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One of the best ways to assist China is through infrastructure investment. China might become more resilient to natural calamities by pouring more money into its transport network. Analyzing the relationship between China's degree of planned expansion and the country's current network of transport hubs can help with city development estimates. A wide range of factors were taken into consideration while evaluating China's dominance and the caliber of its transportation infrastructure. Using a geographical autocorrelation model and a coupling coordination model, the dynamic link between China's adaptability and the caliber of its transportation infrastructure is examined.

China's northwest is underdeveloped in comparison to the southeast, which has a high level of resilience and development of its transportation infrastructure. The relationship between the levels of resilience upheld by China's transport infrastructure is suggested to be coordinated.

The authors find a positive geographical autocorrelation between the degree of coupling coordination and the degree of agglomeration, despite the fact that the distance between cities increases with time. They now believe that there is a connection between an area's population density and the degree of interspousal cooperation within. The consequence is an improvement in both national security and economic prosperity. The facilities for disaster management and transportation in China have received several proposals for improvement.

The authors' Practical Implications suggests that scale inefficiency is a major contributor to the relatively poor efficiency of China's primary inland river ports. Different types of inland river ports may have vastly different water system efficiencies. Input and output congestion at China's important interior river ports has reached 51%, making it very clear that massive amounts of valuable port resources are being wasted.

Many variables, such as climate and human error, affect the total amount of goods that can be moved via inner river ports. Ports situated either higher up or lower down the same canal may perform better or worse, respectively, depending on the circumstances.

There is a dearth of empirical research examining the influence of various facets of sustainable banking on the environmental sustainability performance (SP) of banks in developing economies like Bangladesh. This study looks at how green banking practices (GBPs), green finance (GF) and corporate social responsibility (CSR) practices affect SP in both direct and indirect ways.

The research framework of this study was designed based on legitimacy theory to examine the direct and indirect impacts of GBP on environmental SP through GF and CSR practices. Based on a structured questionnaire and convenience sampling, the data were collected from banking institutions to investigate the association among the study variables. Subsequently, the obtained data were evaluated using a well-established structural equation modeling (SEM) approach via SmartPls 4.0 software.

The empirical findings reveal that GBP has a significant direct impact on GF, CSR practices and the banks' SP. Further, the findings show that GF has a direct and significant impact on CSR practices and SP. Likewise, CSR practices have a direct and significant influence on the SP of banks. Additionally, among indirect effects, both CSR practices and GF mediate the association between GBP and SP, whereas GF also has an indirect effect on the relationship between GBP and CSR practices. Surprisingly, the findings demonstrate that CSR practices do not have an indirect effect on the association between GF and SP. Hence, the greater the bank's involvement in green banking activities, the greater the influence of green financing and CSR practices on environmental sustainability.

This study adds to the growing body of research in the areas of sustainable banking and environmental sustainability literature by evaluating the link between GBP, CSR practices, GF and SP. Besides, this is a ground-breaking study that examines both direct and indirect effects of different aspects of sustainable banking (GBP, GF and CSR practices) on the SP of the banking industry in an emerging country like Bangladesh. On the theoretical level, it adds to the application and expansion of legitimacy theory in the sphere of banking and finance. It provides new insights into the dynamics of green banking, GF and CSR practices within the framework of legitimacy theory. Hence, the current study offers significant suggestions to managers, academicians and researchers on how to advance the sustainability of the banking industry by adopting green banking, GF and CSR practices.

The global emphasis on sustainability is driving organizations to embrace financial technology (Fintech) solutions as a means of enhancing their sustainable performance. This study seeks to unveil the intermediary role played by green finance and competitiveness, along with the moderating impact of digital transformation (DT), in the intricate relationship between Fintech adoption and sustainable performance.

Drawing on existing literature, we construct a comprehensive conceptual framework to thoroughly analyse these interconnected variables. To empirical validate of our model, a dual structural equation modelling–artificial neural network) SEM–ANN approach was employed, adding a robust layer of validation to our study’s proposed framework. A sample of 438 banking employees in Pakistan was collected using a simple random sampling technique, with 411 samples deemed suitable for subsequent analysis. Initially, data scrutiny and hypothesis testing were carried out using Smart-PLS 4.0 and SPSS-23. Subsequently, the ANN technique was utilized to assess the importance of exogenous factors in forecasting endogenous factors.

The findings from this research underscore the direct and significant influence of Fintech adoption and DT on the sustainable performance of banks. Notably, green finance and competitiveness emerge as pivotal mediators, bridging the gap between Fintech adoption and sustainable performance. Moreover, DT emerges as a critical moderator, shaping the relationships between Fintech adoption and both green finance and competitiveness. The integration of the ANN approach enhances the SEM analysis, providing deeper insights and a more comprehensive understanding of the subject matter.

This study contributes to the enhanced comprehension of Fintech, green finance, competitiveness, DT and the sustainable performance of banks. Recognizing the importance of amalgamating Fintech adoption, green finance and transformational leadership becomes essential for elevating the sustainable performance of banks. The insights garnered from this study hold valuable implications for policymakers, practitioners and scholars aiming to enhance the sustainable performance of banks within the competitive business landscape.

Software has become increasingly important in business. However, the value of aggregate in-house and packaged software investments and the influence of an industry's software investment opportunities (SIOs) are poorly understood in the literature. This study addresses this research gap and proposes that an industry's SIOs play an essential role in the economic impacts of industry in-house and packaged software investments.

A model of the economic impacts of in-house and packaged software investments at the industry level under different SIOs is developed and empirically tested based on a panel dataset of private industries in the USA between 1998 and 2020.

The results show that with the increase in the number of SIOs in an industry, the economic performance of in-house software investments increases, while that of packaged software investments decreases.

By highlighting the role of SIOs in moderating the economic performance of in-house and packaged software, this study shows the critical role of the information technology (IT) environment in understanding software's economic value.

Prior IT productivity research usually assumes constant returns on IT investment. This study suggests that the impact of IT investment on productivity may not be constant but may change with the IT investment scale and over time. Specifically, we divide IT investment into commercial IT and in-house IT and investigate their changing impacts on industry labor productivity.

A model of the productivity impacts of commercial IT and in-house IT with changing effects of scale and over time is developed and empirically tested based on industry-level panel data from the US. Bureau of Economic Analysis (BEA).

The returns on commercial IT investment increase with scale but decrease over time, while the returns on in-house IT increase over time.

This study provides a new perspective for IT productivity research by investigating the changing productivity impacts of IT investment. It also suggests that commercial IT and in-house IT should be distinguished, as they have different impacts on productivity.

The paper presents reliability, maintainability and life cycle cost (LCC) analysis of a computerized numerical control (CNC) turning center which is manufactured and used in India. The purpose of this paper is to identify the critical components/subsystems from reliability and LCC perspective. The paper further aims at improving reliability and LCC by implementing reliability-improvement methods.

This paper uses a methodology for the reliability analysis based on the assessment of trends in maintenance data. The data required for reliability and LCC analysis are collected from the manufacturers and users of CNC turning center over a period of eight years. ReliaSoft’s Weibull++9 software has been used for verifying goodness of fit and estimating parameters of the distribution. The LCC of the system is estimated for five cost elements: acquisition cost, operation cost, failure cost, support cost and net salvage value.

The analysis shows that the spindle bearing, spindle belt, spindle drawbar, insert, tool holder, drive battery, hydraulic hose, lubricant hose, coolant hose and solenoid valve are the components with low reliability. With certain design changes and implementation of reliability-based maintenance policies, system reliability is improved, especially during warranty period. The reliability of the CNC turning center is improved by nearly 45 percent at the end of warranty period and system mean time between failure is increased from 15,000 to 17,000 hours. The LCC analysis reveals that the maintenance cost, operating cost and support costs dominate the LCC and contribute to the tune of 87 percent of the total LCC.

The proposed methodology provides an excellent tool that can be utilized in industries, where safety, reliability, maintainability and availability of the system play a vital role. The approach may be improved by collecting data from more number of users of the CNC turning centers.

The approach presented in this paper is generic and can be applied to analyze the repairable systems. A real case study is presented to show the applicability of the approach.

The proposed methodology provides a practical approach for the analysis of time-to-failure and time-to-repair data based on the assessment of trends in the maintenance data. The methodology helps in selecting a proper approach of the analysis such as Bayesian method, parametric methods and nonparametric methods.