Search results

The paper explores the notion of worker voice in terms of its implications for supply chain justice. The paper proposes the value of the recognition perspective on social justice for framing workers’ experiences in global supply chains and identifies opportunities for the advancement of the worker voice agenda with recognition justice in mind.

The paper adopts a conceptual approach to explore the notion of worker voice in supply chains in terms of the recognition perspective on social justice.

Sustainable supply chain management (SSCM) scholarship has considered worker voice in terms of two key paradigms, which we term communication and representation. To address recognition justice for workers in global supply chains, the worker voice agenda must consider designing worker voice mechanisms to close recognition gaps for workers with marginalised identities; the shared responsibilities of supply chain actors to listen alongside the expectation of workers to use their voice; and the expansion of the concept of worker voice to cut across home-work boundaries.

The paper offers conceptual clarity on the emerging notion of worker voice in SSCM and is the first to interrogate the implications of recognition justice for the emergent worker voice agenda. It articulates key opportunities for future research to further operationalise worker voice upon a recognition foundation.

A real potential exists for library use of voice technologies: as aids to the disabled or illiterate library user, as front‐ends for general library help systems, in online systems for commands or control words, and in many of the hands‐busy‐eyes‐busy activities that are common in libraries. Initially, these applications would be small, limited processes that would not require the more fluent human‐machine communication that we might hope for in the future. Voice technologies will depend on and benefit from new computer systems, advances in artificial intelligence and expert systems to facilitate their use and enable them to better circumvent present input and output problems. These voice systems will gradually assume more importance, improving access to information and complementing existing systems, but they will not likely revolutionize or dominate human‐machine communications or library services in the near future.

Healthcare professionals are key in healthcare organisations but are subject to long working hours and may have to make complex life-and-death decisions. As frontline agents dealing with human lives, giving them a voice is paramount. This study explores the impact of employee voice (assessed based on employee perceptions on how much they are consulted and how much influence they have on task-related decisions) on health professionals' work engagement and burnout when mediated by relational outcomes (perceived organisational support, workplace trust, workplace recognition and meaningful work).

A sample of 3,266 health professionals retrieved from the European Working Condition Survey was used. The quantitative analysis was performed using the partial least square structural equation modelling and multiple regression analyses.

The results indicate that employee voice has a direct positive impact on work engagement, but employee voice's direct effects on burnout still need to be confirmed. Relational outcomes are found to mediate the relationship between employee voice and burnout (decreasing it) and between employee voice and work engagement (increasing it).

Practices of employee voice in the workplace are fundamental to promoting health professionals' well-being. Trust, recognition, support and the feeling of doing meaningful work increase the influence of employee voice, especially in reducing the levels of burnout.

This is the first study that assesses, at a European level, the importance that ‘giving health professionals a voice' has on crucial employee outcomes: work engagement, burnout and relational outcomes.

Purpose: The purpose of this chapter is to review and critically evaluate robots, artificial intelligence and service automation (RAISA) applications in the restaurant industry to educate professors, graduate students, and industry professionals.

Design/methodology/approach: This chapter is a survey of applications of RAISA in restaurants. The chapter is based on the review of professional and peer-reviewed academic literature, and the industry insight section was prepared based on a 50-minute interview with Mr. Juan Higueros, Chief Operations Officer of Bear Robotics.

Findings: Various case studies presented in this chapter illustrate numerous possibilities for automation: from automating a specific function to complete automation of the front of the house (e.g., Eatsa) or back of the house (e.g., Spyce robotic kitchen). The restaurant industry has already adopted chatbots; voice-activated and biometric technologies; robots as hosts, food runners, chefs, and bartenders; tableside ordering; conveyors; and robotic food delivery.

Practical implications: The chapter presents professors and students with a detailed overview of RAISA in the restaurant industry that will be useful for educational and research purposes. Restaurant owners and managers may also benefit from reading this chapter as they will learn about the current state of technology and opportunities for RAISA implementation.

Originality/value: To the best of the authors’ knowledge, this chapter presents the first systematic and in-depth review of RAISA technologies in the restaurant industry.

Voice as the communications device for computer—human interaction is not a new concept, having been a favorite of the SF writers for many years. It is the most immediate and natural means of communication, and is in use today as voice response or voice recognition systems for human—computer interfaces in business, industry and medicine. This article examines the potential for their use within the library environment, as an additional tool for computer input or output.

Increased demands on catalogers to increase productivity, while maintaining quality and accuracy, can be difficult to meet, and may even be hazardous to their health. OCLC Passport for Windows (PFW) and CatME provide some ability to create macros and shortcuts to speed cataloging activities, but do not solve the problems created by long work sessions. Voice recognition software, which works with most applications, is an effective way to input commands and data accurately into a computer. The software can be customized to provide single word input of complex commands, allowing the cataloger to concentrate more on the content of their records, rather than the input. This type of software is helpful not only to workers with repetitive strain injury (RSI) or physical disabilities, but also to anyone requiring accurate input during extended work sessions. This article explains how the software works, offers examples, and provides tips on working with using voice recognition.

This paper describes the development process of a mobile Voice User Interface (VUI) for Korean users with dysarthria with currently available speech recognition technology by conducting systematic user needs analysis and applying usability testing feedback to prototype system designs.

Four usability surveys are conducted for the development of the prototype system. According to the two surveys on user needs and user experiences with existing VUI systems at the stage of the prototype design, the target platforms, and target applications are determined. Furthermore, a set of basic words is selected by the prospective users, which enables the system to be not only custom designed for dysarthric speakers but also individualized for each user. Reflecting the requests relating to general usage of the VUI and the UI design preference of users through evaluation of the initial prototype, we develop the final prototype, which is an individualized voice keyboard for mobile devices based on an isolated word recognition engine with word prediction.

The results of this paper show that target user participation in system development is effective for improving usability and satisfaction of the system, as the system is developed considering various ideas and feedback obtained in each development stage from different prospective users.

We have developed an automatic speech recognition-based mobile VUI system not only custom designed for dysarthric speakers but also individualized for each user, focussing on the usability aspect through four usability surveys. This voice keyboard system has the potential to be an assistive and alternative input method for people with speech impairment, including mild to moderate dysarthria, and people with physical disabilities.

This paper assesses the ability of the minimally verbal child with autism to recognise their own voice. The rationale for this study rests in recent advances in technology aimed at making the voice of speech generating devices (SGDs) sound more like the child using them (van Santen and Black, 2009). The purpose of this paper is to investigate the child’s ability to actually recognise the sound of their own voice in a series of short experiments using computer-based methodology.

Using a voice-face matching computerised paradigm, the performance of 33 children with autism was compared to that of 27 children with developmental delay (DD), and 33 typically developing (TD) children. The children were matched for verbal and non-verbal ability and a training period was conducted prior to the main test to ensure children’s understanding of what was expected of them.

The findings of this study suggest that the child with autism recognise the sound of their own voice at test, but with much greater difficulty than age-and-ability matched comparison groups. The implications of this finding are useful for researchers in the field of speech mimicry technology and manufacturers of SGD software packages. The paper also provides empirical insights about how the child with autism may process voice in their everyday social interactions.

Some limitations to this study exist, for instance, there were only a small number of presentations involving self-voice in this task. This may have over simplified the process for the young TD children and the children with DD. Nevertheless, it is striking that despite being matched for non-verbal mental age, the children with autism performed significantly less well than either of the other two groups of children. However, future studies would benefit from adjusting the number of presentations of voice and face accordingly. It is also important to note that for some children with autism the simultaneous presentation of faces and voices may act more as an interference effect (Cook and Wilding, 1997; Joassin et al., 2004) than a facilitation effect (Molholm et al., 2002). Future studies may wish to test a subgroup on voice recognition without the aid of visual prompts.

The paper includes implications for the type of voice children with autism may prefer to use when communicating via a SGD. The authors suggest that if the child does not recognise or prefer the sound of their own natural voice on such devices, partial or complete abandonment of the SGD may occur.

This paper fulfils an identified need to research how children’s abilities and preferences can be taken into account at the point of decision making for particular communication tools.

As voice search has progressively become a new way of information acquisition and human–computer interaction, this paper aims to explore the users' voice search behavior in human–vehicle interaction.

This study employed mixed research methods, including questionnaires and interviews. A total of 151 Amazon MTurk volunteers were recruited to complete a questionnaire based on their most recent and impressive voice search experience. After the questionnaire, this paper conducted an online interview with the participants.

This paper studied users' voice search behavior characteristics in the context of the human–vehicle interaction and analyzed the voice search content, search need, search motivation and user satisfaction. In addition, this paper studied the barriers and suggestions for voice search in human–vehicle interaction through a content analysis of the interviews.

This paper's analysis of users' barriers and suggestions has a specific reference value for optimizing the voice search interaction system and improving the service.

This study is exploratory research that seeks to identify users' voice search needs and tasks and investigate voice search satisfaction in human–vehicle interaction context.

The purpose of this paper is to identify and analyse the difficulties encountered in the implementation of a voice picking system at a large multinational company of the tractor industrial segment, outlining a comparison related to the main critical factors concerning the system implementation at a Brazilian and a USA plant.

The methodology utilised was qualitative and exploratory conducted through case studies in the two plants of the multinational company. The main data were collected through interviews with key managers directly involved in the project of voice picking system implementation.

The results indicate that the picking processes in the two plants were similar, since both were designed for the production line and conducted using bar-code readers and paper lists. Nevertheless, the internal warehousing process in the USA was more mature and computerised, whereas the Brazilian process still had opportunity for improvement, such as, the visual storage process, where the operator was responsible for locating an empty position.

Since this research is an exploratory case study, its results cannot be generalised.

The paper provides relevant practical information and experiences to managers interested in implementing voice picking systems, as well as interested in improving the accuracy and productivity of logistics processes within warehouses.

The voice picking systems are more widespread in the USA than in Brazil, and therefore, companies around the world can use this studied case to better understand about the voice picking systems implementation process in both emerging and mature marketplaces.