The phenomenon of IT investment in the digital era is interesting to study especially from aspects of its benefits. Ranganathan and Brown (2006) estimated that almost 40% of capital expenditure is spent on IT. As a research company and IT advisor, Gartner, Inc. noted that global company expenditure related to IT increased by 0.5% to 3.8% in 2017 and by 0.2% to4.5% in the following year. As with developed economies Indonesia, a developing country, also showed a rapid increase in IT investment in many companies (Winarno, 2019). This study uses RBT theory, RBT theory explains that resources are essential for improving the performance of the firm (Barney, 1991). Investment in IT as a potential resource creates competitive advantages for firms (Bharadwaj, 2000). Cobb-Douglas’s production function theory stated that the inputs in production factors, including IT capital, nonIT capital, and labor, would increase the firm’s productivity (Hitt & Brynjolfsson 1996; Dewan & Kraemer 2000). This theory supports the previous statement. Based on this argument, companies that have received benefits in the first year and following IT investment would motivate to invest more in subsequent periods.

Data used in this study were sourced from the firms’ annual reports published through the Indonesia Stock Exchange (IDX) and the Indonesian Capital Market Directory (ICMD). Panel data over a 5-year period were used, spanning 2013-2017. Information on IT expenditure was obtained from corporate annual financial statements, while data on other variables were sourced from the ICMD, often used in previous studies. The 5-year span was considered sufficient for an overview of time lag as adopted in some past studies (Cline & Guynes 2001; Brynjolfsson 1993; Lee & Kim 2006; Campbell, 2012).

The findings of this study offer several implications. First, the relationship of financial performance in the form of profitability will be secured by the firm and should increase after one year of IT investment (t + 1). This study established that it takes a 1-year time lag on IT investment for an impact to register itself on the firm’s financial performance. Managers or decision-makers must pay attention to the time lag for IT investment for the materialization of financial benefits. There is the organizational learning process, structural effects, and complementary effects need to be understood in order to appreciate that there will be a time lag for IT implementation before the benefits are registered by the firm (Shaft et al. 2007). Secondly, the immediate impact of IT investment on the firm’s performance occurs when it is measured by market performance (Tobin’s Q). Information about IT investment is good news for investors. It is expected that the firm’s future performance will be reflected directly in the stock price in the IT investment period as evident in the findings of earlier studies (Bharadwaj et al. 1999; Chari et al. 2008; Bardhan et al. 2013; Kohli et al. 2012).

This research potentially provides several contributions. First, The International Data Corporation (IDC) stated that the phenomenon of IT and digital spending in the financial services industry in Indonesia showed a significant increase in IT application during the Covid-19 pandemic. The financial industry has also the largest number of firms with IT investments. This reliance is predicted to increase IT spending by 12.5% in 2022 (https://www.indotelko.com/read/1538705973/ belanja-ti-keuangan-12-5). Based on this development, this study adopts the time-lag concept to re-examine the relationship between IT investment and firm performance in the Indonesian context; namely as a developing country with different industrial characteristics relative to developed countries. Second, the pattern of relationship between time lag that affects IT investment on performance of the firm is examined through a dynamic panel since there is evidence of lag dependence on firm performance variables (Weill 1992; Lim et al. 2015). The dynamic model is therefore more precisely estimated using the GMM approach. In several past studies (Lee & Kim 2006; Brynjolfsson et al. 1994; Shaft et al. 2007), the research model was estimated through the use of dynamic ordinary least squares (DOLS). Such estimation approach used in the previous studies has the potential to produce biased and inconsistent results due to the problem of dynamic endogeneity of the dependent variable that is influenced by values in the preceding period (Schultz et al. 2010; Wintoki et al. 2012; Ullah et al. 2018; Tanjung 2020). Third, the relative adjusted performance measures used in the same industry, adopted and modified in this study, established that abnormal firm performance in similar industries produced consistent performance results.

Author: Prof. Dr. Bambang Tjahjadi, S.E., M.BA, Ak.

Journal link: https://repository.unej.ac.id/handle/123456789/105332