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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.

Depending on an experimental approach to find optimal parameters for producing fully dense (relative density > 99%) Inconel 718 (IN718) components in the selective laser melting (SLM) process is expensive and offers no guarantee of success. Accordingly, this study aims to propose a multi-scale simulation framework to guide the choice of processing parameters in a more pragmatic manner.

In the proposed approach, a powder layer, ray tracing and heat transfer simulation models are used to calculate the melt pool dimensions and evaporation volume corresponding to a small number of laser power and scanning speed conditions within the input design space. A layer-heating model is then used to determine the inter-layer idle time required to maximize the temperature convergence rate of the solidified layer beneath the power bed. The simulation results are used to train surrogate models to construct SLM process maps for 3,600 pairs of the laser power and scanning speed within the input design space given three different values of the underlying solidified layer temperature (i.e., 353 K, 673 K and 873 K). The ideal selection of laser power and scanning speed of each process map is chosen based on four quality-related criteria listed as follows: without the appearance of key-hole melting; an evaporation volume less than the volume of the d90 powder particles; ensuring the stability of single scan tracks; and avoiding a weak contact between the melt pool and substrate. Finally, the optimal laser power and scanning speed parameters for the SLM process are determined by superimposing the optimal regions of the individual process maps.

The feasibility of the proposed approach is demonstrated by fabricating IN718 test specimens using the optimal processing conditions identified by the simulation framework. It is shown that the maximum density of the fabricated parts is 99.94%, while the average density is 99.88% and the standard deviation is less than 0.05%.

The present study proposed a multi-scale simulation model which can efficiently predict the optimal processing conditions for producing fully dense components in the SLM process. If the geometry of the three-dimensional printed part is changed or the machine and powder material is altered, users can use the proposed method for predicting the processing conditions that can produce the high-density part.

Managing differences is a difficult undertaking, especially considering the difficulties arising from the unconscious functions of our brains. Organisations should strive to counteract the potentially harmful effects of unconscious bias by implementing policies that support bias-aware management and decision-making. Although it is obvious that bias cannot be completely eliminated, there is enough data, as discussed in this work, to demonstrate that unconscious bias and stereotypes can be addressed and decreased with mindfulness-based interventions (MBIs) to some extent. Mindfulness involves the process of bringing non-judgemental awareness to experience by striving for full attention in the present moment. In this context, including mindfulness practises into training programmes for equality, diversity, and inclusion may serve as an accelerator for recognising hidden biases, reducing stereotypes, eliminating discrimination, and encouraging cognitive changes. This chapter explains the ways in which MBIs can be used to promote cognitive changes and comprehend the automatic and unconscious nature of emotions and thoughts in order to remove barriers between all differences in the workplace.

Virtual reality (VR) is becoming a more available technology including in public spaces like libraries. The value and role of VR as a tool for learning and social engagement are unclear. The purpose of this paper is to explore the ways in which library patrons and librarians perceive VR and experience VR through library drop-in programs.

This paper is based on research conducted in seven Washington State Libraries where VR was adopted for drop-in programming for the first time. Data was collected between March and June 2018 and involved interviews with librarians and patrons, a patron user experience survey, and observational field notes from researchers on site during library programs.

Findings are presented in relation to user perceptions of VR compared to their actual VR experiences, and in relation to informal learning and social engagements. The authors frame the analysis and discussion in relation to sociotechnical imaginaries – culturally situated ideas about the relationship between society and technology, and considering the larger cultural landscape that informs collective views about the present and future.

The paper discusses pending and potential inequalities related to gender, race and class in conversation with technology industry and VR. Issues discussed include unequal access to technology in public libraries and representation of minoritized groups in VR.

This work takes a critical perspective considering the inequities in relation to mainstreaming VR through public spaces like libraries.

The aim of this chapter is to define and explore the group of emotions known as self-conscious emotions. The state of the knowledge on guilt, shame, pride, and embarrassment is reviewed, with particular attention paid to research on these four self-conscious emotions in work and organizational settings. Surprisingly little research on self-conscious emotions comes from researchers interested in occupational stress and well-being, yet these emotions are commonly experienced and may be a reaction to or even a source of stress. They may also impact behaviors and attitudes that affect stress and well-being. I conclude the review with a call for more research on these emotions as related to stress and well-being, offering some suggestions for areas of focus.

This study presents a framework to estimate throughput and cost of additive manufacturing (AM) as related to process parameters, material thermodynamic properties and machine specifications. Taking a 3D model of the part design as input, the model uses a parametrization of the rate-limiting physics of the AM build process – herein focusing on laser powder bed fusion (LPBF) and scaling of LPBF melt pool geometry – to estimate part- and material-specific build time. From this estimate, per-part cost is calculated using a quantity-dependent activity-based production model.

Analysis tools that assess how design variables and process parameters influence production cost increase our understanding of the economics of AM, thereby supporting its practical adoption. To this aim, our framework produces a representative scaling among process parameters, build rate and production cost.

For exemplary alloys and LPBF system specifications, predictions reveal the underlying tradeoff between production cost and machine capability, and look beyond the capability of currently commercially available equipment. As a proxy for build quality, the number of times each point in the build is re-melted is derived analytically as a function of process parameters, showcasing the tradeoff between print quality due to increased melting cycles, and throughput.

Typical cost models for AM only assess single operating points and are not coupled to models of the representative rate-limiting process physics. The present analysis of LPBF elucidates this important coupling, revealing tradeoffs between equipment capability and production cost, and looking beyond the limits of current commercially available equipment.

Discusses an ongoing programme, the overall purpose of which is to develop an integrated set of stochastic simulation models of firms in the textile, apparel and retail industries. The models are to be used primarily for research, education and industrial problem solving in the areas of plant and company operations with emphasis on Quick Response (QR) methodologies driven by Point‐of‐Sale (POS) data. A second objective is that of developing interactive management information systems using high‐level decision‐surface models (simulation metamodels) of expected system performance as a function of key input parameters.

Purpose – The purpose of this chapter is to explore homicide trends in Trinidad and Tobago, to describe the factors that impact the risk for homicide perpetration and victimization, and to discuss the effectiveness of strategies implemented by law enforcement agencies to prosecute homicide cases.

Design/methodology/approach – The chapter employs a detailed review of relevant literature to explore homicide trends and the strategies instituted to investigate and prosecute this criminal offense.

Findings – Our findings suggest that homicide victimization and perpetration is concentrated among young men of African descent, who reside in underprivileged communities with a high population density. Gang violence prompted by a narco-drug economy, coupled with gun violence, accentuates the risk of homicide perpetration and victimization. As homicide rates remained high, law enforcement officials in Trinidad and Tobago were ill equipped to investigate and make arrests in these offenses.

Originality/value – This chapter adds to the literature on homicide in Trinidad and Tobago by (1) showing that geographic and demographic factors structure homicide victimization and (2) exploring how the political economy of drugs in the Caribbean contributes to murder.