Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2019, , 1 - 16, 17.06.2019
https://doi.org/10.34109/ijefs.201911101

Öz

Kaynakça

  • Abell, D. F. (1980). Defining the Business: The Starting Point for Strategic Planning. Englewood Cliffs NJ: Prentice-Hall.
  • Agarwal, R. C., Aggarwal, C. C. & Prasad, V. V. V. (2001). A tree projection algorithm for generation of frequent item sets. Journal of Parallel and Distributed Computing, 61(3), 350-371.
  • Aslan, M. (2017). Economic approach to strategic decisions, global business strategies in crisis, Springer International Publishing, 15-29.
  • Athiyaman, A. (2014). Using data to gain insights into biomass home heating, The 2014 Pellet Fuel Institute Annual Conference, Orlando, FL, July 26-29.
  • Athiyaman, A. (2018). Developing the US biomass residential heating market: insights from research, International Journal of Social Ecology and Sustainable Development, 9(4), 16-34.
  • Athiyaman, A. (2015a). Market potential for residential biomass beating equipment: stochastic and econometric assessments, International Journal of Sustainable Economies Management, 4(3), 2015a, 1-15.
  • Athiyaman, A. (2015b). Biomass residential heating: semantic structure and implications for advertising, Studies in Agricultural Economics, 117(1), 57-60.
  • Bain, J. S. (1968). Industrial Organization: A Treatise. Vol. 2. London: John Wiley.
  • Barker, D. I., Barker, M. S. & Pinard, K. T. (2012). Internet Research (Illustrated). 6th ed. Boston, MA: Cengage.
  • Biel, A. (1990). Strong brand, high spend, Admap, (November), 35-40. Bracmort, K. (2015). Biomass: comparison of definitions in legislation, Congressional Research Service Report, 7-5700.
  • Bullock, G, & Yu, P. (2016). Mental budgets and green consumerism: consumer responses to categorization of organic premiums, Proceedings of the 2016 Academy of Management, Vol, No. 1, 15074.
  • Choo, C. W., Detlor, B & Turnbull, D. (2013). Web work: information seeking and knowledge work on the world wide eb, Spring Science & Business Media, Vol. 1.
  • Cocos, A., Apidianaki , M & Callison-Burch, C. (2017). Mapping the paraphrase database to wordnet, Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (SEM 2017), 84-90.
  • Day, G. S. (1981). The Product life cycle: analysis and applications issues, Journal of Marketing, 45(Fall), 60-67.
  • Forsyth, J. & Boucher, L. (2010). Winning the research revolution, Consumer and Shopper Insights, December 1-3.
  • Fusari, A. (2016). A new economics for modern dynamic economies: innovation, uncertainty and entrepreneurship, Vol. 219, Taylor & Francis.
  • Gershoff, A & Irwin, J. (2012). Why not choose green? consumer decision making for environmentally friendly products, The Oxford Handbook of Business and the Natural Environment, Oxford, UK: Oxford University Press, P. Bansal and A. Hoffman (eds.), 366–383.
  • Hearth, Patio & Barbecue Association. Hearth industry unit shipments. (2016). http://www.hpba.org/statistics/hpba-us-hearth-statistics. Accessed 2016/05/16.
  • Howard, J. A. (1989). Buyer Behavior in Marketing Strategy, Englewood Cliffs NJ: Prentice-Hall.
  • IMF Research Bulletin (2018). https://www.imf.org/External/Pubs/FT/irb/ 2016/ 01/index.pdf .Accessed 2018/05/9
  • Kotler, P. (2017). Customer value management, Journal of Creating Value, 3(2), 170-172.
  • Lambert, T. E., Mattson, G. A., & Dorriere, K. (2017). The impact of growth and innovation clusters on unemployment in US metro regions, Regional Science Policy & Practice, 9(1), 25-37.
  • Llave, M. R. (2017). Business intelligence and analytics in small and mediumsized enterprises: a systematic literature review, Procedia Computer Science, 121, 194-205.
  • Lukas, E., Spengler, T. S., Stefan Kupfer, and Kieckhäfe, K. (2017) When and how much to invest? Investment and capacity choice under product life cycle uncertainty, European Journal of Operational Research, 260(3), 1105-1114.
  • Maddala, G.S. & Lahiri, K. (1992). Introduction to Econometrics (Vol. 2), New York: Macmillan.
  • Manyika, J., Michael, C., Jacques, B., Richard, D., Peter, B., & Alex, M. (2013). Disruptive technologies, McKinsey Quarterly, May 2013, 1-13.
  • Matsuyama, M. (2017). Competitive uncertainty and environmental scanning: The role of strategic – innocent quivocality, Business Policy and Strategy Conference, Academy of Management Annual Meeting Proceedings; 2017.
  • Qureshi, I.H. (2017). Marketing assets: A framework for differential advantage, Asian Journal of Management, 8(2), 220-228.
  • Rossiter, J. R., Consumer Behavior, Sydney, Australia: AGSM, 1996.
  • Rossiter, J. R. & Percy, L. (1997). Advertising Communications & Promotion Management, Boston, MA: Irwin-McGraw-Hill.
  • Schumpeter, J. A. (1939). Business Cycles, Vol. 1, New York: McGraw Hill.
  • Sethuraman, R, & Tellis, G. J. (1991). An analysis of the trade-off between advertising and price discounting, Journal of Marketing Research, 160-174.
  • Saravanakumar, K. & Cherukuri, A. K. (2014). Optimized web search results through additional retrieval lists inferred using wordnet similarity measure, Data Mining and Intelligent Computing (ICDMIC), 2014 International Conference, 1-7.
  • Spencer, S. (2011). Google Power Search, O'Reilly Media.
  • Srivastava, J. & Cooley, R. (2003). Web business intelligence: Mining the web for actionable knowledge, INFORMS Journal on Computing, 15(2), 191-207.
  • Steinhardt, G. (2017). Extending product life cycle stages, The product manager’s toolkit, Berlin: Springer International Publishing, 79-86.
  • Stephenson, E. & Pandit, A. (2008). How companies act on global trends: A Mckinsey survey. (2008). The McKinsey Quarterly, March 1-9.
  • U.S. Census Bureau. Annual Survey of Manufactures. (2016). https://www.census.gov/manufacturing/asm/historical_data/.2016/02/15.
  • Vidale, H. L. & Wolfe, H. B. (1957). An operations research study of sales response to advertising, Operations Research, 5, 370-381.
  • Zimmerman, Alan & Blythe, Jim. (2017). Business to Business Marketing: A Global Perspective, Abingdon, UK: Routledge.

MARKET INTELLIGENCE FROM THE INTERNET: AN ILLUSTRATION USING THE BIOMASS HEATING INDUSTRY

Yıl 2019, , 1 - 16, 17.06.2019
https://doi.org/10.34109/ijefs.201911101

Öz

Extant research on marketing strategy suggests that most companies underuse web
intelligence as publicly available data on the Internet are considered hard to access
and analyse. This paper demonstrates how biomass home heating businesses can
utilise the Internet for data collection and business insights. The market structure
of the biomass heating industry was identified using the Google Correlate
algorithm. The production rule ‘that newer the product the higher is consumer
search for the product’ was operationalised using the correlations of the concept
‘home heating equipment’. Intra-industry competition was assessed using
Google’s brand impression analysis and firm behaviour and performance were
modelled using a differential equation relating product sales to marketing
expenditures. Empirical analysis reveals that the product form “biomass home
heating” is growing, pellet stoves and fireplace inserts top the lists of “stove”
searches, there are two competitive clusters of biomass firms and the marketing
spending for the industry is well below its optimum level needed to increase and
maintain sales.
Keywords: Market intelligence, Biomass home heating, US biomass markets,
Marketing optimisation, Google tools

Kaynakça

  • Abell, D. F. (1980). Defining the Business: The Starting Point for Strategic Planning. Englewood Cliffs NJ: Prentice-Hall.
  • Agarwal, R. C., Aggarwal, C. C. & Prasad, V. V. V. (2001). A tree projection algorithm for generation of frequent item sets. Journal of Parallel and Distributed Computing, 61(3), 350-371.
  • Aslan, M. (2017). Economic approach to strategic decisions, global business strategies in crisis, Springer International Publishing, 15-29.
  • Athiyaman, A. (2014). Using data to gain insights into biomass home heating, The 2014 Pellet Fuel Institute Annual Conference, Orlando, FL, July 26-29.
  • Athiyaman, A. (2018). Developing the US biomass residential heating market: insights from research, International Journal of Social Ecology and Sustainable Development, 9(4), 16-34.
  • Athiyaman, A. (2015a). Market potential for residential biomass beating equipment: stochastic and econometric assessments, International Journal of Sustainable Economies Management, 4(3), 2015a, 1-15.
  • Athiyaman, A. (2015b). Biomass residential heating: semantic structure and implications for advertising, Studies in Agricultural Economics, 117(1), 57-60.
  • Bain, J. S. (1968). Industrial Organization: A Treatise. Vol. 2. London: John Wiley.
  • Barker, D. I., Barker, M. S. & Pinard, K. T. (2012). Internet Research (Illustrated). 6th ed. Boston, MA: Cengage.
  • Biel, A. (1990). Strong brand, high spend, Admap, (November), 35-40. Bracmort, K. (2015). Biomass: comparison of definitions in legislation, Congressional Research Service Report, 7-5700.
  • Bullock, G, & Yu, P. (2016). Mental budgets and green consumerism: consumer responses to categorization of organic premiums, Proceedings of the 2016 Academy of Management, Vol, No. 1, 15074.
  • Choo, C. W., Detlor, B & Turnbull, D. (2013). Web work: information seeking and knowledge work on the world wide eb, Spring Science & Business Media, Vol. 1.
  • Cocos, A., Apidianaki , M & Callison-Burch, C. (2017). Mapping the paraphrase database to wordnet, Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (SEM 2017), 84-90.
  • Day, G. S. (1981). The Product life cycle: analysis and applications issues, Journal of Marketing, 45(Fall), 60-67.
  • Forsyth, J. & Boucher, L. (2010). Winning the research revolution, Consumer and Shopper Insights, December 1-3.
  • Fusari, A. (2016). A new economics for modern dynamic economies: innovation, uncertainty and entrepreneurship, Vol. 219, Taylor & Francis.
  • Gershoff, A & Irwin, J. (2012). Why not choose green? consumer decision making for environmentally friendly products, The Oxford Handbook of Business and the Natural Environment, Oxford, UK: Oxford University Press, P. Bansal and A. Hoffman (eds.), 366–383.
  • Hearth, Patio & Barbecue Association. Hearth industry unit shipments. (2016). http://www.hpba.org/statistics/hpba-us-hearth-statistics. Accessed 2016/05/16.
  • Howard, J. A. (1989). Buyer Behavior in Marketing Strategy, Englewood Cliffs NJ: Prentice-Hall.
  • IMF Research Bulletin (2018). https://www.imf.org/External/Pubs/FT/irb/ 2016/ 01/index.pdf .Accessed 2018/05/9
  • Kotler, P. (2017). Customer value management, Journal of Creating Value, 3(2), 170-172.
  • Lambert, T. E., Mattson, G. A., & Dorriere, K. (2017). The impact of growth and innovation clusters on unemployment in US metro regions, Regional Science Policy & Practice, 9(1), 25-37.
  • Llave, M. R. (2017). Business intelligence and analytics in small and mediumsized enterprises: a systematic literature review, Procedia Computer Science, 121, 194-205.
  • Lukas, E., Spengler, T. S., Stefan Kupfer, and Kieckhäfe, K. (2017) When and how much to invest? Investment and capacity choice under product life cycle uncertainty, European Journal of Operational Research, 260(3), 1105-1114.
  • Maddala, G.S. & Lahiri, K. (1992). Introduction to Econometrics (Vol. 2), New York: Macmillan.
  • Manyika, J., Michael, C., Jacques, B., Richard, D., Peter, B., & Alex, M. (2013). Disruptive technologies, McKinsey Quarterly, May 2013, 1-13.
  • Matsuyama, M. (2017). Competitive uncertainty and environmental scanning: The role of strategic – innocent quivocality, Business Policy and Strategy Conference, Academy of Management Annual Meeting Proceedings; 2017.
  • Qureshi, I.H. (2017). Marketing assets: A framework for differential advantage, Asian Journal of Management, 8(2), 220-228.
  • Rossiter, J. R., Consumer Behavior, Sydney, Australia: AGSM, 1996.
  • Rossiter, J. R. & Percy, L. (1997). Advertising Communications & Promotion Management, Boston, MA: Irwin-McGraw-Hill.
  • Schumpeter, J. A. (1939). Business Cycles, Vol. 1, New York: McGraw Hill.
  • Sethuraman, R, & Tellis, G. J. (1991). An analysis of the trade-off between advertising and price discounting, Journal of Marketing Research, 160-174.
  • Saravanakumar, K. & Cherukuri, A. K. (2014). Optimized web search results through additional retrieval lists inferred using wordnet similarity measure, Data Mining and Intelligent Computing (ICDMIC), 2014 International Conference, 1-7.
  • Spencer, S. (2011). Google Power Search, O'Reilly Media.
  • Srivastava, J. & Cooley, R. (2003). Web business intelligence: Mining the web for actionable knowledge, INFORMS Journal on Computing, 15(2), 191-207.
  • Steinhardt, G. (2017). Extending product life cycle stages, The product manager’s toolkit, Berlin: Springer International Publishing, 79-86.
  • Stephenson, E. & Pandit, A. (2008). How companies act on global trends: A Mckinsey survey. (2008). The McKinsey Quarterly, March 1-9.
  • U.S. Census Bureau. Annual Survey of Manufactures. (2016). https://www.census.gov/manufacturing/asm/historical_data/.2016/02/15.
  • Vidale, H. L. & Wolfe, H. B. (1957). An operations research study of sales response to advertising, Operations Research, 5, 370-381.
  • Zimmerman, Alan & Blythe, Jim. (2017). Business to Business Marketing: A Global Perspective, Abingdon, UK: Routledge.
Toplam 40 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Araştırma Makalesi
Yazarlar

Adee Athiyaman Bu kişi benim

Thebe Magapa Bu kişi benim

Yayımlanma Tarihi 17 Haziran 2019
Yayımlandığı Sayı Yıl 2019

Kaynak Göster

APA Athiyaman, A., & Magapa, T. (2019). MARKET INTELLIGENCE FROM THE INTERNET: AN ILLUSTRATION USING THE BIOMASS HEATING INDUSTRY. International Journal of Economics and Finance Studies, 11(1), 1-16. https://doi.org/10.34109/ijefs.201911101
AMA Athiyaman A, Magapa T. MARKET INTELLIGENCE FROM THE INTERNET: AN ILLUSTRATION USING THE BIOMASS HEATING INDUSTRY. IJEFS. Haziran 2019;11(1):1-16. doi:10.34109/ijefs.201911101
Chicago Athiyaman, Adee, ve Thebe Magapa. “MARKET INTELLIGENCE FROM THE INTERNET: AN ILLUSTRATION USING THE BIOMASS HEATING INDUSTRY”. International Journal of Economics and Finance Studies 11, sy. 1 (Haziran 2019): 1-16. https://doi.org/10.34109/ijefs.201911101.
EndNote Athiyaman A, Magapa T (01 Haziran 2019) MARKET INTELLIGENCE FROM THE INTERNET: AN ILLUSTRATION USING THE BIOMASS HEATING INDUSTRY. International Journal of Economics and Finance Studies 11 1 1–16.
IEEE A. Athiyaman ve T. Magapa, “MARKET INTELLIGENCE FROM THE INTERNET: AN ILLUSTRATION USING THE BIOMASS HEATING INDUSTRY”, IJEFS, c. 11, sy. 1, ss. 1–16, 2019, doi: 10.34109/ijefs.201911101.
ISNAD Athiyaman, Adee - Magapa, Thebe. “MARKET INTELLIGENCE FROM THE INTERNET: AN ILLUSTRATION USING THE BIOMASS HEATING INDUSTRY”. International Journal of Economics and Finance Studies 11/1 (Haziran 2019), 1-16. https://doi.org/10.34109/ijefs.201911101.
JAMA Athiyaman A, Magapa T. MARKET INTELLIGENCE FROM THE INTERNET: AN ILLUSTRATION USING THE BIOMASS HEATING INDUSTRY. IJEFS. 2019;11:1–16.
MLA Athiyaman, Adee ve Thebe Magapa. “MARKET INTELLIGENCE FROM THE INTERNET: AN ILLUSTRATION USING THE BIOMASS HEATING INDUSTRY”. International Journal of Economics and Finance Studies, c. 11, sy. 1, 2019, ss. 1-16, doi:10.34109/ijefs.201911101.
Vancouver Athiyaman A, Magapa T. MARKET INTELLIGENCE FROM THE INTERNET: AN ILLUSTRATION USING THE BIOMASS HEATING INDUSTRY. IJEFS. 2019;11(1):1-16.

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