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Volume 16 Issue 4 March - May 2022

Article

De-Centralized Cross Border Payments for Global Economic Status Quo

Asish Dash* , Swarupa C. Kulkarni**

* Grazing Minds Research & Consulting, Mumbai, Maharashtra, India.

** NCRD's Sterling Institute of Management Studies, Nerul, Navi Mumbai, Maharashtra, India.

Dash, A., and Kulkarni, S. C. (2022). De-Centralized Cross Border Payments for Global Economic Status Quo. i-manager’s Journal on Management, 16(4), 1-4. https://doi.org/10.26634/jmgt.16.4.18899

Abstract

The recent Russia-Ukraine war crisis and the subsequent economic sanctions imposed by the US via a restriction on the SWIFT payment system have highlighted the increased reliance of global economies on a single message service for international trade. This, along with high inflation in the US and falling global economies world-wide and the struggle of the USD to maintain its dominance is bringing about a concept of dedollarisation, where economies are trying to have their reserves in alternate currencies and have global trade in other currencies of choice. This paper discusses about a Globally Backed Stablecoin (GBS) that envelopes the benefits of blockchain and tries to overcome the negatives of Central Bank Digital Currency (CBDC) as an answer to the future of global trade where it becomes difficult to influence its value or usage by few participants and gives better transparency in the global trade. This is another step to ensure that economies are not held hostage by sanctions or threats and unlike the US Dollar or SWIFT systems, payment systems cannot be used as a weapon for economic wars.

References

[1]. Auer, R., Haene, P., & Holden, H. (2021). Multi-CBDC arrangements and the future of cross-border payments. BIS Papers. 1-17.

[2]. Bech, M. L., Faruqui, U., & Shirakami, T. (2020). Payments without borders. BIS Quarterly Review, 53-65.

[3]. Bianchi, J., & Lorenzoni, G. (2021). The Prudential Use of Capital Controls and Foreign Currency Reserves. National Bureau of Economic Research, Cambridge, 1-60.

[4]. Boar, C., & Wehrli, A. (2021). Ready, steady, go?- Results of the third BIS survey on central bank digital currency. BIS Papers, 1-20.

[5]. De Goede, M. (2020). Finance/security infrastructures. Review of International Political Economy, 28(2), 351-368. https://doi.org/10.1080/09692290.2020.1830832

[6]. Eichengreen, B., Chitu, L., & Mehl, A. (2016). Stability or upheaval? The currency composition of international reserves in the long run. IMF Economic Review, 64(2), 354-380. https://doi.org/10.1057/imfer.2015.19

[7]. Goldberg, L. S. (2011). The international role of the dollar: does it matter if this changes? Federal Reserve Bank of New York staff Report, (522), 1-24.

[8]. Igwe, I. O. C. (2018). History of the international economy: The Bretton Woods system and its impact on the economic development of developing countries. Athens Journal of Law, 4(2), 105-126. https://doi.org/10.30958/ajl.4.2.1

[9]. Ize, A., & Yeyati, E. L. (2006). Financial dedollarization: is it for real? Financial Dollarization, 38-63. https://doi.org/10.1057/9780230380257_3

[10]. Liao, G. Y., & Caramichael, J. (2022). Stablecoins: Growth Potential and Impact on Banking. International Finance Discussion Papers (IFDP), 1-24. https://doi.org/10.17016/IFDP.2022.1334

[11]. Park, H., & Son, J. C. (2022). Dollarization, inflation and foreign exchange markets: A cross country analysis. International Journal of Finance & Economics, 27(3), 2724-2736. https://doi.org/10.1002/ijfe.2295

[12]. Vieira, F. A., Holland, M., & Resende, M. F. (2012). Financial dollarization and systemic risks: new empirical evidence. Journal of International Money and Finance, 31(6), 1695-1714. https://doi.org/10.1016/j.jimonfin.2012.03.007

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Research Paper

Implementation of Law on Occupational Safety, Health, Welfare, Working Conditions Influence Robust Industrial Relations

Yerragola Prakash* , Bojja Charwak, Padishala Vijaya Kumar*

*-*** School of Management Studies, Jawaharlal Nehru Technological University, Kakinada, Andhra Pradesh, India.

Prakash, Y., Charwak, B., and Kumar, P. V. (2022). Implementation of Law on Occupational Safety, Health, Welfare, Working Conditions Influence Robust Industrial Relations. i-manager’s Journal on Management, 16(4), 5-24. https://doi.org/10.26634/jmgt.16.4.18755

Abstract

There is an obligation on the part of the employer to implement laws on occupational safety and working conditions that create a safe and healthy work environment at the workplace. A code of conduct between buyers and sellers has become mandated before purchasing the goods. In this regard, a multistage sampling method is adopted to study 3 textile units with a sample size of the workforce (n=1008). Exploratory and regression analysis are used to identify significant factors that contribute to robust industrial relations. Findings of this study indicate there is a significant influence of occupational safety category 1 and welfare factor that has a positive effect on the perception of the workforce on industrial relations. This study reveals that the employers, managers, and executives of the organization have to give high priority to the above factors to maintain harmonious industrial relations.

References

[1]. Ahasan, M. R., & Partanen, T. (2001). Occupational health and safety in the least developed countries-a simple case of neglect. Journal of Epidemiology, 11(2), 74-80. https://doi.org/10.2188/jea.11.74

[2]. Amponsah-Tawiah, K., & Dartey-Baah, K. (2011). Occupational health and safety: key issues and concerns in Ghana. International Journal of Business and Social Science, 2(14).

[3]. Aronsson, G. (1999). Contingent workers and health and safety. Work, Employment and Society, 13(3), 439-459. https://doi.org/10.1177/09500179922118024

[4]. Atusingwize, E., Musinguzi, G., Ndejjo, R., Buregyeya, E., Kayongo, B., Mubeezi, R., ... & Ssempebwa, J. C. (2019). Occupational safety and health regulations and implementation challenges in Uganda. Archives of Environmental & Occupational Health, 74(1-2), 58-65. https://doi.org/10.1080/19338244.2018.1492895

[5]. Baker, E., Israel, B. A., & Schurman, S. (1996). The integrated model: implications for worksite health promotion and occupational health and safety practice. Health Education Quarterly, 23(2), 175-190. https://doi.org/10.1177/109019819602300204

[6]. Bazas, T. (2001). Occupational health practice in Greece. Journal of Occupational Health, 43(3), 165-167. https://doi.org/10.1539/joh.43.165

[7]. Bevan, S. (2015). Economic impact of musculoskeletal disorders (MSDs) on work in Europe. Best Practice & Research Clinical Rheumatology, 29(3), 356-373. https://doi.org/10.1016/j.berh.2015.08.002

[8]. Chen, M. S., & Chan, A. (2010). Occupational health and safety in China: The case of state-managed enterprises. International Journal of Health Services, 40(1), 43-60. https://doi.org/10.2190/HS.40.1.c

[9]. Chu, K. H. L., & Murrmann, S. K. (2006). Development and validation of the hospitality emotional labor scale. Tourism Management, 27(6), 1181-1191. https://doi.org/10.1016/j.tourman.2005.12.011

[10]. Comrey, A. L., & Lee, H. B. (1992). Interpretation and Application of Factor Analytic Results. In A. L. Comrey, & H. B. Lee (Eds.), A First Course in Factor Analysis (p. 2). Hillsdale, NJ: Lawrence Eribaum Associates.

[11]. Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334. https://doi.org/10.1007/BF02310555

[12]. Haldiya, K. R., Sachdev, R., Mathur, M. L., & Saiyed, H. N. (2005). Knowledge, attitude and practices related to occupational health problems among salt workers working in the desert of Rajasthan, India. Journal of Occupational Health, 47(1), 85-88. https://doi.org/10.1539/joh.47.85

[13]. Hale, A., & Booth, R. (2019). The safety professional in the UK: Development of a key player in occupational health and safety. Safety Science, 118, 76-87. https://doi.org/10.1016/j.ssci.2019.04.015

[14]. Hamid, A. R. A., Razak, A. R. A., Yusof, A. M., Jaya, R. P., Zakaria, R., Aminudin, E., ... & Rashid, I. A. (2019). Noncompliance of the occupational safety and health legislation in the Malaysian construction industry. In IOP Conference Series: Earth and Environmental Science, 1-8. https://doi.org/10.1088/1755-1315/220/1/012043

[15]. Hamja, A., Maalouf, M., & Hasle, P. (2019). The effect of lean on occupational health and safety and productivity in the garment industry–a literature review. Production & Manufacturing Research, 7(1), 316-334. https://doi.org/10.1080/21693277.2019.1620652

[16]. Hutcheson, G., & Sofroniou, N. (1999). The Multivariate Social Scientist: Introductory Statistics Using Generalized Linear Models. Sage Publication, Thousand Oaks, CA. https://doi.org/10.4135/9780857028075

[17]. Ilić, A., Simić, J., &Krstić, I. (2019). The legal framework of occupational safety and health system in serbia and Montenegro: comparative review. Facta Universitatis, Series: Law and Politics, 16(2), 121-130.

[18]. International Labour Organization. (2003). Safety in Numbers: Pointers for a Global Safety Culture at Work, 1-27. Retrieved from https://www.ilo.org/wcmsp5/groups/public/ed_protect/protrav/safework/documents/publication/wcms_142840.pdf

[19]. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate Data Analysis. Pearson Education Limited Harlow, Essex.

[20]. Kabir, H., Maple, M., Usher, K., & Islam, M. S. (2019). Health vulnerabilities of readymade garment (RMG) workers: a systematic review. BMC Public Health, 19(1), 1-20. https://doi.org/10.1186/s12889-019-6388-y

[21]. Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31-36. https://doi.org/10.1007/Bf02291575

[22]. Kline, P. (2000). The handbook of psychological testing. Psychology Press.

[23]. Hünefeld, L., Gerstenberg, S., & Hüffmeier, J. (2020). Job satisfaction and mental health of temporary agency workers in Europe: A systematic review and research agenda. Work & Stress, 34(1), 82-110. https://doi.org/10.1080/02678373.2019.1567619

[24]. Lipscomb, H. J., Loomis, D., McDonald, M. A., Argue, R. A., & Wing, S. (2006). A conceptual model of work and health disparities in the United States. International Journal of Health Services, 36(1), 25-50. https://doi.org/10.2190/ BRED-NRJ7-3LV7-2QCG

[25]. Manothum, A., Rukijkanpanich, J., Thawesaengskulthai, D., Thampitakkul, B., Chaikittiporn, C., & Arphorn, S. (2009). A participatory model for improving occupational health and safety: improving informal sector working conditions in Thailand. International Journal of Occupational and Environmental Health, 15(3), 305-314. https://doi.org/ 10.1179/oeh. 2009.15.3.305

[26]. Ministry of Textiles. (2020). Annual Report 2019-20. Retrieved from http://texmin.nic.in/sites/default/files/AR_MoT_2019-20_English.pdf

[27]. Nassiri, P., Abbasi, A. M., Poornadjaf, A., Shalkouhi, P. J., & Bahrami, P. (2019). Occupational noise and blood pressure variation. Lebanese Science Journal, 20(1), 148-160. http://dx.doi.org/10.22453/LSJ-020.1.148-160

[28]. Nishikido, N., Yuasa, A., Motoki, C., Tanaka, M., Arai, S., Matsuda, K., ... & Kawakami, Y. (2006). Development of multi-dimensional action checklist for promoting new approaches in participatory occupational safety and health in small and medium-sized enterprises. Industrial Health, 44(1), 35-41. https://doi.org/10.2486/indhealth.44.35

[29]. Nunnally, J. C. (1978). Psychometric theory 2E. Tata McGraw-hill education.

[30]. Nunnally, J. C. (1994). Psychometric theory 3E. Tata McGraw-Hill education.

[31]. Sinha, P. R. N., Sinha, I. B., & Shekhar, S. P. (2017). Industrial Relations, Trade Unions and Labour Legislation. Pearson Education, India.

[32]. Quinlan, M., Mayhew, C., & Bohle, P. (2001). The global expansion of precarious employment, work disorganization, and consequences for occupational health: placing the debate in a comparative historical context. International Journal of Health Services, 31(3), 507-536. https://doi.org/10.2190/22BK-9XC0-AK7L-M6QH

[33]. Ramos-Galarza, C., & Acosta-Rodas, P. (2019). Stress and productivity in workers of textile companies. Journal of Fashion Marketing and Management. 23(1), 17-29. https://doi.org/10.1108/JFMM-02-2018-0030

[34]. Ruiz-Frutos, C., Pinos-Mora, P., Ortega-Moreno, M., & Gómez-Salgado, J. (2019). Do companies that claim to be socially responsible adequately manage occupational safety and health?. Safety Science, 114, 114-121. https://doi.org/10.1016/j.ssci.2019.01.010

[35]. Samano-Rios, M. L., Ijaz, S., Ruotsalainen, J., Breslin, F. C., Gummesson, K., & Verbeek, J. (2019). Occupational safety and health interventions to protect young workers from hazardous work–A scoping review. Safety Science, 113, 389-403. https://doi.org/10.1016/ j.ssci.2018.11.024

[36]. Samuels, P. (2017). Advice on Exploratory Factor Analysis. Retrieved from http://bcu-test.eprints-hosting.org/6076/

[37]. Stefanović, V., Urošević, S., Mladenović- Ranisavljević, I., & Stojilković, P. (2019). Multi-criteria ranking of workplaces from the aspect of risk assessment in the production processes in which women are employed. Safety Science, 116, 116-126. https://doi.org/10.1016/j.ssci.2019.03.006

[38]. Stefanović, V., Urošević, S., Stević, Ž., & Mladenović- Ranisavljević, I. (2021). Multicriteria ranking of the influential factors of safety as criteria for development of the occupational safety and health climate. International Journal of Occupational Safety and Ergonomics, 27(3), 763-773. https://doi.org/10.1080/10803548.2019.1646474

[39]. Tafere, G. A., Beyera, G. K., & Wami, S. D. (2020). The effect of organizational and individual factors on health and safety practices: results from a cross-sectional study among manufacturing industrial workers. Journal of Public Health, 28, 173-179. https://doi.org/10.1007/s10389-019-01050-y

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Research Paper

A Study on Factors Affecting Online Food Delivery Experience

Poonam Arora* , Ritika Singh, Mohit Soni*, Karan Singhal****

*-**** St. Kabir Institute of Professional Studies, Ahmedabad, Gujarat, India.

Arora, P., Singh, R., Soni, M., and Singhal, K. (2022). A Study on Factors Affecting Online Food Delivery Experience. i-manager’s Journal on Management, 16(4), 25-30. https://doi.org/10.26634/jmgt.16.4.18884

Abstract

Before the pandemic, restaurants were gradually adapting to the food delivery platforms along with dine in. As the pandemic came in, people suddenly proceeded to live in their homes a lot more and do leisure activities from the comfort of their homes. As the pandemic surged and the implementation of government rules came into existence, consumers stopped dining-in. The only medium of resort was the adoption of digital aid. This study aims to understand the various factors that affect the Online Food Delivery Experience (OFDO). This quantitative study was conducted on 354 respondents following a descriptive research design using a structured questionnaire. The study showed that factors such as time-saving orientation, hygiene maintenance, good food quality, good e-service quality, and technological readiness among people have a positive influence on the Food Delivery platform experience. Where as, fear of privacy and security and perceived threats have a negative impact on the food delivery platform experience. A Chi-square test was used to analyse the influence of various factors such as time-saving orientation, E-Service quality, food quality and hygiene on the experience with food delivery platforms.

References

[1]. Ali, S., Khalid, N., Javed, H. M. U., & Islam, D. M. Z. (2020). Consumer adoption of online food delivery ordering (OFDO) services in Pakistan: The impact of the COVID-19 pandemic situation. Journal of Open Innovation: Technology, Market, and Complexity, 7(1), 10. https://doi.org/10.3390/joitmc7010010

[2]. Chai, L. T., & Yat, D. N. C. (2019). Online food delivery services: Making food delivery the new normal. Journal of Marketing Advances and Practices, 1(1), 62-77.

[3]. Chang, H. H., & Meyerhoefer, C. D. (2021). COVID 19 and the demand for online food shopping services: Empirical evidence from Taiwan. American Journal of Agricultural Economics, 103(2), 448-465. https://doi.org/10.1111/ajae.12170

[4]. Flanagan, E. W., Beyl, R. A., Fearnbach, S. N., Altazan, A. D., Martin, C. K., & Redman, L. M. (2021). The impact of COVID 19 stay at home orders on health behaviors in adults. Obesity, 29(2), 438-445. https://doi.org/10.1002/oby.23066

[5]. Hassen, T. B., El Bilali, H., & Allahyari, M. S. (2020). Impact of COVID-19 on food behavior and consumption in Qatar. Sustainability, 12(17), 6973. https://doi.org/10.3390/su12176973

[6]. Mehrolia, S., Alagarsamy, S., & Solaikutty, V. M. (2021). Customers response to online food delivery services during COVID 19 outbreak using binary logistic regression. International Journal of Consumer Studies, 45(3), 396-408. https://doi.org/10.1111/ijcs.12630

[7]. Pinto, P., Hawaldar, I. T., & Pinto, S. (2021). Antecedents of behavioral intention to use online food delivery services: An empirical investigation. Innovative Marketing, 17(1), 1-15. http://dx.doi.org/10.21511/im. 17(1).2021.01

[8]. Prasetyo, Y. T., Tanto, H., Mariyanto, M., Hanjaya, C., Young, M. N., Persada, S. F., ... & Redi, A. A. N. P. (2021). Factors affecting customer satisfaction and loyalty in online food delivery service during the COVID-19 pandemic: Its relation with open innovation. Journal of Open Innovation: Technology, Market, and Complexity, 7(1), 76. https://doi.org/10.3390/joitmc7010076

[9]. Raj, M., Sundararajan, A., & You, C. (2020). COVID-19 and digital resilience: Evidence from Uber Eats. arXiv preprint arXiv:2006.07204. https://doi.org/10.48550/arXiv.2006.07204

[10]. Shanmugam, K., Jeganathan, K., Basheer, M. S. M., Firthows, M. A. M., & Jayakody, A. (2020). Impact of business intelligence on business performance of food delivery platforms in Sri Lanka. Global Journal of Management and Business Research: G Interdisciplinary, 20(6), 39-51.

[11]. Singh, G. (2020). E-Readiness and Customer Perception about the E-Commerce during Lockdown: COVID-19 Perspectives. Swaranjali Publication, 2, (pp.14). http://dx.doi.org/10.2139/ssrn.3694279

[12]. Singh, S., Kumar, R., Panchal, R., & Tiwari, M. K. (2021). Impact of COVID-19 on logistics systems and disruptions in food supply chain. International Journal of Production Research, 59(7), 1993-2008. https://doi.org/10.1080/00207543.2020.1792000

[13]. Suhartanto, D., Helmi, M., Tan, K., Sjahroeddin, F., & Kusdibyo, L. (2019). Loyalty towards online food delivery service: the role of e-service quality and food quality. Journal of Foodservice Business Research, 22(1), 81-97. https://doi.org/10.1080/15378020.2018.1546076

[14]. Sukhwani, V., Deshkar, S., & Shaw, R. (2020). Covid- 19 lockdown, food systems and urban–rural partnership: Case of Nagpur, India. International Journal of Environmental Research and Public Health, 17(16), 5710. https://doi.org/10.3390/ijerph17165710

[15]. Zhao, Y., & Bacao, F. (2020). What factors determining customer continuingly using food delivery apps during 2019 novel coronavirus pandemic period? International Journal of Hospitality Management, 91, (pp. 102683). https://doi.org/10.1016/j.ijhm.2020.102683

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Research Paper

Selection of Best Scooter Model using the Fuzzy- AHP MCDM Methodology

Debojit Roy* , Soupayan Mitra**

*-** Department of Mechanical Engineering, Jalpaiguri Government Engineering College, Jalpaiguri, West Bengal, India.

Roy, D., and Mitra, S. (2022). Selection of Best Scooter Model using the Fuzzy- AHP MCDM Methodology. i-manager’s Journal on Management, 16(4), 31-41. https://doi.org/10.26634/jmgt.16.4.18917

Abstract

The Multi-Criteria Decision Making (MCDM) is a new and advanced managerial tool for evaluating the best solution at the optimal level. The main purpose of the MCDM tool is to solve complex decision problems where the decision-makers are experiencing lots of conflicts. The decisions are to be made based on the criteria and their relative importance. If the decision that has to be taken have financial and resource involvement, the decision has to be taken very attentively. Selecting the best-suited scooter also involves many complex aspects like design and ergonomics, power output, fuel economy, price, and many other aspects. The objectives of this particular work are to find the best scooter model among four selective alternatives and to study and evaluate various MCDM tools like the Fuzzy-AHP methods, which are vigorously used in solving different complex decision or selection problems based on criteria associated with this problem.

References

[1]. Anupama, K. S. S., Gowri, S. S., Rao, B. P., & Rajesh, P. (2015). Application of madm algorithms to network selection. International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering, 3(6), 64-67.

[2]. Biswas, T. K., Chaki, S., & Das, M. C. (2019). MCDM technique application to the selection of an Indian institute of technology. Operational Research in Engineering Sciences: Theory and Applications, 2(3), 65-76.

[3]. Brauers, W.K. (2004). Optimization Methods for a Stakeholder Society. A Revolution in Economic Thinking by Multiobjective Optimization. Kluwer Academic Publishers, Boston.

[4]. Buckley, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17(3), 233-247. https://doi.org/10.1016/0165-0114(85)90090-9

[5]. Buckley, J. J., Feuring, T., & Hayashi, Y. (2001). Fuzzy hierarchical analysis revisited. European Journal of Operational Research, 129(1), 48-64. https://doi.org/10.1016/S0377-2217(99)00405-1

[6]. Chaibate, H., Hadek, A., Ajana, S., & Bakkali, S. (2021). Analytical hierarchy process applied to pedagogical method selection problems. Education Research International, 2021, 1-13. https://doi.org/10.1155/2021/6664758

[7]. Chen, Y., & Qu, L. (2006). Evaluating the selection of logistics centre location using fuzzy MCDM model based on entropy weight. In 2006, 6th World Congress on Intelligent Control and Automation, 2, 7128-7132. https://doi.org/10.1109/WCICA.2006.1714468

[8]. de FSM Russo, R., & Camanho, R. (2015). Criteria in AHP: a systematic review of literature. Procedia Computer Science, 55, 1123-1132. https://doi.org/10.1016/j.procs.2015.07.081

[9]. Hasan, M. F., & Sobhan, M. A. (2020). Describing Fuzzy membership function and detecting the outlier by using five number summary of data. American Journal of Computational Mathematics, 10(3), 410-424. https://doi.org/10.4236/ajcm.2020.103022

[10]. Hwang, C. L., Lai, Y. J., & Liu, T. Y. (1993). A new approach for multiple objective decision making. Computers & Operations Research, 20(8), 889-899. https://doi.org/10.1016/0305-0548(93)90109-V

[11]. Jozaghi, A., Alizadeh, B., Hatami, M., Flood, I., Khorrami, M., Khodaei, N., & Ghasemi Tousi, E. (2018). A comparative study of the AHP and TOPSIS techniques for dam site selection using GIS: A case study of Sistan and Baluchestan Province, Iran. Geosciences, 8(12), 494. https://doi.org/10.3390/geosciences8120494

[12]. Kao, J. C., Wang, C. N., Nguyen, V. T., & Husain, S. T. (2022). A fuzzy mcdm model of supplier selection in supply chain management. Intelligent Automation and Soft Computing, 31(3), 1451-1466.

[13]. Kaya, I., Colak, M., & Terzi, F. (2019). A comprehensive review of fuzzy multi criteria decision making methodologies for energy policy making. Energy Strategy Reviews, 24, 207-228. https://doi.org/10.1016/j.esr.2019.03.003

[14]. Kung, J. Y., Chuang, T. N., & Ky, C. M. (2011). A fuzzy MCDM method to select the best company based on financial report analysis. In 2011, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011), 2013-2017. https://doi.org/10.1109/FUZZY.2011.6007679

[15]. Kuo, M. S., & Liang, G. S. (2011). Combining VIKOR with GRA techniques to evaluate service quality of airports under fuzzy environment. Expert Systems with Applications, 38(3), 1304-1312. https://doi.org/10.1016/j.eswa.2010.07.003

[16]. Lokare, V. T., & Jadhav, P. M. (2016). Using the AHP and TOPSIS methods for decision making in best course selection after HSC. In 2016, International Conference on Computer Communication and Informatics (ICCCI), 1-6. https://doi.org/10.1109/ICCCI.2016.7479937

[17]. Mukhametzyanov, I., & Pamucar, D. (2018). A sensitivity analysis in MCDM problems: A statistical approach. Decision Making: Applications in Management and Engineering, 1(2), 51-80.

[18]. Opricovic, S., & Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445-455. https://doi.org/10.1016/S0377-2217(03)00020-1

[19]. Radwan, N. (2014). What is the difference between AHP, Fuzzy AHP, Fuzzy Logic and Fuzzy Delphi method? Retrieved from https://www.researchgate.net/post/What_is_the_difference_between_AHP_Fuzzy_AHP_Fuzzy_Logic_and_Fuzzy_Delphi_method/548dd83ed4c11826128b45f4/citation/download

[20]. Saaty, T. L. (2014). Analytic Heirarchy Process. Wiley StatsRef: Statistics Reference Online. https://doi.org/10.1002/9781118445112.stat05310

[21]. Seçme, N. Y., Bayrakdaroğlu, A., & Kahraman, C. (2009). Fuzzy performance evaluation in Turkish banking sector using analytic hierarchy process and TOPSIS. Expert Systems with Applications, 36(9), 11699-11709. https://doi.org/10.1016/j.eswa.2009.03.013

[22]. Tang, Y. C., & Beynon, M. J. (2005). Application and development of a fuzzy analytic hierarchy process within a capital investment study. Journal of Economics and Management, 1(2), 207-230.

[23]. Taweesangrungroj, A., Rattanabanchuen, R., & Sinthupinyo, S. (2022). A Decision-Making Model of Technological-Focused Government Agency Selection of Technological Start-Up Businesses. Trends in Sciences, 19(1), 1749-1749. https://doi.org/10.48048/tis.2022.1749

[24]. Zadeh, L. A. (1965). Fuzzy Sets. Information and Control, 8(3), 338-353. https://doi.org/10.1016/S0019-9958(65)90241-X

[25]. Zeynali, M., Aghdaie, M.H., Rezaeiniya, N., & Zolfani, S.H. (2012). A hybrid fuzzy multiple criteria decision making (MCDM) approach to combination of materials selection. African Journal of Business Management, 6(45), 11171-11178. https://doi.org/10.5897/AJBM11.2022

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A Study on Insurance Policy Holders (Life) Purchasing Behavior with Reference to Rajamahendravaram, Andhra Pradesh

P. Hari Kumar* , P. V. V. Satyanarayana, P. Vijaya Kumar*

* Jawaharlal Nehru Technological University, Kakinada, Andhra Pradesh, India.

-* School of Management Studies, Jawaharlal Nehru Technological University, Kakinada, Andhra Pradesh, India.

Kumar, P. H., Satyanarayana, P. V. V., and Kumar, P. V. (2022). A Study on Insurance Policy Holders (Life) Purchasing Behavior with Reference to Rajamahendravaram, Andhra Pradesh. i-manager’s Journal on Management, 16(4), 42-50. https://doi.org/10.26634/jmgt.16.4.18940

Abstract

Human life is a very important asset and life insurance is one of the most significant types of insurance that provides financial protection to individuals and their families in the event of uncertain risks and losses. Life insurance provides both security and protection to individuals and promotes savings among people. This exploratory and descriptive study was selected with the aim of identifying the factors that influence customers' purchasing decisions for insurance policies and analyzing customer preferences when making life insurance investment decisions. Various insurance-related factors were discussed in the paper. Data for this study were collected from primary source as well as secondary sources. The survey area was limited to Rajamandravaram District of East Godavari, A.P., and nearly 220 respondents were considered as a sample size. The survey analyzed respondents' preferred type of insurance, preferred insurer, characteristics, benefits of insurance that attracted them to purchase, how satisfied they were with the life insurance they purchased, and what difficulties they encountered when they made decisions to purchase life insurance. The study also analyzed the association between preferred type of insurance policy and age.

References

[1]. Balaji, C. (2015). Customer awareness and satisfaction of life insurance policy holders with reference to Mayiladuthurai town. International Journal of Multidisciplinary Research and Development, 2(1), 145-147.

[2]. Chaudhary, S. (2016). Consumer perception regarding life insurance policies: A factor analytical approach. Pacific Business Review International, 9(6), 52-61.

[3]. Dash, G. (2013). A buyer vs. seller perspective of 7Ps in post-liberalisation Indian life insurance sector. Delhi Business Review, 14(1), 45-55.

[4]. Goel, S. (2014). Health insurance: An empirical study of consumer behaviour in Rohtak district of Haryana. International Journal of Research in Management, Science & Technology, 2(2), 69-72.

[5]. Guru, P., & Umamaheswari, D. (2018). An empirical investigation to analyses the factors influencing the consumer perception regarding life insurance policies using path analysis. International Journal Supply Chain Management, 7(5), 927-932.

[6]. Guru, P., & Umamaheswari, D. (2019). A study on factors deciding selection of policies of private life insurance companies among consumers in Thanjavur district. International Journal of Recent Technology and Engineering, 7, 45-48.

[7]. Khurana, S. (2013). Analysis of service quality gap in Indian life insurance industry. European Journal of Commerce and Management Research, 2(3), 41-48.

[8]. Mahajan, K. (2013). Analysing consumer decision making process in life insurance services. International Journal of Marketing, Financial Services & Management Research, 2(5), 60-68.

[9]. Ragunathan, M. V. (2016). A study on consumer behavior towards life insurance products with reference to Idbi fortis company limited, Dindigul district, International Journal of applied science, 6(8), 182-185.

[10]. Sidhardha, D., & Sumanth, M. (2017). Consumer buying behavior towards life insurance: An analytical study. International Journal of Commerce and Management Research, 3(7), 1-5.

[11]. Singh, H. (2014). An empirical study of life insurance consumer's behaviour in Uttar Pradesh. An Internationally Indexed Refereed Research Journal & A complete Periodical dedicated to Humanities & Social Science Research, 5(1), 1-7.

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A Study on Insurance Policy Holders (Life) Purchasing Behavior with Reference to Rajamahendravaram, Andhra Pradesh

P. Hari Kumar* , P. V. V. Satyanarayana**, P. Vijaya Kumar***

* Jawaharlal Nehru Technological University, Kakinada, Andhra Pradesh, India. **-*** School of Management Studies, Jawaharlal Nehru Technological University, Kakinada, Andhra Pradesh, India.

Kumar, P. H., Satyanarayana, P. V. V., and Kumar, P. V. (2022). A Study on Insurance Policy Holders (Life) Purchasing Behavior with Reference to Rajamahendravaram, Andhra Pradesh. i-manager’s Journal on Management, 16(4), 42-50. https://doi.org/10.26634/jmgt.16.4.18940

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* Grazing Minds Research & Consulting, Mumbai, Maharashtra, India.

** NCRD's Sterling Institute of Management Studies, Nerul, Navi Mumbai, Maharashtra, India.

Yerragola Prakash* , Bojja Charwak, Padishala Vijaya Kumar*

Poonam Arora* , Ritika Singh, Mohit Soni*, Karan Singhal****

P. Hari Kumar* , P. V. V. Satyanarayana, P. Vijaya Kumar*

* Jawaharlal Nehru Technological University, Kakinada, Andhra Pradesh, India.

-* School of Management Studies, Jawaharlal Nehru Technological University, Kakinada, Andhra Pradesh, India.