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Some twenty five years ago Dr. A.H. Stuart established a private research laboratory for the investigation of certain industrial problems which were then being brought to his notice. These problems ranged over a wide area but in recent years those connected with lubrication have been much in evidence. Some of them have lead to an intensive study of the physical properties of graphite. In addition to a large number of private reports to engineering firms, he has published over 400 papers and articles on this work. Dr. Stuart has served on a number of research committees and panels of examiners and is the author of six books on applied mathematics. In the following article he discusses the value of colloidal graphite for lubrication at high temperatures and pressures, for running‐in new machinery and its application to resin‐bonded fabric bearings.

The friction characteristics of dry films formed on the surface of metals by natural or artificial means has been investigated in some detail, both in this country and in the U.S.A. for some years past. The work is of more than academic interest and has been stimulated by an ever increasing number of industrial problems which call for dry film lubrication in their solution.

This chapter is a contribution to the intellectual history of the anxiety that full employment in the modern United States depended somehow on military spending. This discourse (conveniently abbreviated as “military Keynesianism”) is vaguely familiar, but its contours and transit still await a full study. The chapter shows the origins of the idea in the left-Keynesian milieu centered around Harvard’s Alvin Hansen in the late 1930s, with a particular focus on the diverse group that cowrote the 1938 stagnationist manifesto An Economic Program for American Democracy. After a discussion of how these young economists participated in the World War II mobilization, the chapter considers how questions of stagnation and military stimulus were marginalized during the years of the high Cold War, only to be revived by younger radicals. At the same time, it demonstrates the existence of a community of discourse that directly links the Old Left of the 1930s and 1940s with the New Left of the 1960s and 1970s, and cuts across the division between left-wing social critique and liberal statecraft.

This essay is a review of the recent literature on the methodology of economics, with a focus on three broad trends that have defined the core lines of research within the discipline during the last two decades. These trends are: (a) the philosophical analysis of economic modelling and economic explanation; (b) the epistemology of causal inference, evidence diversity and evidence-based policy and (c) the investigation of the methodological underpinnings and public policy implications of behavioural economics. The final output is inevitably not exhaustive, yet it aims at offering a fair taste of some of the most representative questions in the field on which many philosophers, methodologists and social scientists have recently been placing a great deal of intellectual effort. The topics and references compiled in this review should serve at least as safe introductions to some of the central research questions in the philosophy and methodology of economics.

Introduction: Traditional recruitment system relied heavily on the applicants’ curriculum vitae (CV). This system, besides becoming redundant, has proved to be a futile exercise leading to the hiring of candidates that eventually turn out to be ‘misfits’. CVs were the only source of candidates’ data available for the recruiters a few years back. Face-to-face interviews was considered to be the ultimate solution for hiring suitable candidates. However, evidence suggests that interview scores and job performances do not complement each other. Advancement in artificial intelligence (AI) has introduced several techniques in the recruitment process.

Purpose: This chapter underscores the drawbacks of the traditional recruitment process. Evidence suggests that the traditional recruitment process is prone to subjectivity and is time-consuming. Surprisingly, despite the disadvantages, the integration of AI into the recruitment process is still slow. This chapter highlights the need to harness AI and the advantage technology could bring to the recruitment process. Some of the techniques that are garnering attention and widely used by organisations, such as chatbots, gamification, virtual employment interviews, and resume screening are described to enable the readers to understand with less effort. Chatbots and gamification techniques are described through process flow charts. We also describe the various types of interviews that could be conducted through virtual platforms and the modality by which the resume screening technique operates. Today, we are at a juncture wherein it is pertinent to acknowledge the superiority of technology-driven processes over traditional ones. This chapter will help the readers to understand the modus operandi to implement chatbots, gamification, virtual interviews and online resume screening techniques besides their advantages.

Scope: Although chatbots, resume screening, virtual interviews, and gamification are used in other areas, too, such as training and development, marketing, etc., in this chapter, we restrict solely to employee recruitment processes.

Methodology: Scoping review is used to examine the existing literature from various databases such as Google Scholar, IEEE, Proquest, Emerald, Elsevier, and JSTOR databases are used for extracting relevant articles.

Findings: Automation and analytics in recruitment and selection remove bias which is otherwise increasingly found in manual hiring processes. Also, previous studies have observed that candidates engage in impression management tactics in traditional face-to-face interviews. However, through automated recruitment processes, the influence of these tactics can be eliminated. AI-based virtual interviews reduce human bias. It also helps recruiters to hire talents across the globe. Gamification improves the candidate’s perception of the work and work environments. Through gamified techniques, the recruiters can understand whether a candidate possesses the required job skills. Chatbots are an interactive technique that can respond to interviewees’ queries. Resume screening techniques can save the recruiter’s time by screening and selecting the most appropriate candidates from a large pool. Hence, the chosen candidates alone can be referred to the next stage of the recruitment cycle. AI improves the efficiency of the recruitment process. It reduces mundane tasks. It saves time for the human resources (HR) team.

Strategic option generation is a fundamental step in strategy formulation. Several lenses have been proposed to explain its foundations, including the microeconomics positioning school, and the resource and capabilities based view of the firm. These approaches are largely based on inductive and deductive logics, which are not the logics that provide strategic options that are potentially novel, profitable, and largely differentiated from competitive offerings. In this chapter, we propose a unifying framework of the cognitive foundations of strategic option generation. Building on five fundamental cognitive acts – imitation, framing, analogical reasoning, abductive reasoning, and mental simulation, this proposed model both synthesizes the extant literature and provides guidance about promising avenues for future theoretical and empirical research.

Firms pursue a number of redeployment strategies in order to achieve growth and create value for their stakeholders. While the majority of previous research focuses on how firms create synergic value by sharing resources across multiple business units, we lack a systematic analysis of the determinants of different redeployment strategies. In this paper, we develop a theoretical framework that allows us to systematically investigate how intrinsic resource characteristics affect resource redeployment strategies. Our framework identifies four critical characteristics of resources, that is, fungibility, scale-free nature, decomposability, and tradability. We develop a number of predictions that provide guidance for researchers to identify the optimal resource redeployment strategy appropriate for resources with a certain set of characteristics.