Search results

In keeping with recent body image social trends, consumer demand for the adoption of plus-size models is increasing, although the use of thin models remains prevalent. The current study explores how consumers process information about fashion products displayed on different sizes of models in advertisements, focusing on model and consumer body sizes and both genders. As an underlying mechanism explaining how the relationship between model and consumer body sizes shapes consumer purchase intention, this study explores the role of guilt, shame and mental imagery.

The current study uses a text analytics technique to identify female consumers' general opinions of thin models in advertising. Employing a 3 (consumer body size: normal, overweight, obese) × 2 (model body size: thin, plus-size) × 2 (gender: male, female) between-subjects online experiment (n = 718), the main study comparatively analyzes the influences of plus-size and thin models on consumer responses.

The results reveal that, despite body positivity movements, thin models still generate negative emotions among female consumers. For obese female consumers, advertisements featuring plus-size models produce fewer negative emotions but not more mental imagery than advertisements featuring thin models. Conversely, for obese male consumers, advertisements featuring plus-size models generate more mental imagery but not more negative emotions than advertisements featuring thin models. The results also reveal that the relationship between consumer body size and guilt is moderated by perceived model size, which is also moderated by gender in generating mental imagery. While guilt plays a mediating role in enhancing mental imagery, resulting in purchase intention, shame does not take on this role.

This study is the first to present an integrated model that elucidates how consumers with varying body sizes respond to different sizes of models in advertising and how these responses impact purchase intentions.

Our findings only apply to contexts where consumers purchase fashion clothing in response to advertisements featuring thin versus plus-size models.

Exposing normal-size consumers to plus-size models generates less mental imagery, and thus, practitioners should seek to match the body sizes of the models featured in advertising to the body sizes of their target audience or ad campaigns that include both plus-size and thin models may help improve message persuasiveness in fashion advertising. Moreover, guilt-appeal advertising campaigns using thin models would appeal more to thin consumers of both genders than shame-appeal advertising.

This study aims to objectively synthesize the volume of accounting literature on financial statement fraud (FSF) using a systematic literature review research method (SLRRM). This paper analyzes the vast FSF literature based on inclusion and exclusion criteria. These criteria filter articles that are present in the accounting fraud domain and are published in peer-reviewed quality journals based on Australian Business Deans Council (ABDC) journal ranking. Lastly, a reverse search, analyzing the articles' abstracts, further narrows the search to 88 peer-reviewed articles. After examining these 88 articles, the results imply that the current literature is shifting from traditional statistical approaches towards computational methods, specifically machine learning (ML), for predicting and detecting FSF. This evolution of the literature is influenced by the impact of micro and macro variables on FSF and the inadequacy of audit procedures to detect red flags of fraud. The findings also concluded that A* peer-reviewed journals accepted articles that showed a complete picture of performance measures of computational techniques in their results. Therefore, this paper contributes to the literature by providing insights to researchers about why ML articles on fraud do not make it to top accounting journals and which computational techniques are the best algorithms for predicting and detecting FSF.

This paper chronicles the cluster of narratives surrounding the inadequacy of current accounting and auditing practices in preventing and detecting Financial Statement Fraud. The primary objective of this study is to objectively synthesize the volume of accounting literature on financial statement fraud. More specifically, this study will conduct a systematic literature review (SLR) to examine the evolution of financial statement fraud research and the emergence of new computational techniques to detect fraud in the accounting and finance literature.

The storyline of this study illustrates how the literature has evolved from conventional fraud detection mechanisms to computational techniques such as artificial intelligence (AI) and machine learning (ML). The findings also concluded that A* peer-reviewed journals accepted articles that showed a complete picture of performance measures of computational techniques in their results. Therefore, this paper contributes to the literature by providing insights to researchers about why ML articles on fraud do not make it to top accounting journals and which computational techniques are the best algorithms for predicting and detecting FSF.

This paper contributes to the literature by providing insights to researchers about why the evolution of accounting fraud literature from traditional statistical methods to machine learning algorithms in fraud detection and prediction.

The paper provides a detailed historical account of Douglass C. North's early intellectual contributions and analytical developments in pursuing a Grand Theory for why some countries are rich and others poor.

The author approaches the discussion using a theoretical and historical reconstruction based on published and unpublished materials.

The systematic, continuous and profound attempt to answer the Smithian social coordination problem shaped North's journey from being a young serious Marxist to becoming one of the founders of New Institutional Economics. In the process, he was converted in the early 1950s into a rigid neoclassical economist, being one of the leaders in promoting New Economic History. The success of the cliometric revolution exposed the frailties of the movement itself, namely, the limitations of neoclassical economic theory to explain economic growth and social change. Incorporating transaction costs, the institutional framework in which property rights and contracts are measured, defined and enforced assumes a prominent role in explaining economic performance.

In the early 1970s, North adopted a naive theory of institutions and property rights still grounded in neoclassical assumptions. Institutional and organizational analysis is modeled as a social maximizing efficient equilibrium outcome. However, the increasing tension between the neoclassical theoretical apparatus and its failure to account for contrasting political and institutional structures, diverging economic paths and social change propelled the modification of its assumptions and progressive conceptual innovation. In the later 1970s and early 1980s, North abandoned the efficiency view and gradually became more critical of the objective rationality postulate. In this intellectual movement, North's avant-garde research program contributed significantly to the creation of New Institutional Economics.

This study aims to develop a novel theoretical model for predicting the users’ intention to use virtual tools designed for construction risk evaluation. Risk evaluation is a vital objective for construction managers. This paper intends to examine critical factors such as potential benefits, motivation, performance expectancy and rich sources of information that may affect users’ intention to use virtual technology.

A pile training module (PTM) was developed in a virtual environment to analyze the proposed virtual reality-technology acceptance model (VR-TAM) factors. Further, a questionnaire survey was conducted with the participation of 102 construction professionals in China to validate the proposed VR-TAM model and PTM tool. The retrieved data was computed to test the proposed model by using partial least squares structural equation modeling and the significance of the PTM tool in a virtual environment.

The results of this study reveal that high-significance paths represent five relationships between crucial factors affecting users’ intention to use a selected virtual reality (VR) module. Five of seven hypothesis paths were significant with acceptable t-values. By quantitative measurement of high-significance paths, this research has found that each factor under VR-TAM has received significant loadings, with many above the 0.7 threshold mark and others around 0.6. The top factors include “motivation” and “benefits” and have multiplier effects on “intention to use” as the source factors.

The finding of this study presents crucial factors for VR adoption, and the proposed VR-TAM model contributes to the body of knowledge toward managing construction risk using pre-optimization and understanding in a virtual environment. This study supports Chinese construction company managers in effectively using VR technology in their construction projects for risk assessment and management.

This study offered the development of a novel VR-TAM integrated with risk assessment techniques for piling processes. Further, the developed model was analyzed by using a survey of Chinese construction professionals to collect perceptions about the modified theoretical model of VR-TAM.

Numerous attempts at installing six sigma (SS) have faced challenges and fallen short of the desired success. Thus, it becomes vital to identify the critical factors and characteristics that play a pivotal role in achieving successful adoption. In this study the research has aimed to highlight that a considerable number of corporate SS initiatives, around 60%, fail primarily due to the improper incorporation of essential elements and flawed assumptions.

To validate the influence of critical success factors (CSFs) on SS accomplishment, the study employed a research design combining exploratory and mixed-methods approaches. A Likert-scale questionnaire was utilized, and a simple random sampling method was employed to gather data. Out of the 2,325 potential participants approached, 573 responses were received, primarily from Germany, the United Kingdom and Sweden. The analysis focused on 260 completed questionnaires and statistical methods including structural equation modeling (SEM), exploratory factor analysis (EFA) and Confirmatory Factor Analysis (CFA) were utilized for data analysis.

The study acknowledged four essential components of CSFs that are imperative for sustaining the success of SS: (1) Competence of belt System employees; (2) Project management skills; (3) Organizational economic capability and (4) Leadership commitment and engagement. These factors were identified as significant contributors to the maintenance of SS’s success.

The practical implications of this research imply that institutions, practitioners, and researchers can utilize the four identified factors to foster the sustainable deployment of SS initiatives. By incorporating these factors, organizations can enhance the effectiveness and longevity of their SS practices.

The investigation's originality lies in its contribution to assessing CSFs in SS deployment within the European automobile industry, utilizing a mixed-methods research design supplemented by descriptive statistics.

This paper aims to explore the intention to adopt the Metaverse in Islamic banks, with a particular focus on evaluating perceived usefulness, ease of use, user satisfaction and the influence of religiosity. Integrating the technology adoption model (TAM) and religiosity intention model, this study will dissect the multidimensional aspects influencing the acceptance of Metaverse technologies.

Surveying Islamic bank professionals in Jordan, this study used a structured questionnaire and data augmentation to analyze Metaverse adoption factors. Using partial least squares-structural equation modeling, the relationships between ease of use, usefulness, religiosity and satisfaction were explored.

The study identifies pivotal relationships among perceived usefulness, ease of use, user satisfaction and religiosity in the context of adopting metaverse technologies in Islamic banks in Jordan. Evidence highlights the dominant role of perceived usefulness and ease in influencing both intention to use and satisfaction levels. Religiosity, while not a direct influencer, plays a collaborative role, underscoring a balanced mix of technological and religious elements that will potentially shape the adoption trajectory of metaverse technologies within this specific banking sector.

Integrating metaverse technologies in Islamic banks necessitates balancing technological advances with Sharia compliance. The study underscores the importance of aligning user experience with religious values and fostering innovation within Islamic ethical guidelines.

This study uniquely integrates the TAM and religiosity-intention model to explore metaverse adoption in Islamic banks, unveiling a nuanced interplay between technology and religious values. It offers practical insights for tailoring innovations in the Islamic financial ecosystem.

The increasing complexity of civil engineering projects necessitates focusing on new competencies of project participants. Based on the research on team performance and design processes that are more closely linked to the relevance of the project context, it is hypothesised that empathic abilities could play an important role in the performance of civil engineering projects. Therefore, this study aims to investigate whether performance can be improved by focusing on empathic abilities during the integrated design phase.

Semi-structured in-depth interviews with experts were conducted to explore the relevance of empathic abilities and their interaction with performance in a real-life infrastructure project. The project team’s empathy level was measured by means of a survey using Davis’ Interpersonal Reactivity Index method. Finally, differences between expected and measured levels of empathy were analysed.

The results provide insights into how empathic abilities interact with performance. The measurement indicates that, on average, professionals in the civil engineering industry score relatively low on empathy. In addition, differences were identified between the expected distribution and the measured empathy levels of the team, implying a potential for improvement, in particular by increasing the empathic abilities of the project management and increasing gender diversity.

To the best of the authors’ knowledge, this study is the first to investigate a relationship between empathy and the performance of civil engineering projects. The results provide initial insights into the empathic ability of civil engineering project teams and the potential of empathy to improve performance. Furthermore, from an empathy perspective, this study advocates increasing the gender diversity of project teams to improve performance.

This research examines the drivers of electric vehicle (EV) acceptance in the Kingdom of Saudi Arabia (KSA) by applying the unified theory of acceptance and use of technology (UTAUT) model, contextualized for the EV setting. The study aims to provide insights supporting the transition to sustainable transportation and identifying consumer perceptions and behavioral intentions toward EV adoption.

Based on survey data from a convenience sample collected from undergraduate and MBA students in a major university of KSA, the authors use seemingly unrelated regressions to provide novel insights on electric vehicle acceptance.

The study shows UTAUT constructs influence purchase intentions and attitudinal outcomes. Results indicate that perceived EV sustainability plays an important role in the relationship between UTAUT constructs and purchase intention alongside attitudes toward EV technology. Technological innovativeness enhances the impact of EV attitude and weakens the effect of perceived EV sustainability on purchase intention.

The study benefits researchers on sustainable technology acceptance and stakeholders facilitating sustainable transportation shifts. The insights guide the promotion of eco-friendly transportation solutions.

The research contextualizes and extends the UTAUT model constructs to understand drivers of EV acceptance. The study contributes to understanding sustainable innovation acceptance, considering the mediating role of perceptions of EV sustainability and the moderating role of technological innovativeness in driving purchase intentions.

This paper aims to analyze the adoption of social media platforms by tourists in Pakistan. Based on an adaptation of the technology acceptance model (TAM), this study assesses the factors that lead users to adopt these platforms.

A survey was administered to a convenience sample of 399 travelers who use social media in Pakistan. A Confirmatory factor analysis was conducted using AMOS to evaluate convergent and discriminant validity as well as composite reliability. Structural equation modeling was applied to examine the causal relationship among all proposed constructs.

The findings reveal that the perceived usefulness (PU) and perceived ease of use (PEoU) of a social media platform positively impact the behavioral intention of its users. The proposed constructs of compatibility, enjoyment, user expertise and e-trust all demonstrated their crucial roles in the adoption of a social media platform for tourism-related activities by enhancing the platform's PEoU and usefulness.

This research validates the relationship between PEoU and PU of a social media platform in the hospitality industry. Interestingly, this study has expanded TAM by validating the addition of four more constructs, (1) compatibility, (2) enjoyment, (3) e-trust, and (4) expertise, to add worth to this model regarding the understanding of social media usage in this specific industry. The findings are valuable both for managers and policymakers in the tourism sector in Pakistan, as the latter can utilize the results to entice a larger segment of social media users to the tourism industry.

This study attempts to examine the factors that influence user intention to adopt e-procurement in the Nigerian public sector.

A well-structured questionnaire was used to collect primary data from 278 procurement and information technology (IT) departments’ officials of key federal government ministries and agencies. The technology acceptance model (TAM) model was adopted and extended with security-related factors, namely perceived trust and perceived security. A partial least squares-structural equation modelling (PLS-SEM) approach was used to test and validate the model.

The results indicated that perceived usefulness is the best predictor of users’ intention to adopt e-procurement, followed by perceived security and perceived trust. In contrast, however, perceived ease of use was found to have a significant negative effect on the intention to adopt e-procurement.

This study is among the first in the Nigerian public sector context to evaluate users’ perceptions on e-procurement adoption with the use of a distinctive research model (TAM). The study's findings contribute to a better understanding of the factors influencing the adoption of e-procurement in the Nigerian public sector.