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This interdisciplinary study aims to analyze how service organizations communicate sustainable beliefs in their social media narratives and use them to generate brand awareness, customer recognition and ongoing demand for sustainable service.

A two-phase exploratory analysis of 10,342 tweets from 2019–2020 was conducted by sustainable global corporations to identify best practices for their social media teams operating within a service-based business model. First, the significant themes were identified using an unguided machine learning approach of three types of firms: services, goods and mixed. Next, the full set of tweets with linguistic sentiment analysis was analyzed followed by a deeper view of the services-based organizations based on their strategic focus (business-to-business [B2B] versus mixed).

The findings indicate that tweets that appear to create the highest customer engagement are characterized as having high levels of analytical language, high clout (i.e. are socially relevant), a positive tone, a high number of words and a high number of words per sentence. On the other hand, having complex language in terms of six-letter words does not seem to associate with customer engagement. The last level of analysis shows that B2B services-based corporations with positive tone and higher word count exhibit higher levels of retweets. Implications include providing rational and informational tweets to increase engagement and highlight societal relevance.

Climate change has negative consequences on human and physical capital, and ecosystems across the globe. This study provides specific recommendations for how services corporations can increase their sustainable communications and actions.

The key implication of our research is that corporations must strategically design social media narratives about climate change as part of their online branding and communications process.

This study analyses the impact of economic and trade policy uncertainty on US and Chinese stock markets. Also, this study examines the hedge and safe-haven properties of US and China stocks against both US and Chinese economic and trade policy uncertainty.

To achieve the desired goals, the authors employ Dynamic Conditional Correlation through Glosten et al. (1993) model based on the Generalized Autoregressive Conditional Heteroscedasticity (DCC-GJR-GARCH (1, 1)) and Quantile cross-spectral (QS) models. The study uses monthly observations spanning from March 2010 to June 2022.

This study evidence that the economic and trade policy uncertainty between USA and China is extremely sensitive and has high volatility clustering effects on DJChina88 and DJUS, respectively. Conversely, against the Chinese economic and trade policy uncertainty, the US stock market indexes show both hedging properties across the period and safe-haven during COVID-19 and Russia–Ukraine crises. In contrast, among the Chinese stock markets, only DJShenzhen and DJShanghai stock indices might provide strong hedging and safe-haven properties against the US economic and trade policy uncertainties; however, DJShenzhen (DJChina88) stock shows weak hedge and safe-haven properties (hedging benefits) against Chinese trade policy uncertainty (CTPU) (Chinese economic policy uncertainty [CEPU]).

The findings have significant implications for investors, portfolio managers and regulators in hedging and making proper decisions under uncertain circumstances.

The study extends the literature on stock market performance to cover the economic and trade policy uncertainty by providing novel evidence during the recent COVID-19 and Russia–Ukraine invasion.

This paper aims to examine the factors that lead to the failure of startups in India and proposes a ‘Four Dimensional (4D) Strategic Framework’ to drive success.

This study is exploratory and uses a narrative analysis methodology to analyse the accounts of key startup stakeholders – founders, investors, former employees and consumers; to identify their failure factors. A conveniently selected sample of 165 startups was studied to understand better the reasons for their failure within a thematic framework developed from David Feinleib’s (2012) handbook “Why Startups Fail”.

Results indicate that a dearth of capital or running out of money and inadequate sales and marketing strategy, which leads businesses to fall behind rivals and lose money on each transaction, are the most common factors for startup failure in India.

“Startups” are substantial for emerging economies like India because they fuel technological innovation and economic progress and provide for the modern workforce’s needs and aspirations. However, they seem to be typically unprofitable, with a modest probability of survival. Subsisting studies mainly focus primarily on success factors and very few on why startups fail, with significant disagreement on an appropriate methodology. To the best of the authors’ knowledge, this is the first study that analyses failure factors of Indian startups using narrative analysis of its key stakeholders. It aims to aid the conception of profitable entrepreneurship by reducing the failure frequency in the startup and small business ecology.

The purpose of this study is to determine whether COVID-19 had an impact on the brand equity of the Top 100 global brands in the Americas, European and Asian regions over the three years of assessment (2020–2022).

A secondary data method (document scanning) was used to gather the study’s data from Brand Finance’s Global 500 annual reports from 2019 to 2022. The data for this study was analysed using the IBM Statistical Package for Social Science (SPSS) Statistics for Windows, Version 26.0. The data were subjected to a descriptive test and one-way analysis of variance.

The findings showed that most of the Top 100 global brands from the Americas, Europe and Asia experienced little or no impact due to COVID-19. Thus, no significant differences were found to exist among the Top 100 global regional brands due to COVID-19 in the years 2020 and 2021. However, there is a significant difference in 2022 due to its small effect size.

The findings of this paper contribute to brand equity literature and global branding literature in the context of COVID-19. This paper innovatively frames brand equity and provides guidelines to help brands sustain their financial-based brand equity during a worldwide crisis.

The objective of this chapter is to identify the key characteristics of Global Services businesses that will thrive and achieve success in the future. These factors are integrated into three main pillars, which we refer to as the Triple-Win. The first and most obvious pillar is technology as a tool. The second pillar is the design and sustainability of the business model, without which the previous factor would be merely a cost and not an investment. And last but not the least, there is the purpose which gives meaning to the proposal, focusing on the human being and their environment. The DIDPAGA business model sits at the intersection of these three elements.

Customer satisfaction (CS) is a key factor in maintaining customer relations and achieving corporate success. This paper aims to empirically investigate the value relevance of CS accounting for corporate performance (CP) of top global brands worldwide.

A sample of top 100 global brands located in different countries and operating over various industries is examined for a period of three years comprising 2020 till 2022. A quantitative research methodology is used for conducting content analysis of companies’ annual reports and carrying out ordinary least squares multiple regression tests using different financial and market measures, as proxies for CP.

Results show that CS can significantly enhance CP. Findings indicate a significant positive association of current and lagged CS with both profitability and market value, thereby documenting consistent evidence in a global market setting.

The study provides an aggregate picture of the value relevance of CS while a disaggregated view across different industries can reveal deeper insights. However, the study has important implications for corporate executives, investors, accountants and standard setters, offering global insights that appreciate CS for improving CP and creating value for businesses. It helps in understanding customers preferences, designing corporate policies and strategies, predicting CP, developing alternative methods of CS measurement and reporting and recommending possible accounting treatments.

This study adds to the relatively limited literature on the potential contribution of CS within the accounting literature. It extends the scope of prior research by documenting quantitative empirical evidence of the value relevance of CS for CP of top global brands, using different financial and market measures. It provides international insights into a global market setting, in which diversity is inherent and competition is fierce. Hence, the study largely contributes to resolving existing debate by documenting consistent objective evidence over a wide regional diversity using various indicators.

Renewable energy infrastructure is an important asset class in the context of reducing global carbon emissions going forward. This includes solar power, wind farms, hydro, battery storage and hydrogen. This paper examines the risk-adjusted performance and diversification benefits of listed renewable energy infrastructure globally over Q1:2009–Q4:2022 to examine the role of renewable energy infrastructure in a global infrastructure portfolio and in a global mixed-asset portfolio. The performance of renewable energy infrastructure is compared with the other major infrastructure sectors and other major asset classes. The strategic investment implications for institutional investors and renewable energy infrastructure in their portfolios going forward are also highlighted. This includes identifying effective pathways for renewable energy infrastructure exposure by institutional investors.

Using quarterly total returns, the risk-adjusted performance and portfolio diversification benefits of global listed renewable energy infrastructure over Q1:2009–Q4:2022 is assessed. Asset allocation diagrams are used to assess the role of renewable energy infrastructure in a global infrastructure portfolio and in a global mixed-asset portfolio.

Listed renewable energy infrastructure was seen to underperform the other infrastructure sectors and other major asset classes over 2009–2022. While delivering portfolio diversification benefits, no renewable energy infrastructure was seen in the optimal infrastructure portfolio or mixed-asset portfolio. More impressive performance characteristics were seen by nonlisted infrastructure funds over this period. Practical reasons for these results are provided as well as effective pathways going forward are identified for the fuller inclusion of renewable energy infrastructure in institutional investor portfolios.

Institutional investors have an important role in supporting reduced global carbon emissions via their investment mandates and asset allocations. Renewable energy infrastructure will be a key asset to assist in the delivery of this important agenda for a greener economy and addressing global warming. Based on this performance analysis, effective pathways are identified for institutional investors of different size assets under management (AUM) to access renewable energy infrastructure. This will see institutional investors embracing critical investment issues as well as environmental and social issues in their investment strategies going forward.

This paper is the first published empirical research analysis on the performance of renewable energy infrastructure at a global level. This research enables empirically validated, more informed and practical decision-making by institutional investors in the renewable energy infrastructure space. The ultimate aim of this paper is to articulate the potential strategic role of renewable energy infrastructure as an important infrastructure sector in the institutional real asset investment space and to identify effective pathways to achieve this renewable energy infrastructure exposure, as institutional investors focus on the strategic issues in reducing global carbon emissions in the context of increased global warming.

Over the last decade, investments in green energy companies have witnessed noticeable growth rates. However, the glacial pace of the world economic restoration due to COVID-19 pandemic placed a high degree of uncertainty over this market. Therefore, this study investigates the short- and long-term relationships between COVID-19 new cases and WilderHill New Energy Global Innovation Index (NEX) using daily data over the period from January 23, 2020 to February 1, 2023.

The authors utilize an autoregressive distributed lag bounds testing estimation technique.

The results show a significant positive impact of COVID-19 new cases on the returns of NEX index in the short run, whereas it has a significant negative impact in the long run. It is also found that the S&P Global Clean Energy Index has a significant positive impact on the returns of NEX index. Although oil has an influential effect on stock returns, the results show insignificant impact.

Governments have the chance to flip this trend by including investment in green energy in their economic growth stimulation policies. Governments should highlight the fundamental advantages of investing in this type of energy such as creating job vacancies while reducing emissions and promoting innovation.

First, as far as the authors are aware, the authors are the first to examine the effect of oil prices on clean energy stocks during COVID-19. Second, the authors contribute to studies on the relationship between oil prices and renewable energy. Third, the authors add to the emerging strand of literature on the impact of COVID-19 on various sectors of the economy. Fourth, the findings of the paper can add to the growing literature on sustainable development goals, in specific the papers related to energy sustainability.

The COVID-19 pandemic triggered an increase in online traffic, with many assuming that this technology would facilitate coping through active social connections. This study aims to interrogate the nature of this traffic-engagement relationship by distinguishing between passive (e.g. browsing) and active (e.g. reacting, commenting and sharing) engagement, and examining behavioral shifts across platforms.

Three field studies assessed changes in social media engagement during the COVID-19 pandemic. These studies included social media engagement with the most followed accounts (Twitter), discussion board commenting (Reddit) and news content sharing (Facebook).

Even though people spent more time online during the pandemic, the current research finds people were actively engaging less. Users were reacting less to popular social media accounts, commenting less on discussion boards and even sharing less news content.

While the current work provides a systematic observation of engagement during a global crisis, it does not claim causality based on its correlational nature. Future research should test potential mechanisms (e.g. anxiety, threat and privacy) to draw causal inference and identify possible interventions.

The pandemic shed light on a complex systemic issue: the misunderstanding and oversimplification of how online platforms facilitate social cohesion. It encourages thoughtful consideration of online social dynamics, emphasizing that not all engagement is equal and that the benefits of connection may not always be realized as expected.

This research provides a postmortem on the traffic-engagement relationship, highlighting that increased online presence does not necessarily translate to active social connection, which might help explain the rise in mental health issues that emerged from the pandemic.