.
[3] தொல்காப்பியர், தொல்காப்பியம்சொல்லதிகாரம், மு. சண்முகம்பிள்ளை (ப.ஆ.), முல்லைநிலையம், சென்னை, முதற்பதிப்பு, 1995.
[4] நுண்பொருள்மாலை, திருமேனிகாரிஇரத்தினக்கவிராயர், இ.சுந்தரமூர்த்தி – பதிப்பாய்வு, தேன்மொழிநூலகம், முதற்பதிப்பு, 1980.
[5] பவணந்திமுனிவர், நன்னூல்சொல்லதிகாரம், சோம. இளவரசு (உ.ஆ.), மணிவாசகர்பதிப்பகம், சென்னை, முதற்பதிப்பு, 2004, ஏழாம்பதிப்பு, 2013.
[6] முதற்பாவலர், கு., யாப்புக்குவயது 50 – குறள்மணிமாலை, நறுமுகைபதிப்பகம், செஞ்சி, முதற்பதிப்பு, 2015

Received :13 August 2021
Accepted :20 September 2021
Published :27 September 2021
DOI: 10.30726/ijlca/v8.i3.2021.83005

Impact of Quality on Customers’ Buying Behaviour towards Point of Purchase Display with reference to Haryana

Author
Dr. Randeep Kaur, Dr. Sunita Sukhija
Keywords
Retail; Organized; Quality; Purchase; Consumer Behaviour; Buying decision.
Abstract
The present paper focuses on the impact of quality on customers’ buying behaviour towards point-of-purchase display at various retail outlets in Haryana. Point-of-Purchase Display plays an important role to increase the sale of the retailers. Today customers are rational and prefer quality products at reasonable price. Moreover, due to the emergence of the supermarkets as the dominant retail, the retail industry is experiencing vibrant changes all over the world. Retail industry in India has grown to be more complex and dynamic with an increase rate of speed from unorganized towards being organized. In this research paper data has been collected from 100 respondents and analysed with the help of Statistical Package for the Social Sciences (SPSS) using one way ANOVA and t-test with demographic factors i.e. age-wise, gender-wise, occupation-wise and income-wise. . After analysing the data it was found that, there is neutral relationship in the opinion of different age groups and gender groups over the point-of-purchase display on quality. On the other hand Occupation and income does not have any importance on customers view point regarding ‘quality’. To conclude we can say that point-of-purchase display is not directly related to the quality.
References
[1] Ailawadi, K., L., Farris, P., and Shames, E., (1999). Trade promotion: essential to selling through resellers. Sloan Management Review, 41(1),83-92.
[2] Binoy, M., (2015).A study on changing trends in online shopping of Indian customers in apparel segment. International Journal of Applied Research, 1(9), 207-214.
[3] B., H, and ,Punkaj, (2014), “The importance of point of purchase display on store atmospheric” International Journal of Engineering and Management Research, Vol.4 No.5, pp.122-129.
[4] Kazmi, S., Q., (2012).Customer perception and buying decisions (The Pasta Study)”. International Journal of Advancements in Research and Technology, 1(6).
[5] Koo, D., M., (2003).Inter-relationships among store images, store satisfaction, and store loyalty among Korea discount retail patrons. Asia Pacific Journal of Marketing and Logistics, 15(4), 42–71.
[6] Kumar, A., H., Hemanth, J., S., Franklin, S., S., (2014).A Study on factors influencing customer buying behaviour in cosmetic Products. International Journal of Scientific and Research Publications, 4(9), 1-6.
[7] Mohanraj, M., P., (2017). Customers’ compulsive buying behaviour – An Empirical Study. Great Lakes Herald, 11(1), 1 – 18.
[8] Oliver, R., L., and Swan, J., E., (1989). Consumer perceptions of interpersonal equity and satisfaction in transactions: a field survey approach. Journal of Marketing, 53(2), 21-35.
[9] Prasad,Y. R., (2012).A study on attributes influencing the purchasing behaviour of apparel customers in organized outlets. African Journal of Business Management, 6 (45), 11294-11303.
[10] Pawar, S., A., and Naranje, S., (2015). A study on factors influencing on buying behaviour of customers.International Journal of Engineering, Technology, Science and Research, 2.
[11] Yoon, S., J., (2013).Antecedents and consequences of in-store experiences based on an experiential typology. European Journal of Marketing, 47(5/6), 693-714.

Received :11 August 2021
Accepted :20 September 2021
Published :26 September 2021
DOI: 10.30726/ijmrss/v8.i3.2021.83018

Three New Models for Ranking of Candidates In the Preferential Voting Systems

Author
Mohammad Azadfallah
Keywords
Voting Systems; Markov Chain Model; Borda’s Function; TOPSIS with Interval Data; Ordinal Preference; Ranking of Candidates Problems
Abstract
Election is the main challenge to the political and social science. In the meantime, in the literature, several methods to decide the winner of elections have been proposed; theoretically there is no reason to be limited to these models. Hence, in this paper, we assume three new approaches (1. election result prediction by pre-election preference information using Markov chain model [to identify the efficient electoral strategy for each candidate]. 2. Improved Borda’s function method using the weights of decision makers [or voters]. And 3. A new interval TOPSIS-based approach applying ordinal set of preferences [so, data is ordinal form that first convert to interval value and then inject them into the conventional interval TOPSIS model]) for ranking candidates in voting systems. Ultimately, three numerical examples in social choice context are given to depict the feasibility and practability of the proposed methods. In sum, this paper suggests a mind line for decreasing the wrong choice winner risks correlated with voting systems.
References
[1] Aghayi, N, and Tavana, M. (2019). A novel three-stage distance-based consensus ranking method. Journal of Industrial Engineering International, 15(2019), 17-24.
[2] Alam, M. M., Mezbahuddin, M., and Shoma, S. N. (2015). Election result prediction system using hidden Markov model [HMM]. International Journal of Computer Applications, 129(3), 1-4.
[3] Alguliyev, R., Alguliyev, R., and Yusifov, F. (2019). Multi-criteria evaluation the positional approach to candidate selection in E-voting. Decision Making: applications in Management and Engineering, 2(2), 65-80.
[4] Almedia, A. T. D. and Nurmi, H. (2015). Aiding the choice of a voting procedure for a business decision problem. https://pdfs.semanticscholar.org/27bc/c03a203ab2ee46.pdf. Access date: 24 Dec 2019.
[5] Almedia, A. T. D., Morais, D. C., and Nurmi, H. (2019). Systems, procedures and voting rules in context: A primer for voting rule selection. Springer Nature Switzerland AG 2019.
[6] Al-Tarawneh, H. A. (2012). The main factors beyond decision making. Journal of Management Research, 4(1), 1-23.
[7] Azadfallah, M. (2016). A new aggregation rule for ranking suppliers in group decision making under multiple criteria. Journal of Supply Chain Management System. 5(4), 38-48.
[8] Azadfallah, M. (2019). A new MCDM approach for ranking of candidates in voting systems. International Journal Systems Sciences. 11(2), 119-133.
[9] Bag, S., Azad, M. A., and Hao, E. (2019). E2E verifiable Borda count voting system without tallying authorities, Proceedings of the 14th international conference on Availability, and Security, 2019(1), 1-9.
[10] Beck, M. S. L. and Dassonne Ville, R. (2015). Forecasting elections in Europe: systematic model. Research and Politics, January-March 2015, 1-11.
[11] Bouyssou, D., Marchant, T., and Perny, P. (2009). Social choice theory and multicriteria decision aiding, in decision making process: concepts and methods (eds. D. Bouyssou, D. Dubois, M. Pirlot, and H. Prade), ISTE, London, UK. Doi: 10.1002/9780470611876.ch19.741-770.
[12] Bouyssou, D., Marchant, T., Pirlot, M., Tsoukias, A., and Vincke, Ph. (2006). Evaluation and decision models with multi criteria: stepping stones for the analyst. Springer, doi: 10.1007/0-387-31099-1.
[13] Bradle, F. and Peters, D. (2019). An axiomatic characterization of the Borda mean rule. SOC Choice Welfare, 52(4), 685-707.
[14] Brandt, F., Couitzer, V., Endriss, U., Lang, J., and Procaccia, A. D. (2016). Introduction to computational social choice. Handbook of Computational Social Choice, F. Brandt, V. Couitzer (eds.), Cambridge University Press, 2016, 1-29.
[15] Breton, M. L. and Truchon, M. (1997). A Borda measure for social choice functions. Mathematical Social Sciences, 34(3), 249-272.
[16] Cheng, K. E. and Deek, F. P. (2012). Voting tools in group decision support systems: theory and implementation. Int. J. Management and Decision Making, 12(1), 1-21.
[17] Colladon, A. F. (2020). Forecasting election results by studying brand importance in online news. International Journal of Forecasting, 36(2), 414-427.
[18] Debord, B. (1992). An axiomatic characterization of Borda’s k-choice function. Social Choice and Welfare, 9(4), 337-343.
[19] Dizaji, L. Y. and Khanmohammadi, S. (2016). A new multi-criteria decision making based on fuzzy-TOPSIS theory. Journal of Advances in Computer Engineering and Technology, 2(4), 39-48.
[20] Ebrhimnejad A. (2012). Ranking of candidates in the preferential voting framework based on a new approach. ASM 12 proceedings of the 6th international conference on applied mathematics, simulation, modeling Athens, Greece, March 7-9, 2012, 78-81.
[21] Ebrhimnejad, A. & Nasseri, H. (2012). A new approach for ranking of candidates in voting systems. The 4th National conference on Data Envelopment Analysis, June 13-14, 2012, University of Mazandaran, Babolsar, Iran, 1-3.
[22] Egecioglu, O. and Giritligil, A. E. (2011). The likelihood of choosing the Borda-winner with partial preference rankings of the electorate. Journal of Modern Applied Statistical Methods, 10(1), 349-361.
[23] Fallahpour, A. (2016). Development of multi-criteria decision making model for supplier selection using Gene expression programming. PhD thesis, Faculty of Engineering, Supervisors: Dr. Olugu and Dr. Nurmaya, MALAYA, Kualalampur.
[24] Fraser, N. M. and Hauge, W. (1998). Multi-criteria approval; application of approval voting concepts to MCDM problems. Journal of Multi-criteria Decision Analysis, 7(5), 263-273.
[25] Habenicht, W., Scheubrein, B., and Scheubrein, R. (2009). Multiple-criteria decision making. Optimization and Operations Research, Edited by Derigs Encyclopedia of life support systems, Vol. IV, EOLSS publisher/UNESCO.
[26] Hajimirsadeghi, H. and Lucas, C. (2009). Extended TOPSIS for group decision making with linguistic quantifier and concept of majority opinion. https://www.semanticscholar.org > Access date: 20 July 2017, 1-7.
[27] Hummel, P., and Rothschild, D. (2013). Fundamental models for forecasting elections. Research DMR.com/ Hummel Rothscild_Fundamentalmodel, 1-45.
[28] Hummel, P., and Rothschild, D. (2014).Fundamental models for forecasting elections at the state level. Electoral Studies, 35(2014), 133-139.
[29] Hwang, C.L. & Lin, M. J. (1987). Group decision making under Multiple Criteria: methods and applications, Springer Verlag.
[30] Hwang, C.L. & Yoon, K. (1981). Multiple attribute decision-making methods and applications, Springer Verlag.
[31] Jahanshahloo, G. R., Lotfi, F. H., and Davoodi, A. R. (2009). Extension of TOPSIS for decision-making problems with interval data: interval efficiency. Mathematical and computer modeling 49 (2009), 1137-1142.
[31] Jahanshahloo, G. R., Lotfi, F. H., and Izadikhah, M. (2006). An algorithmic method to extend TOPSIS for decision making problems with interval data. Applied Mathematics and Computation, 175(2006), 1375-1384.
[32] Janse, B. (2019). Borda count method. Retrieved [17 March 2020] from tools hero: https://www.toolshero.com/decision-making/borda-count-method/.
[33] Jimenez, J. M. M. and Polasek, W. (2003). E-democracy and knowledge. A multi criteria framework for the new democratic era. Journal of Multi-criteria Decision Analysis, 12(2-3), 163-176.
[34] Kassraie, P., Modirshanechi, A., and Aghajan, H. K. (2017). Election vote share prediction using a sentiment-based fusion of twitter data with Google trends and online polls. In Proceedings of the 6th international conference of Data Science, Technology and Applications, (DATA 2017), 363-370.
[35] Koffi, C. (2015). Exploring a generalized partial Borda count voting system. Senior projects spring 2015, 153. https://digital commons, bard/edu/ senproj_S2015/153.
[36] Kou, S. G., and Sobel, M. E. (2004). Forecasting the vote: a theoretical comparison of election markets and public opinion polls. Political Analysis, 12(2004), 277-295.
[37] Kurihara, T. (2020). Net Borda rules with desirability. WINPEC Working Paper Series No. E2002, May 2020, Waseda University, Tokyo, Japan.
[38] Lapresta, J. G., Paner, M. M., and Meneses, L. C. (2008). Defining the Borda count in a linguistic decision making context. Preprint submitted to Elsevier Science,/5October 2008. Retrieved from http://www.researchgate.net/publication/ 228359030_defining_Borda_count_in_a_linguistic_decision_making_context.
[39] Lapresta, J. L. G. and Panero, M. M. (2002). Borda count versus approval voting: a fuzzy approach. Public Choice, 112(1-2), 167-184.
[40] Laukkanen, S., Palander, T., and Kangas, J. (2004). Applying voting theory in participatory decision support for sustainable timber narvesting. Canadian Journal of Forest Research, 34(7), 1511-1524.
[41] Liu, F. H. F. and Hai, H. L. (2005). The voting analytic hierarchy process method for selecting supplier. Int. J. Production Economics, 97(2005), 308-317.
[42] Macdonald, R. and Mao, X. (2015). Forecasting the 2015 general election with internet big data: an application of the trust framework. Glasgow: Business School-Economics, University of Glasgow.
[43] Mohaghar, A., Kashef, M., and Khanmohammadi, E. (2014). A novel technique to solve the supplier selection problem: combination
decision making trial & evaluation laboratory, graph theory and matrix approach methods. International Journal of Industrial Engineering & Production Research, 25(2), 103-113.
[44] Nagadevara, V. (2005). Building predictive model for election results in India-an application of classification trees and neural networks. JABE, 5(3), ISSN: 1542-871.
[45] Nicholson, A. (2005). Voting and Markov processes. Proceeding of the national conference on undergraduate research (NCUR) 2005, Virginia Military Institute, Washington and Lee University, Lexington, Virginia, April 21-23, 2005, 1-7.
[46] Nurmi, H. (2007). Assessing Borda’s rule and its modifications. From Book: designing an all-inclusive democracy: consensual voting procedure for use in parliaments, Councils and Committees, doi: 10.1007/978-3-540-33164-3_7.
[47] Opricovic, S. and Tzeng, G. H. (2004). Comprise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European of Operational Research, 156 (2004), 445-455.
[48] Payne, C. (2001). Election forecasting in the UK. Paper presented at the institute of European and American studies, Academia Sinica, Taipei, Taiwan, Nov. 28, 2001, 1-27.
[49] Polykovskiy, S., Berghammer, R., and Neumann, F. (2016). Solving hard control problems in voting system via integer programming. European Journal of Operational Research, 250(1), 204-213.
[50] Roszkowska, E. (2011). Multi-criteria decision making models by applying the TOPSIS method to crisp and interval data. Multiple Criteria Decision Making/ University of Economics in Katowice, 6, 200-230, 2011.
[51] Roszkowska, E. (2013). Rank ordering criteria weighting methods- A comparative overview. Optimum. Studia Ekonomiczne NR, 5(65), 14-33.
[52] Saari, D. G. (2006). Which is better: the Condorcet or Borda winner? SOC Choice Welfare, 26(2006), 107-129.
[53] Shih, H. S., Shyur, H. J., and Lee, E. S. (2007). An extension of TOPSIS for group decision making. Mathematical and Computer Modelling, 45(2007), 801-813.
[54] Soltanifar, M. and Lotfi, F. H. (2011). The voting analytic hierarchy process method for discriminating among efficient decision making units in data envelopment analysis. Computers & Industrial Engineering, 60(4), 585-592.
[55] Soltanifar, M. (2017). A new group voting Analytical Hierarchy Process method using preferential voting. Journal Of Operational Research And Its Applications, 14(3540016),1-13.
[56] Srdjevic, B., Srdjevic, Z., and Medeiros, Y. D. P. (2017). Multicriteria and social choice methods in assessing water management plans. Proceedings of the 8th international conference of information and communication 2017. Technologies in agriculture, food and environment (HAICTA) 2017, Chania, Greece, 21-24 September 2017.
[57] Stein, W. E., Mizzi, P. J., and Pfaffenberger, R. C. (1994). A stochastic dominance analysis of ranked voting systems with scoring. European Journal of Operational Research, 74(1994), 78-85.
[58] Stoltenberg, E. A. (2013). Bayesian forecasting of election result in multiparty systems. MSC thesis, Faculty of Social Sciences, University of OSLO.
[59] Tajvidi Asr, E., Hayaty, M., Rafiee, R., Ataei, M., and Jalali, S. E. (2015). Selection of optimum tunnel support system using aggregated ranking of SAW, TOPSIS and LA methods. International Journal of Applied Operational Research, 5(4), 46-63.
[60] Talemi, H. T., Jahanbani, K., and Heidarkhani, A. (2013). Application of Markov chain in forecasting demand of trading company. Interdisciplinary Journal of Contemporary research in Business, 5(1), 1070-1074.
[70] Walter, D. (2015). Picking the winner(s): forecasting elections in multiparty systems. Electoral Studies, 40(2015), 1-13.
[71] Wang, Y. M., Greatbank, R., and Yang, J. B. (2005). Interval efficiency assessment using data envelopment analysis. Fuzzy Sets and Systems, 153(2005), 347-370.
[72] Xia, L. (2011). Generalized scoring rules: a framework that reconciles Borda and Condorcet. ACM SIGecom Exch., 10(2), 1-7.
[73] Yue, Z. (2013). Group decision making with Multi attribute interval data. Information Fusion, 14(4), 551-561.
[74] Zakaria, N. N., Othman, M., Sokkalingam, R., Daud, H., Abdullah, L. and Kadir, E. A. (2019). Markov chain model development for forecasting air pollution index of Miri, Sarawak. Sustainability, 11(5190), 1-11.
[75] Zolghadr, M., Niaki, S. A. A., and Niaki, S. T. A. (2018). Modeling and forecasting US presidential election using leavening algorithm. J Ind Eng Int, 14(2018), 491-500.

Received : 17 January 2021
Accepted : 24 April 2021
Published : 01 May 2021
DOI: 10.30726/ijmrss/v8.i2.2021.82009

Word of Mouth Marketing Strategy by Consumer Satisfaction

Author
Nurita Andriani
Keywords
Product Quality; Gold Store; Service Quality; Customer Satisfaction; Word of Mouth; WOM.
Abstract
This study aims to analyze the influence of gold goods quality and service quality on WOM (Word of Mouth) by using consumer satisfaction as a variable mediator (intervening) study at Mirage Jewellery Gold Shop. The quality of gold goods is a consideration for consumers in making purchases at Mirage Jewellery Gold Shop. Respondents in this study were consumers who made transactions at Mirage Jewellery Gold Store. The analysis method used is Structural Equation Modelling (SEM) analysis that is run with AMOS program. Hypothetical test results with SEM indicate that 1. The quality of gold goods has a positive effect on consumer satisfaction, 2. The quality of service has a positive effect on customer satisfaction, 3. Consumer satisfaction has a positive and significant effect on WOM4.The quality of service positively influenced WOM’s study on Mirage Gold Jewellery Stores.
References
[1] Ammari, N. (2012). TheEffects of Loyalty Program Qualityon Word-of-Mouth Recommendations Intentions. World Academy of Science, Engineering and Technology, 64(4), 2012.
[2] Anderson, E. W. (2008). Customer Satisfaction and WOM.Service Research, 1(1), 5–17.
[3] Anita. (2015). Comparative Analysis of Gold Precious Metals Investments with Shares of Mining Companies on the Indonesia Stock Exchange 2010-2014, 5(2), 243–252.
[4] Asteria, D. K. (2018). Jewelry Rings Become Young People’s Choice. Retrieved from https://lifestyle.bisnis.com /read/ 20180417/104/785535/perhiasan-
[5] Athiyah, L.(2016).Product’s Quality and Its Impact on Customer Satisfaction Afield study inDiwaniyah Dairy Factory. Proceedings of the 10th International Management Conference, 57–65. Retrieved from F/1_7.pdf
[6] Bahri- ammari, N. (2012). Effect of Loyalty Quality On Word Program – Recommendations -Mouthintentions,6(1), 619–628.
[7] Bharwana, T. K., & Mohsin, M. (2013).Impact of Service Quality on Customers’ Satisfaction: A Study from Service Sector especially Private Colleges of .International Journal of Scientific and ResearchPublications,3(5), 1–7. https://doi.org/10.1016/ j.geoderma. 2012.02.011
[8] Chaniotakis, I. E., & Lymperopoulos, C. (2009). Service quality effecton satisfaction and word of mouth in the health care industry. Managing Service Quality,19(2), 229–242. https://doi.org/ 10.1108/09604520910943206
[9] Febrian, A. (2018). Gold Bars Sell Sweet, How Gold Jewelry? Kontan. Co.Id. Retrieved from https://lifestyle.kontan.co.id/news/emas- bars-bestselling-sweet-how-demand-gold-jewelry
[10] Ferdinand, A. (2013). Management Research Method. Semcharcoal: The Publishing Body of Diponegoro University.
[11] Imam, G. (2013).Multivariate Analysis Application with SPSS Program. Semarang: Diponegoro University Publishing Board.
[12] Kotler, P. (2009).Marketing Management. (Erlangga, Ed.).jakarta.
[13] Kusnandar, R. (2010). CFig Smart Gardening Gold.jakarta: Trans Media Library.
[14] Leonnard, S.,Comm, M., & Thung, F. (2021). The relationship of service quality, word-of-mouth, and repurchase intention in online transportation services. Journal of Process Management. New Technologies,5(4), 30–40. https://doi.org/10.5937/jouproman5-15210
[15] Muhammad Awan, H., Shahzad Bukhari, K., & Iqbal, A. (2011). Service quality and customer satisfaction in the banking sector: A comparative study of conventional and Islamic banks in Pakistan. JournalofIslamicMarketing,2(3), 203–224. https://doi.org/10.1108/17590831111164750
[16] Muhammad Tahir Jan, Kalthom Abdullah:,& Ali Shafiq. (2013). The Impact of Customer Satisfaction on Word-of-Mouth. International Journal of Information Technology&ComputerScience,10(3), 10.
[17] Mulyanto. (2021). The Influenceof Product Quality, Service Quality and Trust on Customer Satisfaction and Its Impact on Customer Loyalty (Case Study PT ABCTbk).International Journal of Scientific & Engineering Research,8(7), 2330–2336.
[18] Ngo, M. V., &Nguyen,H. H. (2016). The Relationship between Service Quality, Customer Satisfaction and Customer Loyalty: An Investigation in Vietnamese Retail Banking Sector. Journal of Competitiveness, 8(2), 103–116. https://doi.org/10.7441/joc.2016.02.08
[19] Novalius, F. (2021). Buy Taxable Gold, Antam Sales Do Not Fall. Okezone.Com Retrieved from https://economy. okezone.com/ read/2021 /10/06/320/1789885/beli-emas-kena- tax-antam-call-sales-not-down
[20] Service, H. K., & Purchased, D. A. N. (2021). Relationship quality service, said- ofmouth, and purchased kembali intention in online transportation services,5(4), 30-40.
[21] Product, K.,Impact,D. A. N.,& Satisfaction,T. (2016). Study of the importance of Research Assumptions There is a link with statistical indications between product quality and external customer satisfaction there is a relationship, 57–65.
[22] Taghizadeh, H.,Taghipourian,M. J., &Khazaei,A. (2013). The effect of customer satisfaction on word of mouth communication. Research Journal of Applied Sciences, Engineering and Technology, 5(8), 2569–2575. https://doi.org/10.19026/rjaset.5.4698

Received : 04 February 2021
Accepted : 19 April 2021
Published : 30 April 2021
DOI: 10.30726/ijmrss/v8.i2.2021.82008

Financial Liquidity, Asset Management and Financial Performance in Indonesia Listed Companies

Author
  Mohammad Arief 
Keywords
Liquidity; Management of Asset; Cash Turnover; Capital Structure; Financial Performance.
Abstract
This study aims to examine the effect of liquidity, asset management, cash turnover and capital structure on financial performance in manufacturing companies listed on the Indonesia Stock Exchange. The research was conducted with a quantitative research approach. This type of research is descriptive research. The populations in the study as many as 159 companies and the number of samples of 85 manufacturing companies are listed on the Stock Exchange Indonesia. The variables related to this research are liquidity (current ratio), asset management (total asset turnover), cash turnover, capital structure (debt to equity ratio) and Return on Asset. The research method used is the classical assumption test method and multiple linear regression analysis. The results showed that partially liquidity (current ratio) had a significant effect on Return on Asset, Asset Management (total asset turnover) had a significant effect on Return on Asset, and Cash Turnover (debt to equity ratio) had no significant effect. Return on Asset and Capital Structure have no significant effect on Return on Asset (ROA). Simultaneously Liquidity (current ratio), Asset Management (total asset turnover), Turnover Cash (cash turnover) and Capital Structure (debt to equity ratio) affect significantly to the Financial Performance in Indonesia Listed Companies.
References
[1]   Burksaitiene, D., Draugele, L. (2018), Capital structure impact on liquidity management. International Journal of Economics, Business and Management Research, 2(1), 110-127.

[2]   Cheriyan, N.K., Daniel, L. (2019), Relationship between Liquidity, Volatility and Trading Activity: An Intraday Analysis of Indian Stock Market. International Journal of Economics and Financial Issues, 9(1), 17-22.

[3]   Demirgunes, K. (2016), The effect of liquidity on financial performance: Evidence from Turkish retail industry. International Journal of Economics and Finance, 8(4), 63-79.

[4]   Endah, W., Nurlaela, S., Titisari, K.H. (2017), The effect of liquidity ratio, productivity ratio, profitability ratio, and solvability ratio on sukuk ranking. Accounting and Tax Journal, 18(1), 130-139.

[5]   Ghasemi, M., Ab-Razak, N.H. (2016), The impact of liquidity on the capital structure: Evidence from Malaysia. International Journal of Economics and Finance, 8(10), 130-139.

[6]   Liaqat, I., Saddique, S., Bagh, T., Khan, M.A., Naseer, M.M., Khan, M.A. (2017), Capital structure as driving force of financial performance: Case of energy and fuel sector of Pakistan. International Journal of Accounting and Financial Reporting, 7(1), 86-100.

[7]   Marfuah, S.A., Nurlaela, S. (2017), Effect of company size, asset growth, profitability, and sales growth on the capital structure of the cosmetics and household company on the Indonesia stock exchange. Accounting and Tax Journal, 18(1), 16-30.

[8]   Gladys, M., Omagwa, J. (2017), Asset structure and financial performance: A case of the Nairobi securities exchange, Kenya. Research Journal of Finance and Accounting, 8(4), 192-200.

[9]   Nainggolan, H.L., Pratiwi, P.S. (2017), Analysis of factors affecting corporate financial performance. Media Economics and Management, 32(1), 80-96.

[10] Obilikwu, J. (2018), The imact of capital, concentration, size and liquidity on banking industry performance in Nigeria. International Journal of Economics and Financial Issues, 8(4), 54-60.

[11] Olusuyi, A.E., Felix, A.E. (2017), The effect of capital structure on the financial performance of manufacturing firms in Nigeria (2008-2014). Journal of Accounting and Financial Management, 3(3), 37-48.

[12] Osaretin, K.O., Sodik, A.O., Fredrick, I. (2019), Capital structure and the profitability-liquidity trade-off. International Journal of Economics and Financial Issues, 9(3), 48-64.

[13] Vy, L.T.P., Nguyet, P.T.B. (2017), Capital structure and firm performance: Empirical evidence from a small transition country. Research in International Business and Finance, 42, 710-726.

[14]         Yusuf, M., Surjaatmadja, S. (2018), Analysis of financial performance on profitability with non performance financing as variable moderation. International Journal of Economics and Financial Issues, 8(4), 126-132.

Received : 27 February 2021
Accepted : 31 March 2021
Published : 06 April 2021
DOI: 10.30726/ijmrss/v8.i2.2021.82006

A Comparative Study of Analysis and Investigation using Digital Forensics

Author
Nikunj Pansari and Dr. Ajay Agarwal
Keywords
Data Extraction; Digital Forensics; Confidentiality; Security; Tools
Abstract
Data Analysis and Investigation using Digital forensics from Digital Storage Devices, is a defined way towards effective data backup strategies, as well as a key aspect in Data Privacy and Confidentiality. Digital storage Devices like Hard Drives (internal or external), USB Drives, floppy disks, etc. provide a good medium for better utilisation and storage of data and information. So, the main task is to retrieve the stolen or lost data from these devices. Digital forensics provides the exact concept for this data extraction, in a systematic and effective manner. Now, there can be various conditions of a damaged digital storage device like it may be burnt, wet or physically damaged parts, all these conditions play a significant role in Data Extraction. Since, Data is the most important asset for any organisation, so compromising with its Security and Confidentiality, may be wrong or devastating option, for future. Just spending thousands and millions of dollars in finding the vulnerability (large-scale or small-scale), is not a solution for being secure. There has to be proper and effective choice of ways and tools for it.
References
[1] Analysis of Open Source and Proprietary Source Digital Forensic Tools by Neelam Maurya , Jyoti Awasthi , Raghvendra Pratap Singh , Dr. Abhishek Vaish. International Journal of Advanced Engineering and Global Technology I Vol-03, Issue-07, July 2015 [ISSN No: 2309-4893].
[2] Framework for a Digital Forensic Investigation,Michael Kohn, JHP Eloff and MS Olivier, Information and Computer Security Architectures Research Group (ICSA),Department of Computer Science,University of Pretoria
[3] A Review and Comparative Study of Digital Forensic Investigation Models, Kwaku Kyei , Pavol Zavarsky , Dale Lindskog, Ron Ruhl, Information Systems Security Department, Concordia University ,College of Alberta, Edmonton T5B 4E4, Canada.
[4] Comparative Analysis and Study of Forensic Investigation Tools: A View, Ms. Neha N. Agrawal, Dr. R. N. Jugele, International Journal of Computer Technology & Applications,Vol 9(3),75-79 [ISSN: 2229-6093].
[5] A Comparative Study based Digital Forensic Tool:Complete Automated Tool by Nilakshi Jain1, Dr. Dhananjay R Kalbande, The International Journal of FORENSIC COMPUTER SCIENCE, IJoFCS (2014) 1, 22-29.
[6] https://www.digital4n6journal.com/
[7] https://www.guidancesoftware.com/blog/digital-forensics/
[8] https://www.intaforensics.com/digital-forensics/
[9] https://en.wikipedia.org/wiki/List_of_digital_forensics_tools

Received : 16 January 2020

?Accepted : 24 May 2020

Published : 04 June 2020

DOI: 10.30726/ijlca/v7.i2.2020.72004