Search results

In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in retail. However, extending activities through reality-mediation is still mostly believed to offer an inferior experience due to their shortcomings in usability, wearability, graphical fidelity, etc. This study aims to address the research gap by experimentally examining the acceptance of metaverse shopping.

This study conducts a 2 (VR: with vs. without) × 2 (AR: with vs. without) between-subjects laboratory experiment involving 157 participants in simulated daily shopping environments. This study builds a physical brick-and-mortar store at the campus and stocked it with approximately 600 products with accompanying product information and pricing. The XR devices and a 3D laser scanner were used in constructing the three XR shopping conditions.

Results indicate that XR can offer an experience comparable to, or even surpassing, traditional shopping in terms of its instrumental and hedonic aspects, regardless of a slightly reduced perception of usability. AR negatively affected perceived ease of use, while VR significantly increased perceived enjoyment. It is surprising that the lower perceived ease of use appeared to be disconnected from the attitude toward metaverse shopping.

This study provides important experimental evidence on the acceptance of XR shopping, and the finding that low perceived ease of use may not always be detrimental adds to the theory of technology adoption as a whole. Additionally, it provides an important reference point for future randomized controlled studies exploring the effects of technology on adoption.

This paper aims to introduce a model using a digital twin concept in a cold heading manufacturing and develop a digital visual management (VM) system using Lean overall equipment effectiveness (OEE) tool to enhance the process performance and establish Fourth Industrial Revolution (I4.0) platform in small and medium enterprises (SMEs).

This work utilised plan, do, check, act Lean methodology to create a digital twin of each machine in a smart manufacturing facility by taking the Lean tool OEE and digitally transforming it in the context of I4.0. To demonstrate the effectiveness of process digitisation, a case study was carried out at a manufacturing department to provide the data to the model and later validate synergy between Lean and I4.0 platform.

The OEE parameter can be increased by 10% using a proposed digital twin model with the introduction of a Level 0 into VM platform to clearly define the purpose of each data point gathered further replicate in projects across the value stream.

The findings suggest that researchers should look beyond conversion of stored data into visualisations and predictive analytics to improve the model connectivity. The development of strong big data analytics capabilities in SMEs can be achieved by shortening the time between data gathering and impact on the model performance.

The novelty of this study is the application of OEE Lean tool in the smart manufacturing sector to allow SME organisations to introduce digitalisation on the back of structured and streamlined principles with well-defined end goals to reach the optimal OEE.

Self-regulation is the level of learning where the learner becomes an active agent in their learning process in terms of activity and aspects of motivation and metacognition. The current paper mostly deals with the metacognitive aspect. The purpose of this study is to gain insight into self-regulation of learning in the context of modern technology in higher education. This study also aims to highlight the direction, tendencies and trends toward which self-regulation of learning is moving in relation to modern technologies.

The review study was compiled via searches in three databases: Scopus, Web of Science and ERIC. A filter was used to search for empirical studies solely in English, published over the past decade on the topics of self-regulation of learning and technology in higher education.

The findings clearly show a correlation between self-regulation of learning and modern technology, especially after a significant event such as the Covid-19 pandemic. However, in the wake of this change, the field of education has seen the emergence of methods and new platforms that can provide support for the development of self-regulated learning strategies.

The originality of the study lies in the fact that it focuses on the link between self-regulation of learning and modern technologies in higher education, including some predictions of the future direction of self-regulation of learning in this context.

This paper aims to critically examine the accounting and information systems literature to understand the changes that are occurring in the management accounting profession. The changes the authors are interested in are linked to technology-driven innovations in managerial decision-making and in organizational structures. In addition, the paper highlights research gaps and opportunities for future research.

The authors adopted a grounded theory literature review method (Wolfswinkel et al., 2013) to achieve the study’s aims.

The authors identified four research themes that describe the changes in the management accounting profession due to technology-driven innovations: structured vs unstructured data, human vs algorithm-driven decision-making, delineated vs blurred functional boundaries and hierarchical vs platform-based organizations. The authors also identified tensions mentioned in the literature for each research theme.

Previous studies display a rather narrow focus on the role of digital technologies in accounting work and new competences that management accountants require in the digital era. By contrast, the authors focus on the broader technology-driven shifts in organizational processes and structures, which vastly change how accounting information is collected, processed and analyzed internally to support managerial decision-making. Hence, the paper focuses on how management accountants can adapt and evolve as their organizations transition toward a digital environment.

This study aims to investigate the adoption of Quality 4.0 (Q4.0) and assess the critical failure factors (CFFs) for its implementation and how its failure is measured.

A qualitative study based on in-depth interviews with quality managers and executives was conducted to establish the CFFs for Q4.0.

The significant CFFs highlighted were resistance to change and a lack of understanding of the concept of Q4.0. There was also a complete lack of access to or availability of training around Q4.0.

The study enhances the body of literature on Q4.0 and is one of the first research studies to provide insight into the CFFs of Q4.0.

Based on the discussions with experts in the area of quality in various large and small organizations, one can understand the types of Q4.0 initiatives and the CFFs of Q4.0. By identifying the CFFs, one can establish the steps for improvements for organizations worldwide if they want to implement Q4.0 in the future on the competitive global stage.

The concept of Q4.0 is at the very nascent stage, and thus, the CFFs have not been found in the extant literature. As a result, the article aids businesses in understanding possible problems that might derail their Q4.0 activities.

The purpose of this paper is to develop a software-library in the R programming language that implements the concepts of the interpretive coordinate, interpretive axis and interpretive plane. This allows for the automatic and reliable interpretation of results from the multiple correspondence analysis (MCA) as previously proposed and published. Consequently, the users can seamlessly apply these concepts to their data, both via R commands and a corresponding graphical interface.

Within the context of this study, and through extensive literature review, the advantages of developing software using the Shiny library were examined. This library allows for the development of full-stack applications for R users without the need for knowledge of the corresponding technologies required for the development of complex applications. Additionally, the structural components of a Shiny application were presented, leading ultimately to the proposed software application.

Software utilizing the Shiny library enables nonexpert developers to rapidly develop specialized applications, either to present or to assist in the understanding of objects or concepts that are scientifically intriguing and complex. Specifically, with this proposed application, the users can promptly and effectively apply the scientific concepts addressed in this study to their data. Additionally, they can dynamically generate charts and reports that are readily available for download and sharing.

The proposed package is an implementation of the fundamental concepts of the exploratory MCA method. In the next step, discoveries from the geometric data analysis will be added as features to provide more comprehensive information to the users.

The practical implications of this work include the dissemination of the method’s use to a broader audience. Additionally, the decision to implement it with open-source code will result in the integration of the package’s functions by other third-party user packages.

The proposed software introduces the initial implementation of concepts such as interpretive coordination, the interpretive axis and the interpretive plane. This package aims to broaden and simplify the application of these concepts to benefit stakeholders in scientific research. The software can be accessed for free in a code repository, the link to which is provided in the full text of the study.

This study aims to critically review the research on food eco-labels to identify research gaps and recommend future research directions in business and management.

A hybrid integrated review combines bibliometric analysis with an in-depth framework-based study of theory–context–characteristics–methodology (TCCM) and reviews quality research published over 21 years between 2002 and 2022.

We identify key research themes and the knowledge structure of food eco-label research. Future researchers should explore food eco-label dynamics and phenomena in areas related to consumer behaviour, information, consumer knowledge, environmental concerns, trust, packaging and willingness-to-pay as antecedent factors.

This review contributes to the business and management literature by quantifying existing research and consolidating its evolution. The articles were sourced from the established Web of Science (WoS) database. Other databases should be included in future reviews. We also focus on research published in business and management. Further studies could include research beyond such specialised domains.

Consumers need more information on the objectives and meaning of food eco-labels. The dissemination of knowledge on eco-labels, as well as effective communication and information on eco-labels, are relevant to future research issues.

The knowledge derived from this research holds significant potential in shaping policies and devising tools aimed at reducing the carbon footprint linked to food production and consumption. Considering the substantial impact of these activities on our planet’s carbon footprint, addressing food security and sustainability emerges as a crucial concern for humanity. Recognising the importance of eco-label communication and information becomes particularly pertinent for future generations, who stand to bear the most substantial impact of climate change and sustainable development. These generations are also more inclined toward embracing and implementing sustainable practices.

There are no comprehensive, integrated reviews exploring the methods, variables and constructs used in studies on food eco-labels based on all articles published in WoS journals in the business and management domains. This is the first comprehensive literature review using a hybrid approach (bibliometric review with TCCM framework) in the field of food eco-label research.

本研究擬以批判性的態度,審閱過去有關食物生態標籤的研究,以能確認研究缺口,並於商業和管理的範疇裡,建議今後的研究方向。

這是一個混合綜合審閱研究。研究結合了文獻計量分析方法和理論 -背景 - 特徵 - 方法論 (TCCM) 框架; 研究人員審閱於2002年與2022年間二十一年裡出版的高水平學術研究。

我們確認了關於食物生態標籤的研究裡主要的研究主題和知識結構。研究人員和學者今後應致力關於消費行為、資訊、顧客知識、環境關注、信任、包裝和支付意願等議題的研究範疇,以能在這些範疇內,把食物生態標籤的變革動力和現象,作為是先前因素進行探索。

本研究確定了現存有關的研究的數量,並幫助鞏固了這類研究的發展,就此,對商業和管理文獻作出了貢獻。審閱的學術論文均來自被認可的 Web of Science 資料庫。今後的研究應涵蓋其它資料庫; 而且,我們的焦點是放在關於商業和管裡的文獻上; 研究人員和學者今後或許也應致力於其它研究範疇。

消費者需要更多關於食物生態標籤目標和意義的資訊; 因此,今後的研究須關注生態標籤知識的傳播,以及生態標籤的有效溝通和資訊。

根據於 Web of Science 出版、以及在商業和管理領域內的學術論文,似乎沒有全面的或綜合的審閱,去探索有關食物生態標籤研究內採用的研究方法、變數和構築。本研究為在食物生態標籤研究領域裡,首個使用混合方式 (結合文獻計量分析方法和理論 -背景 - 特徵 - 方法論 (TCCM) 框架)的全面文獻審閱。

This paper explores Lean Six Sigma principles and the DMAIC (define, measure, analyze, improve, control) methodology to propose a new Lean Six Sigma 4.0 (LSS 4.0) framework for employee occupational exams and address the real-world issue of high-variability exams that may arise.

This study uses mixed methods, combining qualitative and quantitative data collection. A detailed case study assesses the impact of LSS interventions on the exam management process and tests the applicability of the proposed LSS 4.0 framework for employee occupational exams.

The results reveal that changing the health service supplier in the explored organization caused a substantial raise in occupational exams, leading to increased costs. By using syntactic interoperability, lean, six sigma and DMAIC approaches, improvements were identified, addressing process deviations and information requirements. Implementing corrective actions improved the exam process, reducing the number of exams and associated expenses.

It is important to acknowledge certain limitations, such as the specific context of the case study and the exclusion of certain exam categories.

The practical implications of this research are substantial, providing organizations with valuable managerial insights into improving efficiency, reducing costs and ensuring regulatory compliance while managing occupational exams.

This study fills a research gap by applying LSS 4.0 to occupational exam management, offering a practical framework for organizations. It contributes to the existing knowledge base by addressing a relatively novel context and providing a detailed roadmap for process optimization.

A positive outlook on the impact of Industry 4.0 (I4.0) on sustainability prevails in the literature. However, some studies have highlighted potential areas of concern that have not yet been systematically addressed. The goal of this study is to challenge the assumption of a sustainable Fourth Industrial Revolution by (1) identifying the possible unintended negative impacts of I4.0 technologies on sustainability; (2) highlighting the underlying motivations and potential actions to mitigate such impacts; and (3) developing and evaluating alternative assumptions on the impacts of I4.0 technologies on sustainability.

Building on a problematization approach, a systematic literature review was conducted to develop potential alternative assumptions about the negative impacts of I4.0 on sustainability. Then, a Delphi study was carried out with 43 experts from academia and practice to evaluate the alternative assumptions. Two rounds of data collection were performed until reaching the convergence or stability of the responses.

The results highlight various unintended negative effects on environmental and social aspects that challenge the literature. The reasons behind the high/low probability of occurrence, the severity of each impact in the next five years and corrective actions are also identified. Unintended negative environmental effects are less controversial than social effects and are therefore more likely to generate widely accepted theoretical propositions. Finally, the alternative hypothesis ground is partially accepted by the panel, indicating that the problematization process has effectively opened up new perspectives for analysis.

This study is one of the few to systematically problematize the assumptions of the I4.0 and sustainability literature, generating research propositions that reveal several avenues for future research.

Both technological and human-centric perspectives need to be acknowledged when combining lean production practices and Industry 4.0 (I4.0) technologies. This study aims to explore and explain how lean production practices and I4.0 technologies may coexist to enhance the human-centric perspective of manufacturing operations in the era of Industry 5.0 (I5.0).

The research approach is an explorative and longitudinal case study. The qualitative data collection encompasses respondents from different job functions and organizational levels to cover the entire organization. In total, 18 interviews with 19 interviewees and five focus groups with a total of 25 participants are included.

Identified challenges bring forth that manufacturing organizations must have the ability to see beyond lean production philosophy and I4.0 to meet the demand for a human-centric perspective in socially sustainable manufacturing in the era of Industry 5.0.

The study suggests that while lean production practices and I4.0 practices may be considered separately, they need to be integrated as complementary approaches. This underscores the complexity of managing simultaneous organizational changes and new digital initiatives.

The research presented illuminates the elusive phenomena comprising the combined aspects of a human-centric perspective, specifically bringing forth implications for the co-existence of lean production practices and I4.0 technologies, in the transformation towards I5.0.

The study contributes to new avenues of research within the field of socially sustainable manufacturing. The study provides an in-depth analysis of the human-centric perspective when transforming organizations towards Industry 5.0.