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The purpose of this study is to explore the changing buying behavior of young Bangladeshi consumers in this pandemic situation toward online orientation. The major determinants of the technology acceptance model (TAM) and consumer value theory are used to explore their impact on buying attitudes toward behavior.

In this study, a model has been conceptualized to examine the influence of hedonic and utilitarian motivational values along with perceived usefulness and perceived ease of use on actual buying behavior under pandemic conditions. A structured questionnaire has been prepared for an online survey, and data have been collected from 395 online shoppers. The structural equation modeling technique has been applied to analyze the data using SPSS and SmartPLS 3 software.

The results of this study support that perceived enjoyment and utilitarian attributes (price, convenience and health aspects) positively affect online buying attitudes along with perceived usefulness and perceived ease of use. Finally, online buying behavior is significantly influenced by the positive attitude of consumers.

The findings of this study may contribute to developing marketing strategies that may attract buyers toward a new business orientation with prosperous supreme features in the future. The emergence of the COVID-19 pandemic has changed the existing behavioral patterns of consumers and opened a new opportunity for marketers.

Young consumers are a larger section, and deep knowledge about youngsters may direct marketers toward appropriate use of marketing tools and strategies in the future.

This study integrated the TAM with hedonic and utilitarian motivational predictors to measure their impact on consumers' online buying behavior.

The transition to green growth goals requires the concerted efforts of the whole society. Enterprises, as important players in the market, play a key role in promoting green and sustainable development. The rise of the concept of sustainable development has enabled more enterprises to disclose environmental, social and governance (ESG) information, and ESG behaviour is regarded as a positive strategic behaviour to implement the new development concept. This paper aims to explore the influence of ESG performance on enterprise green innovation.

This study applies a fixed effect model and the regulation effect of empirical analysis to explore the influence of ESG performance on enterprise green innovation. The object of investigation is 2014–2021 Shanghai and Shenzhen A-share listed companies.

The results of an empirical analysis outline the following conclusions: (1) ESG performance has a significant effect on enterprise green innovation, mainly by easing the pressure of the financing enterprise, fitting stakeholders’ environmental protection concept and obtaining employee organizational identity that influences enterprise green innovation. (2) Government regulation positively regulates the role of ESG performance in promoting the green innovation of enterprises. (3) Heterogeneity analysis found that the strengthening role of ESG performance on the green innovation of enterprises is stronger in green invention patents, state-owned enterprises and nonheavily polluting industries.

Despite the valuable findings, this study has a few limitations. Thus, it is necessary to extend the object of investigation by adding other Asian countries, which allows for comparison analysis and allocating best practices for promoting green innovation. Besides, innovation and ESG performance depend on the quality of institutions. In this case, the future study should incorporate the indicators that reveal the quality of institutions (corruption, transparency, digitalisation, voice, accountability, etc.).

According to the above conclusions, this paper proposes suggestions at the level of enterprises, government and investors. At the enterprise level, ESG responsibility should be strengthened, ESG information should be consciously disclosed and the quality of ESG disclosure should be improved. Government departments should play the role of supervisors, improve the construction of ESG information disclosure systems and promote the formation of ESG systems. At the social level, investors should improve the ESG information status and pay more attention to the ESG performance of enterprises.

This study fills the scientific gaps in the analysis impact of ESG performance on the green innovation of enterprises. This paper contributes to the theoretical landscape of ESG efficiency by developing approaches based on two empirical models: testing the impact of enterprise ESG performance on green innovation and testing whether government regulation plays a regulatory role in the relationship between ESG performance and green innovation. Besides, this study analysed the ESG performance and green innovation within the following categories: heavy and nonheavy polluter industries; state and nonstate-owned enterprise groups.

This study aims to investigate the technology usage behaviour of the tourists in line with the modified unified theory of acceptance and use of technology (UTAUT) model.

Data were collected from a survey of 265 tourists using the random sampling technique. Partial least squares-based structural equation modelling (PLS-SEM) technique was used to analyze the data.

The findings revealed that performance expectancy, hedonic motivation and habit significantly influence the behavioural intention of tourists to use information and communication technology (ICT), while effort expectancy, social influence, and facilitating conditions do not have a significant influence. However, actual ICT usage behaviour largely depends on the behavioural intention of the tourists, and their habits, while the facilitating conditions do not have any influence in this case.

The findings uncover the core factors influencing tourists' actual ICT use behaviour that can assist the concerned stakeholders in designing tourism planning and sales. The study results also offer pathways for the world's tourism industry for a healthy recovery from the COVID-19 pandemic.

The findings have made robust contributions by extending the existing UTAUT-based literature by adding two new moderators in the relationship between behavioural intention and actual ICT usage behaviour.

The approach to integrate concepts from different disciplines so as to solve the problems facing smallholder farmers has gained momentum in recent years. However, very little is known about how word-of-mouth (WOM) dimensions can be used in agricultural marketing to explain market participation among smallholder farmers. Therefore, this study investigates the perceived usefulness of WOM in explaining smallholder farmers’ market participation.

The cross-sectional design was carried out to survey a sample of 467 smallholder farmers. This study used partial least squares structural equation modelling (PLS-SEM) in SmartPLS 4 to test hypotheses.

The results revealed that WOM dimensions such as expertise differential, strong tie and trustworthiness among smallholder farmers significantly influence the WOM message delivery. Likewise, the findings suggest that WOM message delivery significantly influences market participation among smallholder farmers. Finally, it was revealed that WOM message delivery significantly mediates the relationship between WOM dimensions and market participation.

This study provides useful insights to smallholder farmers on how to use WOM dimensions to enhance more market participation in formal markets, especially through proper WOM message delivery.

The current study solves the problem of information asymmetry among smallholder farmers through WOM. It is perhaps the first study to establish the link between WOM dimensions and market participation among smallholder farmers in the context of developing countries.

Despite a significant rise in the adoption of online stock trading applications, the research on measuring and enhancing the service experience of customers is scarce. This paper aims to put forth a credible service performance measurement tool, APPQUAL, customized for stock trading applications.

The paper is based on a multi-method research using qualitative and quantitative research. Further, structural equation modeling is used to establish constructs for measuring service performance.

APPQUAL is conceived and built to measure the service performance of stock trading applications. The APPQUAL measures service performance based on five unique dimensions – Safety Accuracy, Performance, Support and Usability associated with the perceived e-service quality of stock trading applications.

This study extends measurement scales for service quality measurement for a relatively new service of online stock trading applications. The scales are adapted as well as built with the help of an iterative process. The methodology is in line with the previous academic research, and the new scales developed can lead to further extensions to scale for different services.

The APPQUAL tool developed as part of this study can be applied to assess service performance and perceived service quality of stock trading applications, which have leap frogged in terms of adoption but have also been met with criticism on poor customer experience. This study shall add to the body of knowledge of stock trading platforms to enhance service experience by targeting the right factors and underlying items. The efficacy and application of the tool have been demonstrated in this paper by applying it to Zerodha and Upstox, the two of the biggest online stock trading applications in India.

There is no research or tool available currently which focuses on the service quality of the new-age platform application of stock trading apps. This is especially glaring due to the large-scale adoption of these applications by Indian customers.

This study aims to evaluate the short-term impact of brokerage analysts’ recommendations on abnormal returns using a sample selected from the S&P BSE 100 in the Indian context. The efficient market hypothesis, specifically, its semi-strong form, is tested for “Buy” stock recommendations published in the electronic version of Business Standard. The crucial issue is, are there any abnormal returns that can be earned following a recommendation? If so, how quickly do prices incorporate the information value of these recommendations? It tests the impact of analyst recommendations on average abnormal returns (AARs) and standardized abnormal returns (SRs) to determine their statistical significance.

Using a sample of stock recommendations published in the e-version of Business Standard, the event study methodology is used to determine whether AARs and SRs are significantly different from zero for the duration of the event window by using several significance tests.

The findings indicate a marginal opportunity for profit in the short term, restricted to the event day. However, the effect does not persist, i.e. the market is efficient in its semi-strong form implying that investors cannot consistently earn abnormal returns by following analysts’ recommendations. Post the event date, the market reaction to analyst recommendations becomes positive, however, insignificant until the ninth day after the recommendation providing support to the underreaction hypothesis given by Shliefer (2000) and post-recommendation price drift documented by Womack (1996). The study contributes by using different statistical tests to determine the significance of returns.

There are important implications for traders, investors and portfolio managers. The speed with which market prices incorporate publicly available information is useful in formulating trading strategies. However, stock characteristics such as market capitalization, volatility and level of analyst coverage need to be incorporated while making investment decisions.

The study contributes by using different statistical tests to determine the significance of returns.

The 2019 Global Assessment Report on Disaster Risk Reduction (GAR) cites earthquakes as the most damaging natural hazard globally, causing billions of dollars of damage and killing thousands of people. Earthquakes have the potential to drastically impact physical, social and economic landscapes; to reduce this risk, earthquake early warning (EEW) systems have been developed. However, these technical EEW systems do not operate in a vacuum; the inequities in social systems, along with the needs of diverse populations, must be considered when developing these systems and their associated communication campaigns.

This article reviews aspects of social vulnerability as they relate to ShakeAlert, the EEW system for the USA. The authors identified two theories (relationship management theory and mute group theory) to inform self-reflective questions for agencies managing campaigns for EEW systems, which can assist in the development of more inclusive communication practices. Finally, the authors suggest this work contributes to important conversations about diversity, equity and inclusion (DEI) issues within early warning systems and earthquake preparedness campaigns in general.

To increase inclusivity, Macnamara (2012) argues that self-reflective questioning while analyzing perspective, philosophy and approaches for a campaign can help. Specific to EEW campaigns, developers may find self-reflective questions a useful approach to increase inclusion. These questions are guided by two theories and are explored in the paper.

Several research limitations exist. First, this work explores two theories to develop a combined theoretical model for self-reflective questions. Further research is required to determine if this approach and the combination of these two theories have adequately informed the development of the reflective questions.

The authors could find little peer-reviewed work examining DEI for EEW systems, and ShakeAlert in particular. While articles on early warning systems exist that explore aspects of this, EEW and ShakeAlert, with its very limited time frames for warnings, creates unique challenges.