Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
research-article

Impact of working capital on firm performance: : Does IT matter?

Published: 14 March 2023 Publication History

Abstract

Although prior research in operations management has explored the working capital—firm performance relationship, the results from these studies remain inconclusive, with studies finding positive, curvilinear, or even insignificant relationships. This is largely due to contingent factors that make this relationship both complex and idiosyncratic. To strengthen the beneficial effect of working capital on performance, firms must therefore make appropriate investments that would foster more objective, informed, and firm‐specific working capital choices. This article examines one such investment, namely in information technology (IT), that can allow firms to optimize the working capital–firm performance relationship. This is important, as the role of IT in this relationship is yet to be explored. Using proprietary IT data from the Harte Hanks database, and based on a sample of 1,054 US‐based manufacturing firms during 2011–2013, we find that IT investment positively moderates the performance effects of inventory, payables, and receivables cycles, and that these moderating effects vary by the type of IT investment, namely IT infrastructure and IT labor. Drawing on the theory of the Smart Machine, we explain how IT infrastructure and IT labor perform distinct roles that can help automate (i.e., use technology to increase the speed and accuracy of process execution) and/or informate (i.e., use technology to create new information), thereby moderating the working capital–firm performance relationship. We argue and find evidence that, due to the largely transactional nature of working capital processes, IT infrastructure has a relatively stronger moderating effect on performance than IT labor.

Highlights

If your firm's working capital policies are not translating into performance gains—look at investments in IT as a way to accelerate such benefits.
IT can play a dual role in affecting the payoff from working capital—IT to automate and IT to informate processes.
Investment in IT infrastructure and IT labor play distinct facilitating roles in improving firm performance via effective working capital management—IT infrastructure's role in the speed and accuracy of working capital process execution makes it more important than IT labor.

References

[1]
Abdullah, A., Hashmi, M. A., & Iqbal, M. S. (2022). Impact of working capital management on firm profitability and liquidity: the moderating role of family ownership. Accounting Research Journal, 35, 676–697.
[2]
Ahmad, R., & Javaid, F. (2016). The moderating role of corporate governance on working capital management and firms performance. Journal of Global Economics, Management & Business Research, 7(3), 182–194.
[3]
Aktas, N., Croci, E., & Petmezas, D. (2015). Is working capital management value‐enhancing? Evidence from firm performance and investments. Journal of Corporate Finance, 30, 98–113.
[4]
Alti, A. (2006). How Persistent is the impact of market timing on capital structure? Journal of Finance, 61(4), 10–11.
[6]
Aral, S., Brynjolfsson, E., & Wu, D. J. (2006). Which came first, IT or productivity? New York University.
[7]
Aral, S., & Weill, P. (2007). IT Assets, organizational capabilities, and firm performance: How resource allocations and organizational differences explain performance variation. Organization Science, 18, 763–780.
[8]
Baker, M., & Wurgler, J. (2002). Market timing and capital structure. Journal of Finance, 57, 1–32.
[9]
Banker, R. D., Bardhan, I. R., Chang, H., & Lin, S. (2006). Plant Information Systems, Manufacturing Capabilities, and Plant Performance. MIS Quarterly, 30, 315–337.
[10]
Baños‐Caballero, S., García‐Teruel, P. J., & Martínez‐Solano, P. (2014). Working capital management, corporate performance, and financial constraints. Journal of Business Research, 67, 332–338.
[11]
Bardhan, I., Krishnan, V., & Lin, S. (2013). Business Value of Information Technology: Testing the Interaction Effect of IT and R & D on Tobin's Q. Information System Research, 24, 1147–1161.
[12]
Barker, J. M., Hofer, C., Hoberg, K., & Eroglu, C. (2022). Supplier inventory leanness and financial performance. Journal of Operation Management, 68, 385–407.
[13]
Barratt, M., & Oke, A. (2007). Antecedents of supply chain visibility in retail supply chains: A resource‐based theory perspective. Journal of Operation Management, 25, 1217–1233.
[14]
Bartelsman, E. J., Ricardo, J. C., & Lyons, R. K. (1994). Customer‐ and supplier‐driven externalities. American Economic Association, 84, 1075–1084.
[15]
Bascle, G. (2008). Controlling for endogeneity with instrumental variables in strategic management research. Strateg. Organ., 6, 285–327.
[16]
Bendig, D., Strese, S., & Brettel, M. (2017). The link between operational leanness and credit ratings. J. Oper. Manag., 52, 46–55.
[17]
Bharadwaj, A. (2000). A resource‐based perspective on information technology capability and firm performance: an empirical investigation. MISQ, 24, 169–196.
[18]
Bharadwaj, A., Sundar, B., & Konsynski, B. R. (1999). Information technology effects on firm performance as measured by Tobin's q. Management Science, 45, 1008–1024.
[19]
Blinder, A. S., & Maccini, L. J. (1991). Taking stock: A critical assessment of recent research on inventories. Journal of Economic Perspectives, 5, 73–96.
[20]
Bourgeois, L. J., & Singh, J. V. (1983). Organizational slack and political behavior among top management teams. Academic of Management Proceedings, 1983, 43–47.
[21]
Bravo, E. R., Santana, M., & Rodon, J. (2016). Automating and informating: roles to examine technology's impact on performance. Behavior of Information Technologies, 35, 586–604.
[22]
Bromiley, P. (1991). Testing a causal model of corporate risk taking and performance. Academy of Management Journal, 34, 37–59.
[23]
Brush, T. H., Bromiley, P., & Hendrickx, M. (2000). The free cash flow hypothesis for sales growth and firm performance. Strategic Management Journal, 19, 989–999.
[24]
Brynjolfsson, E., & Hitt, l. M. (2000). Beyond computation: Information technology, organizational transformation and business performance. Journal of Economic Perspective, 14, 23–48.
[25]
Bun, M. J. G., & Harrison, T. D. (2019). OLS and IV estimation of regression models including endogenous interaction terms. Economic Review, 38, 814–827.
[26]
Burton‐Jones, A. (2014). What have we learned from the smart machine? Information and Organisation, 24, 71–105.
[27]
Cai, Z., Huang, Q., Liu, H., & Liang, L. (2016). The moderating role of information technology capability in the relationship between supply chain collaboration and organizational responsiveness Evidence from China. International Journal of Operations & Production Management, 36, 63–83.
[28]
Cannon, A. R. (2008). Inventory improvement and financial performance. International Journal of Production Economics, 115(2), 581–593.
[29]
Capkun, V., Hameri, A., & Weiss, L. A. (2009). On the relationship between inventory and financial performance in manufacturing companies. International Journal of Operations & Production Management, 29, 789–806.
[30]
Certo, S. T., Withers, M. C., & Semadeni, M. (2017). A tale of two effects: Using longitudinal data to compare within‐and between‐firm effects. Strategic Management Journal, 38, 1536–1556.
[31]
Chari, M. D. R., Devaraj, S., & David, P. (2008). The Impact of Information Technology Investments and Diversification Strategies on Firm Performance. Management Science, 54, 224–234.
[32]
Chatterjee, D., Pacini, C., Sambamurthy, V., Journal, S., Systems, I., Fall, N., & Taylor, P. (2002). The Shareholder‐ Wealth and Trading‐ Volume Effects of Information‐Technology Infrastructure Investments. Journal of Management Information Systems, 19, 7–42.
[33]
Clogg, C., & Petkova, E. (1995). Symposium on applied statistical methods for comparing regression coefficients between Models 1. American Journal of Sociology, 100, 1261–1293.
[34]
Cook, R. D. (1977). Detection of influential observation in linear regression. Technometrics, 19(1), 15–18.
[35]
Dalci, I., Tanova, C., Ozyapici, H., & Bein, M. A. (2019). The moderating impact of firm size on the relationship between working capital management and profitability. Prague Economic Papers, 28, 296–312.
[36]
Deb, P., David, P., & O'Brien, J. (2017). When is cash good or bad for firm performance? Strategic Management Journal, 38, 436–454.
[37]
Deb, P., David, P., O'Brien, J. P., & Duru, A. (2019). Attainment discrepancy and investment: Effects on firm performance. Journal of Business Research, 99, 186–196.
[38]
Dehning, B., Richardson, V. J., & Zmud, R. W. (2003). The value relevance of announcements of transformational information technology investments information technology investments. MIS Quarterly, 27(4), 637–656.
[39]
Dehning, B., Richardson, V. J., & Zmud, R. W. (2007). The financial performance effects of IT‐based supply chain management systems in manufacturing firms. Journal of Operation Management, 25, 806–824.
[40]
Deloof, M. (2003). Does working capital management affects profitability of Belgian firms? Journal of Business Finance & Accounting, 30, 573–587.
[41]
Devaraj, S., Krajewski, L., & Wei, J. C. (2007). Impact of eBusiness technologies on operational performance: The role of production information integration in the supply chain. Journal of Operation Management, 25, 1199–1216.
[42]
Ehie, I. C., & Olibe, K. (2010). The effect of R&D investment on firm value: An examination of US manufacturing and service industries. International Journal of Production Economics, 128, 127–135.
[43]
Eroglu, C., & Hofer, C. (2011). Lean, leaner, too lean? the inventory‐performance link revisited. Journal of Operation Management, 29, 356–369.
[44]
Esenduran, G., Gray, J. V., & Tan, B. (2022). A Dynamic Analysis of Supply Chain Risk Management and Extended Payment Terms. Production and Operations Management, 31, 1394–1417.
[45]
Fawcett, S. E., Waller, M. A., & Fawcett, A. M. (2010). Elaborating a dynamic systems theory to understand collaborative inventory successes and failures. International Journal of Logistics Management, 21, 510–537.
[46]
Fu, R., Tang, Y., & Chen, G. (2020). Chief sustainability officers and corporate social (Ir) responsibility. Strategic Management Journal, 41(4), 656–680.
[47]
Galbraith, J. R. (1974). Organization Design: An Information Processing View. Interfaces (Providence)., 4, 28–36.
[48]
Gelsomino, L. M., Mangiaracina, R., Perego, A., & Tumino, A. (2016). Supply chain finance: a literature review. International Journal of Physical Distribution & Logistics Management, 46, 348–366.
[49]
Gibbons, B., Greenstein, S., Hart, O., Kerr, W., King, A., Lederman, M., Matouschek, N., Sadun, R., Stern, S., Thomas, C., Williams, H., & Lunch, P. (2014). Delegation in multi‐establishment firms: Evidence from IT purchasing. J. Econ. Manag. Strateg, 23, 225–258.
[50]
Gill, A., Kang, P., & Amiraslany, A. (2022). Information technology investment and working capital management efficiency: evidence from India survey data. South Asian Journal of Business Studies. https://doi.org/10.1108/SAJBS-06-2021-0239
[51]
Giroud, X., & Mueller, H. M. (2011). corporate governance, product market competition, and equity prices. Journal of Finance, 66, 563–600.
[52]
Grosse‐Ruyken, P. T., Wagner, S. M., & Jönke, R. (2011). What is the right cash conversion cycle for your supply chain? International Journal of Services and Operations Management, 10, 13–29.
[53]
Gunasekaran, A., Patel, C., & Tirtiroglu, E. (2001). Performance measures and metrics in a supply chain environment. International Journal of Operations & Production Management, 21, 71–87.
[54]
Hall, B. H. (1993). The stock market's valuation of R & D investment during the 1980s. American Economic Association, 83, 259–264.
[55]
Hayes, A. F., Glynn, C. J., & Huge, M. E. (2012). Cautions regarding the interpretation of regression coefficients and hypothesis tests in linear models with interactions. Communication Methods and Measures, 6(1), 1–11.
[56]
Hitt, L. M. (1999). Information Technology and Firm Boundaries: Evidence from Panel Data. Information System Research, 10, 134–149.
[57]
Hofmann, E., & Belin, O. (2011). Supply Chain Finance Solutions. Springer.
[58]
Hofmann, E., & Kotzab, H. (2010). A supply chain‐oriented approach of working capital management. Journal of Business Logistics, 31, 305–330.
[59]
Huang, P., Ceccagnoli, M., Forman, C., & Wu, D. J. (2022). IT knowledge spillovers, absorptive capacity, and productivity: Evidence from enterprise software. Information Systems Research, 33(3), 908–934.
[60]
Huff, J., & Rogers, D. S. (2015). Funding the Organization through Supply Chain Finance: A Longitudinal Investigation. Supply Chain Forum, 16, 4–17.
[61]
Hull, R. M. (1999). Leverage ratios, industry norms, and stock price reaction: An empirical investigation of stock‐for‐debt transactions. Finance Management, 28, 32.
[62]
Jarrahi, M. H. (2019). In the age of the smart artificial intelligence: AI's dual capacities for automating and informating work. Business Information Review, 36, 178–187.
[63]
Jayachandran, S., Kalaignanam, K., & Eilert, M. (2013). Product and environmental social performance: Varying effect on firm performance. Strategic Management Journal, 34, 1255–1264.
[64]
Jose, M. L., Lancaster, C., & Stevens, J. L. (1996). Corporate returns and cash conversion cycles. Journal of Economic Finance, 20, 33–46.
[65]
Karimi, J., Somers, T. M., & Bhattacherjee, A. (2007). The role of information systems resources in ERP capability building and business process outcomes. Journal of Management Information Systems, 24, 221–260.
[66]
Keum, D. D. (2021). Innovation, short‐termism, and the cost of strong corporate governance. Strategic Management Journal, 42, 3–29.
[67]
Kieschnick, R., Laplante, M., & Moussawi, R. (2013). Working capital management and shareholders' wealth. Review of Finance, 17(5), 1827–1852.
[68]
Kim, C., & Bettis, R. A. (2014). Cash is surprisingly valuable as a strategic asset. Strategic Management Journal, 35, 2053–2063.
[69]
Kim, K. (2017). Information technology investments and firm risk across industries: Evidence from the bond market. MIS Quarterly, 41, 1–13.
[70]
Kohli, R., & Devaraj, S. (2003). Measuring information technology payoff: A meta‐analysis of structural variables in firm‐level empirical research. Information System Research, 14, 127–145.
[71]
Kovach, J. J., Hora, M., Manikas, A., & Patel, P. C. (2015). Firm performance in dynamic environments: The role of operational slack and operational scope. Journal of Operation Management, 37, 1–12.
[72]
Kroes, J. R., & Manikas, A. S. (2014). Cash flow management and manufacturing firm financial performance:A longitudinal perspective. International Journal of Production Economics, 148, 37–50.
[73]
Lam, H. K. S., & Zhan, Y. (2021). The impacts of supply chain finance initiatives on firm risk: evidence from service providers listed in the US. International Journal of Operations & Production Management, 41, 383–409.
[74]
Lansing, E., Collins, F., & Wiley, J. (2017). Research notes and commentaries toward greater understanding of market orientation and the resource‐based view. Strategic Management Journal, 28, 961–964.
[75]
Larcker, D. F., & Rusticus, T. O. (2010). On the use of instrumental variables in accounting research. Journal of Accounting Economics, 49, 186–205.
[76]
Lazaridis, I., & Tryfonidis, D. (2006). The relationship between working capital management and profitability of listed companies in the Athens Stock Exchange. Journal of Finance Management Analysis, 30, 1–12.
[77]
Lee, B., Barua, A., & Whinston, A. B. (1997). Discovery of causal relationships in MIS research: A methodological framework. MIS Quarterly, 21, 109–136.
[78]
Lee, D., & Mithas, S. (2014). IT investments, alignment and firm performance: Evidence from an emerging economy. 35th Int. conf. inf. syst. building a better world through inf. syst. (ICIS 2014), 1–18.
[79]
Loughran, T., & Ritter, J. (2004). Why has IPO underpricing changed over time? Finance Management, 33(3), 5–37.
[80]
Luo, X., Gu, B., & Zhang, C. (2014). IT investments and firm stock market value: The mediating role of stock analysts. 2014 47th Hawaii International Conference on System Sciences, IEEE. https://doi.org/10.1109/HICSS.2014.505
[81]
Macrotrends, 2022. US Manufacturing trends [WWW Document]. Macrotrends LLC. https://www.macrotrends.net/countries/USA/united‐states/manufacturing‐output
[82]
Martin, G. P., Gomez‐Mejia, L. R., & Wiseman, R. M. (2013). Executive stock options as mixed gambles: Revisiting the behavioral agency model. Academic Management Journal, 56, 451–472.
[83]
McConnell, J. J., & Servaes, H. (1990). Additional evidence on equity ownership and corporate value, 2, 595–612.
[84]
Melville, N., Kraemer, K., & Gurbaxani, V. (2004). Review: Information technology and organizational performance: An integrative model of IT business value. MIS Quarterly, 28, 283–322.
[85]
Mishra, S., Modi, S. B., & Animesh, A. (2013). The relationship between information technology capability, inventory efficiency, and shareholder wealth: A firm‐level empirical analysis. Journal of Operation Management, 31, 298–312.
[86]
Mitra, S. (2005). Information technology as an enabler of growth in firms: An empirical assessment. Journal of Management Information Systems, 22, 279–300.
[87]
Modi, S. B., & Mishra, S. (2011). What drives financial performance‐resource efficiency or resource slack?: Evidence from U.S. based manufacturing firms from 1991 to 2006. Journal of Operation Management, 29, 254–273.
[88]
Moeller, J. (2015). A word on standardization in longitudinal studies: don't. Frontiers in Psychology, 6, 1389.
[89]
Montgomery, C. A., & Wernerfelt, B. (1988). Diversification, ricardian rents, and Tobin's q. RAND Journal of Economics, 19, 623–632.
[90]
Ng, C. K., Smith, J. K., & Smith, R. L. (1999). Evidence on the determinants of credit terms used in interfirm trade. Journal of Finance, 54, 1109–1129.
[91]
Nizalova, O. Y., & Murtazashvili, I. (2016). Exogenous Treatment and Endogenous Factors: Vanishing of Omitted Variable Bias on the Interaction Term. Journal of Economic Methods, 5, 71–77.
[92]
Paternoster, R., Brame, R., Mazerolle, P., & Piquero, A. (1998). Using the correct statistical test for the equality of regression coefficients. Criminology, 36(4), 859–866.
[93]
Peng, J., & Zhou, Z. (2019). Working capital optimization in a supply chain perspective. European Journal of Operational Research, 277, 846–856.
[94]
Pesaran, M. H., & Smith, R. J. (1994). A generalized R^ 2 criterion for regression models estimated by the instrumental variables method. Econometrica: Journal of the Econometric Society, 62(3), 705–710.
[95]
Peterson, M. A., & Rajan, R. G. (1997). Trade credit: Theories and evidence. Review of Financial Studies, 10, 661–691.
[96]
Powell, T. C., & Dent‐Micallef, A. (1997). Information technology as competitive advantage: The role of human, business, and technology resources. Strategic Management Journal, 18, 375–405.
[97]
Rai, A., Patnayakuni, R., & Patnayakuni, N. (1997). Technology investment and business performance. Communication ACM, 40, 89–97.
[98]
Rai, A., Patnayakuni, R., & Seth, N. (2006). Firm performance impacts of digitally enabled supply chain integration capabilities. MIS Quarterly, 30, 225–246.
[99]
Ravichandran, T., & Lertwongsatien, C. (2005). Effect of information systems resources and capabilities on firm performance: A resource‐based perspective. Journal of Management Information Systems, 21, 237–276.
[100]
Ravichandran, T., Liu, Y., Han, S., & Hasan, I. (2009). Diversification and Firm Performance: Exploring the Moderating Effects of Information Technology Spending. Journal of Management Information Systems, 25, 205–240.
[101]
Richard, P. J., Devinney, T. M., Yip, G. S., & Johnson, G. (2009). Measuring organizational performance: Towards methodological best practice. Journal of Management, 35, 718–804.
[102]
Rogers, D. S., Leuschner, R., & Choi, T. Y. (2020). Supply chain financing: Funding the supply chain and the organization. World Scientific.
[103]
Schwarz, A., & Hirschheim, R. (2003). An extended platform logic perspective of IT governance: Managing perceptions and activities of IT. Journal of Strategic Information Systems, 12, 129–166.
[104]
Seidel, S., & Berente, N. (2020). Automate, informate, and generate: Affordance primitives of smart devices and the internet of things. In Handbook of digital innovation (pp. 198–210). Edward Elgar Publishing.
[105]
Sharma, A. K., & Kumar, S. (2011). Effect of working capital management on firm profitability: Empirical evidence from India. Global Business Review, 12, 159–173.
[106]
Shin, S., Ennis, K. L., & Paul Spurlin, W. (2015). Effect of inventory management efficiency on profitability: Current evidence from the U.S. manufacturing industry. Journal of Economics and Economic Education Research, 16, 98–106.
[107]
Singhania, M., & Mehta, P. (2017). Working capital management and firms' profitability: evidence from emerging Asian countries. South Asian Journal of Business Studies, 6, 80–97.
[108]
Smirlock, M., Gilligan, T., & Marshall, W. (1984). Tobin's q and the structure–performance relationship. American Economic Association, 74, 1051–1060.
[109]
Szymanski, D. M., Bharadwaj, S. G., & Varadarajan, P. R. (1993). An analysis of the market share‐ profitability relationship. Journal of Marketing, 57, 1–18.
[110]
Tambe, P., & Hitt, L. M. (2012). The productivity of information technology investments: New evidence from IT labor data. Information Systems Research, 23, 599–617.
[111]
Thomas, D. S. (2021). Annual Report on U.S. Manufacturing Industry Statistics: 2021, NIST Advanced Manufacturing series. Gaithersburg, MD.
[112]
Vomberg, A., Homburg, C., & Bornemann, T. (2015). Talented people and strong brands: The contribution of human capital and brand equity to firm value. Strategic Management Journal, 36, 2122–2131.
[113]
Weill, P. (1992). The relationship between investment in information technology and firm performance: A study of the value manufacturing sector. Information Systems Research, 3, 307–333.
[114]
Wetzel, P., & Hofmann, E. (2019). Supply chain finance, financial constraints and corporate performance: An explorative network analysis and future research agenda. International Journal of Production Economics, 216, 364–383.
[115]
White, H. (1980). A heteroskedasticity‐consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48, 817–838.
[116]
Wilner, B. S. (2000). The exploitation of relationships in financial distress: The case of trade credit. Journal of Finance, 55, 153–178.
[117]
Wooldridge, J. M. (2017). Introductory econometrics: A modern approach 5e. In Instrumental variables estimation and two stage least squares (pp. 512–542).
[118]
Worldbank, 2022. Manufacturing value adds. The World Bank Group. https://data.worldbank.org/indicator/NV.IND.MANF.CD?end=2021&start=2000
[119]
Wuttke, D. A., Rosenzweig, E. D., & Heese, H. S. (2019). An empirical analysis of supply chain finance adoption. Journal of Operations Management, 65, 242–261.
[120]
Zeidan, R., & Shapir, O. M. (2017). Cash conversion cycle and value‐enhancing operations: Theory and evidence for a free lunch. Journal of Corporate Finance, 45, 203–219.
[121]
Zhu, K. (2004). The Complementarity of Information Technology Infrastructure and E‐Commerce Capability: A Resource‐Based Assessment of Their Business Value. Journal of Management Information Systems, 21, 167–202.
[122]
Zuboff, S. (1985). Automate/infornate: The two faces of intelligent technology. Organisational Dynamics, 14(2), 5–18.
[123]
Zuboff, S. (1988). In the age of the smart machine: The future of work and power. Basic Books, Inc.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image Journal of Operations Management
Journal of Operations Management  Volume 69, Issue 6
September 2023
176 pages
ISSN:0272-6963
EISSN:1873-1317
DOI:10.1002/joom.v69.6
Issue’s Table of Contents

Publisher

John Wiley & Sons, Inc.

United States

Publication History

Published: 14 March 2023

Author Tags

  1. automate
  2. days inventory outstanding
  3. days payables outstanding
  4. days sales outstanding
  5. informate
  6. IT infrastructure intensity
  7. IT labor intensity
  8. Tobin's q
  9. working capital management

Qualifiers

  • Research-article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 0
    Total Downloads
  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 09 Nov 2024

Other Metrics

Citations

View Options

View options

Get Access

Login options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media