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Open Access
Article
Publication date: 17 June 2020

Ursula Ploll and Tobias Stern

Vegetarian and vegan dietary practices have recently moved from being marginal activities to occupying a more mainstream position. While the reasons for this have been analysed by…

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Abstract

Purpose

Vegetarian and vegan dietary practices have recently moved from being marginal activities to occupying a more mainstream position. While the reasons for this have been analysed by many researchers, the extent to which the underlying motives may influence other behavioural contexts remains relatively unexplored. The present research thus analyses the degree to which vegetarians and vegans also act in an environmental and animal-conscious manner.

Design/methodology/approach

A self-administered survey was conducted among omnivores, conscientious omnivores, vegetarians and vegans in Austria. The research design is embedded in an extended version of the theory of planned behaviour (TPB). A mixed-mode sampling strategy resulted in 556 completed surveys.

Findings

The TPB correlation analysis shows that there are significant relations between dietary motives, subjective norms, attitudes, behavioural intentions and the behaviour in question. When considering all dietary groups, the results indicate that the differentiation in behaviour is impacted by dietary identity: the stricter the diet, the stronger the behaviour related to animal-wellbeing and environmental protection.

Originality/value

First, this research evaluated motivational drivers through a pairwise comparison, which resulted in strength factors instead of single motivational driver. Second and foremost, this research draws a connection between dietary categories and the wider behavioural implications related to these identities and their underlying motivational drivers.

Details

British Food Journal, vol. 122 no. 11
Type: Research Article
ISSN: 0007-070X

Keywords

Article
Publication date: 15 February 2009

Tobias Stern, Rainer Haas and Oliver Meixner

The aim of this paper is to investigate consumer attitudes to, and acceptance of, affective communication in the context of pre‐knowledge regarding wood‐based food additives.

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Abstract

Purpose

The aim of this paper is to investigate consumer attitudes to, and acceptance of, affective communication in the context of pre‐knowledge regarding wood‐based food additives.

Design/methodology/approach

A survey of 263 Austrian consumers was carried out to investigate pre‐knowledge, attitude and attitude change as a result of affective communication about wood‐based food additives.

Findings

About 14 per cent of the sample had pre‐knowledge concerning wood‐based food additives. In general the attitudes towards wood‐based additives were significantly better than those towards food additives in general. The results indicate a connection between pre‐knowledge and attitude. Respondents who had knowledge about wood‐based food additives evaluated them better, especially in contrast to those who had wrong ideas about them. Furthermore, it proved possible to improve the evaluations of those respondents who did not know about wood‐based additives by providing basic information.

Practical implications

The provision of additional information would improve the marketing potential of wood‐based additives, especially in contrast to additives in general. If the topic is ignored, there is a risk that public discussion could be based on non‐knowledge‐based conceptions by some consumers. The provision of early impact information is suggested in this regard.

Originality/value

Although the use of wood as a raw material in the food industry is common, it has not been a subject of public or scientific discussion to date.

Details

British Food Journal, vol. 111 no. 2
Type: Research Article
ISSN: 0007-070X

Keywords

Article
Publication date: 21 April 2022

Aruni Ghosh and Madhurima Deb

This study aims to propose a novel way to explore the narrative structure of advertisements, a nascent area of research, through the protagonist’s emotional arc progression.

Abstract

Purpose

This study aims to propose a novel way to explore the narrative structure of advertisements, a nascent area of research, through the protagonist’s emotional arc progression.

Design/methodology/approach

The multi-methods approach is used. In Study 1, the authors explore the basic universal emotional arcs through the analysis of narrative advertisements from six key economies. In Studies 2 and 3, the authors experimentally test hypotheses concerning the narrative structure and viewers’ attitudes toward the narrative using representative samples (317 and 193 ads, respectively).

Findings

The authors identify five broad emotional arcs of the protagonist in audiovisual advertisements. Different emotional arcs are found to induce different attitudes in the audience. Narratives ending in a positive mode and the narrative arcs with higher emotional shifts are more favorably evaluated by the audience.

Research limitations/implications

The present study is limited to textual stimuli tested in a US population and does not consider protagonist characteristic portrayal.

Practical implications

Understanding consumer preferences for different emotional arcs can help practitioners to develop more clutter-breaking and relevant advertisements.

Originality/value

To the best of the authors’ knowledge, this study is the first to explore the narrative structure theory in the context of advertisements using a positivist approach.

Details

European Journal of Marketing, vol. 56 no. 4
Type: Research Article
ISSN: 0309-0566

Keywords

Article
Publication date: 19 July 2023

Gaurav Kumar, Molla Ramizur Rahman, Abhinav Rajverma and Arun Kumar Misra

This study aims to analyse the systemic risk emitted by all publicly listed commercial banks in a key emerging economy, India.

Abstract

Purpose

This study aims to analyse the systemic risk emitted by all publicly listed commercial banks in a key emerging economy, India.

Design/methodology/approach

The study makes use of the Tobias and Brunnermeier (2016) estimator to quantify the systemic risk (ΔCoVaR) that banks contribute to the system. The methodology addresses a classification problem based on the probability that a particular bank will emit high systemic risk or moderate systemic risk. The study applies machine learning models such as logistic regression, random forest (RF), neural networks and gradient boosting machine (GBM) and addresses the issue of imbalanced data sets to investigate bank’s balance sheet features and bank’s stock features which may potentially determine the factors of systemic risk emission.

Findings

The study reports that across various performance matrices, the authors find that two specifications are preferred: RF and GBM. The study identifies lag of the estimator of systemic risk, stock beta, stock volatility and return on equity as important features to explain emission of systemic risk.

Practical implications

The findings will help banks and regulators with the key features that can be used to formulate the policy decisions.

Originality/value

This study contributes to the existing literature by suggesting classification algorithms that can be used to model the probability of systemic risk emission in a classification problem setting. Further, the study identifies the features responsible for the likelihood of systemic risk.

Details

Journal of Modelling in Management, vol. 19 no. 2
Type: Research Article
ISSN: 1746-5664

Keywords

Content available
1381

Abstract

Details

Journal of Property Investment & Finance, vol. 30 no. 4
Type: Research Article
ISSN: 1463-578X

Book part
Publication date: 21 February 2008

Mingliang Li and Justin L. Tobias

We describe a new Bayesian estimation algorithm for fitting a binary treatment, ordered outcome selection model in a potential outcomes framework. We show how recent advances in…

Abstract

We describe a new Bayesian estimation algorithm for fitting a binary treatment, ordered outcome selection model in a potential outcomes framework. We show how recent advances in simulation methods, namely data augmentation, the Gibbs sampler and the Metropolis-Hastings algorithm can be used to fit this model efficiently, and also introduce a reparameterization to help accelerate the convergence of our posterior simulator. Conventional “treatment effects” such as the Average Treatment Effect (ATE), the effect of treatment on the treated (TT) and the Local Average Treatment Effect (LATE) are adapted for this specific model, and Bayesian strategies for calculating these treatment effects are introduced. Finally, we review how one can potentially learn (or at least bound) the non-identified cross-regime correlation parameter and use this learning to calculate (or bound) parameters of interest beyond mean treatment effects.

Details

Modelling and Evaluating Treatment Effects in Econometrics
Type: Book
ISBN: 978-0-7623-1380-8

Content available
Book part
Publication date: 21 July 2016

Abstract

Details

Research in Organizational Change and Development
Type: Book
ISBN: 978-1-78635-360-3

Article
Publication date: 1 May 1959

D. Spector, H.S. Preiser† and D. Khoushy

During a two‐week voyage of the S.S. Israel from Haifa to New York, experiments were conducted with a platinum‐clad trailing anode system for cathodic protection. Preparation for…

Abstract

During a two‐week voyage of the S.S. Israel from Haifa to New York, experiments were conducted with a platinum‐clad trailing anode system for cathodic protection. Preparation for the voyage and day‐to‐day working of the experiments are described as are the successful efforts made to overcome the mechanical difficulties that arose. Concrete results that emerge indicate a growing and glowing future for such installations on large ships.

Details

Anti-Corrosion Methods and Materials, vol. 6 no. 5
Type: Research Article
ISSN: 0003-5599

Book part
Publication date: 24 April 2023

J. Isaac Miller

Transient climate sensitivity relates total climate forcings from anthropogenic and other sources to surface temperature. Global transient climate sensitivity is well studied, as…

Abstract

Transient climate sensitivity relates total climate forcings from anthropogenic and other sources to surface temperature. Global transient climate sensitivity is well studied, as are the related concepts of equilibrium climate sensitivity (ECS) and transient climate response (TCR), but spatially disaggregated local climate sensitivity (LCS) is less so. An energy balance model (EBM) and an easily implemented semiparametric statistical approach are proposed to estimate LCS using the historical record and to assess its contribution to global transient climate sensitivity. Results suggest that areas dominated by ocean tend to import energy, they are relatively more sensitive to forcings, but they warm more slowly than areas dominated by land. Economic implications are discussed.

Details

Essays in Honor of Joon Y. Park: Econometric Methodology in Empirical Applications
Type: Book
ISBN: 978-1-83753-212-4

Keywords

Article
Publication date: 21 September 2020

Frederik Kunze, Tobias Basse, Miguel Rodriguez Gonzalez and Günter Vornholz

In the current low-interest market environment, more and more asset managers have started to consider to invest in property markets. To implement adequate and forward-looking risk…

Abstract

Purpose

In the current low-interest market environment, more and more asset managers have started to consider to invest in property markets. To implement adequate and forward-looking risk management procedures, this market should be analyzed in more detail. Therefore, this study aims to examine the housing market data from the UK. More specifically, sentiment data and house prices are examined, using techniques of time-series econometrics suggested by Toda and Yamamoto (1995). The monthly data used in this study is the RICS Housing Market Survey and the Nationwide House Price Index – covering the period from January 2000 to December 2018. Furthermore, the authors also analyze the stability of the implemented Granger causality tests. In sum, the authors found clear empirical evidence for unidirectional Granger causality from sentiment indicator to the house prices index. Consequently, the sentiment indicator can help to forecast property prices in the UK.

Design/methodology/approach

By investigating sentiment data for house prices using techniques of time-series econometrics (more specifically the procedure suggested by Toda and Yamamoto, 1995), the research question whether sentiment indicators can be helpful to predict property prices in the UK is analyzed empirically.

Findings

The empirical results show that the RICS Housing Market Survey can help to predict the house prices in the UK.

Practical implications

Given these findings, the information provided by property market sentiment indicators certainly should be used in a forward-looking early warning system for house prices in the UK.

Originality/value

To authors’ knowledge, this is the first paper that uses the procedure suggested by Toda and Yamaoto to search for suitable early warning indicators for investors in UK real estate assets.

Details

The Journal of Risk Finance, vol. 21 no. 5
Type: Research Article
ISSN: 1526-5943

Keywords

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