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There are certain differences in the production products of enterprises. What are the impacts of product differentiation on the iron and steel industry? Based on the macro background of CO₂ emission reduction, this paper aims to analyze the economic benefits and environmental changes of the iron and steel industry under the dual influence of CO₂ emission reduction policy and product differentiation policy.

Taking the basic data of iron and steel industry in six regions of China as an example, this paper constructed an extended two-stage dynamic game model to analyze the impact of product differentiation and carbon tax policy on the production, economic indicators and CO₂ emission levels for the overall industry and regional enterprises.

As the CO₂ emission reduction target increased, the unit carbon tax and total tax increased, whereas the macro-environmental losses, social welfare, consumer surplus and outputs decrease. Emission reduction pressures and other economic indicators showed obvious regional differences. Differentiated products promoted various indicators of enterprises and industries; higher degrees of product differentiation resulted in greater promoting effects on economic indicators.

This paper constructed multiple emission reduction and production backgrounds, and discusses the impact of the comprehensive implementation of these policies, which has been practically absent in previous studies. The results of this study are consistent with the current industrial policy for stable production and environmental protection, and also provides a reference for the formulation of detailed policies in the future.

This paper aims to assess the impact of digital financial innovation on financial system development in Common Market for eastern and Southern Africa (COMESA). This paper evaluates the dynamic relationship between digital financial innovation measures and financial system development using time series data from COMESA countries for the period 1997–2019.

A dynamic autoregressive distributed lag model (ARDL) was adopted and the mean group (MG), pooled mean group (PMG) and dynamic fixed effect (DFE) of the model were estimated to evaluate the short- and long-run impact. In addition, the dynamic generalized method of moments (DGMM) was adopted for a robustness check. The Hausman test results show PMG to be the most consistent and efficient estimator, while the coefficient of lagged dependent variable of different GMM is less than the fixed effect coefficient, and, as such, suggests system GMM is the most suitable estimator. Data for the study were sourced from World Bank Development Indicator (WDI, 2020), World Governance Indicator (WGI, 2020) and World Bank Global Financial Development Database (GFD, 2020).

The result shows that digital financial innovation significantly impacts financial system development in the long run. As such, the evidence revealed that automated teller machines (ATMs), point of sale (POS), mobile payments (MP) and mobile banking are significant and contribute positively to financial system development in the long run, while mobile money (MM) and Internet banking (INB) are insignificant but exhibit positive and inverse relationship with financial development respectively. Further investigation revealed that institutional quality and a stable macroeconomic environment including their interactive term are significantly imperative in predicting financial system development in the COMESA region.

Researchers recommend a cohesive and conscious policy that would checkmate the divergence in the short run and suggest a common regional innovative financial strategy that could be pursued to incentivize technology transfer needed to promote financial system development in the long run. More so, plausible product and process innovations may be adapted to complement innovative institutions in the different components of the COMESA financial system.

Digital financial innovation services if well managed increase the inherent benefits in financial system development.

To the best of the authors’ knowledge, this paper presents new background information on digital financial innovation that may stimulate the development of the financial system, particularly in the COMESA region. It also exposes the relevance of digital financial innovation, institutional quality and stable macroeconomic environment as well as their interactive effect on COMESA financial system development.

The empirical study of factors related to digital transformation (DT) in the banking sector is still limited, even though the importance of the topic is universally evident. To bridge that gap, this paper aims to explore the role of digital leadership (DL), innovative culture (IC) and technostress inhibitors (TI) to support engagement for improved digital innovation (DI). Based on the literature, these variables are crucial aspects of digitalisation, even though there is no agreement on their conclusiveness.

This quantitative study tested a new conceptual model using survey data from five major banks in Libya. Partial least squares structural equation modelling was used to analyse the data from the 292 usable responses.

The results showed that DL and IC positively affect DI. Techno-work engagement (TE) mediated the relationship between leadership, culture and innovation. TI played a significant moderating role in leadership, culture and engagement relationships.

The research findings highlight critical issues about how leadership style and fostering organisational support in the banking sector can enhance DT. Leaders must demonstrate a commitment to long-term resource allocation to avoid possible negative effects from digital stress while pursuing DI through work engagement.

The study suggests that fostering organisational support can enhance DT in retail banks, potentially leading to improved customer experiences and increased access to financial services. These programs will help banks contribute to societal and economic development.

This timely study examines predictor mechanisms of innovation in retail banking that resonate within the restrictions of organisational and DI frameworks and the social exchange theory. Exploring the intervening effect of TE in the leadership, culture and innovation associations is unprecedented.

In this study, three models were empirically compared, the DeLone and McLean model, the Seddon model and the Modified Seddon model, by measuring the impact of a business intelligence system (BIS) in companies in Peru. After that, the mediators and dependent constructs were analysed to determine if they were behaving properly (a good level of variance explanation and significant relations with others constructs). The study used a sample of 104 users of the BIS, from companies in several important economic sectors, in a quasi-voluntary context and with six constructs: information quality, system quality, service quality, system dependence (system use), user satisfaction and perceived usefulness (individual impact).

To interpret the results, the authors used structural equations. The idea was to look for the best fit and explanations for the outcomes. The main difference in these models is that the DeLone and McLean model considers system dependence (system use) as a part of information system success, but in the Seddon model, it is a consequence of it.

The Seddon model seems to show the best fit and explanation for the outcomes. After that, a review of the system use construct was realised, because of its limited variance explained and the few significant relations with other constructs, to improve its explanation power in future research.

It is estimated that the sample includes more than 15 per cent of all the companies that use a BISs in Peru, so the size of the sample is adequate, but it is not entirely random and therefore limits the generalizability of outcomes. Besides that, a sample size that is bigger could be better for the sake of making a more detailed analysis, permitting the use of some items with less power, or the use of another statistical procedure for structural equations such as the Asymptotical Distribution Free, permitting a more detailed analysis (Hair et al., 2006).

Business intelligence (BI), one of the most important components of information systems (IS), is playing a very relevant role in business in this time of high competition, high amounts of data and new technology. Currently, companies feel pressured to respond quickly to change and complicated conditions in the market, needing to make the correct tactical, operational and strategic decisions (Chugh and Grandhi, 2013). BI is one of the most important drivers of the decade (Gartner, 2013). Big companies of IS are creating special units specialised in BI, helping companies become more efficient and effective in daily operations.

Pilot upgrade training is critical to aircraft and passenger safety. This study aims to identify variances in the US Air Force C-130J pilot upgrade training based on geographic location and provide a model to enhance policy that will impact future pilot training efforts that lower cost and increase operator quality and proficiency.

This research employed a mixed-method approach. First, the authors collected data and analyzed 90 C-130J pilots' aviation records and then contextualized this analysis with interviews of experts. Finally, the authors present a modified version of Six Sigma's define–measure–analyze–improve–control (DMAIC) that identifies and reduces the variances in C-130J pilot training, translating into higher quality outcomes.

The results indicate significant statistical variances across geographically separated C-130J pilot training organizations. This leads some organizations to have higher proficiency levels in specific tasks and others with comparative deficiencies. Additionally, the data analysis in this study enabled a recommended number of flight hours in several distinct categories that should be obtained before upgrading a pilot to aircraft commander to enhance standards.

This research was limited to C-130J pilot upgrades, but these results can be implemented within any field that utilizes hours as a measure of experience. Implications from this research can be employed to scope policy that will influence pilot training requirements across all airframes in civilian and military aviation.

This research proposes a process improvement methodology that could be immediately implemented within the C-130J community and, more importantly, in any upgrade training where humans advance into higher echelons of a profession.