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The paper examines the increase in annual income of the new middle-class (The NMC) of Delhi-NCR and its impact on their investment habits, consumption habits and lifestyle. The paper aims to look into the transformation of the new middle-class into the NMC in emerging economies and its potential to the companies and investors.

This study draws insight from 558 new middle-class consumers in Delhi-NCR. ANOVA, post hoc tests , and hierarchical multiple linear regression model are applied to test the proposed hypotheses.

The NMC living in India's megacities imitates the lifestyle of their counterparts living in the West. To maintain their status and present themselves different from those living in middle or lower-middle-class categories, they spend audaciously, even though the income is low. When they enter the new middle class, their consumption, saving and lifestyle diversify positively.

This study has limitations. First, the authors do not apply any behavioral theory or marketing model such as the theory of reasoned action (TRA), Engel-kollat-Blackwell (EKB) model or theory of normative model of target markets. Second, the research is limited to the NMC of only one emerging economy, i.e., India. Third, the research sample is limited to only one megacity of India, i.e., Delhi. Finally, this research used only one factor, i.e., AI, to study the consumption pattern.

The results suggest that considering the buying habits and lifestyle of Indian the NMC, consumers would prove helpful to the companies in product decision-making. Furthermore, understanding change in investment habits across different income levels would be advantageous to financial institutions, investment planners and marketers while designing their products to attract investment.

The research holds significance from the point of view of understanding Indian consumers encompassing the the NMC and predicting their implications on consumer goods-producing industries, which shall, in turn, facilitate producers and government in formulating policies and strategies.

Wages have been spreading out across workers over time – or in other words, the 90th/50th wage ratio has risen over time. A key question is, has the productivity distribution also spread out across worker skill levels over time? Using our calculations of productivity by skill level for the United States, we show that the distributions of both wages and productivity have spread out over time, as the right tail lengthens for both. We add Organization for Economic Co-Operation and Development (OECD) countries, showing that the wage–productivity correlation exists, such that gains in aggregate productivity, or GDP per person, have resulted in higher wages for workers at the top and bottom of the wage distribution. However, across countries, those workers in the upper-income ranks have seen their wages rise the most over time. The most likely international factor explaining these wage increases is the skill-biased technological change of the digital revolution. The new artificial intelligence (AI) revolution that has just begun seems to be having similar skill-biased effects on wages. But this current AI, called “supervised learning,” is relatively similar to past technological change. The AI of the distant future will be “unsupervised learning,” and it could eventually have an effect on the jobs of the most highly skilled.

The purpose of this paper is to examine the likely impact of AI robotics technology on the labor market through the lens of comparative advantage.

The first section reviews the recent success of AI in outperforming humans in cognitive intense activities such as Go, poker and other strategic games, which portends a shift in comparative advantage in human brain power work to machines. It notes the potential for a portfolio of specialized computer algorithms to compete with human general intelligence in work. The analysis contributes to the debate between economists dubious about claims that AI robotics will disrupt work and futurists who expect many jobs to be fully automated in coming years. It advances three “laws of robo-economics” to guide thinking about the new technologies and presents evidence that growing robot intensity has begun to impact the job market.

The paper finds that the case for AI robotics substantially changing the world of work and the distribution of income is more compelling than the case that it will have similar impacts on wages and employment as past technological changes. It advances an ownership solution to spread the benefits of AI robot-driven automation widely.

To the extent that who owns the robots rules the world, it argues for a concerted social effort to widen the “who” in ownership from the few to the many. It reviews policies to expand employee ownership of their own firm and of the stream of revenue via profit-sharing and gain-sharing bonuses. But the paper notes that ensuring that growth of AI robotics benefits all through ownership will require expansion of workers’ and citizens’ stake in business broadly, through collective investment via pension funds, individual investment in mutual funds and development of sovereign wealth funds.

This article is concerned with pre‐tax total income distribution in 18 “western” countries. Its objective is a tentative comparison among national income distributions and the study of trends since the 1950s. Similar issues have recently been analysed in a number of studies. This analysis differs from them in three main respects. Firstly, it refers to a group of nations which excludes developing countries. In spite of substantial differences in political and socio‐economic structures in this group of countries, processes of income distribution have a great degree of similarity. Income statistics are then more “homogeneous” and their comparison more meaningful than in studies covering developed and developing nations. Secondly, the article differs in the methodology it uses. Other studies have relied on “strict comparisons” of income statistics, for example they have compared values of coefficients of inequality and of income shares. In this article “loose classification”, for example categorisation of countries into groups (see following section), is used as a means of comparing income distributions. This makes it possible to allow, within limits, for the fact that the value of the data can be different from the one which is observed, even when statistics seem “fairly” accurate and comparable. Thirdly, the possible influence of the data source on each country's position is examined by considering a plurality of sources whenever possible. Intentionally, this article does not include discussion of most of the problems which exist in the field of income distribution—including those concerning coverage and reliability of data. It is expected that the reader keeps them and their various caveats well in mind when evaluating the empirical evidence which is presented. The explanation of differences in income distribution structures is outside the scope of this article.

This paper aims to identify the motivations for choosing all‐inclusive package tours when traveling, and to specify the visitor and travel attributes associated with those motivations.

A specific visitor‐exit‐survey involving all‐inclusive tourists visiting the Balearic Islands (n=843) was conducted during the summer of 2006 at the Airport of Palma de Mallorca. Then, through discrete choice models‐binary logit, relationships between the identified motivations and specified attributes were analyzed by looking for the attributes that are more associated with each motive.

The study results show that tourists traveling through all‐inclusive tours attach more importance to the motivations related to convenience and relaxation, economies of resources as well as safety and security in their vacationing processes; with specific tourist and trip attributes influencing the probability for confirmation.

Understanding the motivation of different tourist profiles visiting the destinations is useful in managing the tourism industry for satisfying specific tourist segments without jeopardizing the interests of the host community. A full understanding of all‐inclusive motivation would help travel organizers and marketers to plan, design and deliver products and services that cater for the specific needs of the all‐inclusive market, with the aim of capturing the financial benefits which are the central element of the economy.

There is still little knowledge in the literature about all‐inclusive package tourism. Specifically, the knowledge of tourist motivation with reference to the tour mode choice within the tourism landscape is still diluted, and therefore the motive behind one traveling through certain tour modes like all‐inclusives continues to miss the ground works. Nor have the factors that influence evaluation of the motivations related to the decision of this type of trip have been much studied, which renders this field of study one of the underdeveloped areas in the tourism social sciences. The paper attempts to contribute where there is this lack of knowledge.

Extant literature indicates the influence of anxiety on job insecurity (JI). However, the effect of financial anxiety (FA) on JI has received lesser attention. Further, there is a dearth of literature on this relationship during a global crisis, such as COVID-19, and more so in the Indian context. This study attempts to empirically explore the relationship between FA and JI in presence of moderators, such as gender, tenure and individual annual income.

Data were collected from 584 employees engaged in remote working in the information technology (IT) sector in India during the COVID-19 crisis. The data were analysed using SPSS 25 and AMOS 24. A hierarchical regression method was followed to test the hypothesis. In step 1, JI was regressed on FA in presence of control variables. In step 2, moderators, such as gender, tenure and individual annual income, were entered along with interaction terms.

Findings revealed a significant positive relation between FA and JI. The moderating effects of gender, tenure and annual income on the relationship between FA and JI were significant and interesting.

The paper empirically studies the role of FA on JI of Indian IT employees during COVID- 19. It is a response to researchers' call to integrate the effect of different moderators on the relationship between FA and JI during a crisis that has direct impacts on both. The influence of moderators on JI was interesting in the reversal effects produced.

The purpose of this paper is to pinpoint and analyse ethical issues raised by the dual role of artificial intelligence (AI) in relation to climate change, that is, AI as a contributor to climate change and AI as a contributor to fighting climate change.

This paper consists of three main parts. The first part provides a short background on AI and climate change respectively, followed by a presentation of empirical findings on the contribution of AI to climate change. The second part presents proposals by various AI researchers and commentators on how AI companies may contribute to fighting climate change by reducing greenhouse gas emissions from training and use of AI and by providing AI assistance to various mitigation and adaptation measures. The final part investigates ethical issues raised by some of the options presented in the second part.

AI applications may lead to substantial emissions but may also play an important role in mitigation and adaptation. Given this dual role of AI, ethical considerations by AI companies and governments are of vital importance.

This paper pinpoints practical ethical issues that AI companies and governments should take into account.

Given the potential impact of AI on society, it is vital that AI companies and governments take seriously the ethical issues raised by the dual role of AI in relation to climate change.

AI has been the subject of substantial ethical investigation, and even more so has climate change. However, the relationship between AI and climate change has received only limited attention from an ethical perspective. This paper provides such considerations.

The high frequency of disruption and dislocation of many industries, the migration to low-cost countries of different assets and activities, the increase in systemic risk, the birth of social and ecological constraints, as well as the new worldwide competitors require businesses and the overall society to change. In a so-called Industry 4.0. era, understanding the impact of artificial intelligence (AI) in developed as well as in underdeveloped economies has become increasingly crucial. The purpose of this study is to shed the light on the peculiarities of Chinese AI assessing the state of art of AI in this unique and valuable context.

Through a research based on a qualitative data analysis, the present paper suggests a new way to analyse AI and to support a better understanding of the local Chinese aspects influencing its development and implementation.

The development and implementation of AI in China required tailor solutions which account for the following three main dimensions: the location (i.e. territorial extension, the administrative boundaries); the government approach; and the human capital.

The analysis presents a broad level activity. In addition, the paper focused on Chinese scientific literature and different types of data (i.e. institutional documents, professional reports, websites and speeches in Chinese). The paper used a multi-faceted approach, including also the tacit knowledge of the authors about the context under investigation.