Fig. 1: Conceptual Model. | Humanities and Social Sciences Communications

Fig. 1: Conceptual Model.

From: Analysing the impact of digital technology diffusion on the efficiency and convergence process of the commercial banking industry of Pakistan

Fig. 1

Our conceptual model Figure explains the two-stage DEA-based research design. In the first stage, we employ four inputs (total deposits (TD), interest expense (IE), fixed assets (FA), and non-interest expenses (NIE)) and use three outputs (total loans (TL), interest income (II), and non-interest income (NII)) to estimate banking efficiency by both original and bootstrap DEA methods (see top left side). First, we obtained the original overall technical efficiency (OTE: O) and then decomposed it into the original pure technical efficiency (PTE: O) and original scale efficiency (SE: O) using the original DEA estimator. Second, we estimate the bootstrap bias-corrected overall technical efficiency (BSBC: OTE) using the Bootstrap DEA, and further decompose it into the bootstrap bias-corrected pure technical efficiency (BSBC: PTE) and the bootstrap bias-corrected scale efficiency (BSBC: SE). On the right and bottom-left sides, Figure represents the second stage of the DEA research workflow. Here, the effects of digitalisation on banking efficiency (BSBC: PTE) and its convergence process are being analysed. A list of explanatory variables, examined in terms of their influence on BSBC: PTE, is located on the rightmost part of Figure. Factors related to digitalization: 1. ATM-based transactions (ABTR). 2. Internet-based transactions (IBTR). 3. Point-of-sale-based transactions (POSBTR). 4. Digitalisation Index (DIG Index). Bank-specific factors: 1. Net interest margin (NIM) ratio. 2. The return on equity (ROE) ratio. 3. The return on assets (ROA) ratio. 4. Cost-to-income (CIR) ratio. 5. Equity-to-asset (CAPT) ratio. 6. Bank ownership types (OWNERSHIP DUMMIES). Macroeconomic control factors: 1. Inflation rate (INFRATE). 2. Interest rate (INTRATE). 3. Gross domestic product growth rate (GDPGR). The second stage of DEA also investigates the efficiency convergence dynamics, which include efficiency absolute beta convergence and efficiency absolute sigma convergence. Absolute beta convergence is expanded to efficiency conditional beta convergence, examining the effect of digitalisation on the banking efficiency convergence process. The listed contextual variables at the bottom left are the ones used to estimate the efficiency conditional beta-convergence dynamics. In the following, there are the four bank-specific and two country-specific digitalisation factors that are included in this research: The natural logarithm of ATM-based transactions (lnABTR). 2. The natural logarithm of internet-based transactions (lnIBTR). 3. The natural logarithm of point of sale based ln of transactions (lnPOSBTR). 4. The Digitalization Index (DIG Index). 5. Digital information and communication technology availability index (DICTA Index). 6. Digital information and communication technology utilization index (DICTU Index). Bank-specific control factors: 1. The cost-to-income ratio’s natural logarithm (lnCIR). 2. The natural logarithm of the total assets (SIZE). 3. Loan growth ratio (LGR). 4. Loan loss provisions to non-performing loans (LLPTNPL) ratio. 5. Non-performing loans to total loans (NPLTTL) ratio. 6. The natural logarithm for the total number of employees (lnHR). Finally, macroeconomic control factors include M2 money supply growth (M2_GR), the inflation rate (INFRATE), and the gross domestic product growth rate (GDPGR).

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