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Blockchain is a disruptive technology that has matured to deliver robust, global, IT systems, yet adoption lags predictions. The authors explore barriers to adoption in the context of a global challenge with multiple stakeholders: integration of carbon markets. Going beyond the dominant economic-rationalistic paradigm of information system (IS) innovation adoption, the authors reduce pro-innovation bias and broaden inter-organizational scope by using technological frames theory to capture the cognitive framing of the challenges perceived within the world’s largest carbon emitter: China.

Semi-structured interviews with 15 key experts representing three communities in China’s carbon markets: IT experts in carbon markets; carbon market experts with conceptual knowledge of blockchain and carbon market experts with practical blockchain experience.

Perceived technical challenges were found to be the least significant in explaining adoption. Significant challenges in five areas: social, political legal and policy (PLP), data, organizational and managerial (OM) and economic, with PLP and OM given most weight. Mapping to frames developed to encompass these challenges: nature of technology, strategic use of technology and technology readiness resolved frame incongruence that, in the case explored, did not lead to rejection of blockchain, but a decision to defer investment, increase the scope of analysis and delay the adoption decision.

Increases scope and resolution of IS adoption research. Technological frames theory moves from predominant economic-rational models to a social cognitive perspective. Broadens understanding of blockchain adoption in a context combining the world’s most carbon emissions with ownership of most blockchain patents, detailing socio-technical challenges and delivering practical guidance for policymakers and practitioners.

The purpose of this paper is to give compiled information on previously applied cotton fabric surface modifications. The paper covered most of the modifications done on cotton fabric to improve its properties or to add some functional properties. The paper presented mostly studied research works that brought a significant surface improvement on cotton fabric.

Different previous works on surface modifications of cotton fabrics such as pilling, wrinkle and microbial resistance, hydrophobicity, cationization, flame retardancy and UV-protection characteristics were studied and their methods of modification including the main findings are well reported in this paper.

Several modification treatments on surface modification of cotton fabrics indicated an improvement in the desired properties in which the modification is needed. For instance, the pilling tendency, wrinkling, microbial degradation and UV degradation drawbacks of cotton fabric can be overcome through different modification techniques.

To the best of the author’s knowledge, there are no compressive documents that covered all the portions presented in this review. The author tried to cover the surface modifications done to improve the main properties of cotton fabric.

This study aims to develop a scale using item response theory (IRT) to assess the entrepreneurial potential for digital transformation in Brazilian companies.

IRT was used to develop a scale for entrepreneurial potential in digital transformation. This scale was constructed from a questionnaire, covering the domains: (1) data-driven culture, (2) openness to knowledge and adaptation to change, (3) connectivity and (4) creativity and innovation. The questionnaire was administered to a sample of 216 entrepreneurs from small business enterprise (SBE) and startups in Brazil.

A questionnaire was developed and validated to assess the latent trait of entrepreneurial potential within the context of digital transformation. Additionally, a three-level scale of entrepreneurial potential was established: low (level I), intermediate (level II) and high (level III). The interpretation of this scale provides valuable information on which domains, such as data-driven culture, innovation, among others, can be enhanced to improve the potential of entrepreneur for digital transformation.

The sample was limited to small Brazilian companies and startups, which may restrict the applicability of the results to other business or geographic contexts. Additionally, the items evaluated in the scale may not fully capture all nuances of entrepreneurial potential for digital transformation. Future research should consider including new items that cover a broader range of entrepreneurial characteristics.

The findings of this study have significant practical implications for the Brazilian entrepreneurial ecosystem, the entrepreneurs themselves, public policy makers and entrepreneurship support institutions. These results can guide digital transformation strategies, adjustments in public policies and investments, thereby promoting economic development and innovation in the country.

This study stands out for using IRT as a robust methodology to develop an interpretative scale to assess entrepreneurial potential in the digital transformation era. By focusing on Brazilian SBEs and startups, the study offers an original contribution on how these companies are handling the challenges of digitalization and identifying areas for improvement to further promote digital transformation among entrepreneurs.

This study aims to address the aspects of product and process innovation strategies and their determining factors to understand their characteristics in clothing manufacturing and contribution for a successful and competitive clothing industry.

This general review is based on literature data of previous studies on innovation that transcend and cover the aspects of innovation applicable in the clothing industry. Although the scope of discussion is theoretically broad, it focusses on the context of innovation strategies in clothing manufacturing and the determinant factors indicating the acquisition and implementation of product and process-related innovation activities, simultaneously exploring and linking their implications for adopting, managing and integrating enterprise activities to the values of desired innovation novel models.

Based on theoretical background and pragmatic generalizations, product and process innovation strategies in clothing manufacturing firms tend to incline more towards computer-integrated technologies and concepts meant to promote product development, process optimization and organizational integration. Industry, technological and R&D factors tend to significantly determine innovation capability of a clothing firm.

This review generates integrated conceptual frameworks for product and process innovation strategies applicable in clothing firms and their determinant factors as prelude to empirical validation.

This paper is based on the personal connections of the four authors to Shivaji Park, the largest public space in Mumbai. Three of the authors are childhood friends and were once long-term residents of that area. The focus of this article is Shivaji Park, anecdotally the largest park in the island city of Mumbai, with its historical connotations and its ongoing role as a relational and cultural artefact in the lives of these authors. The ongoing member status of all four authors in connection with the public space is explored despite all of them now ceasing to be locals.

This article uses a qualitative approach utilising informal conversations between the four authors recorded on zoom as the research method. Supported by belonging and emotional reflexivity as conceptual frames, it investigates how the spatial context fosters a binding relationality, which is ongoing despite the now disparate locations of the authors.

Based on a critical analysis of the recorded conversations between the authors the findings highlight that belonging/unbelonging centres around emotionally tinged representations of place.

The core of this paper rests in the emotional connections between the authors based on their collective memories with a public space and its surrounding areas as a focus. The use of informal conversations is crucial in teasing out nuanced aspects of data collected based on human relationalities. The paper emphasises the repercussions of ongoing changes stemming from urban progress. They incur emotional and human costs through a “culling” of connections and belongings.

This paper aims to prepare Poly(Styrene-Butyl acrylate-Methacrylic acid) @Poly Gallic acid-Fe³⁺ photonic crystal composite inks [P(St-BA-MAA)@PGA-Fe³⁺ PCCI, @ means the PGA-Fe³⁺ is loaded on the microspheres] and construct noniridescent structural colors on fabric substrates, with the goal of improving the visibility of structural colors.

P(St-BA-MAA)@PGA-Fe³⁺ PCCI were prepared by coating P(St-BA-MAA) microspheres with a metal-polyphenol network formed by gallic acid (GA, C₇H₆O₅) and Fe³⁺. The assembly effects of the inks were explored under different conditions, including pH, temperature, concentration and surface tension. The optimal self-assembly conditions of the inks were determined using the controlled variable method.

The results demonstrated the successful preparation of P(St-BA-MAA)@PGA-Fe³⁺ PCCI. The metal polyphenol network film composed of GA and Fe³⁺ was successfully coated on the surface of P(St-BA-MAA) seed microspheres. The assembly mechanism of the inks was investigated, indicating that at a diethylene glycol (DEG, C₄H₁₀O₃) concentration of 0.3 wt% and pH of 7, bright noniridescent structural colors could be formed on fabric surfaces after self-assembly by PCCI at 60 °C for 10 min. Furthermore, the mechanical fastness of the structural colors was enhanced due to the adherence of the soft shell composed of P(St-BA-MAA) and GA.

Utilizing a cost-effective approach and a diverse array of readily available raw materials, we have successfully prepared P(St-BA-MAA)@PGA-Fe³⁺ PCCI, which boasts superior performance and offers fabrics a range of unique coloring styles. This innovation paves the way for potential applications of structural colors in practical production, thereby broadening their realm of utility.

The Chinese data setting allows researchers to explore the influence of local versus national (central) government ownership on companies. This study aims to examine the influence of government ownership (local versus national) and auditor choice (choosing larger or smaller firms) on audit pricing in China.

This study executed three panel data regressions to examine the two hypotheses using 19,626 observations from 2009 to 2017 in the Chinese data setting. This study also uses the Sobel test to investigate the moderating effect of auditor choice.

This study first examines whether choosing a large audit firm positively influences audit pricing and whether listed state-owned enterprises (SOEs) charge less audit fees to audit firms after controlling for various variables. However, the interaction influence of government ownership and audit firm size on audit pricing is positive, suggesting that a large audit firm charges a client company more, even if the client is an SOE. More importantly, when we divide SOEs into national- and local-SOEs, the results of the influence of auditor choice, government ownership and the interaction of government ownership on audit pricing are consistent (plus, minus, plus), and audit firms charge local-SOEs less than national-SOEs. Furthermore, from the additional analysis, this study finds that the strong auditor type has a moderate effect on the case of local-SOEs on audit pricing and local-SOEs choose smaller auditors.

Research on the differences between local and national government ownership is limited. This study adds empirical results from this perspective. In particular, the findings suggest a further audit pricing research direction to consider the influence of client companies’ ownership types and auditor choice, especially in countries with planned economies.

This research examines how responsible deployment of ChatGPT in the UAE’s government sector, guided by New Public Management principles, can enhance customer journeys by integrating services across government bodies. Through semi-structured interviews with UAE government officers, the study investigates this approach’s benefits, challenges, and applications for achieving efficient and integrated public service delivery.

This research adopts a qualitative approach, purposive sampling strategy, and semi-structured interviews to explore the subjective viewpoints of 20 high-level UAE government authorities. The thematic analysis uncovers ChatGPT’s benefits, challenges, and applications, aligning with New Public Management principles.

Thematic analysis reveals four themes: Benefits and Applications of ChatGPT, Challenges, Strategies to Overcome Challenges, and Steps for Customer Journey Enhancement through ChatGPT.

The analysis is based on participant responses provided during the interviews, which may be subject to biases or incomplete information. Secondly, the study focuses solely on the provided applications and participant responses, limiting the generalizability of the conclusions to other contexts.

The implementation of ChatGPT in the government sector has practical implications for transforming its operations and enhancing communication, efficiency, decision-making, and service offerings: citizen engagement, streamlined processes, and informed governance.

This study uniquely examines ChatGPT’s role in government, offering insights into communication, efficiency, decision-making, and service offerings. Identifying hurdles enriches understanding of ChatGPT’s practical integration in government.

Predictive digital twin technology, which amalgamates digital twins (DT), the internet of Things (IoT) and artificial intelligence (AI) for data collection, simulation and predictive purposes, has demonstrated its effectiveness across a wide array of industries. Nonetheless, there is a conspicuous lack of comprehensive research in the built environment domain. This study endeavours to fill this void by exploring and analysing the capabilities of individual technologies to better understand and develop successful integration use cases.

This study uses a mixed literature review approach, which involves using bibliometric techniques as well as thematic and critical assessments of 137 relevant academic papers. Three separate lists were created using the Scopus database, covering AI and IoT, as well as DT, since AI and IoT are crucial in creating predictive DT. Clear criteria were applied to create the three lists, including limiting the results to only Q1 journals and English publications from 2019 to 2023, in order to include the most recent and highest quality publications. The collected data for the three technologies was analysed using the bibliometric package in R Studio.

Findings reveal asymmetric attention to various components of the predictive digital twin’s system. There is a relatively greater body of research on IoT and DT, representing 43 and 47%, respectively. In contrast, direct research on the use of AI for net-zero solutions constitutes only 10%. Similarly, the findings underscore the necessity of integrating these three technologies to develop predictive digital twin solutions for carbon emission prediction.

The results indicate that there is a clear need for more case studies investigating the use of large-scale IoT networks to collect carbon data from buildings and construction sites. Furthermore, the development of advanced and precise AI models is imperative for predicting the production of renewable energy sources and the demand for housing.

This paper makes a significant contribution to the field by providing a strong theoretical foundation. It also serves as a catalyst for future research within this domain. For practitioners and policymakers, this paper offers a reliable point of reference.

The purpose of this study is to comprehensively analyze the research article retractions in social sciences over the past decade (2014–2023).

The study used scientometric methods to evaluate the prevalence, patterns and factors contributing to social sciences article retractions. Bibliographic data of retracted articles were collected from the Retraction Watch Database under an agreement signed with the database. Further, citations of the retracted articles were collected from Scopus and Google Scholar. The analysis encompasses performance assessment and citation-based analysis to reveal the trend of retraction and scrutinize the impact of retracted articles.

Over the past decade, article retractions have shown dynamic trends, with notable fluctuations in recent years. Further, investigating the time taken for article retraction reveals the urgency of addressing issues identified soon after publication. Scientific misconduct and publication-related concerns emerge as primary factors leading to retractions. Countries such as Russia, the USA, China and publishers such as Elsevier and Taylor and Francis led in the retractions of social science articles. A significant portion of retracted works had garnered academic attention prior to retraction and even after retraction.

This study can contribute to a better understanding among scholars and stakeholders of the trends and reasons for retractions of research articles in the social sciences.