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This study aims to analyze why listed Taiwanese firms uniquely rejected the early adoption of International Financial Reporting Standards (IFRS) in 2012. It investigates the underlying decision-making processes behind this policy reluctance to further understand the continuous phenomenon of rare voluntary IFRS adoption.

It reports on fieldwork evidence obtained in situ by in-depth interviewing in Mandarin. It uses qualitative methods, complemented by quantitative cost-benefit metrics of IFRS adoption. It presents five diverse illustrative case-study vignettes, using a judgment sample based on expert opinion.

While the net-benefits of implementing IFRS varied across firms, this study’s unanimous finding was that no firms (in the sample or population) adopted IFRS early, despite stated intentions to the contrary. The key reasons for shunning early IFRS adoption were found to be frequent changes in regulations, insufficient benefits from adopting IFRS and the undermining of comparability across companies, compounded with scarce preparation time. Further, this study found that the Taiwanese accounting regulator’s reluctance toward IFRS adoption, partly caused by a long-standing US influence, contributed to this anomalous outcome.

This study recommends two critical policy changes: more realistic timelines and less frequent regulatory changes.

To the best of the authors’ knowledge, this is the first study to investigate the reasons behind the anomaly of no early adoption of IFRS in Taiwan, using new primary data and illustrative case studies. Its novelty lies in extending understanding beyond the existing quantitative literature on accounting standards, using new “thick” qualitative evidence on motives for such choices and decision-making processes, which have been neglected in previous work.

The study investigates the linkage between personality traits and firm performance. It examines the role of the pursuit of excellence, perseverance, a proactive mindset and formal education in determining the entrepreneurial success of MSMEs.

Data were collected from 432 MSME entrepreneurs using a structured questionnaire from India's two major industrial towns to analyze the impact of personality traits on firm performance. Structural equation modeling (SEM) was employed to assess the direct and indirect relationships with the help of mediation analysis.

The findings assert that personality traits improve firm performance and determine the success of MSMEs. The results reveal that the need for achievement, a proactive mindset and the pursuit of excellence are crucial to firm performance. In addition, formal education mediates between perseverance and the pursuit of excellence personality attributes on the one side and firm performance on the other.

The research has various theoretical and practical implications for entrepreneurs, financial institutions and policymakers. The results could be productively used to nurture the entrepreneurial ecosystem in India.

Although research on personality traits as a driver of firm performance is growing, the pursuit of excellence, perseverance and proactive mindset attributes as enablers of firm performance have not garnered much attention. The study presents a precise conceptual model by integrating the aforementioned dimensions in the backdrop of an emerging market.

The study aims to analyze the synergy of artificial intelligence (AI), with scientometrics, webometrics and bibliometrics to unlock and to emphasize the potential of the applications and benefits of AI algorithms in these fields.

By conducting a systematic literature review, our aim is to explore the potential of AI in revolutionizing the methods used to measure and analyze scholarly communication, identify emerging research trends and evaluate the impact of scientific publications. To achieve this, we implemented a comprehensive search strategy across reputable databases such as ProQuest, IEEE Explore, EBSCO, Web of Science and Scopus. Our search encompassed articles published from January 1, 2000, to September 2022, resulting in a thorough review of 61 relevant articles.

(1) Regarding scientometrics, the application of AI yields various distinct advantages, such as conducting analyses of publications, citations, research impact prediction, collaboration, research trend analysis and knowledge mapping, in a more objective and reliable framework. (2) In terms of webometrics, AI algorithms are able to enhance web crawling and data collection, web link analysis, web content analysis, social media analysis, web impact analysis and recommender systems. (3) Moreover, automation of data collection, analysis of citations, disambiguation of authors, analysis of co-authorship networks, assessment of research impact, text mining and recommender systems are considered as the potential of AI integration in the field of bibliometrics.

This study covers the particularly new benefits and potential of AI-enhanced scientometrics, webometrics and bibliometrics to highlight the significant prospects of the synergy of this integration through AI.

This study aims to explore the gendered nature of housing insecurity by investigating how gender affects women’s experience moving from transitional to market housing. By describing women’s pathways out of supportive or transitional housing support, the authors show how patriarchal forces in housing policies and practices affect women’s efforts to find secure housing. The authors argue that gender-neutral approaches to housing will fail to meet women’s needs.

This study explores the narratives from women accessing support services in Halifax, Canada. The first author conducted deep narrative interviews with women seeking to move from transition to market housing.

This research sheds light on the effects of gendered barriers to safe, suitable and affordable housing; how women’s experiences and expectations are shaped by these barriers; and, how housing-based supports must address the uniquely gendered experiences women face as they access market housing. In addition, this research reveals the importance of gender-responsive services that empower women facing a sexist housing market.

Little research has explored questions related to gender and housing among those seeking to move from transitional to marker housing, and existing research focuses on women’s housing insecurity as it relates to domestic violence. The sample of women included those having housing insecurity for a variety of reasons, including substance use and young motherhood.

Time of flight (ToF) imaging is a promising emerging technology for the purposes of crop identification. This paper aim to presents localization system for identifying and localizing asparagus in the field based on point clouds from ToF imaging. Since the semantics are not included in the point cloud, it contains the geometric information of other objects such as stones and weeds other than asparagus spears. An approach is required for extracting the spear information so that a robotic system can be used for harvesting.

A real-time convolutional neural network (CNN)-based method is used for filtering the point cloud generated by a ToF camera, allowing subsequent processing methods to operate over smaller and more information-dense data sets, resulting in reduced processing time. The segmented point cloud can then be split into clusters of points representing each individual spear. Geometric filters are developed to eliminate the non-asparagus points in each cluster so that each spear can be modelled and localized. The spear information can then be used for harvesting decisions.

The localization system is integrated into a robotic harvesting prototype system. Several field trials have been conducted with satisfactory performance. The identification of a spear from the point cloud is the key to successful localization. Segmentation and clustering points into individual spears are two major failures for future improvements.

Most crop localizations in agricultural robotic applications using ToF imaging technology are implemented in a very controlled environment, such as a greenhouse. The target crop and the robotic system are stationary during the localization process. The novel proposed method for asparagus localization has been tested in outdoor farms and integrated with a robotic harvesting platform. Asparagus detection and localization are achieved in real time on a continuously moving robotic platform in a cluttered and unstructured environment.

This study aims to examine how new regulation changes for the auditor’s report, so-called key audit matters (KAMs), influence tax avoidance.

This study uses data from firms listed on the Omani capital market over the period 2012–2019 and analyzes these data using pooled panel data regression with a robust standard error. It uses two common proxies for tax avoidance and two measures for the KAMs disclosure requirement.

This study finds a sharp decrease in the effective tax rate following the introduction of KAMs disclosure and the issuance of more KAMs in audit reports. This result is supported by several robustness checks. In an additional analysis, the authors observe interesting results, indicating that real earnings management mediates this association, while the audit committee plays a moderating role. The authors do not find a moderating effect of Big4 on this association, but find discrepancies within the Big4 firms in relation to this moderating effect.

The results of this study indicate that although the introduction of the KAMs disclosure requirement may have positive consequences, it may also lead to unintended negative consequences. This conclusion has not been comprehensively reported in literature.

This study aims to conceptualize and measure strategic leadership capabilities within research and development (R&D) teams pursuing high-tech innovation at public-funded R&D organizations in India.

A rigorous five-stage multi-method approach defines, conceptualizes and validates the core construct “strategic leadership capabilities for innovation” (SLCI). The first stage correlates the insights generated from theoretical analysis and expert opinions on the importance of leadership for innovation. The second study identifies a three-dimensional factor structure underlying the SLCI construct and the third validates it through a confirmatory factor analysis. Replication provides additional validation.

SLCI emerges as a three-dimensional construct with sub-dimensions: dynamic envisioning, ambidextrous resource utilization and empowering support for innovation.

Conceptualization of the SLCI construct and its measurement through a 15-item scale that has been empirically validated in the public-funded R&D organizations in India.

This study aims to explore the range of sustainability-related discourses by the stakeholders within a particular Finnish Higher Education Institution (HEI); interaction between the discourses and the context of the HEI; and the extent to which different understandings of sustainability cause challenges for the implementation of the university strategy for sustainability. Specifically, the paper explores how the employees within the HEI make sense of sustainability in their teaching, research and daily life and the extent to which sustainability-related discourses are aligned with the university strategy.

This research draws upon collected qualitative and quantitative data. It focuses on individual discourses by executives, teaching and research staff within an HEI regarding their understandings of sustainability and the Sustainable Development Goals (SDGs).

This paper illustrates the key challenges of sustainability and SDG implementation that may emerge in HEIs due to varied understandings. The results indicate a need for efficient HEI strategic vision communication and consideration of the stakeholders’ multiplicity of sustainability values.

This paper sheds light on the challenges involved in seeking to enhance sustainable development in an academic setting with multiple disciplines and categories of staff guided by academic freedom. The analysis thus advances the understanding of academic sustainability-related discourses and framings as well as mechanisms through which the implementation of sustainability-related efforts can be enhanced in such a context.

There is a growing interest in investigating craft beer tourism and consumption experiences as different destinations seek to position unique attributes and cultures in their culinary offerings. Yet, in this space, factors that have triggered the creation, management and marketing of craft beer tourism remain implicit. The purpose of this paper is therefore to present a systematic literature review of craft beer tourism, apply a conceptual model of craft beer gastronomy tourism and, in turn, provide strategic imperatives for the sector moving forward.

A comprehensive search for craft beer tourism in hospitality and tourism literature was undertaken using a combination of Google Scholar search terms as well as institutional library databases. Then, following the steps proposed by Xiao and Watson (2019), articles were sorted into themes before determining their appropriateness to be included in a systematic literature review.

Based on prior research, a Craft beer gastronomy tourism model is proposed. This model was found to provide a macro perspective of the craft beer tourism literature and was applied using the systematic literature review. It was found that not many of the papers fit the three-step process, and a fragmented relationship between craft breweries and tourism was observed. On reviewing the theories and frameworks used, it was found that there was not much consistency with the majority using frameworks and concepts. Furthermore, most studies were undertaken from the perspective of a single region or homogenous samples, with few offering cross-sectional comparisons. The most common methods of the papers were surveys and interviews, with a majority being cross-sectional.

The systematic literature review has led to the development of a novel conceptual model that highlights the current focal areas but also gaps that inform future studies and managerial implications.

Given the positive organizational principles associated with total quality management (TQM) – customer focus, continuous improvement, and process management – one would assume TQM's application is universally beneficial across businesses. Generally, research supports that notion. However, given resource limitations and shallow management teams in small businesses, there are multiple challenges in implementing TQM in small and medium-sized enterprises (SMEs). Therefore, small business leaders should benefit from knowledge linking other management practices to TQM’s positive effect on small firm performance, which enhances these leaders' return on TQM investment.

The authors apply partial least squares structural equation modeling (PLS-SEM) to explore TQM’s effect on small business performance and how other management practices enhance that relationship. Specifically, the authors explore how a comprehensive strategic approach (CSA) – a higher-order construct consisting of strategic planning, goal setting, and financial ratio analysis – moderates the relationship between TQM and small business performance. Given the complexity of the authors' model, the application of higher-order constructs, and the exploratory nature of this work, PLS-SEM is well suited for this study.

Consistent with prior research, the authors found that TQM (also a higher-order construct, consisting of seven lower-order constructs) positively impacts small firm performance. In addition, the authors found that CSA positively moderates the relationship between TQM and financial performance.

TQM’s effect on small business performance is enhanced when leaders implement a CSA. In other words, when small business leaders strategically plan, set goals, and analyze financial ratios, TQM's positive effect on firm performance is enhanced. This finding provides business leaders insights for how to maximize the TQM investment return.