i-manager Publications

i-manager's Journal on Management (JMGT)

Current Issue Vol. 18 Issue 3

Looking Forward to the Debate of Future Business Towards Digital Transformation
Opportunities of Tourism and Hospitality Education in Bangladesh: Career Perspectives
Creating Loyalty through Relationship Marketing in Mobile Financial Service Industry: Moderating Role of Client Demographics
Impact of Digital Marketing on Consumer Behavior in Small Medium Entrepreneurship Businesses in Malawi
Measuring Sustainability in the Broadcasting Media Industry in Bangladesh

Most Cited

Volume 15 Issue 1 June - August 2020

Article

Impact and Role of Artificial Intelligence in Sales and Marketing

Arun Kumar Neeli*

MBA Marketing, Palamuru University, Telangana, India.

Kumar, N. A. (2020). Impact and Role of Artificial Intelligence in Sales and Marketing. i-manager's Journal on Management, 15(1), 1-6. https://doi.org/10.26634/jmgt.15.1.17067

Abstract

In the recent years there have been rapid advances in the fields of information technology, processing power, data handling methods, robotics, and artificial intelligence. These advances impact businesses all over the world and play as a key role in their growth and development. Artificial Intelligence as a concept is changing the way companies work. Due to the enormous potential and applicability it is being implemented in many fields like information technology, retail industry, space science, automobile Industry, entertainment, medical, transportation, medical, social sciences, business management, etc. In this paper we will explore What is AI and how the advances of AI are impacting the growth and evolution of sales and marketing field. Additionally this paper discusses how different techniques and methods of AI are changing the activities and functions of sales and marketing. Finally, we will conclude with analysis on the present role of AI in lives of sales and marketing professionals.

References

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[3]. Balakrishnan, P. S., Cooper, M. C., Jacob, V. S., & Lewis, P. A. (1996). Comparative performance of the FSCL neural net and K-means algorithm for market segmentation. European Journal of Operational Research, 93(2), 346- 357. https://doi.org/10.1016/0377-2217(96)00046-X

[4]. Casabayó, M., Agell, N., & Sánchez-Hernández, G. (2015). Improved market segmentation by fuzzifying crisp clusters: A case study of the energy market in Spain. Expert Systems with Applications, 42 (3), 1637-1643. https://doi. org/10.1016/j.eswa.2014.09.044

[5]. Cespedes, F. V. (1994). Industrial marketing: Managing new requirements. Mit Sloan Management Review, 35(3), 45.

[6]. Chen, H., & Zimbra, D. (2010). AI and opinion mining. IEEE Intelligent Systems, 25(3), 74-80.

[7]. Coussement, K., & Van den Poel, D. (2008). Churn prediction in subscription services: An application of support vector machines while comparing two parameterselection techniques. Expert Systems with Applications, 34(1), 313-327.

[8]. Courville, A., Goodfellow, I., Bengio, Y., & Bengio, Y. (2016). Deep Learning (Vol. 1). Cambridge: MIT Press.

[9]. Eggel, T., & Reinhold, M. (2014). Second generation recommendation engines in a SME B2B context: A case study. In 13th Internation Science-to-Bussiness Marketting Conference, Winterthur.

[10]. Florez-Lopez, R., & Ramon-Jeronimo, J. M. (2009). Marketing segmentation through machine learning models: An approach based on customer relationship management and customer profitability accounting. Social Science Computer Review, 27(1), 96-117. https://doi.org/10.1177%2F0894439308321592

[11]. Ghose, T. K., & Tran, T. T. (2010, May). A dynamic pricing approach in e-commerce based on multiple purchase attributes. In Canadian Conference on Artificial Intelligence (pp. 111-122). Berlin, Heidelberg: Springer.

[12]. Huang, B., Kechadi, M. T., & Buckley, B. (2012). Customer churn prediction in telecommunications. Expert Systems with Applications, 39(1), 1414-1425. https://doi. org/10.1016/j.eswa.2011.08.024

[13]. Huang, J. J., Tzeng, G. H., & Ong, C. S. (2007). Marketing segmentation using support vector clustering. Expert Systems with Applications, 32(2), 313-317. https:// doi.org/10.1016/j.eswa.2005.11.028

[14]. Hülsmann, M., Borscheid, D., Friedrich, C. M., & Reith, D. (2012). General sales forecast models for automobile markets and their analysis. Transactions on Machine Learning and Data Mining, 5(2), 65-86

[15]. Järvinen, J., & Taiminen, H. (2016). Harnessing marketing automation for B2B content marketing. Industrial Marketing Management, 54, 164-175.

[16]. Martínez, A., Schmuck, C., Pereverzyev Jr, S., Pirker, C., & Haltmeier, M. (2020). A machine learning framework for customer purchase prediction in the non-contractual setting. European Journal of Operational Research, 281(3), 588-596.

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[20]. Perakakis, E., Mastorakis, G., & Kopanakis, I. (2019). Social media monitoring: An Innovative Intelligent Approach. Designs, 3(2), 24-36. https://doi.org/10.3390/ designs3020024

[21]. Rafiei, M. H., & Adeli, H. (2016). A novel machine learning model for estimation of sale prices of real estate units. Journal of Construction Engineering and Management, 142(2).

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[24]. Rosienkiewicz, M. (2019, September). Accuracy assessment of artificial intelligence-based hybrid models for spare parts demand forecasting in mining industry. In International Conference on Information Systems Architecture and Technology (pp. 176-187). Springer, Cham.

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[29]. Yeo, J., Kim, S., Koh, E., Hwang, S. W., & Lipka, N. (2016, April). Browsing2purchase: Online customer model for sales forecasting in an e-commerce site. In Proceedings of the 25th International Conference Companion on World Wide Web (pp. 133-134). https://doi.org/10.1145/ 2872518. 2889394

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Research Paper

Factors Affecting Performance of Small and Micro Enterprises: Owner's Gender based Comparative Analysis in Assosa Zone, Benishangulgumuz Region, Ethiopia

Abdurkerim Hedo Geleto* , D. Guruswamy**

*-** Department of Accounting & Finance College of Business & Economics, Arsi University, Asella, Ethiopia.

Geleto, A. H., and Guruswamy, D. (2020). Factors Affecting Performance of Small and Micro Enterprises: Owner's Gender based Comparative Analysis in Assosa Zone, Benishangulgumuz Region, Ethiopia. i-manager's Journal on Management, 15(1), 7-18. https://doi.org/10.26634/jmgt.15.1.17089

Abstract

The study sought to examine factors that influence performance of small and micro enterprises through owner's gender based comparative study in Assosa Zone, Ethiopia. Explanatory research design was employed in the study. Primary and secondary data were collected from selected Small and Micro Enterprises, Central Statistical Agency and Ministry of Finance and Economic Development. Total population comprises 603 small and micro enterprises that are registered and doing business in Assosa Zone. Stratified random sampling technique was applied to select respondents from both female and male owned small and micro enterprises. Financial performance was dependent variable whereas education level, access to training, size of the business, age of business, access to credit, interest rate on credit, initial investment, and sector involved were independent variables employed for the analysis. The findings of the study revealed that access to credit, investment, sector involved in and size of small and micro enterprises are variables that significantly and statistically affect financial performance of male owned small and micro enterprises. In addition, education level, access to training and age of SMEs are variable that affect financial performance of female owned small and micro enterprises significantly and statistically.

References

[1]. Bekele, E., & Worku, Z. (2008). Women entrepreneurship in micro, small and medium enterprises: The case of Ethiopia. Journal of International Women's Studies, 10(2), 3-19.

[2]. Chirwa, W. (2004). Gender and Performance of Micro and Small Enterprises in Malawi. Development Southern Africa.

[3]. Cleary, P. D., & Angel, R. (1984). The analysis of relationships involving dichotomous dependent variables. Journal of Health and Social Behavior, 334-348.

[4]. Debelo, K. B., Teshome, A., & Minalu, T. (2015). Factors affecting developments of micro and small enterprises; case of Mettu, Hurumu, Bedelle and Gore towns of Ilu Aba Bora administrative zone. International Journal of Scientific and Research Publications. 5 (1).

[5]. Eshetu, T., Ketema, M., & Ketema, B. (2013). Economic impact of support service program on micro and small enterprises: The case of Dire Dawa Administration, Ethiopia. Agris Online Papers in Economics and Informatics, 5, 21-29.

[6]. Gebreeyesus, M. (2007). Growth of micro-enterprises: Empirical evidence from Ethiopia. Ethiopian Development Research Institute (EDRI), 1-21.

[7]. Geleta, D. S. (2013). Socio-economic contributions of micro and small enterprises: the case of Jimma City. Science, Technology and Arts Research Journal, 2(2), 123-134.

[8]. Haris, M., & Raviv, A. (2012). The theory of capital structure of small and medium enterprises. The Journal of Finance, 46(1), 297-355. https://doi.org/10.1111/j.1540- 6261.1991.tb03753

[9]. Hailu, H. K. (2010). Success factors in micro and small enterprises cluster development: Case of gullele handloom clusters in Ethiopia (Unpublished Masters dissertation). Pretoria: Graduate School of Business Leadership, University of South Africa.

[10]. Hundera, M. B. (2014). Micro and small scale enterprises (MSEs) development services in women's entrepreneurial start-ups in Ethiopia: A study conducted in three cities: Dire Dawa, Harar and Jigjiga. Journal of Behavioural Economics, Finance, Entrepreneurship, Accounting and Transport, 2(4), 77-88.

[11]. Inmyxai, S., & Takahashi, Y. (2012). Factors mediating gender and firm performance in LAO micro, small, and medium sized enterprises. Asia Pacific Management Review, 17(2), 145-175.

[12]. Kefale, M., & Chinnan, K. P. M. (2012). Employment growth and challenges in small and micro enterprises Woldiya, North East Amhara region, Ethiopia. Educational Research and Essays, 1(2), 21-26.

[13].Kiraka, N., Kobia., M, & Katwalo, M. (2013). Micro, small and medium enterprise growth and innovation in kenya: A case study on the women enterprise fund. Investment Climate and Business Environment Research Fund, 47(13).

[14]. Kothari, C. R. (2004). Research Methodology: Methods and Techniques. New Age International.

[15]. Olabisi, S. Y., Olagbemi, A. A., & Atere, A. A. (2011). Factors Affecting Small-Scale Business Performance in Informal Economy in Lagos State-Nigeria: A Gendered Based Analysis. Lagos: Lagos State University.

[16]. Osotimehin, K. O., Jegede, C. A., Akinlabi, B. H., & Olajide, O. T. (2012). An evaluation of the challenges and prospects of micro and small scale enterprises development in Nigeria. American International Journal of Contemporary Research, 2(4), 174-185.

[17]. Petro, M., Annastazia, M., and Robert, G. (2014).The effects of socio-cultural factors on the performance of women small and medium enterprises in Tanzania. Journal of Economics and Sustainable Development. 5(21).

[18]. Qureshi, H., Ayyub, S., Ramzan, M., Zaman, Q., & Yasir, M. (2012). Factors affecting small-business performance in Punjab-Pakistan: A gender based analysis. Interdisciplinary Journal of Contemporary Research in Business, 4(2).

[19]. Sherifat, Y. O. (2013). Gender differentials in factors affecting performance of small-scale enterprises in Lagos State, Nigeria. Innovative Issues and Approaches in Social Sciences, 6(2), 21-39.

[20]. Tefera, H., Gebremichael, A., & Abera, N. (2013). Growth determinants of micro and small enterprises: Evidence from Northern Ethiopia. Journal of Economics and Sustainable Development, 4(9), 127-134.

[21]. Wube, M. C. (2010). Factors affecting the performance of women entrepreneurs in micro and small enterprises: A case of dessie town. A (Post graduate Thesis) Bahir Dar University.

[22]. Yamane Taro (1967). Statistics, An Introductory Analysis, New York : Harper and Row.

[23]. Yusuff, S.,Olagbemi, A., & Atere, A. (2010). Factors affecting small-scale business performance in Informal economy in Lagos state-Nigeria: a gendered based Analysis. Lagos State University.

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Research Paper

The Design of Real Estate Housing Project in Bangkok and the Metropolitan, Thailand for the Year 2021

Vichian Puncreobutr * , Prachuab Trinokorn , Ubon Dhanesschaiyakupta , Jitrapun Pusapukdepob , Mark Anthony Cenas Pa-Alisbo

* Planning and Research, St Theresa International College, Bueng San, Thailand.

Business Administration, St Theresa International College, Bueng San, Thailand.

* Humanities and Social Sciences, St Theresa International College, Bueng San, Thailand.

Faculty of Public Health, St Theresa International College, Bueng San, Thailand.

* Faculty of Education, St. Theresa International College, Nakhon Nayok, Thailand.

Puncreobutr, V., Trinokorn, P., Dhanesschaiyakupta, U., Pusapukdepob, J., and Pa-Alisbo, M. A. C. (2020). The Design of Real Estate Housing Project in Bangkok and the Metropolitan, Thailand for the Year 2021. i-manager's Journal on Management, 15(1), 19-26. https://doi.org/10.26634/jmgt.15.1.17205

Abstract

The objective of this study is to develop the real estate housing project in the year 2021 and to study the design of real estate housing project for Bangkok and the metropolitan. This is a qualitative research, which consists of 2 phrases. The first phrase is the study by document analysis and in-depth interview with consumers looking to buy houses in the Bangkok and metropolitan area. Second phrase is the study by data analysis technique of the housing consumer demand, together with strategic cite forecast techniques. It is found from the study that 1) the concept of developing the housing project in 2021 is a detached house for the elderly and family. There will be a smart home suitable for two ages, middle-aged and elderly. It emphasizes on the importance of environment and inside facilities of the house, where the problem of polluted air PM 2.5 could be reduced. 2) The design of real estate housing project for 2021 consisted of 5 components: First component is the project style and location, consisted of project type, size of the project, location of the project, pricing, reputation of the operator and other services. Second component is the physical characteristic of the housing project, consisting of physical characteristic of the house, style, lay out of a house and the design of the house to be of a contemporary home. Third component is the interior design, consisting of an overall design of living room, dining area, kitchen area, bedroom, bath room and installation of electrical equipment. Fourth component is the layout of the common area, consisting of the club house, public parks, housing project management office, the environmental and utilities management, security system and management system when it becomes a Juristic Person. Fifth component is the design to be a smart home, consisting of security management, energy and resource management, convenience and comfort management, health and wellness management, and media entertainment.

References

[1]. Borirak. T. (2019). The Crisis Lessons from PM 2.5. Air Pollution. EAU Heritage Journal: Science and Technology, 13(3), 44-58.

[2]. Jakpaisan, N. (2017). Feasibility Study on Real-Estate Development for Industrial-Workers Around Amatanakorn Industrial Park (Chonburi). Bangkok: Thammasat University.

[3]. Puncreobutr, V., Waiyakarn, S., Dhamacharoen, A., & Singh, H. K. (2019). The Cause Source and Preventive Ways of PM2. 5 Dust in Bangkok, Thailand. SSRN Electronic Journal https://doi.org/10.2139/ssrn.3329098

[4]. Sirisunhirun, S. (2017). Feasibility Study of Residential Development for Active Adult (Generation B). (Post graduate thesis) Bangkok: Thammasat University.

[5]. Suranporn-In-Jaieuar. (2016). Generation marketing: Attitude and behavior of bangkok population toward single-detached home buying (Master Thesis), Bangkok: Thammasat University.

[6]. Tawha, N., & Chaivisit, P. (2016). The environmental management and housing for the elderly in Muang District, Nakhon Si Thammarat. Apheit Journal, 5(1), 31- 39.

[7]. Thammasat University Research and Consultancy Center. (2017). Thailand Housing Demand Forecast 2017- 2037. (Research Report). Bangkok: National Housing Authority.

[8]. Thirasophon, W. (2015). Factors affecting housing choice in the Bangkok Metropolitan region (Thesis of Master of Business Administration). Bangkok: Thammasat University.

[9]. Virameteekul, C. (2018). Development Guidelines for Future Residences for Seniors: Case Study of Creative Private Sector Housing. National Defense Course, Bangkok: National Defense College.

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Research Paper

The Future of Culinary Tourism: An Emerging Dimension for the Tourism Industry of Bangladesh

Mohammad Badruddoza Talukder*

Department of Tourism and Hospitality Management, Daffodil Institute of Information Technology (DIIT), Under National University, Bangladesh.

Talukder, M. B. (2020). The Future of Culinary Tourism: An Emerging Dimension for the Tourism Industry of Bangladesh. i-manager's Journal on Management, 15(1), 27-34. https://doi.org/10.26634/jmgt.15.1.17181

Abstract

Culinary tourism or gastronomic tourism experiences the food and drink of the country, region or area and is now considered a vital component of the hospitality experience. Eating out is common among tourists and foodies. A high percentage of travelers consider food to be relevant activities during their trip, although food and drink are essential for all tourists. The main objective of this research is to study the emerging problems of culinary tourism in Bangladesh. Culinary tourism campaigns around the world shows a secure link between tourism and food. Many professionals in the food sector in Bangladesh are expanding their field of activity to meet the growing demand for food tourists. In addition, they want to enjoy traditional, hygienic and safe food and beverage items. The research methodology used is an in-depth study of the literature and is based on secondary data and descriptive research. The researcher also emphasizes expert opinion to ensure the reliability of the study. The paper achieves with the current food tourism scenario and offers suggestions for improving and developing food tourism in Bangladesh.

References

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[2]. Hall, C. H. (2004). Preface. In Wine, Food and Tourism Marketing. New York: Haworth Hospitality Press.

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[6]. Mitchell, R., & Hall C. M. (2003). Consuming tourists: food tourism consumer behavior. In C.M. Hall (Eds). Food tourism around the world. Development, Management and Markets (pp. 60-80). Oxford: Butterworth-Heinemann.

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[8]. Smith, S. (2007). Analysis of tourists attending a culinary event: motivations, satisfaction, and behavioral outcomes (Doctoral dissertation). The University of Tennessee, Knoxville.

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[10]. WFTA (World Food Travel Association). (2013). What is Food Tourism? Retrieved from https://www.worldfoodtravel. org/our-story/what-is-food-tourism/

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Review Paper

Employee Turnover: Determinants, Consequences, Trends in Academia and the Implications on Organizational Effectiveness

Pleshette McPhee*

Bahamas Technical and Vocational Institute, Nassau Bahamas.

Mcphee, P. (2020). Employee Turnover: Determinants, Consequences, Trends in Academia and the Implications on Organizational Effectiveness. i-manager's Journal on Management, 15(1), 35-44. https://doi.org/10.26634/jmgt.15.1.17258

Abstract

Employee turnover is costly and a disruptive issue that affects organizational effectiveness. Human resource development (HRD) is concerned with the number of employees leaving. Leaders in HRD would prefer to retain employees than to see them leave a performance gap. This paper explores the determinants of employee turnover, its consequences, trends in academia and implications on institutional effectiveness. Secondary sources of data including peer reviewed articles were utilized. This paper aims to bring awareness to the performance gap and encourage university – based HRD practitioners to redirect efforts and resources to mitigate employee turnover in their institutions.

References

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[4]. Alkahtani, A. H. (2015). Investigating factors that influence employees' turnover intention: A review of existing empirical works. International Journal of Business and Management, 10(12). https://doi.org/10.5539/ijbm.v10n 4p136

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[6]. Ampomah, P., & Cudjor, S. K. (2015). The effect of employee turnover on organizations (Case study of electricity company of Ghana, Cape Coast). Asian Journal of Social Sciences and Management Studies, 2(1), 21-24.

[7]. Anvari, R., JianFu, Z., & Chermahini, S. H. (2014). Effective strategy for solving voluntary turnover problem among employees. Procedia - Social and Behavioral Sciences, 129, 186-190. https://doi.org/10.1016/j.sbspro. 2014.03.665

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[12]. Bilau, A. A., Ajagbe, A. M., Sholanke, A. B., & Sani, T. A. (2015). Impact of employee turnover in small and medium construction firms: A literature review. International Journal of Engineering Research & Technology (IJERT), 4(2), 977- 984.

[13]. Butali, N. D., Wesang'ula, P. M., & Mamuli, L. C. (2013). Effects of staff turnover on the employee performance of work at Masinde Muliro University of Science and Technology. International Journal of Human Resource Studies, 3(1), 1-8. https://doi.org/10.5296/ijhrs.v3i1.3111

[14]. Buzeti, J., Klun, M., & Stare, J. (2016). Evaluation of measures to reduce employee turnover in slovenian organisations. E+M - Ekonomie a Management, 19(1), 121-131. https://doi.org/10.15240/tul/001/2016-1-009

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[16]. Chen, Y.-C., Chen, H.-I., Tsui, P.-L., & Chiang, Y.-C. (2016). Contributing causes of employee loyalty of service personnel in international hotels. International Journal of Organizational Innovation (Online), 9(1), 107-118.

[17]. Choudhary, S. (2016). A study on retention management: How to keep your top talent. International Journal of Advanced Research in Management and Social Sciences, 5(3), 17-31.

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Vichian Puncreobutr * , Prachuab Trinokorn , Ubon Dhanesschaiyakupta , Jitrapun Pusapukdepob , Mark Anthony Cenas Pa-Alisbo