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This study aims to deeply understand customer experiences toward Internet of Things (IoT) applications in retail by developing machine learning models for aspect-based sentiment analysis (SA). It includes creating a related terms dictionary and proposing implications for retail businesses in Vietnam based on these analyses. The ultimate goal is to gain insights into customer opinions and assist administrators in formulating effective digital transformation and business strategies within the Vietnamese market.

Initially, this research uses qualitative methods to identify different aspects of customer experience at stores equipped with IoT applications. Then, quantitative methods were applied through classification machine learning models which were trained on the annotated data set to classify comments into aspects and sentiments. Finally, the classification results were analyzed and visualized to draw implications about customer opinions of these stores.

This study collected 77,042 customers’ comment from potential and actual customers who have ever shopped at retail stores with IoT applications deployed worldwide, identified ten new aspects of customer experience in this field and built a dictionary of related terms. Furthermore, this study contributed two efficient ensemble models with an accuracy of 81% and 89% for analyzing aspects and customer sentiments, respectively. This study also proposes implications for managers regarding the use of IoT technology in retail stores to improve shopping experiences for customers.

This study’s findings help managers develop appropriate digital transformation and business strategies for integrating IoT technology into retail stores, especially for retail businesses in the Vietnamese market based on the analysis results and proposed model.

This paper examines to what extent blockchain creates legitimacy and trust in different modes of public governance. It posits that while blockchain aims for political legitimacy through decentralising, immutable and consensus-based mechanisms, the execution of these mechanisms is limited in legitimating governance, which has knock-on effects on trust. It provides an original contribution by recontextualising and reframing blockchain as a governance mechanism that should, and must, perform a legitimating function in order to engender trust.

The research adopts a comprehensive framework for understanding the legitimacy of blockchain governance, positioning it in terms of co-governance, self-governance and hierarchical governance modes. It systematically analyses blockchain whitepapers, legislation, government documents and other sources in three paradigmatic case studies where blockchain governance failed. These cases are then used to assess blockchain according to three key characteristics of decentralisation, immutability and consensus.

The research finds that blockchain’s use in governance settings still relies on legitimacy conferred from other sources – namely state – in order to generate trust. Significant limitations in its de facto political decentralisation, immutability and consensus protocols can create failures in co-governance, self-governance and hierarchical-governance applications, thus limiting the legitimation function of blockchain in facilitating political trust.

These findings are significant in highlighting blockchain’s limitations as a decentralised, immutable and consensus-driven legitimating tool, which has knock-on effects on trust in technology and governance more broadly. It also has broader implications in more clearly highlighting the interconnectedness of political trust and legitimacy in governance processes.

Polyethylene terephthalate (PET) as a fiber molding polymer is widely used in aerospace, electrical and electronic, clothing and other fields. The purpose of this study is to improve the thermal insulation performance of polyethylene terephthalate (PET), the SiO₂ aerogel/PET composites slices and fibers were prepared, and the effects of the SiO₂ aerogel on the morphology, structure, crystallization property and thermal conductivity of the SiO₂ aerogel/PET composites slices and their fibers were systematically investigated.

The mass ratio of purified terephthalic acid and ethylene glycol was selected as 1:1.5, which was premixed with Sb₂O₃ and the corresponding mass of SiO₂ aerogel, and SiO₂ aerogel/PET composites were prepared by direct esterification and in-situ polymerization. The SiO₂ aerogel/PET composite fibers were prepared by melt-spinning method.

The results showed that the SiO₂ aerogel was uniformly dispersed in the PET matrix. The thermal insulation coefficient of PET was significantly reduced by the addition of SiO₂ aerogel, and the thermal conductivity of the 1.0 Wt.% SiO₂ aerogel/PET composites was reduced by 75.74 mW/(m · K) compared to the pure PET. The thermal conductivity of the 0.8 Wt.% SiO₂ aerogel/PET composite fiber was reduced by 46.06% compared to the pure PET fiber. The crystallinity and flame-retardant coefficient of the SiO₂ aerogel/PET composite fibers showed an increasing trend with the addition of SiO₂ aerogel.

The SiO₂ aerogel/PET composite slices and their fibers have good thermal insulation properties and exhibit good potential for application in the field of thermal insulation, such as warm clothes. In today’s society where the energy crisis is becoming increasingly serious, improving the thermal insulation performance of PET to reduce energy loss will be of great significance to alleviate the energy crisis.

In this study, SiO₂ aerogel/PET composite slices and their fibers were prepared by an in situ polymerization process, which solved the problem of difficult dispersion of nanoparticles in the matrix and the thermal conductivity of PET significantly reduced.

Amid the increasing water risks faced by firms, external investors are becoming more interested in corporate water disclosure and research on its drivers has become prominent. This paper aims to investigate the impact of water resource tax (WRT) on water disclosure and other related drivers.

This study uses the WRT policy as a quasi-natural experiment and applies the difference-in-differences method.

The results indicate that WRT policy significantly stimulates water disclosure. Improving green innovation and strengthening internal control are potential channels through which WRT works. Moreover, WRT’s effect is more pronounced in firms that face high institutional pressures and have better internal resource support.

The findings suggest that water-sensitive firms should disclose water information to acquire resources from external stakeholders to support their green transition. It also provides implications for governments to incorporate other external forces in shaping the direction and intensity of WRT and consider the resource constraints of small and private firms in green transformation.

This study is of assistance in promoting water environmental protection in areas experiencing water stress and provides an opportunity for external stakeholders (external investors, nongovernmental organizations, governments, consumers, suppliers, communities and media) to advocate the water disclosure of firms with high water risks.

The attempt is novel in the context of considering the water regulation risks and the demands of external stakeholders. It provides new insights into the factors influencing water disclosure from the perspective of political stakeholders.

Toner is a crucial dry colorant composite used in printing based on the electrophotographic process. The quality of printed images is greatly influenced by the toner production method and material formulation. Chemically in situ polymerization methods are currently preferred. This paper aims to optimize the characteristics of a composite produced through emulsion polymerization using common raw materials for electrophotographic toner production.

Emulsion polymerization provides the possibility to optimize the physical and color properties of the final products. Response surface methodology (RSM) was used to optimize variables affecting particle size (PS), PS distribution (PSD), glass transition temperature (T_g°C), color properties (ΔE) and monomer conversion. Box–Behnken experimental design with three levels of styrene and butyl acrylate monomer ratios, carbon black pigment and sodium dodecyl sulfate surfactant was used for RSM optimization. Additionally, thermogravimetric analysis and surface morphology of composite particles were examined.

The results indicated that colorants with small PS, narrow PSDs, spherical shape morphology, acceptable thermal and color properties and a high percentage of conversion could be easily prepared by optimization of material parameters in this method. The anticipated outcome of the present inquiry holds promise as a guiding beacon toward the realization of electrographic toner of superior quality and exceptional efficacy, a vital factor for streamlined mass production.

To the best of the authors’ knowledge, for the first time, material parameters were evaluated to determine their impact on the characteristics of emulsion polymerized toner composites.

With the development of Web information systems, steel e-commerce platforms have accumulated a large number of quality objection texts. These texts reflect consumer dissatisfaction with the dimensions, appearance and performance of steel products, providing valuable insights for product improvement and consumer decision-making. Currently, mainstream solutions rely on pre-trained models, but their performance on domain-specific data sets and few-shot data sets is not satisfactory. This paper aims to address these challenges by proposing more effective methods for improving model performance on these specialized data sets.

This paper presents a method on the basis of in-domain pre-training, bidirectional encoder representation from Transformers (BERT) and prompt learning. Specifically, a domain-specific unsupervised data set is introduced into the BERT model for in-domain pre-training, enabling the model to better understand specific language patterns in the steel e-commerce industry, enhancing the model’s generalization capability; the incorporation of prompt learning into the BERT model enhances attention to sentence context, improving classification performance on few-shot data sets.

Through experimental evaluation, this method demonstrates superior performance on the quality objection data set, achieving a Macro-F1 score of 93.32%. Additionally, ablation experiments further validate the significant advantages of in-domain pre-training and prompt learning in enhancing model performance.

This study clearly demonstrates the value of the new method in improving the classification of quality objection texts for steel products. The findings of this study offer practical insights for product improvement in the steel industry and provide new directions for future research on few-shot learning and domain-specific models, with potential applications in other fields.

This study is of great significance in revealing the interactive and coordinated relationship between tourism development and the ecological environment, improving the level of environmental governance in the process of tourism economic development and realising the dual-carbon goal and sustainable development of the tourism industry.

This paper performs slack-based measure (SBM)-data envelopment analysis (DEA) analysis, benchmark regression and threshold effect measurement on a sample of 277 cities in China from 2011 to 2019, to estimate the impact of the digital economy on tourism eco-efficiency and to identify the moderating role of environmental regulation.

China’s tourism eco-efficiency shows a spatio-temporal characteristic of steady growth amid fluctuations. The digital economy has a positive facilitating effect on tourism eco-efficiency, which is non-linear with a single threshold effect (0.631), and when the level of the digital economy exceeds the threshold value, its facilitating effect increases from 0.696 to 0.927. Environmental regulation does not play the role of “the icing on the cake” during the digital economy’s impact on tourism eco-efficiency.

This study for the first time includes the digital economy, eco-efficiency and environmental regulation in the research perspective, and analysed the mechanism of action between the three, expanding the depth of research on the digital economy and environmental regulation in the field of tourism. Meanwhile, based on the development needs of policy specialisation and industrial refinement, this study has strong practical significance when conducted at the city level.

This study aims to investigate the circumstances where the positive influences of leader’s self-confidence are weakened in situations of conflict management (CM) arising due to innovation implementation. Specifically, this study tests the moderating influence of financial slack, internal opposition posturing and performance feedback on the relationship between self-confidence and conflict management styles (CMS). The findings are not complete.

This experimental study was conducted in two stages: In Stage 1, the authors studied moderating effects of financial slack (sound/unsound) and internal opposition posture (encouraging/ discouraging) on the relationship between leader’s self-confidence and CMS, namely, dominating, integrating and avoiding. In Stage 2, the authors studied the moderating effect of performance feedback (success/failure) on the relationship between leader’s self-confidence and three CMS. Data were collected from 268 senior-level Indian managers in Stage 1, out of which 235 managers also responded in Stage 2. These participants assumed the positions of chief executive officers (CEOs) within major Indian manufacturer specializing in electrical components, enabling us to empirically test the proposed model. Furthermore, a qualitative analysis of 10 semistructured interviews with Indian CEOs were conducted to enrich the discussion of the results.

Leader’s self-confidence determined the three CMS with highly self-confident leaders displaying irrational behavior in persisting with innovation through dominating style. Internal opposition posture and performance feedback exerted main effects on dominating style.

This study supports behavioral decision theory of firm and escalation of commitment theory.

This study underscores the need for personality and self-awareness training amongst senior managers to mitigate irrational behavior due to excessive self-confidence and enhanced effective CM.

This study identifies a crucial boundary condition where high self-confidence in innovation implementation may lead to irrational behavior and ineffective CM.

This research aims to investigate the relationship between knowledge capabilities, engagement capabilities, operational capabilities and sustainable supply chain flexibility in the steel production industry. In addition, it seeks to understand how these elements contribute toward achieving a net-zero supply chain, under the moderation of industry dynamism.

In total, 371 people have responded to the self-administered survey that the authors developed. The nonresponse bias analysis was carried out before diving into fundamental assumptions, such as homoscedasticity and normality. The data's reliability and construct validity were assessed by using confirmatory factor analysis. The hypothesized conclusions were supported by subsequent regression outputs, strengthening the body of existing academic research.

The research's empirical results highlight the positive relationship among knowledge capabilities, operational capabilities, sustainable supply chain flexibility and net-zero supply chain, particularly under the influence of industry dynamism. Information obtained from the steel production industry corroborates these findings. Moderation role of industry dynamism in the relationship between operational capabilities, engagement capability and sustainable supply chain flexibility was found significant.

This conceptual framework clarifies how knowledge capability, dynamic capabilities and the flexibility of a sustainable supply chain interact. It highlights how these factors collectively work together to attain a sustainable supply chain with net-zero environmental impact.

Can digital financial inclusion (DFI) as an emerging and innovative financial service encourage economic development?

Based on a Bayesian macroeconomic investigation framework, this research study presents the level of internet growth as a threshold variable and examines the influence of DFI on economic development based on state panel data from 2008 to 2021 in India.

The outcome of DFI on economic development through various mediation models. The results illustrate that DFI growth substantially contributes to economic development.

Encouraging small and medium-sized enterprise entrepreneurship and motivating populations’ utilization are two significant networks through which DFI progress affects economic growth.