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There is little empirical evidence on how blockchain affordances may encourage consumers to make sustainable choices. Thus, this paper examines how blockchain affordances affect consumers’ sustainable consumption.

We focus on three blockchain affordances: transparency, traceability, and immutability in this paper. By integrating the affordance lens and theory of consumption values (TCV), we develop a research model wherein we posit that blockchain affordances influence several consumption values, which then affect consumers’ intention to purchase sustainable products. In the study, we designed a scenario and user interface for a novel blockchain-based app for sustainable consumption in the context of the fashion industry and surveyed 295 European consumers to examine the study’s research model. We then analyzed the collected data using the partial least squares technique.

The results show that blockchain affordances positively affect consumption values, including efficiency, social impression, trust, and sustainability information clarity. In turn, these values influence the consumers’ purchase intention of sustainable products. Additionally, our post hoc analysis shows that these consumption values fully mediate the effect of blockchain affordances on consumers’ purchase intention, where trust and sustainability information clarity is found to have a higher impact.

Empirical research studies focusing on understanding blockchain’s effect on sustainable consumption values have been limited in prior literature. This study, drawing on the affordance lens, proposes distinct blockchain affordances and empirically validates their impact on consumers’ sustainable purchase intention. By integrating TCV, it highlights the mediating mechanism that drives blockchain’s impact on consumers’ purchase intention. We empirically identify the values that mediate the effects of blockchain affordances on consumers’ purchase intention; further, we discuss implications for research and practice based on the study findings.

While prior studies predominantly focus on the overall impact of digital transformation on environmental, social and governance (ESG) performance, this study employs dynamic capability theory to examine two different dimensions of digital transformation, namely digital transformation quantity and digital transformation structure, and how they influence the ESG performance of enterprises. The mediating roles of social attention and green innovation are investigated to further explore the underlying mechanisms.

The authors apply fixed effects models and empirically test the hypotheses using samples of Chinese A-share listed companies from 2011 to 2020. In addition, difference-in-differences and instrumental variable methods are used in the robustness test.

When digital transformation is categorized into quantity and structure, the impact mechanisms are found to be distinct. Externally, digital transformation quantity attracts social attention, aiding enterprises in evolutionary adaptability and acquiring resources to support ESG practices. Internally, digital transformation structure fosters green innovation, enabling enterprises to overcome technical obstacles and harness technology’s potential to enhance their ESG performance.

This study contributes to the current knowledge by differentiating digital transformation into quantity and structure, which helps to further explore the mechanism of digital transformation on ESG and address the research gap. Meanwhile, the concept of adaptability in the dynamic capability theory is employed to construct the model, offering a deeper perspective and expanding the theory. This nuanced investigation of the mediating effects of social attention and green innovation elucidates how different dimensions of digital transformation contribute to the development and utilization of dynamic capabilities, thereby enhancing enterprises’ ESG performance.

This study analyzes the performance implications of adopting blockchain to support supply chain business processes. The technology holds as many promises as implementation challenges, so interest in its impact on operational performance has grown steadily over the last few years.

Drawing on transaction cost economics and the contingency theory, we built a set of hypotheses. These were tested through a long-term event study and an ordinary least squares regression involving 130 adopters listed in North America.

Compared with the control sample, adopters displayed significant abnormal performance in terms of labor productivity, operating cycle and profitability, whereas sales appeared unaffected. Firms in regulated settings and closer to the end customer showed more positive effects. Neither industry-level competition nor the early involvement of a project partner emerged as relevant contextual factors.

This research presents the first extensive analysis of operational performance based on objective measures. In contrast to previous studies and theoretical predictions, the results indicate that blockchain adoption is not associated with sales improvement. This can be explained considering that secure data storage and sharing do not guarantee the factual credibility of recorded data, which needs to be proved to customers in alternative ways. Conversely, improvements in other operational performance dimensions confirm that blockchain can support inter-organizational transactions more efficiently. The results are relevant in times when, following hype, there are signs of disengagement with the technology.

This study aims to explore the impact of artificial intelligence-powered personalised recommendations (AI-PPRs) on user engagement, browsing behaviour and purchase intentions on TikTok (Douyin in China), focusing on how these recommendations affect user satisfaction and purchase intention, while also addressing potential privacy concerns. In addition, the research investigates the influence of AI-recommended product presentation, timing and placement, as well as social factors such as key opinion leaders’ (KOLs) influence on consumer decision-making.

Using the expectancy-value theory and the stimulus-organism-response model, this research used a qualitative methodology through interviews with Douyin users to explore their experiences and perceptions of AI-PPRs.

The findings indicate that Douyin’s proactive “push” mechanism of AI-PPRs enhances user engagement by effortlessly integrating product discovery into the entertainment experience. Content-driven AI-PPRs align with user preferences, decrease search time and increase satisfaction and purchase intentions through engaging short videos and live streaming. However, privacy concerns emerge when personalisation is perceived as excessively intrusive, leading to negative emotions and avoidance behaviours. Recommendation timing and cultural context significantly influence receptiveness, with inappropriate timing (e.g. during holidays) causing negative reactions. Technical challenges, such as network issues during live streaming, negatively impact user experience and engagement. Content quality is crucial, and poor or irrelevant content leads to negative perceptions and disengagement. While KOLs face scepticism due to perceived commercialisation, endorsements from trusted figures and authentic influencers are better received. Innovative payment methods, like “Douyin Monthly Payment”, enhance financial flexibility and promote customer loyalty. This study highlights the need to balance personalisation with privacy, emphasising the importance of content quality and authenticity in influencer marketing. For businesses using AI-PPRs, maintaining this balance is essential for preserving trust and sustaining consumer engagement and loyalty.

This study contributes valuable insights to the field by unravelling the intricate dynamics between AI-PPRs, user preferences and social influences. The findings provide practical implications for companies aiming to optimise personalised recommendation algorithms and enhance user engagement, thereby facilitating business growth in the dynamic short video e-commerce market.

This study investigates antecedents determining the inclination to engage in future environmental entrepreneurial activities. Building on passion research and social cognitive theory, the authors explore the role of environmental passion for environmental entrepreneurial intention, drawing attention to the mediating role of environmental self-efficacy.

A regression-based path analysis for mediation to test the developed hypotheses on a sample of 139 young individuals is applied.

The results demonstrate a significant positive effect of environmental passion on environmental entrepreneurial intention. The mediation analysis shows a positive direct and indirect effect of passion on intention, concluding that self-efficacy is a partial mediator. The results further suggest that environmental entrepreneurial intention is related to gender. In contrast, covariates like age, entrepreneurial exposure and entrepreneurship education have no significant effect.

The results have implications for practitioners and policymakers who aim to further entrepreneurship for environmental sustainability. It underlines the need to take emotional antecedents seriously, suggests policy for creative and interdisciplinary education with respect to its challenges and emphasizes the roles of teachers in fostering passion.

The results provide a deeper contextualized understanding of passion, self-efficacy and intention in environmental entrepreneurship. These results offer an original perspective of entrepreneurship as a conduit to channel energy, concerns and passionate interests in the natural environment. The study presents theoretical implications for passion theory by extending sources of passion and clarifying the direction of self-efficacy in entrepreneurship.

This study aims to review and synthesize the burgeoning field of auditing research utilizing Chinese data. Over the past decades, there has been a remarkable rise in such research, driven by China’s abundant audit data, distinctive institutional features and enduring cultural influences. The purpose is to comprehensively review auditing studies featured in top-tier accounting journals, shedding light on the unique contributions made possible by Chinese data. By identifying key themes across domains, this paper aims to underscore the cultural and contextual disparities between China and Western countries, predominantly the USA, within the area of auditing.

This study presents a systematic review of China-themed auditing research, primarily published in seven leading global accounting journals. The researchers conducted a comprehensive search of the websites of these journals, identifying relevant articles using search terms such as “China auditing,” “Chinese Stock Market and Accounting Research (CSMAR),” “institutional environment,” and “internal control.” After the initial search, 54 relevant articles were selected and reviewed. The study covers all China-specific auditing research, categorizing key themes into six areas to explore how scholars use Chinese data to address important auditing questions.

The findings reveal a significant increase in auditing research utilizing Chinese data, prominently featured in top-tier academic journals. This study categorizes six central themes, highlighting the broad range of topics explored using Chinese audit data. More importantly, the research identifies substantial cultural and contextual differences between China and Western nations, particularly the USA, that influence the auditing profession and markets. Exploring these themes underscores the invaluable insights derived from Chinese data, shedding light on areas not previously addressed by studies relying solely on Western datasets.

The value of this study lies in its comprehensive examination of seminal auditing studies using Chinese data, making a distinctive contribution to the auditing literature. This paper highlights the inadequacies of Western datasets in addressing certain auditing questions and emphasizes the unique advantages offered by China’s extensive public audit data, institutional characteristics and cultural determinants. The identified gap in the literature underscores the unexplored opportunities for further research in the Chinese auditing context. This study, therefore, provides a roadmap for future scholars, encouraging the exploration of new avenues and fostering a deeper understanding of the cultural nuances influencing auditing practices in China.

Using an integrated theoretical model, this study aims to examine the moderating role of gamification in influencing intentions to use mobile payment applications in Bahrain.

The current examination happens to be the first approximation in the context of Bahrain wherein an extended TPB-based model integrating variables from TAM and UTAUT2 is used along with gamification and situational influence to examine the intentions to use m-payment applications.

The findings revealed that among the variates of the TPB, AT and PB significantly affect the intentions (IN) to use m-payment applications in Bahrain, but SN fails to affect intentions, similarly SI also fails to affect intentions thereby proving that the pandemic fails to drive the intention of the population under study toward using m-payment applications. However, when the application offers gamification (GM) features, SI significantly affects intentions through GM, thus experience along with situation drives intentions and this becomes the major theoretical contribution of the study.

This examination offers useful practical implications in the form of the findings revealing that GM affects intentions to use m-payment applications and that GM moderates the relationship between perceived risk (PR) and IN, as well as SI and IN, which can be used by the service providers to improve the user experience and achieve better acceptance of their application.

The novelty of the study lies in testing the integrated theoretical model in the context of a GCC nation, Bahrain.

Although many countries are focusing on the management of construction and demolition waste (CDW) resource utilization, the effect of risk aversion of the green innovation-led enterprise on the performance of the CDW resource utilization supply chain is unclear when considering different green innovation contexts (green innovation led by the building materials remanufacturer or by the construction waste recycler). This study aims to investigate how the level of risk aversion of the green innovation-led enterprise affects CDW resource utilization under different green innovation contexts based on contingency theory.

Using Stackelberg game theory, this study establishes a decision model consisting of a building materials remanufacturer, construction waste recycler and CDW production unit and investigates how the level of risk aversion of the green innovation-led enterprise under different green innovation contexts influences the performance level of the supply chain.

The conclusions are as follows. (1) For the green innovation-led enterprise, the risk-averse behaviour is always detrimental to his own profits. (2) For the follower, the profits of the construction waste recycler are negatively correlated with the level of risk aversion of the green innovation-led enterprise in the case of a small green innovation investment coefficient. If the green innovation investment coefficient is high, the opposite result is obtained. (3) When the green innovation investment coefficient is low, the total supply chain profits decrease as the level of risk aversion of the green innovation-led enterprise increases. When the green innovation investment coefficient is high, total supply chain profit shows an inverted U-shaped trend with respect to the degree of risk aversion of the green innovation-led enterprise.

(1) This study is the first to construct a green innovation context led by different enterprises in the CDW resource utilization supply chain, which provides a new perspective on green management and operation. (2) This study is the first to explore the operation mechanism of the CDW resource utilization supply chain based on contingency theory, which provides new evidence from the CDW resource utilization supply chain to prove contingency theory. At the same time, this study examines the interactive effects of the green innovation cost coefficient and the degree of risk aversion of green innovation-led enterprises on the performance of supply chain members, expanding the contingency theory research on contingencies affecting enterprise performance. (3) This study will guide members of the CDW resource utilization supply chain to rationally face risks and achieve optimal supply chain performance.

As social networks have developed to be a ubiquitous platform of public opinion spreading, it becomes more and more crucial for maintaining social security and stability by accurately predicting various trends of public opinion dissemination in social networks. Considering the fact that the dissemination of online public opinion is a dynamic process full of uncertainty and complexity, this study establishes a novel conformable fractional discrete grey model with linear time-varying parameters, namely the CFTDGM(1,1) model, for more accurate prediction of online public opinion trends.

First, the conformable fractional accumulation and difference operators are employed to build the CFTDGM(1,1) model for enhancing the traditional integer-order discrete grey model with linear time-varying parameters. Then, to improve forecasting accuracy, a base value correction term is introduced to optimize the iterative base value of the CFTDGM(1,1) model. Next, the differential evolution algorithm is selected to determine the optimal order of the proposed model through a comparison with the whale optimization algorithm and the particle swarm optimization algorithm. The least squares method is utilized to estimate the parameter values of the CFTDGM(1,1) model. In addition, the effectiveness of the CFTDGM(1,1) model is tested through a public opinion event about “IG team winning the championship”. Finally, we conduct empirical analysis on two hot online public opinion events regarding “Chengdu toddler mauled by Rottweiler” and “Mayday band suspected of lip-syncing,” to further assess the prediction ability and applicability of the CFTDGM(1,1) model by comparison with seven other existing grey models.

The test case and empirical analysis on two recent hot events reveal that the CFTDGM(1,1) model outperforms most of the existing grey models in terms of prediction performance. Therefore, the CFTDGM(1,1) model is chosen to forecast the development trends of these two hot events. The prediction results indicate that public attention to both events will decline slowly over the next three days.

A conformable fractional discrete grey model is proposed with the help of conformable fractional operators and a base value correction term to improve the traditional discrete grey model. The test case and empirical analysis on two recent hot events indicate that this novel model has higher accuracy and feasibility in online public opinion trend prediction.

This study examines the interaction between sales control systems and firm level strategic orientations and their joint effects on company performance in B2B context. Independent and joint effects of market orientation (MO), innovation orientation (IO) and sales control systems (SCS) on firm performance were analyzed.

A quantitative research methodology is adopted to compile firm-level primary data from manufacturing companies located in an organized industrial zone. Research data were collected by face-to-face surveys from 302 sales professionals. The research model and hypotheses were tested by using partial least squares (PLS) structural equation modeling (SEM) with Smart PLS 3.0.

In addition to confirming the positive effects of MO and IO on performance, data analyses revealed that SCS exert an indirect effect on company performance which is fully mediated by MO.

The research was limited to a developing country context and research data was collected from a convenient sample of B2B companies by a cross-sectional study. Cross-cultural and longitudinal studies may provide additional insights. Firm level strategic orientations and sales control systems must be examined together in an integrated way to explore their effects on company performance. The individual effects of these structures on business performance may manifest differently when they come together.

Results indicate that the sales control system setup is critical for the implementation of a market-oriented strategy. This study highlights the importance of setting a compatible sales control system to achieve organizational goals in accordance with the strategic orientations which affect the success of particular organizational strategies.

Although the current literature identifies the independent and joint effects of market orientation and innovation orientation on company performance, empirical studies probing the interaction of sales control systems with these constructs is very scarce. Understanding how sales control systems relate to strategic orientations will help design a more effective sales organization and improve company performance. This study contributes to the literature by promoting additional insights by linking sales control systems with market orientation, innovation orientation and company performance.