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In smart cities striving for innovation, development, and prosperity, hydrogen offers a promising path for decarbonization. However, its effective integration into the evolving energy landscape requires understanding regional intricacies and identifying areas for improvement. This chapter examines hydrogen transport from production to utilization, evaluating technologies’ pros, cons, and process equations and using Analytic Hierarchy Process (AHP) as a Multi-Criteria Decision-Making (MCDM) tool to assess these technologies based on multiple criteria. It also explores barriers and opportunities in hydrogen transport within the 21st-century energy transition, providing insights for overcoming challenges. Evaluation criteria for hydrogen transport technologies were ranked by relative importance, with energy efficiency topping the list, followed by energy density, infrastructure requirements, cost, range, and flexibility. Safety, technological maturity, scalability, and compatibility with existing infrastructure received lower weights. Hydrogen transport technologies were categorized into three performance levels: low, medium, and high. Hydrogen tube trailers ranked lowest, while chemical hydrides, hydrail, liquid organic hydrogen carriers, hydrogen pipelines, and hydrogen blending exhibited moderate performance. Compressed hydrogen gas, liquid hydrogen, ammonia carriers, and hydrogen fueling stations demonstrated the highest performance. The proposed framework is crucial for next-gen smart cities, cutting emissions, boosting growth, and speeding up development with a strong hydrogen infrastructure. This makes the region a sustainable tech leader, improving air quality and well-being. Aligned with Gulf Region goals, it is key for smart cities. Policymakers, industries, and researchers can use these insights to overcome barriers and seize hydrogen transport tech opportunities.

After half a decade of balance sheet clean-up prompted by the Reserve Bank of India’s (RBI) asset quality review (AQR), Indian banks are back on track for increased loan growth. Being a financial vehicle for the economy, loan growth cannot be put on hold for a long period of time. But it is also important to understand that loan growth carries an inherent risk of default. A trade-off exists between loan growth, non-performing loans (NPLs) and bank profitability. Our study highlights the importance of understanding this relationship.

For our study, we have taken a sample of India’s private and public sector banks. The dataset consists of the financials of our sample for the period 2006–2021. Two-step differenced generalized method of moments (SYS-GMM) estimation has been used to establish the relationship. The mediating role of NPLs in the relationship between loan growth and profitability is examined by the mediation analysis using structural equation modeling (SEM) and the Sobel test. We have used Stata 16.1 for the analysis of our dataset.

The findings of our study suggest that bank lending is a major contributor to the bank’s earnings. Loan growth after a certain point has a negative impact on profitability, and it also adds to the NPLs of the bank. The study result indicates that moderate loan growth is key to steady and stable growth in the Indian banking industry.

Our study is directed toward understanding the positive and negative manifestations of loan growth. We develop a framework to understand this relationship and then empirically prove it. The study is beneficial for employees and policymakers alike to minimize the negative impact of loan growth.

The issue of the simultaneous impact of loan growth on NPLs and profitability has not been studied in the Indian banking sector. Also, this study adds to the present literature by studying the mediation effect of the NPLs on the loan growth and profitability relationship.

Knowing financial and economic information beforehand benefits in planning and developing policies for every country especially for a developing country like Thailand and for other Asian countries. Unfortunately, missing data or non-response plays an essential role in many areas of studies including finance and economics. Eradication of missing data in a proper way before further analysis can gain remarkable outcomes and can be effective for planning policies. This review on the generalized regression estimators for population total can be applied to financial, economic and other data when missing data are present.

The generalized regression estimators for estimating population total, including the variance estimators under unequal probability sampling without replacement with missing data are explored under the reverse framework. Applications to financial and economic data in Thailand are also reviewed.

The review of literatures related to the proposed estimator shows the best performance, giving smaller variances in all scenarios.

The generalized regression estimators can assist in estimating financial and economic data that contain missing values with different missing mechanisms and can be used in other applications which help gain more superior estimators.

This study aims to investigate the impact of local windfall gains from the Spanish Christmas lottery on household consumption behavior.

The study applies differences-in-differences to assess permanent income hypothesis (PIH) validity, examining pre- and postlottery consumption effects. Additionally, it also uses an instrumental variable regression, using the lottery shock as an instrument for total expenditures, to estimate the Engel curves.

The paper finds a PIH violation; households in winning region notably increase consumption on durable and nondurable goods compared to nonwinning ones. Moreover, durable goods consumption is responsive to lottery winnings, while nondurable goods consumption are unit-elastic to expenditure shocks.

To the best of the author’s knowledge, this is the first paper analyzing the effects of winning regions of the Spanish Christmas lottery in all types of consumption goods, testing its consequences in the PIH and estimating its effects in the Engel curves.

This study aims to investigate the influence of the reviewed establishment’s price level and the user’s social network size and reputation status on consumers’ tendency to post more visual imagery content. Furthermore, it explores the moderating effects of user experiences and geographic distance on these dynamics.

This study adopts a multi-method approach to explore both the determinants behind the sharing of user-generated photos in online reviews and their internal mechanisms. Using a comprehensive secondary data set from Yelp.com, the authors focused on restaurant reviews from a prominent tourist destination to construct econometric models incorporating time-fixed effects. To enhance the robustness of the authors’ findings, the authors complemented the big data analysis with a series of controlled experiments.

The reviewed establishments price level and the users reputation status and social network size incite corresponding motivations conspicuous display “reputation seeking” and social approval motivating users to incorporate more images in reviews. “User experiences can amplify the influence of these factors on image sharing.” An increase in the users geographical distance lessens the impact of the price level on image sharing, but it heightens the influence of the users reputation and social network size on the number of shared images.

As a result of this study, high-end establishments can increase their online visibility by leveraging user-generated visual content. A structured rewards program could significantly boost engagement by incentivizing photo sharing, particularly among users with elite status and extensive social networks. Additionally, online review platforms can enhance users’ experiences and foster more dynamic interactions by developing personalized features that encourage visual content production.

This research, anchored in trait activation theory, offers an innovative examination of the determinants of photo-posting behavior in online reviews by enriching the understanding of how the intricate interplay between users’ characteristics and situational cues can shape online review practices.

The study evaluates the influence of human capital efficiency (HCE) and market power on bank performance.

The study employs two measures of bank performance: profitability and stability. Unbalanced panel data of 35 banks operating in Kenya for 2005–2020 collected from published financial statements is utilized. The study employs the feasible generalized least squares (FGLS) method in the analysis and the two-step system generalized method of moments (GMM) for robustness check.

The study affirms an inverted U-shaped relationship between market power and bank performance. The effect of market power on bank profitability is enhanced when a bank has highly efficient human capital. Further, HCE significantly impacts bank stability for banks with low HCE. Interestingly, a further increase in HCE narrows the net interest margins for banks with high HCE, conferring welfare benefits to customers as interest rate spreads shrink.

This study provides important insights into the role of human capital in bank performance. First, banks ought to invest in promoting HCE through training and development. As regulators root for bank consolidation, attention to HCE is imperative for fostering profitability and stability.

The study fills an essential gap in the literature by evaluating the effect of firm-level market power on bank performance in an emerging market. We adopt a novel stochastic frontier estimator to generate the Lerner index. Further, this is the first study known to the authors to evaluate the effect of market power on bank performance in the context of human capital efficiency variations.

This study examines the impacts of the Ethiopian developmental state model on the competition, efficiency and profitability of banks.

The competition, efficiency and profitability of the Ethiopian bank are measured using Panzar Rose, data envelopment analysis and financial ratio. Fixed-effect panel regression methods are applied to test the direction and strength of association between the Ethiopian developmental state model and the competition, efficiency and profitability of the country's banks while controlling bank-specific market structure and macroeconomic factors.

The Ethiopian developmental state model embeds the state-directed financial system, which affects the banking industry using a range of credit allocation instruments. Of which, directed credit schemes, interest rate control and the lack of financial freedom reduce the competition and efficiency of banks. The National Bank of Ethiopia (NBE) advances to the government and the sale of Treasury bills to a captive market enhances banking competition while negatively affecting banking efficiency. Interest rate control and the lack of financial freedom lower banking profitability. Unexpectedly, directed credit schemes improve banking profitability.

As with any study, this one has limitations. The intra-period comparison of efficiency is based on balanced data. Future studies can use methods that can measure the efficiency of banks using unbalanced data. The computation of the yearly H-statistic is constrained by the small sample size. The use of high-frequency data for measuring competition can provide us with better insights into banking competition in Ethiopia. Furthermore, there are a number of methods for measuring banking competition, efficiency and profitability with different assumptions. Approaching the subject of this study by applying different methods will offer different insights.

The contributions of this study to practice are at two levels. First, at the policy level, it enhances our understanding of the impacts of developmental state model policies, as implemented in Ethiopia, on the banking industry and therefore provides suggestions to policymakers to reform the sector's policies. Second, it offers input to the management of banks regarding the factors that impact the industry.

The banking industry is often studied in the context of financial liberalisation. The originality of this study lies in investigating how the competition, efficiency and profitability of banks are affected when operating in the context of significant state interventions in the industry.

Foreign direct investment (FDI) has a critical role in boosting agricultural productivity and the growth of emerging economies. The relationship between FDI inflows and environmental factors has not received much attention in identifying its impact on agricultural output. Using annual time series data from 1990 to 2023, this study examines the causal association and short- and long-run effects of FDI inflows, forest coverage and CO2 emissions on the agricultural productivity of the India, China and US (ICU) economies. The autoregressive distributed lag (ARDL) results confirmed that FDI inflows have a significant and positive impact on Indian and Chinese agriculture productivity, whereas CO2 emissions adversely affect US agriculture productivity in the long run. In the short run, CO2 emissions led to agricultural productivity in both China and the US economies. The bound test and error correction model (ECM) result also confirmed the long-run connection and convergence of the equilibrium path among the studied variables except India. The findings of the Granger causality test showed a unidirectional causal link between agriculture productivity and FDI inflows and forest coverage in India and a bidirectional causal link between CO2 emission and agricultural yield and forest coverage and CO2 emission in the Chinese agriculture sector. The study also revealed a unidirectional causal association between forest coverage and agricultural output and between FDI, CO2 emissions and forest coverage in the US agriculture sector. Policymakers were advised to encourage FDI in the agriculture sector and expand the use of environment-friendly technology to decrease carbon emissions and promote forest coverage for sustainable growth and higher agricultural production.

The purpose of this paper is to examine the association between company reputation and dividend policy.

In this study, sample of 98,809 firm-year observations from 22 countries covering 2005–2016 were used.

Firm reputation concerns are associated with higher propensities to pay dividends and payout ratios. Further, this positive effect is more pronounced for firms with high free cash flows, high information asymmetry and low institutional monitoring. The results are robust to an instrumental variable approach, propensity score matching and the Heckman two-stage correction approach while addressing endogeneity concerns.

These findings have significant implications for various stakeholders, such as existing and potential investors, managers, policymakers and regulators, by providing insights into the relationship between corporate reputation and firm dividend payout decisions. Corporate reputation is highlighted as crucial for accessing finance, emphasizing the role of national regulators and policymakers in facilitating firms' efforts to improve their reputation. The study highlights the dynamics of corporate reputation and dividend payout, calling for proactive engagement from regulators and policymakers. Crafting policies conducive to reputation-building can enhance firms' financial prospects, indicating the need for strategic interventions at managerial, regulatory and policy levels. Understanding the influence of economic context is crucial for firms to tailor reputation management strategies and optimize funding opportunities in different economic environments.

Overall, results suggest that reputation serves as a disciplining mechanism, where firms will pay dividends to maintain their reputations.