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This study aims to systematically review the literature on how various factors influence investor sentiment and affect financial markets. This study also sought to present an overview of explored contexts and research foci, identifying gaps in the literature and setting an agenda for future research.

The systematic literature investigation yielded 555 journal articles, with few other exceptional inclusions. The data have been extracted from the two databases, i.e. Scopus and Web of Science. For bibliometric analysis, VOSviewer and Biblioshiny by R have been used. The period of investigation is from 1985 to July 2023.

This systematic literature review helped us identify factors influencing investor sentiment and financial markets. This study has broadly classified these factors into two categories: rational and irrational. Rational factors include – economics and monetary policy, exchange rate, interest rates, inflation, government mandatory regulations, earning announcements, stock-split, dividend decisions, audit quality, environmental, social and governance aspects and ratings. Irrational factors include – behavioural and psychological factors, social media and online talk, news and entertainment, geopolitical and war events, calendar anomalies, environmental, natural disasters, religious events and festivals, irrationality caused due to government/supervisory body regulations, and corporate events. Using these factors, this study has developed an investor sentiment model. In addition, this review identified research trends, methodology, data and techniques used by researchers.

This review comprehensively explains how various factors affect investor sentiment and the stock market using the investor sentiment model. It further proposes an extensive future research agenda. This study has implications for stock market participants.

This paper develops a decision-analysis model to prioritize and select the site to establish a new hospital over different indicators such as cost, market conditions, environmental factors, government factors, locations and demographics. In this way, an integrated model is proposed under the intuitionistic fuzzy information (IFI), the standard deviation (SD), the rank-sum (RS) and the measurement of alternatives and ranking using the compromise solution (MARCOS) approach for ranking hospital sites (HSs).

The IF-SD-RS model is presented to obtain the combined weight with the objective and subjective weights of diverse sub-criteria and indicators for ranking sites to establish the hospital. The IF-MARCOS model is discussed to prioritize the various sites to establish the hospital over several crucial indicators and sub-criteria.

The authors implement the developed model on a case study of HSs assessment for the construction of new hospital. In this regard, inclusive set of 6 key indicators and 18 sub-criteria are considered for the evaluation of HSs. This study distinguished that HS (h₂) with combined utility function 0.737 achieves highest rank compared to the other three sites for the given information. Sensitivity analysis is discussed with different parameter values of sub-criteria to examine how changes in weight parameter ratings of the sub-criteria affect the prioritization of the options. Finally, comparative discussion is made with the diverse extant models to show the reasonability of the developed method.

This study aims to develop an original hybrid weighting tool called the IF-SD-RS model with the integration of IF-SD and IF-RS approaches to find the indicators' weights for prioritizing HSs. The developed integrated weighting model provides objective weight by IF-SD and subjective weight with the IF-RS model. The model presented in the paper deals with a consistent multi-attribute decision analysis (MADA) concerning the relations between indicators and sub-criteria for choosing the appropriate options using the developed IF-SD-RS-MARCOS model.

This paper aims to investigate the dynamic volatility connectedness among 13 G20 countries by using the volatility indices.

The connectedness approach based on the time-varying parameter vector autoregression model has been used to investigate the linkage. The period of study is from 1 January 2014 to 20 April 2023.

This analysis revealed that volatility connectedness among the countries during COVID-19 and Russia–Ukraine conflict had increased significantly. Furthermore, analysis has indicated that investors had not anticipated the World Health Organization announcement of COVID-19 as a global pandemic. Contrarily, investors had anticipated the Russian invasion of Ukraine, evident in a significant rise in volatility before and after the invasion. In addition, the transmission of volatility is from developed to developing countries. Developed countries are NET volatility transmitters, whereas developing countries are NET volatility receivers. Finally, the ordinary least square regression result suggests that the volatility connectedness index is informative of stock market dynamics.

The connectedness approach has been widely used to estimate the dynamic connectedness among market indices, cryptocurrencies, sectoral indices, enegy commodities and metals. To the best of the authors’ knowledge, none of the previous studies have directly used the volatility indices to measure the volatility connectedness. Hence, this study is the first of its kind that has used volatility indices to measure the volatility connectedness among the countries.

This study investigates how the conflict between Russia and Ukraine impacts global inflation.

The study uses monthly consumer price index (CPI) data from 60 countries for 30 months, from January 2020 to June 2022. An event study methodology has been employed to check abnormal variation in the CPI, after classifying country-specific monthly data into nine groups.

The outcome revealed that Russia's full-scale invasion of Ukraine triggered inflation globally. However, the severity of inflation in the sample countries is determined by their geographical proximity and trading activity with the countries in conflict. A significant rise in inflation was observed among major European economies during the invasion. As the war continues, the increase in the price of essential commodities is evident worldwide.

The war literature till now has concentrated on stock markets, energy markets, exchange rates and precious metals. Since no previous research has attempted to quantify the abnormal effect of the war on domestic and global inflation, the current study will shed much-needed light on the subject.

The purpose of this study is to determine the effect of loneliness and alienation in the workplace on the intention of leaving employment and whether emotional exhaustion has a mediating role in this effect.

The hypotheses generated within the framework of the study model were evaluated by using the data set obtained from 402 survey participants working at nine shopping malls in the Central and Eastern Black Sea regions of Turkey and statistical analysis programs. In this context, the confirmatory factor analysis (CFA) was used to determine the validity of the scale and the structural equation modeling (SEM) was used to test the research hypotheses.

The study reveals that loneliness and alienation in the workplace have an effect on the intention of leaving employment and that this effect is fully mediated by emotional exhaustion. Whether this full mediating role determined by the SEM is meaningful or not was evaluated by Bootstrap analysis and the results revealed that the effect is meaningful.

Developing effective communication channels that will prevent the employee from feeling isolated at work and eliminating the pressure and inadequate physical working conditions created by unrealistic sales targets are recommended. In addition, it is thought that if employees are included in decision-making processes and have sufficient autonomy related to the job, work alienation can be prevented.

This research is important in terms of evaluating shopping centers, which are accepted as the symbol of consumption today, not only with their economic aspects but also with their employees. In this context, the research has revealed that shopping mall employees want to leave their jobs due to emotional exhaustion caused by loneliness and alienation at work.

With gaining popularity, online communities are increasing. It is leading to the data and information overflow. So, there are some challenges like cyber frauds, cyberbullying, etc. while engaging with online communities. Not only this, anonymity of the participants, stress and racism are also big challenges in online communities' interaction. Online harassers' attack tactics have changed over time. In addition, there are challenges like quality of discussion, inequality in participation of the users, etc. may scale online communities towards incitement and activism. Therefore, this study will try to analyse these challenges for overall benefit of the society.

The underlying fuzzy set theory is employed to handle the fuzziness of users' perceptions since the attributes are expressed in linguistic preferences. Through exhaustive literature review, the authors have identified 15 challenges. These challenges are further categorised as cause and effect by using DEMATEL (Decision-Making Trial and Evaluation Laboratory) approach.

Lack of strategic planning and uninspired discussions between users has emerged as a major challenge in cause category. This study further demonstrates how individual challenge can be managed and developed to navigate the online communities to maintain a healthy environment in society.

Results are based on limited dataset. Therefore, findings cannot be generalised for all online communities.

The research findings offer a suitable direction to policymakers to formulate and design policies, laws and regulations to increase user engagement in the online community. The study is beneficial to firms and researchers in understanding the factors influencing effective management of online communities.

Social enterprises (SEs) have experienced unprecedented uncertainty due to COVID-19, and it has challenged the fundamental assumptions underlying the SEs. Little is known about the strategic response of SEs when their fundamental characteristics are being challenged. The purpose of this paper is to explore – how do SEs respond to a crisis caused by the pandemic?

This paper adopts a case study approach and reports the response strategy of impulse social enterprises (ISE) from India. Data were collected through interviews, Webinars and organizational reports. To analyze the data, the authors examined the fundamental assumption on SE that was challenged by the pandemic.

The response strategy of ISE is driven by social and substantive rationality focusing on the relationship with the community and doing what is good for them. The role of communication was vital in gathering support and resources to continue with their function. ISE adapted a mindset of mission agility and created an alternative market for its product.

This study highlights the response strategy of SE in an emerging economy like India, which experienced one of the stringent lockdowns. It is probably one of the few studies that examined the responses of SE under a crisis that challenged their fundamental attributes by adopting the framework of Bacq and Lumpkin (2021).