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정보기술, 기업 및 산업특성, 재고회전율 간의 관계에 대한 실증분석

Investigating the Relationships Among Inventory Turnover Performance, IT, and Firm and Industry Characteristics

  • 투고 : 2019.04.22
  • 심사 : 2019.05.27
  • 발행 : 2019.06.30

초록

본 연구는 다음의 세 가지 목적을 갖는다. 첫째, 98개 미국기업의 11년(1999년에서 2009년)치 자료를 통하여 정보기술(IT) 관련 투자가 기업의 재고회전율에 미치는 영향을 분석한다. 둘째, 기업 및 산업의 특성이 재고회전율에 미치는 영향을 살펴본다. 구체적으로, 기업의 특성을 반영하기 위하여 수직결합도(vertical integration)와 성장옵션(growth option)을 고려하였고 기업이 속한 산업의 특성을 반영하기 위해 산업역동성(industry dynamism)과 산업집중도(industry concentration)를 선택하였다. 셋째, 분석 대상기업의 재고회전율에 대한 시계열적 추세를 검토한다. 본 연구의 주요 결과는 다음과 같다. 첫째, 정보기술 투자와 성장옵션은 재고회전율에 양의 영향을 주었다. 둘째, 수직결합도와 산업집중도는 재고회전율은 음의 영향을 주었다. 셋째, 재고회전율에 대한 산업역동성의 효과는 양의 값을 보였다. 마지막으로 분석기간 동안 재고회전율과 '조정된 재고회전율'로 표현된 재고생산성(inventory productivity)의 상승추세를 확인하였다.

The objective of this study is three-fold: to investigate the relationship between information technology (IT) investment and inventory turnover, using 98 U.S. firms spanning eleven years (from 1999 to 2009); to analyze the correlation of inventory turnover with firm and industry characteristics, where vertical integration and growth options are chosen to reflect the features of the firm's internal characteristics, and industry dynamism and industry concentration are selected to represent the industry's competitive environment; and to examine time trends in inventory turnover. The significant findings include the following: (i) both IT investment and growth options have a positive impact on inventory turnover; (ii), but vertical integration and industry concentration have a negative impact on inventory turnover; (iii) the impact of industry dynamism on inventory turnover positive; and (iv) the time trends in inventory turnover and 'adjusted inventory turnover' have been increased during the sample period from 1999 to 2009.

키워드

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Fig. 1 Total U.S. business inventory over time

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Fig. 2 Total inventories over time: from a data set used in this research

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Fig. 3 Histogram for time-specific effect(Ct) for Model

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Fig. 4 Histogram for time-specific effect(Ct) for Model2

Table 1 The variables considered in Gaur et al. [23], Gaur and Kesavan [24], and the present study

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Table 2 Summary Statistics of the Variables

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Table 3 Results for Models 1 and 2

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Table 4 A summary of the conclusionsof the hypothesis tests

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Table 5 Estimates of Time-specific Fixed effect

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Table 6 Estimates of time variable

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Table 7 Results for Models 5 and 6

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참고문헌

  1. Andreyeva, T., Long, M,W., and Browenll, K,D., "The impact of food prices on consumption: a systemetics review of research on the price Elasticity of demand for food," American Journal of Public Health, Vol. 100, No. 2, pp. 216-222, 2010 https://doi.org/10.2105/AJPH.2008.151415
  2. Barua, A., Kriebel, C. H., and Mukhopadhyay, T., “Information technologies and business value: An analytic and empirical investigation,” Information Systems Research, Vol. 6, No. 1, pp. 3-23, 1995. https://doi.org/10.1287/isre.6.1.3
  3. Bender, D. H., "Financial impact of information processing," Journal of Management Information Systems, Vol. 3, No. 2, pp. 22-32, 1986 https://doi.org/10.1080/07421222.1986.11517760
  4. Bergh, D. D., “Product-market uncertainty, portfolio restructuring, and performance: An information processing and resource-based view,” Journal of Management, Vol. 24, No. 2, pp. 135-155, 1998. https://doi.org/10.1177/014920639802400201
  5. Bharadwaj, A. S., Bharadwaj, S. G., and Konsynski, B. R., “Information technology effects on firm performance as measured by Tobin's q,” Management Science, Vol. 45, No. 7, pp. 1008-1024, 1999. https://doi.org/10.1287/mnsc.45.7.1008
  6. Cachon, G. P. and Olivares, M., “Drivers of finished-goods inventory in the US automobile industry,” Management Science, Vol. 56, No. 1, pp. 202-216, 2010. https://doi.org/10.1287/mnsc.1090.1095
  7. Cannon, A. R., “Inventory improvement and financial performance,” International Journal of Production Economics, Vol. 115, No. 92, pp. 581-593, 2008. https://doi.org/10.1016/j.ijpe.2008.07.006
  8. Cao, C., Simin, T,, and Zhao, J., "Can growth options explain the trend in idiosyncratic risk?," Review of Financial Studies Vol. 21, No. 6, pp,2599-2633, 2008. https://doi.org/10.1093/rfs/hhl039
  9. Capkun, V., Hameri, A. P., and Weiss, L. A. Weiss., “On the relationship between inventory and financial performance in manufacturing companies,” International Journal of Operations & Production Management, Vol. 29, No. 8, pp. 789-806, 2009. https://doi.org/10.1108/01443570910977698
  10. Chari, M. D., Devaraj, S., and David, P., “Research note-the impact of information technology investments and diversification strategies on firm performance,” Management Science, Vol. 54, No. 1, pp. 224-234, 2008. https://doi.org/10.1287/mnsc.1070.0743
  11. Chen, H., Frank, M. Z., and Wu, O. Q., "What actually happened to the inventories of American companies between 1981 and 2000?" Management Science, Vol. 51, No. 7, pp. 1015-1031, 2005. https://doi.org/10.1287/mnsc.1050.0368
  12. Chen, H., Frank, M. Z., and Wu, O. Q., “US retail and wholesale inventory performance from 1981 to 2004,” Manufacturing & Service Operations Management, Vol. 9, No. 4, pp. 430-456, 2007. https://doi.org/10.1287/msom.1060.0129
  13. Choi, H. R., Park, B. J., Shin, J. J., and Keceli, Y., “Development of the automated gate system based on RFID/OCR in a container terminal,” Journal of the Korea Industrial Information Society, Vol. 12, No. 2, pp. 37-48, 2007.
  14. Cron, W. L. and Sobol, M. G., “The relationship between computerization and performance: a strategy for maximizing the economic benefits of computerization,” Information & Management, Vol. 6, No. 3, pp. 171-181, 1983. https://doi.org/10.1016/0378-7206(83)90034-4
  15. Dehgani, R., ""The impact of information technology and communication systems on the agility of supply chain management systems," https://doi.org/10.1108/K-10-2018-0532, 2019.
  16. Dess, G. G. and Beard, D. W., “Dimensions of organizational task environments,” Administrative Science Quarterly, Vol. 29, No. 1, pp. 52-73, 1984. https://doi.org/10.2307/2393080
  17. Dewan, S., Michael, S. C., and Min, C.K., “Firm characteristics and investments in information technology: Scale and scope effects,” Information Systems Research, Vol. 9, No. 3, pp. 219-232, 1998. https://doi.org/10.1287/isre.9.3.219
  18. Economic Report of the President., "The annual report of the council of economic advisors. In The Economics of the President," U.S. Government Printing Office, Washington, D.C, 2001.
  19. Eroglu, C. and Hofer, C., “Lean, leaner, too lean? The inventory-performance link revisited,” Journal of Operations Management, Vol. 29, No. 44, pp. 356-369, 2001. https://doi.org/10.1016/j.jom.2010.05.002
  20. Fan, T., Tao, F., Deng, S. and Li, S., "Impact of RFID technology on supply chain decisions with inventory inaccuracies," International Journal of Production Economics, Vol. 159, pp. 117-125, 2015. https://doi.org/10.1016/j.ijpe.2014.10.004
  21. Floyd, S. W. and Wooldridge., B., “Path analysis of the relationship between competitive strategy, information technology, and financial performance,” Journal of Management Information Systems, Vol. 7, No. 1, pp. 47-64, 1990. https://doi.org/10.1080/07421222.1990.11517880
  22. Frohlich, M. T. and Westbrook, R., “Demand chain management in manufacturing and services: web-based integration, drivers and performance,” Journal of Operations Management, Vol. 20, No. 66, pp. 729-745, 2002. https://doi.org/10.1016/S0272-6963(02)00037-2
  23. Gaur, V., Fisher, M. L., and Raman, A., “An econometric analysis of inventory turnover performance in retail services,” Management Science, Vol. 51, No. 2, pp. 181-194, 2005. https://doi.org/10.1287/mnsc.1040.0298
  24. Gaur, V. and Kesavan, S., "The effects of firm size and sales growth rate on inventory turnover performance in the U.S. retail sector," In Retail Supply Chain Management, Springer, pp. 25-52, 2015.
  25. Greenspan, A., "Maintaining Economic Volatility. Federal Reserve Board," Remarks in the Millennium Lecture Series, 1999.
  26. Grossman, G and Helpman, E., “Quality ladders and product cycles,” The Quarterly Journal of Economics, Vol. 106, No. 2, pp. 557-586, 1991. https://doi.org/10.2307/2937947
  27. Gurbaxani, V., and Whang, S., “The impact of information systems on organizations and markets,” Communications of the ACM, Vol. 34, No. 1, pp. 9-73, 1991.
  28. Hancerliogullari, G., Sen, A., and Aktunc, E.A., “Demand uncertainty and inventory turnover performance: An empirical analysis of the US retail industry,” International Journal of Physical Distribution and Logistics Management, Vol. 46, No. 6, pp. 681-708, 2016. https://doi.org/10.1108/IJPDLM-12-2014-0303
  29. Hausman, J. A. and Taylor, W. E., “Panel data and unobservable individual effects,” Econometrica, Vol. 49, No. 6, pp. 1377-1398, 1981. https://doi.org/10.2307/1911406
  30. Hawawini, G., Subramanian, V., and Verdin, P., “Is performance driven by industry or firm specific factors? A new look at the evidence,” Strategic Management Journal, Vol. 24, No. 1, pp. 1-16, 2003. https://doi.org/10.1002/smj.278
  31. Hill, C. W. and Hoskisson, R. E., “Strategy and structure in the multiproduct firm,” Academy of Management Review, Vol. 12, No. 2, pp. 331-341, 1987. https://doi.org/10.5465/amr.1987.4307949
  32. Hitt, L. M. and Brynjolfsson, E., “Productivity, business profitability, and consumer surplus: three different measures of information technology value,” MIS Quarterly, Vol. 20, No. 2, pp. 121-142, 1996. https://doi.org/10.2307/249475
  33. Imrohoroglu, A. and Tuzel, S., "Firm-level productivity, risk, and return," Management Science, Vol. 60, No. 8, pp. 2973-2009, 2014. https://doi.org/10.1287/mnsc.2013.1849
  34. Jorgenson, D. W., “Information technology and the US economy,” The American Economic Review, Vol. 91, No. 1, pp. 1-32, 2001. https://doi.org/10.1257/aer.91.1.1
  35. Jung, Y S., “A study on the manufacturing performance with ERP Systems,” Journal of the Korea Industrial Information Society, Vol. 6, No. 4, pp. 30-38, 2001.
  36. Keats, B. W. and Hitt, M. A., “A causal model of linkages among environmental dimensions, macro organizational characteristics, and performance,” Academy of management Journal, Vol. 31, No. 3, pp. 570-598, 1988. https://doi.org/10.2307/256460
  37. Kim, B., Na, J., and Kim, S., "Effects of target firm's inventory turnover on post-merger and acquisition performance," International Journal of Applied Management Science, Vol. 10, Issues. 3, DOI: 10.1504/IJAMS.2018.093800, 2018.
  38. Kim, G., Lin, W. T., and Simpson, N., “Evaluating the performance of U.S. manufacturing and service operations in the presence of IT: a Bayesian stochastic production frontier approach,” International Journal of Production Research, Vol. 53, No. 18, pp. 5500-5523, 2015. https://doi.org/10.1080/00207543.2015.1026616
  39. Kim, J. J., Cho, K. C., and Kim, J. W., “Medical information processing system based on wireless network using RFID,” Journal of the Korea Industrial Information Society, Vol. 11, No. 4, pp. 1-9, 2006.
  40. Lai, R. K., "Inventory signals." Harvard NOM Research Paper Series (06-09), 2006.
  41. Lee, H., Padamanabhan, P., and Whang, S., “Information distortion in supply chain: the bullwhip effect,” Management Science, Vol. 43, No. 4, pp. 546-558, 1997. https://doi.org/10.1287/mnsc.43.4.546
  42. Lee, H. H., Zhou, J., and Hsu, P. H., "The role of innovation in inventory turnover performance," Decision Support Systems, Vol. 76, pp. 35-44, 2015. https://doi.org/10.1016/j.dss.2015.02.010
  43. Lin, W. T. and Shao, B., “The business value of information technology and inputs substitution: the productivity paradox revisited,” Decision Support Systems, Vol. 42, No. 2, pp. 493-507, 2006. https://doi.org/10.1016/j.dss.2005.10.011
  44. Lin, W. T. and Chiang, C. Y., “The impacts of country characteristics upon the value of information technology as measured by productive efficiency,” International Journal of Production Economics, Vol. 132, No. 1, pp. 13-33, 2011. https://doi.org/10.1016/j.ijpe.2011.02.013
  45. Lin, W. T. and Zhao, N., "Measuring and comparing the performance of U.S. manufacturing and service operations in the presence of information technology," Working paper, 2015..
  46. Mason, E. S., “Price and production policies of large-scale enterprise,” The American Economic Review, Vol. 29, No. 1, pp. 61-74, 1939.
  47. Melville, N., Gurbaxani, V., and Kraemer, K., “The productivity impact of information technology across competitive regimes: The role of industry concentration and dynamism,” Decision Support Systems, Vol. 43, No. 1, pp. 229-242, 2007. https://doi.org/10.1016/j.dss.2006.09.009
  48. Mishra, S., Modi, S.B., and Animesh, A., “The relationship between information technology capability, inventory efficiency, and shareholder wealth: A firm-level empirical analysis,” Journal of Operation. Management, Vol. 31, No. 1, pp. 298-312, 2013. https://doi.org/10.1016/j.jom.2013.07.006
  49. Mukhopadhyay, T., Kekre, S., and Kalathur, S., “Business value of information technology: a study of electronic data interchange,” MIS Quarterly, Vol. 19, No. 2, pp. 137-156, 1995. https://doi.org/10.2307/249685
  50. Olivares, M. and Cachon, G. P., “Competing retailers and inventory: An empirical investigation of General Motors' dealerships in isolated US markets,” Management Science, Vol. 55, No. 9, pp. 1586-1604, 2009. https://doi.org/10.1287/mnsc.1090.1050
  51. Rabinovich, E., Dresner, M. E., and Evers, P.T., “Assessing the effects of operational processes and information systems on inventory performance,” Journal of Operations Management, Vol. 21, No. 1, pp. 63-80, 2003. https://doi.org/10.1016/S0272-6963(02)00041-4
  52. Rajagopalan, S. and Malhotra, A., “Have US manufacturing inventories really decreased? An empirical study,” Manufacturing & Service Operations Management, Vol. 3, No. 1, pp. 14-24, 2001. https://doi.org/10.1287/msom.3.1.14.9995
  53. Rumyantsev, S. and Netessine, S., “What can be learned from classical inventory models? A cross industry exploratory investigation,” Manufacturing & Service Operations Management, Vol. 9, No. 4, pp. 409-429, 2007. https://doi.org/10.1287/msom.1070.0166
  54. Sambamurthy, V., Bharadwaj, A., and Grover, V., “Shaping agility through digital options: re-conceptualizing the role of information technology in contemporary firms,” MIS Quarterly, Vol. 27, No. 2, pp. 237263, 2003.
  55. Scherer, F. M., and Ross, D., "Industrial market structure and economic performance," University of Illinois at Urbana-Champaign's Academy for entrepreneurial leadership historical research reference in entrepreneurship, 1990.
  56. Shah, R. and Shin, H., “Relationships among information technology, inventory, and profitability: an investigation of level invariance using sector level data,” Journal of Operations Management, Vol. 25, No. 4, pp. 768-784, 2007. https://doi.org/10.1016/j.jom.2007.01.011
  57. Sullivan, M, W., “How brand names affect the demand for two automobiles,” Journal of Marketing Research, Vol. 35, No. 2, pp. 54-65, 1998. https://doi.org/10.1177/002224379803500107
  58. Varian, H. R, Microeconomic Analysis (Vol. 2). New York: Norton, 1992.
  59. Vickery, S. K., Jayaram, J., Droge, C., and Calantone, R., “The effects of an integrative supply chain strategy on customer service and financial performance: an analysis of direct versus indirect relationships,” Journal of Operations Management, Vol. 21, No. 5, pp. 523-539, 2003. https://doi.org/10.1016/j.jom.2003.02.002
  60. Wan, X. and Sanders, N.R., "The negative impact of product variety: forecast bias, inventory levels, and the role of vertical integration," International Journal of Production Economics, Vol. 186. pp. 123-131. 2017. https://doi.org/10.1016/j.ijpe.2017.02.002
  61. WISTA (World Information Technology and Service Alliance)., Digital Planet. Vienna, VA, USA, 2002.