Data for: Intellectual capital efficiency and ICT firm value in Nigeria and South Africa – The intervening effect of profitability
Description
The dataset consists of data on a range of variables including share price, human capital efficiency (HCE), structural capital efficiency (SCE), capital employed efficiency and return on assets (ROA). By structure, the dataset is a yearly time-series-cross-sectional data (with n=28; t=10).
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Dependent variable Market value of firm is measured as the share prices of each firm selected for the period of the study (2004 to 2018) on the last day of the year (Özer & Çam, 2017). The share price determines the market value of a company. Furthermore, in the context of IC and firms value, Hassan (2019) asserts that share prices reported by international and local stock markets represent vital measures of market-based corporate economic prosperity. Independent variable Although there are several techniques for the measurement of ICE, however for this study, the Pulic's (1998) value-added intellectual coefficient (VAIC) was employed as used by many other studies (see, for example, Anifowose et al., 2018; Bala et al., 2019; Kasoga, 2020; Bala et al, 2021). Our decision to use this measurement astrategy was further informed by its wide acceptability and uncomplicated approach. VAIC is a composite of HCE, SCE and CEE. The value-added (VA) is computed as the addition of operating profit (OP), employee costs (EC), depreciation expenses (DE) and amortization expenses (A) (Omiunu, 2019). Thus, HCE = VA/HC, where human capital (HC) is the employees’ wages & salaries (Buallay, 2018; Bala, Raja, & Dandago, 2019). However, SCE = SC/VA, where structural capital (SC) is equal to VA minus HC (Pulic, 1998; Bala et al., 2019). Lastly, CEE = VA/CE, where CE is the physical & financial capital (Pulic, 1998; Nuryaman, 2015). Mediating variable Corporate profitability can be assessed by many ratios. However, one of the most commonly used by studies (Deniswara et al., 2019; Irman & Purwati, 2020) is the value of Return on Assets (ROA). Hence, we employ ROA as a measure of profitability, inconsistent with the works of Kamaludin, Ibrahim, and Sundarasen (2020). Profitability is the ability to gain on investment, it is a prerequisite for the growth and development of a business entity, and the achievement of its core business goal. ROA is computed in this study thus; ROA = (Net Income Before Tax)/(Total Assets) x 100 (1) Empirical model The model of this study follows the works of Amin et al. (2018); Bala et al., (2019) and Kasogna (2020). Based on the objective of the study to establish the impact of ICE on the firms’ value on one hand, and the intervening effect of ROA on the other. Also, due to the nature of the dataset, the following models I and II were used: Model I: 〖SP〗_it= ∝_it+δ_1 〖HCE〗_it+δ_2 〖SCE〗_it+δ_3 〖CEE〗_it+ε_it (2) Model II: 〖SP〗_it= ∝_it+δ_1 〖HCE〗_it+δ_2 〖SCE〗_it+δ_3 〖CEE〗_it+ δ_4 〖ROA〗_it +ε_it (3)