Search results

Introduction: The rapid growth of high technology has urged many organisations to dynamically look for innovative ways, ideas, testing, and ingenious solution in improving their current product, process, system, and technology. For contemporary business, artificial intelligence (AI)-based people analytics is an instrument currently employed to develop a better prosperous future.

Purpose: The study aims to investigate the usage of AI in human resource management (HRM) practices. It also examines the benefits and challenges of using AI in implementing people analytics in organisations.

Methodology: This chapter contains a systemic review of articles and papers on analytics. The presented qualitative study did a literature review based on the articles published in the last five years and extracted from the Scopus database.

Findings: This chapter indicated that AI-based people analytics is on the verge of changing various aspects of HRM practices better to furnish it for a vibrant, ever-changing workplace. It concludes different usage of AI in people analytics for better managing human resources (HR) at the workplace. Also explored the benefits and challenges of implementing AI in the people analytics domain.

Implications: This chapter will help understand ongoing practices of AI-enabled process benefits and challenges. This insight will help develop a better AI-enabled function for a better decision-making system. The future scope of the study is how to overcome the challenges.

The cities, for the most part, appeared up until the middle of the 1990s to be islands within the larger Chinese political economy in which job-secure workers could be certain that their livelihood, health, education, and living abodes would evermore undergird their and their children's sustenance. At least until the late 1980s, urbanites who stuck with the state sector even considered good treatment on the job a kind of birthright, an entitlement that was sure to be enforced. In the cities, true, there had always been the disadvantaged after 1949 – those without offspring or spouses, the disabled, and people unable to support themselves. But this relatively tiny batch of individuals generally survived in the shadows and out of sight, subsisting – but just barely – as members of the “three withouts” on a mere pittance, in the form of meager “social relief” disbursed by civil affairs departments.⁸

In the last few decades, there has been growing interest in forecasting with computer intelligence, and both fuzzy time series (FTS) and artificial neural networks (ANNs) have gained particular popularity, among others. Rather than the conventional methods (e.g., econometrics), FTS and ANN are usually thought to be immune to fundamental concepts such as stationarity, theoretical causality, post-sample control, among others. On the other hand, a number of studies significantly indicated that these fundamental controls are required in terms of the theory of forecasting, and even application of such essential procedures substantially improves the forecasting accuracy. The aim of this paper is to fill the existing gap on modeling and forecasting in the FTS and ANN methods and figure out the fundamental concepts in a comprehensive work through merits and common failures in the literature. In addition to these merits, this paper may also be a guideline for eliminating unethical empirical settings in the forecasting studies.

Even more than 50 years after the Civil Rights Act of 1964 prohibited discrimination toward a number of groups in employment settings in the United States, workplace discrimination remains a persistent problem in organizations. This chapter provides a comprehensive review and analysis of contemporary theory and evidence on the nature, causes, and consequences of discrimination before synthesizing potential methods for its reduction. We note the strengths and weaknesses of this scholarship and highlight meaningful future directions. In so doing, we hope to both inform and inspire organizational and scholarly efforts to understand and eliminate workplace discrimination.

In this chapter, we will review the history, deregulation, policy reforms, and airline consolidations and mergers of the Chinese airline industry. The measurement of airline competition in China’s domestic market will also be discussed. Although air deregulation is still ongoing, the Chinese airline industry has become a market-driven business subject to some mild regulations. Then, we will review the impressive development of the high-speed rail (HSR) network in China and its effects on the domestic civil aviation market. In general, previous studies have found that the introduction of HSR services has a significant negative impact on airfare and air travel demand in China. The rapidly expanding network of HSR has important policy implications for Chinese airlines.

This chapter reviews three main issues in the interactions between air transport and high-speed rail (HSR) in China, namely the interaction between low-cost carriers (LCCs) and HSR, HSR speed effect on airlines, and airline–HSR integration. Studies on these three aspects of airline–HSR interactions have yet been well reviewed, and our chapter aims to fill in this gap. In this chapter, we comprehensively survey literature on the topics, especially studies on Chinese markets that have recently witnessed major HSR developments (and have planned further large-scale HSR expansion in the coming years). Our review shows that, first, compared to full-service carriers, LCCs face fiercer competition from HSR. However, the expansion of HSR network in China can be better coordinated with LCC development. Second, HSR speed exerts two countervailing effects on airline demand and price (the “travel-time” effect and “safety” effect, respectively). Specifically, an HSR speed reduction can have a positive effect on airlines due to longer HSR travel time, but a negative effect on airlines due to improved perception on HSR safety. Third, airline–HSR integration can be implemented through cooperation between airlines and HSR operators and through co-location of airports and HSR stations and can have important implications for intermodal transport and social welfare.

The five countries in Central Asia, namely Uzbekistan, Kazakhstan, Turkmenistan, Tajikistan, and Kyrgyzstan, are landlocked and therefore rely critically on aviation for passenger travel and express cargo logistics. However, despite substantial growth in the past decade, the aviation market in the region is still not realizing its full potential. This chapter reviews the development status of the international air travel market from Central Asia, with an aim of identifying the key barriers for industrial development and growth, and possible remedies to address these challenges. Overall, our study suggests that international market growth from the region is significantly influenced by historical patterns and political ties with Russia. Whereas markets linking selected countries such as Turkey and the UAE have experienced substantial growth, further liberalization is needed for the region to achieve better connectivity with major trade partners and aviation markets.

This chapter reviews the key results obtained in previous studies of airline mergers. It is found that the effect of mergers on airfares is dependent on the network configurations of merging airlines. Fare increases are frequently observed on overlapped routes. However, if the networks of two merging airlines are complementary, the expanded network after the merger leads to cost savings, increase in travel options, and improvement in service quality. Therefore, in a deregulated market, with few entry barriers, relaxing merger regulations is likely to improve welfare. However, most welfare evaluations do not incorporate quality changes or dynamic competition effects. Empirical investigations are primarily ex post analysis of mergers that have already passed antitrust reviews. The relationship between market concentration and welfare might be nonlinear and market specific. Therefore, airline mergers and alliances should be reviewed case by case. Methodological improvements are needed in future studies to control for the effects of complicating factors inherent in ex post evaluations.