Search results
1 – 10 of over 1000Majid Rahi, Ali Ebrahimnejad and Homayun Motameni
Taking into consideration the current human need for agricultural produce such as rice that requires water for growth, the optimal consumption of this valuable liquid is…
Abstract
Purpose
Taking into consideration the current human need for agricultural produce such as rice that requires water for growth, the optimal consumption of this valuable liquid is important. Unfortunately, the traditional use of water by humans for agricultural purposes contradicts the concept of optimal consumption. Therefore, designing and implementing a mechanized irrigation system is of the highest importance. This system includes hardware equipment such as liquid altimeter sensors, valves and pumps which have a failure phenomenon as an integral part, causing faults in the system. Naturally, these faults occur at probable time intervals, and the probability function with exponential distribution is used to simulate this interval. Thus, before the implementation of such high-cost systems, its evaluation is essential during the design phase.
Design/methodology/approach
The proposed approach included two main steps: offline and online. The offline phase included the simulation of the studied system (i.e. the irrigation system of paddy fields) and the acquisition of a data set for training machine learning algorithms such as decision trees to detect, locate (classification) and evaluate faults. In the online phase, C5.0 decision trees trained in the offline phase were used on a stream of data generated by the system.
Findings
The proposed approach is a comprehensive online component-oriented method, which is a combination of supervised machine learning methods to investigate system faults. Each of these methods is considered a component determined by the dimensions and complexity of the case study (to discover, classify and evaluate fault tolerance). These components are placed together in the form of a process framework so that the appropriate method for each component is obtained based on comparison with other machine learning methods. As a result, depending on the conditions under study, the most efficient method is selected in the components. Before the system implementation phase, its reliability is checked by evaluating the predicted faults (in the system design phase). Therefore, this approach avoids the construction of a high-risk system. Compared to existing methods, the proposed approach is more comprehensive and has greater flexibility.
Research limitations/implications
By expanding the dimensions of the problem, the model verification space grows exponentially using automata.
Originality/value
Unlike the existing methods that only examine one or two aspects of fault analysis such as fault detection, classification and fault-tolerance evaluation, this paper proposes a comprehensive process-oriented approach that investigates all three aspects of fault analysis concurrently.
Details
Keywords
Mike Tsionas and A. George Assaf
The purpose of this note is to describe the concept of regression trees (RTs) for hospitality data analysis.
Abstract
Purpose
The purpose of this note is to describe the concept of regression trees (RTs) for hospitality data analysis.
Design/methodology/approach
RT is an effective non-parametric predicting modelling approach that would free researchers from the need to force a certain functional form. The method does not require normalization or scaling of data.
Findings
The authors illustrate how RTs can be used to find a model that would result in the best prediction.
Research limitations/implications
A common challenge facing hospitality researchers is to estimate a regression model with the correct specification. RTs can help researchers identify the best explanatory model for prediction.
Originality/value
This paper describes the concept of RTs for the modelling of hospitality data.
Details
Keywords
Anna-Lena Weber, Brigitte Ruesink and Steven Gronau
This article aims to investigate the impact of (1) the establishment of a refugee settlement, (2) the energy demand of a host and refugee population, (3) the residence time of…
Abstract
Purpose
This article aims to investigate the impact of (1) the establishment of a refugee settlement, (2) the energy demand of a host and refugee population, (3) the residence time of refugees and (4) interventions in the energy sector on sustainable utilization of the forest.
Design/methodology/approach
Refugee movements from the Democratic Republic of Congo and settlement construction in a Zambian host society provide the setting. An agent-based model is developed. It uses survey data from 277 Zambian households, geographic information system coordinates and supplementary data inputs.
Findings
The future forest stock remains up to 30 years without an influx of refugees. Refugee developments completely deplete the forest over time. The settlement construction severely impacts the forest, while refugees' energy needs seem less significant. Compared with the repatriation of refugees, permanent integration has no influential impact on forest resources. Interventions in the energy sector through alternative sources slow down deforestation. Once a camp is constructed, tree cutting by hosts causes forest covers to decline even if alternative energy is provided.
Practical implications
The analysis is useful for comparable host–refugee settings and United Nations High Commissioner for Refugees interventions in settlement situations. Forest and energy sector interventions should involve host and refugee stakeholders.
Originality/value
This article adds value through an agent-based model in the Zambian deforestation–refugee context. The study has a pilot character within the United Nation's Comprehensive Refugee Response Framework. It fills a gap in long-term assessments of refugee presence in local host communities.
Details
Keywords
Valeriia Baklanova, Aleksei Kurkin and Tamara Teplova
The primary objective of this research is to provide a precise interpretation of the constructed machine learning model and produce definitive summaries that can evaluate the…
Abstract
Purpose
The primary objective of this research is to provide a precise interpretation of the constructed machine learning model and produce definitive summaries that can evaluate the influence of investor sentiment on the overall sales of non-fungible token (NFT) assets. To achieve this objective, the NFT hype index was constructed as well as several approaches of XAI were employed to interpret Black Box models and assess the magnitude and direction of the impact of the features used.
Design/methodology/approach
The research paper involved the construction of a sentiment index termed the NFT hype index, which aims to measure the influence of market actors within the NFT industry. This index was created by analyzing written content posted by 62 high-profile individuals and opinion leaders on the social media platform Twitter. The authors collected posts from the Twitter accounts that were afterward classified by tonality with a help of natural language processing model VADER. Then the machine learning methods and XAI approaches (feature importance, permutation importance and SHAP) were applied to explain the obtained results.
Findings
The built index was subjected to rigorous analysis using the gradient boosting regressor model and explainable AI techniques, which confirmed its significant explanatory power. Remarkably, the NFT hype index exhibited a higher degree of predictive accuracy compared to the well-known sentiment indices.
Practical implications
The NFT hype index, constructed from Twitter textual data, functions as an innovative, sentiment-based indicator for investment decision-making in the NFT market. It offers investors unique insights into the market sentiment that can be used alongside conventional financial analysis techniques to enhance risk management, portfolio optimization and overall investment outcomes within the rapidly evolving NFT ecosystem. Thus, the index plays a crucial role in facilitating well-informed, data-driven investment decisions and ensuring a competitive edge in the digital assets market.
Originality/value
The authors developed a novel index of investor interest for NFT assets (NFT hype index) based on text messages posted by market influencers and compared it to conventional sentiment indices in terms of their explanatory power. With the application of explainable AI, it was shown that sentiment indices may perform as significant predictors for NFT sales and that the NFT hype index works best among all sentiment indices considered.
Details
Keywords
Judit Gárdos, Julia Egyed-Gergely, Anna Horváth, Balázs Pataki, Roza Vajda and András Micsik
The present study is about generating metadata to enhance thematic transparency and facilitate research on interview collections at the Research Documentation Centre, Centre for…
Abstract
Purpose
The present study is about generating metadata to enhance thematic transparency and facilitate research on interview collections at the Research Documentation Centre, Centre for Social Sciences (TK KDK) in Budapest. It explores the use of artificial intelligence (AI) in producing, managing and processing social science data and its potential to generate useful metadata to describe the contents of such archives on a large scale.
Design/methodology/approach
The authors combined manual and automated/semi-automated methods of metadata development and curation. The authors developed a suitable domain-oriented taxonomy to classify a large text corpus of semi-structured interviews. To this end, the authors adapted the European Language Social Science Thesaurus (ELSST) to produce a concise, hierarchical structure of topics relevant in social sciences. The authors identified and tested the most promising natural language processing (NLP) tools supporting the Hungarian language. The results of manual and machine coding will be presented in a user interface.
Findings
The study describes how an international social scientific taxonomy can be adapted to a specific local setting and tailored to be used by automated NLP tools. The authors show the potential and limitations of existing and new NLP methods for thematic assignment. The current possibilities of multi-label classification in social scientific metadata assignment are discussed, i.e. the problem of automated selection of relevant labels from a large pool.
Originality/value
Interview materials have not yet been used for building manually annotated training datasets for automated indexing of scientifically relevant topics in a data repository. Comparing various automated-indexing methods, this study shows a possible implementation of a researcher tool supporting custom visualizations and the faceted search of interview collections.
Details
Keywords
Torgrim Sneve Guttormsen, Joar Skrede, Paloma Guzman, Kalliopi Fouseki, Chiara Bonacchi and Ana Pastor Pérez
The paper explores the potential value of urban assemblage theory as a conceptual framework for understanding the role heritage has in social sustainable urban placemaking. The…
Abstract
Purpose
The paper explores the potential value of urban assemblage theory as a conceptual framework for understanding the role heritage has in social sustainable urban placemaking. The authors conceptualise urban placemaking as a dynamic and complex social assemblage. Heritage is one of the many dimensions of such a complex and dynamic urban assembly. Based on the approach to urban assemblage theory, the authors aim to uncover how postindustrial city-making unfolds. When approaching the case studies, the authors ask the following: Whose city for which citizens are visible through the selected case studies? How is social sustainability achieved through heritage in urban placemaking?
Design/methodology/approach
The main research material is derived from theoretical literature and the testing of an assemblage methodological approach through three Norwegian urban regeneration case studies where heritage partake in urban placemaking. The three case studies are the Tukthus wall (what is left of an 19th century old prison), the Vulkan neighbourhood (an 19th century industrial working area) and Sørengkaia (an 19th century industrial harbour area) in Oslo, Norway. The three case studies are representing urban regeneration projects which are common worldwide, and not at least in a European context.
Findings
The paper reveals the dynamic factors and processes at play in urban placemaking, which has its own distinct character by the uses of heritage in each of the case study areas. Placemaking could produce “closed” systems which are stable in accordance with its original functions, or they could be “open” systems affected by the various drivers of change. The paper shows how these forces are depending on two sets of binary forces at play in urban placemaking: forces of “assemblages” co-creating a place versus destabilising forces of “disassembly” which is redefining the place as a process affected by reassembled placemaking.
Research limitations/implications
For research, the authors focus on the implications this paper has for the field of urban heritage studies as it provides a useful framework to capture the dynamic complexity of urban heritage areas.
Practical implications
For practice, the authors state that the paper can provide a useful platform for dialogue and critical thinking on strategies being planned.
Social implications
For society, the paper promotes the significance in terms of fostering an inclusive way of thinking and planning for urban heritage futures.
Originality/value
The paper outlines dynamics of urban regeneration through heritage which are significant for understanding urban transformation as value for offering practical solutions to social problems in urban planning. The assemblage methodological approach (1) makes awareness of the dynamic processes at play in urban placemaking and makes the ground for mapping issue at stake in urban placemaking; (2) becomes a source for modelling urban regeneration through heritage by defining a conceptual framework of dynamic interactions in urban placemaking; and (3) defines a critically reflexive tool for evaluating good versus bad (heritage-led) urban development projects.
Details
Keywords
Nirma Sadamali Jayawardena, Sara Quach, Chinmoy Bandyopadhyay and Park Thaichon
This study examined the differential effects of printed advertisements with luxury and nonluxury brands on consumer brand attitude persuasion using a qualitative experimental…
Abstract
Purpose
This study examined the differential effects of printed advertisements with luxury and nonluxury brands on consumer brand attitude persuasion using a qualitative experimental approach.
Design/methodology/approach
The authors adopted a qualitative experimental approach and the authors conducted two experiments over six months. In the first experiment, participants were asked to view five print advertisements related to five different luxury brands. In the second experiment, the same participants were asked to view another five print advertisements on non-luxury brands. The qualitative thematic differences for each brand were analyzed using NVivo software, employing the theoretical assumptions of Petty and Cacioppo's (1981) elaboration likelihood model (ELM).
Findings
In experiments 1 and 2, it was identified that brand experience, personalized brand experience, product quality, product quantity, personal image-conscious, nonpersonal image-conscious, affordability and unaffordability as the main thematic findings leading to consumer attitude persuasion.
Practical implications
The two main contributions are as follows: theoretically, applying a social psychology theory to the advertising industry offers an understanding of the social cognition stages of a human mindset. As a practical implication, this study's findings guide advertising agencies, marketers and salespeople regarding how to design effective print advertisements in a way that persuades consumer attitudes.
Originality/value
Through the theoretical assumptions of Petty and Cacioppo's (1981) ELM, this paper can be considered one of the first studies to combine social psychology and advertising to investigate the differential effects on consumer brand attitude persuasion for luxury and nonluxury brands.
Details
Keywords
Nirma Sadamali Jayawardena, Mitchell Ross, Sara Quach and Debra Grace
The purpose of this study is to investigate visual comprehension in memory for 360-degree video advertisements amongst adolescents under single and repeated viewing conditions.
Abstract
Purpose
The purpose of this study is to investigate visual comprehension in memory for 360-degree video advertisements amongst adolescents under single and repeated viewing conditions.
Design/methodology/approach
This study explored visual comprehension in memory for 360-degree video advertisements using the theoretical assumptions of the social psychology theory of social information processing by Wyer (2003). The authors conducted two experiments over a timeline of three months. In the first experiment, participants watched the 360-degree video advertisement once, and after one week, the same set of participants watched the same advertisement again. The theoretical assumptions in the comprehension unit were used to design the experiments and to explore visual comprehension in memory for 360-degree video advertisements. The data were collected using surveys and interviews through an experimental research design approach. NVivo software was used to analyse the data.
Findings
This study found that while female participants were able to comprehend colours in the visuals better, male participants were better able to comprehend facial expressions presented in the visuals. Further, both female and male participants were able to comprehend locations within the advertisement visuals. It was found that participants understood the plot or the story of the advertisement better after the second viewing than after the first viewing.
Practical implications
The two main contributions from this study are as follows: from a theoretical perspective, the application of a social psychology theory for the advertising sector enables us to gather more insights about the social cognition stages of a human mindset such as information retrieval, judgement, decision making, goal stimulation and short- and long-term memory. In doing so, this study not only explored adolescents' visual comprehension memory of 360-degree video advertisements, but it also contributed to the theory of social information processing by Wyer (2003) by exploring consumer visual comprehension memory. From a practical perspective, the findings of this study provide a solid foundation for future advertising firms or agencies, marketers, and salespeople on how to design effective advertisements using 360-degree video versions in a way that appeals to consumer visual memory.
Originality/value
This paper can be considered as amongst the first studies which combine social psychology with advertising to investigate visual comprehension memory for 360-degree video advertisements amongst adolescents.
Details
Keywords
Anna Young-Ferris, Arunima Malik, Victoria Calderbank and Jubin Jacob-John
Avoided emissions refer to greenhouse gas emission reductions that are a result of using a product or are emission removals due to a decision or an action. Although there is no…
Abstract
Purpose
Avoided emissions refer to greenhouse gas emission reductions that are a result of using a product or are emission removals due to a decision or an action. Although there is no uniform standard for calculating avoided emissions, market actors have started referring to avoided emissions as “Scope 4” emissions. By default, making a claim about Scope 4 emissions gives an appearance that this Scope of emissions is a natural extension of the existing and accepted Scope-based emissions accounting framework. The purpose of this study is to explore the implications of this assumed legitimacy.
Design/methodology/approach
Via a desktop review and interviews, we analyse extant Scope 4 company reporting, associated accounting methodologies and the practical implications of Scope 4 claims.
Findings
Upon examination of Scope 4 emissions and their relationship with Scopes 1, 2 and 3 emissions, we highlight a dynamic and interdependent relationship between quantification, commensuration and standardization in emissions accounting. We find that extant Scope 4 assessments do not fit the established framework for Scope-based emissions accounting. In line with literature on the territorializing nature of accounting, we call for caution about Scope 4 claims that are a distraction from the critical work of reducing absolute emissions.
Originality/value
We examine the implications of assumed alignment and borrowed legitimacy of Scope 4 with Scope-based accounting because Scope 4 is not an actual Scope, but a claim to a Scope. This is as an act of accounting territorialization.
Details