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This study examines the contribution of urban development to Vietnam's economic progress over the period 1986–2020. The study uses an augmented Solow framework, where urbanization is included as a shift variable in addition to capital per worker and accounts for structural breaks. It examines the cointegration and the long-run and short-run effects of urban development from four different cases of cointegration (constant, restricted constant, restricted trend and trend options), with each case accounting for the effect of a significant structural break. Also, the study provides causality nexus to check the presence of urbanization-led growth hypothesis. From the results, we note a long-run positive effect of urbanization on economic growth, but no short-run effects. In all cases, a 1% increase in population results in 0.8–0.9 increase of output, hence supporting a positive and momentous effect of urbanization over the long-term. We note a significant positive effect of a single structural break period (1991), which is a period of major shift towards economic progress. We note bidirectional causality between capital and output and a unidirectional causality from output and capital to urbanization. The former suggests a mutually reinforcing effect of capital accumulation and economic growth, and the latter indicates that urban development necessitates economic growth and capital accumulation. The findings derived from this study provide further impetus for urban development and urban policies and consider urbanization as a critical source of economic growth for Vietnam.

The purpose of this study is to examine how Industry 4.0 (I4.0) implementation might improve marketing performance (MP). Early adopters now have the chance to capitalize on the advantages of this successful implementation owing to the transition to I4.0. To improve MP, businesses must be able to identify and manage their effective implementation of I4.0 technologies, which are essential to improve industrial performance.

A survey was created and sent to 311 samples of manufacturing companies. To investigate the hypothesis created in this context, the study includes a survey-based analysis. To present the study’s findings, partial least squares-structural equation modeling has been used.

According to the findings, it can be concluded that an efficient implementation of Industry 4.0 (EII) can improve MP by positively impacting consumer loyalty and increasing customer loyalty (CL) positively enhancing by product customization (PC). The study’s key results, however, are how both PC and CL affect MP.

The intensive production technologies that are at the center of I4.0 will be better understood by professionals thanks to this study. The Internet of Things, artificial intelligence, additive manufacturing, sophisticated robots and many more are examples of these technologies. I4.0’s application strengthens efficiency and high-quality production. The I4.0 concept is gaining popularity in both developed and emerging countries due to its higher performance. Additionally, business people are actively working to implement I4.0 and make it a big success.

The study identifies the successful adoption of I4.0 that has a substantial impact on businesses’ MP. However, there is a lack of noteworthy studies that can concentrate on the marketing reach with I4.0 deployment. As a result, the goal of the current research is to comprehend how I4.0 will affect MP.

Using the most recent dataset from 2013–2014 to 2017–2018, the study examines the efficiency of 75 coal-fired power plants in the Indian thermal power sector. The authors obtained robust estimates of efficiency scores by employing Seiford and Zhu’s (2002) DEA-based classification invariance technique to account for CO₂ emissions as an undesirable output. Meta-frontier analysis and the Tobit regression are used to compute technology heterogeneity across power plants belonging to public and private groups and investigate the factors driving carbon-adjusted efficiency, respectively. The results reveal that, on average, the efficiency of power plants during the study period is 78.26%, showing significant room for reduction in CO₂ emissions alongside augmentation in electricity generation. Private plants are more efficient than public ones, and relative performance inefficiency is the primary source of inefficiency in the thermal power sector. Regression analysis indicates that domestic-equipped plants perform with lesser levels of efficiency, and plants with more units are more inefficient than plants with fewer units. Carbon productivity significantly improves efficiency since fewer fossil fuels with high carbon will generate more electricity.

Nowadays fossil fuel prices have increased; therefore, consumption of energy reduction has become a significant issue. Hence, this study aims to explore energy-efficient mechanical devices and their energy management.

This study focused on numerical analysis of various factors, including pressure drop, sensitivity, heat transfer and friction factor. This study compared the performance of two different arrangements of the heat exchanger: flat tube and staggered circular tube. This study also investigated the impact of varying coolant volume fractions.

This numerical analysis compares the geometric properties of flat and circular tube cross-sections while considering the flow of nanofluid inside and air outside. The current experimental investigation specifically examines the temperature-dependent characteristics (specific heat capacity, viscosity, density and thermal conductivity) of the stable ternary hybrid nanofluid mixture composed of Al₂O₃, CuO and TiO₂.

While several researchers have conducted numerical investigations on laminar flow in circular tubes, only a few studies are available on flat tube heat exchangers that use nanofluids just for internal flow. Furthermore, there is no simultaneous study on internal and exterior flow. Therefore, more investigation is necessary to examine the combined three-dimensional examination of shapes and their thermal-hydraulic influence using hybrid nanofluids.

Purpose: Green consumerism is on the rise in the 21st century, impelling businesses to prioritise environmental awareness and expand eco-products to keep up with the growing demand. This research examines how social media (SM) and moral obligations (MO) affect consumer views and their propensity to make eco-friendly choices.

Methodology: Data were gathered from 508 participants using an adaptive questionnaire. The proposed model was tested using ‘structural equation modelling’.

Findings: The results show that electronic word-of-mouth (EWOM) and the intent to acquire green goods favourably impact consumer behaviour. MO positively influences attitudes and intentions to make green purchases (GPI), with attitudes acting as a mediator between MO and GPI.

Implications: This research is of utmost importance for marketers wanting to enhance their SM communication strategies to influence consumers’ opinions of green products and raise the possibility that they would make environmentally conscious purchases.

This chapter investigates pandemic impact in a variety of industries, including food, travel, education and pharmaceuticals, considering elements such as isolation, emotions and social influences, which can lead to panic buying. The goal of this research is to ascertain how COVID-19 influences the buying decisions of customers. Additionally, the study aims to identify consumer consumption trends for a spectrum of products and services, including fast-moving consumer goods (FMCGs), entertainment, pharmaceuticals, travel and tourism. A comprehensive review of different research papers is done to conclude. The papers considered are from 2020 to 2022. Different keywords are used to search the relevant papers such as ‘pandemic’, ‘COVID-19’, ‘behaviour’, ‘impulsive’, etc. TCCM framework has been applied while reviewing the articles. During the isolation, consumer behaviour moved to panic buying and stockpiling, favouring organic basics, and encouraging e-commerce, as well as economic nationalism favouring made-in-India products. This study helps in knowing the reasons for change in consumers' behaviour for different products and services due to unforeseeable situations like COVID-19 and can find possible ways to deal with them. Business owners learn about changing consumer purchasing behaviours and how to modify products. The government can change policies to improve medical tourism and social protection.

The aim of this study is to investigate and clarify how the triple helix actors can effectively implement the concepts of Kaizen to navigate and overcome the complex obstacles brought on by the global COVID-19 pandemic.

Through broad literature reviews, nine common parameters under triple helix actor have been recognized. A regression analysis has been done to study how the triple helix actors’ common parameters impact Kaizen implementation in business operations.

The results of this study revealed insightful patterns in the relationships between the common parameters of triple helix actor and the dependent variables. Notably, the results also showed that leadership commitment (LC) emerges as a very significant component, having a big impact on employee engagement as well as organizational performance.

In addition to offering valuable insights, this study has limitations including the potential for response bias in survey data and the focus on a specific set of common parameters, which may not encompass the entirety of factors influencing Kaizen implementation within the triple helix framework during the pandemic.

The originality of this study lies in its comprehensive exploration of the interplay between triple helix actors and Kaizen principles in addressing COVID-19 challenges. By identifying and analyzing nine specific common parameters, the study provides a novel framework for understanding how triple helix actors collaboratively enhance organizational performance and employee engagement during challenging times.

The short/fast-food and perishable food supply chains (PFSC) have similar characteristics of lower lifespan and variable demand, leading to significant waste. However, the global population surge and increased health awareness make it impossible to continue wasting food because it is responsible for the loss of economy, resources, and biodiversity. A sustainable transition in short and PFSC is necessary; thus, addressing challenges is critical to explore the best strategy for redesigning PFSC.

An extensive literature review helped to identify 40 challenges, while a Delphi study highlighted 21 critical challenges. The fuzzy decision-making trial and evaluation laboratory method establishes a causal relationship between sustainable development (SD) challenges to help redesign PFSC.

From a strategic development perspective, frequent transportation disruption is the main critical challenge. Lack of supplier reliability is the most substantial cause of independence, with a causal value of 2.878. Overhead costs and lack of green maintenance strategies are part of the performance-oriented challenges. As it belongs to the driving zone, the second quadrant requires control while transforming PFSC for better sustainable development.

The study has several implications, such as lack of supplier reliability and frequent transportation disruption, which have the most robust causal value used as short-term strategy development. For short- and fast-food supply chains, it is necessary to study market and consumer behavior patterns to optimize inventory and customer service. Combating transportation disruption and supplier reliability challenges is vital in both PFSC and short and fast-food supply chains to reduce waste and promote sustainability.

The study’s findings are unique and put value toward the sustainable transition of PFSC by revealing critical challenges and their impact.

Integrating digital technologies such as artificial intelligence and blockchain make the agri-food supply chain (ASCM) transparent, resilient and flexible. However, its adoption is quite complex due to various anticipated barriers. So, the presented research purposes to explore and investigate the barriers.

This study employs hybrid approach including Best-Worst Method (BWM) and Graph Theoretic Approach (GTA). Data were collected from industry experts employed in the agri-food sector and analyzed by means of standard operating procedures.

GTA results show that Technological barriers have the highest barrier intensity. Moreover, BWM results show that “Increased operational complexity” is the topmost barrier to adopting blockchain in ASCM. “Lack of interoperability” ranks second among the identified barriers.

The results benefit the managers, practitioners and researchers to understand the anticipated barriers so that necessary strategies can be developed, and organizations can become more resilient, agile, transparent and traceable.

The presented work is the first to develop a mathematical model and assess the industry’s eagerness to adopt blockchain in ASCM. The proposed framework will greatly benefit the stakeholders working in agri-food sector.

Capital markets are the backbone of an economy. COVID-19 has created an unacceptable and unpredictable economic environment worldwide, resulting in a significant setback for securities exchanges. India also experienced two waves of this pandemic, which led to a significant downturn in the capital market.

Researchers have endeavored to study the impact of the first and second waves of COVID-19 on the performance of various sectoral stocks in India. The performance of selected sectoral indices of the Bombay Stock Exchange was compared with the market performance of the S&P BSE 100. An event study was conducted to analyze the normal return, abnormal return (A.R.), and t-statistics of A.R. for various sectoral stocks. In addition, the abnormal returns of sectoral stocks between the first and second waves of COVID-19 in India were compared

The results of the tests showed heterogeneous A.R. between different sectors in both the first and second waves of COVID-19 in India. Positive investor outlook and government financial support programs for various sectors helped them recover from the second wave of COVID-19.

The study analyzed the impact of the peak of the first and second waves of COVID-19 on selected sectoral indices. There may be several reasons for the performance of this particular stock index. However, we have tried to analyze the best possible reasons for this turbulence in the performance of stocks of selected sectoral indices. The study can be further analyzed to examine the long-term impact of such a pandemic on other sectors.

The study is based on the panic behavior of investors during such a pandemic. No one was prepared for this and expected this pandemic to last this long. This pandemic has taught so many lessons to everyone involved. Investors need to be prepared and cautious for such unforeseen disasters before making any investment decision. They need to analyze which industry can survive under such circumstances, and then they should invest there. Industries and enterprises must adapt and improve by honestly looking at their weaknesses and trying to meet investors' expectations.