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Covid-19 pandemic is a unique and extraordinary situation for the globe, which has potentially disrupted almost all aspects of life. In this global crisis, the tourism and hospitality sector has collapsed in almost all parts of the world, and the same is true for India. Therefore, this paper aims to investigate the impact of Covid-19 on the Indian tourism industry.

This study develops an appropriate model to forecast the expected loss of foreign tourist arrivals (FTAs) in India for 10 months. Since the FTAs follow a seasonal trend, seasonal autoregressive integrated moving average (SARIMA) method has been employed to forecast the expected FTAs in India from March 2020 to December 2020. The results of the proposed model are then compared with the ones obtained by Holt-Winter's (H-W) model to check the robustness of the proposed model.

The SARIMA model seeks to manifest the monthly arrival of foreign tourists and also elaborates on the progressing expected loss of foreign tourists arrive for the next three quarters is approximately 2 million, 2.3 million and 3.2 million, respectively. Thus, in the next three quarters, there will be an enormous downfall of FTAs, and there is a need to adopt appropriate measures. The comparison demonstrates that SARIMA is a better model than H-W model.

Several studies have been reported on pandemic-affected tourism sectors using different techniques. The earlier pandemic outbreak was controlled and region-specific, but the Covid-19 eruption is a global threat having potential ramifications and strong spreading power. This work is one of the first attempts to study and analyse the impact of Covid-19 on FTAs in India.

Diversity management is gaining attention in the organizations. This study aims to theorize and test a model linking efforts to support diversity and organizational value of diversity with job satisfaction and organizational identification and to propose that these relationships are mediated by an organization’s diversity climate.

Employee survey was used to collect data from employees at an Australian manufacturing organization. Structural equation modelling in AMOS was performed for the proposed model, controlling for age and gender.

The mediating role of diversity climate in the relationship of organizational value of diversity and outcomes (job satisfaction and organizational identification) is significant. The authors discuss theoretical, research and practical contributions.

The present study extends the literature by testing a mediation model derived from the signalling and social exchange theories.

This study aims to investigate whether the impact of effectiveness of diversity training on affective commitment is different for men versus women and whether affective commitment mediates the relationship between effectiveness of diversity training and employee outcomes of turnover intention and job satisfaction.

The data were collected from 134 employees working in an Australian manufacturing organization by using an employee survey. Structural equation modeling was used to analyze the data using AMOS.

The results of this study support the proposed hypotheses, demonstrating a significant, indirect effect of effective diversity training on job satisfaction and turnover intention via affective commitment. Moreover, gender moderates the relationship between effective diversity training and affective commitment.

The findings suggest that organizations can enhance affective commitment and job satisfaction and reduce turnover intention by providing effective diversity training to employees. Gender of employees should also be considered when evaluating the effectiveness of training.

This study provides pioneering evidence of the following relationships: diversity training effectiveness and turnover intention via affective commitment; diversity training effectiveness and job satisfaction via affective commitment; and diversity training effectiveness and affective commitment for men versus women.

The purpose of this paper is to investigate the behavior peculiarities of the labor force participation in Eastern European countries.

The authors provide the analysis of nonlinearity in dynamics of economic active population and perform the econometric analysis using logistic smooth transition autoregressive models that are flexible and capture various kinds of behavior for different modes. The paper investigates labor markets of six Eastern European countries, Hungary, Bulgaria, Poland, Slovakia, Romania and Croatia that are characterized by lower level of labor force participation rate (LFPR) than average level in EU.

The results of modeling quantitatively characterize smooth changes in the behavior modes of labor force activity for each country and indicate how population economic activity depends on previous labor market states. The estimated slope parameters that determine the smoothness of transition between regimes show that, in all countries, the labor force participation quite quickly reacts to changes that occurred on the labor market in the past. During recession periods, households of European countries that joint EU last decade in order to prevent the depletion of their total income increased labor supply and showed increased activity in job search.

This paper indicates the nonlinearity and asymmetry in LFPR in transition economies, discovers variety of its dynamics in the different regimes and determines the indicators that cause the change of the population economic activity behavior in each country.

The purpose of this paper is to investigate why professional workers actually remain in their organisations.

The design of the study was cross-sectional. A number of factors important for the retention of professional workers were identified from the literature. A 19 item “retention scale” was developed based on the identified retention factors and their characteristics. It was proposed that the retention factors could be divided into two levels: organisational and job. The retention scale was completed by 138 workers form the UK site of a multinational Marketing company. The reliability of the scale was assessed using Cronbach’s α and was found to be 0.80.

Factor analysis supported the division of the retention factors into organisational and job levels with a two factor structure in which organisational levels loaded strongly on component 1 and job level items loaded strongly on component 2. Scores on these two subscales predicted individual workers’ intention to remain within their organisation using both MANOVA and logistic regression analysis.

This is a preliminary look at factors important for the retention of professional workers and as such has several limitations. A more comprehensive review of the literature on retention is required and further testing of the model is required with a larger sample size. Links with the literature on the psychological contract also need to be more fully explored.

This research has practical implications for practitioners due to the importance of retaining top talent for increased competitive advantage. The factors that have been found here to be important for retaining professional workers have also been observed in high performing companies.

The retirement of the baby boomer generation means that there has to be a greater emphasis on retaining key employees in organisations to mitigate the loss of key skills and competences.

Most previous studies and many HR managers concerned with the retention of professional and other workers tend to concentrate on those aspects of the job or of the organisation that make them leave. This study is concerned with why people stay with their employers.

Managerial finance (MF) started publication in 1975 and celebrated its 45th anniversary in 2019. The purpose of this study is to provide a bibliometric analysis of MF between 1996 and 2019.

This study uses the Scopus database to analyze the most frequent authors in MF along with their affiliated institutions and countries. It also identifies the most often cited MF articles. This study uses bibliometric indicators to analyze productivity and stature of MF. It also uses such tools as bibliographic coupling, keyword analysis and coauthorship analysis to analyze MF. Further, the study provides a temporal analysis of MF publishing across different ownership periods.

MF publishes between 60 and 70 articles each year and its number of citations steadily grows. Although contributors to the journal come from around the globe, they most often are affiliated with the United States, the United Kingdom and Greece. Temporal analysis of journal's themes reveals that it has expanded its scope from accounting research to a much wider array of finance topics. Bibliographic coupling network analysis shows that major themes published in MF involve stock markets, corporate governance, banking, financial decision-making and initial public offerings.

Due to the unavailability of bibliometric data, the analysis excludes an analysis of MF between 1975 and 1995.

This study provides the first overview of the MF's publication and citation trends as well as its thematic structure. It also suggests future directions that the journal might take.

This study aims to analyse the scientific relationship between technological innovation and carbon emissions. Taking the Chinese electric power industry as the empirical research object, this study examined the effect of power technological innovation on carbon emissions and proposed policy recommendations for the development of technological innovation in China.

This study first calculated the energy consumption and carbon emission level of the Chinese electric power industry from 2005 to 2018. Secondly, this study built an evaluation index system for technological innovation of electric power with six indicators: average utilisation hours of power generation equipment; power consumption rate of power plant; line loss rate; standard coal consumption for power generation; standard coal consumption for power supply; and number of patent applications granted for generation, conversion or distribution of electric power in China. Finally, from a practical point of view, the relationship between technological innovation and carbon emissions of the Chinese electric power industry from 2005 to 2018 is evaluated and analysed.

Power technology innovation has been found to have a long-term and relatively large effect on carbon emissions, and carbon emissions have a short-term and insignificant impact on power technology innovation.

This study puts forward relevant suggestions for developing technological innovation and technology transfer, which is essential to establishing a low-carbon or zero-carbon power system in China.

This study provides empirical evidence for clarifying the relationship between technological innovation and carbon emissions in the power industry and further develops research theories on technological innovation and carbon emissions.

Relevant authorities will adopt measures to promote technological innovation and development in the power sector to reduce carbon emissions.

This study built an evaluation index system with six indicators for technological innovation of electric power. The evaluation method was used to measure the technological innovation level of the Chinese electric power industry. The causal link between technological innovation and carbon emissions in China was analysed.