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Article
Publication date: 15 January 2019

Marcel Bastiaansen, Xander Dennis Lub, Ondrej Mitas, Timothy Hyungsoo Jung, Mário Passos Ascenção, Dai-In Han, Teemu Moilanen, Bert Smit and Wim Strijbosch

This paper aims to stimulate the discussion in the fields of hospitality, tourism and leisure on what exactly constitutes “an experience” and how to measure it; the authors unpack…

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Abstract

Purpose

This paper aims to stimulate the discussion in the fields of hospitality, tourism and leisure on what exactly constitutes “an experience” and how to measure it; the authors unpack the experience construct into its core constituent elements, namely, emotions.

Design/methodology/approach

The paper reviews insights from psychology and cognitive neuroscience that define experiences as a fine-grained temporal succession of emotions that occur during an experiential episode. Limitations of current methods for measuring experiences are discussed, after which biometric and neuroscientific methods are reviewed that are optimally geared toward measuring emotions, as they occur during an experience with fine temporal detail.

Findings

An overview is presented of the available studies within the fields of hospitality, tourism and leisure that use these methodologies. These studies show that using these methodologies provides a fruitful methodological approach to measuring experiences in real time.

Practical implications

Companies are constantly seeking to create memorable experiences for their customers. The proposed research methodologies allow companies to get a more fine-grained image of what impacts customers over the course of their experience and to actively integrate the use of emotions into creating experiences, as emotions are key to making them memorable.

Originality/value

The paper sketches the contours of a rapidly emerging framework that unpacks memorable experiences into their constituent element – emotions. It is proposed that this will contribute to a deeper understanding of how consumers experience offerings in the hospitality, tourism and leisure industry.

Details

International Journal of Contemporary Hospitality Management, vol. 31 no. 2
Type: Research Article
ISSN: 0959-6119

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Article
Publication date: 7 April 2015

Bert Smit and Roy C. Wood

– This paper aims to develop an understanding of the potential for application of facilities management concepts and principles in the context of the “zoo sector”.

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Abstract

Purpose

This paper aims to develop an understanding of the potential for application of facilities management concepts and principles in the context of the “zoo sector”.

Design/methodology/approach

The paper is a conceptual one and begins with a narrative designed to provide sufficient background to understanding key issues relevant to the practice of facilities management in zoological and similar institutions, including the implications of conservational/scientific and display imperatives of zoological facilities for facilities management. We then consider how these issues can be worked through in the context of four broad dimensions of facilities management: strategies for the management of stakeholder behaviour (non-human animals, personnel and visitors); building and environmental design (including space usage); safety, security and health; and “miscellaneous” services. The paper concludes by providing a provisional framework for further research into facilities management in the zoo sector.

Findings

As a conceptual paper, there are no empirical findings. Conceptually, the paper offers an initial and simple framework for interpreting the possible application of facilities management in zoological and related facilities.

Originality/value

In a search of the two principal journals in the field of facilities management, nothing could be found of direct relevance to the management of facilities in zoological and similar organizations. This paper is thus a singular contribution to the field. Conceptually, the authors attribute neglect of the topic to the distinctive traditions in the study of facilities management, which, at the risk of caricature, emphasise either the pre-eminence of a building and building services approach to facilities management, or an approach which is almost exclusively focused on the “human” dimensions to the discipline.

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Article
Publication date: 29 December 2022

Xiaoguang Tian, Robert Pavur, Henry Han and Lili Zhang

Studies on mining text and generating intelligence on human resource documents are rare. This research aims to use artificial intelligence and machine learning techniques to…

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Abstract

Purpose

Studies on mining text and generating intelligence on human resource documents are rare. This research aims to use artificial intelligence and machine learning techniques to facilitate the employee selection process through latent semantic analysis (LSA), bidirectional encoder representations from transformers (BERT) and support vector machines (SVM). The research also compares the performance of different machine learning, text vectorization and sampling approaches on the human resource (HR) resume data.

Design/methodology/approach

LSA and BERT are used to discover and understand the hidden patterns from a textual resume dataset, and SVM is applied to build the screening model and improve performance.

Findings

Based on the results of this study, LSA and BERT are proved useful in retrieving critical topics, and SVM can optimize the prediction model performance with the help of cross-validation and variable selection strategies.

Research limitations/implications

The technique and its empirical conclusions provide a practical, theoretical basis and reference for HR research.

Practical implications

The novel methods proposed in the study can assist HR practitioners in designing and improving their existing recruitment process. The topic detection techniques used in the study provide HR practitioners insights to identify the skill set of a particular recruiting position.

Originality/value

To the best of the authors’ knowledge, this research is the first study that uses LSA, BERT, SVM and other machine learning models in human resource management and resume classification. Compared with the existing machine learning-based resume screening system, the proposed system can provide more interpretable insights for HR professionals to understand the recommendation results through the topics extracted from the resumes. The findings of this study can also help organizations to find a better and effective approach for resume screening and evaluation.

Details

Business Process Management Journal, vol. 29 no. 1
Type: Research Article
ISSN: 1463-7154

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Article
Publication date: 7 December 2015

Jos M.A.F. Sanders, Marc A.W. Damen and Karen Van Dam

Based on the theory of planned behaviour and social learning theory, the purpose of this paper is to investigate the effect of training participation and learning experience on…

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Abstract

Purpose

Based on the theory of planned behaviour and social learning theory, the purpose of this paper is to investigate the effect of training participation and learning experience on the beliefs of low-educated employees about their self-efficacy for learning.

Design/methodology/approach

Low-educated workers of three different organizations (n=359) filled out a questionnaire at three different points in time, with a half-yearly interval. Regression analyses were used to establish the effects of training participation and learning experience on learning self-efficacy.

Findings

Training participation alone did not affect low-educated workers’ learning self-efficacy, but a positive learning experience did contribute to workers’ post-training learning self-efficacy. These results support the relevance of positive learning experiences.

Research limitations/implications

Follow-up studies could focus on the effects of learning self-efficacy for subsequent learning activities, establish which aspects of training contribute to a positive learning experience, and include contextual characteristics that may predict learning self-efficacy.

Practical implications

To stimulate learning among lower educated workers, it is necessary that they have confidence in their ability to successfully complete their training. Trainers and training developers working for this specific target group of lower educated workers should aim to provide training that is a positive experience, besides being a learning exercise.

Originality/value

The study is the first to analyse the longitudinal effects of training participation and learning experience on post-training learning self-efficacy among low-educated workers.

Details

Evidence-based HRM: a Global Forum for Empirical Scholarship, vol. 3 no. 3
Type: Research Article
ISSN: 2049-3983

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Book part
Publication date: 19 February 2019

Madeleine Lefebvre

Upcycling was introduced in The Archers by Fallon Rogers, who created a business from selling furniture she had upcycled. The author cites other examples from Archers episodes…

Abstract

Upcycling was introduced in The Archers by Fallon Rogers, who created a business from selling furniture she had upcycled. The author cites other examples from Archers episodes: Bert Fry’s egg mobile was originally an old caravan. Eddie Grundy built Lynda Snell’s shepherd’s hut from farmyard scrap. Josh Archer expanded his online farm equipment sales to include old items refurbished and sold for profit. Definitions of upcycling imply that the original item has become worthless. The author, however, includes examples of nostalgic value placed on relics of a bygone age and suggests a dichotomy between the values of older versus younger Ambridge residents. Upcycling can also be viewed in a metaphorical sense: Lilian Bellamy, for example, regularly upcycled herself with cosmetic assistance. The most sinister example is that of Rob Titchener, who used coercive control to upcycle Helen (then) Titchener into the image he wanted. The author concludes that while motives may take several forms, it is Fallon Rogers who consistently uses both creativity and business sense in her upcycling endeavours.

Details

Gender, Sex and Gossip in Ambridge
Type: Book
ISBN: 978-1-78769-948-9

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Article
Publication date: 9 June 2022

Fu-Chieh Hsu, Jing Liu and Hua Lin

Our knowledge of what emotions are elicited explicitly from food consumption and gastronomy experiences in the travel destination and how these emotions establish a relationship…

1583

Abstract

Purpose

Our knowledge of what emotions are elicited explicitly from food consumption and gastronomy experiences in the travel destination and how these emotions establish a relationship with tourists’ behavior is limited. Thus, this study aims to enrich the current knowledge in the gastronomy tourism field from the affective experience perspective and develop a scale to measure tourists’ affective gastronomy experiences (TAGES).

Design/methodology/approach

Both qualitative scale development and quantitative scale validation were conducted to ensure the psychometric properties of TAGES.

Findings

With the focus group’s contributions and experts’ validation, 12 gastronomy experience affects were identified in the first stage. In the second stage, a quantitative data collection involving 650 samples helped refine the scale. Finally, a reliable and valid scale with five items measuring TAGES was successfully developed.

Originality/value

This study provides a novel perspective by viewing tourists’ gastronomy experiences through an affective lens. Moreover, this study successfully provides evidence for the psychometric properties of the newly developed TAGES by systematically applying item response theory (IRT) and classical test theory (CTT). This study enriches the gastronomy tourism domain by developing the TAGES and presenting a rigorous and exhaustive investigation of its psychometric properties based on an integration of IRT and CTT. A valid and reliable scale that measures the TAGES fills the gastronomy literature gap and proposes an effective tool for future gastronomy experience studies.

Details

International Journal of Contemporary Hospitality Management, vol. 34 no. 9
Type: Research Article
ISSN: 0959-6119

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Article
Publication date: 1 June 2005

Li‐teh Sun

Man has been seeking an ideal existence for a very long time. In this existence, justice, love, and peace are no longer words, but actual experiences. How ever, with the American…

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Abstract

Man has been seeking an ideal existence for a very long time. In this existence, justice, love, and peace are no longer words, but actual experiences. How ever, with the American preemptive invasion and occupation of Afghanistan and Iraq and the subsequent prisoner abuse, such an existence seems to be farther and farther away from reality. The purpose of this work is to stop this dangerous trend by promoting justice, love, and peace through a change of the paradigm that is inconsistent with justice, love, and peace. The strong paradigm that created the strong nation like the U.S. and the strong man like George W. Bush have been the culprit, rather than the contributor, of the above three universal ideals. Thus, rather than justice, love, and peace, the strong paradigm resulted in in justice, hatred, and violence. In order to remove these three and related evils, what the world needs in the beginning of the third millenium is the weak paradigm. Through the acceptance of the latter paradigm, the golden mean or middle paradigm can be formulated, which is a synergy of the weak and the strong paradigm. In order to understand properly the meaning of these paradigms, however, some digression appears necessary.

Details

International Journal of Sociology and Social Policy, vol. 25 no. 6/7
Type: Research Article
ISSN: 0144-333X

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Article
Publication date: 29 May 2023

Jinxiang Zeng, Shujin Cao, Yijin Chen, Pei Pan and Yafang Cai

This study analyzed the interdisciplinary characteristics of Chinese research studies in library and information science (LIS) measured by knowledge elements extracted through the…

435

Abstract

Purpose

This study analyzed the interdisciplinary characteristics of Chinese research studies in library and information science (LIS) measured by knowledge elements extracted through the Lexicon-LSTM model.

Design/methodology/approach

Eight research themes were selected for experiment, with a large-scale (N = 11,625) dataset of research papers from the China National Knowledge Infrastructure (CNKI) database constructed. And it is complemented with multiple corpora. Knowledge elements were extracted through a Lexicon-LSTM model. A subject knowledge graph is constructed to support the searching and classification of knowledge elements. An interdisciplinary-weighted average citation index space was constructed for measuring the interdisciplinary characteristics and contributions based on knowledge elements.

Findings

The empirical research shows that the Lexicon-LSTM model has superiority in the accuracy of extracting knowledge elements. In the field of LIS, the interdisciplinary diversity indicator showed an upward trend from 2011 to 2021, while the disciplinary balance and difference indicators showed a downward trend. The knowledge elements of theory and methodology could be used to detect and measure the interdisciplinary characteristics and contributions.

Originality/value

The extraction of knowledge elements facilitates the discovery of semantic information embedded in academic papers. The knowledge elements were proved feasible for measuring the interdisciplinary characteristics and exploring the changes in the time sequence, which helps for overview the state of the arts and future development trend of the interdisciplinary of research theme in LIS.

Details

Aslib Journal of Information Management, vol. 75 no. 3
Type: Research Article
ISSN: 2050-3806

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Article
Publication date: 1 February 2022

Yaotan Xie and Fei Xiang

This study aimed to adapt existing text-mining techniques and propose a novel topic recognition approach for textual patient reviews.

193

Abstract

Purpose

This study aimed to adapt existing text-mining techniques and propose a novel topic recognition approach for textual patient reviews.

Design/methodology/approach

The authors first transformed multilabel samples for adapting model training forms. Then, an improved method was proposed based on dynamic mixed sampling and transfer learning to improve the learning problem caused by imbalanced samples. Specifically, the training of our model was based on the framework of a convolutional neural network and self-trained Word2Vector on large-scale corpora.

Findings

Compared with the SVM and other CNN-based models, the CNN+ DMS + TL model proposed in this study has made significant improvement in F1 score.

Originality/value

The improved methods based on dynamic mixed sampling and transfer learning can adequately manage the learning problem caused by the skewed distribution of samples and achieve the effective and automatic topic recognition of textual patient reviews.

Peer review

The peer-review history for this article is available at: https://publons.com/publon/10.1108/OIR-01-2021-0059.

Details

Online Information Review, vol. 46 no. 6
Type: Research Article
ISSN: 1468-4527

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Article
Publication date: 30 July 2024

Sheng-Qun Chen, Ting You and Jing-Lin Zhang

This study aims to enhance the classification and processing of online appeals by employing a deep-learning-based method. This method is designed to meet the requirements for…

18

Abstract

Purpose

This study aims to enhance the classification and processing of online appeals by employing a deep-learning-based method. This method is designed to meet the requirements for precise information categorization and decision support across various management departments.

Design/methodology/approach

This study leverages the ALBERT–TextCNN algorithm to determine the appropriate department for managing online appeals. ALBERT is selected for its advanced dynamic word representation capabilities, rooted in a multi-layer bidirectional transformer architecture and enriched text vector representation. TextCNN is integrated to facilitate the development of multi-label classification models.

Findings

Comparative experiments demonstrate the effectiveness of the proposed approach and its significant superiority over traditional classification methods in terms of accuracy.

Originality/value

The original contribution of this study lies in its utilization of the ALBERT–TextCNN algorithm for the classification of online appeals, resulting in a substantial improvement in accuracy. This research offers valuable insights for management departments, enabling enhanced understanding of public appeals and fostering more scientifically grounded and effective decision-making processes.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

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