scholarly journals Revealing industry challenge and business response to Covid-19: a text mining approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mu Yang ◽  
Chunjia Han
Keyword(s):  
Machine Learning ◽  
Design Methodology ◽  
Hospitality Industry ◽  
User Generated Content ◽  
Learning Approaches ◽  
Topic Modelling ◽  
Content Type ◽  
Business Response ◽  
First Time ◽  
Level Analysis

Purpose This study aims to conduct a “real-time” investigation with user-generated content on Twitter to reveal industry challenges and business responses to the coronavirus (Covid-19) pandemic. Specifically, using the hospitality industry as an example, the study analyses how Covid-19 has impacted the industry, what are the challenges and how the industry has responded. Design/methodology/approach With 94,340 tweets collected between October 2019 and May 2020 by a programmed Web scraper, unsupervised machine learning approaches such as structural topic modelling are applied. Originality/value This study contributes to the literature on business response during crises providing for the first time a study of using unstructured content on social media for industry-level analysis in the hospitality context.

An algorithm to elicitate ELECTRE II, III and IV parameters

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Brunno e Souza Rodrigues ◽  
Carla Martins Floriano ◽  
Valdecy Pereira ◽  
Marcos Costa Roboredo
Keyword(s):  
Machine Learning ◽  
Genetic Algorithm ◽  
Design Methodology ◽  
Content Type ◽  
Numerical Examples ◽  
Ensemble Technique ◽  
Robust Solutions ◽  
Ranking Trees ◽  
Final Rank ◽  
First Time

PurposeThis paper presents an algorithm that can elicitate all or any combination of parameters for the ELECTRE II, III or IV, methods. The algorithm takes some steps of a machine learning ensemble technique, the random forest, and for that, the authors named the approach as Ranking Trees Algorithm.Design/methodology/approachFirst, for a given method, the authors generate a set of ELECTRE models, where each model solves a random sample of criteria and actions (alternatives). Second, for each generated model, all actions are projected in a 1D space; in general, the best actions have higher values in a 1D space than the worst ones; therefore, they can be used to guide the genetic algorithm in the final step, the optimization phase. Finally, in the optimization phase, each model has its parameters optimized.FindingsThe results can be used in two different ways; the authors can merge all models, to find the elicitated parameters in this way, or the authors can ensemble the models, and the median of all ranks represents the final rank. The numerical examples achieved a Kendall Tau correlation rank over 0.85, and these results could perform as well as the results obtained by a group of specialists.Originality/valueFor the first time, the elicitation of ELECTRE parameters is made by an ensemble technique composed of a set of uncorrelated multicriteria models that can generate robust solutions.

Knowledge sharing, shared leadership and innovative behaviour: a cross-level analysis

2020 ◽  
Vol 41 (8) ◽  
pp. 1221-1233
Author(s):  
Rama Krishna Kishore Vandavasi ◽  
David C. McConville ◽  
Jin-Feng Uen ◽  
Prasanthi Yepuru
Keyword(s):  
Knowledge Sharing ◽  
Shared Leadership ◽  
Design Methodology ◽  
Hospitality Industry ◽  
Positive Impact ◽  
Hotel Industry ◽  
Content Type ◽  
Team Members ◽  
Innovative Behaviour ◽  
Level Analysis

PurposeThe purpose of this study is to investigate the effect of knowledge sharing among team members on the development of shared leadership and innovative behaviour.Design/methodology/approachData were collected from 64 management teams and 427 individuals working in 26 different hotels in the hospitality industry in Taiwan.FindingsThe results show that knowledge sharing has both direct and indirect effects on the development of shared leadership and individual innovative behaviour.Research limitations/implicationsResults suggest that knowledge sharing supports the occurrence of shared leadership, leading to an increase in innovative behaviour. The authors infer from the findings that encouraging a culture of knowledge sharing can have a positive impact on the creativity of teams.Originality/valueThis study advances knowledge of shared leadership as a mediator using a multilevel approach to test antecedents of innovative behaviour in the Taiwan hotel industry.

Interest rate option hedging portfolios without bank account

2019 ◽  
Vol 37 (1) ◽  
pp. 134-142
Author(s):  
Alberto Bueno-Guerrero
Keyword(s):  
Design Methodology ◽  
Contingent Claim ◽  
Necessary And Sufficient Condition ◽  
Barrier Option ◽  
Bank Account ◽  
Content Type ◽  
Option Hedging ◽  
Hedging Portfolio ◽  
Necessary And Sufficient ◽  
First Time

Purpose This paper aims to study the conditions for the hedging portfolio of any contingent claim on bonds to have no bank account part. Design/methodology/approach Hedging and Malliavin calculus techniques recently developed under a stochastic string framework are applied. Findings A necessary and sufficient condition for the hedging portfolio to have no bank account part is found. This condition is applied to a barrier option, and an example of a contingent claim whose hedging portfolio has a bank account part different from zero is provided. Originality/value To the best of the authors’ knowledge, this is the first time that this issue has been addressed in the literature.

scholarly journals Meta-analysis cum machine learning approaches address the structure and biogeochemical potential of marine copepod associated bacteriobiomes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Balamurugan Sadaiappan ◽  
Chinnamani PrasannaKumar ◽  
V. Uthara Nambiar ◽  
Mahendran Subramanian ◽  
Manguesh U. Gauns
Keyword(s):  
Machine Learning ◽  
Iron Transport ◽  
Meta Analysis ◽  
Zooplankton Community ◽  
Gradient Boosting ◽  
Learning Approaches ◽  
16S Rdna Gene ◽  
Marine Copepod ◽  
Form Of Life ◽  
First Time

AbstractCopepods are the dominant members of the zooplankton community and the most abundant form of life. It is imperative to obtain insights into the copepod-associated bacteriobiomes (CAB) in order to identify specific bacterial taxa associated within a copepod, and to understand how they vary between different copepods. Analysing the potential genes within the CAB may reveal their intrinsic role in biogeochemical cycles. For this, machine-learning models and PICRUSt2 analysis were deployed to analyse 16S rDNA gene sequences (approximately 16 million reads) of CAB belonging to five different copepod genera viz., Acartia spp., Calanus spp., Centropages sp., Pleuromamma spp., and Temora spp.. Overall, we predict 50 sub-OTUs (s-OTUs) (gradient boosting classifiers) to be important in five copepod genera. Among these, 15 s-OTUs were predicted to be important in Calanus spp. and 20 s-OTUs as important in Pleuromamma spp.. Four bacterial s-OTUs Acinetobacter johnsonii, Phaeobacter, Vibrio shilonii and Piscirickettsiaceae were identified as important s-OTUs in Calanus spp., and the s-OTUs Marinobacter, Alteromonas, Desulfovibrio, Limnobacter, Sphingomonas, Methyloversatilis, Enhydrobacter and Coriobacteriaceae were predicted as important s-OTUs in Pleuromamma spp., for the first time. Our meta-analysis revealed that the CAB of Pleuromamma spp. had a high proportion of potential genes responsible for methanogenesis and nitrogen fixation, whereas the CAB of Temora spp. had a high proportion of potential genes involved in assimilatory sulphate reduction, and cyanocobalamin synthesis. The CAB of Pleuromamma spp. and Temora spp. have potential genes accountable for iron transport.

The carmine dilemma: does the natural colourant preference outweigh nausea?

2018 ◽  
Vol 120 (8) ◽  
pp. 1915-1928
Author(s):  
Judith Müller-Maatsch ◽  
Johannes Jasny ◽  
Katharina Henn ◽  
Claudia Gras ◽  
Reinhold Carle
Keyword(s):  
Design Methodology ◽  
Consumer Perception ◽  
Natural Food ◽  
German Population ◽  
Misleading Information ◽  
Content Type ◽  
Broad Cross Section ◽  
First Time ◽  
Self Administered Questionnaire ◽  
Insight Into

Purpose The purpose of this paper is to provide insight into the consumers’ perception of natural and artificial food colourants. Furthermore, attitudes towards the application of carmine, being technically important and ubiquitously used to impart red shades, are assessed and analysed. Originating from insects, carmine is considered as natural but may arouse disgust. Design/methodology/approach In total, 625 individuals were surveyed using an online, self-administered questionnaire to represent a broad cross-section of the German population. Findings Independent of their origin, the application of colourants was rejected by 57.0 per cent of the interviewees. In total, 31.8 per cent of the participants stated a neutral attitude, while only 11.2 per cent expressed a positive notion. Most respondents preferred colourants from natural sources to artificial ones. While consumers perceive natural food colourants composed of genuine plant pigments positively, 61.6 per cent of respondents disliked the application of animal-derived colourants, 24.8 per cent of them did neither reject nor like it, and only 13.6 per cent of the interviewees stated a positive attitude towards them. The findings of this paper further indicate consumers’ preference for colourants to be either artificial or plant-derived rather than carmine. Food colourants are being rejected, possibly due to misleading information and confusing labelling. Consequently, information about carmine, including its origin and production, did not increase the aversion to products that are dyed with it, but increased their acceptance. Originality/value This study outlines consumer perception and attitudes towards food colourants. For the first time, the findings of this paper report the effect of revealing information about an additive, which initially aroused disgust, and its influence on consumer perception.

Feasibility study of automatically performing the concrete delivery dispatching through machine learning techniques

2015 ◽  
Vol 22 (5) ◽  
pp. 573-590 ◽  
Author(s):  
Mojtaba Maghrebi ◽  
Claude Sammut ◽  
S. Travis Waller
Keyword(s):  
Machine Learning ◽  
Human Resources ◽  
Design Methodology ◽  
Machine Learning Techniques ◽  
Mixing Process ◽  
Content Type ◽  
Practical Solution ◽  
Learning Techniques ◽  
Ready Mixed Concrete ◽  
Practical Implications

Purpose – The purpose of this paper is to study the implementation of machine learning (ML) techniques in order to automatically measure the feasibility of performing ready mixed concrete (RMC) dispatching jobs. Design/methodology/approach – Six ML techniques were selected and tested on data that was extracted from a developed simulation model and answered by a human expert. Findings – The results show that the performance of most of selected algorithms were the same and achieved an accuracy of around 80 per cent in terms of accuracy for the examined cases. Practical implications – This approach can be applied in practice to match experts’ decisions. Originality/value – In this paper the feasibility of handling complex concrete delivery problems by ML techniques is studied. Currently, most of the concrete mixing process is done by machines. However, RMC dispatching still relies on human resources to complete many tasks. In this paper the authors are addressing to reconstruct experts’ decisions as only practical solution.

A multi-manned assembly line balancing problem with classified teams: a new approach

2016 ◽  
Vol 36 (1) ◽  
pp. 51-59 ◽  
Author(s):  
Hamid Yilmaz ◽  
Mustafa Yilmaz
Keyword(s):  
Design Methodology ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Line Balancing ◽  
Test Problems ◽  
New Approach ◽  
Content Type ◽  
Line Test ◽  
Assembly Line Balancing Problem ◽  
First Time

Purpose – Within team-oriented approaches, tasks are assigned to teams before being assigned to workstations as a reality of industry. So it becomes clear, which workers assemble which tasks. Design/methodology/approach – Team numbers of the assembly line can increase with the number of tasks, but at the same time, due to physical situations of the stations, there will be limitations of maximum working team numbers in a station. For this purpose, heuristic assembly line balancing (ALB) procedure is used and mathematical model is developed for the problem. Findings – Well-known assembly line test problems widely used in the literature are solved to indicate the effectiveness and applicability of the proposed approach in practice. Originality/value – This paper draws attention to ALB problem in which workers have been assigned to teams in advance due to the need for specialized skills or equipment on the line for the first time.

European sources for advertising and marketing history

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jeannette Strickland
Keyword(s):  
Latin America ◽  
Design Methodology ◽  
Western Europe ◽  
Original Study ◽  
Eastern Bloc ◽  
Online Searching ◽  
Content Type ◽  
Marketing History ◽  
The World ◽  
First Time

Purpose This paper aims to build on Fred Beard’s study of the world’s archives to identity historical advertising and marketing ephemera, published in this journal in 2018, by focussing on resources available in Europe to augment his survey. Design/methodology/approach Online searching, supplemented by literature emanating from the business archive sector, led to the identification of 177 repositories or online sites in Europe holding advertising and marketing archives of significance for researchers. These are set out in two accompanying tables. Findings A wide diversity of European archives that are open to researchers is revealed in this paper. Many are the archives of the business themselves, but a number of collecting repositories are also listed, brought together for the first time. Research limitations/implications This paper focusses solely on Europe but does not claim to be comprehensive, as the study was time-limited and readers will, no doubt, know of resources that the author has missed. The findings relate mostly to Western Europe, so there is scope for further study to encompass archives in the former eastern bloc. Exploration of sources in Africa, Asia and Latin America would further supplement Beard’s original study. Originality/value This research brings together the broadest list of advertising and marketing sources open to researchers in Europe published to date. As Beard’s focus was more on the Americas, this examination redresses the balance with an array of European sources which, it is hoped, will contribute to the greater use of many little-known or under-researched resources by researchers across the world.

Forecasting the risk at infractions: an ensemble comparison of machine learning approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lei Li ◽  
Desheng Wu
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Short Term Memory ◽  
Model Performance ◽  
Large Data ◽  
Support Vector ◽  
Learning Approaches ◽  
Content Type ◽  
Day To Day Operations ◽  
Prediction Approach

PurposeThe infraction of securities regulations (ISRs) of listed firms in their day-to-day operations and management has become one of common problems. This paper proposed several machine learning approaches to forecast the risk at infractions of listed corporates to solve financial problems that are not effective and precise in supervision.Design/methodology/approachThe overall proposed research framework designed for forecasting the infractions (ISRs) include data collection and cleaning, feature engineering, data split, prediction approach application and model performance evaluation. We select Logistic Regression, Naïve Bayes, Random Forest, Support Vector Machines, Artificial Neural Network and Long Short-Term Memory Networks (LSTMs) as ISRs prediction models.FindingsThe research results show that prediction performance of proposed models with the prior infractions provides a significant improvement of the ISRs than those without prior, especially for large sample set. The results also indicate when judging whether a company has infractions, we should pay attention to novel artificial intelligence methods, previous infractions of the company, and large data sets.Originality/valueThe findings could be utilized to address the problems of identifying listed corporates' ISRs at hand to a certain degree. Overall, results elucidate the value of the prior infraction of securities regulations (ISRs). This shows the importance of including more data sources when constructing distress models and not only focus on building increasingly more complex models on the same data. This is also beneficial to the regulatory authorities.

“Never the first time on a patient”: the stakes of high-fidelity simulation for safety training

2018 ◽  
Vol 32 (5) ◽  
pp. 23-25 ◽  
Author(s):  
Lucie Cuvelier
Keyword(s):  
Case Studies ◽  
Design Methodology ◽  
Reading Time ◽  
Safety Training ◽  
High Fidelity ◽  
High Fidelity Simulation ◽  
Content Type ◽  
Pertinent Information ◽  
First Time ◽  
Practical Implications

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings An operative approach is described that is designed to structure the debriefing along three axes. Practical implications The paper provides strategic insights and practical thinking that have influenced some of the world’s leading organizations. Originality/value The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

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